Role of Chromosomal Microarray and RNA Fusion Analysis in Detecting KMT2A-PTD and Stem Cell Transplant Impact on Mortality

Role of Chromosomal Microarray and RNA Fusion Analysis in Detecting KMT2A-PTD and Stem Cell Transplant Impact on Mortality | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Role of Chromosomal Microarray and RNA Fusion Analysis in Detecting KMT2A -PTD and Stem Cell Transplant Impact on Mortality Bhaumik Shah , Roniya Francis , Ashishkumar Sonani , Jianming Pei , Peter Abdelmessieh , Mariusz A. Wasik , Nicholas Mackrides , View ORCID Profile Reza Nejati doi: https://doi.org/10.1101/2025.05.27.25328455 Bhaumik Shah 1 Department of Pathology, Fox Chase Cancer Center , Temple Health, Philadelphia, Pennsylvania, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Roniya Francis 1 Department of Pathology, Fox Chase Cancer Center , Temple Health, Philadelphia, Pennsylvania, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ashishkumar Sonani 1 Department of Pathology, Fox Chase Cancer Center , Temple Health, Philadelphia, Pennsylvania, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jianming Pei 1 Department of Pathology, Fox Chase Cancer Center , Temple Health, Philadelphia, Pennsylvania, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Peter Abdelmessieh 2 Department of Bone Marrow Transplant & Cellular Therapy, Fox Chase Cancer Center , Temple Health, Philadelphia, Pennsylvania, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mariusz A. Wasik 1 Department of Pathology, Fox Chase Cancer Center , Temple Health, Philadelphia, Pennsylvania, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nicholas Mackrides 1 Department of Pathology, Fox Chase Cancer Center , Temple Health, Philadelphia, Pennsylvania, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Reza Nejati 1 Department of Pathology, Fox Chase Cancer Center , Temple Health, Philadelphia, Pennsylvania, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Reza Nejati For correspondence: Reza.Nejati{at}fccc.edu Abstract Full Text Info/History Metrics Preview PDF Abstract KMT2A partial tandem duplication ( KMT2A -PTD) is a recurrent, high-risk alteration in myeloid neoplasms, yet no gold standard exists for its detection due to complex genomic architecture. We conducted a retrospective study of 97 specimens from 17 patients with KMT2A -PTD-positive myeloid neoplasms (11 AML, 4 MDS, 2 MPN) to compare chromosomal microarray analysis (CMA) and RNA fusion testing. Overall concordance was 73.3% (κ = 0.467), with RNA fusion identifying more cryptic KMT2A -PTDs (p = 0.035), while CMA detected non-canonical KMT2A -PTDs and, additionally, secondary genomic abnormalities (e.g., trisomy 8 and CN-LOH of diverse genes). KMT2A- PTD cases exhibited high clonal complexity and distinct mutational profiles, including mutations of DNMT3A , TET2, ASXL1, RUNX1, FLT3 , and others. Higher KMT2A -PTD transcript expression (split reads and SR/C ratio) correlated with DNMT3A , RUNX1 , and FLT3 mutations, and RUNX1T1 copy number gain (p < 0.05), and was reduced in CN-LOH cases. RNA fusion consistently identified breakpoints at exon 10→2 or exon 11→2, affecting key oncogenic domains (CXXC, PHD finger, and bromodomain). Six-month overall survival was 41.2%, with HSCT significantly improving outcomes (68.6% vs. 0% at 17 months, p = 0.028), non-transplanted patients showing shorter median PFS (∼6 months), and FLT3 -mutated patients experiencing 100% mortality (p = 0.0456). In conclusion, CMA and RNA fusion analyses offer complementary diagnostic value in KMT2A-PTD-positive myeloid neoplasms. Such integrated genomic testing improves detection and refines risk stratification. Given the poor prognosis associated with KMT2A -PTD, especially in patients with co-occurring high-risk mutations, our findings support early consideration of HSCT in such patients. Introduction Partial tandem duplication of KMT2A gene ( KMT2A -PTD) is a recurrent genetic alteration in myeloid neoplasms, seen in 5-10% of acute myeloid leukemia (AML), 2–7% of myelodysplastic syndromes (MDS), and, rarely, in myeloproliferative neoplasms (MPN) [ 1 , 2 ]. This structural variant, typically spanning 10-50 kb, involves in-frame duplication of KMT2A exons (e.g., 2-8 or 2-10) via Alu-element-mediated homologous recombination, disrupting the CXXC and PHD domains [ 1 ]. The resultant aberrant protein drives leukemogenesis by upregulating HOX genes, promoting cell proliferation and differentiation arrest, linked to poor prognosis [ 3 ]. Approximately 16% of cases develop secondary genomic events, such as copy-neutral loss of heterozygosity (CN-LOH) or KMT2A -PTD allele amplification, enhancing RNA expression and promoting disease progression. KMT2A -PTD frequently co-occurs with mutations in DNMT3A , RUNX1 , and FLT3 genes, amplifying epigenetic and cell-signalling dysregulation, raising the risk of leukemic transformation in MDS/MPN, and increasing relapse rates [ 4 , 5 ]. Its expression and complexity are notable in high-risk/advanced MDS or MPN, or secondary AML. Clinically, KMT2A -PTD confers a poor prognosis, (median overall survival (OS) 9.85 months in MDS, 4.5–12.1 months in AML), driven by chemotherapy-resistance and relapse [ 4 , 6 ]. It also serves as a biomarker for menin inhibitors, targeting