Safety, Outcomes, and T-Cell Characteristics in Patients with Relapsed or Refractory MDS or CMML Treated with Atezolizumab in Combination with Guadecitabine

Myelodysplastic syndromes (MDS) are clonal hematopoietic stem cell malignancies whose incidence increases with age (1). Among the few treatment options available for higher-risk MDS (HR-MDS), hypomethylating agents (HMA) such as azacitidine and decitabine are relatively safe and effective in approximately half of patients; however, responses are not durable and median overall survival (mOS) after failure of an HMA is 4 to 6 months (2–4).

The mechanisms of resistance to HMAs are not entirely clear. Tumor cell–intrinsic factors such as changes in azanucleoside uptake and metabolism and cell-cycle quiescence have been suggested, and several studies in patients indicate that changes in the microenvironment may also play important roles (5, 6). Our group observed that azacitidine-induced demethylation and upregulation of programmed cell death protein 1 (PD-1) in peripheral T cells was associated with a dismal outcome in patients with HR-MDS (7). Others have identified upregulation of programmed death-ligand 1 (PD-L1) in CD34⁺ myeloblasts of patients with MDS after treatment with HMAs (8). In addition, it has been shown that T-cell receptor clonotypes change after treatment with HMA (9). Taken together, these findings suggest that HMAs may engender resistance through unintended dampening of the T-cell response to the malignant cells in MDS.

We hypothesized that immune checkpoint inhibition could overcome HMA resistance in patients with MDS or chronic myelomonocytic leukemia (CMML) who were refractory to HMA therapy or had relapsed after responding. To investigate this, we conducted a Phase I/II study combining a novel decitabine prodrug, guadecitabine, with a PD-L1 inhibitor, atezolizumab. We chose guadecitabine based on early-phase studies in which this drug demonstrated a longer duration of in vivo exposure to the active drug and promising clinical results. Subsequent large Phase III clinical trials failed to demonstrate superiority to other HMAs in the treatment of MDS and acute myeloid leukemia (AML) so the drug is not being further developed.

This study was a multicenter open-label Phase I dose-finding sub-study followed by a Phase II efficacy study (clinicaltrials.gov identifier NCT02935361) evaluating the combination of guadecitabine with atezolizumab for the treatment of patients with HR-MDS or CMML relapsing after or refractory to at least 4 cycles of at least one HMA. HR-MDS was defined as intermediate, high, or very high risk by the Revised International Prognostic Scoring System (IPSS-R; ref. 10) and CMML was categorized as CMML-1 or CMML-2 by the World Health Organization (WHO) 2016 criteria applied at the time of study entry (11). While the IPSS-R is not validated among patients at relapse, we considered it an appropriate strategy to exclude lower-risk patients at time of study entry. The protocol was approved by the Institutional Review Board (IRB) at each participating institution and written informed consent was obtained from each patient; the study was conducted in accordance with Good Clinical Practice and the Belmont Report. The study drugs, guadecitabine and atezolizumab, were provided by Astex Pharmaceuticals, Inc. and Genentech, Inc., respectively. Astex ceased manufacturing of guadecitabine and all available product expired 10 months after the last patient was enrolled on this study. The 3 patients who were on study after that received decitabine as per standard FDA prescribing information in lieu of guadecitabine.

Phase I followed a modified 3+3 dose-escalation design beginning with 50% of the recommended dose level (DL) of guadecitabine, 30 mg/m² (DL 0), given subcutaneously for 5 consecutive days, in combination with a fixed dose of atezolizumab, 840 mg given intravenously on Days 8 and 22 of a 28-day cycle. Guadecitabine would be escalated to 60 mg/m² (DL 1) if no dose-limiting toxicities (DLT) occurred in the first 3 patients on DL 0; expansion of the cohort to 6 would occur for 1 DLT and cessation of further treatment would occur if 2 or 3 patients experienced DLTs. If a DLT occurred in 2 or more patients in the DL 1 group, the dose would be de-escalated to 45 mg/m² (DL 1) and the same rules applied as for DL 1.

