Prognostic model development for classification of colorectal adenocarcinoma by using machine learning model based on feature selection technique boruta

Colorectal cancer (CRC) is the third most prevalent cancer type and accounts for nearly one million deaths worldwide. The CRC mRNA gene expression datasets from TCGA and GEO (GSE144259, GSE50760, and GSE87096) were analyzed to find the significant differentially expressed genes (DEGs). These significant genes were further processed for feature selection through boruta and the confirmed features of importance (genes) were subsequently used for ML-based prognostic classification model development. These genes were analyzed for survival and correlation analysis between final genes and infiltrated immunocytes. A total of 770 CRC samples were included having 78 normal and 692 tumor tissue samples. 170 significant DEGs were identified after DESeq2 analysis along with the topconfects R package. The 33 confirmed features of importance-based RF prognostic classification model have given accuracy, precision, recall, and f1-score of 100% with 0% standard deviation. The overall survival analysis had finalized GLP2R and VSTM2A genes that were significantly downregulated in tumor samples and had a strong correlation with immunocyte infiltration. The involvement of these genes in CRC prognosis was further confirmed on the basis of their biological function and literature analysis. The current findings indicate that GLP2R and VSTM2A may play a significant role in CRC progression and immune response suppression

Current Promising Therapeutic Targets for Aspergillosis Treatment

Aspergillosis is a fungal disease caused by different species of Aspergillus. They live in soil,dust and decomposed material. Number of Aspergillus species found till now is about 300 and more are still to be identified. Only few Aspergillus species can cause human disease and the most common species for human infection is Aspergillus fumigatus, which is a ubiquitous airborne saprophytic fungus. Severity of the disease ranges from an allergic response to life-threatening generalized infection. They grow optimally at 37°C and can grow upto 50°C. The fungal conidia are being constantly inhaled by humans and animals everyday normally gets eliminated by innate immune mechanism. Due to increasing number of immunocompromised patients, severe and fatal Aspergillosis cases have augmented. Currently, available antifungal drug for the treatment of Aspergillosis act on these three molecular target are 14 alpha demethylase for Azoles, ergosterol for Polyene and β-1,3-glucan synthase for Echinocandin. These antifungal drug show high resistance problem and toxicity. So, it is high time to develop new drugs for treatment with reduced toxicity and drug resistant problem. Synthesis of essential amino acid is absent in human as they obtain it from their diet but fungi synthesis these amino acid. Thus, enzymes in this pathway acts as novel drug target. This article summarizes promising drug targets presents in different metabolic pathway of Aspergillus genome and discusses their molecular functions in detail. This review also list down the inhibitors of these novel target. We present a comprehensive review that will pave way for discovery and development of novel antifungals against these drug targets for Aspergillosis treatment