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Till JE, McDaniel L, Chang C, Long Q, Pfeiffer SM, Lyman JP, Padrón LJ, Maurer DM, Yu JX, Spencer CN, Gherardini PF, Da Silva DM, LaVallee TM, Abbott C, Chen RO, Boyle SM, Bhagwat N, Cannas S, Sagreiya H, Li W, Yee SS, Abdalla A, Wang Z, Yin M, Ballinger D, Wissel P, Eads J, Karasic T, Schneider C, O'Dwyer P, Teitelbaum U, Reiss KA, Rahma OE, Fisher GA, Ko AH, Wainberg ZA, Wolff RA, O'Reilly EM, O'Hara MH, Cabanski CR, Vonderheide RH, Carpenter EL. Circulating KRAS G12D but not G12V is associated with survival in metastatic pancreatic ductal adenocarcinoma. Nat Commun 2024; 15:5763. [PMID: 38982051 PMCID: PMC11233636 DOI: 10.1038/s41467-024-49915-5] [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: 12/05/2023] [Accepted: 06/18/2024] [Indexed: 07/11/2024] Open
Abstract
While high circulating tumor DNA (ctDNA) levels are associated with poor survival for multiple cancers, variant-specific differences in the association of ctDNA levels and survival have not been examined. Here we investigate KRAS ctDNA (ctKRAS) variant-specific associations with overall and progression-free survival (OS/PFS) in first-line metastatic pancreatic ductal adenocarcinoma (mPDAC) for patients receiving chemoimmunotherapy ("PRINCE", NCT03214250), and an independent cohort receiving standard of care (SOC) chemotherapy. For PRINCE, higher baseline plasma levels are associated with worse OS for ctKRAS G12D (log-rank p = 0.0010) but not G12V (p = 0.7101), even with adjustment for clinical covariates. Early, on-therapy clearance of G12D (p = 0.0002), but not G12V (p = 0.4058), strongly associates with OS for PRINCE. Similar results are obtained for the SOC cohort, and for PFS in both cohorts. These results suggest ctKRAS G12D but not G12V as a promising prognostic biomarker for mPDAC and that G12D clearance could also serve as an early biomarker of response.
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Affiliation(s)
- Jacob E Till
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | | | - Changgee Chang
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Qi Long
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jaclyn P Lyman
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
| | - Lacey J Padrón
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
| | - Deena M Maurer
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
| | - Jia Xin Yu
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
| | | | | | - Diane M Da Silva
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
| | | | | | | | | | - Neha Bhagwat
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Samuele Cannas
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Hersh Sagreiya
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Wenrui Li
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Stephanie S Yee
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Aseel Abdalla
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Zhuoyang Wang
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Melinda Yin
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Dominique Ballinger
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Paul Wissel
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer Eads
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Thomas Karasic
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Charles Schneider
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Peter O'Dwyer
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Ursina Teitelbaum
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | - Kim A Reiss
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Andrew H Ko
- University of California, San Francisco, San Francisco, CA, USA
| | - Zev A Wainberg
- University of California, Los Angeles, Los Angeles, CA, USA
| | - Robert A Wolff
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Mark H O'Hara
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Erica L Carpenter
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, PA, USA.
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Cornelli L, Van Paemel R, Ferro Dos Santos MR, Roelandt S, Willems L, Vandersteene J, Baert E, Mus LM, Van Roy N, De Wilde B, De Preter K. Diagnosis of pediatric central nervous system tumors using methylation profiling of cfDNA from cerebrospinal fluid. Clin Epigenetics 2024; 16:87. [PMID: 38970137 PMCID: PMC11225235 DOI: 10.1186/s13148-024-01696-w] [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: 04/04/2024] [Accepted: 06/17/2024] [Indexed: 07/07/2024] Open
Abstract
Pediatric central nervous system tumors remain challenging to diagnose. Imaging approaches do not provide sufficient detail to discriminate between different tumor types, while the histopathological examination of tumor tissue shows high inter-observer variability. Recent studies have demonstrated the accurate classification of central nervous system tumors based on the DNA methylation profile of a tumor biopsy. However, a brain biopsy holds significant risk of bleeding and damaging the surrounding tissues. Liquid biopsy approaches analyzing circulating tumor DNA show high potential as an alternative and less invasive tool to study the DNA methylation pattern of tumors. Here, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the circulating cell-free DNA (cfDNA) in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected cerebrospinal fluid samples from 19 pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. Analyses on the cfDNA showed high variability of cfDNA quantities across patients ranging from levels below the limit of quantification to 40 ng cfDNA per milliliter of CSF. Classification based on methylation profiling of cfDNA from CSF was correct for 7 out of 20 samples in our cohort. Accurate results were mostly observed in samples of high quality, more specifically those with limited high molecular weight DNA contamination. Interestingly, we show that centrifugation of the CSF prior to processing increases the fraction of fragmented cfDNA to high molecular weight DNA. In addition, classification was mostly correct for samples with high tumoral cfDNA fraction as estimated by computational deconvolution (> 40%). In summary, analysis of cfDNA in the CSF shows potential as a tool for diagnosing pediatric nervous system tumors especially in patients with high levels of tumoral cfDNA in the CSF. Further optimization of the collection procedure, experimental workflow and bioinformatic approach is required to also allow classification for patients with low tumoral fractions in the CSF.
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Affiliation(s)
- Lotte Cornelli
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Center for Medical Biotechnology, VIB-UGent, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Ruben Van Paemel
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Pediatric Hematology, Oncology and Stem Cell Transplantation, Ghent University Hospital, Ghent, Belgium
| | - Maísa R Ferro Dos Santos
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Center for Medical Biotechnology, VIB-UGent, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Sofie Roelandt
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Center for Medical Biotechnology, VIB-UGent, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Leen Willems
- Department of Pediatric Hematology, Oncology and Stem Cell Transplantation, Ghent University Hospital, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | | | - Edward Baert
- Department of Neurosurgery, Ghent University Hospital, Ghent, Belgium
| | - Liselot M Mus
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Pediatric Hematology, Oncology and Stem Cell Transplantation, Ghent University Hospital, Ghent, Belgium
| | - Nadine Van Roy
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Bram De Wilde
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Pediatric Hematology, Oncology and Stem Cell Transplantation, Ghent University Hospital, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Katleen De Preter
- Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
- Center for Medical Biotechnology, VIB-UGent, Ghent, Belgium.
- Cancer Research Institute Ghent, Ghent, Belgium.
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3
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Li A, Lou E, Leder K, Foo J. Early ctDNA kinetics as a dynamic biomarker of cancer treatment response. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.01.601508. [PMID: 39005329 PMCID: PMC11244961 DOI: 10.1101/2024.07.01.601508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Circulating tumor DNA assays are promising tools for the prediction of cancer treatment response. Here, we build a framework for the design of ctDNA biomarkers of therapy response that incorporate variations in ctDNA dynamics driven by specific treatment mechanisms. We develop mathematical models of ctDNA kinetics driven by tumor response to several therapy classes, and utilize them to simulate randomized virtual patient cohorts to test candidate biomarkers. Using this approach, we propose specific biomarkers, based on ctDNA longitudinal features, for targeted therapy, chemotherapy and radiation therapy. We evaluate and demonstrate the efficacy of these biomarkers in predicting treatment response within a randomized virtual patient cohort dataset. These biomarkers are based on novel proposals for ctDNA sampling protocols, consisting of frequent sampling within a compact time window surrounding therapy initiation - which we hypothesize to hold valuable prognostic information on longer-term treatment response. This study highlights a need for tailoring ctDNA sampling protocols and interpretation methodology to specific biological mechanisms of therapy response, and it provides a novel modeling and simulation framework for doing so. In addition, it highlights the potential of ctDNA assays for making early, rapid predictions of treatment response within the first days or weeks of treatment, and generates hypotheses for further clinical testing.
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Affiliation(s)
- Aaron Li
- School of Mathematics, University of Minnesota, Twin Cities, MN, USA
| | - Emil Lou
- Masonic Cancer Center, University of Minnesota, Twin Cities, MN, USA
- Division of Hematology, Oncology, and Transplantation, Department of Medicine, University of Minnesota, MN, USA
| | - Kevin Leder
- Department of Industrial and Systems Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Jasmine Foo
- School of Mathematics, University of Minnesota, Twin Cities, MN, USA
- Masonic Cancer Center, University of Minnesota, Twin Cities, MN, USA
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4
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Yoon SE, Shin SH, Nam DK, Cho J, Kim WS, Kim SJ. Feasibility of Circulating Tumor DNA Analysis in Patients with Follicular Lymphoma. Cancer Res Treat 2024; 56:920-935. [PMID: 38228081 PMCID: PMC11261198 DOI: 10.4143/crt.2023.869] [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: 07/23/2023] [Accepted: 01/15/2024] [Indexed: 01/18/2024] Open
Abstract
PURPOSE The feasibility of sequencing circulating tumor DNA (ctDNA) in plasma as a biomarker to predict early relapse or poor prognosis in patients with follicular lymphoma (FL) receiving systemic immunochemotherapy is not clear. MATERIALS AND METHODS We sequenced DNA from cell-free plasma that was serially obtained from newly diagnosed FL patients undergoing systemic immunochemotherapy. The mutation profiles of ctDNA at the time of diagnosis and at response evaluation and relapse and/or progression were compared with clinical course and treatment outcomes. RESULTS Forty samples from patients receiving rituximab-containing immunochemotherapy were analyzed. Baseline sequencing detected mutations in all cases, with the major detected mutations being KMT2C (50%), CREBBP (45%), and KMT2D (45%). The concentration of ctDNA and tumor mutation burden showed a significant association with survival outcome. In particular, the presence of mutations in CREBBP and TP53 showed poor prognosis compared with patients without them. Longitudinal analysis of ctDNA using serially collected plasma samples showed an association between persistence or reappearance of ctDNA mutations and disease relapse or progression. CONCLUSION Analysis of ctDNA mutations in plasma at diagnosis might help predict outcome of disease, while analysis during follow-up may help to monitor disease status of patients with advanced FL. However, the feasibility of ctDNA measurement must be improved in order for it to become an appropriate and clinically relevant test in FL patients.
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Affiliation(s)
- Sang Eun Yoon
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | | | | | - Junhun Cho
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Won Seog Kim
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Seok Jin Kim
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University School of Medicine, Seoul, Korea
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5
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Widman AJ, Shah M, Frydendahl A, Halmos D, Khamnei CC, Øgaard N, Rajagopalan S, Arora A, Deshpande A, Hooper WF, Quentin J, Bass J, Zhang M, Langanay T, Andersen L, Steinsnyder Z, Liao W, Rasmussen MH, Henriksen TV, Jensen SØ, Nors J, Therkildsen C, Sotelo J, Brand R, Schiffman JS, Shah RH, Cheng AP, Maher C, Spain L, Krause K, Frederick DT, den Brok W, Lohrisch C, Shenkier T, Simmons C, Villa D, Mungall AJ, Moore R, Zaikova E, Cerda V, Kong E, Lai D, Malbari MS, Marton M, Manaa D, Winterkorn L, Gelmon K, Callahan MK, Boland G, Potenski C, Wolchok JD, Saxena A, Turajlic S, Imielinski M, Berger MF, Aparicio S, Altorki NK, Postow MA, Robine N, Andersen CL, Landau DA. Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment. Nat Med 2024; 30:1655-1666. [PMID: 38877116 PMCID: PMC7616143 DOI: 10.1038/s41591-024-03040-4] [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: 12/21/2023] [Accepted: 04/30/2024] [Indexed: 06/16/2024]
Abstract
In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.
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Affiliation(s)
- Adam J Widman
- New York Genome Center, New York, NY, USA.
- Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | | | - Amanda Frydendahl
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Daniel Halmos
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Cole C Khamnei
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Nadia Øgaard
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Srinivas Rajagopalan
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Anushri Arora
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Aditya Deshpande
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | | | - Jean Quentin
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jake Bass
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Mingxuan Zhang
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Theophile Langanay
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Laura Andersen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | | | - Will Liao
- New York Genome Center, New York, NY, USA
| | - Mads Heilskov Rasmussen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Tenna Vesterman Henriksen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Sarah Østrup Jensen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Jesper Nors
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Christina Therkildsen
- Gastro Unit, Copenhagen University Hospital, Amager - Hvidovre Hospital, Hvidovre, Denmark
| | - Jesus Sotelo
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Ryan Brand
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Joshua S Schiffman
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Ronak H Shah
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Colleen Maher
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
| | - Lavinia Spain
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
- Renal and Skin Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Kate Krause
- Mass General Cancer Center, Massachusetts General Hospital, Boston, MA, USA
| | - Dennie T Frederick
- Mass General Cancer Center, Massachusetts General Hospital, Boston, MA, USA
| | - Wendie den Brok
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Caroline Lohrisch
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Tamara Shenkier
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Christine Simmons
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Diego Villa
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Andrew J Mungall
- Michael Smith Genome Sciences Centre, Vancouver, British Columbia, Canada
| | - Richard Moore
- Michael Smith Genome Sciences Centre, Vancouver, British Columbia, Canada
| | - Elena Zaikova
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Viviana Cerda
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Esther Kong
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Daniel Lai
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | | | | | - Dina Manaa
- New York Genome Center, New York, NY, USA
| | | | - Karen Gelmon
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | | | - Genevieve Boland
- Mass General Cancer Center, Massachusetts General Hospital, Boston, MA, USA
| | - Catherine Potenski
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jedd D Wolchok
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Samra Turajlic
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
- Renal and Skin Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Marcin Imielinski
- New York Genome Center, New York, NY, USA
- Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | | | - Sam Aparicio
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Michael A Postow
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | | | - Claus Lindbjerg Andersen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Dan A Landau
- New York Genome Center, New York, NY, USA.
- Weill Cornell Medicine, New York, NY, USA.
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6
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Rocco G, Pennazza G, Tan KS, Vanstraelen S, Santonico M, Corba RJ, Park BJ, Sihag S, Bott MJ, Crucitti P, Isbell JM, Ginsberg MS, Weiss H, Incalzi RA, Finamore P, Longo F, Zompanti A, Grasso S, Solomon SB, Vincent A, McKnight A, Cirelli M, Voli C, Kelly S, Merone M, Molena D, Gray K, Huang J, Rusch VW, Bains MS, Downey RJ, Adusumilli PS, Jones DR. A Real-World Assessment of Stage I Lung Cancer Through Electronic Nose Technology. J Thorac Oncol 2024:S1556-0864(24)00211-9. [PMID: 38762120 DOI: 10.1016/j.jtho.2024.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 04/03/2024] [Accepted: 05/02/2024] [Indexed: 05/20/2024]
Abstract
INTRODUCTION Electronic nose (E-nose) technology has reported excellent sensitivity and specificity in the setting of lung cancer screening. However, the performance of E-nose specifically for early-stage tumors remains unclear. Therefore, the aim of our study was to assess the diagnostic performance of E-nose technology in clinical stage I lung cancer. METHODS This phase IIc trial (NCT04734145) included patients diagnosed with a single greater than or equal to 50% solid stage I nodule. Exhalates were prospectively collected from January 2020 to August 2023. Blinded bioengineers analyzed the exhalates, using E-nose technology to determine the probability of malignancy. Patients were stratified into three risk groups (low-risk, [<0.2]; moderate-risk, [≥0.2-0.7]; high-risk, [≥0.7]). The primary outcome was the diagnostic performance of E-nose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models. RESULTS Based on the predefined cutoff (<0.20), E-nose agreed with histopathologic results in 86% of cases, achieving an F1 score of 92.5%, based on 86 true positives, two false negatives, and 12 false positives (n = 100). E-nose would refer fewer patients with malignant nodules to observation (low-risk: 2 versus 9 and 11, respectively; p = 0.028 and p = 0.011) than would the Swensen and Brock models and more patients with malignant nodules to treatment without biopsy (high-risk: 27 versus 19 and 6, respectively; p = 0.057 and p < 0.001). CONCLUSIONS In the setting of clinical stage I lung cancer, E-nose agrees well with histopathology. Accordingly, E-nose technology can be used in addition to imaging or as part of a "multiomics" platform.
