Method and system for biomarker detection and discovery - Patents.com

Abstract

Provided herein are methods and systems for discovering biomarkers associated with disease risk, as well as methods of using the identified biomarkers to detect disease prognosis and progression.

Description

[Technical field]

[0001] cross reference This application claims the benefit of U.S. Provisional Patent Application No. 63 / 136,572, filed January 12, 2021, U.S. Provisional Patent Application No. 63 / 190,719, filed May 19, 2021, and U.S. Provisional Patent Application No. 63 / 191,886, filed May 21, 2021, each of which is incorporated by reference in its entirety. [Background technology]

[0002] The discovery and use of biomarkers to detect, monitor, and treat disease states shows promise in improving outcomes in patients. Because diseases often have complex etiologies, it is difficult to select biomarkers to detect, monitor, and treat diseases. For example, early localized tumors are often cured by surgical resection. However, some fatal cancers cause few symptoms, resulting in delayed diagnosis. Early cancer detection could transform the field by increasing survival rates while simplifying treatment. Summary of the Invention

[0003] In one aspect, a method for identifying a biomarker as associated with a disease state is provided. Optionally, the method includes: (a) isolating a first plurality of analytes in a first biological sample of an individual known to have a disease state using an electrode array configured to generate an AC dielectrophoretic field; (b) isolating a second plurality of analytes in a second biological sample of a healthy individual using an electrode array configured to generate an AC dielectrophoretic field; and (c) identifying a subset of the first plurality of analytes, the subset being quantitatively different in the first biological sample compared to the second biological sample and identified as associated with the disease state. Optionally, the isolating step includes using electrodes configured to generate low and high dielectrophoretic field regions. Optionally, the isolating step includes capturing the first plurality of analytes or the second plurality of analytes on one or more electrodes. Optionally, the subset includes mass spectrometry of the first plurality of analytes and the second plurality of analytes. Optionally, identifying the subset comprises quantifying each of the first plurality of analytes and the second plurality of analytes. Optionally, the analyte comprises a protein or polypeptide. Optionally, the analyte comprises a nucleic acid. Optionally, the analyte comprises an exosome. Optionally, the disease state is cancer, a neurological disease, an infectious disease, or an inflammatory disease. Optionally, the cancer is pancreatic cancer, ovarian cancer, bladder cancer, colon cancer, lung cancer, brain cancer, prostate cancer, breast cancer, skin cancer, lymphoma, tongue cancer, mouth cancer, pharyngeal cancer, oral cavity cancer. cancer), esophageal cancer, stomach cancer, small intestine cancer, colon cancer, rectal cancer, anal cancer, anorectal cancer, liver cancer, intrahepatic bile duct cancer, gallbladder cancer, biliary tract cancer, digestive cancer, laryngeal cancer, bronchial cancer, respiratory cancer, bone cancer, joint cancer, soft tissue cancer, heart cancer, melanoma, non-epithelial skin cancer, uterine cancer, cervical cancer, vulvar cancer, vaginal cancer, penile cancer, genital cancer, testicular cancer, kidney cancer, renal pelvis cancer, ureter cancer, urinary system cancer, eye cancer, orbital cancer, nervous system cancer, endocrine cancer, thyroid cancer, Hodgkin's lymphoma, non-Hodgkin's lymphoma, myeloma, acute lymphocytic leukemia, chronic lymphocytic leukemia, acute myeloid leukemia, chronic myeloid leukemia, or leukemia.

[0004] In another aspect, a method of analysis is provided that includes: (a) measuring the amount of an analyte in a biological sample from the individual; and (b) identifying the individual as at risk for developing a disease if the amount of the analyte is greater or less than that observed in a control sample, the analyte comprising one or more biomarkers identified by any of the methods provided herein. Optionally, the measuring step comprises isolating the analyte in the biological sample using an electrode array configured to generate an AC dielectrophoretic field. Optionally, the isolating step comprises using electrodes configured to generate low and high dielectrophoretic field regions. Optionally, the isolating step comprises capturing a first plurality of analytes or a second plurality of analytes on one or more electrodes. Optionally, the measuring step comprises mass spectrometry of the analyte. Optionally, the analyte comprises a protein or a polypeptide. Optionally, the analyte comprises a nucleic acid. Optionally, the analyte comprises an exosome. Optionally, the disease is cancer, a neurological disease, an infectious disease, or an inflammatory disease. Optionally, the cancer is pancreatic cancer, ovarian cancer, bladder cancer, colon cancer, lung cancer, brain cancer, prostate cancer, breast cancer, skin cancer, lymphoma, or leukemia.

[0005] In a further aspect, a method of identifying therapeutic targets is provided, the method comprising: (a) isolating a first plurality of analytes in a first biological sample of an individual known to have a disease state using an electrode array configured to generate an AC dielectrophoretic field; (b) isolating a second plurality of analytes in a second biological sample of a healthy individual using electrodes configured to generate an AC dielectrophoretic field; and (c) identifying a subset of the first plurality of analytes that is quantitatively different in the first biological sample compared to the second biological sample and is identified as a therapeutic target for drug discovery or development.

[0006] Incorporation by Reference All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. [Brief description of the drawings]

[0007] The patent or patent application file contains at least one drawing which shall be in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

[0008] The novel features of the invention are set forth with particularity in the appended claims. The features and advantages of the present invention will be better understood by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:

[0009] [Figure 1] (Left) A top perspective view of the assay cartridge, (center) visualization of blood cells separated from the sample away from the electrode, and (left) visualization of DNA and extracellular vesicles on the electrode. [Diagram 2] FIG. 1 shows the workflow of biomarker analysis: on the left, biomarkers isolated on electrodes, in the middle, various biomarkers to be analyzed, and on the right, modalities of downstream analysis, either off-chip or on-chip. [Diagram 3] FIG. 1 shows an example of a method for isolating nucleic acids from a cell. [Figure 4] FIG. 1 shows an example of a method for isolating extracellular nucleic acids from a cell-containing fluid. [Diagram 5] FIG. 1 shows a flow diagram for biomarker discovery. [Figure 6] (Left) Cluster diagram of exosomal proteins isolated from pancreatic cancer patients; (right) Heatmap of biomarkers over- and under-expressed in pancreatic cancer compared to healthy controls. [Figure 7]FIG. 1 shows subjects used in a multi-cancer study with samples from patients known to have cancer and healthy controls. [Figure 8] FIG. 1 shows the results of a multi-cancer study using samples from patients with confirmed cancer and healthy controls. [Figure 9A] Figure 9 shows an overview of the experiment: Figure 9A shows a workflow diagram. [Figure 9B] Figure 9B shows an overview of the experiment. Figure 9B shows the statistical approach to develop the EXPLORE test and evaluate its performance, where 100 iterations of randomly selected subjects were used for development (training set, 67% subjects) and performance evaluation (test set, 33% subjects). [Figure 9C] Figure 9C shows the relative concentrations of the 13 exoproteins used in the EXPLORE study by subject ID. Concentration levels were normalized to the highest concentration observed for each biomarker, with the lowest expression shown in white and the highest expression in green. [Figure 10A] Figure 10 shows the performance of the EXPLORE test. Figure 10A shows the ROC curves of the cancer cohort versus healthy controls, the black line represents the average curve of 100 iterations (gray line). The red diamond represents 99% specificity. [Figure 10B] Figure 10 shows the performance of the EXPLORE test: Figure 10B shows the proportion of cancer patients correctly classified by stage (sensitivity) with a specificity of >99%. [Figure 10C] Figure 10 shows the performance of the EXPLORE test. Figure 10C shows the proportion of cancer patients detected based on cancer type with a specificity of >99% (sensitivity). Error bars indicate 95% confidence intervals. [Figure 11A] Figure 11 shows the percentage of EXPLORE studies that were detected at <99% (top), 97% (middle), and 95% (bottom) for cancer subtypes. Figure 11A shows the percentage of pancreatic ductal adenocarcinomas detected at 21 stage I (96%, 97%, 98%) and 23 stage II (95%, 96%, 97%) cases. [Figure 11B]Figure 11B shows the percentage of EXPLORE studies that were detected in <99% (top), 97% (middle), and 95% (bottom) of cancer subtypes. Figure 11B shows the percentage of ovarian cancers detected in 37 stage I (65%, 69%, 76%) and 25 stage IA patients (66%, 69%, 75%), as well as 22 stage I and II serous adenocarcinoma patients (69%, 73%, 80%). [Figure 11C] Figure 11C shows the percentage of EXPLORE tests detected at less than 99% (top), 97% (middle), and 95% (bottom) for cancer subtypes. Figure 11C shows the percentage of bladder cancers detected at 27 stage I (56%, 61%, 67%), 15 low grade (52%, 58%, 68%), and 33 high grade (50%, 54%, 62%), both in stages I and II. Diamonds represent the mean values, respectively, and error bars represent 95% confidence intervals from 100 test intervals. [Figure 12A] Figure 12 shows the size distribution and particle concentration of exosomes isolated from healthy controls and cancer patients. Figure 12A shows the characterization of exosome samples by NTA analysis for particle size distribution. [Figure 12B] Figure 12B shows the size distribution and particle concentration of exosomes isolated from healthy controls and cancer patients. Figure 12B shows the characterization of exosome samples by NTA analysis for particle concentration. Median and range were calculated for healthy controls (green) and cancer patients (red). [Figure 13A] 13A-13C show heat maps of normalized concentration values ​​of proteins analyzed for cancer and healthy cohorts.FIG. 13A shows a heat map of exoproteins. [Figure 13B] Figure 13B shows a heat map of normalized concentration values ​​of proteins analyzed for cancer and healthy cohorts. Figure 13B shows a heat map of free proteins. Normalization is across cohorts for each marker. Each column represents a subject of the study. [Figure 14]Waterfall plot of protein biomarkers used in the assay. Values ​​are graded from high (left) to low (right). Each column represents an individual patient sample (red: cancer patients, green: healthy controls). [Figure 15] Figure 1 shows the performance of the EXPLORE test with exoproteins and free proteins. The ROC curves were generated using protein concentrations derived from exoproteins (black) or free proteins (orange) in plasma. The AUROCs are shown on the graphs by cohort with 95% confidence intervals. [Figure 16A] Figure 16 shows protein level correlations: Figure 16A shows the Pearson correlation coefficients of exosomal proteins. [Figure 16B] Correlation of protein levels: Figure 16B shows the Pearson correlation coefficient of free protein. [Figure 17] Schematic diagram of EV isolation workflow using AC electrokinetic (ACE) or ultracentrifugation. Top: Workflow using the Verita™ isolation platform. Plasma samples are flowed over an AC electrokinetic (ACE) microelectrode array, and EVs are collected on the electrodes. Unbound material is removed by buffer washes, the electric field is turned off, and EVs are eluted in buffer. Bottom: Workflow for differential ultracentrifugation. Plasma samples are diluted and large debris is pelleted by low-speed centrifugation. The supernatant is removed and subjected to two additional cycles of low-speed centrifugation. EVs in the clarified supernatant are then subjected to two rounds of ultracentrifugation, and finally the pellet is resuspended in buffer. [Figure 18A] Characterization of EVs isolated by ACE or differential ultracentrifugation. Figure 18A shows the distribution of particle sizes as determined by nanoparticle tracking analysis. Verita-isolated EVs are shown in blue and ultracentrifugation-isolated EVs in grey. [Figure 18B] Characterization of EVs isolated by ACE or differential ultracentrifugation (Figure 18B) shows the levels of remaining total contaminating proteins based on Qubit™ protein assay. [Figure 18C] Characterization of EVs isolated by ACE or differential ultracentrifugation. Figure 18C shows the difference between controls (left box) and cancer cases (right box) shown for biomarkers CA19-9 and CA125. Top: EVs isolated using the Verita™ system; bottom: EVs isolated by differential ultracentrifugation. [Figure 19] Figure 1 illustrates the development of a classification algorithm for early detection of multiple cancers. Biomarker selection is performed via Recursive Feature Reduction (REF) with cross-validation. After biomarker selection, the dataset is split into a training set and a test set. The training set is used to determine the coefficients in the logistic regression for each biomarker, and the test set is used to evaluate the performance of the logistic regression fit from the training set on a "hold-out" test set. Finally, the process of splitting the dataset into training and test sets is randomly repeated 100 times for performance validation. [Figure 20A] Figure 20 shows the overall performance for detecting the presence of early stage cancer using EV protein-based logistic classifiers. Figure 20A shows the ROC curves from the comparison of cancer cases and controls in the holdout test set, with the black line representing the average curve of 100 independently resampled holdout test sets (gray line). [Figure 20B] Figure 20B shows the overall performance for detecting the presence of early cancer using the EV protein-based logistic classifier. Figure 20B shows the stage-specific sensitivity at >99% specificity. The left bar represents the combined sensitivity for detecting stage I pancreatic, ovarian, and bladder cancer, and the right bar represents the combined sensitivity for detecting stage II of these cancers. [Figure 20C]Figure 20C shows the overall performance for detecting the presence of early cancer using EV protein-based logistic classifiers. Figure 20C shows the sensitivity by cancer type at >99% specificity. The left bar represents the sensitivity for detecting stage I and II pancreatic cancer, the middle bar represents the sensitivity for detecting stage I and II ovarian cancer, and the right bar represents the sensitivity for detecting stage I and II bladder cancer. Error bars represent two-sided 95% Wilson confidence intervals. [Figure 21A] Figure 21 shows the sensitivity at >99% specificity for detecting cancer using EV protein biomarkers. Figure 21A shows the sensitivity for detecting either stage I or stage II pancreatic cancer. Error bars represent two-sided 95% Wilson confidence intervals. [Figure 21B] Figure 21B shows the sensitivity at >99% specificity for detecting different cancers using EV protein biomarkers. Figure 21B shows the sensitivity for detecting either stage I or stage II ovarian cancer. Error bars represent two-sided 95% Wilson confidence intervals. [Figure 21C] Figure 21C shows the sensitivity at >99% specificity for detecting additional cancers using EV protein biomarkers. Figure 21C shows the sensitivity for detecting either stage I or stage II bladder cancer. Error bars represent two-sided 95% Wilson confidence intervals. [Figure 22A] Figure 22A shows a comparison of NTA results from controls and cancer cases. Figure 22A shows particle concentration of Verita purified EVs. The left box is EVs from a control sample, and the right box is EVs from a cancer case. [Figure 22B] Figure 22B shows a comparison of NTA results from controls and cancer cases. Figure 22B shows Verita purified EV particles, median particle size. The left box is EVs from a control sample, and the right box is EVs from a cancer case. [Figure 22C] Figure 22C shows a comparison of NTA results from a control and a cancer case. Figure 22C shows the overall particle size distribution of cancer and control. The top line is the EVs from the control sample, and the bottom line is the EVs from the cancer case. [Figure 23A]Figure 23 shows a comparison between EVs isolated using Verita™ or differential ultracentrifugation. Figure 23A shows particle size distributions for the control, and ovarian, bladder, and pancreatic cancer samples. The blue line is Verita-isolated EVs, and the gray line is EVs isolated by ultracentrifugation. [Figure 23B] Comparison of EVs isolated using Verita™ or differential ultracentrifugation. Figure 23B shows protein bioanalyzer dielectrophoresis patterns of selected samples. The blue dashed line indicates the protein size range for albumin (50-60 kDa), the green dashed line indicates the same range for fibrinogen (70-85 kDa), and the cyan dashed line indicates the range for IgG (140-180 kDa). [Figure 24A] Figure 24 shows a heatmap of normalized concentration values ​​of proteins analyzed for cancer and control cases. Figure 24A shows exoproteins. Normalization is across the cohort for each marker, with each column representing a subject in the study. [Figure 24B] Figure 24B shows a heatmap of normalized concentration values ​​of proteins analyzed for cancer and control cases. Figure 24B shows free protein. Normalization is across the cohort for each marker, with each column representing a subject in the study. [Diagram 25] FIG. 1 shows a comparison of EV protein concentrations for controls and cancer cases across all biomarkers selected in the model (controls are left boxes, cancer cases are right boxes). [Figure 26] FIG. 1 shows the Pearson correlation coefficients of selected biomarkers in the logistic classifier model. [Figure 27] Figure 13. ROC comparison of EV proteins vs. free proteins. ROC curves were generated using protein concentrations derived from exoproteins (black line) or free proteins (orange line) with selected biomarkers in a logistic classifier model. [Figure 28A]Assay performance with EVs spiked into K2EDTA plasma at known particle concentrations. (A) Concentrations of CA19-9 measured in H1975 EVs at three different particle concentrations show a linear response with input. K2EDTA plasma without EV spikes showed trace concentrations of the marker. [Figure 28B] (B) Performance of the assay with EVs spiked into K2EDTA plasma at known particle concentrations. (B) Quantitative detection of expected proteins based on EV type spiked into K2EDTA plasma. H1975 cell EVs are red markers, HeLa cell EVs are blue markers. [Figure 29A] Figure 29 shows Pearson correlation of protein levels.Figure 29A shows EV proteins. [Figure 29B] Figure 29B shows the Pearson correlation of protein levels. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Metastatic cancers are lethal, and pancreatic cancer, for example, is one of the most lethal cancers with a dismal 5-year survival rate of about 3%. In fact, pancreatic ductal adenocarcinoma (PDAC) will soon become the second leading cause of all cancer-related deaths in the United States. In contrast, the small number of patients (11%) diagnosed with localized disease have a 5-year survival rate of about 40%. Such a large survival difference between early and advanced stage disease is not unique to pancreatic cancer. The 5-year survival rate for metastatic ovarian cancer is notable at less than 31%, compared to 93% for about 15% of women with localized disease. Even with surgical management and adjuvant therapy, recurrence will occur in 80% of women with advanced disease, after which the malignancy cannot be cured any more. Similarly, in bladder cancer, detection of disease that has not spread beyond the lining of the bladder wall results in a 5-year survival rate of 96%. Importantly, surgical intervention may only require transurethral bladder tumour resection, whereas more invasive cancers may require radical removal of the entire bladder, so early detection has limited impact on quality of life.

[0011] As with many other malignancies, there are no approved screening modalities for these three cancers. Several emerging blood-based multi-cancer detection assays attempt to address early detection of these cancers by combining machine learning with DNA mutations / methylation and / or protein biomarkers. However, at the specificity required for widespread screening (>99%), many of these tests have demonstrated low sensitivity of 0% in stage I-II cancers (Liu, MC et al., "Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA." Annals of Oncology 31, 745-759 (2020); Cohen, JD et al., "Detection and localization of surgically resectable cancers with a multi-analyte blood test." Science 359, 926-930 (2018)). In recent years, proteins bound to exosomes (extracellular vesicles that mediate intercellular communication) have been shown to be promising biomarkers for identifying lung and pancreatic cancer (Hoshino, A. et al., "Extracellular Vesicle and Particle Biomarkers Define Multiple Human Cancers." Cell 182, 1044-1061. e1018 (2020)). However, exosome isolation required a cumbersome one-day ultracentrifugation process.The methods provided herein include the use of exosomes isolated using an AC electrokinetic platform, Verita™ (Hinestrosa, JP et al., "Simultaneous Isolation of Circulating Nucleic Acids and EV-Associated Protein Biomarkers From Unprocessed Plasma Using a AC Electrokinetics-Based Platform." Frontiers in Bioengineering and Biotechnology 8 (2020)), and the use of probed exosome-derived proteins (exoproteins), which enables the detection of pancreatic and brain cancer in a workflow of less than two hours.

[0012] Provided herein are systems and methods utilizing circulating markers, such as proteins associated with plasma exosomes, for use in multi-type cancer detection tests to identify stage I and II cancers. Optionally, the methods herein are useful for detecting pancreatic, ovarian, and bladder cancer. Optionally, the methods herein are useful for detecting cancers where early detection provides high clinical value. Optionally, the methods herein show reliable detection of early disease with an area under the curve (AUC) of 0.95 (95% confidence interval (CI) = 0.94-0.97). Optionally, the proportion of stage I disease detected with 99% specificity reached 97% for pancreatic, 65% for ovarian (66% for stage IA), and 56% for bladder cancer.

