Biology subjects

Owzar, K.

Publications and source records attributed to Owzar, K..

15 recordsLinked to original sources

bioRxiv2025

A nonhuman primate model mirrors human congenital cytomegalovirus infection and reveals a spectrum of vertical transmission outcomes

Congenital cytomegalovirus (cCMV) is the leading infectious cause of birth defects worldwide, yet immune determinants of protection to inform design of a maternal vaccine remain elusive. Here, we characterized the outcome of primary rhesus CMV (RhCMV) infection during pregnancy in an immune competent nonhuman primate (NHP) model. RhCMV DNA was detected in amniotic fluid and/or fetal tissues in six of 12 (50% placental transmission) CMV-naive rhesus macaque dams inoculated intravenously with RhCMV in early second trimester gestation. Widespread tissue dissemination dominated by one of two inoculated RhCMV strains was present in one fetus (8.3% cCMV disease). Placental RhCMV transmission was associated with elevated fetal and maternal plasma TNF-alpha and reduced maternal brain-derived neurotrophic factor and IL-10 levels. CMV exposure during pregnancy had a broad impact on the placenta and fetus even in the absence of congenital infection as evidenced by RhCMV infection at the maternal-fetal interface in all 12 dams, along with significantly reduced placental efficiency and fetal growth metrics compared to gestation-matched control pregnancies. This NHP model recapitulates key aspects of human cCMV and provides new insight into barriers and biomarkers of successful vertical transmission. One sentence summary: The nonhuman primate model mirrors the epidemiology of human congenital CMV (cCMV) after primary infection and reveals its transmission bottlenecks.

immunology↗

bioRxiv2023

Single Cell Expression Analysis of Ductal Carcinoma in Situ Identifies Alterations in Epithelial Integrity

To identify mechanisms underlying the growth of ductal carcinoma in situ (DCIS) and properties that lead to progression to invasive cancer, we performed single-cell RNA-sequencing (scRNA-seq) on DCIS lesions and matched synchronous normal breast tissue. Using inferred copy number variations (CNV), we identified neoplastic epithelial cells from the clinical specimens which contained a mixture of DCIS and normal ducts. Phylogenetic analysis based on the CNVs demonstrated intratumoral clonal heterogeneity was associated with significant gene expression differences. We also classified epithelial cells into mammary cell states and found that individual genetic clones contained a mixture of cell states suggesting an ongoing pattern of differentiation after neoplastic transformation. Cell state proportions were significantly different based on estrogen receptor (ER) expression with ER-DCIS more closely resembling the distribution in the normal breast, particularly with respect to cells with basal characteristics. Using deconvolution from bulk RNA-seq in archival DCIS specimens, we show that specific alterations in cell state proportions are associated with progression to invasive cancer. Loss of an intact basement membrane (BM) is the functional definition of invasive breast cancer (IBC) and scRNA-seq data demonstrated that ongoing transcription of key BM genes occurs in specific subsets of epithelial cell states. Examining BM in archival microinvasive breast cancers and an in vitro model of invasion, we found that passive loss of BM gene expression due to cell state proportion alterations is associated with loss of the structural integrity of the duct leading to an invasive phenotype. Our analyses provide detailed insight into DCIS biology. SIGNIFICANCESingle cell analysis reveals that preinvasive breast cancer is comprised of multiple genetic clones and there is substantial phenotypic diversity both within and between these clones. Ductal carcinoma in situ (DCIS) of the breast is a non-invasive condition commonly identified through mammographic screening. A primary diagnosis of DCIS carries little mortality risk on its own, but its presence is a risk factor for subsequent clonally related invasive breast cancer (IBC) (1-5).

cancer biology↗

bioRxiv2023

Analysis of ductal carcinoma in situ by self-reported race reveals molecular differences related to outcome.

Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer (IBC). Studies have indicated differences in DCIS outcome based on race or ethnicity, but molecular differences have not been investigated. We examined the molecular profile of DCIS by self-reported race (SRR) and outcome groups in Black (n=99) and White (n=191) women with DCIS in a large DCIS case-control cohort with longitudinal follow up. Gene expression and pathway analyses indicated that different genes and pathways are involved in ipsilateral breast outcome (DCIS or IBC) after DCIS treatment in White versus Black women. We identified differences in ER and HER2 expression, tumor microenvironment composition, and copy number variations by SRR and outcome groups. Our results suggest that different molecular mechanisms drive subsequent ipsilateral breast events in Black versus White women.

cancer biology↗

bioRxiv2023

Time-Informed Dimensionality Reduction for Longitudinal Microbiome Studies

Longitudinal studies are crucial for understanding complex microbiome dynamics and their link to health. We introduce TEMPoral TEnsor Decomposition (TEMPTED), a time-informed dimensionality reduction method for high-dimensional longitudinal data that treats time as a continuous variable, effectively characterizing temporal information and handling varying temporal sampling. TEMPTED captures key microbial dynamics, facilitates beta-diversity analysis, and enhances reproducibility by transferring learned representations to new data. In simulations, it achieves 90% accuracy in phenotype classification, significantly outperforming existing methods. In real data, TEMPTED identifies vaginal microbial markers linked to term and preterm births, demonstrating robust performance across datasets and sequencing platforms.

bioinformatics↗

bioRxiv2023

SifiNet: A robust and accurate method to identify feature gene sets and annotate cells

SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multiomic cellular profiles. It is conveniently available as an open-source R package.

bioinformatics↗

bioRxiv2022

Localizing Rare-Variant Association Regions via Multiple Testing Embedded in an Aggregation Tree

Rare variants (RVs) genetic association studies enable researchers to uncover the variation in phenotypic traits left unexplained by common variation. Traditional single-variant analysis lacks power; thus, researchers have developed various methods to aggregate the effects of RVs across genomic regions to study their collective impact. Some existing methods utilize a static delineation of genomic regions, often resulting in suboptimal effect aggregation, as neutral subregions within the test region will result in an attenuation of signal. Other methods use varying windows to search for signals but often result in long regions containing many neutral RVs. To pinpoint short genomic regions enriched for disease-associated RVs, we developed a novel method, DYNATE (DYNamic Aggregation TEsting). DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones and performs multiple testing for disease associations with controlled weighted false discovery rate. Extensive numerical simulations demonstrate the superior performance of DYNATE under various scenarios compared to existing methods. Importantly, DYNATE-identified regions have higher enrichment levels of disease-associated RVs. We applied DYNATE to an amyotrophic lateral sclerosis (ALS) study and identified a new gene, EPG5, harboringpossibly pathogenic mutations.

genetics↗

bioRxiv2022

Single-cell Landscape Analysis of the Circulating Human B Cell Pool under Selective Pressure of Allogeneic Stem Cell Transplantation

