A biomarker-driven strategy to guide the use of radiotherapy in non-small cell lung cancer

指导非小细胞肺癌放疗使用的生物标志物驱动策略

基本信息

  • 批准号:
    10518064
  • 负责人:
  • 金额:
    $ 35.87万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-06-01 至 2025-05-31
  • 项目状态:
    未结题

项目摘要

ABSTRACT There is an urgent need to nominate biomarkers that are likely to predict the efficacy of radiotherapy and accelerate their clinical translation. Efforts thus far have been limited in large part because the genetic features regulating tumor cell survival and their frequency across and within individual cancer types had not been studied on a large-scale. Our group completed the largest profiling effort of survival after radiation in cancer cell lines, comprising a diverse collection of 533 genetically annotated tumor cell lines from 26 cancer types. To complement this work, we recently initiated the systematic profiling of >1000 genetic variants that could potentially contribute to the resistance of cancer cells to radiation. We combined results from our profiling efforts to identify features that predict the resistance of lung cancer cells to radiation. The objective in this investigation is to advance the clinical translation of two of the most important regulators of radiation resistance in lung cancer, Nrf2 and Braf. The Nrf2 pathway is genetically altered in ~28% of patients with non-small cell lung cancer (NSCLC) and cells with mutations in NFE2L2 or KEAP1 are the most highly correlated with resistance to radiation. To identify genetic dependencies of Nrf2-active tumors, we used computational and experimental approaches to demonstrate the frequent co-occurrence between Nrf2 and phosphoinositide 3-kinase (PI3K) alteration in NSCLCs. Using genetic and chemical means we show that antagonizing the catalytic subunit of PI3K, p110 (encoded by PIK3CA), decreases Nrf2 activity and reverses radiation resistance driven by this pathway. These results provide the rationale to advance a radiosensitization strategy for patients with Nrf2-active NSCLC by targeting PI3K. Our profiling efforts also demonstrate a critical role for BRAF, which is genetically altered in ~7% of patients with NSCLC, in the resistance of lung cancer cells to radiation. We show, for the first time, that BRAF kinase domain mutations confer resistance to radiation in lung cancers and that they, unlike Nrf2 pathway alterations, are almost invariably a minor component of the tumor (i.e. they are subclonal). We use mathematical and experimental models to show that clonal architecture has significant implications for the likelihood of response to targeted therapies and radiation. Together, these results provide a compelling rationale to examine the role of Nrf2 and Braf alterations in predicting outcomes after radiotherapy and advance a genomically-guided radiosensitization strategy for patients with these tumors. If these hypotheses are correct, our results will demonstrate that radiotherapeutic sensitizers can be selected based on both the identity and type (clonal v. subclonal) of genetic alterations identified in a patient's cancer, prompting an evolution in the use of radiation from a generic approach to one that is guided by the genetic composition of individual tumors.
摘要

项目成果

期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Image-Based Deep Neural Network for Individualizing Radiotherapy Dose Is Transportable Across Health Systems.
  • DOI:
    10.1200/cci.22.00100
  • 发表时间:
    2023-01
  • 期刊:
  • 影响因子:
    4.2
  • 作者:
    Randall, James;Teo, Troy;Lou, Bin;Shah, Jainil;Patel, Jyoti;Kamen, Ali;Abazeed, Mohamed E.
  • 通讯作者:
    Abazeed, Mohamed E.
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Mohamed E. Abazeed其他文献

The Society of Thoracic Surgeons Expert Consensus on the Multidisciplinary Management and Resectability of Locally Advanced Non-small Cell Lung Cancer
美国胸外科医师协会关于局部晚期非小细胞肺癌多学科管理与可切除性的专家共识
  • DOI:
    10.1016/j.athoracsur.2024.09.041
  • 发表时间:
    2025-01-01
  • 期刊:
  • 影响因子:
    3.900
  • 作者:
    Samuel S. Kim;David T. Cooke;Biniam Kidane;Luis F. Tapias;John F. Lazar;Jeremiah W. Awori Hayanga;Jyoti D. Patel;Joel W. Neal;Mohamed E. Abazeed;Henning Willers;Joseph B. Shrager
  • 通讯作者:
    Joseph B. Shrager
PP01.132 Auto-Segmentation of Lung Tumors Using Deep Learning Engines
PP01.132 使用深度学习引擎对肺部肿瘤的自动分割
  • DOI:
    10.1016/j.jtho.2024.05.355
  • 发表时间:
    2024-07-01
  • 期刊:
  • 影响因子:
    20.800
  • 作者:
    Yaqi Miao;Sagnik Sarkar;P Troy Teo;Mohamed E. Abazeed
  • 通讯作者:
    Mohamed E. Abazeed
Deep learning for automated, motion-resolved tumor segmentation in radiotherapy
用于放射治疗中自动、运动解析肿瘤分割的深度学习
  • DOI:
    10.1038/s41698-025-00970-1
  • 发表时间:
    2025-06-30
  • 期刊:
  • 影响因子:
    8.000
  • 作者:
    Sagnik Sarkar;P. Troy Teo;Mohamed E. Abazeed
  • 通讯作者:
    Mohamed E. Abazeed
A deep learning model for preoperative risk stratification of pancreatic ductal adenocarcinoma based on genomic predictors of liver metastasis
基于肝转移基因组预测因子的胰腺导管腺癌术前风险分层深度学习模型
  • DOI:
    10.1016/j.ejca.2025.115608
  • 发表时间:
    2025-08-26
  • 期刊:
  • 影响因子:
    7.100
  • 作者:
    Shuhua Zheng;Yirong Liu;P. Troy Teo;Yilin Wu;Jianzhong Zhang;Mohamed E. Abazeed;John P. Hayes
  • 通讯作者:
    John P. Hayes

Mohamed E. Abazeed的其他文献

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{{ truncateString('Mohamed E. Abazeed', 18)}}的其他基金

Cellular plasticity gives rise to phenotypic equilibrium in small cell lung carcinoma
细胞可塑性导致小细胞肺癌的表型平衡
  • 批准号:
    10525950
  • 财政年份:
    2022
  • 资助金额:
    $ 35.87万
  • 项目类别:
A biomarker-driven strategy to guide the use of radiotherapy in non-small cell lung cancer
指导非小细胞肺癌放疗使用的生物标志物驱动策略
  • 批准号:
    10409631
  • 财政年份:
    2018
  • 资助金额:
    $ 35.87万
  • 项目类别:
A biomarker-driven strategy to guide the use of radiotherapy in non-small cell lung cancer
指导非小细胞肺癌放疗使用的生物标志物驱动策略
  • 批准号:
    9928028
  • 财政年份:
    2018
  • 资助金额:
    $ 35.87万
  • 项目类别:
A biomarker-driven strategy to guide the use of radiotherapy in non-small cell lung cancer
指导非小细胞肺癌放疗使用的生物标志物驱动策略
  • 批准号:
    10089004
  • 财政年份:
    2018
  • 资助金额:
    $ 35.87万
  • 项目类别:

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