Search

Previously Reported HPV-Human PPIs. Related to Figures 1 and 2.

Supplementary Data from A Whole-Genome CRISPR Screen Identifies AHR Loss as a Mechanism of Resistance to a PARP7 Inhibitor

This combined Supplementary Document contains Supplementary Notes, Methods and References, Legends to Supplementary Tables S1-S6, and Supplementary Figures S1-S5.

Cancer drugs targeting the identified virus-host protein-protein interactions of SARS-CoV-2

Supplementary Table S2. Drugs and their concentrations used in the isogenic drug screen.

MiST Scores for all HPV-Human PPIs. Related to Figures 1 and 2.

Supplementary Table S3. Chemical-genetic interaction scores derived in this study

Differentially Mutated Genes in HPV(-) vs. HPV(+) Samples. Related to Figure 3.

Supplementary Figure 1. Distribution of gene alterations in Breast TCGA and verification of expression of MCF10A cells. Supplementary Figure 2. Analysis of the MCF10A drug screen. Supplementary Figure 3. Significance of overlap between interactions found in this study and in the CGP. Supplementary Figure 4. Response of isogenic engineered cells to dasatinib. Supplementary Figure 5. Dasatinib sensitivity of CML versus AML cancer cell lines. Supplementary Figure 6. Verification of LYN knockdown via siRNA and response of LYN T319I to dasatinib. Supplementary Figure 7. Co-­�expression of MYC and LYN in breast cancer cell lines.

Inhibitors directed toward PARP1 and PARP2 are approved agents for the treatment of BRCA1 and BRCA2-related cancers. Other members of the PARP family have also been implicated in cancer and are being assessed as therapeutic targets in cancer and other diseases. Recently, an inhibitor of PARP7 (RBN-2397) has reached early-stage human clinical trials. Here, we performed a genome-wide CRISPR screen for genes that modify the response of cells to RBN-2397. We identify the polycyclic aromatic hydrocarbon receptor AHR and multiple components of the cohesin complex as determinants of resistance to this agent. Activators and inhibitors of AHR modulate the cellular response to PARP7 inhibition, suggesting potential combination therapy approaches.

Supplementary Table from A Whole-Genome CRISPR Screen Identifies AHR Loss as a Mechanism of Resistance to a PARP7 Inhibitor

Gene Ontology Terms. Related to Figure 1.

Summary:The mapping of SARS-CoV-2 human protein–protein interactions by Gordon and colleagues revealed druggable targets that are hijacked by the virus. Here, we highlight several oncogenic pathways identified at the host–virus interface of SARS-CoV-2 to enable cancer biologists to apply their knowledge for rapid drug repurposing to treat COVID-19, and help inform the response to potential long-term complications of the disease.

Differentially Expressed Genes upon L2 Overexpression. Related to Figure 5.

Supplementary Table S1. List of constructs used to generate stable cell lines.

Supplementary Data from Resistance to ATR Inhibitors Is Mediated by Loss of the Nonsense-Mediated Decay Factor UPF2

Pan-phospho-RTK profiling identifies HER3 to be hyper-phosphorylated after BYL719 treatment in HPV(+) cell lines

HPV(+) cell lines are less responsive to BKM120 and BEZ235 than HPV(-) cell lines

Over one million cases of gastric cancer are diagnosed each year globally, and the metastatic disease continues to have a poor prognosis. A significant proportion of gastric tumors have defects in the DNA damage response pathway, creating therapeutic opportunities through synthetic lethal approaches. Several small-molecule inhibitors of ATR, a key regulator of the DNA damage response, are now in clinical development as targeted agents for gastric cancer. Here, we performed a large-scale CRISPR interference screen to discover genetic determinants of response and resistance to ATR inhibitors (ATRi) in gastric cancer cells. Among the top hits identified as mediators of ATRi response were UPF2 and other components of the nonsense-mediated decay (NMD) pathway. Loss of UPF2 caused ATRi resistance across multiple gastric cancer cell lines. Global proteomic, phosphoproteomic, and transcriptional profiling experiments revealed that cell-cycle progression and DNA damage responses were altered in UPF2-mutant cells. Further studies demonstrated that UPF2-depleted cells failed to accumulate in G1 following treatment with ATRi. UPF2 loss also reduced transcription–replication collisions, which has previously been associated with ATRi response, thereby suggesting a possible mechanism of resistance. Our results uncover a novel role for NMD factors in modulating response to ATRi in gastric cancer, highlighting a previously unknown mechanism of resistance that may inform the clinical use of these drugs.Significance:Loss of NMD proteins promotes resistance to ATR inhibitors in gastric cancer cells, which may provide a combination of therapeutic targets and biomarkers to improve the clinical utility of these drugs.

Human papillomavirus (HPV) type 16 is implicated in approximately 75% of head and neck squamous cell carcinomas (HNSCC) that arise in the oropharynx, where viral expression of the E6 and E7 oncoproteins promote cellular transformation, tumor growth, and maintenance. An important oncogenic signaling pathway activated by E6 and E7 is the PI3K pathway, a key driver of carcinogenesis. The PI3K pathway is also activated by mutation or amplification of PIK3CA in over half of HPV(+) HNSCC. In this study, we investigated the efficacy of PI3K-targeted therapies in HPV(+) HNSCC preclinical models and report that HPV(+) cell line- and patient-derived xenografts are resistant to PI3K inhibitors due to feedback signaling emanating from E6 and E7. Receptor tyrosine kinase profiling indicated that PI3K inhibition led to elevated expression of the HER3 receptor, which in turn increased the abundance of E6 and E7 to promote PI3K inhibitor resistance. Targeting HER3 with siRNA or the mAb CDX-3379 reduced E6 and E7 abundance and enhanced the efficacy of PI3K-targeted therapies. Together, these findings suggest that cross-talk between HER3 and HPV oncoproteins promotes resistance to PI3K inhibitors and that cotargeting HER3 and PI3K may be an effective therapeutic strategy in HPV(+) tumors.Significance: These findings suggest a new therapeutic combination that may improve outcomes in HPV(+) head and neck cancer patients. Cancer Res; 78(9); 2383–95. ©2018 AACR.

