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Ohmura H, Hanamura F, Okumura Y, Ando Y, Masuda T, Mimori K, Akashi K, Baba E. Liquid biopsy for breast cancer and other solid tumors: a review of recent advances. Breast Cancer 2024:10.1007/s12282-024-01556-8. [PMID: 38492205 DOI: 10.1007/s12282-024-01556-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 02/13/2024] [Indexed: 03/18/2024]
Abstract
Liquid biopsy using circulating tumor DNA (ctDNA) has been reported to be less invasive and effective for comprehensive genetic analysis of heterogeneous solid tumors, including decision-making for therapeutic strategies, predicting recurrence, and detecting genetic factors related to treatment resistance in various types of cancers. Breast cancer, colorectal cancer, and lung cancer are among the most prevalent malignancies worldwide, and clinical studies of liquid biopsy for these cancers are ongoing. Liquid biopsy has been used as a companion diagnostic tool in clinical settings, and research findings have accumulated, especially in cases of colorectal cancer after curative resection and non-small cell lung cancer (NSCLC) after curative chemoradiotherapy, in which ctDNA detection helps predict eligibility for adjuvant chemotherapy. Liquid biopsy using ctDNA shows promise across a wide range of cancer types, including breast cancer, and its clinical applications are expected to expand further through ongoing research. In this article, studies on liquid biopsy in breast cancer, colorectal cancer, and NSCLC are compared focusing on ctDNA.
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Affiliation(s)
- Hirofumi Ohmura
- Department of Oncology and Social Medicine, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-Ku, Fukuoka, 812-8582, Japan
- Department of Internal Medicine, Kyushu University Beppu Hospital, Oita, Japan
| | - Fumiyasu Hanamura
- Department of Internal Medicine, Kyushu University Beppu Hospital, Oita, Japan
| | - Yuta Okumura
- Department of Internal Medicine, Kyushu University Beppu Hospital, Oita, Japan
- Department of Gastrointestinal and Medical Oncology, National Hospital Organization Kyushu Cancer Center, Fukuoka, Japan
| | - Yuki Ando
- Department of Surgery, Kyushu University Beppu Hospital, Oita, Japan
| | - Takaaki Masuda
- Department of Surgery, Kyushu University Beppu Hospital, Oita, Japan
| | - Koshi Mimori
- Department of Surgery, Kyushu University Beppu Hospital, Oita, Japan
| | - Koichi Akashi
- Department of Medicine and Biosystemic Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Eishi Baba
- Department of Oncology and Social Medicine, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-Ku, Fukuoka, 812-8582, Japan.
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2
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Zhang C, Li Z, Liu J, Liu C, Zhang H, Lee WG, Yao C, Guo H, Xu F. Synthetic Gene Circuit-Based Assay with Multilevel Switch Enables Background-Free and Absolute Quantification of Circulating Tumor DNA. Research (Wash D C) 2023; 6:0217. [PMID: 37789988 PMCID: PMC10543738 DOI: 10.34133/research.0217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 08/02/2023] [Indexed: 10/05/2023]
Abstract
Circulating tumor DNA (ctDNA) detection has found widespread applications in tumor diagnostics and treatment, where the key is to obtain accurate quantification of ctDNA. However, this remains challenging due to the issue of background noise associated with existing assays. In this work, we developed a synthetic gene circuit-based assay with multilevel switch (termed CATCH) for background-free and absolute quantification of ctDNA. The multilevel switch combining a small transcription activating RNA and a toehold switch was designed to simultaneously regulate transcription and translation processes in gene circuit to eliminate background noise. Moreover, such a multilevel switch-based gene circuit was integrated with a Cas9 nickase H840A (Cas9n) recognizer and a molecular beacon reporter to form CATCH for ctDNA detection. The CATCH can be implemented in one-pot reaction at 35 °C with virtually no background noise, and achieve robust absolute quantification of ctDNA when integrated with a digital chip (i.e., digital CATCH). Finally, we validated the clinical capability of CATCH by detecting drug-resistant ctDNA mutations from the plasma of 76 non-small cell lung cancer (NSCLC) patients, showing satisfying clinical sensitivity and specificity. We envision that the simple and robust CATCH would be a powerful tool for next-generation ctDNA detection.
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Affiliation(s)
- Chao Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education,
School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, P.R. China
- Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi’an 710049, P.R. China
| | - Zedong Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education,
School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, P.R. China
- Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi’an 710049, P.R. China
- TFX Group-Xi'an Jiaotong University Institute of Life Health, Xi'an 710049, P.R. China
| | - Jie Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education,
School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, P.R. China
- Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi’an 710049, P.R. China
| | - Chang Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education,
School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, P.R. China
- Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi’an 710049, P.R. China
| | - Haoqing Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education,
School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, P.R. China
- Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi’an 710049, P.R. China
| | - Won Gu Lee
- Department of Mechanical Engineering,
Kyung Hee University, Yongin 17104, Republic of Korea
| | - Chunyan Yao
- Department of Transfusion Medicine, Southwest Hospital,
Third Military Medical University (Army Medical University), Chongqing 400038, P.R. China
| | - Hui Guo
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, P.R. China
| | - Feng Xu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education,
School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, P.R. China
- Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi’an 710049, P.R. China
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3
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Santonja A, Cooper WN, Eldridge MD, Edwards PAW, Morris JA, Edwards AR, Zhao H, Heider K, Couturier D, Vijayaraghavan A, Mennea P, Ditter E, Smith CG, Boursnell C, Manzano García R, Rueda OM, Beddowes E, Biggs H, Sammut S, Rosenfeld N, Caldas C, Abraham JE, Gale D. Comparison of tumor-informed and tumor-naïve sequencing assays for ctDNA detection in breast cancer. EMBO Mol Med 2023; 15:e16505. [PMID: 37161793 PMCID: PMC10245040 DOI: 10.15252/emmm.202216505] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 04/05/2023] [Accepted: 04/06/2023] [Indexed: 05/11/2023] Open
Abstract
Analysis of circulating tumor DNA (ctDNA) to monitor cancer dynamics and detect minimal residual disease has been an area of increasing interest. Multiple methods have been proposed but few studies have compared the performance of different approaches. Here, we compare detection of ctDNA in serial plasma samples from patients with breast cancer using different tumor-informed and tumor-naïve assays designed to detect structural variants (SVs), single nucleotide variants (SNVs), and/or somatic copy-number aberrations, by multiplex PCR, hybrid capture, and different depths of whole-genome sequencing. Our results demonstrate that the ctDNA dynamics and allele fractions (AFs) were highly concordant when analyzing the same patient samples using different assays. Tumor-informed assays showed the highest sensitivity for detection of ctDNA at low concentrations. Hybrid capture sequencing targeting between 1,347 and 7,491 tumor-identified mutations at high depth was the most sensitive assay, detecting ctDNA down to an AF of 0.00024% (2.4 parts per million, ppm). Multiplex PCR targeting 21-47 tumor-identified SVs per patient detected ctDNA down to 0.00047% AF (4.7 ppm) and has potential as a clinical assay.
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Affiliation(s)
- Angela Santonja
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Wendy N Cooper
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Matthew D Eldridge
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Paul A W Edwards
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
- Department of PathologyUniversity of CambridgeCambridgeUK
| | - James A Morris
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Abigail R Edwards
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
| | - Hui Zhao
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Katrin Heider
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Dominique‐Laurent Couturier
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
- MRC Biostatistics UnitUniversity of CambridgeCambridgeUK
| | - Aadhitthya Vijayaraghavan
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Paulius Mennea
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Emma‐Jane Ditter
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Christopher G Smith
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Chris Boursnell
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Raquel Manzano García
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Oscar M Rueda
- MRC Biostatistics UnitUniversity of CambridgeCambridgeUK
| | - Emma Beddowes
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Heather Biggs
- Department of OncologyUniversity of CambridgeCambridgeUK
- Precision Breast Cancer Institute, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's HospitalCambridgeUK
| | - Stephen‐John Sammut
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
- Department of OncologyUniversity of CambridgeCambridgeUK
| | - Nitzan Rosenfeld
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
| | - Carlos Caldas
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
- Department of OncologyUniversity of CambridgeCambridgeUK
- Precision Breast Cancer Institute, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's HospitalCambridgeUK
| | - Jean E Abraham
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
- Department of OncologyUniversity of CambridgeCambridgeUK
- Precision Breast Cancer Institute, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's HospitalCambridgeUK
| | - Davina Gale
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing CentreCambridgeUK
- Cancer Research UK Cambridge Centre, Cancer Research UK Cambridge Institute, Li Ka Shing CentreCambridgeUK
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4
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Dutta R, Vallurupalli M, McVeigh Q, Huang FW, Rebbeck TR. Understanding inequities in precision oncology diagnostics. Nat Cancer 2023; 4:787-794. [PMID: 37248397 DOI: 10.1038/s43018-023-00568-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 04/13/2023] [Indexed: 05/31/2023]
Abstract
Advances in molecular diagnostics have enabled the identification of targetable driver pathogenic variants, forming the basis of precision oncology care. However, the adoption of new technologies, such as next-generation sequencing (NGS) panels, can exacerbate healthcare disparities. Here, we summarize data on use patterns of advanced biomarker testing, highlight the disparities in both accessing NGS testing and using this data to match patients to appropriate personalized therapies and propose multidisciplinary strategies to address inequities looking forward.
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Affiliation(s)
- Ritika Dutta
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Mounica Vallurupalli
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Cancer Program, Broad Institute, Cambridge, MA, USA
| | - Quinn McVeigh
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Cancer Program, Broad Institute, Cambridge, MA, USA
| | - Franklin W Huang
- Cancer Program, Broad Institute, Cambridge, MA, USA.
- Division of Hematology and Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
- San Francisco Veterans Health Care System, San Francisco, CA, USA.
| | - Timothy R Rebbeck
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
- Harvard TH Chan School of Public Health, Boston, MA, USA.
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5
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Telekes A, Horváth A. The Role of Cell-Free DNA in Cancer Treatment Decision Making. Cancers (Basel) 2022; 14:6115. [PMID: 36551600 PMCID: PMC9776613 DOI: 10.3390/cancers14246115] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/28/2022] [Accepted: 11/30/2022] [Indexed: 12/14/2022] Open
Abstract
The aim of this review is to evaluate the present status of the use of cell-free DNA and its fraction of circulating tumor DNA (ctDNA) because this year July 2022, an ESMO guideline was published regarding the application of ctDNA in patient care. This review is for clinical oncologists to explain the concept, the terms used, the pros and cons of ctDNA; thus, the technical aspects of the different platforms are not reviewed in detail, but we try to help in navigating the current knowledge in liquid biopsy. Since the validated and adequately sensitive ctDNA assays have utility in identifying actionable mutations to direct targeted therapy, ctDNA may be used for this soon in routine clinical practice and in other different areas as well. The cfDNA fragments can be obtained by liquid biopsy and can be used for diagnosis, prognosis, and selecting among treatment options in cancer patients. A great proportion of cfDNA comes from normal cells of the body or from food uptake. Only a small part (<1%) of it is related to tumors, originating from primary tumors, metastatic sites, or circulating tumor cells (CTCs). Soon the data obtained from ctDNA may routinely be used for finding minimal residual disease, detecting relapse, and determining the sites of metastases. It might also be used for deciding appropriate therapy, and/or emerging resistance to the therapy and the data analysis of ctDNA may be combined with imaging or other markers. However, to achieve this goal, further clinical validations are inevitable. As a result, clinicians should be aware of the limitations of the assays. Of course, several open questions are still under research and because of it cfDNA and ctDNA testing are not part of routine care yet.
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Affiliation(s)
- András Telekes
- Omnimed-Etosz, Ltd., 81 Széher Rd., 1021 Budapest, Hungary
- Semmelweis University, 26. Üllői Rd., 1085 Budapest, Hungary
| | - Anna Horváth
- Department of Internal Medicine and Haematology, Semmelweis University, 46. Szentkirályi Rd., 1088 Budapest, Hungary
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6
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Slonim LB, Mangold KA, Alikhan MB, Joseph N, Reddy KS, Sabatini LM, Kaul KL. Cell-free Nucleic Acids in Cancer: Current Approaches, Challenges, and Future Directions. Clin Lab Med 2022; 42:669-686. [PMID: 36368789 DOI: 10.1016/j.cll.2022.09.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Liron Barnea Slonim
- Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201
| | - Kathy A Mangold
- Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201
| | - Mir B Alikhan
- Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201
| | - Nora Joseph
- Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201
| | - Kalpana S Reddy
- Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201
| | - Linda M Sabatini
- Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201
| | - Karen L Kaul
- Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201.
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Zhang Y, Bae Y, Shibayama S, Wang X, Kato M, Dong L. International co-validation on absolute quantification of single nucleotide variants of KRAS by digital PCR. Anal Bioanal Chem. [DOI: 10.1007/s00216-022-04155-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 05/15/2022] [Accepted: 05/31/2022] [Indexed: 11/01/2022]
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8
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Liu MC, MacKay M, Kase M, Piwowarczyk A, Lo C, Schaeffer J, Finkle JD, Mason CE, Beaubier N, Blackwell KL, Park BH. Longitudinal Shifts of Solid Tumor and Liquid Biopsy Sequencing Concordance in Metastatic Breast Cancer. JCO Precis Oncol 2022; 6:e2100321. [PMID: 35721584 PMCID: PMC9200387 DOI: 10.1200/po.21.00321] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/17/2021] [Accepted: 03/24/2022] [Indexed: 11/21/2022] Open
Abstract
Tissue-based next-generation sequencing (NGS) in metastatic breast cancer (mBC) is limited by the inability to noninvasively track tumor evolution. Cell-free DNA (cfDNA) NGS has made sequential testing feasible; however, the relationship between cfDNA and tissue-based testing in mBC is not well understood. Here, we evaluate concordance between tissue and cfDNA NGS relative to cfDNA sampling frequency in a large, clinically annotated mBC data set. METHODS Tempus LENS was used to analyze deidentified records of mBC cases with Tempus xT (tissue) and xF (cfDNA) sequencing results. Then, various metrics of concordance were assessed within overlapping probe regions of the tissue and cfDNA assays (104 genes), focusing on pathogenic variants. Variant allele frequencies of discordant and concordant pathogenic variants were also compared. Analyses were stratified by mBC subtype and time between tests. RESULTS Records from 300 paired tissue and liquid biopsies were analyzed. Median time between tissue and blood collection was 78.5 days (standard deviation = 642.99). The median number of pathogenic variants/patient was one for cfDNA and two for tissue. Across the cohort, 77.8% of pathogenic tissue variants were found in cfDNA and 75.7% of pathogenic cfDNA variants were found in tissue when tests were ≤ 7 days apart, which decreased to 50.3% and 51.8%, respectively, for > 365 days. Furthermore, the median patient-level variant concordance was 67% when tests were ≤7 days apart and 30%-37% when > 30 days. The median variant allele frequencies of discordant variants were generally lower than those of concordant variants within the same time frame. CONCLUSION We observed high concordances between tissue and cfDNA results that generally decreased with longer durations between tests. Thus, cfDNA NGS reliably measures tissue genomics and is likely beneficial for longitudinal monitoring of molecular changes in mBC.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Ben Ho Park
- Vanderbilt University Medical Center, Nashville, TN
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9
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Quy PN, Fukuyama K, Kanai M, Kou T, Kondo T, Yoshioka M, Matsubara J, Sakuma T, Minamiguchi S, Matsumoto S, Muto M. Inter-assay variability of next-generation sequencing-based gene panels. BMC Med Genomics 2022; 15:86. [PMID: 35428255 PMCID: PMC9013031 DOI: 10.1186/s12920-022-01230-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 04/04/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Tumor heterogeneity has been known to cause inter-assay discordance among next-generation sequencing (NGS) results. However, whether preclinical factors such as sample type, sample quality and analytical features of gene panel can affect the concordance between two different assays remains largely unexplored. METHODS Replicate sets of DNA samples extracted from formalin-fixed paraffin-embedded tissues (FFPE) (n = 20) and fresh frozen (FF) tissues (n = 10) were herein analyzed using a tumor-only (TO) and paired tumor-normal (TN) gene panel in laboratories certified by the Clinical Laboratory Improvement Amendment. Reported variants from the TO and TN panels were then compared. Furthermore, additional FFPE samples were sequentially sliced from the same FFPE block and submitted to another TN panel assay. RESULTS Substantial discordance (71.8%) was observed between the results of the two panels despite using identical DNA samples, with the discordance rate being significantly higher for FFPE samples (p < 0.05). Among the 99 variants reported only in the TO panel, 32.3% were consistent with germline variants, which were excluded in the TN panel, while 30.3% had an allele frequency of less than 5%, some of which were highly likely to be artificial calls. The comparison of two independent TN panel assay results from the same FFPE block also showed substantial discordance rate (55.3%). CONCLUSIONS In the context of clinical settings, our comparative analysis revealed that inter-NGS assay discordance commonly occurred due to sample types and the different analytical features of each panel.
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Affiliation(s)
- Pham Nguyen Quy
- Department of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Keita Fukuyama
- Department of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Masashi Kanai
- Department of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
| | - Tadayuki Kou
- Department of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tomohiro Kondo
- Department of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Masahiro Yoshioka
- Department of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Junichi Matsubara
- Department of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tomohiro Sakuma
- Biomedical Department, Mitsui Knowledge Industry Co., Ltd., Tokyo, Japan
| | - Sachiko Minamiguchi
- Department of Diagnostic Pathology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Shigemi Matsumoto
- Department of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Manabu Muto
- Department of Therapeutic Oncology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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10
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Akabari R, Qin D, Hussaini M. Technological Advances: CEBPA and FLT3 Internal Tandem Duplication Mutations Can be Reliably Detected by Next Generation Sequencing. Genes (Basel) 2022; 13:genes13040630. [PMID: 35456436 PMCID: PMC9028339 DOI: 10.3390/genes13040630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 03/21/2022] [Accepted: 03/30/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND The detection of CEBPA and FLT3 mutations by next generation sequencing (NGS) is challenging due to high GC content and Internal Tandem Duplications (ITDs). Recent advances have been made to surmount these challenges. In this study, we compare three commercial kits and evaluate the performance of these more advanced hybrid-capture and AMP-chemistry based methods. METHODS Amplicon-based TSM 54-Gene Panel (Illumina) was evaluated against hybridization-capture SOPHiA Genetics MSP, OGT SureSeq, and AMP chemistry-based VariantPlex (Archer) for wet-lab workflow and data-analysis pipelines. Standard kit directions and commercial analysis pipelines were followed. Seven CEBPA and 10 FLT3-positive cases were identified that previously were missed on an amplicon NGS assay. The average reads, coverage uniformity, and the detection of CEBPA or FLT3 mutations were compared. RESULTS All three panels detected all 10 CEBPA mutations and all 10 FLT3 ITDs with 100% sensitivity. In addition, there was high concordance (100%) between all three panels detecting 47/47 confirmed variants in a set of core myeloid genes. CONCLUSIONS The results show that the NGS assays are now able to reliably detect CEBPA mutations and FLT3 ITDs. These assays may allow foregoing additional orthogonal testing for CEBPA and FLT3.
