Identification and Comprehensive Prognostic Analysis of a Novel Chemokine-Related lncRNA Signature and Immune Landscape in Gastric Cancer

Gastric cancer (GC) is a malignant tumor with poor survival outcomes. Immunotherapy can improve the prognosis of many cancers, including GC. However, in clinical practice, not all cancer patients are sensitive to immunotherapy. Therefore, it is essential to identify effective biomarkers for predicting the prognosis and immunotherapy sensitivity of GC. In recent years, chemokines have been widely reported to regulate the tumor microenvironment, especially the immune landscape. However, whether chemokine-related lncRNAs are associated with the prognosis and immune landscape of GC remains unclear. In this study, we first constructed a novel chemokine-related lncRNA risk model to predict the prognosis and immune landscape of GC patients. By using various algorithms, we identified 10 chemokine-related lncRNAs to construct the risk model. Then, we determined the prognostic efficiency and accuracy of the risk model. The effectiveness and accuracy of the risk model were further validated in the testing set and the entire set. In addition, our risk model exerted a crucial role in predicting the infiltration of immune cells, immune checkpoint genes expression, immunotherapy scores and tumor mutation burden of GC patients. In conclusion, our risk model has preferable prognostic performance and may provide crucial clues to formulate immunotherapy strategies for GC.

Genomic features and tumor immune microenvironment alteration in NSCLC treated with neoadjuvant PD-1 blockade

Several clinical trials have shown the safety and effectiveness of PD-1/PD-L1 inhibitors in neoadjuvant therapy in resectable non-small cell lung cancer (NSCLC). However, 18–83% patients can benefit from it. In this study, we aimed to assess the association of PD-L1 expression, tumor mutation burden, copy number alteration (CNA, including copy number gain and loss) burden with the pathologic response to neoadjuvant PD-1 blockade and investigate the changes in the tumor immune microenvironment (TIME) during neoadjuvant immunotherapy in NSCLC. Pre-immunotherapy treatment tumor samples from twenty-nine NSCLC patients who received neoadjuvant immunotherapy with sintilimab, an anti-PD-1 drug, were subjected to targeted DNA sequencing and PD-L1 immunochemistry staining. The pathological response was positively correlated with tumor proportion score (TPS) of PD-L1 and negatively correlated with copy number gain (CNgain) burden. Of note, the combination of CNgain burden and TPS can better stratify major pathological response (MPR) patients than did CNgain or TPS alone. Whereas, TMB showed a limited correlation with pathological regression. Additionally, PD-1 blockade led to an increase in CD8+PD-1−T cells which was clinically relevant to MPR as evaluated by multiplex immunofluorescence. A significant reduction in CD19+ cells was observed in the Non-MPR group but not in the MPR group, indicating the involvement of B cells in improving neoadjuvant immunotherapy response in NSCLC. Together, our study provides new data for the correlation of PD-L1 expression and genomic factors with drug response in neoadjuvant immunotherapy settings in NSCLC. The changes of TIME may provide novel insight into the immune responses to neoadjuvant anti-PD-1 therapy.

Recurrent Gallbladder Carcinoma With pMMR/MSS Achieved a Complete Response Following Camrelizumab Combined With Apatinib: A Case Report

Gallbladder carcinoma (GBC) with proficient mismatch repair (pMMR)/microsatellite stable (MSS) is associated with limited response to programmed death-1 (PD-1) inhibitor monotherapy. Limited data of PD-1 blockade combined with anti-angiogenic therapy in GBC are reported. One recurrent GBC patient with pMMR/MSS was treated with camrelizumab plus apatinib. After 4 cycles of combination therapy, the patient achieved a durable complete response with manageable toxicity. The next-generation sequencing and immunohistochemistry analysis showed that tumor mutation burden (TMB) was 7.26 mutants/Mb and PD-L1 expression was 10% (tumor proportion score) and 20% (immune proportion score). This case suggests that camrelizumab in combination with apatinib may be an effective treatment option for GBC patients with pMMR/MSS status, who have moderate expression of TMB and PD-L1. Additionally, TMB and PD-L1 expression may serve as potential biomarkers for predicting PD-1 inhibitor response of GBC. Furthermore, this needs to be verified in future studies.

