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This file contains Supplementary Figure S1 (Correlation between downregulation of EGFR transcriptional target genes, and sensitivity to erlotinib at the high concentration after 6 hours); Supplementary Figure S2 (EGFR inhibitor and DNA damaging agents induce directionally opposing changes in EGR1 expression that are differentially associated with drug sensitivity); Supplementary Figure S3 (Representative 3D response surface plots for the gemcitabine-erlotinib combination in the indicated cell lines); Supplementary Figure S4 (Representative 3D response surface plots for the vorinostat-talazoparib combination in the indicated cell lines); Supplementary Table S1 (Validation of array-based measurements by qRT-PCR); Supplementary Table S2 (Genes with concerted changes in the same direction [upregulation or downregulation] 24 hours after treatment with each of the 15 drugs); and Supplementary Table S4 (Selected genes potentially mediating drug insensitivity to agents in the NCI TPW dataset).

The intracellular effects and overall efficacies of anticancer therapies can vary significantly by tumor type. To identify patterns of drug-induced gene modulation that occur in different cancer cell types, we measured gene-expression changes across the NCI-60 cell line panel after exposure to 15 anticancer agents. The results were integrated into a combined database and set of interactive analysis tools, designated the NCI Transcriptional Pharmacodynamics Workbench (NCI TPW), that allows exploration of gene-expression modulation by molecular pathway, drug target, and association with drug sensitivity. We identified common transcriptional responses across agents and cell types and uncovered gene-expression changes associated with drug sensitivity. We also demonstrated the value of this tool for investigating clinically relevant molecular hypotheses and identifying candidate biomarkers of drug activity. The NCI TPW, publicly available at https://tpwb.nci.nih.gov, provides a comprehensive resource to facilitate understanding of tumor cell characteristics that define sensitivity to commonly used anticancer drugs.Significance:The NCI Transcriptional Pharmacodynamics Workbench represents the most extensive compilation to date of directly measured longitudinal transcriptional responses to anticancer agents across a thoroughly characterized ensemble of cancer cell lines.

The typical low life expectancy and limited therapeutic options for patients with small cell lung cancer (SCLC) caused the National Cancer Institute (NCI) to categorize SCLC as “recalcitrant” cancer. SCLC-CellMiner (https://discover.nci.nih.gov/SclcCellMinerCDB) integrates drug sensitivity and genomic data from 118 patient-derived SCLC cell lines, providing a unique genomic and pharmacological resource. Transcriptomic profiling validates the SCLC consensus nomenclature based on expression of 4 master transcription factors NEUROD1, ASCL1, POU2F3 and YAP1 (NAPY classification) and demonstrate differential transcriptional networks driven by these lineage specific transcription factors. Our analyses reveal transcription networks linking SCLC subtypes with MYC and its paralogs MYCL and MYCN and inactivation of the NOTCH pathway in the neuroendocrine SCLC (N, A & P subgroups). By contrast, YAP1-driven SCLC (SCLC-Y) express the NOTCH pathway and co-express both YAP/TAZ and its negative regulator genes driving the Hippo pathway. SCLC-Y cell lines show the greatest resistance to the standard of care drugs (etoposide, cisplatin and topotecan) while PI3K-AKT-mTOR inhibitors show a higher activity in this subgroup. To explore the immune pathways and the potential value of the transciption factors based classification for selecting SCLC patients likely to respond to immune checkpoint inhibitors, we explored a transcriptome signature based on 18 established native immune response and antigen-presenting genes (APM score). The SCLC-Y cell lines are the only subset expressing innate immune response genes. SCLC-CellMiner is a powerfull tool demonstrating the value of cancer cell line genomic and pharmacological databases. Our analyses suggest the potential genomic molecular classifications to select patients for targeted therapies and immunotherapy, such as patients in the SCLC-Y subgroup who may be most responsive to immune checkpoints modulators. Citation Format: Camille Tlemsani, Lorinc Pongor, Fathi Elloumi, Luc Girard, Kenneth Huffman, Nitin Roper, Sudhir Varma, Augustin Luna, Vinodh Rajapakse, Pascaline Boudou-Rouquette, Robin Sebastian, Kurt Kohn, Julia Krushkal, Mirit Aladjem, Beverly Teicher, Paul Meltzer, William Reinhold, John Minna, Anish Thomas, Yves Pommier. SCLC-CellMiner: An extensive cell line genomic and pharmacology resource identifies a subgroup of small cell lung cancers sensitive to targeted therapies and immunotherapies [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 203.

