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Kolekar P, Balagopal V, Dong L, Liu Y, Foy S, Tran Q, Mulder H, Huskey AL, Plyler E, Liang Z, Ma J, Nakitandwe J, Gu J, Namwanje M, Maciaszek J, Payne-Turner D, Mallampati S, Wang L, Easton J, Klco JM, Ma X. SJPedPanel: A pan-cancer gene panel for childhood malignancies. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.11.27.23299068. [PMID: 38076942 PMCID: PMC10705664 DOI: 10.1101/2023.11.27.23299068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Background Large scale genomics projects have identified driver alterations for most childhood cancers that provide reliable biomarkers for clinical diagnosis and disease monitoring using targeted sequencing. However, there is lack of a comprehensive panel that matches the list of known driver genes. Here we fill this gap by developing SJPedPanel for childhood cancers. Results SJPedPanel covers 5,275 coding exons of 357 driver genes, 297 introns frequently involved in rearrangements that generate fusion oncoproteins, commonly amplified/deleted regions (e.g., MYCN for neuroblastoma, CDKN2A and PAX5 for B-/T-ALL, and SMARCB1 for AT/RT), and 7,590 polymorphism sites for interrogating tumors with aneuploidy, such as hyperdiploid and hypodiploid B-ALL or 17q gain neuroblastoma. We used driver alterations reported from an established real-time clinical genomics cohort (n=253) to validate this gene panel. Among the 485 pathogenic variants reported, our panel covered 417 variants (86%). For 90 rearrangements responsible for oncogenic fusions, our panel covered 74 events (82%). We re-sequenced 113 previously characterized clinical specimens at an average depth of 2,500X using SJPedPanel and recovered 354 (91%) of the 389 reported pathogenic variants. We then investigated the power of this panel in detecting mutations from specimens with low tumor purity (as low as 0.1%) using cell line-based dilution experiments and discovered that this gene panel enabled us to detect ∼80% variants with allele fraction of 0.2%, while the detection rate decreases to ∼50% when the allele fraction is 0.1%. We finally demonstrate its utility in disease monitoring on clinical specimens collected from AML patients in morphologic remission. Conclusions SJPedPanel enables the detection of clinically relevant genetic alterations including rearrangements responsible for subtype-defining fusions for childhood cancers by targeted sequencing of ∼0.15% of human genome. It will enhance the analysis of specimens with low tumor burdens for cancer monitoring and early detection.
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2
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Hu X, Fujiwara T, Sun Y, Huang W, Yan W. Does primary tumor resection improve survival for patients with sarcomas of pelvic bones, sacrum, and coccyx who have metastasis at diagnosis ? EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2023; 32:4362-4376. [PMID: 37870700 DOI: 10.1007/s00586-023-07985-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 09/14/2023] [Accepted: 10/02/2023] [Indexed: 10/24/2023]
Abstract
BACKGROUND Recent studies demonstrated that primary tumor resection (PTR) improves survival of patients with metastatic bone sarcomas. However, it remains quite unclear regarding the role of PTR in the treatment of sarcomas of pelvic bones with synchronous metastasis at diagnosis. METHODS Using the Surveillance, Epidemiology, and End Results Program, we enrolled a total of 385 patients with sarcomas of pelvic bones, sacrum, and coccyx who have metastasis at initial diagnosis, including 139 patients with osteosarcoma, 176 with Ewing sarcoma, and 70 with chondrosarcoma. Association between PTR and disease-specific survival (DSS) were investigated using the univariable and multivariable Cox regression models. Hazard ratio (HR) and 95% confidence interval (CI) were reported. Representative institutional PTR strategies and clinical outcomes for patients with metastatic pelvic sarcomas from our cancer center were displayed. RESULTS The usage rate of PTR was 28.1% (39/139) in osteosarcoma, 13.6% (24/176) in Ewing sarcoma, and 41.4% (29/70) in chondrosarcoma with synchronous metastatic lesions. PTR was not associated with an improved DSS for metastatic pelvic osteosarcoma (HR = 0.686, 95% CI = 0.430 ~ 1.094, P = 0.113) and Ewing sarcoma (HR = 0.580, 95% CI = 0.291 ~ 1.154, P = 0.121). The use of PTR was associated with an improved DSS for metastatic pelvic chondrosarcoma (HR = 0.464, 95% CI = 0.225 ~ 0.954, P = 0.037). CONCLUSION Primary lesion resection may provide a survival benefit for metastatic chondrosarcoma, but not for osteosarcoma and Ewing sarcoma of pelvic bones, sacrum, and coccyx. This population-based study recommends an active surgical intervention for metastatic chondrosarcoma while non-surgical treatment for metastatic osteosarcoma and Ewing sarcoma of the pelvis in terms of survival improvement.
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Affiliation(s)
- Xianglin Hu
- Department of Musculoskeletal Oncology, Spinal Tumor Center, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Tomohiro Fujiwara
- Department of Orthopaedic Surgery, Dentistry, and Pharmaceutical Sciences, Okayama University Graduate School of Medicine, Okayama, Japan
| | - Yangbai Sun
- Department of Musculoskeletal Oncology, Spinal Tumor Center, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Wending Huang
- Department of Musculoskeletal Oncology, Spinal Tumor Center, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Wangjun Yan
- Department of Musculoskeletal Oncology, Spinal Tumor Center, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
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3
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Welch DL, Fridley BL, Cen L, Teer JK, Yoder SJ, Pettersson F, Xu L, Cheng CH, Zhang Y, Alexandrow MG, Xiang S, Robertson-Tessi M, Brown JS, Metts J, Brohl AS, Reed DR. Modeling phenotypic heterogeneity towards evolutionarily inspired osteosarcoma therapy. Sci Rep 2023; 13:20125. [PMID: 37978271 PMCID: PMC10656496 DOI: 10.1038/s41598-023-47412-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 11/10/2023] [Indexed: 11/19/2023] Open
Abstract
Osteosarcoma is the most common bone sarcoma in children and young adults. While universally delivered, chemotherapy only benefits roughly half of patients with localized disease. Increasingly, intratumoral heterogeneity is recognized as a source of therapeutic resistance. In this study, we develop and evaluate an in vitro model of osteosarcoma heterogeneity based on phenotype and genotype. Cancer cell populations vary in their environment-specific growth rates and in their sensitivity to chemotherapy. We present the genotypic and phenotypic characterization of an osteosarcoma cell line panel with a focus on co-cultures of the most phenotypically divergent cell lines, 143B and SAOS2. Modest environmental (pH, glutamine) or chemical perturbations dramatically shift the success and composition of cell lines. We demonstrate that in nutrient rich culture conditions 143B outcompetes SAOS2. But, under nutrient deprivation or conventional chemotherapy, SAOS2 growth can be favored in spheroids. Importantly, when the simplest heterogeneity state is evaluated, a two-cell line coculture, perturbations that affect the faster growing cell line have only a modest effect on final spheroid size. Thus the only evaluated therapies to eliminate the spheroids were by switching therapies from a first strike to a second strike. This extensively characterized, widely available system, can be modeled and scaled to allow for improved strategies to anticipate resistance in osteosarcoma due to heterogeneity.
