Biology subjects

Wagle, N.

Publications and source records attributed to Wagle, N..

16 recordsLinked to original sources

bioRxiv2023

Inference of single cell profiles from histology stains with the Single-Cell omics from Histology Analysis Framework (SCHAF)

Tissue biology involves an intricate balance between cell-intrinsic processes and interactions between cells organized in specific spatial patterns, which can be respectively captured by single cell profiling methods, such as single cell RNA-seq (scRNA-seq) and spatial transcriptomics, and histology imaging data, such as Hematoxylin-and-Eosin (H&E) stains. While single cell profiles provide rich molecular information, they can be challenging to collect routinely in the clinic and either lack spatial resolution or high gene throughput. Conversely, histological H&E assays have been a cornerstone of tissue pathology for decades, but do not directly report on molecular details, although the observed structure they capture arises from molecules and cells. Here, we leverage vision transformers and adversarial deep learning to develop the Single Cell omics from Histology Analysis Framework (SCHAF), which generates a tissue samples spatially-resolved whole transcriptome single cell omics dataset from its H&E histology image. We demonstrate SCHAF on a variety of tissues-- including lung cancer, metastatic breast cancer, placentae, and whole mouse pups--training with matched samples analyzed by sc/snRNA-seq, H&E staining, and, when available, spatial transcriptomics. SCHAF generated appropriate single cell profiles from histology images in test data, related them spatially, and compared well to ground-truth scRNA-Seq, expert pathologist annotations, or direct spatial transcriptomic measurements, with some limitations. SCHAF opens the way to next-generation H&E analyses and an integrated understanding of cell and tissue biology in health and disease.

bioinformatics↗

bioRxiv2022

SlideCNA: Spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data

Solid tumors are spatially heterogeneous in their genetic, molecular and cellular composition, and this variation can be meaningful for diagnosis, prognosis and therapy. Recent spatial profiling studies have mostly charted genetic and RNA variation in tumors separately. To leverage the potential of RNA to identify copy number alterations (CNAs), we developed SlideCNA, a computational tool to extract sparse spatial CNA signals from spatial transcriptomics data, using expression-aware spatial binning. We test SlideCNA on simulated and real Slide-seq data of metastatic breast cancer (MBC) and demonstrate its potential for spatial sub-clone detection.

bioinformatics↗

bioRxiv2021

cDNA-detector: Detection and removal of cDNA contamination in DNA sequencing libraries

Exogenous cDNA introduced into an experimental system, either intentionally or accidentally, can appear as added read coverage over that gene in next-generation sequencing libraries derived from this system. If not properly recognized and managed, this cross-contamination with exogenous signal can lead to incorrect interpretation of research results. Yet, this problem is not routinely addressed in current sequence processing pipelines. Here, we present cDNA-detector, a computational tool to identify and remove exogenous cDNA contamination in DNA sequencing experiments. We apply cDNA-detector to several highly-cited public databases (TCGA, ENCODE, NCBI SRA) and show that contaminant genes appear in sequencing experiments where they lead to incorrect coverage peak calls. Our findings highlight the importance of sensitive detection and removal of contaminant cDNA from NGS libraries before downstream analysis.

bioinformatics↗

bioRxiv2021

A patient-driven clinicogenomic partnership through the Metastatic Prostate Cancer Project

