The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment

AbstractLung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.

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The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment

10.21203/rs.3.rs-960327/v1 ◽

2021 ◽

Author(s):

Wensheng Qiu

Keyword(s):

Alternative Splicing ◽

Lung Adenocarcinoma ◽

Immune Cells ◽

Risk Group ◽

Progression Free Survival ◽

High Risk Group ◽

Free Survival ◽

Normal Tissues ◽

Tumor Tissues ◽

Score Model

Abstract Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from the TCGA database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS, but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.

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The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment

10.21203/rs.3.rs-960327/v2 ◽

2021 ◽

Author(s):

Gongjun Wang ◽

Wensheng Qiu

Keyword(s):

Alternative Splicing ◽

Lung Adenocarcinoma ◽

Immune Cells ◽

Risk Group ◽

Progression Free Survival ◽

High Risk Group ◽

Free Survival ◽

Normal Tissues ◽

Tumor Tissues ◽

Score Model

Abstract Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from the TCGA database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS, but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.

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Identification of prognostic hypoxia-related genes signature on the tumor microenvironment in esophageal cancer

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2021384 ◽

2021 ◽

Vol 18 (6) ◽

pp. 7743-7758

Author(s):

Linlin Tan ◽

◽

Dingzhuo Cheng ◽

Jianbo Wen ◽

Kefeng Huang ◽

...

Keyword(s):

Esophageal Cancer ◽

High Risk ◽

Immune Cells ◽

Immune Cell ◽

Risk Group ◽

Roc Curves ◽

Risk Groups ◽

High Risk Group ◽

The Cancer Genome Atlas ◽

Cancer Genome Atlas

<abstract> <sec><title>Background</title>Hypoxia is a crucial factor in the development of esophageal cancer. The relationship between hypoxia and immune status in the esophageal cancer microenvironment is becoming increasingly important in clinical practice. This study aims to clarify and investigate the possible connection between immunotherapy and hypoxia in esophageal cancer. </sec> <sec><title>Methods</title>The Cancer Genome Atlas databases are used to find two types of esophageal cancer cases. Cox regressions analyses are used to screen genes for hypoxia-related traits. After that, the genetic signature is validated by survival analysis and the construction of ROC curves. GSEA is used to compare differences in enrichment in the two groups and is followed by the CIBERSORT tool to investigate a potentially relevant correlation between immune cells and gene signatures. </sec> <sec><title>Results</title>We found that the esophageal adenocarcinoma hypoxia model contains 3 genes (PGK1, PGM1, SLC2A3), and the esophageal squamous cell carcinoma hypoxia model contains 2 genes (EGFR, ATF3). The findings demonstrated that the survival rate of patients in the high-risk group is lower than in the lower-risk group. Furthermore, we find that three kinds of immune cells (memory activated CD4+ T cells, activated mast cells, and M2 macrophages) have a marked infiltration in the tissues of patients in the high-risk group. Moreover, we find that PD-L1 and CD244 are highly expressed in high-risk groups. </sec> <sec><title>Conclusions</title>Our data demonstrate that oxygen deprivation is correlated with prognosis and the incidence of immune cell infiltration in patients with both types of esophageal cancer, which provides an immunological perspective for the development of personalized therapy. </sec> </abstract>

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Identification of novel alternative splicing isoform biomarkers and their association with overall survival in colorectal cancer

10.21203/rs.2.10736/v2 ◽

2019 ◽

Author(s):

Hongtao Jia ◽

Aili Wang ◽

Haifeng Lian ◽

Yuanyuan Shen ◽

Qian Wang ◽

...

