Druggable genomic landscapes of high-grade gliomas.

Background: Despite the putatively targetable genomic landscape of high-grade gliomas, the long-term survival benefit of genomically-tailored targeted therapies remains discouraging. Methods: Using glioblastoma (GBM) as a representative example of high-grade gliomas, we evaluated the clonal architecture and distribution of hotspot mutations in 388 GBMs from the Cancer Genome Atlas (TCGA). Mutations were matched with 54 targeted therapies, followed by a comprehensive evaluation of drug biochemical properties in reference to the drug's clinical efficacy in high-grade gliomas. We then assessed clinical outcomes of a cohort of patients with high-grade gliomas with targetable mutations reviewed at the Johns Hopkins Molecular Tumor Board (JH MTB; n = 50). Results: Among 1,156 sequence alterations evaluated, 28.6% represented hotspots. While the frequency of hotspot mutations in GBM was comparable to cancer types with actionable hotspot alterations, GBMs harbored a higher fraction of subclonal mutations that affected hotspots (7.0%), compared to breast cancer (4.9%), lung cancer (4.4%), and melanoma (1.4%). In investigating the biochemical features of targeted therapies paired with recurring alterations, we identified a trend toward higher lipid solubility and lower IC50 in GBM cell lines among drugs with clinical efficacy. The drugs' half-life, molecular weight, surface area and binding to efflux transporters were not associated with clinical efficacy. Among the JH MTB cohort of patients with IDH1 wild-type high-grade gliomas who received targeted therapies, trametinib monotherapy or in combination with dabrafenib conferred radiographic partial response in 75% of patients harboring BRAF or NF1 actionable mutations. Cabozantinib conferred radiographic partial response in two patients harboring a MET and a PDGFRA/KDR amplification. Patients with IDH1 wild-type gliomas that harbored actionable alterations who received genotype-matched targeted therapy had longer progression-free (PFS) and overall survival (OS; 7.37 and 14.72 respectively) than patients whose actionable alterations were not targeted (2.83 and 4.2 months respectively). Conclusion: While multiple host, tumor and drug-related features may limit the delivery and efficacy of targeted therapies for patients with high-grade gliomas, genotype-matched targeted therapies confer favorable clinical outcomes. Further studies are needed to generate more data on the impact of biochemical features of targeted therapies on their clinical efficacy for high-grade gliomas.

Precision Oncology Core Data Model to Support Clinical Genomics Decision Making.

PURPOSE: Precision oncology mandates developing standardized common data models (CDMs) to facilitate analyses and enable clinical decision making. Expert-opinion-based precision oncology initiatives are epitomized in Molecular Tumor Boards (MTBs), which process large volumes of clinical-genomic data to match genotypes with molecularly guided therapies. METHODS: We used the Johns Hopkins University MTB as a use case and developed a precision oncology core data model (Precision-DM) to capture key clinical-genomic data elements. We leveraged existing CDMs, building upon the Minimal Common Oncology Data Elements model (mCODE). Our model was defined as a set of profiles with multiple data elements, focusing on next-generation sequencing and variant annotations. Most elements were mapped to terminologies or code sets and the Fast Healthcare Interoperability Resources (FHIR). We subsequently compared our Precision-DM with existing CDMs, including the National Cancer Institute's Genomic Data Commons (NCI GDC), mCODE, OSIRIS, the clinical Genome Data Model (cGDM), and the genomic CDM (gCDM). RESULTS: Precision-DM contained 16 profiles and 355 data elements. 39% of the elements derived values from selected terminologies or code sets, and 61% were mapped to FHIR. Although we used most elements contained in mCODE, we significantly expanded the profiles to include genomic annotations, resulting in a partial overlap of 50.7% between our core model and mCODE. Limited overlap was noted between Precision-DM and OSIRIS (33.2%), NCI GDC (21.4%), cGDM (9.3%), and gCDM (7.9%). Precision-DM covered most of the mCODE elements (87.7%), with less coverage for OSIRIS (35.8%), NCI GDC (11%), cGDM (26%) and gCDM (33.3%). CONCLUSION: Precision-DM supports clinical-genomic data standardization to support the MTB use case and may allow for harmonized data pulls across health care systems, academic institutions, and community medical centers.

