Gene expression signature-based prognostic risk score in gastric cancer

Unraveling the regulatory cell death pathways in gastric cancer: a multi-omics study

Gastric cancer (GC) is a prevalent form of cancer worldwide and has a high death rate, with less than 40% of patients surviving for 5 years. GC demonstrates a vital characteristic of evading regulatory cell death (RCD). However, the extent to which RCD patterns are clinically significant in GC has not been well investigated. The study created a regulatory cell death index (RCDI) signature by employing 101 machine-learning algorithms. These algorithms were based on the expression files of 1292 GC patients from 6 multicenter cohorts. RCDI is a reliable and robust determinant of the likelihood of surviving in general. Furthermore, the precision of RCDI surpasses that of the 20 signatures that have been previously disclosed. The presence of RCDI signature is closely linked to immunological characteristics, such as the infiltration of immune cells, the presence of immunotherapy markers, and the activation of immune-related functions. This suggests that there is a higher level of immune activity in cases with RCDI signature. Collectively, the use of RCDI has the potential to be a strong and encouraging method for enhancing the clinical results of individual individuals with GC.

ESM1 facilitates the EGFR/HER3-triggered epithelial-to-mesenchymal transition and progression of gastric cancer via modulating interplay between Akt and angiopoietin-2 signaling

Gastric cancer (GC) poses global challenges due to its difficult early diagnosis and drug resistance, necessitating the identification of early detection markers and understanding of oncogenic pathways for effective GC therapy. Endothelial cell-specific molecule 1 (ESM1), a secreted glycoprotein, is elevated in various cancers, but its role in GC remains controversial. In our study, ESM1 was elevated in GC tissues, and its concentration was correlated with progression and poorer patient prognosis in independent cohorts. Functionally, ESM1 expression promoted proliferation, anoikis resistance, and motility of GC cells, as well as tumor growth in PDOs and in GC xenograft models. Mechanistically, ESM1 expression triggered the epithelial-to-mesenchymal transition (EMT) of GC cells by enhancing epidermal growth factor receptor (EGFR)/human EGFR 3 (HER3) association and activating the EGFR/HER3-Akt pathway. Additionally, angiopoietin-2 (ANGPT2) was found to be highly correlated with ESM1 and interplayed with Akt to induce the EMT and cancer progression. Use of a signal peptide deletion mutant (ESM1-19del) showed that the secreted form of ESM1 is crucial for its protumorigenic effects by activating the EGFR/HER3-Akt/ANGPT2 pathway to promote the EMT. Patients with high levels of both ESM1 and ANGPT2 had the poorest prognoses. Furthermore, therapeutic peptides successfully inhibited ESM1's induction of the aforementioned signals and motility of GC cells. ESM1's oncogenic role in GC involves activating the EGFR/HER3-Akt/ANGPT2 pathway, presenting a potential therapeutic target for GC.

A novel M2-like tumor associated macrophages-related gene signature for predicting the prognosis and immunotherapy efficacy in gastric cancer

BACKGROUND

M2-like tumor-associated macrophages (M2-like TAMs) play key roles in tumor progression and the immune response. However, the clinical significance and prognostic value of M2-like TAMs-associated regulatory genes in gastric cancer (GC) have not been clarified.

METHODS

Herein, we identified M2-like TAM-related genes by weighted gene coexpression network analysis of TCGA-STAD and GSE84437 cohort. Lasso-Cox regression analyses were then performed to screen for signature genes, and a novel signature was constructed to quantify the risk score for each patient. Tumor mutation burden (TMB), survival outcomes, immune cells, and immune function were analyzed in the risk groups to further reveal the immune status of GC patients. A gene-drug correlation analysis and sensitivity analysis of anticancer drugs were used to identify potential therapeutic agents. Finally, we verified the mRNA expression of signature genes in patient tissues by qRT-PCR, and analyzed the expression distribution of these genes by IHC.

RESULTS

A 4-gene (SERPINE1, MATN3, CD36, and CNTN1) signature was developed and validated, and the risk score was shown to be an independent prognostic factor for GC patients. Further analyses revealed that GC patients in the high-risk group had a worse prognosis than those in the low-risk group, with significant differences in TMB, clinical features, enriched pathways, TIDE score, and tumor microenvironment features. Finally, we used qRT-PCR and IHC analysis to verify mRNA and protein level expression of signature genes.

CONCLUSION

These findings highlight the importance of M2-like TAMs, provide a new perspective on individualized immunotherapy for GC patients.

Identification of a novel gene signature related to prognosis and metastasis in gastric cancer

BACKGROUND

Gastric Cancer (GC) presents poor outcome, which is consequence of the high incidence of recurrence and metastasis at early stages. GC patients presenting recurrent or metastatic disease display a median life expectancy of only 8 months. The mechanisms underlying GC progression remain poorly understood.

METHODS

We took advantage of public available GC datasets from TCGA using GEPIA, and identified the matched genes among the 100 genes most significantly associated with overall survival (OS) and disease free survival (DFS). Results were confirmed in ACRG cohort and in over 2000 GC cases obtained from several cohorts integrated using our own analysis pipeline. The Kaplan-Meier method and multivariate Cox regression analyses were used for prognostic significance and linear modelling and correlation analyses for association with clinic-pathological parameters and biological hallmarks. In vitro and in vivo functional studies were performed in GC cells with candidate genes and the related molecular pathways were studied by RNA sequencing.

RESULTS

High expression of ANKRD6, ITIH3, SORCS3, NPY1R and CCDC178 individually and as a signature was associated with poor prognosis and recurrent disease in GC. Moreover, the expression of ANKRD6 and ITIH3 was significantly higher in metastasis and their levels associated to Epithelial to Mesenchymal Transition (EMT) and stemness markers. In line with this, RNAseq analysis revealed genes involved in EMT differentially expressed in ANKRD6 silencing cells. Finally, ANKRD6 silencing in GC metastatic cells showed impairment in GC tumorigenic and metastatic traits in vitro and in vivo.

CONCLUSIONS

Our study identified a novel signature involved in GC malignancy and prognosis, and revealed a novel pro-metastatic role of ANKRD6 in GC.

Molecular classification and intratumoral heterogeneity of gastric adenocarcinoma

Gastric cancers frequently harbor striking histological complexity and diversity between lesions as well as within single lesions, known as inter- and intratumoral heterogeneity, respectively. The latest World Health Organization Classification of Tumors designated more than 30 histological subtypes for gastric epithelial tumors, assigning 12 subtypes for gastric adenocarcinoma (GAD). Meanwhile, recent advances in genome-wide analyses have provided molecular aspects to the histological classification of GAD, and consequently revealed different molecular traits underlying these histological subtypes. Moreover, accumulating knowledge of comprehensive molecular profiles has led to establishing molecular classifications of GAD, which are often associated with clinical biomarkers for therapeutics and prognosis. However, most of our knowledge of GAD molecular profiles is based on inter-tumoral heterogeneity, and the molecular profiles underlying intratumoral heterogeneity are yet to be determined. In this review, recently established molecular classifications of GAD are introduced in the aspect of pathological diagnosis and are discussed in the context of intratumoral heterogeneity.

Identification of differentially expressed mRNAs as novel predictive biomarkers for gastric cancer diagnosis and prognosis

BACKGROUND

Gastric cancer (GC) has a high mortality rate worldwide. Despite significant progress in GC diagnosis and treatment, the prognosis for affected patients still remains unfavorable.

AIM

To identify important candidate genes related to the development of GC and identify potential pathogenic mechanisms through comprehensive bioinformatics analysis.

METHODS

The Gene Expression Omnibus database was used to obtain the GSE183136 dataset, which includes a total of 135 GC samples. The limma package in R software was employed to identify differentially expressed genes (DEGs). Thereafter, enrichment analyses of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed for the gene modules using the clusterProfile package in R software. The protein-protein interaction (PPI) networks of target genes were constructed using STRING and visualized by Cytoscape software. The common hub genes that emerged in the cohort of DEGs that was retrieved from the GEPIA database were then screened using a Venn Diagram. The expression levels of these overlapping genes in stomach adenocarcinoma samples and non-tumor samples and their association with prognosis in GC patients were also obtained from the GEPIA database and Kaplan-Meier curves. Moreover, real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting were performed to determine the mRNA and protein levels of glutamic-pyruvic transaminase (GPT) in GC and normal immortalized cell lines. In addition, cell viability, cell cycle distribution, migration and invasion were evaluated by cell counting kit-8, flow cytometry and transwell assays. Furthermore, we also conducted a retrospective analysis on 70 GC patients diagnosed and surgically treated in Wenzhou Central Hospital, Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University between January 2017 to December 2020. The tumor and adjacent normal samples were collected from the patients to determine the potential association between the expression level of GPT and the clinical as well as pathological features of GC patients.

RESULTS

We selected 19214 genes from the GSE183136 dataset, among which there were 250 downregulated genes and 401 upregulated genes in the tumor samples of stage III-IV in comparison to those in tumor samples of stage I-II with a P-value < 0.05. In addition, GO and KEGG results revealed that the various upregulated DEGs were mainly enriched in plasma membrane and neuroactive ligand-receptor interaction, whereas the downregulated DEGs were primarily enriched in cytosol and pancreatic secretion, vascular smooth muscle contraction and biosynthesis of the different cofactors. Furthermore, PPI networks were constructed based on the various upregulated and downregulated genes, and there were a total 15 upregulated and 10 downregulated hub genes. After a comprehensive analysis, several hub genes, including runt-related transcription factor 2 (RUNX2), salmonella pathogenicity island 1 (SPI1), lysyl oxidase (LOX), fibrillin 1 (FBN1) and GPT, displayed prognostic values. Interestingly, it was observed that GPT was downregulated in GC cells and its upregulation could suppress the malignant phenotypes of GC cells. Furthermore, the expression level of GPT was found to be associated with age, lymph node metastasis, pathological staging and distant metastasis (P < 0.05).