Keyword(s):

Colorectal Cancer ◽

Overall Survival ◽

Alternative Splicing ◽

Cancer Biology ◽

The Cancer Genome Atlas ◽

Normal Tissues ◽

Eukaryotic Gene ◽

Cancer Genome Atlas ◽

Alternative Splicing Events ◽

Therapeutic Tools

Abstract Alternative splicing is an important mechanism of regulating eukaryotic gene expression. Understanding the most common alternative splicing events in colorectal cancer (CRC) will help developing diagnostic, prognostic or therapeutic tools in CRC. Publicly available RNA-seq data of 31 pairs of CRC and normal tissues and 18 pairs of metastatic and normal tissues were used to identify alternative splicing events using PSI and DEXSeq methods. The highly significant splicing events were used to search a database of The Cancer Genome Atlas (TCGA). We identified alternative splicing events in 10 genes marking the signature of CRC (more inclusion of CLK1-E4, COL6A3-E6, CD44v8-10, alternative first exon regulation of ARHGEF9, CHEK1, HKDC1 and HNF4A) or metastasis (decrease of SERPINA1-E1a, CALD-E5b, E6 and FBLN2-E9). Except for CHEK1, all other 9 splicing events were confirmed by TCGA data with 382 CRC tumors and 52 normal controls. Two splicing events (COL6A3 and HKDC1) were found to be significantly associated with patient overall survival. The alternative splicing signatures of the 10 genes are highly consistent with previous reports and/or relevant to cancer biology. The significant association of higher expression of the COL6A3 E5-E6 junction and HKDC1 E1-E2 with better overall survival was firstly reported. This study might be of significant value in the future biomarker, prognosis marker and therapeutics development of CRC.

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Identification of novel alternative splicing isoform biomarkers and their association with overall survival in colorectal cancer

10.21203/rs.2.10736/v3 ◽

2019 ◽

Author(s):

Haifeng Lian ◽

Aili Wang ◽

Yuanyuan Shen ◽

Qian Wang ◽

Zhenru Zhou ◽

...

Keyword(s):

Colorectal Cancer ◽

Overall Survival ◽

Alternative Splicing ◽

Cancer Biology ◽

The Cancer Genome Atlas ◽

Normal Tissues ◽

Eukaryotic Gene ◽

Cancer Genome Atlas ◽

Alternative Splicing Events ◽

Therapeutic Tools

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Somatic copy number alteration predicts clinical benefit of lung adenocarcinoma patients treated with cytokine-induced killer plus chemotherapy

Cancer Gene Therapy ◽

10.1038/s41417-021-00422-5 ◽

2022 ◽

Author(s):

Fan Kou ◽

Lei Wu ◽

Ye Zhu ◽

Baihui Li ◽

Ziqi Huang ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Copy Number ◽

Immune Cell ◽

Checkpoint Inhibitors ◽

Progression Free Survival ◽

The Cancer Genome Atlas ◽

Whole Exome ◽

Mutation Burden ◽

Cancer Genome Atlas ◽

Nsclc Patients

AbstractSomatic copy number alterations (SCNA), which are widespread in cancer, can predict the efficacy of immune checkpoint inhibitors in non-small-cell lung cancer (NSCLC). However, the usefulness of SCNA for predicting the survival of patients treated with cytokine-induced killer (CIK) cells or chemotherapy (CT) is unknown. This study aimed to explore the correlation between SCNA and clinical outcome in NSCLC patients treated with CIK + CT or CT alone. We performed whole-exome sequencing on 45 NSCLC patients treated with CIK + CT, as well as 305 NSCLC patients treated with CT alone, from The Cancer Genome Atlas, which showed SCNA had a superiority in predicting the progression-free survival (PFS) over tumor mutation burden (TMB) and SCNA + TMB in NSCLC patients treated with CIK + CT, especially in lung adenocarcinoma, while SCNA could not predict the efficacy of CT alone. Additionally, we investigated the association between SCNA and immune cell infiltration by RNA sequencing and immunohistochemistry. The results revealed that SCNA was negatively associated with the expression of dendritic cells. Collectively, this study revealed a negative correlation between SCNA and response to CIK + CT and showed that SCNA is a predictive indicator in LUAD patients treated with CIK + CT.