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Affiliation(s)
- Darcy L Welch
- Adolescent and Young Adult Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA
| | - Brooke L Fridley
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Ling Cen
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Jamie K Teer
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Sean J Yoder
- Molecular Genomics Core Facility, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Fredrik Pettersson
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Liping Xu
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Chia-Ho Cheng
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Yonghong Zhang
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Mark G Alexandrow
- Molecular Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Shengyan Xiang
- Molecular Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Mark Robertson-Tessi
- Integrative Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
- Cancer Biology and Evolution, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Joel S Brown
- Integrative Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
- Cancer Biology and Evolution, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Jonathan Metts
- Sarcoma Department, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Andrew S Brohl
- Sarcoma Department, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
- Molecular Medicine Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Damon R Reed
- Adolescent and Young Adult Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
- Integrative Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
- Cancer Biology and Evolution, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
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4
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Kinnaman MD, Zaccaria S, Makohon-Moore A, Arnold B, Levine MF, Gundem G, Arango Ossa JE, Glodzik D, Rodríguez-Sánchez MI, Bouvier N, Li S, Stockfisch E, Dunigan M, Cobbs C, Bhanot UK, You D, Mullen K, Melchor JP, Ortiz MV, O'Donohue TJ, Slotkin EK, Wexler LH, Dela Cruz FS, Hameed MR, Glade Bender JL, Tap WD, Meyers PA, Papaemmanuil E, Kung AL, Iacobuzio-Donahue CA. Subclonal Somatic Copy-Number Alterations Emerge and Dominate in Recurrent Osteosarcoma. Cancer Res 2023; 83:3796-3812. [PMID: 37812025 PMCID: PMC10646480 DOI: 10.1158/0008-5472.can-23-0385] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 07/14/2023] [Accepted: 09/01/2023] [Indexed: 10/10/2023]
Abstract
Multiple large-scale genomic profiling efforts have been undertaken in osteosarcoma to define the genomic drivers of tumorigenesis, therapeutic response, and disease recurrence. The spatial and temporal intratumor heterogeneity could also play a role in promoting tumor growth and treatment resistance. We conducted longitudinal whole-genome sequencing of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. Subclonal copy-number alterations were identified in all patients except one. In 5 patients, subclones from the primary tumor emerged and dominated at subsequent relapses. MYC gain/amplification was enriched in the treatment-resistant clones in 6 of 7 patients with multiple clones. Amplifications in other potential driver genes, such as CCNE1, RAD21, VEGFA, and IGF1R, were also observed in the resistant copy-number clones. A chromosomal duplication timing analysis revealed that complex genomic rearrangements typically occurred prior to diagnosis, supporting a macroevolutionary model of evolution, where a large number of genomic aberrations are acquired over a short period of time followed by clonal selection, as opposed to ongoing evolution. A mutational signature analysis of recurrent tumors revealed that homologous repair deficiency (HRD)-related SBS3 increases at each time point in patients with recurrent disease, suggesting that HRD continues to be an active mutagenic process after diagnosis. Overall, by examining the clonal relationships between temporally and spatially separated samples from patients with relapsed/refractory osteosarcoma, this study sheds light on the intratumor heterogeneity and potential drivers of treatment resistance in this disease. SIGNIFICANCE The chemoresistant population in recurrent osteosarcoma is subclonal at diagnosis, emerges at the time of primary resection due to selective pressure from neoadjuvant chemotherapy, and is characterized by unique oncogenic amplifications.
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Affiliation(s)
- Michael D. Kinnaman
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Regeneron Pharmaceuticals, Inc., Tarrytown, New York
| | - Simone Zaccaria
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, United Kingdom
- Computational Cancer Genomics Research Group, University College London Cancer Institute, London, United Kingdom
| | - Alvin Makohon-Moore
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Brian Arnold
- Department of Computer Science, Princeton University, Princeton, New Jersey
- Center for Statistics and Machine Learning, Princeton University, Princeton, New Jersey
| | - Max F. Levine
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Gunes Gundem
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Juan E. Arango Ossa
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Dominik Glodzik
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | | | - Nancy Bouvier
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Shanita Li
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Emily Stockfisch
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Marisa Dunigan
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Cassidy Cobbs
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Umesh K. Bhanot
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
- Precision Pathology Biobanking Center, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Daoqi You
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Katelyn Mullen
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- Gerstner Sloan Kettering Graduate School of Biomedical Sciences, New York, New York
| | - Jerry P. Melchor
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Michael V. Ortiz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Tara J. O'Donohue
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Emily K. Slotkin
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Leonard H. Wexler
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Filemon S. Dela Cruz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Meera R. Hameed
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Julia L. Glade Bender
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - William D. Tap
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Paul A. Meyers
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Elli Papaemmanuil
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Andrew L. Kung
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Christine A. Iacobuzio-Donahue
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
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5
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Mannheimer JD, Tawa G, Gerhold D, Braisted J, Sayers CM, McEachron TA, Meltzer P, Mazcko C, Beck JA, LeBlanc AK. Transcriptional profiling of canine osteosarcoma identifies prognostic gene expression signatures with translational value for humans. Commun Biol 2023; 6:856. [PMID: 37591946 PMCID: PMC10435536 DOI: 10.1038/s42003-023-05208-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 08/03/2023] [Indexed: 08/19/2023] Open
Abstract
Canine osteosarcoma is increasingly recognized as an informative model for human osteosarcoma. Here we show in one of the largest clinically annotated canine osteosarcoma transcriptional datasets that two previously reported, as well as de novo gene signatures devised through single sample Gene Set Enrichment Analysis (ssGSEA), have prognostic utility in both human and canine patients. Shared molecular pathway alterations are seen in immune cell signaling and activation including TH1 and TH2 signaling, interferon signaling, and inflammatory responses. Virtual cell sorting to estimate immune cell populations within canine and human tumors showed similar trends, predominantly for macrophages and CD8+ T cells. Immunohistochemical staining verified the increased presence of immune cells in tumors exhibiting immune gene enrichment. Collectively these findings further validate naturally occurring osteosarcoma of the pet dog as a translationally relevant patient model for humans and improve our understanding of the immunologic and genomic landscape of the disease in both species.
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Affiliation(s)
- Joshua D Mannheimer
- Comparative Oncology Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Gregory Tawa
- Division of Preclinical Innovation, Therapeutic Development Branch, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA
| | - David Gerhold
- Division of Preclinical Innovation, Therapeutic Development Branch, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA
| | - John Braisted
- Division of Preclinical Innovation, Therapeutic Development Branch, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA
| | - Carly M Sayers
- Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Troy A McEachron
- Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Paul Meltzer
- Genetics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Christina Mazcko
- Comparative Oncology Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jessica A Beck
- Comparative Oncology Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Amy K LeBlanc
- Comparative Oncology Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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6
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Kinnaman MD, Zaccaria S, Makohon-Moore A, Arnold B, Levine M, Gundem G, Ossa JEA, Glodzik D, Rodríguez-Sánchez MI, Bouvier N, Li S, Stockfisch E, Dunigan M, Cobbs C, Bhanot U, You D, Mullen K, Melchor J, Ortiz MV, O'Donohue T, Slotkin E, Wexler LH, Dela Cruz FS, Hameed M, Glade Bender JL, Tap WD, Meyers PA, Papaemmanuil E, Kung AL, Iacobuzio-Donahue CA. Subclonal somatic copy number alterations emerge and dominate in recurrent osteosarcoma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.05.522765. [PMID: 36711976 PMCID: PMC9881990 DOI: 10.1101/2023.01.05.522765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however, little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. We performed whole-genome sequencing of 37 tumor samples from eight patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. We identified subclonal copy number alterations in all but one patient. We observed that in five patients, a subclonal copy number clone from the primary tumor emerged and dominated at subsequent relapses. MYC gain/amplification was enriched in the treatment-resistant clone in 6 out of 7 patients with more than one clone. Amplifications in other potential driver genes, such as CCNE1, RAD21, VEGFA, and IGF1R, were also observed in the resistant copy number clones. Our study sheds light on intratumor heterogeneity and the potential drivers of treatment resistance in osteosarcoma.
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Affiliation(s)
- Michael D Kinnaman
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Simone Zaccaria
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Computational Cancer Genomics Research Group, University College London Cancer Institute, London, UK
| | - Alvin Makohon-Moore
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Hackensack Meridian Health Center for Discovery and Innovation, Nutley, NJ, USA (current affiliation)
- Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC, USA (current affiliation)
| | - Brian Arnold
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Center for Statistics and Machine Learning, Princeton University, Princeton, NJ, USA
| | - Max 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
- Isabl, New York, NY, USA (current affiliation)
| | - Gunes 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
| | - Juan 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
| | - Dominik Glodzik
- 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
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA (current affiliation)
| | - M Irene Rodríguez-Sánchez
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Wunderman Thompson Health, New York, NY, USA (current affiliation)
| | - Nancy Bouvier
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- IT and Digital Initiatives, Memorial Sloan Kettering Cancer Center, New York, NY, USA (current affiliation)
| | - Shanita Li
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Emily Stockfisch
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Marisa Dunigan
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Cassidy Cobbs
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Umesh 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
| | - Daoqi You
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Katelyn Mullen
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Gerstner Sloan Kettering Graduate School of Biomedical Sciences, New York, NY, USA
| | - Jerry Melchor
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Michael V Ortiz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Tara O'Donohue
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Emily Slotkin
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Leonard H Wexler
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Filemon S Dela Cruz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Meera Hameed
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Julia L Glade Bender
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - William D Tap
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Paul A Meyers
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Elli 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
| | - Andrew L Kung
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Christine A Iacobuzio-Donahue
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
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7
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Rosenkranz AA, Slastnikova TA, Durymanov MO, Georgiev GP, Sobolev AS. Exploiting active nuclear import for efficient delivery of Auger electron emitters into the cell nucleus. Int J Radiat Biol 2023; 99:28-38. [PMID: 32856963 DOI: 10.1080/09553002.2020.1815889] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND The most attractive features of Auger electrons (AEs) in cancer therapy are their extremely short range and sufficiently high linear energy transfer (LET) for a majority of them. The cytotoxic effects of AE emitters can be realized only in close vicinity to sensitive cellular targets and they are negligible if the emitters are located outside the cell. The nucleus is considered the compartment most sensitive to high LET particles. Therefore, the use of AE emitters could be most useful in specific recognition of a cancer cell and delivery of AE emitters into its nucleus. PURPOSE This review describes the studies aimed at developing effective anticancer agents for the delivery of AE emitters to the nuclei of target cancer cells. The use of peptide-based conjugates, nanoparticles, recombinant proteins, and other constructs for AE emitter targeted intranuclear delivery as well as their advantages and limitations are discussed. CONCLUSION Transport from the cytoplasm to the nucleus along with binding to the cancer cell is one of the key stages in the delivery of AE emitters; therefore, several constructs for exploitation of this transport have been developed. The transport is carried out through a nuclear pore complex (NPC) with the use of specific amino acid nuclear localization sequences (NLS) and carrier proteins named importins, which are located in the cytosol. Therefore, the effectiveness of NLS-containing delivery constructs designed to provide energy-dependent transport of AE emitter into the nuclei of cancer cells also depends on their efficient entry into the cytosol of the target cell.
