Characterisation and prognostic impact of ZRSR2 mutations in myeloid neoplasms

Characterisation and prognostic impact of ZRSR2 mutations in myeloid neoplasms | 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 Article Characterisation and prognostic impact of ZRSR2 mutations in myeloid neoplasms Aref Al-Kali, Mahmoud Yacout, Bahga Katamesh, Yazan Jabban, Rong He, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4590446/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Sep, 2024 Read the published version in Leukemia → Version 1 posted 9 You are reading this latest preprint version Abstract The ZRSR2 gene is a member of the spliceosome gene family which are frequently mutated in myeloid neoplasms. ZRSR2 mutations ( ZRSR2m ) occur in less than 5% of MDS, CMML, and AML. Our study included 164 ZRSR2m patients (98.8% males) and 98 ZRSR2wt MDS control cohort. In the ZRSR2m group, there were 53 MDS (32%), 39 CCUS (24%), 33 MPN (20%), 23 MDS/MPN overlap (14%), 15 AML (9%), and 1 MPAL (0.6%). Most MDS patients were the low blast subtype (n=37, 70%). Twenty-seven MDS patients (51%), and 23 CCUS patients (59%) had absolute monocyte count ≥0.5 x10 9 /L and 18 of 23 MDS/MPN overlap were CMML (78%). Mutations in ZRSR2 were spread across the entire gene. The median number of co-mutations was 2, with TET2 (51%) and ASXL1 (32%) being the most common. U2AF1 and SRSF2 , previously described as mutually exclusive with ZRSR2 , were found in 10.4% of patients. Median overall survival (OS) was 51 months, and significantly varied among MNs (p=0.004). ZRSR2m MDS patients had better mOS than the MDS control cohort with ZRSR2wt (35 vs 22 months, p=0.013). ZRSR2m patients with isolated TET2 co-mutation and higher hemoglobin showed improved survival, while patients with RUNX1m , higher WBC count showed worse OS. Health sciences/Diseases/Cancer/Haematological cancer/Myelodysplastic syndrome Health sciences/Diseases/Cancer/Cancer genetics Health sciences/Diseases/Haematological diseases/Haematological cancer/Myelodysplastic syndrome Health sciences/Diseases/Haematological diseases/Haematological cancer/Myeloproliferative disease Health sciences/Pathogenesis/Clinical genetics/Cancer genetics Figures Figure 1 Figure 2 Figure 3 Figure 4 Key points ZRSR2 mutations carry a favorable prognosis among chronic myeloid neoplasms. High frequency of CCUS among ZRSR2m patients. ZRSR2 mutations association with elevated monocyte count and myelomonocytic differentiation. Introduction The Zinc finger (CCCH type), RNA-binding motif, and serine/arginine-rich 2 ( ZRSR2 ) gene, which is located on the X chromosome (Xp22.1) is a member of the RNA splicing machinery family of genes which also includes SF3B1 , SRSF2 , and U2AF1 .[ 1 – 3 ] ZRSR2 normally encodes for a protein that associates with U2AF2/U2AF1 heterodimer and SRSF2 , which are involved in the recognition of 3’-intron splice sites early in the spliceosome assembly process.[ 4 – 7 ] ZRSR2 mutations (m) are found in 1.2% of all cancers with the highest prevalence in lung adenocarcinoma, colon adenocarcinoma, and high-grade ovarian serous adenocarcinoma.[ 8 , 9 ] Thol et al. found that spliceosome genes mutations were found in 35% of myelodysplastic syndrome (MDS) patients, as one of the most common in the disease. They also found ZRSR2, U2AF1, and SRSF2 as being mutually exclusive with each other.[ 3 , 10 ] Alterations in ZRSR2 have been reported in 4% of MDS patients, 8% of therapy-related MDS, and 4% of MDS with increased blasts 2.[ 8 , 11 ] ZRSR2m are also seen across different myeloid neoplasms (MN) including primary and secondary acute myeloid leukemia (AML), chronic myelomonocytic leukemia (CMML), myeloproliferative neoplasm (MPN) and blastic plasmacytoid dendritic cell neoplasm (BPCDN) with lower frequency than MDS. [ 1 , 8 , 12 – 14 ] Contrary to the mutational hotspots found in other members of the splicing machinery genes, Damm et al, reported that ZRSR2 m were spread across the whole gene and consisted mainly of nonsense, frameshift, and splice site mutations with only a few missense mutations.[ 1 , 2 ] Studies investigating ZRSR2 in myeloid neoplasms were limited by the small number of patients having ZRSR2m (25 in one paper), and most failed to show significant association with other mutations or impact on survival analysis.[ 3 ] The only co-mutation that showed significant association with ZRSR2 was TET2 (p < 0.001), indicating a potential relationship or co-occurrence between the two genes.[ 2 , 15 , 16 ] In one study, cells with mutated ZRSR2 gene showed an increase in precursor cells for macrophages and a decrease in precursor cells for erythroid cells.[ 4 ] Additionally, Malcovati et al. reported that TET2 with SRSF2 or ZRSR2 as co-mutations were predictive of myelomonocytic phenotype and showed higher hemoglobin (Hgb) levels and monocyte counts. [ 17 ] Damm et al. demonstrated that ZRSR2m MDS patients were mostly associated with increased blasts. [ 2 ] We hereby report our center experience with ZRSR2m in patients with myeloid (and premyeloid) neoplasms. Methods The study was conducted in a single institution, Mayo Clinic, across its 3 campuses. Next-generation sequencing (NGS) was performed in the molecular hematopathology laboratory mainly on bone marrow (BM) samples (92% of ZRSR2m were found on BM NGS) with the NGS gene panel including 42–47 genes, between 2016–2023.[ 18 ] [supplemental: methods] After obtaining institutional review board approval, patients’ information (including age and gender), clinical characteristics, labs, treatment, treatment response, results of BM morphology, cytogenetics, and molecular studies were abstracted. Myeloid neoplasms were classified and subclassified according to the 5th edition of the World Health Organization (WHO) classification of haematolymphoid tumours 2022.[ 19 ] Response to treatment for MDS patients was determined using revised IWG 2023 response criteria for MDS, and response to treatment for AML patients was determined using ASH diagnosis and management of AML in adults; 2022 ELN recommendations from an international expert panel.[ 20 – 22 ] International prognostic scoring system-molecular and -revised (IPSS-M and IPSS-R) for MDS risk stratification were calculated using mds-risk-model.com.[ 23 , 24 ] BlueSky Statistics V10.3.1 was used for data analysis. Overall Survival (OS) and median follow-up were measured using Kaplan-Meier estimates and Cox regression analysis from the date of NGS to death or last follow-up. A sample of 98 MDS ZRSR2wt control patients were used for survival comparison with ZRSR2m . Cox regression and binary time-dependent covariates were used to measure survival for patients receiving hematopoietic stem cell transplant (HSCT), starting from the date of transplant. Cox proportional hazard regression analysis was used to run the multivariate analysis to determine independent prognostic factors for OS. P values < 0.05 were considered statistically significant. Results Patient Characteristics: NGS was performed clinically on 9320 samples. Among those, 164 patients were found to have the ZRSR2m genotype, 162 of which were male (98.8%) with only 2 female patients (1.2%). NGS was analyzed from BM samples for 151 patients (92.1%) vs only 13 peripheral blood (PB) samples (7.9%). Median patient age was 74 (range 31–92 years old). The most common diagnosis was MDS (n = 53, 32.3%), clonal cytopenia of undetermined significance (CCUS) (n = 39, 23.8%), MPN (n = 33, 20.1%), MDS/MPN overlap (n = 23, 14%), AML (n = 15, 9.1%) and 1 patient diagnosed as mixed phenotype acute leukemia (MPAL). Fifteen (9%) patients had concurrent non-myeloid hematological malignancies diagnosed at the time of the NGS; 2 patients had concurrent chronic lymphocytic leukemia (CLL) and CCUS, multiple myeloma in 3 patients with CCUS and 1 patient with MDS, diffuse large B-cell lymphoma in 1 AML and 1 MDS/MPN overlap patient. While only 15 patients (9.1%) received chemotherapy or radiotherapy prior to their diagnosis, 29 patients (17.7%) received prior immunotherapy with the highest prevalence among CCUS patients (n = 13, 33% of CCUS patients). (Table 1 ) Abnormal cytogenetics were found in 54 patients (33%), with + 8 (16) and -Y (11) being the most common. (supplemental table 2) Table 1 ZRSR2m patients’ characteristics Number 164 Median age, years (Range) 74 (31, 92) Gender (Male), n (%) 162 (98.8) BM blasts (%) 151 (92.1) PB blasts (%) 13 (7.9) Diagnosis at NGS AML (%) 15 (9.1) MDS (%) 53 (32.3) 5q 1 (1.9) SF3B1 2 (3.8) BiTP53 2 (3.8) LB 37 (69.8) IB1 2 (3.8) IB2 6 (11.3) F 3 (5.7) MDS with Monocytes ≥ 0.5 (%) 27 (50.9) MDS/MPN (%) 23 (14) CMML 18 (78.3) Unclassifiable 5 (21.7) MPN (%) 33 (20.1) PV 2 (6.1) ET 1 (3) MF 27 (81.8) Unspecified 2 (6.1) Mast Cell Leukemia 1 (3) CCUS (%) 39 (23.8) CCUS with Monocytes > = 0.5 23 (59) MPAL (%) 1 (0.6) Progression into CMML or MDS/MPN overlap (from CCUS, MDS, MPN) (%) 10 (8) Progression into AML (%) 13 (7.9) Cytogenetics Normal (%) 109 (66.9) Abnormal (%) 54 (33.1) Prior Chemotherapy or Radiotherapy (%) 15 (9.1) Diagnoses associated with prior immunotherapy (%) 29 (17.7) AML 1 (6.7%) MDS 7 (13.2%) MDS/MPN 6 (26.1%) MPN 2 (6.1%) CCUS 13 (33.3%) Abbreviations: BM, bone marrow; PB, Peripheral blood; AML, acute myeloid leukemia; MDS, myelodysplastic syndrome; LB, low blast; IB, increased blast; f, fibrotic; MDS/MPN, myelodysplastic/myeloproliferative neoplasms; CMML, chronic myelomonocytic leukemia; MPN, myeloproliferative neoplasms; PV, Polycythemia Vera; ET, Essential Thrombocythemia; MF, Myelofibrosis CCUS, clonal cytopenia of unknown significance. Seventy-eight patients (48%) were diagnosed prior to our inhouse NGS (median time to NGS was 31.5 months). (supplemental table 7) Out of 10 patients diagnosed as CCUS, 8 (80%) progressed to MDS by the time of the NGS. One AML patient who achieved remission prior to NGS was diagnosed as CCUS by the time of NGS (9 years after initial AML diagnosis) harboring both ZRSR2 and IDH1. Two (7.7%) and 5 (11.5%) MDS patients progressed to AML and MDS/MPN overlap, respectively by the time of NGS. MPN was the most common diagnosis prior to NGS (27, followed by MDS at 26 patients), and none of the MPN patients progressed to AML or MDS/MPN overlap by the time of NGS, however, 9 out of 10 patients diagnosed as essential thrombocytosis (ET) (most common MPN diagnosis prior to NGS, 10 (37%) patients), and 4 out of 6 diagnosed as polycythemia vera (PV) progressed to myelofibrosis (MF) by the time of the NGS. Among MDS, the subtypes were low blast (MDS-LB) (n = 37, 69.8%), increased blast-2 (MDS-IB2) (n = 6, 11.3%), MDS with fibrosis (MDS-f) (n = 3, 5.7%), increased blasts-1 (MDS-IB1) (n-2, 3.8%), MDS-BiTP53 (n-2, 3.8%), MDS- SF3B1 (n-2, 3.8%), and MDS-5q (n = 1, 1.9%). Eighteen of 