Biology subjects

Chatrath, A.

Publications and source records attributed to Chatrath, A..

6 recordsLinked to original sources

bioRxiv2026

tRF-3021a, a tRNA-Ala-TGC derived 3' fragment, promotes glioblastoma cell invasion, suppresses apoptosis, and is required for normal levels of protein synthesis

tRNA-derived fragments (tRFs) are a relatively recently discovered class of small RNAs implicated in gene-regulatory processes in diverse biological contexts but there have been very few reports of a clear phenotypic role of these small RNAs in cancer progression. To select tRFs that should receive priority for mechanistic experiments, we analyzed small RNA-seq data from The Cancer Genome Atlas (TCGA) and found that high expression of three 3' tRFs (tRF-3a), tRF-3009a, tRF-3021a or tRF-3030a, is significantly associated with poor overall survival in low-grade glioma (LGG). In glioblastoma cells, tRF-3009a, tRF-3021a and tRF-3030a enhance cell invasion and migration but tRF-3021a was uniquely required for cell proliferation and suppression of apoptosis. Interestingly, tRF-3021a knockdown decreases global protein synthesis prior to and independent of apoptosis in a number of cancer cell lines, both from and outside the glioblastoma lineage. RNA-seq reveals that the results cannot be explained by microRNA-like functions of tRF-3021a. These data indicate that tRF-3021a supports cancer cell survival and particularly protein synthesis while promoting cellular invasion and migration and suggests that strategies to downregulate this short RNA could be a potential therapeutic approach in cancers. ImplicationtRF-3021a promotes malignant cell phenotypes, sustains global protein synthesis and prevents spontaneous apoptosis, motivating efforts to evaluate it as a biomarker and therapeutic target.

cancer biology↗

bioRxiv2020

Data Integration with SUMO Detects Latent Relationships Between Patients in Lower-Grade Gliomas

Joint analysis of multiple genomic data types can facilitate the discovery of complex mechanisms of biological processes and genetic diseases. We present a novel data integration framework based on non-negative matrix factorization that uses patient similarity networks. Our implementation supports continuous multi-omic datasets for molecular subtyping and handles missing data without using imputation, making it more efficient for genome-wide assays in large cohorts. Applying our approach to gene expression, microRNA expression, and methylation data from patients with lower grade gliomas, we identify a subtype with a significantly poorer prognosis. Tumors assigned to this subtype are hypomethylated genome-wide with a gain of AP-1 occupancy in the demethylated distal enhancers. These tumors genomic profiles are similar to Grade IV gliomas: they are enriched for somatic chr7 gain, chr10 loss, and other molecular events that have yet to be used in the diagnosis of lower-grade gliomas as per the current WHO guidelines.

bioinformatics↗

bioRxiv2019

ATAC-seq identifies thousands of extrachromosomal circular DNA in cancers and cell lines

Extrachromosomal circular DNAs (eccDNAs) lack centromeres and are not passed equally into daughter cells and thus provide a source of cell-cell heterogeneity in normal and tumor cells. Previously we and other groups purified circular DNA and linearized them by rolling circle amplification for paired end high throughput sequencing to identify eccDNA in cells and tissues. We hypothesized that many eccDNA will have more open chromatin and so will be susceptible to linearization and sequencing by tagmentation. Indeed, we find that ATAC-seq on cell lines and cancers, without any enrichment of circular DNA, identifies thousands of eccDNAs. The identified eccDNAs in cell lines were validated by inverse PCR on DNA that survives exonuclease digestion of linear DNA and by metaphase FISH. We demonstrate that ATAC-seq data generated in Lower Grade Gliomas (LGG) and Glioblastomas (GBM) identify eccDNAs, including one containing the well-known EGFR gene amplicon from chr7. Many of the eccDNAs are identified even before amplification of the locus is detected by genotyping arrays. Thus, standard ATAC-seq is a sensitive method to detect segments of DNA that are present as eccDNA in a subset of the tumor cells, ready to be further amplified under appropriate selection, as during therapy.

genomics↗

bioRxiv2019

Parallel Concerted Evolution of Ribosomal Protein Genes in Fungi and Its Adaptive Significance

