Citations

AbstractThe treatment of peripheral nerve injuries remains a major problem worldwide despite the availability of a number of Food and Drug Administration (FDA) approved devices which fail to match the efficacy of autografts. Different strategies are used to improve regeneration and functional recovery using biomaterial nerve conduits. However, there is little investigation of the transcriptomic and proteomic changes which occur as a result of these interventions, particularly regarding transection injuries. This study explores differences between autograft‐mediated repair and conduit‐material‐mediated repair of peripheral nerve injuries to understand fundamental differences in their repair mechanisms at the proteomics level at the proximal, middle, and distal components in the early stages of repair. Pathway analysis demonstrates that each material selectively activates different regenerative pathways and alters different biological functions spatially throughout the biomaterial conduits. The analysis highlights some of the deficiencies in conduit‐mediated repair in comparison to autograft (e.g., recycling of myelin and cholesterol, reduction in reactive oxygen species, and higher expression of regenerative proteins). These findings thus suggest that by supplementing the expression of these proteins on the biomaterial of choice, this study can potentially attain regeneration equivalent to autograft. This approach paves the way for incorporating future biomaterial‐specific functionalities in nerve guidance conduits.

Hospitals are complex systems with essential societal benefits and huge mounting costs. These costs are exacerbated by inefficiencies in hospital processes, which are often manifested by congestion and long delays in patient care. Thus, a queueing-network view of patient flow in hospitals is natural for studying and improving its performance. The goal of our research is to explore patient flow data through the lens of a queueing scientist. The means is exploratory data analysis (EDA) in a large Israeli hospital, which reveals important features that are not readily explainable by existing models. Questions raised by our EDA include: Can a simple (parsimonious) queueing model usefully capture the complex operational reality of the Emergency Department (ED)? What time scales and operational regimes are relevant for modeling patient length of stay in the Internal Wards (IWs)? How do protocols of patient transfer between the ED and the IWs influence patient delay, workload division and fairness? EDA also underscores the importance of an integrative view of hospital units by, for example, relating ED bottlenecks to IW physician protocols. The significance of such questions and our related findings raise the need for novel queueing models and theory, which we present here as research opportunities. Hospital data, and specifically patient flow data at the level of the individual patient, is increasingly collected but is typically confidential and/or proprietary. We have been fortunate to partner with a hospital that allowed us to open up its data for everyone to access. This enables reproducibility of our findings, through a user-friendly platform that is accessible via the Technion SEELab.

Assessment of tumor-infiltrating lymphocytes (TILs) in histopathologic specimens can provide important prognostic information in diverse solid tumor types, and may also be of value in predicting response to treatments. However, implementation as a routine clinical biomarker has not yet been achieved. As successful use of immune checkpoint inhibitors and other forms of immunotherapy become a clinical reality, the need for widely applicable, accessible, and reliable immunooncology biomarkers is clear. In part 1 of this review we briefly discuss the host immune response to tumors and different approaches to TIL assessment. We propose a standardized methodology to assess TILs in solid tumors on hematoxylin and eosin sections, in both primary and metastatic settings, based on the International Immuno-Oncology Biomarker Working Group guidelines for TIL assessment in invasive breast carcinoma. A review of the literature regarding the value of TIL assessment in different solid tumor types follows in part 2. The method we propose is reproducible, affordable, easily applied, and has demonstrated prognostic and predictive significance in invasive breast carcinoma. This standardized methodology may be used as a reference against which other methods are compared, and should be evaluated for clinical validity and utility. Standardization of TIL assessment will help to improve consistency and reproducibility in this field, enrich both the quality and quantity of comparable evidence, and help to thoroughly evaluate the utility of TILs assessment in this era of immunotherapy.

Assessment of the immune response to tumors is growing in importance as the prognostic implications of this response are increasingly recognized, and as immunotherapies are evaluated and implemented in different tumor types. However, many different approaches can be used to assess and describe the immune response, which limits efforts at implementation as a routine clinical biomarker. In part 1 of this review, we have proposed a standardized methodology to assess tumor-infiltrating lymphocytes (TILs) in solid tumors, based on the International Immuno-Oncology Biomarkers Working Group guidelines for invasive breast carcinoma. In part 2 of this review, we discuss the available evidence for the prognostic and predictive value of TILs in common solid tumors, including carcinomas of the lung, gastrointestinal tract, genitourinary system, gynecologic system, and head and neck, as well as primary brain tumors, mesothelioma and melanoma. The particularities and different emphases in TIL assessment in different tumor types are discussed. The standardized methodology we propose can be adapted to different tumor types and may be used as a standard against which other approaches can be compared. Standardization of TIL assessment will help clinicians, researchers and pathologists to conclusively evaluate the utility of this simple biomarker in the current era of immunotherapy.

