scholarly journals SPOCK1 and POSTN are Valuable Prognostic Biomarkers and Correlate with Tumor Immune Infiltrates in Colorectal Cancer

2021 ◽  
Author(s):  
Caiqin Gan ◽  
Mengting Li ◽  
Ganjing Peng ◽  
Wenjie Li ◽  
Haizhou Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Immune Cells ◽  
Cox Regression ◽  
Prognostic Biomarkers ◽  
Immune Checkpoints ◽  
Cancer Tissue ◽  
Cox Regression Analysis ◽  
Colorectal Tissue ◽  
Key Genes ◽  
Immune Score

Abstract Background: Immune cells and stromal cells in the tumor microenvironment (TME) play a vital role in the initiation and progression of colorectal cancer (CRC). The study aimed to screen valuable prognostic biomarkers in CRC based on stromal and immune scores.Method: We used the ESTIMATE algorithm to calculate the immune and stromal scores of CRC samples in TCGA. Then the CRC samples were divided into high and low score groups based on the median value of the immune and stromal scores. Differentially expressed genes (DEGs) associated with immune score and stromal score were screened. WGCNA and univariate COX regression analysis were performed to further identify key prognostic genes. The prognostic value of key genes was validated based on The Gene Expression Profiling Interactive Analysis (GEPIA) and GSE17536 dataset.TIMER and CIBERSORT algorithms were applied to analyze the correlations among key genes and tumor-infiltrating immune cells. Several pairs of colon cancer tissue were used to be proven.Result: 1314 upregulated and 4 downregulated genes associated with immune score and stromal score were identified, which were significantly enriched in immune-related biological processes and pathways. Among these DEGs, SPOCK1 and POSTN were identified as key prognostic genes. High expression of SPCOK1 and POSTN was associated with advanced clinical stage, T stage, N stage, and poor prognosis of CRC. The results from CIBERSORT and TIMER revealed that SPOCK1 and POSTN were associated with tumor-infiltrating immune cells, especially macrophages and neutrophils. Meanwhile, in several pairs of human colorectal tissue samples, SPOK1 and POSTN were found to be significantly overexpressed in colorectal tissue compared with para-cancer tissue, and macrophage surface markers CD68 (co-expressed by M1 and M2 macrophages) and CD206 (M2-specific macrophage expression) were also overexpressed in cancer tissue. Besides, SPOCK1 and POSTN expression were positively correlated with the expression of immune checkpoints.Conclusion: Collectively, our results indicate that SPOCK1 and POSTN may be novel prognostic biomarkers in CRC and correlate with immune infiltrates.

scholarly journals SPOCK1 and POSTN are Valuable Prognostic Biomarkers and Correlate with Tumor Immune Infiltrates in Colorectal Cancer

2021 ◽  
Author(s):  
Caiqin Gan ◽  
Mengting Li ◽  
Ganjing Peng ◽  
Wenjie Li ◽  
Haizhou Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Immune Cells ◽  
Cox Regression ◽  
Prognostic Biomarkers ◽  
Immune Checkpoints ◽  
Cancer Tissue ◽  
Cox Regression Analysis ◽  
Colorectal Tissue ◽  
Key Genes ◽  
Immune Score

