Identification of an Immune-Related Signature Predicting Survival Risk and Immune Microenvironment in Gastric Cancer

CD4+ T cells in antitumor immunity

Advances in cancer immunotherapy have transformed cancer care and realized unprecedented responses in many patients. The growing arsenal of novel therapeutics - including immune checkpoint inhibition (ICI), adoptive T cell therapies (ACTs), and cancer vaccines - reflects the success of cancer immunotherapy. The therapeutic benefits of these treatment modalities are generally attributed to the enhanced quantity and quality of antitumor CD8+ T cell responses. Nevertheless, CD4+ T cells are now recognized to play key roles in both the priming and effector phases of the antitumor immune response. In addition to providing T cell help through co-stimulation and cytokine production, CD4+ T cells can also possess cytotoxicity either directly on MHC class II-expressing tumor cells or to other cells within the tumor microenvironment (TME). The presence of specific populations of CD4+ T cells, and their intrinsic plasticity, within the TME can represent an important determinant of clinical response to immune checkpoint inhibitors, vaccines, and chimeric antigen receptor (CAR) T cell therapies. Understanding how the antitumor functions of specific CD4+ T cell types are induced while limiting their protumorigenic attributes will enable more successful immunotherapies.

Wnt signaling in gastric cancer: current progress and future prospects

Levels of the Wnt pathway components are abnormally altered in gastric cancer cells, leading to malignant cell proliferation, invasion and metastasis, poor prognosis and chemoresistance. Therefore, it is important to understand the mechanism of Wnt signaling pathway in gastric cancer. We systematically reviewed the molecular mechanisms of the Wnt pathway in gastric cancer development; and summarize the progression and the challenges of research on molecular agents of the Wnt pathway.

Immunobiological signatures and the emerging role of SPP1 in predicting tumor heterogeneity, malignancy, and clinical outcomes in stomach adenocarcinoma

BACKGROUND

Immunotherapy, as a form of immunobiological therapy, represents a promising approach for enhancing patients' immune responses. This work aims to present innovative ideas and insights for prognostic assessment and clinical treatment of stomach adenocarcinoma (STAD) by leveraging immunobiological signatures.

METHODS

We employed weighted gene co-expression network analysis (WGCNA) and unsupervised clustering analysis to identify hub genes. These hub genes were utilized to construct a prognostic risk model, and their impact on the tumor microenvironment (TME) and DNA variations was assessed using large-scale STAD patient cohorts. Additionally, we conducted transfection experiments with plasmids to investigate the influence of SPP1 on the malignancy of HGC27 and NCI-N87 cells.

RESULTS

Unsupervised clustering of 12 immune-related genes (IRGs) revealed three distinct alteration patterns with unique molecular phenotypes, clinicopathological characteristics, prognosis, and TME features. Using LASSO and multivariate Cox regression analyses, we identified three hub genes (MMP12, SPP1, PLAU) from the IRGs to establish a risk signature. This IRG-related risk model significantly stratified the prognosis risk among STAD patients in the training (n = 522), testing (n = 521), and validation (n = 300) cohorts. Notably, there were discernible differences in therapy responses and TME characteristics, such as tumor purity and lymphocyte infiltration, between the risk model groups. Subsequently, a nomogram that incorporates the IRG signature and clinicopathological factors demonstrated superior sensitivity and specificity in predicting outcomes for STAD patients. Furthermore, down-regulation of SPP1, as observed after siRNA transfection, significantly inhibited the proliferation and migration abilities of HGC27 and NCI-N87 cells.

CONCLUSIONS

In summary, this study highlights the critical role of immune-related signatures in STAD and offers novel insights into prognosis indicators and immunotherapeutic targets for this condition. SPP1 emerges as an independent prognostic factor for STAD and appears to regulate STAD progression by influencing the immune microenvironment.

An integrated analysis of prognostic mRNA signature in early- and progressive-stage gastric adenocarcinoma

The pathogenesis and vital factors of early and progressive stages of stomach adenocarcinoma (STAD) have not been fully elucidated. In order to discover novel and potential targets to guide effective treatment strategies, a comprehensive bioinformatics study was performed, and the representative results were then validated by quantitative polymerase chain reaction (qPCR) and immunohistochemical (IMC) staining in clinical samples. A total of 4,627, 4,715, and 3,465 differentially expressed genes (DEGs) from overall-, early-, and progressive-stage STAD were identified, respectively. Prognostic models of 5-year OS were established for overall-, early-, and progressive-stage STAD, and ROC curves demonstrated AUC values for each model were 0.73, 0.87, and 0.92, respectively. Function analysis revealed that mRNAs of early-stage STAD were enriched in chemical stimulus-related pathways, whereas remarkable enrichment of mRNAs in progressive-stage STAD mainly lay in immune-related pathways. Both qPCR and IHC data confirmed the up-regulation of IGFBP1 in the early-stage and CHAF1A in progressive-stage STAD compared with their matched normal tissues, indicating that these two representative targets could be used to predict the prognostic status of the patients in these two distinct STAD stages, respectively. In addition, seven mRNAs (F2, GRID2, TF, APOB, KIF18B, INCENP, and GCG) could be potential novel biomarkers for STAD at different stages from this study. These results contributed to identifying STAD patients at high-risk, thus guiding targeted treatment with efficacy in these patients.

Biomarker analysis from a phase II multi-institutional study of nivolumab in patients with advanced refractory biliary tract cancer

BACKGROUND

Our previous phase II study demonstrated that nivolumab provides modest but durable clinical efficacy in patients with refractory biliary tract cancer, suggesting the significant clinical benefit of nivolumab in selected patients and the necessity of predictive biomarkers. We evaluated clinicopathological characteristics and tumour microenvironment of the patients who were enrolled the trial to identify potential biomarkers.

