Prenatally androgenised (PA) sheep are a clinically realistic model of polycystic ovary syndrome (PCOS). They have dysfunctional subcutaneous adipose tissue (SAT) with reduced adipogenesis in adolescence and enlarged adipocytes with increased inflammation in adulthood. We hypothesised that analysis of SAT in young adults, after adipogenesis is complete but before inflammation is apparent, would give insights into the evolution of adipose tissue dysfunction. Pregnant sheep were treated intramuscularly with 100 mg testosterone propionate or vehicle control (C) twice weekly from day 62-102 of gestation. Weight-matched female offspring (PA = 10; C = 10) were studied up to 22 months of age. Glucose tolerance testing was performed, and at sacrifice SAT was fixed for histological analysis and frozen for RNA sequencing (RNAseq) and gene expression analysis. There was no difference in the average size of SAT adipocytes between PA and C young adults. There were no differences in the expression of the adipogenesis markers PPARG, CEBPA and CEBPB, or the inflammatory markers TNF and IL6, although PA sheep were already hyperinsulinaemic. RNAseq identified 792 potentially differentially expressed (P < 0.05) genes in PA sheep SAT (406 upregulated; 386 downregulated). Ingenuity Pathway Analysis highlighted upregulation of fibrotic pathways in the SAT of PA sheep. POSTN, associated with tissue fibrosis, and COL1A1, COL1A2 and COL3A1 were significantly elevated, and histochemistry showed significantly increased SAT fibrosis in PA sheep. Early fibrotic changes in SAT occur before inflammatory gene expression in PA sheep. A fibrotic barrier to healthy adipocyte expansion may have a mechanistic role in the development of inflammation in PCOS.

Transfer RNAs (tRNAs) are essential regulators of protein synthesis, and dysregulation of their abundance and modification status is involved in many human diseases including cancer. Despite the rapid development of novel tRNA sequencing approaches, due to tRNAs' stable secondary structure and abundant modification sites, the human tRNA landscape has remained mostly unexplored. Here, we evaluated the new RNA004 chemistry of Oxford Nanopore Technologies, that is integrated with updated Dorado base-caller models, for tRNA quantification and modification annotation in human cancer models. We demonstrated that this technology identifies variations in tRNA expression across cancer cell lines and in response to external stress conditions, with highly reproducible results. We also show that analysis of base-calling error rate can indicate the presence of known modifications, including the cancer-associated tRNAPhe-Wybutosine modification. Furthermore, implementing the updated Dorado modification-calling feature, we showed the potential of RNA004 tRNA-seq in predicting common tRNA modifications. We also pinpointed possible limitations and challenges associated with both modification calling methods. Overall, RNA004 tRNA-seq can potentially enhance our understanding of the human tRNAome by simultaneously analyzing both tRNA abundance and modifications.

Genomic instability and the accumulation of DNA damage are hallmarks of cancer, often resulting from defects in DNA repair pathways. While normal cells rely on highly coordinated DNA damage response (DDR) mechanisms to maintain genomic integrity, cancer cells exploit aberrant DDR regulation to sustain uncontrolled proliferation and survival. Despite significant advancements in chemotherapy, targeted therapy, and immunotherapy, the emergence of resistance remains a major challenge in cancer treatment. Small molecule inhibitors targeting key DDR proteins have emerged as promising therapeutic agents, not only as direct anticancer drugs but also as indispensable tools for dissecting the molecular intricacies of DNA repair. Recent therapeutic approaches leverage synthetic lethality and DDR pathway vulnerabilities to selectively eradicate tumor cells while minimizing damage to normal tissues. These inhibitors provide insights into mechanisms of tumor resistance, facilitating the rational design of combination therapies to enhance treatment efficacy. This review examines the latest advancements in DNA repair-targeted therapeutics, with a focus on small molecule inhibitors currently under clinical investigation. Additionally, we discuss emerging strategies for optimizing DDR-targeted interventions, including biomarker-driven patient selection and rational drug combinations. Understanding these molecular interactions will contribute to the development of novel, more effective treatment paradigms for cancer therapy.

