151
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Meister MT, Groot Koerkamp MJA, de Souza T, Breunis WB, Frazer‐Mendelewska E, Brok M, DeMartino J, Manders F, Calandrini C, Kerstens HHD, Janse A, Dolman MEM, Eising S, Langenberg KPS, van Tuil M, Knops RRG, van Scheltinga ST, Hiemcke‐Jiwa LS, Flucke U, Merks JHM, van Noesel MM, Tops BBJ, Hehir‐Kwa JY, Kemmeren P, Molenaar JJ, van de Wetering M, van Boxtel R, Drost J, Holstege FCP. Mesenchymal tumor organoid models recapitulate rhabdomyosarcoma subtypes. EMBO Mol Med 2022; 14:e16001. [PMID: 35916583 PMCID: PMC9549731 DOI: 10.15252/emmm.202216001] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 07/11/2022] [Accepted: 07/12/2022] [Indexed: 02/05/2023] Open
Abstract
Rhabdomyosarcomas (RMS) are mesenchyme-derived tumors and the most common childhood soft tissue sarcomas. Treatment is intense, with a nevertheless poor prognosis for high-risk patients. Discovery of new therapies would benefit from additional preclinical models. Here, we describe the generation of a collection of 19 pediatric RMS tumor organoid (tumoroid) models (success rate of 41%) comprising all major subtypes. For aggressive tumors, tumoroid models can often be established within 4-8 weeks, indicating the feasibility of personalized drug screening. Molecular, genetic, and histological characterization show that the models closely resemble the original tumors, with genetic stability over extended culture periods of up to 6 months. Importantly, drug screening reflects established sensitivities and the models can be modified by CRISPR/Cas9 with TP53 knockout in an embryonal RMS model resulting in replicative stress drug sensitivity. Tumors of mesenchymal origin can therefore be used to generate organoid models, relevant for a variety of preclinical and clinical research questions.
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Affiliation(s)
- Michael T Meister
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Marian J A Groot Koerkamp
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Terezinha de Souza
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Willemijn B Breunis
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Department of Oncology and Children's Research CenterUniversity Children's Hospital ZürichZürichSwitzerland
| | - Ewa Frazer‐Mendelewska
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Mariël Brok
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Jeff DeMartino
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Freek Manders
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Camilla Calandrini
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | | | - Alex Janse
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands
| | - M Emmy M Dolman
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Children's Cancer Institute, Lowy Cancer CentreUNSW SydneyKensingtonNSWAustralia,School of Women's and Children's Health, Faculty of MedicineUNSW SydneyKensingtonNSWAustralia
| | - Selma Eising
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands
| | | | - Marc van Tuil
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands
| | - Rutger R G Knops
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands
| | | | | | - Uta Flucke
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands
| | | | - Max M van Noesel
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands
| | | | | | - Patrick Kemmeren
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Center for Molecular MedicineUMC Utrecht and Utrecht UniversityUtrechtThe Netherlands
| | - Jan J Molenaar
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands
| | - Marc van de Wetering
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Ruben van Boxtel
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Jarno Drost
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Oncode InstituteUtrechtThe Netherlands
| | - Frank C P Holstege
- Princess Máxima Center for Pediatric OncologyUtrechtThe Netherlands,Center for Molecular MedicineUMC Utrecht and Utrecht UniversityUtrechtThe Netherlands
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152
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Experimentally Deduced Criteria for Detection of Clinically Relevant Fusion 3′ Oncogenes from FFPE Bulk RNA Sequencing Data. Biomedicines 2022; 10:biomedicines10081866. [PMID: 36009413 PMCID: PMC9405289 DOI: 10.3390/biomedicines10081866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/15/2022] [Accepted: 07/29/2022] [Indexed: 11/25/2022] Open
Abstract
Drugs targeting receptor tyrosine kinase (RTK) oncogenic fusion proteins demonstrate impressive anti-cancer activities. The fusion presence in the cancer is the respective drug prescription biomarker, but their identification is challenging as both the breakpoint and the exact fusion partners are unknown. RNAseq offers the advantage of finding both fusion parts by screening sequencing reads. Paraffin (FFPE) tissue blocks are the most common way of storing cancer biomaterials in biobanks. However, finding RTK fusions in FFPE samples is challenging as RNA fragments are short and their artifact ligation may appear in sequencing libraries. Here, we annotated RNAseq reads of 764 experimental FFPE solid cancer samples, 96 leukemia samples, and 2 cell lines, and identified 36 putative clinically relevant RTK fusions with junctions corresponding to exon borders of the fusion partners. Where possible, putative fusions were validated by RT-PCR (confirmed for 10/25 fusions tested). For the confirmed 3′RTK fusions, we observed the following distinguishing features. Both moieties were in-frame, and the tyrosine kinase domain was preserved. RTK exon coverage by RNAseq reads upstream of the junction site were lower than downstream. Finally, most of the true fusions were present by more than one RNAseq read. This provides the basis for automatic annotation of 3′RTK fusions using FFPE RNAseq profiles.
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153
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Weber D, Ibn-Salem J, Sorn P, Suchan M, Holtsträter C, Lahrmann U, Vogler I, Schmoldt K, Lang F, Schrörs B, Löwer M, Sahin U. Accurate detection of tumor-specific gene fusions reveals strongly immunogenic personal neo-antigens. Nat Biotechnol 2022; 40:1276-1284. [PMID: 35379963 PMCID: PMC7613288 DOI: 10.1038/s41587-022-01247-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 02/02/2022] [Indexed: 02/03/2023]
Abstract
Cancer-associated gene fusions are a potential source for highly immunogenic neoantigens, but the lack of computational tools for accurate, sensitive identification of personal gene fusions has limited their targeting in personalized cancer immunotherapy. Here we present EasyFuse, a machine learning computational pipeline for detecting cancer-specific gene fusions in transcriptome data obtained from human cancer samples. EasyFuse predicts personal gene fusions with high precision and sensitivity, outperforming previously described tools. By testing immunogenicity with autologous blood lymphocytes from patients with cancer, we detected pre-established CD4+ and CD8+ T cell responses for 10 of 21 (48%) and for 1 of 30 (3%) identified gene fusions, respectively. The high frequency of T cell responses detected in patients with cancer supports the relevance of individual gene fusions as neoantigens that might be targeted in personalized immunotherapies, especially for tumors with low mutation burden.
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Affiliation(s)
- D Weber
- TRON − Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz, Germany
| | - J Ibn-Salem
- TRON − Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz, Germany
| | - P Sorn
- TRON − Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz, Germany
| | - M Suchan
- TRON − Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz, Germany
| | - C Holtsträter
- TRON − Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz, Germany
| | | | | | | | - F Lang
- TRON − Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz, Germany
| | - B Schrörs
- TRON − Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz, Germany
| | - M Löwer
- TRON − Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz, Germany
| | - U Sahin
- TRON − Translational Oncology at the University Medical Center of Johannes Gutenberg University Mainz gGmbH, Mainz, Germany,BioNTech SE, Mainz, Germany,Johannes Gutenberg University Mainz, Mainz, Germany,corresponding author:
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154
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Church AJ, Corson LB, Kao PC, Imamovic-Tuco A, Reidy D, Doan D, Kang W, Pinto N, Maese L, Laetsch TW, Kim A, Colace SI, Macy ME, Applebaum MA, Bagatell R, Sabnis AJ, Weiser DA, Glade-Bender JL, Homans AC, Hipps J, Harris H, Manning D, Al-Ibraheemi A, Li Y, Gupta H, Cherniack AD, Lo YC, Strand GR, Lee LA, Pinches RS, Lazo De La Vega L, Harden MV, Lennon NJ, Choi S, Comeau H, Harris MH, Forrest SJ, Clinton CM, Crompton BD, Kamihara J, MacConaill LE, Volchenboum SL, Lindeman NI, Van Allen E, DuBois SG, London WB, Janeway KA. Molecular profiling identifies targeted therapy opportunities in pediatric solid cancer. Nat Med 2022; 28:1581-1589. [PMID: 35739269 PMCID: PMC10953704 DOI: 10.1038/s41591-022-01856-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 05/03/2022] [Indexed: 11/09/2022]
Abstract
To evaluate the clinical impact of molecular tumor profiling (MTP) with targeted sequencing panel tests, pediatric patients with extracranial solid tumors were enrolled in a prospective observational cohort study at 12 institutions. In the 345-patient analytical population, median age at diagnosis was 12 years (range 0-27.5); 298 patients (86%) had 1 or more alterations with potential for impact on care. Genomic alterations with diagnostic, prognostic or therapeutic significance were present in 61, 16 and 65% of patients, respectively. After return of the results, impact on care included 17 patients with a clarified diagnostic classification and 240 patients with an MTP result that could be used to select molecularly targeted therapy matched to identified alterations (MTT). Of the 29 patients who received MTT, 24% had an objective response or experienced durable clinical benefit; all but 1 of these patients received targeted therapy matched to a gene fusion. Of the diagnostic variants identified in 209 patients, 77% were gene fusions. MTP with targeted panel tests that includes fusion detection has a substantial clinical impact for young patients with solid tumors.
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Affiliation(s)
- Alanna J Church
- Boston Children's Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
| | - Laura B Corson
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Sema4, Stamford, CT, USA
| | | | - Alma Imamovic-Tuco
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Deirdre Reidy
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
- University of Connecticut School of Medicine, Farmington, CT, USA
| | - Duong Doan
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
- University of Massachusetts Medical School, Worcester, MA, USA
| | | | - Navin Pinto
- Seattle Children's Hospital, Seattle, WA, USA
- University of Washington, Seattle, WA, USA
| | - Luke Maese
- Primary Children's Hospital, Salt Lake City, UT, USA
- University of Utah Huntsman Cancer Institute, Salt Lake City, UT, USA
| | - Theodore W Laetsch
- University of Texas Southwestern Medical Center, Dallas, TX, USA
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
- University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - AeRang Kim
- Children's National Hospital, Washington, DC, USA
- George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Susan I Colace
- Nationwide Children's Hospital, Columbus, OH, USA
- Ohio State University College of Medicine, Columbus, OH, USA
| | - Margaret E Macy
- Children's Hospital of Colorado, Aurora, CO, USA
- University of Colorado School of Medicine, Aurora, CO, USA
| | - Mark A Applebaum
- University of Chicago, Chicago, IL, USA
- Comer Children's Hospital, Chicago, IL, USA
| | - Rochelle Bagatell
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
- University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Amit J Sabnis
- University of California San Francisco Benioff Children's Hospital, San Francisco, CA, USA
| | - Daniel A Weiser
- Children's Hospital at Montefiore, New York, NY, USA
- Albert Einstein College of Medicine, New York, NY, USA
| | - Julia L Glade-Bender
- Columbia University Irving Medical Center, New York, NY, USA
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alan C Homans
- University of Vermont Medical Center, Burlington, VT, USA
- University of Vermont, Burlington, VT, USA
| | - John Hipps
- University of North Carolina Medical Center, Chapel Hill, NC, USA
- University of North Carolina-Chapel Hill School of Medicine, Chapel Hill, NC, USA
| | | | | | - Alyaa Al-Ibraheemi
- Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Yvonne Li
- Harvard Medical School, Boston, MA, USA
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hersh Gupta
- Harvard Medical School, Boston, MA, USA
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrew D Cherniack
- Harvard Medical School, Boston, MA, USA
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ying-Chun Lo
- Boston Children's Hospital, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
- Mayo Clinic, Rochester, MN, USA
| | - Gianna R Strand
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
- Loyola University, Chicago, IL, USA
| | - Lobin A Lee
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - R Seth Pinches
- Boston Children's Hospital, Boston, MA, USA
- Philadelphia College of Osteopathic Medicine, Philadelphia, PA, USA
| | | | | | | | | | - Hannah Comeau
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
| | - Marian H Harris
- Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Suzanne J Forrest
- Harvard Medical School, Boston, MA, USA
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
| | - Catherine M Clinton
- Boston Children's Hospital, Boston, MA, USA
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
| | - Brian D Crompton
- Harvard Medical School, Boston, MA, USA
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
| | - Junne Kamihara
- Harvard Medical School, Boston, MA, USA
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
| | - Laura E MacConaill
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | | | - Neal I Lindeman
- Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Eliezer Van Allen
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
| | - Steven G DuBois
- Harvard Medical School, Boston, MA, USA
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
| | - Wendy B London
- Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Katherine A Janeway
- Harvard Medical School, Boston, MA, USA
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA, USA
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155
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Tourigny DS, Zucker M, Kim M, Russo P, Coleman J, Lee CH, Carlo MI, Chen YB, Hakimi AA, Kotecha RR, Reznik E. Molecular Characterization of the Tumor Microenvironment in Renal Medullary Carcinoma. Front Oncol 2022; 12:910147. [PMID: 35837094 PMCID: PMC9275834 DOI: 10.3389/fonc.2022.910147] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/27/2022] [Indexed: 11/13/2022] Open
Abstract
Renal medullary carcinoma (RMC) is a highly aggressive disease associated with sickle hemoglobinopathies and universal loss of the tumor suppressor gene SMARCB1. RMC has a relatively low rate of incidence compared with other renal cell carcinomas (RCCs) that has hitherto made molecular profiling difficult. To probe this rare disease in detail we performed an in-depth characterization of the RMC tumor microenvironment using a combination of genomic, metabolic and single-cell RNA-sequencing experiments on tissue from a representative untreated RMC patient, complemented by retrospective analyses of archival tissue and existing published data. Our study of the tumor identifies a heterogenous population of malignant cell states originating from the thick ascending limb of the Loop of Henle within the renal medulla. Transformed RMC cells displayed the hallmarks of increased resistance to cell death by ferroptosis and proteotoxic stress driven by MYC-induced proliferative signals. Specifically, genomic characterization of RMC tumors provides substantiating evidence for the recently proposed dependence of SMARCB1-difficient cancers on proteostasis modulated by an intact CDKN2A-p53 pathway. We also provide evidence that increased cystine-mTORC-GPX4 signaling plays a role in protecting transformed RMC cells against ferroptosis. We further propose that RMC has an immune landscape comparable to that of untreated RCCs, including heterogenous expression of the immune ligand CD70 within a sub-population of tumor cells. The latter could provide an immune-modulatory role that serves as a viable candidate for therapeutic targeting.
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Affiliation(s)
- David S. Tourigny
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY, United States
- School of Mathematics, University of Birmingham, Birmingham, United Kingdom
- *Correspondence: David S. Tourigny, ; A. Ari Hakimi, ; Ritesh R. Kotecha, ; Ed Reznik,
| | - Mark Zucker
- Computational Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Minsoo Kim
- Computational Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Paul Russo
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Jonathan Coleman
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Chung-Han Lee
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Maria I. Carlo
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Ying-Bei Chen
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - A. Ari Hakimi
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- *Correspondence: David S. Tourigny, ; A. Ari Hakimi, ; Ritesh R. Kotecha, ; Ed Reznik,
| | - Ritesh R. Kotecha
- Genitourinary Oncology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- *Correspondence: David S. Tourigny, ; A. Ari Hakimi, ; Ritesh R. Kotecha, ; Ed Reznik,
| | - Ed Reznik
- Computational Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- *Correspondence: David S. Tourigny, ; A. Ari Hakimi, ; Ritesh R. Kotecha, ; Ed Reznik,
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156
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Xie X, Bian Y, Li H, Yin J, Tian L, Jiang R, Zeng Z, Shi X, Lei Z, Hou C, Qu Y, Wang L, Shen J. A Comprehensive Understanding of the Genomic Bone Tumor Landscape: A Multicenter Prospective Study. Front Oncol 2022; 12:835004. [PMID: 35756627 PMCID: PMC9213736 DOI: 10.3389/fonc.2022.835004] [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: 12/14/2021] [Accepted: 05/09/2022] [Indexed: 11/25/2022] Open
Abstract
Complexity and heterogeneity increases the difficulty of diagnosis and treatment of bone tumors. We aimed to identify the mutational characterization and potential biomarkers of bone tumors. In this study, a total of 357 bone tumor patients were recruited and the next generation sequencing (NGS)-based YuanSu450 panel, that includes both DNA and RNA sequencing, was performed for genomic alteration identification. The most common mutated genes in bone tumors included TP53, NCOR1, VEGFA, RB1, CCND3, CDKN2A, GID4, CCNE1, TERT, and MAP2K4. The amplification of genes such as NCOR1, VEGFA, and CCND3 mainly occurred in osteosarcoma. Germline mutation analysis reveal a high frequency of HRD related mutations (46.4%, 13/28) in this cohort. With the assistance of RNA sequencing, 16.8% (19/113) gene fusions were independently detected in 20% (16/79) of patients. Nearly 34.2% of patients harbored actionable targeted mutations, of which the most common mutation is CDKN2A deletion. The different mutational characterizations between juvenile patients and adult patients indicated the potential effect of age in bone tumor treatment. According to the genomic alterations, the diagnosis of 26 (7.28%) bone tumors were corrected. The most easily misdiagnosed bone tumor included malignant giant cell tumors of bone (2.8%, 10/357) and fibrous dysplasia of bone (1.7%, 6/357). Meanwhile, we found that the mutations of MUC16 may be a potential biomarker for the diagnosis of mesenchymal chondrosarcomas. Our results indicated that RNA sequencing effectively complements DNA sequencing and increased the detection rate of gene fusions, supporting that NGS technology can effectively assist the diagnosis of bone tumors.
