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Carcinoma of unknown primary (CUP) is a rare and difficult-to-treat malignancy, the management of which might be improved by the identification of actionable driver mutations. We interrogated 54 to 70 genes in 442 patients with CUP using targeted clinical-grade, next-generation sequencing of circulating tumor DNA (ctDNA). Overall, 80% of patients exhibited ctDNA alterations; 66% (290/442) ≥1 characterized alteration(s), excluding variants of unknown significance. TP53-associated genes were most commonly altered [37.8% (167/442)], followed by genes involved in the MAPK pathway [31.2% (138/442)], PI3K signaling [18.1% (80/442)], and the cell-cycle machinery [10.4% (46/442)]. Among 290 patients harboring characterized alterations, distinct genomic profiles were observed in 87.9% (255/290) of CUP cases, with 99.7% (289/290) exhibiting potentially targetable alterations. An illustrative patient with dynamic changes in ctDNA content during therapy and a responder given a checkpoint inhibitor–based regimen because of a mismatch repair gene anomaly are presented. Our results demonstrate that ctDNA evaluation is feasible in CUP and that most patients harbor a unique somatic profile with pharmacologically actionable alterations, justifying the inclusion of noninvasive liquid biopsies in next-generation clinical trials. Cancer Res; 77(16); 4238–46. ©2017 AACR.

Supplementary data: Supplemental Table 1. 54-70 gene panels. Supplemental Table 2. Genomic alterations in patients with carcinoma of unknown primary (N = 442) Supplemental Table 3. Summary of examples of possible cognate targeted therapies and relevant references. Supplemental Table 4. Complete list of genetic alterations found in 442 patients with carcinoma of unknown primary. Supplemental Figure 1. Frequency distribution of somatic SNVs and germline SNPs. Supplemental Figure 2. Oncoprint of 442 patients with carcinoma of unknown primary Supplemental Figure 3. Analysis of potentially actionable genomic alterations among 442 patients with carcinoma of unknown primary. Supplemental Figure 4. Number of characterized genomic alterations and number of potentially actionable genomic alterations per patient. Supplemental Figure 5. Fraction of ctDNA among frequently altered genes in patients with carcinoma of unknown primary. Supplemental Figure 6. Comparison of molecular alterations between current report using ctDNA and previous reports using tumor tissues from CUP patients.

Purpose:. Breast cancer is a common malignancy among women. About one in eight women in the US will be diagnosed with breast cancer during their lifetime. One of the most commonly altered genetic pathways in breast cancer patients is the PI3K/AKT/mTOR pathway. Among patients treated with everolimus and alpelisib, hyperglycemia is a frequently encountered adverse event. The cause of hyperglycemia is believed to be the inhibition of PI3K/mTOR, which not only plays a role in oncogenesis but also regulates glucose transportation and glycogen synthesis. Inhibition of PI3K/mTOR activity from treatment results in decreased insulin secretion and hyperglycemia. Obesity is a risk factor for both breast cancer and hyperglycemia. Over 70% of breast cancer patients seen in our center are overweight or obese. Being obese alone increases a patient’s risk of developing insulin resistance and hyperglycemia. Little research has been done on whether obese breast cancer patients are at higher risk of treatment induced hyperglycemia. The purpose of this study was to test whether obesity and pre-existing hyperglycemia are risk factors that increase the patients’ chance to develop hyperglycemia while being treated with anti-PI3K/mTOR drugs. Methods:. A retrospective study was performed on 119 breast cancer patients at Avera Cancer Institute. Female patients who had been treated with everolimus and/or alpelisib were included. According to the CDC standard, patients with body mass index (BMI) greater than 25 kg/m2 were considered as obese. Grade 2 and above hyperglycemia was defined as fasting blood glucose level greater than 160 mg/dl per CTCAE. Baseline blood glucose levels prior anti-PI3K/mTOR treatment were considered high if greater than 140 mg/dl per the American Diabetes Association. Results:. Of the 119 patients, 78 were ER+/HER2-; 22 were triple negative; 12 were ER-/HER2+ and 7 were ER+/HER2+. The BMI ranged from 17.79 to 52.87 (94 obese patients). Patients were kept on everolimus/alpelisib from 14 days to 5 years (median = 6 month). After starting everolimus/alpelisib, 17 patients developed hyperglycemia Grade 2 or greater, 16 of whom were obese. Being obese increased the odds of developing hyperglycemia under anti-PI3K/mTOR treatment by 4.58, However, this increase was not significant (p=0.16). Hyperglycemia in most patients was controlled by diet and lifestyle changes. Four patients (all obese) needed either insulin, metformin, DPP-4 and/or SGLT2 inhibitors to control blood glucose levels. Three patients had type 2 diabetes prior to therapy. The fourth patient developed Grade 3 hyperglycemia (>250 mg/dl) nine month after starting everolimus and was put on insulin for two months, with blood glucose returning back to normal. Everolimus was continued for another three month without causing hyperglycemia in this patient. Our data suggests that baseline blood glucose levels play a significant role in developing high grade hyperglycemia under anti-PI3K/mTOR treatment. The odds of developing hyperglycemia increase by a factor of 5.38 in patients with high blood glucose prior treatment (p= 0.007). Conclusion:. Being obese does not alone present a significantly higher risk of developing high grade hyperglycemia while being treated with anti-PI3K/mTOR drugs compared to non-obese patients if their blood glucose is well controlled. Most patients can manage their blood glucose level by diet and lifestyle changes. Patients starting anti-PI3K/mTOR treatment with high blood glucose level at baseline are at a much higher risk of developing drug-induced hyperglycemia and should be closely monitored. Citation Format: Bing Xu, Tobias Messiner, Casey Williams. Risk of everolimus- and alpelisib-induced hyperglycemia in obese and non-obese breast cancer patients with or without pre-existing hyperglycemia [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-08-20.

Private equity firms are responsible for some of the largest, generally exclusive investment strategies for pension funds, endowments and foundations, family offices, and other institutional investors. In order to generate returns known for being significantly higher than public investments, private equity general partners use a variety of strategies. However, such returns don’t come easily. This article will concisely overview and evaluate lower middle market investments ($25-100M) in private equity, and the management’s process. The research consists of an internship with a leading firm in the lower middle market investment category for private equity as well as independent research. Different strategies of private equity firms will be covered, but it is important to note that each strategy covered remains relative, and depends on the process followed by each individual firm.

The calculation of option Greeks is vital for risk management. Traditional pathwise and finite-difference methods work poorly for higher-order Greeks and options with discontinuous payoff functions. The Quasi-Monte Carlo-based conditional pathwise method (QMC-CPW) for options Greeks allows the payoff function of options to be effectively smoothed, allowing for increased efficiency when calculating sensitivities. Also demonstrated in literature is the increased computational speed gained by applying GPUs to highly parallelisable finance problems such as calculating Greeks. We pair QMC-CPW with simulation on the GPU using the CUDA platform. We estimate the delta, vega and gamma Greeks of three exotic options: arithmetic Asian, binary Asian, and lookback. Not only are the benefits of QMC-CPW shown through variance reduction factors of up to $1.0 \times 10^{18}$, but the increased computational speed through usage of the GPU is shown as we achieve speedups over sequential CPU implementations of more than $200$x for our most accurate method., 26 pages, 12 figures

Background Tumor complexity and heterogeneity require matching of actionable genomic alterations with available therapy to increase response rates and prolong survival in patients. However, it has been a long-standing challenge for treating oncologists to select an effective patient-specific therapeutic strategy due to the molecular rationale, disease relevance, and patient-specific issues. To provide a decision-support tool to aid oncologists and educate patients, we have developed a set of molecular and clinical evidence-based criteria as an algorithm for ranking therapeutic strategies in order to deliver optimal care and improve outcomes in patients with malignancy. Methods History of present illness (HPI) and comprehensive genomic profiling (CGP) results of 203 patients with malignant tumors were reviewed by our multidisciplinary Molecular Tumor Board (MTB) from June 2021 to August 2022, and therapeutic recommendations were provided with Matching Score based on molecular matching only as well as with Ranking Score calculated by our molecular and clinical evidence-based algorithm with the criteria not only focusing on molecular matching, but also including disease relevance, patient-specific clinical considerations and treatment availability as weighting factors (Cohort 2). The other 50 patients with previously treated solid tumors reviewed by MTB (before 2018) and treatment recommendations provided with Matching Score only, were used as a control group (Cohort 1). The matching rates from recommendations and treatment outcomes of the patients were then assessed. Results In Cohort 1, of the 50 patients, 33 patients (66%) received matched therapeutic plans recommended by our MTB. The other 17 patients were not on a matched plan from the MTB. Twelve patients (36.4% of 33 patients) achieved progression-free survival (PFS) at 12-week time point, including 8 patients (24.2%) achieved PFS at 6-month time point. The other 21 patients (63.6% of 33 patients) could not be assessed due to treatment termination per drug toxicity or death before the follow-up time point. The median PFS/overall survival (OS) for patients with a Matching Score > 50% (N = 17) were 7.5/10.5 months, whereas with Matching Score ≤ 50% (N = 16) were 3/7.35 months. In Cohort2, of the 203 patients, 89 (43.8%) patients have initiated matched therapeutic plans and follow-up is ongoing. Updated results will be presented at the meeting. Conclusion Our novel molecular and clinical evidence-based algorithm may be used to support oncologists decision-making to utilize the most clinically appropriate and effective therapeutic options. Further validation studies and development of an user-friendly computational ranking platform based on the algorithm are planned in order. Citation Format: Yuliang Sun, Tobias Meissner, Rachel Elsey, Leah Theisen, Crystal Hattum, Bing Xu, John Lee, Casey Williams. Development/validation of a molecular and clinical evidence-based algorithm for selecting optimal precision therapeutic strategy for cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1057.

