Evolution of Endogenous Retroviruses in the Subfamily of Caprinae.

The interest in endogenous retroviruses (ERVs) has been fueled by their impact on the evolution of the host genome. In this study, we used multiple pipelines to conduct a de novo exploration and annotation of ERVs in 13 species of the Caprinae subfamily. Through analyses of sequence identity, structural organization, and phylogeny, we defined 28 ERV groups within Caprinae, including 19 gamma retrovirus groups and 9 beta retrovirus groups. Notably, we identified four recent and potentially active groups prevalent in the Caprinae genomes. Additionally, our investigation revealed that most long noncoding genes (lncRNA) and protein-coding genes (PC) contain ERV-derived sequences. Specifically, we observed that ERV-derived sequences were present in approximately 75% of protein-coding genes and 81% of lncRNA genes in sheep. Similarly, in goats, ERV-derived sequences were found in approximately 74% of protein-coding genes and 75% of lncRNA genes. Our findings lead to the conclusion that the majority of ERVs in the Caprinae genomes can be categorized as fossils, representing remnants of past retroviral infections that have become permanently integrated into the genomes. Nevertheless, the identification of the Cap_ERV_20, Cap_ERV_21, Cap_ERV_24, and Cap_ERV_25 groups indicates the presence of relatively recent and potentially active ERVs in these genomes. These particular groups may contribute to the ongoing evolution of the Caprinae genome. The identification of putatively active ERVs in the Caprinae genomes raises the possibility of harnessing them for future genetic marker development.

Identification of CLIC5 as a Prognostic Biomarker and Correlated Immunomodulator for Lung Adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most common pathological types of lung cancer. The gene Chloride Intracellular Channel 5 (CLIC5) has an important role in neurophysiology, cardiovascular biology, and tumour biology. Here, we explored the prognostic value and immune infiltration of CLIC5 expression in LUAD patients. METHODS: We extracted transcriptional LUAD data from The Cancer Genome Atlas (TCGA) and the University of Alabama Cancer Database to explore CLIC5 expression profiles and their relation to CLIC5 and clinicopathological parameters. The relationship between CLIC5 and survival time was explored using Kaplan-Meier Plotter. Then, we integrated the data from TCGA and the Gene Expression Omnibus (GEO) database to perform univariate and multivariate Cox regression. We performed CLIC5 immunohistochemical staining on 167 lung adenocarcinoma samples for further verification. In addition, we analysed the Gene Ontology (GO) database, Kyoto Encyclopaedia of Genes and Genomes pathways and network analysis of protein-protein interactions in lung tissue, to explore the potential mechanism of CLIC5. To analyse the correlation between immune infiltration and CLIC5 expression, we first compared the expression of immune cells in tumour tissues and normal tissues based on the TCGA and GEO databases. We found 51 immunomodulators related to CLIC5 and structured their enrichment pathways as well as those of 50 correlated genes. We used a Cox regression model to identify multiple-gene risk prediction signatures. Finally, we assessed the prognostic accuracy of the risk scores via receiver operating characteristic curves. RESULTS: CLIC5 expression levels were significantly lower in LUAD tissue than in normal tissue. Lower CLIC5 expression was negatively correlated to the overall survival of LUAD patients based on survival analysis. We identified CLIC5 as an independent prognosis predictor. Functional network analysis suggested that CLIC5 is related to multiple pathways. CLIC5 expression is closely related to infiltration levels of many immune cells and immune marker sets in LUAD patients. Furthermore, the risk score based on immunomodulators related to CLIC5 was an independent prognosis predictor in the TCGA lung cohorts. CONCLUSION: Our findings suggest that CLIC5 is a promising molecular marker for the prognosis and immune infiltration of LUAD patients.

Integrated single-cell and transcriptome sequencing analyses develops a metastasis-based risk score system for prognosis and immunotherapy response in uveal melanoma.

