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DiLorenzo, S.

Publications and source records attributed to DiLorenzo, S..

2 recordsLinked to original sources

Evolution of ipsilateral breast cancer decoded by proteogenomics

Ipsilateral breast tumor recurrence (IBTR) is a clinically important event, where an isolated in-breast recurrence is a potentially curable event but also associated with an increased risk of distant metastases and breast cancer death. It currently remains unclear if IBTRs are associated with molecular changes that can be explored as a resource for precision medicine strategies targeting locally recurring breast cancer. Here, we employed a recently developed proteogenomics workflow to analyze a cohort of 27 primary breast cancers and their matched IBTRs by whole genome sequencing, RNA sequencing, and mass spectrometry-based proteomics to define proteogenomic features of tumor evolution. Analysis of mutational signatures, copy number changes, and cancer specific mutations revealed a relationship with estrogen and progesterone receptor statuses and increased levels of genetic change. This in turn altered the re-programming of the transcriptome and proteome towards a recurring molecular disease phenotype with high replicating capacity and a higher degree of genomic instability possibly enhanced by high expression of APOBEC3B. In conclusion, this study defines how primary breast tumors differentially evolve into different ipsilateral recurrent malignancies depending on their key biomarker status, suggesting that further enhancing the genomic instability in some tumors could serve as an alternative treatment option.

cancer biology↗

Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants

SummaryWhole-genome sequencing (WGS) is a cornerstone of precision medicine, but portable and reproducible open-source workflows for WGS analyses of germline and somatic variants are lacking. We present Sarek, a modular, comprehensive, and easy-to-install workflow, combining a range of software for the identification and annotation of single-nucleotide variants (SNVs), insertion and deletion variants (indels), structural variants, tumor sample heterogeneity, and karyotyping from germline or paired tumor/normal samples. Sarek is implemented in a bioinformatics workflow language (Nextflow) with Docker and Singularity compatible containers, ensuring easy deployment and full reproducibility at any Linux based compute cluster or cloud computing environment. Sarek supports the human reference genomes GRCh37 and GRCh38, and can readily be used both as a core production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups.\n\nAvailabilitySource code and instructions for local installation are available at GitHub (https://github.com/SciLifeLab/Sarek) under the MIT open-source license, and we invite the research community to contribute additional functionality as a collaborative open-source development project.

bioinformatics↗