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Dogan E, Galifi CA, Cecen B, Shukla R, Wood TL, Miri AK. Extracellular matrix regulation of cell spheroid invasion in a 3D bioprinted solid tumor-on-a-chip. Acta Biomater 2024; 186:156-166. [PMID: 39097123 PMCID: PMC11390304 DOI: 10.1016/j.actbio.2024.07.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 07/01/2024] [Accepted: 07/25/2024] [Indexed: 08/05/2024]
Abstract
Tumor organoids and tumors-on-chips can be built by placing patient-derived cells within an engineered extracellular matrix (ECM) for personalized medicine. The engineered ECM influences the tumor response, and understanding the ECM-tumor relationship accelerates translating tumors-on-chips into drug discovery and development. In this work, we tuned the physical and structural characteristics of ECM in a 3D bioprinted soft-tissue sarcoma microtissue. We formed cell spheroids at a controlled size and encapsulated them into our gelatin methacryloyl (GelMA)-based bioink to make perfusable hydrogel-based microfluidic chips. We then demonstrated the scalability and customization flexibility of our hydrogel-based chip via engineering tools. A multiscale physical and structural data analysis suggested a relationship between cell invasion response and bioink characteristics. Tumor cell invasive behavior and focal adhesion properties were observed in response to varying polymer network densities of the GelMA-based bioink. Immunostaining assays and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) helped assess the bioactivity of the microtissue and measure the cell invasion. The RT-qPCR data showed higher expressions of HIF-1α, CD44, and MMP2 genes in a lower polymer density, highlighting the correlation between bioink structural porosity, ECM stiffness, and tumor spheroid response. This work is the first step in modeling STS tumor invasiveness in hydrogel-based microfluidic chips. STATEMENT OF SIGNIFICANCE: We optimized an engineering protocol for making tumor spheroids at a controlled size, embedding spheroids into a gelatin-based matrix, and constructing a perfusable microfluidic device. A higher tumor invasion was observed in a low-stiffness matrix than a high-stiffness matrix. The physical characterizations revealed how the stiffness is controlled by the density of polymer chain networks and porosity. The biological assays revealed how the structural properties of the gelatin matrix and hypoxia in tumor progression impact cell invasion. This work can contribute to personalized medicine by making more effective, tailored cancer models.
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Affiliation(s)
- Elvan Dogan
- Department of Biomedical Engineering, Newark College of Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
| | - Christopher A Galifi
- Department of Pharmacology, Physiology, and Neuroscience and Center for Cell Signaling, Rutgers New Jersey Medical School, Newark, NJ 07103, USA
| | - Berivan Cecen
- Department of Biomedical Engineering, Rowan University, Glassboro, NJ 08028, USA
| | - Roshni Shukla
- Department of Biomedical Engineering, Newark College of Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
| | - Teresa L Wood
- Department of Pharmacology, Physiology, and Neuroscience and Center for Cell Signaling, Rutgers New Jersey Medical School, Newark, NJ 07103, USA
| | - Amir K Miri
- Department of Biomedical Engineering, Newark College of Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA; Department of Mechanical and Industrial Engineering, Newark College of Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
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Jo SY, Lee JD, Won J, Park J, Kweon T, Jo S, Sohn J, Kim SI, Kim S, Park HS. Reversion of pathogenic BRCA1 L1780P mutation confers resistance to PARP and ATM inhibitor in breast cancer. iScience 2024; 27:110469. [PMID: 39156639 PMCID: PMC11326956 DOI: 10.1016/j.isci.2024.110469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 05/12/2024] [Accepted: 07/03/2024] [Indexed: 08/20/2024] Open
Abstract
This study investigates the molecular characteristics and therapeutic implications of the BRCA1 L1780P mutation, a rare variant prevalent among Korean hereditary breast cancer patients. Using patient-derived xenograft (PDX) models and cell lines (PDX-derived cell line) from carriers, sequencing analyses revealed loss of heterozygosity (LOH) at the BRCA1 locus, with one patient losing the wild-type allele and the other mutated allele. This reversion mutation may cf. resistance to homologous recombination deficiency (HRD)-targeting drugs such as PARP inhibitors (PARPi) and ATM inhibitors (ATMi). Although HRDetect and CHORD analyses confirmed a strong association between the L1780P mutation and HRD, effective initially, drug resistance developed in cases with reversion mutations. These findings underscore the complexity of using HRD prediction in personalized treatment strategies for breast cancer patients with BRCA1/2 mutations, as resistance may arise in reversion cases despite high HRD scores.
