Literature DB >> 30401717

Molecular Correlates of Metastasis by Systematic Pan-Cancer Analysis Across The Cancer Genome Atlas.

Fengju Chen1, Yiqun Zhang1, Sooryanarayana Varambally2,3, Chad J Creighton4,5,6,7.   

Abstract

Tumor metastasis is a major contributor to mortality of cancer patients, but the process remains poorly understood. Molecular comparisons between primary tumors and metastases can provide insights into the pathways and processes involved. Here, we systematically analyzed and cataloged molecular correlates of metastasis using The Cancer Genome Atlas (TCGA) datasets across 11 different cancer types, these data involving 4,473 primary tumor samples and 395 tumor metastasis samples (including 369 from melanoma). For each cancer type, widespread differences in gene transcription between primary and metastasis samples were observed. For several cancer types, metastasis-associated genes from TCGA comparisons were found to overlap extensively with external results from independent profiling datasets of metastatic tumors. Although some differential expression patterns associated with metastasis were found to be shared across multiple cancer types, by and large each cancer type showed a metastasis signature that was distinctive from those of the other cancer types. Functional categories of genes enriched in multiple cancer type-specific metastatic overexpression signatures included cellular response to stress, DNA repair, oxidation-reduction process, protein deubiquitination, and receptor activity. The TCGA-derived prostate cancer metastasis signature in particular could define a subset of aggressive primary prostate cancer. Transglutaminase 2 protein and mRNA were both elevated in metastases from breast and melanoma cancers. Alterations in miRNAs and in DNA methylation were also identified. IMPLICATIONS: Our findings suggest that there are different molecular pathways to metastasis involved in different cancers. Our catalog of alterations provides a resource for future studies investigating the role of specific genes in metastasis. ©2018 American Association for Cancer Research.

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Year:  2018        PMID: 30401717      PMCID: PMC6359982          DOI: 10.1158/1541-7786.MCR-18-0601

Source DB:  PubMed          Journal:  Mol Cancer Res        ISSN: 1541-7786            Impact factor:   5.852


  44 in total

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3.  Pan-Cancer Molecular Classes Transcending Tumor Lineage Across 32 Cancer Types, Multiple Data Platforms, and over 10,000 Cases.

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4.  A nineteen gene-based risk score classifier predicts prognosis of colorectal cancer patients.

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6.  miRTarBase: a database curates experimentally validated microRNA-target interactions.

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8.  Molecular stratification of metastatic melanoma using gene expression profiling: Prediction of survival outcome and benefit from molecular targeted therapy.

Authors:  Helena Cirenajwis; Henrik Ekedahl; Martin Lauss; Katja Harbst; Ana Carneiro; Jens Enoksson; Frida Rosengren; Linda Werner-Hartman; Therese Törngren; Anders Kvist; Erik Fredlund; Pär-Ola Bendahl; Karin Jirström; Lotta Lundgren; Jillian Howlin; Åke Borg; Sofia K Gruvberger-Saal; Lao H Saal; Kari Nielsen; Markus Ringnér; Hensin Tsao; Håkan Olsson; Christian Ingvar; Johan Staaf; Göran Jönsson
Journal:  Oncotarget       Date:  2015-05-20

9.  Expression signatures of metastatic capacity in a genetic mouse model of lung adenocarcinoma.

Authors:  Don L Gibbons; Wei Lin; Chad J Creighton; Shuling Zheng; Dror Berel; Yanan Yang; Maria Gabriela Raso; Diane D Liu; Ignacio I Wistuba; Guillermina Lozano; Jonathan M Kurie
Journal:  PLoS One       Date:  2009-04-30       Impact factor: 3.240

10.  Systematic pan-cancer analysis of tumour purity.

Authors:  Dvir Aran; Marina Sirota; Atul J Butte
Journal:  Nat Commun       Date:  2015-12-04       Impact factor: 14.919

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  11 in total

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2.  A cross-cancer metastasis signature in the microRNA-mRNA axis of paired tissue samples.

Authors:  Samuel C Lee; Thomas P Quinn; Alistair Quinn; Thin Nguyen; Svetha Venkatesh
Journal:  Mol Biol Rep       Date:  2019-08-13       Impact factor: 2.316

3.  Mutational concordance between primary and metastatic melanoma: a next-generation sequencing approach.

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Review 4.  Immune Microenvironment of Brain Metastases-Are Microglia and Other Brain Macrophages Little Helpers?

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5.  The Homeobox gene, HOXB13, Regulates a Mitotic Protein-Kinase Interaction Network in Metastatic Prostate Cancers.

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6.  Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis.

Authors:  Zhiguo Zhu; Yaoan Wen; Chunxiang Xuan; Qingping Chen; Qian Xiang; Jiamin Wang; Yangzhou Liu; Lianmin Luo; Shankun Zhao; Yihan Deng; Zhigang Zhao
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7.  Advancing the Role of Gamma-Tocotrienol as Proteasomes Inhibitor: A Quantitative Proteomic Analysis of MDA-MB-231 Human Breast Cancer Cells.

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Review 8.  Treatment of Brain Metastases of Non-Small Cell Lung Carcinoma.

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Review 9.  Targeting neddylation E2s: a novel therapeutic strategy in cancer.

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10.  Evaluation of Somatic Mutations in Solid Metastatic Pan-Cancer Patients.

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Journal:  Cancers (Basel)       Date:  2021-06-03       Impact factor: 6.639

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