P2RY6 has a critical role in mouse skin carcinogenesis by regulating the YAP and β-catenin signaling pathways

Bioinformatics analysis reveals novel tumor antigens and immune subtypes of skin cutaneous melanoma contributing to mRNA vaccine development

Introduction

Skin cutaneous melanoma (SKCM) is a common malignant skin cancer with high mortality and recurrence rates. Although the mRNA vaccine is a promising strategy for cancer treatment, its application against SKCM remains confusing. In this study, we employed computational bioinformatics analysis to explore SKCM-associated antigens for an mRNA vaccine and suitable populations for vaccination.

Methods

Gene expression and clinical data were retrieved from GEO and TCGA. The differential expression levels and prognostic index of selected antigens were computed via GEPIA2,while genetic alterations were analyzed using cBioPortal. TIMER was utilized to assess the correlation between antigen-presenting cell infiltration and antigen. Consensus clustering identified immune subtypes, and immune characteristics were evaluated across subtypes. Weighted gene co-expression network analysis was performed to identify modules of immune-related genes.

Results

We discovered five tumor antigens (P2RY6, PLA2G2D, RBM47, SEL1L3, and SPIB) that are significantly increased and mutated, which correlate with the survival of patients and the presence of immune cells that present these antigens. Our analysis revealed two distinct immune subtypes among the SKCM samples. Immune subtype 1 was associated with poorer clinical outcomes and exhibited low levels of immune activity, characterized by fewer mutations and lower immune cell infiltration. In contrast, immune subtype 2 showed higher immune activity and better patient outcomes. Subsequently, the immune landscape of SKCM exhibited immune heterogeneity among patients, and a key gene module that is enriched in immune-related pathways was identified.

Conclusions

Our findings suggest that the identified tumor antigens could serve as valuable targets for developing mRNA vaccines against SKCM, particularly for patients in immune subtype 1. This research provides valuable insights into personalized immunotherapy approaches for this challenging cancer and highlights the advantages of bioinformatics in identifying immune targets and optimizing treatment approaches.

MiRS-HF: A Novel Deep Learning Predictor for Cancer Classification and miRNA Expression Patterns

Cancer classification and biomarker identification are crucial for guiding personalized treatment. To make effective use of miRNA associations and expression data, we have developed a deep learning model for cancer classification and biomarker identification. We propose an approach for cancer classification called MiRNA Selection and Hybrid Fusion (MiRS-HF), which consists of early fusion and intermediate fusion. The early fusion involves applying a Layer Attention Graph Convolutional Network (LAGCN) to a miRNA-disease heterogeneous network, resulting in a miRNA-disease association degree score matrix. The intermediate fusion employs a Graph Convolutional Network (GCN) in the classification tasks, weighting the expression data based on the miRNA-disease association degree score. Furthermore, MiRS-HF can identify the important miRNA biomarkers and their expression patterns. The proposed method demonstrates superior performance in the classification tasks of six cancers compared to other methods. Simultaneously, we incorporated the feature weighting strategy into the comparison algorithm, leading to a significant improvement in the algorithm's results, highlighting the extreme importance of this strategy.

P2RY6 deletion promotes UVB-induced skin carcinogenesis by activating the PI3K/AKT signal pathway

Our previous research has demonstrated that P2RY6 functions as an oncogene in DMBA/TPA-induced two-stage chemical skin carcinogenesis in mice. However, considering that human skin cancer is predominantly attributed to UV radiation from sunlight, additional investigations are needed to elucidate the role of P2RY6 in UVB-induced skin carcinogenesis. Surprisingly, we found that P2ry6-deficient mice exhibited marked promotion to UVB-induced skin papilloma formation compared with wild-type mice, suggesting its tumor-suppressive role in UVB-induced skin cancer. Additionally, a P2ry6 gene knockout promoted skin hyperplasia induced by short-term UVB irradiation, while UDP, the ligand of P2RY6, could inhibit the short-term UVB-induced increase of epiderma thickness in mouse skin. Furthermore, UVB irradiation could significantly upregulate P2RY6 expression in human and mouse skin cells. These results indicated that P2RY6 may play a crucial protective role in resisting the UVB-induced formation of skin tumors. At the molecular level, the loss of the P2RY6 gene inhibits the ubiquitination modification and expression of XPC after UVB irradiation in skin keratinocytes, resulting in the accumulation of CPDs (cyclobutane pyrimidine dimers). We have also demonstrated that P2RY6 deletion activates the PI3K/AKT signaling pathway both in vitro and in vivo. The CPD accumulation and acute inflammatory response enhanced by the loss of the P2RY6 gene can be reversed by an AKT inhibitor. These findings suggest that P2RY6 may act as a tumor suppressor in UVB-induced skin cancer by regulating the PI3K/AKT signaling pathway.