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Affiliation(s)
- Gaetano Rocco
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York; Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York.
| | - Giorgio Pennazza
- Department of Engineering, Unit of Electronics for Sensor Systems, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Kay See Tan
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Stijn Vanstraelen
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Marco Santonico
- Department of Science and Technology for Sustainable Development and One Health, Unit of Electronics for Sensor Systems, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Robert J Corba
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Bernard J Park
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Smita Sihag
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Matthew J Bott
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Pierfilippo Crucitti
- Department of Thoracic Surgery, Università Campus Bio-Medico di Roma, Rome, Italy
| | - James M Isbell
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Michelle S Ginsberg
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Hallie Weiss
- Department of Anesthesiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Raffaele Antonelli Incalzi
- Department of Geriatrics, Research Unit of Internal Medicine, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Panaiotis Finamore
- Department of Thoracic Surgery, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Filippo Longo
- Department of Thoracic Surgery, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Alessandro Zompanti
- Department of Engineering, Unit of Electronics for Sensor Systems, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Simone Grasso
- Department of Science and Technology for Sustainable Development and One Health, Unit of Electronics for Sensor Systems, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Stephen B Solomon
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Alain Vincent
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Alexa McKnight
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Michael Cirelli
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Carmela Voli
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Susan Kelly
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Mario Merone
- Department of Engineering, Unit of Computational Systems and Bioinformatics, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Daniela Molena
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Katherine Gray
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - James Huang
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Valerie W Rusch
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Manjit S Bains
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Robert J Downey
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Prasad S Adusumilli
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | - David R Jones
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York; Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York
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7
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Stetson D, Labrousse P, Russell H, Shera D, Abbosh C, Dougherty B, Barrett JC, Hodgson D, Hadfield J. Next-Generation Molecular Residual Disease Assays: Do We Have the Tools to Evaluate Them Properly? J Clin Oncol 2024:JCO2302301. [PMID: 38754043 DOI: 10.1200/jco.23.02301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/27/2024] [Accepted: 03/05/2024] [Indexed: 05/18/2024] Open
Affiliation(s)
- Dan Stetson
- Translational Medicine, Oncology R&D, AstraZeneca, Waltham, MA
| | - Paul Labrousse
- Translational Medicine, Oncology R&D, AstraZeneca, Waltham, MA
| | - Hugh Russell
- Translational Medicine, Oncology R&D, AstraZeneca, Waltham, MA
| | - David Shera
- Oncology Biometrics, AstraZeneca, Gaithersburg, MD
| | - Chris Abbosh
- Cancer Biomarker Development, Oncology R&D, AstraZeneca, Cambridge, United Kingdom
| | - Brian Dougherty
- Translational Medicine, Oncology R&D, AstraZeneca, Waltham, MA
| | - J Carl Barrett
- Translational Medicine, Oncology R&D, AstraZeneca, Waltham, MA
| | - Darren Hodgson
- Cancer Biomarker Development, Oncology R&D, AstraZeneca, Cambridge, United Kingdom
| | - James Hadfield
- Translational Medicine, Oncology R&D, AstraZeneca, Cambridge, United Kingdom
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8
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Rickles-Young M, Tinoco G, Tsuji J, Pollock S, Haynam M, Lefebvre H, Glover K, Owen DH, Collier KA, Ha G, Adalsteinsson VA, Cibulskis C, Lennon NJ, Stover DG. Assay Validation of Cell-Free DNA Shallow Whole-Genome Sequencing to Determine Tumor Fraction in Advanced Cancers. J Mol Diagn 2024; 26:413-422. [PMID: 38490303 PMCID: PMC11090203 DOI: 10.1016/j.jmoldx.2024.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 09/21/2023] [Accepted: 01/18/2024] [Indexed: 03/17/2024] Open
Abstract
Blood-based liquid biopsy is increasingly used in clinical care of patients with cancer, and fraction of tumor-derived DNA in circulation (tumor fraction; TFx) has demonstrated clinical validity across multiple cancer types. To determine TFx, shallow whole-genome sequencing of cell-free DNA (cfDNA) can be performed from a single blood sample, using an established computational pipeline (ichorCNA), without prior knowledge of tumor mutations, in a highly cost-effective manner. We describe assay validation of this approach to facilitate broad clinical application, including evaluation of assay sensitivity, precision, repeatability, reproducibility, pre-analytic factors, and DNA quality/quantity. Sensitivity to detect TFx of 3% (lower limit of detection) was 97.2% to 100% at 1× and 0.1× mean sequencing depth, respectively. Precision was demonstrated on distinct sequencing instruments (HiSeqX and NovaSeq) with no observable differences. The assay achieved prespecified 95% agreement of TFx across replicates of the same specimen (repeatability) and duplicate samples in different batches (reproducibility). Comparison of samples collected in EDTA and Streck tubes from single venipuncture in 23 patients demonstrated that EDTA or Streck tubes were comparable if processed within 8 hours. On the basis of a range of DNA inputs (1 to 50 ng), 20 ng cfDNA is the preferred input, with 5 ng minimum acceptable. Overall, this shallow whole-genome sequencing of cfDNA and ichorCNA approach offers sensitive, precise, and reproducible quantitation of TFx, facilitating assay application in clinical cancer care.
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Affiliation(s)
- Micah Rickles-Young
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Gabriel Tinoco
- Division of Medical Oncology, The Ohio State University College of Medicine, Columbus, Ohio; Ohio State University Comprehensive Cancer Center, Columbus, Ohio
| | - Junko Tsuji
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Sam Pollock
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Marcy Haynam
- Ohio State University Comprehensive Cancer Center, Columbus, Ohio; Stefanie Spielman Comprehensive Breast Center, Columbus, Ohio
| | - Heather Lefebvre
- Ohio State University Comprehensive Cancer Center, Columbus, Ohio; Stefanie Spielman Comprehensive Breast Center, Columbus, Ohio
| | - Kristyn Glover
- Ohio State University Comprehensive Cancer Center, Columbus, Ohio; Stefanie Spielman Comprehensive Breast Center, Columbus, Ohio
| | - Dwight H Owen
- Division of Medical Oncology, The Ohio State University College of Medicine, Columbus, Ohio; Ohio State University Comprehensive Cancer Center, Columbus, Ohio
| | - Katharine A Collier
- Division of Medical Oncology, The Ohio State University College of Medicine, Columbus, Ohio; Ohio State University Comprehensive Cancer Center, Columbus, Ohio
| | - Gavin Ha
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Viktor A Adalsteinsson
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Carrie Cibulskis
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Niall J Lennon
- Genomics Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts.
| | - Daniel G Stover
- Division of Medical Oncology, The Ohio State University College of Medicine, Columbus, Ohio; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; Stefanie Spielman Comprehensive Breast Center, Columbus, Ohio.
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9
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Hashimoto T, Nakamura Y, Oki E, Kobayashi S, Yuda J, Shibuki T, Bando H, Yoshino T. Bridging horizons beyond CIRCULATE-Japan: a new paradigm in molecular residual disease detection via whole genome sequencing-based circulating tumor DNA assay. Int J Clin Oncol 2024; 29:495-511. [PMID: 38551727 PMCID: PMC11043144 DOI: 10.1007/s10147-024-02493-4] [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: 01/28/2024] [Accepted: 02/16/2024] [Indexed: 04/26/2024]
Abstract
Circulating tumor DNA (ctDNA) is the fraction of cell-free DNA in patient blood that originates from a tumor. Advances in DNA sequencing technologies and our understanding of the molecular biology of tumors have increased interest in exploiting ctDNA to facilitate detection of molecular residual disease (MRD). Analysis of ctDNA as a promising MRD biomarker of solid malignancies has a central role in precision medicine initiatives exemplified by our CIRCULATE-Japan project involving patients with resectable colorectal cancer. Notably, the project underscores the prognostic significance of the ctDNA status at 4 weeks post-surgery and its correlation to adjuvant therapy efficacy at interim analysis. This substantiates the hypothesis that MRD is a critical prognostic indicator of relapse in patients with colorectal cancer. Despite remarkable advancements, challenges endure, primarily attributable to the exceedingly low ctDNA concentration in peripheral blood, particularly in scenarios involving low tumor shedding and the intrinsic error rates of current sequencing technologies. These complications necessitate more sensitive and sophisticated assays to verify the clinical utility of MRD across all solid tumors. Whole genome sequencing (WGS)-based tumor-informed MRD assays have recently demonstrated the ability to detect ctDNA in the parts-per-million range. This review delineates the current landscape of MRD assays, highlighting WGS-based approaches as the forefront technique in ctDNA analysis. Additionally, it introduces our upcoming endeavor, WGS-based pan-cancer MRD detection via ctDNA, in our forthcoming project, SCRUM-Japan MONSTAR-SCREEN-3.
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Affiliation(s)
- Tadayoshi Hashimoto
- Translational Research Support Office, National Cancer Center Hospital East, Kashiwa, Japan
- Department of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan
| | - Yoshiaki Nakamura
- Translational Research Support Office, National Cancer Center Hospital East, Kashiwa, Japan
- Department of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan
| | - Eiji Oki
- Department of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shin Kobayashi
- Department of Hepatobiliary and Pancreatic Surgery, National Cancer Center Hospital East, Kashiwa, Japan
| | - Junichiro Yuda
- Department of Hematology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Taro Shibuki
- Translational Research Support Office, National Cancer Center Hospital East, Kashiwa, Japan
| | - Hideaki Bando
- Translational Research Support Office, National Cancer Center Hospital East, Kashiwa, Japan
- Department of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan
| | - Takayuki Yoshino
- Department of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
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10
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Ma Z, Xu J, Hou W, Lei Z, Li T, Shen W, Yu H, Liu C, Zhang J, Tang S. Detection of Single Nucleotide Polymorphisms of Circulating Tumor DNA by Strand Displacement Amplification Coupled with Liquid Chromatography. Anal Chem 2024; 96:5195-5204. [PMID: 38520334 DOI: 10.1021/acs.analchem.3c05500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/25/2024]
Abstract
The detection of multiple single nucleotide polymorphisms (SNPs) of circulating tumor DNA (ctDNA) is still a great challenge. In this study, we designed enzyme-assisted nucleic acid strand displacement amplification combined with high-performance liquid chromatography (HPLC) for the simultaneous detection of three ctDNA SNPs. First, the trace ctDNA could be hybridized to the specially designed template strand, which initiated the strand displacement nucleic acid amplification process under the synergistic action of DNA polymerase and restriction endonuclease. Then, the targets would be replaced with G-quadruplex fluorescent probes with different tail lengths. Finally, the HPLC-fluorescence assay enabled the separation and quantification of multiple signals. Notably, this method can simultaneously detect both the wild type (WT) and mutant type (MT) of multiple ctDNA SNPs. Within a linear range of 0.1 fM-0.1 nM, the detection limits of BRAF V600E-WT, EGFR T790M-WT, and KRAS 134A-WT and BRAF V600E-MT, EGFR T790M-MT, and KRAS 134A-MT were 29, 31, and 11 aM and 22, 29, and 33 aM, respectively. By using this method, the mutation rates of multiple ctDNA SNPs in blood samples from patients with lung or breast cancer can be obtained in a simple way, providing a convenient and highly sensitive analytical assay for the early screening and monitoring of lung cancer.
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Affiliation(s)
- Ziyu Ma
- School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, P. R. China
| | - Junjie Xu
- School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, P. R. China
| | - Weilin Hou
- School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, P. R. China
| | - Zi Lei
- School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, P. R. China
| | - Tingting Li
- School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, P. R. China
| | - Wei Shen
- School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, P. R. China
| | - Hui Yu
- Department of Thoracic Surgery, Affiliated Hospital of Jiangsu University, No. 438, Jiefang Road, Zhenjiang 212000, Jiangsu, P. R. China
| | - Chang Liu
- School of Grain Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, P. R. China
| | - Jinghui Zhang
- School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, P. R. China
| | - Sheng Tang
- School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, P. R. China
- College of Chemistry, Chemical Engineering and Materials Science, Soochow University, Suzhou 215123, P. R. China
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11
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Fonseca NM, Maurice-Dror C, Herberts C, Tu W, Fan W, Murtha AJ, Kollmannsberger C, Kwan EM, Parekh K, Schönlau E, Bernales CQ, Donnellan G, Ng SWS, Sumiyoshi T, Vergidis J, Noonan K, Finch DL, Zulfiqar M, Miller S, Parimi S, Lavoie JM, Hardy E, Soleimani M, Nappi L, Eigl BJ, Kollmannsberger C, Taavitsainen S, Nykter M, Tolmeijer SH, Boerrigter E, Mehra N, van Erp NP, De Laere B, Lindberg J, Grönberg H, Khalaf DJ, Annala M, Chi KN, Wyatt AW. Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer. Nat Commun 2024; 15:1828. [PMID: 38418825 PMCID: PMC10902374 DOI: 10.1038/s41467-024-45475-w] [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: 07/21/2023] [Accepted: 01/24/2024] [Indexed: 03/02/2024] Open
Abstract
No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine-learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org ). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.
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Affiliation(s)
- Nicolette M Fonseca
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | | | - Cameron Herberts
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Wilson Tu
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - William Fan
- Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada
| | - Andrew J Murtha
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | | | - Edmond M Kwan
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
- Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada
- Department of Medicine, School of Clinical Sciences; Monash University, Melbourne, VIC, Australia
| | - Karan Parekh
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Elena Schönlau
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Cecily Q Bernales
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Gráinne Donnellan
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Sarah W S Ng
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Takayuki Sumiyoshi
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
- Department of Urology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Joanna Vergidis
- Department of Medical Oncology, BC Cancer, Victoria, BC, Canada
| | - Krista Noonan
- Department of Medical Oncology, BC Cancer, Surrey, BC, Canada
| | - Daygen L Finch
- Department of Medical Oncology, BC Cancer, Kelowna, BC, Canada
| | | | - Stacy Miller
- Department of Radiation Oncology, BC Cancer, Prince George, BC, Canada
| | - Sunil Parimi
- Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada
| | | | - Edward Hardy
- Tom McMurtry & Peter Baerg Cancer Centre, Vernon Jubilee Hospital, Vernon, BC, Canada
| | - Maryam Soleimani
- Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada
| | - Lucia Nappi
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
- Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada
| | - Bernhard J Eigl
- Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada
| | | | - Sinja Taavitsainen
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Center, Tampere, Finland
| | - Matti Nykter
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Center, Tampere, Finland
| | - Sofie H Tolmeijer
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
- Department of Medical Oncology, Research Institute for Medical Innovation, Radboud University, Nijmegen, The Netherlands
| | - Emmy Boerrigter
- Department of Pharmacy, Research Institute for Medical Innovation, Radboud University, Nijmegen, The Netherlands
| | - Niven Mehra
- Department of Medical Oncology, Research Institute for Medical Innovation, Radboud University, Nijmegen, The Netherlands
| | - Nielka P van Erp
- Department of Pharmacy, Research Institute for Medical Innovation, Radboud University, Nijmegen, The Netherlands
| | - Bram De Laere
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Johan Lindberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Henrik Grönberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Daniel J Khalaf
- Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada
| | - Matti Annala
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada.
- Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University and Tays Cancer Center, Tampere, Finland.
| | - Kim N Chi
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada.
- Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada.
| | - Alexander W Wyatt
- Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada.
- Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada.
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12
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Rachman T, Bartlett D, LaFramboise W, Wagner P, Schwartz R, Carja O. Modeling the Effect of Spatial Structure on Solid Tumor Evolution and Circulating Tumor DNA Composition. Cancers (Basel) 2024; 16:844. [PMID: 38473206 PMCID: PMC10930890 DOI: 10.3390/cancers16050844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 03/14/2024] Open
Abstract
Circulating tumor DNA (ctDNA) monitoring, while sufficiently advanced to reflect tumor evolution in real time and inform cancer diagnosis, treatment, and prognosis, mainly relies on DNA that originates from cell death via apoptosis or necrosis. In solid tumors, chemotherapy and immune infiltration can induce spatially variable rates of cell death, with the potential to bias and distort the clonal composition of ctDNA. Using a stochastic evolutionary model of boundary-driven growth, we study how elevated cell death on the edge of a tumor can simultaneously impact driver mutation accumulation and the representation of tumor clones and mutation detectability in ctDNA. We describe conditions in which invasive clones are over-represented in ctDNA, clonal diversity can appear elevated in the blood, and spatial bias in shedding can inflate subclonal variant allele frequencies (VAFs). Additionally, we find that tumors that are mostly quiescent can display similar biases but are far less detectable, and the extent of perceptible spatial bias strongly depends on sequence detection limits. Overall, we show that spatially structured shedding might cause liquid biopsies to provide highly biased profiles of tumor state. While this may enable more sensitive detection of expanding clones, it could also increase the risk of targeting a subclonal variant for treatment. Our results indicate that the effects and clinical consequences of spatially variable cell death on ctDNA composition present an important area for future work.
