scholarly journals Identification of a Novel PPAR Signature for Predicting Prognosis, Immune Microenvironment, and Chemotherapy Response in Bladder Cancer

PPAR Research ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Ke Zhu ◽  
Wen Deng ◽  
Hui Deng ◽  
Xiaoqiang Liu ◽  
Gongxian Wang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Small Molecule ◽  
Immune Cell ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Clinical Factors ◽  
Prognostic Signature ◽  
Small Molecule Drugs

Background. Mounting evidence has confirmed that peroxisome proliferator-activated receptors (PPARs) played a crucial role in the development and progression of bladder cancer (BLCA). The purpose of this study is to comprehensively investigate the function and prognostic value of PPAR-targeted genes in BLCA. Methods. The RNA sequencing data and clinical information of BLCA patients were acquired from The Cancer Genome Atlas (TCGA). The differentially expressed PPAR-targeted genes were investigated. Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis were performed for screening prognostic PPAR-targeted genes and constructing the prognostic PPAR signature and then validated by GSE13507 cohort and GSE32894 cohort. A nomogram was constructed to predict the outcomes of BLCA patients in combination with PPAR signature and clinical factors. Gene set enrichment analysis (GSEA) and immune cell infiltration were implemented to explore the molecular characteristics of the signature. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to predict the chemotherapy responses of the prognostic signature. The candidate small molecule drugs targeting PPAR-targeted genes were screened by the CMAP database. Results. We constructed and validated the prognostic signature comprising of 4 PPAR-targeted genes (CPT1B, CALR, AHNAK, and FADS2), which was an independent prognostic biomarker in BLCA patients. A nomogram based on the signature and clinical factors was established in the TCGA set, and the calibration plots displayed the excellent predictive capacity. GSEA analysis indicated that PPAR signature was implicated in multiple oncogenic signaling pathways and correlated with tumor immune cell infiltration. Patients in the high-risk groups showed greater sensitivity to chemotherapy than those in the low-risk groups. Moreover, 11 candidate small molecule drugs were identified for the treatment of BLCA. Conclusion. We constructed and validated a novel PPAR signature, which showed the excellent performance in predicting prognosis and chemotherapy sensitivity of BLCA patients.

scholarly journals Identification and validation of tumor microenvironment-related lncRNA prognostic signature for uveal melanoma

2021 ◽  
Vol 14 (8) ◽  
pp. 1151-1159
Author(s):  
Chen-Lu Liao ◽  
◽  
Xing-Yu Sun ◽  
Qi Zhou ◽  
Min Tian ◽  
...  
Keyword(s):  
Prognostic Value ◽  
Prognostic Markers ◽  
Immune Cell ◽  
Cox Regression ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Profile Data ◽  
Small Molecule Drugs

AIM: To investigate the role of tumor microenvironment (TME)-related long non-coding RNA (lncRNA) in uveal melanoma (UM), probable prognostic signature and potential small molecule drugs using bioinformatics analysis. METHODS: UM expression profile data were downloaded from the Cancer Genome Atlas (TCGA) and bioinformatics methods were used to find prognostic lncRNAs related to UM immune cell infiltration. The gene expression profile data of 80 TCGA specimens were analyzed using the single sample Gene Set Enrichment Analysis (ssGSEA) method, and the immune cell infiltration of a single specimen was evaluated. Finally, the specimens were divided into high and low infiltration groups. The differential expression between the two groups was analyzed using the R package ‘edgeR’. Univariate, multivariate and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analyses were performed to explore the prognostic value of TME-related lncRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses were also performed. The Connectivity Map (CMap) data set was used to screen molecular drugs that may treat UM. RESULTS: A total of 2393 differentially expressed genes were identified and met the criteria for the low and high immune cell infiltration groups. Univariate Cox analysis of lncRNA genes with differential expression identified 186 genes associated with prognosis. Eight prognostic markers of TME-included lncRNA genes were established as potentially independent prognostic elements. Among 269 differentially expressed lncRNAs, 69 were up-regulated and 200 were down-regulated. Univariate Cox regression analysis of the risk indicators and clinical characteristics of the 8 lncRNA gene constructs showed that age, TNM stage, tumor base diameter, and low and high risk indices had significant prognostic value. We screened the potential small-molecule drugs for UM, including W-13, AH-6809 and Imatinib. CONCLUSION: The prognostic markers identified in this study are reliable biomarkers of UM. This study expands our current understanding of the role of TME-related lncRNAs in UM genesis, which may lay the foundations for future treatment of this disease.