the menin- KMT2A interaction, offering a novel therapeutic avenue. In contrast to KMT2A rearrangements, which are well characterized in acute leukemias and have established diagnostic and therapeutic guidelines, KMT2A -PTD remains under-recognized, with no consensus gold standard for detection and limited data on its clinical significance and management. This unmet need reinforces the importance of developing and validating optimal diagnostic approaches to optimize risk stratification and therapeutic decisions for this high-risk group. Recent advances in understanding KMT2A allelic complexity [ 8 ] and consensus gene structure [ 9 ] have highlighted the need for precise genomic mapping, while epigenetic alterations induced by KMT2A partial tandem duplications underscore their leukemogenic potential [ 13 ]. KMT2A -PTDs are complex gene rearrangements that cannot be fully ascertained using a single genomic platform. Its detection is challenging due to small size, below the resolution limits of karyotyping (5–10 Mb) or standard FISH KMT2A break-apart probes [ 7 ]. Furthermore, its intragenic nature leads to significant overlap in interphase nuclei making its detection unreliable, even with custom probe sets targeting the KMT2A -PTD region. Optical genome mapping (OGM) can resolve large structural variants, such as 11q gains associated with KMT2A -PTD, but is less sensitive for small duplications [ 7 ]. Several methods, including chromosomal microarray (CMA), RNA fusion analysis (e.g., Illumina TruSight RNA Fusion Panel), multiplex ligation-dependent probe amplification (MLPA), next-generation sequencing (NGS), and reverse transcription PCR (RT-PCR), are used, each with distinct limitations (Supplemental Table 1). Long-range RT-qPCR, was historically considered the gold standard and targeting canonical PTDs (exons 2–8 or 2–10), is limited by exon specific primer dependence, inability to detect non-canonical exons or cryptic events and the influence of complex genomic structures or fusion variants during disease progression—limits its value as a true gold standard in clinical settings [ 2 ]. Routine NGS panels, optimized for short nucleotide variants, require custom pipelines for reliable detection due to poor intronic coverage and high VAF thresholds [ 5 , 11 ]. Hybrid capture NGS assays (e.g., Oncomine) can detect KMT2A -PTDs and co-mutations at variant allele frequencies of at least 10%, but also requires customized complex bioinformatics pipelines, limiting its potential as a gold standard in routine clinical detection [ 2 ]. Chromosomal microarray (CMA) offers an alternative by detecting copy-number alterations (CNAs) and copy-neutral loss of heterozygosity (CN-LOH), but is limited for small intragenic duplications without CNAs [ 7 ]. RNA fusion panels, using split-read analysis, detect fusion transcripts with high sensitivity, even in cases with low RNA quality, making them particularly valuable for residual disease monitoring [ 5 ]. No study has directly compared CMA and RNA fusion panels for KMT2A -PTD detection, despite their complementary strengths. In this retrospective study of 97 specimens across 17 patients with KMT2A -PTD myeloid neoplasms at Fox Chase Cancer Center (2011 – 2025), we provide the first head-to-head evaluation of CMA and RNA fusion panels, comprehensively assessing their diagnostic performance. Additionally, we analyzed survival outcomes, co-mutations via NGS, and additional abnormalities (FISH, karyotype, FLT3 ) to elucidate prognostic and therapeutic implications of KMT2A -PTD, highlighting the impact of hematopoietic stem cell transplantation (HSCT) in reducing mortality and informing optimal detection strategies and patient management for this high-risk cohort. Methods Study Design and Specimen/Patient Selection This retrospective study reviewed molecular and cytogenetic data from the Fox Chase Cancer Center database to identify specimens with confirmed KMT2A -PTD) between January 2011 and April 2025. Search criteria included specimens with KMT2A -PTD detected by chromosomal microarray analysis (CMA) and/or RNA fusion panels, along with a concurrent diagnosis of myeloid neoplasm (AML, MDS, or MPN) at the time of KMT2A -PTD detection. Inclusion criteria required KMT2A -PTD to be detected by CMA and/or RNA fusion panel; exclusion criteria were age under 18 years, non-myeloid neoplasms, or unconfirmed KMT2A -PTD. Our cytogenetic database comprised 5,218 eligible specimens analyzed with CMA (Affymetrix CytoScan HD, 2,696,168 markers) and 720 eligible specimens analyzed with NGS-based targeted RNA sequencing (Illumina TruSight RNA Fusion 523-gene panel). Corresponding bone marrow and peripheral blood specimens were verified in the pathology database to determine the total number of unique patients with confirmed KMT2A -PTD. Patients were grouped based on their diagnosis at the time of KMT2A -PTD detection (AML, MDS, or MPN). To enable direct comparison between CMA and RNA fusion methods in absence of definitive gold standard test, all available longitudinal specimens were included, for cross-validation. The study was approved by the Institutional Review Board and conducted in accordance with the Declaration of Helsinki. Data Collection Patient demographics, clinical history (diagnosis/ disease duration, mortality, transplant status, cause of death) and survival data wereextracted from the pathology database and EMRs. Overall survival (OS) was defined as the time from KMT2A -PTD detection (typically at disease progression) to death from any cause or to the last follow-up (April 30, 2025). PFS was defined as the time from the relevant baseline ( KMT2A -PTD detection for non-transplant patients, or transplant for transplant recipients) to the first occurrence of death from any cause or relapse (≥5% blasts following achievement of complete remission). Patients without an event were censored at last follow-up. Ancillary data, including NGS-based targeted DNA sequencing (275-gene Comprehensive Cancer Panel v1), FISH, karyotyping, FLT3 , and NPM1 studies, were extracted to resolve discordant CMA and RNA fusion results using a composite reference standard. NGS, was previously performed previously as part of clinical work up, utilized the 275-gene Comprehensive Cancer Panel v1 (Illumina), including myeloid-relevant genes (e.g., DNMT3A, FLT3, RUNX1 ) as part of the clinical workup. Genomic Coordinate Verification and KMT2A -PTD Classification Genomic coordinates (from CMA/RNA reports) were verified using the UCSC Genome Browser (hg19 assembly) referencing the ENST00000534358.1 transcript (GRCh37.p13, KMT2A -001; Chromosome 11:118,436,492–118,526,832, forward strand) [ 9 ]. This process determined the precise genomic coordinates, duplicated exons and introns, PTD size, and affected functional domains (e.g., CXXC, PHD, and SET). This approach was informed by detailed cytogenetic studies of KMT2A rearrangements [ 14 ], ensuring accurate delineation of structural variants. KMT2A -PTD cases were classified as simple (net +1 copy gain of PTD exons) or complex (e.g., +2/+3 copy gains, CN-LOH, trisomy 11) based on allelic state, copy number, and VAF, adopting definitions from Tsai et al. (2022) [ 8 ]( Table 1 ). Quantitative KMT2A -PTD expression was measured using total split reads and split reads per coverage (SR/C) ratio (Supplemental Table 5) and categorized as high, moderate or low. View this table: View inline View popup Download powerpoint Table 1. Definition of Simple and Complex KMT2A -PTD Allelic States and Copy Number Variations (adopted from Tsai et al. (2022)). Assessment of Diagnostic Performance of CMA and RNA fusion analysis A composite reference standard (CRS) was constructed to classify specimens as KMT2A -PTD-positive or KMT2A -PTD-negative, integrating CMA, RNA fusion analysis, clinical correlation, bone marrow morphology, and ancillary findings (NGS, FISH, karyotyping). The specimen was positive if CMA detected 11q23.3 gains, or RNA fusion analysis identified a fusion transcript. True positives (TP), false negatives (FN), true negatives (TN), and false positives (FP) were adjudicated pre– and post-CRS (Supplemental Methods). Statistical Analysis The diagnostic performance (sensitivity, specificity, PPV, NPV) was assessed pre– and post-CRS. Concordance was quantified using overall concordance, KMT2A -PTD-specific concordance, Cohen’s Kappa, and McNemar’s test. Co-mutation frequencies were determined from NGS data, with associations tested using Fisher’s exact test. KMT2A -PTD expression was correlated with mutations and outcomes using Mann-Whitney U and Kruskal-Wallis tests. PFS and OS were analyzed using Kaplan-Meier curves and log-rank tests, stratified by diagnosis, transplant status, and mutation status. Results Patient demographics and Clinical Characteristics The study identified 17 patients (12 males, 5 females; median age 68 years, range 42–79) with KMT2A -PTD-positive myeloid neoplasms, comprising 11 AML (6 secondary [transformed from MDS or MPN], 5 de novo ), 4 MDS (2 high grade), and 2 MPN (1 high grade) ( Table 2 ) . HSCT was performed in 7 patients (41.18%). Median time from KMT2A -PTD detection to transplant was 5 months, with a median disease-free survival post-transplant of 12 months. View this table: View inline View popup Table 2. Patients’ clinical characteristics, mortality status and KMT2A -PTD status Specimen characteristics Of 97 specimens (79 bone marrow, 18 peripheral blood), 31 were KMT2A -PTD positive, detected by CMA (24/31) and/or RNA fusion (21/22). KMT2A -PTD was classified as simple (14 patients: 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 17), complex (2 patients: patient 2 [trisomy 11, +2 KMT2A -PTD copy gain] and patient 10 [11q CN-LOH, +2 the copy gain]), or non-canonical (1 patient: 16, exons 27–36) ( Table 1 ). The CRS identified 35 PTD-positive specimens’ post-adjudication, including 4 additional false negatives from concordant/discordant negatives identified by NGS, bone marrow morphology and/or FISH. These included three discordant specimens that were negative by CMA without RNA fusion analysis, as well as one discordant specimen that was negative for RNA fusion, with CMA not performed. The specimens negative for KMT2A -PTD by CMA (n=3) showed bone marrow morphology demonstrating 8% blasts (e.g., Patient 4), 10–14% blasts (Patient 2), or 6% circulating blasts (Patient 11). In the specimen that was negative for RNA fusion (Patient 16), FISH demonstrated 8% blasts. Diagnostic Performance Pre-CRS, CMA detected KMT2A -PTD in 24/31 