Artificial Intelligence-Assisted Serial Analysis of Clinical Cancer Genomics Data Identifies Changing Treatment Recommendations and Therapeutic Targets.

PURPOSE: Given the pace of predictive biomarker and targeted therapy development, it is unknown whether repeat annotation of the same next-generation sequencing data can identify additional clinically actionable targets that could be therapeutically leveraged. In this study, we sought to determine the predictive yield of serial reanalysis of clinical tumor sequencing data. EXPERIMENTAL DESIGN: Using artificial intelligence (AI)-assisted variant annotation, we retrospectively reanalyzed sequencing data from 2,219 patients with cancer from a single academic medical center at 3-month intervals totaling 9 months in 2020. The yield of serial reanalysis was assessed by the proportion of patients with improved strength of therapeutic recommendations. RESULTS: A total of 1,775 patients (80%) had ≥1 potentially clinically actionable mutation at baseline, including 243 (11%) patients who had an alteration targeted by an FDA-approved drug for their cancer type. By month 9, the latter increased to 458 (21%) patients mainly due to a single pan-cancer agent directed against tumors with high tumor mutation burden. Within this timeframe, 67 new therapies became available and 45 were no longer available. Variant pathogenicity classifications also changed leading to changes in treatment recommendations for 124 patients (6%). CONCLUSIONS: Serial reannotation of tumor sequencing data improved the strength of treatment recommendations (based on level of evidence) in a mixed cancer cohort and showed substantial changes in available therapies and variant classifications. These results suggest a role for repeat analysis of tumor sequencing data in clinical practice, which can be streamlined with AI support.

An Evaluation of Pretrained BERT Models for Comparing Semantic Similarity Across Unstructured Clinical Trial Texts.

Processing unstructured clinical texts is often necessary to support certain tasks in biomedicine, such as matching patients to clinical trials. Among other methods, domain-specific language models have been built to utilize free-text information. This study evaluated the performance of Bidirectional Encoder Representations from Transformers (BERT) models in assessing the similarity between clinical trial texts. We compared an unstructured aggregated summary of clinical trials reviewed at the Johns Hopkins Molecular Tumor Board with the ClinicalTrials.gov records, focusing on the titles and eligibility criteria. Seven pretrained BERT-Based models were used in our analysis. Of the six biomedical-domain-specific models, only SciBERT outperformed the original BERT model by accurately assigning higher similarity scores to matched than mismatched trials. This finding is promising and shows that BERT and, likely, other language models may support patient-trial matching.

Core Outcome Sets for Medium-Chain Acyl-CoA Dehydrogenase Deficiency and Phenylketonuria.

BACKGROUND: Evidence to guide treatment of pediatric medium-chain acyl-coenzyme A dehydrogenase (MCAD) deficiency and phenylketonuria (PKU) is fragmented because of large variability in outcome selection and measurement. Our goal was to develop core outcome sets (COSs) for these diseases to facilitate meaningful future evidence generation and enhance the capacity to compare and synthesize findings across studies. METHODS: Parents and/or caregivers, health professionals, and health policy advisors completed a Delphi survey and participated in a consensus workshop to select core outcomes from candidate lists of outcomes for MCAD deficiency and PKU. Delphi participants rated the importance of outcomes on a nine-point scale (1-3: not important, 4-6: important but not critical, 7-9: critical). Candidate outcomes were progressively narrowed down over 3 survey rounds. At the workshop, participants evaluated the remaining candidate outcomes using an adapted nominal technique, open discussion, and voting. After the workshop, we finalized the COSs and recommended measurement instruments for each outcome. RESULTS: There were 85, 61, and 53 participants across 3 Delphi rounds, respectively. The candidate core outcome lists were narrowed down to 20 outcomes per disease to be discussed at the consensus workshop. Voting by 18 workshop participants led to COSs composed of 8 and 9 outcomes for MCAD deficiency and PKU, respectively, with measurement recommendations. CONCLUSIONS: These are the first known pediatric COSs for MCAD deficiency and PKU. Adoption in future studies will help to ensure best use of limited research resources to ultimately improve care for children with these rare diseases.