Alloreactivity can drive autoimmune syndromes. After allogeneic hematopoietic stem cell transplantation (allo-HCT) chronic graft-versus-host disease (cGVHD), a B cell-mediated autoimmune-like syndrome, commonly occurs. Because donor-derived B cells continually develop under selective pressure from host alloantigens, aberrant B Cell Receptor (BCR)-activation and IgG production can emerge and contribute to cGVHD pathobiology. To better understand molecular programing of B cells under selective pressure of alloantigens, we performed scRNA-Seq analysis on high numbers of purified B cells from allo-HCT patients. An unsupervised analysis revealed 10 clusters, distinguishable by signature genes for maturation, activation and memory. We found striking transcriptional differences in the memory B cell compartment after allo-HCT compared to healthy or infected individuals. To identify intrinsic properties when B-cell tolerance is lost after allo-HCT, we then assessed clusters for differentially expressed genes (DEGs) between patients with vs. without autoimmune-like manifestations (Active cGVHD vs. No cGVHD, respectively). DEGs were found in Active cGVHD in both naive and BCR-activated clusters, suggesting functional diversity. Some DEGs were also differentially expressed across most clusters, suggesting common molecular programs that may promote B cell plasticity. Our study of human allo-HCT and cGVHD provides new understanding of B-cell memory in the face of chronic alloantigen stimulation. One Sentence SummaryOur scRNA-Seq study of purified B cells after allo-HCT clarifies molecular differences in human B cell subsets when immune tolerance is lost or maintained. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/512162v4_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@5c452eorg.highwire.dtl.DTLVardef@1c1d34borg.highwire.dtl.DTLVardef@171310org.highwire.dtl.DTLVardef@e4bf15_HPS_FORMAT_FIGEXP M_FIG C_FIG The circulating human B cell compartment under the selective pressure of allogeneic hematopoietic stem cell transplantation (Allo-HCT) has an intrinsically altered memory B cell pool. In allo-HCT, genetically disparate donor stem and progenitor cells engraft, regenerating a new peripheral B cell compartment in the host. During ongoing B lymphopoiesis and diversification, selective pressure from alloantigens and other extrinsic factors, including B Cell Activating Factor (BAFF), result in either B cell maturation and immune tolerance (No Chronic GVHD) or altered B cell homeostasis and autoimmune manifestations (Active Chronic GVHD). B cells within defined subsets in patients with Active GVHD have distinct intrinsic programs delineated by differentially expressed genes (DEGs). Some DEGs occur across nearly all B cell subsets ( Differentially Expressed Broadly), while other DEGs are more restricted within only one or a few B cell subsets ( Naive, BCR-activated, or Memory). We affirm altered trajectories for diversification (blue arrow) and enrichment of an atypical memory B cell (ABC) pool, with intrinsic differences when chronic GVHD occurs.

immunology↗

bioRxiv2022

Clustering Deviation Index (CDI): A robust and accurate unsupervised measure for evaluating scRNA-seq data clustering

Single-cell RNA-sequencing (scRNA-seq) technology allows us to explore cellular heterogeneity in the transcriptome. Because most scRNA-seq data analyses begin with cell clustering, its accuracy considerably impacts the validity of downstream analyses. Although many clustering methods have been developed, few tools are available to evaluate the clustering "goodness-of-fit" to the scRNA-seq data. In this paper, we propose a new Clustering Deviation Index (CDI) that measures the deviation of any clustering label set from the observed single-cell data. We conduct in silico and experimental scRNA-seq studies to show that CDI can select the optimal clustering label set. Particularly, CDI also informs the optimal tuning parameters for any given clustering method and the correct number of cluster components.

bioinformatics↗

bioRxiv2021

The Human Tumor Atlas Network (HTAN) Breast PreCancer Atlas: A multi-omic integrative analysis of ductal carcinoma in situ with clinical outcomes

Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We have performed the first multiscale, integrated profiling of DCIS with clinical outcomes by analyzing 677 DCIS samples from 481 patients with 7.1 years median follow-up from the Translational Breast Cancer Research Consortium (TBCRC) 038 study and the Resource of Archival Breast Tissue (RAHBT) cohorts. We identified 812 genes associated with ipsilateral recurrence within 5 years from treatment and developed a classifier that was predictive of DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions were identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome. HIGHLIGHTS Development of a new classifier for DCIS recurrence or progression Outcome associated pathways identified across multiple data types and compartments Four stroma-specific signatures identified CNAs characterize DCIS subgroups associated with high risk invasive cancers

cancer biology↗

bioRxiv2021

Comparative analysis of RNA enrichment methods for preparation of Cryptococcus neoformans RNA sequencing libraries