[0013] Provided herein are systems and methods for discovering biomarkers associated with disease states.

[0014] Also provided herein are a number of biomarkers useful for identifying individuals at risk for disease, or the prognosis or progression of disease in an individual.

[0015] In some embodiments, the methods, devices, or systems include isolating and / or identifying biomarkers from biological complexes, e.g., vesicles such as extracellular vesicles, exosomes, microvesicles, enveloped particles, and other complex particles or biological parcels that contain combinations of biological components including DNA, RNA, proteins, lipids, and other biological molecules. In some embodiments, the methods, devices, or systems described herein isolate biomarkers (e.g., DNA, RNA, nucleosomes, proteins, or cell membrane fragments) from exosomes isolated from a biological sample.

[0016] In some embodiments, the method, device, or system further comprises one or more of concentrating exosomes in a first dielectrophoretic field region (e.g., a high-field DEP region) and isolating biomarkers (e.g., DNA, RNA, nucleosomes, proteins, or cell membrane fragments) from the exosomes. In other embodiments, the method, device, or system comprises one or more of concentrating larger particles (e.g., cells) in a first dielectrophoretic field region (e.g., a low-field DEP region), concentrating exosomes in a second dielectrophoretic field region (e.g., a high-field DEP region), washing away cells and residual material, and isolating biomarkers from the exosomes. The methods also optionally include devices and / or systems capable of one or more of washing or otherwise removing residual (e.g., cellular) material from the exosomes (e.g., rinsing the array with water or buffer while the exosomes are concentrated and maintained within the high field DEP region of the array), optionally degrading residual proteins (e.g., residual proteins from lysed cells and / or other sources, such degradation occurring according to any suitable mechanism, such as with heat, proteases, or chemicals), washing the degraded proteins away from the nucleic acids, and collecting the exosomes. In some embodiments, the result of the methods, device operation, and system operation described herein is isolated microparticles (e.g., exosomes containing DNA, RNA, nucleosomes, proteins, cell membrane fragments), optionally in a quantity and purity suitable for further analysis (e.g., mass spectrometry, DNA sequencing).

[0017] An exemplary workflow is shown in FIG. 2. Biomarkers of a given size range are isolated using dielectrophoresis, and the captured analytes include, but are not limited to, exosomes (including exosomal proteins, RNA, and exosomal DNA), cell-free DNA, methylation markers, and / or plasma proteins. The isolated biomarkers are analyzed after being eluted from the chip or detected on the chip. A more detailed workflow is shown in FIG. 5. Samples from patients with various disease states, including, but not limited to, cancer, neurological disease, or infectious disease, are analyzed by isolating extracellular vesicles (i.e., exosomes) and cell-free DNA. The nucleic acids and cell-free DNA from the extracellular vesicles are analyzed by genomic profiling. The proteins from the extracellular vesicles are analyzed using proteomic methods. Analysis of these analytes and those from healthy controls is optionally performed using machine learning or deep learning algorithms to discover new biomarkers. Analysis of the biomarkers may include functional clustering and expression comparison (e.g., heatmaps) as shown in FIG. 6.

[0018] In some examples, it is advantageous that the method described herein is carried out in a short time, the device is operated in a short time, and the system is operated in a short time.In some embodiments, this period is short based on the "procedure time" measured from the time that fluid is added to the device to the time that isolated nucleic acid is obtained.In some embodiments, the procedure time is less than 3 hours, less than 2 hours, less than 1 hour, less than 30 minutes, less than 20 minutes, less than 10 minutes, or less than 5 minutes.

[0019] In another aspect, the period is short based on "hands-on time," measured as the cumulative amount of time a person must participate in the procedure from the time fluid is added to the device to the time isolated exosomes are obtained. In some embodiments, the hands-on time is less than 40 minutes, less than 20 minutes, less than 10 minutes, less than 5 minutes, less than 1 minute, or less than 30 seconds.

[0020] In some examples, it is advantageous that the devices described herein comprise a single container, the systems described herein comprise a device with a single container, and the methods described herein can be performed in a single container, such as the dielectrophoresis devices described herein. In some aspects, such single container embodiments minimize the number of fluid handling steps and / or are performed in a short time. In some examples, the methods, devices, and systems are contrasted with methods, devices, and systems that use one or more centrifugation steps and / or medium exchange. In some examples, centrifugation extends the amount of hands-on time required to isolate analytes or biomarkers from exosomes, including but not limited to DNA, RNA, nucleosomes, proteins, and / or cell membrane fragments. In another aspect, the single container procedure or device isolates analytes or biomarkers from exosomes (e.g., DNA, RNA, nucleosomes, proteins, and / or cell membrane fragments) using a minimal amount of consumable reagents.

[0021] Devices and Systems In some embodiments herein, devices are described for collecting exosome-derived biomarkers from fluids. In one aspect herein, devices are described for collecting biomarkers from fluids containing cells, acellular portions of fluids, or from other particulate material.

[0022] In some embodiments herein, a device for isolating cellular material is disclosed, the device comprising: a. a housing; b. a heater or heat source and / or reservoir containing a proteolytic agent; and c. a plurality of alternating current (AC) electrodes within the housing, the AC electrodes configured to be selectively excited to establish high and low AC electrokinetic field regions, whereby the AC electrokinetic effect results in the concentration of cells in the low field region of the device. In some embodiments, the plurality of electrodes are configured to be selectively excited to establish high and low dielectrophoretic field regions. In some embodiments, the proteolytic agent is a protease. In some embodiments, the proteolytic agent is proteinase K. In some embodiments, the device further comprises a second reservoir containing an elution agent.

[0023] In some embodiments herein, a device is disclosed comprising: a. a plurality of alternating current (AC) electrodes configured to be selectively excited to establish regions of high and low AC dynamic electric field; and b. a module capable of thermal cycling and performing PCR or other enzymatic reactions.

[0024] In some embodiments herein, a device is disclosed that includes: a. a plurality of alternating current (AC) electrodes configured to be selectively excited to establish high and low AC dynamic electric field regions; and b. a module capable of imaging material captured or sequestered by the AC electrodes. Some embodiments also include chambers and fluidics for the addition and removal of reagents that allow visualization of the captured material.

[0025] In some embodiments, the plurality of electrodes are configured to be selectively excited to establish high and low dielectric field regions. In some embodiments, the device is capable of isolating DNA, including cell-free DNA and DNA fragments, RNA, nucleosomes, exosomes, extracellular vesicles, proteins, cell membrane fragments, mitochondria, and cell vesicles, from biological samples, including fluids. In some embodiments, the device is capable of isolating these materials from cells in the biological sample. In some embodiments, the device is capable of performing PCR amplification or other enzymatic reactions. In some embodiments, DNA is isolated and PCR or other enzymatic reactions are performed in a single chamber. In some embodiments, DNA is isolated and PCR or other enzymatic reactions are performed in multiple regions of a single chamber. In some embodiments, DNA is isolated and PCR or other enzymatic reactions are performed in multiple chambers. In some embodiments, the biomarkers are eluted from the device for further analysis (e.g., mass spectrometry).

[0026] In some embodiments, the device further comprises at least one of an elution tube, a chamber, and a reservoir for carrying out PCR amplification or other enzymatic reactions. In some embodiments, the PCR amplification or other enzymatic reactions are carried out in a serpentine microchannel that includes multiple temperature zones. In some embodiments, the PCR amplification or other enzymatic reactions are carried out in an aqueous droplet confined in an immiscible fluid (i.e., digital PCR). In some embodiments, the thermal cycling comprises convection. In some embodiments, the device comprises a surface in contact with or in close proximity to the electrodes, the surface being functionalized with a biological ligand capable of selectively capturing biomolecules.

[0027] In some embodiments herein, a system for isolating cellular material from a biological sample is disclosed, the system comprising: a. a device comprising a plurality of alternating current (AC) electrodes, the AC electrodes configured to be selectively excited to establish high and low AC electrokinetic field regions, whereby the AC electrokinetic effect results in the concentration of cells in the high field regions of the device; and b. a sequencer, thermocycler, or other device for performing enzymatic reactions on the isolated or collected nucleic acids. In some embodiments, the plurality of electrodes are configured to be selectively excited to establish high and low dielectrophoretic field regions.

[0028] In various embodiments, the DEP field is created or can be created by selectively exciting an array of electrodes as described herein. The electrodes are made of any suitable material that is corrosion resistant, optionally including metals such as precious metals (e.g., platinum, platinum-iridium alloys, palladium, gold, etc.). In various embodiments, the electrodes are of any suitable size, any suitable orientation, any suitable spacing, that are or can be excited in any suitable manner such that suitable DEP and / or other electrokinetic fields are generated.

[0029] In some embodiments herein, methods, devices, and systems are described in which electrodes are arranged in separate chambers, and positive and negative DEP regions are generated in the inner chamber by passing AC DEP fields through pore or hole structures. Various geometric shapes are used to create the desired positive DEP (high electric field) and negative DEP (low electric field) regions to perform cell, microparticle, nanoparticle, and nucleic acid separation. In some embodiments, the pore or hole structures contain (or are filled with) porous materials (hydrogels) or are coated with porous membrane structures. In some embodiments, such pore / hole structure DEP devices reduce electrochemical action, heating, or chaotic fluid movement in the inner separation chamber during the DEP process by separating the electrodes into separate chambers.

[0030] In one aspect herein, a device is described that comprises electrodes, the electrodes are disposed in separate chambers, and the DEP field is generated in the inner chamber by passing through a pore structure. An exemplary device comprises a plurality of electrodes and electrode-containing chambers in a housing. The controller of the device independently controls the electrodes, as described in detail in International Publication WO2009 / 146143, which is incorporated herein by reference for disclosure.

[0031] In some embodiments, the chambered devices are fabricated with a variety of pore and / or hole structures (nanoscale, microscale, and even macroscale) and contain membranes, gels, or filtering materials that control, restrict, or prevent cells, nanoparticles, or other entities from diffusing or being transported into the inner chamber while AC / DC electric fields, solute molecules, buffers, and other small molecules can pass through the chamber.

[0032] In various embodiments, various configurations for the device are possible. For example, the device comprises a larger electrode array in a square or rectangular pattern configured to generate a repeating non-uniform electric field, for example to enable AC electrokinetics. For illustrative purposes only, suitable electrode arrays include, but are not limited to, a 10x10 electrode configuration, a 50x50 electrode configuration, a 10x100 electrode configuration, a 20x100 electrode configuration, or a 20x80 electrode configuration.

[0033] Such devices include, but are not limited to, devices with multiplexed electrodes and chambers, devices that allow for the generation of reconfigurable electric field patterns, devices that combine DC dielectrophoresis and fluidic processes, sample preparation devices, diagnostic devices including sample preparation, enzymatic manipulation of isolated nucleic acid molecules and subsequent detection and analysis, lab-on-a-chip devices, point-of-care, and other clinical diagnostic systems or versions.

[0034] In some embodiments, the planar platinum electrode array device comprises a housing through which the sample fluid flows. In some embodiments, the fluid flows from an inlet end to an outlet end, which optionally comprises a lateral analyte outlet. An exemplary device comprises a plurality of AC electrodes. In some embodiments, the sample consists of a combination of micron-sized entities or cells, larger nanoparticles, and smaller nanoparticles or biomolecules. In some examples, the larger nanoparticles are cell debris dispersed in the sample. In some embodiments, the smaller nanoparticles are proteins, smaller DNA, RNA, and cell fragments. In some embodiments, the planar electrode array device is a 60×20 electrode array, optionally partitioned into three 20×20 arrays that are separately controllable but simultaneously operable. The optional DC electrode can be switched to a negative charge, while the optional auxiliary DC electrode can be switched to a positive charge, for purposes of dielectrophoresis. In some examples, each of the controlled AC and DC systems is used in various embodiments both continuously and / or pulsed (e.g., each can be pulsed on and off for relatively short time intervals). An optional planar electrode array along the side of the sample flow is optionally used to generate DC dielectrophoretic forces as well as AC DEP when overlayered with a nanoporous material (e.g., a synthetic polymer hydrogel). In addition, a microdielectrophoretic separation process is optionally performed within the nanoporous layer using planar electrodes in the array and / or auxiliary electrodes in the xyz dimensions.

[0035] In various embodiments, the methods, devices, and systems are operated at an AC frequency range of 1,000 Hz to 100 MHz, voltages that may range from about 1 volt to 2000 volts pk-pk, DC voltages of 1 volt to 1000 volts, flow rates of 10 microliters per minute to 10 milliliters per minute, and temperatures ranging from 1° C. to 120° C. In some embodiments, the methods, devices, and systems are operated at an AC frequency range of about 3 to about 15 kHz. In some embodiments, the methods, devices, and systems are operated at voltages of 5 to 25 volts pk-pk. In some embodiments, the methods, devices, and systems are operated at voltages of about 1 to about 50 volts / cm. In some embodiments, the methods, devices, and systems are operated at DC voltages of about 1 to about 5 volts. In some embodiments, the methods, devices, and systems are operated at flow rates of about 10 microliters per minute to about 500 microliters per minute. In some embodiments, the methods, devices, and systems are operated at a temperature range of about 20° C. to about 60° C. In some embodiments, the methods, devices, and systems are operated at an AC frequency range of 1,000 Hz to 10 MHz. In some embodiments, the methods, devices, and systems are operated at an AC frequency range of 1,000 Hz to 1 MHz. In some embodiments, the methods, devices, and systems are operated at an AC frequency range of 1,000 Hz to 100 kHz. In some embodiments, the methods, devices, and systems are operated at an AC frequency range of 1,000 Hz to 10 kHz. In some embodiments, the methods, devices, and systems are operated at an AC frequency range of 10 kHz to 100 kHz. In some embodiments, the methods, devices, and systems are operated at an AC frequency range of 100 kHz to 1 MHz. In some embodiments, the methods, devices, and systems are operated at a pk-pk voltage of about 1 volt to 1500 volts. In some embodiments, the methods, devices, and systems are operated at a pk-pk voltage of about 1 volt to 1500 volts. In some embodiments, the methods, devices, and systems are operated at voltages between about 1 volt and 1000 volts pk-pk.In some embodiments, the methods, devices, and systems are operated at a voltage of about 1 volt to 500 volts pk-pk. In some embodiments, the methods, devices, and systems are operated at a voltage of about 1 volt to 250 volts pk-pk. In some embodiments, the methods, devices, and systems are operated at a voltage of about 1 volt to 100 volts pk-pk. In some embodiments, the methods, devices, and systems are operated at a voltage of about 1 volt to 50 volts pk-pk. In some embodiments, the methods, devices, and systems are operated at a DC voltage of 1 volt to 1000 volts. In some embodiments, the methods, devices, and systems are operated at a DC voltage of 1 volt to 500 volts. In some embodiments, the methods, devices, and systems are operated at a DC voltage of 1 volt to 250 volts. In some embodiments, the methods, devices, and systems are operated at a DC voltage of 1 volt to 100 volts. In some embodiments, the methods, devices, and systems are operated at a DC voltage of 1 volt to 50 volts. In some embodiments, the methods, devices, and systems are operated at a flow rate of 10 microliters per minute to 1 ml per minute. In some embodiments, the methods, devices, and systems are operated at a flow rate of 0.1 microliters per minute to 500 microliters per minute. In some embodiments, the methods, devices, and systems are operated at a flow rate of 0.1 microliters per minute to 250 microliters per minute. In some embodiments, the methods, devices, and systems are operated at a flow rate of 0.1 microliters per minute to 100 microliters per minute. In some embodiments, the methods, devices, and systems are operated at a temperature range of 1° C. to 100° C. In some embodiments, the methods, devices, and systems are operated at a temperature range of 20° C. to 95° C. In some embodiments, the methods, devices, and systems are operated at a temperature range of 25° C. to 100° C. In some embodiments, the methods, devices, and systems are operated at room temperature.

[0036] In some embodiments, the controller controls each of the electrodes independently, hi some embodiments, the controller is externally connected to the device, such as by a socket and plug connection, or is integrated into the device housing.

[0037] Also described herein are scaled and sectioned (xy-dimension) arrays of robust electrodes and strategically placed (xyz-dimension) arrangements of auxiliary electrodes that combine DEP, dielectrophoretic, and hydrodynamic forces, and their uses. In some embodiments, clinically relevant volumes of blood, serum, plasma, or other samples are further directly analyzed under higher ionic strength and / or conductivity conditions. Described herein are overlays of robust electrode structures (e.g., platinum, palladium, gold, etc.) with one or more porous material layers (natural or synthetic porous hydrogels, membranes, regulated nanoporous materials, and thin dielectric layered materials) to reduce the effects of any electrochemical (electrolysis) reactions, heating, and chaotic fluid movement that may occur on or near the electrodes, while still allowing effective separation of cells, bacteria, viruses, nanoparticles, exosomes, DNA, RNA, nucleosomes, extracellular vesicles, proteins, cell membrane fragments, mitochondria, and cell vesicles, and other biomolecules to be performed. In some embodiments, in addition to using AC frequency crossover to achieve higher resolution separation, on-device (on-array) DC microdielectrophoresis is used for secondary separation. For example, separation of DNA nanoparticles (20-50 kb), high molecular weight DNA (5-20 kb), medium molecular weight DNA (1-5 kb), and low molecular weight DNA (0.1-1 kb) fragments may be achieved by DC microdielectrophoresis on the array. In some embodiments, the device is further compartmentalized, optionally for the purpose of simultaneously performing co-separation of different blood cells, bacteria, and viruses, as well as DNA on the device.

[0038] In some embodiments, the device comprises a housing and a heater or heat source and / or reservoir containing a proteolytic agent. In some embodiments, the heater or heat source is capable of raising the temperature of the fluid to a desired temperature (e.g., about 30°C, 40°C, 50°C, 60°C, 70°C, etc., suitable for degrading proteins). In some embodiments, the heater or heat source is suitable for operation as a PCR thermocycler. In other embodiments, the heater or heat source is used to maintain a constant temperature (isothermal conditions). In some embodiments, the proteolytic agent is a protease. In other embodiments, the proteolytic agent is proteinase K, and the heater or heat source is used to inactivate the proteolytic agent.

[0039] In some embodiments, the device also includes a plurality of alternating current (AC) electrodes within the housing, the AC electrodes being configurable to be selectively excited to establish high and low dielectrophoretic (DEP) field regions, whereby an AC electrokinetic effect results in concentration of cells in the low field region of the device. In some embodiments, the electrodes are selectively excited to provide a first AC electrokinetic field region, and then, or sequentially, selectively excited to provide a second AC electrokinetic field region. For example, further description of electrodes and cell concentration in DEP fields can be found in International Publication No. WO 2009 / 146143, which is incorporated herein by reference for disclosure.

[0040] In some embodiments, the device includes a second reservoir containing an eluent. The eluent is any fluid suitable for eluting the isolated cellular material from the device. In some examples, the eluent is water or a buffer. In some examples, the eluent includes a reagent required for DNA sequencing. In some cases, the eluent includes a reagent required for mass spectrometry.

[0041] In some embodiments, the device includes multiple reservoirs, each containing a reagent useful for staining and washing the isolated cellular material in the device, examples include antibodies, oligonucleotides, probes, as well as dyes, buffers, washes, water, detergents, and solvents.

[0042] Also provided herein are systems and devices that include a plurality of alternating current (AC) electrodes configured to be selectively excited to establish regions of high and low dielectrophoretic (DEP) fields. In some examples, the AC electrokinetic effect results in the concentration of cells in the low field regions and / or the concentration (i.e., collection or isolation) of molecules (e.g., macromolecules such as nucleic acids) in the high electric field regions of the DEP field.

[0043] Also provided herein are systems and devices comprising a plurality of direct current (DC) electrodes. In some embodiments, the plurality of DC electrodes comprises at least two rectangular electrodes spanning an array. In some embodiments, the electrodes are located at the edges of the array. In some embodiments, the DC electrodes are interspersed between the AC electrodes.