23 MDS/MPN Overlap were CMML (78%) and 5 were unclassifiable (21.7%). Myelofibrosis (MF) was the most common MPN (n = 27, 81.8%), with 2 unspecified (6.1%), 2 polycythemia vera (PV), and 1 case of each essential thrombocythemia (ET) (3%) and mast cell leukemia. Risk stratification among MDS patients by IPSS-M scoring was low risk (n = 16, 30.2%), moderate low risk (n = 13, 24.5%), high risk (n = 12, 22.6%), very low risk (n = 6, 11.3%), very high risk (n = 4, 7.5%), and moderate high risk (n = 2, 3.8%). (Fig. 3 : A, supplemental Figs. 1, 2, 3) Twenty-four (45.3%) of MDS patients were stratified as low risk according to IPSS-R. (supplemental table 8) Median BM blasts among the cohort was 2 (range, 0–91), median Hgb was 9.6 x10 9 /L, and median platelets was 134 x10 9 /L. (supplemental table 1 ) Twenty-seven MDS patients (51%), and 23 CCUS patients (59%) had absolute monocyte count ≥ 0.5 x10 9 /L. (Table 1 ) ZRSR2 mutations Characteristics Median pathogenic ZRSR2m VAF (mVAF) was (range, 2-100). Gender-corrected VAF was 35 (range, 1–66) and was 50 among females. Gender corrected ZRSR2m mVAF was significantly different between different diagnostic groups (AML 41%, MDS 33.5%, MDS/MPN overlap 41%, MPN 29%, CCUS 31.5, p = 0.04) (supplemental Fig. 4). Statistically significant difference was also found between MDS subtypes when compared according to gender corrected VAF (p = 0.04) (supplemental Fig. 5) with IB1 having the highest mVAF. There was no statistically significant difference in gender-corrected VAF between IPSS-M groups (p = 0.2), between patients who progressed or did not progress to AML (p = 0.5), and between MPN subtypes (p = 0.2). Additionally, there was no correlation between mVAF, or gender corrected mVAF, and BM or PB blasts. Multiple ZRSR2 mutations were found in 7 patients (4.3%) including 1 CCUS, 4 MDS, and 2 CMML. Forty-nine percent of mutations occurred in Pre-ZF1 domain of the gene, 27% in the UHM domain and 13% in Post-ZF2 domain. ZF1 and ZF2 carried 4% and 6% of the mutations, respectively, and RS domain carried only 1% of the mutations. (Fig. 1 : C, Supplemental table 3) Mutations were spread across the entire length of the gene with no mutational hotspots. (Fig. 1 : A) The most changed nucleotide was c.827 (n, 14) followed by c.376C > T (n, 9), and c.203 + 1G > A (n, 8). (supplemental table 6) Most common mutation type was nonsense (n = 69, 42%), followed by frameshift (n = 56, 34%), and splice site (n = 39, 24%). (Fig. 1 : B, Supplemental table 3) No correlation was found between mutation type and MN classification, BM or PB blasts, or ZRSR2 mVAF(p = 0.07). Co-mutations The median number of co-mutations was 2 (range, 0–6). The most commonly co-mutated gene pathway was the DNA methylation (n = 98, 60%), followed by chromatin modification (n = 74, 45%), and signaling pathway (n = 66, 40%) (supplemental Fig. 7). Only 1 patient out of 164 had a mutation in the cohesion component gene mutations. A significant correlation was found between MN classification and number of co-mutations in ZRSR2m patients (p < 0.001) (supplemental Fig. 6). On linear regression, CCUS had fewer co-mutations than all other diagnoses, and MDS had fewer co-mutations than AML (p = 0.0004), and MDS/MPN overlap (p = 0.049). The most common co-mutation was TET2 which was present in 84 patients (51%), 42% of which had multiple TET2 mutations. (Fig. 2 , Table 2 ) A significant correlation was found between MN classification and presence of TET2 in ZRSR2m patients (p = 0.007) and were found with highest frequency among MDS/MPN overlap patients (70%) followed by CCUS (64%) and AML (60%). TET2 showed no correlation with presence of elevated monocyte count (p = 0.8), and despite the higher frequency of CMML among TET2m vs TET2wt (15.5% vs 6.2%, p = 0.08). Median Hgb concentration for TET2m and TETwt was 9.95 vs 9.3 x10 9 /L, respectively (p = 0.17). Other common co-mutations were ASXL1 (n = 52, 32%), and JAK2 (n = 31, 19%). (Fig. 2 ) JAK2m was mainly present in patients with MPN (70%) compared to other MNs (p < 0.001) and was present in 7% of MDS/MPN overlap patients and 1 AML patient. (supplemental table 5) A significant correlation was also found between MN classification and RUNX1 co-mutations (p = 0.008), and they were found in 23 patients (14%) with highest prevalence among AML (n = 5, 33%) and MDS (n = 12, 23%). Table 2 Co-mutational pattern in ZRSR2 -mutated MN patients of the major co-mutations Co-mutation Total (164) AML CCUS MDS MDS/MPN MPN Median no. of co-mutations (range) 2 (0–6) 3 (1–6) 1 (0–3) 2 (0–4) 2 (0–6) 2 (1–5) Isolated ZRSR2m (%) 13 (8) 0 (0) 6 (15) 5 (9) 1 (4) 0 Major co-mutations, , n (%) TET2 (multiple, n) 84 (51) (35) 9 (60) (3) 25 (64) (8) 25 (47) (14) 16 (70) (9) 9 (27) (1) ASXL1 52 (32) 5 (33) 8 (20) 18 (34) 7 (30) 14 (42) JAK2 31 (19) 1 (7) 0 0 7 (30) 23 (70) RUNX1 23 (14) 5 (33) 1 (3) 12 (23) 3 (13) 2 (6) EZH2 14 (9) 2 (13) 0 8 (15) 3 (13) 1 (3) U2AF1 9 (6) 3 (6) 1 (3) 3 (6) 1 (4) 1 (3) SRSF2 8 (5) 1 (7) 1 (3) 5 (9) 1 (4) 0 TP53 8 (5) 3 1 4 0 0 CBL 8 (5) 1 0 3 4 0 SF3B1 7 (4) 0 2 (5) 2 (4) 1 (4) 2 (6) Other members of the spliceosome family of genes were present in 14.7% of patients, including U2AF1 9 (5.5%), SRSF2 8 (5%), and SF3B1 7 (4%) patients. In ZRSR2m patients with co-mutated spliceosome genes, the gender-corrected mVAF value for ZRSR2m was within 5% of the mVAF for SRSF2 and U2AF1 but significantly lower than the mVAF for SF3B1 (40.5 vs 41 for SRSF2, 25.5 vs 28 for U2AF1, 5 vs 34 for SF3B1), indicating possibly that ZRSR2m was a subclone in the setting of SF3B1m . Only 13 patients (4.3%) had isolated ZRSR2 mutations, and included 6 CCUS, 5 MDS, 1 MDS/MPN overlap, and 1 MPAL. The median VAF for isolated ZRSR2m patients was similar to patients with co-mutations (69.5 and 70, respectively). Median IPSS-M score was lower in patients with isolated ZRSR2m (-1.18) compared to patients with co-mutations (-0.74) (p = 0.02). There was no difference in BM blasts for isolated ZRSR2m and patients with other co-mutations, (1% vs 2% respectively, p = 0.15), or cytogenetic abnormalities between isolated and co-mutated cases (42% vs 32% abnormal, p = 0.5). Response to therapy and progression Of 164 patients, 108 (66%) received treatment, including 39 MDS, 28 MPN, 17 MDS/MPN overlap, 12 AML, 11 CCUS, and 1 MPAL. Of 12 AML patients receiving treatment, 8 (66.7%) achieved response to therapy with 2 (16.7%) complete remissions with incomplete hematologic recovery (CRi), and 6 (50%) with complete remission (CR), of whom 1 relapsed. (supplemental Fig. 9: B) Among 39 ZRSR2m MDS receiving treatment, 7 (18%) had hematological improvement (HI), 3 (7.7%) had complete remission with limited recovery (CR L ), 1 CR equivalent (2.6), and 3 (7.7%) had CR, of which 2 relapsed. (supplemental Fig. 9: A) Median time to response from treatment initiation date among AML and MDS patients was 1 and 3 months, respectively. (supplemental table 9) Hematopoietic stem cell transplant (HSCT) was performed in 21 patients (12.8%) including 3 AML, 10 MDS, 4 MDS/MPN overlap, and 2 MPN. The median time from NGS to transplant was 4 months. The most used medications were hypomethylating agents (HMA) used in 22% of the patients, including 20 (37.7%) MDS, 7 (30.4%) of MDS/MPN overlap, and 4 (26.7%) of AML. (supplemental Fig. 8) The combination of HMA and venetoclax was also used in 15 patients including 3 AML, 6 MDS, and 2 MDS/MPN overlap cases. (supplemental table 10) Erythropoietin stimulating agents (ESA) were given in 21 patients including 24.5% of MDS, 13% of MDS/MPN overlap, 9% of AML and 5% of CCUS cases. Oral decitabine and cedazuridine combination therapy was given for 6 MDS and 1 CCUS. (table showing response to therapy) Fig. 3 : B shows the progression of mVAF in a ZRSR2m MDS patient among ZRSR2 and the co-mutations and their changes after therapy and HSCT. (Fig. 3 : B) Thirteen patients (8.7%) progressed to AML, 9 from MDS (17%), 2 from MDS/MPN overlap (8.7%), and 2 from MPN (6%), none of these patients had isolated ZRSR2 and only 1 MDS patient had Isolated TET2 as a co-mutation. Among MDS cohort, LB showed significantly lower rate of AML progression (8%) compared to IB2 (50%), BiTP53 (50%), and F (33%) (p = 0.02). (supplemental table 4) The median time to progression from NGS date was 12 months (range, 0–52 months). (Fig. 3 : C) MDS-f had longer median time to progression to AML compared to MDS-IB2 (23.5 vs 6, p = 0.03). Ten patients (8%) progressed into CMML or MDS/MPN overlap from CCUS, MDS, or MPN. Survival There were 68 deaths, with median overall survival (mOS) period of 51 months, and median follow up of 35 months. (Fig. 4 : A) ZRSR2m MDS patients had better mOS compared to the MDS control group with ZRSR2wt (35 months vs 22 months, p = 0.013). (Fig. 4 : B) mOS of ZRSR2m patients varied significantly among different MNs (p = 0.004), with MPAL and AML having the shortest mOS at 3 and 9 months, respectively, followed by MDS/MPN overlap at 27, MPN at 39. MDS and CCUS had the longest mOS at 61 and 56 months, respectively. (Fig. 4 : C) ZRSR2m patients with spliceosome and tumor suppressor gene (TSG) gene pathway co-mutations showed worse survival compared to patients without these mutations (25 vs 56 months for spliceosome genes, p = 0.02 and 20 vs 51 months for TSG, p = 0.04). (supplemental Figs. 10, 13) Patients with TET2 as an isolated co-mutation had better survival (not reached vs 30 months, p = 0.01), and in contrast, patients with RUNX1 co-mutations had worse survival (28 vs 52 months, p = 0.02). (Fig. 4 : D, E) Patients with isolated ZRSR2m showed good survival (not reached vs 40, p = 0.2). There was no difference in survival according to other co-mutated genes or gene pathways. Patients with PB blasts < 5% had better mOS of 52 months vs 9 months in patients with PB blasts ≥ 5% (HR = 0.027, p < 0.001). (supplemental Fig. 11) Higher Hgb concentration showed improved survival (HR = 0.78, p < 0.001), while patients with increased WBCs count (HR = 1.02, p < 0.001), absolute neutrophil count (ANC) (HR = 1.04, p = 0.01), absolute monocyte count (AMC) (HR = 1.2, p = 0.008), BM blasts (HR = 1.02, p < 0.001), PB blasts (HR = 1.03, p < 0.001) showed worse mOS. Patients with higher number of co-mutations showed worse OS (HR = 1.49, p < 0.001). Patients with abnormal cytogenetics had shorter survival periods compared to patients with normal cytogenetics (25 vs 61 months, p < 0.001). (supplemental Fig. 12) Overall survival did not vary with age, HSCT, MDS subtype, IPSS-M group, ZRSR2m site or type. (supplemental Fig. 14) On multivariate analysis, only higher Hgb concentration (HR = 0.8, p = 0.004), PB blasts > 5% (HR = 2.2, p = 0.02), and abnormal cytogenetics (HR = 1.9, p = 0.01) retained significance while isolated TET2m and RUNX1m lost