Clinicopathological and Prognostic Characteristics of CD276 (B7-H3) Expression in Adrenocortical Carcinoma

Background. Adrenocortical carcinoma (ACC) is a rare malignant endocrine tumor with a high tumor recurrence rate and poor postoperative survival. Recent studies suggest that CD276- (B7-H3) targeted therapy represents a promising therapeutic option for solid tumors. However, little is known about the expression status of CD276 or its association with progression and prognosis of ACC. Methods. Clinical data were retrospectively analyzed from patients who underwent resection of ACC at our institution (n=48). Archived, formalin-fixed, and paraffin-embedded samples were collected for immunohistochemical analysis, and the correlation between CD276 expression and clinicopathological parameters was evaluated. Kaplan–Meier and univariate/multivariate Cox regression methods were implemented to identify any prognostic effects. Data from The Cancer Genome Atlas (TCGA) ACC cohort (n=77) were retrieved for quantitative validation analysis. Results. Positive expression of CD276 was detected on the cell membrane and in the cytoplasm of cancer cells or tumor-associated vascular cells in 91.67% (44/48) of ACCs. Vascular expression of CD276 was associated with local aggression (higher T stage, P=0.029) and advanced ENSAT stage (P=0.02). Specifically, patients with a higher CD276-positive cancer cell density exhibited significantly worse overall survival and recurrence-free survival in our cohort (HR=2.8, P=0.01, and HR=7.52, P<0.001, respectively) and in the validation cohort (HR=2.4, P=0.033, and HR=3.7, P<0.001, respectively). The prognostic association remained significant in multivariate Cox regression analysis. Further analysis indicated that CD276 participates in regulating the immune response as well as in the malignant biological behaviors of ACC. Conclusion. These findings highlight the immune checkpoint factor CD276 as an independent prognostic factor and a potential therapeutic target in ACC.

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The Prognostic Value of m6A-related LncRNAs in Patients with HNSCC

10.21203/rs.3.rs-778502/v1 ◽

2021 ◽

Author(s):

Liu-qing Zhou ◽

Jie-yu Zhou ◽

Yao Hu

Keyword(s):

Prognostic Value ◽

Risk Model ◽

Cox Regression ◽

Predictive Ability ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Consensus Clustering ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Cancer Genome Atlas

Abstract Background: N6-methyladenosine (m6A) modifications play an essential role in tumorigenesis. m6A modifications are known to modulate RNAs, including mRNAs and lncRNAs. However, the prognostic role of m6A-related lncRNAs in head and neck squamous cell carcinoma (HNSCC) is poorly understood.Methods: Based on LASSO Cox regression, enrichment analysis, univariate and multivariate Cox regression analysis, a risk prognostic model, and consensus clustering analysis, we analyzed the 12 m6A-related lncRNAs in HNSCC samples data using the data from The Cancer Genome Atlas (TCGA) database.Results: We found twelve m6A-related lncRNAs in the training cohort and validated in all cohorts by Kaplan-Meier and Cox regression analyses, and revealing their independent prognostic value in HNSCC. Moreover, ROC analysis was conducted, confirming the strong predictive ability of this signature for HNSCC prognosis. GSEA and detailed immune infiltration analyses revealed specific pathways associated with m6A-related lncRNAs.Conclusions: In this study, a novel risk model including twelve genes (SAP30L-AS1, AC022098.1, LINC01475, AC090587.2, AC008115.3, AC015911.3, AL122035.2, AC010226.1, AL513190.1, ZNF32-AS1, AL035587.1 and AL031716.1) was built. It could accurately predict HNSCC prognosis and provide potential prediction outcome and new therapeutic target for HNSCC patients.

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Low Expression of RILPL2 Predicts Poor Prognosis and Correlates With Immune Infiltration in Endometrial Carcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.670893 ◽

2021 ◽

Vol 8 ◽

Author(s):

Jinhui Liu ◽

Mengting Xu ◽

Zhipeng Wu ◽

Yan Yang ◽

Shuning Yuan ◽

...