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Affiliation(s)
- Ratilal Akabari
- Department of Pathology, Molecular Oncology and Genetics Diagnostics, SUNY Upstate Medical University, Syracuse, NY 13210, USA;
| | - Dahui Qin
- Department of Pathology, Moffitt Cancer Center, Tampa, FL 33612, USA;
| | - Mohammad Hussaini
- Department of Pathology, Moffitt Cancer Center, Tampa, FL 33612, USA;
- Correspondence: ; Tel.: +1-813-745-6118
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11
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Meng G, Liu X, Ma T, Lv D, Sun G. Predictive value of tumor mutational burden for immunotherapy in non-small cell lung cancer: A systematic review and meta-analysis. PLoS One 2022; 17:e0263629. [PMID: 35113949 PMCID: PMC8812984 DOI: 10.1371/journal.pone.0263629] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 01/22/2022] [Indexed: 01/06/2023] Open
Abstract
Background Immunotherapy has emerged as a promising treatment for non-small cell lung cancer (NSCLC). Yet, some patients cannot benefit from immunotherapy, and reliable biomarkers for selecting sensitive patients are needed. Herein, we performed a meta-analysis to evaluate the predictive value of tumor mutational burden (TMB) in NSCLC patients treated with immunotherapy. Methods Eligible studies were comprehensively searched from electronic databases prior to August 31, 2021. Meta-analyses of high TMB versus low TMB as well as immunotherapy versus chemotherapy in patients with high/low TMB were conducted. Hazard ratio (HR) with corresponding 95% confidence interval (95%CI) for progression-free survival (PFS) and overall survival (OS) and odds ratio (OR) with 95%CI for objective response rate (ORR) were calculated. Results A total of 31 datasets (3437 patients) and 6 randomized controlled trials (3662 patients) were available for meta-analyses of high TMB versus low TMB and immunotherapy versus chemotherapy, respectively. High TMB predicted significantly favorable PFS (HR = 0.54, 95%CI: 0.46–0.63, P<0.001) and OS (HR = 0.70, 95%CI: 0.57–0.87, P = 0.001), and higher ORR (OR = 3.14, 95%CI: 2.28–4.34, P<0.001) compared with low TMB. In patients with high TMB, immunotherapy was associated with improved PFS (HR = 0.62, 95%CI: 0.53–0.72), OS (HR = 0.67, 95%CI: 0.57–0.79) and ORR (OR = 2.35, 95%CI: 1.74–3.18) when compared with chemotherapy. However, in patients with low TMB, immunotherapy seemed to predict inferior PFS (HR = 1.20, 95%CI: 1.02–1.41) and ORR (OR = 0.61, 95%CI: 0.44–0.84) and have no OS benefit (HR = 0.88, 95%CI: 0.74–1.05) as compared with chemotherapy. Conclusion This meta-analysis demonstrates more clinical benefits concerning treatment response and survival outcomes in high-TMB NSCLC patients who are treated with immunotherapy. TMB is a promising biomarker for discriminating NSCLC patients who can benefit more from immunotherapy.
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Affiliation(s)
- Guangxian Meng
- Department of Thoracic surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, China
| | - Xiaowei Liu
- Department of Thoracic surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, China
| | - Tian Ma
- Department of Thoracic surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, China
| | - Desheng Lv
- Department of Thoracic surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, China
| | - Ge Sun
- Department of Thoracic surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning Province, China
- * E-mail:
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12
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Werner B, Warton K, Ford CE. Transcending Blood—Opportunities for Alternate Liquid Biopsies in Oncology. Cancers (Basel) 2022; 14:1309. [PMID: 35267615 PMCID: PMC8909855 DOI: 10.3390/cancers14051309] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 02/28/2022] [Accepted: 03/01/2022] [Indexed: 12/24/2022] Open
Abstract
Simple Summary Cell-free DNA—DNA that has been expelled from cells and can be isolated from blood plasma and other body fluids—is a useful tool in medicine, with applications as a biomarker in diagnosis, prognosis, disease profiling, and treatment selection. In oncology, the ease of access to the tumour genome is a major advantage of cell-free DNA, but while this has led to significant research in blood, other body fluids have not received equal attention. This review article summarises the current research into cell-free DNA in non-blood body fluids, highlighting its values and limitations, and suggesting the direction of future studies. We conclude that cell-free DNA from non-blood body fluids may provide additional information to supplement traditional biopsies, allowing informative and improved patient care across many cancer types. Abstract Cell-free DNA (cfDNA) is a useful molecular biomarker in oncology research and treatment, but while research into its properties in blood has flourished, there remains much to be discovered about cfDNA in other body fluids. The cfDNA from saliva, sputum, cerebrospinal fluid, urine, faeces, pleural effusions, and ascites has unique advantages over blood, and has potential as an alternative ‘liquid biopsy’ template. This review summarises the state of current knowledge and identifies the gaps in our understanding of non-blood liquid biopsies; where their advantages lie, where caution is needed, where they might fit clinically, and where research should focus in order to accelerate clinical implementation. An emphasis is placed on ascites and pleural effusions, being pathological fluids directly associated with cancer. We conclude that non-blood fluids are viable sources of cfDNA in situations where solid tissue biopsies are inaccessible, or only accessible from dated archived specimens. In addition, we show that due to the abundance of cfDNA in non-blood fluids, they can outperform blood in many circumstances. We demonstrate multiple instances in which DNA from various sources can provide additional information, and thus we advocate for analysing non-blood sources as a complement to blood and/or tissue. Further research into these fluids will highlight opportunities to improve patient outcomes across cancer types.
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13
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Yang G, Wei L, Thong BKS, Fu Y, Cheong IH, Kozlakidis Z, Li X, Wang H, Li X. A Systematic Review of Oral Biopsies, Sample Types, and Detection Techniques Applied in Relation to Oral Cancer Detection. BioTech (Basel) 2022; 11:5. [PMID: 35822813 PMCID: PMC9245907 DOI: 10.3390/biotech11010005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 02/18/2022] [Accepted: 02/24/2022] [Indexed: 12/11/2022] Open
Abstract
Background: Early identification of the stage of oral cancer development can lead to better treatment outcomes and avoid malignant transformation. Therefore, this review aims to provide a comprehensive overview that describes the development of standardized procedures for oral sample collection, characterization, and molecular risk assessment. This can help investigators to choose the appropriate sampling method and downstream analyses for different purposes. Methods: This systematic review was conducted according to the PRISMA guidelines. Using both PubMed and Web of Science databases, four independent authors conducted a literature search between 15 and 21 June 2021. We used key search terms to broaden the search for studies. Non-conforming articles were removed using an EndNote-based and manual approach. Reviewers used a designed form to extract data. Results: This review included a total of 3574 records, after eliminating duplicate articles and excluding papers that did not meet the inclusion criteria. Finally, 202 articles were included in this review. We summarized the sampling methods, biopsy samples, and downstream analysis. The biopsy techniques were classified into tissue and liquid biopsy. The common sequential analysis of tissue biopsy includes histopathological examination such as H&E or IHC to identify various pathogenic features. Meanwhile, liquid samples such as saliva, blood, and urine are analyzed for the purpose of screening to detect mutations in cancer. Commonly used technologies are PCR, RT-PCR, high-throughput sequencing, and metabolomic analysis. Conclusions: Currently, tissue biopsies provide increased diagnostic value compared to liquid biopsy. However, the minimal invasiveness and convenience of liquid biopsy make it a suitable method for mass screening and eventual clinical adoption. The analysis of samples includes histological and molecular analysis. Metabolite analysis is rising but remains scarce.
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Affiliation(s)
- Guanghuan Yang
- State Key Laboratory of Oncogenes and Related Genes, Centre for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (G.Y.); (L.W.); (B.K.S.T.); (Y.F.); (I.H.C.); (X.L.)
| | - Luqi Wei
- State Key Laboratory of Oncogenes and Related Genes, Centre for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (G.Y.); (L.W.); (B.K.S.T.); (Y.F.); (I.H.C.); (X.L.)
| | - Benjamin K. S. Thong
- State Key Laboratory of Oncogenes and Related Genes, Centre for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (G.Y.); (L.W.); (B.K.S.T.); (Y.F.); (I.H.C.); (X.L.)
| | - Yuanyuan Fu
- State Key Laboratory of Oncogenes and Related Genes, Centre for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (G.Y.); (L.W.); (B.K.S.T.); (Y.F.); (I.H.C.); (X.L.)
| | - Io Hong Cheong
- State Key Laboratory of Oncogenes and Related Genes, Centre for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (G.Y.); (L.W.); (B.K.S.T.); (Y.F.); (I.H.C.); (X.L.)
| | - Zisis Kozlakidis
- International Agency for Research on Cancer, World Health Organization, 69372 Lyon, France;
| | - Xue Li
- State Key Laboratory of Oncogenes and Related Genes, Centre for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (G.Y.); (L.W.); (B.K.S.T.); (Y.F.); (I.H.C.); (X.L.)
| | - Hui Wang
- State Key Laboratory of Oncogenes and Related Genes, Centre for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (G.Y.); (L.W.); (B.K.S.T.); (Y.F.); (I.H.C.); (X.L.)
| | - Xiaoguang Li
- State Key Laboratory of Oncogenes and Related Genes, Centre for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (G.Y.); (L.W.); (B.K.S.T.); (Y.F.); (I.H.C.); (X.L.)
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14
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Willey JC, Morrison TB, Austermiller B, Crawford EL, Craig DJ, Blomquist TM, Jones WD, Wali A, Lococo JS, Haseley N, Richmond TA, Novoradovskaya N, Kusko R, Chen G, Li QZ, Johann DJ, Deveson IW, Mercer TR, Wu L, Xu J. Advancing NGS quality control to enable measurement of actionable mutations in circulating tumor DNA. Cell Rep Methods 2021; 1:100106. [PMID: 35475002 PMCID: PMC9017191 DOI: 10.1016/j.crmeth.2021.100106] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 05/31/2021] [Accepted: 10/11/2021] [Indexed: 11/25/2022]
Abstract
The primary objective of the FDA-led Sequencing and Quality Control Phase 2 (SEQC2) project is to develop standard analysis protocols and quality control metrics for use in DNA testing to enhance scientific research and precision medicine. This study reports a targeted next-generation sequencing (NGS) method that will enable more accurate detection of actionable mutations in circulating tumor DNA (ctDNA) clinical specimens. To accomplish this, a synthetic internal standard spike-in was designed for each actionable mutation target, suitable for use in NGS following hybrid capture enrichment and unique molecular index (UMI) or non-UMI library preparation. When mixed with contrived ctDNA reference samples, internal standards enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position in each sample. True-positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity.
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Affiliation(s)
- James C. Willey
- College of Medicine and Life Sciences, University of Toledo, Toledo, OH 43614, USA
| | - Tom B. Morrison
- AccuGenomics Inc., The Atrium, Suite 105, 1410 Commonwealth Drive, Wilmington, NC 28403, USA
| | - Bradley Austermiller
- AccuGenomics Inc., The Atrium, Suite 105, 1410 Commonwealth Drive, Wilmington, NC 28403, USA
| | - Erin L. Crawford
- College of Medicine and Life Sciences, University of Toledo, Toledo, OH 43614, USA
| | - Daniel J. Craig
- College of Medicine and Life Sciences, University of Toledo, Toledo, OH 43614, USA
| | - Thomas M. Blomquist
- College of Medicine and Life Sciences, University of Toledo, Toledo, OH 43614, USA
| | | | - Aminah Wali
- Q Solutions, EA Genomics, Morrisville, NC 27560, USA
| | | | - Nathan Haseley
- Illumina Inc., 5200 Illumina Way, San Diego, CA 92122, USA
| | | | | | | | - Guangchun Chen
- University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Quan-Zhen Li
- University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Donald J. Johann
- Winthrop P Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W Markham Street, Little Rock, AR 72205, USA
| | - Ira W. Deveson
- Garvan Institute of Medical Research, Sydney, NSW 2010, Australia
- St. Vincent’s Clinical School, University of New South Wales, Sydney, NSW 2010, Australia
| | - Timothy R. Mercer
- Garvan Institute of Medical Research, Sydney, NSW 2010, Australia
- St. Vincent’s Clinical School, University of New South Wales, Sydney, NSW 2010, Australia
| | - Leihong Wu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA
| | - Joshua Xu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA
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15
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Bieler J, Pozzorini C, Garcia J, Tuck AC, Macheret M, Willig A, Couraud S, Xing X, Menu P, Steinmetz LM, Payen L, Xu Z. High-Throughput Nucleotide Resolution Predictions of Assay Limitations Increase the Reliability and Concordance of Clinical Tests. JCO Clin Cancer Inform 2021; 5:1085-1095. [PMID: 34731027 DOI: 10.1200/cci.21.00057] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
PURPOSE The ability of next-generation sequencing (NGS) assays to interrogate thousands of genomic loci has revolutionized genetic testing. However, translation to the clinic is impeded by false-negative results that pose a risk to patients. In response, regulatory bodies are calling for reliability measures to be reported alongside NGS results. Existing methods to estimate reliability do not account for sample- and position-specific variability, which can be significant. Here, we report an approach that computes reliability metrics for every genomic position and sample interrogated by an NGS assay. METHODS Our approach predicts the limit of detection (LOD), the lowest reliably detectable variant fraction, by taking technical factors into account. We initially explored how LOD is affected by input material amount, library conversion rate, sequencing coverage, and sequencing error rate. This revealed that LOD depends heavily on genomic context and sample properties. Using these insights, we developed a computational approach to predict LOD on the basis of a biophysical model of the NGS workflow. We focused on targeted assays for cell-free DNA, but, in principle, this approach applies to any NGS assay. RESULTS We validated our approach by showing that it accurately predicts LOD and distinguishes reliable from unreliable results when screening 580 lung cancer samples for actionable mutations. Compared with a standard variant calling workflow, our approach avoided most false negatives and improved interassay concordance from 94% to 99%. CONCLUSION Our approach, which we name LAVA (LOD-aware variant analysis), reports the LOD for every position and sample interrogated by an NGS assay. This enables reliable results to be identified and improves the transparency and safety of genetic tests.
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Affiliation(s)
| | | | - Jessica Garcia
- Laboratoire de Biochimie et Biologie Moléculaire, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre Bénite, France.,Institut de Cancérologie des Hospices Civils de Lyon, CIRculating CANcer Program (CIRCAN), Lyon, France
| | - Alex C Tuck
- SOPHiA GENETICS SA, Saint Sulpice, Switzerland
| | | | | | - Sébastien Couraud
- Institut de Cancérologie des Hospices Civils de Lyon, CIRculating CANcer Program (CIRCAN), Lyon, France.,Service de Pneumologie aigue spécialisée et cancérologie thoracique, Groupement hospitalier sud, Institut de Cancérologie des Hospices Civils de Lyon, Pierre Bénite, France
| | | | | | - Lars M Steinmetz
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA.,Department of Genetics, School of Medicine, Stanford University, Stanford, CA
| | - Léa Payen
- Laboratoire de Biochimie et Biologie Moléculaire, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre Bénite, France.,Institut de Cancérologie des Hospices Civils de Lyon, CIRculating CANcer Program (CIRCAN), Lyon, France
| | - Zhenyu Xu
- SOPHiA GENETICS SA, Saint Sulpice, Switzerland
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16
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Deveson IW, Gong B, Lai K, LoCoco JS, Richmond TA, Schageman J, Zhang Z, Novoradovskaya N, Willey JC, Jones W, Kusko R, Chen G, Madala BS, Blackburn J, Stevanovski I, Bhandari A, Close D, Conroy J, Hubank M, Marella N, Mieczkowski PA, Qiu F, Sebra R, Stetson D, Sun L, Szankasi P, Tan H, Tang LY, Arib H, Best H, Burgher B, Bushel PR, Casey F, Cawley S, Chang CJ, Choi J, Dinis J, Duncan D, Eterovic AK, Feng L, Ghosal A, Giorda K, Glenn S, Happe S, Haseley N, Horvath K, Hung LY, Jarosz M, Kushwaha G, Li D, Li QZ, Li Z, Liu LC, Liu Z, Ma C, Mason CE, Megherbi DB, Morrison T, Pabón-Peña C, Pirooznia M, Proszek PZ, Raymond A, Rindler P, Ringler R, Scherer A, Shaknovich R, Shi T, Smith M, Song P, Strahl M, Thodima VJ, Tom N, Verma S, Wang J, Wu L, Xiao W, Xu C, Yang M, Zhang G, Zhang S, Zhang Y, Shi L, Tong W, Johann DJ, Mercer TR, Xu J. Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology. Nat Biotechnol 2021; 39:1115-1128. [PMID: 33846644 PMCID: PMC8434938 DOI: 10.1038/s41587-021-00857-z] [Citation(s) in RCA: 103] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 02/15/2021] [Indexed: 02/08/2023]
Abstract
Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments and proficiency testing on standardized, cell-line-derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas, below this limit, detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false negatives) were more common than erroneous candidates (false positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best practice guidelines and provides a resource for precision oncology.
