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.].

Survival Outcomes by TP53 Mutation Status in Metastatic Breast Cancer.

PURPOSE: We sought to determine the significant genomic alterations in patients with metastatic breast cancer (MBC), and survival outcomes in common genotypes. PATIENTS AND METHODS: High-depth next generation sequencing was performed for 202 genes in tumor and normal DNA from 257 patients with MBC, including 165 patients with ER/PR+ HER2- (hormone receptor positive, HR+ positive), 32 patients with HER2+ and 60 patients with triple negative (ER/PR/HER2-) cancer. Kaplan Meier survival analysis was performed in our discovery set, in breast cancer patients analyzed in The Cancer Genome Atlas, and in a separate cohort of 98 patients with MBC who underwent clinical genomic testing. RESULTS: Significantly mutated genes (SMGs) varied by histology and tumor subtype, but TP53 was a SMG in all three subtypes. The most SMGs in HR+ patients included PIK3CA (32%), TP53 (29%), GATA3 (15%), CDH1 (8%), MAP3K1 (8%), PTEN (5%), TGFBR2 (4%), AKT1 (4%), and MAP2K4 (4%). TP53 mutations were associated with shorter recurrence-free survival (P=0.004), progression-free survival (P=0.00057) and overall survival (P=0.003). Further, TP53 status was prognostic among HR+ patients with PIK3CA mutations. TP53 mutations were also associated with poorer overall survival in the 442 HR+ breast cancer patients in the TCGA (P=0.042) and in an independent set of 96 HR+ MBC who underwent clinical sequencing (P=0.0004). CONCLUSIONS: SMGs differ by tumor subtype but TP53 is significantly mutated in all three breast cancer subtypes. TP53 mutations are associated with poor prognosis in HR+ breast cancer. TP53 mutations should be considered in the design and interpretation of precision oncology trials.

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.

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.

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.

Androgen receptor promotes tamoxifen agonist activity by activation of EGFR in ERα-positive breast cancer.

Tamoxifen (Tam) resistance represents a significant clinical problem in estrogen receptor (ER) α-positive breast cancer. We previously showed that decreased expression of Rho guanine nucleotide dissociation inhibitor (Rho GDI) α, a negative regulator of the Rho GTPase pathway, is associated with Tam resistance. We now discover that androgen receptor (AR) is overexpressed in cells with decreased Rho GDIα and seek to determine AR's contribution to resistance. We engineered ERα-positive cell lines with stable knockdown (KD) of Rho GDIα (KD cells). Resistance mechanisms were examined using microarray profiling, protein-interaction studies, growth and reporter gene assays, and Western blot analysis combined with a specific AR antagonist and other signaling inhibitors. Tam-resistant tumors and cell lines with low Rho GDIα levels exhibited upregulated AR expression. Microarray of Rho GDIα KD cells indicated that activation of EGFR and ERα was associated with Tam treatment. When AR levels were elevated, interaction between AR and EGFR was detected. Constitutive and Tam-induced phosphorylation of EGFR and ERK1/2 was blocked by the AR antagonist Enzalutamide, suggesting that AR-mediated EGFR activation was a mechanism of resistance in these cells. Constitutive ERα phosphorylation and transcriptional activity was inhibited by Enzalutamide and the EGFR inhibitor gefitinib, demonstrating that AR-mediated EGFR signaling activated ERα. Tam exhibited agonist activity in AR overexpressing cells, stimulating ERα transcriptional activity and proliferation, which was blocked by Enzalutamide and gefitinib. We describe a novel model of AR-mediated Tam resistance through activation of EGFR signaling leading to ER activation in ERα-positive cells with low expression of Rho GDIα.

Feasibility of Large-Scale Genomic Testing to Facilitate Enrollment Onto Genomically Matched Clinical Trials.

PURPOSE: We report the experience with 2,000 consecutive patients with advanced cancer who underwent testing on a genomic testing protocol, including the frequency of actionable alterations across tumor types, subsequent enrollment onto clinical trials, and the challenges for trial enrollment. PATIENTS AND METHODS: Standardized hotspot mutation analysis was performed in 2,000 patients, using either an 11-gene (251 patients) or a 46- or 50-gene (1,749 patients) multiplex platform. Thirty-five genes were considered potentially actionable based on their potential to be targeted with approved or investigational therapies. RESULTS: Seven hundred eighty-nine patients (39%) had at least one mutation in potentially actionable genes. Eighty-three patients (11%) with potentially actionable mutations went on genotype-matched trials targeting these alterations. Of 230 patients with PIK3CA/AKT1/PTEN/BRAF mutations that returned for therapy, 116 (50%) received a genotype-matched drug. Forty patients (17%) were treated on a genotype-selected trial requiring a mutation for eligibility, 16 (7%) were treated on a genotype-relevant trial targeting a genomic alteration without biomarker selection, and 40 (17%) received a genotype-relevant drug off trial. Challenges to trial accrual included patient preference of noninvestigational treatment or local treatment, poor performance status or other reasons for trial ineligibility, lack of trials/slots, and insurance denial. CONCLUSION: Broad implementation of multiplex hotspot testing is feasible; however, only a small portion of patients with actionable alterations were actually enrolled onto genotype-matched trials. Increased awareness of therapeutic implications and access to novel therapeutics are needed to optimally leverage results from broad-based genomic testing.

