Matthew P. Salomon

Population genomic analysis uncovers African and European admixture in Drosophila melanogaster populations from the south‐eastern United States and Caribbean Islands

Drosophila melanogaster is postulated to have colonized North America in the past several 100 years in two waves. Flies from Europe colonized the east coast United States while flies from Africa inhabited the Caribbean, which if true, make the south‐east US and Caribbean Islands a secondary contact zone for African and European D. melanogaster. This scenario has been proposed based on phenotypes and limited genetic data. In our study, we have sequenced individual whole genomes of flies from populations in the south‐east US and Caribbean Islands and examined these populations in conjunction with population sequences from the west coast US, Africa, and Europe. We find that west coast US populations are closely related to the European population, likely reflecting a rapid westward expansion upon first settlements into North America. We also find genomic evidence of African and European admixture in south‐east US and Caribbean populations, with a clinal pattern of decreasing proportions of African ancestry with higher latitude. Our genomic analysis of D. melanogaster populations from the south‐east US and Caribbean Islands provides more evidence for the Caribbean Islands as the source of previously reported novel African alleles found in other east coast US populations. We also find the border between the south‐east US and the Caribbean island to be the admixture hot zone where distinctly African‐like Caribbean flies become genomically more similar to European‐like south‐east US flies. Our findings have important implications for previous studies examining the generation of east coast US clines via selection.

Many private mutations originate from the first few divisions of a human colorectal adenoma.

Intratumoural mutational heterogeneity (ITH) or the presence of different private mutations in different parts of the same tumour is commonly observed in human tumours. The mechanisms generating such ITH are uncertain. Here we find that ITH can be remarkably well structured by measuring point mutations, chromosome copy numbers, and DNA passenger methylation from opposite sides and individual glands of a 6 cm human colorectal adenoma. ITH was present between tumour sides and individual glands, but the private mutations were side‐specific and subdivided the adenoma into two major subclones. Furthermore, ITH disappeared within individual glands because the glands were clonal populations composed of cells with identical mutant genotypes. Despite mutation clonality, the glands were relatively old, diverse populations when their individual cells were compared for passenger methylation and by FISH. These observations can be organized into an expanding star‐like ancestral tree with co‐clonal expansion, where many private mutations and multiple related clones arise during the first few divisions. As a consequence, most detectable mutational ITH in the final tumour originates from the first few divisions. Much of the early history of a tumour, especially the first few divisions, may be embedded within the detectable ITH of tumour genomes. Copyright

Mechanisms of immune evasion in triple-negative breast cancer patients.

1096Background: Immunotherapy has shown promising results in enhancing response rates for patients with triple-negative breast cancer (TNBC). The success of immunotherapy is affected by poor tumor antigen presentation. This immune evasion is facilitated by genetic and epigenetic alterations, including aberrant RNA splicing (AS). Here we examined the role of PTBP1, a key RNA splicing factor related to immune evasion in TNBC. Methods: Clinical and gene expression data from 3,614 breast cancer patients included in the METABRIC and TCGA projects were evaluated to identify the impact of PTBP1 on TNBC. Univariate and multivariate statistical modeling was performed to test the association of PTBP1 expression with relapse-free survival (RFS), disease-free survival (DFS), and overall survival (OS). CRISPR-Cas9 technology, followed by RNA sequencing (RNA-Seq) was utilized to identify differentially activated pathways in a TNBC cell model (MDA-MB-231). A portrait of infiltrating immune cells was compiled using the x...

Natural variation of gene models in Drosophila melanogaster.

BackgroundVariation within splicing regulatory sequences often leads to differences in gene models among individuals within a species. Two alleles of the same gene may express transcripts with different exon/intron structures and consequently produce functionally different proteins. Matching genomic and transcriptomic data allows us to identify putative regulatory variants associated with changes in splicing patterns.ResultsHere we analyzed natural variation of splicing patterns in the transcriptomes of 81 natural strains of Drosophila melanogaster with known genotypes. We identified dozens of genotype-specific splicing patterns associated with putative cis-splicing quantitative trait loci (sQTL). The majority of changes can be explained by mutations in splice sites. Allelic-imbalance in splicing patterns confirmed that the majority are regulated mainly by cis-genetic effects. Remarkably, allele-specific splicing changes often lead to qualitative changes in gene models, yielding many isoforms not previously annotated. The observed alterations are typically outside protein-coding regions or affect only very short protein segments.ConclusionsOverall, the sets of gene models appear to be flexible within D. melanogaster populations. The observed variation in splicing patterns are predicted to have limited effects on the encoded protein sequences. To our knowledge, this is the first sQTL mapping study in Drosophila.

GWASeq: targeted re-sequencing follow up to GWAS

BackgroundFor the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called “missing” heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS.ResultsWe investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called ‘SNP-set’ tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer.ConclusionsHere we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.

Epigenetic Profiling for the Molecular Classification of Metastatic Brain Tumors

Optimal treatment of brain metastases is often hindered by limitations in diagnostic capabilities. To meet these challenges, we generated genome-scale DNA methylomes of the three most frequent types of brain metastases: melanoma, breast, and lung cancers (n=96). Using supervised machine learning and integration of multiple DNA methylomes from normal, primary, and metastatic tumor specimens (n=1,860), we unraveled epigenetic signatures specific to each type of metastatic brain tumor and constructed a three-step DNA methylation-based classifier (BrainMETH) that categorizes brain metastases according to the tissue of origin and therapeutically-relevant subtypes. BrainMETH predictions were supported by routine histopathologic evaluation. We further characterized and validated the most predictive genomic regions in a large cohort of brain tumors (n=165) using quantitative methylation-specific PCR. Our study highlights the importance of brain tumor-defining epigenetic alterations, which can be utilized to further develop DNA methylation profiling as a critical tool in the histomolecular stratification of patients with brain metastases.

