Methods for detection and personalized treatment of early stage, advanced or metastatic cancers using precision oncology
Patent Information
- Application Number
- PCT/US2026/021386
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2026-02-09
- Filing Date
- 2026-03-27
- Publication Date
- 2026-10-01
Smart Images
Figure US2026021386_01102026_PF_FP_ABST
Abstract
Description
ONCO-25-OQ2-WOMETHODS FOR DETECTION AND PERSONALIZED TREATMENT OF EARLY STAGE, ADVANCED OR METASTATIC CANCERS USING PRECISION ONCOLOGYBACKGROUND
[0001] The field of oncology has long been engaged in the pursuit of effective treatments for cancer, a leading cause of mortality worldwide. Traditional cancer therapies have included surgery, radiation, and systemic treatments such as chemotherapy, targeted therapies, immunotherapies, hormonal therapy, and biologies. These treatments aim to manage tumor burden and improve patient survival rates.
[0002] Despite advancements in cancer treatment, the heterogeneity of tumors and the variability in patient responses to therapies present significant challenges. The development of personalized medicine, which tailors treatment to individual patient characteristics, has emerged as a critical area of research. This approach often involves genomic profiling to identify targetable mutations within cancer cells. However, the presence of non-targetable mutations and the limited number of patients who benefit from targeted therapies highlight the need for additional methods to optimize treatment strategies.
[0003] Recent publications have described generation of three-dimensional (3D) bladder cancer organoids from urine samples (Viergever et al., Br J Cancer 2023; Walz et al., Cells 2023). These methods require culturing cells in basement membrane extract (Matrigel) and achieve success rates of 55-83%. While promising for research applications, these 3D organoid methods face significant limitations for use in clinical applications such as drug responsiveness testing, including requiring extended culture time to form organoids (7-14 days) and additional time to perform cell culture and drug responsiveness testing, high cost of basement membrane matrices, technical complexity, and variable success rates for culture. Furthermore, the structure of 3D organoids necessarily includes complications for assessing drug effectiveness because of cell-to-cell interactions that cannot be controlled for, which areONCO-25-OQ2-WO not present in a 2D monolayer culture. The present disclosure overcomes these limitations by providing a rapid, cost-effective method using conventional two-dimensional (2D) monolayer culture with >90% success rates.SUMMARY
[0004] The disclosure provides methods, systems and non-transitory computer readable medium claims directed to rapid detection of cancer cells in patients and personalized cancer treatment for patients.
[0005] In a first aspect, a method for guiding personalized cancer treatment for a patient suspected of having early stage, advanced, or metastatic cancer is disclosed. The method includes (a) preparing cell culture from a patient specimen containing malignant cells; (b) isolating and growing one or more cell monolayers from one or more patient specimen, the one or more monolayers comprising malignant cells; (c) exposing cells from the one or more monolayers to at least one candidate therapeutic agent at an appropriate range of clinically significant concentrations; (d) preparing a dose-response curve for each candidate therapeutic agent; (e) scoring responsiveness of the cells to a candidate therapeutic agent by calculating an area under the dose-response curve to determine 50% cell death (IC50); (f) comparing IC50 value to the peak plasma concentration (Cmax) for each candidate therapeutic agent tested to determine drug inactivity (Cmax cell death below 50%); (g) evaluating active candidate therapeutic agents likely to show a positive response (PR) for the patient’s clinical outcome when the malignant cells exhibit high cell growth inhibition (i.e., low IC50 value) to treatment with a candidate therapeutic agent; and (h) generating personalized treatment guidance for the patient based on the identified active candidate therapeutic agents.
[0006] In a second aspect, a system for guiding personalized cancer treatment according to the method disclosed in the first aspect is disclosed. The system includes: (a) an in-vitro / ex-vivo module configured to perform functional cell-based assays on a biologicalONCO-25-OQ2-WO sample; and (b) a treatment guidance module configured to generate personalized treatment guidance based on the results for assessing and determining active candidate therapeutic agents with a positive response.
[0007] In a third aspect, a non-transitory computer readable medium containing instructions that, when executed by a processor, perform a method for providing guidance for personalized cancer treatment. The method performed by the instructions from the non-transitory readable medium includes: (a) receiving and parsing instrument data outputs from a functional cell-based assay exposing isolated malignant cells to one or more candidate therapeutic agents at an appropriate range of clinically significant concentrations according to claim 1; (b) preparing a dose-responsive curve for each candidate therapeutic agent, parsing plot parameters and scoring responsiveness of the cells to each candidate therapeutic agent; (c) deriving drug metrics and assessing and determining active candidate therapeutic agents likely to show positive response (PR) for a patient’s clinical outcome when malignant cells exhibit high activity to treatment with a candidate therapeutic agent; and (d) generating personalized treatment guidance for a patient based on identified active and inactive candidate therapeutic agents.
[0008] The features, functions, and advantages that have been discussed can be achieved independently in various examples or may be combined in yet other examples further details of which can be seen with reference to the following description and drawings.BRIEF DESCRIPTION OF THE DRAWINGS
[0009] FIG. 1 depicts a block diagram of a computing device and a computer network, according to an example implementation;
[0010] FIG. 2 is a flowchart of example methods directed to processes that provide personalized treatment guidance for an individual patient based on evaluating active candidateONCO-25-OQ2-WO therapeutic agents to demonstrate a likelihood of a clinical response in a patient or to correlate between assay results and predictive biomarkers, according to example implementations;
[0011] FIG. 3 is a flowchart of example methods directed to processes that provide for evaluating active candidate therapeutic agents for potential patients based on a trained machine learning (“ML”) model or algorithm to determine outcomes for an individual patient if treated with specific candidate therapeutic agents, and optionally to correlate between assay results and predictive biomarkers, according to example implementations;
[0012] FIG. 4 is a chart with images directed to results of optimizing media and cell growth methods for reproducible viability and efficient growth of cancer cells. Urine samples processed from patients with Non-Muscle Invasive Bladder Cancer (NMIBC) or Muscle Invasive Bladder Cancer (MIBC), both high grade and low grade. Samples processed 24 hours after collection exhibited no loss of viability and results were confirmed with pathology reports for presence of cancer cells;
[0013] FIG. 5 is a flowchart of an example timeline demonstrating integration of OncoChoice® into workflow in accordance with a typical clinical time frame for treating NMIBC patients;
[0014] FIG. 6 is a chart with images directed to OncoChoice® results in patients with NMIBC: FIG. 6a - FIG. 6c: Phase contrast microscopy images show isolation and growth of cancer cells from urine of NMIBC patients using OncoChoice® test across NMIBC subtypes (low grade or high grade tumors); FIG. 6d: OncoChoice® results demonstrate distinct tumor response for each treatment, based on drug activity using algorithmically-derived metrics of dose-response curves and clinically relevant drug concentrations;
[0015] FIG. 7 depicts images directed to use of disclosed methods to reproducibly isolate and grow cancer cells from urine of patients with NMIBC. Phase contrast images were taken at different time points using EVOS m5000 microscope (Thermo Fisher Scientific);ONCO-25-OQ2-WO
[0016] FIG. 8 is a chart directed to OncoChoice® results in patients with NMIBC. Results for eight (8) patients demonstrate distinct tumor response for each treatment, based on drug activity using algorithmically-derived metrics of dose-response curves and clinically relevant drug concentrations;
[0017] FIG. 9 is a chart showing details for four (4) patients confirmed to have advanced non-small cell lung cancer (“NSCLC”) based on isolation and growth of cancer cells from pleural effusion biospecimen, and providing OncoChoice® assay results, as well as proposed treatment based on assay results;
[0018] FIG. 10 is a chart directed to OncoChoice® assay results showing concentration of FDA-approved drugs used in treatment of NSCLC required to kill 50% of cancer cells (nM) for a specific NSCLC patient with lung adenocarcinoma and including a comparison to published doses and plasma concentrations of these drugs;
[0019] FIG. 11 depicts images directed to isolation and cell growth methods for reproducible viability of NSCLC cells. FIG. 1 la - FIG. lie: Images showing lung cancer cells isolated from pleural effusion biospecimen from five (5) patients and showing growth at various time points after isolation using EVOS m5000 phase contrast microscope;