Abstract Background: In vivo synergy with concurrent PI3-Kinase inhibition and PARP inhibition has been observed in BRCA-deficient and BRCA-proficient preclinical models of triple negative breast cancer (TNBC) and ovarian cancer (OC). A phase I trial of the oral pan-class I PI3-Kinase inhibitor BKM120 and the PARP inhibitor olaparib demonstrated anti-cancer activity in TNBC and OC, both in patients with and without germline BRCA1 and BRCA2 (BRCA) mutations. However, CNS toxicity (depression) and liver function test abnormalities limited dose escalation of BKM120 prompting evaluation of the alpha specific PI3-Kinase inhibitor BYL719 (which has no CNS toxicity) in combination with olaparib. Methods: Olaparib was administered twice daily (tablet formulation) and BYL719 daily on a 28-day cycle, both orally. A 3 + 3 dose-escalation design was employed with primary objectives of defining the maximum tolerated dose (MTD) and recommended phase 2 dose of the combination of BYL719 and olaparib, and secondary objectives of defining toxicity, activity, and pharmacokinetic profiles of both agents. Eligibility included recurrent TNBC or high grade serous (HGS) OC, or any histology OC or breast cancer (BC) with presence of a known germline BRCA mutation, performance status of 0-1 and measurable/evaluable cancer. Patients with platinum sensitive or resistant or refractory OC were eligible and prior PARP inhibitor use was allowed. Dose-expansion cohorts at the MTD were enrolled for both BC and OC. Results: 46 patients (16 BC and 30 OC) have been enrolled in the study; 28 patients participated in the dose escalation portion of the study (4 BC and 24 OC). Two patients with OC did not receive study drugs because of ineligibility. MTD was defined as BYL719 200mg once daily and olaparib 200mg twice daily. Dose limiting toxicities included hyperglycemia, rash and fever with decreased neutrophil count. Four patients (3 OC and 1 BC) discontinued protocol therapy because of toxicity (2 for hyperglycemia, 1 for nausea and 1 for allergic reaction). Most common toxicities included nausea, hyperglycemia, fatigue, diarrhea and vomiting. At the MTD, 6 patients with OC and 12 patients with BC were enrolled into a dose expansion cohort. The OC expansion cohort has completed enrollment, while the BC cohort is still enrolling. Among patients with OC who received study drugs (28 patients, 26 (93%) with platinum resistant disease), objective response rate (ORR) by RECIST 1.1 was 36% (10/28 patients, all partial responses (PRs)). Median duration of response was 167 days (range 16-398 days); 5 of 10 patients with PR remain on treatment. ORR was 33% for patients with germline BRCA mutations and 31% for patients without germline BRCA mutations. Among patients without germline BRCA mutations with platinum resistant OC, ORR was 29%. Conclusions: Combined BYL719 and olaparib is feasible, and similar clinical benefit was observed in patients with and without germline BRCA mutations. The activity of this combination in OC patients without germline BRCA mutations and with platinum resistant disease was higher than expected from olaparib monotherapy and warrants further investigation. This work was funded in part by the Stand Up To Cancer Ovarian Dream Team. Clinical trial: NCT01623349. Citation Format: Panagiotis A. Konstantinopoulos, William T. Barry, Michael Birrer, Shannon N. Westin, Sarah Farooq, Karen Cadoo, Christin Whalen, Weixiu Luo, Hui Liu, Carol Aghajanian, David B. Solit, Gordon B. Mills, Barry S. Taylor, Helen Won, Michael F. Berger, Sangeetha Palakurthi, Joyce F. Liu, Lew Cantley, Scott H. Kaufmann, Elizabeth M. Swisher, Alan D. D'Andrea, Eric Winer, Gerburg M. Wulf, Ursula A. Matulonis. Phase I study of the alpha specific PI3-Kinase inhibitor BYL719 and the poly (ADP-Ribose) polymerase (PARP) inhibitor olaparib in recurrent ovarian and breast cancer: Analysis of the dose escalation and ovarian cancer expansion cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr CT008. doi:10.1158/1538-7445.AM2017-CT008

