Identification of Methylation-Driven, Differentially Expressed STXBP6 as a Novel Biomarker in Lung Adenocarcinoma

Circulating resistin levels and mutation burden of the RETN gene variants predict long-term mortality in a Taiwanese population

Human resistin is a proinflammatory cytokine involving the development and progression of cancer and cardiovascular diseases. However, prediction of long-term outcome using circulating resistin level and its genetic determinants in a population-based study remain to be explored. After genome-wide association study (GWAS), DNA methylation (DNAm) analysis and functional assays of a RETN rs370006313 variant, we tested whether resistin level and its genetic determinants can be used to determine the long-term outcomes of 5678 Taiwan Biobank (TWB) participants. GWAS and DNAm analysis revealed RETN variants, rs3219175, rs370006313, and rs3745368, and DNAm sites, cg21271423 and cg09909011, independently associated with circulating resistin levels. Functional assays showed rs370006313 variant played a key role in affecting RETN promoter activity, whereas genotypes of rs3219175 and rs3745368, but not rs370006313, exhibited genome-wide significant associations with RETN promoter DNAm levels. Using Kaplan-Meier survival and Cox regression analyses, participants with progressively increasing resistin levels had a higher hazard ratio for all-cause mortality and cancer mortality compared to those with lower resistin levels. Participants with all three RETN variants (high mutation burden) also exhibited significantly higher hazard ratios for all-cause mortality and cancer mortality, at 3.99 and 5.55, respectively, compared to those without a high mutation burden. In conclusion, RETN rs370006313 is a functional variant affecting RETN promoter activity. Elevated circulating resistin levels and a high RETN mutation burden predict all-cause and cancer mortality in TWB participants. Both resistin levels and RETN variants may serve as biomarkers of long-term outcomes in the general Taiwanese populations.

The upregulation of CLGN in hepatocellular carcinoma is potentially regulated by hsa-miR-194-3p and associated with patient progression

Background

Patients with hepatocellular carcinoma (HCC) have poor prognosis, especially in advanced stages. Targeted therapy is the main treatment for advanced HCC patients, but the optimal targets for HCC remain poorly understood. The main purpose of this study was to identify potential novel prognostic markers and therapeutic targets.

Methods

Firstly, differentially expressed genes (DEGs) in HCC were identified from the Gene Expression Omnibus (GEO) database. The expression, significance in prognosis, and potential mechanisms of DEGs were analyzed using GEPIA, TIMER, HPA, Kaplan Meier Plotter, CBioPortal, miRWalk, TargetScan, and ENCORI databases. Immunohistochemical staining was used to determine the protein expression levels of potential candidate genes.

Results

The mRNA levels of MND1, STXBP6, and CLGN were significantly increased in HCC (p< 0.01). HCC patients with elevated CLGN mRNA levels had poorer overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and disease-specific survival (DSS) (p < 0.05). Higher MND1 mRNA levels significantly correlated with poorer DFS in HCC patients (p< 0.05). However, there was no significant correlation between STXBP6 expression and prognosis of HCC (p> 0.05). Further analysis revealed that patients with elevated CLGN mRNA expression in advanced pathology stages had poorer prognosis (p< 0.01). In addition, CLGN protein levels were elevated in HCC compared to their levels in normal tissues. The mRNA levels of CLGN had no significant correlation with the abundance of six common tumor infiltrating lymphocytes in HCC (COR < 0.5). Moreover, the mutation rate of CLGN was less than 1% in HCC patients (10/1089). Finally, the expression level of hsa-miR-194-3p in HCC was significantly lower than that in normal tissues (p < 0.05), and prognosis of HCC with low expression of hsa-miR-194 was poor (p < 0.05).

Conclusion

The upregulation of CLGN in HCC is significantly associated with poor patient prognosis, especially in the advanced stages, and may be regulated by hsa-miR-194-3p. These findings suggest that CLGN may be closely related to the progression of HCC, and is a potential therapeutic target and prognostic indicator for patients with advanced HCC.