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.

Small cell lung cancer (SCLC), an aggressive neuroendocrine type of lung cancer, rapidly acquires resistance to treatment. SCLC progression, lineage differentiation, and resistance to therapy have been suggested to involve epigenetic processes. To date, epigenetic links connecting SCLC DNA methylation patterns to drug response and the ways in which these links are mediated by gene expression remain unclear. In order to understand how DNA methylation may affect SCLC response to chemotherapy, we performed an epigenome-wide association study of 66 SCLC cell lines. We used Illumina Infinium MethylationEPIC BeadChip to measure methylation of 866,091 probes. We examined how methylation of probes and gene regions was associated with SCLC in vitro response to 526 antitumor agents. We also identified associations of epigenetic variation with drug response which may be mediated by regulation of gene expression. A potentially important strong association was observed for TREX1, which encodes the 3’ exonuclease I (DNase III) that is involved in resolution of chromatin bridges and has a potential role in chromothripsis. Increased methylation and low expression of TREX1 were associated with SCLC cell line sensitivity to multiple Aurora kinase inhibitors AZD-1152, SCH-1473759, SNS-314, and TAK-901, as well as to the CDK inhibitor R-547, Vertex ATR inhibitor Cpd 45, and the mitotic spindle disruptor vinorelbine. TREX1 upregulation has been previously associated with resistance of other cancers to DNA damaging agents and with DNA repair or DNA degradation after drug exposure. In our analysis, when compared to other cancer categories, TREX1 in SCLC cell lines had low mRNA expression and increased DNA methylation upstream of its transcription start site, which may provide a possible molecular mechanism for SCLC sensitivity to Aurora kinase inhibitors. CEP350 and MLPH, which are involved in centrosome machinery and microtubule tracking, were associated with several Aurora kinase inhibitors and other agents. Among other examples, EPAS1 (HIF2A) was associated with several Aurora kinase inhibitors, the PLK1 inhibitor GSK-461364, and the Bcl-2 inhibitor ABT-737. Methylation of KDM1A, encoding the histone modifier lysine demethylase 1A (LSD1), was associated with PLK1 inhibitors and the KSP inhibitor SB-743921. IGFBP5, which is expressed in the tuft cell-like SCLC subtype, was associated with the mTOR inhibitor INK-128. Upstream regions of MDM2 and DLL3, a Notch pathway regulator overexpressed in ASCL1-high SCLC tumors, were associated with Bcl-2 inhibitors. Methylation and expression of YAP1, a SCLC lineage driver regulating the Hippo pathway, were correlated with the MTOR inhibitor rapamycin. Among non-neuroendocrine lineage markers, EPHA2 was associated with Aurora kinase inhibitors and a PLK1 inhibitor, and CD151 with Bcl-2 inhibitors. Increased methylation upstream of SLFN11 was correlated with resistance to DNA damaging agents, which is likely mediated by SLFN11 expression. The 5’ UTR region of the epigenetic modifier EZH2 was associated with Aurora kinase inhibitors and the FGFR inhibitor BGJ-398. These and multiple other associations identified in this study provide a novel understanding of epigenetic mechanisms which may modulate SCLC response to chemotherapy, and suggest potential molecular targets for combination therapies. This research was supported in part with federal funds from the National Cancer Institute, NIH, under contract HHSN261200800001E. Citation Format: Julia Krushkal, Thomas Silvers, Dmitriy Sonkin, Suleyman Vural, John Connelly, Sudhir Varma, Paul S. Meltzer, William C. Reinhold, Annamaria Rapisarda, David Evans, Yves Pommier, Beverly A. Teicher. Associations of epigenome-wide DNA methylation patterns with chemosensitivity and chemoresistance of small cell lung cancer cell lines [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr B013. doi:10.1158/1535-7163.TARG-19-B013

Folate-mediated one-carbon metabolism (OCM) is essential for growth and survival of cancer cells. It affects biosynthesis of nucleotides and amino acids, regulation of redox status, methylation of nucleic acids and proteins, and genome maintenance. We investigated whether the response of cancer cells to antitumor therapy treatment may be partially influenced by variation in expression of one-carbon metabolism genes. We used publicly available gene expression data and drug response measures for 251 antitumor agents in 635 cancer cell lines with matching information from the Cancer Cell Line Encyclopedia and the Genomics of Drug Sensitivity in Cancer resources. We examined whether pre-treatment expression levels of OCM-related genes were associated with drug response. Among the 34 OCM genes examined, expression