Citations

OBJECTIVE Generalized-onset seizures are usually conceptualized as engaging bilaterally distributed networks with no clear focus. However, the authors previously reported a case series demonstrating that in some patients with generalized-onset seizures, focal seizure onset could be discovered after corpus callosotomy. The corpus callosum is considered to be a major pathway for seizure generalization in this group of patients. The authors hypothesized that, in patients with generalized-onset seizures, the structure of the corpus callosum could be different between patients who have lateralized seizures and those who have nonlateralized seizures after corpus callosotomy. The authors aimed to evaluate the structural difference through statistical analysis of diffusion tensor imaging (DTI) scalars between these two groups of patients. METHODS Thirty-two patients diagnosed with generalized-onset motor seizures and without an MRI lesion were included in this study. Among them, 16 patients developed lateralized epileptic activities after corpus callosotomy, and the remaining 16 patients continued to have nonlateralized seizures after corpus callosotomy. Presurgical DTI studies were acquired to quantify the structural integrity of the corpus callosum. RESULTS The DTI analysis showed significant reduction of fractional anisotropy (FA) and increase in radial diffusivity (RD) in the body of the corpus callosum in the lateralized group compared with the nonlateralized group. CONCLUSIONS The authors’ findings indicate the existence of different configurations of bilateral epileptic networks in generalized epilepsy. Generalized seizures with focal onset relying on rapid spread through the corpus callosum might cause more structural damage related to demyelination in the corpus callosum, showing reduced FA and increased RD. This study suggests that presurgical DTI analysis of the corpus callosum might predict the seizure lateralization after corpus callosotomy.

Abstract Background: In an adaptive randomized trial, when new treatment combinations are being tested, it is important to be able to identify patients who are progressing on treatment so that they can be changed to a different therapeutic regimen. We know that even within the molecularly high risk patients in I-SPY 2, there is considerable variation in biology. In this study, we will present results of using MRI-calculated functional tumor volume (FTV) to identify tumor progression for each breast cancer subtype. Methods: Patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Four MRI exams were performed for each patient: pre-NAC (T0), after 3 weeks of NAC (T1), between regimens (T2), and post-NAC (T3). Functional tumor volume (FTV) was calculated at each exam by summing voxels meeting enhancement thresholds. Tumor progression at T1, T2 or T3 was identified by a positive FTV change relative to T0. Visual inspection was used to exclude false progression due to strong background parenchymal enhancement post-contrast, prominent vessels, motion, or insufficient image quality. pCR was defined as no invasive disease in the breast and lymph nodes. Negative predictive value for pCR was defined as:NPV=number of true non-pCRs / number of patients with MRI assessed tumor progressions, where “true non-pCRs” referred to patients who were non-pCRs at surgery and were assessed as progressors by MRI. The analysis was performed in the full cohort and in sub-cohorts defined by HR and HER2 statuses. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Total and non-pCR numbers for each subtype, number of patients with tumor progression assessed by MRI at T1, T2, and T3, and NPVs, are shown in Table 1. In the full cohort, the NPV increased consistently over treatment, from T1 (NPV=83%) to T2 (93%), and to T3 (100%). The HER2+ cancer subtypes showed fewer MRI-assessed tumor progressions than HER2- subtypes: e.g. 10/209 (5%) vs. 108/669 (16%) at T1. NPV was 100% for HER2+ subtypes at T1 and T2 except for a single misclassification of a HR- tumor at T1. Only 6 tumor progressors, all HER2- were identified at T3, and all were confirmed at surgery as non-pCRs (NPV=100%). For HR+/HER2-, the NPV increased slightly from 89% at T1 to 91% at T2, while triple negative subtype had a more substantial increase, from 78% to 92%. Conclusions: Our study showed strong association between tumor progressors assessed by MRI with true non-pCRs after NAC. For HER2+ tumors, although MRI progressors are rare, they strongly indicate non-pCR at all treatment time points, while HER2- subtypes show more accurate results later in treatment. We are evaluating MRI change at 6 weeks to determine if that time point is sufficient to predict progressors. Table 1 MRI assessed tumor progression at different treatment time pointN/non-pCRs/%non-pCRMRI assessed tumor progressionT1 (after 3 weeks)T2 (inter-regimen)T3 (post-NAC)NNPV (%)NNPV (%)NNPV (%)Full cohort878/572/65%11883.14192.76100%HR+/HER2-344/280/81%4588.91190.93100%HR+/HER2+134/85/63%610021000N/AHR-/HER2+75/23/31%47521000N/Atriple negative325/184/57%6377.82692.33100% Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Jessica Gibbs, Lisa J