Biology subjects

Tabone-Eglinger, S.

Publications and source records attributed to Tabone-Eglinger, S..

4 recordsLinked to original sources

bioRxiv2025

Single- and double-strand circulating DNA fragmentomics for enhanced cancer detection performance

In early detection of cancer, the use of circulating cell-free DNA (cirDNA) obtained from blood samples is notable for its minimally invasive nature. We have developed an algorithm designed to discriminate cancer patients and healthy individuals based on cirDNA fragment end motif analysis assisted by machine learning, using data obtained from shallow whole genome sequencing (a method we call EMA). We applied EMA to cirDNA from the plasma of patients with stage II-III breast cancer, stage I-III non-small cell lung cancer, and metastatic colorectal cancer (mCRC). CirDNA from 158 individuals was prepared following the conventional double-stranded DNA library preparation (DSP). Using 3 bp end motifs, each tumor type was detected with a sensitivity of 0.87-1.00, a specificity of 0.95, and an AUC above 0.96. The three selected cancer types could be differentiated with an accuracy (ACC) above 0.94. Multi-cancer detection by pooling samples from the three cancer types showed ACC, AUC and sensitivity of 0.98, 0.99 and 0.98, respectively. Comparisons with 4 and 2 bp end motifs were conducted, and our main observations were confirmed using an external public dataset (N=366). We also performed a single-stranded DNA library preparation (SSP) using mCRC patients and healthy control cirDNA, which allowed us to make the first ever end motif analysis in the literature which compares the use of DSP and SSP. As compared to EMAD (use of DSP), EMAS (use of SSP) produced a very significant difference in end motif frequency and an improved cancer detection performance (ACC, AUC and sensitivity of 0.97, 1.00 and 0.99, respectively). Furthermore, optimal performance was produced when the full-size range was used for EMAS, whereas when the dataset was restricted to fragments of 115 - 220 bp for EMAD. EMAS strong performance, coupled with its compatibility with cost-effective shallow cirDNA sequencing, positions this methodology as a potentially transformative tool in early cancer screening.

genomics↗

bioRxiv2025

Discovery of Epigenetically Silenced Tumor Suppressor Genes in Aggressive Breast Cancer Through a Computational Approach

Breast cancer is characterized by genetic and epigenetic deregulations, leading to aberrant expression of tissue-specific genes that are normally silent in healthy breast tissue. Our previous work identified the embryonic stem cell-specific gene DNMT3B, a de novo DNA methyltransferase, as aberrantly activated in breast cancer, correlating with aggressive tumour behaviour and high relapse risk, regardless of molecular subtype. Through integrative bioinformatic analyses of DNA methylation and transcriptomic data, we identified 154 genes downregulated via DNMT3B-driven promoter hypermethylation, many of which are associated with high relapse risk. Notably, the tumour suppressor gene GATA3 emerged as a primary target of functional inactivation through either loss-of-function mutations or DNMT3B-controlled hypermethylation, in a mutually exclusive manner. Both mechanisms of GATA3 inactivation were associated with similar molecular signatures linked to tumour progression, increased malignancy, and poorer prognosis. However, distinct differences were observed, with immune- and inflammation-related genes enriched in GATA3 hypermethylation cases but depleted in mutation-driven silencing. Additionally, our analysis uncovered other potential tumour suppressor genes epigenetically repressed in aggressive breast cancers. These findings underscore a broader role of GATA3 inactivation beyond genetic alterations and suggest therapeutic opportunities to target epigenetically silenced tumour suppressors in aggressive breast tumours.

bioinformatics↗

bioRxiv2022

Preclinical evaluation of CDK4 phosphorylation predicts high sensitivity of malignant pleural mesotheliomas to CDK4/6 inhibition

Malignant pleural mesothelioma (MPM) is an aggressive cancer with limited therapeutic options. In this study, we evaluated the impact of CDK4/6 inhibition by palbociclib in a panel of 28 MPM cell lines, including 19 patient-derived cell lines, using a variety of approaches including RNA-sequencing. Palbociclib used alone sufficed to strongly and durably inhibit the proliferation of 23 MPM cell lines, indicating a unique sensitivity of MPM to CDK4/6 inhibition. Importantly, insensitivity to palbociclib was mostly explained by the lack of active T172-phosphorylated CDK4. This was associated with the high p16INK4A (CDKN2A) levels that accompany RB1 defects or inactivation, and also (unexpectedly) cyclin E1 over-expression in the presence of wild-type RB1. Prolonged treatment with palbociclib irreversibly inhibited proliferation despite re-induction of cell cycle genes upon drug washout. A senescence-associated secretory phenotype including various potentially immunogenic components was also irreversibly induced. Phosphorylated CDK4 was detected in 80% of 47 MPM tumors indicating their intrinsic sensitivity to CDK4/6 inhibitors. The absence of this phosphorylation in some highly proliferative MPM tumors was linked to partial deletions of RB1, leading to very high p16 (CDKN2A) expression. Our study strongly supports the clinical evaluation of CDK4/6 inhibitory drugs for MPM treatment, in monotherapy or combination therapy.

cancer biology↗

bioRxiv2021

Disentangling heterogeneity of Malignant Pleural Mesothelioma through deep integrative omics analyses

Malignant Pleural Mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Using the largest series of whole-genome sequencing data integrated with transcriptomic and epigenomic data using multi-omic factor analysis, we demonstrate that MPM heterogeneity arises from four sources of variation: tumor cell morphology, ploidy, adaptive immune response, and CpG island methylator phenotype. Previous genomic studies focused on describing only the tumor cell morphology factor, although we robustly find the three other sources in all publicly available cohorts. We prove how these sources of variation explain the biological functions performed by the cancer cells, and how genomic events shape MPM molecular profiles. We show how these new sources of variation help understand the heterogeneity of the clinical behavior of MPM and drug responses measured in cell lines. These findings unearth the interplay between MPM functional biology and its genomic history, and ultimately, inform classification, prognostication and treatment. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/461908v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@b6c43corg.highwire.dtl.DTLVardef@10d45a9org.highwire.dtl.DTLVardef@58746eorg.highwire.dtl.DTLVardef@143f880_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