Significance of Tumor Mutation Burden Combined With Immune Infiltrates in the Progression and Prognosis of Advanced Gastric Cancer

Identification of SLC22A17 DNA methylation hotspot as a potential biomarker in cutaneous melanoma

BACKGROUND

Cancer onset and progression are driven by genetic and epigenetic alterations leading to oncogene activation and the silencing of tumor suppressor genes. Among epigenetic mechanisms, DNA methylation (methDNA) is gaining growing interest in cancer. Promoter hypomethylation is associated with oncogene activation while intragenic methDNA can be involved in transcriptional elongation, alternative spicing, and the activation of cryptic start sites. Several genes involved in the modulation of the tumor microenvironment are regulated by methDNA, including the Solute Carrier Family 22 Member 17 (SLC22A17), which is involved in iron trafficking and extracellular matrix remodeling cooperating with the Gelatinase-Associated Lipocalin (NGAL) ligand. However, the exact role of intragenic methDNA in cancer has not been fully investigated. Therefore, the aim of the present study is to explore the role of methDNA in the regulation of SLC22A17 in cutaneous melanoma (CM), used as a tumor model.

METHODS

Correlation and differential analyses between SLC22A17 expression and methDNA were performed using the data contained in The Cancer Genome Atlas and Gene Expression Omnibus databases. Functional studies on melanoma cell lines treated with 5-Azacytidine (5-Aza) were conducted to assess the correlation between methDNA and SLC22A17 expression. A validation study on the diagnostic potential of the in silico-identified SLC22A17 methDNA hotspot was finally performed by analyzing tissue samples obtained from CM patients and healthy controls.

RESULTS

The computational analyses revealed that SLC22A17 was significantly downregulated in CM, and its expression was related to promoter hypomethylation and intragenic hypermethylation. Moreover, SLC22A17 overexpression and hypermethylation of two intragenic methDNA hotspots were associated with a better clinical outcome in CM patients. The correlation between SLC22A17 methDNA and expression was confirmed in 5-Aza-treated cells. In agreement with in silico analyses, the SLC22A17 promoter methylation hotspot showed higher methDNA levels in CM samples compared to nevi. In addition, the methDNA levels of this hotspot were positively correlated with advanced CM.

CONCLUSIONS

The SLC22A17 methDNA hotspot could represent a promising biomarker for CM, highlighting the regulatory role of methDNA on SLC22A17 expression. These results pave the way for the identification of novel epigenetic biomarkers and therapeutic targets for the management of CM patients.

FOXM1 Upregulates O-GlcNAcylation Level Via The Hexosamine Biosynthesis Pathway to Promote Angiogenesis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) presents significant challenges in treatment and prognosis because of its aggressive nature and high metastatic potential. This study aims to investigate the role of the hexosamine biosynthesis pathway (HBP) and its association with HCC progression and prognosis. We identified SPP1 and FOXM1 as hub genes within the HBP pathway, showing their correlation with poor prognosis and late-stage progression. In addition, the analysis uncovered the complex participation of the HBP pathway in nutrients and oxygen reactions, PI3K-AKT signaling, AMPK activation, and angiogenesis regulation. The disruption of these pathways is pivotal in influencing the growth and progression of HCC. Targeting the HBP presents a promising therapeutic approach to modulate the tumor microenvironment, thereby enhancing the efficacy of immunotherapy. In addition, FOXM1 was identified as the HBP pathway regulator, influencing cellular O-GlcNAcylation level and VEGF secretion, thereby promoting angiogenesis in HCC. Inhibition of O-GlcNAcylation significantly hindered angiogenesis, which is suggested as a potential avenue for therapeutic intervention. Our research demonstrates the practicality of using the HBP-related gene as a prognostic marker in liver cancer patients and suggests targeting FOXM1 as a novel avenue for personalized therapy.

FOXN2, identified as a novel biomarker in serum, modulates the transforming growth factor-beta signaling pathway through its interaction with partitioning defective 6 homolog alpha, contributing to the pathogenesis of gastric cancer

BACKGROUND AND OBJECTIVE

Dysregulated expression of Forkhead Box N2 (FOXN2) has been detected in various cancer types. However, the underlying mechanisms by which FOXN2 contributes to the onset and progression of gastric cancer (GC) remain largely unexplored. This study aimed to elucidate the potential role of FOXN2 within GC, its downstream molecular mechanisms, and its feasibility as a novel serum biomarker for GC.