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Affiliation(s)
- Ira W Deveson
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Binsheng Gong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Kevin Lai
- Bioinformatics, Integrated DNA Technologies, Inc., Coralville, IA, USA
| | | | - Todd A Richmond
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., Pleasanton, CA, USA
| | | | - Zhihong Zhang
- Research and Development, Burning Rock Biotech, Shanghai, China
| | | | - James C Willey
- Departments of Medicine, Pathology, and Cancer Biology, College of Medicine and Life Sciences, University of Toledo Health Sciences Campus, Toledo, OH, USA
| | | | | | - Guangchun Chen
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bindu Swapna Madala
- Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - James Blackburn
- Cancer Theme, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St. Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Igor Stevanovski
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | | | - Devin Close
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, Salt Lake City, UT, USA
| | | | - Michael Hubank
- NIHR Biomedical Research Centre, Royal Marsden Hospital, Sutton, Surrey, UK
| | | | | | - Fujun Qiu
- Research and Development, Burning Rock Biotech, Shanghai, China
| | - Robert Sebra
- Icahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Lihyun Sun
- Elim Biopharmaceuticals, Inc., Hayward, CA, USA
| | - Philippe Szankasi
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, Salt Lake City, UT, USA
| | - Haowen Tan
- Primbio Genes Biotechnology, East Lake High-tech Development Zone, Wuhan, Hubei, China
| | - Lin-Ya Tang
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, Houston, TX, USA
| | - Hanane Arib
- Icahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hunter Best
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, Salt Lake City, UT, USA
- Departments of Pathology and Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, USA
| | | | - Pierre R Bushel
- National Institute of Environmental Health Sciences, Research Triangle Park, Morrisville, NC, USA
| | - Fergal Casey
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., Pleasanton, CA, USA
| | - Simon Cawley
- Clinical Sequencing Division, Thermo Fisher Scientific, South San Francisco, CA, USA
| | - Chia-Jung Chang
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA
| | - Jonathan Choi
- Roche Sequencing Solutions, Inc., Pleasanton, CA, USA
| | - Jorge Dinis
- Roche Sequencing Solutions, Inc., Pleasanton, CA, USA
| | | | - Agda Karina Eterovic
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, Houston, TX, USA
| | - Liang Feng
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., Pleasanton, CA, USA
| | | | - Kristina Giorda
- Marketing, Integrated DNA Technologies, Inc., Coralville, IA, USA
| | | | | | | | | | - Li-Yuan Hung
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Mirna Jarosz
- NGS Products and Services, Integrated DNA Technologies, Inc., Coralville, IA, USA
| | - Garima Kushwaha
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., Pleasanton, CA, USA
| | - Dan Li
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Quan-Zhen Li
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Zhiguang Li
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Liang-Chun Liu
- Clinical Diagnostic Division, Thermo Fisher Scientific, Fremont, CA, USA
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Charles Ma
- Cancer Genetics, Inc., Rutherford, NJ, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Dalila B Megherbi
- CMINDS Research Center, Department of Electrical and Computer Engineering, College of Engineering, University of Massachusetts Lowell, Lowell, MA, USA
| | | | | | - Mehdi Pirooznia
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Paula Z Proszek
- NIHR Biomedical Research Centre, Royal Marsden Hospital, Sutton, Surrey, UK
| | | | - Paul Rindler
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, Salt Lake City, UT, USA
| | | | - Andreas Scherer
- Institute for Molecular Medicine Finland (FIMM), Nordic EMBL Partnership for Molecular Medicine, HiLIFE Unit, Biomedicum Helsinki 2U (D302b), University of Helsinki, Helsinki, Finland
- EATRIS ERIC- European Infrastructure for Translational Medicine, Amsterdam, The Netherlands
| | | | - Tieliu Shi
- Center for Bioinformatics and Computational Biology and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, China
| | - Melissa Smith
- Icahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ping Song
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, Houston, TX, USA
| | - Maya Strahl
- Icahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Nikola Tom
- EATRIS ERIC- European Infrastructure for Translational Medicine, Amsterdam, The Netherlands
- Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | | | - Jiashi Wang
- Research and Development, Integrated DNA Technologies, Inc., Coralville, IA, USA
| | - Leihong Wu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Wenzhong Xiao
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Chang Xu
- Research and Development, QIAGEN Sciences, Inc., Frederick, MD, USA
| | - Mary Yang
- Department of Information Science, University of Arkansas at Little Rock, Little Rock, AR, USA
| | | | - Sa Zhang
- Clinical Laboratory, Burning Rock Biotech, Guangzhou, China
| | - Yilin Zhang
- Elim Biopharmaceuticals, Inc., Hayward, CA, USA
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, China
- Human Phenome Institute, Fudan University, Shanghai, China
- Fudan-Gospel Joint Research Center for Precision Medicine, Fudan University, Shanghai, China
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Donald J Johann
- Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
| | - Timothy R Mercer
- St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
- Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Sydney, NSW, Australia.
- Australian Institute of Bioengineering and Nanotechnology, University of Queensland, Queensland, QLD, Australia.
| | - Joshua Xu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA.
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17
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Jiao XD, Ding LR, Zhang CT, Qin BD, Liu K, Jiang LP, Wang X, Lv LT, Ding H, Li DM, Yang H, Chen XQ, Zhu WY, Wu Y, Ling Y, He X, Liu J, Shao L, Wang HZ, Chen Y, Zheng JJ, Inui N, Zang YS. Serum tumor markers for the prediction of concordance between genomic profiles from liquid and tissue biopsy in patients with advanced lung adenocarcinoma. Transl Lung Cancer Res 2021; 10:3236-3250. [PMID: 34430361 PMCID: PMC8350084 DOI: 10.21037/tlcr-21-543] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Accepted: 07/22/2021] [Indexed: 12/18/2022]
Abstract
Background The concordance between mutations detected from plasma and tissue is critical for treatment choices of patients with advanced lung adenocarcinoma. Methods We prospectively analyzed the association of the serum tumor markers with the concordance between blood and tissue genomic profiles from 185 patients with advanced lung adenocarcinoma. The concordance was defined according to 3 criteria. Class 1 included all targetable driver mutations in 8 genes; class 2 included class 1 mutations plus mutations in KRAS, STK11, and TP53; class 3 included class 2 mutations plus tumor mutation burden (TMB) status. Results Collectively, 150 out of 185 patients had mutations in both tissue and plasma samples, while one patient was mutation-negative for both, resulting a concordance of 81.6%. The concordance rate for class 1 mutations was 80%, and 65% and 69% for class 2 and class 3, respectively. Carbohydrate antigen 19-9 (CA19-9) or cytokeratin 19 (CYFRA21-1) levels higher than the normal upper limit predicted the concordance of tissue and blood results in class 1 (P=0.005, P=0.011), class 2 (P=0.011, P<0.001), and class 3 (P=0.001, P=0.014). In class 1, the cutoff values of CA19-9 were 30, 36, and 284 U/mL to reach the concordance thresholds of 90%, 95%, and 100%, respectively (P=0.032, P=0.003, P=0.043). For CYFRA21-1, the cutoff values were 6, 18, and 52 µg/L (P=0.005, P=0.051, P=0.354). In class 2, the cutoff values for CYFRA21-1 were 18, 22, and 52 µg/L (P=0.001, P=0.001, P=0.052). In class 3, the cutoff values for CA19-9 were 36, 39, and 85 U/mL (P=0.003, P=0.001, P=0.008). For CYFRA21-1, the cutoff values were 22, 52, and 52 µg/L (P=0.900, P>0.99, P>0.99). When the sum score for 4 serum tumor markers was greater than 35, both class 1, class 2, and class 3 reached a predictive threshold of 90%. Conclusions Serum tumor markers can be used as easy and practical clinical predictors of concordance in mutation profiles between blood and tissue samples from patients with advanced lung adenocarcinoma.
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Affiliation(s)
- Xiao-Dong Jiao
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Li-Ren Ding
- Department of Respiratory Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine at Bingjiang, Hangzhou, China
| | - Chuan-Tao Zhang
- Department of Medical Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Bao-Dong Qin
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Ke Liu
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Lian-Ping Jiang
- Department of Chemotherapy, Minhang Branch, Fudan University, Shanghai Cancer Center, Shanghai, China
| | - Xi Wang
- Department of Oncology, The 903rd Hospital of PLA, Hangzhou, China
| | - Li-Ting Lv
- Department of Oncology, Affiliated Hospital of Nantong University, Nantong, China
| | - Hao Ding
- Division of Respiratory Disease, Affiliated People's Hospital of Jiangsu University, Zhenjiang, China
| | - Dao-Ming Li
- Department of Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hui Yang
- Department of Medical Oncology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou, China
| | - Xue-Qin Chen
- Department of Oncology, Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wen-Yu Zhu
- Department of Oncology, Changzhou No. 2 People's Hospital Cancer Center, Changzhou, China
| | - Ying Wu
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Yan Ling
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Xi He
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Jun Liu
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
| | - Lin Shao
- Department of Data Science, Burning Rock Biotech, Guangzhou, China
| | - Hao-Zhe Wang
- Department of Data Science, Burning Rock Biotech, Guangzhou, China
| | - Yan Chen
- Department of Medicine, Burning Rock Biotech, Guangzhou, China
| | - Jing-Jing Zheng
- Department of Medicine, Burning Rock Biotech, Guangzhou, China
| | - Naoki Inui
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Handayama, Hamamatsu, Japan
| | - Yuan-Sheng Zang
- Department of Medical Oncology, Changzheng Hospital, Naval Medical University, Shanghai, China
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18
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Yang J, Hui Y, Zhang Y, Zhang M, Ji B, Tian G, Guo Y, Tang M, Li L, Guo B, Ma T. Application of Circulating Tumor DNA as a Biomarker for Non-Small Cell Lung Cancer. Front Oncol 2021; 11:725938. [PMID: 34422670 PMCID: PMC8375502 DOI: 10.3389/fonc.2021.725938] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 07/19/2021] [Indexed: 12/21/2022] Open
Abstract
Background Non-small cell lung cancer (NSCLC) is one of the most prevalent causes of cancer-related death worldwide. Recently, there are many important medical advancements on NSCLC, such as therapies based on tyrosine kinase inhibitors and immune checkpoint inhibitors. Most of these therapies require tumor molecular testing for selecting patients who would benefit most from them. As invasive biopsy is highly risky, NSCLC molecular testing based on liquid biopsy has received more and more attention recently. Objective We aimed to introduce liquid biopsy and its potential clinical applications in NSCLC patients, including cancer diagnosis, treatment plan prioritization, minimal residual disease detection, and dynamic monitoring on the response to cancer treatment. Method We reviewed recent studies on circulating tumor DNA (ctDNA) testing, which is a minimally invasive approach to identify the presence of tumor-related mutations. In addition, we evaluated potential clinical applications of ctDNA as blood biomarkers for advanced NSCLC patients. Results Most studies have indicated that ctDNA testing is critical in diagnosing NSCLC, predicting clinical outcomes, monitoring response to targeted therapies and immunotherapies, and detecting cancer recurrence. Moreover, the changes of ctDNA levels are associated with tumor mutation burden and cancer progression. Conclusion The ctDNA testing is promising in guiding the therapies on NSCLC patients.
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Affiliation(s)
- Jialiang Yang
- Chifeng Municipal Hospital, Chifeng, China.,Qingdao Geneis Institute of Big Data Mining and Precision Medicine, Qingdao, China.,Geneis Beijing Co., Ltd., Beijing, China
| | - Yan Hui
- Chifeng Municipal Hospital, Chifeng, China
| | | | | | - Binbin Ji
- Qingdao Geneis Institute of Big Data Mining and Precision Medicine, Qingdao, China.,Geneis Beijing Co., Ltd., Beijing, China
| | - Geng Tian
- Qingdao Geneis Institute of Big Data Mining and Precision Medicine, Qingdao, China.,Geneis Beijing Co., Ltd., Beijing, China
| | - Yangqiang Guo
- China National Intellectual Property Administration, Beijing, China
| | - Min Tang
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | | | - Bella Guo
- Genetron Health (Beijing) Co. Ltd., Beijing, China
| | - Tonghui Ma
- Genetron Health (Beijing) Co. Ltd., Beijing, China
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19
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Macías M, Cañada-Higueras E, Alegre E, Bielsa A, Gracia J, Patiño-García A, Ferrer-Costa R, Sendino T, Andueza MP, Mateos B, Rodríguez J, Corral J, Gúrpide A, Lopez-Picazo JM, Perez-Gracia JL, Gil-Bazo I, Alkorta-Aranburu G, González Á. Performance comparison of two next-generation sequencing panels to detect actionable mutations in cell-free DNA in cancer patients. Clin Chem Lab Med 2021; 58:1341-1348. [PMID: 32623849 DOI: 10.1515/cclm-2019-1267] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 02/10/2020] [Indexed: 02/06/2023]
Abstract
Background Genomic alterations studies in cell-free DNA (cfDNA) have increasing clinical use in oncology. Next-generation sequencing (NGS) technology provides the most complete mutational analysis, but nowadays limited data are available related to the comparison of results reported by different platforms. Here we compare two NGS panels for cfDNA: Oncomine™ Pan-Cancer Cell-Free Assay (Thermo Fisher Scientific), suitable for clinical laboratories, and Guardant360® (GuardantHealth), with more genes targeted but only available in an outsourcing laboratory. Methods Peripheral blood was obtained from 16 advanced cancer patients in which Guardant360® (G360) was requested as part of their clinical assistance. Blood samples were sent to be analyzed with G360 panel, and an additional blood sample was drawn to obtain and analyze cfDNA with Oncomine™ Pan-Cancer (OM) panel in an Ion GeneStudio S5™ System. Results cfDNA analysis globally rendered 101 mutations. Regarding the 55/101 mutations claimed to be included by manufacturers in both panels, 17 mutations were reported only by G360, 10 only by OM and 28 by both. In those coincident cases, there was a high correlation between the variant allele fractions (VAFs) calculated with each panel (r = 0.979, p < 0.01). Regarding the six actionable mutations with an FDA-approved therapy reported by G360, one was missed with OM. Also, 12 mutations with clinical trials available were reported by G360 but not by OM. Conclusions In summary, G360 and OM can produce different mutational profile in the same sample, even in genes included in both panels, which is especially important if these mutations are potentially druggable.
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Affiliation(s)
- Mónica Macías
- Service of Biochemistry, Clínica Universidad de Navarra, Pamplona, Spain
| | | | - Estibaliz Alegre
- Service of Biochemistry, Clínica Universidad de Navarra, Pamplona, Spain.,IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Arancha Bielsa
- CIMA LAB Diagnostics Universidad de Navarra, Pamplona, Spain
| | - Javier Gracia
- CIMA LAB Diagnostics Universidad de Navarra, Pamplona, Spain
| | - Ana Patiño-García
- CIMA LAB Diagnostics Universidad de Navarra, Pamplona, Spain.,IdiSNA, Navarra Institute for Health Research, Pamplona, Spain.,Department of Pediatrics, Clínica Universidad de Navarra, Pamplona, Spain
| | - Roser Ferrer-Costa
- Department of Biochemistry, Hospital Universitari Vall D'Hebron, Universitat Autònoma De Barcelona, Barcelona, Spain
| | - Teresa Sendino
- Service of Biochemistry, Clínica Universidad de Navarra, Pamplona, Spain
| | - María P Andueza
- Department of Oncology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Beatriz Mateos
- Service of Biochemistry, Clínica Universidad de Navarra, Pamplona, Spain
| | - Javier Rodríguez
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain.,Department of Oncology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Jesús Corral
- CIMA LAB Diagnostics Universidad de Navarra, Pamplona, Spain
| | - Alfonso Gúrpide
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain.,Department of Oncology, Clínica Universidad de Navarra, Pamplona, Spain
| | - José M Lopez-Picazo
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain.,Department of Oncology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Jose L Perez-Gracia
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain.,Department of Oncology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Ignacio Gil-Bazo
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain.,Department of Oncology, Clínica Universidad de Navarra, Pamplona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Program of Solid Tumors, Center for Applied Medical Research, University of Navarra, Pamplona, Spain
| | | | - Álvaro González
- Service of Biochemistry, Clínica Universidad de Navarra, Pamplona, Spain.,IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
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20
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Ris F, Hellan M, Douissard J, Nieva JJ, Triponez F, Woo Y, Geller D, Buchs NC, Buehler L, Moenig S, Iselin CE, Karenovics W, Petignat P, Lam GT, Undurraga Malinervo M, Tuttle R, Ouellette J, Bose D, Ismail N, Toso C. Blood-Based Multi-Cancer Detection Using a Novel Variant Calling Assay (DEEPGEN TM): Early Clinical Results. Cancers (Basel) 2021; 13:4104. [PMID: 34439258 PMCID: PMC8392437 DOI: 10.3390/cancers13164104] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Revised: 08/02/2021] [Accepted: 08/12/2021] [Indexed: 01/22/2023] Open
Abstract
This is an early clinical analysis of the DEEPGENTM platform for cancer detection. Newly diagnosed cancer patients and individuals with no known malignancy were included in a prospective open-label case-controlled study (NCT03517332). Plasma cfDNA that was extracted from peripheral blood was sequenced and data were processed using machine-learning algorithms to derive cancer prediction scores. A total of 260 cancer patients and 415 controls were included in the study. Overall, sensitivity for all cancers was 57% (95% CI: 52, 64) at 95% specificity, and 43% (95% CI: 37, 49) at 99% specificity. With 51% sensitivity and 95% specificity for all stage 1 cancers, the stage-specific sensitivities trended to improve with higher stages. Early results from this preliminary clinical, prospective evaluation of the DEEPGENTM liquid biopsy platform suggests the platform offers a clinically relevant ability to differentiate individuals with and without known cancer, even at early stages of cancer.
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Affiliation(s)
- Frederic Ris
- Division of Visceral Surgery, Department of Surgery, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (J.D.); (N.C.B.); (S.M.); (N.I.); (C.T.)
| | - Minia Hellan
- Surgical Oncology, Wright State University, Dayton, OH 45435, USA; (M.H.); (R.T.); (J.O.)
| | - Jonathan Douissard
- Division of Visceral Surgery, Department of Surgery, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (J.D.); (N.C.B.); (S.M.); (N.I.); (C.T.)
| | - Jorge J. Nieva
- Norris Cancer Center, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA;
| | - Frederic Triponez
- Division of Thoracic Surgery, Department of Surgery, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (F.T.); (W.K.)
| | - Yanghee Woo
- Division of Surgical Oncology, Department of Surgery and Cancer Immunotherapeutics Program, City of Hope, Duarte, CA 91010, USA;
| | - David Geller
- Department of Surgery, University of Pittsburgh, Pittsburg, PA 15260, USA;
| | - Nicolas C. Buchs
- Division of Visceral Surgery, Department of Surgery, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (J.D.); (N.C.B.); (S.M.); (N.I.); (C.T.)
| | - Leo Buehler
- Division of Visceral Surgery, Department of Surgery, University Hospital Fribourg, 1700 Fribourg, Switzerland;
| | - Stefan Moenig
- Division of Visceral Surgery, Department of Surgery, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (J.D.); (N.C.B.); (S.M.); (N.I.); (C.T.)
| | - Christophe E. Iselin
- Division of Urology, Department of Surgery, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland;
| | - Wolfram Karenovics
- Division of Thoracic Surgery, Department of Surgery, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (F.T.); (W.K.)
| | - Patrick Petignat
- Divison of Gynecology, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (P.P.); (G.T.L.); (M.U.M.)
| | - Giang Thanh Lam
- Divison of Gynecology, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (P.P.); (G.T.L.); (M.U.M.)
| | - Manuela Undurraga Malinervo
- Divison of Gynecology, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (P.P.); (G.T.L.); (M.U.M.)
| | - Rebecca Tuttle
- Surgical Oncology, Wright State University, Dayton, OH 45435, USA; (M.H.); (R.T.); (J.O.)
| | - James Ouellette
- Surgical Oncology, Wright State University, Dayton, OH 45435, USA; (M.H.); (R.T.); (J.O.)
| | - Debashish Bose
- The Center for Hepatobiliary Disease, Mercy, Baltimore, MD 21202, USA;
| | - Nael Ismail
- Division of Visceral Surgery, Department of Surgery, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (J.D.); (N.C.B.); (S.M.); (N.I.); (C.T.)
| | - Christian Toso
- Division of Visceral Surgery, Department of Surgery, University Hospital Geneva and Medical School, 1211 Geneva, Switzerland; (J.D.); (N.C.B.); (S.M.); (N.I.); (C.T.)
