A practical framework and online tool for mutational signature analyses show inter-tissue variation and driver dependencies

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Mutational signatures of colorectal cancers according to distinct computational workflows

Tumor mutational signatures have gained prominence in cancer research, yet the lack of standardized methods hinders reproducibility and robustness. Leveraging colorectal cancer (CRC) as a model, we explored the influence of computational parameters on mutational signature analyses across 230 CRC cell lines and 152 CRC patients. Results were validated in three independent datasets: 483 endometrial cancer patients stratified by mismatch repair (MMR) status, 35 lung cancer patients by smoking status and 12 patient-derived organoids (PDOs) annotated for colibactin exposure. Assessing various bioinformatic tools, reference datasets and input data sizes including whole genome sequencing, whole exome sequencing and a pan-cancer gene panel, we demonstrated significant variability in the results. We report that the use of distinct algorithms and references led to statistically different results, highlighting how arbitrary choices may induce variability in the mutational signature contributions. Furthermore, we found a differential contribution of mutational signatures between coding and intergenic regions and defined the minimum number of somatic variants required for reliable mutational signature assignment. To facilitate the identification of the most suitable workflows, we developed Comparative Mutational Signature analysis on Coding and Extragenic Regions (CoMSCER), a bioinformatic tool which allows researchers to easily perform comparative mutational signature analysis by coupling the results from several tools and public reference datasets and to assess mutational signature contributions in coding and non-coding genomic regions. In conclusion, our study provides a comparative framework to elucidate the impact of distinct computational workflows on mutational signatures.

The mutagenic consequences of defective DNA repair

Multiple separate repair mechanisms safeguard the genome against various types of DNA damage, and their failure can increase the rate of spontaneous mutagenesis. The malfunction of distinct repair mechanisms leads to genomic instability through different mutagenic processes. For example, defective mismatch repair causes high base substitution rates and microsatellite instability, whereas homologous recombination deficiency is characteristically associated with deletions and chromosome instability. This review presents a comprehensive collection of all mutagenic phenotypes associated with the loss of each DNA repair mechanism, drawing on data from a variety of model organisms and mutagenesis assays, and placing greatest emphasis on systematic analyses of human cancer datasets. We describe the latest theories on the mechanism of each mutagenic process, often explained by reliance on an alternative repair pathway or the error-prone replication of unrepaired, damaged DNA. Aided by the concept of mutational signatures, the genomic phenotypes can be used in cancer diagnosis to identify defective DNA repair pathways.

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- Lung study. KRAS mutations were 3.8-fold more common in adenocarcinomas of never smokers from North America and Europe, while a 1.6-fold higher prevalence of EGFR and TP53 mutations was observed in adenocarcinomas from East Asia. Signature SBS40a, with unknown cause, was found in most samples and accounted for the largest proportion of single base substitutions in adenocarcinomas, being enriched in EGFR -mutated cases. Conversely, the aristolochic acid signature SBS22a was almost exclusively observed in patients from Taipei. Even though LCINS exposed to secondhand smoke had an 8.3% higher mutational burden and 5.4% shorter telomeres, passive smoking was not associated with driver mutations in cancer driver genes or the activities of individual mutational signatures. In contrast, patients from regions with high levels of air pollution were more likely to have TP53 mutations while exhibiting shorter telomeres and an increase in most types of somatic mutations, including a 3.9-fold elevation of signature SBS4 (q-value=3.1 × 10 -5 ), previously linked mainly to tobacco smoking, and a 76% increase of clock-like signature SBS5 (q-value=5.0 × 10 -5 ). A positive dose-response effect was observed with air pollution levels, which correlated with both a decrease in telomere length and an elevation in somatic mutations, notably attributed to signatures SBS4 and SBS5. Our results elucidate the diversity of mutational processes shaping the genomic landscape of lung cancer in never smokers.

Establishment, characterization, and genetic profiling of patient-derived osteosarcoma cells from a patient with retinoblastoma

Osteosarcoma is the most common malignant bone cancer in pediatric patients. Patients who respond poorly to chemotherapy experience worse clinical outcomes with a high mortality rate. The major challenge is the lack of effective drugs for these patients. To introduce new drugs for clinical approval, preclinical studies based on in vitro models must demonstrate the potency of the tested drugs, enabling the drugs to enter phase 1 clinical trials. Patient-derived cell culture is a promising testing platform for in vitro studies, as they more accurately recapitulate cancer states and genetic profiles compared to cell lines. In the present study, we established patient-derived osteosarcoma cells (PDC) from a patient who had previously been diagnosed with retinoblastoma. We identified a new variant of a germline mutation in the RB1 gene in the tissue of the patient. The biological effects of this PDC were studied to observe whether the cryopreserved PDC retained a feature of fresh PDC. The cryopreserved PDC preserved the key biological effects, including cell growth, invasive capability, migration, and mineralization, that define the conserved phenotypes compared to fresh PDC. From whole genome sequencing analysis of osteosarcoma tissue and patient-derived cells, we found that cryopreserved PDC was a minor population in the origin tissue and was selectively grown under the culture conditions. The cryopreserved PDC has a high resistance to conventional chemotherapy. This study demonstrated that the established cryopreserved PDC has the aggressive characteristics of osteosarcoma, in particular the chemoresistance phenotype that might be used for further investigation in the chemoresistant mechanism of osteosarcoma. In conclusion, the approach we applied for primary cell culture might be a promising method to generate in vitro models for functional testing of osteosarcoma.

The genomic landscape of Vk*MYC myeloma highlights shared pathways of transformation between mice and humans

Multiple myeloma (MM) is a heterogeneous disease characterized by frequent MYC translocations. Sporadic MYC activation in the germinal center of genetically engineered Vk*MYC mice is sufficient to induce plasma cell tumors in which a variety of secondary mutations are spontaneously acquired and selected over time. Analysis of 119 Vk*MYC myeloma reveals recurrent copy number alterations, structural variations, chromothripsis, driver mutations, apolipoprotein B mRNA-editing enzyme, catalytic polypeptide (APOBEC) mutational activity, and a progressive decrease in immunoglobulin transcription that inversely correlates with proliferation. Moreover, we identify frequent insertional mutagenesis by endogenous retro-elements as a murine specific mechanism to activate NF-kB and IL6 signaling pathways shared with human MM. Despite the increased genomic complexity associated with progression, advanced tumors remain dependent on MYC. In summary, here we credential the Vk*MYC mouse as a unique resource to explore MM genomic evolution and describe a fully annotated collection of diverse and immortalized murine MM tumors.

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer 1-7 , however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naïve hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

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 burden1. In clear cell renal cell carcinoma, obesity, hypertension and tobacco smoking are risk factors, but they do not explain the geographical variation in its incidence2. 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. Here we sequenced 962 clear cell renal cell carcinomas from 11 countries with varying incidence. The somatic mutation profiles differed between countries. In Romania, Serbia and Thailand, mutational signatures characteristic of aristolochic acid compounds were present in most cases, but these were rare elsewhere. In Japan, a mutational signature of unknown cause was found in more than 70% of cases but in less than 2% elsewhere. A further mutational signature of unknown cause was ubiquitous but exhibited higher mutation loads in countries with higher incidence rates of kidney cancer. Known signatures of tobacco smoking correlated with tobacco consumption, but no signature was associated with obesity or hypertension, suggesting that non-mutagenic mechanisms of action underlie these risk factors. The results of this study indicate the existence of multiple, geographically variable, mutagenic exposures that potentially affect tens of millions of people and illustrate the opportunities for new insights into cancer causation through large-scale global cancer genomics.

