Pancreatic Cancer Action Network's SPARK: A Cloud-Based Patient Health Data and Analytics Platform for Pancreatic Cancer.

PURPOSE: Pancreatic cancer currently holds the position of third deadliest cancer in the United States and the 5-year survival rate is among the lowest for major cancers at just 12%. Thus, continued research efforts to better understand the clinical and molecular underpinnings of pancreatic cancer are critical to developing both early detection methodologies as well as improved therapeutic options. This study introduces Pancreatic Cancer Action Network's (PanCAN's) SPARK, a cloud-based data and analytics platform that integrates patient health data from the PanCAN's research initiatives and aims to accelerate pancreatic cancer research by making real-world patient health data and analysis tools easier to access and use. MATERIALS AND METHODS: The SPARK platform integrates clinical, molecular, multiomic, imaging, and patient-reported data generated from PanCAN's research initiatives. The platform is built on a cloud-based infrastructure powered by Velsera. Cohort exploration and browser capabilities are built using Velsera ARIA, a specialized product for leveraging clinicogenomic data to build cohorts, query variant information, and drive downstream association analyses. Data science and analytic capabilities are also built into the platform allowing researchers to perform simple to complex analysis. RESULTS: Version 1 of the SPARK platform was released to pilot users, who represented diverse end users, including molecular biologists, clinicians, and bioinformaticians. Included in the pilot release of SPARK are deidentified clinical (including treatment and outcomes data), molecular, multiomic, and whole-slide pathology images for over 600 patients enrolled in PanCAN's Know Your Tumor molecular profiling service. CONCLUSION: The pilot release of the SPARK platform introduces qualified researchers to PanCAN real-world patient health data and analytical resources in a centralized location.

Longitudinal multi-omics study of palbociclib resistance in HR-positive/HER2-negative metastatic breast cancer.

BACKGROUND: Cyclin-dependent kinase 4/6 inhibitor (CDK4/6) therapy plus endocrine therapy (ET) is an effective treatment for patients with hormone receptor-positive/human epidermal receptor 2-negative metastatic breast cancer (HR+/HER2- MBC); however, resistance is common and poorly understood. A comprehensive genomic and transcriptomic analysis of pretreatment and post-treatment tumors from patients receiving palbociclib plus ET was performed to delineate molecular mechanisms of drug resistance. METHODS: Tissue was collected from 89 patients with HR+/HER2- MBC, including those with recurrent and/or metastatic disease, receiving palbociclib plus an aromatase inhibitor or fulvestrant at Samsung Medical Center and Seoul National University Hospital from 2017 to 2020. Tumor biopsy and blood samples obtained at pretreatment, on-treatment (6 weeks and/or 12 weeks), and post-progression underwent RNA sequencing and whole-exome sequencing. Cox regression analysis was performed to identify the clinical and genomic variables associated with progression-free survival. RESULTS: Novel markers associated with poor prognosis, including genomic scar features caused by homologous repair deficiency (HRD), estrogen response signatures, and four prognostic clusters with distinct molecular features were identified. Tumors with TP53 mutations co-occurring with a unique HRD-high cluster responded poorly to palbociclib plus ET. Comparisons of paired pre- and post-treatment samples revealed that tumors became enriched in APOBEC mutation signatures, and many switched to aggressive molecular subtypes with estrogen-independent characteristics. We identified frequent genomic alterations upon disease progression in RB1, ESR1, PTEN, and KMT2C. CONCLUSIONS: We identified novel molecular features associated with poor prognosis and molecular mechanisms that could be targeted to overcome resistance to CKD4/6 plus ET. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03401359. The trial was posted on 18 January 2018 and registered prospectively.

Comparative biomarker analysis of PALOMA-2/3 trials for palbociclib.

While cyclin-dependent kinase 4/6 (CDK4/6) inhibitors, including palbociclib, combined with endocrine therapy (ET), are becoming the standard-of-care for hormone receptor-positive/human epidermal growth factor receptor 2‒negative metastatic breast cancer, further mechanistic insights are needed to maximize benefit from the treatment regimen. Herein, we conducted a systematic comparative analysis of gene expression/progression-free survival relationship from two phase 3 trials (PALOMA-2 [first-line] and PALOMA-3 [≥second-line]). In the ET-only arm, there was no inter-therapy line correlation. However, adding palbociclib resulted in concordant biomarkers independent of initial ET responsiveness, with shared sensitivity genes enriched in estrogen response and resistance genes over-represented by mTORC1 signaling and G2/M checkpoint. Biomarker patterns from the combination arm resembled patterns observed in ET in advanced treatment-naive patients, especially patients likely to be endocrine-responsive. Our findings suggest palbociclib may recondition endocrine-resistant tumors to ET, and may guide optimal therapeutic sequencing by partnering CDK4/6 inhibitors with different ETs. Pfizer (NCT01740427; NCT01942135).