[0020] FIG. 12 depicts images directed to results of optimizing media and cell growth methods for reproducible viability and efficient growth of cancer cells for pancreatic cancer, PNET subtype. FIG. 12a -FIG. 12b: Images showing PNET cancer cells isolated from a solid tumor using mechanical digestion, and growth of the cells at various time point after isolation, with growth shown using Laxco digital camera connected to an inverted microscope (Fisher); FIG. 12c: Images showing PNET cancer cells isolated from solid tumor using both mechanical and enzymatic digestion, and growth at various time points after isolation, with growth shown using Laxco digital camera connected to an inverted microscope (Fisher) and EVOS m5000 phase contrast microscope; andONCO-25-OQ2-WO
[0021] The drawings are for the purpose of illustrating examples, but it is understood that the inventions are not limited to the arrangements and instrumentalities shown in the drawings.DETAILED DESCRIPTIONOverview
[0022] The ability to predict a patient’s response to general cytotoxic or targeted therapeutics in the clinic remains a long-sought but elusive goal. The overall objective in personalized medicine is to eradicate a patient’s cancer via control of the tumor burden, reduction of cancer-related symptoms, increase of progression free survival (PFS), overall survival (OS), and objective response rate (ORR) which measures the proportion of patients that experience a reduction in tumor size following specific treatment. The current clinical methods of providing individualized treatment (also known as precision medicine — matching a drug to patient-specific features) encompass genomic and functional approaches.Genomic Precision Medicine
[0023] The fundamental basis for genomic precision medicine involves identification of specific somatic alterations in cancer patients that can guide the development of targeted therapeutics for such abnormalities and improve a patient’s overall survival. Somatic mutations are categorized as “driver” and “passenger” alterations and include point mutations, deletions, translocations, amplifications, and chromosomal aberrations. (Letai, A. Nat. Med. 2017) (Martincorena, I & Campbell, P.J. Science 2015). Therapeutics that target these alterations have been successfully developed and demonstrated patient benefits, giving rise to a new translational strategy in a clinical setting. However, despite the many genomic advances that identified “druggable” mutations and enabled development of effective targeted therapeutics, few patients benefit from these drugs and only modest clinical benefit has been identified primarily through non-randomized retrospective studies. For example, a recent study showsONCO-25-OQ2-WO that between 40-60% of patients with Non-Small Cell Lung Cancer (“NSCLC”) lack an actionable mutation. (Steeghs, E., et al, Lung Cancer, 167:87-97 (2022)). Another study shows that at least 40% of patients with NSCLC lack an actionable driver mutation or a high level of PD-L1 expression, and for these patients the treatment landscape is still evolving. (Johnson, M., MD, et al. Am. Soc. Clin. Oncol. Ed. Book, 696-707 (2018)). Additionally, a large population of patients harbor numerous “non-druggable” aberrations that render them insensitive to targeted drugs; thus, while genomic methods are a good first step, personalized treatment in a clinical setting cannot rely exclusively on such methods.Functional Precision Medicine
[0024] Functional precision medicine involves monitoring of cancer cells upon exposure to a single therapeutic or a combination of therapeutics. Most of the commonly used chemotherapeutics in the clinic were discovered through some form of phenotypic-based observation, thus highlighting the importance and advantages of functional precision medicine. Genomic and functional methods complement each other such that they should be considered simultaneously when evaluating and determining the optimal drug regimen for individual cancer patients. Given that clinical decision-making is time sensitive, methods with a fast turnaround should be favored. The methods and systems disclosed herein provide improved functional methods that enable testing the activity of candidate therapeutic agents on primary cancer cells isolated and grown to confluency from a sufficient sample in a clinically suitable time frame of between 48 and 120 hours. Accordingly, this disclosure enables accurate testing of such candidate therapeutic agents on individual patients in a timely manner.Analytical Methods to Assess Responsiveness of Malignant Cells to Candidate Agent(s)
[0025] Aspects of this disclosure involve determining a cell death index within a dose range and calculating the area under the curve for the resulting dose-response curve to achieve 50% cell death (IC50) accounting for the relevant clinical dosage (i.e., peak plasmaONCO-25-OQ2-WO concentration, where IC50 < Cmax). The IC50 for a candidate agent with desired response (active agent) accurately reflects the sensitivity of cells to in-vitro / ex-vivo therapy exposure, and accounts for differences in dose-response curves. Thus, according to some aspects, the disclosure provides analytical methods for scoring the responsiveness of patient’s malignant cells to candidate therapeutic agents, thereby allowing accurate evaluations of candidate therapy response. This allows for distinguishing responsiveness of malignant cells to different candidate therapeutic agents and informing treating physicians and patients on the best treatment regimen.
[0026] In other aspects, the invention provides methods for evaluating and determining effectiveness of potential therapies approved in each cancer (e.g., chemotherapy and targeted therapy), such as testing different candidate therapeutic agents used to treat a type of cancer. In some aspects, this cancer is metastatic breast cancer (“MBC”), non-small cell lung cancer (“NSCLC”), small-cell lung cancer (“SCLC”), colorectal cancer, renal cancer, pancreatic cancer, including pancreatic neuroendocrine tumor (“PNET”) and pancreatic ductal adenocarcinoma (“PDAC”) subtypes, gastrointestinal cancer, ovarian cancer, fallopian cancer, primary peritoneal carcinoma (“PPC”), or bladder cancer, including non-muscle invasive bladder cancer (“NMIBC”) and muscle-invasive bladder cancer (“MIBC”) subtypes. In further aspects, this cancer is any early stage, advanced or metastatic cancer. In some aspects, this cancer is a cancer of unknown primary tumor, or other metastatic cancer of solid tumor origin.
[0027] In some aspects, a clinically appropriate specimen is obtained from a patient based on a specimen suspected of containing or that contains malignant cells or shedding malignant cells. In some aspects, the types of specimen that are clinically appropriate for each patient depends on the type of cancer present in the patient. In some aspects, clinically appropriate specimen contain fluids suspected of containing or that contain malignant cells. In some aspects, clinically appropriate specimen can be collected from a core needle biopsy, solidONCO-25-OQ2-WO tumor biopsy, or any procedure to remove biological fluid (e.g., paracentesis, thoracentesis). In some aspects, appropriate patient specimens may include but not be limited to pleural effusions, peritoneal effusions, ascites, urine, blood, tissue or fluid collected during a solid tumor biopsy, tissue or fluid collected during a core needle biopsy or other fluid removal procedure, or any other specimen suspected of containing or that contain malignant cells or shedding malignant cells.
[0028] In some aspects, this disclosure provides methods to evaluate and determine effectiveness of specific candidate therapeutic agents, including but not limited to chemotherapy drugs, small molecule drugs, cell permeable Antibody Drug Conjugates (“ADC”), oncolytic viruses, drug-delivery systems and associated drug-delivery devices, off-label drugs, investigational drugs, repurposed drugs, or any current or new therapeutic agent capable of being tested in vitro / ex-vivo, as selected at the discretion of the treating physician. In additional aspects, this disclosure evaluates and determines the effectiveness of specific candidates of any of the above therapeutic agents, selected at the discretion of the treating physician, either individually or as combination therapeutics, for activity against early stage, advanced, or metastatic cancer cells in individual patients. In additional aspects, the disclosure evaluates and determines the effectiveness of candidate chemotherapy agents from drug classes including, but not limited to taxanes, vinca alkaloids, nucleoside metabolic inhibitors, platinum-based drugs, Topo 1 inhibitors, Topo 2 inhibitors, mitotic inhibitors, alkylating agents, DNA-damaging agents, antibiotics, antimetabolites, and anthracyclines, or other chemotherapeutics used for treating patients with advanced or metastatic cancer, as selected at the discretion of the treating physician. In additional aspects, the disclosure evaluates and determines the effectiveness of candidate therapeutic agents, including but not limited to chemotherapy agents from drug classes including but not limited to taxanes, antimetabolites, or alkylating agents, drug-delivery systems and associated drug-delivery devices, oncolyticONCO-25-OQ2-WO viruses, or other therapeutics used for treating patient with early stage cancers, such as NMIBC bladder cancer, pancreatic cancer, or advanced or metastatic cancers, as selected at the discretion of the treating physician.