METHODS

Tissue samples from GC patients and corresponding non-cancerous tissues were collected. Peripheral blood samples were obtained from GC patients and healthy controls. The expression of FOXN2 was determined using quantitative real-time PCR, western blotting, and immunohistochemistry. The expression of FOXN2 in GC cells was modulated by transfection with small interfering RNA (siRNA) or the pcDNA 3.1 expression vector. Cell proliferation was assessed using the Cell Counting Kit-8 and 5-ethynyl-2'-deoxyuridine incorporation assays. The migratory and invasive capacities of cells were evaluated by Transwell assays, apoptosis rates were measured by flow cytometry, and the expression of proliferative, apoptotic, and epithelial-mesenchymal transition (EMT) markers were assessed by western blot analysis.

RESULTS

FOXN2 was found to be overexpressed in the serum, tissues, and cells of GC, correlating with distant metastasis and TNM staging. FOXN2 demonstrated diagnostic value in differentiating GC patients from healthy individuals, with higher levels of FOXN2 being indicative of poorer survival rates. Silencing FOXN2 in vitro inhibited the proliferation, invasion, migration, and EMT of GC cells, while promoting apoptosis. FOXN2 was shown to regulate the transforming growth factor-beta (TGFβ) receptor signaling pathway in GC cells via its interaction with Partitioning Defective 6 Homolog Alpha (PARD6A).

CONCLUSION

In summary, our data suggest that FOXN2 acts as an oncogenic factor in GC, modulating the TGFβ pathway by binding to PARD6A, thereby influencing gastric carcinogenesis. This study underscores the functional significance of FOXN2 as a potential serum biomarker and therapeutic target in GC.

The macrophage-associated prognostic gene ANXA5 promotes immunotherapy resistance in gastric cancer through angiogenesis

Gastric cancer (GC) remains a predominant form of malignant tumor globally, necessitating innovative non-surgical therapeutic approaches. This investigation aimed to delineate the expression landscape of macrophage-associated genes in GC and to evaluate their prognostic significance and influence on immunotherapeutic responsiveness. Utilizing the CellMarker2.0 database, we identified 69 immune cell markers with prognostic relevance in GC, including 12 macrophage-specific genes. A Weighted Gene Co-Expression Network Analysis (WGCNA) isolated 3,181 genes correlated with these macrophage markers. The Cancer Genome Atlas (TCGA-STAD) dataset was employed as the training set, while data from the GSE62254 served as the validation cohort. 13 genes were shortlisted through LASSO-Cox regression to formulate a prognostic model. Multivariable Cox regression substantiated that the calculated risk score serves as an imperative independent predictor of overall survival (OS). Distinct macrophage infiltration profiles, pathway associations, treatment susceptibilities, and drug sensitivities were observed between high- and low-risk groups. The preliminary validation of ANXA5 in predicting the survival rates of GC patients at 1 year, 3 years, and 5 years, as well as its expression levels were higher and role in promoting tumor angiogenesis in GC through immunohistochemistry and angiogenesis experiments. In summary, macrophage-related genes were potentially a novel crosstalk mechanism between macrophages and endothelial cells in the tumor microenvironment, and the interplay between inflammation and angiogenesis might have also offered new therapeutic targets, providing a new avenue for personalized treatment interventions.

Comprehensive analysis of disulfidptosis related genes and prognosis of gastric cancer

BACKGROUND

Gastric cancer (GC) is a common malignant tumor of the digestive system. Disulfidptosis is a new programmed cell death mechanism, although its specific mechanism in GC is incompletely understood.

AIM

In this study, we used bioinformatics analysis to explore a disulfidptosis-based predictive model related to GC prognosis and to identify potential therapeutic targets and sensitive drugs for GC.

METHODS

We extracted GC-related data from The Cancer Genome Atlas and Gene Expression Omnibus databases. R software (version 4.2.1) was used for correlation analysis.

RESULTS

Through the above analysis, we found that the disulfidptosis related gene may be related to the prognosis of GC. Six genes, namely, PLS3, GRP, APOD, SGCE, COL8A1, and VAMP7, were found to constitute a predictive model for GC prognosis. APOD is a potential therapeutic target for treating GC. Bosutinib and other drugs are sensitive for the treatment of GC.

