Necroptosis executioner MLKL plays pivotal roles in agonist-induced platelet prothrombotic responses and lytic cell death in a temporal order.

Necroptosis is a form of programmed cell death executed by receptor-interacting serine/threonine protein kinase 1 (RIPK1), RIPK3, and mixed lineage kinase domain-like (MLKL). Platelets are circulating cells that play central roles in haemostasis and pathological thrombosis. In this study we demonstrate seminal contribution of MLKL in transformation of agonist-stimulated platelets to active haemostatic units progressing eventually to necrotic death on a temporal scale, thus attributing a yet unrecognized fundamental role to MLKL in platelet biology. Physiological agonists like thrombin instigated phosphorylation and subsequent oligomerization of MLKL in platelets in a RIPK3-independent but phosphoinositide 3-kinase (PI3K)/AKT-dependent manner. Inhibition of MLKL significantly curbed agonist-induced haemostatic responses in platelets that included platelet aggregation, integrin activation, granule secretion, procoagulant surface generation, rise in intracellular calcium, shedding of extracellular vesicles, platelet-leukocyte interactions and thrombus formation under arterial shear. MLKL inhibition, too, prompted impairment in mitochondrial oxidative phosphorylation and aerobic glycolysis in stimulated platelets, accompanied with disruption in mitochondrial transmembrane potential, augmented proton leak and drop in both mitochondrial calcium as well as ROS. These findings underscore the key role of MLKL in sustaining OXPHOS and aerobic glycolysis that underlie energy-intensive platelet activation responses. Prolonged exposure to thrombin provoked oligomerization and translocation of MLKL to plasma membranes forming focal clusters that led to progressive membrane permeabilization and decline in platelet viability, which was prevented by inhibitors of PI3K/MLKL. In summary, MLKL plays vital role in transitioning of stimulated platelets from relatively quiescent cells to functionally/metabolically active prothrombotic units and their ensuing progression to necroptotic death.

Analysis of transcriptomic data sets supports the role of IL-6 in NETosis and immunothrombosis in severe COVID-19.

BACKGROUND: There is an urgent need to understand the key events driving pathogenesis of severe COVID-19 disease, so that precise treatment can be instituted. In this respect NETosis is gaining increased attention in the scientific community, as an important pathological process contributing to mortality. We sought to test if indeed there exists robust evidence of NETosis in multiple transcriptomic data sets from human subjects with severe COVID-19 disease. Gene set enrichment analysis was performed to test for up-regulation of gene set functional in NETosis in the blood of patients with COVID-19 illness. RESULTS: Blood gene expression functional in NETosis increased with severity of illness, showed negative correlation with blood oxygen saturation, and was validated in the lung of COVID-19 non-survivors. Temporal expression of IL-6 was compared between severe and moderate illness with COVID-19. Unsupervised clustering was performed to reveal co-expression of IL-6 with complement genes. In severe COVID-19 illness, there is transcriptional evidence of activation of NETosis, complement and coagulation cascade, and negative correlation between NETosis and respiratory function (oxygen saturation). An early spike in IL-6 is observed in severe COVID-19 illness that is correlated with complement activation. CONCLUSIONS: Based on the transcriptional dynamics of IL-6 expression and its downstream effect on complement activation, we constructed a model that links early spike in IL-6 level with persistent and self-perpetuating complement activation, NETosis, immunothrombosis and respiratory dysfunction. Our model supports the early initiation of anti-IL6 therapy in severe COVID-19 disease before the life-threatening complications of the disease can perpetuate themselves autonomously.

Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass.

BACKGROUND: Most often, the patients with pancreatic diseases are presented with a mass in pancreatic head region and existing methods of diagnosis fail to confirm whether the head mass is malignant or benign. As subsequent management of the disease hugely depends on the correct diagnosis, we wanted to explore possible biomarkers which could distinguish benign and malignant pancreatic head masses. METHODS: In order to address that gap, we performed a case-control study to identify genome-wide differentially expressed coding and noncoding genes between pancreatic tissues collected from benign and malignant head masses. These genes were next shortlisted using stringent criteria followed by selection of top malignancy specific genes. They subsequently got validated by quantitative RT-PCR and also in other patient cohorts. Survival analysis and ROC analysis were also performed. RESULTS: We identified 55 coding and 13 noncoding genes specific for malignant pancreatic head masses. Further shortlisting and validation, however, resulted in 5 coding genes as part of malignancy specific multi-gene signature, which was validated in three independent patient cohorts of 145 normal and 153 PDAC patients. We also found that overexpression of these genes resulted in survival disadvantage in the patients and ROC analysis identified that combination of 5 coding genes had the AUROC of 0.94, making them potential biomarker. CONCLUSIONS: Our study identified a multi-gene signature comprising of 5 coding genes (CDCA7, DLGAP5, FOXM1, TPX2 and OSBPL3) to distinguish malignant head masses from benign ones.

Sepsis-associated pathways segregate cancer groups.