Background: The combination of a poly ADP ribose polymerase (PARP) inhibitor with a DNA-damaging agent has shown promise in treating triple-negative breast cancer (TNBC); however, not all patients respond to this combination. The Src protein kinase modulates multiple cancer cell properties and plays a key role in tumorigenic processes. However, Src inhibitors as single agents have shown limited effects in solid tumors. In this study, we examined the antitumor effects of the Src inhibitor dasatinib, the PARP inhibitor veliparib, and the DNA-damaging agent carboplatin in TNBC cells in vitro and tumors in vivo to try to identify the combination with the most clinical potential. Methods: The BRCA-mutated and PTEN null TNBC cell line, SUM149PT, was used in this study. For in vitro studies, proliferation, cellular apoptosis, and 3D on-top clonogenic growth were measured, tube formation assays and western blot analysis were performed. For in vivo studies, a xenograft model was used to examine treatment responses, and immunohistochemical analysis was performed. Results: Surprisingly, treatment with the combination of veliparib plus carboplatin led to an increase in Src phosphorylation. Importantly, addition of dasatinib attenuated Src overexpression induced by veliparib plus carboplatin and further inhibited the downstream signaling of Src, thereby enhancing the antitumor efficacy of veliparib plus carboplatin. In an SUM149PT xenograft model, the triple combination of dasatinib with veliparib plus carboplatin showed greater tumor growth inhibitory effects compared with single agents or double combinations. No systemic toxicity was observed in mice treated with the triple combination. Conclusion: Here, we provide novel evidence that veliparib combined with carboplatin drives Src activation in the preclinical model tested. Moreover, we provide provocative in vitro and in vivo data highlighting the potential for increasing therapeutic efficacy by combining dasatinib with veliparib and carboplatin in BRCA-mutated and PTEN null TNBC. Citation Format: yuliang Sun, Xiaoqian Lin, Jennifer Aske, Casey Williams, Mark Abramovitz, Brian Leyland-Jones. Preclinical model of TNBC: Dasatinib attenuates Src pathway signaling and combined with veliparib and carboplatin potently inhibits tumor growth [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-11-19.

Background Malignancies are molecularly complex and become more resistant with each line of therapy. We hypothesized that offering matched, individualized combination therapies to patients with treatment-naïve, advanced cancers would be feasible and efficacious. Patients with newly diagnosed unresectable/metastatic, poor-prognosis cancers were enrolled in a cross-institutional prospective study. Methods A total of 145 patients were included in the study. Genomic profiling (tissue and/or circulating tumor DNA) was performed in all patients, and PD-L1 immunohistochemistry, tumor mutational burden, and microsatellite status assessment were performed in a subset of patients. We evaluated safety and outcomes: disease-control rate (stable disease for ≥ 6 months or partial or complete response), progression-free survival (PFS), and overall survival (OS). Results Seventy-six of 145 patients (52%) were treated, most commonly for non-colorectal gastrointestinal cancers, carcinomas of unknown primary, and hepatobiliary malignancies (53% women; median age, 63 years). The median number of deleterious genomic alterations per patient was 5 (range, 0–15). Fifty-four treated patients (71%) received ≥ 1 molecularly matched therapy, demonstrating the feasibility of administering molecularly matched therapy. The Matching Score, which reflects the percentage of targeted alterations, correlated linearly with progression-free survival (R2 = 0.92; P = 0.01), and high (≥ 60%) Matching Score was an independent predictor of improved disease control rate [OR 3.31 (95% CI 1.01–10.83), P = 0.048], PFS [HR 0.55 (0.28–1.07), P = 0.08], and OS [HR 0.42 (0.21–0.85), P = 0.02]. Serious adverse event rates were similar in the unmatched and matched groups. Conclusions Personalized combination therapies targeting a majority of a patient’s molecular alterations have antitumor activity as first-line treatment. These findings underscore the feasibility and importance of using tailored N-of-1 combination therapies early in the course of lethal malignancies. Trial registration I-PREDICT (NCT02534675) was registered on August 25, 2015.

PURPOSE OF REVIEW We are in an exhilarating time in which innovations exist to help reduce the impact of cancer for individuals, practitioners and society. Innovative tools in cancer genomics can optimize decision-making concerning appropriate drugs (alone or in combination) to cure or prolong life. The genomic characterization of tumours can also give direction to the development of novel drugs. Next-generation tumour sequencing is increasingly becoming an essential part of clinical decision-making, and, as such, will require appropriate coordination for effective adoption and delivery. RECENT FINDINGS There are several challenges that will need to be addressed if we are to facilitate cancer genomics as part of routine community oncology practice. Recent research into this novel testing paradigm has demonstrated the barriers are at the individual level, while others are at the institution and societal levels. SUMMARY This article, based on the authors' experience in community oncology practice and summary of literature, describes these challenges so strategies can be developed to address these challenges to improve patient outcomes.

We describe how faculty and staff used improvement science design Plan-Do-Study-Act (PDSA) cycles and engaged in interdisciplinary conversations in an effort to improve students’ performance in int...

Cancer treatments have evolved from indiscriminate cytotoxic agents to selective genome- and immune-targeted drugs that have transformed outcomes for some malignancies.1 Tumor complexity and heterogeneity suggest that the “precision medicine” paradigm of cancer therapy requires treatment to be personalized to the individual patient.2–6 To date, precision oncology trials have been based upon molecular matching with predetermined monotherapies.7–14 Several of these trials have been hindered by very low matching rates, often in the 5–10% range,15 and low response rates. Low matching rates may be due to the use of limited gene panels, restrictive molecular matching algorithms, lack of drug availability or the deterioration and death of end-stage patients before therapy can be implemented. We hypothesized that personalized treatment with combination therapies would improve outcomes in patients with refractory malignancies. As a first test of this concept, we implemented a cross-institutional, prospective study (I-PREDICT, NCT02534675) that used tumor DNA sequencing and timely recommendations for individualized treatment with combination therapies. We found that administration of customized multi-drug regimens was feasible, with 49% of consented patients receiving personalized treatment. Targeting of a larger fraction of identified molecular alterations, yielding a higher “matching score,” was correlated with significantly improved disease control rates, as well as longer progression-free and overall survival rates, as compared to when fewer somatic alterations were targeted. Our findings suggest that the current clinical trial paradigm for precision oncology, which pairs one driver mutation with one drug, may be optimized by treating molecularly complex and heterogeneous cancers with combinations of customized agents.

Background: Tumor complexity and heterogeneity require matching of actionable genomic alterations with available therapy to increase response rates and prolong survival in patients with cancer. It has been a long-standing challenge for treating oncologists to select an effective patient-specific therapeutic strategy due to the molecular rationale, disease relevance, patient-specific issues, including patient access to treatments. We have developed a set of molecular and clinical evidence-based criteria as an algorithm for ranking therapeutic strategies in order to deliver optimal care and improve outcomes in patients with metastatic malignancies. Methods: Patients included in the analysis received comprehensive genomic profiling (CGP) for selected biomarkers. CGP results of 50 patients with stage IV tumors were reviewed by our multidisciplinary Molecular Tumor Board (MTB), after which treatment recommendations were generated based on molecular matching only (Cohort 1). CGP results of the other current 29 patients with stage IV breast cancer were reviewed by MTB, and therapeutic recommendations were provided with ranking scores calculated by our molecular and clinical evidence-based algorithm with the criteria not only focusing on molecular matching, but also including disease relevance, patient-specific clinical considerations and treatment availability as weighting factors (Cohort 2). The matching rates from recommendations and treatment outcomes of the two cohorts were then assessed. Results: In Cohort 1, of the 50 patients, 34 patients (68%) were initiated with personalized therapeutic plans based on molecular matching that were recommended by our MTB. The other 16 patients were not treated with molecular matching therapeutic plans recommended by MTB, as the results of treating oncologists’ choices, treatment availability or patient preference. Patients were followed and outcomes were then evaluated. Thirteen patients (38.2% of 34 patients) achieved progression-free survival (PFS) at 12-week time point, and 6 patients achieved PFS (including stable disease, N=4 and partial response, N=2) at 6-month time point. The other 21 patients (61.8% of 34 patients) could not be assessed due to disease progression, treatment termination per drug toxicity or death before the follow-up time point. Cohort 2 is ongoing, the results of which will be presented in the meeting. Conclusion: Our novel molecular and clinical evidence-based algorithm may be used to support oncologists decision-making to utilize the most clinically appropriate and effective therapeutic options. Additional studies with larger sample sizes in different type of solid tumors are planned in order to determine a clinically and statistically relevant range of score for the treatment recommendations with optimal clinical outcomes. Citation Format: Yuliang Sun, Tobias Meissner, Rachel Elsey, Leah Theisen, Jason Jones, Casey Williams. Development of a molecular and clinical evidence-based algorithm for selecting optimal precision therapeutic strategy for patients with metastatic breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4095.

