Biology subjects

Harismendy, O.

Publications and source records attributed to Harismendy, O..

13 recordsLinked to original sources

bioRxiv2023

Tumor microenvironmental determinants of high-risk DCIS progression

ABSTRACT/SUMMARYDuctal carcinoma in situ (DCIS) constitutes an array of morphologically recognized intraductal neoplasms in the mammary ductal tree defined by an increased risk for subsequent invasive carcinomas at or near the site of biopsy detection. However, only 15-45% of untreated DCIS cases progress to invasive cancer, so understanding mechanisms that prevent progression is key to avoid overtreatment and provides a basis for alternative therapies and prevention. This study was designed to characterize the tumor microenvironment and molecular profile of high-risk DCIS that grew to a large size but remained as DCIS. All patients had DCIS lesions >5cm in size with at least one additional high-risk feature: young age (<45 years), high nuclear grade, hormone receptor negativity, HER2 positivity, the presence of comedonecrosis, or a palpable mass. The tumor immune microenvironment was characterized using multiplex immunofluorescence to identify immune cells and their spatial relationships within the ducts and stroma. Gene copy number analysis and whole exome DNA sequencing identified the mutational burden and driver mutations, and quantitative whole-transcriptome/gene expression analyses were performed. There was no association between the percent of the DCIS genome characterized by copy number variants (CNAs) and recurrence events (DCIS or invasive). Mutations, especially missense mutations, in the breast cancer driver genes PIK3CA and TP53 were common in this high-risk DCIS cohort (47% of evaluated lesions). Tumor infiltrating lymphocyte (TIL) density was higher in DCIS lesions with TP53 mutations (p=0.0079) compared to wildtype lesions, but not in lesions with PIK3CA mutations (p=0.44). Immune infiltrates were negatively associated with hormone receptor status and positively associated with HER2 expression. High levels of CD3+CD8-T cells were associated with good outcomes with respect to any subsequent recurrence (DCIS or invasive cancer), whereas high levels of CD3+Foxp3+ Treg cells were associated with poor outcomes. Spatial proximity analyses of immune cells and tumor cells demonstrated that close proximity of T cells with tumor cells was associated with good outcomes with respect to any recurrence as well as invasive recurrences. Interestingly, we found that myoepithelial continuity (distance between myoepithelial cells surrounding the involved ducts) was significantly lower in DCIS lesions compared to normal tissue (p=0.0002) or to atypical ductal hyperplasia (p=0.011). Gene set enrichment analysis identified several immune pathways associated with low myoepithelial continuity and a low myoepithelial continuity score was associated with better outcomes, suggesting that gaps in the myoepithelial layer may allow access/interactions between immune infiltrates and tumor cells. Our study demonstrates the immune microenvironment of DCIS, in particular the spatial proximity of tumor cells and T cells, and myoepithelial continuity are important determinants for progression of disease.

cancer biology↗

bioRxiv2022

Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Intraductal papillary mucinous neoplasms (IPMNs) are cystic precursor lesions to pancreatic ductal adenocarcinoma (PDAC). IPMNs undergo multistep progression from low grade (LG) to high grade (HG) dysplasia, culminating in invasive neoplasia. While patterns of IPMN progression have been analyzed using multi-region sequencing for somatic mutations, there is no integrated assessment of molecular events, including copy number alterations (CNAs) and transcriptomics changes, that accompany IPMN progression. We performed laser capture microdissection on surgically resected IPMNs of varying grades of histological dysplasia obtained from 24 patients (total of 74 independent histological lesions), followed by whole exome and whole transcriptome sequencing. Overall, HG IPMNs displayed a significantly greater aneuploidy score than LG lesions, with chromosome 1q amplification, in particular, being associated with HG progression and with cases that harbored cooccurring PDAC. Furthermore, the combined assessment of single nucleotide variants (SNVs) and CNAs identified both linear and branched evolutionary trajectories, underscoring the heterogeneity in the progression of LG lesions to HG and PDAC. At the transcriptome level, upregulation of MYC-regulated targets and downregulation of transcripts associated with the MHC class I antigen presentation machinery was a common feature of progression to HG. Taken together, this work emphasizes the role of 1q copy number amplification as a putative biomarker of high-risk IPMNs, underscores the importance of immune evasion even in non-invasive precursor lesions, and supports a previously underappreciated role of CNA-driven branching evolution as an avenue for IPMN progression. Our study provides important molecular context for risk stratification and cancer interception opportunities in IPMNs. SignificanceIntegrated molecular analysis of genomic and transcriptomic alterations in the multistep progression of intraductal papillary mucinous neoplasms (IPMNs), which are bona fide precursors of pancreatic cancer, identifies features associated with progression of low-risk lesions to high-risk lesions and cancer, which might enable patient stratification and cancer interception strategies.

