The tandem duplicator phenotype as a distinct genomic configuration in cancer.

Next-generation sequencing studies have revealed genome-wide structural variation patterns in cancer, such as chromothripsis and chromoplexy, that do not engage a single discernable driver mutation, and whose clinical relevance is unclear. We devised a robust genomic metric able to identify cancers with a chromotype called tandem duplicator phenotype (TDP) characterized by frequent and distributed tandem duplications (TDs). Enriched only in triple-negative breast cancer (TNBC) and in ovarian, endometrial, and liver cancers, TDP tumors conjointly exhibit tumor protein p53 (TP53) mutations, disruption of breast cancer 1 (BRCA1), and increased expression of DNA replication genes pointing at rereplication in a defective checkpoint environment as a plausible causal mechanism. The resultant TDs in TDP augment global oncogene expression and disrupt tumor suppressor genes. Importantly, the TDP strongly correlates with cisplatin sensitivity in both TNBC cell lines and primary patient-derived xenografts. We conclude that the TDP is a common cancer chromotype that coordinately alters oncogene/tumor suppressor expression with potential as a marker for chemotherapeutic response.

Systems consequences of amplicon formation in human breast cancer.

Chromosomal structural variations play an important role in determining the transcriptional landscape of human breast cancers. To assess the nature of these structural variations, we analyzed eight breast tumor samples with a focus on regions of gene amplification using mate-pair sequencing of long-insert genomic DNA with matched transcriptome profiling. We found that tandem duplications appear to be early events in tumor evolution, especially in the genesis of amplicons. In a detailed reconstruction of events on chromosome 17, we found large unpaired inversions and deletions connect a tandemly duplicated ERBB2 with neighboring 17q21.3 amplicons while simultaneously deleting the intervening BRCA1 tumor suppressor locus. This series of events appeared to be unusually common when examined in larger genomic data sets of breast cancers albeit using approaches with lesser resolution. Using siRNAs in breast cancer cell lines, we showed that the 17q21.3 amplicon harbored a significant number of weak oncogenes that appeared consistently coamplified in primary tumors. Down-regulation of BRCA1 expression augmented the cell proliferation in ERBB2-transfected human normal mammary epithelial cells. Coamplification of other functionally tested oncogenic elements in other breast tumors examined, such as RIPK2 and MYC on chromosome 8, also parallel these findings. Our analyses suggest that structural variations efficiently orchestrate the gain and loss of cancer gene cassettes that engage many oncogenic pathways simultaneously and that such oncogenic cassettes are favored during the evolution of a cancer.

Systems analysis of EGF receptor signaling dynamics with microwestern arrays.

We describe microwestern arrays, which enable quantitative, sensitive and high-throughput assessment of protein abundance and modifications after electrophoretic separation of microarrayed cell lysates. This method allowed us to measure 91 phosphosites on 67 proteins at six time points after stimulation with five epidermal growth factor (EGF) concentrations in A431 human carcinoma cells. We inferred the connectivities among 15 phosphorylation sites in 10 receptor tyrosine kinases (RTKs) and two sites from Src kinase using Bayesian network modeling and two mutual information-based methods; the three inference methods yielded substantial agreement on the network topology. These results imply multiple distinct RTK coactivation mechanisms and support the notion that small amounts of experimental data collected from phenotypically diverse network states may enable network inference.

Signaling network state predicts twist-mediated effects on breast cell migration across diverse growth factor contexts.

Epithelial-mesenchymal transition (EMT), whether in developmental morphogenesis or malignant transformation, prominently involves modified cell motility behavior. Although major advances have transpired in understanding the molecular pathways regulating the process of EMT induction per se by certain environmental stimuli, an important outstanding question is how the activities of signaling pathways governing motility yield the diverse movement behaviors characteristic of pre-induction versus postinduction states across a broad landscape of growth factor contexts. For the particular case of EMT induction in human mammary cells by ectopic expression of the transcription factor Twist, we found the migration responses to a panel of growth factors (EGF, HRG, IGF, HGF) dramatically disparate between confluent pre-Twist epithelial cells and sparsely distributed post-Twist mesenchymal cells-but that a computational model quantitatively integrating multiple key signaling node activities could nonetheless account for this full range of behavior. Moreover, motility in both conditions was successfully predicted a priori for an additional growth factor (PDGF) treatment. Although this signaling network state model could comprehend motility behavior globally, modulation of the network interactions underlying the altered pathway activities was identified by ascertaining differences in quantitative topological influences among the nodes between the two conditions.

