Backtracking the cellular origins of ETV6::RUNX1 childhood acute lymphoblastic leukemia in cord blood (ReCord study)

Abstract Introduction:Childhood leukemia usually develops via a two-hit mechanism, with a preleukemic genomic lesion arising before birth as the first step. In utero origins of preleukemia have been described for several subtypes of acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML); however, backtracking studies have largely relied on newborn dried bloodspots, precluding identification of preleukemic cells of origin. We developed the “ReCord” study (R01CA262012) to conduct comprehensive backtracking and characterization of preleukemic cells across leukemia subtypes, via recruitment of childhood leukemia patients with banked cord blood (CB) at birth. We present initial results for a set of patients with ETV6::RUNX1 fusions. Methods:Childhood leukemia patients with banked CB at birth and available diagnostic leukemia (tumor) samples are enrolled into ReCord through Children's Oncology Group (COG) project AEPI20N1 or as volunteers. Paired tumor-germline whole-genome sequencing (WGS) and tumor RNA-sequencing were conducted to identify molecular subtypes and somatic driver events in each patient. We have first focused on ETV6::RUNX1 fusions, which have established in utero origins. Precise fusion breakpoint locations were obtained from structural variant calling in WGS data. Snapgene was used to generate patient-specific transgenes from which patient-specific droplet digital PCR (ddPCR) primer/probe assays were designed and optimized for backtracking experiments. A control gene ddPCR assay allowed quantification. Patient CB samples were enriched for CD34 expression using microbead selection. CD34-enriched or CD34-depleted cells were FACS-sorted to isolate 5 populations: B cells (CD34-CD19+), other differentiated cells (CD34-CD19-), B progenitors (Lin-CD34+CD38+CD19+), other progenitors (Lin-CD34+CD38+CD19-), and earliest hematopoietic stem/progenitor cells (HSPC) (Lin-CD34+CD38-), where Lin=CD2/3/14/16/56/235+ cells. None of the earliest HSPC were CD19+. Sorted CB populations were analyzed for ETV6::RUNX1 fusions using patient-specific ddPCR assays. Results:To date, we have enrolled 58 childhood leukemia patients in ReCord (45 ALL, 12 AML, 1 MPAL), of whom 40 were recruited through COG and 18 were volunteers. CB samples have been received for 28/58 patients, and paired tumor samples obtained for 19 of these. We determined the molecular subtypes and genomic driver events via WGS and RNA-sequencing in 15/19 patients; for 4 patients, leukemia blast count was too low (≤10%) to detect somatic drivers. We initially identified 3 childhood ALL patients with ETV6::RUNX1 fusions, and confirmed fusion breakpoints by PCR and Sanger sequencing. Patient-specific ddPCR assays were optimized in each corresponding tumor sample and then tested in the 5 sorted CB cell populations. For two out of three patients, we detected preleukemic ETV6::RUNX1 fusions in at least one CB cell population. In patient 1, the ETV6::RUNX1 fusion was detected in all three CD34+ CB populations, with the highest clonal frequency seen in B-cell progenitors (73%), then earliest HSPCs (20%), and the lowest frequency found in non-B-cell progenitors (9%). The two CD34- populations had very low detection rates (0.4% & 1.3%). In patient 2, the fusion was only detected in the CD34-CD19+ B-cell compartment at low frequency (0.2%). For patient 3, no preleukemia was detectable in any of the five CB populations. ddPCR assays have been designed and optimized for 5 additional patients with varying driver events to date (n=3 ALL, n=2 AML). Discussion:ReCord has amassed, to our knowledge, the largest collection of paired CB and tumor samples from childhood leukemia patients. Initial backtracking experiments in patient CB revealed variation in the cell types that harbor ETV6::RUNX1 preleukemic fusions, with only one of three patients harboring the fusion in the earliest stem and progenitor cell compartment. A second aliquot of CB and the corresponding tumor sample from each of these 3 patients are currently being processed for simultaneous single cell genotyping and transcriptomic assays (TARGET-seq). Molecular characterization of normal, preleukemic and leukemic cells, will throw light on the specific prenatal cell types that transform to leukemia, and the molecular mechanisms involved. The ReCord study will eventually inform the potential for newborn screening of preleukemia.

