Abstract PD2-09: Characterization of the lymphovascular invasion microenvironment reveals immune response dichotomy

Background: Metastasis is the leading cause of cancer related deaths in breast cancer patients. Lymphovascular invasion represents one of the earliest stages of metastasis wherein the cells are introduced to a very different and distinct microenvironment. Methods: We leveraged spatial techniques developed for limited specimens in archival tissue to study patient matched cross-sectional tumor samples from different stages of breast neoplasia including normal breast, ductal carcinoma in situ (DCIS), primary invasive carcinoma (IBC), lymphovascular invasion (LVI) and regional lymph node metastasis. We selected a set of 21 patients with ER+ breast cancer to generate cross-sectional samples of each of these stages, for a total of 331 samples. The areas of LVI were identified by a combination of H&E review and immunohistochemistry for podoplanin. We performed smart-3SEQ for gene expression profiling and light pass whole genome sequencing for DNA copy number alterations. Results: We profiled the spectrum of neoplasia for transcriptome-wide gene expression. Principal component analysis of all 252 DCIS, LVI, IBC, or metastasis samples using the top 500 genes with the highest variance demonstrated that clustering was roughly based on the diagnostic stage (i.e. DCIS, LVI, IBC, or metastasis). Differential gene expression profiling identified thousands of genes increased or decreased in expression across the transitional stages with the largest change in gene expression being the transition from normal breast to DCIS, dominated by gene expression down regulation. We next performed NMF clustering on 62 samples of LVI from 18 cases and identified two patterns of gene expression which define two subgroups. Gene ontology analysis revealed that one cluster was associated with increased proliferation and metabolism, whereas the second cluster was dominated by an immune response. When we analyzed the immune and proliferative LVI subgroups separately, we found that the immune profiles in the patient matched IBC and LVI samples from the LVI Immune cluster were similar, whereas the immune profiles in the patient matched IBC and LVI samples from the Proliferative cluster were significantly different. At the LVI stage, all immune cell populations estimated by CibersortX were decreased in the Proliferative LVI cluster. These changes were validated using immunofluorescence for proliferation (Ki67), T cells (CD3) and macrophages (CD68) on the same samples. Using the LVI centroids, we built a model that could predict the same clusters in the METABRIC IBC. Kaplan-Meier analysis showed a significant difference between groups, with the Proliferative-like IBC group having a worse prognosis than the Immune-like IBC group. Conclusions: We observed a dichotomy at the LVI stage with a more proliferative cluster that may escape the immune response and an immune cluster which has a microenvironment with a similar pattern to its primary IBC. The recognition of two groups of LVI, differing in immune association and proliferation, raises the possibility that the risk of metastasis could be different in these two groups, leading to different biological pathways of progression.

Citation Format: Belén Rivero-Gutiérrez, Diego Mallo, Almudena Espín-Pérez, Sujay Vennam, Chunfang Zhu, Sushama Varma, Greg Scott, Joseph Foley, E Shelley Hwang, Carlo Maley, Robert West. Characterization of the lymphovascular invasion microenvironment reveals immune response dichotomy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD2-09.

Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts

Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We perform multiscale, integrated molecular profiling of DCIS with clinical outcomes by analyzing 774 DCIS samples from 542 patients with 7.3 years median follow-up from the Translational Breast Cancer Research Consortium 038 study and the Resource of Archival Breast Tissue cohorts. We identify 812 genes associated with ipsilateral recurrence within 5 years from treatment and develop a classifier that predicts DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions are identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome.

