Tanmay Gandhi’s research while affiliated with Baylor College of Medicine and other places

Osteosarcoma is the most prevalent bone tumor in pediatric patients. Neoadjuvant chemotherapy has improved osteosarcoma patient survival, however the 5-year survival rate for localized osteosarcoma is 75% with a 30–50% recurrence rate. We, therefore, sought to identify a prognostic gene signature which could predict poor prognosis in localized osteosarcoma patients. Using the TARGET osteosarcoma transcriptomic dataset, we identified a 13-hub gene signature associated with overall survival and time to death of localized osteosarcoma patients, with the high-risk group showing a 22% and the low-risk group showing 100% overall survival. Furthermore, network analysis identified five modules of co-expressed genes that significantly correlated with survival, and identified 65 pathways enriched across 3 modules, including Hedgehog signaling, which includes 2 of the 13 genes, IHH and GLI1. Subsequently, we demonstrated that GLI antagonists inhibited growth of a recurrent localized PDX-derived cell line with elevated IHH and GLI1 expression, but not a non-relapsed cell line with low pathway activation. Finally, we show that our signature outperforms previously reported signatures in predicting poor prognosis and death within 3 years in patients with localized osteosarcoma.

Oxygen supplementation is life saving for premature infants and for COVID-19 patients but can induce long-term pulmonary injury by triggering inflammation, with xenobiotic-metabolizing CYP enzymes playing a critical role. Murine studies showed that CYP1B1 enhances, while CYP1A1 and CYP1A2 protect from, hyperoxic lung injury. In this study we tested the hypothesis that Cyp1b1-null mice would revert hyperoxia-induced transcriptomic changes observed in WT mice at the transcript and pathway level. Wild type (WT) C57BL/6J and Cyp1b1-null mice aged 8-10 weeks were maintained in room air (21% O2) or exposed to hyperoxia (>95% O2) for 48h. Transcriptomic profiling was conducted using the Illumina microarray platform. Hyperoxia exposure led to robust changes in gene expression and in the same direction in WT, Cyp1a1-, Cyp1a2-, and Cyp1b1-null mice, but to different extents for each mouse genotype. At the transcriptome level, all Cyp1-null murine models reversed hyperoxia effects. Gene Set Enrichment Analysis identified 118 hyperoxia-affected pathways mitigated only in Cyp1b1-null mice, including lipid, glutamate, and amino acid metabolism. Cell cycle genes Cdkn1a and Ccnd1 were induced by hyperoxia in both WT and Cyp1b1-null mice but mitigated in Cyp1b1-null O2 compared to WT O2 mice. Hyperoxia gene signatures associated positively with bronchopulmonary dysplasia (BPD), which occurs in premature infants (with supplemental oxygen being one of the risk factors), but only in the Cyp1b1-null mice did the gene profile after hyperoxia exposure show a partial rescue of BPD-associated transcriptome. Our study suggests that CYP1B1 plays a pro-oxidant role in hyperoxia-induced lung injury.

Introduction To understand mechanisms and identify potential targets for intervention in the current crisis of opioid use disorder (OUD), postmortem brains represent an under-utilized resource. To refine previously reported gene signatures of neurobiological alterations in OUD from the dorsolateral prefrontal cortex (Brodmann Area 9, BA9), we explored the role of microRNAs (miRNA) as powerful epigenetic regulators of gene function. Methods Building on the growing appreciation that miRNAs can cross the blood-brain barrier, we carried out miRNA profiling in same-subject postmortem samples from BA9 and blood tissues. Results miRNA–mRNA network analysis showed that even though miRNAs identified in BA9 and blood were fairly distinct, their target genes and corresponding enriched pathways overlapped strongly. Among the dominant enriched biological processes were tissue development and morphogenesis, and MAPK signaling pathways. These findings point to robust, redundant, and systemic opioid-induced miRNA dysregulation with a potential functional impact on transcriptomic changes. Further, using correlation network analysis, we identified cell-type specific miRNA targets, specifically in astrocytes, neurons, and endothelial cells, associated with OUD transcriptomic dysregulation. Finally, leveraging a collection of control brain transcriptomes from the Genotype-Tissue Expression (GTEx) project, we identified a correlation of OUD miRNA targets with TGF beta, hypoxia, angiogenesis, coagulation, immune system, and inflammatory pathways. Discussion These findings support previous reports of neurovascular and immune system alterations as a consequence of opioid abuse and shed new light on miRNA network regulators of cellular response to opioid drugs.