[0029] In further aspects, the disclosure evaluates and determines the effectiveness of specific candidate chemotherapy agents including but not limited to 5 -Fluorouracil (“5-FU”), Abraxane, Alkeran, Axitinib, Belzutifan, Cabazitaxel, Cabozantinib, Capecitabine, Carboplatin, Carmustine, Cisplatin, Cyclophosphamide, Docetaxel, Doxorubicin, Daunorubicin, Epirubicin, Eribulin, Mesylate, Estramustine, Etoposide, Everolimus, Gemcitabine, Ifosfamide, Irinotecan, Ixabepilone, Lenvatinib, Mitomycin C, Mitoxantrone, Methotrexate, Niraparib, Olaparib, Oxaliplatin, Paclitaxel, Pazopanib, Pemetrexed, Procarbazine, Rucaparib, Sorafenib, Sutinib, Talazoparib, Temozolomide, Temsirolimus, Tivozanib, Topotecan, Trifluridine, Vinblastine, Vincristine, and Vinorelbine, small molecule drugs, cell permeable Antibody Drug Conjugates (“ADC”) like deruxtecan, which can be tested individually or as combination therapeutics for activity against early stage, advanced or metastatic cancer cells, with candidate agent(s) selected and modified by treating physicians. This disclosure evaluates and determines the effectiveness and payload of drug delivery systems through delivery devices (e.g., TAR200) designed to provide controlled release of one or more therapeutic agents to the patient locally over a specified period of time. Furthermore, this disclosure evaluates and determines the effectiveness of specific candidate immunotherapeutic agents including but not limited to oncolytic viruses (e.g., CG0070). As just one example, in vitro / ex-vivo exposure of malignant cells to taxanes or other MBC chemotherapeutics is an independent predictor of a positive outcome (e.g., PR) to chemotherapy regimen comprising of taxanes. (Liebers et al. Nat. Cancer, 4(12): 1648-1659 (2023)). This disclosure thereby supports individualized treatment decisions, including decisions involving treatment with any of the above candidate targeted therapeutic agents.ONCO-25-OQ2-WO Materials and MethodsCulturing Primary Cells from Malignant Fluids
[0030] Under sterile conditions following aseptic laboratory technique, malignant fluids from solid tumors (e.g., pleural effusions, peritoneal effusions, or ascites) are transferred to 50 mL sterile tubes (Corning, Shiphol Rijk, The Netherlands) and centrifuged at between 1000 to 1400 rpm for between 10 to 15 min at 4 degrees. Once the supernatant is removed, cells are washed and re-suspended in growth medium (RPMI 1640 enriched with fetal bovine serum, FBS). After evaluation of viability, cells are seeded at a density of 3 * 106cells / mL in 75 cm2tissue culture flasks at 37°C and 5% CO2. Culture medium is changed accordingly. When cultures reach sub-confluence, cells are sub-cultured at a dilution of 1 :2 until they begin to grow rapidly. If testing is not performed once cells reach confluency, cells should be subcultured at a dilution of 1 :5 as needed until testing is performed.Culturing Primary Cells from Urine Suspected to Contain or that Contains Cancer Cells
[0031] Urine collected prior, during, and / or after Transurethral Resection of Bladder Tumor (TURBT) in a patient with suspected or confirmed malignant bladder cancer is washed with an equal amount of cold PBS (Dulbecco’s Phosphate Buffered Saline, Gibco Life Technologies, Carlsbad, CA, USA) and stored at 4 degrees until processing. Mixture is then transferred to sterile 50mL tubes and centrifuged 250-500g for 10 min at 4 degrees. Urine supernatant is decanted off, leaving ImL to resuspend the supernatant. Urine supernatant is washed with cold PBS. Mixture is centrifuged again 250-500g for 10-15 min at 4 degrees. Once the supernatant is removed, cells are washed and re-suspended in growth medium (advanced DMEM / F12 enriched with fetal bovine serum, FBS, and Penicillin / Streptomycin 10,000 unites / mL (Thermo Fischer, Waltham, MA, USA)). Growth medium further comprises growth factors FGF7 (25ng / ml), FGF10 (lOOng / ml), FGF2 (12.5 ng / ml), B27 supplement (lml / 50ml media), Nicotinamide (lOmM), Rock inhibitor (lOpM), A83-01 (5pM). After evaluation ofONCO-25-OQ2-WO viability, cells are seeded at a density of 3 * 106cells / mL in 75 cm2tissue culture flasks at 37°C and 5% CO2. Culture medium is changed accordingly. When cultures reach sub-confluence, cells are sub-cultured at a dilution of 1:2 until they begin to grow rapidly. If testing is not performed once cells reach confluency, cells should be sub-cultured at a dilution of 1:5 as needed until testing is performed.Culturing Primary Cells from Solid Tumors
[0032] Under sterile conditions following septic laboratory technique, malignant cells are obtained from fresh solid tumor sample containing at least 50g or 1 cm3of fresh cancerous tissue by (1) enzymatic treatment with Collagenase - DNase I - Dispase II blend (Img / ml collagenase, 0.1 mg / ml DNase, >2 units / mL Dispase II) via incubation for 30 minutes to 2 hours in a water bath, at 37°C, (2) mechanical isolation or disintegration without enzymatic digestion, or (3) both. Mechanical isolation or disintegration is performed by mincing the sample with a sterile surgical scalpel. Tumor cells are transferred to 50 mL sterile tubes (Corning, Shiphol Rijk, The Netherlands) and suspended in an appropriate growth medium. Tumor cells are then filtered through a 70pm nylon mesh cell strainer to remove cell clusters. Tumor cells are then centrifuged at between 1000-1400 rpm for 10-15 min at 4°C. Once the supernatant is removed, cells are washed and re-suspended in growth medium (RPMI 1640 or DMEM / F12, HEPES enriched with fetal bovine serum (FBS), and relevant growth factors as needed. After evaluation of viability, cells are seeded at a density of 3 * 106cells / mL in 75 cm2tissue culture flasks at 37°C and 5% CO2. Culture medium is changed accordingly. When cultures reach sub-confluence, cells are sub-cultured at a dilution of 1:2 until they begin to grow rapidly and are ready for testing. Standard culture protocols detailed above can be used to culture malignant cells from relevant specimen forNSCLC, SCLC, colorectal cancer, renal cancer, gastrointestinal cancer, ovarian cancer, fallopian cancer, and primary peritoneal carcinoma (“PPC”).ONCO-25-OQ2-WOMethods for Assessing and Evaluating Response of Malignant Cells to Drug Treatment Using Fluorometric Cytotoxicity Assay
[0033] Resazurin is the active compound of the commercially available compound Alamar Blue. (Majumder, B. et al. 2015). The resazurin assay can be used to quantify cell proliferation and cytotoxicity as the resazurin substance increases in fluorescence in the presence of metabolically active cells. (Siena, S. etal. 2009). Cell viability can also be assessed using other suitable assays, such as the commercially available colorimetric assays MTT or XTT (Abeam; Invitrogen) or luminescence-based ATP assays (Abeam; Invitrogen; Promega).
