The Identification of Prognostic and Metastatic Alternative Splicing in Skin Cutaneous Melanoma

Skin cutaneous melanoma (SKCM) is a type of highly invasive cancer originated from melanocytes. It is reported that aberrant alternative splicing (AS) plays an important role in the neoplasia and metastasis of many types of cancer. Therefore, we investigated whether ASEs of pre-RNA have such an influence on the prognosis of SKCM and the related mechanism of ASEs in SKCM. The RNA-seq data and ASEs data for SKCM patients were obtained from the TCGA and TCGASpliceSeq database. The univariate Cox regression revealed 1265 overall survival-related splicing events (OS-SEs). Screened by Lasso regression, 4 OS-SEs were identified and used to construct an effective prediction model (AUC: .904), whose risk score was proved to be an independent prognostic factor. Furthermore, Kruskal–Wallis test and Mann–Whitney–Wilcoxon test showed that an aberrant splicing type of aminoacyl tRNA synthetase complex-interacting multifunctional protein 2 (AIMP2) regulated by CDC-like kinase 1 (CLK1) was associated with the metastasis and stage of SKCM. Besides, the overlapped signal pathway for AIMP2 was galactose metabolism identified by the co-expression analysis. External database validation also confirmed that AIMP2, CLK1, and the galactose metabolism were associated with the metastasis and stage of SKCM patients. ChIP-seq and ATAC-seq methods further confirmed the transcription regulation of CLK1, AIMP2, and other key genes, whose cellular expression was detected by Single Cell Sequencing. In conclusion, we proposed that CLK1-regulated AIMP2-78704-ES might play a critical role in the tumorigenesis and metastasis of SKCM via galactose metabolism. Besides, we established an effective model with MTMR14-63114-ES, URI1-48867-ES, BATF2-16724-AP, and MED22-88025-AP to predict the metastasis and prognosis of SKCM patients.

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Molecular Characterization and Clinical Relevance of m6A RNA Methylation Regulators in Cervical Cancer

10.21203/rs.3.rs-113477/v1 ◽

2020 ◽

Author(s):

Jin Chen ◽

Ji He ◽

Xiaolei Ma ◽

Xia Guo

Keyword(s):

Cervical Cancer ◽

Clinical Relevance ◽

Cox Regression ◽

Critical Role ◽

The Cancer Genome Atlas ◽

Rna Modification ◽

Lasso Regression ◽

Cox Regression Analysis ◽

Rna Methylation ◽

M6a Rna Methylation

Abstract Background: RNA modification, such as methylation of N6 adenosine (m6A), plays a critical role in many biological processes. However, the role of m6A RNA modification in cervical cancer (CC) remains largely unknown. Methods: The present study systematically investigated the molecular signatures and clinical relevance of 20 m6A RNA methylation regulators (writers, erasers, readers) in CC. The mRNA expression and clinical significance of m6A-related genes were investigated using data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cervical cancer cohort. Mutations, copy number variation (CNV), differential expression, gene ontology analysis and the construction of a mRNA-microRNA regulatory network were performed to investigate the underlying mechanisms involved in the abnormal expression of m6A-related genes. Results: We found inclusive genetic information alterations among the m6A regulators and that their transcript expression levels were significantly associated with cancer hallmark-related pathways activity, such as the PI3K-AKT signaling pathway, microRNAs in cancer and the focal adhesion pathway, which were significantly enriched. Moreover, m6A regulators were found to be potentially useful for prognostic stratification and we identified FMR1 and ZC3H13 as potential prognostic risk oncogenes by LASSO regression. The ROC curves of 3, 5 and 10 years were 0.685, 0.726 and 0.741, respectively. The specificity for 3, 5 and 10 years were 0.598, 0.631 and 0.833, the sensitivity were 0.707, 0.752 and 0.811, respectively. Conclusions: Multivariable Cox regression analysis revealed that the risk score is an independent prognostic marker and can be used to predict the clinical and pathological features of CC.

