Innate CD8 T-cells as a potential predictive biomarker for deep molecular response in chronic myeloid leukemia patients

Innate CD8 T-cells as a potential predictive biomarker for deep molecular response in chronic myeloid leukemia patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Innate CD8 T-cells as a potential predictive biomarker for deep molecular response in chronic myeloid leukemia patients Emilie Cayssials, Lucie Lefèvre, Amandine Decroos, Florence Jacomet, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7590855/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Dec, 2025 Read the published version in Cancer Immunology, Immunotherapy → Version 1 posted 20 You are reading this latest preprint version Abstract In chronic myeloid leukemia (CML), the role of immune effectors has been suggested in the achievement of a sustained deep molecular response (DMR) and treatment-free remission (TFR) after tyrosine kinase inhibitor (TKI) discontinuation. A contributory role of the distinct new innate CD8 T-cell pool in control of CML residual disease after TKI cessation was recently highlighted. Here, we evaluated longitudinally whether innate CD8 T-cells predict CML therapy success in a cohort of newly diagnosed CML patients treated in the DasaPegIFN clinical trial. After 3 months of treatment (M3), we observed a significant increase of innate CD8 T-cell frequency as compared to diagnosis, together with an early shift within the pool of CD8 T-cells towards an innate/memory phenotype. We also found that patients with high innate CD8 T-cell frequency at M3 achieved DMR earlier and at higher rates than patients with low innate CD8 T-cell frequency. Remarkably, this signature pre-existed at the time of diagnosis, suggesting the possible role of the patient’s initial individual immune status. High innate CD8 T-cell frequency was also associated with maintaining DMR stability for 2 years. Taken together, our findings highlight innate CD8 T-cells as a potential marker for CML therapy success and TFR eligibility. Chronic myeloid leukemia deep molecular response immune biomarker innate CD8 T-cell Figures Figure 1 Figure 2 Figure 3 Introduction Since the advent of tyrosine kinase inhibitors (TKIs), chronic myeloid leukemia (CML) has become a chronic disease with life expectancy comparable to that of unaffected individuals. Following treatment by TKI, 5-year probability of achieving a deep molecular response (DMR) ranges from 38% to 64%[ 1 ]. Second-generation TKIs (nilotinib, dasatinib and bosutinib) have been associated with an earlier and higher rate of patients experiencing DMR. Achieving a sustained DMR represents the most recent goal in CML treatment, both to prevent disease progression and to allow an attempt at TKI discontinuation (Hochhaus et al., Leukemia 2020). Although the immune abnormalities reported in CML-chronic phase (CP) patients at diagnosis are partially corrected after TKI therapy, only a few studies have focused on immunological prognosis factors impacting the depth of the response, which heretofore include NK cells (or NK cell-related markers such as killer-cell immunoglobulin-like receptors (KIR)) and Vδ2 γδ T-cells[ 2 – 6 ]. Considering the main conventional anti-tumoral effector compartment, namely conventional cytotoxic CD8 T-cells, to date no relationship has been established between prognosis and treatment success. We recently identified a new subset of CD8 T-cells sharing properties with conventional memory CD8 T-cells, and exhibiting NK-like features. This CD8 T-cell subset is characterized by CD8 expression along with a classical TCRαβ, NK receptors (panKIR/NKG2A), an EMRA (effector memory cells re-expressing CD45RA) phenotype (CD45RA + , CCR7 − ) and high Eomesodermin (Eomes) expression[ 7 , 8 ]. Innate CD8 T-cells hold high anti-tumoral potential, as evidenced by their prompt IFN-γ production in response to innate-like co-stimulation by IL-12 and IL-18[ 7 , 8 ]. Our previous work has shown that peripheral blood innate CD8 T-cells (CD8 + TCR-αβ + Eomes + panKIR/NKG2A + ) are drastically reduced and functionally deficient in CML patients at diagnosis[ 9 ]. Moreover, innate CD8 T-cell deficiencies at CML diagnosis have been found to be partially reversed in stable complete cytogenetic remission 8 and major molecular response (MMR) patients on TKI treatment[ 10 ], highlighting this CD8 T-cell subset as a new potential effector controlling CML. Consistent with this notion, we demonstrated that innate CD8 T-cells are markedly increased in patients in sustained TFR as compared to patients in MMR under TKI therapy, and even to healthy donors[ 10 ]. Finally, in a previous prospective study comparing patients in TFR versus in molecular relapse (MR) after TKI cessation, we have shown that innate CD8 T-cells, in combination with NK cells, may be a predictive marker for TFR success in CML treatment[ 11 ]. In the present study, we hypothesized that innate CD8 T-cells are closely associated with the achievement of DMR under TKI therapy. To test this assumption, we prospectively and longitudinally analyzed a cohort of 38 CP-CML (chronic phase of CML) patients treated first-line with dasatinib for three months and subsequently in combination with small doses of IFN-α[ 12 ]. This protocol aimed to achieve high rates of early and sustained DMR, hence offering the possibility to investigate biological markers linked to DMR achievement at one year and/or DMR stability over two years in the same cohort over time. Methods 1. Patient and healthy donor characteristics The present work is a sub-study of the DASA-PegIFN study (EudraCT Number 2012-003389-42, ClinicalTrials.gov. NCT01872442) approved by the National Health regulatory authorities and ethical committee (Poitiers, France). This study is a prospective, nonrandomized phase 2 trial, conducted in 22 centers in France. All the participating patients provided their written informed consent for the clinical study and ancillary biological studies. Briefly, newly diagnosed Ph + CP-CML patients were treated with first-line dasatinib at 100 mg/day. At month 3, Peg-Interferon-alpha-2b (PegIntron®, Merck KGaA, Darmstadt, Germany) was initiated at 30 µg/week subcutaneously for eligible patients (in the absence of significant cytopenia or extra hematological adverse event greater than grade 2 with dasatinib alone for the 3 first months) and for a maximum duration of 21 months. The results of this trial and protocol have been reported[ 12 ]. During the trial, peripheral blood was collected on heparin at several time points: at diagnosis, and at 3, 6, 12 and 24 months after initiation of treatment. Among the 61 patients eligible for the dasatinib + Peg-IFNα2b therapy from month 3, we analyzed samples from 40 consecutive patients for whom at least four time points were available. Two of them were excluded for technical issues. Patient responses to treatment were classified as conforming to 2013 ELN criteria. Major molecular response (MMR) was defined as a ratio of BCR::ABL1 / ABL1 IS ≤ 0.1% on the international scale (IS). A ratio of BCR::ABL1 / ABL1 IS ≤ 0.01% defines a deep molecular response (DMR). Patients were separated into two groups according to whether or not (noDMR) they achieved DMR at 12 months (DMR) (see Table 1 for the whole cohort and group patient’s characteristics). Table 1 All DMR at 12 months * (n = 38) noDMR DMR (n = 22) (n = 16) Age (years) 45 ± 12 42 ± 12 48 ± 12 Sex, n (%) F 15 (39%) 6 (27%) 9 (56%) M 23 (61%) 16 (73%) 7 (44%) Sokal score, n (%) Low (< 0.8) 25 (66%) 11 (50%) 14 (88%) Int/high (≥ 0.8) 13 (34%) 11 (50%) 2 (12%) ELTS score, n (%) Low 30 14 16 Intermediate 6 6 0 High 2 2 0 *DMR: deep molecular response ( BCR::ABL1/ABL1 IS ≤ 0.01%) Frozen peripheral blood mononuclear cells (PBMC) from 21 healthy donors (HD) (median age 28 years, range: 22–65, sex ratio: 0.5) were obtained from the French Blood Institute (Etablissement Français du Sang, Lyon, France). 2. PBMC isolation and cryopreservation PBMCs were isolated from blood samples by density gradient centrifugation (Histopaque®-1077, Sigma-Aldrich, St Louis, MO, USA), resuspended in 90% Fetal Bovine Serum (10270106, Gibco®, Thermo Fisher Scientific, Waltham, MA, USA) with 10% DMSO (D2650, Sigma-Aldrich), and cryopreserved at -80°C or in liquid nitrogen until use. 3. Flow cytometry Phenotypic analysis of cells from HD and CML patients was performed using ex vivo flow cytometry. All monoclonal antibodies (mAbs) used in this study are listed in Supplementary Table 1 . Expression of the different markers was assessed by staining PBMC with appropriate combinations of mAbs. PanKIR/NKG2A referred to staining with a mixture of the following three antibodies from Miltenyi Biotec (Bergisch Gladbach, Germany) KIR2D, KIR3DL1/KIR3DL2 (CD158e/k) and NKG2A (CD159a). Dead cells were excluded using the Live/Dead® Fixable NearIR Dead Cell Stain kit (L10119, Invitrogen™, Thermo Fisher Scientific). For intranuclear Eomes staining, cells were permeabilized using an anti-human Foxp3 staining kit according to the manufacturer’s protocol (73-5776-40, eBioscience™, Thermo Fisher Scientific). Flow data were acquired on a FACSVerse flow cytometer (Becton, Dickinson & Company, Franklin Lakes, NJ, US) with FACSuite™ software (Becton, Dickinson & Company) and analyzed using FlowJo™ v10 (Becton, Dickinson & Company). A detailed gating strategy is presented in Supplementary Fig. 1 . Results are expressed as frequencies or as mean fluorescence intensity (MFI). 