Abstract
Immune checkpoint blockade (ICB) therapy has provided clinical benefits for patients with advanced non-small-cell lung cancer (NSCLC), but the majority still do not respond. Although a few biomarkers of ICB treatment response have been developed, the predictive power of these biomarkers showed substantial variation across datasets. Therefore, predicting response to ICB therapy remains a challenge. Here, we provided a concise combinatorial strategy for predicting ICB therapy response and constructed the ICB treatment signature (ITS) in lung cancer. The prediction performance of ITS has been validated in an independent ICB treatment cohort of NSCLC, where patients with higher ITS score were significantly associated with longer progression-free survival and better response. And ITS score was more powerful than traditional biomarkers, such as TMB and PD-L1, in predicting the ICB treatment response in NSCLC. In addition, ITS scores still had predictive effects in other cancer data sets, showing strong scalability and robustness. Further research showed that a high ITS score represented comprehensive immune activation characteristics including activated immune cell infiltration, increased mutation load, and TCR diversity. In conclusion, our practice suggested that the combination of biomarkers will lead to a better prediction of ICB treatment prognosis, and the ITS score will provide NSCLC patients with better ICB treatment decisions.
Highlights
Lung cancer is the most common malignant tumor in the world [1]
To construct an integrated Immune checkpoint blockade (ICB) response biomarker, we first evaluated genes and pathways associated with three mechanisms related to ICB response (CTL, Tumor mutation burden (TMB), and TGF-b signaling) in lung cancer samples
We identified 756 and 1,100 genes associated with high cytotoxic T lymphocyte (CTL) levels in lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC), respectively, of which 608 genes were found in both cancers (Figures 1A, S1A)
Summary
Lung cancer is the most common malignant tumor in the world [1]. In the current clinical practice, immune checkpoint therapy [2, 3] and combination therapy strategy [4, 5] has achieved amazing therapeutic effects in the treatment of cancer and have changed the clinical management of cancer. Higher TMB is associated with improved prognosis and increased response rate to ICB therapies in most studies [9,10,11]. Decreased T-cell infiltration has been reported to be associated with a poorer prognosis [13], and TGF-b signal limits the infiltration of T cells, forming a suppressed immune microenvironment [14, 15]. These mechanisms were used to develop ICB response biomarkers, such as TIDE [16] and PAN-fibroblast TGF-b response signature [17]
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