Molecular profiling studies have enabled numerous discoveries for metastatic prostate cancer (MPC), but they have mostly occurred in academic medical institutions focused on select patient populations. We developed the Metastatic Prostate Cancer Project (MPCproject, mpcproject.org), a patient-partnered initiative to empower MPC patients living anywhere in the U.S. and Canada to participate in molecular research and contribute directly to translational discovery. Here we present clinicogenomic results from our partnership with the first 706 MPCproject participants. We found that a patient-centered and remote research strategy enhanced engagement with patients in rural and medically underserved areas. Furthermore, patient-reported data achieved 90% consistency with abstracted health records for therapies and provided a mechanism for patient-partners to share information about their cancer experience not documented in medical records. Among the molecular profiling data from 333 patient-partners (n = 573 samples), whole exome sequencing of 63 tumor samples obtained from hospitals across the U.S. and Canada and 19 plasma cell-free DNA (cfDNA) samples from blood donated remotely recapitulated known findings in MPC and enabled longitudinal study of prostate cancer evolution. Inexpensive ultra-low coverage whole genome sequencing of 318 cfDNA samples from donated blood revealed clinically relevant genomic changes like AR amplification, even in the context of low tumor burden. Collectively, this study illustrates the power of a longitudinal partnership with patients to generate a more representative clinical and molecular understanding of MPC. NoteTo assist our patient-partners and the wider MPC community interpret the results of this study, we have included a glossary of terms in the Supplementary Materials.

cancer biology↗

bioRxiv2021

Hotspot ESR1 mutations are multimodal and contextual drivers of breast cancer metastasis

Constitutively active estrogen receptor- (ER/ESR1) mutations have been identified in approximately one third of ER+ metastatic breast cancer. Although these mutations are known mediators of endocrine resistance, their potential role in promoting metastatic disease has not yet been mechanistically addressed. In this study, we show the presence of ESR1 mutations exclusively in distant, but not local recurrences. In concordance with transcriptomic profiling of ESR1 mutant tumors, genome-edited Y537S and D538G cell models have a reprogrammed cell adhesive gene network via alterations in desmosome/gap junction genes and the TIMP3/MMP axis, which functionally confers enhanced cell-cell contacts while decreased cell-ECM adhesion. Context-dependent migratory phenotypes revealed co-targeting of Wnt and ER as vulnerability. Mutant ESR1 exhibits non-canonical regulation of several metastatic pathways including secondary transactivation and de novo FOXA1-driven chromatin remodeling. Collectively, our data supports evidence for ESR1 mutation-driven metastases and provides insight for future preclinical therapeutic strategies. SignificanceContext and allele-dependent transcriptome and cistrome reprogramming in genome-edited ESR1 mutation cell models elicit diverse metastatic phenotypes, including but not limited to alterations in cell adhesion and migration. The gain-of-function mutations can be pharmacologically targeted, and thus may be key components of novel therapeutic treatment strategies for ER-mutant metastatic breast cancer.

cancer biology↗

bioRxiv2020

ESR1 mutant breast cancers show elevated basal cytokeratins and immune activation

Estrogen receptor alpha (ER/ESR1) is mutated in 30-40% of endocrine resistant ER-positive (ER+) breast cancer. ESR1 mutations cause ligand-independent growth and increased metastasis in vivo and in vitro. Despite the distinct clinical features and changes in therapeutic response associated with ESR1 mutations, there are no data about their potential role in intrinsic subtype switching. Applying four luminal and basal gene set pairs, ESR1 mutant cell models and clinical samples showed a significant enrichment of basal subtype markers. Among them, the six basal cytokeratins (BCKs) were the most enriched genes. Induction of BCKs was independent of ER binding and instead associated with chromatin reprogramming centered around a progesterone receptor-orchestrated topological associated domain at the KRT14/16/17 genomic region. Unexpectedly, high BCK expression in ER+ primary breast cancer is associated with good prognosis, and these tumors show enriched activation of a number of immune pathways, a distinctive feature shared with ESR1 mutant tumors. S100A8 and S100A9 were among the most highly induced immune mediators shared between high-BCKs ER+ and ESR1 mutant tumors, and single-cell RNA-seq analysis inferred their involvement in paracrine crosstalk between epithelial and stromal cells. Collectively, these observations demonstrate that ESR1 mutant tumors gain basal features with induction of basal cytokeratins via epigenetic mechanisms in rare subpopulation of cells. This is associated with increased immune activation, encouraging additional studies of immune therapeutic vulnerabilities in ESR1 mutant tumors.

cancer biology↗

bioRxiv2020

COUNTEN an AI-driven tool for rapid, and objective structural analyses of the Enteric Nervous System

