SETD4 expression is correlated with leukemic burden and SMYD2 transcription in acute lymphoblastic leukemia 

SETD4 expression is correlated with leukemic burden and SMYD2 transcription in acute lymphoblastic leukemia | 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 SETD4 expression is correlated with leukemic burden and SMYD2 transcription in acute lymphoblastic leukemia Luis Augusto Muniz Telles, Mariana Braccialli de Loyola, Luis Henrique Toshihiro Sakamoto, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6191336/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy worldwide. Despite a good rate of treatment success, the poor prognosis underscores the urgent need for new prognostic markers and effective therapeutic strategies. The SET family of lysine methyltransferases (KMTs) has been implicated in several cancers. While SMYD2 has been identified as a prognostic marker in ALL, SETD4 is a member that is still poorly characterized. Methods In the present study, we analyzed the expression patterns of SETD4 in 83 pediatric ALL patients at diagnosis and during treatment using RT‒ qPCR. Kaplan-Meier analysis was employed to evaluate survival outcomes between the high and basal SETD4 expression groups. Results We found that SETD4 transcription levels are significantly upregulated in BM samples derived from ALL patients compared to non-neoplastic BM (median fold-change of 5.14 p = 0.0095) and SETD4 expression is correlated with leukemic burden. Importantly, the levels of SETD4 decreased in chemotherapy-responsive patients. We further investigated whether SETD4 transcription levels are associated with those of SMYD2 . Notably, a positive correlation between both genes was observed at diagnosis (Spearman r = 0.759, p < 0.0001), with a substantial correlation persisting throughout treatment (Spearman r = 0.925, p < 0.01). Furthermore, patients classified in the high-risk category exhibited elevated SETD4 expression, with those displaying high SETD4 transcription exhibiting the poorest survival outcomes. Conclusion Our findings unveil the involvement of SETD4 in leukemogenesis and highlight its potential as a promising prognostic marker. Health sciences/Biomarkers Health sciences/Oncology Lymphoblastic leukemia Epigenetics Gene expression Prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy, with an incidence of approximately 2–4 cases per 100,000 children under 15 years of age. Notably, the peak incidence occurs between 3 and 5 years of age ( 1 ). Despite favorable treatment outcomes, relapsed disease remains the leading cause of mortality in pediatric ALL patients. Consequently, ongoing research has focused on identifying better prognostic markers and treatment enhancements for ALL management ( 1 ). ALL comprises two primary subtypes: B-cell ALL and T-cell ALL. B- ALL is significantly more prevalent, constituting approximately 85% of all cases ( 2 ). Cytogenetic aberrations are common findings in ALL, especially among pediatric patients and have long been recognized for their substantial impact on clinical outcomes ( 3 – 5 ). However, recent advancements in sequencing and genomic analysis technologies have unveiled novel alterations at the submicroscopic scale. These subtle changes play crucial roles in determining disease aggressiveness and resistance to chemotherapy. Collectively, these scientific breakthroughs enable the identification of new ALL subtypes and enhance the precision of patient prognosis, thereby facilitating more effective risk-adapted treatment strategies and supportive care ( 2 ). Lysine methyltransferases (KMTs) are proteins that add methyl marks to lysine residues in both histones and non-histone proteins. These marks contribute to a wide range of epigenetic modifications, including the establishment and propagation of various gene expression patterns. Dysregulation of KMT activity can cause widespread epigenetic changes that contribute to cancer development and progression ( 6 ). SMYD2 (SET and MYND domain-containing protein 2) is a lysine methyltransferase known to play significant roles in cancer ( 7 , 8 ). Aberrant SMYD2 expression in children with ALL was previously described as a poor prognostic factor, as it correlated with unfavorable clinical characteristics such as age and increased blast counts following chemotherapy ( 9 , 10 ). SET domain-containing protein 4 (SETD4), which is also a histone lysine methyltransferase, has been implicated in the regulation of various cellular processes, including cell proliferation, cell cycle regulation, and maintenance of cancer stem cell (CSC) quiescence. Recent studies have shed light on its roles in breast cancer, non-small cell lung cancer (NSCLC), and radiation-induced lymphomagenesis ( 11 – 14 ). However, its clinical significance in ALL remain unexplored. Here, we analyzed the expression pattern of SETD4 among pediatric ALL patients and non-neoplastic bone marrow samples and investigated the correlation between SETD4 transcription changes and the leukemic burden in ALL patients during chemotherapy and SMYD2 transcription. METHODS Patient sample collection Bone marrow aspirates from 83 pediatric ALL patients were collected at Jose Alencar Children’s Hospital of Brasilia between 2008 and 2010 during initial disease presentation as part of routine diagnosis and genetic analysis of leukemia. B-ALL patients were treated according to the Brazilian Cooperative Group for Treatment of Childhood Acute Lymphocytic Leukemia (GBTLI) protocol, and T-ALL patients were treated according to the ALL-Berlin-Frankfurt-Münster (BFM-95) protocol ( 15 , 16 ). Bone marrow samples from 15 patients were obtained on the 15th and 29th days of induction chemotherapy. Additionally, bone marrow samples from eight children with idiopathic thrombocytopenic purpura were used as non-neoplastic controls. Blast percentages were confirmed in Wright ‒Giemsa-stained smears, with all leukemic samples containing more than 40% blasts. The study protocol was approved by the Regional Ethics Committee of the Federal District, Brazil, with written informed consent from patients and/or guardians. The study followed the Declaration of Helsinki. Clinical data collection Clinical characteristics, including sex, age and white blood cell (WBC) count in peripheral blood at ALL diagnosis, immunophenotyping of bone marrow blasts, cytogenetic alterations and bone marrow status at the 15th and 29th days of chemotherapy, were obtained from medical records and described previously ( 9 ). High-risk patients included those who were e less than 2 years old or more than 9 years old, and/or had peripheral blood WBC counts exceeding 50,000/mm3, and/or showed infiltration in the central nervous system at the time of diagnosis and/or unfavorable cytogenetic findings. RNA isolation, cDNA synthesis and RT‒qPCR Bone marrow mononuclear cells (BMMCs) were isolated by Ficoll density centrifugation. Total RNA was extracted from each sample using TRIzol Reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s protocol. Single-stranded complementary DNA was generated from total RNA with reverse transcriptase and random primers, using the High-Capacity cDNA Reverse Transcription Kit (Life Technologies, Carlsbad, CA, USA). qPCR was performed on a StepOnePlusTM Real-Time PCR System (Applied Biosystems, Carlsbad, CA, USA) using Taq-Man Gene Expression Assays according to the manufacturer’s instructions (Hs00213731_m1, Cat. no. 4331182 for SETD4; Hs00220210 m1, Cat. no. 4331182 for SMYD2 ; and Hs99999903 m1, Cat. no. 4331182 for ACTB ; Life Technologies). qPCR assays were carried out in a final volume of 10 µL in 96-well plates. Each plate included triplicates of cDNA from bone marrow samples, multiple water blanks and triplicates of inter-run calibrators (a unique cDNA sample used for all PCR run plates). PCR was conducted with the following conditions: 95°C for 2 min, followed by 40 cycles at 95°C for 15 s and 60°C for 40 s. Quantitation cycle (Cq) values were obtained from this experiment and the ∆∆CT method was applied to these values using ACTB as a reference gene for input normalization and scaling all samples by the mean Cq values of non-neoplastic samples. The 3rd quartile of non-neoplastic samples RQ’s was used as a threshold to classify a sample as having high or basal SETD4 mRNA expression. The datasets analyzed during the current study are available in the supplementary materials (Table 1). RT‒qPCR data and statistical analysis Descriptive statistics were used to summarize the study data. Statistical significance was defined as a two-tailed p value < 0.05. We used Mann‒Whitney U test for independent samples to compare the expression of SETD4 between ALL and in non-neoplastic bone marrow samples and between high-risk and low-risk samples. For risk- stratification analysis, only samples with complete clinical information were considered. In the heatmap analysis, z-scores were calculated by processing the delta CT data with RStudio. Correlations between the mRNA levels of SETD4 and SMYD2 in 83 ALL specimens were analyzed using Spearman correlation analysis. Survival curves were estimated using the Kaplan–Meier method. Survival data were censored for patients who were alive at the time of the last observation. Survival data were derived through the Kaplan–Meier method, excluding survival data of the patients who remained alive at the conclusion of the observation period. Survival outcomes were compared using the log-rank test. Univariate and multivariate Cox regression analyses were employed to evaluate the impact of SETD4 expression levels on both overall survival (OS) and event-free survival (EFS). Exploratory analysis of online data repositories Data for boxplot graphs showing SETD4 microarray transcription levels in leukemia samples and non-neoplastic normal samples were obtained from the Bloodspot database in the form of log2 scaled intensity values ( 17 ). The ALL samples were from the T and B-cell types and exhibited t(12;21), (1;19), t(8;14) and hyperploidy. RESULTS SETD4 transcription is upregulated in ALL patients To verify whether SETD4 was differentially expressed in ALL, we performed quantitative RT‒qPCR on