The association of immunosurveillance and distant metastases in colorectal cancer

Abstract Background Colorectal cancer (CRC) is the third most common malignancy worldwide, but the key driver to distant metastases is still unknown. This study aimed to elucidate the link between immunosurveillance and organotropism of metastases in CRC by evaluating different gene signatures and pathways. Material and methods CRC patients undergoing surgery at the Department of General, Visceral and Transplantation Surgery at the Ludwig-Maximilian University Hospital Munich (Munich, Germany) were screened and categorized into M0 (no distant metastases), HEP (liver metastases) and PER (peritoneal carcinomatosis) after a 5-year follow-up. Six patients of each group were randomly selected to conduct a NanoString analysis, which includes 770 genes. Subsequently, all genes were further analyzed by gene set enrichment analysis (GSEA) based on seven main cancer-associated databases. Results Comparing HEP vs. M0, the gene set associated with the Toll-like receptor (TLR) cascade defined by the Reactome database was significantly overrepresented in HEP. HSP90B1, MAPKAPK3, PPP2CB, PPP2R1A were identified as the core enrichment genes. The immunologic signature pathway GSE6875_TCONV_VS_FOXP3_KO_TREG_DN with FOXP3 as downstream target was significantly overexpressed in M0. RB1, TMEM 100, CFP, ZKSCAN5, DDX50 were the core enrichment genes. Comparing PER vs. M0 no significantly differentially expressed gene signatures were identified. Conclusion Chronic inflammation might enhance local tumor growth. This is the first study identifying immune related gene sets differentially expressed between patients with either liver or peritoneal metastases. The present findings suggest that the formation of liver metastases might be associated with TLR-associated pathways. In M0, a high expression of FOXP3 + tumor infiltrating lymphocytes (TILs) seemed to prevent at least in part metastases. Thus, these correlative findings lay the cornerstone to further studies elucidating the underlying mechanisms of organotropism of metastases.

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Distant Liver Metastases as a Major Factor Influencing Survival in Patients with Colorectal Cancer

Folia Medica ◽

10.1515/folmed-2016-0023 ◽

2016 ◽

Vol 58 (3) ◽

pp. 182-187

Author(s):

Dimitar K. Penchev ◽

Lilyana V. Vladova ◽

Miroslav Z. Zashev ◽

Radosvet P. Gornev

Keyword(s):

Colorectal Cancer ◽

Liver Metastases ◽

Median Survival ◽

Metastatic Disease ◽

Descriptive Analysis ◽

Distant Metastases ◽

University Hospital ◽

Rank Test ◽

Hepatic Metastatic Disease

Abstract Aim: To assess the effect of the factor ‘hepatic metastatic disease’ on long-term outcomes in patients with colorectal cancer. Materials and methods: We analysed retrospectively 200 randomly selected patients. Forty-two of them were excluded from the study for different reasons so the study contingent was 158 patients over a period of 23 years. All were diagnosed and treated in the Lozenetz University Hospital, in the Department of General Surgery. 125 of the patients were diagnosed with colorectal cancer without distant metastases and 33 of the patients had liver metastases as a result of colorectal carcinoma. The statistical analysis was performed using SPSS 19 IMB, with a level of significance of P < 0.05 at which the null hypothesis is rejected. We also used descriptive analysis, Kaplan-Meier estimator, Log-Rank Test and Life-Table statistics models. Results: The median survival for patients without metastases was 160 months, and the median was 102 months. The median survival for patients with liver metastases was 28 months and the median was 21 months. One-year survival for patients without metastases was 92% versus 69% in patients with liver metastases. Conclusion: Average, annual and median survivals are influenced statistically significantly by the presence of liver metastases compared to overall survival and that of patients without metastatic colorectal cancer. Liver metastatic disease is a proven factor affecting long-term prognosis and survival in patients with colorectal cancer.

