Regulation of rDNA Transcription by Proto-Oncogene PELP1

Proline-, glutamic acid-, and leucine-rich protein (PELP1) is a novel nuclear receptor coregulator with a multitude of functions. PELP1 serves as a scaffolding protein that couples various signaling complexes with nuclear receptors and participates as a transcriptional coregulator. Recent data suggest that PELP1 expression is deregulated in hormonal cancers, and that PELP1 functions as a proto-oncogene; however, the mechanism by which PELP1 promotes oncogenesis remains elusive.Using pharmacological inhibitors, confocal microscopy and biochemical assays, we demonstrated that PELP1 is localized in the nucleolus and that PELP1 is associated with the active ribosomal RNA transcription. Cell synchronization studies showed that PELP1 nucleolar localization varies and the greatest amount of nucleolar localization was observed during S and G2 phases. Using pharmacological compounds and CDK site mutants of PELP1, we found that CDK's activity plays an important role on PELP1 nucleolar localization. Depletion of PELP1 by siRNA decreased the expression of pre-rRNA. Reporter gene assays using ribosomal DNA (pHrD) luc-reporter revealed that PELP1WT but not PELP1MT enhanced the expression of reporter. Deletion of nucleolar domains abolished PELP1-mediated activation of the pHrD reporter. ChIP analysis revealed that PELP1 is recruited to the promoter regions of rDNA and is needed for optimal transcription of ribosomal RNA.Collectively, our results suggest that proto-oncogene PELP1 plays a vital role in rDNA transcription. PELP1 modulation of rRNA transcription, a key step in ribosomal biogenesis may have implications in PELP1-mediated oncogenic functions

The ​oestrogen receptor alpha-regulated lncRNA ​NEAT1 is a critical modulator of prostate cancer

The androgen receptor (AR) plays a central role in establishing an oncogenic cascade that drives prostate cancer progression. Some prostate cancers escape androgen dependence and are often associated with an aggressive phenotype. The oestrogen receptor alpha (ERα) is expressed in prostate cancers, independent of AR status. However, the role of ERα remains elusive. Using a combination of chromatin immunoprecipitation (ChIP) and RNA-sequencing data, we identified an ERα-specific non-coding transcriptome signature. Among putatively ERα-regulated intergenic long non-coding RNAs (lncRNAs), we identified nuclear enriched abundant transcript 1 (NEAT1) as the most significantly overexpressed lncRNA in prostate cancer. Analysis of two large clinical cohorts also revealed that NEAT1 expression is associated with prostate cancer progression. Prostate cancer cells expressing high levels of NEAT1 were recalcitrant to androgen or AR antagonists. Finally, we provide evidence that NEAT1 drives oncogenic growth by altering the epigenetic landscape of target gene promoters to favour transcription

AI Foundation Models for Weather and Climate: Applications, Design, and Implementation

Machine learning and deep learning methods have been widely explored in understanding the chaotic behavior of the atmosphere and furthering weather forecasting. There has been increasing interest from technology companies, government institutions, and meteorological agencies in building digital twins of the Earth. Recent approaches using transformers, physics-informed machine learning, and graph neural networks have demonstrated state-of-the-art performance on relatively narrow spatiotemporal scales and specific tasks. With the recent success of generative artificial intelligence (AI) using pre-trained transformers for language modeling and vision with prompt engineering and fine-tuning, we are now moving towards generalizable AI. In particular, we are witnessing the rise of AI foundation models that can perform competitively on multiple domain-specific downstream tasks. Despite this progress, we are still in the nascent stages of a generalizable AI model for global Earth system models, regional climate models, and mesoscale weather models. Here, we review current state-of-the-art AI approaches, primarily from transformer and operator learning literature in the context of meteorology. We provide our perspective on criteria for success towards a family of foundation models for nowcasting and forecasting weather and climate predictions. We also discuss how such models can perform competitively on downstream tasks such as downscaling (super-resolution), identifying conditions conducive to the occurrence of wildfires, and predicting consequential meteorological phenomena across various spatiotemporal scales such as hurricanes and atmospheric rivers. In particular, we examine current AI methodologies and contend they have matured enough to design and implement a weather foundation model.Comment: 44 pages, 1 figure, updated Fig.

Novel insights into breast cancer genetic variance through RNA sequencing

Using RNA sequencing of triple-negative breast cancer (TNBC), non-TBNC and HER2-positive breast cancer sub-types, here we report novel expressed variants, allelic prevalence and abundance, and coexpression with other variation, and splicing signatures. To reveal the most prevalent variant alleles, we overlaid our findings with cancer- and population-based datasets and validated a subset of novel variants of cancer-related genes: ESRP2, GBP1, TPP1, MAD2L1BP, GLUD2 and SLC30A8. As a proof-of-principle, we demonstrated that a rare substitution in the splicing coordinator ESRP2(R353Q) impairs its ability to bind to its substrate FGFR2 pre-mRNA. In addition, we describe novel SNPs and INDELs in cancer relevant genes with no prior reported association of point mutations with cancer, such as MTAP and MAGED1. For the first time, this study illustrates the power of RNA-sequencing in revealing the variation landscape of breast transcriptome and exemplifies analytical strategies to search regulatory interactions among cancer relevant molecules

The oestrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer

The androgen receptor (AR) plays a central role in establishing an oncogenic cascade that drives prostate cancer progression. Some prostate cancers escape androgen dependence and are often associated with an aggressive phenotype. The oestrogen receptor alpha (ERα) is expressed in prostate cancers, independent of AR status. However, the role of ERα remains elusive. Using a combination of chromatin immunoprecipitation (ChIP) and RNA-sequencing data, we identified an ERα-specific non-coding transcriptome signature. Among putatively ERα-regulated intergenic long non-coding RNAs (lncRNAs), we identified nuclear enriched abundant transcript 1 (NEAT1) as the most significantly overexpressed lncRNA in prostate cancer. Analysis of two large clinical cohorts also revealed that NEAT1 expression is associated with prostate cancer progression. Prostate cancer cells expressing high levels of NEAT1 were recalcitrant to androgen or AR antagonists. Finally, we provide evidence that NEAT1 drives oncogenic growth by altering the epigenetic landscape of target gene promoters to favour transcription

Arpc1b, a centrosomal protein, is both an activator and substrate of Aurora A

In addition to its function as an Arp2/3 complex subunit, Arp1cb interacts with and stimulates Aurora A at centrosomes, functioning in cell cycle progression

Association between Incidental Pelvic Inflammation and Aggressive Prostate Cancer

The impact of pelvic inflammation on prostate cancer (PCa) biology and aggressive phenotype has never been studied. Our study objective was to evaluate the role of pelvic inflammation on PCa aggressiveness and its association with clinical outcomes in patients following radical prostatectomy (RP). This study has been conducted on a retrospective single-institutional consecutive cohort of 2278 patients who underwent robot-assisted laparoscopic prostatectomy (RALP) between 01/2013 and 10/2019. Data from 2085 patients were analyzed to study the association between pelvic inflammation and adverse pathology (AP), defined as Gleason Grade Group (GGG) > 2 and ≥ pT3 stage, at resection. In a subset of 1997 patients, the association between pelvic inflammation and biochemical recurrence (BCR) was studied. Alteration in tumor transcriptome and inflammatory markers in patients with and without pelvic inflammation were studied using microarray analysis, immunohistochemistry, and culture supernatants derived from inflamed sites used in functional assays. Changes in blood inflammatory markers in the study cohort were analyzed by O-link. In univariate analyses, pelvic inflammation emerged as a significant predictor of AP. Multivariate cox proportional-hazards regression analyses showed that high pelvic inflammation with pT3 stage and positive surgical margins significantly affected the time to BCR (p ≤ 0.05). PCa patients with high inflammation had elevated levels of pro-inflammatory cytokines in their tissues and in blood. Genes involved in epithelial-to-mesenchymal transition (EMT) and DNA damage response were upregulated in patients with pelvic inflammation. Attenuation of STAT and IL-6 signaling decreased tumor driving properties of conditioned medium from inflamed sites. Pelvic inflammation exacerbates the progression of prostate cancer and drives an aggressive phenotype.</p

Chromatin remodeling in cancer: A gateway to regulate gene transcription

Cancer cells are remarkably adaptive to diverse survival strategies, probably due to its ability to interpret signaling cues differently than the normal cells. It appears as if cancer cells are constantly sampling, selecting and adapting signaling pathways to favor its proliferation. This process of successful adaptive evolution eventually renders a retractile nature to therapeutic regimens, fueling to the process of cancer progression. Based on plethora of available information, it is now evident that multiple signaling pathways eventually converge, perhaps, in a tempo‐spatial manner, onto DNA template‐dependent dynamic processes. Considering the complexity and packaging of eukaryotic genome, this process involves energy‐dependent sub‐events mediated by chromatin remodelers. Chromatin remodeler proteins function as gatekeepers and constitute a major determinant of accessibility of accessory factors to nucleosome DNA, allowing a wide repertoire of biological functions. And thus, aberrant expression or epigenetic modulation of remodeler proteins confers a unique ability to cancer cells to reprogram its genome for the maintenance of oncogenic phenotypes. Cancer cells can uniquely select a multi‐subunit remodeler proteome for oncogenic advantage. This review summarizes our current understanding and importance of remodeler and chromatin proteins in cancer biology and also highlights the paradoxical role of proteins with or without dual‐regulator functions. It is our hope that an in‐depth understanding of these events is likely to provide a next set of opportunities for novel strategies for targeted cancer therapeutics

The MORC family: New epigenetic regulators of transcription and DNA damage response

Microrchidia (MORC) is a highly conserved nuclear protein superfamily with widespread domain architectures that intimately link MORCs with signaling-dependent chromatin remodeling and epigenetic regulation. Accumulating structural and biochemical evidence has shed new light on the mechanistic action and emerging role of MORCs as epigenetic regulators in diverse nuclear processes. In this Point of View, we focus on discussing recent advances in our understanding of the unique domain architectures of MORC family of chromatin remodelers and their potential contribution to epigenetic control of DNA template-dependent processes such as transcription and DNA damage response. Given that the deregulation of MORCs has been linked with human cancer and other diseases, further efforts to uncover the structure and function of MORCs may ultimately lead to the development of new approaches to intersect with the functionality of MORC family of chromatin remodeling proteins to correct associated pathogenesis