scholarly journals High Expression of AMIGO2 Is an Independent Predictor of Poor Prognosis in Pancreatic Cancer

2021 ◽  
Author(s):  
zhang jing ◽  
Fu xi feng
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Patients ◽  
Tp53 Mutation ◽  
Enrichment Analysis ◽  
High Expression ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Human Protein Atlas ◽  
Cancer Tissues ◽  
Kaplan Meier Plotter

Abstract Background.The AMIGO2 extracellular domain has a leucine - rich repetitive domain (LRR) and encodes a type 1 transmembrane protein , and is a member of the AMIGO gene family .Although the abnormal expression of AMIGO2 is associated with multiple tumors , the relationship with pancreatic cancer is not clear .Methods.The expression of AMIGO2 mRNA and proteins in pancreatic cancer was analyzed using NCBI GEO database and GEPIA2、Human Protein Atlas database.The RNA sequencing data of pancreatic cancer and clinical data of pancreatic cancer patients in TCGA public database were retrospectively analyzed. AMIGO2 gene expression data and their corresponding clinical information in the sample were analyzed retrospectively. The diagnostic value of AMIGO2 expression in pancreatic cancer patients was determined by receiver operating characteristic (ROC) curve analysis. The effects of AMIGO2 expression differences on survival time of pancreatic cancer patients were analyzed by Kaplan-Meier Plotter database and GEPIA2 database.The correlation between AMIGO2 gene and TP53 mutation in pancreatic cancer was analyzed by UALCAN database and TIMER database. The similar genes of AMIGO2 in pancreatic cancer were analyzed by GEPIA2 database, and the biological behavior, cellular composition, molecular function enrichment analysis and protein interaction of similar genes were analyzed by DAVID database and Metascape database. enrichment analysis of AMIGO2 similar gene pathways using KEGG database. The MSIGDB cancer coexpression module in Harmonizome database and TIMER database were used to study the gene coexpression of AMIGO2 in pancreatic cancer. AMIGO2 transcription factors were predicted using the JASPER database. The pathway of AMIGO2 transcription factors and co-expression genes was studied by KEGG database.Results. The expression of AMIGO2 (GSE16515, GSE15471) in pancreatic cancer tissues was significantly higher than that in normal tissues (P < 0.05). The GEPIA2 database also confirmed that the expression of AMIGO2 in pancreatic cancer tissues was significantly higher than that in normal tissues. The expression level of AMIGO2 gene was correlated with lymph node metastasis and histological grade of pancreatic cancer (P<0.05). The high expression of AMIGO2 protein in pancreatic cancer was confirmed in Human Protein Atlas database. The overall survival rate and progression-free survival rate of pancreatic cancer patients with high expression of AMIGO2 were significantly shorter than those of patients with low expression of AMIGO2 in Kaplan-Meier Plotter database and GEPIA2 database. In the gene ontology analysis, it is found that AMIGO2 is involved in cell adhesion, proliferation, migration, apoptosis and other biological processes. KEGG analysis pathway is concentrated in the focal adhesion pathway, mitotic cell cycle changes, and the regulation of cell protein localization. Abnormal expression of AMIGO2 was found in pancreatic cancer caused by TP53 mutation in UALCAN and TIMER databases.In JASPAR database, we predicted that there are 10 transcription sites between AMIGO2 and transcription factor MYB. In addition, there are positive genes related to AMIGO2 in TIMER database and transcription factor MYB regulates tumor cell proliferation and apoptosis in PI3K-Akt signal transduction pathway and WNT signal pathway in pancreatic cancer.