significance. (Table 3 ) Table 3 Multivariate analysis results. (*) indicates statistical significance. Hazard Ratio p value Confidence interval Isolated TET2 0.5885 0.2015 0.2608–1.3277 Hemoglobin 0.8208 0.0036 ** 0.7185–0.9376 RUNX1 1.6112 0.1374 0.8587–3.0232 Peripheral circulating blasts 2.2251 0.0165 * 1.1572–4.2785 Abnormal cytogenetics 1.9319 0.0098 ** 1.172–3.1844 Molecular dynamics Sequential NGS (S1-NGS) was performed in 55 out of the 164 patients (33.5%), 50 (91%) of them continued to have ZRSR2m . Only 19 patients out of 55 (34.5%) performed a second sequential NGS (S2-NGS) and 17 (89.5%) of them continued to have ZRSR2m , and out of the 3 patients who cleared the mutation on S1-NGS, only one performed S2-NGS and did not show re-emergence of the mutation. Out of the 21 patients who had HSCT, 4 (19%) performed sequential NGS posttransplant and all of them negative NGS with complete clearance of ZRSR2m and the co-mutated genes. Median number of co-mutations remained 2 in the first NGS and throughout both S1-NGS and S2-NGS. mVAF for ZRSR2m was 80% and 89% for S1-NGS and S2-NGS, respectively, showing a statistically significant increase of 11% for S1-NGS from the first NGS (p = 0.01). Discussion Our study has the largest cohort of ZRSR2m MN patients (164) and includes premyeloid, chronic myeloid and acute leukemias. The cohort consisted predominantly of males with only 2 female patients which confirms previous literature of ZRSR2m’s male predominance and suggested theory that it functions mainly as an X-linked recessive tumor suppressor gene. [ 2 ] We also show improved survival among MDS patients harboring ZRSR2m which suggests that ZRSR2 mutations carry a favorable prognosis. In accordance with previous studies, ZRSR2m was found across different MNs, however, our study found a notable association with a higher incidence of CCUS diagnoses which was the second most common diagnosis following MDS, which is a novel finding. Among ZRSR2m MDS group, the most common subtype was MDS-LB constituting 70% of MDS followed by MDS-IB2 with only 11% which is different from prior literature stating that ZRSR2m MDS were mostly subclassified as IB1 and IB2. [ 2 , 17 ] Additionally, the most common risk stratification of MDS and CCUS patients according to IPSS-M and IPSS-R was low risk, followed by moderate low in IPSS-m. Only 17% of ZRSR2m MDS progressed to AML which is a low rate compared to current literature’s 30–40%.[ 25 , 26 ] The above-mentioned constellation of ZRSR2m being associated with pre-MNs disorders (CCUS), lower-grade of MDS and lower rate of AML progression suggests that the mutation carries a favorable prognosis among chronic myeloid neoplasms, especially in isolated TET2m group. Madan et al described an increase in colony forming unit-macrophage (CFU-M) among CD34 + cells that were ZRSR2 inactivated which was supported clinically in our study as we found that over half of the ZRSR2m MDS and CCUS cohort had elevated absolute monocyte count (≥ 0.5 x10 9 /L).[ 4 ] The majority of MDS/MPN overlap patients were diagnosed as CMML, furthermore, about 8% of patients originally diagnosed as CCUS, MDS or MPN progressed or were re-diagnosed as CMML later. These findings indicate a possible association between ZRSR2 and monocytic differentiation. Malcovati et al. described that an association between TET2 and ZRSR2 was predictive of myelomonocytic phenotype, and showed significantly higher Hgb levels and monocyte count. However, among our ZRSR2m cohort, no correlation was shown for TET2m vs TETwt regarding monocyte count.[ 17 ] Moreover, There was a slightly increased frequency of CMML among TET2m , but failed to show significance (p = 0.08). Interestingly, MPN was found in 20% of ZRSR2m patients and consisted mainly of MF (61% of which progressed from PV or ET prior to NGS) and was associated with increased frequency of JAK2 mutations as expected (70%). This raises the possibility of acquiring ZRSR2m later in MPN progression into MF. Our study demonstrated a strong association between ZRSR2m and TET2m (51% of patients) which is consistent with previous studies.[ 2 , 15 ] Presence of TET2 m as an isolated co-mutation was shown to be associated with longer survival among ZRSR2m MN patients, and had a significant difference on MN classification with highest prevalence among MDS/MPN overlap patients. Despite past studies with smaller number of ZRSR2m MN patients proposing that the gene is mutually exclusive with two other members of the spliceosome family of genes (U2AF1 and SRSF2), 10.4% of our ZRSR2m MN patients had either U2AF1 (5.5%) or SRSF2 (4.9%) .[ 3 ] Survival among ZRSR2m MN patients was affected mostly by the MN diagnosis (AML showing worst survival) and expectedly by PB blasts > 5%. Other factors that affected survival positively was higher Hgb concentration and the presence of isolated TET2m. On the contrary, presence of RUNX1m and cytogenetic abnormalities affected survival negatively. Our study was limited by data collection from a single institution, the retrospective nature of the study, lack of longer follow up, small cohort size due to rarity of the gene. Additionally, NGS was not done at diagnosis in some of our cases but rather later which adds a time bias. In conclusion, the ZRSR2m was almost exclusively seen in males, with a striking increased frequency of CCUS patients. TET2m was the most common co-mutation and is linked to better survival especially as an isolated co-mutation. Over half of the patients with ZRSR2m MDS and CCUS had a higher absolute monocyte count indicating a possible association with monocytic differentiation. However, further studies are needed to confirm these findings. Declarations Acknowledgements: The protein diagram was generated using ProteinPaint (https://proteinpaint.stjude.org/). The Fishplots depicting clonal evolution were generated using https://github.com/chrisamiller/fishplot. Grants support: none Authorship Contributions : MY, BK, and AA planned the study, reviewed data, performed statistical analysis, and wrote the manuscript. RH and DV performed molecular analysis and reviewed the manuscript. PG performed cytogenetic analysis and reviewed the analysis. KB coordinated NGS data collection. DJ, JF, JP, AS, MH, KB, WH, MP, MS, and HA reviewed the paper and contributed patients. Conflict of Interest disclosure : The authors declare no competing financial interests. Data Availability: The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Previous publications: Part of this manuscript was accepted for poster publication at the European Hematology Association Congress 2024. References Yoshida, K., et al., Frequent pathway mutations of splicing machinery in myelodysplasia . Nature, 2011. 478(7367): p. 64–9. Damm, F., et al., Mutations affecting mRNA splicing define distinct clinical phenotypes and correlate with patient outcome in myelodysplastic syndromes . Blood, 2012. 119(14): p. 3211–8. Thol, F., et al., Frequency and prognostic impact of mutations in SRSF2, U2AF1, and ZRSR2 in patients with myelodysplastic syndromes . Blood, 2012. 119(15): p. 3578–84. Madan, V., et al., Aberrant splicing of U12-type introns is the hallmark of ZRSR2 mutant myelodysplastic syndrome . Nat Commun, 2015. 6: p. 6042. Gómez-Redondo, I., et al., Zrsr2 and functional U12-dependent spliceosome are necessary for follicular development . iScience, 2022. 25(2): p. 103860. Tronchère, H., J. Wang, and X.D. Fu, A protein related to splicing factor U2AF35 that interacts with U2AF65 and SR proteins in splicing of pre-mRNA . Nature, 1997. 388(6640): p. 397–400. Shen, H., et al., The U2AF35-related protein Urp contacts the 3' splice site to promote U12-type intron splicing and the second step of U2-type intron splicing . Genes Dev, 2010. 24(21): p. 2389–94. AACR Project GENIE: Powering Precision Medicine through an International Consortium . Cancer Discov, 2017. 7(8): p. 818–831. Inoue, D., et al., Minor intron retention drives clonal hematopoietic disorders and diverse cancer predisposition . Nat Genet, 2021. 53(5): p. 707–718. Chiereghin, C., et al., The Genetics of Myelodysplastic Syndromes: Clinical Relevance . Genes (Basel), 2021. 12(8). Hosono, N., Genetic abnormalities and pathophysiology of MDS . Int J Clin Oncol, 2019. 24(8): p. 885–892. Togami, K., et al., Sex-Biased ZRSR2 Mutations in Myeloid Malignancies Impair Plasmacytoid Dendritic Cell Activation and Apoptosis . Cancer Discov, 2022. 12(2): p. 522–541. Lindsley, R.C., et al., Acute myeloid leukemia ontogeny is defined by distinct somatic mutations . Blood, 2015. 125(9): p. 1367–76. Bouligny, I.M., K.R. Maher, and S. Grant, Secondary-Type Mutations in Acute Myeloid Leukemia: Updates from ELN 2022 . Cancers (Basel), 2023. 15(13). Papaemmanuil, E., et al., Clinical and biological implications of driver mutations in myelodysplastic syndromes. Blood, 2013. 122(22): p. 3616-27; quiz 3699. Garcia-Ruiz, C., et al., Concurrent Zrsr2 mutation and Tet2 loss promote myelodysplastic neoplasm in mice . Leukemia, 2022. 36(10): p. 2509–2518. Malcovati, L., et al., Driver somatic mutations identify distinct disease entities within myeloid neoplasms with myelodysplasia . Blood, 2014. 124(9): p. 1513–21. He, R., et al., Hybridization capture-based next generation sequencing reliably detects FLT3 mutations and classifies FLT3-internal tandem duplication allelic ratio in acute myeloid leukemia: a comparative study to standard fragment analysis . Modern Pathology, 2020. 33(3): p. 334–343. Khoury, J.D., et al., The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms . Leukemia, 2022. 36(7): p. 1703–1719. Zeidan, A.M., et al., Consensus proposal for revised International Working Group 2023 response criteria for higher-risk myelodysplastic syndromes . Blood, 2023. 141(17): p. 2047–2061. Döhner, H., et al., Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN . Blood, 2022. 140(12): p. 1345–1377. Kurzer, J.H. and O.K. Weinberg, Updates in molecular genetics of acute myeloid leukemia . Semin Diagn Pathol, 2023. 40(3): p. 140–151. Greenberg, P.L., et al., Revised international prognostic scoring system for myelodysplastic syndromes . Blood, 2012. 120(12): p. 2454–65. Bernard, E., et al., Molecular International Prognostic Scoring System for Myelodysplastic Syndromes . NEJM Evidence, 2022. 1(7): p. EVIDoa2200008. Volpe, V.O., G. Garcia-Manero, and R.S. Komrokji, Myelodysplastic Syndromes: A New Decade . Clin Lymphoma Myeloma Leuk, 2022. 22(1): p. 1–16. Menssen, A.J. and M.J. Walter, Genetics of progression from MDS to secondary leukemia . Blood, 2020. 