3. Statistical analysis All statistical data analyses were performed using GraphPad Prism v7.0 (GraphPad Software, Inc). Friedman’s test with Dunn’s multiple comparison test and Mann-Whitney two-tailed test were used for unpaired data analysis. Two-way ANOVA with Šídák's multiple comparison and Wilcoxon tests were used for paired data. A p value < 0.05 was considered significant (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001). Receiver operating characteristic (ROC) curves were built using the logarithm of innate CD8 T-cell frequency after three months of therapy or at diagnosis. The Youden index was used to determine the cut-off of innate CD8 T-cell frequency. Cumulative incidence was presented as Kaplan-Meier curves. Significant differences between curves were analyzed using a log-rank test statistical analysis. Results The first three months of treatment are associated with increased innate CD8 T-cell frequency We analyzed peripheral blood innate CD8 T-cells (defined as Eomes + panKIR/NKG2A + cells among TCR-αβ + CD8 + cells) by flow cytometry at multiple time points from diagnosis up to 24 months of therapy in 38 CML patients participating in the phase II DASA-PegIFN clinical trial (see Methods and Table 1 ) . Figure 1A shows a two-fold increase in the percentage of innate CD8 T-cells at the three-month (M3) treatment stage (dasatinib alone, PegIFN not yet initiated) as compared to diagnosis in a representative patient. Considering the entire cohort, we found a significant increase in the frequency of innate CD8 T-cells (5.98 ± 5.43% vs. 3.78 ± 3.39%, mean ± SD), as compared to diagnosis (Fig. 1B, M3 vs . diagnosis). After M3, we observed a decline in the percentage of CD8 T-cells (rapid between M3 and M6, and slower thereafter). However, it is worth noting that this rate remains higher than at the time of diagnosis. When individual patients were examined, higher levels of innate CD8 T-cells were observed at M3 in 79% of them (Fig. 1C). In accordance with our previous observation in another independent cohort of CML patients[9], we confirmed the specific quantitative deficiency of innate CD8 T-cells at diagnosis as compared to the healthy donor (HD) group ( Supplementary Fig. 2 ). Early effects of TKI therapy on the pool of CD8 T-cells were not restricted to innate CD8 T-cells, as in 82% of patients conventional-memory CD8 T-cell (defined as Eomes + panKIR/NKG2A − ) frequency concomitantly increased, whereas naïve CD8 T-cell (defined as Eomes − panKIR/NKG2A − ) frequency decreased after three months of therapy ( Supplementary Fig. 3 ), as previously described[13]. Innate CD8 T-cell frequency at M3 selectively predicts DMR achievement at 12 months We then searched for a potential relationship between the frequency of innate CD8 T-cells and the achievement of a deep molecular response (DMR) at 12 months. Taking the entire kinetics into account, we evidenced that DMR patients had significantly higher innate CD8 T-cell frequencies throughout the 24 months of therapy compared to the noDMR group (Fig. 2A ). Remarkably, the increased frequency of innate CD8 T-cells after three months of therapy, in comparison to diagnosis, was more pronounced in the DMR group than in the noDMR group (Fig. 2B). This phenomenon was specific to innate CD8 T-cells, as conventional-memory CD8 T-cell frequency did not differ between the two groups at diagnosis and at M3 ( Supplementary Fig. 4 ). One explanation could be a shift within the CD8 T-cell pool in favor of innate CD8 T-cells at the expense of the naïve T-cell pool, as suggested by the lower frequency of naïve CD8 T-cells observed concomitantly at M3 ( Supplementary Fig. 4 ). Furthermore, we observed that innate CD8 T-cell frequency at diagnosis tended to be higher in the DMR group than in the no-DMR group (p-value: 0.0511, Mann-Whitney test, data not shown). These results provide evidence that innate CD8 T-cell frequency at three months of dasatinib therapy may be a predictive marker for DMR achievement (evaluated at 12 months). Innate CD8 T-cell frequency as an indicator of DMR achievement and its durability ROC curves were built to determine a cut-off value for innate CD8 T-cell frequency at M3 (p-value: 0.0044), and to establish whether this parameter could be used as a biomarker ( Supplementary Fig. 5 ). The analysis showed that the cut-off value for innate CD8 T-cell frequency was 6.43% at M3. Then, we determined the cumulative incidence of DMR over the first 24 months of therapy in patients with low versus high innate CD8 T-cell frequencies at M3 (Fig. 3B). DMR achievement occurred significantly earlier and at higher rates in patients with high innate CD8 T-cell frequency at M3. Patients with low innate CD8 T-cell frequency (n = 25) exhibited slow kinetics of DMR obtention that never reached the rate of patients with high innate CD8 T-cell frequency (n = 13): 51.30% during the 24 months of treatment compared to 32.47%. (Fig. 3B). These data supports the conclusion that high innate CD8 T-cell frequency in peripheral blood after three months of therapy may be an indicator of early DMR achievement. Of note, by applying the same approach based on the frequency of innate CD8 T-cells at diagnosis (Fig. 3A), we observed that 70.94% of patients with > 5.5% of innate CD8 T-cells at diagnosis achieved DMR in 21 months of treatment and that only 25.34% of the CML patients with ≤ 5.5% of innate CD8 T-cells reached DMR in two years. Consequently, innate CD8 T-cell frequency at diagnosis may also predicts DMR achievement. Alongside DMR achievement, its stability over time (≥ 2 years) is a crucial criterion for CML patients to be eligible for treatment discontinuation[14]. In the DasaPeg IFN trial, with median follow-up of 54.1 months (range 30.6–69.1), 46% of patients achieved a 2-year sustained DMR[12]. To test whether innate CD8 T-cell frequency was associated with treatment response stability, we separated patients with stable DMR for more than two years (n = 18) from patients without stable DMR (n = 16). Remarkably, innate CD8 T-cell frequency after three months of therapy was significantly higher in patients with a stable DMR for more than two years than in patients without a stable DMR (Fig. 3C). The same conclusion could be applied when considering the frequency of innate CD8 T-cells at CML diagnosis (Fig. 3C ) , thereby reinforcing the notion that the status of innate CD8 T-cells is closely associated with a stable DMR in CML patients. Finally, this effect was specific to the innate CD8 T-cell compartment, as conventional-memory and naïve CD8 T-cell frequencies were similar between the two groups regardless of the time point (at diagnosis or after three months of therapy) ( Supplementary Fig. 6 ). Taken together, our results demonstrate that innate CD8 T-cell frequency at M3 is associated with an early, deep and, stable response to CML therapy. Moreover, this phenomenon may be partially related to the status of this distinct CD8 T-cell compartment at the time of CML diagnosis. Discussion A sustained DMR has become a goal in efforts to strengthen CML stability and is a prerequisite for attempts at TKI cessation[ 14 , 15 ]. Recent data in the literature highlight the potential contribution of immune effectors such as NK cells and γδ T-cells in clinical responses to TKI therapy[ 4 , 6 , 16 ], including achievement of DMR[ 17 – 19 ]. Here, we focused on new effector CD8 T-cells, specifically innate CD8 T-cells, which consist of unconventional T-cells with innate-like responses. We provided evidence for their close association with the achievement of sustained DMR in a prospective longitudinal study in the DASA-PegIFN clinical trial[ 12 , 20 ]. We have previously reported deficiencies of innate CD8 T-cells at CML diagnosis that were at least partially corrected in patients having achieved complete cytogenetic remission and MMR following TKI therapy[ 9 , 10 ]. Here, to reach definitive conclusions on the involvement of innate CD8 T-cells in CML control, we conducted a prospective monitoring from CML diagnosis and through 24 months of treatment. To date, very few immunological longitudinal studies have been carried out[ 5 , 13 ], particularly taking the patient’s initial immune status into account. In this work, we observed an increased frequency of innate CD8 T-cells in most patients (79%) as early as the third month of treatment, i.e. during the initial treatment phase with dasatinib alone. Mechanistically, dasatinib has been described to have immune-mediated effects[ 6 , 16 , 21 – 23 ], in particular on T-cells. It could act either by driving the proliferation of innate CD8 T-cells or by increasing their number through differentiation from their conventional CD8 T-cell counterparts. Consistent with the latter hypothesis, we have previously shown in a murine model of dasatinib oral gavage that this TKI induced a drastic decrease of thymic memory CD8 T-cells with a shift toward innate CD8 T-cells[ 24 ]. In the present study, we demonstrated that the increased proportion of innate CD8 T-cell compartments is concomitant with increased conventional CD8 memory T-cell frequency, and is also closely associated with decreased frequency of naïve CD8 T-cells, suggesting a shift from naïve to memory T-cells. These results are also congruent with a previous study[ 13 ], which demonstrated significant phenotypic changes in immune effector CD8 T-cells towards an EMRA phenotype after three months of treatment with dasatinib. Indeed, we previously showed that the innate CD8 T-cell compartment is primarily composed of memory cells exhibiting an EMRA phenotype and preferentially expressing the surface molecule CD57, a terminal differentiation marker[ 8 ]. Following the M3 frequency peak, we observed a decrease in the frequency of innate CD8 T-cells in the whole cohort. This observation is consistent with the