Diana Abdueva

Transcriptional profiling of MnSOD-mediated lifespan extension in Drosophila reveals a species-general network of aging and metabolic genes

BackgroundSeveral interventions increase lifespan in model organisms, including reduced insulin/insulin-like growth factor-like signaling (IIS), FOXO transcription factor activation, dietary restriction, and superoxide dismutase (SOD) over-expression. One question is whether these manipulations function through different mechanisms, or whether they intersect on common processes affecting aging.ResultsA doxycycline-regulated system was used to over-express manganese-SOD (MnSOD) in adult Drosophila, yielding increases in mean and maximal lifespan of 20%. Increased lifespan resulted from lowered initial mortality rate and required MnSOD over-expression in the adult. Transcriptional profiling indicated that the expression of specific genes was altered by MnSOD in a manner opposite to their pattern during normal aging, revealing a set of candidate biomarkers of aging enriched for carbohydrate metabolism and electron transport genes and suggesting a true delay in physiological aging, rather than a novel phenotype. Strikingly, cross-dataset comparisons indicated that the pattern of gene expression caused by MnSOD was similar to that observed in long-lived Caenorhabditis elegans insulin-like signaling mutants and to the xenobiotic stress response, thus exposing potential conserved longevity promoting genes and implicating detoxification in Drosophila longevity.ConclusionThe data suggest that MnSOD up-regulation and a retrograde signal of reactive oxygen species from the mitochondria normally function as an intermediate step in the extension of lifespan caused by reduced insulin-like signaling in various species. The results implicate a species-conserved net of coordinated genes that affect the rate of senescence by modulating energetic efficiency, purine biosynthesis, apoptotic pathways, endocrine signals, and the detoxification and excretion of metabolites.

BMI-1 Promotes Ewing Sarcoma Tumorigenicity Independent of CDKN2A Repression

Deregulation of the polycomb group gene BMI-1 is implicated in the pathogenesis of many human cancers. In this study, we have investigated if the Ewing sarcoma family of tumors (ESFT) expresses BMI-1 and whether it functions as an oncogene in this highly aggressive group of bone and soft tissue tumors. Our data show that BMI-1 is highly expressed by ESFT cells and that, although it does not significantly affect proliferation or survival, BMI-1 actively promotes anchorage-independent growth in vitro and tumorigenicity in vivo. Moreover, we find that BMI-1 promotes the tumorigenicity of both p16 wild-type and p16-null cell lines, demonstrating that the mechanism of BMI-1 oncogenic function in ESFT is, at least in part, independent of CDKN2A repression. Expression profiling studies of ESFT cells following BMI-1 knockdown reveal that BMI-1 regulates the expression of hundreds of downstream target genes including, in particular, genes involved in both differentiation and development as well as cell-cell and cell-matrix adhesion. Gain and loss of function assays confirm that BMI-1 represses the expression of the adhesion-associated basement membrane protein nidogen 1. In addition, although BMI-1 promotes ESFT adhesion, nidogen 1 inhibits cellular adhesion in vitro. Together, these data support a pivotal role for BMI-1 ESFT pathogenesis and suggest that its oncogenic function in these tumors is in part mediated through modulation of adhesion pathways.

Mouse Mesenchymal Stem Cells Expressing PAX-FKHR Form Alveolar Rhabdomyosarcomas by Cooperating with Secondary Mutations

Alveolar rhabdomyosarcomas (ARMS) are highly malignant soft-tissue sarcomas that arise in children, adolescents, and young adults. Although formation and expression of the PAX-FKHR fusion genes is thought to be the initiating event in this cancer, the role of PAX-FKHR in the neoplastic process remains largely unknown in a progenitor cell that is undefined. We hypothesize that PAX-FKHR determine the ARMS progenitor to the skeletal muscle lineage, which when coupled to the inactivation and/or activation of critical cell signaling pathways leads to the formation of ARMS. Because a number of studies have proposed that mesenchymal stem cells (MSC) are the progenitor for several of the sarcomas, we tested this hypothesis in MSCs. We show that PAX-FKHR induce skeletal myogenesis in MSCs by transactivating MyoD and myogenin. Despite exhibiting enhanced growth in vitro, the PAX-FKHR-expressing populations do not form colonies in soft agar or tumors in mice. Expression of dominant-negative p53, or the SV40 early region, elicits tumor formation in some of the PAX-FKHR-expressing populations. Additional activation of the Ras signaling pathway leads to highly malignant tumor formation for all of the populations. The PAX-FKHR-expressing tumors were shown to have histologic, immunohistochemical, and gene expression profiles similar to human ARMS. Our results show the critical role played by PAX-FKHR in determining the molecular, myogenic, and histologic phenotype of ARMS. More importantly, we identify MSCs as a progenitor that can give rise to ARMS.