Analysis on methylation and expression of PSMB8 and its correlation with immunity and immunotherapy in lung adenocarcinoma

Aim: To find biomarkers for immunity and immunotherapy in lung adenocarcinoma (LUAD) through multiomics analysis. Materials & methods: The multiomics data of patients with LUAD were downloaded from the TCGA and GEO databases. CIBERSORT, quanTIseq, ESTIMATEScore, k-means clustering, gene set enrichment analysis, gene set variation analysis, immunophenoscore and logistic regression were used in this study. Results: PSMB8 HypoMet-HighExp group patients have more active immune-related pathways, more antitumor immune cells, less protumor immune cells, higher immunophenoscore and longer progression-free survival of immune checkpoint inhibitor therapy than HyperMet-LowExp group. In multivariate analysis, PSMB8 showed an independent value. Conclusion: The combination of DNA methylation and mRNA expression of PSMB8 could independently distinguish types of tumor immune microenvironment and predict programmed cell death protein 1/programmed cell death-ligand 1 inhibitors' effects in patients with LUAD.

Genetic Obesity Variants and Risk of Conventional Adenomas and Serrated Polyps

BACKGROUND

Higher body mass index (BMI) is associated with increased risk of colorectal cancer. How genetically predicted BMI may be associated with colorectal cancer precursors is unknown.

AIMS

Our objective was to quantify the association of genetically predicted and measured BMI with risk of colorectal cancer precursors.

METHODS

We evaluated the association of genetically predicted and measured BMI with risk of conventional adenomas, serrated polyps, and synchronous polyps among 27,426 participants who had undergone at least one lower gastrointestinal endoscopy in the Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-up Study. Genetic risk score was derived from 97 BMI-related single nucleotide polymorphisms. Multivariable logistic regression evaluated each polyp subtype compared to non-polyps.

RESULTS

For conventional adenomas, the OR per 2-kg/m² increase was 1.03 (95% CI, 1.01-1.04) for measured BMI and 0.98 (95% CI, 0.88-1.10) for genetically predicted BMI; for serrated polyps, the OR was 1.06 (95% CI, 1.04-1.08) and 1.04 (95% CI, 0.90-1.20), respectively; for synchronous polyps, the OR was 1.10 (95% CI, 1.07-1.13) and 1.09 (95% CI, 0.89-1.34), respectively. Genetically predicted BMI was associated with synchronous polyps in women (OR = 1.37, 95% CI: 1.05-1.79).

CONCLUSION

Genetically predicted BMI was not associated with colorectal cancer precursor lesions. The confidence intervals were wide and encompassed those for measured BMI, indicating that null findings may be due to insufficient power.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Predicting the Lung Adenocarcinoma and Its Biomarkers by Integrating Gene Expression and DNA Methylation Data

The early symptoms of lung adenocarcinoma patients are inapparent, and the clinical diagnosis of lung adenocarcinoma is primarily through X-ray examination and pathological section examination, whereas the discovery of biomarkers points out another direction for the diagnosis of lung adenocarcinoma with the development of bioinformatics technology. However, it is not accurate and trustworthy to diagnose lung adenocarcinoma due to omics data with high-dimension and low-sample size (HDLSS) features or biomarkers produced by utilizing only single omics data. To address the above problems, the feature selection methods of biological analysis are used to reduce the dimension of gene expression data (GSE19188) and DNA methylation data (GSE139032, GSE49996). In addition, the Cartesian product method is used to expand the sample set and integrate gene expression data and DNA methylation data. The classification is built by using a deep neural network and is evaluated on K-fold cross validation. Moreover, gene ontology analysis and literature retrieving are used to analyze the biological relevance of selected genes, TCGA database is used for survival analysis of these potential genes through Kaplan-Meier estimates to discover the detailed molecular mechanism of lung adenocarcinoma. Survival analysis shows that COL5A2 and SERPINB5 are significant for identifying lung adenocarcinoma and are considered biomarkers of lung adenocarcinoma.

A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

Objective

To discover potential predictors and explore how to build better models by summarizing the existing prognostic prediction models of non-small cell lung cancer (NSCLC).

Background

Research on clinical prediction models of NSCLC has experienced explosive growth in recent years. As more predictors of prognosis are discovered, the choice of predictors to build models is particularly important, and in the background of more applications of next-generation sequencing technology, gene-related predictors are widely used. As it is more convenient to obtain samples and follow-up data, the prognostic model is preferred by researchers.

