Early cancer detection using cell-free proteomics

Abstract

Provided herein are methods and compositions for detecting cancer in a subject. The methods can comprise contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; isolating the solid support comprising bound extracellular vesicles; lysing the bound extracellular vesicles to form a protein sample; contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; comparing the mass spectrometry data to reference data; and identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data.

Description

772734-ASB-016PCTITLE: Early Cancer Detection Using Cell-Free ProteomicsPRIORITY

[0001] This application claims the benefit of U.S. Ser. No. 63 / 730,417, filed on December 10, 2024, U.S. Ser. No. 63 / 884,758, filed on September 19, 2025, U.S. Ser. No. 63 / 884,766, filed on September 19, 2025, U.S. Ser. No. 63 / 884,769, filed on September 19, 2025, U.S. Ser. No. 63 / 884,771 , filed on September 19, 2025, and U.S. Ser. No. 63 / 910,351 , filed on November s, 2025, all of which are incorporated herein by reference in their entireties.BACKGROUND

[0002] Treating cancer is still a significant challenge. Current liquid biopsy techniques largely revolve around nucleotide-based approaches of cell free DNA and RNA or single protein biomarkers. However, these assays often lack sensitivity and / or specificity at early stages of disease. To address these challenges deep proteome assessment of biological samples, which has only recently become a reality with advancements in technology, has allowed the discovery of more proteins with less material. To find these proteins, especially ones with low abundance, strategies to remove the more abundant proteins in the plasma and analyze the remaining 1 % of the plasma proteome that contains the diversity needed to differentiate biological samples for disease characterization needed to be developed. Empowering patients with early detections and opportunities for targeted curative interventions.SUMMARY

[0003] Provided herein are methods of detecting cancer in a subject The methods can comprise, in a first aspect: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and772734-ASB-016PC g) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data.

[0004] A second aspect provides methods of treating cancer. The methods can comprise: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and h) where the subject is identified as having cancer, administering one or more anti-cancer agents or treatments to the subject.

[0005] In any of the first and second aspects, the methods can further comprise additionally performing three dimensional (3D) digital holography on a blood sample from the subject to identify and / or isolate circulating tumor cells. Cancer can be detected prior to or at stage 0, I, II, III or IV. Cancer can be detected prior to or at stage III. The blood sample can be whole blood, serum, or plasma. The methods ca further comprise centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support. The methods can comprise, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, treating the blood sample by: a) applying centrifugal force of 200-1 ,600 x g b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g and obtaining the supernatant as the blood sample.

[0006] In any of the first and second aspects, the solid support comprising bound extracellular vesicles can be isolated by centrifugation, elution, chromatography, or magnetization. A solid support can be an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a772734-ASB-016PC heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof. The solid support can be a magnetic bead. The solid support can be functionalized with one or more specific binding proteins that bind extracellular vesicles. The one or more specific binding proteins that bind extracellular vesicles can specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1A1 , CD44, SLC3A2, LAMP1 , EGFR, HER2, c- MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7- H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, CA19-9, or combinations thereof. The solid support functionalized to bind the proteins in the protein sample can be carboxyl modified, amine modified, hydroxyl modified, sulfhydryl modified, epoxide modified, biotin modified, streptavidin modified, avidin modified, modified with one or more antibodies, modified with one or more lectins, and / or carbonyl modified, or combinations thereof.

[0007] In any of the first and second aspects, the EV derived protein sample can be digested prior to performing mass spectrometry. The digestion can be one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg- C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof. The digest can be a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

[0008] In any of the first and second aspects, the EVs can be a sub-set of EVs. The sub-set of EVs comprises EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutI O pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

[0009] In any of the first and second aspects, the blood sample can be collected from the subject into a storage container comprising imidazolidinyl urea, diazolidinyl urea formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5- hydroxymethoxymethyl-1 -1 aza-3,7-dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1 -1 aza- 3,7-dioxabicyclo[3.3.0]octane, 5-hydroxy[methyleneoxy]methyl-1-1 aza-3, 7- dioxabicyclo[3.3.0]octane, quaternary adamantine, 1 -(3,4-bis-hydroxymethyl-2,5-dioxo- imidazolidin-4-yl)-1 ,3-bis-hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-772734-ASB-016PC 4-yl)-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis. The blood sample can be treated with one or more Schiff base ligands prior to contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample. The blood sample can be positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

[0010] In any of the first and second aspects, the biomarkers can be treatment- related cancer biomarkers. The reference data can comprise amounts of one or more biomarkers from a healthy subject. The one or more biomarkers of step g) can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or the one or more biomarkers from a healthy subject can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.

[0011] A third aspect provides a method of detecting breast cancer in a subject . The method can comprise: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subject as having breast cancer if the amount of one or more biomarkers differs from the reference data.

[0012] A fourth aspect provides a method of decreasing false negative breast cancer diagnoses in a group of subjects comprising:772734-ASB-016PC a) contacting a blood sample from each of the subjects in the group of subjects with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subjects as having breast cancer where the amount of one or more biomarkers differs from the reference data, wherein the number of false negative diagnosis in the group of subjects is decreased as compared to a group of subjects receiving a diagnosis via mammography.

[0013] A fifth aspect provides a method of treating breast cancer. The method can comprise: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and h) where the subject is identified as having breast cancer, administering one or more anti-breast cancer agents or breast cancer treatments to the subject.

[0014] In any of the third, fourth, and fifth aspects, each of the subjects in the group can have had negative mammogram results within about 1 week, 2 weeks, or 1 , 2, 3, 4, 5, 6 months of performing the method. Each of the subjects in the group can have dense breast tissue.772734-ASB-016PC

[0015] In any of the third, fourth, and fifth aspects, the method can further comprise additionally performing three dimensional (3D) digital holography on a blood sample from the group of subjects to identify and / or isolate circulating tumor cells.

[0016] In any of the third, fourth, and fifth aspects, the breast cancer can be detected prior to or at stage 0, I, II, III or IV. The breast cancer can be detected prior to or at stage III. The blood sample can be whole blood, serum, or plasma.

[0017] In any of the third, fourth, and fifth aspects, the method can further comprise centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support. In an aspect, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, the blood sample can be treated by a) applying centrifugal force of 200-1 ,600 x g b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g and obtaining the supernatant as the blood sample.

[0018] In any of the third, fourth, and fifth aspects, isolating the solid support comprising bound extracellular vesicles can be performed by centrifugation, elution, chromatography, or magnetization. The solid support can be an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof. The solid support can be a magnetic bead. The solid support of step a) can be functionalized with one or more specific binding proteins that bind extracellular vesicles. The one or more specific binding proteins that bind extracellular vesicles can specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1A1 , CD44, SLC3A2, LAMP1 , EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, CA19-9, or combinations thereof. The solid support functionalized to bind the proteins in the protein sample can be carboxyl modified, amine modified, hydroxyl modified, sulfhydryl modified, epoxide modified, biotin modified, streptavidin modified, avidin modified, modified with one or more antibodies, modified with one or more lectins, and / or carbonyl modified, or combinations thereof. The EV derived protein sample can be digested prior to performing mass spectrometry. The digestion can be one or more of772734-ASB-016PC a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys- N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof. The digest can be a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

[0019] In any of the third, fourth, and fifth aspects, the EVs can be a sub-set of EVs. The sub-set of EVs can comprise EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutIO pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

[0020] In any of the third, fourth, and fifth aspects, the blood sample can be collected from the subject into a storage container comprising imidazolidinyl urea, diazolidinyl urea formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1-1 aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxy[methyleneoxy]methyl-1-1 aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis- hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis. The blood sample can be treated with one or more Schiff base ligands prior to step a). The blood sample can be positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

[0021] In any of the third, fourth, and fifth aspects, the biomarkers can be treatment- related cancer biomarkers. The reference data can comprise amounts of one or more biomarkers from a healthy subject. The one or more biomarkers of step g) can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or the one or more biomarkers from a healthy subject can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.772734-ASB-016PC

[0022] In a sixth aspect, a method of monitoring cancer treatment in a subject is provided. The method can comprise: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) repeating steps a)-f) at a different time point; h) comparing the mass spectrometry data obtained at points f) and g) to determine if there are any changes, whereby cancer treatment is monitored.

[0023] The reference data can comprise the amount of one or more biomarkers from healthy patients. Cancer can be detected prior to or at stage 0, I, II, III or IV. Cancer can be detected prior to or at stage III. The blood sample can be whole blood, serum, or plasma.

[0024] The method can further comprise centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support. In an aspect, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, the blood sample can be treated by a) applying centrifugal force of 200-1 ,600 x g b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g and obtaining the supernatant as the blood sample. Isolating the solid support comprising bound extracellular vesicles can be performed by centrifugation, elution, chromatography, or magnetization. The solid support can be an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof. The solid support can be a magnetic bead. The solid support of step a) can be functionalized with one or more specific binding proteins that bind extracellular vesicles. The one or more specific binding proteins that bind extracellular vesicles can specifically772734-ASB-016PC bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin- 1 , flotillin-2, CD31 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1A1 , CD44, SLC3A2, LAMP1 , EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, CA19-9, or combinations thereof. The solid support functionalized to bind the proteins in the protein sample can be functionalized with free carboxyl groups, hydroxyl groups, carbonyl groups, amine groups, epoxide groups, sulfhydryl groups, biotin, streptavidin, avidin, antibodies, lectins, or combinations thereof.

[0025] In an aspect, the EV derived protein sample can be digested prior to performing mass spectrometry. The digestion can be one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof. The digest can be a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

[0026] In an aspect, the EVs are a sub-set of EVs. The sub-set of EVs can comprise EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutIO pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

[0027] In an aspect, the blood sample from the subject can be collected from the subject into a storage container comprising formaldehyde, formalin, glyceraldehyde, imidazolidinyl urea, or diazolidinyl urea, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5- hydroxymethoxymethyl-1 -1 aza-3,7-dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1 -1 aza- 3,7-dioxabicyclo[3.3.0]octane, 5-hydroxy[methyleneoxy]methyl-1-1 aza-3, 7- dioxabicyclo[3.3.0]octane, quaternary adamantine, 1 -(3,4-bis-hydroxymethyl-2,5-dioxo- imidazolidin-4-yl)-1 ,3-bis-hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin- 4-yl)-urea, or (4-hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis. The blood sample can be treated with one or more Schiff base ligands prior to step a). The blood sample can be positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:772734-ASB-016PC(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

[0028] In an aspect, the method can further comprise additionally performing three dimensional (3D) digital holography on a blood sample from the subject to identify and / or isolate circulating tumor cells.

[0029] In an aspect, the one or more biomarkers can be treatment-related cancer biomarkers. The reference data can comprise amounts of one or more biomarkers from a healthy subject. The one or more biomarkers can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or the one or more biomarkers from a healthy subject can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.

[0030] In a seventh aspect, a method of detecting cancer in a subject is provided. The method can comprise: a) collecting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and h) performing imaging on the subject to determine the location of a primary tumor or lesion, determine metastatic spread, or determine tumor recurrence.

[0031] In an eighth aspect, a method for reducing an amount of imaging necessary in a group of subjects to be screened for cancer is provided. The method can comprise: a) contacting a blood sample from each of the subjects with a solid support functionalized to bind extracellular vesicles in the blood sample;772734-ASB-016PC b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to healthy reference data; and g) identifying each of the subjects of the group as not having cancer if the amounts of one or more biomarkers do not differ from healthy reference data and identifying each of the subjects of the group as having cancer if the amounts of one or more biomarkers differs from the reference data; and h) performing imaging on only the subjects identified as having cancer to determine the location of a primary tumor or lesion, determine metastatic spread, or determine tumor recurrence, wherein the amount of imaging is reduced in the group of subjects.

[0032] In any of the seventh and eighth aspects, the method can further comprise additionally performing three dimensional (3D) digital holography on a blood sample from the group of subjects to identify and / or isolate circulating tumor cells.

[0033] In any of the seventh and eighth aspects, the imaging can comprise in vitro imaging; in vivo whole-body imaging; in vivo organ specific imaging; in vivo tissue specific imaging; or combinations thereof. Cancer can be detected prior to or at stage 0, I, II, III or IV. Cancer can be detected prior to or at stage III. The blood sample can be whole blood, serum, or plasma.

[0034] In any of the seventh and eighth aspects, the method can further comprise centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support. In an aspect, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, the blood sample can be treated by a) applying centrifugal force of 200-1 ,600 x g; b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g and obtaining the supernatant as the blood sample.

[0035] In any of the seventh and eighth aspects, isolating the solid support comprising bound extracellular vesicles can be performed by centrifugation, elution, chromatography, or magnetization. The solid support can be an agarose bead,772734-ASB-016PC a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof. The solid support can be a magnetic bead. The solid support of step a) can be functionalized with one or more specific binding proteins that bind extracellular vesicles. The one or more specific binding proteins that bind extracellular vesicles can specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1A1 , CD44, SLC3A2, LAMP1 , EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, CA19-9, or combinations thereof. The solid support functionalized to bind the proteins in the protein sample can be functionalized with free carboxyl groups, hydroxyl groups, carbonyl groups, amine groups, epoxide groups, sulfhydryl groups, biotin, streptavidin, avidin, antibodies, lectins, or combinations thereof.

[0036] In any of the seventh and eighth aspects, t he EV derived protein sample can be digested prior to performing mass spectrometry. The digestion can be one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys- N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof. The digest can be a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof. The EVs can be a sub-set of EVs. The sub-set of EVs can comprise EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutIO pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

[0037] In any of the seventh and eighth aspects, the blood sample can be collected from the subject into a storage container comprising formaldehyde, formalin, glyceraldehyde, imidazolidinyl urea, diazolidinyl urea, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1-1 aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxy[methyleneoxy]methyl-1-1 aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis-772734-ASB-016PC hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis. The blood sample can be treated with one or more Schiff base ligands prior to step a). The blood sample can be positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

[0038] In any of the seventh and eighth aspects, the biomarkers can be treatment- related cancer biomarkers. The reference data can comprise amounts of one or more biomarkers from a healthy subject. The one or more biomarkers of step g) can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or the one or more biomarkers from a healthy subject can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.

[0039] In a ninth aspect, a method of detecting cancer in a subject is provided. The method can comprise: a) having the subject self-collect a blood sample, and optionally, having the subject add a protective agent to the blood sample; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data.

[0040] In a tenth aspect, a method of treating cancer in a subject is provided. The method can comprise:772734-ASB-016PC a) having the subject self-collect a blood sample; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and i) where the subject is identified as having cancer, administering one or more anticancer agents or treatments to the subject.

[0041] In an eleventh aspect, a method of monitoring cancer treatment in a subject is provided. The method can comprise: a) having the subject self-collect a blood sample; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) repeating steps a)-g) at a different time point; i) comparing the mass spectrometry data obtained at points f) and g) to determine if there are any changes, whereby the cancer treatment is monitored.

[0042] In a twelfth aspect, a method of detecting cancer in a subject is provided. The method can comprise having the subject self-collect a blood sample and then:772734-ASB-016PC a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying each of the subjects in the group as having cancer if the amount of one or more biomarkers differs from the reference data; and h) performing imaging on the subjects in the group having cancer to determine the location of a primary tumor or lesion.

[0043] A thirteenth aspect provides a method for reducing an amount of imaging necessary in a group of subjects to be screened for cancer. The method can comprise: a) having each subject in the group of subjects self-collect a blood sample; b) contacting the blood sample from each of the subjects with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to healthy reference data; and h) identifying each of the subjects in the group as not having cancer if the amount of biomarkers do not differ from healthy reference data and identifying each of the subjects in the group as having cancer if the amount of one or more biomarkers differs from the healthy reference data; and i) performing imaging on only the subjects identified as having cancer to determine the location of a primary tumor or lesion, wherein the amount of imaging is reduced in the group of subjects.772734-ASB-016PC

[0044] In any of the ninth, tenth, eleventh, twelfth, or thirteenth aspects, the method can further comprise additionally performing three dimensional (3D) digital holography on a blood sample from the subject to identify and / or isolate circulating tumor cells.

[0045] In any of the twelfth or thirteenth aspects, the imaging can comprises in vitro imaging; in vivo whole-body imaging; in vivo organ specific imaging; in vivo tissue specific imaging; or combinations thereof.

[0046] In any of the ninth, tenth, eleventh, twelfth, or thirteenth aspects, cancer can be detected prior to or at stage 0, I, II, III or IV. Cancer can be detected prior to or at stage III. The blood sample can be whole blood, serum, or plasma.

[0047] In any of the ninth, tenth, eleventh, twelfth, or thirteenth aspects, the method can further comprise centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support. In an aspect, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, the blood sample can be treated by a) applying centrifugal force of 200-1 ,600 x g b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g and obtaining the supernatant as the blood sample.

[0048] In any of the ninth, tenth, eleventh, twelfth, or thirteenth aspects, isolating the solid support comprising bound extracellular vesicles can be performed by centrifugation, elution, chromatography, or magnetization. The solid support can be an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a heparin-conjugated affinity chromatography column, a size exclusion chromatography column, an immobilized metal affinity column, a chromatography column, or any combination thereof. The solid support can be a magnetic bead. The solid support of step a) can be functionalized with one or more specific binding proteins that bind extracellular vesicles. Specific binding proteins can specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1A1 , CD44, SLC3A2, LAMP1 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, EGFR, HER2, c- MET, VEGFR, EpCAM, MUC1 , integrins (e.g. av[33 or a6p4), PD-L1 , PD-1 , B7-H3, B7- H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, or CA19-9. The solid support can be functionalized to bind the proteins in the protein sample can be carboxyl modified, amine modified, hydroxyl modified, sulfhydryl modified, epoxide modified, biotin772734-ASB-016PC modified, streptavidin modified, avidin modified, modified with one or more antibodies, modified with one or more lectins, and / or carbonyl modified, or combinations thereof.

[0049] In any of the ninth, tenth, eleventh, twelfth, or thirteenth aspects, the EV derived protein sample can be digested prior to performing mass spectrometry. The digestion can be one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof. The digest can be a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof. The EVs can be a sub-set of EVs. The sub-set of EVs can comprise EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutIO pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

[0050] In any of the ninth, tenth, eleventh, twelfth, or thirteenth aspects, the blood sample can be collected from the subject into a storage container comprising imidazolidinyl urea, diazolidinyl urea, formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1-1aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxy[methyleneoxy]methyl-1-1aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis- hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis. The blood sample can be treated with one or more Schiff base ligands prior to step b). The blood sample can be positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

[0051] In any of the ninth, tenth, eleventh, twelfth, or thirteenth aspects, the blood sample can be 50 pL to 1 ,000 pL. After step a) the sample can be shipped to a testing center greater than 5 miles away from the subject.772734-ASB-016PC

[0052] In any of the ninth, tenth, eleventh, twelfth, or thirteenth aspects, the biomarkers can be treatment-related cancer biomarkers. The reference data can comprise amounts of one or more biomarkers from a healthy subject. The one or more biomarkers can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or the one or more biomarkers from a healthy subject can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.

[0053] A fourteenth aspect provides a method of detecting cancer in a subject. The method can comprise: a) adding a protective agent to a blood sample from the subject; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data.

[0054] A fifteenth aspect provides a method of treating cancer. The method can comprise: a) adding a protective agent to a blood sample from the subject; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and772734-ASB-016PC h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and i) where the subject is identified as having cancer, administering one or more anticancer agents or treatments to the subject.

[0055] A sixteenth aspect provides a method of monitoring cancer treatment in a subject. The method can comprise: a) adding a protective agent to a blood sample from the subject; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) repeating steps a)-g) at a different time point; i) comparing the mass spectrometry data obtained at points f) and g) to determine if there are any changes.

[0056] A seventeenth aspect provides a method of detecting cancer in a subject. The method can comprise: a) adding a protective agent to a blood sample from the subject; b) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and772734-ASB-016PC i) performing imaging on the subject to determine the location of a primary tumor or lesion.

[0057] An eighteenth aspect provides a method for reducing an amount of imaging necessary in a group of subjects to be screened for cancer. The method can comprise: a) adding a protective agent to a blood sample from each of the subjects in the group; b) contacting the blood sample from each of the subjects with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to healthy reference data; and h) identifying each of the subjects in the group as not having cancer if the amount of one or more biomarkers do not differ from the healthy reference data and identifying each of the subjects in the group as having cancer if the amount of one or more biomarkers differs from the healthy reference data; and i) performing imaging on only the subjects identified as having cancer to determine the location of a primary tumor or lesion, wherein the amount of imaging is reduced in the group of subjects.

[0058] In any of the fourteenth, fifteenth, sixteenth, seventeenth, or eighteenth aspects, the method can further comprise additionally performing three dimensional (3D) digital holography on a blood sample from the subject to identify and / or isolate circulating tumor cells.

[0059] In any of the seventeenth, or eighteenth aspects, the imaging comprises: in vitro imaging; in vivo whole-body imaging; in vivo organ specific imaging; in vivo tissue specific imaging; or combinations thereof. Cancer can be detected prior to or at stage 0, I, II, III or IV. Cancer can be detected prior to or at stage III. The blood sample can be whole blood, serum, or plasma.

[0060] In any of the fourteenth, fifteenth, sixteenth, seventeenth, or eighteenth aspects, the method can further comprise centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support. In an aspect, prior to772734-ASB-016PC adding the blood sample to the solid support functionalized to bind extracellular vesicles, and before or after adding the protective agent, the blood sample can be treated by a) applying centrifugal force of 200-1 ,600 x g; b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g; and obtaining the supernatant as the blood sample.

[0061] In any of the fourteenth, fifteenth, sixteenth, seventeenth, or eighteenth aspects, isolating the solid support comprising bound extracellular vesicles can be performed by centrifugation, elution, chromatography, or magnetization. The solid support can be an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof. The solid support can be a magnetic bead. The solid support of step a) can be functionalized with one or more specific binding proteins that bind extracellular vesicles. The one or more specific binding proteins that bind extracellular vesicles can specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin- 1 , flotillin-2, CD31 , clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1 A1 , CD44, SLC3A2, LAMP1 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, or CA19-9. The solid support functionalized to bind the proteins in the protein sample can be carboxyl modified, amine modified, hydroxyl modified, sulfhydryl modified, epoxide modified, biotin modified, streptavidin modified, avidin modified, modified with one or more antibodies, modified with one or more lectins, and / or carbonyl modified, or combinations thereof.

[0062] In any of the fourteenth, fifteenth, sixteenth, seventeenth, or eighteenth aspects, the EV derived protein sample can be digested prior to performing mass spectrometry. The digestion can be one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof. The digest can be a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

[0063] In any of the fourteenth, fifteenth, sixteenth, seventeenth, or eighteenth aspects, the EVs can be a sub-set of EVs. The sub-set of EVs comprises EVs of about772734-ASB-016PC 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 m to aboutI O pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

[0064] In any of the fourteenth, fifteenth, sixteenth, seventeenth, or eighteenth aspects, the blood sample can be collected from the subject into a storage container comprising imidazolidinyl urea, diazolidinyl urea, formaldehyde, formalin, glutaraldehyde, or combinations thereof, or wherein imidazolidinyl urea, diazolidinyl urea, formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1 -1 aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxymethyl-1-1 aza-3,7-dioxabicyclo[3.3.0]octane, 5-hydroxy[methyleneoxy]methyl- 1-1 aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis- hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis-hydroxymethyl-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4-hydroxymethyl-2,5-dioxo- imidazolidine-4-yl)-urea, or combinations thereof, or wherein one or more of these reagents are added to the storage container after collection of the blood sample. The blood sample can be collected from the subject into a storage container comprising one or more protease inhibitors and / or one or more phosphatase inhibitors; or wherein one or more protease inhibitors and / or one or more phosphatase inhibitors are added to the storage container after collection of the blood sample. The blood sample can be treated with one or more Schiff base ligands prior to step b). The blood sample can be positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after: a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form the protein sample; and / or d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

[0065] In any of the fourteenth, fifteenth, sixteenth, seventeenth, or eighteenth aspects, the blood sample can be 50 pL to 1 ,000 pL. In an aspect, after step a) the sample is shipped to a testing center greater than 5 miles away from the subject.

