Integrative analysis of cancer-associated fibroblast signature in gastric cancer

Development and validation of a cancer-associated fibroblast gene signature-based model for predicting immunotherapy response in colon cancer

The efficacy of immune checkpoint inhibitors in colon cancer has been established, and there is an urgent need to identify new molecular markers for colon cancer immunotherapy to guide clinical decisions. Using the "EPIC" and "MCPcounter" R packages to conduct cancer-associated fibroblast (CAF) infiltration scoring on colon cancer samples from the TCGA database and the GEO database, the WGCNA analysis was performed on the two databases' samples based on the CAF infiltration scores to screen for CAF-related genes. LASSO regression analysis was used to construct a risk model with these genes. Comprehensive bioinformatics analysis was conducted on the constructed model to evaluate the stability of its prediction of CAF infiltration abundance and the stability of its prediction of immunotherapy efficacy. The newly constructed risk model could well reflect the abundance of CAF infiltration in colon cancer, with a correlation coefficient of 0.91 in the training cohort TCGA-COAD and 0.88 in the validation cohort GSE39582. GSEA analysis revealed that CAF is closely related to functions associated with extracellular matrix remodeling. The constructed risk model can predict the efficacy of immunotherapy in colon cancer well, with the high-risk group showing significantly poorer immunotherapy response than the low-risk group, with an expected effective rate of immunotherapy of 68 vs. 24% in the training group (P < 0.001) and 64 vs. 26% in the validation group (P < 0.001). The AUC value for predicting immunotherapy response by the risk model in the training group was 0.780 (95% CI 0.736-0.820), and in the validation group, the AUC value was 0.774 (95% CI 0.735-0.810). Drug sensitivity analysis showed that the expected chemotherapeutic effect in the low-risk group was superior to that in the high-risk group. CAF is associated with immunosuppression and drug resistance. Predicting the efficacy of immunotherapy in colon cancer based on the abundance of CAF infiltration is a feasible approach. For the high-risk population identified by our model, clinical consideration should be given to prioritizing non-immunotherapy approaches to avoid potential risks associated with immunotherapy.

Dasatinib demonstrates efficacy in organoid derived paclitaxel-resistant Trp53/Cdh1-deficient mouse gastric adenocarcinoma with peritoneal metastasis

Gastric cancer peritoneal metastasis (GCPM) typically indicates a poor clinical prognosis and is frequently observed in diffuse gastric cancer (GC) patients with CDH1 loss of function. GCPM characterized for its aggressiveness and resistance to chemotherapy, most notably paclitaxel (PTX), poses significant treatment challenges. Previously, no mouse gastric adenocarcinoma (MGA) cell lines with Trp53 (encoding mouse p53) and Cdh1 (encoding mouse E-cadherin) mutations and a high potential for peritoneal metastasis in mice have been established. Here, we derived a mouse GC cell line, called MTC, from subcutaneously transplanted mouse Trp53-/-Cdh1-/- GC organoids. Through matching the short tandem repeat profile of MTC with those in current cell banks, we verified the uniqueness of MTC. Furtherly, we confirmed the features of MTC by detecting the expression of p53, E-cadherin, and pan-CK. After long-term exposure of the original MTC line to PTX, we developed a more aggressive, PTX-resistant cell line, termed MTC-R. Compared with MTC, MTC-R demonstrated enhanced tumorigenicity and high potential for peritoneal metastasis in subcutaneous and intraperitoneal tumour models both in BALB/c nude mice and C57BL/6 J mice. Transcriptome analysis revealed the ECM‒receptor interaction pathway activation during the development of PTX resistance, and dasatinib (DASA) was identified as a potential drug targeting this pathway. DASA showed promise in ameliorating disease progression and improving overall survival in MTC-R GCPM model in C57BL/6 J mice. Overall, we established a novel MGA cell line with Trp53 and Cdh1 mutations and its PTX-resistant variant and demonstrated the efficacy of DASA in treating PTX-resistant GCPM.

The Role of MATN3 in Cancer Prognosis and Immune Infiltration Across Multiple Tumor Types

Background: MATN3 is a member of the matrix protein family and is involved in the regulation of osteoarthritis as well as the development of gastric cancer. We investigated the role of MATN3 in pan-cancer and validated this result by in vitro experiments. Material and Methods: We applied multiple databases to explore the expression of MATN3 in 33 types of tumors. Kaplan-Meier survival analysis is performed to understand the effect of MATN3 on Prognostic value in patients with different cancer types. The TIMER database was applied to explore the relationship between MATN3 and immune checkpoint genes, immunomodulatory genes, and immune infiltration, the Sanger box was applied to explore the relationship between MATN3 and methylation, the Genomic Cancer Analysis database was utilized to explore the relationship between MATN3 expression and pharmacological sensitivity, and the STRING database was used to explore the co-expressed genes and to complete the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Data from The Cancer Genome Atlas as well as Genotype-Tissue Expression databases were statistically analyzed and visualized using the R software. Immunohistochemistry and Western blotting for detection of MATN3 expression. CCK-8 and clone formation were used to detect cell proliferation, Wound-healing assay and transwell invasion were used to detect cell migration and invasion ability. Results: MATN3 is overexpressed in most cancer types, indicating a poorer prognosis. It is closely linked to methylation, immunomodulatory genes, and immune checkpoint genes, contributing to immune infiltration in various cancer types. In vitro experiments showed that silencing MATN3 inhibited cell proliferation, migration, and invasion ability. Conclusions: MATN3 is involved in the immune infiltration of cancer and affects the prognosis of many cancer types, and can be used as an immune as well as prognostic biomarker for pan-cancer.