[0044] In some embodiments, the systems or devices described herein comprise means for manipulating nucleic acids. In some embodiments, the systems or devices described herein comprise means for performing enzymatic reactions. In other embodiments, the systems or devices described herein comprise means for performing polymerase chain reactions, isothermal amplification, ligation reactions, restriction analysis, nucleic acid cloning, transcription or translation assays, or other enzyme-based molecular biology assays.

[0045] In some embodiments, the system or device described herein comprises a nucleic acid sequencer. The sequencer is optionally any suitable DNA sequencing device, including but not limited to a Sanger sequencer, a pyrosequencer, an ion semiconductor sequencer, a polony sequencer, a sequencing by ligation device, a DNA nanoball sequencing device, or a single molecule sequencing device.

[0046] In some embodiments, the systems or devices described herein are capable of maintaining a constant temperature. In some embodiments, the systems or devices described herein are capable of cooling the array or chamber. In some embodiments, the systems or devices described herein are capable of heating the array or chamber. In some embodiments, the systems or devices described herein comprise a thermocycler. In some embodiments, the devices disclosed herein comprise local temperature control elements. In some embodiments, the devices disclosed herein are capable of both sensing and controlling temperature.

[0047] In some embodiments, the device further comprises a heating or thermal element. In some embodiments, the heating or thermal element is localized under the electrodes. In some embodiments, the heating or thermal element comprises a metal. In some embodiments, the heating or thermal element comprises tantalum, aluminum, tungsten, or a combination thereof. Generally, the temperature achieved by the heating or thermal element is proportional to the current passing through it. In some embodiments, the devices disclosed herein comprise a localized cooling element. In some embodiments, a heat-resistant element is disposed beneath the exposed electrode array. In some embodiments, the devices disclosed herein are capable of achieving and maintaining a temperature between about 20°C and about 120°C. In some embodiments, the devices disclosed herein are capable of achieving and maintaining a temperature between about 30°C and about 100°C. In other embodiments, the devices disclosed herein are capable of achieving and maintaining a temperature between about 20°C and about 95°C. In some embodiments, the devices disclosed herein are capable of achieving and maintaining a temperature of between about 25° C. and about 90° C., between about 25° C. and about 85° C., between about 25° C. and about 75° C., between about 25° C. and about 65° C., or between about 25° C. and about 55° C. In some embodiments, the devices disclosed herein are capable of achieving and maintaining a temperature of about 20° C., about 30° C., about 40° C., about 50° C., about 60° C., about 70° C., about 80° C., about 90° C., about 100° C., about 110° C., or about 120° C.

[0048] An exemplary device is shown in Figure 1, where in the left panel the cartridge has a DEP electrode. Visualization of the electrode after separation shows that blood cells are clustering away from the electrode (middle panel). DNA and extracellular vesicles accumulating on the electrode are seen in the right panel.

[0049] electrode The multiple alternating current electrodes are optionally configured in any manner suitable for the separation processes described herein. For example, further description of systems or devices including electrodes and / or cell concentration in a DEP field can be found in WO 2009 / 146143, which is incorporated herein by reference for disclosure.

[0050] In some embodiments, the electrodes disclosed herein can include any suitable metal. In some embodiments, the electrodes can include, but are not limited to, aluminum, copper, carbon, iron, silver, gold, palladium, platinum, iridium, platinum-iridium alloys, ruthenium, rhodium, osmium, tantalum, titanium, tungsten, polysilicon, and indium tin oxide, or combinations thereof, as well as silicide materials such as platinum silicide, titanium silicide, gold silicide, or tungsten silicide. In some embodiments, the electrodes can include a screen-printable conductive ink.

[0051] In some embodiments, the ratio of the electrode edge-to-edge (E2E) to diameter is about 0.5 mm to about 5 mm. In some embodiments, the ratio of E2E to diameter is about 1 mm to about 4 mm. In some embodiments, the ratio of E2E to diameter is about 1 mm to about 3 mm. In some embodiments, the ratio of E2E to diameter is about 1 mm to about 2 mm. In some embodiments, the ratio of E2E to diameter is about 2 mm to about 5 mm. In some embodiments, the ratio of E2E to diameter is about 1 mm. In some embodiments, the ratio of E2E to diameter is about 2 mm. In some embodiments, the ratio of E2E to diameter is about 3 mm. In some embodiments, the ratio of E2E to diameter is about 4 mm. In some embodiments, the ratio of E2E to diameter is about 5 mm.

[0052] In some embodiments, the electrodes disclosed herein are dry etched. In some embodiments, the electrodes are wet etched. In some embodiments, the electrodes are subjected to a combination of dry and wet etching.

[0053] In some embodiments, the electrodes are individually controlled at each site.

[0054] In some embodiments, the array of electrodes is controlled together.

[0055] In some embodiments, a passivation layer is utilized. In some embodiments, the passivation layer can be formed from any suitable material known in the art. In some embodiments, the passivation layer comprises silicon nitride. In some embodiments, the passivation layer comprises silicon dioxide. In some embodiments, the passivation layer has a relative electrical permittivity of about 2.0 to about 8.0. In some embodiments, the passivation layer has a relative electrical permittivity of about 3.0 to about 8.0, about 4.0 to about 8.0, or about 5.0 to about 8.0. In some embodiments, the passivation layer has a relative electrical permittivity of about 2.0 to about 4.0. In some embodiments, the passivation layer has a relative electrical permittivity of about 2.0 to about 3.0. In some embodiments, the passivation layer has a relative electrical permittivity of about 2.0, about 2.5, about 3.0, about 3.5, or about 4.0.

[0056] In some embodiments, the passivation layer is between about 0.1 microns and about 10 microns thick. In some embodiments, the passivation layer is between about 0.5 microns and 8 microns thick. In some embodiments, the passivation layer is between about 1.0 microns and 5 microns thick. In some embodiments, the passivation layer is between about 1.0 microns and 4 microns thick. In some embodiments, the passivation layer is between about 1.0 microns and 3 microns thick. In some embodiments, the passivation layer is between about 0.25 microns and 2 microns thick. In some embodiments, the passivation layer is between about 0.25 microns and 1 micron thick.

[0057] In some embodiments, the passivation layer is comprised of any suitable insulating low-k dielectric material, including but not limited to silicon nitride and silicon dioxide. In some embodiments, the passivation layer is selected from the group consisting of polyamide, carbon doped silicon nitride, carbon doped silicon dioxide, fluorine doped silicon nitride, fluorine doped silicon dioxide, porous silicon dioxide, or any combination thereof. In some embodiments, the passivation layer can comprise a screen printable dielectric ink.

[0058] Electrode shape In some embodiments, the electrodes disclosed herein can be arranged in any manner suitable for carrying out the methods disclosed herein.

[0059] In some embodiments, the electrodes are in a dot configuration, e.g., the electrodes have a generally circular or circular configuration. In some embodiments, the orientation angle between the dots is about 25° to about 60°. In some embodiments, the orientation angle between the dots is about 30° to about 55°. In some embodiments, the orientation angle between the dots is about 30° to about 50°. In some embodiments, the orientation angle between the dots is about 35° to about 45°. In some embodiments, the orientation angle between the dots is about 25°. In some embodiments, the orientation angle between the dots is about 30°. In some embodiments, the orientation angle between the dots is about 35°. In some embodiments, the orientation angle between the dots is about 40°. In some embodiments, the orientation angle between the dots is about 45°. In some embodiments, the orientation angle between the dots is about 50°. In some embodiments, the orientation angle between the dots is about 55°. In some embodiments, the orientation angle between the dots is about 60°.

[0060] In some embodiments, the electrodes are in a substantially rectangular configuration.

[0061] In some embodiments, the electrodes are in a configuration resembling a wavy or non-linear line. In some embodiments, the array of electrodes is in a wavy or non-linear line configuration, which includes repeating units comprising a shape of pairs of dots connected by a linker, the dots and linkers defining the boundaries of the electrodes, the linkers tapering inward toward or at the midpoint between the pairs of dots, the diameter of the dots is the widest point along the length of the repeating unit, and the end-to-end distance between the parallel sets of repeating units is equidistant or nearly equidistant. In some embodiments, the electrodes are strips resembling wavy lines as shown in FIG. 8. In some embodiments, the edge-to-edge distance between the electrodes is equidistant or nearly equidistant throughout the wavy line configuration. In some embodiments, the use of wavy line electrodes disclosed herein enhances the gradient of the DEP field.

[0062] In some embodiments, the electrodes disclosed herein are in a planar configuration. In some embodiments, the electrodes disclosed herein are in a non-planar configuration.

[0063] In some embodiments, the devices disclosed herein selectively capture biomolecules on their surfaces. For example, the devices disclosed herein may capture biomolecules such as nucleic acids, for example, by a. nucleic acid hybridization, b. antibody-antibody interaction, c. biotin-avidin interaction, d. ionic or electrostatic interaction, or e. any combination thereof. Thus, the devices disclosed herein may incorporate functionalized surfaces that include capture molecules such as complementary nucleic acid probes, antibodies, or other protein captures capable of capturing biomolecules (such as nucleic acids), biotin, or other anchored captures capable of capturing complementary target molecules such as avidin, capture molecules capable of capturing biomolecules (such as nucleic acids) by ionic or electrostatic interaction, or any combination thereof.

[0064] In some embodiments, the surface is functionalized to minimize and / or inhibit non-specific binding interactions by a. polymers (e.g., polyethylene glycol PEG), b. ionic or electrostatic interactions, c. surfactants, or d. any combination thereof. In some embodiments, the methods disclosed herein include the use of additives that reduce non-specific binding interactions by interfering with such interactions, such as Tween 20, bovine serum albumin, non-specific immunoglobulins, etc.

[0065] In some embodiments, the device comprises multiple microelectrode devices oriented (a) side-by-side, (b) facing vertically, or (c) facing horizontally, hi other embodiments, the electrodes are in a sandwich configuration, e.g., stacked on top of each other in a vertical format.

[0066] Hydrogels Covering the electrode structure with one or more layers of material can reduce harmful electrochemical effects, including but not limited to electrolysis reactions, heating, and chaotic fluid movement that may occur on or near the electrodes, while still allowing effective separation of cells, bacteria, viruses, nanoparticles, DNA, and other biomolecules. In some embodiments, the material layered on the electrode structure can be one or more porous layers. In other embodiments, the one or more porous layers are polymeric layers. In other embodiments, the one or more porous layers are hydrogels.

[0067] Generally, hydrogels must have sufficient mechanical strength and be relatively chemically inert so that they can withstand the electrochemical effects at the electrode surface without reorganization or degradation. Generally, hydrogels are sufficiently permeable to small amounts of aqueous ions, but keep biomolecules away from the electrode surface.

[0068] In some embodiments, the hydrogel is a monolayer or a coating.

[0069] In some embodiments, the hydrogel comprises a porosity gradient, where the bottom of the hydrogel layer is more porous than the top of the hydrogel layer.

[0070] In some embodiments, the hydrogel comprises multiple layers or coatings. In some embodiments, the hydrogel comprises two coatings. In some embodiments, the hydrogel comprises three coatings. In some embodiments, the bottom (first) coating is more porous than the subsequent coatings. In some embodiments, the top coating is less porous than the first coating. In some embodiments, the top coating has an average pore size that serves as a size cut-off for particles greater than 100 picometers in diameter.

[0071] In some embodiments, the hydrogel has a conductivity of about 0.001 S / m to about 10 S / m. In some embodiments, the hydrogel has a conductivity of about 0.01 S / m to about 10 S / m. In some embodiments, the hydrogel has a conductivity of about 0.1 S / m to about 10 S / m. In some embodiments, the hydrogel has a conductivity of about 1.0 S / m to about 10 S / m. In some embodiments, the hydrogel has a conductivity of about 0.01 S / m to about 5 S / m. In some embodiments, the hydrogel has a conductivity of about 0.01 S / m to about 4 S / m. In some embodiments, the hydrogel has a conductivity of about 0.01 S / m to about 3 S / m. In some embodiments, the hydrogel has a conductivity of about 0.01 S / m to about 2 S / m. In some embodiments, the hydrogel has a conductivity of about 0.1 S / m to about 5 S / m. In some embodiments, the hydrogel has a conductivity of about 0.1 S / m to about 4 S / m. In some embodiments, the hydrogel has a conductivity of about 0.1 S / m to about 3 S / m. In some embodiments, the hydrogel has a conductivity of about 0.1 S / m to about 2 S / m. In some embodiments, the hydrogel has a conductivity of about 0.1 S / m to about 1.5 S / m. In some embodiments, the hydrogel has a conductivity of about 0.1 S / m to about 1.0 S / m.

[0072] In some embodiments, the hydrogel has a conductivity of about 0.1 S / m. In some embodiments, the hydrogel has a conductivity of about 0.2 S / m. In some embodiments, the hydrogel has a conductivity of about 0.3 S / m. In some embodiments, the hydrogel has a conductivity of about 0.4 S / m. In some embodiments, the hydrogel has a conductivity of about 0.5 S / m. In some embodiments, the hydrogel has a conductivity of about 0.6 S / m. In some embodiments, the hydrogel has a conductivity of about 0.7 S / m. In some embodiments, the hydrogel has a conductivity of about 0.8 S / m. In some embodiments, the hydrogel has a conductivity of about 0.9 S / m. In some embodiments, the hydrogel has a conductivity of about 1.0 S / m.

[0073] In some embodiments, the hydrogel has a thickness of about 0.1 microns to about 10 microns. In some embodiments, the hydrogel has a thickness of about 0.1 microns to about 5 microns. In some embodiments, the hydrogel has a thickness of about 0.1 microns to about 4 microns. In some embodiments, the hydrogel has a thickness of about 0.1 microns to about 3 microns. In some embodiments, the hydrogel has a thickness of about 0.1 microns to about 2 microns. In some embodiments, the hydrogel has a thickness of about 1 micron to about 5 microns. In some embodiments, the hydrogel has a thickness of about 1 micron to about 4 microns. In some embodiments, the hydrogel has a thickness of about 1 micron to about 3 microns. In some embodiments, the hydrogel has a thickness of about 1 micron to about 2 microns. In some embodiments, the hydrogel has a thickness of about 0.5 microns to about 1 micron.

[0074] In some embodiments, the viscosity of the hydrogel solution prior to spin coating ranges from about 0.5 cP to about 5 cP. In some embodiments, a single coating of hydrogel solution has a viscosity of about 0.75 cP to 5 cP prior to spin coating. In some embodiments, in a multi-layer hydrogel, the first hydrogel solution has a viscosity of about 0.5 cP to about 1.5 cP prior to spin coating. In some embodiments, the second hydrogel solution has a viscosity of about 1 cP to about 3 cP. The viscosity of the hydrogel solution is based on the polymer concentration in the solvent (0.1% to 10%) and the polymer molecular weight (10,000 to 300,000), as well as the starting viscosity of the solvent.

[0075] In some embodiments, the first hydrogel coating has a thickness between about 0.5 microns and 1 micron. In some embodiments, the first hydrogel coating has a thickness between about 0.5 microns and 0.75 microns. In some embodiments, the first hydrogel coating has a thickness between about 0.75 and 1 micron. In some embodiments, the second hydrogel coating has a thickness between about 0.2 microns and 0.5 microns. In some embodiments, the second hydrogel coating has a thickness between about 0.2 and 0.4 microns. In some embodiments, the second hydrogel coating has a thickness between about 0.2 microns and 0.3 microns. In some embodiments, the second hydrogel coating has a thickness between about 0.3 and 0.4 microns.

[0076] In some embodiments, the hydrogel comprises any suitable synthetic polymer that forms a hydrogel. In general, any sufficiently hydrophilic and polymerizable molecule may be utilized in the manufacture of synthetic polymer hydrogels for use as disclosed herein. The polymerizable moieties in the monomer may include, but are not limited to, substituted or unsubstituted α, β, unsaturated carbonyls that are double bonded to oxygen and directly bonded to a carbon that is single bonded to another oxygen, nitrogen, sulfur, halogen, or carbon; vinyls that are single bonded to oxygen, nitrogen, halogen, phosphorus, or sulfur; allyls that are single bonded to a carbon that is single bonded to oxygen, nitrogen, halogen, phosphorus, or sulfur; homoallyls that are single bonded to a carbon that is single bonded to another carbon that is single bonded to oxygen, nitrogen, halogen, phosphorus, or sulfur; and alkynyl moieties in which a triple bond exists between two carbon atoms. In some embodiments, acryloyl or acrylamide monomers such as acrylates, methacrylates, acrylamides, methacrylamides, etc. are useful in the formation of hydrogels as disclosed herein. More preferred acrylamide monomers include acrylamide, N-substituted acrylamide, N-substituted methacrylamide, and methacrylamide. In some embodiments, the hydrogel comprises a polymer such as an epoxide-based polymer, a vinyl-based polymer, an allylic-based polymer, a homoallylic-based polymer, a cyclic anhydride-based polymer, an ester-based polymer, an ether-based polymer, an alkylene glycol-based polymer (e.g., polypropylene glycol), and the like.

[0077] In some embodiments, the hydrogel comprises polyhydroxyethyl methacrylate (pHEMA), cellulose acetate, cellulose acetate phthalate, cellulose acetate butyrate, or any suitable acrylamide or vinyl based polymer, or derivatives thereof.

[0078] In some embodiments, the hydrogel is applied by vapor deposition.

[0079] In some embodiments, the hydrogel is polymerized via atom transfer radical polymerization (ATRP).

[0080] In some embodiments, the hydrogel is polymerized via reversible addition-fragmentation chain transfer (RAFT) polymerization.

[0081] In some embodiments, additives are added to the hydrogel to increase the conductivity of the gel. In some embodiments, the hydrogel additive is a conductive polymer (e.g., PEDOT:PSS), a salt (e.g., copper chloride), a metal (e.g., gold), a plasticizer (e.g., PEG200, PEG400, or PEG600), or a cosolvent.

[0082] In some embodiments, the hydrogel also contains compounds or materials that help maintain the stability of DNA hybrids, including, but not limited to, histidine, histidine peptides, polyhistidine, lysine, lysine peptides, and other cationic compounds or substances.

[0083] Dielectrophoretic field In some embodiments, the methods, devices, and systems described herein provide mechanisms for collecting, separating, and / or isolating cells, particles, and / or molecules (e.g., exosomes, DNA, RNA, nucleosomes, extracellular vesicles, proteins, cell membrane fragments, mitochondria, and cellular vesicles) from fluid materials (optionally containing other substances such as contaminants and residual cellular material).

[0084] In some embodiments, an AC electric field is generated to collect, separate, or isolate biomolecules such as exosomes, DNA, RNA, nucleosomes, extracellular vesicles, proteins, cell membrane fragments, mitochondria, and cellular vesicles. In some embodiments, the AC electric field is a dielectrophoretic field. Thus, in some embodiments, dielectrophoresis (DEP) is utilized in various steps of the methods described herein.

[0085] In some embodiments, the devices and systems described herein are capable of generating DEP fields, etc. In certain embodiments, DEP is used to concentrate cells and / or nucleic acids (e.g., at the same time or at different times). In certain embodiments, the methods described herein further include exciting the array of electrodes to generate a first, second, and any additional optional DEP fields. In some embodiments, the devices and systems described herein are capable of being energized to generate a first, second, and any additional optional DEP fields.

[0086] DEP is a phenomenon in which a force is applied to a dielectric particle when it is exposed to a non-uniform electric field. Depending on the steps of the methods described herein, the aspects of the devices and systems described herein, etc., the dielectric particles in various embodiments herein are biological cells and / or molecules such as nucleic acid molecules. Various steps of the methods described herein, or aspects of the devices or systems described herein, may be used to isolate and separate various components, such as intact cells or other specific materials. Furthermore, different electric field regions of the DEP field may be used in various steps of the methods described herein, or aspects of the devices and systems. This dielectrophoretic force does not require charging of the particles. In some instances, the strength of the force depends on the electric properties of the medium and the specific particle, the shape and size of the particle, and the frequency of the electric field. In some instances, an electric field with a specific frequency selectivity manipulates the particles. In certain aspects described herein, these processes allow cells and / or smaller particles (such as molecules, including nucleic acid molecules) to be separated from other components (e.g., those in a fluid medium) or from each other.

