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Veselovsky E, Lebedeva A, Kuznetsova O, Kravchuk D, Belova E, Taraskina A, Grigoreva T, Kavun A, Yudina V, Belyaeva L, Nikulin V, Mileyko V, Tryakin A, Fedyanin M, Ivanov M. Evaluation of blood MSI burden dynamics to trace immune checkpoint inhibitor therapy efficacy through the course of treatment. Sci Rep 2024; 14:23454. [PMID: 39379462 PMCID: PMC11461614 DOI: 10.1038/s41598-024-73952-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Accepted: 09/23/2024] [Indexed: 10/10/2024] Open
Abstract
Analysis of serial liquid biopsy (LB) samples has been found to be a promising approach for the monitoring of tumor dynamics in the course of therapy for patients with colorectal cancer (CRC). Currently, somatic mutations are used for tracing the dynamics of the tumor via LB. However, the analysis of the dynamic changes in the molecular signatures such as microsatellite instability (MSI) is not currently used. We hypothesized that changes in blood MSI burden (bMSI) could be registered using serial LB sampling in the course of immune checkpoint inhibitors (ICI), and that its changes could potentially correlate with treatment outcomes. We report the preliminary findings of the observational trial launched to study (NCT06414304) the dynamics of bMSI in 9 MSI-positive CRC patients receiving ICI. NGS-based MSI testing was performed on both pre-treatment FFPE and serial LB samples. For patients who had detectable bMSI burden in any of the LB samples (n = 8, 89%), median bMSI was 1.4% (range, 0.01-40%). Among patients with detectable MSI in available FFPE samples, median MSI burden was 29.3% (range, 10-40%). bMSI detected in baseline LB and FFPE samples were positively correlated (Pearson's R 0.47). Maximal variant allele frequencies of driver mutations observed in LB were also positively correlated with bMSI burden (Pearson's R 0.7). Patients who had clinical benefit had undetectable bMSI burden at follow-up. Our results provide the rationale for further validation of bMSI as a predictive biomarker of ICI in MSI-positive patients.
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Affiliation(s)
- Egor Veselovsky
- OncoAtlas LLC, 4/1A, Leninskiy Prospect, Moscow, Russian Federation, 119049
- Department of Evolutionary Genetics of Development, Koltzov Institute of Developmental Biology of the Russian Academy of Sciences, Moscow, Russian Federation
| | - Alexandra Lebedeva
- OncoAtlas LLC, 4/1A, Leninskiy Prospect, Moscow, Russian Federation, 119049
- Sechenov First Moscow State Medical University, Moscow, Russian Federation
| | - Olesya Kuznetsova
- OncoAtlas LLC, 4/1A, Leninskiy Prospect, Moscow, Russian Federation, 119049
- Federal State Budgetary Institution N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russian Federation
| | - Daria Kravchuk
- State Budgetary Institution of Health Care of the City of Moscow "Moscow Multidisciplinary Clinical Center" "Kommunarka" of the Department of Health of the City of Moscow, Moscow, Russian Federation
| | - Ekaterina Belova
- OncoAtlas LLC, 4/1A, Leninskiy Prospect, Moscow, Russian Federation, 119049
- Sechenov First Moscow State Medical University, Moscow, Russian Federation
- Lomonosov Moscow State University, Moscow, Russian Federation
| | | | - Tatiana Grigoreva
- OncoAtlas LLC, 4/1A, Leninskiy Prospect, Moscow, Russian Federation, 119049
- Sechenov First Moscow State Medical University, Moscow, Russian Federation
| | - Alexandra Kavun
- OncoAtlas LLC, 4/1A, Leninskiy Prospect, Moscow, Russian Federation, 119049
| | - Victoria Yudina
- Federal State Budgetary Institution N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russian Federation
| | - Laima Belyaeva
- OncoAtlas LLC, 4/1A, Leninskiy Prospect, Moscow, Russian Federation, 119049
- Sechenov First Moscow State Medical University, Moscow, Russian Federation
| | - Vladislav Nikulin
- Federal State Budgetary Institution N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russian Federation
| | - Vladislav Mileyko
- OncoAtlas LLC, 4/1A, Leninskiy Prospect, Moscow, Russian Federation, 119049
- Sechenov First Moscow State Medical University, Moscow, Russian Federation
| | - Alexey Tryakin
- Federal State Budgetary Institution N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russian Federation
| | - Mikhail Fedyanin
- Federal State Budgetary Institution N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russian Federation
- State Budgetary Institution of Health Care of the City of Moscow "Moscow Multidisciplinary Clinical Center" "Kommunarka" of the Department of Health of the City of Moscow, Moscow, Russian Federation
- Federal State Budgetary Institution "National Medical and Surgical Center named after N.I. Pirogov" of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - Maxim Ivanov
- OncoAtlas LLC, 4/1A, Leninskiy Prospect, Moscow, Russian Federation, 119049.