Preclinical Evaluation of 89Zr-Df-IAB22M2C PET as an Imaging Biomarker for the Development of the GUCY2C-CD3 Bispecific PF-07062119 as a T Cell Engaging Therapy.

PURPOSE: A sensitive and specific imaging biomarker to monitor immune activation and quantify pharmacodynamic responses would be useful for development of immunomodulating anti-cancer agents. PF-07062119 is a T cell engaging bispecific antibody that binds to CD3 and guanylyl cyclase C, a protein that is over-expressed by colorectal cancers. Here, we used 89Zr-Df-IAB22M2C (89Zr-Df-Crefmirlimab), a human CD8-specific minibody to monitor CD8+ T cell infiltration into tumors by positron emission tomography. We investigated the ability of 89Zr-Df-IAB22M2C to track anti-tumor activity induced by PF-07062119 in a human CRC adoptive transfer mouse model (with injected activated/expanded human T cells), as well as the correlation of tumor radiotracer uptake with CD8+ immunohistochemical staining. PROCEDURES: NOD SCID gamma mice bearing human CRC LS1034 tumors were treated with four different doses of PF-07062119, or a non-targeted CD3 BsAb control, and imaged with 89Zr-Df-IAB22M2C PET at days 4 and 9. Following PET/CT imaging, mice were euthanized and dissected for ex vivo distribution analysis of 89Zr-Df-IAB22M2C in tissues on days 4 and 9, with additional data collected on day 6 (supplementary). Data were analyzed and reported as standard uptake value and %ID/g for in vivo imaging and ex vivo tissue distribution. In addition, tumor tissues were evaluated by immunohistochemistry for CD8+ T cells. RESULTS: The results demonstrated substantial mean uptake of 89Zr-Df-IAB22M2C (%ID/g) in PF-07062119-treated tumors, with significant increases in comparison to non-targeted BsAb-treated controls, as well as PF-07062119 dose-dependent responses over time of treatment. A moderate correlation was observed between tumor tissue radioactivity uptake and CD8+ cell density, demonstrating the value of the imaging agent for non-invasive assessment of intra-tumoral CD8+ T cells and the mechanism of action for PF-07062119. CONCLUSION: Immune-imaging technologies for quantitative cellular measures would be a valuable biomarker in immunotherapeutic clinical development. We demonstrated a qualification of 89Zr-IAB22M2C PET to evaluate PD responses (mice) to a novel immunotherapeutic.

Chemotherapy induces dynamic immune responses in breast cancers that impact treatment outcome.

To elucidate the effects of neoadjuvant chemotherapy (NAC), we conduct whole transcriptome profiling coupled with histopathology analyses of a longitudinal breast cancer cohort of 146 patients including 110 pairs of serial tumor biopsies collected before treatment, after the first cycle of treatment and at the time of surgery. Here, we show that cytotoxic chemotherapies induce dynamic changes in the tumor immune microenvironment that vary by subtype and pathologic response. Just one cycle of treatment induces an immune stimulatory microenvironment harboring more tumor infiltrating lymphocytes (TILs) and up-regulation of inflammatory signatures predictive of response to anti-PD1 therapies while residual tumors are immune suppressed at end-of-treatment compared to the baseline. Increases in TILs and CD8+ T cell proportions in response to NAC are independently associated with pathologic complete response. Further, on-treatment immune response is more predictive of treatment outcome than immune features in paired baseline samples although these are strongly correlated.

Comparison of the molecular and cellular phenotypes of common mouse syngeneic models with human tumors.

