Comparison of Genomic Characterization in Upper Tract Urothelial Carcinoma and Urothelial Carcinoma of the Bladder

Background: Different genomic characterization in urothelial carcinoma (UC) by site of origin, may imply contrasting therapeutic opportunities and pathogenetic mechanisms. The aim of this study was to investigate whether the differences between upper tract urothelial carcinoma (UTUC) and urothelial carcinoma of the bladder (UCB) result from intrinsic biological diversity.Methods: We prospectively sequenced 118 tumors and matched blood DNA from Chinese UC patients using next-generation sequencing (NGS) techniques, including 45 UTUC and 73 UCB.Results: There were marked disparities in the mutational landscape for UC according to race and site of origin. Signature 22 for exposure to aristolochic acid (AA) and signature 10 for defects in polymerase POLE were only observed in the UTUC cohort. Conversely, signature 6 for defective DNA mismatch repair only existed in the UCB cohort. Compared to UCB, UTUC had higher clonal (p<0.001) and subclonal mutation numbers (p=0.015). TP53, PIK3CA, and FGFR3 mutations may be the driver genes for UTUC, whereas for UCB, the driver gene may be BRCA1. UTUC patients had lower PD-L1 than UCB patients. There was no significant difference in the number of DDR mutations, copy number variation (CNV) counts, tumor mutational burden (TMB) or clinical actionability between UTUC and UCB.Conclusions: UTUC and UCB exhibit significant differences in the prevalence of common genomic landscape and carcinogenesis. Consequently, molecular subtypes differ according to location, and these results may have important implications for the site-specific management of patients with urothelial carcinoma. Mutational signature may be used as a screening tool to assist clinical differential diagnosis between UTUC and UCB.

Extensive subclonal mutational diversity in human colorectal cancer and its significance

Human colorectal cancers (CRCs) contain both clonal and subclonal mutations. Clonal driver mutations are positively selected, present in most cells, and drive malignant progression. Subclonal mutations are randomly dispersed throughout the genome, providing a vast reservoir of mutant cells that can expand, repopulate the tumor, and result in the rapid emergence of resistance, as well as being a major contributor to tumor heterogeneity. Here, we apply duplex sequencing (DS) methodology to quantify subclonal mutations in CRC tumor with unprecedented depth (104) and accuracy (<10−7). We measured mutation frequencies in genes encoding replicative DNA polymerases and in genes frequently mutated in CRC, and found an unexpectedly high effective mutation rate, 7.1 × 10−7. The curve of subclonal mutation accumulation as a function of sequencing depth, using DNA obtained from 5 different tumors, is in accord with a neutral model of tumor evolution. We present a theoretical approach to model neutral evolution independent of the infinite-sites assumption (which states that a particular mutation arises only in one tumor cell at any given time). Our analysis indicates that the infinite-sites assumption is not applicable once the number of tumor cells exceeds the reciprocal of the mutation rate, a circumstance relevant to even the smallest clinically diagnosable tumor. Our methods allow accurate estimation of the total mutation burden in clinical cancers. Our results indicate that no DNA locus is wild type in every malignant cell within a tumor at the time of diagnosis (probability of all cells being wild type, 10−308).

Distance measures for tumor evolutionary trees

Motivation There has been recent increased interest in using algorithmic methods to infer the evolutionary tree underlying the developmental history of a tumor. Quantitative measures that compare such trees are vital to a number of different applications including benchmarking tree inference methods and evaluating common inheritance patterns across patients. However, few appropriate distance measures exist, and those that do have low resolution for differentiating trees or do not fully account for the complex relationship between tree topology and the inheritance of the mutations labeling that topology. Results Here, we present two novel distance measures, Common Ancestor Set distance (CASet) and Distinctly Inherited Set Comparison distance (DISC), that are specifically designed to account for the subclonal mutation inheritance patterns characteristic of tumor evolutionary trees. We apply CASet and DISC to multiple simulated datasets and two breast cancer datasets and show that our distance measures allow for more nuanced and accurate delineation between tumor evolutionary trees than existing distance measures. Availability and implementation Implementations of CASet and DISC are freely available at: https://bitbucket.org/oesperlab/stereodist. Supplementary information Supplementary data are available at Bioinformatics online.

