Biology subjects

Asghar, W.

Publications and source records attributed to Asghar, W..

2 recordsLinked to original sources

bioRxiv2021

Integrative genomic and epigenomic analyses identified IRAK1 as a novel target for chronic inflammation-driven prostate tumorigenesis

The impacts of many inflammatory genes in prostate tumorigenesis remain understudied despite the increasing evidence that associates chronic inflammation with prostate cancer (PCa) initiation, progression, and therapy resistance. The overarching goal of this study was to identify dysregulated inflammatory genes that correlate with PCa progression and decipher their molecular mechanisms as well as clinical significance in PCa using integrative genomics, transcriptomics, and epigenomics approach. Our Weighted Gene Co-expression Analysis (WGCNA) and multivariate analysis identified 10 inflammatory genes: IRAK1, PPIL5/LRR1, HMGB3, HMGB2, TRAIP, IL1F5/IL36RN, ILF2, TRIM59, NFKBIL2/TONSL, and TRAF7 that were significantly associated with PCa progression. We explored the potentials of IRAK1 and other inflammatory genes as diagnostic and/or prognostic biomarkers by performing both KM survival and AUROC curve analyses. Our results indicate the clinical significance of these inflammatory genes in predicting the development and progression of PCa. IRAK1 was found to be overexpressed and hypomethylated in most PCa samples. A significantly high percentage of castration-resistant PCa (CRPC) and neuroendocrine PCa (NEPC) samples display copy number variations, especially amplification of the IRAK1 gene compared to the indolent prostate adenocarcinoma (PRAD) samples. Furthermore, we identified missense and frameshift mutations of IRAK1 in a few PRAD samples with potential functional implications. In conclusion, the results from this study suggest that IRAK1 dysregulation may be an important contributor to chronic prostatitis (inflammation) and PCa progression.

cancer biology↗

bioRxiv2020

Smartphone-based Sickle Cell Disease Detection and Monitoring for Point-of-Care Settings

Sickle cell disease (SCD) is a worldwide hematological disorder causing painful episodes, anemia, organ damage, stroke, and even deaths. It is more common in sub-Saharan Africa and other resource-limited countries. Conventional laboratory-based diagnostic methods for SCD are time-consuming, complex, and cannot be performed at point-of-care (POC) and home settings. Optical microscope-based classification and counting demands a significant amount of time, extensive setup, and cost along with the skilled human labor to distinguish the normal red blood cells (RBCs) from sickled cells. There is an unmet need to develop a POC and home-based test to diagnose and monitor SCD and reduce mortality in resource-limited settings. An early-stage and timely diagnosis of SCD can help in the effective management of the disease. In this article, we utilized a smartphone-based image acquisition method for capturing RBC images from the SCD patients in normoxia and hypoxia conditions. A computer algorithm is developed to differentiate RBCs from the patients blood before and after cell sickling. Using the developed smartphone-based technique, we obtained similar percentage of sickle cells in blood samples as analyzed by conventional method (standard microscope). The developed method of testing demonstrates the potential utility of the smartphone-based test for reducing the overall cost of screening and management for SCD, thus increasing the practicality of smartphone-based screening technique for SCD in low-resource settings. Our setup does not require any special storage requirements and is particularly useful in assessing the severity of the SCD. This is the characteristic advantage of our technique as compared to other hemoglobin-based POC diagnostic techniques.

bioengineering↗