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Published before final editing as: Blood. 2026 Mar 27:blood.2025031102. doi: 10.1182/blood.2025031102 Search in PMC Search in PubMed View in NLM Catalog Add to search IGH::FENDRR and specific KRAS mutations define a novel B-ALL molecular subtype with poor chemotherapy response Sonja Bendig Sonja Bendig 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 2 Clinical Research Unit ‘CATCH ALL’ (KFO 5010) funded by the Deutsche Forschungsgemeinschaft; Find articles by Sonja Bendig 1, 2, * , Alina M Hartmann Alina M Hartmann 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 2 Clinical Research Unit ‘CATCH ALL’ (KFO 5010) funded by the Deutsche Forschungsgemeinschaft; Find articles by Alina M Hartmann 1, 2, * , Wiebke Wessels Wiebke Wessels 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 3 Children’s Cancer Institute, Sydney, Australia; Find articles by Wiebke Wessels 1, 3, * , Thomas Beder Thomas Beder 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; Find articles by Thomas Beder 1 , Rathana Kim Rathana Kim 4 Hematology Laboratory, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris (AP-HP), Institut de Recherche Saint-Louis, Université Paris Cité, Paris, France; Find articles by Rathana Kim 4 , Marie Passet Marie Passet 4 Hematology Laboratory, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris (AP-HP), Institut de Recherche Saint-Louis, Université Paris Cité, Paris, France; Find articles by Marie Passet 4 , Qingsong Gao Qingsong Gao 5 Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA; Find articles by Qingsong Gao 5 , Nadine Wolgast Nadine Wolgast 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 2 Clinical Research Unit ‘CATCH ALL’ (KFO 5010) funded by the Deutsche Forschungsgemeinschaft; Find articles by Nadine Wolgast 1, 2 , Johanna M Horns Johanna M Horns 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; Find articles by Johanna M Horns 1 , Leonardo Alves Santos Leonardo Alves Santos 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; Find articles by Leonardo Alves Santos 1 , Katharina Iben Katharina Iben 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 2 Clinical Research Unit ‘CATCH ALL’ (KFO 5010) funded by the Deutsche Forschungsgemeinschaft; Find articles by Katharina Iben 1, 2 , Fabio D Steffen Fabio D Steffen 6 Department of Oncology and Children’s Research Center, University Children’s Hospital, Zurich, Switzerland; Find articles by Fabio D Steffen 6 , Loredana Cantoni Loredana Cantoni 6 Department of Oncology and Children’s Research Center, University Children’s Hospital, Zurich, Switzerland; Find articles by Loredana Cantoni 6 , Britta Kehden Britta Kehden 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; Find articles by Britta Kehden 1 , Guranda Chitadze Guranda Chitadze 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 2 Clinical Research Unit ‘CATCH ALL’ (KFO 5010) funded by the Deutsche Forschungsgemeinschaft; Find articles by Guranda Chitadze 1, 2 , Axel Künstner Axel Künstner 7 Medical Systems Biology Group, Lübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany; Find articles by Axel Künstner 7 , Hauke Busch Hauke Busch 7 Medical Systems Biology Group, Lübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany; Find articles by Hauke Busch 7 , Beat Bornhauser Beat Bornhauser 6 Department of Oncology and Children’s Research Center, University Children’s Hospital, Zurich, Switzerland; Find articles by Beat Bornhauser 6 , Jean-Pierre Bourquin Jean-Pierre Bourquin 6 Department of Oncology and Children’s Research Center, University Children’s Hospital, Zurich, Switzerland; Find articles by Jean-Pierre Bourquin 6 , Thibaut Leguay Thibaut Leguay 8 Hematology Department, CHU