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Large-Scale Transcriptome Analysis Identified Novel Ferroptosis-Related Gene Signatures for Predicting the Prognostic of Patients with Lung Adenocarcinoma

10.21203/rs.3.rs-49010/v1 ◽

2020 ◽

Author(s):

Lei Sun ◽

Jia Gu ◽

Wenke Liu ◽

Zhe Zhang ◽

Yao Yao ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Risk Score ◽

Cox Regression ◽

Risk Group ◽

Tumor Staging ◽

Critical Role ◽

The Cancer Genome Atlas ◽

Wilcoxon Test ◽

Glutathione Depletion ◽

The Impact

Abstract Background: Lung cancer is the most common of all malignant tumors. Traditional tumor staging has general sensitivity and specificity in predicting patient prognosis. Ferroptosis is a novel form of non-apoptotic form of cell death promoted by lipid peroxidation. Ferroptosis may be involved in the malignant progression of tumors through the regulation of glutathione depletion or the P53 signaling pathway. However, there are fewer studies on the impact of ferroptosis on tumor prognosis.Methods: We summarized 22 molecules that regulate ferroptosis. The transcriptome and corresponding clinical data were obtained from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The Wilcoxon test was utilized to analyze the expression of ferroptosis-related genes. We established risk score signatures, and all patients divided into two groups. Survival curves and multifactorial Cox regression analyses were performed to explore the prognostic value of ferroptosis on lung adenocarcinoma (LUAD).Results: We found that most ferroptosis-related genes are specifically expressed in LUAD tissue. We established a six‑mRNA signature and a seven‑IncRNA signature. All the models showed high predictive performance (AUC: 0.66–0.8), and patients in the low-risk group had higher overall survival than those in the high-risk group (P<0.05). The risk score is an independent risk factor for predicting the prognosis of LUAD.Conclusions: Our study demonstrates the critical role of ferroptosis in LUAD, and it is expected to supply a reference for the prognostic stratification of LUAD.

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The Identification and Validation of a Robust Immune-Associated Gene Signature in Cutaneous Melanoma

Journal of Immunology Research ◽

10.1155/2021/6686284 ◽

2021 ◽

Vol 2021 ◽

pp. 1-14

Author(s):

Le-Bin Song ◽

Jiao-Chen Luan ◽

Qi-Jie Zhang ◽

Lin Chen ◽

Hao-Yang Wang ◽

...

Keyword(s):

Regression Analysis ◽

Survival Analysis ◽

Cutaneous Melanoma ◽

Cox Regression ◽

Risk Group ◽

Cox Model ◽

Critical Role ◽

Gene Signature ◽

Low Risk ◽

Cox Regression Analysis

Background. Cutaneous melanoma is defined as one of the most aggressive skin tumors in the world. An increasing body of evidence suggested an indispensable association between immune-associated gene (IAG) signature and melanoma. This article is aimed at formulating an IAG signature to estimate prognosis of melanoma. Methods. 434 melanoma patients were extracted from The Cancer Genome Atlas (TCGA) database, and 1811 IAGs were downloaded from the ImmPort database in our retrospective study. The Cox regression analysis and LASSO regression analysis were utilized to establish a prognostic IAG signature. The Kaplan-Meier (KM) survival analysis was performed, and the time-dependent receiver operating characteristic curve (ROC) analysis was further applied to assess the predictive value. Besides, the propensity score algorithm was utilized to balance the confounding clinical factors between the high- and low-risk groups. Results. A total of six prognostic IAGs comprising of INHA, NDRG1, IFITM1, LHB, GBP2, and CCL8 were eventually filtered out. According to the KM survival analysis, the results displayed a shorter overall survival (OS) in the high-risk group compared to the low-risk group. In the multivariate Cox model, the gene signature was testified as a remarkable prognostic factor ( HR = 45.423 , P < 0.001 ). Additionally, the ROC curve analyses were performed which demonstrated our IAG signature was superior to four known biomarkers mentioned in the study. Moreover, the IAG signature was significantly related to immunotherapy-related biomarkers. Conclusion. Our study demonstrated that the six IAG signature played a critical role in the prognosis and immunotherapy of melanoma, which might help clinicians predict patients’ survival and provide individualized treatment.