[0066] In any of the fourteenth, fifteenth, sixteenth, seventeenth, or eighteenth aspects, the biomarkers can be treatment-related cancer biomarkers. The reference data can comprise amounts of one or more biomarkers from a healthy subject. The one or772734-ASB-016PC more biomarkers of step g) can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or the one or more biomarkers from a healthy subject can comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.BRIEF DESCRIPTION OF THE FIGURES

[0067] FIG. 1A-1 C show an overview of the study design and summary of protein identification. (1 A). Blood was drawn from a total of 335 patients for this study, including 116 early-stage (Stage 0-2) breast cancer patients and 219 healthy control individuals. The breast cancer patients were newly diagnosed and treatment naive, and the healthy control individuals were screened for previous and hereditary cancer history prior to enrollment. Samples were shipped overnight for processing and mass spectrometry analysis. The resulting patient proteome profiles were used to train a machine learning classifier to identify patients with early-stage breast cancer. (1 B) Well-plate schematic of the first two plates showing the number of proteins identified between breast cancer (all slash marks as shown in A2, A9, H8, top, and H2 bottom) and healthy control individuals (all slash marks as shown in A3, C8 top, and F5, F6 bottom). The plate layout was randomized to minimize plate specific effects on the analysis. (1 C) Bar graph depicting the number of proteins identified per sample in breast cancer patients and healthy control individuals. Created in BioRender. Ball, H. (2025) BioRender.com / pbyhjdd

[0068] FIG. 2A-2C show performance of the protein-based ML classifier. (2A) Receiver operating curve (ROC) showing the model’s strong discriminatory power to distinguish between breast cancer patients and healthy controls. (2B) Dot plot of the overall sensitivity and specificity of the ML classifier. (2C) Dot plot of the sensitivity of the ML classifier broken down by breast density. Here, low density is defined as women with BIRADS A or B, while high density is defined as women with BI-RADS C or D. Brackets on dot plots represent the 95% Wilson confidence intervals on the measurements.

[0069] FIG. 3. Volcano plot reveals several proteins enriched in cancer patients as compared to healthy control patients.

[0070] FIG. 4. Selective pathways expressed in cancer patients compared to healthy control patients from deep proteome profiling comprising the expression of 3,000+ proteins.

[0071] FIG. 5A-5B show rug plots denoting the mean abundance distribution of: (5A) the top 100 breast cancer specific proteins selected by the classifier and (5B) the top 100 healthy control specific proteins selected by the classifier. The increased concentration of cohort-specific proteins in the lower abundant regions highlights the importance of our772734-ASB-016PC deep proteomic profiling workflow in identifying markers differentially expressed across the two cohorts.

[0072] FIG. 6A-6B show evaluation of the protein-based classifier on individuals between the ages of 40-74. (6A) Box plots of the distribution of ages across the breast cancer patients (n = 100) and healthy controls (n = 67). (6B) Dot plot of the sensitivity and specificity of the classifier for the age-adjusted cohort.

[0073] FIG. 7A-7C show methodology of protein normalization strategy. (7A) Scatter plot of all the PG abundances normalized for n vs (n+1 ) runs. (7B) Boxplot for median fold change by run of PG abundances normalized for n vs (n+1 ) runs. (7C) R2fit for PG abundances normalized tor n vs (n+1 ) runs.

[0074] FIG. 8A-8F. Overview of the sample processing methodology (8A) after receiving the banked plasma samples through injection onto the mass spectrometer followed by data processing, normalization and then cancer prediction (8B). Created using BioRender. The number of peptide (8C) and proteins (8D) across health and breast cancer samples (both training and validation cohorts) were nearly identical. Spearman correlation (8E) and principal component analysis (PCA, F) were assessed for any discrepancies across the samples which again were nearly identical.

[0075] FIG. 9A-9E. Training and validation performance. Receiver operator curve (ROC) was assessed for the training (9A) and validation (9C) with performance of sensitivity and specificity for the training (9B) and validation samples (9D). Sensitivity remained high across all breast cancer stages (9E).

[0076] FIG. 10A-10B Sensitivity across breast cancer subtypes. Sensitivity analyses of breast cancer molecular (10A) and pathological (10B) subtypes show no discernable differences among the different groups.

[0077] FIG. 11A-11 B. Assessment of confounders based on age and sample source. To ensure that the training model was not influenced by confounders, we assessed model performance by age (11 A) and sample source (11 B).

[0078] FIG. 12A-12D. Pathway analysis of breast cancer enriched proteins. Gene set enrichment analysis was performed on all pathways with >15 genes (12A) and found enrichment of pathways including epithelial-to-mesenchymal transition (EMT) (12B, 12C) and PI3K-AKT signaling (12B, 12D).

[0079] FIG. 13A-13B. Healthcare utility of deep proteome based breast cancer supplemental screening test. Women with dense breasts were assumed to receive standard of care with low uptake of supplemental screening or receive our test following a negative mammogram (13A) and found to have a much higher rate of detected dense772734-ASB-016PC breast cancers with low rates of false positives when screened via the methods as disclosed herein (13B).

[0080] FIG. 14. Plate layout highlights the locations of the controls and patient samples. Columns 1 and 12 are reserved for standard curves during peptide normalization.

[0081] FIG. 15A-15G. Plate level controls to assess mass spectrometry functionality. Commercial enolase standards were assessed for retention time (RT) differences (15A) and total precursor areas for four selected peptides (15B). Commercial HeLa cell lysates were assessed for the total number of peptides (15C), proteins (15D), and peptide abundances of four selected peptides (15E). The percent coefficient of variation (%CV) (15F) was also evaluated on HeLa cell lysates to measure the consistency and reproducibility of the mass spectrometry runs. Total ion chromatograms (TIC) were compared between blank injections and patient sample injections to determine possible carryover of protein signals. The blank samples represent <1 % of the patient samples TIC (15G).

[0082] FIG. 16A-16D. Sample level controls to assess processing functionality. Commercial yeast lysate was added to an individual well to mimic sample preparation. Cysteine modifications were evaluated to measure proper alkylation and reduction efficiency (16A). Positive (16B) and negative (16C) control samples consisting of breast cancer and healthy patients, respectively, were evaluated for the number of peptides (16B) and proteins (16C) between both groups. The performance of the controls were also evaluated (16D).

[0083] FIG. 17. Repeatability and reproducibility samples were processed in triplicate by a single operator (n=8) or reproduced by two operators (n=8). The model scores show tight clustering within a donor, indicating that most of the variability can be assigned to sample variability rather than operator or test variability. After classification using the model threshold, 100% of the donors showed full agreement between the repeated measurements.

[0084] FIG. 18. Depth of proteome coverage. The S-plot shows protein abundance over 8 orders of magnitude over 9,000 proteins. Typical proteins described in the Human Protein Atlas are shown.

[0085] FIG. 19A-19B. Assessment of confounders based on race and sample preparation batch. To ensure that the training model was not influenced by confounders, we assessed model performance by race (19A) and sample preparation batch or by plate (19B).

[0086] FIG. 20A-20C. Immune-related pathways are not enriched in breast cancer patients. We evaluated GSEA pathways including inflammatory response (20A),772734-ASB-016PC interferon gamma response (20B), and interferon alpha response (20C). Each pathway showed no enrichment in either healthy or breast cancer patient samples.DETAILED DESCRIPTION

[0087] Aspects of the disclosure are more particularly described below. The examples set forth herein are intended as illustrative only, as numerous modifications and variations therein will be apparent to those skilled in the art. The terms used in the specification generally have their ordinary meanings in the art, within the context of the invention, and in the specific context where each term is used. Some terms have been more specifically defined below to provide additional guidance to the practitioner of the methods described below and in the appended claims.Overview

[0088] Aspects of the disclosure include methods of isolating, detecting, and analyzing extracellular vesicles from a biological sample. Proteomic analysis can be performed on extracellular vesicles (EVs) in a biological sample, which includes identifying, quantifying, and / or characterizing proteins or a group of proteins in the sample by mass spectrometry. EV characteristics can differ by disease state, enabling the biomarker signature profile of these EVs to be used in identifying the presence of cancer or tumor cells. Furthermore, the biomarker signature profile can be used to identify the most promising cellular and immunotherapies for that individual. Furthermore, the biomarker signature profile can be combined with imaging of cells, tissues, or organs. These techniques can be combined with 3D holographic imagery of cells from the same patient sample to improve the accuracy of detecting cancer in the patient.Extracellular Vesicles

[0089] Extracellular vesicles (EVs) are a class of membrane bound organelles secreted by various cell types. By way of example and without limitation, EVs include fragments of cells, exosomes, ectosomes, microvesicles, small microvesicles, vesiculated organelles, vesicles produced by living cells (e.g. by direct plasma membrane budding or fusion of the late endosome with the plasma membrane), migrasomes, apoptotic bodies, secretory autophagosomes, apoptopodia, and oncosomes. One or more types of EVs can be isolated and used in the methods described herein. EVs carry various types of molecules. The cargo can comprise small molecules, nucleic acids, proteins, carbohydrates, lipids, small molecules, and / or combinations thereof. EVs are stable carriers of proteins and the characteristics of the proteins can differ by the disease state of the host animal or cell culture from which the772734-ASB-016PCEVs are secreted, the type of biofluid containing the cells or EVs, or the organ type from which the cells secreting EVs reside. In some aspects, EV cargo can be used as biomarkers of disease such as cancer.

[0090] In some aspects, the provided techniques enrich and / or isolate exosomes in a sample. As used herein, the term “exosome” refers to cell-derived small extracellular vesicles derived from direct plasma membrane budding or fusion of the late endosome or a multivesicular bodies (MVB) with the cellular plasma membrane.

[0091] In some aspects, the provided techniques isolate and / or enrich microvesicles in a biological sample. “Microvesicles” are extracellular vesicles derived from the plasma membrane budding directly outwards. In some aspects, microvesicles may be larger than exosomes in size, such as from 40 to 1000 nm. Microvesicles may also be known as “ectosomes” or “microparticles.”

[0092] Apoptotic bodies are plasma membrane-budding extracellular vesicles in the context of apoptosis.Biological Samples

[0093] Methods for isolation or analysis of extracellular vesicles are provided herein. In various aspects, a biological sample is collected from an animal subject (human or non-human animal). In some cases, a biological sample includes a subject or patient sample. In various aspects, the biological sample contains extracellular vesicles or a sub-set of extracellular vesicles.

[0094] A patient or subject can be a human or non-human animal. A source can be a direct or indirect source of a biological sample. For example, a biological sample can be obtained from a depository, such as a blood or tissue bank, and / or directly from a patient. A source of a biological sample can be selected based on the presence or possible presence of a cell-type, or cell-free protein source of interest therein.

[0095] A source of a biological sample can be a subject being treated for a disorder, or seeking treatment, monitoring, adjustment, or modification of an existing therapeutic intervention, or at a risk of developing a disorder. A disorder can be any alternation in a state of a subject’s body or of some of the organs thereof, that interrupts or disturbs the performance of body or organ functions. A source of a biological sample can be a subject at risk of, diagnosed with, or under clinical management for a cancer. For example, a source of a biological sample can be a subject who has undergone chemotherapy or radiation therapy. The cancer can be, for example, lung cancer, esophageal cancer, bladder cancer, gastric cancer, colon cancer, skin cancer, thyroid cancer, colorectal772734-ASB-016PC cancer, breast cancer, lymphoma, pancreatic cancer, prostate cancer, ovarian cancer, pelvic cancer, uterine cancer, and / or testicular cancer.

[0096] In an aspect, a subject has cancer, or a cancer associated condition. The cancer or cancer associated condition may be adenoid cystic carcinoma, adrenal gland tumor, adrenocorical carcinoma, amyloidosis, anal cancer, appendix cancer, astrocytoma, ataxia-telangiectasia, atypical teratoid, beckwith-wiedemann syndrome, cholangiocarcinoma, birt-hogg-dube syndrome, bile duct cancer, bone cancer, brain stem glioma, brain tumor, breast cancer, metastatic breast cancer, bronchial tumor, male breast cancer, prostate cancer, basal cell, melanoma, chordoma, craniopharyngioma, colon cancer, colorectal cancer, bladder cancer, kidney cancer, ductal carcinoma in situ, diffuse intrinsic pontine glioma, intraocular melanoma, islet cell tumors, embryonal tumors, lacrimal gland cancer, laryngeal and hypopharyngeal cancer, lung cancer (nonsmall cell, small cell), leukemia (acute lymphoblastic, acute lymphocytic, acute myeloid, B cell prolymphocytic, chronic lymphocytic, chronic myeloid, chronic T cell lymphocytic, eosinophilic), Liver Cancer, Li-Fraumei syndrome, lymphoma (Hodgkin and nonHodgkin), Burkitt lymphoma, AIDS-related lymphoma, lynch syndrome, mastocytosis, medulloblastoma, meningioma, mesothelioma, multiple endocrine neoplasia, multiple myeloma, MUTYH-associated polyposis, myelodyspastic syndrome, nasal cavity and paranasal sinus cancer, neuroblastoma, neuroendocrine tumors, neurofibromatosis, penile cancer, parathyroid cancer, skin cancer, ovarian cancer, fallopian tube cancer, peritoneal cancer, osteosarcoma, pituitary gland tumor, pleupulmonary blastoma, oral and oropharyngeal cancer, uterine cancer, pancreatic cancer, carney complex, brain and spinal cord cancer, cervical cancer, cowden syndrome, craniopharyngioma, desmoid tumor, desmoplatic infantile ganglioglioma, ependymoma, esthesioneuroblastoma, esophageal cancer, ewing sarcoma, eye cancer, eyelid cancer, familial adenomatous polyposis, familial GIST, familial malignant melanoma, familial pancreatic cancer, endometrial cancer, lip cancer, oral cancer, gallbladder cancer, gastrointestinal stromal tumor, germ cell tumor, gestational trophoblastic disease, head and neck cancer, head cancer, neck cancer, mouth cancer, hereditary breast and ovarian cancer, gastric cancer, hereditary diffuse gastric cancer, hereditary, leiomyomastosis and renal cell cancer, hereditary pancreatitis, hereditary papillary renal carcinoma, hereditary mixed polyposis syndrome, HIV / AIDS related cancers, hepatocellular cancer, hairy cell leukemia, heart tumors, retinoblastoma, rhabdomyosarcoma, salivary gland cancer, sarcoma, Kaposi sarcoma, small bowel cancer, stomach cancer, testicular cancer, thymoma and thymic772734-ASB-016PC carcinoma, thymus cancer, thyroid cancer, vaginal cancer, vulvar cancer, Werner syndrome, Xeroderma pigmentosum, or any combination thereof.

[0097] A biological sample can include cell homogenates, cell fractions, cell-free fractions such as plasma, tissue homogenates, and biological fluids, or purified fractions or semi-purified fractions thereof containing one or more proteins. In some aspects, the biological sample can be a liquid biopsy of the cancer. A biological sample can be, for example, whole blood, plasma, serum, cerebrospinal fluid, saliva, urine, or lymphatic fluid. A biological sample can be about 2,000, 1 ,000, 750, 500, 250, 100, 50, 10 pL or less.

[0098] A purified or semi-purified fraction of a homogenate or biological fluid can be obtained by precipitation, centrifugation, filtration, immuno-depletion, immune- enrichment, and / or chromatographic methods. In some aspects, a biological sample can include a cheek swab sample, a cell sample, a tissue sample, a fine needle aspirated tissue sample, bone marrow sample, tumor sample, tumor biopsy, any body fluid or biofluid, or their combinations. Tissue homogenates and biological fluids can include venous and arterial blood, lymph, urine, sperm, ascites, cerebrospinal fluid, pleural liquid, sputum, expectoration, nasal liquid, articular fluid, lachrymal liquid, liquid from urethra and ureter, biliary fluid, pancreatic fluid, gastric fluid, intestinal fluids, rectal fluid, feces, vaginal fluid, mucosa of organs like mouth, larynx, pharynx, uterus, cervix, vagina, esophagus, stomach, small and large intestine mucosa, breast, prostate, liver, lung, bone marrow and any other organ. For example, a tissue homogenate can include embryonic, epididymis, eye, muscle, skin, tendon, vein, artery, blood, heart, spleen, lymph node, bone marrow, lung, bronchus, trachea, intestine, small intestine, large intestine, colon, rectum, salivary gland, tongue, gall bladder, appendix, liver, pancreas, brain, stomach, skin, kidney, ureter, bladder, urethra, gonad, testis, ovary, uterus, fallopian tube, thymus, pituitary, thyroid, adrenal gland, or parathyroid, and can be healthy tissue or unhealthy tissue. Examples of unhealthy tissue include, but are not limited to, malignancies in reproductive tissue, lung, breast, colorectal, prostate, nasopharynx, stomach, testis, skin, nervous system, bone, ovary, liver, blood tissue, pancreas, uterus, kidney, and lymphatic tissue. A malignancy may be of one or more histological subtypes, such as carcinoma, adenocarcinoma, sarcoma, fibroadenocarcinoma, neuroendocrine, or undifferentiated subtypes. A biological sample or biological fluid can be a liquid biopsy, for example, urine, blood, whole blood, serum, plasma, cerebrospinal fluid, interstitial fluid, intestinal fluid, peritoneal fluid, pleural fluid,772734-ASB-016PC lymphatic fluid, cyst fluid, semen, bone marrow, ascites, tears, saliva, mucus, sputum, or lavage (e.g., lung, nasal, gargle, peritoneal lavages), or other suitable liquid sample.

[0099] Forexample, a biological sample can include one, 10, 50, 100, 1 ,000 ormore EV-derived protein samples. A biological sample can be, e.g., a biopsy sample, a biofluid sample, cell-free protein sample or a lysate of any of these samples.

[0100] A cell type can identify a cell based on morphology, phenotype, developmental origin, or other known or identifiable distinguishing cellular characteristics. A variety of different cell types may be obtained from a single source. For example, a biological sample can include one or more of tumor cells, cancer cells, tumor microemboli, gametes (including female gametes, such as eggs or egg cells, and male gametes, such as sperm), ovarian epithelial cells, ovarian fibroblasts, testicular cells, urinary bladder cells, pancreatic epithelium, pancreatic alpha cells, immune cells, B cells, T cells, natural killer cells, dendritic cells, cancer cells, eukaryotic cells, stem cells, blood cells, muscle cells, adipocytes, skin cells, nerve cells, bone cells, pancreatic cells, endothelial cells, pancreatic beta cells, pancreatic endothelium, bone marrow lymphoblasts, bone marrow B lymphoblasts, bone marrow macrophages, bone marrow erythroblasts, bone marrow dendritic cells, bone marrow adipocytes, bone marrow chondrocytes, promyelocytes, bone marrow megakaryocytes, bladder cells, brain B lymphocytes, brain glia cells, brain cells, brain astrocytes, neuroectoderm, brain macrophages, brain microglia, brain epithelial cells, neurons, cortical neurons, brain fibroblasts, breast epithelial cells, colon B lymphocytes, breast epithelial cells, breast myoepithelial cells, breast fibroblasts, colon intestinal epithelial cells, cervical epithelial cells, breast ductal epithelial cells, tongue epithelial cells, tonsil dendritic cells, tonsil B lymphocytes, peripheral blood lymphoblasts, peripheral blood T lymphoblasts, peripheral blood skin T lymphocytes, peripheral blood natural killer cells, peripheral blood B lymphoblasts, peripheral blood mononuclear cells, peripheral blood myeloblasts, peripheral blood monocytes, peripheral blood promyelocytes, peripheral blood macrophages, peripheral blood basophils, hepatic endothelial cells, hepatic mast cells, peripheral blood macrophages, peripheral blood basophils, hepatic endothelial cells, hepatic mast cells, peripheral blood epithelial cells, liver epithelial cells, liver B lymphocytes, spleen endothelial cells, spleen epithelial cells, spleen B lymphocytes, liver cells, liver fibroblasts, lung epithelial cells, bronchial epithelial cells, lung fibroblasts, lung B lymphocytes, lung Schwann cells, lung squamous cells, lung macrophages, lung osteoblasts, neuroendocrine cells, alveolar cells, stomach epithelial cells, stomach772734-ASB-016PC fibroblasts, and in general any of the cells of the source of a biological sample, or cells from another organism present in a biological sample.

[0101] A biological sample can include any number of cells. For example, a biological sample can include one, 10, 50, 100, 1 ,000 or more cells of a single cell-type or of a combination of cell-types. The number of cells per unit volume can range from one to 1 ,000,000 or more cells per milliliter, including at least 10 / ml, 100 / ml, 1000 / ml, 5,000 / ml, 10,000 / ml, 50,000 / ml, 100,000 / ml, 150,000 / ml, 500,000 / ml, or more cell / ml.

[0102] A biological sample can be a complex composition of cells, which can be treated to enrich or isolate one or more cell-types, or to facilitate enrichment or isolation of one or more cell-types. Enrichment and / or isolation can increase the proportion of one or more cell-types present in a biological sample, such as one or more low-frequency cell-types, relative to a higher-frequency cell-type, as compared with the distribution of cell-types in an unenriched biological sample when it is obtained from the same source or a substantially similar source. An enriched or isolated biological sample comprising one or more cell-types can be enriched in a target cell type, as compared to the unenriched biological sample.

[0103] In an aspect, a cell-free protein sample can be extracellular vesicles (e.g., extracellular vesicles from plasma), apoptotic bodies, migrasomes, microvesicles, exosomes, or other lipid membrane encapsulated nanoparticles less than 1 micrometer in diameter, or combinations thereof. A cell-free protein sample can contain a multitude of different types of proteins, e.g., 5, 10, 100, 1 ,000, 10,000 or more different types of proteins.

[0104] A biological sample can optionally be enriched in one or more cell-types by one or more sample processing steps, such as dilution, filtration, immunogenic separation, electrophoresis, centrifugation, microfluidics, microscopy, and imaging. An enriched biological sample can include any number of cells. For example, an enriched biological sample can include one, 10, 50, 100, 1 ,000 or more cells of a single cell-type or of a combination of cell-types. The number of cells per unit volume can range from one to 1 ,000,000 or more cells per milliliter, including at least 10 / ml, 100 / ml, 1000 / ml, 5,000 / ml, 10,000 / ml, 50,000 / ml, 100,000 / ml, 150,000 / ml, 500,000 / ml, or more cell / ml. An enriched or isolated biological sample can comprise one or more cell-types, such as an immune cell or subset of immune cells, mesenchymal cells, such as fibroblasts, and / or circulating tumor cells or subset of circulating tumor cells. Immune cells and subsets thereof include innate immune cells, e.g., granulocytes, neutrophils, eosinophils, basophils, mast cells, monocytes, dendritic cells, and macrophages; adaptive immune772734-ASB-016PC cells, e.g., B cells and T cells and subsets thereof, including T helper cells (Th) 1 , Th2, Th 17, and regulatory T cells; and cells having characteristics of innate and adaptive immune cells, such as Natural Killer cells. Circulating tumor cells subsets can include epithelial and mesenchymal circulating tumor cells. An enriched or isolated biological sample comprising one or more cell-types can be depleted in one or more cell-types that were present in an unenriched biological sample obtained from the same source or a substantially similar source. A biological sample obtained from substantially similar sources can include a negligible difference in composition and distribution of cell-types.

[0105] A biological sample can include one or more cell-types and other biomolecules, or mixtures thereof, such as one or more proteins, lipids, carbohydrates, and nucleic acids. A biological sample can be a cell lysate, i.e., without any steps to separate and / or purify and / or eliminate cellular components or cellular debris. A biological sample can include one or more reagents to stabilize cell-types or biomolecules in a collected sample for transport, storage, or other handling.

[0106] A biological sample, e.g., blood, can be about 1 ,000, 750, 500, 400, 300, 200, 250, 100, 50 pL or less of a biological sample.