extracts from bone marrow (BM) aspirates of ALL patients and of non-malignant BM samples and evaluated the relative expression using the housekeeping gene ACTB for normalization. The expression of SETD4 was significantly greater in malignant samples, with a median fold-change of 5.14 (95% CI = 0.4539–23.74; p = 0.0095, Mann‒Whitney U test, Fig. 1a). Similarly, two distinct microarray datasets with 318 and 317 ALL patients (Affymetrix Probes 219482_at and 23989_X_at, respectively) available in the Bloodspot database indicated that SETD4 was highly expressed (p < 0.0001) in the ALL samples compared to the non-leukemic samples (Fig. 1B). SETD4 transcription correlates with a decrease in leukemic burden and SMYD2 transcription during chemotherapy To investigate whether SETD4 is predominantly transcribed in leukemic cells compared to normal cells, we conducted RT‒ qPCR on samples from 15 patients on days 15 and 29 of chemotherapy and assessed whether SETD4 transcription levels decrease concomitantly with the reduction in leukemic burden. At the time of diagnosis, 13 patients exhibited high SETD4 expression. Among these, 11 patients demonstrated reduced SETD4 levels by day 15. Notably, the two patients with basal SETD4 expression at diagnosis did not exhibit lower levels at this time point. However, with the exception of patient 96 (from the basal expression group), all patients showed decreased SETD4 levels by day 29 (Fig. 2 a). Additionally, we evaluated the leukemic burden in the bone marrow of these 15 patients at three time points: diagnosis, day 15, and day 29 after initiating treatment (Fig. 2 b). As anticipated, all patients experienced a decline in leukemic cells by days 15 and 29 post-diagnosis, with five patients achieving complete clearance of leukemic blasts by day 29. We previously reported that SMYD2 transcription levels are upregulated in ALL patients and is a poor prognostic factor ( 9 ). We investigated whether SETD4 and SMYD2 share any biological relationship in this context. First, we compared the transcription levels of SETD4 and SMYD2 among all patients at diagnosis (Fig. 3a). Next, the transcription levels of SETD4 and SMYD2 were examined on days 15 and 29 of chemotherapy. Surprisingly, a positive and strong correlation was detected between both genes at diagnosis (Spearman r = 0.759, p < 0,0001) and on either day of treatment (Spearman r = 0.925, p < 0.01) (Fig. 3b). SETD4 transcription levels may be a marker for risk stratification To investigate the relationship between SETD4 expression levels and the risk stratification of ALL patients, samples from high-risk and low-risk groups were compared. Importantly, high-risk patients presented increased relative SETD4 mRNA expression (Fig. 4). Since SETD4 is upregulated in most ALL patients, particularly those classified as high-risk, we analyzed their survival to determine whether this methyltransferase could significantly impact survival outcomes. We observed that high expression levels of SETD4 are associated with decreased overall survival (OS) and event-free survival (EFS) in this subset of patients. Kaplan–Meier analysis revealed that the 3-year OS probability for the group of patients with high SETD4 expression was 27.8%, whereas it was 76.7% for the basal expression group (p < 0.05). Additionally, the 3-year EFS probability for the basal SETD4 expression group was 82.78%, which was significantly higher than that of the group with high SETD4 expression (Fig. 5 ). DISCUSSION Several KMTs have been identified as key players in leukemogenesis. In MLL-rearranged leukemia, the uncontrolled activities of the KMTs DOT1L and ASH1L are crucial for abnormal cell proliferation. Concurrently, rearrangements in MLL, which is also a methyltransferase, are considered unfavorable prognostic factors ( 18 – 21 ). Another KMT, WHSC1 (also known as MMSET or NSD2), is aberrantly highly expressed due to the t(4;14) chromosomal translocation in a myeloma subtype with a poor prognosis ( 22 ). Furthermore, the WHSCH1 p.E1099K (EK) mutation is significantly prevalent among patients who experience relapsed ALL, suggesting its importance in clonal evolution and the development of drug resistance ( 23 ). Additionally, SETD8 has been shown to regulate the interaction of p53 with Numb through methylation of the phosphotyrosine-binding (PTB) domain of the latter ( 24 ). Also, the association between the rs16917496 polymorphism of the SETD8 gene and the risk of ALL was significant ( 25 ). On the other hand, SETD1A has been implicated in regulating p53 and its target genes expression by biding to the Trp53 promoter and inducing specific miRNAs associated with it ( 26 – 28 ). Moreover, it has been linked to the process of progenitor B-cell maturation in mice ( 29 ). The first study highlighting the oncogenic significance of SETD4 was published by Faria and colleagues in 2013 ( 13 ). These findings highlight the role of SETD4 in breast cancer, suggesting that its structure is similar to that of SETD3, with differences mainly in loop regions. SETD4 was found in both the nucleus and cytosol in the breast cancer cell lines MDA-MB-231, MGSO-3, and MACL-1. Its upregulation was linked to an ER-negative and triple-negative phenotype. Knockdown of SETD4 decreased cell proliferation in MDA-MB-231 cells by affecting the G1/S cell cycle transition, significantly reducing cyclin D1 levels. Another study revealed that SETD4 controls breast cancer stem cell quiescence (qCSC) through heterochromatin formation via trimethylation of H3K20, leading to chemoradiotherapy resistance and tumor relapse in mice. Moreover, the authors identified SETD4 qCSCs in several cancer types, such as gastric, lung, liver, ovarian and cervical cancers. In addition, SETD4 upregulation has recently been identified in advanced-stage non-small cell lung cancer (NSCLC) tissues compared to early-stage tissues, particularly in the chemoresistant group. Furthermore, SETD4 overexpression facilitated PTEN-mediated inhibition of the PI3K-mTOR pathway in activated qLCSCs (A-qLCSCs), indicating that SETD4 plays a role in conferring chemoresistance, tumor progression, and poor prognosis in NSCLC by regulating the behavior of CSCs ( 12 ). Interestingly, another study revealed that the knockdown of SETD4 in hepatocellular carcinoma cells resistant to sorafenib restored their sensitivity to the drug, leading to a decrease in cell viability. A reduction in SETD4 expression combined with sorafenib treatment, downregulated AKT phosphorylation, thereby inducing the death of HCC cells ( 30 ). However, the involvement of SETD4 in leukemia has not been previously explored. On the other hand, SMYD2 has been identified as a significant therapeutic target in oncology, and its overexpression is linked to poor prognosis in various cancers, including papillary thyroid, bladder, gastric, cervical and liver cancers ( 31 – 35 ). Although the oncogenic mechanisms of SMYD2 have not been fully elucidated, it is known to modify the methylation pattern of p53, RB1 and PTEN, leading to the suppression of their transcriptional functions and the promotion of cell cycle progression ( 33 , 36 , 37 ). Our previous work revealed that SMYD2 expression was significantly higher in pediatric ALL patients than in controls and that OS and EFS were negatively correlated with SMYD2 expression. In addition, the level of SMYD2 decreased during treatment ( 9 ). These results were consistent with those of Zhang and colleagues, who reported a significantly reduced response to prednisone treatment in a group with high SMYD2 expression ( 10 ). In addition, SMYD2 upregulation pattern was also observed in chronic lymphocytic leukemia (CLL) patients ( 38 ). Bagistar and colleagues reported the significant involvement of smyd2 in the initiation of leukemia via the MLL-AF9 fusion oncogene without affecting normal development and hematopoiesis. Findings from in vivo and in vitro investigations in mice have shown that the absence of smyd2 in primary leukemia cells results in reduced competitive fitness compared to that in wild-type leukemia cells ( 39 ). Also, similar to SETD4 in breast cancer, SMYD2 has been described as a quiescence regulator, and its downregulation in acute myeloid leukemia (AML) results in reduced sensitivity to therapy ( 40 ). Taken together, these findings suggest the importance of SMYD2 in leukemia. Here, we provide new insights into the importance of SETD4 in ALL and its correlation with SMYD2 transcription. Our findings demonstrate that, similar to SMYD2 , SETD4 expression is also upregulated in ALL BM samples compared to non-neoplastic BM samples. This observation was consistently validated across databases and through different techniques, including qPCR and microarray analysis. Additionally, we observed a significant decrease in SETD4 expression on days 15 and 29 of chemotherapy. Given that both SMYD2 and SETD4 specifically trimethylate histone H3 at lysine 4 (H3K4me3) and promote cell cycle progression by stimulating the G1/S transition, we investigated the relationship between SETD4 and SMYD2 expression in ALL. We detected a strong correlation between the transcription levels of these genes before and during chemotherapy, suggesting that they share common transcriptional regulators or pathways. Further studies are warranted to explore this relationship in greater detail. Additionally, we observed that patients in the high-risk group exhibited elevated SETD4 mRNA expression. Furthermore, patients exhibiting high SETD4 expression had worse OS and EFS than patients with low expression. Although it is unclear whether this upregulation is a driver or a passenger alteration, it is plausible that SETD4 may act as an oncogene in this disease, given the well-established roles of various SET domain proteins in cancer ( 41 ). Despite the likely oncogenic effect of SETD4 on ALL leukemogenesis, its role in cancer development is ambiguous and appears to be context dependent. SETD4 is mostly downregulated in prostate cancer cells and tissue samples. A decrease in the expression of SETD4 is correlated with inferior clinicopathological characteristics, such as pathologic grade, clinical