decrease of EMRA CD8 T-cells reported by Huuhtanen et al. , after administration of IFN-α in combination with dasatinib[ 13 ]. They demonstrated that IFN-α broadens the immune repertoire and increases the number of costimulatory intercellular interactions, highlighting the positive immunomodulatory effects of IFN-α. However, in their clinical trial, as in ours, no patients without IFN-α treatment were included, therefore no definitive conclusions can be drawn about the impact of IFN-α. As expected, a high proportion of DMR (42%) was obtained at 12 months in our dasaPEG trial. This allowed us to compare the frequency of innate CD8 T-cells between patients achieving DMR at 12 months (DMR, n = 16) and those who did not (noDMR, n = 22). Remarkably, although an increased proportion of innate CD8 T-cells was observed in both DMR and noDMR groups between diagnosis and the third month of dasatinib treatment, frequency of these cells measured at three months was significantly higher in the DMR group. Moreover, the higher level of innate CD8 T-cell frequency in DMR patients was maintained during the following 12 months (after 24 months of treatment). On the other hand, conventional memory T-cells did not discriminate between DMR and no-DMR patient groups, indicating that innate CD8 T-cells are specifically associated with DMR achievement. Finally, the high proportion of innate CD8 T-cells at M3 was associated with sustained DMR at 2-years, suggesting that innate CD8 T-cells influence not only the speed and rate of reaching DMR, but also its durability. Another important aspect revealed by our study concerns the potential role of the patient's immune system state at the time of diagnosis in determining the efficacy of treatment response. Indeed, despite a quantitative deficit in innate CD8 T-cells, at the time of diagnosis, their proportion tends to be higher in patients who achieve/sustain DMR than in those who do not. These data allow us to propose a scenario in which the more innate CD8 T-cells are represented at the time of diagnosis, the more efficiently they will be amplified by dasatinib so as to achieve stable DMR. All in all, our data lead us to suggest that innate CD8 T-cell frequency may be a predictive immune marker of the achievement of stable DMR in CML patients. Of note, this hypothseis was obtained despite our small number of patients and the homogeneous nature of our cohort (low risk of progression based on Sokal and ELTS scores). Another limitation is that we only analyzed the numerical level of innate CD8 T-cells, without studying their antitumor functions, especially those of the innate type. Therefore, further studies focusing on innate CD8 T-cells, including an analysis of their innate-associated transcription factors, effector markers (perforin, granzyme B) and immune checkpoints, may be useful to identify a full DMR immune signature. More generally, given the patients’ immune and clinical status, our study requires confirmation using large longitudinal cohorts, including patients treated not only with dasatinib but also with all other TKIs available for first-line treatment (imatinib, nilotinib, bosutinib). In CML, biomarkers are now needed to predict both the achievement of stable DMR and the success of treatment discontinuation. In this respect, a new paradigm would assume that innate CD8 T-cells can serve as a longitudinal predictive marker from diagnosis until eligibility for treatment discontinuation. By providing evidence that an individual’s innate CD8 T-cell immune profile as early as diagnosis may be a predictive marker of stable DMR, our data support this assumption. Declarations Acknowledgments We are especially indebted to Jeffrey Arsham for editing the English of our manuscript. We thank Julie Paul from the CIC-1402 for her help with statistical analysis. We thank the ImageUP (Université de Poitiers) flow cytometry core facilities, and Centre de Ressources Biologiques (CRB, CHU de Poitiers). This study was supported by INSERM, CHU de Poitiers, Université de Poitiers, Fi-LMC (France intergroupe des Leucemies Myéloides Chroniques), Association Laurette Fugain (ALF 2015_10), Ligue contre le Cancer du Grand Ouest (Comités départementaux de la Vienne, de la Charente, de la Charente Maritime et des Deux-Sèvres), Association pour la Recherche en Immunologie-Poitou-Charentes (ARIM-PC), le Cancéropôle Grand Sud-Ouest et le Groupement Interrégional de Recherche Clinique et d’Innovation Sud-Ouest Outre-Mer (API-K 2017), and INCa-DGOS 8658 (PRT-K 2015-052). A.B. and E.C. were supported by fellowships provided by Fondation Brystol-Meyers Squibb and Région Nouvelle Aquitaine, and Sport & Collection, respectively. Funding This study was supported by INSERM, CHU de Poitiers, Université de Poitiers, Fi-LMC (France intergroupe des Leucemies Myéloides Chroniques), Association Laurette Fugain (ALF 2015_10), Ligue contre le Cancer du Grand Ouest (Comités départementaux de la Vienne, de la Charente, de la Charente Maritime et des Deux-Sèvres), Association pour la Recherche en Immunologie-Poitou-Charentes (ARIM-PC), le Cancéropôle Grand Sud-Ouest et le Groupement Interrégional de Recherche Clinique et d’Innovation Sud-Ouest Outre-Mer (API-K 2017), and INCa-DGOS 8658 (PRT-K 2015-052). A.B. and E.C. were supported by fellowships provided by Fondation Brystol-Meyers Squibb and Région Nouvelle Aquitaine, and Sport & Collection, respectively. Competing Interests The authors have no conflicting financial interestsin in relation to the work described. Author Contributions A.B., L.L., E.C., A.D. and F.J. designed the experiments, performed the experiments, analyzed and interpreted the data. N.P. contributed to sample preparation from patients and healthy controls and performed the experiments. L.R., J.C.C., F.G and F.N. provided clinical samples and contributed to the interpretation of data. S.R., A.B., A.D. and L.L performed the statiscal analysis. A.B., E.C., A.D. and L.L wrote the first draft of the manuscript. L.R., A.B. A.H. and JM.G. together were responsible for the overall study design, supervised the project and take primary responsibility for writing the manuscript. DASA-PegIFN study investigators : Lydia Roy, Agnès Guerci-Bresler, Martine Escoffre-Barbe, Stéphane Giraudier, Aude Charbonnier, Viviane Dubruille, Françoise Huguet, Hyacinthe Johnson-Ansah, Pascal Lenain, Shanti Ame, Gabriel Etienne, Delphine Rea, Pascale Cony-Makhoul, Stéphane Courby, Jean-Christophe Ianotto, Laurence Legros, Antoine Machet, Valérie Coiteux, Eric Hermet, Francois-Xavier Mahon, Philippe Rousselot, Franck Nicolini, Emilie Cayssials, François Guilhot. Data availability The datasets generated and analysed during the current study are available from the corresponding author on reasonable request. Email: [email protected] Ethics approval The present work is a sub-study of the DASA-PegIFN study (EudraCT Number 2012-003389-42, ClinicalTrials.gov. NCT01872442) approved by the National Health regulatory authorities and ethical committee (Poitiers, France). This study is a prospective, nonrandomized phase 2 trial, conducted in 22 centers in France. Consent to participate All the participating patients provided their written informed consent for the clinical study and ancillary biological studies. References Han JJ (2023) Treatment-free remission after discontinuation of imatinib, dasatinib, and nilotinib in patients with chronic myeloid leukemia. 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Haematologica 108:1555–1566. https://doi.org/10.3324/haematol.2022.282005 Roy L, Chomel J-C, Guilhot J, et al (2015) Combination of Dasatinib and Peg-Interferon Alpha 2b in Chronic Phase Chronic Myeloid Leukemia (CP-CML) First Line: Preliminary Results of a Phase II Trial, from the French Intergroup of CML (Fi-LMC). Blood 126:134–134. https://doi.org/10.1182/blood.V126.23.134.134 Kreutzman A, Ilander M, Porkka K, et al (2014) Dasatinib promotes Th1-type responses in granzyme B expressing T-cells. Oncoimmunology 3:e28925. https://doi.org/10.4161/onci.28925 Wu KN, Wang YJ, He Y, et al (2014) Dasatinib promotes the potential of proliferation and antitumor responses of human γδT cells in a long-term induction ex vivo environment. Leukemia 28:206–210. https://doi.org/10.1038/leu.2013.221 Mustjoki S, Auvinen K, Kreutzman A, et al (2013) Rapid mobilization of cytotoxic lymphocytes induced by dasatinib therapy. Leukemia 27:914–924. https://doi.org/10.1038/leu.2012.348 Barbarin A, Abdallah M, Lefèvre L, et al (2020) Innate T-αβ lymphocytes as new immunological components of anti-tumoral “off-target” effects of the tyrosine kinase inhibitor dasatinib. Sci Rep 10:1–9. https://doi.org/10.1038/s41598-020-60195-z Supplementary Material Supplementary Table 1 and Supplementary Figures 1-6 are not available with this version. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7590855","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":518304422,"identity":"9c93aaae-3872-4ffb-91b9-3b2c9ebf1039","order_by":0,"name":"Emilie Cayssials","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Poitiers","correspondingAuthor":false,"prefix":"","firstName":"Emilie","middleName":"","lastName":"Cayssials","suffix":""},{"id":518304423,"identity":"acd359de-735a-4ce6-957e-0a1981bb6740","order_by":1,"name":"Lucie Lefèvre","email":"","orcid":"","institution":"IRMETIST","correspondingAuthor":false,"prefix":"","firstName":"Lucie","middleName":"","lastName":"Lefèvre","suffix":""},{"id":518304424,"identity":"ce0a258a-1b12-4ef0-81b4-294b4d4ab49d","order_by":2,"name":"Amandine Decroos","email":"","orcid":"","institution":"IRMETIST","correspondingAuthor":false,"prefix":"","firstName":"Amandine","middleName":"","lastName":"Decroos","suffix":""},{"id":518304425,"identity":"59f96049-c2a3-4f0e-a1a3-7853a482da57","order_by":3,"name":"Florence Jacomet","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Poitiers","correspondingAuthor":false,"prefix":"","firstName":"Florence","middleName":"","lastName":"Jacomet","suffix":""},{"id":518304426,"identity":"1ddc94f3-17be-4cad-b901-4ab300818c2d","order_by":4,"name":"Nathalie Piccirilli","email":"","orcid":"","institution":"CHU de Poitiers","correspondingAuthor":false,"prefix":"","firstName":"Nathalie","middleName":"","lastName":"Piccirilli","suffix":""},{"id":518304427,"identity":"4c1aa8a0-749d-453c-87f5-622ec37998cc","order_by":5,"name":"Florence Tartarin","email":"","orcid":"","institution":"INSERM CIC-1402","correspondingAuthor":false,"prefix":"","firstName":"Florence","middleName":"","lastName":"Tartarin","suffix":""},{"id":518304428,"identity":"c55fcc3d-4268-4896-80bd-681adb9249e3","order_by":6,"name":"François Guilhot","email":"","orcid":"","institution":"CHU de Poitiers","correspondingAuthor":false,"prefix":"","firstName":"François","middleName":"","lastName":"Guilhot","suffix":""},{"id":518304429,"identity":"68607e2a-cbc6-42b9-bfc6-aab46cff769b","order_by":7,"name":"Jean-Claude Chomel","email":"","orcid":"","institution":"CHU de Poitiers","correspondingAuthor":false,"prefix":"","firstName":"Jean-Claude","middleName":"","lastName":"Chomel","suffix":""},{"id":518304430,"identity":"f96de964-e967-4401-9c36-c0da29a67055","order_by":8,"name":"Philippe Rousselot","email":"","orcid":"","institution":"Centre Hospitalier de Versailles","correspondingAuthor":false,"prefix":"","firstName":"Philippe","middleName":"","lastName":"Rousselot","suffix":""},{"id":518304431,"identity":"f7582b30-42ba-4168-b948-ee1319eda96f","order_by":9,"name":"Franck E. 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08:13:06","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101893,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7590855/v1/8b1e86c3abc07ff06a0b9ba8.html"},{"id":92572674,"identity":"f4474849-0291-4922-a9eb-34973c31ac11","added_by":"auto","created_at":"2025-10-01 08:05:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103334,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInnate CD8 T-cells are enhanced after 3 months of CML therapy.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) C\u003c/strong\u003eytograms of one representative CML patient at diagnosis (Diag, upper) and at 3 months (M3, lower) are shown.\u003cstrong\u003e (B) \u003c/strong\u003eKinetics of innate CD8 T-cell frequencies in CML patients analyzed from diagnosis and up to 24 months of treatment (Diag: n=38; M3: n=34; M6: n=34; M12: n=33; M24: n=31). Data are expressed as mean ± SEM. Statistical analysis: Friedman-test (n=27), with Dunn’s multiple comparison test, for Dunn’s test comparing innate CD8 T-cells frequency at each time point to diagnosis. \u003cstrong\u003e(C)\u003c/strong\u003e Frequencies of innate CD8 T-cells (log2 scale) at diagnosis (Diag, n=34) and after 3 months of CML therapy (M3, n=34). Statistical analysis: Wilcoxon test.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7590855/v1/6f73274a009f865587cff357.png"},{"id":92572676,"identity":"811d6086-7b40-4ad5-999a-6a6d0b55d71c","added_by":"auto","created_at":"2025-10-01 08:05:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":75421,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHigh innate CD8 T-cell frequency at diagnosis and after three months of treatment is associated with DMR achievement.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Kinetics of innate CD8 T-cell frequencies in CML patients having achieved DMR (DMR, green line) or not (noDMR, red line) after 12 months of therapy. Patients were analyzed from diagnosis and up to 24 months of treatment (Diag: noDMR n=22; DMR n=16; M3: noDMR n=19; DMR n=15; M6: noDMR n=20; DMR n=14; M12: noDMR n=18; DMR n=15; M24: noDMR n=17; DMR n=14). Data are expressed as a curve of mean ± SEM. Statistical analysis: two-way ANOVA was performed with Šídák's multiple comparisons test comparing each time point between patients groups. (\u003cstrong\u003eB\u003c/strong\u003e) Frequencies of innate CD8 T-cells at diagnosis and after 3 months in patients having achieved DMR (DMR, left panel; Diag : n=15, M3: n=15) or not (noDMR, right panel; Diag : n=20, M3: n=20) after 12 months of therapy. Statistical analysis: Wilcoxon test.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7590855/v1/2d55a7116dafe275944dac0f.png"},{"id":92572679,"identity":"6a300805-ccad-49ee-9c55-cbea736228ab","added_by":"auto","created_at":"2025-10-01 08:05:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":153491,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHigh innate CD8 T-cell frequency in CML patients at diagnosis and after three months of treatment is associated with both achieved and sustained DMR.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA and B\u003c/strong\u003e) Cumulative incidence of the deep molecular response (DMR) over the first 24 months of therapy in patients with low (red line) or high (green line) innate CD8 T-cell frequency at diagnosis (\u003cstrong\u003eA\u003c/strong\u003e) or at 3 months (\u003cstrong\u003eB\u003c/strong\u003e). The number of subjects at risk is shown below the curves. The optimal cut-off values of innate CD8 T-cell frequency (5.50% at diagnosis and 6.43% at 3 months) were calculated using the Youden index. Data are expressed with Kaplan-Meier curves. Statistical analysis: Mantel-cox test. (\u003cstrong\u003eC\u003c/strong\u003e) Frequencies of innate CD8 T-cells at diagnosis (left panel) or at 3 months (right panel) in patients achieving a stable DMR over 2 years (DMR ≥2y; n=18) or not (DMR \u0026lt;2y ; n=16). Data are expressed as mean ± SD. Statistical analysis: comparison between group was done using unpaired Mann-Whitney test.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7590855/v1/216c9f81b9c65b93b19815c0.png"},{"id":98814371,"identity":"51e7b11e-9b82-4d52-93b4-c645a18473b0","added_by":"auto","created_at":"2025-12-22 16:12:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1289822,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7590855/v1/69a93b96-0665-44c1-95fd-39f00b8bce37.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Innate CD8 T-cells as a potential predictive biomarker for deep molecular response in chronic myeloid leukemia patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSince the advent of tyrosine kinase inhibitors (TKIs), chronic myeloid leukemia (CML) has become a chronic disease with life expectancy comparable to that of unaffected individuals. Following treatment by TKI, 5-year probability of achieving a deep molecular response (DMR) ranges from 38% to 64%[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Second-generation TKIs (nilotinib, dasatinib and bosutinib) have been associated with an earlier and higher rate of patients experiencing DMR. Achieving a sustained DMR represents the most recent goal in CML treatment, both to prevent disease progression and to allow an attempt at TKI discontinuation (Hochhaus et al., Leukemia 2020).\u003c/p\u003e\u003cp\u003eAlthough the immune abnormalities reported in CML-chronic phase (CP) patients at diagnosis are partially corrected after TKI therapy, only a few studies have focused on immunological prognosis factors impacting the depth of the response, which heretofore include NK cells (or NK cell-related markers such as killer-cell immunoglobulin-like receptors (KIR)) and Vδ2 γδ T-cells[\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e–\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Considering the main conventional anti-tumoral effector compartment, namely conventional cytotoxic CD8 T-cells, to date no relationship has been established between prognosis and treatment success.\u003c/p\u003e\u003cp\u003eWe recently identified a new subset of CD8 T-cells sharing properties with conventional memory CD8 T-cells, and exhibiting NK-like features. This CD8 T-cell subset is characterized by CD8 expression along with a classical TCRαβ, NK receptors (panKIR/NKG2A), an EMRA (effector memory cells re-expressing CD45RA) phenotype (CD45RA\u003csup\u003e+\u003c/sup\u003e, CCR7\u003csup\u003e−\u003c/sup\u003e) and high Eomesodermin (Eomes) expression[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Innate CD8 T-cells hold high anti-tumoral potential, as evidenced by their prompt IFN-γ production in response to innate-like co-stimulation by IL-12 and IL-18[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Our previous work has shown that peripheral blood innate CD8 T-cells (CD8\u003csup\u003e+\u003c/sup\u003e TCR-αβ\u003csup\u003e+\u003c/sup\u003e Eomes\u003csup\u003e+\u003c/sup\u003e panKIR/NKG2A\u003csup\u003e+\u003c/sup\u003e) are drastically reduced and functionally deficient in CML patients at diagnosis[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Moreover, innate CD8 T-cell deficiencies at CML diagnosis have been found to be partially reversed in stable complete cytogenetic remission\u003csup\u003e8\u003c/sup\u003e and major molecular response (MMR) patients on TKI treatment[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], highlighting this CD8 T-cell subset as a new potential effector controlling CML. Consistent with this notion, we demonstrated that innate CD8 T-cells are markedly increased in patients in sustained TFR as compared to patients in MMR under TKI therapy, and even to healthy donors[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Finally, in a previous prospective study comparing patients in TFR \u003cem\u003eversus\u003c/em\u003e in molecular relapse (MR) after TKI cessation, we have shown that innate CD8 T-cells, in combination with NK cells, may be a predictive marker for TFR success in CML treatment[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the present study, we hypothesized that innate CD8 T-cells are closely associated with the achievement of DMR under TKI therapy. To test this assumption, we prospectively and longitudinally analyzed a cohort of 38 CP-CML (chronic phase of CML) patients treated first-line with dasatinib for three months and subsequently in combination with small doses of IFN-α[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This protocol aimed to achieve high rates of early and sustained DMR, hence offering the possibility to investigate biological markers linked to DMR achievement at one year and/or DMR stability over two years in the same cohort over time.