de Bordeaux, Hôpital du Haut-Levêque, Pessac, France; Find articles by Thibaut Leguay 8 , Nicolas Boissel Nicolas Boissel 9 Hematology Department, Hôpital Saint-Louis, AP-HP, Université Paris Cité, Paris, France; Find articles by Nicolas Boissel 9 , Nicola Gökbuget Nicola Gökbuget 10 Department of Medicine II, Hematology/Oncology, Goethe University, Frankfurt, Germany; Find articles by Nicola Gökbuget 10 , Ilaria Iacobucci Ilaria Iacobucci 5 Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA; Find articles by Ilaria Iacobucci 5 , Charles G Mullighan Charles G Mullighan 5 Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA; 11 Center of Excellence for Leukemia Studies, St. Jude Children’s Research Hospital, Memphis, TN, USA Find articles by Charles G Mullighan 5, 11 , Emmanuelle Clappier Emmanuelle Clappier 4 Hematology Laboratory, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris (AP-HP), Institut de Recherche Saint-Louis, Université Paris Cité, Paris, France; Find articles by Emmanuelle Clappier 4, * , Claudia D Baldus Claudia D Baldus 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 2 Clinical Research Unit ‘CATCH ALL’ (KFO 5010) funded by the Deutsche Forschungsgemeinschaft; Find articles by Claudia D Baldus 1, 2, * , Monika Brüggemann Monika Brüggemann 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 2 Clinical Research Unit ‘CATCH ALL’ (KFO 5010) funded by the Deutsche Forschungsgemeinschaft; Find articles by Monika Brüggemann 1, 2, * , Lorenz Bastian Lorenz Bastian 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 2 Clinical Research Unit ‘CATCH ALL’ (KFO 5010) funded by the Deutsche Forschungsgemeinschaft; Find articles by Lorenz Bastian 1, 2, * Author information Copyright and License information 1 Medical Department II, Hematology/Oncology, University Hospital Schleswig-Holstein, Kiel, Germany; 2 Clinical Research Unit ‘CATCH ALL’ (KFO 5010) funded by the Deutsche Forschungsgemeinschaft; 3 Children’s Cancer Institute, Sydney, Australia; 4 Hematology Laboratory, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris (AP-HP), Institut de Recherche Saint-Louis, Université Paris Cité, Paris, France; 5 Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA; 6 Department of Oncology and Children’s Research Center, University Children’s Hospital, Zurich, Switzerland; 7 Medical Systems Biology Group, Lübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany; 8 Hematology Department, CHU de Bordeaux, Hôpital du Haut-Levêque, Pessac, France; 9 Hematology Department, Hôpital Saint-Louis, AP-HP, Université Paris Cité, Paris, France; 10 Department of Medicine II, Hematology/Oncology, Goethe University, Frankfurt, Germany; 11 Center of Excellence for Leukemia Studies, St. Jude Children’s Research Hospital, Memphis, TN, USA * These authors contributed equally to this work Authorship Contributions MB, LB, SB, AMH and WW designed the study. SB, WW, AMH and BK collected and selected patient data. RK, MP, QG, TG, NB, IL, CGM and EC collected and analyzed data for validation cohorts. NG, TG and NB provided clinical data. SB and WW analyzed and interpreted EC-NDC data and MRD tracking. SB, AMH, RK, MP, QG, EC and LB analyzed and interpreted transcriptome data. AMH, TB, and NW performed integrative bioinformatic data analysis. JMH, LAS, LB, AK and HB analyzed methylation data. KI and LB analyzed copy number variations. SB and AMH performed statistical tests and produced visualizations. FDS, LC, BB and JB performed and interpreted drug response profiling. IL, CG and EC contributed to the conceptual framework of the study. MB, LB and CDB supervised the study. SB wrote the first draft of the manuscript. All authors approved the final version of the manuscript. ✉ Corresponding author : Prof. Dr. med. Monika Brüggemann, Unit for Hematological Diagnostics, Medical Department II, University Hospital Schleswig-Holstein, Campus Kiel, Langer Segen 8-10, 24105 Kiel, Germany, [email protected] PMC Copyright notice PMCID: PMC13072441 NIHMSID: NIHMS2161857 PMID: 41894249 The publisher's version of this article is available at Blood Abstract Large scale sequencing efforts have defined up to 27 diagnostic entities in B-ALL, leaving few samples without subtype assignment. Extended genomic and transcriptomic profiling in routine diagnostics broadens the sample collection and holds the potential to identify novel B-ALL subtypes. By analyzing an aggregated set of 4,857 B-ALL patients from three cohorts, we identified a novel group of twenty cases (age 18–66 years, median: 34 years) characterized by a previously undescribed IGH::FENDRR rearrangement exclusive to this subtype (n=17/20), KRAS p.A146T/V/P mutations (n=17/20 vs. n=86/4,857; p<0.001) and distinct DNA-methylation/gene expression profiles, including overexpression of the lncRNA FENDRR and the transcription factor FOXF1 (‘FOXF1/FENDRR’) as well as JAK/STAT and RAS signaling signatures. A gene expression machine learning classifier identified FOXF1/FENDRR cases in two independent cohorts with high accuracy. Patients treated according to GMALL/GRAALL protocols showed very poor chemotherapy response with n=8/13 having induction failure or MRD ≥10 −3 and n=8/12 remaining MRD positive after 1 st consolidation / salvage. MRD-stratified intensification including blinatumomab (n=10) and/or allogenic stem cell transplantation (n=12) resulted in ongoing molecular remission in 13/16 cases. FOXF1/FENDRR patients represent a novel B-ALL subtype which might benefit from early immunotherapeutic treatment or targeted interventions. Scientific category: Lymphoid Neoplasia Introduction The molecular landscape of B-cell precursor acute lymphoblastic leukemia (B-ALL) is shaped by genomic aberrations and corresponding transcriptional profiles. 1 The International Consensus Classification of Myeloid Neoplasms and Acute Leukemias (ICC) and the 5 th edition of the World Health Organization (WHO) Classification of Lymphoid Neoplasms define up to 22 molecular subtypes, as well as 5 provisional entities. 2 , 3 However, 10 – 15% of patients cannot be assigned to recognized subtypes, suggesting the existence of yet unidentified drivers. Here we report a novel molecular subtype defined by a rearrangement of IGH to the FOXF1/FENDRR loci and particular KRAS mutations. Study design We analyzed 1,715 adult B-ALL patients treated according to the Multicenter Study Group on Adult ALL (GMALL) protocols with the EuroClonality NGS DNA Capture Assay (EC-NDC Assay) 4 followed by ARResT/Interrogate analysis 5 (n=981) and/or whole transcriptome sequencing (WTS) using the Illumina stranded mRNA protocol followed by IntegrateALL and ALLCatchR analysis 6 , 7 (n=767). A machine learning classifier for identification of FOXF1/FENDRR patients was trained on 707 B-ALL samples by performing LASSO feature selection 8 and a 10-fold randomized stratified cross validation scheme with an ensemble of five machine learning methods implemented in the R package caret. 9 Subsequently we applied it to two independent B-ALL cohorts for identification of additional patients: a cohort of 1,154 adult B-ALL samples from the GRAALL study group and the St. Jude cohort reported by Gu et al. 10 , 11 (n=1,988). DNA methylation pattern was profiled for 9/20 patients using the Infinium Methylation EPIC v2.0 array and compared to 83 primary diagnostic B-ALL samples. Copy number alterations were assessed by multiplex ligation-dependent probe amplification (MLPA) using the SALSA MLPA Probemix P335 ALL-IKZF1 (MRC Holland) and SNP array–based genotyping using the Illumina Infinium Genotyping System (iScan) according to the manufacturer’s instructions. Ex vivo drug response profiling (DRP) was performed for one FOXF1/FENDRR patient-derived xenograft (PDX) by exposing leukemic cells to a panel of selected inhibitors and conventional chemotherapeutics for 72h as previously described. 