Resistin-like beta reduction is associated to low survival rate and is downregulated by adjuvant therapy in colorectal cancer patients

Sex-specific modulation of FOLR1 and its cycle enzyme genes in Alzheimer's disease brain regions

Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive and functional decline. Its incidence increases significantly with age and is more prevalent in women than men. We investigated the folate receptor alpha (FOLR1) gene expression levels in the central nervous system (CNS) of AD and non-demented healthy control (NDHC) subjects. Our cohort included 3,946 samples: 2,391 NDHC and 1,555 AD patients, stratified by brain region, age, and sex. Interestingly, a significant increase in FOLR1 expression was observed only in females with AD compared to NDHC females. Furthermore, we found that FOLR1 expression was differentially increased in the prefrontal cortex (PFC) and diencephalon (DIE) only in AD females. Moreover, in females, genes involved in the folic acid (FA) cycle that drives DNA synthesis were significantly modulated. In contrast, in males, downregulation of TYMS effectively blocks the completion of the cycle, thereby preventing downstream DNA synthesis. Tissue Transcriptome Deconvolution (TTD) analysis revealed astrocytes and endothelial cells associated with FOLR1 expression in both AD males and females. Gene Ontology analysis supported these findings, showing enrichment in processes aligned with these cell types. Positive correlations between brain FOLR1 expression and markers for astrocytes (glial fibrillary acidic protein) and endothelial cells (CD31) provided further validation. Our findings suggest a potential role for sex-dependent FOLR1 expression and its association with specific brain regions and cellular processes in AD.

Exploring SERPINA3 as a neuroinflammatory modulator in Alzheimer's disease with sex and regional brain variations

SERPINA3, a serine protease inhibitor, is strongly associated with neuroinflammation, a typical condition of AD. Its expression is linked to microglial and astrocytic markers, suggesting it plays a significant role in modulating neuroinflammatory responses. In this study, we examined the SERPINA3 expression levels, along with CHI3L1, in various brain regions of AD patients and non-demented healthy controls (NDHC). Nineteen microarray datasets were analyzed, with brain samples stratified by sex and age from areas including the prefrontal cortex, occipital lobe, and cerebellum. Results showed that SERPINA3 was significantly highly expressed in AD patients compared to NDHCs only in males. Sex-specific differences were observed only in NDHCs, where females had higher SERPINA3 levels than males. ROC analysis suggested that SERPINA3 could be a strong marker for distinguishing AD in males but not females. In NDHCs, SERPINA3 expression correlated more strongly with age than in AD patients. In brain regions, SERPINA3 expression in NDHC females was higher across multiple areas, while in AD patients, this difference was limited to the prefrontal cortex. The most significant differences between NDHC and AD patients were found in the occipital and prefrontal regions. Furthermore, we identified a potential nuclear localization for SERPINA3, supported by immunohistochemistry analysis from The Human Protein Atlas. Correlation with neuropathological traits, including Clinical Dementia Rating (CDR) and Braak Neurofibrillary Tangle Score, showed positive significant associations between SERPINA3 and CDR in AD patients. Performing a docking analysis, we revealed an interaction region between SERPINA3 and CHI3L1 proteins, suggesting a potential role in AD. Tissue transcriptomic deconvolution analysis indicated a significant overlap between SERPINA3 expression and microglial/astrocytic signatures, suggesting that SERPINA3 plays a key role in modulating neuroinflammation in AD.

