Cancer Genomics and Diagnostics

Segregating DNA lesions point to high selective advantage of tumor initiating cells

The paper uses DNA lesion segregation to estimate tumor initiating events and shows early cancer drivers have a fitness advantage exceeding 30%.

AI-Driven Variant Annotation for Precision Oncology in Breast Cancer

This paper uses AI/ML to annotate genomic variants in breast cancer, identifying new actionable mutations and functional consequences beyond known drivers.

Tracking clonal evolution of drug resistance in ovarian cancer patients by exploiting structural variants in cfDNA

This study tracks clonal evolution of drug resistance in ovarian cancer using structural variants in cfDNA, finding polyclonal resistance with dominant high-fitness clones and genomic features linked to drug resistance.

Analytical Validation of a Pan-Cancer NGS Assay for In-House Liquid Biopsy Testing: An International Multicenter Study

This study validates a pan-cancer NGS assay for liquid biopsy testing across multiple centers, showing high sensitivity and specificity for detecting genomic alterations in cfDNA.

Somatic evolution of prostate cancer: mutation, selection, and epistasis across disease stages

This study quantifies mutation rates, selection coefficients, and epistatic interactions across prostate cancer stages, revealing dynamic selective pressures and therapeutic implications.

Mutation bias in driver genes reveals the distribution of effects of oncogenic mutations

The paper quantifies mutation bias in driver genes to estimate the number of driver mutations and their effect distribution across oncogenes and tumor-suppressor genes.

RCANE: A Deep Learning Algorithm for Whole-genome Pan-Cancer Somatic Copy Number Aberration Prediction using RNA-seq Data

RCANE predicts whole-genome somatic copy number aberrations across cancers using RNA-seq data, outperforming existing methods on TCGA and DepMap datasets.

CLONAL SELECTION SUPPORTED BY SINGLE CELL DNA SEQUENCING REVEALS HORMONAL ADAPTATION AND RESISTANCE IN LOCALLY ADVANCED BREAST CANCER DURING NEOADJUVANT AROMATASE INHIBITION

This study uses whole-exome sequencing and single-cell DNA sequencing to analyze subclonal evolution in breast cancer during aromatase inhibitor treatment, identifying resistance mechanisms and actionable targets.

The tissue specificity of cancer genes

This study identifies tissue-specific cancer genes using a statistical framework applied to a large dataset, revealing that tissue specificity is common in cancer genes.

Trans-Driver: a deep learning approach for cancer driver gene discovery with multi-omics data

Trans-Driver identifies 185 candidate cancer driver genes from 20,000 protein-coding genes using multi-omics data integration, outperforming single-omics methods.

Discovery of circulating cell-free DNA 5hmC biomarkers for peritoneal metastasis in colorectal and appendiceal cancer

This study uses 5hmC-Seal technology to detect 5hmC signatures in cfDNA from plasma, identifying peritoneal metastases in CRC and AA with high sensitivity but moderate specificity.

RIPPLET: Mutation-Only Gene and Pathway Profiling for Precision Oncology

RIPPLET converts somatic DNA variants into gene-impact scores and pathway-perturbation profiles, outperforming multi-omic tools in identifying cancer drivers and predicting drug response without RNA data.

Single- and double-strand circulating DNA fragmentomics for enhanced cancer detection performance

This paper develops a method using circulating DNA fragment end motifs and machine learning to detect cancer with high accuracy across multiple cancer types.

Discovery and performance of DNA methylation panels for cancer detection and classification in blood

This paper identifies DNA methylation biomarker panels for multi-cancer detection and tissue-of-origin classification using blood samples, achieving high sensitivity and low false positive rates.

Longitudinal Phylogenetic Inference of Copy Number Alterations and Single Nucleotide Variants from Single-Cell Sequencing

LoPhy reconstructs the joint evolution of SNVs and CNAs from longitudinal single-cell data, revealing their roles in AML progression and therapy resistance.

Transcriptomic Mutational Profiling of Gastric Adenocarcinoma in Northern Brazil

This study analyzes mutational profiles in gastric adenocarcinoma samples from northern Brazil using NGS, identifying key mutations and patterns associated with replication damage and DNA repair.

A Universal Duplex Sequencing Approach for Accurate Detection of Somatic Mutations

This paper introduces UDSeq, a duplex sequencing protocol for accurate somatic mutation detection with low DNA input and high coverage, achieving a low error rate and enabling cross-species profiling.

Extrachromosomal DNA driven oncogene spatial heterogeneity and evolution in glioblastoma

This study investigates the spatial-temporal evolution of extrachromosomal DNA (ecDNA) in glioblastoma, showing that EGFR ecDNA drives tumor evolution and identifies a potential therapeutic window for early intervention.

Translating clinical gene sequencing into a foundational representation of tumor subtype

This paper introduces MutationProjector, an AI model that converts tumor mutation profiles into cancer subtype representations, achieving strong performance in predicting treatment responses and classifying metastasis.

Development of circulating cell-free DNA reduced representation bisulfite sequencing for clinical methylomics diagnostics

The paper introduces cf-RRBS, a method for methylation profiling of fragmented plasma DNA, enabling cost-effective and accurate non-invasive lung cancer subtyping.

UALCAN Mobile, an app for cancer proteogenomic data analysis.

UALCAN Mobile provides cancer proteogenomic data analysis through an app, enabling users to explore gene, protein, and epigenetic changes across multiple cancer types and stratifications.

Comprehensive analysis of microbial content in whole-genome sequencing samples from The Cancer Genome Atlas project

The paper analyzes microbial content in 5,734 whole-genome sequencing samples from TCGA to provide a comprehensive reference dataset for future cancer microbiome studies.

Cancer subclone detection based on DNA copy number in single cell and spatial omic sequencing data

Clonalscope detects cancer subclones using DNA copy number data from single-cell and spatial omic sequencing, identifying spatially segregated subclones and validating them with matched scDNA-seq data.

Inferring Phylogenetic Trees of Cancer Evolution from Longitudinal Single-Cell Copy Number Profiles

This paper introduces NestedBD-Long, a method for inferring cancer evolution phylogenetic trees from longitudinal single-cell copy number data, showing improved accuracy with more temporal samples.

MRDadaptis: Self-Adaptive Parameter Configuration Enhances Minimal Residual Disease Detection in Heterogeneous ctDNA Samples

MRDadaptis improves MRD detection in heterogeneous ctDNA samples by automatically adapting parameters using Bayesian optimization and meta-learning, enhancing detection stability and performance.

Long-read sequencing of single cell-derived melanoma subclones reveals divergent and parallel genomic and epigenomic evolutionary trajectories

The paper uses long-read sequencing to analyze genomic and epigenomic changes in melanoma subclones, revealing parallel evolutionary paths and lineage-specific methylation patterns.

Recovery of human upper airway epithelium after smoking cessation is driven by a slow-cycling stem cell population and immune surveillance

Seq2Karyotype (S2K): A Method for in-silico Karyotyping Using Single-Sample Whole-Genome Sequencing Data

Seq2Karyotype (S2K) enables in-silico karyotyping from whole-genome sequencing data, revealing intratumoral heterogeneity and evolutionary trajectories in cancer samples.

Urine cf-Nucleosomes: A Non-invasive Window into Human Physiology and Disease

The paper demonstrates that urine contains cell-free nucleosomes that retain histone modifications and can reflect tissue-specific and pathological changes.

In silico generation of synthetic cancer genomes using generative AI

The paper introduces OncoGAN, a generative AI tool that creates synthetic cancer genomes to address the lack of gold-standard datasets for benchmarking cancer genome analysis tools.