Bioinformatic screening of human ESTs for differentially expressed genes in normal and tumor tissues

Abstract Background: Tumor-associated macrophages (TAMs) are closely related to unfavorable prognosis of patients with clear cell renal cell carcinoma (ccRCC). However, the important molecules in the interaction between ccRCC and TAMs are unclear.Methods: TCGA-KIRC gene expression data of tumor tissues and normal tissues adjacent to tumor were compared to identify differentially expressed genes in ccRCC. TAMs related genes were discovered by analyzing the correlation between these differentially expressed genes and common macrophage biomarkers. Gene set enrichment analysis was performed to predict functions of TAMs related gene. The findings were further validated using RNA sequencing data obtained from the CheckMate 025 study and immunohistochemical analysis of samples from 350 patients with ccRCC. Kaplan–Meier survival curve, Cox regression analysis and Harrell’s concordance index analysis were used to determine the prognostic significance.Results: In this study, we applied bioinformatic analysis to explore TAMs related differentially expressed genes in ccRCC and identified 5 genes strongly correlated with all selected macrophage biomarkers: STAC3, LGALS9, TREM2, FCER1G, and PILRA. Among them, FCER1G was abundantly expressed in tumor tissues and showed prognostic importance in patients with ccRCC who received treatment with Nivolumab; however, it did not exhibit prognostic value in those treated with Everolimus. We also discovered that high expression levels of FCER1G are related to T cell suppression. Moreover, combination of FCER1G and macrophage biomarker CD68 can improve the prognostic stratification of patients with ccRCC from TCGA-KIRC. Based on the immunohistochemical analysis of samples from patients with ccRCC, we further validated that FCER1G and CD68 are both highly expressed in tumor tissue and correlate with each other. Higher expression of CD68 or FCER1G in ccRCC tissue indicates shorter overall survival and progression-free survival; patients with high expression of both CD68 and FCER1G have the worst outcome. Combining CD68 and FCER1G facilitates the screening of patients with a worse prognosis from the same TNM stage group.Conclusions: High expression of FCER1G in ccRCC is closely related to TAMs infiltration and suppression of T cell function. Combining the expression levels of FCER1G and macrophage biomarker CD68 may be a promising postoperative prognostic index for patients with ccRCC.

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Dissecting the Single-Cell Transcriptome Network in Superficial/Deep Tumor Tissues of Diffuse Gastric Cancer

10.21203/rs.3.rs-1130074/v1 ◽

2021 ◽

Author(s):

Yili Ren ◽

Beibei Zhang ◽

Chenkai Xu ◽

Lei Zhang

Keyword(s):

Gastric Cancer ◽

Survival Analysis ◽

Single Cell ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Differentially Expressed ◽

Cell Subpopulation ◽

Diffuse Gastric Cancer ◽

Normal Tissues ◽

Tumor Tissues

Abstract Background and purpose: Gastric cancer is a type of highly heterogeneous malignant tumor and the prognosis of gastric cancer is hard to be improved due to limited knowledge on the molecular mechanism of heterogeneity. Single-cell sequencing technology is recently widely used for the investigation of both inter-tumoral heterogeneity and intra-tumoral heterogeneity. The present study aims to explore the potential oncogene by analyzing the single-cell data in the GSE167297 dataset.Methods: The GSE167297 dataset was downloaded from the GEO database, followed by quality control to remove data with lower quality. The division on cell subtypes was determined by the characteristic marker expressed in each cell subpopulation. Wilcoxon rank-sum test was used to screen out differentially expressed genes. Survival analysis was performed to evaluate the prognostic value of G-protein subunit g 11 (GNG11) gene which was significantly overexpressed in deep tumor tissues of diffuse gastric cancer.Results: In both normal tissues and tumor tissues, subtypes of immune cells and stromal cells were identified, with a higher proportion of infiltrated macrophages observed in deep tumor tissues. EPCAM was found significantly highly expressed in a cell subpopulation from gastric tumor tissues. 515 differentially expressed genes (| log2FC | > 2 and FDR < 1e-5) were screened out between normal tissues and tumor tissues. 86 differentially expressed genes (| log2FC | > 1 and FDR < 0.01) were screened out between superficial and deep tumor tissues, in which GNG11 was most highly expressed in deep tumor tissues (mean expression value: 0.1247, FC value: 52.2109). Disease-specific survival analysis on GNG11 results showed that the HR [95%CI] in the constructed univariate Cox proportional risk model was 4.419 [1.399-13.96] and the P-value in the log-rank test was 0.0056.Conclusion: Differentially expression profiles were provided both extratumorally and intratumorally, indicating a higher infiltration of macrophages in deep tumor tissues. Additionally,GNG11 was screened out to be a significant risk factor in STAD patients.

