Two Similar Signatures for Predicting the Prognosis and Immunotherapy Efficacy of Stomach Adenocarcinoma Patients

FGL1 Promotes Tumor Immune Escape in Stomach Adenocarcinoma via the Notch Signaling Pathway

Immune escape is the major reason for immunotherapy failure in stomach adenocarcinoma (STAD). We tried to reveal the underlying mechanism of FGL1 influencing STAD in this study. Bioinformatics analyses were conducted to analyze the expression of FGL1, the signaling pathways affected by FGL1, and the relation between FGL1 and immune cell infiltration. Quantitative real-time PCR (qRT-PCR), cell counting kit-8 assay, colony formation assay, flow cytometry and Transwell assay were adopted to analyze FGL1 expression, cell viability, cell proliferation, cell apoptosis, and cell invasion, respectively. Enzyme-linked immunosorbent assay, lactate dehydrogenase method, qRT-PCR and Western blot were adopted to reveal proinflammatory cytokine expression, cytotoxicity and mRNA and protein expression of the Notch signaling-related genes, respectively, after co-culture of STAD cells and CD8+T cells. Nude mice experiment was conducted to validate the results obtained above. FGL1 expressed highly in STAD and could activate the Notch signaling pathway, and it was negatively correlated with CD8+T cell infiltration. Cell experiments confirmed that high expression of FGL1 facilitated proliferation and hindered apoptosis of STAD cells. Knockdown of FGL1 could facilitate expression of pro-inflammatory factors and the cytotoxicity of CD8+T cells in co-culture system of STAD and CD8+ T cells. Knockdown of FGL1 could suppress the expression of the Notch signaling pathway-related genes, and the addition of Notch inhibitor proved that FGL1 promoted immune escape via the Notch signaling pathway. This study investigated the influence of FGL1 on STAD immune escape and demonstrated that FGL1 inhibited CD8+ T cell activation by activating the Notch signaling pathway and thus promoted tumor immune escape in STAD, providing a new potential diagnostic marker and therapeutic target for the immunotherapy of STAD patients.

Transcriptome sequencing and miRNA-mRNA network construction in exosome of macrophage M2 in stomach adenocarcinoma

BACKGROUND

Stomach adenocarcinoma (STAD) is the most common histological type of gastric cancer (GC). Macrophages are an essential part of the tumor microenvironment. We attempted to search for potential molecular markers associated with macrophages, which might be helpful for STAD diagnosis and treatment.

METHODS

Firstly, exosome in macrophages was extracted for RNA sequencing to identify differentially expressed microRNAs (miRNAs) (DEmiRNAs). Then, DEmiRNAs and differentially expressed mRNAs (DEmRNAs) were screened in the Cancer Genome Atlas (TCGA) database. The miRNAs related to macrophage M2 polarization were obtained by intersecting the DEmiRNAs obtained from the sequencing data and TCGA data. Using the Pearson correlation coefficient method, the mRNAs significantly related to macrophage M2 were screened out, followed by construction of the macrophage M2-miRNA-mRNA network. Subsequently, real-time-polymerase chain reaction (RT-PCR) and online datasets were applied to validate the expression of DEmiRNAs and DEmRNAs.

RESULTS

A total of 6 DEmiRNAs were identified in RNA sequencing; 59 DEmiRNAs and 1838 DEmRNAs were identified in TCGA database. Among which, a common miRNA (hsa-miR-133a-3p) associated with the M2 polarization of macrophages was identified. Fifteen common mRNAs were obtained between DEmRNAs and mRNAs targeted by DEmiRNAs. Eventually, a core macrophage M2-1 down-regulated miRNA-7 and up-regulated mRNAs network was constructed, including hsa-miR-133a-3p, SLC39A1, TTYH3, HAVCR2, TPM3, XPO1, POU2F1, and MMP14. The expression of miRNA and mRNAs was in line with the validation results of RT-PCR and online datasets.

CONCLUSION

In this study, the screening of biomarkers in exosome of macrophage M2 may contribute to the prognosis of STAD patients.

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.

