Activity of the Ubiquitin-activating Enzyme Inhibitor TAK-243 in Adrenocortical Carcinoma Cell Lines, Patient-derived Organoids, and Murine Xenografts

Current treatment options for metastatic adrenocortical carcinoma (ACC) have limited efficacy, despite the common use of mitotane and cytotoxic agents. This study aimed to identify novel therapeutic options for ACC. An extensive drug screen was conducted to identify compounds with potential activity against ACC cell lines. We further investigated the mechanism of action of the identified compound, TAK-243, its synergistic effects with current ACC therapeutics, and its efficacy in ACC models including patient-derived organoids and mouse xenografts. TAK-243, a clinical ubiquitin-activating enzyme (UAE) inhibitor, showed potent activity in ACC cell lines. TAK-243 inhibited protein ubiquitination in ACC cells, leading to the accumulation of free ubiquitin, activation of the unfolded protein response, and induction of apoptosis. TAK-243 was found to be effluxed out of cells by MDR1, a drug efflux pump, and did not require Schlafen 11 (SLFN11) expression for its activity. Combination of TAK-243 with current ACC therapies (e.g., mitotane, etoposide, cisplatin) produced synergistic or additive effects. In addition, TAK-243 was highly synergistic with BCL2 inhibitors (Navitoclax and Venetoclax) in preclinical ACC models including patient-derived organoids. The tumor suppressive effects of TAK-243 and its synergistic effects with Venetoclax were further confirmed in a mouse xenograft model. These findings provide preclinical evidence to support the initiation of a clinical trial of TAK-243 in patients with advanced-stage ACC. TAK-243 is a promising potential treatment option for ACC, either as monotherapy or in combination with existing therapies or BCL2 inhibitors.

SIGNIFICANCE

ACC is a rare endocrine cancer with poor prognosis and limited therapeutic options. We report that TAK-243 is active alone and in combination with currently used therapies and with BCL2 and mTOR inhibitors in ACC preclinical models. Our results suggest implementation of TAK-243 in clinical trials for patients with advanced and metastatic ACC.

UGDH promotes tumor-initiating cells and a fibroinflammatory tumor microenvironment in ovarian cancer

BACKGROUND

Epithelial ovarian cancer (EOC) is a global health burden, with the poorest five-year survival rate of the gynecological malignancies due to diagnosis at advanced stage and high recurrence rate. Recurrence in EOC is driven by the survival of chemoresistant, stem-like tumor-initiating cells (TICs) that are supported by a complex extracellular matrix and immunosuppressive microenvironment. To target TICs to prevent recurrence, we identified genes critical for TIC viability from a whole genome siRNA screen. A top hit was the cancer-associated, proteoglycan subunit synthesis enzyme UDP-glucose dehydrogenase (UGDH).

METHODS

Immunohistochemistry was used to characterize UGDH expression in histological and molecular subtypes of EOC. EOC cell lines were subtyped according to the molecular subtypes and the functional effects of modulating UGDH expression in vitro and in vivo in C1/Mesenchymal and C4/Differentiated subtype cell lines was examined.

RESULTS

High UGDH expression was observed in high-grade serous ovarian cancers and a distinctive survival prognostic for UGDH expression was revealed when serous cancers were stratified by molecular subtype. High UGDH was associated with a poor prognosis in the C1/Mesenchymal subtype and low UGDH was associated with poor prognosis in the C4/Differentiated subtype. Knockdown of UGDH in the C1/mesenchymal molecular subtype reduced spheroid formation and viability and reduced the CD133 + /ALDH high TIC population. Conversely, overexpression of UGDH in the C4/Differentiated subtype reduced the TIC population. In co-culture models, UGDH expression in spheroids affected the gene expression of mesothelial cells causing changes to matrix remodeling proteins, and fibroblast collagen production. Inflammatory cytokine expression of spheroids was altered by UGDH expression. The effect of UGDH knockdown or overexpression in the C1/ Mesenchymal and C4/Differentiated subtypes respectively was tested on mouse intrabursal xenografts and showed dynamic changes to the tumor stroma. Knockdown of UGDH improved survival and reduced tumor burden in C1/Mesenchymal compared to controls.

CONCLUSIONS

These data show that modulation of UGDH expression in ovarian cancer reveals distinct roles for UGDH in the C1/Mesenchymal and C4/Differentiated molecular subtypes of EOC, influencing the tumor microenvironmental composition. UGDH is a strong potential therapeutic target in TICs, for the treatment of EOC, particularly in patients with the mesenchymal molecular subtype.

CellMinerCDB: NCATS Is a Web-Based Portal Integrating Public Cancer Cell Line Databases for Pharmacogenomic Explorations

Major advances have been made in the field of precision medicine for treating cancer. However, many open questions remain that need to be answered to realize the goal of matching every patient with cancer to the most efficacious therapy. To facilitate these efforts, we have developed CellMinerCDB: National Center for Advancing Translational Sciences (NCATS; https://discover.nci.nih.gov/rsconnect/cellminercdb_ncats/), which makes available activity information for 2,675 drugs and compounds, including multiple nononcology drugs and 1,866 drugs and compounds unique to the NCATS. CellMinerCDB: NCATS comprises 183 cancer cell lines, with 72 unique to NCATS, including some from previously understudied tissues of origin. Multiple forms of data from different institutes are integrated, including single and combination drug activity, DNA copy number, methylation and mutation, transcriptome, protein levels, histone acetylation and methylation, metabolites, CRISPR, and miscellaneous signatures. Curation of cell lines and drug names enables cross-database (CDB) analyses. Comparison of the datasets is made possible by the overlap between cell lines and drugs across databases. Multiple univariate and multivariate analysis tools are built-in, including linear regression and LASSO. Examples have been presented here for the clinical topoisomerase I (TOP1) inhibitors topotecan and irinotecan/SN-38. This web application provides both substantial new data and significant pharmacogenomic integration, allowing exploration of interrelationships.

SIGNIFICANCE

CellMinerCDB: NCATS provides activity information for 2,675 drugs in 183 cancer cell lines and analysis tools to facilitate pharmacogenomic research and to identify determinants of response.