cancer biology↗

bioRxiv2022

Differential Analysis of Stromal-Epithelial Interactions between In Situ and Invasive Breast Cancer using Gene Expression Profiling

BackgroundChanges in microenvironment cell-cell interactions (CCI) during the progression from ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) are poorly understood. Gene expression studies are confounded by cellular heterogeneity and few separate stromal and epithelial contributions, resulting in a lack of reliable prognostic biomarker to guide treatment decisions. MethodsThe gene expression of 293 microdissected regions from DCIS (92 epithelial, 31 stromal) and IDC (78 epithelial, 30 stromal) cases was aggregated from 6 datasets. Expression signatures of 6 cell lineages extracted from normal breast single-cell profiling were used to correct for differences in cell abundance. Subtype-specific functional differences between DCIS and IDC were measured for each region type using Gene Set Enrichment Analysis (GSEA). DCIS-IDC stromal-epithelial interactions were compared using the expression product of 139 ligand-receptor (LR) pairs permuting the DCIS-IDC labels to assess significance. ResultsVariation in cell-lineage abundance separated epithelial regions into 4 clusters, including one enriched for DCIS (Myoepi-Enriched) and two for IDC (Infiltrated, Vascularized). GSEA on cell lineage normalized expression data identified subtype-independent changes in epithelial regions (induction of Extracellular Matrix maintenance genes, reduction of Tp53 signaling in IDC), as well as subtype-specific changes (proliferation in ER- and Her2-IDC, reduction in Nucleotide Excision Repair in ER+ IDC). In the stroma, Notch and Rho-GTPase signaling were induced in IDC irrespective of subtype. The stromal-epithelial interaction level of 6 and 4 LR pairs were significantly enriched in DCIS and IDC, respectively. Five of the 6 DCIS-enriched LR pairs involved ephrin interactions, with interaction level progressively decreasing from normal to DCIS to IDC. In contrast, 2 IDC-enriched LR pairs involved T-cell activity likely regulating Treg proliferation (CD28-CD86) or T and NK cells stimulation (CD226-PVR). Notably, the bulk expression product of one identified LR pair (EPHB4-EFNB1) was associated with poor survival in IDC (HR=1.47, p=0.04) suggesting that early remodeling of this stromal-epithelial interaction may have long-lasting impact on disease severity. ConclusionsThe observed changes in cell states and stromal-epithelial interactions, beyond those driven by difference in cell abundance, may lead to new biomarkers for prognosis and targets for secondary prevention.

cancer biology↗

bioRxiv2021

Stromal remodeling regulates dendritic cell abundance and activity in the tumor microenvironment

Stimulatory dendritic cells (SDC), enriched within Batf3-DC (cDC1), engage in productive interactions with CD8+ effectors along tumor-stroma boundaries. The paradoxical accumulation of "poised" cross-presenting Batf3-DC within stromal sheets, distal to tumoral nests, is unlikely to simply reflect passive exclusion away from immunosuppressive tumor cores. Drawing parallels with embryonic morphogenesis, we hypothesized that invasive margin stromal remodeling may generate developmentally conserved cell-fate cues that regulate Batf3-DC behavior. We find that CD8+ T-cells massively infiltrate tumor matrices undergoing proteoglycan versican (VCAN) proteolysis, an essential organ-sculpting modification in development and adult tissue-plane forging. VCAN proteolysis releases a bioactive fragment (matrikine), versikine, that is necessary and sufficient for Batf3-DC accumulation. Versikine does not influence tumor-seeding pre-DC differentiation; rather, it orchestrates a distinctive activation program conferring exquisite sensitivity to DNA-sensing, coupled with survival support from atypical innate lymphoid cells. Thus, homeostatic signals from stroma invasion regulate SDC survival and activity to promote T- cell inflammation. HIGHLIGHTSO_LITumor stroma remodeling generates cross-presenting DC survival and activation cues. C_LIO_LIStromal-activated Batf3-DC are hypersensitive to dsDNA-sensing. C_LIO_LIStromal signals promote atypical innate lymphoid cells (GM-CSFhi/ IFN{gamma}lo). C_LIO_LIT-cell repriming by stroma-licensed Batf3-DC may overcome exclusion at tumor margins. C_LI

immunology↗

bioRxiv2021

The breast pre-cancer atlas illustrates the molecular and micro-environmental diversity of ductal carcinoma in situ