Abstract Background: High percent mammographic density (MD), which reflects the relative fibroglandular tissue content of the breast, is one of the strongest breast cancer risk factors; however, the pathologic mediators of this risk are unknown. We hypothesize that analysis of breast tissue sections using deep learning approaches may characterize histologic features that underpin risk associated with high MD. Methods: Non-targeted H&E stained breast tissue sections of diagnostic image-guided breast biopsies were evaluated among 588 women enrolled following an abnormal mammogram in the Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project (2007-2010). Overall volumetric percent MD for the biopsied breast and localized volumetric percent MD surrounding the biopsy site were determined for each participant. A deep convolutional neural network (CNN) model was trained to identify and quantitatively assess breast epithelial, stroma and fat tissue and their organizational and spatial arrangements. Least absolute shrinkage and selection operator (Lasso) regression was used to determine relationships between MD measures and pathological features. To ensure reliability of the model, a cross-validation strategy was employed to build and assess the performance of the fitted model. Finally, Spearman correlation coefficients were estimated to test the association between the predicted density values by each model (predicting overall or localized MD) and the actual MD measurements. We report the average and standard deviation (SD) of the correlation coefficients. Results: In an independent validation set, the CNN model was 95.5% accurate in classifying epithelial, stromal and fat tissue. The mean (SD) correlations between the predicted model and the actual measurements for overall and localized MD were 0.70 (0.06) and 0.65 (0.06) respectively. The amount of stroma identified (normalized to tissue area) had the highest selection probability (P-value) by the Lasso model and thus the strongest positive relationship with MD (P-value >0.9 for each MD measurement). In contrast, the amount of normalized epithelial tissue was not related to MD (P-value=0.01 for each MD measurement). No association was observed for the total normalized fat area with MD (P-value <0.31 for each MD measurement). In addition, the number of distributed epithelial regions was positively associated, whereas the distance between epithelial regions was inversely associated with overall MD (P-value <0.87 and 0.62, respectively). Conclusions: These results show that greater stromal tissue amount and spatial distribution patterns of epithelial regions, rather than total epithelial amounts, had the strongest relationships with elevated MD. Future work will determine the relationship of these MD features with biopsy diagnosis. Citation Format: Maeve Mullooly, Babak Ehteshami Bejnordi, Maya Palakal, Pamela M. Vacek, Donald L. Weaver, John A. Shepherd, Bo Fan, Amir Pasha Mahmoudzadeh, Jeff Wang, Jason M. Johnson, Sally D. Herschorn, Brian L. Sprague, Ruth M. Pfeiffer, Louise A. Brinton, Mark E. Sherman, Andrew Beck, Gretchen L. Gierach. Application of convolutional neural networks to breast biopsies to uncover tissue correlates of mammographic breast density [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4235. doi:10.1158/1538-7445.AM2017-4235

AbstractBackgroundData on the clinical utility of left atrial (LA) hemodynamic monitoring during percutaneous mitral interventions are limited.ObjectivesTo evaluate the association between intraprocedural LA pressures during percutaneous mitral paravalvular leak (PVL) closure and long term survival.MethodsPatients who underwent mitral PVL repair with invasive LA pressure monitoring were divided at baseline to three tertiles based on their mean final LA pressure (<25%; 25‐30%; >30% of mean systolic blood pressure). Primary outcome was all‐cause mortality.Results134 patients (mean age 68 ± 12 years) were studied. Over 3 year mean follow‐up, 81 (38%) patients died. The cumulative probability of death at 3 years was significantly higher among patients in the highest LA pressure tertile (56 ± 8% vs. 28 ± 5%, log rank P < 0.001). More than mild residual mitral regurgitation (MR) by transesophageal echocardiography (TEE) was associated with a 2.5‐fold increased risk of death and patients in the highest LA pressure tertile had 2.2‐fold higher mortality (P < 0.001 and = 0.003 respectively). After adjustment for residual MR by TEE, each 10% acute procedural reduction in LA pressures was associated with a significant 9% reduced risk of death (P = 0.023). Multivariate Cox regression with adjustment for multiple predictors of death showed that patients in lower LA pressure tertiles had 59% lower mortality (P = 0.003).ConclusionLower LA pressure following mitral PVL closure is an independent predictor of improved survival, even after adjustment for residual MR. LA pressure monitoring may be a useful tool for procedural guidance during mitral PVL closure.