The dysfunction of membraneless organelles (MLOs) has been implicated in tumorigenesis and progression by aberrant liquid-liquid phase separation (LLPS). However, the role of MLOs in the prognosis and tumor immune microenvironment (TIME) of colorectal cancer (CRC) remains unclear.

Clear cell renal cell carcinoma (ccRCC) is a prevalent pathological subtype of renal cell carcinoma that arises from renal tubular epithelial cells. ccRCC has long been characterized by high mortality, and at present, surgical resection is the only curative treatment, but its effectiveness is low and survival rates are low. N-acetyltransferase 10 (NAT10) is a protein that acts as an acetyltransferase, has distinct catalytic and regulatory functions, and is involved in the progression of various cancers such as bladder cancer, hepatocellular carcinoma, and multiple myeloma. Ferroptosis is a novel form of programmed cell death that is iron-dependent and distinct from apoptosis, necrosis, and autophagy. Therefore, this study aimed to investigate the potential functions of NAT10 in this context, with a particular focus on its interactions and mechanisms involving ferroptosis.

In breast cancer, elevated serum interleukin-6 (IL-6) level is associated with a poor prognosis during eribulin treatment; however, the mechanisms underlying IL-6-mediated resistance and its potential as a therapeutic target remain unclear. We aimed to determine whether IL-6 is involved in eribulin resistance and evaluate the therapeutic potential of combining eribulin with an IL-6 receptor-specific inhibitor to overcome resistance.

Neoantigens, arising from somatic mutations, have the potential to induce immune responses against tumor cells. As natural neoantigens that drive immune responses are uncommon, some methods to optimize neoantigens have been devised, leading to "heteroclitic" neoantigens capable of triggering cross-immunization. Existing methods, however, concentrate exclusively on the affinity of neoantigens for human leukocyte antigen (HLA), while neglecting the enhancement of their immunogenicity. Here, we developed a machine learning-based method, Naso, which integrates simulated annealing search and multi-objective training to optimize the immunogenicity of neoantigens. We also designed a search space optimization strategy to improve search efficiency. Experimental evaluation demonstrated that Naso outperforms existing methods in enhancing the immunogenicity of neoantigens. Specifically, Naso can transform nonimmunoreactive neoantigens into immunoreactive ones with no more than three mutation amino acids. Moreover, Naso can obtain competitive results in other immunological features, such as binding affinity and presentation. Consequently, Naso-optimized neoantigens can elicit an immune response and facilitate cross-immunization, thereby promoting the development of heteroclitic neoantigen-based vaccines. The source code of Naso is available at https://github.com/lyotvincent/Naso.

This study aims to screen immune metabolism-associated biomarkers for pediatric opsoclonus myoclonus ataxia syndrome (OMAS) in neuroblastoma.

Albumin (ALB) and total protein (TP) are vital constituents of the blood, and their levels and roles in the risk of colorectal cancer (CRC) are of significance. Previous observational studies have reported correlations among ALB, TP, and CRC. However, the existence of a causal relationship between ALB and CRC in European populations has not been adequately investigated and the causal link between TP and CRC remains unexplored. To address these gaps, we applied Mendelian randomization (MR) to investigate the potential causal relationship between ALB, TP, and CRC. Two-sample MR analysis was used to investigate whether there was a causal relationship between ALB, TP, and CRC. Our exposure data were extracted from genome-wide association study (GWAS) databases sourced from the UK Biobank, containing 315,268 and 314,921 Europeans participants for ALB and TP analyses, respectively. Single nucleotide polymorphisms that were significantly associated with ALB and TP were assessed using GWAS datasets. Our data were derived from the FinnGen Consortium CRC GWAS, which contained 6509 CRC cases and 28,7137 controls. Causal inference between ALB, TP, and CRC was performed using 3 MR methods: inverse variance weighting (IVW), MR-Egger, and weighted median. The IVW analysis showed no significant causal association between ALB and CRC (OR = 1.04, 95% CI = 0.89-1.21, P = .65). In contrast, the IVW analysis for TP and CRC showed a significant causal association (OR = 0.78, 95% CI = 0.66-0.92, P = .003), suggesting a reduced risk of CRC. Through a 2-sample MR study investigating the causal relationship between ALB, TP, and CRC in a European population, our findings revealed a significant causal relationship between TP and a reduced risk of CRC.