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Affiliation(s)
- Thomas Rachman
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, PA 15213, USA
| | - David Bartlett
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA
| | - William LaFramboise
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA
| | - Patrick Wagner
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh, PA 15224, USA
| | - Russell Schwartz
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Oana Carja
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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13
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Tran HT, Heeke S, Sujit S, Vokes N, Zhang J, Aminu M, Lam VK, Vaporciyan A, Swisher SG, Godoy MCB, Cascone T, Sepesi B, Gibbons DL, Wu J, Heymach JV. Circulating tumor DNA and radiological tumor volume identify patients at risk for relapse with resected, early-stage non-small-cell lung cancer. Ann Oncol 2024; 35:183-189. [PMID: 37992871 PMCID: PMC11233158 DOI: 10.1016/j.annonc.2023.11.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 11/01/2023] [Accepted: 11/15/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND Predicting relapse and overall survival (OS) in early-stage non-small-cell lung cancer (NSCLC) patients remains challenging. Therefore, we hypothesized that detection of circulating tumor DNA (ctDNA) can identify patients with increased risk of relapse and that integrating radiological tumor volume measurement along with ctDNA detectability improves prediction of outcome. PATIENTS AND METHODS We analyzed 366 serial plasma samples from 85 patients who underwent surgical resections and assessed ctDNA using a next-generation sequencing liquid biopsy assay, and measured tumor volume using a computed tomography-based three-dimensional annotation. RESULTS Our results showed that patients with detectable ctDNA at baseline or after treatment and patients who did not clear ctDNA after treatment had a significantly worse clinical outcome. Integrating radiological analysis allowed the stratification in risk groups prognostic of clinical outcome as confirmed in an independent cohort of 32 patients. CONCLUSIONS Our findings suggest ctDNA and radiological monitoring could be valuable tools for guiding follow-up care and treatment decisions for early-stage NSCLC patients.
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Affiliation(s)
- H T Tran
- Department of Thoracic Head & Neck Medical Oncology
| | - S Heeke
- Department of Thoracic Head & Neck Medical Oncology
| | - S Sujit
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston
| | - N Vokes
- Department of Thoracic Head & Neck Medical Oncology
| | - J Zhang
- Department of Thoracic Head & Neck Medical Oncology
| | - M Aminu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston
| | - V K Lam
- Department of Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins, Baltimore
| | - A Vaporciyan
- Department of Thoracic and Cardiovascular Surgery
| | - S G Swisher
- Department of Thoracic and Cardiovascular Surgery
| | - M C B Godoy
- Department of Thoracic Imaging, The University of Texas MD Anderson Cancer Center, Houston, USA
| | - T Cascone
- Department of Thoracic Head & Neck Medical Oncology
| | - B Sepesi
- Department of Thoracic Head & Neck Medical Oncology
| | - D L Gibbons
- Department of Thoracic Head & Neck Medical Oncology
| | - J Wu
- Department of Thoracic Head & Neck Medical Oncology; Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston
| | - J V Heymach
- Department of Thoracic Head & Neck Medical Oncology.
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14
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Martin-Alonso C, Tabrizi S, Xiong K, Blewett T, Sridhar S, Crnjac A, Patel S, An Z, Bekdemir A, Shea D, Wang ST, Rodriguez-Aponte S, Naranjo CA, Rhoades J, Kirkpatrick JD, Fleming HE, Amini AP, Golub TR, Love JC, Bhatia SN, Adalsteinsson VA. Priming agents transiently reduce the clearance of cell-free DNA to improve liquid biopsies. Science 2024; 383:eadf2341. [PMID: 38236959 DOI: 10.1126/science.adf2341] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 12/01/2023] [Indexed: 01/23/2024]
Abstract
Liquid biopsies enable early detection and monitoring of diseases such as cancer, but their sensitivity remains limited by the scarcity of analytes such as cell-free DNA (cfDNA) in blood. Improvements to sensitivity have primarily relied on enhancing sequencing technology ex vivo. We sought to transiently augment the level of circulating tumor DNA (ctDNA) in a blood draw by attenuating its clearance in vivo. We report two intravenous priming agents given 1 to 2 hours before a blood draw to recover more ctDNA. Our priming agents consist of nanoparticles that act on the cells responsible for cfDNA clearance and DNA-binding antibodies that protect cfDNA. In tumor-bearing mice, they greatly increase the recovery of ctDNA and improve the sensitivity for detecting small tumors.
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Affiliation(s)
- Carmen Martin-Alonso
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Harvard-MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Shervin Tabrizi
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Kan Xiong
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Timothy Blewett
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Andjela Crnjac
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sahil Patel
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Division of Pulmonary and Critical Care, Department of Medicine, Massachusetts General Hospital, Boston, MA 02124, USA
| | - Zhenyi An
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ahmet Bekdemir
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Douglas Shea
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shih-Ting Wang
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Sergio Rodriguez-Aponte
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Christopher A Naranjo
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Justin Rhoades
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jesse D Kirkpatrick
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Harvard-MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Heather E Fleming
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ava P Amini
- Microsoft Research, Cambridge, MA 02142, USA
| | - Todd R Golub
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - J Christopher Love
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Sangeeta N Bhatia
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Harvard-MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
- Wyss Institute at Harvard University, Boston, MA 02215, USA
- Howard Hughes Medical Institute, Cambridge, MA 02138, USA
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15
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van den Broek D, Groen HJM. Screening approaches for lung cancer by blood-based biomarkers: Challenges and opportunities. Tumour Biol 2024; 46:S65-S80. [PMID: 37393461 DOI: 10.3233/tub-230004] [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] [Indexed: 07/03/2023] Open
Abstract
Lung cancer (LC) is one of the leading causes for cancer-related deaths in the world, accounting for 28% of all cancer deaths in Europe. Screening for lung cancer can enable earlier detection of LC and reduce lung cancer mortality as was demonstrated in several large image-based screening studies such as the NELSON and the NLST. Based on these studies, screening is recommended in the US and in the UK a targeted lung health check program was initiated. In Europe lung cancer screening (LCS) has not been implemented due to limited data on cost-effectiveness in the different health care systems and questions on for example the selection of high-risk individuals, adherence to screening, management of indeterminate nodules, and risk of overdiagnosis. Liquid biomarkers are considered to have a high potential to address these questions by supporting pre- and post- Low Dose CT (LDCT) risk-assessment thereby improving the overall efficacy of LCS. A wide variety of biomarkers, including cfDNA, miRNA, proteins and inflammatory markers have been studied in the context of LCS. Despite the available data, biomarkers are currently not implemented or evaluated in screening studies or screening programs. As a result, it remains an open question which biomarker will actually improve a LCS program and do this against acceptable costs. In this paper we discuss the current status of different promising biomarkers and the challenges and opportunities of blood-based biomarkers in the context of lung cancer screening.
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Affiliation(s)
- Daniel van den Broek
- Department of laboratory Medicine, The Netherlands Cancer Institute, Amsterdam, The Netherlands
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16
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Stolovich-Rain M, Fridlich O, Azulai S, Klochendler A, Anzi S, Magenheim J, Stein I, Mushasha F, Glaser B, Pikarsky E, Ben-Zvi D, Dor Y. Extensive elimination of acinar cells during normal postnatal pancreas growth. Cell Rep 2023; 42:113457. [PMID: 37995187 DOI: 10.1016/j.celrep.2023.113457] [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: 09/26/2022] [Revised: 09/01/2023] [Accepted: 11/02/2023] [Indexed: 11/25/2023] Open
Abstract
While programmed cell death plays important roles during morphogenetic stages of development, post-differentiation organ growth is considered an efficient process whereby cell proliferation increases cell number. Here we demonstrate that early postnatal growth of the pancreas unexpectedly involves massive acinar cell elimination. Measurements of cell proliferation and death in the human pancreas in comparison to the actual increase in cell number predict daily elimination of 0.7% of cells, offsetting 88% of cell formation over the first year of life. Using mouse models, we show that death is associated with mitosis, through a failure of dividing cells to generate two viable daughters. In p53-deficient mice, acinar cell death and proliferation are reduced, while organ size is normal, suggesting that p53-dependent developmental apoptosis triggers compensatory proliferation. We propose that excess cell turnover during growth of the pancreas, and presumably other organs, facilitates robustness to perturbations and supports maintenance of tissue architecture.
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Affiliation(s)
- Miri Stolovich-Rain
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Ori Fridlich
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Shira Azulai
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Agnes Klochendler
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Shira Anzi
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Judith Magenheim
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Ilan Stein
- The Concern Foundation Laboratories at The Lautenberg Center for Immunology and Cancer Research, Israel-Canada Medical Research Institute, Faculty of Medicine, The Hebrew University, Jerusalem, Israel; Department of Pathology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Fatima Mushasha
- The Concern Foundation Laboratories at The Lautenberg Center for Immunology and Cancer Research, Israel-Canada Medical Research Institute, Faculty of Medicine, The Hebrew University, Jerusalem, Israel
| | - Benjamin Glaser
- Endocrinology and Metabolism Service, Department of Internal Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Eli Pikarsky
- The Concern Foundation Laboratories at The Lautenberg Center for Immunology and Cancer Research, Israel-Canada Medical Research Institute, Faculty of Medicine, The Hebrew University, Jerusalem, Israel; Department of Pathology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Danny Ben-Zvi
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Yuval Dor
- Department of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel.
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17
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Melton CA, Freese P, Zhou Y, Shenoy A, Bagaria S, Chang C, Kuo CC, Scott E, Srinivasan S, Cann G, Roychowdhury-Saha M, Chang PY, Singh AH. A Novel Tissue-Free Method to Estimate Tumor-Derived Cell-Free DNA Quantity Using Tumor Methylation Patterns. Cancers (Basel) 2023; 16:82. [PMID: 38201510 PMCID: PMC10777919 DOI: 10.3390/cancers16010082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/07/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024] Open
Abstract
Estimating the abundance of cell-free DNA (cfDNA) fragments shed from a tumor (i.e., circulating tumor DNA (ctDNA)) can approximate tumor burden, which has numerous clinical applications. We derived a novel, broadly applicable statistical method to quantify cancer-indicative methylation patterns within cfDNA to estimate ctDNA abundance, even at low levels. Our algorithm identified differentially methylated regions (DMRs) between a reference database of cancer tissue biopsy samples and cfDNA from individuals without cancer. Then, without utilizing matched tissue biopsy, counts of fragments matching the cancer-indicative hyper/hypo-methylated patterns within DMRs were used to determine a tumor methylated fraction (TMeF; a methylation-based quantification of the circulating tumor allele fraction and estimate of ctDNA abundance) for plasma samples. TMeF and small variant allele fraction (SVAF) estimates of the same cancer plasma samples were correlated (Spearman's correlation coefficient: 0.73), and synthetic dilutions to expected TMeF of 10-3 and 10-4 had estimated TMeF within two-fold for 95% and 77% of samples, respectively. TMeF increased with cancer stage and tumor size and inversely correlated with survival probability. Therefore, tumor-derived fragments in the cfDNA of patients with cancer can be leveraged to estimate ctDNA abundance without the need for a tumor biopsy, which may provide non-invasive clinical approximations of tumor burden.
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18
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Wang D, Rausch C, Buerger SA, Tschuri S, Rothenberg-Thurley M, Schulz M, Hasenauer J, Ziemann F, Metzeler KH, Marr C. Modeling early treatment response in AML from cell-free tumor DNA. iScience 2023; 26:108271. [PMID: 38047080 PMCID: PMC10690559 DOI: 10.1016/j.isci.2023.108271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 10/03/2023] [Accepted: 10/17/2023] [Indexed: 12/05/2023] Open
Abstract
Monitoring disease response after intensive chemotherapy for acute myeloid leukemia (AML) currently requires invasive bone marrow biopsies, imposing a significant burden on patients. In contrast, cell-free tumor DNA (ctDNA) in peripheral blood, carrying tumor-specific mutations, offers a less-invasive assessment of residual disease. However, the relationship between ctDNA levels and bone marrow blast kinetics remains unclear. We explored this in 10 AML patients with NPM1 and IDH2 mutations undergoing initial chemotherapy. Comparison of mathematical mixed-effect models showed that (1) inclusion of blast cell death in the bone marrow, (2) transition of ctDNA to peripheral blood, and (3) ctDNA decay in peripheral blood describes kinetics of blast cells and ctDNA best. The fitted model allows prediction of residual bone marrow blast content from ctDNA, and its scaling factor, representing clonal heterogeneity, correlates with relapse risk. Our study provides precise insights into blast and ctDNA kinetics, offering novel avenues for AML disease monitoring.
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Affiliation(s)
- Dantong Wang
- Institute of AI for Health, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany
- Center for Mathematics, Technische Universität München, Garching 85748, Germany
| | - Christian Rausch
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital (LMU), Munich, Germany
- German Cancer Consortium (DKTK), partner sites Munich/Dresden, Germany
| | - Simon A. Buerger
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital (LMU), Munich, Germany
| | - Sebastian Tschuri
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital (LMU), Munich, Germany
| | - Maja Rothenberg-Thurley
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital (LMU), Munich, Germany
| | - Melanie Schulz
- Institute of AI for Health, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany
- Center for Mathematics, Technische Universität München, Garching 85748, Germany
| | - Jan Hasenauer
- Center for Mathematics, Technische Universität München, Garching 85748, Germany
- Computational Health Center, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany
- Faculty of Mathematics and Natural Sciences, Rheinische Friedrich-Wilhelms-Universität Bonn, 53115 Bonn, Germany
| | - Frank Ziemann
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital (LMU), Munich, Germany
- German Cancer Consortium (DKTK), partner sites Munich/Dresden, Germany
| | - Klaus H. Metzeler
- Department of Hematology and Cell Therapy, University Hospital Leipzig (UHL) 04103, Germany
| | - Carsten Marr
- Institute of AI for Health, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany
- Center for Mathematics, Technische Universität München, Garching 85748, Germany
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19
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Yuan S, Nie R, Huang Y, Chen Y, Wang S, Sun X, Li Y, Liu Z, Chen Y, Yao Y, Xu Y, Qiu H, Liang Y, Wang W, Liu Z, Zhao Q, Xu R, Zhou Z, Wang F. Residual circulating tumor DNA after adjuvant chemotherapy effectively predicts recurrence of stage II-III gastric cancer. Cancer Commun (Lond) 2023; 43:1312-1325. [PMID: 37837629 PMCID: PMC10693304 DOI: 10.1002/cac2.12494] [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: 03/26/2023] [Revised: 09/24/2023] [Accepted: 10/03/2023] [Indexed: 10/16/2023] Open
Abstract
BACKGROUND Circulating tumor DNA (ctDNA) is a promising biomarker for predicting relapse in multiple solid cancers. However, the predictive value of ctDNA for disease recurrence remains indefinite in locoregional gastric cancer (GC). Here, we aimed to evaluate the predictive value of ctDNA in this context. METHODS From 2016 to 2019, 100 patients with stage II/III resectable GC were recruited in this prospective cohort study (NCT02887612). Primary tumors were collected during surgical resection, and plasma samples were collected perioperatively and within 3 months after adjuvant chemotherapy (ACT). Somatic variants were captured via a targeted sequencing panel of 425 cancer-related genes. The plasma was defined as ctDNA-positive only if one or more variants detected in the plasma were presented in at least 2% of the primary tumors. RESULTS Compared with ctDNA-negative patients, patients with positive postoperative ctDNA had moderately higher risk of recurrence [hazard ratio (HR) = 2.74, 95% confidence interval (CI) = 1.37-5.48; P = 0.003], while patients with positive post-ACT ctDNA showed remarkably higher risk (HR = 14.99, 95% CI = 3.08-72.96; P < 0.001). Multivariate analyses indicated that both postoperative and post-ACT ctDNA positivity were independent predictors of recurrence-free survival (RFS). Moreover, post-ACT ctDNA achieved better predictive performance (sensitivity, 77.8%; specificity, 90.6%) than both postoperative ctDNA and serial cancer antigen. A comprehensive model incorporating ctDNA for recurrence risk prediction showed a higher C-index (0.78; 95% CI = 0.71-0.84) than the model without ctDNA (0.71; 95% CI = 0.64-0.79; P = 0.009). CONCLUSIONS Residual ctDNA after ACT effectively predicts high recurrence risk in stage II/III GC, and the combination of tissue-based and circulating tumor features could achieve better risk prediction.