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Affiliation(s)
- Andrey A Rosenkranz
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russia.,Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | | | | | | | - Alexander S Sobolev
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russia.,Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
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8
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How Genetics and Genomics Advances Are Rewriting Pediatric Cancer Research and Clinical Care. Medicina (B Aires) 2022; 58:medicina58101386. [PMID: 36295546 PMCID: PMC9610804 DOI: 10.3390/medicina58101386] [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: 08/10/2022] [Revised: 09/28/2022] [Accepted: 09/28/2022] [Indexed: 11/17/2022] Open
Abstract
In the last two decades, thanks to the data that have been obtained from the Human Genome Project and the development of next-generation sequencing (NGS) technologies, research in oncology has produced extremely important results in understanding the genomic landscape of pediatric cancers, which are the main cause of death during childhood. NGS has provided significant advances in medicine by detecting germline and somatic driver variants that determine the development and progression of many types of cancers, allowing a distinction between hereditary and non-hereditary cancers, characterizing resistance mechanisms that are also related to alterations of the epigenetic apparatus, and quantifying the mutational burden of tumor cells. A combined approach of next-generation technologies allows us to investigate the numerous molecular features of the cancer cell and the effects of the environment on it, discovering and following the path of personalized therapy to defeat an "ancient" disease that has had victories and defeats. In this paper, we provide an overview of the results that have been obtained in the last decade from genomic studies that were carried out on pediatric cancer and their contribution to the more accurate and faster diagnosis in the stratification of patients and the development of new precision therapies.
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9
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Bertrums EJ, Rosendahl Huber AK, de Kanter JK, Brandsma AM, van Leeuwen AJ, Verheul M, van den Heuvel-Eibrink MM, Oka R, van Roosmalen MJ, de Groot-Kruseman HA, Zwaan CM, Goemans BF, van Boxtel R. Elevated Mutational Age in Blood of Children Treated for Cancer Contributes to Therapy-Related Myeloid Neoplasms. Cancer Discov 2022; 12:1860-1872. [PMID: 35678530 PMCID: PMC7613255 DOI: 10.1158/2159-8290.cd-22-0120] [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: 01/28/2022] [Revised: 05/06/2022] [Accepted: 06/07/2022] [Indexed: 01/07/2023]
Abstract
Childhood cancer survivors are confronted with various chronic health conditions like therapy-related malignancies. However, it is unclear how exposure to chemotherapy contributes to the mutation burden and clonal composition of healthy tissues early in life. Here, we studied mutation accumulation in hematopoietic stem and progenitor cells (HSPC) before and after cancer treatment of 24 children. Of these children, 19 developed therapy-related myeloid neoplasms (t-MN). Posttreatment HSPCs had an average mutation burden increase comparable to what treatment-naïve cells accumulate during 16 years of life, with excesses up to 80 years. In most children, these additional mutations were induced by clock-like processes, which are also active during healthy aging. Other patients harbored mutations that could be directly attributed to treatments like platinum-based drugs and thiopurines. Using phylogenetic inference, we demonstrate that most t-MN in children originate after the start of treatment and that leukemic clones become dominant during or directly after chemotherapy exposure. SIGNIFICANCE Our study shows that chemotherapy increases the mutation burden of normal blood cells in cancer survivors. Only few drugs damage the DNA directly, whereas in most patients, chemotherapy-induced mutations are caused by processes similar to those present during normal aging. This article is highlighted in the In This Issue feature, p. 1825.
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Affiliation(s)
- Eline J.M. Bertrums
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Oncode Institute, Utrecht, the Netherlands.,Department of Pediatric Oncology, Erasmus Medical Center – Sophia Children's Hospital, Rotterdam, the Netherlands
| | - Axel K.M. Rosendahl Huber
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Oncode Institute, Utrecht, the Netherlands
| | - Jurrian K. de Kanter
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Oncode Institute, Utrecht, the Netherlands
| | - Arianne M. Brandsma
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Oncode Institute, Utrecht, the Netherlands
| | - Anaïs J.C.N. van Leeuwen
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Oncode Institute, Utrecht, the Netherlands
| | - Mark Verheul
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Oncode Institute, Utrecht, the Netherlands
| | | | - Rurika Oka
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Oncode Institute, Utrecht, the Netherlands
| | - Markus J. van Roosmalen
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Oncode Institute, Utrecht, the Netherlands
| | | | - C. Michel Zwaan
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Department of Pediatric Oncology, Erasmus Medical Center – Sophia Children's Hospital, Rotterdam, the Netherlands
| | - Bianca F. Goemans
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Ruben van Boxtel
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.,Oncode Institute, Utrecht, the Netherlands.,Corresponding Author: Ruben van Boxtel, Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584 CS, Utrecht, the Netherlands. Phone: 0031 (0)889727272; E-mail:
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10
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Brady SW, Gout AM, Zhang J. Therapeutic and prognostic insights from the analysis of cancer mutational signatures. Trends Genet 2022; 38:194-208. [PMID: 34483003 PMCID: PMC8752466 DOI: 10.1016/j.tig.2021.08.007] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/06/2021] [Accepted: 08/11/2021] [Indexed: 02/08/2023]
Abstract
The somatic mutations in each cancer genome are caused by multiple mutational processes, each of which leaves a characteristic imprint (or 'signature'), potentially caused by specific etiologies or exposures. Deconvolution of these signatures offers a glimpse into the evolutionary history of individual tumors. Recent work has shown that mutational signatures may also yield therapeutic and prognostic insights, including the identification of cell-intrinsic signatures as biomarkers of drug response and prognosis. For example, mutational signatures indicating homologous recombination deficiency are associated with poly(ADP)-ribose polymerase (PARP) inhibitor sensitivity, whereas APOBEC-associated signatures are associated with ataxia telangiectasia and Rad3-related kinase (ATR) inhibitor sensitivity. Furthermore, therapy-induced mutational signatures implicated in cancer progression have also been uncovered, including the identification of thiopurine-induced TP53 mutations in leukemia. In this review, we explore the various ways mutational signatures can reveal new therapeutic and prognostic insights, thus extending their traditional role in identifying disease etiology.
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Affiliation(s)
- Samuel W Brady
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
| | - Alexander M Gout
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Jinghui Zhang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
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11
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Zoumpoulidou G, Alvarez-Mendoza C, Mancusi C, Ahmed RM, Denman M, Steele CD, Tarabichi M, Roy E, Davies LR, Manji J, Cristalli C, Scotlandi K, Pillay N, Strauss SJ, Mittnacht S. Therapeutic vulnerability to PARP1,2 inhibition in RB1-mutant osteosarcoma. Nat Commun 2021; 12:7064. [PMID: 34862364 PMCID: PMC8642453 DOI: 10.1038/s41467-021-27291-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 11/11/2021] [Indexed: 11/09/2022] Open
Abstract
Loss-of-function mutations in the RB1 tumour suppressor are key drivers in cancer, including osteosarcoma. RB1 loss-of-function compromises genome-maintenance and hence could yield vulnerability to therapeutics targeting such processes. Here we demonstrate selective hypersensitivity to clinically-approved inhibitors of Poly-ADP-Polymerase1,2 inhibitors (PARPi) in RB1-defective cancer cells, including an extended panel of osteosarcoma-derived lines. PARPi treatment results in extensive cell death in RB1-defective backgrounds and prolongs survival of mice carrying human RB1-defective osteosarcoma grafts. PARPi sensitivity is not associated with canonical homologous recombination defect (HRd) signatures that predict PARPi sensitivity in cancers with BRCA1,2 loss, but is accompanied by rapid activation of DNA replication checkpoint signalling, and active DNA replication is a prerequisite for sensitivity. Importantly, sensitivity in backgrounds with natural or engineered RB1 loss surpasses that seen in BRCA-mutated backgrounds where PARPi have established clinical benefit. Our work provides evidence that PARPi sensitivity extends beyond cancers identifiable by HRd and advocates PARP1,2 inhibition as a personalised strategy for RB1-mutated osteosarcoma and other cancers.