of GART, TYMS, SHMT2, MTR, ALDH2, BHMT, MAT2B, MTHFD2, NNMT, and SLC46A1 showed modest correlations with response to treatment with a variety of antitumor agents. Higher expression levels of the SLC46A1 transporter gene were associated with resistance to multiple drugs, whereas elevated expression of GART, TYMS, SHMT2, MTR, BHMT, and MAT2B was associated with chemosensitivity to multiple antitumor agents. NNMT expression was bimodally distributed and showed different directions of association with various agents. Correlation of increased NNMT expression with sensitivity to dasatinib was validated in the NCI-60 cancer cell line panel. Expression of several OCM genes was strongly associated with expression of multiple components of drug target pathways. For example, expression of both TYMS and GART was strongly positively correlated with BRCA1 expression, NNMT expression was associated with expression of multiple drug target genes including EGFR and ABL2, and the expression of TYMS, DHFR, and SHMT1 was positively correlated with AURKB expression. Pretreatment expression levels of many OCM genes including DHFR, TYMS, ATIC, GART, AHCY, MTHFD1, SLC19A1, and multiple other genes were positively correlated with each other, suggesting their co-regulation. In contrast, NNMT expression was negatively correlated with expression of several other OCM genes. Further studies could investigate whether correlations of expression levels of individual OCM genes with drug response are related to specific metabolic roles of these genes or whether such associations may be due to the general increase in cellular growth and proliferation and tumor progression, which may affect sensitivity to cancer treatment. Citation Format: Julia Krushkal, Suleyman Vural, Dong-Joon Min. Association of transcriptional levels of folate-mediated one-carbon metabolism related genes in cancer cell lines with drug treatment response [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 4246.

DNA methylation has a powerful influence on cellular processes. It plays important roles in cancer initiation and progression. Cancer cells exhibit frequent epigenomic alterations that affect expression of genes involved in apoptosis, cell proliferation, and DNA repair. We used expression information of known methylating and demethylating genes in cancer cell lines to analyze their association with methylation levels of individual probes and median epigenome-wide methylation levels. We utilized RNA-seq gene expression measures and Illumina Infinium HumanMethylation450 BeadChip DNA methylation data of 645 cancer cell lines from 23 cancer types from the Cancer Cell Line Encyclopedia and Genomics of Drug Sensitivity in Cancer resources. We analyzed 73 genes, products of which are involved in methylation and demethylation processes, and examined correlations between expression levels of these genes and methylation status of individual probes and epigenome-wide. In a combined analysis across all cancer types, we observed statistically significant correlations between expression of global DNA methyltransferase genes, DNMT1, DNMT3A, and DNMT3B, and probe methylation levels in 566, 909, and 230 genes, respectively. In particular, DNMT3A expression was associated with methylation status of growth factor and receptor genes FGF1, FGFR4, and EGFR. Expression of hydroxymethylating genes TET1, TET2, and TET3 was correlated with methylation status of probes in 363, 1, and 1055 genes, respectively, including associations of TET3 expression with methylation of probes in the FGF1, KIT, FHIT, IGF1R, IGF2BP2, and PARP3 genes, which may affect growth, proliferation, and DNA repair of tumor cells. APOBEC1, CBX2, UHRF1 and ZBTB38, products of which are involved in various molecular steps of DNA methylation or demethylation, had the largest numbers of associations in different cancer types. For example, in chronic lymphocytic leukemia cell lines we observed a strong negative correlation between ZBTB38 expression, the product of which binds methylated DNA, and methylation levels of probes in 204 genes. We also found a strong correlation between UHRF1 gene expression and methylation levels of probes in 150 genes in chronic lymphocytic leukemia cell lines, in agreement with reported roles of the product of this gene in binding DNA methyltransferases and affecting DNMT1 methylation activity. These results provide a better understanding of molecular mechanisms of epigenetic dysregulation in cancer cells and may provide strategies for future analysis of molecular targets of drug response that may be affected via epigenetic processes. Citation Format: Suleyman Vural, Julia Krushkal. A survey of molecular factors of DNA methylation and demethylation in a broad range 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 2479.

