Systems-epigenomics inference of transcription factor activity implicates aryl-hydrocarbon-receptor inactivation as a key event in lung cancer development

Experience Sharing in Pathological Diagnosis of Early Adenocarcinoma of the Lung

BACKGROUND

In daily work, there are still many pathologists who have difficulty handling the diagnosis of atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic adenocarcinoma, and the boundaries are not clear enough. Sometimes, the diagnosis is difficult, and there is sometimes poor reproducibility between different pathologists. Accurate diagnosis and differential diagnosis require a certain amount of experience.

METHODS

During the COVID-19 pandemic, we collected a large number (n = 381) of specimens of early lung adenocarcinoma, most of which (n = 356) were solitary lesions and 25 were multifocal lesions. There were 78 nodules in multifocal lesions, total 434 nodules. We summarized very careful microscopic observation and comparative analysis on all frozen and paraffin sections collected from many early lung adenocarcinoma specimens, continuously summarizing our experience.

RESULTS

Based on the World Health Organization's 2021 classification and diagnostic criteria for lung adenocarcinoma, new perspectives have been proposed on how to distinguish between atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic adenocarcinoma. In particular, new perspectives have been proposed on how to identify invasive aspects, and there are also some new perspectives on early lung mucinous lesions.

CONCLUSION

Atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic adenocarcinoma all have corresponding morphological diagnostic criteria, but the morphological boundaries are sometimes not easy to determine and require some experience accumulation. The intraoperative frozen pathological diagnosis of early adenocarcinoma of the lung needs to be closely combined with imaging examination, and has very rich morphological experience.

Loss of coordination between basic cellular processes in human aging

Age-related loss of gene expression coordination has been reported for distinct cell types and may lead to impaired cellular function. Here we propose a method for quantifying age-related changes in transcriptional regulatory relationships between genes, based on a model learned from external data. We used this method to uncover age-related trends in gene-gene relationships across eight human tissues, which demonstrates that reduced co-expression may also result from coordinated transcriptional responses. Our analyses reveal similar numbers of strengthening and weakening gene-gene relationships with age, impacting both tissue-specific (for example, coagulation in blood) and ubiquitous biological functions. Regulatory relationships becoming weaker with age were established mostly between genes operating in distinct cellular processes. As opposed to that, regulatory relationships becoming stronger with age were established both within and between different cellular functions. Our work reveals that, although most transcriptional regulatory gene-gene relationships are maintained during aging, those with declining regulatory coupling result mostly from a loss of coordination between distinct cellular processes.

An improved epigenetic counter to track mitotic age in normal and precancerous tissues

The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC's mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.

On epigenetic stochasticity, entropy and cancer risk

Epigenetic changes are known to accrue in normal cells as a result of ageing and cumulative exposure to cancer risk factors. Increasing evidence points towards age-related epigenetic changes being acquired in a quasi-stochastic manner, and that they may play a causal role in cancer development. Here, I describe the quasi-stochastic nature of DNA methylation (DNAm) changes in ageing cells as well as in normal cells at risk of neoplastic transformation, discussing the implications of this stochasticity for developing cancer risk prediction strategies, and in particular, how it may require a conceptual paradigm shift in how we select cancer risk markers. I also describe the mounting evidence that a significant proportion of DNAm changes in ageing and cancer development are related to cell proliferation, reflecting tissue-turnover and the opportunity this offers for predicting cancer risk via the development of epigenetic mitotic-like clocks. Finally, I describe how age-associated DNAm changes may be causally implicated in cancer development via an irreversible suppression of tissue-specific transcription factors that increases epigenetic and transcriptomic entropy, promoting a more plastic yet aberrant cancer stem-cell state. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Significance of Gastrokine-1 Polymorphism Rs4254535 as a Prognostic Marker and its Association with Clinical Characteristics in Chinese Lung Cancer Patients

Background: The single nucleotide polymorphism (SNP) of Gastrokine-1 (GKN1) is associated with lung cancer but its association with prognosis is not clear. Methods: Genomic DNA was extracted from the blood samples of 888 patients with lung cancer. The association between GKN1 polymorphism rs4254535 and prognostic was analyzed by the Kaplan-Meier (KM) method, Log-rank test, and Cox proportional hazards model. Results: In females and patients diagnosed with late-stage lung cancer, the CC genotype (CC vs TT, adjusted odds ratio [HR] = 0.57, 95% Confidence Interval [CI]: 0.33-0.99, P = 0.045; HR = 0.66, 95% CI: 0.48-0.92, P = 0.014) and recessive CC genotype (CC vs TT + TC, HR = 0.55, 95% CI: 0.32-0.94, P = 0.028; HR = 0.64, 95% CI: 0.47-0.89, P = 0.006) of rs4254535 conferred a better prognosis, compared with the TT and TT + TC genotype. Rs4254535 dominate TC + CC genotype, recessive CC genotype, and C allele who were adenocarcinoma patients had a significantly better prognosis. The recessive CC genotype of non-smoking patients has a better prognosis, compared to the TT + TC genotype. Additionally, in the dominant TT + TC genotype and C allele, no family history patients had a significantly better prognosis, compared to the TT genotype. Conclusion: For lung cancer patients, GKN1 polymorphism rs4254535 may be a protective genetic marker and predicts the prognosis of lung cancer patients.

