mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

Cancer stem cells (CSCs), characterized by self-renewal and unlimited proliferation, lead to therapeutic resistance in lung cancer. In this study, we aimed to investigate the expressions of stem cell-related genes in lung adenocarcinoma (LUAD). The stemness index based on mRNA expression (mRNAsi) was utilized to analyze LUAD cases in the Cancer Genome Atlas (TCGA). First, mRNAsi was analyzed with differential expressions, survival analysis, clinical stages, and gender in LUADs. Then, the weighted gene co-expression network analysis was performed to discover modules of stemness and key genes. The interplay among the key genes was explored at the transcription and protein levels. The enrichment analysis was performed to annotate the function and pathways of the key genes. The expression levels of key genes were validated in a pan-cancer scale. The pathological stage associated gene expression level and survival probability were also validated. The Gene Expression Omnibus (GEO) database was additionally used for validation. The mRNAsi was significantly upregulated in cancer cases. In general, the mRNAsi score increases according to clinical stages and differs in gender significantly. Lower mRNAsi groups had a better overall survival in major LUADs, within five years. The distinguished modules and key genes were selected according to the correlations to the mRNAsi. Thirteen key genes (CCNB1, BUB1, BUB1B, CDC20, PLK1, TTK, CDC45, ESPL1, CCNA2, MCM6, ORC1, MCM2, and CHEK1) were enriched from the cell cycle Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, relating to cell proliferation Gene Ontology (GO) terms, as well. Eight of the thirteen genes have been reported to be associated with the CSC characteristics. However, all of them have been previously ignored in LUADs. Their expression increased according to the pathological stages of LUAD, and these genes were clearly upregulated in pan-cancers. In the GEO database, only the tumor necrosis factor receptor associated factor-interacting protein (TRAIP) from the blue module was matched with the stemness microarray data. These key genes were found to have strong correlations as a whole, and could be used as therapeutic targets in the treatment of LUAD, by inhibiting the stemness features.

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Identification of key genes associated with lung adenocarcinoma by bioinformatics analysis

Science Progress ◽

10.1177/0036850421997276 ◽

2021 ◽

Vol 104 (1) ◽

pp. 003685042199727

Author(s):

Xinyu Wang ◽

Jiaojiao Yang ◽

Xueren Gao

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Lung Adenocarcinoma ◽

Cox Regression ◽

Enrichment Analysis ◽

Tumor Stage ◽

Gene Expression Omnibus ◽

Poor Overall Survival ◽

Key Genes ◽

Low Expression

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer, comprising around 40% of all lung cancer. Until now, the pathogenesis of LUAD has not been fully elucidated. In the current study, we comprehensively analyzed the dysregulated genes in lung adenocarcinoma by mining public datasets. Two sets of gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. The dysregulated genes were identified by using the GEO2R online tool, and analyzed by R packages, Cytoscape software, STRING, and GPEIA online tools. A total of 275 common dysregulated genes were identified in two independent datasets, including 54 common up-regulated and 221 common down-regulated genes in LUAD. Gene Ontology (GO) enrichment analysis showed that these dysregulated genes were significantly enriched in 258 biological processes (BPs), 27 cellular components (CCs), and 21 molecular functions (MFs). Furthermore, protein-protein interaction (PPI) network analysis showed that PECAM1, ENG, KLF4, CDH5, and VWF were key genes. Survival analysis indicated that the low expression of ENG was associated with poor overall survival (OS) of LUAD patients. The low expression of PECAM1 was associated with poor OS and recurrence-free survival of LUAD patients. The cox regression model developed based on age, tumor stage, ENG, PECAM1 could effectively predict 5-year survival of LUAD patients. This study revealed some key genes, BPs, CCs, and MFs involved in LUAD, which would provide new insights into understanding the pathogenesis of LUAD. In addition, ENG and PECAM1 might serve as promising prognostic markers in LUAD.