Micro-environmental and molecular factors mediating the progression of Breast Ductal Carcinoma In Situ (DCIS) are not well understood, impeding the development of prevention strategies and the safe testing of treatment de-escalation. We addressed methodological barriers and characterized the mutational, transcriptional, histological and microenvironmental landscape across 85 multiple micro-dissected regions from 39 cases. Most somatic alterations, including whole genome duplications, were clonal, but genetic divergence increased with physical distance. Phenotypic and subtype heterogeneity frequently associated with underlying genetic heterogeneity and regions with low-risk features preceded those with high-risk features according to the inferred phylogeny. B- and T-lymphocytes spatial analysis identified 3 immune states, including an epithelial excluded state located preferentially at DCIS regions, and characterized by histological and molecular features of immune escape, independently from molecular subtypes. Such breast pre-cancer atlas with uniquely integrated observations will help scope future expansion studies and build finer models of outcomes and progression risk.

genomics↗

bioRxiv2021

Germline variants that influence the tumor immune microenvironment also drive response to immunotherapy

With the continued promise of immunotherapy as an avenue for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Approaches that intersect SNP modifiers of molecular phenotype, such as gene expression, with disease phenotypes have shown promise for implicating causal genetic factors. Here we evaluated 194 literature-curated TIME associations and 890 associations detected with 157 immune phenotype (IP) components found using genotypes from over 8,000 individuals in The Cancer Genome Atlas. Of these 1084, 233 associations comprising 219 unique TIME-SNPs were also cancer relevant, associating with cancer risk, survival, and/or immunotherapy treatment response. Many cancer relevant TIME-SNPS overlapped regions of active transcription, and were associated with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. TIME-SNPs associated with cancer risk and response to immunotherapy implicated genes involved in antigen presentation, especially by antigen presenting cells. The strongest associations with survival were with PD-L1 and CTLA-4, suggesting that SNPs modifying the potential for immune evasion could contribute to disease progression. To assess whether our approach could reveal novel cancer immunotherapy targets, we inhibited CTSS, a gene implicated by cancer risk and immunotherapy response-associated TIME-SNPs; CTSS inhibition resulted in slowed tumor growth and extended survival in vivo. These results validate the potential of cancer relevant TIME-SNPs to implicate target genes for countering immune suppressive characteristics of the TIME and set the stage for future host genetics analysis integrating germline variation and TIME characteristics. SignificanceA systematic screen for common germline variants associated with the tumor immune microenvironment across > 8000 tumors reveals novel cancer risk factors and targets for immunotherapy.

cancer biology↗

bioRxiv2020

Mutational profiling of micro-dissected pre-malignant lesions from archived specimens

BackgroundSystematic cancer screening has led to the increased detection of pre-malignant lesions (PMLs). The absence of reliable prognostic markers has led mostly to over treatment resulting in potentially unnecessary stress, or potentially insufficient treatment and avoidable progression. Importantly, most mutational profiling studies have relied on PML synchronous to invasive cancer, or performed in patients without outcome information, hence limiting their utility for biomarker discovery. The limitations in comprehensive mutational profiling of PMLs are in large part due to the significant technical and methodological challenges: most PML specimens are small, fixed in formalin and paraffin embedded (FFPE) and lack matching normal DNA. MethodsUsing test DNA from a highly degraded FFPE specimen, multiple targeted sequencing approaches were evaluated, varying DNA input amount (3-200 ng), library preparation strategy (BE: Blunt-End, SS: Single-Strand, AT: A-Tailing) and target size (whole exome vs cancer gene panel). Variants in high-input DNA from FFPE and mirrored frozen specimens were used for PML-specific variant calling training and testing, respectively. The resulting approach was applied to profile and compare multiple regions micro-dissected (mean area 5 mm2) from 3 breast ductal carcinoma in situ (DCIS). ResultsUsing low-input FFPE DNA, BE and SS libraries resulted in 4.9 and 3.7 increase over AT libraries in the fraction of whole exome covered at 20x (BE:87%, SS:63%, AT:17%). Compared to high-confidence somatic mutations from frozen specimens, PML-specific variant filtering increased recall (BE:85%, SS:80%, AT:75%) and precision (BE:93%, SS:91%, AT:84%) to levels expected from sampling variation. Copy number alterations were consistent across all tested approaches and only impacted by the design of the capture probe-set. Applied to DNA extracted from 9 micro-dissected regions (8 PML, 1 normal epithelium), the approach achieved comparable performance, illustrated the data adequacy to identify candidate driver events (GATA3 mutations, ERBB2 or FGFR1 gains, TP53 loss) and measure intra-lesion genetic heterogeneity. ConclusionAlternate experimental and analytical strategies increased the accuracy of DNA sequencing from archived micro-dissected PML regions, supporting the deeper molecular characterization of early cancer lesions and achieving a critical milestone in the development of biology-informed prognostic markers and precision chemo-prevention strategies.