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21
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Li M, Xie S, Lu C, Zhu L, Zhu L. Application of Data Science in Circulating Tumor DNA Detection: A Promising Avenue Towards Liquid Biopsy. Front Oncol 2021; 11:692322. [PMID: 34367974 PMCID: PMC8337081 DOI: 10.3389/fonc.2021.692322] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 07/05/2021] [Indexed: 01/10/2023] Open
Abstract
The circulating tumor DNA (ctDNA), as a promising biomarker of liquid biopsy, has potential clinical relevance on the molecular diagnosis and monitoring of cancer. However, the trace concentration level of ctDNA in the peripheral blood restricts its extensive clinical application. Recently, high-throughput-based methodologies have been leveraged to improve the sensitivity and specificity of ctDNA detection, showing a promising avenue towards liquid biopsy. This review briefly summarizes the high-throughput data features concerned by current ctDNA detection strategies and the technical obstacles, potential solutions, and clinical relevance of current ctDNA profiling technologies. We also highlight future directions improving the limit of detection of ctDNA for better clinical application. This review may serve as a reference for the crosslinks between data science and ctDNA-based liquid biopsy, benefiting clinical translation in advanced cancer diagnosis.
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Affiliation(s)
| | | | | | - Lingyun Zhu
- Department of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, China
| | - Lvyun Zhu
- Department of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, China
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22
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Finkle JD, Boulos H, Driessen TM, Lo C, Blidner RA, Hafez A, Khan AA, Lozac'hmeur A, McKinnon KE, Perera J, Zhu W, Dowlati A, White KP, Tell R, Beaubier N. Validation of a liquid biopsy assay with molecular and clinical profiling of circulating tumor DNA. NPJ Precis Oncol 2021; 5:63. [PMID: 34215841 PMCID: PMC8253837 DOI: 10.1038/s41698-021-00202-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 05/28/2021] [Indexed: 11/09/2022] Open
Abstract
Liquid biopsy is a valuable precision oncology tool that is increasingly used as a non-invasive approach to identify biomarkers, detect resistance mutations, monitor disease burden, and identify early recurrence. The Tempus xF liquid biopsy assay is a 105-gene, hybrid-capture, next-generation sequencing (NGS) assay that detects single-nucleotide variants, insertions/deletions, copy number variants, and chromosomal rearrangements. Here, we present extensive validation studies of the xF assay using reference standards, cell lines, and patient samples that establish high sensitivity, specificity, and accuracy in variant detection. The Tempus xF assay is highly concordant with orthogonal methods, including ddPCR, tumor tissue-based NGS assays, and another commercial plasma-based NGS assay. Using matched samples, we developed a dynamic filtering method to account for germline mutations and clonal hematopoiesis, while significantly decreasing the number of false-positive variants reported. Additionally, we calculated accurate circulating tumor fraction estimates (ctFEs) using the Off-Target Tumor Estimation Routine (OTTER) algorithm for targeted-panel sequencing. In a cohort of 1,000 randomly selected cancer patients who underwent xF testing, we found that ctFEs correlated with disease burden and clinical outcomes. These results highlight the potential of serial testing to monitor treatment efficacy and disease course, providing strong support for incorporating liquid biopsy in the management of patients with advanced disease.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Wei Zhu
- Tempus Labs, Chicago, IL, USA
| | - Afshin Dowlati
- University Hospitals Seidman Cancer Center, Cleveland, OH, USA
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23
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Nteliopoulos G, Page K, Hills A, Howarth K, Emmett W, Green E, Martinson LJ, Fernadez-Garcia D, Hastings R, Guttery DS, Kenny L, Stebbing J, Cleator S, Rehman F, Gleason KLT, Sanela A, Ion C, Rushton AJ, Rosenfeld N, Coombes RC, Shaw JA. Comparison of two targeted ultra-deep sequencing technologies for analysis of plasma circulating tumour DNA in endocrine-therapy-resistant breast cancer patients. Breast Cancer Res Treat 2021; 188:465-476. [PMID: 34097174 PMCID: PMC8260509 DOI: 10.1007/s10549-021-06220-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 03/30/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE There is growing interest in the application of circulating tumour DNA (ctDNA) as a sensitive tool for monitoring tumour evolution and guiding targeted therapy in patients with cancer. However, robust comparisons of different platform technologies are still required. Here we compared the InVisionSeq™ ctDNA Assay with the Oncomine™ Breast cfDNA Assay to assess their concordance and feasibility for the detection of mutations in plasma at low (< 0.5%) variant allele fraction (VAF). METHODS Ninety-six plasma samples from 50 patients with estrogen receptor (ER)-positive metastatic breast cancer (mBC) were profiled using the InVision Assay. Results were compared to the Oncomine assay in 30 samples from 26 patients, where there was sufficient material and variants were covered by both assays. Longitudinal samples were analysed for 8 patients with endocrine resistance. RESULTS We detected alterations in 59/96 samples from 34/50 patients analysed with the InVision assay, most frequently affecting ESR1, PIK3CA and TP53. Complete or partial concordance was found in 28/30 samples analysed by both assays, and VAF values were highly correlated. Excellent concordance was found for most genes, and most discordant calls occurred at VAF < 1%. In longitudinal samples from progressing patients with endocrine resistance, we detected consistent alterations in sequential samples, most commonly in ESR1 and PIK3CA. CONCLUSION This study shows that both ultra-deep next-generation sequencing (NGS) technologies can detect genomic alternations even at low VAFs in plasma samples of mBC patients. The strong agreement of the technologies indicates sufficient reproducibility for clinical use as prognosic and predictive biomarker.
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Affiliation(s)
- Georgios Nteliopoulos
- Department of Surgery and Cancer, Division of Cancer, Imperial College London, London, UK
| | - Karen Page
- Department of Genetics and Genome Biology and Leicester Cancer Research Centre, College of Life Sciences, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - Allison Hills
- Department of Surgery and Cancer, Division of Cancer, Imperial College London, London, UK
| | | | | | | | - Luke J Martinson
- Department of Genetics and Genome Biology and Leicester Cancer Research Centre, College of Life Sciences, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - Daniel Fernadez-Garcia
- Department of Genetics and Genome Biology and Leicester Cancer Research Centre, College of Life Sciences, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - Robert Hastings
- Department of Genetics and Genome Biology and Leicester Cancer Research Centre, College of Life Sciences, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - David S Guttery
- Department of Genetics and Genome Biology and Leicester Cancer Research Centre, College of Life Sciences, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - Laura Kenny
- Department of Medical Oncology, Imperial College London, Charing Cross Hospital, London, UK
| | - Justin Stebbing
- Department of Medical Oncology, Imperial College London, Charing Cross Hospital, London, UK
| | - Susan Cleator
- Department of Medical Oncology, Imperial College London, Charing Cross Hospital, London, UK
| | - Farah Rehman
- Department of Medical Oncology, Imperial College London, Charing Cross Hospital, London, UK
| | - Kelly L T Gleason
- Department of Medical Oncology, Imperial College London, Charing Cross Hospital, London, UK
| | - Andrijac Sanela
- Department of Medical Oncology, Imperial College London, Charing Cross Hospital, London, UK
| | - Charlotte Ion
- Department of Medical Oncology, Imperial College London, Charing Cross Hospital, London, UK
| | - Amelia J Rushton
- Department of Surgery and Cancer, Division of Cancer, Imperial College London, London, UK
| | | | - R Charles Coombes
- Department of Surgery and Cancer, Division of Cancer, Imperial College London, London, UK
| | - Jacqueline A Shaw
- Department of Genetics and Genome Biology and Leicester Cancer Research Centre, College of Life Sciences, University of Leicester, University Road, Leicester, LE1 7RH, UK.
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24
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Borkowska EM, Barańska M, Kowalczyk M, Pietruszewska W. Detection of PIK3CA Gene Mutation in Head and Neck Squamous Cell Carcinoma Using Droplet Digital PCR and RT-qPCR. Biomolecules 2021; 11:818. [PMID: 34072735 PMCID: PMC8227819 DOI: 10.3390/biom11060818] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/18/2021] [Accepted: 05/25/2021] [Indexed: 12/11/2022] Open
Abstract
Head and neck squamous cell carcinomas (HNSCC) are the seventh cause of human malignancy with low survival rate due to late diagnosis and treatment. Its etiology is diverse; however genetic factors are significant. The most common mutations in HNSCC were found in the genes: PIK3CA (10-12%), BRCA1 (6%), and BRCA2 (7-9%). In some cases, these biomarkers correlate with recurrences or survival showing a potential of prognostic and predictive value. A total of 113 formalin-fixed paraffin embedded (FFPE) tumor samples were collected from patients with HNSCC (oral cavity: 35 (31.0%); oropharynx: 30 (26.0%); larynx: 48 (43.0%)). We examined PIK3CA H1047R mutation by Real Time PCR (RT-qPCR) and droplet digital PCR (ddPCR). BRCA1 and BRCA2 mutations were analyzed by RT-qPCR while p16 protein expression was assessed by immunohistochemistry. Finally, we identified HPV infection by RT-qPCR. The relationships between genomic alterations and clinical parameters were assessed using the Yates' corrected Chi-squared test or Fisher's exact test for nominal variables. Kaplan Meier plots were applied for survival analysis. Our results revealed 9 PIK3CA H1047R mutations detected by ddPCR: 8 of them were negative in RT-qPCR. Due to the use of different methods to test the presence of the PIK3CA gene mutation, different treatment decisions might be made. That is why it is so important to use the most sensitive methods available. We confirmed the usefulness of ddPCR in the PIK3CA mutation assessment in FFPE samples.
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Affiliation(s)
- Edyta M. Borkowska
- Department of Clinical Genetics Chair of Laboratory and Clinical Genetics, Medical University of Lodz, 92-213 Lodz, Poland;
| | - Magda Barańska
- Department of Otolaryngology, Head and Neck Oncology, Medical University of Lodz, 93-143 Lodz, Poland; (M.B.); (M.K.)
| | - Magdalena Kowalczyk
- Department of Otolaryngology, Head and Neck Oncology, Medical University of Lodz, 93-143 Lodz, Poland; (M.B.); (M.K.)
| | - Wioletta Pietruszewska
- Department of Otolaryngology, Head and Neck Oncology, Medical University of Lodz, 93-143 Lodz, Poland; (M.B.); (M.K.)
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25
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Garcia J, Kamps-Hughes N, Geiguer F, Couraud S, Sarver B, Payen L, Ionescu-Zanetti C. Sensitivity, specificity, and accuracy of a liquid biopsy approach utilizing molecular amplification pools. Sci Rep 2021. [PMID: 34031447 DOI: 10.1038/s41598‐021‐89592‐8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Circulating cell-free DNA (cfDNA) has the potential to be a specific biomarker for the therapeutic management of lung cancer patients. Here, a new sequencing error-reduction method based on molecular amplification pools (MAPs) was utilized to analyze cfDNA in lung cancer patients. We determined the accuracy of MAPs plasma sequencing with respect to droplet digital polymerase chain reaction assays (ddPCR), and tested whether actionable mutation discovery is improved by next-generation sequencing (NGS) in a clinical setting. This study reports data from 356 lung cancer patients receiving plasma testing as part of routine clinical management. Sequencing of cfDNA via MAPs had a sensitivity of 98.5% and specificity 98.9%. The ddPCR assay was used as the reference, since it is an established, accurate assay that can be performed contemporaneously on the same plasma sample. MAPs sequencing detected somatic variants in 261 of 356 samples (73%). Non-actionable clonal hematopoiesis-associated variants were identified via sequencing in 21% of samples. The accuracy of this cfDNA sequencing approach was similar to that of ddPCR assays in a clinical setting, down to an allele frequency of 0.1%. Due to broader coverage and high sensitivity for insertions and deletions, sequencing via MAPs afforded important detection of additional actionable mutations.
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Affiliation(s)
- Jessica Garcia
- Laboratoire de Biochimie Et Biologie Moléculaire, Groupe Hospitalier Sud, Hospices Civils de Lyon, 69495, Pierre Bénite, France.,CIRculating CANcer (CIRCAN) Program, Hospices Civils de Lyon Cancer Institute, 69495, Pierre Bénite, France
| | | | - Florence Geiguer
- Laboratoire de Biochimie Et Biologie Moléculaire, Groupe Hospitalier Sud, Hospices Civils de Lyon, 69495, Pierre Bénite, France.,CIRculating CANcer (CIRCAN) Program, Hospices Civils de Lyon Cancer Institute, 69495, Pierre Bénite, France
| | - Sébastien Couraud
- CIRculating CANcer (CIRCAN) Program, Acute Respiratory Disease and Thoracic Oncology Department, Lyon Sud Hospital, Cancer Institute of Hospices Civils de Lyon, Lyon, France
| | | | - Léa Payen
- Laboratoire de Biochimie Et Biologie Moléculaire, Groupe Hospitalier Sud, Hospices Civils de Lyon, 69495, Pierre Bénite, France.,CIRculating CANcer (CIRCAN) Program, Hospices Civils de Lyon Cancer Institute, 69495, Pierre Bénite, France
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26
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Garcia J, Kamps-Hughes N, Geiguer F, Couraud S, Sarver B, Payen L, Ionescu-Zanetti C. Sensitivity, specificity, and accuracy of a liquid biopsy approach utilizing molecular amplification pools. Sci Rep 2021; 11:10761. [PMID: 34031447 PMCID: PMC8144209 DOI: 10.1038/s41598-021-89592-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 04/19/2021] [Indexed: 02/07/2023] Open
Abstract
Circulating cell-free DNA (cfDNA) has the potential to be a specific biomarker for the therapeutic management of lung cancer patients. Here, a new sequencing error-reduction method based on molecular amplification pools (MAPs) was utilized to analyze cfDNA in lung cancer patients. We determined the accuracy of MAPs plasma sequencing with respect to droplet digital polymerase chain reaction assays (ddPCR), and tested whether actionable mutation discovery is improved by next-generation sequencing (NGS) in a clinical setting. This study reports data from 356 lung cancer patients receiving plasma testing as part of routine clinical management. Sequencing of cfDNA via MAPs had a sensitivity of 98.5% and specificity 98.9%. The ddPCR assay was used as the reference, since it is an established, accurate assay that can be performed contemporaneously on the same plasma sample. MAPs sequencing detected somatic variants in 261 of 356 samples (73%). Non-actionable clonal hematopoiesis-associated variants were identified via sequencing in 21% of samples. The accuracy of this cfDNA sequencing approach was similar to that of ddPCR assays in a clinical setting, down to an allele frequency of 0.1%. Due to broader coverage and high sensitivity for insertions and deletions, sequencing via MAPs afforded important detection of additional actionable mutations.
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Affiliation(s)
- Jessica Garcia
- Laboratoire de Biochimie Et Biologie Moléculaire, Groupe Hospitalier Sud, Hospices Civils de Lyon, 69495, Pierre Bénite, France
- CIRculating CANcer (CIRCAN) Program, Hospices Civils de Lyon Cancer Institute, 69495, Pierre Bénite, France
| | | | - Florence Geiguer
- Laboratoire de Biochimie Et Biologie Moléculaire, Groupe Hospitalier Sud, Hospices Civils de Lyon, 69495, Pierre Bénite, France
- CIRculating CANcer (CIRCAN) Program, Hospices Civils de Lyon Cancer Institute, 69495, Pierre Bénite, France
| | - Sébastien Couraud
- CIRculating CANcer (CIRCAN) Program, Acute Respiratory Disease and Thoracic Oncology Department, Lyon Sud Hospital, Cancer Institute of Hospices Civils de Lyon, Lyon, France
| | | | - Léa Payen
- Laboratoire de Biochimie Et Biologie Moléculaire, Groupe Hospitalier Sud, Hospices Civils de Lyon, 69495, Pierre Bénite, France
- CIRculating CANcer (CIRCAN) Program, Hospices Civils de Lyon Cancer Institute, 69495, Pierre Bénite, France
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Hicks JK, Howard R, Reisman P, Adashek JJ, Fields KK, Gray JE, McIver B, McKee K, O'Leary MF, Perkins RM, Robinson E, Tandon A, Teer JK, Markowitz J, Rollison DE. Integrating Somatic and Germline Next-Generation Sequencing Into Routine Clinical Oncology Practice. JCO Precis Oncol 2021; 5:PO.20.00513. [PMID: 34095711 PMCID: PMC8169076 DOI: 10.1200/po.20.00513] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 02/14/2021] [Accepted: 04/20/2021] [Indexed: 12/27/2022] Open
Abstract
Next-generation sequencing (NGS) is rapidly expanding into routine oncology practice. Genetic variations in both the cancer and inherited genomes are informative for hereditary cancer risk, prognosis, and treatment strategies. Herein, we focus on the clinical perspective of integrating NGS results into patient care to assist with therapeutic decision making. Five key considerations are addressed for operationalization of NGS testing and application of results to patient care as follows: (1) NGS test ordering and workflow design; (2) result reporting, curation, and storage; (3) clinical consultation services that provide test interpretations and identify opportunities for molecularly guided therapy; (4) presentation of genetic information within the electronic health record; and (5) education of providers and patients. Several of these key considerations center on informatics tools that support NGS test ordering and referencing back to the results for therapeutic purposes. Clinical decision support tools embedded within the electronic health record can assist with NGS test utilization and identifying opportunities for targeted therapy including clinical trial eligibility. Challenges for project and change management in operationalizing NGS-supported, evidence-based patient care in the context of current information technology systems with appropriate clinical data standards are discussed, and solutions for overcoming barriers are provided.