Impact of U2AF1 Mutations on Clinical Characteristics and RNA Splicing in Myelodysplastic Syndromes (MDS)

To investigate the clinical impact of U2AF1MT in MDS, we studied a cohort of 511 patients who were performed 112-targeted gene sequencing. We identified U2AF1MT in 86 (17%) subjects, including U2AF1S34F (64%, n=55), U2AF1S34Y (23%, n=20), U2AF1Q157R (6%, n=5), U2AF1Q157P (5%, n=4) and U2AF1R156H (2%, n=2). Compared to many MDS-related gene mutation, U2AF1MT more frequently occurred in younger patients (Median age: 45 vs. 54 yrs; P=0.001). We performed multivariate analysis to characterize the associations between U2AF1MT and other common gene mutations and cytogenetic abnormalities, SF3B1MT (P=0.001, OR=0.214, 95%CI: 0.083-0.55) was inversely associated with U2AF1MT subjects, while isolated +8 (P<0.001, OR=4.671, 95%CI: 2.510-8.689), KRASMT (P=0.008, OR=3.521, 95%CI: 1.388-8.934), and ASXL1MT (P=0.033, OR=2.003, 95%CI: 1.059-3.786) was significantly enriched in U2AF1MT subjects. Using copy number-adjusted VAF, we reconstructed the clonal architecture of U2AF1MT patients to establish whether a U2AF1MT was an ancestral or subclonal mutation. 65 patients with 1 or more mutation, except for U2AF1MT, were analyzed. U2AF1MT was an ancestral mutation in 46 (71%) patients and was a subclonal mutation in 19 (29%) patients. In our cohort, U2AF1MT was associated with worse overall survival (OS, P=0.01). Considering for different type of U2AF1MT, MDS patients with U2AF1Q157/R156MT tended to have a reduced median survival as opposed to patients with S34 (17 vs. 30 months, P=0.318). Then, we performed a comprehensive and systematic analysis to determine the impact of U2AF1MT on pre-mRNA splicing in bone marrow mononuclear cells from 40 patients and 5 healthy controls. We identified 315 misregulated splicing events between patients with U2AF1MT (n=20) and those without any spliceosome mutations (n=17) (Figure 1A). U2AF1MT were associated with a higher proportion of exon skipping (SE, 68%), mutually exclusive exons (MXE, 19%) and alternative 3′ splice site (A3SS, 8%) usage events (Figure 1B). Interestingly, only one gene (MRS2, Magnesium Transporter MRS2) with significantly dysregulated expression was observed from the aberrantly spliced genes. Gene ontology (GO) analysis was performed on the genes showing significant aberrant splicing events and the analysis showed a strong cluster of GOs associated with histone modification, RNA metabolism and cell cycle processing. Gene set enrichment analysis (GSEA) revealed DNA damage response pathway, including DNA Repair and p53 pathway as one of the major gene sets up regulated upon U2AF1MT (Figure 2). Then, the single cell RNA-sequencing was performed in Lin-CD34+CD38-CD90+CD45RA- hematopoietic stem cell (HSC) from one sample with U2AF1MT. After QC filtering, 5 HSC with U2AF1MT and 47 HSC without any spliceosome mutations were used for aberrant splicing events analysis. Totally, 1752 misregulated splicing events were indentified (Figure 3A). Forty three genes with significantly dysregulated expression were observed from the aberrantly spliced genes, including 6 genes (TP53BP1, MDM2, PRC1, RAD51C, IP6K2, TMBIM6) taking part in DNA damage response (Figure 3B). In summary, this comprehensive study provides novel insights into U2AF1MT MDS disease pathophysiology, with newly identified clinical associations, and dysregulated genes and pathways representing potential new therapeutic targets. Disclosures No relevant conflicts of interest to declare.