BACKGROUND: The clinical success of immune checkpoint inhibitors demonstrates that reactivation of the human immune system delivers durable responses for some patients and represents an exciting approach for cancer treatment. An important class of preclinical in vivo models for immuno-oncology is immunocompetent mice bearing mouse syngeneic tumors. To facilitate translation of preclinical studies into human, we characterized the genomic, transcriptomic, and protein expression of a panel of ten commonly used mouse tumor cell lines grown in vitro culture as well as in vivo tumors. RESULTS: Our studies identified a number of genetic and cellular phenotypic differences that distinguish commonly used mouse syngeneic models in our study from human cancers. Only a fraction of the somatic single nucleotide variants (SNVs) in these common mouse cell lines directly match SNVs in human actionable cancer genes. Some models derived from epithelial tumors have a more mesenchymal phenotype with relatively low T-lymphocyte infiltration compared to the corresponding human cancers. CT26, a colon tumor model, had the highest immunogenicity and was the model most responsive to CTLA4 inhibitor treatment, by contrast to the relatively low immunogenicity and response rate to checkpoint inhibitor therapies in human colon cancers. CONCLUSIONS: The relative immunogenicity of these ten syngeneic tumors does not resemble typical human tumors derived from the same tissue of origin. By characterizing the mouse syngeneic models and comparing with their human tumor counterparts, this study contributes to a framework that may help investigators select the model most relevant to study a particular immune-oncology mechanism, and may rationalize some of the challenges associated with translating preclinical findings to clinical studies.

Combining CDK4/6 inhibition with taxanes enhances anti-tumor efficacy by sustained impairment of pRB-E2F pathways in squamous cell lung cancer.

The CDK4/6 inhibitor palbociclib reduces tumor growth by decreasing retinoblastoma (RB) protein phosphorylation and inducing cell cycle arrest at the G1/S phase transition. Palbociclib in combination with anti-hormonal therapy brings significant benefit to breast cancer patients. In this study, novel combination approaches and underlying molecular/cellular mechanisms for palbociclib were explored in squamous cell lung cancer (SqCLC), the second most common subtype of non-small cell lung cancer. While approximate 20% lung patients benefit from immunotherapy, most SqCLC patients who receive platinum-doublet chemotherapy as first-line treatment, which often includes a taxane, are still in need of more effective combination therapies. Our results demonstrated enhanced cytotoxicity and anti-tumor effect with palbociclib plus taxanes at clinically achievable doses in multiple SqCLC models with diverse cancer genetic backgrounds. Comprehensive gene expression analysis revealed a sustained disruption of pRB-E2F signaling by combination that was accompanied with enhanced regulation of pleiotropic biological effects. These included several novel mechanisms such as abrogation of G2/M and mitotic spindle assembly checkpoints, as well as impaired induction of hypoxia-inducible factor 1 alpha (HIF-1α). The decrease in HIF-1α modulated a couple key angiogenic and anti-angiogenic factors, resulting in an enhanced anti-angiogenic effect. This preclinical work suggests a new therapeutic opportunity for palbociclib in lung and other cancers currently treated with taxane based chemotherapy as standard of care.

TNER: a novel background error suppression method for mutation detection in circulating tumor DNA.

BACKGROUND: Ultra-deep next-generation sequencing of circulating tumor DNA (ctDNA) holds great promise as a tool for the early detection of cancer and for monitoring disease progression and therapeutic responses. However, the low abundance of ctDNA in the bloodstream coupled with technical errors introduced during library construction and sequencing complicates mutation detection. RESULTS: To achieve high accuracy of variant calling via better distinguishing low-frequency ctDNA mutations from background errors, we introduce TNER (Tri-Nucleotide Error Reducer), a novel background error suppression method that provides a robust estimation of background noise to reduce sequencing errors. The results on both simulated data and real data from healthy subjects demonstrate that the proposed algorithm consistently outperforms a current, state-of-the-art, position-specific error polishing model, particularly when the sample size of healthy subjects is small. CONCLUSIONS: TNER significantly enhances the specificity of downstream ctDNA mutation detection without sacrificing sensitivity. The tool is publicly available at https://github.com/ctDNA/TNER .

Outlier analysis of functional genomic profiles enriches for oncology targets and enables precision medicine.

BACKGROUND: Genome-scale functional genomic screens across large cell line panels provide a rich resource for discovering tumor vulnerabilities that can lead to the next generation of targeted therapies. Their data analysis typically has focused on identifying genes whose knockdown enhances response in various pre-defined genetic contexts, which are limited by biological complexities as well as the incompleteness of our knowledge. We thus introduce a complementary data mining strategy to identify genes with exceptional sensitivity in subsets, or outlier groups, of cell lines, allowing an unbiased analysis without any a priori assumption about the underlying biology of dependency. RESULTS: Genes with outlier features are strongly and specifically enriched with those known to be associated with cancer and relevant biological processes, despite no a priori knowledge being used to drive the analysis. Identification of exceptional responders (outliers) may not lead only to new candidates for therapeutic intervention, but also tumor indications and response biomarkers for companion precision medicine strategies. Several tumor suppressors have an outlier sensitivity pattern, supporting and generalizing the notion that tumor suppressors can play context-dependent oncogenic roles. CONCLUSIONS: The novel application of outlier analysis described here demonstrates a systematic and data-driven analytical strategy to decipher large-scale functional genomic data for oncology target and precision medicine discoveries.

