Biology subjects

Raman, A. T.

Publications and source records attributed to Raman, A. T..

4 recordsLinked to original sources

bioRxiv2021

High Enhancer Activity is an Epigenetic Feature of HPV Negative Atypical Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease with significant morbidity and mortality and frequent recurrence. Pre-NGS efforts to transcriptionally classify HNSCC into groups of varying prognosis have identified four accepted molecular subtypes of disease: Atypical (AT), Basal (BA), Classical (CL), and Mesenchymal (MS). Here, we investigated the active enhancer landscapes of these subtypes using representative HNSCC cell lines and identified samples belonging to the AT subtype as having increased enhancer activity compared to the other 3 HNSCC subtypes. Cell lines belonging to atypical subtype were more resistant to bromodomain inhibitors (BETi). PRO-Seq experiments that both TCGA tumors and AT cell lines showed higher eRNA transcripts for enhancers controlling BETi resistance pathways, such as lipid metabolism and MAPK signaling. Additionally, HiChIP experiments suggested higher enhancer-promoter (E-P) contacts in the AT subtype, including on genes identified in the eRNA analysis. Consistently, known BETi resistance pathways were upregulated upon exposure to these inhibitors. Together, our results identify that the AT subtype of HNSCC is associated with high enhancer activity, resistance to BET inhibition, and signaling pathways that could serve as future targets for sensitizing HNSCC to BET inhibition.

cancer biology↗

bioRxiv2021

H3K4me1-marked Enhancer Activation in Resistant Prostate Cancers Implicates SOX4 and MENIN Inhibition as Therapeutic Strategies

Chromatin elements and regulators play important roles during progression of prostate cancer, however, their involvement in response to therapy is less well understood. Using comprehensive chromatin profiling of patient-derived tumors, we find that enhancer elements marked by H3K4me1 are highly enriched in aggressive therapy-resistant prostate cancers on important resistance-driving genes, such as those involved in FOXA1, NOTCH and TGF-{beta} signaling. Importantly, by targeting H3K4me1-elements through inhibition of the MLL complex, a H3K4 methyltransferase, we reduced the proliferative capacity and H3K4me1-associated loci in enzalutamide-resistant prostate cancer lines. We identify AR, FOXA1, HOXB13 and SOX4 as a subset of core TFs that are critical for establishing transcriptional networks via active enhancer reprogramming during acquisition of resistance to therapy. Knock-down of SOX4 reduced cell proliferation and disrupted the H3K4me1 enhancer landscape, further suggesting a role for this TF in therapy-resistance. Overall, our data implicate H3K4me1-marked enhancers as a key epigenetic feature of therapy-resistance, implicate SOX4 in enhancer reprogramming and suggest use of MLL/MENIN inhibitors as a potential therapeutic strategy in high-grade and locally advanced prostate cancers that do not respond to traditional therapies.

cancer biology↗

bioRxiv2020

Chromatin State Dynamics Confers Specific Therapeutic Strategies in Enhancer Subtypes of Colorectal Cancer

The extent and function of chromatin state aberrations during colorectal cancer (CRC) progression is not completely understood. Here, by comprehensive epigenomic characterization of 56 tumors, adenomas, and their matched normal tissues, we define the dynamics of chromatin states during the progression of colorectal cancer. H3K27ac-marked active enhancer state could distinguish between different stages of CRC progression. By epigenomic editing, we present evidence that gains of tumor-specific enhancers for crucial oncogenes, such as ASCL2 and FZD10, was crucial for excessive proliferation. Consistently, combination of MEK plus bromodomain (BET) inhibition was found to have synergistic effects in CRC patient-derived xenograft (PDX) models. Probing inter-tumor heterogeneity, we identified four distinct enhancer subtypes (EpiC), three of which correlate well with previously defined transcriptomic subtypes (CMSs). Importantly, CMS2 can be divided into two EpiC subgroups with significant survival differences. Leveraging such correlation, we devised a combinatorial therapeutic strategy of enhancer-blocking bromodomain inhibitors with pathway-specific inhibitors (PARPi, EGFRi, and TGF{beta}i) for three EPIC groups. Our data suggest that the dynamics of active enhancer underlies colorectal cancer progression and the patient-specific active enhancer patterns govern their unique gene expression patterns which can be leveraged for precision combination therapy.

cancer biology↗

bioRxiv2017

Bias toward long gene misregulation in synaptic disorders can be an artefact of amplification-based methods

Several recent studies have suggested that genes that are longer than 100 kilobases are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2-mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low fold-changes, disappeared after accounting for baseline variability estimated from randomized control samples. As we found no similar bias with NanoString technology, this long-gene bias seems to be particular to PCR amplification-based platforms. In contrast, authentic long gene effects, such as those caused by topoisomerase inhibition, can be detected even after adjustment for baseline variability. Accurate detection of length-dependent trends requires establishing a baseline from randomized control samples.\n\nHIGHLIGHTSO_LILength-dependent gene misregulation is not intrinsic to Mecp2 disruption.\nC_LIO_LITopoisomerase inhibition produces an authentic long gene bias.\nC_LIO_LIPCR amplification-based high-throughput datasets are biased toward long genes.\nC_LI

neuroscience↗