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Affiliation(s)
- J. Kevin Hicks
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
| | - Rachel Howard
- Department of Health Informatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Phillip Reisman
- Department of Health Informatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Jacob J. Adashek
- Department of Internal Medicine, University of South Florida, Tampa, FL
| | - Karen K. Fields
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Clinical Pathways, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Jhanelle E. Gray
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Bryan McIver
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Head and Neck-Endocrine Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Kelly McKee
- Department of Clinical Pathways, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Mandy F. O'Leary
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Pathology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Randa M. Perkins
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Clinical Informatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Edmondo Robinson
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Internal Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Ankita Tandon
- Department of Internal Medicine, University of South Florida, Tampa, FL
| | - Jamie K. Teer
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Joseph Markowitz
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Cutaneous Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Dana E. Rollison
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
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Weber ZT, Collier KA, Tallman D, Forman J, Shukla S, Asad S, Rhoades J, Freeman S, Parsons HA, Williams NO, Barroso-Sousa R, Stover EH, Mahdi H, Cibulskis C, Lennon NJ, Ha G, Adalsteinsson VA, Tolaney SM, Stover DG. Modeling clonal structure over narrow time frames via circulating tumor DNA in metastatic breast cancer. Genome Med 2021; 13:89. [PMID: 34016182 PMCID: PMC8136103 DOI: 10.1186/s13073-021-00895-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 04/23/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Circulating tumor DNA (ctDNA) offers minimally invasive means to repeatedly interrogate tumor genomes, providing opportunities to monitor clonal dynamics induced by metastasis and therapeutic selective pressures. In metastatic cancers, ctDNA profiling allows for simultaneous analysis of both local and distant sites of recurrence. Despite the promise of ctDNA sampling, its utility in real-time genetic monitoring remains largely unexplored. METHODS In this exploratory analysis, we characterize high-frequency ctDNA sample series collected over narrow time frames from seven patients with metastatic triple-negative breast cancer, each undergoing treatment with Cabozantinib, a multi-tyrosine kinase inhibitor (NCT01738438, https://clinicaltrials.gov/ct2/show/NCT01738438 ). Applying orthogonal whole exome sequencing, ultra-low pass whole genome sequencing, and 396-gene targeted panel sequencing, we analyzed 42 plasma-derived ctDNA libraries, representing 4-8 samples per patient with 6-42 days between samples. Integrating tumor fraction, copy number, and somatic variant information, we model tumor clonal dynamics, predict neoantigens, and evaluate consistency of genomic information from orthogonal assays. RESULTS We measured considerable variation in ctDNA tumor faction in each patient, often conflicting with RECIST imaging response metrics. In orthogonal sequencing, we found high concordance between targeted panel and whole exome sequencing in both variant detection and variant allele frequency estimation (specificity = 95.5%, VAF correlation, r = 0.949), Copy number remained generally stable, despite resolution limitations posed by low tumor fraction. Through modeling, we inferred and tracked distinct clonal populations specific to each patient and built phylogenetic trees revealing alterations in hallmark breast cancer drivers, including TP53, PIK3CA, CDK4, and PTEN. Our modeling revealed varied responses to therapy, with some individuals displaying stable clonal profiles, while others showed signs of substantial expansion or reduction in prevalence, with characteristic alterations of varied literature annotation in relation to the study drug. Finally, we predicted and tracked neoantigen-producing alterations across time, exposing translationally relevant detection patterns. CONCLUSIONS Despite technical challenges arising from low tumor content, metastatic ctDNA monitoring can aid our understanding of response and progression, while minimizing patient risk and discomfort. In this study, we demonstrate the potential for high-frequency monitoring of evolving genomic features, providing an important step toward scalable, translational genomics for clinical decision making.
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Affiliation(s)
- Zachary T Weber
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, 460 W. 12th Avenue, Columbus, OH, 43210, USA
| | - Katharine A Collier
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, 460 W. 12th Avenue, Columbus, OH, 43210, USA
- Division of Medical Oncology, Department of Medicine, College of Medicine, The Ohio State University, 320 W. 10th Avenue, Columbus, OH, 43210, USA
| | - David Tallman
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, 460 W. 12th Avenue, Columbus, OH, 43210, USA
| | - Juliet Forman
- Broad Institute of Harvard & MIT, 415 Main St., Cambridge, MA, 02412, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Sachet Shukla
- Broad Institute of Harvard & MIT, 415 Main St., Cambridge, MA, 02412, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Sarah Asad
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, 460 W. 12th Avenue, Columbus, OH, 43210, USA
| | - Justin Rhoades
- Broad Institute of Harvard & MIT, 415 Main St., Cambridge, MA, 02412, USA
| | - Samuel Freeman
- Broad Institute of Harvard & MIT, 415 Main St., Cambridge, MA, 02412, USA
| | - Heather A Parsons
- Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Nicole O Williams
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, 460 W. 12th Avenue, Columbus, OH, 43210, USA
- Division of Medical Oncology, Department of Medicine, College of Medicine, The Ohio State University, 320 W. 10th Avenue, Columbus, OH, 43210, USA
| | | | - Elizabeth H Stover
- Broad Institute of Harvard & MIT, 415 Main St., Cambridge, MA, 02412, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Haider Mahdi
- Department of Obstetrics and Gynecology, Cleveland Clinic, Cleveland, OH, 44195, USA
- Department of Surgery, Case Comprehensive Cancer Center, Cleveland, OH, 44106, USA
| | - Carrie Cibulskis
- Broad Institute of Harvard & MIT, 415 Main St., Cambridge, MA, 02412, USA
| | - Niall J Lennon
- Broad Institute of Harvard & MIT, 415 Main St., Cambridge, MA, 02412, USA
| | - Gavin Ha
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | | | - Sara M Tolaney
- Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA
| | - Daniel G Stover
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, 460 W. 12th Avenue, Columbus, OH, 43210, USA.
- Division of Medical Oncology, Department of Medicine, College of Medicine, The Ohio State University, 320 W. 10th Avenue, Columbus, OH, 43210, USA.
- Biomedical Research Tower, Room 984, Ohio State University Comprehensive Cancer Center, Stefanie Spielman Comprehensive Breast Center, Columbus, OH, 43210, USA.
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Wang X, Zhang Y, Niu C, Wang S, Li L, Guo Y, Zhu L, Jin X, Gao H, Xu W, Zhu P, Lan Q, Du M, Cheng X, Gao Y, Dong L. Establishment of primary reference measurement procedures and reference materials for EGFR variant detection in non-small cell lung cancer. Anal Methods 2021; 13:2114-2123. [PMID: 33870958 DOI: 10.1039/d1ay00328c] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Circulating tumor DNA (ctDNA)-based mutation detection is promising to change the clinical practice of genotype-directed therapy for cancer. A growing number of non-invasive tests for cancer screening and monitoring that involve the detection of ctDNA have been commercialized. Primary reference measurement procedures (PRMPs) and reference materials (RMs) are urgently needed to assess the non-invasive tests. In this study, a PRMP based on digital PCR (dPCR) and ctDNA RMs for quantification of the frequently occurring variant in epidermal growth factor receptor (EGFR L858R, T790M, and 19Del) in non-small cell lung cancer (NSCLC) were established. The candidate dPCR PRMP showed high specificity (false positive rate 0-0.003%), good repeatability (coefficient of variance (CV), 2-3% for 104 copies/reaction), and high interlaboratory reproducibility (3-10%). A good linearity (0.97 < slope < 1.03, R2 ≥ 0.9999) between the measured mutant (MU) value and prepared value was observed for all assays over the fractional abundance (FA) range, between 25% and 0.05%. The limit of quantification (LoQ) was determined to be 34 L858R, 23 T790M, and 34 19Del copies/reaction, corresponding to a FA of 0.2%. An inter-laboratory study of using the EGFR ctDNA RMs and dPCR assays demonstrated that the participating laboratories produced consistent concentrations of MU and wild-type (WT), as well as FA. This study demonstrates that dPCR can act as a potential PRMP for EGFR mutation for validation of NSCLC genotyping tests and ctDNA quantitative tests. The PRMP and RMs established here could improve interlaboratory repeatability and reproducibility, which supports rapid translation and application of non-invasive tests into clinical practice.
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Affiliation(s)
- Xia Wang
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing 100029, People's Republic of China.
| | - Yongzhuo Zhang
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing 100029, People's Republic of China.
| | - Chunyan Niu
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing 100029, People's Republic of China.
| | - Shangjun Wang
- Nanjing Institute of Measurement and Testing Technology, Nanjing 210049, People's Republic of China
| | - Liang Li
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China
| | - Yong Guo
- Department of Biomedical Engineering, School of Medicine, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Tsinghua University, Beijing 100084, People's Republic of China
| | - Lingxiang Zhu
- Human Genetic Resource Center, National Research Institute for Health and Family Planning, Beijing 100081, People's Republic of China
| | - Xiaohua Jin
- Human Genetic Resource Center, National Research Institute for Health and Family Planning, Beijing 100081, People's Republic of China
| | - Huafang Gao
- Human Genetic Resource Center, National Research Institute for Health and Family Planning, Beijing 100081, People's Republic of China
| | - Wentao Xu
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science & Nutritional Engineering, China Agricultural University, Beijing 100083, People's Republic of China
| | - Pengyu Zhu
- Chinese Academy of Inspection and Quarantine, Beijing 100176, People's Republic of China
| | - Qingkuo Lan
- Tianjin Institute of Agricultural Quality Standard and Testing Technology, Tianjin Academy of Agricultural Sciences, Tianjin 300381, People's Republic of China
| | - Meihong Du
- Beijing Engineering Technology Research Centre of Gene Sequencing and Gene Function Analysis, Beijing Center for Physical & Chemical Analysis, Beijing 100093, People's Republic of China
| | - Xiaoyan Cheng
- Beijing Engineering Technology Research Centre of Gene Sequencing and Gene Function Analysis, Beijing Center for Physical & Chemical Analysis, Beijing 100093, People's Republic of China
| | - Yunhua Gao
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing 100029, People's Republic of China.
| | - Lianhua Dong
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing 100029, People's Republic of China.
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30
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Hofman P. Next-Generation Sequencing with Liquid Biopsies from Treatment-Naïve Non-Small Cell Lung Carcinoma Patients. Cancers (Basel) 2021; 13:2049. [PMID: 33922637 PMCID: PMC8122958 DOI: 10.3390/cancers13092049] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 04/11/2021] [Accepted: 04/20/2021] [Indexed: 12/16/2022] Open
Abstract
Recently, the liquid biopsy (LB), a non-invasive and easy to repeat approach, has started to compete with the tissue biopsy (TB) for detection of targets for administration of therapeutic strategies for patients with advanced stages of lung cancer at tumor progression. A LB at diagnosis of late stage non-small cell lung carcinoma (NSCLC) is also being performed. It may be asked if a LB can be complementary (according to the clinical presentation or systematics) or even an alternative to a TB for treatment-naïve advanced NSCLC patients. Nucleic acid analysis with a TB by next-generation sequencing (NGS) is gradually replacing targeted sequencing methods for assessment of genomic alterations in lung cancer patients with tumor progression, but also at baseline. However, LB is still not often used in daily practice for NGS. This review addresses different aspects relating to the use of LB for NGS at diagnosis in advanced NSCLC, including its advantages and limitations.
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Affiliation(s)
- Paul Hofman
- Laboratory of Clinical and Experimental Pathology, Université Côte d’Azur, CHU Nice, FHU OncoAge, Pasteur Hospital, 30 avenue de la voie romaine, BP69, CEDEX 01, 06001 Nice, France; ; Tel.: +33-4-92-03-88-55 or +33-4-92-03-87-49; Fax: +33-4-92-88-50
- Hospital-Integrated Biobank BB-0033-00025, Université Côte d’Azur, CHU Nice, FHU OncoAge, 06001 Nice, France
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Ji X, Ning B, Liu J, Roberts R, Lesko L, Tong W, Liu Z, Shi T. Towards population-specific pharmacogenomics in the era of next-generation sequencing. Drug Discov Today 2021; 26:1776-1783. [PMID: 33892143 DOI: 10.1016/j.drudis.2021.04.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 01/22/2021] [Accepted: 04/12/2021] [Indexed: 11/27/2022]
Abstract
Pharmacogenomics (PGx) has essential roles in identifying optimal drug responders, optimizing dosage regimens and avoiding adverse events. Population-specific therapeutic interventions that tackle the genetic root causes of clinical outcomes are an important precision medicine strategy. In this perspective, we discuss next-generation sequencing genotyping and its significance for population-specific PGx applications. We emphasize the potential of NGS for preemptive pharmacogenotyping, which is crucial to population-specific clinical studies and patient care. We also provide examples that use publicly available population-based genomics data for population-specific PGx studies. Last, we discuss the remaining challenges and regulatory efforts towards improvements in this field.
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Affiliation(s)
- Xiangjun Ji
- The Center for Bioinformatics and Computational Biology, The Institute of Biomedical Sciences and School of Life Sciences, School of Statistics, East China Normal University, Shanghai 200241, China; Guangdong Provincial Key Laboratory of Proteomics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Baitang Ning
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA
| | - Jinghua Liu
- Guangdong Provincial Key Laboratory of Proteomics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Ruth Roberts
- ApconiX, BioHub at Alderley Park, Alderley Edge SK10 4TG, UK; University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Larry Lesko
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, FL, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA.
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA.
| | - Tieliu Shi
- The Center for Bioinformatics and Computational Biology, The Institute of Biomedical Sciences and School of Life Sciences, School of Statistics, East China Normal University, Shanghai 200241, China; Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Rd., Jefferson, AR 72079, USA; National Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, China.
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32
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Gong B, Li D, Kusko R, Novoradovskaya N, Zhang Y, Wang S, Pabón-Peña C, Zhang Z, Lai K, Cai W, LoCoco JS, Lader E, Richmond TA, Mittal VK, Liu LC, Johann DJ, Willey JC, Bushel PR, Yu Y, Xu C, Chen G, Burgess D, Cawley S, Giorda K, Haseley N, Qiu F, Wilkins K, Arib H, Attwooll C, Babson K, Bao L, Bao W, Lucas AB, Best H, Bhandari A, Bisgin H, Blackburn J, Blomquist TM, Boardman L, Burgher B, Butler DJ, Chang CJ, Chaubey A, Chen T, Chierici M, Chin CR, Close D, Conroy J, Cooley Coleman J, Craig DJ, Crawford E, Del Pozo A, Deveson IW, Duncan D, Eterovic AK, Fan X, Foox J, Furlanello C, Ghosal A, Glenn S, Guan M, Haag C, Hang X, Happe S, Hennigan B, Hipp J, Hong H, Horvath K, Hu J, Hung LY, Jarosz M, Kerkhof J, Kipp B, Kreil DP, Łabaj P, Lapunzina P, Li P, Li QZ, Li W, Li Z, Liang Y, Liu S, Liu Z, Ma C, Marella N, Martín-Arenas R, Megherbi DB, Meng Q, Mieczkowski PA, Morrison T, Muzny D, Ning B, Parsons BL, Paweletz CP, Pirooznia M, Qu W, Raymond A, Rindler P, Ringler R, Sadikovic B, Scherer A, Schulze E, Sebra R, Shaknovich R, Shi Q, Shi T, Silla-Castro JC, Smith M, López MS, Song P, Stetson D, Strahl M, Stuart A, Supplee J, Szankasi P, Tan H, Tang LY, Tao Y, Thakkar S, Thierry-Mieg D, Thierry-Mieg J, Thodima VJ, Thomas D, Tichý B, Tom N, Garcia EV, Verma S, Walker K, Wang C, Wang J, Wang Y, Wen Z, Wirta V, Wu L, Xiao C, Xiao W, Xu S, Yang M, Ying J, Yip SH, Zhang G, Zhang S, Zhao M, Zheng Y, Zhou X, Mason CE, Mercer T, Tong W, Shi L, Jones W, Xu J. Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions. Genome Biol 2021; 22:109. [PMID: 33863344 PMCID: PMC8051090 DOI: 10.1186/s13059-021-02315-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 03/18/2021] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Targeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing. RESULTS All panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5-20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden. CONCLUSION This comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.