Healthy gastrointestinal functions require a healthy Enteric Nervous System (ENS). ENS health is often defined by the presence of normal ENS structure. However, we currently lack a comprehensive understanding of normal ENS structure as current methodologies of manual enumeration of neurons within tissue and ganglia can only parse limited tissue regions; and are prone to error, subjective bias, and peer-to-peer discordance. Thus, there is a need to craft objective methods and robust tools to capture and quantify enteric neurons over a large area of tissue and within multiple ganglia. Here, we report on the development of an AI-driven tool COUNTEN which parses HuC/D-immunolabeled adult murine myenteric ileal plexus tissues to enumerate and classify enteric neurons into ganglia in a rapid, robust, and objective manner. COUNTEN matches trained humans in identifying, enumerating and clustering myenteric neurons into ganglia but takes a fraction of the time, thus allowing for accurate and rapid analyses of a large tissue region. Using COUNTEN, we parsed thousands of myenteric neurons and clustered them in hundreds of myenteric ganglia to compute metrics that help define the normal structure of the adult murine ileal myenteric plexus. We have made COUNTEN freely and openly available to all researchers, to facilitate reproducible, robust, and objective measures of ENS structure across mouse models, experiments, and institutions.

neuroscience↗

bioRxiv2020

Cell-line-specific network models of ER+ breast cancer identify PI3Kα inhibitor sensitivity factors and drug combinations

Durable control of invasive solid tumors necessitates identifying therapeutic resistance mechanisms and effective drug combinations. A promising approach to tackle the cancer drug resistance problem is to build mechanistic mathematical models of the signaling network of cancer cells, and explicitly model the dynamics of information flow through this network under distinct genetic conditions and in response to perturbations. In this work, we used a network-based mathematical model to identify sensitivity factors and drug combinations for the PI3K inhibitor alpelisib, which was recently approved for ER+ PIK3CA mutant breast cancer. We experimentally validated the model-predicted efficacious combination of alpelisib and BH3 mimetics (e.g. MCL1 inhibitors) in ER+ breast cancer cell lines. We also experimentally validated the reduced sensitivity to alpelisib caused by FOXO3 knockdown, which is a novel potential resistance mechanism. Our experimental results showed cell line-specific sensitivity to the combination of alpelisib and BH3 mimetics, which was driven by the choice of BH3 mimetics. We find that cell lines were sensitive to the addition of either MCL1 inhibitor s63845 alone or in combination with BCL-XL/BCL-2 inhibitor navitoclax, and that the need for the combination of both BH3 mimetics was predicted by the expression of BCL-XL. Based on these results, we developed cell line-specific network models that are able to recapitulate the observed differential response to alpelisib and BH3 mimetics, and also incorporate the most recent knowledge on resistance and response to PI3K inhibitors. Overall, we present an approach for the development, experimental testing, and refining of mathematical models, which we apply to the context of PI3K inhibitor drug resistance in breast cancer. Our approach predicted and validated PI3K inhibitor sensitivity factors (FOXO3 knockdown) and drug combinations (BH3 mimetics), and illustrates that network-based mathematical models can contribute to overcoming the challenge of cancer drug resistance.

cancer biology↗

bioRxiv2020

Expansion Sequencing: Spatially Precise In Situ Transcriptomics in Intact Biological Systems

AbstractMethods for highly multiplexed RNA imaging are limited in spatial resolution, and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to mouse brain, yielding readout of thousands of genes, including splice variants and novel transcripts. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in neurons of the mouse hippocampus, revealing patterns across multiple cell types; layer-specific cell types across mouse visual cortex; and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus ExSeq enables highly multiplexed mapping of RNAs, from nanoscale to system scale. One Sentence SummaryIn situ sequencing of physically expanded specimens enables multiplexed mapping of RNAs at nanoscale, subcellular resolution.

genomics↗

bioRxiv2019

The genomic landscape of intrinsic and acquired resistance to cyclin-dependent kinase 4/6 inhibitors in patients with hormone receptor positive metastatic breast cancer