Whole Exome Sequencing of Rapid Autopsy Tumors and Xenograft Models Reveals Possible Driver Mutations Underlying Tumor Progression.

Pancreatic Ductal Adenocarcinoma (PDAC) is a highly lethal malignancy due to its propensity to invade and rapidly metastasize and remains very difficult to manage clinically. One major hindrance towards a better understanding of PDAC is the lack of molecular data sets and models representative of end stage disease. Moreover, it remains unclear how molecularly similar patient-derived xenograft (PDX) models are to the primary tumor from which they were derived. To identify potential molecular drivers in metastatic pancreatic cancer progression, we obtained matched primary tumor, metastases and normal (peripheral blood) samples under a rapid autopsy program and performed whole exome sequencing (WES) on tumor as well as normal samples. PDX models were also generated, sequenced and compared to tumors. Across the matched data sets generated for three patients, there were on average approximately 160 single-nucleotide mutations in each sample. The majority of mutations in each patient were shared among the primary and metastatic samples and, importantly, were largely retained in the xenograft models. Based on the mutation prevalence in the primary and metastatic sites, we proposed possible clonal evolution patterns marked by functional mutations affecting cancer genes such as KRAS, TP53 and SMAD4 that may play an important role in tumor initiation, progression and metastasis. These results add to our understanding of pancreatic tumor biology, and demonstrate that PDX models derived from advanced or end-stage likely closely approximate the genetics of the disease in the clinic and thus represent a biologically and clinically relevant pre-clinical platform that may enable the development of effective targeted therapies for PDAC.

PEST domain mutations in Notch receptors comprise an oncogenic driver segment in triple-negative breast cancer sensitive to a γ-secretase inhibitor.

PURPOSE: To identify and characterize novel, activating mutations in Notch receptors in breast cancer and to determine response to the gamma secretase inhibitor (GSI) PF-03084014. EXPERIMENTAL DESIGN: We used several computational approaches, including novel algorithms, to analyze next-generation sequencing data and related omic datasets from The Cancer Genome Atlas (TCGA) breast cancer cohort. Patient-derived xenograft (PDX) models were sequenced, and Notch-mutant models were treated with PF-03084014. Gene-expression and functional analyses were performed to study the mechanism of activation through mutation and inhibition by PF-03084014. RESULTS: We identified mutations within and upstream of the PEST domains of NOTCH1, NOTCH2, and NOTCH3 in the TCGA dataset. Mutations occurred via several genetic mechanisms and compromised the function of the PEST domain, a negative regulatory domain commonly mutated in other cancers. Focal amplifications of NOTCH2 and NOTCH3 were also observed, as were heterodimerization or extracellular domain mutations at lower incidence. Mutations and amplifications often activated the Notch pathway as evidenced by increased expression of canonical Notch target genes, and functional mutations were significantly enriched in the triple-negative breast cancer subtype (TNBC). PDX models were also identified that harbored PEST domain mutations, and these models were highly sensitive to PF-03084014. CONCLUSIONS: This work suggests that Notch-altered breast cancer constitutes a bona fide oncogenic driver segment with the most common alteration being PEST domain mutations present in multiple Notch receptors. Importantly, functional studies suggest that this newly identified class can be targeted with Notch inhibitors, including GSIs.

Cell Index Database (CELLX): a web tool for cancer precision medicine.

The Cell Index Database, (CELLX) (http://cellx.sourceforge.net) provides a computational framework for integrating expression, copy number variation, mutation, compound activity, and meta data from cancer cells. CELLX provides the computational biologist a quick way to perform routine analyses as well as the means to rapidly integrate data for offline analysis. Data is accessible through a web interface which utilizes R to generate plots and perform clustering, correlations, and statistical tests for associations within and between data types for ~20,000 samples from TCGA, CCLE, Sanger, GSK, GEO, GTEx, and other public sources. We show how CELLX supports precision oncology through indications discovery, biomarker evaluation, and cell line screening analysis.

