bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract PO-078: Single-cell transcriptomic analysis of highly-multiplexed IHC images via antigen mapping
Authors: Govek Kiya W. , Troisi Emma C. , Miao Zhen , Woodhouse Steven , Camara Pablo G. 
Published: December 2020

Abstract
Recently developed technologies for digital imaging and highly multiplexed immunohistochemistry (mIHC) are enabling complex quantitative descriptions of tissue architecture. Imaging mass cytometry, multiplexed ion beam imaging, and co-detection by indexing can be used to profile the expression of dozens of proteins in a tissue section with single-cell resolution. Despite this progress, the amount of cell types and states that can be simultaneously identified by mIHC in a tissue section is still limited. Standard methods for identifying cell populations cluster cells according to expression similarities of the profiled antigens. These clusters are then manually annotated using previous knowledge of cell population markers. However, this is generally a partial, subjective, and biased process. Clusters often differ little in their antigenic profile and the interpretation of those differences is unclear. Moreover, the design of comprehensive antibody panels that include specific markers for every cell type and state present in the tissue is usually unfeasible. To overcome these limitations and increase the level of annotation of mIHC data, we propose an approach for enriching mIHC slides with single-cell RNA-seq data. Currently available single-cell RNA-seq technologies profile the expression of thousands of genes in each cell, allowing researchers to finely classify cells based on their gene expression profile. Some of the most recent approaches, like CITE-seq, REAP-seq, and Ab-seq, allow augmenting single-cell transcriptomes with concurrent protein measurements by staining dissociated cells with oligo-tagged antibodies. These approaches can be therefore used to determine the quantitative relation between gene and antigen expression levels. Here, we build upon CITE-seq and computational methods for the integration of single-cell omics data to identify and annotate cell populations in mIHC images in an automated way based on single-cell gene expression data from the same tissue. Our method, Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA), performs transcriptome-guided annotation of mIHC datasets. It increases the phenotypic resolution of histological analyses by enabling annotation of subtle cell populations, spatial patterns of transcription, and interactions between cell types. We use the murine spleen as a test system to benchmark the stability and performance of STvEA and demonstrate its utility by using it to annotate published CODEX and CyTOF datasets of this organ.
Citation Format: Kiya W. Govek, Emma C. Troisi, Zhen Miao, Steven Woodhouse, Pablo G. Camara. Single-cell transcriptomic analysis of highly-multiplexed IHC images via antigen mapping [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-078.
Abstract PO-085: Mass spectrometry imaging of N-glycans identifies racial discrepancies in human prostate tumors
Authors: Conroy Lindsey R. , Young Lyndsay E.A. , Austin Grant L. , Stanback Alexandra E. , Allison Derek B. , Gentry Matthew S. , Drake Richard R. , Sun Ramon C. 
Published: December 2020