[0107] A biological sample can include a protein of interest. A protein of interest can be preselected and vary according to the purpose of a proteomic analysis, such that a protein of interest in one analysis can be irrelevant in another analysis. A protein of interest can be, for example, a diagnostic, predictive, therapeutic, or prognostic biological marker, or biomarker, an enzyme, glycoprotein, hormone, receptor, antigen, antibody, growth factor, cytokine, fusion protein, etc., without limitation. A protein of interest can be obtained by recombinant DNA technology, or be a putative protein, the existence of which can be predicted on the basis of an open reading frame in a nucleic acid sequence.Sample Collection

[0108] In an aspect, a biological sample (e.g., a blood-based sample or other suitable sample) is collected and added to a collection tube or container (e.g., about a 5, 2, 1 , 0.5 mL container). A collection tube or container can comprise a protective agent, a stabilizing agent, or preservative agent comprising imidazolidinyl urea, diazolidinyl urea, formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5- hydroxymethoxymethyl-1 -1 aza-3,7-dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1 -1 aza- 3,7-dioxabicyclo[3.3.0]octane, 5-hydroxy[methyleneoxy]methyl-1-1 aza-3, 7- dioxabicyclo[3.3.0]octane, quaternary adamantine, 1 -(3,4-bis-hydroxymethyl-2,5-dioxo- imidazolidin-4-yl)-1 ,3-bis-hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-772734-ASB-016PC 4-yl)-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea or combinations thereof (at about 0.01 g / ml to about 5 g / ml of the agent or about 0.1 to about 10.0% by weight of the total mixture with the sample), glycine, and / or an anti-coagulant. Ethylenediaminetetraacetic acid (EDTA) in an amount of less than about 0.5, 1.0, 1.8, 2.0, 3.0, 4.0, or 5% by weight of the total mixture can also be present. EDTA can be present in at about 0.5, 1 , 1 .8, 2, 3 mg / ml_ or more of blood. A nuclease inhibitor at about 0.5% to about 20% by weight of the total mixture can also be present. Therefore, a protective agent, a stabilizing agent, or preservative agent can comprise one or more of imidazolidinyl urea, diazolidinyl urea, formaldehyde, formalin, glutaraldehyde, glycine, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1-1 aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxy[methyleneoxy]methyl-1-1 aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis- hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, an anti-coagulant, ethylenediaminetetraacetic acid, and / or a nuclease inhibitor. In an aspect, the collection container has the agent(s) within the container prior to sample collection or the agent(s) are added after sample collection.

[0109] A blood-based sample can be stable at room temperature for about 0, 0.5, 1 , 2, 3, 4, 5, 6, 7, 8, or more days.

[0110] A fixed sample is a sample that has been exposed to a protective agent, a stabilizing agent, and / or a preservative agent like imidazolidinyl urea, diazolidinyl urea, formaldehyde, formalin, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2- nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5- hydroxymethoxymethyl-1 -1 aza-3,7-dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1 -1 aza- 3,7-dioxabicyclo[3.3.0]octane, 5-hydroxy[methyleneoxy]methyl-1-1 aza-3, 7- dioxabicyclo[3.3.0]octane, quaternary adamantine, 1 -(3,4-bis-hydroxymethyl-2,5-dioxo- imidazolidin-4-yl)-1 ,3-bis-hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin- 4-yl)-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, and / or glutaraldehyde to preserve the sample prior to, for example, shipping or storage. In an aspect a fixed sample can be de-crosslinked prior to analysis. A fixed sample can be contacted with one or more Schiff base ligands to de-crosslink preservatives in the sample. A Shift base ligand comprises an imine (-C=N-) functional group derived from the condensation of primary amine (R-NH2) and carbonyl compounds (RIR2-C=O). Schiff base complexes772734-ASB-016PC include V (IV), Mn (II), Ni (II), Mo (VI), Fe (II), Cu (II), Co(ll), Zn(ll), Ru (II), Rh(l), Pd(ll), and Pt(ll) complexes.

[0111] In an aspect, de-crosslinking concentration of one or more Schiff base ligands can be about 500pM to about 5mM (e.g., 500, 600, 700, 800, 900 pM or more or 1 , 2, 3, 4, 5 mM or more (or any range between about 500 pM and 5Mm). In an aspect a de-crosslinking reaction occurs at a pH about 4, 5, 6, 7, 8, 9, or 10 (or any range between about 4 and 10).Isolation of Extracellular Vesicles

[0112] In some aspects, extracellular vesicles are isolated from a subject’s biological sample (e.g., blood or plasma). In some aspects, extracellular vesicles are isolated from a biological sample by applying a centrifugal force of about 200, 300, 400, 500, 600, 700, 800, 900, 1 ,000, 1 ,100, 1 ,200, 1 ,300, 1 ,400, 1 ,500, 1 ,600) x g (or any range between about 200 and 1 ,600 x g), for 1 , 5, or 10, 15, 20, 25 or more minutes followed by transferring the supernatant to a new vessel, and applying centrifugal force of about 1 ,500, 1 ,600, 1 ,700, 1 ,800, 1 ,900, 2,000, 2,100, 2,200, 2,300, 2,400, 2500, 2,750, 3,000, 3,250, 3,500 x g (or any range between about 1 ,500 and 3,500 x g) for 1 , 5, or 10, 15, 20, 25 or more minutes. This low speed of the centrifugation is advantageous because it preserves a broader sample of EVs as compared to methods using higher speeds.

[0113] EVs can range in size from about 30 nm to about 10pm in size. In an aspect, a sub-set of EVs can be used in the methods described herein. A sub-set of EVs can comprise EVs of about 50-300 nm, small EVs of about 30-50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1-10pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm. In an aspect, EVs of all sizes are isolated for further analysis. In an aspect, EVs of all sizes, oncosomes of all sizes, microvesicles of all sizes, migrasomes of all sizes, and apoptotic bodies of all sizes are all isolated and used for further analysis.

[0114] In further aspects, the centrifugation produces a cell-free sample containing the extracellular vesicles.

[0115] In some aspects, the methods provided herein can include immobilizing an entity of interest (e.g., extracellular vesicles or a sub-set of extracellular vesicles) to be analyzed on a solid substrate. Exemplary solid substrates can comprise beads or other suitable surfaces. In some aspects, the solid substrate can be or comprise a capture surface (e.g., an entity capture surface) of an analysis chamber, including, for example, beads, filters, matrices, membranes, plates, tubes, and / or wells.772734-ASB-016PC

[0116] In some aspects, the methods provided herein include an immobilization of extracellular vesicles to a solid substrate, lysis of EVs, and a second immobilization step of immobilizing EV proteins (e.g., EV membrane proteins and / or the contents of the EVs) on a solid substrate. Solid substrates can comprise beads or other suitable solid substrates. In some aspects, a solid substrate can comprise a capture surface (e.g., an entity capture surface) of an analysis chamber, including, for example, beads, filters, matrices, membranes, plates, tubes, and / or wells.

[0117] In some aspects, a solid support is comprised of beads, e.g., magnetic beads. In some aspects, specific binding proteins, such as antibodies or specific binding proteins thereof are affixed to the solid support and bind a target extracellular vesicle in the biofluid to the solid support. Extracellular vesicles can be isolated from the sample by removing the solid support from the sample and subsequently separating the EVs from the solid support by elution or other suitable method. In some aspects, specific binding proteins, such as antibodies or specific binding proteins thereof are affixed to the solid support. In some aspects, specific binding proteins, such as antibodies or specific binding proteins thereof affixed to the solid support are any combination of anti-dextran, anti-CD63, anti-CD81 , anti-CD9, anti-TSG101 , anti-ALIX, anti-HSP70, anti-HSP90, anti- flotillin-1 , anti-flotillin-2, anti-CD31 , anti-VE-cadherin, anti-CD41 , anti-CD61 , anti-CD45, anti-EpCAM, anti-HER2, anti-EGFRvll I, anti-clatherin, anti-CD29, anti-CD47, anti-CD82, anti-CD98, anti-CD147, anti-syntenin, anti-AnxA1 , anti-AnxA2, anti-AnxA5, anti-AnxA6, anti-AnxA7, anti-AnxA11 , anti-ATP1A1 , anti-CD44, anti-SLC3A2, anti-LAMP1 binding specific binding proteins, streptavidin, avidin, lectins, biotin, or combinations thereof, such as antibodies or specific binding proteins thereof. Specific binding proteins (e.g., antibodies and fragments thereof) that bind these targets are known in the art.

[0118] In some aspects, extracellular vesicle-bound solid supports are washed with phosphate buffered saline (PBS). In some aspects, protein-bound solid supports are eluted from solid supports with a lysis buffer (e.g., a lysis buffer containing TCEP (Tris(2- carboxyethyl)phosphine hydrochloride), CAA (chloroacetamide), dithiotheritol (DTT) and iodoacetamide (IAA) or any combination thereof).

[0119] In some aspects, a solid support can bind proteins in the sample such that the target proteins are isolated from the sample by removing impurities from the sample and subsequently separating the target proteins from the solid support by elution or other suitable method. In some aspects, two separate solid support separation steps are performed, with the product of the first separation (proteins derived from extracellular vesicles isolated with solid supports coupled to a combination of, for example, anti-CD63,772734-ASB-016PC anti-CD81 , anti-CD9, anti-TSG101 , anti-ALIX, anti-HSP70, anti-HSP90, anti-flotillin-1 , anti-flotillin-2, anti-CD31 , anti-VE-cadherin, anti-CD41 , anti-CD61 , anti-CD45, anti- EpCAM, anti-HER2, anti-EGFRvlll, anti-clatherin, anti-CD29, anti-CD47, anti-CD82, anti-CD98, anti-CD147, anti-syntenin, anti-AnxA1 , anti-AnxA2, anti-AnxA5, anti-AnxA6, anti-AnxA7, anti-AnxA11 , anti-ATP1A1 , anti-CD44, anti-SLC3A2, anti-LAMP1 binding specific binding proteins, streptavidin, avidin, lectins, biotin, or combinations thereof; or protein cancer markers, e.g., anti-EGFR, anti-HER2, anti-c-MET, anti-VEGFR, anti- EpCAM, anti-MUC1 , anti-integrins (e.g., anti-avp3 anti-a6p4), anti-PD-L1 , anti-PD-1 , anti-B7-H3, anti-B7-H4, anti-CD19, anti-CD20, anti-CD22, anti-CD33, anti-CD30, anti- CEA, anti-PSMA, anti-GD2, anti-CA19-9, or combinations thereof) used as the input for the second separation (e.g., using carboxylate modified solid supports to isolate proteins). In some aspects, the protein binding solid support, e.g., magnetic beads, are modified with free carboxyl groups, hydroxyl groups, carbonyl groups, amine groups, epoxide groups, sulfhydryl groups, biotin, streptavidin, avidin, antibodies, lectins, or combinations thereof. In some aspects, protein-bound solid supports are washed with acetonitrile (ACN), ethanol, H2O, isopropanol, acetone, or any combination thereof.

[0120] In some aspects, the protein-bound solid support (e.g., protein-bound beads, e.g., magnetic beads), are resuspended in TEAB (triethylammonium bicarbonate), ammonium bicarbonate (ABC), tris, HEPES, or other suitable buffer prior to addition of Lys-C and trypsin. In some aspects, protein is eluted from the solid support by addition of Lys-C, trypsin, or a combination thereof. In further aspects, trifluoroacetic acid (TFA), ammonium hydroxide, or any combination thereof can be added to the protein and solid support mixture.Sample Preparation

[0121] In an aspect, certain proteins can be removed from the sample prior to analysis (i.e., negative enrichment). This can significantly reduce the abundance of proteins that are of no interest while increasing the relative concentration of target proteins. In an aspect, proteins are removed or reduced as part of an EV. In another aspect, the removed or reduced proteins are not present in or on an EV. In an aspect, proteins such as albumin, immunoglobulins, and complement proteins can be removed or reduced via immunoprecipitation, affinity procedures, or other suitable methodology. For example, albumin can be removed or reduced from a sample by TCA / acetone precipitation, affinity-based methods using antibodies that bind albumin, and resins that bind albumin. Immunoglobulins can be removed or reduced from a sample via affinity chromatography (e.g., using Protein A or Protein G columns), electrodialysis with metal772734-ASB-016PC ion affinity precipitation, and / or plasma exchange. Complement can be removed or reduced from samples via enzymatic degradation with plasmin, using sorbents in membrane plasmapheresis, the use of antibodies such as eculizumab or ravulizumab, anti-C1q, anti-C3b, anti-C3, or other suitable method. About 50, 100, 250, 500, 750, 1 ,000, 1 ,250, 1 ,500 or more unique proteins can be removed or reduced prior to analysis thereby expanding the dynamic range of protein detection. In an aspect, the amount of unwanted proteins are reduced by about 5, 10, 20, 30, 40, 50, 60, 70, 80, 90% or more. In an aspect, after negative enrichment about 10,000, 8,000, 7,500, 7,000, 6,000, 5,000 or less proteins can be identified in a sample. In an aspect, after negative enrichment about 8,000 or less proteins can be identified in a sample.

[0122] In an aspect, certain proteins can be enriched from the sample prior to analysis (i.e. , positive enrichment). This can increase the relative concentration of target proteins. In an aspect, proteins are enriched as part of an EV. In another aspect, the proteins are not present in or on an EV and are enriched as proteins. Positive protein enrichment can be completed via immunoprecipitation (e.g., using antibodies specificfor target proteins). In an aspect, immunoprecipitation can be combined with other methods, such as size, dipole moment, zeta potential, solubility, deformability, and / or density. In immunoprecipitation methods, for example, antibodies specific for cell membrane proteins or other proteins are immobilized to Protein A or Protein G Sepharose or magnetic beads. The sample is added to the solid support (e.g., beads) and the target protein and / or EV binds to the antibody. The solid support is washed and the target proteins and / or EVs can be eluted from the solid support.

[0123] In an aspect, EVs are positively enriched using immunoprecipitation or other methods targeting CD9, CD63, CD81 , Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin- 2, CD31 , VE-cadherin, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1A1 , CD44, SLC3A2, LAMP1 , CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, CA19-9, or combinations thereof. In an aspect, microvesicles are positively enriched using immunoprecipitation or other methods targeting integrins, selectins, and / or phosphatidylserine. In an aspect, apoptotic bodies are positively enriched using immunoprecipitation or other methods targeting Annexin V and / or histones. In an aspect, migrasomes are positively enriched using immunoprecipitation or other methods targeting tetraspanin-4 and / or integrins.772734-ASB-016PC

[0124] In an aspect, EV or cell membrane proteins are enriched using antibodies or other suitable methods. Examples of membrane proteins are: Spectrin, actin, ankyrin, Band 3 (i.e., AE1) glycophorins, Aquaporin 1 , Piezo-1 , Glutl , CD44, CD47, integrins, selectins, chemokine receptors, antigen-presenting proteins, and serine proteases.

[0125] In an aspect, EV membrane proteins are purified by disrupting EVs and then isolating the membrane proteins by subcellular fractionation using ultracentrifugation or density gradients, adhesion-based methods utilizing polylysine-coated surfaces to bind plasma membranes, or affinity purification using antibodies or lectins to bind specific proteins.

[0126] In an aspect, positive and / or negative enrichment can occur prior to or after contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample. In an aspect, positive and / or negative enrichment can occur prior to or after isolating the solid support comprising bound extracellular vesicles. In an aspect, positive and / or negative enrichment can occur prior to or after lysing the bound extracellular vesicles to form a protein sample. In an aspect, positive and / or negative enrichment can occur prior to or after contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample forming an extracellular vesicle (EV) derived protein sample.Analysis of EV-Derived Proteins

[0127] One or more proteins present in an EV-derived sample can include proteins and other biomolecules, or mixtures thereof, such as one or more lipids, carbohydrates, and nucleic acids. An EV-derived sample can be subjected to one or more steps to separate and / or purify one or more proteins, and / or eliminate non-protein cellular components or cellular debris. Extraction can vary based on sample type and the structure and chemical composition of a protein of interest present in a biological sample or thought to be present in a biological sample.

[0128] An EV-derived sample of extracted proteins can include a proteome or set of intact proteins encoded on a genome as expressed and / or as modified by a cell, tissue, or organism at a given sampling time. A proteome can include extracted proteins and secreted proteins. A proteome can include at least about 20 intact proteins, at least about 50 different intact proteins, at least about 100 different intact proteins, at least about 1 ,000 intact proteins, at least about 2,000 intact proteins, at least about 5,000 intact proteins, at least about 7,500 intact proteins, at least about 10,000 different intact proteins or protein isoforms, at least about 100,000 different intact proteins or protein isoforms, or more. A proteome can include a set of intact proteins or protein isoforms772734-ASB-016PC resulting from any translation event, expressed by a naturally-occurring or transgenic cell. A proteome can include a set of intact proteins or protein isoforms expressed under normal physiological or pathological conditions, and / or in response to exposure to a chemical agent or environmental state. Extracted proteins can include one or more purified fractions of a proteome,

[0129] A set of proteins from an EV-derived sample can include one or more full- length proteins and / or truncated proteins such as protein isoforms (e.g., 1 , 10, 100, 1 ,000, 10,000, 100,000 proteins or more). A full-length protein can be an intact protein as it occurs in its natural state, i. e. , a protein having all amino acids encoded by an intact genetic sequence, unaltered by heat, chemicals, enzyme action or protocols used to extract the protein from a cell amino acid sequence as expressed in vivo, or variants thereof. A truncated protein or protein isoform can be a genome-encoded variant of full- length protein that is shortened relative to a full-length protein due to, for example, premature termination of its synthesis during translation or alternative splicing. A truncated protein can lack an amino acid from a N- or C-terminal end relative to a full- length protein. A full-length or truncated protein can be 10, 20, 30, 40, 50, 60, 70, 80, 100, 200, 300, 400, 500, 600, 700, 800, 1 ,000, 5,000 or more amino acids in length.

[0130] A composition of proteins from an EV-derived sample can include proteins comprising L- and / or D-amino acids, and / or amino acids other than the 20 gene- encoded, proteinogenic amino acids, which amino acids can be incorporated directly into an intact protein by an unusual mRNA translation step (e.g., selenocysteine) produced by metabolic conversions of free amino acids (e.g. ornithine and citrulline), modified by a post-transitional modification (e.g., acetylation, amidation, deamidation, biotinylation, C-mannosylation, flavinylation, farnesylation, formylation, geranyl-geranylation, lipidation, phosphorylation, glycosylation, hydroxylation, disulfide bond formation, methylation, myristoylation, sulphation, carboxylation, ADP-ribosylation, etc.), and / or modified by chemical modification techniques. An intact protein can associate with one or more other intact proteins to form a multi-subunit complex, such as a quaternary structure. The intact proteins of a multi-subunit complex can be different, similar, or identical. An intact protein can be a crosslinked multi-subunit complex, or a subunit thereof. An intact protein can include a branched chain.

[0131] A composition of EV-derived proteins can include an intact protein, or a mixture of different intact proteins, such as two or more different intact proteins, e.g., >5 intact proteins, >10 intact proteins, >20 intact proteins, >30 intact proteins, >40 intact proteins, >50 intact proteins, >60 intact proteins, >70, intact proteins, >80 intact proteins,772734-ASB-016PC >90 intact proteins, >100 intact proteins, >125 intact proteins, >150 intact proteins, >175 intact proteins, >200 intact proteins, >225 intact proteins, >250 intact proteins, >300 intact proteins, >400, intact proteins, >500 intact proteins, >600 intact proteins, >700 intact proteins, >800 intact proteins, >900 intact proteins, >1000 intact proteins, >1250 intact proteins, >1500 intact proteins, >1750 intact proteins, >2000 intact proteins, >2500, intact proteins, >3000 intact proteins, >3500 intact proteins, >4000 intact proteins, >4500 intact proteins, >5000 intact proteins, >6000 intact proteins, >7000 intact proteins, >8000 intact proteins, >9000 intact proteins, >10,000 intact proteins, etc.

[0132] An EV-derived sample protein composition can be enriched in a subset of intact proteins by isolating a desired fraction of a proteome or removing an undesired fraction of intact proteins from a proteome. For example, an EV-derived protein sample enriched in a low abundance protein can include about 15% or less of the total protein content of a proteome, such as about 10% or less, about 5% or less, about 4% or less, about 3% or less, about 2% or less, about 1 % or less of the total protein content of a proteome.

[0133] A composition of EV-derived proteins can include at about 100 mg or less intact protein, such as 50 mg, 10 mg, 1 mg, 0.1 mg, or 0.01 mg protein or less. Intact protein concentration can be in the range of about 100 mg / ml to about 1 femtogram (fg) / ml (e.g., 10.0, 1.0, 0.1 , 0.01 , 0.001 , 0.0001 mg / ml or less). An EV-derived protein composition can be adjusted to any appropriate concentration for distinguishing a measurement of a protein of interest from background noise, according to instrument detection limits, method detection limits, and / or practical quantification limits. For example, mass spectrometry signal can be concentration dependent, and thus protein concentration can be adjusted to around 10-20 pM, or about 0.01 mg / ml for a molecule of 500 g / mole molecular weight. A composition of extracted protein can be adjusted to include about 0.0001 , 0.001 , 0.01 , 0.1 , 1 , 5, 10, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 100 fmol, or more intact protein.

[0134] A composition of EV-derived proteins can include one or more proteins of interest. Non-limiting examples of a protein of interest can include one or more biomarkers associated with a cell-type or organ or tissue of interest; one or more biomarkers associated with a molecular pathway of interest; one or more biomarkers associated with a normal biologic process; one or more biomarkers associated with a pathogenic process; one or more biomarkers associated with early detection of a condition or disease; one or more biomarkers associated with progression of a condition or disease; one or more biomarkers associated with management of a condition or772734-ASB-016PC disease; one or more biomarkers associated with susceptibility to a condition or disease; one or more biomarkers associated with a therapeutic target; one or more biomarkers associated with a response to therapeutic intervention; or a combination thereof. A protein of interest can be a protein associated with a signal transduction pathway, an extracellular signaling pathway, an intracellular pathway, a protein degradation pathway, a transcriptional regulation pathway, or a combination thereof.

[0135] In an aspect, one or more biomarkers can be treatment-related cancer biomarkers. Treatment-related cancer biomarkers are molecules such as a gene mutation (e.g., mutated EGFR) or other protein that indicates a particular cancer therapy is likely to be effective in a certain patient. By testing a patient for these biomarkers treatment decisions can be personalized by choosing targeted therapies or immunotherapies that specifically address the cancer's unique characteristics, thereby improving treatment outcomes. Examples of treatment-related cancer biomarkers include HER2 amplification or overexpression with predicts benefit from trastuzumab, pertuzumab, T-DM1 in breast / gastric cancer; EGFR mutations (e.g., exon 19 deletions, L858R), which predict response to EGFR tyrosine kinase inhibitors (gefitinib, osimertinib) in NSCLC; ALK, ROS1 , and / or NTRK fusions, which predict response to ALK, ROS1 , or TRK inhibitors; PD-L1 expression, which predicts benefit from immune checkpoint inhibitors (pembrolizumab, nivolumab); MSI-high Z dMMR status, which predicts benefit from immune checkpoint inhibitors across multiple cancers; BRCA1 / 2 mutations, which predict sensitivity to PARP inhibitors. Treatment-related cancer biomarkers can also predict non-response or acquired resistance to certain treatments. For example, an EGFR T790M mutation can predict acquired resistance to first / second-gen EGFR inhibitors; KRAS mutations can predict resistance to anti-EGFR antibodies (cetuximab, panitumumab) in colorectal cancer; ESR1 mutations can predict endocrine therapy resistance in breast cancer; AR-V7 splice variant can predict resistance to androgen receptor-targeted therapy in prostate cancer.

[0136] A protein of interest or biomarker can be, for example, those listed in Table 1. In an aspect, an amount of one or more proteins of interest is elevated in cancer patients as compared to healthy patients. In an aspect, an amount of proteins of interest is decreased in cancer patients as compared to healthy patients. A pathway of interest can be, for example, those listed in Table 1. In an aspect, a pathway of interest is activated (i.e. , elevated expression of pathway proteins) in cancer patients as compared to healthy patients (e.g., KRAS-Breast, WNT signaling, LEF1 , and EMT pathways). In an aspect, a pathway of interest is deactivated (i.e., decreased expression of pathway772734-ASB-016PC proteins) in cancer patients as compared to healthy patients. Proteins of interest can be present in a composition of extracted protein at a low concentration, e.g., within 10 fmol / pl or less, 5.00, 4.00, 3.00, 2.00, 1 .50, 1 .00, 0.05, 0.005 fmol / pl or less. In an aspect, the methods described herein can isolate and quantify 2, 10, 50, 100, 500, 1 ,000, 2,000, 5,000 or more proteins of interest that are present at 10.00, 5.00, 4.00, 3.00, 2.00, 1 .50, 1 .00, 0.05, 0.005 fmol / pl or less.Sample Peptides

[0137] Detection and identification of proteins by mass spectrometry (MS) based proteomic analysis involves the detection of peptides obtained by proteolysis. A proteomic analysis can include analyzing one or more sample peptides derived from an EV-derived protein composition, as described above. Peptides can be naturally- occurring in a composition of extracted proteins, formed due to the presence of naturally- occurring proteases, formed due to the addition of proteases or other chemicals, or formed due to fragmentation during isolation. A peptide derived from an EV-derived protein sample can include linear, cyclic, and / or branched chains of amino acid residues.

