Publications by authors named "Reza Mohit"
Introduction: The differential expression of miRNAs, a key regulator in many cell signaling pathways, has been studied in various malignancies and may have an important role in cancer progression, including colorectal cancer (CRC).
Method: The present study used machine learning and gene interaction study tools to explore the prognostic and diagnostic value of miRNAs in CRC. Integrative analysis of 353 CRC samples and normal tissue data was obtained from the TCGA database and further analyzed by R packages to define the deferentially expressed miRNAs (DEMs).
Article Synopsis
- Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, prompting research into new biomarkers for early diagnosis and survival prediction using RNA and microRNA sequencing alongside machine learning.
- Analysis of gene expression from The Cancer Genome Atlas (TCGA) and survival data identified 23 genes and several microRNAs that affect PDAC progression and patient survival.
- Machine learning techniques, particularly Gradient Boosting Machines, were successful in pinpointing key genes and microRNAs, such as CTSW, which could serve as novel genetic markers for earlier detection of the disease.
Colorectal cancer (CRC) is the third most common cause of cancer-related deaths. The five-year relative survival rate for CRC is estimated to be approximately 90% for patients diagnosed with early stages and 14% for those diagnosed at an advanced stages of disease, respectively. Hence, the development of accurate prognostic markers is required.
View Article and Find Full Text PDFGastric cancer is the high mortality rate cancers globally, and the current survival rate is 30% even with the use of combination therapies. Recently, mounting evidence indicates the potential role of miRNAs in the diagnosis and assessing the prognosis of cancers. In the state-of-art research in cancer, machine-learning (ML) has gained increasing attention to find clinically useful biomarkers.
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