Clinical next generation sequencing to identify actionable aberrations in a phase I program.

PURPOSE: We determined the frequency of recurrent hotspot mutations in 46 cancer-related genes across tumor histologies in patients with advanced cancer. METHODS: We reviewed data from 500 consecutive patients who underwent genomic profiling on an IRB-approved prospective clinical protocol in the Phase I program at the MD Anderson Cancer Center. Archival tumor DNA was tested for 740 hotspot mutations in 46 genes (Ampli-Seq Cancer Panel; Life Technologies, CA). RESULTS: Of the 500 patients, 362 had at least one reported mutation/variant. The most common likely somatic mutations were within TP53 (36%), KRAS (11%), and PIK3CA (9%) genes. Sarcoma (20%) and kidney (30%) had the lowest proportion of likely somatic mutations detected, while pancreas (100%), colorectal (89%), melanoma (86%), and endometrial (75%) had the highest. There was high concordance in 62 patients with paired primary tumors and metastases analyzed. 151 (30%) patients had alterations in potentially actionable genes. 37 tumor types were enrolled; both rare actionable mutations in common tumor types and actionable mutations in rare tumor types were identified. CONCLUSION: Multiplex testing in the CLIA environment facilitates genomic characterization across multiple tumor lineages and identification of novel opportunities for genotype-driven trials.

A decision support framework for genomically informed investigational cancer therapy.

Rapidly improving understanding of molecular oncology, emerging novel therapeutics, and increasingly available and affordable next-generation sequencing have created an opportunity for delivering genomically informed personalized cancer therapy. However, to implement genomically informed therapy requires that a clinician interpret the patient's molecular profile, including molecular characterization of the tumor and the patient's germline DNA. In this Commentary, we review existing data and tools for precision oncology and present a framework for reviewing the available biomedical literature on therapeutic implications of genomic alterations. Genomic alterations, including mutations, insertions/deletions, fusions, and copy number changes, need to be curated in terms of the likelihood that they alter the function of a "cancer gene" at the level of a specific variant in order to discriminate so-called "drivers" from "passengers." Alterations that are targetable either directly or indirectly with approved or investigational therapies are potentially "actionable." At this time, evidence linking predictive biomarkers to therapies is strong for only a few genomic markers in the context of specific cancer types. For these genomic alterations in other diseases and for other genomic alterations, the clinical data are either absent or insufficient to support routine clinical implementation of biomarker-based therapy. However, there is great interest in optimally matching patients to early-phase clinical trials. Thus, we need accessible, comprehensive, and frequently updated knowledge bases that describe genomic changes and their clinical implications, as well as continued education of clinicians and patients.

Implementation of biomarker-driven cancer therapy: existing tools and remaining gaps.

There has been growing interest in biomarker-driven personalized cancer therapy, also known as precision medicine. Recently, dozens of molecular tests, including next generation sequencing, have been developed to detect biomarkers that have the potential to predict response of cancers to particular targeted therapies. However, detection of cancer-related biomarkers is only the first step in the battle. Deciding what therapy options to pursue can also be daunting, especially when tumors harbor more than one potentially actionable aberration. Further, different mutations/variants in a single gene may have different functional consequences, and response to targeted agents may be context dependent. However, early clinical trials with new molecular entities are increasingly conducted in a biomarker-selected fashion, and even when trials are not biomarker-selected, much effort is placed on enrolling patients onto clinical trials where they have the highest probability of response. We review available molecular tests and therapy discerning tools, including tools available for assessing functional consequences of molecular alterations and tools for finding applicable clinical trials, which exist to help bridge the gap between detection of cancer-related biomarker to the initiation of biomarker-matched targeted therapies.

Metastasis tumor-associated protein 2 enhances metastatic behavior and is associated with poor outcomes in estrogen receptor-negative breast cancer.

