Multi-omics analysis at epigenomics and transcriptomics levels reveals prognostic subtypes of lung squamous cell carcinoma

GWAS reveals Genetic Susceptibility to Air Pollution-Related Asthma Exacerbations in Children of African Ancestry

Background

The relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, mitigation efforts have yielded mixed results, potentially due to genetic variability in the response to AAP. We hypothesize that common single nucleotide polymorphisms (SNPs) are linked to AAP sensitivity and test this through a Genome Wide Association Study (GWAS).

Methods

We selected a cohort of pediatric asthma patients frequently exposed to AAP. Patients experiencing exacerbations immediately following AAP spikes were deemed sensitive. A GWAS compared sensitive versus non-sensitive patients. Findings were validated using data from the All of Us program.

Results

Our study included 6,023 pediatric asthma patients. Due to the association between AAP exposure and race, GWAS analysis was feasible only in the African ancestry cohort. Seven risk loci reached genome-wide significance, including four non-intergenic variants. Two variants were validated: rs111970601 associated with sensitivity to CO (odds ratio [OR], 6.58; PL=L1.63L×L10-8; 95% CI, 3.42-12.66) and rs9836522 to PM2.5 sensitivity (OR 0.75; PL=L3,87 ×L10-9; 95% CI, 0.62-0.91).

Interpretation

While genetic variants have been previously linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. The identified variants implicate genes with a known role in asthma and established links to AAP. Future research should explore how clinical interventions interact with genetic risk to mitigate the effects of AAP, particularly to enhance health equity for vulnerable populations.

What is already known on this topic

The relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, efforts to mitigate the impact of AAP on children with asthma have yielded mixed results, potentially due to genetic variability in response to AAP.

What this study adds

Using publicly available AAP data, we identify which children with asthma experience exacerbations immediately following spikes in AAP. We then conduct a Genome Wide Association Study (GWAS) comparing these patients with those who have no temporal association between AAP spikes and asthma exacerbations, identifying several Single Nucleotide Polymorphisms (SNPs) significantly associated with AAP sensitivity.

How this study might affect research practice or policy

While genetic variants have previously been linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. This creates a framework for identifying children especially at risk when exposed to AAP. These children should be targeted with policy interventions to reduce exposure and may require specific treatments to mitigate the effects of ongoing AAP exposure in the interim.

Epigenetic alterations in urothelial bladder cancer associated with disease outcomes

OBJECTIVES

Bladder cancer (BLCA) is a molecular heterogeneous disease with known genetic distinctive signatures. However, DNA methylation is highly prevalent across a wide range of tumors, suggesting its potential in oncogenesis. Here, we aimed to interrogate the role of nine epigenetic alterations as diagnostic and prognostic markers in BLCA.

METHODS

DNA methylation, gene expression, and clinicopathological information were retrieved from The Cancer Genome Atlas data portal. Methylation values and gene expression were assessed to determine their association with normal and malignant tissue. Additionally, we studied the association between methylation values and clinicopathological variables. For the prognostic model, Kaplan-Meier Survival curves were generated. Lastly, univariate and multivariate analysis were performed to evaluate the simultaneous impact of methylation and clinicopathological variables on the risk of tumor progression and survival.

RESULTS

Nine CpG sites' methylation β -values involved in our study demonstrated different methylation signatures between normal and malignant urothelium. Hypermethylated CpGs were overrepresented in tumor tissue (p < 0.0001). Opposingly, 4 CpG sites showed lower methylation values in tumor samples (p < 0.0001). Cg12743248high and cg17192862low are risk factors for progression-free survival, whereas cg12374721high (HR:3.003 (1.283-7.030)) also demonstrated to be the most valuable independent risk factor for disease progression and a risk factor for overall survival.

CONCLUSIONS

We have identified that methylated cg12374721 shows promise as a diagnostic and independent prognostic marker in BLCA progression.

The predictive value of BTG1 for the response of newly diagnosed acute myeloid leukemia to decitabine

BACKGROUND

Decitabine has been widely used to treat acute myeloid leukemia (AML); however as AML is a heterogeneous disease, not all patients benefit from decitabine. This study aimed to identify markers for predicting the response to decitabine.