New Ameloblastoma Cell Lines Enable Preclinical Study of Targeted Therapies

Ameloblastoma (AB) is an odontogenic tumor that arises from ameloblast-lineage cells. Although relatively uncommon and rarely metastatic, AB tumors are locally invasive and destructive to the jawbone and surrounding structures. Standard-of-care surgical resection often leads to disfigurement, and many tumors will locally recur, necessitating increasingly challenging surgeries. Recent genomic studies of AB have uncovered oncogenic driver mutations, including in the mitogen-activated protein kinase (MAPK) and Hedgehog signaling pathways. Medical therapies targeting those drivers would be a highly desirable alternative or addition to surgery; however, a paucity of existing AB cell lines has stymied clinical translation. To bridge this gap, here we report the establishment of 6 new AB cell lines-generated by "conditional reprogramming"-and their genomic characterization that reveals driver mutations in FGFR2, KRAS, NRAS, BRAF, PIK3CA, and SMO. Furthermore, in proof-of-principle studies, we use the new cell lines to investigate AB oncogene dependency and drug sensitivity. Among our findings, AB cells with KRAS or NRAS mutation (MAPK pathway) are exquisitely sensitive to MEK inhibition, which propels ameloblast differentiation. AB cells with activating SMO-L412F mutation (Hedgehog pathway) are insensitive to vismodegib; however, a distinct small-molecule SMO inhibitor, BMS-833923, significantly reduces both downstream Hedgehog signaling and tumor cell viability. The novel cell line resource enables preclinical studies and promises to speed the translation of new molecularly targeted therapies for the management of ameloblastoma and related odontogenic neoplasms.

The microdissected gene expression landscape of nasopharyngeal cancer reveals vulnerabilities in FGF and noncanonical NF-κB signaling

Nasopharyngeal cancer (NPC) is an Epstein-Barr virus (EBV)-positive epithelial malignancy with an extensive inflammatory infiltrate. Traditional RNA-sequencing techniques uncovered only microenvironment signatures, while the gene expression of the tumor epithelial compartment has remained a mystery. Here, we use Smart-3SEQ to prepare transcriptome-wide gene expression profiles from microdissected NPC tumors, dysplasia, and normal controls. We describe changes in biological pathways across the normal to tumor spectrum and show that fibroblast growth factor (FGF) ligands are overexpressed in NPC tumors, while negative regulators of FGF signaling, including SPRY1, SPRY2, and LGALS3, are down-regulated early in carcinogenesis. Within the NF-κB signaling pathway, the critical noncanonical transcription factors, RELB and NFKB2, are enriched in the majority of NPC tumors. We confirm the responsiveness of EBV-positive NPC cell lines to targeted inhibition of these pathways, reflecting the heterogeneity in NPC patient tumors. Our data comprehensively describe the gene expression landscape of NPC and unravel the mysteries of receptor tyrosine kinase and NF-κB pathways in NPC.

Abstract GS4-07: The Breast PreCancer Atlas DCIS genomic signatures define biology and correlate with clinical outcomes: An analysis of TBCRC 038 and RAHBT cohorts

Background. DCIS consists of a molecularly heterogeneous group of premalignant lesions, with variable risk of invasive progression. Understanding biomarkers for invasive progression could help individualize treatment recommendations based upon tumor biology. As part of the NCI Human Tumor Atlas Network (HTAN), we conducted comprehensive genomic analyses on two large DCIS case-control cohorts. Methods. We performed smart3-seq and low-pass whole genome sequencing on two independent, retrospective, longitudinally sampled DCIS case-control cohorts. TBCRC 038 was a multicenter cohort diagnosed with DCIS between 1998 and 2016 at one of the Translational Breast Cancer Research sites; the RAHBT (Resource of Archival Human Breast Tissue) cohort included women identified through the St. Louis Breast Tissue Repository, and the Women’s Health Repository diagnosed between 1997 and 2001. We studied the spectrum of molecular changes present and sought genomic predictors of subsequent ipsilateral breast events (iBEs: DCIS recurrence or invasive progression) in both DCIS epithelium and stroma in formalin fixed paraffin embedded tissue. We generated de novo tumor and stroma-centric subtypes for DCIS that represents fundamental transcriptomic organization. Copy number analysis was performed using low-pass DNA sequencing. Non-negative matrix factorization (NMF) was applied to the RNA expression of all coding genes to identify clusters. A negative-binomial regression model was used to identify differentially expressed genes. Results. We analyzed 677 DCIS samples from 481 patients with 7.1 years median follow-up. In TBCRC samples, we identified three clusters via NMF in TBCRC referred to as ER low, quiescent, and ER high. The ER-low cluster had significantly higher levels of ERBB2 and lower levels of ESR1 compared to quiescent and ER-high clusters. Quiescent cluster lesions were less proliferative and less metabolically active than ER high and ER low subtypes. These findings were replicated in the RAHBT cohort. Focusing on the stromal component of DCIS from laser capture microdissection in RAHBT samples, we identified four distinct DCIS-associated stromal clusters. A “normal-like” stromal cluster with ECM organization and PI3K-AKT signaling; a “collagen-rich” stromal cluster; a “desmoplastic” stromal cluster with high fibroblast and total myeloid abundance, mostly associated with macrophages and myeloid dendritic cells (mDC); and an “immune-dense” stromal cluster. Further, we compared differentially expressed genes in patients with or without subsequent iBEs within 5 years of diagnosis. Hypothesizing that the resulting 812 DE genes (DESeq2) represent multiple routes to subsequent iBEs, we leveraged NMF to identify paths to progression. In both TBCRC and RAHBT cohorts, poor outcome groups exhibited increased ER, MYC signaling, and oxidative phosphorylation, supporting that these pathways are important for DCIS recurrence and progression. Conclusion. Comprehensive genomic profiling in two independent DCIS cohorts with longitudinal outcomes shows distinct DCIS stromal expression patterns and immune cell composition. RNA expression profiles reveal underlying tumor biology that is associated with later iBEs in both cohorts. These studies provide new insight into DCIS biology and will guide the design of diagnostic strategies to prevent invasive progression.