Resistance to dual blockade of the kinases PI3K and mTOR in KRAS-mutant colorectal cancer models results in combined sensitivity to inhibition of the receptor tyrosine kinase EGFR.

Targeted blockade of aberrantly activated signaling pathways is an attractive therapeutic strategy for solid tumors, but drug resistance is common. KRAS is a frequently mutated gene in human cancer but remains a challenging clinical target. Inhibitors against KRAS signaling mediators, namely, PI3K (phosphatidylinositol 3-kinase) and mTOR (mechanistic target of rapamycin), have limited clinical efficacy as single agents in KRAS-mutant colorectal cancer (CRC). We investigated potential bypass mechanisms to PI3K/mTOR inhibition in KRAS-mutant CRC. Using genetically engineered mouse model cells that had acquired resistance to the dual PI3K/mTOR small-molecule inhibitor PF-04691502, we determined with chemical library screens that inhibitors of the ERBB [epidermal growth factor receptor (EGFR)] family restored the sensitivity to PF-04691502. Although EGFR inhibitors alone have limited efficacy in reducing KRAS-mutant tumors, we found that PF-04691502 induced the abundance, phosphorylation, and activity of EGFR, ERBB2, and ERBB3 through activation of FOXO3a (forkhead box O 3a), a transcription factor inhibited by the PI3K to AKT pathway. PF-04691502 also induced a stem cell-like gene expression signature. KRAS-mutant patient-derived xenografts from mice treated with PF-04691502 had a similar gene expression signature and exhibited increased EGFR activation, suggesting that this drug-induced resistance mechanism may occur in patients. Combination therapy with dacomitinib (a pan-ERBB inhibitor) restored sensitivity to PF-04691502 in drug-resistant cells in culture and induced tumor regression in drug-resistant allografts in mice. Our findings suggest that combining PI3K/mTOR and EGFR inhibitors may improve therapeutic outcome in patients with KRAS-mutant CRC.

Patterns of somatic alterations between matched primary and metastatic colorectal tumors characterized by whole-genome sequencing.

Colorectal cancer (CRC) patients have poor prognosis after formation of distant metastasis. Understanding the molecular mechanisms by which genetic changes facilitate metastasis is critical for the development of targeted therapeutic strategies aimed at controlling disease progression while minimizing toxic side effects. A comprehensive portrait of somatic alterations in CRC and the changes between primary and metastatic tumors has yet to be developed. We performed whole genome sequencing of two primary CRC tumors and their matched liver metastases. By comparing to matched germline DNA, we catalogued somatic alterations at multiple scales, including single nucleotide variations, small insertions and deletions, copy number aberrations and structural variations in both the primary and matched metastasis. We found that the majority of these somatic alterations are present in both sites. Despite the overall similarity, several de novo alterations in the metastases were predicted to be deleterious, in genes including FBXW7, DCLK1 and FAT2, which might contribute to the initiation and progression of distant metastasis. Through careful examination of the mutation prevalence among tumor cells at each site, we also proposed distinct clonal evolution patterns between primary and metastatic tumors in the two cases. These results suggest that somatic alterations may play an important role in driving the development of colorectal cancer metastasis and present challenges and opportunities when considering the choice of treatment.

Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer.

Gastric cancer is a heterogeneous disease with diverse molecular and histological subtypes. We performed whole-genome sequencing in 100 tumor-normal pairs, along with DNA copy number, gene expression and methylation profiling, for integrative genomic analysis. We found subtype-specific genetic and epigenetic perturbations and unique mutational signatures. We identified previously known (TP53, ARID1A and CDH1) and new (MUC6, CTNNA2, GLI3, RNF43 and others) significantly mutated driver genes. Specifically, we found RHOA mutations in 14.3% of diffuse-type tumors but not in intestinal-type tumors (P < 0.001). The mutations clustered in recurrent hotspots affecting functional domains and caused defective RHOA signaling, promoting escape from anoikis in organoid cultures. The top perturbed pathways in gastric cancer included adherens junction and focal adhesion, in which RHOA and other mutated genes we identified participate as key players. These findings illustrate a multidimensional and comprehensive genomic landscape that highlights the molecular complexity of gastric cancer and provides a road map to facilitate genome-guided personalized therapy.

MTOR mutations in the crosshairs of targeted therapy.

