A novel metabolic subtype with S100A7 high expression represents poor prognosis and immuno-suppressive tumor microenvironment in bladder cancer

Role of TAP1 in the identification of immune-hot tumor microenvironment and its prognostic significance for immunotherapeutic efficacy in gastric carcinoma

Background

Gastric cancer (GC), a multifaceted gastrointestinal malignancy, is the fourth most prevalent contributor to cancer-related fatalities globally. As a member of the ATP-binding cassette (ABC) family, transporter associated with antigen processing 1 (TAP1) is crucial for conveying antigen peptides from the cytoplasm to the lumen of the endoplasmic reticulum and subsequently loading them onto the major histocompatibility complex (MHC) class I molecules. Recent studies have established the biological significance of TAP1 in upholding tumor survival and facilitating immune evasion by remodeling the tumor microenvironment (TME) and orchestrating immune infiltration. The study was conducted to elucidate the association of TAP1 expression with immunological characteristics, and sought to exploit the value of TAP1 as a biomarker reflecting the inflamed TME and immunotherapeutic response.

Methods

RNA-sequencing profiles and clinical annotations were obtained from The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) cohort and Gene Expression Omnibus (GEO) portal. Preprocessing was conducting using the limma package. Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules and TAP1 co-expressed genes (CEGs) based on correlation patterns. Consensus clustering and silhouette analysis determined the optimal number of TAP1-related groups. Gene expression profiles were integrated and classified using the pamr package. The Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate immunological characteristics. Differential expression analysis was conducted using the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Single-cell RNA sequencing (scRNA-seq) datasets were analyzed using the Seurat toolkit to characterize cell types.

Results

Within this investigation, no significant differences in TAP1 expression were observed among patients exhibiting various clinicopathological features, indicating that TAP1 expression was not specific to molecular subtypes. Subsequent analysis revealed a positive correlation between TAP1 and diverse immunological traits, encompassing immunomodulators, tumor-infiltrating immune cells, as well as immune checkpoints across multiple datasets. Besides, within a GC immunotherapy cohort, individuals displaying high TAP1 expression demonstrated an increased likelihood of achieving complete remission (CR) post-treatment, suggesting heightened sensitivity to immunotherapy. In the clinical cohort, TAP1 overexpression in GC patients was positively correlated with CD8.

Conclusions

TAP1 appears linked to an inflamed TME and serves as a prospective biomarker for discerning immunological attributes and gauging immunotherapeutic responses in GC, particularly in identifying immune-reactive tumors.

Unraveling metabolic characteristics and clinical implications in gastric cancer through single-cell resolution analysis

Background: Gastric cancer is a highly prevalent malignant neoplasm. Metabolic reprogramming is intricately linked to both tumorigenesis and cancer immune evasion. The advent of single-cell RNA sequencing technology provides a novel perspective for evaluating cellular metabolism. This study aims to comprehensively investigate the metabolic pathways of various cell types in tumor and normal samples at high resolution and delve into the intricate regulatory mechanisms governing the metabolic activity of malignant cells in gastric cancer. Methods: Utilizing single-cell RNA sequencing data from gastric cancer, we constructed metabolic landscape maps for different cell types in tumor and normal samples. Employing unsupervised clustering, we categorized malignant cells in tumor samples into high and low metabolic subclusters and further explored the characteristics of these subclusters. Results: Our research findings indicate that epithelial cells in tumor samples exhibit significantly higher activity in most KEGG metabolic pathways compared to other cell types. Unsupervised clustering, based on the scores of metabolic pathways, classified malignant cells into high and low metabolic subclusters. In the high metabolic subcluster, it demonstrated the potential to induce a stronger immune response, correlating with a relatively favorable prognosis. In the low metabolic subcluster, a subset of cells resembling cancer stem cells (CSCs) was identified, and its prognosis was less favorable. Furthermore, a set of risk genes associated with this subcluster was discovered. Conclusion: This study reveals the intricate regulatory mechanisms governing the metabolic activity of malignant cells in gastric cancer, offering new perspectives for improving prognosis and treatment strategies.

Mini-Review: Current Bladder Cancer Treatment-The Need for Improvement

Bladder cancer is the tenth most common cancer and is a significant burden on health care services worldwide, as it is one of the most costly cancers to treat per patient. This expense is due to the extensive treatment and follow-ups that occur with costly and invasive procedures. Improvement in both treatment options and the quality of life these interventions offer has not progressed at the rates of other cancers, and new alternatives are desperately needed to ease the burden. A more modern approach needs to be taken, with urinary biomarkers being a positive step in making treatments more patient-friendly, but there is still a long way to go to make these widely available and of a comparable standard to the current treatment options. New targets to hit the major signalling pathways that are upregulated in bladder cancer, such as the PI3K/AkT/mTOR pathway, are urgently needed, with only one drug approved so far, Erdafitinib. Immune checkpoint inhibitors also hold promise, with both PD-1 and CDLA-4 antibody therapies approved for use. They effectively block ligand/receptor binding to block the immune checkpoint used by tumour cells. Other avenues must be explored, including drug repurposing and novel biomarkers, which have revolutionised this area in other cancers.