Thompson, Aubrey

Abstract Hepatocellular Carcinoma (HCC) and Cholangiocarcinoma (CCA) are the predominant forms of liver cancer, with a devastating combined incidence of 40,000 cases per year in the United States. Despite many differences between the cancers, liver transplant has found great success in treating both over traditional methods. However, up to 35% of patients’ cancer still recur within five years. Given the risk and resource intensiveness of this treatment, it is critical to identify factors that influence recurrence in these cancers. Previous studies have found the micro-environments of HCC tumors tend to be immune-active while those of CCA tumors tend to be immunosuppressive. Increased immune activity at the tumor level is associated with better patient outcomes, but the role and impact of the regional immune response in liver cancer is not well understood. Liver draining lymph node tissue was collected from patients undergoing orthotopic liver transplant (OLT) for HCC, CCA, or other reasons (control). Nanostring GeoMx Digital Spatial Profiler (DSP) was used to measure immune marker levelsWe found increased immune activity in the LNs of patients with HCC compared to CCA, showing significantly higher levels of lymphocytes and immune activity markers, matching previous tumor microenvironment findings. Additionally, comparing recurrent and non-recurrent HCC or CCA samples, we see generally increased immune activity in non-recurrent lymph nodes, also identifying specific immune markers in both cancer types that correlate with cancer recurrence or non-recurrence. These also reveal patterns of activity specific to both cancer type and recurrence status. Overall, this study provides novel insights into the regional immune response in liver cancers and identifies candidate proteins to serve as predictors of recurrence in liver cancer. We suggest CD163, CD66b, CD8, and CD56 as markers to predict post-OLT HCC recurrence and CD163, CD66b, ID01, and OX40L as candidate markers to predict post-OLT CCA recurrence using LN samples. Further spatial analysis of this data may further characterize immune activity in these lymph nodes, and future studies focusing on identified differences in immune activity may reveal factors affecting liver cancer aggressiveness and recurrence. Citation Format: Peyton Hickman, Aubrey E. Thompson, Justin Nguyen. The role of draining lymph nodes in the post-transplant recurrence of liver cancer: Examining immune response using spatial proteomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 624.

Abstract Background: The intrinsic immune response in triple negative breast cancer (TNBC) has both prognostic and predictive utility, and immune-related biomarkers are now actionable targets in TNBC. Current modalities for immune profiling are limited by lack of spatial context and precise quantitation. We used quantitative digital spatial profiling (DSP) to 1) characterize the immune architecture of tumoral and stromal regions in TNBC and 2) identify prognostic immune signatures. Methods: From the FinXX trial of adjuvant capecitabine therapy, tumor sections (FFPE) matched for patient characteristics, treatment arm and RFS-based outcome (N=44) were assessed with Nanostring GeoMxTM DSP. Briefly, with 3-plex immunofluorescence (pan-cytokeratin, CD45, CD68 with SYTO-13 dye for nuclei), spatially-defined CD45-enriched or CD68-enriched stromal segments and adjacent tumor segments (N=950) were selected for digital quantitation (NanoString nCounter) of 39 immune proteins (e.g. immune cell profiling proteins: CD3, CD4, CD8, CD11c, CD20, CD56, CD68, HLA-DR, PD-1, PD-L1, Granzyme B), immune drug targets (e.g. VISTA, STING, IDO1), and activation status-related proteins (e.g. ICOS, PD-L2, CD40, CD40L, CD44). Normalized, differentially-expressed (DE) proteins were evaluated, and weighted gene co-expression network analysis (WGCNA) was performed to identify modules of highly co-expressing immune proteins, and association with RFS as a categorical variable was determined. Results: 20 DE proteins in tumor segments were associated with RFS. Among them, those with the highest RFS-associated fold changes (FC) included CD20, CD40, CD56, HLA-DR, Granzyme B, and PD-L2 (FC): 2.1-4.4) (p < 0.05). In contrast, only 4 DE proteins were associated with RFS in stromal segments (Granzyme B, IDO-1, PD-L1, and PD-L2 (FC: 1.5-3.3) (p < 0.05). By WGCNA, 2 tumor-based immune modules [IM1 (lymphocyte infiltration) and IM2 (lymphocyte activation)] were identified based on their co-expression. The top three co-expressed proteins in IM1 were CD4, CD40, and CD45 (r >0.9). The three top co-expressed proteins in IM2 were PD-L1, PD-L2, and Granzyme B (r > 0.85). Together with CD56 expression, IM1 and IM2 comprised a set of 3 intratumoral immune features that associated with RFS. For recurring tumors, all 3 immune features clustered with low scores . Among non-recurrent tumors, two distinct, non-overlapping clusters with inverse characteristics were identified: high IM2, low IM1, low CD56 vs. low IM2, high IM1, and high CD56. Overall, across all 3 immune features, PDL2, CD40 and CD56 expression most strongly associated with RFS. Conclusion: With spatially-defined, precise quantification of immune proteins, we identified 3 immune features, including two distinct immune modules, IM1 and IM2 that correlate with durable RFS. These immune modules of highly co-expressing proteins were associated with RFS only when present in the tumor compartment but not tumor-adjacent, immune cell-rich stroma. Citation Format: Jodi M. Carter, Saranya Chumsri, Yaohua Ma, Xue Wang, Jennifer M. Kachergus, Douglas Hinerfeld, Heather Ann Brauer, Sarah Warren, Heikki Joensuu, Edith A. Perez, Aubrey Thompson. Quantitative digital spatial profiling reveals novel prognostic intratumoral immune signatures in triple-negative breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1004.