In Phase II, patients received 60 mg/m² guadecitabine subcutaneously daily for 5 days of a 28-day treatment cycle along with a fixed dose of 840 mg atezolizumab intravenously on Days 8 and 22. Guadecitabine could be held or dose reduced to manage toxicity. Atezolizumab toxicity was managed on the basis of the FDA prescribing information and investigator's brochure. Efficacy was measured by overall response rate (ORR) based on the 2006 International Working Group (IWG) Response Criteria for MDS (12). Overall survival (OS) and progression-free survival (PFS) were secondary endpoints.

Inclusion criteria were: (i) age ≥ 18 years and able to consent; (ii) diagnosis of MDS according to the 2016 WHO criteria, of intermediate or higher risk (3+) by IPSS-R criteria, or CMML-1 or CMML-2; (iii) prior treatment with at least 4 cycles of azacitidine and/or decitabine with either disease progression by 2006 IWG criteria (ref. 12; “refractory”) or loss of a previously documented response (“relapsed”) and ineligible for allogeneic stem cell transplant; (iv) Eastern Cooperative Oncology Group (ECOG) performance status of 0–2; (v) adequate hepatorenal function (creatinine < 2.5 × upper limit of normal; bilirubin < 2.5 × upper limit of normal, transaminases < 3 × upper limit of normal); (vi) willingness to use contraception or abstain from childbearing.

Exclusion criteria were: (i) active autoimmune disease other than vitiligo, type 1 diabetes, or controlled hypothyroidism; (ii) interstitial lung disease, or any disease requiring supplemental oxygen; (iii) history of pneumonitis or fibrosis from any cause; (iv) active treatment for other malignancies except hormonal therapy for stable breast or prostate cancer; (v) history of allergy to compounds of similar chemical or biologic composition as HMAs or to humanized antibodies or fusion proteins; (vi) >30% blasts in marrow or total white blood cell count >25×10³/L; (vii) active infection within 72 hours, need for antibiotics within 7 days or life-threatening infection within 28 days; treatment with investigational agent within 28 days; (viii) ongoing treatment with >10 mg prednisone or other immunosuppressive or immunostimulatory agent; (ix) prior allogeneic stem cell or solid organ transplantation, regardless of duration since transplant; (x) prior treatment with any immune checkpoint inhibitor (ICI).

Standard descriptive statistics were used to summarize baseline and study results including toxicity data. The observed ORR for the first 6 cycles and during all time on treatment was calculated as the ratio of the number of patients who experienced complete remission (CR), marrow CR (mCR), partial remission (PR), or hematologic improvement (HI) divided by the total number of patients treated on study, and its associated binomial 95% confidence interval (CI) was calculated (13). The association of baseline characteristics with response to study treatment was tested by using Fisher exact test. OS was calculated from the date of treatment start to death due to any cause or to the latest follow-up. PFS was calculated as the time from treatment start to the date of progression or death whichever observed first, or to the latest follow-up. Kaplan–Meier plots were used to estimate the probabilities of OS and PFS. The associated 95% CIs were calculated using Greenwood's standard errors formula. Log-rank test was used to test the association of baseline clinical characteristics with OS and PFS. Cox proportional model was used for multivariable analysis including all variables with P ≤ 0.20 in the univariate analysis in the model. HRs were used to calculate the relative risks of death and likelihood ratio test was used to test the associate of baseline characteristic with OS and PFS in the multivariable analysis. Landmark method was used to test the association of response and OS. For analysis of the impact of correlative data on outcome, including mutations and T-cell characteristics, we employed an additional category of “long survivors” or “short survivors” whose survival from Cycle 1 Day 1 (C1D1) was greater than/equal to, or less than, 15 months respectively. All reported P values were two-sided and P values ≤ 0.05 were considered statistically significant. All analyses were conducted using SAS statistical software (version 9.4; SAS Institute Inc, Cary, NC).

Bone marrow mononuclear cells (BMMC) were isolated at screening and within 96 hours prior to Day 1 of Cycles 3, 5, and 7, and CD3⁺ cells (T cells), CD34⁺ cells, and the CD3- and CD34-depleted population was isolated using magnetic beads (for details see Supplemental Methods).

