MétaCan
Menu
Back to cohort
Record W4389248130 · doi:10.1182/blood-2023-190180

Single Cell Transcriptomic Analysis of B-Cell Acute Lymphoblastic Leukemia (B-ALL) Reveals Correlation between Leukemia Cell State, Genetic Alterations and Clinical Outcome

2023· article· en· W4389248130 on OpenAlexaff
Ilaria Iacobucci, Andy G.X. Zeng, Qingsong Gao, Laura Garcia Prat, Pradyumna Baviskar, Sayyam Shah, Alexander Murison, Véronique Voisin, Colin Bailey, Matthew Lear, Anjali S. Advani, Selina M. Luger, Elisabeth Paietta, Wendy Stock, John E. Dick, Charles G. Mullighan

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsBiologyTranscriptomeGeneLeukemiaGeneticsGene expressionCell cycleB cellGene expression profilingMolecular biologyCancer research

Abstract

fetched live from OpenAlex

I.I., A.G.X.Z, Q.G., L.G.P.: co-first authors; J.E.D., C.G.M.: co-senior authors Introduction: Genomic analyses of bulk ALL samples have improved our understanding of the genetic basis and risk stratification of B-ALL, but do not directly examine intratumor heterogeneity or enable inference of leukemia developmental state and cell of origin. Methods: We profiled 89 B-ALL samples by single-cell RNA-seq (scRNA-seq) (10X Genomics 5'v2) and compared them to a scRNA-seq reference map of normal human B-cell development. Results: Analysis of heterogeneity of inferred DNA copy number alterations at single cell level showed that aneuploid ALL with near haploidy and hyperdiploid harbor chromosomal losses or gains in all blasts, consistent with early, synchronous origin rather than sequential accumulation. A subset of TCF3::PBX1 samples harbored clones with progressive overexpression of genes surrounding PBX1 which scWGS confirmed caused by accumulation of DNA gains. Extensive intra-sample heterogeneity was observed by non-negative matrix factorization and driven by five consensus gene expression signatures: cell cycle (S; G2/M), metabolism, differentiation and inflammation. Signature composition refined leukemic subtyping; for example, within DUX4-r B-ALL two groups were discerned: one with higher inflammation score, expression of stem cell genes and worse outcome and one with lower inflammation score and expression of Pro-B related genes. To understand variation in developmental states among B-ALL blasts, we first developed an atlas of human B cell development. Marker genes elucidated from bulk RNA-seq on purified human HSC, MPP, LMPP, MLP, CLP, Pre-Pro-B, Pro-B, Pre-B, and B populations guided the development of a new scRNA-seq atlas of human B cell development comprising 130,085 cells spanning 90 fetal, pediatric, and adult samples from 8 studies (Fig 1A). Unexpectedly, we found that human CLPs retain transcriptional programs governed by CEBPA; in vitro and in vivo functional assays validated the capacity of CLPs for extensive myeloid differentiation prior to lineage restriction at the Pro-B stage. We next mapped our 89 B-ALL sc samples to precise cellular states along B cell development and clustered samples by leukemia cell composition. As expected, most samples exhibited similarity of GEP to that of pro-B cells, and this was most pronounced among hyperdiploid samples. High pre-B abundance was observed in MEF2D-r and TCF3::PBX1, while an HSC/MPP/LMPP enriched cluster encompassed ZNF384-r and a subset of DUX4-r B-ALL. Notably, one ZNF384-r B-ALL patient with LMPP involvement at diagnosis retained these LMPP-like cells at relapse despite a lineage switch to AML. Finally, we identified a group of patients with high early lymphoid (MLP, CLP, Pre-Pro-B) abundance representing a subset of Ph+ and KMT2A-r samples (Fig. 1B). We next utilized marker genes from each B-ALL cell state to estimate their relative abundance within a bulk RNA-seq cohort of 2046 B-ALL patients. In addition to validating these associations between genomic class and leukemia cell state, we identified age-dependent patterns of B-ALL state involvement wherein early lymphoid involvement is highest in infancy and adulthood while Pro-B involvement is highest in childhood. In childhood, high-risk disease is associated with higher early lymphoid ( P=4.9e-12) and lower Pro-B ( P=0.0085) abundance. Further, patients with residual disease (RD) levels above 1% are enriched for higher upfront early lymphoid abundance ( P=1e-7) and lower Pro-B ( P=4.1e-5) and Pre-B ( P=2.2e-11) abundance compared to patients with RD < 0.01%. Finally, B-ALL cell state improved resolution of previously reported transcriptional heterogeneity within defined genomic classes. Early lymphoid abundance discerns between two subtypes within Ph+ (Kim Nat Gen 2023) with AUC=0.953 ( P=2.4e-9), as well as two subtypes within KMT2A-r (Brady Nat Gen 2022) with AUC=0.996 ( P=1.1e-6). Notably we find that KMT2A::AFF1 fusions produce early lymphoid-enriched disease compared to KMT2A::MLLT3 ( P=0.0024) and KMT2A::MLLT10 ( P=0.0037), wherein the latter two fusions exhibit Pre-B enrichment ( P=0.025 and P=0.0037, respectively). Conclusions: Understanding variation in transcriptional programs and developmental states of B-ALL blasts by sc transcriptome refines existing clinical and genomic classifications and provides novel prognostic markers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.274
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBloodSame topicCancer Genomics and DiagnosticsFrench-language works237,207