Management of Breast Cancer During the COVID-19 Pandemic: A Stage- and Subtype-Specific Approach.

The COVID-19 pandemic has rapidly changed delivery of cancer care. Many nonurgent surgeries are delayed to preserve hospital resources, and patient visits to health care settings are limited to reduce exposure to SARS-CoV-2. Providers must carefully weigh risks and benefits of delivering immunosuppressive therapy during the pandemic. For breast cancer, a key difference is increased use of neoadjuvant systemic therapy due to deferral of many breast surgeries during the pandemic. In some cases, this necessitates increased use of genomic tumor profiling on core biopsy specimens to guide neoadjuvant therapy decisions. Breast cancer treatment during the pandemic requires multidisciplinary input and varies according to stage, tumor biology, comorbidities, age, patient preferences, and available hospital resources. We present here the Johns Hopkins Women's Malignancies Program approach to breast cancer management during the COVID-19 pandemic. We include algorithms based on tumor biology and extent of disease that guide management decisions during the pandemic. These algorithms emphasize medical oncology treatment decisions and demonstrate how we have operationalized the general treatment recommendations during the pandemic proposed by national groups, such as the COVID-19 Pandemic Breast Cancer Consortium. Our recommendations can be adapted by other institutions and medical oncology practices in accordance with local conditions and resources. Guidelines such as these will be important as we continue to balance treatment of breast cancer against risk of SARS-CoV-2 exposure and infection until approval of a vaccine.

Use of complementary and alternative medicine in patients with inborn errors of metabolism: A single-center study.

BACKGROUND AND OBJECTIVES: There is a paucity of information on the use of complementary and alternative medicine (CAM) in patients with inborn errors of metabolism (IEM). This study's objective was to evaluate the self-reported use and perceived effectiveness of CAM in adults and children with IEM. METHODS: Patients aged 0-70 years and caregivers seen at the London Health Sciences Centre Metabolic Clinic (London, Ontario, Canada) between July 2017 and August 2017 were recruited to complete a questionnaire regarding CAM use to help their IEM diagnosis and perceived effectiveness of these therapies. Survey responses were analyzed using descriptive statistics; age, sex, and education level associations among CAM users were tested using the Pearson χ 2 test. RESULTS: Of 50 potential participants, 44 (88%) completed the questionnaire, including 21 adults (6 by caregivers) and 23 children (22 by caregivers). The most common IEM category was Aminoacidopathies and Small Molecule Disorders (50%). Twenty-seven (61%) participants reported CAM use to help their IEM diagnosis. The most common CAM therapies used were chiropractic manipulation, omega-3 fatty acids, probiotics, and aromatherapy/essential oils. Most CAM users and caregivers (74%) perceived their CAM therapies as effective overall. Among CAM users, 40% had not discussed CAM use with a health care professional (HCP). CAM use was similar when comparing age, sex and education level. CONCLUSIONS: CAM is commonly used among patients with IEM. The safety and efficacy of CAM therapies for IEM should be further investigated. HCPs and patients should openly discuss CAM use in order to evaluate safety.

Outcomes in pediatric studies of medium-chain acyl-coA dehydrogenase (MCAD) deficiency and phenylketonuria (PKU): a review.