Abstract
Prostate cancer is the most commonly diagnosed cancer in men worldwide. A critical knowledge gap in prostate cancer biology is the molecular events underlining higher incidence and mortality rate in Black men. Identifying molecular features that separate racial disparities is a critical step in prostate cancer research that could lead to predictive biomarkers and personalized therapy. N-linked glycosylation is a required co-translational event during protein folding that modulates many biological processes, such as cell adhesion, immune modulation, cell-matrix interactions, and cell proliferation. Recently, aberrant N-linked glycosylation has been reported in prostate cancers. However, the full clinical implications of dysregulated glycosylation in prostate cancer has yet to be explored. Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) is a new and innovative technique that combines mass spectrometry with imaging, enabling the detection of glycans with spatial distribution. Herein, we performed MALDI-MSI analysis to characterize the N-glycan profile from tissue microarrays of over 100 patient tumors banked at the University of Kentucky with over 10 years of follow-up data. Additionally, we performed MALDI-MSI analysis on large sections of prostate cancer to define the regional distribution of N-glycans within the tumor microenvironment. We successfully identified 46 unique glycans from readily available formalin-fixed paraffin-embedded prostate tissue, and found significant N-glycan dysregulation between benign and prostate tumor tissue across all patient groups. High mannose as well as tri- and tetra-antennary N-glycans were predominantly found in tumor tissue and correlate with increased tumor grade. Surprisingly, several species of N-glycans were profoundly different between early grade prostate tumors resected from White and Black patients. Further, these glycans predict opposing overall survival between White and Black patients with prostate cancer. These data suggest differential N-linked glycosylation underline the racial disparity of prostate cancer prognosis. Our study highlights the potential clinical applications of MALDI-MSI for digital pathology and biomarker applications, and reveals molecular features that contribute to the racial disparity in diagnosis and survival of prostate cancer patients.
Citation Format: Lindsey R. Conroy, Lyndsay E.A. Young, Grant L. Austin, Alexandra E. Stanback, Derek B. Allison, Matthew S. Gentry, Richard R. Drake, Ramon C. Sun. Mass spectrometry imaging of N-glycans identifies racial discrepancies in human prostate tumors [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-085.
Abstract PO-090: Protein-based immune profiles of basal-like vs luminal breast cancers
Authors: Walens Andrea , Olsson Linnea T. , Gao Xiaohua , Hamilton Alina M. , Kirk Erin L. , Cohen Stephanie M. , Midkiff Bentley R. , Xia Yongjuan , Sherman Mark E. , Nikolaishvili-Feinberg Nana , Hoadley Katherine A. , Troester Melissa A. , Calhoun Benjamin C. 
Published: December 2020

Abstract
Background: Tumor infiltrating lymphocytes (TILs) play an important, but incompletely understood role in chemotherapy response and prognosis. In breast cancer, there appear to be distinct immune responses by subtype, but most studies have used limited numbers of protein markers or bulk sequencing of RNA to characterize immune response, in which spatial organization cannot be assessed. Methods: To identify immune phenotypes of Basal-like vs. Luminal breast cancer we used the GeoMx® (NanoString) platform to perform digital spatial profiling (DSP) of immune-related proteins in tumor whole sections and tissue microarrays (TMA). Visualization of CD45, CD68, or pan-Cytokeratin by immunofluorescence was used to select regions of interest (ROIs) in formalin-fixed paraffin embedded tissue sections. 44 antibodies representing stromal markers and multiple immune cell types were applied to quantify the tumor microenvironment. Results: In whole tumor slides, immune hot spots (CD45+) had increased expression of many immune markers, suggesting a diverse and robust immune response. In epithelium-enriched areas, immune signals were also detectable and varied by subtype, with Regulatory T cell (Treg) markers (CD4, CD25, FOXP3) being higher in Basal-like vs. Luminal breast cancer. Extending these findings to TMAs with more patients (n=75), we confirmed subtype-specific immune profiles, including enrichment of Treg markers in Basal-likes. Conclusion: This work demonstrated that immune responses can be detected in epithelium-rich tissue, and that TMAs are a viable approach for obtaining important immunoprofiling data. In addition, we found that immune marker expression is associated with BC subtype, suggesting possible prognostic or targetable differences.
Citation Format: Andrea Walens, Linnea T. Olsson, Xiaohua Gao, Alina M. Hamilton, Erin L. Kirk, Stephanie M. Cohen, Bentley R. Midkiff, Yongjuan Xia, Mark E. Sherman, Nana Nikolaishvili-Feinberg, Katherine A. Hoadley, Melissa A. Troester, Benjamin C. Calhoun. Protein-based immune profiles of basal-like vs luminal breast cancers [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-090.
Abstract PO-097: High resolution analysis of clonal dynamics using lineage tracing and single cell transcriptomics
Authors: Brenner Eric A. , Morgan Daylin , Al'Khafaji Aziz , Gutierrez Catherine , Wu Catherine J. , Brock Amy 
Published: December 2020