Clinical resistance mechanisms to CDK4/6 inhibitors in HR+ breast cancer have not been clearly defined. Whole exome sequencing of 59 tumors with CDK4/6i exposure revealed multiple candidate resistance mechanisms including RB1 loss, activating alterations in AKT1, RAS, AURKA, CCNE2, ERBB2, and FGFR2, and loss of ER expression. In vitro experiments confirmed that these alterations conferred CDK4/6i resistance. Cancer cells cultured to resistance with CDK4/6i also acquired RB1, KRAS, AURKA, or CCNE2 alterations, which conferred sensitivity to AURKA, ERK, or CHEK1 inhibition. Besides inactivation of RB1, which accounts for [~]5% of resistance, seven of these mechanisms have not been previously identified as clinical mediators of resistance to CDK4/6 inhibitors in patients. Three of these--RAS activation, AKT activation, and AURKA activation--have not to our knowledge been previously demonstrated preclinically. Together, these eight mechanisms were present in 80% of resistant tumors profiled and may define therapeutic opportunities in patients. SignificanceWe identified eight distinct mechanisms of resistance to CDK4/6 inhibitors present in 80% of resistant tumors profiled. Most of these have a therapeutic strategy to overcome or prevent resistance in these tumors. Taken together, these findings have critical implications related to the potential utility of precision-based approaches to overcome resistance in many patients with HR+ MBC.

cancer biology↗

bioRxiv2019

Reversion and non-reversion mechanisms of resistance to PARP inhibitor or platinum chemotherapy in BRCA1/2-mutant metastatic breast cancer

BackgroundLittle is known about mechanisms of resistance to PARP inhibitors and platinum chemotherapy in patients with metastatic breast cancer and BRCA1/2 mutations. Further investigation of resistance in clinical cohorts may point to strategies to prevent or overcome treatment failure. Patients and MethodsWe obtained tumor biopsies from metastatic breast cancer patients with BRCA1/2 deficiency before and after acquired resistance to PARP inhibitor or platinum chemotherapy. Whole exome sequencing was performed on each tumor, germline DNA, and circulating tumor DNA. Tumors underwent RNA sequencing, and immunohistochemical staining for RAD51 foci on tumor sections was performed for functional assessment of intact homologous recombination. ResultsPre- and post-resistance tumor samples were sequenced from 8 patients (4 with BRCA1 and 4 with BRCA2 mutation; 4 treated with PARP inhibitor and 4 with platinum). Following disease progression on DNA-damaging therapy, four patients (50%) acquired at least one somatic reversion alteration likely to result in functional BRCA1/2 protein detected by tumor or circulating tumor DNA sequencing. Two patients with germline BRCA1 deficiency acquired genomic alterations anticipated to restore homologous recombination through increased DNA end resection: loss of TP53BP1 in one patient and amplification of MRE11A in another. RAD51 foci were acquired post-resistance in all patients with genomic reversion, consistent with reconstitution of homologous recombination. All patients whose tumors demonstrated RAD51 foci post-resistance were intrinsically resistant to subsequent lines of DNA-damaging therapy. ConclusionsGenomic reversion in BRCA1/2 was the most commonly observed mechanism of resistance, occurring in 4 of 8 patients. Novel sequence alterations leading to increased DNA end resection were seen in two patients, and may be targetable for therapeutic benefit. The presence of RAD51 foci by immunohistochemistry was consistent with BRCA1/2 protein functional status from genomic data and predicted response to later DNA-damaging therapy, supporting RAD51 focus formation as a clinically useful biomarker.

cancer biology↗

bioRxiv2019

A single-cell and single-nucleus RNA-seq toolbox for fresh and frozen human tumors