scholarly journals Development of an Immune-Related LncRNA Prognostic Signature for Glioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Yudong Cao ◽  
Hecheng Zhu ◽  
Jun Tan ◽  
Wen Yin ◽  
Quanwei Zhou ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Clinical Outcome ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Immune Infiltration

IntroductionGlioma is the most common primary cancer of the central nervous system with dismal prognosis. Long noncoding RNAs (lncRNAs) have been discovered to play key roles in tumorigenesis in various cancers, including glioma. Because of the relevance between immune infiltrating and clinical outcome of glioma, identifying immune-related lncRNAs is urgent for better personalized management.Materials and methodsSingle-sample gene set enrichment analysis (ssGSEA) was applied to estimate immune infiltration, and glioma samples were divided into high immune cell infiltration group and low immune cell infiltration group. After screening differentially expressed lncRNAs in two immune groups, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct an immune-related prognostic signature. Additionally, we explored the correlation between immune infiltration and the prognostic signature.ResultsA total of 653 samples were appropriate for further analyses, and 10 lncRNAs were identified as immune-related lncRNAs in glioma. After univariate Cox regression and LASSO Cox regression analysis, six lncRNAs were identified to construct a prognostic signature for glioma, which could be taken as independent prognostic factors in both univariate and multivariate Cox regression analyses. Moreover, risk score was significantly correlated with all the 29 immune-related checkpoint expression (p < 0.05) in ssGSEA except neutrophils (p = 0.43).ConclusionThe study constructed an immune-related prognostic signature for glioma, which contributed to improve clinical outcome prediction and guide immunotherapy.

scholarly journals An immune cell infiltration-related gene signature predicts prognosis for bladder cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hualin Chen ◽  
Yang Pan ◽  
Xiaoxiang Jin ◽  
Gang Chen
Keyword(s):  
Bladder Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
External Validation ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Prognostic Indicators ◽  
Immune Cell Infiltration ◽  
Related Gene

AbstractTo explore novel therapeutic targets, develop a gene signature and construct a prognostic nomogram of bladder cancer (BCa). Transcriptome data and clinical traits of BCa were downloaded from UCSC Xena database and Gene Expression Omnibus (GEO) database. We then used the method of Single sample Gene Set Enrichment analysis (ssGSEA) to calculate the infiltration abundances of 24 immune cells in eligible BCa samples. By weighted correlation network analysis (WGCNA), we identified turquoise module with strong and significant association with the infiltration abundance of immune cells which were associated with overall survival of BCa patients. Subsequently, we developed an immune cell infiltration-related gene signature based on the module genes (MGs) and immune-related genes (IRGs) from the Immunology Database and Analysis Portal (ImmPort). Then, we tested the prognostic power and performance of the signature in both discovery and external validation datasets. A nomogram integrated with signature and clinical features were ultimately constructed and tested. Five prognostic immune cell infiltration-related module genes (PIRMGs), namely FPR1, CIITA, KLRC1, TNFRSF6B, and WFIKKN1, were identified and used for gene signature development. And the signature showed independent and stable prognosis predictive power. Ultimately, a nomogram consisting of signature, age and tumor stage was constructed, and it showed good and stable predictive ability on prognosis. Our prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for BCa. Further researches are needed to verify the clinical effectiveness of this nomogram and these biomarkers.