Background: Uveal melanoma (UM) is the most frequent ocular neoplasm with a strong metastatic ability. The prognostic value of metastasis-associated genes (MAGs) of UM remains unclear. It is urgent to develop a prognostic score system according to the MAGs of UM. Methods: Unsupervised clustering was used to identify MAGs-based molecular subtypes. Cox methods were utilized to generate a prognostic score system. The prognostic ability of the score system was detected by plotting ROC and survival curves. The immune activity and underlying function were depicted by CIBERSORT GSEA algorithms. Results: Gene cluster analysis determined two MAGs-based subclusters in UM, which were remarkably different in clinical outcomes. A risk score system containing six MAGs (COL11A1, AREG, TIMP3, ADAM12, PRRX1 and GAS1) was set up. We employed ssGSEA to compare immune activity and immunocyte infiltration between the two risk groups. Notch, JAK/STAT and mTOR pathways were greatly enriched in the high-risk group. Furthermore, we observed that knockdown of AREG could inhibit UM proliferation and metastasis by in vitro assays. Conclusion: The MAGs-based subtype and score system in UM can enhance prognosis assessment, and the core system provides valuable reference for clinical decision-making.

A prognostic model and immune regulation analysis of uterine corpus endometrial carcinoma based on cellular senescence.

Background: This study aimed to explore the clinical significance of cellular senescence in uterine corpus endometrial carcinoma (UCEC). Methods: Cluster analysis was performed on GEO data and TCGA data based on cellular senescence related genes, and then performed subtype analysis on differentially expressed genes between subtypes. The prognostic model was constructed using Lasso regression. Survival analysis, microenvironment analysis, immune analysis, mutation analysis, and drug susceptibility analysis were performed to evaluate the practical relevance. Ultimately, a clinical nomogram was constructed and cellular senescence-related genes expression was investigated by qRT-PCR. Results: We ultimately identified two subtypes. The prognostic model divides patients into high-risk and low-risk groups. There were notable discrepancies in prognosis, tumor microenvironment, immunity, and mutation between the two subtypes and groups. There was a notable connection between drug-sensitive and risk scores. The nomogram has good calibration with AUC values between 0.75-0.8. In addition, cellular senescence-related genes expression was investigated qRT-PCR. Conclusion: Our model and nomogram may effectively forecast patient prognosis and serve as a reference for patient management.

HPV-Related Prognostic Signature Predicts Survival in Head and Neck Squamous Cell Carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers, worldwide. Considering the role of human papilloma virus (HPV) in tumor development and sensitivity to treatment of HNSCC, we aimed to explore the prognostic classification ability of HPV-related signatures in head and neck cancer. Methods: HPV-related signatures were screened out based on Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. HPV-related signatures with prognostic value were identified through univariate Cox regression analysis and a risk signature was established by least absolute shrinkage and selection operator (LASSO). Further, we developed a nomogram by integrating independent prognostic factors. Results: A total of 55 HPV-associated signatures were differentially expressed and ten of them were associated with prognosis of HNSCC patients. The prognostic signature based on CDKN2A, CELSR3, DMRTA2, SERPINE1, TJP3, FADD, and IGF2BP2 expression was constructed. Univariate and multivariate regression analyses demonstrated that the novel prognostic signature was an independent prognostic factor of HNSCC. The nomogram integrating the prognostic signature and other independent prognostic factors was developed. Conclusion: In summary, the prognostic signature of the HPV-related signatures might serve as an important prognostic biomarker for patients with HNSCC.

Comprehensive analysis of PTPN gene family revealing PTPN7 as a novel biomarker for immuno-hot tumors in breast cancer.

