ARID1A Is a Prognostic Biomarker and Associated with Immune Infiltrates in Hepatocellular Carcinoma

Objective. ARID1A has been discovered as a potential cancer biomarker. But its role in hepatocellular carcinoma (HCC) is subject to considerable dispute. Methods. The relationship between ARID1A and clinical factors was investigated. Clinicopathological variables related to overall survival in HCC subjects were identified using Cox and Kaplan–Meier studies. The connection between immune infiltrating cells and ARID1A expression was investigated using the tumor Genome Atlas (TCGA) dataset for gene set enrichment analysis (GSEA). Finally, a cell experiment was used to confirm it. Results. The gender and cancer topography (T) categorization of HCC were linked to increased ARID1A expression. Participants with advanced levels of ARID1A expression had a worse prognosis than someone with lower levels. ARID1A was shown to be a risk indicator of overall survival on its own. ARID1A expression is inversely proportional to immune cell infiltration. In vitro, decreasing ARID1A expression substantially slowed the cell cycle and decreased HCC cell proliferation, migration, and invasion. Conclusion. The expression of ARID1A could be used to predict the outcome of HCC. It is closely related to tumor immune cell infiltration.

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EPDR1 correlates with immune cell infiltration in hepatocellular carcinoma and can be used as a prognostic biomarker

10.21203/rs.3.rs-28073/v1 ◽

2020 ◽

Author(s):

Ruochan Chen ◽

Yiya Zhang

Keyword(s):

Hepatocellular Carcinoma ◽

Functional Analysis ◽

Immune Cell ◽

Prognostic Biomarker ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Normal Tissues

Abstract Background: Hepatocellular carcinoma (HCC) has high mortality rate and is a serious disease burden globally. Hence, identification and characterization of novel biomarkers for the diagnosis and prognosis of HCC are critically important. The protein EPDR1 (ependymin related 1) is a member of piscine brain glycoproteins and is involved in cell adhesion. This is the first study to report the expression of EPDR1 and its prognostic significance, pathological role, and association with cancer immunity in HCC.Methods: The gene expression, prognostic, and clinicopathological analyses were performed based on the data obtained from multiple transcriptome databases. Protein expression of EPDR1 in HCC was verified using human protein atlas and CPTAC databases. Co-expression network analysis using the LinkedOmics database was performed to identify genes co-expressed with EPDR1 expression. Functional analysis of the co-expressed genes, including gene set enrichment analysis was performed to identify the functional role of EPDR1. The statistical analysis was conducted in R, and the relationship between EPDR1 expression and immune cell infiltration was analyzed using TIMER and CIBERSORT resources. Results: The expression of EPDR1 was found to be significantly higher in HCC tissues than in the normal tissues and is an independent prognostic factor for the overall survival of HCC patients. Further, a high level of EPDR1 was shown to be correlated with advanced stage of HCC. Functional analysis revealed that EPDR1 is associated with multiple signaling pathways as well as pathways related to cancer and apoptosis. Notably, EPDR1 expression significantly correlated with purity and the infiltration levels of B cells, CD8+ and CD4+ T cells, macrophages, neutrophils, and dendritic cells in HCC. Further, the EPDR1 expression significantly correlated with the expression of immune signatures, such as KIR2DL4, ITGAM, GATA3, STAT6, STAT5A, BCL6, STAT3, and HAVCR2.Conclusions: Our study identified EPDR1 as a novel prognostic biomarker in HCC. The expression of EPDR1 was shown to be associated with immune cell infiltration as well as the signature molecules that potentially regulate these processes during the carcinogenesis of HCC. With better understanding of its biological function, EPDR1 could become an effective target for HCC diagnosis and treatment in the future.

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Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.653836 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shixin Xiang ◽

Jing Li ◽

Jing Shen ◽

Yueshui Zhao ◽

Xu Wu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Regression Analysis ◽

Tumor Microenvironment ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Tumor Purity

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis.Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER).Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine–cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration.Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.

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Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.611058 ◽

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.

