Banerjee, Anjishnu

Background/objectives: Improvements in esophageal adenocarcinoma (EAC) treatment have reduced mortality. While chemoradiation before surgery was previously a standard of care, updated guidelines recommend peri-operative chemotherapy without chemoradiation. Continued investigation into optimal non-operative treatment paradigms for patients who defer surgery or are not candidates for surgery and certain chemotherapy regimens is needed. The impact of induction chemotherapy prior to chemoradiation on survival and surgical outcomes remains unclear. This study assessed survival and surgical outcomes in a real-world cohort of EAC patients receiving induction chemotherapy before chemoradiation. Methods: This single-institution, IRB-approved, retrospective cohort study included patients with newly diagnosed stage II-IVb (oligometastatic for IVb) EAC who received definitive chemoradiation (radiation ≥ 40 Gy and two cycles of chemotherapy) +/− esophagectomy from 2007 to 2022. Patients receiving induction chemotherapy were compared to those who did not. Endpoints included survival and surgical outcomes. Results: A total of 141 EAC patients received definitive chemoradiation; 83 received induction chemotherapy before chemoradiation. Patients receiving induction chemotherapy were younger (p < 0.01) with slightly lower performance status (p = 0.27) and presented at a more advanced stage (p < 0.001). Median OS was 3.5 years in the induction chemotherapy group compared to 2.2 years (p = 0.10). There was no difference in pathologic complete response (p = 0.81), esophagectomy frequency (p = 0.87), or surgical downstaging between treatment groups (p = 0.84). Conclusions: In this real-world, single-institutional patient cohort investigating induction chemotherapy prior to chemoradiation in EAC, patients receiving induction chemotherapy did well but did not have a statistically significant improvement in survival outcomes or surgical outcomes. This study showed that significant numbers of real-world patients may not receive esophagectomy. Thus, prospective, randomized clinical trials are warranted to better delineate the efficacy and selection of patients for induction chemotherapy when non-operative approaches are favored.

Delta like canonical notch ligand 4 (Dll4) expression levels in tumors are known to affect the efficacy of cancer therapies. This study aimed to develop a model to predict Dll4 expression levels in tumors using dynamic enhanced near-infrared (NIR) imaging with indocyanine green (ICG). Two rat-based consomic xenograft (CXM) strains of breast cancer with different Dll4 expression levels and eight congenic xenograft strains were studied. Principal component analysis (PCA) was used to visualize and segment tumors, and modified PCA techniques identified and analyzed tumor and normal regions of interest (ROIs). The average NIR intensity for each ROI was calculated from pixel brightness at each time interval, yielding easily interpretable features including the slope of initial ICG uptake, time to peak perfusion, and rate of ICG intensity change after reaching half-maximum intensity. Machine learning algorithms were applied to select discriminative features for classification, and model performance was evaluated with a confusion matrix, receiver operating characteristic curve, and area under the curve. The selected machine learning methods accurately identified host Dll4 expression alterations with sensitivity and specificity above 90%. This may enable stratification of patients for Dll4 targeted therapies. NIR imaging with ICG can noninvasively assess Dll4 expression levels in tumors and aid in effective decision making for cancer therapy.