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Pan-cancer analysis of heterogeneity of tumor mutational burden and genomic mutation under treatment pressure.
Huang, R J; Huang, Y S; An, N; Hu, J J; Wu, C Y; Chen, Y X; Chen, J Y; Zhao, Q; Xu, R H; Yuan, S Q; Wang, F.
Afiliação
  • Huang RJ; Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou.
  • Huang YS; Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou.
  • An N; Department of Gastric Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou.
  • Hu JJ; Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou.
  • Wu CY; Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou.
  • Chen YX; Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou.
  • Chen JY; Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou.
  • Zhao Q; Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou; Bioinformatic Platform, Sun Yat-sen University Cancer Center, State Key Laboratory of On
  • Xu RH; Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou; Research Unit of Precision Diagnosis and Treatment for Gastrointestinal Cancer, Chinese
  • Yuan SQ; Department of Gastric Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou. Electronic address: yuanshq@sysucc.org.cn.
  • Wang F; Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University, Guangzhou; Research Unit of Precision Diagnosis and Treatment for Gastrointestinal Cancer, Chinese
ESMO Open ; 9(7): 103494, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38981309
ABSTRACT

BACKGROUND:

High tumor mutational burden (TMB) is one of the widely researched predictive biomarkers of immune checkpoint inhibitors and has been shown to be closely related with response to immunotherapy in multiple cancer types. However, for patients who have failed conventional therapy and are about to undergo immunotherapy, there is no consensus recommendation on the timing of tumor sampling for TMB analysis, and the effects of different therapies on TMB have not been clarified. This retrospective observational study aimed to investigate the heterogeneity of TMB and genomic mutation under the treatment pressure. PATIENTS AND

METHODS:

We retrospectively collected the available genomic and therapeutic information from 8051 samples across 15 tumor types (>50 samples/tumor) found in 30 published studies and investigated the distribution and heterogeneity of TMB under treatment across diverse cohorts.

RESULTS:

This integrated analysis has shown anticancer treatments increased TMB. Significant effects of treatment on TMB were more frequently observed in tumor types with lower treatment-naïve TMB, including breast, prostate, and pediatric cancers. For different cancer therapies, chemotherapy was prone to be correlated with an increased TMB in most cancer types. Meanwhile, the fraction of the TMB-high category of breast, prostate, and bladder cancers and glioma increased significantly after chemotherapy. Several actionable genes including ERS1 and NF1 in breast cancer, as well as some prognostic markers including TERT in bladder cancer and IDH1 in glioma, were significantly changed in post-chemotherapy tumors compared to treatment-naïve tumors.

CONCLUSION:

Our study reveals the heterogeneity of TMB under treatment across diverse cancer types and provides evidences that chemotherapy was associated with increases in TMB as well as the fraction of TMB-high category, suggesting that resampling tumor tissues for calculating post-chemotherapy TMB could be a better option for predicting the response to immunotherapy, especially for tumors with initially low TMB.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores Tumorais / Mutação / Neoplasias Limite: Female / Humans Idioma: En Revista: ESMO Open Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biomarcadores Tumorais / Mutação / Neoplasias Limite: Female / Humans Idioma: En Revista: ESMO Open Ano de publicação: 2024 Tipo de documento: Article
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