Citation Format: Siri H Strand, Belén Rivero-Gutiérrez, Kathleen E Houlahan, Jose A Seoane, Lorraine M King, Tyler Risom, Lunden Simpson, Sujay Vennam, Aziz Khan, Timothy Hardman, Bryan E Harmon, Fergus J Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla F McAuliffe, Julie Nangia, Joanna Lee, Jennifer Tseng, Anna Maria Storniolo, Alastair Thompson, Gaorav Gupta, Robyn Burns, Deborah J Veis, Katherine DeSchryver, Chunfang Zhu, Magdalena Matusiak, Jason Wang, Shirley X Zhu, Jen Tappenden, Daisy Yi Ding, Dadong Zhang, Jingqin Luo, Shu Jiang, Sushama Varma, Cody Straub, Sucheta Srivastava, Christina Curtis, Rob Tibshirani, Robert Michael Angelo, Allison Hall, Kouros Owzar, Kornelia Polyak, Carlo Maley, Jeffrey R Marks, Graham A Colditz, E Shelley Hwang, Robert B West. The Breast PreCancer Atlas DCIS genomic signatures define biology and correlate with clinical outcomes: An analysis of TBCRC 038 and RAHBT cohorts [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr GS4-07.

Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma

Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand the changes in the tumor microenvironment (TME) accompanying transition to IBC, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to interrogate 79 clinically annotated surgical resections using machine learning tools for cell segmentation, pixel-based clustering, and object morphometrics. Comparison of normal breast with patient-matched DCIS and IBC revealed coordinated transitions between four TME states that were delineated based on the location and function of myoepithelium, fibroblasts, and immune cells. Surprisingly, myoepithelial disruption was more advanced in DCIS patients that did not develop IBC, suggesting this process could be protective against recurrence. Taken together, this HTAN Breast PreCancer Atlas study offers insight into drivers of IBC relapse and emphasizes the importance of the TME in regulating these processes.

Transcriptome and genome evolution during HER2-amplified breast neoplasia

Background

The acquisition of oncogenic drivers is a critical feature of cancer progression. For some carcinomas, it is clear that certain genetic drivers occur early in neoplasia and others late. Why these drivers are selected and how these changes alter the neoplasia’s fitness is less understood.

Methods

Here we use spatially oriented genomic approaches to identify transcriptomic and genetic changes at the single-duct level within precursor neoplasia associated with invasive breast cancer. We study HER2 amplification in ductal carcinoma in situ (DCIS) as an event that can be both quantified and spatially located via fluorescence in situ hybridization (FISH) and immunohistochemistry on fixed paraffin-embedded tissue.

