Dunetz, Bryant

This prospective phase II clinical trial (Side Out 2) explored the clinical benefits of treatment selection informed by multi‐omic molecular profiling (MoMP) in refractory metastatic breast cancers (MBCs). Core needle biopsies were collected from 32 patients with MBC at trial enrollment. Patients had received an average of 3.94 previous lines of treatment in the metastatic setting before enrollment in this study. Samples underwent MoMP, including exome sequencing, RNA sequencing (RNA‐Seq), immunohistochemistry, and quantitative protein pathway activation mapping by Reverse Phase Protein Microarray (RPPA). Clinical benefit was assessed using the previously published growth modulation index (GMI) under the hypothesis that MoMP‐selected therapy would warrant further investigation for GMI ≥ 1.3 in ≥ 35% of the patients. Of the 32 patients enrolled, 29 received treatment based on their MoMP and 25 met the follow‐up criteria established by the trial protocol. Molecular information was delivered to the tumor board in a median time frame of 14 days (11–22 days), and targetable alterations for commercially available agents were found in 23/25 patients (92%). Of the 25 patients, 14 (56%) reached GMI ≥ 1.3. A high level of DNA topoisomerase I (TOPO1) led to the selection of irinotecan‐based treatments in 48% (12/25) of the patients. A pooled analysis suggested clinical benefit in patients with high TOPO1 expression receiving irinotecan‐based regimens (GMI ≥ 1.3 in 66.7% of cases). These results confirmed previous observations that MoMP increases the frequency of identifiable actionable alterations (92% of patients). The MoMP proposed allows the identification of biomarkers that are frequently expressed in MBCs and the evaluation of their role as predictors of response to commercially available agents. Lastly, this study confirmed the role of MoMP for informing treatment selection in refractory MBC patients: more than half of the enrolled patients reached a GMI ≥ 1.3 even after multiple lines of previous therapies for metastatic disease.

Abstract Background: Although the efficacy of different immunotherapeutic agents varies greatly across tumor types, little is known about the role of different metastatic tumor microenvironments in modulating the expression of immune-checkpoints like PD-L1. Using metastatic breast cancer as a model, this work explored whether metastatic lesions derived from different patients, but colonizing the same host target organ, showed organ-specific immune signatures. Methods: Snap frozen metastatic lesions collected from 30 breast cancer patients enrolled in a prospective phase II multi-omic precision medicine clinical trial (“Side-Out II”) were used for this analysis. Sites of metastasis were: liver (LI) (n=10), skin/chest wall (SC) (n=10), and other lesions (OL) (n=10) [including lymph nodes (LN) (n=4), lung (LU) (n=3), and intra-abdominal lesions (IA) (n=3)]. Pure tumor epithelia were isolated from each specimen via Laser Capture Microdissection (LCM). PD-L1 expression (Antibody Clone E1L3N) was quantitatively measured using the Reverse Phase Protein Microarray (RPPA), a high-throughput, multiplex immunoassay that provides operator-independent quantitative data starting from a small amount of biological material. Proportion of patients with PD-L1 expression above the median and the 75th percentile of the population was compared across metastatic sites. Results: PD-L1 expression had a >5 fold dynamic range across breast cancer-derived metastatic lesions with different distribution across metastatic sites. Specifically, PD-L1 expression of 6/10 LIs, 5/10 OLs (including 2 LU and 3 LN positive lesions), and 4/10 SC metastases was greater than the population median of all metastases combined. LI metastases were the most represented group above the 75th percentile of the population (4/10), followed by OS (2/10) (including 1 LU and 1 LN positive lesions), and SC (1/10). Of the 15 lesions above the population median, 6 were LI (40%), 5 were OS (33%), and 4 were SC (27%); of the 7 metastases above the 75th percentile, 4 were LI (57%), 2 were OS (29%), and 1 was SC (14%). Conclusions: The LCM-RPPA workflow can capture PD-L1 protein expression on a continuous quantitative scale and provide a broader understanding of the dynamic range of expression. Our data suggest that organ specific microenvironments in which metastatic lesions develop may strongly influence overall PD-L1 tumor cell expression. If different metastatic host organs can modulate PD-L1 expression, location of the metastatic lesion should be kept in consideration when selecting patients that are candidates for immunotherapy. Such hypotheses should be further validated in prospective clinical trial where quantitative PD-L1 expression of different metastatic lesions is evaluated along with response to targeted immuno-oncology compounds. Citation Format: Mariaelena Pierobon, K Alex Hodge, Elisa Baldelli, Steven Anthony, Nicholas J. Robert, Donald W. Northfelt, Mohammad J. Jahanzeb, Linda Vocila, Lance A. Liotta, Bryant Dunetz, Emanuel F. Petricoin. PD-L1 expression differs across cancer metastatic sites from breast tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3129.