Targeted sequencing was performed on DNA from BMMCs (depleted of CD3⁺ and CD34⁺ cells) and BM CD3⁺ T cells from patients who had sufficient extracted DNA and had received at least 1 cycle of treatment. A custom Twist panel consisting of 145 genes related to myeloid cancer was applied, and samples were sequenced on an Illumina NextSeq 500 instrument at an average target coverage of 600x to 1,000x per sample (for details see Supplemental Methods). We focused on the 40 genes most commonly mutated in MDS for analysis (Supplementary Table S1). The lower level of detection in the BMMCs was set to a variant allele frequency (VAF) of 2% for all genes, except TP53, for which we used a cutoff of 1%. In the separated CD3⁺ T-cell population we confirmed 90% or greater purity in selected cases. To avoid any false positivity due to contamination by myeloid cells after cell sorting, we only report mutations with a VAF ≥ 10% in the sorted T cells.

Peripheral blood mononuclear cell (PBMC) samples were analyzed using multicolor flow cytometry to evaluate immune activation and correlation of treatment outcome with established T-cell and natural killer (NK)-cell phenotype and activation panels (14). Phenotype panels of T and NK cells consisted of fluorophore-labelled antibodies recognizing cell surface markers of CD4⁺, CD8⁺, and NK cells (Panel 1 and Panel 2), and the T-cell activation panel included fluorophore-labelled antibodies specific to cell surface and intracellular T-cell activation markers (Panel 3). On the basis of sample availability, we evaluated up to three different time points from each of 21 patients: pretreatment (defined as “PRE”), during the second treatment cycle (C2D1 or C2D8; defined as “EARLY”), and after the third or fourth treatment cycle (C4D1, C4D8, or C5D1; defined as “LATE”).

DNA sequencing data and the remainder of the dataset may be requested, pursuant to local IRB guidelines, by emailing the corresponding author.

Between November 2016 and October 2020, 33 patients (22 men and 11 women) from 4 centers in the United States were enrolled in the study. Demographics and disease characteristics are shown in Table 1. The median age at enrollment was 73 (range, 54–85) years. At study entry, 30 patients had MDS, primarily higher risk (17 high, 2 very high, 11 intermediate) by the IPSS-R; a majority (70%) had HMA-refractory disease, as opposed to HMA-responsive disease with relapse (30%), prior to enrollment. Two patients had CMML-1 and 1 patient had CMML-2. Prior regimens included azacitidine monotherapy (31 patients), decitabine monotherapy (8 patients), guadecitabine monotherapy (1 patient), lenalidomide monotherapy (6 patients), low-dose cytarabine monotherapy (2 patients), and induction chemotherapy (1 patient). Six (18.1%) patients received sequential HMAs prior to study entry. Bone marrow blast count at study entry was available for 32 patients: it was > 5% in 16 patients (50%), 2.1% to 5% in 10 patients (31%), and ≤2% in 6 patients (19%).

Patients received a median of 6 treatment cycles (range 1–22). ORR by 6 months was 30% (95% CI, 16%–49%) with 1 CR (3%); 3 (9%) patients achieved HI (2 neutrophil, 1 erythroid), 5 (15%) achieved mCR and 1 achieved PR (Table 2). One additional patient achieved CR after 6 months for a best on-study ORR of 33% (95% CI, 19%–52%) with CR rate of 6%. Median duration of response among the 11 responders was 10.1 (range 1.8–47.6) months. A statistically significant association was found between female gender and response, P = 0.018. There was no significant association of any other baseline characteristics with response to the study treatment.

With a median follow-up of 30.1 (range 11.1–51.6) months for the entire cohort (Table 2), and one patient still on treatment as of this publication, mOS was 15.1 months (95% CI, 8.5–25.3). Median PFS was 7.2 months (95% CI, 3.6–13.8). The impact of baseline characteristics on survival is shown in Table 3. Patients under 75 years of age lived significantly longer (mOS 20.3 months; 95% CI, 8.5–51.6+) than older patients (mOS 9.5 months; 95% CI, 1.5–15.1; P = 0.030). There was a trend toward better survival among women (mOS 25.3 months; 95% CI, 9.5–51.6+) compared with men (8.5 months; 95% CI, 3.3–20.3). Among the 30 patients with MDS, mOS was 16.4 (95% CI, 9.5–27.3) months, superior to that of patients with CMML (2.1 months; 95% CI, 0.9–15.1). Median OS for patients who achieved an IWG response was 19.8 months (95% CI, 7.6–49.7+), which was not statistically superior to that of nonresponders whose mOS was 8.7 months (95% CI, 6.4–25.4; P = 0.12); individual outcomes are shown in Fig. 1. After adjusting by other variables in the Cox proportional hazards model, age (HR for ≥ 75 3.34; 95% CI, 1.25–8.97; P = 0.022), gender (HR for males 3.30; 95% CI, 1.20–9.02; P = 0.018), and number of prior chemotherapy regimens (HR for > 1 regimen 3.29; 95% CI, 1.24–8.74; P = 0.019) were significantly associated with survival. Gender and number of prior regimens were also significantly associated with PFS after adjusting for other variables in the Cox proportional model. There was no statistically significant association found between overall or PFS and baseline blast count, IPSS-R score, relapsed versus refractory disease, or ECOG performance status at baseline.