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Affiliation(s)
- Se-Young Jo
- Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea
- Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, Korea
| | - Jeong Dong Lee
- Avison Biomedical Research Center, Yonsei University College of Medicine, Seoul, Korea
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea
| | - Jeongsoo Won
- Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea
- Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, Korea
| | - Jiho Park
- Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea
| | - Taeyong Kweon
- Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, Korea
- Department of Medical Science, Yonsei University College of Medicine, Seoul, Korea
| | - Seongyeon Jo
- Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, Korea
- Department of Medical Science, Yonsei University College of Medicine, Seoul, Korea
| | - Joohyuk Sohn
- Division of Medical Oncology, Department of Internal Medicine Yonsei University College of Medicine, Seoul, Korea
| | - Seung-Il Kim
- Department of Surgery, Yonsei University College of Medicine, Seoul, Korea
| | - Sangwoo Kim
- Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea
- Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, Korea
- Postech Biotech Center, Pohang University of Science and Technology (POSTECH), Pohang, Korea
| | - Hyung Seok Park
- Department of Surgery, Yonsei University College of Medicine, Seoul, Korea
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3
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Hiatt JB, Doebley AL, Arnold HU, Adil M, Sandborg H, Persse TW, Ko M, Wu F, Quintanal Villalonga A, Santana-Davila R, Eaton K, Dive C, Rudin CM, Thomas A, Houghton AM, Ha G, MacPherson D. Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions. SCIENCE ADVANCES 2024; 10:eadk2082. [PMID: 38598634 PMCID: PMC11006233 DOI: 10.1126/sciadv.adk2082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 02/27/2024] [Indexed: 04/12/2024]
Abstract
We report an approach for cancer phenotyping based on targeted sequencing of cell-free DNA (cfDNA) for small cell lung cancer (SCLC). In SCLC, differential activation of transcription factors (TFs), such as ASCL1, NEUROD1, POU2F3, and REST defines molecular subtypes. We designed a targeted capture panel that identifies chromatin organization signatures at 1535 TF binding sites and 13,240 gene transcription start sites and detects exonic mutations in 842 genes. Sequencing of cfDNA from SCLC patient-derived xenograft models captured TF activity and gene expression and revealed individual highly informative loci. Prediction models of ASCL1 and NEUROD1 activity using informative loci achieved areas under the receiver operating characteristic curve (AUCs) from 0.84 to 0.88 in patients with SCLC. As non-SCLC (NSCLC) often transforms to SCLC following targeted therapy, we applied our framework to distinguish NSCLC from SCLC and achieved an AUC of 0.99. Our approach shows promising utility for SCLC subtyping and transformation monitoring, with potential applicability to diverse tumor types.