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Identification and Validation of a Novel Immune-Related Four-lncRNA Signature for Lung Adenocarcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.639254 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jixin Wang ◽

Xiangjun Yin ◽

Yin-Qiang Zhang ◽

Xuming Ji

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Lasso Regression ◽

Kaplan Meier

Lung adenocarcinoma (LUAD) is a major subtype of lung cancer, the prognosis of patients with which is associated with both lncRNAs and cancer immunity. In this study, we collected gene expression data of 585 LUAD patients from The Cancer Genome Atlas (TCGA) database and 605 subjects from the Gene Expression Omnibus (GEO) database. LUAD patients were divided into high and low immune-cell-infiltrated groups according to the single sample gene set enrichment analysis (ssGSEA) algorithm to identify differentially expressed genes (DEGs). Based on the 49 immune-related DE lncRNAs, a four-lncRNA prognostic signature was constructed by applying least absolute shrinkage and selection operator (LASSO) regression, univariate Cox regression, and stepwise multivariate Cox regression in sequence. Kaplan–Meier curve, ROC analysis, and the testing GEO datasets verified the effectiveness of the signature in predicting overall survival (OS). Univariate Cox regression and multivariate Cox regression suggested that the signature was an independent prognostic factor. The correlation analysis revealed that the infiltration immune cell subtypes were related to these lncRNAs.

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Identification of Potential Key Genes and Pathways in Enzalutamide-Resistant Prostate Cancer Cell Lines: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database

BioMed Research International ◽

10.1155/2020/8341097 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Long Zheng ◽

Xiaojie Dou ◽

Xiaodong Ma ◽

Wei Qu ◽

Xiaoshuang Tang

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Cell Lines ◽

Molecular Mechanisms ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Gene Set Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Key Genes ◽

Geo Database

Enzalutamide (ENZ) has been approved for the treatment of advanced prostate cancer (PCa), but some patients develop ENZ resistance initially or after long-term administration. Although a few key genes have been discovered by previous efforts, the complete mechanisms of ENZ resistance remain unsolved. To further identify more potential key genes and pathways in the development of ENZ resistance, we employed the GSE104935 dataset, including 5 ENZ-resistant (ENZ-R) and 5 ENZ-sensitive (ENZ-S) PCa cell lines, from the Gene Expression Omnibus (GEO) database. Integrated bioinformatics analyses were conducted, such as analysis of differentially expressed genes (DEGs), Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein-protein interaction (PPI) analysis, gene set enrichment analysis (GSEA), and survival analysis. From these, we identified 201 DEGs (93 upregulated and 108 downregulated) and 12 hub genes (AR, ACKR3, GPER1, CCR7, NMU, NDRG1, FKBP5, NKX3-1, GAL, LPAR3, F2RL1, and PTGFR) that are potentially associated with ENZ resistance. One upregulated pathway (hedgehog pathway) and seven downregulated pathways (pathways related to androgen response, p53, estrogen response, TNF-α, TGF-β, complement, and pancreas β cells) were identified as potential key pathways involved in the occurrence of ENZ resistance. Our findings may contribute to further understanding the molecular mechanisms of ENZ resistance and provide some clues for the prevention and treatment of ENZ resistance.

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Functions and clinical significance of KLRG1 in the development of lung adenocarcinoma and immunotherapy

BMC Cancer ◽

10.1186/s12885-021-08510-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xiaodong Yang ◽

