An Integrated Prognostic Classifier for Stage I Lung Adenocarcinoma Based on mRNA, microRNA, and DNA Methylation Biomarkers

Molecular pathological approach to cancer epigenomics and its clinical application

Careful microscopic observation of histopathological specimens, accumulation of large numbers of high-quality tissue specimens, and analysis of molecular pathology in relation to morphological features are considered to yield realistic data on the nature of multistage carcinogenesis. Since the morphological hallmark of cancer is disruption of the normal histological structure maintained through cell-cell adhesiveness and cellular polarity, attempts have been made to investigate abnormalities of the cadherin-catenin cell adhesion system in human cancer cells. It has been shown that the CDH1 tumor suppressor gene encoding E-cadherin is silenced by DNA methylation, suggesting that a "double hit" involving DNA methylation and loss of heterozygosity leads to carcinogenesis. Therefore, in the 1990s, we focused on epigenomic mechanisms, which until then had not received much attention. In chronic hepatitis and liver cirrhosis associated with hepatitis virus infection, DNA methylation abnormalities were found to occur frequently, being one of the earliest indications that such abnormalities are present even in precancerous tissue. Aberrant expression and splicing of DNA methyltransferases, such as DNMT1 and DNMT3B, was found to underlie the mechanism of DNA methylation alterations in various organs. The CpG island methylator phenotype in renal cell carcinoma was identified for the first time, and its therapeutic targets were identified by multilayer omics analysis. Furthermore, the DNA methylation profile of nonalcoholic steatohepatitis (NASH)-related hepatocellular carcinoma was clarified in groundbreaking studies. Since then, we have developed diagnostic markers for carcinogenesis risk in NASH patients and noninvasive diagnostic markers for upper urinary tract cancer, as well as developing a new high-performance liquid chromatography-based diagnostic system for DNA methylation diagnosis. Research on the cancer epigenome has revealed that DNA methylation alterations occur from the precancerous stage as a result of exposure to carcinogenic factors such as inflammation, smoking, and viral infections, and continuously contribute to multistage carcinogenesis through aberrant expression of cancer-related genes and genomic instability. DNA methylation alterations at the precancerous stages are inherited by or strengthened in cancers themselves and determine the clinicopathological aggressiveness of cancers as well as patient outcome. DNA methylation alterations have applications as biomarkers, and are expected to contribute to diagnosis, as well as preventive and preemptive medicine.

Cell-free DNA methylation profile potential in the diagnosis of lung squamous cell carcinoma

Background

Aberrant methylation plays an essential role in early cancer development. In this study, we investigated methylation patterns in lung squamous cell carcinoma (LUSC) and matched non-tumor tissue and plasma samples to evaluate the potential of these patterns in the diagnosis of LUSC.

Methods

The study group included 49 patients with stage I-III LUSC. We collected resected tumor tissue, paired peritumoral tissue, distant normal tissue, and corresponding plasma samples. A bespoke lung cancer bisulfite sequencing panel was used to profile the methylation level. Another 48 healthy volunteers provided control plasma samples.

Results

Peritumoral and distant normal tissues presented similar methylation signatures, distinct from those in tumor tissue samples. A comparison of methylation profiles led to the identification of 871 tumor-specific differentially methylated blocks, including 847 hypermethylated and 24 hypomethylated blocks (adjusted P value <0.05). All top-ranked blocks were tumor-related. Tissue samples were analyzed for field cancerization to identify progressively aggravating aberrant methylations during tumor initiation and development. The analysis revealed that 221 blocks presented a stepwise increase in methylation levels, while seven blocks presented a stepwise decrease in methylation pattern as the sampling drew nearer to the tumor. The malignant contaminated ratio (MCR) confirmed the presence of distinct methylation patterns between tumor and peritumoral tissue samples. We then constructed a diagnostic panel using a combined diagnostic score of cell-free DNA (cfDNA) that showed high sensitivity and specificity. The healthy controls had a significantly lower combined diagnostic score (cd-score) than LUSC patients. Additionally, based on the methylation profiles, LUSC could be classified into two subgroups, C1 and C2. The methylation profile of the C2 group was not distinct from the healthy controls, which had a significantly lower cd-score than did the C1 group.

Conclusions

LUSC-specific methylation patterns could potentially discriminate between peritumoral tissue, distant normal tumor tissue, and tumor tissues. This preliminary study also supported the potential utility of cfDNA methylation analysis in diagnosing LUSC.

Leveraging an immune cell signature to improve the survival and immunotherapy response of lung adenocarcinoma

Background: Immune cells play a critical role in the prognosis of cancer. However, the function of different immune cell types in lung adenocarcinoma (LUAD) and the development of a prognostic signature based on immune cell types have not been comprehensively investigated. Methods: We collected and included a total of 2499 LUAD patients and performed calculations to determine the penetration level of 24 immune cells. This examination was conducted using the macro-gene-based approach provided by ImmuCellAI. We performed a meta-analysis using Lasso-Cox analysis to establish the immune cell pair score (ICPS). We conducted a survival analysis to measure differences in survival across ICPS-risk groups. Wilcox test was used to measure the difference in expression level. Spearman correlation analysis was used for the relevance assessment. Results: We collected a total of 24 immune cell types to construct cell pairs. Utilizing 17 immune cell pairs, we constructed and validated the ICPS, which plays a critical role in stratifying survival and dynamically monitoring the effectiveness of immunotherapy. Additionally, we identified several candidate drugs that target ICPS. Conclusions: The ICPS shows promise as a valuable tool for identifying suitable candidates for immunotherapy among patients. Our comprehensive assessment of immune cell interactions in LUAD contributes to a deeper understanding of infiltration patterns and functions, thereby guiding the development of more efficacious immunotherapy strategies.

The role of m6A demethylases in lung cancer: diagnostic and therapeutic implications

m6A is the most prevalent internal modification of eukaryotic mRNA, and plays a crucial role in tumorigenesis and various other biological processes. Lung cancer is a common primary malignant tumor of the lungs, which involves multiple factors in its occurrence and progression. Currently, only the demethylases FTO and ALKBH5 have been identified as associated with m6A modification. These demethylases play a crucial role in regulating the growth and invasion of lung cancer cells by removing methyl groups, thereby influencing stability and translation efficiency of mRNA. Furthermore, they participate in essential biological signaling pathways, making them potential targets for intervention in lung cancer treatment. Here we provides an overview of the involvement of m6A demethylase in lung cancer, as well as their potential application in the diagnosis, prognosis and treatment of the disease.

Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis

BACKGROUND

To evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis.

METHODS

We measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only.

FINDINGS

There were 86 proteins nominally associated with mortality (p < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10-1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61-0.66), compared with 0.62 (95% CI: 0.59-0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: -0.003 to 0.035).

INTERPRETATION

Blood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information.

FUNDING

No explicit funding for this study. Authors and data collection supported by the US National Cancer Institute (U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden (AMP19-962), and Swedish Department of Health Ministry.

A Systematic Review of Progress toward Unlocking the Power of Epigenetics in NSCLC: Latest Updates and Perspectives

Epigenetic research has the potential to improve our understanding of the pathogenesis of cancer, specifically non-small-cell lung cancer, and support our efforts to personalize the management of the disease. Epigenetic alterations are expected to have relevance for early detection, diagnosis, outcome prediction, and tumor response to therapy. Additionally, epi-drugs as therapeutic modalities may lead to the recovery of genes delaying tumor growth, thus increasing survival rates, and may be effective against tumors without druggable mutations. Epigenetic changes involve DNA methylation, histone modifications, and the activity of non-coding RNAs, causing gene expression changes and their mutual interactions. This systematic review, based on 110 studies, gives a comprehensive overview of new perspectives on diagnostic (28 studies) and prognostic (25 studies) epigenetic biomarkers, as well as epigenetic treatment options (57 studies) for non-small-cell lung cancer. This paper outlines the crosstalk between epigenetic and genetic factors as well as elucidates clinical contexts including epigenetic treatments, such as dietary supplements and food additives, which serve as anti-carcinogenic compounds and regulators of cellular epigenetics and which are used to reduce toxicity. Furthermore, a future-oriented exploration of epigenetic studies in NSCLC is presented. The findings suggest that additional studies are necessary to comprehend the mechanisms of epigenetic changes and investigate biomarkers, response rates, and tailored combinations of treatments. In the future, epigenetics could have the potential to become an integral part of diagnostics, prognostics, and personalized treatment in NSCLC.

FHL1 as a novel prognostic biomarker and correlation with immune infiltration levels in lung adenocarcinoma

Aim: We aimed to examine the effect of FHL1 in the diagnosis and prognosis of non-small-cell lung cancer and its relationship with tumor-infiltrating immune cells. Methods: FHL1 expression status and influence on clinical characteristics, diagnosis and prognosis in non-small-cell lung cancer were assessed. Interaction networks of FHL1 were revealed, and a correlation analysis between FHL1 expression and tumor immunity was performed. Results: FHL1 expression was significantly lower in tumors, and downregulated FHL1 predicted a worse prognosis for lung adenocarcinoma. FHL1 expression was correlated with tumor-infiltrating immune cells, immune checkpoints and chemokine levels. Conclusion: FHL1 is a powerful biomarker to evaluate the diagnosis and prognosis and immune infiltration level of lung adenocarcinoma.