Keyword(s):

Regression Analysis ◽

Endometrial Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Critical Role ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Promising Target

Increasing numbers of biomarkers have been identified in various cancers. However, biomarkers associated with endometrial carcinoma (EC) remain largely to be explored. In the current research, we downloaded the RNA-seq data and corresponding clinicopathological features from the Cancer Genome Atlas (TCGA) database. We conducted an expression analysis, which resulted in RILPL2 as a novel diagnostic biomarker in EC. The dysregulation of RILPL2 in EC was also validated in multiple datasets. The correlations between clinical features and RILPL2 expression were assessed by logistic regression analysis. Then, Kaplan-Meier analysis, univariate and multivariate Cox regression analysis were performed to estimate prognostic values of RILPL2 in the TCGA cohort, which revealed that increased level of RILPL2 was remarkably associated with better prognosis and could act as an independent prognostic biomarker in patients with EC. Moreover, correlation analysis of RILPL2 and tumor-infiltrating immune cells (TIICs) indicated that RILPL2 might play a critical role in regulating immune cell infiltration in EC and is related to immune response. Besides, high methylation level was a significant cause of low RILPL2 expression in EC. Subsequently, weighted gene co-expression network analysis (WGCNA) and enrichment analysis were conducted to explore the RILPL2-involved underlying oncogenic mechanisms, and the results indicated that RILPL2 mainly regulated cell cycle. In conclusion, our findings provided evidence that downregulation of RILPL2 in EC is an indicator of adverse prognosis and RILPL2 may act as a promising target for the therapeutics of EC.

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Integrated Analysis of lncRNA-Mediated ceRNA Network Reveals a Prognostic Signature for Hepatocellular Carcinoma

Frontiers in Genetics ◽

10.3389/fgene.2020.602542 ◽

2020 ◽

Vol 11 ◽

Author(s):

Jian-Rong Sun ◽

Chen-Fan Kong ◽

Kun-Min Xiao ◽

Jia-Lu Yang ◽

Xiang-Ke Qu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Regression Analysis ◽

Cox Regression ◽

Tnm Stage ◽

The Cancer Genome Atlas ◽

Integrated Analysis ◽

Cox Regression Analysis ◽

Cerna Network ◽

Kaplan Meier ◽

Risk Patients

Hepatocellular carcinoma (HCC) is one of the most common types of malignancy and is associated with high mortality. Prior research suggests that long non-coding RNAs (lncRNAs) play a crucial role in the development of HCC. Therefore, it is necessary to identify lncRNA-associated therapeutic biomarkers to improve the accuracy of HCC prognosis. Transcriptomic data of HCC obtained from The Cancer Genome Atlas (TCGA) database were used in the present study. Differentially expressed RNAs (DERNAs), including 74 lncRNAs, 16 miRNAs, and 35 mRNAs, were identified using bioinformatics analysis. The DERNAs were subsequently used to reconstruct a competing endogenous RNA (ceRNA) network. A lncRNA signature was revealed using Cox regression analysis, including LINC00200, MIR137HG, LINC00462, AP002478.1, and HTR2A-AS1. Kaplan-Meier plot demonstrated that the lncRNA signature is highly accurate in discriminating high- and low-risk patients (P < 0.05). The area under curve (AUC) value exceeded 0.7 in both training and validation cohort, suggesting a high prognostic potential of the signature. Furthermore, multivariate Cox regression analysis indicated that both the TNM stage and the lncRNA signature could serve as independent prognostic factors for HCC (P < 0.05). Then, a nomogram comprising the TNM stage and the lncRNA signature was determined to raise the accuracy in predicting the survival of HCC patients. In the present study, we have introduced a ceRNA network that could contribute to provide a new insight into the identification of potential regulation mechanisms for the development of HCC. The five-lncRNA signature could serve as a reliable biosignature for HCC prognosis, while the nomogram possesses strong potential in clinical applications.

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An energy metabolism-based eight-gene signature correlates with the clinical outcome of esophagus carcinoma

BMC Cancer ◽

10.1186/s12885-021-08030-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Weifeng Zheng ◽

Chaoying Chen ◽

Jianghao Yu ◽

Chengfeng Jin ◽

Tiemei Han

Keyword(s):

Energy Metabolism ◽

Cox Regression ◽

Expression Profiles ◽

Predictive Performance ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Cox Regression Analysis ◽

