GLI1 encodes a transcription factor that targets cell cycle regulators affecting stem cell proliferation. GLI1 gene fusions were initially described in pericytomas with a t[7;12] translocation and more recently in gastric plexiform fibromyxomas and gastroblastomas. This study describes the clinicopathologic, immunohistochemical, and molecular features of three intestinal-based neoplasms harboring GLI1 gene fusions. We studied three unique mesenchymal small bowel tumors. Paraffin embedded tumor tissues from these cases and 62 additional tumor samples that included a plexiform fibromyxoma were sequenced using a targeted RNAseq method to detect fusion events. The study patients included two women and one man who were 52, 80, and 22 years of age at the time of diagnosis. The tumors involved the submucosa and muscularis propria of the duodenum, jejunum, and ileum. All 3 tumors contained a proliferation of monotonous oval or spindle cells with scattered, somewhat dilated vessels. Two cases showed epithelioid structures such as glands, tubules, or nests. Immunohistochemical analysis revealed cytokeratin expression in the epithelioid components of both tumors displaying these features, and variable numbers of mesenchymal cells. Diffuse CD56 positivity was seen in the mesenchymal component of 2 tumors and desmin and smooth muscle actin staining in the other tumor. Immunostains for S-100 protein, DOG-1, and CD117 were negative in all cases. GLI1 fusions with different partner genes were detected in all tumors, and in the plexiform fibromyxoma, used as a control. Validation by fluorescence in situ hybridization was performed. None of the tumors have recurred or metastasize after surgery. We describe novel GLI1 fusions in 3 mesenchymal neoplasms of the small intestine, including 2 with biphenotypic features. Thus far, all cases have pursued indolent clinical courses. We propose the term “GLI1-rearranged enteric tumor” to encompass this group of unique neoplasms of the small intestine that harbor GLI1 gene fusions and expand the spectrum of gastrointestinal neoplasms with these alterations.
Patient-derived tumor organoids (PDTOs) have become relevant pre-clinical models for therapeutic modeling since they highly recapitulate patients' responses to treatment. Nevertheless, their value for immunotherapy modeling has not been fully explored. We developed a tumor processing protocol that enables the establishment of PDTOs and tumor-infiltrating lymphocytes (TILs) isolation. By the optimization of functional assays, we compared the T-cells effector functions of matching PBMCs and TILs, demonstrating that PBMCs after co-culture and TILs after initial expansion display similar responses. In addition, the evaluation of cytokine production by fluorospot in combination with an image-based killing assay enables the screening of anti-PD-1 combinations with alternative immune checkpoint inhibitors as well as its combination with target inhibitors. Our proof-of-concept functional assays showed the potential and versatility of PDTOs and T-cell co-culture systems for immunotherapy screening. The optimization of scalable functional assays downstream co-culture represents a significant step forward to increase the value of PDTOs as pre-clinical models for immunotherapeutic screens.
Estimating tumor purity is especially important in the age of precision medicine. Purity estimates have been shown to be critical for correction of tumor sequencing results, and higher purity samples allow for more accurate interpretations from next-generation sequencing results. In addition, tumor purity has been shown to be correlated with survival outcomes for several diseases. Molecular-based purity estimates using computational approaches require sequencing of tumors, which is both time-consuming and expensive. Here we propose an approach, weakly-supervised purity (wsPurity), which can accurately quantify tumor purity within a slide, using multiple and different types of cancer. This approach allows for a flexible analysis of tumors from whole slide imaging (WSI) of histology hematoxylin and eosin (H&E) slides. Our model predicts tumor type with high accuracy (greater than 80% on an independent test cohort), and tumor purity at a higher accuracy compared to a comparable fully-supervised approach (0.1335 MAE on an independent test cohort). In addition to tumor purity prediction, our approach can identify high resolution tumor regions within a slide, to enrich tumor cell selection for downstream analyses. This model could also be used in a clinical setting, to stratify tumors into high and low tumor purity, using different thresholds, in a cancer-dependent manner, depending on what purity levels correlate with worse disease outcomes. In addition, this approach could be used in clinical practice to select the best tissue block for sequencing. Overall, this approach can be used in several different ways to analyze WSIs of tumor H&E sections.
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