Leptomeningeal spread of glioma in the molecular era.

e13537 Background: Leptomeningeal disease (LMD) is an uncommon event in patients with gliomas which is estimated to occur in 4% of cases and is associated with poor outcome. Genomic alterations in gliomas that precipitate LMD have not been characterized. Methods: We performed a retrospective chart review of patients with gliomas (grade II-IV)- for whom we have genomic testing data at The Ohio State University. We identified patients who developed LMD. LMD was defined as leptomeningeal enhancement as seen on brain or spine imaging. Patients with negative cerebrospinal fluid (CSF) cytology were not excluded if imaging was convincing of LMD. Genomic testing was performed through Foundation One. Results: 129 charts of glioma patients were reviewed. We identified 6 patients with LMD. One is still alive. All patients were diagnosed histologically as glioblastoma. One patient had Lynch syndrome. All patients were men with a median age at diagnosis of 44 (range 20-65). All tumors appeared to have extended into the ventricles on brain imaging. 4 tumors had evidence of subependymal spread prior (range 45-93 days) or at the time of LMD enhancement. 4 patients had available CSF studies: 2 of whom had evidence of atypical or malignant cells. CSF protein was elevated in all four samples (range 113-492 mg/dL). CSF glucose was low in all four samples (range < 10-46 mg/dL). 5 tumor samples were IDH wild type whereas 1 had IDH1 R132H mutation. MGMT promoter was methylated in 3 tumors and unmethylated in 3. The genomic alterations varied among samples and included EGFR V765M mutation (N = 1), PDGFR amplification (N = 1), PDGFRA Y849C subclonal mutation (N = 1), CDKN2A/B loss (N = 3), TP53 mutations (N = 4) and TERT promoter mutations (N = 3). No case had EGFR amplification or EGFRvIII mutation. Other alterations observed included DNMT3A mutation, KIT, MYC and MDM2 amplifications and RB1 losses. PD-L1 expression ranged from 5-40%. One intracranial sample had a 20% PD-L1 expression with LMD from this tumor exhibiting 40% PD-L1 expression. Of the five deceased patients (all IDH WT), median overall survival (OS) was 355 days (range 184-557). Median OS after LMD diagnosis was 84 days (range 58-225). Conclusions: In this series, 4.5% of glioma patients developed LMD. Samples were associated with a variety of genomic alterations but without a specific predictor of leptomeningeal involvement. This is possibly due to the small number of cases. Physical proximity of the tumor to the ventricles appears to be a potential risk factor. Larger studies of LMD in gliomas are warranted to identify potential genetic drivers, if any exist.

Distance Measures for Tumor Evolutionary Trees

In recent years, there has been increased interest in studying cancer by using algorithmic methods to infer the evolutionary tree underlying a tumor’s developmental history. Quantitative measures that compare such trees are then vital to benchmarking these algorithmic tree inference methods, understanding the structure of the space of possible trees for a given dataset, and clustering together similar trees in order to evaluate inheritance patterns. However, few appropriate distance measures exist, and those that do exist have low resolution for differentiating trees or do not fully account for the complex relationship between tree topology and how the mutations that label that topology are inherited. Here we present two novel distance measures,CommonAncestorSetdistance (CASet) andDistinctlyInheritedSetComparison distance (DISC), that are specifically designed to account for the subclonal mutation inheritance patterns characteristic of tumor evolutionary trees. We apply CASet and DISC to two simulated and two breast cancer datasets and show that our distance measures allow for more nuanced and accurate delineation between tumor evolutionary trees than existing distance measures. Implementations of CASet and DISC are available at:https://bitbucket.org/oesperlab/stereodist.

On measuring selection in cancer from subclonal mutation frequencies

ABSTRACTRecently available cancer sequencing data have revealed a complex view of the cancer genome containing a multitude of mutations, including drivers responsible for cancer progression and neutral passengers. Measuring selection in cancer and distinguishing drivers from passengers have important implications for development of novel treatment strategies. It has recently been argued that a third of cancers are evolving neutrally, as their mutational frequency spectrum follows a 1/f power law expected from neutral evolution in a particular intermediate frequency range. We study a stochastic model of cancer evolution and derive a formula for the probability distribution of the cancer cell frequency of a subclonal driver, demonstrating that driver frequency is biased towards 0 and 1. We show that it is difficult to capture a driver mutation at an intermediate frequency, and thus the calling of neutrality due to a lack of such driver will significantly overestimate the number of neutrally evolving tumors. Our approach provides precise quantification of the validity of the 1/f statistic across the entire range of all relevant parameter values. Our results are also applicable to the question of distinguishing driver and passenger mutations in a general exponentially expanding population.