There were no DLTs among the three patients treated at DL 1 in Phase I nor in the first three treated at DL 1 in Phase II. Among the entire patient population there were three deaths (9%) at ≤ 30 days of first administration of study drug. One patient with high-risk MDS and grade 4 neutropenia at baseline received Days 1 to 8 and subsequently developed sepsis; he opted to withdraw all therapy and died at Day 23. A second patient with CMML-1 at baseline presented for Day 1 of treatment with extreme leukocytosis, received Days 1 to 8 of study therapy along with hydroxyurea, and was subsequently found to have brain lesions concerning for leukemic infiltrates. He opted to withdraw all therapy on day 10 and died at home on day 30. The third patient had high-risk MDS and grade 4 thrombocytopenia at baseline; he received Days 1 to 8 of study therapy and presented with headache and neutropenic fever on day 16 for which he was treated with broad-spectrum antibiotics. He had two episodes of convulsions prompting treatment for presumed encephalitis with steroids and died on Day 21 due to brainstem herniation after a lumbar puncture. Cerebrospinal fluid analysis and imaging were felt to be inconsistent with autoimmune encephalitis. However, the neutropenic sepsis was considered likely due to study treatment.

Grade 4 toxicities of any attribution occurred in 21 (64%) patients. The most common study drug–related toxicities were thrombocytopenia (39%), neutropenia (30%), and anemia (30%; Supplementary Table S2). Five patients (16%) came off study for drug-related toxicity. Immune-related adverse events (IRAE) occurred in 12 (36%) patients: 2 with grade 3 autoimmune encephalitis, 2 with grade 3 pneumonitis, 1 with grade 2 arthritis, 1 with grade 2 hypothyroidism, 1 with grade 2 colitis, 4 with grade 1 rash, and 1 with grade 1 hyperthyroidism (Supplementary Table S3). One of the 2 patients with presumed grade 3 autoimmune encephalitis was treated with steroids; both patients recovered and were taken off the study. One was a 62-year-old male with very high–risk MDS who died at 4 months, and the other was a 71-year-old female with high-risk MDS who died at 9.5 months. Of the 2 patients with autoimmune pneumonitis, 1 was an 81-year-old male with intermediate-risk MDS and baseline grade 4 thrombocytopenia who was treated with steroids but died within 1 week in multiorgan failure due transfusion-associated circulatory overload; the other was a 68-year-old male with high-risk MDS who recovered without therapy and was alive at 24.6 months. They developed the complication during cycle 2 and cycle 1, respectively. The median time to develop an IRAE was 1.2 (range 0.2–9.4) months, after a median of 4 (range 1–15) doses of atezolizumab with a median time to recovery of 17 (range 1–28) days (Supplementary Table S3).

DNA was available for genetic analyses in 27 of the 33 patients enrolled in the trial.

BMMCs: All patients except one carried somatic mutations in BMMCs (Fig. 2). The median number of mutated genes was 3 (range 0–9), and some genes carried more than one mutation. The most frequently mutated genes were the epigenetic regulators ASXL1 (12 patients) and EZH2 (7 patients), with less frequent mutations in TET2 (6), DNMT3A (5), and IDH1 (2). Mutations in RUNX1 (8) were also common. Among classical tumor suppressors, TP53 (4) and PTPN11 (3) were the most frequently mutated. No characteristic pattern was seen in the distribution among short and long survivors.

