Surprising impact of stromal TIL’s on immunotherapy efficacy in a real-world lung cancer study

Abstract

Immune checkpoint inhibitors (ICI), such as anti-PD-1 agents, have become part of the standard of care treatment of advanced non-small cell lung cancer (NSCLC). Predictive biomarkers are needed to identify patients that benefit from anti-PD-1 treatments. Tumor infiltrating lymphocytes (TILs) and PD-L1 are major players in the ICI mechanism of action. In this study, we assess the impact of real-world clinicopathological variables, including TILs and PD-L1, on anti-PD-1 efficacy. Methods: We performed a monocenter retrospective study in advanced NSCLC treated with nivolumab or pembrolizumab between January 2015 and February 2019. The impact of baseline clinical and pathological variables was assessed by univariate and multivariate models. TILs, defined as CD8+T-cells, and PD-L1 were scored in tumor and stroma, and correlated with progression free survival (PFS) and overall survival (OS). Results: We included 366 patients of whom 141 were assessed for tumor and stromal TILs. The median follow-up time was 487 days. In the whole cohort, PFS was associated with high tumor PD-L1, high albumin and good performance. OS was associated with low LDH, high albumin, good performance and 'first-line treatment'. In the TILs subcohort, stromal TILs had the strongest impact on PFS and OS. Stromal TILs were a stronger marker for PFS and OS than tumoral TILs, tumoral PD-L1 or stromal PD-L1. Remaining factors for PFS and OS were albumin and albumin with LDH, respectively. Conclusions: This real-world study on clinicopathological features shows that stromal CD8 + TILs were the strongest predictor for PFS and OS in patients with advanced NSCLC on anti-PD-1 therapy. Other predictors for PFS and OS included albumin and albumin together with LDH, respectively. This study highlights the pivotal role of the stromal compartment in the mechanisms of action of ICI, and the need for further studies aiming to overcome this stromal firewall.

The association between CD8+ tumor-infiltrating lymphocytes and the clinical outcome of cancer immunotherapy: A systematic review and meta-analysis

“…A total of 5123 articles were obtained through the initial search strategy. After screening abstract and reviewing full texts, 33 articles [ [7] , [8] , [9] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] ] published from 2014 to 2021 were considered as eligible in final analyses ( Fig. 1 A).…”

Neoadjuvant immune checkpoint inhibitors in resectable non-small-cell lung cancer: a systematic review

“…By contrast, biomarkers which have been associated with responses to ICIs include PD-L1 expression in stromal cells, 16 CD28 expression on CD8 + tumor-infiltrating lymphocytes (TILs), 37 and stromal TILs. 38 This highlights the need to identify appropriate predictive biomarkers for selecting patients upfront. Third, the lack of a standardized approach for pathological reporting of resected lung carcinomas following neoadjuvant treatment may reflect a lack of sufficient input from pathologists in study design.…”

The effect of tumor size and metastatic extent on the efficacy of first line pembrolizumab monotherapy in patients with high PD-L1 expressing advanced NSCLC tumors

“…For all the analyses a rough effect size and a corrected effect size was estimated, the latter was corrected for age (<70 or ≥70 years), albumin (<35 or ≥35 g/dL), LDH (<250 or ≥250 U/L), lung metastases (yes or no), bone metastases (yes or no), brain metastases (yes or no) and liver metastases (yes or no). These variables were previously shown to influence the survival of ICI treated patients [8].…”

“…This highlights not only the need for better therapies, but also the need for insight in selecting the right therapy for the right patients based on strong predictive biomarkers. In clinical practice, PD-L1 is the commonly used predictive biomarker [6][7][8]. Another possible marker that could predict response is the tumor size and its metastatic extent.…”