bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract PO-037: Characterization of stemness and immunogenicity of cancer stem cells of intrahepatic cholangiocarcinoma
Authors: Fu Jianyang , Zhu Yunhua , McGrath Nichole A. , Cam Maggie , Xie Changqing
Published: December 2020

Cholangiocarcinoma (CCA) is one of leading causes of cancer related mortality with limited treatment options. Cancer stem cells (CSCs) have been recognized as a critical driving force of CCA initiation and drug-resistance, representing an attractive and innovative therapeutic target. In this study, single-cell transcriptomic landscape of cancer biospecimens from 10 patients with intrahepatic cholangiocarcinoma (iCCA) were investigated. We characterized CSC in CCA subtypes and identified the differential genes between CSCs and malignant cells. We found that there is the heterogeneity of CSCs in iCCA in terms of stemness makers and immunity per se. Our study pointed to low immunity spectrum of CSCs of iCCA that contribute to immune evasion. We found that SPP1 gene is highly expressed compared to malignant cells in CSC, which indicated that Osteopontin, which is coded by SPP1, may acts as an immune checkpoint to suppress T cell activation and confer host tumor immune tolerance. Our analysis from TCGA database also confirmed that, stemness was strongly associated with cell native immunosuppressive pathway and SPP1 gene expression. Our data indicate that CSC evade innate immune suppression through induced SPP1 expression and Osteopontin may serve as a potential therapeutic intervention for CCA patients.

Citation Format: Jianyang Fu, Yunhua Zhu, Nichole A. McGrath, Maggie Cam, Changqing Xie. Characterization of stemness and immunogenicity of cancer stem cells of intrahepatic cholangiocarcinoma [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-037.
Abstract PO-039: Spatially discrete signalling niches regulate fibroblast heterogeneity in human lung cancer
Authors: Hanley Christopher Jon , Waise Sara , Rachel Parker , Lopez Maria-Antoinette , Taylor Julian , Kimbley Lucy , West Jonathon , Ottensmeier Christian , Rose-Zerilli Mat , Thomas Gareth
Published: December 2020

In this study we set out to define the prominent fibroblast subpopulations found in human non-small cell lung cancer. Fibroblasts are functionally heterogeneous cells, capable of promoting and suppressing tumor progression. Across cancer types, the extent and cause of this phenotypic diversity remains unknown. We used single-cell RNA sequencing and multiplexed immunohistochemistry to examine fibroblast heterogeneity in human lung and non-small cell lung cancer (NSCLC) samples. We then performed in silico and in vitro analyses to examine the molecular mechanisms regulating fibroblast phenotypes. Single-cell RNA sequencing identified seven fibroblast subpopulations: including inflammatory fibroblasts and myofibroblasts (representing terminal differentiation states), quiescent fibroblasts, proto-myofibroblasts (x2) and proto-inflammatory fibroblasts (x2). Multiplex immunohistochemistry showed that these fibroblast subpopulations were variably distributed throughout tissues but accumulated at discrete niches associated with differentiation status. Bioinformatics analyses suggested TGF-β1 and IL-1 as key regulators of myofibroblastic and inflammatory differentiation respectively. However, in vitro analyses showed that whilst TGF-β1 stimulation in combination with increased tissue tension could induce myofibroblast marker expression, it failed to fully re-capitulate ex-vivo¬ phenotypes. Similarly, IL-1β treatment only induced upregulation of a subset of inflammatory fibroblast marker genes. In silico modelling of ligand-receptor signaling identified additional pathways and cell interactions likely to be involved in fibroblast activation. This highlighted a potential role for IL-11 and IL-6 (among other ligands) in myofibroblast and inflammatory fibroblast activation respectively. This analysis provides valuable insight into fibroblast subtypes and differentiation mechanisms in NSCLC.