CD3⁺ T cells: Mutations in ≥ 20% of the T-cell population were frequently observed, particularly in epigenetic regulators and splicing factor-encoding genes (Fig. 2). Among 27 patients with mutation data available, mutations were present in 9 of 15 “long survivors” and in 6 of 12 “short survivors;” there was no significant difference between the groups (P = 0.7, Fisher test).

ASXL1 was the most frequent mutation detected; in 7 patients it was found only in the myeloid cells and in 5 it was identified in both the myeloid and the T-cell populations (“shared”). While there was no significant association between the mutation and response to the study treatment, the median survival of the patients with shared mutations was not reached whereas it was 16.4 months (95% CI, 3.3–27.3) among those without the mutation (n = 15) and 9.5 months with the myeloid-only mutation (95% CI, 2.1–35.0; Supplementary Fig. S1). This was statistically significant after adjusting by age at study entry, gender, diagnosis, and the number of prior chemotherapy regimens using the Cox proportional hazards model (P = 0.001, based on likelihood ratio test). There were insufficient occurrences of the other mutations in the different cell populations to determine their effect on survival.

We evaluated lymphocytes with a focus on subset frequencies and activation and proliferative characteristics of both T cells and NK cells (Supplementary Fig. S2; Fig. 3). We identified the T effector memory subset of CD8⁺ T cells (T_EFF: CD45RA+, CD197−) as the most frequent subset of CD8⁺ T cells at baseline and throughout treatment. We observed no differences in the frequencies of CD4⁺ or CD8⁺ memory T cells (CM: CD45RA−, CD197+; EM: CD45RA−, CD197−; T_EFF: CD45RA+, CD197−) at baseline or throughout treatment in terms of response or survival. The frequency of T_EFF cells out of the total pool of CD8⁺ T cells tended to be higher in patients at all 3 time points with longer OS (≥ 15 months), though this was not statistically significant (Fig. 3A).

While the T_EFF-cell subset seemed enriched in long survivors, no treatment-induced change was observed in the subsets expressing T-cell activation markers such as CD39, CD69, or PD-1. On the contrary, in the short survivors a higher fraction of the T_EFF-cell subset expressed PD-1, and there was also a tendency for increased expression of CD69 and CD39 (Fig. 3B). The expression of Ki67 (a proliferation marker) was also increased in the T_EFF-cell subset of the short survivors (Fig. 3C). This difference between short and long survivors was even more pronounced for T_EFF cells expressing both PD-1 and Ki67 (Fig. 3C). PD-1 surface expression on CD8⁺ T cells was upregulated in the short-survivor group (Fig. 3D). We did not find any correlation between CD8⁺ T-cell activation and T-cell mutations identified in the two groups. Furthermore, no differences were observed at the baseline or posttreatment in the frequency and proliferation of CD4 memory and regulatory subsets.

Given the impact of gender on survival we also analyzed the functional activation of CD8⁺ T cells for males and females by comparing baseline and posttreatment expression of PD-1 (frequency and intensity), CD39, and CD69 (Supplementary Fig. S3). We noted higher expression and intensity of PD-1 and lower expression of CD39 and CD69 at baseline among females with no change over the course of treatment, whereas males had lower baseline expression and intensity of PD-1 and a significant upregulation after treatment. CD39 and CD69 expression was higher in males at baseline and throughout treatment and did not appear to change significantly with therapy.

We found no differences in NK-cell (CD56^dim CD16⁺) frequencies or treatment-induced change in activation markers, although patients with short survival tended to display more activated NK cells (Supplementary Fig. S4).

In this study, we combined guadecitabine, a novel HMA, with an ICI of PD-L1, atezolizumab, based on translational data suggesting that upregulation of PD-1 in T lymphocytes by azacitidine contributes to HMA resistance and is associated with poor outcome (5). Our patient population consisted of older patients with HMA-relapsed and -refractory MDS and is representative of the epidemiology of MDS in the U.S. (Supplementary Table S4). The tolerability of the regimen was comparable with that seen in solid tumor trials of immunotherapy combinations with 36% of patients experiencing immune-related adverse events which were all grade 3 or lower. Early deaths occurred in 3 patients (9%) after Days 1 to 8 of study treatment, 2 of whom had high-risk MDS and 1 appeared to be transitioning from CMML to AML during the first cycle. Two of these patients developed sepsis and opted to forego further antibiotics and transition to hospice. The third patient developed sepsis with multiorgan failure and died of brainstem herniation after a lumbar puncture. Response rates were modest, with 33% of patients experiencing an IWG-defined response at any time, including 2 with CR. Median survival was 15.1 months in the entire study population and 16.4 months in the 30 patients with MDS. In a multivariate analysis, we observed a statistically significant longer OS in patients younger than 75, in women, and in patients with only 1 prior treatment regimen (Table 3).

