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Shirai Y, Ueno T, Kojima S, Ikeuchi H, Kitada R, Koyama T, Takahashi F, Takahashi K, Ichimura K, Yoshida A, Sugino H, Mano H, Narita Y, Takahashi M, Kohsaka S. The development of a custom RNA-sequencing panel for the identification of predictive and diagnostic biomarkers in glioma. J Neurooncol 2024; 167:75-88. [PMID: 38363490 PMCID: PMC10978676 DOI: 10.1007/s11060-024-04563-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 01/02/2024] [Indexed: 02/17/2024]
Abstract
PURPOSE Various molecular profiles are needed to classify malignant brain tumors, including gliomas, based on the latest classification criteria of the World Health Organization, and their poor prognosis necessitates new therapeutic targets. The Todai OncoPanel 2 RNA Panel (TOP2-RNA) is a custom-target RNA-sequencing (RNA-seq) using the junction capture method to maximize the sensitivity of detecting 455 fusion gene transcripts and analyze the expression profiles of 1,390 genes. This study aimed to classify gliomas and identify their molecular targets using TOP2-RNA. METHODS A total of 124 frozen samples of malignant gliomas were subjected to TOP2-RNA for classification based on their molecular profiles and the identification of molecular targets. RESULTS Among 55 glioblastoma cases, gene fusions were detected in 11 cases (20%), including novel MET fusions. Seven tyrosine kinase genes were found to be overexpressed in 15 cases (27.3%). In contrast to isocitrate dehydrogenase (IDH) wild-type glioblastoma, IDH-mutant tumors, including astrocytomas and oligodendrogliomas, barely harbor fusion genes or gene overexpression. Of the 34 overexpressed tyrosine kinase genes, MDM2 and CDK4 in glioblastoma, 22 copy number amplifications (64.7%) were observed. When comparing astrocytomas and oligodendrogliomas in gene set enrichment analysis, the gene sets related to 1p36 and 19q were highly enriched in astrocytomas, suggesting that regional genomic DNA copy number alterations can be evaluated by gene expression analysis. CONCLUSIONS TOP2-RNA is a highly sensitive assay for detecting fusion genes, exon skipping, and aberrant gene expression. Alterations in targetable driver genes were identified in more than 50% of glioblastoma. Molecular profiling by TOP2-RNA provides ample predictive, prognostic, and diagnostic biomarkers that may not be identified by conventional assays and, therefore, is expected to increase treatment options for individual patients with glioma.
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Affiliation(s)
- Yukina Shirai
- Division of Cellular Signaling, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Department of Respiratory Medicine, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8431, Japan
| | - Toshihide Ueno
- Division of Cellular Signaling, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Shinya Kojima
- Division of Cellular Signaling, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Hiroshi Ikeuchi
- Division of Cellular Signaling, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Department of General Thoracic Surgery, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8431, Japan
| | - Rina Kitada
- Division of Cellular Signaling, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Takafumi Koyama
- Department of Experimental Therapeutics, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Fumiyuki Takahashi
- Department of Respiratory Medicine, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8431, Japan
| | - Kazuhisa Takahashi
- Department of Respiratory Medicine, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8431, Japan
| | - Koichi Ichimura
- Department of Brain Disease Translational Research, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8431, Japan
| | - Akihiko Yoshida
- Department of Diagnostic Pathology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Hirokazu Sugino
- Department of Diagnostic Pathology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Hiroyuki Mano
- Division of Cellular Signaling, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Yoshitaka Narita
- Department of Neurosurgery and Neuro-Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Masamichi Takahashi
- Department of Neurosurgery and Neuro-Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
| | - Shinji Kohsaka
- Division of Cellular Signaling, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