Abstract Background: Immune cells and stromal cells in the tumor microenvironment (TME) play a vital role in the initiation and progression of colorectal cancer (CRC). The study aimed to screen valuable prognostic biomarkers in CRC based on stromal and immune scores.Method: We used the ESTIMATE algorithm to calculate the immune and stromal scores of CRC samples in TCGA. Then the CRC samples were divided into high and low score groups based on the median value of the immune and stromal scores. Differentially expressed genes (DEGs) associated with immune score and stromal score were screened. WGCNA and univariate COX regression analysis were performed to further identify key prognostic genes. The prognostic value of key genes was validated based on The Gene Expression Profiling Interactive Analysis (GEPIA) and GSE17536 dataset.TIMER and CIBERSORT algorithms were applied to analyze the correlations among key genes and tumor-infiltrating immune cells.Several pairs of colon cancer tissue were used to be proven.Result: 1314 upregulated and 4 downregulated genes associated with immune score and stromal score were identified, which were significantly enriched in immune-related biological processes and pathways. Among these DEGs, SPOCK1 and POSTN were identified as key prognostic genes. High expression of SPCOK1 and POSTN was associated with advanced clinical stage, T stage, N stage, and poor prognosis of CRC. The results from CIBERSORT and TIMER revealed that SPOCK1 and POSTN were associated with tumor-infiltrating immune cells, especially macrophages and neutrophils. Meanwhile, in several pairs of human colorectal tissue samples, SPOK1 and POSTN were found to be significantly overexpressed in colorectal tissue compared with para-cancer tissue, and macrophage surface markers CD68 (co-expressed by M1 and M2 macrophages) and CD206 (M2-specific macrophage expression) were also overexpressed in cancer tissue. Besides, SPOCK1 and POSTN expression were positively correlated with the expression of immune checkpoints.Conclusion: Collectively, our results indicate that SPOCK1 and POSTN may be novel prognostic biomarkers in CRC and correlate with immune infiltrates.

scholarly journals SPOCK1 and POSTN are Valuable Prognostic Biomarkers and Correlate With Tumor Immune Infiltrates in Colorectal Cancer

2020 ◽  
Author(s):  
Mengting Li ◽  
Wenjie Li ◽  
Haizhou Wang ◽  
Yanan Peng ◽  
Qian Hu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Immune Cells ◽  
Cox Regression ◽  
Clinical Stage ◽  
Vital Role ◽  
Prognostic Biomarkers ◽  
Advanced Clinical Stage ◽  
Cox Regression Analysis ◽  
Key Genes ◽  
Immune Score

Abstract BackgroundImmune cells and stromal cells in the tumor microenvironment (TME) play a vital role in the initiation and progression of colorectal cancer (CRC). The study aimed to screen valuable prognostic biomarkers in CRC on the basis of stromal and immune scores.MethodsWe used the ESTIMATE algorithm to calculate the immune and stromal scores of CRC samples in TCGA. Then the CRC samples were divided into high and low score groups based on the median value of the immune and stromal scores. Differentially expressed genes (DEGs) associated with immune score and stromal score were screened. WGCNA and univariate COX regression analysis were performed to further identify key prognostic genes. The prognostic value of key genes was validated based on The Gene Expression Profiling Interactive Analysis (GEPIA) and GSE17536 dataset. TIMER and CIBERSORT algorithms were applied to analyze the correlations among key genes and tumor-infiltrating immune cells. Results1314 upregulated and 4 downregulated genes associated with immune score and stromal score were identified, which were significantly enriched in immune-related biological processes and pathways. Among these DEGs, SPOCK1 and POSTN were identified as key prognostic genes. High expression of SPCOK1 and POSTN was associated with advanced clinical stage, T stage, N stage, and poor prognosis of CRC. The results from CIBERSORT and TIMER revealed that SPOCK1 and POSTN were associated with tumor-infiltrating immune cells, especially macrophages and neutrophils. Besides, SPOCK1 and POSTN expression were positively correlated with the expression of immune checkpoints.ConclusionCollectively, our results indicate that SPOCK1 and POSTN may be novel prognostic biomarkers in CRC and correlate with immune infiltrates.

scholarly journals Prediction of Prognostic Biomarkers and Construction of an Autophagy Prognostic Model for Colorectal Cancer Using Bioinformatics

2020 ◽  
Vol 19 ◽  
pp. 153303382098417
Author(s):  
Ting-ting Liu ◽  
Shu-min Liu
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Prognostic Model ◽  
Cox Regression ◽  
Small Gtpase ◽  
Functional Enrichment ◽  
Clinical Correlation ◽  
Cox Regression Analysis ◽  
Prognostic Analysis ◽  
Key Genes