Results

By combining the HER2-FISH with the laser capture microdissection (LCM) Smart-3SEQ method, we found that HER2 amplification in DCIS alters the transcriptomic profiles and increases diversity of copy number variations (CNVs). Particularly, interferon signaling pathway is activated by HER2 amplification in DCIS, which may provide a prolonged interferon signaling activation in HER2-positive breast cancer. Multiple subclones of HER2-amplified DCIS with distinct CNV profiles are observed, suggesting that multiple events occurred for the acquisition of HER2 amplification. Notably, DCIS acquires key transcriptomic changes and CNV events prior to HER2 amplification, suggesting that pre-amplified DCIS may create a cellular state primed to gain HER2 amplification for growth advantage.

Conclusion

By using genomic methods that are spatially oriented, this study identifies several features that appear to generate insights into neoplastic progression in precancer lesions at a single-duct level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01451-6.

Abstract PD5-08: The human tumor atlas network (HTAN) breast pre cancer atlas: A multi-omic integrative analysis of ductal carcinoma in situ (DCIS) and correlation with clinical outcomes

Introduction. As nonobligate precursors of invasive disease, pre-cancers provide a unique vantage point from which to study the molecular pathways and evolutionary dynamics that lead to the development of life-threatening cancers. Ductal carcinoma in situ (DCIS) is the most commonly diagnosed precursor of breast cancer, with variable propensity for invasive progression. In order to address the problems of over- and under-treatment, we performed a multimodal, integrated profile of DCIS with clinical outcomes with which to develop and validate predictors of invasive progression. Methods. We present observations on DNA, RNA, and protein expression on two independent patient cohorts of DCIS, diagnosed from 1981 to 2014, from the Translational Breast Cancer Research Consortium (TBCRC 038) and the Washington University Repository of Archival Human Breast Tissue (RAHBT). Patients initially diagnosed with DCIS, with either DCIS or invasive recurrence (cases; mean follow up 5.8 years) were matched to those without recurrence (controls; mean follow up 10.3 years), based upon age at diagnosis and year of diagnosis. Results. We present genomic and cellular changes that correlate with both disease states and patient outcomes in DCIS. DCIS can be clustered by classification systems developed for IBC. Specific immune cell types and pathways correlate with longitudinal outcome. Luminal cell adhesion and metabolism pathways are upregulated in controls and cases, respectively. Highly multiplexed ion beam imaging (MIBI) was used to validate RNA seq findings, and to provide single cell-level spatial context for molecular alterations.Conclusion. We have performed an integrated multi-omic analysis of DCIS and associated tumor micorenvironment. Our multi-scale approach employs in situ methods to generate a spatially resolved atlas of breast precancers where different modalities can be directly compared to each other, and correlated with conventional pathology findings and clinical outcome. The PreCancer Atlas represents a complex multi-modal database for DCIS study, whose design allows for future discovery and hypothesis generation.

Table 1. Breast Pre-cancer Atlas Multi-scale Characterization AssaysAssayScaleType of DataIntegration and validation with other assaysRNA-seq (Single duct, single cell, TME)Cell, duct, organ, normal tissue1. Whole transcriptome gene expression profiling per single duct (also enabling CNV and cell type prediction)2. Whole transcriptome gene expression profiling per single duct1. Prediction of CNV confirmed by DNA-seq (single duct) and FISH (single cell)2. Prediction of cell type composition (Cibersort) confirmed by multiplex IHC and multicolor flow cytometryLow-pass whole genome DNA-seqDuct and adjacent normalCNV profiling per single ductAnalysis of CNV supported by RNA-seq (single duct) and MIBI (single cell)Whole genome sequencingDuct and adjacent normalMutation status per single ductMutational analysis confirmed by RNA-seqMultiplex IHC (MIBI & Cyclic multicolor)Cell1. Cell type2. Proteomic analysisAnalysis of cell type supported by RNA-seq of ducts (Cibersort) and single cellsH&E MorphometricsCell, duct, organSpatial location of cell types, organization of ductsAnalysis of H&E images correlated with FISH data

