The mutational landscape of a US Midwestern breast cancer cohort reveals subtype-specific cancer drivers and prognostic markers
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C. Guda | K. Cowan | D. Kelly | M. Desler | J. Eudy | Yuan-De Tan | N. N. Vellichirammal | Peng Xiao | Oleg Shats
[1] Hushan Yang,et al. Whole-exome sequencing identifies somatic mutations and intratumor heterogeneity in inflammatory breast cancer , 2021, npj Breast Cancer.
[2] J. Balko,et al. Genomic evaluation of tumor mutational burden-high (TMB-H) versus TMB-low (TMB-L) metastatic breast cancer to reveal unique mutational features. , 2021 .
[3] Howard H. Yang,et al. CBFB cooperates with p53 to maintain TAp73 expression and suppress breast cancer , 2021, PLoS genetics.
[4] J. Ferlay,et al. Cancer statistics for the year 2020: An overview , 2021, International journal of cancer.
[5] Chun-Yu Liu,et al. Comprehensive molecular profiling of Taiwanese breast cancers revealed potential therapeutic targets: prevalence of actionable mutations among 380 targeted sequencing analyses , 2021, BMC Cancer.
[6] X. Castells,et al. Recommendations from the European Commission Initiative on Breast Cancer for multigene testing to guide the use of adjuvant chemotherapy in patients with early breast cancer, hormone receptor positive, HER-2 negative , 2021, British Journal of Cancer.
[7] Zhongmin Liu,et al. AHNAK2 Promotes Migration, Invasion, and Epithelial-Mesenchymal Transition in Lung Adenocarcinoma Cells via the TGF-β/Smad3 Pathway , 2020, OncoTargets and therapy.
[8] Chun-Yu Liu,et al. Comprehensive molecular profiling of Taiwanese breast cancers revealed potential therapeutic targets: prevalence of actionable mutations among 380 targeted sequencing analyses , 2020, BMC cancer.
[9] Yulei N. Wang,et al. Impact of TP53 mutations in breast cancer: Clinicopathological features and prognosisImpact of TP53 mutations in breast CA , 2020, Thoracic cancer.
[10] Brian D. Bennett,et al. Cancer-specific mutation of GATA3 disrupts the transcriptional regulatory network governed by Estrogen Receptor alpha, FOXA1 and GATA3. , 2020, Nucleic acids research.
[11] Hsi-Yuan Huang,et al. Pathway mutations in breast cancer using whole-exome sequencing. , 2020, Oncology research.
[12] R. Karchin,et al. Integrated Informatics Analysis of Cancer-Related Variants , 2020, JCO clinical cancer informatics.
[13] Hui Zhang,et al. MicroRNA-299-5p inhibits cell metastasis in breast cancer by directly targeting serine/threonine kinase 39 , 2020, Oncology reports.
[14] E. Lander,et al. Identification of cancer driver genes based on nucleotide context , 2019, Nature Genetics.
[15] Anas M. Saad,et al. Causes of death after breast cancer diagnosis: A US population‐based analysis , 2019, Cancer.
[16] J. Heymach,et al. Co-occurring genomic alterations in non-small-cell lung cancer biology and therapy , 2019, Nature Reviews Cancer.
[17] R. Karchin,et al. CHASMplus Reveals the Scope of Somatic Missense Mutations Driving Human Cancers. , 2019, Cell systems.
[18] Hailing Lu,et al. Tumor-associated antigens identified early in mouse mammary tumor development can be effective vaccine targets. , 2019, Vaccine.
[19] Howard H. Yang,et al. The transcription factor CBFB suppresses breast cancer through orchestrating translation and transcription , 2019, Nature Communications.
[20] H. Carter,et al. GPCRs show widespread differential mRNA expression and frequent mutation and copy number variation in solid tumors , 2019, bioRxiv.
[21] H. Harrison,et al. The RUNX Transcriptional Coregulator, CBFβ, Suppresses Migration of ER+ Breast Cancer Cells by Repressing ERα-Mediated Expression of the Migratory Factor TFF1 , 2019, Molecular Cancer Research.
[22] Helen E. Parkinson,et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019 , 2018, Nucleic Acids Res..
[23] Gregory M. Cooper,et al. CADD: predicting the deleteriousness of variants throughout the human genome , 2018, Nucleic Acids Res..
[24] Yassen Assenov,et al. Maftools: efficient and comprehensive analysis of somatic variants in cancer , 2018, Genome research.
[25] Xiu-zhi Guo,et al. Methylation of NBPF1 as a novel marker for the detection of plasma cell-free DNA of breast cancer patients. , 2018, Clinica chimica acta; international journal of clinical chemistry.
[26] Steven J. M. Jones,et al. Oncogenic Signaling Pathways in The Cancer Genome Atlas. , 2018, Cell.
[27] L. Pusztai,et al. An integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes , 2018, British Journal of Cancer.