CONCLUSION

RUNX2, SPI1, LOX, FBN1 and GPT were identified key hub genes in GC by bioinformatics analysis. GPT was significantly associated with the prognosis of GC, and its upregulation can effectively inhibit the proliferative, migrative and invasive capabilities of GC cells.

HSPA4 upregulation induces immune evasion via ALKBH5/CD58 axis in gastric cancer

INTRODUCTION

Gastric cancer (GC) is one of the leading causes of cancer-related death worldwide. Recently, targeted therapies including PD1 (programmed cell death 1) antibodies have been used in advanced GC patients. However, identifying new biomarker for immunotherapy is still urgently needed. The objective of this study is to unveil the immune evasion mechanism of GC cells and identify new biomarkers for immune checkpoint blockade therapy in patients with GC.

METHODS

Coimmunoprecipitation and meRIP were performed to investigate the mechanism of immune evasion of GC cells. Cocuture system was established to evaluate the cytotoxicity of cocultured CD8+ T cells. The clinical significance of HSPA4 upregulation was analyzed by multiplex fluorescent immunohistochemistry staining in GC tumor tissues.

RESULTS

Histone acetylation causes HSPA4 upregulation in GC tumor tissues. HSPA4 upregulation increases the protein stability of m6A demethylase ALKBH5. ALKBH5 decreases CD58 in GC cells through m6A methylation regulation. The cytotoxicity of CD8+ T cells are impaired and PD1/PDL1 axis is activated when CD8+ T cells are cocultured with HSPA4 overexpressed GC cells. HSPA4 upregulation is associated with worse 5-year overall survival of GC patients receiving only surgery. It is an independent prognosis factor for worse survival of GC patients. In GC patients receiving the combined chemotherapy with anti-PD1 immunotherapy, HSPA4 upregulation is observed in responders compared with non-responders.

CONCLUSION

HSPA4 upregulation causes the decrease of CD58 in GC cells via HSPA4/ALKBH5/CD58 axis, followed by PD1/PDL1 activation and impairment of CD8+ T cell's cytotoxicity, finally induces immune evasion of GC cells. HSPA4 upregulation is associated with worse overall survival of GC patients with only surgery. Meanwhile, HSPA4 upregulation predicts for better response in GC patients receiving the combined immunotherapy.

Thrombospondins in the tumor microenvironment

Many cancers begin with the formation of a small nest of transformed cells that can remain dormant for years. Thrombospondin-1 (TSP-1) initially promotes dormancy by suppressing angiogenesis, a key early step in tumor progression. Over time, increases in drivers of angiogenesis predominate, and vascular cells, immune cells, and fibroblasts are recruited to the tumor mass forming a complex tissue, designated the tumor microenvironment. Numerous factors, including growth factors, chemokine/cytokine, and extracellular matrix, participate in the desmoplastic response that in many ways mimics wound healing. Vascular and lymphatic endothelial cells, and cancer-associated pericytes, fibroblasts, macrophages and immune cells are recruited to the tumor microenvironment, where multiple members of the TSP gene family promote their proliferation, migration and invasion. The TSPs also affect the immune signature of tumor tissue and the phenotype of tumor-associated macrophages. Consistent with these observations, expression of some TSPs has been established to correlate with poor outcomes in specific types of cancer.

Pathophysiological roles of thrombospondin-4 in disease development

Thrombospondin-4 (TSP-4) belongs to the extracellular matrix glycoprotein family of thrombospondins (TSPs). The multidomain, pentameric structure of TSP-4 allows its interactions with numerous extracellular matrix components, proteins and signaling molecules that enable its modulation to various physiological and pathological processes. Characterization of TSP-4 expression under development and pathogenesis of disorders has yielded important insights into mechanisms underlying the unique role of TSP-4 in mediating various processes including cell-cell, cell-extracellular matrix interactions, cell migration, proliferation, tissue remodeling, angiogenesis, and synaptogenesis. Maladaptation of these processes in response to pathological insults and stress can accelerate the development of disorders including skeletal dysplasia, osteoporosis, degenerative joint disease, cardiovascular diseases, tumor progression/metastasis and neurological disorders. Overall, the diverse functions of TSP-4 suggest that it may be a potential marker or therapeutic target for prognosis, diagnosis, and treatment of various pathological conditions upon further investigations. This review article highlights recent findings on the role of TSP-4 in both physiological and pathological conditions with a focus on what sets it apart from other TSPs.

Evaluations of Biomarkers CDX1 and CDX2 in Gastric Cancer Prognosis: A Meta-analysis

CDX1 and CDX2 are homeobox-type transcription factors that are potential biomarkers and are associated with prognostic significance in intestinal-type gastric cancer early disease before lymph node metastasis is associated with better prognosis. In addition, the genes IDH 1 and IDH 2 previously known to be involved in brain cancer are implicated in cancer-related molecular signatures as a result new targeted personalized therapies may be possible. Our retrospective study determined the correlation between CDX markers and clinicopathologic data including survival in patients with gastric cancer. This study included studies from 1997 to December 2022 a meta-analysis to provide odds ratios (ORs) and relative risks (RRs). We discussed in detail the impact of IDH 1/2 on the prognosis of gastric cancer outcomes and potential therapeutic strategies. Our meta-analysis included 20 studies identifying 11,163 patients with gastric cancer. We found that CDX 1 overexpression was associated with better overall survival (pooled HR: 1.28) and CDX 2 expression and better 3-year survival (pooled HR: 1.64) and 5-year survival was the pooled HR was correlated 1 94 with both showing statistical correlation. Evidence suggests that IDH 1/2 mutations and CDX 1/2 overexpression are closely associated with metabolic abnormalities epigenetic changes and mutations evidence suggests the potential for novel targeted therapies in gastric cancer. CDX 1/2 overexpression is associated with a favorable prognosis in gastric cancer cases. Further studies are needed to explore the clinical significance of IDH 1/2 mutations and CDX 1/2 expression.

Gastric cancer peritoneal metastasis related signature predicts prognosis and sensitivity to immunotherapy in gastric cancer

Gastric cancer peritoneal metastases (GCPM) is a leading cause of GC-related death. Early detection of GCPM is critical for improving the prognosis of advanced GC. Differentially expressed genes (DEGs) were identified in the GSE62254 database to distinguish between GCPM and non-GCPM. The gastric cancer peritoneal metastases signature (GCPMs) was developed using DEGs. We analysed the effectiveness of GCPMs as indicators for prognosis, chemotherapy, and immune therapy response in GC patients. Subsequently, we analysed the correlation between GCPMs and immune microenvironment as well as immune escape in GC patients. Random forest model and immunohistochemistry was utilized to identify the crucial genes that can aid in the diagnosis of GCPM. We identified five DEGs and utilized their expression to construct GCPMs. Patients with high GCPMs had a higher likelihood of a poor prognosis, while those with low GCPMs appeared to potentially benefit more from chemotherapy. GCPMs were a dependable marker for predicting the response to immunotherapy. Additionally, GCPMs was found to be significantly linked to stromal score and cancer-associated fibroblasts. SYNPO2 has been identified as the gene with the highest significance in the diagnosis of GCPM. Immunohistochemistry suggests that SYNPO2-positive expression in tumour cells, fibroblasts, inflammatory cell may be associated with promoting peritoneal metastasis in GC. GCPMs have shown to be a promising biomarker for predicting the prognosis and response of GC patients to chemotherapy and immunotherapy. The use of GCPMs for individual tumour evaluation may pave the way for personalized treatment for GC patients in the future.

Microdissection of cancer-associated fibroblast infiltration subtypes unveils the secreted SERPINE2 contributing to immunosuppressive microenvironment and immuotherapeutic resistance in gastric cancer: A large-scale study integrating bulk and single-cell transcriptome profiling

In the era of immunotherapy, the suboptimal response rate and the development of acquired resistance among the initial beneficiaries continue to present significant challenges across multiple malignancies, including gastric cancer (GC). Considering that the interactions of tumor stroma, especially the cancer-associated fibroblasts (CAFs), with immune and tumor cells, play indispensable roles in tumor progression, tumor microenvironment remodeling and therapeutic responsiveness, in-depth exploration on the roles of CAFs and pivotal mediators of their functions may provide novel clues to increase the effectiveness of current immunotherapeutic drugs and further achieve synergistic antitumor response. Herein, through the consensus clustering of canonical biomarkers, three GC subclasses with different abundance of CAFs were virtually microdissected in four integrated bulk cohorts encompassing 2148 GC patients from 11 independent datasets. An extensive immunogenomic analysis revealed that tumors with high CAFs infiltration were characterized with unfavorable outcomes, aggressive phenotypes, decreased tumor immunogenicity, high risk of immune evasion and thus immunotherapeutic resistance. By leveraging large-scale single-cell transcriptomic profiling, a series of CAF-secreted proteins were identified, among which the SERPINE2 was confirmed to be restrictively enriched in stromal fibroblasts of GC tissues and contribute to promoting a protumor milieu and fostering an immunosuppressive microenvironment via bioinformatics computations and tissue microarray analysis. Moreover, pan-cancer investigations generalized the immunological roles of SERPINE2, especially in pan-gastrointestinal malignancies, with multiple real-world immunotherapy cohorts further confirming its implications on predicting immunotherapeutic efficacy. In conclusion, these findings suggest that the CAF-derived SERPINE2 is a promising immune-oncology target with therapeutic implications to further synergize the immunotherapeutic combinations.

