Sage Journals: Discover world-class research

Abstract

Background:

RNA splicing factor (SF) mutations are associated with adverse outcomes in patients with acute myeloid leukemia (AML) and higher-risk myelodysplastic syndromes/neoplasms (HR-MDS). Preclinical data suggest that aberrant RNA splicing can lead to the generation of neoantigens, which renders these tumors more susceptible to immune checkpoint inhibitors. However, dedicated studies on immune checkpoint inhibitors in AML and MDS patients with SF mutations are limited.

Objectives:

To characterize the immune and epigenetic landscape of AML and MDS patients with SF mutations.

Design:

Post hoc analysis of the impact of RNA SF mutations (defined as any of SF3B1, SRSF2, U2AF1, and ZRSR2) on outcomes of newly diagnosed, older or intensive chemotherapy-ineligible patients with AML or HR-MDS treated with azacitidine ± the anti-PD-L1 antibody durvalumab as part of the randomized, phase II FUSION trial.

Methods:

Primary endpoint was the overall response rate (ORR). Flow cytometry and gene expression profiling using bulk RNA sequencing were performed on pretreatment bone marrow aspirate samples.

Results:

One hundred twenty-six patients with AML (51 SF-mutant and 75 wild type) and 79 patients with MDS (33 SF-mutant and 46 wild type) were included. ORR was independent of SF mutation status for both AML (SF-mutant: 35.3% vs wild-type: 33.3%; p = 0.47) and MDS patients (51.5% vs 56.5%; p = 0.63). Median overall survival was similar for SF-mutant and wild-type AML (14.9 months vs 12.2 months; p = 0.50) and MDS patients (23.5 months vs 10.6 months; p = 0.16). There were no differences in key cell populations from bone marrow aspirate flow cytometry samples. Gene expression analyses showed an increase in MKI-67 expression in SF wild-type patients, but no differences were observed in several immune-related genes including IL7R and PD-L1.

Conclusion:

Addition of durvalumab to azacitidine did not improve ORR or OS among older patients with newly diagnosed AML and HR-MDS independent of SF mutation status.

Trial registration: NCT02775903

Keywords

AML gene expression immune phenotype MDS outcomes splicing mutation

Introduction

RNA splicing is a tightly regulated process during which the precursor messenger RNA (mRNA) is being transformed into a mature mRNA.¹ Alterations in RNA splicing have been implicated in aberrant gene expression, the generation of neoantigens, and in the malignant transformation of different tumor types.¹ Mutations affecting genes essential for RNA splicing regulation such as SF3B1, SRSF2, U2AF1, and ZRSR2 are enriched among patients with myelodysplastic syndromes/neoplasms (MDS) and secondary acute myeloid leukemia (AML).^1,2 While the prognostic impact of RNA splicing factor mutations is context-dependent and may depend on the type of treatment patients received, they generally confer an adverse prognosis among patients with higher-risk MDS (HR-MDS) and AML and are associated with lower response rates to currently available therapies.^3–6

Previous attempts to develop targeted therapies for splicing factor-mutant myeloid malignancies have largely been unsuccessful with low response rates using monotherapy approaches.^7,8 Preclinical data suggest that splicing mutations can lead to the generation of neoantigens, which might render splicing factor-mutant MDS and AML cells more susceptible to treatment with immune checkpoint inhibitors.⁹ However, dedicated analyses of patients with splicing factor-mutant MDS and AML who were treated with immune checkpoint inhibitors are limited. Furthermore, the immunologic landscape of patients with splicing factor-mutant MDS and AML is poorly characterized, which further limits the development of immunotherapies for patients with myeloid malignancies.

The FUSION AML-001 trial was a large phase II trial that randomized 205 older patients with previously untreated AML or HR-MDS to either azacitidine (AZA) monotherapy or AZA in combination with the anti-PD-L1 antibody durvalumab.^10,11 The primary endpoint results of this trial showed that the addition of durvalumab did not improve objective response rate (ORR) or overall survival (OS) and have been published previously.^10,11 As patients enrolled in the trial underwent extensive and serial assessments of molecular, immunologic, and epigenetic parameters, we performed a post hoc comparison of the immune landscape as well as clinical outcomes of patients with splicing factor-mutant AML and MDS and those with splicing factor wild-type disease.