We used gene expression information and mutational signature analysis of cell lines from a diverse range of cancerous tissues to examine the activity of two members of the APOBEC family of cytidine deaminases, APOBEC3A and APOBEC3B, and three additional genes. APOBEC3B is known to increase the mutation load in many cancers, generating kataegis clusters of closely spaced, single strand-specific DNA substitutions with a characteristic hypermutation signature. Some studies also suggested that APOBEC3A, REV1, UNG, and FHIT may also participate in hypermutation processes associated with APOBEC activity. We investigated how the activities of these five genes may affect the abundance of APOBEC-like signatures and whether they may be associated with sensitivity of cancer cells to treatment in different cancer categories. We analyzed several data sources for 1,408 cell lines from 26 cancer types available from the Cancer Cell Line Encyclopedia (CCLE) and the Genomics of Drug Sensitivity in Cancer (GDSC) resources. These data included whole exome sequencing (WES) data, microarray gene expression information, and drug sensitivity information. We examined correlations of the abundance of APOBEC-associated motifs and WES-wide mutation loads with APOBEC3A, APOBEC3B, REV1, UNG, and FHIT gene expression, as well as their association with cell line chemosensitivity to 255 antitumor drugs in multiple cancer subtypes. We were able to confirm several previously reported expression and chemosensitivity associations and found additional correlations, which may be clinically important. Sensitivity to JQ1, JNK inhibitors AS601245 and VIII, BMS-509744, bicalutamide, and several other agents was correlated with candidate gene expression levels or with abundance of APOBEC-like motif clusters in specific cancer categories such as pancreatic, breast and non-small cell lung cancer cell lines. For example, we observed a strong negative correlation between APOBEC3A expression in pancreatic cell lines and sensitivity to JQ1, a BET inhibitor, which had been reported to inhibit pancreatic cancer cells in vitro and in vivo. In glioma cell lines, APOBEC3B expression was significantly negatively correlated with sensitivity to a CDK9 inhibitor THZ-2-49 and HSP90 inhibitors AUY922 and 17-AAG (tanespimycin). We observed a strong correlation between the combined length of kataegis clusters and chemoresistance to bicalutamide, a nonsteroidal antiandrogen drug, in breast cancer cell lines. Our findings suggest that associations of sensitivity to drug treatment with activities of APOBEC3A/B, REV1, UNG, and FHIT and with the rates of APOBEC-associated mutagenic processes may vary among different cancer categories. Citation Format: Suleyman Vural, Julia Krushkal, Richard Simon. Activity of APOBEC3A, APOBEC3B, REV1, UNG, and FHIT is associated with drug sensitivity in specific cancer subtypes [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 1282.

