Epigenetic-smoking interaction reveals histologically heterogeneous effects of TRIM27 DNA methylation on overall survival among early-stage NSCLC patients

BHAFT: Bayesian heredity-constrained accelerated failure time models for detecting gene-environment interactions in survival analysis

In addition to considering the main effects, understanding gene-environment (G × E) interactions is imperative for determining the etiology of diseases and the factors that affect their prognosis. In the existing statistical framework for censored survival outcomes, there are several challenges in detecting G × E interactions, such as handling high-dimensional omics data, diverse environmental factors, and algorithmic complications in survival analysis. The effect heredity principle has widely been used in studies involving interaction identification because it incorporates the dependence of the main and interaction effects. However, Bayesian survival models that incorporate the assumption of this principle have not been developed. Therefore, we propose Bayesian heredity-constrained accelerated failure time (BHAFT) models for identifying main and interaction (M-I) effects with novel spike-and-slab or regularized horseshoe priors to incorporate the assumption of effect heredity principle. The R package rstan was used to fit the proposed models. Extensive simulations demonstrated that BHAFT models had outperformed other existing models in terms of signal identification, coefficient estimation, and prognosis prediction. Biologically plausible G × E interactions associated with the prognosis of lung adenocarcinoma were identified using our proposed model. Notably, BHAFT models incorporating the effect heredity principle could identify both main and interaction effects, which are highly useful in exploring G × E interactions in high-dimensional survival analysis. The code and data used in our paper are available at https://github.com/SunNa-bayesian/BHAFT.

Bayesian Approaches in Exploring Gene-environment and Gene-gene Interactions: A Comprehensive Review

Rapid advancements in high-throughput biological techniques have facilitated the generation of high-dimensional omics datasets, which have provided a solid foundation for precision medicine and prognosis prediction. Nonetheless, the problem of missing heritability persists. To solve this problem, it is essential to explain the genetic structure of disease incidence risk and prognosis by incorporating interactions. The development of the Bayesian theory has provided new approaches for developing models for interaction identification and estimation. Several Bayesian models have been developed to improve the accuracy of model and identify the main effect, gene-environment (G×E) and gene-gene (G×G) interactions. Studies based on single-nucleotide polymorphisms (SNPs) are significant for the exploration of rare and common variants. Models based on the effect heredity principle and group-based models are relatively flexible and do not require strict constraints when dealing with the hierarchical structure between the main effect and interactions (M-I). These models have a good interpretability of biological mechanisms. Machine learning-based Bayesian approaches are highly competitive in improving prediction accuracy. These models provide insights into the mechanisms underlying the occurrence and progression of complex diseases, identify more reliable biomarkers, and develop higher predictive accuracy. In this paper, we provide a comprehensive review of these Bayesian approaches.

DNA Methylation Changes in Autologous Hematopoietic Stem Cell Transplant Patients

BACKGROUND

Blood cancers may be potentially cured with hematopoietic stem cell transplantation (HCT); however, standard pre-assessments for transplant eligibility do not capture all contributing factors for transplant outcomes. Epigenetic biomarkers predict outcomes in various diseases. This pilot study aims to explore epigenetic changes (epigenetic age and differentially methylated genes) in patients before and after autologous HCT, that can serve as potential biomarkers to better predict HCT outcomes.

METHODS

This study used a prospective longitudinal study design to compare genome wide DNA methylation changes in 36 autologous HCT eligible patients recruited from the Cellular Immunotherapies and Transplant clinic at a designated National Cancer Center.

RESULTS

Genome-wide DNA methylation, measured by the Illumina Infinium Human Methylation 850K BeadChip, showed a significant difference in DNA methylation patterns post-HCT compared to pre-HCT. Compared to baseline levels of DNA methylation pre-HCT, 3358 CpG sites were hypo-methylated and 3687 were hyper-methylated. Identified differentially methylated positions overlapped with genes involved in hematopoiesis, blood cancers, inflammation and immune responses. Enrichment analyses showed significant alterations in biological processes such as immune response and cell structure organization, however no significant pathways were noted. Though participants had an advanced epigenetic age compared to chronologic age before and after HCT, both epigenetic age and accelerated age decreased post-HCT.