Methods

Study population

The phase II FUSION trial (NCT02775903) randomized newly diagnosed patients with AML or higher-risk MDS who were older than 75 years of age or otherwise ineligible for intensive chemotherapy to either AZA monotherapy or AZA + durvalumab.^10,11 Here, we performed a subgroup analysis comparing patients with splicing factor-mutant and splicing factor wild-type MDS and AML who were enrolled in the FUSION trial (NCT02775903). As the addition of durvalumab to AZA did not improve outcomes and the baseline patient and disease characteristics between both treatment arms were comparable, we pooled patients across treatment arms and disease types for this analysis.^10–12 Patients enrolled in the original FUSION trial provided informed consent prior to enrollment in the study, and the study protocol was approved by the institutional review board at all participating sites.

Definition of clinical endpoints

The ORR was defined as a composite of complete response (CR), marrow CR, partial response, or hematologic improvement based on modified International Working Group (IWG) 2006 response criteria for patients with MDS and as a composite of CR or CR with incomplete hematologic recovery based on modified IWG 2003 response criteria for AML patients, respectively. OS was measured as the time from randomization to death from any cause.

Next-generation sequencing and definition of splicing factor mutation status

All patients underwent a 38 gene-targeted myeloid mutation analysis from bone marrow samples obtained at screening at Munich Leukemia Laboratory. The list of genes included in the panel is provided in Supplemental Table 1. The mean sequencing coverage across the panel and samples was approximately 3000x. Genetic alterations not matching the reference sequence were noted as mutated, common single nucleotide polymorphism, or as a variant of unknown significance. Mutational load and coverage were assessed at each nonreference location. Patients were classified as having splicing factor-mutant disease if a pathogenic variant in SF3B1, SRSF2, U2AF1, or ZRSR2 at a variant allele frequency (VAF) ⩾2% was found at screening.

RNA sequencing

Gene expression profiles of bone marrow aspirates from screening and cycle 3 day 22 (C3D22) were studied by bulk RNA sequencing as previously described.^10–12 Briefly, EA Genomics (Q2 Solutions) used the Qiagen Micro RNeasy kit (Hilden, Germany) to extract RNA and made libraries using TruSeq SBS v4 chemistry (Illumina; San Diego, USA). We used polyA enrichment and sequenced on an Illumina HiSeq 2500, with 2 × 50 bp read lengths. Alignment was performed with STAR on the full hg38 human genome, and gene-level counts were obtained. Gene expression was then normalized with the function voom in the R package limma.

Bone marrow aspirate flow cytometry

Bone marrow aspirates were collected at screening and sent to Munich Leukemia Laboratory for processing and flow cytometry (see prior study¹¹ for full details). Two panels of flow cytometry antibodies were used to detect granulocytes, lymphocytes, monocytes, and T-cells and reported as a percent of parent population. Tumor blasts were gated based on CD34 and CD117 variant expression. PD-L1 (clone 29E.2A3) surface expression was quantified using QuantiBrite beads.

Statistical analysis

All analyses were performed as a comparison between the pooled cohorts of patients with and without splicing factor mutations and separately by disease type (AML vs MDS) unless otherwise indicated. Survival analysis was performed using the R package “survival” and “survminer,” with the log-rank p values and median survival shown in the plots. Patient characteristics are compared between patients with splicing factor mutated versus wild-type disease status using the “prop.test” method in R when comparing the proportion of patients in each group, or a Wilcoxon rank sum test for numeric characteristics. All boxplots (box and whisker plots) were generated using ggplot2 where the central line shows the median, the ends of the boxes show the interquartile range (IQR), and the whiskers show the most distant point ⩽1.5 times the IQR.

Results

Baseline patient and disease characteristics

A total of 126 patients with AML (51 splicing factor-mutant and 75 splicing factor wild-type) and 79 patients with MDS (33 splicing factor-mutant and 46 splicing factor wild type) were included in the analysis. Baseline patient and disease characteristics by splicing factor mutation status are shown in Table 1. Among AML patients, there were no differences in terms of baseline disease and demographic characteristics between splicing factor-mutant and splicing factor wild-type patients. In the MDS patient cohort, patients with splicing factor-mutant disease were older (75.3 years vs 71.2 years; p = 0.02) and less likely to have therapy-related MDS (0% vs 13.0%; p = 0.04).

Table 1.

Baseline patient and disease characteristics.