Background: The non-receptor protein tyrosine phosphatase (PTPN) gene family has been considered to be involved in the oncogenesis and development of multiple cancers. However, its prognostic utility and immunological relevance in breast cancer (BrCa) have not been clarified. Methods: A transcriptional level interpretation of the expressions and prognostic values was analyzed using the data from The Cancer Genome Atlas (TCGA) cohort. In addition, GO and DAVID pinpoint the functional enrichment of PTPNs. Moreover, the immune correlations of PTPN7 in BrCa and pan-cancer were further investigated based on the TCGA cohort and were testified using the in-house and the Gene Expression Omnibus (GEO) cohorts. Results: For systematic analysis of the PTPN family, we found that the expression levels of PTPN1, PTPN6, PTPN7, PTPN18, PTPN20, and PTPN22 was promoted in tumor tissues while comparing with paraneoplastic tissues during our study. We further investigated their functions and protein-protein interactions (PPI), and these results strongly suggested that PTPN family was associated with protein dephosphorylation. Next, we performed an immunological relevance analysis and found that PTPN7 was correlated with immune infiltration, suggesting a stronger association of PTPN7 with immuno-hot tumors in BrCa. In addition, results from the in-house cohort confirmed the positive correlation between PTPN7 and PD-L1. The pan-cancer analysis revealed that PTPN7 was related to PD-L1 and CTLA-4 expression in almost all cancer types. Finally, the predictive value of PTPN7 for immunotherapy was significant in two independent GEO cohorts. Conclusion: In conclusion, this is the first extensive research on the correlation between PTPN family expression and immune characterization in BrCa. As results, PTPN7 expression is associated with immuno-hot tumors and could be a promising predictive biomarker for immunotherapy in not only BrCa but multiple cancers.

Molecular subtypes, clinical significance, and tumor immune landscape of angiogenesis-related genes in ovarian cancer.

Angiogenesis is a physiological process, where new blood vessels are formed from pre-existing vessels through the mechanism called sprouting. It plays a significant role in supporting tumor growth and is expected to provide novel therapeutic ideas for treating tumors that are resistant to conventional therapies. We investigated the expression pattern of angiogenesis-related genes (ARGs) in ovarian cancer (OV) from public databases, in which the patients could be classified into two differential ARG clusters. It was observed that patients in ARGcluster B would have a better prognosis but lower immune cell infiltration levels in the tumor microenvironment. Then ARG score was computed based on differentially expressed genes via cox analysis, which exhibited a strong correlation to copy number variation, immunophenoscore, tumor mutation load, and chemosensitivity. In addition, according to the median risk score, patients were separated into two risk subgroups, of which the low-risk group had a better prognosis, increased immunogenicity, and stronger immunotherapy efficacy. Furthermore, we constructed a prognostic nomogram and demonstrated its predictive value. These findings help us better understand the role of ARGs in OV and offer new perspectives for clinical prognosis and personalized treatment.

Overexpression of CDCP1 is Associated with Poor Prognosis and Enhanced Immune Checkpoints Expressions in Breast Cancer.

CUB-domain containing protein 1 (CDCP1) is a transmembrane protein acting as an effector of SRC family kinases, which play an oncogenic role in multiple human cancers. However, its clinical and immune correlations in breast cancer (BrCa) have not been explored. To define the expression, prognostic value, and potential molecular role of CDCP1 in BrCa, multiple public datasets, and an in-house cohort were used. Compared with paratumor tissue, CDCP1 was remarkably upregulated in the tumor tissues at both mRNA and protein levels. In the in-house cohort, CDCP1 protein expression was related to several clinicopathological parameters, including age, ER status, PR status, molecular type, and survival status. Kaplan-Meier analysis and Cox regression analysis exhibited that CDCP1 was an important prognostic biomarker in BrCa. In addition, enrichment analysis uncovered that CDCP1 was not only involved in multiple oncogenic pathways, but correlated with overexpression of immune checkpoints. Overall, we reported that increased expression of CDCP1 is a favorable prognostic factor in patients with BrCa. In addition, the correlations between CDCP1 and immune checkpoints provide a novel insight into the adjuvant treatment for immune checkpoint blockade via targeting CDCP1.

Peroxidase is a novel potential marker in glioblastoma through bioinformatics method and experimental validation.