Ribosomal RNA (rRNA) is the major RNA constituent of cells, therefore most RNA sequencing (RNA-Seq) experiments involve removal of rRNA. This process, called RNA enrichment, is done primarily to reduce cost: without rRNA removal, deeper sequencing would need to be performed to balance the sequencing reads wasted on rRNA. The ideal RNA enrichment method would remove all rRNA without affecting other RNA in the sample. We have tested the performance of three RNA enrichment methods on RNA isolated from Cryptococcus neoformans, a fungal pathogen of humans. We show that the RNase H depletion method unambiguously outperforms the commonly used Poly(A) isolation method: the RNase H method more efficiently depletes rRNA while more accurately recapitulating the expression levels of other RNA observed in an unenriched "gold standard". The RNase H depletion method is also superior to the Ribo-Zero depletion method as measured by rRNA depletion efficiency and recapitulation of protein-coding gene expression levels, while the Ribo-Zero depletion method performs moderately better in preserving non-coding RNA (ncRNA). Finally, we have leveraged this dataset to identify novel long non-coding RNA (lncRNA) genes and to accurately map the C. neoformans mitochondrial rRNA genes. ARTICLE SUMMARYWe compare the efficacy of three different RNA enrichment methods for RNA-Seq in Cryptococcus neoformans: RNase H depletion, Ribo-Zero depletion, and Poly(A) isolation. We show that the RNase H depletion method, which is evaluated in C. neoformans samples for the first time here, is highly efficient and specific in removing rRNA. Additionally, using data generated through these analyses, we identify novel long non-coding RNA genes in C. neoformans. We conclude that RNase H depletion is an effective and reliable method for preparation of C. neoformans RNA-Seq libraries.

microbiology↗

bioRxiv2021

APOBEC mutagenesis inhibits breast cancer growth through induction of a T cell-mediated antitumor immune response

The APOBEC family of cytidine deaminases is one of the most common endogenous sources of mutations in human cancer. Genomic studies of tumors have found that APOBEC mutational signatures are particularly enriched in the HER2 subtype of breast cancer and have been associated with immunotherapy response in diverse cancer types. However, the direct consequences of APOBEC mutagenesis on the tumor immune microenvironment have not been thoroughly investigated. To address this, we developed syngeneic murine mammary tumor models with inducible expression of APOBEC3B. We found that APOBEC activity induces an antitumor adaptive immune response and CD4+ T cell-mediated tumor growth inhibition. While polyclonal APOBEC tumors had a moderate growth defect, clonal APOBEC tumors were almost completely rejected by the immune system, suggesting that APOBEC-mediated genetic heterogeneity limits the antitumor adaptive immune response. Consistent with the observed immune infiltration in APOBEC tumors, APOBEC activity sensitized HER2-driven breast tumors to checkpoint inhibition. In human breast cancers, the relationship between APOBEC mutagenesis and immunogenicity varied by breast cancer subtype and the frequency of subclonal mutations. This work provides a mechanistic basis for the sensitivity of APOBEC tumors to checkpoint inhibitors and suggests a rationale for using APOBEC mutational signatures as a biomarker predicting immunotherapy response in HER2-positive breast cancers. SIGNIFICANCEAPOBEC mutational signatures are observed in many cancers, yet the consequences of these mutations on the tumor immune microenvironment are not well understood. Using a novel mouse model, we show that APOBEC activity sensitizes HER2-driven mammary tumors to checkpoint inhibition and could inform immunotherapy treatment strategies for HER2-positive breast cancer patients.

cancer biology↗

bioRxiv2020

Activation of Notch1 drives the development of radiation-induced thymic lymphoma in p53 wild-type mice

Mouse models of radiation-induced thymic lymphoma are widely used to study the development of radiation-induced blood cancers and to gain insights into the biology of human T-lymphoblastic leukemia/lymphoma. Here, we aimed to determine key oncogenic drivers for the development of radiation-induced thymic lymphoma by performing whole-exome sequencing using tumors and paired normal tissues from mice with and without irradiation. Thymic lymphomas from irradiated wild-type (WT), p53+/- and KrasLA1 mice were not observed to harbor significantly higher numbers of non-synonymous somatic mutations compared to thymic lymphomas from unirradiated p53-/- mice. However, we observed distinct patterns of recurrent mutations in genes that control the Notch1 signaling pathway based on the mutational status of p53. Preferential activation of Notch1 signaling in p53 WT lymphomas was also observed at the RNA and protein level. Using reporter mice for activation of the Notch1 signaling we observed that TBI enriched Notch1hi CD44+ thymocytes, which are capable of self-renewal in vivo. Mechanistically, genetic inhibition of Notch1 signaling in thymocytes prevented the formation of radiation-induced thymic lymphoma in p53 WT mice. Taken together, our results demonstrate a critical role of activated Notch1 signaling in driving multi-step carcinogenesis of thymic lymphoma following total-body irradiation in p53 WT mice.