Introduction: The adoption of routine tumor sequencing, and the incorporation of biomarker-based clinical trials in the treatment of cancer has been steadily rising over the past few years. Access and ability to participate in clinical trials is a key element in providing therapeutic options for cancer patients.At the Avera Cancer Institute, options of biomarker-based clinical trials are routinely presented to the treating clinicians at the molecular tumor board (MTB). With everincreasing numbers of trials, a systematic method for keepingtrack of available trials andevaluating patients for trial options was needed. A search for solutions led to only one open-source tool, MatchMiner, but it did not meet our needs. Methods and Results: We developed an open-source web application, TrialMatch, that has the ability to (i) add trials through a semi-automated curation interface, (ii) browse and search trials, (iii) and match patients to biomarker-based trials.TrialMatch is an R Shiny application that uses a mongo database to store the trial data. Software installation and application instantiation is managed through Docker. Curate This section has fields for a user to enter trial name and a NCT ID from clinicaltrials.gov. It then queries the clinicaltrials.gov API and fetches data about the sponsor, treatment, etc.Although disease and biomarker data are available on clinicaltrials.gov, they are not stored as discrete fields that can be queried, and hence require manual input. The user provides disease type based on the OncoTree classification, as well as biomarker information for mutations, copy numbers, fusions, TMB, MSI status, PD-L1 status, RNA expression, and disease specific markers such as ER/PR/HER2 status.All information for a particular trial is entered in a mongo database collection, with each trial stored as a document. The ability to add and edit data fields can be restricted to specific users. Browse This section allows the user to browse through all trials with key information such as NCT ID, trial name, disease, and biomarkers. Each row represents one trial and can be expanded to show more detailed information. This is useful to keep track of trials, and to quickly filter trials to a specific disease or biomarker. Match This section displays a patient-centric view of the trials that each patients’ age, sex, disease, and biomarkers have matched to. The matching can be automated for scheduled recurrentruns. At Avera, this is used during MTB to evaluate treatment options, but can also be used by clinicians to get a sense of the trials available for their patients, while awaiting formal review. Conclusion: We believe that this computational tool fulfills a crucial need in the clinical application of precision oncology, and will ultimately increase clinical trial enrollment for patients. Citation Format: Anu Amallraja, Shivani Kapadia, Padmadpriya Swaminathan, Casey Williams, Tobias Meissner. TrialMatch: A computational resource for the management of biomarker-based clinical trials at a precision oncology center [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1899.

Background: Available literature suggests that provider adherence to best practice guidelines regarding the prescribing and management of opioid therapies is low. Documentation of patient screening for present or future opioid use disorder is inconsistent. Provider incorporation of evidence-based guidelines into routine patient care is essential to optimizing outcomes related to opioid use disorders. Purpose/Specific Aims: The purpose of this scholarly project was to facilitate recognition of patients at high risk for opioid use disorders and facilitate best evidence based practices in the care of this population. Specific aims were to achieve provider compliance with: patient risk screening, PDMP review, completion of signed care plans, and reduction of inappropriate opioid prescriptions. Methods: A quasi-experimental design was used for this quality improvement project. The sample included patients receiving treatment for acute or chronic pain, or who were identified as having a substance use disorder. The project was conducted at an internal medicine practice in the northeast region. The intervention included an educational program addressing the ASAM guidelines and ORT utilization with implementation of a SmartPhrase in Epic. Baseline data was collected for the two-month period preceding the intervention and post-intervention data was collected for the three-month period following the intervention. Differences in pre- and post- intervention results were analyzed using chi square. Results: This project resulted in improved compliance with the implementation of urine toxicology screening, PDMP review, and completion of a controlled substance agreement. Compliance with ORT was not achieved. Conclusion: This project led to an increase in compliance with best opioid prescribing practices. The ORT was not consistently implemented; however, the number of new opioid prescriptions remained negligible. Additional efforts will be necessary to maintain the progress achieved in this project including attention to continued provider education. Real-time auditing and feedback will also be incorporated, and opportunities to involve office staff will be explored.

Personalized treatment vs. standard of care is much debated, especially in clinical practice. Here we investigated whether overall survival differences in metastatic colorectal cancer patients are explained by tumor mutation profiles or by treatment differences in real clinical practice. Our retrospective study of metastatic colorectal cancer patients of confirmed European ancestry comprised 54 Americans and 54 gender-matched Germans. The Americans received standard of care, and on treatment failure, 35 patients received individualized treatments. The German patients received standard of care only. Tumor mutations, tumor mutation burden and microsatellite status were identified by using the FoundationOne assay or the IDT Pan-Cancer assay. High-risk patients were identified according to the mutational classification by Schell and colleagues. Results: Kaplan&ndash, Meier estimates show the high-risk patients to survive 16 months longer under individualized treatments than those under only standard of care, in the median (p &lt, 0.001). Tumor mutation profiles stratify patients by risk groups but not by country. Conclusions: High-risk patients appear to survive significantly longer (p &lt, 0.001) if they receive individualized treatments after the exhaustion of standard of care treatments. Secondly, the tumor mutation landscape in Americans and Germans is congruent and thus warrants the transatlantic exchange of successful treatment protocols and the harmonization of guidelines.

Purpose The Herceptin Adjuvant study is an international multicenter randomized trial that compared 1 or 2 years of trastuzumab given every 3 weeks with observation in women with human epidermal growth factor 2–positive (HER2+) breast cancer after chemotherapy. Identification of biomarkers predictive of a benefit from trastuzumab will minimize overtreatment and lower health care costs. Methods To identify possible single-gene biomarkers, an exploratory analysis of 3,669 gene probes not expected to be expressed in normal breast tissue was conducted. Disease-free survival (DFS) was used as the end point in a Cox regression model, with the interaction term between C8A mRNA and treatment as a categorical variable split on the cohort mean. Results A significant interaction between C8A mRNA and treatment was detected ( P < .001), indicating a predictive response to trastuzumab treatment. For the C8A-low subgroup (mRNA expression lower than the cohort mean), no significant treatment benefit was observed ( P = .73). In the C8A-high subgroup, patients receiving trastuzumab experienced a lower hazard of a DFS event by approximately 75% compared with those in the observation arm (hazard ratio [HR], 0.25; P < .001). A significant prognostic effect of C8A mRNA also was seen ( P < .001) in the observation arm, where the C8A-high group hazard of a DFS event was three times the respective hazard of the C8A-low group (HR, 3.27; P < .001). C8A mRNA is highly prognostic in the Hungarian Academy of Science HER2+ gastric cancer cohort (HR, 1.72; P < .001). Conclusion C8A as a single-gene biomarker prognostic of DFS and predictive of a benefit from trastuzumab has the potential to improve the standard of care in HER2+ breast cancer if validated by additional studies. Understanding the advantage of overexpression of C8A related to the innate immune response can give insight into the mechanisms that drive cancer.

We present a protocol for live cancer cell-imaging by triple-fluorescent staining to test 3 crucial mechanisms of apoptosis; the enzymatic activity of executioner caspase3, caspase-dependent phosphatidylserine presentation on the cell surface and mitochondrial function. We standardized a protocol to co-stain live tumor cells with the NucView488-Casp3 substrate, CF594 AnnexinV, and MitoViewBlue. We validated this protocol following apoptosis induction with paclitaxel or in combination with BKM120. Fluorescent imaging of cells using simultaneous live/dead cell markers (CalceinAM green/EthD-1red) was used as internal control. We used quantitative confluence (Essen), AnnexinV-PE staining (Accuri C6), expression of cl-caspase3, Cl-PARP and mitochondrial potential (TMRE-A) as validation criteria in A2780 and OVK18 cells following drug treatment which decreased proliferation, & increased apoptotic signaling with mitochondrial depolarization. Treatment blocked cytoplasmic MitoViewBlue staining while increased both nuclear NucView488-Casp3 substrate and red membranous CF594 AnnexinV staining. Merged images showed 100% mutual exclusivity between MitoViewBlue and caspase3 or AnnexinV stains in control and treated cells as determined by overlap and colocalization coefficients. Caspase3 and AnnexinV staining in treated cells were both separate and overlapped (yellow fluorescence) indicating the sequence of apoptotic-events. The protocol will help in deciphering mechanistic involvement of different stages/features of apoptosis in tumor cell following anti-cancer drugs in real-time.