[0138] A population of sample peptides can be obtained from an EV-derived sample by digesting one or more extracted proteins by enzymatic or chemical proteolysis. Proteolysis can result in cleavage of an intact protein into a population of peptide samples comprising two or more (e.g., 2, 3, 4, 5 or more) peptide fragments. The number of target peptides produced by proteolysis can vary based on the size and amino acid sequence, differential post-translational modification, alternative splicing, and the completeness of proteolytic digestion of a protein of interest present in a composition of extracted proteins.

[0139] Peptides obtained by proteolysis can exhibit different attributes, some of which can be more easily observed using MS techniques. Some peptides derived from an intact protein are common to multiple proteins or protein isoforms rendering them unsuitable as evidence for the presence or quantification of a protein of interest. A peptide fragment that can be used as a MS-detectable representative of the protein of interest can be a target for analysis (i.e. , a target peptide). A target peptide can be monitored by MS in middle-down or bottom-up methods. A target peptide can be preselected and possess known chemical, physical, and / or other properties whereby detection of a target peptide is indicative of the presence of a protein of interest in a biological sample, and / or that a quantity of a target peptide reliably represents the quantity of a protein of interest in an EV-derived sample.772734-ASB-016PC

[0140] A population of sample peptides can include at about 10 mg or less target peptide, such as 1 mg or less, 0.05 mg or less, 0.01 mg or less. A target peptide can be present in the population in a low concentration, e.g., within 10 fmol / pl or less, 5.00, 4.00, 3.00, 2.00, 1 .50, 1 .00, 0.05, 0.005 fmol / pl or less. A population of sample peptides can include total peptide content of about 10 mg or less, such as 1 mg or less, 0.05 mg or less, 0.01 mg or less. A population of sample peptides can be adjusted to an appropriate concentration, such as about 100, 95, 90, 85, 80, 75, 70, 65, 60, 55, 50, 45, 40, 35, 30, 25, 20, 15, 10, 5, 1 , 0.1 , 0.01 , 0.001 , 0.0001 fmol / pl peptide or less.

[0141] A population of sample peptides can include a mixture of different target peptides derived from one or more proteins of interest e.g., >5, >10, >20, >30, >40, >50, >60, >70, >80, >90, >100, >125, >150, >175, >200, >225, >250, >300, >400, >500, >600, >700, >800, >900, >1000, >1250, >1500, >1750, >2000, >2500, >3000, >3500, >4000, >4500, >5000, >6000, >7000, >8000, >9000, >10,000, >30,000, >50,000, >75,000, > 100,000, > 125,000, > 150,000 or more target peptides, etc.Methods of Proteomic Analysis

[0142] The methods described herein provide for mass spectrometry analysis such that specific preselected proteins (e.g., target proteins) can be identified and quantified accurately using mass spectrometric attributes. The mass spectrometric attributes of detected preselected exogenous peptides can be used to identify and optionally quantify preselected proteins obtained from an individual assay mixture. Therefore, methods of analyzing a test sample, such as a biological sample, are provided. The methods can comprise digesting EV-derived proteins to form a population of sample peptides, and performing mass spectrometry (e.g., tandem mass spectrometry, matrix-assisted laser desorption / ionization (MALDI) spectrometry, electrospray ionization spectrometry, LC- MS / MS, etc.) on the population of sample peptides to obtain an analysis of the peptides derived from the EV-derived protein sample. Protein identification can be done by matching the observed ion patterns (peptide mass fingerprints) with known protein sequences. Software can assist in piecing together the fragments to identify the full proteins. The methods can be applied to multiple populations of sample peptides and / or multiple test samples, e.g., EV-derived protein samples. In these aspects, the test peptides derived from one or more EV-derived protein samples receive a unique label from other test peptides in other test samples so the test sample from which each of the test peptides originates can be distinguished. The unique labels can be isobaric tags, such as e.g., iTRAQ® and TMTTM. The unique labels can be non-isobaric tags such as dimethyl, diethyl, SILAC (Stable Isotope Labeling by Amino acids in Cell culture), ICPL772734-ASB-016PC(Isotope-Coded Protein Labeling), 180 digestion, ICAT (Isotope-Coded Affinity Tags), or similar.

[0143] Before being subjected to mass spectrometry analysis peptides can be separated by chromatography, such as nanoliquid chromatography (nLC), or capillary electrophoresis. Peptide ions can be subjected to two, three or more rounds of MS analysis for peptide identification and quantification. A MS scan (MS1 ) can determine a mass over charge ratio (m / z) for the ion. Then, selected ions can be accumulated and fragmented, and their fragments are analyzed by a second MS scan (MS2). In some aspects, analysis of the test peptides can comprise obtaining a relative quantification of test peptides. In some aspects, analysis of the labeled test peptides can comprise sequencing the labeled test peptides. Relative quantification can be determined, which refers to the abundance of a protein or peptide in one sample relative to its abundance in another sample. A peptide signal in each run can provide a relative quantitation of the same peptides coming from each of the individual test samples.

[0144] The mass spectrometry data, i.e., the amount or level of each protein or peptide, can be compared to reference data from healthy subjects, that is, subjects without cancer. Significant differences in the level or amount of each protein or peptide in a subject sample can be determined or noted.

[0145] For all methods described herein, reference data can comprise mass spectrometry data of levels or amounts of biomarkers (i.e., proteins of interest) (e.g., 1 , 2, 3, 4, 5, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers) obtained from healthy subjects (e.g., 1 , 10, 100, 200, 300 or more healthy subjects). A subject can be identified as having cancer (e.g., breast cancer) if the amounts or levels of one or more (e.g., 1 , 2, 3, 4, 5, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more) biomarkers significantly differs from the healthy reference data. A difference can be an increase or decrease in the level or amount of a biomarker. Biomarkers here mean individual biomarkers or pathways (see, e.g., in one aspect, Table 1 ).Methods of Detecting Cancer

[0146] An aspect provides a method of detecting cancer in a subject. A blood sample can be collected from a subject and contacted with a solid support functionalized to bind extracellular vesicles in the blood sample. The solid support of can be functionalized with one or more specific binding proteins (e.g., an antibody or specific binding fragment thereof) that bind extracellular vesicles. A specific binding protein can specifically bind one or more of or any combination of CD63, CD81 , CD9, dextran, Alix,772734-ASB-016PC TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1A1 , CD44, SLC3A2, LAMP1 , EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, or GD2, CA19-9, or glycosylation (e.g., lectins). “Specifically binds” refers to the ability of a specific binding protein to recognize and bind to a particular antigen or epitope with a measurable affinity that is significantly greater than its affinity for unrelated antigens under similar conditions. This includes binding that is detectable using standard immunological assays (e.g., ELISA, SPR, flow cytometry) and excludes non-specific interactions resulting from general physicochemical properties.

[0147] Prior to contacting the blood sample with the solid support functionalized to bind extracellular vesicles, the blood sample can be centrifuged at about 200, 300, 400, 500, 600, 700, 800, 900, 1 ,000, 1 ,100, 1 ,200, 1 ,300, 1 ,400, 1 ,500, 1 ,600 x g or more (or any range between 200 and 1 ,600 x g), the supernatant can be transferred to a new vessel. This can be centrifuged at about 1 ,500, 1 ,600, 1 ,700, 1 ,800, 1 ,900, 2,000, 2, 100, or 2,220, 2,300, 2,400, 2,500, 2,600. 2,700, 2,800, 2,900, 3,000, 3,100, 3,200, 3,300, 3,400, 3,500 x g or more (or any range between 1 ,500 and 3,500 x g). The supernatant can then be used as the blood sample,

[0148] The solid support comprising bound extracellular vesicles can be isolated by, e.g., centrifugation, elution, chromatography, or magnetization. The bound extracellular vesicles can be lysed to form a protein sample. The protein sample can be contacted with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample. The solid support functionalized to bind the proteins in the protein sample can be functionalized with, e.g., free carboxyl groups, hydroxyl groups, carbonyl groups, amine groups, epoxide groups, sulfhydryl groups, biotin, streptavidin, avidin, antibodies, lectins, or combinations thereof. Each of these functionalization groups can bind a certain population of proteins.

[0149] In an aspect, the EV derived protein sample can be digested prior to performing mass spectrometry. The digest can be one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof. In an aspect, the digest can be a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.772734-ASB-016PC

[0150] An EV derived protein sample can comprise about 4,000, 5,000, 6,000, 7,000, 8,000, 9,000 or more unique proteins. A dynamic range of protein abundances spanning over 8 orders of magnitude can be identified, highlighting the ability to capture low abundance protein fractions.

[0151] Mass spectrometry can be performed on the EV derived protein sample and mass spectrometry data collected. The mass spectrometry data is compared to reference data. Reference data can comprise mass spectrometry data of levels of biomarkers (e.g., 1 , 2, 3, 4, 5, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers) obtained from healthy subjects (e.g., 1 , 10, 100, 200, 300 or more healthy subjects). A subject can be identified as having cancer (e.g., breast cancer) if the levels or amounts of at least one (e.g., 1 , 2, 3, 4, 5, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more) biomarker differs from the reference data. Biomarkers here mean individual biomarkers or pathways (see, e.g., Table 1 ).

[0152] In an aspect, elevated or reduced levels of biomarkers or activated or deactivated pathways (see Table 1 ) indicate the presence of cancer in general or a specific cancer (e.g., breast cancer). In an aspect, elevated or reduced levels of biomarkers or activated or deactivated pathways (see Table 1 ) indicate the presence of an immune response to the presence of cancer. In this aspect, a positive result indicates the presence of cancer in general.

[0153] In an aspect, if cancer is indicated, then imaging can be performed on the patient to determine the location of a primary tumor cells or lesion, determine metastatic spread, ordetermine tumor recurrence. The imaging can comprise, e.g., in vitro imaging; in vivo whole-body imaging; in vivo organ specific imaging; in vivo tissue specific imaging; or combinations thereof.

[0154] In some aspects, where the imagining results are not clear but the proteomic analysis points to a cancer diagnosis, then the patient is treated for cancer.

[0155] In an aspect, cancer (e.g., breast cancer) is detected prior to or at stage 0, I, II, III, or IV. In general, stage 0 cancer is abnormal cells that resemble cancer under a microscope but have not penetrated the basement membrane or invaded neighboring tissues; stage I cancer is small and confined to its organ of origin, without spread to lymph nodes or distant sites; stage II cancer is larger or has grown deeper into surrounding tissues and there may be limited spread to nearby lymph nodes, but no distant metastasis. Stage III cancer is significantly larger and / or more deeply invasive and has spread to regional lymph nodes and possibly adjacent tissues or organs, but not772734-ASB-016PC to distant sites; stage IV cancer has metastasized to distant parts of the body, such as liver, lungs, bone, brain and is the most advanced stage, often requiring systemic therapy rather than local treatment alone.

[0156] In stage 0 of breast cancer the disease is only in the ducts or lobules of the breast and has not spread to the surrounding tissue. This stage is also known as noninvasive cancer. At stage I breast cancer is considered invasive because the cancer cells are present in normal breast tissue. At stage IA the tumor is small and has not spread to the lymph nodes. At stage IB the tumor is in the lymph nodes and may also be present in the breast tissue. The tumor is less than 2 cm in size. Stage II is invasive breast cancer. At stage HA a tumor may not be found in the breast or there is a tumor that is 2 cm or smaller in the breast, but cancer cells have spread to at least 1 to 3 lymph nodes or a 2 to 5 cm tumor is present in the breast without spread to the axillary lymph nodes. At stage I IB the tumor is 2 to 5 cm and the disease has spread to 1 to 3 axillary lymph nodes or the tumor is larger than 5 cm but has not spread to the axillary lymph nodes. Stage III is invasive breast cancer. There are 3 types. At stage 111 A the tumor of any size has spread to 4 to 9 lymph nodes or the tumor is larger than 5cm and only has spread to 1-3 lymph nodes. At stage 111 B the tumor may be any size and the disease has spread to the chest wall. The disease may cause swelling of the breast and may be in up to 9 lymph nodes. Inflammatory breast cancer is considered stage 111 B. At stage 11 IC the tumor may be any size with spread to 10 or more lymph nodes. Stage IV is considered metastatic breast cancer. The tumor can be any size and the disease has spread to other organs and tissues, such as the bones, lungs, brain, liver, distant lymph nodes, or chest wall.

[0157] In an aspect, methods described herein can have a sensitivity of about 60, 65, 70, 75, 80, 85, 86, 87, 88, 89, 90, 91 , 92, 93, 94, 95, 96, 97, 98, 99% or more. Sensitivity measures a test’s ability to correctly identify a condition (e.g., cancer) when it is present, which means it accurately produces a positive result for subjects with the condition and minimizes false negatives. Sensitivity is calculated as the proportion of true positives out of all subjects who have the disease (true positives + false negatives). Specificity is a measure of a diagnostic test's ability to correctly identify individuals who do not have a condition, minimizing false positives. Specificity is calculated as the proportion of true negatives among all truly negative cases. In an aspect, methods described herein can have a specificity of about 60, 65, 70, 75, 80, 85, 86, 87, 88, 89,90, 91 , 92, 93, 94, 95, 96, 97, 98, 99% or more.772734-ASB-016PC

[0158] In an aspect, the methods of detection are combined with 3D holographic signatures of the morphology of peripheral blood cells (see below) to more accurately detect cancer.

[0159] Any of the solid supports can be e.g., an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof.Methods of Detection of Breast Cancer

[0160] Mammography is the gold standard for population-based breast cancer screening. However, its detection sensitivity is significantly reduced in women with dense breast tissue, who face an elevated risk of developing breast cancer. Recent updates to the FDA’s mammography regulations5underscore the increasing focus on optimizing screening strategies in this patient population (representing approximately 50% of the US screening population). MRI and Contrast-Enhanced Mammography (CEM) have recently shown potential as a promising supplement to traditional mammography screens in the BRAIDs trial6. A consensus on the best imaging strategy for individuals with dense breasts has not been established. Although supplemental imaging such as breast MRI can improve cancer detection in women with dense breasts, its use is not routinely recommended for average-risk individuals due to increased rates of false positives, over-diagnosis, additional biopsies, concern for contrast related toxicity, patient anxiety, and cost. Therefore, supplemental MRI imaging is often reserved for use in high-risk patients (with a lifetime risk of breast cancer >20%). There is currently a lack of sufficient evidence to justify the benefit of use in patients with high breast density who otherwise have a negative screening mammogram, creating an opportunity for new supplemental screening tests to help bridge this gap for high-risk patients.

[0161] The implementation of liquid biopsy-based tests for early cancer detection is poised to be an important component of the supplemental screening landscape, including breast cancer. These tests can help reduce unnecessary imaging or other diagnostic interventions, thus decreasing costs related to current supplemental screening guidelines while increasing detection rates. The low sensitivity for breast cancer at early stages with nucleotide-based tests offers opportunities to bring new technologies and approaches, such as proteomics, to at-risk women where supplemental screening would typically be implemented. Proteomics is an emerging field in the clinical diagnostics space with niche uses for blood-based diagnostic testing. This772734-ASB-016PC has typically been through analyses of a single protein or a few proteins. The incorporation of large-scale, unbiased (or shotgun) proteomics using mass spectrometry (MS)-based technologies for clinical diagnostics has not been utilized to date.

[0162] Provided herein are methods of detecting breast cancer in a subject. The methods can comprise contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; isolating the solid support comprising bound extracellular vesicles; lysing the bound extracellular vesicles to form a protein sample; contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; comparing the mass spectrometry data to reference data; and identifying the subject as having breast cancer if the levels or amounts of at least one biomarker differs from the reference data. In an aspect, the EV derived protein sample can be protease digested prior to performing mass spectrometry.

[0163] In an aspect, where breast cancer is detected, the subject can be administered one or more treatments for breast cancer.

[0164] The methods can further comprise centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support. The blood sample can be treated, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, by a) applying centrifugal force of 200-1 ,600 x g, b) transferring supernatant to a new vessel; c) applying centrifugal force of 1500-3,500 x g and obtaining the supernatant as the blood sample. The isolation of the solid support comprising bound extracellular vesicles can be performed by centrifugation, elution, chromatography, or magnetization. The solid support can be functionalized with one or more specific binding proteins that bind extracellular vesicles.

[0165] In an aspect, the diagnostic methods can be used in subjects who have had a negative mammography result. In an aspect, the diagnostic methods can be used in subjects who have a diagnosis of dense breast tissue. Dense breast tissue is breast tissue that has a higher proportion of fibrous and glandular tissue (milk ducts, glands, connective tissue) compared to fatty tissue, as seen on a mammogram. Dense breast tissue appears white on a mammogram and can obscure cancers, which also appear as white.

[0166] These methods can decrease false negative breast cancer diagnoses in subjects. That is, the methods described herein have fewer false negative breast cancer772734-ASB-016PC test results as compared to mammography, Contrast-Enhanced Mammography (CEM), ultrasound, and / or breast MRI.

[0167] The methods can further comprise performing three dimensional (3D) digital holography on a blood sample from the patient to identify and / or isolate circulating tumor cells.

[0168] In an aspect, the breast cancer is detected prior to or at stage 0, I, II, III or IV.Self-Sampling of Blood

[0169] In an aspect, a patient or subject can self-sample a blood sample with, e.g., capillary sampling ortransdermal sampling. In capillary samples, a patient or subject can use a lancet (e.g., 0.85 mm to 2.2 mm lancet) to sample blood from, e.g., an earlobe, heel, finger, arm, or other suitable site. A patient can swab the collection site with an alcohol wipe or other sanitizing wipe or solution, and then puncture the skin with the lancet and collect a blood sample with a capillary tube. Transdermal patch based phlebotomy devices and touch activated phlebotomy devices (e.g., TAP® Micro and TAP® Micro Select devices by YourBio Health, Medford MA).

[0170] In another aspect, the blood sample can be collected into a storage container from the subject comprising one or more fixatives, such as imidazolidinyl urea, diazolidinyl urea formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1-1 aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxy[methyleneoxy]methyl-1-1 aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis- hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof. Alternatively, the patient or medical professional can add these components to the collection container before or after collection (e.g., about 0.5, 1 , 2, 5, or 10 minutes after collection).

[0171] In an aspect, one or more protein stabilizers (i.e. , protease inhibitors) can be present in a collection tube or added to the tube by a patient or medical professional before or after collection. In an aspect, a protein stabilizer can be added to the collection tube at about 0.5, 1 , 2, 5, or 10 minutes after collection. Protein stabilizers can include, for example, ethylenediaminetetraacetic acid (EDTA), 4-(2-Aminoethyl)benzenesulfonyl fluoride (AEBSF), aprotinin, leupeptin, phenylmethanesulfonyl fluoride (PMSF), E-64 (Sigma Aldrich), bestatin, pepstatin A, Na-tosyl-L-lysine chloromethyl ketone (TLCK), N-772734-ASB-016PC tosyl-L-phenylalanine chloromethyl ketone (TPCK), diisopropyl fluorophosphate (DFP), soybean trypsin inhibitor (STBI), N-ethylmaleimide (NEM), and ethylene glycol bis(p- aminoethyl ether)-N,N,N',N'-tetraacetic acid (EGTA).

[0172] In an aspect, one or more phosphorylation stabilizers (i.e., phosphatase inhibitors) can be present in a collection tube or added to the tube by a patient or medical professional before or after collection. In an aspect, a phosphorylation stabilizer can be added to the collection tube at about 0.5, 1 , 2, 5, or 10 minutes after collection. Phosphorylation stabilizers can include, for example, sodium orthovanadate, beta glycerophosphate, sodium fluoride, sodium pyrophosphate, sodium molybdate, okadaic acid, calyculin A, sodium pervanadate, phenylarsine oxide, microcystin-LR, fostriecin, phoslactomycin, sodium phosphate, and imidazole.

[0173] 1 , 5, 10, 20, 50, 60, 75, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1 ,000 pL of each of one or more fixatives, protein stabilizers, and / or phosphorylation stabilizers can be added to a blood sample of 50, 100, 200, 500, 750, 1 ,000, 1 ,500, 2,000 pL or more. The total amount of one or more fixatives, protein stabilizers, and / or phosphorylation stabilizers added to a collection tube can be about 1 , 5, 10, 20, 50, 60, 75, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1 ,000, 2,000, 3,000, 4,000, or 5,000 pL.

[0174] In an aspect, the sample is shipped to a testing center greater than 5, 20, 100 miles or more away from the subject. In an aspect, no refrigeration or ice is required for shipping. In an aspect, the sample is stable for 1 , 2, 3, 4, 5, 10 or more days.

[0175] In an aspect, a subject only has to draw about 1 ,000, 750, 500, 400, 300, 200, 250, 100, 50 pL or less of a blood sample.

[0176] In an aspect, prior to processing, one or more Schiff base ligands are added to the blood storage container to de-crosslink the crosslinking incorporated into the sample by the one or more fixatives. For example, one or more Schiff base ligands can be added to the blood storage container prior to contacting the blood sample with a solid support functionalized to bind extracellular vesicles in the blood sample.3D Holographic Signatures

[0177] In an aspect, a 3D holographic signature of the morphology of cells in a peripheral blood sample (or other suitable sample) can be combined with the proteomic profiling of the same blood sample from a patient. See, for example, Fig. 1 and 2. The generation of a 3D holographic signature can be done, for example, using the methods as described in US Pat. Publ. US 2021-0237064, which is incorporated herein by reference in its entirety.772734-ASB-016PC

[0178] A 3D holographic signature can be generated using a biological fluid filtration system. The system can include a fluid receiving device adapted to receive a biological fluid (e.g., a blood sample, cerebrospinal fluid, lymphatic fluid, etc.); a valve comprising an inlet, a first outlet, and a second outlet, wherein the inlet of the valve is fluidly connected to the fluid receiving device; a scanner configured to scan the biological fluid within the fluid receiving device to produce scanned data relating to the biological fluid within the fluid receiving device, wherein the scanner comprises an optical scanner comprising a digital holographic microscope. The system can further include a control unit in communication with the scanner and the valve, wherein the control unit is configured to receive the scanned data from the scanner, wherein the control unit is configured to compare the scanned data to reference data, wherein the reference data comprise one or more characteristics of a healthy cell. The control unit can be configured to recognize the one or more characteristics of the healthy cell within the scanned data; and to control the valve based on the scanned data from the scanner. The control unit can be configured to control the valve to: (a) direct the biological fluid through the first outlet if the control unit does not recognize the one or more characteristics of the healthy cell in the scanned data, and (b) direct the biological fluid through the second outlet if the control unit recognizes the one or more characteristics of the healthy cell in the scanned data. The fluid receiving device can be comprised of a microfluidic channel. The control unit can further be configured to indicate the presence of a tumor cell in the biological fluid when the one or more characteristics of the healthy cell are not recognized in the scanned data. The reference data can further comprise an image of a healthy cell. The scanned data can further comprise an image of one or more constituents of the biological fluid. The control unit can be configured to extract a characteristic of one or more cellular constituents of the biological fluid in the scanned data, the characteristic selected from the group consisting of cell thickness, cell area, cell volume, cell dry mass, a phase shift across the cell, surface roughness and texture, cell shape, elongation, convexity, luminance, circularity, solidity and combinations thereof. The reference data can further comprise one or more characteristics of a benign constituent, wherein the control unit is further configured to recognize the one or more characteristics of the benign constituent and direct the biological fluid through the second outlet if the control unit recognizes the one or more characteristics of the benign constituent within the scanned data. The optical scanner can further includes a monochromatic laser and / or a light emitting diode.

[0179] In another aspect, a biological fluid filtration system can comprise a fluid receiving device adapted to receive a biological fluid, wherein the fluid receiving device772734-ASB-016PC includes a plurality of microfluidic channels; a valve comprising an inlet, a first outlet, and a second outlet, wherein the inlet of the valve is fluidly connected to the fluid receiving device; a scanner configured to scan the biological fluid within the fluid receiving device to produce a scanned data comprising a holographic image of one or more constituents of the biological fluid within the fluid receiving device, wherein the scanner is comprised of an optical scanner comprising a digital holographic microscope. The system can further comprise a control unit in communication with the scanner and the valve, wherein the control unit is configured to receive the scanned data from the scanner, wherein the control unit is configured to compare the scanned data to reference data, the reference data comprising one or more characteristics of a healthy blood cell, wherein the control unit is configured to recognize the one or more characteristics of the healthy blood cell within the scanned data; and wherein the control unit is configured to control the valve based on the scanned data from the scanner. The control unit can be configured to control the valve to: (a) direct the biological fluid through the first outlet if the control unit does not recognize the one or more characteristics of the healthy blood cell in the scanned data, and (b) direct the biological fluid through the second outlet if the control unit recognizes the one or more characteristics of the healthy blood cell in the scanned data.