Early mutation bursts in colorectal tumors

Tumor growth is an evolutionary process involving accumulation of mutations, copy number alterations, and cancer stem cell (CSC) division and differentiation. As direct observation of this process is impossible, inference regarding when mutations occur and how stem cells divide is difficult. However, this ancestral information is encoded within the tumor itself, in the form of intratumoral heterogeneity of the tumor cell genomes. Here we present a framework that allows simulation of these processes and estimation of mutation rates at the various stages of tumor development and CSC division patterns for single-gland sequencing data from colorectal tumors. We parameterize the mutation rate and the CSC division pattern, and successfully retrieve their posterior distributions based on DNA sequence level data. Our approach exploits Approximate Bayesian Computation (ABC), a method that is becoming widely-used for problems of ancestral inference.

Abstract B2-23: A Big Bang model of human colorectal tumor growth

What happens in the early and still undetectable human malignancy is unknown because direct observations are impractical. Here we present a “Big Bang” model, whereby a tumor grows predominantly as a single expansion producing numerous intermixed sub-clones, which are not subject to stringent clonal selection. In this model, both public and most detectable private mutations arise during the earliest phase of tumor growth. Multi-scale genomic profiling of 349 individual glands sampled from 15 colorectal tumors revealed the absence of selective sweeps, uniformly high intra-tumor heterogeneity, and sub-clone mixing in distant tumor regions, as postulated by the Big Bang. By integrating the data in a spatial model of tumor growth and statistical inference framework we also verified the most striking prediction of our model, namely that most detectable intra-tumor heterogeneity originates from private alterations acquired early during growth, and not from the later expansion of selected sub-clones. Hence, early sub-clones define the genomic profile of colorectal carcinomas and advanced adenomas, whereas potentially dangerous late-arising sub-clones will go undetected. Moreover, our results suggest that sub-clone mixing may be a biomarker of malignant potential. This new model provides a quantitative framework that explains the origins of intra-tumor heterogeneity and tumor growth dynamics with significant clinical implications. Citation Format: Andrea Sottoriva, Haeyoun Kang, Zhicheng Ma, Trevor A. Graham, Matthew Salomon, Junsong Zhao, Paul Marjoram, Kim Siegmund, Michael F. Press, Darryl Shibata, Christina Curtis. A Big Bang model of human colorectal tumor growth. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-23.

Humanin Prevents Age-Related Cognitive Decline in Mice and is Associated with Improved Cognitive Age in Humans

Advanced age is associated with a decline in cognitive function, likely caused by a combination of modifiable and non-modifiable factors such as genetics and lifestyle choices. Mounting evidence suggests that humanin and other mitochondrial derived peptides play a role in several age-related conditions including neurodegenerative disease. Here we demonstrate that humanin administration has neuroprotective effects in vitro in human cell culture models and is sufficient to improve cognition in vivo in aged mice. Furthermore, in a human cohort, using mitochondrial GWAS, we identified a specific SNP (rs2854128) in the humanin-coding region of the mitochondrial genome that is associated with a decrease in circulating humanin levels. In a large, independent cohort, consisting of a nationally-representative sample of older adults, we find that this SNP is associated with accelerated cognitive aging, supporting the concept that humanin is an important factor in cognitive aging.

Multiplex Gene Profiling of Cell-Free DNA in Patients With Metastatic Melanoma for Monitoring Disease

Purpose Hotspot blood cell-free DNA (cfDNA) biomarker assays have limited utility in profiling tumor heterogeneity and burden and in capturing regional metastasis with low disease burden in patients with melanoma. We investigated the utility of a sensitive 54-cancer gene digital next-generation sequencing approach targeting blood cfDNA single nucleotide variants (SNVs) and copy number amplification for monitoring disease in patients with melanoma with regional or distant organ metastasis (DOM). Patients and Methods A total of 142 blood samples were evaluated by digital next-generation sequencing across two patient cohorts. Cohort 1 contained 44 patients with stage II, III, or IV disease with matched tumor DNA at the time of surgery or DOM. Cohort 2 consisted of 12 overlapping patients who were longitudinally monitored after complete lymph node dissection to DOM. Results In cohort 1, cfDNA SNVs were detected in 75% of patients. Tumor-cfDNA somatic SNV concordance was 85% at a variant allele fraction of ≥ 0.5%. An SNV load (number of unique SNVs detected) of greater than two SNVs and an SNV burden (total cumulative SNV VAF) of > 0.5% were significantly associated with worse overall survival (P < .05) in stage IV patients. In cohort 2, 98 longitudinal blood samples along with matched regional and distant metastases from 12 stage III patients were analyzed before complete lymph node dissection and throughout disease progression. cfDNA SNV levels correlated with tumor burden (P = .019), enabled earlier detection of recurrence compared with radiologic imaging (P < .01), captured tumor heterogeneity, and identified increasing SNVs levels before recurrence. Conclusion This study demonstrates significant utility for cfDNA profiling in patients with melanoma with regional and/or distant metastasis for earlier detection of recurrence and progression and in capturing tumor evolution and heterogeneity, thus impacting how patients with melanoma are monitored.