Blockade of the PI3K pathway with BKM120 or BEZ235 increases HER3/AKT signaling

Legend for supplemental figures

Supplementary Figure from Resistance to ATR Inhibitors Is Mediated by Loss of the Nonsense-Mediated Decay Factor UPF2

Clinical characteristics of patients prior to surgery and PDX establishment

HER3 blockade enhances the sensitivity of HPV(+) cell lines to BKM120

KRAS is mutated in 35%-45% of colorectal cancers (CRC), and KRAS mutational status determines the prognosis and therapeutic options available to patients with advanced CRC. Direct KRASG12C inhibitors have proven to be highly effective for patients with non-small cell lung cancers, but unfortunately are relatively ineffective in the treatment of CRC. Thus, we have investigated tissue-specific mechanisms of resistance to direct KRAS inhibition. We used multiplex inhibitor bead kinome profiling (MIBs) and global phosphoproteomic analysis to determine the signaling response to the KRASG12C inhibitor ARS-1620 in four human colon cancer cell lines. Analyzing the kinome revealed a profound reprogramming beyond the Ras/MAPK pathway. We used network propagation to integrate analysis across these lines and define essential signaling nodes modified by direct KRAS inhibition, including two distinct signaling nodes containing RAS/MAPK and WNT-regulating kinases. Two additional smaller nodes contained WNK kinases and their effectors, followed by Hippo and a number of cell cycle-related kinases. The WNK kinases have been identified to modulate beta-catenin, a major driver of CRC biology, via the GID E3 ubiquitin ligase complex. Thus, to understand the signaling that links KRAS and beta-catenin, we used small molecule inhibitors of these kinases along with ARS-1620, we tested how they affected the transcription of beta-catenin targets. Additionally, we assessed the correlation between WNK/GID complex, and beta-catenin transcriptional output using western blot and quantitative real time PCR and observe that inhibition of KRASG12C also modulates beta-catenin transcriptional output. Our results identify new families of possible kinase targets in CRCs expressing KRAS mutations and shed light on the relationship of KRAS, beta-catenin, and WNK/GID in CRC maintenance. By dissecting these signaling relationships, we hope to identify potential drug combinations to overcome primary resistance KRASG12C inhibition in CRC. Citation Format: Kasturi Nayak, Yeonjoo Hwang, LeeAnn Wang, Danielle L. Swaney, Nevan J. Krogan, John D. Gordan. Inhibition of KRASG12C in colon cancer illustrates a link between beta-catenin, WNK, and the GID complex [abstract]. In: Proceedings of the AACR Special Conference on Colorectal Cancer; 2022 Oct 1-4; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_1):Abstract nr B016.

The DNA damage response (DDR) ensures error-free genome replication and transcription, but is often disrupted in cancer. We developed DDRAM, a multilayered map of DDR derived from our own high-throughput physical interaction screen as well as genome, transcriptome, and proteome datasets from published sources. DDRAM organizes 328 genes into 41 hierarchical pathways. We identify 55 (17%) novel DDR genes with functions distributed across various pathways, and novel and more specific roles for 153 (47%) of established DDR genes. We perform epistasis mapping to support novel pathway assignments of FOXK1 in nucleotide metabolism and XRCC3 in the Fanconi anemia pathway. Using quantitative imaging of a fluorescent probe, in some cases confirmed by epistasis mapping, we experimentally validate members of the Short Patch Base Excision Repair pathway over a time course, revealing a more complete model of poly(ADP-ribose)-dependent recruitment to sites of DNA damage. Citation Format: Anton Kratz, Minkyu Kim, Fan Zheng, Christopher A. Koczor, Samson Fong, Jianfeng Li, Robert W. Sobol, Nevan Krogan, Trey Ideker. A multiscale map of DNA damage response in human cells [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 2078.

Cancers have been associated with a diverse array of genomic alterations, many of which are rare with unknown significance. To understand the cellular mechanisms impacted by such alterations in breast invasive carcinoma, we have applied affinity-purification mass spectrometry to delineate comprehensive biophysical interaction networks for 40 frequently altered breast cancer proteins across three human breast cell lines, providing a novel resource of context-specific and shared protein-protein interaction networks in breast cancer cells. These networks interconnect and enrich for common and rare cancer mutations, and are substantially rewired by mutations. Our analysis identifies novel PIK3CA-interacting proteins which repress AKT signaling, and UBE2N emerges as a BRCA1 interactor predictive of clinical response to PARP inhibition. We also show that Spinophilin interacts with and dephosphorylates BRCA1 to promote DNA double-strand break repair. Thus, cancer protein interaction landscapes provide a framework for recognizing oncogenic drivers and drug vulnerabilities. Citation Format: Minkyu Kim, Jisoo Park, Mehdi Bouhaddou, Kyumin Kim, Ajda Rojc, Maya Modak, Margaret Soucheray, Patrick O'Leary, Denise Wolf, Dominique C. Mitchell, Fan Zheng, John D. Gordan, Jean-Philippe Coppé, Danielle L. Swaney, Laura van' t Veer, Alan Ashworth, Trey Ideker, Nevan J. Krogan. The protein interaction landscape of breast cancer [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 2308.

This abstract was not presented at the symposium.

