ALBERT

Description: Abstract 3576 Immunophenotype holds central role in the differential diagnosis of leukemic B-chronic lymphoproliferative disorders (B-CLPDs). However, select cases show overlapping characteristics and represent a diagnostic challenge. CD1d is an MHC-like molecule which presents glycolipids to the CD1d-restricted NKT cells, thus regulating innate and adaptive immune responses. Normal B-cells constitutively express CD1d, but its expression in B-CLPDs is currently unknown, with the exception of B-CLL in which there are only sparse and conflicting data. In the present study we assessed the diagnostic utility of CD1d expression in B-CLPDs and correlated the latter with various prognostic markers of B-CLL. CD1d expression was measured by 4-color flow cytometry on peripheral blood (PB), bone marrow (BM) and lymph node (LN) samples from 147 patients with B-CLL, 24 with mantle cell lymphoma (MCL), 20 with lymphoplasmacytic lymphoma (LPL), 10 with splenic marginal zone lymphoma (SMZL), 14 with hairy cell leukemia (HCL) and 3 with atypical hairy cell leukemia (aHCL).The utility of CD1d as a diagnostic marker for B-CLL versus the rest B-CLPDs was evaluated with receiver operator characteristic (ROC) curve analysis. A cut off value of 40% was selected and subsequently sensitivity, specificity, and likelihood ratios (LR) were calculated. One-way ANOVA was used for the assessment of differences in CD1d mean fluorescence intensity (MFI) between B-CLPDs with very high CD1d expression. The association of CD1d expression with CD38, CD49d and IgHV status was tested with Pearson and Spearman correlation, respectively. CD1d expression in B-CLPDs was as follows: B-CLL: 26%(range 0%-100%), MCL: 76%(15%-100%), LPL: 70%(53%-88%), SMZL: 96%(78%-100%), HCL: 100% and aHCL: 64%(51%-75)%. A CD1d expression of less than 40% was strongly indicative of B-CLL (LR: 26, specificity: 97%, sensitivity: 77%, figures 1 & 2A), as in all non B-CLL patients CD1d was 〉 40%. CD1d expression remained unaltered during either disease progression or relapse after chemotherapy in 17 patients with B-CLL that were assessed in various time points. Furthermore, CD1d was equally expressed in the BM, LN and PB of 6 patients with B-CLL, whereas it showed no significant correlation with CD38, CD49d and IgHV mutational status. Interestingly, in contrast to the generally low CD1d expression in B-CLL, all patients with trisomy 12 (n=5) expressed high CD1d levels (65-100%), in line with previous data reporting aberrant immunophenotypic features in trisomy 12. Also, HCL cells displayed significantly stronger intensity of CD1d expression (MFI: 196±26) compared to SMZL (MFI: 60±11, p=0.03), aHCL (MFI: 20.6±7, p=0.02) and normal B-cells (MFI: 62±5, p=0.03, figure 2B). In conclusion, our findings suggest that CD1d is a useful immunophenotypic marker for the differential diagnosis of B-CLL versus other B-CLPDs, as it is significantly downregulated in the former and it remains unaffected by disease stage and treatment status. Additionally, CD1d expression could also help in the differential diagnosis of B-CLPDs with prominent splenomegaly and overlapping phenotypes. Figure 1. ROC curve depicting the accuracy of CD1d expression of predicting the diagnosis of B-CLL in 218 patients with B-CLPDs. Figure 1. ROC curve depicting the accuracy of CD1d expression of predicting the diagnosis of B-CLL in 218 patients with B-CLPDs. Figure 2. CD1d expression in normal and clonal B-cells. (A) CD1d expression in a B-CLL (i) and a MCL (ii) patient. Normal B-cells are shown in orange and CD5+ neoplastic lymphocytes in green. (B) Stronger expression of CD1d in HCL (filled histogram in i, green color in ii) compared to SLVL (open histogram, i) and normal B cells (orange color, ii). Figure 2. CD1d expression in normal and clonal B-cells. (A) CD1d expression in a B-CLL (i) and a MCL (ii) patient. Normal B-cells are shown in orange and CD5+ neoplastic lymphocytes in green. (B) Stronger expression of CD1d in HCL (filled histogram in i, green color in ii) compared to SLVL (open histogram, i) and normal B cells (orange color, ii). Disclosures: No relevant conflicts of interest to declare.

