Literature DB >> 32611582

The Association of MUC16 Mutation with Tumor Mutation Burden and Its Prognostic Implications in Cutaneous Melanoma.

Xuefeng Wang1, Xiaoqing Yu2, Michael Krauthammer3, Willy Hugo4, Chunzhe Duan5, Peter A Kanetsky5, Jamie K Teer2, Zachary J Thompson2, Denise Kalos2, Kenneth Y Tsai6, Keiran S M Smalley7, Vernon K Sondak8, Y Ann Chen1, Jose R Conejo-Garcia9.   

Abstract

BACKGROUND: MUC16 is a mucin marker that is frequently mutated in melanoma, but whether MUC16 mutations could be useful as a surrogate biomarker for tumor mutation burden (TMB) remains unclear.
METHODS: This study rigorously evaluates the MUC16 mutation as a clinical biomarker in cutaneous melanoma by utilizing genomic and clinical data from patient samples from The Cancer Genome Atlas (TCGA) and two independent validation cohorts. We further extended the analysis to studies with patients treated with immunotherapies.
RESULTS: Analysis results showed that samples with MUC16 mutations had a higher TMB than the samples of wild-type, with strong statistical significance (P < 0.001) in all melanoma cohorts tested. Associations between MUC16 mutations and TMB remained statistically significant after adjusting for potential confounding factors in the TCGA cohort [OR, 9.28 (95% confidence interval (CI), 5.18-17.39); P < 0.001], Moffitt cohort [OR, 31.95 (95% CI, 8.71-163.90); P < 0.001], and Yale cohort [OR, 8.09 (95% CI, 3.12-23.79); P < 0.01]. MUC16 mutations were also found to be associated with overall survival in the TCGA [HR, 0.62; (95% CI, 0.45-0.85); P < 0.01] and Moffitt cohorts [HR, 0.49 (95% CI, 0.28-0.87); P = 0.014]. Strikingly, MUC16 is the only top frequently mutated gene for which prognostic significance was observed. MUC16 mutations were also found valuable in predicting anti-CTLA-4 and anti-PD-1 therapy responses.
CONCLUSIONS: MUC16 mutation appears to be a useful predictive marker of global TMB and patient survival in melanoma. IMPACT: This is, to the best of our knowledge, the first systematic evaluation of MUC16 mutation as a clinical biomarker and a predictive biomarker for immunotherapy in melanoma. ©2020 American Association for Cancer Research.

Entities:  

Mesh:

Substances:

Year:  2020        PMID: 32611582      PMCID: PMC7483810          DOI: 10.1158/1055-9965.EPI-20-0307

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  19 in total

1.  VarSifter: visualizing and analyzing exome-scale sequence variation data on a desktop computer.

Authors:  Jamie K Teer; Eric D Green; James C Mullikin; Leslie G Biesecker
Journal:  Bioinformatics       Date:  2011-12-30       Impact factor: 6.937

2.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

Authors:  Aaron McKenna; Matthew Hanna; Eric Banks; Andrey Sivachenko; Kristian Cibulskis; Andrew Kernytsky; Kiran Garimella; David Altshuler; Stacey Gabriel; Mark Daly; Mark A DePristo
Journal:  Genome Res       Date:  2010-07-19       Impact factor: 9.043

3.  Genetic basis for clinical response to CTLA-4 blockade in melanoma.

Authors:  Alexandra Snyder; Vladimir Makarov; Taha Merghoub; Jianda Yuan; Jedd D Wolchok; Timothy A Chan; Jesse M Zaretsky; Alexis Desrichard; Logan A Walsh; Michael A Postow; Phillip Wong; Teresa S Ho; Travis J Hollmann; Cameron Bruggeman; Kasthuri Kannan; Yanyun Li; Ceyhan Elipenahli; Cailian Liu; Christopher T Harbison; Lisu Wang; Antoni Ribas
Journal:  N Engl J Med       Date:  2014-11-19       Impact factor: 91.245

4.  NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data.

Authors:  Vanessa Jurtz; Sinu Paul; Massimo Andreatta; Paolo Marcatili; Bjoern Peters; Morten Nielsen
Journal:  J Immunol       Date:  2017-10-04       Impact factor: 5.422

5.  Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab.