The identification of genetic lesions that affect tumor sensitivity to targeted therapies is a major objective of precision medicine. Two reports in this issue combine tumor genome analyses with functional characterization to uncover activating mutations in MTOR that confer sensitivity to a clinically used mTOR inhibitor.

Cross-species analysis of genetically engineered mouse models of MAPK-driven colorectal cancer identifies hallmarks of the human disease.

Effective treatment options for advanced colorectal cancer (CRC) are limited, survival rates are poor and this disease continues to be a leading cause of cancer-related deaths worldwide. Despite being a highly heterogeneous disease, a large subset of individuals with sporadic CRC typically harbor relatively few established 'driver' lesions. Here, we describe a collection of genetically engineered mouse models (GEMMs) of sporadic CRC that combine lesions frequently altered in human patients, including well-characterized tumor suppressors and activators of MAPK signaling. Primary tumors from these models were profiled, and individual GEMM tumors segregated into groups based on their genotypes. Unique allelic and genotypic expression signatures were generated from these GEMMs and applied to clinically annotated human CRC patient samples. We provide evidence that a Kras signature derived from these GEMMs is capable of distinguishing human tumors harboring KRAS mutation, and tracks with poor prognosis in two independent human patient cohorts. Furthermore, the analysis of a panel of human CRC cell lines suggests that high expression of the GEMM Kras signature correlates with sensitivity to targeted pathway inhibitors. Together, these findings implicate GEMMs as powerful preclinical tools with the capacity to recapitulate relevant human disease biology, and support the use of genetic signatures generated in these models to facilitate future drug discovery and validation efforts.

Decoding complex patterns of genomic rearrangement in hepatocellular carcinoma.

Elucidating the molecular basis of hepatocellular carcinoma (HCC) is crucial to developing targeted diagnostics and therapies for this deadly disease. The landscape of somatic genomic rearrangements (GRs), which can lead to oncogenic gene fusions, remains poorly characterized in HCC. We have predicted 4314 GRs including large-scale insertions, deletions, inversions and translocations based on the whole-genome sequencing data for 88 primary HCC tumor/non-tumor tissues. We identified chromothripsis in 5 HCC genomes (5.7%) recurrently affecting chromosomal arms 1q and 8q. Albumin (ALB) was found to harbor GRs, deactivating mutations and deletions in 10% of cohort. Integrative analysis identified a pattern of paired intra-chromosomal translocations flanking focal amplifications and asymmetrical patterns of copy number variation flanking breakpoints of translocations. Furthermore, we predicted 260 gene fusions which frequently result in aberrant over-expression of the 3' genes in tumors and validated 18 gene fusions, including recurrent fusion (2/88) of ABCB11 and LRP2.

Molecular predictors of sensitivity to the insulin-like growth factor 1 receptor inhibitor Figitumumab (CP-751,871).

Figitumumab (CP-751,871), a potent and fully human monoclonal anti-insulin-like growth factor 1 receptor (IGF1R) antibody, has been investigated in clinical trials of several solid tumors. To identify biomarkers of sensitivity and resistance to figitumumab, its in vitro antiproliferative activity was analyzed in a panel of 93 cancer cell lines by combining in vitro screens with extensive molecular profiling of genomic aberrations. Overall response was bimodal and the majority of cell lines were resistant to figitumumab. Nine of 15 sensitive cell lines were derived from colon cancers. Correlations between genomic characteristics of cancer cell lines with figitumumab antiproliferative activity revealed that components of the IGF pathway, including IRS2 (insulin receptor substrate 2) and IGFBP5 (IGF-binding protein 5), played a pivotal role in determining the sensitivity of tumors to single-agent figitumumab. Tissue-specific differences among the top predictive genes highlight the need for tumor-specific patient selection strategies. For the first time, we report that alteration or expression of the MYB oncogene is associated with sensitivity to IGF1R inhibitors. MYB is dysregulated in hematologic and epithelial tumors, and IGF1R inhibition may represent a novel therapeutic opportunity. Although growth inhibitory activity with single-agent figitumumab was relatively rare, nine combinations comprising figitumumab plus chemotherapeutic agents or other targeted agents exhibited properties of synergy. Inhibitors of the ERBB family were frequently synergistic and potential biomarkers of drug synergy were identified. Several biomarkers of antiproliferative activity of figitumumab both alone and in combination with other therapies may inform the design of clinical trials evaluating IGF1R inhibitors.