Explaining differences in saturation levels for Affymetrix GeneChip® arrays

The experimental spike-in studies of microarray hybridization conducted by Affymetrix demonstrate a nonlinear response of fluorescence intensity signal to target concentration. Several theoretical models have been put forward to explain these data. It was shown that the Langmuir adsorption isotherm recapitulates a general trend of signal response to concentration. However, this model fails to explain some key properties of the observed signal. In particular, according to the simple Langmuir isotherm, all probes should saturate at the same intensity level. However, this effect was not observed in the publicly available Affymetrix spike-in data sets. On the contrary, it was found that the saturation intensities vary greatly and can be predicted based on the probe sequence composition. In our experimental study, we attempt to account for the unexplained variation in the observed probe intensities using customized fluidics scripts. We explore experimentally the effect of the stringent wash, target concentration and hybridization time on the final microarray signal. The washing effect is assessed by scanning chips both prior to and after the stringent wash. Selective labeling of both specific and non-specific targets allows the visualization and investigation of the washing effect for both specific and non-specific signal components. We propose a new qualitative model of the probe-target hybridization mechanism that is in agreement with observed hybridization and washing properties of short oligonucleotide microarrays. This study demonstrates that desorption of incompletely bound targets during the washing cycle contributes to the observed difference in saturation levels.

Non-linear analysis of GeneChip arrays

The application of microarray hybridization theory to Affymetrix GeneChip data has been a recent focus for data analysts. It has been shown that the hyperbolic Langmuir isotherm captures the shape of the signal response to concentration of Affymetrix GeneChips. We demonstrate that existing linear fit methods for extracting gene expression measures are not well adapted for the effect of saturation resulting from surface adsorption processes. In contrast to the most popular methods, we fit background and concentration parameters within a single global fitting routine instead of estimating the background before obtaining gene expression measures. We describe a non-linear multi-chip model of the perfect match signal that effectively allows for the separation of specific and non-specific components of the microarray signal and avoids saturation bias in the high-intensity range. Multimodel inference, incorporated within the fitting routine, allows a quantitative selection of the model that best describes the observed data. The performance of this method is evaluated on publicly available datasets, and comparisons to popular algorithms are presented.

Using expression arrays for copy number detection: an example from E. coli

BackgroundThe sequencing of many genomes and tiling arrays consisting of millions of DNA segments spanning entire genomes have made high-resolution copy number analysis possible. Microarray-based comparative genomic hybridization (array CGH) has enabled the high-resolution detection of DNA copy number aberrations. While many of the methods and algorithms developed for the analysis microarrays have focused on expression analysis, the same technology can be used to detect genetic alterations, using for example standard commercial Affymetrix arrays. Due to the nature of the resultant data, standard techniques for processing GeneChip expression experiments are inapplicable.ResultsWe have developed a robust and flexible methodology for high-resolution analysis of DNA copy number of whole genomes, using Affymetrix high-density expression oligonucleotide microarrays. Copy number is obtained from fluorescence signals after processing with novel normalization, spatial artifact correction, data transformation and deletion/duplication detection. We applied our approach to identify deleted and amplified regions in E. coli mutants obtained after prolonged starvation.ConclusionThe availability of Affymetrix expression chips for a wide variety of organisms makes the proposed array CGH methodology useful more generally.

