Early results of the integrative epigenomic-transcriptomic landscape of colorectal adenoma and cancer.

BACKGROUND: Aberrant methylation is common during the initiation and progression of colorectal cancer (CRC), and detecting these changes that occur during early adenoma (ADE) formation and CRC progression has clinical value. AIM: To identify potential DNA methylation markers specific to ADE and CRC. METHODS: Here, we performed SeqCap targeted bisulfite sequencing and RNA-seq analysis of colorectal ADE and CRC samples to profile the epigenomic-transcriptomic landscape. RESULTS: Comparing 22 CRC and 25 ADE samples, global methylation was higher in the former, but both showed similar methylation patterns regarding differentially methylated gene positions, chromatin signatures, and repeated elements. High-grade CRC tended to exhibit elevated methylation levels in gene promoter regions compared to those in low-grade CRC. Combined with RNA-seq gene expression data, we identified 14 methylation-regulated differentially expressed genes, of which only AGTR1 and NECAB1 methylation had prognostic significance. CONCLUSION: Our results suggest that genome-wide alterations in DNA methylation occur during the early stages of CRC and demonstrate the methylation signatures associated with colorectal ADEs and CRC, suggesting prognostic biomarkers for CRC.

Identification of gene signatures and molecular mechanisms underlying the mutual exclusion between psoriasis and leprosy.

Leprosy and psoriasis rarely coexist, the specific molecular mechanisms underlying their mutual exclusion have not been extensively investigated. This study aimed to reveal the underlying mechanism responsible for the mutual exclusion between psoriasis and leprosy. We obtained leprosy and psoriasis data from ArrayExpress and GEO database. Differential expression analysis was conducted separately on the leprosy and psoriasis using DEseq2. Differentially expressed genes (DEGs) with opposite expression patterns in psoriasis and leprosy were identified, which could potentially involve in their mutual exclusion. Enrichment analysis was performed on these candidate mutually exclusive genes, and a protein-protein interaction (PPI) network was constructed to identify hub genes. The expression of these hub genes was further validated in an external dataset to obtain the critical mutually exclusive genes. Additionally, immune cell infiltration in psoriasis and leprosy was analyzed using single-sample gene set enrichment analysis (ssGSEA), and the correlation between critical mutually exclusive genes and immune cells was also examined. Finally, the expression pattern of critical mutually exclusive genes was evaluated in a single-cell transcriptome dataset. We identified 1098 DEGs in the leprosy dataset and 3839 DEGs in the psoriasis dataset. 48 candidate mutually exclusive genes were identified by taking the intersection. Enrichment analysis revealed that these genes were involved in cholesterol metabolism pathways. Through PPI network analysis, we identified APOE, CYP27A1, FADS1, and SOAT1 as hub genes. APOE, CYP27A1, and SOAT1 were subsequently validated as critical mutually exclusive genes on both internal and external datasets. Analysis of immune cell infiltration indicated higher abundance of 16 immune cell types in psoriasis and leprosy compared to normal controls. The abundance of 6 immune cell types in psoriasis and leprosy positively correlated with the expression levels of APOE and CYP27A1. Single-cell data analysis demonstrated that critical mutually exclusive genes were predominantly expressed in Schwann cells and fibroblasts. This study identified APOE, CYP27A1, and SOAT1 as critical mutually exclusive genes. Cholesterol metabolism pathway illustrated the possible mechanism of the inverse association of psoriasis and leprosy. The findings of this study provide a basis for identifying mechanisms and therapeutic targets for psoriasis.

Integration of metabolomics and transcriptomics analyses reveals sphingosine-1-phosphate-mediated S1PR2/PI3K/Akt pathway involved in Talaromyces marneffei infection of macrophages.

Talaromycosis is a fatal mycosis caused by the thermally dimorphic fungus Talaromyces marneffei (T. marneffei). The pathogenic mechanisms of talaromycosis are still poorly understood. This work combined metabolomics, transcriptomics, and verification experiments in vivo and in vitro to detect metabolic profiles and differentially expressed genes (DEGs) in T. marneffei infected and uninfected macrophages to explore possible pathogenesis and underlying mechanisms. A total of 256 differential metabolites (117 up-regulated and 148 down-regulated) and 1320 DEGs (1286 up-regulated and 34 down-regulated) were identified between the two groups. Integrative metabolomics and transcriptomics analysis showed sphingolipid signaling pathway is the most influential. Verification experiments showed that compared with the control group, the production of sphingosine-1-phosphate (S1P) and the expression of the S1PR1, S1PR2, phosphor-PI3K, and phosphor-Akt genes involved in the sphingolipid signaling pathway have significantly increased in the T. marneffei infection group (p < 0.05). T. marneffei activates the S1PR2/PI3K/Akt pathways in J774A.1 macrophage, regulation of the S1P singling might serve as a promising therapeutic strategy for talaromycosis.

Corrigendum: IL36G is associated with cutaneous antiviral competence in psoriasis.

[This corrects the article DOI: 10.3389/fimmu.2022.971071.].

L36G is associated with cutaneous antiviral competence in psoriasis.