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Affiliation(s)
- Joseph B. Hiatt
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Veterans Affairs Puget Sound Healthcare System - Seattle Branch, Seattle, WA, USA
- Division of Medical Oncology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Anna-Lisa Doebley
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, WA, USA
- Medical Scientist Training Program, University of Washington, Seattle, WA, USA
| | - Henry U. Arnold
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Mohamed Adil
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Holly Sandborg
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Thomas W. Persse
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Minjeong Ko
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Feinan Wu
- Genomics and Bioinformatics Shared Resource, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Alvaro Quintanal Villalonga
- Department of Medicine, Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Rafael Santana-Davila
- Division of Medical Oncology, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Keith Eaton
- Division of Medical Oncology, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Caroline Dive
- Cancer Research UK National Biomarker Centre, University of Manchester, Manchester, UK
| | - Charles M. Rudin
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Graduate Program in Pharmacology, Weill Cornell Medical College; New York, NY, USA
| | - Anish Thomas
- Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - A. McGarry Houghton
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Gavin Ha
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - David MacPherson
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
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4
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De Sarkar N, Patton RD, Doebley AL, Hanratty B, Adil M, Kreitzman AJ, Sarthy JF, Ko M, Brahma S, Meers MP, Janssens DH, Ang LS, Coleman IM, Bose A, Dumpit RF, Lucas JM, Nunez TA, Nguyen HM, McClure HM, Pritchard CC, Schweizer MT, Morrissey C, Choudhury AD, Baca SC, Berchuck JE, Freedman ML, Ahmad K, Haffner MC, Montgomery RB, Corey E, Henikoff S, Nelson PS, Ha G. Nucleosome Patterns in Circulating Tumor DNA Reveal Transcriptional Regulation of Advanced Prostate Cancer Phenotypes. Cancer Discov 2023; 13:632-653. [PMID: 36399432 PMCID: PMC9976992 DOI: 10.1158/2159-8290.cd-22-0692] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 10/01/2022] [Accepted: 11/16/2022] [Indexed: 11/19/2022]
Abstract
Advanced prostate cancers comprise distinct phenotypes, but tumor classification remains clinically challenging. Here, we harnessed circulating tumor DNA (ctDNA) to study tumor phenotypes by ascertaining nucleosome positioning patterns associated with transcription regulation. We sequenced plasma ctDNA whole genomes from patient-derived xenografts representing a spectrum of androgen receptor active (ARPC) and neuroendocrine (NEPC) prostate cancers. Nucleosome patterns associated with transcriptional activity were reflected in ctDNA at regions of genes, promoters, histone modifications, transcription factor binding, and accessible chromatin. We identified the activity of key phenotype-defining transcriptional regulators from ctDNA, including AR, ASCL1, HOXB13, HNF4G, and GATA2. To distinguish NEPC and ARPC in patient plasma samples, we developed prediction models that achieved accuracies of 97% for dominant phenotypes and 87% for mixed clinical phenotypes. Although phenotype classification is typically assessed by IHC or transcriptome profiling from tumor biopsies, we demonstrate that ctDNA provides comparable results with diagnostic advantages for precision oncology. SIGNIFICANCE This study provides insights into the dynamics of nucleosome positioning and gene regulation associated with cancer phenotypes that can be ascertained from ctDNA. New methods for classification in phenotype mixtures extend the utility of ctDNA beyond assessments of somatic DNA alterations with important implications for molecular classification and precision oncology. This article is highlighted in the In This Issue feature, p. 517.
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Affiliation(s)
- Navonil De Sarkar
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Pathology and Prostate Cancer Center of Excellence, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Robert D. Patton
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Anna-Lisa Doebley
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington
- Medical Scientist Training Program, University of Washington, Seattle, Washington
| | - Brian Hanratty
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Mohamed Adil
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Adam J. Kreitzman
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Jay F. Sarthy