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20
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Rachman T, Bartlett D, Laframboise W, Wagner P, Schwartz R, Carja O. Modeling the effect of spatial structure on solid tumor evolution and ctDNA composition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.10.566658. [PMID: 37986965 PMCID: PMC10659436 DOI: 10.1101/2023.11.10.566658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Circulating tumor DNA (ctDNA) monitoring, while sufficiently advanced to reflect tumor evolution in real time and inform on cancer diagnosis, treatment, and prognosis, mainly relies on DNA that originates from cell death via apoptosis or necrosis. In solid tumors, chemotherapy and immune infiltration can induce spatially variable rates of cell death, with the potential to bias and distort the clonal composition of ctDNA. Using a stochastic evolutionary model of boundary-driven growth, we study how elevated cell death on the edge of a tumor can simultaneously impact driver mutation accumulation and the representation of tumor clones and mutation detectability in ctDNA. We describe conditions in which invasive clones end up over-represented in ctDNA, clonal diversity can appear elevated in the blood, and spatial bias in shedding can inflate subclonal variant allele frequencies (VAFs). Additionally, we find that tumors that are mostly quiescent can display similar biases, but are far less detectable, and the extent of perceptible spatial bias strongly depends on sequence detection limits. Overall, we show that spatially structured shedding might cause liquid biopsies to provide highly biased profiles of tumor state. While this may enable more sensitive detection of expanding clones, it could also increase the risk of targeting a subclonal variant for treatment. Our results indicate that the effects and clinical consequences of spatially variable cell death on ctDNA composition present an important area for future work.
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Affiliation(s)
- Thomas Rachman
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology
| | - David Bartlett
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh PA
| | | | - Patrick Wagner
- Allegheny Cancer Institute, Allegheny Health Network, Pittsburgh PA
| | - Russell Schwartz
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Oana Carja
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
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21
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Sikosek T, Horos R, Trudzinski F, Jehn J, Frank M, Rajakumar T, Klotz LV, Mercaldo N, Kahraman M, Heuvelman M, Taha Y, Gerwing J, Skottke J, Daniel-Moreno A, Sanchez-Delgado M, Bender S, Rudolf C, Hinkfoth F, Tikk K, Schenz J, Weigand MA, Feindt P, Schumann C, Christopoulos P, Winter H, Kreuter M, Schneider MA, Muley T, Walterspacher S, Schuler M, Darwiche K, Taube C, Hegedus B, Rabe KF, Rieger-Christ K, Jacobsen FL, Aigner C, Reck M, Bankier AA, Sharma A, Steinkraus BR. Early Detection of Lung Cancer Using Small RNAs. J Thorac Oncol 2023; 18:1504-1523. [PMID: 37437883 DOI: 10.1016/j.jtho.2023.07.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 06/20/2023] [Accepted: 07/05/2023] [Indexed: 07/14/2023]
Abstract
INTRODUCTION Lung cancer remains the deadliest cancer in the world, and lung cancer survival is heavily dependent on tumor stage at the time of detection. Low-dose computed tomography screening can reduce mortality; however, annual screening is limited by low adherence in the United States of America and still not broadly implemented in Europe. As a result, less than 10% of lung cancers are detected through existing programs. Thus, there is a great need for additional screening tests, such as a blood test, that could be deployed in the primary care setting. METHODS We prospectively recruited 1384 individuals meeting the National Lung Screening Trial demographic eligibility criteria for lung cancer and collected stabilized whole blood to enable the pipetting-free collection of material, thus minimizing preanalytical noise. Ultra-deep small RNA sequencing (20 million reads per sample) was performed with the addition of a method to remove highly abundant erythroid RNAs, and thus open bandwidth for the detection of less abundant species originating from the plasma or the immune cellular compartment. We used 100 random data splits to train and evaluate an ensemble of logistic regression classifiers using small RNA expression of 943 individuals, discovered an 18-small RNA feature consensus signature (miLung), and validated this signature in an independent cohort (441 individuals). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin. RESULTS We generated diagnostic models and report a median receiver-operating characteristic area under the curve of 0.86 (95% confidence interval [CI]: 0.84-0.86) in the discovery cohort and generalized performance of 0.83 in the validation cohort. Diagnostic performance increased in a stage-dependent manner ranging from 0.73 (95% CI: 0.71-0.76) for stage I to 0.90 (95% CI: 0.89-0.90) for stage IV in the discovery cohort and from 0.76 to 0.86 in the validation cohort. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased after surgery with curative intent. In additional experiments, results of dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted through home sampling. CONCLUSIONS These data suggest the potential of a small RNA-based blood test as a viable alternative to low-dose computed tomography screening for early detection of smoking-associated lung cancer.
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Affiliation(s)
| | | | - Franziska Trudzinski
- Center for Interstitial and Rare Lung Diseases, Department of Pneumology and Critical Care Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Julia Jehn
- Hummingbird Diagnostics GmbH, Heidelberg, Germany
| | | | | | - Laura V Klotz
- Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany; Department of Thoracic Surgery, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Nathaniel Mercaldo
- Institute for Technology Assessment, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | | | | | - Yasser Taha
- Hummingbird Diagnostics GmbH, Heidelberg, Germany
| | | | | | | | | | | | | | | | - Kaja Tikk
- Hummingbird Diagnostics GmbH, Heidelberg, Germany
| | - Judith Schenz
- Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Markus A Weigand
- Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Peter Feindt
- Klinik für Thoraxchirurgie, Clemenshospital Münster, Münster, Germany
| | - Christian Schumann
- Klinik für Pneumologie, Thoraxonkologie, Schlaf- und Beatmungsmedizin, Klinikum Kempten und Klinik Immenstadt, Klinikverbund Allgäu, Kempten, Germany
| | - Petros Christopoulos
- Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany; Department of Thoracic Oncology, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Hauke Winter
- Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany; Department of Thoracic Surgery, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Michael Kreuter
- Mainz Center for Pulmonary Medicine, Departments of Pneumology, Mainz University Medical Center and of Pulmonary, Critical Care & Sleep Medicine, Marienhaus Clinic Mainz, Mainz, Germany
| | - Marc A Schneider
- Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany; Translational Research Unit, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Thomas Muley
- Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany; Translational Research Unit, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Stephan Walterspacher
- Lungenzentrum Bodensee, II. Medizinische Klinik, Klinikum Konstanz, Konstanz, Germany; Faculty of Health/School of Medicine, Witten/Herdecke University, Witten, Germany
| | - Martin Schuler
- West German Cancer Center, Department of Medical Oncology, University Hospital Essen, Essen, Germany
| | - Kaid Darwiche
- Klinik für Pneumologie, Universitätsmedizin Essen - Ruhrlandklinik, Essen, Germany
| | - Christian Taube
- Klinik für Pneumologie, Universitätsmedizin Essen - Ruhrlandklinik, Essen, Germany
| | - Balazs Hegedus
- Department of Thoracic Surgery, University Medicine Essen, Ruhrlandklinik, Essen, Germany
| | - Klaus F Rabe
- LungenClinic Grosshansdorf, Airway Research Center North, German Center for Lung Research (DZL), Grosshansdorf, Germany; Department of Medicine, Christian Albrechts University of Kiel, Kiel, Germany
| | - Kimberly Rieger-Christ
- Department of Translational Research, Lahey Hospital and Medical Center, Burlington, Massachusetts
| | - Francine L Jacobsen
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Clemens Aigner
- Department of Thoracic Surgery, University Medicine Essen, Ruhrlandklinik, Essen, Germany
| | - Martin Reck
- LungenClinic Grosshansdorf, Airway Research Center North, German Center for Lung Research (DZL), Grosshansdorf, Germany
| | - Alexander A Bankier
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Amita Sharma
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
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22
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Bearz A, Martini JF, Jassem J, Kim SW, Chang GC, Shaw AT, Shepard DA, Dall'O' E, Polli A, Thurm H, Zalcman G, Garcia Campelo MR, Penkov K, Hayashi H, Solomon BJ. Efficacy of Lorlatinib in Treatment-Naive Patients With ALK-Positive Advanced NSCLC in Relation to EML4::ALK Variant Type and ALK With or Without TP53 Mutations. J Thorac Oncol 2023; 18:1581-1593. [PMID: 37541389 DOI: 10.1016/j.jtho.2023.07.023] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/27/2023] [Accepted: 07/28/2023] [Indexed: 08/06/2023]
Abstract
INTRODUCTION Lorlatinib, a third-generation ALK tyrosine kinase inhibitor, improved outcomes compared with crizotinib in patients with previously untreated ALK-positive advanced NSCLC in the phase 3 CROWN study. Here, we investigated response correlates using plasma circulating tumor DNA (ctDNA) and tumor tissue profiling. METHODS ALK fusions and ALK with or without TP53 mutations were assessed by next-generation sequencing. End points included objective response rate (ORR), duration of response, and progression-free survival (PFS) by blinded independent central review on the basis of EML4::ALK variants and ALK with or without TP53 or other mutation status. RESULTS ALK fusions were detected in the ctDNA of 62 patients in the lorlatinib arm and 64 patients in the crizotinib arm. ORRs were numerically higher with lorlatinib versus crizotinib for EML4::ALK variant 1 (v1; 80.0% versus 50.0%) and variant 2 (v2; 85.7% versus 50.0%) but were similar between the arms for variant 3 (v3; 72.2% versus 73.9%). Median PFS in the lorlatinib arm was not reached for EML4::ALK v1 and v2 and was 33.3 months for v3; in the crizotinib arm, median PFS was 7.4 months, not reached, and 5.5 months, respectively. ORRs and PFS were improved with lorlatinib versus crizotinib regardless of TP53 mutation status and in patients harboring preexisting bypass pathway resistance alterations. In the lorlatinib arm, PFS was lower in patients who had a co-occurring TP53 mutation. Results from ctDNA analysis were similar to those observed with tumor tissue samples. CONCLUSIONS Patients with untreated ALK-positive advanced NSCLC derived greater clinical benefits, with higher ORRs and potentially longer PFS, when treated with lorlatinib compared with crizotinib, independent of EML4::ALK variant or ALK mutations, TP53 mutations, or bypass resistance alterations.
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Affiliation(s)
- Alessandra Bearz
- Division of Medical Oncology, CRO National Cancer Institute of Aviano, Aviano, Italy
| | | | - Jacek Jassem
- Department of Oncology and Radiotherapy, Medical University of Gdańsk, Gdańsk, Poland
| | - Sang-We Kim
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - Gee-Chen Chang
- School of Medicine and Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan; Division of Pulmonary Medicine, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung, Taiwan; Institute of Biomedical Sciences, National Chung Hsing University, Taichung, Taiwan
| | - Alice T Shaw
- Center for Thoracic Cancers, Massachusetts General Hospital, Boston, Massachusetts
| | | | - Elisa Dall'O'
- Oncology Research and Development, Pfizer, Milan, Italy
| | - Anna Polli
- Oncology Research and Development, Pfizer, Milan, Italy
| | - Holger Thurm
- Oncology Research and Development, Pfizer, La Jolla, California
| | - Gerard Zalcman
- Thoracic Oncology, Hospital Bichat-Claude Bernard, Paris, France
| | | | - Konstantin Penkov
- Private Medical Institution, Euromedservice, St. Petersburg, Russian Federation
| | - Hidetoshi Hayashi
- Department of Medical Oncology, Kindai University Faculty of Medicine, Osaka, Japan
| | - Benjamin J Solomon
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
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23
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Mamis K, Zhang R, Bozic I. Stochastic model for cell population dynamics quantifies homeostasis in colonic crypts and its disruption in early tumorigenesis. Proc Biol Sci 2023; 290:20231020. [PMID: 37848058 PMCID: PMC10581771 DOI: 10.1098/rspb.2023.1020] [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: 05/08/2023] [Accepted: 09/22/2023] [Indexed: 10/19/2023] Open
Abstract
The questions of how healthy colonic crypts maintain their size, and how homeostasis is disrupted by driver mutations, are central to understanding colorectal tumorigenesis. We propose a three-type stochastic branching process, which accounts for stem, transit-amplifying (TA) and fully differentiated (FD) cells, to model the dynamics of cell populations residing in colonic crypts. Our model is simple in its formulation, allowing us to estimate all but one of the model parameters from the literature. Fitting the single remaining parameter, we find that model results agree well with data from healthy human colonic crypts, capturing the considerable variance in population sizes observed experimentally. Importantly, our model predicts a steady-state population in healthy colonic crypts for relevant parameter values. We show that APC and KRAS mutations, the most significant early alterations leading to colorectal cancer, result in increased steady-state populations in mutated crypts, in agreement with experimental results. Finally, our model predicts a simple condition for unbounded growth of cells in a crypt, corresponding to colorectal malignancy. This is predicted to occur when the division rate of TA cells exceeds their differentiation rate, with implications for therapeutic cancer prevention strategies.
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Affiliation(s)
- Konstantinos Mamis
- Department of Applied Mathematics, University of Washington, Seattle, WA 98195, USA
| | - Ruibo Zhang
- Department of Applied Mathematics, University of Washington, Seattle, WA 98195, USA
| | - Ivana Bozic
- Department of Applied Mathematics, University of Washington, Seattle, WA 98195, USA
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Kisistók J, Christensen DS, Rasmussen MH, Duval L, Aggerholm-Pedersen N, Luczak AA, Sorensen BS, Jakobsen MR, Oellegaard TH, Birkbak NJ. Analysis of circulating tumor DNA during checkpoint inhibition in metastatic melanoma using a tumor-agnostic panel. Melanoma Res 2023; 33:364-374. [PMID: 37294123 PMCID: PMC10470440 DOI: 10.1097/cmr.0000000000000903] [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: 12/15/2022] [Accepted: 05/10/2023] [Indexed: 06/10/2023]
Abstract
Immunotherapy has revolutionized treatment of patients diagnosed with metastatic melanoma, where nearly half of patients receive clinical benefit. However, immunotherapy is also associated with immune-related adverse events, which may be severe and persistent. It is therefore important to identify patients that do not benefit from therapy early. Currently, regularly scheduled CT scans are used to investigate size changes in target lesions to evaluate progression and therapy response. This study aims to explore if panel-based analysis of circulating tumor DNA (ctDNA) taken at 3-week intervals may provide a window into the growing cancer, can be used to identify nonresponding patients early, and determine genomic alterations associated with acquired resistance to checkpoint immunotherapy without analysis of tumor tissue biopsies. We designed a gene panel for ctDNA analysis and sequenced 4-6 serial plasma samples from 24 patients with unresectable stage III or IV melanoma and treated with first-line checkpoint inhibitors enrolled at the Department of Oncology at Aarhus University Hospital, Denmark. TERT was the most mutated gene found in ctDNA and associated with a poor prognosis. We detected more ctDNA in patients with high metastatic load, which indicates that more aggressive tumors release more ctDNA into the bloodstream. Although we did not find evidence of specific mutations associated with acquired resistance, we did demonstrate in this limited cohort of 24 patients that untargeted, panel-based ctDNA analysis has the potential to be used as a minimally invasive tool in clinical practice to identify patients where the benefits of immunotherapy outweigh the drawbacks.