Variable	AML		p Value	MDS		p Value
Variable	SF-mutant (n = 51)	SF-WT (n = 75)	p Value	SF-mutant (n = 33)	SF-WT (n = 46)	p Value
Age (mean; SD)	76.4 (6.0)	75.4 (5.4)	0.348	75.3 (7.1)	71.2 (8.1)	0.022
Male sex (n; %)	31 (60.8%)	37 (49.3%)	0.278	27 (81.8%)	29 (63.0%)	0.119
Race (n; %)
White	31 (60.8%)	55 (73.3%)		24 (72.7%)	37 (80.4%)
Black	1 (2.0%)	0		0	0
Other	1 (2.0%)	1 (1.3%)		1 (3.0%)	2 (4.4%)
Asian	0	0		1 (3.0%)	2 (4.4%)
Not reported	18 (35.3%)	19 (25.3%)	0.290	7 (21.2%)	5 (10.9%)	0.699
Ethnicity (n; %)
Non-Hispanic	31 (60.8%)	47 (62.7%)		24 (72.7%)	35 (76.1%)
Hispanic	1 (2.0%)	8 (10.7%)		1 (3.0%)	5 (10.9%)
Not reported	18 (35.3%)	19 (25.3%)		8 (24.2%)	6 (13.0%)
Unknown	1 (2.0%)	1 (1.3%)	0.182	0	0	0.252
ECOG PS (n; %)
0	24 (47.1%)	26 (35.1%)		14 (43.8%)	18 (39.1%)
1	26 (51.0%)	42 (56.8%)		17 (53.1%)	25 (54.3%)
2	1 (2.0%)	6 (8.1%)	0.194	1 (3.1%)	3 (6.5%)	0.869
Secondary disease (n; %)*	25 (49.0%)	28 (37.3%)	0.354	0	6 (13.0%)	0.038
Bone marrow blast percentage (mean; SD)	34.7% (16.5)	38.3% (22.7)	0.315	9.8% (5.3)	9.0% (4.6)	0.478
Peripheral blood blast percentage (mean; SD)	9.1% (12.0)	13.6% (21.0)	0.134	1.7% (3.4)	2.1% (3.1)	0.689

Secondary disease in the context of MDS represents therapy-related disease, while secondary disease among AML patients also includes patients with an antecedent MDS or myeloproliferative neoplasm.

AML, acute myeloid leukemia; ECOG PS, Eastern Cooperative Group Performance Status; MDS, myelodysplastic syndrome; SD, standard deviation; SF, splicing factor.

The most common splicing factor mutations occurred in SRSF2 (n = 27 patients; 21%) and SF3B1 (n = 13; 10%) as well as in SRSF2 (n = 18; 23%) and U2AF1 (n = 11; 14%) in our AML and MDS cohort, respectively. The most common mutation (70%) in SF3B1 was K700Q. For SRSF2, all mutations occurred at the P95 position, with about 60% being P95H missense mutations. In U2AF1, 65% of the mutations were at Q157, while all mutations in ZRSR2 were unique.

The mean VAF of the detected splicing mutation was 33.9% (standard deviation: 16.0%) with only 14 out of 70 mutations (20%) occurring at a VAF of <20%. Supplemental Table 2 provides an overview of the distribution and VAF of splicing mutations by disease. There were seven AML (18.9% of all TP53-mutant AML patients) and two MDS patients (8.3% of TP53-mutant MDS patients) with concurrent TP53 and splicing mutations in the entire cohort, respectively.

Efficacy

The ORR of AZA ± durvalumab was independent of splicing factor mutation status among AML patients with 35.3% for splicing factor-mutant and 33.3% for splicing factor wild-type disease, respectively (p = 0.469). For MDS patients, the ORR was also similar for splicing factor-mutant and splicing factor wild-type disease (51.5% vs 56.5%; p = 0.627).

We next compared OS by splicing factor mutation status and found that OS was not statistically different between neither splicing factor-mutant and splicing factor wild-type AML (median 14.9 months (95% confidence interval (CI): 11.3–20.5 months) vs 12.2 months (95% CI: 9.7–15.9 months); p = 0.50; Figure 1(a)) nor MDS patients (median 23.5 months (95% CI: 12.3 months–not reached) vs 10.6 months (95% CI: 9.7 months–not reached); p = 0.16; Figure 1(b)). Furthermore, OS was independent of the addition of durvalumab and TP53 co-mutation status in both groups (Supplemental Figures 1 and 2, respectively).

Figure 1.

Overall survival by splicing factor mutation status.