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Affiliation(s)
- Xianbiao Xie
- Department of Musculoskeletal Oncology Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yiying Bian
- Department of Musculoskeletal Oncology Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Haomiao Li
- Department of Musculoskeletal Oncology, Center for Orthopaedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Junqiang Yin
- Department of Musculoskeletal Oncology Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Lantian Tian
- Department of Hepatobiliary Surgery, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Renbing Jiang
- Department of Bone and Soft Tissue, Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, China
| | - Ziliang Zeng
- Department of Musculoskeletal Oncology Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xiaoliang Shi
- Department of Medicine, Shanghai OrigiMed Co., Ltd, Shanghai, China
| | - Zixiong Lei
- Department of Musculoskeletal Oncology, Center for Orthopaedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Changhe Hou
- Department of Musculoskeletal Oncology, Center for Orthopaedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Yueting Qu
- Department of Medicine, Shanghai OrigiMed Co., Ltd, Shanghai, China
| | - Liwei Wang
- Department of Medicine, Shanghai OrigiMed Co., Ltd, Shanghai, China
| | - Jingnan Shen
- Department of Musculoskeletal Oncology Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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157
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Azatyan A, Zaphiropoulos PG. Circular and Fusion RNAs in Medulloblastoma Development. Cancers (Basel) 2022; 14:cancers14133134. [PMID: 35804907 PMCID: PMC9264760 DOI: 10.3390/cancers14133134] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/20/2022] [Accepted: 06/23/2022] [Indexed: 01/27/2023] Open
Abstract
Simple Summary Expression of circular RNAs is known to be deregulated in cancer. Here the most comprehensive set of differentially expressed RNA circles in medulloblastoma compared to cerebellum is provided. Additionally, fusion RNAs are also identified in both cancerous and normal cerebellar tissue. Some of the fusions detected in medulloblastoma are generated by genomic rearrangements that link different genes. However, fusion RNAs are also detected in normal cerebellum. In fact, there are cases where the same fusion RNA is also found in medulloblastoma. This observation underscores that the formation of fusion transcripts may not be limited to chromosomal events but could also result from mechanisms that act at the RNA level. These include read-through transcription of neighboring genes and intermolecular splicing of pre-mRNAs from different genes Importantly, these RNA “recombination” events occur not only in normal but also in cancerous tissue. Abstract Background. The cerebellar cancer medulloblastoma is the most common childhood cancer in the brain. Methods. RNA sequencing of 81 human biospecimens of medulloblastoma using pipelines to detect circular and fusion RNAs. Validation via PCR and Sanger sequencing. Results. 27, 56, 28 and 11 RNA circles were found to be uniquely up-regulated, while 149, 7, 20 and 15 uniquely down-regulated in the SHH, WNT, Group 3, and Group 4 medulloblastoma subtypes, respectively. Moreover, linear and circular fusion RNAs containing exons from distinct genes joined at canonical splice sites were also identified. These were generally expressed less than the circular RNAs, however the expression of both the linear and the circular fusions was comparable. Importantly, the expression of the fusions in medulloblastoma was also comparable to that of cerebellum. Conclusions. A significant number of fusions in tumor may be generated by mechanisms similar to the ones generating fusions in normal tissue. Some fusions could be rationalized by read-through transcription of two neighboring genes. However, for other fusions, e.g., a linear fusion with an exon from a downstream gene joined 5′ to 3′ with an exon from an upstream gene, more complicated splicing mechanisms, e.g., trans-splicing, have to be postulated.
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158
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Sudarshan D, Avvakumov N, Lalonde ME, Alerasool N, Joly-Beauparlant C, Jacquet K, Mameri A, Lambert JP, Rousseau J, Lachance C, Paquet E, Herrmann L, Thonta Setty S, Loehr J, Bernardini MQ, Rouzbahman M, Gingras AC, Coulombe B, Droit A, Taipale M, Doyon Y, Côté J. Recurrent chromosomal translocations in sarcomas create a megacomplex that mislocalizes NuA4/TIP60 to Polycomb target loci. Genes Dev 2022; 36:664-683. [PMID: 35710139 DOI: 10.1101/gad.348982.121] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 05/31/2022] [Indexed: 11/25/2022]
Abstract
Chromosomal translocations frequently promote carcinogenesis by producing gain-of-function fusion proteins. Recent studies have identified highly recurrent chromosomal translocations in patients with endometrial stromal sarcomas (ESSs) and ossifying fibromyxoid tumors (OFMTs), leading to an in-frame fusion of PHF1 (PCL1) to six different subunits of the NuA4/TIP60 complex. While NuA4/TIP60 is a coactivator that acetylates chromatin and loads the H2A.Z histone variant, PHF1 is part of the Polycomb repressive complex 2 (PRC2) linked to transcriptional repression of key developmental genes through methylation of histone H3 on lysine 27. In this study, we characterize the fusion protein produced by the EPC1-PHF1 translocation. The chimeric protein assembles a megacomplex harboring both NuA4/TIP60 and PRC2 activities and leads to mislocalization of chromatin marks in the genome, in particular over an entire topologically associating domain including part of the HOXD cluster. This is linked to aberrant gene expression-most notably increased expression of PRC2 target genes. Furthermore, we show that JAZF1-implicated with a PRC2 component in the most frequent translocation in ESSs, JAZF1-SUZ12-is a potent transcription activator that physically associates with NuA4/TIP60, its fusion creating outcomes similar to those of EPC1-PHF1 Importantly, the specific increased expression of PRC2 targets/HOX genes was also confirmed with ESS patient samples. Altogether, these results indicate that most chromosomal translocations linked to these sarcomas use the same molecular oncogenic mechanism through a physical merge of NuA4/TIP60 and PRC2 complexes, leading to mislocalization of histone marks and aberrant Polycomb target gene expression.
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Affiliation(s)
- Deepthi Sudarshan
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
| | - Nikita Avvakumov
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
| | - Marie-Eve Lalonde
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
| | - Nader Alerasool
- Donnelly Centre for Cellular and Biomolecular Research, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| | - Charles Joly-Beauparlant
- Computational Biology Laboratory, CHU de Québec-Université Laval Research Center, Quebec City, Quebec G1V 4G2, Canada
| | - Karine Jacquet
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
| | - Amel Mameri
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
| | - Jean-Philippe Lambert
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada.,Centre for Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario M5G 1X5, Canada
| | - Justine Rousseau
- Institut de Recherches Cliniques de Montréal, Department of Biochemistry and Molecular Medicine, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| | - Catherine Lachance
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
| | - Eric Paquet
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
| | - Lara Herrmann
- Computational Biology Laboratory, CHU de Québec-Université Laval Research Center, Quebec City, Quebec G1V 4G2, Canada
| | - Samarth Thonta Setty
- Computational Biology Laboratory, CHU de Québec-Université Laval Research Center, Quebec City, Quebec G1V 4G2, Canada
| | - Jeremy Loehr
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
| | - Marcus Q Bernardini
- Department of Gynecologic Oncology, Princess Margaret Cancer Center, University Health Network, Sinai Health System, Toronto, Ontario M5B 2M9, Canada.,Department of Obstetrics and Gynecology, University of Toronto, Toronto, Ontario M5G 1X8, Canada
| | - Marjan Rouzbahman
- Department of Laboratory Medicine and Pathobiology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario M5G 2C4, Canada
| | - Anne-Claude Gingras
- Centre for Systems Biology, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario M5G 1X5, Canada
| | - Benoit Coulombe
- Institut de Recherches Cliniques de Montréal, Department of Biochemistry and Molecular Medicine, Université de Montréal, Montreal, Quebec H3T 1J4, Canada
| | - Arnaud Droit
- Computational Biology Laboratory, CHU de Québec-Université Laval Research Center, Quebec City, Quebec G1V 4G2, Canada
| | - Mikko Taipale
- Donnelly Centre for Cellular and Biomolecular Research, Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| | - Yannick Doyon
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
| | - Jacques Côté
- Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Center, Laval University Cancer Research Center, Quebec City, Quebec G1R 3S3, Canada
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Parker AC, Quinteros BI, Piccolo SR. The DNA methylation landscape of five pediatric-tumor types. PeerJ 2022; 10:e13516. [PMID: 35707123 PMCID: PMC9190670 DOI: 10.7717/peerj.13516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 05/09/2022] [Indexed: 01/17/2023] Open
Abstract
Fewer DNA mutations have been identified in pediatric tumors than in adult tumors, suggesting that alternative tumorigenic mechanisms, including aberrant DNA methylation, may play a prominent role. In one epigenetic process of regulating gene expression, methyl groups are attached at the 5-carbon of the cytosine ring, leading to 5-methylcytosine (5mC). In somatic cells, 5mC occurs mostly in CpG islands, which are often within promoter regions. In Wilms tumors and acute myeloid leukemias, increased levels of epigenetic silencing have been associated with worse patient outcomes. However, to date, researchers have studied methylation primarily in adult tumors and for specific genes-but not on a pan-pediatric cancer scale. We addressed these gaps first by aggregating methylation data from 309 noncancerous samples, establishing baseline expectations for each probe and gene. Even though these samples represent diverse, noncancerous tissue types and population ancestral groups, methylation levels were consistent for most genes. Second, we compared tumor methylation levels against the baseline values for 489 pediatric tumors representing five cancer types: Wilms tumors, clear cell sarcomas of the kidney, rhabdoid tumors, neuroblastomas, and osteosarcomas. Tumor hypomethylation was more common than hypermethylation, and as many as 41.7% of genes were hypomethylated in a given tumor, compared to a maximum of 34.2% for hypermethylated genes. However, in known oncogenes, hypermethylation was more than twice as common as in other genes. We identified 139 probes (31 genes) that were differentially methylated between at least one tumor type and baseline levels, and 32 genes that were differentially methylated across the pediatric tumor types. We evaluated whether genomic events and aberrant methylation were mutually exclusive but did not find evidence of this phenomenon.
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160
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Boulouadnine B, de Villenfagne L, Galant C, Sciot R, Brichard B, Demoulin JB. Identification of a novel PHIP::BRAF gene fusion in infantile fibrosarcoma. Genes Chromosomes Cancer 2022; 61:678-682. [PMID: 35672277 DOI: 10.1002/gcc.23077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/23/2022] [Accepted: 05/30/2022] [Indexed: 11/07/2022] Open
Abstract
INTRODUCTION The ETV6::NTRK3 fusion is the most common gene alteration in infantile fibrosarcoma, a soft tissue tumor affecting patients under two years of age. Less frequently, these tumors harbor fusions of genes encoding other kinases, such as BRAF, which activates MEK in the mitogen-activated protein kinase pathway. The identification and characterization of these oncogenes is crucial to facilitate diagnosis, validate new treatments and better understand the pathophysiology of these neoplasms. METHODS Herein, we analyzed an ETV6::NTRK3-negative infantile fibrosarcoma from a 5-day-old patient by RNA-sequencing to identify new fusion transcripts. Functional exploration of the fusion of interest was performed by in vitro assays to study its activity, oncogenicity and sensitivity to the MEK inhibitor trametinib. RESULTS We identified a novel fusion involving the PHIP and BRAF genes. The corresponding fusion protein constitutively activated the mitogen-activated protein kinase pathway, resulting in fibroblast transformation. Treatment of transfected cells with trametinib effectively inhibited signaling by PHIP::BRAF. CONCLUSION PHIP::BRAF is a novel fusion oncogene that can be targeted by trametinib in infantile fibrosarcoma. This article is protected by copyright. All rights reserved.
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Affiliation(s)
| | | | - Christine Galant
- Department of Pathology, Cliniques Universitaires Saint-Luc and Université catholique de Louvain, Brussels, Belgium
| | - Raphael Sciot
- Department of Pathology, University Hospital Leuven and KULeuven, Leuven, Belgium
| | - Bénédicte Brichard
- Department of Pediatric Hematology and Oncology, Cliniques Universitaires Saint-Luc and Université catholique de Louvain, Brussels, Belgium
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161
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Creaney J, Patch AM, Addala V, Sneddon SA, Nones K, Dick IM, Lee YCG, Newell F, Rouse EJ, Naeini MM, Kondrashova O, Lakis V, Nakas A, Waller D, Sharkey A, Mukhopadhyay P, Kazakoff SH, Koufariotis LT, Davidson AL, Ramarao-Milne P, Holmes O, Xu Q, Leonard C, Wood S, Grimmond SM, Bueno R, Fennell DA, Pearson JV, Robinson BW, Waddell N. Comprehensive genomic and tumour immune profiling reveals potential therapeutic targets in malignant pleural mesothelioma. Genome Med 2022; 14:58. [PMID: 35637530 PMCID: PMC9150319 DOI: 10.1186/s13073-022-01060-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 05/15/2022] [Indexed: 12/14/2022] Open
Abstract
Background Malignant pleural mesothelioma (MPM) has a poor overall survival with few treatment options. Whole genome sequencing (WGS) combined with the immune features of MPM offers the prospect of identifying changes that could inform future clinical trials. Methods We analysed somatic mutations from 229 MPM samples, including previously published data and 58 samples that had undergone WGS within this study. This was combined with RNA-seq analysis to characterize the tumour immune environment. Results The comprehensive genome analysis identified 12 driver genes, including new candidate genes. Whole genome doubling was a frequent event that correlated with shorter survival. Mutational signature analysis revealed SBS5/40 were dominant in 93% of samples, and defects in homologous recombination repair were infrequent in our cohort. The tumour immune environment contained high M2 macrophage infiltrate linked with MMP2, MMP14, TGFB1 and CCL2 expression, representing an immune suppressive environment. The expression of TGFB1 was associated with overall survival. A small subset of samples (less than 10%) had a higher proportion of CD8 T cells and a high cytolytic score, suggesting a ‘hot’ immune environment independent of the somatic mutations. Conclusions We propose accounting for genomic and immune microenvironment status may influence therapeutic planning in the future. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-022-01060-8.
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162
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Ding Y, Sun C, Su W, Miao C, He X, Wang JS, Zhang ZH. Detecting anaplastic lymphoma kinase (ALK) gene rearrangements with next-generation sequencing remains a reliable approach in patients with non-small-cell lung cancer. Virchows Arch 2022; 481:405-419. [PMID: 35624360 DOI: 10.1007/s00428-022-03339-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 04/12/2022] [Accepted: 05/12/2022] [Indexed: 11/24/2022]
Abstract
Next-generation sequencing (NGS) is rapidly becoming routine in clinical oncology practice to identify therapeutic biomarkers, including gene rearrangements in anaplastic lymphoma kinase (ALK). Our study investigated the concordance of ALK positivity evaluated by DNA-based NGS with orthogonal ALK testing methods such as fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and RNA-based NGS (RNA-NGS). Thirty-eight patients with lung adenocarcinoma who were detected with ALK rearrangements using DNA-NGS and also had adequate tissue samples submitted for FISH, IHC, and RNA-NGS, were included in this study. Of the 38 patients, RNA samples from 3 patients failed quality control for RNA-NGS. The concordance of ALK positivity was calculated relative to DNA-NGS results. The concordance rates were 97.1% (34/35) for RNA-NGS, 94.7% (36/38) for IHC, and 97.4% (37/38) for FISH. DNA-NGS detected single ALK rearrangements in 14 (35.0%) patients and complex ALK rearrangements in 26 (65.0%). RNA-NGS detected only single transcripts of the primary ALK fusions. A novel LANCL1-ALK (L7:A20) detected using DNA-NGS was detected as EML4-ALK (E13:A20) transcripts using RNA-NGS. Interestingly, patients with single ALK rearrangements were more likely to be detected with atypical isolated red signals (p < 0.001), while patients with complex ALK rearrangements were more likely to be detected with atypical split red and green signals less than 2 signal diameters apart (p < 0.001). Our study highlights the reliability of NGS in the accurate detection of specific ALK fusion variants and concomitant mutations that are crucial for individualized treatment decisions in patients with lung cancer.