Clinically conserved genomic subtypes of gastric adenocarcinoma

Gastric adenocarcinoma (GAC) is a lethal disease characterized by genomic and clinical heterogeneity. By integrating 8 previously established genomic signatures for GAC subtypes, we identified 6 clinically and molecularly distinct genomic consensus subtypes (CGSs). CGS1 have the poorest prognosis, very high stem cell characteristics, and high IGF1 expression, but low genomic alterations. CGS2 is enriched with canonical epithelial gene expression. CGS3 and CGS4 have high copy number alterations and low immune reactivity. However, CGS3 and CGS4 differ in that CGS3 has high HER2 activation, while CGS4 has high SALL4 and KRAS activation. CGS5 has the high mutation burden and moderately high immune reactivity that are characteristic of microsatellite instable tumors. Most CGS6 tumors are positive for Epstein Barr virus and show extremely high levels of methylation and high immune reactivity. In a systematic analysis of genomic and proteomic data, we estimated the potential response rate of each consensus subtype to standard and experimental treatments such as radiation therapy, targeted therapy, and immunotherapy. Interestingly, CGS3 was significantly associated with a benefit from chemoradiation therapy owing to its high basal level of ferroptosis. In addition, we also identified potential therapeutic targets for each consensus subtype. Thus, the consensus subtypes produced a robust classification and provide for additional characterizations for subtype-based customized interventions.

Identification of INHBA as a potential biomarker for gastric cancer through a comprehensive analysis

Inhibin subunit beta A (INHBA) is a member of the transforming growth factor-beta (TGF-β) superfamily that plays a fundamental role in various cancers. However, a systematic analysis of the exact role of INHBA in patients with gastric cancer (GC) has not yet been conducted. We evaluated the expression levels of INHBA and the correlation between INHBA and GC prognosis in GC. The relationship between INHBA expression, immune infiltration levels, and type markers of immune cells in GC was also explored. In addition, we studied INHBA mutations, promoter methylation, and functional enrichment analysis. Besides, high expression levels of INHBA in GC were significantly related to unfavorable prognosis. INHBA was negatively correlated with B cell infiltration, but positively correlated with macrophage and most anticancer immunity steps. INHBA expression was positively correlated with the type markers of CD8+ T cells, neutrophils, macrophages, and dendritic cells. INHBA has a weak significant methylation level change between tumor and normal tissues and mainly enriched in cancer-related signaling pathways. The present study implies that INHBA may serve as a potential biomarker for predicting the prognosis of patients with GC. INHBA is a promising predictor of immunotherapy response, with higher levels of INHBA indicating greater sensitivity.

A prediction model for prognosis of gastric adenocarcinoma based on six metabolism-related genes

Background

The study of tumor metabolism is of great value to elucidate the mechanism of tumorigenesis and predict the prognosis of patients. However, the prognostic role of metabolism-related genes (MRGs) in gastric adenocarcinoma (GAD) remains poorly understood.

Methods

We downloaded the gene chip dataset GSE79973 (n = 20) of GAD from the Gene Expression Omnibus (GEO) database to compare differentially expressed genes (DEGs) between normal and tumor tissues. We then extracted MRGs from these DEGs and systematically investigated the prognostic value of these differential MRGs for predicting patients' overall survival by univariable and multivariable Cox regression analysis. Six metabolic genes (ACOX3, APOE, DIO2, HSD17B4, NUAK1, and WHSC1L1) were identified as prognosis-associated hub genes, which were used to build a prognostic model in the training dataset GSE15459 (n = 200), and then validated in the dataset GSE62254 (n = 300).

Results

Patients were divided into high-risk and low-risk subgroups based on the model's risk score, and it was found that patients in the high-risk subgroup had shorter overall survival than those in the low-risk subgroup, both in the training and testing datasets. In addition, for the training and testing cohorts, the area under the ROC curve of the prognostic model for one-year survival prediction was 0.723 and 0.667, respectively, indicating that the model has good predictive performance. Furthermore, we established a nomogram based on tumor stage and risk score to effectively predict the overall survival (OS) of GAD patients. The expression of 6 MRGs at the protein level was confirmed by immunohistochemistry (IHC). Kaplan-Meier survival analysis further confirmed that their expression influenced OS in GAD patients.

Conclusion

Collectively, the 6 MRGs signature might be a reliable tool for assessing OS in GAD patients, with potential application value in clinical decision-making and individualized therapy.

Identification of a six-gene signature to predict survival and immunotherapy effectiveness of gastric cancer

Background

Gastric cancer (GC) ranks as the fifth most prevalent malignancy and the second leading cause of oncologic mortality globally. Despite staging guidelines and standard treatment protocols, significant heterogeneity exists in patient survival and response to therapy for GC. Thus, an increasing number of research have examined prognostic models recently for screening high-risk GC patients.

Methods

We studied DEGs between GC tissues and adjacent non-tumor tissues in GEO and TCGA datasets. Then the candidate DEGs were further screened in TCGA cohort through univariate Cox regression analyses. Following this, LASSO regression was utilized to generate prognostic model of DEGs. We used the ROC curve, Kaplan-Meier curve, and risk score plot to evaluate the signature's performance and prognostic power. ESTIMATE, xCell, and TIDE algorithm were used to explore the relationship between the risk score and immune landscape relationship. As a final step, nomogram was developed in this study, utilizing both clinical characteristics and a prognostic model.

Results

There were 3211 DEGs in TCGA, 2371 DEGs in GSE54129, 627 DEGs in GSE66229, and 329 DEGs in GSE64951 selected as candidate genes and intersected with to obtain DEGs. In total, the 208 DEGs were further screened in TCGA cohort through univariate Cox regression analyses. Following this, LASSO regression was utilized to generate prognostic model of 6 DEGs. External validation showed favorable predictive efficacy. We studied interaction between risk models, immunoscores, and immune cell infiltrate based on six-gene signature. The high-risk group exhibited significantly elevated ESTIMATE score, immunescore, and stromal score relative to low-risk group. The proportions of CD4⁺ memory T cells, CD8⁺ naive T cells, common lymphoid progenitor, plasmacytoid dentritic cell, gamma delta T cell, and B cell plasma were significantly enriched in low-risk group. According to TIDE, the TIDE scores, exclusion scores and dysfunction scores for low-risk group were lower than those for high-risk group. As a final step, nomogram was developed in this study, utilizing both clinical characteristics and a prognostic model.

Conclusion

In conclusion, we discovered a 6 gene signature to forecast GC patients' OS. This risk signature proves to be a valuable clinical predictive tool for guiding clinical practice.

A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer

BACKGROUND

Molecular biomarkers that predict disease progression can help identify tumor subtypes and shape treatment plans. In this study, we aimed to identify robust biomarkers of prognosis in gastric cancer based on transcriptomic data obtained from primary gastric tumors.

METHODS

Microarray, RNA sequencing, and single-cell RNA sequencing-based gene expression data from gastric tumors were obtained from public databases. Freshly frozen gastric tumors (n = 42) and matched FFPE (formalin-fixed, paraffin-embedded) (n = 40) tissues from a Turkish gastric cancer cohort were used for quantitative real-time PCR and immunohistochemistry-based assessments of gene expression, respectively.

RESULTS

A novel list of 20 prognostic genes was identified and used for the classification of gastric tumors into two major tumor subgroups with differential stromal gene expression ("Stromal-UP" (SU) and "Stromal-DOWN" (SD)). The SU group had a more mesenchymal profile with an enrichment of extracellular matrix-related gene sets and a poor prognosis compared to the SD group. Expression of the genes within the signature correlated with the expression of mesenchymal markers ex vivo. A higher stromal content in FFPE tissues was associated with shorter overall survival.

CONCLUSIONS

A stroma-rich, mesenchymal subgroup among gastric tumors identifies an unfavorable clinical outcome in all cohorts tested.

A thirty-three gene-based signature predicts lymph node metastasis and prognosis in patients with gastric cancer

Recently, several studies have indicated the great potential of gene expression signature of the primary tumor in predicting lymph node metastasis; however, few current gene biomarkers can predict lymph node status and prognosis in gastric cancer (GC). Thus, we used the RNA-seq data from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes between pathological lymph node-negative (pN0) and positive (pN+) patients and to establish a gene signature that could predict lymph node metastasis. Meanwhile, the robustness of identified gene signatures was validated in an independent dataset Asian Cancer Research Group (n = 300). In this study, our thirty-three gene-based signature was highly correlated with lymph node metastasis and could successfully discriminate pN + patients in the training set (Area under the receiver operating characteristic curve = 0.951). Moreover, Disease-free survival (P = 0.0029) and overall survival (P = 0.026) were significantly worse in high-risk compared with low-risk patients overall and when confined to pN0 patients only (P < 0.0001). Of note, this gene signature also proved useful in predicting lymph node status and survival in the validation cohort. The present study suggests a thirty-three gene-based signature that could effectively predict lymph node metastasis and prognosis in GC.

Bulk and single-cell transcriptome profiling reveal the metabolic heterogeneity in gastric cancer

Metabolic reprogramming has been defined as a key hall mark of human tumors. However, metabolic heterogeneity in gastric cancer has not been elucidated. Here we separated the TCGA-STAD dataset into two metabolic subtypes. The differences between subtypes were elaborated in terms of transcriptomics, genomics, tumor-infiltrating cells, and single-cell resolution. We found that metabolic subtype 1 is predominantly characterized by low metabolism, high immune cell infiltration. Subtype 2 is mainly characterized by high metabolism and low immune cell infiltration. From single-cell resolution, we found that the high metabolism of subtype 2 is dominated by epithelial cells. Not only epithelial cells, but also various immune cells and stromal cells showed high metabolism in subtype 2 and low metabolism in subtype 1. Our study established a classification of gastric cancer metabolic subtypes and explored the differences between subtypes from multiple dimensions, especially the single-cell resolution.