CONCLUSION

The results of this study indicate that disulfidptosis is related to the prognosis and treatment of GC, while APOD represents a potential therapeutic target for GC.

Genetically engineered neural stem cells expressing cytosine deaminase and interferon-beta enhanced T cell-mediated antitumor immunity against gastric cancer in a humanized mouse model

AIMS

Gastric cancer (GC) is an invasive, fatal disease with a poor prognosis. Gene-directed enzyme prodrug therapy via genetically engineered neural stem cells (GENSTECs) has been widely studied in various malignancies, such as breast, ovarian, and renal cancer. In this study, the human neural stem cells expressing cytosine deaminase and interferon beta (HB1.F3.CD.IFN-β) cells were applied to convert non-toxic 5-fluorocytosine to cytotoxic 5-fluorouracil and secrete IFN-β.

MATERIALS AND METHODS

Human lymphokine-activated killer cells (LAKs) were generated by stimulating human peripheral blood mononuclear cells (PBMCs) by interleukin-2, and we evaluated the cytotoxic activity and migratory ability of LAKs co-cultured with GNESTECs or their conditioned media in vitro. A GC-bearing human immune system (HIS) mouse model was generated by transplanting human PBMCs followed by subcutaneous engraftment of MKN45 cells in NSG-B2m mice to evaluate the involvement of T cell-mediated anti-cancer immune activity of GENSTECs.

KEY FINDINGS

In vitro studies showed the presence of HB1.F3.CD.IFN-β cells facilitated the migration ability of LAKs to MKN45 cells and activated their cytotoxic potential. In MKN45-xenografted HIS mice, treatment with HB1.F3.CD.IFN-β cells resulted in increased cytotoxic T lymphocyte (CTL) infiltration throughout the tumor, including the central area. Moreover, the group treated to HB1.F3.CD.IFN-β showed increased granzyme B expression in the tumor, eventually enhancing the tumor-killing potential of CTLs and significantly delaying tumor growth.

SIGNIFICANCE

These results indicate that the HB1.F3.CD.IFN-β cells exert anti-cancer effects on GC by facilitating the T cell-mediated immune response, and GENSTECs are a promising therapeutic strategy for GC.

Genomic and transcriptomic profiling indicates the prognosis significance of mutational signature for TMB-high subtype in Chinese patients with gastric cancer

INTRODUCTION

Gastric cancer (GC)is the third leading cause of cancer-related deaths in China and immunotherapy emerging as a revolutionary treatment for GC recently. Tumor mutational burden (TMB) is a predictive biomarker of immunotherapy in multiple cancers. However, the prognostic significance and subtype of TMB in GC is not fully understood.

OBJECTIVES

This study aims to evaluate the prognostic value of TMB in Chinese GC and further classify TMB-high GC (GCTMB-H) patients combing with mutational signatures.

METHODS

Genomic profiling of 435 cancer-gene panel was performed using 206 GC samples from Chinese people. Actionable genetic alterations were compared across all the samples to generate actionable subtyping. The prognostic value of TMB in Chinese GC was evaluated. Mutational signatures were analyzed on TMB-H subtype to stratify the prognosis of TMB. Transcriptomic analysis was applied to compare the distributed immunocytes among different subtypes.

RESULTS

88.3% (182/206) of GC samples had at least one mutation, while 45.1% (93/206) had at least one somatic copy number alteration (SCNA). 29.6% (61/206) of GC samples were TMB-H, including 13 MSI-H and 48 MSS tumors. According to distinct genetic alteration profiles of 69 actionable genes, we classified GC samples into eight molecular subtypes, including TMB-H, ERBB2 amplified, ATM mutated, BRCA2 mutated, CDKN2A/B deleted, PI3KCA mutated, KRAS mutated, and less-mutated subtype. TMB-H subtype presented a remarkable immune-activated phenotype as determined by transcriptomic analysis that was further validated in the TCGA GC cohort. GCTMB-H patients exhibited significantly better survival (P = 0.047). But Signature 1-high GCTMB-H patients had relatively worse prognosis (P = 0.0209, HR = 2.571) than Signature 1-low GCTMB-H patients from Chinese GC cohort, also validated in TCGA GC cohort, presenting highly activated carbohydrate, fatty acid or lipid metabolism.

CONCLUSION

The Signature 1-high GCTMB-H could be a marker of poor prognosis and is associated with metabolism disorder.