YAP/TAZ Signalling Controls Epidermal Keratinocyte Fate

The paralogues Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) control cell proliferation and cell fate determination from embryogenesis to ageing. In the skin epidermis, these proteins are involved in both homeostatic cell renewal and injury-induced regeneration and also drive carcinogenesis and other pathologies. YAP and TAZ are usually considered downstream of the Hippo pathway. However, they are the central integrating link for the signalling microenvironment since they are involved in the interplay with signalling cascades induced by growth factors, cytokines, and physical parameters of the extracellular matrix. In this review, we summarise the evidence on how YAP and TAZ are activated in epidermal keratinocytes; how YAP/TAZ-mediated signalling cooperates with other signalling molecules at the plasma membrane, cytoplasmic, and nuclear levels; and how YAP/TAZ ultimately controls transcription programmes, defining epidermal cell fate.

Prognostic prediction using a gene signature developed based on exhausted T cells for liver cancer patients

Background

Liver hepatocellular carcinoma (LIHC) is a solid primary malignancy with poor prognosis. This study discovered key prognostic genes based on T cell exhaustion and used them to develop a prognostic prediction model for LIHC.

Methods

SingleR's annotations combined with Seurat was used to automatically annotate the single-cell clustering results of the LIHC dataset GSE166635 downloaded from the Gene Expression Omnibus (GEO) database and to identify clusters related to exhausted T cells. Patients were classified using ConsensusClusterPlus package. Next, weighted gene co-expression network analysis (WGCNA) package was employed to distinguish key gene module, based on which least absolute shrinkage and selection operator (Lasso) and multi/univariate cox analysis were performed to construct a RiskScore system. Kaplan-Meier (KM) analysis and receiver operating characteristic curve (ROC) were employed to evaluate the efficacy of the model. To further optimize the risk model, a nomogram capable of predicting immune infiltration and immunotherapy sensitivity in different risk groups was developed. Expressions of genes were measured by quantitative real-time polymerase chain reaction (qRT-PCR), and immunofluorescence and Cell Counting Kit-8 (CCK-8) were performed for analyzing cell functions.

Results

We obtained 18,413 cells and clustered them into 7 immune and non-immune cell subpopulations. Based on highly variable genes among T cell exhaustion clusters, 3 molecular subtypes (C1, C2 and C3) of LIHC were defined, with C3 subtype showing the highest score of exhausted T cells and a poor prognosis. The Lasso and multivariate cox analysis selected 7 risk genes from the green module, which were closely associated with the C3 subtype. All the patients were divided into low- and high-risk groups based on the medium value of RiskScore, and we found that high-risk patients had higher immune infiltration and immune escape and poorer prognosis. The nomogram exhibited a strong performance for predicting long-term LIHC prognosis. In vitro experiments revealed that the 7 risk genes all had a higher expression in HCC cells, and that both liver HCC cell numbers and cell viability were reduced by knocking down MMP-9.

Conclusion

We developed a RiskScore model for predicting LIHC prognosis based on the scRNA-seq and RNA-seq data. The RiskScore as an independent prognostic factor could improve the clinical treatment for LIHC patients.