[0034] In one exemplary method, to a 384-well plate, 40 pL of 1.25X compound dilution or 1.25% DMSO-containing media is added. Candidate therapeutic agents, including but not limited to chemotherapy drugs, including but not limited to 5 -Fluorouracil (“5-FU”), Abraxane, Alkeran, Axitinib, Belzutifan, Cabazitaxel, Cabozantinib, Capecitabine, Carboplatin, Carmustine, Cisplatin, Cyclophosphamide, Docetaxel, Doxorubicin, Daunorubicin, Epirubicin, Eribulin, Mesylate, Estramustine, Etoposide, Everolimus, Gemcitabine, Ifosfamide, Irinotecan, Ixabepilone, Lenvatinib, Mitomycin C, Mitoxantrone, Methotrexate, Niraparib, Olaparib, Oxaliplatin, Paclitaxel, Pazopanib, Pemetrexed, Procarbazine, Rucaparib, Sorafenib, Sutinib, Talazoparib, Temozolomide, Temsirolimus, Tivozanib, Topotecan, Trifluridine, Vinblastine, Vincristine, and Vinorelbine, small molecule drugs, cell permeable Antibody Drug Conjugates (“ADC”) like deruxtecan, off-label drugs, investigational drugs, repurposed drugs, immunotherapeutic drugs including oncolytic viruses, drug delivery systems and devices to determine payload and effectiveness, or any current or new therapeutic agent capable of being tested in vitro / ex-vivo, as selected at the discretion of the treating physician, can be tested individually or as a combination treatment. Concentrations of compounds tested ranges from lOOOpM to 3E-6 nM. For combination treatments, each drug concentration corresponds to guideline-recommended clinical dosage of the combination regimen. In addition to the combination treatment, each combination agent is also tested as anONCO-25-OQ2-WO individual drug at the relevant clinical dosage (i.e., Cmax value) in parallel. For single agents, on each plate at least 3 technical replicates of each concentration are performed. For combination treatments, on each plate at least 6 technical replicates are performed. Next, 10 pL of a 100,000 cells / mL suspension are added to each well, yielding a final concentration of 1,000 cells / well. To three wells, 1 pL of 10 mM doxorubicin (final concentration of 200 pM) is added as a positive control that should result in cell death. Plates are sealed with gas-permeable seals and incubated at 37 °C for an appropriate time. In some aspects, the incubation period can be 24, 36, 48, 60, or 72 hours. In some aspects, the incubation period can be longer, such as 80 or 96 hours or more. Suitable incubation times vary depending on a drug’s mechanism of action and the cell type. After an appropriate incubation period, 5 pL of Alamar blue are added, plates are incubated for 3-4 hours. Fluorescence is read on an Analyst HT or a Molecular Devices SpectraMax 3 (excitation = 555 nm, emission = 585 nm, emission cutoff = 570 nm). Wells are normalized to the average of untreated wells (0% cell death).Data Analysis for Cell Response to Drug Treatment
[0035] Data is plotted as compound concentration versus percent dead cells and fitted to a logistic-dose response curve using OriginPro (OriginLab, Northampton, MA). Hill Slope, Emax, and cell death at Cmax values can be obtained from curves fitted by OriginPro and Knime. For both single-agent treatments and combination therapies, responsiveness of each drug is categorized into active or high, moderately active, and low or inactive for each patient.
[0036] Where IC50 is not available (i.e., cell death is less than 50% at the highest drug concentration), the drug is labeled as inactive. For drugs with available IC50 values, they will be distributed into active, moderately active, or inactive categories from lowest to highest values. In cases where IC50 value is labeled as inactive, cell death at Cmax is used to determine agent’s final responsiveness (i.e., cell death below 50% is considered as inactive drug; cell death at or above 50% given Cmax concentration is considered moderately active). The data isONCO-25-OQ2-WO generated in duplicate or triplicate (dependent on cell numbers), and IC50 values, Hill slopes, and Emax values are reported as the average of three separate experiments along with standard error of the mean.Data Analysis to Assess and Evaluate Cell Response to Combination Drug Therapies
[0037] In addition to the above analysis, for tested combination therapies, dose-responsive curves are generated for each drug alone and in combination (e.g., two (2) or more drugs). Additionally, IC50 values are calculated for single agents and used to determine any synergistic, additive, or antagonistic effects from the specific combination treatment for an individual patient. Statistical models such as the Chou-Talalay method (Zhang N, et al. 2016) using CompuSyn software (Informer Technologies, Inc.) or the Bliss independence model (Liu Q, et al. 2018) can be used to determine the combination index (CI) and assess whether a combination treatment has a greater (synergistic), expected (additive) or lesser (antagonistic) effect compared to the sum of the effects of each drug alone.
[0038] Combination therapies can be tested at multiple concentrations to identify and generate dose-responsive curves. Such concentrations can include clinically relevant concentrations at Cmax, 0.5x Cmax, and 2x Cmax. Cell death can be determined for combination therapies similar to for single drugs and evaluated if the cell death for the combination therapies is greater than each individual drug. If the combination therapy is more toxic to the malignant cells, this combination therapy is prioritized and if not, it is labeled inactive.Example 1:Media Optimization to Reproducibly Isolate and Grow Bladder Cancer Cells from Urine
[0039] Urine samples were collected from seven (7) patients with either non-muscle invasive bladder cancer (NMIBC) or muscle invasive bladder cancer (MIBC), both low-grade and high-grade. The samples were processed and cells isolated and grown according to theONCO-25-OQ2-WO specific media and protocol identified in FIG. 4. Modification and optimization of both the media and protocol used with patient samples in FIG. 4 resulted in the Culture of Primary Cells from Urine Containing Cancer Cells disclosed herein.
[0040] FIG. 4 shows urine samples obtained from patients before, during, and / or after TURBT and processed using the media optimization disclosed in Culture of Primary Cells from Urine Containing Cancer Cells above. The results of cell viability and count are detailed in FIG. 4. Patient 1 (Pl) had urine samples collected both during TURBT and 1-day post TURBT. Patient 2 (P2) had a urine sample collected before TURBT only, and processing resulted in adherent cells after one week. For Patient 3 (P3), a urine sample was obtained during TURBT, resulting in adherent cells after one week. Urine samples from Patient 4 (P4) and Patient 7 (P7) were collected during TURBT, maintained at 4°C, and processed both immediately and 24 hours after collection, with no negative impact on cell viability detected. Urine samples processed from patients with Non-Muscle Invasive Bladder Cancer (NMIBC) or Muscle Invasive Bladder Cancer (MIBC), both high grade and low grade, exhibited growth of cancer cells in 100% of patient samples when using optimized media and cell growth method disclosed herein. Results were confirmed with pathology reports for presence of cancer cells.Example 2:Study for Patients with Suspected or Recurrent NMIBC
[0041] An exploratory, single-institution, observational study involved adult patients undergoing Transurethral Resection of Bladder Tumor (TURBT) for suspected or recurrent non-muscle invasive bladder cancer (NMIBC), both low-grade and high-grade. Urine samples were collected pre- and post-operatively for use in the using OncoChoice® test. The samples were processed and cells isolated and grown according to the specific media and protocol detailed in Example 1 (above). As shown in FIG. 6a-c, phase-contrast microscopy images from urine samples of patients (n=3) with NMIBC show successful isolation and growth of cancerONCO-25-OQ2-WO cells using OncoChoice® test across NMIBC subtypes: FIG. 6a P001 demonstrated (Ta high grade); FIG. 6b P002 demonstrated (Ta low grade); and FIG. 6c P003 demonstrated (T1 high grade). FIG. 6d provides a chart showing OncoChoice® testing to evaluate drug activity of Gemcitabine, Docetaxel, Mitomycin C, and combination treatment with Gemcitabine / Docetaxel on all patient samples. OncoChoice® results demonstrate distinct variability in tumor response to each treatment. For example, variable responses to treatment with each single agent (e.g., gemcitabine, docetaxel, or mitomycin alone) vs. a combination treatment (gemci tabine / docetaxel) were observed in the first two patients, while patient 3 cells responded similarly to both treatments. Physician’s choice represents treatment prescribed to each patient, respectively. The Activity Scale in FIG. 6d represents drug activity from algorithmically-derived metrics of dose-response curves and clinically relevant drug concentrations. (n=3 biological replicates). This observational study was continued and expanded to include ten (10) total patients currently. Patient 004 was determined to be negative for malignancy through isolation and growth according to the specific media and protocol detailed in Example 1 (above). This result was confirmed with pathology reports for the absence of malignant cells. Additionally, malignant cells from Patient 007 were terminated due to risk of contamination to other samples (i.e., turbulent media after 12 hr). Images showing isolation and growth of cancer cells from urine samples for Patients 001-003, 005-006, and 008-010 are shown in FIG. 7. Results of treatment of cancer cells using OncoChoice® in these same patients with NMIBC are shown in FIG. 8. Results from the remaining eight (8) patients demonstrate distinct tumor response for each treatment, based on drug activity using algorithmically-derived metrics of dose-response curves and clinically relevant drug concentrations. OncoChoice® results in Fig. 8 show varied and personalized results when cancer cells were treated with the combination therapy Gemcitabine / Docetaxel (hereinafter, “Gem / Doce”), showing moderate activity in isolated cancer cells of the Patient 002, PatientONCO-25-OQ2-WO 005, and Patient 009. Importantly, each of these patients was previously treated with Gem / Doce, and each patient responded as indicated by the OncoChoice® assay data. Similarly, Patient 006 was previously treated with Gemcitabine, and is currently being treated again with Gemcitabine. OncoChoice® results in FIG. 8 show high activity in the isolated cancer cells of Patient 006, and Patient 006 is expected to respond to treatment as indicated by OncoChoice® assay data.