Abstract
The immense evolutionary capacity of cancer poses major challenges to current therapeutic efforts, and results from the vast clonal heterogeneity and ability of individual cancer cells to adapt to diverse selective pressures. More complete mechanistic understanding of the basis of therapeutic resistance has been limited by difficulties in coupling genetic identity of cells to their respective transcriptomic and functional outputs. To this end, we developed a novel high-complexity expressed barcode system, ClonMapper, that integrates DNA barcoding with single-cell RNA-sequencing and clonal isolation to characterize thousands of clones within a mixed cancer cellpopulation. In applying this system to breast cancer and B cell cancer cell lines in the setting of resistance to doxorubicin and fludarabine-based chemotherapy, we discover pretreatment sub-populations with distinct expression profiles that not only confer distinct treatment survivorship trajectories, but also provide the basis for long-term clonal equilibrium between co-existing clones in the absence of treatment. These data reveal the diverse clonal characteristics and therapeutic responses of a heterogeneous cancer cell population and highlight the unprecedented resolution that can be achieved using ClonMapper.
Citation Format: Eric A. Brenner, Daylin Morgan, Aziz Al'Khafaji, Catherine Gutierrez, Catherine J. Wu, Amy Brock. High resolution analysis of clonal dynamics using lineage tracing and single cell transcriptomics [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-097.
Abstract PO-101: Transcriptional heterogeneity in lung adenocarcinoma reveals distinct therapeutic vulnerabilities
Authors: Daemen Anneleen , Cooper Jonathan E. , Myrta Szymon , Wongchenko Matthew J. , Lin Eva , Long Jason E. , Foreman Oded , Modrusan Zora , Tremayne Jarrod , de la Cruz Cecile C. , Merchant Mark , Martin Scott E. , Yan Yibing , Junttila Melissa R. 
Published: December 2020

Abstract
Lung adenocarcinomas comprise the largest fraction of non-small cell lung cancer, which is the leading cause of cancer deaths. 75% of adenocarcinomas lack targeted therapies due to scarcity of druggable drivers. Here we leverage transcriptional data from &gt;800 early-stage and advanced patients to classify tumors based on signaling similarities and discover subgroups within this unmet patient population. We identify three robust subtypes dubbed Mucinous, Proliferative, and Mesenchymal with respective pathway phenotypes. These transcriptional states lack discrete and causative mutational etiology as evidenced by similarly distributed oncogenic drivers including KRAS and EGFR. The subtypes capture heterogeneity even amongst tumors lacking known oncogenic drivers. Paired multi-regional intratumoral biopsies demonstrate unified subtypes despite divergently evolved pro-oncogenic mutations, indicating subtype stability during selective pressure. Heterogeneity amongst in vitro and in vivo preclinical models is expounded by the human lung adenocarcinoma subtypes and can be leveraged to discover subtype-specific vulnerabilities. As proof-of-concept, we identify differential subtype response to MEK pathway inhibition in a chemical library screen of 89 lung cancer cell lines, which reproduces across model systems and a clinical trial, supporting prognostic utility of transcriptional subtyping. Our findings support forward translational relevance of transcriptional subtypes, where further exploration therein may improve lung adenocarcinoma treatment.
Citation Format: Anneleen Daemen, Jonathan E. Cooper, Szymon Myrta, Matthew J. Wongchenko, Eva Lin, Jason E. Long, Oded Foreman, Zora Modrusan, Jarrod Tremayne, Cecile C. de la Cruz, Mark Merchant, Scott E. Martin, Yibing Yan, Melissa R. Junttila. Transcriptional heterogeneity in lung adenocarcinoma reveals distinct therapeutic vulnerabilities [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-101.
Abstract PO-111: Identifying epigenetic mechanisms for proliferation and self-renewal of tumor-propagating cells (TPC) in lung cancer
Authors: Fuentes Eunice Lopez , Sweet-Cordero Alejandro 
Published: December 2020