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Affiliation(s)
- Binsheng Gong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Dan Li
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Rebecca Kusko
- Immuneering Corporation, One Broadway, 14th Floor, Cambridge, MA, 02142, USA
| | | | - Yifan Zhang
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
- Department of Information Science, University of Arkansas at Little Rock, 2801 S. Univ. Ave, Little Rock, AR, 72204, USA
| | - Shangzi Wang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Carlos Pabón-Peña
- Agilent Technologies, 5301 Stevens Creek Blvd, Santa Clara, CA, 95051, USA
| | - Zhihong Zhang
- Research and Development, Burning Rock Biotech, Shanghai, 201114, China
| | - Kevin Lai
- Bioinformatics, Integrated DNA Technologies, Inc., 1710 Commercial Park, Coralville, IA, 52241, USA
| | - Wanshi Cai
- iGeneTech, 8 Shengmingyuan Rd., Zhongguancun Life Science Park, Changping District, Beijing, 100080, China
| | | | - Eric Lader
- Research and Development, QIAGEN Sciences Inc., Frederick, MD, 21703, USA
| | - Todd A Richmond
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., 4300 Hacienda Dr, Pleasanton, CA, 94588, USA
| | - Vinay K Mittal
- Thermo Fisher Scientific, 110 Miller Ave, Ann Arbor, MI, 48104, USA
| | - Liang-Chun Liu
- Clinical Diagnostic Division, Thermo Fisher Scientific, 46500 Kato Rd, Fremont, CA, 94538, USA
| | - Donald J Johann
- Winthrop P Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W Markham St, Little Rock, AR, 72205, USA
| | - James C Willey
- Departments of Medicine, Pathology, and Cancer Biology, College of Medicine and Life Sciences, University of Toledo Health Sciences Campus, 3000 Arlington Ave, Toledo, OH, 43614, USA
| | - Pierre R Bushel
- National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Chang Xu
- Research and Development, QIAGEN Sciences Inc., Frederick, MD, 21703, USA
| | - Guangchun Chen
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, 5323 Harry Hine Blvd, Dallas, TX, 75390, USA
| | - Daniel Burgess
- Research and Development, Roche Sequencing Solutions Inc., 500 South Rosa Rd, Madison, WI, 53719, USA
| | - Simon Cawley
- Clinical Sequencing Division, Thermo Fisher Scientific, 180 Oyster Point Blvd, South San Francisco, CA, 94080, USA
| | - Kristina Giorda
- Marketing, Integrated DNA Technologies, Inc., 1710 Commercial Park, Coralville, IA, 52241, USA
| | - Nathan Haseley
- Illumina Inc., 5200 Illumina Way, San Diego, CA, 92122, USA
| | - Fujun Qiu
- Research and Development, Burning Rock Biotech, Shanghai, 201114, China
| | - Katherine Wilkins
- Agilent Technologies, 5301 Stevens Creek Blvd, Santa Clara, CA, 95051, USA
| | - Hanane Arib
- Icahn Institute and Dept. of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | | | - Kevin Babson
- Greenwood Genetic Center, 106 Gregor Mendel Circle, Greenwood, SC, 29646, USA
| | - Longlong Bao
- Department of Pathology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Institute of Pathology, Fudan University, Shanghai, 200032, China
| | - Wenjun Bao
- JMP Life Sciences, SAS Institute Inc., Cary, NC, 27519, USA
| | | | - Hunter Best
- Departments of Pathology and Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, 84108, USA
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, 500 Chipeta Way, Salt Lake City, UT, 84108, USA
| | | | - Halil Bisgin
- Department of Computer Science, Engineering and Physics, University of Michigan-Flint, Flint, MI, 48502, USA
| | - James Blackburn
- Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, University of New South Wales, Sydney, NSW, 2010, Australia
| | - Thomas M Blomquist
- Department of Pathology, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA
- Lucas County Coroner's Office, 2595 Arlington Ave., Toledo, OH, 43614, USA
| | - Lisa Boardman
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Blake Burgher
- OmniSeq, Inc. 700 Ellicott St, Buffalo, NY, 14203, USA
| | - Daniel J Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | - Chia-Jung Chang
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA
| | - Alka Chaubey
- Greenwood Genetic Center, 106 Gregor Mendel Circle, Greenwood, SC, 29646, USA
| | - Tao Chen
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | | | - Christopher R Chin
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | - Devin Close
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, 500 Chipeta Way, Salt Lake City, UT, 84108, USA
| | | | | | - Daniel J Craig
- Department of Medicine, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA
| | - Erin Crawford
- Department of Medicine, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA
| | - Angela Del Pozo
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
| | - Ira W Deveson
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Daniel Duncan
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - Agda Karina Eterovic
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, 6565 MD Anderson Blvd, Houston, TX, 77030, USA
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | | | | | - Sean Glenn
- OmniSeq, Inc. 700 Ellicott St, Buffalo, NY, 14203, USA
| | - Meijian Guan
- JMP Life Sciences, SAS Institute Inc., Cary, NC, 27519, USA
| | - Christine Haag
- Molecular Laboratory, Prof. F. Raue, Im Weiher 12, Heidelberg, Germany
| | - Xinyi Hang
- iGeneTech, 8 Shengmingyuan Rd., Zhongguancun Life Science Park, Changping District, Beijing, 100080, China
| | - Scott Happe
- Agilent Technologies, 1834 State Hwy 71 West, Cedar Creek, TX, 78612, USA
| | - Brittany Hennigan
- Greenwood Genetic Center, 106 Gregor Mendel Circle, Greenwood, SC, 29646, USA
| | - Jennifer Hipp
- Department of Pathology, Strata Oncology, Inc., Ann Arbor, MI, 48103, USA
| | - Huixiao Hong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Kyle Horvath
- ResearchDx, Inc., 5 Mason, Irvine, CA, 92618, USA
| | - Jianhong Hu
- Human Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA
| | - Li-Yuan Hung
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Mirna Jarosz
- NGS Products and Services, Integrated DNA Technologies, Inc., 1710 Commercial Park, Coralville, IA, 52241, USA
| | - Jennifer Kerkhof
- Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, 800 Commissioners Rd E, London, Ontario, N6A5W9, Canada
| | - Benjamin Kipp
- Division of Anatomic Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - David Philip Kreil
- Bioinformatics Research, Institute of Molecular Biotechnology, Boku University Vienna, Vienna, Austria
| | - Paweł Łabaj
- Małopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
- Department of Biotechnology, Boku University, Vienna, Austria
| | - Pablo Lapunzina
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, IdiPaz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
- ITHACA, European Reference Network on Rare Congenital Malformations and Rare Intellectual Disability, European Commission, Lille, France
| | - Peng Li
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Quan-Zhen Li
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, 5323 Harry Hine Blvd, Dallas, TX, 75390, USA
| | - Weihua Li
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Zhiguang Li
- Center of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, China
| | - Yu Liang
- Geneis, 5 Guangshun North St., Chaoyang District, Beijing, 100102, China
| | - Shaoqing Liu
- GeneSmile Ltd Co., Jiangsu Cancer Hospital, 42 Baiziting St., Xuanwu District, Nanjing, 210009, Jiangsu, China
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Charles Ma
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - Narasimha Marella
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - Rubén Martín-Arenas
- Genycell Biotech España, Calle Garrido Atienza, 18320 Santa Fe, Granada, Spain
| | - Dalila B Megherbi
- CMINDS Research Center, Department of Electrical and Computer Engineering, College of Engineering, University of Massachusetts Lowell, Lowell, MA, 01854, USA
| | - Qingchang Meng
- Human Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA
| | - Piotr A Mieczkowski
- Department of Genetics, University of North Carolina, 250 Bell Tower Drive, Chapel Hill, NC, 27599, USA
| | - Tom Morrison
- Accugenomics, Inc., 1410 Commonwealth Drive, Suite 105, Wilmington, NC, 20403, USA
| | - Donna Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA
| | - Baitang Ning
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Barbara L Parsons
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Cloud P Paweletz
- Translational Research Laboratory, Belfer Center for Applied Cancer Science, Dana-Farber Cancer Institute, 360 Longwood Ave, Boston, MA, 02215, USA
| | - Mehdi Pirooznia
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Wubin Qu
- iGeneTech, 8 Shengmingyuan Rd., Zhongguancun Life Science Park, Changping District, Beijing, 100080, China
| | - Amelia Raymond
- Astrazeneca Pharmaceuticals, 35 Gatehouse Dr, Waltham, MA, 02451, USA
| | - Paul Rindler
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, 500 Chipeta Way, Salt Lake City, UT, 84108, USA
| | | | - Bekim Sadikovic
- Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, 800 Commissioners Rd E, London, Ontario, N6A5W9, Canada
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, N6A3K7, Canada
| | - Andreas Scherer
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Institute for Molecular Medicine Finland (FIMM), Nordic EMBL Partnership for Molecular Medicine, HiLIFE Unit, Biomedicum Helsinki 2U (D302b), P.O. Box 20, (Tukholmankatu 8), FI-00014 University of Helsinki, Helsinki, Finland
| | - Egbert Schulze
- Laboratory for Molecular Genetics, Endocrine Practice, Im Weiher 12, 69121, Heidelberg, Germany
| | - Robert Sebra
- Icahn Institute and Dept. of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | - Rita Shaknovich
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - Qiang Shi
- Division of Systems Biology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tieliu Shi
- Center for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, 500 Dongchuan Rd, Shanghai, 200241, China
| | | | - Melissa Smith
- Icahn Institute and Dept. of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | - Mario Solís López
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
| | - Ping Song
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, 6565 MD Anderson Blvd, Houston, TX, 77030, USA
| | - Daniel Stetson
- Astrazeneca Pharmaceuticals, 35 Gatehouse Dr, Waltham, MA, 02451, USA
| | - Maya Strahl
- Icahn Institute and Dept. of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | - Alan Stuart
- Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, 800 Commissioners Rd E, London, Ontario, N6A5W9, Canada
| | - Julianna Supplee
- Translational Research Laboratory, Belfer Center for Applied Cancer Science, Dana-Farber Cancer Institute, 360 Longwood Ave, Boston, MA, 02215, USA
| | - Philippe Szankasi
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, 500 Chipeta Way, Salt Lake City, UT, 84108, USA
| | - Haowen Tan
- Primbio Genes Biotechnology, Building C6-501, Biolake, No.666 Gaoxin Ave., East Lake High-tech Development Zone, Wuhan, 430074, Hubei, China
| | - Lin-Ya Tang
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, 6565 MD Anderson Blvd, Houston, TX, 77030, USA
| | - Yonghui Tao
- Department of Pathology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Institute of Pathology, Fudan University, Shanghai, 200032, China
| | - Shraddha Thakkar
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Danielle Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA
| | - Jean Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA
| | - Venkat J Thodima
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - David Thomas
- St Vincent's Clinical School, University of New South Wales, Sydney, NSW, 2010, Australia
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Boris Tichý
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic
| | - Nikola Tom
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic
| | - Elena Vallespin Garcia
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
| | - Suman Verma
- ResearchDx, Inc., 5 Mason, Irvine, CA, 92618, USA
| | - Kimbley Walker
- Human Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA
| | - Charles Wang
- Center for Genomics, School of Medicine, Loma Linda University, Loma Linda, CA, 92350, USA
- Division of Microbiology & Molecular Genetics, Department of Basic Sciences, School of Medicine, Loma Linda University, Loma Linda, CA, 92350, USA
| | - Junwen Wang
- Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Department of Health Sciences, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Yexun Wang
- Research and Development, QIAGEN Sciences Inc., Frederick, MD, 21703, USA
| | - Zhining Wen
- College of Chemistry, Sichuan University, Chengdu, 610064, Sichuan, China
| | - Valtteri Wirta
- Science for Life Laboratory, Karolinska Institutet, Tomtebodavägen 23B, 171 65, Solna, Sweden
| | - Leihong Wu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, MD, 20894, USA
| | - Wenzhong Xiao
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Shibei Xu
- Department of Biostatistics, Columbia Mailman School of Public Health, 722 West 168th St., New York, NY, 10032, USA
| | - Mary Yang
- Department of Information Science, University of Arkansas at Little Rock, 2801 S. Univ. Ave, Little Rock, AR, 72204, USA
| | - Jianming Ying
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Shun H Yip
- Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Center for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China
| | - Guangliang Zhang
- Clinical Laboratory, Burning Rock Biotech, Guangzhou, 510300, Guangdong, China
| | - Sa Zhang
- Clinical Laboratory, Burning Rock Biotech, Guangzhou, 510300, Guangdong, China
| | - Meiru Zhao
- Geneplus, PKUCare Industrial Park, Changping District, Beijing, 102206, China
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Xiaoyan Zhou
- Department of Pathology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Institute of Pathology, Fudan University, Shanghai, 200032, China
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | - Timothy Mercer
- Australian Institute of Bioengineering and Nanotechnology, University of Queensland, Brisbane, QLD, Australia
- Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China.
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
- Fudan-Gospel Joint Research Center for Precision Medicine, Fudan University, Shanghai, 200438, China.
| | - Wendell Jones
- Q2 Solutions - EA Genomics, 5927 S Miami Blvd, Morrisville, NC, 27560, USA.
| | - Joshua Xu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA.
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Abstract
Patient-specific biomarkers form the foundation of precision medicine strategies. To realize the promise of precision medicine in patients with colorectal cancer (CRC), access to cost-effective, convenient, and safe assays is critical. Improvements in diagnostic technology have enabled ultrasensitive and specific assays to identify cell-free DNA (cfDNA) from a routine blood draw. Clinicians are already employing these minimally invasive assays to identify drivers of therapeutic resistance and measure genomic heterogeneity, particularly when tumor tissue is difficult to access or serial sampling is necessary. As cfDNA diagnostic technology continues to improve, more innovative applications are anticipated. In this review, we focus on four clinical applications for cfDNA analysis in the management of CRC: detecting minimal residual disease, monitoring treatment response in the metastatic setting, identifying drivers of treatment sensitivity and resistance, and guiding therapeutic strategies to overcome resistance.
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Affiliation(s)
- Van K Morris
- Department of Gastrointestinal Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA
| | - John H Strickler
- Division of Medical Oncology, Duke University Medical Center, Durham, North Carolina 27710, USA;
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34
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Starks ER, Swanson L, Docking TR, Bosdet I, Munro S, Moore RA, Karsan A. Assessing Limit of Detection in Clinical Sequencing. J Mol Diagn 2021; 23:455-466. [PMID: 33486075 DOI: 10.1016/j.jmoldx.2020.12.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 12/05/2020] [Accepted: 12/30/2020] [Indexed: 10/22/2022] Open
Abstract
Clinical reporting of solid tumor sequencing requires reliable assessment of the accuracy and reproducibility of each assay. Somatic mutation variant allele fractions may be below 10% in many samples due to sample heterogeneity, tumor clonality, and/or sample degradation in fixatives such as formalin. The toolkits available to the clinical sequencing community for correlating assay design parameters with assay sensitivity remain limited, and large-scale empirical assessments are often relied upon due to the lack of clear theoretical grounding. To address this uncertainty, a theoretical model was developed for predicting the expected variant calling sensitivity for a given library complexity and sequencing depth. Binomial models were found to be appropriate when assay sensitivity was only limited by library complexity or sequencing depth, but functional scaling for library complexity was necessary when both library complexity and sequencing depth were co-limiting. This model was empirically validated with sequencing experiments by using a series of DNA input amounts and sequencing depths. Based on these findings, a workflow is proposed for determining the limiting factors to sensitivity in different assay designs, and the formulas for these scenarios are presented. The approach described here provides designers of clinical assays with the methods to theoretically predict assay design outcomes a priori, potentially reducing burden in clinical tumor assay design and validation efforts.
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Affiliation(s)
- Elizabeth R Starks
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, British Columbia, Canada.
| | - Lucas Swanson
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, British Columbia, Canada
| | - T Roderick Docking
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, British Columbia, Canada
| | - Ian Bosdet
- Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Sarah Munro
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, British Columbia, Canada
| | - Richard A Moore
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, British Columbia, Canada
| | - Aly Karsan
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, British Columbia, Canada; Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
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Abstract
INTRODUCTION Fibroblast growth factor receptors (FGFR 1-4) are a highly conserved family of receptor tyrosine kinases, involved in several physiological processes. Genetic aberrations of FGFRs and their ligands, fibroblast growth factors (FGFs) are involved in several pathological processes including cancer. The FGF-FGFR axis has emerged as a treatment target in oncology. Because these aberrations drive cancer progression, the development of FGFR targeted therapies have been accelerated. AREAS COVERED In this comprehensive review, we evaluate molecular pathology and targeted therapies to FGFRs. We reviewed the evidence for safety and efficacy from preclinical and clinical studies (phase I-III) of FGFR targeted therapies. We also discuss potential challenges in bringing these targeted therapies from bench to bedside and the potential opportunities. EXPERT OPINION Despite the challenges of the clinical development of FGFR targeted therapies, two FGFR small-molecule inhibitors, namely Erdafitinib and Pemigatinib, are FDA approved for urothelial cancer and cholangiocarcinoma, respectively. Understanding and detection of FGFR genomic aberrations, protein overexpression and the development of isoform-specific inhibitors are factors in the clinical success of these therapies. An enhanced understanding of patient selection based on a gene signatures or biomarkers is key to success of FGFR targeted therapies.
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Affiliation(s)
- Sreenivasa R Chandana
- Phase I Program, START Midwest , Grand Rapids, MI, USA.,Department of Medical Oncology, Cancer and Hematology Centers of Western Michigan , Grand Rapids, MI, USA.,Department of Medicine, College of Human Medicine, Michigan State University , East Lansing, MI, USA
| | - Hani M Babiker
- Early Phase Clinical Trials Program, University of Arizona Cancer Center , Tucson, AZ, USA
| | - Daruka Mahadevan
- Early Phase Clinical Trials Program, University of Arizona Cancer Center , Tucson, AZ, USA.,Division of Hematology-Oncology, Mays Cancer Center, University of Texas Health San Antonio , San Antonio, TX, USA
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Halbert B, Einstein DJ. Hot or Not: Tumor Mutational Burden (TMB) as a Biomarker of Immunotherapy Response in Genitourinary Cancers. Urology 2020; 147:119-126. [PMID: 33137348 DOI: 10.1016/j.urology.2020.10.030] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 10/19/2020] [Accepted: 10/20/2020] [Indexed: 12/31/2022]
Abstract
Pembrolizumab was recently approved for treatment of cancers with high tumor mutational burden (TMB). We conduct a focused literature review of TMB as a predictive biomarker. TMB quantifies the sum of nonsynonymous coding mutations (typically single nucleotide substitutions and short insertion-deletions) per megabase of sequenced DNA. As a proxy for expression of immunogenic neoantigens, TMB may be an effective predictive biomarker for response to immune checkpoint inhibitors. However, like other biomarkers in this setting, TMB has many limitations; the effect of this FDA approval in the current management of genitourinary cancers is likely limited to select situations.
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Affiliation(s)
- Brian Halbert
- Division of Medical Oncology, Beth Israel Deaconess Medical Center, Boston, MA
| | - David J Einstein
- Division of Medical Oncology, Beth Israel Deaconess Medical Center, Boston, MA.
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37
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Verma S, Moore MW, Ringler R, Ghosal A, Horvath K, Naef T, Anvari S, Cotter PD, Gunn S. Analytical performance evaluation of a commercial next generation sequencing liquid biopsy platform using plasma ctDNA, reference standards, and synthetic serial dilution samples derived from normal plasma. BMC Cancer 2020; 20:945. [PMID: 33004033 PMCID: PMC7528227 DOI: 10.1186/s12885-020-07445-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 09/21/2020] [Indexed: 01/01/2023] Open
Abstract
Background Circulating tumor (ct) DNA assays performed in clinical laboratories provide tumor biomarker testing support for biopharmaceutical clinical trials. Yet it is neither practical nor economically feasible for many of these clinical laboratories to internally develop their own liquid biopsy assay. Commercially available ctDNA kits are a potential solution for laboratories seeking to incorporate liquid biopsy into their test menus. However, the scarcity of characterized patient samples and cost of purchasing validation reference standards creates a barrier to entry. In the current study, we evaluated the analytical performance of the AVENIO ctDNA liquid biopsy platform (Roche Sequencing Solutions) for use in our clinical laboratory. Method Intra-laboratory performance evaluation of AVENIO ctDNA Targeted, Expanded, and Surveillance kits (Research Use Only) was performed according to College of American Pathologists (CAP) guidelines for the validation of targeted next generation sequencing assays using purchased reference standards, de-identified human plasma cell-free (cf) DNA samples, and contrived samples derived from commercially purchased normal and cancer human plasma. All samples were sequenced at read depths relevant to clinical settings using the NextSeq High Output kit (Illumina). Results At the clinically relevant read depth, Avenio ctDNA kits demonstrated 100% sensitivity in detecting single nucleotide variants (SNVs) at ≥0.5% allele frequency (AF) and 50% sensitivity in detecting SNVs at 0.1% AF using 20–40 ng sample input amount. The assay integrated seamlessly into our laboratory’s NGS workflow with input DNA mass, target allele frequency (TAF), multiplexing, and number of reads optimized to support a high-throughput assay appropriate for biopharmaceutical trials. Conclusions Our study demonstrates that AVENIO ctDNA liquid biopsy platform provides a viable alternative for efficient incorporation of liquid biopsy assays into the clinical laboratory for detecting somatic alterations as low as 0.5%. Accurate detection of variants lower than 0.5% could potentially be achieved by deeper sequencing when clinically indicated and economically feasible.
