Membrane tension sensing molecule-FNBP1 is a prognostic biomarker related to immune infiltration in BRCA, LUAD and STAD

Genetic parameters and haplotype-based genome-wide association study of indicator traits for gastrointestinal parasite resistance in Santa Ines sheep

Genetic parameters are of great importance in animal breeding since they determine the strategies necessary to increase the genetic progress in economic traits, for example indicator traits for resistance to endoparasites in sheep. Furthermore, genetic markers have been used to identify genomic regions associated with economically important traits, which can help increase the genetic response through genomic selection. Therefore, this study aimed to estimate genetic parameters and perform a haplotype-based genome wide association study (GWAS) to identify genomic regions associated with indicator traits for endoparasite resistance in Santa Ines sheep. Haplotype GWAS was performed using linkage disequilibrium blocks (haploblocks) defined by the Haploview software. Records from 1725 animals for Famacha© (FAM, N = 5560), packed cell volume (PCV, N = 5135), total plasma protein (TPP, N = 4356), and fecal egg count (FEC, N = 4248) were used for analysis. The pedigree file contained information from 4821 animals; of these, 638 animals were genotyped using the Ovine SNP50 Genotyping BeadChip. Heritability estimates were moderate for FAM (0.26), PCV (0.26), TPP (0.16), and log-transformed FEC (0.19). Genomic regions that explained more than 0.3 % of the total additive genetic variance of the traits were defined as significant. These regions overlapped with quantitative traits loci associated with eosinophil number, fecal egg count, hematocrit, and immunoglobulin levels. In the top regions for the traits evaluated we found genes individually involved in inflammatory response, immunity, macrophage function in host-pathogen interactions, and other biological functions. All indicator traits for resistance to gastrointestinal parasites evaluated in this study exhibited sufficient genetic variability to respond to selection and can be used to improve the health and consequently the production of Santa Ines sheep.

Uncovering driver genes in breast cancer through an innovative machine learning mutational analysis method

Breast cancer has become a severe public health concern and one of the leading causes of cancer-related death in women worldwide. Several genes and mutations in these genes linked to breast cancer have been identified using sophisticated techniques, despite the fact that the exact cause of breast cancer is still unknown. A commonly used feature for identifying driver mutations is the recurrence of a mutation in patients. Nevertheless, some mutations are more likely to occur than others for various reasons. Sequencing analysis has shown that cancer-driving genes operate across complex networks, often with mutations appearing in a modular pattern. In this work, as a retrospective study, we used TCGA data, which is gathered from breast cancer patients. We introduced a new machine-learning approach to examine gene functionality in networks derived from mutation associations, gene-gene interactions, and graph clustering for breast cancer analysis. These networks have uncovered crucial biological components in critical pathways, particularly those that exhibit low-frequency mutations. The statistical strength of the clinical study is significantly boosted by evaluating the network as a whole instead of just single gene effects. Our method successfully identified essential driver genes with diverse mutation frequencies. We then explored the functions of these potential driver genes and their related pathways. By uncovering low-frequency genes, we shed light on understudied pathways associated with breast cancer. Additionally, we present a novel Monte Carlo-based algorithm to identify driver modules in breast cancer. Our findings highlight the significance and role of these modules in critical signaling pathways in breast cancer, providing a comprehensive understanding of breast cancer development. Materials and implementations are available at: [https://github.com/MahnazHabibi/BreastCancer].

A Potential Prognostic Gene Signature Associated with p53-Dependent NTRK1 Activation and Increased Survival of Neuroblastoma Patients

Neuroblastoma is the most common extracranial solid tumour in children, comprising close to 10% of childhood cancer-related deaths. We have demonstrated that activation of NTRK1 by TP53 repression of PTPN6 expression is significantly associated with favourable survival in neuroblastoma. The molecular mechanisms by which this activation elicits cell molecular changes need to be determined. This is critical to identify dependable biomarkers for the early detection and prognosis of tumours, and for the development of personalised treatment. In this investigation we have identified and validated a gene signature for the prognosis of neuroblastoma using genes differentially expressed upon activation of the NTRK1-PTPN6-TP53 module. A random survival forest model was used to construct a gene signature, which was then assessed across validation datasets using Kaplan-Meier analysis and ROC curves. The analysis demonstrated that high BASP1, CD9, DLG2, FNBP1, FRMD3, IL11RA, ISGF10, IQCE, KCNQ3, and TOX2, and low BSG/CD147, CCDC125, GABRB3, GNB2L1/RACK1 HAPLN4, HEBP2, and HSD17B12 expression was significantly associated with favourable patient event-free survival (EFS). The gene signature was associated with favourable tumour histology and NTRK1-PTPN6-TP53 module activation. Importantly, all genes were significantly associated with favourable EFS in an independent manner. Six of the signature genes, BSG/CD147, GNB2L1/RACK1, TXNDC5, FNPB1, B3GAT1, and IGSF10, play a role in cell differentiation. Our findings strongly suggest that the identified gene signature is a potential prognostic biomarker and therapeutic target for neuroblastoma patients and that it is associated with neuroblastoma cell differentiation through the activation of the NTRK1-PTPN6-TP53 module.