The Cancer Genome Atlas and similar projects have now analyzed over 10,000 tumor genomes, providing a catalog of the gene mutations, copy number variants and other genetic alterations that are present cancer. In many cases though, it remains unclear which are the key driver mutations or dependencies in a given cancer and how these influence pathogenesis and response to therapy. Although tumors of similar types and clinical outcomes can have patterns of mutations that are strikingly different, it is becoming apparent that these mutations recurrently hijack the same hallmark molecular pathways and networks. For this reason, cancer research and treatment is increasingly dependent on knowledge of biological networks of multiple types, including physical interactions among proteins and both synthetic-lethal and epistatic interactions among genes. Founded in 2015 by labs at UC San Diego and UCSF, the mission of the Cancer Cell Map Initiative (CCMI) is to enable a new era of cancer discovery and treatment based on the complete elucidation of the molecular networks underlying cancer. We believe that this information will be critical for developing computational models of cancer cells that will enable both basic research and clinical decision-making. Our initial research efforts are focused on head and neck cancer and breast cancer but we believe that our approach is widely applicable. Here, I will discuss results from three of the CCMI's main research efforts. One major focus is using affinity purification followed by mass spectrometry (AP/MS) to map protein-protein interactions of frequently mutated genes in multiple, relevant cell culture models. These efforts for approximately 40 genes in both head and neck cancer and breast cancer have largely been completed leading to a range of validation and follow-up studies. To complement these context-specific structural maps, a second main research effort is to generate functional maps by measuring genetic interactions using CRISPR/Cas9 in many of the same cell culture models. Many of these screens have now been completed with data analysis ongoing. Along with these two experimental efforts, a third focus has been to use bioinformatics approaches to assemble a hierarchical map of biological subsystems in cancer, to identify which systems in which cohorts are mutated more often than expected by chance and to explore these potentially driver systems in more detail through a range of experimental studies. To share these and other network maps, the CCMI's bioinformatics core has created the network data exchange (NDEx, ndexbio.org), an open-source framework where scientists and organizations can share, store, manipulate and publish biological network knowledge. Citation Format: Jason F. Kreisberg, Fan Zheng, Samson Fong, Brent M. Kuenzi, Kyle Ford, Danielle Swaney, Minkyu Kim, Jisoo Park, Zhiyong Wang, Dexter Pratt, Natalia Jura, Silvio Gutkind, Prashant Mali, Nevan Krogan, Trey Ideker. Using physical, genetic and integrated cancer cell maps to investigate head and neck cancer and breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 223.

Hepatocellular carcinoma (HCC) is the second leading cause of cancer death worldwide. Advanced HCC has proven particularly difficult to treat because of a scarcity of clear genetic drivers of cancer progression; thus, there are currently no predictive markers that guide HCC therapy. HCC arises in the context of co-morbid hepatitis due to hepatitis B virus (HBV), hepatitis C (HCV) or fatty liver disease. We hypothesize that protein-protein interactions (PPIs) between viral proteins and HCC genes may contribute to tumor initiation and maintenance. In order to characterize these PPIs, we performed affinity purification - mass spectrometry (APMS), defining 145 HBV/host PPIs including known and novel interacting partners. We next used a network propagation algorithm to identify host genes and protein complexes that were preferentially mutated in the absence of HBV infection. HBV is a small DNA virus, with 4 genes of which only one has enzymatic activity, raising a question as to how HBV interaction modifies host behavior. Using AP-MS of host proteins, we found that the HBV X protein (HBx) remodels multiple host protein complexes through direct interaction. These physical effects on complex components result in distinct biochemical behavior from the CRL4 E3 ubiquitin ligase complex as well as the phosphatase PP2A, as determined through global phosphoproteomics and ubiquitin analysis. We show that this remodeling driven by HBx substantially changes cellular protein turnover and downstream signaling dynamics. We followed this up with assessments of cellular viability and proliferation in response to pharmacological inhibition or CRISPRi-based knockdown of HBx effectors. Our data support a model where HBV proteins alter the components and behavior of key regulatory protein complexes in the cell, altering tumor behavior and raising the possibility of precision therapeutics for HCC. Citation Format: John D. Gordan, Adriana Pitea, Manon Eckhardt, Gwendolyn Jang, Rigney E. Turnham, Alex L M. Choi, John Von Dollen, Huat C. Lim, Elizabeth F. Thayer, R. Katie Kelley, Danielle L. Swaney, Wei Zhang, Fabian J. Theis, Trey Ideker, Nevan J. Krogan. Hepatitis B virus remodels host protein interaction networks to generate distinct cellular dependencies [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 4891.

Deficiency in one or more subsystems of the DNA damage response and repair system hierarchy is a hallmark of cancer and makes DNA repair an attractive target for physical or chemical therapies. An accurate, complete, yet parsimonious model of the systems and pathways comprising the hierarchy of DNA repair mechanisms can be expected to further our understanding of cancer genesis and progression and to facilitate the development of improved cancer therapies. Previous attempts in building a hierarchical model of DNA repair include methods based on literature curation (Gene Ontology [1]) and expert consensus (2). However, as these models rely on manual curation, rapid integration of novel omics-scale experimental data sets is not practicable. Moreover, Gene Ontology is by its definition only concerned with the modeling of pathways in the healthy cell and does not aim to reflect cancer-specific aspects. To bridge this gap, we here describe the generation of an entirely data-driven model of DNA repair, inferred from a large meta-compendium describing the physical interactions between proteins based on an integration of over 110 experimental data sets from different omics levels (genome, transcriptome, proteome). Augmenting a technique that we developed earlier, Active Interaction Mapping (AIM) (3), we define a hierarchical model of DNA repair consisting of 293 genes organized in 40 systems. Briefly, we integrate the interaction evidence using a random forest regressor to generate a weighted, integrated network; we then transform the network into a consensus matrix and feed this into an algorithm based on previous work (4) to identify the hierarchical structure embedded in the network. The hierarchical model takes the form of a directed acyclic graph (DAG), which allows us to model pleiotropic aspects of molecular systems, as some proteins and systems play functional roles in different ancestor systems. Using a network biology approach, we suggest a list of 293 genes playing central roles in DNA repair and find evidence that genome replication and RNA splicing processes are more intimately connected to DNA repair than previously appreciated. We find novel roles for about one third of the genes in our model, identify novel subsystems of already known systems in DNA repair, and can describe novel interactions between already known DNA repair systems. Finally, we perform perturbations of the DNA repair hierarchy in different cell lines, measure the impact on the protein-protein and genetic interaction networks, and use the identified interactions to search for impacted connections within and between systems of the DNA repair model. References: 1. Ashburner M et al., Nature Genetics 2000;25:25. 2. Pearl LH et al., Nature Reviews Cancer 2015;15:166. 3. Kramer MH et al., Molecular Cell 2017;65:761. 4. Kramer M, Dutkowski J, Yu M, Bafna V, Ideker T. Bioinformatics 2014;30:i34. This abstract is also being presented as Poster B43. Citation Format: Anton Kratz, Fan Zheng, Min Kyu, Nevan Krogan, Trey Ideker. A hierarchical model of DNA repair inferred from omics-scale genetic interaction data reveals the dynamics of DNA damage induction [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PHB03.