An Updated Review of Resistin and Colorectal Cancer

Resistin is one of the most important adipokines, and its role lies mainly in controlling insulin sensitivity and inflammation. However, over the last years, the study of resistin gained increased popularity since it was proved that there is a considerable relationship between high levels of resistin and obesity as well as obesity-induced diseases, including diabetes, cardiovascular disorders, and cancer. Regarding cancer risk, circulating resistin levels have been correlated with several types of cancer, including colorectal, breast, lung, endometrial, gastroesophageal, prostate, renal, and pancreatic cancer. Colorectal cancer is regarded as a multi-pathway disease. Several pathophysiological features seem to promote colorectal cancer (CRC) such as chronic inflammation, insulin resistance, and obesity. Even though the molecular mechanisms involved in CRC development remain rather vague, it is widely accepted that several biochemical factors promote CRC by releasing augmented pro-inflammatory cytokines, like IGF-I, insulin, sex-steroid hormones, and adipokines. A wide range of research studies has focused on evaluating the impact of circulating resistin levels on CRC risk and determining the efficacy of chemotherapy in CRC patients by measuring resistin levels. Moreover, significant outcomes have emerged regarding the association of specific single nucleotide polymorphisms (SNPs) in the resistin gene and CRC risk. The present study reviewed the role of circulating resistin levels in CRC development and shed light on specific resistin gene SNPs implicated in the disease's development. Finally, we analyzed the impact of resistin levels on the effectiveness of chemotherapy and further discussed whether resistin can be regarded as a valuable biomarker for CRC prognosis and treatment. Resistin is one of the most important adipokines, and its role lies mainly in controlling insulin sensitivity and inflammation. However, over the last years, the study of resistin gained increased popularity since it was proved that there is a considerable relationship between high levels of resistin and obesity as well as obesity-induced diseases, including diabetes, cardiovascular disorders, and cancer. This review discusses the aberrant expression of resistin and its receptors, its diverse downstream signaling, and its impact on tumor growth, metastasis, angiogenesis, and therapy resistance to support its clinical exploitation in biomarker and therapeutic development.

Construction of a new prognostic model for colorectal cancer based on bulk RNA-seq combined with The Cancer Genome Atlas data

Background

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths, and improving the prognosis of CRC patients is an urgent concern. The aim of this study was to explore new immunotherapy targets to improve survival in CRC patients.

Methods

We analyzed CRC-related single-cell data GSE201348 from the Gene Expression Omnibus (GEO) database, and identified differentially expressed genes (DEGs). Subsequently, we performed differential analysis on the rectum adenocarcinoma (READ) and colon adenocarcinoma (COAD) transcriptome sequencing data [The Cancer Genome Atlas (TCGA)-CRC queue] and clinical data downloaded from TCGA database. Subgroup analysis was performed using CIBERSORTx and cluster analysis. Finally, biomarkers were identified by one-way cox regression as well as least absolute shrinkage and selection operator (LASSO) analysis.

Results

In this study, we analyzed CRC-related single-cell data GSE201348, and identified 5,210 DEGs. Subsequently, we performed differential analysis on the TCGA-CRC queue database, and obtained 4,408 DEGs. Then, we categorized the cancer samples in the sequencing data into three groups (k1, k2, and k3), with significant differences observed between the k1 and k2 groups via survival analysis. Further differential analysis on the samples in the k1 and k2 groups identified 1,899 DEGs. A total of 77 DEGs were selected among those DEGs obtained from three differential analyses. Through subsequent Cox univariate analysis and LASSO analysis, seven biomarkers (RETNLB, CLCA4, UGT2A3, SULT1B1, CCL24, BMP5, and ATOH1) were identified and selected to establish a risk score (RS).

Conclusions

To sum up, this study demonstrates the potential of the seven-gene prognostic risk model as instrumental variables for predicting the prognosis of CRC.

High-accuracy prediction of colorectal cancer chemotherapy efficacy using machine learning applied to gene expression data

Introduction: FOLFOX and FOLFIRI chemotherapy are considered standard first-line treatment options for colorectal cancer (CRC). However, the criteria for selecting the appropriate treatments have not been thoroughly analyzed. Methods: A newly developed machine learning model was applied on several gene expression data from the public repository GEO database to identify molecular signatures predictive of efficacy of 5-FU based combination chemotherapy (FOLFOX and FOLFIRI) in patients with CRC. The model was trained using 5-fold cross validation and multiple feature selection methods including LASSO and VarSelRF methods. Random Forest and support vector machine classifiers were applied to evaluate the performance of the models. Results and Discussion: For the CRC GEO dataset samples from patients who received either FOLFOX or FOLFIRI, validation and test sets were >90% correctly classified (accuracy), with specificity and sensitivity ranging between 85%-95%. In the datasets used from the GEO database, 28.6% of patients who failed the treatment therapy they received are predicted to benefit from the alternative treatment. Analysis of the gene signature suggests the mechanistic difference between colorectal cancers that respond and those that do not respond to FOLFOX and FOLFIRI. Application of this machine learning approach could lead to improvements in treatment outcomes for patients with CRC and other cancers after additional appropriate clinical validation.