Authors:  Nadeem Riaz; Jonathan J Havel; Vladimir Makarov; Alexis Desrichard; Walter J Urba; Jennifer S Sims; F Stephen Hodi; Salvador Martín-Algarra; Rajarsi Mandal; William H Sharfman; Shailender Bhatia; Wen-Jen Hwu; Thomas F Gajewski; Craig L Slingluff; Diego Chowell; Sviatoslav M Kendall; Han Chang; Rachna Shah; Fengshen Kuo; Luc G T Morris; John-William Sidhom; Jonathan P Schneck; Christine E Horak; Nils Weinhold; Timothy A Chan
Journal:  Cell       Date:  2017-10-12       Impact factor: 41.582

6.  Genomic correlates of response to CTLA-4 blockade in metastatic melanoma.

Authors:  Eliezer M Van Allen; Diana Miao; Bastian Schilling; Sachet A Shukla; Christian Blank; Lisa Zimmer; Antje Sucker; Uwe Hillen; Marnix H Geukes Foppen; Simone M Goldinger; Jochen Utikal; Jessica C Hassel; Benjamin Weide; Katharina C Kaehler; Carmen Loquai; Peter Mohr; Ralf Gutzmer; Reinhard Dummer; Stacey Gabriel; Catherine J Wu; Dirk Schadendorf; Levi A Garraway
Journal:  Science       Date:  2015-09-10       Impact factor: 47.728

7.  Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma.

Authors:  Willy Hugo; Jesse M Zaretsky; Lu Sun; Chunying Song; Blanca Homet Moreno; Siwen Hu-Lieskovan; Beata Berent-Maoz; Jia Pang; Bartosz Chmielowski; Grace Cherry; Elizabeth Seja; Shirley Lomeli; Xiangju Kong; Mark C Kelley; Jeffrey A Sosman; Douglas B Johnson; Antoni Ribas; Roger S Lo
Journal:  Cell       Date:  2016-03-17       Impact factor: 41.582

Review 8.  Understanding the Unique Attributes of MUC16 (CA125): Potential Implications in Targeted Therapy.

Authors:  Srustidhar Das; Surinder K Batra
Journal:  Cancer Res       Date:  2015-11-02       Impact factor: 12.701

9.  Multiomics Prediction of Response Rates to Therapies to Inhibit Programmed Cell Death 1 and Programmed Cell Death 1 Ligand 1.

Authors:  Joo Sang Lee; Eytan Ruppin
Journal:  JAMA Oncol       Date:  2019-11-01       Impact factor: 31.777

10.  Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden.

Authors:  Zachary R Chalmers; Caitlin F Connelly; David Fabrizio; Laurie Gay; Siraj M Ali; Riley Ennis; Alexa Schrock; Brittany Campbell; Adam Shlien; Juliann Chmielecki; Franklin Huang; Yuting He; James Sun; Uri Tabori; Mark Kennedy; Daniel S Lieber; Steven Roels; Jared White; Geoffrey A Otto; Jeffrey S Ross; Levi Garraway; Vincent A Miller; Phillip J Stephens; Garrett M Frampton
Journal:  Genome Med       Date:  2017-04-19       Impact factor: 11.117

View more
  4 in total

1.  Single-Cell Characterization of the Immune Microenvironment of Melanoma Brain and Leptomeningeal Metastases.

Authors:  Inna Smalley; Zhihua Chen; Manali Phadke; Jiannong Li; Xiaoqing Yu; Clayton Wyatt; Brittany Evernden; Jane L Messina; Amod Sarnaik; Vernon K Sondak; Chaomei Zhang; Vincent Law; Nam Tran; Arnold Etame; Robert J B Macaulay; Zeynep Eroglu; Peter A Forsyth; Paulo C Rodriguez; Y Ann Chen; Keiran S M Smalley
Journal:  Clin Cancer Res       Date:  2021-05-25       Impact factor: 12.531

2.  Tumor Molecular Features Predict Endometrial Cancer Patients' Survival After Open or Minimally Invasive Surgeries.

Authors:  Yibo Dai; Jingyuan Wang; Luyang Zhao; Zhiqi Wang; Jianliu Wang
Journal:  Front Oncol       Date:  2021-02-26       Impact factor: 6.244

3.  Association of novel MUC16, MAP3K15 and ABCA1 mutation with giant congenital melanocytic nevus.

Authors:  Renpeng Zhou; Qirui Wang; Jialin Hou; Danru Wang; Yimin Liang
Journal:  Hereditas       Date:  2022-09-09       Impact factor: 2.595

4.  LRP1B mutation: a novel independent prognostic factor and a predictive tumor mutation burden in hepatocellular carcinoma.

Authors:  Fahui Liu; Wanyun Hou; Jiadong Liang; Lilan Zhu; Chunying Luo
Journal:  J Cancer       Date:  2021-05-13       Impact factor: 4.207

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.