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

10.21203/rs.3.rs-117723/v1 ◽

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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RNA N6-Methyladenosine Regulator-Mediated Methylation Modifications Pattern and Immune Infiltration Features in Glioblastoma

Frontiers in Oncology ◽

10.3389/fonc.2021.632934 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yimin Pan ◽

Kai Xiao ◽

Yue Li ◽

Yuzhe Li ◽

Qing Liu

Keyword(s):

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Lasso Regression ◽

Gene Set Enrichment ◽

Clinical Prognosis ◽

Prognostic Assessment ◽

The Relationship

Glioblastoma (GBM) is a group of intracranial neoplasms with intra-tumoral heterogeneity. RNA N6-methyladenosine (m6A) methylation modification reportedly plays roles in immune response. The relationship between the m6A modification pattern and immune cell infiltration in GBM remains unknown. Utilizing expression data of GBM patients, we thoroughly explored the potential m6A modification pattern and m6A-related signatures based on 21 regulators. Thereafter, the m6A methylation modification-based prognostic assessment pipeline (MPAP) was constructed to quantitatively assess GBM patients’ clinical prognosis combining the Robustness and LASSO regression. Single-sample gene-set enrichment analysis (ssGSEA) was used to estimate the specific immune cell infiltration level. We identified two diverse clusters with diverse m6A modification characteristics. Based on differentially expressed genes (DEGs) within two clusters, m6A-related signatures were identified to establish the MPAP, which can be used to quantitatively forecast the prognosis of GBM patients. In addition, the relationship between 21 m6A regulators and specific immune cell infiltration was demonstrated in our study and the m6A regulator ELAVL1 was determined to play an important role in the anticancer response to PD-L1 therapy. Our findings indicated the relationship between m6A methylation modification patterns and tumor microenvironment immune cell infiltration, through which we could comprehensively understand resistance to multiple therapies in GBM, as well as accomplish precise risk stratification according to m6A-related signatures.

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Prediction of Hepatocellular Carcinoma Prognosis and Immune Cell Infiltration Using Gene Signature Associated with Inflammatory Response

Computational and Mathematical Methods in Medicine ◽

10.1155/2022/2415129 ◽

2022 ◽

Vol 2022 ◽

pp. 1-24

Author(s):

Bin-Bin Da ◽

Shuai Luo ◽

Ming Huang ◽

Fei Song ◽

Rong Ding ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Inflammatory Response ◽

Immune Cell ◽

Cox Regression ◽

Inflammatory Responses ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Differential Analysis

It has been demonstrated that the inflammatory response influences cancer development and can be used as a prognostic biomarker in various tumors. However, the relevance of genes associated with inflammatory responses in hepatocellular carcinoma (HCC) remains unknown. The Cancer Genome Atlas (TCGA) database was analyzed using weighted gene coexpression network analysis (WGCNA) and differential analysis to discover essential inflammatory response-related genes (IFRGs). Cox regression studies, both univariate and multivariate, were employed to develop a prognostic IFRGs signature. Additionally, Gene Set Enrichment Analysis (GSEA) was used to deduce the biological function of the IFRGs signature. Finally, we estimated immune cell infiltration using a single sample GSEA (ssGSEA) and x-cell. Our results revealed that, among the major HCC IFRGs, two (DNASE1L3 and KLKB1) were employed to create a predictive IFRG signature. The IFRG signature could correctly predict overall survival (O.S) as per Kaplan-Meier time-dependent roc curves analysis. It was also linked to pathological tumor stage and T stage and might be used as a prognostic predictor in HCC. GSEA analysis concluded that the IFRG signature might influence the immune response in HCC. Immunological cell infiltration and immune checkpoint molecule expression differed in the high-risk and low-risk groups. As a result of our findings, DNASILE may play a role in the tumor microenvironment. However, more research is necessary to confirm the role of DNASE1L3 and KLKB1.

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Down-Regulated CLDN10 Predicts Favorable Prognosis and Correlates With Immune Infiltration in Gastric Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.747581 ◽

2021 ◽

Vol 12 ◽

Author(s):

XiongHui Rao ◽

JianLong Jiang ◽

ZhiHao Liang ◽

JianBao Zhang ◽

ZheHong Zhuang ◽

...