Peroxidase (PXDN), a specific extracellular matrix (ECM)-associated protein, has been determined as a tumor indicator and therapeutic target in various tumors. However, the effects of PXDN in prognostic performance and clinical implications in glioblastoma multiforme (GBM) remains unknown. Here, we assessed PXDN expression pattern and its performance on prognosis among GBM cases from TCGA and CGGA databases. PXDN was up-regulated within GBM samples in comparison with normal control. High PXDN expression was a dismal prognostic indicator in GBM. Single cell RNA analysis was conducted to detect the cell localization of PXDN. We also set up a PPI network to explore the interacting protein associated with PXDN, including TSKU, COL4A1 and COL5A1. Consistently, functional enrichment analysis revealed that several cancer hallmarks were enriched in the GBM cases with high PXDN expression, such as epithelial-mesenchymal transition (EMT), fatty acid metabolism, glycolysis, hypoxia, inflammatory response, and Wnt/beta-catenin signaling pathway. Next, this study analyzed the association of PXDN expression and immunocyte infiltration. PXDN expression was in direct proportion to the infiltrating degrees of NK cells resting, T cells regulatory, M0 macrophage, monocytes and eosinophils. The roles of PXDN on immunity were further estimated by PXDN-associated immunomodulators. In addition, four prognosis-related lncRNAs co-expressed with PXDN were identified. Finally, we observed that PXDN depletion inhibits GBM cell proliferation and migration by in vitro experiments. Our data suggested that PXDN has the potential to be a powerful prognostic biomarker, which might offer a basis for developing therapeutic targets for GBM.

Systematic Characterization of Expression Patterns and Immunocorrelations of Formin-Like Genes in Breast Cancer.

Background: Members of the formin-like gene (FMNL) family are required for cytoskeleton-related processes, and their expressions are implicated to the progression of a multitude of malignancies. However, there are insufficient studies on transcription factors and promising prognosis benefit of FMNLs during the genesis of breast cancer (BrCa). Methods: The transcriptional levels of FMNL family members in primary BrCa tissues and their association with intrinsic subclasses were analyzed using the UALCAN database. Then, the prognostic values of FMNLs in BrCa patients were investigated via the Kaplan-Meier plotter. Moreover, the correlations between FMNL expression levels and immune infiltrations were analyzed using the TIMER database. In addition, the expression patterns of FMNLs in BrCa were investigated by single-cell RNA-sequencing (scRNA-seq) analysis and were validated by immunohistochemistry (IHC) staining. Results: The transcriptional level of FMNL1 was shown to be considerably increased in BrCa. It is surprising that the transcriptional quantities of FMNL2 and FMNL3 were substantially reduced. In addition, during the comparison of several BrCa subclasses, FMNL1 and FMNL2 mRNA levels of patients with HER2-positive and triple-negative BrCa subclasses increased, while FMNL3 mRNA levels reduced. With the processions of experimentation, high FMNL1 expression was hopefully linked to well clinical outcome, while high FMNL2 expression predicted poor prognosis. Moreover, FMNL1 was highly expressed in tumor-infiltrating immune cells (TIICs) in tumor tissues. Last but not least, FMNL1 was highly expressed in TIICs and served as a gene marker for TIICs. Conclusions: The fact and result which we analyzed demonstrate FMNL1 as a diagnostic marker for TIICs by comprehensively elucidating the expression patterns and changeable prognostic implications of FMNLs in BrCa clinical applications.

The IFN-γ-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma.

Background: One of the most common diseases that have a negative impact on women's health is endometrial carcinoma (EC). Advanced endometrial cancer has a dismal prognosis and lacks solid prognostic indicators. IFN-γ is a key cytokine in the inflammatory response, and it has also been suggested that it has a role in the tumor microenvironment. The significance of IFN-γ-related genes and long non-coding RNAs in endometrial cancer, however, is unknown. Methods: The Cancer Genome Atlas (TCGA) database was used to download RNA-seq data from endometrial cancer tissues and normal controls. Genes associated with IFN-γ were retrieved from the gene set enrichment analysis (GSEA) website. Co-expression analysis was performed to find lncRNAs linked to IFN-γ gene. The researchers employed weighted co-expression network analysis (WGCNA) to find lncRNAs that were strongly linked to survival. The prognostic signature was created using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. The training cohort, validation cohort, and entire cohort of endometrial cancer patients were then split into high-risk and low-risk categories. To investigate variations across different risk groups, we used survival analysis, enrichment analysis, and immune microenvironment analysis. The platform for analysis is R software (version X64 3.6.1). Results: Based on the transcript expression of IFN-γ-related lncRNAs, two distinct subgroups of EC from TCGA cohort were formed, each with different outcomes. Ten IFN-γ-related lncRNAs were used to build a predictive signature using Cox regression analysis and the LASSO regression, including CFAP58, LINC02014, UNQ6494, AC006369.1, NRAV, BMPR1B-DT, AC068134.2, AP002840.2, GS1-594A7.3, and OLMALINC. The high-risk group had a considerably worse outcome (p < 0.05). In the immunological microenvironment, there were also substantial disparities across different risk categories. Conclusion: Our findings give a reference for endometrial cancer prognostic type and immunological status assessment, as well as prospective molecular markers for the disease.

