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Identi Cation Hub Genes of Consensus Molecular Subtype Correlation Identication Hub Genes of Consensus Molecular Subtype Correlation With Immune Inltration and Predict Prognosis in Gastric Cancer Bin Yu First Aliated Hospital of Nanchang University Xin Yu First Aliated Hospital of Nanchang University Jianping Xiong First Aliated Hospital of Nanchang University Mei Ma ( [email protected] ) First Aliated Hospital of Nanchang University Research Article Keywords: Gastric Cancer, Prognosis, Immune Inltration, OGN, CHRDL2 Posted Date: July 29th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-692503/v2 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Identification Hub Genes of Consensus Molecular Subtype Correlation with Immune Infiltration and Predict Prognosis in Gastric Cancer Bin Yu1, Xin Yu2, Jianping Xiong2, Mei Ma2 1 Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, 330006 2 Department of Oncology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, 330006 * Correspondence: [email protected], [email protected] Abstract Gastric Cancer (GC) has a great fatality rate, meanwhile, there is still a lack of available biomarkers for prognosis. The goal of the research was to discover key and novel potential biomarkers for GC. We screened for the expression of significantly altered genes based on survival rates from two consensus molecular subtypes (CMS) of GC. Subsequently, functional enrichment analysis showed these genes involved in many cancers. And we picked 6 hub genes that could both secreted in the tumor microenvironment and expression enhanced in immune cells. Then, Kaplan Meier survival and expression detected in the tumor pathological stage were utilized to clarify the prognostic of these 6 hub genes. The results indicated that OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1, respectively, were significantly associated with poor OS in GC patients. And their expression increased with cancer advanced. Moreover, immune infiltration analysis displayed that those hub genes expression positively with M2 macrophage, CD8+ T Cell, most immune inhibitors, and majority immunostimulators. In summary, our results suggested that OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1 were all potential biomarkers for GC prognosis and might also be potential therapeutic targets for GC. Keywords Gastric Cancer, Prognosis, Immune Infiltration, OGN, CHRDL2 Introduction Gastric Cancer (GC) is one of the most common malignant tumors, and its mortality ranks fourth among all malignant tumors in the world[1]. According to the global cancer statistics (2020), there were over one million new cases of GC and with a mortality rate of 7.7% of the total cancer deaths[1]. Due to the lack of effective biomarkers, most patients with GC are diagnosed at an advanced stage and distant metastasis often occurs at this stage, leading to a poor prognosis. The 5-year overall survival rate of GC is about 20%−30% in most parts of the world[2]. The earlier the effective intervention for GC patients, the more beneficial to improve their survival rate. Therefore, it is necessary to identify the key prognostic biomarkers in early time for GC therapy. Immune checkpoint blockade (ICB) has been brought new hope for many cancers treatment. While ICB does not valid in most cases, including GC[3], and thus more research is required to drive the field forward. Immune-related cells in the tumor microenvironment (TME) also indispensable for the development, progression, and prognosis of GC. Despite CD8+T cells are considered to be an anti-tumor component in the TME[4], studies on the relationship between CD8+T cells and prognosis in GC yielded in divergence[5, 6]. Programmed cell death protein 1 (PD-1) is an important immune checkpoint molecule in CD8+ T cell and its upregulation disturbs the anti- tumor function of CD8+ T cell[7]. PD-1+CD8+ T cell infiltration was significantly increased in patients with GC[6]. While PD-1 blockade combined with immune modulators, such as TGF-β1 inhibitor, might take patients more benefits than targeted PD-1 alone [6]. And it was also reported that some subsets of CD8+T, such as CXCR5+CD8+T[8], but not CD8+T itself connected with better overall survival (OS) in patients with GC. Therefore, it is important to find out the key molecules that regulate immune modulators in TME or/and co-express molecular in CD8+T that mediated its function. Besides, the latest studies have proved that macrophages, mostly M2 polarized macrophages, have a vital role in the GC advance[9, 10]. Infiltration of M2 macrophage might be a worthwhile biomarker for GC prognosis[11]. Targeting M2 macrophages may be a promising therapeutic strategy, therefore, it is valuable that uncover M2- related molecules. Here, we picked out those genes that were significantly associated with the survival of GC patients. And selected hub genes, OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1, which secreted into TME and enhanced in immune cells. After validated their expression value for GC diagnosis, we performed immune infiltration analysis of these 6 hub genes. Our study might provide novel biomarkers for GC advance, and potential targets that combined using with ICB to improve GC therapy. Results Identification of robust genes associated with GC survival The COMSUC web server[12] was used to find out the hub genes significantly correlated with the survival of GC patients. we firstly clustered GC samples into two consensus molecular subtypes (CMS) by multiple methods, including K-means, hierarchical clustering (Hclust), non-negative matrix factorization (NMF) (Figure. 