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INTRODUCTION Mutations in BTK and PLCG2 have been reported to occur in ~80% of CLL patients (pts) who have progression of disease on ibrutinib therapy (Woyach, JCO 2017; Ahn, Blood 2017). These mutations are described as appearing months before actual relapse and thus considered as a potential predictive biomarker for future relapse (Quinquenel, Blood 2019). However, the outcomes of these pts after disease progression are not well described. In this study, we seek to investigate time to next therapy and overall survival (OS) following progression among CLL pts on ibrutinib therapy with and without these resistance mutations. METHODS Between 10/2012 and 6/2019, we identified 34 pts in the Mayo Clinic clinical CLL resource who progressed while receiving ibrutinib therapy and also had testing for BTK and PLCG2 mutation performed as part of routine clinical practice at either NeoGenomics Laboratories or The Ohio State University. OS was calculated from time of ibrutinib progression to last known alive or death date; OS was plotted using Kaplan Meier methods and was compared using the log-rank test between various groups (e.g., mutation positive vs negative; CLL progression vs Richter's). Cumulative incidence of time to next treatment in those who had a treatment after progression was adjusted for the competing risk of death. RESULTS Of 34 pts who progressed while receiving ibrutinib, 26 pts experienced CLL progression and 8 pts had Richter's transformation; baseline characteristics in Table 1A. The presence of a BTK or PLCG2 mutation was found in 20/34 (59%) pts (specific mutations in Table 1B). BTK mutation alone was present in 9 pts, 7 pts had PLCG2 mutation alone, and 4 pts had both mutations. Median time between a positive test and start of next therapy was 4 months (range 1-19 months) and did not vary between BTK vs PLCG2 mutations. Among the 26 pts with CLL progression, 18 (69%) pts had a mutation present: BTK alone (n=8), PLCG2 alone (n=6), both (n=4). Therapy following progression on ibrutinib in these pts was as follows: venetoclax (n=16; 11 pts who continued ibrutinib in combination), idelalisib (n=4), investigational treatments (n=2), continued ibrutinib alone (n=2), dose-adjusted EPOCH-R (etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin, and rituximab; n=1), and unknown (n=1). Twelve of the 26 pts with CLL progression on ibrutinib, including 8 pts with a prior resistance mutation detected, had subsequent progression of disease on the aforementioned next line therapy. Treatment of these patients consisted of the following: restarted ibrutinib in addition to current treatment of venetoclax (n=5), venetoclax (n=2), pembrolizumab (n=2; 1 pt with continued ibrutinib), obinutuzumab with continued ibrutinib (n=1), gemcitabine and vinorelbine with continued ibrutinib (n=1), and no further treatment (n=1). Among the 8 pts with Richter's transformation as the initial progression event on ibrutinib after mutation testing, 1 pt had a BTK mutation and 1 pt had a PLCG2 mutation. Treatments following progression on ibrutinib included multi-agent chemoimmunotherapy (n=3; 2 pts received rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone [R-CHOP] with continued ibrutinib and 1 pt received doxorubicin, bleomycin, vinblastine, dacarbazine [ABVD] alone), pembrolizumab (n=3; 1 pt in combination with continued ibrutinib), venetoclax in combination with continued ibrutinib (n=1), and venetoclax and obinutuzumab (n=1). The median time to next treatment (second line of treatment beyond ibrutinib) for the 31 pts who started another therapy following progression on ibrutinib was 16.7 months (95% CI 9.6-NE; Figure 1A) and was not significantly different for pts with or without a resistance mutation (p=0.57). Median OS for all 26 pts with CLL progression was 28.7 month and there was no difference according to presence or absence of a resistance mutation (median 28.7 months vs 18.2 months, p=0.53; Figure 1B). The 8 pts with Richter's transformation had a median OS of 7.1 months (95% CI 2.0-NE). CONCLUSION Approximately 60% of pts tested in this progression cohort had a BTK or PLCG2 mutation at time of or preceding progression on ibrutinib therapy. OS and time to next therapy did not differ statistically between pts with mutated vs non-mutated clones; however, caution should be applied with the conclusions given the limited sample size. Disclosures Ding: DTRM Biopharma: Research Funding; Merck: Research Funding. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Kay:MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB. Parikh:Ascentage Pharma: Research Funding; Genentech: Honoraria; Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding.