scholarly journals Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Xingwang Zhao ◽  
Longlong Zhang ◽  
Juan Wang ◽  
Min Zhang ◽  
Zhiqiang Song ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Tissue Destruction ◽  
Systemic Lupus ◽  
Ppi Networks

Abstract Background Systemic lupus erythematosus (SLE) is a multisystemic, chronic inflammatory disease characterized by destructive systemic organ involvement, which could cause the decreased functional capacity, increased morbidity and mortality. Previous studies show that SLE is characterized by autoimmune, inflammatory processes, and tissue destruction. Some seriously-ill patients could develop into lupus nephritis. However, the cause and underlying molecular events of SLE needs to be further resolved. Methods The expression profiles of GSE144390, GSE4588, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between SLE and healthy samples. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by metascape etc. online analyses. The protein–protein interaction (PPI) networks of the DEGs were constructed by GENEMANIA software. We performed Gene Set Enrichment Analysis (GSEA) to further understand the functions of the hub gene, Weighted gene co‐expression network analysis (WGCNA) would be utilized to build a gene co‐expression network, and the most significant module and hub genes was identified. CIBERSORT tools have facilitated the analysis of immune cell infiltration patterns of diseases. The receiver operating characteristic (ROC) analyses were conducted to explore the value of DEGs for SLE diagnosis. Results In total, 6 DEGs (IFI27, IFI44, IFI44L, IFI6, EPSTI1 and OAS1) were screened, Biological functions analysis identified key related pathways, gene modules and co‐expression networks in SLE. IFI27 may be closely correlated with the occurrence of SLE. We found that an increased infiltration of moncytes, while NK cells resting infiltrated less may be related to the occurrence of SLE. Conclusion IFI27 may be closely related pathogenesis of SLE, and represents a new candidate molecular marker of the occurrence and progression of SLE. Moreover immune cell infiltration plays important role in the progession of SLE.

scholarly journals A novel pyroptosis-associated gene signature for immune status and prognosis of cutaneous melanoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12304
Author(s):  
Zhengyuan Wu ◽  
Leilei Chen ◽  
Chaojie Jin ◽  
Jing Xu ◽  
Xingqun Zhang ◽  
...  
Keyword(s):  
Cutaneous Melanoma ◽  
Immune Status ◽  
Immune Cell ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Tumor Cell Death ◽  
Prognostic Gene ◽  
Prognostic Gene Signature

Background Cutaneous melanoma (CM) is a life-threatening destructive malignancy. Pyroptosis significantly correlates with programmed tumor cell death and its microenvironment through active host-tumor crosstalk. However, the prognostic value of pyroptosis-associated gene signatures in CM remains unclear. Methods Gene profiles and clinical data of patients with CM were downloaded from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes associated with pyroptosis and overall survival (OS). We constructed a prognostic gene signature using LASSO analysis, then applied immune cell infiltration scores and Kaplan-Meier, Cox, and pathway enrichment analyses to determine the roles of the gene signature in CM. A validation cohort was collected from the Gene Expression Omnibus (GEO) database. Results Four pyroptosis-associated genes were identified and incorporated into a prognostic gene signature. Integrated bioinformatics findings showed that the signature correlated with patient survival and was associated with tumor growth and metastasis. The results of Gene Set Enrichment Analysis of a risk signature indicated that several enriched pathways are associated with cancer and immunity. The risk signature for immune status significantly correlated with tumor stem cells, the immune microenvironment, immune cell infiltration and immune subtypes. The expression of four pyroptosis genes significantly correlated with the OS of patients with CM and was related to the sensitivity of cancer cells to several antitumor drugs. A signature comprising four genes associated with pyroptosis offers a novel approach to the prognosis and survival of patients with CM and will facilitate the development of individualized therapy.