[0087] In various embodiments provided herein, the methods or devices described herein include producing a plurality of DEP field regions. For example, the methods or devices include a first DEP field region and a second DEP field region having an array. In various embodiments provided herein, the devices or systems described herein are capable of producing a first DEP field region and a second DEP field region having an array. In some examples, the first and second electric field regions are part of a single field (e.g., the first and second regions exist simultaneously but are found in different locations within the device and / or on the array). In some embodiments, the first and second electric field regions are different electric fields (e.g., the first region is created by energizing an electrode at a first time and the second region is created by energizing an electrode at a second time). In certain aspects, the first DEP field region is suitable for concentrating or isolating cells (e.g., into a low DEP field region). In some embodiments, the second DEP field region is suitable for concentrating smaller particles, such as molecules (e.g., nucleic acids, including cell-free nucleic acids), e.g., toward the high DEP field region. In some examples, the methods described herein optionally exclude the use of either the first or second DEP field regions.

[0088] As described below, in some examples, the first DEP field is suitable for concentrating or isolating nucleic acids, including cell-free nucleic acids, that are greater than a certain size, smaller than a certain size, or within a certain size range.In some examples, the second DEP field is suitable for concentrating or isolating nucleic acids, including cell-free nucleic acids, that are greater than a certain size, smaller than a certain size, or within a certain size range.The first and second DEP fields can be configured to concentrate or isolate nucleic acids of the same or different sizes.Therefore, the methods and devices disclosed herein can be used to evaluate nucleic acids of various different sizes.

[0089] Also described herein are embodiments that include three or more DEP field regions, each of which can be configured to operate with the same or different number of electric field regions as at least one other electric field region. Thus, the embodiments can concentrate or isolate different materials in a biological sample based on different properties. For example, a first DEP field region can be configured to isolate cells, a second DEP field region can be configured to isolate or concentrate cell-free DNA greater than 500 bp, a third DEP field region can be configured to isolate or concentrate cell-free DNA between 300 bp and 500 bp, and a fourth DEP field region can be configured to isolate or concentrate cell-free DNA less than 300 bp. Some of such embodiments can include quantifying the amount of DNA isolated or concentrated within each electric field region.

[0090] In some embodiments, the first DEP field region is in the same chamber as the second DEP field region in the devices disclosed herein, hi some embodiments, the first DEP field region and the second DEP field region occupy the same region of the electrode array.

[0091] In some embodiments, the first DEP field region is in a separate chamber or in an entirely separate device from the second DEP field region in the devices disclosed herein.

[0092] First DEP field region In some embodiments, for example in high conductance buffers (greater than 100 mS / m), the methods described herein include applying a fluid containing cells or other particulate material to a device comprising an electrode array, thereby concentrating the cells at the first DEP field region. In some embodiments, the devices and systems described herein are capable of applying a fluid containing cells or other particulate material to a device comprising an electrode array, thereby concentrating the cells at the first DEP field region. Thereafter or simultaneously, the second or optionally the third and fourth DEP regions may collect or isolate other fluid components, including biomolecules such as nucleic acids.

[0093] The first DEP field region may be any field region suitable for concentrating cells from a fluid. In this application, the cells are generally concentrated near the electrode array. In some embodiments, the first DEP field region is a low dielectrophoretic field region. In some embodiments, the first DEP field region is a high dielectrophoretic field region. In some aspects, for example in a low conductance buffer (less than 100 mS / m), the methods described herein include applying a fluid containing cells to a device comprising an electrode array, thereby concentrating the cells or other particulate material in the first DEP field region.

[0094] In some aspects, the devices and systems described herein are capable of applying a fluid containing cells or other particulate material to a device comprising an electrode array and concentrating the cells in a first DEP field region. In various embodiments, the first DEP field region may be any electric field region suitable for concentrating cells from a fluid. In some embodiments, the cells are concentrated on the electrode array. In some embodiments, the cells are trapped in a high dielectrophoretic field region. In some embodiments, the cells are trapped in a low dielectrophoretic field region. The trapping of high and low electric fields depends on the conductivity of the fluid as a whole, and generally the intersection point is between about 300-500 mS / m. In some embodiments, the first DEP field region is a low dielectrophoretic field region implemented with a fluid conductivity of greater than about 300 mS / m. In some embodiments, the first DEP field region is a low dielectrophoretic field region implemented with a fluid conductivity of less than about 300 mS / m. In some embodiments, the first DEP field region is a high dielectrophoretic field region implemented at a fluid conductivity greater than about 300 mS / m. In some embodiments, the first DEP field region is a high dielectrophoretic field region implemented at a fluid conductivity less than about 300 mS / m. In some embodiments, the first DEP field region is a low dielectrophoretic field region implemented at a fluid conductivity greater than about 500 mS / m. In some embodiments, the first DEP field region is a low dielectrophoretic field region implemented at a fluid conductivity less than about 500 mS / m. In some embodiments, the first DEP field region is a high dielectrophoretic field region implemented at a fluid conductivity greater than about 500 mS / m. In some embodiments, the first DEP field region is a high dielectrophoretic field region implemented at a fluid conductivity less than about 500 mS / m.

[0095] In some embodiments, the first dielectrophoretic field region is produced by an alternating current. The alternating current has any amperage, voltage, frequency, etc. suitable for concentrating cells. In some embodiments, the first dielectrophoretic field region is produced using an alternating current having an amperage of 0.1 microamps to 10 amps, a peak-to-peak voltage of 1 to 50 volts, and / or a frequency of 1 to 10,000,000 Hz. In some embodiments, the first DEP field region is produced using an alternating current having a peak-to-peak voltage of 5 to 25 volts. In some embodiments, the first DEP field region is produced using an alternating current having a frequency of 3 to 15 kHz. In some embodiments, the first DEP field region is produced using an alternating current having an amperage of 1 milliamp to 1 amp. In some embodiments, the first DEP field region is produced using an alternating current having an amperage of 0.1 microamps to 1 amp. In some embodiments, the first DEP field region is produced using an alternating current having an amperage of 1 microamp to 1 amp. In some embodiments, the first DEP field region is produced using an alternating current having an amperage of 100 microamps to 1 amp. In some embodiments, the first DEP field region is produced using an alternating current having an amperage of 500 microamps to 500 milliamps. In some embodiments, the first DEP field region is produced using an alternating current having a peak-to-peak voltage of 1 to 25 volts. In some embodiments, the first DEP field region is produced using an alternating current having a peak-to-peak voltage of 1 to 10 volts. In some embodiments, the first DEP field region is produced using an alternating current having a peak-to-peak voltage of 25 to 50 volts. In some embodiments, the first DEP field region is produced using a frequency of 10 to 1,000,000 Hz. In some embodiments, the first DEP field region is produced using a frequency between 100 and 100,000 Hz. In some embodiments, the first DEP field region is produced using a frequency between 100 and 10,000 Hz. In some embodiments, the first DEP field region is produced using a frequency between 10,000 and 100,000 Hz.In some embodiments, the first DEP field region is produced using a frequency between 100,000 and 1,000,000 Hz.

[0096] In some embodiments, the first dielectrophoretic field region is produced by direct current. The direct current has any amperage, voltage, frequency, etc. suitable for concentrating cells. In some embodiments, the first dielectrophoretic field region is produced using direct current having an amperage of 0.1 microamps to 1 amp, a voltage of 10 millivolts to 10 volts, and / or a pulse width of 1 millisecond to 1000 seconds and a pulse frequency of 0.001 to 1000 Hz. In some embodiments, the first DEP field region is produced using direct current having an amperage of 1 microamp to 1 amp. In some embodiments, the first DEP field region is produced using direct current having an amperage of 100 microamps to 500 milliamps. In some embodiments, the first DEP field region is produced using direct current having an amperage of 1 milliamp to 1 amp. In some embodiments, the first DEP field region is produced using a direct current having an amperage of 1 microamp to 1 milliamp. In some embodiments, the first DEP field region is produced using a direct current having a pulse width of 500 milliseconds to 500 seconds. In some embodiments, the first DEP field region is produced using a direct current having a pulse width of 500 milliseconds to 100 seconds. In some embodiments, the first DEP field region is produced using a direct current having a pulse width of 1 second to 1000 seconds. In some embodiments, the first DEP field region is produced using a direct current having a pulse width of 500 milliseconds to 1 second. In some embodiments, the first DEP field region is produced using a pulse frequency of 0.01 to 1000 Hz. In some embodiments, the first DEP field region is produced using a pulse frequency of 0.1 to 100 Hz. In some embodiments, the first DEP field region is produced using a pulse frequency of 1 to 100 Hz. In some embodiments, the first DEP field region is produced using a pulse frequency of 100-1000 Hz.

[0097] In some embodiments, the fluid contains a mixture of cell types. For example, blood contains red blood cells and white blood cells. Environmental samples contain many types of cells and other particulate material over a wide range of concentrations. In some embodiments, one cell type (or any number of cell types that is less than the total number of cell types that comprise the sample) is preferentially enriched in the first DEP field. Without being limited thereto, this embodiment may be useful for focusing a nucleic acid isolation procedure on a particular environmental contaminant, such as E. coli in feces, whereby DNA sequencing may be used to identify the source of the contaminant. In another non-limiting example, the first DEP field is operated in a manner that specifically enriches viruses but not cells (e.g., in a fluid with a conductivity greater than 300 mS / m, viruses will concentrate in high DEP field regions, while larger cells will concentrate in low DEP field regions).

[0098] In some embodiments, the methods, devices, or systems described herein are suitable for isolating or separating specific cell types. In some embodiments, the DEP field of the methods, devices, or systems is specifically tailored to allow for separation or concentration of specific types of cells into the field region of the DEP field. In some embodiments, the methods, devices, or systems described herein provide more than one field region in which more than one type of cell is isolated or concentrated. In some embodiments, the methods, devices, or systems described herein are adjustable to allow for isolation or concentration of different types of cells within the DEP field region. In some embodiments, the methods provided herein further include tuning the DEP field. In some embodiments, the devices or systems provided herein can have a tuned DEP field. In some examples, such tuning can be in providing a DEP field that is specifically suited for a desired purpose. For example, alterations in the array, energy, or another parameter are optionally utilized to tune the DEP field. Tuning parameters for finer resolution include electrode diameter, edge-to-edge distance between electrodes, voltage, frequency, fluid conductivity, and hydrogel composition.

[0099] In some embodiments, the first DEP field region includes the entire electrode array. In some embodiments, the first DEP field region includes a portion of the electrode array. In some embodiments, the first DEP field region includes about 90%, about 80%, about 70%, about 60%, about 50%, about 40%, about 30%, about 25%, about 20%, or about 10% of the electrode array. In some embodiments, the first DEP field region includes about one-third of the electrode array.

[0100] Second DEP field region The second DEP field region can be configured to be the same or different from the first DEP field region. As described above, the second DEP field region can be configured to isolate or concentrate the same or different macromolecules and cellular components as the first DEP field region. These include macromolecules, and cellular components include exosomes, DNA, RNA, nucleosomes, extracellular vesicles, proteins, cell membrane fragments, mitochondria, and cell vesicles.

[0101] In some aspects, the first DEP field region and the second DEP field region can be configured to isolate or concentrate different subsets of the same type of macromolecule or cellular component. For example, in some embodiments, the first DEP field region can be configured to isolate or concentrate a first macromolecule or a first cellular component of a first size or a first size range, and the second DEP field region can be configured to isolate or concentrate a first macromolecule or a first cellular component of a second size or a second size range. In one example, the first DEP field region can be configured to isolate or concentrate cell-free DNA between 300-500 bp, and the second DEP field region can be configured to isolate or concentrate cell-free DNA less than 300 bp. Thus, multiple electric field regions can be used to distinguish subsets of the same type of macromolecule or cellular component. In an exemplary advantage, the use of multiple electric field regions can also enable quantification of one or more subsets of the same type of macromolecule or cellular component.

[0102] In one aspect, following lysis of the cells (as provided below), the methods described herein include concentrating the nucleic acid at a second DEP field region. In another aspect, the devices and systems described herein are capable of concentrating the nucleic acid at a second DEP field region. In some embodiments, the second DEP field region is any field region suitable for concentrating nucleic acid. In some embodiments, the nucleic acid is concentrated on an electrode array. In some embodiments, the second DEP field region is a high dielectrophoretic field region. The second DEP field region is optionally the same as the first DEP field region.

[0103] In some embodiments, the second dielectrophoretic field region is produced by an alternating current. In some embodiments, the alternating current has any amperage, voltage, frequency, etc. suitable for concentrating nucleic acids. In some embodiments, the second dielectrophoretic field region is produced using an alternating current having an amperage of 0.1 microamps to 10 amps, a peak-to-peak voltage of 1 to 50 volts, and / or a frequency of 1 to 10,000,000 Hz. In some embodiments, the second DEP field region is produced using an alternating current having an amperage of 0.1 microamps to 1 amp. In some embodiments, the second DEP field region is produced using an alternating current having an amperage of 1 microamp to 1 amp. In some embodiments, the second DEP field region is produced using an alternating current having an amperage of 100 microamps to 1 amp. In some embodiments, the second DEP field region is produced using an alternating current having an amperage of 500 microamps to 500 milliamps. In some embodiments, the second DEP field region is produced using an alternating current having a peak-to-peak voltage of 1-25 volts. In some embodiments, the second DEP field region is produced using an alternating current having a peak-to-peak voltage of 1-10 volts. In some embodiments, the second DEP field region is produced using an alternating current having a peak-to-peak voltage of 25-50 volts. In some embodiments, the second DEP field region is produced using a frequency of 10-1,000,000 Hz. In some embodiments, the second DEP field region is produced using a frequency of 100-100,000 Hz. In some embodiments, the second DEP field region is produced using a frequency of 100-10,000 Hz. In some embodiments, the second DEP field region is produced using a frequency of 10,000-100,000 Hz. In some embodiments, the second DEP field region is produced using a frequency between 100,000 and 1,000,000 Hz.

[0104] In some embodiments, the second dielectrophoretic field region is produced by direct current. In some embodiments, the direct current has any amperage, voltage, frequency, etc. suitable for concentrating nucleic acids. In some embodiments, the second dielectrophoretic field region is produced using direct current having an amperage of 0.1 microamps to 1 amp, a voltage of 10 millivolts to 10 volts, and / or a pulse width of 1 millisecond to 1000 seconds and a pulse frequency of 0.001 to 1000 Hz. In some embodiments, the second DEP field region is produced using alternating current having a peak-to-peak voltage of 5 to 25 volts. In some embodiments, the second DEP field region is produced using alternating current having a frequency of 3 to 15 kHz. In some embodiments, the second DEP field region is produced using alternating current having an amperage of 1 milliamp to 1 amp. In some embodiments, the second DEP field region is produced using direct current having an amperage of 1 microamp to 1 amp. In some embodiments, the second DEP field region is produced using a direct current having an amperage of 100 microamps to 500 milliamps. In some embodiments, the second DEP field region is produced using a direct current having an amperage of 1 milliamp to 1 amp. In some embodiments, the second DEP field region is produced using a direct current having an amperage of 1 microamp to 1 milliamp. In some embodiments, the second DEP field region is produced using a direct current having a pulse width of 500 milliseconds to 500 seconds. In some embodiments, the second DEP field region is produced using a direct current having a pulse width of 500 milliseconds to 100 seconds. In some embodiments, the second DEP field region is produced using a direct current having a pulse width of 1 second to 1000 seconds. In some embodiments, the second DEP field region is produced using a direct current having a pulse width of 500 milliseconds to 1 second. In some embodiments, the second DEP field region is produced using a pulse frequency of 100-1000 Hz. In some embodiments, the second DEP field region is produced using a pulse frequency of 0.1-100 Hz.In some embodiments, the second DEP field region is produced using a pulse frequency of 1-100 Hz. In some embodiments, the second DEP field region is produced using a pulse frequency of 100-1000 Hz.

[0105] In some embodiments, the second DEP field region includes the entire electrode array. In some embodiments, the second DEP field region includes a portion of the electrode array. In some embodiments, the second DEP field region includes about 90%, about 80%, about 70%, about 60%, about 50%, about 40%, about 30%, about 25%, about 20%, or about 10% of the electrode array. In some embodiments, the second DEP field region includes about one-third of the electrode array.

[0106] Biomarker isolation In some embodiments herein, methods, devices, and systems are described for isolating biomarkers from biological complexes, e.g., vesicles such as extracellular vesicles, exosomes, microvesicles, enveloped particles, and other complex particles or biological compartments that contain combinations of biological components including DNA, RNA, proteins, lipids, and other biomolecules.

[0107] In one aspect herein, a method is described for isolating biomarkers from exosomes (e.g., DNA, RNA, nucleosomes, proteins, and / or cell membrane fragments) from a fluid. In some embodiments, the biomarkers are cell-free nucleic acids. In some embodiments, the method includes applying the fluid to a device comprising an electrode array, concentrating a plurality of exosomes in a first AC electrokinetic (e.g., dielectrophoretic) field region, and eluting the exosomes from the device for further analysis (e.g., sequencing, mass spectrometry, etc.).

[0108] In some embodiments herein, a method for isolating cell-free nucleic acids from a fluid is disclosed, comprising: a. applying the fluid to a device comprising an electrode array; b. concentrating a plurality of cellular materials in a first AC electrokinetic (e.g., dielectrophoretic) field region; c. isolating the nucleic acids in a second AC electrokinetic (e.g., dielectrophoretic) field region; and d. washing away the cellular materials. In some examples, the remaining cellular materials are concentrated near the low electric field region. In some embodiments, the remaining materials are washed from the device and / or from the nucleic acids. In some embodiments, the nucleic acids are concentrated in the second AC electrokinetic (e.g., dielectrophoretic) field region.

[0109] In some embodiments, the biomarker nucleic acid is initially intracellular. As seen in FIG. 3, the method includes concentrating the cells near a high electric field region in some instances. In some embodiments herein, a method for isolating nucleic acid from a fluid containing cells is disclosed, the method including: a. applying the fluid to a device comprising an electrode array; b. concentrating a plurality of cells in a first AC electrokinetic (e.g., dielectrophoretic) field region; c. isolating the nucleic acid in a second AC electrokinetic (e.g., dielectrophoretic) field region; and d. washing away the cells. In some instances, the cells are lysed in the high electric field region. After lysis, the nucleic acid remains in the high electric field region and / or is concentrated in the high electric field region. In some instances, the remaining cellular material is concentrated near the low electric field region. In some embodiments, the remaining material is washed from the device and / or from the nucleic acid. In some embodiments, the nucleic acid is concentrated in the second AC electrokinetic (e.g., dielectrophoretic) field region.

[0110] In one aspect herein, a method is described for isolating biomarkers from a fluid containing cells or other particulate material. In some embodiments, the biomarkers are not intracellular (e.g., cell-free DNA in the fluid). In some embodiments herein, a method is disclosed for isolating biomarkers from a fluid containing cells or other particulate material, comprising: a. applying the fluid to a device comprising an electrode array; b. concentrating a plurality of cells in a first AC electrokinetic (e.g., dielectrophoretic) field region; c. isolating biomarkers (e.g., exosomes, DNA, RNA, nucleosomes, extracellular vesicles, proteins, cell membrane fragments, mitochondria, and cell vesicles) in a second AC electrokinetic (e.g., dielectrophoretic) field region; and d. flushing the cells. In some embodiments, the method further comprises degrading residual proteins after flushing the cells. FIG. 4 shows an exemplary method for isolating extracellular nucleic acids from a fluid containing cells. Using similar methods, other small particles, such as vesicles, such as extracellular vesicles, exosomes, microvesicles, enveloped particles, and other complex particles or biological compartments that contain combinations of biological components, including DNA, RNA, proteins, lipids, and other biomolecules, are isolated from cells. In some embodiments, cells are concentrated at or near low electric field regions, and nucleic acids (or other small particles) are concentrated at or near high electric field regions. In some examples, cells are washed from the device and / or from nucleic acids (or other small particles).