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Identification of Genes Related to Immune Infiltration in the Tumor Microenvironment of Cutaneous Melanoma

Frontiers in Oncology ◽

10.3389/fonc.2021.615963 ◽

2021 ◽

Vol 11 ◽

Author(s):

Rujia Qin ◽

Wen Peng ◽

Xuemin Wang ◽

Chunyan Li ◽

Yan Xi ◽

...

Keyword(s):

Regression Analysis ◽

Tumor Microenvironment ◽

Cutaneous Melanoma ◽

Cox Regression ◽

The Cancer Genome Atlas ◽

Training Dataset ◽

Lasso Regression ◽

Hub Genes ◽

Dynamic Regulation ◽

Cox Regression Analysis

Cutaneous melanoma (CM) is the leading cause of skin cancer deaths and is typically diagnosed at an advanced stage, resulting in a poor prognosis. The tumor microenvironment (TME) plays a significant role in tumorigenesis and CM progression, but the dynamic regulation of immune and stromal components is not yet fully understood. In the present study, we quantified the ratio between immune and stromal components and the proportion of tumor-infiltrating immune cells (TICs), based on the ESTIMATE and CIBERSORT computational methods, in 471 cases of skin CM (SKCM) obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were analyzed by univariate Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis to identify prognosis-related genes. The developed prognosis model contains ten genes, which are all vital for patient prognosis. The areas under the curve (AUC) values for the developed prognostic model at 1, 3, 5, and 10 years were 0.832, 0.831, 0.880, and 0.857 in the training dataset, respectively. The GSE54467 dataset was used as a validation set to determine the predictive ability of the prognostic signature. Protein–protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA) were used to verify “real” hub genes closely related to the TME. These hub genes were verified for differential expression by immunohistochemistry (IHC) analyses. In conclusion, this study might provide potential diagnostic and prognostic biomarkers for CM.

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Ferroptosis-Associated Classifier and Indicator for Prognostic Prediction in Cutaneous Melanoma

Journal of Oncology ◽

10.1155/2021/3658196 ◽

2021 ◽

Vol 2021 ◽

pp. 1-16

Author(s):

Hao Zeng ◽

Cong You ◽

Leran Zhao ◽

Jiangyi Wang ◽

Xiaoying Ye ◽

...

Keyword(s):

Cutaneous Melanoma ◽

Cox Regression ◽

Critical Role ◽

Principal Component ◽

Good Prognosis ◽

Differentially Expressed ◽

Prognostic Impact ◽

Chemotherapy Drugs ◽

Melanoma Patients ◽

Prognostic Prediction

Ferroptosis plays a critical role in different types of cancers, but the prognostic impact of ferroptosis in cutaneous melanoma remains lacking. Therefore, ferroptosis-related genes (FRGs) were firstly obtained from the FerrDb database and the differentially expressed FRGs were identified by the “limma” algorithm. Next, the prognostic differentially expressed FRGs were screened out by univariate Cox regression, which were subsequently used to cluster melanomas into two subtypes (clusters A and B). Besides, the Boruta algorithm and principal component analysis (PCA) were performed to build a 15-FRGs indicator, which can robustly predict patients’ overall survival (OS) and be considered as an independent prognostic factor in melanoma. The melanoma patients were further divided into high- and low-FRGs score groups. The high score group have a good prognosis, with higher T cell immune infiltrating and lower mutation frequencies in NRAS, KRAS, and NF1. Finally, we discovered that many immune processes and several chemotherapy drugs were closely associated with FRGs score. Thus, our study provides a novel ferroptosis-associated classifier and indicator to predict the prognosis of melanoma. Besides, we identified several potential chemotherapy drugs to induce ferroptosis and could supply additional effective treatments.