Prognostic Gene ◽

Kaplan Meier ◽

Esophagus Carcinoma

Abstract Background The essence of energy metabolism has spread to the field of esophageal cancer (ESC) cells. Herein, we tried to develop a prognostic prediction model for patients with ESC based on the expression profiles of energy metabolism associated genes. Materials and methods The overall survival (OS) predictive gene signature was developed, internally and externally validated based on ESC datasets including The Cancer Genome Atlas (TCGA), GSE54993 and GSE19417 datasets. Hub genes were identified in each energy metabolism related molecular subtypes by weighted gene correlation network analysis, and then enrolled for determination of prognostic genes. Univariate, LASSO and multivariate Cox regression analysis were applied to assess prognostic genes and build the prognostic gene signature. Kaplan-Meier curve, time-dependent receiver operating characteristic (ROC) curve, nomogram, decision curve analysis (DCA), and restricted mean survival time (EMST) were used to assess the performance of the gene signature. Results A novel energy metabolism based eight-gene signature (including UBE2Z, AMTN, AK1, CDCA4, TLE1, FXN, ZBTB6 and APLN) was established, which could dichotomize patients with significantly different OS in ESC. The eight-gene signature demonstrated independent prognostication potential in patient with ESC. The prognostic nomogram constructed based on the gene signature showed excellent predictive performance, whose robustness and clinical usability were higher than three previous reported prognostic gene signatures. Conclusions Our study established a novel energy metabolism based eight-gene signature and nomogram to predict the OS of ESC, which may help in precise clinical management.

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Blocking siglec-10hi tumor-associated macrophages improves anti-tumor immunity and enhances immunotherapy for hepatocellular carcinoma

Experimental Hematology and Oncology ◽

10.1186/s40164-021-00230-5 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Nan Xiao ◽

Xiaodong Zhu ◽

Kangshuai Li ◽

Yifan Chen ◽

Xuefeng Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cell Function ◽

Cox Regression ◽

Human Tumor ◽

The Cancer Genome Atlas ◽

Sequencing Data ◽

Tumor Associated Macrophages ◽

Cox Regression Analysis ◽

Kaplan Meier

Abstract Background Tumor-associated macrophages (TAMs) promote key processes in the modulation of tumor microenvironment (TME). However, the clinical significance of heterogeneous subpopulations of TAMs in hepatocellular carcinoma (HCC) remains unknown. Methods HCC tissues from Zhongshan Hospital and data from The Cancer Genome Atlas were obtained and analyzed. Immunohistochemistry and flow cytometry were performed to detect the characteristics of sialic acid-binding immunoglobulin-like lectin 10high (Siglec-10hi) TAMs and explore their impact on the TME of HCC. The effect of Siglec-10 blockade was evaluated in vitro based on fresh human tumor tissues. Results Our data revealed that Siglec-10 was abundant in a large proportion of HCC specimens and prominently distributed on macrophages. Kaplan–Meier curves and Cox regression analysis showed that intratumoral Siglec-10+ cell enrichment was associated with unfavorable prognosis in patients with HCC. Notably, multiple anti-inflammatory cytokines and inhibitory receptors were enriched in Siglec-10hi TAMs. RNA sequencing data also revealed that numerous M2-like signaling pathways were significantly upregulated in Siglec-10hi TAMs. High infiltration of Siglec-10hi TAMs was associated with impaired CD8+ T cell function in HCC. Of note, blocking Siglec-10 with the competitive binding antibody Siglec-10 Fc led to decreased expression of immunosuppressive molecules and increased the cytotoxic effects of CD8+ T cells against HCC cells. Moreover, blocking Siglec-10 promoted the anti-tumor efficacy of the programmed cell death protein 1 (PD-1) inhibitor pembrolizumab. Conclusions Siglec-10hi TAMs are associated with immune suppression in the TME, and indicate poor prognosis in patients with HCC. Targeting Siglec-10hi TAMs may serve as a promising immunotherapy approach for HCC.

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Establishment of a 5 DNA Methylation Site Prognostic Signature Associated with N6-Methyladenosine in Lung Adenocarcinoma

10.21203/rs.3.rs-1071199/v1 ◽

2021 ◽

Author(s):

Liqiang Yuan ◽

Wei Jiang ◽

Zhanyu Xu ◽

Kung Deng ◽

Yu Sun ◽

...

Keyword(s):