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Identification of differentially expressed gene sets using the Generalized Berk–Jones statistic

Bioinformatics ◽

10.1093/bioinformatics/btz277 ◽

2019 ◽

Vol 35 (22) ◽

pp. 4568-4576 ◽

Cited By ~ 1

Author(s):

Sheila M Gaynor ◽

Ryan Sun ◽

Xihong Lin ◽

John Quackenbush

Keyword(s):

Transcription Factors ◽

Differential Expression ◽

Cancer Genomics ◽

Differentially Expressed Gene ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Supplementary Information ◽

Disease Etiology ◽

Gene Set ◽

Analytical Approaches

Abstract Motivation Cancer genomics studies frequently aim to identify genes that are differentially expressed between clinically distinct patient subgroups, generally by testing single genes one at a time. However, the results of any individual transcriptomic study are often not fully reproducible. A particular challenge impeding statistical analysis is the difficulty of distinguishing between differential expression comprising part of the genomic disease etiology and that induced by downstream effects. More robust analytical approaches that are well-powered to detect potentially causative genes, are less prone to discovering spurious associations, and can deliver reproducible findings across different studies are needed. Results We propose a set-based procedure for testing of differential expression and show that this set-based approach can produce more robust results by aggregating information across multiple, correlated genomic markers. Specifically, we adapt the Generalized Berk–Jones statistic to test for the transcription factors that may contribute to the progression of estrogen receptor positive breast cancer. We demonstrate the ability of our method to produce reproducible findings by applying the same analysis to 21 publicly available datasets, producing a similar list of significant transcription factors across most studies. Our Generalized Berk–Jones approach produces results that show improved consistency over three set-based testing algorithms: Generalized Higher Criticism, Gene Set Analysis and Gene Set Enrichment Analysis. Availability and implementation Data are in the MetaGxBreast R package. Code is available at github.com/ryanrsun/gaynor_sun_GBJ_breast_cancer. Supplementary information Supplementary data are available at Bioinformatics online.

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Gene Set Correlation Analysis and Visualization Using Gene Expression Data

Current Bioinformatics ◽

10.2174/1574893615999200629124444 ◽

2020 ◽

Vol 15 ◽

Author(s):

Chen-An Tsai ◽

James J. Chen

Keyword(s):

Gene Expression ◽

Correlation Analysis ◽

Gene Expression Data ◽

Differentially Expressed Gene ◽

Differentially Expressed ◽

Superior Performance ◽

Expression Data ◽

Gene Set ◽

Gene Sets ◽

Set Correlation

Background: Gene set enrichment analyses (GSEA) provide a useful and powerful approach to identify differentially expressed gene sets with prior biological knowledge. Several GSEA algorithms have been proposed to perform enrichment analyses on groups of genes. However, many of these algorithms have focused on identification of differentially expressed gene sets in a given phenotype. Objective: In this paper, we propose a gene set analytic framework, Gene Set Correlation Analysis (GSCoA), that simultaneously measures within and between gene sets variation to identify sets of genes enriched for differential expression and highly co-related pathways. Methods: We apply co-inertia analysis to the comparisons of cross-gene sets in gene expression data to measure the costructure of expression profiles in pairs of gene sets. Co-inertia analysis (CIA) is one multivariate method to identify trends or co-relationships in multiple datasets, which contain the same samples. The objective of CIA is to seek ordinations (dimension reduction diagrams) of two gene sets such that the square covariance between the projections of the gene sets on successive axes is maximized. Simulation studies illustrate that CIA offers superior performance in identifying corelationships between gene sets in all simulation settings when compared to correlation-based gene set methods. Result and Conclusion: We also combine between-gene set CIA and GSEA to discover the relationships between gene sets significantly associated with phenotypes. In addition, we provide a graphical technique for visualizing and simultaneously exploring the associations of between and within gene sets and their interaction and network. We then demonstrate integration of within and between gene sets variation using CIA and GSEA, applied to the p53 gene expression data using the c2 curated gene sets. Ultimately, the GSCoA approach provides an attractive tool for identification and visualization of novel associations between pairs of gene sets by integrating co-relationships between gene sets into gene set analysis.

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Integrated Insight into the Molecular Mechanisms of Spontaneous Abortion during Early Pregnancy in Pigs

International Journal of Molecular Sciences ◽

10.3390/ijms22126644 ◽

2021 ◽

Vol 22 (12) ◽

pp. 6644

Author(s):

Xupeng Zang ◽

Ting Gu ◽

Wenjing Wang ◽

Chen Zhou ◽

Yue Ding ◽

...