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Affiliation(s)
- Judit Kisistók
- Department of Molecular Medicine, Aarhus University Hospital
- Department of Clinical Medicine, Aarhus University
- Bioinformatics Research Center, Aarhus University
| | - Ditte Sigaard Christensen
- Department of Molecular Medicine, Aarhus University Hospital
- Department of Clinical Medicine, Aarhus University
- Department of Oncology, Aarhus University Hospital, Aarhus
| | - Mads Heilskov Rasmussen
- Department of Molecular Medicine, Aarhus University Hospital
- Department of Clinical Medicine, Aarhus University
| | - Lone Duval
- Department of Oncology, Goedstrup Hospital, Herning
| | | | | | | | | | - Trine Heide Oellegaard
- Department of Clinical Medicine, Aarhus University
- Department of Oncology, Goedstrup Hospital, Herning
| | - Nicolai Juul Birkbak
- Department of Molecular Medicine, Aarhus University Hospital
- Department of Clinical Medicine, Aarhus University
- Bioinformatics Research Center, Aarhus University
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Xu K, Yu AR, Pan SB, He J. Diagnostic value of methylated branched chain amino acid transaminase 1/IKAROS family zinc finger 1 for colorectal cancer. World J Gastroenterol 2023; 29:5240-5253. [PMID: 37901447 PMCID: PMC10600955 DOI: 10.3748/wjg.v29.i36.5240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 09/01/2023] [Accepted: 09/07/2023] [Indexed: 09/20/2023] Open
Abstract
BACKGROUND The diagnostic value of combined methylated branched chain amino acid transaminase 1 (BCAT1)/IKAROS family zinc finger 1 (IKZF1) in plasma for colorectal cancer (CRC) has been explored since 2015. Recently, several related studies have published their results and showed its diagnostic efficacy. AIM To analyze the diagnostic value of methylated BCAT1/IKZF1 in plasma for screening and postoperative follow-up of CRC. METHODS The candidate studies were identified by searching the PubMed, Embase, Cochrane Library, CNKI, and Wanfang databases from May 31, 2003 to June 1, 2023. Sensitivity, specificity, and diagnostic accuracy were calculated by merging ratios or means. RESULTS Twelve eligible studies were included in the analysis, involving 6561 participants. The sensitivity of methylated BCAT1/IKZF1 in plasma for CRC diagnosis was 60% [95% confidence interval (CI) 53-67] and specificity was 92% (95%CI: 90-94). The positive and negative likelihood ratios were 8.0 (95%CI: 5.8-11.0) and 0.43 (95%CI: 0.36-0.52), respectively. Diagnostic odds ratio was 19 (95%CI: 11-30) and area under the curve was 0.88 (95%CI: 0.85-0.91). The sensitivity and specificity for CRC screening were 64% (95%CI: 59-69) and 92% (95%CI: 91-93), respectively. The sensitivity and specificity for recurrence detection during follow-up were 54% (95%CI: 42-67) and 93% (95%CI: 88-96), respectively. CONCLUSION The detection of methylated BCAT1/IKZF1 in plasma, as a non-invasive detection method of circulating tumor DNA, has potential CRC diagnosis, but the clinical application prospect needs to be further explored.
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Affiliation(s)
- Ke Xu
- Clinical Medical College, Chengdu Medical College, Chengdu 610500, Sichuan Province, China
- Department of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu 610500, Sichuan Province, China
| | - Ai-Ru Yu
- Clinical Medical College, Chengdu Medical College, Chengdu 610500, Sichuan Province, China
- Department of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu 610500, Sichuan Province, China
| | - Shen-Bin Pan
- Clinical Medical College, Chengdu Medical College, Chengdu 610500, Sichuan Province, China
- Department of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu 610500, Sichuan Province, China
| | - Jie He
- Clinical Medical College, Chengdu Medical College, Chengdu 610500, Sichuan Province, China
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu 610500, Sichuan Province, China
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Salari K, Sundi D, Lee JJ, Wu S, Wu CL, DiFiore G, Yan QR, Pienkny A, Lee CK, Oberlin D, Barme G, Piser J, Kahn R, Collins E, Phillips KG, Caruso VM, Goudarzi M, Garcia-Ransom M, Lentz PS, Evans-Holm ME, MacBride AR, Fischer DS, Haddadzadeh IJ, Mazzarella BC, Gray JW, Koppie TM, Bicocca VT, Levin TG, Lotan Y, Feldman AS. Development and Multicenter Case-Control Validation of Urinary Comprehensive Genomic Profiling for Urothelial Carcinoma Diagnosis, Surveillance, and Risk-Prediction. Clin Cancer Res 2023; 29:3668-3680. [PMID: 37439796 PMCID: PMC10502470 DOI: 10.1158/1078-0432.ccr-23-0570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 04/25/2023] [Accepted: 07/11/2023] [Indexed: 07/14/2023]
Abstract
PURPOSE Urinary comprehensive genomic profiling (uCGP) uses next-generation sequencing to identify mutations associated with urothelial carcinoma and has the potential to improve patient outcomes by noninvasively diagnosing disease, predicting grade and stage, and estimating recurrence risk. EXPERIMENTAL DESIGN This is a multicenter case-control study using banked urine specimens collected from patients undergoing initial diagnosis/hematuria workup or urothelial carcinoma surveillance. A total of 581 samples were analyzed by uCGP: 333 for disease classification and grading algorithm development, and 248 for blinded validation. uCGP testing was done using the UroAmp platform, which identifies five classes of mutation: single-nucleotide variants, copy-number variants, small insertion-deletions, copy-neutral loss of heterozygosity, and aneuploidy. UroAmp algorithms predicting urothelial carcinoma tumor presence, grade, and recurrence risk were compared with cytology, cystoscopy, and pathology. RESULTS uCGP algorithms had a validation sensitivity/specificity of 95%/90% for initial cancer diagnosis in patients with hematuria and demonstrated a negative predictive value (NPV) of 99%. A positive diagnostic likelihood ratio (DLR) of 9.2 and a negative DLR of 0.05 demonstrate the ability to risk-stratify patients presenting with hematuria. In surveillance patients, binary urothelial carcinoma classification demonstrated an NPV of 91%. uCGP recurrence-risk prediction significantly prognosticated future recurrence (hazard ratio, 6.2), whereas clinical risk factors did not. uCGP demonstrated positive predictive value (PPV) comparable with cytology (45% vs. 42%) with much higher sensitivity (79% vs. 25%). Finally, molecular grade predictions had a PPV of 88% and a specificity of 95%. CONCLUSIONS uCGP enables noninvasive, accurate urothelial carcinoma diagnosis and risk stratification in both hematuria and urothelial carcinoma surveillance patients.
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Affiliation(s)
- Keyan Salari
- Department of Urology, Massachusetts General Hospital, Boston, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Debasish Sundi
- Department of Urology, The Ohio State University Comprehensive Cancer Center & Pelotonia Institute for Immuno-Oncology, Columbus, Ohio
| | - Jason J. Lee
- Department of Urology, Massachusetts General Hospital, Boston, Massachusetts
| | - Shulin Wu
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts
| | - Chin-Lee Wu
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts
| | - Gabrielle DiFiore
- Department of Urology, The Ohio State University Comprehensive Cancer Center & Pelotonia Institute for Immuno-Oncology, Columbus, Ohio
| | - Q. Robert Yan
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Andrew Pienkny
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Chi K. Lee
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Daniel Oberlin
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Greg Barme
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Joel Piser
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Robert Kahn
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Edward Collins
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | | | | | | | | | | | | | | | | | | | | | - Joe W. Gray
- Oregon Health & Science University, Portland, Oregon
| | - Theresa M. Koppie
- Oregon Health & Science University, Portland, Oregon
- Willamette Urology, Salem, Oregon
| | | | | | - Yair Lotan
- Department of Urology, University of Texas Southwestern Medical Center Dallas, Dallas, Texas
| | - Adam S. Feldman
- Department of Urology, Massachusetts General Hospital, Boston, Massachusetts
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27
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Hoerres D, Dai Q, Elmore S, Sheth S, Gupta GP, Kumar S, Gulley ML. Calibration of cell-free DNA measurements by next-generation sequencing. Am J Clin Pathol 2023; 160:314-321. [PMID: 37244060 PMCID: PMC10472744 DOI: 10.1093/ajcp/aqad055] [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: 02/08/2023] [Accepted: 04/17/2023] [Indexed: 05/29/2023] Open
Abstract
OBJECTIVES Accurate monitoring of disease burden depends on accurate disease marker quantification. Although next-generation sequencing (NGS) is a promising technology for noninvasive monitoring, plasma cell-free DNA levels are often reported in misleading units that are confounded by non-disease-related factors. We proposed a novel strategy for calibrating NGS assays using spiked normalizers to improve precision and to promote standardization and harmonization of analyte concentrations. METHODS In this study, we refined our NGS protocol to calculate absolute analyte concentrations to (1) adjust for assay efficiency, as judged by recovery of spiked synthetic normalizer DNAs, and (2) calibrate NGS values against droplet digital polymerase chain reaction (ddPCR). As a model target, we chose the Epstein-Barr virus (EBV) genome. In patient (n = 12) and mock (n = 12) plasmas, NGS and 2 EBV ddPCR assays were used to report EBV load in copies per mL of plasma. RESULTS Next-generation sequencing was equally sensitive to ddPCR, with improved linearity when NGS values were normalized for spiked DNA read counts (R2 = 0.95 for normalized vs 0.91 for raw read concentrations). Linearity permitted NGS calibration to each ddPCR assay, achieving equivalent concentrations (copies/mL). CONCLUSIONS Our novel strategy for calibrating NGS assays suggests potential for a universal reference material to overcome biological and preanalytical variables hindering traditional NGS strategies for quantifying disease burden.
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Affiliation(s)
- Derek Hoerres
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, US
| | - Qunsheng Dai
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, US
- Lineberger Comprehensive Cancer Center, Chapel Hill, NC, US
| | - Sandra Elmore
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, US
- Lineberger Comprehensive Cancer Center, Chapel Hill, NC, US
| | - Siddharth Sheth
- Lineberger Comprehensive Cancer Center, Chapel Hill, NC, US
- Division of Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC, US
| | - Gaorav P Gupta
- Lineberger Comprehensive Cancer Center, Chapel Hill, NC, US
- Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC, US
| | - Sunil Kumar
- Lineberger Comprehensive Cancer Center, Chapel Hill, NC, US
- Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC, US
| | - Margaret L Gulley
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, US
- Lineberger Comprehensive Cancer Center, Chapel Hill, NC, US
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Gupta S, Westacott MJ, Ayers DG, Weiss SJ, Whitley P, Mueller C, Weaver DC, Schneider DJ, Karimpour-Fard A, Hunter LE, Drolet DW, Janjic N. Plasma proteome of growing tumors. Sci Rep 2023; 13:12195. [PMID: 37500700 PMCID: PMC10374562 DOI: 10.1038/s41598-023-38079-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 07/03/2023] [Indexed: 07/29/2023] Open
Abstract
Early detection of cancer is vital for the best chance of successful treatment, but half of all cancers are diagnosed at an advanced stage. A simple and reliable blood screening test applied routinely would therefore address a major unmet medical need. To gain insight into the value of protein biomarkers in early detection and stratification of cancer we determined the time course of changes in the plasma proteome of mice carrying transplanted human lung, breast, colon, or ovarian tumors. For protein measurements we used an aptamer-based assay which simultaneously measures ~ 5000 proteins. Along with tumor lineage-specific biomarkers, we also found 15 markers shared among all cancer types that included the energy metabolism enzymes glyceraldehyde-3-phosphate dehydrogenase, glucose-6-phophate isomerase and dihydrolipoyl dehydrogenase as well as several important biomarkers for maintaining protein, lipid, nucleotide, or carbohydrate balance such as tryptophanyl t-RNA synthetase and nucleoside diphosphate kinase. Using significantly altered proteins in the tumor bearing mice, we developed models to stratify tumor types and to estimate the minimum detectable tumor volume. Finally, we identified significantly enriched common and unique biological pathways among the eight tumor cell lines tested.
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Affiliation(s)
- Shashi Gupta
- SomaLogic, Inc., 2945 Wilderness Place, Boulder, CO, 80301, USA
| | | | - Deborah G Ayers
- SomaLogic, Inc., 2945 Wilderness Place, Boulder, CO, 80301, USA
| | - Sophie J Weiss
- SomaLogic, Inc., 2945 Wilderness Place, Boulder, CO, 80301, USA
| | - Penn Whitley
- Boulder BioConsulting, Inc., 325 S 68th St., Boulder, CO, 80303, USA
| | | | - Daniel C Weaver
- Boulder BioConsulting, Inc., 325 S 68th St., Boulder, CO, 80303, USA
| | | | - Anis Karimpour-Fard
- University of Colorado School of Medicine, Mailstop 8303, Aurora, CO, 80045, USA
| | - Lawrence E Hunter
- University of Colorado School of Medicine, Mailstop 8303, Aurora, CO, 80045, USA
| | - Daniel W Drolet
- SomaLogic, Inc., 2945 Wilderness Place, Boulder, CO, 80301, USA
| | - Nebojsa Janjic
- SomaLogic, Inc., 2945 Wilderness Place, Boulder, CO, 80301, USA.
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Chen K, Kang G, Zhang Z, Lizaso A, Beck S, Lyskjær I, Chervova O, Li B, Shen H, Wang C, Li B, Zhao H, Li X, Yang F, Kanu N, Wang J. Individualized dynamic methylation-based analysis of cell-free DNA in postoperative monitoring of lung cancer. BMC Med 2023; 21:255. [PMID: 37452374 PMCID: PMC10349423 DOI: 10.1186/s12916-023-02954-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 06/20/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND The feasibility of DNA methylation-based assays in detecting minimal residual disease (MRD) and postoperative monitoring remains unestablished. We aim to investigate the dynamic characteristics of cancer-related methylation signals and the feasibility of methylation-based MRD detection in surgical lung cancer patients. METHODS Matched tumor, tumor-adjacent tissues, and longitudinal blood samples from a cohort (MEDAL) were analyzed by ultra-deep targeted sequencing and bisulfite sequencing. A tumor-informed methylation-based MRD (timMRD) was employed to evaluate the methylation status of each blood sample. Survival analysis was performed in the MEDAL cohort (n = 195) and validated in an independent cohort (DYNAMIC, n = 36). RESULTS Tumor-informed methylation status enabled an accurate recurrence risk assessment better than the tumor-naïve methylation approach. Baseline timMRD-scores were positively correlated with tumor burden, invasiveness, and the existence and abundance of somatic mutations. Patients with higher timMRD-scores at postoperative time-points demonstrated significantly shorter disease-free survival in the MEDAL cohort (HR: 3.08, 95% CI: 1.48-6.42; P = 0.002) and the independent DYNAMIC cohort (HR: 2.80, 95% CI: 0.96-8.20; P = 0.041). Multivariable regression analysis identified postoperative timMRD-score as an independent prognostic factor for lung cancer. Compared to tumor-informed somatic mutation status, timMRD-scores yielded better performance in identifying the relapsed patients during postoperative follow-up, including subgroups with lower tumor burden like stage I, and was more accurate among relapsed patients with baseline ctDNA-negative status. Comparing to the average lead time of ctDNA mutation, timMRD-score yielded a negative predictive value of 97.2% at 120 days prior to relapse. CONCLUSIONS The dynamic methylation-based analysis of peripheral blood provides a promising strategy for postoperative cancer surveillance. TRIAL REGISTRATION This study (MEDAL, MEthylation based Dynamic Analysis for Lung cancer) was registered on ClinicalTrials.gov on 08/05/2018 (NCT03634826). https://clinicaltrials.gov/ct2/show/NCT03634826 .
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Affiliation(s)
- Kezhong Chen
- Thoracic Oncology Institute and Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China.
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, University College London, 72 Huntley St, London, WC1E 6DD, UK.
| | - Guannan Kang
- Thoracic Oncology Institute and Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
| | | | | | - Stephan Beck
- University College London Cancer Institute, University College London, 72 Huntley St, London, WC1E 6DD, UK
| | - Iben Lyskjær
- University College London Cancer Institute, University College London, 72 Huntley St, London, WC1E 6DD, UK
| | - Olga Chervova
- University College London Cancer Institute, University College London, 72 Huntley St, London, WC1E 6DD, UK
| | - Bingsi Li
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Haifeng Shen
- Thoracic Oncology Institute and Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
| | | | - Bing Li
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Heng Zhao
- Thoracic Oncology Institute and Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China
| | - Xi Li
- Burning Rock Biotech, Guangzhou, 510300, China
| | - Fan Yang
- Thoracic Oncology Institute and Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China.
| | - Nnennaya Kanu
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, University College London, 72 Huntley St, London, WC1E 6DD, UK.
| | - Jun Wang
- Thoracic Oncology Institute and Department of Thoracic Surgery, Peking University People's Hospital, Beijing, 100044, China.