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Minjeong Ko
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Sandipan Brahma
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Michael P. Meers
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Derek H. Janssens
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Lisa S. Ang
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Ilsa M. Coleman
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Arnab Bose
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Ruth F. Dumpit
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Jared M. Lucas
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Talina A. Nunez
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Holly M. Nguyen
- Department of Urology, University of Washington, Seattle, Washington
| | | | - Colin C. Pritchard
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
| | - Michael T. Schweizer
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Oncology, Department of Medicine, University of Washington, Seattle, Washington
| | - Colm Morrissey
- Department of Urology, University of Washington, Seattle, Washington
| | - Atish D. Choudhury
- Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Sylvan C. Baca
- Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | | | - Matthew L. Freedman
- Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Kami Ahmad
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Michael C. Haffner
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
| | - R. Bruce Montgomery
- Division of Oncology, Department of Medicine, University of Washington, Seattle, Washington
| | - Eva Corey
- Department of Urology, University of Washington, Seattle, Washington
| | - Steven Henikoff
- Division of Basic Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Howard Hughes Medical Institute, Chevy Chase, Maryland
| | - Peter S. Nelson
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Clinical Research, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Urology, University of Washington, Seattle, Washington
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Division of Oncology, Department of Medicine, University of Washington, Seattle, Washington
- Corresponding Authors: Gavin Ha, Fred Hutchinson Cancer Center, 1100 Fairview Avenue North, Seattle, WA 98109. Phone: 206-667-2802; E-mail: ; and Peter S. Nelson, Fred Hutchinson Cancer Center, 1100 Fairview Avenue North, Seattle, WA 98109. Phone: 206-667-3377; E-mail:
| | - Gavin Ha
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
- Division of Human Biology, Fred Hutchinson Cancer Center, Seattle, Washington
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle, Washington
- Corresponding Authors: Gavin Ha, Fred Hutchinson Cancer Center, 1100 Fairview Avenue North, Seattle, WA 98109. Phone: 206-667-2802; E-mail: ; and Peter S. Nelson, Fred Hutchinson Cancer Center, 1100 Fairview Avenue North, Seattle, WA 98109. Phone: 206-667-3377; E-mail:
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5
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Chen GM, Chen CH, Perazzelli J, Grupp SA, Barrett DM, Tan K. Characterization of Leukemic Resistance to CD19-Targeted CAR T-cell Therapy through Deep Genomic Sequencing. Cancer Immunol Res 2023; 11:13-19. [PMID: 36255409 PMCID: PMC9808313 DOI: 10.1158/2326-6066.cir-22-0095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 07/27/2022] [Accepted: 10/12/2022] [Indexed: 01/07/2023]
Abstract
Chimeric antigen receptor (CAR) T-cell therapy targeting CD19 has been a clinical breakthrough for pediatric B-cell acute lymphoblastic leukemia (B-ALL), and loss of the CD19 target antigen on leukemic cells represents a major mechanism of relapse. Previous studies have observed CD19 mutations specific to CD19- relapses, and we sought to clarify and strengthen this relationship using deep whole-exome sequencing in leukemic cells expanded in a patient-derived xenograft. By assessing pre-treatment and relapse cells from 13 patients treated with CAR T-cell therapy, 8 of whom developed CD19- relapse and 5 of whom developed CD19+ relapse, we demonstrate that relapse-specific single-nucleotide variants and small indels with high allele frequency combined with deletions in the CD19 gene in a manner specific to those patients with CD19- relapse. Before CAR T-cell infusion, one patient was found to harbor a pre-existing CD19 deletion in the context of genomic instability, which likely represented the first hit leading to the patient's subsequent CD19- relapse. Across patients, preexisting mutations and genomic instability were not significant predictors of subsequent CD19- relapse across patients, with sample size as a potential limiting factor. Together, our results clarify and strengthen the relationship between genomic events and CD19- relapse, demonstrating this intriguing mechanism of resistance to a targeted cancer immunotherapy.
