الفهرس 
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Abstract
Acute myeloid leukemia (AML) is a hematopoietic malignancy characterized by a clonal expansion of low differentiated hematopoietic precursors that infiltrate the bone marrow and limit normal hematopoiesis. Although AML occurs in all ages, it appears predominantly in older people. AML remain a major clinical challenge characterized by a poor prognosis, poor overall survival and management difficulties, which is even more difficult in elderly patients who frequently have other pathologies associated with age (Valhondo et al., 2020). The capacity of the immune system to control tumor growth and metastasis has focused attention in order to develop new strategies to treat cancer directed to stimulate the patient immune system such as checkpoint blockade or using engineered immune cells to attack cancer as it is currently used in CAR-T therapies. Thus, novel cancer immunotherapies have emerged in the last decades that are being analyzed in clinical trials in patients with hematologic and solid cancer (Winer et al., 2019). The analysis of the patient immune system represents a central point for the design of personalized immunotherapies. Several alterations have been described in T and NK cells in AML patients that limit tumor control by the immune system (Barrett et al., 2020). Nectin and nectin-like molecules can represent biomarkers for cancer diagnosis, players in immune responses and targets for cancer immunotherapy. CD112 (Nectin-2) and CD155 (Necl-5) were identified as ligands for the DNAM-1 receptor (Gao et al., 2017). DNAM-1 (also known as CD226) was first discovered as a costimulatory receptor expressed on cytotoxic T cells. DNAM-1 is also expressed by NK cells and is involved in T cell- and NK cell-mediated cytotoxicity (Valhondo et al., 2020). In the last decade, one of the major advances in cancer immunotherapy was the use of monoclonal antibodies (mAbs) to block inhibitory immune checkpoints. One of these inhibitory receptors is TIGIT (T cell immunoreceptor with Ig and ITIM domains) , that is expressed in different immune cells such as T cells, regulatory T cells, follicular T cells and NK cells. TIGIT could bind to CD155 (PVR) on dendritic cells (DCs), macrophages, etc. with high affinity. TIGIT shares the same ligands, CD155 and CD112, with the activating/co-stimulatory receptor DNAM-1 and shows higher affinity than DNAM-1 for CD155 (Sanchez-Correa et al., 2019). Blockade of TIGIT led to increased cell proliferation, cytokine production, and degranulation of TA-specific CD8+ T cells and TIL (tumor infiltrating lymphocytes) CD8+ T cells ( Joe-Marc Chauvin et al.,2015). The aim of the study is to assess the prognostic value of Poliovirus receptor (CD155) in patients with acute myeloid leukemia. To achieve this aim , CD155 expression was detected in 70 patients with denovo AML beside 30 matched healthy control. Our results could be summarized as follow : There was significant elevation of WBCS and LDH in AML group compared to control group. Hb and PLT were significantly reduced in AML group compared to control group. Otherwise no other significant could be detected.There was significant elevation of CD155 in AML group compared to control group. No significant difference regarding age and gender among studied groups There was significant positive correlation between CD155 and LDH. Otherwise no other significant difference could be detected.ROC analysis was conducted to identify the optimal CD155 levels for prediction of AML. CD155 best cut-off values were 1.0 The area under the curve (AUC) was 0.945 (p=<0.001). Univariate analysis revealed that CD155 was significant risk factor for shorter OS among cases and also positive expression of CD16 and CD56 and AML M3 were significantly associated with longer survival. Multivariate analysis revealed that only CD155 was significantly risk factor for shorter OS. At the end of follow up period (24months), overall survival (OS) of studied patients estimates 87.1% at 12months interval. OS of studied patients estimates 52.9% at 24 months interval. As regard CD155, OS estimates 87.5% at 12 months interval and 87.5% at 24 months interval in (CD155<1.0) group, also OS estimates 91.9% at 12 months interval and 48.4% at 24 months interval in (CD155>1.0)group, significant difference between 2 groups (P 0.048). At the end of follow up period (24months), disease free survival (DFS) of studied patients estimates 85.3% at 12months interval. DFS of studied patients estimates 70.0% at 21 months interval. As regard CD155, DFS estimates 100% at 21 months interval in (CD155<1.0) group, also DFS estimates 88.5% at 12 months interval and 64.5% at 24 months interval in (CD155>1.0)group, no significant difference between 2 groups (P 0.080).