Background Cancer is a genetic disease in which cells may accumulate somatic mutations. The measurement of the frequency these somatic mutations occur is referred to as tumor mutational burden or TMB. A minority of these mutations may give rise to neoantigens that could in turn be recognized and targeted by the immune system. The more somatic mutations a tumor develops, the more likely these neoantigens are to form. Recent studies, namely KEYNOTE-158, found high TMB status to be associated with improved outcomes in patients receiving pembrolizumab monotherapy. Materials and Methods This was a single-center retrospective study that analyzed 73 patients who received cancer treatment at Avera Cancer Institute between June 2016 and July 2019. Patients were included/excluded from the final analysis based on having received at least one dose of pembrolizumab, ipilimumab, and/or nivolumab. Information was collected on patient characteristics, treatment, and clinical outcomes. The primary outcomes were complete and partial response rates and were assessed objectively based on a composite of radiographic reports, physician documentation, and treatment course. Secondary outcomes were clinical outcomes in patients with PD-1 and/or PD-L1 expression, clinical outcomes in patients receiving mono-immunotherapy vs combination therapy, and clinical outcomes based on the line of treatment in which immunotherapy was utilized. Results A total of 34 patients met the inclusion criteria of having a high TMB value (10 mutations/megabase) and having received one dose of pembrolizumab, ipilimumab, or nivolumab. Primary Outcomes•16 patients experienced a partial response (AR = 0.47) and 6 of these patients experienced a complete response (AR = 0.17) Secondary Outcomes•Absolute risk with prior TMB information (PR 0.43, CR: 0.17)•Absolute risks for monotherapy (PR: 0.375, CR: 0.125) vs combination therapy (PR: 0.556, CR: 0.375)•Average line of treatment for TF, PR, and CR were 2.24, 2, and 1.83 respectively. Discussion Studies like KEYNOTE-158 found a significant correlation between high TMB and improved clinical outcomes in patients receiving checkpoint inhibitors. However, in this cohort of patients high TMB status was not a good predictor of therapeutic success compared to the data presented in KEYNOTE-001, CHECKMATE-057, OAK, or PACIFIC. While there are limitations associated with the sample size, the data support that checkpoint therapy benefits patients when it is used earlier in their treatment course and combined with other treatments. Further exploration is required to determine the most appropriate cut point for calling a patient TMB high as well as how TMB and PD-L1 predict response to specific therapies. Citation Format: Khai Nguyen, Bing Xu, Rachel Elsey, Tobias Meissner, Casey Williams. A single-center retrospective review assessing the use of tumor mutation burden as a predictor of therapeutic success in patients receiving immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 371.

Purpose: Little is known about the physiological impact of smoking cessation on a patient with cancer. Smoking cessation immediately after a cancer diagnosis likely induces a nicotine withdrawal syndrome that drastically alters catecholamine production and activity and may negatively impact a patient's mental health. Studies have demonstrated that stress-related catecholamines may negatively affect cancer progression, but data regarding the acute effects on immune system function is lacking. The molecular mechanisms of hypersensitivity to taxane chemotherapy are not well defined, but for a majority of patients that develop a reaction to paclitaxel, the reaction occurs with the first or second infusion. Our hypothesis is patients that are highly anxious are more likely to develop a reaction to chemotherapy such as paclitaxel, particularly if they have a recent history of nicotine addiction and are trying to quit. Methods: A retrospective chart review of patients with breast or gynecological cancers was conducted at Avera Cancer Institute. A total of 58 female patients with a history of a hypersensitivity reactions to taxane chemotherapy were included. Data collected on patient characteristics included, smoking history, history of depression or anxiety, and onset of hypersensitivity reaction. The primary outcome was strength of association between nicotine exposure and onset of reaction, based upon odds ratio and relative risk. Secondary outcomes included the effects of anxiety and nicotine withdrawal on clinical outcomes and anxiety-related impact on therapeutic execution. Results: Of the 58 patients with a history of taxane hypersensitivity, 12 (20.7%) had a diagnosis of anxiety, 19 (32.8%) were former smokers, and 2 (3.4%) were current smokers. Among the 12 patients who had a diagnosis of anxiety at the time of their reaction, 5 (41.7%) were documented to be former or current smokers. Patients previously exposed to nicotine were found to be more likely to experience a hypersensitivity reaction within cycle 1 of chemotherapy (Odds Ratio 1.26). The risk of experiencing a reaction within the first cycle was found to be 16% higher in those who were exposed to nicotine compared to those who were not. Conclusion: The results of our analysis indicate that recent nicotine addiction and anxiety may increase the likelihood of a taxane hypersensitivity reaction during cycle 1. Those without a smoking history mainly experienced reactions during cycles 2, 3, or 4, which reinforced our findings. Limitations associated with this study include small sample size and the challenges of interpreting clinical notes in the electronic medical record. A larger analysis is required to confirm our results and data collection is ongoing. Citation Format: Devon C. Barry, Natalie Hartung, Casey Williams. Impact of smoking cessation and anxiety on hypersensitivity reactions in cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 683.

Background: RAS mutations are found in nearly one third of patients with cancer. As part of the Ras-Raf-MEK-ERK pathway, RAS mutations lead to uninhibited cell growth, proliferation, and survival. KRAS mutations account for a large majority of RAS mutations, especially in lung, colon, and pancreatic cancers. Trametinib, a MEK inhibitor, is approved at 2mg daily for the treatment of melanoma, lung, and thyroid cancers with BRAF mutations when in combination with dabrafenib, a BRAF inhibitor. However, trametinib's safety and efficacy in patients with KRAS-mutated tumors is still under investigation. The purpose of this analysis was to determine the tolerability of trametinib in patients with KRAS alterations. Methods: A retrospective, single-center, IRB-approved, cohort analysis was performed on patients with solid tumors at a regional cancer center. Patients who received at least one dose of trametinib were queried to be included in original chart review, including patients who had received trametinib as part of an IRB-approved precision oncology trial. The primary endpoint was tolerability as defined by proportion of patients who required dose reductions or complete discontinuation of therapy due to drug intolerance and by mean percent of FDA-approved dosing. Additional data collected includes patient demographics, cancer diagnosis, and outcome; number of previous therapy lines; agents combined with trametinib; and the nature of adverse events, if applicable. Results: Thirty-three patients were included for final evaluation. The average age of the patients included was 59.8 (range 32-81) years and the most common diagnoses were colon cancer, non-small cell lung cancer, and gynecological cancer. On average, patients had 2.5 (range 0-9) previous lines of therapy. Only 2 patients received single agent trametinib, while the remainder were treated in combination with additional agents (range 1-4). Seventeen (52%) patients tolerated trametinib therapy without progression for 2 months, including six (18%) who received treatment for 6 months or longer. Of these 17, three (9%) were initiated at 2mg daily, ten (30%) were initiated at half the approved dose, and the remaining patients were initiated at less than half of the approved dose. Twelve (36%) of these patients required dose reductions due to intolerance, and twelve (36%) patients ultimately discontinued trametinib therapy due to intolerance. None of these patients tolerated the full FDA-approved dose and the mean percent of recommended dose, after dose reductions, was 38%. Conclusion: This study demonstrates that trametinib therapy at 2mg daily is intolerable for most patients, especially in combination with other neoplastic therapies. The impact on efficacy of the subsequent dose reductions is unknown. Further investigation is required in order to determine the most tolerable dose of trametinib that is still efficacious. Citation Format: Julie R. Spangler, Rachel J. Elsey, Casey B. Williams. Tolerability and outcomes of trametinib treatment in KRAS mutated solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1353.

Purpose Obesity has been shown to be strongly associated with the development of breast and gynecologic cancers. PIK3CA is one of the most commonly altered genes in solid tumors, and patients who have alterations are routinely initiated on therapies that target this pathway. However, response can vary greatly between patients, and the reason for differences in response has yet to be completely understood. Obesity has been shown to alter cancer metabolism and further dysregulate the PI3K/AKT/mTOR pathway which may affect response to target therapy. L. Cantley and colleagues suggest that the state of consistent hyperinsulinemia, which is common in obesity, can compromise the clinical benefit of PI3K-pathway targeted therapy, as insulin is a known potent stimulator of this pathway. Therefore, the purpose of this study was to compare clinical outcomes between obese and non-obese patients on pathway-directed therapy. Methods A retrospective analysis was performed on 140 patients with breast, ovarian, cervical, or endometrial malignancies at Avera Cancer Institute. Female patients with a documented oncogenic PIK3CA alteration were included in the study. Overall survival (OS) and progression free survival (PFS) were the primary endpoints. BMI groups were determined by using existing clinical categories of obesity as defined by the CDC. Patients were stratified into 2 BMI groups: Group A 25 kg/m2 and Group B 25 kg/m2. The Kaplan-Meier method was used to derive time-to-event estimates and test for significance. A cox proportional-hazard model was utilized to determine the association between survival time for patients with BMI being the predictor variable. Results Of the 140 patients, 106 patients had breast cancer, 21 patients had endometrial cancer, 9 patients had ovarian cancer, 3 patients had cervical cancer, and 1 patient had vaginal melanoma. There were 52 patients in Group A and 88 patients in Group B. 25 of the 140 patients had documented PIK3CA alterations but were never initiated on targeted therapy. Group B was found to reduce the hazard by a factor of 0.63 (p=0.09). The subset of Group B with PI3K/mTOR targeted therapy was found to reduce the hazard by a factor of 0.43 (p=0.008). Among the 43 patients who were included in PFS analysis, it was found that there was no statistically significant (p=0.6) improved PFS between the two groups. Conclusion In this analysis, patients with a PIK3CA mutation and who had a higher BMI had an improved response rate from targeted therapy and overall survival than compared to patients with a lower BMI. Treatment lines prior to initiation of targeted therapy varied greatly, and differences in the multiple types of malignancies studied in this analysis was a limitation. More prospective studies that are statistically powered are warranted in order to assess the true impact of obesity on improved OS compared to patients with a BMI 25. Citation Format: Diana Kim, Bing Xu, Rachel Elsey, Tobias Meissner, Casey Williams. Clinical outcomes between obese and non-obese breast and gynecological cancer patients with alterations in the PI3K/AKT/mTOR pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1385.