[0180] Therefore, a method of generating a 3D holographic signature of the morphology of cells in a sample can comprise receiving the cell sample (e.g., biological fluid) by the fluid receiving device; scanning the biological fluid within the fluid receiving device by the scanner. Cells do not necessarily need to be sorted. In an aspect, the cells can be sorted by directing the biological fluid through the first outlet if the control unit does not recognize the one or more characteristics of the healthy cell within the scanned data; and directing the biological fluid through the second outlet if the control unit recognizes the one or more characteristics of the healthy cell within the scanned data. The biological fluid filtration system of can further comprising a microfluidic separator fluidly connected to an inlet of the fluid receiving device for removing one or more constituents from the biological fluid. The control unit can be configured to extract a parameter from the image of the one or more constituents of the biological fluid, wherein the parameter is selected from the group consisting of cell thickness, cell area, cell volume, cell dry mass, a phase shift across the cell, surface roughness and texture, cell shape, elongation, convexity, luminescence, circularity, solidity, nucleus-cytoplasmic ratio, inner diameter and combinations thereof.772734-ASB-016PC

[0181] The combination of 3D holographic signatures of the morphology of peripheral blood cells with deep proteomic profiling from the same sample can provide more sensitive and specific testing results for detection of cancers.Methods of Treatment

[0182] Where the subject is identified as having cancer one or more anti-cancer agents or treatments can be administered to the subject. In some aspects, a subject is diagnosed with cancer, suffering from cancer, being treated for cancer, or suspected of having cancer or a cancer associated condition. In further aspects, the cancer is detected or diagnosed in a subject.

[0183] In some aspects, the subject is administered an anti-cancer treatment, prophylactic, or therapeutic agents or therapies. Exemplary anti-cancer agents include, but are not limited to, cytostatics, enzyme inhibitors, gene regulators, cytotoxic nucleosides, tubulin binding agents or tubulin inhibitors, proteasome inhibitors, hormones and hormone antagonists, anti-angiogenesis agents, and the like. In some aspects, the therapeutic agent is a chemotherapeutic agent, an anti-cancer agent, an anti-angiogenic agent, an anti-fibrotic agent, a biomarker based treatment, an immunotherapeutic agent, hormone therapy, hyperthermia, photodynamic therapy, a therapeutic antibody, a bispecific antibody, an “antibody-like” therapeutic protein (such as DARTs®, Duobodies®, Bites®, XmAbs®, TandAbs®, Fab derivatives), an antibodydrug conjugate (ADC), a radiotherapeutic agent, an anti-neoplastic agent, an antiproliferation agent, an oncolytic virus, a gene modifier or editor (such as CRISPR / Cas9, zinc finger nucleases or synthetic nucleases, or TALENs), a CAR T-cell immunotherapeutic agent, an engineered T cell receptor (TCR-T), a stem cell transplant, surgery, targeted therapy, or any combination thereof. In some aspects, the therapeutic agent is an anti-cancer agent. In some aspects, the therapeutic agent is a chemotherapeutic agent. These therapeutic agents may be in the forms of compounds, antibodies, polypeptides, or polynucleotides.

[0184] Exemplary anti-cancer agents include, but are not limited to, curcumin, interferon (interferon, IFN), cytokines, antibodies (such as trastuzumab (trastuzumab, HERCEPTIN®), T-DM1 , bevacizumab (bevacizumab, AVASTIN®), cetuximab (cetuximab, ERBITUX®), panitumumab (panitumumab, VECTIBIX®), rituximab (RITUXAN®) and bexa (tositumomab, BEXXAR®)), Anti-estrogen (anti-estrogen, such as tamoxifen (tamoxifen), raloxifene (raloxifene) and megestrol (megestrol)), luteinizing hormone agonist (LHRH agonist, such as goserelin (goscrclin and leuprolide acetate), anti-androgen (such as flutamide and bicalutamide), photodynamic therapies, such as772734-ASB-016PC verteporfin (vertoporfin, BPD-MA), phthalocyanine, photosensitizer Pc4 (photosensitizer Pc4) and demethoxy-hypocrellin A, 2BA-2-DMHA), nitrogen mustard (nitrogen mustard, For example, cyclophosphamide, ifosfamide, trofosfamide, chlorambucil, estramustine and melphalan)), nitrosoureas (nitrosoureas, such as carmustine (BCNU) and lomustine (CCNU)), alkylsulphonates, such as busulfan and sulfan (treosulfan), triazene (such as dacarbazine and temozolomide), platinum containing compounds, such as cisplatin, carboplatin and oxaliplatin), vinca alkaloid, such as vincristine, vinblastine, vindesine, and vinorelbine, taxoid, such as paclitaxel or paclitaxel (Abraxane) bound to nanoparticle albumin, and Paclitaxel (DHA-paclitaxel, Taxoprexin) bound to docosahexaenoic acid, Paclitaxel bound to polyglutamic acid (PG-paclitaxel, paclitaxel poliglumex, CT-2103, XYOTAX), tumor activation prodrug ANG1005 (Angiopep-2 bound to three molecules of paclitaxel), paclitaxel-EC-1 (paclitaxel bound to the erbB2-recognizing peptide EC-1) and paclitaxel bound to glucose (e.g. etoposide, etoposide phosphate), Teniposide, topotecan, 9-aminocamptothecin, camptoirinotecan, irinotecan, crisnatol, and Mitomycin C and other paclitaxel equivalents), antimetabolites (anti-metabolite), dihydrofolate reductase inhibitors (DHFR inhibitors, such as methotrexate, methotrexate (dichloromethotrexate), trimetrexate and edatrexate), inosine-5'-monophosphate dehydrogenase inhibitors (IMP dehydrogenase inhibitors, such as mycophenolic acid, thiazofurin) tiazofurin, ribavirin and EICAR), ribonuclotide reductase inhibitors (such as hydroxyurea and deferoxamine), uracil analogs such as 5-fluorouracil (5-fluorouracil, 5- FU), floxuridine, doxifluridine, ratitrexed, tegafluorouracil (tegafur-uracil and capecitabine), cytosine analogs (such as cytarabine, araC or cytosine arabinoside and fludarabine), purine analogs (purine analog, such as mercaptopurine and Thioguanine), vitamin D3 analog (Vitamin D3 analog, such as EB 1089, CB 1093 and KH 1060), isoprenylation inhibitor, such as Lovastatin (lovastatin), dopaminergic neurotoxin (dopaminergic neurotoxin, such as 1-methyl-4-phenylpyridinium ion (1-methyl-4- phenylpyridinium ion)), cell cycle inhibitors (such as Staurosporium (Staurosporine), actinomycin (such as actinomycin D), bleomycin (such as bleomycin A2, bleomycin B2 and peplomycin), anthracycline, such as daunorubicin, doxorubicin, pegylated liposomal doxorubicin, idarubicin, epirubicin, pirarubicin, zorubicin and mitoxantrone), multidrug resistance inhibitors (MDR inhibitors, such as verapamil), calcium adenosine triphosphate Enzyme inhibitors (Ca2+ATPase inhibitor, such as thapsigargin), imatinib, thalidomide, lenalidomide, tyrosine kinase inhibitor (tyrosine kinase) inhibitor, such as axitinib (AG013736), bosutinib (SKI-606), nib (cediranib, RECENTINTM, AZD2171), dasatinib (SPRYCEL®, BMS-354825), erlotinib Erlotini b, TARCEVA®), gefitinib772734-ASB-016PC (IRESSA®), imatinib (Gleevec®, CGP57148B, STI-571 ), lapatinib (TYKERB®, TYVERB®), letatidine (Lestaurtinib, CEP-701 ), neratinib (HKI-272), nilo (nilotinib, TASIGNA®), masanib (semaxanib, semaxinib, SU5416), sunitinib (SUTENT®, SU11248), toceranib (PALLADIA®), vandetanib (ZACTIMA®, ZD6474), vatalanib (PTK787, PTK / ZK), trastuzumab (HERCEPTIN) ®), bevacizumab (AVASTIN®), rituximab (RITUXAN®), cetuximab (ERBITUX®), panitumumab (VECTIBIX®), blue Nizumab (ranibizumab, Lucentis®), nilo (nilotinib, TASIGNA®), sorafenib (NEXAVAR®), everolimus (AFINITOR®), alemtuzumab (CAMPATH®), gemtuzumab (ozogamicin, MYLOTARG®), sirolimus (temsirolimus, TORISEL®), ENMD-2076, PCI-32765, AC220, dovitinib lactate (TKI258, CHIR-258 ), BIBW2992 (TOVOKTM), SGX523, PF-04217903, PF-02341066, PF-299804, BMS-777607, ABT-869, MP470, BIBF 1120 (VARGATEF®), AP24534, JNJ-26483327, MGCD265, DCC-2036 , BMS-690154, CEP-11981 , Tivozanib (AV-951 ), OSI-930, MM-121 , XL-184, XL-647, and / or XL228), Proteasome inhibitors (for example, bortezomib (Velcade)), mammalian mTOR inhibitors (for example, rapamycin, temsirolimus, CCI-779), Everolimus (RAD-001 ), Rapamycin derivatives (ridaforolimus, AP23573, Ahad), AZD8055 (AstraZeneca), BEZ235 (Novartis), BGT226 (Norvartis), XL765 (Sanofi Aventis), PF- 4691502 (Pfizer), GDC0980 (Genetech), SF1126 (Semafoe) and OSI-027 (OSI)), oblimersen, gemcitabine, carminomycin, leucovorin, Pemetrexed, cyclophosphamide, dacarbazine, procarbazine, prednisolone, dexamethasone, camptotheca Base (campathecin), plicamycin , asparaginase, aminopterin, methotrexate (methopterin), porfiromycin, melphalan, Leurosidine, Leurosine, Chlorambucil, Trabectedin, Discodermolide, Carminomycin and Hexamethyl Melamine. Treatments for Breast Cancer

[0185] Treatment for breast cancer can include local treatments such as surgery (e.g., lumpectomy (breast-conserving surgery), mastectomy (partial or total removal of the breast), sentinel lymph node biopsy, axillary lymph node dissection, and / or radiation therapy (e.g., external beam radiation or brachytherapy (internal radiation)). Systemic treatments can be combined with local treatments or used without local treatments. Systemic treatments include chemotherapy such as alkylating agents (e.g., cyclophosphamide (Cytoxan) and thiotepa (Thioplex, Tepylute)), anthracyclines (e.g., doxorubicin (Adriamycin), epirubicin (Ellence), daunorubicin (Cerubidine, DaunoXome) mitoxantrone (Novantrone)), antimetabolites (e.g., fluorouracil (5-FU) (Adrucil), capecitabine (Xeloda), methotrexate (Trexall, Xatmep), gemcitabine (Gemzar, Infugem)), taxanes (e.g., paclitaxel (Taxol), docetaxel (Taxotere), albumin-bound paclitaxel (Abraxane)), epothilones (e.g., ixabepilone (Ixempra)), platinum-based772734-ASB-016PC chemotherapy drugs (e.g., carboplatin, cisplatin), antitumor antibiotics (e.g., mitomycin)), vinca alkaloids (e.g., vinblastine, vinorelbine). Combinations regimens can also be used to treat breast cancer (e.g., doxorubicin + cyclophosphamide; docetaxel + doxorubicin + cyclophosphamide; cyclophosphamide + methotrexate + 5-fu; docetaxel + cyclophosphamide; paclitaxel + carboplatin). Hormone therapy (e.g., tamoxifen; aromatase inhibitors (letrozole, anastrozole, exemestane); and ovarian suppression (e.g., with LHRH agonists)) can be used to treat breast cancer. Targeted therapy (e.g., HER2-targeted drugs (trastuzumab, pertuzumab); CDK4 / 6 inhibitors (palbociclib, ribociclib); PARR inhibitors (olaparib, talazoparib)) can be used to treat breast cancer. Other breast cancer treatments include immunotherapy (e.g., checkpoint inhibitors (e.g., pembrolizumab for certain triple-negative breast cancers); immune checkpoint inhibitors (e.g., embrolizumab (Keytruda), dostarlimab (Jemperli)). Adoptive cell therapy (CAR-T) can also be used to treat breast cancer.Methods of Monitoring Treatment in a Patient

[0186] In some aspects, the methods described herein can be used to generate unique signatures for a patient. For example, an EV-derived protein sample from a patient can be analyzed and compared to an EV-derived protein sample from the same patient at a different time point, e.g., after cancer treatment.

[0187] In some aspects, patients with the same type of cancer can have different expression patterns of these unique proteins. This information can be used as a companion diagnostic to help guide therapy decision making for clinicians to their patients. This information can also be used as discovery approach to identify other protein targets of interest that indicate, for example, resistance to current treatment and help guide the next therapy.

[0188] Therefore, in an aspect, a method of proteomic analysis of EV-derived protein samples from cancer patients is provided. The method can comprise obtaining an EV-derived protein sample from a cancer patient and obtaining an EV-derived protein sample from a healthy patient; digesting the EV-derived proteins from the first unhealthy patient and the second healthy patient to prepare a population of sample peptides from the first unhealthy patient and the second healthy patient. Mass spectrometry can be performed on the first and second digested protein samples to analyze the EV-derived proteins from the first unhealthy patient and the second healthy patient. The mass spectrometry data can be analyzed to identify a proteome analysis of the first unhealthy patient and the second healthy patient. These can be compared to identify unique protein expression in the unhealthy patient. Alternatively, the healthy patient data can be772734-ASB-016PC previously collected and stored for comparison to the cancer patient. In an aspect, healthy patient data can be collected from 100, 200, 300, 400, 500, 600, 700 or more healthy patients.

[0189] In an aspect, a blood sample can be collected from a subject and contacted with a solid support functionalized to bind extracellular vesicles in the blood sample. The solid support comprising bound extracellular vesicles can be isolated. The bound extracellular vesicles can be lysed to form a protein sample. The protein sample can be contacted with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample. Mass spectrometry can be performed on the EV derived protein sample and mass spectrometry data collected. The mass spectrometry data is compared to reference data. Mass spectrometry can be performed on the EV derived protein sample and mass spectrometry data collected. The mass spectrometry data can be compared to reference data. A subject is identified as having cancer if the levels or amounts of at least one (e.g., 1 , 2, 3, 4, 5, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more) biomarker differs from the reference data. Biomarkers here mean individual biomarkers or pathways.

[0190] These steps can be repeated at different time points (e.g., times that are 1 week, 1 month, 3 months, 6 months, 1 year or more apart). The mass spectrometry data from the two time points can be comparted. The time points may be before and after one or more treatments. A subject is identified as having cancer if the levels or amounts of at least one (e.g., 1 , 2, 3, 4, 5, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more) biomarker differs from the reference data. Biomarkers here mean individual biomarkers or pathways.

[0191] In an aspect, a library of expressed proteins from one or more healthy patients is used for comparison instead of a healthy patient EV-derived protein sample.

[0192] In an aspect, treatment can be adjusted based on the results. For example if the biomarkers or pathways indicate that the cancer is still present then the dose of an anti-cancer agent therapy or treatment can be adjusted; an additional anti-cancer agent therapy or treatment can be added; and / or the specific anti-cancer agent therapy or treatment can be changed. If the biomarkers or pathways indicate that the cancer is not present then the anti-cancer agent therapy or treatment can be ceased.

[0193] The method can further comprise reacting the sample peptides with a tandem mass tag (TMT) reagent to prepare TMT-labeled sample peptides. The TMT reagent can be selected from the group consisting of Aminoxy-TMT, Glyco-TMT, iodo- TMT, and TMT pro. Other tags such as dimethyl, diethyl, SI LAC (Stable Isotope Labeling772734-ASB-016PC by Amino acids in Cell culture), ICPL (Isotope-Coded Protein Labeling), 180 digestion, ICAT (Isotope-Coded Affinity Tags), or similar can also be used. Digesting the extracted proteins can comprise a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu- C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof.

[0194] In an aspect proteomic analysis can be combined with risk factors to further enhance specificity and sensitivity of testing. For example, risk factors known to increase the chances of breast cancer include age, family history of breast cancer, genetic mutations like BRCA1 and BRCA2, dense breasts, early menstruation, late menopause, having a first child later in life, not breastfeeding, being overweight or obese, excessive alcohol consumption, lack of physical activity, exposure to radiation to the chest, and a personal history of breast cancer. Therefore, if a patient has 1 , 2, 3, 4, 5, or more risk factors, this information can be combined with the proteomic results to achieve an improved result.

[0195] In some aspects, the methods advantageously require only the use of small amount of blood from a patient. In some aspects, since the amount of blood required for testing is so small, a subject can self-sample the blood. For example, a subject could draw their own blood via capillary sampling. In an aspect, only about 1 ,000, 750, 500, 400, 300, 200, 250, 100, 50 L or less of blood is required.Methods for Reducing Cancer Imaging

[0196] In an aspect, methods for reducing cancer imaging that is necessary in a group of subjects to be screened for cancer are provided. In an aspect, the amount of imaging is reduced as compared to methods of detection of cancer that do not comprise the instant methods of detection of cancer. In another aspect, the amount of imaging can be reduced as compared to liquid biopsies for circulating tumor DNA (ctDNA) or circulating tumor cells (CTCs), tumor marker tests (e.g., prostate-specific antigen (PSA), CA-125, alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA)), complete blood count (CBC), or biopsies. The amount of imaging can be reduced by about 3, 5, 10, 15, 20% or more.

[0197] Methods provided herein can reduce the number of false positives by reducing the amount of imaging tests for cancer. For example, methods can reduce the number of subjects that need to be imaged for cancer by about 5, 10, 20, 30, 40, 50 % or more.772734-ASB-016PC

[0198] In an aspect, methods can comprise contacting a blood sample from each of the subjects, for example a group of 5, 10, 50, 100, 500 or more subjects, with a solid support functionalized to bind extracellular vesicles in the blood sample; isolating the solid support comprising bound extracellular vesicles; lysing the bound extracellular vesicles to form a protein sample; contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; and comparing the mass spectrometry data to reference data. In an aspect, a subject of the group is identified as not having cancer if the levels or amounts of biomarkers do not significantly differ from healthy reference data. In an aspect, a subject is identified as having cancer if the levels or amounts of at least one biomarker differs significantly from the healthy reference data. The healthy reference data can be obtained from one or more subjects (e.g., 100, 200, 300, 400, 500, 600, 700 or more) that do not have cancer. Imaging is performed only for the subjects identified as having cancer to determine the location of a primary tumor cells or lesion, determine metastatic spread, or determine tumor recurrence. The amount of imaging is reduced in the group of subjects as compared to a group of subjects diagnosed with mammography, Contrast-Enhanced Mammography (CEM), ultrasound, and / or breast MRI. The amount of imaging can be reduced by about 3, 5, 10, 15, 20% or more. The amount of imaging for the subject pool is therefore reduced since part of the group will not be subjected to imaging.

[0199] The compositions and methods are more particularly described below and the Examples set forth herein are intended as illustrative only, as numerous modifications and variations therein will be apparent to those skilled in the art. The terms used in the specification generally have their ordinary meanings in the art, within the context of the compositions and methods described herein, and in the specific context where each term is used. Some terms have been more specifically defined herein to provide additional guidance to the practitioner regarding the description of the compositions and methods.

[0200] As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items. As used in the description herein and throughout the claims that follow, the meaning of “a”, “an”, and “the” includes plural reference as well as the singular reference unless the context clearly dictates otherwise. The term “about” in association with a numerical value means that the value varies up or down by 5%. For example, for a value of about 100, means 95 to 105 (or any value between 95 and 105).772734-ASB-016PC

[0201] All patents, patent applications, and other scientific or technical writings referred to anywhere herein are incorporated by reference herein in their entirety. The aspects illustratively described herein suitably can be practiced in the absence of any element or elements, limitation or limitations that are specifically or not specifically disclosed herein. Thus, for example, in each instance herein any of the terms "comprising," "consisting essentially of," and "consisting of" can be replaced with either of the other two terms, while retaining their ordinary meanings. The terms and expressions which have been employed are used as terms of description and not of limitation, and there is no intention that in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the claims. Thus, it should be understood that although the present methods and compositions have been specifically disclosed by aspects and optional features, modifications and variations of the concepts herein disclosed can be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of the compositions and methods as defined by the description and the appended claims.

[0202] Any single term, single element, single phrase, group of terms, group of phrases, or group of elements described herein can each be specifically excluded from the claims.

[0203] Whenever a range is given in the specification, for example, a temperature range, a time range, a composition, or concentration range, all intermediate ranges and subranges, as well as all individual values included in the ranges given are intended to be included in the disclosure. It will be understood that any subranges or individual values in a range or subrange that are included in the description herein can be excluded from the aspects herein. It will be understood that any elements or steps that are included in the description herein can be excluded from the claimed compositions or methods.

[0204] In addition, where features or aspects of the compositions and methods are described in terms of Markush groups or other grouping of alternatives, those skilled in the art will recognize that the compositions and methods are also thereby described in terms of any individual member or subgroup of members of the Markush group or other group.

[0205] The following are provided for exemplification purposes only and are not intended to limit the scope of the aspects described in broad terms above.772734-ASB-016PCEXAMPLESExample 1 : Multi-modal detection platform

[0206] Cancer cells disseminate into the vasculature at an early stage, seeding metastatic sites in breast cancer. These early-stage tumor cells that extravasate and lodge at metastatic sites can enter dormancy, marking a potential source of late recurrence and therapy resistance. Thus, the presence of early disseminated cells poses risks to patients but also enables early detection and provides opportunities for targeted curative interventions. We evaluated this in a cohort of women with newly diagnosed early-stage breast cancer (Stage 0 - 2).

[0207] A multi-modal liquid biopsy platform that combines 3D holographic signatures of the morphology of peripheral blood cells with deep proteomic profiling from the same sample was used. The platform employs enrichment techniques to ensure high cell recovery and proteome accuracy. See US Pat. Publ. US 2021-0237064 A1 , PCT / US24 / 55191 , and PCT / US24 / 55244, incorporated herein by reference in their entireties.Patients• 335 participants o Breast Cancer Classification■ 116 women with newly diagnosed and untreated Stage 0-2 breast cancer• Stage 0 (n=30)• Stage 1 (n=72)• Stage 2 (n= 14)■ 219 healthy controls o Breast Density Distribution in the cancer patients■ High (n=41 )■ Low (n=39)■ Not specified (n=36)Deep Proteomic Profiling

[0208] At the same time, extensive proteomic profiling maps the expression of 3,000+ proteins against established oncogenic pathways. This innovative multi-modal analysis provides a highly accurate classifier for distinguishing cancer from healthy772734-ASB-016PC patients and uncovers critical insights into oncogenic pathways, paving the way for personalized treatment strategies tailored to each cancer patient.(Table 1).Table 1 : Proteomics of Breast Cancer Cells772734-ASB-016PC772734-ASB-016PC772734-ASB-016PC772734-ASB-016PC772734-ASB-016PC772734-ASB-016PC772734-ASB-016PC

[0209] The interim findings from 94 participants, comprising 47 women with newly diagnosed and untreated Stage 0-2 [stage 0 (n=14), I (n=23), II (n=8) and 2 not reported] breast cancer and 47 healthy controls, underscore the groundbreaking potential of this multi-modal liquid biopsy platform. Breast density distribution in the cancer patients was A (n=0), B (n=11 ), C (n=33), D (n=2) and 1 not reported. The results here provide clear evidence of early dissemination in the majority of breast cancer patients and demonstrate the platform’s ability to sensitively detect and identify the expression of cancer-associated pathways — such as KRAS-Breast, WNT signaling, LEF1 , and EMT in the earliest stages (FIG. 3, 4).Example 2.