CONCLUSION

Epigenetic changes, both in epigenetic age and differentially methylated genes were observed in autologous HCT recipients, and should be explored as biomarkers to predict transplant outcomes after autologous HCT in larger, longitudinal studies.

A trans-omics assessment of gene-gene interaction in early-stage NSCLC

Epigenome-wide gene-gene (G × G) interactions associated with non-small-cell lung cancer (NSCLC) survival may provide insights into molecular mechanisms and therapeutic targets. Hence, we proposed a three-step analytic strategy to identify significant and robust G × G interactions that are relevant to NSCLC survival. In the first step, among 49 billion pairs of DNA methylation probes, we identified 175 775 G × G interactions with PBonferroni  ≤ 0.05 in the discovery phase of epigenomic analysis; among them, 15 534 were confirmed with P ≤ 0.05 in the validation phase. In the second step, we further performed a functional validation for these G × G interactions at the gene expression level by way of a two-phase (discovery and validation) transcriptomic analysis, and confirmed 25 significant G × G interactions enriched in the 6p21.33 and 6p22.1 regions. In the third step, we identified two G × G interactions using the trans-omics analysis, which had significant (P ≤ 0.05) epigenetic cis-regulation of transcription and robust G × G interactions at both the epigenetic and transcriptional levels. These interactions were cg14391855 × cg23937960 (βinteraction  = 0.018, P = 1.87 × 10-12 ), which mapped to RELA × HLA-G (βinteraction  = 0.218, P = 8.82 × 10-11 ) and cg08872738 × cg27077312 (βinteraction  = -0.010, P = 1.16 × 10-11 ), which mapped to TUBA1B × TOMM40 (βinteraction =-0.250, P = 3.83 × 10-10 ). A trans-omics mediation analysis revealed that 20.3% of epigenetic effects on NSCLC survival were significantly (P = 0.034) mediated through transcriptional expression. These statistically significant trans-omics G × G interactions can also discriminate patients with high risk of mortality. In summary, we identified two G × G interactions at both the epigenetic and transcriptional levels, and our findings may provide potential clues for precision treatment of NSCLC.

Emerging roles of TRIM27 in cancer and other human diseases

As a member of the TRIM protein family, TRIM27 is a RING-mediated E3 ubiquitin ligase that can mark other proteins for degradation. Its ubiquitination targets include PTEN, IκBα and p53, which allows it to regulate many signaling pathways to exert its functions under both physiological and pathological conditions, such as cell proliferation, differentiation and apoptosis. During the past decades, TRIM27 was reported to be involved in many diseases, including cancer, lupus nephritis, ischemia-reperfusion injury and Parkinson’s disease. Although the research interest in TRIM27 is increasing, there are few reviews about the diverse roles of this protein. Here, we systematically review the roles of TRIM27 in cancer and other human diseases. Firstly, we introduce the biological functions of TRIM27. Next, we focus on the roles of TRIM27 in cancer, including ovarian cancer, breast cancer and lung cancer. At the same time, we also describe the roles of TRIM27 in other human diseases, such as lupus nephritis, ischemia-reperfusion injury and Parkinson’s disease. Finally, we discuss the future directions of TRIM27 research, especially its potential roles in tumor immunity.

Epigenome-wide gene–age interaction study reveals reversed effects of MORN1 DNA methylation on survival between young and elderly oral squamous cell carcinoma patients