Non-Invasive Biomarkers for Early Lung Cancer Detection

Worldwide, lung cancer (LC) is the most common cause of cancer death, and any delay in the detection of new and relapsed disease serves as a major factor for a significant proportion of LC morbidity and mortality. Though invasive methods such as tissue biopsy are considered the gold standard for diagnosis and disease monitoring, they have several limitations. Therefore, there is an urgent need to identify and validate non-invasive biomarkers for the early diagnosis, prognosis, and treatment of lung cancer for improved patient management. Despite recent progress in the identification of non-invasive biomarkers, currently, there is a shortage of reliable and accessible biomarkers demonstrating high sensitivity and specificity for LC detection. In this review, we aim to cover the latest developments in the field, including the utility of biomarkers that are currently used in LC screening and diagnosis. We comment on their limitations and summarise the findings and developmental stages of potential molecular contenders such as microRNAs, circulating tumour DNA, and methylation markers. Furthermore, we summarise research challenges in the development of biomarkers used for screening purposes and the potential clinical applications of newly discovered biomarkers.

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.

Benefits from Adjuvant Chemotherapy in Patients with Resected Non-Small Cell Lung Cancer: Possibility of Stratification by Gene Amplification of ACTN4 According to Evaluation of Metastatic Ability

Surgical treatment is the best curative treatment option for patients with non-small cell lung cancer (NSCLC), but some patients have recurrence beyond the surgical margin even after receiving curative surgery. Therefore, therapies with anti-cancer agents also play an important role perioperatively. In this paper, we review the current status of adjuvant chemotherapy in NSCLC and describe promising perioperative therapies, including molecularly targeted therapies and immune checkpoint inhibitors. Previously reported biomarkers of adjuvant chemotherapy for NSCLC are discussed along with their limitations. Adjuvant chemotherapy after resective surgery was most effective in patients with metastatic lesions located just outside the surgical margin; in addition, these metastatic lesions were the most sensitive to adjuvant chemotherapy. Thus, the first step in predicting patients who have sensitivity to adjuvant therapies is to perform a qualified evaluation of metastatic ability using markers such as actinin-4 (ACTN4). In this review, we discuss the potential use of biomarkers in patient stratification for effective adjuvant chemotherapy and, in particular, the use of ACTN4 as a possible biomarker for NSCLC.

CCT6A and CHCHD2 Are Coamplified with EGFR and Associated with the Unfavorable Clinical Outcomes of Lung Adenocarcinoma

Chaperonin containing TCP1 subunit 6A (CCT6A) and coiled-coil-helix-coiled-coil-helix domain containing 2 (CHCHD2) are located at the chromosome 7p11 region proximal to epidermal growth factor receptor (EGFR). However, the amplifications, expressions, and the prognostic effects of CCT6A and CHCDH2 in lung adenocarcinoma (LUAD) are unclear. Here, using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, we found that CCT6A was coamplified and coexpressed with EGFR in LUAD patients. CCT6A amplification was correlated with the unfavorable outcomes of LUAD. Moreover, CCT6A was upregulated in LUAD tissues, and CCT6A overexpression was correlated with the unfavorable relapse free survival or overall survival of LUAD. On the contrary, CCT6A was hypomethylated in LUAD, and CCT6A hypermethylation was correlated with the favorable overall survival of LUAD. Similar expression and methylation profiling of CCT6A were obtained in 479 lung normal tissues and 544 LUAD tissues collected from 11 independent datasets. In 1,462 LUAD patients from eight independent cohorts, CCT6A was also correlated with LUAD relapse-free survival or overall survival. Furthermore, CCT6A overexpression promoted the cell growth and invasion of LUAD. Identification of genes differentially expressed in CCT6A highly expressed LUAD patients revealed that CHCHD2 was the most correlated with CCT6A expression. CHCHD2 was coamplified with CCT6A. CHCHD2 was upregulated in LUAD tissues, and overexpression of CHCHD2 was correlated with the shorted relapse-free survival or overall survival of LUAD. Overall, our results revealed that CCT6A and CHCHD2 were coamplifying and coexpressing with EGFR and were correlated with the unfavorable clinical outcomes of LUAD.

CancerNet: a unified deep learning network for pan-cancer diagnostics

Background

Despite remarkable advances in cancer research, cancer remains one of the leading causes of death worldwide. Early detection of cancer and localization of the tissue of its origin are key to effective treatment. Here, we leverage technological advances in machine learning or artificial intelligence to design a novel framework for cancer diagnostics. Our proposed framework detects cancers and their tissues of origin using a unified model of cancers encompassing 33 cancers represented in The Cancer Genome Atlas (TCGA). Our model exploits the learned features of different cancers reflected in the respective dysregulated epigenomes, which arise early in carcinogenesis and differ remarkably between different cancer types or subtypes, thus holding a great promise in early cancer detection.

Results

Our comprehensive assessment of the proposed model on the 33 different tissues of origin demonstrates its ability to detect and classify cancers to a high accuracy (> 99% overall F-measure). Furthermore, our model distinguishes cancers from pre-cancerous lesions to metastatic tumors and discriminates between hypomethylation changes due to age related epigenetic drift and true cancer.

Conclusions

Beyond detection of primary cancers, our proposed computational model also robustly detects tissues of origin of secondary cancers, including metastatic cancers, second primary cancers, and cancers of unknown primaries. Our assessment revealed the ability of this model to characterize pre-cancer samples, a significant step forward in early cancer detection. Deployed broadly this model can deliver accurate diagnosis for a greatly expanded target patient population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04783-y.

Comparison of tumor and two types of paratumoral tissues highlighted epigenetic regulation of transcription during field cancerization in non-small cell lung cancer

Background

Field cancerization is the process in which a population of normal or pre-malignant cells is affected by oncogenic alterations leading to progressive molecular changes that drive malignant transformation. Aberrant DNA methylation has been implicated in early cancer development in non-small cell lung cancer (NSCLC); however, studies on its role in field cancerization (FC) are limited. This study aims to identify FC-specific methylation patterns that could distinguish between pre-malignant lesions and tumor tissues in NSCLC.

Methods

We enrolled 52 patients with resectable NSCLC and collected resected tumor (TUM), tumor-adjacent (ADJ) and tumor-distant normal (DIS) tissue samples, among whom 36 qualified for subsequent analyses. Methylation levels were profiled by bisulfite sequencing using a custom lung-cancer methylation panel.

Results

ADJ and DIS samples demonstrated similar methylation profiles, which were distinct from distinct from that of TUM. Comparison of TUM and DIS profiles led to identification of 1740 tumor-specific differential methylated regions (DMRs), including 1675 hypermethylated and 65 hypomethylated (adjusted P < 0.05). Six of the top 10 tumor-specific hypermethylated regions were associated with cancer development. We then compared the TUM, ADJ, and DIS to further identify the progressively aggravating aberrant methylations during cancer initiation and early development. A total of 332 DMRs were identified, including a predominant proportion of 312 regions showing stepwise increase in methylation levels as the sample drew nearer to the tumor (i.e. DIS < ADJ < TUM) and 20 regions showing a stepwise decrease pattern. Gene set enrichment analysis (GSEA) for KEGG and GO terms consistently suggested enrichment of DMRs located in transcription factor genes, suggesting a central role of epigenetic regulation of transcription factors in FC and tumorigenesis.

Conclusion

We revealed distinct methylation patterns between pre-malignant lesions and malignant tumors, suggesting the essential role of DNA methylation as an early step in pre-malignant field defects. Moreover, our study also identified differentially methylated genes, especially transcription factors, that could potentially be used as markers for lung cancer screening and for mechanistic studies of FC and early cancer development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01192-1.

The prognostic value of homeobox A9 (HOXA9) methylation in solid tumors: a systematic review and meta-analysis

Background

The prognosis of homeobox A9 (HOXA9) methylation have been assessed in a variety of cancers; nevertheless, the results remain undetermined due to discrete outcome and the limitations of small sample size. Therefore, we conducted a meta-analysis to explore the effect of HOXA9 methylation on the prognostic outcomes of patients with solid tumors.

Methods

Qualified studies were verified by searching PubMed, Excerpta Medica Database and Web of Science until September, 2020. Clinicopathological factors and hazard ratio (HR) of 95% confidence interval (95% CI) were selected. Subgroup analysis including carcinoma category, analysis method and sample size were adopted.