Wilmes, Ella F Jones, Bonnie N Joe, Laura S Sit, Christina Yau, A. Jo Chien, Elissa Price, Kathy S Albain, Theresa Kuritza, Kevin Morley, Judy C Boughey, Kathy Brandt, Sadia Choudhery, Amy S Clark, Mark Rosen, Elizabeth S McDonald, Anthony D Elias, Dulcy Wolverton, Kelly Fountain, David M Euhus, Heather S Han, Bethany Niell, Jennifer Drukteinis, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Smita M Asare, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Donald A Berry, Angela DeMichele, Hiroyuki Abe, Deepa Sheth, Kirsten K Edmiston, Erin D Ellis, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Michael Nelson, An Church, Claudine Isaacs, Qamar J Khan, Karen Y Oh, Neda Jafarian, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Pulin Sheth, Linda Hovanessian-Larsen, Mohammad Eghtedari, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Sally Goudreau, Thelma Brown, Laura J Esserman, Nola M Hylton. Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial [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 PD9-04.

Abstract Background: Young women with breast cancer (BC) often receive aggressive local therapy and are more likely to undergo (bilateral) mastectomy and receive postmastectomy radiation (RT) than older women. Our previous work suggested better quality of life (QOL) outcomes among women undergoing breast conserving therapy (BCT) vs. mastectomy, even with reconstruction (recon), although limited data was available regarding recon. In the current analysis, we sought to understand the impact of recon, accounting for RT, on long-term satisfaction and QOL. Methods: Between 10/2016-11/2017, we administered the BREAST-Q, a validated patient-reported outcomes measure designed to evaluate satisfaction and QOL after breast cancer surgery and recon, to 743 women in the Young Women’s Breast Cancer Study, a multi-site prospective cohort that enrolled women diagnosed (dx’d) at age < 40 from 2006-2016. Demographic and treatment information was obtained by surveys and chart review. Recon was defined as autologous, implant or complex (combination of autologous and implant). Mean BREAST-Q scores for each domain (breast satisfaction, physical, psychosocial, and sexual) were compared by recon types and stratified by receipt of RT; higher BREAST-Q scores (range: 0-100) indicate better QOL. Linear regression was used to identify predictors of BREAST-Q scores. Results: 584 women with Stage 0-3 BC completed the Breast-Q at a median of 5.7 [range 2-10] years from dx), 357 (61%) had mastectomy and recon and were included in the analytic sample. Median age at dx was 36 years; 85% had stage 0, 1 or 2 disease; 41% received RT and 76% underwent bilateral mastectomy. 90.5% underwent immediate recon; of which 65.5% were tissue expander placement. Definitive recon included autologous tissue in 16%; implants in 81% and complex recon in 3%. Mean BREAST-Q breast satisfaction, psychosocial, and physical well-being scores differed based on recon type accounting for RT (Table 1). Significantly lower scores for breast satisfaction were seen in women having implant +RT. Scores were not impacted by bilateral procedure, timing of recon, use of tissue expander, extent of axillary surgery, cancer stage or other treatment factors. In multivariate analyses, receipt of RT, lymphedema and implant-based recon were associated with lower breast satisfaction scores. Physical well-being scores were lower for those with complex recon, for non-White women, for women who reported being financially uncomfortable, for those with lymphedema, and for those <5 years from surgery. Psychosocial well-being scores were lower for women who received RT, had BMI >25, and for those who reported being financially uncomfortable. Sexual well-being scores were lower for women with a BMI >25 and for those who reported being financially uncomfortable. Conclusion Type of recon and receipt of radiation among young survivors who undergo mastectomy and recon for early breast cancer appears to have a differential impact on satisfaction and QOL. Our finding of lower breast satisfaction among young women who received RT, particularly after implant recon, underscores the importance of counseling regarding surgical options, especially for women who may receive RT after mastectomy and who are candidates for BCT. Table 1. Unadjusted BREAST-Q scores stratified by RTBREAST-Q DomainAutologous -RT N=29Autologous +RT N=27Implant -RT N=174Implant +RT N=113Complex N=13Global p-valueSatisfaction with Breasts, mean (sd)67 (19)63 (18)64 (18)53 (18)58 (22)<0.01Physical well-being, mean (sd)81 (13)80 (14)80 (15)77 (14)67 (18)0.01Psychosocial well-being, mean (sd)71 (18)64 (18)72 (20)66 (23)62 (20)0.03Sexual well-being, mean (sd)54 (21)50 (24)52 (20)47 (22)48 (27)0.26RT= radiation Citation Format: Laura Dominici, Jiani Hu, Hee Jeong Kim, Tari King, Kathryn Ruddy, Rulla Tamimi, Jeffrey Peppercorn, Lidia Schapira, Virginia Borges, Stephen Come, Ellen Warner, Julia Wong, Ann Partridge, Shoshana Rosenberg. BREAST-Q satisfaction and quality of life outcomes in young women undergoing mastectomy and reconstruction for 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 PD6-1.