Lipocalin 2 receptors: facts, fictions, and myths

The human 25-kDa Lipocalin 2 (LCN2) was first identified and purified as a protein that in part is associated with gelatinase from neutrophils. This protein shows a high degree of sequence similarity with the deduced sequences of rat α2-microglobulin-related protein and the mouse protein 24p3. Based on its typical lipocalin fold, which consists of an eight-stranded, anti-parallel, symmetrical β-barrel fold structure it was initially thought that LCN2 is a circulating protein functioning as a transporter of small lipophilic molecules. However, studies in Lcn2 null mice have shown that LCN2 has bacteriostatic properties and plays a key role in innate immunity by sequestering bacterial iron siderophores. Numerous reports have further shown that LCN2 is involved in the control of cell differentiation, energy expenditure, cell death, chemotaxis, cell migration, and many other biological processes. In addition, important roles for LCN2 in health and disease have been identified in Lcn2 null mice and multiple molecular pathways required for regulation of Lcn2 expression have been identified. Nevertheless, although six putative receptors for LCN2 have been proposed, there is a fundamental lack in understanding of how these cell-surface receptors transmit and amplify LCN2 to the cell. In the present review we summarize the current knowledge on LCN2 receptors and discuss inconsistencies, misinterpretations and false assumptions in the understanding of these potential LCN2 receptors.

CHSY3 promotes proliferation and migration in gastric cancer and is associated with immune infiltration

BACKGROUND

The glycosyltransferase CHSY3 is a CHSY family member, yet its importance in the context of gastric cancer development remains incompletely understood. The present study was thus developed to explore the mechanistic importance of CHSY3 as a regulator of gastric cancer.

METHODS

Expression of CHSY3 was verified by TCGA, GEO and HPA databases. Kaplan-Meier curve, ROC, univariate cox, multivariate cox, and nomogram models were used to verify the prognostic impact and predictive value of CHSY3. KEGG and GO methods were used to identify signaling pathways associated with CHSY3. TIDE and IPS scores were used to assess the immunotherapeutic value of CHSY3. WGCNA, Cytoscape constructs PPI networks and random forest models to identify key Hub genes. Finally, qRT-PCR and immunohistochemical staining were performed to verify CHSY3 expression in clinical specimens. The ability of CHSY3 to regulate tumor was further assessed by CCK-8 assay and cloning assay, EDU assay, migration assay, invasion assay, and xenograft tumor model analysis.

RESULTS

The expression of CHSY3 was discovered to be abnormally upregulated in GC tissues through TCGA, GEO, and HPA databases, and the expression of CHSY3 was associated with poor prognosis in GC patients. Correlation analysis and Cox regression analysis revealed higher CHSY3 expression in higher T staging, an independent prognostic factor for GC. Moreover, elevated expression of CHSY3 was found to reduce the benefit of immunotherapy as assessed by the TIDE score and IPS score. Then, utilizing WGCNA, the PPI network constructed by Cytoscape, and random forest model, the Hub genes of COL5A2, POSTN, COL1A1, and FN1 associated with immunity were screened. Finally, the expression of CHSY3 in GC tissues was verified by qRT-PCR and immunohistochemical staining. Moreover, the expression of CHSY3 was further demonstrated by in vivo and in vitro experiments to promote the proliferation, migration, and invasive ability of GC.

CONCLUSIONS

The results of this study suggest that CHSY3 is an important regulator of gastric cancer progression, highlighting its promise as a therapeutic target for gastric cancer.

Identification and validation of biomarkers for epithelial-mesenchymal transition-related cells to estimate the prognosis and immune microenvironment in primary gastric cancer by the integrated analysis of single-cell and bulk RNA sequencing data

BACKGROUND

The epithelial-mesenchymal transition (EMT) is associated with gastric cancer (GC) progression and immune microenvironment. To better understand the heterogeneity underlying EMT, we integrated single-cell RNA-sequencing (scRNA-seq) data and bulk sequencing data from GC patients to evaluate the prognostic utility of biomarkers for EMT-related cells (ERCs), namely, cancer-associated fibroblasts (CAFs) and epithelial cells (ECs).