specimens (sensitivity 77.42%, specificity 100%, PPV 100%, NPV 76.67%), while RNA fusion detected 21/22 (sensitivity 95.45%, specificity 100%, PPV 100%, NPV 90.91%). Post-CRS, CMA sensitivity decreased to 68.57% (24/35) and RNA fusion to 87.50% (21/24) due to additional false negatives (e.g., Patient 4’s 8% blasts, Patient 2’s 10–14% blasts), with specificity and PPV remaining 100% (NPV: CMA 63.33%, RNA 72.73%). Both CMA and RNA fusion analysis demonstrated 100% specificity and positive predictive value (PPV), as no false positives were identified due to validation by the composite reference standard, ensuring all positive results were true positives. Overall concordance was 73.33% (κ=0.4667), with 45.16% KMT2A-PTD specific concordance. RNA fusion outperformed CMA in discordant cases (p=0.03516). KMT2A gain was detected by FISH in 5 of 22 specimens (16.13% sensitivity) and by karyotype in 7 of 37 specimens (22.58% sensitivity). FLT3 mutations were found in 9 of 19 specimens from 4 patients (100% sensitivity). Chromosomal Microarray Analysis CMA confirms KMT2A -PTD in Patients 1, 2, 3, 8, 9, 10, 11, 12, 13, 14 (partial), 15, 17, with sizes (10,890–65,301 bp) overlapping RNA breakpoints. Patients 4–7 lacked detection by CMA, but were detected by RNA fusion panel, indicating cryptic PTDs, despite high blast percentage in the specimens. KMT2A -PTD genomic coordinates reported by CMA ( Figure 1 ) were mapped to the ENST00000534358.1 transcript ( KMT2A -001; GRCh37.p13, hg19), confirming duplicated exons (e.g., 2–8, 2–10) ( Figure 2 ) and functional domains (CXXC, PHD, and SET) ( Supplemental Table 2 ). Patient 16 showed an atypical KMT2A -PTD involving introns 26-27 to 35-36 and exons 27-36 (SET domain), outside the typical breakpoints in exons 2-11, raising questions about its classification as a true KMT2A -PTD High-frequency region (Exons 2–5, Introns 1-2 to 4-5) was covered in 17 of 20 specimens, indicating a core region of KMT2A -PTDs affecting the CXXC domain (exons 4–5), critical for oncogenic activity in AML, MDS, and MPN. Mid-frequency region (exons 6–8 and introns 6-7 to 8-9) involved the PHD domain (exons 6–10) covered in 8 specimens (patient 1, 2, 9, 11, 13, 14, 15, and 17), and the AT Hooks (exons 1–2) in five cases (patient 2, 3, 11, 15, and 17). Involvement of the bromodomain (exons 11–20) was observed in three cases (patient 2, 14, and 17). The degree of CXXC domain involvement varied, with partial involvement noted in five cases (patient 1, 3, 8, 10, and 13). Download figure Open in new tab Figure 1. Genomic Coordinates and Exon/Intron Coverage of KMT2A -PTD Detected by Chromosomal Microarray (CMA). (A) Horizontal bar plot displaying genomic coordinates and sizes of KMT2A -PTD regions for 12 patients (1, 2, 3, 8, 9, 10, 11, 12, 13, 14, 15, 17) mapped to the ENST00000534358.1 transcript (GRCh37.p13, hg19). Bars range from 10,890 bp (Patient 8: 118,339,219–118,350,109) to 65,301 bp (Patient 2: 118,302,712–118,368,013), with Patient 16’s non-canonical PTD (50,853 bp, 118,374,566–118,425,419, exons 27–36, introns 26–27 to 35–36) in green. (B) Stacked bar plot showing exon (green) and intron (blue) coverage frequency across specimens, with high involvement in exons 2–5 (CXXC domain, ∼12 patients) and reduced in exons 6–10 (PHD domain, ∼8 patients). Patients 4–7, undetected by CMA but confirmed by RNA fusion, are excluded. The figure aids in identifying core PTD regions (exons 2–5) and functional domains (CXXC, PHD, SET) critical for leukemogenesis. Data reflects analysis up to April 30, 2025. Download figure Open in new tab Figure 2. Comparison of Chromosomal Abnormalities in KMT2A -PTD-Negative versus KMT2A -PTD-Positive Groups. Bar chart comparing the frequency and types of chromosomal abnormalities detected by Chromosomal Microarray (CMA) in KMT2A -PTD-negative (Patients 4, 5, 6, 7; n=4) and KMT2A -PTD-positive (Patients 2, 9, 10, 11, 14, 17; n=6) groups, based on 97 specimens. The positive group exhibits 17 abnormality types (e.g., KMT2A gain [11q23.3, 3 copies], trisomy 11 [Patient 2], CN-LOH 7q [EZH2, Patient 14]) versus 6 in the negative group (e.g., loss 3q [Patient 6], trisomy 8 [Patients 5, 14]). Colors distinguish abnormality categories (e.g., gains, losses, CN-LOH). Higher complexity in the positive group correlates with increased mortality (83.3% [5/6] vs. 75% [3/4], data up to April 30, 2025). Coordinates are mapped to hg19 assembly. Additional chromosomal abnormalities detected by CMA In seven patients (1, 3, 8, 12, 13, 15, and 16), KMT2A -PTD was identified by CMA as the sole cytogenetic abnormality. Conversely, in four patients (4, 5, 6, and 7), while CMA did not detect KMT2A -PTD, other genomic aberrations were observed ( Figure 2 ; Supplemental Table 3). These included chromosomal numerical gains (trisomy/tetrasomy 13, trisomy 8), deletions (3q, 11p in patient 6), and CN-LOH at 11q (patient 7). Concurrent RNA fusion analysis confirmed KMT2A -PTD in these four patients, suggesting a small duplication (∼10–50 kb) at 11q23.3 (e.g., chr11:118,302,712-118,368,013).. The KMT2A -PTD-positive group (patients: 2, 9, 10, 11, 14, and 17) had 17 secondary abnormality types, versus 6 in the KMT2A -PTD-negative group (patients: 4, 5, 6, and 7). All six patients with CMA-detected KMT2A -PTD exhibited