Citations

406 Background: Anxiety is highly prevalent among oncology patients, often arising from uncertainty around diagnosis, treatment options, and prognosis. Elevated anxiety can impair decision-making, reduce treatment adherence, and diminish overall quality of life. Effective second opinion consultations may help mitigate anxiety and increase patients’ confidence in recommending healthcare services to others. Our study evaluates the impact of oncology second opinion (OSO) consultations on anxiety level (AL) and confidence in the organization (CIO) providing the second opinion, i.e., Cincinnati Cancer Advisors (CCA) and Naples Cancer Advisors (NCA). Methods: The study included patients with cancer diagnoses, age ≥18 years, who were served in person for OSO at CCA and NCA. A survey was used before and after consultation, measuring AL (scale 1- 10) and CIO level (scale 1 - 10), assessed by asking patients how likely they would refer loved ones to the organization. After the content and face validation, patients completed the survey anonymously, put it in a sealed envelope, and dropped it in a dedicated box. Data was analyzed using paired t-tests to compare the change from pre- to post-consultation scores. Spearman’s correlation test was used to assess the relation between the changes in AL and CIO. Statistical significance was assessed using an alpha-level of 0.05. Analyses were conducted via R and R Studio (version 2025.5.1.513). Results: Overall, 46 consecutive patients participated (45 completed AL pre and post visit survey and 43 completed the CIO pre and post visit survey). The mean pre-consultation anxiety score was 5.92 (SD = 2.58), and the post-consultation score was 3.87 (SD = 2.10), demonstrating a significant reduction (mean paired difference = -2.05; p < 0.0001). The mean pre-consult CIO was 8.21 (SD = 2.03), increasing to 9.73 post-consultation (SD = 0.53), indicating a significant improvement (mean paired difference = 1.66; p < 0.0001). The correlation between changes in AL and CIO was not statistically significant, which may be attributed to the high baseline CIO scores (ceiling effect) and the small sample size. Conclusions: Oncology second opinion was associated with a marked decrease in patient AL and a significant increase in CIO. The patient survey will continue to recruit additional participants to increase the sample size and explore the correlation between changes in AL and CIO. Studying the downstream impact on patient experience and outcome is warranted.

Abstract Background In 2008, bevacizumab received accelerated Food and Drug Administration (FDA) approval for use in human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC). Based on the preclinical and preliminary clinical activity of the trastuzumab and bevacizumab combination, ECOG-ACRIN E1105 trial was developed to determine if the addition of bevacizumab to a chemotherapy and trastuzumab combination for first-line therapy would improve progression-free survival (PFS) in patients with HER2-positive MBC. Findings: 96 patients were randomized to receive standard first-line chemotherapy and trastuzumab with or without bevacizumab between November 2007 and October 2009, and 93 began protocol therapy. Induction therapy was given for 24 weeks, followed by maintenance trastuzumab with or without bevacizumab. 60% (56/93) began carboplatin and 74% (69/93) completed 6 cycles of induction therapy. Primary endpoint was PFS. Median PFS was 11.1 and 13.8 months for placebo and bevacizumab arms, respectively (hazard ratio [HR] 95%, Confidence Interval [Cl] for bevacizumab vs. placebo: 0.73 [0.43–1.23], p = 0.24), and at a median follow-up of 70.7 months, median survival was 49.1 and 63 months (HR [95% Cl] for OS: 1.09 [0.61–1.97], p = 0.75). The most common toxicities across both arms were neutropenia and hypertension, with left ventricular systolic dysfunction, fatigue, and sensory neuropathy reported more frequently with bevacizumab. Conclusions In this trial, the addition of bevacizumab did not improve outcomes in patients with metastatic HER2-positive breast cancer. Although the trial was underpowered due to smaller than anticipated sample size, these findings corroborated other clinical trials during this time.

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.

605 Background: Pre-clinical and nonrandomized clinical data support synergy of the combination of bevacizumab and trastuzumab. We conducted a randomized double-blinded phase III trial of chemotherapy/trastuzumab ± bevacizumab to evaluate efficacy (PFS after treatment initiation) of the addition of bevacizumab in first-line treatment of HER2+ MBC. Methods: Days 1, 8 and 15 paclitaxel ± carboplatin were administered with trastuzumab and either placebo or bevacizumab 10 mg/kg every 2 weeks for a total of 6 months. Antibody therapy was then continued without chemo every 3 weeks, until disease progression or unacceptable toxicity. Disease assessments were performed every 3 months. Results: Ninety-six of the planned 489 analyzable patients (pts) were accrued between 2007 and 2009, at which time the study terminated due to poor accrual. Seventy % of pts were post-menopausal, 60% had ER+/HER2+ BC. Median age was 55 years (28-80). Outcomes and toxicities are summarized on the tables below. Median follow-up was 30 months. Conclusions: The combination of chemotherapy, trastuzumab, and bevacizumab did not significantly increased toxicity, and was overall safe and well tolerated. No significant differences in clinical benefit were observed between both treatment arms. Data on CTCs and Quality of Life will be presented at the meeting. This study was conducted by the Eastern Cooperative Oncology Group (Robert L. Comis, MD, Chair) and supported in part by Public Health Service Grants CA23318, CA66636, CA21115, CA32291, CA31946, CA49957, CA27525, CA14548, CA17145, CA32102, CA25224, CA49. [Table: see text] [Table: see text]

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 &gt;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 (&gt; 35-fold), followed by OC (&lt; 13-fold), MBC (&lt; 4-fold), and PC (&lt; 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 &lt; 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 &lt; 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 &lt; 0.01, mTOR (S2448) P &lt; 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&gt;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.