The standard-of-care for limited stage and extensive stage SCLC has remained etoposide and a platinum complex for more than 30 years because 60-80% of patients respond; however, SCLC inevitably recurs. Recurrent SCLC has proven to be resistant to many therapeutics administered as second- or third-line treatments; therefore, combining therapies in the first instance may be a critically useful strategy. A high throughput screen was performed where 62 SCLC lines were exposed to etoposide (0.3uM)/carboplatin (3.7 uM) (E/C) with or without simultaneous exposure to a third agent (n = 220). Viability of the cells was measured using CellTiter-Glo after 96 hr exposure to 9 concentrations of each individual compound or combination with E/C. The test concentrations encompassed the clinical Cmax for each third agent, and the concentrations of E/C selected for the screen were systematically determined to produce SCLC kill that would allow observation of additivity/synergy upon addition of a third agent. IC50s were determined from the concentration response data and showed that the predominant effect of adding a third agent to E/C was additive. Less than additive effects occurred more frequently in SCLC lines that were sensitive to etoposide/carboplatin. Antagonism with E/C occurred in combination with taxanes and tubulin fragmenters such as vinorelbine. Effective single agents such as the nuclear kinase inhibitors (aurora kinase inhibitors, KSP/EG5 inhibitors and polo-like kinase inhibitors) were antagonistic in combination with E/C but were effective single agents. Greater than additive SCLC killing occurred with E/C in combination with several classes of agents. The combination of the Chk1 inhibitor rabusertib with E/C resulted in an IC50 that was >1 log lower than that of rabusertib alone in several SCLC lines. The GSK-3β inhibitor LY-2090314 produced greater than additive SCLC killing in combination with E/C. LY-2090314 had little effect on the SCLC lines alone but the simultaneous combination with E/C resulted in multi-log killing in selected SCLC lines. The BET bromodomain inhibitor MK-8628 was highly effective when combined with E/C as was the PARP1 inhibitor talazoparib in a small subset of the SCLC lines. While many agents have been tested in combination with E/C in SCLC and failed to improve patients’ survival, the findings of this study identified third agents that may represent new leads for the treatment of this recalcitrant disease. Distinct patterns of response in select subsets of the 62 SCLC lines tested may allow identification of biomarkers predictive of the responders to certain 3-drug regimens. This project has been funded in whole or in part with federal funds from the National Cancer Institute, NIH, under contract no. HHSN261200800001E. Note: This abstract was not presented at the meeting. Citation Format: Beverly A. Teicher, Michael Selby, Thomas Silvers, Julie Laudeman, Russell Reinhart, Rene Delosh, Chad Ogle, Ralph Parchment, Julia Krushkal, Dmitriy Sonkin, Joel Morris, Mark Kunkel, David Evans. Small cell lung carcinoma (SCLC) cell line screen of standard of care (etoposide/carboplatin) plus a third agent [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 4831. doi:10.1158/1538-7445.AM2017-4831

The APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like) gene family of cytidine deaminases includes evolutionarily conserved genes that play important roles in DNA repair and mRNA editing. Activity of at least two APOBEC family members, APOBEC3A and APOBEC3B, can lead to kataegis, a mutagenic process in cancer cells that generates clusters of closely spaced, single strand specific C->T DNA substitutions. APOBEC mutagenesis has a characteristic signature, most commonly represented by the 5’-Tp(C->T)pW-3’ sequence motif, with additional substitutions also reported. This hypermutation signature and high mRNA expression of APOBEC3A and APOBEC3B have been associated with several cancer types. Most previous studies of APOBEC signatures have examined tumor sequence data from clinical samples, for which limited or no information about drug response was available. We investigated the presence of the mutational signature and mRNA expression patterns of the APOBEC3A and APOBEC3B genes in extensively characterized cell lines, in order to identify those cell lines that carry mutations generated by kataegis, with the aim of establishing associations between the APOBEC mutational signature, individual cancer types, and the patterns of sensitivity to antitumor agents. For this purpose, we analyzed whole exome sequencing (WES) data and mRNA expression of the APOBEC3A and APOBEC3B genes in two resources with extensive drug response data: the NCI-60 cell line panel, which includes 59 human cancer cell lines representing 9 cancer types and drug response