Biology subjects

Skidmore, Z. L.

Publications and source records attributed to Skidmore, Z. L..

9 recordsLinked to original sources

bioRxiv2023

Endothelial cells are a key target of IFN-g during response to combined PD-1/CTLA-4 ICB treatment in a mouse model of bladder cancer

To explore mechanisms of response to combined PD-1/CTLA-4 immune checkpoint blockade (ICB) treatment in individual cell types, we generated scRNA-seq using a mouse model of invasive urothelial carcinoma with three conditions: untreated tumor, treated tumor, and tumor treated after CD4+ T cell depletion. After classifying tumor cells based on detection of somatic variants and assigning non-tumor cell types using SingleR, we performed differential expression analysis, overrepresentation analysis, and gene set enrichment analysis (GSEA) within each cell type. GSEA revealed that endothelial cells were enriched for upregulated IFN-g response genes when comparing treated cells to both untreated cells and cells treated after CD4+ T cell depletion. Functional analysis showed that knocking out IFNgR1 in endothelial cells inhibited treatment response. Together, these results indicated that IFN-g signaling in endothelial cells is a key mediator of ICB induced anti-tumor activity.

cancer biology↗

bioRxiv2021

Genomic and transcriptomic somatic alterations of hepatocellular carcinoma in non-cirrhotic livers

BackgroundLiver cancer is the second leading cause of cancer-related deaths worldwide. Hepatocellular carcinoma (HCC) risk factors include chronic hepatitis, cirrhosis, and alcohol abuse, whereby tumorigenesis is induced through inflammation and subsequent fibrotic response. However, a subset of HCC arises in non-cirrhotic livers. We characterized the genomic and transcriptomic landscape of non-cirrhotic HCC to identify features underlying the diseases development and progression. MethodsWhole genome and transcriptome sequencing was performed on 30 surgically resectable tumors comprised of primarily of non-cirrhotic HCC and adjacent normal tissue. Using somatic variants, capture reagents were created and employed on an additional 87 cases of mixed cirrhotic/non-cirrhotic HCC. Cases were analyzed to identify viral integrations, single nucleotide variants (SNVs), insertions and deletions (INDELS), copy number variants, loss of heterozygosity, gene fusions, structural variants, and differential gene expression. ResultsWe detected 3,750 SNVs/INDELS and extensive CNVs and expression changes. Recurrent TERT promoter mutations occurred in >52% of non-cirrhotic discovery samples. Frequently mutated genes included TP53, CTNNB1, and APOB. Cytochrome P450 mediated metabolism was significantly downregulated. Structural variants were observed at MACROD2, WDPCP and NCKAP5 in >20% of samples. Furthermore, NR1H4 fusions involving gene partners EWSR1, GNPTAB, and FNIP1 were detected and validated in 2 non-cirrhotic samples. ConclusionGenomic analysis can elucidate mechanisms that may contribute to non-cirrhotic HCC tumorigenesis. The comparable mutational landscape between cirrhotic and non-cirrhotic HCC supports previous work suggesting a convergence at the genomic level during disease progression. It is therefore possible genomic-based treatments can be applied to both HCC subtypes with progressed disease. HighlightsO_LINon-cirrhotic HCC genomically resembles cirrhotic HCC C_LIO_LIComprehensive genome- and transcriptome-wide profiling allows detection of novel structural variants, fusions, and undiagnosed viral infections C_LIO_LINR1H4 fusions may represent a novel mechanism for tumorigenesis in HCC C_LIO_LINon-cirrhotic HCC is characterized by genotoxic mutational signatures and dysregulated liver metabolism C_LIO_LIClinical history and comprehensive omic profiling incompletely explain underlying etiologies for non-cirrhotic HCC highlighting the need for further research C_LI Short DescriptionThis study characterizes the genomic landscape of hepatocellular carcinomas (HCCs) in non-cirrhotic livers. Using 117 HCCs tumor/normal pairs, we identified 3,750 SNVs/INDELS with high variant frequency in TERT, TP53, CTNNB1, and APOB. CYP450 was significantly downregulated and many structural variants were observed. This characterization could assist in elucidating non-cirrhotic HCC tumorigenesis.