METHODS

scRNA-seq data from primary GC tumor samples were obtained from the Gene Expression Omnibus (GEO) database to identify ERC marker genes. Bulk GC datasets from the Cancer Genome Atlas (TCGA) and GEO were used as training and validation sets, respectively. Differentially expressed markers were identified from the TCGA database. Univariate Cox, least-absolute shrinkage, and selection operator regression analyses were performed to identify EMT-related cell-prognostic genes (ERCPGs). Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses were adopted to evaluate the prognostic utility of the ERCPG signature. An ERCPG-based nomogram was constructed by integrating independent prognostic factors. Finally, we evaluated the correlations between the ERCPG signature and immune-cell infiltration and verified the expression of ERCPG prognostic signature genes by in vitro cellular assays.

RESULTS

The ERCPG signature was comprised of seven genes (COL4A1, F2R, MMP11, CAV1, VCAN, FKBP10, and APOD). Patients were divided into high- and low-risk groups based on the ERCPG risk scores. Patients in the high-risk group showed a poor prognosis. ROC and calibration curves suggested that the ERCPG signature and nomogram had a good prognostic utility. An immune cell-infiltration analysis suggested that the abnormal expression of ERCPGs induced the formation of an unfavorable tumor immune microenvironment. In vitro cellular assays showed that ERCPGs were more abundantly expressed in GC cell lines compared to normal gastric tissue cell lines.

CONCLUSIONS

We constructed and validated an ERCPG signature using scRNA-seq and bulk sequencing data from ERCs of GC patients. Our findings support the estimation of patient prognosis and tumor treatment in future clinical practice.

Exploring the prognostic function of TMB-related prognostic signature in patients with colon cancer

Tumor mutation burden (TMB) level is identified as a useful predictor in multiple tumors including colon adenocarcinoma (COAD). However, the function of TMB related genes has not been explored previously. In this study, we obtained patients' expression and clinical data from The Cancer Genome Atlas (TCGA) and the National Center for Biotechnology Information (NCBI). TMB genes were screened and subjected to differential expression analysis. Univariate Cox and LASSO analyses were utilized to construct the prognostic signature. The efficiency of the signature was tested by using a receiver operating characteristic (ROC) curve. A nomogram was further plotted to assess the overall survival (OS) time of patients with COAD. In addition, we compared the predictive performance of our signature with other four published signatures. Functional analyses indicated that patients in the low-risk group have obviously different enrichment of tumor related pathways and tumor infiltrating immune cells from that of high-risk patients. Our findings suggested that the ten genes' prognostic signature could exert undeniable prognostic functions in patients with COAD, which might provide significant clues for the development of personalized management of these patients.

Targeting FGFR Pathway Is Not an Effective Therapeutic Strategy in Patients with Unselected Metastatic Esophagogastric Cancer Resistant to Trastuzumab

Trastuzumab plus chemotherapy is the standard of care for the first-line treatment of patients with HER2+ advanced esophagogastric (EG) cancer. Nevertheless, patients frequently develop resistance. In preclinical models, we identified the overexpression of Fibroblast Growth Factor Receptor (FGFR) 3 as a mechanism potentially involved in trastuzumab-acquired resistance. FGFR inhibition could be a potential mechanism as a second-line treatment. In this Simon’s two-stage phase 2, single arm study, patients with advanced EG cancer refractory to trastuzumab-containing therapies received pemigatinib, an inhibitor of FGFR. The primary end point was the 12-week progression-free survival rate. Translational analyses were performed on tissue and plasma samples. Eight patients were enrolled in the first stage. Although the 6-week disease control rate was 25%, only one patient achieved a stable disease after 12 weeks of treatment. The trial was discontinued before the second stage. Two out of six evaluable tumor samples expressed FGFR3. No FGFRs amplification was detected. HER2 amplification was lost in three out of eight patients. Three patients had an high Tumor Mutational Burden, and two of them are significantly long-term survivors. These results do not support the therapeutic efficacy of targeting FGFR in unselected patients with advanced EG cancer, who are refractory to trastuzumab-containing therapies.