Keyword(s):

Immune Response ◽

Spontaneous Abortion ◽

Molecular Mechanisms ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Gene Set ◽

Cerna Network ◽

Major Interest ◽

End Stage ◽

Insight Into

Due to the high rate of spontaneous abortion (SAB) in porcine pregnancy, there is a major interest and concern on commercial pig farming worldwide. Whereas the perturbed immune response at the maternal–fetal interface is an important mechanism associated with the spontaneous embryo loss in the early stages of implantation in porcine, data on the specific regulatory mechanism of the SAB at the end stage of the implantation remains scant. Therefore, we used high-throughput sequencing and bioinformatics tools to analyze the healthy and arresting endometrium on day 28 of pregnancy. We identified 639 differentially expressed lncRNAs (DELs) and 2357 differentially expressed genes (DEGs) at the end stage of implantation, and qRT-PCR was used to verify the sequencing data. Gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and immunohistochemistry analysis demonstrated weaker immune response activities in the arresting endometrium compared to the healthy one. Using the lasso regression analysis, we screened the DELs and constructed an immunological competitive endogenous RNA (ceRNA) network related to SAB, including 4 lncRNAs, 11 miRNAs, and 13 genes. In addition, Blast analysis showed the applicability of the constructed ceRNA network in different species, and subsequently determined HOXA-AS2 in pigs. Our study, for the first time, demonstrated that the SAB events at the end stages of implantation is associated with the regulation of immunobiological processes, and a specific molecular regulatory network was obtained. These novel findings may provide new insight into the possibility of increasing the litter size of sows, making pig breeding better and thus improving the efficiency of animal husbandry production.

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Transcriptional survey of alveolar macrophages in a murine model of chronic granulomatous inflammation reveals common themes with human sarcoidosis

AJP Lung Cellular and Molecular Physiology ◽

10.1152/ajplung.00289.2017 ◽

2018 ◽

Vol 314 (4) ◽

pp. L617-L625 ◽

Cited By ~ 8

Author(s):

Arjun Mohan ◽

Anagha Malur ◽

Matthew McPeek ◽

Barbara P. Barna ◽

Lynn M. Schnapp ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Murine Model ◽

Alveolar Macrophages ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Multiwall Carbon Nanotube ◽

Gene Set Enrichment ◽

Integrated Network ◽

Gene Set ◽

Gene Sets

To advance our understanding of the pathobiology of sarcoidosis, we developed a multiwall carbon nanotube (MWCNT)-based murine model that shows marked histological and inflammatory signal similarities to this disease. In this study, we compared the alveolar macrophage transcriptional signatures of our animal model with human sarcoidosis to identify overlapping molecular programs. Whole genome microarrays were used to assess gene expression of alveolar macrophages in six MWCNT-exposed and six control animals. The results were compared with the transcriptional profiles of alveolar immune cells in 15 sarcoidosis patients and 12 healthy humans. Rigorous statistical methods were used to identify differentially expressed genes. To better elucidate activated pathways, integrated network and gene set enrichment analysis (GSEA) was performed. We identified over 1,000 differentially expressed between control and MWCNT mice. Gene ontology functional analysis showed overrepresentation of processes primarily involved in immunity and inflammation in MCWNT mice. Applying GSEA to both mouse and human samples revealed upregulation of 92 gene sets in MWCNT mice and 142 gene sets in sarcoidosis patients. Commonly activated pathways in both MWCNT mice and sarcoidosis included adaptive immunity, T-cell signaling, IL-12/IL-17 signaling, and oxidative phosphorylation. Differences in gene set enrichment between MWCNT mice and sarcoidosis patients were also observed. We applied network analysis to differentially expressed genes common between the MWCNT model and sarcoidosis to identify key drivers of disease. In conclusion, an integrated network and transcriptomics approach revealed substantial functional similarities between a murine model and human sarcoidosis particularly with respect to activation of immune-specific pathways.

