IGF1R constitutive activation expands luminal progenitors and influences lineage differentiation during breast tumorigenesis.

Breast tumors display tremendous heterogeneity in part due to varying molecular alterations, divergent cells of origin, and differentiation. Understanding where and how this heterogeneity develops is likely important for effective breast cancer eradication. Insulin-like growth factor (IGF) signaling is critical for normal mammary gland development and function, and has an established role in tumor development and resistance to therapy. Here we demonstrate that constitutive activation of the IGF1 receptor (IGF1R) influences lineage differentiation during mammary tumorigenesis. Transgenic IGF1R constitutive activation promotes tumors with mixed histologies, multiple cell lineages and an expanded bi-progenitor population. In these tumors, IGF1R expands the luminal-progenitor population while influencing myoepithelial differentiation. Mammary gland transplantation with IGF1R-infected mammary epithelial cells (MECs) resulted in hyperplastic, highly differentiated outgrowths and attenuated reconstitution. Restricting IGF1R constitutive activation to luminal versus myoepithelial lineage-sorted MECs resulted in ductal reconstitutions co-expressing high IGF1R levels in the opposite lineage of origin. Using in vitro models, IGF1R constitutively activated MCF10A cells showed increased mammosphere formation and CD44+/CD24-population, which was dependent upon Snail and NFκB signaling. These results suggest that IGF1R expands luminal progenitor populations while also stimulating myoepithelial cell differentiation. This ability to influence lineage differentiation may promote heterogeneous mammary tumors, and have implications for clinical treatment.

Correction: A feasibility study of returning clinically actionable somatic genomic alterations identified in a research laboratory.

[This corrects the article DOI: 10.18632/oncotarget.16018.].

Use of a Targeted Exome Next-Generation Sequencing Panel Offers Therapeutic Opportunity and Clinical Benefit in a Subset of Patients With Advanced Cancers.

PURPOSE: Smaller hotspot-based next-generation sequencing (NGS) panels have emerged to support standard of care therapy for patients with cancer. When standard treatments fail, it is unknown whether additional testing using an expanded panel of genes provides any benefit. The purpose of this study was to determine if larger sequencing panels that capture additional actionable genes, coupled with decision support, translates into treatment with matched therapy after frontline therapy has failed. PATIENTS AND METHODS: A prospective protocol accrued 521 patients with a wide variety of refractory cancers. NGS testing using a 46- or 50-gene hotspot assay, then a 409-gene whole-exome assay, was sequentially performed in a Clinical Laboratory Improvement Amendments-certified clinical laboratory. A decision-support team annotated somatic alterations in clinically actionable genes for function and facilitated therapeutic matching. Survival and the impact of matched therapy use were determined by Kaplan-Meier estimate, log-rank test, and Cox proportional hazards regression. RESULTS: The larger NGS panel identified at least one alteration in an actionable gene not previously identified in the smaller sequencing panel in 214 (41%) of 521 of enrolled patients. After the application of decision support, 41% of the alterations in actionable genes were considered to affect the function of the gene and were deemed actionable. Forty patients (40 of 214 [19%]) were subsequently treated with matched therapy. Treatment with matched therapy was associated with significantly improved overall survival compared with treatment with nonmatched therapy (P = .017). CONCLUSION: Combining decision support with larger NGS panels that incorporate genes beyond those recommended in current treatment guidelines helped to identify patients who were eligible for matched therapy while improving overall treatment selection and survival. This survival benefit was restricted to a small subset of patients.

Precision Oncology Decision Support: Current Approaches and Strategies for the Future.

With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719-31. ©2018 AACR.

Physician interpretation of genomic test results and treatment selection.

BACKGROUND: Genomic testing is increasingly performed in oncology, but concerns remain regarding the clinician's ability to interpret results. In the current study, the authors sought to determine the agreement between physicians and genomic annotators from the Precision Oncology Decision Support (PODS) team at The University of Texas MD Anderson Cancer Center in Houston regarding actionability and the clinical use of test results. METHODS: On a prospective protocol, patients underwent clinical genomic testing for hotspot mutations in 46 or 50 genes. Six months after sequencing, physicians received questionnaires for patients who demonstrated a variant in an actionable gene, investigating their perceptions regarding the actionability of alterations and clinical use of these findings. Genomic annotators independently classified these variants as actionable, potentially actionable, unknown, or not actionable. RESULTS: Physicians completed 250 of 288 questionnaires (87% response rate). Physicians considered 168 of 250 patients (67%) as having an actionable alteration; of these, 165 patients (98%) were considered to have an actionable alteration by the PODS team and 3 were of unknown significance. Physicians were aware of genotype-matched therapy available for 119 patients (71%) and 48 of these 119 patients (40%) received matched therapy. Approximately 46% of patients in whom physicians regarded alterations as not actionable (36 of 79 patients) were classified as having an actionable/potentially actionable mutation by the PODS team. However, many of these were only theoretically actionable due to limited trials and/or therapies (eg, KRAS). CONCLUSIONS: Physicians are aware of recurrent mutations in actionable genes on "hotspot" panels. As larger genomic panels are used, there may be a growing need for annotation of actionability. Decision support to increase awareness of genomically relevant trials and novel treatment options for recurrent mutations (eg, KRAS) also are needed. Cancer 2018;124:966-72. © 2017 American Cancer Society.