Interpreting cancer genomes requires a broad understanding of the composition and organization of cellular processes under selective pressure for mutations. Here, we integrate systematic screens for protein interaction with tumor genetic analysis to elucidate a multiscale hierarchical map of 378 protein systems recurrently altered in one or more cancer types. Diverse gene mutations converge on commonly mutated systems, from small protein complexes in specific tumor types to large molecular assemblies and organelles disrupted in most cancers. Unexpected findings include collagen structural alterations with significant prognostic value; mutations impacting the desmosome in 65% melanomas; complexes related to splicing and DNA repair; and an expanded actomyosin cluster involving PIK3CA. The map implicates 556 cancer genes, many well supported by functional assays, including canonical genes implicated in new tissues (e.g., BRCA1/2 mutations in bladder cancer). This work explains mutational heterogeneity as a collection of convergence points across scales of cell biology. This abstract is also being presented as Poster B52. Citation Format: Fan Zheng, Keiichiro Ono, Erica Silva, Danielle Swaney, Minkyu Kim, Julia Shangguan, Dexter Pratt, Xiaolin Nan, Nevan Krogan, Trey Ideker. A multiscale map of recurrently mutated systems in cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PR14.

A key unanswered question in cancer genetics is how different mutations, dispersed across a multitude of genes, elicit similar pathology and patient outcomes. The answer may lie in understanding the molecular networks and protein complexes (i.e. signaling pathways, chromatin architecture, etc) in cancer and mapping mutated genes into the complexes and pathways in which they function. Determining how systematic interaction networks are wired in cancer cells and how different mutations perturb these networks will guide the search for new cancer genes and provide a platform for integrating patient data to make biological and clinical predictions more accurate. The goal of this study is to uncover the comprehensive protein-protein interaction networks and pathways in various breast cancer subtypes to better understand how mutated cancer genes and genomes hijack and re-wire pathways and complexes during the course of breast tumorigenesis. Here we catalog protein-protein interactions for 40 genes recurrently mutated in breast cancer, using affinity purification and mass spectrometry. To identify co-associated proteins, cDNA clones expressing each protein were tagged with 3xFLAG at either N or C-terminus and introduced into MCF10A (non-tumorigenic “healthy” control), MCF7 (luminal A subtype), and MDA-MB-231 (claudin-low) cells using doxycycline-inducible lentiviral vectors. For proteins with prevalent pathogenic mutations (e.g. PIK3CA-H1047R, BRCA1-C61G), mutant cDNA clones were also analyzed in parallel. Our interaction network reveals subtype and mutation-specific protein-protein interactions, many of which are not previously reported. Given that genes encoding components of a protein complex or a biological pathway often share similar phenotype upon genetic perturbation, we genetically knocked out genes interacting with DNA damage response (DDR) proteins using CRISPR/Cas9, and found multiple novel interacting genes whose knockout results in significant PARPi (olaparib) and/or cisplatin sensitivity. This result not only functionally validates the physical protein interactions, but also demonstrates that our interactome mapping approach can helps identify newdruggable vulnerabilities in cancer cells. We anticipate the breast cancer interactome study will uncover aberrant pathways and protein complexes uniquely operating in breast cancer cells, and thus pinpoint proteins that may potentially serve as distinct biomarkers or therapeutic targets for tumors having the same or similar subtypes and/or genomic mutations. Citation Format: Kim M, Kim K, Tutuncuoglu B, Soucheray M, Swaney D, Zheng F, Park J, O'Leary P, Coppé J-P, van 't Veer L, Ashworth A, Ideker T, Krogan N. Analyzing the physical and functional protein interaction landscape of breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P6-06-01.

Recent progress in genome sequencing has revealed numerous mutations in cancer genomes, but how many of these alterations result in changes in normal cellular processes is poorly understood. In addition, the biologic functions of the majority of genes (e.g., BRCA1/2) with cancer-associated mutations have not been fully characterized, despite their expression and/or activity being highly correlated with cancer. Through years of study, it is becoming clear that cancer is a disease that arises not only because of defects in individual genes and proteins, but also because of the action of hallmark cellular processes and biologic pathways. Therefore, what is urgently needed is to put the cancer genomic information into biologic context by mapping mutated genes onto the complexes and pathways in which they function. The goal of this study is to uncover the comprehensive protein-protein interaction networks and pathways in various breast cancer subtypes to better understand how mutated cancer genes and genomes hijack and rewire pathways and complexes during the course of breast tumorigenesis. Here we catalog protein-protein interactions for more than 40 genes recurrently mutated in breast cancer, using affinity purification and mass spectrometry (AP-MS). Our interaction network reveals subtype and mutation-specific protein-protein interactions, most of which are not previously reported. We anticipate the breast cancer interactome study will uncover many previously unidentified aberrant pathways and protein complexes uniquely operating in breast cancer cells, and thus pinpoint proteins central in these pathways and complexes that may potentially serve as distinct biomarkers or therapeutic targets for tumors having the same or similar subtypes and/or genomic mutations. Citation Format: Minkyu Kim, Kyumin Kim, Margaret Soucheray, Danielle Swaney, Nevan Krogan. Studying the interactome of breast cancer: The cancer cell map initiative [abstract]. In: Proceedings of the AACR Special Conference: Advances in Breast Cancer Research; 2017 Oct 7-10; Hollywood, CA. Philadelphia (PA): AACR; Mol Cancer Res 2018;16(8_Suppl):Abstract nr B45.