cancer biology↗

bioRxiv2021

Single Cell T Cell Receptor Repertoire Profiling for Dogs

BackgroundSpontaneous cancers in companion dogs are increasingly recognized as robust models of human disease. This recognition has led to translational clinical trials in companion dogs with osteosarcoma, lymphoma, melanoma, squamous cell carcinoma, and soft tissue sarcoma. The ability to precisely track tumor-specific immune responses in such clinical trials would benefit from reagents to perform species-specific single cell T cell receptor sequencing (scTCRseq). This technology defines clones of T cells reacting to immune interventions and can help identify the specific epitope of response. Single cell gene expression data give insights into the activity and polarization of the T cell. To date, scTCRseq has not been demonstrated for canine samples. MethodsSamples from two responding dogs in a trial of an autologous deglycosylated melanoma vaccine were selected to demonstrate applicability of scTCRseq in a cancer immunotherapy setting. A single-cell suspension of cryopreserved peripheral blood mononuclear cells (PBMC) was prepared for 10X single cell sequencing. Full length 10X cDNA was amplified using a custom-designed nested PCR of the alpha/beta V(D)J region. A library made from this enriched product (scTCRseq) and a 10X gene expression (GEX) library (scRNAseq) were sequenced on the NovaSeq 6000. Results1,850-2,172 estimated V(D)J-expressing cells yielded 87-103.7 million reads with 73.8%-75.8% mapped to a V(D)J gene (beta/alpha chains ratio 1.5:1). 43 TRAJ, 29 TRAV, 12 TRBJ, and 22 TRBV gene segments were observed representing 72.9%, 51.8%, 100%, and 62.9% of all known V and J gene segments respectively. A large diversity of clonotypes was captured with 966-1,253 TRA/TRB clonotypes identified. Both dogs also exhibited a small number of highly abundant T cell clonotypes suggesting the presence of an anti-tumor T cell population. GEX enriched libraries successfully defined large clusters of CD8+ and CD4+ T cells that overlapped with V(D)J-expressing cells. DiscussionThe developed reagents successfully generated scTCRseq data, for the first time, which allowed the T cell repertoire to be surveyed in dogs responding to anti-tumor immunotherapy. These reagents will allow longitudinal tracking of anti-tumor T cell dynamics in canine cancer immunotherapy trials.

genomics↗

bioRxiv2021

Evolution of the open-access CIViC knowledgebase is driven by the needsof the cancer variant interpretation community

CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. With nearly 300 contributors, CIViC contains peer-reviewed, published literature curated and expert-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViCs functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new evidence types (predisposing, oncogenic and functional). The growing CIViC knowledgebase distributes clinically-relevant cancer variant data currently representing >2500 variants in >400 genes from >2800 publications.

genomics↗

bioRxiv2021

Comparative Multiomic Analysis Reveals Low T Cell Infiltration as the Primary Feature of Tobacco Use in HPV(+) Oropharyngeal Cancer

PurposeTobacco use is an independent adverse prognostic feature in human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC). Despite this, the biologic features associated with tobacco use have not been systematically investigated in this population. We sought to characterize the genomic and immunologic features of HPV(+) OPSCC associated with tobacco use and adverse oncologic outcomes. Experimental DesignWhole exome sequencing of 47 primary HPV(+) OPSCC tumors was performed to investigate mutational differences associated with tobacco exposure. To characterize the tumor immune microenvironment (TIME), targeted mRNA hybridization was performed and immunohistochemical (IHC) staining was used to validate these findings. ResultsLow expression of transcripts in a T cell-inflamed gene expression profile (TGEP) was associated with tobacco use at the time of diagnosis and lower overall and disease-free survival. Tobacco use was associated with an increased proportion of T>C substitutions and a lower proportion of mutational signatures typically observed in HPV(+) OPSCC tumors, but was not associated with increases in mutational burden or the rate of recurrent oncogenic mutations. ConclusionsIn HPV(+) OPSCC, low T cell infiltration of primary tumors is associated with current tobacco use and worse oncologic outcomes. Rather than an increased mutational burden, tobaccos primary and clinically relevant association is immunosuppression of the primary TIME. An objective clinical assay like the TGEP, which quantifies immune infiltration of the primary TIME, may have value for HPV(+) OPSCC risk stratification in future clinical trials.

cancer biology↗

bioRxiv2018

Development of a precision oncology single molecule molecular inversion probe (smMIP) panel using a community-consensus approach