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003e1. Patient and healthy donor characteristics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe present work is a sub-study of the DASA-PegIFN study (EudraCT Number 2012-003389-42, ClinicalTrials.gov. NCT01872442) approved by the National Health regulatory authorities and ethical committee (Poitiers, France). This study is a prospective, nonrandomized phase 2 trial, conducted in 22 centers in France. All the participating patients provided their written informed consent for the clinical study and ancillary biological studies.\u003c/p\u003e\u003cp\u003eBriefly, newly diagnosed Ph\u003csup\u003e+\u003c/sup\u003e CP-CML patients were treated with first-line dasatinib at 100 mg/day. At month 3, Peg-Interferon-alpha-2b (PegIntron®, Merck KGaA, Darmstadt, Germany) was initiated at 30 µg/week subcutaneously for eligible patients (in the absence of significant cytopenia or extra hematological adverse event greater than grade 2 with dasatinib alone for the 3 first months) and for a maximum duration of 21 months. The results of this trial and protocol have been reported[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. During the trial, peripheral blood was collected on heparin at several time points: at diagnosis, and at 3, 6, 12 and 24 months after initiation of treatment. Among the 61 patients eligible for the dasatinib + Peg-IFNα2b therapy from month 3, we analyzed samples from 40 consecutive patients for whom at least four time points were available. Two of them were excluded for technical issues. Patient responses to treatment were classified as conforming to 2013 ELN criteria. Major molecular response (MMR) was defined as a ratio of \u003cem\u003eBCR::ABL1\u003c/em\u003e/\u003cem\u003eABL1\u003c/em\u003e\u003csup\u003eIS\u003c/sup\u003e ≤ 0.1% on the international scale (IS). A ratio of \u003cem\u003eBCR::ABL1\u003c/em\u003e/\u003cem\u003eABL1\u003c/em\u003e\u003csup\u003eIS\u003c/sup\u003e ≤ 0.01% defines a deep molecular response (DMR). Patients were separated into two groups according to whether or not (noDMR) they achieved DMR at 12 months (DMR) (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for the whole cohort and group patient’s characteristics).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAll\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eDMR at 12 months *\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(n = 38)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003enoDMR\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eDMR\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(n = 22)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(n = 16)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45 ± 12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 ± 12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 ± 12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (39%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (56%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (44%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSokal score, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow (\u0026lt; 0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (88%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInt/high (≥ 0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (12%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eELTS score, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntermediate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e*DMR: deep molecular response (\u003cem\u003eBCR::ABL1/ABL1\u003c/em\u003e\u003csup\u003eIS\u003c/sup\u003e ≤ 0.01%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eFrozen peripheral blood mononuclear cells (PBMC) from 21 healthy donors (HD) (median age 28 years, range: 22–65, sex ratio: 0.5) were obtained from the French Blood Institute (Etablissement Français du Sang, Lyon, France).\u003c/p\u003e\u003cp\u003e\u003cb\u003e2. PBMC isolation and cryopreservation\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePBMCs were isolated from blood samples by density gradient centrifugation (Histopaque®-1077, Sigma-Aldrich, St Louis, MO, USA), resuspended in 90% Fetal Bovine Serum (10270106, Gibco®, Thermo Fisher Scientific, Waltham, MA, USA) with 10% DMSO (D2650, Sigma-Aldrich), and cryopreserved at -80°C or in liquid nitrogen until use.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3. Flow cytometry\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePhenotypic analysis of cells from HD and CML patients was performed using \u003cem\u003eex vivo\u003c/em\u003e flow cytometry. All monoclonal antibodies (mAbs) used in this study are listed in \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e. Expression of the different markers was assessed by staining PBMC with appropriate combinations of mAbs. PanKIR/NKG2A referred to staining with a mixture of the following three antibodies from Miltenyi Biotec (Bergisch Gladbach, Germany) KIR2D, KIR3DL1/KIR3DL2 (CD158e/k) and NKG2A (CD159a). Dead cells were excluded using the Live/Dead® Fixable NearIR Dead Cell Stain kit (L10119, Invitrogen™, Thermo Fisher Scientific). For intranuclear Eomes staining, cells were permeabilized using an anti-human Foxp3 staining kit according to the manufacturer’s protocol (73-5776-40, eBioscience™, Thermo Fisher Scientific). Flow data were acquired on a FACSVerse flow cytometer (Becton, Dickinson \u0026amp; Company, Franklin Lakes, NJ, US) with FACSuite™ software (Becton, Dickinson \u0026amp; Company) and analyzed using FlowJo™ v10 (Becton, Dickinson \u0026amp; Company). A detailed gating strategy is presented in \u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e. Results are expressed as frequencies or as mean fluorescence intensity (MFI).\u003c/p\u003e\u003cp\u003e\u003cb\u003e3. Statistical analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll statistical data analyses were performed using GraphPad Prism v7.0 (GraphPad Software, Inc). Friedman’s test with Dunn’s multiple comparison test and Mann-Whitney two-tailed test were used for unpaired data analysis. Two-way ANOVA with Šídák's multiple comparison and Wilcoxon tests were used for paired data. A p value \u0026lt; 0.05 was considered significant (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001). Receiver operating characteristic (ROC) curves were built using the logarithm of innate CD8 T-cell frequency after three months of therapy or at diagnosis. The Youden index was used to determine the cut-off of innate CD8 T-cell frequency. Cumulative incidence was presented as Kaplan-Meier curves. Significant differences between curves were analyzed using a log-rank test statistical analysis.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eThe first three months of treatment are associated with increased innate CD8 T-cell frequency\u003c/h2\u003e\n \u003cp\u003eWe analyzed peripheral blood innate CD8 T-cells (defined as Eomes\u003csup\u003e+\u003c/sup\u003e panKIR/NKG2A\u003csup\u003e+\u003c/sup\u003e cells among TCR-\u0026alpha;\u0026beta;\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003e+\u003c/sup\u003e cells) by flow cytometry at multiple time points from diagnosis up to 24 months of therapy in 38 CML patients participating in the phase II DASA-PegIFN clinical trial (see Methods and Table 1\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n \u003cp\u003eFigure 1A shows a two-fold increase in the percentage of innate CD8 T-cells at the three-month (M3) treatment stage (dasatinib alone, PegIFN not yet initiated) as compared to diagnosis in a representative patient. Considering the entire cohort, we found a significant increase in the frequency of innate CD8 T-cells (5.98\u0026thinsp;\u0026plusmn;\u0026thinsp;5.43% \u003cem\u003evs.\u003c/em\u003e 3.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.39%, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), as compared to diagnosis (Fig. 1B, M3 \u003cem\u003evs\u003c/em\u003e. diagnosis). After M3, we observed a decline in the percentage of CD8 T-cells (rapid between M3 and M6, and slower thereafter). However, it is worth noting that this rate remains higher than at the time of diagnosis. When individual patients were examined, higher levels of innate CD8 T-cells were observed at M3 in 79% of them (Fig. 1C). In accordance with our previous observation in another independent cohort of CML patients[9], we confirmed the specific quantitative deficiency of innate CD8 T-cells at diagnosis as compared to the healthy donor (HD) group (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;2\u003c/strong\u003e). Early effects of TKI therapy on the pool of CD8 T-cells were not restricted to innate CD8 T-cells, as in 82% of patients conventional-memory CD8 T-cell (defined as Eomes\u003csup\u003e+\u003c/sup\u003e panKIR/NKG2A\u003csup\u003e\u0026minus;\u003c/sup\u003e) frequency concomitantly increased, whereas na\u0026iuml;ve CD8 T-cell (defined as Eomes\u003csup\u003e\u0026minus;\u003c/sup\u003e panKIR/NKG2A\u003csup\u003e\u0026minus;\u003c/sup\u003e) frequency decreased after three months of therapy (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;3\u003c/strong\u003e), as previously described[13].