Yuexin Zheng ◽

Zhihai Han ◽

Xiliang Zhang

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Lung Adenocarcinoma ◽

Molecular Mechanisms ◽

Killer Cell ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Normal Lung ◽

Using Data ◽

Low Expression

Abstract Background As a marker of differentiation, Killer cell lectin like receptor G1 (KLRG1) plays an inhibitory role in human NK cells and T cells. However, its clinical role remains inexplicit. This work intended to investigate the predictive ability of KLRG1 on the efficacy of immune-checkpoint inhibitor in the treatment of lung adenocarcinoma (LUAD), as well as contribute to the possible molecular mechanisms of KLRG1 on LUAD development. Methods Using data from the Gene Expression Omnibus, the Cancer Genome Atlas and the Genotype-Tissue Expression, we compared the expression of KLRG1 and its related genes Bruton tyrosine kinase (BTK), C-C motif chemokine receptor 2 (CCR2), Scm polycomb group protein like 4 (SCML4) in LUAD and normal lung tissues. We also established stable LUAD cell lines with KLRG1 gene knockdown and investigated the effect of KLRG1 knockdown on tumor cell proliferation. We further studied the prognostic value of the four factors in terms of overall survival (OS) in LUAD. Using data from the Gene Expression Omnibus, we further investigated the expression of KLRG1 in the patients with different responses after immunotherapy. Results The expression of KLRG1, BTK, CCR2 and SCML4 was significantly downregulated in LUAD tissues compared to normal controls. Knockdown of KLRG1 promoted the proliferation of A549 and H1299 tumor cells. And low expression of these four factors was associated with unfavorable overall survival in patients with LUAD. Furthermore, low expression of KLRG1 also correlated with poor responses to immunotherapy in LUAD patients. Conclusion Based on these findings, we inferred that KLRG1 had significant correlation with immunotherapy response. Meanwhile, KLRG1, BTK, CCR2 and SCML4 might serve as valuable prognostic biomarkers in LUAD.

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Development and validation of a 13-m6a related lncRNA prognostic signature for lung adenocarcinoma

10.21203/rs.3.rs-771653/v1 ◽

2021 ◽

Author(s):

Pingfan Wu ◽

Xiaowen Zhao ◽

Ling Xue ◽

Xiaojing Yang ◽

Yuxiang Shi ◽

...

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Treatment Strategies ◽

Risk Groups ◽

Gene Expression Omnibus ◽

High Risk Group ◽

The Cancer Genome Atlas ◽

Prognostic Signature ◽

P53 Signaling ◽

Selection Operator

Abstract Considerable evidence suggests that N6-methyladenosine (m6A) is involved in the regulation of long non-coding RNA (lncRNA), whichparticipates in the occurrence, development and prognosis of tumorscancerBut the relationship between m6A regulators-related lncRNA (mRlncRNA) and lung adenocarcinoma (LUAD) remains unclear. This study aims to determine a feature based on mRlncRNA for prognostic evaluation of LUAD patients. By integrating the gene expression data of LUAD and normal samples from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, the m6A gene and mRlncRNA with imbalanced expression were screened out. Then we used the least absolute shrinkage and selection operator (LASSO) to obtain the 13-lncRNA prognostic signature in the TCGA training cohort. Patients were divided into two risk groups based on the risk score of lncRNAs characteristics, and their overall survival (OS) was significantly different. The predictive power of this signature was verified in TCGA testing cohort and entire TCGA cohort. These landmark lncRNAs were involved in several biologiocal processes and pathways related to cell cycle, DNA replication, P53 signaling pathway and mismatch repair. Besides, the high-risk group was low-response to cisplatin, while high-response to mitomycin, docetaxel and immunotherapy. In conclusion, we identified a 13-mRlncRNA model associated with prognosis and treatment sensitivity in LUAD, which may provide clues about the influence of m6A on lncRNA in LUAD and promote the further improvement of LUAD individualized treatment strategies.

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Functions and Clinical Significance of KLRG1 in the Development of Lung Adenocarcinoma and Immunotherapy

10.21203/rs.3.rs-59360/v1 ◽

2020 ◽

Author(s):

Xiaodong Yang ◽

Yuexin Zheng ◽

Zhihai Han ◽

xiliang zhang

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Lung Adenocarcinoma ◽

Killer Cell ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Prognostic Biomarkers ◽