Previous studies have demonstrated a significant correlation between immune cells and thyroid cancer (TC). Nevertheless, there remains uncertainty regarding whether this association indicates a causal relationship. We performed a bidirectional Mendelian randomization (MR) analysis to explore the causal relationship between 731 immune phenotypes and thyroid cancer. Our primary analytical method was the inverse variance weighting technique, complemented by supporting analyses using weighted median, MR-Egger, simple mode, and weighted mode. Our results were also robustly assessed using sensitivity analyses to account for heterogeneity and potential horizontal pleiotropy. The results from the inverse variance weighting analysis, which examined 7 groups of immune cells in their antithyroid cancer effects, indicated that 11 immune cell traits were positively correlated with the occurrence and progression of thyroid cancer (odds ratio [OR] > 1, P < .05), while 22 immune cell traits showed a negative correlation (OR < 1, P < .05). In the reverse MR analysis, thyroid cancer was positively associated with 2 immune cell phenotypes (P < .05, OR > 1) and negatively associated with 1 immune cell phenotype (P < .05, OR < 1). None of these findings displayed evidence of heterogeneity, horizontal pleiotropy, or reverse causality (P > .05). This research offers a perspective on the biological mechanisms between thyroid cancer and immune cells, contributing to the exploration of early intervention and treatment options.

Acute myeloid leukemia (AML) is a heterogeneous blood cancer that arises from transformed myeloid precursor cells in a compromised bone marrow microenvironment. This environment is essential for AML initiation, progression, and relapse. Alongside oncogenic changes in hematopoietic cells, immunological dysregulation also contributes to leukemogenesis. The present study is aimed to identify prognostic genes in stromal and immune cells associated with AML using the weighted gene co-expression network analysis (WGCNA).

Observational studies suggest an association between nonalcoholic fatty liver disease (NAFLD) and liver cancer, but its causal nature remains unclear. A 2-sample Mendelian randomization (MR) analysis was performed using NAFLD and liver cancer summary statistics from genome-wide association study databases. Instrumental variables satisfying the 3 core MR assumptions were selected. Causal effects were estimated using inverse-variance weighted, MR-Egger, weighted median, and other methods, followed by sensitivity and power analyses. All 4 MR analyses demonstrated a positive causal association between NAFLD and liver cancer risk [odds ratio > 1, inverse-variance weighted P < .001]. Sensitivity analysis indicated no significant level of multiplicity or heterogeneity in the instrumental variables, and individual single nucleotide polymorphisms had no significant impact on the results. However, statistical power was insufficient. This study provides the first MR evidence demonstrating a genetically predicted causal relationship between NAFLD and liver cancer that is consistent across subtypes. Sensitivity analyses confirmed the absence of horizontal pleiotropy or heterogeneity, strengthening the robustness of the findings. These results offer genetic support for early NAFLD intervention to reduce the risk of liver cancer. However, the limited statistical power highlights the need for larger-scale genome-wide association study to identify more and stronger genetic instruments for a more precise quantification of the causal effect of NAFLD on liver cancer risk.