Skeletal muscle omics signatures in cancer cachexia: perspectives and opportunities

Cachexia is a life-threatening complication of cancer that occurs in up to 80% of patients with advanced cancer. Cachexia reflects the systemic consequences of cancer and prominently features unintended weight loss and skeletal muscle wasting. Cachexia impairs cancer treatment tolerance, lowers quality of life, and contributes to cancer-related mortality. Effective treatments for cancer cachexia are lacking despite decades of research. High-throughput omics technologies are increasingly implemented in many fields including cancer cachexia to stimulate discovery of disease biology and inform therapy choice. In this paper, we present selected applications of omics technologies as tools to study skeletal muscle alterations in cancer cachexia. We discuss how comprehensive, omics-derived molecular profiles were used to discern muscle loss in cancer cachexia compared with other muscle-wasting conditions, to distinguish cancer cachexia from treatment-related muscle alterations, and to reveal severity-specific mechanisms during the progression of cancer cachexia from early toward severe disease.

Artificial intelligence-guided discovery of gastric cancer continuum

BACKGROUND

Detailed understanding of pre-, early and late neoplastic states in gastric cancer helps develop better models of risk of progression to gastric cancers (GCs) and medical treatment to intercept such progression.

METHODS

We built a Boolean implication network of gastric cancer and deployed machine learning algorithms to develop predictive models of known pre-neoplastic states, e.g., atrophic gastritis, intestinal metaplasia (IM) and low- to high-grade intestinal neoplasia (L/HGIN), and GC. Our approach exploits the presence of asymmetric Boolean implication relationships that are likely to be invariant across almost all gastric cancer datasets. Invariant asymmetric Boolean implication relationships can decipher fundamental time-series underlying the biological data. Pursuing this method, we developed a healthy mucosa → GC continuum model based on this approach.

RESULTS

Our model performed better against publicly available models for distinguishing healthy versus GC samples. Although not trained on IM and L/HGIN datasets, the model could identify the risk of progression to GC via the metaplasia → dysplasia → neoplasia cascade in patient samples. The model could rank all publicly available mouse models for their ability to best recapitulate the gene expression patterns during human GC initiation and progression.

CONCLUSIONS

A Boolean implication network enabled the identification of hitherto undefined continuum states during GC initiation. The developed model could now serve as a starting point for rationalizing candidate therapeutic targets to intercept GC progression.

Identification of critical prognosis signature associated with lymph node metastasis of stomach adenocarcinomas

Lymph node metastasis (LNM) is an important factor affecting the prognosis of patients with gastric adenocarcinoma (STAD), which is the most common malignancy of the human digestive system. Current detection techniques have limited sensitivity and specificity, and there is a lack of effective biomarkers to screen for LNM. Therefore, it is critical to screen for biomarkers that predict LNM in STAD. Gene expression differential analysis (false discovery rate < 0.05, |log₂Fold change| ≥1.5) was performed on 102 LNM samples, 224 non-LNM samples, and 29 normal gastric tissue samples from The Cancer Genome Atlas (TCGA) STAD dataset, and 269 LNM-specific genes (DEGs) were obtained. Enrichment analysis showed that LNM-specific genes functioned mainly in cytokine-cytokine receptor interactions, calcium signaling, and other pathways. Ten DEGs significantly associated with overall survival in STAD patients were screened by multivariate Cox regression, and an LNM-based 10-mRNA prognostic signature was established (Logrank P < 0.0001). This 10-mRNA signature was well predicted in both the TCGA training set and the Gene Expression Omnibus validation dataset (GSE84437) and was associated with survival in patients with LNM or advanced-stage STAD. Using Kaplan-Meier survival, receiver operating characteristic curve, C-index analysis, and decision curve analysis, the 10-mRNA signature was found to be a more effective predictor of prognosis in STAD patients than the other two reported models (P < 0.0005). Protein-protein interaction network and gene set enrichment analysis of the 10-mRNA signature revealed that the signature may affect the expression of multiple biological pathways and related genes. Finally, the expression levels of prognostic genes in STAD tissues and cell lines were verified using qRT-PCR, Western blot, and the Human Protein Atlas database. Taken together, the prognostic signature constructed in this study may become an indicator for clinical prognostic assessment of LNM-STAD and provide a new strategy for future targeted therapy.

Bioinformatic Analysis of PTTG Family and Prognosis and Immune Cell Infiltration in Gastric Cancer

Gastric cancer is the sixth highest incidence rate in the world. Although treatment has made progress, the prospect of gastric cancer patients is bleak. Difficulties and future prospects of immunotherapy in cancer treatment. Adaptive cell therapy, cancer vaccines, gene therapy, and monoclonal antibody therapy have all been used in gastric cancer with some initial success. PTTGs (pituitary tumor-transforming genes) have been proven to be closely related to the prognosis of many malignant tumors. However, the prognosis and immune cell infiltration of gastric adenocarcinoma (STAD) remain unclear. We retrieved multiple databases to understand the possible activity of PTTGs and their expression in gastric cancer, as well as their relationship with clinical data, overall survival rate, first progression, and survival rate after progression. PTTGs are overexpressed in STAD tumor tissues. Many clinical variables are closely related to PTTGs. In addition, PTTG was associated with overall survival independent of disease. In addition, the expression of PTTG1/2 was positively correlated with the molecular status of the immune checkpoint and negatively correlated with the infiltration of various immune cells. Data research shows that PTTG and STAD are closely related. This paved the way for future research, revealed the complex pathophysiology of gastric cancer, and introduced an effective new treatment.

An integrative approach toward identification and analysis of therapeutic targets involved in HPV pathogenesis with a focus on carcinomas

BACKGROUND

Persistent infection of high-risk HPVs is known to cause diverse carcinomas, mainly cervical, oropharyngeal, penile, etc. However, efficient treatment is still lacking.

OBJECTIVE

Identify and analyze potential therapeutic targets involved in HPV oncogenesis and repurposing drug candidates.

METHODS

Integrative analyses were performed on the compendium of 1887 HPV infection-associated or integration-driven disrupted genes cataloged from the Open Targets Platform and HPVbase resource. Potential target genes are prioritized using STRING, Cytoscape, cytoHubba, and MCODE. Gene ontology and KEGG pathway enrichment analysis are performed. Further, TCGA cancer genomic data of CESC and HNSCC is analyzed. Moreover, regulatory networks are also deduced by employing NetworkAnalyst.

RESULTS

We have implemented a unique approach for identifying and prioritizing druggable targets and repurposing drug candidates against HPV oncogenesis. Overall, hundred key genes with 44 core targets were prioritized with transcription factors (TFs) and microRNAs (miRNAs) regulators pertinent to HPV pathogenesis. Genomic alteration profiling further substantiated our findings. Among identified druggable targets, TP53, NOTCH1, PIK3CA, EP300, CREBBP, EGFR, ERBB2, PTEN, and FN1 are frequently mutated in CESC and HNSCC. Furthermore, PIK3CA, CCND1, RFC4, KAT5, MYC, PTK2, EGFR, and ERBB2 show significant copy number gain, and FN1, CHEK1, CUL1, EZH2, NRAS, and H2AFX was marked for the substantial copy number loss in both carcinomas. Likewise, under-explored relevant regulators, i.e., TFs (HINFP, ARID3A, NFATC2, NKX3-2, EN1) and miRNAs (has-mir-98-5p, has-mir-24-3p, has-mir-192-5p, has-mir-519d-3p) is also identified.

CONCLUSIONS

We have identified potential therapeutic targets, transcriptional and post-transcriptional regulators to explicate HPV pathogenesis as well as potential repurposing drug candidates. This study would aid in biomarker and drug discovery against HPV-mediated carcinoma.

Transcriptomic study of gastrointestinal stromal tumors with liver metastasis

Introduction: GIST (gastrointestinal stromal tumor) is the most prominent mesenchymal neoplasms of the gastrointestinal tract, and liver is the most common metastasis site for GIST. The molecular mechanism leading to liver metastasis of GIST is currently unclear. Methods: With the goal of revealing the underlying mechanism, we performed whole-genome gene expression profiling on 18 pairs of RNA samples comprised of GIST tissues (with liver metastasis) and corresponding non-tumor tissues. After identifying differentially expressed gene, functional annotation and signal pathway analyses were conducted. GSE13861, datasets that compare GIST (without liver metastasis) with adjacent tissues, served as a comparison. Results: A total of 492 up-regulated genes and 629 down-regulated genes were identified as differentially expressed genes between liver metastasis tissues and non-tumor tissues. We characterized expression patterns of DEGs identified from our cohort and GSE13861 that show signatures of enrichment for functionality. In subsequent gene set enrichment analysis, differentially expressed genes were mainly enriched in Epithelial Mesenchymal Transition in both datasets. 493 genes were overlapped among our whole-genome gene expression profiling results and GSE13861, consisting 188 up-regulated genes and 305 down-regulated genes. By using CytoHubba plugin of Cytoscape, CDH1, CD34, KIT, PROM1, SOX9, FGF2, CD24, ALDH1A1, JAG1 and NES were identified as top ten hub genes in tumorigenesis and liver metastasis of GIST. higher expression levels of FGF2, JAG1, CD34, ALDH1A1 and the lower expression level of CDH1 were respectively associated with unfavorable overall survival. Meanwhile higher expression levels of CD34, FGF2, KIT, JAG1, ALDH1A were correlated with worse disease-free survival. Discussion: The present study may help to provide candidate pathways and targets for treatment of GIST and prevention methods to liver metastasis.