stage and Gleason score. Moreover, SETD4 overexpression inhibited prostate cancer cell proliferation ( 42 ). In contrast, the expression of SMYD2 was elevated in prostate cancer tissues compared with that in benign prostate tissues, and an increase in SMYD2 expression was linked to a greater risk of biochemical recurrence following radical prostatectomy. Additionally, reducing SMYD2 levels suppressed the proliferation of prostate cancer cells in vivo and in vitro ( 43 ). Although the limited sample size in our study, the data provide novel insights into the role of SETD4 in acute lymphoblastic leukemia (ALL) and reveal a positive association with SMYD2 transcription levels. These findings suggest a potential oncogenic role for SETD4 , highlighting its promise as a biomarker for treatment response and a potential target for future cancer pharmacology. Abbreviations ALL Acute lymphoblastic leukemia KMT Lysine methyltransferases RT‒qPCR Quantitative reverse transcription polymerase chain reaction BM Bone Marrow CSC Cancer steam cell NSCLC non-small cell lung cancer GBTLI Brazilian Cooperative Group for Treatment of Childhood Acute Lymphocytic Leukemia BFM 95-Berlin-Frankfurt-Münster 95 protocol WBC white blood cell BMMC Bone marrow mononuclear cell Cq Quantitation cycle NM Non-malignant OS Overall survival EFS Event-free survival CLL Chronic lymphocytic leukemia CML Chronic myeloid leukemia Declarations Ethics approval and consent to participate The study protocol was approved by the Regional Ethics Committee of the Federal District, Brazil, with written informed consent from patients and/or guardians. The study followed the Declaration of Helsinki. Availability of data and materials All data is available upon reasonable request. Competing interests The authors declare no competing interests. Funding This work was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de Apoio à Pesquisa do Distrito Federal (FAPDF). Authors' contributions F.P-S., A.B.M., and L.H.T.S., Conceptualization; L.H.T.S., D.A.R.R. and F.P-S., methodology; L.H.T.S managed specimen collection and collected the data; L.A.M.T. performed experiments and contributed to data analysis, M.B.L. partially contributed to the experiments presented in this manuscript. F.P-S., L.A.M.T., and M.B.L wrote and finalized the manuscript. All authors reviewed and approved the submitted version of the manuscript. Acknowledgements The authors are thankful to all members of the laboratory of molecular pathology of cancer for their support. We thank the staff of the Hospital da Criança de Brasília José Alencar for their kind assistance. References Inaba H, Mullighan CG. Pediatric acute lymphoblastic leukemia. Haematologica. 2020 Sep 10;105(11):2524–39. Tran TH, Hunger SP. The genomic landscape of pediatric acute lymphoblastic leukemia and precision medicine opportunities. Seminars in Cancer Biology. 2022 Sep;84:144–52. Carroll AJ, Crist WM, Parmley RT, Roper M, Finley MDCWH. Pre-B Cell Leukemia Associated With Chromosome Translocation 1; 19. Blood. 1984 Mar 1;63(3):721–4. Van den Berghe H, David G, Broeckaert-Van Orshoven A, Louwagie A, Verwilghen R, Casteels-Van Daele M, et al. A new chromosome anomaly in acute lymphoblastic leukemia (ALL). Hum Genet. 1979 Jan 25;46(2):173–80. Prognostic importance of chromosome number in 136 untreated children with acute lymphoblastic leukemia | Blood | American Society of Hematology [Internet]. [cited 2024 Feb 24]. Available from: https://ashpublications.org/blood/article/60/4/864/163138/Prognostic-importance-of-chromosome-number-in-136 Husmann D, Gozani O. Histone lysine methyltransferases in biology and disease. Nat Struct Mol Biol. 2019 Oct;26(10):880–9. Huang J, Perez-Burgos L, Placek BJ, Sengupta R, Richter M, Dorsey JA, et al. Repression of p53 activity by Smyd2-mediated methylation. Nature. 2006 Nov;444(7119):629–32. Li LX, Zhou JX, Calvet JP, Godwin AK, Jensen RA, Li X. Lysine methyltransferase SMYD2 promotes triple negative breast cancer progression. Cell Death Dis. 2018 Feb 27;9(3):1–17. Sakamoto LHT, Andrade RV de, Felipe MSS, Motoyama AB, Pittella Silva F. SMYD2 is highly expressed in pediatric acute lymphoblastic leukemia and constitutes a bad prognostic factor. Leukemia Research. 2014 Apr 1;38(4):496–502. Overexpression of SET and MYND domain-containing protein 2 (SMYD2) is associated with poor prognosis in pediatric B lineage acute lymphoblastic leukemia [Internet]. [cited 2024 May 29]. Available from: https://www.tandfonline.com/doi/epdf/10.1080/10428194.2019.1675875?needAccess=true Ye S, Ding YF, Jia WH, Liu XL, Feng JY, Zhu Q, et al. SET Domain-Containing Protein 4 Epigenetically Controls Breast Cancer Stem Cell Quiescence. Cancer Res. 2019 Sep 15;79(18):4729–43. Wang Y, Yu Y, Yang W, Wu L, Yang Y, Lu Q, et al. SETD4 Confers Cancer Stem Cell Chemoresistance in Nonsmall Cell Lung Cancer Patients via the Epigenetic Regulation of Cellular Quiescence. Stem Cells Int. 2023;2023:7367854. Faria JAQA, Corrêa NCR, de Andrade C, de Angelis Campos AC, dos Santos Samuel de Almeida R, Rodrigues TS, et al. SET domain-containing Protein 4 (SETD4) is a Newly Identified Cytosolic and Nuclear Lysine Methyltransferase involved in Breast Cancer Cell Proliferation. J Cancer Sci Ther. 2013 Jan 21;5(2):58–65. Feng X, Lu H, Yue J, Schneider N, Liu J, Denzin LK, et al. Loss of Setd4 delays radiation-induced thymic lymphoma in mice. DNA Repair (Amst). 2020 Feb;86:102754. Brandalise S, Odone V, Pereira W, Andrea M, Zanichelli M, Aranega V. Treatment results of three consecutive Brazilian cooperative childhood ALL protocols: GBTLI-80, GBTLI-82 and -85. ALL Brazilian Group. Leukemia. 1993 Aug;7 Suppl 2:S142-145. Möricke A, Reiter A, Zimmermann M, Gadner H, Stanulla M, Dördelmann M, et al. Risk-adjusted therapy of acute lymphoblastic leukemia can decrease treatment burden and improve survival: treatment results of 2169 unselected pediatric and adolescent patients enrolled in the trial ALL-BFM 95. Blood. 2008 May 1;111(9):4477–89. Bagger FO, Sasivarevic D, Sohi SH, Laursen LG, Pundhir S, Sønderby CK, et al. BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis. Nucleic Acids Res. 2016 Jan 4;44(D1):D917–24. Grigsby SM, Friedman A, Chase J, Waas B, Ropa J, Serio J, et al. Elucidating the Importance of DOT1L Recruitment in MLL-AF9 Leukemia and Hematopoiesis. Cancers (Basel). 2021 Feb 5;13(4):642. El Chaer F, Keng M, Ballen KK. MLL-Rearranged Acute Lymphoblastic Leukemia. Curr Hematol Malig Rep. 2020 Apr;15(2):83–9. Zhu L, Li Q, Wong SHK, Huang M, Klein BJ, Shen J, et al. ASH1L Links Histone H3 Lysine 36 di-methylation to MLL Leukemia. Cancer Discov. 2016 Jul;6(7):770–83. Aljazi MB, Gao Y, Wu Y, Mias GI, He J. Histone H3K36me2-Specific Methyltransferase ASH1L Promotes MLL-AF9-Induced Leukemogenesis. Front Oncol. 2021 Oct 8;11:754093. Issa ME, Takhsha FS, Chirumamilla CS, Perez-Novo C, Vanden Berghe W, Cuendet M. Epigenetic strategies to reverse drug resistance in heterogeneous multiple myeloma. Clin Epigenetics. 2017 Feb 10;9:17. Narang S, Evensen NA, Saliba J, Pierro J, Loh ML, Brown PA, et al. NSD2 E1099K drives relapse in pediatric acute lymphoblastic leukemia by disrupting 3D chromatin organization. Genome Biol. 2023 Apr 4;24(1):64. Dhami G, Liu H, Galka M, Voss C, Wei R, Muranko K, et al. Dynamic Methylation of Numb by Set8 Regulates Its Binding to p53 and Apoptosis. Molecular Cell. 2013;50(4):565–76. Hashemi M, Sheybani-Nasab M, Naderi M, Roodbari F, Taheri M. Association of functional polymorphism at the miR-502-binding site in the 3′ untranslated region of the SETD8 gene with risk of childhood acute lymphoblastic leukemia, a preliminary report. Tumor Biol. 2014 Oct 1;35(10):10375–9. Tajima K, Yae T, Javaid S, Tam O, Comaills V, Morris R, et al. SETD1A modulates cell cycle progression through a miRNA network that regulates p53 target genes. Nat Commun. 2015 Sep 23;6(1):8257. Yae T, Tajima K, Maheswaran S. SETD1A induced miRNA network suppresses the p53 gene expression module. Cell Cycle. 2016;15(4):487–8. Ogawa S, Fukuda A, Matsumoto Y, Hanyu Y, Sono M, Fukunaga Y, et al. SETDB1 Inhibits p53-Mediated Apoptosis and Is Required for Formation of Pancreatic Ductal Adenocarcinomas in Mice. Gastroenterology. 2020 Aug;159(2):682-696.e13. Tusi BK, Deng C, Salz T, Zeumer L, Li Y, So CWE, et al. Setd1a regulates progenitor B-cell-to-precursor B-cell development through histone H3 lysine 4 trimethylation and Ig heavy-chain rearrangement. FASEB J. 2015 Apr;29(4):1505–15. Li GM, Wang YG, Pan Q, Wang J, Fan JG, Sun C. RNAi screening with shRNAs against histone methylation-related genes reveals determinants of sorafenib sensitivity in hepatocellular carcinoma cells. Int J Clin Exp Pathol. 2014;7(3):1085–92. Tan Z, Fu S, Feng R, Huang Y, Li N, Wang H, et al. Identification of Potential Biomarkers for Progression and Prognosis of Bladder Cancer by Comprehensive Bioinformatics Analysis. J Oncol. 2022 Apr 19;2022:1802706. Xu H, Ba Z, Liu C, Yu X. Long noncoding RNA DLEU1 promotes proliferation and glycolysis of gastric cancer cells via APOC1 upregulation by recruiting SMYD2 to induce trimethylation of H3K4 modification. Transl Oncol. 2023 Oct;36:101731. Wang Y, Jin G, Guo Y, Cao Y, Niu S, Fan X, et al. SMYD2 suppresses p53 activity to promote glucose metabolism in cervical cancer. Exp Cell Res. 2021 Jul 15;404(2):112649. Xu W, Chen F, Fei X, Yang X, Lu X. Overexpression of SET and MYND Domain-Containing Protein 2 (SMYD2) Is Associated with Tumor Progression and Poor Prognosis in Patients with Papillary Thyroid Carcinoma. Med Sci Monit. 2018 Oct 15;24:7357–65. Positive Expression of SMYD2 is Associated with Poor Prognosis in Patients with Primary Hepatocellular Carcinoma - PubMed [Internet]. [cited 2024 May 30]. Available from: https://pubmed.ncbi.nlm.nih.gov/29344279/ Cho HS, Hayami S, Toyokawa G, Maejima K, Yamane Y, Suzuki T, et al. RB1 methylation by SMYD2 enhances cell cycle progression through an increase of RB1 phosphorylation. Neoplasia. 