Dna Methylation ◽

Lung Adenocarcinoma ◽

Cox Regression ◽

Clinicopathological Parameters ◽

Main Body ◽

Methylation Site ◽

Cox Regression Analysis ◽

Site Model ◽

Kaplan Meier ◽

Cox Analysis

Abstract Background: There is a high incidence of lung adenocarcinoma (LUAD). Even with surgery, targeted therapy and immunotherapy, the survival rate of LUAD patients is still low. N6-methyladenosine (m6A) and DNA methylation markers can help with the diagnosis and treatment of LUAD patients. Therefore, it is necessary to identify a novel m6A-related DNA methylation sites signature to predict the survival of patients with LUAD. Methods: In this study, we screened 15 m6A-related genes and their 217 methylation sites. RNA sequencing data of 15 genes and the clinicopathological parameters of TCGA-LUAD were obtained from the TCGA database (http://cancergenome.nih.gov/). The LUAD-DNA CpG site information was obtained from the Illumina Human Methylation 450 BeadChip (Illumina, San Diego, CA, United States). The methylation sites related to prognosis were screened using univariate COX analysis, and the independent predictors of LUAD patients were identified using multivariate COX analysis of least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Finally, a model with 5 methylation sites as the main body to predict the prognosis of OS in patients with LUAD was obtained. According to the risk grouping of the prediction model, Kaplan-Meier curve and the receiver operating characteristic (ROC) curve were performed in the test and training sets to assess the predicted capacity of the model. In addition, a nomogram constructed by combining the risk score of methylation group and other related clinicopathological factors to verify the reliability of our model.Results: We constructed a m6A-related 5-DNA methylation site model to predict OS in LUAD patients. According to the results of the Kaplan-Meier curve, both the test set and the training set, the high-risk group showed a worse prognosis. The AUCs of the 5 DNA methylation signature at 1, 5 and 10 years in test datasets were 0.730, 0.649 and 0.726, respectively, and 0.679, 0.656 and 0.732 in training datasets. Finally, we constructed a nomogram to further verify the reliability of the model.Conclusion: In this study, we analyzed the methylation sites of m6A-related genes and established a m6A-related 5-DNA methylation site model to predict OS in LUAD patients.

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SELE gene as a characteristic prognostic biomarker of colorectal cancer

Journal of International Medical Research ◽

10.1177/03000605211004386 ◽

2021 ◽

Vol 49 (4) ◽

pp. 030006052110043

Author(s):

Na Li ◽

Honghe Xiao ◽

Jiangli Shen ◽

Ximin Qiao ◽

Fenjuan Zhang ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Proportional Hazards ◽

Cox Regression ◽

Expression Profiles ◽

Immunohistochemical Analysis ◽

Cox Proportional Hazards ◽

The Cancer Genome Atlas ◽

Clinical Value ◽

Cox Regression Analysis

Objective To investigate the expression and clinical value of the E-selectin gene ( SELE) in colorectal cancer (CRC). Methods Using gene expression profiles and clinicopathological data for patients with CRC from The Cancer Genome Atlas, and tumor and adjacent normal tissues from 31 patients with CRC from Xianyang Central Hospital, we studied the correlation between SELE gene expression and clinical parameters using Kaplan–Meier and Cox proportional hazards regression analyses. Results Higher expression of SELE was significantly associated with a poorer prognosis and shorter survival in patients with CRC. The median expression level of SELE was significantly higher in CRC tissues compared with healthy adjacent tissue. Cox regression analysis showed that the prognosis of CRC was significantly correlated with the expression of SELE. Immunohistochemical analysis also showed that positive expression of E-selectin increased significantly in line with increasing TNM stage. Conclusion: This study confirmed that SELE gene expression is an independent prognostic factor in patients with CRC.

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Identification and Validation of a Ferroptosis-Related Long Non-coding RNA Signature for Predicting the Outcome of Lung Adenocarcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.690509 ◽

2021 ◽

Vol 12 ◽

Author(s):

Zhiyuan Zheng ◽

Qian Zhang ◽

Wei Wu ◽

Yan Xue ◽

Shuhan Liu ◽

...

Keyword(s):

Immune Response ◽

Lung Adenocarcinoma ◽

Cox Regression ◽

Information Criteria ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Risk Scores ◽

Regression Analyses ◽

Cox Regression Analysis ◽

Kaplan Meier

BackgroundFerroptosis is a recently recognized type of programmed cell death that is involved in the biological processes of various cancers. However, the mechanism of ferroptosis in lung adenocarcinoma (LUAD) remains unclear. This study aimed to determine the role of ferroptosis-associated long non-coding RNAs (lncRNAs) in LUAD and to establish a prognostic model.MethodsWe downloaded ferroptosis-related genes from the FerrDb database and RNA sequencing data and clinicopathological characteristics from The Cancer Genome Atlas. We randomly divided the data into training and validation sets. Ferroptosis-associated lncRNA signatures with the lowest Akaike information criteria were determined using COX regression analysis and the least absolute shrinkage and selection operator. The risk scores of ferroptosis-related lncRNAs were calculated, and patients with LUAD were assigned to high- and low-risk groups based on the median risk score. The prognostic value of the risk scores was evaluated using Kaplan–Meier curves, Cox regression analyses, and nomograms. We then explored relationships between ferroptosis-related lncRNAs and the immune response using gene set enrichment analysis (GSEA).ResultsTen ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan–Meier and Cox regression analyses confirmed that the risk scores were independent predictors of LUAD outcome in the training and validation sets (all P < 0.05). The area under the curve confirmed that the signatures could determine the prognosis of LUAD. The predictive accuracy of the established nomogram model was verified using the concordance index and calibration curve. The GSEA showed that the 10 ferroptosis-related lncRNAs might be associated with tumor immune response.ConclusionWe established a novel signature involving 10 ferroptosis-related lncRNAs (LINC01843, MIR193BHG, AC091185.1, AC027031.2, AL021707.2, AL031667.3, AL606834.1, AC026355.1, AC124045.1, and AC025048.4) that can accurately predict the outcome of LUAD and are associated with the immune response. This will provide new insights into the development of new therapies for LUAD.