12 , 13 All patients provided written informed consent in accordance with the Declaration of Helsinki. This study was approved by the institutional review board of the Christian-Albrechts-University in Kiel (ethics approval number D416/21). Detailed information on the methods are available in the supplement . Results and discussion From 4,857 B-ALL patients (3,572 adult, 1,285 children), we identified twenty (13 male, 7 female) with recurrent distinct characteristics identifying them as a novel molecular subtype. Age at initial diagnosis ranged from 18–66 years (median: 34 years) and all presented with a pre-B/common-B-ALL immunophenotype. Compared with an overall GMALL08 cohort (ages 18–55), these patients had significantly lower white blood count at diagnosis, with a median of 1.74 × 10 9 /L (range 0.86–4.3 × 10 9 /L) versus 7.7 × 10 9 /L (range 0.3–731.9 × 10 9 /L; p<0.001; Table 1 ). Table 1. Clinical characteristics of FOXF1/FENDRR patients Patient Cohort Sex Age WBC (× 10 9 /L) Immuno-phenotype MRD post Ind MRD post Cons 1 Blina allo-HSCT outcome 1 GMALL f 46 2.30 c-ALL 4.00E-04 1.00E-03 yes yes alive in CR at 2099 d 2 GMALL m 32 1.70 c-ALL NA 7.00E-04 no yes alive in CR at 944 d 3 GMALL m 22 0.86 c-ALL positive <lE-05 negative <lE-05 yes yes alive in CR at 742 d 4 GMALL m 41 1.61 c-ALL 8.00E-04 positive <lE-03 yes yes alive in CR at 377 d 5 GMALL f 19 2.60 Pre-B-ALL 9.00E-03 1.00E-02 yes yes alive in CR at 574 d 6 GMALL m 40 4.28 c/pre-B- positive <lE-04 negative <3E-05 no no alive in CR at 666 d 7 GMALL f 66 1.48 c-ALL - - - - died during induction therapy 8 a) GMALL m 48 1.23 c/pre-B- - - no yes alive in CR at 519 d g b) GMALL m 34 1.44 c-ALL 1.10E-01 NA yes yes alive in CR at 458 d 10 GMALL m 33 4.30 Pre-B-ALL 7.00E-03 2.00E-02 yes yes alive in CR at 1709 d 11 GMALL m 28 2.10 Pre-B-ALL 3.00E-02 negative <lE-05 no no alive in CR at 92 d B_SL122 GRAALL f 23 2.20 c-ALL 5.00E-01 2.00E-04 yes yes died at 212 d G14_0280 GRAALL m 30 1.00 c-ALL 3.00E-01 2.00E-04 no yes alive in CR at 1174 d G14_0727 GRAALL m 33 2.38 c-ALL 7.00E-01 negative <lE-05 yes c) yes alive in CR at 337 d B_SL445 GRAALL f 36 1.74 Pre-B-ALL 5.00E-04 5.00E-04 yes d) no relapsed at 761 d B_SL1005 GRAALL m 19 2.60 c-ALL 2.00E-01 3.00E-01 yes e) yes alive at 498 d SJERG021891 St Jude m 22 2.70 NA NA NA NA NA NA SJALL054487 St Jude f 55 0.90 NA NA NA NA NA NA SJALL054499 St Jude f 37 1.30 NA NA NA NA NA NA SJBALL014249 St Jude m 18 NA NA NA NA NA NA NA Open in a new tab a) no MRD measurements due to failure to detect IG/TR markers b) received early blinatumomab during induction therapy followed by allo-HSCT due to induction failure c) VANDA-BLINA salvage d) after relapse e) after loss of B-cell aplasia after CAR-T cell therapy Unsupervised analysis of GMALL cohort B-ALL cases (n=77/767) without confirmed subtype allocation identified a distinct cluster for n=9/77 cases ( Figure 1A , 1B ) characterized by absence of recurrent B-ALL subtype-defining driver aberrations and 799 differentially expressed genes (FDR <0.05, log2FC>2) compared to the remaining B-ALL samples ( Supplementary Figure S1 ). Most strikingly upregulated genes were Forkhead Protein 1 ( FOXF1 ) and its adjacent FOXF1 enhancer-derived non-coding RNA ( FENDRR ; Figure 1C ). We therefore termed this group FOXF1/FENDRR. Further included in this signature were the largely unstudied OLFM3 , the argonaute proteins PIWIL1 and PIWIL3 , as well as KDR (previously: VEGFR2) , a critical mediator of VEGF-driven signaling pathways, which is regulated by FOXF1 . 