Objective: The incidence of colorectal cancer is increasing every year, and autophagy may be related closely to the pathogenesis of colorectal cancer. Autophagy is a natural catabolic mechanism that allows the degradation of cellular components in eukaryotic cells. However, autophagy plays a dual role in tumorigenesis. It not only promotes normal cell survival and tumor growth but also induces cell death and suppresses tumors survival. In addition, the pathogenesis of various conditions, including inflammation, neurodegenerative diseases, or tumors, is associated with abnormal autophagy. The present work aimed to examine the significance of autophagy-related genes (ARGs) in prognosis prediction, to construct an autophagy prognostic model, and to identify independent prognostic factors for colorectal cancer (CRC). Methods: This study discovered a total of 36 ARGs in CRC cases using The Cancer Genome Atlas (TCGA) and Human Autophagy-dedicated (HADd) databases along with functional enrichment analysis. Then, an autophagy prognostic model was constructed using univariate Cox regression analysis, and the key prognostic genes were screened. Finally, independent prognostic markers were determined through independent prognostic analysis and clinical correlation analysis of key genes. Results: Of the 36 differentially expressed ARGs, 13 were related to prognosis, as determined by univariate Cox regression analysis. A total of 6 key genes were obtained by a multivariate Cox regression analysis. Independent prognostic values were shown by 3 genes, namely, microtubule-associated protein 1 light chain 3 (MAP1LC3C), small GTPase superfamily and Rab family (RAB7A), and WD-repeat domain phosphoinositide-interacting protein 2 (WIPI2) by independent prognostic analysis and clinical correlation. Conclusions: In this study, molecular bioinformatics technology was employed to determine and construct a prognostic model of autophagy for colon cancer patients, which revealed 3 autophagy-related features, namely, MAP1LC3C, WIPI2, and RAB7A.

scholarly journals Development of an Immune Infiltration-Related Eight-Gene Prognostic Signature in Colorectal Cancer Microenvironment

2020 ◽  
Vol 2020 ◽  
pp. 1-43
Author(s):  
Beilei Wu ◽  
Lijun Tao ◽  
Daqing Yang ◽  
Wei Li ◽  
Hongbo Xu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Score ◽  
Immune Cells ◽  
Clinical Characteristics ◽  
Cox Regression ◽  
Roc Curves ◽  
Functional Enrichment ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Score Model

Objective. Stromal cells and immune cells have important clinical significance in the microenvironment of colorectal cancer (CRC). This study is aimed at developing a CRC gene signature on the basis of stromal and immune scores. Methods. A cohort of CRC patients (n=433) were adopted from The Cancer Genome Atlas (TCGA) database. Stromal/immune scores were calculated by the ESTIMATE algorithm. Correlation between prognosis/clinical characteristics and stromal/immune scores was assessed. Differentially expressed stromal and immune genes were identified. Their potential functions were annotated by functional enrichment analysis. Cox regression analysis was used to develop an eight-gene risk score model. Its predictive efficacies for 3 years, 5 years, overall survival (OS), and progression-free survival interval (PFI) were evaluated using time-dependent receiver operating characteristic (ROC) curves. The correlation between the risk score and the infiltering levels of six immune cells was analyzed using TIMER. The risk score was validated using an independent dataset. Results. Immune score was in a significant association with prognosis and clinical characteristics of CRC. 736 upregulated and two downregulated stromal and immune genes were identified, which were mainly enriched into immune-related biological processes and pathways. An-eight gene prognostic risk score model was conducted, consisting of CCL22, CD36, CPA3, CPT1C, KCNE4, NFATC1, RASGRP2, and SLC2A3. High risk score indicated a poor prognosis of patients. The area under the ROC curves (AUC) s of the model for 3 years, 5 years, OS, and PFI were 0.71, 0.70, 0.73, and 0.66, respectively. Thus, the model possessed well performance for prediction of patients’ prognosis, which was confirmed by an external dataset. Moreover, the risk score was significantly correlated with immune cell infiltration. Conclusion. Our study conducted an immune-related prognostic risk score model, which could provide novel targets for immunotherapy of CRC.