Results

In the meta-analysis 1,031 patients with solid carcinoma from 7 eligible investigations were involved. Among human cancer we discovered that the high HOXA9 methylation level was negative correlative with overall survival (OS) (HR =2.36; 95% CI: 1.70–3.26). In the subgroup analysis, we found HOXA9 methylation over-expression had statistical significance with poorer OS in lung cancer patients (HR =3.08, 95% CI: 1.70–5.55, P=0.002) and non-lung cancer (HR =2.10, 95% CI: 1.42–3.10, P=0.0002). Similar result was found in sample size. Greater than or equal to 100 (HR =2.31, 95% CI: 1.54–3.45, P<0.0001) and less than 100 (HR =2.45, 95% CI: 1.42–4.23, P=0.001).

Discussion

HOXA9 methylation has a significantly estimable biomarker of predicting poor prognosis and a potential target for therapy in solid malignant carcinoma from our meta-analysis.

Cathepsin B is a potential therapeutic target for coronavirus disease 2019 patients with lung adenocarcinoma

Coronavirus disease 2019 (COVID-19) was declared a serious global public health emergency. Hospitalization and mortality rates of lung cancer patients diagnosed with COVID-19 are higher than those of patients presenting with other cancers. However, the reasons for the outcomes being disproportionately severe in lung adenocarcinoma (LUAD) patients with COVID-19 remain elusive. The present study aimed to identify the possible causes for disproportionately severe COVID-19 outcomes in LUAD patients and determine a therapeutic target for COVID-19 patients with LUAD. We used publicly available data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and various bioinformatics tools to identify and analyze the genes implicated in SARS-CoV-2 infection in LUAD patients. Upregulation of the SARS-CoV-2 infection-related molecules dipeptidyl peptidase 4, basigin, cathepsin B (CTSB), methylenetetrahydrofolate dehydrogenase, and peptidylprolyl isomerase B rather than angiotensin-converting enzyme 2 may explain the relatively high susceptibility of LUAD patients to SARS-CoV-2 infection. CTSB was highly expressed in the LUAD tissues after SARS-CoV-2 infection, and its expression was positively correlated with immune cell infiltration and proinflammatory cytokine expression. These findings suggest that CTSB plays a vital role in the hyperinflammatory response in COVID-19 patients with LUAD and is a promising target for the development of a novel drug therapy for COVID-19 patients.

Extracellular Vesicles in Lung Cancer Metastasis and Their Clinical Applications

Extracellular vesicles (EVs) are heterogenous membrane-encapsulated vesicles secreted by every cell into the extracellular environment. EVs carry bioactive molecules, including proteins, lipids, DNA, and different RNA forms, which can be internalized by recipient cells, thus altering their biological characteristics. Given that EVs are commonly found in most body fluids, they have been widely described as mediators of communication in several physiological and pathological processes, including cancer. Moreover, their easy detection in biofluids makes them potentially useful candidates as tumor biomarkers. In this manuscript, we review the current knowledge regarding EVs and non-coding RNAs and their role as drivers of the metastatic process in lung cancer. Furthermore, we present the most recent applications for EVs and non-coding RNAs as cancer therapeutics and their relevance as clinical biomarkers.

Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm

Thyroid cancer (TC) is known with a high rate of persistence and recurrence. We aimed to develop a prognostic signature to monitor and assess the survival of TC patients. mRNA expression and methylation data were downloaded from the TCGA database. Then, R package methylmix was applied to construct a mixed model was used to identify methylation-driven genes (MDGs) according to the methylation levels. Furthermore, an MDGs based prognostic signature and predictive nomogram were constructed according to the analysis of univariate and multivariate Cox regression. Totally 62 methylation-driven genes that were mainly enriched in substrate-dependent cell migration, cellular response to mechanical stimulus, et al. were found in TC tissues. aldolase C (AldoC), C14orf62, dishevelled 1 (DVL1), and protein tyrosine phosphatase receptor type C (PTPRC) were identified to be significantly related to patients' survival, and may serve as independent prognostic biomarkers for TC. Additionally, the prognostic methylation signature and a novel prognostic, predictive nomogram was established based on the methylation level of 4 MDGs. In this study, we developed a 4-MDGs based prognostic model, which might be the potential predictors for the survival rate of TC patients, and this findings might provide a novel sight for accurate monitoring and prognosis assessment.

Identification of the molecular function of tripartite motif containing 58 in human lung cancer

Lung cancer is a major public health problem worldwide, with a high associated incidence and mortality. In the present study, novel epigenetic signatures were identified through genome-wide DNA methylation microarrays. The results revealed that tripartite motif containing 58 (TRIM58), a potential tumor suppressor gene exhibited high methylation and low expression in lung cancer tissue samples compared with normal tissues. Receiver operating characteristic curve analysis demonstrated that TRIM58 may be a promising early diagnostic indicator of lung cancer. In addition, the present study analyzed the role of TRIM58 in tumorigenesis and development in lung cancer A549 cells. Wound healing assay and transwell migration assay were used to investigate cell migration, and flow cytometry analysis was used to detect apoptosis. Silencing TRIM58 accelerated the proliferation and migration of lung cancer cells. In contrast, the overexpression of TRIM58 significantly inhibited the proliferation and migration of lung cancer cells and promoted apoptosis. Gene set enrichment analysis revealed that TRIM58 expression was negatively correlated with MYC targets, G₂M checkpoints and the mTORC1 signaling pathway. These results of the present study suggested that TRIM58, a potential tumor suppressor gene may serve as a novel diagnostic biomarker and therapeutic target in human lung cancer.

TMEM100 negatively regulated by microRNA‑106b facilitates cellular apoptosis by suppressing survivin expression in NSCLC

Non‑small cell lung cancer (NSCLC) is a common malignant tumour. Nevertheless, the 5‑year survival rate of NSCLC patients remains poor. Thus, identifying critical factors involved in regulating the progression of NSCLC is important for providing potential treatment targets. In the present study, it was observed that transmembrane protein 100 (TMEM100) was significantly downregulated in NSCLC tissues compared with paired peritumoral tissues. Decreased TMEM100 expression was associated with poor clinical outcomes in NSCLC patients. Moreover, TMEM100 overexpression inhibited colony formation and facilitated apoptosis by suppressing survivin expression in NSCLC cells, whereas TMEM100 knockdown had the opposite effect. In addition, microRNA (miR)‑106b, a miR with controversial roles in different human cancers, was upregulated in NSCLC and directly downregulated TMEM100 expression. The roles of miR‑106b in cell survival were mitigated by the restoration of TMEM100. The aforementioned results indicated that TMEM100 induced cell apoptosis and inhibited cell survival by serving as a tumour suppressor and that miR‑106b‑mitigatedTMEM100 expression defined a potentially oncogenic pathway in NSCLC.

DNA hypermethylation of the ZNF132 gene participates in the clinicopathological aggressiveness of 'pan-negative'-type lung adenocarcinomas

Although some previous studies have examined epigenomic alterations in lung adenocarcinomas, correlations between epigenomic events and genomic driver mutations have not been fully elucidated. Single-CpG resolution genome-wide DNA methylation analysis with the Infinium HumanMethylation27 BeadChip was performed using 162 paired samples of adjacent normal lung tissue (N) and the corresponding tumorous tissue (T) from patients with lung adenocarcinomas. Correlations between DNA methylation data on the one hand and clinicopathological parameters and genomic driver mutations, i.e. mutations of EGFR, KRAS, BRAF and HER2 and fusions involving ALK, RET and ROS1, were examined. DNA methylation levels in 12 629 probes from N samples were significantly correlated with recurrence-free survival. Principal component analysis revealed that distinct DNA methylation profiles at the precancerous N stage tended not to induce specific genomic driver aberrations. Most of the genes showing significant DNA methylation alterations during transition from N to T were shared by two or more driver aberration groups. After small interfering RNA knockdown of ZNF132, which showed DNA hypermethylation only in the pan-negative group and was correlated with vascular invasion, the proliferation, apoptosis and migration of cancer cell lines were examined. ZNF132 knockdown led to increased cell migration ability, rather than increased cell growth or reduced apoptosis. We concluded that DNA hypermethylation of the ZNF132 gene participates in the clinicopathological aggressiveness of ‘pan-negative’ lung adenocarcinomas. In addition, DNA methylation alterations at the precancerous stage may determine tumor aggressiveness, and such alterations that accumulate after driver mutation may additionally modify clinicopathological features through alterations of gene expression.

In silico analysis identifies neuropilin-1 as a potential therapeutic target for SARS-Cov-2 infected lung cancer patients

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), and is highly contagious and pathogenic. TMPRSS2 and Neuropilin-1, the key components that facilitate SARS-CoV-2 infection, are potential targets for treatment of COVID-19. Here we performed a comprehensive analysis on NRP1 and TMPRSS2 in lung to provide information for treating comorbidity of COVID-19 with lung cancer. NRP1 is widely expressed across all the human tissues while TMPRSS2 is expressed in a restricted pattern. High level of NRP1 associates with worse prognosis in multiple cancers, while high level of TMPRSS2 is associated with better survival of Lung Adenocarcinoma (LUAD). Moreover, NRP1 positively correlates with the oncogenic Cancer Associated Fibroblast (CAF), macrophage and endothelial cells infiltration, negatively correlates with infiltration of CD8⁺ T cell, the tumor killer cell in Lung Squamous cell carcinoma (LUSC). TMPRSS2 shows negative correlation with the oncogenic events in LUAD. RNA-seq data show that NRP1 level is slightly decreased in peripheral blood of ICU admitted COVID-19 patients, unaltered in lung, while TMPRSS2 level is significantly decreased in lung of COVID-19 patients. Our analysis suggests NRP1 as a potential therapeutic target, while sets an alert on targeting TMPRSS2 for treating comorbidity of COVID-19 and lung cancers.