GOAT: Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network for eosinophilic asthma subtype

MOTIVATION

Asthma is a heterogeneous disease where various subtypes are established and molecular biomarkers of the subtypes are yet to be discovered. Recent availability of multi-omics data paved a way to discover molecular biomarkers for the subtypes. However, multi-omics biomarker discovery is challenging because of the complex interplay between different omics layers.

RESULTS

We propose a deep attention model named Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network (GOAT) for identifying molecular biomarkers for eosinophilic asthma subtypes with multi-omics data. GOAT identifies genes that discriminate subtypes using a graph neural network by modeling complex interactions among genes as the attention mechanism in the deep learning model. In experiments with multi-omics profiles of the COREA (Cohort for Reality and Evolution of Adult Asthma in Korea) asthma cohort of 300 patients, GOAT outperforms existing models and suggests interpretable biological mechanisms underlying asthma subtypes. Importantly, GOAT identified genes that are distinct only in terms of relationship with other genes through attention. To better understand the role of biomarkers, we further investigated two transcription factors, CTNNB1 and JUN, captured by GOAT. We were successful in showing the role of the transcription factors in eosinophilic asthma pathophysiology in a network propagation and transcriptional network analysis, which were not distinct in terms of gene expression level differences.

AVAILABILITY AND IMPLEMENTATION

Source code is available https://github.com/DabinJeong/Multi-omics_biomarker. The preprocessed data underlying this article is accessible in data folder of the github repository. Raw data are available in Multi-Omics Platform at http://203.252.206.90:5566/, and it can be accessible when requested.

Identifying genetic regulatory variants that affect transcription factor activity

Genetic variants affecting gene expression levels in humans have been mapped in the Genotype-Tissue Expression (GTEx) project. Trans-acting variants impacting many genes simultaneously through a shared transcription factor (TF) are of particular interest. Here, we developed a generalized linear model (GLM) to estimate protein-level TF activity levels in an individual-specific manner from GTEx RNA sequencing (RNA-seq) profiles. It uses observed differential gene expression after TF perturbation as a predictor and, by analyzing differential expression within pairs of neighboring genes, controls for the confounding effect of variation in chromatin state along the genome. We inferred genotype-specific activities for 55 TFs across 49 tissues. Subsequently performing genome-wide association analysis on this virtual trait revealed TF activity quantitative trait loci (aQTLs) that, as a set, are enriched for functional features. Altogether, the set of tools we introduce here highlights the potential of genetic association studies for cellular endophenotypes based on a network-based multi-omics approach. The transparent peer review record is available.

AhR Promotes the Development of Non-small cell lung cancer by Inducing SLC7A11-dependent Antioxidant Function

Objective: Aryl hydrocarbon receptor (AhR) is a transcription factor. It is reported that AhR is associated with non-small cell lung cancer (NSCLC), but the mechanisms underlying this relationship remain unclear. Therefore, we investigated the role of AhR in NSCLC to elucidate the underlying mechanisms. Methods: We collected clinical lung cancer samples and constructed AhR overexpression and knockdown cell lines to investigate the tumorigenicity of AhR in vivo and in vitro. Furthermore, we performed a ferroptosis induction experiment and chromatin immunoprecipitation experiment. Results: AhR was highly expressed in NSCLC tissue. AhR knockdown cells showed ferroptosis related phenomenon. Furthermore, Chromatin immunoprecipitation confirmed the correlation between AhR and solute carrier family 7 member 11 (SLC7A11) and ferroptosis induction experiment confirmed that AhR affects ferroptosis via SLC7A11. Specifically, AhR regulates ferroptosis-related SLC7A11, which affects ferroptosis and promotes NSCLC progression. Conclusions: AhR promoted NSCLC development and positively correlated with SLC7A11, affecting its actions. AhR bound to the promoter region of SLC7A11 promotes NSCLC by activating SLC7A11 expression, improving the oxidative sensitivity of cells, and inhibiting ferroptosis. Thus, AhR affects ferroptosis in NSCLC by regulating SLC7A11, providing foundational evidence for novel ferroptosis-related treatments.

Longitudinal change in blood DNA epigenetic signature after smoking cessation

Cigarette smoking is associated with epigenetic changes that may be reversible following smoking cessation. Whole blood DNA methylation was evaluated in Framingham Heart Study Offspring (n = 169) and Third Generation (n = 30) cohort participants at two study visits 6 years apart and in Atherosclerosis Risk in Communities (ARIC) study (n = 222) participants at two study visits 20 years apart. Changes in DNA methylation (delta β values) at 483,565 cytosine-phosphate-guanine (CpG) sites and differentially methylated regions (DMRs) were compared between participants who were current, former, or never smokers at both visits (current-current, former-former, never-never, respectively), versus those who quit in the interim (current-former). Interim quitters had more hypermethylation at four CpGs annotated to AHRR, one CpG annotated to F2RL3, and one intergenic CpG (cg21566642) compared with current-current smokers (FDR < 0.02 for all), and two significant DMRs were identified. While there were no significant differentially methylated CpGs in the comparison of interim quitters and former-former smokers, 106 DMRs overlapping with small nucleolar RNA were identified. As compared with all non-smokers, current-current smokers additionally had more hypermethylation at two CpG sites annotated to HIVEP3 and TMEM126A, respectively, and another intergenic CpG (cg14339116). Gene transcripts associated with smoking cessation were implicated in immune responses, cell homoeostasis, and apoptosis. Smoking cessation is associated with early reversion of blood DNA methylation changes at CpG sites annotated to AHRR and F2RL3 towards those of never smokers. Associated gene expression suggests a role of longitudinal smoking-related DNA methylation changes in immune response processes.