Clinical targeted sequencing panels are important for identifying actionable variants for cancer patients, however, there are currently no strategies to create impartial and rationally-designed panels to accommodate rapidly growing knowledge within the field. Here we use the Clinical Interpretations of Variants in Cancer database (CIViC) in conjunction with single-molecule molecular inversion probe (smMIP) capture to identify and design probes targeting clinically relevant variants in cancer. In total, 2,027 smMIPs were designed to target 111 eligible CIViC variants. The total genomic region covered by the CIViC smMIPs reagent was 61.5 kb. When compared to existing genome or exome sequencing results (n = 27 cancer samples from 5 tumor types), CIViC smMIP sequencing demonstrated a 95% sensitivity for variant detection (n = 61/64 variants). Variant allele frequency for variants identified on both sequencing platforms were highly concordant (Pearson correlation = 0.885; n = 61 variants). Moreover, for individuals with paired tumor/normal samples (n = 12), 182 clinically relevant variants missed by original sequencing were discovered by CIViC smMIPs sequencing. This design paradigm demonstrates the utility of an open-sourced database built on attendant community contributions for each variant with peer-reviewed interpretations. Use of a public repository for variant identification, probe development, and variant annotation could provide a transparent approach to build a dynamic next-generation sequencing-based oncology panel.

bioinformatics↗

bioRxiv2018

Spontaneous aggressive ERα+ mammary tumor model is driven by Kras activation

The NRL-PRL murine model, defined by mammary-selective transgenic rat prolactin ligand rPrl expression, establishes spontaneous ER+ mammary tumors, mimicking the association between elevated prolactin (PRL) and risk for development of ER+ breast cancer in postmenopausal women. Whole genome and exome sequencing in a discovery cohort (n=5) of end stage tumors revealed canonical activating mutations and copy number amplifications of Kras. The frequent mutations in this pathway were validated in an extension cohort, identifying activating Ras alterations in 79% (23/29) of tumors. Transcriptome analyses over the course of oncogenesis revealed marked alterations associated with Ras activity in established tumors, compared to preneoplastic tissues, in cell-intrinsic processes associated with mitosis, cell adhesion and invasion, as well as in the tumor microenvironment, including immune activity. These genomic analyses suggest that PRL induces a selective bottleneck for spontaneous Ras-driven tumors which may model a subset of aggressive clinical ER+ breast cancers.

cancer biology↗

bioRxiv2018

RegTools: Integrated analysis of genomic and transcriptomic data for discovery of splicing variants in cancer

Somatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools (www.regtools.org), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. RegTools was applied to over 9,000 tumor samples with both tumor DNA and RNA sequence data. We discovered 235,778 events where a splice-associated variant significantly increased the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotated them with the Variant Effect Predictor (VEP), SpliceAI, and Genotype-Tissue Expression (GTEx) junction counts and compared our results to other tools that integrate genomic and transcriptomic data. While many events were corroborated by the aforementioned tools, the flexibility of RegTools also allowed us to identify novel splice-associated variants and previously unreported patterns of splicing disruption in known cancer drivers, such as TP53, CDKN2A, and B2M, as well as in genes not previously considered cancer-relevant.

bioinformatics↗

bioRxiv2018

Standard operating procedure for somatic variant refinement of tumor sequencing data

PurposeManual review of aligned sequencing reads is required to develop a high-quality list of somatic variants from massively parallel sequencing data (MPS). Despite widespread use in analyzing MPS data, there has been little attempt to describe methods for manual review, resulting in high inter- and intra-lab variability in somatic variant detection and characterization of tumors.\n\nMethodsOpen source software was used to develop an optimal method for manual review setup. We also developed a systemic approach to visually inspect each variant during manual review.\n\nResultsWe present a standard operating procedures for somatic variant refinement for use by manual reviewers. The approach is enhanced through representative examples of 4 different manual review categories that indicate a reviewers confidence in the somatic variant call and 19 annotation tags that contextualize commonly observed sequencing patterns during manual review. Representative examples provide detailed instructions on how to classify variants during manual review to rectify lack of confidence in automated somatic variant detection.\n\nConclusionStandardization of somatic variant refinement through systematization of manual review will improve the consistency and reproducibility of identifying true somatic variants after automated variant calling.

genetics↗