Methods

PubMed and the Cochrane Library were searched using the items “NSCLC”, “prognostic model”, “prognosis prediction”, and “survival prediction” from 1 January 1980 to 5 May 2021. Reference lists from articles were reviewed and relevant articles were identified.

Conclusions

The performance of gene-related models has not obviously improved. Relative to the innovation and diversity of predictors, it is more important to establish a highly stable model that is convenient for clinical application. Most of the prevalent models are highly biased and referring to PROBAST at the beginning of the study may be able to significantly control the bias. Existing models should be validated in a large external dataset to make a meaningful comparison.

circ_0002346 Suppresses Non-Small-Cell Lung Cancer Progression Depending on the Regulation of the miR-582-3p/STXBP6 Axis

Background

Accumulating articles have reported the pivotal regulatory roles of circular RNAs (circRNAs) in non-small-cell lung cancer (NSCLC) tumorigenesis. Here, our purpose was to explore the role of circ_0002346 in NSCLC progression and its associated mechanism.

Methods

Cell proliferation ability was assessed by a 5-ethynyl-2′-deoxyuridine (EDU) assay and a colony formation assay. Transwell assays were conducted to analyze cell migration and invasion abilities. Cell apoptosis was analyzed by flow cytometry and by using a caspase3 activity assay kit. The glycolysis of NSCLC cells was analyzed using a fluorescence-based glucose/lactate assay kit. A dual-luciferase reporter assay and an RNA pull-down assay were performed to verify the binding relationship between microRNA-582-3p (miR-582-3p) and circ_0002346 or syntaxin-binding protein 6 (STXBP6).

Results

circ_0002346 level was prominently downregulated in NSCLC tissues and cell lines. circ_0002346 overexpression significantly suppressed the proliferation, migration, invasion, and glycolysis and triggered the apoptosis of NSCLC cells. circ_0002346 directly interacted with miR-582-3p, and circ_0002346 overexpression-mediated antitumor effects in NSCLC cells were partly reversed by miR-582-3p overexpression. miR-582-3p directly interacted with the 3′ untranslated region (3′UTR) of STXBP6, and STXBP6 silencing partly counteracted circ_0002346 overexpression-mediated antitumor influences in NSCLC cells. circ_0002346 can upregulate the expression of STXBP6 by acting as a miR-582-3p sponge in NSCLC cells. circ_0002346 overexpression suppressed xenograft tumor growth in vivo.

Conclusion

circ_0002346 overexpression suppressed the malignant properties of NSCLC cells by binding to miR-582-3p to induce the expression of STXBP6.

Hypomethylation-Mediated AGR2 Overexpression Facilitates Cell Proliferation, Migration, and Invasion of Lung Adenocarcinoma

Objective

Studies have indicated that AGR2 is crucial in many cancers. However, its methylation level in lung adenocarcinoma (LUAD) is rarely known. Hence, the effect of AGR2 methylation on LUAD was explored in the study.

Methods

qRT-PCR was adopted to detect the expression of AGR2 in LUAD cells and normal lung cells. Methylation-specific PCR (MSP) was used to detect the methylation of AGR2 promoter region in different cell lines. MTT, Transwell and wound healing assays were used to verify the progression of cells in each transfection group.

Results

The expression of AGR2 was significantly up-regulated in LUAD cells relative to that in normal cells. Moreover, the expression of AGR2 was inversely modulated by DNA methylation, and the hypomethylation of CpG islands would lead to the increased expression of AGR2. Finally, overexpression and hypomethylation of AGR2 facilitated the proliferation, invasion and migration of LUAD cells.

Conclusion

These results demonstrated that hypomethylation of AGR2 promoter region promoted the expression of AGR2 in LUAD cells, thus promoting the progression of LUAD cells.