New Insights on the Genetics of Pheochromocytoma and Paraganglioma and Its Clinical Implications

Simple Summary

Pheochromocytoma and paraganglioma (together PPGL) are rare neuroendocrine tumors that arise from chromaffin tissue and produce catecholamines. Approximately 40% of cases of PPGL carry a germline mutation, suggesting that they have a high degree of heritability. The underlying mutation influences the PPGL clinical presentation such as cell differentiation, specific catecholamine production, tumor location, malignant potential and genetic anticipation, which helps to better understand the clinical course and tailor treatment accordingly. Genetic testing for pheochromocytoma and paraganglioma allows an early detection of hereditary syndromes and facilitates a close follow-up of high-risk patients. In this review article, we present the most recent advances in the field of genetics and we discuss the latest guidelines on the surveillance of asymptomatic SDHx mutation carriers.

Abstract

Pheochromocytomas (PHEOs) and paragangliomas (PGLs) are rare neuroendocrine tumors that arise from chromaffin cells. PHEOs arise from the adrenal medulla, whereas PGLs arise from the neural crest localized outside the adrenal gland. Approximately 40% of all cases of PPGLs (pheochromocytomas/paragangliomas) are associated with germline mutations and 30–40% display somatic driver mutations. The mutations associated with PPGLs can be classified into three groups. The pseudohypoxic group or cluster I includes the following genes: SDHA, SDHB, SDHC, SDHD, SDHAF2, FH, VHL, IDH1/2, MHD2, EGLN1/2 and HIF2/EPAS; the kinase group or cluster II includes RET, NF1, TMEM127, MAX and HRAS; and the Wnt signaling group or cluster III includes CSDE1 and MAML3. Underlying mutations can help understand the clinical presentation, overall prognosis and surveillance follow-up. Here we are discussing the new genetic insights of PPGLs.

Novel and Highly Potent ATR Inhibitor M4344 Kills Cancer Cells With Replication Stress, and Enhances the Chemotherapeutic Activity of Widely Used DNA Damaging Agents

Although several ATR inhibitors are in development, there are unresolved questions regarding their differential potency, molecular signatures of patients with cancer for predicting activity, and most effective therapeutic combinations. Here, we elucidate how to improve ATR-based chemotherapy with the newly developed ATR inhibitor, M4344 using in vitro and in vivo models. The potency of M4344 was compared with the clinically developed ATR inhibitors BAY1895344, berzosertib, and ceralasertib. The anticancer activity of M4344 was investigated as monotherapy and combination with clinical DNA damaging agents in multiple cancer cell lines, patient-derived tumor organoids, and mouse xenograft models. We also elucidated the anticancer mechanisms and potential biomarkers for M4344. We demonstrate that M4344 is highly potent among the clinically developed ATR inhibitors. Replication stress (RepStress) and neuroendocrine (NE) gene expression signatures are significantly associated with a response to M4344 treatment. M4344 kills cancer cells by inducing cellular catastrophe and DNA damage. M4344 is highly synergistic with a broad range of DNA-targeting anticancer agents. It significantly synergizes with topotecan and irinotecan in patient-derived tumor organoids and xenograft models. Taken together, M4344 is a promising and highly potent ATR inhibitor. It enhances the activity of clinical DNA damaging agents commonly used in cancer treatment including topoisomerase inhibitors, gemcitabine, cisplatin, and talazoparib. RepStress and NE gene expression signatures can be exploited as predictive markers for M4344.

Abstract 212: Sarcoma-CellMiner: An extensive resource for patient-derived sarcoma cell line epigenetics, genomics and pharmacology

Sarcomas represent a heterogeneous group of cancers with many histological subtypes. Their prognosis remains poor and treatment is mainly based on palliative chemotherapy at metastatic stage. Tumor genome sequencing failed to identify recurrent somatic drivers while several oncogenic gene fusion-translocations have been identified in specific sarcoma subtypes. Because of the rarity and heterogeneity of sarcomas, only few sarcoma patients are enrolled in clinicals trials according their subtype. Increased translational research according subtypes of sarcoma patients is needed to improve patient management. To characterize the differences between subgroups and build translational hypotheses, we built a novel resource, Sarcoma-Cellminer, which integrates drug sensitivity and genomic data from 112 patient-derived sarcoma cell lines. These data will be available from a web-based tool (https://discover.nci.nih.gov/SclcCellMinerCDB/) derived from our CellMiner cross-database web application (https://discover.nci.nih.gov/cellminercdb). Among the 112 cell lines, 65 are bone sarcomas (including 38 Ewing sarcomas and 22 osteosarcomas), 45 are soft tissue sarcomas (including 21 rhabdomyosarcomas). Transcriptome (RNAseq and microarray), copy number, microRNA, genome-wide methylation, and drug sensitivity data are included and made publicly available. We also generated new genomic data including copy number and methylation (850 k) for 79 cell lines from the NCI in addition to the 42 cell lines from Broad Institute (CCLE) and the 40 cell lines from the MGH-Sanger (GDSC). We created the “SCLC-Global” expression set by regrouping all datasets by Z-score normalization, which enables cross-database analyses of gene expression and molecular pathways. Hierarchical clustering based on expression and methylation data identifies subtypes of sarcomas. Histone genes stand out suggesting that epigenetic regulation of canonical histones is a feature of sarcoma genesis. Sarcoma-CellMiner includes drug sensitivity data for over 500 different drugs tested in the NCI, CCLE and GDSC databases. They show two subgroups of Ewing sarcomas: one sensitive to PARP inhibitors and one resistant. Similarly, profile of response to dasatinib is different when comparing alveolar and embryonal rhabdomyosarcomas. Sarcoma-CellMiner is a powerful tool demonstrating the value of patient-derived cancer cell line databases. It provides hypothesis-driven rationale for using omics, especially transcriptome and epigenetic data to better understand sarcoma heterogeneity and select personalized treatments for clinical trials.

Citation Format: Camille Tlemsani, Lorinc Pongor, Javed Khan, Fathi Elloumi, Sudhir Varma, Augustin Luna, Vinodh Rajapakse, Kurt Kohn, Julia Krushkal, Mirit Aladjem, Beverly Teicher, Paul Meltzer, William Reinhold, Christine Heske, Yves Pommier. Sarcoma-CellMiner: An extensive resource for patient-derived sarcoma cell line epigenetics, genomics and pharmacology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 212.

Abstract 1055: Novel and highly potent ATR inhibitor M4344 kills cancer cells with replication stress and enhances the chemotherapeutic activity of widely used DNA damaging agents

Purpose: Although several ATR inhibitors are in development, there are unresolved questions regarding their differential potency, molecular signatures of cancer patients for predicting activity and most effective therapeutic combinations. Here, we elucidate how to improve ATR-based chemotherapy with the newly developed ATR inhibitor, M4344 using in vitro and in vivo models.