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Affiliation(s)
- Ying Ding
- Department of Pathology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Chang Sun
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, 210029, China
| | - Wei Su
- The First School of Clinical Medicine, Nanjing Medical University, Nanjing, 210029, China
| | - Chen Miao
- Department of Pathology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Xiao He
- Department of Pathology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Jin-Song Wang
- Department of Pathology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210000, China
| | - Zhi-Hong Zhang
- Department of Pathology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
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163
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Shukla N, Levine MF, Gundem G, Domenico D, Spitzer B, Bouvier N, Arango-Ossa JE, Glodzik D, Medina-Martínez JS, Bhanot U, Gutiérrez-Abril J, Zhou Y, Fiala E, Stockfisch E, Li S, Rodriguez-Sanchez MI, O'Donohue T, Cobbs C, Roehrl MHA, Benhamida J, Iglesias Cardenas F, Ortiz M, Kinnaman M, Roberts S, Ladanyi M, Modak S, Farouk-Sait S, Slotkin E, Karajannis MA, Dela Cruz F, Glade Bender J, Zehir A, Viale A, Walsh MF, Kung AL, Papaemmanuil E. Feasibility of whole genome and transcriptome profiling in pediatric and young adult cancers. Nat Commun 2022; 13:2485. [PMID: 35585047 PMCID: PMC9117241 DOI: 10.1038/s41467-022-30233-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 04/21/2022] [Indexed: 02/07/2023] Open
Abstract
The utility of cancer whole genome and transcriptome sequencing (cWGTS) in oncology is increasingly recognized. However, implementation of cWGTS is challenged by the need to deliver results within clinically relevant timeframes, concerns about assay sensitivity, reporting and prioritization of findings. In a prospective research study we develop a workflow that reports comprehensive cWGTS results in 9 days. Comparison of cWGTS to diagnostic panel assays demonstrates the potential of cWGTS to capture all clinically reported mutations with comparable sensitivity in a single workflow. Benchmarking identifies a minimum of 80× as optimal depth for clinical WGS sequencing. Integration of germline, somatic DNA and RNA-seq data enable data-driven variant prioritization and reporting, with oncogenic findings reported in 54% more patients than standard of care. These results establish key technical considerations for the implementation of cWGTS as an integrated test in clinical oncology. Cancer whole-genome and transcriptome sequencing (cWGTS) has been challenging to implement in clinical settings. Here, the authors develop a workflow to deliver robust cWGTS analyses and reports within clinically-relevant timeframes for paediatric, adolescent and young adult solid tumour patients.
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Affiliation(s)
- N Shukla
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - M F Levine
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - G Gundem
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - D Domenico
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - B Spitzer
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - N Bouvier
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - J E Arango-Ossa
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - D Glodzik
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - J S Medina-Martínez
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - U Bhanot
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Precision Pathology Biobanking Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - J Gutiérrez-Abril
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Y Zhou
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - E Fiala
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - E Stockfisch
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - S Li
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - T O'Donohue
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - C Cobbs
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - M H A Roehrl
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Precision Pathology Biobanking Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - J Benhamida
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - F Iglesias Cardenas
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - M Ortiz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - M Kinnaman
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - S Roberts
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - M Ladanyi
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - S Modak
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - S Farouk-Sait
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - E Slotkin
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - M A Karajannis
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - F Dela Cruz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - J Glade Bender
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - A Zehir
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - A Viale
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - M F Walsh
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - A L Kung
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | - E Papaemmanuil
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. .,Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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164
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Kim CG, Sim NS, Kim JE, Yun KH, Lee YH, Kim SH, Baek W, Han YD, Kim SK, Kim JH, Koh YW, Jung I, Shin SJ, Rha SY, Ahn JH, Kim HS. Phase II clinical trial of Eribulin-gemcitabine combination therapy in previously treated patients with advanced liposarcoma or leiomyosarcoma. Clin Cancer Res 2022; 28:3225-3234. [PMID: 35583824 DOI: 10.1158/1078-0432.ccr-22-0518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 04/08/2022] [Accepted: 05/16/2022] [Indexed: 11/16/2022]
Abstract
PURPOSE Monotherapy with eribulin or gemcitabine has been found to be moderately effective in treating soft-tissue sarcomas (STS). In this study, we evaluated the efficacy and safety of eribulin-gemcitabine combination therapy for the two most common histologic types of STS, liposarcoma and leiomyosarcoma. PATIENTS AND METHODS In this non-randomized, multicenter, phase II study, we included patients with progressive disease who had received one or two courses of chemotherapy that included doxorubicin. Patients were administered 1.4 mg/m2 eribulin and 1,000 mg/m2 gemcitabine on days 1 and 8 every 3 weeks. The primary endpoint was progression-free survival rate at 12 weeks (PFSR12wks), with null and alternative hypotheses of PFSR12wks {less than or equal to}20.0% and {greater than or equal to}40.0%, respectively. Exploratory biomarker analyses with next-generation sequencing (NGS) were performed on pretreatment tumor samples. RESULTS Among the 37 patients included, the overall PFSR12wks was 73.0%, achieving the primary endpoint. The objective response rate, disease control rate, median progression-free survival, and median overall survival were 16.2%, 78.4%, 5.6 months, and 31.9 months, respectively, without differences according to histologic type. New safety signals and treatment-related deaths were not documented. NGS-based transcriptome analysis revealed that functional enrichment in the transforming growth factor-ß pathway was mostly associated with a poor outcome, whereas single genetic alterations largely failed to predict treatment outcome. CONCLUSIONS Eribulin-gemcitabine combination therapy showed promising activity and an acceptable safety profile in patients with liposarcoma or leiomyosarcoma. Gene expression profiling with pathway enrichment analysis would have possibilities to have predictive value for survival outcome, necessitating further investigation to confirm.
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Affiliation(s)
- Chang Gon Kim
- Yonsei University College of Medicine, Seoul, Korea (South), Republic of
| | - Nam Suk Sim
- Yonsei University College of Medicine, Severance Hospital, Korea (South), Republic of
| | - Jeong Eun Kim
- Asan Medical Center, , University of Ulsan College of Medicine, Seoul, Korea (South), Republic of
| | - Kum-Hee Yun
- Yonsei Cancer Center, Seoul, Korea (South), Republic of
| | - Young Han Lee
- Yonsei University College of medicine, Seoul, Korea (South), Republic of
| | - Seung Hyun Kim
- Yonsei University College of Medicine, Seoul, Korea (South), Republic of
| | - Wooyeol Baek
- Yonsei University College of Medicine, Korea (South), Republic of
| | - Yoon Dae Han
- Yonsei University College of Medicine, Seoul, Korea (South), Republic of
| | - Sang Kyum Kim
- Yonsei University College of Medicine, Seoul, Korea (South), Republic of
| | - Jee Hung Kim
- Gangnam Severance Hospital, Seoul, Korea (South), Republic of
| | - Yoon Woo Koh
- Yonsei University College of Medicine, Seoul, Korea (South), Republic of
| | | | - Su-Jin Shin
- Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea (South), Republic of
| | - Sun Young Rha
- Yonsei University College of Medicine, Seoul, Korea (South), Republic of
| | - Jin-Hee Ahn
- Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea (South), Republic of
| | - Hyo Song Kim
- Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Korea (South), Republic of
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165
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Zhang M, Hwang IT, Li K, Bai J, Chen JF, Weissman T, Zou JY, Lu Z. Classification and clustering of RNA crosslink-ligation data reveal complex structures and homodimers. Genome Res 2022; 32:968-985. [PMID: 35332099 PMCID: PMC9104705 DOI: 10.1101/gr.275979.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 01/11/2022] [Indexed: 12/04/2022]
Abstract
The recent development and application of methods based on the general principle of "crosslinking and proximity ligation" (crosslink-ligation) are revolutionizing RNA structure studies in living cells. However, extracting structure information from such data presents unique challenges. Here, we introduce a set of computational tools for the systematic analysis of data from a wide variety of crosslink-ligation methods, specifically focusing on read mapping, alignment classification, and clustering. We design a new strategy to map short reads with irregular gaps at high sensitivity and specificity. Analysis of previously published data reveals distinct properties and bias caused by the crosslinking reactions. We perform rigorous and exhaustive classification of alignments and discover eight types of arrangements that provide distinct information on RNA structures and interactions. To deconvolve the dense and intertwined gapped alignments, we develop a network/graph-based tool Crosslinked RNA Secondary Structure Analysis using Network Techniques (CRSSANT), which enables clustering of gapped alignments and discovery of new alternative and dynamic conformations. We discover that multiple crosslinking and ligation events can occur on the same RNA, generating multisegment alignments to report complex high-level RNA structures and multi-RNA interactions. We find that alignments with overlapped segments are produced from potential homodimers and develop a new method for their de novo identification. Analysis of overlapping alignments revealed potential new homodimers in cellular noncoding RNAs and RNA virus genomes in the Picornaviridae family. Together, this suite of computational tools enables rapid and efficient analysis of RNA structure and interaction data in living cells.
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Affiliation(s)
- Minjie Zhang
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California, Los Angeles, California 90089, USA
| | - Irena T Hwang
- Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA
| | - Kongpan Li
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California, Los Angeles, California 90089, USA
| | - Jianhui Bai
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California, Los Angeles, California 90089, USA
| | - Jian-Fu Chen
- Center for Craniofacial Molecular Biology, University of Southern California (USC), Los Angeles, California 90033, USA
| | - Tsachy Weissman
- Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA
| | - James Y Zou
- Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA
- Department of Biomedical Data Science and Chan-Zuckerberg Biohub, Stanford University, Palo Alto, California 94305, USA
| | - Zhipeng Lu
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California, Los Angeles, California 90089, USA
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166
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Patel RA, Coleman I, Roudier MP, Konnick EQ, Hanratty B, Dumpit R, Lucas JM, Ang LS, Low JY, Tretiakova MS, Ha G, Lee JK, True LD, De Marzo AM, Nelson PS, Morrissey C, Pritchard CC, Haffner MC. Comprehensive assessment of anaplastic lymphoma kinase in localized and metastatic prostate cancer reveals targetable alterations. CANCER RESEARCH COMMUNICATIONS 2022; 2:277-285. [PMID: 36337169 PMCID: PMC9635400 DOI: 10.1158/2767-9764.crc-21-0156] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/14/2022] [Accepted: 04/14/2022] [Indexed: 06/16/2023]
Abstract
Anaplastic lymphoma kinase (ALK) is a tyrosine kinase with genomic and expression changes in many solid tumors. ALK inhibition is first line therapy for lung cancers with ALK alterations, and an effective therapy in other tumor types, but has not been well-studied in prostate cancer. Here, we aim to delineate the role of ALK genomic and expression changes in primary and metastatic prostate cancer. We determined ALK expression by immunohistochemistry and RNA-Seq, and genomic alterations by NGS. We assessed functional consequences of ALK overexpression and pharmacological ALK inhibition by cell proliferation and cell viability assays. Among 372 primary prostate cancer cases we identified one case with uniformly high ALK protein expression. Genomic analysis revealed a SLC45A3-ALK fusion which promoted oncogenesis in in vitro assays. We observed ALK protein expression in 5/52 (9%) of metastatic prostate cancer cases, of which 4 of 5 had neuroendocrine features. ALK-expressing neuroendocrine prostate cancer had a distinct transcriptional program, and earlier disease progression. An ALK-expressing neuroendocrine prostate cancer model was sensitive to pharmacological ALK inhibition. In summary, we found that ALK overexpression is rare in primary prostate cancer, but more frequent in metastatic prostate cancers with neuroendocrine differentiation. Further, ALK fusions similar to lung cancer are an occasional driver in prostate cancer. Our data suggest that ALK-directed therapies could be an option in selected patients with advanced prostate cancer.
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Affiliation(s)
- Radhika A. Patel
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Ilsa Coleman
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | | | - Eric Q. Konnick
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
- The Brotman Baty Institute for Precision Medicine, Seattle, Washington
| | - Brian Hanratty
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Ruth Dumpit
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Jared M. Lucas
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Lisa S. Ang
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Jin-Yih Low
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Maria S. Tretiakova
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
| | - Gavin Ha
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
- The Brotman Baty Institute for Precision Medicine, Seattle, Washington
| | - John K. Lee
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Lawrence D. True
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
| | - Angelo M. De Marzo
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Peter S. Nelson
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
- The Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Colm Morrissey
- Department of Urology, University of Washington, Seattle, Washington
| | - Colin C. Pritchard
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
- The Brotman Baty Institute for Precision Medicine, Seattle, Washington
| | - Michael C. Haffner
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
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167
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Abstract
Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.
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168
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Konovalov N, Timonin S, Asyutin D, Raevskiy M, Sorokin M, Buzdin A, Kaprovoy S. Transcriptomic Portraits and Molecular Pathway Activation Features of Adult Spinal Intramedullary Astrocytomas. Front Oncol 2022; 12:837570. [PMID: 35387112 PMCID: PMC8978956 DOI: 10.3389/fonc.2022.837570] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 02/21/2022] [Indexed: 11/30/2022] Open
Abstract
In this study, we report 31 spinal intramedullary astrocytoma (SIA) RNA sequencing (RNA-seq) profiles for 25 adult patients with documented clinical annotations. To our knowledge, this is the first clinically annotated RNA-seq dataset of spinal astrocytomas derived from the intradural intramedullary compartment. We compared these tumor profiles with the previous healthy central nervous system (CNS) RNA-seq data for spinal cord and brain and identified SIA-specific gene sets and molecular pathways. Our findings suggest a trend for SIA-upregulated pathways governing interactions with the immune cells and downregulated pathways for the neuronal functioning in the context of normal CNS activity. In two patient tumor biosamples, we identified diagnostic KIAA1549-BRAF fusion oncogenes, and we also found 16 new SIA-associated fusion transcripts. In addition, we bioinformatically simulated activities of targeted cancer drugs in SIA samples and predicted that several tyrosine kinase inhibitory drugs and thalidomide analogs could be potentially effective as second-line treatment agents to aid in the prevention of SIA recurrence and progression.
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Affiliation(s)
| | | | | | - Mikhail Raevskiy
- Omicsway Corp., Walnut, CA, United States.,Moscow Institute of Physics and Technology, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maxim Sorokin
- Moscow Institute of Physics and Technology, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Anton Buzdin
- Omicsway Corp., Walnut, CA, United States.,Moscow Institute of Physics and Technology, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Oncobox Ltd., Moscow, Russia
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169
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Expanding the spectrum of cancer targets by predicting individual gene fusions. Nat Biotechnol 2022; 40:1188-1189. [PMID: 35383308 DOI: 10.1038/s41587-022-01267-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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170
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Lovino M, Montemurro M, Barrese VS, Ficarra E. Identifying the oncogenic potential of gene fusions exploiting miRNAs. J Biomed Inform 2022; 129:104057. [PMID: 35339665 DOI: 10.1016/j.jbi.2022.104057] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 12/11/2022]
Abstract
It is estimated that oncogenic gene fusions cause about 20% of human cancer morbidity. Identifying potentially oncogenic gene fusions may improve affected patients' diagnosis and treatment. Previous approaches to this issue included exploiting specific gene-related information, such as gene function and regulation. Here we propose a model that profits from the previous findings and includes the microRNAs in the oncogenic assessment. We present ChimerDriver, a tool to classify gene fusions as oncogenic or not oncogenic. ChimerDriver is based on a specifically designed neural network and trained on genetic and post-transcriptional information to obtain a reliable classification. The designed neural network integrates information related to transcription factors, gene ontologies, microRNAs and other detailed information related to the functions of the genes involved in the fusion and the gene fusion structure. As a result, the performances on the test set reached 0.83 f1-score and 96% recall. The comparison with state-of-the-art tools returned comparable or higher results. Moreover, ChimerDriver performed well in a real-world case where 21 out of 24 validated gene fusion samples were detected by the gene fusion detection tool Starfusion. ChimerDriver integrates transcriptional and post-transcriptional information in an ad-hoc designed neural network to effectively discriminate oncogenic gene fusions from passenger ones. ChimerDriver source code is freely available at https://github.com/martalovino/ChimerDriver.
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Affiliation(s)
- Marta Lovino
- University of Modena and Reggio Emilia, Via Vivarelli 10/1, 41125 Modena, Italy.
| | | | - Venere S Barrese
- Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, Italy
| | - Elisa Ficarra
- University of Modena and Reggio Emilia, Via Vivarelli 10/1, 41125 Modena, Italy
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171
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Shale C, Cameron DL, Baber J, Wong M, Cowley MJ, Papenfuss AT, Cuppen E, Priestley P. Unscrambling cancer genomes via integrated analysis of structural variation and copy number. CELL GENOMICS 2022; 2:100112. [PMID: 36776527 PMCID: PMC9903802 DOI: 10.1016/j.xgen.2022.100112] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 09/29/2021] [Accepted: 02/25/2022] [Indexed: 11/17/2022]
Abstract
Complex somatic genomic rearrangements and copy number alterations are hallmarks of nearly all cancers. We have developed an algorithm, LINX, to aid interpretation of structural variant and copy number data derived from short-read, whole-genome sequencing. LINX classifies raw structural variant calls into distinct events and predicts their effect on the local structure of the derivative chromosome and the functional impact on affected genes. Visualizations facilitate further investigation of complex rearrangements. LINX allows insights into a diverse range of structural variation events and can reliably detect pathogenic rearrangements, including gene fusions, immunoglobulin enhancer rearrangements, intragenic deletions, and duplications. Uniquely, LINX also predicts chained fusions that we demonstrate account for 13% of clinically relevant oncogenic fusions. LINX also reports a class of inactivation events that we term homozygous disruptions that may be a driver mutation in up to 9% of tumors and may frequently affect PTEN, TP53, and RB1.