Epigenetic Regulation of Cancer Stem Cells by the Aryl Hydrocarbon Receptor Pathway

Compelling evidence has demonstrated that tumor bulk comprises distinctive subset of cells generally referred as cancer stem cells (CSCs) that have been proposed as a strong sustainer and promoter of tumorigenesis and therapeutic resistance. These distinguished properties of CSCs have raised interest in understanding the molecular mechanisms that govern the maintenance of these cells. Numerous experimental and epidemiological studies have demonstrated that exposure to environmental toxins such as the polycyclic aromatic hydrocarbons (PAHs) is strongly involved in cancer initiation and progression. The PAH-induced carcinogenesis is shown to be mediated through the activation of a cytosolic receptor, aryl hydrocarbon receptor (AhR)/Cytochrome P4501A pathway, suggesting a possible direct link between AhR and CSCs. Several recent studies have investigated the role of AhR in CSCs self-renewal and maintenance, however the molecular mechanisms and particularly the epigenetic regulations of CSCs by the AhR/CYP1A pathway have not been reviewed before. In this review, we first summarize the crosstalk between AhR and cancer genetics, with a particular emphasis on the mechanisms relevant to CSCs such as Wnt/β-catenin, Notch, NF-κB, and PTEN-PI3K/Akt signaling pathways. The second part of this review discusses the recent advances and studies highlighting the epigenetic mechanisms mediated by the AhR/CYP1A pathway that control CSC gene expression, self-renewal, and chemoresistance in various human cancers. Furthermore, the review also sheds light on the importance of targeting the epigenetic pathways as a novel therapeutic approach against CSCs.

Inference of age-associated transcription factor regulatory activity changes in single cells

Transcription factors (TFs) control cell identity and function. How their activity is altered during healthy aging is critical for an improved understanding of aging and disease risk, yet relatively little is known about such changes at cell-type resolution. Here we present and validate a TF activity estimation method for single cells from the hematopoietic system that is based on TF regulons, and apply it to a mouse single-cell RNA-sequencing atlas, to infer age-associated differentiation activity changes in the immune cells of different organs. This revealed an age-associated signature of macrophage dedifferentiation, which is shared across tissue types, and aggravated in tumor-associated macrophages. By extending the analysis to all major cell types, we reveal cell-type and tissue-type-independent age-associated alterations to regulatory factors controlling antigen processing, inflammation, collagen processing and circadian rhythm, that are implicated in age-related diseases. Finally, our study highlights the limitations of using TF expression to infer age-associated changes, underscoring the need to use regulatory activity inference methods.

Computational identification of preneoplastic cells displaying high stemness and risk of cancer progression

Evidence points towards the differentiation state of cells as a marker of cancer risk and progression. Measuring the differentiation state of single cells in a preneoplastic population could thus enable novel strategies for early detection and risk prediction. Recent maps of somatic mutagenesis in normal tissues from young healthy individuals have revealed cancer driver mutations, indicating that these do not correlate well with differentiation state and that other molecular events also contribute to cancer development. We hypothesized that the differentiation state of single cells can be measured by estimating the regulatory activity of the transcription factors (TFs) that control differentiation within that cell lineage. To this end, we present a novel computational method called CancerStemID that estimates a stemness index of cells from single-cell RNA-Seq data. CancerStemID is validated in two human esophageal squamous cell carcinoma (ESCC) cohorts, demonstrating how it can identify undifferentiated preneoplastic cells whose transcriptomic state is overrepresented in invasive cancer. Spatial transcriptomics and whole-genome bisulfite sequencing demonstrated that differentiation activity of tissue-specific TFs was decreased in cancer cells compared to the basal cell-of-origin layer and established that differentiation state correlated with differential DNA methylation at the promoters of these TFs, independently of underlying NOTCH1 and TP53 mutations. The findings were replicated in a mouse model of ESCC development, and the broad applicability of CancerStemID to other cancer-types was demonstrated. In summary, these data support an epigenetic stem-cell model of oncogenesis and highlight a novel computational strategy to identify stem-like preneoplastic cells that undergo positive selection.

Analysis of lung cancer-related genetic changes in long-term and low-dose polyhexamethylene guanidine phosphate (PHMG-p) treated human pulmonary alveolar epithelial cells

BACKGROUND

Lung injury elicited by respiratory exposure to humidifier disinfectants (HDs) is known as HD-associated lung injury (HDLI). Current elucidation of the molecular mechanisms related to HDLI is mostly restricted to fibrotic and inflammatory lung diseases. In our previous report, we found that lung tumors were caused by intratracheal instillation of polyhexamethylene guanidine phosphate (PHMG-p) in a rat model. However, the lung cancer-related genetic changes concomitant with the development of these lung tumors have not yet been fully defined. We aimed to discover the effect of long-term exposure of PHMG-p on normal human lung alveolar cells.

METHODS

We investigated whether PHMG-p could increase distorted homeostasis of oncogenes and tumor-suppressor genes, with long-term and low-dose treatment, in human pulmonary alveolar epithelial cells (HPAEpiCs). Total RNA sequencing was performed with cells continuously treated with PHMG-p and harvested after 35 days.