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Affiliation(s)
| | | | | | | | - Milly Denman
- UCL Cancer Institute, University College London, London, UK
| | | | - Maxime Tarabichi
- The Francis Crick Institute, London, UK.,Institute for Interdisciplinary Research, Université Libre de Bruxelles, Brussels, Belgium
| | - Errin Roy
- UCL Cancer Institute, University College London, London, UK
| | | | - Jiten Manji
- UCL Cancer Institute, University College London, London, UK
| | - Camilla Cristalli
- Experimental Oncology Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Katia Scotlandi
- Experimental Oncology Laboratory, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Nischalan Pillay
- UCL Cancer Institute, University College London, London, UK.,Department of Histopathology, Royal National Orthopaedic Hospital, Stanmore, London, UK
| | - Sandra J Strauss
- UCL Cancer Institute, University College London, London, UK.,London Sarcoma Service, University College London Hospitals Foundation Trust, London, UK
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12
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Jiang J, Wang W, Xiang W, Jiang L, Zhou Q. The phosphoinositide 3-kinase inhibitor ZSTK474 increases the susceptibility of osteosarcoma cells to oncolytic vesicular stomatitis virus VSVΔ51 via aggravating endoplasmic reticulum stress. Bioengineered 2021; 12:11847-11857. [PMID: 34720036 PMCID: PMC8809975 DOI: 10.1080/21655979.2021.1999372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 10/22/2021] [Accepted: 10/24/2021] [Indexed: 11/17/2022] Open
Abstract
Blockage of phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) signal pathway is effective to increase the cytotoxic effects of oncolytic virus on cancer cells, but the detailed mechanisms are still largely unknown. Based on this, the present study managed to investigate the anti-tumor effects of PI3K inhibitor ZSTK474 and oncolytic vesicular stomatitis virus VSVΔ51 combination treatments on osteosarcoma (OS) in vitro and in vivo. Specifically, ZSTK474 aggravated the inhibiting effects of VSVΔ51 on osteosarcoma development by triggering endoplasmic reticulum (ER)-stress mediated apoptotic cell death. Mechanistically, either ZSTK474 or VSVΔ51 alone had limited effects on cell viability in osteosarcoma cells, while ZSTK474 and VSVΔ51 combination treatments significantly induced osteosarcoma cell apoptosis. Interestingly, VSVΔ51 increased the expression levels of IRE1α and p-PERK to initiate ER stress in osteosarcoma cells, which were aggravated by co-treating cells with ZSTK474. Next, the promoting effects of ZSTK474-VSVΔ51 combined treatment on osteosarcoma cell death were abrogated by the ER-stress inhibitor 4-phenyl butyric acid (4-PBA), indicating that ZSTK474 enhanced the cytotoxic effects of VSVΔ51 on osteosarcoma cells in an ER-stress dependent manner. Finally, the xenograft tumor-bearing mice models were established, and the results showed that ZSTK474-VSVΔ51 combined treatment synergistically hindered tumorigenesis of osteosarcoma cells in vivo. Taken together, our data suggested that ZSTK474 was a novel agent to enhance the cytotoxic effects of VSVΔ51 on osteosarcoma by aggravating ER-stress, and the present study might provide alternative therapy treatments for osteosarcoma in clinic.
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Affiliation(s)
- Jinqiong Jiang
- Department of Oncology, Hunan Provincial People’s Hospital, the First Affiliated Hospital of Hunan Normal University, Changsha, China
| | - Weida Wang
- Department of Spine Surgery, The First Hospital of Changsha, Changsha, Hunan, China
| | - Weineng Xiang
- Department of Spine Surgery, The First Hospital of Changsha, Changsha, Hunan, China
| | - Lin Jiang
- Department of Spine Surgery, The First Hospital of Changsha, Changsha, Hunan, China
| | - Qian Zhou
- Department of Spine Surgery, The First Hospital of Changsha, Changsha, Hunan, China
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13
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Skowron MA, Oing C, Bremmer F, Ströbel P, Murray MJ, Coleman N, Amatruda JF, Honecker F, Bokemeyer C, Albers P, Nettersheim D. The developmental origin of cancers defines basic principles of cisplatin resistance. Cancer Lett 2021; 519:199-210. [PMID: 34320371 DOI: 10.1016/j.canlet.2021.07.037] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/02/2021] [Accepted: 07/23/2021] [Indexed: 02/09/2023]
Abstract
Cisplatin-based chemotherapy has been used for more than four decades as a standard therapeutic option in several tumor entities. However, being a multifaceted and heterogeneous phenomenon, inherent or acquired resistance to cisplatin remains a major obstacle during the treatment of several solid malignancies and inevitably results in disease progression. Hence, we felt there was an urgent need to evaluate common mechanisms between multifarious cancer entities to identify patient-specific therapeutic strategies. We found joint molecular and (epi)genetic resistance mechanisms and specific cisplatin-induced mutational signatures that depended on the developmental origin (endo-, meso-, ectoderm) of the tumor tissue. Based on the findings of thirteen tumor entities, we identified three resistance groups, where Group 1 (endodermal origin) prominently indicates NRF2-pathway activation, Group 2 (mesodermal origin, primordial germ cells) shares elevated DNA repair mechanisms and decreased apoptosis induction, and Group 3 (ectodermal and paraxial mesodermal origin) commonly presents deregulated apoptosis induction and alternating pathways as the main cisplatin-induced resistance mechanisms. This review further proposes potential and novel therapeutic strategies to improve the outcome of cisplatin-based chemotherapy.
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Affiliation(s)
- Margaretha A Skowron
- Department of Urology, Urological Research Laboratory, Translational UroOncology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany.
| | - Christoph Oing
- Department of Oncology, Hematology and Bone Marrow Transplantation with Section of Pneumology, University Medical Center Hamburg-Eppendorf, Martinsstraße 52, 20246 Hamburg, Germany; Mildred Scheel Cancer Career Center HaTriCs4, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Martinsstraße 52, 20246 Hamburg, Germany.
| | - Felix Bremmer
- Institute of Pathology, University Medical Center Göttingen, Robert-Koch-Str.4, 37075 Gottingen, Germany.
| | - Philipp Ströbel
- Institute of Pathology, University Medical Center Göttingen, Robert-Koch-Str.4, 37075 Gottingen, Germany.
| | - Matthew J Murray
- Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge CB2 1QP, UK; Department of Pediatric Hematology and Oncology, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge CB2 0QQ, UK.
| | - Nicholas Coleman
- Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge CB2 1QP, UK; Department of Histopathology, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge CB2 0QQ, UK.
| | - James F Amatruda
- Departments of Pediatrics and Medicine, Keck School of Medicine, Cancer and Blood Disease Institute, Children's Hospital Los Angeles, University of Southern California, 1975 Zonal Ave., Los Angeles, CA 90033, USA.
| | - Friedemann Honecker
- Laboratory of Experimental Oncology, Department of Oncology, Hematology and Bone Marrow Transplantation with Section Pneumology, Hubertus Wald-Tumorzentrum, University Medical Center Hamburg-Eppendorf, Martinsstraße 52, 20246 Hamburg, Germany; Tumor and Breast Center ZeTuP St. Gallen, Rorschacher Strasse 150, 9000 St. Gallen, Switzerland.
| | - Carsten Bokemeyer
- Department of Oncology, Hematology and Bone Marrow Transplantation with Section of Pneumology, University Medical Center Hamburg-Eppendorf, Martinsstraße 52, 20246 Hamburg, Germany.
| | - Peter Albers
- Department of Urology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Moorenstraße 5, 40225 Düsseldorf, Germany.
| | - Daniel Nettersheim
- Department of Urology, Urological Research Laboratory, Translational UroOncology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany.