BACKGROUND: Inherited metabolic diseases (IMDs) are a group of individually rare single-gene diseases. For many IMDs, there is a paucity of high-quality evidence that evaluates the effectiveness of clinical interventions. Clinical effectiveness trials of IMD interventions could be supported through the development of core outcome sets (COSs), a recommended minimum set of standardized, high-quality outcomes and associated outcome measurement instruments to be incorporated by all trials in an area of study. We began the process of establishing pediatric COSs for two IMDs, medium-chain acyl-CoA dehydrogenase (MCAD) deficiency and phenylketonuria (PKU), by reviewing published literature to describe outcomes reported by authors, identify heterogeneity in outcomes across studies, and assemble a candidate list of outcomes. METHODS: We used a comprehensive search strategy to identify primary studies and guidelines relevant to children with MCAD deficiency and PKU, extracting study characteristics and outcome information from eligible studies including outcome measurement instruments for select outcomes. Informed by an established framework and a previously published pediatric COS, outcomes were grouped into five, mutually-exclusive, a priori core areas: growth and development, life impact, pathophysiological manifestations, resource use, and death. RESULTS: For MCAD deficiency, we identified 83 outcomes from 52 articles. The most frequently represented core area was pathophysiological manifestations, with 33 outcomes reported in 29/52 articles (56%). Death was the most frequently reported outcome. One-third of outcomes were reported by a single study. The most diversely measured outcome was cognition and intelligence/IQ for which eight unique measurement instruments were reported among 14 articles. For PKU, we identified 97 outcomes from 343 articles. The most frequently represented core area was pathophysiological manifestations with 31 outcomes reported in 281/343 articles (82%). Phenylalanine concentration was the most frequently reported outcome. Sixteen percent of outcomes were reported by a single study. Similar to MCAD deficiency, the most diversely measured PKU outcome was cognition and intelligence/IQ with 39 different instruments reported among 82 articles. CONCLUSIONS: Heterogeneity of reported outcomes and outcome measurement instruments across published studies for both MCAD deficiency and PKU highlights the need for COSs for these diseases, to promote the use of meaningful outcomes and facilitate comparisons across studies.

Demonstrating the impact of POLST forms on hospital care requires information not contained in state registries.

BACKGROUND: Physician Orders for Life-Sustaining Treatment (POLST) programs have expanded rapidly, but evaluating their impact on hospital care is challenging. OBJECTIVES: To demonstrate how careful study design can reveal POLST's impact at hospital admission and why analyses of state registry data are unlikely to capture POLST's effects. DESIGN: Prospective cohort study. SETTING AND PARTICIPANTS: Adult in-patients with Do Not Intubate and/or Do Not Resuscitate (DNR/I) orders in the electronic medical record at the time of discharge from Johns Hopkins Hospital over 18 months. For patients with unplanned readmissions within 30 days, records were reviewed to determine if a Maryland Medical Order for Life-Sustaining Treatment (MOLST) form was presented and for the time from readmission to a DNR/I order in the EMR. Analyses were stratified by whether patients could communicate or were accompanied by a proxy at readmission. RESULTS: Among 1,507 patients with DNR/I orders at discharge, 124 (8%) had unplanned readmissions, 112 (90%) could communicate or were accompanied by a proxy at readmission, and 12 (10%) could not communicate and were unaccompanied. For patients who were unaccompanied and could not communicate, MOLST significantly decreased the median time from readmission to DNR/I order (1.2 vs 27.1 hours, P = .001), but this association was greatly attenuated among patients who could communicate or were accompanied by a proxy (16.4 vs 25.4 hours P = .10). CONCLUSION: Among patients who wanted to avoid intubation and/or CPR, MOLST forms were protective when the patient was unaccompanied by a healthcare proxy at admission and could not communicate. Fewer than 10% of patients met these criteria during unplanned readmissions, and state registry data does not allow this sub-population to be identified.

First-in-Human Phase I Study of the Activin A Inhibitor, STM 434, in Patients with Granulosa Cell Ovarian Cancer and Other Advanced Solid Tumors.

