Petricoin, EF

Abstract Background: The explosion in new treatment options targeting immune checkpoints, HER signaling, DNA repair deficiency, AKT, and other pathways calls for updated breast cancer subtypes beyond HR and HER2 status to predict which patients will respond to which treatments. Here we leverage the I-SPY 2 TRIAL biomarker program over the past 8 years across 10 treatment arms to elucidate a minimal set of biomarkers that may improve response prediction in a modern treatment context, and to investigate which new patient phenotypes are identified by these response-predictive biomarkers. Methods: 986 patients were considered in this analysis. Treatments included paclitaxel alone (or with trastuzumab (H) in HER2+) or combined with investigational agents: veliparib/carboplatin (VC); neratinib; MK2206; ganitumab; ganetespib; AMG386; TDM1/pertuzumab (P); H/P; and pembrolizumab (Pembro). 24 prospectively defined, mechanism-of-action and pathway-based expression and phospho-protein signatures/biomarkers assayed from pre-treatment biopsies were previously found to be predictive in a particular agent/arm in pre-specified analysis. Here we evaluate these biomarkers in all patients. We assessed association between each biomarker and response in the population as a whole and within each arm and HR/HER2 subtype using a logistic model. To identify optimal dichotomizing thresholds for select biomarkers, 2-fold cross-validation was repeated 500 times. Our analysis is exploratory and does not adjust for multiplicities. Results: Our initial set of 24 predictive biomarkers reflects DNA repair deficiency (n=2), immune activation (n=7), ER signaling (n=2), HER2 signaling (n=4), proliferation (n=2), phospho-activation of AKT/mTOR (n=2), and ANG/TIE2 (n=1) pathways, among others. Biomarkers reflecting similar biology are correlated and cluster together. We make use of this correlation structure to reduce the dimensionality of the biomarker set to five predictive signals: proliferation, DNA repair deficiency (DRD), immune-engaged (Immune+), luminal/ER (lum), and HER2-activated. These biomarkers, when dichotomized, identify patient groups with differential predicted sensitivities to I-SPY 2 agents and are present at different proportions within receptor subtypes. For instance, in the HER2- subset, Immune+/DRD+ patients are predicted sensitive to both VC and Pembro, and account for 39% of TN, but only 12% of HR+HER2-. On the other end of the spectrum, only 17% of TN are Immune-/DRD-, compared to the majority (56%) of HR+HER2-. There are also subsets of patients positive for only one marker. For the HER2+ subset, 67% are HER2-activated+, and 25% lum+; of these HER2-activated+ patients are more likely to be Immune+ (44%), vs 23% in lum+. HER2-activated+/Immune+ patients have higher predicted sensitivity to HER2-targeted agents than lum+ or Immune- patients. In all, these molecular phenotypes predict sensitivity to one or more I-SPY 2 investigational agents for 75% of the ˜ 1000 patients. Conclusion: Molecular phenotypes reflecting proliferation, immune engagement, HER2-activation, luminal/ER-signaling, and DNA repair deficiency may provide a roadmap to guide treatment prioritization for emerging therapeutics. Citation Format: Wolf DM, Yau C, Wulfkuhle J, Petricoin E, Campbell M, Brown-Swigart L, Hirst G, Asare S, Zhu Z, Lee EP, Delson A, Pohlmann P, I-SPY 2 TRIAL Consortium, Hylton N, Liu MC, Symmans F, DeMichele A, Yee D, Berry D, Esserman L, van 't Veer L. Identifying breast cancer molecular phenotypes to predict response in a modern treatment landscape: Lessons from ˜1000 patients across 10 arms of the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-10-02.

