Molecular characterization of clinical responses to PD‐1/PD‐L1 inhibitors in non‐small cell lung cancer: Predictive value of multidimensional immunomarker detection for the efficacy of PD‐1 inhibitors in Chinese patients. Issue 5 (23rd April 2019)
- Record Type:
- Journal Article
- Title:
- Molecular characterization of clinical responses to PD‐1/PD‐L1 inhibitors in non‐small cell lung cancer: Predictive value of multidimensional immunomarker detection for the efficacy of PD‐1 inhibitors in Chinese patients. Issue 5 (23rd April 2019)
- Main Title:
- Molecular characterization of clinical responses to PD‐1/PD‐L1 inhibitors in non‐small cell lung cancer: Predictive value of multidimensional immunomarker detection for the efficacy of PD‐1 inhibitors in Chinese patients
- Authors:
- Song, Peng
Cui, Xiaoxia
Bai, Li
Zhou, Xiangdong
Zhu, Xiaoli
Zhang, Jian
Jin, Faguang
Zhao, Jianping
Zhou, Chengzhi
Zhou, Yanbin
Zhang, Xiaoju
Wang, Kai
Wang, Qi
Yu, Yao
Zhang, Xiaoyu
Bai, Chunxue
Zhang, Li - Abstract:
- Abstract : According to multiple studies, the objective response rate of PD‐1/PD‐L1 inhibitors in the second‐line treatment of unscreened non‐small cell lung cancer (NSCLC) is only approximately 20%. Predictive biomarkers of treatment efficacies are still under investigation. In selected NSCLC patients with PD‐L1 expression ≥ 50%, the response rate of pembrolizumab in first‐line treatment can reach 44.8%. Moreover, patients with a higher tumor mutation burden (TMB) tend to achieve a better response with nivolumab. Besides PD‐L1 expression and TMB, taking all these indicators into consideration would hypothetically maximize the clinical response in a specific subgroup of patients. Our study aims to accumulate large and complete samples and clinical data to verify the biomarkers and their cutoff values related to the efficacy of PD‐1/PD‐L1 inhibitors in Chinese NSCLC patients, and to construct a comprehensive predictive model by combining multi‐omics data with contemporary machine learning techniques. NSCLC patients administered treatment of anti‐PD‐1/PD‐L1 antibodies or a combination with other drugs have been enrolled. The estimated enrollment is 250 participants. A sophisticated predictive model of immunotherapy response in the Chinese population has not yet been developed. It is clinically and practically imperative to comprehensively evaluate the possible indicators of Chinese NSCLC patients through multiple test platforms, such as next generation sequencing, PCR, orAbstract : According to multiple studies, the objective response rate of PD‐1/PD‐L1 inhibitors in the second‐line treatment of unscreened non‐small cell lung cancer (NSCLC) is only approximately 20%. Predictive biomarkers of treatment efficacies are still under investigation. In selected NSCLC patients with PD‐L1 expression ≥ 50%, the response rate of pembrolizumab in first‐line treatment can reach 44.8%. Moreover, patients with a higher tumor mutation burden (TMB) tend to achieve a better response with nivolumab. Besides PD‐L1 expression and TMB, taking all these indicators into consideration would hypothetically maximize the clinical response in a specific subgroup of patients. Our study aims to accumulate large and complete samples and clinical data to verify the biomarkers and their cutoff values related to the efficacy of PD‐1/PD‐L1 inhibitors in Chinese NSCLC patients, and to construct a comprehensive predictive model by combining multi‐omics data with contemporary machine learning techniques. NSCLC patients administered treatment of anti‐PD‐1/PD‐L1 antibodies or a combination with other drugs have been enrolled. The estimated enrollment is 250 participants. A sophisticated predictive model of immunotherapy response in the Chinese population has not yet been developed. It is clinically and practically imperative to comprehensively evaluate the possible indicators of Chinese NSCLC patients through multiple test platforms, such as next generation sequencing, PCR, or immunohistochemistry. This study is registered in the Chinese Clinical Trial Registry (ChiCTR1900021395). … (more)
- Is Part Of:
- Thoracic cancer. Volume 10:Issue 5(2019)
- Journal:
- Thoracic cancer
- Issue:
- Volume 10:Issue 5(2019)
- Issue Display:
- Volume 10, Issue 5 (2019)
- Year:
- 2019
- Volume:
- 10
- Issue:
- 5
- Issue Sort Value:
- 2019-0010-0005-0000
- Page Start:
- 1303
- Page End:
- 1309
- Publication Date:
- 2019-04-23
- Subjects:
- Multi‐omics -- NSCLC -- PD‐1/PD‐L1 inhibitor -- predictive biomarker
Chest -- Cancer -- Periodicals
Chest -- Cancer -- Treatment -- Periodicals
Chest -- Surgery -- Periodicals
616.99494005 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291759-7714;jsessionid=9202029487E02D838DF722140677202D.d04t01 ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1759-7714 ↗
http://onlinelibrary.wiley.com/ ↗
http://www.wiley.com/bw/journal.asp?ref=1759-7706&site=1 ↗ - DOI:
- 10.1111/1759-7714.13078 ↗
- Languages:
- English
- ISSNs:
- 1759-7706
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 8820.242500
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