PURPOSE: STM 434 is a soluble receptor ligand trap targeting activin A, a protein in the TGFß family that plays important roles in growth, differentiation, and cancer cachexia. This study evaluated the safety, antitumor activity, and metabolic effects of STM 434 in a first-in-human, multicenter, phase I clinical trial (NCT02262455). PATIENTS AND METHODS: Patients with advanced solid tumors were enrolled in 8 dose cohorts ranging from 0.25 mg/kg every 4 weeks to 8 mg/kg every 2 weeks via a 3 + 3 dose-escalation design. The primary endpoint was maximum tolerated dose (MTD). Secondary endpoints included safety, pharmacokinetics, and response. As activin A is implicated in metabolism and muscle function, changes in key metabolic parameters, including lean body mass and 6-minute walk test, were serially measured. RESULTS: Thirty-two patients were treated on study. The most common treatment-related adverse events were fatigue (41%) and mucocutaneous bleeding complications including epistaxis (34%) and gingival bleeding (22%), likely related to off-target inhibition of bone morphogenetic protein 9 (BMP9). STM 434 treatment resulted in the expected follicle-stimulating hormone level decreases in most patients and in metabolic parameter changes, including an increase in total lean body mass and 6-minute walk test distance. No responses were observed in the 30 evaluable patients, but the stable disease rate in patients with granulosa cell ovarian cancer was 10 of 12 (80%). CONCLUSIONS: Although no direct antitumor efficacy was documented, potentially clinically meaningful dose-related metabolic effects, including treatment of cancer cachexia, were observed that support further exploration of activin A inhibitors that limit BMP9 blockade.See related commentary by Bonilla and Oza, p. 5432.

Real-World Outcomes of an Automated Physician Support System for Genome-Driven Oncology.

PURPOSE: Matching patients to investigational therapies requires new tools to support physician decision making. We designed and implemented Precision Insight Support Engine (PRECISE), an automated, just-in-time, clinical-grade informatics platform to identify and dynamically track patients on the basis of molecular and clinical criteria. Real-world use of this tool was analyzed to determine whether PRECISE facilitated enrollment to early-phase, genome-driven trials. MATERIALS AND METHODS: We analyzed patients who were enrolled in genome-driven, early-phase trials using PRECISE at Memorial Sloan Kettering Cancer Center between April 2014 and January 2018. Primary end point was the proportion of enrolled patients who were successfully identified using PRECISE before enrollment. Secondary end points included time from sequencing and PRECISE identification to enrollment. Reasons for a failure to identify genomically matched patients were also explored. RESULTS: Data were analyzed from 41 therapeutic trials led by 19 principal investigators. In total, 755 patients were accrued to these studies during the period that PRECISE was used. PRECISE successfully identified 327 patients (43%) before enrollment. Patients were diagnosed with 29 tumor types and harbored alterations in 43 oncogenes, most commonly ERBB2 (21.3%), PIK3CA (14.1%), and BRAF (8.7%). Median time from sequencing to enrollment was 163 days (interquartile range, 66 to 357 days), and from PRECISE identification to enrollment 87 days (interquartile range, 37 to 180 days). Common reasons for failing to identify patients before enrollment included accrual on the basis of molecular alterations that did not match pre-established PRECISE genomic eligibility (140 [33%] of 428) and external sequencing not available for parsing (127 [30%] of 428). CONCLUSION: PRECISE identified 43% of all patients accrued to a diverse cohort of early-phase, genome-matched studies. Purpose-built informatics platforms represent a novel and potentially effective method for matching patients to molecularly selected studies.

RAF inhibitor PLX8394 selectively disrupts BRAF dimers and RAS-independent BRAF-mutant-driven signaling.