METHODS

An intersection of in vitro experiments and bioinformatics was performed using a combination of epigenetic and transcriptomic analysis. A tumor-suppressor gene associated with methylation and the response to decitabine was screened. Then the sensitivity and specificity of this marker in predicting the response to decitabine was confirmed in 54 samples from newly diagnosed AML patients treated with decitabine plus IA regimen in a clinical trial (ChiCTR2000037928).

RESULTS

In vitro experiments showed that decitabine caused hypomethylation and upregulation of BTG1, while downregulation of BTG1 attenuated the inhibitory effect of decitabine. In newly diagnosed AML patients who received decitabine plus IA regimen, the predictive value of BTG1 to predict complete remission (CR) was assigned with a sensitivity of 86.7% and a specificity of 100.0% when BTG1 expression was < 0.292 (determined using real-time quantitative PCR), with area under the curve (AUC) = 0.933, P = 0.021. The predictive value of BTG1 to predict measurable residual disease (MRD) negativity was assigned with a sensitivity of 100.0% and a specificity of 80.0% when BTG1 expression was < 0.292 (AUC = 0.892, P = 0.012). Patients were divided into low and high BTG1 expression groups according to a cutoff of 0.292, and the CR rate of the low-expression group was significantly higher than that of the high-expression group (97.5% vs. 50%, P < 0.001).

CONCLUSIONS

Low expression of BTG1 was associated with CR and MRD negativity in newly diagnosed AML patients treated with a decitabine-containing regimen, suggesting that BTG1 is a potential marker for predicting the response to decitabine in newly diagnosed AML.

CLINICAL TRIAL REGISTRATION

ChiCTR2000037928.

A 15-Gene-Based Risk Signature for Predicting Overall Survival in SCLC Patients Who Have Undergone Surgical Resection

Small cell lung cancer (SCLC) is a malignancy with a poor prognosis whose treatment has not progressed for decades. The survival benefit of surgery and the selection of surgical candidates are still controversial in SCLC. This study is the first report to identify transcriptomic alterations associated with prognosis and propose a gene expression-based risk signature that can be used to predict overall survival (OS) in SCLC patients who have undergone potentially curative surgery. An integrative transcriptome analysis of three gene expression datasets (GSE30219, GSE43346, and GSE149507) revealed 1734 up-regulated and 2907 down-regulated genes. Cox-Mantel test, Cox regression, and Lasso regression analyses were used to identify genes to be included in the risk signature. EGAD00001001244 and GSE60052-cohorts were used for internal and external validation, respectively. Overall survival was significantly poorer in patients with high-risk scores compared to the low-risk group. The discriminatory performance of the risk signature was superior to other parameters. Multivariate analysis showed that the risk signature has the potential to be an independent predictor of prognosis. The prognostic genes were enriched in pathways including regulation of transcription, cell cycle, cell metabolism, and angiogenesis. Determining the roles of the identified prognostic genes in the pathogenesis of SCLC may contribute to the development of new treatment strategies. The risk signature needs to be validated in a larger cohort of patients to test its usefulness in clinical decision-making.

Characteristic of Molecular Subtypes in Lung Squamous Cell Carcinoma Based on Autophagy-Related Genes and Tumor Microenvironment Infiltration

Background

Recently, a large number of studies have sought personalized treatment for lung squamous cell carcinoma (LUSC) by dividing patients into different molecular subtypes. Autophagy plays an important role in maintaining the tumor microenvironment and immune-related biological processes. However, the molecular subtypes mediated by autophagy in LUSC are not clear.

Methods

Based on 490 LUSC samples, we systematically analyzed the molecular subtype modification patterns mediated by autophagy-related genes. The ssGSEA and CIBERSORT algorithm were utilized to quantify the relative abundance of TME cell infiltration. Principal component analysis was used to construct autophagy prognostic score (APS) model.

Results

We identified three autophagy subtypes in LUSC, and their clinical outcomes and TME cell infiltration had significant heterogeneity. Cluster A was rich in immune cell infiltration. The enrichment of EMT stromal pathways and immune checkpoint molecules were significantly enhanced, which may lead to its immunosuppression. Cluster B was characterized by relative immunosuppression and relative stromal activation. Cluster C was activated in biological processes related to repair. Patients with high APS were significantly positively correlated with TME stromal activity and poor survival. Meanwhile, high APS showed an advantage in response to anti-PD1 and anti-CTLA4 immunotherapy.