Abstract Background: Strong background parenchymal enhancement (BPE) may cause overestimation in tumor volume measured from dynamic contrast-enhanced (DCE) MRI, which may adversely affect the ability of MR tumor volume to predict treatment outcome for patients undergoing neoadjuvant chemotherapy (NAC). Specifically, an overestimation of tumor volume can result in misclassification of patients with complete pathologic response (pCR) as non-responders, leading to less confidence in MRI prediction. As well, overestimation of extent of disease might lead to more aggressive surgical therapy than necessary. This study investigated whether high BPE in the contralateral breast influences the predictive performance of MRI-measured functional tumor volume (FTV) for patients with locally advanced breast cancer undergoing NAC. Methods: patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Each patient had 4 MRI exams: pre-NAC (T0), after 3 weeks of NAC (T1), between NAC regimens (T2), and post-NAC (T3). FTV was calculated at each MRI exam by summing voxels meeting enhancement thresholds. Background parenchymal enhancement (BPE) in the contralateral breast was calculated automatically as mean percentage enhancement on the early (nominal 150sec post-contrast) image in the fibroglandular tissue segmented from 5 continuous axial slices centered in the inferior-to-superior stack. For each treatment time point, patients having both FTV and BPE measurements were included in the analysis. The area under the ROC curve (AUC) was estimated as the association between FTV and pCR at T1, T2, and T3. The analysis was conducted in the full patient cohort and in sub-cohorts defined by hormone receptor (HR) and HER2 status. In each patient cohort, a cut-off BPE value was selected to classify patients with high vs. low BPE by testing AUCs estimated with low-BPE patients reached maximum when the cut-off value varied from median to maximum in steps of 10%. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Table 1 shows the number of patients, pCR rate, and AUC of FTV for predicting pCR using all patients available vs. a subset patients with low BPE (< BPE cut-off). In the full cohort, AUC increased slightly across all time points after patients with high BPE were removed. In the HR+/HER2- subtype, AUC increased at T1 after removal of cases with high BPE (0.65 vs. 0.71). For HR-/HER2+, AUC increased substantially after removal of high BPE cases (0.65 to 0.86 at T1, 0.71 to 0.87 at T2, and 0.71 to 0.89 at T3), with greater improvement at the early time point (T1) compared to later time points (T2 and T3). Only a slight improvement in the AUC was observed in the HR+/HER2+ and HR-/HER2- subtypes across all time points. Conclusions: High background parenchymal enhancement adversely affected the predictive performance of functional tumor volume measured by DCE-MRI, at early treatment time point for HR+/HER2- and across all time points for HR-/HER2+ cancer subtype. The adverse effect might be offset using subtype-optimized enhancement threshold in calculating functional tumor volume. Table 1 Effect of BPE on the prediction of pCR using FTV at various treatment time pointsT1T2T3npCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offFullAll64734%0.662762334%0.701761134%0.6925Subset45334%0.6831133%0.7230534%0.72HR+/HER2-All26218%0.651924918%0.718225518%0.7519Subset13118%0.7124818%0.7120419%0.76HR+/HER2+All10636%0.642110538%0.62269634%0.7120Subset5332%0.668438%0.665740%0.73HR-/HER2+All5175%0.65204774%0.71204973%0.7116Subset3073%0.862871%0.872475%0.89HR-/HER2-All22842%0.682822243%0.751821143%0.6916Subset15940%0.7111137%0.7810540%0.75 Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Roy Harnish, Ella F Jones, Lisa J Wilmes, Jessica Gibbs, Elissa Price, Bonnie N Joe, A. Jo Chien, Donald A Berry, Judy C Boughey, Kathy S Albain, Amy S Clark, Kirsten K Edmiston, Anthony D Elias, Erin D Ellis, David M Euhus, Heather S Han, Claudine Isaacs, Qamar J Khan, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Christina Yau, Smita M Asare, Angela DeMichele, Sally Goudreau, Hiroyuki Abe, Deepa Sheth, Dulcy Wolverton, Kelly Fountain, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Theresa Kuritza, Kevin Morley, Michael Nelson, An Church, Bethany Niell, Jennifer Drukteinis, Karen Y Oh, Neda Jafarian, Kathy Brandt, Sadia Choudhery, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Mohammad Eghedari, Pulin Sheth, Linda Hovanessian-Larsen, Mark Rosen, Elizabeth S McDonald, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Laura J Esserman, Nola M Hylton. The effect of background parenchymal enhancement on the predictive performance of functional tumor volume measured in MRI [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 P6-02-01.