Experimental design: The potency of M4344 was compared with the clinically developed ATR inhibitors BAY1895344, berzosertib, and ceralasertib. The anticancer activity of M4344 was investigated as monotherapy and combination with clinical DNA damaging agents in multiple cancer cell lines, patient-derived tumor organoids and mouse xenograft models. We also elucidated the anticancer mechanisms and potential biomarkers for M4344.

Results: M4344 is highly potent among the clinically developed ATR inhibitors. Replication stress (RepStress) and neuroendocrine (NE) gene expression signatures are significantly associated with a response to M4344 treatment. M4344 kills cancer cells by inducing cellular catastrophe and DNA damage. M4344 is highly synergistic with a broad range of DNA-targeting anticancer agents. It significantly synergizes with topotecan and irinotecan in patient-derived tumor organoids and xenograft models.

Conclusions: M4344 is a promising and highly potent ATR inhibitor. It enhances the activity of clinical DNA damaging agents commonly used in cancer treatment including topoisomerase inhibitors, gemcitabine, cisplatin and talazoparib. RepStress and NE gene expression signatures can be exploited as predictive markers for M4344.

Citation Format: Ukhyun Jo, Ilya Senatorov, Astrid Zimmermann, Liton Kumar Saha, Yasuhisa Murai, Se Hyun Kim, Vinodh N Rajapakse, Fathi Elloumi, Nobuyuki Takahashi, Christopher Schultz, Anish Thomas, Frank Zenke, Yves Pommier. Novel and highly potent ATR inhibitor M4344 kills cancer cells with replication stress and enhances the chemotherapeutic activity of widely used DNA damaging agents [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1055.

CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics

CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH and MD Anderson Cancer Center (MDACC). We present CellMinerCDB 1.2 with updates to datasets from NCI-60, Broad Cancer Cell Line Encyclopedia and Sanger/MGH, and the addition of new datasets, including NCI-ALMANAC drug combination, MDACC Cell Line Project proteomic, NCI-SCLC DNA copy number and methylation data, and Broad methylation, genetic dependency and metabolomic datasets. CellMinerCDB (v1.2) includes several improvements over the previously published version: (i) new and updated datasets; (ii) support for pattern comparisons and multivariate analyses across data sources; (iii) updated annotations with drug mechanism of action information and biologically relevant multigene signatures; (iv) analysis speedups via caching; (v) a new dataset download feature; (vi) improved visualization of subsets of multiple tissue types; (vii) breakdown of univariate associations by tissue type; and (viii) enhanced help information. The curation and common annotations (e.g. tissues of origin and identifiers) provided here across pharmacogenomic datasets increase the utility of the individual datasets to address multiple researcher question types, including data reproducibility, biomarker discovery and multivariate analysis of drug activity.

SCLC-CellMiner: A Resource for Small Cell Lung Cancer Cell Line Genomics and Pharmacology Based on Genomic Signatures

CellMiner-SCLC (https://discover.nci.nih.gov/SclcCellMinerCDB/) integrates drug sensitivity and genomic data, including high-resolution methylome and transcriptome from 118 patient-derived small cell lung cancer (SCLC) cell lines, providing a resource for research into this "recalcitrant cancer." We demonstrate the reproducibility and stability of data from multiple sources and validate the SCLC consensus nomenclature on the basis of expression of master transcription factors NEUROD1, ASCL1, POU2F3, and YAP1. Our analyses reveal transcription networks linking SCLC subtypes with MYC and its paralogs and the NOTCH and HIPPO pathways. SCLC subsets express specific surface markers, providing potential opportunities for antibody-based targeted therapies. YAP1-driven SCLCs are notable for differential expression of the NOTCH pathway, epithelial-mesenchymal transition (EMT), and antigen-presenting machinery (APM) genes and sensitivity to mTOR and AKT inhibitors. These analyses provide insights into SCLC biology and a framework for future investigations into subtype-specific SCLC vulnerabilities.

Abstract 2090: Machine learning-derived gene signature predicts strong sensitivity of several solid tumors to the alkylating agent LP-184

A novel clinical agent, LP-184 is being developed in conjunction with a dedicated machine learning-guided response signature, to allow optimal benefit of LP-184 through genomics-guided therapy. To define correlates of tumor genomics with sensitivity to LP-184, we used RADR™ (Response Algorithm for Drug Positioning and Rescue), a proprietary artificial intelligence (AI)-driven platform, and CellMinerCDB (cross database)™, a systems biology platform integrating molecular and pharmacological datasets on cancer cell lines. The input for our correlational analyses, include LP-184 IC50 data on NCI-60 cell line panel representing drug response, and multi-omics data on these cell lines. CellMinerCDB™ based analysis of LP-184 using a Lasso regression model generated a 38 gene response signature that included expression of APP, NEK6, EGFR, SQSTM1, SLC25A42, SLC16A10, POLD1, SMARCC1, POLG2, CHEK1. In building the model, the signature demonstrates a sensitivity R2 = 0.98 between observed and predicted IC50 values. Additional omics data including methylation and protein levels validate the relevance of several signature genes: APP, NEK6, EGFR, SQSTM1. Concurrently, a RADR™ based analysis of LP-184 using an Artificial Neural Network (ANN) classifier model generated a 10 gene response signature with PTGR1 and PTPN14 as the top weighted genes by relative importance. To establish a signature with highest possible sensitivity, we integrated these 2 additional genes in the 38 gene signature, creating a modified 40 gene signature now having an R2 = 0.99. We next used laboratory experimental studies to measure the performance of this signature. Using an independent set of 18 cell lines not used in signature development, we obtained IC50 values and categorized cell lines as sensitive or resistant. Our in silico results matched in vitro experimental results for 13/18 cell lines (72 percent accuracy). We further applied this 40 gene signature to interrogate 1036 cell lines representing a spectrum of tumor types in the Cancer Cell Line Encyclopedia (CCLE) and obtain a signature-derived IC50. The predicted IC50 ranges from 2.7nM to 114.6uM. The least responsive tumors represent hematological cancers, reproducing the observations made in the NCI-60 panel. 92 of 116 (79%) hematologic cancers in the CCLE database showed a predicted IC50 above 1µM with a median of 3.4uM. The top 279 cell line records with a predicted IC50 below 100nM represented solid tumors with NSCLC, renal, CNS and head & neck cancers as the most sensitive. In conclusion our results demonstrate that the development of LP-184 guided by tumor gene expression patterns modeled using a combination of algorithms and signatures provides a valuable component to the armamentarium of drugs in diverse solid tumors.