2012 Jun;14(6):476–86. Wang L, Li L, Zhang H, Luo X, Dai J, Zhou S, et al. Structure of Human SMYD2 Protein Reveals the Basis of p53 Tumor Suppressor Methylation. J Biol Chem. 2011 Nov 4;286(44):38725–37. Residual expression of SMYD2 and SMYD3 is associated with the acquisition of complex karyotype in chronic lymphocytic leukemia | Tumor Biology [Internet]. [cited 2024 May 30]. Available from: https://link.springer.com/article/10.1007/s13277-016-4846-z Bagislar S, Sabò A, Kress TR, Doni M, Nicoli P, Campaner S, et al. Smyd2 is a Myc-regulated gene critical for MLL-AF9 induced leukemogenesis. Oncotarget. 2016 Sep 13;7(41):66398–415. Zipin-Roitman A, Aqaqe N, Yassin M, Biechonski S, Amar M, van Delft MF, et al. SMYD2 lysine methyltransferase regulates leukemia cell growth and regeneration after genotoxic stress. Oncotarget. 2017 Feb 6;8(10):16712–27. Bennett RL, Swaroop A, Troche C, Licht JD. The Role of Nuclear Receptor-Binding SET Domain Family Histone Lysine Methyltransferases in Cancer. Cold Spring Harb Perspect Med. 2017 Jun 1;7(6):a026708. Wang C, Wang T, Li KJ, Hu LH, Li Y, Yu YZ, et al. SETD4 inhibits prostate cancer development by promoting H3K27me3-mediated NUPR1 transcriptional repression and cell cycle arrest. Cancer Letters. 2023 Nov 28;579:216464. Li J, Wan F, Zhang J, Zheng S, Yang Y, Hong Z, et al. Targeting SMYD2 inhibits prostate cancer cell growth by regulating c-Myc signaling. Molecular Carcinogenesis. 2023;62(7):940–50. Additional Declarations No competing interests reported. Supplementary Files Supptable1.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6191336","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":433841843,"identity":"b0ad9fe3-ccec-466b-beaf-5422a315131a","order_by":0,"name":"Luis Augusto Muniz Telles","email":"","orcid":"","institution":"University of Brasília","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"Augusto Muniz","lastName":"Telles","suffix":""},{"id":433841844,"identity":"e2bf3132-eba6-4304-89d2-a79693860c7a","order_by":1,"name":"Mariana Braccialli de Loyola","email":"","orcid":"","institution":"University of Brasília","correspondingAuthor":false,"prefix":"","firstName":"Mariana","middleName":"Braccialli","lastName":"de Loyola","suffix":""},{"id":433841845,"identity":"43de0065-156f-4eca-8f83-d0e8b066d96c","order_by":2,"name":"Luis Henrique Toshihiro Sakamoto","email":"","orcid":"","institution":"University of Brasília","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"Henrique Toshihiro","lastName":"Sakamoto","suffix":""},{"id":433841846,"identity":"3de6d61e-6b82-4c89-97b3-7adb9a892d91","order_by":3,"name":"Doralina do Amaral Ramos Rabello","email":"","orcid":"","institution":"University of Brasília","correspondingAuthor":false,"prefix":"","firstName":"Doralina","middleName":"do Amaral Ramos","lastName":"Rabello","suffix":""},{"id":433841847,"identity":"5d961949-3cc3-422d-a9d7-cbcf1c70492d","order_by":4,"name":"Andrea Barretto Motoyama","email":"","orcid":"","institution":"University of Brasília","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"Barretto","lastName":"Motoyama","suffix":""},{"id":433841848,"identity":"08859e0f-c52b-44bc-9047-22c8bf835d15","order_by":5,"name":"Fabio Pittella-Silva","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYDACZhBRYMHAz8DAxsDYQJQWZqA6AwkGyQaitTBAtRgcIFaLOTv/8QcfDCTkjW/kHnvAuOMeYS2WzcyMjTMMJAy33chLN2A8U0xYi8FhZsZmHgMJxm03cswkGNsSiNTyx0DCfvMMkrQAvZ+4QYJYLUC/GM7sMZBInnHmjblB4hkitJjzH3zw4UeFjW1/e47Zg487iHEYCo8IDehaRsEoGAWjYBRgAwDAxDQx6CzYGgAAAABJRU5ErkJggg==","orcid":"","institution":"University of Brasília","correspondingAuthor":true,"prefix":"","firstName":"Fabio","middleName":"","lastName":"Pittella-Silva","suffix":""}],"badges":[],"createdAt":"2025-03-10 03:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6191336/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6191336/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79325789,"identity":"32750507-023d-4698-9394-f4f3f51d987b","added_by":"auto","created_at":"2025-03-27 05:30:44","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":64364,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSETD4\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e mRNA expression in leukemic bone marrow samples compared to that in non-neoplastic BM samples\u003c/strong\u003e. (a) \u003cem\u003eSETD4\u003c/em\u003eexpression in leukemic BM samples from 83 patients compared to that in non-neoplastic samples. Boxplot representing log-scaled qPCR SETD4 relative quantitation values normalized to\u003cem\u003e ACTB\u003c/em\u003e. The Mann‒Whitney U test was utilized to assess group differences. Compared with ALL samples (n=83), non-malignant samples (n=8) exhibited lower \u003cem\u003eSETD4\u003c/em\u003e expression. (b) Comparison of \u003cem\u003eSETD4\u003c/em\u003emRNA expression non-malignant (NM) and malignant BM ALL samples from the Bloodspot dataset. The transcription levels of \u003cem\u003eSETD4\u003c/em\u003eare upregulated in ALL samples. The data were confirmed by two distinct probes available in Bloodspot.\u003c/p\u003e","description":"","filename":"Figure1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6191336/v1/e4de5b933378a6be1aee7588.jpg"},{"id":79325790,"identity":"1e34fe8c-1fac-446f-acf6-28754d7c318a","added_by":"auto","created_at":"2025-03-27 05:30:44","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":54479,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe correlation between BM leukemic burden and SETD4 mRNA expression. \u003c/strong\u003e(a) Log scaled RQ \u003cem\u003eSETD4\u003c/em\u003e mRNA level data of 15 patients referred to the 15\u003csup\u003eth\u003c/sup\u003e and 29\u003csup\u003eth\u003c/sup\u003e days of chemotherapy. Patients marked with asterisks (*) did not exhibit a decrease in SETD4 expression on the 15th day of treatment. (b) Analysis of the percentage of leukemic BM cells at diagnosis and on the 15\u003csup\u003eth\u003c/sup\u003e and 29\u003csup\u003eth\u003c/sup\u003e days of chemotherapy. BM leukemic cell percentages are plottedas absolute values for diagnosis and the 15\u003csup\u003eth\u003c/sup\u003e, and 29\u003csup\u003eth\u003c/sup\u003e days of chemotherapy.\u003c/p\u003e","description":"","filename":"Figure2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6191336/v1/a66894ed6b6c14a45f4cc2cf.jpg"},{"id":79325809,"identity":"52efa440-e836-4060-9f1c-973cb2c3f8e0","added_by":"auto","created_at":"2025-03-27 05:30:45","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":82785,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation between \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSETD4 \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSMYD2\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eexpression profiles.\u003c/strong\u003e (a) Heatmap showing mRNA z-score expression levels analyzed in samples from 83 patients, revealing a substantial correlation between both genes (Spearman \u003cem\u003er\u003c/em\u003e = 0.759, p \u0026lt;0,0001). (b) Samples from 15 patients were analyzed on days 15 and 29 of treatment and showed a strong correlation (Spearman r = 0.925, p \u0026lt; 0.01). Axes represent log-scaled relative quantitation values for each gene. Points illustrate the relationship between these values.\u003c/p\u003e","description":"","filename":"Figure3.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6191336/v1/44808d7e833ed933fd98b201.jpg"},{"id":79325791,"identity":"2bb64989-a3b5-405b-9b17-4e5e8bc4c2b4","added_by":"auto","created_at":"2025-03-27 05:30:44","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":30551,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSETD4\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e mRNA expression in BM samples from the high-risk and low-risk groups\u003c/strong\u003e. Boxplot illustrating log-scaled qPCR \u003cem\u003eSETD4\u003c/em\u003erelative quantitation values normalized to \u003cem\u003eACTB\u003c/em\u003e. Out of 83 patients, 47 presented complete clinical data and were categorized as high-risk (n=38) or low risk (n=9). The Mann‒Whitney U test was used to assess group differences.\u003c/p\u003e","description":"","filename":"Figure4.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6191336/v1/4736817b829167fb4a31d160.jpg"},{"id":79325810,"identity":"38d0ec72-c2a5-4bb0-abbf-9ebcf6b9360c","added_by":"auto","created_at":"2025-03-27 05:30:45","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":69580,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall survival and event-free survival of ALL patients\u003c/strong\u003e \u003cstrong\u003eaccording to \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSETD4\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e expression levels. \u003c/strong\u003e(a) High \u003cem\u003eSETD4 \u003c/em\u003eexpression is associated with poor OS in childhood ALL patients (p=0.034) with an HR of 2.47 (95% CI: 1.069–5.713). The 3-year OS probability for patients with high SETD4 expression was 27.8 (b) High \u003cem\u003eSETD4 \u003c/em\u003eexpression is also correlated with poor EFS in childhood ALL patients (p=0.041), with an HR of 2.34 (95% CI: 1.013–5.399). The EFS probability was 82.78% for the basal group.\u003c/p\u003e","description":"","filename":"Figure5.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6191336/v1/c0a4fe86c873367f63788d2e.jpg"},{"id":81091870,"identity":"44e45ce8-b258-4021-b8a1-079f803da797","added_by":"auto","created_at":"2025-04-22 07:17:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1102593,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6191336/v1/deaaf609-48f5-4fc1-9080-4f647116a949.pdf"},{"id":79325793,"identity":"afc75a4c-793e-4f68-ae82-6a1d21524946","added_by":"auto","created_at":"2025-03-27 05:30:44","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":35129,"visible":true,"origin":"","legend":"","description":"","filename":"Supptable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6191336/v1/e6ef09e5be4f9d6d08730bfb.