scholarly journals DPYSL2 as potential diagnostic and prognostic biomarker linked to immune infiltration in lung adenocarcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yang-Jie Wu ◽  
Ai-Tao Nai ◽  
Gui-Cheng He ◽  
Fei Xiao ◽  
Zhi-Min Li ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Roc Curve ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
List Type ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background Dihydropyrimidinase like 2 (DPYSL2) has been linked to tumor metastasis. However, the function of DPSY2L in lung adenocarcinoma (LUAD) is yet to be explored. Methods Herein, we assessed DPYSL2 expression in various tumor types via online databases such as Oncomine and Tumor Immune Estimation Resource (TIMER). Further, we verified the low protein and mRNA expressions of DPYSL2 in LUAD via the ULCAN, The TCGA and GEPIA databases. We applied the ROC curve to examine the role of DPYSL2 in diagnosis. The prognostic significance of DPYSL2 was established through the Kaplan–Meier plotter and the Cox analyses (univariate and multivariate). TIMER was used to explore DPYSL2 expression and its connection to immune infiltrated cells. Through Gene Set Enrichment Analysis, the possible mechanism of DPYSL2 in LUAD was investigated. Results In this study, database analysis revealed lower DPYSL2 expression in LUAD than in normal tissues. The ROC curve suggested that expression of DPYSL2 had high diagnostic efficiency in LUAD. The DPYSL2 expression had an association with the survival time of LUAD patients in the Kaplan–Meier plotter and the Cox analyses. The results from TIMER depicted a markedly positive correlation of DPYSL2 expression with immune cells infiltrated in LUAD, such as macrophages, dendritic cells, CD4+ T cells, and neutrophils. Additionally, many gene markers for the immune system had similar positive correlations in the TIMER analysis. In Gene Set Enrichment Analysis, six immune-related signaling pathways were associated with DPYSL2. Conclusions In summary, DPYSL2 is a novel biomarker with diagnostic and prognostic potential for LUAD as well as an immunotherapy target. Highlights Expression of DPYSL2 was considerably lower in LUAD than in normal tissues. Investigation of multiple databases showed a high diagnostic value of DPYSL2 in LUAD. DPYSL2 can independently predict the LUAD outcomes. Immune-related mechanisms may be potential ways for DPYSL2 to play a role in LUAD.

scholarly journals Expression and Prognostic Characteristics of m6 A RNA Methylation Regulators in Breast Cancer

2020 ◽  
Vol 11 ◽  
Author(s):  
Bo Zhang ◽  
Yanlin Gu ◽  
Guoqin Jiang
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
High Expression ◽  
Cancer Gene ◽  
Breast Cancer Patients ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
Her 2 ◽  
Kaplan Meier Plotter

PurposeN6-methyladenosine (m6A) is the most prevalent modification in mRNA methylation which has a wide effect on biological functions. This study aims to figure out the efficacy of m6A RNA methylation regulator-based biomarkers with prognostic significance in breast cancer.Patients and MethodsThe 23 RNA methylation regulators were firstly analyzed through ONCOMINE, then relative RNA-seq transcriptome and clinical data of 1,096 breast cancer samples and 112 normal tissue samples were acquired from The Cancer Gene Atlas (TCGA) database. The expressive distinction was also showed by the Gene Expression Omnibus (GEO) database. The gene expression data of m6A RNA regulators in human tissues were acquired from the Genotype-Tissue Expression (GTEx) database. The R v3.5.1 and other online tools such as STRING, bc-GeneExminer v4.5, Kaplan-Meier Plotter were applied for bioinformatics analysis.ResultsResults from ONCOMINE, TCGA, and GEO databases showed distinctive expression and clinical correlations of m6A RNA methylation regulators in breast cancer patients. The high expression of YTHDF3, ZC3H13, LRPPRC, and METTL16 indicated poor survival rate in patients with breast cancer, while high expression of RBM15B pointed to a better survival rate. Both univariate and multivariate Cox regression analyses revealed that age and risk scores were related to overall survival (OS). Univariate analysis also delineated that stage, tumor (T) status, lymph node (N) status, and metastasis (M) status were associated with OS. From another perspective, Kaplan-Meier Plotter platform showed that the relatively high expression of YTHDF3 and LRPPRC and the relatively low expression of RBM15B, ZC3H13, and METTL16 in breast cancer patients had worse Relapse-Free Survival (RFS). Breast Cancer Gene-Expression Miner v4.5 showed that LRPPRC level was negatively associated with ER and PR expression, while METTL16, RBM15B, ZC3H13 level was positively linked with ER and PR expression. In HER-2 (+) breast cancer patients, the expression of LRPPRC, METTL16, RBM15B, and ZC3H13 were all lower than the HER-2 (−) group.ConclusionThe significant difference in expression levels and prognostic value of m6A RNA methylation regulators were analyzed and validated in this study. This signature revealed the potential therapeutic value of m6A RNA methylation regulators in breast cancer.