Citation Format: Christopher Jon Hanley, Sara Waise, Parker Rachel, Maria-Antoinette Lopez, Julian Taylor, Lucy Kimbley, Jonathon West, Christian Ottensmeier, Mat Rose-Zerilli, Gareth Thomas. Spatially discrete signalling niches regulate fibroblast heterogeneity in human 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-039.
Abstract PO-043: Plexiform neurofibroma microenvironment at single-cell resolution
Authors: Kershner Leah J. , Wu Jianqiang , Salomonis Nathan , Ratner Nancy
Published: December 2020

Plexiform neurofibromas (PN) are benign nerve sheath Schwann cell tumors, which occur in at least 50% of individuals with loss of function mutations in the NF1 tumor suppressor gene, an off signal for RAS-GTPases. Tumors form, at least in part, through activation of the RAS-MAPK pathway in Schwann cells. Though benign, PN can cause significant morbidity and are often inoperable due to integration with vital peripheral nerves. Recent clinical trials have shown that MEK inhibition can shrink most PN, but continued MEK inhibition is required for sustained response. It is recognized that PN contain many cell types in addition to Schwann cells, and that Schwann cells are present in varying proportions. However, biomarkers for many cell types have not yet been identified, and it is not known whether subpopulations of certain cell types exist within neurofibromas. To address these issues, we performed single cell RNA sequencing on PN using a genetically engineered mouse model which closely recapitulates human PN. We have characterized tumor composition, and identified PN Schwann cells, satellite glial cells, endothelial cells, fibroblasts, macrophages, T cells, dendritic cells, and other previously unreported cell types. We identified multiple subpopulations of Schwann cells, macrophages and fibroblasts within benign PN. Cluster by cluster comparison of PN to age-matched healthy nerve and to pretumor nerve tissue from the same mouse model revealed gene regulatory networks that are significantly altered in PN, after loss of NF1 function. Further, inference of cell-cell communication networks shows robust changes in PN that are absent before tumors form, and that are potentially targetable. Comparison to MEK inhibitor treated PN and to human PN sc-RNASeq is ongoing. Taken together, these approaches characterize PN, provide potential biomarkers for cell populations and identify targets for drug treatment. Supported by NIH (NINDS-28840) and the DOD Program on Neurofibromatosis. LK is supported by NIH Ruth L. Kirschstein T32.

Citation Format: Leah J. Kershner, Jianqiang Wu, Nathan Salomonis, Nancy Ratner. Plexiform neurofibroma microenvironment at single-cell resolution [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-043.
Abstract PO-047: Anti-proliferative effect of cannabidiol (CBD) against B and T-cell lymphoma
Authors: Omer Saba , Boothe Dawn , Mansour Mohammed , Dhanasekaran Muralikrishnan , Pondugula Satyanarayana
Published: December 2020

In the last two decades, Cannabinoids have been studied extensively for its potential use in various fields of medicine including oncology. Today some of the cannabinoids are FDA approved for the treatment of chemotherapy-induced side effects in cancer treatment however, studies are showing their effect against tumor growth as well. Aggressive B cell lymphoma or Non-Hodgkin lymphoma (NHL) is the fifth leading cause of human cancer death and is the second fastest-growing cancer with regard to mortality in people as 30% of patients develop resistance against chemotherapy. For this reason, it is essential to develop novel strategies to improve the outcome of patients suffering from aggressive or therapy-resistant lymphoma. The purpose of this study was to demonstrate the antitumor effects of cannabinoids in B cell lymphoma using canine as a model due to striking similarities b/w canine and human B cell lymphoma in histology, biology and gene expression. For this study, Canine B cell lymphoma cell lines 1771 and CLBL1 were cultured in RPMI. Expression of cannabinoid receptors studied using qPCR. Based on receptor expression cells were treated with receptor agonists (AEA, 2AG, CBD, THC, WIN and HU-210,) and antagonists (S16 and S28). Cell viability assessed using MTT assay. Biochemical analysis performed using spectrofluorometry to evaluate apoptotic makers involved in inducing cell death. Data was analyzed using ordinary one way ANOVA on Prism software. All B cell lymphoma cell lines showed positive expression of CB1 and CB2 receptors. Cell viability assay demonstrated a dose-dependent decrease in cell proliferation with all cannabinoid receptor agonists used except for 2AG. Biochemical analysis showed a decrease in nitrite and caspase activity in treated cells as compared to control untreated cells. Our results suggest that cannabinoids have an anti-proliferative and apoptotic effect on canine lymphoma cells and it can be developed as a potential anti-cancer agent for the treatment of canine and human B cell lymphoma.