Abstract
Lung cancer is a leading cause of death worldwide and lung adenocarcinoma (LUAD) is the most common subtype. LUAD tumors have a functional heterogeneity in regard to tumor-propagating capacity. Cells with an increased capacity to sustain tumor growth are called tumor-propagating cells (TPC or cancer stem cells) and they have been associated with chemoresistance and tumor relapse. A TPC population identified in a mouse model of LUAD (Kras G12D/wt/p53 fl/fl)(KP) sustain growth in serial orthotopic transplantations and are distinguished by expression of Notch receptors. Furthermore, TPCs gene expression signature is associated with a worse prognosis in human cancer. My hypothesis is the TPCs gene expression may be regulated by global chromatin alterations driven by epigenetic regulators. In LUAD, secondary tumors derived from TPC or non-TPC sorted populations regenerated both TPC and non-TPC populations, recapitulating the heterogeneity of the original tumor, suggesting TPC plasticity and supporting an epigenetic regulation. The main goal of my work is to identify and understand epigenetic mechanisms of TPC maintenance in LUAD and determine their relevance for other cancers. TPC and non-TPC populations show dramatic differential protein expression of H3K4me3 and H4K16ac histone modifications associated with transcription activation. To better understand how these histone marks alter the genome of TPCs, I performed ATAC-seq (Assay for Transposase-Accessible Chromatin followed by sequencing) and CARM (CRISPR/Cas9-assisted removal of mitochondrial DNA) to remove mitochondrial DNA prior to sequencing in both TPC and non-TPC populations from primary cells of KP mouse models. I have identified unique open chromatin regions in TPCs which were associated to the closest gene. For TPCs, the main enriched cluster of pathways included Notch signaling pathway and pathways associated with remodeling of the tumor microenvironment. In parallel, I am customizing an epigenetic short hairpin RNA (shRNA) library to screen epigenetic regulators implicated in plasticity and self-renewal ability of TPCs and I will evaluate them whether function through Notch signaling.
Citation Format: Eunice Lopez Fuentes, Alejandro Sweet-Cordero. Identifying epigenetic mechanisms for proliferation and self-renewal of tumor-propagating cells (TPC) in lung cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-111.
Abstract PO-113: Molecular interplay between dormant bone marrow-resident tumor cells (BMRCs) and CTCs in breast cancer
Authors: Boral Debasish , Liu Haowen N. , Kenney S. Ray , Marchetti Dario 
Published: December 2020

Abstract
Despite widespread knowledge that bone marrow-resident breast cancer cells (BMRCs) affect tumor progression, signaling mechanisms of BMRCs implicated in maintaining long-term dormancy have not been characterized. Further, there is no model of clinical dormancy that can comprehensively emulate the entire spectrum of heterogeneous clones of Circulating Tumor Cells (CTCs) present in cancer patients. To overcome these hurdles, we developed a new experimental model of clinical dormancy employing patient-isolated de novo CTCs and their injection in xenografts with subsequent tumor monitoring and CTC characterization (ex vivo CTCs). We hypothesized that significant distinctions exist between signaling pathways of bone marrow-homing vs metastasis-competent CTCs upon transplantation in xenografts. Comparative transcriptomic analyses of ex vivo vs de novo CTCs identified increased mTOR signaling – a critical pathway frequently dysregulated in breast cancer and implicated in cell survival and dormancy – with contrasting actions by its two complementary arms (mTORC2/mTORC1). Heightened mTORC2 downstream targets augmented quiescent CTCs (Ki67-/RBL2+ cells) in paired breast cancer tissues, along with high mTORC2 activity in solitary BMRCs and tissue-resident CTCs. Further, shRNA mediated knockdown of RICTOR, an essential component of mTORC2, augmented Ki67/PCNA biomarker expression and proliferation. Collectively, these findings suggest that the balance between mTORC1 vs mTORC2 signaling regulates CTC-associated mitotic and/or dormancy characteristics. Further elucidation of mTOR-mediated CTC dormancy will provide novel strategies for therapeutic interventions in patients having early-event metastatic seeding but yet to develop clinically-detectable overt metastasis.
Citation Format: Debasish Boral, Haowen N. Liu, S. Ray Kenney, Dario Marchetti. Molecular interplay between dormant bone marrow-resident tumor cells (BMRCs) and CTCs in breast cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-113.
Abstract PO-127: Single-cell liquid biopsy reveals circulating heterogeneity and converging subpopulations in relation to immunotherapy response in melanoma
Authors: Song Qianqian , Forbes Elizabeth , Miller Lance D. , Triozzi Pierre L. , Liu Liang , Zhang Wei , Soto-Pantoja David R. 
Published: December 2020