Normal Lung ◽

Using Data ◽

Low Expression

Abstract Background. As a marker of differentiation, Killer cell lectin like receptor G1 (KLRG1) plays an inhibitory role in human NK cells and T cells. However, its clinical role remains inexplicit. This work intended to investigate the predictive ability of KLRG1 in lung adenocarcinoma (LUAD) after immune-checkpoint inhibitor therapy, as well as to explore the role of a possible KLRG1 molecular mechanism on LUAD development.Methods. Using data from the Gene Expression Omnibus, the Cancer Genome Atlas and the Genotype-Tissue Expression, we compared the expression of KLRG1 and its related genes Bruton tyrosine kinase (BTK), C-C motif chemokine receptor 2 (CCR2), Scm polycomb group protein like 4 (SCML4) in LUAD and normal lung tissues. We further established a stable LUAD cell line with KLRG1 knockdown and investigate the effect of KLRG1 knockdown on tumor cell proliferation. We also studied the prognostic value of the four factors in terms of overall survival (OS) in LUAD. Using data from the Gene Expression Omnibus, we further investigated the expression of KLRG1 in the patients with different responses after immunotherapy.Results. The expression of KLRG1, BTK, CCR2 and SCML4 was significantly downregulated in LUAD tissues compared to normal controls. Knockdown of KLRG1 promoted the proliferation of A549 tumor cells. And low expression of these four factors was all associated with unfavorable overall survival in patients with LUAD. Furthermore, low expression of KLRG1 also correlated with poor responses in LUAD patients after immunotherapy.Conclusion. Based on these findings, we infer that KLRG1 had significant correlation with immunotherapy response. Meanwhile, KLRG1, BTK, CCR2 and SCML4 might serve as valuable prognostic biomarkers in LUAD. Key pointsKLRG1 inhibits the progress of LUAD.KLRG1 had significant correlation with immunotherapy response.KLRG1, BTK, CCR2 and SCML4 might serve as valuable prognostic biomarkers in LUAD.

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Potential Role of S-Palmitoylation in Cancer Stem Cells of Lung Adenocarcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.734897 ◽

2021 ◽

Vol 9 ◽

Author(s):

Yitong Zhang ◽

Fenglan Li ◽

Kexin Fu ◽

Xiqing Liu ◽

I-Chia Lien ◽

...

Keyword(s):

Stem Cell ◽

Cancer Stem Cell ◽

Lung Adenocarcinoma ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Protein Levels ◽

Exact Function ◽

Chromosomal Passenger ◽

Human Protein Atlas ◽

Localization Signal

S-palmitoylation, catalyzed by a family of 23 zinc finger Asp-His-His-Cys (DHHC) domain-containing (ZDHHC) protein acyltransferases localized on the cell membrane. However, stemness genes modulated by ZDHHCs in lung adenocarcinoma (LUAD) remain to be defined. Previously, we have constructed a network of cancer stem cell genes, including INCENP, based on mRNA stemness indices (mRNAsi) of LUAD. INCENP has the function of a chromosomal passenger complex locating to centromeres, which is performed by the conserved region of its N-terminal domain. INCENP protein with a deletion of the first non-conserved 26 amino acid sequence failed to target centromeres. However, the exact function of the deleted sequence has not been elucidated. To identify novel cancer stem cell-relevant palmitoylated proteins and responsible ZDHHC enzymes in LUAD, we analyzed multi-omics data obtained from the database of The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and the Human Protein Atlas (HPA). ZDHHC5 is distinguished from the ZDHHC family for being up-regulated in mRNA and protein levels and associated with malignant prognosis. ZDHHC5 was positively associated with INCENP, and the correlation score increased with LUAD stages. CSS-Palm results showed Cys15 was the S-palmitoylation site of INCENP. Interestingly, Cys15 locates in the 1–26 aa sequence of INCENP, and is a conserved site across species. As INCENP is a nuclear protein, we predicted that the nuclear localization signal of ZDHHC5 was specific to the importin αβ pathway, and the result of immunofluorescence proves that ZDHHC5 is located in the nucleoplasm, in addition to the plasma membrane. Therefore, our study indicates the S-palmitoylation of INCENP mediated by ZDHHC5 as a potential mechanism of S-palmitoylation to modulate CSCs in LUAD.

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Integrated analysis of cancer stem cells-associated lncRNA-miRNA-mRNA network for ovarian cancer via microarray and Gene Expression Omnibus database

10.21203/rs.3.rs-106454/v1 ◽

2020 ◽

Author(s):

Zheng Li ◽

Zhijiao Wang ◽

Yingying Zhou

Keyword(s):