Description: Abstract 2921 STAT3 and STAT5 regulate fundamental cellular processes and comprise the most studied signaling molecules of both normal and malignant hematopoiesis. Deregulation of STAT signaling contributes to leukemogenesis and may serve as a treatment target. In leukemic progenitors (LPs), the clustering of STAT3 and STAT5 phosphorylation patterns, both basal and after growth factor stimulation, can be achieved by flow cytometry, leading to the identification of distinct signaling profiles (SPs). In acute myeloid leukemia patients, SPs reflect the biological behavior of the LPs and can distinguish patient subgroups with worse prognosis and/or resistance to treatment. As epigenetic defects of genes involved in cell signaling are frequently observed in cancer cells we investigated the alterations in the SPs of MDS progenitors during azacytidine treatment and their correlation with response, cytogenetics and transfusion requirements. Bone marrow samples of 24 high risk MDS patients were obtained before and 15 days after the initiation of azacytidine in order to assess potential changes in SP before the disappearance of the LPs. According to the IWG response criteria patients were divided into group A (CR, PR and HI, n=10) and group B (stable disease and failure, n=14). Immunomagnetically purified LPs were either left untreated or stimulated with G-CSF and GM-CSF for 15` and then stained intracellularly with monoclonal antibodies against STAT3 and STAT5. The comparisons of basal and potentiated responses before and 15 days after azacytidine initiation were made with Mann-Whitney U-test. Clustering of SPs was performed with hierarchical cluster analysis and was correlated with treatment response, cytogenetics and transfusion dependence by using Chi square or Fisher Exact tests as appropriate. All analyses were performed using SPSS 14.0 software (SPSS Science, Chicago, IL). By clustering the SPs before and 15 days after the initiation of azacytidine we distinguished two subgroups of patients based on both the basal levels and potentiated response to growth factors. Patients with generally weak expression of STAT3 and STAT5 had significantly better response to azacytidine compared to those with strong expression of the same molecules (p=0.035), whereas there were no correlation of SPs with the karyotype (p=0.45) and transfusion rate (p=0.39). In line with the above, we further identified a STAT3+STAT5+ double positive population of MDS progenitors whose pretreatment levels after G-CSF and GM-CSF stimulation were inversely associated with treatment response (figure 1). Additionally, SP kinetics were following the disease course and response to therapy. In two late-stage MDS patients who achieved complete remission the SP was restored to early-stage MDS levels in day 15 after azacytidine initiation (figure 2A). In contrast, the SPs in the majority of non-responding patients remained unaltered (figure 2B), whereas the SP of a relapsing patient reverted to pretreatment levels after an initial restoration to early-stage MDS levels (figure 3). Figure 1. Significantly lower pretreatment levels of STAT3+STAT5+ MDS progenitors after G and GM-CSF stimulation in responding patients. (A) Representative plots of a patient who failed azacytidine (i, ii) and one who achieved CR (iii, iv). (B) Cumulative results in responding (A) and non-responding (B) patients. Figure 1. Significantly lower pretreatment levels of STAT3+STAT5+ MDS progenitors after G and GM-CSF stimulation in responding patients. . / (A) Representative plots of a patient who failed azacytidine (i, ii) and one who achieved CR (iii, iv). (B) Cumulative results in responding (A) and non-responding (B) patients. Figure 2. The kinetics of SPs follow the response to azacytidine. (A) The SP of a late-stage MDS patient who attained PR reverted to early-stage MDS levels at day 15 after the first cycle of azacytidine. (B) By contrast, a patient who failed treatment displayed no SP changes. Figure 2. The kinetics of SPs follow the response to azacytidine. . / (A) The SP of a late-stage MDS patient who attained PR reverted to early-stage MDS levels at day 15 after the first cycle of azacytidine. (B) By contrast, a patient who failed treatment displayed no SP changes. Figure 3. Kinetics of the SP in a relapsing patient Plots of a patient who achieved CR but relapsed 4 months after the discontinuation of azacytidine. Figure 3. Kinetics of the SP in a relapsing patient . / Plots of a patient who achieved CR but relapsed 4 months after the discontinuation of azacytidine. In conclusion, we demonstrate that SP alterations of MDS progenitors during azacytidine treatment can predict clinical response. Moreover, it appears that azacytidine can restore the leukemic signaling in MDS by modifying both the basal and potentiated expression of STAT3 and STAT5. Our findings advocate the differentiating activity of hypomethylating agents, potentially via epigenetic reprogramming of pivotal signaling networks of leukemic progenitors. Disclosures: No relevant conflicts of interest to declare.