[0111] In one aspect, the methods, systems, and devices described herein isolate nucleic acids from a fluid containing cells or other particulate material. In one aspect, dielectrophoresis is used to concentrate the cells. In some embodiments, the fluid is a liquid, optionally water, or an aqueous solution or dispersion. In some embodiments, the fluid is any suitable fluid, including bodily fluids. Exemplary bodily fluids include blood, serum, plasma, bile, milk, cerebrospinal fluid, gastric fluid, ejaculate, mucus, peritoneal fluid, saliva, sweat, tears, urine, and the like. In some embodiments, nucleic acids are isolated from bodily fluids using the methods, systems, or devices described herein as part of a medical therapeutic or diagnostic procedure, device, or system. In some embodiments, the fluid is tissue and / or cells solubilized and / or dispersed in the fluid. For example, the tissue may be a cancerous tumor from which nucleic acids may be isolated using the methods, devices, or systems described herein.

[0112] In some embodiments, the fluid may also include other particulate material. Such particulate material may be, for example, inclusion bodies (e.g., ceroid or Mallory bodies), cellular casts (e.g., granular casts, hyaline casts, cellular casts, waxy casts, and pseudocasts), Pick bodies, Lewy bodies, fibrillary tangles, fibrillogenesis, cellular tangles, and other particulate material. In some embodiments, the particulate material is an aggregated protein (e.g., β-amyloid).

[0113] The fluid can have any conductivity, including high conductivity or low conductivity. In some embodiments, the conductivity is between about 1 μS / m and about 10 mS / m. In some embodiments, the conductivity is between about 10 μS / m and about 10 mS / m. In other embodiments, the conductivity is between about 50 μS / m and about 10 mS / m. In still other embodiments, the conductivity is between about 100 μS / m and about 10 mS / m, between about 100 μS / m and about 8 mS / m, between about 100 μS / m and about 6 mS / m, between about 100 μS / m and about 5 mS / m, between about 100 μS / m and about 4 mS / m, between about 100 μS / m and about 3 mS / m, between about 100 μS / m and about 2 mS / m, or between about 100 μS / m and about 1 mS / m.

[0114] In some embodiments, the conductivity is about 1 μS / m. In some embodiments, the conductivity is about 10 μS / m. In some embodiments, the conductivity is about 100 μS / m. In some embodiments, the conductivity is about 1 mS / m. In other embodiments, the conductivity is about 2 mS / m. In some embodiments, the conductivity is about 3 mS / m. In still other embodiments, the conductivity is about 4 mS / m. In some embodiments, the conductivity is about 5 mS / m. In some embodiments, the conductivity is about 10 mS / m. In still other embodiments, the conductivity is about 100 mS / m. In some embodiments, the conductivity is about 1 S / m. In other embodiments, the conductivity is about 10 S / m.

[0115] In some embodiments, the conductivity is at least 1 μS / m. In still other embodiments, the conductivity is at least 10 μS / m. In some embodiments, the conductivity is at least 100 μS / m. In some embodiments, the conductivity is at least 1 mS / m. In further embodiments, the conductivity is at least 10 mS / m. In still other embodiments, the conductivity is at least 100 mS / m. In some embodiments, the conductivity is at least 1 S / m. In some embodiments, the conductivity is at least 10 S / m. In some embodiments, the conductivity is at most 1 μS / m. In some embodiments, the conductivity is at most 10 μS / m. In other embodiments, the conductivity is at most 100 μS / m. In some embodiments, the conductivity is at most 1 mS / m. In some embodiments, the conductivity is at most 10 mS / m. In some embodiments, the conductivity is at most 100 mS / m. In still other embodiments, the conductivity is at most 1 S / m. In some embodiments, the conductivity is at most 10 S / m.

[0116] In some embodiments, the fluid is a small amount of liquid, including less than 10 mL. In some embodiments, the fluid is less than 8 mL. In some embodiments, the fluid is less than 5 mL. In some embodiments, the fluid is less than 2 mL. In some embodiments, the fluid is less than 1 mL. In some embodiments, the fluid is less than 500 μL. In some embodiments, the fluid is less than 200 μL. In some embodiments, the fluid is less than 100 μL. In some embodiments, the fluid is less than 50 μL. In some embodiments, the fluid is less than 10 μL. In some embodiments, the fluid is less than 5 μL. In some embodiments, the fluid is less than 1 μL.

[0117] In some embodiments, the amount of fluid applied to the device or used in the method comprises less than about 100,000,000 cells. In some embodiments, the fluid comprises less than about 10,000,000 cells. In some embodiments, the fluid comprises less than about 1,000,000 cells. In some embodiments, the fluid comprises less than about 100,000 cells. In some embodiments, the fluid comprises less than about 10,000 cells. In some embodiments, the fluid comprises less than about 1,000 cells. In some embodiments, the fluid is cell-free.

[0118] In some embodiments, isolation of nucleic acid from a fluid containing cells or other particulate material by the devices, systems, and methods described herein takes less than about 30 minutes, less than about 20 minutes, less than about 15 minutes, less than about 10 minutes, less than about 5 minutes, or less than about 1 minute. In other embodiments, isolation of nucleic acid from a fluid containing cells or other particulate material by the devices, systems, and methods described herein takes less than about 30 minutes, less than about 20 minutes, less than about 15 minutes, less than about 10 minutes, less than about 5 minutes, less than about 2 minutes, or less than about 1 minute. In further embodiments, isolation of nucleic acid from a fluid containing cells or other particulate material by the devices, systems, and methods described herein takes less than about 15 minutes, preferably less than about 10 minutes or less than about 5 minutes.

[0119] In some examples, exosomes, extracellular DNA, cell-free DNA fragments, or other nucleic acids (extracellular) are isolated from fluids containing cells of other particulate materials. In some embodiments, the fluid contains cells. In some embodiments, the fluid does not contain cells.

[0120] Cell lysis In one aspect, after concentrating the cells in the first dielectrophoretic field region, the method includes releasing nucleic acid from the cells. In another aspect, the devices and systems described herein are capable of releasing nucleic acid from the cells. In some embodiments, the nucleic acid is released from the cells in the first dielectrophoretic field region.

[0121] In some embodiments, the methods described herein release nucleic acid from a plurality of cells by lysing the cells. In some embodiments, the devices and systems described herein are capable of releasing nucleic acid from a plurality of cells by lysing the cells. One method of cell lysis includes applying a direct current to the cells after isolation of the cells on an array. The direct current has any suitable amperage, voltage, etc. suitable for lysing the cells. In some embodiments, the current has a voltage of about 1 volt to about 500 volts. In some embodiments, the current has a voltage of about 10 volts to about 500 volts. In other embodiments, the current has a voltage of about 10 volts to about 250 volts. In yet other embodiments, the current has a voltage of about 50 volts to about 150 volts. Voltage is generally a driver of cell lysis, since high electric fields cause membrane integrity failure.

[0122] In some embodiments, the direct current used for lysis includes one or more pulses having any duration, frequency, etc. suitable for lysing cells. In some embodiments, a voltage of about 100 volts is applied for about 1 millisecond to lyse cells. In some embodiments, a voltage of about 100 volts is applied two or three times to the second source.

[0123] In some embodiments, the frequency of the direct current depends on volts / cm, pulse width, and fluid conductivity. In some embodiments, the pulses have a frequency of about 0.001 to about 1000 Hz. In some embodiments, the pulses have a frequency of about 10 to about 200 Hz. In other embodiments, the pulses have a frequency of about .01 Hz to 1000 Hz. In still other embodiments, the pulses have a frequency of about 0.1 Hz to 1000 Hz, about 1 Hz to 1000 Hz, about 1 Hz to 500 Hz, about 1 Hz to 400 Hz, about 1 Hz to 300 Hz, or about 1 Hz to about 250 Hz. In some embodiments, the pulses have a frequency of about 0.1 Hz. In other embodiments, the pulses have a frequency of about 1 Hz. In yet other embodiments, the pulses have a frequency of about 5 Hz, about 10 Hz, about 50 Hz, about 100 Hz, about 200 Hz, about 300 Hz, about 400 Hz, about 500 Hz, about 600 Hz, about 700 Hz, about 800 Hz, about 900 Hz, or about 1000 Hz.

[0124] In other embodiments, the pulses have a duration of about 1 millisecond (ms) to 1000 seconds (s). In some embodiments, the pulses have a duration of about 10 ms to 1000 s. In still other embodiments, the pulses have a duration of about 100 ms to 1000 s, about 1 s to 1000 s, about 1 s to 500 s, about 1 s to 250 s, or about 1 s to 150 s. In some embodiments, the pulses have a duration of about 1 ms, about 10 ms, about 100 ms, about 1 s, about 2 s, about 3 s, about 4 s, about 5 s, about 6 s, about 7 s, about 8 s, about 9 s, about 10 s, about 20 s, about 50 s, about 100 s, about 200 s, about 300 s, about 500 s, or about 1000 s. In some embodiments, the pulses have a frequency of 0.2 to 200 Hz with a duty cycle of 10 to 50%.

[0125] In some embodiments, the direct current is applied as one or more pulses. Any suitable number of pulses may be applied, including about 1-20 pulses. There is any suitable time between pulses, including about 1 millisecond to 1000 seconds. In some embodiments, the pulse duration is .01 to 10 seconds.

[0126] In some embodiments, cells are lysed using other methods combined with the direct current applied to the isolated cells. In yet other embodiments, cells are lysed without the use of direct current. In various aspects, the devices and systems may be capable of lysing cells with direct current in combination with other means, or may be capable of lysing cells without the use of direct current. Any method of cell lysis known to those skilled in the art may be suitable, including, but not limited to, application of chemical lysing agents (e.g., acids), enzymatic lysing agents, heat, pressure, shear force, sonic energy, osmotic shock, or combinations thereof. Lysozyme is an example of an enzymatic lysing agent.

[0127] Removal of residual material In some embodiments, the method includes optionally washing residual material from the target cellular material after concentrating the target cellular material in the second DEP field region. In some embodiments, the device or system described herein can optionally include a reservoir containing a fluid suitable for washing residual material from the target cellular material. In some embodiments, the target cellular material is retained near the electrode array, for example, in the second DEP field region, by continuing to energize the electrodes. "Residual material" is material that is originally present in the fluid, originally present in the cell, added during the procedure, created during any step of the process, including but not limited to lysis of the cells (i.e., residual cellular material). For example, residual material includes unlysed cells, cell wall fragments, proteins, lipids, carbohydrates, minerals, salts, buffers, plasma, and undesired nucleic acids. In some embodiments, the lysed cellular material includes residual proteins released from the plurality of cells upon lysis. It is possible that not all of the target cellular material is concentrated in the second DEP field. In some embodiments, a certain amount of the target cellular material is washed away with the residual material.

[0128] In some embodiments, the residual material is washed away in any suitable fluid, such as water, TBE buffer, etc. In some embodiments, the residual material is washed away with any suitable volume of fluid, washed away for any suitable period of time, washed away with more than one fluid, or any other variation. In some embodiments, the method of washing away the residual material is related to the desired level of isolation for target cell material with more pure target cell material requiring more stringent washing and / or cleaning. In other embodiments, the method of washing away the residual material is related to the particular starting material and its composition. In some cases, starting materials that are high in lipids require a washing procedure that includes a hydrophobic fluid suitable for solubilizing lipids.

[0129] In some embodiments, the method includes a step of degrading residual material, including residual proteins. In some embodiments, the device or system is capable of degrading residual material, including residual proteins. For example, proteins are degraded by one or more of chemical degradation (e.g., acid hydrolysis) and enzymatic degradation. In some embodiments, the enzymatic degrading agent is a protease. In other embodiments, the proteolytic agent is proteinase K. The optional degrading step of residual material is carried out for any suitable time, temperature, etc. In some embodiments, the degraded residual material (including degraded proteins) is washed away from the nucleic acid.

[0130] In some embodiments, the agent used to degrade the residual material is inactivated or decomposed. In some embodiments, the device or system is capable of decomposing or inactivating the agent used to degrade the residual material. In some embodiments, the enzyme used to degrade the residual material is inactivated by heat (e.g., 50-95°C for 5-15 minutes). For example, enzymes including proteases (e.g., proteinase K) are decomposed and / or inactivated using heat (typically, 70°C for 15 minutes). In some embodiments where the residual protein is decomposed by enzymes, the method further comprises a step of inactivating the decomposition enzyme (e.g., proteinase K) after the protein is decomposed. In some embodiments, the heat is provided by a heating module in the device (temperature range is, for example, 30-95°C).

[0131] The order and / or combination of certain steps of the above method can be changed. In some embodiments, the above device or method can perform certain steps in any order or combination. For example, in some embodiments, residual material and degraded proteins are washed away in separate or simultaneous steps. That is, the residual material is washed away, followed by degrading the residual protein, and then the degraded protein is washed away from the nucleic acid. In some embodiments, the residual protein is degraded first, and then both the residual material and the degraded protein are washed away from the nucleic acid in a combined step.

[0132] In some embodiments, the target cellular material is retained in the device and optionally used in further procedures such as PCR or other procedures that manipulate or amplify nucleic acids. In some embodiments, the devices and systems are capable of performing PCR or any other procedure. In other embodiments, the target cellular material is collected and / or eluted from the device. In some embodiments, the devices and systems can allow for collection and / or elution of the target cellular material from the device or system. In some embodiments, the isolated cellular material is collected by (i) turning off the second dielectrophoretic field region and (ii) eluting the material from the array in an elution solution. Exemplary elution agents include water, TE, TBE, and L-histidine buffer.

[0133] Biomolecules In some embodiments, the methods, devices, or systems described herein are optionally utilized to obtain, isolate, or separate any desired biological material that may be obtained from the aforementioned methods, devices, or systems, such as extracellular vesicles, exosomes, microvesicles, enveloped particles, and other composite particles or biological compartments that include combinations of biological components including DNA, RNA, proteins, lipids, and other biomolecules. The nucleic acids isolated by the methods, devices, and systems described herein include DNA (deoxyribonucleic acid), RNA (ribonucleic acid), and combinations thereof. DNA can include cell-free DNA and DNA fragments. In some embodiments, the nucleic acids are isolated in a form suitable for sequencing or further manipulation of the nucleic acids, including amplification, ligation, or cloning. The proteins isolated by the methods, devices, and systems described herein include protein complexes, full-length proteins, processed proteins, and protein fragments. In some embodiments, the proteins are isolated in a form suitable for mass spectrometry or analysis with antibodies (e.g., ELISA, Western blot, immunofluorescence staining).

[0134] In some embodiments, the isolated, separated, or captured nucleic acids include DNA fragments that are selectively or preferentially isolated, separated, or captured based on their size. In some embodiments, the DNA fragments that are selectively or preferentially isolated, separated, or captured are between 250-600 bp, 250-275 bp, 275-300 bp, 300-325 bp, 325-350 bp, 350-375 bp, 375-400 bp, 400-425 bp, 425-450 bp, 450-475 bp, 475-500 bp, 500-525 bp, 525-550 bp, 550-575 bp, 575-600 bp, 300-400 bp, 400-500 bp, and / or 300-500 bp in length. In some embodiments, the DNA fragments selectively or preferentially isolated, separated, or captured are between 600-700bp, 700-800bp, 800-900bp, 900-1000bp, 1-2kbp, 2-3kbp, 3-4kbp, 4-5kbp, 5-6kbp, 6-7kbp, 7-8kbp, 8-9kbp, or 9-10kbp. In some embodiments, the DNA fragments selectively or preferentially isolated, separated, or captured are greater than 300, 400, 500, 600, 700, 800, 900, or 1000bp in size.

[0135] In some embodiments, the DNA fragments are cell-free DNA fragments.

[0136] In various embodiments, the isolated or separated nucleic acid is at least 99% by weight free of other substances, at least 99% by weight free of residual cellular material (e.g., from the lysed cells from which the nucleic acid is obtained), at least 98% by weight free of other substances, at least 98% by weight free of residual cellular material, at least 95% by weight free of other substances, at least 95% by weight free of residual cellular material, at least 90% by weight free of other substances, at least 90% by weight free of residual cellular material, at least 80% by weight free of other substances, at least 80% by weight free of residual cellular material, or at least A composition comprising nucleic acid that is 70% by weight free of other substances, at least 70% by weight free of residual cellular material, at least 60% by weight free of other substances, at least 60% by weight free of residual cellular material, at least 50% by weight free of other substances, at least 50% by weight free of residual cellular material, at least 30% by weight free of other substances, at least 30% by weight free of residual cellular material, at least 10% by weight free of other substances, at least 10% by weight free of residual cellular material, at least 5% by weight free of other substances, or at least 5% by weight free of residual cellular material.

[0137] In various embodiments, the nucleic acid has any suitable purity. For example, when a DNA sequencing procedure can work with a nucleic acid sample having about 20% residual cellular material, isolation of up to 80% nucleic acid is suitable. In some embodiments, the isolated nucleic acid comprises less than about 80%, less than about 70%, less than about 60%, less than about 50%, less than about 40%, less than about 30%, less than about 20%, less than about 10%, less than about 5%, or less than about 2% by mass of non-nucleic acid cellular material and / or protein. In some embodiments, the isolated nucleic acid comprises more than about 99%, more than about 98%, more than about 95%, more than about 90%, more than about 80%, more than about 70%, more than about 60%, more than about 50%, more than about 40%, more than about 30%, more than about 20%, or more than about 10% by mass of nucleic acid.

[0138] The nucleic acid is isolated in any suitable form, including unmodified, derivatized, fragmented, non-fragmented, etc. In some embodiments, the nucleic acid is collected in a form suitable for sequencing. In some embodiments, the nucleic acid is collected in a fragmented form suitable for shotgun sequencing, amplification, or other manipulations. The nucleic acid may be collected from the device in a solution containing reagents used in the DNA sequencing procedure, such as nucleotides used in sequencing by synthesis methods.

[0139] In some embodiments, the methods described herein result in an isolated nucleic acid sample that is approximately representative of the nucleic acid of the starting sample. In some embodiments, the devices and systems described herein are capable of isolating nucleic acids from a sample that is approximately representative of the nucleic acid of the starting sample. That is, the population of nucleic acids collected by the methods described above or that can be collected by the devices or systems described above is substantially proportional to the population of nucleic acids present in cells in the fluid. In some embodiments, this aspect is advantageous in applications where the fluid is a complex mixture of multiple cell types and the practitioner desires a nucleic acid-based procedure to determine the relative populations of various cell types.

[0140] In some embodiments, the nucleic acids isolated using the methods described herein or isolatable by the devices described herein are of high quality and / or suitable for direct use in downstream procedures such as DNA sequencing, nucleic acid amplification such as PCR, or other nucleic acid manipulations such as ligation, cloning, further translation or transformation assays. In some embodiments, the collected nucleic acids comprise up to 0.01% protein. In some embodiments, the collected nucleic acids comprise up to 0.5% protein. In some embodiments, the collected nucleic acids comprise up to 0.1% protein. In some embodiments, the collected nucleic acids comprise up to 1% protein. In some embodiments, the collected nucleic acids comprise up to 2% protein. In some embodiments, the collected nucleic acids comprise up to 3% protein. In some embodiments, the collected nucleic acids comprise up to 4% protein. In some embodiments, the collected nucleic acids comprise up to 5% protein.

[0141] In some embodiments, the nucleic acid isolated by the methods described herein or isolatable by the devices described herein has a concentration of at least 0.5 ng / mL. In some embodiments, the nucleic acid isolated by the methods described herein or isolatable by the devices described herein has a concentration of at least 1 ng / mL. In some embodiments, the nucleic acid isolated by the methods described herein or isolatable by the devices described herein has a concentration of at least 5 ng / mL. In some embodiments, the nucleic acid isolated by the methods described herein or isolatable by the devices described herein has a concentration of at least 10 ng / mL.

[0142] In some embodiments, about 50 picograms of nucleic acid are isolated from about 5,000 cells using the methods, systems, or devices described herein. In some embodiments, the methods, systems, or devices described herein result in at least 10 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 20 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 50 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 75 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 100 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 200 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 300 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 400 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 500 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 1,000 picograms of nucleic acid from about 5,000 cells. In some embodiments, the methods, systems, or devices described herein result in at least 5,000 picograms of nucleic acid from about 5,000 cells.

