Cancer Genomics and Diagnostics

Mega-frequency mutagenesis: generation of non-random precise mutations with extremely high frequency upon adaptation of cancer cells to drugs and stress

The paper shows that cancer cells generate non-random, high-frequency mutations during drug adaptation, enriched near transcription factor binding sites.

Inference of cancer driver mutations from tumor microenvironmentcomposition: a pan-cancer study with cross-platform external validation

The paper trains machine learning models to predict cancer driver mutations from tumor microenvironment composition across multiple cancers and validates them externally.

Deletions Rate-Limit Breast and Ovarian Cancer Initiation

The paper identifies genomic deletions as the rate-limiting mutational processes in breast and ovarian cancer initiation, requiring 1-3 deletions for tumor development.

Enzyme family-centred approach identifies helicases as recurrent hemizygous tumour suppressor genes

The paper identifies helicases as frequently mutated enzyme families in cancer, showing their role in genomic instability and DNA repair defects, with AQR as a novel hemizygous tumor suppressor.

Sensitive detection of copy number alterations in low-pass liquid biopsy sequencing data

This paper introduces BayesCNA, a Bayesian method for detecting copy number alterations in low-pass liquid biopsy sequencing data, showing improved sensitivity in low-quality cases.

A signature-agnostic test for differences between tumor mutation spectra reveals carcinogen and ancestry effects

The paper introduces AMSD, a signature-agnostic metric to detect differences in mutation spectra between groups, showing its effectiveness in identifying carcinogen and ancestry effects.

Interclonal cooperation and suppression shape early Ras-driven tumour growth

This study identifies cooperative and suppressive interclonal interactions during early Ras-driven tumourigenesis using a Drosophila model, revealing key modifiers like SWI/SNF and cell competition regulators.

Precision single-cell profiling of Circulating Tumour Cells: novel markers and data-driven characterization by CTCeek

The paper identifies novel markers for CTC subtypes and introduces CTCeek, a tool to annotate bona fide CTCs from scRNA-seq data.

Integrated inference of cancer gene expression from cell-free plasma chromatin

APEX infers cancer gene expression from plasma cfChIP-seq data, outperforming existing methods and enabling subtype classification and biomarker identification.

OncoBERT: Context-Aware Modeling of Somatic Mutations for Precision Oncology

OncoBERT models somatic mutations in cancer to identify patient-specific subtypes and improve prediction of treatment response by integrating mutational context with clinical biomarkers.

Systematic functional drug testing in patient-derived models reveals ex vivo sensitivities associated with clinical outcome in rare solid tumors

This study develops an ex vivo drug sensitivity testing platform for rare solid tumors and finds that high in vitro sensitivity correlates with clinical benefit and progression-free survival.

Genomic and Evolutionary Determinants of Two-hit Frequencies in Tumor Suppressor Genes

The paper analyzes two-hit inactivation frequencies in tumor suppressor genes across 9,000 tumors, identifying factors like mutation impact, zygosity, and chromosomal context that influence these frequencies.

A Robust Framework for Predicting Mutation Effects on Transcription Factor Binding: Insights from Mutational Signatures in 560 Breast CancerGenomes

The paper develops a framework to predict mutation effects on transcription factor binding using mutational signatures in breast cancer genomes, revealing subtype-specific rewiring of gene regulatory networks.

SigRescueR: A Pan-System Framework for Noise Correction and Mutational Signature Identification Across Sequencing Platforms

SigRescueR corrects noise and identifies mutational signatures across sequencing platforms, revealing environmental and therapeutic mutagenic patterns in cancer genomes.

Genetic barcoding uncovers the clonal makeup of solid and liquid biopsies

This study uses genetic barcoding to analyze clonal composition in solid and liquid biopsies of breast cancer models, revealing differences in clonal diversity and DNA shedding patterns.

Accurate somatic variant detection from formalin fixed, paraffin embedded tissue (FFPE) derived WES and WGS by DeepOmicsFFPE-PLUS, a sequence context-based transformer

This paper develops DeepOmicsFFPE-PLUS, a transformer-based tool to accurately detect somatic variants from FFPE-derived WES and WGS data, outperforming existing methods and restoring biologically relevant mutational signatures.

Combined inference of known and novel mutational signatures with ReDeNovo

ReDeNovo infers both known and novel mutational signatures from cancer genomes, outperforming existing methods and identifying new signatures in real data.

Mutational signatures in cancer genomes alter protein sequence motifs in cellular signaling networks

The paper identifies mutational signatures in cancer genomes that alter protein sequence motifs in signaling networks, linking mutation etiology to functional consequences.

Sensitive tumor detection, accurate quantification, and cancer subtype classification using low-pass whole methylome sequencing of plasma DNA

This paper introduces METER, a computational tool that enables sensitive tumor detection, accurate quantification, and cancer subtype classification using low-pass whole methylome sequencing of plasma DNA.

Re-evaluating the Need for Double Centrifugation in Plasma Cell-Free DNA Analysis

This study shows that single-spun plasma is sufficient for accurate cfDNA analysis, challenging the need for double centrifugation in liquid biopsy workflows.

Detection and monitoring of translocation renal cell carcinoma via plasma cell-free epigenomic profiling

This paper detects and monitors translocation renal cell carcinoma (tRCC) using plasma cell-free epigenomic profiling, achieving high accuracy in distinguishing tRCC from other cancers and healthy controls.

Toward identification of common DNA repair process in mutational signatures

The paper introduces RePrint, a method to infer shared DNA repair mechanisms between mutational signatures, outperforming existing methods and enabling guilt-by-association predictions.

Molecular determinants of antibody-mediated priming to enhance detection of ctDNA

This paper identifies molecular features of monoclonal antibodies that enhance ctDNA detection by increasing its concentration in blood.

Exploring the Space of Tumor Phylogenies Consistent with Single-Cell Whole-Genome Sequencing Data

SCOPE explores the space of tumor phylogenies consistent with scWGS data, showing multiple phylogenies are possible and highlighting how data quality and evolutionary constraints affect uncertainty.

Genomic evolution of pancreatic cancer at single-cell resolution

This study uses single-nucleus DNA sequencing to analyze pancreatic cancer evolution, revealing patterns of mutation and copy number variation across clinical scenarios.

SigDyn: single-cell mutational signature dynamics

SigDyn analyzes single-cell mutational signature dynamics to uncover tumor evolution and heterogeneity, revealing therapeutic insights in invasive ductal carcinoma and laryngeal squamous cell carcinoma.

Cancer-like fragmentomic characteristics of somatic variants in cell-free DNA

This study identifies cancer-like fragmentomic traits in somatic variants of cfDNA, enabling cancer diagnosis through integrative genomic and fragmentomic analysis using AI models.

A Scalable Framework for Pan-Cancer Tumor Evolution Analysis Enables Transfer of Progression Mechanisms Across Tumor Entities

fastMHN enables pan-cancer tumor evolution analysis by approximating complex progression models, identifying a progression group linked to STK11 mutations across multiple cancer types.

SigFormer: an Attention-Based Framework for Robust Single-Sample Mutational Signature Decomposition

SigFormer improves single-sample mutational signature decomposition by using a transformer framework, outperforming existing methods in high-noise and overcomplete settings.

Unsupervised Identification of Cancer Attractor States through the Lens of Embryonic Origin and Cancer Hallmarks

This paper identifies stable cancer attractor states by integrating embryonic origin with hallmark-related mutations, revealing organ-specific metastatic patterns and prognostic inversions.