- Sechenov First Moscow State Medical University, Moscow, Russian Federation.
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Janitri V, ArulJothi KN, Ravi Mythili VM, Singh SK, Prasher P, Gupta G, Dua K, Hanumanthappa R, Karthikeyan K, Anand K. The roles of patient-derived xenograft models and artificial intelligence toward precision medicine. MedComm (Beijing) 2024; 5:e745. [PMID: 39329017 PMCID: PMC11424683 DOI: 10.1002/mco2.745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Revised: 08/22/2024] [Accepted: 08/22/2024] [Indexed: 09/28/2024] Open
Abstract
Patient-derived xenografts (PDX) involve transplanting patient cells or tissues into immunodeficient mice, offering superior disease models compared with cell line xenografts and genetically engineered mice. In contrast to traditional cell-line xenografts and genetically engineered mice, PDX models harbor the molecular and biologic features from the original patient tumor and are generationally stable. This high fidelity makes PDX models particularly suitable for preclinical and coclinical drug testing, therefore better predicting therapeutic efficacy. Although PDX models are becoming more useful, the several factors influencing their reliability and predictive power are not well understood. Several existing studies have looked into the possibility that PDX models could be important in enhancing our knowledge with regard to tumor genetics, biomarker discovery, and personalized medicine; however, a number of problems still need to be addressed, such as the high cost and time-consuming processes involved, together with the variability in tumor take rates. This review addresses these gaps by detailing the methodologies to generate PDX models, their application in cancer research, and their advantages over other models. Further, it elaborates on how artificial intelligence and machine learning were incorporated into PDX studies to fast-track therapeutic evaluation. This review is an overview of the progress that has been done so far in using PDX models for cancer research and shows their potential to be further improved in improving our understanding of oncogenesis.
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Affiliation(s)
| | - Kandasamy Nagarajan ArulJothi
- Department of Genetic Engineering, College of Engineering and TechnologySRM Institute of Science and TechnologyChengalpattuTamil NaduIndia
| | - Vijay Murali Ravi Mythili
- Department of Genetic Engineering, College of Engineering and TechnologySRM Institute of Science and TechnologyChengalpattuTamil NaduIndia
| | - Sachin Kumar Singh
- School of Pharmaceutical SciencesLovely Professional UniversityPhagwaraPunjabIndia
| | - Parteek Prasher
- Department of ChemistryUniversity of Petroleum & Energy Studies, Energy AcresDehradunIndia
| | - Gaurav Gupta
- Centre for Research Impact & Outcome, Chitkara College of PharmacyChitkara UniversityRajpuraPunjabIndia
| | - Kamal Dua
- Faculty of Health, Australian Research Center in Complementary and Integrative, MedicineUniversity of Technology SydneyUltimoNSWAustralia
- Discipline of Pharmacy, Graduate School of HealthUniversity of Technology SydneyUltimoNSWAustralia
| | - Rakshith Hanumanthappa
- JSS Banashankari Arts, Commerce, and SK Gubbi Science CollegeKarnatak UniversityDharwadKarnatakaIndia
| | - Karthikeyan Karthikeyan
- Centre of Excellence in PCB Design and Analysis, Department of Electronics and Communication EngineeringM. Kumarasamy College of EngineeringKarurTamil NaduIndia
| | - Krishnan Anand
- Department of Chemical Pathology, School of Pathology, Office of the Dean, Faculty of Health SciencesUniversity of the Free StateBloemfonteinSouth Africa
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Heeke AL, Sha W, Feldman R, Fisher J, Hadzikadic-Gusic L, Symanowski JT, White RL, Tan AR. The Genomic Landscape of Breast Cancer in Young and Older Women. Clin Breast Cancer 2024; 24:630-638.e3. [PMID: 39174364 DOI: 10.1016/j.clbc.2024.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 07/05/2024] [Accepted: 07/13/2024] [Indexed: 08/24/2024]
Abstract
BACKGROUND Young women with breast cancer (YWBC; ≤40 years) often have a poorer prognosis than older women with breast cancer (OWBC; ≥65 years). We explored molecular features of tumors from YWBC and OWBC to identify a biologic connection for these patterns. MATERIALS AND METHODS We retrospectively analyzed the molecular profiles of 1879 breast tumors. Testing included immunohistochemistry (IHC), in situ hybridization (ISH), and next-generation sequencing. Statistical analyses included Pearson's chi2 test for comparisons, with significance defined as FDR (false discovery rate)-P < .05. RESULTS TP53 and BRCA1 somatic mutations were more common in YWBC tumors than in OWBC tumors (53%, 42%; P = .0001, FDR-P = .0025 and 7%, 2%; P = .0001, FDR-P = .0025; respectively). Conversely, OWBC tumors had higher androgen receptor expression (55%, 45%; P = .0002, FDR-P = .0025) higher PD-L1 expression detected by IHC (8%, 5%; P = .0476, FDR-P = .2754), and more frequent PIK3CA mutations (33%, 17%; P = < .0001, FDR-P = < .0001). Among HR+/HER2- samples, YWBC had more gene amplifications in FGF3 (27%, 10%; P = .0353, FDR-P = .2462), FGF4 (27%, 9%; P = .0218, FDR-P = .1668), FGF19 (30%, 12%; P = .034, FDR-P = .2462) and CCND1 (37%, 18%; P = .0344, FDR-P = .2462) than OWBC. CONCLUSIONS Our data suggest distinct molecular aberrations exist between YWBC and OWBC. Exploiting these molecular changes could refine our treatment strategies in YWBC and OWBC.