complex karyotypes, alongside chromosomal numerical abnormalities, such as trisomy 11 (patient 2), trisomies 8 and 13 (patient 10), and gains of 1q, 2p, 8, and 11p/q segments (patients 14, 17). Furthermore, structural abnormalities documented in these six patients included also multi-chromosomal CN-LOH affecting 6q, 9p, 13q, 16p, 7q, 16q, and 11q (patients 2, 9, 10, 11, and 14), and losses of 6p and Yq (patients 14 and 17). RNA fusion analysis The RNA fusion study confirmed KMT2A -PTD in 21 specimens across 16 patients (Cases 1–15, 17); patient 16 was excluded due to negative RNA fusion. Breakpoints were identified in KMT2A -PTD exon 2 (118,339,490–118,339,559), exon 10 (118,355,577–118,355,690), exon 11 (118,359,329–118,359,475), and exon 8 in patient 17 (118,353,137–118,353,210) ( Figure 3 ; Supplemental Table 4) . Common breakpoint patterns included exon 10 to exon 2 (16,200 bp, patients 1, 2, 4, 5, 7, 13, 14, 15) and exon 11 to exon 2 (13,720 bp, patients 3, 6, 8, 9, 10, 12). Variant breakpoints were in exon 10 to exon 2 (15,539 bp, patient 11) and exon 8 to exon 2 (19,985 bp, patient 17). The size of the KMT2A gene’s PTD ranged from 13,720 bp to 19,985 bp (patient 17). The reading frame was in-frame in 19 of 21 specimens, potentially leading to HOX gene dysregulation. Out-of-frame duplications were observed in patient 3 (specimen 2) and patient 14 (specimen 2), which might be less oncogenic. The functional domains of KMT2A protein, including AT Hooks (exons 1–2), CXXC zinc finger (exons 4–5), PHD zinc finger (exons 6–10), bromodomain (exons 11–20), and SET domain (exons 27–36), were generally retained with the exception of patient 17, whose partial PHD finger retained only 11% of the sequence. Download figure Open in new tab Figure 3. Frequency of KMT2A -PTD Breakpoints and Exon Involvement Detected by RNA Fusion Analysis. (A) Bar plot illustrating the frequency of KMT2A -PTD breakpoint start positions by exon across 21 specimens from 16 patients (Patients 1–15, 17). Breakpoints are primarily at exon 10 (∼11 specimens) and exon 11 (∼8 specimens), with minor involvement at exon 8 (∼1 specimen), corresponding to common patterns like exon 10→2 (16,200 bp; Patients 1, 2, 4, 5, 7, 13, 14, 15) and exon 11→2 (13,720 bp; Patients 3, 6, 8, 9, 10, 12). Variant breakpoints include exon 10→2 (15,539 bp; Patient 11) and exon 8→2 (19,985 bp; Patient 17). (B) Bar plot showing the frequency of KMT2A exon involvement in PTD regions across all 17 patients, with highest frequencies in exons 2–3 (∼14–16 patients), decreasing through exons 4–12. Colors denote distinct exons for visual distinction. Breakpoints affect key oncogenic domains (e.g., AT Hooks in exons 1–2, CXXC in 4–5, PHD in 6–10, bromodomain in 11–20), with in-frame duplications in 19/21 specimens potentially driving HOX dysregulation. Patient 16 (non-canonical PTD, exons 27–36) is excluded due to negative RNA fusion. Coordinates reference hg19 assembly and ENST00000534358.1 transcript. KMTA -PTD Expression Level Summary RNA fusion split reads indicated higher transcript abundance in high-expression patients (1, 3, 4, 7, 8, 9, 10, 12; median SR 196, SR/C 0.1584) versus moderate (2, 3, 6, 10, 13; median SR 95, SR/C 0.0998) and low (4, 5, 11, 14, 15, 17; SR 26.5, SR/C 0.0465) groups ( Supplemental Table 5 ). Higher expression correlated with DNMT3A (p ≈ 0.0423, 0.0387), RUNX1 (p ≈ 0.0198, 0.0234), FLT3 (p ≈ 0.0087, 0.0123), and RUNX1T1 gain (p ≈ 0.0345, 0.0412), and lower expression with CN-LOH (p ≈ 0.0214, 0.0178). DNMT3A mutation-positive samples (n=10 patients, 13 specimens) showed significantly higher median split reads (102 vs 45.5, p ≈ 0.0423) and SR/C ratio (0.1189 vs 0.0682, p ≈ 0.0387) than DNMT3A mutation-negative samples (n=6 patients, 8 specimens) ( Figure 4 ). High KMT2A -PTD expression (patients 1, 7, 8, 9, 12) correlates with high blast percentages and high-risk features like FLT3 -ITD, while low expression (patients 5, 11, 14, 15, 17) aligns with lower blasts or RNA-only PTDs. Download figure Open in new tab Figure 4. Median KMT2A -PTD Expression Levels by Mutation Status from RNA Fusion Analysis. (A) Bar plot displaying median total split reads for KMT2A -PTD-positive specimens by mutation status. DNMT3A -positive samples (n=13 from 10 patients) show a median of 102 split reads vs. 45.5 for DNMT3A -negative (n=8 from 6 patients, p≈0.0423). RUNX1 -positive samples (median 118) exceed RUNX1 -negative (median 43, p≈0.0198), and FLT3 -positive samples (estimated ∼150 based on p≈0.0087) are elevated. Error bars indicate interquartile ranges. (B) Bar plot showing median split reads per coverage ratio (SR/C) by mutation status. DNMT3A -positive median SR/C is 0.1189 vs. 0.0682 for DNMT3A -negative (p≈0.0387), RUNX1 -positive is 0.1406 vs. 0.0646 for RUNX1-negative (p≈0.0234), and FLT3 -positive is higher (∼0.12, p≈0.0123). Higher expression correlates with aggressive clones ( FLT3 -ITD) and is reduced in CN-LOH cases (p≈0.0214). Data from 60/97 specimens, analyzed up to April 30, 2025, and mapped to hg19 assembly. Download figure Open in new tab Figure 5. Top Mutated Genes across 60 Specimens analyzed by NGS-based targeted DNA sequencing (275-gene panel). Bar plot displaying the mutation frequency (%) of the most prevalent gene mutations in 60 of 97 specimens