Citation Format: Saba Omer, Dawn Boothe, Mohammed Mansour, Muralikrishnan Dhanasekaran, Satyanarayana Pondugula. Anti-proliferative effect of cannabidiol (CBD) against B and T-cell lymphoma [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-047.
Abstract PO-051: Tumor stem cells arising from a non-stem origin maintain a differentiated phenotype and modulate T cell activity
Authors: Scurrah Cherie’ R. , Chen Bob , Markham Nick , Simmons Alan , Southard-Smith Austin , Macedonia Mary , Choi Eunyoung , Liu Qi , Washington Kay , Coffey Bob , Goettel Jeremy , Lau Ken
Published: December 2020

Tumor stem cells (TSCs) contribute to cancer mortality via therapeutic resistance, tumor recurrence, and metastatic mechanisms. However, the origins of the stem capacity to TSCs remains in question, but all TSCs descend from the original tumor cell-of-origin where the first oncogenic event occurred. Tumors arising from different cells-of-origin are histologically identical, but it is unknown whether TSCs that arose from different origins are molecularly and functionally distinct. Using mouse models driving identical Apc mutations from Lrig1-expressing and Mist1-expressing cells, we characterized TSCs of tumors driven from stem and non-stem cells-of-origin using single cell RNA sequencing (scRNA-seq), organoids, and multiplexed imaging. We revealed reduced stem capacity but increased class II antigen presentation ability for non-stem cell (Mist1) driven TSCs compared with stem cell (Lrig1) driven TSCs, which resulted in a favorable immune microenvironment skewed towards active cytotoxic response in Mist1-driven tumors. These results suggest that the cell-of-origin of tumorigenesis provides a specific context by which TSCs are generated, dictating their interactions with the tumor microenvironment.

Citation Format: Cherie’ R. Scurrah, Bob Chen, Nick Markham, Alan Simmons, Austin Southard-Smith, Mary Macedonia, Eunyoung Choi, Qi Liu, Kay Washington, Bob Coffey, Jeremy Goettel, Ken Lau. Tumor stem cells arising from a non-stem origin maintain a differentiated phenotype and modulate T cell activity [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-051.
Abstract PO-055: Global immune characterization of hepatocellular carcinoma identifies macrophage and T cell subsets related to disease progression
Authors: Song Guohe , Shi Yang , Lin Youpei , Zhang Juan , Yang Shuaixi , Gao Qiang
Published: December 2020

Diverse immune cells in the tumor microenvironment form a complex ecosystem, but our knowledge of their heterogeneity and dynamics within hepatocellular carcinoma (HCC) remains poorly understood. We assess the plasticity and phenotypes of immune cells within HCC microenvironment at single-cell level. We performed single-cell RNA sequencing on 41,698 immune cells from 7 pairs of HCC tumors and nontumor liver tissues. We combined bioinformatic analyses, flow cytometry and multiplex immunohistochemistry to assess the heterogeneity of different immune subsets in functional characteristics, transcriptional regulation, phenotypic switching, and interactions. We identified 29 immune subsets of myeloid cells, NK cells, and lymphocytes with unique transcriptomic profiles in HCC. A highly complex immunological network was shaped by immune subsets with diverse characteristics that can transit among different states and mutually engage through intercellular communication. Notably, we identified a subset of M2 macrophage with high expression of CCL18 and transcription factor CREM that was enriched in advanced HCC patients, and potentially participated in tumor progression. We also detected a new subset of activated CD8+ T cells highly expressing XCL1 that correlated with better patient survival, and possibly enhanced anti-tumor response. Meanwhile, distinct transcriptomic signatures, cytotoxic phenotypes and evolution trajectory of effector CD8+ T cells from early-stage to advanced HCC were also identified. Our study presents a comprehensive insight for dissecting the immune microenvironment in HCC and highlights novel macrophage and T cell subsets that could be further exploited in future immunotherapy.