[28] Qi Zhao,et al. STK39 blockage by RNA interference inhibits the proliferation and induces the apoptosis of renal cell carcinoma , 2018, OncoTargets and therapy.
[29] L. Saal,et al. Tumor PIK3CA Genotype and Prognosis in Early-Stage Breast Cancer: A Pooled Analysis of Individual Patient Data. , 2018, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[30] Ahmet Zehir,et al. Molecular Determinants of Response to Anti-Programmed Cell Death (PD)-1 and Anti-Programmed Death-Ligand 1 (PD-L1) Blockade in Patients With Non-Small-Cell Lung Cancer Profiled With Targeted Next-Generation Sequencing. , 2018, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[31] Accelerating , 2018, Eureka!.
[32] Tom R. Gaunt,et al. CScape: a tool for predicting oncogenic single-point mutations in the cancer genome , 2017, Scientific Reports.
[33] Tom R. Gaunt,et al. CScape: a tool for predicting oncogenic single-point mutations in the cancer genome , 2017, Scientific Reports.
[34] Patrick McGillivray,et al. Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes , 2017, Nature Communications.
[35] P. Stephens,et al. Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers , 2017, Molecular Cancer Therapeutics.
[36] Yun Cao,et al. STK39, overexpressed in osteosarcoma, regulates osteosarcoma cell invasion and proliferation , 2017, Oncology letters.
[37] J. Michael Cherry,et al. Evaluating the clinical validity of gene-disease associations: an evidence-based framework developed by the Clinical Genome Resource , 2017, bioRxiv.
[38] Piero Fariselli,et al. PhD-SNPg: a webserver and lightweight tool for scoring single nucleotide variants , 2017, Nucleic Acids Res..
[39] Valeria Vitelli,et al. Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome , 2017, Breast Cancer Research.
[40] J. Michael Cherry,et al. Evaluating the clinical validity of gene-disease associations: an evidence-based framework developed by the Clinical Genome Resource , 2017, bioRxiv.
[41] Trevor Hastie,et al. REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants. , 2016, American journal of human genetics.
[42] Z. Li,et al. Role of high expression levels of STK39 in the growth, migration and invasion of non-small cell type lung cancer cells , 2016, Oncotarget.
[43] Xiaohua Chen,et al. A novel subtype classification and risk of breast cancer by histone modification profiling , 2016, Breast Cancer Research and Treatment.
[44] David C. Jones,et al. Landscape of somatic mutations in 560 breast cancer whole genome sequences , 2016, Nature.
[45] E. Osinaga,et al. MUC5B silencing reduces chemo-resistance of MCF-7 breast tumor cells and impairs maturation of dendritic cells. , 2016, International journal of oncology.
[46] F. Cunningham,et al. The Ensembl Variant Effect Predictor , 2016, bioRxiv.
[47] Yun Qin,et al. Tumor-Suppressor Gene NBPF1 Inhibits Invasion and PI3K/mTOR Signaling in Cervical Cancer Cells , 2016, Oncology research.
[48] Ricardo Villamarín-Salomón,et al. ClinVar: public archive of interpretations of clinically relevant variants , 2015, Nucleic Acids Res..
[49] David L. Masica,et al. Assessing the Pathogenicity of Insertion and Deletion Variants with the Variant Effect Scoring Tool (VEST‐Indel) , 2015, Human mutation.
[50] H. Gogas,et al. Significance of PIK3CA Mutations in Patients with Early Breast Cancer Treated with Adjuvant Chemotherapy: A Hellenic Cooperative Oncology Group (HeCOG) Study , 2015, PloS one.
[51] O. Hofmann,et al. VarDict: a novel and versatile variant caller for next-generation sequencing in cancer research , 2016, Nucleic acids research.
[52] R. Gibbs,et al. Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies. , 2015, Human molecular genetics.
[53] Xiaohui Xie,et al. DANN: a deep learning approach for annotating the pathogenicity of genetic variants , 2015, Bioinform..
[54] Kevin Y. Yip,et al. FunSeq2: a framework for prioritizing noncoding regulatory variants in cancer , 2014, Genome Biology.
[55] D. Rea,et al. Mutational analysis of PI3K/AKT signaling pathway in tamoxifen exemestane adjuvant multinational pathology study. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[56] Tom R. Gaunt,et al. Ranking non-synonymous single nucleotide polymorphisms based on disease concepts , 2014, Human Genomics.
[57] Richard Leslie,et al. GRASP: analysis of genotype-phenotype results from 1390 genome-wide association studies and corresponding open access database , 2014, Bioinform..
[58] Mauricio O. Carneiro,et al. From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline , 2013, Current protocols in bioinformatics.
[59] Mark J. Ratain,et al. Tumour heterogeneity in the clinic , 2013, Nature.
[60] Steven A. Roberts,et al. An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers , 2013, Nature Genetics.
