Biology subjects

Subramanian, K.

Publications and source records attributed to Subramanian, K..

4 recordsLinked to original sources

bioRxiv2018

Decreased RORC expression and downstream signaling in HTLV-1-associated Adult T-cell Lymphoma/Leukemia uncovers an antiproliferative IL17 link: a potential target for immunotherapy?

Retinoic acid-related drugs have shown promising pre-clinical activity in Adult T-cell Leukemia/Lymphoma (ATL), but RORC (Retinoic acid Orphan Receptor C) signaling has not been explored. Therefore, we investigated transcriptome-wide interactions of the RORC pathway in Human T-cell Leukemia Virus-1 (HTLV-1) infection and ATL, using our own and publicly available gene expression data for ATL and other leukemias, HTLV-1-infected individuals and healthy controls. Gene expression data from ATL patients were analyzed using Weighted Gene Correlation Network Analysis (WGCNA) to determine gene modules and their correlation to clinical and molecular data. Both PBMCs and CD4+ T-cells showed decreased RORC expression in four different ATL cohorts. A small subset of RORChi ATL patients was identified with significantly lower pathognomonic CADM1 and HBZ levels but similar levels of other ATL markers (CD4/CD25/CCR4), hinting at a less aggressive ATL subtype. In addition, an age-dependent decrease in RORC expression was found in HTLV-1-infected individuals, but not in healthy controls, suggesting an early molecular event predisposing to leukemogenesis. Genes upstream of RORC signaling were members of a proliferative gene module (containing proliferation markers PCNA/MKI67), whereas downstream members clustered in an antiproliferative gene module. IL17C transcripts showed the strongest negative correlation to PCNA in both ATL cohorts, which was replicated in two large cohorts of T- and B-cell acute leukemias. In conclusion, decreased RORC expression and downstream signaling might represent an early event in ATL pathogenesis. An antiproliferative IL17C/PCNA link is shared between ATL, T-ALL and B-ALL, suggesting (immuno)therapeutic benefit of boosting RORC/IL17 signaling.\n\nAbbreviations

immunology↗

bioRxiv2018

Active gelation breaks time-reversal-symmetry of mitotic chromosome mechanics

In cell division, mitosis is the phase in which duplicated sets of chromosomes are mechanically aligned to form the metaphase plate before being segregated in two daughter cells. Irreversibility is a hallmark of this process, despite the fundamental laws of Newtonian mechanics being time symmetric.\n\nHere we show experimentally that mitotic chromosomes receive the arrow of time by time-reversal-symmetry breaking of the underlying mechanics in prometaphase. By optically inducing hydrodynamic flows within prophase nuclei, we find that duplicated chromatid pairs initially form a fluid suspension in the nucleoplasm: although showing little motion on their own, condensed chromosomes are free to move through the nucleus in a time-reversible manner. Actively probing chromosome mobility further in time, we find that this viscous suspension of chromatin transitions into a gel after nuclear breakdown. This gel state, in which chromosomes cannot be moved by flows, persists even when chromosomes start moving to form the metaphase plate. Complemented by minimal reconstitution experiments, our active intra-nuclear micro-rheology reveals time-reversal-symmetry breaking of chromosome mechanics to be caused by the transition from a purely fluid suspension into an active gel.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC=\"FIGDIR/small/296566_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (36K):\norg.highwire.dtl.DTLVardef@15b00edorg.highwire.dtl.DTLVardef@199eb2dorg.highwire.dtl.DTLVardef@1f0550org.highwire.dtl.DTLVardef@95cb5a_HPS_FORMAT_FIGEXP M_FIG C_FIG One sentence summaryFlows induced in living cell nuclei reveal the rheological changes that bring chromosomes under mechanical control during mitosis.

biophysics↗

bioRxiv2017

Therapeutically advantageous secondary targets of abemaciclib identified by multi-omics profiling of CDK4/6 inhibitors

FDA approval of multiple drugs differing in chemical structures but targeting the same protein raises the question whether such drugs have sufficiently similar mechanisms of action to be considered functionally equivalent. In this paper we compare three recently approved inhibitors of the cyclin-dependent kinases CDK4/6 - palbociclib, ribociclib, and abemaciclib - that are becoming important therapies for the treatment of hormone-receptor positive breast and potentially other cancers. We find that transcriptional and proteomic changes induced by the three drugs differ significantly and that abemaciclib has unique cellular activities including induction of cell death (even in pRb-deficient cells), arrest in the G2 phase of the cell cycle, and reduced drug adaptation. These activities appear to arise from inhibition of kinases other than CDK4/6 including CDK2/Cyclin A/E and CDK1/Cyclin B.\n\nSIGNIFICANCEThe target profiles of most drugs are established relatively early in their development and are not systematically revisited at the time of approval. Scattered reports suggest that palbociclib, ribociclib, and abemaciclib differ in pharmacokinetics, dosing, and adverse effects but the three drugs are generally regarded as similar. Our finding that the drugs differ substantially in mechanism of action - abemaciclib retains activities of the earlier-generation drug alvocidib - suggests the potential for different uses in the clinic: in particular, abemaciclib may show activity in patients progressing on palbociclib or ribociclib. More generally, our approach relying on data from five distinct phenotypic and biochemical assays strongly suggests that a multi-faceted approach is necessary to get a reliable picture the target spectrum of kinase inhibitors.

cancer biology↗

bioRxiv2017

From word models to executable models of signaling networks using automated assembly

Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. We present an approach to building computational models directly from natural language using automated assembly. Molecular mechanisms described in simple English are read by natural language processing algorithms, converted into an intermediate representation and assembled into executable or network models. We have implemented this approach in the Integrated Network and Dynamical Reasoning Assembler (INDRA), which draws on existing natural language processing systems as well as pathway information in Pathway Commons and other online resources. We demonstrate the use of INDRA and natural language to model three biological processes of increasing scope: (i) p53 dynamics in response to DNA damage; (ii) adaptive drug resistance in BRAF-V600E mutant melanomas; and (iii) the RAS signaling pathway. The use of natural language for modeling makes routine tasks more efficient for modeling practitioners and increases the accessibility and transparency of models for the broader biology community.\n\nStandfirst textINDRA uses natural language processing systems to read descriptions of molecular mechanisms and assembles them into executable models.\n\nHighlightsO_LIINDRA decouples the curation of knowledge as word models from model implementation\nC_LIO_LIINDRA is connected to multiple natural language processing systems and can draw on information from curated databases\nC_LIO_LIINDRA can assemble dynamical models in rule-based and reaction network formalisms, as well as Boolean networks and visualization formats\nC_LIO_LIWe used INDRA to build models of p53 dynamics, resistance to targeted inhibitors of BRAF in melanoma, and the Ras signaling pathway from natural language\nC_LI

systems biology↗