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Affiliation(s)
- Charles Shale
- Hartwig Medical Foundation Australia, Sydney, NSW, Australia
- Hartwig Medical Foundation, Science Park 408, Amsterdam, the Netherlands
| | - Daniel L. Cameron
- Hartwig Medical Foundation Australia, Sydney, NSW, Australia
- Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, VIC, Australia
| | - Jonathan Baber
- Hartwig Medical Foundation Australia, Sydney, NSW, Australia
- Hartwig Medical Foundation, Science Park 408, Amsterdam, the Netherlands
| | - Marie Wong
- Children’s Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women’s and Children’s Health, UNSW Sydney, Kensington, NSW, Australia
| | - Mark J. Cowley
- Children’s Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women’s and Children’s Health, UNSW Sydney, Kensington, NSW, Australia
| | - Anthony T. Papenfuss
- Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, VIC, Australia
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Edwin Cuppen
- Hartwig Medical Foundation, Science Park 408, Amsterdam, the Netherlands
- Center for Molecular Medicine and Oncode Institute, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, the Netherlands
| | - Peter Priestley
- Hartwig Medical Foundation Australia, Sydney, NSW, Australia
- Hartwig Medical Foundation, Science Park 408, Amsterdam, the Netherlands
- Corresponding author
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172
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Borden ES, Buetow KH, Wilson MA, Hastings KT. Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation. Front Oncol 2022; 12:836821. [PMID: 35311072 PMCID: PMC8929516 DOI: 10.3389/fonc.2022.836821] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 02/07/2022] [Indexed: 12/16/2022] Open
Abstract
Prioritization of immunogenic neoantigens is key to enhancing cancer immunotherapy through the development of personalized vaccines, adoptive T cell therapy, and the prediction of response to immune checkpoint inhibition. Neoantigens are tumor-specific proteins that allow the immune system to recognize and destroy a tumor. Cancer immunotherapies, such as personalized cancer vaccines, adoptive T cell therapy, and immune checkpoint inhibition, rely on an understanding of the patient-specific neoantigen profile in order to guide personalized therapeutic strategies. Genomic approaches to predicting and prioritizing immunogenic neoantigens are rapidly expanding, raising new opportunities to advance these tools and enhance their clinical relevance. Predicting neoantigens requires acquisition of high-quality samples and sequencing data, followed by variant calling and variant annotation. Subsequently, prioritizing which of these neoantigens may elicit a tumor-specific immune response requires application and integration of tools to predict the expression, processing, binding, and recognition potentials of the neoantigen. Finally, improvement of the computational tools is held in constant tension with the availability of datasets with validated immunogenic neoantigens. The goal of this review article is to summarize the current knowledge and limitations in neoantigen prediction, prioritization, and validation and propose future directions that will improve personalized cancer treatment.
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Affiliation(s)
- Elizabeth S Borden
- Department of Basic Medical Sciences, College of Medicine-Phoenix, University of Arizona, Phoenix, AZ, United States.,Department of Research and Internal Medicine (Dermatology), Phoenix Veterans Affairs Health Care System, Phoenix, AZ, United States
| | - Kenneth H Buetow
- School of Life Sciences, Arizona State University, Tempe, AZ, United States.,Center for Evolution and Medicine, Arizona State University, Tempe, AZ, United States
| | - Melissa A Wilson
- School of Life Sciences, Arizona State University, Tempe, AZ, United States.,Center for Evolution and Medicine, Arizona State University, Tempe, AZ, United States
| | - Karen Taraszka Hastings
- Department of Basic Medical Sciences, College of Medicine-Phoenix, University of Arizona, Phoenix, AZ, United States.,Department of Research and Internal Medicine (Dermatology), Phoenix Veterans Affairs Health Care System, Phoenix, AZ, United States
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173
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Cheng R, Xu Z, Luo M, Wang P, Cao H, Jin X, Zhou W, Xiao L, Jiang Q. Identification of alternative splicing-derived cancer neoantigens for mRNA vaccine development. Brief Bioinform 2022; 23:bbab553. [PMID: 35279714 DOI: 10.1093/bib/bbab553] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 11/15/2021] [Accepted: 12/02/2021] [Indexed: 12/17/2023] Open
Abstract
Messenger RNA (mRNA) vaccines have shown great potential for anti-tumor therapy due to the advantages in safety, efficacy and industrial production. However, it remains a challenge to identify suitable cancer neoantigens that can be targeted for mRNA vaccines. Abnormal alternative splicing occurs in a variety of tumors, which may result in the translation of abnormal transcripts into tumor-specific proteins. High-throughput technologies make it possible for systematic characterization of alternative splicing as a source of suitable target neoantigens for mRNA vaccine development. Here, we summarized difficulties and challenges for identifying alternative splicing-derived cancer neoantigens from RNA-seq data and proposed a conceptual framework for designing personalized mRNA vaccines based on alternative splicing-derived cancer neoantigens. In addition, several points were presented to spark further discussion toward improving the identification of alternative splicing-derived cancer neoantigens.
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Affiliation(s)
- Rui Cheng
- Harbin Institute of Technology, China
| | | | - Meng Luo
- Harbin Institute of Technology, China
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174
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Park SJ, Kang YE, Kim JH, Park JL, Kim SK, Baek SW, Chu IS, Yi S, Lee SE, Park YJ, Jung EJ, Kim JM, Ko HM, Kim JR, Jung SN, Won HR, Chang JW, Koo BS, Kim SY. Transcriptomic analysis of papillary thyroid cancer focused on immune-subtyping, oncogenic fusion, and recurrence. Clin Exp Otorhinolaryngol 2022; 15:183-193. [PMID: 35255661 PMCID: PMC9149236 DOI: 10.21053/ceo.2021.02215] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 01/08/2022] [Indexed: 11/22/2022] Open
Abstract
Objectives Thyroid cancer is the most common endocrine tumor, with rapidly increasing incidence worldwide. However, its transcriptomic characteristics associated with immunological signatures, driver fusions, and recurrence markers remain unclear. We aimed to investigate the transcriptomic characteristics of advanced papillary thyroid cancer. Methods This study included 282 papillary thyroid cancer tumor samples and 155 normal samples from Chungnam National University Hospital and Seoul National University Hospital. Transcriptomic quantification was determined by high-throughput RNA sequencing. We investigated the associations of clinical parameters and molecular signatures using RNA sequencing. We validated predictive biomarkers using the Cancer Genome Atlas database. Results Through a comparison of differentially expressed genes, gene sets, and pathways in papillary thyroid cancer compared to normal tumor-adjacent tissue, we found increased immune signaling associated with cytokines or T cells and decreased thyroid hormone synthetic pathways. In addition, patients with recurrence presented increased CD8+ T-cell and Th1-cell signatures. Interestingly, we found differentially overexpressed genes related to immune-escape signaling such as CTLA4, IDO1, LAG3, and PDCD1 in advanced papillary thyroid cancer with a low thyroid differentiation score. Fusion analysis showed that the PI3K and mitogen-activated protein kinase (MAPK) signaling pathways were regulated differently according to the RET fusion partner genes (CCDC6 or NCOA4). Finally, we identified HOXD9 as a novel molecular biomarker that predicts the recurrence of thyroid cancer in addition to known risk factors (tumor size, lymph node metastasis, and extrathyroidal extension). Conclusion We identified a high association with immune-escape signaling in the immune-hot group with aggressive clinical characteristics among Korean thyroid cancer patients. Moreover, RET fusion differentially regulated PI3K and MAPK signaling depending on the partner gene of RET, and HOXD9 was found to be a recurrence marker for advanced papillary thyroid cancer.
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175
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Kim P, Tan H, Liu J, Kumar H, Zhou X. FusionAI, a DNA-sequence-based deep learning protocol reduces the false positives of human fusion gene prediction. STAR Protoc 2022; 3:101185. [PMID: 35252882 PMCID: PMC8892011 DOI: 10.1016/j.xpro.2022.101185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Even though there were many tool developments of fusion gene prediction from NGS data, too many false positives are still an issue. Wise use of the genomic features around the fusion gene breakpoints will be helpful to identify reliable fusion genes efficiently. For this aim, we developed FusionAI, a deep learning pipeline predicting human fusion gene breakpoints from DNA sequence. FusionAI is freely available via https://compbio.uth.edu/FusionGDB2/FusionAI. For complete details on the use and execution of this protocol, please refer to Kim et al. (2021b). FusionAI can predict the fusion breakpoints from the given DNA sequence FusionAI can reduce the false positives of the predicted fusion genes by other tools FusionAI can identify the genomic features related to the genomic breakage FusionAI creates a landscape image of 44 human genomic features around the breakpoints
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176
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Wei S, Kutikov A, Patchefsky AS, Flieder DB, Talarchek JN, Al-Saleem T, Dulaimi E, Uzzo RG, Testa JR, Pei J. Papillary Renal Neoplasm With Reverse Polarity Is Often Cystic: Report of 7 Cases and Review of 93 Cases in the Literature. Am J Surg Pathol 2022; 46:336-343. [PMID: 34352808 DOI: 10.1097/pas.0000000000001773] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Papillary renal neoplasm with reverse polarity (PRNRP) is a newly proposed entity with distinct histology and frequent KRAS mutations. To date, 93 cases of PRNRPs have been reported. In this study, we present 7 new cases of PRNRP and review the literature. Most of the pathologic features in our 7 cases are similar to those previously reported cases. However, all 7 of our cases showed at least partial cystic changes, which was not stressed in prior studies. Single-nucleotide polymorphism-microarray based chromosomal analysis demonstrated no trisomy or other alteration of chromosomes 7 or 17; and no loss or other alteration of chromosome Y was detected in all 7 cases. Next-generation sequencing detected KRAS missense mutations in 4 of 7 cases. No fusion genes were detected. In summary, PRNRP is a small, well-circumscribed often encapsulated and cystic neoplasm with loose papillary formations. Cuboidal tumor cells always have eosinophilic cytoplasm and nuclei located at the pole opposite the basement membrane with a low World Health Organization (WHO)/International Society of Urologic Pathologists (ISUP) nuclear grade. The fibrovascular cores can be hyalinized or edematous. Macrophage aggregates and intracellular hemosiderin are uncommon, and no psammoma bodies or necrosis should be seen. Immunophenotypically, this tumor is always positive for CK7 and GATA3, and negative for CD117 and vimentin. CD10 and AMACR can be positive, but often weakly and focally. PRNRP often has KRAS mutations, however, only 32% of cases have chromosomal abnormalities in chromosomes 7, 17, and Y. No recurrences, metastases, or tumor-related deaths have been reported following complete resection.
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MESH Headings
- Adult
- Aged
- Aged, 80 and over
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Carcinoma, Papillary/diagnosis
- Carcinoma, Papillary/genetics
- Carcinoma, Papillary/metabolism
- Carcinoma, Papillary/pathology
- Carcinoma, Renal Cell/diagnosis
- Carcinoma, Renal Cell/genetics
- Carcinoma, Renal Cell/metabolism
- Carcinoma, Renal Cell/pathology
- Cysts/diagnosis
- Cysts/genetics
- Cysts/metabolism
- Cysts/pathology
- Female
- Humans
- Kidney Neoplasms/diagnosis
- Kidney Neoplasms/genetics
- Kidney Neoplasms/metabolism
- Kidney Neoplasms/pathology
- Male
- Middle Aged
- Prognosis
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Affiliation(s)
| | | | | | | | | | | | | | | | - Joseph R Testa
- Cancer Signaling and Epigenetics Program, Fox Chase Cancer Center, Philadelphia, PA
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177
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Li Y, Zhang Y, Pan T, Zhou P, Zhou W, Gao Y, Zheng S, Xu J. Shedding light on the hidden human proteome expands immunopeptidome in cancer. Brief Bioinform 2022; 23:6533503. [PMID: 35189633 DOI: 10.1093/bib/bbac034] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 01/07/2022] [Accepted: 01/25/2022] [Indexed: 01/04/2023] Open
Abstract
Unrestrained cellular growth and immune escape of a tumor are associated with the incidental errors of the genome and transcriptome. Advances in next-generation sequencing have identified thousands of genomic and transcriptomic aberrations that generate variant peptides that assemble the hidden proteome, further expanding the immunopeptidome. Emerging next-generation sequencing technologies and a number of computational methods estimated the abundance of immune infiltration from bulk transcriptome have advanced our understanding of tumor microenvironments. Here, we will characterize several major types of tumor-specific antigens arising from single-nucleotide variants, insertions and deletions, gene fusion, alternative splicing, RNA editing and non-coding RNAs. Finally, we summarize the current state-of-the-art computational and experimental approaches or resources and provide an integrative pipeline for the identification of candidate tumor antigens. Together, the systematic investigation of the hidden proteome in cancer will help facilitate the development of effective and durable immunotherapy targets for cancer.
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Affiliation(s)
- Yongsheng Li
- College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China
| | - Yunpeng Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
| | - Tao Pan
- College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China
| | - Ping Zhou
- Department of Radiotherapy, the First Affiliated Hospital of Hainan Medical University, Hainan, China
| | - Weiwei Zhou
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
| | - Yueying Gao
- College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China
| | - Shaojiang Zheng
- Key Laboratory of Emergency and Trauma of Ministry of Education, Tumor Institute of the First Affiliated Hospital, Hainan Medical University, Haikou, 571199, China
| | - Juan Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
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178
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Deng W, Murugan S, Lindberg J, Chellappa V, Shen X, Pawitan Y, Vu TN. Fusion Gene Detection Using Whole-Exome Sequencing Data in Cancer Patients. Front Genet 2022; 13:820493. [PMID: 35251131 PMCID: PMC8888970 DOI: 10.3389/fgene.2022.820493] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 01/31/2022] [Indexed: 12/13/2022] Open
Abstract
Several fusion genes are directly involved in the initiation and progression of cancers. Numerous bioinformatics tools have been developed to detect fusion events, but they are mainly based on RNA-seq data. The whole-exome sequencing (WES) represents a powerful technology that is widely used for disease-related DNA variant detection. In this study, we build a novel analysis pipeline called Fuseq-WES to detect fusion genes at DNA level based on the WES data. The same method applies also for targeted panel sequencing data. We assess the method to real datasets of acute myeloid leukemia (AML) and prostate cancer patients. The result shows that two of the main AML fusion genes discovered in RNA-seq data, PML-RARA and CBFB-MYH11, are detected in the WES data in 36 and 63% of the available samples, respectively. For the targeted deep-sequencing of prostate cancer patients, detection of the TMPRSS2-ERG fusion, which is the most frequent chimeric alteration in prostate cancer, is 91% concordant with a manually curated procedure based on four other methods. In summary, the overall results indicate that it is challenging to detect fusion genes in WES data with a standard coverage of ∼ 15–30x, where fusion candidates discovered in the RNA-seq data are often not detected in the WES data and vice versa. A subsampling study of the prostate data suggests that a coverage of at least 75x is necessary to achieve high accuracy.
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Affiliation(s)
- Wenjiang Deng
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sarath Murugan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Johan Lindberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Venkatesh Chellappa
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Xia Shen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Biostatistics Group, Greater Bay Area Institute of Precision Medicine, Fudan University, Guangzhou, China
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Yudi Pawitan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- *Correspondence: Yudi Pawitan, ; Trung Nghia Vu,
| | - Trung Nghia Vu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- *Correspondence: Yudi Pawitan, ; Trung Nghia Vu,
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179
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Karaoglanoglu F, Chauve C, Hach F. Genion, an accurate tool to detect gene fusion from long transcriptomics reads. BMC Genomics 2022; 23:129. [PMID: 35164688 PMCID: PMC8842519 DOI: 10.1186/s12864-022-08339-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Accepted: 01/27/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND The advent of next-generation sequencing technologies empowered a wide variety of transcriptomics studies. A widely studied topic is gene fusion which is observed in many cancer types and suspected of having oncogenic properties. Gene fusions are the result of structural genomic events that bring two genes closely located and result in a fused transcript. This is different from fusion transcripts created during or after the transcription process. These chimeric transcripts are also known as read-through and trans-splicing transcripts. Gene fusion discovery with short reads is a well-studied problem, and many methods have been developed. But the sensitivity of these methods is limited by the technology, especially the short read length. Advances in long-read sequencing technologies allow the generation of long transcriptomics reads at a low cost. Transcriptomic long-read sequencing presents unique opportunities to overcome the shortcomings of short-read technologies for gene fusion detection while introducing new challenges. RESULTS We present Genion, a sensitive and fast gene fusion detection method that can also detect read-through events. We compare Genion against a recently introduced long-read gene fusion discovery method, LongGF, both on simulated and real datasets. On simulated data, Genion accurately identifies the gene fusions and its clustering accuracy for detecting fusion reads is better than LongGF. Furthermore, our results on the breast cancer cell line MCF-7 show that Genion correctly identifies all the experimentally validated gene fusions. CONCLUSIONS Genion is an accurate gene fusion caller. Genion is implemented in C++ and is available at https://github.com/vpc-ccg/genion .