[0210] Despite the widespread use of mammography as the standard of care for breast cancer screening, its accuracy remains limited for select patient populations, such as women with high breast density. Liquid biopsy-based tests offer an accessible complement to conventional screening methods. Here, we screened the plasma proteome of women with early-stage breast cancer and developed a protein-based classifier to distinguish between healthy and diseased patients. A cohort of 335 women, comprising 116 patients with newly diagnosed, treatment naive breast cancer (Stage 0- 2) and 219 healthy controls, had plasma samples collected and processed in a blinded manner using a sample preparation method as described herein coupled with semi- quantitative, label-free mass spectrometry (MS)-based analysis. The median number of772734-ASB-016PC proteins detected per patient across breast cancer and healthy individuals was 6,991 and 6,818, respectively. A machine learning-based classifier was trained and validated on patient proteome profiles using a leave-one-out cross-validation (LOOCV) approach to identify breast cancer patients. The classifier achieved an AUC of 0.96 (95% Cl: 0.93- 0.97), with a sensitivity of 86.2% (95% Cl: 78.8-91.3%) and a specificity of 90.4% (95% Cl: 85.8-93.6%). In breast cancer patients, the classifier retained >85% sensitivity regardless of breast density (low density: 87.2%, high density: 90.2%) at 90% specificity. Our workflow demonstrates the potential of plasma proteomics as a potent diagnostic tool in early-stage breast cancer screening.

[0211] Breast cancer patient survival improves drastically when detected early, with many localized cases being curative with surgical intervention

[0001] , Mammography remains the gold standard in breast cancer detection, with biennial screenings recommended by the U.S. Preventive Services Task Force (USPSTF) for women starting at age 40. However, inconsistencies in mammographic detection, particularly in women with dense breast tissue, can lead to inaccurate diagnosis [2], Approximately 50% of women above the age of 40 have dense breast tissue (defined as Bl RADS C and D), and women with dense breasts have a higher risk of developing breast cancer [3], While alternative imaging methods, such as MRI, digital breast tomosynthesis (or 3D mammography), contrast enhanced mammography (CEM), and ultrasonography are available, there is no clear consensus on guidelines for their use in patients with high breast tissue density who do not meet other “high risk" criteria [4], [5], Consequently, these tests are often not covered by insurance for the general population, leading to broad inaccessibility and high out-of-pocket costs. Hence, there is a strong need for diagnostic tests capable of detecting early-stage breast cancer that are both sensitive and accessible to the public.

[0212] Liquid biopsies have the potential to vastly improve the accessibility of early cancer detection. These tests screen biological fluids, such as blood, sampled through standard medical procedures for various cancer analytes, including cell free DNA (cfDNA), circulating tumor DNA (ctDNA), microRNAs, orphan non-coding RNAs (oncRNAs), and proteins [6], There are currently no FDA approved liquid biopsy tests to detect early-stage breast cancer. Galleri, a multi-cancer detection assay developed by GRAIL, is a commercially available blood test that screens patients using targeted methylation analysis of ctDNA [7], While the specificity of this assay is high (>99%), the sensitivity for early-stage breast cancer detection is low (2.6%-47.5% for stage 1 and 2 patients, respectively) [8], likely due to the low shedding rate of ctDNA in early-stage772734-ASB-016PC cancers [9], Several protein biomarkers have been approved by the FDA for treatment monitoring in breast cancer, including CA 15-3, CA 27-29, and carcinoembryonic antigen (CEA). However, they lack sufficient sensitivity and specificity for early detection

[0010] , More sensitive technologies will be required to explore the full proteomic landscape in early-stage breast cancer.

[0213] The plasma proteome is highly complex, estimated to contain over 10,000 unique proteins ranging more than 10 orders of magnitude in abundance

[0011] , A subset of these targets is heavily overrepresented in plasma, limiting the detection of low abundance proteins

[0012] , Liquid chromatography-tandem mass spectrometry (LC- MS / MS, hereafter referred to as MS in this example) is an unbiased method of protein quantification capable of identifying a wide range of proteins. These techniques often generate complex datasets, comprising thousands of peptide fragments correlated to hundreds of proteins or more. Consequently, studies aimed at disease detection tend to focus on select panels of differentially expressed proteins, which may not capture the intricacies of the proteomic landscape and lead to diagnostic inaccuracies

[0015] ,

[0214] Here, we present a liquid biopsy-based proteomics workflow for early-stage breast cancer detection aimed at overcoming the current limitations of low specificity in this setting while achieving high sensitivity. Sample preparation workflow combines protein enrichment with semi-quantitative, label-free MS-based analysis to enhance the dynamic range of proteins detected within each sample. Raw MS profiles are processed using a breast cancer-focused, spectral library to quantify greater than 6,500 proteins per patient on average. We trained a protein-based machine learning classifier to identify patients with early-stage breast cancer. This unbiased approach to protein analysis incorporates a large proportion of the detected proteome within each patient, expanding the total number of proteins used for diagnostic assessment. Collectively, this study demonstrates a streamlined, high-throughput workflow for early-stage breast cancer detection while addressing several key limitations with modern proteome analysis.Materials and Methods:Sample Acquisition and Processing

[0215] This was a case-control, observational study. Early-stage breast cancer patients were recruited as part of a local study at Allina Health Cancer Institute (Minneapolis, MN) and sourced from iSpecimen (Woburn, MA). Women over the age of 18 were eligible for inclusion in this study if they were 1 ) treatment naive with 2) no prior history of cancer and 3) had a confirmed diagnosis of stage 0-2 breast cancer based on histopathological analysis. Healthy women donors were recruited at Astrin Biosciences772734-ASB-016PC (Saint Paul, MN) and sourced from iSpecimen and ZenBio (Durham, NC). Healthy women donors aged 18-74 were considered eligible if they had 1 ) no prior history of cancer and 2) had no first-degree relatives with a history of breast cancer. The studies were approved by the WCG Institutional Review Board and all participants provided written informed consent.

[0216] Whole blood was collected into EDTA tubes and shipped overnight before being double-spun for plasma isolation. The supernatant was transferred to a fresh conical each time before being aliquoted and stored at -80°C. Previously un-thawed plasma aliquots were then loaded into a Microlab Prep (Hamilton) robot liquid handler along with process and digestion controls, and positive and negative controls comprising pooled cancer patient and healthy plasma, respectively. Functionalized superparamagnetic bead solutions were added to each sample to allow for preferential protein capture while leaving behind contaminating high abundance proteins. In parallel to protein capture, incubation, wash, and lysis plates were created. These optimized buffers serve to assist in depleting weakly and non-specifically adhered proteins and to fully denature, reduce, and alkylate the proteins. The deep-well plate along with wash and lysis plates were transferred to a Kingfisher Flex (Thermo Fisher) that performed a series of gentle washes followed by heated lysis on a heated shaker. Using the Microlab Prep, the samples were transferred to a 96 well LoBinding plate (Eppendorf, 0030129512) for all subsequent steps. A protein recapture buffer was then added to promote optimal protein recovery. Following a series of wash buffer exchanges, the samples were transferred into a digestion buffer (pH 8.0) and digested with Lys-C and Trypsin overnight. The next morning, the beads were removed, and the peptide- containing supernatant was transferred and dried down on a vacuum concentrator (Labconco).Peptide Quantification and Mass Spectrometry Parameters

[0217] Peptides were resuspended and quantified using a quantitative fluorometric peptide assay (Thermo Fisher, 23290) to normalize peptide quantities prior to loading onto EvoTips (EvoSep, EV2011). EvoTips were prepared as directed by the manufacturer with the exception that all volumes used were doubled. Samples were then analyzed on an Orbitrap Astral (Thermo Fisher) coupled to an EvoSep One (EvoSep) running a whisper zoom 40 SPD method with a 15 cm Ion Opticks column (AUR3- 15075C18-XT) and set to 1 ,800 V. The Astral was run with default parameters from the Label Free Quantification using Data Independent Acquisition (LFQ DIA) preset with 3 Th windows.772734-ASB-016PCMass Spectrometry Data Analysis

[0218] A spectral library was generated using a subset of patient samples. All results were generated from DIA-NN (2.1.0) with the following settings: Maximum mass accuracy fixed to 11 and 10 ppm (MS1 and MS2 respectively), scan window of 7, trypsin / P, missed cleavages 1 , peptide length between 7 and 30, carbamidomethylation as a fixed modification, up to one variable modification of methionine oxidation or N- terminal acetylation, and 1 % FDR. A random subset of 100 patient samples was designated as "normalizing samples" for protein quantification. QuantUMS parameters were trained on these 100 samples and fixed for subsequent analysis

[0019] , The remaining samples were each processed in independent DIA-NN sessions alongside all 100 normalizing samples (i.e. total of 101 samples) to obtain the MaxLFQ-normalized quantifications

[0020] ,

[0219] The gene group-level abundance data from DIA-NN was preprocessed as follows. Razor peptides were assigned to the most likely corresponding gene, and abundances were aggregated by summing values across unique genes, treating missing values as zero during aggregation. Non-missing abundances were log-transformed, and any remaining missing values were imputed using the minimum observed abundance for each gene symbol minus one. Finally, the abundances were standardized by gene (zero mean and unit variance) to generate features suitable for machine learning classification models.Statistical Analysis to Develop a Cancer Classifier

[0220] We used logistic regression with L1 regularization (Lasso, least absolute shrinkage and selection operator) to classify breast cancer patients from healthy controls. We employed a leave-one-out cross-validation (LOOCV) strategy for model validation, i.e., for each sample a model was trained excluding the held-out sample, and prediction probabilities were obtained on that sample. Classification performance metrics were then computed by aggregating prediction outcomes across all samples. All data preprocessing steps, including missing value imputation and normalization, were performed within each LOOCV fold using only the training data and then applied to the held-out sample. Additionally, the Lasso penalization parameter was tuned within each LOOCV fold using a nested 5-fold cross-validation on the training set. All data analysis was performed using Python 3.12.4; the model was trained using the scikit-learn library (version 1 .4.2).772734-ASB-016PCTable 2. Summary of patient demographics between breast cancer and healthy control cohorts.772734-ASB-016PCResults:Proteomic analysis of the patient cohort

[0221] A total of 335 women were recruited for this study, including 116 newly diagnosed, treatment naive Stage 0-2 breast cancer patients (stage 0: n = 30, I: n = 72, II: n = 14) and 219 healthy controls. The patient demographics are summarized in Table 2. The median age (Q1-Q3) in the cancer and non-cancer groups were 64 (52-70) and 32 (25-34), respectively. The racial demographics between the breast cancer and healthy control groups were roughly equivalent, with a larger proportion of white individuals in the breast cancer group relative to the healthy control group (84.5% vs 70.8%, respectively). Blood samples were de-identified and blinded before processing with Astrin’s proprietary sample preparation workflow (Figure 1A). All MS files were mapped using Astrin’s breast cancer-focused spectral library to identify and quantify proteome profiles.

[0222] The median (Q1-Q3) number of proteins detected between cancer and healthy control groups were 6,991 (6,735-7,140) and 6,818 (6,499-7,100) proteins, respectively, with 9,030 unique proteins observed across both cohorts. Samples across the well plates were randomized to reduce plate specific effects on protein identification. Inspection of the number of proteins identified by well-plate showed no discernible patterns (Figure 1 B) across groups, suggesting the absence of plate-based interactions. Most patients had more than 6,500 proteins detected per sample (78.2%, 262 / 335), demonstrating both the consistency of our sample preparation and the sensitivity of our MS method (Figure 1 C). Quantitative assessment of protein intensities showed that we captured a dynamic range of protein abundances spanning over 8 orders of magnitude, highlighting the workflow’s potential to capture low abundance protein fractions (Figure 5).Protein-based classification of disease status

[0223] To aid in the interpretation of the quantified plasma proteins and identify patients with early-stage breast cancer, we trained a machine learning classifier on patient proteome profiles to distinguish between cancer and healthy individuals. The protein-based classifier achieved an AUG of 0.96 (95% Bootstrap Cl: 0.93-0.97) in differentiating between early-stage breast cancer patients and healthy individuals. A Receiver operating curve (ROC) showed strong discriminative performance, demonstrating the model's accuracy for early-stage breast cancer prediction (Figure 2A). Across all patients, the model achieved a sensitivity of 86.2% (95% Wilson Cl: 78.8- 91.3%) with a specificity of 90.4% (95% Wilson Cl: 85.8-93.6%) (Figure 2B). We also772734-ASB-016PC evaluated the model on all individuals within the LISPSTF recommended screening age for breast cancer (40-74, n = 167). The differences in the sensitivity and specificity between the total cohort and the age-adjusted cohort were not statistically significant, with only a small decrease in specificity observed (sensitivity: 86.2% vs 86.0% (Two- sided Z-test p-value: 0.97); specificity: 90.4% vs 86.6% (Two-sided Z-test p-value: 0.37)) (Figure 6).

[0224] To emphasize this workflow’s potential as a diagnostic tool for women with dense breasts, we evaluated differences in the model’s accuracy based on breast density. For breast cancer patients with both low (BI-RADS A / B) and high (BI-RADS C / D) breast densities, the model maintains a sensitivity of greater than 85% across both groups (low density: 87.2% (73.3%-94.4%), high density: 90.2% (77.5%-96.1 %)) at a set specificity of 90.4% (Figure 2C).Discussion:

[0225] Liquid biopsy-based proteomics holds the potential to advance the sensitivity of early-stage cancer detection, leading to increased diagnosis in patient populations where conventional screening methods are insufficient. Despite the surge of interest in liquid biopsies over the past decade for their application in treatment monitoring and molecular residual disease (MRD) detection, their use as a diagnostic tool remains limited. There are limited results, however, for the detection of early-stage breast cancer. Other early cancer detection tests have sought to combine multiple cancer analytes in the hopes of increasing diagnostic accuracy. The CancerSEEK assay, which combines targeted mutational analysis of ctDNA with the quantification of select protein biomarkers, showed strong results for certain cancer types, but reported poor sensitivity for breast cancer (33%)

[0023] , In this study, we aim to overcome these limitations by developing an accessible, proteomic-based liquid biopsy specifically for early-stage breast cancer detection.

[0226] Here, we captured a median of over 6,500 proteins per patient using our MSbased analysis in both cancer and non-cancer individuals. Compared to other high throughput methods, the depth of our results highlights the strength of our analysis workflow and underscores our potential to screen for low abundant proteins within the plasma proteome.

[0227] We designed a novel DIA analysis normalization pipeline to ensure we could process samples in a robust and computation-efficient manner. By normalizing each sample to a set of 100 “normalizing samples”, we ensured that the protein abundance quantifications were directly comparable across samples, making them ideal for a772734-ASB-016PC downstream machine learning pipeline. To validate the efficacy of this approach, we aimed to understand the marginal effect of adding one extra sample to the normalization set. We randomly selected four normalization subsets consisting of 10, 20, 50, and 100 samples, respectively. For each subset, one additional randomly chosen sample was added, and MaxLFQ-normalized protein group (PG) abundance values were calculated. This process was repeated three times for each normalization subset. The results demonstrated that the stability of protein quantification increases with the size of the normalization set, with minimal impact from the addition of a single sample at larger subset sizes (Figure 7). This strategy allows us to process future samples independently using the precomputed protein quantifications of the normalizing samples via MaxLFQ without having to rerun the DI A analysis on the entire dataset.

[0228] To encapsulate information from the full range of proteins identified in this study, we trained a logistic regression classifier with L1 regularization to detect early- stage breast cancer based on patient proteome profiles. This approach simultaneously regularizes the classifier to improve prediction accuracy while performing variable selection by shrinking the coefficients of less informative proteins to zero. Given a relatively limited sample size, we used a LOOCV approach to obtain nearly unbiased estimates of the performance metrics. Recent studies have also explored the potential of MS-based plasma proteomics in early-stage breast cancer detection

[0027] ,

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[0020] J. Cox, M. Y. Hein, C. A. Luber, I. Paron, N. Nagaraj, and M. Mann, ‘Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal772734-ASB-016PCPeptide Ratio Extraction, Termed MaxLFQ’, Molecular & Cellular Proteomics, vol. 13, no. 9, pp. 2513-2526, Sep. 2014, doi: 10.1074 / mcp.M113.031591 .

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[0028] C. Fredolini et al., ‘Shotgun proteomics coupled to nanoparticle-based biomarker enrichment reveals a novel panel of extracellular matrix proteins as candidate serum protein biomarkers for early-stage breast cancer detection’, Breast Cancer Research, vol. 22, no. 1 , p. 135, Dec. 2020, doi: 10.1186 / s13058-020-01373-9.Example 3Summary

[0229] We analyzed the plasma proteome of 1 ,259 biobanked samples from healthy women and women with breast cancer. A protein-based machine learning classifier was used to identify breast cancer with high accuracy. The classifier was trained on 845 women, comprising of 466 healthy and 379 with newly diagnosed, treatment naive breast cancer and validated on 397 women (195 healthy and 202 breast cancer). All plasma samples were processed in a blinded manner coupled with semi-quantitative, label-free mass spectrometry (MS)-based analysis. The validation performance achieved 92.3% specificity, 92.6% sensitivity and an AUG of 0.975. Sensitivity remained high across all breast cancer stages and pathological and molecular subtypes. Gene set enrichment analyses (GSEA) identified epithelial-to-mesenchymal transition (EMT) and PI3K-AKT signaling as enriched in the breast cancer samples, highlighting that our test can identify cancer-related proteins in early-stage patients. A simulated population demonstrates the utility of our test as a supplement to mammography, detecting nearly all (93%) breast772734-ASB-016PC cancers missed by mammography and reducing the number of false positives relative to MRI and Contrast-Enhanced Mammography (CEM) by >10-fold. Overall, our proteomic data demonstrates high sensitivity and specificity in women with breast cancer, especially at early stages, and is a favorable supplemental test post mammogram.

[0230] Here, we assessed a large cohort of biobanked samples from 1 ,259 women to detect breast cancer as early as stage 0 through deep proteomic profiling via MS. We have further refined and validated our automated processing pipeline to continuously prepare and analyze hundreds of plasma samples with low sample error rates and high reproducibility while obtaining sensitivities near 90% across all stages of breast cancer using our proprietary spectral library with an improved machine learning algorithm. While this workflow is currently used for breast cancer detection, this pipeline can be broadly adapted to other types of cancer and diseases.Materials and Methods:Sex as a Biological Variable

[0231] Our study examined female subjects only since >99% of breast cancer cases are in females.Sample Acquisition and Processing

[0232] Breast cancer and healthy plasma samples were purchased from two different biobanks (ProteoGenex and BiolVT) and shipped frozen to Astrin Biosciences. Cancer samples were selected based on the following criteria: 1 ) treatment naive, 2) no prior history of cancer, and 3) a confirmed diagnosis of breast cancer based on histopathological analysis of subsequent biopsy or resected tissue samples. Healthy female donors were selected to create an age-matched population.

[0233] Samples were prepared as described in Example 1. Briefly, plasma aliquots were loaded onto a Microlab Prep (Hamilton) robot liquid handler along with process and digestion controls and positive and negative controls comprising pooled breast cancer and healthy patient plasma, respectively. A functionalized superparamagnetic bead solution was added to allow for preferential protein capture while leaving behind contaminating high abundance proteins. The sample plate along with wash and lysis plates were transferred to a Kingfisher Flex (Thermo Fisher) which performed a series of washes ending with sample lysis on a heated shaker. Using the Microlab Prep, the samples were transferred to a 96-well LoBinding plate (Eppendorf, 0030129512) for all subsequent sample steps. A protein recapture buffer was then added to promote protein recovery followed by a series of buffer exchanges ending with digestion buffer (pH 8.0)772734-ASB-016PC and digested with Lys-C and trypsin overnight. The next morning, the peptide-containing supernatant was removed and dried on a vacuum concentrator (Labconco).

[0234] For plate and mass spectrometry controls, we purchased enolase (Waters), HeLa lysates (Thermo Fisher), and nine different positive and negative controls from a biobanked source. The positive and negative controls were pooled to create a common sample source to assess performance on a plate-by-plate basis. Multiple blank controls were also included with each plate to test both for sample carryover and any contamination throughout the sample processing.Characterization of breast cancer molecular subtypes

[0235] Typical subtyping requires pathology reports that include ER / PR / HER2 expression, proliferation information via Ki-67, and histopathology of the tumor. We used the following characterization based on available information shared to us from each biobank on the reporting of hormone status. HER2 was considered positive with staining intensity of 3+: Hormone receptor positive (i.e. estrogen receptor or progesterone receptor) (HR+) and HER2 positive (HER2+); HR+ and HER2 negative (HER2-); HR negative (HR-) and HER2+; and HR- and HER2-.Peptide Quantification and Mass Spectrometry Parameters

[0236] Prepared peptides were resuspended in 0.1 % formic acid in water and quantified using a quantitative fluorometric peptide assay (Thermo Fisher, 23290). EvoTips were prepared as directed by the manufacturer with the exception that solvent volumes were doubled. Samples were analyzed on an Orbitrap Astral mass spectrometer (Thermo Fisher) coupled to an EvoSep One liquid chromatography (LC) system (EvoSep) running the whisper zoom 40 SPD with an Ion Opticks column (AUR3- 15075C18-XT) set to 1 ,600 V and default parameters from the Label Free Quantification using Data Independent Acquisition (LFQ DIA) preset with 3 Th windows.Mass Spectrometry Data Analysis

[0237] Running in data-independent acquisition (DIA) mode, the Orbitrap Astral produces raw mass spectra from which peptide quantities can be computed based on a spectral library. Peptide quantities are then analyzed to produce gene group abundance data that are ultimately used for the classifier. The spectral library used herein was generated from an independent set of 280 patient samples consisting of individuals with breast cancer and healthy controls as described in Example 1 . All peptide quantification and gene group abundance data were generated from DIA-NN (2.1.0) with default parameters except for the following settings: Maximum mass accuracy fixed to 11 and 10 ppm (MS1 and MS2 respectively), scan window of 7, up to one variable modification772734-ASB-016PC of methionine oxidation or N-terminal acetylation. A random subset of 100 patient samples used for spectral library generation was designated as "normalizing samples" for protein quantification. QuantUMS parameters were trained on these 100 samples and fixed for subsequent analysis14. The samples were each processed in independent DIA- NN sessions alongside all 100 normalizing samples (i.e. total of 101 samples) to obtain the MaxLFQ-normalized quantifications15.

[0238] The gene group-level abundance data from DIA-NN was preprocessed as follows. Non-missing abundances were log-transformed, and any remaining missing values were imputed using the minimum observed abundance for each gene-group minus one. Finally, the abundances were standardized by gene-group (zero mean and unit variance) to generate features suitable for machine learning classification models.

[0239] We developed QC metrics for both the plate level and the individual sample level. At the plate level, we evaluated mass spectrometry controls that included commercial enolase standards for retention time and total precursor ion intensity, commercial HeLa cell lysates were evaluated for peptide and protein IDs and selected peptides were assessed for consistent abundance values across the plates, and blank injections were added to compare total ion chromatograms (TIC) between blank and patient samples. Processing controls, commercial yeast lysates, and positive and negative controls were analyzed to ensure all sample processing steps were sufficiently completed. At the sample level, we required that each sample meet minimum peptide and protein IDs. Plates or samples not meeting these QC thresholds were re-ran. Two unsuccessful runs of the same sample resulted in discarding that sample.Reproducibility and Repeatability Analysis

[0240] For reproducibility experiments, two different operators ran the same samples from 8 donors (4 healthy and 4 breast cancer) over two different days. For repeatability experiments, the first operator ran samples from 4 donors (2 healthy and 2 breast cancer) in triplicate across three different plates, while a second operator ran a different set of samples from 4 donors (2 healthy and 2 breast cancer) in triplicate on a single plate. In total, 16 donors were run for reproducibility, and 24 donors were run for repeatability. Performance of each sample was assessed where each of the samples was classified as healthy or breast cancer. If the same sample was classified correctly across operators or days, then the sample was positive. If the samples were classified differently across operators or days, then the sample was negative.Training and Validation Split772734-ASB-016PC

[0241] We randomly assigned 845 of the samples to the training portion and the remaining 397 samples were assigned to the validation portion (a roughly 70:30 split), where their clinical information was blinded from sample preparation and analysis. Validation samples were batched separately from training samples to mimic real world situations around sample acquisition for an early detection test. Any samples that did not pass QC were removed from the analysis.Machine learning and cross-validation analysis

[0242] To avoid the potential of confounding by source, we implemented an Exponentiated Gradient method16, ensembling L2-norm regularized logistic regression, with the constraint of demographic parity across two sources. The default parameters in fairlearn library were used. To make predictions as part of cross-validation and to assess performance on the holdout validation, predictions of each component logistic regression were weighted according to the model weights estimated by the Exponentiated Gradient method. Source was treated as a sensitive feature.