Development and Validation of a Tumor Mutation Burden-Related Immune Prognostic Signature for Ovarian Cancers

Ovarian cancer (OC), one of the most common malignancies of the female reproductive system, is characterized by high incidence and poor prognosis. Tumor mutation burden (TMB), as an important biomarker that can represent the degree of tumor mutation, is emerging as a key indicator for predicting the efficacy of tumor immunotherapy. In our study, the gene expression profiles of OC were downloaded from TCGA and GEO databases. Subsequently, we analyzed the prognostic value of TMB in OC and found that a higher TMB score was significantly associated with a better prognosis (p = 0.004). According to the median score of TMB, 9 key TMB related immune prognostic genes were selected by LASSO regression for constructing a TMB associated immune risk score (TMB-IRS) signature, which can effectively predict the prognosis of OC patients (HR = 2.32, 95% CI = 1.68–3.32; AUC = 0.754). Interestingly, TMB-IRS is also closely related to the level of immune cell infiltration and immune checkpoint molecules (PD1, PD-L1, CTLA4, PD-L2) in OC. Furthermore, the nomogram combined with TMB-IRS and a variety of clinicopathological features can more comprehensively evaluate the prognosis of patients. In conclusion, we explored the relationship between TMB and prognosis and validated the TMB-IRS signature based on TMB score in an independent database (HR = 1.60, 95% CI = 1.13–2.27; AUC = 0.639), which may serve as a novel biomarker for predicting OC prognosis as well as possible therapeutic targets.

Characterization of m6A Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration in Ovarian Cancer

Introduction: Studies have demonstrated the epigenetic regulation of immune responses in various cancers. However, little is known about the RNA N6-methyladenosine (m6A) modification patterns of the microenvironment (TME) cell infiltration in ovarian cancer (OC).Methods: We evaluated the correlation between m6A modification patterns and TME cell infiltration based on 459 OC samples from the Cancer Genome Atlas and Gene-Expression Omnibus database. We constructed an m6Ascore system to quantify m6A modification patterns using principal component analysis.Results: Based on unsupervised clustering, three m6A modification patterns were identified. Gene set variation analysis showed that the antigen presentation signal pathway, the NOTCH signaling pathway, and the metabolism-related pathway differed significantly across m6A modificaiton patterns. The m6Ascore is closely correlated with TME cell infiltration. OC patients with lower m6Ascores had worse outcomes. There was better risk stratification with combined m6Ascore and tumor mutation burden. The responses to immune checkpoint inhibitor treatment significantly differed between high and low m6Ascore groups.Conclusion: M6A modification plays an essential role in TME cell infiltration in OC. Evaluating the m6A modification patterns in OC patients could enhance our understanding of TME infiltration characterization and guide immunotherapy strategies.

DNA Repair and Replication-Related Gene Signature Based on Tumor Mutation Burden Reveals Prognostic and Immunotherapy Response in Gastric Cancer

The genomic variant features (mutations, deletions, structural variants, etc.) within gastric cancer impact its evolution and immunogenicity. The tumor has developed several coping strategies to respond to these changes by DNA repair and replication (DRR). However, the intrinsic relationship between the associated DRR-related genes and gastric cancer progression remained unknown. This study selected DRR-related genes with tumor mutation burden based on the TCGA (The Cancer Genome Atlas) database of gastric cancer transcriptome and mutation data. The prognosis model of seven genes (LAMA2, CREB3L3, SELP, ABCC9, CYP1B1, CDH2, and GAMT) was constructed by a univariate and LASSO regression analysis and divided into high-risk and low-risk groups with the median risk score. Survival analysis showed that overall survival (OS) was lower in the high-risk group than that in the low-risk group. Moreover, patients with gastric cancer in the high-risk group have worse survival in different subgroups, including age, gender, histological grade, and TNM stage. The nomogram that included risk scores for DRR-related genes could accurately foresee OS of patients with gastric cancer. Interestingly, the tumor mutation burden score was higher in the low-risk group than that in the high-risk group, and the risk score for DRR-related genes was negatively correlated with tumor mutation burden in gastric cancer. Next, we further combined the risk score and tumor mutation burden to evaluate the prognosis of gastric cancer patients. The low-risk cohort had a better prognosis than the high-risk cohort in the high tumor mutation burden subgroup. The number of mutation types in the high-risk group was lower than that in the low-risk group. In the immune microenvironment of gastric cancer, more naïve B cells, memory resting CD4+ T cells, Treg cells, monocytes cells, and resting mast cells were infiltrated in the high-risk group. At last, PD-L1 and IAP expressions were negatively correlated with the risk scores; patients with gastric cancer in the low-risk group showed better immunotherapy outcomes than those in the high-risk group. Overall, the DRR-related gene signature based on tumor mutation burden is a novel biomarker for prognostic and immunotherapy response in patients with gastric cancer.