scholarly journals Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhuomao Mo ◽  
Daiyuan Liu ◽  
Dade Rong ◽  
Shijun Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Immunosuppressive Microenvironment

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

scholarly journals Comprehensive Characterization of Transforming Growth Factor Beta Receptor 1 in Stomach Adenocarcinoma Identifies a Prognostic Signature for Predicting Clinical Outcomes and Immune Infiltrates

2021 ◽  
Author(s):  
Yi He ◽  
Haiyang Zhang ◽  
Yan Zhang ◽  
Peiyun Wang ◽  
Kegan Zhu ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Signaling Pathway ◽  
Operating Characteristic ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Pathologic Stage ◽  
Stomach Adenocarcinoma ◽  
Receiver Operating

Abstract Background: Stomach adenocarcinoma (STAD) is the common cancer and ranks third leading cause of cancer death worldwide. TGF‑β receptor 1 (TGFBR1), serving important roles in the TGF‑β family, the mechanisms whereby TGFβ2 governs tumor progression, immune cell infiltration and its correlation with tumor microenvironment (TME) in STAD remains unintelligible. Methods: First, we used the data in the TCGA, GEPIA, and HPA databases to explore the expression level of TGFBR1 in STAD, the correlation between TGFBR1 expression and the clinical features of STAD, its impact on the survival of STAD. Subsequently, a receiver operating characteristic (ROC) curve and nomogram were constructed and LASSO (the Least Absolute Shrinkage and Selection Operator)-selected features were used to build the TGFBR1 prognostic signature. Moreover, GSEA enrichment analysis is used to find the potential molecular mechanism of TGFBR1 to promote the malignant process of STAD. Finally, we further explored the influence of theTGFBR1 expression on the immune microenvironment of STAD patients through the TIMER2.0 and GEPIA database.Results: In our study, TGFBR1 expression was significantly elevated in patients with STAD and positively co-expression with pathologic stage, lymph node metastases (LNM) stage and histopathological grade of STAD. LASSO-selected features were used to build the TGFBR1 prognostic signature. 9 factors with non-zero coefficients were identified. The corresponding risk scores were computed, according to the following formula: Risk score = (-0.2914) *DIXDC1+ (0.1113) *STON1-GTF2A1L+(0.3092) *FERMT2+(-0.0146) *BHMT2+(0.1798) *ABCC9+(0.068) *MSRB3+(-0.1007) *SYNC+(-0.0891) *SORBS1+(0.0828) *TGFBR1.Survival analysis revealed that patients with high TGFBR1 had shorter OS, FP, and PPS. Multivariate Cox analysis revealed TGFBR1 was an independent prognostic factor for OS in STAD. The receiver operating characteristic (ROC) analysis suggested high diagnostic value with the area under curve (AUC) of TGFBR1 was 0.739, and a prognostic nomogram involving age, T, N, M classification, pathologic stage, primary therapy outcome, histologic grade and TGFBR1 to predict the 1, 3, 5-year OS was constructed. GSEA revealed that high TGFBR1 expression was correlated with pathway in cancer, MAPK signaling pathway, NOTCH signaling pathway, focal adhesion and VEGF-C production. ssGSEA showed that TGFBR1 is correlated with NK cells, Tem and Th17 cells. Furthermore, elevated TGFBR1 expression was found to be significantly correlated with several immune checkpoint and immune markers associated with immune cell subsets. Conclusion: In summary, TGFBR1 could be a prognostic biomarker and an important regulator of immune cell infiltration in STAD. The present study revealed the probable underlying molecular mechanisms of TGFBR1 in STAD and provided a potential target for improving the prognosis.

scholarly journals SERPINE1 associated with remodeling of the tumor microenvironment in colon cancer progression: a novel therapeutic target

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shaokun Wang ◽  
Li Pang ◽  
Zuolong Liu ◽  
Xiangwei Meng
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
The Relationship