Citation Format: Shelley Hwang, Siri H Strand, Belen Rivero, Lorraine King, Tyler Risom, Bryan Harmon, Fergus Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla McAuliffe, Julie Nangia, Ana Maria Storniolo, Alastair Thompson, Gaorav Gupta, Joanna Lee, Jennifer Tseng, Robyn Burns, ChunFang Zhu, Magda Matusiak, Shirley X Zhu, Jason Wang, Jose Seoane, Jen Tappenden, Daisy Ding, Dadong Zhang, Jingqin Luo, Sujay Vennam, Sushama Varma, Lunden Simpson, Luis Cisneros, Timmothy Hardman, Lauren Anderson, Cody Straub, Sucheta Srivastava, Deb J Veis, Christina Curtis, Rob Tibshirani, Robert Michael Angelo, Allison Hall, Kouros Owzar, Kornelia Polyak, Carlo Maley, Jeff Marks, Graham Colditz, Robert B West. The human tumor atlas network (HTAN) breast pre cancer atlas: A multi-omic integrative analysis of ductal carcinoma in situ (DCIS) and correlation with clinical outcomes [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD5-08.

Abstract PR05: Mapping the tumor and microenvironmental evolution underlying DCIS progression through multiplexed ion beam imaging

Ductal Carcinoma in Situ (DCIS) is a pre-invasive lesion that accounts for nearly 20% of new breast cancer diagnoses. Of these cases, about half will progress to invasive breast cancer (IBC) within ten years. However, because diagnostic criteria for delineating low risk lesions from those likely to progress to IBC have not been identified, many patients are receiving unnecessary chemotherapy and surgery that can result in therapy-related morbidity and death. With this in mind, we used Multiplexed Ion Beam Imaging by time of flight (MIBI-TOF) and RNA-seq laser-capture microdissection (SMART-3SEQ) to construct a comprehensive spatial atlas describing the structure, function, and cellular composition of DCIS. MIBI-TOF and SMART-3SEQ were used to compare lesions from patients that later developed IBC with those from age- and history matched DCIS controls without recurrence. Using a 37-marker staining panel to interrogate 137 lesions, we identified 30 distinct cell populations of the epithelial, stromal, and immune lineages that were arranged in recurrent cellular microenvironments specific for DCIS or invasive disease. We observe a coordinated shift in the immune and stromal compartments as invasive disease arises, including an expansion of immune cell diversity and transition to reactive stromal phenotypes in synchronous DCIS + IBC, which was distinct from the macrophage-dominant microenvironment of recurrent IBC. Single-cell segmentation using a deep learning model was combined with pixel-level coexpression analysis to determine how thickness, continuity, and phenotype of ductal myoepithelium changes as tumors progress from a pre-invasive state. These data were incorporated into a comprehensive model which was subsequently used to identify a subset of features that correlate with disease-free survival following DCIS tumor resection. Taken together, these features represent important prognostic metrics that can be used to separate pre-invasive from indolent DCIS tumors, and allow for tailored therapy that improves patient outcomes and quality of life in this disease.

Citation Format: Tyler Risom, Belen Rivero, Candace Liu, Alex Baranski, Siri Strand, Noah Greenwald, Erin McCaffrey, Sushama Varma, Leeat Keren, Sucheta Srivastava, Chunfang Zhu, Sujay Vennam, Shelley Hwang, Graham Colditz, Sean Bendall, Robert West, Michael Angelo. Mapping the tumor and microenvironmental evolution underlying DCIS progression through multiplexed ion beam imaging [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 PR05.

Genomic landscape of ductal carcinoma in situ and association with progression

PURPOSE

The detection rate of breast ductal carcinoma in situ (DCIS) has increased significantly, raising the concern that DCIS is overdiagnosed and overtreated. Therefore, there is an unmet clinical need to better predict the risk of progression among DCIS patients. Our hypothesis is that by combining molecular signatures with clinicopathologic features, we can elucidate the biology of breast cancer progression, and risk-stratify patients with DCIS.

METHODS

Targeted exon sequencing with a custom panel of 223 genes/regions was performed for 125 DCIS cases. Among them, 60 were from cases having concurrent or subsequent invasive breast cancer (IBC) (DCIS + IBC group), and 65 from cases with no IBC development over a median follow-up of 13 years (DCIS-only group). Copy number alterations in chromosome 1q32, 8q24, and 11q13 were analyzed using fluorescence in situ hybridization (FISH). Multivariable logistic regression models were fit to the outcome of DCIS progression to IBC as functions of demographic and clinical features.