PTMScout, a Web resource for analysis of high throughput post-translational proteomics studies.

The rate of discovery of post-translational modification (PTM) sites is increasing rapidly and is significantly outpacing our biological understanding of the function and regulation of those modifications. To help meet this challenge, we have created PTMScout, a web-based interface for viewing, manipulating, and analyzing high throughput experimental measurements of PTMs in an effort to facilitate biological understanding of protein modifications in signaling networks. PTMScout is constructed around a custom database of PTM experiments and contains information from external protein and post-translational resources, including gene ontology annotations, Pfam domains, and Scansite predictions of kinase and phosphopeptide binding domain interactions. PTMScout functionality comprises data set comparison tools, data set summary views, and tools for protein assignments of peptides identified by mass spectrometry. Analysis tools in PTMScout focus on informed subset selection via common criteria and on automated hypothesis generation through subset labeling derived from identification of statistically significant enrichment of other annotations in the experiment. Subset selection can be applied through the PTMScout flexible query interface available for quantitative data measurements and data annotations as well as an interface for importing data set groupings by external means, such as unsupervised learning. We exemplify the various functions of PTMScout in application to data sets that contain relative quantitative measurements as well as data sets lacking quantitative measurements, producing a set of interesting biological hypotheses. PTMScout is designed to be a widely accessible tool, enabling generation of multiple types of biological hypotheses from high throughput PTM experiments and advancing functional assignment of novel PTM sites. PTMScout is available at http://ptmscout.mit.edu.

A Phase 1 Study of a CDH6-Targeting Antibody-Drug Conjugate in Patients with Advanced Solid Tumors with Evaluation of Inflammatory and Neurological Adverse Events.

PURPOSE: This first-in-human study (NCT02947152) evaluated the safety, tolerability, pharmacokinetics, and preliminary efficacy of HKT288, a first-in-class CDH6-targeting antibody-drug conjugate (ADC). EXPERIMENTAL DESIGN: HKT288 was administered intravenously (IV) every 3 weeks until patients experienced unacceptable toxicity or progressive disease (PD). The starting dose of 0.3 mg/kg was determined based on the highest nonseverely toxic dose in monkeys, which was 2 mg/kg IV weekly. Based on preclinical toxicology, skin, eyes, bone marrow, and liver were expected targets of toxicity. RESULTS: Nine patients were enrolled: 5 with renal cell carcinoma and 4 with epithelial ovarian cancer. The best overall response on the 0.3 mg/kg cohort in patients with measurable disease was RECIST v1.1 stable disease in 3 patients and PD in 2 patients. The most frequent adverse events (AEs) regardless of causality were pyrexia (44.4%), constipation (44.4%), fatigue (33.3%), and vomiting (33.3%). Three suspected-related neurologic AEs (Grade 2) were reported on the 0.75 mg/kg cohort: seizure in 1 patient and another patient with aphasia and encephalopathy. Further studies were unable to identify the underlying mechanism of the neurologic AEs, and the study was terminated early. CONCLUSIONS: Preclinical toxicology did not predict the neurotoxicity observed with HKT288, and a comprehensive assessment performed post hoc did not identify the mechanism of toxicity. The development of further CDH6-targeting ADCs should be pursued with caution.

A CRISPR Screen Reveals Resistance Mechanisms to CD3-Bispecific Antibody Therapy.

CD3-bispecific antibodies represent an important therapeutic strategy in oncology. These molecules work by redirecting cytotoxic T cells to antigen-bearing tumor cells. Although CD3-bispecific antibodies have been developed for several clinical indications, cases of cancer-derived resistance are an emerging limitation to the more generalized application of these molecules. Here, we devised whole-genome CRISPR screens to identify cancer resistance mechanisms to CD3-bispecific antibodies across multiple targets and cancer types. By validating the screen hits, we found that deficiency in IFNγ signaling has a prominent role in cancer resistance. IFNγ functioned by stimulating the expression of T-cell killing-related molecules in a cell type-specific manner. By assessing resistance to the clinical CD3-bispecific antibody flotetuzumab, we identified core fucosylation as a critical pathway to regulate flotetuzumab binding to the CD123 antigen. Disruption of this pathway resulted in significant resistance to flotetuzumab treatment. Proper fucosylation of CD123 was required for its normal biological functions. In order to treat the resistance associated with fucosylation loss, flotetuzumab in combination with an alternative targeting CD3-bispecific antibody demonstrated superior efficacy. Together, our study reveals multiple mechanisms that can be targeted to enhance the clinical potential of current and future T-cell-engaging CD3-bispecific antibody therapies.