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Affiliation(s)
- Gregory M. Chen
- Graduate Group in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Chia-Hui Chen
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Jessica Perazzelli
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Stephan A. Grupp
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.,Department of Pediatrics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - David M. Barrett
- Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.,Department of Pediatrics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Kai Tan
- Graduate Group in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, Pennsylvania.,Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.,Department of Pediatrics, University of Pennsylvania, Philadelphia, Pennsylvania.,Corresponding Author: Kai Tan, University of Pennsylvania, 3501 Civic Center Boulevard, Philadelphia, PA 19104. Phone: 267-425-0050; E-mail:
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6
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Kim YS, Park M, Jin S, Jeong GH, Chung YJ, Bang CH. Genomic comparison between an in vitro three-dimensional culture model of melanoma and the original primary tumor. Arch Dermatol Res 2022; 315:1225-1231. [PMID: 36513861 DOI: 10.1007/s00403-022-02502-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/18/2022] [Accepted: 12/01/2022] [Indexed: 12/14/2022]
Abstract
Three-dimensional (3D) melanoma culture is a personalized in vitro model that can be used for high-fidelity pre-clinical testing and validation of novel therapies. However, whether the genomic landscape of 3D cultures faithfully reflects the original primary tumor which remains unknown. The purpose of our study was to compare the genomic landscapes of 3D culture models with those of the original tumors. Patient-derived xenograft (PDX) tumors were established by engrafting fresh melanoma tissue from each patient. Then, a 3D culture model was generated using cryopreserved PDX tumors embedded in pre-gelled porcine skin decellularized extracellular matrix with normal human dermal fibroblasts. Using whole-exome sequencing, the genomic landscapes of 3D cultures, PDX tumors, and the original tumor were compared. We found that 91.4% of single-nucleotide variants in the original tumor were detected in the 3D culture and PDX samples. Putative melanoma driver mutations (BRAF p.V600E, CDKN2A p.R7*, ADAMTS1 p.Q572*) were consistently identified in both the original tumor and 3D culture samples. Genome-wide copy number alteration profiles were almost identical between the original tumor and 3D culture samples, including the driver events of ARID1B loss, BRAF gain, and CCND1 gain. In conclusion, our study revealed that the genomic profiles of the original tumor and our 3D culture model showed high concordance, indicating the reliability of our 3D culture model in reflecting the original characteristics of the tumor.
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Affiliation(s)
- Yoon-Seob Kim
- Precision Medicine Research Center, The Catholic University of Korea, Seoul, Republic of Korea.,IRCGP, The Catholic University of Korea, Seoul, Republic of Korea.,Department of Microbiology, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-Gu, Seoul, 06591, Republic of Korea
| | - Minji Park
- T&R Biofab Co.Ltd., Seongnam-Si, Republic of Korea
| | - Songwan Jin
- Department of Mechanical Engineering, Tech University of Korea, Siheung-Si, Republic of Korea
| | - Ga Hee Jeong
- Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yeun-Jun Chung
- Precision Medicine Research Center, The Catholic University of Korea, Seoul, Republic of Korea. .,IRCGP, The Catholic University of Korea, Seoul, Republic of Korea. .,Department of Microbiology, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-Gu, Seoul, 06591, Republic of Korea. .,Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
| | - Chul Hwan Bang
- Department of Dermatology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-Gu, Seoul, 06591, Republic of Korea.
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7
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Seo J, Kim H, Min KI, Kim C, Kwon Y, Zheng Z, Kim Y, Park HS, Ju YS, Roh MR, Chung KY, Kim J. Weight-bearing activity impairs nuclear membrane and genome integrity via YAP activation in plantar melanoma. Nat Commun 2022; 13:2214. [PMID: 35468978 PMCID: PMC9038926 DOI: 10.1038/s41467-022-29925-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 04/08/2022] [Indexed: 11/26/2022] Open
Abstract
Acral melanoma commonly occurs in areas that are not exposed to much sunlight, such as the sole of the foot. Little is known about risk factors and mutational processes of plantar acral melanoma. Nuclear envelope rupture during interphase contributes to genome instability in cancer. Here, we show that the nuclear and micronuclear membranes of melanoma cells are frequently ruptured by macroscopic mechanical stress on the plantar surface due to weight-bearing activities. The marginal region of plantar melanoma nodules exhibits increased nuclear morphological abnormalities and collagen accumulations, and is more susceptible to mechanical stress than the tumor center. An increase in DNA damage coincides with nuclear membrane rupture in the tumor margin. Nuclear envelope integrity is compromised by the mechanosensitive transcriptional cofactor YAP activated in the tumor margin. Our results suggest a mutagenesis mechanism in melanoma and explain why plantar acral melanoma is frequent at higher mechanical stress points.