Cancer is governed by modular systems of genes, the composition and organization of which remains poorly understood. Here, we integrate physical and functional networks from a wide range of molecular studies to assemble a comprehensive multi-scale map of human cancer cell biology. This map consists of a hierarchical catalog of protein complexes, signaling pathways and inter-pathway crosstalk implicated in cancer, and it suggests many uncharacterized functional modules as intriguing hypotheses for further validation. Analysis of the pattern of somatic mutations in The Cancer Genome Atlas (TCGA) reveals that these mutations target systems of varying scales above the level of individual genes. The map also provides a platform to integrate and interpret new 'omics data; we integrate new protein-protein interactions identified using AP-MS in multiple breast cancer cell lines, revealing how different functional modules are rewired in cancer cells. A general model browsing tool has been created to visualize and navigate these hierarchical cancer maps. This multi-scale mapping approach elucidates the molecular heterogeneity of cancer, connects tumor genotypes to phenotypes and, ultimately, enables a platform for cancer precision medicine. Citation Format: Fan Zheng, Michael K. Yu, Minkyu Kim, Keiichiro Ono, Mitchell Flagg, Jason F. Kreisberg, Nevan Krogan, Trey Ideker. Multi-scale mapping of the physical and functional architecture of the cancer cell [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 1317.

In cancer, epigenetic modifications are strongly altered and are responsible for gene expression aberrations. In a drug screening initiative, we recently reported that proscillaridin, a cardiac glycoside (CG), exhibits unsuspected epigenetic and anticancer activities. To understand CG's epigenetic mechanisms of action, we performed RNA sequencing analysis, which showed proscillaridin effects on global gene expressions in acute lymphoblastic leukemia cells (MOLT-4). Genes associated with apoptosis and cell differentiation were upregulated whereas master transcription factors and oncogenic pathway genes were downregulated. Mechanistic studies revealed that proscillaridin decreased histone 3 acetylation, which correlated with histone acetyltransferase (KATs) downregulation (CBP, P300, TIP60, GCN5 and MOZ). Acetylome studies by mass spectrometry showed an acetylation loss in chromatin regulators, the oncogene C-MYC and its associated proteins. Proscillaridin induced C-MYC transcript and protein degradation. Moreover, in a panel of cancer cell lines, we measured that cancer cells sensitivity to proscillaridin treatment was positively correlated with C-MYC protein levels. Conversely, proscillaridin did not affect C-MYC protein level in low C-MYC expressing cancer cell lines. For the first time, we showed that CGs target histone acetyltransferases and C-MYC oncogene in high C-MYC expressing cancers. We propose that CGs can be repurposed as new epigenetic drugs in high C-MYC expressing cancers. Citation Format: Elodie M. Da Costa, Gregory Armaos, Annie Beaudry, Chantal Richer, Maxime Caron, Pascal St-Onge, Jeffrey Johnson, Nevan Krogan, Yuka Sai, Michael Downey, Daniel Sinnett, Serge McGraw, Noël J. Raynal. Targeting histone acetyltransferases to reprogram high C-MYC expressing cancers [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 1381.

Characterization of the genomic landscapes of cancer patients has provided valuable insights into the key oncogenic drivers and revolutionized the concept of precision treatment of patients. However, a key limitation is that targetable alterations are only found in a small fraction of patients. This is due to the fact that the majority of cancer drugs are developed against specific oncogenes. However, oncogenes do not act in isolation but rather function as a part of complex protein interactions that can alter oncogene activity and dependence. We hypothesize that a systems approach to read the cellular activity of oncogenic proteins by mapping interaction network states of cancer cells can aid in patient stratification for targeted therapy. To identify interaction networks centered on the major class of cancer drug targets, we experimentally mapped protein-protein interaction (PPI) networks of all 90 human tyrosine kinases (TK) using proteomics approach of affinity purification and mass spectrometry. This analysis identified 1,458 high confidence interactors of TK in HEK293 cells. Detailed analyses of this interactome revealed the diverse cellular localizations and novel associations of TK with multiple protein complexes, suggesting a broader functional role in cellular signaling than previously appreciated. To map the cellular activity of TK in cancer patients, we developed a novel computational approach to integrate PPI networks with genomic data from cancer patients profiled in TCGA. Application to lung adenocarcinoma samples identified that activity of EGFR interactors could be used to define an EGFR network state that was highly predictive of the presence of EGFR mutation. Intriguingly, our analysis identified that 23% of EGFR wild-type samples were positive for the EGFR network state, suggesting a role for EGFR in lung cancer beyond EGFR mutant cases. Furthermore, this state was highly predictive of erlotinib sensitivity in EGFR wild-type lung PDX and cell lines. We identified that many KRAS and NF1 mutant NSCLC samples were EGFR network state positive and displayed evidence of EGFR activation identified by RPPA. These results indicate that a network state approach can precisely expand the pool of patients that may benefit from EGFR TK inhibitors (TKi). Finally, we tested whether components of TK networks were critical for their function by performing synthetic lethal RNAi screens in cell lines with mutation in key TK and identified many kinase interactors as drug sensitizers. Our results indicate that integration of high-throughput genomic datasets with the PPI networks provides an effective tool to understand complex oncogenic network states of cancer cells and provides a high-resolution readout of tumor cell dependence. This work provides the most complete interaction map for TK to date and is a valuable resource to probe mechanisms of oncogene addiction to improve the utility of TKi in cancer. Citation Format: Swati Kaushik, Gwendolyn Jang, Hsien-Ming Hu, Khyati Shah, Xin Zhao, John Jascur, John Von Dollen, Erik Verschueren, Jeffrey Johnson, Nevan Krogan, Sourav Bandyopadhyay. A tyrosine kinase interactome reveals network states that guide the use of targeted therapies in 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 3297.