136(1): p. 50–60. Additional Declarations There is NO conflict of interest to disclose. Supplementary Files Supplemental.docx Cite Share Download PDF Status: Published Journal Publication published 23 Sep, 2024 Read the published version in Leukemia → Version 1 posted Editorial decision: revise 03 Jul, 2024 Review # 2 received at journal 02 Jul, 2024 Review # 1 received at journal 21 Jun, 2024 Reviewer # 2 agreed at journal 18 Jun, 2024 Reviewer # 1 agreed at journal 17 Jun, 2024 Reviewers invited by journal 17 Jun, 2024 Editor assigned by journal 17 Jun, 2024 Submission checks completed at journal 17 Jun, 2024 First submitted to journal 16 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":465518,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Representation of \u003cem\u003eZRSR2 \u003c/em\u003emutations detected, positioned on the ZRSR2 protein and its functional domains. (B-C) Pie charts showing percentage of each \u003cem\u003eZRSR2\u003c/em\u003e mutation class (B), and domain affected.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4590446/v1/8a27e47d0d26fb179751a153.jpg"},{"id":60353771,"identity":"b7a4b439-08d3-44a5-b1c8-63938d88b763","added_by":"auto","created_at":"2024-07-15 23:42:50","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1587970,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Co-mutational pattern in 164 \u003cem\u003eZRSR2m\u003c/em\u003e MN patients. Each patient is represented by a column. (B) Bar chart showing frequency of all the co-mutations in 164 \u003cem\u003eZRSR2m\u003c/em\u003epatients. (C) Dependency wheel chart showing co-mutational pattern among the 10 most common mutations that accompanied \u003cem\u003eZRSR2\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4590446/v1/e4713127dea433451484e942.jpg"},{"id":60353770,"identity":"58be4a47-0898-48b3-be96-7253d14ae746","added_by":"auto","created_at":"2024-07-15 23:42:50","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":384924,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Density plot showing IPSS-M score distribution for \u003cem\u003eZRSR2m\u003c/em\u003e MDS patients. (B) Fishplot showing the progression of mutations VAF in \u003cem\u003eZRSR2m\u003c/em\u003e MDS patients throughout disease course and therapy. (C) Time to progression to AML from date of NGS for ZRSR2m patients according to myeloid neoplasm diagnoses.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4590446/v1/588a97b1f55eb742228329ae.jpg"},{"id":60354022,"identity":"d4f54afd-5079-4761-8f30-115ec3ac6849","added_by":"auto","created_at":"2024-07-15 23:50:50","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":423274,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Overall survival for 164 \u003cem\u003eZRSR2m\u003c/em\u003eMN patients (with dotted red line showing median OS). (B) OS of \u003cem\u003eZRSR2m\u003c/em\u003evs \u003cem\u003eZRSRwt\u003c/em\u003e in MDS patients. (C) OS according to different myeloid neoplasms in \u003cem\u003eZRSR2m\u003c/em\u003e patients. (D) OS according to the presence of an isolated \u003cem\u003eTET2\u003c/em\u003e co-mutation in ZRSR2m MN patients. (E) OS of \u003cem\u003eRUNX1m\u003c/em\u003evs \u003cem\u003eRUNX1wt\u003c/em\u003e in \u003cem\u003eZRSR2m\u003c/em\u003e MN patients.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4590446/v1/9958dfc7e4805b9db0a28f41.jpg"},{"id":65431746,"identity":"aee4c98a-04d3-4219-a73a-403f89e3b8b7","added_by":"auto","created_at":"2024-09-27 11:59:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3523246,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4590446/v1/b1fcc036-3083-4354-9a17-d40c1688d91b.pdf"},{"id":60353774,"identity":"d431c170-582e-4734-9edd-9b4d90a531b3","added_by":"auto","created_at":"2024-07-15 23:42:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":469724,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Supplemental.docx","url":"https://assets-eu.researchsquare.com/files/rs-4590446/v1/0a4d011fcf8f3e09c6d4f806.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Characterisation and prognostic impact of ZRSR2 mutations in myeloid neoplasms","fulltext":[{"header":"Key points","content":"\u003cul\u003e\n \u003cli\u003e\u003cem\u003eZRSR2\u003c/em\u003e mutations carry a favorable prognosis among chronic myeloid neoplasms.\u003c/li\u003e\n \u003cli\u003eHigh frequency of CCUS among \u003cem\u003eZRSR2m\u003c/em\u003e patients.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eZRSR2\u003c/em\u003e mutations association with elevated monocyte count and myelomonocytic differentiation.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe Zinc finger (CCCH type), RNA-binding motif, and serine/arginine-rich 2 (\u003cem\u003eZRSR2\u003c/em\u003e) gene, which is located on the X chromosome (Xp22.1) is a member of the RNA splicing machinery family of genes which also includes \u003cem\u003eSF3B1\u003c/em\u003e, \u003cem\u003eSRSF2\u003c/em\u003e, and \u003cem\u003eU2AF1\u003c/em\u003e.[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] \u003cem\u003eZRSR2\u003c/em\u003e normally encodes for a protein that associates with \u003cem\u003eU2AF2/U2AF1\u003c/em\u003e heterodimer and \u003cem\u003eSRSF2\u003c/em\u003e, which are involved in the recognition of 3\u0026rsquo;-intron splice sites early in the spliceosome assembly process.[\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] \u003cem\u003eZRSR2\u003c/em\u003e mutations (m) are found in 1.2% of all cancers with the highest prevalence in lung adenocarcinoma, colon adenocarcinoma, and high-grade ovarian serous adenocarcinoma.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThol et al. found that spliceosome genes mutations were found in 35% of myelodysplastic syndrome (MDS) patients, as one of the most common in the disease. They also found \u003cem\u003eZRSR2, U2AF1, and SRSF2\u003c/em\u003e as being mutually exclusive with each other.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] Alterations in \u003cem\u003eZRSR2\u003c/em\u003e have been reported in 4% of MDS patients, 8% of therapy-related MDS, and 4% of MDS with increased blasts 2.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] \u003cem\u003eZRSR2m\u003c/em\u003e are also seen across different myeloid neoplasms (MN) including primary and secondary acute myeloid leukemia (AML), chronic myelomonocytic leukemia (CMML), myeloproliferative neoplasm (MPN) and blastic plasmacytoid dendritic cell neoplasm (BPCDN) with lower frequency than MDS. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eContrary to the mutational hotspots found in other members of the splicing machinery genes, Damm et al, reported that \u003cem\u003eZRSR2\u003c/em\u003em were spread across the whole gene and consisted mainly of nonsense, frameshift, and splice site mutations with only a few missense mutations.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eStudies investigating \u003cem\u003eZRSR2\u003c/em\u003e in myeloid neoplasms were limited by the small number of patients having \u003cem\u003eZRSR2m\u003c/em\u003e (25 in one paper), and most failed to show significant association with other mutations or impact on survival analysis.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] The only co-mutation that showed significant association with \u003cem\u003eZRSR2\u003c/em\u003e was \u003cem\u003eTET2\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating a potential relationship or co-occurrence between the two genes.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] In one study, cells with mutated \u003cem\u003eZRSR2\u003c/em\u003e gene showed an increase in precursor cells for macrophages and a decrease in precursor cells for erythroid cells.[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Additionally, Malcovati et al. reported that \u003cem\u003eTET2\u003c/em\u003e with \u003cem\u003eSRSF2\u003c/em\u003e or \u003cem\u003eZRSR2\u003c/em\u003e as co-mutations were predictive of myelomonocytic phenotype and showed higher hemoglobin (Hgb) levels and monocyte counts. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] Damm et al. demonstrated that \u003cem\u003eZRSR2m\u003c/em\u003e MDS patients were mostly associated with increased blasts. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] We hereby report our center experience with \u003cem\u003eZRSR2m\u003c/em\u003e in patients with myeloid (and premyeloid) neoplasms.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe study was conducted in a single institution, Mayo Clinic, across its 3 campuses. Next-generation sequencing (NGS) was performed in the molecular hematopathology laboratory mainly on bone marrow (BM) samples (92% of \u003cem\u003eZRSR2m\u003c/em\u003e were found on BM NGS) with the NGS gene panel including 42\u0026ndash;47 genes, between 2016\u0026ndash;2023.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] [supplemental: methods] After obtaining institutional review board approval, patients\u0026rsquo; information (including age and gender), clinical characteristics, labs, treatment, treatment response, results of BM morphology, cytogenetics, and molecular studies were abstracted.\u003c/p\u003e \u003cp\u003eMyeloid neoplasms were classified and subclassified according to the 5th edition of the World Health Organization (WHO) classification of haematolymphoid tumours 2022.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] Response to treatment for MDS patients was determined using revised IWG 2023 response criteria for MDS, and response to treatment for AML patients was determined using ASH diagnosis and management of AML in adults; 2022 ELN recommendations from an international expert panel.[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] International prognostic scoring system-molecular and -revised (IPSS-M and IPSS-R) for MDS risk stratification were calculated using mds-risk-model.com.