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"SETD4 expression is correlated with leukemic burden and SMYD2 transcription in acute lymphoblastic leukemia ","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAcute lymphoblastic leukemia (ALL) is the most common childhood malignancy, with an incidence of approximately 2\u0026ndash;4 cases per 100,000 children under 15 years of age. Notably, the peak incidence occurs between 3 and 5 years of age (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Despite favorable treatment outcomes, relapsed disease remains the leading cause of mortality in pediatric ALL patients. Consequently, ongoing research has focused on identifying better prognostic markers and treatment enhancements for ALL management (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). ALL comprises two primary subtypes: B-cell ALL and T-cell ALL. B- ALL is significantly more prevalent, constituting approximately 85% of all cases (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Cytogenetic aberrations are common findings in ALL, especially among pediatric patients and have long been recognized for their substantial impact on clinical outcomes (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). However, recent advancements in sequencing and genomic analysis technologies have unveiled novel alterations at the submicroscopic scale. These subtle changes play crucial roles in determining disease aggressiveness and resistance to chemotherapy. Collectively, these scientific breakthroughs enable the identification of new ALL subtypes and enhance the precision of patient prognosis, thereby facilitating more effective risk-adapted treatment strategies and supportive care (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLysine methyltransferases (KMTs) are proteins that add methyl marks to lysine residues in both histones and non-histone proteins. These marks contribute to a wide range of epigenetic modifications, including the establishment and propagation of various gene expression patterns. Dysregulation of KMT activity can cause widespread epigenetic changes that contribute to cancer development and progression (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSMYD2 (SET and MYND domain-containing protein 2) is a lysine methyltransferase known to play significant roles in cancer (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Aberrant \u003cem\u003eSMYD2\u003c/em\u003e expression in children with ALL was previously described as a poor prognostic factor, as it correlated with unfavorable clinical characteristics such as age and increased blast counts following chemotherapy (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). SET domain-containing protein 4 (SETD4), which is also a histone lysine methyltransferase, has been implicated in the regulation of various cellular processes, including cell proliferation, cell cycle regulation, and maintenance of cancer stem cell (CSC) quiescence. Recent studies have shed light on its roles in breast cancer, non-small cell lung cancer (NSCLC), and radiation-induced lymphomagenesis (\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). However, its clinical significance in ALL remain unexplored.\u003c/p\u003e \u003cp\u003eHere, we analyzed the expression pattern of \u003cem\u003eSETD4\u003c/em\u003e among pediatric ALL patients and non-neoplastic bone marrow samples and investigated the correlation between \u003cem\u003eSETD4\u003c/em\u003e transcription changes and the leukemic burden in ALL patients during chemotherapy and \u003cem\u003eSMYD2\u003c/em\u003e transcription.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient sample collection\u003c/h2\u003e \u003cp\u003eBone marrow aspirates from 83 pediatric ALL patients were collected at Jose Alencar Children\u0026rsquo;s Hospital of Brasilia between 2008 and 2010 during initial disease presentation as part of routine diagnosis and genetic analysis of leukemia. B-ALL patients were treated according to the Brazilian Cooperative Group for Treatment of Childhood Acute Lymphocytic Leukemia (GBTLI) protocol, and T-ALL patients were treated according to the ALL-Berlin-Frankfurt-M\u0026uuml;nster (BFM-95) protocol (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Bone marrow samples from 15 patients were obtained on the 15th and 29th days of induction chemotherapy. Additionally, bone marrow samples from eight children with idiopathic thrombocytopenic purpura were used as non-neoplastic controls. Blast percentages were confirmed in Wright ‒Giemsa-stained smears, with all leukemic samples containing more than 40% blasts. The study protocol was approved by the Regional Ethics Committee of the Federal District, Brazil, with written informed consent from patients and/or guardians. The study followed the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical data collection\u003c/h3\u003e\n\u003cp\u003eClinical characteristics, including sex, age and white blood cell (WBC) count in peripheral blood at ALL diagnosis, immunophenotyping of bone marrow blasts, cytogenetic alterations and bone marrow status at the 15th and 29th days of chemotherapy, were obtained from medical records and described previously (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). High-risk patients included those who were e less than 2 years old or more than 9 years old, and/or had peripheral blood WBC counts exceeding 50,000/mm3, and/or showed infiltration in the central nervous system at the time of diagnosis and/or unfavorable cytogenetic findings.\u003c/p\u003e\n\u003ch3\u003eRNA isolation, cDNA synthesis and RT‒qPCR\u003c/h3\u003e\n\u003cp\u003eBone marrow mononuclear cells (BMMCs) were isolated by Ficoll density centrifugation. Total RNA was extracted from each sample using TRIzol Reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer\u0026rsquo;s protocol. Single-stranded complementary DNA was generated from total RNA with reverse transcriptase and random primers, using the High-Capacity cDNA Reverse Transcription Kit (Life Technologies, Carlsbad, CA, USA). qPCR was performed on a StepOnePlusTM Real-Time PCR System (Applied Biosystems, Carlsbad, CA, USA) using Taq-Man Gene Expression Assays according to the manufacturer\u0026rsquo;s instructions (Hs00213731_m1, Cat. no. 4331182 for \u003cem\u003eSETD4;\u003c/em\u003e Hs00220210 m1, Cat. no. 4331182 for \u003cem\u003eSMYD2\u003c/em\u003e; and Hs99999903 m1, Cat. no. 4331182 for \u003cem\u003eACTB\u003c/em\u003e; Life Technologies). qPCR assays were carried out in a final volume of 10 \u0026micro;L in 96-well plates. Each plate included triplicates of cDNA from bone marrow samples, multiple water blanks and triplicates of inter-run calibrators (a unique cDNA sample used for all PCR run plates). PCR was conducted with the following conditions: 95\u0026deg;C for 2 min, followed by 40 cycles at 95\u0026deg;C for 15 s and 60\u0026deg;C for 40 s. Quantitation cycle (Cq) values were obtained from this experiment and the ∆∆CT method was applied to these values using \u003cem\u003eACTB\u003c/em\u003e as a reference gene for input normalization and scaling all samples by the mean Cq values of non-neoplastic samples. The 3rd quartile of non-neoplastic samples RQ\u0026rsquo;s was used as a threshold to classify a sample as having high or basal \u003cem\u003eSETD4\u003c/em\u003e mRNA expression. The datasets analyzed during the current study are available in the supplementary materials (Table\u0026nbsp;1).\u003c/p\u003e\n\u003ch3\u003eRT‒qPCR data and statistical analysis\u003c/h3\u003e\n\u003cp\u003eDescriptive statistics were used to summarize the study data. Statistical significance was defined as a two-tailed p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. We used Mann‒Whitney U test for independent samples to compare the expression of \u003cem\u003eSETD4\u003c/em\u003e between ALL and in non-neoplastic bone marrow samples and between high-risk and low-risk samples. For risk- stratification analysis, only samples with complete clinical information were considered. In the heatmap analysis, z-scores were calculated by processing the delta CT data with RStudio. Correlations between the mRNA levels of SETD4 and SMYD2 in 83 ALL specimens were analyzed using Spearman correlation analysis. Survival curves were estimated using the Kaplan\u0026ndash;Meier method. Survival data were censored for patients who were alive at the time of the last observation. Survival data were derived through the Kaplan\u0026ndash;Meier method, excluding survival data of the patients who remained alive at the conclusion of the observation period. Survival outcomes were compared using the log-rank test. Univariate and multivariate Cox regression analyses were employed to evaluate the impact of \u003cem\u003eSETD4\u003c/em\u003e expression levels on both overall survival (OS) and event-free survival (EFS).\u003c/p\u003e\n\u003ch3\u003eExploratory analysis of online data repositories\u003c/h3\u003e\n\u003cp\u003eData for boxplot graphs showing \u003cem\u003eSETD4\u003c/em\u003e microarray transcription levels in leukemia samples and non-neoplastic normal samples were obtained from the Bloodspot database in the form of log2 scaled intensity values (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The ALL samples were from the T and B-cell types and exhibited t(12;21), (1;19), t(8;14) and hyperploidy.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSETD4 transcription is upregulated in ALL patients\u003c/h2\u003e \u003cp\u003eTo verify whether \u003cem\u003eSETD4\u003c/em\u003e was differentially expressed in ALL, we performed quantitative RT‒qPCR on extracts from bone marrow (BM) aspirates of ALL patients and of non-malignant BM samples and evaluated the relative expression using the housekeeping gene \u003cem\u003eACTB\u003c/em\u003e for normalization. The expression of \u003cem\u003eSETD4\u003c/em\u003e was significantly greater in malignant samples, with a median fold-change of 5.14 (95% CI\u0026thinsp;=\u0026thinsp;0.4539\u0026ndash;23.74; p\u0026thinsp;=\u0026thinsp;0.0095, Mann‒Whitney U test, Fig.\u0026nbsp;1a). Similarly, two distinct microarray datasets with 318 and 317 ALL patients (Affymetrix Probes 219482_at and 23989_X_at, respectively) available in the Bloodspot database indicated that \u003cem\u003eSETD4\u003c/em\u003e was highly expressed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) in the ALL samples compared to the non-leukemic samples (Fig.\u0026nbsp;1B).