Human papillomavirus (HPV) 16 plays an etiologic role in a growing subset of head and neck squamous cell carcinoma (HNSCC), where viral expression of the E6 and E7 oncoproteins is necessary for tumor growth and maintenance. Although patients with HPV(+) tumors have a more favorable prognosis, there are currently no HPV-selective therapies. Accumulating evidence indicates that HPV oncoproteins can activate the Phosphoinositol-3-Kinase (PI3K) pathway, which contributes to transformation. Furthermore, PI3K is genomically activated by PIK3CA mutation or amplification in a disproportionately high number of HPV(+) tumors as compared to HPV(-) tumors. Based on this knowledge, we investigated the efficacy of PI3K-targeted therapies in preclinical models of HPV(+) HNSCC. Our results indicate that HPV(+) preclinical models were less sensitive to the PI3K inhibitors BYL719, BKM120, and BEZ235 as compared with HPV(-) models. Sensitivity of HPV(+) cell lines to PI3K inhibitors was increased upon knockdown of the E6 and E7 oncoproteins. Reciprocally, overexpression of E6 and E7 in HPV(-) cells rendered them resistant to PI3K-targeted therapies. Proteomic analyses indicated that treatment of HPV(+) cell lines and patient-derived xenografts (PDXs) with the PI3Kα inhibitor BYL719 induced expression of the receptor tyrosine kinase HER3, as well as E6 and E7. HER3 was found to regulate the abundance of E6 and E7 in the HPV(+) models. Targeting HER3 with siRNAs or the monoclonal antibody, KTN3379, blocked the increase in E6 and E7 protein levels following BYL719 treatment, and enhanced the efficacy of PI3K inhibitors in HPV(+) cell line and PDX models. Taken together, these results suggest that crosstalk between HER3 and HPV16-E6E7 can limit the efficacy of PI3K inhibitors, and that co-targeting HER3 and PI3K may be an effective therapeutic strategy in HPV(+) tumors. This abstract is also being presented as Poster 67. Citation Format: Toni M. Brand, Stefan Hartmann, Neil E. Bhola, Hua Li, Yan Zeng, Rachel O'Keefe, Max V. Ranall, Sourav Bandyopadhyay, Margaret Soucheray, Danielle L. Swaney, Nevan Krogan, Carolyn Kemp, Umamaheswar Duvvuri, Daniel E. Johnson, Michelle A. Ozbun, Julie E. Bauman, Jennifer R. Grandis. HER3 crosstalk with HPV16-E6E7 is a feedback resistance mechanism to PI3K-targeted therapies in head and neck cancer [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Optimizing Survival and Quality of Life through Basic, Clinical, and Translational Research; April 23-25, 2017; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(23_Suppl):Abstract nr PR04.

Background: Collaborative team science provides a starting point for comprehensive change, and advocates have a unique and important role developing and engaging in transdisciplinary collaboratives that focus on new questions and new possibilities to advance the science of ethnic and medically underserved health care disparities. Participating in four areas : 1) research and programmatic support, 2) education and outreach, 3) policy and strategy, and 4) representation and advisory, the UCSF Breast Science Advocacy Core (BSAC) Program, a volunteer affiliate of the Breast Oncology Program (BOP), one of ten multidisciplinary research programs under the umbrella of the UCSF Helen Diller Comprehensive Cancer Center promotes a transformative, transdisciplinary, integrated environment to study the biological basis of the diseases that comprise breast cancer; to define the risk of developing or progressing with specific types of breast cancer; to develop novel interventions that work locally and globally to reduce morbidity and mortality from breast cancer and its treatment; and to leverage new collaborative research, education, and mentoring/training opportunities that address cancer outcome disparities. Advocates involved in KOMEN, DOD, PCORI, AND CBCRP funded research and training grants apply four core principles that forge synergy with NCI Advocacy Research Working Group Recommendations: 1)strategic innovation, 2)collaborative execution, 3)evidence based decision-making, and 4) ethical codes of conduct. Embracing transdisciplinary professionalism, researchers and advocates build on their track record as shared value partners committed to furthering the collective impact of science advocacy exchange (SAE). Study Objectives: Genomic analyses of patient tumors have unearthed an overwhelming number of recurrent somatic alterations in genes that have dramatic effects on tumor biology, patient drug responses, and clinical outcomes. In one study, high grade triple negative breast cancer (TNBC) accounts for 34% of breast cancers in African American women versus 21% in white women. A growing body of evidence has shown that African American women have biologically more aggressive disease, independent of social determinants, and suffer the highest mortality rates. While biological breakthroughs of the last decade have greatly advanced our understanding of cancer, in advanced TNBC, a poor prognosis subtype, there is an urgent need to translate this evolving patient genomic data into new therapeutic paradigms. Our study focuses on the intersection of synthetic lethal approaches, MYC driven human cancers, and immunotherapy as an “innovation agenda”. A distinct MYC vision highlights how overexpression is associated with aggressive outcomes and poor patient outcomes, and synthetic lethal strategies to target MYC (CDK inhibitors, PIM2, as well as the PDI immune pathways) have potential for addressing outcome disparities In African American Women with Triple Negative Breast Cancer (TNBC). Key Findings: We have developed a screening technique that can be used to rapidly and accurately identify potential synthetic lethal interactions in TNBC. This platform utilizes an isogenic cell line system that we have developed to model oncogene activation in TNBC. A growing body of evidence has shown that: 1) Quantitative approach maps genotype-specific drug responses in isogenic cells 2) Systematic discovery of biomarkers for cancer drugs under clinical investigation 3) Clinically actionable synthetic lethal interaction between MYC and dasatinib is discovered 4) Mechanism of dasatinib action through inhibition of LYN kinase is described Key Take-Away Message: The inclusion of advocates in convergent science settings remind academic stakeholders that research is there to benefit the patient as they attempt to spark innovation, democratize science, and support smarter interventions that expedite the incredible potential of future investments in bioscience within disparities arenas. Citation Format: Susan Samson, Alicia Y. Zhou, Maria Martins, Alexandra Corella, Dai Horiuchi, Christina Yau, Taha Rakshandehroo, John Gordan, Rebecca Levin, Jeff Johnson, John Jascur, Mike Shales, Antonio Sorrentino, Jaime Cheah, Paul Clemens, Alykhan Shamji, Stuart Schreiber, Nevan Krogan, Kevan Shokat, Frank McCormick, Sourav Bandyopadhyay, Andrei Goga. Genomics, advocacy, and emerging therapeutics to address triple-negative breast cancer (TNBC) outcome disparities. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr C88.