Engaging stemness improves cancer immunotherapy

Intra-tumoral immune cells promote the stemness of cancer stem cells (CSCs) in the tumor microenvironment (TME). CSCs promote tumor progression, relapse, and resistance to immunotherapy. Cancer stemness induces the expression of neoantigens and neo-properties in CSCs, creating an opportunity for targeted immunotherapies. Isolation of stem-like T cells or retaining stemness in T clonotypes strategies produces exhaustion-resistance T cells with superior re-expansion capacity and long-lasting responses after adoptive cell therapies. Stem cells-derived NK cells may be the next generation of NK cell products for immunotherapy. Here, we have reviewed mechanisms by which stemness factors modulated the immunoediting of the TME and summarized the potentials of CSCs in the development of immunotherapy regimens, including CAR-T cells, CAR-NK cells, cancer vaccines, and monoclonal antibodies. We have discussed the natural or genetically engineered stem-like T cells and stem cell-derived NK cells with increased cytotoxicity to tumor cells. Finally, we have provided a perspective on approaches that may improve the therapeutic efficacy of these novel adoptive cell-based products in targeting immunosuppressive TME.

Gastric adenocarcinoma with high‑level microsatellite instability: A case report

Gastric cancer (GC) ranks fifth on the list of the most common malignancies worldwide. In Peru, gastric neoplasms are considered the second leading cause of mortality among males. Among the molecular subgroups of GC, microsatellite instability presents a favorable prognosis due to its hypermutated phenotype, which activates immunosurveillance. The present study describes the case of a 75-year-old patient, who was admitted in the hospital with a history of upper gastrointestinal bleeding and recurrent hospital admission, due to severe anemia. The patient presented with pale skin, normal vital functions, slight swelling of the lower extremities, and abdominal distention and bloating upon a physical examination. An endoscopic examination revealed an infiltrating circular ulcerated lesion. The histopathological analysis identified a moderately differentiated intestinal-type adenocarcinoma with pathological stage T3N0M0. Tumor genomic profiling demonstrated alterations in 15 different genes with a tumor mutational burden of 28 mutations/Mb. Finally, the patient underwent a partial gastrectomy without pre-operative chemotherapy. After 4 days, the patient presented with post-operative complications for which he was re-operated on. The patient did not survive. To the best of our knowledge, in the present case, pernicious anemia was an early sign of GC and a gastroscopy had to be performed. Furthermore, MutS homolog 3 alterations probably conditioned the presence of multiple frame-shift mutations.

Identification and Validation of a m5C RNA Modification-Related Gene Signature for Predicting Prognosis and Immunotherapeutic Efficiency of Gastric Cancer

Background

5-methylcytosine (m5C) is a major site of RNA methylation modification, and its abnormal modification is associated with the development of gastric cancer (GC). This study aimed to explore the value of m5C-related genes on the prognosis of GC patients through bioinformatics.

Methods

First, m5C-related genes were obtained by nonnegative matrix factorization (NMF) analysis and differentially expressed analysis. The m5C-related model was established and validated in distinct datasets. Moreover, a differential analysis of risk scores according to clinical characteristics was performed. The enrichment analysis was carried out to elucidate the underlying molecular mechanisms. Furthermore, we calculated the differences in immunotherapy and chemotherapy sensitivity between the high- and low-risk groups. Finally, we validated the expression levels of identified model genes by quantitative real-time polymerase chain reaction (qRT-PCR).

Results

A total of five m5C-related subtypes of GC patients in the TCGA database were identified. The m5C-related model was constructed based on APOD, ASCL2, MFAP2, and CREB3L3. Functional enrichment revealed that the m5C-related model might involve in the cell cycle and cell adhesion. Moreover, the high-risk group had a higher abundance of stromal and immune cells in malignant tumor tissues and a lower tumor purity than the low-risk group. The patients in the high-risk group were more sensitive to chemotherapy and had better sensitivity to CTLA4 inhibitors. Furthermore, qRT-PCR results from our specimens verified an over-expression of ASCL2, CREB3L3, and MFAP2 in the cancer cells compared with the normal cells.

Conclusion

A total of five GC subtypes were identified, and a risk model was constructed based on m5C modification.