Abstract Dysregulation of estrogen receptor gene (ESR1) is an established mechanism of inducing endocrine therapy resistance. We previously discovered a chromosomal translocation event generating an estrogen receptor gene fused in-frame to C-terminal sequences of YAP1 (ESR1-YAP1) that contributed to endocrine therapy resistance in estrogen receptor positive (ER+) breast cancer models. This current study compares functional and pharmacological properties of additional ESR1 gene fusion events of both early stage (ESR1-NOP2) and advanced endocrine therapy resistant (ESR1-YAP1 and ESR1-PCDH11x) breast cancers. The YAP1 and PCDH11x fusions conferred estrogen-independent and fulvestrant-resistant growth in T47D, an ER+ breast cancer cell line in vitro and in vivo, in contrast to the NOP2 fusion which was sensitive to hormone deprivation. Immunohistochemical (IHC) staining of mouse lungs revealed significantly higher numbers of micrometastatic ER+ cells from the T47D tumors expressing the YAP1 and PCDH11x fusions than YFP control and NOP2 fusion. Estrogen response element (ERE) reporter and pull down assays revealed that although all ESR1 fusions studied bound EREs, only the YAP1 and PCDH11x caused ERE activation. Cell lines containing these “canonical” ESR1 fusions upregulated expression of ER responsive genes such as TFF1 and GREB1 in hormone deprived conditions. In contrast, the NOP2 fusion neither induced ERE activity nor upregulated TFF1 and GREB1 gene expression. The proliferative ability of canonical fusion-containing T47D cells was inhibited by palbociclib, a CDK4/6 inhibitor, in a dose-dependent manner. In vivo growth of patient-derived xenograft tumors naturally harboring the ESR1-YAP1 fusion (WHIM18) was significantly reduced in mice fed palbociclib-containing chow. Mice transplanted with WHIM18 also formed lung micrometastases, with an ER IHC staining pattern similar to lungs from YAP1 and PCDH11x fusion expressing T47D xenografts. In conclusion, in-frame ERE activating canonical fusions occur in end-stage, drug resistant, advanced breast cancer and can be added to ESR1 point mutations as a class of somatic mutation that may cause acquired resistance. Endocrine therapy resistant growth induced by these fusions can be treated with CDK4/6 inhibition, using an FDA approved drug, palbociclib, which could potentially improve outcomes in patients with ESR1 translocated tumors. Citation Format: Jonathan T. Lei, Jieya Shao, Jin Zhang, Michael Iglesia, Doug W. Chan, Ryoichi Matsunuma, Xiaping He, Purba Singh, Yoshimasa Kosaka, Robert Crowder, Svasti Haricharan, Shyam Kavuri, Jeremy Hoog, Chanpheng Phommaly, Rodrigo Goncalves, Susana Romalho, Wei-Chu Lai, Oliver Hampton, Anna Rogers, Ethan Tobias, Poojan Parikh, Sherri Davies, Cynthia Ma, Vera Suman, Kelly Hunt, Mark Watson, Katherine A. Hoadley, Aubrey Thompson, Charles Perou, Chad J. Creighton, Chris Maher, Matthew J. Ellis. Estrogen receptor gene fusions drive endocrine therapy resistance in estrogen receptor positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1033. doi:10.1158/1538-7445.AM2017-1033

