Paz P Polak

Differential causative effects of germline pathogenic variants in MUTYH and PALB2 in a patient with colorectal polyposis and breast cancer

The paper investigates the differential contributions of MUTYH and PALB2 germline variants to colorectal polyposis and breast cancer using mutational signatures in a single patient.

A comprehensive genomic framework for identifying genes predisposing to homologous recombination repair deficient breast cancer

The paper develops a genomic framework to identify genes predisposing to homologous recombination repair deficient breast cancer by integrating mutational signatures, exome data, and clinical-genomic analysis.

Learning the cellular origins of cancer using single-cell chromatin landscapes

This study uses single-cell chromatin accessibility data and machine learning to predict cancer cell origins, revealing new insights into tumor development and challenging existing views on cancer origins.

COOBoostR: an extreme gradient boosting-based tool for robust tissue or cell-of-origin prediction of tumors

COOBoostR uses extreme gradient boosting to predict tumor tissue or cell-of-origin using chromatin marks and mutation density data, outperforming random forest methods in speed and accuracy.

Whole Exome Sequencing of Nigerian Prostate Tumors from the Prostate Cancer Transatlantic Consortium (CaPTC) Reveals DNA Repair Genes Associated with African Ancestry

This study analyzes whole-exome sequencing data from Nigerian prostate cancer tumors to identify germline and somatic variants associated with African ancestry and DNA repair gene mutations.

Genome-wide mutational signatures of immunological diversification in normal lymphocytes

The paper analyzes the mutational landscape of normal lymphocytes, revealing off-target effects of programmed genome engineering and the impact of differentiation and microenvironment exposure.

Somatic mutation landscape reveals differential variability of cell-of-origin for primary liver cancer

The paper uses whole-genome sequencing to predict cell-of-origin for primary liver cancers, finding heterogeneity in origin predictions across cancer types.

A comprehensive analysis of RNA sequences reveals macroscopic somatic clonal expansion across normal tissues

This study analyzes RNA-seq data from 6,700 normal tissues to identify somatic mutations and their association with age and tissue proliferation, finding tissue-specific cancer mutation hotspots.

Tumor mutational landscape is a record of the pre-malignant state

The paper predicts cancer cell-of-origin from DNA sequences by matching mutational landscapes to chromatin modification patterns in normal tissues.