scholarly journals IMUP and GPRC5A: Two Newly Identified Risk Score Indicators in Pancreatic Ductal Adenocarcinoma

2021 ◽  
Author(s):  
Rong Wei ◽  
Zixin Zeng ◽  
Ningning Shen ◽  
Ziyue Wang ◽  
Honghong Shen ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Immune Cells ◽  
Cox Regression ◽  
Bioinformatic Analysis ◽  
Cancer Development ◽  
Local Hospital ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Key Genes ◽  
The Difference

Abstract Background Pancreatic cancer has been a threateningly lethal malignant tumor worldwide. Despite the promising survival improvement in other cancer types attributing to the fast development of molecular precise medicine, the current treatment situation of pancreatic cancer is still woefully challenging since its limited response to neither traditional radiotherapy and chemotherapy nor emerging immunotherapy. The study is to explore potential responsible genes during the development of pancreatic cancer, thus identifying promising gene indicators and probable drug targets. Methods Different bioinformatic analysis were used to interpret the genetic events in pancreatic cancer development. Firstly, based on multiple cDNA microarray profiles from Gene Expression Omnibus (GEO) database, the genes with differently mRNA expression in cancer comparing to normal pancreatic tissues were identified, followed by being grouped based on the difference level. Then, GO and KEGG were performed to separately interpret the multiple groups of genes, and further Kaplan-Meier survival and Cox Regression analysis assisted us to scale down the candidate genes and select the potential key genes. Further, the basic physicochemical properties, the association with immune cells infiltration, mutation or other types variations besides expression gap in pancreatic cancer comparing to normal tissues of the selected key genes were analyzed. Moreover, the aberrant changed expression of key genes was validated by immunohistochemistry (IHC) experiment using local hospital tissue microarray samples and the clinical significance was explored based on TCGA clinical data. Results Firstly, a total of 22491 genes were identified to express differently in cancer comparing to normal pancreatic tissues based on 5 cDNA expression profiles, and the difference of 487/22491 genes was over 8-fold, and 55/487 genes were shared in multi profiles. Moreover, after genes interpretation which showed the >8-fold genes were mainly related to extracellular matrix structural constituent regulation, Kaplan-Meier survival and Cox-regression analysis were performed continually, and the result indicated that of the 55 extracellular locating genes, GPRC5A and IMUP were the only two independent prognostic indicators of pancreatic cancer. Further, detailed information of IMUP and GPRC5A were analyzed including their physicochemical properties, their expression and variation ratio and their association with immune cells infiltration in cancer, as well as the probable signaling pathways of genes regulation on pancreatic cancer development. Lastly, local IHC experiment performed on PAAD tissue array which was produced with 64 local hospital patients samples confirmed that GPRC5A and IMUP were abnormally up-regulated in pancreatic cancer, which directly associated with worse patients both overall (OS) and recurrence free survival (RFS). Conclusions Using multiple bioinformatic analysis as well as local hospital samples validation, we revealed that GPRC5A and IMUP expression were abnormally up-regulated in pancreatic cancer which associated statistical significantly with patients survival, and the genes’ biological features and clinical significance were also explored. However, more detailed experiments and clinical trials are obligatory to support their further potential drug-target role in clinical medical treatment.

scholarly journals Prognostic Gene Expression Signature in Patients With Distinct Glioma Grades

2021 ◽  
Vol 12 ◽  
Author(s):  
Saadia Ait Ssi ◽  
Dounia Chraa ◽  
Khadija El Azhary ◽  
Souha Sahraoui ◽  
Daniel Olive ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Cells ◽  
Cox Regression ◽  
Gene Expression Signature ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Tumor Escape ◽  
Cox Regression Analysis ◽  
Patient Prognosis ◽  
Cluster 2