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Affiliation(s)
- Fatih Karaoglanoglu
- School of Computing Science, Simon Fraser University, Burnaby, BC, Canada.,Vancouver Prostate Centre, Vancouver, BC, Canada
| | - Cedric Chauve
- Department of Mathematics, Simon Fraser University, Burnaby, BC, Canada.
| | - Faraz Hach
- Vancouver Prostate Centre, Vancouver, BC, Canada. .,Department of Urologic Sciences, The University of British Columbia, Vancouver, BC, Canada.
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180
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Korsching E, Matschke J, Hotfilder M. Splice variants denote differences between a cancer stem cell side population of EWSR1‑ERG‑based Ewing sarcoma cells, its main population and EWSR1‑FLI‑based cells. Int J Mol Med 2022; 49:39. [PMID: 35088879 PMCID: PMC8815407 DOI: 10.3892/ijmm.2022.5094] [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: 11/12/2021] [Accepted: 12/17/2021] [Indexed: 11/06/2022] Open
Abstract
Ewing sarcoma is a challenging cancer entity, which, besides the characteristic presence of a fusion gene, is driven by multiple alternative splicing events. So far, splice variants in Ewing sarcoma cells were mainly analyzed for EWSR1‑FLI1. The present study provided a comprehensive alternative splicing study on CADO‑ES1, an Ewing model cell line for an EWSR1‑ERG fusion gene. Based on a well‑-characterized RNA‑sequencing dataset with extensive control mechanisms across all levels of analysis, the differential spliced genes in Ewing cancer stem cells were ATP13A3 and EPB41, while the main population was defined by ACADVL, NOP58 and TSPAN3. All alternatively spliced genes were further characterized by their Gene Ontology (GO) terms and by their membership in known protein complexes. These results confirm and extend previous studies towards a systematic whole‑transcriptome analysis. A highlight is the striking segregation of GO terms associated with five basic splice events. This mechanistic insight, together with a coherent integration of all observations with prior knowledge, indicates that EWSR1‑ERG is truly a close twin to EWSR1‑FLI1, but still exhibits certain individuality. Thus, the present study provided a measure of variability in Ewing sarcoma, whose understanding is essential both for clinical procedures and basic mechanistic insight.
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Affiliation(s)
- Eberhard Korsching
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, D‑48149 Münster, Germany
| | - Julian Matschke
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, D‑48149 Münster, Germany
| | - Marc Hotfilder
- Department of Pediatric Hematology and Oncology, University Hospital Münster, D‑48149 Münster, Germany
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181
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Macagno N, Pissaloux D, de la Fouchardière A, Karanian M, Lantuejoul S, Galateau Salle F, Meurgey A, Chassagne-Clement C, Treilleux I, Renard C, Roussel J, Gervasoni J, Cockenpot V, Crozes C, Baltres A, Houlier A, Paindavoine S, Alberti L, Duc A, Loarer FL, Dufresne A, Brahmi M, Corradini N, Blay JY, Tirode F. Wholistic approach - transcriptomic analysis and beyond using archival material for molecular diagnosis. Genes Chromosomes Cancer 2022; 61:382-393. [PMID: 35080790 DOI: 10.1002/gcc.23026] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 12/29/2021] [Indexed: 11/07/2022] Open
Abstract
Many neoplasms remain unclassified after histopathological examination, which requires further molecular analysis. To this regard, mesenchymal neoplasms are particularly challenging due to the combination of their rarity and the large number of subtypes, and many entities still lack robust diagnostic hallmarks. RNA transcriptomic profiles have proven to be a reliable basis for the classification of previously unclassified tumors and notably for mesenchymal neoplasms. Using exome-based RNA capture sequencing on more than 5000 samples of archival material (FFPE), the combination of expression profiles analyzes (including several clustering methods), fusion genes, and small nucleotide variations has been developed at the Centre Léon Bérard (CLB) in Lyon for the molecular diagnosis of challenging neoplasms and the discovery of new entities. The molecular basis of the technique, the protocol, and the bioinformatics algorithms used are described herein, as well as its advantages and limitations.
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Affiliation(s)
- Nicolas Macagno
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France.,Aix-Marseille University, Marmara institute, INSERM, U1251, MMG, DOD-CET, Marseille, France.,NETSARC+, French Sarcoma Group (GSF-GETO) network, France.,CARADERM, French network of rare skin cancers, France
| | - Daniel Pissaloux
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France.,INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France
| | - Arnaud de la Fouchardière
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France.,INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France
| | - Marie Karanian
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France.,NETSARC+, French Sarcoma Group (GSF-GETO) network, France.,INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France.,Department of Biopathology, UNICANCER, Bergonié Institute, Bordeaux, France
| | - Sylvie Lantuejoul
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France.,INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France.,Grenoble Alpes University, Grenoble, France.,MESOPATH, MESOBANK, French network of mesothelioma, France
| | - Françoise Galateau Salle
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France.,MESOPATH, MESOBANK, French network of mesothelioma, France
| | - Alexandra Meurgey
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France.,NETSARC+, French Sarcoma Group (GSF-GETO) network, France
| | | | | | - Caroline Renard
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France
| | - Juliette Roussel
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France
| | - Julie Gervasoni
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France
| | - Vincent Cockenpot
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France
| | - Carole Crozes
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France
| | - Aline Baltres
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France
| | - Aurélie Houlier
- Department of Biopathology, UNICANCER, Centre Léon Bérard, Lyon, France
| | | | - Laurent Alberti
- INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France
| | - Adeline Duc
- INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France
| | - Francois Le Loarer
- NETSARC+, French Sarcoma Group (GSF-GETO) network, France.,Department of Biopathology, UNICANCER, Bergonié Institute, Bordeaux, France
| | - Armelle Dufresne
- NETSARC+, French Sarcoma Group (GSF-GETO) network, France.,INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France.,Department of Oncology, UNICANCER, Centre Léon Bérard, Lyon, France
| | - Mehdi Brahmi
- NETSARC+, French Sarcoma Group (GSF-GETO) network, France.,INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France.,Department of Oncology, UNICANCER, Centre Léon Bérard, Lyon, France
| | - Nadège Corradini
- NETSARC+, French Sarcoma Group (GSF-GETO) network, France.,INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France.,Institute of pediatric oncology, IHOPe, UNICANCER, Centre Léon Bérard, Lyon, France
| | - Jean-Yves Blay
- NETSARC+, French Sarcoma Group (GSF-GETO) network, France.,Department of Oncology, UNICANCER, Centre Léon Bérard, Lyon, France.,Univ Lyon, Université Claude Bernard Lyon I, Lyon, France.,Headquarters, UNICANCER, Paris, France
| | - Franck Tirode
- INSERM 1052, CNRS 5286, Cancer Research Center of Lyon (CRCL), Lyon, France.,Department of Biopathology, UNICANCER, Bergonié Institute, Bordeaux, France.,Univ Lyon, Université Claude Bernard Lyon I, Lyon, France
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182
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Yao Q, Bai Q, Zhang X, Ji G, Chang H, Cai X, Yu L, Wang J, Zhu X, Zhou X. Assessment of ALK Fusions in Uncommon Inflammatory Myofibroblastic Tumors With ALK IHC Positivity but FISH-Equivocal Findings by Targeted RNA Sequencing. Arch Pathol Lab Med 2022; 146:1234-1242. [PMID: 35041745 DOI: 10.5858/arpa.2021-0230-oa] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/07/2021] [Indexed: 11/06/2022]
Abstract
CONTEXT.— Fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) are common methods to detect ALK status in inflammatory myofibroblastic tumors (IMTs). However, equivocal ALK FISH signals and inconsistency between FISH and IHC are occasionally observed. OBJECTIVE.— To study the inconsistency between FISH and IHC, and clarify ALK status in IMT by targeted RNA sequencing (RNAseq). DESIGN.— In this study, 12 consultation cases preliminarily diagnosed as uncommon IMTs with ALK IHC positivity but FISH negativity, plus 3 ALK-positive and 3 ALK-negative IMTs, were re-analyzed by IHC, FISH, and RNAseq. RESULTS.— As a result, 1 case with FUS-TFCP2 fusion was detected by RNAseq, which was previously misdiagnosed as IMT. In the other 11 uncommon IMTs, 90.9% (10 of 11) showed equivocal ALK FISH signals, and all were confirmed to harbor ALK fusion by RNAseq, except for 1 failure, suggesting that a low threshold for ALK FISH might be proposed in IMT. Furthermore, RNAseq also identified IGFBP5-ALK in 1 case with ALK IHC positivity but typical FISH negativity, suggesting the possibility of false negatives for ALK FISH. For the typical IMTs, ALK fusion was identified by RNAseq in all 3 ALK-positive IMTs as expected, and additionally FN1-ROS1 fusions were identified in 2 of 3 ALK-negative IMTs. CONCLUSIONS.— These findings indicated that RNAseq can simultaneously detect multiple gene fusions and provide fusion forms and breakpoints, which is of great value for differential diagnosis, especially for those uncommon IMTs with equivocal FISH findings, or inconsistency between IHC and FISH.
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Affiliation(s)
- Qianlan Yao
- From the Department of Pathology, Shanghai Cancer Center, the Department of Oncology, Shanghai Medical College, and the Institute of Pathology, Fudan University, Shanghai, China (Yao, Bai, Ji, Chang, Cai, Yu, Wang, Zhu, Zhou)
| | - Qianming Bai
- From the Department of Pathology, Shanghai Cancer Center, the Department of Oncology, Shanghai Medical College, and the Institute of Pathology, Fudan University, Shanghai, China (Yao, Bai, Ji, Chang, Cai, Yu, Wang, Zhu, Zhou)
| | - Xin Zhang
- Department of Pathology, Fudan University, Zhongshan Hospital, Shanghai, China (Zhang)
| | - Gang Ji
- From the Department of Pathology, Shanghai Cancer Center, the Department of Oncology, Shanghai Medical College, and the Institute of Pathology, Fudan University, Shanghai, China (Yao, Bai, Ji, Chang, Cai, Yu, Wang, Zhu, Zhou)
| | - Heng Chang
- From the Department of Pathology, Shanghai Cancer Center, the Department of Oncology, Shanghai Medical College, and the Institute of Pathology, Fudan University, Shanghai, China (Yao, Bai, Ji, Chang, Cai, Yu, Wang, Zhu, Zhou)
| | - Xu Cai
- From the Department of Pathology, Shanghai Cancer Center, the Department of Oncology, Shanghai Medical College, and the Institute of Pathology, Fudan University, Shanghai, China (Yao, Bai, Ji, Chang, Cai, Yu, Wang, Zhu, Zhou)
| | - Lin Yu
- From the Department of Pathology, Shanghai Cancer Center, the Department of Oncology, Shanghai Medical College, and the Institute of Pathology, Fudan University, Shanghai, China (Yao, Bai, Ji, Chang, Cai, Yu, Wang, Zhu, Zhou)
| | - Jian Wang
- From the Department of Pathology, Shanghai Cancer Center, the Department of Oncology, Shanghai Medical College, and the Institute of Pathology, Fudan University, Shanghai, China (Yao, Bai, Ji, Chang, Cai, Yu, Wang, Zhu, Zhou)
| | - Xiaoli Zhu
- From the Department of Pathology, Shanghai Cancer Center, the Department of Oncology, Shanghai Medical College, and the Institute of Pathology, Fudan University, Shanghai, China (Yao, Bai, Ji, Chang, Cai, Yu, Wang, Zhu, Zhou)
| | - Xiaoyan Zhou
- From the Department of Pathology, Shanghai Cancer Center, the Department of Oncology, Shanghai Medical College, and the Institute of Pathology, Fudan University, Shanghai, China (Yao, Bai, Ji, Chang, Cai, Yu, Wang, Zhu, Zhou)
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183
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Butzmann A, Sridhar K, Jangam D, Song H, Singh A, Kumar J, Chisholm KM, Pinsky B, Huang F, Ohgami RS. Mutations in JAK/STAT and NOTCH1 Genes Are Enriched in Post-Transplant Lymphoproliferative Disorders. Front Oncol 2022; 11:790481. [PMID: 35111674 PMCID: PMC8801788 DOI: 10.3389/fonc.2021.790481] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/13/2021] [Indexed: 12/22/2022] Open
Abstract
Post-transplant lymphoproliferative disorders (PTLD) are diseases occurring in immunocompromised patients after hematopoietic stem cell transplantation (HCT) or solid organ transplantation (SOT). Although PTLD occurs rarely, it may be associated with poor outcomes. In most cases, PTLD is driven by Epstein-Barr virus (EBV) infection. Few studies have investigated the mutational landscape and gene expression profile of PTLD. In our study, we performed targeted deep sequencing and RNA-sequencing (RNA-Seq) on 16 cases of florid follicular hyperplasia (FFH) type PTLD and 15 cases of other PTLD types that include: ten monomorphic (M-PTLD), three polymorphic (P-PTLD), and two classic Hodgkin lymphoma type PTLDs (CHL-PTLD). Our study identified recurrent mutations in JAK3 in five of 15 PTLD cases and one of 16 FFH-PTLD cases, as well as 16 other genes that were mutated in M-PTLD, P-PTLD, CHL-PTLD and FFH-PTLD. Digital image analysis demonstrated significant differences in single cell area, major axis, and diameter when comparing cases of M-PTLD and P-PTLD to FFH-PTLD. No morphometric relationship was identified with regards to a specific genetic mutation. Our findings suggest that immune regulatory pathways play an essential role in PTLD, with the JAK/STAT pathway affected in many PTLDs.
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Affiliation(s)
- Alexandra Butzmann
- Agilent Technologies, Santa Clara, CA, United States
- Department of Pathology, University of California, San Francisco, San Francisco, CA, United States
- *Correspondence: Alexandra Butzmann,
| | - Kaushik Sridhar
- Department of Pathology, University of California, San Francisco, San Francisco, CA, United States
| | - Diwash Jangam
- Department of Pathology, Stanford University, Stanford, CA, United States
| | - Hanbing Song
- Department of Pathology, University of California, San Francisco, San Francisco, CA, United States
| | - Amol Singh
- Department of Pathology, Stanford University, Stanford, CA, United States
| | - Jyoti Kumar
- Department of Pathology, Stanford University, Stanford, CA, United States
| | - Karen M. Chisholm
- Department of Laboratories, Seattle Children’s Hospital, Seattle, WA, United States
| | - Benjamin Pinsky
- Department of Pathology, Stanford University, Stanford, CA, United States
| | - Franklin Huang
- Department of Pathology, University of California, San Francisco, San Francisco, CA, United States
| | - Robert S. Ohgami
- Department of Pathology, University of California, San Francisco, San Francisco, CA, United States
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184
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RNA-Seq for the detection of gene fusions in solid tumors: development and validation of the JAX FusionSeq™ 2.0 assay. J Mol Med (Berl) 2022; 100:323-335. [PMID: 35013752 DOI: 10.1007/s00109-021-02149-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 09/30/2021] [Accepted: 10/05/2021] [Indexed: 10/19/2022]
Abstract
Whole transcriptome sequencing (RNA-Seq) has gained prominence for the detection of fusions in solid tumors. Here, we describe the development and validation of an in-house RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, in formalin-fixed paraffin-embedded (FFPE) specimens, using seventy tumor samples with varying fusion status. Conditions were optimized for RNA input of 50 ng, shown to be adequate to call known fusions at as low as 20% neoplastic content. Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. Performance analysis of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility. This clinically developed and validated RNA-Seq-based approach for fusion detection in FPPE samples was shown to be on par if not superior to off-the-shelf commercially offered assays. With gene fusions implicated in a variety of cancer types, offering high-quality, low-cost molecular testing services for FFPE specimens will serve to best benefit the patient and the advancement of precision medicine in molecular oncology. KEY MESSAGES: A custom RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. The assay can be performed with low RNA input and neoplastic content. Performance characteristics of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility.