Citation Format: Umesh Kathad, Aditya Kulkarni, Jean Philippe Richard, Terri Lehman, Rama Modali, Kishor Bhatia, Panna Sharma, Fathi Elloumi, Yves Pommier, William C. Reinhold. Machine learning-derived gene signature predicts strong sensitivity of several solid tumors to the alkylating agent LP-184 [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 2090.

Candidate biomarker assessment for pharmacological response

Using the information from our CellMiner (https://discover.nci.nih.gov/cellminer/) and CellMinerCDB (https://discover.nci.nih.gov/cellminercdb/) web-based applications, we identified 3978 molecular events with significant links to pharmacological response for genes that are either targets, biomarkers, or have established causal linkage to drugs. Molecular events included DNA copy number, methylation and mutation; and transcript; and whole or phospho-protein expression for the NCI-60 human cancer cell lines. While all forms of molecular data were informative in some (gene-drug) pairings, the type of significantly linked molecular events was found to vary widely by drug. Some forms of molecular data were found to have more frequent significant correlation than others. Leading were phosphoproteins as measured by antibody (31%), followed by transcript as measured by microarray (16%), and total protein levels as measured by mass spectrometry or antibody (14%). All other measurements ranged between 5 and 11%. Data reliability was underscored by concordant results when using differing drugs with the same targets, as well as different measurements of the same molecular parameter. The significance of correlations of the various molecular parameters to the pharmacological responses provides functional indication of those parameters that are biologically relevant for each gene-drug pairing, as well as comparisons between measurement types.

TREML4 Promotes Inflammatory Programs in Human and Murine Macrophages and Alters Atherosclerosis Lesion Composition in the Apolipoprotein E Deficient Mouse

The Triggering Receptor Expressed on Myeloid cells-like 4 (TREML4) is a member of the TREM receptor family, known modulators of inflammatory responses. We have previously found that TREML4 expression positively correlates with human coronary arterial calcification (CAC). However, the role of TREML4 in the pathogenesis of cardiovascular disease remains incompletely defined. Since macrophages play a key role in inflammatory conditions, we investigated if activated macrophages selectively expressed TREML4 and found that carriage of either one of the eQTL SNP's previously associated with increased TREML4 expression conferred higher expression in human inflammatory macrophages (M1) compared to alternatively activated macrophages (M2). Furthermore, we found that TREML4 expression in human M1 dysregulated several inflammatory pathways related to leukocyte activation, apoptosis and extracellular matrix degradation. Similarly, murine M1 expressed substantial levels of Treml4, as did oxLDL treated macrophages. Transcriptome analysis confirmed that murine Treml4 controls the expression of genes related to inflammation and lipid regulation pathways, suggesting a possible role in atherosclerosis. Analysis of Apoe-/-/Treml4-/- mice showed reduced plaque burden and lesion complexity as indicated by decreased stage scores, macrophage content and collagen deposition. Finally, transcriptome analysis of oxLDL-loaded murine macrophages showed that Treml4 represses a specific set of genes related to carbohydrate, ion and amino acid membrane transport. Metabolomic analysis confirmed that Treml4 deficiency may promote a beneficial relationship between iron homeostasis and glucose metabolism. Together, our results suggest that Treml4 plays a role in the development of cardiovascular disease, as indicated by Treml4-dependent dysregulation of macrophage inflammatory pathways, macrophage metabolism and promotion of vulnerability features in advanced lesions.

Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines

Here we describe a proteomic data resource for the NCI-60 cell lines generated by pressure cycling technology and SWATH mass spectrometry. We developed the DIA-expert software to curate and visualize the SWATH data, leading to reproducible detection of over 3,100 SwissProt proteotypic proteins and systematic quantification of pathway activities. Stoichiometric relationships of interacting proteins for DNA replication, repair, the chromatin remodeling NuRD complex, β-catenin, RNA metabolism, and prefoldins are more evident than that at the mRNA level. The data are available in CellMiner (discover.nci.nih.gov/cellminercdb and discover.nci.nih.gov/cellminer), allowing casual users to test hypotheses and perform integrative, cross-database analyses of multi-omic drug response correlations for over 20,000 drugs. We demonstrate the value of proteome data in predicting drug response for over 240 clinically relevant chemotherapeutic and targeted therapies. In summary, we present a novel proteome resource for the NCI-60, together with relevant software tools, and demonstrate the benefit of proteome analyses.

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High-quality NCI-60 proteotypes created using pressure cycling technology and SWATH-MS

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Proteotypes improve drug response prediction in multi-omics regression analysis

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∼3000 measured proteins allow investigation into protein complex stoichiometry

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CellMinerCDB (discover.nci.nih.gov/cellminercdb) portal allows dataset exploration

Abstract 2488: CellMinerCDB and CellMiner web-applications for genomics and pharmacogenomics analyses of cancer cell lines

The CellMiner (http://discover.nci.nih.gov/cellminer)and CellMinerCDB (https://discover.nci.nih.gov/cellminercdb/) web-applications provide complimentary functionality and datatsets that may be used for comparisons of genomic, molecular and pharmacological data within the NCI-60 cancerous cell lines, Cancer Cell Line Encyclopedia (CCLE), Genomics of Drug Sensitivity in Cancer (GDSC), Cancer Therapeutics Response Portal (CTRP), NCI/DTP small cell lung cancer (SCLC), and NCI Almanac cell line sets. CellMiner contains data for the NCI-60, including the most extensive sets of molecular and drug activity data (generated by the NCI Developmental Therapeutics Program https://dtp.cancer.gov),found for any of the databases. CellMinerCDB contains all the above mentioned cell line sets, including the substantially increased cell line numbers and tissue of origin types found in the CCLE, GDSC, and CTRP. The two web-applications have separate but complimentary functionalities. Each cell line set has some variable number of data types, some of which measure the same parameters, and some that do not. The number and make up of cell lines also varies, from 60 for the NCI-60, 69 for the SCLC, and ~1000 for the CCLE, GDSC, and CTRP. As there are partial overlaps of cell lines between many of these cell line sets, one may fill in some data type gaps by merging data from two sources, as well as do quality control by comparisons of the same data from multiple institutions. This rich set of data and functions facilitates the exploration of the relationships between and among molecular alterations and pharmacological responses in cancer cell lines from the omic perspective.

Citation Format: William C. Reinhold, Sudir Varma, Yang-Hsin Wang, Fathi Elloumi, Yves Pommier. CellMinerCDB and CellMiner web-applications for genomics and pharmacogenomics analyses of cancer cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2488.