RESULTS

We observed recurrent variants of known IBC-related mutations, and the most commonly mutated genes in DCIS were PIK3CA (34.4%) and TP53 (18.4%). There was an inverse association between PIK3CA kinase domain mutations and progression (Odds Ratio [OR] 10.2, p < 0.05). Copy number variations in 1q32 and 8q24 were associated with progression (OR 9.3 and 46, respectively; both p < 0.05).

CONCLUSIONS

PIK3CA kinase domain mutations and the absence of copy number gains in DCIS are protective against progression to IBC. These results may guide efforts to distinguish low-risk from high-risk DCIS.

Detection of Circulating Tumor DNA in Patients With Uterine Leiomyomas

PURPOSE

The preoperative distinction between uterine leiomyoma (LM) and leiomyosarcoma (LMS) is difficult, which may result in dissemination of an unexpected malignancy during surgery for a presumed benign lesion. An assay based on circulating tumor DNA (ctDNA) could help in the preoperative distinction between LM and LMS. This study addresses the feasibility of applying the two most frequently used approaches for detection of ctDNA: profiling of copy number alterations (CNAs) and point mutations in the plasma of patients with LM.

PATIENTS AND METHODS

By shallow whole-genome sequencing, we prospectively examined whether LM-derived ctDNA could be detected in plasma specimens of 12 patients. Plasma levels of lactate dehydrogenase, a marker suggested for the distinction between LM and LMS by prior studies, were also determined. We also profiled 36 LM tumor specimens by exome sequencing to develop a panel for targeted detection of point mutations in ctDNA of patients with LM.

RESULTS

We identified tumor-derived CNAs in the plasma DNA of 50% (six of 12) of patients with LM. The lactate dehydrogenase levels did not allow for an accurate distinction between patients with LM and patients with LMS. We identified only two recurrently mutated genes in LM tumors (MED12 and ACLY).

CONCLUSION

Our results show that LMs do shed DNA into the circulation, which provides an opportunity for the development of ctDNA-based testing to distinguish LM from LMS. Although we could not design an LM-specific panel for ctDNA profiling, we propose that the detection of CNAs or point mutations in selected tumor suppressor genes in ctDNA may favor a diagnosis of LMS, since these genes are not affected in LM.

Genomic analysis of benign prostatic hyperplasia implicates cellular re-landscaping in disease pathogenesis

Benign prostatic hyperplasia (BPH) is the most common cause of lower urinary tract symptoms in men. Current treatments target prostate physiology rather than BPH pathophysiology and are only partially effective. Here, we applied next-generation sequencing to gain new insight into BPH. By RNAseq, we uncovered transcriptional heterogeneity among BPH cases, where a 65-gene BPH stromal signature correlated with symptom severity. Stromal signaling molecules BMP5 and CXCL13 were enriched in BPH while estrogen regulated pathways were depleted. Notably, BMP5 addition to cultured prostatic myofibroblasts altered their expression profile towards a BPH profile that included the BPH stromal signature. RNAseq also suggested an altered cellular milieu in BPH, which we verified by immunohistochemistry and single-cell RNAseq. In particular, BPH tissues exhibited enrichment of myofibroblast subsets, whilst depletion of neuroendocrine cells and an estrogen receptor (ESR1)-positive fibroblast cell type residing near epithelium. By whole-exome sequencing, we uncovered somatic single-nucleotide variants (SNVs) in BPH, of uncertain pathogenic significance but indicative of clonal cell expansions. Thus, genomic characterization of BPH has identified a clinically-relevant stromal signature and new candidate disease pathways (including a likely role for BMP5 signaling), and reveals BPH to be not merely a hyperplasia, but rather a fundamental re-landscaping of cell types.

Abstract 3411: Biological subtypes of nasopharyngeal carcinoma by genomic profiling

Objective:

Nasopharyngeal carcinoma (NPC) is a common Epstein-barr virus-associated epithelial malignancy in several parts of the world including Southeast Asia. While the majority of patients are treated uniformly with a combination of chemo and radiation therapy, 20% of patients experience recurrence, most commonly in the form of distant metastasis. NPC subtypes based on underlying differences in biology are unexplored and are likely responsible for the heterogeneous clinical response. As NPC biopsies are small and have significant stromal infiltrate, obtaining pure epithelial cells for genomic profiling is a challenge. We aim to overcome these limitations to identify biological subtypes and dysregulated molecular pathways in NPC.