Keyword(s):

Gastric Cancer ◽

T Cell ◽

Immune Cell ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Her2 Status ◽

Immune Cell Infiltration ◽

Cell Markers ◽

Immune Infiltration

Background: CLDN10, an important component of the tight junctions of epithelial cells, plays a crucial role in a variety of tumors. The effect of CLDN10 expression in gastric cancer, however, has yet to be elucidated.Methods: Differential expression of CLDN10 at the mRNA and protein levels was evaluated using Oncomine, ULCAN, HPA and TIMER2.0 databases. Real-time polymerase chain reaction (RT-PCR) was utilized to further verify the expression of CLDN10 in vitro. Correlations between CLDN10 expression and clinical outcomes of gastric cancer were explored by Kaplan-Meier Plotter. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) were performed via LinkedOmics and GeneMANIA. The correlations between CLDN10 expression and immune cell infiltration and somatic copy number alternations (SCNA) in gastric cancer were explored by TIMER2.0 and GEPIA2.0.Results: CLDN10 expression was lower in gastric cancer compared to adjacent normal tissues, and associated with better prognosis. CLDN10 also showed significant differences at different T stages, Lauren classification, treatments and HER2 status. PPI and GSEA analysis showed that CLDN10 might be involved in signal transmission, transmembrane transport and metabolism. In some major immune cells, low expression of CLDN10 was associated with increased levels of immune cell infiltration. In addition, it was found that different SCNA status in CLDN10 might affect the level of immune cell infiltration. Furthermore, the expression of CLDN10 was significantly associated with the expression of several immune cell markers, especially B cell markers, follicular helper T cell (Tfh) markers and T cell exhaustion markers.Conclusion: Down-regulated CLDN10 was associated with better overall survival (OS) in gastric cancer. And CLDN10 may serve as a potential prognostic biomarker and correlate to immune infiltration levels in gastric cancer.

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Cancer Stemness Associated With Prognosis and the Efficacy of Immunotherapy in Adrenocortical Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.651622 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xiaoxi Shi ◽

Yuanlin Liu ◽

Shuai Cheng ◽

Haidi Hu ◽

Jian Zhang ◽

...

Keyword(s):

Adrenocortical Carcinoma ◽

Immune Cell ◽

Checkpoint Inhibitors ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Potential Biomarker ◽

Lower Expression

BackgroundCancer stem cells (CSCs) have been proven to influence drug resistance, recurrence, and metastasis in tumors. Our study aimed to identify stemness-related prognostic biomarkers for new therapeutic strategies in adrenocortical carcinoma.MethodsRNA-seq data and clinical characteristics were downloaded from The Cancer Genome Atlas (TCGA). The stemness indexes, mDNAsi and mRNAsi, were calculated to classify all samples into low-score and high-score groups. Two algorithms, based on the R language, ESTIMATE and single-sample Gene Set Enrichment Analysis (ssGSEA) were used to assess the immune cell infiltration states of adrenocortical carcinoma patients. Weighted Gene Co-expression Network Analysis (WGCNA) was used to find genes that were related to the stemness of cancer. By bioinformatics methods, the correlations between biomarkers capable of predicting immune checkpoint inhibitors (ICIs) responses and stemness of cancer were explored.ResultsHigh-mRNAsi predicted shorter overall survival (OS) and a higher metastatic trend in adrenocortical carcinoma (ACC) patients. Compared with the low-mRNAsi group, the high-mRNAsi group had a lower ImmuneScore and StromalScroe. Twenty-two stemness-related prognostic genes were obtained by WGCNA, which focused on the function of the cell cycle and cell mitosis. Immune cell infiltration, especially CD8+T cell, increased in the low-mRNAsi group compared with the high-mRNAsi group. Lower expression of PD-L1, CTLA-4, and TIGHT was evaluated in the high-mRNAsi group.ConclusionsACC patients with high-mRNAsi have poor prognosis and less immune cell infiltration. Combined with the finding of lower expression of CTLA-4, TIGHT, and PD-L1 in the high-mRNAsi group, we came to the conclusion that stemness index is a potential biomarker to predict the effectiveness of ICIs.