High-Expression HBO1 Predicts Poor Prognosis in Gastric Cancer

2019 ◽  
Vol 152 (4) ◽  
pp. 517-526 ◽  
Author(s):  
Yan Wang ◽  
Sufang Chen ◽  
Wei Tian ◽  
Qing Zhang ◽  
Chunyi Jiang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Messenger Rna ◽  
Origin Recognition Complex ◽  
Tnm Staging ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Serum Carcinoembryonic Antigen ◽  
Polymerase Chain ◽  
Cancer Tissues ◽  
Kaplan Meier Plotter

Abstract Objectives Our goal was to assess the expression of histone acetyltransferase binding to origin recognition complex 1 (HBO1) in gastric cancer and the effect on prognosis for the patients. Methods We used quantitative reverse transcription polymerase chain reaction, Western blot, and tissue microarray immunohistochemistry to investigate the expressions of HBO1 messenger RNA (mRNA) and protein in gastric cancer tissues. Online resources, including Oncomine and Kaplan-Meier Plotter, were used to further assess the correlation between HBO1 expression and the prognosis of the patients with gastric cancer. Results HBO1 mRNA and protein expressions in gastric cancer tissues were both significantly higher than those in normal tissues. The correlations between high HBO1 expression and differentiation, invasive depth (T), lymph node metastasis (N), distant metastasis (M), TNM staging, and serum carcinoembryonic antigen levels were positive. High HBO1 expression was negatively correlated with survival time in patients with gastric cancer. Conclusions HBO1 might be a valuable biomarker to evaluate the prognosis of patients with gastric cancer.

scholarly journals The prognostic values of signal transducers activators of transcription family in ovarian cancer

2017 ◽  
Vol 37 (4) ◽  
Author(s):  
Saisai Li ◽  
Bo Sheng ◽  
Menghuang Zhao ◽  
Qi Shen ◽  
Haiyan Zhu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Ovarian Carcinoma ◽  
Cancer Patients ◽  
Tp53 Mutation ◽  
Signal Transducers ◽  
Kaplan Meier ◽  
Poor Differentiation ◽  
Cancer Types ◽  
High Level ◽  
Kaplan Meier Plotter

Signal transducer and activator of transcription (STAT), a family of latent cytoplasmic transcription factors, are composed of seven identified members (STAT1, STAT2, STAT3, STAT4, STAT5a, STAT5b, STAT6). STATs are associated with several biological processes such as cell proliferation, invasion, and metastasis in various cancer types. In addition, the STAT family has been well studied as a prognostic predictor for a considerable number of solid tumors. However, the prognostic value of the STAT family in ovarian cancer patients remains unclear. In our present study, we intend to access the prognostic roles of the STAT family in ovarian carcinoma through the ‘Kaplan–Meier plotter’ (KM plotter) online database, which collected gene expression data and survival information (overall survival (OS)) from a total of 1582 ovarian cancer patients. Our results show that high mRNA expression of STAT1, STAT4, STAT5a, STAT5b, and STAT6, are correlated to a better OS of ovarian cancer patients, especially the high level of STAT1 and STAT4 are significantly related to a favorable OS for serous ovarian cancer patients. We further accessed the prognostic roles of individual STATs in other clinicopathological features, such as pathological grades, clinical stages, and TP53 mutation, and found that these genes indicate a favorable prognosis especially for late stage, poor differentiation, and TP53 mutated ovarian cancer patients. In conclusion, these results suggest that the STAT family plays a significant prognostic role in ovarian carcinoma and individual STATs, except STAT2 and STAT3, may act as favorable prognostic markers in ovarian cancer.

scholarly journals COL5A3 is a prognostic biomarker and correlated with immune infiltrates in pancreatic cancer