METHODS

Baseline clinicopathological characteristics and pretreatment tumour samples were collected. The obtained tumour samples were assessed for whole exome sequencing, RNA sequencing and immunohistochemistry. Their correlations with clinical outcome were analysed.

RESULTS

Pretreatment tumour evaluation revealed PD-L1 expression on tumour, CD8 T cell infiltration and high ratio of CD8 T cell/regulatory T cell in tumour microenvironment were significantly associated with prolonged progression-free survival (PFS), while PD-1 expression on lymphocytes and CD68 macrophages infiltration in tumour microenvironment had no predictive role. Asian patients (N = 3) had improved PFS and disease control rate compared with non-Asian (N = 54). A six-gene predictive model was constructed by evaluation of total 23,550 candidate genes from RNA sequencing of baseline tumour samples using LASSO-Cox regression analysis, and high score of the six-gene prediction model was associated with prolonged PFS.

CONCLUSION

This study suggests that PD-L1 expression on tumour, CD8 T cell infiltration and high ratio of CD8/regulatory T cells and six-gene expression profile in tumour microenvironment may be potential predictive biomarkers of nivolumab in biliary tract cancers. Further studies are needed to confirm these findings.

An Immune Signature for Risk Stratification and Therapeutic Prediction in Helicobacter Pylori-Infected Gastric Cancer

Simple Summary

Helicobacter pylori (HP) infection is the greatest risk factor for gastric cancer (GC), and over half of the world’s population is colonized with HP. Up to now, many gene signatures are designed for predicting the prognosis of GC patients, while there are no signatures designed specifically for HP+ GC patients. Considering the tight association between HP infection and tumor immune microenvironment, we constructed an immune-related signature named IRSHG in this study, aiming to provide new insight into the treatment for HP+ GC patients. IRSHG was the first prognostic signature for HP+ GC patients, demonstrating high reliability and feasibility in predicting the prognosis. In addition, IRSHG could help investigate potential therapies and guide anti-PD-1 immunotherapy for HP+ GC patients, providing new insight for the personalized treatment of GC.

Abstract

Helicobacter pylori (HP) infection is the greatest risk factor for gastric cancer (GC). Increasing evidence has clarified that tumor immune microenvironment (TIME) is closely related to the prognosis and therapeutic efficacy of HP-positive (HP+) GC patients. In this study, we aimed to construct a novel immune-related signature for predicting the prognosis and immunotherapy efficacy of HP+ GC patients. A total of 153 HP+ GC from three different cohorts were included in this study. An Immune-Related prognostic Signature for HP+ GC patients (IRSHG) was established using Univariate Cox regression, the LASSO algorithm, and Multivariate Cox regression. Univariate and Multivariate analyses proved IRSHG was an independent prognostic predictor for HP+ GC patients, and an IRSHG-integrated nomogram was established to quantitatively assessthe prognostic risk. The low-IRSHG group exhibited higher copy number load and distinct mutation profiles compared with the high-IRSHG group. In addition, the difference of hallmark pathways and immune cells infiltration between the two groups was investigated. Notably, tumor immune dysfunction and exclusion (TIDE) analysis indicated that the low-IRSHG group had a higher sensitivity to anti-PD-1 immunotherapy, which was validated by an external pabolizumab treatment cohort. Moreover, 98 chemotherapeutic drugs and corresponding potential biomarkers were identified for two groups, and several drugs with potential ability to reverse IRSHG score were identified using CMap analysis. Collectively, IRSHG may serve as a promising biomarker for survival outcome as well as immunotherapy efficacy. Furthermore, it can also help to prioritize potential therapeutics for HP+ GC patients, providing new insight for the personalized treatment of HP-infected GC.

Identification of the Immune Subtype of Hepatocellular Carcinoma for the Prediction of Disease-Free Survival Time and Prevention of Recurrence by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data

Background

The main factors affecting the long-term prognosis of hepatocellular carcinoma (HCC) patients undergoing radical surgery are recurrence and metastasis. However, the methods for predicting disease-free survival (DFS) time and preventing postoperative recurrence of HCC are still very limited.

Methods

In this study, immune cell abundances in HCC samples were analyzed by single-sample gene set enrichment analysis (ssGSEA), while the prognostic values of immune cells for DFS time prediction were evaluated by the least absolute shrinkage and selection operator (LASSO) and subsequent univariate and multivariate Cox analyses. Next, a risk score was constructed based on the most prognostic immune cells and their corresponding coefficients. Interactions among prognostic immune cells and the specific targets for the prevention of recurrence were further identified by single-cell RNA (scRNA) sequencing data and CellMiner.

Results

A novel efficient T cell risk score (TCRS) was constructed based on data from the three most prognostic immune cell types (effector memory CD8 T cells, regulatory T cells and follicular helper T cells) for identifying an immune subtype of HCC patients with longer DFS times and inflammatory immune characteristics. Functional differences between the high- and low-score groups separated by TCRS were clarified, and the cell-cell communication among these immune cells was elucidated. Finally, fifteen hub genes that may be potential therapeutic targets for the prevention of recurrence were identified.

Conclusions

We constructed and verified a useful model for the prediction of DFS time of HCC after surgery. In addition, fifteen hub genes were identified as candidates for the prevention of recurrence, and a preliminarily investigation of potential drugs targeting these hub genes was carried out.

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.