Pan-cancer analysis reveals interleukin-17 family members as biomarkers in the prediction for immune checkpoint inhibitor curative effect

Background

The interleukin-17 (IL-17) family contains six homologous genes, IL-17A to IL-17F. Growing evidence indicates that dysregulated IL-17 family members act as major pathogenic factors in the early and late stages of cancer development and progression. However, the prevalence and predictive value of IL-17 for immune checkpoint inhibitor (ICI) therapeutic effectiveness in multiple tumor types remain largely unknown, and the associations between its expression levels and immunotherapy-associated signatures also need to be explored.

Methods

The pan-cancer dataset in The Cancer Genome Atlas (TCGA) was downloaded from UCSC Xena (http://xena.ucsc.edu/). The immunotherapeutic cohorts included IMvigor210, which were obtained from the Gene Expression Omnibus database and included in a previously published study. Other datasets, namely, the GEO dataset and PRECOG, GEO, and METABRIC databases, were also included. In 33 TCGA tumor types, a pan-cancer analysis was carried out including their expression map, clinical risk assessment, and immune subtype analysis, along with their association with the stemness indices, tumor microenvironment (TME) in pan-cancer, immune infiltration analysis, ICI-related immune indicators, and drug sensitivity. RT-PCR was also carried out to verify the gene expression levels among MCF-10A and MCF-7 cell lines.

Results

The expression of the IL-17 family is different between tumor and normal tissue in most cancers, and consistency has been observed between gene activity and gene expression. RT-PCR results show that the expression differences in the IL-17 family of human cell (MCF-10A and MCF-7) are consistent with the bioinformatics differential expression analysis. Moreover, the expression of the IL-17 family can be a sign of patients’ survival prognosis in some tumors and varies in different immune subtypes. Moreover, the expression of the IL-17 family presents a robust correlation with immune cell infiltration, ICI-related immune indicators, and drug sensitivity. High expression of the IL-17 family is significantly related to immune-relevant pathways, and the low expression of IL-17B means a better immunotherapeutic response in BLCA.

Conclusion

Collectively, IL-17 family members may act as biomarkers in predicting the prognosis of the tumor and the therapeutic effects of ICIs, which provides new guidance for cancer treatment.

Construction of ovarian metastasis-related immune signature predicting prognosis of gastric cancer patients

BACKGROUND

Ovarian metastasis (OM) results in poor survival of gastric cancer (GC) patients. While immunotherapy has emerged as a promising approach for late-stage GC, validated immune-related prognostic signatures still remain in need. In this study, we constructed an ovarian metastasis- and immune-related prognostic signature (OMIRPS), characterized the molecular and immune features of OMIRPS-categorized subgroups and predicted their potential response to immunotherapy.

METHODS

Three individual cohorts were used to construct and evaluate OMIRPS: RNA-seq of matched primary GC and OM from Fudan University Shanghai Cancer Center (FUSCC) (discovery cohort, n = 4), The Cancer Genome Atlas (TCGA) (training cohort, n = 544) and GSE84437 (validation cohort, n = 433). Differentially expressed genes (DEGs) identified between primary GC and OM and immune-related genes (IRGs) from the ImmPort and InnateDB databases were used to identify immune-related prognostic hub genes, which were further used to construct OMIRPS by using LASSO regression analysis. Prognosis, molecular characteristics, immune features, and differential immunotherapy efficacy between different OMIRPS subgroups were analyzed.

RESULTS

Functional analyses of DEGs revealed the significance of immune-related signatures and pathways in the OM. Immune-related prognostic hub genes including TNFRSF18, CARD11, BCL11B, NRP1, BNIP3L, and ATF3 were utilized to construct OMIRPS, which was identified as an independent prognostic factor. Comprehensive analyses unveiled the distinctive molecular and immune characteristics of OMIRPS-high and -low subgroup in regard to enriched pathways, mutation rate, tumor mutation burden, microsatellite instability status, infiltrated immune cell, immune exclusion score, and the prediction of immunotherapy efficacy. Additionally, OMIRPS was associated with Immune Subtypes with borderline significance.

CONCLUSIONS

RNA-seq of paired primary and ovarian metastatic tumors unveiled the significance of immune-related pathways and tumor immune microenvironment in OM. OMIRPS served as a promising biomarker to predict the prognosis of GC patients and distinguish the molecular features, immune characteristics, and efficacy of immunotherapy between different subgroups.