\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eInnate CD8 T-cell frequency at M3 selectively predicts DMR achievement at 12 months\u003c/h3\u003e\n\u003cp\u003eWe then searched for a potential relationship between the frequency of innate CD8 T-cells and the achievement of a deep molecular response (DMR) at 12 months. Taking the entire kinetics into account, we evidenced that DMR patients had significantly higher innate CD8 T-cell frequencies throughout the 24 months of therapy compared to the noDMR group (Fig. 2A\u003cstrong\u003e).\u003c/strong\u003e Remarkably, the increased frequency of innate CD8 T-cells after three months of therapy, in comparison to diagnosis, was more pronounced in the DMR group than in the noDMR group (Fig. 2B). This phenomenon was specific to innate CD8 T-cells, as conventional-memory CD8 T-cell frequency did not differ between the two groups at diagnosis and at M3 (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;4\u003c/strong\u003e). One explanation could be a shift within the CD8 T-cell pool in favor of innate CD8 T-cells at the expense of the na\u0026iuml;ve T-cell pool, as suggested by the lower frequency of na\u0026iuml;ve CD8 T-cells observed concomitantly at M3 (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;4\u003c/strong\u003e). Furthermore, we observed that innate CD8 T-cell frequency at diagnosis tended to be higher in the DMR group than in the no-DMR group (p-value: 0.0511, Mann-Whitney test, data not shown).\u003c/p\u003e\n\u003cp\u003eThese results provide evidence that innate CD8 T-cell frequency at three months of dasatinib therapy may be a predictive marker for DMR achievement (evaluated at 12 months).\u003c/p\u003e\n\u003ch3\u003eInnate CD8 T-cell frequency as an indicator of DMR achievement and its durability\u003c/h3\u003e\n\u003cp\u003eROC curves were built to determine a cut-off value for innate CD8 T-cell frequency at M3 (p-value: 0.0044), and to establish whether this parameter could be used as a biomarker (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;5\u003c/strong\u003e). The analysis showed that the cut-off value for innate CD8 T-cell frequency was 6.43% at M3. Then, we determined the cumulative incidence of DMR over the first 24 months of therapy in patients with low \u003cem\u003eversus\u003c/em\u003e high innate CD8 T-cell frequencies at M3 (Fig. 3B). DMR achievement occurred significantly earlier and at higher rates in patients with high innate CD8 T-cell frequency at M3. Patients with low innate CD8 T-cell frequency (n\u0026thinsp;=\u0026thinsp;25) exhibited slow kinetics of DMR obtention that never reached the rate of patients with high innate CD8 T-cell frequency (n\u0026thinsp;=\u0026thinsp;13): 51.30% during the 24 months of treatment compared to 32.47%. (Fig. 3B). These data supports the conclusion that high innate CD8 T-cell frequency in peripheral blood after three months of therapy may be an indicator of early DMR achievement. Of note, by applying the same approach based on the frequency of innate CD8 T-cells at diagnosis (Fig. 3A), we observed that 70.94% of patients with \u0026gt;\u0026thinsp;5.5% of innate CD8 T-cells at diagnosis achieved DMR in 21 months of treatment and that only 25.34% of the CML patients with \u0026le;\u0026thinsp;5.5% of innate CD8 T-cells reached DMR in two years. Consequently, innate CD8 T-cell frequency at diagnosis may also predicts DMR achievement.\u003c/p\u003e\n\u003cp\u003eAlongside DMR achievement, its stability over time (\u0026ge;\u0026thinsp;2 years) is a crucial criterion for CML patients to be eligible for treatment discontinuation[14]. In the DasaPeg IFN trial, with median follow-up of 54.1 months (range 30.6\u0026ndash;69.1), 46% of patients achieved a 2-year sustained DMR[12]. To test whether innate CD8 T-cell frequency was associated with treatment response stability, we separated patients with stable DMR for more than two years (n\u0026thinsp;=\u0026thinsp;18) from patients without stable DMR (n\u0026thinsp;=\u0026thinsp;16). Remarkably, innate CD8 T-cell frequency after three months of therapy was significantly higher in patients with a stable DMR for more than two years than in patients without a stable DMR (Fig. 3C). The same conclusion could be applied when considering the frequency of innate CD8 T-cells at CML diagnosis (Fig. 3C\u003cstrong\u003e)\u003c/strong\u003e, thereby reinforcing the notion that the status of innate CD8 T-cells is closely associated with a stable DMR in CML patients. Finally, this effect was specific to the innate CD8 T-cell compartment, as conventional-memory and na\u0026iuml;ve CD8 T-cell frequencies were similar between the two groups regardless of the time point (at diagnosis or after three months of therapy) (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;6\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTaken together, our results demonstrate that innate CD8 T-cell frequency at M3 is associated with an early, deep and, stable response to CML therapy. Moreover, this phenomenon may be partially related to the status of this distinct CD8 T-cell compartment at the time of CML diagnosis.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eA sustained DMR has become a goal in efforts to strengthen CML stability and is a prerequisite for attempts at TKI cessation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Recent data in the literature highlight the potential contribution of immune effectors such as NK cells and γδ T-cells in clinical responses to TKI therapy[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], including achievement of DMR[\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Here, we focused on new effector CD8 T-cells, specifically innate CD8 T-cells, which consist of unconventional T-cells with innate-like responses. We provided evidence for their close association with the achievement of sustained DMR in a prospective longitudinal study in the DASA-PegIFN clinical trial[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWe have previously reported deficiencies of innate CD8 T-cells at CML diagnosis that were at least partially corrected in patients having achieved complete cytogenetic remission and MMR following TKI therapy[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Here, to reach definitive conclusions on the involvement of innate CD8 T-cells in CML control, we conducted a prospective monitoring from CML diagnosis and through 24 months of treatment. To date, very few immunological longitudinal studies have been carried out[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], particularly taking the patient\u0026rsquo;s initial immune status into account.\u003c/p\u003e\u003cp\u003eIn this work, we observed an increased frequency of innate CD8 T-cells in most patients (79%) as early as the third month of treatment, i.e. during the initial treatment phase with dasatinib alone. Mechanistically, dasatinib has been described to have immune-mediated effects[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], in particular on T-cells. It could act either by driving the proliferation of innate CD8 T-cells or by increasing their number through differentiation from their conventional CD8 T-cell counterparts.\u003c/p\u003e\u003cp\u003eConsistent with the latter hypothesis, we have previously shown in a murine model of dasatinib oral gavage that this TKI induced a drastic decrease of thymic memory CD8 T-cells with a shift toward innate CD8 T-cells[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In the present study, we demonstrated that the increased proportion of innate CD8 T-cell compartments is concomitant with increased conventional CD8 memory T-cell frequency, and is also closely associated with decreased frequency of na\u0026iuml;ve CD8 T-cells, suggesting a shift from na\u0026iuml;ve to memory T-cells. These results are also congruent with a previous study[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], which demonstrated significant phenotypic changes in immune effector CD8 T-cells towards an EMRA phenotype after three months of treatment with dasatinib. Indeed, we previously showed that the innate CD8 T-cell compartment is primarily composed of memory cells exhibiting an EMRA phenotype and preferentially expressing the surface molecule CD57, a terminal differentiation marker[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFollowing the M3 frequency peak, we observed a decrease in the frequency of innate CD8 T-cells in the whole cohort. This observation is consistent with the decrease of EMRA CD8 T-cells reported by Huuhtanen \u003cem\u003eet al.\u003c/em\u003e, after administration of IFN-α in combination with dasatinib[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. They demonstrated that IFN-α broadens the immune repertoire and increases the number of costimulatory intercellular interactions, highlighting the positive immunomodulatory effects of IFN-α. However, in their clinical trial, as in ours, no patients without IFN-α treatment were included, therefore no definitive conclusions can be drawn about the impact of IFN-α.