Ali Bashashati

Per-Channel Basis Normalization Methods for Flow Cytometry Data

Between‐sample variation in high‐throughput flow cytometry data poses a significant challenge for analysis of large‐scale data sets, such as those derived from multicenter clinical trials. It is often hard to match biologically relevant cell populations across samples because of technical variation in sample acquisition and instrumentation differences. Thus, normalization of data is a critical step before analysis, particularly in large‐scale data sets from clinical trials, where group‐specific differences may be subtle and patient‐to‐patient variation common. We have developed two normalization methods that remove technical between‐sample variation by aligning prominent features (landmarks) in the raw data on a per‐channel basis. These algorithms were tested on two independent flow cytometry data sets by comparing manually gated data, either individually for each sample or using static gating templates, before and after normalization. Our results show a marked improvement in the overlap between manual and static gating when the data are normalized, thereby facilitating the use of automated analyses on large flow cytometry data sets. Such automated analyses are essential for high‐throughput flow cytometry.

Histological Transformation and Progression in Follicular Lymphoma: A Clonal Evolution Study

Background Follicular lymphoma (FL) is an indolent, yet incurable B cell malignancy. A subset of patients experience an increased mortality rate driven by two distinct clinical end points: histological transformation and early progression after immunochemotherapy. The nature of tumor clonal dynamics leading to these clinical end points is poorly understood, and previously determined genetic alterations do not explain the majority of transformed cases or accurately predict early progressive disease. We contend that detailed knowledge of the expansion patterns of specific cell populations plus their associated mutations would provide insight into therapeutic strategies and disease biology over the time course of FL clinical histories. Methods and Findings Using a combination of whole genome sequencing, targeted deep sequencing, and digital droplet PCR on matched diagnostic and relapse specimens, we deciphered the constituent clonal populations in 15 transformation cases and 6 progression cases, and measured the change in clonal population abundance over time. We observed widely divergent patterns of clonal dynamics in transformed cases relative to progressed cases. Transformation specimens were generally composed of clones that were rare or absent in diagnostic specimens, consistent with dramatic clonal expansions that came to dominate the transformation specimens. This pattern was independent of time to transformation and treatment modality. By contrast, early progression specimens were composed of clones that were already present in the diagnostic specimens and exhibited only moderate clonal dynamics, even in the presence of immunochemotherapy. Analysis of somatic mutations impacting 94 genes was undertaken in an extension cohort consisting of 395 samples from 277 patients in order to decipher disrupted biology in the two clinical end points. We found 12 genes that were more commonly mutated in transformed samples than in the preceding FL tumors, including TP53, B2M, CCND3, GNA13, S1PR2, and P2RY8. Moreover, ten genes were more commonly mutated in diagnostic specimens of patients with early progression, including TP53, BTG1, MKI67, and XBP1. Conclusions Our results illuminate contrasting modes of evolution shaping the clinical histories of transformation and progression. They have implications for interpretation of evolutionary dynamics in the context of treatment-induced selective pressures, and indicate that transformation and progression will require different clinical management strategies.

Pairwise network mechanisms in the host signaling response to coxsackievirus B3 infection

Signal transduction networks can be perturbed biochemically, genetically, and pharmacologically to unravel their functions. But at the systems level, it is not clear how such perturbations are best implemented to extract molecular mechanisms that underlie network function. Here, we combined pairwise perturbations with multiparameter phosphorylation measurements to reveal causal mechanisms within the signaling network response of cardiomyocytes to coxsackievirus B3 (CVB3) infection. Using all possible pairs of six kinase inhibitors, we assembled a dynamic nine-protein phosphorylation signature of perturbed CVB3 infectivity. Cluster analysis of the resulting dataset showed repeatedly that paired inhibitor data were required for accurate data-driven predictions of kinase substrate links in the host network. With pairwise data, we also derived a high-confidence network based on partial correlations, which identified phospho-IκBα as a central “hub” in the measured phosphorylation signature. The reconstructed network helped to connect phospho-IκBα with an autocrine feedback circuit in host cells involving the proinflammatory cytokines, TNF and IL-1. Autocrine blockade substantially inhibited CVB3 progeny release and improved host cell viability, implicating TNF and IL-1 as cell autonomous components of CVB3-induced myocardial damage. We conclude that pairwise perturbations, when combined with network-level intracellular measurements, enrich for mechanisms that would be overlooked by single perturbants.

Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates

Significance The study of cell-to-cell genomic differences in complex multicellular systems such as cancer requires genome sequencing of large numbers of single cells. This in turn necessitates the uniform amplification of single-cell genomes with high reproducibility across large numbers of cells, which remains an outstanding challenge. Here, we introduce a method that uses commercially available liquid dispensing to perform inexpensive and high-throughput single-cell whole genome amplification (WGA) in nanoliter volumes. For the first time, to our knowledge, we demonstrate robust and highly uniform nanoliter-volume single-cell WGA across a large replicate set consisting of more than 100 single cells. Comparison with previous datasets shows that this method improves uniformity and achieves levels of genome coverage and genomic variant detection comparable or superior to existing methods. The genomes of large numbers of single cells must be sequenced to further understanding of the biological significance of genomic heterogeneity in complex systems. Whole genome amplification (WGA) of single cells is generally the first step in such studies, but is prone to nonuniformity that can compromise genomic measurement accuracy. Despite recent advances, robust performance in high-throughput single-cell WGA remains elusive. Here, we introduce droplet multiple displacement amplification (MDA), a method that uses commercially available liquid dispensing to perform high-throughput single-cell MDA in nanoliter volumes. The performance of droplet MDA is characterized using a large dataset of 129 normal diploid cells, and is shown to exceed previously reported single-cell WGA methods in amplification uniformity, genome coverage, and/or robustness. We achieve up to 80% coverage of a single-cell genome at 5× sequencing depth, and demonstrate excellent single-nucleotide variant (SNV) detection using targeted sequencing of droplet MDA product to achieve a median allelic dropout of 15%, and using whole genome sequencing to achieve false and true positive rates of 9.66 × 10−6 and 68.8%, respectively, in a G1-phase cell. We further show that droplet MDA allows for the detection of copy number variants (CNVs) as small as 30 kb in single cells of an ovarian cancer cell line and as small as 9 Mb in two high-grade serous ovarian cancer samples using only 0.02× depth. Droplet MDA provides an accessible and scalable method for performing robust and accurate CNV and SNV measurements on large numbers of single cells.

CDK12 regulates alternative last exon mRNA splicing and promotes breast cancer cell invasion

Abstract CDK12 (cyclin-dependent kinase 12) is a regulatory kinase with evolutionarily conserved roles in modulating transcription elongation. Recent tumor genome studies of breast and ovarian cancers highlighted recurrent CDK12 mutations, which have been shown to disrupt DNA repair in cell-based assays. In breast cancers, CDK12 is also frequently co-amplified with the HER2 (ERBB2) oncogene. The mechanisms underlying functions of CDK12 in general and in cancer remain poorly defined. Based on global analysis of mRNA transcripts in normal and breast cancer cell lines with and without CDK12 amplification, we demonstrate that CDK12 primarily regulates alternative last exon (ALE) splicing, a specialized subtype of alternative mRNA splicing, that is both gene- and cell type-specific. These are unusual properties for spliceosome regulatory factors, which typically regulate multiple forms of alternative splicing in a global manner. In breast cancer cells, regulation by CDK12 modulates ALE splicing of the DNA damage response activator ATM and a DNAJB6 isoform that influences cell invasion and tumorigenesis in xenografts. We found that there is a direct correlation between CDK12 levels, DNAJB6 isoform levels and the migration capacity and invasiveness of breast tumor cells. This suggests that CDK12 gene amplification can contribute to the pathogenesis of the cancer.