Community-based adaptation (CBA) is an approach to strengthening the adaptive capacity of local communities vulnerable to climate change. The CBA approach increasingly features in discussions among policy makers, planners, advocates, and researchers, and has been endorsed and adopted by numerous governmental and non-governmental organizations. However, to date the CBA approach has lacked conceptual clarity, and the term is interpreted and deployed in various and often contradictory ways. This paper seeks to address this deficit by explaining the rationale put forth for CBA by its proponents, outlining its guiding principles, and theorizing some of its key challenges, which often point to opportunities for the approach to evolve.

Carcinoma of unknown primary (CUP) is a rare and difficult-to-treat malignancy, the management of which might be improved by the identification of actionable driver mutations. We interrogated 54 to 70 genes in 442 patients with CUP using targeted clinical-grade, next-generation sequencing of circulating tumor DNA (ctDNA). Overall, 80% of patients exhibited ctDNA alterations; 66% (290/442) ≥1 characterized alteration(s), excluding variants of unknown significance. TP53-associated genes were most commonly altered [37.8% (167/442)], followed by genes involved in the MAPK pathway [31.2% (138/442)], PI3K signaling [18.1% (80/442)], and the cell-cycle machinery [10.4% (46/442)]. Among 290 patients harboring characterized alterations, distinct genomic profiles were observed in 87.9% (255/290) of CUP cases, with 99.7% (289/290) exhibiting potentially targetable alterations. An illustrative patient with dynamic changes in ctDNA content during therapy and a responder given a checkpoint inhibitor–based regimen because of a mismatch repair gene anomaly are presented. Our results demonstrate that ctDNA evaluation is feasible in CUP and that most patients harbor a unique somatic profile with pharmacologically actionable alterations, justifying the inclusion of noninvasive liquid biopsies in next-generation clinical trials. Cancer Res; 77(16); 4238–46. ©2017 AACR.

As a genetic disease [1] cancer dysregulates key oncogenic pathways that influence cell growth, proliferation, survival, angiogenesis, and metastasis. Among the major determinants that enable cancer cells to acquire malignant traits are genomic diversity and instability. In the post human genome project era, cancer-specific genomic maps are redesigning tumor taxonomy. The treatment modalities, as well as the overall management of cancer as a disease in today's clinic, have started depending heavily on the molecular pathology of the individual tumor(s) in addition to the fundamental classification of cancers by histopathology. The enrichment tumor taxonomy by genomic morphology has also opened up the possibilities for genomics-driven drug development. The success of a cancer drug today is fundamentally based on the success in identifying target genes that control tumorigenic pathways. One primary goal of precision cancer medicine is to make clinical decisions based on genomic/proteomic data, which can identify a target or targets for therapy, and subsequent inevitable development of therapeutic resistance to the drug. The ability to exploit tumor genetic information for its full clinical potential has only recently become evident. Over the last decade, the convergence of discovery, technology, and therapeutic development has created an unparalleled opportunity to test the hypothesis that systematic knowledge of genomic and proteomic information from individual tumor(s) may significantly improve clinical outcomes for many patients with unmanageable tumor burden. This review presents the signaling logic behind the ground rules for the rational approach to the genomics-driven precision medicine.

Introduction Next generation sequencing has facilitated the understanding of pathogenesis and molecular heterogeneity of breast cancer (BC) as well as accelerated the path towards precision medicine. DNA sequencing (DNA-Seq) based assays for the detection of mutations and alterations in solid and hematologic cancers are finding their way into clinical practice and are readily available as clinical products. RNA sequencing (RNA-Seq), so far being vastly applied in the research context, promises to expand the diagnostic, prognostic and therapeutic use of this technology in cancer. Beyond mutational status, RNA-Seq enables the detection of fusions, quantification of gene expression level, detection of differentially expressed genes, molecular based subtyping, and risk-stratification. In this study we analyzed RNA-Seq and copy number data from BC patients that had undergone DNA-Seq based diagnostics through commercial providers with the goal to detect additional actionable targets. Materials and Methods We included 18 BC patients (5/18 triple negative) that had previously undergone DNA-based targeted (321 genes) sequencing. RNA-Seq to a minimum of 75M reads (75pb) was performed using 100 ng of total RNA on the Illumina NextSeq 500 platform. STAR was used for alignment (hg19) and gene expression quantification (RefSeq). Fusions were detected using STAR-Fusion. DESeq2 was utilized to identify patient specific differentially expressed genes by analyzing samples individually against a set of 13 controls from healthy breast tissue generated in-house. Copy number variations (CNVs) were detected using the Nanostring CNV Cancer panel (89 genes) on the Nanostring nCounter platform. Differentially upregulated or amplified genes were queried against DGIdb and Gene Drug Knowledge database for suitable drug matches, limiting the queries to clinically actionable antineoplastic drugs. Results Analyzing the cohort of 18 BC patients, we detected on average 26 BC relevant genes (526 total, log2 FC > 2) to be upregulated per patient. Querying the upregulated genes against DGIdb, we found a total of 18 genes that had drug matches and fulfilled the criteria of being actionable antineoplastic drugs, with 17/18 samples having a minimum of two gene targets (avg: 4). Most frequent upregulated genes were TOP2A (83%), AURKA (61%), AURKB (56%), RET (39%)and FGFR3 (28%). In the case of CNVs, 12/18 patients showed at least one gene target with clinically actionable drugs associated. This was observed across 12 gene targets that were amplified (avg: 3) and 4 gene targets that underwent deletions (avg: 1). Most frequent CNVs included MYC (14%) and CCND1 (12%). 4/7 patients having an AURKA overexpression also showed an AURKA amplification on the CNV assay. 10/18 patients had fusions events, with an average of three fusions per patient, including GAB2-WNT11, PAK1-TENM4 and FGFR2-CEP55 fusions. Conclusions We show that RNA-Seq and copy number assays provide additional clinical value by detecting suitable drug targets beyond traditional DNA-based approaches. We are conducting further analysis on how these additionally derived drug targets could improve the current treatment schedule of those patients. Citation Format: Meissner T, Amallraja A, Mark A, Andrews A, Connolly C, Young B, De P, Williams C, Leyland-Jones B. The value of RNA-Seq for the detection of clinically actionable targets in breast cancer - A small cohort analysis [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 P1-05-22.

Introduction Variant calling based on DNA samples has been the gold standard of clinical testing since the advent of Sanger sequencing. The use of DNA variants has proved a great value to guide treatment in cancer patients. However, DNA based analysis will not inform about expression status of the gene harboring a particular variant. RNA has long been used to monitor expression. To this point RNA assays and analysis are confined to the research laboratory and rarely used clinically except in specifically defined gene signatures such as PAM50 and OncoType Dx. Beyond expression, RNA has the ability to confirm expression of DNA variants and identify fusion events. We hypothesize that the combination of DNA and RNA based data will allow the determination of variant specific expression status and improve clinical diagnostics. It has been previously shown that RNA sequencing (RNA-Seq) based variant calls are highly accurate and confirm DNA based variant calls. In this study we investigated the utility of RNA-Seq as a diagnostic assay integrated with DNA based sequencing data. Materials and Methods Targeted DNA sequencing of 321 genes was performed on 37 patient samples (FFPE), including 22 breast cancer samples by a commercial vendor. RNA-Seq on the same patient samples was performed using 100ng of total RNA. Libraries were run on the Illumina NextSeq 500 with a minimum of 75M paired 75bp reads. To evaluate RNA-seq expression reproducibility, replicates of 6 normal ovarian tissue samples (min. 50M reads) were run in sets of triplicates. STAR was used for alignment (hg19) and gene expression quantification (RefSeq). RNA-Seq based variant calling was performed using the SNPiR pipeline. Based on the results of the commercial assay, DNA based variants were examined for expression of the corresponding genes and ability to confirm variants in the RNA-Seq data. Results RNA expression data showed no corresponding gene expression for at least one single nucleotide variant (SNV) in 9/37 patients analyzed (24.3%). In 18/37 patients (48.6%) SNV corresponding expression was in the lowest quartile of expression values. Variant calls could be confirmed by RNA-Seq for 95/455 SNVs, with adequate coverage in 263 of the remaining 360 variant locations (median coverage: 34). Of these, a homozygous reference call was made in 166/263 SNVs. Concordance for RNA-Seq gene level expression data between replicates was > 0.995. Conclusions These findings suggest that RNA-Seq based data can provide clinical value when using gene expression values in combination with DNA based variant calls. We found gene level expression to be highly reproducible and will further investigate the use of spike in controls to determine clinically usable expression ranges and lower limit of expression values. To our knowledge, it has not been shown that RNA-Seq based variant calls are reproducible which is the focus of our current research as this will be one requirement for usage in a regulated environment. While our use of RNA Seq is currently limited to gene expression level data, we have demonstrated a clinically relevant benefit to using RNA Seq data as an additive feature to the current standard of DNA variant calling. Citation Format: Young B, Mark A, Meissner T, Amallraja A, Andrews A, Connolly C, Williams C, Leyland-Jones B. Utilities and challenges of RNA-Seq based expression and variant calling in a clinical setting [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 P1-05-23.