Vascular endothelial cell-derived exosomal miR-30a-5p inhibits lung adenocarcinoma malignant progression by targeting CCNE2

This study tried to explore the molecular mechanism underlying progression of lung adenocarcinoma (LUAD), and discuss the extracellular communication between cancer cells and vascular endothelial cells. Roughly, differential analysis was carried out to note that miR-30a-5p was lowly expressed in LUAD while CCNE2 was highly expressed. Cell functional experiments demonstrated that overexpressed miR-30a-5p led to suppressed cell abilities in proliferation, migration and invasion. Dual-luciferase reporter gene assay and RNA immunoprecipitation verified the binding of miR-30a-5p and CCNE2, as well as decreased mRNA and protein expression of CCNE2 with miR-30a-5p overexpression. Simultaneous upregulation of miR-30a-5p and CCNE2 reversed the promotion of CCNE2 on malignant behaviors of LUAD cells. In vivo mice experiments exhibited that high miR-30a-5p expression hindered tumor growth. Additionally, miR-30a-5p was localized on the Extracellular Vesicles miRNA (EVmiRNA) database.MiR-30a-5p was abundant in exosomes derived from vascular endothelial cells. To validate that miR-30a-5p could be delivered to LUAD cells via exosomes and then make an effect, exosomes from vascular endothelial cells were firstly extracted and identified by transmission electron microscopy and detection of exosomal marker proteins (Alix, CD63, TSG101). Sequentially, the extracted exosomes were labeled with PKH67 to note that exosomes could be internalized by cancer cells. Further experiments indicated that miR-30a-5p was increased in cancer cells co-cultured with exosomes, which in turn suppressed cell malignant behaviors and made cell cycle arrest. In all, our findings clarified that exosomes derived from vascular endothelial cells delivered miR-30a-5p to LUAD cells to affect tumor malignant progression via the miR-30a-5p/CCNE2 axis.

Transcriptome Based Estrogen Related Genes Biomarkers for Diagnosis and Prognosis in Non-small Cell Lung Cancer

Background

Lung cancer is the tumor with the highest morbidity and mortality, and has become a global public health problem. The incidence of lung cancer in men has declined in some countries and regions, while the incidence of lung cancer in women has been slowly increasing. Therefore, the aim is to explore whether estrogen-related genes are associated with the incidence and prognosis of lung cancer.

Methods

We obtained all estrogen receptor genes and estrogen signaling pathway genes in The Cancer Genome Atlas (TCGA), and then compared the expression of each gene in tumor tissues and adjacent normal tissues for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) separately. Survival analysis was performed of the differentially expressed genes in LUAD and LUSC patients separately. The diagnostic and prognostic values of the candidate genes were validated in the Gene Expression Omnibus (GEO) datasets.

Results

We found 5 estrogen receptor genes and 66 estrogen pathway genes in TCGA. A total of 50 genes were differently expressed between tumor tissues and adjacent normal tissues and 6 of the 50 genes were related to the prognosis of LUAD in TCGA. 56 genes were differently expressed between tumor tissues and adjacent normal tissues and none of the 56 genes was related to the prognosis of LUSC in TCGA. GEO datasets validated that the 6 genes (SHC1, FKBP4, NRAS, PRKCD, KRAS, ADCY9) had different expression between tumor tissues and adjacent normal tissues in LUAD, and 3 genes (FKBP4, KRAS, ADCY9) were related to the prognosis of LUAD.

Conclusions

The expressions of FKBP4 and ADCY9 are related to the pathogenesis and prognosis of LUAD. FKBP4 and ADCY9 may serve as biomarkers in LUAD screening and prognosis prediction in clinical settings.

Tumor suppressor gene DLC1: Its modifications, interactive molecules, and potential prospects for clinical cancer application

Deleted in liver cancer 1 (DLC1) is a recognized tumor suppressor gene that negatively regulates Rho family proteins by hydrolyzing the active GTP-bound state to its inactive GDP-bound state. Active Rho proteins play a positive role in tumorigenesis. Numerous in vitro and in vivo experiments have shown that DLC1 is downregulated or inactivated in various solid tumors, which may be due to the following five reasons: genomic deletion, epigenetic modification and ubiquitin-dependent proteasomal degradation may cause DLC1 underexpression; phosphorylation at the post-translation level may cause DLC1 inactivation; and failure to localize at focal adhesions (FAs) may prevent DLC1 from exerting full activity. All of the causes could be attributed to molecular binding. Experimental evidence suggests that direct or indirect targeting of DLC1 is feasible for cancer treatment. Therefore, elucidating the interaction of DLC1 with its binding partners might provide novel targeted therapies for cancer. In this review, we summarized the binding partners of DLC1 at both the gene and protein levels and expounded a variety of anticancer drugs targeting DLC1 to provide information about DLC1 as a cancer diagnostic indicator or therapeutic target.

A highly expressed mRNA signature for predicting survival in patients with stage I/II non-small-cell lung cancer after operation

There is an urgent need to identify novel biomarkers that predict the prognosis of patients with NSCLC. In this study,we aim to find out mRNA signature closely related to the prognosis of NSCLC by new algorithm of bioinformatics. Identification of highly expressed mRNA in stage I/II patients with NSCLC was performed with the “Limma” package of R software. Survival analysis of patients with different mRNA expression levels was subsequently calculated by Cox regression analysis, and a multi-RNA signature was obtained by using the training set. Kaplan–Meier estimator, log-rank test and receiver operating characteristic (ROC) curves were used to analyse the predictive ability of the multi-RNA signature. RT-PCR used to verify the expression of the multi-RNA signature, and Westernblot used to verify the expression of proteins related to the multi-RNA signature. We identified fifteen survival-related mRNAs in the training set and classified the patients as high risk or low risk. NSCLC patients with low risk scores had longer disease-free survival than patients with high risk scores. The fifteen-mRNA signature was an independent prognostic factor, as shown by the ROC curve. ROC curve also showed that the combined model of the fifteen-mRNA signature and tumour stage had higher precision than stage alone. The expression of fifteen mRNAs and related proteins were higher in stage II NSCLC than in stage I NSCLC. Multi-gene expression profiles provide a moderate prognostic tool for NSCLC patients with stage I/II disease.

The prognostic impact of circulating homeobox A9 methylated DNA in advanced non-small cell lung cancer

BACKGROUND

The homeobox A9 gene encodes a transcription factor, and aberrantly methylated homeobox A9 in the circulation has been suggested as a prognostic marker in early stage non-small cell lung cancer (NSCLC). The aim of the present study was to investigate the prognostic impact of methylated homeobox A9 in plasma from patients with advanced NSCLC.

METHODS

Blood samples were prospectively collected from patients with NSCLC stage III and IV receiving standard first line chemotherapy. Sampling took place before treatment initiation and subsequently before each treatment cycle. Plasma was stored at -80 °C until analysis. DNA was extracted, and following bisulfite conversion methylated homeobox A9 was analyzed by methylation specific droplet digital polymerase chain reaction. Detection of methylated homeobox A9 was assessed as a binary variable. The primary endpoint was overall survival (OS).

RESULTS

A total of 231 patients were included. At baseline methylated homeobox A9 was detected in 78.5% of the patients with a clear correlation to survival. The median OS for patients with and without detectable methylated homeobox A9 was 7.4 and 11.1 months, respectively [hazard ratio (HR) 1.79, 95% confidence interval (CI): 1.35-2.38, P<0.001]. The difference increased after the first cycle of treatment. At this time point the median OS was 6.2 and 15.6 months for patients with and without detectable methylated homeobox A9, respectively (HR 2.07, 95% CI: 1.58-2.73, P<0.001). The independent prognostic impact of detectable methylated homeobox A9 after one treatment cycle assessed by multiple Cox regression including known prognostic factors resulted in a HR of 3.79 (2.19-6.54, P<0.001) compared to undetectable methylated homeobox A9.

CONCLUSIONS

Measurable methylated homeobox A9 after the first treatment cycle may serve as a valuable prognostic marker in patients with advanced NSCLC. Routine clinical application with treatment reconsideration calls for further studies, preferably in prospective clinical trials.