[0143] Assays and Applications In some embodiments, the methods described herein further comprise amplifying the isolated nucleic acid by polymerase chain reaction (PCR). In some embodiments, the PCR reaction is carried out on or near the electrode array or in the device. In some embodiments, the device or system comprises a heater and / or a temperature control mechanism suitable for thermal cycling.

[0144] PCR is optionally performed using conventional thermal cycling by placing the reacting chemical analyte between two efficient thermally conductive elements (e.g., aluminum or silver) and regulating the reaction temperature using a TEC. Additional designs optionally use infrared heating through optically transparent materials such as glass or thermal polymers. In some examples, designs use smart polymers or smart glass with conductive wiring networked through the substrate. This conductive wiring allows rapid thermal conduction in the material to obtain the desired temperature changes and gradients (by applying appropriate DC voltages) to maintain an efficient PCR reaction. In certain examples, heating is applied using resistive tip heaters and other resistive elements, which change the temperature rapidly and proportionally to the amount of current passing through them.

[0145] In some embodiments, when used in conjunction with conventional fluorescence measurement methods (ccd, pmt, other optical detectors, and optical filters), fold amplification is monitored in real time or at timed intervals. In certain instances, quantification of the final fold amplification is reported via optical detection, which is converted to AFU (any fluorescence unit that correlates to the analysis of doubling) or translated into an electrical signal by impedance measurement or other electrochemical sensing.

[0146] Given the small size of the microelectrode array, these elements are optionally added around the microelectrode array, and the PCR reaction is performed in the main sample processing chamber (on the DEP array), or the analytes to be amplified are optionally transported by fluidics to another chamber in the fluidic cartridge to enable lab-on-chip processing on the cartridge.

[0147] In some examples, light delivery schemes are utilized to provide optical excitation and / or emission and / or detection of multiplication. In certain embodiments, this includes using flow cell materials (thermal polymers such as acrylic (PMMA), cyclic olefin polymer (COP), cyclic olefin copolymer (COC), etc.) as light guides to eliminate the need to use external elements. In addition, in some examples, light emitting diodes or LEDs, vertical cavity surface emitting lasers or VCSELs, and other illumination schemes as light sources are integrated directly inside the flow cell or built directly on the microelectrode array surface to internally control and power the antigen. Small PMT, CCD, or CMOS detectors can also be incorporated into the flow cell. Such miniaturization and miniaturization allows for compact devices that can rapidly deliver and detect signals while reducing the footprint of similar conventional devices (i.e., standard benchtop PCR / QPCR / fluorometers).

[0148] On-chip amplification In some examples, silicon microelectrode arrays can withstand the thermal cycling required for PCR. In some applications, on-chip PCR is advantageous because small amounts of target nucleic acid may be lost during the transfer process. In certain embodiments of the device, system, or process described herein, any one or more of a number of PCR techniques are optionally used, including any one or more of direct thermal cycling in a flow cell, transfer of material through microchannels with different temperature zones, and transfer of a volume to a PCR tube that can be amplified on the system or transferred to a PCR machine. In some examples, droplet PCR is performed where a T-junction containing an immiscible fluid and an interface stabilizer (such as a surfactant) is accompanied at the outlet. In an embodiment, the droplets are thermal cycled by any suitable method.

[0149] In some embodiments, amplification is carried out using an isothermal reaction, such as transcription-mediated amplification, nucleic acid sequence-based amplification, signal-mediated amplification of RNA technologies, strand displacement amplification, rolling circle amplification, loop-mediated isothermal amplification of DNA, isothermal multiple displacement amplification, helicase-dependent amplification, single primer isothermal amplification, or circular helicase-dependent amplification.

[0150] In various embodiments, amplification is performed in homogeneous solution or as a heterogeneous system with anchor primers. In some of the latter embodiments, the resulting amplicons are directly ligated to a surface for higher multiplexing. In some embodiments, the amplicons are denatured to give single-stranded products on or near the electrode. Hybridization reactions are then optionally performed to investigate genetic information such as single nucleotide polymorphisms (SNPs), short tandem repeats (STRs), mutations, insertions / deletions, methylation, etc. Methylation is optionally determined by parallel analysis in which one DNA sample is treated with bisulfite and the other is not. Bisulfite depurines unmodified Cs that become Us. Methylated Cs are unaffected in some instances. In some embodiments, allele-specific base extension is used to report the base of interest.

[0151] The surface is optionally modified with non-specific moieties rather than specific interactions for capture. For example, the surface can be modified with polycations, i.e., polylysine, to capture DNA molecules that can be released by reverse bias (-V). In some embodiments, the modifications to the surface are uniform across the surface or specifically patterned to functionalize the electrode or non-electrode regions. In certain embodiments, this is accomplished by photolithography, electrochemical activation, spotting, and the like.

[0152] In some applications, the chip may include multiple regions, each region configured to capture DNA fragments of specific or different sizes. The chip regions may sometimes vary in voltage, amperage, frequency, pitch, electrode diameter, well depth, or other factors to selectively capture fragments of different sizes in different regions. In some embodiments, each region comprises an array of multiple electrodes.

[0153] In various embodiments, the devices or regions are run in series or in parallel. In some embodiments, multiple chip designs are used to narrow the size range of collected materials to create a bandpass filter. In some examples, the current chip geometry (e.g., 80 um diameter electrodes (80 / 200) on a 200 um center-to-center pitch) acts as a 500 bp cutoff filter (e.g., using voltage and frequency conditions of about 10 Vpp and 10 kHz). In such examples, nucleic acids greater than 500 bp are captured and nucleic acids less than 500 bp are not captured. Alternative electrode diameter and pitch geometries have different cutoff sizes such that the combination of chips results in the desired fragment size. In some examples, 40 um diameter electrodes (40 / 100) on a 100 um center-to-center pitch have a lower cutoff threshold, while 160 um diameter electrodes (160 / 400) on a 400 um center-to-center pitch have a higher cutoff threshold compared to the 80 / 200 geometry under similar conditions. In various embodiments, geometries on a single chip or multiple chips are combined to select for fragments or particles of a particular size. For example, a chip with a 600bp cutoff leaves nucleic acids less than 600bp in solution, and the material is then optionally recaptured by a chip with a 500bp cutoff (opposite the 600bp chip). This leaves a nucleic acid population containing 500-600bp in solution. This population is then optionally amplified in the same chamber, a side chamber, or any other configuration. In some embodiments, size selection is achieved using a single electrode geometry, where nucleic acids greater than 500bp are isolated on the electrode, followed by washing, and the ACEK high electric field strength is reduced (changes in voltage, frequency, conductivity) to release nucleic acids less than 600bp, resulting in a nucleic acid population between 500-600bp in the supernatant.In some embodiments, the device is configured to selectively capture nucleic acid fragments between 250-600 bp, 250-275 bp, 275-300 bp, 300-325 bp, 325-350 bp, 350-375 bp, 375-400 bp, 400-425 bp, 425-450 bp, 450-475 bp, 475-500 bp, 500-525 bp, 525-550 bp, 550-575 bp, 575-600 bp, 300-400 bp, 400-500 bp, and / or 300-500 bp in length.

[0154] In some embodiments, the chip device is oriented vertically with a heater at the bottom that creates a temperature gradient column. In a particular example, the bottom is the denaturation temperature, the middle is the annealing temperature, and the top is the extension temperature. In some examples, the process is continuously induced by convection. In some embodiments herein, methods or systems are provided that include electrode designs that specifically result in electric heat flow and accelerated processes. In some embodiments, such designs are optionally on the same device or on separate devices positioned accordingly. In some examples, a steep temperature gradient is obtained by active or passive cooling at the top, such as via fins or fans. In some examples, the devices or systems described herein include temperature sensors on the device or in the reaction chamber to monitor the temperature, or the methods described herein use such temperature sensors, which are optionally used to adjust the temperature based on feedback. In some examples, such sensors are combined with materials with different heat transfer properties to create continuous and / or discontinuous gradient profiles.

[0155] In some embodiments, amplification proceeds at a constant temperature (ie, isothermal amplification).

[0156] In some embodiments, the method disclosed herein further comprises sequencing the nucleic acid isolated as disclosed herein.In some embodiments, the nucleic acid is sequenced by Sanger sequencing or next-generation sequencing (NGS).In some embodiments, next-generation sequencing methods include, but are not limited to, pyrosequencing, ion semiconductor sequencing, polony sequencing, sequencing by ligation, DNA nanoball sequencing, sequencing by ligation, or single molecule sequencing.

[0157] In some embodiments, the isolated nucleic acids disclosed herein are used for Sanger sequencing. In some embodiments, Sanger sequencing is performed in the same device (lab-on-chip) as nucleic acid isolation. The lab-on-chip workflow for sample preparation and Sanger sequencing results incorporates the following steps: a) sample extraction using ACE chip, b) performing amplification of target sequences on chip, c) capturing PCR products by ACE, d) performing cycle sequencing to enrich target strands, e) capturing enriched target strands, f) performing Sanger chain termination reaction, performing dielectrophoretic separation of target sequences by capillary dielectrophoresis with multicolor fluorescence detection on chip. If necessary, nucleic acid washing, reagent addition, and voltage off are performed. Reactions can be performed on a single chip with multiple capture zones or on separate chips and / or reaction chambers.

[0158] In some embodiments, the methods disclosed herein further comprise performing a reaction on the nucleic acid (e.g., fragmentation, restriction digestion, ligation of DNA or RNA). In some embodiments, the reaction occurs on or near an array or within a device as disclosed herein.

[0159] Other Assays The isolated nucleic acid disclosed herein may further be utilized in various assay formats.For example, the device addressed by nucleic acid probe or amplicon may be utilized for dot blot or reverse dot blot analysis, base stacking single nucleotide polymorphism (SNP) analysis, SNP analysis with electronic stringency, or STR analysis.In addition, such device disclosed herein may be utilized for enzymatic nucleic acid modification or protein-nucleic acid interaction, for example, gene expression analysis with enzymatic reporting, fixed nucleic acid amplification, or other nucleic acid modification suitable for solid phase format, including restriction endonuclease cleavage, endonuclease or exonuclease cleavage, minor groove binding protein assay, terminal transferase reaction, polynucleotide kinase or phosphatase reaction, ligase reaction, topoisomerase reaction, and other nucleic acid binding or nucleic acid modification protein reaction.

[0160] In addition, the devices disclosed herein may be useful for immunoassays. For example, in some embodiments, the locations of the device may be linked to antigens (e.g., peptides, proteins, carbohydrates, lipids, proteoglycans, glycoproteins, etc.) to assay for antibodies in a body fluid sample by sandwich assay, competitive assay, or other formats. Alternatively, the locations of the device may be addressed by antibodies to detect antigens in a sample by sandwich assay, competitive assay, or other assay formats. Since the isoelectric points of antibodies and proteins can be fairly easily determined by experiment or pH / charge calculations, the advantages of electronic addressing and electronic concentration of the device may be exploited by simply adjusting the pH of the buffer so that the addressed species or non-analyte species are charged.

[0161] In a further aspect, the devices disclosed herein are useful for the analysis of biomarkers by mass spectrometry.

[0162] In some embodiments, the isolated nucleic acids are useful for use in immunoassay-type arrays or nucleic acid arrays.

[0163] Definitions and Abbreviations The articles "a," "an," and "The" are open-ended. For example, "the method" can be more than one method, as this encompasses the broadest definition of the phrase.

[0164] "Vpp" is the peak-to-peak voltage.

[0165] "DEP" is an abbreviation for dielectrophoresis. EXAMPLES

[0166] Example 1: Chip Construction A 45x20 custom made 80μm diameter annular platinum microelectrode array was fabricated on a 200um center pitch based on previous results (see references 1-3 below). All 900 microelectrodes were activated collectively and AC biased to form a checkerboard field shape. Positive DEP regions occur directly on the microelectrodes and negative low field regions occur between the microelectrodes. The array was overcoated with a 200nm-500nm thick layer of porous poly-Hema hydrogel (Procedure: 12% pHema stock solution in ethanol purchased from PolySciences Inc. is diluted to 5% with ethanol. 70uL of the 5% solution is spun onto the chip described above at a rotation speed of 6K RPM using a spin coater. The chip + hydrogel layer is then placed in a 60°C oven for 45 minutes) and enclosed in a microfluidic cartridge to form a 50μL sample chamber covered with an acrylic window. Electrical connections to the microelectrodes are accessed through a Molex connector on the PCB board within the flow cell. A function generator (HP3245A) provided a sinusoidal electrical signal of 10 KHz and 10-14 V peak-to-peak depending on the conductivity of the solution. Images were captured with a fluorescence microscope (Leica) and an EGFP cube (bandpass filter with emission 485 nm and excitation 525 nm). The excitation source was a PhotoFluor II 200W Hg arc lamp.

[0167] [1] R. Krishnan, B. D. Sullivan, R. L. Mifflin, S. C. E. Sener, and M. J. Heller, “Alternating current electrokinetic separation and detection of DNA nanoparticles in high-conductance solutions.” Electrophoresis, vol. 29, pp. 1765–1774, 2008.

[0168] [2] R. Krishnan and M. J. Heller, "An AC electrokinetic method for enhanced detection of DNA nanoparticles." J. Biophotonics, Vol. 2, pp. 253-261, 2009.

[0169] [3] R. Krishnan, DA Dehlinger, GJ Gemmen, RL Mifflin, SCE Sener, and MJ Heller, “Interaction of nanoparticles at the DEP microelectrode interface under high conductance conditions,” Electrochem. Comm., Vol. 11, pp. 1661-1666, 2009.

[0170] Example 2: Biomarker discovery methods Plasma samples were obtained from individuals with pancreatic cancer. Extracellular vesicles were isolated from a portion of the plasma samples, and cell-free nucleic acids were obtained from the plasma samples using AC dielectrophoresis. The nucleic acids from the extracellular vesicles and the cell-free nucleic acids were subjected to genomic profiling via next-generation sequencing. In parallel, the proteins from the extracellular vesicles were subjected to proteomic analysis via mass spectrometry. The combined analysis found biomarkers that were over- or under-expressed in the samples when compared to plasma samples from healthy individuals, which were identified as biomarkers for pancreatic cancer. A flow diagram of the method is shown in Figure 5. A cluster diagram and heat map of the expression of various biomarkers are shown in Figure 6.

[0171] Example 3: Multi-cancer study A multi-cancer study was developed to determine in a single test whether an individual had one of four different cancers. To validate the method, 247 early stage cancer patients and healthy controls were tested for various biomarkers. The study population is shown in Figure 7. The results are shown in Figure 8, which shows an overall specificity of 97% and a sensitivity of 87%, establishing specificity for each cancer type and stage. This example shows that multiple cancers can be tested in a single assay.

[0172] Example 4: Cancer Detection Exosomes were isolated from the plasma of 134 treatment-naïve cancer patients (42 with ovarian cancer, 44 with pancreatic cancer, and 48 with bladder cancer) and 110 healthy individuals (Figure 9A) (see Methods for details). All cancer patients were histopathologically recognized as stage I or stage II by the American Joint Committee on Cancer (AJCC), and the median age was 59 years (Tables 1-2). Notably, 63% of patients with overall cancer (48% pancreatic, 88% ovarian, and 56% bladder) were stage I, while the remaining 37% were stage II. There were also 25 stages of IAS (60% ovarian) in the ovarian cohort. Healthy individuals had no known history of cancer or autoimmune disease, and the median age was 53 years.

[0173] [Table 1]

[0174] [Table 2-1]

[0175] [Table 2-2]

[0176] [Table 2-3]

[0177]

Table 2-4

[0178]

Table 2-5

[0179]

Table 2-6

[0180]

Table 2-7

[0181]

Table 2-8

[0182]

Table 2-9

[0183]

Table 2-10

[0184]

Table 2-11

[0185] Using existing literature on cancer-associated proteins, 42 protein biomarkers were selected and two other factors (age and sex) were selected for evaluation (Table 4). These proteins were found to be reproducibly assessable through the immunoassay platform, and therefore exoprotein levels of the 42 markers were measured in the plasma of all subjects (Table 5). Particle size distribution and concentration confirmed comparable exosome isolation in both cohorts (Table 3, Figure 12). Heatmaps for protein abundance of exoproteins and free proteins (total circulating plasma proteins) are shown in Figure 13. All biomarkers in Table 4 were evaluated for inclusion in a logistic regression model to be carried forward to detect early stage cancer, i.e., the EXPLORE study.

[0186] [Table 3-1]

[0187] [Table 3-2]

[0188] [Table 3-3]

[0189] [Table 3-4]

[0190] [Table 3-5]

[0191] [Table 3-6]

[0192] [Table 3-7]

[0193]

Table 3-8

[0194]

Table 3-9

[0195]

Table 3-10

[0196]

Table 4-1

[0197]

Table 4-2

[0198]

Table 5-1

[0199]

Table 5-2

[0200]

Table 5-3

[0201]

Table 5-4

[0202]

Table 5-5

[0203]

Table 5-6

[0204]

Table 5-7

[0205]

Table 5-8

[0206]

Table 5-9

[0207]

Table 5-10

[0208]

Table 5-11

[0209]

Table 5-12

[0210]

Table 5-13

[0211]

Table 5-14

[0212]

Table 5-15

[0213]

Table 5-16

[0214]

Table 5-17

[0215]

Table 5-18

[0216]

Table 5-19

[0217]

Table 5-20

[0218]

Table 5-21

[0219]

Table 5-22

[0220]

Table 5-23

[0221]

Table 5-24

[0222]

Table 5-25

[0223]

Table 5-26

[0224]

Table 5-27

[0225]

Table 5-28

[0226]

Table 5-29

[0227]

Table 5-30

[0228]

Table 5-31

[0229]

Table 5-32

[0230]

Table 5-33

[0231]

Table 5-34

[0232]

Table 5-35

[0233]

Table 5-36

[0234]

Table 5-37

[0235]

Table 5-38

[0236]

Table 5-39

[0237]

Table 5-40

[0238]

Table 5-41

[0239]

Table 5-42

[0240]

Table 5-43

[0241]

Table 5-44

[0242]

Table 5-45

[0243]

Table 5-46

[0244]

Table 5-47

[0245]

Table 5-48

[0246]

Table 5-49

[0247]

Table 5-50

[0248]

Table 5-51

[0249]

Table 5-52

[0250]

Table 5-53

[0251]

Table 5-54

[0252]

Table 5-55

[0253]

Table 5-56

[0254]

Table 5-57

[0255]

Table 5-58

[0256]

Table 5-59

[0257]

Table 5-60

[0258]

Table 5-61

[0259]

Table 5-62

[0260]

Table 5-63

[0261]

Table 5-64

[0262]

Table 5-65

[0263]

Table 5-66

[0264]

Table 5-67

[0265]

Table 5-68

[0266]

Table 5-69

[0267]

Table 5-70

[0268]

Table 5-71

[0269]

Table 5-72

[0270]

Table 5-73

[0271]

Table 5-74

[0272]

Table 5-75

[0273]

Table 5-76

[0274]

Table 5-77

[0275]

Table 5-78

[0276]

Table 5-79

[0277]

Table 5-80

[0278]

Table 5-81

[0279]

Table 5-82

[0280]

Table 5-83

[0281]

Table 5-84

[0282]

Table 5-85

[0283]

Table 5-86

[0284]

Table 5-87

[0285]

Table 5-88

[0286]

Table 5-89

[0287]

Table 5-90

[0288]

Table 5-91

[0289]

Table 5-92

[0290]

Table 5-93

[0291]

Table 5-94

[0292]

Table 5-95

[0293]

Table 5-96

[0294]

Table 5-97

[0295]

Table 5-98

[0296]

Table 5-99

[0297]

Table 5-100

[0298]

Table 5-101

[0299]

Table 5-102

[0300]

Table 5-103

[0301]

Table 5-104

[0302]

Table 5-105

[0303]

Table 5-106

[0304]

Table 5-107

[0305] [Table 5-108]

[0306] [Table 5-109]

[0307] [Table 5-110]

[0308] [Table 5-111]

[0309] [Table 5-112]

[0310] To calculate the overall average ROC (Figure 9B, Methods), 100 computational iterations were performed. For each iteration, the entire dataset in Table 5 was randomly split into 2 / 3 training and 1 / 3 test sets. The training set was used to generate regression coefficients for each of the biomarkers, and the test set was used to generate receiver operating characteristic (ROC) curves and AUC statistics. This rigorous statistical analysis identified 13 proteins that, when combined with patient age, can effectively identify early-stage cancer (Figure 9C, Table 2, Table 6). The resulting average ROC curve is shown in Figure 10A. When the entire cancer cohort was compared to healthy individuals using the EXPLORE test, the average AUC was 0.95 (95% CI = 0.94-0.97) and the average sensitivity was 71.2% with a specificity of over 99%.