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SNHG3/miR-148a-3p Axis–mediated High Expression of DNMT1 Correlates with Poor Prognosis and Tumor Immune Infiltration of Hepatocellular Carcinoma

10.21203/rs.3.rs-864636/v1 ◽

2021 ◽

Author(s):

Ninghua Yao ◽

Wei Jiang ◽

Jie Sun ◽

Chen Yang ◽

Wenjie Zheng ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Immune Cell Infiltration ◽

Gene Set Enrichment ◽

Gene Set ◽

Immune Infiltration ◽

Computer Analyses ◽

Dnmt1 Expression

Abstract Background Epigenetic reprogramming plays an important role in the occurrence, development, and prognosis of hepatocellular carcinoma (HCC). DNA methylation is a key epigenetic regulatory mechanism, and DNA methyltransferase 1 (DNMT1) is the major enzyme responsible for maintenance methylation. Nevertheless, the role and mechanism of DNMT1 in HCC remains poorly defined. Methods In the current study, we conducted pan-cancer analysis for DNMT1’s expression and prognosis using The Cancer Genome Atlas (TCGA) data set. We conducted gene Set Enrichment Analysis (GSEA) between high-and-low DNMT1 expression groups to identify DNMT1-related functional significance. We also investigated the relationship between DNMT1 expression and tumor immune microenvironment, including immune cell infiltration and the expression of immune checkpoints. Through a combination series of computer analyses (including expression analyses, correlation analyses, and survival analyses), the noncoding RNAs (ncRNAs) that contribute to the overexpression of DNMT1 were ultimately identified. Results We found that DNMT1 was upregulated in 16 types of human carcinoma including HCC, and DNMT1 might be a biomarker predicting unfavorable prognosis in HCC patients. DNMT1 mRNA expression was statistically associated with age, histological grade, and the level of serum AFP. Moreover, DNMT1 level was significantly and positively linked to tumor immune cell infiltration, immune cell biomarkers, and immune checkpoint expression. Meanwhile, Gene Set Enrichment Analysis (GSEA) revealed that high-DNMT1 expression was associated with epithelial mesenchymal transition (EMT), E2F target, G2M checkpoint, and inflammatory response. Finally, through a combination series of computer analyses the SNHG3/hsa-miR-148a-3p/DNMT1 axis was confirmed as the potential regulatory pathway in HCC. Conclusion SNHG3/miR-148a-3p axis upregulation of DNMT1 may be related to poor outcome, tumor immune infiltration, and regulated malignant properties in HCC.

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Comprehensive Analysis of the Immune and Prognostic Implication of COL6A6 in Lung Adenocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.633420 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yi Ma ◽

Mantang Qiu ◽

Haifa Guo ◽

Haiming Chen ◽

Jiawei Li ◽

...

Keyword(s):

T Cell ◽

Lung Adenocarcinoma ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Gene Copy ◽

Immune Cell Infiltration ◽

Term Survival

Collagen type VI alpha 6 chain (COL6A6), a novel collagen, has been considered as a tumor suppressor and therapeutic target in several tumors. However, the functional role of COL6A6 in immune cell infiltration and prognostic value in lung adenocarcinoma (LUAD) remains unknown. Here, we evaluated COL6A6 expression and its impact on survival among LUAD patients from The Cancer Genome Atlas (TCGA) and several other databases. COL6A6 was downregulated in LUAD tissues compared to normal tissues at both mRNA and protein levels. COL6A6 expression was negatively associated with pathological stage, tumor stage, and lymph node metastasis. High COL6A6 expression was a favorable prognostic factor in LUAD. Next, we explored the associations between COL6A6 expression and immune cell infiltration. COL6A6 expression was positively associated with the infiltration of B cells, T cells, neutrophils and dendritic cells. Additionally, the immune cell infiltration levels were associated with COL6A6 gene copy number in LUAD. Consistently, gene set enrichment analysis showed that various immune pathways were enriched in the LUAD samples with high COL6A6 expression, including pathways related to T cell activation and T cell receptor signaling. The impacts of COL6A6 on immune activity were further assessed by enrichment analysis of 50 COL6A6-associated immunomodulators. Thereafter, using Cox regression, we identified a seven-gene risk prediction signature based on the COL6A6-associated immunomodulators. The resulting risk score was an independent prognostic predictor in LUAD. Receiver operating characteristic curve analysis confirmed that the seven-gene signature had good prognostic accuracy in the TCGA-LUAD cohort and a Gene Expression Omnibus dataset. Finally, we constructed a clinical nomogram to predict long-term survival probabilities, and calibration curves verified its accuracy. Our findings highlight that COL6A6 is involved in tumor immunity, suggesting COL6A6 may be a potential immunotherapeutic target in LUAD. The proposed seven-gene signature is a promising prognostic biomarker in LUAD.

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