Rosa Karlic

Cell-of-origin chromatin organization shapes the mutational landscape of cancer

Cancer is a disease potentiated by mutations in somatic cells. Cancer mutations are not distributed uniformly along the human genome. Instead, different human genomic regions vary by up to fivefold in the local density of cancer somatic mutations, posing a fundamental problem for statistical methods used in cancer genomics. Epigenomic organization has been proposed as a major determinant of the cancer mutational landscape. However, both somatic mutagenesis and epigenomic features are highly cell-type-specific. We investigated the distribution of mutations in multiple independent samples of diverse cancer types and compared them to cell-type-specific epigenomic features. Here we show that chromatin accessibility and modification, together with replication timing, explain up to 86% of the variance in mutation rates along cancer genomes. The best predictors of local somatic mutation density are epigenomic features derived from the most likely cell type of origin of the corresponding malignancy. Moreover, we find that cell-of-origin chromatin features are much stronger determinants of cancer mutation profiles than chromatin features of matched cancer cell lines. Furthermore, we show that the cell type of origin of a cancer can be accurately determined based on the distribution of mutations along its genome. Thus, the DNA sequence of a cancer genome encompasses a wealth of information about the identity and epigenomic features of its cell of origin.

A mutational signature reveals alterations underlying deficient homologous recombination repair in breast cancer

Biallelic inactivation of BRCA1 or BRCA2 is associated with a pattern of genome-wide mutations known as signature 3. By analyzing ∼1,000 breast cancer samples, we confirmed this association and established that germline nonsense and frameshift variants in PALB2, but not in ATM or CHEK2, can also give rise to the same signature. We were able to accurately classify missense BRCA1 or BRCA2 variants known to impair homologous recombination (HR) on the basis of this signature. Finally, we show that epigenetic silencing of RAD51C and BRCA1 by promoter methylation is strongly associated with signature 3 and, in our data set, was highly enriched in basal-like breast cancers in young individuals of African descent.

Long non-coding RNA exchange during the oocyte-to-embryo transition in mice

Abstract The oocyte-to-embryo transition (OET) transforms a differentiated gamete into pluripotent blastomeres. The accompanying maternal-zygotic RNA exchange involves remodeling of the long non-coding RNA (lncRNA) pool. Here, we used next generation sequencing and de novo transcript assembly to define the core population of 1,600 lncRNAs expressed during the OET (lncRNAs). Relative to mRNAs, OET lncRNAs were less expressed and had shorter transcripts, mainly due to fewer exons and shorter 5′ terminal exons. Approximately half of OET lncRNA promoters originated in retrotransposons suggesting their recent emergence. Except for a small group of ubiquitous lncRNAs, maternal and zygotic lncRNAs formed two distinct populations. The bulk of maternal lncRNAs was degraded before the zygotic genome activation. Interestingly, maternal lncRNAs seemed to undergo cytoplasmic polyadenylation observed for dormant mRNAs. We also identified lncRNAs giving rise to trans-acting short interfering RNAs, which represent a novel lncRNA category. Altogether, we defined the core OET lncRNA transcriptome and characterized its remodeling during early development. Our results are consistent with the notion that rapidly evolving lncRNAs constitute signatures of cells-of-origin while a minority plays an active role in control of gene expression across OET. Our data presented here provide an excellent source for further OET lncRNA studies.

Analysis of somatic microsatellite indels identifies driver events in human tumors

Microsatellites (MSs) are tracts of variable-length repeats of short DNA motifs that exhibit high rates of mutation in the form of insertions or deletions (indels) of the repeated motif. Despite their prevalence, the contribution of somatic MS indels to cancer has been largely unexplored, owing to difficulties in detecting them in short-read sequencing data. Here we present two tools: MSMuTect, for accurate detection of somatic MS indels, and MSMutSig, for identification of genes containing MS indels at a higher frequency than expected by chance. Applying MSMuTect to whole-exome data from 6,747 human tumors representing 20 tumor types, we identified >1,000 previously undescribed MS indels in cancer genes. Additionally, we demonstrate that the number and pattern of MS indels can accurately distinguish microsatellite-stable tumors from tumors with microsatellite instability, thus potentially improving classification of clinically relevant subgroups. Finally, we identified seven MS indel driver hotspots: four in known cancer genes (ACVR2A, RNF43, JAK1, and MSH3) and three in genes not previously implicated as cancer drivers (ESRP1, PRDM2, and DOCK3).