Gene Expression ◽

Ovarian Cancer ◽

Stem Cells ◽

Stem Cell ◽

Cancer Stem Cells ◽

Signaling Pathway ◽

Gene Expression Omnibus ◽

Integrated Analysis ◽

Cerna Network ◽

Geo Database

Abstract Background: Cancer stem cells (CSCs) are associated with the recurrence, metastasis and chemoresistance of epithelial ovarian cancer. Competing endogenous RNAs (CeRNAs) play an important role in maintenance of ovarian cancer stem cell-like cells (OCSCs) characteristics. To construct a ceRNA regulatory network for OCSCs, microarray technology and Gene Expression Omnibus (GEO) database had been used. Human serous epithelial ovarian carcinoma cell line COC1 cells were treated with cisplatin and paclitaxel then maintained in stem cell conditions for 6 days to obtain CD117+/CD133+ cells (OCSCs). We identified the differentially expressed miRNAs (DEMs), lncRNA (DELs) and mRNA (DEGs) between OCSCs and COC1 by microarray and combined them with representative microarray profiles in GEO Database. Results: According to the combination, 28 DEMs were identified at first, and 452 DEGs were obtained combining with the predicted targets of these miRNAs and our mRNA microarray results. Up-regulated DEGs of them were significantly enriched in ‘p53 signaling pathway’, ‘FoxO signaling pathway’ and ‘MicroRNAs in cancer’, whereas down-regulated DEGs were significantly enriched in ‘Adherens junction’ and ‘Hepatitis C’ pathway. 29 transcripts of 17 lncRNAs should be the ceRNAs of 10 of these miRNAs according to bioinformatics predicted results and lncRNA microarray. Finally, we obtained ceRNA network with 10 DEMs, 21 DEGs, and 25 transcripts of 13 DELs which should play an important role in maintenance of OCSCs characteristics. LINC00665-miR-146a-5p-NRP2 should be one of ceRNA pathways of the network. The qPCR results indicated that the expression of miR-146a-5p in OCSCs was lower than that in COC1, and LINC00665 shows the opposite trend. These results were consistent with the results of microarray partially. When LINC00665 expression was up-regulated in COC1, the cell proliferation ability enhanced, apoptosis rate reduced, and the percentage of G2/M phase cells increased. Conclusions: The ceRNA network we constructed may be involved in the stem cell characteristics maintenance of OCSCs and provide directions for further OCSCs research in the future, so as to assist the development and treatment of ovarian cancer.

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Longitudinal Analysis of Gene Expression Changes During Cervical Carcinogenesis Reveals Potential Therapeutic Targets

Evolutionary Bioinformatics ◽

10.1177/1176934320920574 ◽

2020 ◽

Vol 16 ◽

pp. 117693432092057

Author(s):

Lijun Yu ◽

Meiyan Wei ◽

Fengyan Li

Keyword(s):

Gene Expression ◽

Western Blotting ◽

Protein Interactions ◽

Target Genes ◽

Quantitative Polymerase Chain Reaction ◽

Enrichment Analysis ◽

Gene Interaction ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Gene Expressions

Despite advances in the treatment of cervical cancer (CC), the prognosis of patients with CC remains to be improved. This study aimed to explore candidate gene targets for CC. CC datasets were downloaded from the Gene Expression Omnibus database. Genes with similar expression trends in varying steps of CC development were clustered using Short Time-series Expression Miner (STEM) software. Gene functions were then analyzed using the Gene Ontology (GO) database and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Protein interactions among genes of interest were predicted, followed by drug-target genes and prognosis-associated genes. The expressions of the predicted genes were determined using real-time quantitative polymerase chain reaction (RT-qPCR) and Western blotting. Red and green profiles with upward and downward gene expressions, respectively, were screened using STEM software. Genes with increased expression were significantly enriched in DNA replication, cell-cycle-related biological processes, and the p53 signaling pathway. Based on the predicted results of the Drug-Gene Interaction database, 17 drug-gene interaction pairs, including 3 red profile genes (TOP2A, RRM2, and POLA1) and 16 drugs, were obtained. The Cancer Genome Atlas data analysis showed that high POLA1 expression was significantly correlated with prolonged survival, indicating that POLA1 is protective against CC. RT-qPCR and Western blotting showed that the expressions of TOP2A, RRM2, and POLA1 gradually increased in the multistep process of CC. TOP2A, RRM2, and POLA1 may be targets for the treatment of CC. However, many studies are needed to validate our findings.

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