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30
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Sasieni P, Smittenaar R, Hubbell E, Broggio J, Neal RD, Swanton C. Modelled mortality benefits of multi-cancer early detection screening in England. Br J Cancer 2023; 129:72-80. [PMID: 37185463 PMCID: PMC10307803 DOI: 10.1038/s41416-023-02243-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 03/14/2023] [Accepted: 03/17/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND Screening programmes utilising blood-based multi-cancer early detection (MCED) tests, which can detect a shared cancer signal from any site in the body with a single, low false-positive rate, could reduce cancer burden through early diagnosis. METHODS A natural history ('interception') model of cancer was previously used to characterise potential benefits of MCED screening (based on published performance of an MCED test). We built upon this using a two-population survival model to account for an increased risk of death from cfDNA-detectable cancers relative to cfDNA-non-detectable cancers. We developed another model allowing some cancers to metastasise directly from stage I, bypassing intermediate tumour stages. We used incidence and survival-by-stage data from the National Cancer Registration and Analysis Service in England to estimate longer-term benefits to a cohort screened between ages 50-79 years. RESULTS Estimated late-stage and mortality reductions were robust to a range of assumptions. With the least favourable dwell (sojourn) time and cfDNA status hazard ratio assumptions, we estimated, among 100,000 screened individuals, 67 (17%) fewer cancer deaths per year corresponding to 2029 fewer deaths in those screened between ages 50-79 years. CONCLUSION Realising the potential benefits of MCED tests could substantially reduce late-stage cancer diagnoses and mortality.
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Affiliation(s)
- Peter Sasieni
- Comprehensive Cancer Centre, King's College London, Guy's Campus, Great Maze Pond, London, SE1 1UL, UK.
| | | | | | - John Broggio
- NHS Digital, 7 and 8 Wellington Place, Leeds, West Yorkshire, LS1 4AP, UK
| | - Richard D Neal
- Department of Health and Community Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Charles Swanton
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, WC1E 6DD, UK
- Cancer Evolution and Genome Instability Laboratory, Francis Crick Institute, London, NW1 1AT, UK
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31
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Boutin M, Topham JT, Feilotter H, Kennecke HF, Couture F, Harb M, Kavan P, Berry S, Lim HJ, Goffin JR, Ahmad C, Lott A, Renouf DJ, Jonker DJ, Tu D, O’Callaghan CJ, Chen EX, Loree JM. Optimizing the number of variants tracked to follow disease burden with circulating tumor DNA assays in metastatic colorectal cancer. Ther Adv Med Oncol 2023; 15:17588359231183682. [PMID: 37389190 PMCID: PMC10302520 DOI: 10.1177/17588359231183682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 05/31/2023] [Indexed: 07/01/2023] Open
Abstract
Background The number of somatic mutations detectable in circulating tumor DNA (ctDNA) is highly heterogeneous in metastatic colorectal cancer (mCRC). The optimal number of mutations required to assess disease kinetics is relevant and remains poorly understood. Objectives To determine whether increasing panel breadth (the number of tracked variants in a ctDNA assay) would alter the sensitivity in detecting ctDNA in patients with mCRC. Design We used archival tissue sequencing to perform an in silico assessment of the optimal number of tracked mutations to detect and monitor disease kinetics in mCRC using sequencing data from the Canadian Cancer Trials Group CO.26 trial. Methods For each patient, 1, 2, 4, 8, 12, or 16 of the most clonal (highest variant allele frequency) somatic variants were selected from archival tissue-based whole-exome sequencing and assessed for the proportion of variants detected in matched ctDNA at baseline, week 8, and progression timepoints. Results Data from 110 patients were analyzed. Genes most frequently encountered among the top four highest VAF variants in archival tissue were TP53 (51.9% of patients), APC (43.3%), KRAS (42.3%), and SMAD4 (9.6%). While the frequency of detecting at least one tracked variant increased when expanding beyond variant pool sizes of 1 and 2 in baseline (p = 0.0030) and progression (p = 0.0030) ctDNA samples, we observed no significant benefit to increases in variant pool size past four variants in any of the ctDNA timepoints (p < 0.05). Conclusion While increasing panel breadth beyond two tracked variants improved variant re-detection in ctDNA samples from patients with treatment refractory mCRC, increases beyond four tracked variants yielded no significant improvement in variant re-detection.
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Affiliation(s)
- Mélina Boutin
- Division of Medical Oncology, BC Cancer, Vancouver, BC, Canada Centre Intégré de Cancérologie de la Montérégie, Université de Sherbrooke, QC, Canada
| | | | - Harriet Feilotter
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON, Canada
| | | | | | | | | | - Scott Berry
- Department of Oncology, Queen’s University, Kingston, ON, Canada
| | - Howard J. Lim
- Division of Medical Oncology, BC Cancer, Vancouver, BC, Canada
| | | | | | | | - Daniel J. Renouf
- Division of Medical Oncology, BC Cancer, Vancouver, BC, Canada Pancreas Center BC, Vancouver, BC, Canada
| | - Derek J. Jonker
- The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
| | - Dongsheng Tu
- Canadian Cancer Trials Group, Queen’s University, Kingston, ON, Canada
| | | | - Eric X. Chen
- Princess Margaret Cancer Centre, Toronto, ON, Canada
| | - Jonathan M. Loree
- Division of Medical Oncology, BC Cancer, 600 West 10th Avenue, Vancouver, BC V5Z 4E6, Canada
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Dy GK, Govindan R, Velcheti V, Falchook GS, Italiano A, Wolf J, Sacher AG, Takahashi T, Ramalingam SS, Dooms C, Kim DW, Addeo A, Desai J, Schuler M, Tomasini P, Hong DS, Lito P, Tran Q, Jones S, Anderson A, Hindoyan A, Snyder W, Skoulidis F, Li BT. Long-Term Outcomes and Molecular Correlates of Sotorasib Efficacy in Patients With Pretreated KRAS G12C-Mutated Non-Small-Cell Lung Cancer: 2-Year Analysis of CodeBreaK 100. J Clin Oncol 2023; 41:3311-3317. [PMID: 37098232 PMCID: PMC10414711 DOI: 10.1200/jco.22.02524] [Citation(s) in RCA: 38] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 02/16/2023] [Accepted: 03/03/2023] [Indexed: 04/27/2023] Open
Abstract
Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.In the longest follow-up, to our knowledge, for a KRASG12C inhibitor, we assessed the long-term efficacy, safety, and biomarkers of sotorasib in patients with KRAS G12C-mutated advanced non-small-cell lung cancer (NSCLC) from the CodeBreaK 100 clinical trial (ClinicalTrials.gov identifier: NCT03600883). This multicenter, single-group, open-label phase I/phase II trial enrolled 174 patients with KRAS G12C-mutated, locally advanced or metastatic NSCLC after progression on prior therapies. Patients (N = 174) received sotorasib 960 mg once daily with the primary end points for phase I of safety and tolerability and for phase II of objective response rate (ORR). Sotorasib produced an ORR of 41%, median duration of response of 12.3 months, progression-free survival (PFS) of 6.3 months, overall survival (OS) of 12.5 months, and 2-year OS rate of 33%. Long-term clinical benefit (PFS ≥ 12 months) was observed in 40 (23%) patients across PD-L1 expression levels, in a proportion of patients with somatic STK11 and/or KEAP1 alterations, and was associated with lower baseline circulating tumor DNA levels. Sotorasib was well tolerated, with few late-onset treatment-related toxicities, none of which led to treatment discontinuation. These results demonstrate the long-term benefit of sotorasib, including in subgroups with poor prognosis.
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Affiliation(s)
- Grace K. Dy
- Roswell Park Comprehensive Cancer Center, Buffalo, NY
| | - Ramaswamy Govindan
- Siteman Cancer Center, Washington University School of Medicine, St Louis, MO
| | | | | | | | - Jürgen Wolf
- Center for Integrated Oncology, University Hospital Cologne, Cologne, Germany
| | | | | | | | | | - Dong-Wan Kim
- Seoul National University College of Medicine and Seoul National University Hospital, Seoul, South Korea
| | - Alfredo Addeo
- Hopitaux Universitaires de Geneve, Geneve, Switzerland
| | - Jayesh Desai
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Martin Schuler
- West German Cancer Center, University Hospital Essen, Essen, Germany
| | - Pascale Tomasini
- Multidisciplinary Oncology and Therapeutic Innovations Department, Aix Marseille University, APHM, INSERM, NCRS, CRCM, Hôpital de la Timone, Marseille, France
| | - David S. Hong
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Piro Lito
- Memorial Sloan Kettering Cancer Center, Weill Cornell Medicine, New York, NY
| | | | | | | | | | | | | | - Bob T. Li
- Memorial Sloan Kettering Cancer Center, Weill Cornell Medicine, New York, NY
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Lin LH, Chang KW, Cheng HW, Liu CJ. Identification of Somatic Mutations in Plasma Cell-Free DNA from Patients with Metastatic Oral Squamous Cell Carcinoma. Int J Mol Sci 2023; 24:10408. [PMID: 37373553 DOI: 10.3390/ijms241210408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/01/2023] [Accepted: 06/15/2023] [Indexed: 06/29/2023] Open
Abstract
The accurate diagnosis and treatment of oral squamous cell carcinoma (OSCC) requires an understanding of its genomic alterations. Liquid biopsies, especially cell-free DNA (cfDNA) analysis, are a minimally invasive technique used for genomic profiling. We conducted comprehensive whole-exome sequencing (WES) of 50 paired OSCC cell-free plasma with whole blood samples using multiple mutation calling pipelines and filtering criteria. Integrative Genomics Viewer (IGV) was used to validate somatic mutations. Mutation burden and mutant genes were correlated to clinico-pathological parameters. The plasma mutation burden of cfDNA was significantly associated with clinical staging and distant metastasis status. The genes TTN, PLEC, SYNE1, and USH2A were most frequently mutated in OSCC, and known driver genes, including KMT2D, LRP1B, TRRAP, and FLNA, were also significantly and frequently mutated. Additionally, the novel mutated genes CCDC168, HMCN2, STARD9, and CRAMP1 were significantly and frequently present in patients with OSCC. The mutated genes most frequently found in patients with metastatic OSCC were RORC, SLC49A3, and NUMBL. Further analysis revealed that branched-chain amino acid (BCAA) catabolism, extracellular matrix-receptor interaction, and the hypoxia-related pathway were associated with OSCC prognosis. Choline metabolism in cancer, O-glycan biosynthesis, and protein processing in the endoplasmic reticulum pathway were associated with distant metastatic status. About 20% of tumors carried at least one aberrant event in BCAA catabolism signaling that could possibly be targeted by an approved therapeutic agent. We identified molecular-level OSCC that were correlated with etiology and prognosis while defining the landscape of major altered events of the OSCC plasma genome. These findings will be useful in the design of clinical trials for targeted therapies and the stratification of patients with OSCC according to therapeutic efficacy.
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Affiliation(s)
- Li-Han Lin
- Department of Medical Research, MacKay Memorial Hospital No. 92, Sec. 2, Chung San N. Rd., Taipei 10449, Taiwan
| | - Kuo-Wei Chang
- Institute of Oral Biology, School of Dentistry, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan
- Department of Stomatology, Taipei Veterans General Hospital, Taipei 11121, Taiwan
| | - Hui-Wen Cheng
- Department of Medical Research, MacKay Memorial Hospital No. 92, Sec. 2, Chung San N. Rd., Taipei 10449, Taiwan
| | - Chung-Ji Liu
- Department of Medical Research, MacKay Memorial Hospital No. 92, Sec. 2, Chung San N. Rd., Taipei 10449, Taiwan
- Institute of Oral Biology, School of Dentistry, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan
- Department of Oral and Maxillofacial Surgery, Taipei MacKay Memorial Hospital, Taipei 10449, Taiwan
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Magbanua MJM, Brown Swigart L, Ahmed Z, Sayaman RW, Renner D, Kalashnikova E, Hirst GL, Yau C, Wolf DM, Li W, Delson AL, Asare S, Liu MC, Albain K, Chien AJ, Forero-Torres A, Isaacs C, Nanda R, Tripathy D, Rodriguez A, Sethi H, Aleshin A, Rabinowitz M, Perlmutter J, Symmans WF, Yee D, Hylton NM, Esserman LJ, DeMichele AM, Rugo HS, van 't Veer LJ. Clinical significance and biology of circulating tumor DNA in high-risk early-stage HER2-negative breast cancer receiving neoadjuvant chemotherapy. Cancer Cell 2023; 41:1091-1102.e4. [PMID: 37146605 PMCID: PMC10330514 DOI: 10.1016/j.ccell.2023.04.008] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 01/30/2023] [Accepted: 04/12/2023] [Indexed: 05/07/2023]
Abstract
Circulating tumor DNA (ctDNA) analysis may improve early-stage breast cancer treatment via non-invasive tumor burden assessment. To investigate subtype-specific differences in the clinical significance and biology of ctDNA shedding, we perform serial personalized ctDNA analysis in hormone receptor (HR)-positive/HER2-negative breast cancer and triple-negative breast cancer (TNBC) patients receiving neoadjuvant chemotherapy (NAC) in the I-SPY2 trial. ctDNA positivity rates before, during, and after NAC are higher in TNBC than in HR-positive/HER2-negative breast cancer patients. Early clearance of ctDNA 3 weeks after treatment initiation predicts a favorable response to NAC in TNBC only. Whereas ctDNA positivity associates with reduced distant recurrence-free survival in both subtypes. Conversely, ctDNA negativity after NAC correlates with improved outcomes, even in patients with extensive residual cancer. Pretreatment tumor mRNA profiling reveals associations between ctDNA shedding and cell cycle and immune-associated signaling. On the basis of these findings, the I-SPY2 trial will prospectively test ctDNA for utility in redirecting therapy to improve response and prognosis.
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Affiliation(s)
| | | | - Ziad Ahmed
- University of California, San Francisco, San Francisco, CA 94143, USA
| | - Rosalyn W Sayaman
- University of California, San Francisco, San Francisco, CA 94143, USA
| | | | | | - Gillian L Hirst
- University of California, San Francisco, San Francisco, CA 94143, USA
| | - Christina Yau
- University of California, San Francisco, San Francisco, CA 94143, USA
| | - Denise M Wolf
- University of California, San Francisco, San Francisco, CA 94143, USA
| | - Wen Li
- University of California, San Francisco, San Francisco, CA 94143, USA
| | - Amy L Delson
- UCSF Breast Science Advocacy Core, San Francisco, CA 94143, USA
| | - Smita Asare
- Quantum Leap Healthcare Collaborative, San Francisco, CA 94118, USA
| | - Minetta C Liu
- Natera, Inc., Austin, TX 78753, USA; Mayo Clinic, Rochester, MN 55905, USA
| | - Kathy Albain
- Loyola University Chicago, Maywood, IL 60153, USA
| | - A Jo Chien
- University of California, San Francisco, San Francisco, CA 94143, USA
| | | | | | - Rita Nanda
- University of Chicago, Chicago, IL 60637, USA
| | - Debu Tripathy
- University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | | | | | | | | | - Jane Perlmutter
- UCSF Breast Science Advocacy Core, San Francisco, CA 94143, USA
| | - W Fraser Symmans
- University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Douglas Yee
- University of Minnesota, Minneapolis, MN 55455, USA
| | - Nola M Hylton
- University of California, San Francisco, San Francisco, CA 94143, USA
| | - Laura J Esserman
- University of California, San Francisco, San Francisco, CA 94143, USA
| | | | - Hope S Rugo
- University of California, San Francisco, San Francisco, CA 94143, USA
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Semenkovich NP, Szymanski JJ, Earland N, Chauhan PS, Pellini B, Chaudhuri AA. Genomic approaches to cancer and minimal residual disease detection using circulating tumor DNA. J Immunother Cancer 2023; 11:e006284. [PMID: 37349125 PMCID: PMC10314661 DOI: 10.1136/jitc-2022-006284] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/26/2023] [Indexed: 06/24/2023] Open
Abstract
Liquid biopsies using cell-free circulating tumor DNA (ctDNA) are being used frequently in both research and clinical settings. ctDNA can be used to identify actionable mutations to personalize systemic therapy, detect post-treatment minimal residual disease (MRD), and predict responses to immunotherapy. ctDNA can also be isolated from a range of different biofluids, with the possibility of detecting locoregional MRD with increased sensitivity if sampling more proximally than blood plasma. However, ctDNA detection remains challenging in early-stage and post-treatment MRD settings where ctDNA levels are minuscule giving a high risk for false negative results, which is balanced with the risk of false positive results from clonal hematopoiesis. To address these challenges, researchers have developed ever-more elegant approaches to lower the limit of detection (LOD) of ctDNA assays toward the part-per-million range and boost assay sensitivity and specificity by reducing sources of low-level technical and biological noise, and by harnessing specific genomic and epigenomic features of ctDNA. In this review, we highlight a range of modern assays for ctDNA analysis, including advancements made to improve the signal-to-noise ratio. We further highlight the challenge of detecting ultra-rare tumor-associated variants, overcoming which will improve the sensitivity of post-treatment MRD detection and open a new frontier of personalized adjuvant treatment decision-making.