The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

High-grade serous ovarian cancer exhibits extensive intratumoral heterogeneity coupled with widespread intraperitoneal disease. Despite this, metastatic spread of tumor clones is non-random, implying the existence of local microenvironmental factors that shape tumor progression. We interrogated the molecular interface between tumor-infiltrating lymphocytes (TIL) and cancer cells in 143 samples from 21 patients using whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T- and B-cell receptor sequencing. We identify 3 immunologic response categories, which frequently co-exist within individual patients. Furthermore, epithelial CD8+ TIL were inversely associated with malignant cell diversity, evidenced by subclonal neoepitope elimination and spatial tracking between tumor and T-cell clones. Intersecting mutational signatures and immune analysis showed that foldback inversion genomic aberrations lead to worse outcomes even in the presence of cytotoxic TIL (n=433). Thus, regional variation in immune contexture mirrors the pattern of intraperitoneal malignant spread, provoking new perspectives for treatment of this challenging disease.

LINE-1 retrotransposon-mediated DNA transductions in endometriosis associated ovarian cancers

OBJECTIVEnEndometrioid (ENOC) and clear cell ovarian carcinoma (CCOC) share a common precursor lesion, endometriosis, hence the designation endometriosis associated ovarian cancers (EAOC). Long interspersed nuclear element 1 (LINE-1 or L1), is a family of mobile genetic elements activated in many cancers capable of moving neighboring DNA through 3 transductions. Here we investigated the involvement of specific L1-mediated transductions in EAOCs.nnnMETHODSnThrough whole genome sequencing, we identified active L1-mediated transductions originating within the TTC28 gene in 34% (10/29) of ENOC and 31% (11/35) of CCOC cases. We used PCR and capillary sequencing to assess the presence of specific TTC28-L1 transductions in formalin-fixed paraffin-embedded (FFPE) blocks from six different anatomical sites (five tumors and one normal control) for four ENOC and three CCOC cases, and compared the results to the presence of single nucleotide variations (SNVs)/frame shift (fs) mutations detected using multiplex PCR and next generation sequencing.nnnRESULTSnTTC28-L1 mediated transductions were identified in at least three tumor samplings in all cases, and were present in all five tumor samplings in 5/7 (71%) cases. In these cases, KRAS, PIK3CA, CTNNB1, ARID1A, and PTEN mutations were found across all tumor sites while other selected SNV/fs mutations of unknown significance were present at varying allelic frequencies.nnnCONCLUSIONnThe TTC28-L1 transductions along with classical driver mutations were near ubiquitous across the tumors, suggesting that L1 activation likely occurred early in the development of EAOCs. TTC28-L1 transductions could potentially be used to determine clonal relationships and to track ovarian cancer progression.

Hidden Markov Support Vector Machines for Self-Paced Brain Computer Interfaces

Brain Computer Interfaces (BCI) aim at providing a means to control devices with brain signals. Self-paced BCIs, as opposed to synchronous ones, have the advantage of being operational at all times and not only at specific system-defined periods. Traditionally, in the BCI field, a sliding window over the brain signal is used to detect the intention of the user at a given time. This approach ignores the temporal correlations between the adjacent time windows. This paper proposes a novel approach to classify self-paced BCI data using structural support vector machines. Our proposed approach considers the history of the brain signals in the context of sequential supervised learning to better detect the intention of the user from his/her brain signals. We have compared our proposed model to the sliding window approach with Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA) classifiers. Using data collected from 4 individuals form BCI competition IV, it is shown that the F1 score of our approach is significantly better than the sliding window approach. The average F1 score of our method across all subjects is 0.3 and 0.5 higher than the sliding window with SVM and LDA classifiers, respectively.

Abstract PR07: Synchronous ovarian and endometrial carcinomas: The case for pseudo-metastasis.