"Personalized Cancer Therapy": A Publicly Available Precision Oncology Resource.

High-throughput genomic and molecular profiling of tumors is emerging as an important clinical approach. Molecular profiling is increasingly being used to guide cancer patient care, especially in advanced and incurable cancers. However, navigating the scientific literature to make evidence-based clinical decisions based on molecular profiling results is overwhelming for many oncology clinicians and researchers. The Personalized Cancer Therapy website (www.personalizedcancertherapy.org) was created to provide an online resource for clinicians and researchers to facilitate navigation of available data. Specifically, this resource can be used to help identify potential therapy options for patients harboring oncogenic genomic alterations. Herein, we describe how content on www.personalizedcancertherapy.org is generated and maintained. We end with case scenarios to illustrate the clinical utility of the website. The goal of this publicly available resource is to provide easily accessible information to a broad oncology audience, as this may help ease the information retrieval burden facing participants in the precision oncology field. Cancer Res; 77(21); e123-6. ©2017 AACR.

Genomic analysis of exceptional responder to regorafenib in treatment-refractory metastatic rectal cancer: a case report and review of the literature.

We present the case of a 53-year-old male with metastatic rectal cancer who was treatment resistant to FOLFOX and FOLFOXIRI. Due to a Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation, regorafenib was given in the third line setting. Surprisingly, the patient had a prolonged partial response that lasted 27 months. Mutational status was extensively evaluated to identify potential alterations that might play a role as predictive markers for this unusual event. A poorly characterized but nontransforming mutation in Fms-like tyrosine kinase 4 (FLT4) was present in the tumor. Prior to and at the time of clinical progression, we found amplification of fibroblast growth factor receptor 1 (FGFR1) and epidermal growth factor receptor (EGFR), loss of the FLT4 mutation, and gain of KIT proto-oncogene receptor tyrosine kinase (KIT) G961S suggesting potential roles in acquired resistance.

A feasibility study of returning clinically actionable somatic genomic alterations identified in a research laboratory.

PURPOSE: Molecular profiling performed in the research setting usually does not benefit the patients that donate their tissues. Through a prospective protocol, we sought to determine the feasibility and utility of performing broad genomic testing in the research laboratory for discovery, and the utility of giving treating physicians access to research data, with the option of validating actionable alterations in the CLIA environment. EXPERIMENTAL DESIGN: 1200 patients with advanced cancer underwent characterization of their tumors with high depth hybrid capture sequencing of 201 genes in the research setting. Tumors were also tested in the CLIA laboratory, with a standardized hotspot mutation analysis on an 11, 46 or 50 gene platform. RESULTS: 527 patients (44%) had at least one likely somatic mutation detected in an actionable gene using hotspot testing. With the 201 gene panel, 945 patients (79%) had at least one alteration in a potentially actionable gene that was undetected with the more limited CLIA panel testing. Sixty-four genomic alterations identified on the research panel were subsequently tested using an orthogonal CLIA assay. Of 16 mutations tested in the CLIA environment, 12 (75%) were confirmed. Twenty-five (52%) of 48 copy number alterations were confirmed. Nine (26.5%) of 34 patients with confirmed results received genotype-matched therapy. Seven of these patients were enrolled onto genotype-matched targeted therapy trials. CONCLUSION: Expanded cancer gene sequencing identifies more actionable genomic alterations. The option of CLIA validating research results can provide alternative targets for personalized cancer therapy.

ALK: a tyrosine kinase target for cancer therapy.