Methods:

We first evaluated 217 whole exomes sequences, including 102 microdissected tumors, from three previous studies for single nucleotide variants and copy number changes, following GATK standards and using next generation sequencing copy number callers. We then applied a novel method for gene expression profiling developed in our lab to a new cohort of EBV-positive primary NPC cases from our institution. We performed laser capture microdissection, separately dissecting tumor, normal and microenvironment for each case. We applied Smart-3SEQ, a novel 3' end RNA-Seq technique which allows for the accurate quantification of transcript abundance in dissected FFPE samples comprising only a few hundred cells.

Results:

We achieved a per-base concordance of 80.4% between copy number profiles by SNP array and whole exome sequencing. Unsupervised clustering identified three distinct copy-number groups of NPC tumors, with a low copy-number group demonstrating an 18.7% better 5-year disease-specific survival, not attributable to stage. Apart from broad cytogenetic changes, narrow regions of amplifications (e.g. 1q21, 11q13) and deletions (e.g. 9p21, 11q22) were important for defining copy-number subtypes.

Preliminary differential gene expression analysis showed that genes involved in cell cycle and cellular differentiation were significantly dysregulated in tumor cells (p &lt; 0.001 and p = 0.03 respectively), while genes involved in cilia assembly and flagella transport were upregulated in normal cells (p &lt; 0.001 for both). Our further analysis includes defining tumor subtypes based on gene expression, identifying key driver pathways, and correlating with EBV-latent gene expression, the immune environment, as well as clinical outcome.

Conclusion:

NPC tumors are biologically heterogeneous and can be classified based on their mutational and gene expression profiles. This provides an important basis for the consideration of escalation and de-escalation of therapy in selected patient groups.

Citation Format: Kai Xun Joshua Tay, Chunfang Zhu, Sujay Vennam, Sushama Varma, Quynh-Thu Le, John Sunwoo, Robert West. Biological subtypes of nasopharyngeal carcinoma by genomic profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3411.

Combination Approach for Detecting Different Types of Alterations in Circulating Tumor DNA in Leiomyosarcoma

Purpose: The clinical utility of circulating tumor DNA (ctDNA) monitoring has been shown in tumors that harbor highly recurrent mutations. Leiomyosarcoma represents a type of tumor with a wide spectrum of heterogeneous genomic abnormalities; thus, targeting hotspot mutations or a narrow genomic region for ctDNA detection may not be practical. Here, we demonstrate a combinatorial approach that integrates different sequencing protocols for the orthogonal detection of single-nucleotide variants (SNV), small indels, and copy-number alterations (CNA) in ctDNA.Experimental Design: We employed Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for the analysis of SNVs and indels, together with a genome-wide interrogation of CNAs by Genome Representation Profiling (GRP). We profiled 28 longitudinal plasma samples and 25 tumor specimens from 7 patients with leiomyosarcoma.Results: We detected ctDNA in 6 of 7 of these patients with >98% specificity for mutant allele fractions down to a level of 0.01%. We show that results from CAPP-Seq and GRP are highly concordant, and the combination of these methods allows for more comprehensive monitoring of ctDNA by profiling a wide spectrum of tumor-specific markers. By analyzing multiple tumor specimens in individual patients obtained from different sites and at different times during treatment, we observed clonal evolution of these tumors that was reflected by ctDNA profiles.Conclusions: Our strategy allows for the comprehensive monitoring of a broad spectrum of tumor-specific markers in plasma. Our approach may be clinically useful not only in leiomyosarcoma but also in other tumor types that lack recurrent genomic alterations. Clin Cancer Res; 24(11); 2688-99. ©2018 AACR.

Abstract A05: Circulating tumor DNA levels correlate with response to treatment in LMS patients

Circulating tumor DNA (ctDNA) has significant potential for several clinical applications, including assessment of treatment response and monitoring of recurrent/residual disease. We performed a pilot study to explore the feasibility of ctDNA monitoring in patients with leiomyosarcoma (LMS).