Outcomes after failure of upfront HMA are dismal (4), and Phase II studies of treatments for patients with relapsed or refractory (R/R) MDS have not produced mOS beyond 1 year. These include guadecitabine monotherapy and other HMA-ICI combinations. In a Phase II study of patients treated with guadecitabine alone, mOS was 11.7 months in the 53 patients with R/R MDS or CMML (15). Another Phase II study administered pembrolizumab, a PD-1 inhibitor, with azacitidine to a similar study population, achieving an ORR of 25% and mOS of only 5.8 months (16). The addition of venetoclax, a bcl-2 inhibitor, to azacytidine produced a mOS of 11.4 months in a similar patient population (17). The tolerability of azacitidine with atezolizumab for treatment of MDS was recently questioned in a clinical trial in which patients experienced significant toxicity, leading to discontinuation of the trial (18). Early deaths were noted in the HMA-naïve cohort whereas in the small cohort of 14 patients with R/R MDS, the results were comparable with ours with respect to response rates (28.6%) and deaths (18%). It is unclear if the lower toxicity in the previously HMA-exposed patients is due to lower tumor burden or perhaps a reduction in the number or reactivity of T-cell clones leading to fewer autoimmune adverse events.

We did not find immune-related adverse events to be a major cause of death. The most serious were 2 events of autoimmune encephalitis and 2 of autoimmune pneumonitis, all grade 3. In a recent publication, autoimmune pneumonitis occurred in 12% of patients with AML treated on different studies with ICI-containing regimens (nivolumab, a PD-1 inhibitor, and/or ipilimumab, a CTLA4 inhibitor; ref. 19). Almost half of these events were fatal. Male sex and thrombocytopenia were considered risk factors and the development of pneumonitis was associated with a higher risk for mortality overall. While only 2 (6.1%) patients developed autoimmune pneumonitis in our study, both were males and 1 died within a week of starting steroids. Autoimmune encephalitis is more difficult to diagnose accurately than pneumonitis and both of the patients in our study who were treated as such presented with altered mentation and were concurrently treated empirically for infection. In another study combining atezolizumab with an HMA, only 1 case of autoimmune pneumonitis in 46 treated patients was noted, and no cases of autoimmune encephalitis were reported, but there were several reports of autoimmune hepatitis (18). Given the small sizes and discordant toxicity results from our study and that of Gerds and colleagues, it is difficult to assert that the profile of autoimmune adverse events is unique to the ICI target in patients with myeloid malignancies.

In 27 of 33 patients enrolled in our study, we sequenced a panel of 40 genes commonly mutated in MDS and identified mutations in the myeloid compartment BMMCs (CD3-depleted) and in sorted CD3⁺ T lymphocytes. To the best of our knowledge the detailed mutational spectrum of T cells in MDS after treatment with HMAs and/or treated with ICIs has not previously been reported, although clonal involvement of the T-cell compartment is recognized (20). In the myeloid compartment mutations were frequently observed in ASXL1, RUNX1 and EZH2, while 4 of 27 had a TP53 mutation; there was no significant difference in the distributions of myeloid mutations among patients with long and short survival. For T-cell mutation detection we employed a rigorous VAF cutoff of 10% to avoid misleading data due to lack of purity or from very small clones, which may be less likely to affect T-cell function. We found that 15 of 27 patients carried mutations in T cells. In all but one case, the mutations detected in T cells were also present in the myeloid compartment, suggesting origination from a common stem cell ancestor. Mutations restricted to the myeloid compartment were more frequent in classical tumor suppressor genes, probably reflecting their origin in later-stage progenitors from this compartment. One case showed mutations in the T-cell compartment only, which could be a result of more efficient removal of myeloid clones by the previous HMA treatment. We could also have overlooked mutations in smaller T-cell subsets; the limited amount of material did not allow for further analyses of specific T-cell subsets. Importantly, all patients were previously treated with HMA in first line, so the high frequency of mutated T-cell clones may be a consequence of selection by HMA.