Genome-wide runs of homozygosity signatures in diverse Indian goat breeds

The present study analyzed ROH and consensus ROH regions in 102 animals of eleven diverse Indian goat (Capra hircus) breeds using whole genome sequencing. A total of 51,705 ROH and 21,271 consensus regions were identified. The mean number of ROH per animal was highest in the meat breed, Jharkhand Black (2693) and lowest in the pashmina breed, Changthangi (60). The average length of ROH (ALROH) was maximum in Kanniadu (974.11 Kb) and minimum in Tellicherry (146.98 Kb). Long ROH is typically associated with more recent inbreeding, whereas short ROH is connected to more ancient inbreeding. The overall ROH-based genomic inbreeding (FROH) was highest for Jharkhand Black (0.602) followed by Kanniadu (0.120) and Sangamneri (0.108) among all breeds. FROH of Jharkhand Black was higher than Kanniadu  up to 5 Mb ROH length category. However, in > 20 Mb ROH length category, Kanniadu (0.98)  exhibited significantly higher FROH than Jharkhand Black (0.46). This  implies that Kanniadu had higher levels of recent inbreeding than Jharkhand Black. Despite this, due to the presence of both recent and ancient inbreeding, Jharkhand Black  demonstrated higher overall FROH compared to Kanniadu. ROH patterns revealed dual purpose (meat and dairy) and pashmina breeds as less consanguineous while recent inbreeding was apparent in meat breeds. Analysis of ROH consensus regions identified selection sweeps in key genes governing intramuscular fat deposition, meat tenderisation, lean meat production and carcass weight (CDK4, ALOX15, CASP9, PRDM16, DVL1) in meat breeds; milk fat percentage and mammary gland development (POLD1, NOTCH2, ARHGAP35) in dual purpose (meat and dairy) breeds; while cold adaptation and hair follicle development (APOBEC1, DNAJC3, F2RL1, FGF9) in pashmina breed. MAPK, RAS, BMP and Wnt signaling pathways associated with hair follicle morphogenesis in Changthangi were also identified. PCA analysis based on ROH consensus regions revealed that meat breeds are more diverse than other goat breeds/populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-03921-y.

The role of P2Y6 receptor in the pathogenesis of cardiovascular and inflammatory diseases

The purinergic receptor P2Y6 receptor (P2Y6R) is a member of the G protein-coupled receptors (GPCR) family. P2Y6R is widely expressed in various cell types and plays a critical role in physiological processes, where it is activated by extracellular uridine diphosphate (UDP) and mobilizes Ca2+ via the Gαq/11 protein pathway. We have recently discovered the pathophysiological role of P2Y6R in cardiovascular and inflammatory diseases, including inflammatory bowel disease and non-alcoholic fatty liver disease. Furthermore, we uncovered the redox-dependent internalization of P2Y6R. In this review, we provide a comprehensive overview of the pathophysiological activity of P2Y6R in cardiovascular and inflammatory diseases. Additionally, we discuss the concept of atypical internalization control of GPCRs, which may be applied in the prevention and treatment of intestinal inflammation and cardiovascular remodeling.

Knockout of Purinergic P2Y6 Receptor Fails to Improve Liver Injury and Inflammation in Non-Alcoholic Steatohepatitis

Nonalcoholic steatohepatitis (NASH) is a disease that progresses from nonalcoholic fatty liver (NAFL) and which is characterized by inflammation and fibrosis. The purinergic P2Y₆ receptor (P2Y₆R) is a pro-inflammatory G_q/G₁₂ family protein-coupled receptor and reportedly contributes to intestinal inflammation and cardiovascular fibrosis, but its role in liver pathogenesis is unknown. Human genomics data analysis revealed that the liver P2Y₆R mRNA expression level is increased during the progression from NAFL to NASH, which positively correlates with inductions of C-C motif chemokine 2 (CCL2) and collagen type I α1 chain (Col1a1) mRNAs. Therefore, we examined the impact of P2Y₆R functional deficiency in mice crossed with a NASH model using a choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD). Feeding CDAHFD for 6 weeks markedly increased P2Y₆R expression level in mouse liver, which was positively correlated with CCL2 mRNA induction. Unexpectedly, the CDAHFD treatment for 6 weeks increased liver weights with severe steatosis in both wild-type (WT) and P2Y₆R knockout (KO) mice, while the disease marker levels such as serum AST and liver CCL2 mRNA in CDAHFD-treated P2Y₆R KO mice were rather aggravated compared with those of CDAHFD-treated WT mice. Thus, P2Y₆R may not contribute to the progression of liver injury, despite increased expression in NASH liver.