RNA Sequencing of the NCI-60: Integration into CellMiner and CellMiner CDB

CellMiner (http://discover.nci.nih.gov/cellminer) and CellMinerCDB (https://discover.nci.nih.gov/cellminercdb/) are web-based applications for mining publicly available genomic, molecular, and pharmacologic datasets of human cancer cell lines including the NCI-60, Cancer Cell Line Encyclopedia, Genomics of Drug Sensitivity in Cancer, Cancer Therapeutics Response Portal, NCI/DTP small cell lung cancer, and NCI Almanac cell line sets. Here, we introduce our RNA sequencing (RNA-seq) data for the NCI-60 and their access and integration with the other databases. Correlation to transcript microarray expression levels for identical genes and identical cell lines across CellMinerCDB demonstrates the high quality of these new RNA-seq data. We provide composite and isoform transcript expression data and demonstrate diversity in isoform composition for individual cancer- and pharmacologically relevant genes, including HRAS, PTEN, EGFR, RAD51, ALKBH2, BRCA1, ERBB2, TP53, FGFR2, and CTNND1. We reveal cell-specific differences in the overall levels of isoforms and show their linkage to expression of RNA processing and splicing genes as well as resultant alterations in cancer and pharmacologic gene sets. Gene-drug pairings linked by pathways or functions show specific correlations to isoforms compared with composite gene expression, including ALKBH2-benzaldehyde, AKT3-vandetanib, BCR-imatinib, CDK1 and 20-palbociclib, CASP1-imexon, and FGFR3-pazopanib. Loss of MUC1 20 amino acid variable number tandem repeats, which is used to elicit immune response, and the presence of the androgen receptor AR-V4 and -V7 isoforms in all NCI-60 tissue of origin types demonstrate translational relevance. In summary, we introduce RNA-seq data to our CellMiner and CellMinerCDB web applications, allowing their exploration for both research and translational purposes. SIGNIFICANCE: The current study provides RNA sequencing data for the NCI-60 cell lines made accessible through both CellMiner and CellMinerCDB and is an important pharmacogenomics resource for the field.

A randomized trial of induction docetaxel-cisplatin-5FU followed by concomitant cisplatin-RT versus concomitant cisplatin-RT in nasopharyngeal carcinoma (GORTEC 2006-02)

Background

Concomitant chemotherapy (CT)-radiotherapy (RT) is a standard of care in locally advanced nasopharyngeal carcinoma (NPC) and a role for induction CT is not established.

Methods

Patients with locally advanced NPC, WHO type 2 or 3, were randomized to induction TPF plus concomitant cisplatin-RT or concomitant cisplatin-RT alone. The TPF regimen consisted of three cycles of Docetaxel 75 mg/m2 day 1; cisplatin 75 mg/m2 day 1; 5FU 750 mg/m2/day days 1-5. RT consisted of 70 Gy in 7 weeks plus concomitant cisplatin 40 mg/m2 weekly.

Results

A total of 83 patients were included in the study. Demographics and tumour characteristics were well balanced between both arms. Most of the patients (95%) in the TPF arm received three cycles of induction CT. The rate of grade 3-4 toxicity and the compliance (NCI-CTCAE v3) during cisplatin-RT were not different between both arms. With a median follow-up of 43.1 months, the 3-year PFS rate was 73.9% in the TPF arm versus 57.2% in the reference arm [hazard ratio (HR) = 0.44; 95% confidence interval (CI): 0.20-0.97, P = 0.042]. Similarly the 3 years overall survival rate was 86.3% in the TPF arm versus 68.9% in the reference arm (HR = 0.40; 95% CI: 0.15-1.04, P = 0.05).

Conclusion

In conclusion, several important aspects can be emphasized: the compliance to induction TPF was good and TPF did not compromise the tolerance of the concomitant RT-cisplatin phase. The improved PFS and overall survival rates needs to be confirmed by further trials.

CellMinerCDB for Integrative Cross-Database Genomics and Pharmacogenomics Analyses of Cancer Cell Lines

CellMinerCDB provides a web-based resource (https://discover.nci.nih.gov/cellminercdb/) for integrating multiple forms of pharmacological and genomic analyses, and unifying the richest cancer cell line datasets (the NCI-60, NCI-SCLC, Sanger/MGH GDSC, and Broad CCLE/CTRP). CellMinerCDB enables data queries for genomics and gene regulatory network analyses, and exploration of pharmacogenomic determinants and drug signatures. It leverages overlaps of cell lines and drugs across databases to examine reproducibility and expand pathway analyses. We illustrate the value of CellMinerCDB for elucidating gene expression determinants, such as DNA methylation and copy number variations, and highlight complexities in assessing mutational burden. We demonstrate the value of CellMinerCDB in selecting drugs with reproducible activity, expand on the dominant role of SLFN11 for drug response, and present novel response determinants and genomic signatures for topoisomerase inhibitors and schweinfurthins. We also introduce LIX1L as a gene associated with mesenchymal signature and regulation of cellular migration and invasiveness.

[Results of a retrospective study on radiotherapy for gastric mucosa-associated lymphoid tissue lymphoma]

PURPOSE

We aimed to evaluate therapeutic results of radiotherapy for gastric mucosa-associated lymphoid tissue (MALT) lymphomas.

PATIENTS AND METHODS

We reviewed retrospectively the records of 11 patients presenting with gastric MALT lymphoma treated between 1993 and 2014. Patients with low-grade lymphoma in failure after helicobacter eradication had exclusive gastric external radiotherapy. Chemotherapy followed by radiotherapy were indicated in case of high grade lymphoma. Radiotherapy doses range between 30 and 40Gy (2Gy per fraction, five fractions per week).

RESULTS

All tumours were IE stage. Seven patients with low-grade lymphoma had radiotherapy. Four patients with high-grade lymphoma received chemotherapy then radiotherapy. Ten patients are in complete remission after treatment achievement. Five and 10 years disease-free survival are 100%. No severe toxicity was seen.

CONCLUSION

Eradication of Helicobacter pylori is the mainstay of treatment of gastric MALT. External irradiation is an effective and well-tolerated treatment modality in case of resistance to helicobacter eradication.