[0042] The results of the OncoChoice® assay demonstrate substantial variability from patient-to-patient, and these results enable physicians and facilities to use OncoChoice® to determine and select a more effective treatment option for each patient based on effectiveness of a treatment option on each patient’ s cancer cells. Moreover, the OncoChoice® assay provides physicians with identifying less commonly used FDA-approved drugs for NMIBC (e.g., mitomycin C) that are likely to be more effective for a specific patient than using a preferred treatment regimen (e.g., gemcitabine or gem / doce).Example 3:Isolation and Growth of Pancreatic Cancer Cells from Solid Tumors for P NET Cancer
[0043] Under sterile conditions following septic laboratory technique, malignant cells are obtained from fresh solid tumor sample containing at least 50g or 1 cm3of fresh cancerous tissue by (1) enzymatic treatment with Collagenase - DNase I - Dispase II blend (Img / ml collagenase, 0.1 mg / ml DNase, >2 units / mL Dispase II) via incubation for 30 minutes in a water bath, at 37°C or (2) mechanical isolation or disintegration without enzymatic digestion, or both. Mechanical isolation or disintegration is performed by mincing the sample with a sterile surgical scalpel. Tumor cells are transferred to 50 mL sterile tubes (Coming, Shiphol Rijk, The Netherlands) and suspended in an appropriate growth medium with optimized growth factors (DMEM / F12, HEPES enriched with fetal bovine serum (FBS)) and growth factors EFG (20ng / mL), FGF2 (lOng / mL), PIGF (lOOng / mL), IGF-1 (770ng / mL)). Tumor cells are thenONCO-25-OQ2-WO filtered through a 70pm nylon mesh cell strainer to remove cell clusters. Tumor cells are then centrifuged at between 1000-1400 rpm for 10-15 min at 4°C. Once the supernatant is removed, cells are washed and re-suspended in the same growth medium and growth factors. After evaluation of viability, cells are seeded at a density of 3 * 106cells / mL in 75 cm2tissue culture flasks at 37°C and 5% CO2. Culture medium is changed accordingly. When cultures reach subconfluence, cells are sub-cultured at a dilution of 1:2 until they begin to grow rapidly and are ready for testing. Solid tumor samples processed from a patient with PNET cancer, exhibited growth of cancer cells in the patient sample when using optimized media and the cell growth method disclosed herein. Samples processed 24 hours after collection exhibited no loss of viability. FIG. 12a - FIG. 12c depicts images verifying growth of malignant PNET cancer cells at various time points after isolation. FIG. 12a and FIG. 12b both depict cells isolated using mechanical digestion, and growth at various time points; FIG. 12c depicts cells isolated using both mechanical and enzymatic digestion, and growth at various time points. Results were confirmed with pathology reports for presence of cancer cells.Example 4:Comparison of 2D Monolayer Methods and 3D Organoid Methods
[0044] Urine samples from bladder cancer patients (n=19) were processed using the present 2D monolayer method disclosed in Example 1. Success rate: 95% (18 / 19); time to drug testing: 2-5 days.
[0045] Published 3D organoid methods: 55-83% success rates; time to drug testing: 10-14 days; costs significantly increase due to requirement for 3D enablement, including both time and materials (i.e., Matrigel / BME matrix).
[0046] The 2D monolayer approach provides superior success rates, faster turnaround to better serve patients in clinical applications, and significantly lower costs for clinical drug activity testing applications, based on the reduced time frame and cost of materials.ONCO-25-OQ2-WO Incorporation of OncoChoice® in Clinical Applications
[0047] Study outcomes as demonstrated in Example 2 include 100% success rate in isolating and growing cancer tumor cells from urine samples of all NMIBC patients across low-and high-grade tumors. Processing time for OncoChoice® testing includes 2-5 days to verify whether cancer is present in a patient sample, and approximately 7- to 14-days for cells to grow sufficiently to run an array of testing multiple drugs on the cells in triplicate and obtain tumor response profiles.
[0048] Additionally, use of OncoChoice® to isolate and grow cancer cells from urine samples in patients suspected of having bladder cancer demonstrates the ability to detect cancer cells within 2-4 days, before pathology results are available. In the study from Example 2, four (4) patients were originally suspected of having NMIBC. Using OncoChoice® to isolate and grow cells from the patient samples obtained, OncoChoice® was able to determine that one of the four patients did not have cancer through lack of growth of cancer cells in the patient sample (results were confirmed by a pathology report a week after TURBT). The other three patients were confirmed to have cancer through both use of OncoChoice® to isolate and grow cancer cells from the patient urine samples, and a confirmatory pathology report. OncoChoice® testing was also able to detect the presence of very early-stage cancer (Ta low grade) in samples from one of the patients.
[0049] Outcomes from the study detailed in Example 2 demonstrate that integration of OncoChoice® in clinical applications is not only feasible but also provides an advantage by preemptively evaluating a chemotherapeutic agent’s efficacy in treating a specific patient’s tumor. OncoChoice® testing can identify distinct variability in tumor response patterns observed across intravesical agents without requiring a patient to endure chemotherapy treatment with agents that do not provide beneficial treatment based on that patient’s specific tumor response profile. In addition, OncoChoice® may also be used as follow-up test duringONCO-25-OQ2-WO the maintenance phase. During this time, patients typically wait three to four months to have a follow-up check to determine whether their cancer responded to the specific intravesical chemotherapy treatment used. OncoChoice® may be utilized during this maintenance phase to monitor a patient bi-weekly or monthly through just a urine sample. Use of OncoChoice® during the maintenance phase provides the advantage of enabling the treating physician or team to know whether the treatment appears to be working or whether the tumor appears to be continuing to grow and disease progressing, rather than losing valuable time by waiting the entire three months. An additional benefit of using OncoChoice® is reducing overall healthcare costs by detecting cancer early, non-invasively identifying and evaluating the efficacy of treatment with chemotherapeutic agents alone or in combination before treatment is selected and initiated, and providing non-invasive follow-up screening to determine treatment efficacy without the need for expensive procedures.