Description: CD4+ T cells hold a central role in tumor immunity by orchestrating and regulating antitumor responses. Azacytidine can apparently modulate tumor immunity in myelodysplastic syndrome (MDS) patients and affect CD4+ cell polarization, mainly in responding patients. Signal transducer and activator of transcription (STAT) proteins have essential roles in the epigenetic control of T helper (TH) cell differentiation and aberrant STAT signaling is involved in the pathobiology of numerous malignancies by compromising tumor immunity. MDS have a strong immunopathogenetic component, but the CD4+ cell STAT signaling network and the effect of hypomethylating therapy on the former have not yet been investigated. We applied phospho-specific flow cytometry to explore the alterations of STAT signaling in CD4+ cells during azacytidine treatment and addressed their association with clinical and biological parameters. Peripheral blood mononuclear cells of 26 late-stage MDS and low blast count AML (LBC-AML) patients and 7 age-matched healthy individuals were obtained before and 15 days after azacytidine initiation. According to WHO classification, two patients had RCMD (8%), 10 (38%) had RAEB-II, 8 (31%) CMML-II and 6 (23%) LBC-AML. Based on the IWG criteria patients were divided into responders (CR, PR and hematologic improvement, n=12) and non-responders (stable disease and failure, n=14). We applied a modified protocol of phospho-specific flow cytometry to measure either basal (untreated) or potentiated (after stimulation with IL-6, IFNá and IL-2 for 15') phospho-STAT1, 3 and 5 levels with simultaneous staining for CD3 and CD4. The following potentiated, i.e. target/stimuli, nodes were studied: pSTAT1/IL-6, pSTAT1/IFNá, pSTAT3/IL-6, pSTAT5/IFNá and pSTAT5/IL-2. In the same patients TH cell subsets were measured by intracellular staining with IFNã, IL-4, FOXP3 and IL-17A along with CD3 and CD4. Comparisons were performed by Mann Whitney, Kruskal Wallis or Wilcoxon Signed-Rank test as appropriate. Clustering of signaling profiles (SPs) was performed with hierarchical cluster analysis and correlations by using ÷2 or Fisher Exact tests. Unsupervised clustering of the CD4+ SPs in MDS patients and controls revealed 4 signaling clusters (SC1-4, figure 1). No differences were noticed among the SCs in relation to treatment response, cytogenetics, IPSS, WPSS and IPSS-R and transfusion requirements. By contrast, the disease subtypes were nonrandomly distributed among the clusters (p=0.036). Most RAEB-II patients segregated in cluster 2, which displayed high basal levels of pSTAT5 and intense response of pSTAT1 to IL-6 and IFNá and of pSTAT5 to IFNá, whereas all healthy subjects were enclosed in SC4 which was characterized by low basal levels of all pSTATs and powerful response of pSTAT1 and 5 to IFNá and of pSTAT3 to IL-6. Also, SCs showed similar levels of TH cells, with the exception of SC1 which was associated with markedly higher levels of FOXP3+/IL-17+ cells both on day 0 (0.29% of total CD4+ cells, range 0.04%-0.54%, p=0.04) and day15 (0.31%, range 0.12%-0.35%, p=0.04) after azacitidine administration compared to other SCs. Interestingly, the levels of FOXP3+/IL-17+ cells downregulated significantly on day 15 in responders (0.07%, range 0.04%-0.4% vs 0.04%, range 0.02%-0.16%, p=0.03), whereas non responders showed a non-significant decrease (0.13%, range 0.01%-0.54% vs 0.08%, range 0.04%-0.31, p=0.2). We further performed cluster analysis of patients SPs 15 days after azacytidine initiation. Patients were separated in two SCs, while normal controls still formed a different cluster (SC3, Figure 2), indicating that, at least on day 15, azacytidine was not able to restore the abnormal STAT signaling in