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Identification of novel alternative splicing isoform biomarkers and their association with overall survival in colorectal cancer

10.21203/rs.2.10736/v4 ◽

2020 ◽

Author(s):

Haifeng Lian ◽

Aili Wang ◽

Yuanyuan Shen ◽

Qian Wang ◽

Zhenru Zhou ◽

...

Keyword(s):

Colorectal Cancer ◽

Overall Survival ◽

Alternative Splicing ◽

Cancer Biology ◽

The Cancer Genome Atlas ◽

Sample Type ◽

Normal Tissues ◽

Eukaryotic Gene ◽

Cancer Genome Atlas ◽

Therapeutic Tools

Abstract Background: Alternative splicing (AS) is an important mechanism of regulating eukaryotic gene expression. Understanding the most common AS events in colorectal cancer (CRC) will help developing diagnostic, prognostic or therapeutic tools in CRC.Methods: Publicly available RNA-seq data of 28 pairs of CRC and normal tissues and 18 pairs of metastatic and normal tissues were used to identify AS events using PSI and DEXSeq methods. Result: The highly significant splicing events were used to search a database of The Cancer Genome Atlas (TCGA). We identified AS events in 9 genes in CRC (more inclusion of CLK1-E4, COL6A3-E6, CD44v8-10, alternative first exon regulation of ARHGEF9, CHEK1, HKDC1 and HNF4A) or metastasis (decrease of SERPINA1-E1a, CALD-E5b, E6). Except for CHEK1, all other 8 splicing events were confirmed by TCGA data with 382 CRC tumors and 51 normal controls. The combination of three splicing events was used to build a logistic regression model that can predict sample type (CRC or normal) with near perfect performance (AUC=1). Two splicing events (COL6A3 and HKDC1) were found to be significantly associated with patient overall survival. The AS features of the 9 genes are highly consistent with previous reports and/or relevant to cancer biology. Conclusions: The significant association of higher expression of the COL6A3 E5-E6 junction and HKDC1 E1-E2 with better overall survival was firstly reported. This study might be of significant value in the future biomarker, prognosis marker and therapeutics development of CRC.

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Identification of a prognostic signature of nine metabolism-related genes for hepatocellular carcinoma

PeerJ ◽

10.7717/peerj.9774 ◽

2020 ◽

Vol 8 ◽

pp. e9774

Author(s):

Chaozhi Tang ◽

Jiakang Ma ◽

Xiuli Liu ◽

Zhengchun Liu

Keyword(s):

Hepatocellular Carcinoma ◽

Risk Group ◽

Progression Free Survival ◽

High Risk Group ◽

Cancer Genome ◽

Low Risk ◽

The Cancer Genome Atlas ◽

Diagnostic Efficiency ◽

Prognostic Signature ◽

Free Survival

Background Hepatocellular carcinoma (HCC) is the fifth most common cancer. Since changes in liver metabolism contribute to liver disease development, it is necessary to build a metabolism-related prognostic model for HCC. Methods We constructed a metabolism-related-gene (MRG) signature comprising nine genes, which segregated HCC patients into high- and low-risk groups. Results The survival rate (overall survival: OS; relapse-free survival; and progression-free survival) of patients in the low-risk group of The Cancer Genome Atlas (TCGA) cohort was significantly higher than that of patients in the high-risk group. The OS prognostic signature was validated in the International Cancer Genome Consortium independent cohort. The corresponding receiver operating characteristic curves of the model indicated that the signature had good diagnostic efficiency, in terms of improving OS over 1, 3, and 5 years. Hierarchical analysis demonstrated that the MRG signature was significantly associated with better prognosis in male patients, patients aged ≤ 65 years, and patients carrying the wild-type TP53 or CTNNB1 genes. A nomogram was established, and good performance and clinical practicability were confirmed. Additionally, using the GSE109211 dataset from the Gene Expression Omnibus database, we were able to verify that the nine genes in this MRG signature had different responses to sorafenib, suggesting that some of these MRGs may act as therapeutic targets for HCC. Conclusions We believe that these findings will add value in terms of the diagnosis, treatment, and prognosis of HCC.