Identification of STXBP6-IRF1 positive feedback loop in regulation of PD-L1 in cancer

The clinical success of immune checkpoint blockade against diverse human cancers highlights the critical importance of insightful understanding into mechanisms underlying PD-L1 regulation. IFN-γ released by intratumoral lymphocytes regulates PD-L1 expression in tumor cells through JAK-STAT-IRF1 pathway, while the molecular events prime IRF1 to translocate into nucleus are still obscure. Here we identified STXBP6, previously recognized involving in SNARE complex assembly, negatively regulates PD-L1 transcription via retention of IRF1 in cytoplasm. IFN-γ exposure stimulates accumulation of cytosolic IRF1, which eventually saturates STXBP6 and triggers nuclear translocation of IRF1. Nuclear IRF1 in turn inhibits STXBP6 expression and thereby liberates more IRF1 to migrate to nucleus. Therefore, we identified a novel positive feedback loop between STXBP6 and IRF1 in regulation of PD-L1 expression in cancer. Furthermore, we demonstrate STXBP6 overexpression significantly inhibits T cell activation both in vitro and in vivo. These findings offer new insight into the complexity of PD-L1 expression in cancer and suggest a valuable measure to predict the response to PD-1/PD-L1-based immunotherapy.

PI(4,5)P2-dependent regulation of exocytosis by amisyn, the vertebrate-specific competitor of synaptobrevin 2

The functions of nervous and neuroendocrine systems rely on fast and tightly regulated release of neurotransmitters stored in secretory vesicles through SNARE-mediated exocytosis. Few proteins, including tomosyn (STXBP5) and amisyn (STXBP6), were proposed to negatively regulate exocytosis. Little is known about amisyn, a 24-kDa brain-enriched protein with a SNARE motif. We report here that full-length amisyn forms a stable SNARE complex with syntaxin-1 and SNAP-25 through its C-terminal SNARE motif and competes with synaptobrevin-2/VAMP2 for the SNARE-complex assembly. Furthermore, amisyn contains an N-terminal pleckstrin homology domain that mediates its transient association with the plasma membrane of neurosecretory cells by binding to phospholipid PI(4,5)P₂ However, unlike synaptrobrevin-2, the SNARE motif of amisyn is not sufficient to account for the role of amisyn in exocytosis: Both the pleckstrin homology domain and the SNARE motif are needed for its inhibitory function. Mechanistically, amisyn interferes with the priming of secretory vesicles and the sizes of releasable vesicle pools, but not vesicle fusion properties. Our biochemical and functional analyses of this vertebrate-specific protein unveil key aspects of negative regulation of exocytosis.

Genome-Wide DNA Methylation Profiling in Early Stage I Lung Adenocarcinoma Reveals Predictive Aberrant Methylation in the Promoter Region of the Long Noncoding RNA PLUT: An Exploratory Study

INTRODUCTION

Surgical procedure is the treatment of choice in early stage I lung adenocarcinoma. However, a considerable number of patients experience recurrence within the first 2 years after complete resection. Suitable prognostic biomarkers that identify patients at high risk of recurrence (who may probably benefit from adjuvant treatment) are still not available. This study aimed at identifying methylation markers for early recurrence that may become important tools for the development of new treatment modalities.

METHODS

Genome-wide DNA methylation profiling was performed on 30 stage I lung adenocarcinomas, comparing 14 patients with early metastatic recurrence with 16 patients with a long-term relapse-free survival period using methylated-CpG-immunoprecipitation followed by high-throughput next-generation sequencing. The differentially methylated regions between the two subgroups were validated for their prognostic value in two independent cohorts using the MassCLEAVE assay, a high-resolution quantitative methylation analysis.

RESULTS

Unsupervised clustering of patients in the discovery cohort on the basis of differentially methylated regions identified patients with shorter relapse-free survival (hazard ratio: 2.23; 95% confidence interval: 0.66-7.53; p = 0.03). In two validation cohorts, promoter hypermethylation of the long noncoding RNA PLUT was significantly associated with shorter relapse-free survival (hazard ratio: 0.54; 95% confidence interval: 0.31-0.93; p < 0.026) and could be reported as an independent prognostic factor in the multivariate Cox regression analysis.

CONCLUSIONS

Promoter hypermethylation of the long noncoding RNA PLUT is predictive in patients with early stage I adenocarcinoma at high risk for early recurrence. Further studies are needed to validate its role in carcinogenesis and its use as a biomarker to facilitate patient selection and risk stratification.