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Detection of differentially expressed genes in primary tumor tissues using representational differences analysis coupled to microarray hybridization

Nucleic Acids Research ◽

10.1093/nar/26.12.3059 ◽

1998 ◽

Vol 26 (12) ◽

pp. 3059-3065 ◽

Cited By ~ 100

Author(s):

S. M. Welford ◽

J. Gregg ◽

E. Chen ◽

D. Garrison ◽

P. H. Sorensen ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Primary Tumor ◽

Differentially Expressed ◽

Microarray Hybridization ◽

Tumor Tissues

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Gene Expression Analysis of Human Papillomavirus-Associated Colorectal Carcinoma

BioMed Research International ◽

10.1155/2020/5201587 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Qiancheng Qiu ◽

Yazhen Li ◽

Zhiqiang Fan ◽

Fen Yao ◽

Wenjun Shen ◽

...

Keyword(s):

Human Papillomavirus ◽

Signaling Pathways ◽

Differentially Expressed Genes ◽

Target Genes ◽

Hpv Infection ◽

Differentially Expressed ◽

Noncancerous Tissue ◽

Normal Tissues ◽

Tumor Tissues ◽

Taqman Array

Purpose. Human papillomavirus (HPV) antigens had been found in colorectal cancer (CRC) tissue, but little evidence demonstrates the association of HPV with oncogene mutations in CRC. We aim to elucidate the mutated genes that link HPV infection and CRC carcinogenesis. Methods. Cancerous and adjacent noncancerous tissues were obtained from CRC patients. HPV antigen was measured by using the immunohistochemical (IHC) technique. The differentially expressed genes (DEGs) in HPV-positive and HPV-negative tumor tissues were measured by using TaqMan Array Plates. The target genes were validated with the qPCR method. Results. 15 (31.9%) cases of CRC patients were observed to be HPV positive, in which HPV antigen was expressed in most tumor tissues rather than in adjacent noncancerous tissues. With TaqMan Array Plates analyses, we found that 39 differentially expressed genes (DEGs) were upregulated, while 17 DEGs were downregulated in HPV-positive CRC tissues compared with HPV-negative tissues. Four DEGs (MMP-7, MYC, WNT-5A, and AXIN2) were upregulated in tumor vs. normal tissues, or adenoma vs. normal tissue in TCGA, which was overlapped with our data. In the confirmation test, MMP-7, MYC, WNT-5A, and AXIN2 were upregulated in cancerous tissue compared with adjacent noncancerous tissue. MYC, WNT-5A, and AXIN2 were shown to be upregulated in HPV-positive CRC tissues when compared to HPV-negative tissues. Conclusion. HPV-encoding genome may integrate into the tumor genomes that involved in multiple signaling pathways. Further genomic and proteomic investigation is necessary for obtaining a more comprehensive knowledge of signaling pathways associated with the CRC carcinogenesis.

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A Novel Five-Gene Signature for Prognosis Prediction in Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.642563 ◽

2021 ◽

Vol 11 ◽

Author(s):

Lisa Su ◽

Genhao Zhang ◽

Xiangdong Kong

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Differentially Expressed Genes ◽

Gene Signature ◽

Differentially Expressed ◽

Clinical Samples ◽

Tumor Tissues ◽

Global Health Issue ◽

Poor Outcomes ◽

Cancer Tissues

Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes. In this study, our purpose was to explore an effective prognostic marker for HCC. Five cohort profile datasets from GEO (GSE25097, GSE36376, GSE62232, GSE76427 and GSE101685) were integrated with TCGA-LIHC and GTEx dataset to identify differentially expressed genes (DEGs) between normal and cancer tissues in HCC patients, then 5 upregulated differentially expressed genes and 32 downregulated DEGs were identified as common DEGs in total. Next, we systematically explored the relationship between the expression of 37 common DEGs in tumor tissues and overall survival (OS) rate of HCC patients in TCGA and constructed a novel prognostic model composed of five genes (AURKA, PZP, RACGAP1, ACOT12 and LCAT). Furthermore, the predicted performance of the five-gene signature was verified in ICGC and another independent clinical samples cohort, and the results demonstrated that the signature performed well in predicting the OS rate of patients with HCC. What is more, the signature was an independent hazard factor for HCC patients when considering other clinical factors in the three cohorts. Finally, we found the signature was significantly associated with HCC immune microenvironment. In conclusion, the prognostic five-gene signature identified in our present study could efficiently classify patients with HCC into subgroups with low and high risk of longer overall survival time and help clinicians make decisions for individualized treatment.

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