Ludmil B. Alexandrov

The paper curates 49 experimental single-base substitution signatures from cancer genomes to link mutational processes to DNA damage mechanisms.

The paper evaluates how different model architectures, LD filtering thresholds, and variant prioritization methods affect gene-level eQTL score prediction quality using over 3 million models.

This study identifies the mechanism of SBS17 mutational signature as misincorporation of dUTP during DNA replication and mutagenic bypass of abasic sites, applicable to both spontaneous and chemotherapy-induced mutations in gastrointestinal cancers.

The paper identifies and validates a previously missed mutational signature in microsatellite-stable colorectal cancer, showing it is distinct from known signatures and not caused by canonical DNA repair defects.

This study examines ecDNA in lung cancer, finding it in 18.9% of patients and associating it with worse survival and genomic instability.

The paper identifies mutational signatures in cancer genomes caused by tobacco-specific nitrosamines NNN and NNK, showing their unique contribution to specific cancer types.

The paper identifies mutational signatures in normal kidney cells from multiple countries, revealing exposure to exogenous mutagens including aristolochic acids and unknown agents prevalent in Japan.

The paper models microbial community assembly dynamics in Barrett's esophagus and esophageal adenocarcinoma, finding neutral dynamics in normal tissue and BE but not EAC, with H. pylori showing non-neutral behavior in BE non-cancer outcomes.

This study uses multi-omics profiling to show that house dust mite exposure accelerates lung tumor growth through immune-mediated mechanisms by altering the tumor microenvironment.

This study identifies three distinct evolutionary trajectories in lung adenocarcinomas using whole-genome sequencing, revealing that some never-smoking tumors follow smoking-like paths driven by KRAS mutations.

This study evaluates how variant calling strategies affect mutational signature inference, finding that consensus calling reduces artifacts while preserving true signals.

This study shows that DREAM complex activity influences somatic mutation burden, lifespan, and age-related disease, with reduced activity linked to longer lifespan and lower disease risk.

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.

The paper identifies three subtypes of NS-LUAD using RNA-seq data and develops a 60-gene signature that predicts survival across subgroups.

This study identifies biallelic germline variants in MCM8 and MCM9 as linked to polyposis, gastric cancer, early-onset colorectal cancer, and hypogonadism, with MCM9 variants showing stronger associations.

DupCaller improves mutation detection in duplex sequencing by using sample-specific error profiles and a strand-aware model, increasing sensitivity across various samples and conditions.

SigProfilerTopography evaluates how chromatin organization and other genomic features influence mutational signatures in cancer genomes.

This study analyzes 1024 lung adenocarcinomas to identify evolutionary patterns and mutational mechanisms, revealing distinct trajectories linked to smoking, ancestry, and retrotransposition.

This study shows that carcinogen-induced DNA adducts enhance APOBEC3B-mediated mutagenesis, leading to increased mutation rates in cancer genomes.

This study analyzes acral melanoma genomes and transcriptomes from Mexican patients, finding ancestry-related mutation patterns and survival differences.

The paper identifies two lung cancer subtypes defined by APOBEC mutagenesis levels and shows their association with different genetic mutations, aging, and immune responses.

This study shows spaceflight accelerates hematopoietic stem cell aging through molecular changes like reduced dormancy and mutagenesis, suggesting potential for prevention.

This study analyzes mouse skin tumors to determine how environmental factors like TPA, obesity, and wounding affect mutational burden and cancer risk, finding that tumor promoters, not mutation number, limit tumor growth.

SigProfilerAssignment refits known substitution, doublet, indel and copy-number mutational signatures to single samples and probabilistically to individual mutations, outperforming four refitting tools on 2,700 synthetic genomes.

The paper introduces an updated tool for visualizing and exploring large mutational events in cancer genomes using two classification schemas.

DeepMosaic detects mosaic single nucleotide variants without control samples using deep convolutional neural networks, achieving high accuracy and uncovering many variants missed by existing methods.

SigProfilerExtractor is a tool for de novo mutational signature extraction that outperforms existing methods and identifies four novel signatures, including one linked to tobacco smoking.

The paper presents a genetic model of central chondrosarcoma using genomic and epigenomic data to identify mutations and methylation patterns associated with patient outcomes.

The paper investigates the development and evolution of extrachromosomal DNA (ecDNA) in Barrett's esophagus patients progressing to esophageal adenocarcinoma, finding ecDNA is strongly associated with cancer progression and enriched for oncogenes and immunomodulatory genes.

SigProfilerClusters identifies all types of clustered mutations by calculating sample-dependent thresholds and subclassifies them into established categories.