Abstract Introduction: Invasive lobular carcinoma (ILC) comprises approximately ∼10-20% of breast cancers (BC) and appears to have a distinct biology from invasive ductal carcinoma (IDC). ILC is known to have a higher incidence of multifocal (MF) disease when compared to IDC (Biglia N, EJSO, 2013) and in general, MF BC has been associated with an increased rate of regional lymph node metastases (Cabioglu N, JACS, 2009). Treatment decisions are most often defined by the largest of the MF tumors without targeting potentially relevant biologic heterogeneity of the disease. We conducted a genomic analysis of MF ILC to help address this knowledge void. Methods: We characterized gene expression in multiple foci from 11 patients (pts) with MF ILC (all ER+ and HER2-, mean number of foci = 2.62) and 13 benign breast tissues. RNA was extracted from 3×1.5mm cores from each foci and gene expression was measured in 730 known cancer genes using the NanoString PanCancer pathways panel. Differential gene expression analyses were performed between 1) MF tumors and benign tissue (BT) accounting for pairing of pts and 2) different foci of MF tumors from the same ILC pt by ANOVA. The association of clinical covariates (age, number of tumors, grade and stage) in the top genes that were differentially expressed between multiple foci was assessed by linear mixed models accounting for pt and tumor. Results: A total of 20 genes (including MET and EGFR, top 5 genes: SPRY2, SOX17, FIGF, PDGFA, IL6) were differentially expressed (p<0.05) between malignant foci from the same pt, after correction by false discovery rate (FDR). EGFR expression was also negatively associated with the number of positive lymph nodes (N1a vs N0 absolute fold change = 0.51, p = 0.043). We observed an excess of genes that were down-regulated in MF ILC compared to BT. 277 genes were differentially expressed at p<0.05 after correction by FDR. The top 5 differentially expressed genes (by fold change) between ILC and BT were COL11A1, COL1A1, WIF1, FIGF and PROM1. CDH1, a known marker of ILC, was down-regulated in ILC compared to benign (absolute fold change = 2.54, p = 6.02×10−6), ranked only 39/277 genes by fold change. MET and EGFR ranked 29 and 42/277 genes (p = 5.99×10−9 and 3.32×10−8 respectively). Conclusion: We observed significant heterogeneity for 20/730 genes between individual foci of MF ILC within the same pt suggesting that MF synchronous ILC lesions may have different biologic behavior. This in turn may have important prognostic implications with potential therapeutic utility. Our analyses also shows significant down-regulation of gene expression between ILC tumors and BT for many genes other than CDH1 suggesting that additional biomarkers can be used to further characterize ILC Study funded in part by Mayo Clinic Cancer Focus Research Team, the 26.2 with Donna Foundation and the Serene M. and Frances C. Durling endowment. Citation Format: Pooja Advani, Nadine Norton, Daniel J. Serie, Xochiquetzal Geiger, Julia E. Crook, Aubrey E. Thompson, Edith A. Perez, Alvaro Moreno Aspitia. Characterization of individual foci of multifocal invasive lobular breast cancer using gene expression profiling. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4761. doi:10.1158/1538-7445.AM2015-4761

Abstract MOTIVATION: Transcriptome sequencing (RNA-seq) is the most economical and information-rich next generation sequencing technology to study genomic medicine. Genomic features such as gene expression, transcript expression, fusion transcripts, long non-coding RNAs and expressed single nucleotide variants (eSNVs) can be obtained from RNA-seq data. There are several computational workflows to obtain gene counts, transcript counts and fusion gene candidates, but not a comprehensive system to identify expressed SNVs from RNA-sequencing data. METHODS: We have developed a novel computational system (The eSNV-Detect) with parallel alignment strategies to identify expressed SNVs accurately from tumor transcriptome sequencing data. Sequence-based features like reads supporting reference allele, alternate allele, ratio of alternate reads to total read depth, base qualities, mapping qualities, forward strand and reverse strand supporting reads etc. along with a variety of databases such as dbSNP, 1000 genome, 5400 exome, refGene, avsift, ljb_phylop from UCSC were used to call SNVs from RNA-sequencing data. For the expressed SNVs detected in tumors, we can also identify the amino acid change and classify the protein domains using our method. RESULTS: We have applied the eSNV-Detect method to call novel expressed SNVs in two tumors (one HER2 positive and one ER positive breast tumor). BWA and Bowtie were used to align the two breast tumors. Several filtering criteria's were applied to the tumors to remove any known (germ line) or low confidence SNVs. We randomly selected 83 and 31 eSNVs for the HER2 and ER positive tumors respectively and performed Sanger sequencing validation in tumor and matched normal tissues of the tumor. We were able to validate 81 out of 83 eSNVs in the HER2 tumor sample, and 29 out of 31 eSNVs in the ER positive tumor sample. Of the eSNVs that we validated 39/81 and 10/31 were localized to functional protein domains in HER2 and ER positive tumors respectively. We are also in the process of validating eSNVs detected from RNA-seq with the tumor and blood exome sequencing data we have for the same patients. Citation Format: Xiaojia Tang, Saurabh Baheti, Khader Shameer, Kevin J. Thompson, Jean-Pierre Kocher, Edith A. Perez, Aubrey E. Thompson, Krishna R. Kalari. The eSNV-Detect: a computational system to identify expressed single nucleotide variants from tumor transcriptomes. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3185. doi:10.1158/1538-7445.AM2013-3185