Activating BRAF mutants and fusions signal as RAS-independent constitutively active dimers with the exception of BRAF V600 mutant alleles which can function as active monomers1. Current RAF inhibitors are monomer selective, they potently inhibit BRAF V600 monomers but their inhibition of RAF dimers is limited by induction of negative cooperativity when bound to one site in the dimer1-3. Moreover, acquired resistance to these drugs is usually due to molecular lesions that cause V600 mutants to dimerize4-8. We show here that PLX8394, a new RAF inhibitor9, inhibits ERK signaling by specifically disrupting BRAF-containing dimers, including BRAF homodimers and BRAF-CRAF heterodimers, but not CRAF homodimers or ARAF-containing dimers. Differences in the amino acid residues in the amino (N)-terminal portion of the kinase domain of RAF isoforms are responsible for this differential vulnerability. As a BRAF-specific dimer breaker, PLX8394 selectively inhibits ERK signaling in tumors driven by dimeric BRAF mutants, including BRAF fusions and splice variants as well as BRAF V600 monomers, but spares RAF function in normal cells in which CRAF homodimers can drive signaling. Our work suggests that drugs with these properties will be safe and useful for treating tumors driven by activating BRAF mutants or fusions.

Basket Studies: Redefining Clinical Trials in the Era of Genome-Driven Oncology.

Understanding a tumor's detailed molecular profile has become increasingly necessary to deliver the standard of care for patients with advanced cancer. Innovations in both tumor genomic sequencing technology and the development of drugs that target molecular alterations have fueled recent gains in genome-driven oncology care. "Basket studies," or histology-agnostic clinical trials in genomically selected patients, represent one important research tool to continue making progress in this field. We review key aspects of genome-driven oncology care, including the purpose and utility of basket studies, biostatistical considerations in trial design, genomic knowledgebase development, and patient matching and enrollment models, which are critical for translating our genomic knowledge into clinically meaningful outcomes.

Long term side effects of adjuvant chemotherapy in patients with early breast cancer.

Adjuvant systemic therapy along with screening has been key to the observed improvements in disease-free and overall survival (DFS/OS) in breast cancer. Improvements in overall survival already take into account therapy related toxicities that can result in death. However, this measure alone does not adequately capture the impact on health-related quality of life. Therefore, it is important to examine the prevalence, frequency and short/long-term impact of therapy-related toxicities, identify patients who might be at greatest risk. Ultimately decisions regarding expected therapy benefits (relative and absolute percentage improvements in DFS/OS) must be made against a background of known potential harms. For many patients with early breast cancer (EBC), their risk of recurrence is not zero but is small. At the same time, for many therapies for early stage breast cancer, the risk of serious side effects is small but is not zero. As we better understand the long-term side effects of adjuvant chemotherapy and targeted therapy, it becomes critical to integrate our growing understanding of breast cancer biology with standard high-quality histopathologic measures to better identify the patients most likely to benefit from the various options for combined multimodality therapy. Hence, we must strive against the notion of recommending adjuvant systemic chemotherapy "just in case." This article focuses on the long-term side effects of adjuvant chemotherapy in patients with EBC.

PI3K inhibition results in enhanced estrogen receptor function and dependence in hormone receptor-positive breast cancer.

Activating mutations of PIK3CA are the most frequent genomic alterations in estrogen receptor (ER)-positive breast tumors, and selective phosphatidylinositol 3-kinase α (PI3Kα) inhibitors are in clinical development. The activity of these agents, however, is not homogeneous, and only a fraction of patients bearing PIK3CA-mutant ER-positive tumors benefit from single-agent administration. Searching for mechanisms of resistance, we observed that suppression of PI3K signaling results in induction of ER-dependent transcriptional activity, as demonstrated by changes in expression of genes containing ER-binding sites and increased occupancy by the ER of promoter regions of up-regulated genes. Furthermore, expression of ESR1 mRNA and ER protein were also increased upon PI3K inhibition. These changes in gene expression were confirmed in vivo in xenografts and patient-derived models and in tumors from patients undergoing treatment with the PI3Kα inhibitor BYL719. The observed effects on transcription were enhanced by the addition of estradiol and suppressed by the anti-ER therapies fulvestrant and tamoxifen. Fulvestrant markedly sensitized ER-positive tumors to PI3Kα inhibition, resulting in major tumor regressions in vivo. We propose that increased ER transcriptional activity may be a reactive mechanism that limits the activity of PI3K inhibitors and that combined PI3K and ER inhibition is a rational approach to target these tumors.

