Identification of Survival-Associated Alternative Splicing Signatures in Lung Squamous Cell Carcinoma

Identification of a prognostic gene signature in patients with cisplatin resistant squamous cell lung cancer

Background

In the absence of targeted mutations and immune checkpoints, platinum-based chemotherapy remains a gold standard agent in the treatment of patients with lung squamous cell carcinoma (LUSC). However, cisplatin resistance greatly limits its therapeutic efficacy and presents challenges in the treatment of lung cancer patients. Therefore, the potential clinical needs for this research focus on identifying novel molecular signatures to further elucidate the underlying mechanisms of cisplatin resistance in LUSC. A growing body of evidence indicates that alternative splicing (AS) events significantly influence the tumor progression and survival of patients with LUSC. However, there are few systematic analyses of AS reported in LUSC. This study aims to explore the role of messenger RNA (mRNA), microRNA (miRNA), and AS in predicting prognosis in patients with cisplatin-resistant LUSC and provide potential therapeutic targets and drugs.

Methods

Gene expression and miRNA expression, using RNA sequencing (RNA-seq), and SpliceSeq data were downloaded from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to construct predictive models. Kaplan-Meier survival analyses were used to evaluate patients' prognosis. Single-sample gene set enrichment analysis (ssGSEA) conducted via the R package "GSEAbase" was used to evaluate the immune-related characteristics. Immunohistochemistry was used to examine protein expression. The Connectivity Map (CMap) database was used to screen for potential drugs. The 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT) assay was used to determine and calculate the half-maximal inhibitory concentration (IC50) of the drugs, sulforaphane and parthenolide.

Results

In this study, bioinformatics were used to identify mRNAs, miRNAs, and AS events related to response to cisplatin and to establish an integrated prognostic signature for 70 patients with LUSC and cisplatin resistance. The prognostic signature served as an independent prognostic factor with high accuracy [hazard ratio (HR) =2.346, 95% confidence interval (CI): 1.568-3.510; P<0.001], yielding an area under the curve (AUC) of 0.825, 0.829, and 0.877 for 1-, 3-, and 5-year survival, respectively. It also demonstrated high predictive performance in this cohort of patients with LUSC, with an AUC of 0.734, 0.767, and 0.776 for 1-, 3-, and 5-year survival, respectively. This integrated signature was also found to be an independent indicator among conventional clinical features (HR =2.288, 95% CI: 1.547-3.383; P<0.001). In addition, we analyzed the correlation of the signature with immune infiltration and identified several small-molecule drugs that had the potential to improve the survival of patients with LUSC.

Conclusions

This study provides a framework for the mRNA-, miRNA-, and AS-based evaluation of cisplatin response and several potential therapeutic drugs for targeting cisplatin resistance in LUSC. These findings may serve as a theoretical basis for the clinical alleviation of cisplatin resistance and thus help to improve treatment responses to chemotherapy in patients with LUSC.

Propofol regulates the progression of hepatocellular carcinoma via the POLR2L/TGF-β signaling pathway

Background

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality. Propofol has been reported to modulate tumorigenesis in HCC; the aim of this study was to investigate the effect of the interaction of propofol with POLR2L on HCC tumor progression in HCC.

Methods

The propofol-related GSE101724 dataset was analyzed using weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) to identify overlapping genes. Key genes were selected from The Cancer Genome Atlas-liver hepatocellular carcinoma (TCGA-LIHC)-DEGs for prognostic analysis. The impact of POLR2L on LIHC patient survival was assessed, followed by in vitro experiments to validated its effects on HCC cell behavior and signaling pathways.

Results

Fourteen overlapping genes were identified in the turquoise module (highest correlation) of up-regulated DEGs and GSE101724. Further analysis obtained 11 key overlapping genes from 14 overlapping genes and TCGA-LIHC-DEGs, among which HSPE1 and POLR2L showed significant prognostic correlation. Patients with LIHC have a worse chance of surviving when their POLR2L expression is elevated. Knockdown POLR2L significantly inhibited the proliferation, invasion, and migration of HCC cell lines. Downregulation of POLR2L was accompanied by induced apoptosis, cell cycle arrest, and modulation of the expression of apoptosis-related genes. Propofol was found to downregulate POLR2L expression, inhibiting cell proliferation and growth. Further, it was shown that propofol controlled the development of HCC by influencing the POLR2L/TGF-β signaling loop.

Conclusions

The results validated the predictive relevance of POLR2L in HCC and emphasized that propofol can regulate HCC progression through the POLR2L/TGF-β signaling pathway.

