Karlin, Nina J.

Abstract Context Clinical applications of genomic assessment of thyroid cancers are rapidly evolving. Objectives, Design, and Setting We studied tumor samples from patients with imminently threatening and rare thyroid cancers to identify genomic alterations that might correlate with outcomes and/or be productively therapeutically targetable. Patient Context Progressive and metastatic, and/or rare, thyroid cancers were studied, 2012 to 2016, at Mayo Clinic sites. Intervention The intervention was Foundation One tumor interrogation. Main Outcome Measures Main outcome measures included genomic alterations, patient characteristics, and overall survival. Results Samples from 55 patients were evaluated: 20 anaplastic thyroid cancers (ATCs) (36%), 25 radioactive iodine–refractory differentiated thyroid cancers (DTCs)/poorly differentiated thyroid cancers (PDTCs) (45%; 14 papillary thyroid cancer [PTCs], 6 PDTCs, 5 Hürthle cell cancers), 8 medullary thyroid cancers (MTCs) (15%), and 2 others (a spindle epithelial tumor with thymus-like differentiation, and a primary thyroid sarcoma). Overall, 72% of DTCs, 79% of ATCs, and 75% of MTCs were deemed to have potentially productively targetable alterations. The most commonly encountered mutation was of TERT promoter (56% of DTCs, 68% of ATCs)—but this is not presently targetable. Targetable BRAFV600E mutations were found in 40% of DTCs/PDTCs (83% of PTCs) and 32% of ATCs; of MTCs, 75% had targetable RET mutations, and 25% HRAS mutations. Of patient tumors with nonmutated BRAFV600E, 53% of DTC/PDTCs and 69% of ATCs had other potentially productively targetable mutations. Genomic alterations in our series of poor prognosis metastatic DTC/PDTCs also closely resembled those seen in ATC. Conclusions Whereas genomic interrogation of favorable prognosis thyroid cancer seems ill advised, potentially productively targetable mutations were demonstrated in the majority of tumors from patients with metastatic thyroid cancers requiring systemic therapy, suggesting a rationale for the selective application of this technology.

Abstract Background: Unlike with solid organ cancers, little data is available on how diabetes mellitus (DM) and hematologic malignancies interact to affect survival and glycemic control. We examined the impact of DM on survival in patients with leukemia and the effect of leukemia on glycemic control. Materials and Methods: Patients with leukemia with and without DM were matched 1:1 (2007–2017), 70 matched pairs (total N=140 pts) were included in the analysis. We compared characteristics between cases and controls and assessed survival with the Kaplan-Meier method and Cox proportional hazards model. Mixed models compared hemoglobin A1c (HbA1c) and glucose levels over time. Results: The median age of patients at diagnosis was 56 (18–94); 60% were male and 89% had acute leukemia. Among those with DM, HbA1c was only recorded in 25 of 70 patients during the year following cancer diagnosis and was 6.8%. There was no change in HbA1c values over time in these DM patients. Mean glucose was significantly different between DM and non-DM patients (p<0.001). Time (days since leukemia diagnosis) was significant (p<0.001) and there was a significant interaction effect (p=0.01). Glucose values increased in the DM patients during the year following diagnosis, while remaining stable in those without DM. Median follow-up time was 23.2 months. Three-year survival was estimated at 46% for DM patients versus 45% in non-DM pts by Kaplan Meier method (p=0.79). Hazard ratio (stratification for matched pairs) was 1.05 (95% CI: 0.57 - 1.94; p=0.88). Three-year relapse-free survival was estimated at 34% for DM patients versus 43% for non-DM patients (p=0.58). Hazard ratio (stratification for matched pairs) = 1.10 (95% CI: 0.61–1.98; p=0.76). Conclusions: DM did not adversely impact survival in patients with leukemia. Leukemia and its treatment did not affect glycemic control. This should be reassuring to hematologists and endocrinologists who treat patients with leukemia and diabetes.