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Penkova A, Kuziakova O, Gulaia V, Tiasto V, Goncharov NV, Lanskikh D, Zhmenia V, Baklanov I, Farniev V, Kumeiko V. Comprehensive clinical assays for molecular diagnostics of gliomas: the current state and future prospects. Front Mol Biosci 2023; 10:1216102. [PMID: 37908227 PMCID: PMC10613994 DOI: 10.3389/fmolb.2023.1216102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 09/04/2023] [Indexed: 11/02/2023] Open
Abstract
Glioma is one of the most intractable types of cancer, due to delayed diagnosis at advanced stages. The clinical symptoms of glioma are unclear and due to a variety of glioma subtypes, available low-invasive testing is not effective enough to be introduced into routine medical laboratory practice. Therefore, recent advances in the clinical diagnosis of glioma have focused on liquid biopsy approaches that utilize a wide range of techniques such as next-generation sequencing (NGS), droplet-digital polymerase chain reaction (ddPCR), and quantitative PCR (qPCR). Among all techniques, NGS is the most advantageous diagnostic method. Despite the rapid cheapening of NGS experiments, the cost of such diagnostics remains high. Moreover, high-throughput diagnostics are not appropriate for molecular profiling of gliomas since patients with gliomas exhibit only a few diagnostic markers. In this review, we highlighted all available assays for glioma diagnosing for main pathogenic glioma DNA sequence alterations. In the present study, we reviewed the possibility of integrating routine molecular methods into the diagnosis of gliomas. We state that the development of an affordable assay covering all glioma genetic aberrations could enable early detection and improve patient outcomes. Moreover, the development of such molecular diagnostic kits could potentially be a good alternative to expensive NGS-based approaches.
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Affiliation(s)
- Alina Penkova
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
| | - Olga Kuziakova
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
| | - Valeriia Gulaia
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
| | - Vladlena Tiasto
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
| | - Nikolay V. Goncharov
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
- A. V. Zhirmunsky National Scientific Center of Marine Biology, FEB RAS, Vladivostok, Russia
| | - Daria Lanskikh
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
| | - Valeriia Zhmenia
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
| | - Ivan Baklanov
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
- A. V. Zhirmunsky National Scientific Center of Marine Biology, FEB RAS, Vladivostok, Russia
| | - Vladislav Farniev
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
| | - Vadim Kumeiko
- Institute of Life Sciences and Biomedicine, Far Eastern Federal University, Vladivostok, Russia
- A. V. Zhirmunsky National Scientific Center of Marine Biology, FEB RAS, Vladivostok, Russia
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Guo MZ, Marrone KA, Spira A, Waterhouse DM, Scott SC. Targeted Treatment of Non-Small Cell Lung Cancer: Focus on Capmatinib with Companion Diagnostics. Onco Targets Ther 2021; 14:5321-5331. [PMID: 34853516 PMCID: PMC8627896 DOI: 10.2147/ott.s273357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 11/04/2021] [Indexed: 11/28/2022] Open
Abstract
MET dysregulation promoting tumorigenesis in non-small cell lung cancer (NSCLC) is associated with worse outcomes following chemotherapy as compared to non-driver mutated NSCLC and occurs either through mutations causing MET exon 14 skipping (METex14) or gene amplification and overexpression that result in enhanced receptor signaling. Capmatinib is the first FDA-approved targeted therapy for NSCLC with METex14 skipping mutations, approved in 2020. FoundationOne® CDx, a comprehensive genomic profiling test for solid tumors, was concurrently approved as a companion diagnostic for capmatinib use. The GEOMETRY mono-1 phase II trial of capmatinib monotherapy demonstrated an overall response rate (ORR) of 68% in treatment naïve (n=28) and 41% in pre-treated (n=69) METex14 skipping advanced NSCLC; in MET amplified advanced NSCLC (gene copy number ≥ 10) ORRs of 40% in treatment naïve and 29% in pre-treated disease was seen. This review outlines the clinical data supporting capmatinib approval in the treatment of NSCLC and FoundationOne® CDx approval as a companion diagnostic. We detail the practical clinical administration of capmatinib, including dosing and toxicity management, compare capmatinib to other approved and investigational MET-targeted therapies, discuss limitations of capmatinib, and highlight ongoing trials of capmatinib in combinatorial approaches.