Breast cancer (BC) ranks among the most prevalent cancers in females, with bone metastasis significantly compromising patients' quality of life and survival rates. Enhancing our comprehension of BC bone metastasis mechanisms at the molecular level holds promise for improving BC treatment and prognosis. Leveraging bioinformatics tools, we integrated multiple datasets, conducted comprehensive analyses across various databases, identified biomarkers associated with BC bone metastasis, and constructed a prognostic model. Firstly, 3 BC bone metastasis-related datasets were downloaded from gene expression omnibus, the data were merged, and batch effects were removed, followed by identification of differentially expressed genes (DEGs). Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the DEGs. A protein-protein interaction network was constructed using the STRING database to screen hub genes. Then, survival analysis of hub genes was performed using the Cancer Genome Atlas (TCGA) database. A prognostic model was constructed using key genes with survival differences, and the model was evaluated. Two hundred ninety-two DEGs were identified. Gene ontology and KEGG pathway enrichment analysis yielded 769 biological processes (BPs), 78 cellular components, 43 molecular functions, and 50 KEGG pathways. Fifteen hub genes were selected from the protein-protein interaction network. Survival analysis revealed 6 genes related to BC survival. The prognostic model identified 4 genes with important predictive value for BC prognosis. Our study utilized bioinformatics analysis to identify a series of DEGs related to BC bone metastasis. Based on further selection of hub genes, we constructed a relatively ideal prognostic model for BC, and identified 4 genes (DLGAP5, TPX2, PLK1, and CENPN) with valuable predictive value for BC prognosis.

The study aimed to investigate the prognostic significance of efferocytosis-related genes in ovarian cancer (OC) with regard to cancer development, progression, invasion, and metastasis. OC cohorts were assembled from bioinformatics repositories. Utilizing consensus clustering analysis, distinct clusters were delineated based on the intersection of OC-related genes and efferocytosis-related genes. A prognostic signature specific to efferocytosis in OC was developed using data from The Cancer Genome Atlas, validated against the gene expression omnibus database, and subjected to independent prognostic analysis. Subsequently, a nomogram model was formulated. Moreover, investigations encompassed the immune microenvironment, immunotherapy, mutation profiling, drug sensitivity assessments, drug prediction models, and molecular docking analyses. Finally, quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays were employed to ascertain the mRNA expression levels of key genes. Five key genes, FCGBP, BTN3A3, WDR91, SLC25A45, and BTNL3, were identified as significantly associated with OC. Both datasets and qRT-PCR demonstrated elevated expression levels of FCGBP and WDR91 in OC. Notably, AFLATOXIN B1 exhibited strong binding affinity to SLC25A45, ciclopirox to BTN3A3, and irinotecan to WDR91. The risk score, age, and stage were identified as independent prognostic factors, with the nomogram displaying efficacy in predicting OC patient survival. Variations in the immune cell infiltration profiles, including naive B cells, and expression levels of 6 immune checkpoint genes, such as CTLA4, were notable. High tumor mutation burden scores were associated with improved survival outcomes. Additionally, significant differences in the IC50 values of 123 anticancer drugs were observed between the 2 risk groups. This findings of this study highlight the efficacy of the efferocytosis-associated risk model in predicting the survival outcomes of OC patients, thus providing a novel reference for prognostic prediction in OC patients.

The intricate relationship between the gut microbiota (GM) and immune-mediated diseases deserves deep exploration. Our study focused on investigating the potential causal link between the recently discovered 885 GM and endometrial cancer (EC), as well as determining the role of immune cells in mediating this relationship. Causal relationship between GM and EC was firstly investigated using a 2-sample Mendelian randomization (MR) analysis. Subsequently, a 2-step MR study was conducted to provide evidence for a mediating role of immune traits in this causal pathway. MR analyses revealed genus Bacillus and Bacillaceae A had a protective effect on EC, while Fusobacterium A and GCA-900199385 sp900320755 showed a positive correlation with EC. Mediation analyses indicated that these GM components influence EC through various immune cell traits as mediators, including IgD+ CD38br %lymphocytes and transitional AC on the B cell panel, DP (CD4+CD8+) % leukocytes on the TBNK panel, and CD25 on memory B cells. Our study suggested added genetic evidence support the causal relationship between GM and EC, with a partial contributing role of immune cells in mediating such effects. Further in-depth functional research is warranted to fully explore the mechanisms of intermediation behind this intricate association.