Genomic characterization of biliary tract cancers identifies driver genes and predisposing mutations

BACKGROUND & AIMS Biliary tract cancers (BTCs) are clinically and pathologically heterogeneous and respond poorly to treatment. Genomic profiling can offer a clearer understanding of their carcinogenesis, classification and treatment strategy. We performed large-scale genome sequencing analyses on BTCs to investigate their somatic and germline driver events and characterize their genomic landscape. METHODS We analyzed 412 BTC samples from Japanese and Italian populations, 107 by whole-exome sequencing (WES), 39 by whole-genome sequencing (WGS), and a further 266 samples by targeted sequencing. The subtypes were 136 intrahepatic cholangiocarcinomas (ICCs), 101 distal cholangiocarcinomas (DCCs), 109 peri-hilar type cholangiocarcinomas (PHCs), and 66 gallbladder or cystic duct cancers (GBCs/CDCs). We identified somatic alterations and searched for driver genes in BTCs, finding pathogenic germline variants of cancer-predisposing genes. We predicted cell-of-origin for BTCs by combining somatic mutation patterns and epigenetic features. RESULTS We identified 32 significantly and commonly mutated genes including TP53, KRAS, SMAD4, NF1, ARID1A, PBRM1, and ATR, some of which negatively affected patient prognosis. A novel deletion of MUC17 at 7q22.1 affected patient prognosis. Cell-of-origin predictions using WGS and epigenetic features suggest hepatocyte-origin of hepatitis-related ICCs. Deleterious germline mutations of cancer-predisposing genes such as BRCA1, BRCA2, RAD51D, MLH1, or MSH2 were detected in 11% (16/146) of BTC patients. CONCLUSIONS BTCs have distinct genetic features including somatic events and germline predisposition. These findings could be useful to establish treatment and diagnostic strategies for BTCs based on genetic information. LAY SUMMARY We here analyzed genomic features of 412 BTC samples from Japanese and Italian populations. A total of 32 significantly and commonly mutated genes were identified, some of which negatively affected patient prognosis, including a novel deletion of MUC17 at 7q22.1. Cell-of-origin predictions using WGS and epigenetic features suggest hepatocyte-origin of hepatitis-related ICCs. Deleterious germline mutations of cancer-predisposing genes were detected in 11% of patients with BTC. BTCs have distinct genetic features including somatic events and germline predisposition.

Abstract 3304: The mutation landscape of cancers serves as a record of early malignant transformation

How the cell lineage influences a tissue9s susceptibility to malignant transformation is a fundamental question in cancer biology, which has been barely addressed in cancer genomics thus far. Cell properties are encoded in the cell type-specific chromatin structure and we previously demonstrated that the cell-of-origin (COO) chromatin organization is a key determinant of the landscape of somatic mutations, which accumulated over lifetime serving as a memory of the historical cell lineage (Polak et al, Nature , 2015). We now show that this principle is generalizable to common tumor types and offers insights into the molecular events of cancer initiation. We extended our work to 2,641 genomes from 30 cancer types and epigenetic modifications from 98 normal tissues. In 25 cancer types, the tumor originated from a cell type that was its direct cellular counterpart or a close proxy; in only two, there was no match or a close proxy; and in the remaining three (esophageal, pancreatic ductal and biliary adenocarcinoma) the best matched cell type suggested metaplasia to stomack mucosa like tissue.The cellular context of breast tumor formation was investigated in more detail, showing that the COO, and not the gene inactivation event, determines the subtype. Basal-like tumors appeared to arise from luminal progenitor cells, while all other subtypes arose from mature luminal cells. Furthermore, irrespective of the inactivation mechanism (pathogenic germline, somatic truncating or epigenetic silencing event), all BRCA1/2- and RAD51C-altered basal-like tumors best matched to luminal progenitors while BRCA1/2- and CHEK2 -mutated luminal A/B subtypes best matched mature luminal cells. Finally, we observed that tumor type-specific driver genes reside in genomic regions that are defined by a highly active chromatin environment in their COOs. This highlights their essential role in cell type differentiation and implies the acquisition of somatic mutations early, when the chromatin architecture still reflected the COO. Taken together, our findings shed light on the crucial role of the COO in shaping the mutational landscape and tumor evolution. Citation Format: Paz Polak, Rosa Karlic, Kirsten Kubler, William D. Foulkes, Gad Getz. The mutation landscape of cancers serves as a record of early malignant transformation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3304.