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185
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Dong L, Lu D, Chen R, Lin Y, Zhu H, Zhang Z, Cai S, Cui P, Song G, Rao D, Yi X, Wu Y, Song N, Liu F, Zou Y, Zhang S, Zhang X, Wang X, Qiu S, Zhou J, Wang S, Zhang X, Shi Y, Figeys D, Ding L, Wang P, Zhang B, Rodriguez H, Gao Q, Gao D, Zhou H, Fan J. Proteogenomic characterization identifies clinically relevant subgroups of intrahepatic cholangiocarcinoma. Cancer Cell 2022; 40:70-87.e15. [PMID: 34971568 DOI: 10.1016/j.ccell.2021.12.006] [Citation(s) in RCA: 132] [Impact Index Per Article: 66.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 07/19/2021] [Accepted: 12/08/2021] [Indexed: 02/08/2023]
Abstract
We performed proteogenomic characterization of intrahepatic cholangiocarcinoma (iCCA) using paired tumor and adjacent liver tissues from 262 patients. Integrated proteogenomic analyses prioritized genetic aberrations and revealed hallmarks of iCCA pathogenesis. Aflatoxin signature was associated with tumor initiation, proliferation, and immune suppression. Mutation-associated signaling profiles revealed that TP53 and KRAS co-mutations may contribute to iCCA metastasis via the integrin-FAK-SRC pathway. FGFR2 fusions activated the Rho GTPase pathway and could be a potential source of neoantigens. Proteomic profiling identified four patient subgroups (S1-S4) with subgroup-specific biomarkers. These proteomic subgroups had distinct features in prognosis, genetic alterations, microenvironment dysregulation, tumor microbiota composition, and potential therapeutics. SLC16A3 and HKDC1 were further identified as potential prognostic biomarkers associated with metabolic reprogramming of iCCA cells. This study provides a valuable resource for researchers and clinicians to further identify molecular pathogenesis and therapeutic opportunities in iCCA.
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Affiliation(s)
- Liangqing Dong
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Dayun Lu
- Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China; University of Chinese Academy of Sciences, Number 19A Yuquan Road, Beijing 100049, China
| | - Ran Chen
- University of Chinese Academy of Sciences, Number 19A Yuquan Road, Beijing 100049, China; State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Youpei Lin
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Hongwen Zhu
- Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Zhou Zhang
- Burning Rock Biotech, Shanghai 201114, China
| | - Shangli Cai
- Burning Rock Biotech, Shanghai 201114, China
| | - Peng Cui
- Burning Rock Biotech, Shanghai 201114, China
| | - Guohe Song
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Dongning Rao
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Xinpei Yi
- Lester and Sue Smith Breast Center, Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Yingcheng Wu
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Nixue Song
- Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China; University of Chinese Academy of Sciences, Number 19A Yuquan Road, Beijing 100049, China
| | - Fen Liu
- University of Chinese Academy of Sciences, Number 19A Yuquan Road, Beijing 100049, China; State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Yunhao Zou
- University of Chinese Academy of Sciences, Number 19A Yuquan Road, Beijing 100049, China; State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Shu Zhang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Xiaoming Zhang
- Key Laboratory of Molecular Virology and Immunology, Institut Pasteur of Shanghai, Chinese Academy of Sciences, Shanghai, China
| | - Xiaoying Wang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Shuangjian Qiu
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China
| | - Jian Zhou
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China; Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Shisheng Wang
- Frontiers Science Center for Disease-related Molecular Network, Institutes for Systems Genetics, Key Lab of Transplant Engineering and Immunology, MOH, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Xu Zhang
- Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Shanghai Institute of Materia Medica-University of Ottawa Joint Research Center in Systems and Personalized Pharmacology, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Yongyong Shi
- Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), The Collaborative Innovation Center for Brain Science, Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Daniel Figeys
- Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Shanghai Institute of Materia Medica-University of Ottawa Joint Research Center in Systems and Personalized Pharmacology, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Li Ding
- Department of Medicine, McDonnell Genome Institute, Siteman Cancer Center, Washington University, St. Louis, MI 63108, USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NewYork, NY 10029, USA
| | - Bing Zhang
- Lester and Sue Smith Breast Center, Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Henry Rodriguez
- Office of Cancer Clinical Proteomics Research, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Qiang Gao
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China; Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China; State Key Laboratory of Genetic Engineering, Fudan University, Shanghai 200433, China.
| | - Daming Gao
- University of Chinese Academy of Sciences, Number 19A Yuquan Road, Beijing 100049, China; State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China; School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
| | - Hu Zhou
- Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China; University of Chinese Academy of Sciences, Number 19A Yuquan Road, Beijing 100049, China; Shanghai Institute of Materia Medica-University of Ottawa Joint Research Center in Systems and Personalized Pharmacology, 555 Zuchongzhi Road, Shanghai 201203, China.
| | - Jia Fan
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai 200032, China; Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
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186
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Song H, Weinstein HNW, Allegakoen P, Wadsworth MH, Xie J, Yang H, Castro EA, Lu KL, Stohr BA, Feng FY, Carroll PR, Wang B, Cooperberg MR, Shalek AK, Huang FW. Single-cell analysis of human primary prostate cancer reveals the heterogeneity of tumor-associated epithelial cell states. Nat Commun 2022; 13:141. [PMID: 35013146 PMCID: PMC8748675 DOI: 10.1038/s41467-021-27322-4] [Citation(s) in RCA: 68] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 10/29/2021] [Indexed: 12/31/2022] Open
Abstract
Prostate cancer is the second most common malignancy in men worldwide and consists of a mixture of tumor and non-tumor cell types. To characterize the prostate cancer tumor microenvironment, we perform single-cell RNA-sequencing on prostate biopsies, prostatectomy specimens, and patient-derived organoids from localized prostate cancer patients. We uncover heterogeneous cellular states in prostate epithelial cells marked by high androgen signaling states that are enriched in prostate cancer and identify a population of tumor-associated club cells that may be associated with prostate carcinogenesis. ERG-negative tumor cells, compared to ERG-positive cells, demonstrate shared heterogeneity with surrounding luminal epithelial cells and appear to give rise to common tumor microenvironment responses. Finally, we show that prostate epithelial organoids harbor tumor-associated epithelial cell states and are enriched with distinct cell types and states from their parent tissues. Our results provide diagnostically relevant insights and advance our understanding of the cellular states associated with prostate carcinogenesis.
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Affiliation(s)
- Hanbing Song
- grid.266102.10000 0001 2297 6811Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Hannah N. W. Weinstein
- grid.266102.10000 0001 2297 6811Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Paul Allegakoen
- grid.266102.10000 0001 2297 6811Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Marc H. Wadsworth
- grid.116068.80000 0001 2341 2786The Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02139 USA ,grid.116068.80000 0001 2341 2786Institute for Medical Engineering and Science (IMES), Massachusetts Institute of Technology, Cambridge, MA 02139 USA ,grid.116068.80000 0001 2341 2786Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139 USA ,grid.116068.80000 0001 2341 2786Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA ,grid.66859.340000 0004 0546 1623Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142 USA
| | - Jamie Xie
- grid.266102.10000 0001 2297 6811Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Heiko Yang
- grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Department of Urology, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Ethan A. Castro
- grid.266102.10000 0001 2297 6811Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Kevin L. Lu
- grid.266102.10000 0001 2297 6811Department of Pathology, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Bradley A. Stohr
- grid.266102.10000 0001 2297 6811Department of Pathology, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Felix Y. Feng
- grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Department of Urology, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Departments of Radiation Oncology, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Peter R. Carroll
- grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Department of Urology, University of California, San Francisco, San Francisco, CA 94143 USA
| | - Bruce Wang
- grid.266102.10000 0001 2297 6811Division of Gastroenterology, Department of Medicine, University of California, San Francisco, CA 94143 USA
| | - Matthew R. Cooperberg
- grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Department of Urology, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.410372.30000 0004 0419 2775Division of Hematology and Oncology, Department of Medicine, San Francisco Veterans Affairs Medical Center, San Francisco, CA 94121 USA
| | - Alex K. Shalek
- grid.116068.80000 0001 2341 2786The Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02139 USA ,grid.116068.80000 0001 2341 2786Institute for Medical Engineering and Science (IMES), Massachusetts Institute of Technology, Cambridge, MA 02139 USA ,grid.116068.80000 0001 2341 2786Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139 USA ,grid.116068.80000 0001 2341 2786Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA ,grid.66859.340000 0004 0546 1623Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142 USA
| | - Franklin W. Huang
- grid.266102.10000 0001 2297 6811Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.266102.10000 0001 2297 6811Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143 USA ,grid.410372.30000 0004 0419 2775Division of Hematology and Oncology, Department of Medicine, San Francisco Veterans Affairs Medical Center, San Francisco, CA 94121 USA
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187
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Davidson NM, Chen Y, Sadras T, Ryland GL, Blombery P, Ekert PG, Göke J, Oshlack A. JAFFAL: detecting fusion genes with long-read transcriptome sequencing. Genome Biol 2022; 23:10. [PMID: 34991664 PMCID: PMC8739696 DOI: 10.1186/s13059-021-02588-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 12/22/2021] [Indexed: 12/26/2022] Open
Abstract
In cancer, fusions are important diagnostic markers and targets for therapy. Long-read transcriptome sequencing allows the discovery of fusions with their full-length isoform structure. However, due to higher sequencing error rates, fusion finding algorithms designed for short reads do not work. Here we present JAFFAL, to identify fusions from long-read transcriptome sequencing. We validate JAFFAL using simulations, cell lines, and patient data from Nanopore and PacBio. We apply JAFFAL to single-cell data and find fusions spanning three genes demonstrating transcripts detected from complex rearrangements. JAFFAL is available at https://github.com/Oshlack/JAFFA/wiki .
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Affiliation(s)
- Nadia M Davidson
- Peter MacCallum Cancer Centre, Victoria, Australia.
- School of BioSciences, University of Melbourne, Victoria, Australia.
- The Walter and Eliza Hall Institute, Victoria, Australia.
| | - Ying Chen
- Genome Institute of Singapore, Singapore, Singapore
| | - Teresa Sadras
- Peter MacCallum Cancer Centre, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Georgina L Ryland
- Peter MacCallum Cancer Centre, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
- Centre for Cancer Research, University of Melbourne, Victoria, Australia
| | - Piers Blombery
- Peter MacCallum Cancer Centre, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
| | - Paul G Ekert
- Peter MacCallum Cancer Centre, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
- Children's Cancer Institute, Lowy Cancer Centre, UNSW, Sydney, NSW, Australia
- School of Women's and Children's Health, UNSW, Sydney, NSW, Australia
- Murdoch Children's Research Institute, Victoria, Australia
| | - Jonathan Göke
- Genome Institute of Singapore, Singapore, Singapore
- National Cancer Centre Singapore, Singapore, Singapore
| | - Alicia Oshlack
- Peter MacCallum Cancer Centre, Victoria, Australia.
- School of BioSciences, University of Melbourne, Victoria, Australia.
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia.
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188
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McLean-Holden AC, Rooper LM, Lubin DJ, Magliocca KR, Manucha V, Sadow PM, Tobias J, Vargo RJ, Thompson LDR, Heidarian A, Weinreb I, Wenig B, Gagan J, Hernandez-Prera JC, Bishop JA. Frankly Invasive Carcinoma Ex-intraductal Carcinoma: Expanding on an Emerging and Perplexing Concept in Salivary Gland Tumor Pathology. Head Neck Pathol 2022; 16:657-669. [PMID: 34985683 PMCID: PMC9424381 DOI: 10.1007/s12105-021-01408-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 12/22/2021] [Indexed: 01/07/2023]
Abstract
Intraductal carcinoma (IDC) of the salivary glands is an uncommon and enigmatic tumor, our understanding of which is rapidly evolving. Recent studies have demonstrated multiple IDC subtypes and consistent gene fusions, most frequently involving RET. Because IDC is a ductal proliferation surrounded by flattened myoepithelial cells, it was previously presumed to be analogous to breast ductal carcinoma in situ, but recent evidence has shown that the myoepithelial cells of fusion-positive IDC harbor the same genetic alterations of the ductal cells and are therefore neoplastic. In addition, there are rare reports of fusion-positive IDC with overt areas of irregular invasion lacking myoepithelial cells, but this phenomenon is not well documented or understood. This study aims to better characterize these frankly invasive carcinoma ex-IDC. All cases of frankly invasive carcinoma ex-IDC were obtained from the authors' files. Inclusion criteria included a component of concurrent or antecedent IDC and/or a fusion known to be associated with IDC. Immunohistochemistry (S100, SOX10, mammaglobin, androgen receptor, p63, p40) and molecular analysis (targeted RNA sequencing or large panel DNA next generation sequencing) was performed. Clinical follow-up was obtained from medical records. Ten cases of frankly invasive carcinoma ex-IDC were identified. The tumors occurred in 8 men and 2 women ranging from 33 to 82 years (mean, 66.3). All but one case arose in the parotid gland. In 4 cases, the IDC component was intercalated duct type. It was mixed apocrine/intercalated duct in two, and in the remaining 4 cases, no residual IDC was identified. The frankly invasive carcinomas were remarkably heterogeneous, ranging from minimally to widely invasive beyond the confines of the IDC, low-grade to high-grade, with morphologies that varied from duct-forming to those having clear cell or sarcomatoid features, to frankly apocrine. The original diagnoses for these cases were (adeno) carcinoma, not otherwise specified (n = 6), salivary duct carcinoma (n = 3), and secretory carcinoma (n = 1). All cases harbored fusions: NCOA4::RET (n = 6), TRIM33::RET (n = 2), TRIM27::RET (n = 1), and STRN::ALK (n = 1). Clinically, one tumor recurred locally, cervical lymph node metastases occurred in five patients, and distant metastasis later developed in four of these patients. Our findings highlight striking diversity in frankly invasive carcinomas that arise from fusion-positive IDC, a tumor which may serve as a precursor neoplasm like pleomorphic adenoma. These carcinomas vary in their extent of invasion, grade, histologic appearances, and clinical behavior. Importantly, in contrast to pure IDC, which is believed to be indolent, many frankly invasive cases were aggressive. Because RET and ALK fusions are targetable, it is important to recognize the broad spectrum of frankly invasive carcinomas that can arise from IDC, particularly because some cases are completely overrun or recur without any recognizable IDC component. These results suggest fusion analysis may be of clinical benefit on any salivary gland (adeno) carcinoma, not otherwise specified or salivary duct carcinoma.
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Affiliation(s)
- Anne C McLean-Holden
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Pathology and Laboratory Medicine, Emory University Hospital, Atlanta, GA, USA
| | - Lisa M Rooper
- Department of Pathology and Oncology, The Johns Hopkins Hospital, Baltimore, MD, USA
| | - Daniel J Lubin
- Department of Pathology and Laboratory Medicine, Emory University Hospital, Atlanta, GA, USA
| | - Kelly R Magliocca
- Department of Pathology and Laboratory Medicine, Emory University Hospital, Atlanta, GA, USA
| | - Varsha Manucha
- Department of Pathology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Peter M Sadow
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jonathan Tobias
- Department of Pathology, Greater Cincinnati Pathologists, Inc, The Christ Hospital, Cincinnati, OH, USA
| | - Richard J Vargo
- Oral and Maxillofacial Pathology Specialty Care Unit, A.T. Still University-Missouri School of Dentistry & Oral Health, St. Louis, MO, USA
| | | | - Amin Heidarian
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Ilan Weinreb
- Department of Pathology, Department of Laboratory Medicine and Pathobiology, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Bruce Wenig
- Department of Anatomic Pathology, Moffitt Cancer Center, Tampa, FL, USA
| | - Jeffrey Gagan
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Justin A Bishop
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
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189
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Kerbs P, Vosberg S, Krebs S, Graf A, Blum H, Swoboda A, Batcha AMN, Mansmann U, Metzler D, Heckman CA, Herold T, Greif PA. Fusion gene detection by RNA-sequencing complements diagnostics of acute myeloid leukemia and identifies recurring NRIP1-MIR99AHG rearrangements. Haematologica 2022; 107:100-111. [PMID: 34134471 PMCID: PMC8719081 DOI: 10.3324/haematol.2021.278436] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 05/03/2021] [Indexed: 12/04/2022] Open
Abstract
Identification of fusion genes in clinical routine is mostly based on cytogenetics and targeted molecular genetics, such as metaphase karyotyping, fluorescence in situ hybridization and reverse-transcriptase polymerase chain reaction. However, sequencing technologies are becoming more important in clinical routine as processing time and costs per sample decrease. To evaluate the performance of fusion gene detection by RNAsequencing compared to standard diagnostic techniques, we analyzed 806 RNA-sequencing samples from patients with acute myeloid leukemia using two state-of-the-art software tools, namely Arriba and FusionCatcher. RNA-sequencing detected 90% of fusion events that were reported by routine with high evidence, while samples in which RNA-sequencing failed to detect fusion genes had overall lower and inhomogeneous sequence coverage. Based on properties of known and unknown fusion events, we developed a workflow with integrated filtering strategies for the identification of robust fusion gene candidates by RNA-sequencing. Thereby, we detected known recurrent fusion events in 26 cases that were not reported by routine and found discrepancies in evidence for known fusion events between routine and RNA-sequencing in three cases. Moreover, we identified 157 fusion genes as novel robust candidates and comparison to entries from ChimerDB or Mitelman Database showed novel recurrence of fusion genes in 14 cases. Finally, we detected the novel recurrent fusion gene NRIP1- MIR99AHG resulting from inv(21)(q11.2;q21.1) in nine patients (1.1%) and LTN1-MX1 resulting from inv(21)(q21.3;q22.3) in two patients (0.25%). We demonstrated that NRIP1-MIR99AHG results in overexpression of the 3' region of MIR99AHG and the disruption of the tricistronic miRNA cluster miR-99a/let-7c/miR-125b-2. Interestingly, upregulation of MIR99AHG and deregulation of the miRNA cluster, residing in the MIR99AHG locus, are known mechanisms of leukemogenesis in acute megakaryoblastic leukemia. Our findings demonstrate that RNA-sequencing has a strong potential to improve the systematic detection of fusion genes in clinical applications and provides a valuable tool for fusion discovery.