The interplay between sleep characteristics, estrogen sulfotransferase (SULT1E1), and lung cancer may involve complex interactions. While prior research has predominantly examined the association of SULT1E1 with breast cancer and the individual effects of sleep characteristics on lung cancer, the potential multifaceted interactions among these 3 factors remain underexplored. This study employed a two-sample univariable Mendelian randomization framework to systematically examine potential causal associations between 8 distinct sleep-related traits and lung cancer, encompassing its various histological subtypes. Mediation Mendelian randomization (MR) analysis was implemented to assess the putative mediating role of SULT1E1 in these associations. Methodological rigor was ensured through the application of multiple complementary MR approaches. Comprehensive evaluation of heterogeneity and horizontal pleiotropy was conducted utilizing the MR-Egger regression intercept test, Cochran Q statistic, and leave-one-out sensitivity analysis. Furthermore, the Mendelian Randomization Pleiotropy RESidual Sum and Outlier was systematically applied to identify and adjust for potential horizontal pleiotropic effects. Moreover, we employed the false discovery rate method to correct for multiple hypothesis testing and control the risk of false-positive results. Mediation MR analysis, revealed a causal association between sleep duration and a reduced risk of squamous cell lung cancer (SCC), with 9.3% of the effect mediated by SULT1E1. Dozing off during the day was causally associated with a reduced risk of lung cancer and non-small cell lung cancer. Lack of sleep was causally associated with a reduced risk of small cell lung cancer. A causal association was observed between reduced sleep duration and an elevated risk of SCC. Mediation analysis demonstrated that SULT1E1 mediated 9.3% of the total effect of reduced sleep duration on SCC development.

Ovarian cancer (OC) demonstrates the poorest prognosis among gynecological malignancies, with five-year survival rates below 45%, primarily due to late-stage diagnosis. To address this challenge, we systematically identified OC-specific differentially expressed genes (DEGs) to develop a robust diagnostic model based on eleven machine learning algorithms. Furthermore, we explored the potential mechanism of key DEG in OC.

Cisplatin (DDP) is the major chemotherapeutic drug used to treat gastric cancer (GC). However, DDP-associated side effects and resistance chemoresistance have limited its clinical application. Psoralidin (PSO) is the main extract of Psoralea corylifolia and has antitumor effects. The present study is designed to investigate the antitumor functions and mechanisms of PSO and DDP in GC.

Gastric cancer (GC) is a common type of cancer known for its challenges in early detection and unfavorable prognosis. The pathway involving Wnt/β-catenin and the improper regulation of microRNAs (miRNAs), especially miR-27a-3p, are crucial in the advancement of GC. Ursolic acid (UA), which is a naturally occurring anticancer agent, shows promise in the inhibition of GC. Although UA's anticancer effects have been recognized, the underlying molecular mechanisms in GC remain incompletely defined. Our findings indicate that UA strongly restricts the expansion, motility, and invasive behavior of GC cells by dampening activity within the Wnt/β-catenin cascade. Treatment with UA lowered miR-27a-3p expression, and blocking this miRNA further curtailed tumor cell aggressiveness by restoring DKK2, which functions as a suppressor of Wnt-driven signaling. The protein under investigation showed lower expression in advanced tumors. Its expression in these advanced tumors correlated with better pathologic outcomes and survival prognosis. Thus, we can categorize this protein as a novel tumor suppressor in GC. Consistent with these in vitro results, in vivo assays demonstrated that UA effectively curtailed tumor development. Taken together, these findings indicate that UA restricts GC progression via modulation of the miR-27a-3p/DKK2/Wnt/β-catenin axis, providing mechanistic insights for potential therapeutic strategies.

Neighborhood socioeconomic deprivation is a recognized contributor to disparities in breast cancer outcomes, yet the biological mechanisms linking neighborhood context to tumor behavior remain poorly defined. The conserved transcriptional response to adversity (CTRA), characterized by upregulation of pro-inflammatory genes and downregulation of type I interferon and antibody-related genes, may represent a stress-related immune dysregulation pathway relevant to cancer aggressiveness and survival.