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Affiliation(s)
- Nicholas P Semenkovich
- Division of Endocrinology, Metabolism, and Lipid Research, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jeffrey J Szymanski
- Division of Cancer Biology, Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Noah Earland
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Pradeep S Chauhan
- Division of Cancer Biology, Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Bruna Pellini
- Department of Thoracic Oncology, Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
- Department of Oncologic Sciences, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA
| | - Aadel A Chaudhuri
- Division of Cancer Biology, Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, Missouri, USA
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
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36
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Barker AD, Alba MM, Mallick P, Agus DB, Lee JSH. An Inflection Point in Cancer Protein Biomarkers: What Was and What's Next. Mol Cell Proteomics 2023:100569. [PMID: 37196763 PMCID: PMC10388583 DOI: 10.1016/j.mcpro.2023.100569] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 04/26/2023] [Accepted: 05/08/2023] [Indexed: 05/19/2023] Open
Abstract
Biomarkers remain the highest value proposition in cancer medicine today - especially protein biomarkers. Yet despite decades of evolving regulatory frameworks to facilitate the review of emerging technologies, biomarkers have been mostly about promise with very little to show for improvements in human health. Cancer is an emergent property of a complex system and deconvoluting the integrative and dynamic nature of the overall system through biomarkers is a daunting proposition. The last two decades have seen an explosion of multi-omics profiling and a range of advanced technologies for precision medicine, including the emergence of liquid biopsy, exciting advances in single cell analysis, artificial intelligence (machine and deep learning) for data analysis and many other advanced technologies that promise to transform biomarker discovery. Combining multiple omics modalities to acquire a more comprehensive landscape of the disease state, we are increasingly developing biomarkers to support therapy selection and patient monitoring. Furthering precision medicine, especially in oncology, necessitates moving away from the lens of reductionist thinking towards viewing and understanding that complex diseases are, in fact, complex adaptive systems. As such, we believe it is necessary to re-define biomarkers as representations of biological system states at different hierarchical levels of biological order. This definition could include traditional molecular, histologic, radiographic, or physiological characteristics, as well as emerging classes of digital markers and complex algorithms. To succeed in the future, we must move past purely observational individual studies and instead start building a mechanistic framework to enable integrative analysis of new studies within the context of prior studies. Identifying information in complex systems and applying theoretical constructs, such as information theory, to study cancer as a disease of dysregulated communication could prove to be "game changing" for the clinical outcome of cancer patients.
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Affiliation(s)
- Anna D Barker
- Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA; Complex Adaptive Systems Initiative and School of Life Sciences, Arizona State University, Tempe, Arizona
| | - Mario M Alba
- Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA
| | - Parag Mallick
- Canary Center at Stanford for Cancer Early Detection, Stanford University, Stanford, CA; Department of Radiology, Stanford University, Stanford, CA
| | - David B Agus
- Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA; Keck School of Medicine, University of Southern California, Los Angeles, CA; Viterbi School of Engineering, University of Southern California, Los Angeles, CA
| | - Jerry S H Lee
- Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA; Keck School of Medicine, University of Southern California, Los Angeles, CA; Viterbi School of Engineering, University of Southern California, Los Angeles, CA
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37
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Guan SW, Lin Q, Yu HB. Intratumour microbiome of pancreatic cancer. World J Gastrointest Oncol 2023; 15:713-730. [PMID: 37275446 PMCID: PMC10237023 DOI: 10.4251/wjgo.v15.i5.713] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/26/2023] [Accepted: 04/04/2023] [Indexed: 05/12/2023] Open
Abstract
Pancreatic cancer is a high mortality malignancy with almost equal mortality and morbidity rates. Both normal and tumour tissues of the pancreas were previously considered sterile. In recent years, with the development of technologies for high-throughput sequencing, a variety of studies have revealed that pancreatic cancer tissues contain small amounts of bacteria and fungi. The intratumour microbiome is being revealed as an influential contributor to carcinogenesis. The intratumour microbiome has been identified as a crucial factor for pancreatic cancer progression, diagnosis, and treatment, chemotherapy resistance, and immune response. A better understanding of the biology of the intratumour microbiome of pancreatic cancer contributes to the establishment of better early cancer screening and treatment strategies. This review focuses on the possible origins of the intratumour microbiome in pancreatic cancer, the intratumour localization, the interaction with the tumour microenvironment, and strategies for improving the outcome of pancreatic cancer treatment. Thus, this review offers new perspectives for improving the prognosis of pancreatic cancer.
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Affiliation(s)
- Shi-Wei Guan
- Department of Surgery, Wenzhou Central Hospital, The Dingli Clinical Institute of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China
| | - Quan Lin
- Department of Surgery, Wenzhou Central Hospital, The Dingli Clinical Institute of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China
| | - Hai-Bo Yu
- Department of Surgery, Wenzhou Central Hospital, The Dingli Clinical Institute of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China
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38
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Li Y, Jiang G, Wu W, Yang H, Jin Y, Wu M, Liu W, Yang A, Chervova O, Zhang S, Zheng L, Zhang X, Du F, Kanu N, Wu L, Yang F, Wang J, Chen K. Multi-omics integrated circulating cell-free DNA genomic signatures enhanced the diagnostic performance of early-stage lung cancer and postoperative minimal residual disease. EBioMedicine 2023; 91:104553. [PMID: 37027928 PMCID: PMC10102814 DOI: 10.1016/j.ebiom.2023.104553] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 03/17/2023] [Accepted: 03/19/2023] [Indexed: 04/08/2023] Open
Abstract
BACKGROUND Liquid biopsy is a promising non-invasive alternative for cancer screening and minimal residual disease (MRD) detection, although there are some concerns regarding its clinical applications. We aimed to develop an accurate detection platform based on liquid biopsy for both cancer screening and MRD detection in patients with lung cancer (LC), which is also applicable to clinical use. METHODS We applied a modified whole-genome sequencing (WGS) -based High-performance Infrastructure For MultIomics (HIFI) method for LC screening and postoperative MRD detection by combining the hyper-co-methylated read approach and the circulating single-molecule amplification and resequencing technology (cSMART2.0). FINDINGS For early screening of LC, the LC score model was constructed using the support vector machine, which showed sensitivity (51.8%) at high specificity (96.3%) and achieved an AUC of 0.912 in the validation set prospectively enrolled from multiple centers. The screening model achieved detection efficiency with an AUC of 0.906 in patients with lung adenocarcinoma and outperformed other clinical models in solid nodule cohort. When applied the HIFI model to real social population, a negative predictive value (NPV) of 99.92% was achieved in Chinese population. Additionally, the MRD detection rate improved significantly by combining results from WGS and cSMART2.0, with sensitivity of 73.7% at specificity of 97.3%. INTERPRETATION In conclusion, the HIFI method is promising for diagnosis and postoperative monitoring of LC. FUNDING This study was supported by CAMS Innovation Fund for Medical Sciences, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, Beijing Natural Science Foundation and Peking University People's Hospital.
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Silva-Aravena F, Núñez Delafuente H, Gutiérrez-Bahamondes JH, Morales J. A Hybrid Algorithm of ML and XAI to Prevent Breast Cancer: A Strategy to Support Decision Making. Cancers (Basel) 2023; 15:cancers15092443. [PMID: 37173910 PMCID: PMC10177162 DOI: 10.3390/cancers15092443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/15/2023] [Accepted: 04/18/2023] [Indexed: 05/15/2023] Open
Abstract
Worldwide, the coronavirus has intensified the management problems of health services, significantly harming patients. Some of the most affected processes have been cancer patients' prevention, diagnosis, and treatment. Breast cancer is the most affected, with more than 20 million cases and at least 10 million deaths by 2020. Various studies have been carried out to support the management of this disease globally. This paper presents a decision support strategy for health teams based on machine learning (ML) tools and explainability algorithms (XAI). The main methodological contributions are: first, the evaluation of different ML algorithms that allow classifying patients with and without cancer from the available dataset; and second, an ML methodology mixed with an XAI algorithm, which makes it possible to predict the disease and interpret the variables and how they affect the health of patients. The results show that first, the XGBoost Algorithm has a better predictive capacity, with an accuracy of 0.813 for the train data and 0.81 for the test data; and second, with the SHAP algorithm, it is possible to know the relevant variables and their level of significance in the prediction, and to quantify the impact on the clinical condition of the patients, which will allow health teams to offer early and personalized alerts for each patient.
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Affiliation(s)
- Fabián Silva-Aravena
- Facultad de Ciencias Sociales y Económicas, Universidad Católica del Maule, Avenida San Miguel 3605, Talca 3460000, Chile
| | - Hugo Núñez Delafuente
- Doctorado en Sistemas de Ingeniería, Facultad de Ingeniería, Universidad de Talca, Camino Los Niches Km 1, Curicó 3340000, Chile
| | - Jimmy H Gutiérrez-Bahamondes
- Doctorado en Sistemas de Ingeniería, Facultad de Ingeniería, Universidad de Talca, Camino Los Niches Km 1, Curicó 3340000, Chile
| | - Jenny Morales
- Facultad de Ciencias Sociales y Económicas, Universidad Católica del Maule, Avenida San Miguel 3605, Talca 3460000, Chile
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Zhang S, Zhang J, Hu X, Yin S, Yuan Y, Xia L, Cao F, Yan X, Yan Z, Mao Q, Xie D, Liu Y. Noninvasive detection of brain gliomas using plasma cell-free DNA 5-hydroxymethylcytosine sequencing. Int J Cancer 2023; 152:1707-1718. [PMID: 36522844 DOI: 10.1002/ijc.34401] [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: 07/08/2022] [Revised: 10/16/2022] [Accepted: 11/14/2022] [Indexed: 12/23/2022]
Abstract
Liquid biopsy techniques based on deep sequencing of plasma cell-free DNA (cfDNA) could detect the low-frequency somatic mutations and provide an accurate diagnosis for many cancers. However, for brain gliomas, reliable performance of these techniques currently requires obtaining cfDNA from patients' cerebral spinal fluid, which is cumbersome and risky. Here we report a liquid biopsy method based on sequencing of plasma cfDNA fragments carrying 5-hydroxymethylcytosine (5hmC) using selective chemical labeling (hMe-Seal). We first constructed a dataset including 180 glioma patients and 229 non-glioma controls. We found marked concordance between cfDNA hydroxymethylome and the aberrant transcriptome of the underlying gliomas. Functional analysis also revealed overrepresentation of the differentially hydroxymethylated genes (DhmGs) in oncogenic and neural pathways. After splitting our dataset into training and test cohort, we showed that a penalized logistic model constructed with training set DhmGs could distinguish glioma patients from healthy controls in both our test set (AUC = 0.962) and an independent dataset (AUC = 0.930) consisting of 111 gliomas and 111 controls. Additionally, the DhmGs between gliomas with mutant and wild-type isocitrate dehydrogenase (IDH) could be used to train a cfDNA predictor of the IDH mutation status of the underlying tumor (AUC = 0.816), and patients with predicted IDH mutant gliomas had significantly better outcome (P = .01). These results indicate that our plasma cfDNA 5hmC sequencing method could obtain glioma-specific signals, which may be used to noninvasively detect these patients and predict the aggressiveness of their tumors.
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Affiliation(s)
- Shuxin Zhang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
- Department of Head and Neck Surgery, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jun Zhang
- Frontier Science Centre for Disease Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Xinlei Hu
- Frontier Science Centre for Disease Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Senlin Yin
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Yunbo Yuan
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Lin Xia
- Frontier Science Centre for Disease Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Feng Cao
- Frontier Science Centre for Disease Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Xiaoqin Yan
- Frontier Science Centre for Disease Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Ziyue Yan
- Frontier Science Centre for Disease Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Qing Mao
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Dan Xie
- Frontier Science Centre for Disease Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Yanhui Liu
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
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41
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Moser T, Kühberger S, Lazzeri I, Vlachos G, Heitzer E. Bridging biological cfDNA features and machine learning approaches. Trends Genet 2023; 39:285-307. [PMID: 36792446 DOI: 10.1016/j.tig.2023.01.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 01/10/2023] [Accepted: 01/19/2023] [Indexed: 02/15/2023]
Abstract
Liquid biopsies (LBs), particularly using circulating tumor DNA (ctDNA), are expected to revolutionize precision oncology and blood-based cancer screening. Recent technological improvements, in combination with the ever-growing understanding of cell-free DNA (cfDNA) biology, are enabling the detection of tumor-specific changes with extremely high resolution and new analysis concepts beyond genetic alterations, including methylomics, fragmentomics, and nucleosomics. The interrogation of a large number of markers and the high complexity of data render traditional correlation methods insufficient. In this regard, machine learning (ML) algorithms are increasingly being used to decipher disease- and tissue-specific signals from cfDNA. Here, we review recent insights into biological ctDNA features and how these are incorporated into sophisticated ML applications.
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Affiliation(s)
- Tina Moser
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Stefan Kühberger
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Isaac Lazzeri
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Georgios Vlachos
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria
| | - Ellen Heitzer
- Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Neue Stiftingtalstrasse 6, 8010 Graz, Austria; Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Medical University of Graz, Graz, Austria.
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Rhrissorrakrai K, Utro F, Levovitz C, Parida L. Lesion Shedding Model: unraveling site-specific contributions to ctDNA. Brief Bioinform 2023; 24:7068948. [PMID: 36869848 PMCID: PMC10025438 DOI: 10.1093/bib/bbad059] [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: 10/19/2022] [Revised: 01/09/2023] [Accepted: 02/01/2023] [Indexed: 03/05/2023] Open
Abstract
Sampling circulating tumor DNA (ctDNA) using liquid biopsies offers clinically important benefits for monitoring cancer progression. A single ctDNA sample represents a mixture of shed tumor DNA from all known and unknown lesions within a patient. Although shedding levels have been suggested to hold the key to identifying targetable lesions and uncovering treatment resistance mechanisms, the amount of DNA shed by any one specific lesion is still not well characterized. We designed the Lesion Shedding Model (LSM) to order lesions from the strongest to the poorest shedding for a given patient. By characterizing the lesion-specific ctDNA shedding levels, we can better understand the mechanisms of shedding and more accurately interpret ctDNA assays to improve their clinical impact. We verified the accuracy of the LSM under controlled conditions using a simulation approach as well as testing the model on three cancer patients. The LSM obtained an accurate partial order of the lesions according to their assigned shedding levels in simulations and its accuracy in identifying the top shedding lesion was not significantly impacted by number of lesions. Applying LSM to three cancer patients, we found that indeed there were lesions that consistently shed more than others into the patients' blood. In two of the patients, the top shedding lesion was one of the only clinically progressing lesions at the time of biopsy suggesting a connection between high ctDNA shedding and clinical progression. The LSM provides a much needed framework with which to understand ctDNA shedding and to accelerate discovery of ctDNA biomarkers. The LSM source code has been available in the IBM BioMedSciAI Github (https://github.com/BiomedSciAI/Geno4SD).
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Affiliation(s)
| | - Filippo Utro
- IBM Research, IBM, 1101 Kitchawan Road, 10598, NY, USA
| | | | - Laxmi Parida
- IBM Research, IBM, 1101 Kitchawan Road, 10598, NY, USA
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Udagawa S, Ooki A, Shinozaki E, Fukuda K, Yamaguchi K, Osumi H. Circulating Tumor DNA: The Dawn of a New Era in the Optimization of Chemotherapeutic Strategies for Metastatic Colo-Rectal Cancer Focusing on RAS Mutation. Cancers (Basel) 2023; 15:cancers15051473. [PMID: 36900264 PMCID: PMC10001242 DOI: 10.3390/cancers15051473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 02/10/2023] [Accepted: 02/22/2023] [Indexed: 03/02/2023] Open
Abstract
Genotyping of tumor tissues to assess RAS and BRAF V600E mutations enables us to select optimal molecularly targeted therapies when considering treatment strategies for patients with metastatic colorectal cancer. Tissue-based genetic testing is limited by the difficulty of performing repeated tests, due to the invasive nature of tissue biopsy, and by tumor heterogeneity, which can limit the usefulness of the information it yields. Liquid biopsy, represented by circulating tumor DNA (ctDNA), has attracted attention as a novel method for detecting genetic alterations. Liquid biopsies are more convenient and much less invasive than tissue biopsies and are useful for obtaining comprehensive genomic information on primary and metastatic tumors. Assessing ctDNA can help track genomic evolution and the status of alterations in genes such as RAS, which are sometimes altered following chemotherapy. In this review, we discuss the potential clinical applications of ctDNA, summarize clinical trials focusing on RAS, and present the future prospects of ctDNA analysis that could change daily clinical practice.
