Biology subjects

Chelala, C.

Publications and source records attributed to Chelala, C..

5 recordsLinked to original sources

bioRxiv2026

Systematic benchmarking of low-input whole exome sequencing workflows for longitudinal ctDNA profiling in pancreatic ductal adenocarcinoma

Whole exome sequencing (WES) of circulating tumour DNA (ctDNA) enables longitudinal monitoring of tumour dynamics, evolution and treatment response but remains technically challenging in low-input, low-shedding settings such as pancreatic ductal adenocarcinoma (PDAC). Here, we systematically compared three commercially available low-input WES workflows incorporating Agilent (V6, V8) and Qiagen exome capture designs using ultra-low input cfDNAs extracted from multiple matched longitudinal plasma samples from PDAC patients. Using predefined performance metrics including coverage, duplication rate and variant detection and additional metrics relevant for clinical genomic profiling in patient care, we show that all three workflows produced high-quality sequencing data, even from very low input cfDNA. Within the conditions tested here, the Agilent V8 workflow provided the most favourable balance of coverage uniformity, sequencing efficiency and hotspot coverage for low input, low tumour fraction cfDNA WES. These findings demonstrate that workflow design, including capture footprint, substantially influences ctDNA WES performance in low-input clinical contexts. These findings are particularly relevant in early stage and/or minimal residual disease settings, where tumour fractions are low and recovery of genomic information from limited-input samples is critical.

genomics↗

bioRxiv2025

Coenzyme A homeostasis regulates hypoxic signalling via UBFD1in triple-negative breast cancer

Hypoxia-inducible factors (HIFs) orchestrate cellular responses to oxygen deprivation and are frequently activated in triple-negative breast cancer (TNBC), driving metastasis and poor prognosis1,2. However, the full mechanisms of how HIFs are activated are not completely understood. It has been long noted that certain tumours have decreased levels of coenzyme A compared to surrounding tissues3,4, but the functional consequences of this remain unknown. Here, we identify Coenzyme A Synthase (CoAsy) as a novel regulator of HIF signalling. We demonstrate that CoAsy loss stabilises HIF-1 and HIF-2 independently of the canonical oxygen sensing pathway. Proximity-labelling proteomics revealed that CoAsy deficiency disrupts the association between HIF-1 and the proteasome through UBFD1, a novel CoA-binding protein that scaffolds HIF for degradation. UBFD1s CoA-dependent interaction with HIF- is mediated by its PH domain, which undergoes CoAlation, an understudied post-translational modification. COASY loss of heterozygosity occurs in [~]1/3 of breast cancer patients and correlates with increased HIF activity, lack of hormone receptor expression and poor patient outcome. In vivo studies confirm that restoring CoAsy expression in tumours suppresses metastasis to the lung. These findings uncover a critical metabolic checkpoint regulating hypoxic signalling and identify CoAsy as a potential biomarker and therapeutic target in aggressive breast cancers.

molecular biology↗

bioRxiv2020

SNPnexus COVID: Facilitating the analysis of COVID-19 host genetics

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has demanded an unprecedented scientific response, with researchers collaborating on a global scale to better understand how host genetics can influence susceptibility to coronavirus infection and the severity of COVID-19 symptoms. The number of projects directed towards sequencing patients genomes has increased rapidly during this time with the rate of data generation outpacing the resources available for analysis and biological interpretation of these datasets. SNPnexus COVID is a cutting-edge web-based analytical platform that allows researchers to analyse and interpret the functional implications of genetic variants in COVID-19 patient genomes and to prioritise those that demonstrate clinical utility for the prevention, management and/or treatment of COVID-19. Our resource links to diverse multifactorial datasets and information resources that would require substantial time and computational power to otherwise mine independently. This streamlines biological data interpretation and allows researchers to better understand the multidimensional characteristics of their data. Importantly, SNPnexus COVID is powered by the SNPnexus software and follows its intuitive infrastructure, which precludes the need for programmatic experience in its users. SNPnexus COVID is freely available at https://www.snp-nexus.org/v4/covid/

genomics↗

bioRxiv2019

The breast cancer oncogene IKKε coordinates mitochondrial function and serine metabolism

The I{kappa}B kinase {varepsilon} (IKK{varepsilon}) is a key molecule at the crossroads of inflammation and cancer. Known for its role as an activator of NF{kappa}B and IRF3 signalling leading to cytokine secretion, the kinase is also a breast cancer oncogene, overexpressed in a variety of tumours. However, to what extent IKK{varepsilon} remodels cellular metabolism is currently unknown. Here we used a combination of metabolomics and phosphoproteomics to show that IKK{varepsilon} orchestrates a complex metabolic reprogramming that affects mitochondrial metabolism and serine biosynthesis. Acting independently of its canonical signalling role, IKK{varepsilon} upregulates the serine biosynthesis pathway (SBP) mainly by limiting glucose and pyruvate derived anaplerosis of the TCA cycle. In turn, this elicits activation of the transcription factor ATF4 and upregulation of the SBP genes. Importantly, pharmacological inhibition of the IKK{varepsilon}-induced metabolic phenotype reduces proliferation of breast cancer cells. Finally, we show that in a set of basal ER negative and highly proliferative human breast cancer tumours, IKK{varepsilon} and PSAT1 expression levels are positively correlated corroborating the link between IKK{varepsilon} and the SBP in the clinical context.

cancer biology↗

bioRxiv2017

IW-Scoring: an Integrative Weighted Scoring framework for annotating and prioritizing genetic variations in the noncoding genome

IW-Scoring represents a new Integrative Weighted Scoring model to annotate and prioritise functionally relevant noncoding variations. The pipeline integrates 11 popular algorithms and outperforms individual methods in three independent data sets, including variants in ClinVar database and GWAS studies, and cancer mutations. Using IW-Scoring, we located 11 recurrently mutated noncoding regions enriched for at least three functional mutations in 14 follicular lymphoma genomes, and validated 9 clusters (82%) in the International Cancer Genome Consortium cohort (n=36), including promoter and enhancer regions of PAX5. IW-Scoring offers greater versatility to identify trait and disease associated noncoding variants.

bioinformatics↗