BackgroundGlioma is the most common type of primary brain tumor in adults. Patients with the most malignant form have an overall survival time of <16 months. Although considerable progress has been made in defining the adapted therapeutic strategies, measures to counteract tumor escape have not kept pace, due to the developed resistance of malignant glioma. In fact, identifying the nature and role of distinct tumor-infiltrating immune cells in glioma patients would decipher potential mechanisms behind therapy failure.MethodsWe integrated into our study glioma transcriptomic datasets from the Cancer Genome Atlas (TCGA) cohort (154 GBM and 516 LGG patients). LM22 immune signature was built using CIBERSORT. Hierarchical clustering and UMAP dimensional reduction algorithms were applied to identify clusters among glioma patients either in an unsupervised or supervised way. Furthermore, differential gene expression (DGE) has been performed to unravel the top expressed genes among the identified clusters. Besides, we used the least absolute shrinkage and selection operator (LASSO) and Cox regression algorithm to set up the most valuable prognostic factor.ResultsOur study revealed, following gene enrichment analysis, the presence of two distinct groups of patients. The first group, defined as cluster 1, was characterized by the presence of immune cells known to exert efficient antitumoral immune response and was associated with better patient survival, whereas the second group, cluster 2, which exhibited a poor survival, was enriched with cells and molecules, known to set an immunosuppressive pro-tumoral microenvironment. Interestingly, we revealed that gene expression signatures were also consistent with each immune cluster function. A strong presence of activated NK cells was revealed in cluster 1. In contrast, potent immunosuppressive components such as regulatory T cells, neutrophils, and M0/M1/M2 macrophages were detected in cluster 2, where, in addition, inhibitory immune checkpoints, such as PD-1, CTLA-4, and TIM-3, were also significantly upregulated. Finally, Cox regression analysis further corroborated that tumor-infiltrating cells from cluster 2 exerted a significant impact on patient prognosis.ConclusionOur work brings to light the tight implication of immune components on glioma patient prognosis. This would contribute to potentially developing better immune-based therapeutic approaches.

scholarly journals The expression of long-chain non-coding RNA DMTF1v4 in colorectal cancer tissue and its relationship with clinicopathological features

2019 ◽  
Vol 17 ◽  
pp. 205873921984554
Author(s):  
Yanjuan Cai ◽  
Shutong Zhuang ◽  
Hongpeng Liu ◽  
Jianfu Qiu ◽  
Li Zeng
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Distant Metastasis ◽  
Cox Regression ◽  
Cancer Tissue ◽  
Depth Of Invasion ◽  
Cox Regression Analysis ◽  
Node Metastasis ◽  
Non Coding Rna ◽  
Long Chain

Emerging studies have showed that long-chain non-coding RNA DMTF1v4 might participate in the process of multidrug resistance phenotype of gastric cancer. However, its expression and function in colorectal cancer (CRC) is still unknown. In this study, we discovered that DMTF1v4 was generally 5.15 ± 1.67 times upregulated in CRC tissues compared to the adjacent normal tissues. Moreover, the expression level of DMTF1v4 was closely related to the distant metastasis of tumor, but it was not related to age, sex, tumor location, tumor staging, depth of invasion, lymph node metastasis, and differentiation level. Survival analysis showed that the overall survival rate of patients with high expression of DMTF1v4 was 45.0% in cancer tissues, which was significantly lower than 82.5% of DMTF1v4 low expression patients (χ2 = 11.562, P < 0.01). The results of univariate COX regression analysis showed that DMTF1v4, TNM (tumor, node, metastasis) staging, distant metastasis, and tumor differentiation were closely related to the prognosis of patients ( P < 0.05). Multivariate COX regression analysis showed that DMTF1v4 and distant metastasis could be independent prognostic factors for CRC patients. In conclusion, this study revealed that DMTF1v4 might promote the development of CRC, which can be used as an independent factor to judge the prognosis of CRC.