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Genetic and Epigenetic landscape of leukocyte infiltration identifies an immune prognosticator in lung adenocarcinoma

Cancer Biomarkers ◽

10.3233/cbm-203071 ◽

2021 ◽

pp. 1-13

Author(s):

Seema Khadirnaikar ◽

Annesha Chatterjee ◽

Sudhanshu Kumar Shukla

Keyword(s):

Lung Adenocarcinoma ◽

Immune Cell ◽

Cox Regression ◽

Strong Association ◽

Critical Role ◽

Significant Proportion ◽

Immune Gene ◽

Leukocyte Infiltration ◽

Clinical Genetic ◽

Factors Affecting

BACKGROUND: Leukocyte infiltration plays an critical role in outcome of various diseases including Lung adenocarcinoma (LUAD). OBJECTIVES: To understand the genetic and epigenetic factors affecting leukocyte infiltration and identification and validation of immune based biomarkers. METHOD: Correlation analysis was done to get the associations of the factors. CIBERSORT analysis was done for immune cell infiltration. Genetic and epigenetic analysis were performed. Cox regression was carried out for survival. RESULTS: We categorized the TCGA-LUAD patients based on Leukocyte fraction (LF) and performed extensive immunogenomic analysis. Interestingly, we showed that LF has a negative correlation with copy number variation (CNV) but not with mutational load. However, several individual genetic mutations, including KRAS and KEAP1, were significantly linked with LF. Also, as expected, patients with high LF showed significantly increased expression of genes involved in leukocyte migration and activation. DNA methylation changes also showed a strong association with LF and regulated a significant proportion of genes associated with LF. We also developed and validated an independent prognostic immune signature using the top six prognostic genes associated with LF. CONCLUSION: Together, we have identified clinical, genetic, and epigenetic variations associated with LUAD LF and developed an immune gene-based signature for disease prognostication.

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Identification of prognostic alternative splicing events in sarcoma

Scientific Reports ◽

10.1038/s41598-021-94485-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hongshuai Li ◽

Jie Yang ◽

Guohui Yang ◽

Jia Ren ◽

Yu Meng ◽

...

Keyword(s):

Alternative Splicing ◽

Cox Regression ◽

Univariate Analysis ◽

Area Under The Curve ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Cox Regression Analysis ◽

Functional Roles ◽

Cancer Pathogenesis ◽

Rare Malignancy

AbstractSarcoma is a rare malignancy with unfavorable prognoses. Accumulating evidence indicates that aberrant alternative splicing (AS) events are generally involved in cancer pathogenesis. The aim of this study was to identify the prognostic value of AS-related survival genes as potential biomarkers, and highlight the functional roles of AS events in sarcoma. RNA-sequencing and AS-event datasets were downloaded from The Cancer Genome Atlas (TCGA) sarcoma cohort and TCGA SpliceSeq, respectively. Survival-related AS events were further assessed using a univariate analysis. A multivariate Cox regression analysis was also performed to establish a survival-gene signature to predict patient survival, and the area-under-the-curve method was used to evaluate prognostic reliability. KOBAS 3.0 and Cytoscape were used to functionally annotate AS-related genes and to assess their network interactions. We detected 9674 AS events in 40,184 genes from 236 sarcoma samples, and the 15 most significant genes were then used to construct a survival regression model. We further validated the involvement of ten potential survival-related genes (TUBB3, TRIM69, ZNFX1, VAV1, KCNN2, VGLL3, AK7, ARMC4, LRRC1, and CRIP1) in the occurrence and development of sarcoma. Multivariate survival model analyses were also performed, and validated that a model using these ten genes provided good classifications for predicting patient outcomes. The present study has increased our understanding of AS events in sarcoma, and the gene-based model using AS-related events may serve as a potential predictor to determine the survival of sarcoma patients.

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Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer

BMC Gastroenterology ◽

10.1186/s12876-021-01734-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Sheng Zheng ◽

Zizhen Zhang ◽

Ning Ding ◽

Jiawei Sun ◽

Yifeng Lin ◽

...