Statin shapes inflamed tumor microenvironment and enhances immune checkpoint blockade in non-small cell lung cancer.

Immune checkpoint blockade (ICB) therapy has achieved breakthroughs in the treatment of advanced non-small cell lung cancer (NSCLC). Nevertheless, the low response due to immuno-cold (i.e., tumors with limited tumor-infiltrating lymphocytes) tumor microenvironment (TME) largely limits the application of ICB therapy. Based on the glycolytic/cholesterol synthesis axis, a stratification framework for EGFR-WT NSCLC was developed to summarize the metabolic features of immuno-cold and immuno-hot tumors. The cholesterol subgroup displays the worst prognosis in immuno-cold NSCLC, with significant enrichment of the cholesterol gene signature, indicating that targeting cholesterol synthesis is essential for the therapy for immuno-cold NSCLC. Statin, the inhibitor for cholesterol synthesis, can suppress the aggressiveness of NSCLC in vitro and in vivo and can also drastically reverse the phenotype of immuno-cold to an inflamed phenotype in vivo. This change led to a higher response to ICB therapy. Moreover, both our in-house data and meta-analysis further support that statin can significantly enhance ICB efficacy. In terms of preliminary mechanisms, statin could transcriptionally inhibit PD-L1 expression and induce ferroptosis in NSCLC cells. Overall, we reveal the significance of cholesterol synthesis in NSCLC and demonstrate the improved therapeutic efficacy of ICB in combination with statin. These findings could provide a clinical insight to treat NSCLC patients with immuno-cold tumors.

Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer.

Ovarian cancer (OvCa) is one of the most widespread malignant tumors, which has the highest morbidity and unsatisfactory clinical outcomes among all gynecological malignancies in the world. Previous studies found that cancer-associated fibroblasts (CAFs) play significant roles in tumor growth, progression, and chemoresistance. In the current research, weighted gene co-expression network analysis (WGCNA), univariable COX regression, and the least absolute shrinkage and selection operator (LASSO) analysis were applied to recognize CAF-specific genes. After multiple bioinformatic analyses, four genes (AXL, GPR176, ITGBL1, and TIMP3) were identified as OvCa-specific CAF markers and used to construct the prognostic signature (CAFRS). Furthermore, the specificity of the four genes' expression was further validated at the single-cell level, which was high-selectively expressed in CAFs. In addition, our results showed that CAFRS is an independent significant risk factor affecting the clinical outcomes of OvCa patients. Meanwhile, patients with higher CAFRS were more likely to establish chemoresistance to platinum. Besides, the CAFRS were notably correlated with well-known signal pathways that were related to tumor progression. In summary, our study identifies four CAF-specific genes and constructs a novel prognostic signature, which may provide more insights into precise prognostic assessment in OvCa.

m6A Regulator-Mediated Tumour Infiltration and Methylation Modification in Cervical Cancer Microenvironment.

Background: N6-methyladenosine (m6A) is the most abundant internal mRNA modification in eukaryotic cells. There is accumulating evidence that m6A methylation can play a significant role in the early diagnosis and treatment of cancers. However, the mechanism underlying the involvement of m6A in cervical cancer remains unclear. Methods: Here, we examined the m6A modification patterns of immune cells in the tumour microenvironments (TMEs) of 306 patients with cervical cancer from The Cancer Genome Atlas dataset and analysed the relations between them according to 32 m6A regulators. Immune infiltration in the TME of cervical cancer was analysed using the CIBERSORT algorithm and single-sample gene set enrichment analysis. The m6Ascore was structured though principal component analysis. Results: Two different m6A modification patterns were detected in 306 patients with cervical cancer, designated as m6Acluster A and B. The immune cell infiltration characteristics and biological behaviour differed between the two patterns, with m6Acluster A showing a higher level of immune infiltration. The samples were also divided into two genomic subtypes according to 114 m6A regulatory genes shown to be closely correlated with prognosis on univariate Cox regression analysis. Survival analysis showed that gene cluster B was related to better survival than gene cluster A. Most of the m6A regulators showed higher expression in gene cluster B than in gene cluster A. Single-sample gene set enrichment analysis indicated a higher level of immune cell infiltration in gene cluster A. The m6Ascore signature was examined to determine the m6A modification patterns in cervical cancer. Patients with a high m6Ascore showed better survival, while the low m6Ascore group had a higher mutation frequency and better response to treatment. Conclusions: This study showed that m6A modification patterns play important roles in cervical cancer. Analysis of m6A modification patterns will yield an improved understanding of the TME in cervical cancer, and facilitate the development of better immunotherapy strategies.