Abstract Background: We have previously examined the link between diabetes mellitus (DM) and malignancy with respect to mortality, but little is known about how the cancer affects glycemic control. Therefore, the aim of this study was to evaluate metabolic parameters in patients with cancer with and without DM. Methods: We selected 1404 patients with newly diagnosed prostate, breast, lung, colorectal, and pancreatic cancer from the institutional cancer registry from 2010–2015. Records were selected and matched 2:1 cancer without DM (n=936) and cancer and concurrent DM patients (n=468). Patients were matched by year of diagnosis, age, gender, and cancer type. Metabolic parameters during the year after cancer diagnosis were examined using linear mixed models with fixed effects for time, cancer type, DM status and individual-specific random effect allowing each patient to have a different intercept. Results: Prostate cancer accounted for the majority of cases (n=199), followed by lung cancer (n=91), breast cancer (n=71), colorectal cancer (n=54), and pancreas cancer (n=53). Mean overall hemoglobin A1c (HbA1c) was 6.9 (1.2)%. Pancreas cancer patients had higher HbA1c overall (p=0.02). There was no change in HbA1c one year post cancer diagnosis (p=0.28). Mean glucose in non-DM was 108(18) mg/dL and 146 (45) mg/dL in DM pts. Lung and pancreas cancer patients had higher glucose values overall (p<0.001). Time (p<0.001), DM (p<0.001) and time * DM (p=0.02) were significant in a mixed model. A decrease in glucose over the year was observed in DM patients across all cancer types. Conclusions: A diagnosis of malignancy does not worsen glycemic control within the first year of cancer diagnosis. This should be reassuring to endocrinologists and oncologists who treat patients with DM and cancer. Longer term studies, and analysis in larger and more diverse patients groups are needed.

5544 Background: Pazopanib, an orally bioavailable multitargeted inhibitor of kinases including VEGF-R, demonstrated impressive activity in metastatic differentiated thyroid cancer (49% durable RECIST PRs) and promising preclinical activity in anaplastic thyroid cancer (ATC) models, prompting its evaluation also as a candidate therapeutic in advanced ATC. Methods: A multicenter single arm phase II trial of 800 mg pazopanib daily was undertaken with the primary endpoint of RECIST response rate. The trial was designed such that there would be a 90% chance of detecting a response rate of >20% at the 0.10 significance level when the true tumor response rate is >5%. A pre-specified stopping rule designated that enrollment would cease unless 1 or more RECIST PRs+CRs were observed in the first 14 of 33 potential patients. Eligibility required informed consent, >18 years of age, performance status ECOG 0-2, systolic blood pressure (BP) <140 mm Hg and diastolic BP <90 mm Hg at entry, QTc interval <480 msecs, and measurable disease by RECIST criteria. Anatomical imaging and toxicity evaluations were required every 4 weeks. Results: Sixteen patients were enrolled. One patient withdrew prior to therapy, leaving 15 evaluable patients – 33.3% were male, with a median age of 66 years (range 45-77); 11 of 15 patients had progressed through prior systemic therapy. Four patients required 1-2 dose reductions, with the most common severe toxicities (CTC-AE version 3.0 grades 3-5) hypertension (13%) and pharyngolaryngeal pain (13%). Reasons for treatment discontinuation included: disease progression (12 pts), death on study due to a vascular event possibly related to treatment (1 pt.), and intolerability (radiation recall tracheitis – 1 pt, and uncontrolled hypertension – 1 pt). Although transient disease regression was observed in several patients, there were no confirmed RECIST tumor responses, triggering study closure at time of interim analysis. Two patients are alive with disease 9.9 months and 2.9 years post-registration; the remaining 13 died of disease. The median time to progression was 62 days and the median survival time was 111 days. Conclusions: Pazopanib has poor single agent activity in advanced anaplastic thyroid cancer.