RESULTS

After PHMG-p treatment, genes with transcriptional expression changes of more than 2.0-fold or less than 0.5-fold were identified. Within 10 days of exposure, 2 protein-coding and 5 non-coding genes were selected, whereas in the group treated for 27-35 days, 24 protein-coding and 5 non-coding genes were identified. Furthermore, in the long-term treatment group, 11 of the 15 upregulated genes and 9 of the 14 downregulated genes were reported as oncogenes and tumor suppressor genes in lung cancer, respectively. We also found that 10 genes of the selected 24 protein-coding genes were clinically significant in lung adenocarcinoma patients.

CONCLUSIONS

Our findings demonstrate that long-term exposure of human pulmonary normal alveolar cells to low-dose PHMG-p caused genetic changes, mainly in lung cancer-associated genes, in a time-dependent manner.

UCH-L3 structure and function: Insights about a promising drug target

In the past few years, researchers have shed light on the immense importance of ubiquitin in numerous regulatory pathways. The post-translational addition of mono or poly-ubiquitin molecules namely "ubiquitinoylation" is therefore pivotal to maintain the cell's vitality, maturation, differentiation, and division. Part of conserving homeostasis stems from maintaining the ubiquitin pool in the vicinity of the cell's intracellular environment; this crucial role is played by deubiquitylating enzymes (DUBs) that cleave ubiquitin molecules from target molecules. To date, they are categorized into 7 families with ubiquitin carboxyl c-terminal de-hydrolase family (UCH) as the most common and well-studied. Ubiquitin C-terminal hydrolase L (UCH-L3) is a significant protein in this family as it has been implicated in many molecular and cellular processes with its mRNA identified in a range of body tissues including the brain. It goes without saying that it manifests in maintaining health and when abnormally regulated in disease. As it is an attractive small molecule drug target, scientists have used high throughput screening (HTS) and other drug discovery methods to discover inhibitors for this enzyme for the treatment of cancer and neurodegenerative diseases. In this review we present an overview of UCH-L3 catalytic mechanism, structure, its role in DNA repair and cancer along with the inhibitors discovered so far to halt its activity.

Integrative Molecular Analyses of an Individual Transcription Factor-Based Genomic Model for Lung Cancer Prognosis

Objective

Precision medicine with molecular profiles has revolutionized the management of lung cancer contributing to improved prognosis. Herein, we aimed to uncover the gene expression profiling of transcription factors (TFs) in lung cancer as well as to develop a TF-based genomic model.

Methods

We retrospectively curated lung cancer patients from public databases. Through comparing mRNA expression profiling between lung cancer and normal specimens, specific TFs were determined. Thereafter, a TF genomic model was developed with univariate Cox regression and stepwise multivariable Cox analyses, which was verified through the GSE72094 dataset. Gene set enrichment analyses (GSEA) were presented. Downstream targets of TFs were predicted with ChEA, JASPAR, and MotifMap projects, and their biological significance was investigated through the clusterProfiler algorithm.

Results

In the TCGA cohort, we proposed a TF-based genomic model, comprised of SATB2, HLF, and NPAS2. Lung cancer individuals were remarkably stratified into high- and low-risk groups. Survival analyses uncovered that high-risk populations presented unfavorable survival outcomes. ROCs confirmed the excellent predictive potency in patients' prognosis. Additionally, this model was an independent prognostic indicator in accordance with multivariate analyses. The clinical implication of the model was well verified in an independent dataset. High risk score was in relation to carcinogenic pathways. Downstream targets were characterized by immune and carcinogenic activation.

Conclusion

The proposed TF genomic model acts as a promising marker for estimation of lung cancer patients' outcomes. Prospective research is required for testing the clinical utility of the model in individualized management of lung cancer.

Quantifying smoking exposure, genomic correlates, and related risk of treatment failure in p16+ squamous cell carcinoma of the oropharynx

OBJECTIVES

HPV-associated (p16+) squamous cell carcinoma of the oropharynx (OPSCC) has improved survival as compared to HPV-negative, smoking-associated disease. Intermediate outcomes have been noted in patients with p16+ tumors and smoking exposure. However, the extent of smoking exposure required for outcomes to decrease has not been delineated due to low failure rates and poor availability of quantitative tobacco smoke exposure data. Our primary objective is to characterize the dose-dependent relationship between recurrence-free survival (RFS) and tobacco smoke exposure in p16+ OPSCC and secondarily correlate tobacco smoke exposure with genomic alterations.

METHODS

Single institution chart review was performed of patients diagnosed with p16+ OPSCC from 2003 to 2015. Patients were excluded if staging, treatment details, recurrence status, or smoking exposure in pack-years were not available. Two hundred and forty-four patients were included.

RESULTS

Patients with 25 pack-years or greater smoking history exhibited a dose-dependent decrease in RFS compared to never smokers. This was robust to multivariate analysis for including staging and demographic factors. Forty-three patients with available targeted tumor sequencing data were identified. A strong trend was observed for increased C to A transversion mutations above 25 pack-years, which are known to be associated with exposure to tobacco smoke. Similarly, the proportion of COSMIC Signature 4 mutations were also found to be more common in patients with more than 25 pack-years of smoking exposure.