BACKGROUND: Sepsis and cancer are both leading causes of death, and occurrence of any one, increases the likelihood of the other. While cancer patients are susceptible to sepsis, survivors of sepsis are also susceptible to develop certain cancers. This mutual dependence for susceptibility suggests shared biology between the two disease categories. Earlier analysis had revealed a cancer-related pathway to be up-regulated in Septic Shock (SS), an advanced stage of sepsis. This has motivated a more comprehensive comparison of the transcriptomes of SS and cancer. METHODS: Gene Set Enrichment Analysis was performed to detect the pathways enriched in SS and cancer. Thereafter, hierarchical clustering was applied to identify relative segregation of 17 cancer types into two groups vis-a-vis SS. Biological significance of the selected pathways was explored by network analysis. Clinical significance of the pathways was tested by survival analysis. A robust classifier of cancer groups was developed based on machine learning. RESULTS: A total of 66 pathways were observed to be enriched in both SS and cancer. However, clustering segregated cancer types into two categories based on the direction of transcriptomic change. In general, there was up-regulation in SS and one group of cancer (termed Sepsis-Like Cancer, or SLC), but not in other cancers (termed Cancer Alone, or CA). The SLC group mainly consisted of malignancies of the gastrointestinal tract (head and neck, oesophagus, stomach, liver and biliary system) often associated with infection. Machine learning classifier successfully segregated the two cancer groups with high accuracy (> 98%). Additionally, pathway up-regulation was observed to be associated with survival in the SLC group of cancers. CONCLUSION: Transcriptome-based systems biology approach segregates cancer into two groups (SLC and CA) based on similarity with SS. Host response to infection plays a key role in pathogenesis of SS and SLC. However, we hypothesize that some component of the host response is protective in both SS and SLC.

Hepatic miR-126 is a potential plasma biomarker for detection of hepatitis B virus infected hepatocellular carcinoma.

Controversies about the origin of circulating miRNAs have encouraged us to identify organ specific circulating miRNAs as disease biomarkers. To identify liver-specific miRNAs for hepatocellular carcinoma (HCC), global expression profiling of miRNAs in liver tissue of HBV-HCC and HBV-control with no or mild fibrosis was evaluated. A total of 40 differentially expressed miRNAs were identified in HCC. Among ten highly altered miRNAs, six miRNAs were successfully validated in tissues, whereas only two miRNAs, miR-126 and miR-142-3p showed increased expression in plasma of HBV-HCC compared to HBV-non-HCC patients. Subsequently, ROC curve analysis revealed that neither miR-126 nor miR-142-3p performed better than AFP in discriminating HCC from non-HCC while combination of each with AFP showed significantly higher efficiency rather than AFP alone (AUC: 0.922, 0.908 vs. 0.88; sensitivity: 0.84, 0.86 vs. 0.82 and specificity: 0.92, 0.94 vs. 0.86 respectively). Interestingly, triple combination of markers (miR-126 + miR-142-3p + AFP) showed no additive effect on efficiency (AUC: 0.925) over the dual combination. Again, the expression of only miR-126 was noticed significantly higher in HBV-HCC patients with low-AFP [<250 ng/ml] compared to either non-HCC or liver cirrhosis (AUC: 0.77, 0.64, respectively). Furthermore, no alteration in expression of mir-126 in HCV-HCC or non-viral-HCC revealed that miR-126 + AFP might be specific to HBV-HCC. To understand the physiological role of these two miRNAs in hepato-carcinogenesis, target genes related to cancer pathways (APAF1, APC2, CDKN2A, IRS1, CRKL, LIFR, EGR2) were verified. Thus, combination of circulating miR-126 + AFP is a promising noninvasive diagnostic biomarker for HBV-HCC and may be useful in the management of HCC patients.

A combined gene signature of hypoxia and notch pathway in human glioblastoma and its prognostic relevance.

Hypoxia is a hallmark of solid tumors including glioblastoma (GBM). Its synergism with Notch signaling promotes progression in different cancers. However, Notch signaling exhibits pleiotropic roles and the existing literature lacks a comprehensive understanding of its perturbations under hypoxia in GBM with respect to all components of the pathway. We identified the key molecular cluster(s) characteristic of the Notch pathway response in hypoxic GBM tumors and gliomaspheres. Expression of Notch and hypoxia genes was evaluated in primary human GBM tissues by q-PCR. Clustering and statistical analyses were applied to identify the combination of hypoxia markers correlated with upregulated Notch pathway components. We found well-segregated tumor-clusters representing high and low HIF-1α/PGK1-expressors which accounted for differential expression of Notch signaling genes. In combination, a five-hypoxia marker set (HIF-1α/PGK1/VEGF/CA9/OPN) was determined as the best predictor for induction of Notch1/Dll1/Hes1/Hes6/Hey1/Hey2. Similar Notch-axis genes were activated in gliomaspheres, but not monolayer cultures, under moderate/severe hypoxia (2%/0.2% O2). Preliminary evidence suggested inverse correlation between patient survival and increased expression of constituents of the hypoxia-Notch gene signature. Together, our findings delineated the Notch-axis maximally associated with hypoxia in resected GBM, which might be prognostically relevant. Its upregulation in hypoxia-exposed gliomaspheres signify them as a better in-vitro model for studying hypoxia-Notch interactions than monolayer cultures.