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Chebib, Ivan

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Chebib

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Ivan

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Chebib, Ivan

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Now showing 1 - 3 of 3
  • Publication

    Expression of programmed cell death ligand 1 (PD-L1) and prevalence of tumor-infiltrating lymphocytes (TILs) in chordoma

    (Impact Journals LLC, 2015) Feng, Yong; Shen, Jacson; Gao, Yan; Liao, Yunfei; Cote, Gregory; Choy, Edwin; Chebib, Ivan; Mankin, Henry; Hornicek, Francis; Duan, Zhenfeng

    Chordomas are primary malignant tumors of the notochord that are resistant to conventional chemotherapy. Expression of programmed cell death ligand 1 (PD-L1), prevalence of tumor-infiltrating lymphocytes (TILs), and their clinical relevance in chordoma remain unknown. We evaluated PD-L1 expression in three chordoma cell lines and nine chordoma tissue samples by western blot. Immunohistochemical staining was performed on a chordoma tissue microarray (TMA) that contained 78 tissue specimens. We also correlated the expression of PD-L1 and TILs with clinical outcomes. PD-L1 protein expression was demonstrated to be induced by IFN-γ in both UCH1 and UCH2 cell lines. Across nine human chordoma tissue samples, PD-L1 protein was differentially expressed. 94.9% of chordoma samples showed positive PD-L1 expression in the TMA. The expression score of PD-L1 for metastatic chordoma tumors was significant higher as compared with non-metastatic chordoma tumors. Expression of PD-L1 protein significantly correlates with the presence of elevated TILs, which correlates with metastasis. In summary, our study showed high levels of PD-L1 are expressed in chordoma, which is correlated with the prevalence of TILs. The current study suggests targeting PD-L1 may be a novel immunotherapeutic strategy for chordoma clinical trials.

  • Publication

    Distinguishing Untreated Osteoblastic Metastases From Enostoses Using CT Attenuation Measurements

    (American Roentgen Ray Society, 2016) Ulano, Adam; Bredella, Miriam; Burke, Patrick J; Chebib, Ivan; Simeone, Frank; Huang, Ambrose; Torriani, Martin; Chang, Connie

    Purpose: To determine if CT density thresholds of osteoblastic bone lesions can be used to distinguish untreated osteoblastic metastases from enostoses. Materials and Methods: The study group comprised 62 patients (37 enostoses, 25 untreated osteoblastic metastases) with sclerotic bone lesions found on CT. Etiology of sclerotic lesions was assessed histologically or by clinical and imaging follow-up. None of the patients had prior treatment for metastases. The average and maximum densities in Hounsfield Units (HU) were measured. Receiver operating curve (ROC) analysis was performed to determine sensitivity, specificity, area under the ROC curve (AUC), confidence intervals (CI), and cutoff values of CT densities to differentiate metastases from enostoses. Interreader reproducibility was assessed using intraclass correlation coefficient (ICC) with 95% CI. Results: Mean and maximum CT densities of enostoses were 1190 ± 239 and 1323 ± 234 HU and of osteoblastic metastases were 654 ± 176 and 787 ± 194 HU, respectively. Using a cut-off of 885 HU for average density, AUC was 0.982, sensitivity was 95%, and specificity was 96%. Using a cut-off of 1058 HU for maximum CT density, AUC was 0.976, sensitivity was 95%, and specificity was 96%. Mean density ICC was 0.987 for enostoses and 0.81 for metastases. Maximum density ICC was 0.814 for enostoses and 0.980 for metastases. Conclusion: CT density measurements can be used to distinguish untreated osteoblastic metastases from enostoses. An average density of 885 HU and a maximum density of 1058 HU provide reliable thresholds below which a metastatic lesion is the favored diagnosis.

  • Publication

    Opposing Immune and Genetic Mechanisms Shape Oncogenic Programs in Synovial Sarcoma

    (Cold Spring Harbor Laboratory, 2021-01-25) Jerby-Arnon, Livnat; Neftel, Cyril; Shore, Marni E.; Weisman, Hannah R.; Mathewson, Nathan; McBride, Matthew J.; Haas, Brian; Izar, Benjamin; Volorio, Angela; Boulay, Gaylor; Cironi, Luisa; Richman, Alyssa R.; Broye, Liliane C.; Gurski, Joseph M.; Luo, Christina; Mylvaganam, Ravindra; Nguyen, Lan; Mei, Shaolin; Melms, Johannes; Georgescu, Christophe; Cohen, Ofir; Buendia Buendia, Jorge Eduardo; Segerstolpe, Asa; Sud, Malika; Cuoco, Michael; Labes, Danny; Zollinger, Daniel R.; Ortogero, Nicole; Beechem, Joseph M.; Nielsen, G. Petur; Chebib, Ivan; Nguyen-Ngoc, Tu; Montemurro, Michael; Cote, Gregory; Choy, Edwin; Letovanec, Igor; Cherix, Stéphane; Wagle, Nikhil; Sorger, Peter; Haynes, Alex; Mullen, John; Stamenkovic, Ivan; Rivera, Miguel; Kadoch, Cigall; Wucherpfennig, Kai; Rozenblatt-Rosen, Orit; Suvà, Mario L.; Riggi, Nicolò; Regev, Aviv

    ABSTRACTSynovial sarcoma is an aggressive mesenchymal neoplasm, driven by the SS18-SSX fusion, and characterized by immunogenic antigens expression and exceptionally low T cell infiltration levels. To study the cancer-immune interplay in this disease, we profiled 16,872 cells from 12 human synovial sarcoma tumors using single-cell RNA-sequencing (scRNA-Seq). Synovial sarcoma manifests antitumor immunity, high cellular plasticity and a core oncogenic program, which is predictive of low immune levels and poor clinical outcomes. Using genetic and pharmacological perturbations, we demonstrate that the program is controlled by the SS18-SSX driver and repressed by cytokines secreted by macrophages and T cells in the tumor microenvironment. Network modeling predicted that SS18-SSX promotes the program through HDAC1 and CDK6. Indeed, the combination of HDAC and CDK4/6 inhibitors represses the program, induces immunogenic cell states, and selectively targets synovial sarcoma cells. Our study demonstrates that immune evasion, cellular plasticity, and cell cycle are co-regulated and can be co-targeted in synovial sarcoma and potentially in other malignancies.