Introduction Metastasis is the primary cause of cancer-related death, with genomic evolution between primary and metastatic breast cancer only recently being studied in smaller numbers. We reconstructed the tumor evolution of a female patient originally diagnosed with localized ER+ HER2- disease to investigate the molecular changes that triggered relapse after long term aromatase inhibitor (AI) therapy and tracked them during subsequent treatments. The patient was diagnosed in 2002, relapsed in 2012 (regional lymph node), progressed in 2015 (liver metastasis), and passed away in 2018. We performed DNA- and RNA-sequencing on FFPE tumor samples and multiple liquid biopsies. The patient underwent eight lines of therapy including genome guided targeted therapy. Materials and Methods Whole exome and transcriptome sequencing was performed on the patient's primary tumor site at diagnosis (T1) and a metastatic lymph node (M1). Targeted DNA sequencing was performed on a metastatic liver sample (M2, 315 genes) and on liquid biopsies (n=11, 70 genes) every 2-3 months from 2015-2018. Results The mutational landscape between timepoints T1, M1 and M2 revealed low mutational burden at diagnosis which ultimately doubled at progression with active mutational processes (APOBEC, POLE) showing concordance between timepoints. DNA-based analysis revealed multiple mutations in the PI3K-Akt signaling pathway. Two mutations were shared between the samples: a clonal PIK3CA Q546R and a TP53 E180K mutation detected as clonal in M1/M2 and subclonal in T1. Individual samples carried private driver mutations, ranging from n=4 in T1, n=7 in M1 to n=16 in M2. While T1 harbored a single clonal driver mutation, with additional driver mutations being subclonal, M1 and M2 harbored multiple clonal driver mutations and a smaller percentage of subclonal driver mutations. A phylogenetic tree showed branching off between T1 and M1/M2. Liquid biopsies, while initially negative, started to detect mutations found among T1, M1 and M2, with increasing allele frequency (AF) throughout time. By the end of 2016, an ESR1 E380Q mutation not previously detected was found at a low AF that had rapidly increased by the end of 2017. RNA-Seq analysis revealed 908 (209 up, 699 down) genes to be differentially expressed between T1 and M1. Most significantly downregulated genes in M1 were TFF1 and PGR indicating loss-of-sensitivity / resistance to AI therapy. Most upregulated genes in M1 included PTHLH, S100P, and SOX2 which have been implicated in promoting tumor growth and metastasis. Pathway analysis between T1 and M1 showed enrichment for the hallmark gene sets ‘Estrogen Response early and late’ and ‘Epithelial mesenchymal transition’. Conclusions This phylogenetic reconstruction of the life history of a single patient's cancer revealed an increased mutational rate over time between the patient's primary tumor at diagnosis and samples taken at relapse; and a high level of heterogeneity with metastatic sites sharing only one driver mutation with the primary tumor at diagnosis and having acquired multiple de-novo driver mutations. Transcriptome profiling aided in uncovering the mechanisms that lead to the patient's initial relapse, indicating expression profile changes that promote tumor progression and metastasis as well as reduced sensitivity / resistance to the patients AI based therapy. Monitoring tumor progression through frequent liquid biopsies allowed for the detection of mutations from multiple metastatic sites, in addition to the detection and growth of an AI resistant clone harboring an ESR1 E380Q mutation that was not present in any of the solid tissue samples. Citation Format: Bing Xu, Anu Amallraja, Padmapriya Swaminathan, Rachel Elsey, Christel Davis, Stephanie Theel, Sarah Viet, Jason Petersen, Amy Krie, Gareth E Davies, Casey B Williams, Erik Ehli, Tobias Meissner. Case report - 16 year life history and genomic evolution of an ER+ HER2- breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-05-20.

Triple-negative breast cancer (TNBC) has a poor prognosis because of limited treatment options. The combination of a poly ADP ribose polymerase (PARP) inhibitor with a DNA-damaging agent has shown promise in treating TNBC; however, not all patients respond to this combination. The Src protein kinase modulates multiple cancer cell properties and plays a key role in tumorigenic processes. However, Src inhibitors as single agents have shown limited effects in solid tumors. Here, we examined the antitumor effects of the Src inhibitor dasatinib, the PARP inhibitor veliparib, and the DNA-damaging agent carboplatin in TNBC models to try and identify the combination with the most clinical potential. Dasatinib, veliparib and carboplatin were tested in TNBC cells in vitro and in xenograft tumors in vivo. Surprisingly, treatment with the combination of veliparib plus carboplatin led to an increase in Src phosphorylation. Importantly, dasatinib attenuated Src overexpression induced by veliparib plus carboplatin and further inhibited the downstream signaling of Src. In xenograft models, the triple combination of dasatinib with veliparib plus carboplatin showed greater tumor growth inhibitory effects compared with single agents or double combinations. No systemic toxicity was observed in mice treated with the triple combination. This study emphasizes the merit of evaluating the triple combination therapy, dasatinib with veliparib plus carboplatin, in TNBC clinical trials.

Cancer research is moving at a startling pace, most particularly with the identification and characterization of molecular signatures and biomarkers that will be used for prevention, early detection, diagnosis, treatment, prediction, and prognostication. The goal of cancer therapy is to match the right treatment with the right patient. To this end, several clinical trials are now employing patient stratification using “Massive Parallel Sequencing” or informally called “Next -Generation Sequencing” (NGS) to identify clinically actionable targets in real time.

The precision medicine (PM) revolution is well underway, and next-generation sequencing (NGS) is helping take cancer treatment to new levels. Finding actionable targets in real time is now a reality, and data from several clinical trials based on identified molecular alterations can be assessed and can help address the question of whether personalized treatment based on genomics produces superior survival outcomes compared with unselected treatment. Targeted treatment-based clinical trials have shown benefit in molecular subgroups of patients. Of further interest, it appears that genomics and immunotherapy are coupled to each other, since the immune system recognizes neo-antigens produced by the mutanome. Hence, some of the most important markers predicting response to immunotherapy are genomic markers, PDL1 amplification (for PD-1/PD-L1 checkpoint inhibitors), and tumor mutational burden. However, a number of challenges remain to be addressed if the use of molecular profiling-guided therapy in PM-designed clinical trials is to become the standard on which cancer treatment is based. In this chapter, we explore what it will take for PM trials that use molecular profiling as part of the eligibility criteria to be successful and the remaining hurdles that need to be overcome.

5569 Background: Evidence suggests that activation of the PI3K/AKT/mTOR pathway by paclitaxel may play a role in the development of taxane resistance. Conversely, PI3K inhibitors have been shown to sensitize tumors to the effects of paclitaxel. Therefore, the link between taxane resistance and activation of the PI3K/AKT/mTOR signaling pathway suggests inhibition of this pathway in combination with antimitotic drugs like paclitaxel may improve treatment outcomes in many malignancies. To further investigate this hypothesis we combined the TORC 1/2 inhibitor sapanisertib (TAK-228), the PI3Kα isoform inhibitor serabelisib (TAK-117), and paclitaxel in a phase I trial of heavily pretreated patients to determine the safety, efficacy, and RP2D. Methods: This is an open label, cohort study of sapanisertib (TAK-228) and serabelisib (TAK-117) given on days 2-4, 9-11, 16-18, and 23-25 with paclitaxel on days 1, 8, and 15 of a 28-day cycle. A traditional 3+3 dose escalation design with a maximum of 5 dosing cohorts was used. All 5 cohorts plus an expansion cohort are presented. Results: Enrollment has been completed and the overall results are summarized. Nineteen patients were enrolled; the majority were heavily pretreated with the average number of prior regimens exceeding 4. Based upon ITT, the ORR is 37%. The ORR is 47% in patients that completed at least 3 cycles. The clinical benefit rate is 73% and the PFS currently stands at approximately 11 months. Two patients with endometrioid endometrial adenocarcinoma achieved a complete response. All patients received comprehensive genomic profiling and 7 patients received prior mTOR inhibitor. Overall, the combination was well tolerated, except by patients in cohort 5. One DLT occurred in the last patient enrolled. The most common non-laboratory AEs were nausea (6%), fatigue (5%), and mucositis (5%). There were 45 (9%) grade 3 or 4 events, and the most common were decreased WBC and non-febrile neutropenia. Hyperglycemia was common in patients with a history of diabetes mellitus. Conclusions: Overall, the combination of sapanisertib, serabelisib, and paclitaxel was safe and efficacious throughout the first 4 cohorts. There were few serious adverse events, and most side effects were managed with routine supportive care interventions. Preliminary clinical results appear very promising, especially for patients with PI3K/AKT/mTOR pathway mutations. The positive effects of the combination were routinely seen in the lowest dosing cohorts and clinical benefit was even seen in patients that had previously failed everolimus or temsirolimus. All patients were either resistant or refractory to paclitaxel at time of enrollment, so further exploration of this combination to elucidate the mechanism of benefit is warranted. Clinical trial information: NCT03154294.