Abstract Motivation: Overexpression of HER2 (the product of the ERBB2 gene) occurs in about 15% of all breast tumors. We have undertaken to use next generation transcriptome sequencing technology to identify genomic features that are unique to HER2+ tumors. Interactome mapping was then used to integrate the genes associated with these features into a transcriptome landscape model, with a view towards identifying nodes of interaction that might be targeted in HER2+ tumors. Methods: We performed 50nt paired-end RNA-sequencing for 24 breast tumors: 8 each HER2+, ER+, triple negatives (TN). In addition to breast adenocarcinomas, we also sequenced 8 early passage non-transformed HMEC cell lines as normal controls. Reads from RNA sequencing were aligned to the genome and exon junctions using TopHat software. Gene counts were summarized and annotations were performed using our in-house programs. Tukey's test was used to obtain genes or transcripts that are specific to HER2 tumor group compared to other tumors/normal. A combination of bioinformatics softwares and algorithms were used to identify SNVs. Results: Only 13527 genes with median gene count greater than 16 reads in at least one of the 4 groups were considered for differential gene expression and splicing analysis. Some 696 genes were differentially expressed in HER2+ tumors compared to ER+, TN tumors and HMECs. We identified 272 alternately spliced transcripts for which the HER2+ tumors exhibited a mean transcript expression ratio significantly different from the means of other tumor groups. We also identified 4735 expressed single nucleotide variants that are uniquely associated with HER2+ tumors compared to other tumors/normal groups. Among these 3579/4735 sequence polymorphisms were not present in the 1000 genome germline sequence database or in the dbSNP132 database of naturally occurring germline polymorphisms. Integration of all the genes obtained from genomic feature analyses (differential expression, alternative splicing, single nucleotide variance) has been carried out to indentify biological processes that are specific to the HER2+ tumor subtype. Key nodes and pathways that are specific to HER2+ tumors will be evaluated for association with clinical outcome in a large series of patients who have received HER2-targeted therapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4926. doi:1538-7445.AM2012-4926

Abstract Motivation: KRAS is commonly mutated in a variety of cancers including lung cancer. The KRAS gene is frequently mutated at codons 12 and 13 in lung adenocarcinomas in patients with a history of smoking. Tumors harboring an activating KRAS mutation are aggressive and are often resistant to available therapies. In the present study, we set out to identify pathways that are specifically altered in lung cancer patients whose tumors harbor a KRAS mutation using next generation sequencing technology. Methods: We performed 50nt paired-end RNA-sequencing in 15 lung adenocarcinoma samples (8 and 7 samples with and without KRAS mutation). Reads were aligned to genome and exon junctions using Illumina's alignment tool ELAND_RNA. CASAVA and Genome Studio data analysis software were used to obtain read counts for genes, exons and exon junctions. We applied a variety of computational methods (Casper R package, Bowtie, TopHat) and softwares (Partek, R statistical software, JMP, Ingenuity Pathway Anlaysis, DAVID) to carry out our analyses. Results: Differential gene expression and splicing analysis were performed between the two groups. We identified 115 genes that were differentially expressed and 112 genes that consist of splicing variants with at least 2 fold changes and p-value < 0.01. We randomly selected 6/15 samples and performed real-time qRT-PCR for 6 differentially expressed genes. Significant correlations were observed ranging from 0.44 to 0.83, when qRT-PCR results were compared with RNA-sequencing expression data. Pathway analysis with 115 differentially expressed genes and 112 splicing variants revealed that the most significant pathway is composed entirely of NFκB focus genes, suggesting that there is a direct connection between oncogenic KRAS and activation of the NFκB signaling pathway. Conclusions: NFκB has been implicated in KRas-mediated formation of early stage lung adenomas in the LSL-Kas mouse model. Our data indicate that this connection also occurs in human lung cancer and establish NFκB activation as a key manifestation of KRAS mutation in human lung cancer. Hence drugs targeting NFκB and NFκB related genes may potentially be helpful for the treatment of patients with oncogenic KRAS mutations. (Supported in part by grants from the 26.2 with Donna Foundation and the Florida Department of Health Bankhead/Coley program.) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4975. doi:10.1158/1538-7445.AM2011-4975