[0243] We performed five-fold cross-validation of this model to assess the performance of our assay in distinguishing breast cancer from healthy samples in the training portion. At each iteration of the cross-validation, the data pre-processing described above was learned without the heldout fold, and the learned statistics were then applied to the heldout fold. The lambda parameter (strength of L2 regularization) was tuned by performing nested cross-validation (five folds) and selecting the parameter which maximized accuracy. A threshold for >90% specificity was determined using the outer-fold cross-validated predictions in healthy samples. The model was then trained on all of the training data, using the most frequently selected lambda from the previous step, and predictions were made on the validation samples. Validation samples were called positive if the predicted score was above the threshold determined from the training data and otherwise called negative. After these classifications were made, the validation data was unblinded, and sensitivity and specificity were calculated. All data analysis was performed using Python 3.12.4; the model was trained using the scikit-learn library (version 1.4.2) and the fairlearn library (version 0.13.0).

[0244] We assessed the robustness of our classifier by looking for associations between the cross-validated labels of the healthy samples using the heldout and potential confounders including source, race, age of the donor at time of collection, and batch. This confounder analysis is repeated in the validation set, using the predicted labels of healthy samples. We performed a chi-squared contingency table test for all772734-ASB-016PC these factors. The age of the donor was binarized based on the mean of the healthy samples.Gene Set Enrichment Analysis

[0245] Preranked gene set enrichment analysis (GSEA, version 4.4.0) was performed comparing all the healthy control samples to the breast cancer samples (including training and validation sets). Limma (version 3.64.1 ) of non-imputed data was used to perform differential expression of proteins (DEP) between the two groups, where Empirical Bayes moderation of the standard errors was applied with robust variance estimation and a trend prior (trend=TRUE, robust=TRUE). The ranked list was made using sign(logFC)*-log10(adj.P.Val) to rank the genes, and this ranked list was then used as input to preranked GSEA.Healthcare utility

[0246] To model the impact of the breast cancer early detection test on finding dense breast cancers missed by the current screening guidelines, we simulated a population of 100,000 women with dense breasts screened via annual mammogram. Based on the literature, we simulated the dense breast population of women to have the following characteristics:• 84% have BI-RADS density score 3 and 16% have density score 4. [PMID 31623646]• 1 .24% of BI-RADS density score 3 have incident breast cancer and 1 .30% of BIRADS density score 4 have incident breast cancer. [PMID 31623646]

[0247] Performance of diagnostics for dense breast cancer were derived from published literature to incorporate into the simulation:• Sensitivity and specificity of screening mammogram in BI-RADS density score 3 are 69% (62%-76%) and 97% respectively; sensitivity and specificity in BI-RADS density score 4 are 47% (30%-65%) and 98%, respectively. [PMID 31623646]• Sensitivity and specificity of MRI are 97% (86%-99%) and 69% (46%-85%), respectively. [PMID 36154284]• Sensitivity and specificity of CEM are 91 % (77%-97%) and 74% (52%-89%), respectively. [PMID 36154284]• Sensitivity and specificity of ABUS are 67% (53%-79%) and 89.9% (89.1 %- 90.6%), respectively. [PMID 19727744]

[0248] Using the above as well as the sensitivity and specificity of our test as measured in the validation study, we simulated the number of false negative breast cancers and false positives in women with dense breasts. In this population, we assume772734-ASB-016PC all women receive a mammogram, and then following a negative mammogram, women may receive one of four different supplemental screens, with adherences ranging from 1 % to 100%. This simulation is repeated 100,000 times, and we summarize the number of false negatives and false positives by median, 2.5 percentile, and 97.5 percentile. Uncertainty of sensitivity and specificity for all diagnostics are incorporated into the simulation.Study approval

[0249] Samples were obtained from biobank locations who consent patients under appropriate institution review board approved protocols. All the patient data was provided to Astrin Biosciences in a de-identified manner.Data Availability

[0250] The data sets analyzed in this study are available upon reasonable request by email to the corresponding author.Results:Development of a high throughput pipeline for protein-based detection from plasma

[0251] For MS-based proteomics to be considered a viable platform for early cancer screening, it was necessary to develop and rigorously validate a high throughput assay capable of analyzing hundreds of patient samples per week. To do this, we utilized an automated robotics platform that allows up to 76 samples to be processed in parallel (FIG. 8A, B, FIG. 14). To validate that sample preparation and analysis meet strict criteria around repeatability (under same conditions) and reproducibility (under different conditions), multiple controls were included. Utilizing commercial digests of yeast enolase and HeLa lysates, we can measure the quantification of specific peptides and show that the retention time stability across all of our sample batches is consistent (FIG. 15 A-F). To confirm that we are minimizing sample carryover from run to run on the MS, we analyzed the TIC of blank injections and patient samples (healthy and cancer). The blank injections were <1 % of the total TIC signal from patient samples (FIG. 15G).

[0252] While this demonstrates that the Evosep One liquid chromatography (LC) system and the Orbitrap Astral mass spectrometer (MS) are well suited to the challenging conditions required to meet the high standards required for a clinical assay, sample preparation remained as the most likely source for variation. To circumvent this, we prepared and included a known concentration of intact yeast protein extract that was spiked onto each plate and processed in parallel with the patient samples. This allowed us to track sample recovery, reduction and alkylation efficiency, peptide recovery, and protein and peptide identifications (FIG. 16A). In addition, positive and negative controls772734-ASB-016PC made from pools of 9 late-stage breast cancer samples (stage III and IV) and healthy patient samples, respectively, were analyzed. These control pools provided information on the consistency of the preparation process over time including peptide and protein IDs (FIG. 16B, C). These samples were not included as part of the training data, but we verified that they classified correctly once the model training was completed (FIG. 16D).

[0253] This laboratory developed assay was validated in accordance with the Clinical Laboratory Improvement Amendments (CLIA) standards for high-complexity testing, and the assay's analytical performance has been characterized and documented. Indeed, repeatability and reproducibility analysis showed full agreement between repeated measurements of the same samples. The n=8 samples measured in triplicate showed an average positive agreement (APA) of 100% (4 / 4), and an average negative agreement (ANA) of 100% (4 / 4). The samples measured by two different operators also had APA of 100% (4 / 4) and ANA of 100% (4 / 4). Qualitatively, model scores showed strong agreement within donors whether from the same operator or across operators (FIG. 17).

[0254] Using this high throughput proteomic pipeline, we trained on plasma samples that passed quality control (QC) metrics for peptide and protein counts (FIG. 8 C, D). This results in a total of 845 women, including 379 newly diagnosed, treatment naive breast cancer patients (pathological stage 0: n = 45, I: n = 130, II: n = 152, III: n = 35, IV: n = 14) and 466 healthy controls. The patient demographics are summarized in Table 3. The plasma samples were de-identified, randomized, and blinded before processing and running on the MS. All MS files were run sequentially and normalized to identify and quantify each individual patient’s proteome.

[0255] For all patient samples that were ran, the median (Q1 -Q3) number of proteins detected between breast cancer and healthy samples were 7,064 (6,904-7, 160) and 7,054 (6,876-7,187) proteins, respectively, with 9,266 unique proteins observed across both cohorts. Most patients had more than 6,500 proteins detected per sample (92.5%, 1149 / 1242) with no significant differences in means across the two cohorts (Welch’s t-test p-value: 0.81 (training), 0.50 (validation)), demonstrating both the consistency of our sample preparation and the sensitivity of our MS method (FIG. 8C, D). Semi-quantitative assessment of protein intensities showed that we captured a dynamic range of protein abundances spanning over 8 orders of magnitude (FIG. 12), highlighting the workflow’s potential to capture low abundance protein fractions. Spearman correlation (FIG 8E) and principal component analysis of all proteins in the proteome (PCA, FIG. 8F) resulted in no discernible differences between the healthy and772734-ASB-016PC breast cancer samples validating the quality of sample and batch preparation in this cohort.Model training and held-out validation for breast cancer prediction

[0256] In cross-validation of the training samples, we observed an AUC of 0.961 (95% Bootstrap Cl: 0.947-0.97) (FIG. 9A) in distinguishing breast cancer from healthy samples. A receiver operating curve (ROC) showed strong discriminative performance, demonstrating the model's accuracy for breast cancer prediction (FIG. 9A). Across all patient samples in the training cohort, the model achieved a sensitivity of 89.2% (95% Wilson Cl: 85.7-91.9%) with a specificity of 90.1 % (95% Wilson Cl: 87.1-92.5%) (FIG. 9B).

[0257] To validate our training model, we analyzed 397 samples consisting of 195 healthy and 202 breast cancer patients (pathological stage 0: 13, stage I: 69, stage II: 98, stage 111:16, and stage IV: 2; stage unknown: 4) as a held-out validation set. Overall performance was 92.6% sensitivity at 92.3% specificity with an AUC of 0.975 (95% Bootstrap Cl: 0.961-0.987) and a negative predictive value (NPV) of 99.96% (95% Cl: 99.93-99.98) (FIG. 9C, D). When broken down by stage, we observed no discernible differences of performance accuracy across stages, which may relate to overall tumor burden (stage 0-IV sensitivities: 84.6%, 88.4%, 96.9%, 87.5%, and 100.0%, respectively) (FIG. 9E). Performance across breast cancer molecular (HR+ / HER2+, HR+ / HER2-, HR- / HER2+, and HR- / HER2-) and pathological (LCIS, DCIS, ILC and IDC) subtypes were also similar between the different groups (FIG. 10A, B). Potential confounders were also assessed in our training and validation cohorts including age, source, race, and plate (or batch) (FIG. 11 A, B and FIG. 19A, B). We observed no difference between the predicted label and the tested variables among healthy samples in either the training or validation (Table 4).Pathway analyses of breast cancer samples

[0258] To ensure we are identifying and enriching cancer-associated proteins and pathways, we performed gene set enrichment analyses (GSEA) of the breast cancer samples. Based on 50 Hallmark pathways, we first assessed if the number of proteins detected met the minimum recommended threshold of 15 genes for each of the pathways (FIG. 12A). While this threshold was met for almost all pathways, on average -68% of the genes in each pathway were represented. GSEA identified enriched cancer- associated pathways including epithelial-to-mesenchymal transition (EMT), PI3K-AKt signaling, KRAS up signaling, and WNT / beta-catenin signaling (Fig 5B-D). Importantly, several immune-activation or regulatory pathways (Interferon gamma, alpha, TGF beta)772734-ASB-016PC were not significantly enriched in breast cancer samples, or even decreased in these plasma samples (IL6, IL2, TNFalpha signaling) (FIG. 20A-C). Altogether, the plasma proteins captured were associated with known breast cancer pathways with limited or even negative associations with immune cell activity.Healthcare utility of breast cancer early detection test

[0259] While breast density was lacking in our particular cohort to assess model performance, we have published in an earlier manuscript that the performance of our test is independent of breast density. Based on that information and our sensitivity and specificity, we modeled the utility of our test to detect breast cancers in women with dense breasts in a screening population. We observed a dramatic increase in the proportion of dense breast cancers detected when incorporating our test as a supplemental screening test following a negative mammogram (FIG. 13A). In our analysis, we found that without supplemental screening, 431 (95% Cl: 347-521 ) breast cancers were misdiagnosed. Increasing uptake in all pathways resulted in fewer missed breast cancers, but with ABUS, 142 (95% Cl: 87-212) breast cancers were still missed at 100% uptake. Conversely, while MRI and CEM missed only 13 (95% Cl: 2-49) and 39 (95% Cl: 11-105) breast cancers respectively, there were 32,526 (95% Cl: 16,958- 54,361 ) and 27,724 (95% Cl: 13,701-49,766) false positives at 100% uptake (FIG. 13A, B). Meanwhile, false positives remain low with our deep proteome analysis (4,898; 95% Cl: 3,582-7,333) at 100% uptake with a similarly low number of breast cancers (49; 95% Cl: 25-89) being misdiagnosed. Even with a moderate uptake (40%) of our test, we would reduce the number of misdiagnosed dense breast cancers detected to 278 (95% Cl: 221 - 342) (FIG. 13B).Discussion:

[0260] We have developed and built a reproducible and repeatable protein-based liquid biopsy assay that is robust for breast cancer detection, especially at early stages including pathological stages 0, I, and II. There were also no discernable differences in performance across molecular or pathological subtypes. Our machine learning classifier was able to discern cancer-specific signals and was not confounded by other variables including age, sample source, and batch. This assay is automated and capable of analyzing several hundred samples in parallel. Holdout validation of this test maintained high sensitivity and specificity, paving the way for such a test to be offered as a supplemental screening option for women with a negative mammogram with moderate to high risk of harboring breast cancer. This is especially important for women with dense breast tissue and an invasive lobular carcinoma (ILC) pathology, which are extremely772734-ASB-016PC difficult to detect via mammogram due to their distinct biology and growth pattern as compared to intraductal carcinoma (IDC). Importantly, our test identified 100% of the ILC cases and we plan to enrich for this histology in future prospective studies to confirm performance as it will be critical to have an early detection test sensitive enough to detect ILCs.

[0261] For over four decades, mammograms have been used to screen for breast cancer, enabling early diagnosis in many individuals, thereby increasing breast cancer survival. While mammogram sensitivity in women with non-dense breast tissue is high, women with dense breast tissue are at risk of missed tumors as mammograms have been shown to miss more than half of diagnosed cancers (8.4 / 1000 for mammogram and 17.4 / 1000 AB-MRIs per 1000 supplemental exams)6. This underscores the considerable opportunity to enhance cancer detection in women with dense breast tissue. Currently, women with dense breasts are referred to an additional screening modality, typically ultrasound, which increases the number of cancers detected but still with low sensitivity. Although supplemental imaging techniques such as automated whole breast ultrasound, CEM, and abbreviated MRI (AB-MRI) each offer incremental gains, they are constrained by important trade-offs including operator dependence, cost, higher recall burdens, limited accessibility, and reliance on contrast agents. These persistent challenges highlight the need for innovative approaches capable of improving detection which are convenient, affordable, specific, and do not strain clinical workflows. In this context, our proposed breast cancer early detection test offers a promising path forward with a high sensitivity in early-stage breast cancers, including women with dense breasts, while maintaining high specificity and NPV. As a liquid biopsy test, implementation of the plasma derived deep proteome analysis into the clinic would be straightforward and could be widely implemented after mammogram and before MRI as a supplemental screening test. For example, a dense breast patient who needs supplemental screening would receive our test following a negative mammogram with the goal of reducing unnecessary MRIs. In the case of a positive result, the patient would then be referred to an MRI for tumor identification and biopsy.

[0262] In recent years, many blood-based cancer screening tests have entered the market. Shield™ by Guardant specifically detects the presence of colorectal cancer while FirstLook by DELFI Diagnostics detects lung cancer. Notably, Grail Galleri® and Exact Sciences CancerGuard™ are both multi-cancer early detection (MCED) tests with varying sensitivities based on the cancer type evaluated and cancer stage. All of these tests detect cancer via cfDNA, such as fragmentomics, methylation, or somatic alteration772734-ASB-016PC as the primary analyte, with some supplemented by a panel of blood-based proteins, such as in the CancerGuard™ test. Importantly, it should be emphasized that the sensitivity for early-stage breast cancer detection is low for both Galleri® and CancerGuard™ implying that cfDNA-based assays, even with a small sub-sampling of proteins, may not be sufficient as the primary analyte for early-stage breast cancer detection, likely due to the low shedding rate of cfDNA in early-stage cancers17. Indeed, the sensitivity for early-stage breast cancer detection using Galleri® is 2.6%-47.5% for stage I and II patients, respectively18and for CancerGuard™ is 8.3%-40.0% for stage I and II patients, respectively. Further, the MCED tests require several milliliters (mL) to several tubes of blood. The described breast cancer early detection test has the unique advantage of finding early-stage breast cancer with <1 mL of blood with sensitivities over 90% across stages O-ll, and will be comparable in cost to MRI or other screening tests.

[0263] There are a few notable limitations to this study. First, the analysis is conducted on samples purchased from biobanks. While we ruled out confounding with available clinical information, we cannot rule out the possibility that our classifier is confounded by other unmeasured factors, such as selection bias and variations in collection and storage techniques. Second, this analysis has been conducted on women where BI-RADS density was not recorded. Importantly, our analysis of a separate study showed that it is likely that our test performance is independent of breast density11. Future studies will be required to confirm performance and suitability for supplemental analysis of dense breast cancer patients at the same time. Third, for validation, we randomly allocated our dataset into training and validation. These validation samples were batched separately from the training samples and so represent generalization to future batches. However, future validations will be required to confirm generalizability to future groups of individuals from those observed in training using external datasets. Fourth, the racial demographics of healthy and breast cancer patient training and validation sets were predominantly white (92.8% and 93.2%, respectively), potentially limiting the validity of these findings for minority groups. Future efforts will be aimed at prospective collection of samples that increase source variety with more complete clinical annotations and reducing racial disparities in our validation cohorts. Finally, our current methodology requires blood to be drawn into EDTA tubes, centrifuged, and frozen the same day. Future work will also evaluate other ways to mitigate protein variations that come from blood stored in EDTA tubes, with the goal of increasing the accessibility and consistency of recruited samples.772734-ASB-016PCConclusions:

[0264] We describe a novel deep proteome-based breast cancer early detection test that can serve as a supplemental screening test particularly in patients with dense breasts (Bl RADS C,D) as seen on screening mammography. The test has a high sensitivity and high specificity with an NPV of 99.7% with the potential to reduce a significant number of unnecessary MRIs and biopsies.Table 3. Patient demographics and splits used in the training and validation sets.772734-ASB-016PC772734-ASB-016PCTable 4. Confounder analysisRefrences for Example 3.1. Boyd, N.F., et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med 356, 227-236 (2007).2. McCormack, V.A. & dos Santos Silva, I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev 15, 1159-1169 (2006).3. Duffy, S.W., et al. Mammographic density and breast cancer risk in breast screening assessment cases and women with a family history of breast cancer. European journal of cancer 88, 48-56 (2018).4. Payne, N.R., et al. Breast density effect on the sensitivity of digital screening mammography in a UK cohort. Eur Radiol 35, 177-187 (2025).5. Mammography Quality Standards Act. (ed. Food and Drug Administration, H.) (2023).6. Gilbert, F.J., et al. Comparison of supplemental breast cancer imaging techniques-interim results from the BRAID randomised controlled trial. Lancet 405, 1935-1944 (2025).7. Force, U.S.P.S.T., et al. Screening for Breast Cancer: US Preventive Services Task Force Recommendation Statement. JAMA 331 , 1918-1930 (2024).8. Zajec, M., et al. Mass Spectrometry for Identification, Monitoring, and Minimal Residual Disease Detection of M-Proteins. Clin Chem 66, 421-433 (2020).9. Bamidge, D.R., et al. Using mass spectrometry to monitor monoclonal immunoglobulins in patients with a monoclonal gammopathy. J Proteome Res 13, 1419-1427 (2014).10. Banerjee, S. Empowering Clinical Diagnostics with Mass Spectrometry. ACS Omega 5, 2041-2048 (2020).11. Horrmann, A., et al. A Plasma-based Deep Proteomic Platform for Early-Stage Breast Cancer Detection. medRxiv, 2025.2009.2022.25336353 (2025).12. Inic, Z., et al. Difference between Luminal A and Luminal B Subtypes According to Ki-67, Tumor Size, and Progesterone Receptor Negativity Providing Prognostic Information. Clin Med Insights Oncol 8, 107-111 (2014).13. Orrantia-Borunda E, A.-N.P., Acuna-Aguilar LE, Gomez-Valles FO, Ramirez- Valdespino CA. Subtypes of Breast Cancer. Breast Cancer (2022).14. Kistner, F., Grossmann, J.L., Sinn, L.R. & Demichev, V. QuantUMS: uncertainty772734-ASB-016PC minimisation enables confident quantification in proteomics. bioRxiv, 2023.2006.2020.545604 (2023). Cox, J., et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics 13, 2513-2526 (2014). Agarwal, A.B., A; Dudik, M; Langford; Wallach, H. A Reductions Approach to Fair Classification. Proceedings of Machine Learning Research 80(2018). Panet, F., et al. Use of ctDNA in early breast cancer: analytical validity and clinical potential. NPJ Breast Cancer 10, 50 (2024). Klein, E.A., et al. Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set. Ann Oncol 32, 1167-1177 (2021).

Claims

1. 772734-ASB-016PCCLAIMSWe claim:1 . A method of detecting cancer in a subject comprising: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data.

2. A method of treating cancer comprising: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and h) where the subject is identified as having cancer, administering one or more anti-cancer agents or treatments to the subject.772734-ASB-016PC3. The method of any of claims 1-2, further comprising additionally performing three dimensional (3D) digital holography on a blood sample from the subject to identify and / or isolate circulating tumor cells.

4. The method of any one of claims 1 -3, wherein cancer is detected prior to or at stage 0, 1, II, III or IV.

5. The method of any one of claims 1 -4, wherein cancer is detected prior to or at stage III.

6. The method of any one of claims 1-5, wherein the blood sample is whole blood, serum, or plasma.

7. The method of any one of claims 1-6, further comprising centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support.

8. The method of claim 7, wherein, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, the blood sample is treated by a) applying centrifugal force of 200-1 ,600 x g; b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g and obtaining the supernatant as the blood sample.

9. The method of any one of claims 1-8, wherein isolating the solid support comprising bound extracellular vesicles is performed by centrifugation, elution, chromatography, or magnetization.

10. The method of any one of claims 1-9, wherein the solid support is an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof.772734-ASB-016PC11 . The method of any of one claims 1-10, wherein the solid support is a magnetic bead.

12. The method of any one of claims 1-11 , wherein the solid support of step a) is functionalized with one or more specific binding proteins that bind extracellular vesicles.

13. The method of claim 12, wherein the one or more specific binding proteins that bind extracellular vesicles specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1 A1 , CD44, SLC3A2, LAMP1 , EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, CA19-9, or combinations thereof.

14. The method of any one of claims 1-13, wherein the solid support functionalized to bind the proteins in the protein sample is carboxyl modified, amine modified, hydroxyl modified, sulfhydryl modified, epoxide modified, biotin modified, streptavidin modified, avidin modified, modified with one or more antibodies, modified with one or more lectins, and / or carbonyl modified, or combinations thereof.

15. The method of any one of claims 1-14, wherein the EV derived protein sample is digested prior to performing mass spectrometry.

16. The method of claim 15, wherein the digestion is one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof.

17. The method of claim 16, wherein the digest is a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

18. The method of any one of claims 1-17, wherein the EVs are a sub-set of EVs.772734-ASB-016PC19. The method of claim 18, wherein the sub-set of EVs comprises EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutl 0 pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

20. The method of any one of claims 1-19, wherein the blood sample is collected from the subject into a storage container comprising imidazolidinyl urea, diazolidinyl urea formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1-1aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxy[methyleneoxy]methyl-1-1aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis- hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis.21 . The method of claim 20, wherein the blood sample is treated with one or more Schiff base ligands prior to step a).

22. The method of any one of claims 1-21 , wherein the blood sample is positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

23. The method of any one of claims 1-22, wherein the biomarkers are treatment- related cancer biomarkers.772734-ASB-016PC24. The method of any one of claims 1-23, wherein the reference data comprises amounts of one or more biomarkers from a healthy subject.

25. The method of any one of claims 1-24, wherein the one or more biomarkers of step g) comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or wherein the one or more biomarkers from a healthy subject comprises 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.

26. A method of detecting breast cancer in a subject comprising: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subject as having breast cancer if the amount of one or more biomarkers differs from the reference data.

27. A method of decreasing false negative breast cancer diagnoses in a group of subjects comprising: a) contacting a blood sample from each of the subjects in the group of subjects with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and772734-ASB-016PC g) identifying the subjects as having breast cancer where the amount of one or more biomarkers differs from the reference data, wherein the number of false negative diagnosis in the group of subjects is decreased as compared to a group of subjects receiving a diagnosis via mammography.

28. A method of treating breast cancer comprising: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and h) where the subject is identified as having breast cancer, administering one or more anti-breast cancer agents or breast cancer treatments to the subject.

29. The method of any one of claims 26-28, wherein the group of subjects has had negative mammogram results.

30. The method of any one of claims 26-29, wherein the group of subjects has dense breast tissue.31 . The method of any of claims 26-30, further comprising additionally performing three dimensional (3D) digital holography on a blood sample from the group of subjects to identify and / or isolate circulating tumor cells.

32. The method of any one of claims 26-31 , wherein the breast cancer is detected prior to or at stage 0, 1, II, III or IV.772734-ASB-016PC33. The method of any one of claims 26-32, wherein breast cancer is detected prior to or at stage III.

