Cancer Genomics and Diagnostics

SUITOR: selecting the number of mutational signatures through cross-validation

SUITOR selects the optimal number of mutational signatures using cross-validation, improving accuracy over existing methods in cancer genomics.

Mutated Tumor Suppressors Follow Oncogenes Profile by the Gene Hypermethylation of Partners in the Protein Interaction Networks

The paper classifies tumor suppressors and oncogenes using network-based analysis and a novel preferential attachment score, showing mutated tumor suppressors integrate hyper-methylated partners like oncogenes.

Proof-of-concept pilot study on comprehensive spatiotemporal intra-patient heterogeneity for colorectal cancer with liver metastasis

This study evaluates intra-patient heterogeneity in colorectal cancer with liver metastasis using multi-regional tumor and liquid biopsies to identify actionable mutations and spatiotemporal tumor evolution.

SWAN Identification of Common Aneuploidy-Based Oncogenic Drivers

The paper introduces SWAN, a tool to identify oncogenic drivers in solid tumors by analyzing copy-number alterations, RNA expression, and mutations through pathway-network analysis.

Distinct and common features of numerical and structural chromosomal instability across different cancer types

This study analyzes chromosomal instability in 33 cancer types, finding distinct associations between whole chromosome instability (W-CIN) and whole genome doubling, and structural chromosomal instability (S-CIN) and homologous recombination deficiency, with implications for drug resistance and prognosis.

Resolving clonal substructure from single cell genomic data using CopyKit

CopyKit is a computational tool that resolves clonal substructure and reconstructs genetic lineages in tumors using single cell copy number data.

Reconstructing complex cancer evolutionary histories from multiple bulk DNA samples using Pairtree

Pairtree reconstructs clone trees from multiple bulk DNA samples to infer cancer evolutionary histories with higher accuracy and scalability.

SomaticSiMu: a mutational signature simulator

SomaticSiMu simulates mutational signatures in genomic sequences and evaluates its reliability using machine learning and mutational signature extraction.

Deciphering of Somatic Mutational Signatures of Cancer

This paper introduces a computational framework, GSGP, to decipher somatic mutational signatures and identifies novel aetiologies, including an RNA-derived signature in colorectal cancer.

A clinically annotated post-mortem approach to study multi-organ somatic mutational clonality in histologically healthy tissues.

The paper uses post-mortem tissues to study mutational clonality in healthy tissues, finding smoking-induced clonal changes in oral epithelia and confirming NOTCH1/2-, TP53-, and FAT1-driven clones.

Read depth correction for somatic mutations

The paper estimates the true mutation VAF distributions from low-depth sequencing by comparing with high-depth data, finding TCGA MC3 underreports mutations by 17%.

MutationalPatterns: The one stop shop for the analysis of mutational processes

The paper introduces an updated R/Bioconductor package for analyzing mutational patterns, demonstrating its ability to detect mutational signatures and their biological implications using simulated and real data.

Somatic mutational profiles and germline polygenic risk scores in human cancer

This study examines associations between somatic mutational profiles and germline polygenic risk scores in 12 cancer types, finding 17 significant links after correction.

DBFE: Distribution-based feature extraction from copy number and structural variants in whole-genome data

DBFE extracts features from genomic variants to improve classifier learning in cancer genomics, identifying biomarkers linked to cancer subtypes and treatment response.

A Platform for Oncogenomic Reporting and Interpretation

PORI is an open-source platform for interpreting somatic variants in cancer, demonstrating that 88.2% of TCGA tumors have at least one potentially targetable alteration.

MetaMutationalSigs: Comparison of mutational signature refitting results made easy

MetaMutationalSigs aggregates and compares mutational signature refitting results from different tools to facilitate comparison across cancer types.

The effect of pre-analytical and physiological variables on cell-free DNA fragmentation.

This study examines how pre-analytical and physiological factors affect cfDNA fragmentation patterns and fragment-end sequences using whole genome sequencing.

Refined characterization of circulating tumor DNA through biological feature integration

This study identifies and integrates three genome-wide features of cfDNA fragmentation to enhance ctDNA detection in ovarian cancer patients.

Establishment of reference standards for multifaceted mosaic variant analysis

This paper establishes reference standards for mosaic variant analysis using a large set of simulated variants to improve detection accuracy and algorithm development.

SCONCE: A method for profiling Copy Number Alterations in Cancer Evolution using Single Cell Whole Genome Sequencing

SCONCE accurately calls copy number alterations in cancer using single cell whole genome sequencing by incorporating tumor evolutionary history and technical noise correction.

FiMO: Inferring the Temporal Order of Mutations on Clonal Phylogeny under Finite-sites Models

FiMO infers the temporal order of somatic mutations in cancer using a Bayesian framework, outperforming existing methods on synthetic and real datasets.

MutSigCVsyn: Identification of Thirty Synonymous Cancer Drivers

The paper introduces MutSigCVsyn, an algorithm to identify synonymous cancer drivers by accounting for mutational heterogeneity, and identifies 30 novel synonymous drivers in cancer whole-genome sequences.

The breast pre-cancer atlas illustrates the molecular and micro-environmental diversity of ductal carcinoma in situ

The paper creates a breast pre-cancer atlas by analyzing multiple micro-dissected regions from DCIS cases, revealing molecular and micro-environmental diversity and immune states associated with progression risk.

Comparison of double-stranded and single-stranded cfDNA library construction methods for targeted genome and methylation sequencing

This study compares two cfDNA library construction methods for targeted genome and methylation sequencing, finding dsLib better for mutation detection and ssLib better for methylation analysis.

A framework for mutational signature analysis based on DNA shape parameters

This paper introduces a framework for mutational signature analysis using DNA shape parameters to better understand mutagenesis mechanisms and improve mutation rate baselines.

Transcription Factor-Centric Approach to Identify Non-Recurring Putative Regulatory Drivers in Cancer

The paper identifies non-recurring putative regulatory driver mutations in cancer by analyzing their effects on transcription factor-DNA binding rather than mutation recurrence.

Prediction of high-risk liver cancer patients from their mutation profile: Benchmarking of mutation calling techniques

The paper benchmarks mutation calling techniques for liver cancer prognosis using VCF and MAF files, finding MuTect2's VCF files best predict high-risk patients with high AUROC and HR.

Mutational Analysis and Deep Learning Classification of Uterine and Cervical Cancers

The paper develops a deep learning tool to classify uterine and cervical cancers based on somatic mutations with 94.3% training and 89.2% test accuracy.

Correlation-based and feature-driven mutation signature analyses to identify genetic features associated with DNA mutagenic processes in cancer genomes

Validation of a Pancreatic Cancer Detection Test in New-Onset Diabetes Using Cell-Free DNA 5-Hydroxymethylation Signatures

This paper validates a pancreatic cancer detection test using 5-hydroxymethylation signatures in cell-free DNA from patients with new-onset diabetes, showing high specificity and moderate sensitivity.