Antagonism of EGFR and HER3 enhances the response to inhibitors of the PI3K-Akt pathway in triple-negative breast cancer.

Both abundant epidermal growth factor receptor (EGFR or ErbB1) and high activity of the phosphatidylinositol 3-kinase (PI3K)-Akt pathway are common and therapeutically targeted in triple-negative breast cancer (TNBC). However, activation of another EGFR family member [human epidermal growth factor receptor 3 (HER3) (or ErbB3)] may limit the antitumor effects of these drugs. We found that TNBC cell lines cultured with the EGFR or HER3 ligand EGF or heregulin, respectively, and treated with either an Akt inhibitor (GDC-0068) or a PI3K inhibitor (GDC-0941) had increased abundance and phosphorylation of HER3. The phosphorylation of HER3 and EGFR in response to these treatments was reduced by the addition of a dual EGFR and HER3 inhibitor (MEHD7945A). MEHD7945A also decreased the phosphorylation (and activation) of EGFR and HER3 and the phosphorylation of downstream targets that occurred in response to the combination of EGFR ligands and PI3K-Akt pathway inhibitors. In culture, inhibition of the PI3K-Akt pathway combined with either MEHD7945A or knockdown of HER3 decreased cell proliferation compared with inhibition of the PI3K-Akt pathway alone. Combining either GDC-0068 or GDC-0941 with MEHD7945A inhibited the growth of xenografts derived from TNBC cell lines or from TNBC patient tumors, and this combination treatment was also more effective than combining either GDC-0068 or GDC-0941 with cetuximab, an EGFR-targeted antibody. After therapy with EGFR-targeted antibodies, some patients had residual tumors with increased HER3 abundance and EGFR/HER3 dimerization (an activating interaction). Thus, we propose that concomitant blockade of EGFR, HER3, and the PI3K-Akt pathway in TNBC should be investigated in the clinical setting.

mTORC1 inhibition is required for sensitivity to PI3K p110α inhibitors in PIK3CA-mutant breast cancer.

Activating mutations of the PIK3CA gene occur frequently in breast cancer, and inhibitors that are specific for phosphatidylinositol 3-kinase (PI3K) p110α, such as BYL719, are being investigated in clinical trials. In a search for correlates of sensitivity to p110α inhibition among PIK3CA-mutant breast cancer cell lines, we observed that sensitivity to BYL719 (as assessed by cell proliferation) was associated with full inhibition of signaling through the TORC1 pathway. Conversely, cancer cells that were resistant to BYL719 had persistently active mTORC1 signaling, although Akt phosphorylation was inhibited. Similarly, in patients, pS6 (residues 240/4) expression (a marker of mTORC1 signaling) was associated with tumor response to BYL719, and mTORC1 was found to be reactivated in tumors from patients whose disease progressed after treatment. In PIK3CA-mutant cancer cell lines with persistent mTORC1 signaling despite PI3K p110α blockade (that is, resistance), the addition of the allosteric mTORC1 inhibitor RAD001 to the cells along with BYL719 resulted in reversal of resistance in vitro and in vivo. Finally, we found that growth factors such as insulin-like growth factor 1 and neuregulin 1 can activate mammalian target of rapamycin (mTOR) and mediate resistance to BYL719. Our findings suggest that simultaneous administration of mTORC1 inhibitors may enhance the clinical activity of p110α-targeted drugs and delay the appearance of resistance.