scholarly journals Identification of Novel Diagnostic Biomarkers in Prostate Adenocarcinoma Based on the Stromal-Immune Score and Analysis of the WGCNA and ceRNA Network

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Tengfei Zhang ◽  
Yaxuan Wang ◽  
Yiming Dong ◽  
Lei Liu ◽  
Yikai Han ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Tumor Microenvironment ◽  
Cox Regression ◽  
Differentially Expressed Gene ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Prognostic Biomarkers ◽  
Mechanism Study ◽  
Cox Regression Analysis ◽  
Immune Score

Prostate cancer is still a significant global health burden in the coming decade. Novel biomarkers for detection and prognosis are needed to improve the survival of distant and advanced stage prostate cancer patients. The tumor microenvironment is an important driving factor for tumor biological functions. To investigate RNA prognostic biomarkers for prostate cancer in the tumor microenvironment, we obtained relevant data from The Cancer Genome Atlas (TCGA) database. We used the bioinformatics tools Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm and weighted coexpression network analysis (WGCNA) to construct tumor microenvironment stromal-immune score-based competitive endogenous RNA (ceRNA) networks. Then, the Cox regression model was performed to screen RNAs associated with prostate cancer survival. The differentially expressed gene profile in tumor stroma was significantly enriched in microenvironment functions, like immune response, cancer-related pathways, and cell adhesion-related pathways. Based on these differentially expressed genes, we constructed three ceRNA networks with 152 RNAs associated with the prostate cancer tumor microenvironment. Cox regression analysis screened 31 RNAs as the potential prognostic biomarkers for prostate cancer. The most interesting 8 prognostic biomarkers for prostate cancer included lncRNA LINC01082, miRNA hsa-miR-133a-3p, and genes TTLL12, PTGDS, GAS6, CYP27A1, PKP3, and ZG16B. In this systematic study for ceRNA networks in the tumor environment, we screened out potential biomarkers to predict prognosis for prostate cancer. Our findings might apply a valuable tool to improve prostate cancer clinical management and the new target for mechanism study and therapy.

scholarly journals The Role of CXCL10 in Prognosis of Patients with Colon Cancer and Tumor Microenvironment Remodeling

2020 ◽  
Author(s):  
Hongli Yin ◽  
Weiwei Song ◽  
Chenguang Han ◽  
Qiantai Mao ◽  
Zhaoshuai Ji ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Cox Regression Analysis ◽  
Immune Cell Subsets ◽  
Intersection Analysis ◽  
Immune Score

Abstract Background: In the past few years, tumor microenvironment (TME) has gradually become a hot topic in tumor research, which has important significance in the diagnosis, prevention and prognosis of tumors. Importantly, the immune system is a major contributing factor in TME, and studies have shown that tumors are partially infiltrated with various immune cell subsets. The immune characteristics of the TME play an essential role in evaluating the prognosis of patients. The immune scoring system based on the distribution of tumor local immune cell subsets and cell density has been an essential indicator in the evaluation of patient prognosis and has been verified in various tumor studies. TME is indispensable in the occurrence and development of Colorectal cancer (CRC). However, understanding the dynamic regulation of immunity and matrix components in TME of CRC is still a challenge and should be investigated further.Methods: In this study, we collected transcriptome RNA-seq data of 521 Colon adenocarcinoma (COAD) patients from The Cancer Genome Atlas (TCGA) data portal. We then estimate the fraction of stromal and immune cells in COAD cases by ESTIMATE algorithms [1]. A total of 1109 stromal-immune score-related differentially expressed genes (DEGs) were identified and used to generate a high-confidence protein–protein intersection (PPI) network and univariate COX regression analysis. Intersection analysis of the data from PPI network and univariate COX regression analysis showed the core gene. Then we performed Gene set enrichment analysis (GSEA), survival analysis and clinical analysis for CXCL10, and applied CIBERSORT algorithms to estimate the tumor-infiltrating immune cells (TICs) proportion in COAD cases.Results: The proportion of immune and stromal components in TME are associated with the progression of COAD. For example, tumor metastasis is inversely proportional to immune score. A total of 1109 DEGs were obtained by analyzing the low-score shared genes and the high-score shared genes by intersection analysis which might be the determinant of TME status. The GO enrichment analysis indicated that DEGs are associated with immune-related terms. KEGG pathway enrichment analysis showed that these DEGs are mainly enriched in cytokine cytokine receptor signaling pathway etc. Therefore, DEGs are related to immune regulation, which indicates that the participation of immune factors is the main characteristic of TME in COAD. Moreover, the expression level of CXCL10 has significantly connection with the prognosis of patients and the progression of COAD. Conclusion: Taken together, we conducted a comprehensive analysis of the TME in COAD, and predicted a prognostic indicator for COAD, which provided a novel insight for therapeutics of COAD.