The anaplastic lymphoma kinase (ALK) gene plays an important physiologic role in the development of the brain and can be oncogenically altered in several malignancies, including non-small-cell lung cancer (NSCLC) and anaplastic large cell lymphomas (ALCL). Most prevalent ALK alterations are chromosomal rearrangements resulting in fusion genes, as seen in ALCL and NSCLC. In other tumors, ALK copy-number gains and activating ALK mutations have been described. Dramatic and often prolonged responses are seen in patients with ALK alterations when treated with ALK inhibitors. Three of these-crizotinib, ceritinib, and alectinib-are now FDA approved for the treatment of metastatic NSCLC positive for ALK fusions. However, the emergence of resistance is universal. Newer ALK inhibitors and other targeting strategies are being developed to counteract the newly emergent mechanism(s) of ALK inhibitor resistance. This review outlines the recent developments in our understanding and treatment of tumors with ALK alterations.

Clinical Use of Precision Oncology Decision Support.

PURPOSE: Precision oncology is hindered by the lack of decision support for determining the functional and therapeutic significance of genomic alterations in tumors and relevant clinically available options. To bridge this knowledge gap, we established a Precision Oncology Decision Support (PODS) team that provides annotations at the alteration-level and subsequently determined if clinical decision-making was influenced. METHODS: Genomic alterations were annotated to determine actionability based on a variant's known or potential functional and/or therapeutic significance. The medical records of a subset of patients annotated in 2015 were manually reviewed to assess trial enrollment. A web-based survey was implemented to capture the reasons why genotype-matched therapies were not pursued. RESULTS: PODS processed 1,669 requests for annotation of 4,084 alterations (2,254 unique) across 49 tumor types for 1,197 patients. 2,444 annotations for 669 patients included an actionable variant call: 32.5% actionable, 9.4% potentially, 29.7% unknown, 28.4% non-actionable. 66% of patients had at least one actionable/potentially actionable alteration. 20.6% (110/535) patients annotated enrolled on a genotype-matched trial. Trial enrolment was significantly higher for patients with actionable/potentially actionable alterations (92/333, 27.6%) than those with unknown (16/136, 11.8%) and non-actionable (2/66, 3%) alterations (p=0.00004). Actionable alterations in PTEN, PIK3CA, and ERBB2 most frequently led to enrollment on genotype-matched trials. Clinicians cited a variety of reasons why patients with actionable alterations did not enroll on trials. CONCLUSION: Over half of alterations annotated were of unknown significance or non-actionable. Physicians were more likely to enroll a patient on a genotype-matched trial when an annotation supported actionability. Future studies are needed to demonstrate the impact of decision support on trial enrollment and oncologic outcomes.

Proteomic Screening and Lasso Regression Reveal Differential Signaling in Insulin and Insulin-like Growth Factor I (IGF1) Pathways.

Insulin and insulin-like growth factor I (IGF1) influence cancer risk and progression through poorly understood mechanisms. To better understand the roles of insulin and IGF1 signaling in breast cancer, we combined proteomic screening with computational network inference to uncover differences in IGF1 and insulin induced signaling. Using reverse phase protein array, we measured the levels of 134 proteins in 21 breast cancer cell lines stimulated with IGF1 or insulin for up to 48 h. We then constructed directed protein expression networks using three separate methods: (i) lasso regression, (ii) conventional matrix inversion, and (iii) entropy maximization. These networks, named here as the time translation models, were analyzed and the inferred interactions were ranked by differential magnitude to identify pathway differences. The two top candidates, chosen for experimental validation, were shown to regulate IGF1/insulin induced phosphorylation events. First, acetyl-CoA carboxylase (ACC) knock-down was shown to increase the level of mitogen-activated protein kinase (MAPK) phosphorylation. Second, stable knock-down of E-Cadherin increased the phospho-Akt protein levels. Both of the knock-down perturbations incurred phosphorylation responses stronger in IGF1 stimulated cells compared with insulin. Overall, the time-translation modeling coupled to wet-lab experiments has proven to be powerful in inferring differential interactions downstream of IGF1 and insulin signaling, in vitro.

Automated identification of molecular effects of drugs (AIMED).

INTRODUCTION: Genomic profiling information is frequently available to oncologists, enabling targeted cancer therapy. Because clinically relevant information is rapidly emerging in the literature and elsewhere, there is a need for informatics technologies to support targeted therapies. To this end, we have developed a system for Automated Identification of Molecular Effects of Drugs, to help biomedical scientists curate this literature to facilitate decision support. OBJECTIVES: To create an automated system to identify assertions in the literature concerning drugs targeting genes with therapeutic implications and characterize the challenges inherent in automating this process in rapidly evolving domains. METHODS: We used subject-predicate-object triples (semantic predications) and co-occurrence relations generated by applying the SemRep Natural Language Processing system to MEDLINE abstracts and ClinicalTrials.gov descriptions. We applied customized semantic queries to find drugs targeting genes of interest. The results were manually reviewed by a team of experts. RESULTS: Compared to a manually curated set of relationships, recall, precision, and F2 were 0.39, 0.21, and 0.33, respectively, which represents a 3- to 4-fold improvement over a publically available set of predications (SemMedDB) alone. Upon review of ostensibly false positive results, 26% were considered relevant additions to the reference set, and an additional 61% were considered to be relevant for review. Adding co-occurrence data improved results for drugs in early development, but not their better-established counterparts. CONCLUSIONS: Precision medicine poses unique challenges for biomedical informatics systems that help domain experts find answers to their research questions. Further research is required to improve the performance of such systems, particularly for drugs in development.