Background Comorbid anxiety and depression are common and are associated with greater disease burden than either alone. Our recent efforts have identified an association between gut microbiota dysfunction and severity of anxiety and depression. In this follow-up, we applied Differential Co-Expression Analysis (DiffCoEx) to identify potential gut microbiota biomarker(s) candidates of treatment resistance among psychiatric inpatients. Methods In a sample of convenience, 100 psychiatric inpatients provided clinical data at admission and discharge; fecal samples were collected early during the hospitalization. Whole genome shotgun sequencing methods were used to process samples. DiffCoEx was used to identify clusters of microbial features significantly different based on treatment resistance status. Once overlapping features were identified, a knowledge-mining tool was used to review the literature using a list of microbial species/pathways and a select number of medical subject headlines (MeSH) terms relevant for depression, anxiety, and brain-gut-axis dysregulation. Network analysis used overlapping features to identify microbial interactions that could impact treatment resistance. Results DiffCoEx analyzed 10,403 bacterial features: 43/44 microbial features associated with depression treatment resistance overlapped with 43/114 microbial features associated with anxiety treatment resistance. Network analysis resulted in 8 biological interactions between 16 bacterial species. Clostridium perfringens evidenced the highest connection strength (0.95). Erysipelotrichaceae bacterium 6_1_45 has been most widely examined, is associated with inflammation and dysbiosis, but has not been associated with depression or anxiety. Conclusion DiffCoEx potentially identified gut bacteria biomarker candidates of depression and anxiety treatment-resistance. Future efforts in psychiatric microbiology should examine the mechanistic relationship of identified pro-inflammatory species, potentially contributing to a biomarker-based algorithm for treatment resistance.

To understand mechanisms and identify potential targets for intervention in the current crisis of opioid use disorder (OUD), postmortem brains represent an under-utilized resource. To refine previously reported gene signatures of neurobiological alterations in OUD from the dorsolateral prefrontal cortex (Brodmann Area 9, BA9), we explored the role of microRNAs (miRNA) as powerful epigenetic regulators of gene function. Building on the growing appreciation that miRNAs can cross the blood-brain barrier, we carried out miRNA profiling in same-subject postmortem samples from BA9 and blood tissues. miRNA-mRNA network analysis showed that even though miRNAs identified in BA9 and blood were fairly distinct, their target genes and corresponding enriched pathways were highly overlapping, with tube development and morphogenesis, and pathways related to endothelial cell function and vascular organization, among the dominant enriched biological processes. These findings point to robust, redundant, and systemic opioid-induced miRNA dysregulation with potential functional impact on transcriptomic changes. Further, using correlation network analysis we identified cell-type specific miRNA targets, specifically in astrocytes, neurons, and endothelial cells, associated with OUD transcriptomic dysregulation. Our refined miRNA-mRNA networks enabled identification of novel pharmaco-chemical interventions for OUD, particularly targeting the TGF beta-p38MAPK signaling pathway. Finally, leveraging a collection of control brain transcriptomes from the Genotype-Tissue Expression (GTEx) project, we identified correlation of OUD miRNA targets with TGF beta, hypoxia, angiogenesis, coagulation, immune system and inflammatory pathways. These findings support previous reports of neurovascular and immune system alterations as a consequence of opioid abuse.