Novel insights into tumorigenesis revealed by molecular analysis of Lynch syndrome cases with multiple colorectal tumors

Background

Lynch syndrome (LS) is an autosomal dominant multi-organ cancer syndrome with a high lifetime risk of cancer. The number of cumulative colorectal adenomas in LS does not generally exceed ten, and removal of adenomas via routine screening minimizes the cancer burden. However, abnormal phenotypes may mislead initial diagnosis and subsequently cause suboptimal treatment.

Aim

Currently, there is no standard guide for the care of multiple colorectal adenomas in LS individuals. We aimed to shed insight into the molecular features and reasons for multiplicity of adenomas in LS patients.

Methods

We applied whole exome sequencing on nine adenomas (ten samples) and three assumed primary carcinomas (five samples) of an LS patient developing the tumors during a 21-year follow-up period. We compared the findings to the tumor profiles of two additional LS cases ascertained through colorectal tumor multiplicity, as well as to ten adenomas and 15 carcinomas from 23 unrelated LS patients with no elevated adenoma burden from the same population. As LS associated cancers can arise via several molecular pathways, we also profiled the tumors for CpG Island Methylator Phenotype (CIMP), and LINE-1 methylation.

Results

All tumors were microsatellite unstable (MSI), and MSI was present in several samples derived from normal mucosa as well. Interestingly, frequent frameshift variants in RNF43 were shared among substantial number of the tumors of our primary case and the tumors of LS cases with multiple tumors but almost absent in our control LS cases. The RNF43 variants were completely absent in the normal tissue, indicating tumor-associated mutational hotspots. The RNF43 status correlated with the mutational signature SBS96. Contrary to LS tumors from the reference set with no elevated colorectal tumor burden, the somatic variants occurred significantly more frequently at C>T in the CpG context, irrespective of CIMP or LINE-1 status, potentially indicating other, yet unknown methylation-related mechanisms. There were no signs of somatic mosaicism affecting the MMR genes. Somatic variants in APC and CTNNB1 were unique to each tumor.

Conclusion

Frequent somatic RNF43 hot spot variants combined with SBS96 signature and increased tendency to DNA methylation may contribute to tumor multiplicity in LS.

Somatic mutations of esophageal adenocarcinoma: a comparison between Black and White patients

Esophageal adenocarcinoma is the most common histological subtype of esophageal cancer in Western countries and shows poor prognosis with rapid growth. EAC is characterized by a strong male predominance and racial disparity. EAC is up to fivefold more common among Whites than Blacks, yet Black patients with EAC have poorer survival rates. The racial disparity remains largely unknown, and there is limited knowledge of mutations in EAC regarding racial disparities. We used whole-exome sequencing to show somatic mutation profiles derived from tumor samples from 18 EAC male patients. We identified three molecular subgroups based on the pre-defined esophageal cancer-specific mutational signatures. Group 1 is associated with age and NTHL1 deficiency-related signatures. Group 2 occurs primarily in Black patients and is associated with signatures related to DNA damage from oxidative stress and NTHL1 deficiency-related signatures. Group 3 is associated with defective homologous recombination-based DNA often caused by BRCA mutation in White patients. We observed significantly mutated race related genes (LCE2B in Black, SDR39U1 in White) were (q-value < 0.1). Our findings underscore the possibility of distinct molecular mutation patterns in EAC among different races. Further studies are needed to validate our findings, which could contribute to precision medicine in EAC.

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 residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

Post-therapy emergence of an NBN reversion mutation in a patient with pancreatic acinar cell carcinoma

Pancreatic acinar cell carcinoma (PACC) is a rare form of pancreatic cancer that commonly harbors targetable alterations, including activating fusions in the MAPK pathway and loss-of-function (LOF) alterations in DNA damage response/homologous recombination DNA repair-related genes. Here, we describe a patient with PACC harboring both somatic biallelic LOF of NBN and an activating NTRK1 fusion. Upon disease progression following 13 months of treatment with folinic acid, fluorouracil, irinotecan, and oxaliplatin (FOLFIRINOX), genomic analysis of a metastatic liver biopsy revealed the emergence of a novel reversion mutation restoring the reading frame of NBN. To our knowledge, genomic reversion of NBN has not been previously reported as a resistance mechanism in any tumor type. The patient was treated with, but did not respond to, targeted treatment with a selective NTRK inhibitor. This case highlights the complex but highly actionable genomic landscape of PACC and underlines the value of genomic profiling of rare tumor types such as PACC.

The spectrum of TP53 mutations in Rwandan patients with gastric cancer

BACKGROUND

Gastric cancer is the sixth most frequently diagnosed cancer and third in causing cancer-related death globally. The most frequently mutated gene in human cancers is TP53, which plays a pivotal role in cancer initiation and progression. In Africa, particularly in Rwanda, data on TP53 mutations are lacking. Therefore, this study intended to obtain TP53 mutation status in Rwandan patients with gastric cancer.

RESULTS

Formalin-fixed paraffin-embedded tissue blocks of 95 Rwandan patients with histopathologically proven gastric carcinoma were obtained from the University Teaching Hospital of Kigali. After DNA extraction, all coding regions of the TP53 gene and the exon-intron boundary region of TP53 were sequenced using the Sanger sequencing. Mutated TP53 were observed in 24 (25.3%) of the 95 cases, and a total of 29 mutations were identified. These TP53 mutations were distributed between exon 4 and 8 and most of them were missense mutations (19/29; 65.5%). Immunohistochemical analysis for TP53 revealed that most of the TP53 missense mutations were associated with TP53 protein accumulation. Among the 29 mutations, one was novel (c.459_477delCGGCACCCGCGTCCGCGCC). This 19-bp deletion mutation in exon 5 caused the production of truncated TP53 protein (p.G154Wfs*10). Regarding the spectrum of TP53 mutations, G:C > A:T at CpG sites was the most prevalent (10/29; 34.5%) and G:C > T:A was the second most prevalent (7/29; 24.1%). Interestingly, when the mutation spectrum of TP53 was compared to three previous TP53 mutational studies on non-Rwandan patients with gastric cancer, G:C > T:A mutations were significantly more frequent in this study than in our previous study (p = 0.013), the TCGA database (p = 0.017), and a previous study on patients from Hong Kong (p = 0.006). Even after correcting for false discovery, statistical significance was observed.

CONCLUSIONS

Our results suggested that TP53 G:C > T:A transversion mutation in Rwandan patients with gastric cancer is more frequent than in non-Rwandan patients with gastric cancer, indicating at an alternative etiological and carcinogenic progression of gastric cancer in Rwanda.

Accurate and sensitive mutational signature analysis with MuSiCal

Mutational signature analysis is a recent computational approach for interpreting somatic mutations in the genome. Its application to cancer data has enhanced our understanding of mutational forces driving tumorigenesis and demonstrated its potential to inform prognosis and treatment decisions. However, methodological challenges remain for discovering new signatures and assigning proper weights to existing signatures, thereby hindering broader clinical applications. Here we present Mutational Signature Calculator (MuSiCal), a rigorous analytical framework with algorithms that solve major problems in the standard workflow. Our simulation studies demonstrate that MuSiCal outperforms state-of-the-art algorithms for both signature discovery and assignment. By reanalyzing more than 2,700 cancer genomes, we provide an improved catalog of signatures and their assignments, discover nine indel signatures absent in the current catalog, resolve long-standing issues with the ambiguous 'flat' signatures and give insights into signatures with unknown etiologies. We expect MuSiCal and the improved catalog to be a step towards establishing best practices for mutational signature analysis.