Background: The 2008 International Working Group for CLL (IWCLL) criteria define MBL as a clonal B-cell disorder with a peripheral blood B-cell count of <5 x 109/L, in the absence of cytopenias(s), lymphadenopathy and/or organomegaly on physical examination, and no other concomitant lymphoproliferative disorder. In the presence of palpable lymphadenopathy and/or organomegaly, and a B-cell count of < 5 x 109/L, a diagnosis of small lymphocytic lymphoma (SLL) is established. A study by Gentile et al (Am J Hematol. 2013) reported that 29 out of 62 individuals with clinically identified MBL (42%) had lymphadenopathy identified on CT imaging. Notably, however, after a median follow-up of 35 months, the rate of progression among cases of MBL with lymphadenopathy identified on CT imaging was only 6.9% (2/29 patients), which was no different than in cases of MBL without lymphadenopathy on CT imaging (rate of progression, 9%; 3/33 patients). Our study sought to 1) determine if lymphadenopathy and/or organomegaly detected by imaging studies performed for unrelated reasons in individuals with MBL can identify a subset with shorter time to first CLL therapy (TFT) and overall survival (OS); and 2) compare outcomes of individuals with MBL who have incidentally detected lymphadenopathy/splenomegaly and SLL patients. Methods: We used the Mayo Clinic CLL Database to identify individuals with high-count MBL (absolute B-cell count: 0.5 - 4.9 x 109/L) and divided them into the following three cohorts: a) Cohort A: no imaging studies available at MBL diagnosis; b) Cohort B: imaging studies done within one year of MBL with no evidence of lymphadenopathy and/or organomegaly; and c) Cohort C: imaging studies done within one year of MBL with lymphadenopathy and/or organomegaly, attributable to MBL. All individuals with MBL were first seen at Mayo Clinic after 1/1/2002; those with a concomitant lymphoproliferative disorder within 3 months of diagnosis were excluded. Patients with SLL seen during the same time interval were identified as a comparison cohort. We compared the baseline characteristics (Kruskal Wallis for continuous and Chi-square for categorical variables) and TFT and OS across the three MBL cohorts, and patients with SLL. Cumulative incidence of TFT was adjusted for the competing risk of death. Age- and sex-adjusted OS was analyzed using inverse weights methods. Results: 657 individuals with high-count MBL with a median follow-up of 6.7 years were identified: 415 (63%) individuals were in Cohort A, 142 (22%) in Cohort B, and 100 in (15%) Cohort C. Compared to Cohort B, individuals in Cohort C were more likely to have unmutated IGHV, high expression of CD38, and higher beta-2 microglobulin level (Table 1). SLL patients were younger, had higher rate of unmutated IGHV, and had high expression of CD49d compared to MBL individuals in Cohort C (Table 1). There was suggestive evidence of a difference in TFT between Cohorts B and C (estimated 10-year treatment rate 28.3% vs. 41.6%; p=0.16; HR 1.62 95% CI 0.84-3.15). TFT was significantly shorter in SLL patients compared to those with Cohort C (estimated 10-year treatment rate 71% vs. 41.6%, respectively, P<0.001; Figure 1A). There was a trend toward shorter OS in Cohort C compared to Cohort B (estimated 10-year OS rate 53.7% vs. 64.2%, respectively, P=0.09; Figure 1B). In contrast, there was no difference in OS among MBL individuals in Cohort C compared to those with SLL (estimated 10-year OS rate 56.9% vs. 62.6%, P=0.72). Summary/Conclusion: Our findings demonstrate that individuals with MBL who have incidentally identified lymphadenopathy/splenomegaly at diagnosis are more likely to have an unfavorable risk profile, shorter TFT and OS compared to patients who did not have lymphadenopathy/splenomegaly at MBL diagnosis. Additionally, these individuals have a longer TFT but similar OS compared to SLL patients seen during the same time interval. If externally validated, these findings have significant implications for individuals with newly diagnosed MBL. Disclosures Ding: Merck: Research Funding; DTRM Biopharma: Research Funding. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Kay:MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB. Parikh:AstraZeneca: Honoraria, Research Funding; Janssen: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding.

