Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
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Τρίτη 10 Οκτωβρίου 2017

Hodgkin Lymphoma: A Complex Metabolic Ecosystem with Glycolytic Reprogramming of the Tumor Microenvironment

Publication date: Available online 10 October 2017
Source:Seminars in Oncology
Author(s): Lekha Mikkilineni, Diana Whitaker-Menezes, Marina Domingo-Vidal, John Sprandio, Paola Avena, Paolo Cotzia, Alina Dulau-Florea, Jerald Gong, Guldeep Uppal, Tingting Zhan, Benjamin Leiby, Zhao Lin, Barbara Pro, Federica Sotgia, Michael P. Lisanti, Ubaldo Martinez-Outschoorn
BackgroundTwenty percent of patients with classical Hodgkin Lymphoma (cHL) have aggressive disease defined as relapsed or refractory disease to initial therapy. At present we cannot identify these patients pre-treatment. The microenvironment is very important in cHL since non-cancer cells constitute the majority of the cells in these tumors. Non-cancer intra-tumoral cells such as tumor-associated macrophages (TAMs) have been shown to promote tumor growth in cHL via crosstalk with the cancer cells. Metabolic heterogeneity is defined as high mitochondrial metabolism in some tumor cells and glycolysis in others. We hypothesized that there are metabolic differences between cancer cells and non-cancer tumor cells such as TAMs and tumor-infiltrating lymphocytes in cHL and that greater metabolic differences between cancer cells and TAMs are associated with poor outcomes.MethodsA case-control study was conducted with 22 tissue samples of cHL at diagnosis from a single institution. The case samples were from 11 patients with aggressive cHL who had relapsed after standard treatment with adriamycin bleomycin vinblastine and dacarbazine (ABVD) or were refractory to this treatment. The control samples were from 11 patients with cHL who achieved a remission and never relapsed after ABVD. Reactive non-cancerous lymph nodes from 4 subjects served as additional controls. Samples were stained by immunohistochemistry for three metabolic markers: translocase of the outer mitochondrial membrane 20 (TOMM20), monocarboxylate transporter 1 (MCT1) and monocarboxylate transporter 4 (MCT4). TOMM20 is a marker of mitochondrial oxidative phosphorylation (OXPHOS) metabolism. Monocarboxylate transporter 1 (MCT1) is the main importer of lactate into cells and is a marker of OXPHOS. Monocarboxylate transporter 4 (MCT4) is the main lactate exporter out of cells and is a marker of glycolysis. The immunoreactivity for TOMM20, MCT1 and MCT4 was scored based on staining intensity and percentage of positive cells, as follows: 0 for no detectable staining in > 50% of cells; 1+ for faint to moderate staining in > 50% of cells, and 2+ for high or strong staining in >50% of cells.ResultsTOMM20, MCT1 and MCT4 expression was significantly different in Hodgkin and Reed Sternberg (HRS) cells, which are the cancerous cells in cHL compared to tumor associated macrophages (TAMs) and tumor-associated lymphocytes. HRS have high expression of TOMM20 and MCT1 while TAMs have absent expression of TOMM20 and MCT1 in all but 2 cases. Tumor-infiltrating lymphocytes have low TOMM20 expression and absent MCT1 expression. Conversely, high MCT4 expression was found in TAMs, but absent in HRS cells in all but 1 case. Tumor-infiltrating lymphocytes had absent MCT4 expression. Reactive lymph nodes in contrast to cHL tumors had low TOMM20, MCT1and MCT4 expression in lymphocytes and macrophages. High TOMM20 and MCT1 expression in cancer cells with high MCT4 expression in TAMs is a signature of high metabolic heterogeneity between cancer cells and the tumor microenvironment (TME). A high metabolic heterogeneity signature was associated with relapsed or refractory cHL with a hazard ratio of 5.87 [1.16-29.71] (two sided p< 0.05) compared to the low metabolic heterogeneity signature.ConclusionAggressive cHL exhibits features of metabolic heterogeneity with high mitochondrial metabolism in cancer cells and high glycolysis in TAMs, which is not seen in reactive lymph nodes. Future studies will need to confirm the value of these markers as prognostic and predictive biomarkers in clinical practice. Treatment intensity may be tailored in the future to the metabolic profile of the tumor microenvironment and drugs that target metabolic heterogeneity may be valuable in this disease.



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