Deep Learning Artificial Intelligence Predicts Homologous Recombination Deficiency and Platinum Response From Histologic Slides.

Purpose: Cancers with homologous recombination deficiency (HRD) can benefit from platinum salts and poly(ADP-ribose) polymerase inhibitors. Standard diagnostic tests for detecting HRD require molecular profiling, which is not universally available.

Methods: We trained DeepHRD, a deep learning platform for predicting HRD from hematoxylin and eosin (H&E)-stained histopathological slides, using primary breast (n = 1,008) and ovarian (n = 459) cancers from The Cancer Genome Atlas (TCGA).

Detecting HRD in whole-genome and whole-exome sequenced breast and ovarian cancers.

Breast and ovarian cancers harboring homologous recombination deficiency (HRD) are sensitive to PARP inhibitors and platinum chemotherapy. Conventionally, detecting HRD involves screening for defects in , , and other relevant genes. Recent analyses have shown that HRD cancers exhibit characteristic mutational patterns due to the activities of HRD-associated mutational signatures.

The mutagenic forces shaping the genomic landscape of lung cancer in never smokers.

Lung cancer in never smokers (LCINS) accounts for up to 25% of all lung cancers and has been associated with exposure to secondhand tobacco smoke and air pollution in observational studies. Here, we evaluate the mutagenic exposures in LCINS by examining deep whole-genome sequencing data from a large international cohort of 871 treatment-naïve LCINS recruited from 28 geographical locations within the Sherlock- study. mutations were 3.

The Complexity of Tobacco Smoke-Induced Mutagenesis in Head and Neck Cancer.

Tobacco smoke, alone or combined with alcohol, is the predominant cause of head and neck cancer (HNC). Here, we further explore how tobacco exposure contributes to cancer development by mutational signature analysis of 265 whole-genome sequenced HNC from eight countries. Six tobacco-associated mutational signatures were detected, including some not previously reported.

Geographic variation of mutagenic exposures in kidney cancer genomes.

International differences in the incidence of many cancer types indicate the existence of carcinogen exposures that have not yet been identified by conventional epidemiology make a substantial contribution to cancer burden. In clear cell renal cell carcinoma, obesity, hypertension and tobacco smoking are risk factors, but they do not explain the geographical variation in its incidence. Underlying causes can be inferred by sequencing the genomes of cancers from populations with different incidence rates and detecting differences in patterns of somatic mutations.

APOBEC shapes tumor evolution and age at onset of lung cancer in smokers.

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B). However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown.

Rare SNP in the gene interferes with RPA interaction and cellular function of HELB.

HELB is a human helicase involved in initiation of DNA replication, the replication stress response, and regulation of double-strand DNA break repair. rs75770066 is a rare SNP in the HELB gene that affects age at natural menopause. rs75770066 results in a D506G substitution in an acidic patch within the 1A domain of the helicase that is known to interact with RPA.

APOBEC3B regulates R-loops and promotes transcription-associated mutagenesis in cancer.

The single-stranded DNA cytosine-to-uracil deaminase APOBEC3B is an antiviral protein implicated in cancer. However, its substrates in cells are not fully delineated. Here APOBEC3B proteomics reveal interactions with a surprising number of R-loop factors.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator.

Background: All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs.

Topography of mutational signatures in human cancer.

The somatic mutations found in a cancer genome are imprinted by different mutational processes. Each process exhibits a characteristic mutational signature, which can be affected by the genome architecture. However, the interplay between mutational signatures and topographical genomic features has not been extensively explored.

Workflow enabling deepscale immunopeptidome, proteome, ubiquitylome, phosphoproteome, and acetylome analyses of sample-limited tissues.

Serial multi-omic analysis of proteome, phosphoproteome, and acetylome provides insights into changes in protein expression, cell signaling, cross-talk and epigenetic pathways involved in disease pathology and treatment. However, ubiquitylome and HLA peptidome data collection used to understand protein degradation and antigen presentation have not together been serialized, and instead require separate samples for parallel processing using distinct protocols. Here we present MONTE, a highly sensitive multi-omic native tissue enrichment workflow, that enables serial, deep-scale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome from the same tissue sample.

Multiomic analysis of malignant pleural mesothelioma identifies molecular axes and specialized tumor profiles driving intertumor heterogeneity.