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14
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Kasiram MZ, Hapidin H, Abdullah H, Ahmad A, Sulong S. Combination Therapy of Cisplatin and other Agents for Osteosarcoma: A Review. CURRENT CANCER THERAPY REVIEWS 2021. [DOI: 10.2174/1573394716999201016160946] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Background:
Osteosarcoma is the most common type of primary bone tumor in children
and adolescents, which is associated with rapid progression and poor prognosis. Multimodal
therapy is the most common approach utilized for osteosarcoma management, such as the application
of chemotherapy in combination with surgery or radiation therapy. Cisplatin is one of the predominantly
used chemotherapeutic agents for osteosarcoma. Optimally, it is employed in combination
with other chemotherapeutic drugs along with surgery or radiation therapy. Despite the availability
of numerous treatment approaches, the patient survival rate has not definitively improved
over the past three decades.
Methods:
We have summarized all findings regarding the combination of cisplatin with other chemotherapeutic
agents as well as with phytochemical compounds.
Results:
A combination of cisplatin with a phytochemical compound synergistically enhances the
killing effect of cisplatin on osteosarcoma cells with fewer side effects compared to combination
with other chemotherapeutic agents.
Conclusion:
Conclusively, a combination of cisplatin with selected chemotherapeutic drugs has
been shown to be effective. However, the unchanged survival rate has posed an urge to search for a
new combination regimen. As a collaborative effort to substantiate the therapeutic efficacy, the
combination with phytochemical compounds shows a promising response both in vitro as well as
in the preclinical study.
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Affiliation(s)
- Mohamad Z. Kasiram
- School of Health Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Hermizi Hapidin
- School of Health Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Hasmah Abdullah
- School of Health Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Azlina Ahmad
- School of Dental Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Sarina Sulong
- Human Genome Centre, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kelantan, Malaysia
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15
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Gout AM, Arunachalam S, Finkelstein DB, Zhang J. Data-driven approaches to advance research and clinical care for pediatric cancer. Biochim Biophys Acta Rev Cancer 2021; 1876:188571. [PMID: 34051287 DOI: 10.1016/j.bbcan.2021.188571] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 05/07/2021] [Accepted: 05/22/2021] [Indexed: 11/17/2022]
Abstract
Pediatric cancer is a rare disease with a distinct etiology and mutational landscape compared with adult cancer. Multi-omics profiling of retrospective and prospective cohorts coupled with innovative computational analysis have been instrumental in uncovering mechanisms of tumorigenesis and drug resistance that are now informing pediatric cancer clinical therapy. In this review we present the major data resources of pediatric cancer and actionable insights into pediatric cancer etiology stemming from the identification of oncogenic gene fusions, mutational signature analysis, systems biology, cancer predisposition and survivorship studies - that have led to improved clinical diagnosis, discovery of new drug-targets, pharmacological therapy, and screening for genetic predisposition. Ultimately, integration of large-scale omics datasets generated through international collaboration is required to maximize the power of data-driven approaches to advance pediatric cancer research informing clinical therapy.
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Affiliation(s)
- Alexander M Gout
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Sasi Arunachalam
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - David B Finkelstein
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Jinghui Zhang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
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16
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Szikriszt B, Póti Á, Németh E, Kanu N, Swanton C, Szüts D. A comparative analysis of the mutagenicity of platinum-containing chemotherapeutic agents reveals direct and indirect mutagenic mechanisms. Mutagenesis 2021; 36:75-86. [PMID: 33502495 PMCID: PMC8081379 DOI: 10.1093/mutage/geab005] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 01/19/2021] [Indexed: 12/14/2022] Open
Abstract
Platinum-based drugs are a mainstay of cancer chemotherapy. However, their mutagenic effect can increase tumour heterogeneity, contribute to the evolution of treatment resistance and also induce secondary malignancies. We coupled whole genome sequencing with phenotypic investigations on two cell line models to compare the magnitude and examine the mechanism of mutagenicity of cisplatin, carboplatin and oxaliplatin. Cisplatin induced significantly more base substitution mutations than carboplatin or oxaliplatin when used at equitoxic concentrations on human TK6 or chicken DT40 cells, and also induced the highest number of short insertions and deletions. The analysis of base substitution spectra revealed that all three tested platinum drugs elicit both a direct mutagenic effect at purine dinucleotides, and an indirect effect of accelerating endogenous mutagenic processes, whereas the direct mutagenic effect appeared to correlate with the level of DNA damage caused as assessed through histone H2AX phosphorylation and single-cell agarose gel electrophoresis, the indirect mutagenic effects were equal. The different mutagenicity and DNA-damaging effect of equitoxic platinum drug treatments suggest that DNA damage independent mechanisms significantly contribute to their cytotoxicity. Thus, the comparatively high mutagenicity of cisplatin should be taken into account in the design of chemotherapeutic regimens.
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Affiliation(s)
- Bernadett Szikriszt
- Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Ádám Póti
- Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Eszter Németh
- Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Nnennaya Kanu
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Charles Swanton
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Dávid Szüts
- Institute of Enzymology, Research Centre for Natural Sciences, Budapest, Hungary
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17
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Davis EM, Sun Y, Liu Y, Kolekar P, Shao Y, Szlachta K, Mulder HL, Ren D, Rice SV, Wang Z, Nakitandwe J, Gout AM, Shaner B, Hall S, Robison LL, Pounds S, Klco JM, Easton J, Ma X. SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data. Genome Biol 2021; 22:37. [PMID: 33487172 PMCID: PMC7829059 DOI: 10.1186/s13059-020-02254-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 12/18/2020] [Indexed: 12/20/2022] Open
Abstract
Background There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations. Results We propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket. Conclusions Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets.
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Affiliation(s)
- Eric M Davis
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Yu Sun
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.,Department of Computer Science, University of Memphis, Memphis, TN, USA
| | - Yanling Liu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Pandurang Kolekar
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Ying Shao
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Karol Szlachta
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Heather L Mulder
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | | | - Stephen V Rice
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Zhaoming Wang
- Department of Epidemiology & Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Joy Nakitandwe
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Alexander M Gout
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Bridget Shaner
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Salina Hall
- Discovery Life Sciences, Huntsville, AL, USA
| | - Leslie L Robison
- Department of Epidemiology & Cancer Control, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Stanley Pounds
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jeffery M Klco
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - John Easton
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Xiaotu Ma
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
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18
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McLeod C, Gout AM, Zhou X, Thrasher A, Rahbarinia D, Brady SW, Macias M, Birch K, Finkelstein D, Sunny J, Mudunuri R, Orr BA, Treadway M, Davidson B, Ard TK, Chiao A, Swistak A, Wiggins S, Foy S, Wang J, Sioson E, Wang S, Michael JR, Liu Y, Ma X, Patel A, Edmonson MN, Wilkinson MR, Frantz AM, Chang TC, Tian L, Lei S, Islam SMA, Meyer C, Thangaraj N, Tater P, Kandali V, Ma S, Nguyen T, Serang O, McGuire I, Robison N, Gentry D, Tang X, Palmer LE, Wu G, Suh E, Tanner L, McMurry J, Lear M, Pappo AS, Wang Z, Wilson CL, Cheng Y, Meshinchi S, Alexandrov LB, Weiss MJ, Armstrong GT, Robison LL, Yasui Y, Nichols KE, Ellison DW, Bangur C, Mullighan CG, Baker SJ, Dyer MA, Miller G, Newman S, Rusch M, Daly R, Perry K, Downing JR, Zhang J. St. Jude Cloud: A Pediatric Cancer Genomic Data-Sharing Ecosystem. Cancer Discov 2021; 11:1082-1099. [PMID: 33408242 DOI: 10.1158/2159-8290.cd-20-1230] [Citation(s) in RCA: 101] [Impact Index Per Article: 33.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/17/2020] [Accepted: 12/14/2020] [Indexed: 02/07/2023]
Abstract
Effective data sharing is key to accelerating research to improve diagnostic precision, treatment efficacy, and long-term survival in pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data-sharing ecosystem for accessing, analyzing, and visualizing genomic data from >10,000 pediatric patients with cancer and long-term survivors, and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabytes are freely available, including 12,104 whole genomes, 7,697 whole exomes, and 2,202 transcriptomes. The resource is expanding rapidly, with regular data uploads from St. Jude's prospective clinical genomics programs. Three interconnected apps within the ecosystem-Genomics Platform, Pediatric Cancer Knowledgebase, and Visualization Community-enable simultaneously performing advanced data analysis in the cloud and enhancing the Pediatric Cancer knowledgebase. We demonstrate the value of the ecosystem through use cases that classify 135 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 pediatric cancer subtypes. SIGNIFICANCE: To advance research and treatment of pediatric cancer, we developed St. Jude Cloud, a data-sharing ecosystem for accessing >1.2 petabytes of raw genomic data from >10,000 pediatric patients and survivors, innovative analysis workflows, integrative multiomics visualizations, and a knowledgebase of published data contributed by the global pediatric cancer community.This article is highlighted in the In This Issue feature, p. 995.