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Affiliation(s)
- Matthew Z Guo
- Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
| | - Kristen A Marrone
- Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
| | - Alexander Spira
- Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA.,Virginia Cancer Specialists Research Institute, Fairfax, VA, USA.,US Oncology, The Woodlands, TX, USA
| | - David M Waterhouse
- US Oncology, The Woodlands, TX, USA.,Oncology Hematology Care, Cincinnati, OH, Usa
| | - Susan C Scott
- Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
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Zheng F, Kelly MR, Ramms DJ, Heintschel ML, Tao K, Tutuncuoglu B, Lee JJ, Ono K, Foussard H, Chen M, Herrington KA, Silva E, Liu S, Chen J, Churas C, Wilson N, Kratz A, Pillich RT, Patel DN, Park J, Kuenzi B, Yu MK, Licon K, Pratt D, Kreisberg JF, Kim M, Swaney DL, Nan X, Fraley SI, Gutkind JS, Krogan NJ, Ideker T. Interpretation of cancer mutations using a multiscale map of protein systems. Science 2021; 374:eabf3067. [PMID: 34591613 PMCID: PMC9126298 DOI: 10.1126/science.abf3067] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
A major goal of cancer research is to understand how mutations distributed across diverse genes affect common cellular systems, including multiprotein complexes and assemblies. Two challenges—how to comprehensively map such systems and how to identify which are under mutational selection—have hindered this understanding. Accordingly, we created a comprehensive map of cancer protein systems integrating both new and published multi-omic interaction data at multiple scales of analysis. We then developed a unified statistical model that pinpoints 395 specific systems under mutational selection across 13 cancer types. This map, called NeST (Nested Systems in Tumors), incorporates canonical processes and notable discoveries, including a PIK3CA-actomyosin complex that inhibits phosphatidylinositol 3-kinase signaling and recurrent mutations in collagen complexes that promote tumor proliferation. These systems can be used as clinical biomarkers and implicate a total of 548 genes in cancer evolution and progression. This work shows how disparate tumor mutations converge on protein assemblies at different scales.
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Affiliation(s)
- Fan Zheng
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
| | - Marcus R. Kelly
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
| | - Dana J. Ramms
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
- Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA
- Department of Pharmacology, University of California San Diego, La Jolla, CA 92093, USA
| | - Marissa L. Heintschel
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Kai Tao
- Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR, 97239, USA
- Center for Spatial Systems Biomedicine, Oregon Health and Science University, Portland, OR, 97201, USA
| | - Beril Tutuncuoglu
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, CA 94158, USA
- The J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, 94158, USA
| | - John J. Lee
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Keiichiro Ono
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Helene Foussard
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, CA 94158, USA
- The J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Michael Chen
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Kari A. Herrington
- Department of Biochemistry and Biophysics Center for Advanced Light Microscopy at UCSF, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Erica Silva
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Sophie Liu
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Jing Chen
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Christopher Churas
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Nicholas Wilson
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Anton Kratz
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
| | - Rudolf T. Pillich
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
| | - Devin N. Patel
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
| | - Jisoo Park
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
| | - Brent Kuenzi
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
| | - Michael K. Yu
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Katherine Licon
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
| | - Dexter Pratt
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Jason F. Kreisberg
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
| | - Minkyu Kim
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, CA 94158, USA
- The J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Danielle L. Swaney
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, CA 94158, USA
- The J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Xiaolin Nan
- Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR, 97239, USA
- Center for Spatial Systems Biomedicine, Oregon Health and Science University, Portland, OR, 97201, USA
- Knight Cancer Early Detection Advanced Research Center, Oregon Health and Science University, Portland, OR, 97201, USA
| | - Stephanie I. Fraley
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - J. Silvio Gutkind
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
- Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA
- Department of Pharmacology, University of California San Diego, La Jolla, CA 92093, USA
| | - Nevan J. Krogan
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, CA 94158, USA
- The J. David Gladstone Institutes, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Trey Ideker
- Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
- Cancer Cell Map Initiative (CCMI), La Jolla and San Francisco, CA, USA
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