scholarly journals IMUP and GPRC5A: two newly identified risk score indicators in pancreatic ductal adenocarcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rong Wei ◽  
Guoye Qi ◽  
Zixin Zeng ◽  
Ningning Shen ◽  
Ziyue Wang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Immune Cells ◽  
Cox Regression ◽  
Bioinformatic Analysis ◽  
Cancer Development ◽  
Local Hospital ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Key Genes ◽  
The Difference

Abstract Background Pancreatic cancer has been a threateningly lethal malignant tumor worldwide. Despite the promising survival improvement in other cancer types attributing to the fast development of molecular precise medicine, the current treatment situation of pancreatic cancer is still woefully challenging since its limited response to neither traditional radiotherapy and chemotherapy nor emerging immunotherapy. The study is to explore potential responsible genes during the development of pancreatic cancer, thus identifying promising gene indicators and probable drug targets. Methods Different bioinformatic analysis were used to interpret the genetic events in pancreatic cancer development. Firstly, based on multiple cDNA microarray profiles from Gene Expression Omnibus (GEO) database, the genes with differently mRNA expression in cancer comparing to normal pancreatic tissues were identified, followed by being grouped based on the difference level. Then, GO and KEGG were performed to separately interpret the multiple groups of genes, and further Kaplan–Meier survival and Cox Regression analysis assisted us to scale down the candidate genes and select the potential key genes. Further, the basic physicochemical properties, the association with immune cells infiltration, mutation or other types variations besides expression gap in pancreatic cancer comparing to normal tissues of the selected key genes were analyzed. Moreover, the aberrant changed expression of key genes was validated by immunohistochemistry (IHC) experiment using local hospital tissue microarray samples and the clinical significance was explored based on TCGA clinical data. Results Firstly, a total of 22,491 genes were identified to express differently in cancer comparing to normal pancreatic tissues based on 5 cDNA expression profiles, and the difference of 487/22491 genes was over eightfold, and 55/487 genes were shared in multi profiles. Moreover, after genes interpretation which showed the > eightfold genes were mainly related to extracellular matrix structural constituent regulation, Kaplan–Meier survival and Cox-regression analysis were performed continually, and the result indicated that of the 55 extracellular locating genes, GPRC5A and IMUP were the only two independent prognostic indicators of pancreatic cancer. Further, detailed information of IMUP and GPRC5A were analyzed including their physicochemical properties, their expression and variation ratio and their association with immune cells infiltration in cancer, as well as the probable signaling pathways of genes regulation on pancreatic cancer development. Lastly, local IHC experiment performed on PAAD tissue array which was produced with 62 local hospital patients samples confirmed that GPRC5A and IMUP were abnormally up-regulated in pancreatic cancer, which directly associated with worse patients both overall (OS) and recurrence free survival (RFS). Conclusions Using multiple bioinformatic analysis as well as local hospital samples validation, we revealed that GPRC5A and IMUP expression were abnormally up-regulated in pancreatic cancer which associated statistical significantly with patients survival, and the genes’ biological features and clinical significance were also explored. However, more detailed experiments and clinical trials are obligatory to support their further potential drug-target role in clinical medical treatment.

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