14 , 15 Using our ALLCatchR 6 tool for B-ALL subtype prediction, most patients showed BCR::ABL1-like candidate predictions while lacking typical BCR::ABL1-like ALL drivers (n=15/18). DNA methylation profiling confirmed independence of a FOXF1/FENDRR cluster despite some overlap with BCR::ABL1-positive/-like cases ( Figure 1D , Supplementary Figure S3 ). We identified 34 genes as specific to this group by feature selection ( Supplementary Figure S2A , S2B ) and implemented them in the ALLCatchR 2,802-gene signature for B-ALL subtype discrimination. 6 We trained a machine learning classifier for these ‘FOXF1/FENDRR’ cases which specifically identified all 9 of 9 patients with RNA-seq in the training set. Testing on the independent GRAALL and St. Jude cohorts identified 5/1,154 and 4/1,988 additional FOXF1/FENDRR gene expression cases respectively ( Figure 1E ). Figure 1: Open in a new tab Molecular profiling of a novel B-ALL subtype: FOXF1/FENDRR subtype. (A) UMAP of 767 adult B-ALL patients with WTS data from the discovery cohort. (B) Unsupervised clustering of the top 300 variable expressed genes of 767 adult B-ALL patients with WTS data from the discovery cohort. (C) Expression of FENDRR and FOXF1 across molecular subgroups (n =767). (D) Methylation profile of FOXF1/FENDRR patients (n=9/11) and a B-ALL cohort of other subtypes (n=83). 1 Principal component analysis of the top 0.1 % most variable CpGs are shown. Lines connect centroids of the previously established B-ALL subtypes 1 , subgroup colors are consistent with Figure 1A . (E) FENDRR expression vs. class probability of a machine learning classifier trained on the discovery cohort for the identification FOXF1/FENDRR cases. Results from two independent validation cohorts are shown. FENDRR itself was not included in the classifier. (F) Genomic breakpoints of FOXF1/FENDRR patients of the discovery cohort (n=11) on chromosome 14 and chromosome 16. (G) Genomic profiling of FOXF1/FENDRR patients from the discovery cohort (n=11) and the two validation cohorts (n=9). (H) Distribution of KRAS mutations in FOXF1/FENDRR patients (n=20) compared to other B-ALL subtypes (n=3,688). A total of n=13 patients with multiple KRAS mutations including codon 146 and other codons were listed as “other KRAS mutations”. In 17 out of these 20 patients and none of the remaining 4,837 cases, we detected the so far not described IGH::FENDRR rearrangement by genomic (n=12/12, NDC-Capture panel / WGS) and/or transcriptomic (n=9/18 RNA-seq) profiling ( Figure 1F ). The lack of fusion transcript detection by RNA-Seq in some cases may reflect a low blast percentage in the respective samples (blast percentage 11 – 50%). Genomic FENDRR breakpoints were intronic (n=6/12) or downstream (n=6/12) of FENDRR ( Supplementary Table S1 ). FENDRR expression was limited to the first exon in cases with intronic breakpoints, while downstream breakpoints resulted in expression of the complete lncRNA ( Supplementary Figure S4 ). FOXF1 was highly expressed in all cases, consistent with the assumption that the IGH enhancer is redirected to drive expression of FOXF1 and the remaining FENDRR exons. During treatment courses, IGH::FENDRR levels were comparable to established IG markers, supporting its specificity for the leukemic clone and its potential applicability as an MRD marker ( Supplementary Figure S5 ). In addition, genomic profiling identified KRAS mutations in all FOXF1/FENDRR cases, representing the only recurrent secondary aberration ( Supplementary Table S1 ). The most frequent variants were p.A146V/T/P (n=17/20), whereas p.G12R, p.A18D, and p.E63K were detected in one case each ( Figure 1G , H ). This represented a strong enrichment of codon 146 variants compared to other B-ALL cases (85% vs. 1%; p<0.001) ( Figure 1H ). Notably, the overall less frequent codon 146 or p.G12R and p.A18D variants have been shown to induce weaker downstream MAPK activity compared to typical hotspots (e.g.; KRAS G12D) 16 , 17 , 18 , 19 implying a ‘Goldilocks principle’ of MAPK signaling in FOXF1/FENDRR. FOXF1 has been shown to regulate STAT3 20 while it is by itself subjected to JAK2-dependent regulation. 