Functional Signatures in Non-Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis of Sex-Based Differences in Transcriptomic Studies

While studies have established the existence of differences in the epidemiological and clinical patterns of lung adenocarcinoma between male and female patients, we know relatively little regarding the molecular mechanisms underlying such sex-based differences. In this study, we explore said differences through a meta-analysis of transcriptomic data. We performed a meta-analysis of the functional profiling of nine public datasets that included 1366 samples from Gene Expression Omnibus and The Cancer Genome Atlas databases. Meta-analysis results from data merged, normalized, and corrected for batch effect show an enrichment for Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways related to the immune response, nucleic acid metabolism, and purinergic signaling. We discovered the overrepresentation of terms associated with the immune response, particularly with the acute inflammatory response, and purinergic signaling in female lung adenocarcinoma patients, which could influence reported clinical differences. Further evaluations of the identified differential biological processes and pathways could lead to the discovery of new biomarkers and therapeutic targets. Our findings also emphasize the relevance of sex-specific analyses in biomedicine, which represents a crucial aspect influencing biological variability in disease.

Denoising Autoencoder, A Deep Learning Algorithm, Aids the Identification of A Novel Molecular Signature of Lung Adenocarcinoma

Precise biomarker development is a key step in disease management. However, most of the published biomarkers were derived from a relatively small number of samples with supervised approaches. Recent advances in unsupervised machine learning promise to leverage very large datasets for making better predictions of disease biomarkers. Denoising autoencoder (DA) is one of the unsupervised deep learning algorithms, which is a stochastic version of autoencoder techniques. The principle of DA is to force the hidden layer of autoencoder to capture more robust features by reconstructing a clean input from a corrupted one. Here, a DA model was applied to analyze integrated transcriptomic data from 13 published lung cancer studies, which consisted of 1916 human lung tissue samples. Using DA, we discovered a molecular signature composed of multiple genes for lung adenocarcinoma (ADC). In independent validation cohorts, the proposed molecular signature is proved to be an effective classifier for lung cancer histological subtypes. Also, this signature successfully predicts clinical outcome in lung ADC, which is independent of traditional prognostic factors. More importantly, this signature exhibits a superior prognostic power compared with the other published prognostic genes. Our study suggests that unsupervised learning is helpful for biomarker development in the era of precision medicine.

Noninvasive Diagnostics for Early Detection of Lung Cancer: Challenges and Potential with a Focus on Changes in DNA Methylation

Lung cancer remains the leading cause of cancer deaths in the United States and the world. Early detection of this disease can reduce mortality, as demonstrated for low-dose computed tomography (LDCT) screening. However, there remains a need for improvements in lung cancer detection to complement LDCT screening and to increase adoption of screening. Molecular changes in the tumor, and the patient's response to the presence of the tumor, have been examined as potential biomarkers for diagnosing lung cancer. There are significant challenges to developing an effective biomarker with sufficient sensitivity and specificity for the early detection of lung cancer, particularly the detection of circulating tumor DNA, which is present in very small quantities. We will review approaches to develop biomarkers for the early detection of lung cancer, with special consideration to detection of rare tumor events, focus on the use of DNA methylation-based detection in plasma and sputum, and discuss the promise and challenges of lung cancer early detection. Plasma-based detection of lung cancer DNA methylation may provide a simple cost-effective method for the early detection of lung cancer.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

A gene-based survival score for lung adenocarcinoma by multiple transcriptional datasets analysis

Background

Lung adenocarcinoma (LUAD) remains a crucial factor endangering human health. Gene-based clinical predictions could be of great help for cancer intervention strategies. Here, we tried to build a gene-based survival score (SS) for LUAD via analyzing multiple transcriptional datasets.

Methods

We first acquired differentially expressed genes between tumors and normal tissues from intersections of four LUAD datasets. Next, survival-related genes were preliminarily unscrambled by univariate Cox regression and further filtrated by LASSO regression. Then, we applied PCA to establish a comprehensive SS based on survival-related genes. Subsequently, we applied four independent LUAD datasets to evaluate prognostic prediction of SS. Moreover, we explored associations between SS and clinicopathological features. Furthermore, we assessed independent predictive value of SS by multivariate Cox analysis and then built prognostic models based on clinical stage and SS. Finally, we performed pathway enrichments analysis and investigated immune checkpoints expression underlying SS in four datasets.

Results

We established a 13 gene-based SS, which could precisely predict OS and PFS of LUAD. Close relations were elicited between SS and canonical malignant indictors. Furthermore, SS could serve as an independent risk factor for OS and PFS. Besides, the predictive efficacies of prognostic models were also reasonable (C-indexes: OS, 0.7; PFS, 0.7). Finally, we demonstrated enhanced cell proliferation and immune escape might account for high clinical risk of SS.

Conclusions

We built a 13 gene-based SS for prognostic prediction of LUAD, which exhibited wide applicability and could contribute to LUAD management.

miR-146b Reverses epithelial-mesenchymal transition via targeting PTP1B in cisplatin-resistance human lung adenocarcinoma cells

Epithelial-mesenchymal transformation (EMT) is associated with drug resistance in human lung adenocarcinoma cells, but its specific mechanism has not been clarified. In this study, we investigated the effect of miRNA-146b on EMT in cisplatin (DDP) resistant human lung adenocarcinoma cells and the corresponding mechanism. Cisplatin resistant (CR) human lung adenocarcinoma cells (A549/DDP and H1299/DDP) were established, and the EMT characteristics and invasion and metastasis ability of CR cells were determined by tumor cell-related biological behavior experiments. The role of miR-146b in EMT of CR cells was determined by in vitro functional test. The targeted binding of miR-146b to protein tyrosine phosphatase 1B (PTP1B) was verified by biological information and double luciferin gene reporting experiments. The effect of miR-146b on tumor growth and EMT phenotype in vivo was investigated by establishing the xenotransplantation mouse model. Compared with the control group, H1299/DDP and A549/DDP cells showed the enhanced EMT phenotypes, invasion and migration ability. Besides, miR-146b was lowly expressed in H1299/DDP and A549/DDP cells. More importantly, overexpressed miR-146b could specifically bind to PTP1B, thus inhibiting the EMT process and ultimately reducing CR in H1299/DDP and A549/DDP cells. Finally, overexpressed miR-146b observably inhibited tumor growth in xenograft model mice and inhibited the EMT phenotype of A549/DDP cells in vivo by regulating the expressions of EMT-related proteins. Overexpressed miR-146b could reverse the EMT phenotype of CR lung adenocarcinoma cells by targeting PTP1B, providing new therapeutic directions for CR of lung adenocarcinoma cells.

Loss of miR-145-5p Causes Ceruloplasmin Interference with PHD-Iron Axis and HIF-2α Stabilization in Lung Adenocarcinoma-Mediated Angiogenesis

For decades, lung cancer has been the leading cause of cancer-related death worldwide. Hypoxia-inducible factors (HIFs) play critical roles in mediating lung cancer development and metastasis. The present study aims to clarify how HIF’s over-activation affects lung cancer angiogenesis not only in a normoxic condition, but also a hypoxic niche. Our study shows that human lung cancer exhibits elevated levels of ceruloplasmin (CP), which has a negative impact on the prognosis of patients. CP affects the cellular Fe²⁺ level, which inactivates prolyl hydroxylase (PHD) 1 and 2, resulting in HIF-2α enhancement. Increased HIF-2α leads to vascular endothelial growth factor-A (VEGF-A) secretion and angiogenesis. The expression of CP is under the epigenetic control of miR-145-5p. Restoration of miR-145-5p by miRNA mimics transfection decreases CP expression, increases Fe²⁺ and PHD1/2 levels and HIF hydroxylation while reduced HIF-2α levels resulting in the inhibition of tumor angiogenesis. In contrast, inhibition of miR-145-5p by miRNA inhibitors increases the expression of CP and VEGF-A in lung cancer cells. Significantly, miR-145-5p expression is lost in the tumor samples of lung cancer patients, and low miR-145-5p expression is strongly correlated with a shorter overall survival time. In conclusion, the current study reveals the clinical importance and prognostic value of miR-145-5p and CP. It identifies a unique mechanism of HIF-2α over-activation, which is mediated by iron imbalance of the iron-PHD coupling that modulates tumor angiogenesis.

Circulating miRNAs as Biomarkers in Aggressive B Cell Lymphomas

B cell lymphomas are heterogeneous malignancies of hematological origin with vastly different biology and clinical outcomes. Histopathology of tissue biopsies and image-based assessment guide clinical decisions. Given that tissue biopsies cannot be frequently repeated and will not inform on systemic responses to the treatment, more accessible biomarkers, such as circulating miRNAs, are considered. Aberrant miRNA expression in lymphoma tissues and ongoing immune reactions may lead to miRNA alterations in circulation. miRNAs bound to extracellular vesicles (EVs) are of interest because of their role in intercellular communication and organ crosstalk. Herein, we highlight the role of miRNAs and EVs in B cell lymphomagenesis and explain how circulating miRNAs may be turned into robust liquid biopsy tests for aggressive B cell lymphoma.