Discovery and Optimization of HKT288, a Cadherin-6-Targeting ADC for the Treatment of Ovarian and Renal Cancers.

Despite an improving therapeutic landscape, significant challenges remain in treating the majority of patients with advanced ovarian or renal cancer. We identified the cell-cell adhesion molecule cadherin-6 (CDH6) as a lineage gene having significant differential expression in ovarian and kidney cancers. HKT288 is an optimized CDH6-targeting DM4-based antibody-drug conjugate (ADC) developed for the treatment of these diseases. Our study provides mechanistic evidence supporting the importance of linker choice for optimal antitumor activity and highlights CDH6 as an antigen for biotherapeutic development. To more robustly predict patient benefit of targeting CDH6, we incorporate a population-based patient-derived xenograft (PDX) clinical trial (PCT) to capture the heterogeneity of response across an unselected cohort of 30 models-a novel preclinical approach in ADC development. HKT288 induces durable tumor regressions of ovarian and renal cancer models in vivo, including 40% of models on the PCT, and features a preclinical safety profile supportive of progression toward clinical evaluation.Significance: We identify CDH6 as a target for biotherapeutics development and demonstrate how an integrated pharmacology strategy that incorporates mechanistic pharmacodynamics and toxicology studies provides a rich dataset for optimizing the therapeutic format. We highlight how a population-based PDX clinical trial and retrospective biomarker analysis can provide correlates of activity and response to guide initial patient selection for first-in-human trials of HKT288. Cancer Discov; 7(9); 1030-45. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 920.

Receptor tyrosine kinases fall into distinct classes based on their inferred signaling networks.

Although many anticancer drugs that target receptor tyrosine kinases (RTKs) provide clinical benefit, their long-term use is limited by resistance that is often attributed to increased abundance or activation of another RTK that compensates for the inhibited receptor. To uncover common and unique features in the signaling networks of RTKs, we measured time-dependent signaling in six isogenic cell lines, each expressing a different RTK as downstream proteins were systematically perturbed by RNA interference. Network models inferred from the data revealed a conserved set of signaling pathways and RTK-specific features that grouped the RTKs into three distinct classes: (i) an EGFR/FGFR1/c-Met class constituting epidermal growth factor receptor, fibroblast growth factor receptor 1, and the hepatocyte growth factor receptor c-Met; (ii) an IGF-1R/NTRK2 class constituting insulin-like growth factor 1 receptor and neurotrophic tyrosine receptor kinase 2; and (iii) a PDGFRß class constituting platelet-derived growth factor receptor ß. Analysis of cancer cell line data showed that many RTKs of the same class were coexpressed and that increased abundance of an RTK or its cognate ligand frequently correlated with resistance to a drug targeting another RTK of the same class. In contrast, abundance of an RTK or ligand of one class generally did not affect sensitivity to a drug targeting an RTK of a different class. Thus, classifying RTKs by their inferred networks and then therapeutically targeting multiple receptors within a class may delay or prevent the onset of resistance.

Eap1p, an adhesin that mediates Candida albicans biofilm formation in vitro and in vivo.

Candida albicans is the leading cause of systemic fungal infections in immunocompromised humans. The ability to form biofilms on surfaces in the host or on implanted medical devices enhances C. albicans virulence, leading to antimicrobial resistance and providing a reservoir for infection. Biofilm formation is a complex multicellular process consisting of cell adhesion, cell growth, morphogenic switching between yeast form and filamentous states, and quorum sensing. Here we describe the role of the C. albicans EAP1 gene, which encodes a glycosylphosphatidylinositol-anchored, glucan-cross-linked cell wall protein, in adhesion and biofilm formation in vitro and in vivo. Deleting EAP1 reduced cell adhesion to polystyrene and epithelial cells in a gene dosage-dependent manner. Furthermore, EAP1 expression was required for C. albicans biofilm formation in an in vitro parallel plate flow chamber model and in an in vivo rat central venous catheter model. EAP1 expression was upregulated in biofilm-associated cells in vitro and in vivo. Our results illustrate an association between Eap1p-mediated adhesion and biofilm formation in vitro and in vivo.