1a- b). And we found that CMS1 had lower survival than CMS2 (Figure. 1c). 52 genes prominently up-regulated expression in CMS1 compare to CMS2 (Figure. 1d). These genes may act independently or work in concert for GC survival. Functional enrichment analysis of survival-related CMS genes To identify the notably enriched pathway and biological process of survival-related CMS genes, we explored in Metascape website [13] and found those genes related to many processes of cancer (Figure. 2a). And the most relative pathway was early gastric cancer (Figure. 2a). Then we analyzed the sub-network of those CMS1 genes in TCGA RNAseq of STAD, most of them had some connections in each other (Figure. 2b). According to those results, we speculated whether those genes were regulated by some common transcription factors (TFs). After performing TF enrichment in Knock TF (http://www.licpathway.net/KnockTF/index.html), more than ten TFs predicted may regulate over 73% of genes of these selected 52 genes (Table 1). The top 4 TFs were TFAP4, TP53, CREB1, and PTEN, respectively (Figure. 2c), and they all have been reported to promote the progression of GC [14-17]. Furthermore, we explored the characteristics of the 52 genes in the GeneCards (https://www.genecards.org/) and the Human Protein Atlas (https://www.proteinatlas.org/). As shown in Table 2, 10 genes could be transcribed into secreted proteins, 22 genes enriched in immune cells and only 7 genes own both characters (Fig. 2d). Survival outcomes in selected genes To verify whether the selected 7 genes (OGN, CHRDL2, C2orf40, THBS4, CHRDL1, ANGPTL1, SLIT2) were correlated with worse overall survival (OS) in GC patients, survival analysis was performed in Kaplan Meier plotter [18]. On account of many articles that have been shown that SLIT2 was over-expression in gastric cancer and might be an independent risk factor for GC [19, 20], we did not explore it further in this paper. The Kaplan Meier plotter results showed that the up-regulated expression of OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1, respectively, was correlated with poorer OS in GC patients (Fig. 3a-f). Among them, OGN and CHRDL2 were firstly reported in GC that their expression was related to OS of GC patients. To further confirm the correlation of 6 genes expression with tumor progression in GC, expression in different stages was executed in GEPIA[21]. The analyzed results indicated that the expression of OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1 was gradually increased in the GC stage (Fig. 4a-f). These results revealed these 6 hub genes were significantly related to the aggravation and survival of GC. Immune cell infiltration analysis To investigate the relationship between the expression of these hub genes (OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1) and immune infiltration, the TIMER website[22] was used to analyze the correlation between these hub genes and multiple immune cells. The results indicated that the expression of these hub genes was significantly positively correlated with CD8+ T Cell, CD4+ T Cell, macrophage, neutrophil, dendritic cell (Fig. 5). Next, we further analyzed the correlations of macrophage subtypes infiltration with these hub genes in GC. The results exhibited these 6 hub genes had no significant link in M1-related markers with their expression, but exhibited remarkable connection in M2 and TAMs (Fig. 6). Correlation analysis between hub genes and immune markers To better understand the immune function of these hub genes, we explored the relationship between their expression and immune markers in TISIDB[23]. Tumor immunology analysis exhibited that the expression of these 6 genes was positively correlated with most immunoinhibitors (Fig. 7a) and majority immunostimulators (Fig. 8a). Furthermore, we check out the striking different genes verified again in GEPIA, like CSF1R and Cxcl12, and got similar results (Fig. 7b-g, 8b-g). In the end, we search data found that OGN, C2orf40, CHRDL2, THBS4, CHRDL1, and ANGPTL1 had different immune subtypes in GC (Fig. 9a-f) and their expression was divergent in various molecular subtypes (Fig. 10a-f). In summary, these results implied that these 6 hub genes might potentially govern the conscription and awakening of immune cells in GC. Discussion Chemotherapy, radiotherapy, surgery, immunotherapy, and targeted therapy are effective in the progression of GC in appropriate indications. While the limited OS that no more than 30% in most countries, there are still need specific biomarkers to guide rational using drugs, especially for ICB treatment.
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