CD4+ cells. In conclusion, we demonstrate that the STAT signaling biosignature of CD4+ cells in late stage MDS patients is abnormal and also differs among the various disease subtypes. Moreover, consistent with recent data (Bontkes HJ, 2012, Constantini B et al, 2012), azacytidine treatment appears to affect mainly the FOXP3/TH17 axis, particularly in responders. Our results further suggest a clinically relevant immunomodulatory activity of azacytidine. Figure 1. Heatmap of pretreatment signaling clusters (SC) in CD4+ cells of patients and normal subjects. Figure 1. Heatmap of pretreatment signaling clusters (SC) in CD4+ cells of patients and normal subjects. Figure 2. Heatmap of SCs in CD4+ cells of patients and normal subjects on day 15 after azacytidine initiation. Figure 2. Heatmap of SCs in CD4+ cells of patients and normal subjects on day 15 after azacytidine initiation. Disclosures Kotsianidis: Genesis Pharma Hellas: Honoraria.

Description: The role of thrombophilia and LMWH use in pregnancy loss (PL) and pregnancy complications (PC) is debated. In this retrospective study from a single center we analyzed the clinical outcome of pregnancies in relation to thrombophilic factors and the use of LMWH, aspirin and folic acid in 143 women followed up for a total of 173 pregnancies referred to our center from 2003 to 2016. Methods: Women were referred to our unit for: more than 2 unexplained PL (n=96, 78 experienced only early PL, 11 had only late PL, 7 had both early and late), one pregnancy loss(n=45) or one pregnancy complication (placenta abruption, intrauterine growth restriction, eclampsia, n=2). Mutations in Factor V-Leiden (FVL, G1691A), Prothrombin (PTG, G20210A) and MTHFR (C677T, A 1206C) were checked by DNA hybridization Kit. Plasma levels of antithrombin-III, protein-C, free Protein-S, APCR, FVIII, FXII, PT aPTT, fibrinogen, homocysteine and La-test were measured by photometry (DACO). Anticardiolopin and anti-β2GPI antibodies (IGG and IGM) were measured by ELISA in serum (APLA). End points were live birth and pregnancy complications. The prevalence of thrombophilia in our cohort was similar with previous studies and 34/143 (23,4%) women were negative for all thrombophilic factors. We observed mutations in FVL(11,6%), PTG (9,6%), MTHFR (homozygous or double heterozygous, 33,3%) and deficiencies of AT-III (3,3%), Prot-C (1,6%), Prot-S (8,8%), APS (8,7%). Combined severe trombophilic factors were found in 31 women (21,5%) (FVL+PTG 4/31, Natural Anticoagulants one out 3 Def + MTHFR 3/31, APS + MTHFR 2/31, FVL+MTHFR 16/31, PTG + MTHFR 6/31). We then separated our cohort into women with 2 complications. The second group had significantly higher incidence of FVL mutation (12,5 vs 8,3%, p=0.05) and deficiencies of AT-III and Free Prot-S ( 6,5 vs 0 %, p=0.01) compared to the first one. By contrast, women in the first group had higher incidence of La-test (12,5 vs 4,5%, p=0,03), APLA ( 12 vs 6,6%, p=0.03) and Prot.C deficiency (4,5 vs 0%, p=0.01). In univariate analysis both hereditary and acquired thrombophilic factors did not correlated with pregnancy outcome (live birth or pregnancy complications). Only age as a continuous parameter correlated negatively with live birth and positively with pregnancy complications (p=0.01 and p=0.025, respectively), whereas high BMI as a continuous parameter also negatively affected live births (p= 0.049). Logistic regression analysis reveals that the age of 35 is the cut off for unfortunate pregnancy outcome. Pregnancies were proceeded with (n=143, 81,7%) or without (n=32, 18,3%,) LMWH. The decision to use LMWH were based in a positive thrombophilia screening test (n=84) or to prior history 〉2 pregnancy complications with negative trombophilia testing (n=59). Concomitant use of ASA was prescribed in 78 pregnancies (dose less than 100 mg/day) and concomitant follic acid in 143 pregnancies. The percentage of live births were identical in women treated with LMWH (87,4%) or not (87,5%, p=0.9). In multivariate analysis, the only factor that was strongly correlated to live birth was the duration of LMWH treatment (odds ratio, OR =3,567, 95% CI (1.845, 6,894), p= 0,01) and the titration of the dose with anti-Xa (OR=5,138, 95% CI (1,717, 15,376), p = 0,01, fig.1a). By ROC analysis the duration of LMWH which correlated to live birth was ≥ 5.5 months(fig. 1b). The addition of ASA was insignificant for live birth (p=0.7), while the duration (〉6months) of follic acid also appeared to add a benefit in combination with LMWH (p=0.01). Moreover, pregnancies proceeded without LMWH exhibited higher rates of pregnancy complications (18,75 vs 11,2%, p=0.08) and prematurity (14,3 vs 8,8%, p=0.05). In summary, our findings argue against hereditary thrombophilia screening in the cases of previous pregnancy loss or pregnancy complications. On the contrary, testing for APS even after the first event might be of value as this population often has laboratory evidence of APS and may benefit from proper anticoagulation. The use of LMWH and folic acid but not of ASA was related to less pregnancy complications or prematurity, whereas proper titration of LMWH by using anti-Xa and long duration of therapy were the only important factors for successful pregnancy outcome. Disclosures No relevant conflicts of interest to declare.

Description: Azacytidine (AZA), the mainstay of therapy in high risk Myelodysplastic syndromes (HR-MDS), affects CD4+ T-cell polarization and function, but the effect of these changes on tumor immunity is unclear. Signal transducer and activator of transcription (STAT) proteins are key regulators of differentiation and polarization of CD4+ T-cells in both health and cancer, but the STAT signaling architecture of CD4+ T-cell subsets in HR-MDS and its modulation by AZA are currently unknown. We applied single-cell phosphospecific flow cytometry in peripheral blood mononuclear cells from 67 HR-MDS patients at various time-points during AZA therapy. Unsupervised clustering of pretreatment STAT signaling profiles (SPs) of CD4+ T-cells revealed three signaling clusters (SCs), mainly differing in the potentiated responses of STAT3 to IL-6 stimulation (IL-6/STAT3 node). Compared to SC#1 and SC#3, patients in SC#2 displayed higher IL-6/STAT3 levels, higher levels of naïve (TN, p=0.05) and lower levels of PD1+ (p=0.04) and central memory ( TCM, p=0.04) CD4+ T-cells, and longer median overall survival (mOS, p=0.028, fig 1A). Moreover, comparisons of single signaling nodes revealed that the IL-6/STAT3 node correlated inversely with PD1+ (p=0.02) and IL-4+ (p=0.04) and positively with naïve CD4+ (p=0.04) and IFNγ+CD8+ T-cells (p=0.01). No other differences in clinicobiologic parameters, CD4+ and CD8+ T-cell subpopulations (FOXP3, IFNγ, IL-4, IL-17, Perforin and Helios) were noted among the 3 SCs and all other single nodes. To assess the effect of AZA on STAT signaling, we clustered the fold fold-change of pre- versus 6-month post-AZA SPs in CD4+ T-cells. Again the IL6/STAT3 node was the only differentiator among the clusters, and, by single node analysis, downregulation of IL6/STAT3 at 6th cycle (n=26) was associated with better response to AZA (p=0.02) and longer mOS (p=0.03), compared to upregulation of the same node (n=22); the latter also accompanied by an increase of IFNγ+CD8+ cells after AZA, (p=0.02, fig 1B). Further supporting a direct and beneficial modulation of the IL-6/STAT3 axis in CD4+ T-cells by AZA, the kinetics of IL-6/STAT3 during AZA therapy revealed a marked downregulation of the former node both at day15 (p=0.04) and cycle 6 after AZA (p=0.04) in responders (n=5), while no changes were observed in non-responders (n=7). We further compared the transcriptional profiles of isolated bone marrow CD4+ T-cells between responders (n=4) and non-responders to AZA (n=4) by RNA-seq, both prior and after AZA. No significant differences in pretreatment gene expression were identified. By contrast, 105 genes were differentially expressed at cycle 6 compared to pretreatment in responders (FDR