Abstract Background: While genomic alterations are central players in tumor progression, proteins are the targets for precision therapy. The degree by which “actionable” genomic alterations translate into activated/altered proteins and pathway is still under investigation. Using a multi-OMIC approach from the SideOut 2 metastatic breast cancer (MBC) trial, this study explored the concordance between selected “actionable” genomic alterations and protein expression/activation. Methods: Snap frozen biopsies from 29 MBC patients enrolled in a prospective phase II trial were used for this analysis. Exome WES and RNASeq data was processed using an in-house developed pipeline and identified amplification of CCND1 (6/29), FGFR1 (4/29), and FGF 3, 4, 5, and 19 (4/29) as some of most frequent “actionable” genomic alterations in our MBC cohort. Signaling analysis of the 29 cases was performed using Reverse Phase Protein Microarray coupled with Laser Capture Microdissection. Protein expression/phosphorylation was measured in a continuous scale and classified based on quartile distribution. Concordance between CCND1 amplification and Cyclin D1 expression, along with the activation of FOXM1 T600 and Rb S780, was explored. Amplification of the FGFR1 locus or its ligands was correlated with the level of activation/phosphorylation of FGFR1 Y653/654. Results: While Cyclin D1 protein expression was greater than the population mean for 4/6 (67%) patients with CCND1 amplification, only 2/6 (33%) patients with CCND1 amplification had Cyclin D1 level within the top quartile of the population (n=29). FOXM1 T600 activation was independent from CCND1 amplification, with high levels of FOXM1 T600 predominantly in the CCND1 wild-type population. Only 1/6 (17%) patients with CCND1 amplification had FOXM1 T600 level similar to the top quartile of the population while a second patient was above the population median. Activation of Rb S780 was above the population median, but below the top quartile, in 2/6 (33%) CCND1 amplified patients. Similarly, none of the patients with activation of FGFR Y653/654 equal to the top quartile harbored an FGFR1 amplification. Only 1/4 (25%) patients carrying an FGFR1 amplification had an activation of FGFR Y653/654 above the population median. Similarly, 1/4 (25%) patients with FGF ligand amplification showed FGFR Y653/654 level within the top quartile while three patients had FGFR Y653/654 activation below the population median. No significant results were found between proteomic (below/above the median) and genomic characteristics by Fisher test (p>0.05). Conclusion: Molecular genotyping of “actionable” cancer targets alone may be insufficient in predicting whether the actual drug target protein is expressed and/or activated in any given patient's tumor. Although these results need further validation, the combination of genomic and proteomic data may represent a more informative approach for identifying real molecular drivers of individual lesions as well as “actionable” protein/phosphoprotein targets in the absence of genomic events. Multi-OMIC approaches may lead to more effective stratification in precision medicine trials. Citation Format: Pierobon M, Wong S, Reeded A, Anthony S, Robert N, Northfelt DW, Jahanzeb M, Vocila L, Wulfkuhle J, Dunetz B, Aldrich J, Byron S, Craig D, Liotta L, Carpten J, Petricoin EF. A multi-OMIC analysis to explore the impact of “actionable” genomic alterations on protein pathway activation: Clinical implication for precision medicine in metastatic breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-07-09.

Abstract Background: The identification of organ-specific targetable signatures may help design more effective treatment for patients with metastatic breast cancer (MBC). We took a multi-OMIC approach to assess whether the AKT-mTOR pathway is globally activated during metastatic progression or whether it represents an organ-specific target. Methods: Snap frozen biopsies from 25 MBC patients enrolled in a prospective phase II trial were used. Sites of metastasis were classified as liver (n=8) and others (n=17), the latter including cutaneous, lung, lymph nodes, and intra-abdominal lesions. Signaling analysis of the 25 cases was performed using Reverse Phase Protein Microarray (RPPA) coupled with Laser Capture Microdissection. Activation of the AKT-mTOR pathway was quantified as phosphorylation of AKT (S473) and the mTOR target p70S6 (T389). Matched exome (WES) and RNASeq data were available for 17 of 25 patients, five with liver metastases. Sequencing data was processed using an in-house developed pipeline to identify somatic events including coding mutations, copy number alterations, gene fusions, and differential expression. Activation of the AKT-mTOR pathway and sequencing data were compared between hepatic and non-hepatic lesions using an integrated RPPA and genomic approach. Results: Among liver metastases, AKT was activated in 4 of the 8 (50.0%) patients, while 6 of the 8 cases (75.0%) showed activation of p70S6. Sequencing data revealed mutation of PIK3CA in 4 of the 5 liver metastases (80.0%). Three of the PIK3CA mutated specimens with catalytic domain mutations (codons 1023 and 147) demonstrated co-activation of AKT and p70S6, while the fourth case, containing a helical domain mutation (E542K), had activation of p70S6 only. The PIK3CA wild-type liver metastasis demonstrated low activation of AKT and p70S6. For non-hepatic metastases AKT was activated in 2 of the 17 cases (11.8%) and p70S6 in 5 of the 17 patients (29.4%). Discussion: Although these results need further validation, activation of the AKT-mTOR pathway appears to be a hepatic specific signature in MBC and could be used for the selection of targeted agents for hepatic lesions. Citation Format: Pierobon M, Wong S, Reeder A, Anthony SP, Robert NJ, Northfelt DW, Jahanzeb M, Vocila L, Wulfkuhle J, Dunetz B, Aldrich J, Byron S, Craig D, Liotta L, Petricoin EF, Carpten J. The AKT-mTOR pathway as a potential organ-specific drug target signature of hepatic metastases from breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-05-21.