2021 ◽  
Author(s):  
Yongjie Li ◽  
Min Zeng ◽  
Ting Wang ◽  
Feng Jiang
Keyword(s):  
Pancreatic Cancer ◽  
Roc Curve ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
High Expression ◽  
Immune Infiltration ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Tumor Tissues

Abstract Background Pancreatic cancer is a malignant tumor of digestive system with high fatality rate, and its prognosis is very poor. Type Ⅴ collagen α3 (COL5A3) is highly expressed in a variety of tumor tissues, but its prognostic value and immune infiltration in pancreatic cancer are still unclear. Therefore, we evaluated the prognostic role of COL5A3 in pancreatic cancer and its correlation with immune infiltration. Methods The transcriptional expression profiles of COL5A3 in pancreatic cancer and normal tissues were downloaded from the Cancer Genome Atlas (TCGA). In the GEO (Gene expression omnibus) dataset (GSE16515), we compared the expression of COL5A3 in normal and tumor tissues. The expression of COL5A3 protein was evaluated by the human protein atlas (THPA). The effect of COL5A3 on survival was evaluated by Kaplan-Meier method. Receiver operating characteristic (ROC) curve was used to distinguish pancreatic cancer from paracancerous normal tissues. Protein-protein interaction (PPI) network was constructed by the STRING. Use the "ClusterProfiler" package for functional enrichment analysis. Tumor immune estimation resource (TIMER) and tumor-immune system interaction database (TISIDB) were used to determine the relationship between COL5A3mRNA expression and immune infiltration. Results Compared with normal tissues, COL5A3 is highly expressed in pancreatic cancer tissues. The high expression of COL5A3 is related to the poor clinicopathological features and poor prognosis of pancreatic cancer. Kaplan-Meier survival analysis showed that the prognosis of pancreatic cancer patients with high expression of COL5A3 was worse than that of patients with low expression of COL5A3. ROC curve shows that COL5A3 has high sensitivity and specificity in the diagnosis of pancreatic cancer. Correlation analysis showed that the expression of COL5A3mRNA was related to immune cell infiltration. Conclusion This study reveals for the first time that COL5A3 may be a new prognostic biomarker related to immune infiltration and provide a new target for the diagnosis and treatment of pancreatic cancer.

scholarly journals ACSL3 As a Potential Prognostic Biomarker in Patients With Breast Cancer

2021 ◽  
Author(s):  
Xiangyu Sun ◽  
Meng Li ◽  
Mozhi Wang ◽  
Mengshen Wang ◽  
Haoran Dong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Potential Function ◽  
Prognostic Value ◽  
Prognostic Biomarker ◽  
Human Protein ◽  
Breast Cancer Patients ◽  
Kaplan Meier ◽  
Human Protein Atlas ◽  
Kaplan Meier Plotter

Abstract Objective: To explore the expression pattern of long chain fatty acyl CoA synthetase 3 (ACSL3) in breast cancer, and evaluate the clinical significance of ACSL3 by analyzing potential function and prognostic value of ACSL3 in human breast carcinoma.Methods: The expression of ACSL3 in normal mammary tissues and breast tumor tissues was analyzed by GEPIA and Human Protein Atlas. The prognostic value of ACSL3 was evaluated by Kaplan–Meier plotter analysis. ACSL3 expression was analyzed by immunohistochemistry in 297 breast cancer patients from the First Hospital of China Medical University Furthermore, based on LinkedOmics database, analyses of GO and KEGG pathways were performed to identify the potential function of ACSL3. Tumor Immune Estimation Resource (TIMER) database was used to evaluate the association between ACSL3 and immune infiltration in breast cancer. Results: GEPIA and Human Protein Atlas indicated that ACSL3 was significantly upregulated in breast carcinomas. Kaplan-Meier plotter analysis showed that increased expression of ACSL3 mRNA was significantly associated with shorter overall survival (OS) and relapse-free survival (RFS) in breast cancer patients. Results from immunochemical staining showed that ACSL3 was obviously related to clinicopathological features of breast cancer, and ACSL3 was highly abundant in TNBC tumors. Moreover, survival analysis of breast cancer patients demonstrated that higher ACSL3 protein expression is unfavorable prognostic biomarker in breast cancer patients. Results from TIMER database indicated that ACSL3 expression was significantly correlated with infiltration level of multiple immune cells. Further studies are needed to explore underlying mechanism of the pro-tumor effects of ACSL3 expression.Conclusions: ACSL3 may not only serve as a reliable predictive biomarker of breast cancer but also have impact on the occurrence and progression of breast cancer. Thus, ACSL3 may be an emerging therapeutic target for the development of molecular-targeted therapeutic strategies for breast cancer.