[0311] [Table 6]

[0312] The 13 exoprotein biomarkers used in the EXPLORE study span a wide range of biological functions that may represent pivotal points in cancer development. Neuropilin-1 and HER2 are thought to mediate aberrant growth factor signaling in early malignancies (Niland, S. and Eble, JA, Neuropilins in the Context of Tumor Vasculature, International Journal of Molecular Sciences 20, 639 (2019); Moasser, MM, The oncogene HER2:its signaling and transforming functions and its role in human cancer pathogenesis. Oncogene 26, 6469-6487 (2007)). CA19-9, MPO, and TIMP-1 were previously identified in another multi-cancer assay (Liu, MC, et al., "Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA." Annals of Oncology 31, 745-759 (2020)). VEGFR1, sc-Kit / SCFR, and sE-selectin may affect angiogenesis (Dvorak, HF, "Vascular Permeability Factor / Vascular Endothelial Growth Factor: A Critical Cytokine in Tumor Angiogenesis and a Potential Target for Diagnosis and Therapy." Journal of Clinical Oncology 20, 4368-4380 (2002); Lennartsson, J. & Ronnstrand, L., "Stem cell factor receptor / c-Kit: from basic science to clinical implications.Physiol Rev 92,1619-1649(2012);Kjaergaard,AG,Dige,A.,Nielsen,JS,Tonnesen,E.,Krog,J.,The use of the soluble adhesion molecules sE-selectin,sICAM-1,sVCAM-1,sPECAM-1 and their ligands CD11a and CD49d as diagnostic and prognostic biomarkers in septic and critically ill non-septic ICU patients.,Apmis 124,846-855(2016)), while exosomal cathepsin-D, MIA, IGFBP3, sFas, and ferritin are known to affect tumor progression (Hoshino,A. et al.,Extracellular Vesicle and Particle Biomarkers Define Multiple Human Cancers.,Cell 182,1044-1061.e1018(2020);Hoshino,A.et al., "Tumour exosome integrins determine organotropic metastasis.",Nature 527,329-335(2015))(Table 6, Table 7). Waterfall plots for each of the mentioned exoproteins are shown in Figure 14 and Figure 15 shows that EXPLORE exoproteins predict the presence of cancer more accurately than their equivalent free proteins (0.95 vs 0.85 AUC).

[0313] A key feature of a viable screening test is its ability to accurately detect early cancers. At >99% specificity (where only 1 in 110 healthy individuals was falsely identified as positive), the EXPLORE test demonstrated a sensitivity of 70.4% and 72.3% for stage I and stage II patients across all cancers, respectively (Figure 10B). When analyzed by cancer type at >99% specificity, the EXPLORE test demonstrated a sensitivity of 69% and 51% for ovarian and bladder cancer, respectively, and a remarkable 96% for detecting early stage pancreatic cancer (Figure 10C). Unlike previously described multi-cancer assays, EXPLORE demonstrated remarkable sensitivity in detecting early stage disease in these challenging cancers.

[0314] To further understand the potential clinical significance of the EXPLORE test, we assessed its performance across cancer stages and histological breakdown, and compared its average sensitivity at three specificity levels (99%, 97%, and 95%) used in the various screening assays.

[0315] The study demonstrated near perfect sensitivity in detecting both 21 stage I (97%, 98%, 99%) and 23 stage II (95%, 96%, 97%) cases in PDAC patients at the highest levels of specificity (Figure 11A), with the potential for dramatic clinical impact. Detection of stage I ovarian cancer (N=37) was also at the level of potential clinical impact (65%, 69%, 76%), with a significant increase in sensitivity observed at lower specificities. Importantly, the high sensitivity for detection of both stage IA (n=25, 66%, 69%, 75%) and the aggressive and potentially lethal serous adenocarcinoma histology (stage I / II, n=22, 69%, 73%, 80%) clearly demonstrates the potential value of the EXPLORE test for ovarian cancer (Figure 11B). Early detection for either subtype could have a dramatic impact on survival as surgery is curative. The study for bladder cancer was equally able to detect 27 stage I patients (56%, 61%, 67%), 15 low-grade cancers (52%, 58%, 68%), and 33 high-grade cancers (50%, 54%, 62%) within 95% CI across all three specificities (Figure 11C). Interestingly, when considering the approximately 4% decrease in specificity from >99% to 95%, all three subtypes exhibited a dramatic increase in mean sensitivity of 11% to 16%. Taken together, these results suggest that the EXPLORE study is not biased towards any subcohort within each cancer.

[0316] While detection of pancreatic and ovarian cancer requires a specificity of approximately 99% to be feasible for screening at a population level, it can be argued that bladder cancer may benefit from an even lower specificity threshold. Late-stage bladder cancer has a significant impact on quality of life and is the most expensive to treat, especially in the United States. Tests with higher sensitivity may help reduce the burden on both patients and the healthcare system by detecting more positives at earlier stages when treatment is simpler. Further false positives (due to low specificity) can be mitigated by the use of non-invasive, urine-based confirmatory tests.

[0317] In summary, a non-invasive test combining 13 exosomal proteins with age, a known cofactor in cancer, is being developed to detect stage I and II pancreatic, ovarian, and bladder cancer.

[0318] The three cancer types tested herein (pancreatic, ovarian, and bladder) are estimated to account for approximately 88,000 deaths in the United States in 2021, representing approximately 14% of all cancer-related deaths.

[0319] method

[0320] Sample collection and processing

[0321] All specimens for this study were obtained from a commercial biorepository (ProteoGenex, Culver City, CA, USA). Peripheral blood was collected under appropriate Institutional Review Board / Independent Ethics Committee approval, and all subjects provided informed consent. All subjects with a confirmed cancer diagnosis were treatment-naïve (prior to surgery, local and / or systemic anticancer therapy) at the time of blood collection. Demographic, surgical, and pathological information, as well as AJCC stage (7th edition), were provided by the biorepository and reviewed for accuracy by the study authors. Ovarian cancer patients did not uniformly undergo comprehensive surgical staging, so underlying disease higher than the assigned stage cannot be excluded. A total of 249 subjects were enrolled in the study, including 136 subjects diagnosed with one of the three cancers between January 2014 and September 2020 (the “cancer cohort patients”). In the cancer cohort, whole venous blood specimens were collected shortly after cancer diagnosis (median 1 day, mean 2.7 days) and before any surgical intervention, radiation therapy, or cancer-related systemic therapy. Median age was 59 years [IQR 54-67] in subjects with a known cancer diagnosis (n=136, 56 men, 82 women) and 53 years [IQR 45-61] in subjects with no history of cancer (n=113, 49 men, 64 women; Table S1). Whole blood samples were collected in K2EDTA plasma vacutainer tubes and processed to plasma within 4 hours of collection. A double spin was performed on whole blood at 1,500xg for 10 minutes at 4°C without brake. After the first spin, the plasma was transferred to a new tube and subjected to a second spin at 1,500xg for 10 minutes. After the second spin, the plasma was aliquoted into 1 mL tubes and frozen at -80°C within 1 hour. All specimens used in this study were treated under the same conditions.

[0322] Exosome isolation and particle characterization

[0323] Exosomes were extracted from 240 μL of plasma using an AC electrokinetic-based isolation method (Biological Dynamics, CA, USA) as previously described. Briefly, undiluted plasma was introduced into a Verita™ chip, in which exosomes were captured on the microelectrode. Residual plasma was washed away while the AC electrokinetic field was still activated to maintain capture. The AC electrokinetic field was then inactivated, releasing the exosomes from the microelectrode, and the solution containing the isolated exosomes was eluted for proteomic analysis. This method has also been traditionally used to isolate cell-free DNA and exosomal RNA, as well as to detect both solid tumors and hematological malignancies. After extraction, EVs were characterized using nanoparticle tracking analysis (NTA) via a ZetaView instrument (Particle Metrix, Inning am Ammersee, Germany). Table 3 shows the particle size and concentration values ​​of isolated exosomes.

[0324] Proteomic analysis

[0325] Bead-based immunoassay kits (Panel 1 of human circulating biomarker magnetic beads (Cat. No. HCCBP1 MAG-58K), Panel 2 of human angiogenesis magnetic beads (Cat. No. HANG2MAG-12K), and Panel 3 of human circulating cancer biomarkers (Cat. No. HCCBP3MAG-58K)) were produced from commercial sources (Millipore Sigma, Burlington, MA). Extracted exosome samples and released proteins were tested for target protein concentration on a MAGPIX system (Luminex Corp, Austin, TX). Final protein concentrations were determined using Belysa software v.3.0 (Luminex).

[0326] EXPLORE trial progress

[0327] After initially evaluating 54 proteins, 42 different biomarkers were selected for further analysis (Tables 4 and 5). In case of missing values ​​or results below the limit of detection (LOD), the value of that protein was set (imputed) to the LOD. The distribution of all biomarkers was evaluated. Considering the wide range of associated concentrations, and imputed LOD values ​​among the biomarkers, the distribution was found to be highly skewed. For this reason, a log2 transformation of all exosomal protein biomarker values ​​was used for subsequent analysis. Using the R modules "outlier" and "GmAMisc" for evaluation of outliers based on standard Grubbs and related tests, we found evidence for some extreme values, but none of them reached statistical significance considering the number of tests pursued, and the conservative Bonferroni correction of the associated p-values. An analysis based on their biomarker profile for abnormal individuals was also pursued in comparison to other individuals in the sample. Using the "hclust" module in R, a Euclidean distance matrix was constructed across individuals. One individual with an extreme profile compared to the others was identified and this individual was removed from further analysis. The correlation between biomarkers was explored using the R module "Corrplot" to determine the possibility of multicollinearity in the building classification models (correlation plots from measurements of all biomarkers are shown in Figure 16). The association of biomarkers to cancer diagnosis was explored using the R module "stats" by pursuing standard Student's t-tests, Wilcoxon non-parametric t-tests, and ANOVAs for each biomarker (Table 8). The results of these analyses, along with assessment of missing and imputed values, and a qualitative literature-based assessment of the biological relevance of each biomarker, were used to guide the selection of biomarkers to be evaluated in the logistic regression analysis.

[0328] Logistic regression analysis and receiver operating characteristic curve (ROC) analysis.

[0329] A classification model based on logistic regression was developed using biomarkers with the "caret" package in R, which we refer to as "EXPLORE". To pursue a fair evaluation of the model given the relatively small sample size and to avoid overfitting, we evaluated the performance of the EXPLORE classification model by generating 100 random data partitions, of which 66% were dedicated to the training set and 33% to the test set (Figure 9B). Receiver operating characteristic ROC curves, area under the curve (AUC), and related metrics were calculated. The ROC curve and AUC analysis of the training set yielded better predictive values ​​than those obtained from the test set analysis, as expected, but clearly reflected the possibility of overfitting. Therefore, the performance of the model is reported based on the training dataset, with a focus on the performance from the test set. The resulting model was used to evaluate the ability of EXPLORE to accurately detect individuals with different cancers and cancer stages, as well as to compare models based on release as opposed to exosomal protein levels. During the evaluation of the logistic regression module, the influence of each individual's profile on the resulting module was evaluated, for example, using the leverage statistic in the R module "car". Based on these analyses, four individuals had a consistently large influence on the model, and when these individuals were removed from the analysis, the performance of the model improved, but this performance improvement was not statistically significant from the performance of the model that retained these individuals (data not shown). To ensure the robustness of the model and its performance evaluation on subsets of individuals with different cancers and stages, these individuals were excluded from all further analyses.

[0330] Automated classifier analysis.

[0331] As a complement to the selection of biomarkers for use in the classifier, the use of stepwise logistic regression and LASSO-based logistic regression was considered for the automatic selection of biomarkers for the classification model using the R modules "caret" and "glmnet". The performance of the classifiers resulting from the application of these methods did not significantly improve the results, likely due to small sample sizes and multicollinearity between the biomarkers.

[0332] Further analysis and plotting

[0333] Further analyses and plots for both the main text and supplementary information were performed in GraphPad Prism (version 9.0.2) and JMP (version 14.1.0).

[0334] Example 5: Preparation of ACE-purified exosome samples for mass spectrometry Existing standard methods for preparing protein samples for mass spectrometry are not sufficient to extract proteins from exosomes due to their very low buoyant density and rigid lipid exterior. In addition, components of some elution buffers used to collect exosomes from the ACE chip can pose challenges to standard sample preparation methods for mass spectrometry. Therefore, the following method was utilized to ensure efficient extraction of the full range of proteins to be analyzed.

[0335] Using the elution protocol described above, exosomes were purified from human plasma using three separate chips, collected in elution buffer, and then pooled. To lyse the exosomes, 100 μL of sample was added to 900 μL of lysis buffer containing (1) a detergent such as 2% octylglucoside, (2) a protease inhibitor such as phenylmethylsulfonyl fluoride (PMSF), leupeptin, and / or ethylenediaminetetraacetic acid (EDTA), (3) a phosphatase inhibitor such as sodium orthovanadate, and (4) a denaturant such as 4-8 M urea. The mixture was vortexed for 5 min, followed by probe sonication consisting of three separate pulses of 5 s each, with the probe set at 20% of full power. To remove insoluble debris, the protein sample was centrifuged at 12,000 rpm for 10 min, and the supernatant containing the extracted proteins was collected. Protein disulfide bonds were reduced by the addition of 100 mM dithiothreitol (DTT) and subsequently alkylated with iodoacetamide. Total proteins were precipitated from the sample mixture by the addition of trichloroacetic acid (TCA).

[0336] To remove residual TCA, the precipitated samples were washed twice with ice-cold acetone. If the pH of the samples was too low, it was adjusted to neutral by the addition of NH4HCO3. The samples were then subjected to two separate enzymatic digestions, first using Lys C enzyme overnight at 37°C, followed by trypsin for 6 h at 37°C. To desalt the resulting peptide mixture, the samples were passed through a Waters C18 HPLC column, washed with aqueous solutions, and eluted with acetonitrile. Peptides were quantified using a Pierce Pepquant kit, and 50 μg of each sample was subjected to mass spectrometry.

[0337] Biomarker proteins identified by mass spectrometry of ACE-purified exosomes using the sample preparation method outlined above (Table 7)

[0338] [Table 7]

[0339] Example 6: Early multi-cancer detection using extracellular vesicle protein-based blood tests Extracellular vesicles (EVs) were isolated from both control plasma and plasma from stage I and II pancreatic, ovarian, and bladder cancer cases (Figure 17). EV populations isolated using alternating current electrokinetics (ACE) technology are consistent with the presence of exosomes according to the ISEV 2018 guidelines24 (mean particle size ~120 nm; CD63 positive; TSG101 detectable only after membrane permeabilization; rounded cup-like morphology as seen by scanning electron microscopy (SEM) imaging; with functional RNA). After EV isolation, particle size distribution and concentration were measured to confirm equivalent isolation for both cohorts (Figures 22A-C). All cancer cases were untreated to simulate a real-world screening scenario, and histopathological staging was confirmed using the American Joint Commission on Cancer (AJCC) guidelines to ensure that these cases were early-stage patients. The median age of the cancer cases was 60 years (59.7% women, 40.3% men). Notably, 63.3% of all cancer cases were stage I, while the remaining 36.7% were stage II. Furthermore, the stage I ovarian cohort contained the majority (60%) of stage IA specimens. The control group had no history of cancer or autoimmune disease and had a median age of 57 years (50.0% women, 50.0% men).

[0340] To evaluate the benefit of using ACE-isolated EVs in proteomic analysis, EVs were isolated from a subset of case and control patient samples using either ACE or differential ultracentrifugation (Figure 17). After isolation, the only physical difference observed between the two methods was a slight decrease in the mean particle size of EVs isolated when using ACE (138 nm for UC vs. 120 nm for ACE EVs, Figure 18A). Further breakdown of the particle size distribution is shown in Figures 23A-B. When EVs prepared by the two methods were evaluated for total plasma protein content, UC EV preparations were found to contain much higher levels than ACE EVs (Figure 18B). For example, contamination with the plasma protein IgG was much higher in the UC-isolated material (Figures 23A-B). This is consistent with previous reports that UC-prepared EVs are co-purified with protein and nucleic acid aggregates. Comparing EVs purified by the two different methods for their protein biomarker signals, we found a strong differentiation between cases and controls for two key biomarkers (CA19-9 and CA125) from ACE-isolated EVs, but not UC-isolated EVs (Figure 18C). A summary of EV measurements from both isolation techniques is shown in Table 8. These results confirm that ACE EV isolation can be a suitable tool to purify EVs directly from plasma, thus providing a relevant avenue for proteomic analysis. Moreover, EV isolation with ACE is more efficient, does not require additional pre- or post-processing steps, does not rely on immunoaffinity, and involves less sample handling that may damage EVs, with the entire process taking approximately 2 hours. Most importantly, ACE isolation of EVs, unlike UC, has the potential to be integrated into high-throughput automated systems.

[0341] [Table 8-1]

[0342] [Table 8-2]

[0343]

Table 8-3

[0344]

Table 8-4

[0345]

Table 8-5

[0346] The case-control study included measuring the levels of 42 EV-associated protein biomarkers for both the test cohort cancer cases (47 pancreatic, 44 ovarian, 48 bladder) and controls (184 controls) via multiplex immunoassays, with assessment of each protein level performed individually (heatmaps of normalized protein levels are shown in Figures 24A-B). In addition, levels of unpurified total circulating plasma proteins ("free proteins") were measured from the same test cohort (Figures 24A-B). To identify EV-associated protein biomarkers with the greatest differentiation potential, a selection process was utilized to select the most relevant biomarkers based on very high specificity (>99%) using recursive feature reduction with cross-validation (REFE). The use of iterative cross-validation performed best within the limitations of the sample size in this pilot study (N=323). A 5-fold cross-validation with 100 iterations was performed (Figure 19), and across all iterations, the RFE algorithm used stepwise backward selection to arrive at the optimal number of biomarkers that maximized the partial AUC (pAUC) (31). By optimizing p(AUC) between specificities of 0.75 and 1.00, the selection of biomarkers was tailored to reduce the occurrence of false positives (controls incorrectly called cancer), as this is important for MCED-type approaches to reduce the costs associated with false positive tests. This strategy resulted in the selection of 13 EV protein markers. After biomarker selection, we estimated the coefficient of each biomarker in a logistic regression model exploring the possibility of detecting cancer at an early stage by randomly splitting the cohort into a training set (67% of samples) and a "hold-out" set (33% of samples) stratified by cancer type (pancreatic, ovarian, and bladder) (Figure 19). The training set was used to estimate the individual logistic regression coefficients, and performance was simultaneously evaluated against a hold-out test set. Boxplots comparing cases and controls for the 13 selected biomarkers are shown in Figure 25, their coefficients and significance scores are shown in Table 9, and their Pearson correlation coefficients are shown in Table 10 and Figure 26.