Abstract Background: The efficacy of immunotherapy, including therapeutic strategies capable of modulating innate/adaptive immune resistance, varies greatly across tumor types. As the number of available immunotherapies accelerates, the study of predictive markers by IHC (e.g. PDL1 expression) is under intense investigation. However, staining protocol inconsistency, variation across scoring systems, and subjective interpretation of the immunostaining have produced conflicting results thus far. This work explored the role of Laser Capture Microdissection (LCM) coupled with Reverse Phase Protein Microarray (RPPA) as an alternative high throughput, quantitative, operator independent platform for measuring PDL1 expression across tumor types. Material and Methods: Pure epithelial cells were isolated via LCM from 178 samples including: 72 ovarian cancers (OC), 57 lung adenocarcinomas (LC), 30 metastatic breast cancers (MBC), and 19 pancreatic cancers (PC). PDL1 expression was measured on a continuous scale using quantitative RPPA based analysis. Each tumor type was processed and arrayed independently. Experimental samples and reference standards used for inter-assay normalization were printed in triplicates. Results: PDL1 expression varied greatly across tumor types. LC were characterized by the greatest intra-tumor fold dynamic range (> 35-fold), followed by OC (< 13-fold), MBC (< 4-fold), and PC (< 2-fold). PDL1 expression of 46/57 (80.7%) LC, 17/30 (56.7%) MBC, 6/19 (31.5%) PC, and 20/72 (27.8%) OC was greater than the population median of all tumors combined. Within the LC samples with PDL1 expression equal to the top quartile of the population, 10 (71.4%) were KRAS mutant lesions and 4 (28.6%) were WT tumors. Finally, amongst LC and PC harboring a KRAS mutation, PC showed an overall lower expression of PDL1 with only 2/19 (10.5%) cases been above the population median and none within the top quartile of the population. Conclusions: The LCM-RPPA workflow has the unique ability to capture immune checkpoint expression on a continuous quantitative scale as well as capture its broad dynamic range. Because RPPA is unconstrained by antigen retrieval issues as well as subjectivity of IHC interpretation, this approach may generate more accurate cut-point of therapeutic response prediction. Overall the dynamic range of PDL1 was broader in LC compared to other solid tumors, and LC had a much higher proportion of patients with tumors expressing high levels of PDL1. These quantitative differences may explain therapeutic efficacy of PDL1 inhibition across tumor types. Such speculative hypothesis should be further validated in prospective clinical trials. Finally, these preliminary data suggest that organ specific microenvironments more than specific driving mutations (e.g. KRAS) may strongly influence PDL1 expression in malignant lesions. Citation Format: Elisa Baldelli, Valerie Calvert, K. Alex Hodge, Maria Isabella Sereni, Guido Gambara, Eric B. Haura, Lucio Crino', Bryant Dunetz, Sergio Pecorelli, David J. Perry, Stephen P. Anthony, Nicholas Robert, Donald W. Northfelt, Mohammad Jahanzeb, Emanuel F. Petricoin, Mariaelena Pierobon. Quantitative measurement of PDL1 expression across tumor types using laser capture microdissection and reverse phase protein microarray [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5656. doi:10.1158/1538-7445.AM2017-5656