Estimating gene expression from DNA methylation and copy number variation: A deep learning regression model for multi-omics integration

Gene expression analysis plays a significant role for providing molecular insights in cancer. Various genetic and epigenetic factors (being dealt under multi-omics) affect gene expression giving rise to cancer phenotypes. A recent growth in understanding of multi-omics seems to provide a resource for integration in interdisciplinary biology since they altogether can draw the comprehensive picture of an organism's developmental and disease biology in cancers. Such large scale multi-omics data can be obtained from public consortium like The Cancer Genome Atlas (TCGA) and several other platforms. Integrating these multi-omics data from varied platforms is still challenging due to high noise and sensitivity of the platforms used. Currently, a robust integrative predictive model to estimate gene expression from these genetic and epigenetic data is lacking. In this study, we have developed a deep learning-based predictive model using Deep Denoising Auto-encoder (DDAE) and Multi-layer Perceptron (MLP) that can quantitatively capture how genetic and epigenetic alterations correlate with directionality of gene expression for liver hepatocellular carcinoma (LIHC). The DDAE used in the study has been trained to extract significant features from the input omics data to estimate the gene expression. These features have then been used for back-propagation learning by the multilayer perceptron for the task of regression and classification. We have benchmarked the proposed model against state-of-the-art regression models. Finally, the deep learning-based integration model has been evaluated for its disease classification capability, where an accuracy of 95.1% has been obtained.

Semaphorin 5A suppresses the proliferation and migration of lung adenocarcinoma cells

Semaphorin 5A (SEMA5A), a member of the semaphorin family, plays an important role in axonal guidance. Previously, the authors identified another possible role of SEMA5A as a prognostic biomarker for non-smoking women with lung adenocarcinoma in Taiwan, and this phenomenon has been validated in other ethnic groups. However, the functional significance of SEMA5A in lung adenocarcinoma remains unclear. Therefore, we assessed the function of SEMA5A in three lung adenocarcinoma cell lines in this study. Kaplan-Meier Plotter for lung cancer was conducted for survival analyses. Reverse transcription-quantitative PCR (RT-qPCR) and western blot analysis were performed to investigate the expression and post-translational regulation of SEMA5A in lung adenocar-cinoma cell lines. A pre-designed PyroMark CpG assay and 5-aza-2′-deoxycytidine treatment were used to measure the methylation levels of SEMA5A. The biological functions of lung adenocarcinoma cells overexpressing SEMA5A were investigated by microarrays, and validated both in vitro (proliferation, colony formation and migration assays) and in vivo (tumor xenografts) experiments. The results revealed that the hypermethylation of SEMA5A and the cleavage of the extracellular domain of SEMA5A were responsible for the downregulation of the SEMA5A levels in lung adenocarcinoma cells (A549 and H1299) as compared to the normal controls. Functional analysis of SEMA5A-regulated genes revealed that they were involved in cellular growth and proliferation. The overexpression of SEMA5A in A549 and H1299 cells significantly decreased the proliferation (P<0.01), colony formation (P<0.001) and migratory ability (P<0.01) of the cells. The suppressive effects of SEMA5A on the proliferative and migratory ability of the cells were also observed in both in vitro and in vivo experiments using brain metastatic Bm7 lung adenocarcinoma cells. On the whole, the findings of this study suggest a suppressive role for SEMA5A in lung adenocarcinoma involving the inhibition of the proliferation and migration of lung transformed cells.

The characteristics of lung cancer in Xuanwei County: A review of differentially expressed genes and noncoding RNAs on cell proliferation and migration

The occurrence of lung cancers is the highest in Xuanwei County, Yunnan province, China, especially among nonsmoking women. Domestic combustion of smoky coal induces serious indoor air pollution and is considered to be the main cause of human lung cancers. The occurrence of lung cancer in Xuanwei County has unique characteristics, such as the high morbidity in nonsmoking women or people with no family history. In the present review, we summarize advances in identification of differentially expressed genes, regulatory lncRNAs and miRNAs in cell proliferation and migration of lung cancers in Xuanwei County. Moreover, several regulatory differentially expressed genes (DEGs) or noncoding RNAs have diagnostic and prognostic significance for lung cancers in Xuanwei County and have the potential to serve as biomarkers.