Ribosomal proteins (RPs) genes encode structure components of ribosomes, the cellular machinery for protein synthesis. A single functional copy has been maintained in most of 78-80 RP families in animals due to evolutionary constraints imposed by gene dosage balance. Some fungal species have maintained duplicate copies in most RP families. How the RP genes were duplicated and maintained in these fungal species, and their functional significance remains unresolved. To address these questions, we identified all RP genes from 295 fungi and inferred the timing and nature of gene duplication for all RP families. We found that massive duplications of RP genes have independently occurred by different mechanisms in three distantly related lineages. The RP duplicates in two of them, budding yeast and Mucoromycota, were mainly created by whole genome duplication (WGD) events. However, in fission yeasts, duplicate RP genes were likely generated by retroposition, which is unexpected considering their dosage sensitivity. The sequences of most RP paralogs in each species have been homogenized by repeated gene conversion, demonstrating parallel concerted evolution, which might have facilitated the retention of their duplicates. Transcriptomic data suggest that the duplication and retention of RP genes increased RP transcription abundance. Physiological data indicate that increased ribosome biogenesis allowed these organisms to rapidly consuming sugars through fermentation while maintaining high growth rates, providing selective advantages to these species in sugar-rich environments.

evolutionary biology↗

bioRxiv2018

The Germline Variants rs61757955 and rs34988193 are Predictive of Survival in Low Grade Glioma Patients

AbstractLow grade gliomas are invasive brain tumors that are difficult to completely resect neurosurgically. They often recur following resection and progress, resulting in death. Although previous studies have shown that specific germline variants increase the risk of tumor formation, no previous study has screened many germline variants to identify variants predictive of survival in glioma patients. In this study, we present an approach to identify the small fraction of prognostic germline variants from the pool of over four million variants that we variant called in The Cancer Genome Atlas whole exome sequencing and RNA sequencing datasets. We identified two germline variants that are predictive of poor patient outcomes by Cox regression, controlling for eleven covariates. rs61757955 is a germline variant found in the 3 UTR of GRB2 associated with increased KRAS signaling, CIC mutations, and 1p/19q co-deletion. rs34988193 is a germline variant found in the tumor suppressor gene ANKDD1a that causes an amino acid change from lysine to glutamate. This variant was found to be predictive of poor prognosis in two independent low grade glioma datasets and is predicted to be within the top 0.06% of deleterious mutations across the human genome. The wild type residue is conserved in all 22 other species with a homologous protein.\n\nImplicationsThis is the first study presenting an approach to screening many germline variants to identify variants predictive of survival and our application of this methodology revealed the germline variants rs61757955 and rs34988193 as being predictive of survival in low grade glioma patients.

cancer biology↗

bioRxiv2018

A prognostic signature for lower-grade gliomas based on expression of long noncoding RNAs

Diffuse low-grade and intermediate-grade gliomas (together known as lower-grade gliomas, WHO grade II and III) develop in the supporting glial cells of brain and are the most common types of primary brain tumor. Despite a better prognosis for lower-grade gliomas, 70% of patients undergo high-grade transformation within 10 years, stressing the importance of better prognosis. Long non-coding RNAs (lncRNAs) are gaining attention as potential biomarkers for cancer diagnosis and prognosis. We have developed a computational model, UVA8, for prognosis of lower-grade gliomas by combining lncRNA expression, Cox regression and L1-LASSO penalization. The model was trained on a subset of patients in TCGA. Patients in TCGA, as well as a completely independent validation set (CGGA) could be dichotomized based on their risk score, a linear combination of the level of each prognostic lncRNA weighted by its multivariable cox regression coefficient. UVA8 is an independent predictor of survival and outperforms standard epidemiological approaches and previous published lncRNA-based predictors as a survival model. Guilt-by-association studies of the lncRNAs in UVA8, all of which predict good outcome, suggest they have a role in suppressing interferon stimulated response and epithelial to mesenchymal transition. The expression levels of 8 lncRNAs can be combined to produce a prognostic tool applicable to diverse populations of glioma patients. The 8 lncRNA (UVA8) based score can identify grade II and grade III glioma patients with poor outcome and thus identify patients who should receive more aggressive therapy at the outset.

genomics↗