Abstract INTRODUCTION Opsoclonus–myoclonus syndrome (OMS) is a rare neurological disorder characterized by spontaneous multidirectional saccadic eye movements, myoclonus, and ataxia. It is suspected to be an autoimmune mediated process precipitated by a paraneoplastic or infectious trigger. Among the pediatric population, OMS is often associated with neuroblastoma and anti-Hu antibody. Paraneoplastic syndromes in adults manifesting as OMS are most commonly described in breast, gynecological and small cell lung cancer with associated anti-neuronal antibodies (ANNA-2; anti-Ri). We describe the first case of OMS associated with lung adenocarcinoma and Contactin-associated protein-like 2 (Caspr2) antibody. CASE REPORT: A 46-year-old-woman with history of limited small cell lung cancer (SCLC) status-post chemotherapy with cisplatin and etoposide and prophylactic whole brain radiation, presented with new onset gait instability, nausea, vomiting, vertigo, and opsoclonus. Two months prior to her presentation, a chest computed topography (CT) revealed no evidence of recurrent disease. Brain MRI revealed T2 hyperintensities in the white matter and central pons presumably related to chronic small vessel ischemic changes, unchanged from prior imaging. CSF studies revealed normal cell count, glucose, and protein. Gram stain, culture and meningoencephalitis panel were negative. Her paraneoplastic panel revealed a positive Caspr2 antibody. A repeat CT chest for cancer surveillance revealed a new lung mass. Immunotherapy treatment included plasmapheresis, corticosteroids, and intravenous immunoglobulin therapy. She underwent a biopsy of the new pulmonary lesion and the pathology was consistent with non-small cell lung carcinoma. Her symptoms slowly improved after treatment. Unfortunately, her disease progressed on repeat PET scan despite surgical resection of the lung mass. She ultimately elected for hospice. CONCLUSION We report a novel antibody, Caspr2, occurring in association with paraneoplastic OMS. While SCLC is the most common neoplasm associated with OMS among adults, non-small cell lung carcinoma should be considered. Prompt immunotherapy and neoplasm treatment may result in improvement.

Abstract BACKGROUND Conventional magnetic resonance imaging (MR) guides patient care in GBM. However, there is mounting awareness that MR enhancement is non-specific reflecting either tumor progression or non-tumoral inflammatory changes. Histological evaluation of GBM is held as the gold standard for disease assessment. However, the invasiveness of this methodology and the sample sparsity limit its usefulness. Methods to infer histological underpinnings of MRI are needed to improve clinical care. METHODS A transfer learning mixed effects model based on T1Gd and FLAIR MR voxel based image features trained and cross-validated to predict FPKM values of CD68, CASP3, CD8A and IL13RA2. Training data included RNAseq from 38 image-localized biopsies from 15 newly-diagnosed GBM patients. These models were then applied to two independent patients, chosen based on therapy and the quality of image registration, at three different time points, just prior to receiving IL13RA2 targeted CAR-T therapy for rGBM, after 2 cycles and after 4 cycles, resulting in a voxel-based prediction of the relative expression levels of these genes. RESULTS Cross-validation of the proposed machine learning models demonstrated a Pearson Correlation coefficient between predicted and observed FPKM values of 0.89 (CD68), 0.92 (CASP3), 0.93 (CD8A), and 0.88 (IL13RA2). When the models were applied to the two CAR-T patients, CD68-modeled expression levels were seen to increase throughout therapy for one patient, while remaining stable for the other. Survival from first CAR-T infusion was, respectively, 412 and 83 days suggesting that the increased CD68 was indicative of therapeutic effectivity. Further, the spatial activity predictions were consistent with expected therapeutic action as the correlation coefficient between CASP3 and the product of IL13R2 and CD8A expression was 0.81, suggesting the T-cells targeting IL13RA2 were inducing cell death. CONCLUSIONS Preliminary results with our model highlights the potential of spatially resolved radiomic maps to provide insight into regional therapeutic effectivity.