Purpose of review In this review, we summarize recent and current biomarkers and assays that are being considered in the selection of suitable patients with estrogen receptor-positive early breast cancer for extended (years 5-10) adjuvant endocrine therapy (AET). Recent findings Women with estrogen receptor-positive early-stage breast cancer (65% of cases) continue to have late risk for distant recurrence extending beyond 5 years from surgery. Recent large trials have consistently demonstrated improvement for prolonging endocrine therapy. However, endocrine therapy can cause women bothersome side effects and can negatively impact quality of life. Determining which patients remain at risk for disease recurrence and predicting which of these patients would derive the most benefit from the addition of extended AET are key issues faced by patients and oncologists today. A number of predictive molecular assays have been developed and are being considered as tools to be used in guiding the implementation of adjuvant systemic therapy. Summary The future holds much promise and as more information and understanding is acquired, treatment regimens will increasingly incorporate clinically validated biomarker assays in the decision-making process that will be of great benefit to these patients. Proving clinical utility, though, will ultimately decide their implementation.

Metastatic breast cancer is one of the leading causes of cancer-related death in women. Limited studies have been done on the genomic evolution between primary and metastatic breast cancer. We reconstructed the genomic evolution through the 16-yr history of an ER+ HER2− breast cancer patient to investigate molecular mechanisms of disease relapse and treatment resistance after long-term exposure to hormonal therapy. Genomic and transcriptome profiling was performed on primary breast tumor (2002), initial recurrence (2012), and liver metastasis (2015) samples. Cell-free DNA analysis was performed at 11 time points (2015–2017). Mutational analysis revealed a low mutational burden in the primary tumor that doubled at the time of progression, with driver mutations in PI3K–Akt and RAS–RAF signaling pathways. Phylogenetic analysis showed an early branching off between primary tumor and metastasis. Liquid biopsies, although initially negative, started to detect an ESR1 E380Q mutation in 2016 with increasing allele frequency until the end of 2017. Transcriptome analysis revealed 721 (193 up, 528 down) genes to be differentially expressed between primary tumor and first relapse. The most significantly down-regulated genes were TFF1 and PGR, indicating resistance to aromatase inhibitor (AI) therapy. The most up-regulated genes included PTHLH, S100P, and SOX2, promoting tumor growth and metastasis. This phylogenetic reconstruction of the life history of a single patient's cancer as well as monitoring tumor progression through liquid biopsies allowed for uncovering the molecular mechanisms leading to initial relapse, metastatic spread, and treatment resistance.

Introduction Despite many advances, the treatment for most patients with advanced solid tumors in the abdomen continues to be a clinical challenge. Copy number variants (CNVs) are an important part of the genomic landscape of these patients. Next-generation sequencing (NGS) tests used in the clinical setting are predominantly multi-gene targeted panels (FM, Guardant, NeoGenomics). Although this is the current standard, there is still doubt about the reliability and accuracy of such panels (PMID: 28472276), and panel based CNV-calling in clinical labs use stringent thresholds that may filter out many CNVs. The purpose of our study was to evaluate the clinical utility of a 125-gene targeted sequencing panel in detecting actionable CNVs in a cohort of colorectal cancer patients, with the eventual goal of identifying appropriate genome-guided therapy options. Materials and Methods We performed (i) targeted (350X) NGS based on the IDT xGen 125-gene Pan-Cancer panel on tumor and matched normal blood samples of 54 patients as well as (ii) very low-coverage (LC-WGS, 0.1X) whole genome sequencing on tumor and matched blood samples for the same set of patients. Bioinformatics methods included adapter trimming with bbduk, alignment with bwa-mem, quality control with FASTQC and Qualimap. CNVkit, ichorNCA, and Control-FREEC were used to call CNVs. For CNVkit and ichorNCA, the normal samples were combined to create a ‘reference normal'. Multiple window sizes were utilized to call CNVs at different scales. Results We compared the results of CNV calls from CNVkit, ichorCNA and Control-FREEC from targeted and LC-WGS data. This analysis indicates that targeted panels are at least currently not capable of reliably identifying the copy number landscape of clinical colorectal samples when matched normal samples are utilized. While within the targeted region we identified a median of five clinically actionable CNVs per sample for both targeted and whole genome sequencing (CNV amplification threshold of 5 copies), discordance of called CNVs on average was 56 percent. Numerical copy number calls tend to be higher for the targeted panel (mean: 10) vs LC-WGS (mean: 6) Beyond the targeted regions, LC-WGS detected a median of one additional clinical actionable CNV in genes such as PD-L1, JAK2, LRP1B, VEGFA, BCL2, and CCND3 which are not part of the targeted gene panel. Conclusions Our analysis suggests that CNV calling from targeted panels can be improved upon by incorporating very low-coverage whole genome sequencing. Citation Format: Anu Amallraja, Janina Fuß, Casey B. Williams, Michael Forster, Sebastian Hinz, Tobias Meißner, Alexander Hendricks. Very low coverage whole genome sequencing improves clinically relevant copy number variation calling compared to targeted sequencing [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3617.

Background: The combination of a poly ADP ribose polymerase (PARP) inhibitor with a DNA-damaging agent has shown promise in treating triple-negative breast cancer (TNBC); but not all patients respond to this combination. The Src protein kinase modulates multiple cancer cell properties and plays a key role in tumorigenic processes. However, Src inhibitors as single agents have shown limited effects in solid tumors. In this study, we examined the antitumor effects of the Src inhibitor dasatinib, the PARP inhibitor veliparib, and the DNA-damaging agent carboplatin in PTEN-null TNBC cells in vitro and tumors in vivo to try to identify the combination with the most clinical potential. Methods: The PTEN-null TNBC cell line, MDA-MB-468, was used in this study. For in vitro studies, proliferation, cellular apoptosis, and 3D on-top clonogenic growth were measured, tube formation assays and western blot analysis were performed. For in vivo studies, a xenograft model was used to examine treatment responses, and immunohistochemical analysis was performed. Results: Interestingly, treatment with the combination of veliparib plus carboplatin led to an increase in Src phosphorylation of MDA-MB-468 cells. Importantly, addition of dasatinib attenuated Src overexpression induced by veliparib plus carboplatin and further increased the activation of caspase 3 and PARP, thereby enhancing the antitumor efficacy of veliparib plus carboplatin. In an MDA-MB-468 xenograft model, the triple combination of dasatinib with veliparib plus carboplatin showed greater tumor growth inhibitory effects compared with single agents or double combinations. No systemic toxicity was observed in mice treated with the triple combination. Conclusion: Here, we provide novel evidence that veliparib combined with carboplatin drives Src activation in the preclinical model tested. Moreover, we provide provocative in vitro and in vivo data highlighting the potential for increasing therapeutic efficacy by combining dasatinib with veliparib and carboplatin in PTEN-null TNBC. Citation Format: Yuliang Sun, Xiaoqian Lin, Jennifer Aske, Casey Williams, Mark Abramovitz, Brian Leyland-Jones. Dasatinib attenuates Src pathway signaling and combined with veliparib and carboplatin potently inhibits tumor growth in PTEN-null TNBC model [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 126.