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Affiliation(s)
- Jimyung Seo
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
| | - HyunSeok Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
| | - Kyoung Il Min
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
| | - Changgon Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
| | - Yongsoo Kwon
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
| | - Zhenlong Zheng
- Department of Dermatology, Severance Hospital, Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Yusung Kim
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
| | - Hyung-Soon Park
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
| | - Young Seok Ju
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
| | - Mi Ryung Roh
- Department of Dermatology, Gangnam Severance Hospital, Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, Korea.
| | - Kee Yang Chung
- Department of Dermatology, Severance Hospital, Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, Korea.
| | - Joon Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea.
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8
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Humanized 3D scaffold xenotransplantation models for Myelodysplastic Syndromes. Exp Hematol 2021; 107:38-50. [DOI: 10.1016/j.exphem.2021.12.395] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 12/10/2021] [Accepted: 12/18/2021] [Indexed: 11/19/2022]
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9
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Elias R, Tcheuyap VT, Kaushik AK, Singla N, Gao M, Reig Torras O, Christie A, Mulgaonkar A, Woolford L, Stevens C, Kettimuthu KP, Pavia-Jimenez A, Boroughs LK, Joyce A, Dakanali M, Notgrass H, Margulis V, Cadeddu JA, Pedrosa I, Williams NS, Sun X, DeBerardinis RJ, Öz OK, Zhong H, Seshagiri S, Modrusan Z, Cantarel BL, Kapur P, Brugarolas J. A renal cell carcinoma tumorgraft platform to advance precision medicine. Cell Rep 2021; 37:110055. [PMID: 34818533 PMCID: PMC8762721 DOI: 10.1016/j.celrep.2021.110055] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 10/10/2021] [Accepted: 11/03/2021] [Indexed: 12/30/2022] Open
Abstract
Renal cell carcinoma (RCC) encompasses a heterogenous group of tumors, but representative preclinical models are lacking. We previously showed that patient-derived tumorgraft (TG) models recapitulate the biology and treatment responsiveness. Through systematic orthotopic implantation of tumor samples from 926 ethnically diverse individuals into non-obese diabetic (NOD)/severe combined immunodeficiency (SCID) mice, we generate a resource comprising 172 independently derived, stably engrafted TG lines from 148 individuals. TG lines are characterized histologically and genomically (whole-exome [n = 97] and RNA [n = 102] sequencing). The platform features a variety of histological and oncogenotypes, including TCGA clades further corroborated through orthogonal metabolomic analyses. We illustrate how it enables a deeper understanding of RCC biology; enables the development of tissue- and imaging-based molecular probes; and supports advances in drug development.
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Affiliation(s)
- Roy Elias
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Vanina T Tcheuyap
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Akash K Kaushik
- Howard Hughes Medical Institute and Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Nirmish Singla
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Urology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ming Gao
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Oscar Reig Torras
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Alana Christie
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Division of Biostatistics, Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Aditi Mulgaonkar
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Layton Woolford
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Christina Stevens
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Kavitha Priya Kettimuthu
- Department of Biochemistry, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Andrea Pavia-Jimenez
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Lindsey K Boroughs
- Howard Hughes Medical Institute and Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Allison Joyce
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Marianna Dakanali
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Hollis Notgrass
- Department of Pathology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Vitaly Margulis
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Urology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jeffrey A Cadeddu
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Urology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ivan Pedrosa
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Noelle S Williams
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Xiankai Sun
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ralph J DeBerardinis
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Howard Hughes Medical Institute and Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Orhan K Öz
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Hua Zhong
- Department of Pathology, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Somasekar Seshagiri
- Department of Microchemistry, Proteomics, Lipidomics and NGS, Genentech, Inc., South San Francisco, CA, USA
| | - Zora Modrusan
- Department of Microchemistry, Proteomics, Lipidomics and NGS, Genentech, Inc., South San Francisco, CA, USA
| | - Brandi L Cantarel
- Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Payal Kapur
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Urology, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Pathology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Brugarolas
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, TX, USA.