CRUX, a platform for visualising, exploring and analysing cancer genome cohort data

To better understand how tumours develop, identify prognostic biomarkers and find new treatments, researchers have generated vast catalogues of cancer genome data. However, these datasets are complex, so interpreting their important features requires specialized computational skills and analytical tools, which presents a significant technical challenge. To address this, we developed CRUX, a platform for exploring genomic data from cancer cohorts. CRUX enables researchers to perform common analyses including cohort comparisons, biomarker discovery, survival analysis, and to create visualisations including oncoplots and lollipop charts. CRUX simplifies cancer genome analysis in several ways: (i) it has an easy-to-use graphical interface; (ii) it enables users to create custom cohorts, as well as analyse precompiled public and private user-created datasets; (iii) it allows analyses to be run locally to address data privacy concerns (though an online version is also available) and (iv) it makes it easy to use additional specialized tools by exporting data in the correct formats. We showcase CRUX's capabilities with case studies employing different types of cancer genome analysis, demonstrating how it can be used flexibly to generate valuable insights into cancer biology. CRUX is freely available at https://github.com/CCICB/CRUX and https://ccicb.shinyapps.io/crux (DOI: 10.5281/zenodo.8015714).

Genomic and epigenomic basis of breast invasive lobular carcinomas lacking CDH1 genetic alterations

CDH1 (E-cadherin) bi-allelic inactivation is the hallmark alteration of breast invasive lobular carcinoma (ILC), resulting in its discohesive phenotype. A subset of ILCs, however, lack CDH1 genetic/epigenetic inactivation, and their genetic underpinning is unknown. Through clinical targeted sequencing data reanalysis of 364 primary ILCs, we identified 25 ILCs lacking CDH1 bi-allelic genetic alterations. CDH1 promoter methylation was frequent (63%) in these cases. Targeted sequencing reanalysis revealed 3 ILCs harboring AXIN2 deleterious fusions (n = 2) or loss-of-function mutation (n = 1). Whole-genome sequencing of 3 cases lacking bi-allelic CDH1 genetic/epigenetic inactivation confirmed the AXIN2 mutation and no other cell-cell adhesion genetic alterations but revealed a new CTNND1 (p120) deleterious fusion. AXIN2 knock-out in MCF7 cells resulted in lobular-like features, including increased cellular migration and resistance to anoikis. Taken together, ILCs lacking CDH1 genetic/epigenetic alterations are driven by inactivating alterations in other cell adhesion genes (CTNND1 or AXIN2), endorsing a convergent phenotype in ILC.

Genomic and transcriptomic profiling of hepatocellular carcinoma reveals a rare molecular subtype

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide, occurring predominantly in patients with underlying chronic liver disease and cirrhosis. Here, we describe a case of a 62-year-old man that was admitted to our hospital and diagnosed with HCC where the cancer has already metastasized to the retroperitoneum and peritoneum. In order to better characterize the HCC, both the cancerous liver tissue and the adjacent normal liver tissue of the patient were collected and subjected to a genomic, transcriptomic and proteomic analysis. Our patient carries a highly mutated HCC, which is characterized by both somatic mutation in the following genes ALK, CDK6, TP53, PGR. In addition, we observe several molecular alterations that are associated with potential therapy resistance, for example the expression of the organic-anion-transporting polypeptide (OATP) family members B1 and B3, that mediate the transport of the anticancer drugs, has been found decreased. Overall, our molecular profiling potentially classify the patient with poor prognosis and possibly displaying resistance to pharmacological therapy.

Methods for Estimating Personal Disease Risk and Phylogenetic Diversity of Hematopoietic Stem Cells

An individual's chronological age does not always correspond to the health of different tissues in their body, especially in cases of disease. Therefore, estimating and contrasting the physiological age of tissues with an individual's chronological age may be a useful tool to diagnose disease and its progression. In this study, we present novel metrics to quantify the loss of phylogenetic diversity in hematopoietic stem cells (HSCs), which are precursors to most blood cell types and are associated with many blood-related diseases. These metrics showed an excellent correspondence with an age-related increase in blood cancer incidence, enabling a model to estimate the phylogeny-derived age (phyloAge) of HSCs present in an individual. The HSC phyloAge was generally older than the chronological age of patients suffering from myeloproliferative neoplasms (MPNs). We present a model that relates excess HSC aging with increased MPN risk. It predicted an over 200 times greater risk based on the HSC phylogenies of the youngest MPN patients analyzed. Our new metrics are designed to be robust to sampling biases and do not rely on prior knowledge of driver mutations or physiological assessments. Consequently, they complement conventional biomarker-based methods to estimate physiological age and disease risk.

Pathogenic germline variants in non-BRCA1/2 homologous recombination genes in ovarian cancer: Analysis of tumor phenotype and survival

OBJECTIVE

To define molecular features of ovarian cancer (OC) with germline pathogenic variants (PVs) in non-BRCA homologous recombination (HR) genes and analyze survival compared to BRCA1/2 and wildtype (WT) OC.

METHODS

We included patients with OC undergoing tumor-normal sequencing (MSK-IMPACT) from 07/01/2015-12/31/2020, including germline assessment of BRCA1/2 and other HR genes ATM, BARD1, BRIP1, FANCA, FANCC, NBN, PALB2, RAD50, RAD51B, RAD51C, and RAD51D. Biallelic inactivation was assessed within tumors. Progression-free (PFS) and overall survival (OS) were calculated from pathologic diagnosis using the Kaplan-Meier method with left truncation. Whole-exome sequencing (WES) was performed in a subset.

RESULTS

Of 882 patients with OC, 56 (6.3%) had germline PVs in non-BRCA HR genes; 95 (11%) had BRCA1-associated OC (58 germline, 37 somatic); and 59 (6.7%) had BRCA2-associated OC (40 germline, 19 somatic). High rates of biallelic alterations were observed among germline PVs in BRIP1 (11/13), PALB2 (3/4), RAD51B (3/4), RAD51C (3/4), and RAD51D (8/10). In cases with WES (27/35), there was higher tumor mutational burden (TMB; median 2.5 [1.1-6.0] vs. 1.2 mut/Mb [0.6-2.6]) and enrichment of HR-deficient (HRD) mutational signatures in tumors associated with germline PALB2 and RAD51B/C/D compared with BRIP1 PVs (p < 0.01). Other features of HRD, including telomeric-allelic imbalance (TAI) and large-scale state transitions (LSTs), were similar. Although there was heterogeneity in PFS/OS by gene group, only BRCA1/2-associated OC had improved survival compared to WT OC (p < 0.01).

CONCLUSIONS

OCs associated with germline PVs in non-BRCA HR genes represent a heterogenous group, with PALB2 and RAD51B/C/D associated with an HRD phenotype.

Spatiotemporal genomic profiling of intestinal metaplasia reveals clonal dynamics of gastric cancer progression

Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. Analyzing 1,256 gastric samples (1,152 IMs) across 692 subjects from a prospective 10-year study, we identify 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9). Single-cell and spatial profiles highlight changes in tissue ecology and IM lineage heterogeneity, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling reveals expression-based molecular subtypes of IM associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical-genomic models outperform clinical-only models in predicting IMs likely to transform to GC. By highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression, our results raise opportunities for GC precision prevention and interception.