We did not observe any significant difference between long and short survivors with respect to the presence of mutated T cells. However, we did find that ASXL1 mutations, which have previously been associated with HMA resistance in MDS (21), were present in both the BMMCs and the T cells of both of the patients who achieved a CR and in 5 of 8 affected long survivors, while ASXL1 mutations were restricted to the myeloid compartment in all 4 affected short survivors. A multivariate analysis demonstrated superior survival in patients with shared ASXL1 mutations compared with those with myeloid-only or those lacking ASXL1 mutations. Notably, ASXL1 mutations were also associated with improved survival in a study of patients with relapsed and refractory AML treated with azacitidine and the PD-1 inhibitor nivolumab, though their prevalence in T lymphocytes was not investigated (22). While the impact of each of the commonly occurring myeloid somatic mutations has not been defined in T cells, it is now recognized that both DNMT3A and TET2 disruption can influence the epigenetic profile and promote CAR T-cell function (23–25). A recent study in mice expressing mutant ASXL1 in T cells demonstrated increased PD-1 expression which may support the efficacy of immune checkpoint inhibition in cancer patients whose T cells carry this mutation (25). These observations merit confirmation in a larger cohort of patients with ASXL1 mutations.

We performed a comprehensive flow cytometry assessment of T cells from before and after treatment initiation. As expected, we identified significant upregulation of activation markers in CD8⁺ T cells, which was more pronounced in men, but we could not correlate this with response to treatment or longer survival. In fact, there seems to be more early activation of CD8⁺ T cells among short survivors, although the overall fraction of effector CD8⁺ T cells in this group tended to be lower. We did not have sufficient samples to determine if ASXL1-mutated T cells had a unique phenotype at baseline or over the course of therapy. This deserves further investigation. It is also possible that the beneficial impact of PD-L1 inhibition among long survivors is exerted through other cells in the marrow microenvironment, such as myeloid-derived suppressor cells, which are known to express PD-L1 (26).

In conclusion, the combination of guadecitabine and atezolizumab in patients with refractory or relapsed MDS produced a modest response rate and potentially a survival advantage in certain patients with R/R MDS. The toxicity profile was not unexpected with 64% of patients developing grade 4 toxicities and 36% developing immune-related adverse events, all ≤ grade 3. Because the initiation of this study, guadecitabine failed to show superiority to other HMAs in R/R MDS and R/R AML patients in two large Phase III trials. This suggests that any benefit achieved by the patients in our study was from the combination, not the guadecitabine itself. Our findings therefore warrant further investigation of the potential for immune checkpoint inhibition to resensitize MDS to any of the available HMAs in R/R MDS and provide an impetus to explore the biologic roles of gender, co-occurring T-cell mutations in ASXL1 and other genes, and myeloid-derived cells in the microenvironment.

C.L. O'Connell reports grants from Van Andel Research Institute-Stand Up to Cancer, as well as nonfinancial support from Astex Pharmaceuticals, Inc. and Genentech, Inc. during the conduct of the study; C.L. O'Connell also reports other support from Astex Pharmaceuticals, Inc, outside the submitted work. P. Kropf reports personal fees from Bristol Myers Squibb outside the submitted work. J.W. Hansen reports personal fees from Bristol Myers Squibb outside the submitted work. B.A. Youngblood reports patents related to DNMT3A programming and deletion in T-cell therapy licensed, and a patent for deletion of clonal hematopoiesis drivers in adoptively transferred T cells for therapy pending. S.R. Hadrup reports other support from Tetramershop, as well as personal fees and other support from PokeAcell outside the submitted work. In addition, S.R. Hadrup is coinventor of the patents WO2015185067 and WO2015188839 for the barcoded MHC technology which is licensed to Immudex, and coinventor of the licensed patent for combination encoding of MHC multimers (EP2088/009356), licensee: Sanquin, NL; these patents/technologies were not used for the manuscript submitted. J.-P. Issa reports grants from Astex during the conduct of the study, as well as personal fees from Astex and Daiichi outside the submitted work. P. Jones reports personal fees from Zymo Research Corp., H3 Biomedicine, CPRIT, Cancer Research UK (CRUK), and Omega Therapeutics outside the submitted work. I. Siddiqi reports personal fees from EUSA Pharma outside the submitted work. K. Grønbaek reports nonfinancial support from Astex and Genentech, as well as grants from Van Andel Research Institute, Danish Cancer Society, Novo Nordisk Foundation, and Lundbeck Foundation during the conduct of the study; K. Grønbaek also reports grants from Novo Nordisk Foundation, Danish Cancer Society, Independent Research Fund Denmark, Danish Cancer Society, and Janssen Pharma outside the submitted work. No disclosures were reported by the other authors.