Construction and Analysis of a ceRNA Network Reveals Potential Prognostic Markers in Colorectal Cancer

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide and is derived from an accumulation of genetic and epigenetic changes. This study explored potential prognostic markers in CRC via the construction and in-depth analysis of a competing endogenous RNA (ceRNA) network, which was generated through a three-step process. First, we screened candidate hub genes in CRC as the primary gene markers to survey their related regulatory non-coding RNAs, miRNAs. Second, the interacting miRNAs were used to search for associated lncRNAs. Thus, candidate RNAs were first constructed into ceRNA networks based on close associations with miRNAs. Further analysis at the isomiR level was also performed for each miRNA locus to understand the detailed expression patterns of the multiple variants. Finally, RNAs were performed an in-depth analysis of expression correlations, which contributed to further screening and validation of potential RNAs with close correlations to each other. Using this approach, nine hub genes, 13 related miRNAs, and 29 candidate lncRNAs were collected and used to construct the ceRNA network. Further in-depth analysis identified the MFAP5-miR-200b-3p-AC005154.6 axis as a potential prognostic marker in CRC. MFAP5 and miR-200b-3p have previously been reported to play important roles in tumorigenesis. These RNAs showed potential prognostic values, and the combination of them may have more sensitivity than using them alone. In conclusion, MFAP5, miR-200b-3p, and AC005154.6 may have potential prognostic value in CRC and may provide a prognostic reference for this patient population.

OSluca: An Interactive Web Server to Evaluate Prognostic Biomarkers for Lung Cancer

Lung cancer is the principal cause of leading cancer-related incidence and mortality in the world. Various studies have excavated the potential prognostic biomarkers for cancer patients based on gene expression profiles. However, most of these reported biomarkers lack independent validation in multiple cohorts. Herein, we collected 35 datasets with long-term follow-up clinical information from TCGA (2 cohorts), GEO (32 cohorts), and Roepman study (1 cohort), and developed a web server named OSluca (Online consensus Survival for Lung Cancer) to assess the prognostic value of genes in lung cancer. The input of OSluca is an official gene symbol, and the output web page of OSluca displays the survival analysis summary with a forest plot and a survival table from Cox proportional regression in each cohort and combined cohorts. To test the performance of OSluca, 104 previously reported prognostic biomarkers in lung carcinoma were evaluated in OSluca. In conclusion, OSluca is a highly valuable and interactive prognostic web server for lung cancer. It can be accessed at http:// bioinfo.henu.edu.cn/LUCA/LUCAList.jsp.

Diagnostic, progressive and prognostic performance of m6A methylation RNA regulators in lung adenocarcinoma

Background: N6-methyladenosine (m⁶A) RNA methylation is dynamically and reversibly regulated by methyl-transferases ("writers"), binding proteins ("readers"), and demethylases ("erasers"). The m⁶A is restored to adenosine and thus to achieve demethylation modification. The abnormality of m⁶A epigenetic modification in cancer has been increasingly attended. However, we are rarely aware of its diagnostic, progressive and prognostic performance in lung adenocarcinoma (LUAD). Methods and Results: The expression of 13 widely reported m⁶A RNA regulators in LUAD and normal samples were systematically analyzed. There were 12 m⁶A RNA methylation genes displaying aberrant expressions, and an 11-gene diagnostic score model was finally built (Diagnostic score =0.033*KIAA1429+0.116*HNRNPC+0.115*RBM15-0.067* METTL3-0.048*ZC3H13-0.221*WTAP+0.213*YTHDF1-0.132*YTHDC1-0.135* FTO+0.078*YTHDF2+0.014*ALKBH5). Receiver operating characteristic (ROC) analysis was performed to demonstrate superiority of the diagnostic score model (Area under the curve (AUC) was 0.996 of training cohort, P<0.0001; AUC was 0.971 of one validation cohort-GSE75037, P<0.0001; AUC was 0.878 of another validation cohort-GSE63459, P<0.0001). In both training and validation cohorts, YTHDC2 was associated with tumor stage (P<0.01), while HNRNPC was up expressed in progressed tumor (P<0.05). Besides, WTAP, RBM15, KIAA1429, YTHDF1, and YTHDF2 were all up expressed for TP53 mutation. Furthermore, using least absolute shrinkage and selection operator (lasso) regression analysis, a ten-gene risk score model was built. Risk score=0.169*ALKBH5-0.159*FTO+0.581*HNRNPC-0.348* YTHDF2-0.265*YTHDF1-0.123*YTHDC2+0.434*RBM15+0.143*KIAA1429-0.200*WTAP-0.310*METTL3. There existed correlation between the risk score and TNM stage (P<0.01), lymph node stage (P<0.05), gender (P<0.05), living status (P<0.001). Univariate and multivariate Cox regression analyses of relevant clinicopathological characters and the risk score revealed risk score was an independent risk factor of lung adenocarcinoma (HR: 2.181, 95%CI (1.594-2.984), P<0.001). Finally, a nomogram was built to facilitate clinicians to predict outcome. Conclusions: m⁶A epigenetic modification took part in the progression, and provided auxiliary diagnosis and prognosis of LUAD.

Genome-wide DNA methylation profile of early-onset endometrial cancer: its correlation with genetic aberrations and comparison with late-onset endometrial cancer

The present study was performed to clarify the significance of DNA methylation alterations during endometrial carcinogenesis. Genome-wide DNA methylation analysis and targeted sequencing of tumor-related genes were performed using the Infinium MethylationEPIC BeadChip and the Ion AmpliSeq Cancer Hotspot Panel v2, respectively, for 31 samples of normal control endometrial tissue from patients without endometrial cancer and 81 samples of endometrial cancer tissue. Principal component analysis revealed that tumor samples had a DNA methylation profile distinct from that of control samples. Gene Ontology enrichment analysis revealed significant differences of DNA methylation at 1034 CpG sites between early-onset endometrioid endometrial cancer (EE) tissue (patients aged ≤40 years) and late-onset endometrioid endometrial cancer (LE) tissue, which were accumulated among 'transcriptional factors'. Mutations of the CTNNB1 gene or DNA methylation alterations of genes participating in Wnt signaling were frequent in EEs, whereas genetic and epigenetic alterations of fibroblast growth factor signaling genes were observed in LEs. Unsupervised hierarchical clustering grouped EE samples in Cluster EA (n = 22) and samples in Cluster EB (n = 12). Clinicopathologically less aggressive tumors tended to be accumulated in Cluster EB, and DNA methylation levels of 18 genes including HOXA9, HOXD10 and SOX11 were associated with differences in such aggressiveness between the two clusters. We identified 11 marker CpG sites that discriminated EB samples from EA samples with 100% sensitivity and specificity. These data indicate that genetically and epigenetically different pathways may participate in the development of EEs and LEs, and that DNA methylation profiling may help predict tumors that are less aggressive and amenable to fertility preservation treatment.

Identification of lung adenocarcinoma biomarkers based on bioinformatic analysis and human samples

Lung adenocarcinoma is one of the most common malignant tumors worldwide. Although efforts have been made to clarify its pathology, the underlying molecular mechanisms of lung adenocarcinoma are still not clear. The microarray datasets GSE75037, GSE63459 and GSE32863 were downloaded from the Gene Expression Omnibus (GEO) database to identify biomarkers for effective lung adenocarcinoma diagnosis and therapy. The differentially expressed genes (DEGs) were identified by GEO2R, and function enrichment analyses were conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The STRING database and Cytoscape software were used to construct and analyze the protein-protein interaction network (PPI). We identified 376 DEGs, consisting of 83 upregulated genes and 293 downregulated genes. Functional and pathway enrichment showed that the DEGs were mainly focused on regulation of cell proliferation, the transforming growth factor β receptor signaling pathway, cell adhesion, biological adhesion, and responses to hormone stimulus. Sixteen hub genes were identified and biological process analysis showed that these 16 hub genes were mainly involved in the M phase, cell cycle phases, the mitotic cell cycle, and nuclear division. We further confirmed the two genes with the highest node degree, DNA topoisomerase IIα (TOP2A) and aurora kinase A (AURKA), in lung adenocarcinoma cell lines and human samples. Both these genes were upregulated and associated with larger tumor size. Upregulation of AURKA in particular, was associated with lymphatic metastasis. In summary, identification of the DEGs and hub genes in our research enables us to elaborate the molecular mechanisms underlying the genesis and progression of lung adenocarcinoma and identify potential targets for the diagnosis and treatment of lung adenocarcinoma.

Downregulation of hsa-microRNA-204-5p and identification of its potential regulatory network in non-small cell lung cancer: RT-qPCR, bioinformatic- and meta-analyses

Background

Pulmonary malignant neoplasms have a high worldwide morbidity and mortality, so the study of these malignancies using microRNAs (miRNAs) has attracted great interest and enthusiasm. The aim of this study was to determine the clinical effect of hsa-microRNA-204-5p (miR-204-5p) and its underlying molecular mechanisms in non-small cell lung cancer (NSCLC).