Single cell genomics is essential to chart the complex tumor ecosystem. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumor tissues, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each strategy requires modifications to fit the unique characteristics of different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We tested eight tumor types of varying tissue and sample characteristics (resection, biopsy, ascites, and orthotopic patient-derived xenograft): lung cancer, metastatic breast cancer, ovarian cancer, melanoma, neuroblastoma, pediatric sarcoma, glioblastoma, pediatric high-grade glioma, and chronic lymphocytic leukemia. Analyzing 212,498 cells and nuclei from 39 clinical samples, we evaluated protocols by cell quality, recovery rate, and cellular composition. We optimized protocols for fresh tissue dissociation for different tumor types using a decision tree to account for the technical and biological variation between clinical samples. We established methods for nucleus isolation from OCT embedded and fresh-frozen tissues, with an optimization matrix varying mechanical force, buffer, and detergent. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types and intrinsic expression profiles, but at different proportions. Our work provides direct guidance across a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

genomics↗

bioRxiv2019

The Angiosarcoma Project: enabling genomic and clinical discoveries in a rare cancer through patient-partnered research

Despite collectively accounting for 25% of tumors in U.S. adults, rare cancers have significant unmet clinical needs as they are difficult to study due to low incidence and geographically dispersed patient populations. We sought to assess whether a patient-partnered research approach using online engagement can overcome these challenges and accelerate scientific discovery in rare cancers, focusing on angiosarcoma (AS), an exceedingly rare sarcoma with a dismal prognosis and an annual U.S. incidence of 300 cases. Here, we describe the development of the Angiosarcoma Project (ASCproject), an initiative enabling patients across the U.S. and Canada to remotely share their clinical information and biospecimens for research. The project generates and publicly releases clinically annotated genomic data on tumor and germline specimens on an ongoing basis. Over 18 months, 338 AS patients registered for the ASCproject, comprising a significant fraction of all patients. Whole exome sequencing of 47 AS tumors revealed several recurrently mutated genes, including KDR, TP53, and PIK3CA. Activating mutations in PIK3CA were observed nearly exclusively in primary breast AS, suggesting a therapeutic rationale in these patients. AS of the head, neck, face, and scalp (HNFS) was associated with high tumor mutation burden and a dominant mutational signature of UV light exposure, suggesting that UV damage may be a causative factor in HNFS AS and that this AS subset might be amenable to immune checkpoint inhibitor therapy. Medical record review revealed two patients with HNFS AS received off-label treatment with anti-PD-1 therapy and experienced exceptional responses, highlighting immune checkpoint inhibition as a therapeutic avenue for HNFS AS. This patient-partnered approach has catalyzed an opportunity to discover the etiology and potential therapies for AS patients. Collectively, this proof of concept study demonstrates that empowering patients to directly participate in research can overcome barriers in rare diseases and enable biological and clinical discoveries.

cancer biology↗

bioRxiv2019

Prevalence and mutational determinants of high tumor mutation burden in breast cancer

BackgroundHigh tumor mutation burden (TMB) has been associated with benefit to immunotherapy in multiple tumor types. However, the prevalence of hypermutated breast cancer is not well described. The aim of this study is to evaluate frequency, mutational patterns, and genomic profile of hypermutated breast cancer.\n\nPatients and MethodsWe used de-identified data from individuals with primary or metastatic breast cancer from six different publicly available genomic studies. The prevalence of hypermutated breast cancer was determined among 3969 patients samples that underwent whole exome sequencing or gene panel sequencing. Samples were classified as having high TMB if they had [≥]10 mutations per megabase (mut/Mb). An additional 8 patients were identified from a Dana-Farber Cancer Institute cohort for inclusion in the hypermutated cohort. Among patients with high TMB, the mutational patterns, and genomic profile were determined. A subset of patients was treated with regimens containing PD-1 inhibitors.\n\nResultsThe median TMB was 2.63 mut/Mb. Median TMB significantly varied according to tumor subtype (HR-/HER2-> HER2+ > HR+/HER2-, p < 0.05) and sample type (metastatic > primary, p 2.2x10-16). Hypermutated tumors were found in 198 patients (5%), with an enrichment in metastatic versus primary tumors (8.4% versus 2.9%, p = 6.5 x 10-14). APOBEC activity (59.2%), followed by mismatch repair deficiency (MMRd; 36.4%), were the most common mutational processes among hypermutated tumors. Three patients with hypermutated breast cancer--including two with a dominant APOBEC activity signature and one with a dominant MMRd signature--treated with pembrolizumab-based therapies derived an objective and durable response to therapy.\n\nConclusionHypermutation occurs in 5% of all breast cancers, with an enrichment in metastatic tumors. Different mutational signatures are present in this population, with APOBEC activity being the most common dominant process. Preliminary data suggest that hypermutated breast cancers are more likely to benefit from PD-1 inhibitors.\n\nKey MessageHigh tumor mutation burden is found in 5% of all breast cancers and is more common in metastatic tumors. While different mutational signatures are present in hypermutated tumors, APOBEC activity is the most common dominant process. Preliminary data suggest that those tumors are more likely to benefit from PD-1 inhibitors.