Pyrimidinergic receptor P2Y6 expression is elevated in lung adenocarcinoma and is associated with poor prognosis

BACKGROUD

Previous in vitro studies have indicated that pyrimidinergic receptor P2Y6 (P2RY6, P2Y6 receptor) may function as a cancer-promoting factor in lung adenocarcinoma (LUAD). However, the prognostic significance of P2RY6 expression in LUAD has not been investigated.

OBJECTIVE

This study aimed to assess the impact of P2RY6 expression on the survival of patients with LUAD.

METHODS

First, we assessed P2RY6 mRNA and protein expression in LUAD and non-cancerous lung tissues using the online bioinformatics analysis tool GEPIA, fresh LUAD tissues, and LUAD tissue microarrays (TMAs). Second, we investigated the correlation between P2RY6 expression and clinicopathological parameters of LUAD patients based on data from The Cancer Genome Atlas (TCGA) database and TMAs. Finally, we analyzed the prognostic significance of P2RY6 expression in LUAD using the online survival analysis tool Kaplan-Meier Plotter and data from TMAs.

RESULTS

We demonstrated that P2RY6 mRNA and protein expression levels in LUAD tissues were significantly higher than those in non-cancerous lung tissues. The expression of P2RY6 in LUAD was positively correlated with poor differentiation, more lymph node metastasis, and more advanced clinical stage. Higher P2RY6 expression level was correlated with shorter survival of the LUAD patients. Univariate and multivariate Cox regression analyses indicated that higher P2RY6 tumor expression was an independent unfavorable prognostic factor for LUAD patients.

CONCLUSIONS

P2RY6 expression was elevated in LUAD and correlated with poor prognosis.

Integrative analyses of genes related to liver ischemia reperfusion injury

Background

Liver ischemia reperfusion injury (LIRI) is not only a common injury during liver transplantation and major hepatic surgery, but also one of the primary factors that affect the outcome of postoperative diseases. However, there are still no reliable ways to tackle the problem. Our study aimed to find some characteristic genes associated with immune infiltration that affect LIRI, which can provide some insights for future research in the future. Therefore, it is essential for the treatment of LIRI, the elucidation of the mechanisms of LIRI, and exploring the potential biomarkers. Efficient microarray and bioinformatics analyses can promote the understanding of the molecular mechanisms of disease occurrence and development.

Method

Data from GSE151648 were downloaded from GEO data sets, and we performed a comprehensive analysis of the differential expression, biological functions and interactions of LIRI-associated genes. Then we performed Gene ontology (GO) analysis and Kyotoencydlopedia of genes and genomes (KEGG) enrichment analysis of DEGs. At last, we performed a protein-protein interaction network to screen out hub genes.

Results

A total of 161 differentially expressed genes (DEGs) were identified. GO analysis results revealed that the changes in the modules were mostly enriched in the neutrophil degranulation, neutrophil activation involved in immune response, and neutrophil mediated immunity. KEGG enrichment analysis of DEGs demonstrated that LIRI mainly involved the cytokine-cytokine receptor interaction. Our data indicated that macrophages and neutrophils are closely related to LIRI. 9 hub genes were screened out in the protein-protein interaction network.

Conclusions

In summary, our data indicated that neutrophil degranulation, neutrophil activation involved in immune response, neutrophil mediated immunity and cytokine-cytokine receptor interaction may play a key role in LIRI, HRH1, LRP2, P2RY6, PKD1L1, SLC8A3 and TNFRSF8, which were identified as potential biomarkers in the occurrence and development of LIRI. However, further studies are needed to validate these findings and explore the molecular mechanism of these biomarkers in LIRI.