Methods

Expression of miR-204-5p was investigated by real-time quantitative PCR (RT-qPCR). After data mining from public online repositories, several integrative assessment methods, including receiver operating characteristic (ROC) curves, hazard ratios (HR) with 95% confidence intervals (95% CI), and comprehensive meta-analyses, were conducted to explore the expression and clinical utility of miR-204-5p. The potential objects regulated and controlled by miR-204-5p in the course of NSCLC were identified by estimated target prediction and analysis. The regulatory network of miR-204-5p, with its target genes and transcription factors (TFs), was structured from database evidence and literature references.

Results

The expression of miR-204-5p was downregulated in NSCLC, and the downtrend was related to gender, histological type, vascular invasion, tumor size, clinicopathologic grade and lymph node metastasis (P<0.05). MiR-204-5p was useful in prognosis, but was deemed unsuitable at present as an auxiliary diagnostic or prognostic risk factor for NSCLC due to the lack of statistical significance in meta-analyses and absence of large-scale investigations. Gene enrichment and annotation analyses identified miR-204-5p candidate targets that took part in various genetic activities and biological functions. The predicted TFs, like MAX, MYC, and RUNX1, interfered in regulatory networks involving miR-204-5p and its predicted hub genes, though a modulatory loop or axis of the miRNA-TF-gene that was out of range with shortage in database prediction, experimental proof and literature confirmation.

Conclusions

The frequently observed decrease in miR-204-5p was helpful for NSCLC diagnosis. The estimated target genes and TFs contributed to the anti-oncogene effects of miR-204-5p.

Identification of key genes by integrating DNA methylation and next-generation transcriptome sequencing for esophageal squamous cell carcinoma

Aberrant DNA methylation leads to abnormal gene expression, making it a significant regulator in the progression of cancer and leading to the requirement for integration of gene expression with DNA methylation. Here, we identified 120 genes demonstrating an inverse correlation between DNA methylation and mRNA expression in esophageal squamous cell carcinoma (ESCC). Sixteen key genes, such as SIX4, CRABP2, and EHD3, were obtained by filtering 10 datasets and verified in paired ESCC samples by qRT-PCR. 5-Aza-dC as a DNA methyltransferase (DNMT) inhibitor could recover their expression and inhibit clonal growth of cancer cells in seven ESCC cell lines. Furthermore, 11 of the 16 genes were correlated with OS (overall survival) and DFS (disease-free survival) in 125 ESCC patients. ChIP-Seq data and WGBS data showed that DNA methylation and H3K27ac histone modification of these key genes displayed inverse trends, suggesting that there was collaboration between DNA methylation and histone modification in ESCC. Our findings illustrate that the integrated multi-omics data (transcriptome and epigenomics) can accurately obtain potential prognostic biomarkers, which may provide important insight for the effective treatment of cancers.

Integrative analysis of DNA methylation-driven genes for the prognosis of lung squamous cell carcinoma using MethylMix

Background: DNA methylation acts as a key component in epigenetic modifications of genomic function and functions as disease-specific prognostic biomarkers for lung squamous cell carcinoma (LUSC). This present study aimed to identify methylation-driven genes as prognostic biomarkers for LUSC using bioinformatics analysis. Materials and Methods: Differentially expressed RNAs were obtained using the edge R package from 502 LUSC tissues and 49 adjacent non-LUSC tissues. Differentially methylated genes were obtained using the limma R package from 504 LUSC tissues and 69 adjacent non-LUSC tissues. The methylation-driven genes were obtained using the MethylMix R package from 500 LUSC tissues with matched DNA methylation data and gene expression data and 69 non-LUSC tissues with DNA methylation data. Gene ontology and ConsensusPathDB pathway analysis were performed to analyze the functional enrichment of methylation-driven genes. Univariate and multivariate Cox regression analyses were performed to identify the independent effect of differentially methylated genes for predicting the prognosis of LUSC. Results: A total of 44 methylation-driven genes were obtained. Univariate and multivariate Cox regression analyses showed that twelve aberrant methylated genes (ATP6V0CP3, AGGF1P3, RP11-264L1.4, HIST1H4K, LINC01158, CH17-140K24.1, CTC-523E23.14, ADCYAP1, COX11P1, TRIM58, FOXD4L6, CBLN1) were entered into a Cox predictive model associated with overall survival in LUSC patients. Methylation and gene expression combined survival analysis showed that the survival rate of hypermethylation and low-expression of DQX1 and WDR61 were low. The expression of DQX1 had a significantly negatively correlated with the methylation site cg02034222. Conclusion: Methylation-driven genes DQX1 and WDR61 might be potential biomarkers for predicting the prognosis of LUSC.

Circulating MicroRNAs as Potential Biomarkers for Lung Cancer

Lung cancer is the number one cause of cancer-related mortality worldwide. To improve disease outcome, it is crucial to implement biomarkers into the clinics which assist physicians in their decisions regarding diagnosis, prognosis, as well as prediction of treatment response. Liquid biopsy offers an opportunity to obtain such biomarkers in a minimal invasive manner by retrieving tumor-derived material from body fluids of the patient. The abundance of circulating microRNAs is known to be altered in disease and has therefore been studied extensively as a cancer biomarker. Circulating microRNAs present a variety of favorable characteristics for application as liquid biopsy-based biomarkers, including their high stability, relatively high abundance, and presence is nearly all body fluids. Although the application of circulating microRNAs for the management of lung cancer has not entered the clinics yet, several studies showed their utility for diagnosis, prognosis, and efficacy prediction of various treatment strategies, including surgery, radio-/chemotherapy, as well as targeted therapy. To compensate for their limited tumor specificity, several microRNAs are frequently combined into microRNA panels. Moreover, the possibility to combine single microRNAs or microRNA panels with tumor imaging or other cancer-specific biomarkers has the potential to increase specificity and sensitivity and could lead to the clinical application of novel multi-marker combinations.

Circulating HOXA9-methylated tumour DNA: A novel biomarker of response to poly (ADP-ribose) polymerase inhibition in BRCA-mutated epithelial ovarian cancer

AIM

Poly (ADP-ribose) polymerase (PARP) inhibitors have emerged as a novel treatment option in BRCA-mutated ovarian cancer (OC); however, responses are variable and there is a lack of prognostic and predictive biomarkers. We therefore investigated whether homeobox A9 (HOXA9) promoter methylation in circulating tumour DNA (meth-ctDNA) can serve as a biomarker in patients with platinum-resistant BRCA-mutated OC, undergoing treatment with a PARP inhibitor.

METHODS

Patients (n = 32) were enrolled as part of a phase II trial testing veliparib in platinum-resistant BRCA-mutated OC. HOXA9 meth-ctDNA was determined at baseline and just before each treatment cycle using digital droplet polymerase chain reaction. Methylation status and change in methylation compared with baseline were correlated with overall survival (OS) and progression-free survival (PFS).

RESULTS

Detection of HOXA9 meth-ctDNA during treatment with a PARP inhibitor was associated with worse clinical outcomes. This association was apparent after the first cycle of treatment and maintained throughout treatment. After three treatment cycles, patients with detectable HOXA9 meth-ctDNA had a median PFS of 5.1 months compared with 8.3 months for patients without, and a median OS of 9.5 months compared with 19.4 months (p < 0.0001 and p = 0.002, respectively). Patients with detectable HOXA9 meth-ctDNA at baseline, but subsequent undetectable levels, had the most favourable clinical outcome, followed by patients with undetectable levels throughout. These associations were maintained in multivariate analysis.

CONCLUSIONS

Longitudinal monitoring of HOXA9 meth-ctDNA is clinically feasible and is strongly correlated to clinical outcomes (PFS, OS), suggesting that it may serve as a valuable predictive biomarker to inform clinical decision-making in the setting of platinum-resistant BRCA-mutated OC treated with a PARP inhibitor.

Effect of tobacco smoking on the epigenetic age of human respiratory organs

BACKGROUND

Smoking leads to the aging of organs. However, no studies have been conducted to quantify the effect of smoking on the aging of respiratory organs and the aging-reversing ability of smoking cessation.

RESULTS

We collected genome-wide methylation datasets of buccal cells, airway cells, esophagus tissue, and lung tissue from non-smokers, smokers, and ex-smokers. We used the "epigenetic clock" method to quantify the epigenetic age acceleration in the four organs. The statistical analyses showed the following: (1) Smoking increased the epigenetic age of airway cells by an average of 4.9 years and lung tissue by 4.3 years. (2) After smoking ceased, the epigenetic age acceleration in airway cells (but not in lung tissue) slowed to a level that non-smokers had. (3) The epigenetic age acceleration in airway cells and lung tissue showed no gender difference.

CONCLUSIONS

Smoking can accelerate the epigenetic age of human respiratory organs, but the effect varies among organs and can be reversed by smoking cessation. Our study provides a powerful incentive to reduce tobacco consumption autonomously.

