Cancer Genomics and Diagnostics

Theoretical estimates on the expected number of mutations for reconstructing clonal lineage trees

The paper estimates the number of mutations needed to reconstruct clonal lineage trees from large datasets, showing that modest mutation counts suffice for accurate reconstruction.

LongPhase-S: purity estimation and variant recalibration with somatic haplotying for long-read sequencing

LongPhase-S improves somatic variant accuracy by jointly estimating tumor purity and recalibrating variants using somatic haplotyping in long-read sequencing.

Pan-cancer analysis reveals mtDNA copy number as a key determinant of mutational load and disease progression in cancer

This study shows that mtDNA copy number increases with mutational load in cancer and influences disease progression and therapy response across multiple cancer types.

Single-cell copy number alteration signature analysis reveals masked patterns and potential biomarkers for cancer

This study analyzes CNA signatures in single-cell and bulk samples of hepatocellular carcinoma, revealing masked patterns and potential biomarkers for prognosis and treatment.

Frequent Whole-Genome Duplication Events Drive the Genomic Evolution of Triple-Negative Breast Cancer During Neoadjuvant Chemotherapy

This study tracks genomic changes in TNBC during neoadjuvant chemotherapy, finding that whole-genome duplication events drive structural alterations and contribute to tumor evolution and response to treatment.

Hybrid Ornstein-Uhlenbeck-Branching Modeling of Pediatric Leukemia Evolution: A Computational Extension and Cohort-Level Application

This paper develops a computational model to simulate clonal evolution in pediatric leukemia using a hybrid OU-Branching framework and applies it to clinical data to study relapse patterns and therapeutic response.

Comprehensive and accelerated mapping of driver mutations through single-nucleotide random mutagenesis of target genes

This study introduces a genome editing method to rapidly generate and test driver mutations in target genes, identifying novel resistance mutations in lung cancer.

Agent-based simulations of lung tumour evolution suggest that ongoing cell competition drives realistic clonal expansions

This paper uses agent-based simulations to test models of lung tumour growth, finding that stringent cell competition after tumour size stabilization produces realistic clonal expansions and better estimates of driver mutation effects.

A comprehensive view of somatic mosaicism by single-cell DNA analysis

The paper uses single-cell DNA sequencing to analyze somatic mosaicism in postmortem lung and colon tissues, revealing mutation heterogeneity, chromosomal abnormalities, and cellular ancestry.

Computationally reconstructing the evolution of cancer progression risk

This study develops a computational method to infer cancer progression risk by analyzing tumor phylogenetics and mutation data from TCGA cohorts, revealing general mechanisms and cohort-specific variability.

cfOncoXpress: Tumor gene expression prediction from cell-free DNA whole-genome sequences

cfOncoXpress predicts tumor gene expression from cell-free DNA whole-genome sequences using fragmentation patterns and copy number aberrations, outperforming existing methods in prostate and breast cancers.

ClairS-TO: A deep-learning method for long-read tumor-only somatic small variant calling

ClairS-TO is a deep-learning method for long-read tumor-only somatic variant calling that outperforms existing tools and works with both long-read and short-read data.

Phylogenetic analysis of paired breast carcinomas identifies genetic events associated with clonal recurrence and invasive progression

The paper analyzes paired breast carcinomas to determine if recurrences are clonal or new tumors, finding 7% are non-clonal by whole exome sequencing.

Somatic copy number mutations contribute to fitness in transplantation models of spontaneous human breast cancer metastasis

This study shows that somatic copy number mutations (CNA) influence metastatic fitness in breast cancer by mediating transcriptional changes and affecting clone survival in different sites.

Comprehensive Atlas of Cancer-Type-Specific Molecular Features from Comparative Analysis of TCGA Data

The paper creates a comprehensive atlas of cancer-type-specific molecular features by analyzing TCGA data across 39 cancer types and 6 molecular platforms.