Abstract LB-050: Interferon signaling confers resistance to androgen deprivation therapy in advanced prostate cancer

Loss of TP53 and PTEN activity are frequent genetic events in CRPC that are often associated with poorly differentiated, treatment resistant tumors. Using the Pten/Tp53-null mouse prostate cancer (PCa) model (Pb-Cre; Ptenfl/fl Tp53 fl/fl) and organoid cultures we previously have shown that a high proportion of luminal progenitors are intrinsically resistant to androgen deprivation therapy (ADT). To identify mechanisms of ADT resistance in luminal progenitors, we performed RNAseq analysis of luminal progenitor organoids derived from wild-type(WT) and Pten/Tp53-null mice. Pathway analysis identified key signaling alterations in luminal tumor organoids (AR signaling, lipid metabolism, protein secretion, inflammation etc.) that also have been described in FACS-purified human prostate luminal (CD49flo) fractions. Interestingly, we found no difference in transcriptional profiles from intact and previously castrated tumor organoids, suggesting that Pten/Tp53 null luminal progenitors are intrinsically resistance to ADT. Of note, we observed most significant enrichment of interferon(IFN) signaling in luminal progenitor tumor organoids relative to wild type luminal organoids. In other cancers and contrary to the anti-proliferative IFN signaling, expression of a subset of IFN genes contributes to genotoxic therapy resistance. This subset, referred to as IRDS (IFN-related DNA damage signature), includes a group of unphosphorylated STAT1 (U-STAT1)-driven genes that has a pro-survival function and promotes cancer cell intrinsic drug resistance. We hypothesize that the IRDS contributes to survival of PCa cells following ADT or genotoxic therapies. RT-PCR, immunofluorescence, and western blot analysis of luminal progenitor organoids showed higher U-STAT1 levels in tumor- than WT organoids, whereas pSTAT1 (Y701) was undetectable. Similarly, U-STAT1 was upregulated in Pten/Tp53-null tumor tissue relative to normal prostate. Further, for tumor organoids, ADT resulted in higher U-STAT1 levels. STAT1 depletion in tumor organoids decreased the number of progeny organoids in subsequent passages, suggesting a role in self-renewal for luminal tumor stem cells. Altogether, U-STAT1 regulated signaling has pro-survival function in Pten/Tp53-null advanced PCa. Several PDXs originating from metastatic PCa (LuCaPs 23.1, 96 and 141) express high levels of U-STAT1 dependent IFN signaling. STAT1 depletion significantly reduced self-renewing ability of these PDX derived organoids, consistent with mouse luminal tumor organoids. Interestingly, in LuCaP 141, STAT1 depletion synergized with ADT to inhibit growth ex vivo. These findings suggest that U-STAT1 dependent IFN signaling may contribute to castration resistance. We subsequently analyzed human PCa datasets to determine clinical correlates of IRDS. Analysis of the TCGA primary PCa cohort revealed IRDS as a prognostic marker for progression (n= 500, p<0.05). Further, high IRDS-expressing samples in the CRPC dataset were enriched for low AR signaling (n = 150, r= -0.33, p< 0.05). CRPC patients expressing the highest IRDS levels (n=30 of 150) showed enrichment for genes associated with stem cell features and therapy resistance. Overall, our findings suggest U-STAT1 dependent IRDS expression is correlated with poorly differentiated PCa and may contribute to intrinsic therapy resistance.

Citation Format: Supreet Agarwal, Kerry McGowen, Fathi Elloumi, Maggie Cam, Mike Beshiri, Keith Jansson, Eva Corey, Kathleen Kelly. Interferon signaling confers resistance to androgen deprivation therapy in advanced prostate cancer [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 LB-050.

Long Noncoding RNA PURPL Suppresses Basal p53 Levels and Promotes Tumorigenicity in Colorectal Cancer

Basal p53 levels are tightly suppressed under normal conditions. Disrupting this regulation results in elevated p53 levels to induce cell cycle arrest, apoptosis, and tumor suppression. Here, we report the suppression of basal p53 levels by a nuclear, p53-regulated long noncoding RNA that we termed PURPL (p53 upregulated regulator of p53 levels). Targeted depletion of PURPL in colorectal cancer cells results in elevated basal p53 levels and induces growth defects in cell culture and in mouse xenografts. PURPL associates with MYBBP1A, a protein that binds to and stabilizes p53, and inhibits the formation of the p53-MYBBP1A complex. In the absence of PURPL, MYBBP1A interacts with and stabilizes p53. Silencing MYBBP1A significantly rescues basal p53 levels and proliferation in PURPL-deficient cells, suggesting that MYBBP1A mediates the effect of PURPL in regulating p53. These results reveal a p53-PURPL auto-regulatory feedback loop and demonstrate a role for PURPL in maintaining basal p53 levels.

NFκB Promotes Ovarian Tumorigenesis via Classical Pathways That Support Proliferative Cancer Cells and Alternative Pathways That Support ALDH+ Cancer Stem-like Cells

Understanding the mechanisms supporting tumor-initiating cells (TIC) is vital to combat advanced-stage recurrent cancers. Here, we show that in advanced ovarian cancers NFκB signaling via the RelB transcription factor supports TIC populations by directly regulating the cancer stem-like associated enzyme aldehyde dehydrogenase (ALDH). Loss of RelB significantly inhibited spheroid formation, ALDH expression and activity, chemoresistance, and tumorigenesis in subcutaneous and intrabursal mouse xenograft models of human ovarian cancer. RelB also affected expression of the ALDH gene ALDH1A2 Interestingly, classical NFκB signaling through the RelA transcription factor was equally important for tumorigenesis in the intrabursal model, but had no effect on ALDH. In this case, classical signaling via RelA was essential for proliferating cells, whereas the alternative signaling pathway was not. Our results show how NFκB sustains diverse cancer phenotypes via distinct classical and alternative signaling pathways, with implications for improved understanding of disease recurrence and therapeutic response. Cancer Res; 77(24); 6927-40. ©2017 AACR.

Abstract 2896: STAT1 dependent interferon-related DNA damage resistance signature (IRDS) as a survival mechanism in castrate resistant prostate cancer (CRPC)