21 , 22 Consistently, we observed upregulation of both RAS/MAPK and JAK/STAT signaling pathways in FOXF1/FENDRR gene set enrichment analyses ( Supplementary Figure S6 ), which might reflect the partial overlap of DNA methylation/gene expression signatures with BCR::ABL1-positive/-like ALL cases. DRP data on one PDX sample (Pat 6) functionally supported this biology. Sensitivity to MEK inhibitors (trametinib, selumetinib) indicated KRA S mutation-driven RAS-MAPK pathway activation ( Supplementary Figure S7 ), while sensitivity to PI3K/AKT inhibitors (buparlisib, ipatasertib) indicated parallel PI3K/AKT pathway activation. Notably, a series of inhibitors against receptor and non-receptor tyrosine kinases (VEGFR, FLT3, PDGFR, ABL1), including dovitinib and sunitinib, as well as fedratinib and ponatinib, showed distinct effects ex vivo , in line with similarities of FOXF1/FENDRR transcriptomes to BCR::ABL1-positive/ -like ALL. Conversely, resistance to dexamethasone, cytarabine, and the BCL2 inhibitor venetoclax suggests survival is kinase-driven and BCL2-independent. Collectively, the findings from the DRP assay are consistent with the rearrangement broadly activating downstream signaling pathways, which will merit further functional evaluation. FOXF1/FENDRR patients with available outcome data were treated according to the GMALL (n=11; Figure 2A ; Table 1 ), GRAALL (n=4) or FRALLE (n=1) protocols. One GMALL patient died during induction. Of the remaining ten, two were stratified high risk due to MRD persistence and eight to standard risk. One patient received early blinatumomab during induction therapy followed by allogenic stem cell transplantation (allo-HSCT) due to induction failure; in another, MRD measurements failed. Of the remaining eight, only three patients (38%) achieved complete MRD clearance after first consolidation chemotherapy indicating a poor chemotherapy response compared to a GMALL reference cohort (66 % (273/412) MRD negativity at the same time point ( Figure 2B )). Six of these eight patients subsequently received blinatumomab and/or allo-HSCT. Similarly, n=4/5 GRAALL/FRALLE patients failed induction therapy with MRD-levels >10% ( Figure 2B ). After first consolidation, only one patient cleared MRD. Subsequent treatment included blinatumomab (n=2), with one of these patients later proceeding to CAR-T cell therapy (n=1), and allogeneic stem cell transplantation (n=4), collectively supporting a poor chemotherapy response phenotype in FOXF1/FENDRR patients. Figure 2: Open in a new tab Therapy response of FOXF1/FENDRR patients (A) MRD kinetics of FOXF1/FENDRR patients (n=11) within the first year of treatment. Information on blinatumomab and allogeneic stem cell transplantation (allo-HSCT) is included. Each dot represents an MRD measurement. Dots below the dotted line are MRD positive and quantifiable, dots on the dotted line represent MRD positive values below the quantitative range. Dots below the line are MRD negative. (B) MRD response of FOXF1/FENDRR patients of the discovery cohort treated according to GMALL protocols measured by clone-specific real-time quantitative PCR of immune gene rearrangements after consolidation cycle I in