3604 Background: The link between taxane resistance and activation of PI3K/AKT/mTOR signaling suggests that by inhibiting this pathway in combination with anti-microtubule agents like paclitaxel may improve treatment outcomes in many malignancies. To investigate this further we combined the TORC 1/2 inhibitor sapanisertib (TAK-228), the PI3Kα isoform inhibitor serabelisib (TAK-117), and paclitaxel in a phase I trial to determine the safety, efficacy, and RP2D. Methods: Open label, cohort study using a traditional 3+3 dose escalation design with a maximum of 5 dosing cohorts. A dose expansion of cohort 4, the recommended RP2D, is planned for February 2020. Results: Enrollment to the DLT evaluation has been completed and the clinical results are summarized in Table. Sixteen patients have been enrolled; a majority were heavily pretreated and resistant to paclitaxel. Overall, the combination was safe and tolerable. One DLT occurred due to renal dysfunction in cohort 5. 360 adverse events have been reported, but only 28 (8%) grade 3 or 4 events. The most common events were leukopenia and non-febrile neutropenia. Two patients required dose reductions as a result of pneumonitis. The ORR is currently 46% in 13 evaluable patients. CBR is 69% and PFS is currently at 10 months. Two patients achieved a CR and three patients remain on treatment. Conclusions: The combination proved to be well tolerated in the doses and schedules used in cohorts 1-4 and exhibited very promising clinical activity in heavily pretreated patients. This regimen could prove to be a highly effective treatment option and a phase 2 study is warranted at the RP2D. Clinical trial information: NCT03154294 . [Table: see text]

// Michael Forster 1 , Adam Mark 1, 2 , Friederike Egberts 3 , Elisa Rosati 1 , Elke Rodriguez 3 , Martin Stanulla 4 , Dirk Bauerschlag 5 , Christian Schem 6 , Nicolai Maass 5 , Anu Amallraja 7 , Karla K. Murphy 8 , Bruce R. Prouse 8 , Raed A. Sulaiman 8 , Brandon M. Young 7 , Micaela Mathiak 9 , Georg Hemmrich-Stanisak 1 , David Ellinghaus 1 , Stephan Weidinger 3 , Philip Rosenstiel 1 , Norbert Arnold 1, 5 , Brian Leyland-Jones 7 , Casey B. Williams 7 , Andre Franke 1, * and Tobias Meisner 7, * 1 Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany 2 Current address: Center for Computational Biology and Bioinformatics, Department of Medicine, University of California, San Diego, CA, USA 3 Department of Dermatology, Schleswig-Holstein University Hospital, Kiel, Germany 4 Department of Pediatric Haematology and Oncology, Hannover Medical School, Hannover, Germany 5 Department of Gynaecology and Obstetrics, Schleswig-Holstein University Hospital, Kiel, Germany 6 Mammazentrum Hamburg, Hamburg, Germany 7 Department of Molecular and Experimental Medicine, Avera Cancer Institute, Sioux Falls, SD, USA 8 Pathology, Avera McKennan, Sioux Falls, SD, USA 9 Department of Pathology, Schleswig-Holstein University Hospital, Kiel, Germany * These authors share last authorship Correspondence to: Michael Forster, email: m.forster@ikmb.uni-kiel.de Keywords: breast cancer sequencing; normal RNA expression; drug selection; formalin fixed paraffin embedded; fresh frozen Received: March 07, 2018 Accepted: August 04, 2018 Published: August 17, 2018 ABSTRACT Background: While standard RNA expression tests stratify patients into risk groups, RNA-Seq can guide personalized drug selection based on expressed mutations, fusion genes, and differential expression (DE) between tumor and normal tissue. However, patient-matched normal tissue may be unavailable. Additionally, biological variability in normal tissue and technological biases may confound results. Therefore, we present normal expression reference data for two sequencing methods that are suitable for breast biopsies. Results: We identified breast cancer related and drug related genes that are expressed uniformly across our normal samples. Large subsets of these genes are identical for formalin fixed paraffin embedded samples and fresh frozen samples. Adipocyte signatures were detected in frozen compared to formalin samples, prepared by surgeons and pathologists, respectively. Gene expression confounded by adipocytes was identified using fat tissue samples. Finally, immune repertoire statistics were obtained for healthy breast, tumor and fat tissues. Conclusions: Our reference data can be used with patient tumor samples that are asservated and sequenced with a matching aforementioned method. Coefficients of variation are given for normal gene expression. Thus, potential drug selection can be based on confidently overexpressed genes and immune repertoire statistics. Materials and Methods: Normal expression from formalin and frozen healthy breast tissue samples using Roche Kapa RiboErase (total RNA) (19 formalin, 9 frozen) and Illumina TruSeq RNA Access (targeted RNA-Seq, aka TruSeq RNA Exome) (11 formalin, 1 frozen), and fat tissue (6 frozen Access). Tumor DE using 10 formalin total RNA tumor samples and 1 frozen targeted RNA tumor sample.

Background: The optimal treatment strategy for patients with metastatic breast cancer (MBC) is currently unknown. Resistance to standard therapies like anthracyclines and taxanes limit the number of treatment options in many patients to a small number of non-cross-resistant regimens. We hypothesized that genomic and proteomic profiling of clinical MBC samples would identify genomic alterations that are linked to targeted therapies, and that this could facilitate a personalized approach to therapy for our patients. Methods: We retrospectively analyzed 31 consecutive metastatic breast cancer patients that had genomic and/or proteomic studies sent over a 4 month period from February to May 2014. All patients were seen in our Genomic Oncology Clinic and subsequently underwent a rebiopsy of a metastatic site. Formalin-fixed, paraffin-embedded (FFPE) tissue was sent to either Foundation Medicine for genomic profiling, Theranostics for reverse-phase protein microarray, or both. Standard immunohistochemistry for ER, PR, and HER2 was also performed on all patients. Results: Genomic or proteomic alterations were identified in all 31 patients. All patients harbored at least one actionable target and a treatment recommendation for a currently available FDA approved drug or drug combination was able to be suggested in all but one patient. The most commonly observed genomic alterations were within PIK3CA (26%), TP53 (23%), CCND1 (19%), and MYC (16%). Over 30 distinct genomic alterations were identified. Proteomic results were available from 16 patients. Activation of the AKT/mTOR pathway was evident in a majority of patients. A change in HER2 status was also found in 26% of patients. 16% of cases underwent a negative to positive conversion in HER2 status while 10% of cases underwent a positive to negative conversion. It is notable that all 5 patients that underwent a negative to positive conversion in HER2 status had biopsies taken from metastatic disease in the liver. Conclusions: All patients in this retrospective study harbored genomic or proteomic alterations that are associated with targeted therapies. Treatment recommendations were suggested in all but one patient and a majority of patients are receiving the suggested therapy. Our data demonstrate that routine genomic and proteomic analysis in a clinical setting makes a significant positive impact for patients. Citation Format: Casey B Williams, Pradip De, Nandini Dey, Kirstin A Williams, Jessica Klein, Michelle King, Misty Small, Brigitte Cyr, Scooter Willis, Yuliang Sun, Jennifer Carlson, Brandon M Young, Amy Krie, Brian Leyland-Jones. New treatment options for metastatic breast cancer revealed by reverse-phase protein microarray and genomic profiling [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 P2-05-14.

HERA is an international multi-center randomized trial comparing 1 or 2 years trastuzumab, given every 3 weeks, with observation in women with HER2+ breast cancer after standard neoadjuvant or adjuvant chemotherapy. From December 2001 to June 2005, 5102 patients were randomized. Comparing 1 year trastuzumab with observation at 8 years of follow-up, statistically significant differences in disease-free survival (DFS) and overall survival, despite crossover to trastuzumab of observation arm patients, were found. No benefit in DFS of 2 years compared to 1 year trastuzumab was found[Goldhirsch 2013]. To determine possible predictive single-gene biomarkers, an exploratory ITT analysis, with DFS as the primary endpoint, was conducted using mRNA expression data from 610 TransHERA FFPE samplesprofiled on Illumina Whole-Genome DASL cubic spline normalization was applied to the data. Outcome was obtained from the HERA database with 8 years median follow-up and clinical cut-off date April 12, 2012. Characteristics were well balanced between treatment groups. The exploratory analysis of 20,464 genes using DFS as the endpoint identified C8A as a possible biomarker that is prognostic and predictive of response to treatment. Cox regression was used to model DFS, with the interaction term between treatment and C8A as a continuous and a categorical variable split on the cohort mean. The observation arm consists of 199 samples with 66 events and the trastuzumab arm(1&2-year combined) of 411 samples with 108 events. A statistically significant interaction between C8A mRNA and treatment was detected (p C8A is a member of the membrane attack complex and is part of the innate immune system. C8A inserts into the membrane of the target cell and binds with multiple copies of the pore-forming C9 leading to cell lysis. From the GeneAtlas, C8A is highly expressed in liver tissue suggesting an advantage for tumors with high expression of C8A and innate immune response. The Cancer Cell Line Encyclopedia indicates a wide range of C8A mRNA expression. C8A as a single gene biomarker that is prognostic of DFS and predictive of benefit from trastuzumab has the potential to improve the standard of care in HER2+ breast cancer. Understanding the advantage of over expression of C8A related to the innate immune response can give insight into the mechanisms that drive cancer. We note with caution that this finding is the result of an exploratory analysis and is being pursued in additional trastuzumab cohorts for further validation. Citation Format: Scooter Willis, Varvara Polydoropoulou, Zoi Tsourti, Urania Dafni, Brandon Young, Bradley Long, Pradip De, Nandini Dey, Casey Williams, Mitch Dowsett, Brian Leyland-Jones. Exploratory analysis of single gene predictive biomarkers in TransHERA DASL cohort reveals that C8A mRNA expression is prognostic of outcome and predictive of benefit of trastuzumab [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 P3-06-02.