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eBlueSky Statistics V10.3.1 was used for data analysis. Overall Survival (OS) and median follow-up were measured using Kaplan-Meier estimates and Cox regression analysis from the date of NGS to death or last follow-up. A sample of 98 MDS \u003cem\u003eZRSR2wt\u003c/em\u003e control patients were used for survival comparison with \u003cem\u003eZRSR2m\u003c/em\u003e. Cox regression and binary time-dependent covariates were used to measure survival for patients receiving hematopoietic stem cell transplant (HSCT), starting from the date of transplant. Cox proportional hazard regression analysis was used to run the multivariate analysis to determine independent prognostic factors for OS. P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics:\u003c/h2\u003e \u003cp\u003eNGS was performed clinically on 9320 samples. Among those, 164 patients were found to have the \u003cem\u003eZRSR2m\u003c/em\u003e genotype, 162 of which were male (98.8%) with only 2 female patients (1.2%). NGS was analyzed from BM samples for 151 patients (92.1%) vs only 13 peripheral blood (PB) samples (7.9%). Median patient age was 74 (range 31\u0026ndash;92 years old). The most common diagnosis was MDS (n\u0026thinsp;=\u0026thinsp;53, 32.3%), clonal cytopenia of undetermined significance (CCUS) (n\u0026thinsp;=\u0026thinsp;39, 23.8%), MPN (n\u0026thinsp;=\u0026thinsp;33, 20.1%), MDS/MPN overlap (n\u0026thinsp;=\u0026thinsp;23, 14%), AML (n\u0026thinsp;=\u0026thinsp;15, 9.1%) and 1 patient diagnosed as mixed phenotype acute leukemia (MPAL). Fifteen (9%) patients had concurrent non-myeloid hematological malignancies diagnosed at the time of the NGS; 2 patients had concurrent chronic lymphocytic leukemia (CLL) and CCUS, multiple myeloma in 3 patients with CCUS and 1 patient with MDS, diffuse large B-cell lymphoma in 1 AML and 1 MDS/MPN overlap patient. While only 15 patients (9.1%) received chemotherapy or radiotherapy prior to their diagnosis, 29 patients (17.7%) received prior immunotherapy with the highest prevalence among CCUS patients (n\u0026thinsp;=\u0026thinsp;13, 33% of CCUS patients). (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) Abnormal cytogenetics were found in 54 patients (33%), with +\u0026thinsp;8 (16) and -Y (11) being the most common. (supplemental table 2)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\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 \u003cp\u003e\u003cem\u003eZRSR2m\u003c/em\u003e patients\u0026rsquo; characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian age, years (Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (31, 92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (Male), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162 (98.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM blasts (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151 (92.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePB blasts (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (7.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis at NGS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAML (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (32.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5q\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSF3B1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiTP53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (69.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIB1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIB2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (11.3)\u003c/p\u003e \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\u003e3 (5.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMDS with Monocytes\u0026thinsp;\u0026ge;\u0026thinsp;0.5 (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (50.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS/MPN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (78.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnclassifiable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (21.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (20.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (6.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (81.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnspecified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (6.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMast Cell Leukemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCUS (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (23.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCCUS with Monocytes\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;0.5\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPAL (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgression into CMML or MDS/MPN overlap (from CCUS, MDS, MPN) (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgression into AML (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (7.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCytogenetics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109 (66.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54 (33.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior Chemotherapy or Radiotherapy (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnoses associated with prior immunotherapy (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (17.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (13.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS/MPN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (26.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCUS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e BM, bone marrow; PB, Peripheral blood; AML, acute myeloid leukemia; MDS, myelodysplastic syndrome; LB, low blast; IB, increased blast; f, fibrotic; MDS/MPN, myelodysplastic/myeloproliferative neoplasms; CMML, chronic myelomonocytic leukemia; MPN, myeloproliferative neoplasms; PV, Polycythemia Vera; ET, Essential Thrombocythemia; MF, Myelofibrosis CCUS, clonal cytopenia of unknown significance.\u003c/p\u003e\u003cp\u003eSeventy-eight patients (48%) were diagnosed prior to our inhouse NGS (median time to NGS was 31.5 months). (supplemental table 7) Out of 10 patients diagnosed as CCUS, 8 (80%) progressed to MDS by the time of the NGS. One AML patient who achieved remission prior to NGS was diagnosed as CCUS by the time of NGS (9 years after initial AML diagnosis) harboring both \u003cem\u003eZRSR2\u003c/em\u003e and \u003cem\u003eIDH1.\u003c/em\u003e Two (7.7%) and 5 (11.5%) MDS patients progressed to AML and MDS/MPN overlap, respectively by the time of NGS. MPN was the most common diagnosis prior to NGS (27, followed by MDS at 26 patients), and none of the MPN patients progressed to AML or MDS/MPN overlap by the time of NGS, however, 9 out of 10 patients diagnosed as essential thrombocytosis (ET) (most common MPN diagnosis prior to NGS, 10 (37%) patients), and 4 out of 6 diagnosed as polycythemia vera (PV) progressed to myelofibrosis (MF) by the time of the NGS.\u003c/p\u003e \u003cp\u003eAmong MDS, the subtypes were low blast (MDS-LB) (n\u0026thinsp;=\u0026thinsp;37, 69.8%), increased blast-2 (MDS-IB2) (n\u0026thinsp;=\u0026thinsp;6, 11.3%), MDS with fibrosis (MDS-f) (n\u0026thinsp;=\u0026thinsp;3, 5.7%), increased blasts-1 (MDS-IB1) (n-2, 3.8%), MDS-BiTP53 (n-2, 3.8%), MDS-\u003cem\u003eSF3B1\u003c/em\u003e (n-2, 3.8%), and MDS-5q (n\u0026thinsp;=\u0026thinsp;1, 1.9%). Eighteen of 23 MDS/MPN Overlap were CMML (78%) and 5 were unclassifiable (21.7%). Myelofibrosis (MF) was the most common MPN (n\u0026thinsp;=\u0026thinsp;27, 81.8%), with 2 unspecified (6.1%), 2 polycythemia vera (PV), and 1 case of each essential thrombocythemia (ET) (3%) and mast cell leukemia.\u003c/p\u003e \u003cp\u003eRisk stratification among MDS patients by IPSS-M scoring was low risk (n\u0026thinsp;=\u0026thinsp;16, 30.2%), moderate low risk (n\u0026thinsp;=\u0026thinsp;13, 24.5%), high risk (n\u0026thinsp;=\u0026thinsp;12, 22.6%), very low risk (n\u0026thinsp;=\u0026thinsp;6, 11.3%), very high risk (n\u0026thinsp;=\u0026thinsp;4, 7.5%), and moderate high risk (n\u0026thinsp;=\u0026thinsp;2, 3.8%). (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e: A, supplemental Figs.\u0026nbsp;1, 2, 3) Twenty-four (45.3%) of MDS patients were stratified as low risk according to IPSS-R. (supplemental table 8) Median BM blasts among the cohort was 2 (range, 0\u0026ndash;91), median Hgb was 9.6 x10\u003csup\u003e9\u003c/sup\u003e/L, and median platelets was 134 x10\u003csup\u003e9\u003c/sup\u003e/L. (supplemental table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) Twenty-seven MDS patients (51%), and 23 CCUS patients (59%) had absolute monocyte count\u0026thinsp;\u0026ge;\u0026thinsp;0.5 x10\u003csup\u003e9\u003c/sup\u003e/L. (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eZRSR2 mutations Characteristics\u003c/h2\u003e \u003cp\u003eMedian pathogenic \u003cem\u003eZRSR2m\u003c/em\u003e VAF (mVAF) was (range, 2-100). Gender-corrected VAF was 35 (range, 1\u0026ndash;66) and was 50 among females. Gender corrected \u003cem\u003eZRSR2m\u003c/em\u003e mVAF was significantly different between different diagnostic groups (AML 41%, MDS 33.5%, MDS/MPN overlap 41%, MPN 29%, CCUS 31.5, p\u0026thinsp;=\u0026thinsp;0.04) (supplemental Fig.\u0026nbsp;4). Statistically significant difference was also found between MDS subtypes when compared according to gender corrected VAF (p\u0026thinsp;=\u0026thinsp;0.04) (supplemental Fig.\u0026nbsp;5) with IB1 having the highest mVAF. There was no statistically significant difference in gender-corrected VAF between IPSS-M groups (p\u0026thinsp;=\u0026thinsp;0.2), between patients who progressed or did not progress to AML (p\u0026thinsp;=\u0026thinsp;0.5), and between MPN subtypes (p\u0026thinsp;=\u0026thinsp;0.2). Additionally, there was no correlation between mVAF, or gender corrected mVAF, and BM or PB blasts. Multiple \u003cem\u003eZRSR2\u003c/em\u003e mutations were found in 7 patients (4.3%) including 1 CCUS, 4 MDS, and 2 CMML.\u003c/p\u003e \u003cp\u003eForty-nine percent of mutations occurred in Pre-ZF1 domain of the gene, 27% in the UHM domain and 13% in Post-ZF2 domain. ZF1 and ZF2 carried 4% and 6% of the mutations, respectively, and RS domain carried only 1% of the mutations. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e: C, Supplemental table 3) Mutations were spread across the entire length of the gene with no mutational hotspots. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e: A) The most changed nucleotide was c.827 (n, 14) followed by c.376C\u0026thinsp;\u0026gt;\u0026thinsp;T (n, 9), and c.203\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A (n, 8). (supplemental table 6) Most common mutation type was nonsense (n\u0026thinsp;=\u0026thinsp;69, 42%), followed by frameshift (n\u0026thinsp;=\u0026thinsp;56, 34%), and splice site (n\u0026thinsp;=\u0026thinsp;39, 24%). (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e: B, Supplemental table 3) No correlation was found between mutation type and MN classification, BM or PB blasts, or \u003cem\u003eZRSR2\u003c/em\u003e mVAF(p\u0026thinsp;=\u0026thinsp;0.07).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCo-mutations\u003c/h2\u003e \u003cp\u003eThe median number of co-mutations was 2 (range, 0\u0026ndash;6). The most commonly co-mutated gene pathway was the DNA methylation (n\u0026thinsp;=\u0026thinsp;98, 60%), followed by chromatin modification (n\u0026thinsp;=\u0026thinsp;74, 45%), and signaling pathway (n\u0026thinsp;=\u0026thinsp;66, 40%) (supplemental Fig.\u0026nbsp;7). Only 1 patient out of 164 had a mutation in the cohesion component gene mutations. A significant correlation was found between MN classification and number of co-mutations in \u003cem\u003eZRSR2m\u003c/em\u003e patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (supplemental Fig.