Abstract Purpose: Little is known about the molecular signatures associated with specific metastatic sites in breast cancer. Using comprehensive multi-omic molecular profiling, we assessed whether alterations or activation of the PI3K–AKT–mTOR pathway is associated with specific sites of breast cancer metastasis. Experimental Design: Next-generation sequencing–based whole-exome sequencing was coupled with reverse-phase protein microarray (RPPA) functional signaling network analysis to explore the PI3K–AKT–mTOR axis in 32 pretreated breast cancer metastases. RPPA-based signaling data were further validated in an independent cohort of 154 metastatic lesions from breast cancer and 101 unmatched primary breast tumors. The proportion of cases with PI3K–AKT–mTOR genomic alterations or signaling network activation were compared between hepatic and nonhepatic lesions. Results: PIK3CA mutation and activation of AKT (S473) and p70S6K (T389) were detected more frequently among liver metastases than nonhepatic lesions (P < 0.01, P = 0.056, and P = 0.053, respectively). However, PIK3CA mutations alone were insufficient in predicting protein activation (P = 0.32 and P = 0.19 for activated AKT and p70S6K, respectively). RPPA analysis of an independent cohort of 154 tumors confirmed the relationship between pathway activation and hepatic metastasis [AKT (S473), mTOR (S2448), and 4EBP1 (S65); P < 0.01, P = 0.02, and P = 0.01, respectively]. Similar results were also seen between liver metastases and primary breast tumors [AKT (S473) P < 0.01, mTOR (S2448) P < 0.01, 4EBP1 (S65) P = 0.01]. This signature was lost when primary tumors were compared with all metastatic sites combined. Conclusions: Breast cancer patients with liver metastasis may represent a molecularly homogenized cohort with increased incidence of PIK3CA mutations and activation of the PI3K–AKT–mTOR signaling network. Clin Cancer Res; 23(16); 4919–28. ©2017 AACR.

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.

Abstract Background: The development of distant metastases is the strongest prognostic factor associated with cancer mortality. Customization of treatment based on molecular profiling of a patient’s primary tumor has yielded promising results and has opened a new paradigm for treating patients with advanced disease. Nevertheless profiling the primary tumor may not reflect the actionable molecular drivers of the metastatic lesions. In the last few years a large number of genomic and proteomic studies have demonstrated that at the molecular level metastatic lesions significantly differ from matched primary tumors. The impact of metastasis site organ microenvironments on breast cancer primary tumors has been only partially explored. Since most targeted therapies work by modulating aberrantly-activated protein kinase signaling, the aim of this study was to utilize reverse phase protein arrays (RPPA) to explore whether metastatic lesions derived from different patients, but invading the same host target organ showed similarities in their signaling architecture and presented with organ-specific targetable signatures. Methods: Snap frozen material collected from 14 metastatic breast cancer patients enrolled in a prospective phase II trial ("Side Out II") were used for this analysis. Sites of metastasis were: liver (n=7), skin/chest wall (n=4), and lung (n=3). All samples were subjected to Laser Capture Microdissection (LCM) and RPPA to measure the activation/phosphorylation levels of 12 FDA approved drug targets and linked substrates. Results: Among the 7 patients with liver metastases, p70S6K, c-Abl, ERK 1/2 were highly phosphorylated in 5 cases (71.4%), ErbB2/HER2 in 4 cases (57.1%), and AKT in 3 cases (42.8%). On the contrary, of the 4 patients with skin/chest wall lesions 3 showed high activation of ErbB2/HER2, ErbB3/HER3, and ERK 1/2 (75.0%) and 2 of EGFR (50.0%). Of note, none of the skin/chest wall lesions showed activation of AKT and only 1 case presented with activated p70S6K (25.0%). Lung metastasis showed an overall low activation of all 12 analytes measured. Discussion: Although this data is based on a relatively small number of samples and needs further validation, our initial analysis revealed potentially important trends that could have an impact in the prioritization and selection of targeted agents for metastatic breast cancer trials. We found that the distribution of the 12 FDA approved drug targets and downstream substrates varies between different metastatic sites. Thus, the emergent hypothesis from this work is that breast cancer patients with liver metastases may be more susceptible to AKT-mTOR directed targeted therapeutics and patients with skin/chest wall metastasis may benefit from therapies that target EGFR and/or downstream ERK signaling. Citation Format: Mariaelena Pierobon, Stephen P Anthony, K Alex Reeder, Nicholas J Robert, Donald W Northfelt, Mohammad Jahanzeb, Linda Vocila, Julia D Wulfkuhle, Bryant Dunetz, Lance A Liotta, Emanuel F Petricoin. Pathway activation mapping of metastatic breast cancer identifies potential organ-specific signatures: Implications for patient stratification to targeted treatment [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-07-23.