Abstract Aims: We sought to determine which echocardiographic markers of left ventricular (LV) remodeling and diastolic dysfunction can contribute as incremental and independent prognostic information in addition to current clinical risk markers of ischemic LV systolic dysfunction in the Surgical Treatment for Ischemic Heart Failure (STICH) trial.Methods and Results: The cohort consisted of 1511 of 2136 patients in STICH for whom baseline transmitral Doppler (E/A ratio) could be measured by an echocardiographic core laboratory blinded to treatment and outcomes, and prognostic value of echocardiographic variables was determined by a Cox regression model. E/A ratio was the most significant predictor of mortality amongst diastolic variables with lowest mortality for E/A closest 0.8, although mortality was consistently low for E/A 0.6 to 1.0. Mortality increased for E/A <0.6 and > 1.0 up to approximately 2.3, beyond which there was no further increase in risk. Larger LV end-systolic volume index (LVESVI) and E/A <0.6 and >1.0 had incremental negative effects on mortality when added to a clinical multivariable model, where creatinine, LVESVI, age, and E/A ratio accounted for 74% of the prognostic information for predicting risk. LVESVI and E/A ratio were stronger predictors of prognosis than New York Heart Association functional class, anemia, diabetes, history of atrial fibrillation, and stroke.Conclusions: Echocardiographic markers of advanced LV remodeling and diastolic dysfunction added incremental prognostic value to current clinical risk markers. LVESVI and E/A ratio outperformed other markers and should be considered as standard in assessing risks in ischemic heart failure. E/A closest to 0.8 was the most optimal filling pattern.

Abstract Purpose: Clear cell ovarian carcinoma (CCOC) is an aggressive disease that often demonstrates resistance to standard chemotherapies. Approximately 25% of patients with CCOC show a strong APOBEC mutation signature. Here, we determine which APOBEC3 enzymes are expressed in CCOC, establish clinical correlates, and identify a new biomarker for detection and intervention. Experimental Designs: APOBEC3 expression was analyzed by IHC and qRT-PCR in a pilot set of CCOC specimens (n = 9 tumors). The IHC analysis of APOBEC3B was extended to a larger cohort to identify clinical correlates (n = 48). Dose-response experiments with platinum-based drugs in CCOC cell lines and carboplatin treatment of patient-derived xenografts (PDXs) were done to address mechanistic linkages. Results: One DNA deaminase, APOBEC3B, is overexpressed in a formidable subset of CCOC tumors and is low or absent in normal ovarian and fallopian tube epithelial tissues. High APOBEC3B expression associates with improved progression-free survival (P = 0.026) and moderately with overall survival (P = 0.057). Cell-based studies link APOBEC3B activity and subsequent uracil processing to sensitivity to cisplatin and carboplatin. PDX studies extend this mechanistic relationship to CCOC tissues. Conclusions: These studies demonstrate that APOBEC3B is overexpressed in a subset of CCOC and, contrary to initial expectations, associated with improved (not worse) clinical outcomes. A likely molecular explanation is that APOBEC3B-induced DNA damage sensitizes cells to additional genotoxic stress by cisplatin. Thus, APOBEC3B is a molecular determinant and a candidate predictive biomarker of the therapeutic response to platinum-based chemotherapy. These findings may have broader translational relevance, as APOBEC3B is overexpressed in many different cancer types.