\u0026nbsp;6). On linear regression, CCUS had fewer co-mutations than all other diagnoses, and MDS had fewer co-mutations than AML (p\u0026thinsp;=\u0026thinsp;0.0004), and MDS/MPN overlap (p\u0026thinsp;=\u0026thinsp;0.049).\u003c/p\u003e \u003cp\u003eThe most common co-mutation was \u003cem\u003eTET2\u003c/em\u003e which was present in 84 patients (51%), 42% of which had multiple \u003cem\u003eTET2\u003c/em\u003e mutations. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) A significant correlation was found between MN classification and presence of \u003cem\u003eTET2\u003c/em\u003e in \u003cem\u003eZRSR2m\u003c/em\u003e patients (p\u0026thinsp;=\u0026thinsp;0.007) and were found with highest frequency among MDS/MPN overlap patients (70%) followed by CCUS (64%) and AML (60%). \u003cem\u003eTET2\u003c/em\u003e showed no correlation with presence of elevated monocyte count (p\u0026thinsp;=\u0026thinsp;0.8), and despite the higher frequency of CMML among \u003cem\u003eTET2m\u003c/em\u003e vs \u003cem\u003eTET2wt\u003c/em\u003e (15.5% vs 6.2%, p\u0026thinsp;=\u0026thinsp;0.08). Median Hgb concentration for \u003cem\u003eTET2m\u003c/em\u003e and \u003cem\u003eTETwt\u003c/em\u003e was 9.95 vs 9.3 x10\u003csup\u003e9\u003c/sup\u003e/L, respectively (p\u0026thinsp;=\u0026thinsp;0.17). Other common co-mutations were \u003cem\u003eASXL1\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;52, 32%), and \u003cem\u003eJAK2\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;31, 19%). (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e) \u003cem\u003eJAK2m\u003c/em\u003e was mainly present in patients with MPN (70%) compared to other MNs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and was present in 7% of MDS/MPN overlap patients and 1 AML patient. (supplemental table 5) A significant correlation was also found between MN classification and \u003cem\u003eRUNX1\u003c/em\u003e co-mutations (p\u0026thinsp;=\u0026thinsp;0.008), and they were found in 23 patients (14%) with highest prevalence among AML (n\u0026thinsp;=\u0026thinsp;5, 33%) and MDS (n\u0026thinsp;=\u0026thinsp;12, 23%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCo-mutational pattern in \u003cem\u003eZRSR2\u003c/em\u003e-mutated MN patients of the major co-mutations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-mutation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (164)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAML\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCCUS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMDS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMDS/MPN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMPN\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian no. of co-mutations (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0\u0026ndash;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (0\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (1\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated \u003cem\u003eZRSR2m\u003c/em\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor co-mutations,\u003c/p\u003e \u003cp\u003e, 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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTET2\u003c/p\u003e \u003cp\u003e(multiple, n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (51)\u003c/p\u003e \u003cp\u003e(35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (60)\u003c/p\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (64)\u003c/p\u003e \u003cp\u003e(8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (47)\u003c/p\u003e \u003cp\u003e(14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (70)\u003c/p\u003e \u003cp\u003e(9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (27)\u003c/p\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASXL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14 (42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJAK2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23 (70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRUNX1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEZH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eU2AF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRSF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTP53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCBL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSF3B1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 (6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOther members of the spliceosome family of genes were present in 14.7% of patients, including \u003cem\u003eU2AF1\u003c/em\u003e9 (5.5%), \u003cem\u003eSRSF2\u003c/em\u003e 8 (5%), and \u003cem\u003eSF3B1\u003c/em\u003e 7 (4%) patients. In \u003cem\u003eZRSR2m\u003c/em\u003e patients with co-mutated spliceosome genes, the gender-corrected mVAF value for \u003cem\u003eZRSR2m\u003c/em\u003e was within 5% of the mVAF for \u003cem\u003eSRSF2\u003c/em\u003e and \u003cem\u003eU2AF1\u003c/em\u003e but significantly lower than the mVAF for \u003cem\u003eSF3B1\u003c/em\u003e (40.5 vs 41 for SRSF2, 25.5 vs 28 for U2AF1, 5 vs 34 for SF3B1), indicating possibly that \u003cem\u003eZRSR2m\u003c/em\u003e was a subclone in the setting of \u003cem\u003eSF3B1m\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eOnly 13 patients (4.3%) had isolated \u003cem\u003eZRSR2\u003c/em\u003e mutations, and included 6 CCUS, 5 MDS, 1 MDS/MPN overlap, and 1 MPAL. The median VAF for isolated \u003cem\u003eZRSR2m\u003c/em\u003e patients was similar to patients with co-mutations (69.5 and 70, respectively). Median IPSS-M score was lower in patients with isolated \u003cem\u003eZRSR2m\u003c/em\u003e (-1.18) compared to patients with co-mutations (-0.74) (p\u0026thinsp;=\u0026thinsp;0.02). There was no difference in BM blasts for isolated \u003cem\u003eZRSR2m\u003c/em\u003e and patients with other co-mutations, (1% vs 2% respectively, p\u0026thinsp;=\u0026thinsp;0.15), or cytogenetic abnormalities between isolated and co-mutated cases (42% vs 32% abnormal, p\u0026thinsp;=\u0026thinsp;0.5).\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eResponse to therapy and progression\u003c/h2\u003e \u003cp\u003eOf 164 patients, 108 (66%) received treatment, including 39 MDS, 28 MPN, 17 MDS/MPN overlap, 12 AML, 11 CCUS, and 1 MPAL. Of 12 AML patients receiving treatment, 8 (66.7%) achieved response to therapy with 2 (16.7%) complete remissions with incomplete hematologic recovery (CRi), and 6 (50%) with complete remission (CR), of whom 1 relapsed. (supplemental Fig.\u0026nbsp;9: B) Among 39 \u003cem\u003eZRSR2m\u003c/em\u003e MDS receiving treatment, 7 (18%) had hematological improvement (HI), 3 (7.7%) had complete remission with limited recovery (CR\u003csub\u003eL\u003c/sub\u003e), 1 CR equivalent (2.6), and 3 (7.7%) had CR, of which 2 relapsed. (supplemental Fig.\u0026nbsp;9: A) Median time to response from treatment initiation date among AML and MDS patients was 1 and 3 months, respectively. (supplemental table 9) Hematopoietic stem cell transplant (HSCT) was performed in 21 patients (12.8%) including 3 AML, 10 MDS, 4 MDS/MPN overlap, and 2 MPN. The median time from NGS to transplant was 4 months.\u003c/p\u003e \u003cp\u003eThe most used medications were hypomethylating agents (HMA) used in 22% of the patients, including 20 (37.7%) MDS, 7 (30.4%) of MDS/MPN overlap, and 4 (26.7%) of AML. (supplemental Fig.\u0026nbsp;8) The combination of HMA and venetoclax was also used in 15 patients including 3 AML, 6 MDS, and 2 MDS/MPN overlap cases. (supplemental table 10) Erythropoietin stimulating agents (ESA) were given in 21 patients including 24.5% of MDS, 13% of MDS/MPN overlap, 9% of AML and 5% of CCUS cases. Oral decitabine and cedazuridine combination therapy was given for 6 MDS and 1 CCUS. (table showing response to therapy) Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e: B shows the progression of mVAF in a \u003cem\u003eZRSR2m\u003c/em\u003e MDS patient among ZRSR2 and the co-mutations and their changes after therapy and HSCT. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e: B)\u003c/p\u003e \u003cp\u003eThirteen patients (8.7%) progressed to AML, 9 from MDS (17%), 2 from MDS/MPN overlap (8.7%), and 2 from MPN (6%), none of these patients had isolated \u003cem\u003eZRSR2\u003c/em\u003e and only 1 MDS patient had Isolated \u003cem\u003eTET2\u003c/em\u003e as a co-mutation. Among MDS cohort, LB showed significantly lower rate of AML progression (8%) compared to IB2 (50%), BiTP53 (50%), and F (33%) (p\u0026thinsp;=\u0026thinsp;0.02). (supplemental table 4) The median time to progression from NGS date was 12 months (range, 0\u0026ndash;52 months). (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e: C) MDS-f had longer median time to progression to AML compared to MDS-IB2 (23.5 vs 6, p\u0026thinsp;=\u0026thinsp;0.03). Ten patients (8%) progressed into CMML or MDS/MPN overlap from CCUS, MDS, or MPN.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSurvival\u003c/h2\u003e \u003cp\u003eThere were 68 deaths, with median overall survival (mOS) period of 51 months, and median follow up of 35 months. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e: A) \u003cem\u003eZRSR2m\u003c/em\u003e MDS patients had better mOS compared to the MDS control group with \u003cem\u003eZRSR2wt\u003c/em\u003e (35 months vs 22 months, p\u0026thinsp;=\u0026thinsp;0.013). (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e: B) mOS of \u003cem\u003eZRSR2m\u003c/em\u003e patients varied significantly among different MNs (p\u0026thinsp;=\u0026thinsp;0.004), with MPAL and AML having the shortest mOS at 3 and 9 months, respectively, followed by MDS/MPN overlap at 27, MPN at 39. MDS and CCUS had the longest mOS at 61 and 56 months, respectively. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e: C)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eZRSR2m\u003c/em\u003e patients with spliceosome and tumor suppressor gene (TSG) gene pathway co-mutations showed worse survival compared to patients without these mutations (25 vs 56 months for spliceosome genes, p\u0026thinsp;=\u0026thinsp;0.02 and 20 vs 51 months for TSG, p\u0026thinsp;=\u0026thinsp;0.04). (supplemental Figs.\u0026nbsp;10, 13) Patients with \u003cem\u003eTET2\u003c/em\u003e as an isolated co-mutation had better survival (not reached vs 30 months, p\u0026thinsp;=\u0026thinsp;0.01), and in contrast, patients with \u003cem\u003eRUNX1\u003c/em\u003e co-mutations had worse survival (28 vs 52 months, p\u0026thinsp;=\u0026thinsp;0.02). (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e: D, E) Patients with isolated \u003cem\u003eZRSR2m\u003c/em\u003e showed good survival (not reached vs 40, p\u0026thinsp;=\u0026thinsp;0.2). There was no difference in survival according to other co-mutated genes or gene pathways.