34. The method of any one of claims 26-33, wherein the blood sample is whole blood, serum, or plasma.

35. The method of any one of claims 26-34, further comprising centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support.

36. The method of any one of claims 26-34, wherein, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, the blood sample is treated by a) applying centrifugal force of 200-1 ,600 x g; b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g; and obtaining the supernatant as the blood sample.

37. The method of any one of claims 26-37, wherein isolating the solid support comprising bound extracellular vesicles is performed by centrifugation, elution, chromatography, or magnetization.

38. The method of any one of claims 26-38, wherein the solid support is an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof.

39. The method of any of one claims 26-38, wherein the solid support is a magnetic bead.

40. The method of any one of claims 26-39, wherein the solid support of step a) is functionalized with one or more specific binding proteins that bind extracellular vesicles.772734-ASB-016PC41 . The method of claim 40, wherein the one or more specific binding proteins that bind extracellular vesicles specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1 A1 , CD44, SLC3A2, LAMP1 , EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, CA19-9, or combinations thereof.

42. The method of any one of claims 26-41 , wherein the solid support functionalized to bind the proteins in the protein sample is carboxyl modified, amine modified, hydroxyl modified, sulfhydryl modified, epoxide modified, biotin modified, streptavidin modified, avidin modified, modified with one or more antibodies, modified with one or more lectins, and / or carbonyl modified, or combinations thereof.

43. The method of any one of claims 26-42, wherein the EV derived protein sample is digested prior to performing mass spectrometry.

44. The method of claim 43, wherein the digestion is one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof.

45. The method of claim 43, wherein the digest is a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

46. The method of any one of claims 26-45, wherein the EVs are a sub-set of EVs.

47. The method of claim 46, wherein the sub-set of EVs comprises EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutl 0 pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.772734-ASB-016PC48. The method of any one of claims 26-47, wherein the blood sample is collected from the subject into a storage container comprising imidazolidinyl urea, diazolidinyl urea formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1-1aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxy[methyleneoxy]methyl-1-1aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis- hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis.

49. The method of claim 48, wherein the blood sample is treated with one or more Schiff base ligands prior to step a).

50. The method of any one of claims 26-49, wherein the blood sample is positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.51 . The method of any one of claims 26-50, wherein the biomarkers are treatment- related cancer biomarkers.

52. The method of any one of claims 26-51 , wherein the reference data comprises amounts of one or more biomarkers from a healthy subject.

53. The method of any one of claims 26-52, wherein the one or more biomarkers of step g) comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or wherein the one or more biomarkers from a healthy subject comprises 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.772734-ASB-016PC54. A method of monitoring cancer treatment in a subject comprising: a) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) repeating steps a)-f) at a different time point; h) comparing the mass spectrometry data obtained at points f) and g) to determine if there are any changes, whereby cancer treatment is monitored.

55. The method of claim 54, wherein the reference data comprises the amount of one or more biomarkers from healthy patients.

56. The method of any one of claims 54-55, wherein cancer is detected prior to or at stage 0, I, II, III, or IV.

57. The method of any one of claims 54-56, wherein cancer is detected prior to or at stage III.

58. The method of any one of claims 54-57, wherein the blood sample is whole blood, serum, or plasma.

59. The method of any one of claims 54-58, further comprising centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support.772734-ASB-016PC60. The method of any one of claims 54-59, wherein, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, the blood sample is treated by a) applying centrifugal force of 200-1 ,600 x g b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g; and obtaining the supernatant as the blood sample.61 . The method of any one of claims 54-60, wherein isolating the solid support comprising bound extracellular vesicles is performed by centrifugation, elution, chromatography, or magnetization.

62. The method of any one of claims 54-61 , wherein the solid support is an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof.

63. The method of any one of claims 54-62, wherein the solid support is a magnetic bead.

64. The method of any one of claims 54-63, wherein the solid support of step a) is functionalized with one or more specific binding proteins that bind extracellular vesicles.

65. The method of claim 64, wherein the one or more specific binding proteins that bind extracellular vesicles specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1 A1 , CD44, SLC3A2, LAMP1 , EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, CA19-9, or combinations thereof.

66. The method of any one of claims 54-65, wherein the solid support functionalized to bind the proteins in the protein sample is functionalized with free carboxyl groups,772734-ASB-016PC hydroxyl groups, carbonyl groups, amine groups, epoxide groups, sulfhydryl groups, biotin, streptavidin, avidin, antibodies, lectins, or combinations thereof.

67. The method of any one of claims 54-66, wherein the EV derived protein sample is digested prior to performing mass spectrometry.

68. The method of claim 67, wherein the digestion is one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof.

69. The method of claim 67, wherein the digest is a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

70. The method of any one of claims 54-69, wherein the EVs are a sub-set of EVs.71 . The method of claim 70, wherein the sub-set of EVs comprises EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutl 0 pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

72. The method of any one of claims 54-71 , wherein the blood sample from the subject is collected from the subject into a storage container comprising formaldehyde, formalin, glyceraldehyde, imidazolidinyl urea, or diazolidinyl urea, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3- diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1 aza-3,7-dioxabicyclo[3.3.0]octane, 5-hydroxym ethyl- 1 -1 aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxy[methyleneoxy]methyl-1 -1 aza-3, 7- dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5- dioxo-imidazolidin-4-yl)-1 ,3-bis-hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo- imidazolidin-4-yl)-urea, or (4-hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis.772734-ASB-016PC73. The method of claim 72, wherein the blood sample is treated with one or more Schiff base ligands prior to step a).

74. The method of any of claims 54-73, wherein the blood sample is positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

75. The method of any one of claims 55-74, wherein the one or more biomarkers are treatment-related cancer biomarkers.

76. The method of any of claims 54-75, further comprising additionally performing three dimensional (3D) digital holography on a blood sample from the subject to identify and / or isolate circulating tumor cells.

77. The method of any one of claims 54-75, wherein the reference data comprises amounts of one or more biomarkers from a healthy subject.

78. The method of any one of claims 55-77, wherein the one or more biomarkers comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or wherein the one or more biomarkers from a healthy subject comprises 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.

79. A method of detecting cancer in a subject comprising: a) collecting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample;772734-ASB-016PC d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to reference data; and g) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and h) performing imaging on the subject to determine the location of a primary tumor or lesion, determine metastatic spread, or determine tumor recurrence.

80. A method for reducing an amount of imaging necessary in a group of subjects to be screened for cancer, the method comprising: a) contacting a blood sample from each of the subjects with a solid support functionalized to bind extracellular vesicles in the blood sample; b) isolating the solid support comprising bound extracellular vesicles; c) lysing the bound extracellular vesicles to form a protein sample; d) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; e) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; f) comparing the mass spectrometry data to healthy reference data; and g) identifying each of the subjects of the group as not having cancer if the amounts of one or more biomarkers do not differ from healthy reference data and identifying each of the subjects of the group as having cancer if the amounts of one or more biomarkers differs from the reference data; and h) performing imaging on only the subjects identified as having cancer to determine the location of a primary tumor or lesion, determine metastatic spread, or determine tumor recurrence, wherein the amount of imaging is reduced in the group of subjects.81 . The method of any one of claims 79-80 further comprising additionally performing three dimensional (3D) digital holography on a blood sample from the group of subjects to identify and / or isolate circulating tumor cells.772734-ASB-016PC82. The method of any one of claims 79-81 , wherein the imaging comprises: in vitro imaging; in vivo whole-body imaging; in vivo organ specific imaging; in vivo tissue specific imaging; or combinations thereof.

83. The method of any one of claims 79-82, wherein cancer is detected prior to or at stage 0, 1, II, III or IV.

84. The method of any one of claims 79-83, wherein cancer is detected prior to or at stage 3.

85. The method of any one of claims 79-84, wherein the blood sample is whole blood, serum, or plasma.

86. The method of any one of claims 79-85, further comprising centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support.

87. The method of any one of claims 79-86, wherein, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, the blood sample is treated by a) applying centrifugal force of 200-1 ,600 x g b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g and obtaining the supernatant as the blood sample.

88. The method of any one of claims 79-87, wherein isolating the solid support comprising bound extracellular vesicles is performed by centrifugation, elution, chromatography, or magnetization.

89. The method of any one of claims 79-88, wherein the solid support is an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof.772734-ASB-016PC90. The method of any one of claims 79-89, wherein the solid support is a magnetic bead.91 . The method of any one of claims 79-90, wherein the solid support of step a) is functionalized with one or more specific binding proteins that bind extracellular vesicles.

92. The method of claim 91 , wherein the one or more specific binding proteins that bind extracellular vesicles specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1 A1 , CD44, SLC3A2, LAMP1 , EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, CA19-9, or combinations thereof.

93. The method of any of claims 79-92, wherein the solid support functionalized to bind the proteins in the protein sample is functionalized with free carboxyl groups, hydroxyl groups, carbonyl groups, amine groups, epoxide groups, sulfhydryl groups, biotin, streptavidin, avidin, antibodies, lectins, or combinations thereof.

94. The method of any one of claims 79-93, wherein the EV derived protein sample is digested prior to performing mass spectrometry.

95. The method of claim 94, wherein the digestion is one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof.

96. The method of claim 94, wherein the digest is a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

97. The method of any one of claims 79-96, wherein the EVs are a sub-set of EVs.772734-ASB-016PC98. The method of claim 97, wherein the sub-set of EVs comprises EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutl 0 pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

99. The method of any one of claims 79-98, wherein the blood sample is collected from the subject into a storage container comprising formaldehyde, formalin, glyceraldehyde, imidazolidinyl urea, diazolidinyl urea, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1-1aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxy[methyleneoxy]methyl-1-1aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis- hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis.

100. The method of claim 99, wherein the blood sample is treated with one or more Schiff base ligands prior to step a).

101. The method of any one of claims 79-100, wherein the blood sample is positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

102. The method of any one of claims 79-101 wherein the biomarkers are treatment-related cancer biomarkers.772734-ASB-016PC103. The method of any one of claims 79-102, wherein the reference data comprises amounts of one or more biomarkers from a healthy subject.

104. The method of any one of claims 79-103, wherein the one or more biomarkers of step g) comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or wherein the one or more biomarkers from a healthy subject comprises 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.

105. A method of detecting cancer in a subject comprising: a) having the subject self-collect a blood sample, and optionally, having the subject add a protective agent to the blood sample; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data.

106. A method of treating cancer in a subject comprising: a) having the subject self-collect a blood sample; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data;772734-ASB-016PC g) comparing the mass spectrometry data to reference data; and h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and i) where the subject is identified as having cancer, administering one or more anti-cancer agents or treatments to the subject.

107. A method of monitoring cancer treatment in a subject comprising: a) having the subject self-collect a blood sample; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) repeating steps a)-g) at a different time point; i) comparing the mass spectrometry data obtained at points f) and g) to determine if there are any changes, whereby the cancer treatment is monitored.

108. A method of detecting cancer in a subject comprising:(a) having the subject self-collect a blood sample;(b) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(c) isolating the solid support comprising bound extracellular vesicles;(d) lysing the bound extracellular vesicles to form a protein sample;(e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample;(f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data;(g) comparing the mass spectrometry data to reference data; and772734-ASB-016PC(h) identifying each of the subjects in the group as having cancer if the amount of one or more biomarkers differs from the reference data; and(i) performing imaging on the subjects in the group having cancer to determine the location of a primary tumor or lesion.

109. A method for reducing an amount of imaging necessary in a group of subjects to be screened for cancer, the method comprising: a) having each subject in the group of subjects self-collect a blood sample; b) contacting the blood sample from each of the subjects with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to healthy reference data; and h) identifying each of the subjects in the group as not having cancer if the amount of biomarkers do not differ from healthy reference data and identifying each of the subjects in the group as having cancer if the amount of one or more biomarkers differs from the healthy reference data; and i) performing imaging on only the subjects identified as having cancer to determine the location of a primary tumor or lesion, wherein the amount of imaging is reduced in the group of subjects.

110. The method of any one of claims 105-109, further comprising additionally performing three dimensional (3D) digital holography on a blood sample from the subject to identify and / or isolate circulating tumor cells.772734-ASB-016PC111. The method of any one of claims 108-109, wherein the imaging comprises: in vitro imaging; in vivo whole-body imaging; in vivo organ specific imaging; in vivo tissue specific imaging; or combinations thereof.

112. The method of any one of claims 105-111 , wherein cancer is detected prior to or at stage 0, I, II, III or IV.

113. The method of any one of claims 105-112, wherein cancer is detected prior to or at stage III.

114. The method of any one of claims 105-113, wherein the blood sample is whole blood, serum, or plasma.

115. The method of any one of claims 105-114, further comprising centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support.

116. The method of any one of claims 105-115, wherein, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, the blood sample is treated by a) applying centrifugal force of 200-1 ,600 x g b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g; and obtaining the supernatant as the blood sample.

117. The method of any one of claims 105-116, wherein isolating the solid support comprising bound extracellular vesicles is performed by centrifugation, elution, chromatography, or magnetization.

118. The method of any one of claims 105-116, wherein the solid support is an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead, a glass bead, a cellulose bead, a polymeric bead, a heparin-conjugated affinity chromatography column, a size exclusion chromatography column, an immobilized metal affinity column, a chromatography column, or any combination thereof.772734-ASB-016PC119. The method of any one of claims 105-118, wherein the solid support is a magnetic bead.

120. The method of any one of claims 105-119, wherein the solid support of step a) is functionalized with one or more specific binding proteins that bind extracellular vesicles.

121. The method of claim 120, wherein specific binding proteins specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin- 2, CD31 , clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1A1 , CD44, SLC3A2, LAMP1 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, EGFR, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, or CA19-9.

122. The method of any one of claims 105-121 , wherein the solid support functionalized to bind the proteins in the protein sample is carboxyl modified, amine modified, hydroxyl modified, sulfhydryl modified, epoxide modified, biotin modified, streptavidin modified, avidin modified, modified with one or more antibodies, modified with one or more lectins, and / or carbonyl modified, or combinations thereof.

123. The method of any one of claims 105-122, wherein the EV derived protein sample is digested prior to performing mass spectrometry.

124. The method of claim 123, wherein the digestion is one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof.

125. The method of claim 123, wherein the digest is a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

126. The method of any one of claims 105-125, wherein the EVs are a sub-set of EVs.772734-ASB-016PC127. The method of claim 126, wherein the sub-set of EVs comprises EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutl 0 pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

128. The method of any one of claims 105-127, wherein the blood sample is collected from the subject into a storage container comprising imidazolidinyl urea, diazolidinyl urea, formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2-nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5-hydroxymethoxymethyl-1-1aza-3,7- dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1-1aza-3,7-dioxabicyclo[3.3.0]octane, 5- hydroxy[methyleneoxy]methyl-1-1aza-3, 7-dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-1 ,3-bis- hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidin-4-yl)-urea, (4- hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof prior to analysis.

129. The method of claim 128, wherein the blood sample is treated with one or more Schiff base ligands prior to step b).

130. The method of any one of claims 105-129, wherein the blood sample is positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

131. The method of any one of claims 105-130, wherein the blood sample is 50 pL to 1 ,000 pL.772734-ASB-016PC132. The method of any one of claims 105-131 , wherein after step a) the sample is shipped to a testing center greater than 5 miles away from the subject.

133. The method of any one of claims 105-132, wherein the biomarkers are treatment-related cancer biomarkers.

134. The method of any one of claims 105-133, wherein the reference data comprises amounts of one or more biomarkers from a healthy subject.

135. The method of any one of claims 105-134, wherein the one or more biomarkers comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or wherein the one or more biomarkers from a healthy subject comprises 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.

136. A method of detecting cancer in a subject comprising: a) adding a protective agent to a blood sample from the subject; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data.

137. A method of treating cancer comprising: a) adding a protective agent to a blood sample from the subject; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample;772734-ASB-016PC e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and i) where the subject is identified as having cancer, administering one or more anti-cancer agents or treatments to the subject.

138. A method of monitoring cancer treatment in a subject comprising: a) adding a protective agent to a blood sample from the subject; b) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) repeating steps a)-g) at a different time point; i) comparing the mass spectrometry data obtained at points f) and g) to determine if there are any changes.

139. A method of detecting cancer in a subject comprising: a) adding a protective agent to a blood sample from the subject; b) contacting a blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample;772734-ASB-016PC e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to reference data; and h) identifying the subject as having cancer if the amount of one or more biomarkers differs from the reference data; and i) performing imaging on the subject to determine the location of a primary tumor or lesion.

140. A method for reducing an amount of imaging necessary in a group of subjects to be screened for cancer, the method comprising: a) adding a protective agent to a blood sample from each of the subjects in the group; b) contacting the blood sample from each of the subjects with a solid support functionalized to bind extracellular vesicles in the blood sample; c) isolating the solid support comprising bound extracellular vesicles; d) lysing the bound extracellular vesicles to form a protein sample; e) contacting the protein sample with a solid support functionalized to bind the proteins in the protein sample to form an extracellular vesicle (EV) derived protein sample; f) performing mass spectrometry on the EV derived protein sample and collecting mass spectrometry data; g) comparing the mass spectrometry data to healthy reference data; and h) identifying each of the subjects in the group as not having cancer if the amount of one or more biomarkers do not differ from the healthy reference data and identifying each of the subjects in the group as having cancer if the amount of one or more biomarkers differs from the healthy reference data; and i) performing imaging on only the subjects identified as having cancer to determine the location of a primary tumor or lesion, wherein the amount of imaging is reduced in the group of subjects.772734-ASB-016PC141. The method of any one of claims 136-140, further comprising additionally performing three dimensional (3D) digital holography on a blood sample from the subject to identify and / or isolate circulating tumor cells.

142. The method of any one of claims 139 or 140, wherein the imaging comprises: in vitro imaging; in vivo whole-body imaging; in vivo organ specific imaging; in vivo tissue specific imaging; or combinations thereof.

143. The method of any one of claims 136-142, wherein cancer is detected prior to or at stage 0, I, II, III or IV.

144. The method of any one of claims 136-143, wherein cancer is detected prior to or at stage III.

145. The method of any one of claims 136-144, wherein the blood sample is whole blood, serum, or plasma.

146. The method of any one of claims 136-145, further comprising centrifugating the blood sample prior to contacting the blood sample from the subject with a solid support.

147. The method of any one of claims 136-146, wherein, prior to adding the blood sample to the solid support functionalized to bind extracellular vesicles, and before or after adding the protective agent, the blood sample is treated by a) applying centrifugal force of 200-1 ,600 x g; b) transferring supernatant to a new vessel; c) applying centrifugal force of 1 ,500-3,500 x g; and obtaining the supernatant as the blood sample.

148. The method of any one of claims 136-147, wherein isolating the solid support comprising bound extracellular vesicles is performed by centrifugation, elution, chromatography, or magnetization.

149. The method of any one of claims 136-148, wherein the solid support is an agarose bead, a magnetic bead, a silica bead, a polystyrene plate, a polystyrene bead,772734-ASB-016PC a glass bead, a cellulose bead, a polymeric bead, a size exclusion chromatography column, an immobilized metal affinity column, a heparin-conjugated affinity chromatography column, a chromatography column, or any combination thereof.

150. The method of any one of claims 136-149, wherein the solid support is a magnetic bead.

151. The method of any one of claims 136-150, wherein the solid support of step a) is functionalized with one or more specific binding proteins that bind extracellular vesicles.

152. The method of claim 151 , wherein the one or more specific binding proteins that bind extracellular vesicles specifically bind one or more of CD63, CD81 , CD9, dextran, Alix, TSG101 , HSP70, HSP90, flotillin-1 , flotillin-2, CD31 , clatherin, CD29, CD47, CD82, CD98, CD147, syntenin, AnxA1 , AnxA2, AnxA5, AnxA6, AnxA7, AnxA11 , ATP1A1 , CD44, SLC3A2, LAMP1 , VE-cadherin, CD41 , CD61 , CD45, EpCAM, HER2, EGFRvlll, EGER, HER2, c-MET, VEGFR, EpCAM, MUC1 , integrins (e.g. avp3 or a6p4), PD-L1 , PD-1 , B7-H3, B7-H4, CD19, CD20, CD22, CD33, CD30, CEA, PSMA, GD2, or CA19-9.

153. The method of any one of claims 136-152, wherein the solid support functionalized to bind the proteins in the protein sample is carboxyl modified, amine modified, hydroxyl modified, sulfhydryl modified, epoxide modified, biotin modified, streptavidin modified, avidin modified, modified with one or more antibodies, modified with one or more lectins, and / or carbonyl modified, or combinations thereof.

154. The method of any one of claims 136-153, wherein the EV derived protein sample is digested prior to performing mass spectrometry.

155. The method of claim 154, wherein the digestion is one or more of a trypsin digest, chymotrypsin digest, endoproteinase Lys-C digest, endoproteinase Lys-N digest, endoproteinase Asp-N digest, endoproteinase Glu-C digest, endoproteinase Arg-C digest, elastase digest, pepsin digest, thermolysin digest, or a combination thereof.772734-ASB-016PC156. The method of claim 154, wherein the digest is a trypsin digest or an endoproteinase Lys-C digest, or a combination thereof.

157. The method of any one of claims 136-156, wherein the EVs are a sub-set of EVs.

158. The method of claim 157, wherein the sub-set of EVs comprises EVs of about 50 nm to about 300 nm, small EVs of about 30 nm to about 50 nm, microvesicles of about 40 nm to about 1 ,000 nm, oncosomes of about 1 pm to aboutl 0 pm, migrasomes of about 500 nm to about 2pm, or apoptotic bodies of about 50 nm to about 5 pm.

159. The method of any one of claims 136-158, wherein the blood sample is collected from the subject into a storage container comprising imidazolidinyl urea, diazolidinyl urea, formaldehyde, formalin, glutaraldehyde, or combinations thereof, or wherein imidazolidinyl urea, diazolidinyl urea, formaldehyde, formalin, glutaraldehyde, dimethoylol-5,5 dimethylhydantoin, dimethylol urea, 2-bromo-2- nitropropane-1 ,3-diol, oxazolidines, sodium hydroxymethyl glycinate, 5- hydroxymethoxymethyl-1-1aza-3,7-dioxabicyclo[3.3.0]octane, 5-hydroxymethyl-1- 1aza-3,7-dioxabicyclo[3.3.0]octane, 5-hydroxy[methyleneoxy]methyl-1-1aza-3, 7- dioxabicyclo[3.3.0]octane, quaternary adamantine, 1-(3,4-bis-hydroxymethyl-2,5- dioxo-imidazolidin-4-yl)-1 ,3-bis-hydroxymethyl-urea, (4-hydroxymethyl-2,5-dioxo- imidazolidin-4-yl)-urea, (4-hydroxymethyl-2,5-dioxo-imidazolidine-4-yl)-urea, or combinations thereof, or wherein one or more of these reagents are added to the storage container after collection of the blood sample.

160. The method of any one of claims 136-159, wherein the blood sample is collected from the subject into a storage container comprising one or more protease inhibitors and / or one or more phosphatase inhibitors; or wherein one or more protease inhibitors and / or one or more phosphatase inhibitors are added to the storage container after collection of the blood sample.

161. The method of claim 160, wherein the blood sample is treated with one or more Schiff base ligands prior to step b).772734-ASB-016PC162. The method of any one of claims 136-161 , wherein the blood sample is positively enriched for target proteins or negatively enriched to remove or reduce unwanted proteins prior to or after:(a) contacting the blood sample from the subject with a solid support functionalized to bind extracellular vesicles in the blood sample;(b) isolating the solid support comprising bound extracellular vesicles;(c) lysing the bound extracellular vesicles to form the protein sample; and / or(d) contacting the protein sample with the solid support functionalized to bind the proteins in the protein sample.

163. The method of any one of claims 136-162, wherein the blood sample is 50 pL to 1 ,000 pL.

164. The method of any one of claims 136-163, wherein after step a) the sample is shipped to a testing center greater than 5 miles away from the subject.

165. The method of any one of claims 136-164, wherein the biomarkers are treatment-related cancer biomarkers.

166. The method of any one of claims 136-165, wherein the reference data comprises amounts of one or more biomarkers from a healthy subject.

167. The method of any one of claims 136-166, wherein the one or more biomarkers of step g) comprise 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers and / or wherein the one or more biomarkers from a healthy subject comprises 100, 250, 500, 1 ,000, 2,000, 3,000, 4,000, 5,000 or more biomarkers.

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