CONCLUSION

Evidence-based smoking exposure thresholds are needed to define inclusion criteria for trials of de-escalation therapy for p16+ OPSCC. Patients with smoking exposure greater than 20 pack-years have increased risk of recurrence and a distinct pattern of genomic alterations. Further studies are needed to delineate the potential consequences of mild smoking exposure. Smoking-related mutational signatures may hold potential for biomarker development in p16+ OPSCC.

LEVEL OF EVIDENCE

2B.

Integration of Epigenetic Mechanisms into Non-Genotoxic Carcinogenicity Hazard Assessment: Focus on DNA Methylation and Histone Modifications

Epigenetics involves a series of mechanisms that entail histone and DNA covalent modifications and non-coding RNAs, and that collectively contribute to programing cell functions and differentiation. Epigenetic anomalies and DNA mutations are co-drivers of cellular dysfunctions, including carcinogenesis. Alterations of the epigenetic system occur in cancers whether the initial carcinogenic events are from genotoxic (GTxC) or non-genotoxic (NGTxC) carcinogens. NGTxC are not inherently DNA reactive, they do not have a unifying mode of action and as yet there are no regulatory test guidelines addressing mechanisms of NGTxC. To fil this gap, the Test Guideline Programme of the Organisation for Economic Cooperation and Development is developing a framework for an integrated approach for the testing and assessment (IATA) of NGTxC and is considering assays that address key events of cancer hallmarks. Here, with the intent of better understanding the applicability of epigenetic assays in chemical carcinogenicity assessment, we focus on DNA methylation and histone modifications and review: (1) epigenetic mechanisms contributing to carcinogenesis, (2) epigenetic mechanisms altered following exposure to arsenic, nickel, or phenobarbital in order to identify common carcinogen-specific mechanisms, (3) characteristics of a series of epigenetic assay types, and (4) epigenetic assay validation needs in the context of chemical hazard assessment. As a key component of numerous NGTxC mechanisms of action, epigenetic assays included in IATA assay combinations can contribute to improved chemical carcinogen identification for the better protection of public health.

Loss of Aryl Hydrocarbon Receptor Favors K-RasG12D-Driven Non-Small Cell Lung Cancer

Non-small cell lung adenocarcinoma (NSCLC) bearing K-Ras^G12D mutations is one of the most prevalent types of lung cancer worldwide. Aryl hydrocarbon receptor (AHR) expression varies in human lung tumors and has been associated with either increased or reduced lung metastasis. In the mouse, Ahr also adjusts lung regeneration upon injury by limiting the expansion of resident stem cells. Here, we show that the loss of Ahr enhances K-Ras^G12D-driven NSCLC in mice through the amplification of stem cell subpopulations. Consistent with this, we show that K-Ras^G12D;Ahr^-/- lungs contain larger numbers of cells expressing markers for both progenitor Clara (SCGB1A1 and CC10) and alveolar type-II (SFTPC) cells when compared to K-Ras^G12D;Ahr^+/+-driven tumors. They also have elevated numbers of cells positive for pluripotent stem cells markers such as SOX2, ALDH1, EPCAM, LGR5 and PORCN. Typical pluripotency genes Nanog, Sox2 and c-Myc were also upregulated in K-Ras^G12D;Ahr^-/- lung tumors as found by RNAseq analysis. In line with this, purified K-Ras^G12D/+;Ahr^-/^- lung cells generate larger numbers of organoids in culture that can subsequently differentiate into bronchioalveolar structures enriched in both pluripotency and stemness genes. Collectively, these data indicate that Ahr antagonizes K-Ras^G12D-driven NSCLC by restricting the number of cancer-initiating stem cells. They also suggest that Ahr expression might represent a good prognostic marker to determine the progression of K-Ras^G12D-positive NSCLC patients.

Inferring TF activities and activity regulators from gene expression data with constraints from TF perturbation data

Motivation

The activity of a transcription factor (TF) in a sample of cells is the extent to which it is exerting its regulatory potential. Many methods of inferring TF activity from gene expression data have been described, but due to the lack of appropriate large-scale datasets, systematic and objective validation has not been possible until now.

Results

We systematically evaluate and optimize the approach to TF activity inference in which a gene expression matrix is factored into a condition-independent matrix of control strengths and a condition-dependent matrix of TF activity levels. We find that expression data in which the activities of individual TFs have been perturbed are both necessary and sufficient for obtaining good performance. To a considerable extent, control strengths inferred using expression data from one growth condition carry over to other conditions, so the control strength matrices derived here can be used by others. Finally, we apply these methods to gain insight into the upstream factors that regulate the activities of yeast TFs Gcr2, Gln3, Gcn4 and Msn2.

Availability and implementation

Evaluation code and data are available at https://doi.org/10.5281/zenodo.4050573.

Supplementary information

Supplementary data are available at Bioinformatics online.