from 17 patients with KMT2A -PTD-positive myeloid neoplasms. The x-axis lists genes, and the y-axis indicates mutation frequency (%) across specimens. Top mutated genes include DNMT3A (51.67%, 31/60 specimens), RUNX1 (41.67%, 25/60), TET2 (30.00%, 18/60), NRAS (20.00%, 12/60), JAK2 (25.00%, 15/60), ASXL1 (21.67%, 13/60), EZH2 (18.33%, 11/60), GATA2 (15.00%, 9/60), PIK3CA (11.67%, 7/60), and KMT2A (13.33%, 8/60). Colors distinguish categories for visual clarity. Data reflects the mutational spectrum enhancing KMT2A -PTD’s leukemogenic potential, with DNMT3A and RUNX1 showing higher frequencies in KMT2A -PTD-positive specimens (62.5% and 50% of patients, respectively). Coordinates are mapped to hg19 assembly. Mutational spectrum of KMT2A -PTD cases Next-generation sequencing (NGS)-based targeted DNA sequencing of 60 of 97 specimens revealed DNMT3A mutations in 51.67% (31/60 specimens), TET2 in 30.00% (18/60), and ASXL1 in 21.67% (13/60). RUNX1 (41.67%; 25/60) and GATA2 (15.00%; 9/60) were identified as common transcription factor mutations. Cell signaling mutations encompassed JAK2 (25.00%; 15/60), FLT3 (13.33%; 8/60), NRAS (20.00%; 12/60), and PIK3CA (11.67%; 7/60). Additionally, histone modifiers EZH2 (18.33%) and KMT2A (13.33%) exhibited mutations. Analysis of 32 KMT2A -PTD-positive specimens from 16 patients revealed the following mutational frequencies: DNMT3A (62.5% of patients, 62.5% of specimens), RUNX1 (50% of patients, 43.75% of specimens), TET2 (43.75% of patients, 31.25% of specimens), NRAS (25% of patients, 25% of specimens), and JAK2 (25% of patients). Cell line models with KMT2A- PTD have further elucidated mutation interactions [ 27 ], while minimal residual disease studies highlight persistent clonal activity [ 28 ]. WT1 , ASXL1 , ARID1A , and BCL6 were each found in 18.75% of patients. FLT3 mutations in 4 patients (1 by NGS in Patient 10, 5 specimens) co-occurred with complex PTD, RUNX1T1 gain, and trisomy 8/13, indicating high risk. DNMT3A -positive specimens showed significantly higher median RNA fusion assay split reads (102 vs. 45.5; p ≈ 0.0423) and SR/C ratio (0.1189 vs. 0.0682; p ≈ 0.0387) than DNMT3A -negative specimens. Similarly, RUNX1 -positive specimens had significantly higher median total split reads (118 vs. 43; p ≈ 0.0198) and SR/C (0.1406 vs. 0.0646; p ≈ 0.0234) compared to RUNX1 -negative samples. Survival Outcomes Overall mortality was 58.82% (10/17), with 6-month OS at 41.2%; 80% of deceased were male. Survival curves were similar for AML, MDS, and MPN ( Figure 6A ). Non-transplanted patients (n=10) had a median PFS of 6 months (80% events; range: 1–18 months) from KMT2A -PTD detection to death or remission failure, mainly due to refractory disease, relapse, or complications. In the transplanted patients (n=7), PFS from transplant to death or relapse was not reached (median ∼6 months among events; range: 5–55 months), with three events (two deaths: Patients 10, 11; one relapse: Patient 16). The event rate was lower in transplanted patients (42.9%) compared to non-transplanted patients (80%, p=0.0367). HSCT significantly improved survival (mortality at 28.6% vs. 80% in non-transplanted patients; p ≈ 0.0367), with superior survival at 17 months post-diagnosis (68.6% vs. 0% at 17 months, p=0.028; Figure 6B ). Download figure Open in new tab Figure 6. Kaplan-Meier Survival Curves for KMT2A -PTD-Positive Patients. (A) Kaplan-Meier curve depicting overall survival (OS) from KMT2A -PTD detection at diagnosis for 17 patients (11 AML [blue], 4 MDS [green], 2 MPN [orange]). The 6-month OS is 41.2%, with a median survival of 5.5 months among the 10 deceased (58.82% mortality). Curves by diagnosis (AML, MDS, MPN) show similar trends (p > 0.05). Censored data are marked with vertical ticks. (B) Kaplan-Meier curve comparing OS from KMT2A -PTD detection by transplant status (transplanted [blue, n=7] vs. non-transplanted [orange, n=10]). Transplanted patients show superior 17-month OS (68.6% vs. 0%, p=0.028), with median progression-free survival (PFS) not reached (42.9% events) versus ∼6 months for non-transplanted (80% events). FLT3 -positive patients (n=4) exhibit 100% mortality (p=0.0456). Censored data are marked with vertical ticks. Data reflects follow-up to April 30, 2025. FLT3 -positive patients (Patients 3, 7, 9, and 10) demonstrated 100% mortality (median survival: 8.5 months; 2–17 months), significantly higher than FLT3 -negative patients (46.2% mortality, p ≈ 0.0456). Patients harboring DNMT3A, RUNX1, or TET2 mutations had respective mortality rates of 60% (median survival 8.5 months), 62.5% (median 14 months), and 42.9% (median 4 months). Long-term survival data in cytogenetically normal AML with KMT2A -PTD suggest variability in outcomes [ 25 ], while expression studies in relatives indicate potential hereditary factors [ 26 ]. Mortality among patients with abnormal karyotypes (n=8)—including trisomy 8 (Patients 3, 5, and 10), +der (13;13) (Patient 4), and del(3)(q12q21) (Patient 6)— was 62.5% (median survival: 14 months), comparable to those with normal karyotypes (55.6%, p ≈ 0.8843). FISH-detected KMT2A gains (n=4) were associated with a 50% mortality rate (p ≈ 0.6287), while RUNX1T1 gains (n=3) correlated with 100% mortality (p ≈ 0.0891, marginally significant). Discussion Structural KMT2A gene alterations, often fusions, are found in hematologic malignancies like AML, MDS, and MPN. These partner genes are transcriptionally active or promote KMT2A fragment dimerization, acting as pro-oncogenic factors. KMT2A -PTD likely functions via dimerization, similar to some KMT2A translocations.