Biology subjects

Thapa, I.

Publications and source records attributed to Thapa, I..

4 recordsLinked to original sources

bioRxiv2023

A Novel Computational Approach for the Mining of Signature Pathways Using Species Co-occurrence Networks in Gut Microbiomes

Advances in metagenome sequencing data continue to enable new methods for analyzing biological systems. When handling microbial profile data, metagenome sequencing has proven to be far more comprehensive than traditional methods such as 16s rRNA data, which rely on partial sequences. Microbial community profiling can be used to obtain key biological signals that pave the way for better and accurate understanding of complex systems that are critical for advancing biomedical research and healthcare. There have been few attempts to uncover microbial community associations with certain health conditions. However, such attempts have mostly used partial or incomplete data to accurately capture those associations. This study introduces a novel computational approach for the identification of co-occurring microbial communities using the abundance and functional roles of species-level microbiome data. The proposed approach is then used to identify signature pathways associated with inflammatory bowel disease (IBD). Furthermore, we developed a computational pipeline to identify microbial species co-occurrences from metagenome data. When comparing IBD to a control group, we show that co-occurring communities of species are enriched for potential pathways. We also show that the identified co-occurring microbial species operate as a community to facilitate pathway enrichment. The obtained findings suggest that the proposed network model, along with the computational pipeline, provide a valuable analytical tool to analyze complex biological systems and extract pathway signatures that classify or diagnose certain health conditions. CCS CONCEPTS* Applied computing [->] Biological networks; Bioinformatics; Systems biology. ACM Reference FormatSuyeon Kim, Ishwor Thapa, and Hesham Ali. 2023. A Novel Computational Approach for the Mining of Signature Pathways Using Species Co-occurrence Networks in Gut Microbiomes. In Proceedings of ACM Conference (Conference17). ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn

bioinformatics↗

bioRxiv2022

MiR-1253 Potentiates Cisplatin Response in Pediatric Group 3 Medulloblastoma by Regulating Ferroptosis

Medulloblastomas (MB) are the most common malignant pediatric brain tumor and a leading cause of childhood mortality. Aggressive tumors belonging to group 3 (G3MB) are distinguished by a marked reduction in programmed cell death by ferroptosis. These aggressive tumors also enrich iron transport and glutathione metabolism. A highly enriched pathway in these tumors is iron-sulfur (Fe-S) cluster binding corresponding to significant upregulation of ABCB7, a poor prognostic feature linked with accelerated mortality. This study elucidated whether repressing ABCB7 activates ferroptosis to mitigate G3MB aggressiveness and whether this pathway is pharmacologically targetable. In silico and in vitro analyses confirmed upregulation of ABCB7 and GPX4, the central regulator of ferroptosis, in G3MB cell lines and tumors. Repressing ABCB7 (miR-1253OE, siABCB7, sh-ABCB7) induced iron overload, elicited oxidative stress, and triggered lipid peroxidation, leading to an abrogation of medullosphere formation and cell death by ferroptosis. Intriguingly, fractionation studies revealed that ABCB7 repression abrogated GPX4 expression, most likely by GSH depletion. Repressing ABCB7 induced mitochondrial dysfunction and reduced oxidative phosphorylation. Cisplatin, a chemotherapeutic mainstay of G3MB, induces cell death by DNA crosslinking. In ABCB7 repressed cell lines, the IC50 of cisplatin was halved, resulting in augmented oxidative stress and lipid peroxidation, culminating in a higher index of ferroptosis. Artesunate, an anti-malarial drug capable of triggering ferroptosis, was shown to synergize with cisplatin, reducing tumor burden and significantly prolonging survival. Taken together, the current study illustrates how targeting iron transport can augment ferroptosis in G3MBs. It further identifies an FDA-approved drug capable of recapitulating these effects and potentiating mainstay chemotherapy.