scholarly journals Identification of ATFs in Human Breast Cancer by Integrated Bioinformatic Analysis

2021 ◽  
Author(s):  
chenchen Geng ◽  
Qian Pu ◽  
Shuxu Tian ◽  
Wenwen Geng ◽  
Haiyan Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Bioinformatic Analysis ◽  
Free Survival ◽  
Expression Levels ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Protein Expressions ◽  
Human Protein Atlas ◽  
Activating Transcription Factor ◽  
Kaplan Meier Plotter

Abstract Background: To obtain a thorough comprehension of the profile and prognosis of activating transcription factor (ATF) family members in breast cancer.Method: We searched Oncomine, GEPIA, cBioPortal, Kaplan-Meier plotter, and CancerSEA databases to assess expression level, prognostic value, and functions of ATFs in breast cancer. Results: In breast cancer, we found that the expression levels of genes like ATF1, ATF5, and ATF6, were higher than in normal tissues. While the expression levels of ATF3, ATF4, ATF7 were lower in the former than in the latter. Similarly, the ATFs protein expressions were consistent with this in the Human Protein Atlas database. High expressions of ATF2, ATF4, and ATF6-7 were associated with good relapse-free survival. Increased expressions of ATF4 and ATF7 had high overall survival. Conversely, the mRNA expression of ATF1 was negatively correlated with distant metastasis-free survival. Similarly, high expression of ATF2 had reduced post-progression survival. Conclusions: ATF1 was a target of potential therapeutic interest for breast cancer, and ATF4 and ATF6-7 were potential prognostic factors in evaluating breast cancer.

scholarly journals The expression tendency and prognostic value of PDGFRβ in oral cancer

2020 ◽  
Author(s):  
Lili Wang ◽  
Hongguang Song ◽  
Shiming Yang
Keyword(s):  
Overall Survival ◽  
Oral Cancer ◽  
Mrna Expression ◽  
Cancer Patients ◽  
Prognostic Value ◽  
High Expression ◽  
Mrna Expression Level ◽  
Kaplan Meier ◽  
Oral Cancer Patients ◽  
Cancer Tissues

Abstract Background Oral cancer is a common malignant tumor in head and neck with poor prognosis. This study aimed to determine the expression tendency and prognostic value of PDGFRβ in oral cancer. Methods The mRNA expression level of PDGFRβ in the oral cancer tissues and adjacent normal tissues of oral cancer patients were detected by quantitative real-time polymerase chain reaction (qRT-PCR). And the association of PDGFRβ expression with clinicopathological characteristic was analyzed via chi-square test. Then we used Kaplan-Meier analysis to analyze the effects of PDGFRβ expression on the overall survival of oral cancer patients. The multivariate cox analysis was used to evaluate its prognostic value. Results The results indicated that the mRNA expression level of PDGFRβ was significantly increased in oral cancer tissues compared with that in the adjacent normal tissue ( P < 0.001). And its expression is positively associated with clinical stage, T stage, lymph node metastasis and histological grade. Kaplan-Meier analysis revealed that patients with high expression of PDGFRβ had markedly worse overall survival than those with low expression of PDGFRβ (log rank test, P < 0.05). Additionally, cox regression analysis revealed that the high expression of PDGFRβ was an independent prognostic maker in oral cancer patients. Conclusion PDGFRβ is up-regulated and involved in the development of oral cancer. Moreover, it could be an independent prognostic bio-marker for oral cancer.

