Publications by authors named "Edgar Ben-Josef"

Article Synopsis
  • Biliary tract cancers (BTC) are aggressive and often diagnosed too late for surgery, making chemotherapy the main treatment option, while radiotherapy (RT) serves as an alternative for certain cases.
  • A study at the University of Pennsylvania analyzed 78 patients with unresectable BTC receiving RT, finding that better overall survival (OS) was linked to lower CA19-9 levels and improved albumin-bilirubin (ALBI) grades.
  • The developed biomarker model highlights significant variability in OS among patients, indicating that specific risk factors can aid in predicting individual patient outcomes following RT.
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Pancreatic ductal adenocarcinoma (PDAC) represents a challenge in oncology, with limited treatment options for advanced-stage patients. Chimeric antigen receptor T cell (CAR T) therapy targeting mesothelin (MSLN) shows promise, but challenges such as the hostile immunosuppressive tumor microenvironment (TME) hinder its efficacy. This study explores the synergistic potential of combining proton radiation therapy (RT) with MSLN-targeting CAR T therapy in a syngeneic PDAC model.

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Background: In select patients, pancreatic adenocarcinoma remains a local disease, yet there are no validated biomarkers to predict this behavior and who may benefit from aggressive local treatments. This study sought to determine if SMAD4 (mothers against decapentaplegic homolog 4) messenger RNA-sequencing (RNA-seq) expression is a robust method for predicting overall survival (OS) and distant metastasis-free survival (DMFS) in patients with resected pancreatic adenocarcinoma.

Methods: Utilizing The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), 322 patients with resected stage I-III pancreatic adenocarcinoma were identified.

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Background: With advances in understanding liver tolerance, conformal techniques, image guidance, and motion management, dose-escalated radiotherapy has become a potential treatment for inoperable hepatocellular carcinoma (HCC). We aimed to evaluate the possible impact of biologically effective dose (BED) on local control and toxicity among patients with HCC.

Methods And Materials: Patients treated at our institution from 2009 to 2018 were included in this retrospective analysis if they received definitive-intent radiotherapy with a nominal BED of at least 60 Gy.

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It is increasingly recognized that heterogeneities in tumor response and severity of adverse effects in irradiated patients can be attributed to the tumor microenvironment and host-related factors. Among the latter, a growing body of literature in recent years has demonstrated the role of the patient's microbiome in modulating both tumor and normal tissue response to radiotherapy (RT). Upon contact with the environment after birth, the infant's gastrointestinal tract is rapidly colonized by microbiota, which is low in diversity and predominantly characterized by 2 dominant species, Actinobacteria and Proteobacteria.

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Background: SWOG 0809 is the only prospective study of adjuvant chemotherapy followed by chemoradiation focusing on margin status in patients with extrahepatic cholangiocarcinoma (EHCC) and gallbladder cancer (GBCA); however, the effects of adjuvant therapy by nodal status have never been reported in this population.

Methods: Patients with resected EHCC and GBCA, stage pT2-4, node-positive (N+) or margin-positive (R1) who completed four cycles of chemotherapy followed by radiotherapy were included. Cox regression was used to compare overall survival (OS), disease-free survival (DFS), local recurrence, and distant metastasis by nodal status.

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Background And Aims: It has been recently proposed to change the nomenclature of "chronic radiation proctitis" (CRP) to "radiation-associated vascular ectasia" on the basis that signs of inflammation are rarely observed. We herein present data supporting the idea that inflammation is a critical step that initiates the process that culminates in the characteristic changes of CRP.

Methods: In support of inflammation in the pathogenesis of CRP, we review the pertinent literature and publish our new results, including the role of amifostine treatment and proinflammatory factors (p38 MAP kinase, VEGF, and CEACAM1).

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Purpose: Physical activity is associated with decreased hospitalization during cancer treatment. We hypothesize that activity data can help identify and triage high-risk patients with GI cancer undergoing concurrent chemoradiation.

Materials And Methods: This prospective study randomly assigned patients to activity monitoring versus observation.

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Compared with photon stereotactic body radiotherapy (SBRT) plans that may have to use many more penetrating x-ray beams for each isocenter, proton SBRT with ultrahypofractionated doses use fewer beam angles and offer significantly reduced low-dose radiation bath to normal liver tissue. We demonstrate techniques to deliver safe and effective proton SBRT, where planning and organ motion complexity further increased with multiple liver lesions. For treatment planning, we recommend robust and logical beam angles, avoiding devices and encouraging entry perpendicular to the dominant motion, as well as volumetric repainting to mitigate the interplay effect to clinically acceptable levels.

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Purpose: Concurrent chemoradiation therapy is a curative treatment for squamous cell carcinoma of the anus, but patients can suffer from significant treatment-related toxicities. This study was undertaken to determine whether intensity modulated proton therapy (IMPT) is associated with less acute toxicity than intensity modulated radiation therapy (IMRT) using photons.

Materials And Methods: We performed a multi-institutional retrospective study comparing toxicity and oncologic outcomes of IMRT versus IMPT.

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Purpose: Data on management of locally recurrent pancreatic cancer (LRPC) after primary resection are limited. Recently, surprisingly high overall survival rates were reported after irradiation with carbon ions. Here, we report on our clinical experience using carbon ion radiotherapy as definitive treatment in LRPC at the Heidelberg Ion-Beam Therapy Center (HIT).

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Purpose: This study evaluates the toxicity and tumor response with concurrent nab-paclitaxel chemoradiotherapy (CRT) compared with standard (5-fluorouracil or gemcitabine) CRT.