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Affiliation(s)
| | - Mathew W Moore
- ResearchDx, Inc., 5 Mason, Irvine, CA, USA.,PacificDx Clinical Laboratory, 5 Mason, Irvine, CA, USA
| | | | | | | | | | | | - Philip D Cotter
- ResearchDx, Inc., 5 Mason, Irvine, CA, USA.,PacificDx Clinical Laboratory, 5 Mason, Irvine, CA, USA
| | - Shelly Gunn
- ResearchDx, Inc., 5 Mason, Irvine, CA, USA.,PacificDx Clinical Laboratory, 5 Mason, Irvine, CA, USA
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38
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Godsey JH, Silvestro A, Barrett JC, Bramlett K, Chudova D, Deras I, Dickey J, Hicks J, Johann DJ, Leary R, Lee JSH, McMullen J, McShane L, Nakamura K, Richardson AO, Ryder M, Simmons J, Tanzella K, Yee L, Leiman LC. Generic Protocols for the Analytical Validation of Next-Generation Sequencing-Based ctDNA Assays: A Joint Consensus Recommendation of the BloodPAC's Analytical Variables Working Group. Clin Chem 2020; 66:1156-1166. [PMID: 32870995 PMCID: PMC7462123 DOI: 10.1093/clinchem/hvaa164] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 07/07/2020] [Indexed: 12/12/2022]
Abstract
Liquid biopsy, particularly the analysis of circulating tumor DNA (ctDNA), has demonstrated considerable promise for numerous clinical intended uses. Successful validation and commercialization of novel ctDNA tests have the potential to improve the outcomes of patients with cancer. The goal of the Blood Profiling Atlas Consortium (BloodPAC) is to accelerate the development and validation of liquid biopsy assays that will be introduced into the clinic. To accomplish this goal, the BloodPAC conducts research in the following areas: Data Collection and Analysis within the BloodPAC Data Commons; Preanalytical Variables; Analytical Variables; Patient Context Variables; and Reimbursement. In this document, the BloodPAC's Analytical Variables Working Group (AV WG) attempts to define a set of generic analytical validation protocols tailored for ctDNA-based Next-Generation Sequencing (NGS) assays. Analytical validation of ctDNA assays poses several unique challenges that primarily arise from the fact that very few tumor-derived DNA molecules may be present in circulation relative to the amount of nontumor-derived cell-free DNA (cfDNA). These challenges include the exquisite level of sensitivity and specificity needed to detect ctDNA, the potential for false negatives in detecting these rare molecules, and the increased reliance on contrived samples to attain sufficient ctDNA for analytical validation. By addressing these unique challenges, the BloodPAC hopes to expedite sponsors' presubmission discussions with the Food and Drug Administration (FDA) with the protocols presented herein. By sharing best practices with the broader community, this work may also save the time and capacity of FDA reviewers through increased efficiency.
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Affiliation(s)
| | | | | | | | | | | | | | - James Hicks
- University of Southern California, Los Angeles, CA
| | | | | | | | | | - Lisa McShane
- National Cancer Institute at the National Institutes of Health (NIH/NCI), Rockville, MD
| | | | | | | | | | | | - Laura Yee
- National Cancer Institute at the National Institutes of Health (NIH/NCI), Rockville, MD
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Fettke H, Steen JA, Kwan EM, Bukczynska P, Keerthikumar S, Goode D, Docanto M, Ng N, Martelotto L, Hauser C, Southey MC, Azad AA, Nguyen-Dumont T. Analytical validation of an error-corrected ultra-sensitive ctDNA next-generation sequencing assay. Biotechniques 2020; 69:133-40. [PMID: 32654508 DOI: 10.2144/btn-2020-0045] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Plasma circulating tumor DNA (ctDNA) analysis has emerged as a minimally invasive means to perform molecular tumor typing. Here we developed a custom ultra-sensitive ctDNA next-generation sequencing assay using molecular barcoding technology and off-the-shelf reagents combined with bioinformatics tools for enhanced ctDNA analysis. Assay performance was assessed via a spike-in experiment and the technique was applied to analyze 41 plasma samples from men with advanced prostate cancer. Orthogonal validation was performed using a commercial assay. Sensitivity and specificity of 93 and 99.5% were recorded for ultra-rare somatic variants (<1%), with high concordance observed between the in-house and commercial assays. The optimized protocol dramatically improved the efficiency of the assay and enabled the detection of low-frequency somatic variants from plasma cell-free DNA (cfDNA).
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40
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Remon J, Swalduz A, Planchard D, Ortiz-Cuaran S, Mezquita L, Lacroix L, Jovelet C, Rouleau E, Leonce C, De Kievit F, Morris C, Jones G, Mercier K, Howarth K, Green E, Pérol M, Saintigny P, Besse B. Outcomes in oncogenic-addicted advanced NSCLC patients with actionable mutations identified by liquid biopsy genomic profiling using a tagged amplicon-based NGS assay. PLoS One 2020; 15:e0234302. [PMID: 32525942 PMCID: PMC7289417 DOI: 10.1371/journal.pone.0234302] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 05/22/2020] [Indexed: 11/19/2022] Open
Abstract
Circulating tumor DNA (ctDNA)-based molecular profiling is rapidly gaining traction in clinical practice of advanced cancer patients with multi-gene next-generation sequencing (NGS) panels. However, clinical outcomes remain poorly described and deserve further validation with personalized treatment of patients with genomic alterations detected in plasma ctDNA. Here, we describe the outcomes, disease control rate (DCR) at 3 months and progression-free survival (PFS) in oncogenic-addicted advanced NSCLC patients with actionable alterations identified in plasma by ctDNA liquid biopsy assay, InVisionFirst®-Lung. A pooled retrospective analysis was completed of 81 advanced NSCLC patients with all classes of alterations predicting response to current FDA approved drugs: sensitizing common EGFR mutations (78%, n = 63) with T790M (73%, 46/63), ALK / ROS1 gene fusions (17%, n = 14) and BRAF V600E mutations (5%, n = 4). Actionable driver alterations detected in liquid biopsy were confirmed by prior tissue genomic profiling in all patients, and all patients received personalized treatment. Of 82 patients treated with matched targeted therapies, 10% were at first-line, 41% at second-line, and 49% beyond second-line. Acquired T790M at TKI relapse was detected in 73% (46/63) of patients, and all prospective patients (34/46) initiated osimertinib treatment based on ctDNA results. The 3-month DCR was 86% in 81 evaluable patients. The median PFS was of 14.8 months (12.1–22.9m). Baseline ctDNA allelic fraction of genomic driver did not correlate with the response rate of personalized treatment (p = 0.29). ctDNA molecular profiling is an accurate and reliable tool for the detection of clinically relevant molecular alterations in advanced NSCLC patients. Clinical outcomes with targeted therapies endorse the use of liquid biopsy by amplicon-based NGS ctDNA analysis in first line and relapse testing for advanced NSCLC patients.
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Affiliation(s)
- Jordi Remon
- Department of Cancer Medicine, Gustave Roussy, Villejuif, France
| | | | - David Planchard
- Department of Cancer Medicine, Gustave Roussy, Villejuif, France
| | | | - Laura Mezquita
- Department of Cancer Medicine, Gustave Roussy, Villejuif, France
| | - Ludovic Lacroix
- Laboratoire de Recherche Translationnelle, Gustave Roussy, Villejuif, France
| | - Cecile Jovelet
- Laboratoire de Recherche Translationnelle, Gustave Roussy, Villejuif, France
| | - Etienne Rouleau
- Department of Cancer Medicine, Gustave Roussy, Villejuif, France
| | | | | | | | - Greg Jones
- Inivata, Granta Park, Cambridge, United Kingdom
| | | | | | - Emma Green
- Inivata, Granta Park, Cambridge, United Kingdom
| | | | | | - Benjamin Besse
- Department of Cancer Medicine, Gustave Roussy, Villejuif, France
- Université Paris-Sud, Orsay, France
- * E-mail:
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Andreatos N, Iyer G, Grivas P. Emerging biomarkers in urothelial carcinoma: Challenges and opportunities. Cancer Treat Res Commun 2020; 25:100179. [PMID: 32920502 PMCID: PMC8387954 DOI: 10.1016/j.ctarc.2020.100179] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 05/04/2020] [Accepted: 05/07/2020] [Indexed: 12/25/2022]
Abstract
Advanced urothelial carcinoma (UC) is a very important cause of cancer-related morbidity and mortality with, until recently, only a few available therapeutic options. The treatment landscape has dramatically changed in recent years with the introduction of immune checkpoint inhibitors and the development of novel targeted agents, such as erdafitinib, and antibody-drug conjugates, such as enfortumab vedotin. Cost-effective utilization of this rapidly expanding therapeutic armamentarium can be further optimized via the identification and validation of reliable prognostic and predictive biomarkers that inform prognostication and patient selection. In this review, we aim to summarize examples of recent developments in the rapidly expanding field of emerging biomarkers in UC, outlining challenges and opportunities.
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Affiliation(s)
- Nikolaos Andreatos
- Department of Internal Medicine, Cleveland Clinic, Cleveland, OH, United States
| | - Gopa Iyer
- Assistant Attending Physician, Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Petros Grivas
- Division of Oncology, Department of Medicine, University of Washington, Fred Hutchinson Cancer Research Center, Seattle Cancer Care Alliance, Seattle, WA, United States.
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Abstract
As researchers learn more about tumor biology and the molecular mechanisms involved in tumorigenesis, metastasis, and tumor evolution, clinical trials are growing more complex and patient selection for clinical trials is becoming more specific. Rather than exploit certain phenotypic characteristics of tumor cells (e.g., rapid cell division and uncontrolled cell growth), pharmaceuticals targeting the genotypic causes of tumorigenesis are emerging. The sequencing of the human genome, advances in chemical techniques, and increased efficiency in drug target identification have changed the way drugs are developed. Now, more precise drugs targeting specific mutations within individual genes are being used to treat narrow patient populations harboring these specific driver mutations, often with greater efficacy and lower toxicity than traditional chemotherapeutic agents. This precision in drug development relies not only on the ability to design exquisitely specific pharmaceuticals but also to identify (with the same level of precision) the patients who are most likely to respond to those therapies. Robust screening techniques and adequate molecular oncology education are required to match the appropriate patient to precision therapies, and these same screening techniques provide the data necessary to advance to the next generation of drug development.
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Larson K, Kannaiyan R, Pandey R, Chen Y, Babiker HM, Mahadevan D. A Comparative Analysis of Tumors and Plasma Circulating Tumor DNA in 145 Advanced Cancer Patients Annotated by 3 Core Cellular Processes. Cancers (Basel) 2020; 12:E701. [PMID: 32188081 PMCID: PMC7140098 DOI: 10.3390/cancers12030701] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 03/06/2020] [Accepted: 03/14/2020] [Indexed: 02/06/2023] Open
Abstract
Matched-targeted and immune checkpoint therapies have improved survival in cancer patients, but tumor heterogeneity contributes to drug resistance. Our study categorized gene mutations from next generation sequencing (NGS) into three core processes. This annotation helps decipher complex biologic interactions to guide therapy. We collected NGS data on 145 patients who have failed standard therapy (2016 to 2018). One hundred and forty two patients had data for tissue (Caris MI/X) and plasma cell-free circulating tumor DNA (Guardant360) platforms. The mutated genes were categorized into cell fate (CF), cell survival (CS), and genome maintenance (GM). Comparative analysis was performed for concordance and discordance, unclassified mutations, trends in TP53 alterations, and PD-L1 expression. Two gene mutation maps were generated to compare each NGS platform. Mutated genes predominantly matched to CS with concordance between Guardant360 (64.4%) and Caris (51.5%). TP53 alterations comprised a significant proportion of the mutation pool in Caris and Guardant360, 14.7% and 13.1%, respectively. Twenty-six potentially actionable gene alterations were detected from matching ctDNA to Caris unclassified alterations. The CS core cellular process was the most prevalent in our study population. Clinical trials are warranted to investigate biomarkers for the three core cellular processes in advanced cancer patients to define the next best therapies.
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Affiliation(s)
- Kristian Larson
- University of Arizona College of Medicine, 1501 N Campbell Ave, Tucson, AZ 85724, USA;
| | | | - Ritu Pandey
- Department of Cellular and Molecular Medicine, University of Arizona Cancer Center, 1515 N Campbell Ave, Tucson, AZ 85724, USA;
| | - Yuliang Chen
- University of Arizona Cancer Center, 1515 N Campbell Ave, Tucson, AZ 85724, USA;
| | - Hani M. Babiker
- Early Phase Clinical Trials Program, University of Arizona Cancer Center, 1515 N Campbell Ave, Tucson, AZ 85724, USA;
| | - Daruka Mahadevan
- Early Phase Clinical Trials Program, University of Arizona Cancer Center, 1515 N Campbell Ave, Tucson, AZ 85724, USA;
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44
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Galot R, van Marcke C, Helaers R, Mendola A, Goebbels RM, Caignet X, Ambroise J, Wittouck K, Vikkula M, Limaye N, Machiels JPH. Liquid biopsy for mutational profiling of locoregional recurrent and/or metastatic head and neck squamous cell carcinoma. Oral Oncol 2020; 104:104631. [PMID: 32169746 DOI: 10.1016/j.oraloncology.2020.104631] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 02/18/2020] [Accepted: 03/04/2020] [Indexed: 12/12/2022]
Abstract
OBJECTIVES The molecular landscape of head and neck squamous cell carcinoma (HNSCC) harbors potentially actionable genomic alterations. We aimed to study the utility of liquid biopsy to (i) characterize the mutational landscape of recurrent/metastatic HNSCC using a comprehensive gene panel and (ii) estimate the concordance between DNA mutations identified from circulating tumor DNA (ctDNA) and matched tumor tissues. MATERIALS AND METHODS Targeted next-generation sequencing (NGS) was performed on cell-free DNA (cfDNA) of 39 patients with locoregional recurrent (n = 19) and/or metastatic (n = 20) HNSCC. Tumor biopsy (n = 18) was sequenced using the same technique. RESULTS ctDNA was detected in 51% of patients (20/39) with a higher probability of detection in metastatic than locoregional recurrent disease (70% versus 30%, p = 0.025). 81% and 58% of the tissue tumor variants were not detected in plasma when considering all patients and only metastatic patients with detectable ctDNA, respectively. In a multivariate analysis, the likelihood of detecting the tissue tumor variant in plasma was related to metastatic status (p = 0.012), tumor variant allele frequency (p < 0.001) and ctDNA quantity (p < 0.001). 26% of the variants were detected only in liquid and not in the solid biopsy. Three patients without an available tumor sample had plasma containing three different potentially actionable PIK3CA mutations. CONCLUSION CtDNA detection and characterization using targeted NGS is feasible in metastatic HNSCC. Liquid biopsies do not reflect the complete mutation profile of the tumor but have the potential to identify actionable mutations when tumor biopsies are not available as well as variants not found in matched tumor tissue.
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Affiliation(s)
- Rachel Galot
- Department of Medical Oncology, Institut Roi Albert II - Cliniques universitaires Saint-Luc, Brussels, Belgium; Institute for Clinical and Experimental Research (MIRO), Université catholique de Louvain, Brussels, Belgium
| | - Cédric van Marcke
- Department of Medical Oncology, Institut Roi Albert II - Cliniques universitaires Saint-Luc, Brussels, Belgium; Institute for Clinical and Experimental Research (MIRO), Université catholique de Louvain, Brussels, Belgium; Laboratory of Human Molecular Genetics, de Duve Institute, Université catholique de Louvain, Brussels, Belgium
| | - Raphaël Helaers
- Laboratory of Human Molecular Genetics, de Duve Institute, Université catholique de Louvain, Brussels, Belgium
| | - Antonella Mendola
- Institute for Clinical and Experimental Research (MIRO), Université catholique de Louvain, Brussels, Belgium
| | - Rose-Marie Goebbels
- Institute for Clinical and Experimental Research (MIRO), Université catholique de Louvain, Brussels, Belgium
| | - Xavier Caignet
- Institute for Clinical and Experimental Research (MIRO), Université catholique de Louvain, Brussels, Belgium
| | - Jérôme Ambroise
- Institute for Clinical and Experimental Research (CTMA), Université catholique de Louvain, Brussels, Belgium
| | - Kyril Wittouck
- Institute for Clinical and Experimental Research (MIRO), Université catholique de Louvain, Brussels, Belgium
| | - Miikka Vikkula
- Laboratory of Human Molecular Genetics, de Duve Institute, Université catholique de Louvain, Brussels, Belgium
| | - Nisha Limaye
- Genetics of Autoimmune Diseases and Cancer, de Duve Institute, Université catholique de Louvain, Brussels, Belgium
| | - Jean-Pascal H Machiels
- Department of Medical Oncology, Institut Roi Albert II - Cliniques universitaires Saint-Luc, Brussels, Belgium; Institute for Clinical and Experimental Research (MIRO), Université catholique de Louvain, Brussels, Belgium.