Citation Format: Guohe Song, Yang Shi, Youpei Lin, Juan Zhang, Shuaixi Yang, Qiang Gao. Global immune characterization of hepatocellular carcinoma identifies macrophage and T cell subsets related to disease progression [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-055.
Abstract PO-059: The genomic landscape of the in situ to invasive ductal breast carcinoma transition shaped by the immune system
Authors: Trinh Anne , Gil Del Alcazar Carlos R. , Shukla Sachet A. , Chin Koei , Chen Young Hwan , Thibault Guillaume , Eng Jennifer , Jovanovic Bojana , Aldaz C. Marcelo , Park So Yeon , Jong Joon , Wu Catherine , Gray Joe , Polyak Kornelia
Published: December 2020

Background: The transition from ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) is an evolutionary bottleneck where progression occurs only in 30% of patients. Whilst the genetic drivers of this transition remain poorly understood, we have previously shown that immune escape is a key event. In this study, we profile the evolutionary trajectory of matched pure DCIS and IDC in the context of the immune microenvironment. Methods: We have evaluated changes in copy number profiles, mutational profiles, expression and neoantigen load in 6 cases of matched pure DCIS and IDC using exome and RNA sequencing. We have integrated this information with topologic assessment of H&E images and cyclic immunofluorescence. Results: We provide evidence for an evolutionary bottleneck during DCIS to IDC in matched patient samples, showing that copy number aberrations are early events, but low overlap in mutational profiles. Variation in immune composition and spatial orientation can arise as early as in DCIS and are subtype specific. Tumor-specific copy number changes including loss of MHC-I presentation machinery or changes at cytokine rich loci specifically in ER− tumors could contribute to a more immunosuppressive environment in IDC. Oncogenic hotspot mutations can present as neoantigens yet are paradoxically conserved during the DCIS-to-IDC transition. We suggest these mutations have a secondary immune-modulatory function or may be present in normal tissue, escaping immune surveillance as early as in DCIS. Conclusions: We show both genomic and microenvironmental differences in matched pure DCIS and recurrent IDC, highlighting that progression is shaped by both tumor and immune system at this evolutionary bottleneck.

Citation Format: Anne Trinh, Carlos R. Gil Del Alcazar, Sachet A. Shukla, Koei Chin, Young Hwan Chen, Guillaume Thibault, Jennifer Eng, Bojana Jovanovic, C. Marcelo Aldaz, So Yeon Park, Joon Jong, Catherine Wu, Joe Gray, Kornelia Polyak. The genomic landscape of the in situ to invasive ductal breast carcinoma transition shaped by the immune system [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-059.
Abstract PO-066: Computational identification of key pathway and differentially-expressed gene signatures in ovarian cancer stem cells
Authors: Fu Renata H. , Bai Yongsheng , Wang Qi-En
Published: December 2020