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10
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Cejas P, Xie Y, Font-Tello A, Lim K, Syamala S, Qiu X, Tewari AK, Shah N, Nguyen HM, Patel RA, Brown L, Coleman I, Hackeng WM, Brosens L, Dreijerink KMA, Ellis L, Alaiwi SA, Seo JH, Baca S, Beltran H, Khani F, Pomerantz M, Dall'Agnese A, Crowdis J, Van Allen EM, Bellmunt J, Morrisey C, Nelson PS, DeCaprio J, Farago A, Dyson N, Drapkin B, Liu XS, Freedman M, Haffner MC, Corey E, Brown M, Long HW. Subtype heterogeneity and epigenetic convergence in neuroendocrine prostate cancer. Nat Commun 2021; 12:5775. [PMID: 34599169 PMCID: PMC8486778 DOI: 10.1038/s41467-021-26042-z] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 09/07/2021] [Indexed: 12/30/2022] Open
Abstract
Neuroendocrine carcinomas (NEC) are tumors expressing markers of neuronal differentiation that can arise at different anatomic sites but have strong histological and clinical similarities. Here we report the chromatin landscapes of a range of human NECs and show convergence to the activation of a common epigenetic program. With a particular focus on treatment emergent neuroendocrine prostate cancer (NEPC), we analyze cell lines, patient-derived xenograft (PDX) models and human clinical samples to show the existence of two distinct NEPC subtypes based on the expression of the neuronal transcription factors ASCL1 and NEUROD1. While in cell lines and PDX models these subtypes are mutually exclusive, single-cell analysis of human clinical samples exhibits a more complex tumor structure with subtypes coexisting as separate sub-populations within the same tumor. These tumor sub-populations differ genetically and epigenetically contributing to intra- and inter-tumoral heterogeneity in human metastases. Overall, our results provide a deeper understanding of the shared clinicopathological characteristics shown by NECs. Furthermore, the intratumoral heterogeneity of human NEPCs suggests the requirement of simultaneous targeting of coexisting tumor populations as a therapeutic strategy. Neuroendocrine carcinomas (NECs) arise from different anatomic sites, but have similar histological and clinical features. Here, the authors show that the epigenetic landscape of a range of NECs converges towards a common epigenetic state, while distinct subtypes occur within neuroendocrine prostate cancer contributing to intratumor heterogeneity in clinical samples.
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Affiliation(s)
- Paloma Cejas
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA. .,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA. .,Translational Oncology Laboratory, Hospital La Paz Institute for Health Research (IdiPAZ) and CIBERONC, La Paz University Hospital, Madrid, Spain.
| | - Yingtian Xie
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Alba Font-Tello
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Klothilda Lim
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sudeepa Syamala
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Xintao Qiu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Alok K Tewari
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Neel Shah
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Holly M Nguyen
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Radhika A Patel
- Divisions of Human Biology and Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lisha Brown
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Ilsa Coleman
- Divisions of Human Biology and Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Wenzel M Hackeng
- Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Lodewijk Brosens
- Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | | | - Leigh Ellis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Oncologic Pathology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Sarah Abou Alaiwi
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Ji-Heui Seo
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Sylvan Baca
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Himisha Beltran
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Francesca Khani
- Weill Cornell Medical Center, Department of Pathology and Laboratory Medicine, New York Presbyterian Hospital, New York, NY, USA
| | - Mark Pomerantz
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | | | - Jett Crowdis
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eliezer M Van Allen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joaquim Bellmunt
- Beth Israel Deaconess Medical Center and PSMAR-IMIM Lab. Harvard Medical School, Boston, Massachusetts, USA
| | - Colm Morrisey
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Peter S Nelson
- Divisions of Human Biology and Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - James DeCaprio
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Anna Farago
- Massachusetts General Hospital Cancer Center, Boston, MA, USA
| | - Nicholas Dyson
- Massachusetts General Hospital Cancer Center, Boston, MA, USA
| | - Benjamin Drapkin
- Nancy B. and Jake L. Hamon Center for Therapeutic Oncology Research, Dallas, TX, USA.,Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.,Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - X Shirley Liu
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA.,Department of Data Science, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Matthew Freedman
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Michael C Haffner
- Divisions of Human Biology and Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.,Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.,Department of Pathology, University of Washington, Seattle, WA, USA
| | - Eva Corey
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Myles Brown
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA. .,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA.
| | - Henry W Long
- Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA. .,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA.