AS-CMC: a pan-cancer database of alternative splicing for molecular classification of cancer

Alternative splicing (AS) is a post-transcriptional regulation that leads to the complexity of the transcriptome. Despite the growing importance of AS in cancer research, the role of AS has not been systematically studied, especially in understanding cancer molecular classification. Herein, we analyzed the molecular subtype-specific regulation of AS using The Cancer Genome Atlas data and constructed a web-based database, named Alternative Splicing for Cancer Molecular Classification (AS-CMC). Our system harbors three analysis modules for exploring subtype-specific AS events, evaluating their phenotype association, and performing pan-cancer comparison. The number of subtype-specific AS events was found to be diverse across cancer types, and some differentially regulated AS events were recurrently found in multiple cancer types. We analyzed a subtype-specific AS in exon 11 of mitogen-activated protein kinase kinase 7 (MAP3K7) as an example of a pan-cancer AS biomarker. This AS marker showed significant association with the survival of patients with stomach adenocarcinoma. Our analysis revealed AS as an important determinant for cancer molecular classification. AS-CMC is the first web-based resource that provides a comprehensive tool to explore the biological implications of AS events, facilitating the discovery of novel AS biomarkers.

Simultaneous editing of TCR, HLA-I/II and HLA-E resulted in enhanced universal CAR-T resistance to allo-rejection

Introduction

The major challenge for universal chimeric antigen receptor T cell (UCAR-T) therapy is the inability to persist for a long time in patients leading to inferior efficacy clinically. The objective of this study was to design a novel UCAR-T cell that could avoid the occurrence of allo-rejection and provide effective resistance to allogeneic Natural Killer (NK) cell rejection, together with the validation of its safety and efficacy ex vivo and in vivo.

Methods

We prepared T-cell receptor (TCR), Human leukocyte antigen (HLA)-I/II triple-edited (TUCAR-T) cells and evaluated the anti-tumor efficacy ex vivo and in vivo. We measured the resistance of exogenous HLA-E expressing TUCAR-T (ETUCAR-T) to NK rejection by using an enhanced NK. Furthermore, we established the safety and efficacy of this regimen by treating Nalm6 tumor-bearing mice with a repeated high-dose infusion of ETUCAR-T. Moreover, we analyzed the effects of individual gene deficiency CAR-T on treated mice and the changes in the transcriptional profiles of different gene-edited T cells via RNA-Seq.

Results

Data showed that HLA-II editing didn't impair the anti-tumor efficacy of TUCAR-T ex vivo and in vivo and we found for the first time that HLA-II deficiency could facilitate the persistence of CAR-T. Contrastively, as the most commonly eliminated target in UCAR-T, TCR deficiency was found to be a key disadvantageous factor for the shorter-term anti-tumor efficacy in vivo. Our study demonstrated ETUCAR-T could effectively resist allogeneic NK rejection ex vivo and in vivo.

Discussion

Our research provided a potential and effective strategy for promoting the persistence of UCAR-T cells in clinical application. And it reveals the potential key factors of the poor persistence of UCAR-T along with new insights for future development.

A new risk model for CSTA, FAM83A, and MYCT1 predicts poor prognosis and is related to immune infiltration in lung squamous cell carcinoma

OBJECTIVES

To create a prognostic model based on differentially expressed genes (DEGs) in early lung squamous cell carcinoma (LUSC) and characterize the relationship between risk scores and tumor immune infiltration.

METHODS

We identified DEGs in normal and tumor tissues that overlapped between LUSC-related data sets from the Gene Expression Omnibus and the Cancer Genome Atlas and evaluated their roles in the diagnosis and prognosis of LUSC by Kaplan-Meier survival analysis, receiver operating characteristic (ROC) analysis, meta-analysis and nomogram analysis. We then constructed a risk model based on Cox regression analysis and the Akaike information criterion and identified the relationship between LUSC risk scores and immune infiltration.

RESULTS

Sixty-two overlapping DEGs were involved with keratinocyte differentiation, epidermal cell differentiation, neutrophil migration, granulocyte chemotaxis, granulocyte migration, leukocyte aggregation, and positive regulation of nuclear factor-κB (NF-κB) activity. Overexpression of family with sequence similarity 83 member A (FAM83A) and MYC target 1 (MYCT1), kallikrein related peptidase 8 (KLK8), and downregulation of ADP ribosylation factor like GTPase 14 (ARL14), caspase recruitment domain family member 14 (CARD14), cystatin A (CSTA), dickkopf WNT signaling pathway inhibitor 4 (DKK4), desmoglein 3 (DSG3), and keratin 6B (KRT6B) were associated with a poor prognosis in LUSC and had significant value for LUSC diagnosis. The expression of CSTA, FAM83A, and MYCT1 and high-risk scores were independent risk factors for a poor prognosis in LUSC. A risk nomogram revealed that risk scores could predict the prognosis of LUSC. The risk score was associated with neutrophils, naive B cells, helper follicular T cells, and activated dendritic cells.