\u003c/p\u003e \u003cp\u003ePatients with PB blasts\u0026thinsp;\u0026lt;\u0026thinsp;5% had better mOS of 52 months vs 9 months in patients with PB blasts\u0026thinsp;\u0026ge;\u0026thinsp;5% (HR\u0026thinsp;=\u0026thinsp;0.027, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). (supplemental Fig.\u0026nbsp;11) Higher Hgb concentration showed improved survival (HR\u0026thinsp;=\u0026thinsp;0.78, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while patients with increased WBCs count (HR\u0026thinsp;=\u0026thinsp;1.02, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), absolute neutrophil count (ANC) (HR\u0026thinsp;=\u0026thinsp;1.04, p\u0026thinsp;=\u0026thinsp;0.01), absolute monocyte count (AMC) (HR\u0026thinsp;=\u0026thinsp;1.2, p\u0026thinsp;=\u0026thinsp;0.008), BM blasts (HR\u0026thinsp;=\u0026thinsp;1.02, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), PB blasts (HR\u0026thinsp;=\u0026thinsp;1.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) showed worse mOS. Patients with higher number of co-mutations showed worse OS (HR\u0026thinsp;=\u0026thinsp;1.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Patients with abnormal cytogenetics had shorter survival periods compared to patients with normal cytogenetics (25 vs 61 months, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). (supplemental Fig.\u0026nbsp;12) Overall survival did not vary with age, HSCT, MDS subtype, IPSS-M group, \u003cem\u003eZRSR2m\u003c/em\u003e site or type. (supplemental Fig.\u0026nbsp;14) On multivariate analysis, only higher Hgb concentration (HR\u0026thinsp;=\u0026thinsp;0.8, p\u0026thinsp;=\u0026thinsp;0.004), PB blasts\u0026thinsp;\u0026gt;\u0026thinsp;5% (HR\u0026thinsp;=\u0026thinsp;2.2, p\u0026thinsp;=\u0026thinsp;0.02), and abnormal cytogenetics (HR\u0026thinsp;=\u0026thinsp;1.9, p\u0026thinsp;=\u0026thinsp;0.01) retained significance while isolated \u003cem\u003eTET2m\u003c/em\u003e and \u003cem\u003eRUNX1m\u003c/em\u003e lost significance. (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate analysis results. (*) indicates statistical significance.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated TET2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.5885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2608\u0026ndash;1.3277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.8208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0036 **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7185\u0026ndash;0.9376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRUNX1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.6112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8587\u0026ndash;3.0232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral circulating blasts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.2251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0165 *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.1572\u0026ndash;4.2785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal cytogenetics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.9319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0098 **\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.172\u0026ndash;3.1844\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eMolecular dynamics\u003c/h2\u003e \u003cp\u003eSequential NGS (S1-NGS) was performed in 55 out of the 164 patients (33.5%), 50 (91%) of them continued to have \u003cem\u003eZRSR2m\u003c/em\u003e. Only 19 patients out of 55 (34.5%) performed a second sequential NGS (S2-NGS) and 17 (89.5%) of them continued to have \u003cem\u003eZRSR2m\u003c/em\u003e, and out of the 3 patients who cleared the mutation on S1-NGS, only one performed S2-NGS and did not show re-emergence of the mutation. Out of the 21 patients who had HSCT, 4 (19%) performed sequential NGS posttransplant and all of them negative NGS with complete clearance of \u003cem\u003eZRSR2m\u003c/em\u003e and the co-mutated genes. Median number of co-mutations remained 2 in the first NGS and throughout both S1-NGS and S2-NGS. mVAF for \u003cem\u003eZRSR2m\u003c/em\u003e was 80% and 89% for S1-NGS and S2-NGS, respectively, showing a statistically significant increase of 11% for S1-NGS from the first NGS (p\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study has the largest cohort of \u003cem\u003eZRSR2m\u003c/em\u003e MN patients (164) and includes premyeloid, chronic myeloid and acute leukemias. The cohort consisted predominantly of males with only 2 female patients which confirms previous literature of \u003cem\u003eZRSR2m\u0026rsquo;s\u003c/em\u003e male predominance and suggested theory that it functions mainly as an X-linked recessive tumor suppressor gene. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] We also show improved survival among MDS patients harboring \u003cem\u003eZRSR2m\u003c/em\u003e which suggests that \u003cem\u003eZRSR2\u003c/em\u003e mutations carry a favorable prognosis.\u003c/p\u003e \u003cp\u003eIn accordance with previous studies, \u003cem\u003eZRSR2m\u003c/em\u003e was found across different MNs, however, our study found a notable association with a higher incidence of CCUS diagnoses which was the second most common diagnosis following MDS, which is a novel finding. Among \u003cem\u003eZRSR2m\u003c/em\u003e MDS group, the most common subtype was MDS-LB constituting 70% of MDS followed by MDS-IB2 with only 11% which is different from prior literature stating that \u003cem\u003eZRSR2m\u003c/em\u003e MDS were mostly subclassified as IB1 and IB2. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] Additionally, the most common risk stratification of MDS and CCUS patients according to IPSS-M and IPSS-R was low risk, followed by moderate low in IPSS-m. Only 17% of \u003cem\u003eZRSR2m\u003c/em\u003e MDS progressed to AML which is a low rate compared to current literature\u0026rsquo;s 30\u0026ndash;40%.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] The above-mentioned constellation of \u003cem\u003eZRSR2m\u003c/em\u003e being associated with pre-MNs disorders (CCUS), lower-grade of MDS and lower rate of AML progression suggests that the mutation carries a favorable prognosis among chronic myeloid neoplasms, especially in isolated \u003cem\u003eTET2m\u003c/em\u003e group.\u003c/p\u003e \u003cp\u003eMadan et al described an increase in colony forming unit-macrophage (CFU-M) among CD34\u0026thinsp;+\u0026thinsp;cells that were \u003cem\u003eZRSR2\u003c/em\u003e inactivated which was supported clinically in our study as we found that over half of the \u003cem\u003eZRSR2m\u003c/em\u003e MDS and CCUS cohort had elevated absolute monocyte count (\u0026ge;\u0026thinsp;0.5 x10\u003csup\u003e9\u003c/sup\u003e/L).[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] The majority of MDS/MPN overlap patients were diagnosed as CMML, furthermore, about 8% of patients originally diagnosed as CCUS, MDS or MPN progressed or were re-diagnosed as CMML later. These findings indicate a possible association between \u003cem\u003eZRSR2\u003c/em\u003e and monocytic differentiation. Malcovati et al. described that an association between \u003cem\u003eTET2\u003c/em\u003e and \u003cem\u003eZRSR2\u003c/em\u003e was predictive of myelomonocytic phenotype, and showed significantly higher Hgb levels and monocyte count. However, among our \u003cem\u003eZRSR2m\u003c/em\u003e cohort, no correlation was shown for \u003cem\u003eTET2m\u003c/em\u003e vs \u003cem\u003eTETwt\u003c/em\u003e regarding monocyte count.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] Moreover, There was a slightly increased frequency of CMML among \u003cem\u003eTET2m\u003c/em\u003e, but failed to show significance (p\u0026thinsp;=\u0026thinsp;0.08).\u003c/p\u003e \u003cp\u003eInterestingly, MPN was found in 20% of \u003cem\u003eZRSR2m\u003c/em\u003e patients and consisted mainly of MF (61% of which progressed from PV or ET prior to NGS) and was associated with increased frequency of \u003cem\u003eJAK2\u003c/em\u003e mutations as expected (70%). This raises the possibility of acquiring \u003cem\u003eZRSR2m\u003c/em\u003e later in MPN progression into MF. Our study demonstrated a strong association between \u003cem\u003eZRSR2m\u003c/em\u003e and \u003cem\u003eTET2m\u003c/em\u003e (51% of patients) which is consistent with previous studies.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] Presence of \u003cem\u003eTET2\u003c/em\u003em as an isolated co-mutation was shown to be associated with longer survival among \u003cem\u003eZRSR2m\u003c/em\u003e MN patients, and had a significant difference on MN classification with highest prevalence among MDS/MPN overlap patients. Despite past studies with smaller number of \u003cem\u003eZRSR2m\u003c/em\u003e MN patients proposing that the gene is mutually exclusive with two other members of the spliceosome family of genes (U2AF1 and SRSF2), 10.4% of our \u003cem\u003eZRSR2m\u003c/em\u003e MN patients had either \u003cem\u003eU2AF1\u003c/em\u003e (5.5%) or \u003cem\u003eSRSF2\u003c/em\u003e (4.9%) .[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eSurvival among ZRSR2m MN patients was affected mostly by the MN diagnosis (AML showing worst survival) and expectedly by PB blasts\u0026thinsp;\u0026gt;\u0026thinsp;5%. Other factors that affected survival positively was higher Hgb concentration and the presence of isolated \u003cem\u003eTET2m.\u003c/em\u003e On the contrary, presence of \u003cem\u003eRUNX1m\u003c/em\u003e and cytogenetic abnormalities affected survival negatively.\u003c/p\u003e \u003cp\u003eOur study was limited by data collection from a single institution, the retrospective nature of the study, lack of longer follow up, small cohort size due to rarity of the gene. Additionally, NGS was not done at diagnosis in some of our cases but rather later which adds a time bias.\u003c/p\u003e \u003cp\u003eIn conclusion, the ZRSR2m was almost exclusively seen in males, with a striking increased frequency of CCUS patients. TET2m was the most common co-mutation and is linked to better survival especially as an isolated co-mutation. Over half of the patients with ZRSR2m MDS and CCUS had a higher absolute monocyte count indicating a possible association with monocytic differentiation. However, further studies are needed to confirm these findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe protein diagram was generated using ProteinPaint (https://proteinpaint.stjude.org/). The Fishplots depicting clonal evolution were generated using https://github.com/chrisamiller/fishplot.