Identification of Probucol as a candidate for combination therapy with Metformin for Type 2 diabetes.

Type 2 Diabetes (T2D) is often managed with metformin as the drug of choice. While it is effective overall, many patients progress to exhibit complications. Strategic drug combinations to tackle this problem would be useful. We constructed a genome-wide protein-protein interaction network capturing a global perspective of perturbations in diabetes by integrating T2D subjects' transcriptomic data. We computed a 'frequently perturbed subnetwork' in T2D that captures common perturbations across tissue types and mapped the possible effects of Metformin onto it. We then identified a set of remaining T2D perturbations and potential drug targets among them, related to oxidative stress and hypercholesterolemia. We then identified Probucol as the potential co-drug for adjunct therapy with Metformin and evaluated the efficacy of the combination in a rat model of diabetes. We find Metformin-Probucol at 5:0.5 mg/kg effective in restoring near-normal serum glucose, lipid, and cholesterol levels.

Profiling system-wide variations and similarities between Rheumatic Heart Disease and Acute Rheumatic Fever-A pilot analysis.

Rheumatic heart disease (RHD) continues to affect developing countries with low income due to the lack of resources and effective diagnostic techniques. Understanding the genetic basis common to both the diseases and that of progression from its prequel disease state, Acute Rheumatic Fever (ARF), would aid in developing predictive biomarkers and improving patient care. To gain system-wide molecular insights into possible causes for progression, in this pilot study, we collected blood transcriptomes from ARF (5) and RHD (5) patients. Using an integrated transcriptome and network analysis approach, we identified a subnetwork comprising the most significantly differentially expressed genes and most perturbed pathways in RHD compared to ARF. For example, the chemokine signaling pathway was seen to be upregulated, while tryptophan metabolism was found to be downregulated in RHD. The subnetworks of variation between the two conditions provide unbiased molecular-level insights into the host processes that may be linked with the progression of ARF to RHD, which has the potential to inform future diagnostics and therapeutic strategies. We also found a significantly raised neutrophil/lymphocyte ratio in both ARF and RHD cohorts. Activated neutrophils and inhibited Natural Killer cell gene signatures reflected the drivers of the inflammatory process typical to both disease conditions.

Identification of novel biomarkers for lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) is the second most common subtype of lung cancer, accounting for a majority of lung cancer-related deaths. Detection or diagnosis of cancer at an early stage is an unmet clinical need that is being actively explored. In this study, we aimed to identify potential biomarkers for LUSC, by screening expression status of all human genes against LUSC patient samples available with The Cancer Genome Atlas (TCGA). This led to the identification of several genes that are upregulated in LUSC. Further analysis revealed that many of these genes also show higher expression at the protein level not only in lung cancer but also in other cancers. Additionally, some of these genes show stage-dependent higher expression and are associated with statistically significant poor survival of LUSC patients. As per our results, more than 60 genes are overexpressed in LUSC at the level of mRNA and some at the protein level. Thus, we identified genes such as MCC1, MRPL47, CRYGS, HSP40, DNAJC19, GMPS and PARL as novel potential biomarkers for LUSC in this study. We believe that these genes hold great potential as LUSC biomarkers for early detection as the data are derived from patient samples. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03489-z.