Dysregulation of Transcription Factor Activity During Formation of Cancer-Associated Fibroblasts

The reciprocal interactions between cancer cells and the quiescent fibroblasts leading to the activation of cancer-associated fibroblasts (CAFs) serve an important role in cancer progression. Here, we investigated the activation of transcription factors (TFs) in prostate fibroblasts (WPMY cell line) co-cultured with normal prostate or tumorous cells (RWPE1 and RWPE2 cell lines, respectively). After indirect co-cultures, we performed mRNA-seq and predicted TF activity using mRNA expression profiles with the Systems EPigenomics Inference of Regulatory Activity (SEPIRA) package and the GTEx and mRNA-seq data of 483 cultured fibroblasts. The initial differential expression analysis between time points and experimental conditions showed that co-culture with normal epithelial cells mainly promotes an inflammatory response in fibroblasts, whereas with the cancerous epithelial, it stimulates transformation by changing the expression of the genes associated with microfilaments. TF activity analysis revealed only one positively regulated TF in the RWPE1 co-culture alone, while we observed dysregulation of 45 TFs (7 decreased activity and 38 increased activity) uniquely in co-culture with RWPE2. Pathway analysis showed that these 45 dysregulated TFs in fibroblasts co-cultured with RWPE2 cells may be associated with the RUNX1 and PTEN pathways. Moreover, we showed that observed dysregulation could be associated with FER1L4 expression. We conclude that phenotypic changes in fibroblast responses to co-culturing with cancer epithelium result from orchestrated dysregulation of signaling pathways that favor their transformation and motility rather than proinflammatory status. This dysregulation can be observed both at the TF and transcriptome levels.

Benzo[a]pyrene injures BMP2-induced osteogenic differentiation of mesenchymal stem cells through AhR reducing BMPRII

Benzo[a]pyrene(BaP), a polycyclic aromatic hydrocarbons (PAH) of environmental pollutants, is one of the main ingredients in cigarettes and an agonist of the aryl hydrocarbon receptor (AhR). Mesenchymal stem cells (MSCs) including C3H10T1/2 and MEF cells, adult multipotent stem cells, can be differentiated toward osteoblasts during the induction of osteogenic induction factor-bone morphogenetic protein 2(BMP2). Accumulating evidence suggests that BaP decreases bone development in mammals, but the further mechanisms of BaP on BMP2-induced bone formation involved are unknown. Here, we researched the role of BaP on BMP2-induced osteoblast differentiation and bone formation. We showed that BaP significantly suppressed early and late osteogenic differentiation, and downregulated the runt-related transcription factor 2(Runx2), osteocalcin(OCN) and osteopontin (OPN) during the induction of BMP2 in MSCs. Consistent with in vitro results, administration of BaP inhibited BMP2-induced subcutaneous ectopic osteogenesis in vivo. Interestingly, blocking AhR reversed the inhibition of BaP on BMP2-induced osteogenic differentiation, which suggested that AhR played an important role in this process. Moreover, BaP significantly decreased BMP2-induced Smad1/5/8 phosphorylation. Furthermore, BaP significantly reduced bone morphogenetic protein receptor 2(BMPRII) expression and excessively activated Hey1. Thus, our data demonstrate the role of BaP in BMP2-induced bone formation and suggest that impaired BMP/Smad pathways through AhR regulating BMPRII and Hey1 may be an underlying mechanism for BaP inhibiting BMP2-induced osteogenic differentiation.

DNA Methylation Markers in Lung Cancer

Lung cancer is the most common cancer and the leading cause of cancer-related morbidity and mortality worldwide. As early symptoms of lung cancer are minimal and non-specific, many patients are diagnosed at an advanced stage. Despite a concerted effort to diagnose lung cancer early, no biomarkers that can be used for lung cancer screening and prognosis prediction have been established so far. As global DNA demethylation and gene-specific promoter DNA methylation are present in lung cancer, DNA methylation biomarkers have become a major area of research as potential alternative diagnostic methods to detect lung cancer at an early stage. This review summarizes the emerging DNA methylation changes in lung cancer tumorigenesis, focusing on biomarkers for early detection and their potential clinical applications in lung cancer.

Improved detection of tumor suppressor events in single-cell RNA-Seq data

Tissue-specific transcription factors are frequently inactivated in cancer. To fully dissect the heterogeneity of such tumor suppressor events requires single-cell resolution, yet this is challenging because of the high dropout rate. Here we propose a simple yet effective computational strategy called SCIRA to infer regulatory activity of tissue-specific transcription factors at single-cell resolution and use this tool to identify tumor suppressor events in single-cell RNA-Seq cancer studies. We demonstrate that tissue-specific transcription factors are preferentially inactivated in the corresponding cancer cells, suggesting that these are driver events. For many known or suspected tumor suppressors, SCIRA predicts inactivation in single cancer cells where differential expression does not, indicating that SCIRA improves the sensitivity to detect changes in regulatory activity. We identify NKX2-1 and TBX4 inactivation as early tumor suppressor events in normal non-ciliated lung epithelial cells from smokers. In summary, SCIRA can help chart the heterogeneity of tumor suppressor events at single-cell resolution.

A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes

Highly reproducible smoking-associated DNA methylation changes in whole blood have been reported by many Epigenome-Wide-Association Studies (EWAS). These epigenetic alterations could have important implications for understanding and predicting the risk of smoking-related diseases. To this end, it is important to establish if these DNA methylation changes happen in all blood cell subtypes or if they are cell-type specific. Here, we apply a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven large EWAS. We find that most of the highly reproducible smoking-associated hypomethylation signatures are more prominent in the myeloid lineage. A meta-analysis further identifies a myeloid-specific smoking-associated hypermethylation signature enriched for DNase Hypersensitive Sites in acute myeloid leukemia. These results may guide the design of future smoking EWAS and have important implications for our understanding of how smoking affects immune-cell subtypes and how this may influence the risk of smoking related diseases.

