Cancer Genomics and Diagnostics

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.

Copy number aberrations drive kinase re-wiring leading to genetic vulnerabilities in cancer

The paper identifies copy number aberrations that alter kinase signaling and highlights potential therapeutic targets by integrating genomic and proteomic data across cancer samples.

SMuRF: Portable and accurate ensemble-based somatic variant calling

SMuRF improves somatic variant calling accuracy by combining multiple callers using Random Forest, working across cancer types and data types.

Genetic predisposition to mosaic Y chromosome loss in blood is associated with genomic instability in other tissues and susceptibility to non-haematological cancers

The paper identifies genetic determinants of mosaic Y chromosome loss in blood and links it to genomic instability and non-haematological cancer risk.

Whole Genome Doubling mitigates Muller’s Ratchet in Cancer Evolution

The paper investigates how whole genome doubling (WGD) in cancer may mitigate Muller’s Ratchet by reducing negative selection on mutations in essential genes after duplication.

Next Generation-Targeted Amplicon Sequencing (NG-TAS): An optimised protocol and computational pipeline for cost-effective profiling of circulating tumour DNA

NG-TAS is a cost-effective method for profiling ctDNA mutations in cancer patients, showing consistent detection of mutations at >1% allele fraction.

Tumor subclonal progression model for cancer hallmark acquisition

This study develops a method to model tumor subclonal progression by linking genetic aberrations to cancer hallmark acquisition using multiregional sequencing data.

Decomposing the subclonal structure of tumors with two-way mixture models on copy number aberrations

This paper introduces CloneDeMix, a two-way mixture model for analyzing copy number aberrations in tumors, revealing subclonal structure and mutation order with high accuracy.

Machine learning models to predict in vivo drug response via optimal dimensionality reduction of tumour molecular profiles

The paper uses machine learning to predict drug response in tumour models by reducing molecular profile dimensionality, finding multi-gene predictors outperform single-gene markers in several cancer types.

Ccube: A fast and robust method for estimating cancer cell fractions

Ccube estimates cancer cell fractions and subclonal composition from whole-genome sequencing data using a probabilistic framework and variational inference.

Comparative Proteogenomic Analysis of Right-sided Colon Cancer, Left-sided Colon Cancer and Rectal Cancers Reveal Distinct Mutational Profiles.

This study compares proteogenomic profiles of right-sided colon cancer, left-sided colon cancer, and rectal cancers, revealing distinct mutational and protein interaction patterns.

SCIΦ: Single-cell mutation identification via phylogenetic inference

SCIΦ identifies mutations in single-cell tumor data by inferring phylogenetic relationships, outperforming existing methods on simulated and real datasets.

SMuRF: a novel tool to identify genomic regions enriched for somatic point mutations

SMuRF identifies genomic regions enriched for somatic point mutations in user-defined intervals using SNVs from liver cancer data.

Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease

The paper develops a method to determine the tissue origins of circulating cell-free DNA using a methylation atlas and validates it in healthy and disease states.

Cell-free DNA profiling of metastatic prostate cancer reveals microsatellite instability, structural rearrangements and clonal hematopoiesis

This study profiles cell-free DNA in metastatic prostate cancer patients, identifying genomic alterations, microsatellite instability, and clonal hematopoiesis as potential biomarkers.

Early divergence of mutational mechanisms drives genetic heterogeneity of fetal tissues

The paper quantifies somatic mutation accumulation in fetal liver and intestinal stem cells, finding higher mutation rates and distinct mutation spectra in fetal liver compared to fetal intestine and adult tissues.

hsegHMM: Hidden Markov Model-based Allele-specific Copy Number Alteration Analysis Accounting for Hypersegmentation

hsegHMM is a hidden Markov model for allele-specific copy number analysis that addresses hypersegmentation, outperforming FACETS in uneven coverage scenarios.

Cancer3D 2.0: interactive analysis of 3D patterns of cancer mutations in cancer subsets

Cancer3D 2.0 provides an interactive platform to analyze 3D mutation patterns in cancer subsets, enabling identification of novel driver regions in specific patient subgroups.

Combining accurate tumour genome simulation with crowd-sourcing to benchmark somatic structural variant detection

The paper benchmarks somatic structural variant detection methods using synthetic tumors and crowd-sourced submissions, finding that ensembles do not always outperform individual methods.

Reliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity

This study evaluates the reliability of whole-exome sequencing in detecting intratumor genetic heterogeneity, finding that technical noise accounts for a significant proportion of apparent genetic differences.

Reconstructing and characterizing focal amplifications in cancer using AmpliconArchitect

AmpliconArchitect reconstructs focal amplifications in cancer genomes, revealing novel insights into extrachromosomal mechanisms and oncoviral pathogenesis.

TNER: A Novel Background Error Suppression Method for Mutation Detection in Circulating Tumor DNA

TNER improves mutation detection in ctDNA by reducing background errors, outperforming existing methods on simulated and real data.

PANOPLY: Omics-guided drug prioritization method tailored to an individual patient

PANOPLY prioritizes cancer drugs for individual patients using multi-omics data and machine learning, showing effectiveness in a chemotherapy-resistant tumor model.

Process-specific somatic mutation distributions vary with three-dimensional genome structure

The paper examines how somatic mutation distributions vary across chromatin folding domains in cancer genomes, revealing distinct patterns associated with different mutational processes.

Standard operating procedure for somatic variant refinement of tumor sequencing data

This paper establishes a standard operating procedure for manual refinement of somatic variants in tumor sequencing data to improve consistency and reproducibility.

Duplex Proximity Sequencing (Pro-Seq): A method to improve DNA sequencing accuracy without the cost of molecular barcoding redundancy

Pro-Seq improves DNA sequencing accuracy without increasing costs by merging DNA copies into single reads, achieving high sensitivity and specificity in liquid biopsies.

Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires

SCDT: Detecting CNVs of low chimeric ratio in cf-DNA

SCDT detects sub-chromosome CNVs in cf-DNA with high sensitivity and specificity using GC correction and segmentation algorithms.

Specific detection of cell-free DNA derived from intestinal epithelial cells using methylation patterns

The paper identifies methylation patterns specific to intestinal epithelial cells to detect cell-free DNA in plasma, showing increased levels in advanced CRC compared to IBD and PDAC.

Non-canonical secondary structures arising from non-B DNA motifs are determinants of mutagenesis

The paper shows non-B DNA motifs contribute to mutation density in cancer genomes, with secondary structures playing a causal role in mutagenesis.