Abstract PURPOSE Brain tumor related epilepsy (BTE) is a major co-morbidity in patients with glioma. It is difficult to determine whether the use of anti-epileptic drugs is necessary. We attempted to build a machine-learning model to predict the probability of seizure presentation (SP) with glioma. METHODS We trained a random forest classifier using the following variables: volumetric data of pre-treatment MR images (T1Gd and T2-FLAIR sequences), patient demographics (age; sex), and measurements of tumor proliferation (log(ρ)), invasiveness (log(D)) and their relative ratio (log(ρ/D)). Our cohort consisted of 221 patients total. Using an 80-20 ratio, we used 176 patients (76 SP, 100 nSP) for training and the remaining 45 patients (19 SP, 26 nSP) were used for testing. We also trained on male-only and female-only cohorts to evaluate any sex differences in prediction. For training, 108 males (53 SP, 55 nSP) were used and 28 for testing (14 SP, 14 nSP). We used 72 females (21 SP, 49 nSP) for training and 15 (7 SP, 8 nSP) for testing. We corrected for class imbalance in the female cohort before training. Using 10-fold cross-validation and a separate testing set, we measured performance by ROC curve (AUC), accuracy, sensitivity, and specificity of predictions (average of folds in cross validation). RESULTS The female model achieved the highest AUC (0.853) followed by the mixed model (0.726) and the male model (0.651). In the validation set, the accuracy/sensitivity/specificity of the three cohorts were as follows: mixed (0.726/0.696/0.750), female (0.853/0.830/0.875), and male (0.651/0.577/0.722). The performance of the testing set, in terms of accuracy/sensitivity/specificity were: mixed (0.733/0.74/0.73), female (0.8/0.57/1), and male (0.714/0.64/0.79). CONCLUSION We found a negative correlation between seizure probability and size and invasiveness of tumors. Our model shows promising performance on testing set data. Further cohort studies and training is warranted.

Abstract INTRODUCTION Glioblastoma (GBM) is the most common malignant primary brain tumor in adults with a median overall survival (OS) of 15months. Despite advancements in treatments, prognosis is dismal and the prognostic significance of tumor location is not entirely understood. METHODOLOGY: In our study, we investigated sex-specific volumetric, tumor growth kinetics, and outcome differences among GBMs in various brain locations. Primary GBM patients with pretreatment magnetic resonance imaging (MRI) data (N=289, 173 males, 116 females) were selected from our brain tumor repository. Tumor abnormality was segmented on T1-weighted post-gadolinium contrast agent (T1Gd) MRIs. We utilized the Harvard-Oxford brain atlases to determine the location of GBMs. RESULTS Overall, our study found smaller tumors in the left hemisphere. This may be expected as left-hemispheric GBM symptoms could present earlier, leading to earlier diagnosis and treatment. However, when the cohort was split by sex, we found this observation significant for females only in the parietal lobe (p < 0.0001). Further, female GBMs demonstrated smaller necrotic volume in the left hemisphere (p = 0.030). Sex-specific differences in incidence were noted in the temporal and occipital lobes (2M:1F). Comparing tumor growth kinetics in different brain locations and hemispheres, females had significantly lower tumor proliferation rates in the left hemisphere (p = 0.009) and lower tumor proliferation rates in the left frontal lobe (p = 0.031). Controlling for treatment, patients with frontal lobe tumors had significantly longer OS compared to those with GBMs in the temporal lobe (p = 0.046, 312 days). Differences in growth velocities were noted between frontal and parietal lobe with frontal GBMs having lower velocities in comparison to parietal lobe GBMs. CONCLUSION Together, our results demonstrate that tumor growth and proliferation rates may vary based on location and sex. Additional research is needed to further explore the clinical significance of tumor location.

Abstract Sex differences in brain tumor related epilepsy (BTE) as an initial symptom of glioma are rarely investigated. Sex differences are being explored with increased interest more recently. Epidemiological studies have generally indicated overall incidence of epilepsy to be slightly higher in males than females, but a higher incidence of idiopathic generalized epilepsy has been seen in females in some studies. Clinicians regularly face the challenge of anti-epileptic drug prescription determination in patients with newly identified brain mass and would greatly benefit from knowing clinical characteristics in BTE. We analyzed clinical characteristics in patients with pathologically-determined glioma with known seizure status at clinical presentation using non-parametric and Fisher’s Exact tests with the entire cohort and male and female separately. From our clinical data repository, we identified 223 patients (females, n=86 (39%); males, n=137 (61%)) divided by those that presented with seizure (SP, n=96, 43%; F, n= 28; M, n= 68) and those that presented without seizure (nSP, n=127, 57%, F n=58, M n=69). In sex-specific analysis males had a significantly (x2=6.28, p=0.01) higher proportion of SP (49.6%) than females (32.6%). There was a dependence between seizure presentation status and tumor grade in males (x2=5.94, p=0.015). Tumor kinetics in the female cohort showed significantly (p< 0.0001) more diffuse tumors in SP compared to nSP. Right-sided tumors were predominantly nSP, while left-sided tumors were split more evenly between SP and nSP. The predominance of nSP among right-sided tumors seems to be driven by females (74%), male right-sided tumors were split more evenly between SP and nSP. Seizure status is dependent on tumor location for the combined cohort, however not for males (x2=5.23, p=0.16) or females (x2=4.34, p=0.23). Clearly there are sex differences and similarities in clinical characteristics at glioma presentation. Further characterization could lead to improved adherence of national standards for AED prescription.