Description: Abstract 3795 Both basal and cytokine-induced phosho-STAT3 and pSTAT5 levels are altered in leukemias and profiling the STAT signaling network at the single cell level provides prognostic information (Irish et al, 2004). As cell signaling interacts with the epigenome (Mohammad et al, 2010) and numerous genes involved in signaling are aberrantly methylated in MDS (Figueroa et al, 2010) we investigated the alterations of STAT3/5 signaling in MDS progenitors during azacitidine therapy. Bone marrow samples of 58 high-risk MDS and AML/MDS patients were obtained before (d0) and 15 days (d15) after azacytidine initiation and at the indicated time points. According to the IWG response criteria, patients were divided into 4 groups: response (CR and PR, n=11 and n=5, respectively), hematologic improvement (HI, n=8), stable disease (SD, n=11) and failure (F, n=23). Mononuclear cells were either left untreated or stimulated with G-CSF and GM-CSF for 15′ and then stained intracellularly with the indicated antibodies. The hematopoietic hierarchy and G-CSF receptor (CFS3R) transcripts by qPCR were assessed on immunomagnetically purified Lin-CD34+ and CD34+ cells, respectively. Statistical comparisons were done by ANOVA and unpaired or paired t-tests as appropriate. STAT signaling profiles (SPs) in CD34+ cells were grouped using complete linkage hierarchical clustering and correlated with treatment response, karyotype and transfusion rate by using χ2 or Fisher Exact tests. Unsupervised clustering of pretreatment SPs in CD34+ cells identified 2 clusters (Fig 1A) mainly differing in the degree of potentiated STAT3/5 phosphorylation. Patients in cluster I displayed weak potentiated expression of pSTAT3/5 and had marginally better response to azacytidine compared to the ones in cluster II (p=0.06), whereas there were no differences among the two groups regarding the MDS subtype (p=0.41), karyotype (p=0.45) and transfusion rate (p=0.33). We further identified a G-CSF-inducible pSTAT3/5 double positive (DP) subpopulation of MDS CD34+ cells, whose levels both at d0 and d15 of the 1st cycle were inversely associated with response (Fig 1B), whereas its kinetics were following the disease course and response to azacytidine (Fig 1C,D). The DP subset was enriched in GMPs compared to the G-CSF-unresponsive pSTAT3/5 double negative (DN) subpopulation, suggesting a higher leukemia initiating cell activity (Goardon et al, 2011), whereas the DN subset was marginally enriched in MEPs (Fig 2). Also, compared to the DN subset, the DP population exhibited decreased Ki67 expression and increased Bcl2 and p53 levels (Fig 3A), indicating quiescence and increased antiapoptotic and tumor suppressive properties, respectively. Of note, the levels of the above molecules in the two subsets remained unaltered both at d0 and d15, indicating that these subsets represent genuine cellular entities with solid properties. To determine if CSF3R expression and/or its modulation by azacitidine are responsible for the alterations of the DP population, we checked CSF3R levels in isolated CD34+ cells from patients with either absence or full expression of the DP subset because CSF3R is downregulated