comparison to adult B-ALL patients of other subtypes (n=412, GMALL 08 patients with available MRD data). MRD negative: MRD negative with a sensitivity of at least 10 −4 , MRD intermediate: MRD positive <10 −4 or below quantifiable range: MRD positive: MRD above 10 −4 . Patients 7, 8 and 9 were excluded. (C) MRD response of FOXF1/FENDRR patients of the French cohort treated according to GRAALL/FRALLE protocols (n=5) after end of induction in comparison to adult B-ALL patients of other subtypes (n=586, GRAALL-2014 25 ). FOXF1/FENDRR has recently been identified as a driver of a novel lineage-ambiguous high-risk T-ALL subtype in which FOXF1/FENDRR expression is driven from re-targeting of the BCL11B enhancer. 23 B-ALL samples with other lineage transcending ALL divers like KMT2A- or ZNF384- rearrangements show characteristics of more immature B-ALL developmental states. 24 FOXF1/FENDRR B-ALL cases, however, showed highest proximity to more advanced Pre-B II stages consistent with the observed common B-ALL immunophenotypes ( Supplementary Figure S8 ). In conclusion, IGH::FENDRR and specific KRAS mutations define a novel B-ALL subtype in adult patients with a distinct gene expression / DNA methylation signature and poor chemotherapy response. Co-occurrence of these driver events suggests an oncogenic synergy that, while driving resistance against chemotherapy, also exposes potential therapeutic vulnerabilities within the MAPK and PI3K/AKT signaling pathways. Supplementary Material Supplementary Table, Figures, Methods, References NIHMS2161857-supplement-Supplementary_Table__Figures__Methods__References.pdf (2MB, pdf) Key Points. FOXF1/FENDRR is a molecular adult B-ALL subtype defined by IGH::FENDRR , specific KRAS mutations and FOXF1 overexpression. FOXF1/FENDRR B-ALL patients show poor initial chemotherapy response salvaged by immunotherapy or allogenic HSCT. Acknowledgements This study was funded in part by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation) project number 444949889 (KFO 5010 Clinical Research Unit “CATCH ALL”; S.B., A.M.H., N.W., G.C., C.B.D, L.B., M.B.) and the Clinician Scientist Program in Evolutionary Medicine (project number 413490537 (G. C.). C.G.M. is supported by a National Cancer Institute Outstanding Investigator Award (R35 CA197695) and the American and Lebanese Syrian Associated Charities of St. Jude Children’s Research Hospital. Disclosure of Conflicts of Interest CB is consulting Astellas, BMS, AstraZeneca, Amgen, Jazz Pharmaceuticals, Gilead and Jannssen. MB is a member of Incytes and Amgens Board of Directors or advisory committees and the Speakers Bureaus of BD, Janssen, Pfizer and Amgen. CGM has received speaking fees from Amgen, grant support from Pfizer and Abbvie, and royalties from Cyrus. For the remaining authors, no relevant conflicts of interest were declared. Data sharing statement: RNA-seq count data for all FOXF1/FENDRR cases and the remaining B-ALL cohort are publicly available at https://doi.org/10.5281/zenodo.18310354 and https://doi.org/10.5281/zenodo.18952693 . 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[ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Supplementary Table, Figures, Methods, References NIHMS2161857-supplement-Supplementary_Table__Figures__Methods__References.pdf (2MB, pdf) Data Availability Statement RNA-seq count data for all FOXF1/FENDRR cases and the remaining B-ALL cohort are publicly available at https://doi.org/10.5281/zenodo.18310354 and https://doi.org/10.5281/zenodo.18952693 . Raw sequencing data for RNA-seq and gene panel sequencing are available in part through the European Genome-Phenome Archive (EGA) under accessions EGAD00001008633, EGAD00001010070. 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