Genomic sequence context differs between germline and somatic structural variants allowing for their differentiation in tumor samples without paired normals

There is currently no method to distinguish between germline and somatic structural variants (SVs) in tumor samples that lack a matched normal sample. In this study, we analyzed several features of germline and somatic SVs from a cohort of 974 patients from The Cancer Genome Atlas (TCGA). We identified a total of 21 features that differed significantly between germline and somatic SVs. Several of the germline SV features were associated with each other, as were several of the somatic SV features. We also found that these associations differed between the germline and somatic classes, for example, we found that somatic inversions were more likely to be longer events than their germline counterparts. Using these features we trained a support vector machine (SVM) classifier on 555,849 TCGA SVs to computationally distinguish germline from somatic SVs in the absence of a matched normal. This classifier had an ROC curve AUC of 0.984 when tested on an independent test set of 277,925 TCGA SVs. In this dataset, we achieved a positive predictive value (PPV) of 0.81 for an SV called somatic by the classifier being truly somatic. We further tested the classifier on a separate set of 7,623 SVs from pediatric high-grade gliomas (pHGG). In this non-TCGA cohort, our classifier achieved a PPV of 0.828, showing robust performance across datasets.

Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment

MOTIVATION

Analysis of mutational signatures is a powerful approach for understanding the mutagenic processes that have shaped the evolution of a cancer genome. To evaluate the mutational signatures operative in a cancer genome, one first needs to quantify their activities by estimating the number of mutations imprinted by each signature.

RESULTS

Here we present SigProfilerAssignment, a desktop and an online computational framework for assigning all types of mutational signatures to individual samples. SigProfilerAssignment is the first tool that allows both analysis of copy-number signatures and probabilistic assignment of signatures to individual somatic mutations. As its computational engine, the tool uses a custom implementation of the forward stagewise algorithm for sparse regression and nonnegative least squares for numerical optimization. Analysis of 2700 synthetic cancer genomes with and without noise demonstrates that SigProfilerAssignment outperforms four commonly used approaches for assigning mutational signatures.

AVAILABILITY AND IMPLEMENTATION

SigProfilerAssignment is available under the BSD 2-clause license at https://github.com/AlexandrovLab/SigProfilerAssignment with a web implementation at https://cancer.sanger.ac.uk/signatures/assignment/.

Relating mutational signature exposures to clinical data in cancers via signeR 2.0

BACKGROUND

Cancer is a collection of diseases caused by the deregulation of cell processes, which is triggered by somatic mutations. The search for patterns in somatic mutations, known as mutational signatures, is a growing field of study that has already become a useful tool in oncology. Several algorithms have been proposed to perform one or both the following two tasks: (1) de novo estimation of signatures and their exposures, (2) estimation of the exposures of each one of a set of pre-defined signatures.

RESULTS

Our group developed signeR, a Bayesian approach to both of these tasks. Here we present a new version of the software, signeR 2.0, which extends the possibilities of previous analyses to explore the relation of signature exposures to other data of clinical relevance. signeR 2.0 includes a user-friendly interface developed using the R-Shiny framework and improvements in performance. This version allows the analysis of submitted data or public TCGA data, which is embedded in the package for easy access.

CONCLUSION

signeR 2.0 is a valuable tool to generate and explore exposure data, both from de novo or fitting analyses and is an open-source R package available through the Bioconductor project at ( https://doi.org/10.18129/B9.bioc.signeR ).

Concurrent RB1 loss and BRCA-deficiency predicts enhanced immunological response and long-term survival in tubo-ovarian high-grade serous carcinoma

Background

Somatic loss of the tumour suppressor RB1 is a common event in tubo-ovarian high-grade serous carcinoma (HGSC), which frequently co-occurs with alterations in homologous recombination DNA repair genes including BRCA1 and BRCA2 (BRCA). We examined whether tumour expression of RB1 was associated with survival across ovarian cancer histotypes (HGSC, endometrioid (ENOC), clear cell (CCOC), mucinous (MOC), low-grade serous carcinoma (LGSC)), and how co-occurrence of germline BRCA pathogenic variants and RB1 loss influences long-term survival in a large series of HGSC.

Patients and methods

RB1 protein expression patterns were classified by immunohistochemistry in epithelial ovarian carcinomas of 7436 patients from 20 studies participating in the Ovarian Tumor Tissue Analysis consortium and assessed for associations with overall survival (OS), accounting for patient age at diagnosis and FIGO stage. We examined RB1 expression and germline BRCA status in a subset of 1134 HGSC, and related genotype to survival, tumour infiltrating CD8+ lymphocyte counts and transcriptomic subtypes. Using CRISPR-Cas9, we deleted RB1 in HGSC cell lines with and without BRCA1 mutations to model co-loss with treatment response. We also performed genomic analyses on 126 primary HGSC to explore the molecular characteristics of concurrent homologous recombination deficiency and RB1 loss.

Results

RB1 protein loss was most frequent in HGSC (16.4%) and was highly correlated with RB1 mRNA expression. RB1 loss was associated with longer OS in HGSC (hazard ratio [HR] 0.74, 95% confidence interval [CI] 0.66-0.83, P = 6.8 ×10-7), but with poorer prognosis in ENOC (HR 2.17, 95% CI 1.17-4.03, P = 0.0140). Germline BRCA mutations and RB1 loss co-occurred in HGSC (P < 0.0001). Patients with both RB1 loss and germline BRCA mutations had a superior OS (HR 0.38, 95% CI 0.25-0.58, P = 5.2 ×10-6) compared to patients with either alteration alone, and their median OS was three times longer than non-carriers whose tumours retained RB1 expression (9.3 years vs. 3.1 years). Enhanced sensitivity to cisplatin (P < 0.01) and paclitaxel (P < 0.05) was seen in BRCA1 mutated cell lines with RB1 knockout. Among 126 patients with whole-genome and transcriptome sequence data, combined RB1 loss and genomic evidence of homologous recombination deficiency was correlated with transcriptional markers of enhanced interferon response, cell cycle deregulation, and reduced epithelial-mesenchymal transition in primary HGSC. CD8+ lymphocytes were most prevalent in BRCA-deficient HGSC with co-loss of RB1.

Conclusions

Co-occurrence of RB1 loss and BRCA mutation was associated with exceptionally long survival in patients with HGSC, potentially due to better treatment response and immune stimulation.

Base-Excision Repair Mutational Signature in Two Sebaceous Carcinomas of the Eyelid

Personalized medicine aims to develop tailored treatments for individual patients based on specific mutations present in the affected organ. This approach has proven paramount in cancer treatment, as each tumor carries distinct driver mutations that respond to targeted drugs and, in some cases, may confer resistance to other therapies. Particularly for rare conditions, personalized medicine has the potential to revolutionize treatment strategies. Rare cancers often lack extensive datasets of molecular and pathological information, large-scale trials for novel therapies, and established treatment guidelines. Consequently, surgery is frequently the only viable option for many rare tumors, when feasible, as traditional multimodal approaches employed for more common cancers often play a limited role. Sebaceous carcinoma of the eyelid is an exceptionally rare cancer affecting the eye's adnexal tissues, most frequently reported in Asia, but whose prevalence is significantly increasing even in Europe and the US. The sole established curative treatment is surgical excision, which can lead to significant disfigurement. In cases of metastatic sebaceous carcinoma, validated drug options are currently lacking. In this project, we set out to characterize the mutational landscape of two sebaceous carcinomas of the eyelid following surgical excision. Utilizing available bioinformatics tools, we demonstrated our ability to identify common features promptly and accurately in both tumors. These features included a Base-Excision Repair mutational signature, a notably high tumor mutational burden, and key driver mutations in somatic tissues. These findings had not been previously reported in similar studies. This report underscores how, in the case of rare tumors, it is possible to comprehensively characterize the mutational landscape of each individual case, potentially opening doors to targeted therapeutic options.