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSETD4 transcription correlates with a decrease in leukemic burden and SMYD2 transcription during chemotherapy\u003c/h3\u003e\n\u003cp\u003eTo investigate whether \u003cem\u003eSETD4\u003c/em\u003e is predominantly transcribed in leukemic cells compared to normal cells, we conducted RT‒ qPCR on samples from 15 patients on days 15 and 29 of chemotherapy and assessed whether \u003cem\u003eSETD4\u003c/em\u003e transcription levels decrease concomitantly with the reduction in leukemic burden. At the time of diagnosis, 13 patients exhibited high \u003cem\u003eSETD4\u003c/em\u003e expression. Among these, 11 patients demonstrated reduced \u003cem\u003eSETD4\u003c/em\u003e levels by day 15. Notably, the two patients with basal \u003cem\u003eSETD4\u003c/em\u003e expression at diagnosis did not exhibit lower levels at this time point. However, with the exception of patient 96 (from the basal expression group), all patients showed decreased \u003cem\u003eSETD4\u003c/em\u003e levels by day 29 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eAdditionally, we evaluated the leukemic burden in the bone marrow of these 15 patients at three time points: diagnosis, day 15, and day 29 after initiating treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). As anticipated, all patients experienced a decline in leukemic cells by days 15 and 29 post-diagnosis, with five patients achieving complete clearance of leukemic blasts by day 29.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e We previously reported that \u003cem\u003eSMYD2\u003c/em\u003e transcription levels are upregulated in ALL patients and is a poor prognostic factor (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). We investigated whether \u003cem\u003eSETD4\u003c/em\u003e and \u003cem\u003eSMYD2\u003c/em\u003e share any biological relationship in this context. First, we compared the transcription levels of \u003cem\u003eSETD4\u003c/em\u003e and \u003cem\u003eSMYD2\u003c/em\u003e among all patients at diagnosis (Fig.\u0026nbsp;3a). Next, the transcription levels of \u003cem\u003eSETD4\u003c/em\u003e and \u003cem\u003eSMYD2\u003c/em\u003e were examined on days 15 and 29 of chemotherapy. Surprisingly, a positive and strong correlation was detected between both genes at diagnosis (Spearman \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.759, p\u0026thinsp;\u0026lt;\u0026thinsp;0,0001) and on either day of treatment (Spearman \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.925, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;3b).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSETD4 transcription levels may be a marker for risk stratification\u003c/h2\u003e \u003cp\u003eTo investigate the relationship between \u003cem\u003eSETD4\u003c/em\u003e expression levels and the risk stratification of ALL patients, samples from high-risk and low-risk groups were compared. Importantly, high-risk patients presented increased relative \u003cem\u003eSETD4\u003c/em\u003e mRNA expression (Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eSince \u003cem\u003eSETD4\u003c/em\u003e is upregulated in most ALL patients, particularly those classified as high-risk, we analyzed their survival to determine whether this methyltransferase could significantly impact survival outcomes. We observed that high expression levels of \u003cem\u003eSETD4\u003c/em\u003e are associated with decreased overall survival (OS) and event-free survival (EFS) in this subset of patients.\u003c/p\u003e \u003cp\u003eKaplan\u0026ndash;Meier analysis revealed that the 3-year OS probability for the group of patients with high \u003cem\u003eSETD4\u003c/em\u003e expression was 27.8%, whereas it was 76.7% for the basal expression group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, the 3-year EFS probability for the basal \u003cem\u003eSETD4\u003c/em\u003e expression group was 82.78%, which was significantly higher than that of the group with high \u003cem\u003eSETD4\u003c/em\u003e expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eSeveral KMTs have been identified as key players in leukemogenesis. In MLL-rearranged leukemia, the uncontrolled activities of the KMTs DOT1L and ASH1L are crucial for abnormal cell proliferation. Concurrently, rearrangements in MLL, which is also a methyltransferase, are considered unfavorable prognostic factors (\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Another KMT, WHSC1 (also known as MMSET or NSD2), is aberrantly highly expressed due to the t(4;14) chromosomal translocation in a myeloma subtype with a poor prognosis (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Furthermore, the \u003cem\u003eWHSCH1\u003c/em\u003e p.E1099K (EK) mutation is significantly prevalent among patients who experience relapsed ALL, suggesting its importance in clonal evolution and the development of drug resistance (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Additionally, \u003cem\u003eSETD8\u003c/em\u003e has been shown to regulate the interaction of p53 with Numb through methylation of the phosphotyrosine-binding (PTB) domain of the latter (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Also, the association between the rs16917496 polymorphism of the \u003cem\u003eSETD8\u003c/em\u003e gene and the risk of ALL was significant (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). On the other hand, \u003cem\u003eSETD1A\u003c/em\u003e has been implicated in regulating p53 and its target genes expression by biding to the Trp53 promoter and inducing specific miRNAs associated with it (\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Moreover, it has been linked to the process of progenitor B-cell maturation in mice (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe first study highlighting the oncogenic significance of \u003cem\u003eSETD4\u003c/em\u003e was published by Faria and colleagues in 2013 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). These findings highlight the role of SETD4 in breast cancer, suggesting that its structure is similar to that of SETD3, with differences mainly in loop regions. SETD4 was found in both the nucleus and cytosol in the breast cancer cell lines MDA-MB-231, MGSO-3, and MACL-1. Its upregulation was linked to an ER-negative and triple-negative phenotype. Knockdown of \u003cem\u003eSETD4\u003c/em\u003e decreased cell proliferation in MDA-MB-231 cells by affecting the G1/S cell cycle transition, significantly reducing cyclin D1 levels.\u003c/p\u003e \u003cp\u003eAnother study revealed that \u003cem\u003eSETD4\u003c/em\u003e controls breast cancer stem cell quiescence (qCSC) through heterochromatin formation via trimethylation of H3K20, leading to chemoradiotherapy resistance and tumor relapse in mice. Moreover, the authors identified SETD4 qCSCs in several cancer types, such as gastric, lung, liver, ovarian and cervical cancers. In addition, \u003cem\u003eSETD4\u003c/em\u003e upregulation has recently been identified in advanced-stage non-small cell lung cancer (NSCLC) tissues compared to early-stage tissues, particularly in the chemoresistant group. Furthermore, \u003cem\u003eSETD4\u003c/em\u003e overexpression facilitated PTEN-mediated inhibition of the PI3K-mTOR pathway in activated qLCSCs (A-qLCSCs), indicating that SETD4 plays a role in conferring chemoresistance, tumor progression, and poor prognosis in NSCLC by regulating the behavior of CSCs (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Interestingly, another study revealed that the knockdown of \u003cem\u003eSETD4\u003c/em\u003e in hepatocellular carcinoma cells resistant to sorafenib restored their sensitivity to the drug, leading to a decrease in cell viability. A reduction in \u003cem\u003eSETD4\u003c/em\u003e expression combined with sorafenib treatment, downregulated AKT phosphorylation, thereby inducing the death of HCC cells (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). However, the involvement of \u003cem\u003eSETD4\u003c/em\u003e in leukemia has not been previously explored.\u003c/p\u003e \u003cp\u003eOn the other hand, \u003cem\u003eSMYD2\u003c/em\u003e has been identified as a significant therapeutic target in oncology, and its overexpression is linked to poor prognosis in various cancers, including papillary thyroid, bladder, gastric, cervical and liver cancers (\u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Although the oncogenic mechanisms of \u003cem\u003eSMYD2\u003c/em\u003e have not been fully elucidated, it is known to modify the methylation pattern of p53, RB1 and PTEN, leading to the suppression of their transcriptional functions and the promotion of cell cycle progression (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur previous work revealed that \u003cem\u003eSMYD2\u003c/em\u003e expression was significantly higher in pediatric ALL patients than in controls and that OS and EFS were negatively correlated with \u003cem\u003eSMYD2\u003c/em\u003e expression. In addition, the level of SMYD2 decreased during treatment (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). These results were consistent with those of Zhang and colleagues, who reported a significantly reduced response to prednisone treatment in a group with high \u003cem\u003eSMYD2\u003c/em\u003e expression (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). In addition, \u003cem\u003eSMYD2\u003c/em\u003e upregulation pattern was also observed in chronic lymphocytic leukemia (CLL) patients (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBagistar and colleagues reported the significant involvement of \u003cem\u003esmyd2\u003c/em\u003e in the initiation of leukemia via the MLL-AF9 fusion oncogene without affecting normal development and hematopoiesis. Findings from \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e investigations in mice have shown that the absence of \u003cem\u003esmyd2\u003c/em\u003e in primary leukemia cells results in reduced competitive fitness compared to that in wild-type leukemia cells (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Also, similar to \u003cem\u003eSETD4\u003c/em\u003e in breast cancer, \u003cem\u003eSMYD2\u003c/em\u003e has been described as a quiescence regulator, and its downregulation in acute myeloid leukemia (AML) results in reduced sensitivity to therapy (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Taken together, these findings suggest the importance of \u003cem\u003eSMYD2\u003c/em\u003e in leukemia.