cancer biology↗

bioRxiv2020

Adaptation and Selection Shape Clonal Evolution During Residual Disease and Recurrence

The survival of residual tumor cells following therapy and their eventual recurrence constitutes one of the biggest obstacles to obtaining cures in breast cancer, but it remains unclear how the clonal composition of tumors changes during tumor relapse. We used cellular barcoding to directly monitor clonal dynamics during tumor recurrence in a genetically engineered mouse model. We found that the clonal diversity of tumors progressively decreased during tumor regression, residual disease, and recurrence. Only a fraction of subclones survived oncogene withdrawal and persisted in residual tumors. The minimal residual disease phase itself was accompanied by a continued attrition of clones, suggesting an ongoing process of selection during dormancy. The reactivation of dormant residual cells into recurrent tumors followed several distinct evolutionary routes. Approximately half of the recurrent tumors exhibited a striking clonal dominance in which one or two subclones comprised the vast majority of the tumor. The majority of these clonal recurrent tumors exhibited evidence of de novo acquisition of Met amplification, and were sensitive to small-molecule Met inhibitors. A second group of recurrent tumors exhibited marked polyclonality, with thousands of subclones and a clonal architecture very similar to primary tumors. These polyclonal recurrent tumors were not sensitive to Met inhibitors, but were instead dependent upon an autocrine IL-6 - Stat3 pathway. These results suggest that the survival and reactivation of dormant tumors can proceed via multiple independent routes, producing recurrent tumors with distinct clonal composition, genetic alterations, and drug sensitivities.

cancer biology↗

bioRxiv2020

A single cell atlas reveals distinct immune landscapes in transplant and primary tumors that determine response or resistance to immunotherapy

Despite impressive responses in some patients, immunotherapy fails to cure most cancer patients. Preclinical studies indicate that radiotherapy synergizes with immunotherapy, promoting radiation-induced antitumor immunity. Nearly all preclinical immunotherapy studies utilize transplant tumor models, but cure rates of transplant tumor models treated with immunotherapy often overestimate patient responses. Here, we show that transplant tumors are cured by PD-1 blockade and radiotherapy, but identical treatment fails in autochthonous tumors. We generated a single-cell atlas of tumor-infiltrating immune cells from transplant and primary tumors treated with radiation and immunotherapy, which reveals striking differences in their immune landscapes. Although radiotherapy remodels myeloid cell phenotypes in primary and transplant tumors, only transplant tumors are enriched for CD8+ T cells that mediate tumor clearance while mice with primary sarcomas demonstrate tumor-specific tolerance. These results identify distinct microenvironments in tumors that coevolve with the immune system, which promote tolerance that must be overcome for immune-mediated cancer cures.

cancer biology↗

bioRxiv2016

Exploiting expression patterns across multiple gene isoforms to identify radiation response biomarkers in early-stage breast cancer patients.

In an effort to understand the underlying biology of radiation response along with whole transcriptome effects of preoperative radiotherapy in early-stage breast tumors, we propose two efficient score-based statistical methods that exploit gene expression patterns across all available gene transcript isoforms and identify potential biomarkers in the form of differentially expressed genes and differentially enriched gene-sets. We demonstrate the effectiveness of these two methods using extensive simulation studies that show that both of our methods give improved performance, in terms of statistical power, over the most commonly used methods. By exploiting radiation-induced changes in all available gene transcript isoforms, we identified several statistically significant differentially expressed genes related to PI3K-AKT and JAK-STAT signaling pathways along with radiation-induced oncogenic signaling pathways and tumor microenvironment gene signatures that could be potential targets to improve response to radiotherapy in breast tumors.

bioinformatics↗