Many studies have demonstrated the causativeness of cancer stem cells (CSCs), which are able to self-renew, metastasize, differentiate, and resist chemotherapy. Although multiple cell surface markers have been used to identify and isolate cancer stem cells, their uncertainty makes these surface markers unreliable in identifying heterogeneous cancer stem cells. Some transcription factors have been shown to be overexpressed in CSCs residing in multiple types of cancers, and some pathways have been found to regulate CSC populations. However, since some CSCs do not express all of the identified genes, it is important to establish a panel of genes and pathways that can consistently distinguish CSCs. To determine a panel of consensus genes or pathways that can be used to recognize CSCs, we attempted to identify differentially expressed genes and enriched pathways in CSCs, which we call cancer stem cell signature. In this study, we employed two ovarian cancer RNA-seq data (GSE33874 and GSE82304) from the Gene Expression Omnibus (GEO) and considered genes with significant fold changes (|logFC|≥1). We used ComPath to identify pathways that are enriched in each of our selected RNA-seq datasets, then we developed a customized python script to reveal pathways commonly enriched in both datasets. We subsequently applied ComPath’s mapping catalog to elucidate equivalent or hierarchical relationships across common pathways from three different databases (KEGG, Reactome, and WikiPathways). In total, we identified 241 commonly upregulated genes and 96 commonly downregulated genes. We also present 30 equivalent relationships and 98 hierarchical relationships between pathways. Our results confirm several pathways that are reported to be involved in CSC regulation, such as the Wnt signaling pathway and the Hedgehog pathway. Furthermore, we also identified multiple pathways that have been previously associated with poor prognosis or high risk of ovarian cancer, such as the Prolactin signaling pathway and the coagulation cascade, indicating that these pathways may also be involved in the maintenance of ovarian cancer stem cells. We will continue to investigate ovarian CSC gene and pathway signatures by involving more RNA-seq data and pathway analysis databases.

Citation Format: Renata H. Fu, Yongsheng Bai, Qi-En Wang. Computational identification of key pathway and differentially-expressed gene signatures in ovarian cancer stem cells [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-066.
Abstract PO-071: MYC influences metastatic heterogeneity in pancreatic cancer
Authors: Maddipati Ravikanth , Norgard Robert J. , Baslan Timour , Rathi Komal S. , Zhang Amy , Raman Pichai , Wengyn Max D. , Yamazoe Taiji , Li Jinyang , Balli David , LaRiviere Michael , Folkert Ian W. , Millstein Ian D. , Bermeo Jonathan , Carpenter Erica L. , Lowe Scott , Iacobuzio-Donahue Christine , Notta Faiyaz , Stanger Ben Z.
Published: December 2020

Tumor heterogeneity - resulting from genetic and epigenetic alterations acquired during tumor progression - is a critical driver of phenotypic diversity in most cancers. A lethal consequence of tumor heterogeneity is the acquisition of metastatic traits by tumor cells, leading to poor clinical outcomes. This remains a major problem in pancreatic ductal adenocarcinoma (PDAC), which continues to have the worst prognosis of any major cancer type. While most cases of PDAC present with metastatic disease at the time of diagnosis, the patterns and burden of metastasis can vary widely, with some patients exhibiting a limited metastatic burden while others have more extensive spread, which impacts clinical outcomes. However, the biological and functional differences that drive metastatic heterogeneity are poorly understood.

Citation Format: Ravikanth Maddipati, Robert J. Norgard, Timour Baslan, Komal S. Rathi, Amy Zhang, Pichai Raman, Max D. Wengyn, Taiji Yamazoe, Jinyang Li, David Balli, Michael LaRiviere, Ian W. Folkert, Ian D. Millstein, Jonathan Bermeo, Erica L. Carpenter, Scott Lowe, Christine Iacobuzio-Donahue, Faiyaz Notta, Ben Z. Stanger. MYC influences metastatic heterogeneity in pancreatic 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-071.
Abstract PO-072: Control of inter- and intra-patient cancer heterogeneity is a predictively accurate explanation for the success of many combination therapies for solid and hematological cancers
Authors: Palmer Adam C. , Izar Ben , Hwangbo Haeun , Sorger Peter K.
Published: December 2020