Genomic analysis of matrix metalloproteinases affecting the prognosis and immunogenic profile of gastric cancer

This study systematically and comprehensively analyzed the characteristics of matrix metalloproteinases (MMPs) in gastric cancer (GC) and revealed the relationship between MMPs and prognoses, clinicopathological features, tumor microenvironment, gene mutations, and drug therapy response in patients with GC. Based on the mRNA expression profiles of 45 MMP-related genes in GC, we established a model that classified GC patients into three groups based on cluster analysis of the mRNA expression profiles. The 3 groups of GC patients showed significantly different prognoses as well as tumor microenvironmental characteristics. Next, we used Boruta's algorithm and PCA method to establish an MMP scoring system and found that lower MMP scores were associated with better prognoses, lower clinical stages, better immune cell infiltration, lower degrees of immune dysfunction and rejection, and more genetic mutations. Whereas a high MMP score was the opposite. These observations were further validated with data from other datasets, showing the robustness of our MMP scoring system. Overall, MMP could be involved in the tumor microenvironment (TME), clinical features, and prognosis of GC. An in-depth study of MMP patterns can better understand the indispensable role of MMP in the development of GC and reasonably assess the survival prognosis, clinicopathological features, and drug efficacy of different patients, thus providing clinicians with a broader vision of GC progression and treatment.

Identification and validation of critical genes with prognostic value in gastric cancer

Background: Gastric cancer (GC) is a digestive system tumor with high morbidity and mortality rates. Molecular targeted therapies, including those targeting human epidermal factor receptor 2 (HER2), have proven to be effective in clinical treatment. However, better identification and description of tumor-promoting genes in GC is still necessary for antitumor therapy. Methods: Gene expression and clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Last absolute shrinkage and selection operator (LASSO) Cox regression were applied to build a prognostic model, the Prognosis Score. Functional enrichment and single-sample gene set enrichment analysis (ssGSEA) were used to explore potential mechanisms. Western blotting, RNA interference, cell migration, and wound healing assays were used to detect the expression and function of myosin light chain 9 (MYL9) in GC. Results: A four-gene prognostic model was constructed and GC patients from TCGA and meta-GEO cohorts were stratified into high-prognosis score groups or low-prognosis score groups. GC patients in the high-prognosis score group had significantly poorer overall survival (OS) than those in the low-prognosis score groups. The GC prognostic model was formulated as PrognosisScore = (0.06 × expression of BGN) - (0.008 × expression of ATP4A) + (0.12 × expression of MYL9) - (0.01 × expression of ALDH3A1). The prognosis score was identified as an independent predictor of OS. High expression of MYL9, the highest weighted gene in the prognosis score, was correlated with worse clinical outcomes. Functional analysis revealed that MYL9 is mainly associated with the biological function of epithelial-mesenchymal transition (EMT). Knockdown of MYL9 expression inhibits migration of GC cells in vitro. Conclusion: We found that PrognosisScore is potential reliable prognostic marker and verified that MYL9 promotes the migration and metastasis of GC cells.

Construction of mRNA prognosis signature associated with differentially expressed genes in early stage of stomach adenocarcinomas based on TCGA and GEO datasets

Background

Stomach adenocarcinomas (STAD) are the most common malignancy of the human digestive system and represent the fourth leading cause of cancer-related deaths. As early-stage STAD are generally mild or asymptomatic, patients with advanced STAD have short overall survival. Early diagnosis of STAD has a considerable influence on clinical outcomes.

Methods

The mRNA expression data and clinical indicators of STAD and normal tissues were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The gene expression differences were analyzed by R packages, and gene function enrichment analysis was performed. Kaplan–Meier method and univariate Cox proportional risk regression analysis were used to screen differential expressed genes (DEGs) related to survival of STAD patients. Multivariate Cox proportional risk regression analysis was used to further screen and determine the prognostic DEGs in STAD patients, and to construct a multigene prognostic prediction signature. The accuracy of predictive signature was tested by receiver operating characteristic (ROC) curve software package, and the nomogram of patients with STAD was drawn. Cox regression was used to investigate the correlation between multigene prognostic signature and clinical factors. The predictive performance of this model was compared with two other models proposed in previous studies using KM survival analysis, ROC curve analysis, Harrell consistency index and decision curve analysis (DCA). qRT-PCR and Western blot were used to verify the expression levels of prognostic genes. The pathways and functions of possible involvement of features were predicted using the GSEA method.

Results

A total of 569 early-stage specific DEGs were retrieved from TCGA-STAD dataset, including 229 up-regulated genes and 340 down-regulated genes. Enrichment analysis showed that the early-stage specific DEGs were associated with cytokine–cytokine receptor interaction, neuroactive ligand–receptor interaction, and calcium signaling pathway. Multiple Cox regression algorithm was used to identify 10 early-stage specific DEGs associated with overall survival (P < 0.01) of STAD patients, and a multi-mRNA prognosis signature was established. The patients were divided into high-risk group and low-risk group according to the risk score. In the training set, the prognostic signature was positively correlated with tumor size and stage (P < 0.05), survival curve (P < 0.001) and time-dependent ROC (AUC = 0.625). In the training dataset and test dataset, the both signatures had good predictive efficiencies. Cox regression and DCA analysis revealed that the prognostic signature was an independent factor and had a better predict effect than the conventional TNM stage classification method and the earlier published biomarkers on the prognosis of STAD patients.

Conclusion

In this study, based on the early-stage specifically expressed genes, the prognostic signature constructed through TCGA and GEO datasets may become an indicator for clinical prognosis assessment of STAD and a new strategy for targeted therapy in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40001-022-00827-4.

A 9‑gene expression signature to predict stage development in resectable stomach adenocarcinoma

BACKGROUND

Stomach adenocarcinoma (STAD) is a highly heterogeneous disease and is among the leading causes of cancer-related death worldwide. At present, TNM stage remains the most effective prognostic factor for STAD. Exploring the changes in gene expression levels associated with TNM stage development may help oncologists to better understand the commonalities in the progression of STAD and may provide a new way of identifying early-stage STAD so that optimal treatment approaches can be provided.

METHODS

The RNA profile retrieving strategy was utilized and RNA expression profiling was performed using two large STAD microarray databases (GSE62254, n = 300; GSE15459, n = 192) from the Gene Expression Omnibus (GEO) and the RNA-seq database within the Cancer Genome Atlas (TCGA, n = 375). All sample expression information was obtained from STAD tissues after radical resection. After excluding data with insufficient staging information and lymph node number, samples were grouped into earlier-stage and later-stage. Samples in GSE62254 were randomly divided into a training group (n = 172) and a validation group (n = 86). Differentially expressed genes (DEGs) were selected based on the expression of mRNAs in the training group and the TCGA group (n = 156), and hub genes were further screened by least absolute shrinkage and selection operator (LASSO) logistic regression. Receiver operating characteristic (ROC) curves were used to evaluate the performance of the hub genes in distinguishing STAD stage in the validation group and the GSE15459 dataset. Univariate and multivariate Cox regressions were performed sequentially.

RESULTS

22 DEGs were commonly upregulated (n = 19) or downregulated (n = 3) in the training and TCGA datasets. Nine genes, including MYOCD, GHRL, SCRG1, TYRP1, LYPD6B, THBS4, TNFRSF17, SERPINB2, and NEBL were identified as hub genes by LASSO-logistic regression. The model achieved discrimination in the validation group (AUC = 0.704), training-validation group (AUC = 0.743), and GSE15459 dataset (AUC = 0.658), respectively. Gene Set Enrichment Analysis (GSEA) was used to identify the potential stage-development pathways, including the PI3K-Akt and Calcium signaling pathways. Univariate Cox regression indicated that the nine-gene score was a significant risk factor for overall survival (HR = 1.28, 95% CI 1.08-1.50, P = 0.003). In the multivariate Cox regression, only SCRG1 was an independent prognostic predictor of overall survival after backward stepwise elimination (HR = 1.21, 95% CI 1.11-1.32, P < 0.001).

CONCLUSION

Through a series of bioinformatics and validation processes, a nine-gene signature that can distinguish STAD stage was identified. This gene signature has potential clinical application and may provide a novel approach to understanding the progression of STAD.

A nine–consensus–prognostic –gene–based prognostic signature, recognizing the dichotomized subgroups of gastric cancer patients with different clinical outcomes and therapeutic strategies

Background: The increasing prevalence and mortality of gastric cancer (GC) has promoted the urgent need for prognostic signatures to predict the long-term risk and search for therapeutic biomarkers.

Methods and materials: A total of 921 GC patients from three GEO cohorts were enrolled in the current study. The GSE15459 and GSE62254 cohorts were used to select the top prognostic gene via the evaluation of the area under the receiver operating characteristic (ROC) curve (AUC) values. The GSE84437 cohort was used as the external validation cohort. Least absolute shrinkage and selector operation (LASSO) regression analysis was applied to reduce the feature dimension and construct the prognostic signature. Furthermore, a nomogram was constructed by integrating the independent prognostic analysis and validated by calibration plot, decision curve analysis and clinical impact curve. The molecular features and response to chemo-/immunotherapy among risk subgroups were evaluated by the “MOVICS” and “ESTAMATE” R packages and the SubMap algorithm. Lauren classification and ACRG molecular subtype were obtained to compare with the risk model.

Results: Forty-four prognosis-associated genes were identified with a preset cutoff AUC value of 0.65 in both the GSE62254 and GSE15459 cohorts. With the 10-fold cross validation analysis of LASSO, nine genes were selected to construct the nine-consensus-prognostic-gene signature. The signature showed good prognostic value in the GSE62254 (p < 0.001, HR: 3.81, 95% CI: 2.44–5.956) and GSE15459 (p < 0.001, HR: 2.65, 95% CI: 1.892–3.709) cohorts and the external validation GSE84437 cohort (p < 0.001, HR: 2.06, 95% CI: 1.554–2.735). The nomogram constructed based on two independent predictive factors, tumor stage and the signature, predicted events tightly consistent with the actual (Hosmer–Lemeshow p value: 1-year, 0.624; 3-years, 0.795; 5-years, 0.824). For the molecular features, we observed the activation of apical junction, epithelial mesenchymal transition, and immune pathways in the high-risk group, while in the low-risk group, cell cycle associated G2M, E2F and MYC target pathways were activated. Based on the results we obtained, we indicated that gastric patients in the low-risk group are more suitable for 5-fluorouracil therapy, while high-risk group patients are more suitable for anti-CTLA4 immunotherapy, these results need more support in the further studies. After compare with proposed molecular subtypes, we realized that the nine-consensus prognostic gene signature is a powerful addition to identify the gastric patients with poor prognosis.