\u003c/p\u003e \u003cp\u003eHere, we provide new insights into the importance of \u003cem\u003eSETD4\u003c/em\u003e in ALL and its correlation with \u003cem\u003eSMYD2\u003c/em\u003e transcription. Our findings demonstrate that, similar to \u003cem\u003eSMYD2\u003c/em\u003e, \u003cem\u003eSETD4\u003c/em\u003e expression is also upregulated in ALL BM samples compared to non-neoplastic BM samples. This observation was consistently validated across databases and through different techniques, including qPCR and microarray analysis. Additionally, we observed a significant decrease in \u003cem\u003eSETD4\u003c/em\u003e expression on days 15 and 29 of chemotherapy. Given that both SMYD2 and SETD4 specifically trimethylate histone H3 at lysine 4 (H3K4me3) and promote cell cycle progression by stimulating the G1/S transition, we investigated the relationship between \u003cem\u003eSETD4\u003c/em\u003e and \u003cem\u003eSMYD2\u003c/em\u003e expression in ALL. We detected a strong correlation between the transcription levels of these genes before and during chemotherapy, suggesting that they share common transcriptional regulators or pathways. Further studies are warranted to explore this relationship in greater detail.\u003c/p\u003e \u003cp\u003eAdditionally, we observed that patients in the high-risk group exhibited elevated \u003cem\u003eSETD4\u003c/em\u003e mRNA expression. Furthermore, patients exhibiting high \u003cem\u003eSETD4\u003c/em\u003e expression had worse OS and EFS than patients with low expression. Although it is unclear whether this upregulation is a driver or a passenger alteration, it is plausible that \u003cem\u003eSETD4\u003c/em\u003e may act as an oncogene in this disease, given the well-established roles of various SET domain proteins in cancer (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the likely oncogenic effect of \u003cem\u003eSETD4\u003c/em\u003e on ALL leukemogenesis, its role in cancer development is ambiguous and appears to be context dependent. \u003cem\u003eSETD4\u003c/em\u003e is mostly downregulated in prostate cancer cells and tissue samples. A decrease in the expression of \u003cem\u003eSETD4\u003c/em\u003e is correlated with inferior clinicopathological characteristics, such as pathologic grade, clinical stage and Gleason score. Moreover, \u003cem\u003eSETD4\u003c/em\u003e overexpression inhibited prostate cancer cell proliferation (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). In contrast, the expression of \u003cem\u003eSMYD2\u003c/em\u003e was elevated in prostate cancer tissues compared with that in benign prostate tissues, and an increase in \u003cem\u003eSMYD2\u003c/em\u003e expression was linked to a greater risk of biochemical recurrence following radical prostatectomy. Additionally, reducing \u003cem\u003eSMYD2\u003c/em\u003e levels suppressed the proliferation of prostate cancer cells \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough the limited sample size in our study, the data provide novel insights into the role of \u003cem\u003eSETD4\u003c/em\u003e in acute lymphoblastic leukemia (ALL) and reveal a positive association with \u003cem\u003eSMYD2\u003c/em\u003e transcription levels. These findings suggest a potential oncogenic role for \u003cem\u003eSETD4\u003c/em\u003e, highlighting its promise as a biomarker for treatment response and a potential target for future cancer pharmacology.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute lymphoblastic leukemia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKMT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLysine methyltransferases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRT‒qPCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eQuantitative reverse transcription polymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBone Marrow\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCancer steam cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSCLC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-small cell lung cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGBTLI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBrazilian Cooperative Group for Treatment of Childhood Acute Lymphocytic Leukemia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBFM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e95-Berlin-Frankfurt-M\u0026uuml;nster 95 protocol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ewhite blood cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMMC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBone marrow mononuclear cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCq\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eQuantitation cycle\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNon-malignant\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEvent-free survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCLL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic lymphocytic leukemia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCML\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic myeloid leukemia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Regional Ethics Committee of the Federal District, Brazil, with written informed consent from patients and/or guardians. The study followed the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll data is available upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq) and Funda\u0026ccedil;\u0026atilde;o de Apoio \u0026agrave; Pesquisa do Distrito Federal (FAPDF).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eF.P-S., A.B.M., and L.H.T.S., Conceptualization; L.H.T.S., D.A.R.R. and F.P-S., methodology; L.H.T.S managed specimen collection and collected the data; L.A.M.T. performed experiments and contributed to data analysis, M.B.L. partially contributed to the experiments presented in this manuscript. F.P-S., L.A.M.T., and M.B.L wrote and finalized the manuscript. \u0026nbsp;All authors reviewed and approved the submitted version of the manuscript.\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors are thankful to all members of the laboratory of molecular pathology of cancer for their support. We thank the staff of the Hospital da Crian\u0026ccedil;a de Bras\u0026iacute;lia Jos\u0026eacute; Alencar for their kind assistance.\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eInaba H, Mullighan CG. Pediatric acute lymphoblastic leukemia. Haematologica. 2020 Sep 10;105(11):2524\u0026ndash;39. \u003c/li\u003e\n\u003cli\u003eTran TH, Hunger SP. The genomic landscape of pediatric acute lymphoblastic leukemia and precision medicine opportunities. Seminars in Cancer Biology. 2022 Sep;84:144\u0026ndash;52. \u003c/li\u003e\n\u003cli\u003eCarroll AJ, Crist WM, Parmley RT, Roper M, Finley MDCWH. Pre-B Cell Leukemia Associated With Chromosome Translocation 1; 19. Blood. 1984 Mar 1;63(3):721\u0026ndash;4. \u003c/li\u003e\n\u003cli\u003eVan den Berghe H, David G, Broeckaert-Van Orshoven A, Louwagie A, Verwilghen R, Casteels-Van Daele M, et al. A new chromosome anomaly in acute lymphoblastic leukemia (ALL). Hum Genet. 1979 Jan 25;46(2):173\u0026ndash;80. \u003c/li\u003e\n\u003cli\u003ePrognostic importance of chromosome number in 136 untreated children with acute lymphoblastic leukemia | Blood | American Society of Hematology [Internet]. [cited 2024 Feb 24]. Available from: https://ashpublications.org/blood/article/60/4/864/163138/Prognostic-importance-of-chromosome-number-in-136\u003c/li\u003e\n\u003cli\u003eHusmann D, Gozani O. Histone lysine methyltransferases in biology and disease. Nat Struct Mol Biol. 2019 Oct;26(10):880\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eHuang J, Perez-Burgos L, Placek BJ, Sengupta R, Richter M, Dorsey JA, et al. Repression of p53 activity by Smyd2-mediated methylation. Nature. 2006 Nov;444(7119):629\u0026ndash;32. \u003c/li\u003e\n\u003cli\u003eLi LX, Zhou JX, Calvet JP, Godwin AK, Jensen RA, Li X. Lysine methyltransferase SMYD2 promotes triple negative breast cancer progression. Cell Death Dis. 2018 Feb 27;9(3):1\u0026ndash;17. \u003c/li\u003e\n\u003cli\u003eSakamoto LHT, Andrade RV de, Felipe MSS, Motoyama AB, Pittella Silva F. \u003cem\u003eSMYD2\u003c/em\u003e is highly expressed in pediatric acute lymphoblastic leukemia and constitutes a bad prognostic factor. Leukemia Research. 2014 Apr 1;38(4):496\u0026ndash;502. \u003c/li\u003e\n\u003cli\u003eOverexpression of SET and MYND domain-containing protein 2 (SMYD2) is associated with poor prognosis in pediatric B lineage acute lymphoblastic leukemia [Internet]. [cited 2024 May 29]. Available from: https://www.tandfonline.com/doi/epdf/10.1080/10428194.2019.1675875?needAccess=true\u003c/li\u003e\n\u003cli\u003eYe S, Ding YF, Jia WH, Liu XL, Feng JY, Zhu Q, et al. SET Domain-Containing Protein 4 Epigenetically Controls Breast Cancer Stem Cell Quiescence. Cancer Res. 2019 Sep 15;79(18):4729\u0026ndash;43. \u003c/li\u003e\n\u003cli\u003eWang Y, Yu Y, Yang W, Wu L, Yang Y, Lu Q, et al. SETD4 Confers Cancer Stem Cell Chemoresistance in Nonsmall Cell Lung Cancer Patients via the Epigenetic Regulation of Cellular Quiescence. Stem Cells Int. 2023;2023:7367854. \u003c/li\u003e\n\u003cli\u003eFaria JAQA, Corr\u0026ecirc;a NCR, de Andrade C, de Angelis Campos AC, dos Santos Samuel de Almeida R, Rodrigues TS, et al. SET domain-containing Protein 4 (SETD4) is a Newly Identified Cytosolic and Nuclear Lysine Methyltransferase involved in Breast Cancer Cell Proliferation. J Cancer Sci Ther. 2013 Jan 21;5(2):58\u0026ndash;65. \u003c/li\u003e\n\u003cli\u003eFeng X, Lu H, Yue J, Schneider N, Liu J, Denzin LK, et al. Loss of Setd4 delays radiation-induced thymic lymphoma in mice. DNA Repair (Amst). 2020 Feb;86:102754. \u003c/li\u003e\n\u003cli\u003eBrandalise S, Odone V, Pereira W, Andrea M, Zanichelli M, Aranega V. Treatment results of three consecutive Brazilian cooperative childhood ALL protocols: GBTLI-80, GBTLI-82 and -85. ALL Brazilian Group. Leukemia. 