Smoking-associated DNA methylation changes in whole blood have been reported by many EWAS. Here, the authors use a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven EWAS, identifying lineage-specific smoking-associated DNA methylation changes.

The deubiquitylase UCHL3 maintains cancer stem-like properties by stabilizing the aryl hydrocarbon receptor

Cancer stem cells (CSCs) exhibit highly aggressive and metastatic features and resistance to chemotherapy and radiotherapy. Aryl hydrocarbon receptor (AhR) expression varies among non-small cell lung cancers (NSCLCs), and the mechanisms that support abnormal AhR expression in CSCs remain elusive. Here, we identified ubiquitin carboxyl terminal hydrolase L3 (UCHL3), a DUB enzyme in the UCH protease family, as a bona fide deubiquitylase of the AhR in NSCLC. UCHL3 was shown to interact with, deubiquitylate, and stabilize AhR in a manner dependent on its deubiquitylation activity. Moreover, we showed that UCHL3 promotes the stem-like characteristics and potent tumorigenic capacity of NSCLC cells. UCHL3 increased AhR stability and the binding of AhR to the promoter regions of the “stemness” genes ATP-binding cassette subfamily G member 2 (ABCG2), KLF4, and c-Myc. Depletion of UCHL3 markedly downregulated the “stemness” genes ABCG2, KLF4, and c-Myc, leading to the loss of self-renewal and tumorigenesis in NSCLCs. Furthermore, the UCHL3 inhibitor TCID induced AhR degradation and exhibited significantly attenuated efficacy in NSCLC cells with stem cell-like properties. Additionally, UCHL3 was shown to indicate poor prognosis in patients with lung adenocarcinoma. In general, our results reveal that the UCHL3 deubiquitylase is pivotal for AhR protein stability and a potential target for NSCLC-targeted therapy.

Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules

DNA methylation is an essential epigenetic modification for multiple biological processes. DNA methylation in mammals acts as an epigenetic mark of transcriptional repression. Aberrant levels of DNA methylation can be observed in various types of tumor cells. Thus, DNA methylation has attracted considerable attention among researchers to provide new and feasible tumor therapies. Conventional studies considered single-gene methylation or specific loci as biomarkers for tumorigenesis. However, genome-scale methylated modification has not been completely investigated. Thus, we proposed and compared two novel computational approaches based on multiple machine learning algorithms for the qualitative and quantitative analyses of methylation-associated genes and their dys-methylated patterns. This study contributes to the identification of novel effective genes and the establishment of optimal quantitative rules for aberrant methylation distinguishing tumor cells with different origin tissues.

DNA methylation analysis of negative pressure therapy effect in diabetic foot ulcers

OBJECTIVE

Negative pressure wound therapy (NPWT) has been used to treat diabetic foot ulcerations (DFUs). Its action on the molecular level, however, is only partially understood. Some earlier data suggested NPWT may be mediated through modification of local gene expression. As methylation is a key epigenetic regulatory mechanism of gene expression, we assessed the effect of NPWT on its profile in patients with type 2 diabetes (T2DM) and neuropathic non-infected DFUs.

METHODS

Of 36 included patients, 23 were assigned to NPWT and 13 to standard therapy. Due to ethical concerns, the assignment was non-randomized and based on wound characteristics. Tissue samples were obtained before and 8 ± 1 days after therapy initiation. DNA methylation patterns were checked by Illumina Methylation EPIC kit.

RESULTS

In terms of clinical characteristics, the groups presented typical features of T2DM; however, the NPWT group had significantly greater wound area: 16.8 cm2 vs 1.4 cm2 (P = 0.0003). Initially only one region at chromosome 5 was differentially methylated. After treatment, 57 differentially methylated genes were found, mainly located on chromosomes 6 (chr6p21) and 20 (chr20p13); they were associated with DNA repair and autocrine signaling via retinoic acid receptor. We performed differential analyses pre treatment and post treatment. The analysis revealed 426 differentially methylated regions in the NPWT group, but none in the control group. The enrichment analysis showed 11 processes significantly associated with NPWT, of which 4 were linked with complement system activation. All but one were hypermethylated after NPWT.

CONCLUSION

The NPWT effect on DFUs may be mediated through epigenetic changes resulting in the inhibition of complement system activation.

Appraising the causal relevance of DNA methylation for risk of lung cancer

BACKGROUND

DNA methylation changes in peripheral blood have recently been identified in relation to lung cancer risk. Some of these changes have been suggested to mediate part of the effect of smoking on lung cancer. However, limitations with conventional mediation analyses mean that the causal nature of these methylation changes has yet to be fully elucidated.

METHODS

We first performed a meta-analysis of four epigenome-wide association studies (EWAS) of lung cancer (918 cases, 918 controls). Next, we conducted a two-sample Mendelian randomization analysis, using genetic instruments for methylation at CpG sites identified in the EWAS meta-analysis, and 29 863 cases and 55 586 controls from the TRICL-ILCCO lung cancer consortium, to appraise the possible causal role of methylation at these sites on lung cancer.