Conclusion: In summary, we constructed a robust nine-consensus-prognostic-gene signature for the prediction of GC prognosis, which can also predict the personalized treatment of GC patients.

PLXDC1 Can Be a Biomarker for Poor Prognosis and Immune Evasion in Gastric Cancer

Background

Research has revealed that Plexin domain containing 1 (PLXDC1) is correlated with the prognosis of a variety of tumors, but its role in the tumor microenvironment (TME) of gastric cancer has not been reported.

Methods

In this study, we analyzed PLXDC1 expression in gastric cancer using the Oncomine and the Cancer Genome Atlas (TCGA) databases and immunohistochemical staining experiments, and performed prognostic assessment with data from the TCGA and Kaplan–Meier Plotter databases. The immunomodulatory role of PLXDC1 in the gastric cancer TME was analyzed by signaling pathway enrichment, immune cell correlation analysis, immunomodulator risk model construction and immunohistochemical staining experiments of immune cells.

Results

The results indicated that PLXDC1 was overexpressed in gastric cancer and that its overexpression was associated with poor prognosis. Multivariate Cox analysis revealed that PLXDC1 could be an independent biomarker of the risk of gastric cancer. Signaling pathway enrichment revealed that high PLXDC1 expression was involved in signaling pathways related to immune activation and stromal activation, and Tumor Immune Dysfunction and Exclusion (TIDE) assessment indicated that high PLXDC1 expression was associated with a significantly higher risk of immune evasion than low PLXDC1 expression. A Cox risk model based on PLXDC1-associated immunomodulators also presented poor prognosis, and immune evasion was significantly higher in the high-risk group than in the low-risk group. In addition, immunohistochemical staining of CD8/CD3/CD4⁺ T cells in the high and low PLXDC1 expression groups also observed immune cell distribution characteristics of immune evasion.

Conclusion

This study analyzed PLXDC1 from multiple biological perspectives and revealed that PLXDC1 can be a biomarker for poor prognosis and immune evasion in gastric cancer.

High expression of SMARCC1 predicts poor prognosis in gastric cancer patients

The switching/sucrose non-fermenting (SWI/SNF) chromatin remodeling complexes use the energy of ATP hydrolysis to remodel nucleosomes and modulate transcription, which plays an important role in tumors by regulating epigenetics. SWI/SNF Related, Matrix Associated, Actin Dependent Regulator of Chromatin, Subfamily C, Member 1 (SMARCC1) has dual roles in tumors but its role in gastric cancer remains unclear. This study was aimed to find the role of SMARCC1 in gastric cancer. SMARCC1 expression across various tumors from The Cancer Genome Atlas was analyzed using TIMER 2.0 (http://timer.comp-genomics.org/). SMARCC1 mRNA expression profiles in gastric cell lines and gastric tissues were compared with normal tissues and analyzed in the Cancer Cell Line Encyclopedia, Oncomine, and Gene Expression Omnibus databases. SMARCC1 mRNA and protein were then examined in fresh gastric cancer tissues and compared with adjacent normal tissues using quantitative real-time PCR, western blotting, and immunohistochemistry. Associations between SMARCC1 expression and clinicopathological factors, overall survival, and disease-free survival were further evaluated using 130 gastric cancer samples harvested from patients after radical total gastrectomy or subtotal gastrectomy at the Xiangya Hospital of Central South University (Changsha, China). SMARCC1 was frequently upregulated in gastric cancer cells and tissues. SMARCC1 overexpression was significantly associated with tumor size (P=0.002), differentiation (P=0.006), depth of invasion (P=0.001), lymph node involvement (P=0.016), and TNM stage (P=0.007). Furthermore, univariate and multivariate Cox analysis revealed that high SMARCC1 expression, depth invasion, lymph node involvement, and TNM stage were independent risk factors for both overall and disease-free survival in gastric cancer patients (all P<0.05). Kaplan-Meier survival analysis revealed that high SMARCC1 expression predicted poor prognosis in gastric cancer patients (P<0.01). High SMARCC1 expression contributes to poor prognosis in gastric cancer patients. SMARCC1 may be a prognostic biomarker and therapeutic target in gastric cancer.

IFITM3 promotes malignant progression, cancer stemness and chemoresistance of gastric cancer by targeting MET/AKT/FOXO3/c-MYC axis

Background

Targeting the HGF/MET signaling pathway has been a viable therapeutic strategy for various cancer types due to hyperactivation of HGF/MET axis occurs frequently that leads to detrimental cancer progression and recurrence. Deciphering novel molecule mechanisms underlying complex HGF/MET signaling network is therefore critical to development of effective therapeutics for treating MET-dependent malignancies.

Results

Using isobaric mass tag-based quantitative proteomics approach, we identified IFITM3, an interferon-induced transmembrane protein that was highly expressed in micro-dissected gastric cancer (GC) tumor regions relative to adjacent non-tumor epithelia. Analyses of GC clinical specimens revealed that expression IFITM3 was closely correlated to advanced pathological stages. IFITM3 has been reported as a PIP3 scaffold protein that promotes PI3K signaling. In present study, we unprecedentedly unraveled that IFITM3 associated with MET and AKT to facilitate HGF/MET mediated AKT signaling crosstalk in suppressing FOXO3, consequently leading to c-MYC mediated GC progression. In addition, gene ontology analyses of the clinical GC cohort revealed significant correlation between IFITM3-associated genes and targets of c-MYC, which is a crucial downstream effector of HGF/MET pathway in cancer progression. Moreover, we demonstrated ectopic expression of IFITM3 suppressed FOXO3 expression, consequently led to c-MYC induction to promote tumor growth, cell metastasis, cancer stemness as well as chemoresistance. Conversely, depletion of IFITM3 resulted in suppression of HGF triggered cellular growth and migration via inhibition of AKT/c-MYC signaling in GC.

Conclusions

In summary, our present study unveiled a novel regulatory mechanism for c-MYC-driven oncogenesis underlined by IFITM3-mediated signaling crosstalk between MET associated AKT signaling cascade.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00858-8.

Prognostic and Immunological Value of GNB4 in Gastric Cancer by Analyzing TCGA Database

Background

Gastric cancer (GC) represents a universal malignant tumor of the digestive system. Stromal and immune cells belong to two main nontumor components exerting a vital function in the tumor microenvironment.

Methods

Based on TCGA database, this study downloaded clinical information and gene profiles of GC. The ESTIMATE algorithm was adopted for evaluating the score of immune-infiltrating cells. This work employed Sangerbox to explore the differentially denoted genes (DEGs) related to stromal, immunity, and prognosis. Besides, the STRING database was involved in order to detect the association among the proteins. The MCODE module of Cytoscape software was used to screen key genes. Oncomine and GEPIA databases were used, aiming to study the differences in key genes in healthy gastric mucosa and GC. At last, we adopted TISDIB and TIMER databases for analyzing the association of guanine nucleotide binding protein subunit-4 (GNB4) between gastric cancer and tumor immune cells. qRT-PCR was applied for exploring differential GNB4 expression between GC and normal gastric mucosa and investigating the relation of GNB4 with tumor-infiltrating lymphocytes (TILs).

Results

Patients undergoing a great stromal score exhibited worse prognostic outcome, and cases having a low immune score had better prognosis. Overall, altogether 656 genes were upregulated with 5 genes being downregulated, which were matrix immune-related differential genes. Furthermore, 18 genes were screened as hub genes on the basis of the univariate Cox risk model of TCGA database (82 differential genes predicted poor GC survival). Oncomine and GEPIA databases revealed that GNB4 expression in gastric cancer was obviously higher in comparison with that in normal gastric mucosa. The GSEA, TISDIB, and TIMER databases revealed that GNB4 is involved in various tumor signal pathways and immune and metabolic processes. qRT-PCR demonstrated that GNB4 expression in gastric cancer was notably higher in comparison with that in normal gastric mucosa, showing significant association with matrix TILs.

Conclusion

The selected key gene GNB4 is a potential biomarker to guide the immunotherapy of gastric cancer.

High Expression of PRNP Predicts Poor Prognosis in Korean Patients with Gastric Cancer

Gastric cancer (GC) has the highest occurrence and fourth-highest mortality rate of all cancers in Korea. Although survival rates are improving with the development of diagnosis and treatment methods, the five-year survival rate for stage 4 GC in Korea remains <10%. Therefore, it is important to identify candidate prognostic factors for predicting poor prognosis. PRNP is a gene encoding the prion protein PrP, which has been noted for its role in the nervous system and is known to be upregulated in various cancers and associated with both cell proliferation and metastasis. However, the value of PRNP as a prognostic factor for Korean GC patients remains unclear. Here, we analyzed the relationship between PRNP expression and survival in three independent datasets for Korean patients with GC as well as the TCGA-STAD dataset. Survival analysis indicates that high levels of PRNP expression are associated with poor overall survival of patients with GC. Gene set enrichment analysis showed that PRNP is associated with epithelial mesenchymal transition and Hedgehog signaling. In addition, proliferation of GC cell lines was inhibited after siRNA-mediated knockdown of PRNP. In conclusion, our study suggests a potential role for PRNP as a candidate prognostic factor for patients with GC.

TEADs serve as potential prognostic biomarkers and targets for human gastric cancer

TEADs are critical transcription factors that participate in the Hippo pathway. Evidence indicates the promotion role of TEADs in cancer progression. However, the role of TEADs and the expression patterns in gastric cancer remains unclear. In this study, we evaluated the expression levels of TEADs in gastric cancer samples, and the clinical outcomes of patients with high TEADs expression were observed. Co-expression and interaction analysis as well as functional enrichment analysis were further conducted to determine the potential role of TEADs in gastric cancer. These results suggested TEADs may serve as the prognostic biomarkers or therapeutic targets for gastric cancer. However, more studies are warranted to verify our findings and promote the application in gastric cancer patients.

