Biology subjects

Subtelny, A. O.

Publications and source records attributed to Subtelny, A. O..

5 recordsLinked to original sources

bioRxiv2022

A new transcriptional metastatic signature predicts survival in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer in adults. When ccRCC is localized to the kidney, surgical resection or ablation of the tumor is often curative. However, in the metastatic setting, ccRCC remains a highly lethal disease. Here we take advantage of fresh patient samples that include treatment-naive primary tumor tissue, matched adjacent normal kidney tissue, as well as tumor samples collected from patients with bone metastases. Single-cell transcriptomic analysis of tumor cells from the primary tumors revealed a distinct transcriptional signature that was predictive of metastatic potential and patient survival. Analysis of supporting stromal cells within the tumor environment demonstrated vascular remodeling within the endothelial cells and a proliferative signature within the fibroblasts that was associated with poor survival. An in silico cell-to-cell interaction analysis highlighted the CXCL9/CXCL10-CXCR3 axis and the CD70-CD27 axis as potential therapeutic targets. Our findings provide biological insights into the interplay between tumor cells and the ccRCC microenvironment.

cancer biology↗

bioRxiv2022

Integrated single-cell and spatial transcriptomic analyses unravel the heterogeneity of the prostate tumor microenvironment

The treatment of primary prostate cancer delicately balances an active surveillance approach for low-risk disease with multimodal treatment including surgery, radiation therapy, and hormonal therapy for high-risk disease. Recurrence and development of metastatic disease remains a clinical problem, without a clear understanding of what drives immune escape and tumor progression. Here, we sought to comprehensively describe the tumor microenvironment of localized prostate cancer contrasting this with adjacent normal samples and healthy controls. We performed single-cell RNA sequencing and high-resolution spatial transcriptomic analysis. This revealed tumor context dependent changes in gene expression. Our data point towards an immune suppressive tumor microenvironment associated with suppressive myeloid populations and exhausted T-cells, in addition to high stromal angiogenic activity. We inferred cell-to-cell relationships at an unprecedented scale for ligand-receptor interactions within undissociated tissue sections. Our work provides a highly detailed and comprehensive resource of the prostate tumor microenvironment as well as tumor-stromal cell interactions. HighlightsO_LICharacterization of prostate cancer by combined scRNA-seq and spatial transcriptomic analysis C_LIO_LIPrimary prostate cancer establishes a suppressive immune microenvironment C_LIO_LIThe prostate tumor microenvironment exhibits a high angiogenic gene expression pattern C_LIO_LIA new computational analysis pipeline to deconvolute context-specific differential gene expression C_LI

cancer biology↗

bioRxiv2019

MicroRNAs Cause Accelerated Decay of Short-Tailed Target mRNAs

MicroRNAs (miRNAs) specify recruitment of deadenylases to mRNA targets. Despite this recruitment, we find that miRNAs have almost no effect on steady-state poly(A)-tail lengths of their targets in mouse fibroblasts, which motivates acquisition of pre-steady-state measurements of the effects of miRNAs on tail lengths, mRNA levels, and translational efficiencies. Effects on translational efficiency are minimal compared to effects on mRNA levels--even for newly transcribed target mRNAs. Effects on target mRNA levels accumulate as the mRNA population approaches steady state, whereas effects on tail lengths peak for recently transcribed target mRNAs and then subside. Computational modeling of this phenomenon reveals that miRNAs cause not only accelerated deadenylation of their targets but also accelerated decay of short-tailed target molecules. This unanticipated effect of miRNAs largely prevents short-tailed target mRNAs from accumulating despite accelerated target deadenylation. The net result is a nearly imperceptible change to the steady-state tail-length distribution of targeted mRNAs.\n\nHighlightsO_LImiRNAs cause accelerated decay of short-tailed target molecules\nC_LIO_LIThis accelerated decay largely prevents accumulation of short-tailed target mRNAs\nC_LIO_LImiRNAs are similarly effective on short-lived and long-lived target mRNAs\nC_LIO_LIIn 3T3 cells, miRNA effects on translation are negligible--even for nascent mRNA\nC_LI

genomics↗

bioRxiv2019

The Dynamics of Cytoplasmic mRNA Metabolism

For all but a few mRNAs, the dynamics of metabolism are unknown. Here, we developed an experimental and analytical framework for examining these dynamics for mRNAs from thousands of genes. mRNAs of mouse fibroblasts exit the nucleus with diverse intragenic and intergenic poly(A)-tail lengths. Once in the cytoplasm, they have a broad (1000-fold) range of deadenylation rate constants, which correspond to cytoplasmic lifetimes. Indeed, with few exceptions, degradation appears to occur primarily through deadenylation-linked mechanisms, with little contribution from either endonucleolytic cleavage or deadenylation-independent decapping. Most mRNA molecules degrade only after their tail lengths fall below 25 nt. Decay rate constants of short-tailed mRNAs vary broadly (1000-fold) and are more rapid for short-tailed mRNAs that had previously undergone more rapid deadenylation. This coupling helps clear rapidly deadenylated mRNAs, enabling the large range in deadenylation rate constants to impart a similarly large range in stabilities.\n\nHighlightsO_LImRNAs enter the cytoplasm with diverse intra- and intergenic lengths\nC_LIO_LImRNA deadenylation rates span a 1000-fold range and correspond to mRNA half-lives\nC_LIO_LIAfter their tails become short, mRNAs decay at rates that span a 1000-fold range\nC_LIO_LIMore rapidly deadenylated mRNAs decay more rapidly upon reaching short tail lengths\nC_LI

genomics↗

bioRxiv2017

Predicting microRNA targeting efficacy in Drosophila

Important for understanding the regulatory roles of miRNAs is the ability to predict the mRNA targets most responsive to each miRNA. Here, we acquired datasets needed for the quantitative study of microRNA targeting in Drosophila. Analyses of these data expanded the types of sites known to be effective in flies, expanded the mRNA regions with detectable targeting to include 5' UTRs, and identified features of site context that correlate with targeting efficacy. Updated evolutionary analyses evaluated the probability of conserved targeting for each predicted site and indicated that more than a third of the Drosophila genes are preferentially conserved targets of miRNAs. Based on these results, a quantitative model was developed to predict targeting efficacy in insects. This model performed better than existing models and will drive the next version of TargetScanFly (v7.0; targetscan.org), thereby providing a valuable resource for placing miRNAs into gene-regulatory networks of this important experimental organism.

systems biology↗