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Affiliation(s)
- Clay McLeod
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Alexander M Gout
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Xin Zhou
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Andrew Thrasher
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Delaram Rahbarinia
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Samuel W Brady
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Michael Macias
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Kirby Birch
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - David Finkelstein
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Jobin Sunny
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Rahul Mudunuri
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Brent A Orr
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Madison Treadway
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | | | | | - Arthur Chiao
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Andrew Swistak
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Stephanie Wiggins
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Scott Foy
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Jian Wang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Edgar Sioson
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Shuoguo Wang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - J Robert Michael
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Yu Liu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Xiaotu Ma
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Aman Patel
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Michael N Edmonson
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Mark R Wilkinson
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Andrew M Frantz
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Ti-Cheng Chang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Liqing Tian
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Shaohua Lei
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - S M Ashiqul Islam
- Department of Cellular and Molecular Medicine and Department of Bioengineering, Moores Cancer Center, University of California, San Diego, La Jolla, California
| | | | | | | | | | | | | | | | - Irina McGuire
- Department of Information Services, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Nedra Robison
- Department of Information Services, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Darrell Gentry
- Department of Information Services, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Xing Tang
- Department of Hematology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Lance E Palmer
- Department of Hematology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Gang Wu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Ed Suh
- Department of Information Services, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Leigh Tanner
- Department of Information Services, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - James McMurry
- Department of Information Services, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Matthew Lear
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Alberto S Pappo
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Zhaoming Wang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee.,Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Carmen L Wilson
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Yong Cheng
- Department of Hematology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Soheil Meshinchi
- Fred Hutchinson Cancer Research Center Professor of Pediatrics, University of Washington School of Medicine, Seattle, Washington
| | - Ludmil B Alexandrov
- Department of Cellular and Molecular Medicine and Department of Bioengineering, Moores Cancer Center, University of California, San Diego, La Jolla, California
| | - Mitchell J Weiss
- Department of Hematology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Gregory T Armstrong
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Leslie L Robison
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Yutaka Yasui
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Kim E Nichols
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - David W Ellison
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | | | - Charles G Mullighan
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Suzanne J Baker
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Michael A Dyer
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | | | - Scott Newman
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Michael Rusch
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | | | - Keith Perry
- Department of Information Services, St. Jude Children's Research Hospital, Memphis, Tennessee.
| | - James R Downing
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee.
| | - Jinghui Zhang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee.
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19
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Brady SW, Liu Y, Ma X, Gout AM, Hagiwara K, Zhou X, Wang J, Macias M, Chen X, Easton J, Mulder HL, Rusch M, Wang L, Nakitandwe J, Lei S, Davis EM, Naranjo A, Cheng C, Maris JM, Downing JR, Cheung NKV, Hogarty MD, Dyer MA, Zhang J. Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations. Nat Commun 2020; 11:5183. [PMID: 33056981 PMCID: PMC7560655 DOI: 10.1038/s41467-020-18987-4] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 08/27/2020] [Indexed: 02/06/2023] Open
Abstract
Neuroblastoma is a pediatric malignancy with heterogeneous clinical outcomes. To better understand neuroblastoma pathogenesis, here we analyze whole-genome, whole-exome and/or transcriptome data from 702 neuroblastoma samples. Forty percent of samples harbor at least one recurrent driver gene alteration and most aberrations, including MYCN, ATRX, and TERT alterations, differ in frequency by age. MYCN alterations occur at median 2.3 years of age, TERT at 3.8 years, and ATRX at 5.6 years. COSMIC mutational signature 18, previously associated with reactive oxygen species, is the most common cause of driver point mutations in neuroblastoma, including most ALK and Ras-activating variants. Signature 18 appears early and is continuous throughout disease evolution. Signature 18 is enriched in neuroblastomas with MYCN amplification, 17q gain, and increased expression of mitochondrial ribosome and electron transport-associated genes. Recurrent FGFR1 variants in six patients, and ALK N-terminal structural alterations in five samples, identify additional patients potentially amenable to precision therapy.
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Affiliation(s)
- Samuel W Brady
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Yanling Liu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Xiaotu Ma
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Alexander M Gout
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Kohei Hagiwara
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Xin Zhou
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jian Wang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Michael Macias
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Xiaolong Chen
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - John Easton
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Heather L Mulder
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Michael Rusch
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Lu Wang
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Joy Nakitandwe
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Shaohua Lei
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Eric M Davis
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Arlene Naranjo
- Department of Biostatistics, University of Florida, Children's Oncology Group Statistics & Data Center, Gainesville, FL, USA
| | - Cheng Cheng
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - John M Maris
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - James R Downing
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Nai-Kong V Cheung
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Michael D Hogarty
- Division of Oncology, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
| | - Michael A Dyer
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, USA.
| | - Jinghui Zhang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
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20
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Applications of probability and statistics in cancer genomics. QUANTITATIVE BIOLOGY 2020. [DOI: 10.1007/s40484-020-0203-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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21
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Mao CX, Li M, Zhang W, Zhou HH, Yin JY, Liu ZQ. Pharmacogenomics for the efficacy of platinum-based chemotherapy: Old drugs, new integrated perspective. Biomed Pharmacother 2020; 126:110057. [PMID: 32145590 DOI: 10.1016/j.biopha.2020.110057] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Revised: 02/16/2020] [Accepted: 02/25/2020] [Indexed: 01/16/2023] Open
Abstract
Platinum-based chemotherapy remains the cornerstone of treatment for many malignancies. However, although therapeutic efficiency varies greatly among individuals, there is a lack of pharmacogenomic biomarkers that can be used in clinical settings to identify chemosensitive patients and allow stratification. With the development of high-throughput screening techniques and systems biology approaches, a growing body of evidence has shown that platinum resistance is a multifactorial, multi-dimensional, dynamic process incorporating genetic background, tumor evolution and gut microbes. This review critically summarizes potential pharmacogenomic biomarkers for predicting the efficacy of platinum drugs and provides a comprehensive, time-varying perspective that integrates multiple markers.
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Affiliation(s)
- Chen-Xue Mao
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410078, PR China
| | - Min Li
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, PR China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, PR China
| | - Wei Zhang
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410078, PR China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, PR China
| | - Hong-Hao Zhou
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410078, PR China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, PR China
| | - Ji-Ye Yin
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410078, PR China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, PR China.
| | - Zhao-Qian Liu
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, PR China; Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, PR China; Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha 410078, PR China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, PR China.
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22
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Andersson N, Bakker B, Karlsson J, Valind A, Holmquist Mengelbier L, Spierings DCJ, Foijer F, Gisselsson D. Extensive Clonal Branching Shapes the Evolutionary History of High-Risk Pediatric Cancers. Cancer Res 2020; 80:1512-1523. [PMID: 32041836 DOI: 10.1158/0008-5472.can-19-3468] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 12/18/2019] [Accepted: 02/04/2020] [Indexed: 11/16/2022]
Abstract
Darwinian evolution of tumor cells remains underexplored in childhood cancer. We here reconstruct the evolutionary histories of 56 pediatric primary tumors, including 24 neuroblastomas, 24 Wilms tumors, and 8 rhabdomyosarcomas. Whole-genome copy-number and whole-exome mutational profiling of multiple regions per tumor were performed, followed by clonal deconvolution to reconstruct a phylogenetic tree for each tumor. Overall, 88% of the tumors exhibited genetic variation among primary tumor regions. This variability typically emerged through collateral phylogenetic branching, leading to spatial variability in the distribution of more than 50% (96/173) of detected diagnostically informative genetic aberrations. Single-cell sequencing of 547 individual cancer cells from eight solid pediatric tumors confirmed branching evolution to be a fundamental underlying principle of genetic variation in all cases. Strikingly, cell-to-cell genetic diversity was almost twice as high in aggressive compared with clinically favorable tumors (median Simpson index of diversity 0.45 vs. 0.88; P = 0.029). Similarly, a comparison of multiregional sampling data from a total of 274 tumor regions showed that new phylogenetic branches emerge at a higher frequency per sample and carry a higher mutational load in high-risk than in low-risk tumors. Timelines based on spatial genetic variation showed that the mutations most influencing relapse risk occur at initiation of clonal expansion in neuroblastoma and rhabdomyosarcoma, whereas in Wilms tumor, they are late events. Thus, from an evolutionary standpoint, some high-risk childhood cancers are born bad, whereas others grow worse over time. SIGNIFICANCE: Different pediatric cancers with a high risk of relapse share a common generic pattern of extensively branching evolution of somatic mutations. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/7/1512/F1.large.jpg.