Development and validation of an RNA-seq-based transcriptomic risk score for asthma

Recent progress in RNA sequencing (RNA-seq) allows us to explore whole-genome gene expression profiles and to develop predictive model for disease risk. The objective of this study was to develop and validate an RNA-seq-based transcriptomic risk score (RSRS) for disease risk prediction that can simultaneously accommodate demographic information. We analyzed RNA-seq gene expression data from 441 asthmatic and 254 non-asthmatic samples. Logistic least absolute shrinkage and selection operator (Lasso) regression analysis in the training set identified 73 differentially expressed genes (DEG) to form a weighted RSRS that discriminated asthmatics from healthy subjects with area under the curve (AUC) of 0.80 in the testing set after adjustment for age and gender. The 73-gene RSRS was validated in three independent RNA-seq datasets and achieved AUCs of 0.70, 0.77 and 0.60, respectively. To explore their biological and molecular functions in asthma phenotype, we examined the 73 genes by enrichment pathway analysis and found that these genes were significantly (p < 0.0001) enriched for DNA replication, recombination, and repair, cell-to-cell signaling and interaction, and eumelanin biosynthesis and developmental disorder. Further in-silico analyses of the 73 genes using Connectivity map shows that drugs (mepacrine, dactolisib) and genetic perturbagens (PAK1, GSR, RBM15 and TNFRSF12A) were identified and could potentially be repurposed for treating asthma. These findings show the promise for RNA-seq risk scores to stratify and predict disease risk.

Comprehensive Landscape of STEAP Family Members Expression in Human Cancers: Unraveling the Potential Usefulness in Clinical Practice Using Integrated Bioinformatics Analysis

The human Six-Transmembrane Epithelial Antigen of the Prostate (STEAP) family comprises STEAP1-4. Several studies have pointed out STEAP proteins as putative biomarkers, as well as therapeutic targets in several types of human cancers, particularly in prostate cancer. However, the relationships and significance of the expression pattern of STEAP1-4 in cancer cases are barely known. Herein, the Oncomine database and cBioPortal platform were selected to predict the differential expression levels of STEAP members and clinical prognosis. The most common expression pattern observed was the combination of the over- and underexpression of distinct STEAP genes, but cervical and gastric cancer and lymphoma showed overexpression of all STEAP genes. It was also found that STEAP genes’ expression levels were already deregulated in benign lesions. Regarding the prognostic value, it was found that STEAP1 (prostate), STEAP2 (brain and central nervous system), STEAP3 (kidney, leukemia and testicular) and STEAP4 (bladder, cervical, gastric) overexpression correlate with lower patient survival rate. However, in prostate cancer, overexpression of the STEAP4 gene was correlated with a higher survival rate. Overall, this study first showed that the expression levels of STEAP genes are highly variable in human cancers, which may be related to different patients’ outcomes.

Crosstalk of Histone and RNA Modifications Identified a Stromal-Activated Subtype with Poor Survival and Resistance to Immunotherapy in Gastric Cancer

Emerging evidence has revealed the pivotal role of epigenetic modifications in shaping the tumor microenvironment (TME). However, crosstalk between different modification types and their clinical relevance in cancers remain largely unexplored. In this study, using ChIP/MeRIP-seq data of seven human gastric cell lines, we systematically characterized the crosstalk of four epigenetic modification types including H3K4me1, H3K4me3, H3K27ac, and N6-methyladenosine (m6A) and identified a recurrent subtype with high FTO expression and low HDAC1 expression across three independent gastric cancer (GC) cohorts, which we named the epigenetic-modification-dysregulated (EMD) subtype. Patients of the EMD subtype were featured with poor survival, stromal activation, and immune suppression. Extensive relevance to clinical characteristics was observed in the EMD subtype, including the Lauren classification, MSI status, histological grade, TNM stage, the Asian Cancer Research Group classification, and the immune/fibrotic classification. An EMD score was then constructed using WGCNA and ssGSEA algorithms, to precisely recognize the EMD subtype and indicate prognosis and response to immunotherapy in multiple independent GC cohorts. Correlations of the EMD score with tumor mutation burden, tumor purity, aneuploidy score, tumorigenic pathways, TME characteristics, and FTO/HDAC1 ratio were measured. In vitro experiments were performed to demonstrate the correlation between FTO and the epithelial–mesenchymal transition pathway, which suggested FTO as a targetable vulnerability for GC patients with a high EMD score. Altogether, by comprehensively analyzing the epigenetic modification patterns of 1518 GC patients, we identified a novel stromal-activated subtype with poor survival and resistance to immunotherapy, which might benefit from the combined immune checkpoint inhibition therapy with FTO inhibition.

Circulating exosomal gastric cancer-associated long noncoding RNA1 as a noninvasive biomarker for predicting chemotherapy response and prognosis of advanced gastric cancer: A multi-cohort, multi-phase study

Background

A previous validated study has identified the diagnostic value of circulating exosomal lncRNA-GC1 for detecting and monitoring gastric cancer. We aimed to further determine the predictive role of circulating exosomal lncRNA-GC1 for prognosis and chemotherapy response.

Methods

We retrospectively conducted a multi-phase analysis with four independent cohorts of 981 patients. A training cohort was used to generate the predictive model. One internal and two external cohorts were recruited as validation cohorts. Patients with stage II or III gastric cancer in the combined cohort were used to evaluate the predictive value of circulating exosomal lncRNA-GC1 for chemotherapy response.

Findings

In the training cohort, circulating exosomal lncRNA-GC1 was identified as an independent prognostic predictor for disease-free and overall survival. A prognostic risk stratification model based on circulating exosomal lncRNA-GC1 and AJCC stage revealed better predictive accuracy for disease-free and overall survival than the traditional AJCC stage system alone (C-index: DFS 0.701 vs 0.614; OS 0.720 vs 0.611, both P<0.05). And it has been further verified in the validation cohorts. In interaction analysis, for stage II and III GC, patients with low-level of circulating exosomal lncRNA-GC1 derived more survival benefit from adjuvant chemotherapy (P < 0.05); while those with high-level did not.

Interpretation

Measurement of circulating exosomal lncRNA-GC1 provides clinically important prognostic information and could complement the AJCC stage to optimize decision-making for selecting patients who could benefit more from fluorouracil-based chemotherapy after surgery.

Funding

The funders are listed in the Acknowledgement.

A blood-based miRNA signature with prognostic value for overall survival in advanced stage non-small cell lung cancer treated with immunotherapy

Immunotherapies have recently gained traction as highly effective therapies in a subset of late-stage cancers. Unfortunately, only a minority of patients experience the remarkable benefits of immunotherapies, whilst others fail to respond or even come to harm through immune-related adverse events. For immunotherapies within the PD-1/PD-L1 inhibitor class, patient stratification is currently performed using tumor (tissue-based) PD-L1 expression. However, PD-L1 is an accurate predictor of response in only ~30% of cases. There is pressing need for more accurate biomarkers for immunotherapy response prediction. We sought to identify peripheral blood biomarkers, predictive of response to immunotherapies against lung cancer, based on whole blood microRNA profiling. Using three well-characterized cohorts consisting of a total of 334 stage IV NSCLC patients, we have defined a 5 microRNA risk score (miRisk) that is predictive of overall survival following immunotherapy in training and independent validation (HR 2.40, 95% CI 1.37-4.19; P < 0.01) cohorts. We have traced the signature to a myeloid origin and performed miRNA target prediction to make a direct mechanistic link to the PD-L1 signaling pathway and PD-L1 itself. The miRisk score offers a potential blood-based companion diagnostic for immunotherapy that outperforms tissue-based PD-L1 staining.

GGT5 Is an Independent Prognostic Biomarker in Stomach Adenocarcinoma

Gastric cancer is one of the cancers with the highest incidence in the world. Gamma-glutamyltransferase 5 (GGT5) is expressed in different cancers and its role in cancers remains unclear. In this study, we aimed to evaluate the value of GGT5 in stomach adenocarcinoma (STAD). In TCGA, patients with high GGT5 expression had poor overall survival (P=0.006). Based on GSE62254, high expression of GGT5 was associated with poor OS (P=0.014) and PFS (P=0.042). The same result was observed in GSE14210. We further discovered that GGT5 expression was associated with stage, grade, and T stage. Further prognostic analysis of GGT5 showed that GGT5 was associated with prognosis in both univariate analysis (P=0.032) and multivariate analysis (P=0.029). We used gene set enrichment analysis (GSEA) to explore the possible mechanism of GGT5. GSEA suggests that overexpression of GGT5 may be involved in leukocyte transendothelial migration, JAK-STAT signaling pathway, MAPK signaling pathway, and melanoma. The high-expression GGT5 group had higher concentrations of M2 macrophages, T cell regulators, and monocytes, but the contents of plasma cells and M1 macrophages were higher in the low-expression GGT5 group. The results showed that the ESTIMATEScore, ImmuneScore, and StromalScore of the high-expression GGT5 group were higher than those of the low-expression GGT5 group. PD1 and CTLA4 expression levels were higher in the high-expression GGT5 group. The high-expression GGT5 group may be more effective for immunotherapy. These results suggested that GGT5 could be a potential prognostic molecular predictor in STAD.