Malignant pleural mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Through a large series of whole-genome sequencing data, integrated with transcriptomic and epigenomic data using multiomics factor analysis, we demonstrate that the current World Health Organization classification only accounts for up to 10% of interpatient molecular differences. Instead, the MESOMICS project paves the way for a morphomolecular classification of MPM based on four dimensions: ploidy, tumor cell morphology, adaptive immune response and CpG island methylator profile.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator.

Background: All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs.

Uncovering novel mutational signatures by extraction with SigProfilerExtractor.

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures.

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.

Unlabelled: Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DNA repair, E2F targets, G2-M checkpoint, interferon-gamma signaling, and immune-checkpoint components.

Mechanisms of APOBEC3 mutagenesis in human cancer cells.

The APOBEC3 family of cytosine deaminases has been implicated in some of the most prevalent mutational signatures in cancer. However, a causal link between endogenous APOBEC3 enzymes and mutational signatures in human cancer genomes has not been established, leaving the mechanisms of APOBEC3 mutagenesis poorly understood. Here, to investigate the mechanisms of APOBEC3 mutagenesis, we deleted implicated genes from human cancer cell lines that naturally generate APOBEC3-associated mutational signatures over time.

Degradation of GSPT1 causes TP53-independent cell death in leukemia while sparing normal hematopoietic stem cells.

Targeted protein degradation is a rapidly advancing and expanding therapeutic approach. Drugs that degrade GSPT1 via the CRL4CRBN ubiquitin ligase are a new class of cancer therapy in active clinical development with evidence of activity against acute myeloid leukemia in early-phase trials. However, other than activation of the integrated stress response, the downstream effects of GSPT1 degradation leading to cell death are largely undefined, and no murine models are available to study these agents.

Examining clustered somatic mutations with SigProfilerClusters.

Motivation: Clustered mutations are found in the human germline as well as in the genomes of cancer and normal somatic cells. Clustered events can be imprinted by a multitude of mutational processes, and they have been implicated in both cancer evolution and development disorders. Existing tools for identifying clustered mutations have been optimized for a particular subtype of clustered event and, in most cases, relied on a predefined inter-mutational distance (IMD) cutoff combined with a piecewise linear regression analysis.

Recurrent pain in school-aged children: a longitudinal study focusing on the relation to academic achievement.

Recurrent pain is an increasing public health problem among school-aged children, with potential negative impact on children's daily lives, such as schoolwork. The overall aim of this study was to investigate whether recurrent pain in school year 6 was associated with poorer academic achievement at the end of elementary school in school year 9. The study was a follow-up study based on data from " The Study of Health in School-Aged Children from Umeå".

Mapping clustered mutations in cancer reveals APOBEC3 mutagenesis of ecDNA.

Clustered somatic mutations are common in cancer genomes and previous analyses reveal several types of clustered single-base substitutions, which include doublet- and multi-base substitutions, diffuse hypermutation termed omikli, and longer strand-coordinated events termed kataegis. Here we provide a comprehensive characterization of clustered substitutions and clustered small insertions and deletions (indels) across 2,583 whole-genome-sequenced cancers from 30 types of cancer. Clustered mutations were highly enriched in driver genes and associated with differential gene expression and changes in overall survival.

Mutational signatures in esophageal squamous cell carcinoma from eight countries with varying incidence.

Esophageal squamous cell carcinoma (ESCC) shows remarkable variation in incidence that is not fully explained by known lifestyle and environmental risk factors. It has been speculated that an unknown exogenous exposure(s) could be responsible. Here we combine the fields of mutational signature analysis with cancer epidemiology to study 552 ESCC genomes from eight countries with varying incidence rates.

Automating UbiFast for High-throughput and Multiplexed Ubiquitin Enrichment.

Robust methods for deep-scale enrichment and site-specific identification of ubiquitylation sites are necessary for characterizing the myriad roles of protein ubiquitylation. To this end we previously developed UbiFast, a sensitive method for highly multiplexed ubiquitylation profiling where K-ϵ-GG peptides are enriched with anti-K-ε-GG antibody and labeled on-antibody with isobaric labeling reagents for sample multiplexing. Here, we present robotic automation of the UbiFast method using a magnetic bead-conjugated K-ε-GG antibody (mK-ε-GG) and a magnetic particle processor.