A novel CpG island methylation panel predicts survival in lung adenocarcinomas

The lack of clinically useful biomarkers compromise the personalized management of lung adenocarcinomas (ADCs); epigenetic events and DNA methylation in particular have exhibited potential value as biomarkers. By comparing genome-wide DNA methylation data of paired lung ADCs and normal tissues from 6 public datasets, cancer-specific CpG island (CGI) methylation changes were identified with a pre-specified criterion. Correlations between DNA methylation and expression data for each gene were assessed by Pearson correlation analysis. A prognostically relevant CGI methylation signature was constructed by risk-score analysis, and was validated using a training-validation approach. Survival data were analyzed by log-rank test and Cox regression model. In total, 134 lung ADC-specific CGI CpGs were identified, among which, a panel of 9 CGI loci were selected as prognostic candidates, and were used to construct a risk-score signature. The novel CGI methylation signature was identified to classify distinct prognostic subgroups across different datasets, and was demonstrated to be a potent independent prognostic factor for overall survival time of patients with lung ADCs. In addition, it was identified that cancer-specific CGI hypomethylation of RPL39L, along with the corresponding gene expression, provided optimized prognostication of lung ADCs. In summary, cancer-specific CGI methylation aberrations are optimal candidates for novel biomarkers of lung ADCs; the 9-CpG methylation panel and hypomethylation of RPL39L exhibited particularly promising significance.

Epigenetics of lung cancer: a translational perspective

BACKGROUND

Lung cancer remains the most common cause of cancer-related death, with a 5-year survival rate of only 18%. In recent years, the development of targeted pharmacological agents and immunotherapies has substantially increased the survival of a subset of patients. However, most patients lack such efficacious therapy and are, thus, treated with classical chemotherapy with poor clinical outcomes. Therefore, novel therapeutic strategies are urgently needed. In recent years, the development of epigenetic assays and their application to cancer research have highlighted the relevance of epigenetic regulation in the initiation, development, progression and treatment of lung cancer.

CONCLUSIONS

A variety of epigenetic modifications do occur at different steps of lung cancer development, some of which are key to tumor progression. The rise of cutting-edge technologies such as single cell epigenomics is, and will continue to be, crucial for uncovering epigenetic events at a single cell resolution, leading to a better understanding of the biology underlying lung cancer development and to the design of novel therapeutic options. This approach has already led to the development of strategies involving single agents or combined agents targeting epigenetic modifiers, currently in clinical trials. Here, we will discuss the epigenetics of every step of lung cancer development, as well as the translation of these findings into clinical applications.

Expression of the Major and Pro-Oncogenic H3K9 Lysine Methyltransferase SETDB1 in Non-Small Cell Lung Cancer

SETDB1 is a key histone lysine methyltransferase involved in gene silencing. The SETDB1 gene is amplified in human lung cancer, where the protein plays a driver role. Here, we investigated the clinical significance of SETDB1 expression in the two major forms of human non-small cell lung carcinoma (NSCLC), i.e., adenocarcinoma (ADC) and squamous cell carcinoma (SCC), by combining a meta-analysis of transcriptomic datasets and a systematic review of the literature. A total of 1140 NSCLC patients and 952 controls were included in the association analyses. Our data revealed higher levels of SETDB1 mRNA in ADC (standardized mean difference, SMD: 0.88; 95% confidence interval, CI: 0.73-1.02; p < 0.001) and SCC (SMD: 0.40; 95% CI: 0.13-0.66; p = 0.003) compared to non-cancerous tissues. For clinicopathological analyses, 2533 ADC and 903 SCC patients were included. Interestingly, SETDB1 mRNA level was increased in NSCLC patients who were current smokers compared to non-smokers (SMD: 0.26; 95% CI: 0.08-0.44; p = 0.004), and when comparing former smokers and non-smokers (p = 0.009). Furthermore, the area under the curve (AUC) given by the summary receiver operator characteristic curve (sROC) was 0.774 (Q = 0.713). Together, our findings suggest a strong foundation for further research to evaluate SETDB1 as a diagnostic biomarker and/or its potential use as a therapeutic target in NSCLC.

Clinical value of microRNA-198-5p downregulation in lung adenocarcinoma and its potential pathways

Lung adenocarcinoma (LUAD), the main subtype of non-small cell lung cancer, is known to be regulated by various microRNAs (miRs/miRNAs); however, the role of miR-198-5p in LUAD has not been clarified. In the present study, the clinical value of miR-198-5p in LUAD and its potential molecular mechanism was evaluated. miR-198-5p expression was examined by reverse transcription-quantitative PCR (RT-qPCR) in 101 paired LUAD and adjacent normal lung tissues. Subsequently, the miR-198-5p expression level was determined from microarray data from the Gene Expression Omnibus, ArrayExpress and by meta-analyses. Furthermore, the target mRNAs of miR-198-5p from 12 miRNA-mRNA predictive tools were intersected with The Cancer Genome Atlas (TCGA)-based differentially expressed genes. In addition, Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to determine the possible mechanism of miR-198-5p in LUAD. The Search Tool for the Retrieval of Interacting Genes/Proteins database was employed to construct a protein-protein interaction network among the potential target genes of miR-198-5p. The results showed that miR-198-5p expression was lower in LUAD tissues than in adjacent non-cancerous lung tissues (4.469±2.495 vs. 5.301±2.502; P=0.015). Meta-analyses, including the data from the present study and online microarray data, also verified the downregulation of miR-198-5p in 584 cases of LUAD. The expression of miR-198-5p was associated with the age, blood vessel invasion, Tumor-Node-Metastasis stage, and lymph node metastasis of patients with LUAD and served as an independent prognostic factor for survival. The hub genes of miR-198-5p were upregulated in LUAD, according to TCGA and The Human Protein Atlas. For the KEGG pathway analysis, the most enriched KEGG pathway was the p53 signaling pathway (P=1.42×10⁻⁶). These findings indicated that the downregulation of miR-198-5p may play a pivotal role in the development of LUAD by targeting various signaling pathways.

HLA-DQB1 expression on tumor cells is a novel favorable prognostic factor for relapse in early-stage lung adenocarcinoma

Background: Postoperative recurrence is the main cause of a poor prognosis in early-stage lung adenocarcinoma (LUAD). Factors that can predict recurrence risk are critically needed.

Materials and methods: In this study, we designed a screening procedure based on gene profile data and performed validation using TCGA and Daping hospital’s cohorts. Differentially expressed genes (DEGs) between patients with recurrence-free survival (RFS) <1 year and RFS >3 years were identified, overlapping genes among these DEGs were selected as candidate biomarkers. A Cox proportional hazards model, immunohistochemistry and Kaplan-Meier survival analysis were performed to validate these biomarkers in two distinct validation sets.

Results:SFTPB, SFTPD, SFTA1P, HLA-DQB1, ITGB8, ANLN, and LRRN1 were overlapped both in TCGA and Daping discovery sets. The Cox proportional hazards model analysis of the TCGA validation set showed that HLA-DQB1 was an independent prognostic factor for RFS (HR=0.686, 95% CI, 0.542–0.868). Immunohistochemistry and Kaplan-Meier analysis in Daping validation sets confirmed HLA-DQB1 expression on tumor cells (not interstitial cells) to be an effective predictor of postoperative recurrence. Further examination revealed that the level of HLA-DQB1 expression on tumor cells was positively correlated with CD4- and CD8-positive lymphocyte infiltration into the tumor.

Conclusion: All results indicate that high expression of HLA-DQB1 on tumor cells is a good prognostic marker in early-stage LUAD, and the mechanism may be related to anti-tumor immune activity.

Predictability of human differential gene expression

The identification of genes that are differentially expressed provides a molecular foothold onto biological questions of interest. Whether some genes are more likely to be differentially expressed than others, and to what degree, has never been assessed on a global scale. Here, we reanalyze more than 600 studies and find that knowledge of a gene’s prior probability of differential expression (DE) allows for accurate prediction of DE hit lists, regardless of the biological question. This result suggests redundancy in transcriptomics experiments that both informs gene set interpretation and highlights room for growth within the field.

Differential expression (DE) is commonly used to explore molecular mechanisms of biological conditions. While many studies report significant results between their groups of interest, the degree to which results are specific to the question at hand is not generally assessed, potentially leading to inaccurate interpretation. This could be particularly problematic for metaanalysis where replicability across datasets is taken as strong evidence for the existence of a specific, biologically relevant signal, but which instead may arise from recurrence of generic processes. To address this, we developed an approach to predict DE based on an analysis of over 600 studies. A predictor based on empirical prior probability of DE performs very well at this task (mean area under the receiver operating characteristic curve, ∼0.8), indicating that a large fraction of DE hit lists are nonspecific. In contrast, predictors based on attributes such as gene function, mutation rates, or network features perform poorly. Genes associated with sex, the extracellular matrix, the immune system, and stress responses are prominent within the “DE prior.” In a series of control studies, we show that these patterns reflect shared biology rather than technical artifacts or ascertainment biases. Finally, we demonstrate the application of the DE prior to data interpretation in three use cases: (i) breast cancer subtyping, (ii) single-cell genomics of pancreatic islet cells, and (iii) metaanalysis of lung adenocarcinoma and renal transplant rejection transcriptomics. In all cases, we find hallmarks of generic DE, highlighting the need for nuanced interpretation of gene phenotypic associations.