genomics↗

bioRxiv2018

Ad-Seq, a genome-wide DNA-adduct profiling assay

SummaryCarcinogens form adducts with the DNA which, when not properly repaired, can lead to mutations and drive oncogenesis. The identity, sequence specificity and mutagenicity of most DNA-adducts is however poorly understood and current molecular assays are limited in their scope and scalability. We present a novel genome-wide DNA adduct sequencing (Ad-Seq) assay to map the location of DNA-adducts at single-nucleotide resolution. Ad-Seq enriches for DNA fragments containing nuclease digestion resistant DNA-adducts. The genomic location of the resulting reads is aggregated in a quantitative profile showing the DNA-adduct sequence context. Ad-Seq is quantitative and confirms known specificity of damages from Ultra-Violet light (di-pyrimidine) and cisplatin (AG and GG di-purines). Furthermore, in cells, Ad-Seq profile can be compared to chromatin segments to show that cisplatin associated adducts are depleted in open and active chromatin regions. The Ad-Seq assay can therefore generate a broad DNA signature of DNA damage and, by comparing to mutagen exposure or downstream mutational profile and signatures, be used to improve our understanding of cancer molecular etiology.

genomics↗

bioRxiv2017

Evolution and characterization of carboplatin resistance at single cell resolution

Acquired resistance to carboplatin is a major obstacle to the cure of ovarian cancer, but its molecular underpinnings are still poorly understood and often inconsistent between in vitro modeling studies. Using sequential treatment cycles, multiple clones derived from a single ovarian cancer cell reached similar levels of resistance. The resistant clones showed significant transcriptional heterogeneity, with shared repression of cell cycle processes and induction of IFN response signaling, and subsequent pharmacological inhibition of the JAK/STAT pathway led to a general increase in carboplatin sensitivity. Gene-expression based virtual synchronization of 26,772 single cells from 2 treatment steps and 4 resistant clones was used to evaluate the activity of Hallmark gene sets in proliferative (P) and quiescent (Q) phases. Two behaviors were associated with resistance: 1) broad repression in the P phase observed in all clones in early resistant steps and 2) prevalent induction in Q phase observed in the late treatment step of one clone. Furthermore, the induction of IFN response in P phase or Wnt-signaling in Q phase were observed in distinct resistant clones. These observations suggest a model of resistance hysteresis, where functional alterations of the P and Q phase states affect the dynamics of the successive transitions between drug exposure and recovery, and prompts for a precise monitoring of single-cell states to develop more effective schedules for, or combination of, chemotherapy treatments.

cancer biology↗

bioRxiv2017

Sharing genetic admixture and diversity of public biomedical datasets

Genetic ancestry and admixture are critical co-factors to study phenotype-genotype associations using cohorts of human subjects. Most publically available molecular datasets - genomes, exomes or transcriptomes - are however missing this information or only share self-reported ancestry. This represents a limitation to identify and re-purpose datasets to investigate the contribution of race and ethnicity to diseases and traits. we propose an analytical framework to enrich the meta-data from publically available cohorts with admixture information and a resulting diversity score at continental resolution, calculated directly from the data. We illustrate the utility and versatility of the framework using The Cancer Genome Atlas datasets indexed and searched through the DataMed Data Discovery Index. Data repositories or data contributors can use this framework to provide, as metadata, admixture for controlled access datasets, minimizing the work involved in requesting a dataset that may ultimately prove inadequate for a researchers purpose. With the increasingly global scale of human genetics research, research on disease risk and susceptibility would benefit greatly from the adequate estimation and sharing of admixture data following a framework such as the one presented.

genetics↗

bioRxiv2017

Large-Scale Uniform Analysis of Cancer Whole Genomes in Multiple Computing Environments