information for thousands of anticancer agents, and the Cancer Cell Line Encyclopedia (CCLE), which provides WES, whole genome, and RNA-seq sequence information on hundreds of cancer cell lines and drug response data to over 200 agents. We analyzed WES data of 325 CCLE cell lines and 59 NCI-60 cell lines, with variants identified using GATK pipeline and Varscan2 software. The variants in each cell line were filtered to remove common polymorphisms in dbSNP and 1000 Genome Project databases. We searched the discovered variants for the presence of APOBEC signatures, 5’-Tp(C->AGT)pN-3’, 5’-Tp(C->AGT)pD-3’, and 5’-Tp(C->AGT)pW-3’ in closely spaced (1000 and 10,000 bp) windows that appeared on the same DNA strand. We will discuss the use of optimal filters for detecting APOBEC mutational signatures and will present the analyses of associations between APOBEC signatures, mutational load of the tumor cell lines, APOBEC gene expression, and chemosensitivity to treatment. These results contribute to additional characterization of available cell lines by providing information about specific mutational signatures in different categories of cancer. Our findings may assist with identifying antitumor agents that would be appropriate for treatment of cancer cells with specific signature patterns generated by APOBEC mutagenesis. Citation Format: Suleyman Vural, Julia Krushkal, Richard Simon. Analysis of APOBEC3A and APOBEC3B mutational signatures using next-generation sequencing data from cancer cell lines [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 2590. doi:10.1158/1538-7445.AM2017-2590

Cancer cells have profound alterations in glycosylation processes, which affects the functioning of malignant cells and their interaction with surrounding environment. We examined the effects of treatment of cancer cell lines with eleven antitumor agents (bortezomib, cisplatin, dasatinib, doxorubicin, erlotinib, gemcitabine, paclitaxel, sirolimus, sorafenib, sunitinib, and topotecan) on transcriptional changes in 179 candidate genes involved in biochemical glycosylation pathways or encoding glycosylation targets, regulators of glycosylation processes, and components of cancer pathways affected by glycosylation. In order to achieve this goal, we analyzed time course gene expression information for the NCI-60 cancer cell line panel using the data from the NCI Transcriptional Pharmacodynamic Workbench (NCI TPW), a resource developed at the National Cancer Institute. Our analysis identified 145 glycosylation related genes that responded to drug treatment in a concerted manner. Many of these genes had a concerted response to multiple agents; however, the direction and the magnitude of concerted response were specific to individual drugs. Expression of multiple genes prior to treatment and/or transcriptional changes in response to treatment were significantly correlated with drug chemosensitivity, measured as log(GI50). Treatment with dasatinib resulted in the largest number of significant correlations of chemosensitivity with gene expression prior to treatment and with gene expression changes in response to treatment. Significant correlations of transcriptional changes after treatment and/or of pre-treatment gene expression levels of glycosylation related genes and glycosylation targets were also observed for other antitumor agents. Chemosensitivity to kinase inhibitors and DNA damaging agents was significantly correlated with expression of genes involved in N- and O-glycosylation, fucosylation, biosynthesis of poly-N-acetyllactosamine, removal of misfolded proteins, binding to hyaluronic acid and other glycans, and cell adhesion. In particular, tumor cell sensitivity or resistance to multiple agents were significantly correlated with changes in expression of C1GALT1C1 (COSMC), FUCA1, SDC1, MUC1, members of the MGAT, GALNT, B4GALT, B3GNT, MAN, and EDEM gene families, and other genes involved in glycosylation processes or encoding glycosylation targets and signaling regulators. We present a catalog of dynamic concerted changes in expression of glycosylation related genes, their ligands, regulators, and targets in response to chemotherapy, and provide a list of genes that influence the strength of response of cancer cells to treatment. These glycosylation related genes may be considered as potential candidates for drug targeting in combination therapy to enhance the effects of treatment. Funded by NCI Contract No. HHSN261200800001E. Citation Format: Julia Krushkal, Yingdong Zhao, Curtis Hose, Anne Monks, James H. Doroshow, Richard Simon. Longitudinal expression response of glycosylation related genes, regulators, and targets in cancer cell lines treated with eleven anti-tumor agents [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 1557. doi:10.1158/1538-7445.AM2017-1557