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrants support:\u003c/strong\u003e none\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship Contributions\u003c/strong\u003e: MY, BK, and AA planned the study, reviewed data, performed statistical analysis, and wrote the manuscript. RH and DV performed molecular analysis and reviewed the manuscript. PG performed cytogenetic analysis and reviewed the analysis. KB coordinated NGS data collection. DJ, JF, JP, AS, MH, KB, WH, MP, MS, and HA reviewed the paper and contributed patients.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest disclosure\u003c/strong\u003e: The authors declare no competing financial interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevious publications:\u0026nbsp;\u003c/strong\u003ePart of this manuscript was accepted for poster publication at the European Hematology Association Congress 2024.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYoshida, K., et al., \u003cem\u003eFrequent pathway mutations of splicing machinery in myelodysplasia\u003c/em\u003e. Nature, 2011. 478(7367): p. 64\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDamm, F., et al., \u003cem\u003eMutations affecting mRNA splicing define distinct clinical phenotypes and correlate with patient outcome in myelodysplastic syndromes\u003c/em\u003e. Blood, 2012. 119(14): p. 3211\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThol, F., et al., \u003cem\u003eFrequency and prognostic impact of mutations in SRSF2, U2AF1, and ZRSR2 in patients with myelodysplastic syndromes\u003c/em\u003e. Blood, 2012. 119(15): p. 3578\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMadan, V., et al., \u003cem\u003eAberrant splicing of U12-type introns is the hallmark of ZRSR2 mutant myelodysplastic syndrome\u003c/em\u003e. Nat Commun, 2015. 6: p. 6042.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eG\u0026oacute;mez-Redondo, I., et al., \u003cem\u003eZrsr2 and functional U12-dependent spliceosome are necessary for follicular development\u003c/em\u003e. iScience, 2022. 25(2): p. 103860.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTronch\u0026egrave;re, H., J. Wang, and X.D. Fu, \u003cem\u003eA protein related to splicing factor U2AF35 that interacts with U2AF65 and SR proteins in splicing of pre-mRNA\u003c/em\u003e. Nature, 1997. 388(6640): p. 397\u0026ndash;400.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShen, H., et al., \u003cem\u003eThe U2AF35-related protein Urp contacts the 3' splice site to promote U12-type intron splicing and the second step of U2-type intron splicing\u003c/em\u003e. Genes Dev, 2010. 24(21): p. 2389\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eAACR Project GENIE: Powering Precision Medicine through an International Consortium\u003c/em\u003e. Cancer Discov, 2017. 7(8): p. 818\u0026ndash;831.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInoue, D., et al., \u003cem\u003eMinor intron retention drives clonal hematopoietic disorders and diverse cancer predisposition\u003c/em\u003e. Nat Genet, 2021. 53(5): p. 707\u0026ndash;718.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiereghin, C., et al., \u003cem\u003eThe Genetics of Myelodysplastic Syndromes: Clinical Relevance\u003c/em\u003e. Genes (Basel), 2021. 12(8).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHosono, N., \u003cem\u003eGenetic abnormalities and pathophysiology of MDS\u003c/em\u003e. Int J Clin Oncol, 2019. 24(8): p. 885\u0026ndash;892.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTogami, K., et al., \u003cem\u003eSex-Biased ZRSR2 Mutations in Myeloid Malignancies Impair Plasmacytoid Dendritic Cell Activation and Apoptosis\u003c/em\u003e. Cancer Discov, 2022. 12(2): p. 522\u0026ndash;541.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLindsley, R.C., et al., \u003cem\u003eAcute myeloid leukemia ontogeny is defined by distinct somatic mutations\u003c/em\u003e. Blood, 2015. 125(9): p. 1367\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBouligny, I.M., K.R. Maher, and S. Grant, \u003cem\u003eSecondary-Type Mutations in Acute Myeloid Leukemia: Updates from ELN 2022\u003c/em\u003e. Cancers (Basel), 2023. 15(13).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapaemmanuil, E., et al., \u003cem\u003eClinical and biological implications of driver mutations in myelodysplastic syndromes.\u003c/em\u003e Blood, 2013. 122(22): p. 3616-27; quiz 3699.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarcia-Ruiz, C., et al., \u003cem\u003eConcurrent Zrsr2 mutation and Tet2 loss promote myelodysplastic neoplasm in mice\u003c/em\u003e. Leukemia, 2022. 36(10): p. 2509\u0026ndash;2518.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalcovati, L., et al., \u003cem\u003eDriver somatic mutations identify distinct disease entities within myeloid neoplasms with myelodysplasia\u003c/em\u003e. Blood, 2014. 124(9): p. 1513\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe, R., et al., \u003cem\u003eHybridization capture-based next generation sequencing reliably detects FLT3 mutations and classifies FLT3-internal tandem duplication allelic ratio in acute myeloid leukemia: a comparative study to standard fragment analysis\u003c/em\u003e. Modern Pathology, 2020. 33(3): p. 334\u0026ndash;343.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhoury, J.D., et al., \u003cem\u003eThe 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms\u003c/em\u003e. Leukemia, 2022. 36(7): p. 1703\u0026ndash;1719.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeidan, A.M., et al., \u003cem\u003eConsensus proposal for revised International Working Group 2023 response criteria for higher-risk myelodysplastic syndromes\u003c/em\u003e. Blood, 2023. 141(17): p. 2047\u0026ndash;2061.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD\u0026ouml;hner, H., et al., \u003cem\u003eDiagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN\u003c/em\u003e. Blood, 2022. 140(12): p. 1345\u0026ndash;1377.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKurzer, J.H. and O.K. Weinberg, \u003cem\u003eUpdates in molecular genetics of acute myeloid leukemia\u003c/em\u003e. Semin Diagn Pathol, 2023. 40(3): p. 140\u0026ndash;151.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreenberg, P.L., et al., \u003cem\u003eRevised international prognostic scoring system for myelodysplastic syndromes\u003c/em\u003e. Blood, 2012. 120(12): p. 2454\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBernard, E., et al., \u003cem\u003eMolecular International Prognostic Scoring System for Myelodysplastic Syndromes\u003c/em\u003e. NEJM Evidence, 2022. 1(7): p. EVIDoa2200008.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVolpe, V.O., G. Garcia-Manero, and R.S. Komrokji, \u003cem\u003eMyelodysplastic Syndromes: A New Decade\u003c/em\u003e. Clin Lymphoma Myeloma Leuk, 2022. 22(1): p. 1\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMenssen, A.J. and M.J. Walter, \u003cem\u003eGenetics of progression from MDS to secondary leukemia\u003c/em\u003e. Blood, 2020. 136(1): p. 50\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4590446/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4590446/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe ZRSR2 gene is a member of the spliceosome gene family which are frequently mutated in myeloid neoplasms. \u003cem\u003eZRSR2\u003c/em\u003e mutations (\u003cem\u003eZRSR2m\u003c/em\u003e) occur in less than 5% of MDS, CMML, and AML. Our study included 164 \u003cem\u003eZRSR2m\u003c/em\u003e patients (98.8% males) and 98 \u003cem\u003eZRSR2wt\u003c/em\u003e MDS control cohort. In the \u003cem\u003eZRSR2m\u003c/em\u003e group, there were 53 MDS (32%), 39 CCUS (24%), 33 MPN (20%), 23 MDS/MPN overlap (14%), 15 AML (9%), and 1 MPAL (0.6%). Most MDS patients were the low blast subtype (n=37, 70%). Twenty-seven MDS patients (51%), and 23 CCUS patients (59%) had absolute monocyte count ≥0.5 x10\u003csup\u003e9\u003c/sup\u003e/L and 18 of 23 MDS/MPN overlap were CMML (78%). Mutations in \u003cem\u003eZRSR2\u003c/em\u003e were spread across the entire gene. The median number of co-mutations was 2, with TET2 (51%) and ASXL1 (32%) being the most common. \u003cem\u003eU2AF1\u003c/em\u003e and \u003cem\u003eSRSF2\u003c/em\u003e, previously described as mutually exclusive with \u003cem\u003eZRSR2\u003c/em\u003e, were found in 10.4% of patients. Median overall survival (OS) was 51 months, and significantly varied among MNs (p=0.004). \u003cem\u003eZRSR2m\u003c/em\u003e MDS patients had better mOS than the MDS control cohort with \u003cem\u003eZRSR2wt \u003c/em\u003e(35 vs 22 months, p=0.013).\u003cem\u003e ZRSR2m\u003c/em\u003e patients with isolated \u003cem\u003eTET2\u003c/em\u003e co-mutation and higher hemoglobin showed improved survival, while patients with \u003cem\u003eRUNX1m\u003c/em\u003e, higher WBC count showed worse OS.\u003c/p\u003e","manuscriptTitle":"Characterisation and prognostic impact of ZRSR2 mutations in myeloid neoplasms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-15 23:42:45","doi":"10.21203/rs.3.rs-4590446/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-07-03T11:22:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-07-02T17:11:06+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-06-21T05:41:37+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-06-18T20:16:37+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-06-18T02:36:34+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-06-18T02:01:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-17T10:25:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-17T10:24:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Leukemia","date":"2024-06-16T16:20:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8bb3d140-fc90-42ed-bc53-813cd88e8959","owner":[],"postedDate":"July 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33379705,"name":"Health sciences/Diseases/Cancer/Haematological cancer/Myelodysplastic syndrome"},{"id":33379706,"name":"Health sciences/Diseases/Cancer/Cancer genetics"},{"id":33379707,"name":"Health sciences/Diseases/Haematological diseases/Haematological cancer/Myelodysplastic syndrome"},{"id":33379708,"name":"Health sciences/Diseases/Haematological diseases/Haematological cancer/Myeloproliferative disease"},{"id":33379709,"name":"Health sciences/Pathogenesis/Clinical genetics/Cancer genetics"}],"tags":[],"updatedAt":"2024-09-27T10:50:32+00:00","versionOfRecord":{"articleIdentity":"rs-4590446","link":"https://doi.org/10.1038/s41375-024-02374-9","journal":{"identity":"leukemia","isVorOnly":false,"title":"Leukemia"},"publishedOn":"2024-09-23 04:00:00","publishedOnDateReadable":"September 23rd, 2024"},"versionCreatedAt":"2024-07-15 23:42:45","video":"","vorDoi":"10.1038/s41375-024-02374-9","vorDoiUrl":"https://doi.org/10.1038/s41375-024-02374-9","workflowStages":[]},"version":"v1","identity":"rs-4590446","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4590446","identity":"rs-4590446","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}