Osteosarcoma (OS) is the most prevalent bone tumor in pediatric patients. Regimens of neoadjuvant chemotherapy have improved survival of OS patients greatly, however the 5-year survival rate for localized OS is 75% with a 30-50% recurrence rate. We sought to identify genes which could predict chemo-response and survival in localized OS. The TARGET OS RNA-seq dataset was utilized to identify genes and pathways associated with localized patient relapse and survival. We identified 478 differentially expressed genes with a 1.5 FC and FDR < 0.05 common to overall survival and relapse We further performed string analysis to generate a protein-protein interaction network followed by hub analysis with Cytohubba using betweenness centrality and radiality measures. Combining the top 10 hub genes from these two methods resulted in a total of 13 genes: MYOM2, VEGFA, VCAM1, EGFR, MUC1, IHH, GLI1, GPC3, IGF2, GRIA1, GNG12, GNGT1 and C3. These 13 genes were used to stratify localized patients in the TARGET dataset into high-risk and low-risk tertiles. The low-risk group had 100% overall survival while the high-risk group had 44% 5-year survival (p=2e-4). We also found a significant correlation between the 13 genes and time to death in localized patients (p=0.04). Additionally, there was a significant difference in expression of the 13 genes between alive and deceased patients (p=2e-5) and patients who relapsed (p=1.5e-4). Overall, these data suggest that these 13 genes could predict relapse and overall survival in OS patients with localized disease in the TARGET cohort. We performed Weighted Gene Correlation Network Analysis (WGCNA) on the 478 overlapping genes and identified five modules, with our 13 genes split across these modules. All modules were also significantly correlated with vital status suggesting that the genes in our signature represent distinct sub-groups with possibly separate mechanisms. Over-representation analysis was performed for each module and while each module did have distinct pathways, there were 65 pathways which overlapped between 3 of the modules. Of particular interest was Hedgehog signaling, with 2 of our 13 genes, IHH and GLI1, key to Hedgehog signaling, and a Hedgehog pathway inhibitor, Gant-58, scored high in reversing the 478 gene signature as determined using Connectivity Map (Broad Institute). We tested Gant-58 against two PDX OS models. Gant-58 did not inhibit a non-relapsed, chemo sensitive localized PDX-derived cell line, but showed potent activity towards a recurrent localized PDX with elevated IHH and GLI1 expression (p<0.0001). In summary, we identified 13 genes that predict overall survival and relapse in localized OS patients. The 13 genes represent distinct modules of co-expressing genes that significantly correlate with survival. Furthermore, preliminary data indicate Hedgehog pathway has a key role in survival and recurrence of localized OS patients. Citation Format: Tajhal D. Patel, Kshiti Dholakia, Tanmay R. Gandhi, Rupa S. Kanchi, Sandra L. Grimm, Chenlian Fu, Jason T. Yustein, Cristian Coarfa. Identification of a 13 gene signature to predict survival in localized osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6047.

Background: Tuberculosis(TB) isthe archetypical chronic infection, with patients having months ofsymptoms before diagnosis. In the two years aftersuccessful therapy,survivors of TB have a three-fold increased risk of death. Methods: Guinea pigs were infected with Mycobacterium tuberculosis (Mtb) for 45 days, followed by RRBS DNA methylation analysis. In humans, network analysis of differentially expressed genes across three TB cohorts were visualized at the pathway-level. Serum levels of inflammation were measured by ELISA. Horvath (DNA methylation) and RNA-seq biological clocks were used to investigate shiftsin chronological age among humans with TB. Results: Guinea pigs with TB demonstrated DNA hypermethylation and showed system-level similarity to humans with TB (p-value = 0.002). The transcriptome in TB in multiple cohorts was enriched for DNA methylation and cellular senescence. Senescence associated proteins CXCL9, CXCL10, and TNF were elevated in TB patients compared to healthy controls. Humans with TB demonstrate 12.7 years (95% CI: 7.5, 21.9) and 14.38 years (95% CI: 10.23–18.53) of cellular aging as measured by epigenetic and gene expression based cellular clocks, respectively. Conclusions: In both guinea pigs and humans, TB perturbs epigenetic processes, promoting premature cellular aging and inflammation, a plausible means to explain the long-term detrimental health outcomes after TB.

Background In vitro , animal model, and clinical evidence suggests that tuberculosis is not a monomorphic disease, and that host response to tuberculosis is protean with multiple distinct molecular pathways and pathologies (endotypes). We applied unbiased clustering to identify separate tuberculosis endotypes with classifiable gene expression patterns and clinical outcomes. Methods A cohort comprised of microarray gene expression data from microbiologically confirmed tuberculosis patients were used to identify putative endotypes. One microarray cohort with longitudinal clinical outcomes was reserved for validation, as was two RNA-seq cohorts. Finally, a separate cohort of tuberculosis patients with functional immune responses was evaluated to clarify stimulated from unstimulated immune responses. Results A discovery cohort, including 435 tuberculosis patients and 533 asymptomatic controls, identified two tuberculosis endotypes. Endotype A is characterised by increased expression of genes related to inflammation and immunity and decreased metabolism and proliferation; in contrast, endotype B has increased activity of metabolism and proliferation pathways. An independent RNA-seq validation cohort, including 118 tuberculosis patients and 179 controls, validated the discovery results. Gene expression signatures for treatment failure were elevated in endotype A in the discovery cohort, and a separate validation cohort confirmed that endotype A patients had slower time to culture conversion, and a reduced cure rate. These observations suggest that endotypes reflect functional immunity, supported by the observation that tuberculosis patients with a hyperinflammatory endotype have less responsive cytokine production upon stimulation. Conclusion These findings provide evidence that metabolic and immune profiling could inform optimisation of endotype-specific host-directed therapies for tuberculosis.