Training and experimental validation a novel anoikis- and epithelial‒mesenchymal transition-related signature for evaluating prognosis and predicting immunotherapy efficacy in gastric cancer

Anoikis resistance and improper activation of epithelial‒mesenchymal transition (EMT) are critical factors in tumor metastasis and progression. Despite their interaction, the combined impact of anoikis and EMT on prognosis and immunotherapy in gastric cancer remains underexplored. In this study, we identified 354 anoikis- and EMT-related genes (AERGs) through Venn analysis and performed unsupervised clustering to classify gastric cancer patients into two molecular clusters: A and B. Molecular cluster A showed poor prognosis and an immunosuppressive tumor microenvironment, suggesting a "cold tumor" phenotype. Then, a novel AERG-related prognostic model comprising CD24, CRYAB, MMP11, MUC4, PRKAA2, SERPINE1, SKP2, and TP53 was constructed and validated, accurately predicting the 1-, 3-, and 5-year survival rates of gastric cancer patients. Multivariate analysis revealed that the AERG-related risk score was an independent prognostic factor (hazard ratio = 1.651, 95% confidence interval = 1.429-1.907, P<0.001). Further studies demonstrated that, compared to the high-risk group, the low-risk group exhibited higher CD8+ T cell infiltration, tumor mutational burden, immunophenoscores, and lower tumor immune dysfunction and exclusion scores, indicating potential sensitivity to immunotherapy. RT‒qPCR and immunohistochemical staining validated the expression levels of the model's molecular markers. Overall, our AERG-related model shows promise for predicting outcomes and guiding the selection of tailored and precise therapies for gastric cancer patients.

Investigating MATN3 and ASPN as novel drivers of gastric cancer progression via EMT pathways

Gastric cancer (GC) is a leading cause of cancer-related deaths globally, necessitating the identification of novel therapeutic targets. This study investigates the roles of MATN3 and ASPN in GC progression via the epithelial-mesenchymal transition (EMT) pathway. Analysis of the Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD) dataset revealed that both MATN3 and ASPN are significantly upregulated in GC tissues and correlate with poor patient survival. Protein-protein interaction and co-expression analyses confirmed a direct interaction between MATN3 and ASPN, suggesting their synergistic role in EMT activation. Functional assays demonstrated that MATN3 promotes GC cell proliferation, migration, and invasion, while its knockdown inhibits these malignant behaviors and induces apoptosis. ASPN overexpression further amplified these oncogenic effects. In vivo, studies in a mouse model corroborated that co-overexpression of MATN3 and ASPN enhances tumor growth and metastasis. These findings highlight the MATN3-ASPN axis as a potential therapeutic target in GC, offering new insights into the molecular mechanisms driving GC progression.

Matrisomics: Beyond the extracellular matrix for unveiling tumor microenvironment

The matrisome, a group of proteins constituting or interacting with the extracellular matrix (ECM), has garnered attention as a potent regulator of cancer progression. An increasing number of studies have focused on cancer matrisome utilizing diverse -omics approaches. Here, we present diverse patterns of matrisomal populations within cancer tissues, exploring recent -omics studies spanning different '-omics' levels (epigenomics, genomics, transcriptomics, and proteomics), as well as newly developed sequencing techniques such as single-cell RNA sequencing and spatial transcriptomics. Some matrisome genes showed uniform patterns of upregulated or downregulated expression across various cancers, while others displayed different expression patterns according to the cancer types. This matrisomal dysregulation in cancer was further examined according to their originating cell type and spatial location in the tumor tissue. Experimental studies were also collected to demonstrate the identified roles of matrisome genes during cancer progression. Interestingly, many studies on cancer matrisome have suggested matrisome genes as effective biomarkers in cancer research. Although the specific mechanisms and clinical applications of cancer matrisome have not yet been fully elucidated, recent techniques and analyses on cancer matrisomics have emphasized their biological importance in cancer progression and their clinical implications in deciding the efficacy of cancer treatment.