[0050] FIG. 5 shows the timeline for integration of OncoChoice® in the current study detailed in Example 2. Under the current procedure, TURBT is scheduled approximately 7-21 days after a patient is diagnosed with bladder cancer (suspected or recurrent NMIBC). On the day of TURBT both pre- and post-operative urine samples are obtained from each patient. For patients diagnosed with NMIBC in the current study, resection of the bladder tumor and intravesical chemotherapy begins on the same day as the pre- and post-operative urine samples are obtained. Between 7 and 14 days after TURBT procedure, OncoChoice® generates unique tumor response profiles for each patient based on the sample size obtained and the isolation and growth of the cancer tumor cells. Every three to four months after TURBT, a clinical assessment is made to determine if the patient still has cancer and / how well they responded to intravesical chemotherapy following standard guidelines. At this time, OncoChoice® results can be compared to the clinical outcomes to assess assay efficacy in the clinic. In the future, OncoChoice® may use urine samples obtained from Day 0 (day the doctor suspects the patientONCO-25-OQ2-WO has cancer) to determine whether the patient indeed has cancer and determine and share results of multi-drug tumor profile ahead of TURBT, thus ensuring the treating physician is aware of the profile prior to treatment selection, and preventing ineffective treatments from being implemented right after TURBT. In addition, OncoChoice® may be deployed biweekly or monthly to monitor cancer presence and response to intravesical chemotherapy for these patients after TURBT, thus reducing the greater than three months’ timeline patients typically wait for a follow up assessment.Non-Small Cell Lung Cancer (NSCLC) Clinical Trial Protocol
[0051] Study Population: Patients (25-35 total) with advanced Non-Small Cell Lung Cancer (“NSCLC”) continue to be recruited with consent to participate in a single arm noninferiority study. A comparison arm will be determined based on historical medians of Objective Response Rate (“ORR”) for a list of pre-selected drugs at the discretion of treating physicians. A treatment group is undergoing treatment based on OncoChoice® results, where a committee of treating physicians (lung cancer oncologists) are unblinded to the assay results and use assay outcomes to evaluate the results of active and moderately active drugs and select the best treatment regimen for each patient, taking into account the risk / benefit analysis, each patient’s treatment goals and their underlying medical conditions and clinical profile. Study duration includes patient follow-up with tests required by a treating physician (e.g., CT scan and other lab tests) to monitor disease assessment and collect primary and secondary endpoints (e.g., ORR, OS, PFS) may be conducted at 3, 6, 9, 12, 18 and 24 months from day one of treatment for each patient, as applicable.
[0052] Inclusion Criteria: Inclusion criteria for the study includes but is not limited to the following: Patients must have a histologically confirmed diagnosis of advanced NSCLC documented by biopsy and Stage III or IV, if applicable; disease characteristics include a confirmed diagnosis of invasive metastatic or advanced NSCLC (pathologic or cytologic);ONCO-25-OQ2-WO must be at least 18 years of age; must have an ECOG-PS status score of less than or equal to 2; must have not received any cancer treatment for at least two (2) weeks before start of study; must be a candidate for small molecule drug treatment, and must have stable laboratory values (e.g., AST, ALT, ANC, platelets, creatine, bilirubin).
[0053] Primary Clinical Outcome: Objective Response Rate (ORR)
[0054] Secondary Clinical Outcomes: Median Progression Free Survival (PFS), Median overall survival (OS), and Health-Related Quality of Life (HRQoL) including but not limited to adverse drug events (AE).
[0055] Data Collection: (1) Monitor cancer status (e.g., spread of disease in the body) before OncoChoice®-guided cancer treatment (TO) to determine baseline, (2) monitor cancer status and disease assessment every two treatment cycles to assess likelihood of response, (3) monitor cancer status at the end of treatment to determine correlation with assay results, (4) monitor cancer status every 3, 6, 9, and 12 months (starting on Day 1 treatment for each patient) during remission or maintenance phase to determine study primary and secondary endpoints, (5) cross-check clinical outputs (e.g., CT scans, PET scans, other physician-elected laboratory tests) with assay results to determine if disease progressed, stabilized, or responded to drug treatment.
[0056] Initial Trial Results: Eight (8) patients confirmed to have metastatic or advanced NSCLC have been enrolled in the study to date. Attempts were made to obtain pleural effusion biospecimen from each patient. Insufficient biopsy samples were obtained from Patients 001 and 002, and no specimen was obtained from Patient 003. Sufficient biospecimen were obtained from Patients 004 - 007, as shown in FIG. 9. FIG. 9 also provides further details regarding each patient and OncoChoice® assay results, as well as proposed treatment based on assay results. Partial data was obtained for Patient 006, but the study was discontinued for thisONCO-25-OQ2-WO patient sample, as the patient passed away. A sample was recently obtained from Patient 008, recently enrolled in the study (not shown in FIG. 9).
[0057] Cancer cells from biospecimen obtained from five patients were reproducibly isolated and grown using standard culture for primary cells from malignant fluids provided in this disclosure. Growth of NSCLC cells from each patient specimen are shown in FIG. 11 at various time points after isolation.
[0058] A full report for Patient 005 is detailed in FIG. 10 and includes OncoChoice® assay results identifying concentrations of common drugs used in treatment of NSCLC required to kill 50% of cancer cells (nM). FIG. 10 also provides a comparison of OncoChoice® assay results to published doses and plasma concentrations based on FDA literature and publications from NIH sources for the same drugs. Results in FIG. 10 show that for Patient 005, Permetrexed demonstrated minimal effectiveness in killing cancer cells across all tested concentrations, suggesting that at least for Patient 005, these cancer cells may be resistant to permetrexed therapy. Cancer cells from Patient 005 did demonstrate sensitivity to Vinorelbine, and even small amounts of the drug were effective at killing the cancer cells for Patient 005. Paclitaxel and Docetaxel both demonstrated activity in killing the cancer cells but recommendation for either of these treatments alone or as a combination need to be considered in the context of clinical doses. Gemcitabine displayed moderate activity and was within the clinical dose but killing 50% of cancer cells in Patient 005 required relatively high drug concentration. Results from this study are ongoing, but initial OncoChoice® assay results provide targeted and personalized treatment options for treating physician to consider. The benefit of these assay results is that they are specific to each patient because the results are based on treatment of each patient’s own cancer cells.ONCO-25-OQ2-WO Example Architecture
[0059] FIG. 1 is a block diagram illustrating an example of a computing device 100, according to an example implementation. The computing device 100 may be used to perform functions of the exemplary method shown in FIG. 2 and described below. In particular, computing device 100 can be configured to perform one or more functions, including evaluating whether active candidate therapeutic agents are likely show a positive response (PR) for a patient’ s clinical outcome, or to correlate between assay results and biomarkers, according to example implementations, for example. The computing device 100 has a processor(s) 102, and also a communication interface 104, data storage 106, an output interface 108, and a display 110 each connected to a communication bus 112. The computing device 100 may also include hardware to enable communication within the computing device 100 and between the computing device 100 and other devices (e.g., not shown). The hardware may include transmitters, receivers, and antennas, for example.
[0060] The communication interface 104 may be a wireless interface and / or one or more wired interfaces that allow for both short-range communication and long-range communication to one or more networks 114 or to one or more remote computing devices 116 (e.g., a tablet 116a, a personal computer 116b, a laptop computer 116c and a mobile computing device 116d, for example). Such wireless interfaces may provide for communication under one or more wireless communication protocols, such as Bluetooth, WiFi (e.g., an institute of electrical and electronic engineers (IEEE) 802.11 protocol), Long-Term Evolution (LTE), cellular communications, near-field communication (NFC), and / or other wireless communication protocols. Such wired interfaces may include Ethernet interface, a Universal Serial Bus (USB) interface, or similar interface to communicate via a wire, a twisted pair of wires, a coaxial cable, an optical link, a fiber-optic link, or other physical connection to a wiredONCO-25-OQ2-WO network. Thus, the communication interface 104 may be configured to receive input data from one or more devices and may also be configured to send output data to other devices.
[0061] The communication interface 104 may also include a user-input device, such as a keyboard, a keypad, a touch screen, a touch pad, a computer mouse, a track ball and / or other similar devices, for example.