1059 Background: Relapsed TNBC is characterized by its poor prognosis. B is a synthetic DNA minor groove binding non-cross resistant agent that is fully active against DNA-mismatch repair deficient tumor cells. C increases GSH/GST in which enhances the efficacy of B. Methods: Phase II study in pts with mTNBC. C Day 1 followed by B Day 2, repeated every 21 days. Aim: Efficacy of C + B in mTNBC. Primary endpoint: PFS at 3 mo. Secondary endpoints include ORR, duration of response (DOR), 6-mo PFS, OS and AE profile. Tertiary endpoints include assessment of baseline GSH levels, prevalence of BCRA1 mutation and pERK, and correlations with outcome. Results: Closed 3/2012. 48 pts accrued (1 ineligible pt). Median f/u 11.4 mo (6.6-14.8); 2 pts still on treatment. 47 pts evaluable for the PFS endpoint and AEs. 49% received therapy as 3rd-5th line. Median number of cycles = 4 (range 1-15). There are currently 9 confirmed responses (8 PR and 1 CR); DOR = 2.6-14.5 mo. The 3-mo PFS = 51%; 6-mo PFS = 28%; the median TTP is 3.2 mo. AE data: 75% G3/4 hematologic AE: febrile neutropenia 19%. Non-hematologic AEs included G3 (47%) and G4 (15%): G3 fatigue 17%; and no G5 non-heme AE. No correlation of GSH/GST levels with outcome was found. Among 35 pts with evaluable data, no association between BRCA1 expression and outcomes was found. pERK expression was negatively associated with 3-mo PFS, but not 6-mo PFS. Cytoplasmic pERK expression was negatively associated with tumor response (p=0.03). No significant effect of BRCA-1 or pERK expression was found on OS. Conclusions: This trial showed B + C is an active regimen, especially in heavily pretreated mTNBC pts. Correlative data demonstrated a negative association between pERK expression and outcomes. A randomized phase II trial is in development. Clinical trial information: NCT01091454.

612 Background: The aim of this study was to examine the impact of diabetes mellitus (DM) on survival in neuroendocrine tumor and the impact of neuroendocrine tumor on glycemic control in DM. Methods: Patients with newly diagnosed neuroendocrine tumor with and without DM were matched 1:1 according to age, gender, and year of cancer diagnosis (2005-2017). The file was linked to the electronic medical record to obtain information on DM and neuroendocrine tumor therapies and laboratory results. There were 59 matched pairs (total 118 patients) included in the analysis. We compared characteristics between cases and controls and assessed survival with the Kaplan-Meier method and Cox proportional hazards model. Mixed models compared hemoglobin A1c and glucose levels over time. Results: Median age of patients at diagnosis was 67 (40-86); 41% had stage IV disease. Women constituted 49% of the study population; 22% had pancreatic neuroendocrine tumor and 45% had another GI primary neuroendocrine tumor. No differences in race/ethnicity, marital status, alcohol or tobacco use were detected between cancer patients with and without DM. Mean BMI was significantly different between DM and non-DM patients (31.0 [7.90] versus 26.4 [5.27]); p = 0.011. Among those with DM, mean HbA1c during the year following cancer diagnosis was 7.3%. Mean glucose was significantly different between DM (159.1 [43.5] versus non-DM pts 117 [31.5]); p < 0.001. Median follow-up time was 32.8 (2.4-165.4) months in alive patients. Three year survival was estimated at 72% (95% CI: 60-86%) for DM patients versus 80% (95% CI: 70-92%) in non-DM patients by Kaplan Meier method (p = 0.82 log rank test). Hazard ratio (stratification for matched pairs) = 1.33 (95% CI: 0.56 – 3.16; p = 0.51). Conclusions: DM did not adversely impact survival in patients with neuroendocrine tumor. Neuroendocrine tumor and its treatment did not affect glycemic control. This should be reassuring to oncologists and endocrinologists who treat patients with neuroendocrine tumors and diabetes.