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Hsa_circ_0004831 serves as a blood-based prognostic biomarker for colorectal cancer and its potentially circRNA-miRNA-mRNA regulatory network construction

10.21203/rs.3.rs-55340/v3 ◽

2020 ◽

Author(s):

Linlin Xing ◽

Mengyan Xia ◽

Xin Jiao ◽

Ling Fan

Keyword(s):

Colorectal Cancer ◽

Extracellular Vesicles ◽

Regulatory Network ◽

Prognostic Biomarker ◽

Qpcr Assay ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Expression Level ◽

Blood Samples ◽

Tumorigenesis And Progression

Abstract Background: Colorectal cancer (CRC) is a common malignant tumor with unsatisfactory overall prognosis. CircRNAs could be promising prognostic biomarkers in cancers, and play important role in the process of tumorigenesis and progression. Here, we explored the role of hsa_circ_0004831 in blood extracellular vesicles and its prognostic value in CRC. Methods: The circRNA and mRNA expression level matrix in extracellular vesicles of CRC and normal samples were obtained from the exoRBase database. The corresponding miRNA expression level matrix in extracellular vesicles was downloaded from the BBCancer database. Differentially expressed circRNAs, miRNAs and mRNAs were identified using the limma package of R software at the cut-off criteria of fold change (FC) > 2 and adj. p < 0.05. RT-qPCR assay was conducted to measure hsa_circ_0004831 expression level in CRC blood samples. A circRNA-miRNA-mRNA regulatory network of hsa_circ_0004831 was constructed based on competitive endogenous RNA mechanism and differentially expressed genes. The mRNAs co-expressed with hsa_circ_0004831 were screened at the cut-off criteria of pearson |r| > 0.3 and p < 0.05. Gene set enrichment analysis (GSEA) based on co-expressed mRNAs was used to explore the potential molecular function of hsa_circ_0004831. Results: Differentially expressed circRNAs, miRNAs and mRNAs were identified and hsa_circ_0004831 had a FC value of 3.92 in CRC blood extracellular vesicles. The RT-qPCR assay showed that the hsa_circ_0004831 was up-regulated in CRC blood samples. The overall survival analysis found that high expression of hsa_circ_0004831 was linked with poorer prognosis. Finally, a circRNA-miRNA-mRNA regulatory network of hsa_circ_0004831 was constructed based on down-regulated miR-4326 and 12 up-regulated mRNAs. GSEA indicated that mRNAs co-expressed with hsa_circ_0004831 were involved in EMT, WNT and p53 signaling pathways.Conclusions: The study confirmed the up-regulation of hsa_circ_0004831 in CRC, and it may act as a vital prognostic biomarker. The circRNA-miRNA-mRNA regulatory network of hsa_circ_0004831 could be used to uncover the tumorigenesis and progression of CRC.

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Molecular predictors of response to selinexor in advanced unresectable de-differentiated liposarcoma (DDLS).

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.11509 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 11509-11509

Author(s):

Christopher James Walker ◽

Hua Chang ◽

Jianjun Liu ◽

Bruno Vincenzi ◽

Andrea Napolitano ◽

...

Keyword(s):

Rna Sequencing ◽

B Cell Lymphoma ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Tumor Control ◽

