Response to immune checkpoint therapy can be associated with a high mutation burden, but other mechanisms are also likely to be important. We identified a patient with metastatic gastric cancer with meaningful clinical benefit from treatment with the anti-programmed death-ligand 1 (PD-L1) antibody avelumab. This tumor showed no evidence of high mutation burden or mismatch repair defect but was strongly positive for presence of Epstein-Barr virus (EBV) encoded RNA. Analysis of The Cancer Genome Atlas gastric cancer data (25 EBV+, 80 microsatellite-instable [MSI], 310 microsatellite-stable [MSS]) showed that EBV-positive tumors were MSS. Two-sided Wilcoxon rank-sum tests showed that: 1) EBV-positive tumors had low mutation burden (median = 2.07 vs 3.13 in log10 scale, P < 10-12) but stronger evidence of immune infiltration (median ImmuneScore 2212 vs 1295, P < 10-4; log2 fold-change of CD8A = 1.85, P < 10-6) compared with MSI tumors, and 2) EBV-positive tumors had higher expression of immune checkpoint pathway (PD-1, CTLA-4 pathway) genes in RNA-seq data (log2 fold-changes: PD-1 = 1.85, PD-L1 = 1.93, PD-L2 = 1.50, CTLA-4 = 1.31, CD80 = 0.89, CD86 = 1.31, P < 10-4 each), and higher lymphocytic infiltration by histology (median tumor-infiltrating lymphocyte score = 3 vs 2, P < .001) compared with MSS tumors. These data suggest that EBV-positive low-mutation burden gastric cancers are a subset of MSS gastric cancers that may respond to immune checkpoint therapy.
Purpose To determine whether [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) can delineate patients with esophageal cancer who may not benefit from esophagectomy after chemoradiotherapy. Patients and Methods We reviewed records of 163 patients with histologically confirmed stage I to IVA esophageal cancer receiving chemoradiotherapy with or without resection with curative intent. All patients received surgical evaluation. Initial and postchemoradiotherapy FDG-PET scans and prognostic/treatment variables were analyzed. FDG-PET complete response (PET-CR) after chemoradiotherapy was defined as standardized uptake value ≤ 3. Results Eighty-eight patients received trimodality therapy and 75 received chemoradiotherapy. Surgery was deferred primarily due to medical inoperability or unresectable/metastatic disease after chemoradiotherapy. A total of 105 patients were evaluable for postchemoradiotherapy FDG-PET response. Thirty-one percent achieved a PET-CR. PET-CR predicted for improved outcomes for chemoradiotherapy (2-year overall survival, 71% v 11%, P < .01; 2-year freedom from local failure [LFF], 75% v 28%, P < .01), but not trimodality therapy. On multivariate analysis of patients treated with chemoradiotherapy, PET-CR is the strongest independent prognostic variable (survival hazard ratio [HR], 9.82, P < .01; LFF HR, 14.13, P < .01). PET-CR predicted for improved outcomes regardless of histology, although patients with adenocarcinoma achieved a PET-CR less often. Conclusion Patients treated with trimodality therapy found no benefit with PET-CR, likely because FDG-PET residual disease was resected. Definitive chemoradiotherapy patients achieving PET-CR had excellent outcomes equivalent to trimodality therapy despite poorer baseline characteristics. Patients who achieve a PET-CR may not benefit from added resection given their excellent outcomes without resection. These results should be validated in a prospective trial of FDG-PET–directed therapy for esophageal cancer.
Introduction:The development and application of new molecular diagnostic assays based on next-generation sequencing and proteomics require improved methodologies for procurement of target cells from histological sections. Laser microdissection can successfully isolate distinct cells from tissue specimens based on visual selection for many research and clinical applications. However, this can be a daunting task when a large number of cells are required for molecular analysis or when a sizeable number of specimens need to be evaluated.Materials and Methods:To improve the efficiency of the cellular identification process, we describe a microdissection workflow that leverages recently developed and open source image analysis algorithms referred to as computer-aided laser dissection (CALD). CALD permits a computer algorithm to identify the cells of interest and drive the dissection process.Results:We describe several “use cases” that demonstrate the integration of image analytic tools probabilistic pairwise Markov model, ImageJ, spatially invariant vector quantization (SIVQ), and eSeg onto the ThermoFisher Scientific ArcturusXT and Leica LMD7000 microdissection platforms.Conclusions:The CALD methodology demonstrates the integration of image analysis tools with the microdissection workflow and shows the potential impact to clinical and life science applications.
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