1993 Aug;7 Suppl 2:S142-145. \u003c/li\u003e\n\u003cli\u003eM\u0026ouml;ricke A, Reiter A, Zimmermann M, Gadner H, Stanulla M, D\u0026ouml;rdelmann M, et al. Risk-adjusted therapy of acute lymphoblastic leukemia can decrease treatment burden and improve survival: treatment results of 2169 unselected pediatric and adolescent patients enrolled in the trial ALL-BFM 95. Blood. 2008 May 1;111(9):4477\u0026ndash;89. \u003c/li\u003e\n\u003cli\u003eBagger FO, Sasivarevic D, Sohi SH, Laursen LG, Pundhir S, S\u0026oslash;nderby CK, et al. BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis. Nucleic Acids Res. 2016 Jan 4;44(D1):D917\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eGrigsby SM, Friedman A, Chase J, Waas B, Ropa J, Serio J, et al. Elucidating the Importance of DOT1L Recruitment in MLL-AF9 Leukemia and Hematopoiesis. Cancers (Basel). 2021 Feb 5;13(4):642. \u003c/li\u003e\n\u003cli\u003eEl Chaer F, Keng M, Ballen KK. MLL-Rearranged Acute Lymphoblastic Leukemia. Curr Hematol Malig Rep. 2020 Apr;15(2):83\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eZhu L, Li Q, Wong SHK, Huang M, Klein BJ, Shen J, et al. ASH1L Links Histone H3 Lysine 36 di-methylation to MLL Leukemia. Cancer Discov. 2016 Jul;6(7):770\u0026ndash;83. \u003c/li\u003e\n\u003cli\u003eAljazi MB, Gao Y, Wu Y, Mias GI, He J. Histone H3K36me2-Specific Methyltransferase ASH1L Promotes MLL-AF9-Induced Leukemogenesis. Front Oncol. 2021 Oct 8;11:754093. \u003c/li\u003e\n\u003cli\u003eIssa ME, Takhsha FS, Chirumamilla CS, Perez-Novo C, Vanden Berghe W, Cuendet M. Epigenetic strategies to reverse drug resistance in heterogeneous multiple myeloma. Clin Epigenetics. 2017 Feb 10;9:17. \u003c/li\u003e\n\u003cli\u003eNarang S, Evensen NA, Saliba J, Pierro J, Loh ML, Brown PA, et al. NSD2 E1099K drives relapse in pediatric acute lymphoblastic leukemia by disrupting 3D chromatin organization. Genome Biol. 2023 Apr 4;24(1):64. \u003c/li\u003e\n\u003cli\u003eDhami G, Liu H, Galka M, Voss C, Wei R, Muranko K, et al. Dynamic Methylation of Numb by Set8 Regulates Its Binding to p53 and Apoptosis. Molecular Cell. 2013;50(4):565\u0026ndash;76. \u003c/li\u003e\n\u003cli\u003eHashemi M, Sheybani-Nasab M, Naderi M, Roodbari F, Taheri M. Association of functional polymorphism at the miR-502-binding site in the 3\u0026prime; untranslated region of the SETD8 gene with risk of childhood acute lymphoblastic leukemia, a preliminary report. Tumor Biol. 2014 Oct 1;35(10):10375\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eTajima K, Yae T, Javaid S, Tam O, Comaills V, Morris R, et al. SETD1A modulates cell cycle progression through a miRNA network that regulates p53 target genes. Nat Commun. 2015 Sep 23;6(1):8257. \u003c/li\u003e\n\u003cli\u003eYae T, Tajima K, Maheswaran S. SETD1A induced miRNA network suppresses the p53 gene expression module. Cell Cycle. 2016;15(4):487\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eOgawa S, Fukuda A, Matsumoto Y, Hanyu Y, Sono M, Fukunaga Y, et al. SETDB1 Inhibits p53-Mediated Apoptosis and Is Required for Formation of Pancreatic Ductal Adenocarcinomas in Mice. Gastroenterology. 2020 Aug;159(2):682-696.e13. \u003c/li\u003e\n\u003cli\u003eTusi BK, Deng C, Salz T, Zeumer L, Li Y, So CWE, et al. Setd1a regulates progenitor B-cell-to-precursor B-cell development through histone H3 lysine 4 trimethylation and Ig heavy-chain rearrangement. FASEB J. 2015 Apr;29(4):1505\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eLi GM, Wang YG, Pan Q, Wang J, Fan JG, Sun C. RNAi screening with shRNAs against histone methylation-related genes reveals determinants of sorafenib sensitivity in hepatocellular carcinoma cells. Int J Clin Exp Pathol. 2014;7(3):1085\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eTan Z, Fu S, Feng R, Huang Y, Li N, Wang H, et al. Identification of Potential Biomarkers for Progression and Prognosis of Bladder Cancer by Comprehensive Bioinformatics Analysis. J Oncol. 2022 Apr 19;2022:1802706. \u003c/li\u003e\n\u003cli\u003eXu H, Ba Z, Liu C, Yu X. Long noncoding RNA DLEU1 promotes proliferation and glycolysis of gastric cancer cells via APOC1 upregulation by recruiting SMYD2 to induce trimethylation of H3K4 modification. Transl Oncol. 2023 Oct;36:101731. \u003c/li\u003e\n\u003cli\u003eWang Y, Jin G, Guo Y, Cao Y, Niu S, Fan X, et al. SMYD2 suppresses p53 activity to promote glucose metabolism in cervical cancer. Exp Cell Res. 2021 Jul 15;404(2):112649. \u003c/li\u003e\n\u003cli\u003eXu W, Chen F, Fei X, Yang X, Lu X. Overexpression of SET and MYND Domain-Containing Protein 2 (SMYD2) Is Associated with Tumor Progression and Poor Prognosis in Patients with Papillary Thyroid Carcinoma. Med Sci Monit. 2018 Oct 15;24:7357\u0026ndash;65. \u003c/li\u003e\n\u003cli\u003ePositive Expression of SMYD2 is Associated with Poor Prognosis in Patients with Primary Hepatocellular Carcinoma - PubMed [Internet]. [cited 2024 May 30]. Available from: https://pubmed.ncbi.nlm.nih.gov/29344279/\u003c/li\u003e\n\u003cli\u003eCho HS, Hayami S, Toyokawa G, Maejima K, Yamane Y, Suzuki T, et al. RB1 methylation by SMYD2 enhances cell cycle progression through an increase of RB1 phosphorylation. Neoplasia. 2012 Jun;14(6):476\u0026ndash;86. \u003c/li\u003e\n\u003cli\u003eWang L, Li L, Zhang H, Luo X, Dai J, Zhou S, et al. Structure of Human SMYD2 Protein Reveals the Basis of p53 Tumor Suppressor Methylation. J Biol Chem. 2011 Nov 4;286(44):38725\u0026ndash;37. \u003c/li\u003e\n\u003cli\u003eResidual expression of SMYD2 and SMYD3 is associated with the acquisition of complex karyotype in chronic lymphocytic leukemia | Tumor Biology [Internet]. [cited 2024 May 30]. Available from: https://link.springer.com/article/10.1007/s13277-016-4846-z\u003c/li\u003e\n\u003cli\u003eBagislar S, Sab\u0026ograve; A, Kress TR, Doni M, Nicoli P, Campaner S, et al. Smyd2 is a Myc-regulated gene critical for MLL-AF9 induced leukemogenesis. Oncotarget. 2016 Sep 13;7(41):66398\u0026ndash;415. \u003c/li\u003e\n\u003cli\u003eZipin-Roitman A, Aqaqe N, Yassin M, Biechonski S, Amar M, van Delft MF, et al. SMYD2 lysine methyltransferase regulates leukemia cell growth and regeneration after genotoxic stress. Oncotarget. 2017 Feb 6;8(10):16712\u0026ndash;27. \u003c/li\u003e\n\u003cli\u003eBennett RL, Swaroop A, Troche C, Licht JD. The Role of Nuclear Receptor-Binding SET Domain Family Histone Lysine Methyltransferases in Cancer. Cold Spring Harb Perspect Med. 2017 Jun 1;7(6):a026708. \u003c/li\u003e\n\u003cli\u003eWang C, Wang T, Li KJ, Hu LH, Li Y, Yu YZ, et al. SETD4 inhibits prostate cancer development by promoting H3K27me3-mediated NUPR1 transcriptional repression and cell cycle arrest. Cancer Letters. 2023 Nov 28;579:216464. \u003c/li\u003e\n\u003cli\u003eLi J, Wan F, Zhang J, Zheng S, Yang Y, Hong Z, et al. Targeting SMYD2 inhibits prostate cancer cell growth by regulating c-Myc signaling. Molecular Carcinogenesis. 2023;62(7):940\u0026ndash;50. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Lymphoblastic leukemia, Epigenetics, Gene expression, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-6191336/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6191336/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAcute lymphoblastic leukemia (ALL) is the most common childhood malignancy worldwide. Despite a good rate of treatment success, the poor prognosis underscores the urgent need for new prognostic markers and effective therapeutic strategies. The SET family of lysine methyltransferases (KMTs) has been implicated in several cancers. While \u003cem\u003eSMYD2\u003c/em\u003e has been identified as a prognostic marker in ALL, \u003cem\u003eSETD4\u003c/em\u003e is a member that is still poorly characterized.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn the present study, we analyzed the expression patterns of \u003cem\u003eSETD4\u003c/em\u003e in 83 pediatric ALL patients at diagnosis and during treatment using RT‒ qPCR. Kaplan-Meier analysis was employed to evaluate survival outcomes between the high and basal \u003cem\u003eSETD4\u003c/em\u003e expression groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe found that \u003cem\u003eSETD4\u003c/em\u003e transcription levels are significantly upregulated in BM samples derived from ALL patients compared to non-neoplastic BM (median fold-change of 5.14 p\u0026thinsp;=\u0026thinsp;0.0095) and \u003cem\u003eSETD4\u003c/em\u003e expression is correlated with leukemic burden. Importantly, the levels of SETD4 decreased in chemotherapy-responsive patients. We further investigated whether \u003cem\u003eSETD4\u003c/em\u003e transcription levels are associated with those of \u003cem\u003eSMYD2\u003c/em\u003e. Notably, a positive correlation between both genes was observed at diagnosis (Spearman r\u0026thinsp;=\u0026thinsp;0.759, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with a substantial correlation persisting throughout treatment (Spearman r\u0026thinsp;=\u0026thinsp;0.925, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Furthermore, patients classified in the high-risk category exhibited elevated \u003cem\u003eSETD4\u003c/em\u003e expression, with those displaying high \u003cem\u003eSETD4\u003c/em\u003e transcription exhibiting the poorest survival outcomes.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur findings unveil the involvement of \u003cem\u003eSETD4\u003c/em\u003e in leukemogenesis and highlight its potential as a promising prognostic marker.\u003c/p\u003e","manuscriptTitle":"SETD4 expression is correlated with leukemic burden and SMYD2 transcription in acute lymphoblastic leukemia ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-27 05:30:40","doi":"10.21203/rs.3.rs-6191336/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dcd13c62-9ede-47a4-8861-9ac07465113e","owner":[],"postedDate":"March 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":46196305,"name":"Health sciences/Biomarkers"},{"id":46196306,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2025-04-22T07:09:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-27 05:30:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6191336","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6191336","identity":"rs-6191336","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}