CONCLUSIONS

The expression levels of CSTA, FAM83A, and MYCT1 are related to the diagnosis and prognosis of LUSC and may have potential as therapeutic targets in LUSC. A risk model and nomogram based on CSTA, FAM83A, and MYCT1 can predict the prognosis of LUSC.

A Novel Prognosis Signature Based on Ferroptosis-Related Gene DNA Methylation Data for Lung Squamous Cell Carcinoma

Ferroptosis-related genes regulating an iron- and lipid reactive oxygen species (ROS)-dependent form of programmed cell death suggest critical roles for ferroptosis in cancers. However, the prognostic value of ferroptosis-related epigenetic features such as DNA methylation in lung squamous cell carcinoma (LUSC) needs to be studied. Ferroptosis-related genes are collected from the FerrDb database, and the methylation data of these related genes in LUSC methylation data downloaded from the TCGA are retrieved. The DNA methylation data (362 LUSC samples) were analyzed to screen prognostic ferroptosis-related methylation sites. After patients with complete overall survival (OS) information were randomly separated into training cohort (n = 200) and validation cohort (n = 162), the least absolute shrinkage and selection operator (LASSO) and the Cox regression were used to establish and validate the prognostic signature. The time-dependent receiver operating characteristic (ROC) and Kaplan–Meier survival curve analyses, Harrell's concordance index (C-index), calibration analysis, and decision curve analysis (DCA) were performed to evaluate the risk signature and related nomogram. A series of other bioinformatics approaches such as mexpress, cbioportal, maftools, string, metascape, TIMER, and Kaplan–Meier survival curve analysis were also used to determine the methylation, mutation status, protein interaction network or functional enrichment, effects on immune cell infiltration, or expression level prognosis of those signature-related genes. A total of 137 DNA methylation sites were identified as prognostic predictors corresponding to 109 ferroptosis-related genes (FRGs). The methylation signature containing 31 methylation sites proved to be superior predictive efficiency in predicting the 1-, 3-, 5-, and 10-year OS. 8 out of 28 signature-related genes were significantly related to OS time or OS state in patients with LUSC. In addition, DUSP1, ZFN36, and ALOX5 methylation status also correlated with pathological M and ALOX5 methylation correlated with pathological N. The prognostic prediction efficiency of T, N, M, and the stage was inferior to that of the DNA methylation signature. LUSC patients in the high-risk group own a significantly larger number of variants of FRGs than those in the low-risk group. In addition, negative or positive correlation patterns were presented among the different infiltrating immune cells with risk scores or signature-related genes in patients with LUSC. The expression level of 15 signature-related genes showed a significant relationship with OS of LUSC patients. A novel prognostic nomogram survival model containing 4 factors including age, pathologic T, stage, and risk group was constructed and validated, AndC-index, decision curve analysis (DCA), and calibration analysis demonstrated its excellent predictive performance. The FRG DNA methylation data-based prognostic model acts as a powerful prognostic prediction indicator in LUSC patients and is advantageous over the traditional model based on T, N, M, and stage.

Switched alternative splicing events as attractive features in lung squamous cell carcinoma

Background

Alternative splicing (AS) plays important roles in transcriptome and proteome diversity. Its dysregulation has a close affiliation with oncogenic processes. This study aimed to evaluate AS-based biomarkers by machine learning algorithms for lung squamous cell carcinoma (LUSC) patients.

Method

The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database were utilized. After data composition balancing, Boruta feature selection and Spearman correlation analysis were used for differentially expressed AS events. Random forests and a nested fivefold cross-validation were applied for lymph node metastasis (LNM) classifier building. Random survival forest combined with Cox regression model was performed for a prognostic model, based on which a nomogram was developed. Functional enrichment analysis and Spearman correlation analysis were also conducted to explore underlying mechanisms. The expression of some switch-involved AS events along with parent genes was verified by qRT-PCR with 20 pairs of normal and LUSC tissues.