RESULTS

Sixteen CpG sites were identified from the EWAS meta-analysis [false discovery rate (FDR) < 0.05], for 14 of which we could identify genetic instruments. Mendelian randomization provided little evidence that DNA methylation in peripheral blood at the 14 CpG sites plays a causal role in lung cancer development (FDR > 0.05), including for cg05575921-AHRR where methylation is strongly associated with both smoke exposure and lung cancer risk.

CONCLUSIONS

The results contrast with previous observational and mediation analysis, which have made strong claims regarding the causal role of DNA methylation. Thus, previous suggestions of a mediating role of methylation at sites identified in peripheral blood, such as cg05575921-AHRR, could be unfounded. However, this study does not preclude the possibility that differential DNA methylation at other sites is causally involved in lung cancer development, especially within lung tissue.

ChIP-Atlas: a data-mining suite powered by full integration of public ChIP-seq data

We have fully integrated public chromatin chromatin immunoprecipitation sequencing (ChIP-seq) and DNase-seq data (n > 70,000) derived from six representative model organisms (human, mouse, rat, fruit fly, nematode, and budding yeast), and have devised a data-mining platform-designated ChIP-Atlas (http://chip-atlas.org). ChIP-Atlas is able to show alignment and peak-call results for all public ChIP-seq and DNase-seq data archived in the NCBI Sequence Read Archive (SRA), which encompasses data derived from GEO, ArrayExpress, DDBJ, ENCODE, Roadmap Epigenomics, and the scientific literature. All peak-call data are integrated to visualize multiple histone modifications and binding sites of transcriptional regulators (TRs) at given genomic loci. The integrated data can be further analyzed to show TR-gene and TR-TR interactions, as well as to examine enrichment of protein binding for given multiple genomic coordinates or gene names. ChIP-Atlas is superior to other platforms in terms of data number and functionality for data mining across thousands of ChIP-seq experiments, and it provides insight into gene regulatory networks and epigenetic mechanisms.

Identification of differentially methylated cell types in epigenome-wide association studies

An outstanding challenge of epigenome-wide association studies (EWASs) performed in complex tissues is the identification of the specific cell type(s) responsible for the observed differential DNA methylation. Here we present a statistical algorithm called CellDMC ( https://github.com/sjczheng/EpiDISH ), which can identify differentially methylated positions and the specific cell type(s) driving the differential methylation. We validated CellDMC on in silico mixtures of DNA methylation data generated with different technologies, as well as on real mixtures from epigenome-wide association and cancer epigenome studies. CellDMC achieved over 90% sensitivity and specificity in scenarios where current state-of-the-art methods did not identify differential methylation. By applying CellDMC to an EWAS performed in buccal swabs, we identified smoking-associated differentially methylated positions occurring in the epithelial compartment, which we validated in smoking-related lung cancer. CellDMC may be useful in the identification of causal DNA-methylation alterations in disease.

Clinical and genetic differences between pustular psoriasis subtypes

Background

The term pustular psoriasis indicates a group of severe skin disorders characterized by eruptions of neutrophil-filled pustules. The disease, which often manifests with concurrent psoriasis vulgaris, can have an acute systemic (generalized pustular psoriasis [GPP]) or chronic localized (palmoplantar pustulosis [PPP] and acrodermatitis continua of Hallopeau [ACH]) presentation. Although mutations have been uncovered in IL36RN and AP1S3, the rarity of the disease has hindered the study of genotype-phenotype correlations.

Objective

We sought to characterize the clinical and genetic features of pustular psoriasis through the analysis of an extended patient cohort.

Methods

We ascertained a data set of unprecedented size, including 863 unrelated patients (251 with GPP, 560 with PPP, 28 with ACH, and 24 with multiple diagnoses). We undertook mutation screening in 473 cases.

Results

Psoriasis vulgaris concurrence was lowest in PPP (15.8% vs 54.4% in GPP and 46.2% in ACH, P < .0005 for both), whereas the mean age of onset was earliest in GPP (31.0 vs 43.7 years in PPP and 51.8 years in ACH, P < .0001 for both). The percentage of female patients was greater in PPP (77.0%) than in GPP (62.5%; P = 5.8 × 10⁻⁵). The same applied to the prevalence of smokers (79.8% vs 28.3%, P < 10⁻¹⁵). Although AP1S3 alleles had similar frequency (0.03-0.05) across disease subtypes, IL36RN mutations were less common in patients with PPP (0.03) than in those with GPP (0.19) and ACH (0.16; P = 1.9 × 10⁻¹⁴ and .002, respectively). Importantly, IL36RN disease alleles had a dose-dependent effect on age of onset in all forms of pustular psoriasis (P = .003).

Conclusions

The analysis of an unparalleled resource revealed key clinical and genetic differences between patients with PPP and those with GPP.

DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants

Normal tissue at risk of neoplastic transformation is characterized by somatic mutations, copy-number variation and DNA methylation changes. It is unclear however, which type of alteration may be more informative of cancer risk. We analyzed genome-wide DNA methylation and copy-number calls from the same DNA assay in a cohort of healthy breast samples and age-matched normal samples collected adjacent to breast cancer. Using statistical methods to adjust for cell type heterogeneity, we show that DNA methylation changes can discriminate normal-adjacent from normal samples better than somatic copy-number variants. We validate this important finding in an independent dataset. These results suggest that DNA methylation alterations in the normal cell of origin may offer better cancer risk prediction and early detection markers than copy-number changes.