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11
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Zhao Y, Li MC, Konaté MM, Chen L, Das B, Karlovich C, Williams PM, Evrard YA, Doroshow JH, McShane LM. TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived Models Repository. J Transl Med 2021; 19:269. [PMID: 34158060 PMCID: PMC8220791 DOI: 10.1186/s12967-021-02936-w] [Citation(s) in RCA: 152] [Impact Index Per Article: 50.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 06/10/2021] [Indexed: 12/18/2022] Open
Abstract
Background In order to correctly decode phenotypic information from RNA-sequencing (RNA-seq) data, careful selection of the RNA-seq quantification measure is critical for inter-sample comparisons and for downstream analyses, such as differential gene expression between two or more conditions. Several methods have been proposed and continue to be used. However, a consensus has not been reached regarding the best gene expression quantification method for RNA-seq data analysis. Methods In the present study, we used replicate samples from each of 20 patient-derived xenograft (PDX) models spanning 15 tumor types, for a total of 61 human tumor xenograft samples available through the NCI patient-derived model repository (PDMR). We compared the reproducibility across replicate samples based on TPM (transcripts per million), FPKM (fragments per kilobase of transcript per million fragments mapped), and normalized counts using coefficient of variation, intraclass correlation coefficient, and cluster analysis. Results Our results revealed that hierarchical clustering on normalized count data tended to group replicate samples from the same PDX model together more accurately than TPM and FPKM data. Furthermore, normalized count data were observed to have the lowest median coefficient of variation (CV), and highest intraclass correlation (ICC) values across all replicate samples from the same model and for the same gene across all PDX models compared to TPM and FPKM data. Conclusion We provided compelling evidence for a preferred quantification measure to conduct downstream analyses of PDX RNA-seq data. To our knowledge, this is the first comparative study of RNA-seq data quantification measures conducted on PDX models, which are known to be inherently more variable than cell line models. Our findings are consistent with what others have shown for human tumors and cell lines and add further support to the thesis that normalized counts are the best choice for the analysis of RNA-seq data across samples. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-021-02936-w.
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Affiliation(s)
- Yingdong Zhao
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Ming-Chung Li
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Mariam M Konaté
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Li Chen
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Biswajit Das
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Chris Karlovich
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - P Mickey Williams
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Yvonne A Evrard
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - James H Doroshow
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA.
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12
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Abstract
Motivation With an increasing number of patient-derived xenograft (PDX) models being created and subsequently sequenced to study tumor heterogeneity and to guide therapy decisions, there is a similarly increasing need for methods to separate reads originating from the graft (human) tumor and reads originating from the host species’ (mouse) surrounding tissue. Two kinds of methods are in use: On the one hand, alignment-based tools require that reads are mapped and aligned (by an external mapper/aligner) to the host and graft genomes separately first; the tool itself then processes the resulting alignments and quality metrics (typically BAM files) to assign each read or read pair. On the other hand, alignment-free tools work directly on the raw read data (typically FASTQ files). Recent studies compare different approaches and tools, with varying results. Results We show that alignment-free methods for xenograft sorting are superior concerning CPU time usage and equivalent in accuracy. We improve upon the state of the art sorting by presenting a fast lightweight approach based on three-way bucketed quotiented Cuckoo hashing. Our hash table requires memory comparable to an FM index typically used for read alignment and less than other alignment-free approaches. It allows extremely fast lookups and uses less CPU time than other alignment-free methods and alignment-based methods at similar accuracy. Several engineering steps (e.g., shortcuts for unsuccessful lookups, software prefetching) improve the performance even further. Availability Our software xengsort is available under the MIT license at http://gitlab.com/genomeinformatics/xengsort. It is written in numba-compiled Python and comes with sample Snakemake workflows for hash table construction and dataset processing.
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