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Affiliation(s)
- Paul Kerbs
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich; and; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sebastian Vosberg
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich; and; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefan Krebs
- Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, LMU Munich, Munich, Germany
| | - Alexander Graf
- Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, LMU Munich, Munich, Germany
| | - Helmut Blum
- Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, LMU Munich, Munich, Germany
| | - Anja Swoboda
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Aarif M N Batcha
- Department of Medical Data Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany
| | - Ulrich Mansmann
- Department of Medical Data Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany
| | - Dirk Metzler
- Division of Evolutionary Biology, Faculty of Biology, LMU Munich, Planegg-Martinsried, Germany
| | - Caroline A Heckman
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Tobias Herold
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich; and; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Philipp A Greif
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich; and; German Cancer Research Center (DKFZ), Heidelberg, Germany.
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190
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Capone I, Bozzi F, Dagrada GP, Verderio P, Conca E, Busico A, Testi MA, Monti V, Duca M, Proto C, Damian S, Piccolo A, Perrone F, Tamborini E, Devecchi A, Collini P, Lorenzini D, Vingiani A, Agnelli L, Pruneri G. Targeted RNA-sequencing analysis for fusion transcripts detection in tumor diagnostics: assessment of bioinformatic tools reliability in FFPE samples. EXPLORATION OF TARGETED ANTI-TUMOR THERAPY 2022; 3:582-597. [PMCID: PMC9630092 DOI: 10.37349/etat.2022.00102] [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: 04/29/2022] [Accepted: 08/02/2022] [Indexed: 11/07/2022] Open
Abstract
Aim: Diagnostic laboratories are progressively introducing next-generation sequencing (NGS) technologies in the routine workflow to meet the increasing clinical need for comprehensive molecular characterization in cancer patients for diagnosis and precision medicine, including fusion-transcripts detection. Nevertheless, the low quality of messenger RNA (mRNA) extracted from formalin-fixed paraffin-embedded (FFPE) samples may affect the transition from traditional single-gene testing approaches [like fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), or polymerase chain reaction (PCR)] to NGS. The present study is aimed at assessing the overall accuracy of RNA fusion transcripts detection by NGS analysis in FFPE samples in real-world diagnostics. Methods: Herein, NGS data from 190 soft tissue tumors (STTs) and carcinoma cases, discussed in the context of the institutional Molecular Tumor Board, are reported and analyzed by FusionPlex© Solid tumor kit through the manufacturer’s pipeline and by two well-known fast and accurate open-source tools [Arriba (ARR) and spliced transcripts alignment to reference (STAR)-fusion (SFU)]. Results: The combination of FusionPlex© Solid tumor with ArcherDX® Analysis suite (ADx) analysis package has been proven to be sensitive and specific in STT samples, while partial loss of sensitivity has been found in carcinoma specimens. Conclusions: Albeit ARR and SFU showed lower sensitivity, the use of additional fusion-detection tools can contribute to reinforcing or extending the output obtained by ADx, particularly in the case of low-quality input data. Overall, our results sustain the clinical use of NGS for the detection of fusion transcripts in FFPE material.
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Affiliation(s)
- Iolanda Capone
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Fabio Bozzi
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Gian Paolo Dagrada
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Paolo Verderio
- Department of Applied Research and Technological Development, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Elena Conca
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Adele Busico
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Maria Adele Testi
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Valentina Monti
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Matteo Duca
- Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Claudia Proto
- Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Silvia Damian
- Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Alberta Piccolo
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Federica Perrone
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Elena Tamborini
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Andrea Devecchi
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Paola Collini
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Daniele Lorenzini
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
| | - Andrea Vingiani
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy,Department of Oncology and Hemato-oncology, University of Milan, 20133 Milan, Italy
| | - Luca Agnelli
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy,Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy,Correspondence: Luca Agnelli, Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Venezian 1, 20133 Milan, Italy.
| | - Giancarlo Pruneri
- Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy,Department of Oncology and Hemato-oncology, University of Milan, 20133 Milan, Italy
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191
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Hedges DJ. RNA-seq Fusion Detection in Clinical Oncology. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1361:163-175. [DOI: 10.1007/978-3-030-91836-1_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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192
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Laganà A. The Architecture of a Precision Oncology Platform. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1361:1-22. [DOI: 10.1007/978-3-030-91836-1_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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193
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Detroja R, Gorohovski A, Giwa O, Baum G, Frenkel-Morgenstern M. ChiTaH: a fast and accurate tool for identifying known human chimeric sequences from high-throughput sequencing data. NAR Genom Bioinform 2021; 3:lqab112. [PMID: 34859212 PMCID: PMC8633610 DOI: 10.1093/nargab/lqab112] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 10/21/2021] [Accepted: 11/22/2021] [Indexed: 12/16/2022] Open
Abstract
Fusion genes or chimeras typically comprise sequences from two different genes. The chimeric RNAs of such joined sequences often serve as cancer drivers. Identifying such driver fusions in a given cancer or complex disease is important for diagnosis and treatment. The advent of next-generation sequencing technologies, such as DNA-Seq or RNA-Seq, together with the development of suitable computational tools, has made the global identification of chimeras in tumors possible. However, the testing of over 20 computational methods showed these to be limited in terms of chimera prediction sensitivity, specificity, and accurate quantification of junction reads. These shortcomings motivated us to develop the first ‘reference-based’ approach termed ChiTaH (Chimeric Transcripts from High–throughput sequencing data). ChiTaH uses 43,466 non–redundant known human chimeras as a reference database to map sequencing reads and to accurately identify chimeric reads. We benchmarked ChiTaH and four other methods to identify human chimeras, leveraging both simulated and real sequencing datasets. ChiTaH was found to be the most accurate and fastest method for identifying known human chimeras from simulated and sequencing datasets. Moreover, especially ChiTaH uncovered heterogeneity of the BCR-ABL1 chimera in both bulk and single-cells of the K-562 cell line, which was confirmed experimentally.
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Affiliation(s)
- Rajesh Detroja
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Alessandro Gorohovski
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Olawumi Giwa
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Gideon Baum
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Milana Frenkel-Morgenstern
- Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
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194
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LaHaye S, Fitch JR, Voytovich KJ, Herman AC, Kelly BJ, Lammi GE, Arbesfeld JA, Wijeratne S, Franklin SJ, Schieffer KM, Bir N, McGrath SD, Miller AR, Wetzel A, Miller KE, Bedrosian TA, Leraas K, Varga EA, Lee K, Gupta A, Setty B, Boué DR, Leonard JR, Finlay JL, Abdelbaki MS, Osorio DS, Koo SC, Koboldt DC, Wagner AH, Eisfeld AK, Mrózek K, Magrini V, Cottrell CE, Mardis ER, Wilson RK, White P. Discovery of clinically relevant fusions in pediatric cancer. BMC Genomics 2021; 22:872. [PMID: 34863095 PMCID: PMC8642973 DOI: 10.1186/s12864-021-08094-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 10/15/2021] [Indexed: 12/13/2022] Open
Abstract
Background Pediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions. Results Our Ensemble Fusion (EnFusion) approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and Amazon Web Services (AWS) serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a “known fusion list” prevents failure to report known pathogenic events. We have employed the EnFusion pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient’s medical record, both known and novel fusions provided medically meaningful information. Conclusions The EnFusion pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08094-z.
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Affiliation(s)
- Stephanie LaHaye
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - James R Fitch
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Kyle J Voytovich
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Adam C Herman
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Benjamin J Kelly
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Grant E Lammi
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Jeremy A Arbesfeld
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Saranga Wijeratne
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Samuel J Franklin
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Kathleen M Schieffer
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Natalie Bir
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Sean D McGrath
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Anthony R Miller
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Amy Wetzel
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Katherine E Miller
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Tracy A Bedrosian
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Kristen Leraas
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Elizabeth A Varga
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Kristy Lee
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Ajay Gupta
- Division of Hematology, Oncology, Blood and Marrow Transplant, Nationwide Children's Hospital, Columbus, OH, USA
| | - Bhuvana Setty
- Division of Hematology, Oncology, Blood and Marrow Transplant, Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, The Ohio State University, Columbus, OH, USA
| | - Daniel R Boué
- Department of Pathology, The Ohio State University, Columbus, OH, USA.,Department of Pathology, Nationwide Children's Hospital, Columbus, OH, USA
| | - Jeffrey R Leonard
- Department of Pediatrics, The Ohio State University, Columbus, OH, USA.,Section of Neurosurgery, Nationwide Children's Hospital, Columbus, OH, USA
| | - Jonathan L Finlay
- Division of Hematology, Oncology, Blood and Marrow Transplant, Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, The Ohio State University, Columbus, OH, USA
| | - Mohamed S Abdelbaki
- Division of Hematology, Oncology, Blood and Marrow Transplant, Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, The Ohio State University, Columbus, OH, USA
| | - Diana S Osorio
- Division of Hematology, Oncology, Blood and Marrow Transplant, Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, The Ohio State University, Columbus, OH, USA
| | - Selene C Koo
- Department of Pathology, The Ohio State University, Columbus, OH, USA.,Department of Pathology, Nationwide Children's Hospital, Columbus, OH, USA
| | - Daniel C Koboldt
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Alex H Wagner
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, The Ohio State University, Columbus, OH, USA.,Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
| | - Ann-Kathrin Eisfeld
- Division of Hematology, The Ohio State University, Columbus, OH, USA.,Clara D. Bloomfield Center for Leukemia Outcomes Research, The Ohio State University, Columbus, OH, USA.,The Ohio State Comprehensive Cancer Center, Columbus, OH, USA
| | - Krzysztof Mrózek
- Clara D. Bloomfield Center for Leukemia Outcomes Research, The Ohio State University, Columbus, OH, USA.,The Ohio State Comprehensive Cancer Center, Columbus, OH, USA
| | - Vincent Magrini
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, The Ohio State University, Columbus, OH, USA
| | - Catherine E Cottrell
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, The Ohio State University, Columbus, OH, USA.,Department of Pathology, The Ohio State University, Columbus, OH, USA
| | - Elaine R Mardis
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, The Ohio State University, Columbus, OH, USA
| | - Richard K Wilson
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, The Ohio State University, Columbus, OH, USA
| | - Peter White
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA. .,Department of Pediatrics, The Ohio State University, Columbus, OH, USA.
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195
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Fotakis G, Trajanoski Z, Rieder D. Computational cancer neoantigen prediction: current status and recent advances. IMMUNO-ONCOLOGY TECHNOLOGY 2021; 12:100052. [PMID: 35755950 PMCID: PMC9216660 DOI: 10.1016/j.iotech.2021.100052] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Over the last few decades, immunotherapy has shown significant therapeutic efficacy in a broad range of cancer types. Antitumor immune responses are contingent on the recognition of tumor-specific antigens, which are termed neoantigens. Tumor neoantigens are ideal targets for immunotherapy since they can be recognized as non-self antigens by the host immune system and thus are able to elicit an antitumor T-cell response. There are an increasing number of studies that highlight the importance of tumor neoantigens in immunoediting and in the sensitivity to immune checkpoint blockade. Therefore, one of the most fundamental tasks in the field of immuno-oncology research is the identification of patient-specific neoantigens. To this end, a plethora of computational approaches have been developed in order to predict tumor-specific aberrant peptides and quantify their likelihood of binding to patients' human leukocyte antigen molecules in order to be recognized by T cells. In this review, we systematically summarize and present the most recent advances in computational neoantigen prediction, and discuss the challenges and novel methods that are being developed to resolve them. Tumors have the ability to acquire immune escape mechanisms. Tumor-specific aberrant peptides (neoantigens) can elicit an immune response by the host immune system. The identification of neoantigens is one of the most fundamental tasks in the field of immuno-oncology research. A plethora of computational approaches have been developed in order to predict patient-specificneoantigens.
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Affiliation(s)
- G Fotakis
- Institute of Bioinformatics, Biocenter, Medical University of Innsbruck, Innsbruck, Austria
| | - Z Trajanoski
- Institute of Bioinformatics, Biocenter, Medical University of Innsbruck, Innsbruck, Austria
| | - D Rieder
- Institute of Bioinformatics, Biocenter, Medical University of Innsbruck, Innsbruck, Austria
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196
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Bishop JA, Sajed DP, Weinreb I, Dickson BC, Bilodeau EA, Agaimy A, Franchi A, Khurram SA, Da Forno P, Robledo J, Kalmar JR, Aguirre S, Krane JF, Tapia JL, Kiss K, Cordell K, Rosebush M, Barrett AW, Oda D, Assaad A, Nagao T, Kawakami F, Nakaguro M, Zahir I, Wakeman K, Ihrler S, Chenevert J, Lin YL, Westra WH, Gagan J, Rooper LM. Microsecretory Adenocarcinoma of Salivary Glands: An Expanded Series of 24 Cases. Head Neck Pathol 2021; 15:1192-1201. [PMID: 33982215 PMCID: PMC8633253 DOI: 10.1007/s12105-021-01331-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 04/28/2021] [Indexed: 10/21/2022]
Abstract
Microsecretory adenocarcinoma (MSA) is a recently described salivary gland tumor with a characteristic histologic and immunophenotypic profile and recurrent MEF2C-SS18 fusions. Because only six cases of MSA have been published, its complete clinicopathologic spectrum is unclear, and its biologic behavior has not been documented. Here, we present an updated and expanded experience of 24 MSA cases. All cases of MSA were obtained from the authors' files. Immunohistochemistry for S100, SOX10, p63, p40, SMA, calponin, and mammaglobin was performed. Molecular analysis was performed by targeted RNA sequencing, SS18 break apart fluorescence in situ hybridization, and/or reverse transcriptase polymerase chain reaction for MEF2C-SS18 fusion. Clinical follow-up was obtained from medical records. A total of 24 MSA cases were collected, from 13 women and 11 men, ranging from 17 to 83 years (mean 49.5 years). The vast majority (23 of 24) arose in the oral cavity, with the palate (n = 14) and buccal mucosa (n = 6) as the most frequent subsites. Tumors showed consistent histologic features including: (1) microcystic tubules, (2) flattened intercalated duct-like cells, (3) monotonous oval hyperchromatic nuclei, (4) abundant basophilic luminal secretions, (5) fibromyxoid stroma, and (6) circumscribed borders with subtle infiltration. The tumors were very consistently positive for S100 (24 of 24), p63 (24 of 24), and SOX10 (14 of 14) and negative for p40 (0 of 21), calponin (0 of 12) and mammaglobin (0 of 16), while SMA (4 of 20) was variable. MEF2C-SS18 fusion was demonstrated in 21 of 24 cases; in the remaining 3 cases with insufficient RNA, SS18 break apart FISH was positive. Treatment information was available in 17 cases, all of which were managed with surgery only. In 14 cases with follow-up (1-216 months, mean 30), no cases recurred or metastasized. MSA is a distinct salivary gland neoplasm with remarkably consistent clinical, histologic, immunophenotypic, and genetic features that generally behaves in an indolent manner following surgery alone. These observations solidify MSA as a unique, low-grade salivary gland carcinoma that warrants inclusion in the next version of the WHO classification of head and neck tumors.