Metastasis remains a major clinical problem in breast cancer. One family of genes previously linked with metastasis is the metastasis tumor-associated (MTA) family, with members MTA1 enhancing and MTA3 inhibiting cancer metastasis. We have previously found that MTA2 enhances anchorage-independent growth in estrogen receptor α (ERα) breast cancers, and, in combination with other genes, performed as a predictive biomarker in ERα-positive breast cancer. We therefore hypothesized that MTA2 enhances breast cancer progression. To test this, cell growth, soft-agar colony formation, migration, and in vivo metastasis were examined in MTA2-overexpressing and Vector control transfected ERα-negative breast cancer cells. Pathways regulating cell-cell interaction, adhesion, and signaling through the Rho pathway were also investigated. Effects of the inhibition of the Rho pathway using a Rho Kinase inhibitor were assessed in soft-agar colony formation and motility assays in MTA2-overexpressing cells. MTA2 expression was associated with poor prognostic markers, and levels of MTA2 were associated with increased risk of early recurrence in retrospective analyses. MTA2 overexpression was associated with enhanced metastasis, and pathways regulating cell-cell interactions in vitro and in vivo. Most critically, MTA2-enhanced motility could be blocked by inhibiting Rho pathway signaling. We present the novel finding that MTA2 defined a subset of ERα-negative patients with a particularly poor outcome.

Loss of Rho GDIα and resistance to tamoxifen via effects on estrogen receptor α.

BACKGROUND: Estrogen receptor (ER) α is a successful therapeutic target in breast cancer, but patients eventually develop resistance to antiestrogens such as tamoxifen. METHODS: To identify genes whose expression was associated with the development of tamoxifen resistance and metastasis, we used microarrays to compare gene expression in four primary tumors from tamoxifen-treated patients whose breast cancers did not recur vs five metastatic tumors from patients whose cancers progressed during adjuvant tamoxifen treatment. Because Rho guanine dissociation inhibitor (GDI) α was underexpressed in the tamoxifen-resistant group, we stably transfected ERα-positive MCF-7 breast cancer cells with a plasmid encoding a short hairpin (sh) RNA to silence Rho GDIα expression. We used immunoblots and transcription assays to examine the role of Rho GDIα in ER-related signaling and growth of cells in vitro and as xenografts in treated nude mice (n = 8-9 per group) to examine the effects of Rho GDIα blockade on hormone responsiveness and metastatic behavior. The time to tumor tripling as the time in weeks from randomization to a threefold increase in total tumor volume over baseline was examined in treated mice. The associations of Rho GDIα and MTA2 levels with tamoxifen resistance were examined in microarray data from patients. All statistical tests were two-sided. RESULTS: Rho GDIα was expressed at lower levels in ERα-positive tumors that recurred during tamoxifen treatment than in ERα-positive tamoxifen-sensitive primary tumors. MCF-7 breast cancer cells in which Rho GDIα expression had been silenced were tamoxifen-resistant, had increased Rho GTPase and p21-activated kinase 1 activity, increased phosphorylation of ERα at serine 305, and enhanced tamoxifen-induced ERα transcriptional activity compared with control cells. MCF-7 cells in which Rho GDIα expression was silenced metastasized with high frequency when grown as tumor xenografts. When mice were treated with estrogen or estrogen withdrawal, tripling times for xenografts from cells with Rho GDIα silencing were similar to those from vector-containing control cells; however, tripling times were statistically significantly faster than control when mice were treated with tamoxifen (median tripling time for tumors with Rho GDIα small interfering RNA = 2.34 weeks; for control tumors = not reached, hazard ratio = 4.13, 95% confidence interval = 1.07 to 15.96, P = .040 [adjusted for multiple comparisons, P = .119]). Levels of the metastasis-associated protein MTA2 were also increased upon Rho GDIα silencing, and combined Rho GDIα and MTA2 levels were associated with recurrence in 250 tamoxifen-treated patients. CONCLUSION: Loss of Rho GDIα enhances metastasis and resistance to tamoxifen via effects on both ERα and MTA2 in models of ERα-positive breast cancer and in tumors of tamoxifen-treated patients.

Estrogen receptor mutations and changes in downstream gene expression and signaling.

Estrogens play a crucial role in regulating the growth and differentiation of breast cancers, with approximately two thirds of all breast tumors expressing the estrogen receptor alpha (ERalpha). Therefore, therapeutic strategies directed at inhibiting the action of ERalpha by using anti-estrogens such as tamoxifen, or reducing estrogens levels by using aromatase inhibitors, such as letrozole, anastrozole, or exemestane, are the standard treatments offered to women with ERalpha-positive cancer. However, not all patients respond to endocrine therapies (termed de novo resistance), and a large number of patients who do respond will eventually develop disease progression or recurrence while on therapy (acquired resistance). Recently, variant forms of the receptor have been identified owing to alternative splicing or gene mutation. This article reviews these variant receptors and their clinical relevance in resistance to endocrine therapy, by addressing their molecular cross-talk with growth factor receptors and signaling components. Understanding the complexity of receptor-mediated signaling has promise for new combined therapeutic options that focus on more efficient blockade of receptor cross-talk.