There is an urgent need in oncology to link molecular aberrations in tumors with altered cellular behaviors, such as metabolic derangements, and to identify novel therapeutics for cancer treatment. We have sought to identify synthetic-lethal genetic interactions that cancer cells acquire in the presence of specific mutations. Using engineered isogenic cells, we generated an unbiased and quantitative chemical-genetic interaction map that measures the influence of 51 aberrant cancer genes on 90 drug responses. The dataset strongly predicts drug responses found in cancer cell line collections, indicating that isogenic cells can model more complex cellular contexts. Applied to triple-negative breast cancer, we report clinically actionable interactions with the MYC oncogene including resistance to PI3K/AKT pathway inhibitors and an unexpected sensitivity to dasatinib through LYN inhibition in a synthetic-lethal manner. These studies provide new drug and biomarker pairs for clinical investigation. We have also performed global metabolomics analysis in a subset of the isogenic cell lines demonstrating alterations in metabolic pathways that are shared across multiple oncogenes, as well as those that are distinct to specific oncogenic drivers. This scalable approach enables the prediction of drug responses from patient data and can be used to accelerate the development of new genotype-directed therapies. This abstract is also presented as a poster at the Translation of the Cancer Genome conference. Citation Format: Maria M. Martins, Alicia Y. Zhou, Alexandra Corella, Dai Horiuchi, Christina Yau, Taha Rakshandehroo, John D. Gordan, Rebecca S. Levin, Jeff Johnson, John Jascur, Mike Shales, Antonio Sorrentino, Jaime Cheah, Paul A. Clemons, Alykhan Shamji, Stuart Schreiber, Stuart Schreiber, Nevan J. Krogan, Kevan M. Shokat, Kevan M. Shokat, Frank McCormick, Daniel Nomura, Sourav Bandyopadhyay, Andrei Goga. Functional analysis of diverse oncogenic driver mutations using an isogenic cell line library identifies novel drug responses and alterations in metabolism. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr PR07.

There is an urgent need in oncology to link molecular aberrations in tumors with altered cellular behaviors, such as metabolic derangements, and to identify novel therapeutics for cancer treatment. We have sought to identify synthetic-lethal genetic interactions that cancer cells acquire in the presence of specific mutations. Using engineered isogenic cells, we generated an unbiased and quantitative chemical-genetic interaction map that measures the influence of 51 aberrant cancer genes on 90 drug responses. The dataset strongly predicts drug responses found in cancer cell line collections, indicating that isogenic cells can model more complex cellular contexts. Applied to triple-negative breast cancer, we report clinically actionable interactions with the MYC oncogene including resistance to PI3K/AKT pathway inhibitors and an unexpected sensitivity to dasatinib through LYN inhibition in a synthetic-lethal manner. These studies provide new drug and biomarker pairs for clinical investigation. We have also performed global metabolomics analysis in a subset of the isogenic cell lines demonstrating alterations in metabolic pathways that are shared across multiple oncogenes, as well as those that are distinct to specific oncogenic drivers. This scalable approach enables the prediction of drug responses from patient data and can be used to accelerate the development of new genotype-directed therapies. Citation Format: Maria M. Martins, Alicia Y. Zhou, Alexandra Corella, Dai Horiuchi, Christina Yau, Taha Rakshandehroo, John D. Gordan, Rebecca S. Levin, Jeff Johnson, John Jascur, Mike Shales, Antonio Sorrentino, Jaime Cheah, Paul A. Clemons, Alykhan Shamji, Stuart Schreiber, Stuart Schreiber, Nevan J. Krogan, Kevan M. Shokat, Kevan M. Shokat, Frank McCormick, Daniel Nomura, Sourav Bandyopadhyay, Andrei Goga. Functional analysis of diverse oncogenic driver mutations using an isogenic cell line library identifies novel drug responses and alterations in metabolism. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr PR15.

