Biomarkers such as programmed death receptor 1 ligand (PD-L1) expression, tumor mutational burden (TMB), and high microsatellite instability are potentially applicable to predict the efficacy of immune checkpoint blockade (ICB). However, several challenges such as defining the cut-off value, test platform uniformity, and low frequencies limit their broad clinical application. Here we identify comutations in the DNA damage response (DDR) pathways of homologous recombination repair and mismatch repair (HRR-MMR) or HRR and base excision repair (HRR-BER; defined as co-mut) that are associated with increased TMB and neoantigen load and increased levels of immune gene expression signatures. In four public clinical cohorts, co-mut patients presented a higher objective response rate and a longer progression-free survival or overall survival than co-mut patients. Overall, identification of DDR comutations in HRR-MMR or HRR-BER as predictors of response to ICB provides a potentially convenient approach for future clinical practice. Identification of comutations in specific DDR pathways as predictors of superior survival outcomes in response to immune checkpoint blockade provide a clinically convenient approach for estimation of tumor mutational burden and delivery of ICB therapy. .

T-cell receptor (TCR)-based biomarkers might predict patient response to immune checkpoint blockade (ICB) but need further exploration and validation for that use. We sequenced complementarity-determining region 3 of TCRb chains isolated from PD-1 þ CD8 þ T cells to investigate its value for predicting the response to anti-programmed cell death 1 (PD-1)/PD-ligand 1 (PD-L1) therapy in patients with non-small cell lung cancer (NSCLC). Two independent patient cohorts (cohort A, n ¼ 25; cohort B, n ¼ 15) were used as discovery and validation sets, respectively. Pre-and post-ICB peripheral blood samples were collected. In cohort A, patients with high PD-1 þ CD8 þ TCR diversity before ICB treatment showed better response to ICB and progression-free survival (PFS) compared with patients with low diversity [6.4 months vs. 2.5 months, HR, 0.39; 95% confidence interval (CI), 0.17-0.94; P ¼ 0.021]. The results were validated in cohort B. Pre-ICB PD-1 þ CD8 þ TCR diversity achieved an optimal Youden's index of 0.81 (sensitivity ¼ 0.87 and specificity ¼ 0.94) for differentiating the ICB response in the merged dataset (cohort A plus cohort B). Patients with increased PD-1 þ CD8 þ TCR clonality after ICB treatment had longer PFS (7.3 months vs. 2.6 months, HR, 0.26; 95% CI, 0.08-0.86; P ¼ 0.002) than those with decreased clonality. Thus, TCR diversity and clonality in peripheral blood PD-1 þ CD8 þ T cells may serve as noninvasive predictors of patient response to ICB and survival outcomes in NSCLC.

Introduction: Blood-based tumor mutational burden (bTMB) has been studied to identify patients with NSCLC who would benefit from anti-programmed cell death protein 1 (anti-PD-1) or anti-programmed death ligand 1 (anti-PD-L1) therapies. However, it failed to predict overall survival (OS) benefits, which warrants further exploration.Methods: Three independent cohorts of patients with NSCLC treated with immunotherapy were used in this study. A new bTMB algorithm was first developed in the two independent cohorts (POPLAR, N ¼ 211, and OAK, N ¼ 462) and further validated in the third National Cancer Center (NCC) cohort (N ¼ 64).Results: bTMB-H (bTMB cutoff point) was not associated with favorable OS after immunotherapy regardless of the cutoff points in either the POPLAR and OAK or the NCC cohorts (p > 0.05) owing to its correlation with the amount of circulating tumor DNA, which was associated with poor OS. In the POPLAR and OAK cohorts, with allele frequency (AF) adjustment, a high AF bTMB (HAF-bTMB, mutation counts with an AF > 5%) was strongly correlated with the amount of circulating tumor DNA (Pearson r ¼ 0.65),

In clinical practice, there are currently no validated biomarkers that can, prior to treatment, reliably indicate the intrinsically sensitive or resistant features of a non-squamous NSCLC patient to pemetrexed plus platinum doublet chemotherapy. In this study, we investigated the metabolic characteristics of a large cohort of pre-chemotherapeutic serum samples (354 cases) and found tight associations between small metabolite subsets and the responses of patients to this cytotoxic drug combination. We developed an effective discriminant model employing a seven-metabolite panel (Hypotaurine, Uridine, Dodecanoylcarnitine, Choline, Dimethylglycine, Niacinamide, L-palmitoylcarnitine) that can predict the efficacy of this chemotherapeutic regimens, prior to treatment, with a sensitivity of 90.8% and specificity of 79.5%. We also identified three one-carbon metabolism-involved metabolites including choline, betaine and DMG that are potentially associated with drug resistance to pemetrexed. This serum-based biomarker study can be easily applied in clinical practice and personalize treatment decisions. Conclusion:This study developed an effective and convenient discriminant model that can accurately predict the efficacy and survival outcomes of pemetrexed plus platinum doublet chemotherapy prior to treatment delivery.

Background/Aims: Human leukocyte antigen-G (HLA-G) plays an important role in inhibiting natural killer (NK) cell function and promoting immune escape. However, the specific mechanism of HLA-G on NK in gastric cancer (GC) remains not well understood. This study investigated the expression of HLA-G in GC and the role of HLA-G-effected NK cells in GC progression. Methods: HLA-G expression in GC tissues obtained from 49 patients with GC was analyzed by immunohistochemistry and western blot. The number of tumor-infiltrating NK cells and the expression of their surface receptors were analyzed by immunohistochemistry and flow cytometry, respectively. The effect of HLA-G on NK cell proliferation was examined by Cell Counting Kit-8 (CCK8) assay. LDH release assay was used to evaluate the effect of HLA-G on the cytotoxic activity of NK cells, and the levels of IFN-γ and TNF-α in the co-cultured supernatant were detected by ELISA. Mice bearing a xenograft tumor model were used to examine the effect of HLA-G on the anti-tumor effect of NK cells. Results: HLA-G positive expression was detected in most of the GC tissues, and was correlated with the adverse prognosis of the disease. The expression of HLA-G was negatively associated with the number of tumor-infiltrating NK cells. Furthermore, GC cell lines with overexpressed HLA-G revealed their ability to inhibit the cell proliferation and cytotoxic activity of NK-92MI cells, and reduce the secretion of IFN-γ and TNF-α through immunoglobulin-like transcript 2 (ILT2). Finally, this in vivo experiment was able to prove that HLA-G can inhibit the anti-tumor effect of NK cells through ILT2. Conclusion: The expression of HLA-G was strongly correlated with the adverse prognosis of GC. The reason may be that it inhibits the proliferation and cytotoxic activity of infiltrating NK cells through ILT2.