A molecular classification of gastric cancer associated with distinct clinical outcomes and validated by an XGBoost-based prediction model

Gastric cancer (GC) is a heterogeneous disease and a leading cause of cancer-related deaths. Discovering robust, clinically relevant molecular classifications is critical for guiding personalized therapies for GC. Here, we propose a refined molecular classification scheme for GC using integrated optimal algorithms and multi-omics data. Based on the important features of mRNA, microRNA, and DNA methylation data selected by the multivariate Cox regression model, three subtypes linked to distinct clinical outcomes were identified by combining similarity network fusion and consensus clustering methods. Three subtypes were validated by an extreme gradient boosting machine learning prediction model with 125 differentially expressed genes in multiple independent cohorts. The molecular characteristics of mutation signatures, characteristic gene sets, driver genes, and chemotherapy sensitivity for each subtype were also identified: subtype 1 was associated with favorable prognosis and characterized by high ARID1A and PIK3CA mutations, subtype 2 was associated with a poor prognosis and harbored high recurrent TP53 mutations, and subtype 3 was associated with high CHD1, APOA1 mutations, and a poor prognosis. The proposed three-subtype scheme achieved a better clinical prediction performance (area under the curve value = 0.71) than The Cancer Genome Atlas classification, which may provide a practical subtyping framework to improve the treatment of GC.

A novel necroptosis-related gene index for predicting prognosis and a cold tumor immune microenvironment in stomach adenocarcinoma

Background

Gastric cancer (GC) represents a major global clinical problem with very limited therapeutic options and poor prognosis. Necroptosis, a recently discovered inflammatory form of cell death, has been implicated in carcinogenesis and inducing necroptosis has also been considered as a therapeutic strategy.

Objective

We aim to evaluate the role of this pathway in gastric cancer development, prognosis and immune aspects of its tumor microenvironment.

Methods and results

In this study, we evaluated the gene expression of 55 necroptosis-related genes (NRGs) that were identified via carrying out a comprehensive review of the medical literature. Necroptosis pathway was deregulated in gastric cancer samples (n=375) as compared to adjacent normal tissues (n=32) obtained from the “The Cancer Genome Atlas (TCGA)”. Based on the expression of these NRGs, two molecular subtypes were obtained through consensus clustering that also showed significant prognostic difference. Differentially expressed genes between these two clusters were retrieved and subjected to prognostic evaluation via univariate cox regression analysis and LASSO cox regression analysis. A 13-gene risk signature, termed as necroptosis-related genes prognostic index (NRGPI), was constructed that comprehensively differentiated the gastric cancer patients into high- and low-risk subgroups. The prognostic significance of NRGPI was validated in the GEO cohort (GSE84437: n=408). The NRGPI-high subgroup was characterized by upregulation of 10 genes (CYTL1, PLCL1, CGB5, CNTN1, GRP, APOD, CST6, GPX3, FCN1, SERPINE1) and downregulation of 3 genes (EFNA3, E2F2, SOX14). Further dissection of these two risk groups by differential gene expression analysis indicated involvement of signaling pathways associated with cancer cell progression and immune suppression such as WNT and TGF-β signaling pathway. Para-inflammation and type-II interferon pathways were activated in NRGPI-high patients with an increased infiltration of Tregs and M2 macrophage indicating an exhausted immune phenotype of the tumor microenvironment. These molecular characteristics were mainly driven by the eight NRGPI oncogenes (CYTL1, PLCL1, CNTN1, GRP, APOD, GPX3, FCN1, SERPINE1) as validated in the gastric cancer cell lines and clinical samples. NRGPI-high patients showed sensitivity to a number of targeted agents, in particular, the tyrosine kinase inhibitors.

Conclusions

Necroptosis appears to play a critical role in the development of gastric cancer, prognosis and shaping of its tumor immune microenvironment. NRGPI can be used as a promising prognostic biomarker to identify gastric cancer patients with a cold tumor immune microenvironment and poor prognosis who may response to selected molecular targeted therapy.

Identification and Validation of an m6A Modification of JAK-STAT Signaling Pathway–Related Prognostic Prediction Model in Gastric Cancer

Background: Gastric cancer (GC) is one of the malignant tumors worldwide. Janus (JAK)–signal transduction and activator of transcription (STAT) signaling pathway is involved in cellular biological process and immune function. However, the association between them is still not systematically described. Therefore, in this study, we aimed to identify key genes involved in JAK-STAT signaling pathway and GC, as well as the potential mechanism.

Methods: The Cancer Genome Atlas (TCGA) database was the source of RNA-sequencing data of GC patients. Gene Expression Omnibus (GEO) database was used as the validation set. The predictive value of the JAK-STAT signaling pathway-related prognostic prediction model was examined using least absolute shrinkage and selection operator (LASSO); survival, univariate, and multivariate Cox regression analyses; and receiver operating characteristic curve (ROC) analyses to examine the predictive value of the model. Quantitative real-time polymerase chain reaction (qRT-PCR) and chi-square test were used to verify the expression of genes in the model and assess the association between the genes and clinicopathological parameters of GC patients, respectively. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis, version 3.0 (GSEA), sequence-based RNA adenosine methylation site predictor (SRAMP) online websites, and RNA immunoprecipitation (RIP) experiments were used to predict the model-related potential pathways, m6A modifications, and the association between model genes and m6A.