Developing optimal drug combinations is one of the central challenges of cancer treatment research: drug combinations are used to treat most types of cancer, and are almost exclusively responsible for cures of advanced cancers. However, historically successful combination therapies were developed empirically, and the mechanistic basis for their efficacy has been largely speculative. I will present experiments, models, and computational analyses of clinical trial data, to investigate the mechanistic basis of clinically successful combination therapies across 12 types of cancer and 30 different therapies. These studies consistently identify the control of cancer heterogeneity between-patients (inter-tumor) and within-patients (intra-tumor) by independently active drugs as critical contributors to the efficacy of combination therapies in human patients. The key approaches for data analysis and modeling in these studies consist of adapting classical pharmacological concepts to the complex situation of populations of cancers with heterogeneous drug sensitivity. Synergistic drug interactions in humans appears uncommon among approved combination therapies, and even curative regimens exhibit drug additivity in experimental measurements and in clinical outcomes. Mathematical descriptions of heterogeneity in cellular or patient populations, and quantitative experimental measurements of how drug combinations address heterogeneity, lead to accurate predictions of clinical trial results for a diverse range of combination therapies, including those with immune checkpoint inhibitors (correlation between observed and expected Progression Free Survival in 14 trials, Pearson r = 0.98, P < 10^-8) and curative chemotherapy regimens for hematological cancers (correlation between observed and expected response rates and cure rates in 40 years of trials in childhood ALL, Pearson r = 0.99, P < 10^-10). These results have broad significance for the treatment of cancers, for the interpretation of clinical trials, and point to new opportunities to use combination therapies with greater precision.

Citation Format: Adam C. Palmer, Ben Izar, Haeun Hwangbo, Peter K. Sorger. Control of inter- and intra-patient cancer heterogeneity is a predictively accurate explanation for the success of many combination therapies for solid and hematological 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-072.
Abstract PO-075: Dysfunction of centrosome regulation by BRCA1-containing complex increases tumor heterogeneity
Authors: Chiba Natsuko
Published: December 2020

Centrosomes are the major microtubule-organizing centers in animal cells and are critical for the formation of a bipolar mitotic spindle. Alterations in centrosome number and structure often occur together and are associated with many cancers. Centrosome aberrations results in chromosome segregation errors and abnormal cell division, leading to chromosomal instability (CIN). CIN is a major source of aneuploidy, resulting in tumor heterogeneity. Centrosome aberrations are observed in the early stages of tumorigenesis and are correlated with CIN. Breast cancer gene 1 (BRCA1) is a tumor suppressor that is associated with hereditary breast and ovarian cancer. Functions of BRCA1 in DNA repair, especially homologous recombination, has been focused, whereas BRCA1 regulates centrosome together with BRCA1-associated RING domain protein (BARD1). We identified BRCA1-interacting proteins, Obg-like ATPase 1 (OLA1) and receptor for activated C kinase (RACK1). OLA1 and RACK1 directly bound to BRCA1, BARD1, and γ-tubulin and localized the centrosomes throughout the cell cycle. Overexpression of OLA1 or RACK1 caused centrosome amplification due to centriole overduplication in mammary tissue-derived cells. The number of centrioles in cells was higher in cell lines derived from mammary tissue compared to those derived from other tissues. Knockdown of RACK1 caused abnormal centrosomal localization of BRCA1 and abrogated centriole duplication. Overexpression of RACK1 increased the centrosomal localization of BRCA1. Cancer-derived variants of BRCA1, BARD1, OLA1, and RACK1 abolished or weakened their interaction and function in centrosome duplication. These data suggest that the formation of BRCA1/BARD1/OLA1/RACK1 complex is important for centrosome regulation to maintain genome stability and that dysfunction of this complex will increase tumor heterogeneity that associated with carcinogenesis and cancer progression.

Citation Format: Natsuko Chiba. Dysfunction of centrosome regulation by BRCA1-containing complex increases tumor heterogeneity [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-075.
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

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

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

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

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

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 >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

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

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

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.