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Affiliation(s)
- Natalie Andersson
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden
| | - Bjorn Bakker
- European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Jenny Karlsson
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden
| | - Anders Valind
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden.,Department of Pediatrics, Skåne University Hospital, Lund, Sweden
| | | | - Diana C J Spierings
- European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Floris Foijer
- European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - David Gisselsson
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden. .,Division of Oncology-Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden.,Clinical Genetics and Pathology, Laboratory Medicine, Lund University Hospital, Skåne Healthcare Region, Lund, Sweden
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23
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Li B, Brady SW, Ma X, Shen S, Zhang Y, Li Y, Szlachta K, Dong L, Liu Y, Yang F, Wang N, Flasch DA, Myers MA, Mulder HL, Ding L, Liu Y, Tian L, Hagiwara K, Xu K, Zhou X, Sioson E, Wang T, Yang L, Zhao J, Zhang H, Shao Y, Sun H, Sun L, Cai J, Sun HY, Lin TN, Du L, Li H, Rusch M, Edmonson MN, Easton J, Zhu X, Zhang J, Cheng C, Raphael BJ, Tang J, Downing JR, Alexandrov LB, Zhou BBS, Pui CH, Yang JJ, Zhang J. Therapy-induced mutations drive the genomic landscape of relapsed acute lymphoblastic leukemia. Blood 2020; 135:41-55. [PMID: 31697823 PMCID: PMC6940198 DOI: 10.1182/blood.2019002220] [Citation(s) in RCA: 152] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 10/10/2019] [Indexed: 12/23/2022] Open
Abstract
To study the mechanisms of relapse in acute lymphoblastic leukemia (ALL), we performed whole-genome sequencing of 103 diagnosis-relapse-germline trios and ultra-deep sequencing of 208 serial samples in 16 patients. Relapse-specific somatic alterations were enriched in 12 genes (NR3C1, NR3C2, TP53, NT5C2, FPGS, CREBBP, MSH2, MSH6, PMS2, WHSC1, PRPS1, and PRPS2) involved in drug response. Their prevalence was 17% in very early relapse (<9 months from diagnosis), 65% in early relapse (9-36 months), and 32% in late relapse (>36 months) groups. Convergent evolution, in which multiple subclones harbor mutations in the same drug resistance gene, was observed in 6 relapses and confirmed by single-cell sequencing in 1 case. Mathematical modeling and mutational signature analysis indicated that early relapse resistance acquisition was frequently a 2-step process in which a persistent clone survived initial therapy and later acquired bona fide resistance mutations during therapy. In contrast, very early relapses arose from preexisting resistant clone(s). Two novel relapse-specific mutational signatures, one of which was caused by thiopurine treatment based on in vitro drug exposure experiments, were identified in early and late relapses but were absent from 2540 pan-cancer diagnosis samples and 129 non-ALL relapses. The novel signatures were detected in 27% of relapsed ALLs and were responsible for 46% of acquired resistance mutations in NT5C2, PRPS1, NR3C1, and TP53. These results suggest that chemotherapy-induced drug resistance mutations facilitate a subset of pediatric ALL relapses.
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Affiliation(s)
- Benshang Li
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
- Pediatric Translational Medicine Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Samuel W Brady
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Xiaotu Ma
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Shuhong Shen
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
- Pediatric Translational Medicine Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingchi Zhang
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Blood Diseases Hospital-Center for Stem Cell Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
| | - Yongjin Li
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Karol Szlachta
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Li Dong
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Yu Liu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Fan Yang
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
- Pediatric Translational Medicine Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ningling Wang
- Department of Pediatrics, the Second Hospital of Anhui Medical University, Hefei, China
| | - Diane A Flasch
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Matthew A Myers
- Department of Computer Science, Princeton University, Princeton, NJ
| | - Heather L Mulder
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Lixia Ding
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
- Pediatric Translational Medicine Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanling Liu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Liqing Tian
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Kohei Hagiwara
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Ke Xu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Xin Zhou
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Edgar Sioson
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Tianyi Wang
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
| | - Liu Yang
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
| | - Jie Zhao
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
| | - Hui Zhang
- Department of Pediatric Hematology/Oncology, Guangzhou Women and Children's Medical Center, Guangzhou, Guangdong, China
| | - Ying Shao
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | | | - Lele Sun
- WuXi NextCODE Co., Ltd, Shanghai, China
| | - Jiaoyang Cai
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
| | - Hui-Ying Sun
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
| | | | - Lijuan Du
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
- Pediatric Translational Medicine Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hui Li
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
- Pediatric Translational Medicine Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Michael Rusch
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Michael N Edmonson
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - John Easton
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
| | - Xiaofan Zhu
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Blood Diseases Hospital-Center for Stem Cell Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
| | - Jingliao Zhang
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Blood Diseases Hospital-Center for Stem Cell Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
| | | | | | - Jingyan Tang
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
| | - James R Downing
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee, TN
| | - Ludmil B Alexandrov
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA; and
| | - Bin-Bing S Zhou
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center-National Children's Medical Center, and
- Pediatric Translational Medicine Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ching-Hon Pui
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN
| | | | - Jinghui Zhang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN
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24
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Schott C, Shah AT, Sweet-Cordero EA. Genomic Complexity of Osteosarcoma and Its Implication for Preclinical and Clinical Targeted Therapies. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1258:1-19. [PMID: 32767231 DOI: 10.1007/978-3-030-43085-6_1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Osteosarcoma is a genomically complex disease characterized by few recurrent single-nucleotide mutations or in-frame fusions. In contrast, structural alterations, including copy number changes, chromothripsis, kataegis, loss of heterozygosity (LOH), and other large-scale genomic alterations, are frequent and widespread across the osteosarcoma genome. These observed structural alterations lead to activation of oncogenes and loss of tumor suppressors which together contribute to oncogenesis. To date, few targeted therapies for osteosarcoma have been identified. It is likely that effectiveness of targeted therapies will vary greatly in subsets of tumors with distinct key driver events. Model systems which can recapitulate the genetic heterogeneity of this disease are needed to test this hypothesis. One possible approach is to use patient-derived xenograft (PDX) models characterized with regards to their similarity to the human tumor samples from which they were derived. Here we review evidence pointing to the genomic complexity of osteosarcoma and how this is reflected in available model systems. We also review the current state of preclinical testing for targeted therapies using these models.
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Affiliation(s)
- Courtney Schott
- Department of Pediatrics, Division of Hematology and Oncology, University of California San Francisco, San Francisco, CA, USA
| | - Avanthi Tayi Shah
- Department of Pediatrics, Division of Hematology and Oncology, University of California San Francisco, San Francisco, CA, USA
| | - E Alejandro Sweet-Cordero
- Department of Pediatrics, Division of Hematology and Oncology, University of California San Francisco, San Francisco, CA, USA.
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25
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Relapsed Osteosarcoma Trial Concepts to Match the Complexity of the Disease. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1257:85-94. [PMID: 32483733 DOI: 10.1007/978-3-030-43032-0_8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Osteosarcoma relapses not only herald a very poor prognosis but also opportunities to treat this genetically diverse complex cancer in new ways. This review will attempt to show that the field is a rapidly evolving one in which not only cytotoxic agents but also local control strategies and the immune system can be harnessed to improve the prognosis of relapsed patients. The molecular heterogeneity and the difficulty of effectively treating most common patterns of relapse with surgery and/or radiation (lung and/or bone metastases) have been responsible for a wide variety of approaches to learning whether agents are active against osteosarcoma. This chapter will highlight past, current, and potential future approaches to provide more effective systemic therapy for the problem of recurrent metastases of osteosarcoma. These include single-agent trials with a wide variety of agents, radiopharmaceuticals, and immune therapies. Finally, how such efforts are integrated into more effective local control strategies is also discussed.
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26
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Yi X, Deng X, Zhao Y, Deng B, Deng J, Fan H, Du Y, Hao L. Ubiquitin-like protein FAT10 promotes osteosarcoma growth by modifying the ubiquitination and degradation of YAP1. Exp Cell Res 2019; 387:111804. [PMID: 31877302 DOI: 10.1016/j.yexcr.2019.111804] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2019] [Revised: 12/19/2019] [Accepted: 12/22/2019] [Indexed: 02/02/2023]
Abstract
Osteosarcoma is a common malignancy of the bone tissue. The rapid growth exhibited by this cancer is a primary challenge in its treatment. In many types of cancers, FAT10, a ubiquitin-like protein, is involved in several biological activities, especially cell proliferation. Herein, we demonstrate that FAT10 plays a vital role in tumorigenesis and is overexpressed in tumor tissues compared to its expression in adjacent normal tissues. Functional assays revealed that knockdown of FAT10 expression significantly repressed the proliferation of osteosarcoma in vitro and in vivo. Furthermore, our results indicate that FAT10 exhibits oncogenic functions by regulating the level of YAP1, a key protein of the Hippo/YAP signaling pathway, and a significant positive correlation exists between the levels of FAT10 and YAP1. Further analysis showed that FAT10-induced growth of osteosarcoma cells is dependent on YAP1. Mechanistically, FAT10 stabilizes YAP1 expression by regulating its ubiquitination and degradation. Taken together, our results link the two drivers of cell growth in osteosarcoma and reveal a novel pathway for FAT10 regulation. We provide new evidence for the biological and clinical significance of FAT10 as a potential biomarker for osteosarcoma.