Background: Almost half of ovarian endometrioid histotype carcinomas present with concurrent endometrial carcinoma or pre-cancerous lesions. These “synchronous” ovarian and endometrial (SEO) tumors, when organ-confined and low-grade, consistently behave as two independent primary tumors, rather than a tumor-metastasis pair typical of advanced-stage carcinoma. Our study aims to investigate the ancestral relationship between ovarian and endometrial components of SEOs. Methods: We identified a cohort of SEOs and performed targeted, with the Illumina Truseq Custom Amplicon assay, and exome-level, with Nugen Ovation Library System and Agilent SureSelect XT2 capture, library construction followed by massively parallel sequencing on illumina MiSeq or HiSeq. Results: Despite complexities introduced as a result of sampling formalin fixed and paraffin embedded archival specimens we were able to confirm shared identical mutations, and thus a clonal relationship, between ovarian and endometrial tumors in all but one case. Discussion: In simultaneous presentation of cancer of the endometrium and ovary from our series we observed strong evidence of a primary tumor and metastasis relationship. However, the clinical behavior of this series, and SEOs in general, defies the basic tenant of cancer metastasis as a dire prognosis. Curiously similar anomalies, where there is advanced stage yet favorable outcome, occur in other organ systems. We therefore suggest a generalizable process “pseudo-metastasis” through which cells can spread to microenvironment-compatible and physically accessible sites. This restricted metastatic process can occur in cells that lack the full complement of cancer-associated transformation hallmarks required for tissue invasion and hematogenous or lymphatic metastasis. This phenomenon may be an important early step in dissemination of apparent multi-focal benign lesions, pre-malignant lesions, and low-grade carcinomas. This abstract is also presented as Poster B07. Citation Format: Michael S. Anglesio, Yi Kan Wang, Madlen Maassen, Hugo M. Horlings, Ali Bashashati, Blake Gilks, Stefan Kommoss, David G. Huntsman. Synchronous ovarian and endometrial carcinomas: The case for pseudo-metastasis. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr PR07.

Abstract LB-324: Genomic consequences of aberrant DNA repair stratify ovarian cancer histotypes

Background: Ovarian carcinoma is comprised of distinct histological subtypes with different etiology, molecular, genomic and clinical attributes. Patterns of genomic diversity and different treatment responses differentiate each ovarian cancer histotype. The relative patterns of both mutational, copy number and structural variation have not been studied with relation to each disease phenotype. We hypothesized that global genomic architectures will stratify ovarian cancer patients and reveal different treatment response groups. Methods: Whole genome sequencing was performed on 133 ovarian tumors, including 123 carcinomas (59 high-grade serous (HGSC), 35 clear cell (CCOC), 29 endometrioid (ENOC)) and 10 granulosa cell tumours (GCT). Profiles of copy number aberrations, loss of heterozygosity (LOH), mutations (SNVs and INDELs) and structural variations were assessed. Mutational characteristics including mutation signatures derived from tri-nucleotide substitution patterns together with genomic structural characteristics, such as the relative proportion of rearrangement types, reflective of specific DNA repair processes were calculated for each patient. Results: Integrative clustering of the 133 patients according to their mutation and structural signatures resulted in seven distinct subgroups of patients. LOH and the homologous recombination deficiency mutation signature mainly distinguished HGSC cases from non-serous histotypes. HGSC cases were further clustered into two main subgroups. One subgroup (n = 23, 39%) showed a high prevalence of foldback inversions with homology size >5bp, while the other group (n = 25, 42%) was enriched in tandem duplications and deletions, and associated with microhomology ( Conclusion: Our results suggest that mutational and chromosomal structural variant signatures (rearrangement and copy number profiles) constitute new and defining features of ovarian carcinoma that relate to different DNA repair mechanisms. Our results provide insight into divergent etiologies within histotypes and suggest a novel structure on which to base treatment. Citation Format: Yikan Wang, Ali Bashashati, Michael S. Anglesio, Dawn Cochrane, Diljot Grewal, Hugo Horlings, Anthony Karnezis, Anne-Marie Mes-Masson, Aikou Okamoto, Satoshi Yanagida, Nozomu Yanaihara, Misato Saito, Blake Gilks, Jessica McAlpine, Samuel Aparicio, David Huntsman, Sohrab Shah. Genomic consequences of aberrant DNA repair stratify ovarian cancer histotypes. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-324.