C.L. O'Connell: Conceptualization, data curation, supervision, funding acquisition, investigation, methodology, writing–original draft, project administration, writing–review and editing, patient accrual and management. M.R. Baer: Investigation, writing–review and editing, patient accrual and management. A.D. Ørskov: Data curation, formal analysis, methodology, writing–original draft, writing–review and editing, cell sorting, genetic mutation curation and analysis. S.K. Saini: Data curation, formal analysis, methodology, writing–original draft, writing–review and editing, cell sorting, flow cytometry data curation and analysis. V.H. Duong: Writing–review and editing, patient accrual and management. P. Kropf: Writing–review and editing, patient accrual and management. J.W. Hansen: Data curation, writing–review and editing, cell sorting, genetic mutation curation and analysis. D. Tsao-Wei: Formal analysis, methodology, writing–review and editing, statistician. H.S. Jang: Writing–review and editing, cell sorting, genetic analysis. A. Emadi: Writing–review and editing, patient accrual and management. S. Holmberg-Thyden: Writing–review and editing, assistance with interpretation of flow cytometry data. J. Cowland: Writing–review and editing, assistance with interpretation of genetic data. B.T. Brinker: Writing–review and editing, patient accrual and management. K. Horwood: Writing–review and editing, patient accrual and management. R. Burgos: Project administration, writing–review and editing. G. Hostetter: Writing–review and editing, evaluation of immunohistochemistry on biopsy specimens. B.A. Youngblood: Writing–review and editing, assistance with interpretation of T-cell characteristics. S.R. Hadrup: Supervision, methodology, writing–review and editing, supervision and interpretation of flow cytometry data analyses. J.-P. Issa: Methodology, writing–review and editing. P. Jones: Resources, supervision, writing–review and editing. S.B. Baylin: Writing–review and editing. I. Siddiqi: Writing–review and editing, evaluation of immunohistochemistry on biopsy specimens. K. Grønbaek: Conceptualization, supervision, funding acquisition, methodology, writing–original draft, writing–review and editing.

Presented as an abstract at the 60th Annual American Society of Hematology Meeting, San Diego, CA, December 2018.

This work was supported by Van Andel Research Institute through the Van Andel Research Institute – Stand Up To Cancer Epigenetics Dream Team. Stand Up To Cancer is a division of the Entertainment Industry Foundation. The indicated Stand Up To Cancer Grant is administered by the American Association for Cancer Research, the Scientific Partner of SU2C. C.L. O'Connell, M.R. Baer, P. Kropf, K. Grønbaek, S.K. Saini, B.T. Brinker, A.D. Ørskov.

The project described was supported in part by award number P30CA014089 from the NCI, C.L. O'Connell.

The NCI Cancer Center Support Grant (CCSG) P30CA134274, M.R. Baer.

The Lundbeck Foundation (R180–2014–3675), A.D. Ørskov.

The Danish Cancer Society (Danish Research Center for Precision Medicine in Blood Cancer; grant 223-A13071–18-S68), K. Grønbaek.

The Novo Nordisk Foundation (Novo Nordisk Foundation Center for Stem Cell Biology, DanStem; grant NNF17CC0027852), K. Grønbaek.

Greater Copenhagen Health Science Partners (Clinical Academic Group in Blood Cancers), K. Grønbaek.

The Danish Cancer Society (grant no. R72-A4531), S.R. Hadrup.

European Research Council, StG 677268 NextDART), S.R. Hadrup.

We wish to thank our patients with MDS and their family members.

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.