Biology subjects

Sim, N.

Publications and source records attributed to Sim, N..

3 recordsLinked to original sources

bioRxiv2024

TWEAK/Fn14 signalling driven super-enhancer reprogramming promotes pro-metastatic metabolic rewiring in Triple-Negative Breast Cancer

Triple Negative Breast Cancer (TNBC) is the most aggressive breast cancer subtype suffering from limited targeted treatment options. Following recent reports correlating Fn14 receptor overexpression in ER-negative breast cancers with metastatic events, we show that Fn14 is specifically overexpressed in TNBC patients and associated with poor survival. We demonstrate that constitutive Fn14 signalling rewires the transcriptomic and epigenomic landscape of TNBC, leading to enhanced tumour growth and metastasis. We further illustrate that such mechanisms activate TNBC-specific super enhancers (SE) to drive the transcriptional activation of cancer dependency genes via chromatin looping. In particular, we uncover the SE-driven upregulation of NAMPT, which promotes NAD+ and ATP metabolic reprogramming critical for filopodia formation and metastasis. Collectively, our study details the complex mechanistic link between TWEAK/Fn14 signalling and TNBC metastasis, which reveals several vulnerabilities which could be pursued for the targeted treatment of TNBC patients.

cancer biology↗

bioRxiv2023

Quantification of circulating tumor DNA using deep learning

Quantification of circulating tumor DNA (ctDNA) levels in blood enables non-invasive surveillance of cancer progression. Fragle is an ultra-fast deep learning-based method for ctDNA quantification directly from cell-free DNA fragment length profiles. We developed Fragle using low-pass whole genome sequence (lpWGS) data from multiple cancer types and healthy control cohorts, demonstrating high accuracy, and improved lower limit of detection in independent cohorts as compared to existing tumor-naive methods. Uniquely, Fragle is also compatible with targeted sequencing data, exhibiting high accuracy across both research and commercial targeted gene panels. We used this method to study longitudinal plasma samples from colorectal cancer patients, identifying strong concordance of ctDNA dynamics and treatment response. Furthermore, prediction of minimal residual disease in resected lung cancer patients demonstrated significant risk stratification beyond a tumor-naive gene panel. Overall, Fragle is a versatile, fast, and accurate method for ctDNA quantification with potential for broad clinical utility.

bioinformatics↗

bioRxiv2023

NF-κB/p52 augments ETS1 binding genome-wide to promote glioma progression

Gliomas are among the most invasive and chemo-resistant cancers, making them challenging to treat. Chronic inflammation is one of the key drivers of glioma progression as it promotes the aberrant activation of inflammatory pathways such as NF-{kappa}B signalling which drives cancer cell invasion, angiogenesis and tissue remodelling. NF-{kappa}B factors typically dimerize with its own family members, but emerging evidence of their promiscuous interactions with other oncogenic factors have been reported to activate the transcription of new target genes and function. Here, we show that non-canonical NF-{kappa}B activation directly regulates p52 at the ETS1 promoter to activate its expression. This in turn impacts the genomic and transcriptional landscape of ETS1 in a glioma-specific manner. We further show that enhanced non-canonical NF-{kappa}B signalling promotes the co-localization of p52 and ETS1, resulting in the transcriptional activation of non-{kappa}B and/or non-ETS glioma-promoting genes. We conclude that p52-induced ETS1 overexpression in glioma cells remodels the genome-wide regulatory network of p52 and ETS1 to transcriptionally drive cancer progression.

cancer biology↗