TWIST1-EP300 Expedites Gastric Cancer Cell Resistance to Apatinib by Activating the Expression of COL1A2

The association between collagen type I alpha (COL1A) and chemoresistance has been verified in cancers. However, the specific role of COL1A2 in gastric cancer (GC) cell resistance to apatinib, a highly selective small-molecule inhibitor of vascular endothelial growth factor receptor 2, has not been investigated before. The purpose of this study was to explore the potential factors associated with COL1A2 regulation on GC cell apatinib resistance in vitro. With the aid of the Oncomine database and integrated bioinformatics methods, we identified COL1A2 overexpression in GC and its prognostic value. Mechanistically, the COL1A2 promoter has a distinct H3K27ac modification site and that E1A binding protein p300 (EP300) and twist family bHLH transcription factor 1 (TWIST1) can bind to the COL1A2 promoter, which in turn transcriptionally activated COL1A2 expression. In addition, overexpression of COL1A2 significantly promoted resistance to apatinib in GC cells, but knockdown of EP300 or TWIST1 remarkably inhibited COL1A2 expression and promoted sensitivity of GC cells to apatinib. Our findings demonstrated that the combination of EP300 and TWIST1 has a synergistically regulatory effect on COL1A2 expression, thus contributing to apatinib resistance in GC cells.

Comprehensive molecular characterization and identification of prognostic signature in stomach adenocarcinoma on the basis of energy-metabolism-related genes

BACKGROUND

Stomach adenocarcinoma (STAD) is a leading cause of cancer deaths, but its molecular and prognostic characteristics has never been fully illustrated.

AIM

To describe a molecular evaluation of primary STAD and develop new therapies and identify promising prognostic signatures.

METHODS

We describe a comprehensive molecular evaluation of primary STAD based on comprehensive analysis of energy-metabolism-related gene (EMRG) expression profiles.

RESULTS

On the basis of 86 EMRGs that were significantly associated to patients’ progression-free survival (PFS), we propose a molecular classification dividing gastric cancer into two subtypes: Cluster 1, most of which are young patients and display more immune and stromal cell components in tumor microenvironment and lower tumor priority; and Cluster 2, which show early stages and better PFS. Moreover, we construct a 6-gene signature that can classify the prognostic risk of patients after a three-phase training test and validation process. Compared with patients with low-risk score, patients with high-risk score had shorter overall survival. Furthermore, calibration and DCA analysis plots indicate the excellent predictive performance of the 6-gene signature, and which present higher robustness and clinical usability compared with three previous reported prognostic gene signatures. According to gene set enrichment analysis, gene sets related to the high-risk group were participated in the ECM receptor interaction and hedgehog signaling pathway.

CONCLUSION

Identification of the EMRG-based molecular subtypes and prognostic gene model provides a roadmap for patient stratification and trials of targeted therapies.

ENTREP/FAM189A2 encodes a new ITCH ubiquitin ligase activator that is downregulated in breast cancer

The HECT-type ubiquitin E3 ligases including ITCH regulate many aspects of cellular function through ubiquitinating various substrates. These ligases are known to be allosterically autoinhibited and to require an activator protein to fully achieve the ubiquitination of their substrates. Here we demonstrate that FAM189A2, a downregulated gene in breast cancer, encodes a new type of ITCH activator. FAM189A2 is a transmembrane protein harboring PPxY motifs, and the motifs mediate its association with and ubiquitination by ITCH. FAM189A2 also associates with Epsin and accumulates in early and late endosomes along with ITCH. Intriguingly, FAM189A2 facilitates the association of a chemokine receptor CXCR4 with ITCH and enhances ITCH-mediated ubiquitination of CXCR4. FAM189A2-knockout prohibits CXCL12-induced endocytosis of CXCR4, thereby enhancing the effects of CXCL12 on the chemotaxis and mammosphere formation of breast cancer cells. In comparison to other activators or adaptors known in the previous studies, FAM189A2 is a unique activator for ITCH to desensitize CXCR4 activity, and we here propose that FAM189A2 be renamed as ENdosomal TRansmembrane binding with EPsin (ENTREP).

Comprehensive Analysis and Identification of Prognostic Biomarkers and Therapeutic Targets Among FAM83 Family Members for Gastric Cancer

Background: Gastric cancer (GC) is one of the most common and poor prognosis malignancy in the world. The Family with sequence similarity 83 (FAM83) comprises of eight members of A–H. Accumulating evidence confirmed important roles for FAM83 family in tumorigenesis and progression. However, the prognostic values of FAM83 family in GC still have not been clarified.

Methods: ONCOMINE, UALCAN, GEPIA, THE HUMAN PROTEIN ATLAS, Kaplan–Meier Plotter, cBioPortal, DAVID, STRING and TIMER databases and R software were adopted in this study.

Results: In this study, we demonstrated that the mRNA levels of FAM83 B/C/D/H were significantly up-regulated in stomach adenocarcinoma (STAD), but the protein level of FAM83G/H were remarkable lowly in STAD. Next, FAM83C/D/G/H were significantly associated with tumor stages in STAD patients. Then, the mutation rate of FAM83 family members in STAD patients was 46%, and the highest mutation rate was FAM83H (23%). Furthermore, the functions of FAM83 family and their 259 co-expression genes were primarily related to Shigellosis, RNA degradation and Ribosome biogenesis in eukaryotes pathway. Besides, we have established the prognostic model of FAM83 family in STAD, including the prognostic model of STAD patients (FAM83C/D/G), STAD with lymph node metastasis (FAM83C/D/G/H) and STAD with ERBB2 high expression (FAM83G/H). FAM83C/D high expression with a poor prognosis, while FAM83G/H high expression with a favorable prognosis of STAD. Additionally, we found that the expression of FAM83C/D/G/H were significantly correlated with the infiltration of six types of immune cells [B cells, CD8⁺T cells, CD4⁺T cells, macrophages and Myeloid dendritic cells (DC)], whereas CD4⁺T cells and Macrophage cells have higher risk scores (HR > 1) when FAM83C lowly expression and FAM83D highly expression. The risk score of NK cells was significantly reduced when FAM83G lowly expression and FAM83H highly expression (HR < 1).

Conclusion: These findings suggested that FAM83C/D/G/H might play key roles in STAD tumorigenesis and progression, and FAM83C/D might be risk factors but FAM83G/H might be favorable prognostic factors for STAD patients. In addition, CD4⁺T cells and Macrophage cells may be the promoters of FAM83D in progression of STAD, while NK cells may promote the protective effect of FAM83H on STAD patients.

Comprehensive bioinformatics analyses identified Homeobox B9 as a potential prognostic biomarker and therapeutic target for gastric cancer

Background

The Homeobox B (HOXB) family promotes tumor progression, but the mechanism of its action in gastric cancer (GC) is unclear. We sought to identify the HOXB family members that are critical to the prognosis of GC patients.

Methods

The Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), cBioPortal, UALCAN, Kaplan-Meier plotter, and the GeneMANIA databases were used to analyze the messenger RNA (mRNA) expression levels, prognostic value, and gene-gene interaction network of the HOXB9 family members in GC. The expression of HOXB9 in GC and its relationship with various clinicopathological parameters and the prognosis of patients were verified by immunohistochemistry.

Results

The expression of HOXB3, HOXB5, HOXB6, HOXB7, HOXB9, and HOXB13 mRNA was significantly upregulated in GC. There was a significant correlation between the upregulation of HOXB3, HOXB5, and HOXB9 mRNA and a low overall survival (OS) rate. The high expression of HOXB7, HOXB9, and HOXB13 mRNA was closely correlated to tumor grade and stage. HOXB9 was the HOXB family member most closely related to the occurrence and development of GC. A further analysis showed that HOXB9 might be involved in deoxyribonucleic acid repair and division regulation. A validation study showed that the advanced cancer group had a higher level of HOXB9 expression than the early cancer group. The high expression of HOXB9 in gastric tissue plays an important role in the survival and prognosis of GC patients.

Conclusions

HOXB family members have different degrees of abnormal expression in GC. High HOXB9 expression in GC tissues was significantly correlated with a worse prognosis. Thus, HOXB9 is a potential novel biomarker and therapeutic target for GC.

Diagnostic and prognostic value of HOXC family members in gastric cancer

Aims: HOX clusters encode proteins that play pivotal roles in regulating transcription factors and many other proteins during embryogenesis. However, little is known about the diagnostic and prognostic values of HOXC family members in gastric cancer (GC). Materials and methods: The authors evaluated the data in patients with GC based on bioinformatics analysis. Results: HOXC6/8/9/10/11/13 were overexpressed in GC and associated with a poor prognosis. HOXC4/5 were downregulated in GC tissues. Receiver operating characteristic curve analysis demonstrated that they have high diagnostic value. In addition, HOXC4/5/6/9/10/11/13 were negatively correlated with DNA methylation level. The gene set enrichment analysis results implied that they play essential roles in multiple biological processes underlying tumorigenesis. Conclusion: HOXC family members are potential targets for diagnosis and may work as prognostic biomarkers of GC.

Thrombospondin-4 Is a Soluble Dermal Inflammatory Signal That Selectively Promotes Fibroblast Migration and Keratinocyte Proliferation for Skin Regeneration and Wound Healing

Thrombospondin-4 (THBS4) is a non-structural extracellular matrix molecule associated with tissue regeneration and a variety of pathological processes characterized by increased cell proliferation and migration. However, the mechanisms of how THBS4 regulates cell behavior as well as the pathways contributing to its effects have remained largely unexplored. In the present study we investigated the role of THBS4 in skin regeneration both in vitro and in vivo. We found that THBS4 expression was upregulated in the dermal compartment of healing skin wounds in humans as well as in mice. Application of recombinant THBS4 protein promoted cutaneous wound healing in mice and selectively stimulated migration of primary fibroblasts as well as proliferation of keratinocytes in vitro. By using a combined proteotranscriptomic pathway analysis approach we discovered that β-catenin acted as a hub for THBS4-dependent cell signaling and likely plays a key role in promoting its downstream effects. Our results suggest that THBS4 is an important contributor to wound healing and its incorporation into novel wound healing therapies may be a promising strategy for treatment of cutaneous wounds.