genomics↗

bioRxiv2019

Opposing immune and genetic forces shape oncogenic programs in synovial sarcoma

Synovial sarcoma is an aggressive mesenchymal neoplasm, driven by the SS18-SSX fusion, and characterized by immunogenic antigens expression and exceptionally low T cell infiltration levels. To study the cancer-immune interplay in this disease, we profiled 16,872 cells from 12 human synovial sarcoma tumors using single-cell RNA-sequencing (scRNA-Seq). Synovial sarcoma manifests antitumor immunity, high cellular plasticity and a core oncogenic program, which is predictive of low immune levels and poor clinical outcomes. Using genetic and pharmacological perturbations, we demonstrate that the program is controlled by the SS18-SSX driver and repressed by cytokines secreted by macrophages and T cells in the tumor microenvironment. Network modeling predicted that SS18-SSX promotes the program through HDAC1 and CDK6. Indeed, the combination of HDAC and CDK4/6 inhibitors represses the program, induces immunogenic cell states, and selectively targets synovial sarcoma cells. Our study demonstrates that immune evasion, cellular plasticity, and cell cycle are co-regulated and can be co-targeted in synovial sarcoma and potentially in other malignancies.

cancer biology↗

bioRxiv2019

Acquired FGFR and FGF alterations confer resistance to estrogen receptor (ER) targeted therapy in ER+ metastatic breast cancer

Beyond acquired mutations in the estrogen receptor (ER), mechanisms of resistance to ER-directed therapies in ER+ breast cancer have not been clearly defined. We conducted a genome-scale functional screen spanning 10,135 genes to investigate genes whose overexpression confer resistance to selective estrogen receptor degraders. Pathway analysis of candidate resistance genes demonstrated that the FGFR, ERBB, insulin receptor, and MAPK pathways represented key modalities of resistance. In parallel, we performed whole exome sequencing in paired pre-treatment and post-resistance biopsies from 60 patients with ER+ metastatic breast cancer who had developed resistance to ER-targeted therapy. The FGFR pathway was altered via FGFR1, FGFR2, or FGF3 amplifications or FGFR2 mutations in 24 (40%) of the post-resistance biopsies. In 12 of the 24 post-resistance tumors exhibiting FGFR/FGF alterations, these alterations were not detected in the corresponding pre-treatment tumors, suggesting that they were acquired or enriched under the selective pressure of ER-directed therapy. In vitro experiments in ER+ breast cancer cells confirmed that FGFR/FGF alterations led to fulvestrant resistance as well as cross-resistance to the CDK4/6 inhibitor palbociclib. RNA sequencing of resistant cell lines treated with different drug combinations demonstrated that FGFR/FGF induced resistance through ER reprogramming and activation of the MAPK pathway. The resistance phenotypes were reversed by FGFR inhibitors, a MEK inhibitor, and/or a SHP2 inhibitor, suggesting potential treatment strategies. The detection of targetable, clonally acquired genetic alterations in the FGFR pathway in metastatic tumor biopsies highlights the value of serial tumor testing to dissect mechanisms of resistance in human breast cancer and its potential application in directing clinical management.

cancer biology↗