Keyword(s):

Gastric Cancer ◽

Overall Survival ◽

High Efficiency ◽

Cox Regression ◽

Risk Group ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Lasso Regression ◽

Sequencing Data ◽

Cox Regression Analysis

Abstract Introduction Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC). Methods mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively. Results Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan–Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. Conclusions We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It’s assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy.

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Upregulation of Serum lncRNA DLEU1 Predicts Progression of Premalignant Endometrial Lesion and Unfavorable Clinical Outcome of Endometrial Cancer

Technology in Cancer Research & Treatment ◽

10.1177/1533033820965589 ◽

2020 ◽

Vol 19 ◽

pp. 153303382096558

Author(s):

Lixia Shan ◽

Tao Zhao ◽

Yu Wang

Keyword(s):

Endometrial Cancer ◽

Endometrial Hyperplasia ◽

Cox Regression ◽

Quantitative Polymerase Chain Reaction ◽

Critical Role ◽

Disease Free Survival ◽

Lymphocytic Leukemia ◽

Healthy Controls ◽

Clinical Value ◽

Cox Regression Analysis

Objective: Long non-coding RNAs (lncRNAs) play a critical role in tumorigenesis. Upregulation of lncRNA deleted in lymphocytic leukemia 1 (DLEU1) has been reported in endometrial cancer (EC) tissues. This prospective study aimed to determine the potential clinical significance of serum lncRNA DLEU1 in EC. Methods: The serum lncRNA DLEU1 level was detected in EC patients, patients with endometrial hyperplasia and healthy controls by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Then its clinical value in EC was further evaluated. Results: Our results demonstrated that serum lncRNA DLEU1 levels were significantly increased in patients with EC, and serum lncRNA DLEU1 showed good performance for discriminating EC patients from patients with endometrial hyperplasia and healthy controls. In addition, EC patients with advanced clinicopathological features had higher circulating lncRNA DLEU1 level than those with favorable clinical characteristics. Moreover, EC patients in the high serum lncRNA DLEU1 group suffered worse overall survival and disease-free survival than those in the low serum lncRNA DLEU1 group. Furthermore, multivariate cox regression analysis displayed that the serum lncRNA DLEU1 served as an independent prognostic factor for EC. Conclusions: Collectively, our study suggests that serum lncRNA DLEU1 is a novel and promising biomarker for prognostic estimation of EC.

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Alternative splicing acts as an independent prognosticator in ovarian carcinoma

Scientific Reports ◽

10.1038/s41598-021-89778-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yan Ouyang ◽

Kaide Xia ◽

Xue Yang ◽

Shichao Zhang ◽

Li Wang ◽

...

Keyword(s):

Ovarian Cancer ◽

Regression Analysis ◽

Alternative Splicing ◽

Ovarian Carcinoma ◽

Cancer Patients ◽

Cox Regression ◽

Excision Repair ◽

Splicing Factors ◽

Prognostic Signature ◽

Cox Regression Analysis

AbstractAlternative splicing (AS) events associated with oncogenic processes present anomalous perturbations in many cancers, including ovarian carcinoma. There are no reliable features to predict survival outcomes for ovarian cancer patients. In this study, comprehensive profiling of AS events was conducted by integrating AS data and clinical information of ovarian serous cystadenocarcinoma (OV). Survival-related AS events were identified by Univariate Cox regression analysis. Then, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to construct the prognostic signatures within each AS type. Furthermore, we established a splicing-related network to reveal the potential regulatory mechanisms between splicing factors and candidate AS events. A total of 730 AS events were identified as survival-associated splicing events, and the final prognostic signature based on all seven types of AS events could serve as an independent prognostic indicator and had powerful efficiency in distinguishing patient outcomes. In addition, survival-related AS events might be involved in tumor-related pathways including base excision repair and pyrimidine metabolism pathways, and some splicing factors might be correlated with prognosis-related AS events, including SPEN, SF3B5, RNPC3, LUC7L3, SRSF11 and PRPF38B. Our study constructs an independent prognostic signature for predicting ovarian cancer patients’ survival outcome and contributes to elucidating the underlying mechanism of AS in tumor development.

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