\u003c/p\u003e\u003cp\u003e As expected, a high proportion of DMR (42%) was obtained at 12 months in our dasaPEG trial. This allowed us to compare the frequency of innate CD8 T-cells between patients achieving DMR at 12 months (DMR, n\u0026thinsp;=\u0026thinsp;16) and those who did not (noDMR, n\u0026thinsp;=\u0026thinsp;22). Remarkably, although an increased proportion of innate CD8 T-cells was observed in both DMR and noDMR groups between diagnosis and the third month of dasatinib treatment, frequency of these cells measured at three months was significantly higher in the DMR group. Moreover, the higher level of innate CD8 T-cell frequency in DMR patients was maintained during the following 12 months (after 24 months of treatment). On the other hand, conventional memory T-cells did not discriminate between DMR and no-DMR patient groups, indicating that innate CD8 T-cells are specifically associated with DMR achievement. Finally, the high proportion of innate CD8 T-cells at M3 was associated with sustained DMR at 2-years, suggesting that innate CD8 T-cells influence not only the speed and rate of reaching DMR, but also its durability.\u003c/p\u003e\u003cp\u003eAnother important aspect revealed by our study concerns the potential role of the patient's immune system state at the time of diagnosis in determining the efficacy of treatment response. Indeed, despite a quantitative deficit in innate CD8 T-cells, at the time of diagnosis, their proportion tends to be higher in patients who achieve/sustain DMR than in those who do not. These data allow us to propose a scenario in which the more innate CD8 T-cells are represented at the time of diagnosis, the more efficiently they will be amplified by dasatinib so as to achieve stable DMR.\u003c/p\u003e\u003cp\u003eAll in all, our data lead us to suggest that innate CD8 T-cell frequency may be a predictive immune marker of the achievement of stable DMR in CML patients. Of note, this hypothseis was obtained despite our small number of patients and the homogeneous nature of our cohort (low risk of progression based on Sokal and ELTS scores). Another limitation is that we only analyzed the numerical level of innate CD8 T-cells, without studying their antitumor functions, especially those of the innate type. Therefore, further studies focusing on innate CD8 T-cells, including an analysis of their innate-associated transcription factors, effector markers (perforin, granzyme B) and immune checkpoints, may be useful to identify a full DMR immune signature. More generally, given the patients\u0026rsquo; immune and clinical status, our study requires confirmation using large longitudinal cohorts, including patients treated not only with dasatinib but also with all other TKIs available for first-line treatment (imatinib, nilotinib, bosutinib).\u003c/p\u003e\u003cp\u003eIn CML, biomarkers are now needed to predict both the achievement of stable DMR and the success of treatment discontinuation. In this respect, a new paradigm would assume that innate CD8 T-cells can serve as a longitudinal predictive marker from diagnosis until eligibility for treatment discontinuation. By providing evidence that an individual\u0026rsquo;s innate CD8 T-cell immune profile as early as diagnosis may be a predictive marker of stable DMR, our data support this assumption.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are especially indebted to Jeffrey Arsham for editing the English of our manuscript. We thank Julie Paul from the CIC-1402 for her help with statistical analysis. We thank the ImageUP (Universit\u0026eacute; de Poitiers) flow cytometry core facilities, and Centre de Ressources Biologiques (CRB, CHU de Poitiers). This study was supported by INSERM, CHU de Poitiers, Universit\u0026eacute; de Poitiers, Fi-LMC (France intergroupe des Leucemies My\u0026eacute;loides Chroniques), Association Laurette Fugain (ALF 2015_10), Ligue contre le Cancer du Grand Ouest (Comit\u0026eacute;s d\u0026eacute;partementaux de la Vienne, de la Charente, de la Charente Maritime et des Deux-S\u0026egrave;vres), Association pour la Recherche en Immunologie-Poitou-Charentes (ARIM-PC), le Canc\u0026eacute;rop\u0026ocirc;le Grand Sud-Ouest et le Groupement Interr\u0026eacute;gional de Recherche Clinique et d\u0026rsquo;Innovation Sud-Ouest Outre-Mer (API-K 2017), and INCa-DGOS 8658 (PRT-K 2015-052). A.B. and E.C. were supported by fellowships provided by Fondation Brystol-Meyers Squibb and R\u0026eacute;gion Nouvelle Aquitaine, and Sport \u0026amp; Collection, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by INSERM, CHU de Poitiers, Universit\u0026eacute; de Poitiers, Fi-LMC (France intergroupe des Leucemies My\u0026eacute;loides Chroniques), Association Laurette Fugain (ALF 2015_10), Ligue contre le Cancer du Grand Ouest (Comit\u0026eacute;s d\u0026eacute;partementaux de la Vienne, de la Charente, de la Charente Maritime et des Deux-S\u0026egrave;vres), Association pour la Recherche en Immunologie-Poitou-Charentes (ARIM-PC), le Canc\u0026eacute;rop\u0026ocirc;le Grand Sud-Ouest et le Groupement Interr\u0026eacute;gional de Recherche Clinique et d\u0026rsquo;Innovation Sud-Ouest Outre-Mer (API-K 2017), and INCa-DGOS 8658 (PRT-K 2015-052).\u0026nbsp;A.B. and E.C. were supported by fellowships provided by Fondation Brystol-Meyers Squibb and R\u0026eacute;gion Nouvelle Aquitaine, and\u0026nbsp;Sport \u0026amp; Collection, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicting financial interestsin in relation to the work described.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.B., L.L., E.C., A.D. and F.J. designed the experiments, performed the experiments, analyzed and interpreted the data. N.P. contributed to sample preparation from patients and healthy controls and performed the experiments. L.R., J.C.C., F.G and F.N. provided clinical samples and contributed to the interpretation of data. S.R., A.B., A.D. and L.L performed the statiscal analysis. A.B., E.C., A.D. and L.L wrote the first draft of the manuscript. L.R., A.B. A.H. and JM.G. together were responsible for the overall study design, supervised the project and take primary responsibility for writing the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDASA-PegIFN study investigators :\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLydia Roy, Agn\u0026egrave;s Guerci-Bresler, Martine Escoffre-Barbe, St\u0026eacute;phane Giraudier, Aude Charbonnier, Viviane Dubruille, Fran\u0026ccedil;oise Huguet, Hyacinthe Johnson-Ansah, Pascal Lenain, Shanti Ame, Gabriel Etienne, Delphine Rea, Pascale Cony-Makhoul, St\u0026eacute;phane Courby, Jean-Christophe Ianotto, Laurence Legros, Antoine Machet, Val\u0026eacute;rie Coiteux, Eric Hermet, Francois-Xavier Mahon,\u003csup\u003e\u0026nbsp;\u003c/sup\u003ePhilippe Rousselot, Franck Nicolini, Emilie Cayssials, Fran\u0026ccedil;ois Guilhot.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are available from the corresponding author on reasonable request. Email: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present work is a sub-study of the DASA-PegIFN study (EudraCT Number 2012-003389-42, ClinicalTrials.gov. NCT01872442) approved by the National Health regulatory authorities and ethical committee (Poitiers, France). This study is a prospective, nonrandomized phase 2 trial, conducted in 22 centers in France.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the participating patients provided their written informed consent for the clinical study and ancillary biological studies.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHan JJ (2023) Treatment-free remission after discontinuation of imatinib, dasatinib, and nilotinib in patients with chronic myeloid leukemia. Blood Res 58:S58\u0026ndash;S65. https://doi.org/10.5045/br.2023.2023035\u003c/li\u003e\n\u003cli\u003eKreutzman A, Jaatinen T, Greco D, et al (2012) Killer-cell immunoglobulin-like receptor gene profile predicts good molecular response to dasatinib therapy in chronic myeloid leukemia. Exp Hematol 40:906-913.e1. https://doi.org/10.1016/j.exphem.2012.07.007\u003c/li\u003e\n\u003cli\u003eUreshino H, Shindo T, Kojima H, et al (2018) Allelic Polymorphisms of KIRs and HLAs Predict Favorable Responses to Tyrosine Kinase Inhibitors in CML. Cancer Immunol Res 6:745\u0026ndash;754. https://doi.org/10.1158/2326-6066.CIR-17-0462\u003c/li\u003e\n\u003cli\u003eHughes A, Clarson J, Tang C, et al (2017) CML patients with deep molecular responses to TKI have restored immune effectors and decreased PD-1 and immune suppressors. Blood 129:1166\u0026ndash;1176. https://doi.org/10.1182/blood-2016-10-745992\u003c/li\u003e\n\u003cli\u003eBr\u0026uuml;ck O, Blom S, Dufva O, et al (2018) Immune cell contexture in the bone marrow tumor microenvironment impacts therapy response in CML. Leukemia 32:1643\u0026ndash;1656. https://doi.org/10.1038/s41375-018-0175-0\u003c/li\u003e\n\u003cli\u003eChang Y-C, Chiang Y-H, Hsu K, et al (2021) Activated na\u0026iuml;ve \u0026gamma;\u0026delta; T cells accelerate deep molecular response to BCR-ABL inhibitors in patients with chronic myeloid leukemia. Blood Cancer J 11:182. https://doi.org/10.1038/s41408-021-00572-7\u003c/li\u003e\n\u003cli\u003eJacomet F, Cayssials E, Basbous S, et al (2015) Evidence for eomesodermin-expressing innate-like CD8(+) KIR/NKG2A(+) T cells in human adults and cord blood samples. Eur J Immunol 45:1926\u0026ndash;1933. https://doi.org/10.1002/eji.201545539\u003c/li\u003e\n\u003cli\u003eBarbarin A, Cayssials E, Jacomet F, et al (2017) Phenotype of NK-Like CD8(+) T Cells with Innate Features in Humans and Their Relevance in Cancer Diseases. Front Immunol 8:316. https://doi.org/10.3389/fimmu.2017.00316\u003c/li\u003e\n\u003cli\u003eJacomet F, Cayssials E, Barbarin A, et al (2017) The Hypothesis of the Human iNKT/Innate CD8(+) T-Cell Axis Applied to Cancer: Evidence for a Deficiency in Chronic Myeloid