Results: A four-gene prognostic model (GHR, PIM1, IFNA8, and IFNB1) was constructed, namely, riskScore. The Kaplan–Meier curves suggested that patients with high riskScore expression had a poorer prognosis than those with low riskScore expression (p = 0.006). Multivariate Cox regression analyses showed that the model could be an independent predictor (p < 0.001; HR = 3.342, 95%, CI = 1.834–6.088). The 5-year area under time-dependent ROC curve (AUC) reached 0.655. The training test set verified these results. Further analyses unveiled an enrichment of cancer-related pathways, m6A modifications, and the direct interaction between m6A and the four genes.

Conclusion: This four-gene prognostic model could be applied to predict the prognosis of GC patients and might be a promising therapeutic target in GC.

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.

A Risk Model of Eight Immune-Related Genes Predicting Prognostic Response to Immune Therapies for Gastric Cancer

Immune checkpoint inhibitor (ICI) treatment is considered as an innovative approach for cancers. Since not every patient responded well to ICI therapy, it is imperative to screen out novel signatures to predict prognosis. Based on 407 gastric cancer (GC) samples retrieved from The Cancer Genome Atlas (TCGA), 36 immune-related hub genes were identified by weighted gene co-expression network analysis (WGCNA), and eight of them (RNASE2, CGB5, INHBE, DUSP1, APOA1, CD36, PTGER3, CTLA4) were used to formulate the Cox regression model. The obtained risk score was proven to be significantly correlated with overall survival (OS), consistent with the consequence of the Gene Expression Omnibus (GEO) cohort (n = 433). Then, the relationship between the risk score and clinical, molecular and immune characteristics was further investigated. Results showed that the low-risk subgroup exhibited higher mutation rate, more M1 macrophages, CD8+ and CD4+ T cells infiltrating, more active MHC-I, and bias to “IFN-γ Dominant” immune type, which is consistent with our current understanding of tumor prognostic risk. Furthermore, it is suggested that our model can accurately predict 1-, 2-, and 3-year OS of GC patients, and that it was superior to other canonical models, such as TIDE and TIS. Thus, these eight genes are probably considered as potential signatures to predict prognosis and to distinguish patient benefit from ICI, serving as a guiding individualized immunotherapy.

Long non-coding RNA CERS6-AS1 plays a prognostic role in promoting the progression of gastric cancer

This study aims to investigate the potential clinical function of long non-coding RNA CERS6-AS1 (lncRNA CERS6-AS1) integrated miR-567 in gastric cancer. The expression of CERS6-AS1 in gastric cancer tissues was detected through RT-qPCR in contrast to the normal tissues. The correlation between the expression of lncRNA CERS6-AS1 and the characteristics of clinical data was analyzed. Kaplan-Meier curve was used to assess the survival analysis, while Cox proportional hazards model multivariate analysis was performed to evaluate the prognostic risk factors of gastric cancer to verify the prognostic possibility of CERS6-AS1. The expression of CERS6-AS1 in different gastric cancer cells was detected, being the development of gastric cancer cells after knockdown CERS6-AS1 studied using CCK-8, Transwell migration, and invasion detection methods. The targeting effect and interaction between CERS6-AS1 and miR-567 through biological analysis and luciferase activity detection. The expression of lncRNA CERS6-AS1 was elevated in gastric cancer tissues and cells. The results of this study demonstrate that the condition of gastric cancer patients was related to the expression of CERS6-AS1, and therefore CERS6-AS1 might be a prognostic factor for the progression of gastric cancer. In addition, the ability of gastric cancer cells to proliferate, migrate and invade could be reduced by knockdown CERS6-AS1. After CERS6-AS1 knockdown, the expression level of miR-567 in gastric cancer tissues decreased, while the expression level of miR-567 increased. In conclusion, lncRNA CERS6-AS1 might promote the progression of gastric cancer and had the potential as a prognostic marker of gastric cancer.