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Affiliation(s)
- Arielle L Heeke
- Department of Solid Tumor Oncology and Investigational Therapeutics, Levine Cancer Institute, Atrium Health, Charlotte, NC; Sandra Levine Young Women's Breast Cancer Program, Levine Cancer Institute, Atrium Health, Charlotte, NC.
| | - Wei Sha
- Department of Cancer Biostatistics, Levine Cancer Institute, Atrium Health, Charlotte, NC
| | | | - Julie Fisher
- Department of Solid Tumor Oncology and Investigational Therapeutics, Levine Cancer Institute, Atrium Health, Charlotte, NC; Sandra Levine Young Women's Breast Cancer Program, Levine Cancer Institute, Atrium Health, Charlotte, NC
| | - Lejla Hadzikadic-Gusic
- Division of Surgical Oncology, Department of Surgery, Carolinas Medical Center, Levine Cancer Institute, Atrium Health, Charlotte, NC; Sandra Levine Young Women's Breast Cancer Program, Levine Cancer Institute, Atrium Health, Charlotte, NC
| | - James T Symanowski
- Department of Cancer Biostatistics, Levine Cancer Institute, Atrium Health, Charlotte, NC
| | - Richard L White
- Division of Surgical Oncology, Department of Surgery, Carolinas Medical Center, Levine Cancer Institute, Atrium Health, Charlotte, NC; Sandra Levine Young Women's Breast Cancer Program, Levine Cancer Institute, Atrium Health, Charlotte, NC
| | - Antoinette R Tan
- Department of Solid Tumor Oncology and Investigational Therapeutics, Levine Cancer Institute, Atrium Health, Charlotte, NC; Sandra Levine Young Women's Breast Cancer Program, Levine Cancer Institute, Atrium Health, Charlotte, NC
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Lebedeva A, Veselovsky E, Kavun A, Belova E, Grigoreva T, Orlov P, Subbotovskaya A, Shipunov M, Mashkov O, Bilalov F, Shatalov P, Kaprin A, Shegai P, Diuzhev Z, Migiaev O, Vytnova N, Mileyko V, Ivanov M. Untapped Potential of Poly(ADP-Ribose) Polymerase Inhibitors: Lessons Learned From the Real-World Clinical Homologous Recombination Repair Mutation Testing. World J Oncol 2024; 15:562-578. [PMID: 38993246 PMCID: PMC11236374 DOI: 10.14740/wjon1820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 04/29/2024] [Indexed: 07/13/2024] Open
Abstract
Background Testing for homologous recombination deficiency (HRD) mutations is pivotal to assess individual risk, to proact preventive measures in healthy carriers and to tailor treatments for cancer patients. Increasing prominence of poly(ADP-ribose) polymerase (PARP) inhibitors with remarkable impact on molecular-selected patient survival across diverse nosologies, ingrains testing for BRCA genes and beyond in clinical practice. Nevertheless, testing strategies remain a question of debate. While several pathogenic BRCA1/2 gene variants have been described as founder pathogenic mutations frequently found in patients from Russia, other homologous recombination repair (HRR) genes have not been sufficiently explored. In this study, we present real-world data of routine HRR gene testing in Russia. Methods We evaluated clinical and sequencing data from cancer patients who had germline/somatic next-generation sequencing (NGS) HRR gene testing in Russia (BRCA1/2/ATM/CHEK2, or 15 HRR genes). The primary objectives of this study were to evaluate the frequency of BRCA1/2 and non-BRCA gene mutations in real-world unselected patients from Russia, and to determine whether testing beyond BRCA1/2 is feasible. Results Data of 2,032 patients were collected from February 2021 to February 2023. Most had breast (n = 715, 35.2%), ovarian (n = 259, 12.7%), pancreatic (n = 85, 4.2%), or prostate cancer (n = 58, 2.9%). We observed 586 variants of uncertain significance (VUS) and 372 deleterious variants (DVs) across 487 patients, with 17.6% HRR-mutation positivity. HRR testing identified 120 (11.8%) BRCA1/2-positive, and 172 (16.9%) HRR-positive patients. With 51 DVs identified in 242 formalin-fixed paraffin-embedded (FFPE), testing for variant origin clarification was required in one case (0.4%). Most BRCA1/2 germline variants were DV (121 DVs, 26 VUS); in non-BRCA1/2 genes, VUS were ubiquitous (53 DVs, 132 VUS). In silico prediction identified additional 4.9% HRR and 1.2% BRCA1/2/ATM/CHEK2 mutation patients. Conclusions Our study represents one of the first reports about the incidence of DV and VUS in HRR genes, including genes beyond BRCA1/2, identified in cancer patients from Russia, assessed by NGS. In silico predictions of the observed HRR gene variants suggest that non-BRCA gene testing is likely to result in higher frequency of patients who are candidates for PARP inhibitor therapy. Continuing sequencing efforts should clarify interpretation of frequently observed non-BRCA VUS.