after G-CSF stimulation. The two groups showed identical protein and mRNA levels of CSF3R at both d0 and d15 (Fig 3B,C). In summary, we identified a G-CSF-inducible pSTAT3/5 DP subpopulation with leukemic stem cell properties, which is potentially involved in MDS biology and epigenetically modulated, as implied by its kinetics during hypomethylating therapy. More important, given the strong association of pretreatment levels of the DP subset with the response to azacitidine, the latter subset may serve both as a treatment target and response biomarker. Fig 1. (A) Heatmap of pretreatment SPs in CD34+ cells. (B) The DP subset was significantly decreased in responding patients. (C, D) Results and representative plots of the DP subset kinetics in patients with R (n=7), HI (n=3), SD (n=1) and F (n=3). Fig 1. (A) Heatmap of pretreatment SPs in CD34+ cells. (B) The DP subset was significantly decreased in responding patients. (C, D) Results and representative plots of the DP subset kinetics in patients with R (n=7), HI (n=3), SD (n=1) and F (n=3). Figure 2. (A) Cytometric and (B) cumulative analysis (n=8) of the hematopoietic hierarchy in DP and DN subsets. Figure 2. (A) Cytometric and (B) cumulative analysis (n=8) of the hematopoietic hierarchy in DP and DN subsets. Figure 3. (A) Results and histograms of ki67, Bcl-2 and p53 assessment in DP (grey fill) and DN (thick line) subsets (control, thin line). (B) Protein and mRNA expression of CSF3R in patients with absence (n=5) or full expression (n=5) of the DP population. (C) Similar CSF3R levels at d0 and d15, despite changes in the levels of the DP subset (not shown, n=5). Figure 3. (A) Results and histograms of ki67, Bcl-2 and p53 assessment in DP (grey fill) and DN (thick line) subsets (control, thin line). (B) Protein and mRNA expression of CSF3R in patients with absence (n=5) or full expression (n=5) of the DP population. (C) Similar CSF3R levels at d0 and d15, despite changes in the levels of the DP subset (not shown, n=5). Disclosures: Kotsianidis: Genesis-Pharma: Honoraria, Research Funding.

Description: Published articles support the effect of chemotherapy in the immune environment of tumors, including lung carcinomas. The role of CD4 + T-cells is crucial for expansion and accumulation of other antigen-specific immune cells, and the participation of CD8 + cells in tumor killing activity has been confirmed by many studies. However, little is known about the effect of chemotherapy on the healthy lung parenchyma from lung cancer patients, and whether there are differences between the different chemotherapy compounds used to treat this patient population. The aim of our study was to explore the effect of chemotherapy on CD4 + and CD8 + cells in the bronchoalveolar lavage fluid (BALF) of the healthy lung in patients treated with standard chemotherapy regimens. Fifteen patients underwent BAL, in the healthy lung before and after six chemotherapy courses. Platinum-based regimens included vinolerbine (VN) in 6 patients, gemcitabine (GEM) in 4 patients and etoposide (EP) in 5 patients. All patients but one were males and smokers (93%). The median age of patients was 56 years (42–75). No significant difference was noted in the patients’ age between the three treated groups. Furthermore, between the three groups, no significant changes in the means of CD4 + and CD8 + cells were noted. However, when we compared the mean CD4 + cells before and after chemotherapy within each group, changes were noted when comparing VN before versus after (p = 0.05), GEM before versus after (p = 0.03), and EP before versus after (p = 0.036). In our pilot study, changes were noted in BALF CD4 + cells for the three most applied regimens at the normal lung parenchyma.