GPX4 degradation via chaperone-mediated autophagy contributes to antimony-triggered neuronal ferroptosis.

Exposure to antimony (Sb), recently identified as a nerve pollutant, can result in neuron damage; but, associated-neurotoxicological mechanisms were still not clear. Herein, we assessed the role of ferroptosis in Sb-mediated neurotoxicity and clarified the underlying mechanism. Following Sb exposure, ferroptosis was significantly promoted in vivo and in vitro. Moreover, following use of ferrostatin-1 (fer-1) to inhibit ferroptosis, Sb-induced ferroptosis in PC12 cells was effectively attenuated. Sb accelerated lysosomal transport and subsequent degradation of glutathione peroxidase 4 (GPX4), resulting in ferroptosis. Furthermore, chaperone-mediated autophagy (CMA) was activated following treatment with Sb, while inhibition of CMA by lysosomal associated protein 2 A (LAMP2A) knockdown attenuated Sb-induced GPX4 degradation. Sb treatment also increased expression of the chaperones heat shock cognate protein 70 (HSC70) and heat shock protein 90 (HSP90) and the lysosome receptor LAMP2A, and increased binding of HSP90, HSC70, and LAMP2A with GPX4 was observed, indicating increased formation of the chaperone-GPX4 complex. Finally, GPX4 overexpression significantly protected PC12 cells from activation of Sb-stimulated ferroptosis and subsequent cytotoxicity. Collectively, our results provide a original mechanism by which Sb triggers neurotoxicity, to concluded that Sb stimulates neuronal ferroptosis through CMA-mediated GPX4 degradation.

Construction of a ferroptosis scoring system and identification of LINC01572 as a novel ferroptosis suppressor in lung adenocarcinoma.

Background: Ferroptosis is a novel process of programmed cell death driven by excessive lipid peroxidation that is associated with the development of lung adenocarcinoma. N6-methyladenosine (m6a) modification of multiple genes is involved in regulating the ferroptosis process, while the predictive value of N6-methyladenosine- and ferroptosis-associated lncRNA (FMRlncRNA) in the prognosis of patients remains with LUAD remains unknown. Methods: Unsupervised cluster algorithm was applied to generate subcluster in LUAD according to ferroptosis-associated lncRNA. Stepwise Cox analysis and LASSO algorithm were applied to develop a prognostic model. Cellular location was detected by single-cell analysis. Also, we conducted Gene set enrichment analysis (GSEA) enrichment, immune microenvironment and drug sensitivity analysis. In addition, the expression and function of the LINC01572 were investigated by several in vitro experiments including qRT-PCR, cell viability assays and ferroptosis assays. Results: A novel ferroptosis-associated lncRNAs-based molecular subtype containing two subclusters were determined in LUAD. Then, we successfully created a risk model according to five ferroptosis-associated lncRNAs (LINC00472, MBNL1-AS1, LINC01572, ZFPM2-AS1, and TMPO-AS1). Our nominated model had good stability and predictive function. The expression patterns of five ferroptosis-associated lncRNAs were confirmed by polymerase chain reaction (PCR) in LUAD cell lines. Knockdown of LINC01572 significantly inhibited cell viability and induced ferroptosis in LUAD cell lines. Conclusion: Our data provided a risk score system based on ferroptosis-associated lncRNAs with prognostic value in LUAD. Moreover, LINC01572 may serve as a novel ferroptosis suppressor in LUAD.