Validation of a Plasma-Based Comprehensive Cancer Genotyping Assay Utilizing Orthogonal Tissue- and Plasma-Based Methodologies

Purpose: To analytically and clinically validate a circulating cell-free tumor DNA sequencing test for comprehensive tumor genotyping and demonstrate its clinical feasibility. Experimental Design: Analytic validation was conducted according to established principles and guidelines. Blood-to-blood clinical validation comprised blinded external comparison with clinical droplet digital PCR across 222 consecutive biomarker-positive clinical samples. Blood-to-tissue clinical validation comprised comparison of digital sequencing calls to those documented in the medical record of 543 consecutive lung cancer patients. Clinical experience was reported from 10,593 consecutive clinical samples. Results: Digital sequencing technology enabled variant detection down to 0.02% to 0.04% allelic fraction/2.12 copies with ≤0.3%/2.24–2.76 copies 95% limits of detection while maintaining high specificity [prevalence-adjusted positive predictive values (PPV) >98%]. Clinical validation using orthogonal plasma- and tissue-based clinical genotyping across >750 patients demonstrated high accuracy and specificity [positive percent agreement (PPAs) and negative percent agreement (NPAs) >99% and PPVs 92%–100%]. Clinical use in 10,593 advanced adult solid tumor patients demonstrated high feasibility (>99.6% technical success rate) and clinical sensitivity (85.9%), with high potential actionability (16.7% with FDA-approved on-label treatment options; 72.0% with treatment or trial recommendations), particularly in non–small cell lung cancer, where 34.5% of patient samples comprised a directly targetable standard-of-care biomarker. Conclusions: High concordance with orthogonal clinical plasma- and tissue-based genotyping methods supports the clinical accuracy of digital sequencing across all four types of targetable genomic alterations. Digital sequencings clinical applicability is further supported by high rates of technical success and biomarker target discovery. Clin Cancer Res; 24(15); 3539–49. ©2018 AACR.

Abstract 5705: Analytical validation of Guardant360 v2.10

Guardant360 is a cell-free circulating tumor DNA (ctDNA) test that genotypes all guideline-recommended solid tumor somatic genomic treatment targets from a single non-invasive blood draw. The new version, v2.10, was redesigned to enhance sensitivity and specificity across 73 cancer-related genes. It detects all four major variant classes (single nucleotide variants, SNVs, in all 73 genes; indels in 23 genes; gene amplifications, CNAs, in 18 genes; and fusions in 6 genes). Analytical performance was assessed throughout the reportable range via multiple serial dilution studies of orthogonally-characterized contrived and patient samples. Analytical specificity was assessed by calculating the false positive rate in pre-characterized healthy donor sample mixtures serially diluted. Positive predictive value (PPV) was estimated as a function of allelic fraction/copy number from pre-characterized samples and prevalence-adjusted using a cohort of 2,585 consecutive clinical samples. Confirmation was performed using ddPCR. Analytical specificity was 100% for SNVs, fusions, and CNAs and 96% for indels across 25 defined samples. Relative to Guardant360v2.9, v2.10 demonstrated 20-50% increase in fusion molecule recovery. Retrospective in silico analysis of 2,585 consecutive clinical samples demonstrated a 15% increase in actionable fusion detection, a 6%-15% increase in actionable indel detection (excluding newly reportable indels), and a 3%-6% increase in actionable SNV detection. Guardant360 analytical performance characteristics based on standard cfDNA input (30ng). Analytical sensitivity/limit of detection estimates are provided for clinically actionable variants and may vary by sequence context and cfDNA input. PPV is estimated across entire reportable panel space (PPV was 100% for clinically actionable variants). Conclusion: Guardant360 v2.10 comprehensively detects all adult solid tumor guideline-recommended somatic genomic variants with unparalleled sensitivity, accuracy, and specificity. Citation Format: James Vowles, Justin Odegaard, Stefanie Mortimer, Stephen Fairclough, Marcin Sikora, Diana Abdueva, Reza Mokhtari, Arthur Baca, AmirAli Talasaz. Analytical validation of Guardant360 v2.10 [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 5705. doi:10.1158/1538-7445.AM2017-5705

Abstract 3350: Cell-free DNA fragmentation patterns analyzed in over 15000 cancer patients reveal changes associated with tumor somatic mutations and result in improved sensitivity and specificity of somatic variant detection