Lastly, we analyzed OS by the type of splicing mutation separately among mutations that were present in at least 10 patients. There was no statistically significant difference in OS in the AML cohort when comparing SF3B1 mutant versus SF3B1 wild-type (median OS 16.6 months vs 12.2 months; p = 0.68) and SRSF2-mutant versus SRSF2 wild-type (median OS 19.3 months vs 13.0 months; p = 0.33) patients, respectively. Similarly, OS was comparable among MDS patients when analyzed by SRSF2 (median OS 15.5 months vs 11.9 months for mutant and wild-type; p = 0.87) and U2AF1 mutation status (median OS: 23.5 months vs 11.6 months for mutant vs wild type; p = 0.12).

Correlative studies

Next, we performed comprehensive analyses of the immune landscape of patients by splicing factor mutation status. Using bone marrow flow cytometry from pretreatment samples, there were no differences in key cell populations from bone marrow flow cytometry samples including the percentage of CD3⁺ T-cells, PD-1⁺/TIM-3⁺ CD4 T-cells, PD-1⁺/TIM-3⁺ CD8 T-cells, PD-L1-positive progenitor cells, and myeloid progenitor cells by splicing factor mutation status in neither the AML nor MDS subset (Figure 2(a) and (b)). Bone marrow aspirate samples acquired at the C3D22 timepoint demonstrated similar findings. Lastly, we performed bulk RNA sequencing to analyze gene expression by splicing mutation status (Figure 3). In the combined cohort of AML and MDS patient samples we found an increase in expression of the cell proliferation marker MKI-67 and the zinc finger transcription factor ZNF560 in splicing factor wild-type samples compared to splicing factor-mutant samples.¹³ However, there were no differences in the expression of several immune-related genes including IL7R and CD274 (PD-L1).

Figure 2.

Flow cytometry from pretreatment bone marrow samples.

Figure 3.

Gene expression profiling by bulk RNA sequencing.

Discussion

In this post hoc analysis comparing patients treated with AZA ± the anti-PD-L1 inhibitor durvalumab by splicing factor mutation status, we found no impact of splicing factor mutation status on neither ORR nor OS. Furthermore, there were no statistically significant differences in the pretreatment immune landscape as assessed by bone marrow flow cytometry and bulk RNA sequencing.

RNA splicing factor mutations have been associated with poor outcomes among AML patients and are categorized as adverse risk per the ELN 2022 criteria.⁴ However, the ELN 2022 criteria were mainly derived from younger patients treated with intensive chemotherapy. The absence of a survival difference between splicing factor-mutant and splicing factor wild-type patients in our cohort could suggest that the adverse prognostic implications of RNA splicing mutations can potentially be overcome by an AZA-based therapy. This is in line with other recent publications showing that splicing mutations as well as secondary ontogeny mutations in general can be effectively treated with AZA + venetoclax and that the unfavorable outcomes are largely driven by patients who receive intensive chemotherapy.^14,15 Similar results have been reported by a Chinese clinical trial combining AZA/venetoclax with homoharringtonine¹⁶; again highlighting the potential for combination therapies incorporating hypomethylating agents (HMA) and venetoclax. There is increasing preclinical evidence suggesting that aberrant splicing increases the susceptibility to BCL2 inhibition via the loss of function of the splicing factor RBM10 resulting in mis-splicing and inactivation of antiapoptotic factors such as XIAP and BCL2A1 that are implicated in venetoclax resistance.¹⁷ Based on the increasing body of evidence showing that among patients treated with lower-intensity therapies splicing mutations are not associated with adverse outcomes, the 2024 update to the ELN recommendations focusing on the genetic risk classification for adults with AML receiving less-intensive therapies include patients with splicing mutations who are FLT3-ITD^neg, NRAS^wt, KRAS^wt, TP53^wt in the favorable category.⁶ This emphasizes the importance of individualizing treatment selection based on molecular disease features and could suggest further refining prognosis and postinduction treatment strategies according to the type of frontline treatment received.

An alternative explanation for the absence of a survival difference between the two groups could be the fact that patients with splicing factor-mutant disease have lower rates of other adverse prognostic markers such as TP53 mutations and complex karyotype. As our study was enriched with patients with TP53 mutations (29.8%), the negative prognostic impact of TP53 mutations could have been the main driver for the poor outcomes in the splicing factor wild-type group. However, due to the small number of patients with concurrent TP53 and splicing mutations, we were unable to perform a dedicated analysis evaluating the interaction between TP53 and splicing mutations.