m6A Regulators Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization In Nasopharyngeal Carcinoma

BackgroundThe role of RNA N6-methyladenosine (m6A) modification in tumor progression and metastasis has been demonstrated. Nonetheless, potential biological function of m6A modification patterns in nasopharyngeal carcinoma (NPC) remains unknown.MethodsThe m6A modification patterns were comprehensively evaluated based on 26 m6A regulators in NPC, and m6A subtype and also m6A score were identified and systematically correlated with representative tumor characteristics.ResultsTwo distinct m6A subtypes were determined and were highly consistent with immune activated and immune suppressed phenotypes, respectively. More representative m6A scores of individual tumors could predict tumor microenvironment (TME) infiltration, mRNA based stemness index (mRNAsi), EBV gene expression, genetic variation, and prognosis of NPC patients. Low m6A score, characterized by activation of immunity and suppression of mRNAsi and EBV gene, indicated an activated TME phenotype and better PFS and also lower risk of recurrence and metastasis. High m6A score, characterized by activation of Wnt and NF-κB signaling pathway and lack of effective immune infiltration, indicated an immune suppressed TME phenotype and poorer survival. Low m6A score was also correlated with increased tumor mutation burden (TMB) and better response to immunotherapy, and vice versa. A significant therapeutic advantage in patients with low m6A score was confirmed with an anti-PDL1 immunotherapy cohort.Conclusionsm6A patterns played an important role in the diversity and complexity of TME. m6A score could be used to evaluate the m6A pattern of individual tumor to enhance our understanding of TME infiltration and guide more effective immunotherapy strategies.

Prediction of pan-solid tumor pembrolizumab benefit by integrating tumor mutation and gene expression profiling

Pembrolizumab is approved in many advanced solid tumor types, however predictive biomarkers and the proportion of pembrolizumab-benefiting patients vary. Biomarkers beyond PD-L1 immunohistochemistry, microsatellite instability (MSI) status, and tumor mutation burden (TMB) may improve benefit prediction. Here, leveraging treatment data (time to next treatment [TTNT]) and comprehensive genomic and quantitative transcriptomic profiling on routine tumor tissue from 708 patients (24 tumor types) collected in an ongoing observational trial (NCT03061305), we report a multivariate, integrative predictor of pan-solid tumor pembrolizumab benefit. The Immune Response Score (IRS) model, which includes TMB and quantitative PD-1, PD-L2, ADAM12 and CD4 RNA expression, was confirmed as predictive through comparison of pembrolizumab TTNT with previous chemotherapy TTNT in a subset of 166 patients treated with both. Applying IRS to the entire NCT03061305 cohort (n=25,770 patients), 13.2-30.7% of patients (2.2-9.6% of patients outside of pembrolizumab approved tumor types [including TMB-High and MSI-High]) are predicted to benefit substantially from pembrolizumab. Hence, if prospectively validated, the IRS model may improve pembrolizumab benefit prediction across approved tumor types including patients outside of currently approved indications.

Clinical Benefits of Immune Checkpoint Inhibitors and Predictive Value of Tumor Mutation Burden in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Review question / Objective: Is immunotherapy associated with beneficial clinical outcomes for hepatocellular carcinoma (HCC) and how can combination immunotherapy be deployed to produce the best benefit? Is tumor mutation burden (TMB) a predictive biomarker for immune‐checkpoint inhibitors? Condition being studied: To this date, about 50 single-arm clinical trials and several randomized control trials (RCTs) presented final or interim results of investigations on the efficacy of PD-1/PD-L1 inhibitors for advanced HCC. In the CheckMate 459, IMbrave 050, and ORIENT-32, immunotherapies were found to significantly improve progression-free survival (PFS) and overall survival (OS) compared with sorafenib (a tyrosine-kinase inhibitor, as standard systemic treatment) in patients with advanced hepatocellular carcinoma. However, these clinical trials were different on clinical phases, sample size, and response evaluation criteria, and inconsistent clinical outcomes were shown in several trials.