Leukemia. Front Immunol 7:688. https://doi.org/10.3389/fimmu.2016.00688\u003c/li\u003e\n\u003cli\u003eCayssials E, Jacomet F, Piccirilli N, et al (2019) Sustained treatment-free remission in chronic myeloid leukaemia is associated with an increased frequency of innate CD8(+) T-cells. Br J Haematol 186:54\u0026ndash;59. https://doi.org/10.1111/bjh.15858\u003c/li\u003e\n\u003cli\u003eDecroos A, Meddour S, Demoy M, et al (2024) The CML experience to elucidate the role of innate T-cells as effectors in the control of residual cancer cells and as potential targets for cancer therapy. Front Immunol 15:1473139. https://doi.org/10.3389/fimmu.2024.1473139\u003c/li\u003e\n\u003cli\u003eRoy L, Chomel J-C, Guilhot J, et al (2023) Dasatinib plus Peg-Interferon alpha 2b combination in newly diagnosed chronic phase chronic myeloid leukaemia: Results of a multicenter phase 2 study (DASA-PegIFN study). Br J Haematol 200:175\u0026ndash;186. https://doi.org/10.1111/bjh.18486\u003c/li\u003e\n\u003cli\u003eHuuhtanen J, Ilander M, Yadav B, et al (2022) IFN-\u0026alpha; with dasatinib broadens the immune repertoire in patients with chronic-phase chronic myeloid leukemia. J Clin Invest 132:e152585. https://doi.org/10.1172/JCI152585\u003c/li\u003e\n\u003cli\u003eSaussele S, Richter J, Guilhot J, et al (2018) Discontinuation of tyrosine kinase inhibitor therapy in chronic myeloid leukaemia (EURO-SKI): a prespecified interim analysis of a prospective, multicentre, non-randomised, trial. Lancet Oncol 19:747\u0026ndash;757. https://doi.org/10.1016/S1470-2045(18)30192-X\u003c/li\u003e\n\u003cli\u003eHochhaus A, Baccarani M, Silver RT, et al (2020) European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia 34:966\u0026ndash;984. https://doi.org/10.1038/s41375-020-0776-2\u003c/li\u003e\n\u003cli\u003eMustjoki S, Ekblom M, Arstila TP, et al (2009) Clonal expansion of T/NK-cells during tyrosine kinase inhibitor dasatinib therapy. Leukemia 23:1398\u0026ndash;1405. https://doi.org/10.1038/leu.2009.46\u003c/li\u003e\n\u003cli\u003eIriyama N, Fujisawa S, Yoshida C, et al (2015) Early cytotoxic lymphocyte expansion contributes to a deep molecular response to dasatinib in patients with newly diagnosed chronic myeloid leukemia in the chronic phase: results of the D-first study. Am J Hematol 90:819\u0026ndash;824. https://doi.org/10.1002/ajh.24096\u003c/li\u003e\n\u003cli\u003eKnight A, Mackinnon S, Lowdell MW (2012) Human Vdelta1 gamma-delta T cells exert potent specific cytotoxicity against primary multiple myeloma cells. Cytotherapy 14:1110\u0026ndash;1118. https://doi.org/10.3109/14653249.2012.700766\u003c/li\u003e\n\u003cli\u003eHarrington P, Dillon R, Radia D, et al (2023) Differential inhibition of T-cell receptor and STAT5 signaling pathways determines the immunomodulatory effects of dasatinib in chronic phase chronic myeloid leukemia. Haematologica 108:1555\u0026ndash;1566. https://doi.org/10.3324/haematol.2022.282005\u003c/li\u003e\n\u003cli\u003eRoy L, Chomel J-C, Guilhot J, et al (2015) Combination of Dasatinib and Peg-Interferon Alpha 2b in Chronic Phase Chronic Myeloid Leukemia (CP-CML) First Line: Preliminary Results of a Phase II Trial, from the French Intergroup of CML (Fi-LMC). Blood 126:134\u0026ndash;134. https://doi.org/10.1182/blood.V126.23.134.134\u003c/li\u003e\n\u003cli\u003eKreutzman A, Ilander M, Porkka K, et al (2014) Dasatinib promotes Th1-type responses in granzyme B expressing T-cells. Oncoimmunology 3:e28925. https://doi.org/10.4161/onci.28925\u003c/li\u003e\n\u003cli\u003eWu KN, Wang YJ, He Y, et al (2014) Dasatinib promotes the potential of proliferation and antitumor responses of human \u0026gamma;\u0026delta;T cells in a long-term induction ex vivo environment. Leukemia 28:206\u0026ndash;210. https://doi.org/10.1038/leu.2013.221\u003c/li\u003e\n\u003cli\u003eMustjoki S, Auvinen K, Kreutzman A, et al (2013) Rapid mobilization of cytotoxic lymphocytes induced by dasatinib therapy. Leukemia 27:914\u0026ndash;924. https://doi.org/10.1038/leu.2012.348\u003c/li\u003e\n\u003cli\u003eBarbarin A, Abdallah M, Lef\u0026egrave;vre L, et al (2020) Innate T-\u0026alpha;\u0026beta; lymphocytes as new immunological components of anti-tumoral \u0026ldquo;off-target\u0026rdquo; effects of the tyrosine kinase inhibitor dasatinib. Sci Rep 10:1\u0026ndash;9. https://doi.org/10.1038/s41598-020-60195-z\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Supplementary Material","content":"\u003cp\u003eSupplementary Table 1 and Supplementary Figures 1-6 are not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cancer-immunology-immunotherapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ciim","sideBox":"Learn more about [Cancer Immunology, Immunotherapy](http://link.springer.com/journal/262)","snPcode":"262","submissionUrl":"https://submission.nature.com/new-submission/262/3","title":"Cancer Immunology, Immunotherapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Chronic myeloid leukemia, deep molecular response, immune biomarker, innate CD8 T-cell","lastPublishedDoi":"10.21203/rs.3.rs-7590855/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7590855/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn chronic myeloid leukemia (CML), the role of immune effectors has been suggested in the achievement of a sustained deep molecular response (DMR) and treatment-free remission (TFR) after tyrosine kinase inhibitor (TKI) discontinuation. A contributory role of the distinct new innate CD8 T-cell pool in control of CML residual disease after TKI cessation was recently highlighted. Here, we evaluated longitudinally whether innate CD8 T-cells predict CML therapy success in a cohort of newly diagnosed CML patients treated in the DasaPegIFN clinical trial. After 3 months of treatment (M3), we observed a significant increase of innate CD8 T-cell frequency as compared to diagnosis, together with an early shift within the pool of CD8 T-cells towards an innate/memory phenotype. We also found that patients with high innate CD8 T-cell frequency at M3 achieved DMR earlier and at higher rates than patients with low innate CD8 T-cell frequency. Remarkably, this signature pre-existed at the time of diagnosis, suggesting the possible role of the patient\u0026rsquo;s initial individual immune status. High innate CD8 T-cell frequency was also associated with maintaining DMR stability for 2 years. Taken together, our findings highlight innate CD8 T-cells as a potential marker for CML therapy success and TFR eligibility.\u003c/p\u003e","manuscriptTitle":"Innate CD8 T-cells as a potential predictive biomarker for deep molecular response in chronic myeloid leukemia patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-01 08:05:01","doi":"10.21203/rs.3.rs-7590855/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-13T13:59:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-08T17:22:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-08T08:28:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-03T00:33:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-01T09:06:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-21T16:22:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-20T13:20:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"277827460809250493738201213198390384140","date":"2025-09-19T20:45:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-18T09:08:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272494606627166395052423682105136604957","date":"2025-09-18T07:53:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73923391714651982694919730344907980019","date":"2025-09-18T07:18:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283030525732908052901157094434319094373","date":"2025-09-18T05:17:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296532933642470655352948006517935710980","date":"2025-09-18T02:10:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175964619157565704644208643420439932502","date":"2025-09-18T00:23:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1028859964869259012145966468028729280","date":"2025-09-17T21:33:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196468513961589078114617354166914848102","date":"2025-09-17T21:18:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-17T20:41:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-16T10:00:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-16T09:59:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cancer Immunology, Immunotherapy","date":"2025-09-11T10:25:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cancer-immunology-immunotherapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ciim","sideBox":"Learn more about [Cancer Immunology, Immunotherapy](http://link.springer.com/journal/262)","snPcode":"262","submissionUrl":"https://submission.nature.com/new-submission/262/3","title":"Cancer Immunology, Immunotherapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"cbdb9649-4ffb-4a52-ac2c-ecd155b2547d","owner":[],"postedDate":"October 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-22T16:07:55+00:00","versionOfRecord":{"articleIdentity":"rs-7590855","link":"https://doi.org/10.1007/s00262-025-04256-0","journal":{"identity":"cancer-immunology-immunotherapy","isVorOnly":false,"title":"Cancer Immunology, Immunotherapy"},"publishedOn":"2025-12-19 15:57:43","publishedOnDateReadable":"December 19th, 2025"},"versionCreatedAt":"2025-10-01 08:05:01","video":"","vorDoi":"10.1007/s00262-025-04256-0","vorDoiUrl":"https://doi.org/10.1007/s00262-025-04256-0","workflowStages":[]},"version":"v1","identity":"rs-7590855","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7590855","identity":"rs-7590855","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}