[ 10 ]. KMT2A -PTD, poses significant diagnostic challenges due to its size, which is below the resolution of karyotyping (5–10 Mb) and standard FISH KMT2A break-apart probes [ 7 ]. These probes, designed for translocations, fail to reliably detect intragenic duplications due to signal overlap in interphase nuclei, as evidenced by patient 16’s non-canonical PTD (exons 27–36) showing only 9/200 cells with KMT2A gain. In contrast, CMA, with its dense SNP and copy number markers, detected KMT2A -PTD in approximately 50% of cells, aligning with a 40% blast count in bone marrow. This discrepancy underscores CMA’s superior sensitivity for copy number variations (CNVs) compared to FISH, which achieved only 16.13% sensitivity in this cohort [ 10 ]. CMA’s detection of non-canonical PTDs in patient 16 and secondary abnormalities (e.g. trisomy 8 and CN-LOH at 7q22.1qter in patient 14), underscores its superiority in detecting structural changes. However, post-CRS sensitivity in detecting KMT2A -PTD dropped to 68.57% due to false negatives (e.g., Patient 4’s 8% blasts, Patient 2’s 10–14% blasts), validated by NGS and outcomes. RNA fusion’s higher sensitivity (87.50% post-CRS) detected cryptic PTDs in Patients 4–7, validated by morphology, NGS, FISH and karyotype on concurrent and subsequent longitudinal specimens. Concordance was 73.33% (κ=0.4667), with RNA fusion outperforming CMA in discordant cases (p=0.03516), reflecting its sensitivity for low-VAF clones at leukemia transformation. The KMT2A-PTD-positive group detectable by CMA exhibited greater genomic complexity, with 17 secondary chromosomal abnormality types versus 6 in the CMA KMT2A -PTD-negative group, reflecting increased clonal heterogeneity [ 16 ]. Unique abnormalities in the former group (patients 2, 9, 10, 11, 14, and 17) included CN-LOH on 6q, 9p, 13q, 16p, 16q, and 7q, losses on Yq, 6p, and Xq, and gains on 1q, 2p, 11p/q, and trisomy 11, which may amplify the malignancy-promoting effects of oncogenic mutations (e.g., JAK2 , CDKN2A , EZH2 ) and drive aggressive clonal evolution [ 17 ]. In contrast, KMT2A -PTD-negative group (patients 4, 5, 6, and 7) showed fewer abnormalities by CMA, including unique loss of 11p, loss of 3q, and tetrasomy 13, suggesting distinct clonal drivers linked to RNA fusion detection of cryptic PTD [ 18 ]. Abnormalities in this patient group, such as CN-LOH 11q encompassing ATM gene in patient 7 and trisomy 13 associated with RUNX1/FLT3 mutations in patients 4 and 5, align with AML’s intermediate-to-poor prognostic profiles [ 19 ]. NGS analysis revealed DNMT3A (62.5%), RUNX1 (50%), and TET2 (43.75%) as frequent co-mutations, reflecting KMT2A- PTD’s synergy with DNA epigenetic and transcriptional dysregulation [ 20 ]. Higher expression of KMT2A -PTD in DNMT3A-, RUNX1 -, and FLT3 -positive specimens (p=0.0087–0.0452) and RUNX1T1 gain (p=0.0345, 0.0412) indicates aggressive clones, particularly in FLT3 -positive cases (100% mortality, Log-Rank Test, p=0.0456), supported by Zorko et al. (2012) [ 15 ]. The KMT2A -PTD/ DNMT3A / FLT3 -ITD combination, observed in patients 3, 7, 9, and 10, is associated with poor prognosis and high relapse rates, as FLT3 -ITD amplifies signaling dysregulation [ 21 ] and is linked to poor prognosis [ 3 ]. DNMT3A mutations, overlapping with trisomy 2p in patient 14, and EZH2 mutations, amplified by CN-LOH 7q in the same patient, suggest a dosage effect enhancing leukemogenesis, as supported by Mims et al. (2018) [ 22 ]. RUNX1 mutations, coupled with trisomy 21 in patient 14 and trisomy 13 in patients 5 and 10, impair hematopoiesis and synergize with FLT3 mutations, driving AML progression [ 15 ]. FLT3 mutations co-occurred with complex PTD, RUNX1T1 gain, and trisomy 8/13, likely contributing to the 100% mortality rate, as concluded independently and supported by Steudel et al. (2003) [ 12 ]. The cohort’s low 6-month overall survival (OS) at 41.2%, reflects poor prognosis of KMT2A -PTD, with a median survival of 5.5 months among deceased patients, exacerbated by complex PTD and FLT3 mutations. HSCT therapy markedly improved outcomes of the KMT2A -PTD patients (68.6% vs. 0% OS at 17 months, p=0.028), with 71.43% transplanted patients alive (e.g., patient 4: 51 months), supporting observations made by Antherieu et al. (2021) [ 21 ]. Non-transplanted patients (80% deceased, median survival of 6 months) align with data of Shiah et al. (2002). FLT3- positive cases showed limited HSCT benefit, supporting the results reported by others [ 12 ]. The low PFS event rate in transplanted patients indicates HSCT’s role in preventing progression at leukemia transformation, though early censoring underestimates long-term benefits. Limitations include the small sample (17 patients), limiting power for rare events (e.g., FLT3 , n=4). False negatives post-CRS (e.g., Patient 4’s residual disease) highlights the need for integrated testing. Patient 16’s non-canonical PTD requires RT-PCR or OGM validation [ 7 ]. In