Avoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer
Immunotherapy has been focused on by many oncologists and researchers. While, due to technical biases of absolute quantification, few traditional biomarkers for anti-PD-1 immunotherapy have been applied in regular clinical practice of non-small cell lung cancer (NSCLC). Therefore, there is an urgent...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:33bd7fb95ba8489280d6f58b400ea2182021-11-19T07:52:47ZAvoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer1664-322410.3389/fimmu.2021.782106https://doaj.org/article/33bd7fb95ba8489280d6f58b400ea2182021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fimmu.2021.782106/fullhttps://doaj.org/toc/1664-3224Immunotherapy has been focused on by many oncologists and researchers. While, due to technical biases of absolute quantification, few traditional biomarkers for anti-PD-1 immunotherapy have been applied in regular clinical practice of non-small cell lung cancer (NSCLC). Therefore, there is an urgent and unmet need for a feasible tool—immune to data source bias—for identifying patients who might benefit from ICIs in clinical practice. Using the strategy based on the relative ranking of gene expression levels, we herein proposed the novel BRGP index (BRGPI): four BRGPs significantly related with progression-free survival of NSCLC patients treated with anti-PD-1 immunotherapy in the multicohort analysis. Moreover, stratification and multivariate Cox regression analyses demonstrated that BRGPI was an independent prognostic factor. Notably, compared to PD-L1, BRGPI exerted the best predictive ability. Further analysis showed that the patients in the BRGPI-low and PD-L1-high subgroup derived more clinical benefits from anti-PD-1 immunotherapy. In conclusion, the prospect of applying the BRGPI to real clinical practice is promising owing to its powerful and reliable predictive value.Chengming LiuChengming LiuSihui WangSihui WangSufei ZhengSufei ZhengFei XuZheng CaoXiaoli FengYan WangQi XueNan SunNan SunJie HeJie HeFrontiers Media S.A.articleNSCLCimmune checkpoint inhibitorsclinical benefitprognosisBRGPIImmunologic diseases. AllergyRC581-607ENFrontiers in Immunology, Vol 12 (2021) |
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DOAJ |
| collection |
DOAJ |
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EN |
| topic |
NSCLC immune checkpoint inhibitors clinical benefit prognosis BRGPI Immunologic diseases. Allergy RC581-607 |
| spellingShingle |
NSCLC immune checkpoint inhibitors clinical benefit prognosis BRGPI Immunologic diseases. Allergy RC581-607 Chengming Liu Chengming Liu Sihui Wang Sihui Wang Sufei Zheng Sufei Zheng Fei Xu Zheng Cao Xiaoli Feng Yan Wang Qi Xue Nan Sun Nan Sun Jie He Jie He Avoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer |
| description |
Immunotherapy has been focused on by many oncologists and researchers. While, due to technical biases of absolute quantification, few traditional biomarkers for anti-PD-1 immunotherapy have been applied in regular clinical practice of non-small cell lung cancer (NSCLC). Therefore, there is an urgent and unmet need for a feasible tool—immune to data source bias—for identifying patients who might benefit from ICIs in clinical practice. Using the strategy based on the relative ranking of gene expression levels, we herein proposed the novel BRGP index (BRGPI): four BRGPs significantly related with progression-free survival of NSCLC patients treated with anti-PD-1 immunotherapy in the multicohort analysis. Moreover, stratification and multivariate Cox regression analyses demonstrated that BRGPI was an independent prognostic factor. Notably, compared to PD-L1, BRGPI exerted the best predictive ability. Further analysis showed that the patients in the BRGPI-low and PD-L1-high subgroup derived more clinical benefits from anti-PD-1 immunotherapy. In conclusion, the prospect of applying the BRGPI to real clinical practice is promising owing to its powerful and reliable predictive value. |
| format |
article |
| author |
Chengming Liu Chengming Liu Sihui Wang Sihui Wang Sufei Zheng Sufei Zheng Fei Xu Zheng Cao Xiaoli Feng Yan Wang Qi Xue Nan Sun Nan Sun Jie He Jie He |
| author_facet |
Chengming Liu Chengming Liu Sihui Wang Sihui Wang Sufei Zheng Sufei Zheng Fei Xu Zheng Cao Xiaoli Feng Yan Wang Qi Xue Nan Sun Nan Sun Jie He Jie He |
| author_sort |
Chengming Liu |
| title |
Avoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer |
| title_short |
Avoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer |
| title_full |
Avoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer |
| title_fullStr |
Avoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer |
| title_full_unstemmed |
Avoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer |
| title_sort |
avoiding absolute quantification trap: a novel predictive signature of clinical benefit to anti-pd-1 immunotherapy in non-small cell lung cancer |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/33bd7fb95ba8489280d6f58b400ea218 |
| work_keys_str_mv |
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| _version_ |
1718420250935951360 |