While previous preclinical studies have demonstrated that RNA splicing factor mutations can enhance susceptibility to immune checkpoint inhibition via the generation of neoantigens,⁹ we did not find a clinical benefit for the addition of durvalumab in neither the splicing factor-mutant nor splicing factor wild-type cohort. The absence of differences in the immune landscape by splicing factor mutation status as assessed by flow cytometry and gene expression analyses could be a potential explanation for the lack of ORR and OS benefit with anti-PD-L1 therapy in splicing factor-mutant MDS and AML. However, more detailed analyses including the characterization of the generated neoantigens would be helpful to elucidate whether these neoantigens are indeed immunogenic and can be therapeutically targeted. Furthermore, better preclinical models are needed that more closely recapitulate the complexity of the human immune system and the impact of immune checkpoint blockade with regards to the immunosuppressive microenvironment in the bone marrow niche and the timing of immune checkpoint inhibition. One step toward a better understanding of the immune microenvironment are humanized mouse models, which recapitulate the human immune system better and might provide further insight into the disease biology.¹⁸

Our study was limited by the post hoc nature of the analyses. Furthermore, samples were limited to certain pretreatment timepoints, which precludes the assessment of any changes while patients were receiving treatment. Although it is possible that there are differences in the disease biology between the type of splicing mutation and the disease context (AML vs MDS), we had to pool samples and patients across splicing mutation type for some of the analyses due to the small number of patients in each group. Despite pooling patients across splicing factor mutation types, our analysis might have been underpowered to detect statistically significant differences in ORR and OS especially in MDS patient subgroup. Similarly, we were not able to analyze the influence of the VAF of a given splicing factor mutation on outcomes and disease biology.

In conclusion, the addition of the anti-PD-L1 antibody durvalumab to AZA did not improve ORR or OS among older patients with newly diagnosed AML and HR-MDS independent of the presence or the absence of RNA splicing factor mutations. The absence of differences in the immune landscape by splicing factor mutation status as assessed by flow cytometry and gene expression analyses could be a potential explanation for the lack of benefit with anti-PD-L1 therapy in splicing factor-mutant MDS and AML.

Supplemental Material

sj-docx-1-tah-10.1177_20406207251347344 – Supplemental material for Integrated Immune Landscape Analysis of RNA Splicing Factor-Mutant AML and Higher risk MDS Treated with Azacitidine ± Durvalumab

Supplemental material, sj-docx-1-tah-10.1177_20406207251347344 for Integrated Immune Landscape Analysis of RNA Splicing Factor-Mutant AML and Higher risk MDS Treated with Azacitidine ± Durvalumab by Jan Philipp Bewersdorf, Vanessa Hasle, Rory M. Shallis, Ethan Thompson, Daniel Lopes de Menezes, Shelonitda Rose, Isaac Boss, Lourdes Mendez, Nikolai Podoltsev, Maximilian Stahl, Tariq Kewan, Stephanie Halene, Torsten Haferlach, Brian A. Fox and Amer M. Zeidan in Therapeutic Advances in Hematology

Supplemental Material

sj-jpg-2-tah-10.1177_20406207251347344 – Supplemental material for Integrated Immune Landscape Analysis of RNA Splicing Factor-Mutant AML and Higher risk MDS Treated with Azacitidine ± Durvalumab

Supplemental material, sj-jpg-2-tah-10.1177_20406207251347344 for Integrated Immune Landscape Analysis of RNA Splicing Factor-Mutant AML and Higher risk MDS Treated with Azacitidine ± Durvalumab by Jan Philipp Bewersdorf, Vanessa Hasle, Rory M. Shallis, Ethan Thompson, Daniel Lopes de Menezes, Shelonitda Rose, Isaac Boss, Lourdes Mendez, Nikolai Podoltsev, Maximilian Stahl, Tariq Kewan, Stephanie Halene, Torsten Haferlach, Brian A. Fox and Amer M. Zeidan in Therapeutic Advances in Hematology

Supplemental Material

sj-jpg-3-tah-10.1177_20406207251347344 – Supplemental material for Integrated Immune Landscape Analysis of RNA Splicing Factor-Mutant AML and Higher risk MDS Treated with Azacitidine ± Durvalumab

Supplemental material, sj-jpg-3-tah-10.1177_20406207251347344 for Integrated Immune Landscape Analysis of RNA Splicing Factor-Mutant AML and Higher risk MDS Treated with Azacitidine ± Durvalumab by Jan Philipp Bewersdorf, Vanessa Hasle, Rory M. Shallis, Ethan Thompson, Daniel Lopes de Menezes, Shelonitda Rose, Isaac Boss, Lourdes Mendez, Nikolai Podoltsev, Maximilian Stahl, Tariq Kewan, Stephanie Halene, Torsten Haferlach, Brian A. Fox and Amer M. Zeidan in Therapeutic Advances in Hematology

Footnotes

Acknowledgements

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: J.B. is supported by the Edward P. Evans Foundation. A.M.Z. is a Leukemia and Lymphoma Society Scholar in Clinical Research. S.H. was supported by NIH/NIDDK R01DK124788, NIH/NCI R01CA266604, NIH/NCI R01CA222518, NIH/NCI R01CA253981, The Frederick A. Deluca Foundation and the Edward P. Evans Foundation.