conclusion, CMA and RNA fusion are complementary with CRS refining detection accuracy (68.57% and 87.50% sensitivity, respectively). Tissue-specific activity of KMT2A -PTD suggests differential leukemogenic effects, consistent with findings from Dorrance et al. (2008) [ 29 ], while translocations involving KMT2A -PTD indicate complex genomic interactions, as supported by Yanamoto et al. (2005) [ 30 ], and therapeutic targeting of KMT2A -PTD has been explored in long-term studies [ 31 ]. RNA fusion excelling in identifying cryptic PTDs and CMA providing robust genomic structure analysis [ 5 ]. Integrated testing with NGS, FISH, karyotype, and FLT3 analysis enhance risk stratification, guiding targeted therapies such as menin and FLT3 inhibitors [ 22 ]. Given high PFS event rates and poor prognosis, particularly with FLT3 mutations, early HSCT in first remission is critical for managing this genomically complex malignancy. Authorship P.A and J.P. conceived the original idea for this study The diagnostic workup was. The literature review was performed by B.S. and J.P. Data collection and analysis were carried out by B.S and J.P. Data interpretation was performed by J.P., and B.S. B.S. wrote the original draft. Critical review and editing of the manuscript were undertaken by B.S., J.P., P.A., R.F., N.M., M.W, and R.N. All authors approved the final version of the manuscript for submission. Conflict-of-interest disclosure The authors declare no competing commercial interests. Data availability Deidentified raw CMA data (CEL files) and RNA sequencing data supporting the identification of KMT2A -Partial Tandem Duplications, along with a tab-separated values (TSV) file containing breakpoints, read support, and transcript annotations generated using Arriba, are available upon reasonable requests. This data can be obtained by contacting the corresponding author, Reza Nejati ( Reza.Nejati{at}fccc.edu ), subject to compliance with the Institutional Review Board (IRB) policies of Fox Chase Cancer Center to ensure patient confidentiality and ethical standards. View this table: View inline View popup Supplemental Table 1: Comparison of Methodologies for KMT2A-PTD detection View this table: View inline View popup Supplemental Table 2: KMT2A-PTD Genomic Coordinates, Exon Coverage, and Functional Domains detected by CMA (Affymetrix CytoScan HD) View this table: View inline View popup Supplemental Table 3. Unique Chromosomal Abnormalities (CMA), Frequency, Coordinates, Genes, and Mortality Status View this table: View inline View popup Supplemental Table 4: KMT2A-PTD RNA Fusion Panel Results: Breakpoints, Exons, Size, Reading Frame and Retained Domains View this table: View inline View popup Supplemental Table 5: KMT2A-PTD RNA Fusion Panel Results (Arriba): Breakpoints, Split Reads, Discordant Mates, Coverage and Retained Domains Acknowledgments The molecular, cytogenetic and clinical data being utilized in the study were collected previously as part of the patient’s routine clinical care. No separate specimens were collected for the study. The Institutional Review Board of Fox Chase Cancer Center provided ethical approval for this work. All authors state that the presented material does not include any information, unique characteristics or identifiers that could be used alone or in combination with other information to identify, directly or indirectly, any patients of the study. Footnotes The draft has been substantially condensed for clarity and conciseness. Figure legends have been added throughout the manuscript for improved interpretability. Additional analyses have been incorporated, including a comprehensive sensitivity and specificity analysis after applying a composite reference standard, to further strengthen the validity of our findings. Figure 4A has been corrected to display the accurate values for Total Split Reads. Additionally, there has been a minor change to the manuscript title. Reference list 1. ↵ Strout , M.P. , et al. , The partial tandem duplication of ALL1 (MLL) is consistently generated by Alu-mediated homologous recombination in acute myeloid leukemia . Proc Natl Acad Sci U S A , 1998 . 95 ( 5 ): p. 2390 – 5 . OpenUrl Abstract / FREE Full Text 2. ↵ Seto , A. , et al. , Genomic Characterization of Partial Tandem Duplication Involving the KMT2A Gene in Adult Acute Myeloid Leukemia . 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NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Role of Chromosomal Microarray and RNA Fusion Analysis in Detecting KMT2A-PTD and Stem Cell Transplant Impact on Mortality Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Role of Chromosomal Microarray and RNA Fusion Analysis in Detecting KMT2A -PTD and Stem Cell Transplant Impact on Mortality Bhaumik Shah , Roniya Francis , Ashishkumar Sonani , Jianming Pei , Peter Abdelmessieh , Mariusz A. Wasik , Nicholas Mackrides , Reza Nejati medRxiv 2025.05.27.25328455; doi: https://doi.org/10.1101/2025.05.27.25328455 Share This Article: Copy Citation Tools Role of Chromosomal Microarray and RNA Fusion Analysis in Detecting KMT2A -PTD and Stem Cell Transplant Impact on Mortality Bhaumik Shah , Roniya Francis , Ashishkumar Sonani , Jianming Pei , Peter Abdelmessieh , Mariusz A. 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