Background: Cell-free DNA (cfDNA) isolated from plasma consists of DNA fragments surviving clearance of dying cells and bloodstream trafficking. In cancer, these fragments carry the footprint of tumor somatic variation as well as its microenvironment. Since genomic distribution of cell free DNA fragments was shown to reflect nucleosomal occupancy in hematopoietic cells, we hypothesized that (a) heterogeneous patterns of cfDNA positioning would be associated with distinct mutations in patient tumors and (b) integration of fragmentation patterns into analysis would allow increased sensitivity and specificity of somatic mutation detection. Methods: cfDNA fragment length and position distributions as well as associated somatic genomic profiles of over 15,000 patients with advanced-stage clinical cancer were determined by a highly accurate, deep-coverage (15,000x) ctDNA NGS test targeting 70 genes (Guardant360). An integrative data analysis of variant-free fragmentomics domain across different driver mutations was performed to identify patterns associated with detected somatic alterations. Results: We discovered distinct classes of fragmentomics subtypes significantly enriched in samples with different genomic subtypes. An independent cohort of samples with known HER2 immunohistochemistry status was interrogated to confirm discovered association between fragmentation patterns and HER2 status. Integrating fragmentomics amplification signature with ERBB2 copy number analysis has resulted in 42% increase in the sensitivity and 7% increase in specificity of detection. Observed lung adenocarcinoma fragmentomics subtypes co-occured with mutually exclusive genomic alterations and previously described intrinsic molecular subtypes of lung cancer. Conclusions: Fragmentomics classification of cancer cfDNA provides independent evidence for observed somatic variation and underlying tumor microenviroment, leading to higher sensitivity and accuracy of variant detection. Citation Format: Diana Abdueva, Helmy Eltoukhy, Darya Chudova, AmirAli Talasaz. Cell-free DNA fragmentation patterns analyzed in over 15000 cancer patients reveal changes associated with tumor somatic mutations and result in improved sensitivity and specificity of somatic variant detection [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 3350. doi:10.1158/1538-7445.AM2017-3350

Abstract 506: Post-surgical resection monitoring in early stage colorectal carcinoma patients using a circulating cell-free DNA assay with ultra-high accuracy and specificity

Analysis of cell-free circulating tumor DNA (ctDNA) by next-generation sequencing (NGS) allows non-invasive real-time profiling of actionable genomic alterations. Liquid biopsy provides an option for disease monitoring in early stage cancer patients post surgical resection, with a potential to aid in adjuvant decision making. However, to be applicable, tests must cover a broad enough genomic footprint to not require a priori knowledge of mutations, have high specificity, and sensitivity higher than conventional methods. NGS is necessary, since inactivating mutations are the most common alteration type in many common cancer types such as colorectal carcinomas (CRC). Here we present a highly efficient and specific NGS assay for detection of ctDNA in early stage cancer patients, capable of detecting single molecule variants across a 12 kb gene panel with an analytical sensitivity of >0.02% for single nucleotide variants (SNVs) and indels. This panel was applied to a clinical study involving 14 early stage (II/III) CRC patients with both pre- and post-op blood draws (up to 7 days post surgery). A subset (6 patients) also had tumor samples collected at the time of the surgical resection of the tumor. Overall, the detection rate of ctDNA in pre-op blood draws was 93%. In the post-op blood draws ctDNA was detectable in 43% of cases. The estimated average minor allele frequency (MAF) is 0.58% (± 0.82%) in pre-op, 0.18% (±0.21%) in post-op, and 40% (±18%) in tumor samples. When tumor tissue was available and used as a reference, the clinical sensitivity, specificity, and accuracy in pre-op blood samples were 83%, 99.995%, and 99.99%, respectively. SNVs with MAF as low as 0.04% were confirmed in tissue data. The clinical specificity of variants detected in post-op blood samples using pre-op samples as the reference is 99.996%. Cohort expansion to 50 patients and follow-up for clinical recurrence in both cohorts is ongoing. In conclusion, we have developed an assay with ultra-high accuracy and specificity, for the detection of ctDNA in early stage CRC patients that is capable of detecting alterations present in the tumor post-surgical resection. This technology allows for a promising non-invasive route for molecular monitoring of residual disease post surgery and for early detection of relapse compared to traditional methodologies. Citation Format: Stefanie A. Mortimer, Katharine Dilger, Stephen Fairclough, Diana Abdueva, Darya Chudova, Ankit Sarin, Jim Leng, Jeeyun Lee, Helmy Eltoukhy, AmirAli Talasaz. Post-surgical resection monitoring in early stage colorectal carcinoma patients using a circulating cell-free DNA assay with ultra-high accuracy and specificity. [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 506.