DNA methylation serves as a reversible and prognostic biomarker for oral squamous cell carcinoma (OSCC) patients. It is unclear whether the effect of DNA methylation on OSCC overall survival varies with age. As a result, we performed a two-phase gene–age interaction study of OSCC prognosis on an epigenome-wide scale using the Cox proportional hazards model. We identified one CpG probe, cg11676291_MORN1, whose effect was significantly modified by age (HR_discovery = 1.018, p = 4.07 × 10⁻⁰⁷, FDR-q = 3.67 × 10⁻⁰²; HR_validation = 1.058, p = 8.09 × 10⁻⁰³; HR_combined = 1.019, p = 7.36 × 10⁻¹⁰). Moreover, there was an antagonistic interaction between hypomethylation of cg11676291_MORN1 and age (HR_interaction = 0.284; 95% CI, 0.135–0.597; p = 9.04 × 10⁻⁰⁴). The prognosis of OSCC patients was well discriminated by the prognostic score incorporating cg11676291_MORN1–age interaction (HR_{high vs. low} = 3.66, 95% CI: 2.40–5.60, p = 1.93 × 10⁻⁰⁹). By adding 24 significant gene–age interactions using a looser criterion, we significantly improved the area under the receiver operating characteristic curve (AUC) of the model at 3- and 5-year prognostic prediction (AUC_3-year = 0.80, AUC_5-year = 0.79, C-index = 0.75). Our study identified a significant interaction between cg11676291_MORN1 and age on OSCC survival, providing a potential therapeutic target for OSCC patients.

Circ_0030998 Restrains Cisplatin Resistance Through Mediating miR-1323/PDCD4 Axis in Non-small Cell Lung Cancer

We aimed to explore the underlying mechanism behind the cisplatin (DDP) resistance of non-small cell lung cancer (NSCLC) cells to identify novel potential therapeutic targets to overcome chemoresistance. Real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot assay were applied to analyze RNA and protein expression, respectively. Cell Counting Kit-8 (CCK8) assay was conducted to analyze the DDP resistance of NSCLC cells. Colony formation assay and 5-Ethynyl-2'-deoxyuridine (EdU) assay were performed to analyze cell proliferation ability. Flow cytometry was applied to assess cell apoptosis. Cell migration and invasion were assessed by transwell assays. Cell glycolytic metabolism was analyzed using commercial kits. Dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay were performed to test the intermolecular target relations. Circular RNA_0030998 (circ_0030998) was down-regulated in DDP-resistant NSCLC tissues and cell lines. Circ_0030998 overexpression restrained the DDP resistance, proliferation, migration, invasion and glycolytic metabolism and triggered the apoptosis of NSCLC cells. Circ_0030998 overexpression contributed to the anti-tumor effect of DDP in the growth of xenograft tumor in vivo. MicroRNA-1323 (miR-1323) was a molecular target of circ_0030998 in NSCLC cells. Circ_0030998 overexpression-mediated effects on the DDP resistance and malignant properties of NSCLC cells were largely based on its negative regulation of miR-1323. MiR-1323 interacted with programmed cell death 4 (PDCD4). Circ_0030998 positively regulated PDCD4 expression partly through sponging miR-1323. MiR-1323 silencing restrained DDP resistance and progression of NSCLC partly through up-regulating PDCD4. Circ_0030998 suppressed DDP resistance and NSCLC progression depending on the regulation of miR-1323/PDCD4 axis.

Epigenetic Alterations and Inflammation as Emerging Use for the Advancement of Treatment in Non-Small Cell Lung Cancer

Lung cancer remains one of the most common malignancies in the world. Nowadays, the most common lung cancer is non-small cell lung cancer (NSCLC), namely, adenocarcinoma, squamous cell carcinoma, and large cell lung carcinoma. Epigenetic alterations that refer to DNA methylation, histone modifications, and noncoding RNA expression, are now suggested to drive the genesis and development of NSCLC. Additionally, inflammation-related tumorigenesis also plays a vital role in cancer research and efforts have been attempted to reverse such condition. During the occurrence and development of inflammatory diseases, the immune component of inflammation may cause epigenetic changes, but it is not always certain whether the immune component itself or the stimulated host cells cause epigenetic changes. Moreover, the links between epigenetic alterations and cancer-related inflammation and their influences on the human cancer are not clear so far. Therefore, the connection between epigenetic drivers, inflammation, and NSCLC will be summarized. Investigation on such topic is most likely to shed light on the molecular and immunological mechanisms of epigenetic and inflammatory factors and promote the application of epigenetics in the innovative diagnostic and therapeutic strategies for NSCLC.

