Cancer Genomics and Diagnostics

Pan-cancer in silico analysis of somatic mutations in G-protein coupled receptors: The effect of evolutionary conservation and natural variance

This study analyzes somatic mutations in GPCRs across cancer patients and healthy individuals, identifying conserved mutation hotspots and prioritizing GPCRs for further cancer research.

Mutations in a set of ancient matrisomal glycoprotein genes across neoplasia predispose to disruption of morphogenetic transduction

The paper identifies ancient matrisomal glycoprotein genes frequently mutated across cancers, showing their role in tissue morphogenesis and neoplastic transformation.

Database of recurrent mutations (DORM), a web tool to browse recurrent mutations in cancers

DORM is a database of recurrent mutations in cancers, enabling search by protein, amino acid substitution, and regular expressions.

An Automatized Workflow to Study Mechanistic Indicators for Driver Gene Prediction with Moonlight

The paper introduces Moonlight2, an updated framework that uses mutation-based mechanistic indicators to identify driver genes in cancer, applied to Basal-like breast cancer.

Evaluating the analytical validity of mutation calling pipeline for tumor whole exome sequencing

This study evaluates variant calling pipelines for tumor whole exome sequencing, finding no single combination outperforms all variants and recommending merged and ensemble approaches.

Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of the gene regulatory program in cancers

The paper identifies cis-regulatory mutations in cancer that disrupt gene regulatory programs by affecting both transcriptional and post-transcriptional regulation.

Whole genome error-corrected sequencing for sensitive circulating tumor DNA cancer monitoring

This study applies low-cost whole genome sequencing to detect circulating tumor DNA at high sensitivity in plasma samples, achieving error rates as low as 10^-7 and enabling cancer monitoring without matched tumor sequencing.

Multi-omics alleviates the limitations of panel-sequencing for cancer drug response prediction

This study shows that combining transcriptome data with gene panel features improves drug response prediction in cancer.

MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution

MEDICC2 infers cancer phylogenies from copy-number data, accounting for whole-genome doubling and parallel evolution, and performs well on simulated and real datasets.

FINDEL: A Deep Learning Approach To Efficient Artifact Removal From Cancer Genomes

FINDEL uses deep learning and mutational signatures to automate artifact removal from cancer genome sequencing data, improving variant call quality and reducing manual labor.

From multi-omics data to the cancer druggable genediscovery: a novel machine learning-based approach

This paper introduces DF-CAGE, a machine learning method that identifies cancer-druggable genes using multi-omics data from TCGA, finding 465 potential targets and highlighting the importance of CNAs and mutations.

Mosaic chromosomal alterations in blood across ancestries via whole-genome sequencing

This study uses whole-genome sequencing to analyze mosaic chromosomal alterations across diverse ancestries, finding higher rates in certain populations and associations with germline variants.

Time to first cigarette and its impact on lung tumorigenesis

This study shows that time to first cigarette strongly influences lung tumor mutational burden, signatures, and survival in smokers.

Cellpanelr: identify predictive biomarkers from cell line panel response data

Cellpanelr identifies mutation and expression biomarkers from cell line panel response data using DepMap datasets.

EvAM-Tools: tools for evolutionary accumulation and cancer progression models

EvAM-Tools provides an R package and web app for building and analyzing evolutionary models of cancer progression and event accumulation.

CNA Explorer and anaLyzer (CNAEL): an interactive web application and standard operating procedure enabling efficient clinical review and reporting of complex NGS-derived tumor copy number profiles

CNAEL is a web application and protocol that streamlines clinical analysis and reporting of NGS-derived tumor copy number profiles, reducing curation time significantly.

ROKET: Associating Somatic Mutation with Clinical Outcomes through Kernel Regression and Optimal Transport

ROKET uses kernel regression and optimal transport to associate somatic mutations with clinical outcomes, identifying associations in three cancer types.

Integrated analysis of cell-free DNA for the early detection of cancer in people with Li-Fraumeni Syndrome

This study evaluates an integrated liquid biopsy approach for early cancer detection in Li-Fraumeni syndrome patients, showing improved detection rates compared to individual methods.

Enhanced clinical assessment of hematologic malignancies through routine paired tumor:normal sequencing

This study presents a paired tumor:normal sequencing dataset for hematologic malignancies, showing improved identification of somatic variants and their clinical relevance.

Comparative analysis of capture methods for genomic profiling of circulating tumor cells in colorectal cancer

This study compares genomic profiling of circulating tumor cells (CTCs) using three methods in metastatic colorectal cancer, finding differences in mutational burden and diversity estimates.

Megakaryocyte and erythroblast DNA in plasma and platelets

The paper identifies megakaryocytes and erythroblasts as major contributors to circulating cell-free DNA (cfDNA) and shows their DNA can serve as biomarkers for blood cell production disorders.

CNHplus: the chromosomal copy number heterogeneity which respects biological constraints

CNHplus corrects the CNH method's flaw of negative copy numbers and improves survival stratification in cancer patients using TCGA data.

Multifactorial heterogeneity of the human mutation landscape related to DNA replication dynamics

The paper investigates mutation landscape heterogeneity across individuals and cell types, identifying replication timing biases and mutation load as key factors.

DREAMS: Deep Read-level Error Model for Sequencing data applied to low-frequency variant calling and circulating tumor DNA detection

DREAMS improves variant calling and circulating tumor DNA detection by modeling sequencing errors at the read level using deep learning.

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

SigProfilerExtractor is a tool for de novo mutational signature extraction that outperforms existing methods and identifies four novel signatures, including one linked to tobacco smoking.

Intrinsic base substitution patterns in diverse species reveal links to cancer and metabolism

The paper analyzes base substitution patterns across species and finds they align with cancer mutational signatures, linking metabolism to DNA damage and mutation generation.

The mutational landscape of human somatic and germline cells

This study compares mutational landscapes in somatic and germline cells across 29 anatomical structures, identifying key mutational signatures and their contributions to different cell types.

The mutational signatures of formalin fixation on the human genome

This paper identifies mutational signatures caused by formalin fixation and introduces FFPEsig, a method to correct these artefacts in genome sequencing data.

The cytidine deaminase APOBEC3G drives cancer mutagenesis and clonal evolution in bladder cancer

This study shows that APOBEC3G drives mutagenesis and clonal evolution in bladder cancer, contributing to mutational profiles in multiple cancer types.

Direct capture and sequencing reveal ultra-short single-stranded DNA in biofluids

The paper identifies ultra-short single-stranded DNA (ussDNA) in biofluids, showing its presence across species and potential as a DNA biomarker.