Comprehensive bioinformatics analysis identifies several potential diagnostic markers and potential roles of cyclin family members in lung adenocarcinoma

Purpose

The aim of this study was to identify critical genes in lung cancer progression.

Methods

We downloaded and reanalyzed gene expression profiles from different public data-sets using comprehensive bioinformatics analysis. Differentially expressed genes (DEGs) were identified in lung adenocarcinoma tissues compared with adjacent nonmalignant lung tissues. The overlapping DEGs identified from different datasets were used for functional and pathway enrichment analyses and protein–protein interaction (PPI) analysis. Moreover, transcription factors (TFs) and miRNAs that regulated the overlapping DEGs were predicted, followed by a TF–miRNA–target network construction. Furthermore, survival analysis of genes was performed. Several genes were further validated by quantitative real-time PCR (qRT-PCR).

Results

A total of 647 overlapping upregulated genes and 979 overlapping downregulated genes were identified. The overlapping upregulated genes and downregulated genes were involved in different functions, such as cell cycle, p53 signaling pathway, immune response, and cell adhesion molecules (CAMs). Several genes belonging to the cyclin family, including CCNB1, CCNB2, and CCNA2, were hubs of the PPI network and TF–miRNA–target network. Additionally, genes, including NPAS2, GNG7, CHIA, and SLC2A1, were predicted to be prognosis-related DEGs. Gene expression profiles determined by bioinformatics analysis and qRT-PCR were highly comparable.

Conclusion

CCNB1, CCNB2, CCNA2, NPAS2, GNG7, CHIA, and SLC2A1 are promising targets for the clinical diagnosis and therapy of lung adenocarcinoma.

A Systems-Level Analysis Reveals Circadian Regulation of Splicing in Colorectal Cancer

Accumulating evidence points to a significant role of the circadian clock in the regulation of splicing in various organisms, including mammals. Both dysregulated circadian rhythms and aberrant pre-mRNA splicing are frequently implicated in human disease, in particular in cancer. To investigate the role of the circadian clock in the regulation of splicing in a cancer progression context at the systems-level, we conducted a genome-wide analysis and compared the rhythmic transcriptional profiles of colon carcinoma cell lines SW480 and SW620, derived from primary and metastatic sites of the same patient, respectively. We identified spliceosome components and splicing factors with cell-specific circadian expression patterns including SRSF1, HNRNPLL, ESRP1, and RBM 8A, as well as altered alternative splicing events and circadian alternative splicing patterns of output genes (e.g., VEGFA, NCAM1, FGFR2, CD44) in our cellular model. Our data reveals a remarkable interplay between the circadian clock and pre-mRNA splicing with putative consequences in tumor progression and metastasis.

Lung cancer epigenetics: From knowledge to applications

Lung cancer is the leading cause of cancer-related mortality worldwide. Advances in our understanding of the genomics of lung cancer have led to substantial progress in the treatment of specific molecular subsets. Immunotherapy also emerges as a major breakthrough in lung cancer treatment. However, challenges remain as a consensual approach for early lung cancer detection remains elusive while primary or secondary drug resistance eventually leads to treatment failure in all patients with advanced disease. Furthermore, a large portion of patients are still treated with conventional chemotherapy that is only modestly effective. The last two decades have seen exponential developments in the epigenetic understanding of lung cancer. Epigenetic alterations in DNA methylation, non-coding RNA expression, chromatin modeling and post transcriptional regulators are key events in each step of lung cancer pathogenesis. Here, we review the central role epigenetic disruptions play in lung cancer carcinogenesis and the acquisition of cancerous phenotype and aggressive behavior as well as in the resistance to therapy. Epigenetic disruptions could represent reliable biomarkers for lung cancer risk assessment, early diagnosis, prognosis stratification, molecular classification and prediction of treatment efficacy. The therapeutic potential of epigenetics targeted drugs in combination with chemotherapy, targeted therapy and/or immunotherapy is currently being intensively investigated. We suggest that integration of tissue-derived or circulating epigenetic biomarkers and epidrugs in clinical trial design will translate epigenetic knowledge of lung cancer into the clinic and improve lung cancer patient outcomes.