CircSCUBE3 Reduces the Anti-gastric Cancer Activity of Anti-PD-L1

The progression of gastric cancer (GC) is closely related to tumor immune escape. The research, therefore, studied the impact of possible circRNAs on the immune escape of GC tumors and the underlying mechanisms. Here, to explore circRNAs that may affect GC, the differential circRNAs in six normal gastric mucosal tissues and six GC samples (GSM2005868-GSM2005879) were analyzed through the bioinformatics website circmine, and hsa_circ_0076092 (circSCUBE3) was identified as the research object. In vitro assays revealed the functions of circSCUBE3 and its downstream miRNA/mRNA axis in GC cells. The effect of circSCUBE3 against PD-1 anti-tumor activity was evaluated in vivo. The relationship between circSCUBE3 and miR-744-5p, miR-744-5p, and SLC7A5 was identified by RNA immunoprecipitation and dual-luciferase reporter experiments. The effect of SLC7A5 on GC immune escape by regulating PD-L1 expression was assessed by co-culture system and flow cytometry. CircSCUBE3 was up-regulated in human GC tissues and GC cell lines. circSCUBE3 was associated with poor prognosis in GC patients. Functional experiments reported that circSCUBE3 knockdown could suppress GC immune escape. Mechanistically, circSCUBE3 bound to miR-744-5p, which further targeted SLC7A5, and SLC7A5 can affect GC immune escape by regulating PD-L1. Furthermore, in vivo assay manifested that circSCUBE3 attenuated the anti-tumor effect of PD-L1. Our study revealed the importance of the circSCUBE3/miR-744-5p/SLC7A5 axis in GC immune escape and anti-PD-1 resistance.

Ameliorating inflammation in an in vitro model by screening the anti-inflammatory and immunomodulatory roles of putative probiotics in inflammatory bowel disease

IBD is considered a relapsing disease with relapsing phases. Probiotics are beneficial microorganisms that modulate inflammatory signaling pathways. Our aim was to identify the precise molecular effects of probiotics on inflammatory signaling pathways during the presence of inflammation. Evaluation of the expression of JAK/STAT and inflammatory genes after treatment of the HT -29 cell line with the sonicated pathogens and probiotics, simultaneously was performed by quantitative real-time polymerase chain reaction (qPCR) assay. The production of IL-6 and IL-1β after administration of probiotics was conducted by means of cytokine assay. The probiotic cocktail resulted in the downregulation of TIRAP, IRAK4, NEMO, and RIP genes in the NF-кB pathway compared with Sonicat-treated cells. The expression of JAK/STAT genes was various after probiotic treatment. The application of probiotics has been observed to result in a notable decrease in the production of IL-6 and IL-1β. The investigated probiotic cocktail, especially Bifidobacterium spp. showed anti-inflammatory effects on HT -29 cells via modulation of JAK/STAT and NF-кB signaling pathways. The use of probiotics with the least side effects could be considered a suitable treatment for patients with inflammatory bowel disease, even at the beginning of inflammation.

FNBP1 Facilitates Cervical Cancer Cell Survival by the Constitutive Activation of FAK/PI3K/AKT/mTOR Signaling

Cervical cancer is the most prevalent gynecological tumor among women worldwide. Although the incidence and mortality of cervical cancer have been declining thanks to the wide-scale implementation of cytological screening, it remains a major challenge in clinical treatment. High viability is one of the leading causes of the chemotherapeutic resistance in cervical cancers. Formin-binding protein 1 (FNBP1) could stimulate F-actin polymerization beneath the curved plasma membrane in the cell migration and endocytosis, which had previously been well defined. Here, FNBP1 was also demonstrated to play a crucial role in cervical cancer cell survival, and the knockdown of which could result in the attenuation of FAK/PI3K/AKT signaling followed by significant apoptotic accumulation and proliferative inhibition. In addition, the epidermal growth factor (hrEGF) abrogated all the biological effects mediated by the silencing of FNBP1 except for the cell adhesion decrease. These findings indicated that FNBP1 plays a key role in maintaining the activity of focal adhesion kinase (FAK) by promoting cell adhesion. The activated FAK positively regulated downstream PI3K/AKT/mTOR signaling, which is responsible for cell survival. Promisingly, FNBP1 might be a potential target against cervical cancer in combination therapy.