Abstract Background The change of immune cell infiltration essentially influences the process of colorectal cancer development. The infiltration of immune cells can be regulated by a variety of genes. Thus, modeling the immune microenvironment of colorectal cancer by analyzing the genes involved can be more conducive to the in-depth understanding of carcinogenesis and the progression thereof. Methods In this study, the number of stromal and immune cells in malignant tumor tissues were first estimated by using expression data (ESTIMATE) and cell-type identification with relative subsets of known RNA transcripts (CIBERSORT) to calculate the proportion of infiltrating immune cell and stromal components of colon cancer samples from the Cancer Genome Atlas database. Then the relationship between the TMN Classification and prognosis of malignant tumors was evaluated. Results By investigating differentially expressed genes using COX regression and protein-protein interaction network (PPI), the candidate hub gene serine protease inhibitor family E member 1 (SERPINE1) was found to be associated with immune cell infiltration. Gene Set Enrichment Analysis (GSEA) further projected the potential pathways with elevated SERPINE1 expression to carcinogenesis and immunity. CIBERSORT was subsequently utilized to investigate the relationship between the expression differences of SERPINE1 and immune cell infiltration and to identify eight immune cells associated with SERPINE1 expression. Conclusion We found that SERPINE1 plays a role in the remodeling of the colon cancer microenvironment and the infiltration of immune cells.

scholarly journals Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis

2019 ◽  
Author(s):  
Yiling Cao ◽  
Weihao Tang ◽  
Wanxin Tang
Keyword(s):  
Gene Expression ◽  
Lupus Nephritis ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Spearman Correlation ◽  
Core Genes

Abstract Objects Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. Methods Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues of living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Result Five types of immune cells revealed important associations with LN, and monocytes emerged to be the prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8, were closely related to clinical features. Conclusion This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.

scholarly journals KRT17 Serves as an Oncogene and a Predictor of Poor Survival in Hepatocellular Carcinoma Patients

2020 ◽  
Author(s):  
yuyan chen ◽  
Jing Chen ◽  
Zu-Cheng Tian ◽  
Dan-Hua Zhou ◽  
Ran Ji ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Cell ◽  
Immune Cell ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Cancer Type ◽  
Immune Cell Infiltration ◽  
Functional Link ◽  
Network Analyses ◽  
Ppi Networks

Abstract Background: Hepatocellular carcinoma (HCC) is the second most common cancer-associated cause of death globally. It is thus vital that novel diagnostic and prognostic biomarkers associated with early-stage HCC be identified. While keratin 17 (KRT17) has previously been reported to be associated with certain cancer types, its relationship with HCC remains to be defined. Methods：The expression of KRT17 in the TCGA LIHC database and in 44 pairs of HCC patient samples was assessed via qRT-PCR, western blotting, and immunohistochemical staining. The prognostic relevance of KRT17 was assessed using Kaplan-Meir curves, while important cancer- and KRT17-related biological processes were defined through gene set enrichment analysis (GSEA). The functional link between KRT17 expression and tumor cell proliferation/survival was assessed through flow cytometry, colony formation assay, CCK-8 assay, and subcutaneous tumor model approaches. Protein-protein interaction (PPI) networks and analyses of immune cell infiltration were also employed to define key signaling pathways associated with KRT17 expression in HCC. Results：HCC tissue samples exhibited increased KRT17 mRNA and protein expression that was predictive of poorer patient survival (P<0.001). GSEA and functional experiments revealed that KRT17 functioned as a regulator of HCC tumor cell survival, proliferation, and cell cycle progression in vitro and in vivo. PPI network analyses also revealed that KRT17 expression was linked to immune cell infiltration and activation in patients with HCC. Conclusion: We found that increased KRT17 levels were associated with poorer survival, more aggressive disease, and altered immune cell infiltration in patients suffering from HCC. As such, KRT17 may function as an oncogene and a prognostic biomarker in this cancer type.

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