Kovalchuk, Olga

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https://opus.uleth.ca/handle/10133/4539

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Browsing Kovalchuk, Olga by Author "Ghosh, Sunita"

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    Genome-wide profiling of transfer RNAs and their role as novel prognostic markers for breast cancer
    (Nature Publishing Group, 2016) Krishnan, Preethi; Ghosh, Sunita; Wang, Bo; Heyns, Mieke; Li, Dongping; Mackey, John R.; Kovalchuk, Olga; Damaraju, Sambasivarao
    Transfer RNAs (tRNAs, key molecules in protein synthesis) have not been investigated as potential prognostic markers in breast cancer (BC), despite early findings of their dysregulation and diagnostic potential. We aim to comprehensively profile tRNAs from breast tissues and to evaluate their role as prognostic markers (Overall Survival, OS and Recurrence Free Survival, RFS). tRNAs were profiled from 11 normal breast and 104 breast tumor tissues using next generation sequencing. We adopted a Case-control (CC) and Case-Only (CO) association study designs. Risk scores constructed from tRNAs were subjected to univariate and multivariate Cox-proportional hazards regression to investigate their prognostic value. Of the 571 tRNAs profiled, 76 were differentially expressed (DE) and three were significant for OS in the CC approach. We identified an additional 11 tRNAs associated with OS and 14 tRNAs as significant for RFS in the CO approach, indicating that CC alone may not capture all discriminatory tRNAs in prognoses. In both the approaches, the risk scores were significant in the multivariate analysis as independent prognostic factors, and patients belonging to high-risk group were associated with poor prognosis. Our results confirmed global up-regulation of tRNAs in BC and identified tRNAs as potential novel prognostic markers for BC.
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    Next generation sequencing profiling identifies miR-574-3p and miR-660-5p as potential novel prognostic markers for breast cancer
    (BioMed Central, 2015) Krishnan, Preethi; Ghosh, Sunita; Wang, Bo; Li, Dongping; Narasimhan, Ashok; Berendt, Richard; Graham, Kathryn; Mackey, John R.; Kovalchuk, Olga; Damaraju, Sambasivarao
    Background: Prognostication of Breast Cancer (BC) relies largely on traditional clinical factors and biomarkers such as hormone or growth factor receptors. Due to their suboptimal specificities, it is challenging to accurately identify the subset of patients who are likely to undergo recurrence and there remains a major need for markers of higher utility to guide therapeutic decisions. MicroRNAs (miRNAs) are small non-coding RNAs that function as post-transcriptional regulators of gene expression and have shown promise as potential prognostic markers in several cancer types including BC. Results: In our study, we sequenced miRNAs from 104 BC samples and 11 apparently healthy normal (reduction mammoplasty) breast tissues. We used Case–control (CC) and Case-only (CO) statistical paradigm to identify prognostic markers. Cox-proportional hazards regression model was employed and risk score analysis was performed to identify miRNA signature independent of potential confounders. Representative miRNAs were validated using qRT-PCR. Gene targets for prognostic miRNAs were identified using in silico predictions and in-house BC transcriptome dataset. Gene ontology terms were identified using DAVID bioinformatics v6.7. A total of 1,423 miRNAs were captured. In the CC approach, 126 miRNAs were retained with predetermined criteria for good read counts, from which 80 miRNAs were differentially expressed. Of these, four and two miRNAs were significant for Overall Survival (OS) and Recurrence Free Survival (RFS), respectively. In the CO approach, from 147 miRNAs retained after filtering, 11 and 4 miRNAs were significant for OS and RFS, respectively. In both the approaches, the risk scores were significant after adjusting for potential confounders. The miRNAs associated with OS identified in our cohort were validated using an external dataset from The Cancer Genome Atlas (TCGA) project. Targets for the identified miRNAs were enriched for cell proliferation, invasion and migration. Conclusions: The study identified twelve non-redundant miRNAs associated with OS and/or RFS. These signatures include those that were reported by others in BC or other cancers. Importantly we report for the first time two new candidate miRNAs (miR-574-3p and miR-660-5p) as promising prognostic markers. Independent validation of signatures (for OS) using an external dataset from TCGA further strengthened the study findings.
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    Piwi-interacting RNAs and PIWI genes as novel prognostic markers for breast cancer
    (Impact Journals, 2016) Krishnan, Preethi; Ghosh, Sunita; Graham, Kathryn; Mackey, John R.; Kovalchuk, Olga; Damaraju, Sambasivarao
    Piwi-interacting RNAs (piRNAs), whose role in germline maintenance has been established, are now also being classified as post-transcriptional regulators of gene expression in somatic cells. PIWI proteins, central to piRNA biogenesis, have been identified as genetic and epigenetic regulators of gene expression. piRNAs/PIWIs have emerged as potential biomarkers for cancer but their relevance to breast cancer has not been comprehensively studied. piRNAs and mRNAs were profiled from normal and breast tumor tissues using next generation sequencing and Agilent platforms, respectively. Gene targets for differentially expressed piRNAs were identified from mRNA expression dataset. piRNAs and PIWI genes were independently assessed for their prognostic significance (outcomes: Overall Survival, OS and Recurrence Free Survival, RFS). We discovered eight piRNAs as novel independent prognostic markers and their association with OS was confirmed in an external dataset (The Cancer Genome Atlas). Further, PIWIL3 and PIWIL4 genes showed prognostic relevance. 306 gene targets exhibited reciprocal relationship with piRNA expression. Cancer cell pathways such as apoptosis and cell signaling were the key Gene Ontology terms associated with the regulated gene targets. Overall, we have captured the entire cascade of events in a dysregulated piRNA pathway and have identified novel markers for breast cancer prognostication.
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    Profiling of small nucleolar RNAs by next generation sequencing: potential new players for breast cancer prognosis
    (Public Library of Science, 2016) Krishnan, Preethi; Ghosh, Sunita; Wang, Bo; Heyns, Mieke; Graham, Kathryn; Mackey, John R.; Kovalchuk, Olga; Damaraju, Sambasivarao
    One of the most abundant,yet least explored,classes of RNA is the small nucleolar RNAs (snoRNAs), which are well known for their involvement in post-transcriptional modifications of other RNAs. Although snoRNAs were only considered to perform housekeeping functions for a long time, recent studies have highlighted their importance as regulators of gene expression and as diagnostic/prognostic markers.However, the prognostic potential of these RNAs has not been interrogated for breast cancer(BC). The objective of the current study was to identify snoRNAs as prognostic markers for BC. Small RNA sequencing (Illumina Genome Analyzer IIx) was performed for 104BC cases and 11 normal breast tissues. Partek Genomics Suite was used for analyzing the sequencing files.Two independent and proven approaches were used to identify prognostic markers: case-control(CC) and case only(CO). For both approaches, snoRNAs significant in the permutation test following univariate Cox proportional hazards regression model were used for constructing risks cores. Risk scores were subsequently adjusted for potential confounders in a multivariate Cox model. For both approaches, thirteen snoRNAs were associated with overall survival and/or recurrence free survival.Patients belonging to the high-risk group were associated with poor outcomes, and the risk score was significant after adjusting for confounders. Validation of representatives no RNAs (SNORD46andSNORD89) using qRT-PCR confirmed the observations from sequencing experiments.We also observed 64 snoRNAs harboring piwi interacting RNAs and/or micro RNAs that were predicted to target genes (mRNAs) involved in tumor igenesis.Our results demonstrate the potential of snoRNAs to serve (i) as novel prognostic markers for BC and (ii) as indirect regulators of gene expression