Conclusion

This study explored the autophagy molecular subtypes in LUSC. We also discovered the heterogeneity of TME cell infiltration driven by autophagy-related genes. The established APS model is of great significance for evaluating the prognosis of LUSC patients, the infiltration of TME cells, and the effect of immunotherapy.

Integrated profiling of human pancreatic cancer organoids reveals chromatin accessibility features associated with drug sensitivity

Chromatin accessibility plays an essential role in controlling cellular identity and the therapeutic response of human cancers. However, the chromatin accessibility landscape and gene regulatory network of pancreatic cancer are largely uncharacterized. Here, we integrate the chromatin accessibility profiles of 84 pancreatic cancer organoid lines with whole-genome sequencing data, transcriptomic sequencing data and the results of drug sensitivity analysis of 283 epigenetic-related chemicals and 5 chemotherapeutic drugs. We identify distinct transcription factors that distinguish molecular subtypes of pancreatic cancer, predict numerous chromatin accessibility peaks associated with gene regulatory networks, discover regulatory noncoding mutations with potential as cancer drivers, and reveal the chromatin accessibility signatures associated with drug sensitivity. These results not only provide the chromatin accessibility atlas of pancreatic cancer but also suggest a systematic approach to comprehensively understand the gene regulatory network of pancreatic cancer in order to advance diagnosis and potential personalized medicine applications.

A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma

Background: The abundant immune-related long non-coding RNA (IRLNRs) in immune cells and immune microenvironment have the potential to forecast prognosis and evaluate the effect of immunotherapy. IRLNRs analysis will provide a new perspective for LUAC research.

Methods: We calculated the immune score of each sample according to the expression levels of immune-related genes (IRGs) and screened the survival-related IRLNRs (sIRLNRs) by Cox regression analysis. The expression levels of AC068338.3 and AL691432.2 in tissues and cell lines were confirmed by RT-qPCR.

Results: 36 IRLNRs were selected by Pearson correlation analysis. Ten sIRLNRs were significantly correlated with the clinical outcomes of LUAC patients. Five sIRLNRs were identified by multivariate COX regression analysis to establish the immune-related risk score model (IRRS). The overall survival (OS) in the high-risk group was shorter than that in the low-risk group. IRRS could be an independent prognostic factor with significant survival correlation The distributions of immune gene concentrations were different between high-risk group and low-risk group. Furthermore, we further verified that the expression levels of AC068338.3 and AL691432.2 in different LUAC cell lines and tumor tissues were lower than that in Human bronchial epithelial cell (HBE) and adjacent tissues respectively. The lower expression levels of AC068338.3 and AL691432.2 were detected with the more advance T-stages.

Conclusions: Our results highlighted some sIRLNRs with significant clinical correlations and demonstrated their monitored and prognostic values for LUAC patients. The results of this study may provide a new perspective for immunological research and immunotherapy strategies.

Signatures of Multi-Omics Reveal Distinct Tumor Immune Microenvironment Contributing to Immunotherapy in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) contains a variety of genomic and epigenomic abnormalities; the effective tumor markers related to these abnormalities need to be further explored.

Methods

Clustering analysis was performed based on DNA methylation (MET), DNA copy number variation (CNV), and mRNA expression data, and the differences in survival and tumor immune microenvironment (TIME) between subtypes were compared. Further, we evaluated the signatures in terms of both prognostic value and immunological characteristics.

Results

There was a positive correlation between MET and CNV in LUAD. Integrative analysis of multi-omics data from 443 samples determined molecular subtypes, iC1 and iC2. The fractions of CD8+ T cells and activated CD4+ T cells were higher, the fraction of Tregs was lower, and the expression level of programmed death-ligand 1 (PD-L1) was higher in iC2 with a poor prognosis showing a higher TIDE score. We selected PTTG1, SLC2A1, and FAM83A as signatures of molecular subtypes to build a prognostic risk model and divided patients into high-risk group and low-risk group representing poor prognosis and good prognosis, respectively, which were validated in 180 patients with LUAD. Further, the low-risk group with lower TIDE score had more infiltrating immune cells. In 100 patients with LUAD, the high-risk group with an immunosuppressive state had a higher expression of PD-L1 and lower counts of CD8+ T cells and dendritic cells.

Conclusions

These findings demonstrated that combined multi-omics data could determine molecular subtypes with significant differences of prognosis and TIME in LUAD and suggested potent utility of the signatures to guide immunotherapy.