Results

We found 16 pairs of splicing events from same parent genes which were strongly related to the splicing switch (intrapair correlation coefficient = − 1). Next, we built a reliable LNM classifier based on 13 AS events as well as a nice prognostic model, in which switched AS events behaved prominently. The qRT-PCR presented consistent results with previous bioinformatics analysis, and some AS events like ITIH5-10715-AT and QKI-78404-AT showed remarkable detection efficiency for LUSC.

Conclusion

AS events, especially switched ones from the same parent genes, could provide new insights into the molecular diagnosis and therapeutic drug design of LUSC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02429-2.

Systematic Analysis Identifies a Specific RNA-Binding Protein-Related Gene Model for Prognostication and Risk-Adjustment in HBV-Related Hepatocellular Carcinoma

Objective

Increasing evidence shows that dysregulated RNA binding proteins (RBPs) modulate the progression of several malignancies. Nevertheless, their clinical implications of RBPs in HBV-related hepatocellular carcinoma (HCC) remain largely undefined. Here, this study systematically analyzed the associations of RBPs with HBV-related HCC prognosis.

Methods

Based on differentially expressed RBPs between HBV-related HCC and control specimens, prognosis-related RBPs were screened by univariate analyses. A LASSO model was then created. Kaplan-Meier curves, ROCs, multivariate analyses, subgroup analyses and external verification were separately applied to assess the efficacy of this model in predicting prognosis and recurrence of patients. A nomogram was created by incorporating the model and clinical indicators, which was verified by ROCs, calibration curves and decision curve analyses. By CIBERSORT algorithm, the association between the risk score and immune cell infiltrations was evaluated.

Results

Totally, 54 RBPs were distinctly correlated to prognosis of HBV-related HCC. An 11-RBP model was created, containing POLR2L, MRPS12, DYNLL1, ZFP36, PPIH, RARS, SRP14, DDX41, EIF2B4, and NOL12. This risk score sensitively and accurately predicted one-, three- and five-year overall survival, disease-free survival, and progression-free interval. Compared to other clinical parameters, this risk score had the best predictive efficacy. Also, the clinical generalizability of the model was externally verified in the GSE14520 dataset. The nomogram may predict patients' survival probabilities. Also, the risk score was related to the components in the immune microenvironment.

Conclusion

Collectively, RBPs may act as critical elements in the malignant progression of HBV-related HCC and possess potential implications on prognostication and therapy decision.

Microarray analysis of genes with differential expression of m6A methylation in lung cancer

Purpose: N6-methyladenosine (m6A) is among the most abundant mRNA modifications in eukaryote. The aim of the present study was to investigate function of m6A mRNA methylation in lung cancer and the underlying mechanism.

Methods: Microarray analysis was performed to detect the differences in RNA expression between cancerous and adjacent non-cancerous tissue samples. The target mRNAs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Hierarchical clustering of RNAs was conducted to identify distinct m6A methylation or expression patterns between the samples.

Results: In the present study, some differentially expressed genes (DEGs) of mRNAs were identified, including up-regulated secret phosphoprotein 1 (SPP1) and down-regulated pRB. Functional enrichment analysis revealed that while differential hypermethylation was related to cell cycle, intracellular part and protein binding, the main pathway involved herpes simplex virus 1 infection related to down-regulated AKT, Araf1 and BCL2A1. In the meantime, sexual reproduction, cohesin complex and protein C-terminus binding was functionally linked to differential hypomethylation, while fluid shear stress and atherosclerosis were identified as the main pathways related to up-regulated GST and CNP.

Conclusions: We showed that lung cancer development involved differential expression of SPP1 and pRB mRNA, as well as m6A mRNA methylation in AKT, APAF1, BCL2A1, GST and CNP genes.

N6-Methyladenosine RNA Methylation Regulator-Related Alternative Splicing (AS) Gene Signature Predicts Non-Small Cell Lung Cancer Prognosis

Aberrant N6-methyladenosine (m6A) RNA methylation regulatory genes and related gene alternative splicing (AS) could be used to predict the prognosis of non-small cell lung carcinoma. This study focused on 13 m6A regulatory genes (METTL3, METTL14, WTAP, KIAA1429, RBM15, ZC3H13, YTHDC1, YTHDC2, YTHDF1, YTHDF2, HNRNPC, FTO, and ALKBH5) and expression profiles in TCGA-LUAD (n = 504) and TCGA-LUSC (n = 479) datasets from the Cancer Genome Atlas database. The data were downloaded and bioinformatically and statistically analyzed, including the gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. There were 43,948 mRNA splicing events in lung adenocarcinoma (LUAD) and 46,020 in lung squamous cell carcinoma (LUSC), and the data suggested that m6A regulators could regulate mRNA splicing. Differential HNRNPC and RBM15 expression was associated with overall survival (OS) of LUAD and HNRNPC and METTL3 expression with the OS of LUSC patients. Furthermore, the non-small cell lung cancer prognosis-related AS events signature was constructed and divided patients into high- vs. low-risk groups using seven and 14 AS genes in LUAD and LUSC, respectively. The LUAD risk signature was associated with gender and T, N, and TNM stages, but the LUSC risk signature was not associated with any clinical features. In addition, the risk signature and TNM stage were independent prognostic predictors in LUAD and the risk signature and T stage were independent prognostic predictors in LUSC after the multivariate Cox regression and receiver operating characteristic analyses. In conclusion, this study revealed the AS prognostic signature in the prediction of LUAD and LUSC prognosis.