Accurate Discrimination of 23 Major Cancer Types via Whole Genome Somatic Mutation Patterns

In cancer, the primary tumour’s organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of the time a cancer patient presents with metastatic tumour and no obvious primary. Challenges also arise when distinguishing a metastatic recurrence of a previously treated cancer from the emergence of a new one. Here we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types. Our classifier achieves an accuracy of 91% on held-out tumor samples and 82% and 85% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced classifier accuracy. Our results have immediate clinical applicability, underscoring how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of cell-free circulating tumour DNA.The two strongest factors predicting a human cancer9s clinical behaviour are the primary tumour9s anatomic organ of origin and its histopathology. However, roughly 3% of the time a cancer presents with metastatic disease and no primary can be determined even after a thorough radiological survey. A related dilemma arises when a radiologically defined mass is sampled by cytology yielding cancerous cells, but the cytologist cannot distinguish between a primary tumour and a metastasis from elsewhere. Here we use whole genome sequencing (WGS) data from the ICGC/TCGA PanCancer Analysis of Whole Genomes (PCAWG) project to develop a machine learning classifier able to accurately distinguish among 23 major cancer types using information derived from somatic mutations alone. This demonstrates the feasibility of automated cancer type discrimination based on next-generation sequencing of clinical samples. In addition, this work opens the possibility of determining the origin of tumours detected by the emerging technology of deep sequencing of circulating cell-free DNA in blood plasma.

Abstract LB-280: The landscape of somatic microsatellite indels across cancer: detection and identification of driver events

Microsatellites (MSs) are tracts of variable-length repeats of short DNA motifs that are abundant in the human genome and exhibit high rates of mutations in the form of insertions or deletions of the repeated motif (MS indels). Despite their prevalence, the contribution of somatic MS indels to cancer is largely unexplored due to difficulties in detecting them and assessing their significance. Here, we present a comprehensive analysis of MS indels across 20 tumor types. We characterize the overall MS indel landscape and detect genes with candidate driver MS indel events. We present two novel tools: MSMuTect for accurate detection of somatic MS indels and MSMutSig for identifying candidate cancer genes containing events at higher frequency than expected by chance. We observe high variability of the frequency of MS indels across tumors and demonstrate that the number and pattern of MS indels can accurately distinguish microsatellite stable (MSS) tumors from tumors with microsatellite instability (MSI). Applying MSMutSig across 6,788 tumors from 20 different tumor types identified 7 genes with significant MS indel hotspots: ACVR2A, RNF43, DOCK3, MSH3, ESRP1, PRDM2 and JAK1. In the four genes that have been previously implicated in cancer (ACVR2A, RNF43, JAK1 and MSH3), we identified previously unreported MS indels events. Three of the genes with significant loci - DOCK3, PRDM2 and ESRP1- had not been previously listed as cancer genes. MS indels in DOCK3, a negative regulator of the WNT pathway, were mutually exclusive with mutations in CTNNB1. MS indels in ESRP1, an RNA processing gene, correlated with alternative splicing of FGFR2, an event associated with the epithelial-to-mesenchymal transition. Overall, our comprehensive analysis of somatic MS indels across cancer highlights their importance, particularly in MSI tumors, significantly contributes to the ongoing global efforts to detect cancer genes, and may improve classification of patients into clinically-relevant subgroups. Citation Format: Yosef E. Maruvka, Kent W. Mouw, Rosa Karlic, Rasanna Parasuraman, Atanas Kamburov, Paz Polak, Nicholas J. Haradhvala, Julian M. Hess, Esther Rheinbay, Yehuda Brody, Lior Z. Braunstein, Alan D’Andrea, Michael S. Lawrence, Adam Bass, Andre Bernards, Franziska Michor, Gad Getz. The landscape of somatic microsatellite indels across cancer: detection and identification of driver events [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-280. doi:10.1158/1538-7445.AM2017-LB-280