A two-phase comprehensive NSCLC prognostic study identifies lncRNAs with significant main effect and interaction

Long noncoding RNA (lncRNA) are involved in regulating physiological behaviors for various malignant tumors, including non-small-cell lung cancer (NSCLC). However, few studies comprehensively evaluated both lncRNA-lncRNA interaction effects and main effects of lncRNA on overall survival of NSCLC. Hence, we performed a two-phase designed study of lncRNA expression in tumor tissues using 604 NSCLC patients from The Cancer Genome Atlas as the discovery phase and 839 patients from Gene Expression Omnibus as the validation phase. In the discovery phase, we adopted a two-step strategy, Screening before Testing, for dimension reduction and signal detection. These candidate lncRNAs first screened out by the weighted random forest (Ranger), were then tested through the Cox proportional hazards model adjusted for covariates. Significant lncRNAs with either type of effects aforementioned were carried forward into the validation phase to confirm their significances again. As a result, in the discovery phase, 19 lncRNAs were identified by Ranger, among which five lncRNAs and one pair of lncRNA-lncRNA interaction exhibited significant effects (FDR-q ≤ 0.05) main and interaction effects on NSCLC survival, respectively, through Cox model. After the independent validation, we finally observed that one lncRNA (ENSG00000227403.1) with main effect was robustly associated with NSCLC prognosis (HR_discovery = 0.90, P = 1.20 × 10^-3; HR_validation = 0.94, P = 4.11 × 10^-3) and one pair of lncRNAs (ENSG00000267121.4 and ENSG00000272369.1) had significant interaction effect on NSCLC survival (HR_discovery = 1.12, P = 3.07 × 10^-4; HR_validation = 1.11, P = 0.0397). Our comprehensive NSCLC prognostic study of lncRNA provided population-level evidence for further functional study.

Epigenome-wide three-way interaction study identifies a complex pattern between TRIM27, KIAA0226, and smoking associated with overall survival of early-stage NSCLC

The interaction between DNA methylation of tripartite motif containing 27 (cg05293407TRIM27 ) and smoking has previously been identified to reveal histologically heterogeneous effects of TRIM27 DNA methylation on early-stage non-small-cell lung cancer (NSCLC) survival. However, to understand the complex mechanisms underlying NSCLC progression, we searched three-way interactions. A two-phase study was adopted to identify three-way interactions in the form of pack-year of smoking (number of cigarettes smoked per day × number of years smoked) × cg05293407TRIM27  × epigenome-wide DNA methylation CpG probe. Two CpG probes were identified with FDR-q ≤ 0.05 in the discovery phase and P ≤ 0.05 in the validation phase: cg00060500KIAA0226 and cg17479956EXT2 . Compared to a prediction model with only clinical information, the model added 42 significant three-way interactions using a looser criterion (discovery: FDR-q ≤ 0.10, validation: P ≤ 0.05) had substantially improved the area under the receiver operating characteristic curve (AUC) of the prognostic prediction model for both 3-year and 5-year survival. Our research identified the complex interaction effects among multiple environment and epigenetic factors, and provided therapeutic target for NSCLC patients.

Circ_0007580 knockdown strengthens the radiosensitivity of non-small cell lung cancer via the miR-598-dependent regulation of THBS2

Background

Radioresistance is a common cause of treatment failure in many cancers, including non‐small cell lung cancer (NSCLC). Circular RNA (circRNA) has been shown to be involved in the radiosensitivity of many cancers. However, the role and mechanism of circ_0007580 in the radiosensitivity of NSCLC remain unclear.

Methods

The expression levels of circ_0007580, miR‐598 and thrombospondin 2 (THBS2) were estimated by quantitative real‐time PCR. The radiosensitivity of cells was measured using colony formation assay. Cell proliferation and apoptosis were assessed by performing cell counting kit 8 assay, colony formation assay, flow cytometry, and by detecting caspase‐3 and caspase‐9 activities. Protein expression was determined using western blot analysis.