The International Cancer Genome Consortium (ICGC)s Pan-Cancer Analysis of Whole Genomes (PCAWG) project aimed to categorize somatic and germline variations in both coding and non-coding regions in over 2,800 cancer patients. To provide this dataset to the research working groups for downstream analysis, the PCAWG Technical Working Group marshalled ~800TB of sequencing data from distributed geographical locations; developed portable software for uniform alignment, variant calling, artifact filtering and variant merging; performed the analysis in a geographically and technologically disparate collection of compute environments; and disseminated high-quality validated consensus variants to the working groups. The PCAWG dataset has been mirrored to multiple repositories and can be located using the ICGC Data Portal. The PCAWG workflows are also available as Docker images through Dockstore enabling researchers to replicate our analysis on their own data.

genomics↗

bioRxiv2017

PinAPL-Py: a web-service for the analysis of CRISPR-Cas9 Screens

BackgroundLarge-scale genetic screens using CRISPR/Cas9 technology have emerged as a major tool for functional genomics. With its increased popularity, experimental biologists frequently acquire large sequencing datasets for which they often do not have an easy analysis option. While a few bioinformatic tools have been developed for this purpose, their utility is still hindered either due to limited functionality or the requirement of bioinformatic expertise.\n\nResultsTo make sequencing data analysis of CRISPR/Cas9 screens more accessible to a wide range of scientists, we developed a Platform-independent Analysis of Pooled Screens using Python (PinAPL-Py), which is operated as an intuitive web-service. PinAPL-Py implements state-of-the-art tools and statistical models, assembled in a comprehensive workflow covering sequence quality control, automated sgRNA sequence extraction, alignment, sgRNA enrichment/depletion analysis and gene ranking. The workflow is set up to use a variety of popular sgRNA libraries as well as custom libraries that can be easily uploaded. Various analysis options are offered, suitable to analyze a large variety of CRISPR/Cas9 screening experiments. Analysis output includes ranked lists of sgRNAs and genes, and publication-ready plots.\n\nConclusionsPinAPL-Py helps to advance genome-wide screening efforts by combining comprehensive functionality with user-friendly implementation. PinAPL-Py is freely accessible at http://pinapl-py.ucsd.edu with instructions, documentation and test datasets. The source code is available at https://github.com/LewisLabUCSD/PinAPL-Py

bioinformatics↗

bioRxiv2016

Pan-Cancer Analysis Reveals Technical Artifacts in The Cancer Genome Atlas (TCGA) Germline Variant Calls

The degree to which germline variation drives cancer development and shapes tumor phenotypes remains largely unexplored, possibly due to a lack of large scale publicly available germline data for a cancer cohort. Here we called germline variants on 9,618 cases from The Cancer Genome Atlas (TCGA) database representing 31 cancer types. We identified batch effects affecting loss of function (LOF) variant calls that can be traced back to differences in the way the sequence data were generated both within and across cancer types. Overall, LOF indel calls were more sensitive to technical artifacts than LOF Single Nucleotide Variant (SNV) calls. In particular, whole genome amplification of DNA prior to sequencing led to an artificially increased burden of LOF indel calls, which confounded association analyses relating germline variants to tumor type despite stringent indel filtering strategies. Due to the inherent noise we chose to remove all 614 amplified DNA samples, including all acute myeloid leukemia and virtually all ovarian cancer samples, from the final dataset. This study demonstrates how insufficient quality control can lead to false positive germlinetumor type associations and draws attention to the need to be sensitive to problems associated with a lack of uniformity in data generation in TCGA data.\n\nAuthor SummaryCancer research to date has largely focused on genetic aberrations specific to tumor tissue. In contrast, the degree to which germline, or inherited, variation contributes to tumorigenesis remains unclear, possibly due to a lack of accessible germline variant data. In this study we identify germline variants in 9,618 samples using raw germline exome data from The Cancer Genome Atlas (TCGA). There are substantial differences in the way exome sequence data was generated both across and within cancer types in TCGA. We observe that differences in sequence data generation introduced batch effects, or variation that is due to technical factors not true biological variation, in our variant data. Most notably, we observe that amplification of DNA prior to sequencing resulted in an excess of predicted damaging indel variants. We show how these batch effects can confound germline association analyses if not properly addressed. Our study highlights the difficulties of working with large public genomic datasets like TCGA where samples are collected over time and across data centers, and particularly cautions the use of amplified DNA samples for genetic association analyses.

genomics↗