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Affiliation(s)
- Alexandra Lebedeva
- OncoAtlas LLC, Moscow, Russia
- Sechenov First Moscow State Medical University, Moscow, Russia
| | - Egor Veselovsky
- OncoAtlas LLC, Moscow, Russia
- Department of Evolutionary Genetics of Development, Koltzov Institute of Developmental Biology of the Russian Academy of Sciences, Moscow, Russia
| | | | - Ekaterina Belova
- OncoAtlas LLC, Moscow, Russia
- Sechenov First Moscow State Medical University, Moscow, Russia
- Lomonosov Moscow State University, Moscow, Russia
| | - Tatiana Grigoreva
- OncoAtlas LLC, Moscow, Russia
- Sechenov First Moscow State Medical University, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Pavel Orlov
- The Federal Research Center for Fundamental and Translational Medicine (NIIECM FRC FTM), Novosibirsk, Russia
| | - Anna Subbotovskaya
- The Federal Research Center for Fundamental and Translational Medicine (NIIECM FRC FTM), Novosibirsk, Russia
| | - Maksim Shipunov
- The Federal Research Center for Fundamental and Translational Medicine (NIIECM FRC FTM), Novosibirsk, Russia
| | - Oleg Mashkov
- State Budgetary Institution of Healthcare Republican Medical Genetic Center, Ufa, Russia
| | - Fanil Bilalov
- State Budgetary Institution of Healthcare Republican Medical Genetic Center, Ufa, Russia
| | - Peter Shatalov
- National Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia
| | - Andrey Kaprin
- National Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia
| | - Peter Shegai
- National Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia
| | | | | | | | - Vladislav Mileyko
- OncoAtlas LLC, Moscow, Russia
- Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maxim Ivanov
- OncoAtlas LLC, Moscow, Russia
- Sechenov First Moscow State Medical University, Moscow, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia
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Current status and issues related to secondary findings in the first public insurance covered tumor genomic profiling in Japan: multi-site questionnaire survey. J Hum Genet 2022; 67:557-563. [PMID: 35322199 DOI: 10.1038/s10038-022-01028-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 02/23/2022] [Indexed: 11/08/2022]
Abstract
In June 2019, the Japanese National Health Insurance (NHI) system introduced coverage for two types of tumor genomic profiling (TGP): FoundationOneⓇ CDx (F1) and OncoGuide™ NCC OncoPanel System (NCCOP). TGP sometimes reveals germline variants that are potentially pathogenic as secondary findings (SFs). We conducted a questionnaire-based survey to find out the operational statuses of F1 and NCCOP at institutions where TGP was performed to elucidate issues related to SFs. Responses were received from 97 of 112 institutions (86.6%). As of May 31, 2020, 88 (90.7%) and 78 (80.4%) institutions started performing F1 and NCCOP, respectively. Since F1 only examines tumor samples, germline confirmatory testing is necessary to determine whether they are actually germline pathogenic variants (GPVs). When physicians are obtaining informed consent all but 2.3% of the patients requested SF disclosure. Conversely, when presumed germline pathogenic variants (PGPVs) were detected, 46.2% were not willing to receive confirmatory tests as they wanted to prioritize cancer treatment over SFs investigation, while only 23.3% underwent confirmatory tests. Problems in cancer genomic medicine reported by clinical genetics departments included short-staffing (n = 10), insufficient interdepartmental cooperation (n = 9), inconsistent understanding of genetics among healthcare professionals (n = 8), and low utilization rate of SFs due to lack of insurance coverage for confirmatory tests and post-test health checkups (n = 8). Solutions include; determining the appropriate timing to confirm patient intent on SF disclosure, covering confirmatory tests for PGPVs by the NHI, and establishing cooperation between the oncology and clinical genetics departments.
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