[0062] The data storage 106 may include or take the form of one or more computer-readable storage media that can be read or accessed by the processor(s) 102. The computer-readable storage media can include volatile and / or non-volatile storage components, such as optical, magnetic, organic or other memory or disc storage, which can be integrated in whole or in part with the processor(s) 102. The data storage 106 is considered non-transitory computer readable media. In some examples, the data storage 106 can be implemented using a single physical device (e.g., one optical, magnetic, organic or other memory or disc storage unit), while in other examples, the data storage 106 can be implemented using two or more physical devices.
[0063] The data storage 106 thus is a non-transitory computer readable storage medium, and executable instructions 118 are stored thereon. Instructions 118 include computer executable code. When the instructions 118 are executed by the processor(s) 102, the processor(s) 102 are caused to perform functions.
[0064] The processor(s) 102 may be a general-purpose processor or a special purpose processor (e.g., digital signal processors, application specific integrated circuits, etc.). The processor(s) 102 may receive inputs from the communication interface 104 and process the inputs to generate outputs that are stored in the data storage 106 and output to the display 110. The processor(s) 102 can be configured to execute the executable instructions 118 (e.g., computer-readable program instructions) that are stored in the data storage 106 and are executable to provide the functionality of the computing device 100 described herein.ONCO-25-OQ2-WO
[0065] The output interface 108 outputs information to the display 110 or to other components as well. Thus, the output interface 108 may be similar to the communication interface 104 and can be a wireless interface (e.g., transmitter) or a wired interface as well. The output interface 108 may send commands to one or more controllable devices, for example.
[0066] The computing device 100 shown in FIG. 1 may also be representative of a local computing device that may perform one or more of the steps of the method 200 or method 300 described below, may receive input from a user and / or may send data and user input to computing device 100 to perform all or some of the steps of method 200 or method 300.
[0067] FIG. 2 shows a flowchart of example method 200 directed to processes that provide for evaluating and determining activity of candidate therapeutic agents to show likelihood of a clinical response, or to correlate between assay results and biomarkers, according to example implementations. Method 200 is an example method that could be used with the computing device 100 of FIG. 1, for example. In some instances, components of the devices and / or systems may be configured to perform the functions such that the components are configured and structured with hardware and / or software to enable such performance. Components of the devices and / or systems may be arranged to be adapted to, capable of, or suited for performing the functions, such as when operated in a specific manner. Method 200 may include one or more operations, functions, or actions as illustrated by one or more of blocks 205-235. Although the blocks are illustrated in a sequential order, some of these blocks may also be performed in parallel, and / or in a different order than those described herein. Also, the various blocks may be combined into fewer blocks, divided into additional blocks, and / or removed based upon the desired implementation. In some instances, machine outputs can be inputted and formatted using any interactive data visualization and analysis software (i.e., Tableau, Microsoft Power BI, Qlik Sense, Sigma, Domo, Google Charts). In some instances, data including plot parameters can be processed and parsed, and prediction models run usingONCO-25-OQ2-WO any analytics platform with appropriate tools known to one of skill in the art (i.e., Knime, Alteryx, MathWorks MATLAB, Microsoft Azure, SAP Analytics Cloud, Microsoft Power BI).
[0068] Similarly, FIG. 3 shows a flowchart of example method 300 directed to processes that provide for evaluating active candidate therapeutic agents for treatment selection with potential patients based on a trained machine learning (“ML”) model using an algorithm to evaluate and determine outcomes for an individual patient if treated with specific candidate therapeutic agents, and optionally to correlate between assay results and predictive biomarkers, according to example implementations. Method 300 is an example method that could be used with the computing device 100 of FIG. 1, for example. In some instances, components of the devices and / or systems may be configured to perform the functions such that the components are configured and structured with hardware and / or software to enable such performance. Components of the devices and / or systems may be arranged to be adapted to, capable of, or suited for performing the functions, such as when operated in a specific manner. Method 300 may include one or more operations, functions, or actions as illustrated by one or more of blocks 305-335. Although the blocks are illustrated in a sequential order, some of these blocks may also be performed in parallel, and / or in a different order than those described herein. Also, the various blocks may be combined into fewer blocks, divided into additional blocks, and / or removed based upon the desired implementation. In some instances, the OncoChoice® dataset is compiled from a library of prior results and recommendations based on the methods disclosed in FIG. 2, for example. The library of data is used to teach various ML models using an algorithm and the data is parsed and an appropriate ML model is selected based on specific parameters and additional variables present in each new patient test case. In some instances, the variables within the patient reports for inputting can include: weight loss in the last 3-6 months, cancer type, stage of cancer, histology, pathology, Eastern Cooperative Oncology Group performance status (“ECOG-PS”) score, previous treatments and outcomes (e.g.,ONCO-25-OQ2-WO platinum-based treatment), time since last treatment, available biomarkers or oncogenic mutations. In some instances, partitioning the data into training set(s) vs. the test set(s) may include any ratio or division that provides an adequate baseline to evaluate candidate agents and provide associated treatment guidance, such as any ratio of training set(s) to test set(s) between a 50 / 50 split and an 80 / 20 split.
[0069] In some instances, any appropriate ML model may be selected provided that the unique parameters for each ML model are set and modified as required for the available data. Some examples of ML models that may be appropriate for selection based on available data set(s) include:, Ensemble Learning Models (e.g., Random Forest, Gradient Boosted Trees, or XGBoost Tree Ensemble), Decision Tree Models (e.g., Decision Tree Algorithms, Decision Tree Classifiers, or Decision Tree Regressors), Linear Regression Models (e.g., XGBoost Linear Model, or Linear Regression), Linear Classification Models (e.g., Logistic Regression), Generative Models (e.g., Naive Bayes),. As one of skill in the art will understand, for each ML model selected, specific parameters must be set and modified, as appropriate based on specific data set(s) utilized. In some instances, the predictability of the ML model selected may be assessed by false positive percentage or false negative percentage.
[0070] It should be understood that for this and other processes and methods disclosed herein, flowcharts show functionality and operation of one possible implementation of the present examples. In this regard, each block may represent a module, a segment, or a portion of program code, which includes one or more instructions executable by a processor for implementing specific logical functions or steps in the process. The program code may be stored on any type of computer readable medium or data storage, for example, such as a storage device including a disk or hard drive. Further, the program code can be encoded on a computer-readable storage media in a machine-readable format, or on other non-transitory media or articles of manufacture. The computer readable medium may include non-transitory computerONCO-25-OQ2-WO readable medium or memory, for example, such as computer-readable media that stores data for short periods of time such as register memory, processor cache and Random Access Memory (RAM). The computer readable medium may also include non-transitory media, such as secondary or persistent long-term storage, like read only memory (ROM), optical or magnetic disks, compact disc read only memory (CD-ROM), for example. The computer readable media may also be any other volatile or non-volatile storage systems. The computer readable medium may be considered a tangible computer readable storage medium, for example.
[0071] In addition, each block in FIG. 2 or FIG. 3, and within other processes and methods disclosed herein, may represent circuitry that is wired to perform the specific logical functions in the process. Alternative implementations are included within the scope of the examples of the present disclosure in which functions may be executed out of order from that shown or discussed, including substantially concurrent or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art.
Claims
ONCO-25-OQ2-WOCLAIMSWhat is claimed is:
1. A method for guiding personalized cancer treatment for a patient suspected of having early stage, advanced or metastatic cancer, the method comprising:a. preparing cell culture from a patient specimen suspected of containing malignant cells;b. isolating and growing one or more cell monolayers from one or more patient specimen, the one or more monolayers comprising malignant cells;c. exposing cells from said one or more monolayers to at least one candidate therapeutic agent at an appropriate range of clinically significant concentrations; d. preparing a dose-response curve for each candidate therapeutic agent;e. scoring responsiveness of the cells to a candidate therapeutic agent by calculating an area under the dose-response curve to determine 50% cell death (IC50); f. comparing IC50 value to the peak plasma concentration (Cmax) for each candidate therapeutic agent tested to determine drug inactivity (Cmax cell death below 50%);g. evaluating active candidate therapeutic agents likely to show a positive response (PR) for the patient’s clinical outcome when the malignant cells exhibit high activity (i.e., low IC50 value) to treatment with a candidate therapeutic agent; and, h. generating personalized treatment guidance for the patient based on the identified active candidate therapeutic agents.