Author’s note

Disclaimer: Part of this work was presented as a poster presentation at the 66th Annual Meeting of the American Society of Hematology 2024.

Declarations

ORCID iDs

Jan Philipp Bewersdorf

Rory M. Shallis

Amer M. Zeidan

Supplemental material

Supplemental material for this article is available online.

References

Stanley

Abdel-Wahab

. Dysregulation and therapeutic targeting of RNA splicing in cancer. Nat Cancer 2022; 3(5): 536–546.

Chen

Benbarche

Abdel-Wahab

. Splicing factor mutations in hematologic malignancies. Blood 2021; 138(8): 599–612.

Stahl

Derkach

Farnoud

, et al. Molecular predictors of immunophenotypic measurable residual disease clearance in acute myeloid leukemia. Am J Hematol 2023; 98(1): 79–89.

Döhner

Wei

Appelbaum

, et al. Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN. Blood 2022; 140: 1345–1377.

Malcovati

Stevenson

Papaemmanuil

, et al. SF3B1-mutant MDS as a distinct disease subtype: a proposal from the International Working Group for the Prognosis of MDS. Blood 2020; 136(2): 157–170.

Döhner

DiNardo

Appelbaum

, et al. Genetic risk classification for adults with AML receiving less-intensive therapies: the 2024 ELN recommendations. Blood 2024; 144(21): 2169–2173.

Steensma

Wermke

Klimek

, et al. Phase I First-in-Human Dose Escalation Study of the oral SF3B1 modulator H3B-8800 in myeloid neoplasms. Leukemia 2021; 35(12): 3542–3550.

Bewersdorf

Stahl

Taylor

, et al. E7820, an anti-cancer sulfonamide, degrades RBM39 in patients with splicing factor mutant myeloid malignancies: a phase II clinical trial. Leukemia 2023; 37(12): 2512–2516.

De Neef

Thomas

, et al. Pharmacologic modulation of RNA splicing enhances anti-tumor immunity. Cell 2021; 184(15): 4032–4047.e4031.

10.

Zeidan

Boss

Beach

, et al. A randomized phase 2 trial of azacitidine with or without durvalumab as first-line therapy for higher-risk myelodysplastic syndromes. Blood Adv 2022; 6(7): 2207–2218.

11.

Zeidan

Boss

Beach

, et al. A randomized phase 2 trial of azacitidine with or without durvalumab as first-line therapy for older patients with AML. Blood Adv 2022; 6(7): 2219–2229.

12.

Zeidan

Bewersdorf

Hasle

, et al. Integrated genetic, epigenetic, and immune landscape of TP53 mutant AML and higher risk MDS treated with azacitidine. Ther Adv Hematol 2024; 15: 20406207241257904.

13.

Wang

Zhuo

Wang

, et al. Identification and validation of a prognostic risk-scoring model based on ferroptosis-associated cluster in acute myeloid leukemia. Front Cell Dev Biol 2022; 9: 800267.

14.

Shimony

Bewersdorf

Shallis

, et al. Hypomethylating agents plus venetoclax compared with intensive induction chemotherapy regimens in molecularly defined secondary AML. Leukemia 2024; 38(4): 762–768.

15.

Senapati

Urrutia

Loghavi

, et al. Venetoclax abrogates the prognostic impact of splicing factor gene mutations in newly diagnosed acute myeloid leukemia. Blood 2023; 142(19): 1647–1657.

16.

Jin

Zhang

, et al. Venetoclax combined with azacitidine and homoharringtonine in relapsed/refractory AML: a multicenter, phase 2 trial. J Hematol Oncol 2023; 16(1): 42.

17.

Wang

Pineda

JMB

Kim

, et al. Modulation of RNA splicing enhances response to BCL2 inhibition in leukemia. Cancer Cell 2023; 41: 164–180.

18.

Liu

Teodorescu

Halene

, et al. The coming of age of preclinical models of MDS. Front Oncol 2022; 12: 815037.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.06 MB

0.32 MB

0.33 MB