We profiled matching plasma and FFPE tumor specimens from 9 LMS patients. We analyzed between 2 to 6 longitudinal plasma samples (median of 5) and between 1 to 7 tumor specimens (median of 2) per patient. ctDNA analysis was performed on plasma samples collected pre-/post-surgery, throughout chemo-/radiotherapy and during follow-up. We used two separate approaches in our study: 1) targeted deep sequencing of ctDNA, tumor DNA and germline DNA to detect single nucleotide variants and indels using Cancer Personalized Profiling by deep Sequencing with integrated digital error suppression (CAPP-Seq; with a median deduplicated depth of sequencing of 2,136x); 2) copy number variant analysis in ctDNA by genome representation profiling (GRP; median coverage across the whole genome 0.23x) and in the matched tumors by SNP arrays. One patient was excluded from the analysis due to inadequate sequencing coverage in tumor specimen.

For CAPP-Seq analysis, we designed a custom 184kb capture panel targeting 89 genes that are recurrently mutated in LMS. Using strict variant calling criteria (requiring that variants be present on each strand of the original DNA “duplex” molecule) our panel identified a median of one nonsynonymous coding/splicing variant per tumor. We detected the same variants in TP53, RB1 and ATRX genes in ctDNA of 6/8 patients (with a baseline sensitivity of 87.5% and overall specificity of 98.96% calculated using plasma from 24 healthy donors). These six patients presented with advanced disease at the time of the first blood collection and were progressing throughout multiple lines of therapy. Two patients who did not have any variants detectable by CAPP-Seq in plasma had localized disease at the time of the first blood collection and/or responded well to the therapy. We found that changes in ctDNA levels appear to correspond with the extent of disease and response to treatment. Specifically, ctDNA levels decreased in a subset of patients after surgery or at the time of temporary response to chemo- and/or radiotherapy. Congruently, increases in ctDNA levels correlated with progression in most of the patients. There was a high correlation between ctDNA levels detected by CAPP-Seq (quantified as mutant molecules/mL plasma) and GRP (quantified as percent of genome showing copy number aberrations) across all plasma samples (Pearson's r= 0.88, p &lt; 0.0001), but in a few samples ctDNA was detected by only one of the two assays.

Our results suggest that serial analysis of ctDNA is a promising approach for evaluation of treatment response in LMS patients. Validation of these findings in a prospective study on a larger group of patients will be required to determine the use of this approach in a clinical setting.

References:

CAPP-Seq: PMIDs 24705333, 27018799

GRP: PMIDs 25585704, 26687610

Citation Format: Joanna Przybyl, Jacob J. Chabon, Lien Spans, Kristen Ganjoo, Sujay Vennam, Aaron M. Newman, Erna Forgó, Sushama Varma, Shirley Zhu, Maria Debiec-Rychter, Ash Alizadeh, Maximilian Diehn, Matt van de Rijn. Circulating tumor DNA levels correlate with response to treatment in LMS patients [abstract]. In: Proceedings of the AACR Conference on Advances in Sarcomas: From Basic Science to Clinical Translation; May 16-19, 2017; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(2_Suppl):Abstract nr A05.

Macrophage infiltration and genetic landscape of undifferentiated uterine sarcomas

Endometrial stromal tumors include translocation-associated low- and high-grade endometrial stromal sarcomas (ESS) and highly malignant undifferentiated uterine sarcomas (UUS). UUS is considered a poorly defined group of aggressive tumors and is often seen as a diagnosis of exclusion after ESS and leiomyosarcoma (LMS) have been ruled out. We performed a comprehensive analysis of gene expression, copy number variation, point mutations, and immune cell infiltrates in the largest series to date of all major types of uterine sarcomas to shed light on the biology of UUS and to identify potential novel therapeutic targets. We show that UUS tumors have a distinct molecular profile from LMS and ESS. Gene expression and immunohistochemical analyses revealed the presence of high numbers of tumor-associated macrophages (TAMs) in UUS, which makes UUS patients suitable candidates for therapies targeting TAMs. Our results show a high genomic instability of UUS and downregulation of several TP53-mediated tumor suppressor genes, such as NDN, CDH11, and NDRG4. Moreover, we demonstrate that UUS carry somatic mutations in several oncogenes and tumor suppressor genes implicated in RAS/PI3K/AKT/mTOR, ERBB3, and Hedgehog signaling.