Using Machine Learning Methods to Study Colorectal Cancer Tumor Micro-Environment and Its Biomarkers

Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide, and the identification of biomarkers can improve early detection and personalized treatment. In this study, RNA-seq data and gene chip data from TCGA and GEO were used to explore potential biomarkers for CRC. The SMOTE method was used to address class imbalance, and four feature selection algorithms (MCFS, Borota, mRMR, and LightGBM) were used to select genes from the gene expression matrix. Four machine learning algorithms (SVM, XGBoost, RF, and kNN) were then employed to obtain the optimal number of genes for model construction. Through interpretable machine learning (IML), co-predictive networks were generated to identify rules and uncover underlying relationships among the selected genes. Survival analysis revealed that INHBA, FNBP1, PDE9A, HIST1H2BG, and CADM3 were significantly correlated with prognosis in CRC patients. In addition, the CIBERSORT algorithm was used to investigate the proportion of immune cells in CRC tissues, and gene mutation rates for the five selected biomarkers were explored. The biomarkers identified in this study have significant implications for the development of personalized therapies and could ultimately lead to improved clinical outcomes for CRC patients.

A deep transcriptome meta-analysis reveals sex differences in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS), a chronic auto-immune, inflammatory, and degenerative disease of the central nervous system, affects both males and females; however, females suffer from a higher risk of developing MS (2-3:1 ratio relative to males). The precise sex-based factors influencing risk of MS are currently unknown. Here, we explore the role of sex in MS to identify molecular mechanisms underlying observed MS sex differences that may guide novel therapeutic approaches tailored for males or females.

METHODS

We performed a rigorous and systematic review of genome-wide transcriptome studies of MS that included patient sex data in the Gene Expression Omnibus and ArrayExpress databases following PRISMA statement guidelines. For each selected study, we analyzed differential gene expression to explore the impact of the disease in females (IDF), in males (IDM) and our main goal: the sex differential impact of the disease (SDID). Then, for each scenario (IDF, IDM and SDID) we performed 2 meta-analyses in the main tissues involved in the disease (brain and blood). Finally, we performed a gene set analysis in brain tissue, in which a higher number of genes were dysregulated, to characterize sex differences in biological pathways.

RESULTS

After screening 122 publications, the systematic review provided a selection of 9 studies (5 in blood and 4 in brain tissue) with a total of 474 samples (189 females with MS and 109 control females; 82 males with MS and 94 control males). Blood and brain tissue meta-analyses identified, respectively, 1 (KIR2DL3) and 13 (ARL17B, CECR7, CEP78, IFFO2, LOC401127, NUDT18, RNF10, SLC17A5, STMP1, TRAF3IP2-AS1, UBXN2B, ZNF117, ZNF488) MS-associated genes that differed between males and females (SDID comparison). Functional analyses in the brain revealed different altered immune patterns in females and males (IDF and IDM comparisons). The pro-inflammatory environment and innate immune responses related to myeloid lineage appear to be more affected in females, while adaptive responses associated with the lymphocyte lineage in males. Additionally, females with MS displayed alterations in mitochondrial respiratory chain complexes, purine, and glutamate metabolism, while MS males displayed alterations in stress response to metal ion, amine, and amino acid transport.

CONCLUSION

We found transcriptomic and functional differences between MS males and MS females (especially in the immune system), which may support the development of new sex-based research of this disease. Our study highlights the importance of understanding the role of biological sex in MS to guide a more personalized medicine.

Membrane tension-mediated stiff and soft tumor subtypes closely associated with prognosis for prostate cancer patients

BACKGROUND

Prostate cancer (PCa) is usually considered as cold tumor. Malignancy is associated with cell mechanic changes that contribute to extensive cell deformation required for metastatic dissemination. Thus, we established stiff and soft tumor subtypes for PCa patients from perspective of membrane tension.

METHODS

Nonnegative matrix factorization algorithm was used to identify molecular subtypes. We completed analyses using software R 3.6.3 and its suitable packages.

RESULTS

We constructed stiff and soft tumor subtypes using eight membrane tension-related genes through lasso regression and nonnegative matrix factorization analyses. We found that patients in stiff subtype were more prone to biochemical recurrence than those in soft subtype (HR 16.18; p < 0.001), which was externally validated in other three cohorts. The top ten mutation genes between stiff and soft subtypes were DNAH, NYNRIN, PTCHD4, WNK1, ARFGEF1, HRAS, ARHGEF2, MYOM1, ITGB6 and CPS1. E2F targets, base excision repair and notch signaling pathway were highly enriched in stiff subtype. Stiff subtype had significantly higher TMB and T cells follicular helper levels than soft subtype, as well as CTLA4, CD276, CD47 and TNFRSF25.

CONCLUSIONS

From the perspective of cell membrane tension, we found that stiff and soft tumor subtypes were closely associated with BCR-free survival for PCa patients, which might be important for the future research in the field of PCa.