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Ito M, Fujiwara Y, Kubo T, Matsushita H, Kumamoto T, Suzuki T, Sunami K, Yamamoto N, Kohno T. Clonal Hematopoiesis From Next Generation Sequencing of Plasma From a Patient With Lung Adenocarcinoma: A Case Report. Front Oncol 2020; 10:113. [PMID: 32117761 PMCID: PMC7031249 DOI: 10.3389/fonc.2020.00113] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 01/21/2020] [Indexed: 11/13/2022] Open
Abstract
Reliable and accurate next generation sequencing (NGS) technologies are important in precision medicine. Analysis using currently available NGS genomic tests is conducted on cancer-derived DNA collected from tumor tissue, blood, or both. Clonal hematopoiesis (CH) produces a detectable somatic clonal mutation that is commonly associated with clonal expansion of hematopoietic cells with age and genomic analysis of blood samples can be used to detect CH. A 74-year-old Korean male had lung adenocarcinoma with a metastasis to the left scapula. He underwent palliative radiotherapy to the left scapula and received multi-line chemotherapies. After disease progression, he underwent re-biopsy of the metastatic tumor tissue from lung cancer and concomitant blood sampling. NGS genomic testing revealed no significant genomic mutation in the tumor tissue DNA but showed the TP53 mutation C135Y in peripheral blood DNA. To investigate the discordance between the genotyping results in tumor tissue and blood, we tested for the TP53 mutation using a target sequencing test in blood and normal oral mucosa. The TP53 mutation C135Y was only detected in the blood sample, confirming the presence of TP53-mutated CH. We should be aware of different characteristics in NGS genomic testing including sample type such as tumor, blood, or paired specimens. Performing genomic testing on paired tumor and blood samples is effective for discriminating mutations derived from CH from germline mutations and somatic mutations in tumor cells.
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Affiliation(s)
- Munehiro Ito
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Yutaka Fujiwara
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, Japan.,Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan.,Department of Respiratory Medicine, Mitsui Memorial Hospital, Tokyo, Japan
| | - Takashi Kubo
- Division of Translational Genomics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Tokyo, Japan
| | - Hiromichi Matsushita
- Department of Laboratory Medicine, National Cancer Center Hospital, Tokyo, Japan
| | - Tadashi Kumamoto
- Department of Pediatric Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Tatsuya Suzuki
- Department of Hematology, National Cancer Center Hospital, Tokyo, Japan
| | - Kuniko Sunami
- Department of Laboratory Medicine, National Cancer Center Hospital, Tokyo, Japan
| | - Noboru Yamamoto
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, Japan.,Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
| | - Takashi Kohno
- Division of Translational Genomics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Tokyo, Japan.,Division of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan
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Campos-Carrillo A, Weitzel JN, Sahoo P, Rockne R, Mokhnatkin JV, Murtaza M, Gray SW, Goetz L, Goel A, Schork N, Slavin TP. Circulating tumor DNA as an early cancer detection tool. Pharmacol Ther 2020; 207:107458. [PMID: 31863816 PMCID: PMC6957244 DOI: 10.1016/j.pharmthera.2019.107458] [Citation(s) in RCA: 99] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 12/12/2019] [Indexed: 02/07/2023]
Abstract
Circulating tumor DNA holds substantial promise as an early detection biomarker, particularly for cancers that do not have currently accepted screening methodologies, such as ovarian, pancreatic, and gastric cancers. Many features intrinsic to ctDNA analysis may be leveraged to enhance its use as an early cancer detection biomarker: including ctDNA fragment lengths, DNA copy number variations, and associated patient phenotypic information. Furthermore, ctDNA testing may be synergistically used with other multi-omic biomarkers to enhance early detection. For instance, assays may incorporate early detection proteins (i.e., CA-125), epigenetic markers, circulating tumor RNA, nucleosomes, exosomes, and associated immune markers. Many companies are currently competing to develop a marketable early cancer detection test that leverages ctDNA. Although some hurdles (like early stage disease assay accuracy, high implementation costs, confounding from clonal hematopoiesis, and lack of clinical utility studies) need to be addressed before integration into healthcare, ctDNA assays hold substantial potential as an early cancer screening test.
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Affiliation(s)
| | | | - Prativa Sahoo
- City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Russell Rockne
- City of Hope National Medical Center, Duarte, CA 91010, USA
| | | | - Muhammed Murtaza
- Translational Genomics Research Institute, Phoenix, AZ 85004, USA
| | - Stacy W Gray
- City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Laura Goetz
- City of Hope National Medical Center, Duarte, CA 91010, USA; Translational Genomics Research Institute, Phoenix, AZ 85004, USA
| | - Ajay Goel
- City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Nicholas Schork
- City of Hope National Medical Center, Duarte, CA 91010, USA; Translational Genomics Research Institute, Phoenix, AZ 85004, USA
| | - Thomas P Slavin
- City of Hope National Medical Center, Duarte, CA 91010, USA.
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Winn JS, Hasse Z, Slifker M, Pei J, Arisi-Fernandez SM, Talarchek JN, Obeid E, Baldwin DA, Gong Y, Ross E, Cristofanilli M, Alpaugh RK, Fernandez SV. Genetic Variants Detected Using Cell-Free DNA from Blood and Tumor Samples in Patients with Inflammatory Breast Cancer. Int J Mol Sci 2020; 21:E1290. [PMID: 32075053 DOI: 10.3390/ijms21041290] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Revised: 02/11/2020] [Accepted: 02/12/2020] [Indexed: 12/27/2022] Open
Abstract
We studied genomic alterations in 19 inflammatory breast cancer (IBC) patients with advanced disease using samples of tissue and paired blood serum or plasma (cell-free DNA, cfDNA) by targeted next generation sequencing (NGS). At diagnosis, the disease was triple negative (TN) in eleven patients (57.8%), ER+ Her2- IBC in six patients (31.6%), ER+ Her2+ IBC in one patient (5.3%), and ER- Her2+ IBC in one other patient (5.3%). Pathogenic or likely pathogenic variants were frequently detected in TP53 (47.3%), PMS2 (26.3%), MRE11 (26.3%), RB1 (10.5%), BRCA1 (10.5%), PTEN (10.5%) and AR (10.5%); other affected genes included PMS1, KMT2C, BRCA2, PALB2, MUTYH, MEN1, MSH2, CHEK2, NCOR1, PIK3CA, ESR1 and MAP2K4. In 15 of the 19 patients in which tissue and paired blood were collected at the same time point, 80% of the variants detected in tissue were also detected in the paired cfDNA. Higher concordance between tissue and cfDNA was found for variants with higher allele fraction in tissue (AFtissue ≥ 5%). Furthermore, 86% of the variants detected in cfDNA were also detected in paired tissue. Our study suggests that the genetic profile measured in blood cfDNA is complementary to that of tumor tissue in IBC patients.
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Wang Z, Duan J, Cai S, Han M, Dong H, Zhao J, Zhu B, Wang S, Zhuo M, Sun J, Wang Q, Bai H, Han J, Tian Y, Lu J, Xu T, Zhao X, Wang G, Cao X, Li F, Wang D, Chen Y, Bai Y, Zhao J, Zhao Z, Zhang Y, Xiong L, He J, Gao S, Wang J. Assessment of Blood Tumor Mutational Burden as a Potential Biomarker for Immunotherapy in Patients With Non-Small Cell Lung Cancer With Use of a Next-Generation Sequencing Cancer Gene Panel. JAMA Oncol 2020; 5:696-702. [PMID: 30816954 PMCID: PMC6512308 DOI: 10.1001/jamaoncol.2018.7098] [Citation(s) in RCA: 320] [Impact Index Per Article: 80.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Question Is blood tumor mutational burden estimated by a next-generation gene sequencing panel with an optimized panel size and algorithm associated with clinical outcomes in patients with non–small cell lung cancer treated with anti–programmed cell death 1 (anti–PD-1) and anti–programmed cell death ligand 1 (anti–PD-L1) agents? Findings This study of 2 independent cohorts of patients (48 in cohort 1 and 50 in cohort 2) found that NCC-GP150 was a cost-effective panel for tumor mutational burden estimation with satisfactory performance. Blood tumor mutational burden estimated by NCC-GP150 correlated well with tissue tumor mutational burden calculated by whole-exome sequencing, and a blood tumor mutational burden of 6 or higher was positively associated with clinical benefits of anti–PD-1 and anti–PD-L1 therapy in patients with advanced non–small cell lung cancer. Meaning The findings suggest that blood tumor mutational burden measured by NCC-GP150 is a potential biomarker to identify patients with non–small cell lung cancer who could benefit from anti–PD-1 and anti–PD-L1 therapy. Importance Tumor mutational burden (TMB), as measured by whole-exome sequencing (WES) or a cancer gene panel (CGP), is associated with immunotherapy responses. However, whether TMB estimated by circulating tumor DNA in blood (bTMB) is associated with clinical outcomes of immunotherapy remains to be explored. Objectives To explore the optimal gene panel size and algorithm to design a CGP for TMB estimation, evaluate the panel reliability, and further validate the feasibility of bTMB as a clinical actionable biomarker for immunotherapy. Design, Setting, and Participants In this cohort study, a CGP named NCC-GP150 was designed and virtually validated using The Cancer Genome Atlas database. The correlation between bTMB estimated by NCC-GP150 and tissue TMB (tTMB) measured by WES was evaluated in matched blood and tissue samples from 48 patients with advanced NSCLC. An independent cohort of 50 patients with advanced NSCLC was used to identify the utility of bTMB estimated by NCC-GP150 in distinguishing patients who would benefit from anti–programmed cell death 1 (anti–PD-1) and anti–programmed cell death ligand 1 (anti–PD-L1) therapy. The study was performed from July 19, 2016, to April 20, 2018. Main Outcomes and Measures Assessment of the Spearman correlation coefficient between bTMB estimated by NCC-GP150 and tTMB calculated by WES. Evaluation of the association of bTMB level with progression-free survival and response to anti–PD-1 and anti–PD-L1 therapy. Results This study used 2 independent cohorts of patients with NSCLC (cohort 1: 48 patients; mean [SD] age, 60 [13] years; 15 [31.2%] female; cohort 2: 50 patients; mean [SD] age, 58 [8] years; 15 [30.0%] female). A CGP, including 150 genes, demonstrated stable correlations with WES for TMB estimation (median r2 = 0.91; interquartile range, 0.89-0.92), especially when synonymous mutations were included (median r2 = 0.92; interquartile range, 0.91-0.93), whereas TMB estimated by the NCC-GP150 panel found higher correlations with TMB estimated by WES than most of the randomly sampled 150-gene panels. Blood TMB estimated by NCC-GP150 correlated well with the matched tTMB calculated by WES (Spearman correlation = 0.62). In the anti–PD-1 and anti–PD-L1 treatment cohort, a bTMB of 6 or higher was associated with superior progression-free survival (hazard ratio, 0.39; 95% CI, 0.18-0.84; log-rank P = .01) and objective response rates (bTMB ≥6: 39.3%; 95% CI, 23.9%-56.5%; bTMB <6: 9.1%; 95% CI, 1.6%-25.9%; P = .02). Conclusions and Relevance The findings suggest that established NCC-GP150 with an optimized gene panel size and algorithm is feasible for bTMB estimation, which may serve as a potential biomarker of clinical benefit in patients with NSCLC treated with anti–PD-1 and anti–PD-L1 agents.
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Affiliation(s)
- Zhijie Wang
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jianchun Duan
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Shangli Cai
- The Medical Department, 3D Medicines Inc, Shanghai, China
| | - Miao Han
- The Bioinformatics Department, R&D Center of Precision Medicine, 3D Medicines Inc, Shanghai, China
| | - Hua Dong
- The Bioinformatics Department, R&D Center of Precision Medicine, 3D Medicines Inc, Shanghai, China
| | - Jun Zhao
- Department of Thoracic Medical Oncology, Peking University School of Oncology, Beijing Cancer Hospital & Institute, Beijing, China
| | - Bo Zhu
- Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Shuhang Wang
- GCP Center, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Minglei Zhuo
- Department of Thoracic Medical Oncology, Peking University School of Oncology, Beijing Cancer Hospital & Institute, Beijing, China
| | - Jianguo Sun
- Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Qiming Wang
- Department of Internal Medicine, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China
| | - Hua Bai
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jiefei Han
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yanhua Tian
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jing Lu
- The Bioinformatics Department, R&D Center of Precision Medicine, 3D Medicines Inc, Shanghai, China
| | - Tongfu Xu
- The Medical Department, 3D Medicines Inc, Shanghai, China
| | - Xiaochen Zhao
- The Medical Department, 3D Medicines Inc, Shanghai, China
| | - Guoqiang Wang
- The Medical Department, 3D Medicines Inc, Shanghai, China
| | - Xinkai Cao
- The Bioinformatics Department, R&D Center of Precision Medicine, 3D Medicines Inc, Shanghai, China
| | - Fugen Li
- The Bioinformatics Department, R&D Center of Precision Medicine, 3D Medicines Inc, Shanghai, China
| | - Dalei Wang
- The 3DMed Clinical Laboratory, 3D Medicines Inc, Shanghai, China
| | - Yuejun Chen
- The 3DMed Clinical Laboratory, 3D Medicines Inc, Shanghai, China
| | - Yuezong Bai
- The Medical Department, 3D Medicines Inc, Shanghai, China
| | - Jing Zhao
- The Medical Department, 3D Medicines Inc, Shanghai, China
| | - Zhengyi Zhao
- The Medical Department, 3D Medicines Inc, Shanghai, China
| | - Yuzi Zhang
- The Medical Department, 3D Medicines Inc, Shanghai, China
| | - Lei Xiong
- The Medical Department, 3D Medicines Inc, Shanghai, China
| | - Jie He
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Shugeng Gao
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jie Wang
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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Serrano C, Vivancos A, López-Pousa A, Matito J, Mancuso FM, Valverde C, Quiroga S, Landolfi S, Castro S, Dopazo C, Sebio A, Virgili AC, Menso MM, Martín-Broto J, Sansó M, García-Valverde A, Rosell J, Fletcher JA, George S, Carles J, Arribas J. Clinical value of next generation sequencing of plasma cell-free DNA in gastrointestinal stromal tumors. BMC Cancer 2020; 20:99. [PMID: 32024476 PMCID: PMC7003348 DOI: 10.1186/s12885-020-6597-x] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 01/31/2020] [Indexed: 02/08/2023] Open
Abstract
Background Gastrointestinal stromal tumor (GIST) initiation and evolution is commonly framed by KIT/PDGFRA oncogenic activation, and in later stages by the polyclonal expansion of resistant subpopulations harboring KIT secondary mutations after the onset of imatinib resistance. Thus, circulating tumor (ct)DNA determination is expected to be an informative non-invasive dynamic biomarker in GIST patients. Methods We performed amplicon-based next-generation sequencing (NGS) across 60 clinically relevant genes in 37 plasma samples from 18 GIST patients collected prospectively. ctDNA alterations were compared with NGS of matched tumor tissue samples (obtained either simultaneously or at the time of diagnosis) and cross-validated with droplet digital PCR (ddPCR). Results We were able to identify cfDNA mutations in five out of 18 patients had detectable in at least one timepoint. Overall, NGS sensitivity for detection of cell-free (cf)DNA mutations in plasma was 28.6%, showing high concordance with ddPCR confirmation. We found that GIST had relatively low ctDNA shedding, and mutations were at low allele frequencies. ctDNA was detected only in GIST patients with advanced disease after imatinib failure, predicting tumor dynamics in serial monitoring. KIT secondary mutations were the only mechanism of resistance found across 10 imatinib-resistant GIST patients progressing to sunitinib or regorafenib. Conclusions ctDNA evaluation with amplicon-based NGS detects KIT primary and secondary mutations in metastatic GIST patients, particularly after imatinib progression. GIST exhibits low ctDNA shedding, but ctDNA monitoring, when positive, reflects tumor dynamics.
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Affiliation(s)
- César Serrano
- Medical Oncology Department, Vall d'Hebron University Hospital, P. Vall d'Hebron 119, 08035, Barcelona, Spain. .,Preclinical Research Program, Vall d'Hebron Institute of Oncology, Barcelona, Spain.
| | - Ana Vivancos
- Cancer Genomics Group,
- Vall d'Hebron Institute of Oncology, Natzaret 115, 08035, Barcelona, Spain.
| | | | - Judit Matito
- Cancer Genomics Group,
- Vall d'Hebron Institute of Oncology, Natzaret 115, 08035, Barcelona, Spain
| | - Francesco M Mancuso
- Cancer Genomics Group,
- Vall d'Hebron Institute of Oncology, Natzaret 115, 08035, Barcelona, Spain
| | - Claudia Valverde
- Medical Oncology Department, Vall d'Hebron University Hospital, P. Vall d'Hebron 119, 08035, Barcelona, Spain
| | - Sergi Quiroga
- Radiology Department, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Stefania Landolfi
- Pathology Department, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Sandra Castro
- Surgical Oncology Division, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Cristina Dopazo
- Surgical Oncology Division, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Ana Sebio
- Medical Oncology, Sant Pau University Hospital, Barcelona, Spain
| | - Anna C Virgili
- Medical Oncology, Sant Pau University Hospital, Barcelona, Spain
| | - María M Menso
- Radiology Department, Sant Pau University Hospital, Barcelona, Spain
| | | | - Miriam Sansó
- Cancer Genomics Group,
- Vall d'Hebron Institute of Oncology, Natzaret 115, 08035, Barcelona, Spain
| | | | - Jordi Rosell
- Preclinical Research Program, Vall d'Hebron Institute of Oncology, Barcelona, Spain
| | - Jonathan A Fletcher
- Pathology Department, Brigham and Women's Hospital/Harvard Medical School, Boston, USA
| | - Suzanne George
- Center for Sarcoma and Bone Oncology, Dana-Farber Cancer Institute, Boston, USA
| | - Joan Carles
- Medical Oncology Department, Vall d'Hebron University Hospital, P. Vall d'Hebron 119, 08035, Barcelona, Spain
| | - Joaquín Arribas
- Preclinical Research Program, Vall d'Hebron Institute of Oncology, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
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Qiu J, Xu J, Zhang K, Gu W, Nie L, Wang G, Luo Y. Refining Cancer Management Using Integrated Liquid Biopsy. Am J Cancer Res 2020; 10:2374-2384. [PMID: 32089746 PMCID: PMC7019147 DOI: 10.7150/thno.40677] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Accepted: 10/13/2019] [Indexed: 12/17/2022] Open
Abstract
Liquid biopsy has emerged in the last ten years as an appealing noninvasive strategy to support early cancer diagnosis and follow-up interventions. However, conventional liquid biopsy strategies involving specified biomarkers have encountered unexpected inconsistencies stemming from the use of different analytical methodologies. Recent reports have repeatedly demonstrated that integrated detection of multiple liquid biopsy biomarkers can significantly improve diagnostic performance by eliminating the influence of intratumoral heterogeneity. Herein, we review the progress in the field of liquid biopsy and propose a novel integrated liquid biopsy framework consisting of three categories: elementary, intermediate, and advanced integration. We also summarize the merits of the integration strategy and propose a roadmap toward refining cancer diagnosis, metastasis surveillance, and prognostication.
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