[61] Steven A. Roberts,et al. Mutational heterogeneity in cancer and the search for new cancer genes , 2014 .
[62] A. Sivachenko,et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples , 2013, Nature Biotechnology.
[63] Bal Sanghera,et al. Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? , 2012, Insights into Imaging.
[64] V. Gouyer,et al. MUC5B Leads to Aggressive Behavior of Breast Cancer MCF7 Cells , 2012, PloS one.
[65] Gabor T. Marth,et al. Haplotype-based variant detection from short-read sequencing , 2012, 1207.3907.
[66] A. Sivachenko,et al. Sequence analysis of mutations and translocations across breast cancer subtypes , 2012, Nature.
[67] M. Shackleton,et al. Physiological Levels of Pik3ca H1047R Mutation in the Mouse Mammary Gland Results in Ductal Hyperplasia and Formation of ERα-Positive Tumors , 2012, PloS one.
[68] F. Markowetz,et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups , 2012, Nature.
[69] L. Pusztai,et al. Gene expression profi ling in breast cancer: classifi cation, prognostication, and prediction , 2011 .
[70] M. DePristo,et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.
[71] D. Hanahan,et al. Hallmarks of Cancer: The Next Generation , 2011, Cell.
[72] Elizabeth Reed,et al. Multicenter Breast Cancer Collaborative Registry , 2011, Cancer informatics.
[73] Charles M. Perou,et al. Deconstructing the molecular portraits of breast cancer , 2010, Molecular oncology.
[74] Jason I. Herschkowitz,et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer , 2010, Breast Cancer Research.
[75] M. DePristo,et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.
[76] H. Hakonarson,et al. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.
[77] Paul Ellis,et al. PIK3CA mutations associated with gene signature of low mTORC1 signaling and better outcomes in estrogen receptor–positive breast cancer , 2010, Proceedings of the National Academy of Sciences.
[78] Richard Durbin,et al. Fast and accurate long-read alignment with Burrows–Wheeler transform , 2010, Bioinform..
[79] Jorge S Reis-Filho,et al. The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade , 2010, The Journal of pathology.
[80] Ken Chen,et al. VarScan: variant detection in massively parallel sequencing of individual and pooled samples , 2009, Bioinform..
[81] Z. Werb,et al. GATA-3 links tumor differentiation and dissemination in a luminal breast cancer model. , 2008, Cancer cell.
[82] D. Hayes. Pharmacogenomic Predictor of Sensitivity to Preoperative Chemotherapy With Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide in Breast Cancer , 2007 .
[83] Marie-Liesse Asselin-Labat,et al. Gata-3 is an essential regulator of mammary-gland morphogenesis and luminal-cell differentiation , 2007, Nature Cell Biology.
[84] J. Bergh,et al. The clinical value of somatic TP53 gene mutations in 1,794 patients with breast cancer. , 2006, Clinical cancer research : an official journal of the American Association for Cancer Research.
[85] Alan Ashworth,et al. Gene expression patterns for doxorubicin (Adriamycin) and cyclophosphamide (Cytoxan) (AC) response and resistance , 2006, Breast Cancer Research and Treatment.
[86] Debashis Ghosh,et al. Identification of GATA3 as a breast cancer prognostic marker by global gene expression meta-analysis. , 2005, Cancer research.
[87] R. Weigel,et al. GATA-3 expression as a predictor of hormone response in breast cancer. , 2005, Journal of the American College of Surgeons.
[88] J. Stec,et al. Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer. , 2004, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[89] E. Osinaga,et al. Detection of bone marrow‐disseminated breast cancer cells using an RT‐PCR assay of MUC5B mRNA , 2003, International journal of cancer.
[90] A. Kassens. Targets , 2019, Intemperate Spirits.
[91] C. Velde,et al. Systematic review of the clinical and economic value of gene expression profiles for invasive early breast cancer available in Europe. , 2018, Cancer treatment reviews.
[92] N. Socci,et al. Accelerating Discovery of Functional Mutant Alleles in Cancer. , 2018, Cancer discovery.
[93] Erwin G. Van Meir,et al. Adhesion GPCRs in Tumorigenesis. , 2016, Handbook of experimental pharmacology.
[94] Sara A. Grimm,et al. GATA3 in Breast Cancer: Tumor Suppressor or Oncogene? , 2015, Gene expression.
[95] Steven A. Roberts,et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes , 2013 .
[96] Vanessa Andries. Functional analysis of the NBPF1 gene in cancer , 2012 .
[97] S. Yona,et al. Adhesion-GPCRs structure to function , 2010 .
[98] S. Yona,et al. Adhesion-GPCRs: structure to function. Preface. , 2010, Advances in experimental medicine and biology.
[99] Michael A. Hollingsworth,et al. Mucins in cancer: protection and control of the cell surface , 2004, Nature Reviews Cancer.
[100] Hilde van der Togt,et al. Publisher's Note , 2003, J. Netw. Comput. Appl..