Background: Psoriasis is a common inflammatory skin disease that has a great impact on patients' physical and mental health. However, the causes and underlying molecular mechanisms of psoriasis are still largely unknown. Methods: The expression profiles of genes from psoriatic lesion samples and skin samples from healthy controls were integrated via the sva software package, and differentially expressed genes (DEGs) between psoriasis and healthy skin were screened by the limma package. Furthermore, GO and KEGG pathway enrichments for the DEGs were performed using the Clusterprofiler package. Protein-protein interaction (PPI) networks for the DEGs were then constructed to identify hub genes. scGESA analysis was performed on a single-cell RNA sequencing dataset via irGSEA. In order to find the cytokines correlated with the hub genes expression, single cell weighted gene co-expression network analyses (scWGCNA) were utilized to build a gene co-expression network. Furthermore, the featured genes of psoriasis found in suprabasal keratinocytes were intersected with hub genes. We then analyzed the expression of the intersection genes and cytokines in the integrated dataset. After that, we used other datasets to reveal the changes in the intersection genes' expression levels during biological therapy. The relationship between intersection genes and PASI scores was also explored. Results: We identified 148 DEGs between psoriatic and healthy samples. GO and KEGG pathway enrichment analysis suggested that DEGs are mainly involved in the defense response to other organisms. The PPI network showed that 11 antiviral proteins (AVPs) were hub genes. scGSEA analysis in the single-cell transcriptome dataset showed that those hub genes are highly expressed in keratinocytes, especially in suprabasal keratinocytes. ISG15, MX1, IFI44L, and IFI27 were the characteristic genes of psoriasis in suprabasal keratinocytes. scWGCNA showed that three cytokines-IL36G, MIF, and IL17RA-were co-expressed in the turquoise module. Only interleukin-36 gamma (IL36G) was positively correlated with AVPs in the integrated dataset. IL36G and AVPs were found co-expressed in a substantial number of suprabasal keratinocytes. Furthermore, we found that the expression levels of IL36G and the 4 AVPs showed positive correlation with PASI score in patients with psoriasis, and that these levels decreased significantly during treatment with biological therapies, but not with methotrexate. Conclusion: IL36G and antiviral proteins may be closely related with the pathogenesis of psoriasis, and they may represent new candidate molecular markers for the occurrence and severity of psoriasis.

Research progress on genetic heterogeneity between primary and paired metastatic colorectal cancer.

Colorectal cancer (CRC) is one of the leading causes of cancer deaths in China. A standard practice in treating metastatic CRC (mCRC) is to predict benefits of the anti-EGFR monoclonal antibody treatment based on the somatic mutation spectrum. Because metastatic samples are difficult to obtain clinically, primary tumors are normally used instead. However, due to the genetic heterogeneity between primary and paired metastatic tumors, primary site biopsy always underrepresents the mutational landscape of metastatic sites. Currently, the extent of genetic heterogeneity between primary and paired mCRC is still under debate. Here, we review comparative studies of primary and matched mCRC and discuss the underlying causes and potential strategies.

Relationship Between Human mutL Homolog 1 (hMLH1) Hypermethylation and Colorectal Cancer: A Meta-Analysis.

BACKGROUND Hypermethylation of CpG islands in gene promoter regions is an important mechanism of gene inactivation in cancers. Promoter hypermethylation of human mutL homolog 1 (hMLH1) has been implicated in a subset of colorectal cancers that show microsatellite instability (MSI), while the connection of the epigenetic inactivation of hMLH1 in colorectal cancers remains unknown. The aim of this study was to evaluate the relationship between the promoter hypermethylation of hMLH1 and colorectal cancers by performing a meta-analysis. MATERIAL AND METHODS Eligible studies were identified through searching PubMed, Cochrane Library, Web of Science, and Google Scholar databases. R Software including meta packages was used to calculate the pooled and odds ratios (ORs) with corresponding confidence intervals (CIs). Funnel plots were also performed to evaluate publication bias. RESULTS This meta-analysis obtained 45 articles, including 4096 colorectal cancer patients, and identified a significant association between hMLH1 hypermethylation and colorectal cancer risk using the fixed-effects model (OR=8.3820; 95% CI, 6.9202~10.1527; z=21.7431; P<0.0001) and random effects model pooled (OR=10.0963; 95% CI, 6.1919~16.4626; z=9.2688; P<0.0001). The significant relationship was found in subgroup analyses. CONCLUSIONS The results of this meta-analysis show a significant association between hMLH1 hypermethylation and colorectal cancer risk.

Colorectal Cancer Genetic Heterogeneity Delineated by Multi-Region Sequencing.

Intratumor heterogeneity (ITH) leads to an underestimation of the mutational landscape portrayed by a single needle biopsy and consequently affects treatment precision. The extent of colorectal cancer (CRC) genetic ITH is not well understood in Chinese patients. Thus, we conducted deep sequencing by using the OncoGxOne™ Plus panel, targeting 333 cancer-specific genes in multi-region biopsies of primary and liver metastatic tumors from three Chinese CRC patients. We determined that the extent of ITH varied among the three cases. On average, 65% of all the mutations detected were common within individual tumors. KMT2C aberrations and the NCOR1 mutation were the only ubiquitous events. Subsequent phylogenetic analysis showed that the tumors evolved in a branched manner. Comparison of the primary and metastatic tumors revealed that PPP2R1A (E370X), SETD2 (I1608V), SMAD4 (G382T), and AR splicing site mutations may be specific to liver metastatic cancer. These mutations might contribute to the initiation and progression of distant metastasis. Collectively, our analysis identified a substantial level of genetic ITH in CRC, which should be considered for personalized therapeutic strategies.