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Identification of a Metabolism-Related Signature for the Prediction of Survival in Endometrial Cancer Patients

Frontiers in Oncology ◽

10.3389/fonc.2021.630905 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yuan Fan ◽

Xingchen Li ◽

Li Tian ◽

Jianliu Wang

Keyword(s):

Endometrial Cancer ◽

Immune Cells ◽

Risk Group ◽

External Validation ◽

Underlying Mechanism ◽

High Risk Group ◽

Low Risk ◽

The Cancer Genome Atlas ◽

Risk Scores ◽

Lasso Regression

ObjectiveEndometrial cancer (EC) is one of the most common gynecologic malignancies. The present study aims to identify a metabolism-related biosignature for EC and explore the molecular immune-related mechanisms underlying the tumorigenesis of EC.MethodsTranscriptomics and clinical data of EC were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Common differentially expressed metabolism-related genes were extracted and a risk signature was identified by using the least absolute shrinkage and selection operator (LASSO) regression analysis method. A nomogram integrating the prognostic model and the clinicopathological characteristics was established and validated by a cohort of clinical EC patients. Furthermore, the immune and stromal scores were observed and the infiltration of immune cells in EC cells was analyzed.ResultsSix genes, including CA3, HNMT, PHGDH, CD38, PSAT1, and GPI, were selected for the development of the risk prediction model. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better overall survival (OS) (P = 7.874e-05). Then a nomogram was constructed and could accurately predict the OS (AUC = 0.827, 0.821, 0.845 at 3-, 5-, and 7-year of OS). External validation with clinical patients showed that patients with low risk scores had a longer OS (p = 0.04). Immune/stromal scores and infiltrating density of six types of immune cells were lower in high-risk group.ConclusionsIn summary, our work provided six potential metabolism-related biomarkers as well as a nomogram for the prognosis of EC patients, and explored the underlying mechanism involved in the progression of EC.

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Immune cells and signatures characterize tumor microenvironment and predict outcome in ovarian and endometrial cancers

Immunotherapy ◽

10.2217/imt-2021-0052 ◽

2021 ◽

Author(s):

Ying Ni ◽

Ahmed Soliman ◽

Amy Joehlin-Price ◽

Fadi Abdul-Karim ◽

Peter G Rose ◽

...

Keyword(s):

Overall Survival ◽

Endothelial Cells ◽

Immune Cells ◽

Progression Free Survival ◽

The Cancer Genome Atlas ◽

Sequencing Data ◽

Monocytic Cells ◽

Whole Transcriptome Sequencing ◽

Cancer Genome Atlas ◽

Ifn Γ

Aims: We investigated immunogenomic signatures and correlated them with survival in ovarian cancer (OV) and endometrial cancer (EC). Materials & Method: We used whole transcriptome sequencing data from uterine serous cancer and The Cancer Genome Atlas data of OV and EC (n = 719). Gene expression score was calculated. Population abundance of immune cells were estimated. Results: TGF-β, myeloid cells, IFN-γ, T cells, B cells and endothelial cells predicted overall survival. Whereas CD47, neutrophils and endothelial cells predicted progression-free survival. In multivariate analyses, TGF-β, CD47 and monocytic cells predicted survival in high levels of microsatellite instability (MSI-H) EC whereas high IFN-γ trended toward improved survival in the MSI-S EC. High IFN-γ/low TGF-β and high IFN-γ/low CD47 signatures predicted longer overall survival. Low TGF-β/low CD47 signature predicted longer overall survival only in the MSI-H EC. Conclusion: Our data support the role of immune markers in predicting survival in OV/EC.

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