Double Blind Study ◽

Sequencing Analysis ◽

Gene Set Enrichment ◽

Gene Set ◽

Validation Set

11509 Background: Patients (pts) with recurrent inoperative DDLS have a poor prognosis and limited treatment options. Selinexor is an oral, selective inhibitor of nuclear export (SINE) compound approved for previously treated pts with myeloma and diffuse large B-cell lymphoma. SEAL was a Phase 2-3 randomized, double-blind, study of selinexor versus placebo in pts with progressive DDLS and 2-5 prior systemic therapies. SEAL showed significantly prolonged progression-free survival (PFS, HR = 0.70, p = 0.0228) with well managed toxicity. A biomarker predictive of clinical activity could be used to optimize selection of pts with DDLS for selinexor. Methods: Pts were randomized 2:1 for Phase 3: 188 received twice weekly selinexor (60mg) and 97 received placebo. Three exploratory biomarker analyses (RNA sequencing of biopsies) from selinexor-treated pts were performed: discovery set of sensitive (n = 8) or resistant (n = 9) tumors; a validation set of pts with favorable (n = 19) or poor (n = 14) tumor control based on PFS, and paired lesions from a pt who harbored both a responsive and resistant lesion. Tumor biopsies from 24 pts on placebo with short ( < 5 months, n = 18) and long ( > 6 months, n = 6) PFS were RNA sequenced. Gene expressions were compared using a negative binomial distribution with DeSeq2. Pathway analyses were performed using Gene Set Enrichment Analysis (GSEA) with MSigDB Cancer Gene Neighborhoods. Results: RNA sequencing analysis comparing 17 sensitive and resistant tumors identified 114 differentially expressed genes (adjusted p-values < 0.05). Expression of CALB1, which encodes the calcium-binding protein calbindin, was significantly lower in sensitive tumors (adjusted P [Padj] = 7.5x10-20), and expression of GRM1, which encodes a metabotropic glutamate receptor that activates phospholipase C, was higher in selinexor sensitive tumors (Padj= 0.003). These findings were confirmed in an independent validation set (Padj = 0.01 – 0.02). In the pt with paired sensitive and resistant lesions, CALB1 expression was 52-fold lower in the sensitive tumor. In a comparison of placebo-treated pts, neither CALB1 or GRM1 was differentially expressed between pts with short or long PFS, indicating they are markers of response to selinexor treatment, rather than general markers of disease aggressiveness. Gene set enrichment analyses revealed that selinexor sensitive tumors in the discovery and validation sets showed upregulation of cancer genes related to SNRK and the netrin 1 receptor tumor suppressor DCC. The resistant tumors showed upregulated EIF3S2 translation initiator-related genes. Conclusions: Selinexor sensitive DDLS tumors showed low expression of CALB1 and high GRM1. If validated, pts with DDLS whose tumors match this expression profile are especially likely to benefit from selinexor. Clinical trial information: NCT02606461.

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The prognostic role of tissue TLR2 and TLR4 in colorectal cancer

Virchows Archiv ◽

10.1007/s00428-020-02833-5 ◽

2020 ◽

Vol 477 (5) ◽

pp. 705-715

Author(s):

Ines Beilmann-Lehtonen ◽

Camilla Böckelman ◽

Harri Mustonen ◽

Selja Koskensalo ◽

Jaana Hagström ◽

...

Keyword(s):

Colorectal Cancer ◽

Prognostic Factor ◽

Distant Metastases ◽

University Hospital ◽

Rank Test ◽

Pathogen Invasion ◽

Kaplan Meier ◽

Node Positive Disease ◽

Colorectal Cancer Patients ◽

Dukes C

Abstract Colorectal cancer (CRC), the second most common cancer globally, resulted in 881,000 deaths in 2018. Toll-like receptors (TLRs) are crucial to detecting pathogen invasion and inducing the host’s immune response. This study aimed to explore the prognostic value of TLR2 and TLR4 tumor expressions in colorectal cancer patients. We studied the immunohistochemical expressions of TLR2 and TLR4 using tissue microarray specimens from 825 patients undergoing surgery in the Department of Surgery, Helsinki University Hospital, between 1982 and 2002. We assessed the relationships between TLR2 and TLR4 expressions and clinicopathological variables and patient survival. We generated survival curves using the Kaplan-Meier method, determining significance with the log-rank test. Among patients with lymph node–positive disease and no distant metastases (Dukes C), a strong TLR2 immunoactivity associated with a better prognosis (p < 0.001). Among patients with local Dukes B disease, a strong TLR4 immunoactivity associated with a worse disease-specific survival (DSS; p = 0.017). In the multivariate survival analysis, moderate TLR4 immunoactivity compared with strong TLR4 immunoactivity (hazard ratio (HR) 0.66, 95% confidence interval (CI) 0.49–0.89, p = 0.007) served as an independent prognostic factor. In the multivariate analysis for the Dukes subgroups, moderate TLR2 immunoactivity (HR 2.63, 95% CI 1.56–4.44, p < 0.001) compared with strong TLR2 immunoactivity served as an independent negative prognostic factor in the Dukes C subgroup. TLR2 and TLR4 might be new prognostic factors to indicate which CRC patients require adjuvant therapy and which could spare from an unnecessary follow-up, but further investigations are needed.