A blueprint for mutation-defined hallmark vulnerabilities across human cancers

This paper maps mutation-defined cancer vulnerabilities across 22 cohorts, identifying OXPHOS addiction in CDKN2A-loss LUSC and highlighting drug repurposing opportunities using a machine learning framework.

Deep multiplexed 50-marker imaging of circulating tumor cells expands actionable biomarker profiling for precision oncology

This paper introduces a deep multiplexed imaging technique to profile up to 50 markers per circulating tumor cell, enhancing biomarker analysis for precision oncology.

Integrating gene expression, mutation and copy number data to identify driver genes of recurrent chromosome-arm losses

The paper identifies 311 candidate driver genes for recurrent chromosome-arm losses in 20 cancer types using integrated gene expression, mutation, and copy number data from ~7,500 tumors.

Knowledge-informed multimodal cfDNA analysis improves sensitivity and generalization in cancer detection

Fate-AI improves cancer detection sensitivity and generalization by integrating fragmentomic and methylation features from cfDNA sequencing.

Systematic artifacts from Illumina two-color chemistry confound variant identification and actionability in clinical panels

This study identifies systematic T>G sequencing artifacts in Illumina two-color chemistry that can create false pathogenic variants and inflate tumor mutational burden in clinical panels.

A Critical Re-evaluation of the Somatic Mutation Theory (SMT)Conceptual and Quantitative Limits of the Cell-Centric Paradigm

This paper re-evaluates the Somatic Mutation Theory (SMT) and shows that multi-hit carcinogenesis is implausible within realistic timescales, suggesting a shift to communication breakdown as the root cause of cancer.

Timing the onset of homologous recombination deficiency before breast cancer diagnosis

The paper estimates the timing of homologous recombination deficiency (HRD) onset in breast cancers using HRDTimer, finding HRD occurs years before diagnosis in different subtypes.

DeepSomatic: Accurate somatic small variant discovery for multiple sequencing technologies

DeepSomatic is a deep learning method for detecting somatic variants from short-read and long-read sequencing data, outperforming existing callers, especially for indels.

cfMethDB: a comprehensive cfDNA methylation data resource for cancer biomarkers

cfMethDB compiles 4828 cfDNA methylation datasets, identifies 1,048,770 DMCs as potential cancer biomarkers, and provides tools for biomarker discovery and analysis.

Large-scale single-cell phylogenetic mapping of clonal evolution in the human aging esophagus

This paper develops SMART-PTA for single-cell whole-genome and transcriptome sequencing, revealing clonal evolution in aged human esophageal tissue over 70 years.

A telomere-to-telomere map of somatic mutation burden and functional impact in cancer

The paper maps somatic mutation burden and functional impact across the cancer genome using telomere-to-telomere sequencing, revealing novel mutation hotspots and regulatory rewiring mechanisms.

Probability Distribution for Rare Neutral Mutations in Cancers and Application to Dynamic Precision Medicine of Cancer

The paper develops a probability distribution for rare subclones in cancer and applies it to simulate dynamic precision medicine to improve treatment outcomes despite sequencing limitations.

Comprehensive benchmarking of somatic mutation detection by the SMaHT Network

The paper benchmarks somatic mutation detection methods using short-read and long-read sequencing across multiple samples, showing improved accuracy with donor-specific assemblies and highlighting the complementary value of bulk, single-cell, and duplex analyses.

Moving Beyond Binary Biomarkers: Machine Learning Model Resolves Concurrent and Molecularly Heterogeneous Mismatch Repair and Homologous Recombination Deficiencies in Prostate Cancer

This paper develops a machine learning model to identify molecularly distinct DDR subgroups in prostate cancer, revealing concurrent repair deficiencies and improving therapeutic stratification.

Statistical and Evolutionary Analysis of Sequenced DNA from Breast Cancer FFPE Specimens

The paper analyzes FFPE breast cancer specimens to assess recoverable molecular evolution features using computational methods despite sequencing artifacts.