Results

Our data showed that circ_0007580 was highly expressed and miR‐598 was lowly expressed in radioresistant NSCLC tissues. Functional experiments suggested that circ_0007580 silencing could improve the radiosensitivity of cells by suppressing cell proliferation and increasing apoptosis. MiR‐598 was confirmed to be a target of circ_0007580, and its inhibitor could reverse the regulation of circ_0007580 on the radiosensitivity of NSCLC cells. MiR‐598 was found to target THBS2. The suppressive effect of miR‐598 on the radiosensitivity of cells could be reversed by THBS2 overexpression. Additionally, circ_0007580 could sponge miR‐598 to regulate THBS2. In vivo experiments showed that knockdown of circ_0007580 enhanced the radiosensitivity of NSCLC tumors.

Conclusions

Our results revealed that circ_0007580 might be a target for improving the radiosensitivity of NSCLC, which was mainly achieved by regulating the miR‐598/THBS2 axis.

Genome-wide gene-smoking interaction study identified novel susceptibility loci for non-small cell lung cancer in Chinese populations

Gene-smoking interactions play important roles in the development of non-small cell lung cancer (NSCLC). To identify single nucleotide polymorphisms (SNPs) that modify the association of smoking behavior with NSCLC risk, we conducted a genome-wide gene-smoking interaction study in Chinese populations. The genome-wide interaction analysis between SNPs and smoking status (ever- versus never-smokers) was carried out using genome-wide association studies (GWAS) of NSCLC, which included 13,327 cases and 13,328 controls. Stratified analysis by histological subtypes was also conducted. We used a genome-wide significance threshold of 5×10 -8 for identifying significant gene-smoking interactions and 1×10 -6 for identifying suggestive results. Functional annotation was performed to identify potential functional SNPs and target genes. We identified three novel loci with significant or suggestive gene-smoking interaction. For NSCLC, the interaction between rs2746087 (20q11.23) and smoking status reached genome-wide significance threshold (OR = 0.63, 95%CI: 0.54-0.74, P = 3.31×10 -8), and the interaction between rs11912498 (22q12.1) and smoking status reached suggestive significance threshold (OR = 0.72, 95%CI: 0.63-0.82, P = 8.10×10 -7). Stratified analysis by histological subtypes identified suggestive interactions between rs459724 (5q11.2) and smoking status (OR = 0.61, 95%CI: 0.51-0.73, P = 7.55×10 -8) in the risk of lung squamous cell carcinoma. Functional annotation indicated that both classic and novel biological processes, including nicotine addiction and airway clearance, may modulate the susceptibility to NSCLC. These novel loci provide new insights into the biological mechanisms underlying NSCLC risk. Independent replication in large-scale studies is needed and experimental studies are warranted to functionally validate these associations.

DNA Methylation Variation Is Identified in Monozygotic Twins Discordant for Non-syndromic Cleft Lip and Palate

Non-syndromic cleft lip with or without cleft palate (NSCLP) is the most common craniofacial birth defect. The etiology of NSCLP is complex with multiple genes and environmental factors playing causal roles. Although studies have identified numerous genetic markers associated with NSCLP, the role of epigenetic variation remains relatively unexplored. Because of their identical DNA sequences, monozygotic (MZ) twins discordant for NSCLP are an ideal model for examining the potential contribution of DNA methylation to non-syndromic orofacial clefting. In this study, we compared the patterns of whole genome DNA methylation in six MZ twin pairs discordant for NSCLP. Differentially methylated positions (DMPs) and regions (DMRs) were identified in NSCLP candidate genes, including differential methylation in MAFB and ZEB2 in two independent MZ twin pairs. In addition to DNA methylation differences in NSCLP candidate genes, we found common differential methylation in genes belonging to the Hippo signaling pathway, implicating this mechanosensory pathway in the etiology of NSCLP. The results of this novel approach using MZ twins discordant for NSCLP suggests that differential methylation is one mechanism contributing to NSCLP, meriting future studies on the role of DNA methylation in familial and sporadic NSCLP.