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Affiliation(s)
- Justin A Bishop
- Department of Pathology, UT Southwestern Medical Center, Dallas, TX, USA.
| | - Dipti P Sajed
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | - Ilan Weinreb
- Department of Pathology, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Brendan C Dickson
- Department of Pathology & Laboratory Medicine, Mount Sinai Hospital, Toronto, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Elizabeth A Bilodeau
- Department of Diagnostic Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, USA
| | - Abbas Agaimy
- Institute of Pathology, University Hospital of Erlangen, Erlangen, Germany
| | - Alessandro Franchi
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Syed Ali Khurram
- Unit of Oral and Maxillofacial Pathology, School of Clinical Dentistry, 19 Claremont Crescent, Sheffield, S10 2TA, UK
| | - Philip Da Forno
- Department of Cellular Pathology, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Juliana Robledo
- Department of Pathology and Laboratory Medicine, Long School of Medicine, UT Health, San Antonio, TX, USA
| | - John R Kalmar
- Division of Oral and Maxillofacial Pathology, The Ohio State University College of Dentistry, Columbus, OH, USA
| | - Sarah Aguirre
- Division of Oral and Maxillofacial Pathology, The University of Tennessee Health Science Center College of Dentistry, Memphis, TN, USA
| | - Jeffrey F Krane
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | - Jose Luis Tapia
- Department of Oral Diagnostic Sciences, School of Dental Medicine, State University of New York at Buffalo, Buffalo, NY, USA
| | - Katalin Kiss
- Department of Pathology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Kitrina Cordell
- Department of Diagnostic Sciences, Louisiana State University Health Sciences Center School of Dentistry, New Orleans, LA, USA
| | - Molly Rosebush
- Department of Diagnostic Sciences, Louisiana State University Health Sciences Center School of Dentistry, New Orleans, LA, USA
| | - A William Barrett
- Department of Histopathology, Queen Victoria Hospital, Holtye Road, East Grinstead, West Sussex, RH19 3DZ, UK
| | - Dolphine Oda
- Department Oral & Maxillofacial Surgery, School of Dentistry, University of Washington, Seattle, WA, USA
| | - Adel Assaad
- Department of Pathology, Virginia Mason Hospital & Seattle Medical Center, Seattle, WA, USA
| | - Toshitaka Nagao
- Department of Anatomic Pathology, Tokyo Medical University, Tokyo, Japan
| | - Fumi Kawakami
- Department of Diagnostic Pathology, Kumamoto University Hospital, Kumamoto, Japan
| | - Masato Nakaguro
- Departments of Pathology and Laboratory Medicine, Nagoya University Hospital, Nagoya, Japan
| | - Ismail Zahir
- Department of Pathology Mount Sinai Brooklyn, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, USA
| | - Kristina Wakeman
- Department of Pathology and Laboratory Medicine, University of Louisville, Louisville, KY, USA
| | | | - Jacinthe Chenevert
- Pathology Department, L'Hôtel-Dieu de Québec, Centre Hospitalier Universitaire de Québec, Laval University, Quebec, Canada
| | - Yi-Ling Lin
- Division of Diagnostic and Surgical Sciences, School of Dentistry, University of California, Los Angeles, CA, USA
| | - William H Westra
- Department of Pathology, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, USA
| | - Jeffrey Gagan
- Department of Pathology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Lisa M Rooper
- Department of Pathology, The Johns Hopkins Hospital, Baltimore, MD, USA
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197
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Hung KL, Yost KE, Xie L, Shi Q, Helmsauer K, Luebeck J, Schöpflin R, Lange JT, Chamorro González R, Weiser NE, Chen C, Valieva ME, Wong ITL, Wu S, Dehkordi SR, Duffy CV, Kraft K, Tang J, Belk JA, Rose JC, Corces MR, Granja JM, Li R, Rajkumar U, Friedlein J, Bagchi A, Satpathy AT, Tjian R, Mundlos S, Bafna V, Henssen AG, Mischel PS, Liu Z, Chang HY. ecDNA hubs drive cooperative intermolecular oncogene expression. Nature 2021; 600:731-736. [PMID: 34819668 PMCID: PMC9126690 DOI: 10.1038/s41586-021-04116-8] [Citation(s) in RCA: 121] [Impact Index Per Article: 40.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 10/08/2021] [Indexed: 02/07/2023]
Abstract
Extrachromosomal DNA (ecDNA) is prevalent in human cancers and mediates high expression of oncogenes through gene amplification and altered gene regulation1. Gene induction typically involves cis-regulatory elements that contact and activate genes on the same chromosome2,3. Here we show that ecDNA hubs-clusters of around 10-100 ecDNAs within the nucleus-enable intermolecular enhancer-gene interactions to promote oncogene overexpression. ecDNAs that encode multiple distinct oncogenes form hubs in diverse cancer cell types and primary tumours. Each ecDNA is more likely to transcribe the oncogene when spatially clustered with additional ecDNAs. ecDNA hubs are tethered by the bromodomain and extraterminal domain (BET) protein BRD4 in a MYC-amplified colorectal cancer cell line. The BET inhibitor JQ1 disperses ecDNA hubs and preferentially inhibits ecDNA-derived-oncogene transcription. The BRD4-bound PVT1 promoter is ectopically fused to MYC and duplicated in ecDNA, receiving promiscuous enhancer input to drive potent expression of MYC. Furthermore, the PVT1 promoter on an exogenous episome suffices to mediate gene activation in trans by ecDNA hubs in a JQ1-sensitive manner. Systematic silencing of ecDNA enhancers by CRISPR interference reveals intermolecular enhancer-gene activation among multiple oncogene loci that are amplified on distinct ecDNAs. Thus, protein-tethered ecDNA hubs enable intermolecular transcriptional regulation and may serve as units of oncogene function and cooperative evolution and as potential targets for cancer therapy.
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Affiliation(s)
- King L Hung
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Kathryn E Yost
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Liangqi Xie
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, Berkeley, CA, USA
- Howard Hughes Medical Institute, Berkeley, CA, USA
| | - Quanming Shi
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Konstantin Helmsauer
- Department of Pediatric Oncology and Hematology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jens Luebeck
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Robert Schöpflin
- Development and Disease Research Group, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Joshua T Lange
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- ChEM-H, Stanford University, Stanford, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Rocío Chamorro González
- Department of Pediatric Oncology and Hematology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Natasha E Weiser
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Celine Chen
- Department of Pediatric Oncology and Hematology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Maria E Valieva
- Development and Disease Research Group, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ivy Tsz-Lo Wong
- ChEM-H, Stanford University, Stanford, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Sihan Wu
- Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Siavash R Dehkordi
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Connor V Duffy
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Katerina Kraft
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Jun Tang
- ChEM-H, Stanford University, Stanford, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Julia A Belk
- Department of Pathology, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - John C Rose
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - M Ryan Corces
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Jeffrey M Granja
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Rui Li
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Utkrisht Rajkumar
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Jordan Friedlein
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
| | - Anindya Bagchi
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
| | | | - Robert Tjian
- Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, Berkeley, CA, USA
- Howard Hughes Medical Institute, Berkeley, CA, USA
| | - Stefan Mundlos
- Development and Disease Research Group, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Vineet Bafna
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Anton G Henssen
- Department of Pediatric Oncology and Hematology, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Experimental and Clinical Research Center (ECRC), Max Delbrück Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center DKFZ, Heidelberg, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Paul S Mischel
- ChEM-H, Stanford University, Stanford, CA, USA
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Zhe Liu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA.
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198
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Izumi H, Matsumoto S, Liu J, Tanaka K, Mori S, Hayashi K, Kumagai S, Shibata Y, Hayashida T, Watanabe K, Fukuhara T, Ikeda T, Yoh K, Kato T, Nishino K, Nakamura A, Nakachi I, Kuyama S, Furuya N, Sakakibara-Konishi J, Okamoto I, Taima K, Ebi N, Daga H, Yamasaki A, Kodani M, Udagawa H, Kirita K, Zenke Y, Nosaki K, Sugiyama E, Sakai T, Nakai T, Ishii G, Niho S, Ohtsu A, Kobayashi SS, Goto K. The CLIP1-LTK fusion is an oncogenic driver in non-small-cell lung cancer. Nature 2021; 600:319-323. [PMID: 34819663 DOI: 10.1038/s41586-021-04135-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 10/13/2021] [Indexed: 11/09/2022]
Abstract
Lung cancer is one of the most aggressive tumour types. Targeted therapies stratified by oncogenic drivers have substantially improved therapeutic outcomes in patients with non-small-cell lung cancer (NSCLC)1. However, such oncogenic drivers are not found in 25-40% of cases of lung adenocarcinoma, the most common histological subtype of NSCLC2. Here we identify a novel fusion transcript of CLIP1 and LTK using whole-transcriptome sequencing in a multi-institutional genome screening platform (LC-SCRUM-Asia, UMIN000036871). The CLIP1-LTK fusion was present in 0.4% of NSCLCs and was mutually exclusive with other known oncogenic drivers. We show that kinase activity of the CLIP1-LTK fusion protein is constitutively activated and has transformation potential. Treatment of Ba/F3 cells expressing CLIP1-LTK with lorlatinib, an ALK inhibitor, inhibited CLIP1-LTK kinase activity, suppressed proliferation and induced apoptosis. One patient with NSCLC harbouring the CLIP1-LTK fusion showed a good clinical response to lorlatinib treatment. To our knowledge, this is the first description of LTK alterations with oncogenic activity in cancers. These results identify the CLIP1-LTK fusion as a target in NSCLC that could be treated with lorlatinib.
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Affiliation(s)
- Hiroki Izumi
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Shingo Matsumoto
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Jie Liu
- Division of Translational Genomics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Kashiwa, Japan
| | - Kosuke Tanaka
- Division of Translational Genomics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Kashiwa, Japan
| | - Shunta Mori
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Kumiko Hayashi
- LSI Medience Corporation Central Laboratory, Itabashi-ku, Japan
| | - Shogo Kumagai
- Division of Cancer Immunology, Research Institute/Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Kashiwa, Japan
| | - Yuji Shibata
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Takuma Hayashida
- Division of Translational Genomics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Kashiwa, Japan.,Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Kana Watanabe
- Department of Respiratory Medicine, Miyagi Cancer Center, Natori, Japan
| | - Tatsuro Fukuhara
- Department of Respiratory Medicine, Miyagi Cancer Center, Natori, Japan
| | - Takaya Ikeda
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Kiyotaka Yoh
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Terufumi Kato
- Department of Thoracic Oncology, Kanagawa Cancer Center, Yokohama, Japan
| | - Kazumi Nishino
- Department of Thoracic Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Atsushi Nakamura
- Department of Pulmonary Medicine, Sendai Kousei Hospital, Sendai, Japan
| | - Ichiro Nakachi
- Pulmonary Division, Department of Internal Medicine, Saiseikai Utsunomiya Hospital, Utsunomiya, Japan
| | - Shoichi Kuyama
- Department of Respiratory Medicine, National Hospital Organization Iwakuni Clinical Center, Iwakuni, Japan
| | - Naoki Furuya
- Division of Respiratory Medicine, Department of Internal Medicine, St Marianna University School of Medicine, Kawasaki, Japan
| | | | - Isamu Okamoto
- Research Institute for Diseases of the Chest, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kageaki Taima
- Department of Respiratory Medicine, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Noriyuki Ebi
- Department of Respiratory Medicine, Iizuka Hospital, Iizuka, Japan
| | - Haruko Daga
- Department of Medical Oncology, Osaka City General Hospital, Osaka, Japan
| | - Akira Yamasaki
- Division of Respiratory Medicine and Rheumatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Masahiro Kodani
- Division of Respiratory Medicine and Rheumatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Hibiki Udagawa
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan.,Division of Translational Genomics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Kashiwa, Japan
| | - Keisuke Kirita
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Yoshitaka Zenke
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Kaname Nosaki
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Eri Sugiyama
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Tetsuya Sakai
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Tokiko Nakai
- Department of Pathology and Clinical Laboratories, National Cancer Center, Kashiwa, Japan
| | - Genichiro Ishii
- Department of Pathology and Clinical Laboratories, National Cancer Center, Kashiwa, Japan
| | - Seiji Niho
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Atsushi Ohtsu
- Department of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Susumu S Kobayashi
- Division of Translational Genomics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Kashiwa, Japan. .,Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan. .,Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
| | - Koichi Goto
- Department of Thoracic Oncology, National Cancer Center Hospital East, Kashiwa, Japan.
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199
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Hagoel TJ, Cortez Gomez E, Gupta A, Twist CJ, Kozielski R, Martin JC, Gao L, Kuechle J, Singh PK, Lynch M, Wei L, Liu S, Wang J, Ohm JE. CLINICOPATHOLOGIC AND MOLECULAR ANALYSIS OF A SINGLE BCOR-CCNB3+ UNDIFFERENTIATED SARCOMA OF THE KIDNEY CONFERS SIGNIFICANT EPIGENETIC ALTERATIONS. Cold Spring Harb Mol Case Stud 2021; 8:mcs.a005942. [PMID: 34819304 PMCID: PMC8744494 DOI: 10.1101/mcs.a005942] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 11/10/2021] [Indexed: 11/24/2022] Open
Abstract
Undifferentiated soft tissue sarcomas (UDSTSs) are a group of mesenchymal tumors that remain a diagnostic challenge because of their morphologic heterogeneity and unclear histologic origin (Peters et al., Mod Pathol28: 575 [2015]). In this case report, we present the first multiomics molecular signature for a BCOR–CCNB3 sarcoma (BCS) that includes mutation analysis, gene expression, DNA methylation, and micro RNA (miRNA) expression. We identify a paucity of additional mutations in this tumor and detail that there is significant dysregulation of gene expression of epigenetic remodeling agents including key members of the PRC, Sin3A/3b, NuRD, and NcoR/SMRT complexes and the DNA methyltransferases DNMT1, DNMT3a, and DNMT3b. This is accompanied by significant DNA methylation changes and dysregulation of multiple miRNAs with known links to tumorigenesis. This study significantly increases our understanding of the BCOR effects on fusion-positive undifferentiated sarcomas at both the genomic and epigenomic level and suggests that as better-tailored and more refined treatment algorithms continue to evolve, epigenetic modifying agents should be further evaluated for their efficacy against these tumors.
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Affiliation(s)
| | | | - Ajay Gupta
- Roswell Park Comprehensive Cancer Center
| | | | | | | | - Lingui Gao
- Roswell Park Comprehensive Cancer Center
| | | | | | | | - Lei Wei
- Roswell Park Comprehensive Cancer Center
| | - Song Liu
- Roswell Park Comprehensive Cancer Center
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200
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Nong B, Guo M, Wang W, Songyang Z, Xiong Y. Comprehensive Analysis of Large-Scale Transcriptomes from Multiple Cancer Types. Genes (Basel) 2021; 12:1865. [PMID: 34946814 PMCID: PMC8701385 DOI: 10.3390/genes12121865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 11/21/2021] [Accepted: 11/24/2021] [Indexed: 11/16/2022] Open
Abstract
Various abnormalities of transcriptional regulation revealed by RNA sequencing (RNA-seq) have been reported in cancers. However, strategies to integrate multi-modal information from RNA-seq, which would help uncover more disease mechanisms, are still limited. Here, we present PipeOne, a cross-platform one-stop analysis workflow for large-scale transcriptome data. It was developed based on Nextflow, a reproducible workflow management system. PipeOne is composed of three modules, data processing and feature matrices construction, disease feature prioritization, and disease subtyping. It first integrates eight different tools to extract different information from RNA-seq data, and then used random forest algorithm to study and stratify patients according to evidences from multiple-modal information. Its application in five cancers (colon, liver, kidney, stomach, or thyroid; total samples n = 2024) identified various dysregulated key features (such as PVT1 expression and ABI3BP alternative splicing) and pathways (especially liver and kidney dysfunction) shared by multiple cancers. Furthermore, we demonstrated clinically-relevant patient subtypes in four of five cancers, with most subtypes characterized by distinct driver somatic mutations, such as TP53, TTN, BRAF, HRAS, MET, KMT2D, and KMT2C mutations. Importantly, these subtyping results were frequently contributed by dysregulated biological processes, such as ribosome biogenesis, RNA binding, and mitochondria functions. PipeOne is efficient and accurate in studying different cancer types to reveal the specificity and cross-cancer contributing factors of each cancer.It could be easily applied to other diseases and is available at GitHub.
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Affiliation(s)
- Baoting Nong
- Key Laboratory of Gene Engineering of the Ministry of Education, Institute of Healthy Aging Research, School of Life Sciences, Sun Yat-sen University, Guangzhou 510006, China; (B.N.); (M.G.); (Z.S.)
| | - Mengbiao Guo
- Key Laboratory of Gene Engineering of the Ministry of Education, Institute of Healthy Aging Research, School of Life Sciences, Sun Yat-sen University, Guangzhou 510006, China; (B.N.); (M.G.); (Z.S.)
| | - Weiwen Wang
- School of Mathematics, Sun Yat-sen University, Guangzhou 510006, China;
| | - Zhou Songyang
- Key Laboratory of Gene Engineering of the Ministry of Education, Institute of Healthy Aging Research, School of Life Sciences, Sun Yat-sen University, Guangzhou 510006, China; (B.N.); (M.G.); (Z.S.)
| | - Yuanyan Xiong
- Key Laboratory of Gene Engineering of the Ministry of Education, Institute of Healthy Aging Research, School of Life Sciences, Sun Yat-sen University, Guangzhou 510006, China; (B.N.); (M.G.); (Z.S.)
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