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The prognostic value of m6A-related LncRNAs in patients with HNSCC: bioinformatics analysis of TCGA database

Scientific Reports ◽

10.1038/s41598-021-04591-z ◽

2022 ◽

Vol 12 (1) ◽

Author(s):

Liu-qing Zhou ◽

Jin-xiong Shen ◽

Jie-yu Zhou ◽

Yao Hu ◽

Hong-jun Xiao

Keyword(s):

Prognostic Value ◽

Risk Model ◽

Cox Regression ◽

Predictive Ability ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Consensus Clustering ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Cancer Genome Atlas

AbstractN6-methyladenosine (m6A) modifications play an essential role in tumorigenesis. These modifications modulate RNAs, including mRNAs and lncRNAs. However, the prognostic role of m6A-related lncRNAs in head and neck squamous cell carcinoma (HNSCC) is poorly understood. Based on LASSO Cox regression, enrichment analysis, univariate and multivariate Cox regression analysis, a prognostic risk model, and consensus clustering analysis, we analyzed 12 m6A-related lncRNAs in HNSCC sample data from The Cancer Genome Atlas (TCGA) database. We found 12 m6A-related lncRNAs in the training cohort and validated them in all cohorts by Kaplan–Meier and Cox regression analyses, revealing their independent prognostic value in HNSCC. Moreover, ROC analysis was conducted, confirming the strong predictive ability of this signature for HNSCC survival. GSEA and detailed immune infiltration analyses revealed specific pathways associated with m6A-related lncRNAs. In this study, a novel risk model including twelve genes (SAP30L-AS1, AC022098.1, LINC01475, AC090587.2, AC008115.3, AC015911.3, AL122035.2, AC010226.1, AL513190.1, ZNF32-AS1, AL035587.1 and AL031716.1) was built. It could accurately predict HNSCC outcomes and could provide new therapeutic targets for HNSCC patients.

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Development and validation of an immune gene-set based prognostic signature for soft tissue sarcoma

BMC Cancer ◽

10.1186/s12885-021-07852-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Rui Shen ◽

Bo Liu ◽

Xuesen Li ◽

Tengbo Yu ◽

Kuishuai Xu ◽

...

Keyword(s):

Soft Tissue ◽

Soft Tissue Sarcoma ◽

Cox Regression ◽

Survival Curve ◽

The Cancer Genome Atlas ◽

Immune Gene ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Meier Survival Curve

Abstract Background Sarcomas is a group of heterogeneous malignant tumors originated from mesenchymal tissue and different types of sarcomas have disparate outcomes. The present study aims to identify the prognostic value of immune-related genes (IRGs) in sarcoma and establish a prognostic signature based on IRGs. Methods We collected the expression profile and clinical information of 255 soft tissue sarcoma samples from The Cancer Genome Atlas (TCGA) database and 2498 IRGs from the ImmPort database. The LASSO algorithm and Cox regression analysis were used to identify the best candidate genes and construct a signature. The prognostic ability of the signature was evaluated by ROC curves and Kaplan-Meier survival curves and validated in an independent cohort. Besides, a nomogram based on the IRGs and independent prognostic clinical variables was developed. Results A total of 19 IRGs were incorporated into the signature. In the training cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.938, 0.937 and 0.935, respectively. The Kaplan-Meier survival curve indicated that high-risk patients were significantly worse prognosis (P < 0.001). In the validation cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.730, 0.717 and 0.647, respectively. The Kaplan-Meier survival curve also showed significant distinct survival outcome between two risk groups. Furthermore, a nomogram based on the signature and four prognostic variables showed great accuracy in whole sarcoma patients and subgroup analyses. More importantly, the results of the TF regulatory network and immune infiltration analysis revealed the potential molecular mechanism of IRGs. Conclusions In general, we identified and validated an IRG-based signature, which can be used as an independent prognostic signature in evaluating the prognosis of sarcoma patients and provide potential novel immunotherapy targets.

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