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Blood and Brain Transcriptome Analysis Reveals APOE Genotype-mediated and Immune-related Pathways Involved in Alzheimer Disease

10.21203/rs.3.rs-892590/v1 ◽

2021 ◽

Author(s):

Rebecca Panitch ◽

Junming Hu ◽

Weiming Xia ◽

David A Bennett ◽

Thor D Stein ◽

...

Keyword(s):

Alzheimer Disease ◽

Blood Brain Barrier ◽

Vascular Injury ◽

Apoe Genotype ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Brain Barrier ◽

Gene Set Enrichment ◽

Gene Set

Abstract Background: While Alzheimer disease (AD) is generally considered as a brain disorder, blood biomarkers may be useful for diagnosis and prediction of AD brain pathology. The APOE ε4 allele has shown cerebrovascular effects including acceleration of blood brain barrier breakdown. Methods: We evaluated differential expression of previously established AD genes in brains from 344 pathologically confirmed AD cases and 232 controls and in blood from 112 pathologically confirmed AD cases and 67 controls from the Religious Orders Study and Memory and Aging Project. Differential gene expression between AD cases and controls was analyzed in the blood and brain jointly using a multivariate approach in the total sample and within APOE genotype groups. Gene set enrichment analysis was performed within APOE genotype groups using the results from the combined blood and brain analyses to identify biologically important pathways. Gene co-expression networks in brain and blood samples were investigated using weighted correlation network analysis. Top ranked genes from networks and pathways were further evaluated with vascular injury traits. Results: We observed differentially expressed genes with P<0.05 in both brain and blood for established AD genes INPP5D (upregulated) and HLA-DQA1 (downregulated). PIGHP1 and FRAS1 were differentially expressed at the transcriptome-wide level (P<3.3x10 -6 ) within ε2/ε3 and ε3/ε4 groups, respectively. Gene-set enrichment analysis revealed 21 significant pathways (false discovery rate P<0.05) in at least one APOE genotype group. Ten pathways were significantly enriched in the ε3/ε4 group, and six of these were unique to these subjects. Four pathways were enriched for AD upregulated genes in the ε3/ε4 group and AD downregulated genes in ε4 lacking subjects. We identified a co-expressed gene network in brain that reproduced in blood and showed higher average expression in ε4 carriers. Twenty-three genes from pathway and network analyses were significantly associated at P<0.05 with at least one vascular injury trait. Conclusion: These results suggest that APOE genotype contributes to unique expression network profiles in both blood and brain. Several genes in these networks are associated with measures of vascular injury and potentially contribute to ε4’s effect on the blood brain barrier.

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Identification of Cell cycle Gene Signatures Predicting Survival in Patients with Lung Squamous Cell Carcinoma

10.21203/rs.2.17290/v1 ◽

2019 ◽

Author(s):

Lei Zhang ◽

Zhe Zhang ◽

Zhenglun Yu

Keyword(s):

Cell Cycle ◽

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Lung Squamous Cell Carcinoma ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

Test Series ◽

Gene Signatures ◽

Gene Set

Abstract Background:Lung cancer (LC) is one of the most important and common malignant tumors, and its incidence and mortality are increasing annually. Lung squamous cell carcinoma (LUSC) is the common pathological type of lung cancer. A small part of biomarkers have been confirmed to be related to the prognosis and survival by data excavation. However, the moderate forecast effect of a single gene biomarker is not accurate. Thus, we aimed to identify new gene signatures to better predict Lung squamous cell carcinoma ( LU SC). Methods : Using the mRNA-mining approach, we performed mRNA expression profiling in large lung squamous cell carcinoma cohorts (n= from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis(GSVA) were accomplished, and connections between genes and cell cycle were found in the Cox proportional regression model. Results : We have confirmed a set of four genes (CDKN1A, CHEK2, E2F4 and RAD21) that were importantly associated with overall survival (OS) in the test series. Based on the research of the four-gene signature, the patients in the test series could be divided into high-risk and low-risk teams. Additionally, multivariate Cox regression analysis revealed that the prognostic power of the four-gene signature is independent of the clinical factors. Conclusion : Our study demonstrated the connections between the four-gene signature and cell cycle. Novel insights into the research mechanisms of cell cycle was also revealed regarding the biomarkers of a poor prognosis for lung squamous cell carcinoma patients.

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