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Affiliation(s)
- Xuan Yi
- Department of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xueqiang Deng
- Department of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yanzhi Zhao
- The First Clinical Medical College of Nanchang University, Nanchang, China
| | - Binbin Deng
- Department of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Jianyong Deng
- Department of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Huimin Fan
- Department of Ophthalmology, Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yunyan Du
- Department of Medical, Jiangxi Provincial People's Hospital, Nanchang, China; Department of Otorhinolaryngology, Jiangxi Provincial People's Hospital, Nanchang, China.
| | - Liang Hao
- Department of Orthopedics, Second Affiliated Hospital of Nanchang University, Nanchang, China.
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27
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Pich O, Muiños F, Lolkema MP, Steeghs N, Gonzalez-Perez A, Lopez-Bigas N. The mutational footprints of cancer therapies. Nat Genet 2019; 51:1732-1740. [PMID: 31740835 PMCID: PMC6887544 DOI: 10.1038/s41588-019-0525-5] [Citation(s) in RCA: 161] [Impact Index Per Article: 32.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 09/30/2019] [Indexed: 12/02/2022]
Abstract
Some cancer therapies damage DNA and cause mutations both in cancer and healthy cells of the patient. Therapy-induced mutations may underlie some of the long-term and late side effects of treatments, such as mental disabilities, organ toxicities and secondary neoplasms. Currently we ignore the mutation burden caused by different cancer treatments. Here we identify mutational signatures, or footprints of six widely-used anti-cancer therapies across more than 3,500 metastatic tumors originating from different organs. These include previously known and new mutational signatures generated by platinum-based drugs, and a novel signature of nucleoside metabolic inhibitors. Exploiting these mutational footprints, we estimate the contribution of different treatments to the mutation burden of tumors and their risk of contributing coding and potential driver mutations in the genome. The mutational footprints identified here allow for precisely assessing the mutational risk of different cancer therapies to understand their long-term side effects.
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Affiliation(s)
- Oriol Pich
- Institute for Research in Biomedicine Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Ferran Muiños
- Institute for Research in Biomedicine Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Martijn Paul Lolkema
- Department of Medical Oncology, Erasmus Medical Center Cancer Institute, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Neeltje Steeghs
- The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Abel Gonzalez-Perez
- Institute for Research in Biomedicine Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain.,Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain
| | - Nuria Lopez-Bigas
- Institute for Research in Biomedicine Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain. .,Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain. .,Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain.
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28
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Castillo-Tandazo W, Mutsaers AJ, Walkley CR. Osteosarcoma in the Post Genome Era: Preclinical Models and Approaches to Identify Tractable Therapeutic Targets. Curr Osteoporos Rep 2019; 17:343-352. [PMID: 31529263 DOI: 10.1007/s11914-019-00534-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
PURPOSE OF REVIEW Osteosarcoma (OS) is the most common cancer of bone, yet is classified as a rare cancer. Treatment and outcomes for OS have not substantively changed in several decades. While the decoding of the OS genome greatly advanced the understanding of the mutational landscape of OS, immediately actionable therapeutic targets were not apparent. Here we describe recent preclinical models that can be leveraged to identify, test, and prioritize therapeutic candidates. RECENT FINDINGS The generation of multiple high fidelity murine models of OS, the spontaneous disease that arises in pet dogs, and the establishment of a diverse collection of patient-derived OS xenografts provide a robust preclinical platform for OS. These models enable evidence to be accumulated across multiple stages of preclinical evaluation. Chemical and genetic screening has identified therapeutic targets, often demonstrating cross species activity. Clinical trials in both PDX models and in canine OS have effectively tested new therapies for prioritization. Improving clinical outcomes in OS has proven elusive. The integrated target discovery and testing possible through a cross species platform provides validation of a putative target and may enable the rigorous evaluation of new therapies in models where endpoints can be rapidly assessed.
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Affiliation(s)
- Wilson Castillo-Tandazo
- St. Vincent's Institute, 9 Princes St, Fitzroy, VIC, 3065, Australia
- Department of Medicine, St. Vincent's Hospital, University of Melbourne, Fitzroy, VIC, 3065, Australia
| | - Anthony J Mutsaers
- Department of Biomedical Sciences, Ontario Veterinary College, Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, Canada.
| | - Carl R Walkley
- St. Vincent's Institute, 9 Princes St, Fitzroy, VIC, 3065, Australia.
- Department of Medicine, St. Vincent's Hospital, University of Melbourne, Fitzroy, VIC, 3065, Australia.
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, 3000, Australia.
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29
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Krook MA, Bonneville R, Chen HZ, Reeser JW, Wing MR, Martin DM, Smith AM, Dao T, Samorodnitsky E, Paruchuri A, Miya J, Baker KR, Yu L, Timmers C, Dittmar K, Freud AG, Allenby P, Roychowdhury S. Tumor heterogeneity and acquired drug resistance in FGFR2-fusion-positive cholangiocarcinoma through rapid research autopsy. Cold Spring Harb Mol Case Stud 2019; 5:a004002. [PMID: 31371345 PMCID: PMC6672025 DOI: 10.1101/mcs.a004002] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 04/15/2019] [Indexed: 12/20/2022] Open
Abstract
Cholangiocarcinoma is a highly aggressive and lethal malignancy, with limited treatment options available. Recently, FGFR inhibitors have been developed and utilized in FGFR-mutant cholangiocarcinoma; however, resistance often develops and the genomic determinants of resistance are not fully characterized. We completed whole-exome sequencing (WES) of 11 unique tumor samples obtained from a rapid research autopsy on a patient with FGFR-fusion-positive cholangiocarcinoma who initially responded to the pan-FGFR inhibitor, INCB054828. In vitro studies were carried out to characterize the novel FGFR alteration and secondary FGFR2 mutation identified. Multisite WES and analysis of tumor heterogeneity through subclonal inference identified four genetically distinct cancer cell populations, two of which were only observed after treatment. Additionally, WES revealed an FGFR2 N549H mutation hypothesized to confer resistance to the FGFR inhibitor INCB054828 in a single tumor sample. This hypothesis was corroborated with in vitro cell-based studies in which cells expressing FGFR2-CLIP1 fusion were sensitive to INCB054828 (IC50 value of 10.16 nM), whereas cells with the addition of the N549H mutation were resistant to INCB054828 (IC50 value of 1527.57 nM). Furthermore, the FGFR2 N549H secondary mutation displayed cross-resistance to other selective FGFR inhibitors, but remained sensitive to the nonselective inhibitor, ponatinib. Rapid research autopsy has the potential to provide unprecedented insights into the clonal evolution of cancer throughout the course of the disease. In this study, we demonstrate the emergence of a drug resistance mutation and characterize the evolution of tumor subclones within a cholangiocarcinoma disease course.
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Affiliation(s)
- Melanie A Krook
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Russell Bonneville
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
- Biomedical Sciences Graduate Program, The Ohio State University, Columbus, Ohio 43210, USA
| | - Hui-Zi Chen
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
- Division of Medical Oncology, Department of Internal Medicine, The Ohio State University, Columbus, Ohio 43210, USA
| | - Julie W Reeser
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Michele R Wing
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Dorrelyn M Martin
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Amy M Smith
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Thuy Dao
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Eric Samorodnitsky
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Anoosha Paruchuri
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Jharna Miya
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Kaitlin R Baker
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Lianbo Yu
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio 43210, USA
| | - Cynthia Timmers
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Kristin Dittmar
- Department of Radiology, The Ohio State University, Columbus, Ohio 43210, USA
| | - Aharon G Freud
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
- Department of Pathology, The Ohio State University, Columbus, Ohio 43210, USA
| | - Patricia Allenby
- Department of Pathology, The Ohio State University, Columbus, Ohio 43210, USA
| | - Sameek Roychowdhury
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
- Division of Medical Oncology, Department of Internal Medicine, The Ohio State University, Columbus, Ohio 43210, USA
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