cancer biology↗

bioRxiv2021

MiR-212-3p functions as a tumor suppressor gene in group 3 medulloblastoma via targeting Nuclear Factor I/B (NFIB)

BackgroundMedulloblastoma (MB), the most frequent malignant pediatric brain tumor, is subdivided into four primary subgroups, wingless-type (WNT), sonic hedgehog (SHH), group 3, and group 4. Haploinsufficiency of chromosome 17p13.3 and c-Myc amplification distinguish high-risk group 3 tumors associated with rapid metastasis, recurrence and early mortality. We sought to identify the role of miR-212-3p, which resides on chromosome 17p13.3, in the pathophysiology of group 3 MB. MethodsWe first determined miR-212-3p expression in group 3 MB using several publicly-available datasets with confirmatory studies in vitro. We then identified epigenetic regulation by studying methylation and HDAC modifications along the promoter region. We used two systems for expression restoration, i.e. transient transfection or stable induction, to delineate miR-212-3ps tumor suppressive and biochemical properties via assays assessing cancer proliferation, migration, invasion, colony formation, along with cell cycle and apoptosis analyses. We then compared MB and miR target databases to isolate a putative target whose biochemical and oncogenic properties were similarly elucidated using either transient silencing of target expression or stable induction of miR-212-3p. ResultsRNA expression analyses revealed dramatically reduced miR-212-3p levels in group 3 tumors and cell lines mainly through epigenetic silencing via histone modifications. Restoring miR-212-3p expression reduced in vitro cancer cell proliferation, migration, colony formation, and wound healing. Elevated miR-212-3p levels shifted c-Myc phosphorylation (from serine-62 to threonine-58), triggering destabilization and degradation; concurrently, its pro-apoptotic binding partners, i.e., Bin-1 and P19ARF, were upregulated with subsequent elevated apoptotic signals. Using a combination of transcriptomic data and dual luciferase assay, we isolated an oncogenic target of miR-212-3p, i.e. NFIB, a nuclear transcription factor implicated in metastasis and recurrence in various cancers. Increased expression of NFIB was confirmed in group 3 tumors, with poor survival shown in high-expressing patients. Transient NFIB silencing in vitro reduced cancer cell proliferation, colony formation, migration, and invasion. Concurrently, in group 3 MB cells, reduced medullosphere formation along with decreased expression of stem cell markers (Nanog, Oct4, Sox2, CD133) were noted. ConclusionThese results substantiate the tumor-suppressive role of miR-212-3p in group 3 MB and provide a potential therapeutic oncogenic target implicated in metastasis and tumor recurrence.

cancer biology↗

bioRxiv2019

Multiplatform Biomarker Identification using a Data-driven Approach Enables Single-sample Classification

High-throughput gene expression profiles have allowed discovery of potential biomarkers enabling early diagnosis, prognosis and developing individualized treatment. However, it remains a challenge to identify a set of reliable and reproducible biomarkers across various gene expression platforms and laboratories for single sample diagnosis and prognosis. We address this need with our Data-Driven Reference (DDR) approach, which employs stably expressed housekeeping genes as references to eliminate platform-specific biases and non-biological variabilities. Our method identifies biomarkers with \"built-in\" features, and these features can be interpreted consistently regardless of profiling technology, which enable classification of single-sample independent of platforms. Validation with RNA-seq data of blood platelets shows that DDR achieves the superior performance in classification of six different tumor types as well as molecular target statuses (such as MET or HER2-positive, and mutant KRAS, EGFR or PIK3CA) with smaller sets of biomarkers. We demonstrate on the three microarray datasets that our method is capable of identifying robust biomarkers for subgrouping medulloblastoma samples with data perturbation due to different microarray platforms. In addition to identifying the majority of subgroup-specific biomarkers in Code-Set of nanoString, some potential new biomarkers for subgrouping medulloblastoma were detected by our method. Our results show that the DDR method contributes significantly to single-sample classification of disease and shed light on personalized medicine.

bioinformatics↗