The right drugs at the right time for the right patient: the MD Anderson precision oncology decision support platform.

The development of resources for clinical interpretation of cancer-associated genetic alterations has significantly lagged behind the technical developments enabling their detection in a time- and cost-efficient manner. The lack of scientific and informatics decision support for oncologists can lead to no action being taken or suboptimal therapeutic choices being made, which could affect the clinical outcome of a patient as well as convoluting research findings from clinical trials. In this article, we describe the precision oncology decision support (PODS) platform developed within The Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy (IPCT) at MD Anderson Cancer Center; the platform aims to bridge the gap between molecular alteration detection and identification of appropriate treatments.

Using Ontology Fingerprints to disambiguate gene name entities in the biomedical literature.

Ambiguous gene names in the biomedical literature are a barrier to accurate information extraction. To overcome this hurdle, we generated Ontology Fingerprints for selected genes that are relevant for personalized cancer therapy. These Ontology Fingerprints were used to evaluate the association between genes and biomedical literature to disambiguate gene names. We obtained 93.6% precision for the test gene set and 80.4% for the area under a receiver-operating characteristics curve for gene and article association. The core algorithm was implemented using a graphics processing unit-based MapReduce framework to handle big data and to improve performance. We conclude that Ontology Fingerprints can help disambiguate gene names mentioned in text and analyse the association between genes and articles. Database URL: http://www.ontologyfingerprint.org

Advances in Preventive Therapy for Estrogen-Receptor-Negative Breast Cancer.

Preventing breast cancer is an effective strategy for reducing breast cancer deaths. The purpose of chemoprevention (also termed preventive therapy) is to reduce cancer incidence by use of natural, synthetic, or biological agents. The efficacy of tamoxifen, raloxifene, and exemestane as preventive therapy against estrogen-receptor (ER)-positive breast cancer is well established for women at increased risk for breast cancer. However, because breast cancer is a heterogeneous disease, distinct preventive approaches may be required for effective prevention of each subtype. Current research is, therefore, focused on identifying alternative mechanisms by which biologically active compounds can reduce the risk of all breast cancer subtypes including ER-negative breast cancer. Promising agents are currently being developed for prevention of HER2-positive and triple-negative breast cancer (TNBC) and include inhibitors of the ErbB family receptors, COX-2 inhibitors, metformin, retinoids, statins, poly(ADP-ribose) polymerase inhibitors, and natural compounds. This review focuses on recent progress in research to develop more effective preventive agents, in particular for prevention of ER-negative breast cancer.

High IGF-IR activity in triple-negative breast cancer cell lines and tumorgrafts correlates with sensitivity to anti-IGF-IR therapy.

PURPOSE: We previously reported an insulin-like growth factor (IGF) gene expression signature, based on genes induced or repressed by IGF-I, which correlated with poor prognosis in breast cancer. We tested whether the IGF signature was affected by anti-IGF-I receptor (IGF-IR) inhibitors and whether the IGF signature correlated with response to a dual anti-IGF-IR/insulin receptor (InsR) inhibitor, BMS-754807. EXPERIMENTAL DESIGN: An IGF gene expression signature was examined in human breast tumors and cell lines and changes were noted following treatment of cell lines or xenografts with anti-IGF-IR antibodies or tyrosine kinase inhibitors. Sensitivity of cells to BMS-754807 was correlated with levels of the IGF signature. Human primary tumorgrafts were analyzed for the IGF signature and IGF-IR levels and activity, and MC1 tumorgrafts were treated with BMS-754807 and chemotherapy. RESULTS: The IGF gene expression signature was reversed in three different models (cancer cell lines or xenografts) treated with three different anti-IGF-IR therapies. The IGF signature was present in triple-negative breast cancers (TNBC) and TNBC cell lines, which were especially sensitive to BMS-754807, and sensitivity was significantly correlated to the expression of the IGF gene signature. The TNBC primary human tumorgraft MC1 showed high levels of both expression and activity of IGF-IR and IGF gene signature score. Treatment of MC1 with BMS-754807 showed growth inhibition and, in combination with docetaxel, tumor regression occurred until no tumor was palpable. Regression was associated with reduced proliferation, increased apoptosis, and mitotic catastrophe. CONCLUSIONS: These studies provide a clear biological rationale to test anti-IGF-IR/InsR therapy in combination with chemotherapy in patients with TNBC.