[0347] [Table 9]

[0348] [Table 10-1]

[0349] [Table 10-2]

[0350] This performance evaluation was enhanced by utilizing a widely used statistical resampling process that better represents how a larger data set would perform. Resampling was used to evaluate whether the initial random partition created an unrealistic model due to the rare distribution of subjects in the initial partition. 100 training and test sets were randomly resampled from the entire data (2 / 3 and 1 / 3 of subjects, respectively), and 100 individual logistic fits were generated for the training partition. From these fits, individual ROC curves were created for the test set (Figure 20A). Similarly, each time a subject was characterized in the hold-out test set, a fit was generated for the subject's logistic model, which was then averaged over all the times that a particular subject was used in the test set, and from these average fits, the overall performance of the model was evaluated. The performance of each of the 100 randomly partitioned test sets was evaluated individually, and an average threshold for target specificity of >99% was calculated, allowing the determination of the overall average sensitivity and confidence interval.

[0351] When comparing the entire cancer case cohort with control individuals using the EV protein biomarker test, the mean AUC was found to be 0.95 (95% CI = 0.92-0.97) as shown in Figure 20A, and the mean sensitivity was found to be 71.2% (95% CI: 63.2-78.1) at 99.5% specificity (95% CI: 97.0-99.9) as shown in Table 11. For the average of 100 test sets, the AUC of the exoprotein was found to be greater than that of the equivalent plasma free protein, 0.95 vs. 0.87, respectively (Figure 27). Considering all three cancers tested, our EV protein test demonstrated a sensitivity of 70.5% (95% CI: 60.2-79.0) and 72.5% (95% CI: 59.1-82.9) for stage I and II patients, respectively (Figure 20B, Table 11). Furthermore, we analyzed the sensitivity at >99% specificity for each individual cancer and found values ​​of 43.8% (95%CI: 30.7-57.7) for bladder cancer, 75.0% (95%CI: 60.6-85.4) for ovarian cancer, and 95.7% (95%CI: 85.8-98.8) for pancreatic cancer (Figure 20C). These results suggest that EV proteins have the potential to detect early cancers with screening-relevant sensitivity.

[0352] [Table 11]

[0353] The 13 EV protein biomarkers identified herein span a wide range of biological functions that may represent pivotal points in cancer development. Neuropilin-1 and CA15-3 mediate aberrant growth factor signaling in early malignancies. CA19-9, MPO, and TIMP-1, known cancer drivers, were previously utilized in another multi-cancer study. Neuropilin-1 and sE-selectin are known driver genes of the angiogenesis process (37, 38), while exosomal cathepsin-D, MIA, IGFBP3, sFAS, and ferritin have been shown to affect tumor progression. Some of the proteins have previously been shown to be present in EVs. Total serum CA-125 has been approved for use in monitoring treatment response and recurrence in ovarian cancer, but is not recommended for use as a screening marker. Similarly, total serum CA19-9 is approved by the FDA for the treatment and monitoring of recurrence of pancreatic cancer, but importantly, it is not approved for screening, as CA19-9 can be naturally elevated in several benign conditions.

[0354] To further understand the potential utility of the test using EV proteins, the performance was evaluated for each cancer stage and compared with the sensitivity at 99.5% specificity determined from the overall analysis. Considering the relatively small sample size for each cancer type, the study demonstrated very high sensitivity in detecting both 22 stage I (95.5%; CI: 78.2-99.2) and 25 stage II PDAC patients (96.0%, CI: 80.5-99.3) (Figure 21A), indicating a potential major advancement in the early detection of this malignancy. Detection of stage I ovarian cancer (N=39) was also at a level with potential clinical impact (74.4%, CI: 58.9-85.4), as shown in Figure 21B. The ovarian cancer cohort was further classified into both aggressive serous adenocarcinoma histology leading to death (stage I / II, N=22) and stage IA (N=26), with sensitivities ranging from 68.2% (CI: 47.3-83.6) to 73.1% (CI: 53.9-86.3CI) at specificities of >99%, respectively. Early detection for either subtype may have a dramatic impact on survival as surgery is likely curative. In bladder cancer, as shown in Figure 21C, the study was able to detect 27 stage I patients at 44.4% (CI: 27.6-62.7) and 21 stage II patients at 42.9% (CI: 24.5-63.5). The low sensitivity in bladder cancer, compared with the high sensitivity in pancreatic and ovarian cancer, may reflect limitations on the availability of suitable biomarkers to detect early bladder cancer in the panels evaluated. In addition, bladder cancer is known to have high molecular and histological heterogeneity.

[0355] Taken as a whole, these results suggest that EV-based protein biomarker testing is not biased towards any subcohort within each cancer. It can be argued that detection of pancreatic ductal adenocarcinoma (PDAC) and ovarian cancer requires a specificity of approximately 99% to be feasible for screening at a population level, while bladder cancer may benefit from an even lower specificity threshold. In the emerging field of multi-cancer early detection (MCED) testing, while other tests have the potential to improve the prognosis of late-stage cancers, this test is unique because it can provide higher sensitivity for the detection of early cancers, as exemplified by a sensitivity of 96% in stage I and II PDAC cases.

[0356] As with any pilot study, there are limitations to the confirmation response. First, our relatively small sample cohort and inclusion of 100% early-stage tumors, while beneficial for biomarker discovery purposes, do not reflect the characteristics of a realistic cancer population and may have even lower sensitivity when screening a large asymptomatic population (5,8). However, it was decided to focus our cohorts exclusively on stages I and II, as survival is directly associated with early cancer detection. Second, both cohorts were ethnically homogenous, and the sex ratio of males to females may be skewed compared to the overall frequency observed for cancer (5). Subsequently, our control population consisted of individuals without a history of cancer or known confounding comorbidities (e.g., chronic pancreatitis) that may result in additional false-positive results in a true screening setting. Finally, this pilot study requires independent external validation using a larger cohort of blinded samples to validate the potential utility of this MCED approach.

[0357] In summary, we have developed a blood-based EV protein detection test and demonstrated its potential role for MCED. The EV protein biomarker test requires less than 500 μL of plasma, allowing integration into an automated workflow. Using a non-invasive blood-based approach, we selected a panel of 13 EV proteins that enabled the detection of stage I and II pancreatic, ovarian, and bladder cancer with high diagnostic performance (AUC=0.95) along with age, a known cofactor in cancer (54). Most importantly, we obtained a sensitivity of 71.2% with high specificity (99.5%), a factor important for future screening efforts. This test is the first to effectively utilize EVs in early cancer detection via an AC electrokinetic, lab-on-a-chip, scalable platform. The Verita™ platform has multi-omic detection capabilities, allowing the addition of other exoproteins, exosomal mRNA, and / or circulating DNA biomarkers.

[0358] Materials and Methods

[0359] Sample collection and processing

[0360] All specimens in this retrospective study were collected over several years by a commercial biorepository (ProteoGenex, Inglewood, CA, USA). Stage I and II samples were selectively obtained from available stock. Samples were collected from patients in an in-house setting and maintained by a commercial biorepository after collection. In the in-house setting, patients with possible cancer were identified by any suspicious findings occurring during imaging, either according to the patient's symptoms or as part of routine annual examinations. Information on which patients were symptomatic and which were asymptomatic was not available. Cancer was confirmed by subsequent tissue biopsy and staged according to AJCC guidelines (7th edition) by in-house pathologists using pathology and surgical reports, with concurrent imaging to assess any spread to distant sites. All subjects with a confirmed cancer diagnosis were treatment-naïve (prior to surgery, local and / or systemic anticancer therapy) at the time of blood collection. Patient samples were obtained from the biorepository along with demographic, surgical, and pathological information. Through analysis of these data, the second patient staging was examined for accuracy. Ovarian cancer patients did not uniformly undergo comprehensive surgical staging, so underlying disease higher than the designated stage cannot be excluded. The control group had no history of cancer, autoimmune disease, or neurodegenerative disease, as well as the presence of diabetes mellitus (types 1 and 2). A total of 323 subjects were enrolled in the study, including 139 subjects diagnosed with one of the three cancers between January 2014 and September 2020 (the "cancer case patient cohort"). In the cancer case cohort, whole venous blood samples were collected immediately prior to biopsy (median -1 day, mean -2.7 days) and before surgical intervention, radiation therapy, or cancer-related systemic therapy. Median age was 60 years [min 21-max 76] in the cancer case cohort (N=139, 56 men and 83 women) and 57 years [min 40-max 71] in the control cohort (N=184, 82 men and 82 women). Whole blood samples were collected into K2EDTA plasma vacutainer tubes and processed to plasma within 4 hours of collection. First, whole blood was spun at 1,500xg for 10 minutes at 4°C with no brake.After the first spin, the plasma was transferred to a new tube and subjected to a second spin at 1,500xg for 10 min. After the second spin, the plasma was aliquoted into 1 mL tubes and frozen at -80°C within 1 h. All specimens used in this study were processed under the same conditions.

[0361] EV / exosome isolation and particle characterization

[0362] Isolation of EVs using AC electrokinetics

[0363] EVs, including exosomes, were extracted from plasma using an AC electrokinetic (ACE)-based isolation method (Biological Dynamics, CA, USA) as previously described. Briefly, 240 μL of undiluted plasma was introduced into each Verita™ chip, and plasma was flowed across the chip at 3 μL / min for 120 min while applying an electrical signal of 7 Vpp and 14 KHz. EVs were captured on the energized microelectrode array, and unbound material was washed off the chip with Elution Buffer I (Biological Dynamics) at 3 μL / min for 30 min. The electrical signal was turned off, releasing EVs into the solution remaining on the chip (35 μL), which was later collected, and the solution containing purified, enriched / eluted EVs was used directly for further analysis. This method has also been used previously for the isolation of cell-free DNA, exosomal RNA, and exosomal protein markers in both solid tumors and hematological malignancies (25,26,55-58). Verita purified EVs were characterized using nanoparticle tracking analysis (NTA) via a ZetaView instrument (Particle Metrix, Inning am Ammersee, Germany). Figures 22A-22C show exosome particle size and concentration values ​​compared between case and control cohorts.

[0364] Isolation of EVs by differential ultracentrifugation

[0365] A subset of case and control samples were subjected to differential ultracentrifugation as a conventional means of EV isolation. Briefly, 760 μL of 1× PBS was added to 240 μL of plasma each, then spun consecutively at 500×g for 10 min, 3000×g for 20 min, and 12,000×g for 20 min, with the supernatant collected after each step. The resulting supernatant was subsequently subjected to ultracentrifugation at 100,000×g for 70 min, and the pellet was washed with 1× PBS before being subjected to ultracentrifugation again at 100,000×g for 70 min. The supernatant was discarded, and the resulting pellet was resuspended in 120 μL of 1× PBS for further analysis.

[0366] Protein contamination analysis

[0367] To determine the presence of total contaminating proteins in the EV preparations by both the Verita™ platform and differential ultracentrifugation processes, samples were analyzed using a Qubit4 Fluorometer (ThermoFisher Scientific, Waltham, MA) with the Qubit™ Protein Quantitation Assay (Cat. No. Q33212, ThermoFisher Scientific, Waltham, MA) and run according to the manufacturer's specifications. To further understand the composition of contaminating proteins on the isolated products, a 2100 Bioanalyzer (Agilent, Santa Clara, CA) was used with the Protein 230 kit for protein analysis (Cat. No. 5067-1517) according to the manufacturer's instructions.

[0368] Protein biomarker analysis

[0369] Verita-isolated EV samples, as well as the original unpurified plasma samples from the same patients, were used directly in a commercial multiplex immunoassay to quantify the presence of marker proteins. Briefly, 2 × 35 μL of each purified EV sample was used for analysis with each of three different bead-based immunoassay kits according to the manufacturer's instructions for each kit (Human Circulating Biomarker Magnetic Bead Panel 1 (catalog no. HCCBP1MAG-58K), Human Angiogenesis Magnetic Bead Panel 2 (catalog no. HANG2MAG-12K), and Human Circulating Cancer Biomarker Panel 3 (catalog no. HCCBP3MAG-58K); Millipore Sigma, Burlington, MA). Protein biomarker concentrations were assessed using the MAGPIX system (Luminex Corp, Austin, TX) according to the manufacturer's protocol. Final protein concentrations were determined from calibration curves using Belysa software version 3.0 (EMD Millipore). The limits of detection (LOD) and units of measurement for each of the biomarkers are listed in Table 12.

[0370] [Table 12-1]

[0371] [Table 12-2]

[0372] EV isolation model spiked for EV biomarker signals

[0373] To further understand the presence of relevant protein biomarkers on EVs, EVs purified from cell culture supernatants representing two different cell lines were utilized as positive controls. The cell line H1975 (ATCC CRL-5908™) is known to express the CA19-9 marker, while the cell line HeLa (ATCC CRM-CCL-2™) is known to express the CA125 marker. Briefly, H1975 EVs were spiked into K2EDTA plasma at three different dilution ratios (1:200, 1:400, and 1:800 from the original UC preparation) and EVs were isolated using the Verita™ platform and subsequently analyzed for the presence of CA19-9 biomarkers on the Luminex platform (Figures 28A-B). In a separate experiment, H1975 EVs and HeLa EVs were spiked into K2EDTA plasma and isolated using the Verita™ platform. Biomarker readout confirms positive detection of the expected signals: CA19-9 is elevated in H1975 EVs, and CA125 is elevated in HeLa EVs (Figures 28A-B).

[0374] Progression of EV / exoprotein biomarker trials

[0375] Biomarker Selection

[0376] From the initial evaluation of 42 EV proteins, we observed 34 distinct biomarkers with less than 50% of samples missing or below the limit of detection (LOD) (Table 12). In the case of missing values ​​or results below the LOD, values ​​were set (imputed) to the LOD. The distribution of all biomarkers was evaluated and found to be broad. For this reason, a Log2 transformation was used for all EV protein biomarker values ​​in the subsequent analysis. Potential multicollinearity in building classification models was determined by exploring correlations between biomarkers using the R module "Corrplot" (correlation heatmaps from measurements of all biomarkers are shown in Figures 29A-B). Recursive feature reduction with cross-validation was then utilized to determine the most informative biomarkers. This methodology uses four of the five folds to select a subset of biomarkers using stepwise backward selection. This process was repeated five times, using each fold once as a holdout test set. The cross-validation split was chosen randomly, and this was repeated 100 times to select the subset of biomarkers that maximized the partial AUC (pAUC) at specificity ranging from 75% to 100% across the entire test set.

[0377] Coefficient determination and performance evaluation

[0378] Once the biomarkers were selected, the initial split of the data into a training set (67%) and a test set (33%) stratified by cancer type allowed the performance of the selected biomarkers to be determined by estimating the regression coefficients of the model using the training set and evaluating the classification performance in the hold-out test set (Figure 19). In order to pursue a fair evaluation of the model given our relatively small sample size and to avoid overfitting, 100 independent training and test sets (composed of 2 / 3 and 1 / 3 of the 323 individuals stratified by cancer type) were resampled from the entire dataset. For each resampling, the subjects of the training set were used to estimate the biomarker regression coefficients in the model, while the diagnostic performance was evaluated independently for the subjects of the hold-out test set. Receiver operating characteristic (ROC) curves, areas under the curve (AUC), sensitivity, specificity, and related metrics were calculated for the test set based on the individual fits for each of the subjects in each partition. For each test set, a threshold call of >99% specificity was calculated (since there were 61 controls in each test set, this effectively means calling 61 of 61 correctly), followed by calculating the mean threshold. The mean threshold and mean fit in the test set per subject were used to evaluate performance for the entire cohort as well as for subcohorts (e.g., pancreatic cancer). A bias-corrected bootstrap method (N=2000) was used to calculate 95% confidence intervals for the AUC, while confidence intervals for the performance metrics, i.e., sensitivity and specificity, were calculated based on the Wilson two-sided method. During the evaluation of the logistic regression models, the importance of each selected biomarker was evaluated using the mean standardized coefficient (Table 9). Here, "importance" can be understood as a quantitative comparison between predictors. One predictor is more important than another if it contributes more to the prediction of the response variable across all models considered in the regression.

[0379] While preferred embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will occur to those skilled in the art without departing from the invention. It is understood that various alternatives to the embodiments of the invention described herein may be utilized in carrying out the invention. It is intended that the following claims define the scope of the invention, and that methods and structures within the scope of these claims, and their equivalents, be covered thereby.

Claims

1. 1. A system for identifying biomarkers as associated with a disease state, comprising: (a) a first high dielectrophoretic (DEP) region configured to isolate a first plurality of analytes in a first biological sample of an individual known to have a disease state using an electrode array configured to generate an AC dielectrophoretic field, the first DEP region configured to isolate a subset of the first plurality of analytes; (b) a second DEP region configured to isolate a second plurality of analytes in a second biological sample of a healthy individual using an electrode array configured to generate an AC dielectrophoretic field; the subsets are quantitatively different in the first biological sample compared to the second biological sample; The subset is identified as associated with the disease state.

2. The system described in claim 1, wherein the first DEP region is produced using an alternating current having an amperage of 0.1 microamperes to 10 amperes.

3. The system described in claim 1, configured to capture the first plurality of analytes or the second plurality of analytes on one or more electrodes.

4. The system of claim 1 , further comprising a mass spectrometer for mass analysis of the first plurality of analytes and the second plurality of analytes.

5. The system of claim 1 , wherein identifying the subset comprises quantifying each of the first plurality of analytes and the second plurality of analytes.

6. The system of claim 1 , wherein the first plurality of analytes comprises proteins or polypeptides.

7. The system of claim 1 , wherein the first plurality of analytes comprises nucleic acids.

8. 10. The system of claim 1, wherein the first plurality of analytes comprises exosomes.

9. The system of claim 1, further comprising a module capable of thermal cycling or performing PCR on the first plurality of analytes and the second plurality of analytes.

10. The system of claim 1 , wherein the disease state is cancer, a neurological disease, an infectious disease, or an inflammatory disease.

11. The cancer is pancreatic cancer, ovarian cancer, bladder cancer, colon cancer, lung cancer, brain cancer, prostate cancer, breast cancer, skin cancer, lymphoma, tongue cancer, oral cancer, pharyngeal cancer, oral cavity cancer, 11. The system of claim 10, wherein the cancer is selected from the group consisting of cancer of the esophagus, stomach, small intestine, colon, rectum, anus, anorectal, liver, intrahepatic bile duct, gallbladder, biliary tract, digestive system, laryngeal, bronchial, respiratory, bone, joint, soft tissue, heart, melanoma, non-epithelial skin, uterine, cervical, vulvar, vaginal, penis, reproductive system, testicular, kidney, renal pelvis, ureter, urinary system, eye, orbit, nervous system, endocrine, thyroid, Hodgkin's lymphoma, non-Hodgkin's lymphoma, myeloma, acute lymphocytic leukemia, chronic lymphocytic leukemia, acute myeloid leukemia, chronic myeloid leukemia, or leukemia.

12. The system of claim 1, wherein the biomarkers include one or more proteins provided in Table 5.

13. The system of claim 12, wherein the one or more proteins include tenascin-C, sAXL, sE-selectin, sVEGFR3, sc-kit / SCFR, CA125, CA15-3, CA19-9, CEA, FGF2, HEA, HGF, IL-6, IL-8, leptin, MIF, OPN, prolactin, SCF, TNFa, TRAIL, VEGF, b-HCG, total PSA, sFAS, capthepsin D, FAP alpha, ferritin, galectin-3, IGFBP3, MIA, MPO, SHBG, TIMP1, TIMP2, or a combination thereof.

14. The system of claim 1, wherein the biomarkers include one or more proteins provided in Table 4.

15. The system of claim 1, wherein the first DEP field region and the second DEP field region are integrated into a device.

16. The system of claim 1, wherein the first DEP field region and the second DEP field region are in separate devices.

17. A method for identifying a therapeutic target, comprising: (a) isolating a first plurality of analytes in a first biological sample of an individual known to have a disease condition using an electrode array configured to generate an AC dielectrophoretic field; (b) isolating a second plurality of analytes in a second biological sample of a healthy individual using electrodes configured to generate an AC dielectrophoretic field; (c) identifying a subset of the first plurality of analytes that is quantitatively different in the first biological sample compared to the second biological sample and is identified as the therapeutic target; The method includes:

18. The method of claim 16, wherein (c) includes mass spectrometry of the first plurality of analytes and the second plurality of analytes.