Materials And Methods: Fifty patients with borderline resectable or unresectable pancreatic adenocarcinoma from 2014 to 2017 were divided into 2 groups: concurrent nab-paclitaxel (100 to 125 mg/m2 weekly) CRT (median: 2.1 Gy fraction size and 52.

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Background And Aim: This study quantifies how changes in healthcare utilization and delivery during the first months of the COVID-19 pandemic have altered the presentation, treatment, and management of patients with gastrointestinal (GI) malignancies within an academic health system.

Methods And Results: Patients diagnosed with a GI malignancy (ICD10: C15-C26) who received medical care within the health system during the observation period (first 44 weeks of 2019 and 2020) were identified for a retrospective cohort study. Deidentified patient encounter parameters were collected for this observation period and separated into pre-pandemic (weeks 1-10) and early pandemic (weeks 11-20) study periods.

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Article Synopsis
  • A new imaging tool called FAPI-PET/CT helps doctors see cancer cells better than traditional CT scans, especially in pancreatic cancer.
  • In a study, doctors compared their own tumor drawings with automatic measurements from FAPI-PET/CT to see how accurate they were.
  • The results showed that FAPI-PET/CT gives clearer images of tumors, which may help doctors plan better treatment for patients with pancreatic cancer.
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Objective: To report outcomes and toxicity in patients who received definitive concurrent chemoradiation (DCCRT) for non-operable esophageal cancer (EC) in the modern era, and to identify markers of overall and disease-free survival (OS/DFS).

Methods: We conducted a retrospective cohort study of patients with unresectable EC who received DCCRT at our institution between 1/2008 and 1/2019. Descriptive statistics were used to report disease-control outcomes and CTCAE v4.

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TGFβ is a pleiotropic cytokine with immunosuppressive activity. In preclinical models, blockade of TGFβ enhances the activity of radiation and invokes T-cell antitumor immunity. Here, we combined galunisertib, an oral TGFβ inhibitor, with stereotactic body radiotherapy (SBRT) in patients with advanced hepatocellular carcinoma (HCC) and assessed safety, efficacy, and immunologic correlatives.

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Objectives: Survival of patients with locally advanced pancreatic cancer (LAPC) is improved when neoadjuvant chemoradiation enables subsequent surgical resection. Here, the authors assess changes in vessel involvement as a possible indicator of resectability.

Methods: Pancreatic gross tumor and all major abdominal vessels were contoured for 49 patients with unresectable LAPC before and after neoadjuvant chemoradiation.

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Article Synopsis
  • Radiotherapy (RT) is commonly used for treating gastrointestinal (GI) cancers but can face challenges with locoregional recurrences or second cancers; proton-beam RT may offer a safe and effective reirradiation option due to its dosimetric benefits.
  • A systematic review reviewed proton-beam reirradiation for recurrent GI cancers, analyzing 7 studies from an initial pool of 373 articles, with varied patient numbers and specific cancer sites evaluated.
  • Results showed that palliation was achieved in 80-100% of patients with symptoms, local control rates varied from 36-100%, and median overall survival was over a year; notably, no cases of radiation-induced liver disease were reported.
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Background: Several registry-based analyses suggested a survival advantage for married versus single patients with pancreatic cancer. The mechanisms underlying the association of marital status and survival are likely multiple and complex and, therefore, may be obscured in analyses generated from large population-based databases. The goal of this research was to characterize this potential association of marital status with outcomes in patients with resected pancreatic cancer who underwent combined modality adjuvant therapy on a prospective clinical trial.

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Radiomic approaches have achieved promising performance in prediction of clinical outcomes of cancer patients. Particularly, feature dimensionality reduction plays an important role in radiomic studies. However, conventional feature dimensionality reduction techniques are not equipped to suppress data noise or utilize latent supervision information of patient data under study ( difference in patients) for learning discriminative low dimensional representations.

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Feature dimensionality reduction plays an important role in radiomic studies with a large number of features. However, conventional radiomic approaches may suffer from noise, and feature dimensionality reduction techniques are not equipped to utilize latent supervision information of patient data under study, such as differences in patients, to learn discriminative low dimensional representations. To achieve robustness to noise and feature dimensionality reduction with improved discriminative power, we develop a robust collaborative clustering method to simultaneously cluster patients and radiomic features into distinct groups respectively under adaptive sparse regularization.

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Recent radiomic studies have witnessed promising performance of deep learning techniques in learning radiomic features and fusing multimodal imaging data. Most existing deep learning based radiomic studies build predictive models in a setting of pattern classification, not appropriate for survival analysis studies where some data samples have incomplete observations. To improve existing survival analysis techniques whose performance is hinged on imaging features, we propose a deep learning method to build survival regression models by optimizing imaging features with deep convolutional neural networks (CNNs) in a proportional hazards model.

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Most machine learning approaches in radiomics studies ignore the underlying difference of radiomic features computed from heterogeneous groups of patients, and intrinsic correlations of the features are not fully exploited yet. In order to better predict clinical outcomes of cancer patients, we adopt an unsupervised machine learning method to simultaneously stratify cancer patients into distinct risk groups based on their radiomic features and learn low-dimensional representations of the radiomic features for robust prediction of their clinical outcomes. Based on nonnegative matrix tri-factorization techniques, the proposed method applies collaborative clustering to radiomic features of cancer patients to obtain clusters of both the patients and their radiomic features so that patients with distinct imaging patterns are stratified into different risk groups and highly correlated radiomic features are grouped in the same radiomic feature clusters.

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