The fibro-adipogenic progenitor APOD+DCN+LUM+ cell population in aggressive carcinomas

We identified a progenitor cell population highly enriched in samples from invasive and chemo-resistant carcinomas, characterized by a well-defined multigene signature including APOD, DCN, and LUM. This cell population has previously been labeled as consisting of inflammatory cancer-associated fibroblasts (iCAFs). The same signature characterizes naturally occurring fibro-adipogenic progenitors (FAPs) as well as stromal cells abundant in normal adipose tissue. Our analysis of human gene expression databases provides evidence that adipose stromal cells (ASCs) are recruited by tumors and undergo differentiation into CAFs during cancer progression to invasive and chemotherapy-resistant stages.

The MexTAg collaborative cross: host genetics affects asbestos related disease latency, but has little influence once tumours develop

Objectives: This study combines two innovative mouse models in a major gene discovery project to assess the influence of host genetics on asbestos related disease (ARD). Conventional genetics studies provided evidence that some susceptibility to mesothelioma is genetic. However, the identification of host modifier genes, the roles they may play, and whether they contribute to disease susceptibility remain unknown. Here we report a study designed to rapidly identify genes associated with mesothelioma susceptibility by combining the Collaborative Cross (CC) resource with the well-characterised MexTAg mesothelioma mouse model. Methods: The CC is a powerful mouse resource that harnesses over 90% of common genetic variation in the mouse species, allowing rapid identification of genes mediating complex traits. MexTAg mice rapidly, uniformly, and predictably develop mesothelioma, but only after asbestos exposure. To assess the influence of host genetics on ARD, we crossed 72 genetically distinct CC mouse strains with MexTAg mice and exposed the resulting CC-MexTAg (CCMT) progeny to asbestos and monitored them for traits including overall survival, the time to ARD onset (latency), the time between ARD onset and euthanasia (disease progression) and ascites volume. We identified phenotype-specific modifier genes associated with these traits and we validated the role of human orthologues in asbestos-induced carcinogenesis using human mesothelioma datasets. Results: We generated 72 genetically distinct CCMT strains and exposed their progeny (2,562 in total) to asbestos. Reflecting the genetic diversity of the CC, there was considerable variation in overall survival and disease latency. Surprisingly, however, there was no variation in disease progression, demonstrating that host genetic factors do have a significant influence during disease latency but have a limited role once disease is established. Quantitative trait loci (QTL) affecting ARD survival/latency were identified on chromosomes 6, 12 and X. Of the 97-protein coding candidate modifier genes that spanned these QTL, eight genes (CPED1, ORS1, NDUFA1, HS1BP3, IL13RA1, LSM8, TES and TSPAN12) were found to significantly affect outcome in both CCMT and human mesothelioma datasets. Conclusion: Host genetic factors affect susceptibility to development of asbestos associated disease. However, following mesothelioma establishment, genetic variation in molecular or immunological mechanisms did not affect disease progression. Identification of multiple candidate modifier genes and their human homologues with known associations in other advanced stage or metastatic cancers highlights the complexity of ARD and may provide a pathway to identify novel therapeutic targets.

Identification of a novel cancer-associated fibroblasts gene signature based on bioinformatics analysis to predict prognosis and therapeutic responses in breast cancer

Cancer-associated fibroblasts (CAFs) provide suitable conditions for growth of tumor cell and facilitate tumor progression. Hence, we aimed to identify a CAFs-related gene signature associated with the prognosis of patients with breast cancer (BRCA). We downloaded datasets from Gene Expression Omnibus (GEO) and confirmed the correlation between CAFs infiltration scores and prognosis. By performing weighted gene co-expression network analysis (WGCNA) and Lasso Cox regression analysis, we constructed a four-gene (COL5A3, FN1, POSTN, and RARRES2) prognostic CAFs signature model. Based on the median risk score of CAFs, patients with BRCA were divided into high- and low-risk groups. Compared with low-risk group, patients in high-risk group exhibited a poor prognosis and limited response to immunotherapy. Furthermore, patients with high CAFs risk scores were found to have a detrimental prognosis due to the induction of immunosuppressive cell infiltration, resulting in an immunosuppressive tumor microenvironment. Importantly, we found that CAFs overexpressing FN1 and POSTN significantly promoted the wound healing and invasion ability of tumor cells in vitro validation. Taking together, we identified a four-gene prognostic CAFs signature, which was proven to be a reliable indicator for prognosis and therapeutic efficacy in patients with BRCA. This study provided evidence for novel CAFs-based stromal therapy.

Innate immune cells: Key players of orchestra in modulating tumor microenvironment (TME)

The tumor microenvironment (TME) with vital role in cancer progression is composed of various cells such as endothelial cells, immune cells, and mesenchymal stem cells. In particular, innate immune cells such as macrophages, dendritic cells, myeloid-derived suppressor cells, neutrophils, innate lymphoid cells, γδT lymphocytes, and natural killer cells can either promote or suppress tumor progression when present in the TME. An increase in research on the cross-talk between the TME and innate immune cells will lead to new approaches for anti-tumoral therapeutic interventions. This review primarily focuses on the biology of innate immune cells and their main functions in the TME. In addition, it summarizes several innate immune-based immunotherapies that are currently tested in clinical trials.