Using the organoid culture system and aggressive Pten/Tp53-null mouse model (GEMM), we have previously shown that the prostate cancer cell population harbors two classes of self-renewing luminal progenitors which are resistant to in vivo castration and to androgen receptor (AR) inhibitors (enzalutamide) ex vivo. Understanding signaling pathways governing intrinsic survival/self-renewal ability of luminal progenitors in castrate conditions can highlight pathways that play a role in acquired drug resistance. To identify mechanisms of castration resistance in luminal progenitors, we performed RNAseq analysis of luminal progenitor organoids derived from wild-type(WT) and Pten/Tp53-null mice (intact and castrated (two weeks), n=5; each). Gene enrichment analysis identified key signaling pathways altered in luminal tumor organoids (AR signaling, lipid metabolism, protein secretion, inflammation etc.) that have also been described for FACS-purified human prostate luminal (CD49flo) fraction. Interestingly, we found no difference in transcriptional profiles of intact and castrated tumor organoids, suggesting intrinsic survival ability of luminal progenitors upon castration. Of note, we observed most significant enrichment of STAT1-dependent IRDS in luminal progenitor tumor organoids relative to wild type luminal organoids. IRDS comprises of a subset of STAT1-driven genes that have been previously associated with survival of cancer cells and with breast cancer therapy resistance. Our analysis of human prostate cancer datasets revealed IRDS as a prognostic marker for progression in the TCGA primary prostate cancer cohort (p<0.05). Further, high IRDS-expressing CRPC samples (SU2C dataset) were enriched for low AR signaling (r= -0.33, p< 0.05). CRPC patients in IRDS-hi cohort showed enrichment for cancer stem cell phenotype and for genes associated with drug resistance, Consistent with the bioinformatics analysis real time PCR, immunofluorescence and western blot analysis of ex-vivo organoid cultures of castration-resistant Pten/Tp53-null tumor organoids showed higher protein expression of STAT1 and IRDS genes in luminal tumor organoids relative to luminal WT organoids. In vivo, castrated prostate tumors showed higher STAT1 levels than the intact tumors. Treatment with enzalutamide of luminal tumor organoids resulted in time dependent increase in STAT1 expression. STAT1 KD in tumor organoids decreased number of progeny organoids in subsequent generations suggesting either a direct or indirect effect upon self-renewal. Overall, our initial findings suggest STAT1 dependent signaling as a potential mechanism of androgen-independent survival in prostate cancer.

Citation Format: Supreet Agarwal, Kerry McGowen, Keith Jansson, Mike Beshiri, Fathi Elloumi, Maggie Cam, Kathy Kelly. STAT1 dependent interferon-related DNA damage resistance signature (IRDS) as a survival mechanism in castrate resistant prostate cancer (CRPC) [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 2896. doi:10.1158/1538-7445.AM2017-2896

Oncogenic driver genes and the inflammatory microenvironment dictate liver tumor phenotype

The majority of hepatocellular carcinoma develops in the background of chronic liver inflammation caused by viral hepatitis and alcoholic or nonalcoholic steatohepatitis. However, the impact of different types of chronic inflammatory microenvironments on the phenotypes of tumors generated by distinct oncogenes is largely unresolved. To address this issue, we generated murine liver tumors by constitutively active AKT-1 (AKT) and β-catenin (CAT), followed by induction of chronic liver inflammation by 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) and carbon tetrachloride. Also, the impact of DDC-induced chronic liver inflammation was compared between two liver tumor models using a combination of AKT-CAT or AKT-NRAS(G12V) . Treatment with DDC and carbon tetrachloride significantly facilitated the adenoma-to-carcinoma conversion and accelerated the growth of AKT-CAT tumors. Furthermore, DDC treatment altered the morphology of AKT-CAT tumors and caused loss of lipid droplets. Transcriptome analysis of AKT-CAT tumors revealed that cellular growth and proliferation were mainly affected by chronic inflammation and caused up-regulation of Cxcl16, Galectin-3, and Nedd9, among others. Integration with transcriptome profiles from human hepatocellular carcinomas further demonstrated that AKT-CAT tumors generated in the context of chronic liver inflammation showed enrichment of poor prognosis gene sets or decrease of good prognosis gene sets. In contrast, DDC had a more subtle effect on AKT-NRAS(G12V) tumors and primarily enhanced already existent tumor characteristics as supported by transcriptome analysis. However, it also reduced lipid droplets in AKT-NRAS(G12V) tumors.

CONCLUSION

Our study suggests that liver tumor phenotype is defined by a combination of driving oncogenes but also the nature of chronic liver inflammation. (Hepatology 2016;63:1888-1899).

[Embryonal paratesticular rhabdomyosarcoma: a case report and a literature review]

Paratesticular rhabdomyosarcoma is a rare tumor. Multimodality treatment should involve surgery, radiotherapy and chemotherapy, which are indicated according to risk groups. Risk group stratification depends on pretreatment staging and definitive histology. Patients older than 10years or those with suspected lymph nodes on imaging have higher incidence of lymph node involvement. Prognosis is excellent for localized tumors, survival rates exceed 90%. We report a case of embryonal paratesticular rhabdomyosarcoma treated in our institution.

[Large cell neuroendocrine carcinoma of the nasopharynx: A case report]

Neuroendocrine carcinoma of the head and neck is a rare entity. The parotid gland is the most commonly affected site. A nasopharyngeal site has not been previously described. We report a 35-year-old patient who consulted for tinnitus and nasal obstruction. The assessment found a nasopharyngeal tumour T4N0M0. The patient underwent 6 cycles of chemotherapy based on VP16 and cisplatin, followed by radiotherapy at a dose of 70 Gy to the nasopharynx and 50 Gy to the neck. The evolution was marked by clinical improvement and radiological stability. Six months after the end of treatment, the patient had a local and meningeal relapse. He received palliative care. He died 19 months after the end of treatment.

[Is there any difference in therapeutic results of nasopharyngeal carcinoma between adults and children?]

PURPOSE

To compare therapeutic results of nasopharyngeal carcinoma between adults and children.

PATIENTS AND METHODS

Three hundred and seventy seven patients with nasopharyngeal carcinoma received a radiotherapy between 1993 and 2007. Sixty-nine of them were 20years old or less. Two hundred and sixty eight patients received a chemotherapy (neoadjuvant or concomitant).

RESULTS

Overall survival and disease-free survival at 5 years were 67 % and 59.4 % in all patients, respectively. Overall survival rates at 5 years in children and adults were 66 % and 64 %, respectively (P=0.17), disease-free survival rates at 5 years were 66 % and 57 %, respectively (P=0.17). Local failures occurred more frequently in adults than in children (1.4 % versus 14 %). However, metastatic events were frequently seen in children. Late toxicities were important in children, xerostomia was the most common one.

CONCLUSION

Despite locally advanced disease in children, therapeutic results were better than in adults but not statistically significant. The use of treatment combination (chemotherapy and radiotherapy) in juvenile nasopharyngeal carcinoma may explain our findings.