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Affiliation(s)
| | | | | | | | | | - Hiroki Osumi
- Correspondence: ; Tel.: +81-3-3520-0111 or +81-3-3570-0515
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44
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Modeling tumour heterogeneity of PD-L1 expression in tumour progression and adaptive therapy. J Math Biol 2023; 86:38. [PMID: 36695961 DOI: 10.1007/s00285-023-01872-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 12/06/2022] [Accepted: 01/09/2023] [Indexed: 01/26/2023]
Abstract
Although PD-1/PD-L1 inhibitors show potent and durable anti-tumour effects in some refractory tumours, the response rate in overall patients is unsatisfactory, which in part due to the inherent heterogeneity of PD-L1. In order to establish an approach for predicting and estimating the dynamic alternation of PD-L1 heterogeneity during cancer progression and treatment, this study establishes a comprehensive modelling and computational framework based on a mathematical model of cancer cell evolution in the tumour-immune microenvironment, and in combination with epigenetic data and overall survival data of clinical patients from The Cancer Genome Atlas. Through PD-L1 heterogeneous virtual patients obtained by the computational framework, we explore the adaptive therapy of administering anti-PD-L1 according to the dynamic of PD-L1 state among cancer cells. Our results show that in contrast to the continuous maximum tolerated dose treatment, adaptive therapy is more effective for PD-L1 positive patients, in that it prolongs the survival of patients by administration of drugs at lower dosage.
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Stejskal P, Goodarzi H, Srovnal J, Hajdúch M, van ’t Veer LJ, Magbanua MJM. Circulating tumor nucleic acids: biology, release mechanisms, and clinical relevance. Mol Cancer 2023; 22:15. [PMID: 36681803 PMCID: PMC9862574 DOI: 10.1186/s12943-022-01710-w] [Citation(s) in RCA: 56] [Impact Index Per Article: 56.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 12/29/2022] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Despite advances in early detection and therapies, cancer is still one of the most common causes of death worldwide. Since each tumor is unique, there is a need to implement personalized care and develop robust tools for monitoring treatment response to assess drug efficacy and prevent disease relapse. MAIN BODY Recent developments in liquid biopsies have enabled real-time noninvasive monitoring of tumor burden through the detection of molecules shed by tumors in the blood. These molecules include circulating tumor nucleic acids (ctNAs), comprising cell-free DNA or RNA molecules passively and/or actively released from tumor cells. Often highlighted for their diagnostic, predictive, and prognostic potential, these biomarkers possess valuable information about tumor characteristics and evolution. While circulating tumor DNA (ctDNA) has been in the spotlight for the last decade, less is known about circulating tumor RNA (ctRNA). There are unanswered questions about why some tumors shed high amounts of ctNAs while others have undetectable levels. Also, there are gaps in our understanding of associations between tumor evolution and ctNA characteristics and shedding kinetics. In this review, we summarize current knowledge about ctNA biology and release mechanisms and put this information into the context of tumor evolution and clinical utility. CONCLUSIONS A deeper understanding of the biology of ctDNA and ctRNA may inform the use of liquid biopsies in personalized medicine to improve cancer patient outcomes.
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Affiliation(s)
- Pavel Stejskal
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University and University Hospital in Olomouc, Olomouc, 779 00 Czech Republic
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA 94158 USA
| | - Hani Goodarzi
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA 94158 USA
- Department of Urology, University of California San Francisco, San Francisco, CA 94158 USA
| | - Josef Srovnal
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University and University Hospital in Olomouc, Olomouc, 779 00 Czech Republic
| | - Marián Hajdúch
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University and University Hospital in Olomouc, Olomouc, 779 00 Czech Republic
| | - Laura J. van ’t Veer
- Department of Laboratory Medicine, University of California San Francisco, 2340 Sutter Street, San Francisco, CA USA
| | - Mark Jesus M. Magbanua
- Department of Laboratory Medicine, University of California San Francisco, 2340 Sutter Street, San Francisco, CA USA
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Tabrizi S, Martin-Alonso C, Xiong K, Blewett T, Sridhar S, An Z, Patel S, Rodriguez-Aponte S, Naranjo CA, Wang ST, Shea D, Golub TR, Bhatia SN, Adalsteinsson V, Love JC. An intravenous DNA-binding priming agent protects cell-free DNA and improves the sensitivity of liquid biopsies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.13.523947. [PMID: 36711455 PMCID: PMC9882106 DOI: 10.1101/2023.01.13.523947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Blood-based, or "liquid," biopsies enable minimally invasive diagnostics but have limits on sensitivity due to scarce cell-free DNA (cfDNA). Improvements to sensitivity have primarily relied on enhancing sequencing technology ex vivo . Here, we sought to augment the level of circulating tumor DNA (ctDNA) detected in a blood draw by attenuating the clearance of cfDNA in vivo . We report a first-in-class intravenous DNA-binding priming agent given 2 hours prior to a blood draw to recover more cfDNA. The DNA-binding antibody minimizes nuclease digestion and organ uptake of cfDNA, decreasing its clearance at 1 hour by over 150-fold. To improve plasma persistence and limit potential immune interactions, we abrogated its Fc-effector function. We found that it protects GC-rich sequences and DNase-hypersensitive sites, which are ordinarily underrepresented in cfDNA. In tumor-bearing mice, priming improved tumor DNA recovery by 19-fold and sensitivity for detecting cancer from 6% to 84%. These results suggest a novel method to enhance the sensitivity of existing DNA-based cancer testing using blood biopsies.
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Wu NJW, Aquilina M, Qian BZ, Loos R, Gonzalez-Garcia I, Santini CC, Dunn KE. The Application of Nanotechnology for Quantification of Circulating Tumour DNA in Liquid Biopsies: A Systematic Review. IEEE Rev Biomed Eng 2023; 16:499-513. [PMID: 35302938 DOI: 10.1109/rbme.2022.3159389] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Technologies for quantifying circulating tumour DNA (ctDNA) in liquid biopsies could enable real-time measurements of cancer progression, profoundly impacting patient care. Sequencing methods can be too complex and time-consuming for regular point-of-care monitoring, but nanotechnology offers an alternative, harnessing the unique properties of objects tens to hundreds of nanometres in size. This systematic review was performed to identify all examples of nanotechnology-based ctDNA detection and assess their potential for clinical use. Google Scholar, PubMed, Web of Science, Google Patents, Espacenet and Embase/MEDLINE were searched up to 23rd March 2021. The review identified nanotechnology-based methods for ctDNA detection for which quantitative measures (e.g., limit of detection, LOD) were reported and biologically relevant samples were used. The pre-defined inclusion criteria were met by 66 records. LODs ranged from 10 zM to 50nM. 25 records presented an LOD of 10fM or below. Nanotechnology-based approaches could provide the basis for the next wave of advances in ctDNA diagnostics, enabling analysis at the point-of-care, but none are currently used clinically. Further work is needed in development and validation; trade-offs are expected between different performance measures e.g., number of sequences detected and time to result.
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Kim SJ, Kim YJ, Yoon SE, Ryu KJ, Park B, Park D, Cho D, Kim HY, Cho J, Ko YH, Park WY, Kim WS. Circulating Tumor DNA-Based Genotyping and Monitoring for Predicting Disease Relapses of Patients with Peripheral T-Cell Lymphomas. Cancer Res Treat 2023; 55:291-303. [PMID: 35240014 PMCID: PMC9873338 DOI: 10.4143/crt.2022.017] [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: 01/11/2022] [Accepted: 02/23/2022] [Indexed: 02/04/2023] Open
Abstract
PURPOSE Plasma circulating tumor DNA (ctDNA) could reflect the genetic alterations present in tumor tissues. However, there is little information about the clinical relevance of cell-free DNA genotyping in peripheral T-cell lymphoma (PTCL). MATERIALS AND METHODS After targeted sequencing plasma cell-free DNA of patients with various subtypes of PTCL (n=94), we analyzed the mutation profiles of plasma ctDNA samples and their predictive value of dynamic ctDNA monitoring for treatment outcomes. RESULTS Plasma ctDNA mutations were detected in 53 patients (56%, 53/94), and the detection rate of somatic mutations was highest in angioimmunoblastic T-cell lymphoma (24/31, 77%) and PTCL, not otherwise specified (18/29, 62.1%). Somatic mutations were detected in 51 of 66 genes that were sequenced, including the following top 10 ranked genes: RHOA, CREBBP, KMT2D, TP53, IDH2, ALK, MEF2B, SOCS1, CARD11, and KRAS. In the longitudinal assessment of ctDNA mutation, the difference in ctDNA mutation volume after treatment showed a significant correlation with disease relapse or progression. Thus, a ≥ 1.5-log decrease in genome equivalent (GE) between baseline and the end of treatment showed a significant association with better survival outcomes than a < 1.5-log decrease in GE. CONCLUSION Our results suggest the clinical relevance of plasma ctDNA analysis in patients with PTCL. However, our findings should be validated by a subsequent study with a larger study population and using a broader gene panel.
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Affiliation(s)
- Seok Jin Kim
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea,Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Yeon Jeong Kim
- Samsung Genome Institute Samsung Medical Center, Seoul,
Korea
| | - Sang Eun Yoon
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Kyung Ju Ryu
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Bon Park
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | | | - Duck Cho
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Hyun-Young Kim
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Junhun Cho
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Young Hyeh Ko
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea
| | - Woong-Yang Park
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University School of Medicine, Seoul,
Korea,Samsung Genome Institute Samsung Medical Center, Seoul,
Korea
| | - Won Seog Kim
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,
Korea,Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University School of Medicine, Seoul,
Korea
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49
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Eyck BM, Jansen MP, Noordman BJ, Atmodimedjo PN, van der Wilk BJ, Martens JW, Helmijr JA, Beaufort CM, Mostert B, Doukas M, Wijnhoven BP, Lagarde SM, van Lanschot JJB, Dinjens WN. Detection of circulating tumour DNA after neoadjuvant chemoradiotherapy in patients with locally advanced oesophageal cancer. J Pathol 2023; 259:35-45. [PMID: 36196486 PMCID: PMC10092085 DOI: 10.1002/path.6016] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 09/05/2022] [Accepted: 09/30/2022] [Indexed: 11/05/2022]
Abstract
Active surveillance instead of standard surgery after neoadjuvant chemoradiotherapy (nCRT) has been proposed for patients with oesophageal cancer. Circulating tumour DNA (ctDNA) may be used to facilitate selection of patients for surgery. We show that detection of ctDNA after nCRT seems highly suggestive of major residual disease. Tumour biopsies and blood samples were taken before, and 6 and 12 weeks after, nCRT. Biopsies were analysed with regular targeted next-generation sequencing (NGS). Circulating cell-free DNA (cfDNA) was analysed using targeted NGS with unique molecular identifiers and digital polymerase chain reaction. cfDNA mutations matching pre-treatment biopsy mutations confirmed the presence of ctDNA. In total, 31 patients were included, of whom 24 had a biopsy mutation that was potentially detectable in cfDNA (77%). Pre-treatment ctDNA was detected in nine of 24 patients (38%), four of whom had incurable disease progression before surgery. Pre-treatment ctDNA detection had a sensitivity of 47% (95% CI 24-71) (8/17), specificity of 85% (95% CI 42-99) (6/7), positive predictive value (PPV) of 89% (95% CI 51-99) (8/9), and negative predictive value (NPV) of 40% (95% CI 17-67) (6/15) for detecting major residual disease (>10% residue in the resection specimen or progression before surgery). After nCRT, ctDNA was detected in three patients, two of whom had disease progression. Post-nCRT ctDNA detection had a sensitivity of 21% (95% CI 6-51) (3/14), specificity of 100% (95% CI 56-100) (7/7), PPV of 100% (95% CI 31-100) (3/3), and NPV of 39% (95% CI 18-64) (7/18) for detecting major residual disease. The addition of ctDNA to the current set of diagnostics did not lead to more patients being clinically identified with residual disease. These results indicate that pre-treatment and post-nCRT ctDNA detection may be useful in identifying patients at high risk of disease progression. The addition of ctDNA analysis to the current set of diagnostic modalities may not improve detection of residual disease after nCRT. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Ben M Eyck
- Department of Surgery, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Maurice Phm Jansen
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Bo Jan Noordman
- Department of Surgery, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Peggy N Atmodimedjo
- Department of Pathology, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Berend J van der Wilk
- Department of Surgery, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - John Wm Martens
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Jean A Helmijr
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Corine M Beaufort
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Bianca Mostert
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Michail Doukas
- Department of Pathology, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Bas Pl Wijnhoven
- Department of Surgery, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Sjoerd M Lagarde
- Department of Surgery, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - J Jan B van Lanschot
- Department of Surgery, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Winand Nm Dinjens
- Department of Pathology, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, Rotterdam, The Netherlands
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50
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Shen H, Jin Y, Zhao H, Wu M, Zhang K, Wei Z, Wang X, Wang Z, Li Y, Yang F, Wang J, Chen K. Potential clinical utility of liquid biopsy in early-stage non-small cell lung cancer. BMC Med 2022; 20:480. [PMID: 36514063 PMCID: PMC9749360 DOI: 10.1186/s12916-022-02681-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 11/28/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Liquid biopsy has been widely researched for early diagnosis, prognostication and disease monitoring in lung cancer, but there is a need to investigate its clinical utility for early-stage non-small cell lung cancer (NSCLC). METHODS We performed a meta-analysis and systematic review to evaluate diagnostic and prognostic values of liquid biopsy for early-stage NSCLC, regarding the common biomarkers, circulating tumor cells, circulating tumor DNA (ctDNA), methylation signatures, and microRNAs. Cochrane Library, PubMed, EMBASE databases, ClinicalTrials.gov, and reference lists were searched for eligible studies since inception to 17 May 2022. Sensitivity, specificity and area under the curve (AUC) were assessed for diagnostic values. Hazard ratio (HR) with a 95% confidence interval (CI) was extracted from the recurrence-free survival (RFS) and overall survival (OS) plots for prognostic analysis. Also, potential predictive values and treatment response evaluation were further investigated. RESULTS In this meta-analysis, there were 34 studies eligible for diagnostic assessment and 21 for prognostic analysis. The estimated diagnostic values of biomarkers for early-stage NSCLC with AUCs ranged from 0.84 to 0.87. The factors TNM stage I, T1 stage, N0 stage, adenocarcinoma, young age, and nonsmoking contributed to a lower tumor burden, with a median cell-free DNA concentration of 8.64 ng/ml. For prognostic analysis, the presence of molecular residual disease (MRD) detection was a strong predictor of disease relapse (RFS, HR, 4.95; 95% CI, 3.06-8.02; p < 0.001) and inferior OS (HR, 3.93; 95% CI, 1.97-7.83; p < 0.001), with average lead time of 179 ± 74 days between molecular recurrence and radiographic progression. Predictive values analysis showed adjuvant therapy significantly benefited the RFS of MRD + patients (HR, 0.27; p < 0.001), while an opposite tendency was detected for MRD - patients (HR, 1.51; p = 0.19). For treatment response evaluation, a strong correlation between pathological response and ctDNA clearance was detected, and both were associated with longer survival after neoadjuvant therapy. CONCLUSIONS In conclusion, our study indicated liquid biopsy could reliably facilitate more precision and effective management of early-stage NSCLC. Improvement of liquid biopsy techniques and detection approaches and platforms is still needed, and higher-quality trials are required to provide more rigorous evidence prior to their routine clinical application.
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Affiliation(s)
- Haifeng Shen
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Yichen Jin
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Heng Zhao
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Manqi Wu
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Kai Zhang
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Zihan Wei
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Xin Wang
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Ziyang Wang
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Yun Li
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Fan Yang
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Jun Wang
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China
| | - Kezhong Chen
- Thoracic Oncology Institute, Department of Thoracic Surgery, Peking University People's Hospital, Peking University, Xi Zhi Men South Ave No.11, Beijing, 100044, China.
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