Identification of Mutator-Derived Alternative Splicing Signatures of Genomic Instability for Improving the Clinical Outcome of Cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma is an aggressive carcinoma with increasing incidence and poor outcomes worldwide. Genomic instability and alternative splicing (AS) events are hallmarks of carcinoma development and progression. The relationship between genomic instability, AS events, and tumor immune microenvironment remain unclear.

METHODS

The splicing profiles of patients with cholangiocarcinoma were obtained from The Cancer Genome Atlas (TCGA) spliceSeq database. The transcriptomics, simple nucleotide variation (SNP) and clinical data of patients with cholangiocarcinoma were obtained from TCGA database. Patients were divided into genomic unstable (GU-like) and genomic stable (GS-like) groups according to their somatic mutations. Survival-related differential AS events were identified through integrated analysis of splicing profiling and clinical data. Kyoto Encyclopedia of Genes and Genomes enrichment analysis was used to identify AS events occurring in genes enriched in cancer pathways. Pearson correlation was applied to analyze the splicing factors regulating AS events. CIBERSORT was used identify differentially infiltrating immune cells.

RESULTS

A prognostic signature was constructed with six AS events. Using this signature, the hazard ratio of risk score for overall survival is 2.362. For TCGA patients with cholangiocarcinoma, the area under the receiver operating characteristic curve is 0.981. CDK11A is a negative regulator of survival associated AS events. Additionally, the CD8+ T cell proportion and PD-L1 expression are upregulated in patients with cholangiocarcinoma and high splicing signatures.

CONCLUSION

We provide a prognostic signature for cholangiocarcinoma overall survival. The CDK11A splicing factor and SLC46A1-39899-ES and IARS-86836-ES AS events may be potential targets for cholangiocarcinoma therapy. Patients with high AS risk score may be more sensitive to anti-PD-L1/PD1 immunotherapy.

RNA-binding protein with serine-rich domain 1 regulates microsatellite instability of uterine corpus endometrial adenocarcinoma

OBJECTIVE

To determine the role of RNA-binding protein with serine-rich domain 1 (RNPS1) in uterine corpus endometrial carcinoma (UCEC), the role of RNPS1 knockdown in UCEC development in vitro and in vivo, and the relationship between RNPS1 and mismatch repair (MMR) in UCEC.

METHODS

We predicted the potential function of RNPS1 using bioinformatics systems. The expression of RNPS1 in tissues and cell lines was analyzed by western blotting and immunohistochemistry. The expression of RNPS1 in MMR was assessed using bioinformatics and western blotting. The proliferation and apoptosis of UCEC cells were assessed under RNPS1 knockdown conditions, and RNPS1 regulation in MMR was detected by suppressing Notch signaling. Associations between RNPS1 and gene mutations in UCEC and prognosis were analyzed.

RESULTS

The RNPS1 level was higher in UCEC tumors than in normal tissues and tumors or RL952 cells. Prognostic outcomes were worse when UCEC showed abundant RNPS1 expression. Lentiviral RNPS1 knockdown weakened tumor cell proliferation and suppressed biomarker expression, reduced the tumor volume, promoted apoptosis in vitro and in vivo, and inhibited UCEC development. Increased MutS homolog 2 (MSH2) and MutS homolog 6 (MSH6) levels in MMR after RNPS1 knockdown were reversed by inhibiting Notch signaling. Furthermore, RNPS1 was associated with mutations in NAA11, C2orf57, NUPR1, and other genes involved in UCEC prognosis.

CONCLUSION

RNPS1 may regulate the expression levels of MSH2 and MSH6 in MMR, enhancing the proliferation, development, and prognosis of UCEC through a Notch signaling pathway in UCEC. Our study offers a new method and strategy for delaying UCEC development through modulating MMR.