There is an urgent need in oncology to link molecular aberrations in tumors with therapeutics that can be administered in a personalized fashion. One approach identifies synthetic-lethal genetic interactions or emergent dependencies that cancer cells acquire in the presence of specific mutations. Using engineered isogenic cells, we generated an unbiased and quantitative chemical-genetic interaction map that measures the influence of 51 aberrant cancer genes on 90 drug responses. The dataset strongly predicts drug responses found in cancer cell line collections, indicating that isogenic cells can model more complex cellular contexts. Applied to triple-negative breast cancer, we report clinically actionable interactions with the MYC oncogene including resistance to AKT/PI3K pathway inhibitors and an unexpected sensitivity to dasatinib through LYN inhibition in a synthetic-lethal manner, providing new drug and biomarker pairs for clinical investigation. This scalable approach enables the prediction of drug responses from patient data and can be used to accelerate the development of new genotype-directed therapies. Citation Format: Alicia Y. Zhou, Maria M. Martins, Alexandra Corella, Dai Horiuchi, Christina Yau, Taha Rakshandehroo, John D. Gordan, Rebecca S. Levin, Jeff Johnson, John Jascur, Mike Shales, Antonio Sorrentino, Jaime Cheah, Paul A. Clemons, Alykhan Shamji, Stuart L. Schreiber, Nevan J. Krogan, Kevan M. Shokat, Frank McCormick, Andrei Goga, Sourav Bandyopadhyay. Identification of novel drug interactions with MYC via a quantitative chemical-genetic interaction map. [abstract]. In: Proceedings of the AACR Special Conference on Myc: From Biology to Therapy; Jan 7-10, 2015; La Jolla, CA. Philadelphia (PA): AACR; Mol Cancer Res 2015;13(10 Suppl):Abstract nr B48.

Background: Genomic analyses of patient tumors have unearthed an overwhelming number of recurrent somatic alterations in genes that have dramatic effects on tumor biology, patient drug responses, and clinical outcomes. In one study, high-grade triple negative breast cancer (TNBC) accounts for 34% of breast cancers in African American women versus 21% in white women. African American women have biologically more aggressive disease, independent of social determinants, and suffer the highest mortality rates. In advanced TNBC, a poor prognosis subtype, there is an urgent need to translate this emerging patient genomic data into new therapeutic paradigms. Objectives: Our study focuses on emerging compounds that are already approved (i.e., Dasatinib) or in testing for human use and we expect that this work will serve as a prelude to one or more clinical trials in TNBC. We seek to determine if the treatment of metastatic TNBC recurrence with more targeted genotype-specific agents could improve the outcomes/survival of all women in this particularly aggressive poor prognosis subset, including African American women. Methods: To guide the development of genotype-specific therapies in TNBC, we have established an isogenic cell-line drug screen that measures the impact of gene activation on a panel of emerging, clinically relevant compounds targeting a variety of cancer pathways. Using engineered isogenic cells, we generated an unbiased and quantitative chemical-genetic interaction map that measures the influence of 51 aberrant cancer genes on 90 drug responses. We believe that this approach can identify core synthetic lethal interactions, which underlie drug sensitivity and can be used as a foundation to identify patient populations that will selectively respond to drug treatments. Results: Using our systems approach, our interaction map highlights both known and novel connections between oncogene activation and drug responses and provides a modular roadmap for the exploration of synthetic lethal relationships. Applied to triple-negative breast cancer, we report clinically actionable interactions with the MYC oncogene including resistance to AKT/PI3K pathway inhibitors and an unexpected sensitivity to dasatinib through LYN inhibition in a synthetic-lethal manner. Ensuring that the voice of the patient is represented in our scientific inquiry, advocacy has played a significant role in the development and realization of this project. Aligning experiential and professionalized expertise, trained advocates explore relentless challenges and opportunities for moving the science forward. Conclusion: A novel systems biology approach that uses module maps of oncogenes and emerging therapeutics can define synthetic-lethal interactions and actionable therapeutics to help decrease TNBC outcomes/survival disparities in African American women. Citation Format: Alicia Y. Zhou, Maria M. Martins, Alexandra Corella, Dai Horiuchi, Christina Yau, Taha Rakshandehroo, John D. Gordan, Rebecca S. Levin, Jeff Johnson, John Jascur, Mike Shales, Antonio Sorrentino, Jaime Cheah, Paul A. Clemons, Alykhan Shamji, Stuart Schreiber, Nevan J. Krogan, Kevan M. Shokat, Frank McCormick, Susan Samson, Andrei Goga, Sourav Bandyopadhyay. A systems approach combining genomics, advocacy, and emerging novel therapeutics to address triple-negative breast cancer (TNBC) outcomes disparities. [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr B44.

The DNA mismatch repair (MMR) system is responsible for correcting base substitution and insertion-deletion mutations (IDLs) generated during erroneous replication in bacteria, yeast and mammals. MMR complexes also recognize damaged-base mispairs resulting from environmental exposure to DNA damaging agents. The loss of MMR causes a “mutator” phenotype, resulting in the genome-wide accumulation of mutations, and is the underlying cause for Hereditary Non-polyposis Colorectal Cancer / Lynch Syndrome (HNPCC/LS) and a significant proportion of sporadic colorectal cancer (CRC). MMR-deficient tumors also display resistance to DNA damaging agents and, as a consequence, are resistant to a variety of commonly chemotherapeutic agents. Thus, the development of novel therapeutic strategies that more efficiently target MMR-deficient cancer cells would be highly desirable. A promising new direction to identify potential targets for anticancer treatment is the harnessing of synthetic lethality. Here, we have identified conserved synthetic lethal / sick genetic interactions (GIs) for MMR factors between two distant yeast species, S. pombe and S. cerevisiae. We have confirmed several of these negative GIs in mammalian cells, indicating that they are evolutionarily conserved. Specifically, we have identified a negative genetic relationship between Msh2, a major MMR component mutated in colorectal cancer, and Senp6 protease, which regulates the SUMOylation of a range of genome maintenance proteins. Our findings suggest that Senp6 is a promising new target for the treatment of MMR-deficient CRCs. Citation Format: Elena Tosti, Joseph A. Katakowski, Sonja Schaetzlein, Hyun-Soo Kim, Colm J. Ryan, Michael Shales, Assen Roguev, Nevan J. Krogan, Deborah Palliser, Michael-Christopher Keogh, Winfried Edelmann. Identification of evolutionarily conserved genetic interactions in DNA mismatch repair. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Synthetic Lethal Approaches to Cancer Vulnerabilities; May 17-20, 2013; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(5 Suppl):Abstract nr A13.