Introduction The lack of effective, consistent, reproducible and efficient asthma ascertainment methods results in inconsistent asthma cohorts and study results for clinical trials or other studies. We aimed to assess whether application of expert artificial intelligence (AI)-based natural language processing (NLP) algorithms for two existing asthma criteria to electronic health records of a paediatric population systematically identifies childhood asthma and its subgroups with distinctive characteristics. Methods Using the 1997–2007 Olmsted County Birth Cohort, we applied validated NLP algorithms for Predetermined Asthma Criteria (NLP-PAC) as well as Asthma Predictive Index (NLP-API). We categorised subjects into four groups (both criteria positive (NLP-PAC+/NLP-API+); PAC positive only (NLP-PAC+ only); API positive only (NLP-API+ only); and both criteria negative (NLP-PAC−/NLP-API−)) and characterised them. Results were replicated in unsupervised cluster analysis for asthmatics and a random sample of 300 children using laboratory and pulmonary function tests (PFTs). Results Of the 8196 subjects (51% male, 80% white), we identified 1614 (20%), NLP-PAC+/NLP-API+; 954 (12%), NLP-PAC+ only; 105 (1%), NLP-API+ only; and 5523 (67%), NLP-PAC−/NLP-API−. Asthmatic children classified as NLP-PAC+/NLP-API+ showed earlier onset asthma, more Th2-high profile, poorer lung function, higher asthma exacerbation and higher risk of asthma-associated comorbidities compared with other groups. These results were consistent with those based on unsupervised cluster analysis and lab and PFT data of a random sample of study subjects. Conclusion Expert AI-based NLP algorithms for two asthma criteria systematically identify childhood asthma with distinctive characteristics. This approach may improve precision, reproducibility, consistency and efficiency of large-scale clinical studies for asthma and enable population management.

Abstract Although degenerative disc disease (DDD) and related low back pain (LBP) are growing public health problems, the underlying disease mechanisms remain unclear. An increase in the vascular endothelial growth factor (VEGF) levels in DDD has been reported. This study aimed to examine the role of VEGF receptors (VEGFRs) in DDD, using a mouse model of DDD. Progressive DDD was induced by anterior stabbing of lumbar intervertebral discs in wild type (WT) and VEGFR‐1 tyrosine‐kinase deficient mice ( vegfr‐1 TK−/ − ). Pain assessments were performed weekly for 12 weeks. Histological and immunohistochemical assessments were made for discs, dorsal root ganglions, and spinal cord. Both vegfr‐1 TK − / − and WT mice presented with similar pathological changes in discs with an increased expression of inflammatory cytokines and matrix‐degrading enzymes. Despite the similar pathological patterns, vegfr‐1 TK − / − mice showed insensitivity to pain compared with WT mice. This insensitivity to discogenic pain was related to lower levels of pain factors in the discs and peripheral sensory neurons and lower spinal glial activation in the vegfr‐1 TK − / − mice than in the WT mice. Exogenous stimulation of bovine disc cells with VEGF increased inflammatory and cartilage degrading enzyme. Silencing vegfr‐1 by small‐interfering‐RNA decreased VEGF‐induced expression of pain markers, while silencing vegfr‐2 decreased VEGF‐induced expression of inflammatory and metabolic markers without changing pain markers. This suggests the involvement of VEGFR‐1 signaling specifically in pain transmission. Collectively, our results indicate that the VEGF signaling is involved in DDD. Particularly, VEGFR‐1 is critical for discogenic LBP transmission independent of the degree of disc pathology.