BMS-536924 reverses IGF-IR-induced transformation of mammary epithelial cells and causes growth inhibition and polarization of MCF7 cells.

PURPOSE: This study aimed to test the ability of a new insulin-like growth factor receptor (IGF-IR) tyrosine kinase inhibitor, BMS-536924, to reverse the ability of constitutively active IGF-IR (CD8-IGF-IR) to transform MCF10A cells, and to examine the effect of the inhibitor on a range of human breast cancer cell lines. EXPERIMENTAL DESIGN: CD8-IGF-IR-MCF10A cells were grown in monolayer culture, three-dimensional (3D) culture, and as xenografts, and treated with BMS-536924. Proliferation, cell cycle, polarity, and apoptosis were measured. Twenty-three human breast cancer cell lines were treated in monolayer culture with BMS-536924, and cell viability was measured. MCF7, MDA-MB-231, and MDA-MB-435 were treated with BMS-536924 in monolayer and 3D culture, and proliferation, migration, polarity, and apoptosis were measured. RESULTS: Treatment of CD8-IGF-IR-MCF10A cells grown in 3D culture with BMS-536924 caused a blockade of proliferation, restoration of apical-basal polarity, and enhanced apoptosis, resulting in a partial phenotypic reversion to normal acini. In monolayer culture, BMS-536924 induced a dose-dependent inhibition of proliferation, with an accumulation of cells in G(0)/G(1,), and completely blocked CD8-IGF-IR-induced migration, invasion, and anchorage-independent growth. CD8-IGF-IR-MCF10A xenografts treated with BMS-536924 (100 mg/kg/day) showed a 76% reduction in xenograft volume. In a series of 23 human breast cancer cell lines, BMS-536924 inhibited monolayer proliferation of 16 cell lines. Most strikingly, treatment of MCF7 cells grown in 3D culture with BMS-536924 caused blockade of proliferation, and resulted in the formation of hollow polarized lumen. CONCLUSIONS: These results show that the new small molecule BMS-536924 is an effective inhibitor of IGF-IR, causing a reversion of an IGF-IR - mediated transformed phenotype.

The type I insulin-like growth factor receptor pathway: a key player in cancer therapeutic resistance.

The insulin-like growth factor (IGF) ligands stimulate cellular proliferation and survival by activating the type I insulin-like growth factor receptor (IGF-IR). As a result, the IGF signaling system is implicated in a number of cancers, including those of the breast, prostate, and lung. In addition to mitogenic and anti-apoptotic roles that may directly influence tumor development, IGF-IR also appears to be a critical determinant of response to numerous cancer therapies. This review describes the role of the IGF-IR pathway in mediating resistance to both general cytotoxic therapies, such as radiation and chemotherapy, and targeted therapies, such as tamoxifen and trastuzumab. It concludes with a description of approaches to target IGF-IR and argues that inhibition of IGF signaling, in conjunction with standard therapies, may enhance the response of cancer cells to multiple modalities.

Constitutively active type I insulin-like growth factor receptor causes transformation and xenograft growth of immortalized mammary epithelial cells and is accompanied by an epithelial-to-mesenchymal transition mediated by NF-kappaB and snail.

Type I insulin-like growth factor receptor (IGF-IR) can transform mouse fibroblasts; however, little is known about the transforming potential of IGF-IR in human fibroblasts or epithelial cells. We found that overexpression of a constitutively activated IGF-IR (CD8-IGF-IR) was sufficient to cause transformation of immortalized human mammary epithelial cells and growth in immunocompromised mice. Furthermore, CD8-IGF-IR caused cells to undergo an epithelial-to-mesenchymal transition (EMT) which was associated with dramatically increased migration and invasion. The EMT was mediated by the induction of the transcriptional repressor Snail and downregulation of E-cadherin. NF-kappaB was highly active in CD8-IGF-IR-MCF10A cells, and both increased levels of Snail and the EMT were partially reversed by blocking NF-kappaB or IGF-IR activity. This study places IGF-IR among a small group of oncogenes that, when overexpressed alone, can confer in vivo tumorigenic growth of MCF10A cells and indicates the hierarchy in the mechanism of IGF-IR-induced EMT.