2. The method of claim 1, wherein the patient has advanced or metastatic breast, lung, colorectal, renal, pancreatic, pancreatic neuroendocrine (PNET), stomach / gastrointestinal, ovarian, fallopian, primary peritoneal carcinoma (PPC), bladder cancer, head and neck,ONCO-25-OQ2-WO melanoma, sarcoma, ampullary carcinoma, cancer of unknown primary tumor, or other metastatic cancers of solid tumor origin that respond to chemotherapy or a targeted therapy.
3. The method of claim 2, wherein the patient has lung cancer or bladder cancer.
4. The method of claim 1, wherein the patient specimen comprises fluid suspected of containing cancer cells, including urine, blood, cerebrospinal fluid, or fluid from a tissue sample.
5. The method of claim 1, wherein the malignant patient specimen comprises tissue and / or fluid from a core needle biopsy or other fluid-removal procedure (e.g., paracentesis, thoracentesis), including but not limited to peritoneal effusion, or ascites fluid.
6. The method of claim 1, wherein the malignant specimen is a solid tumor biopsy comprising at least 50 mg or 1cm3of cancerous tissue.
7. The method of claim 6, wherein the malignant cells are isolated using one or more of the following methods:a. by enzymatic treatment with Collagenase - DNase I - Dispase II blend; b. mechanically isolated or disintegrated from the cancerous tissue; or c. using both enzymatic and mechanical treatment.
8. The method of any one of claims 1, or 4-6, wherein the malignant cells are isolated, suspended prior to confluency, and seeded for testing.
9. The method of claim 1, wherein the malignant cells are exposed to one or more concentrations of one or more candidate therapeutic agents in a time-course experiment.
10. The method of any one of claims 1 or 9, wherein the cells are exposed to a combination of therapeutics (e.g., two (2) or more drugs) based on treatment guidelines and / or physician selection.
11. The method of claim 1, wherein measuring malignant cell response is determined based on measurement of cell growth or cell death.ONCO-25-OQ2-WO 12. The method of claim 1, wherein measuring malignant cell response is defined as 50% cell death at a clinically relevant concentration of a candidate therapeutic agent.
13. The method of claim 1, wherein malignant cell response to a candidate therapeutic agent is determined by comparing IC50 scores to a cut-off value that is peak plasma concentration (Cmax) for the specific candidate therapeutic agent.
14. The method of claim 1, wherein the method is fully or partially automated.
15. The method of claim 14, further comprising:i. testing malignant cells in tandem for their genetic and molecular profile; and j . identifying genetic alterations within the malignant cells,whereby genetic alterations are used to identify new predictive biomarkers.
16. The method of claim 15, further comprising validating the identified predictive biomarkers through additional functional assays or clinical data.
17. The method of any one of claims 1 or 16, further comprising using the OncoChoice® dataset to discover new candidate therapeutic agents.
18. The method of any one of claims 16 or 17, wherein the personalized treatment guidance includes recommendations for combination therapeutics identified as synergistic based on the integrated results.
19. The method of claim 1, wherein the candidate therapeutic agents are selected from drug classes including but not limited to taxanes, vinca alkaloids, nucleoside metabolic inhibitors, platinum-based drugs, DNA-damaging agents, alkylating agents, mitotic inhibitors, Topo 1 inhibitors, Topo 2 inhibitors, antimetabolites, anthracyclines, antitumor antibiotics, targeted therapeutics, small molecule drugs, cell permeable Antibody Drug Conjugates (“ADC”), oncolytic viruses, payload of drug delivery systems, off-label drugs, investigational drugs, repurposed drugs , or any current or new investigational drugs as selected by the treating physician for treatment of cancer.ONCO-25-OQ2-WO 20. The method of claim 19, wherein the candidate therapeutic agents are selected from 5-Fluorouracil (“5-FU”), Abraxane, Alkeran, Axitinib, Belzutifan, Cabazitaxel, Cabozantinib, Capecitabine, Carboplatin, Carmustine, Cisplatin, Cyclophosphamide, Docetaxel, Doxorubicin, Daunorubicin, Epirubicin, Eribulin, Mesylate, Estramustine, Etoposide, Everolimus, Gemcitabine, Ifosfamide, Irinotecan, Ixabepilone, Lenvatinib, Mitomycin C, Mitoxantrone, Methotrexate, Niraparib, Olaparib, Oxaliplatin, Paclitaxel, Pazopanib, Pemetrexed, Procarbazine, Rucaparib, Sorafenib, Sutinib, Talazoparib, Temozolomide, Temsirolimus, Tivozanib, Topotecan, Trifluridine, Vinblastine, Vincristine, and Vinorelbine.
21. A system for guiding personalized cancer treatment according to the method of claim 1, the system comprising:a. an in-vitro / ex-vivo module configured to perform functional cell-based assays on a biological sample; andb. a treatment guidance module configured to generate personalized treatment guidance based on the results from evaluating and determining active candidate therapeutic agents with a positive response.
22. The system of claim 21, further comprising:c. a genomic analysis module configured to perform genomic profiling on the biological sample; andd. an integration module configured to integrate results from the in vitro / ex-vivo module and the genomic analysis module,whereby the treatment guidance module is configured to generate personalized treatment guidance based on the results of the integration module.
23. The system of claim 22, wherein the integration module utilizes a bioinformatics platform with a machine learning algorithm to identify predictive biomarkers.ONCO-25-OQ2-WO 24. A non-transitory computer-readable medium containing instruction that, when executed by a processor, perform a method for guiding personalized cancer treatment, the method comprising:a. receiving and parsing instrument data outputs from a functional cell-based assay exposing isolated malignant cells to one or more candidate therapeutic agents at an appropriate range of clinically significant concentrations according to claim 1;b. preparing a dose-responsive curve for each candidate therapeutic agent, parsing plot parameters and scoring responsiveness of the cells to each candidate therapeutic agent;c. deriving drug metrics and evaluating and determining active candidate therapeutic agents that will show likelihood of a clinical response in a patient when malignant cells exhibit high activity to treatment with a candidate therapeutic agent; andd. generating personalized treatment guidance for a patient based on identified active candidate therapeutic agents.
25. The non-transitory computer readable medium according to claim 24, wherein the responsiveness of the cells to each candidate therapeutic agent is determined by calculating an area under the dose responsive curve to determine 50% cell death (IC50) and comparing IC50 value to peak plasma concentration (Cmax) for each candidate therapeutic agent tests to determine drug inactivity (Cmax cell death below 50%).
26. The non-transitory computer readable medium according to claim 24, further comprising:e. receiving data from genomic profiling of a biological sample; andONCO-25-OQ2-WO f. integrating the received data to identify predictive biomarkers or gene mutations,wherein the personalized treatment guidance generated for a patient is based on the combination of identified active candidate therapeutic agents and identified predictive biomarkers and / or genomic fingerprint profile; andg. integrating the received data and leveraging predictive biomarkers and / or genomic fingerprint profiles to identify new cancer treatments (e.g., new drugs, therapies) or optimize existing treatments (e.g., drug derivatives).
27. The method of claim 1, wherein step b results in no malignant cells isolated or grown, the patient is determined to not have cancer, and no further steps are taken according to the method of claim 1.
28. The method of claim 1, wherein a patient was previously determined to have cancer, steps a and b are undertaken on an appropriate specimen from the patient during a maintenance phase after a selected chemotherapy treatment is concluded, the steps are undertaken to monitor efficacy of the selected chemotherapy treatment,wherein an absence of isolation and growth of malignant cells indicates efficacy of the selected treatment, and wherein isolation and growth of malignant cells indicates the selected treatment is not effective or has limited activity to treat the patient’s cancer.
29. The method of claim 28, wherein monitoring of the patient is performed on a biweekly or monthly basis.