Mutational spectra are associated with bacterial niche

As observed in cancers, individual mutagens and defects in DNA repair create distinctive mutational signatures that combine to form context-specific spectra within cells. We reasoned that similar processes must occur in bacterial lineages, potentially allowing decomposition analysis to detect both disruption of DNA repair processes and exposure to niche-specific mutagens. Here we reconstruct mutational spectra for 84 clades from 31 diverse bacterial species and find distinct mutational patterns. We extract signatures driven by specific DNA repair defects using hypermutator lineages, and further deconvolute the spectra into multiple signatures operating within different clades. We show that these signatures are explained by both bacterial phylogeny and replication niche. By comparing mutational spectra of clades from different environmental and biological locations, we identify niche-associated mutational signatures, and then employ these signatures to infer the predominant replication niches for several clades where this was previously obscure. Our results show that mutational spectra may be associated with sites of bacterial replication when mutagen exposures differ, and can be used in these cases to infer transmission routes for established and emergent human bacterial pathogens.

Mutational topography reflects clinical neuroblastoma heterogeneity

Neuroblastoma is a pediatric solid tumor characterized by strong clinical heterogeneity. Although clinical risk-defining genomic alterations exist in neuroblastomas, the mutational processes involved in their generation remain largely unclear. By examining the topography and mutational signatures derived from all variant classes, we identified co-occurring mutational footprints, which we termed mutational scenarios. We demonstrate that clinical neuroblastoma heterogeneity is associated with differences in the mutational processes driving these scenarios, linking risk-defining pathognomonic variants to distinct molecular processes. Whereas high-risk MYCN-amplified neuroblastomas were characterized by signs of replication slippage and stress, homologous recombination-associated signatures defined high-risk non-MYCN-amplified patients. Non-high-risk neuroblastomas were marked by footprints of chromosome mis-segregation and TOP1 mutational activity. Furthermore, analysis of subclonal mutations uncovered differential activity of these processes through neuroblastoma evolution. Thus, clinical heterogeneity of neuroblastoma patients can be linked to differences in the mutational processes that are active in their tumors.

Characterization of Cancer Evolution Landscape Based on Accurate Detection of Somatic Mutations in Single Tumor Cells

Accurate detection of somatic mutations in single tumor cells is greatly desired as it allows us to quantify the single-cell mutation burden and construct the mutation-based phylogenetic tree. Here we developed scNanoSeq chemistry and profiled 842 single cells from 21 human breast cancer samples. The majority of the mutation-based phylogenetic trees comprise a characteristic stem evolution followed by the clonal sweep. We observed the subtype-dependent lengths in the stem evolution. To explain this phenomenon, we propose that the differences are related to different reprogramming required for different subtypes of breast cancer. Furthermore, we reason that the time that the tumor-initiating cell took to acquire the critical clonal-sweep-initiating mutation by random chance set the time limit for the reprogramming process. We refer to this model as a reprogramming and critical mutation co-timing (RCMC) subtype model. Next, in the sweeping clone, we observed that tumor cells undergo a branched evolution with rapidly decreasing selection. In the most recent clades, effectively neutral evolution has been reached, resulting in a substantially large number of mutational heterogeneities. Integrative analysis with 522-713X ultra-deep bulk whole genome sequencing (WGS) further validated this evolution mode. Mutation-based phylogenetic trees also allow us to identify the early branched cells in a few samples, whose phylogenetic trees support the gradual evolution of copy number variations (CNVs). Overall, the development of scNanoSeq allows us to unveil novel insights into breast cancer evolution.

Prevalence and significance of DDX41 gene variants in the general population

Germ line variants in the DDX41 gene have been linked to myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) development. However, the risks associated with different variants remain unknown, as do the basis of their leukemogenic properties, impact on steady-state hematopoiesis, and links to other cancers. Here, we investigate the frequency and significance of DDX41 variants in 454 792 United Kingdom Biobank (UKB) participants and identify 452 unique nonsynonymous DNA variants in 3538 (1/129) individuals. Many were novel, and the prevalence of most varied markedly by ancestry. Among the 1059 individuals with germ line pathogenic variants (DDX41-GPV) 34 developed MDS/AML (odds ratio, 12.3 vs noncarriers). Of these, 7 of 218 had start-lost, 22 of 584 had truncating, and 5 of 257 had missense (odds ratios: 12.9, 15.1, and 7.5, respectively). Using multivariate logistic regression, we found significant associations of DDX41-GPV with MDS, AML, and family history of leukemia but not lymphoma, myeloproliferative neoplasms, or other cancers. We also report that DDX41-GPV carriers do not have an increased prevalence of clonal hematopoiesis (CH). In fact, CH was significantly more common before sporadic vs DDX41-mutant MDS/AML, revealing distinct evolutionary paths. Furthermore, somatic mutation rates did not differ between sporadic and DDX41-mutant AML genomes, ruling out genomic instability as a driver of the latter. Finally, we found that higher mean red cell volume (MCV) and somatic DDX41 mutations in blood DNA identify DDX41-GPV carriers at increased MDS/AML risk. Collectively, our findings give new insights into the prevalence and cognate risks associated with DDX41 variants, as well as the clonal evolution and early detection of DDX41-mutant MDS/AML.

Comparison of the transgenic rodent mutation assay, error corrected next generation duplex sequencing, and the alkaline comet assay to detect dose-related mutations following exposure to N-nitrosodiethylamine

N-Nitrosodiethylamine (NDEA), a well-studied N-nitrosamine, was tested in rats to compare the dose-response relationship of three genotoxicity endpoints. Mutant / mutation frequencies were determined using the transgenic rodent (TGR) gene mutation assay and error corrected next generation sequencing (ecNGS) (i.e., duplex sequencing (DS)), and genetic damage was detected by the alkaline comet assay. Big Blue® (cII Locus) animals (n = 6 per dose group) were administered doses of 0.001, 0.01, 0.1, 1, 3 mg/kg/day NDEA by oral gavage. Samples were collected for cII mutation and DS analyses following 28-days of exposure and 3 days recovery. In a separate study, male Sprague-Dawley (SD) rats (n = 6 per dose group) were administered the same doses by oral gavage for two consecutive days and then samples collected for the alkaline comet assay. A dose-related increase in mutant / mutation frequencies of the liver but not duodenum was observed using the TGR assay and DS with DS resulting in a slightly more sensitive response, with a lower benchmark dose (BMD). In addition, a dose-related increase in percent tail DNA was observed in the liver using the alkaline comet assay. Therefore, DS and comet assays showed good utility for hazard identification and dose-response analysis of a representative N-nitrosamine comparable to the TGR gene mutation assay.

MBD4-associated neoplasia syndrome: screening of cases with suggestive phenotypes

Germline mutations in MBD4, which, like MUTYH and NTHL1, encodes a glycosylase of the DNA based excision repair system, cause an autosomal recessive syndrome characterised by increased risk of acute myeloid leukaemia, gastrointestinal polyposis, colorectal cancer (CRC) and, to a lesser extent, uveal melanoma and schwannomas. To better define the phenotypic spectrum and tumour molecular features associated with biallelic MBD4-associated cancer predisposition, and study if heterozygous variants are associated with gastrointestinal tumour predisposition, we evaluated germline MBD4 status in 728 patients with CRC, polyposis, and other suggestive phenotypes (TCGA and in-house cohorts). Eight CRC patients carried rare homozygous or heterozygous germline variants in MBD4. The information gathered on mode of inheritance, variant nature, functional effect of the variant, and tumour mutational characteristics suggested that none of the patients included in the study had an MBD4-associated hereditary syndrome and that the heterozygous variants identified were not associated with the disease.

Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer

HER2-positive (HER2+) breast cancer accounts for 20-25% of all breast cancers. Predictive biomarkers of neoadjuvant therapy response are needed to better identify patients with early stage disease who may benefit from tailored treatments in the adjuvant setting. As part of the TCHL phase-II clinical trial (ICORG10-05/NCT01485926) whole exome DNA sequencing was carried out on normal-tumour pairs collected from 22 patients. Here we report predictive modelling of neoadjuvant therapy response using clinicopathological and genomic features of pre-treatment tumour biopsies identified age, estrogen receptor (ER) status and level of immune cell infiltration may together be important for predicting response. Clonal evolution analysis of longitudinally collected tumour samples show subclonal diversity and dynamics are evident with potential therapy resistant subclones detected. The sources of greater pre-treatment immunogenicity associated with a pathological complete response is largely unexplored in HER2+ tumours. However, here we point to the possibility of APOBEC associated mutagenesis, specifically in the ER-neg/HER2+ subtype as a potential mediator of this immunogenic phenotype.

Mutational signature assignment heterogeneity is widespread and can be addressed by ensemble approaches

Single-base substitution (SBS) mutational signatures have become standard practice in cancer genomics. In lieu of de novo signature extraction, reference signature assignment allows users to estimate the activities of pre-established SBS signatures within individual malignancies. Several tools have been developed for this purpose, each with differing methodologies. However, due to a lack of standardization, there may be inter-tool variability in signature assignment. We deeply characterized three assignment strategies and five SBS signature assignment tools. We observed that assignment strategy choice can significantly influence results and interpretations. Despite varying recommendations by tools, Refit performed best by reducing overfitting and maximizing reconstruction of the original mutational spectra. Even after uniform application of Refit, tools varied remarkably in signature assignments both qualitatively (Jaccard index = 0.38-0.83) and quantitatively (Kendall tau-b = 0.18-0.76). This phenomenon was exacerbated for 'flat' signatures such as the homologous recombination deficiency signature SBS3. An ensemble approach (EnsembleFit), which leverages output from all five tools, increased SBS3 assignment accuracy in BRCA1/2-deficient breast carcinomas. After generating synthetic mutational profiles for thousands of pan-cancer tumors, EnsembleFit reduced signature activity assignment error 15.9-24.7% on average using Catalogue of Somatic Mutations In Cancer and non-standard reference signature sets. We have also released the EnsembleFit web portal (https://www.ensemblefit.pittlabgenomics.com) for users to generate or download ensemble-based SBS signature assignments using any strategy and combination of tools. Overall, we show that signature assignment heterogeneity across tools and strategies is non-negligible and propose a viable, ensemble solution.

Targeting microRNA-145-mediated progressive phenotypes of early bladder cancer in a molecularly defined in vivo model

A progressive subclass of early-stage non-muscle-invasive bladder cancer (NMIBC) frequently recurs and progress into invasive carcinoma, thus decreasing the overall survival rate of NMIBC. However, therapeutic development for progressive NMIBC has been challenging due to the lack of molecularly validated in vivo models and agents targeting its genetic vulnerability. We herein molecularly characterized an interventional model of progressive NMIBC and revealed the principal functions and therapeutic potential of microRNA-145 (miR-145) in early bladder tumorigenesis. N-butyl-N-(4-hydroxybutyl)nitrosamine-induced premalignant lesions (BiPLs) in rats exhibited downregulated expression of miR-145 as well as highly similar mutation/expression profiles to those of the human progressive NMIBC subclass with the worst prognosis. The expression patterns of miR-145 inversely correlated with those of BC-related oncogenes in BiPLs. We also demonstrated that miR-145 dominantly regulated interferon pathways and c-Myc expression, which play a crucial role in the pathogenesis of progressive NMIBC. Furthermore, we demonstrated that miR-145 replacement with a novel miR-145-based intravesical agent (miR-145S1) significantly inhibited the progression of BiPLs in vivo. These results provide insights into the essential role of miR-145 as the earliest-acting oncogenic driver of bladder tumorigenesis as well as a validated interventional model and novel miR-145-based nucleic acid therapeutic agent for progressive NMIBC.

Cross-species oncogenomics offers insight into human muscle-invasive bladder cancer

BACKGROUND

In humans, muscle-invasive bladder cancer (MIBC) is highly aggressive and associated with a poor prognosis. With a high mutation load and large number of altered genes, strategies to delineate key driver events are necessary. Dogs and cats develop urothelial carcinoma (UC) with histological and clinical similarities to human MIBC. Cattle that graze on bracken fern also develop UC, associated with exposure to the carcinogen ptaquiloside. These species may represent relevant animal models of spontaneous and carcinogen-induced UC that can provide insight into human MIBC.

RESULTS

Whole-exome sequencing of domestic canine (n = 87) and feline (n = 23) UC, and comparative analysis with human MIBC reveals a lower mutation rate in animal cases and the absence of APOBEC mutational signatures. A convergence of driver genes (ARID1A, KDM6A, TP53, FAT1, and NRAS) is discovered, along with common focally amplified and deleted genes involved in regulation of the cell cycle and chromatin remodelling. We identify mismatch repair deficiency in a subset of canine and feline UCs with biallelic inactivation of MSH2. Bovine UC (n = 8) is distinctly different; we identify novel mutational signatures which are recapitulated in vitro in human urinary bladder UC cells treated with bracken fern extracts or purified ptaquiloside.

CONCLUSION

Canine and feline urinary bladder UC represent relevant models of MIBC in humans, and cross-species analysis can identify evolutionarily conserved driver genes. We characterize mutational signatures in bovine UC associated with bracken fern and ptaquiloside exposure, a human-linked cancer exposure. Our work demonstrates the relevance of cross-species comparative analysis in understanding both human and animal UC.

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. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no computationally efficient bioinformatics tool that allows visualizing and exploring these large-scale mutational events.

RESULTS

Here, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment.

CONCLUSIONS

The new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/ .

The Vk*MYC Mouse Model recapitulates human multiple myeloma evolution and genomic diversity

Despite advancements in profiling multiple myeloma (MM) and its precursor conditions, there is limited information on mechanisms underlying disease progression. Clincal efforts designed to deconvolute such mechanisms are challenged by the long lead time between monoclonal gammopathy and its transformation to MM. MM mouse models represent an opportunity to overcome this temporal limitation. Here, we profile the genomic landscape of 118 genetically engineered Vk*MYC MM and reveal that it recapitulates the genomic heterogenenity and life history of human MM. We observed recurrent copy number alterations, structural variations, chromothripsis, driver mutations, APOBEC mutational activity, and a progressive decrease in immunoglobulin transcription that inversely correlates with proliferation. Moreover, we identified frequent insertional mutagenesis by endogenous retro-elements as a murine specific mechanism to activate NF-kB and IL6 signaling pathways shared with human MM. Despite the increased genomic complexity associated with progression, advanced tumors remain dependent on MYC expression, that drives the progression of monoclonal gammopathy to MM.

OpenPBTA: The Open Pediatric Brain Tumor Atlas

Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Children's Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.

Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment

Analysis of mutational signatures is a powerful approach for understanding the mutagenic processes that have shaped the evolution of a cancer genome. Here we present SigProfilerAssignment, a desktop and an online computational framework for assigning all types of mutational signatures to individual samples. SigProfilerAssignment is the first tool that allows both analysis of copy-number signatures and probabilistic assignment of signatures to individual somatic mutations. As its computational engine, the tool uses a custom implementation of the forward stagewise algorithm for sparse regression and nonnegative least squares for numerical optimization. Analysis of 2,700 synthetic cancer genomes with and without noise demonstrates that SigProfilerAssignment outperforms four commonly used approaches for assigning mutational signatures. SigProfilerAssignment is freely available at https://github.com/AlexandrovLab/SigProfilerAssignment with a web implementation at https://cancer.sanger.ac.uk/signatures/assignment/.

Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtyping

BACKGROUND

Cancer genome sequencing enables accurate classification of tumours and tumour subtypes. However, prediction performance is still limited using exome-only sequencing and for tumour types with low somatic mutation burden such as many paediatric tumours. Moreover, the ability to leverage deep representation learning in discovery of tumour entities remains unknown.

METHODS

We introduce here Mutation-Attention (MuAt), a deep neural network to learn representations of simple and complex somatic alterations for prediction of tumour types and subtypes. In contrast to many previous methods, MuAt utilizes the attention mechanism on individual mutations instead of aggregated mutation counts.

RESULTS

We trained MuAt models on 2587 whole cancer genomes (24 tumour types) from the Pan-Cancer Analysis of Whole Genomes (PCAWG) and 7352 cancer exomes (20 types) from the Cancer Genome Atlas (TCGA). MuAt achieved prediction accuracy of 89% for whole genomes and 64% for whole exomes, and a top-5 accuracy of 97% and 90%, respectively. MuAt models were found to be well-calibrated and perform well in three independent whole cancer genome cohorts with 10,361 tumours in total. We show MuAt to be able to learn clinically and biologically relevant tumour entities including acral melanoma, SHH-activated medulloblastoma, SPOP-associated prostate cancer, microsatellite instability, POLE proofreading deficiency, and MUTYH-associated pancreatic endocrine tumours without these tumour subtypes and subgroups being provided as training labels. Finally, scrunity of MuAt attention matrices revealed both ubiquitous and tumour-type specific patterns of simple and complex somatic mutations.

CONCLUSIONS

Integrated representations of somatic alterations learnt by MuAt were able to accurately identify histological tumour types and identify tumour entities, with potential to impact precision cancer medicine.

Chromosomal Aberrations Accumulate during Metastasis of Virus-Negative Merkel Cell Carcinoma

Merkel cell carcinoma is a rare, aggressive skin tumor initiated by polyomavirus integration or UV light DNA damage. In New Zealand, there is a propensity toward the UV-driven form (31 of 107, 29% virus positive). Using archival formalin-fixed, paraffin-embedded tissues, we report targeted DNA sequencing covering 246 cancer genes on 71 tumor tissues and 38 nonmalignant tissues from 37 individuals, with 33 of 37 being negative for the virus. Somatic variants of New Zealand virus-negative Merkel cell carcinomas partially overlapped with those reported overseas, including TP53 variants in all tumors and RB1, LRP1B, NOTCH1, and EPHA3/7 variants each found in over half of the cohort. Variants in genes not analyzed or reported in previous studies were also found. Cataloging variants in TP53 and RB1 from published datasets revealed a broad distribution across these genes. Chr 1p gain and Chr 3p loss were identified in around 50% of New Zealand virus-negative Merkel cell carcinomas, and RB1 loss of heterozygosity was found in 90% of cases. Copy number variants accumulate in most metastases. Virus-negative Merkel cell carcinomas have complex combinations of somatic DNA-sequence variants and copy number variants. They likely carry the small genomic changes permissive for metastasis from early tumor development; however, chromosomal alterations may contribute to driving metastatic progression.

Oncogenic structural aberration landscape in gastric cancer genomes

Structural variants (SVs) are responsible for driver events in gastric cancer (GC); however, their patterns and processes remain poorly understood. Here, we examine 170 GC whole genomes to unravel the oncogenic structural aberration landscape in GC genomes and identify six rearrangement signatures (RSs). Non-random combinations of RSs elucidate distinctive GC subtypes comprising one or a few dominant RS that are associated with specific driver events (BRCA1/2 defects, mismatch repair deficiency, and TP53 mutation) and epidemiological backgrounds. Twenty-seven SV hotspots are identified as GC driver candidates. SV hotspots frequently constitute complexly clustered SVs involved in driver gene amplification, such as ERBB2, CCNE1, and FGFR2. Further deconstruction of the locally clustered SVs uncovers amplicon-generating profiles characterized by super-large SVs and intensive segmental amplifications, contributing to the extensive amplification of GC oncogenes. Comprehensive analyses using adjusted SV allele frequencies indicate the significant involvement of extra-chromosomal DNA in processes linked to specific RSs.

Non-BRCA1/BRCA2 high-risk familial breast cancers are not associated with a high prevalence of BRCAness

BACKGROUND

Familial breast cancer is in most cases unexplained due to the lack of identifiable pathogenic variants in the BRCA1 and BRCA2 genes. The somatic mutational landscape and in particular the extent of BRCA-like tumour features (BRCAness) in these familial breast cancers where germline BRCA1 or BRCA2 mutations have not been identified is to a large extent unknown.

METHODS

We performed whole-genome sequencing on matched tumour and normal samples from high-risk non-BRCA1/BRCA2 breast cancer families to understand the germline and somatic mutational landscape and mutational signatures. We measured BRCAness using HRDetect. As a comparator, we also analysed samples from BRCA1 and BRCA2 germline mutation carriers.

RESULTS

We noted for non-BRCA1/BRCA2 tumours, only a small proportion displayed high HRDetect scores and were characterized by concomitant promoter hypermethylation or in one case a RAD51D splice variant previously reported as having unknown significance to potentially explain their BRCAness. Another small proportion showed no features of BRCAness but had mutationally active tumours. The remaining tumours lacked features of BRCAness and were mutationally quiescent.

CONCLUSIONS

A limited fraction of high-risk familial non-BRCA1/BRCA2 breast cancer patients is expected to benefit from treatment strategies against homologue repair deficient cancer cells.

Pan-cancer whole-genome comparison of primary and metastatic solid tumours

Metastatic cancer remains an almost inevitably lethal disease1-3. A better understanding of disease progression and response to therapies therefore remains of utmost importance. Here we characterize the genomic differences between early-stage untreated primary tumours and late-stage treated metastatic tumours using a harmonized pan-cancer analysis (or reanalysis) of two unpaired primary4 and metastatic5 cohorts of 7,108 whole-genome-sequenced tumours. Metastatic tumours in general have a lower intratumour heterogeneity and a conserved karyotype, displaying only a modest increase in mutations, although frequencies of structural variants are elevated overall. Furthermore, highly variable tumour-specific contributions of mutational footprints of endogenous (for example, SBS1 and APOBEC) and exogenous mutational processes (for example, platinum treatment) are present. The majority of cancer types had either moderate genomic differences (for example, lung adenocarcinoma) or highly consistent genomic portraits (for example, ovarian serous carcinoma) when comparing early-stage and late-stage disease. Breast, prostate, thyroid and kidney renal clear cell carcinomas and pancreatic neuroendocrine tumours are clear exceptions to the rule, displaying an extensive transformation of their genomic landscape in advanced stages. Exposure to treatment further scars the tumour genome and introduces an evolutionary bottleneck that selects for known therapy-resistant drivers in approximately half of treated patients. Our data showcase the potential of pan-cancer whole-genome analysis to identify distinctive features of late-stage tumours and provide a valuable resource to further investigate the biological basis of cancer and resistance to therapies.