Tissue banking, bioinformatics, and electronic medical records: the front-end requirements for personalized medicine

Personalized medicine promises patient-tailored treatments that enhance patient care and decrease overall treatment costs by focusing on genetics and "-omics" data obtained from patient biospecimens and records to guide therapy choices that generate good clinical outcomes. The approach relies on diagnostic and prognostic use of novel biomarkers discovered through combinations of tissue banking, bioinformatics, and electronic medical records (EMRs). The analytical power of bioinformatic platforms combined with patient clinical data from EMRs can reveal potential biomarkers and clinical phenotypes that allow researchers to develop experimental strategies using selected patient biospecimens stored in tissue banks. For cancer, high-quality biospecimens collected at diagnosis, first relapse, and various treatment stages provide crucial resources for study designs. To enlarge biospecimen collections, patient education regarding the value of specimen donation is vital. One approach for increasing consent is to offer publically available illustrations and game-like engagements demonstrating how wider sample availability facilitates development of novel therapies. The critical value of tissue bank samples, bioinformatics, and EMR in the early stages of the biomarker discovery process for personalized medicine is often overlooked. The data obtained also require cross-disciplinary collaborations to translate experimental results into clinical practice and diagnostic and prognostic use in personalized medicine.

Systematic bias in genomic classification due to contaminating non-neoplastic tissue in breast tumor samples

Background

Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification.

Methods

To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors.

Results

Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability.

Conclusions

Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor.

Abstract 2213: The normal breast study: Understanding the normal tissue adjacent to breast cancers. Epithelial-to-Mesenchymal transition (EMT) signatures

Significance: Breast Cancers (BC) evolve and acquire adaptive changes while in active communication with the surrounding host normal tissue. Understanding how host tissue interacts with cancers during breast cancer progression could lead to novel biomarkers or targeted therapies.

Innovation: We hypothesized that novel molecular subtypes of microenvironment (ME) can be identified and have prognostic value. Stromal signatures are poorly understood and the independent prognostic value of stroma and/or ME response has not been widely studied.

Approach: We used gene expression data 1) to identify molecular subtypes of microenvironment, 2) to study the distribution and prevalence of microenvironment subtypes in an ethnically diverse group of BC cases and 3) to test the value of ME in predicting breast cancer progression. In 2009, our team initiated the UNC NORMAL BREAST STUDY (NBS), a unique epidemiologic study of normal tissue from ethnically diverse patients at UNC Hospitals. The NBS has recruited over 200 patients undergoing breast surgery at UNC Hospitals, including cosmetic surgeries, excisional diagnostic breast biopsies, lumpectomies and mastectomies. All participants donate snap frozen and paraffin-embedded normal breast tissue. For all patients who have been diagnosed with breast cancer, the gross distance between the tumor and the normal breast tissue specimen is measured. In addition all study participants are asked to submit a blood sample and complete a telephone interview regarding demographics and environmental exposures. Medical record abstraction is performed to obtain treatment data and anthropometry. Each sample is carefully analyzed for histopathology and whole genome gene expression data is collected.

Results: Among the breast cancer patients profiled in our initial studies, unsupervised clustering resulted in two groups of patients, one of which showed expression features suggestive of an activated mesenchyme. We then generated an EMT signature using cell line models and observed that this signature is enriched in one cluster or subgroup of these patients. In the approximately 40% of patients where the EMT signature is enriched, survival was decreased, and survival was significantly decreased among patients with ER positive disease.

Conclusion: The NBS allows a unique opportunity to make an impact in discovering novel biology of human breast cancer microenvironment. The information gained from this translational study will establish whether microenvironment subtypes are associated with recurrence risk and will elucidate how variation in host biology contributes to BC disparities.

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 2213. doi:10.1158/1538-7445.AM2011-2213

Interactions with fibroblasts are distinct in Basal-like and luminal breast cancers

Basal-like breast cancers have several well-characterized distinguishing molecular features, but most of these are features of the cancer cells themselves. The unique stromal-epithelial interactions, and more generally, microenvironmental features of basal-like breast cancers have not been well characterized. To identify characteristic microenvironment features of basal-like breast cancer, we performed cocultures of several basal-like breast cancer cell lines with fibroblasts and compared these with cocultures of luminal breast cancer cell lines with fibroblasts. Interactions between basal-like cancer cells and fibroblasts induced expression of numerous interleukins and chemokines, including IL-6, IL-8, CXCL1, CXCL3, and TGFβ. Under the influence of fibroblasts, basal-like breast cancer cell lines also showed increased migration in vitro. Migration was less pronounced for luminal lines; but, these lines were more likely to have altered proliferation. These differences were relevant to tumor biology in vivo, as the gene set that distinguished luminal and basal-like stromal interactions in coculture also distinguishes basal-like from luminal tumors with 98% accuracy in 10-fold cross-validation and 100% accuracy in an independent test set. However, comparisons between cocultures where cells were in direct contact and cocultures where interaction was solely through soluble factors suggest that there is an important impact of direct cell-to-cell contact. The phenotypes and gene expression changes invoked by cancer cell interactions with fibroblasts support the microenvironment and cell-cell interactions as intrinsic features of breast cancer subtypes.

A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

Batch effects are the systematic non-biological differences between batches (groups) of samples in microarray experiments due to various causes such as differences in sample preparation and hybridization protocols. Previous work focused mainly on the development of methods for effective batch effects removal. However, their impact on cross-batch prediction performance, which is one of the most important goals in microarray-based applications, has not been addressed. This paper uses a broad selection of data sets from the Microarray Quality Control Phase II (MAQC-II) effort, generated on three microarray platforms with different causes of batch effects to assess the efficacy of their removal. Two data sets from cross-tissue and cross-platform experiments are also included. Of the 120 cases studied using Support vector machines (SVM) and K nearest neighbors (KNN) as classifiers and Matthews correlation coefficient (MCC) as performance metric, we find that Ratio-G, Ratio-A, EJLR, mean-centering and standardization methods perform better or equivalent to no batch effect removal in 89, 85, 83, 79 and 75% of the cases, respectively, suggesting that the application of these methods is generally advisable and ratio-based methods are preferred.

ACToR--Aggregated Computational Toxicology Resource

ACToR (Aggregated Computational Toxicology Resource) is a database and set of software applications that bring into one central location many types and sources of data on environmental chemicals. Currently, the ACToR chemical database contains information on chemical structure, in vitro bioassays and in vivo toxicology assays derived from more than 150 sources including the U.S. Environmental Protection Agency (EPA), Centers for Disease Control (CDC), U.S. Food and Drug Administration (FDA), National Institutes of Health (NIH), state agencies, corresponding government agencies in Canada, Europe and Japan, universities, the World Health Organization (WHO) and non-governmental organizations (NGOs). At the EPA National Center for Computational Toxicology, ACToR helps manage large data sets being used in a high-throughput environmental chemical screening and prioritization program called ToxCast.