Abstract
Though treatment with immune checkpoint blockage (ICB) has greatly improved clinical outcomes, not all patients respond to this treatment. Being able to predict which patients are likely to respond would be a significant clinical advance. Thus there remains a need for predictive biomarkers to determine in advance those with the most potential to benefit from immune checkpoint blockade. To date, most biomarkers of response are identified in tumor tissue, whereas biomarkers that can be assessed from peripheral blood are more desirable, due to the ease of access and reproducibility of sampling. To identify biomarkers associated with ICB response from peripheral blood, we apply single cell RNA sequencing to 24 peripheral blood mononuclear cell (PBMC) samples, collected from 12 stage III and IV melanoma patients before and after treatment with anti-PD1 monotherapy. Among these 12 patients, 6 are responders and 6 are non-responders. After quality control, a total of 62,273 single cells remains for further analysis. To define the cell type landscape in an unbiased manner, unsupervised clustering is used. We identify 20 robust cell clusters, including two B cell clusters (B-cell_1; B-cell_2), three myeloid clusters (monocytes, myeloid-derived suppressor cells, and M2 macrophages), twelve clusters enriched for T/NK cells, two clusters of platelets, and Hematopoietic Stem and Progenitor Cells (HSPCs). Across all patients, cell composition differs between pre- and post-treatment samples. Strikingly, responders have significant greater proportions of B-cell_1 cells in their pre-treatment samples than non-responders. At gene level, our analysis identifies an individual overexpressed marker in B-cell_1, i.e. IGLC3, which is highly enriched in responders than non-responders before treatment. In summary, our analysis identifies specific cell type and gene within patients’ PBMC samples that can serve as predictive biomarkers for patient’s response to ICB.
Citation Format: Qianqian Song, Elizabeth Forbes, Lance D. Miller, Pierre L. Triozzi, Liang Liu, Wei Zhang, David R. Soto-Pantoja. Single-cell liquid biopsy reveals circulating heterogeneity and converging subpopulations in relation to immunotherapy response in melanoma [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-127.
Abstract PO-130: The mitochondrial protein ATAD3A promotes cisplatin resistance in oral squamous cell carcinoma
Authors: Lang Liwei , Duncan Leslie , Jensen Caleb , Shay Chloe , Teng Yong 
Published: December 2020

Abstract
Cisplatin is well-known for its damaging effect on nuclear DNA, leading to cell death due to blockage of DNA replication and transcription, but this activity cannot fully explain why cisplatin displays cytotoxicity in post-mitotic tissues, suggesting other mechanisms may be in play. Many studies have challenged the current model of cisplatin resistance, however, the precise mechanism behind is still unknown. Here, we report that the mitochondrial protein ATAD3A functions as an oncogene in oral squamous cell carcinoma (OSCC), promoting cell proliferation and enhancing the ability of colony formation and anchorage-independent growth. Moreover, ATAD3A is involved in cisplatin resistance in OSCC, and knockdown of ATAD3A enhanced the sensitivity of OSCC cells to cisplatin. It appears that ATAD3A-mediated cisplatin resistance is regulated by other mechanisms rather than its expression levels, as evidenced by overexpression of a Walker A (WA) dead mutant of ATAD3A leads to a suppression in OSCC cell growth and resensitizes cisplatin-resistant OSCC cells to this drug, indicating a potent dominant-negative effect of defective ATP-binding of ATAD3A in chemotherapy. Our study demonstrates for the first time that ATAD3A plays an oncogenic role in OSCC and abrogating its ATP-binding ability may represent a promising regimen for better treatment of patients with OSCC, especially for those who suffer from cisplatin-resistance.
Citation Format: Liwei Lang, Leslie Duncan, Caleb Jensen, Chloe Shay, Yong Teng. The mitochondrial protein ATAD3A promotes cisplatin resistance in oral squamous cell carcinoma [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-130.