Abstract Glioblastoma (GBM) is the most aggressive primary brain tumor with an average survival of 15 months with standard of care treatment. GBM patients typically present with necrosis surrounded by enhancement on T1-weighted post gadolinium magnetic resonance imaging (T1gd MRI), however some patients present with a significant cystic component. Cysts are caused by different underlying biological mechanisms to necrosis and are important to identify for future clinical investigations. These cystic components can be manually identified through MRI but this process can be time consuming for large patient cohorts. Over the last two decades, our lab has collected serial MRI data of brain tumor patients. With over 70,000 images now in the database and that number increasing daily, it is clear that we have a unique resource for clinical investigation and a need to automate this process. To this end, the aim of this work was to develop and assess the performance of a convolution neural network (CNN) model for automatic detection of cystic GBMs. In this retrospective IRB-approved work, we collected pretreatment MRIs of a patient cohort consisting of 85 patients with a significant cystic component at presentation along with 400 non-cystic GBM, both identified manually through MRI. Image slices with a view of the cystic component were used as positive samples for training. Data were randomly split into training, validation, and test sets using a 70:15:15 ratio. The proportion of positive to negative cases was comparable between sets. Prior to training, we used image augmentation techniques to compensate for the class imbalance in our data. Our results showed that deep learning networks can automatically detect cystic GBMs on MRIs with high accuracy and thus illustrates the potential use of this technique in clinically relevant settings.

Aims Cardiovascular health metrics predict the risk not only of cardiovascular diseases but also of several types of cancers. Microvascular endothelial dysfunction can predict future cardiovascular adverse events, but the predictive value of microvascular endothelial dysfunction for future risk of solid-tumor cancer has not been characterized. Methods A total of 488 patients who underwent microvascular endothelial function assessment using reactive hyperemia peripheral arterial tonometry were included in this study. Microvascular endothelial dysfunction was defined as a reactive hyperemia peripheral arterial tonometry index ≤2.0. Results Of 221 patients with a baseline reactive hyperemia peripheral arterial tonometry index ≤2.0, 21 patients (9.5%) were diagnosed with incident solid-tumor cancer during follow-up, whereas of 267 patients with a baseline reactive hyperemia peripheral arterial tonometry index >2.0, 10 patients (3.7%) were diagnosed with incident solid-tumor cancer during follow-up ( p = 0.009). Patients with a reactive hyperemia peripheral arterial tonometry index ≤2.0 had lower solid-tumor cancer-free survival compared to patients with a reactive hyperemia peripheral arterial tonometry index >2.0 (log-rank p = 0.017) (median follow-up 6.0 (3.0–9.1) years). Cox proportional hazard analyses showed that a reactive hyperemia peripheral arterial tonometry index ≤2.0 predicted the incidence of solid-tumor cancer, with a hazard ratio of 2.52 (95% confidence interval 1.17–5.45; p = 0.019) after adjusting for age, sex, and coronary artery disease, 2.83 (95% confidence interval 1.30–6.17; p = 0.009) after adjusting for diabetes mellitus, hypertension, smoking status, and body mass index >30 kg/m2, 2.79 (95% confidence interval 1.21–6.41; p = 0.016) after adjusting for fasting plasma glucose, systolic blood pressure, smoking status (current or former), and body mass index, and 2.43 (95% confidence interval 1.10–5.34; p = 0.028) after adjusting for Framingham risk score. Conclusion Microvascular endothelial dysfunction, as defined by a reactive hyperemia peripheral arterial tonometry index ≤2.0, was associated with a greater than two-fold increased risk of solid-tumor cancer. Microvascular endothelial dysfunction may be a useful marker to predict the future risk of solid-tumor cancer, in addition to its known ability to predict cardiovascular disease. Further research is necessary to develop adequate cancer screening strategies for patients with microvascular endothelial dysfunction.