NR4A3 Expression Is Consistently Absent in Acinic Cell Carcinomas of the Breast: A Potential Nosologic Shift

Acinic cell carcinoma (AciCC) is a tumor that is recognized in both the breast and salivary glands. Recently, the recurrent genomic rearrangement, t(4;9)(q13;q31) was identified in salivary AciCC that results in constitutive upregulation of the nuclear transcription factor NR4A3, which can be detected by immunohistochemistry. In this study, we sought to evaluate NR4A3 expression in breast AciCC using immunohistochemistry. Strong and diffuse nuclear staining was considered a positive result. Sixteen AciCCs were studied, including 8 pure AciCCs and 8 AciCCs admixed with other types (invasive carcinoma of no special type in 5 cases and metaplastic carcinoma in 3 cases). All 16 AciCCs showed negative results for NR4A3 expression. Four cases with available material were evaluated for rearrangements of the NR4A3 gene by fluorescence in situ hybridization and no rearrangements were observed. Whole-genome sequencing of 1 AciCC revealed a TP53 splice-site mutation, high levels of genomic instability, and genomic features of homologous recombination DNA repair defects; a structural variant analysis of this case did not reveal the presence of a t(4;9) rearrangement. We conclude that breast AciCCs consistently lack NR4A3 rearrangement or overexpression, unlike most of the salivary AciCCs, and that consistent with previous results, breast AciCCs are associated with genomic alterations more similar to those seen in triple-negative breast carcinomas than salivary gland AciCCs. These results suggest that unlike other salivary gland-like tumors that occur in the breast, the molecular underpinnings of the salivary gland and breast AciCCs are different and that the salivary gland and breast AciCCs likely represent distinct entities.

Tracking the evolution of therapy-related myeloid neoplasms using chemotherapy signatures

Patients treated with cytotoxic therapies, including autologous stem cell transplantation, are at risk for developing therapy-related myeloid neoplasms (tMN). Preleukemic clones (ie, clonal hematopoiesis [CH]) are detectable years before the development of these aggressive malignancies, although the genomic events leading to transformation and expansion are not well defined. Here, by leveraging distinctive chemotherapy-associated mutational signatures from whole-genome sequencing data and targeted sequencing of prechemotherapy samples, we reconstructed the evolutionary life-history of 39 therapy-related myeloid malignancies. A dichotomy was revealed, in which neoplasms with evidence of chemotherapy-induced mutagenesis from platinum and melphalan were hypermutated and enriched for complex structural variants (ie, chromothripsis), whereas neoplasms with nonmutagenic chemotherapy exposures were genomically similar to de novo acute myeloid leukemia. Using chemotherapy-associated mutational signatures as temporal barcodes linked to discrete clinical exposure in each patient's life, we estimated that several complex events and genomic drivers were acquired after chemotherapy was administered. For patients with prior multiple myeloma who were treated with high-dose melphalan and autologous stem cell transplantation, we demonstrate that tMN can develop from either a reinfused CH clone that escapes melphalan exposure and is selected after reinfusion, or from TP53-mutant CH that survives direct myeloablative conditioning and acquires melphalan-induced DNA damage. Overall, we revealed a novel mode of tMN progression that is not reliant on direct mutagenesis or even exposure to chemotherapy. Conversely, for tMN that evolve under the influence of chemotherapy-induced mutagenesis, distinct chemotherapies not only select preexisting CH but also promote the acquisition of recurrent genomic drivers.

Calcifications in triple-negative breast cancer: Molecular features and treatment strategies

Despite the high prevalence of mammographic calcifications, our understanding remains limited regarding the clinical and molecular features of calcifications within triple-negative breast cancer (TNBC). To investigate the clinical relevance and biological basis of TNBC with calcifications of high suspicion for malignancy, we established a study cohort (N = 312) by integrating mammographic records with clinical data and genomic, transcriptomic, and metabolomic profiling. Despite similar clinicopathological features, patients with highly suspicious calcifications exhibited a worse overall survival than those without. In addition, TNBC with highly suspicious calcifications was characterized by a higher frequency of PIK3CA mutation, lower infiltration of immune cells, and increased abnormality of lipid metabolism. Overall, our study systematically revealed clinical and molecular heterogeneity between TNBC with or without calcifications of high suspicion for malignancy. These data might help to understand the clinical relevance and biological basis of mammographic calcifications.

Pathogenic Variants in Adult-Onset Cancer Predisposition Genes in Pediatric Cancer: Prevalence and Impact on Tumor Molecular Features and Clinical Management

PURPOSE

Clinical genomic sequencing of pediatric tumors is increasingly uncovering pathogenic variants in adult-onset cancer predisposition genes (aoCPG). Nevertheless, it remains poorly understood how often aoCPG variants are of germline origin and whether they influence tumor molecular profiles and/or clinical care. In this study, we examined the prevalence, spectrum, and impacts of aoCPG variants on tumor genomic features and patient management at our institution.

EXPERIMENTAL DESIGN

This is a retrospective study of 1,018 children with cancer who underwent clinical genomic sequencing of their tumors. Tumor genomic data were queried for pathogenic variants affecting 24 preselected aoCPGs. Available tumor whole-genome sequencing (WGS) data were evaluated for second hit mutations, loss of heterozygosity (LOH), DNA mutational signatures, and homologous recombination deficiency (HRD). Patients whose tumors harbored one or more pathogenic aoCPG variants underwent subsequent germline testing based on hereditary cancer evaluation and family or provider preference.

RESULTS

Thirty-three patients (3%) had tumors harboring pathogenic variants affecting one or more aoCPGs. Among 21 tumors with sufficient WGS sequencing data, six (29%) harbored a second hit or LOH affecting the remaining aoCPG allele with four of these six tumors (67%) also exhibiting a DNA mutational signature consistent with the altered aoCPG. Two additional tumors demonstrated HRD, of uncertain relation to the identified aoCPG variant. Twenty-one of 26 patients (81%) completing germline testing were positive for the aoCPG variant in the germline. All germline-positive patients were counseled regarding future cancer risks, surveillance, and risk-reducing measures. No patients had immediate cancer therapy changed due to aoCPG data.

CONCLUSIONS

AoCPG variants are rare in pediatric tumors; however, many originate in the germline. Almost one third of tumor aoCPG variants examined exhibited a second hit and/or conferred an abnormal DNA mutational profile suggesting a role in tumor formation. aoCPG information aids in cancer risk prediction but is not commonly used to alter the treatment of pediatric cancers.

Computational Methods Summarizing Mutational Patterns in Cancer: Promise and Limitations for Clinical Applications

Since the rise of next-generation sequencing technologies, the catalogue of mutations in cancer has been continuously expanding. To address the complexity of the cancer-genomic landscape and extract meaningful insights, numerous computational approaches have been developed over the last two decades. In this review, we survey the current leading computational methods to derive intricate mutational patterns in the context of clinical relevance. We begin with mutation signatures, explaining first how mutation signatures were developed and then examining the utility of studies using mutation signatures to correlate environmental effects on the cancer genome. Next, we examine current clinical research that employs mutation signatures and discuss the potential use cases and challenges of mutation signatures in clinical decision-making. We then examine computational studies developing tools to investigate complex patterns of mutations beyond the context of mutational signatures. We survey methods to identify cancer-driver genes, from single-driver studies to pathway and network analyses. In addition, we review methods inferring complex combinations of mutations for clinical tasks and using mutations integrated with multi-omics data to better predict cancer phenotypes. We examine the use of these tools for either discovery or prediction, including prediction of tumor origin, treatment outcomes, prognosis, and cancer typing. We further discuss the main limitations preventing widespread clinical integration of computational tools for the diagnosis and treatment of cancer. We end by proposing solutions to address these challenges using recent advances in machine learning.