scholarly journals Identification of hub genes and potential drugs in hepatocellular carcinoma through integrated bioinformatics analysis

2020 ◽  
Author(s):  
Xiaolong Chen ◽  
Zhixiong Xia ◽  
Yafeng Wan ◽  
Ping Huang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Disease Free Survival ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Hub Genes ◽  
Free Survival ◽  
Protein Protein Interaction ◽  
Kaplan Meier ◽  
Human Protein Atlas ◽  
Kaplan Meier Plotter

Abstract BackgroundHepatocellular carcinoma (HCC) is the third cancer-related cause of death in the world. Until now, the involved mechanisms during the development of HCC are largely unknown. This study aims to explore the driven-genes and potential drugs in HCC. MethodsThree mRNA expression datasets were used to analyze the differentially expressed genes (DEGs) in HCC. The bioinformatics approaches include identification of DEGs and hub genes, GO terms analysis and KEGG enrichment analysis, construction of protein–protein interaction network. The expression levels of hub genes were validated based on TCGA, GEPIA and the Human Protein Atlas. Moreover, overall survival and disease-free survival analysis of the hub genes were further conducted by Kaplan-Meier plotter and the GEPIA. DGIdb database was performed to search the candidate drugs for HCC. ResultsFinally, 197 DEGs were identified. The PPI network was constructed using STRING software. Then ten genes were selected and considered as the hub genes. The ten genes were all closely related to the survival of HCC patients. DGIdb database predicted 39 small molecules as the possible drugs for treating HCC. ConclusionsOur study provides some new insights into HCC pathogenesis and treatments. The candidate drugs may improve the efficiency of HCC therapy in future.

scholarly journals COL5A3 is a Prognostic Biomarker and Correlated with Immune Infiltrates in Pancreatic Cancer

2021 ◽  
Author(s):  
Yongjie Li ◽  
Min Zeng ◽  
Ting Wang ◽  
Feng Jiang
Keyword(s):  
Pancreatic Cancer ◽  
Roc Curve ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
High Expression ◽  
Immune Infiltration ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Tumor Tissues

Abstract Pancreatic cancer is a malignant tumor of digestive system with high fatality rate, and its prognosis is very poor. Type Ⅴ collagen α3 (COL5A3) is highly expressed in a variety of tumor tissues, but its prognostic value and immune infiltration in pancreatic cancer are still unclear. Therefore, we evaluated the prognostic role of COL5A3 in pancreatic cancer and its correlation with immune infiltration. The transcriptional expression profiles of COL5A3 in pancreatic cancer and normal tissues were downloaded from the Cancer Genome Atlas (TCGA). In the GEO (Gene expression omnibus) dataset (GSE16515), we compared the expression of COL5A3 in normal and tumor tissues. The expression of COL5A3 protein was evaluated by the human protein atlas (THPA). The effect of COL5A3 on survival was evaluated by Kaplan-Meier method. Receiver operating characteristic (ROC) curve was used to distinguish pancreatic cancer from paracancerous normal tissues. Protein-protein interaction (PPI) network was constructed by the STRING. Use the "ClusterProfiler" package for functional enrichment analysis. Tumor immune estimation resource (TIMER) and tumor-immune system interaction database (TISIDB) were used to determine the relationship between COL5A3 mRNA expression and immune infiltration. Compared with normal tissues, COL5A3 is highly expressed in pancreatic cancer tissues. The high expression of COL5A3 is related to the poor clinicopathological features and poor prognosis of pancreatic cancer. Kaplan-Meier survival analysis showed that the prognosis of pancreatic cancer patients with high expression of COL5A3 was worse than that of patients with low expression of COL5A3. ROC curve shows that COL5A3 has high sensitivity and specificity in the diagnosis of pancreatic cancer. Correlation analysis showed that the expression of COL5A3 mRNA was related to immune cell infiltration. This study reveals for the first time that COL5A3 may be a new prognostic biomarker related to immune infiltration and provide a new target for the diagnosis and treatment of pancreatic cancer.

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