Institutions

Publication Details

Journal
Blood
Published
2025-11-03
DOI
https://doi.org/10.1182/blood-2025-3368
Primary Topic
Acute Lymphoblastic Leukemia research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Backtracking the cellular origins of ETV6::RUNX1 childhood acute lymphoblastic leukemia in cord blood (ReCord study)

Blood
Acute Lymphoblastic Leukemia research
article

Backtracking the cellular origins of ETV6::RUNX1 childhood acute lymphoblastic leukemia in cord blood (ReCord study)

article en

Abstract

Abstract Introduction:Childhood leukemia usually develops via a two-hit mechanism, with a preleukemic genomic lesion arising before birth as the first step. In utero origins of preleukemia have been described for several subtypes of acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML); however, backtracking studies have largely relied on newborn dried bloodspots, precluding identification of preleukemic cells of origin. We developed the “ReCord” study (R01CA262012) to conduct comprehensive backtracking and characterization of preleukemic cells across leukemia subtypes, via recruitment of childhood leukemia patients with banked cord blood (CB) at birth. We present initial results for a set of patients with ETV6::RUNX1 fusions. Methods:Childhood leukemia patients with banked CB at birth and available diagnostic leukemia (tumor) samples are enrolled into ReCord through Children's Oncology Group (COG) project AEPI20N1 or as volunteers. Paired tumor-germline whole-genome sequencing (WGS) and tumor RNA-sequencing were conducted to identify molecular subtypes and somatic driver events in each patient. We have first focused on ETV6::RUNX1 fusions, which have established in utero origins. Precise fusion breakpoint locations were obtained from structural variant calling in WGS data. Snapgene was used to generate patient-specific transgenes from which patient-specific droplet digital PCR (ddPCR) primer/probe assays were designed and optimized for backtracking experiments. A control gene ddPCR assay allowed quantification. Patient CB samples were enriched for CD34 expression using microbead selection. CD34-enriched or CD34-depleted cells were FACS-sorted to isolate 5 populations: B cells (CD34-CD19+), other differentiated cells (CD34-CD19-), B progenitors (Lin-CD34+CD38+CD19+), other progenitors (Lin-CD34+CD38+CD19-), and earliest hematopoietic stem/progenitor cells (HSPC) (Lin-CD34+CD38-), where Lin=CD2/3/14/16/56/235+ cells. None of the earliest HSPC were CD19+. Sorted CB populations were analyzed for ETV6::RUNX1 fusions using patient-specific ddPCR assays. Results:To date, we have enrolled 58 childhood leukemia patients in ReCord (45 ALL, 12 AML, 1 MPAL), of whom 40 were recruited through COG and 18 were volunteers. CB samples have been received for 28/58 patients, and paired tumor samples obtained for 19 of these. We determined the molecular subtypes and genomic driver events via WGS and RNA-sequencing in 15/19 patients; for 4 patients, leukemia blast count was too low (≤10%) to detect somatic drivers. We initially identified 3 childhood ALL patients with ETV6::RUNX1 fusions, and confirmed fusion breakpoints by PCR and Sanger sequencing. Patient-specific ddPCR assays were optimized in each corresponding tumor sample and then tested in the 5 sorted CB cell populations. For two out of three patients, we detected preleukemic ETV6::RUNX1 fusions in at least one CB cell population. In patient 1, the ETV6::RUNX1 fusion was detected in all three CD34+ CB populations, with the highest clonal frequency seen in B-cell progenitors (73%), then earliest HSPCs (20%), and the lowest frequency found in non-B-cell progenitors (9%). The two CD34- populations had very low detection rates (0.4% & 1.3%). In patient 2, the fusion was only detected in the CD34-CD19+ B-cell compartment at low frequency (0.2%). For patient 3, no preleukemia was detectable in any of the five CB populations. ddPCR assays have been designed and optimized for 5 additional patients with varying driver events to date (n=3 ALL, n=2 AML). Discussion:ReCord has amassed, to our knowledge, the largest collection of paired CB and tumor samples from childhood leukemia patients. Initial backtracking experiments in patient CB revealed variation in the cell types that harbor ETV6::RUNX1 preleukemic fusions, with only one of three patients harboring the fusion in the earliest stem and progenitor cell compartment. A second aliquot of CB and the corresponding tumor sample from each of these 3 patients are currently being processed for simultaneous single cell genotyping and transcriptomic assays (TARGET-seq). Molecular characterization of normal, preleukemic and leukemic cells, will throw light on the specific prenatal cell types that transform to leukemia, and the molecular mechanisms involved. The ReCord study will eventually inform the potential for newborn screening of preleukemia.

BloodVol. 146(Supplement 1)
University of Minnesota (US), Los Angeles County Department of Public Health (US), University of Oxford (GB), MRC Weatherall Institute of Molecular Medicine (GB), Science Oxford (GB)
Openalex Percentile: Top 32%
Acute Lymphoblastic Leukemia research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.