Hematology (Amsterdam, Netherlands) · 2026
Single-cell and bulk transcriptomic integration identifies a high-CNV, dark-zone-enriched malignant cell state associated with adverse prognosis in GCB-DLBCL.
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Wang Jianing, Xiang Xiuying, He Xiaomei, Pan Yun, Jiang Zewei, Tan Jiaxiong
Аннотация
BACKGROUND: Germinal centre B-cell-like diffuse large B-cell lymphoma (GCB-DLBCL) generally has a better prognosis than activated B-cell-like DLBCL, yet a clinically significant subset of patients still develops aggressive disease, suggesting marked malignant cellular heterogeneity within this subtype. This study aimed to characterise malignant cell states in GCB-DLBCL and assess their prognostic relevance.
METHODS: Single-cell transcriptomic data were integrated with inferred copy-number variation (CNV) analysis to characterise malignant B-cell states. Regulatory programmes, functional features, and genetic associations were investigated using regulon analysis, functional profiling, and scPAGWAS. Single-cell-derived signatures were projected onto three independent bulk transcriptomic cohorts by deconvolution to evaluate clinical relevance. Integrative analyses were then performed to identify candidate molecular features associated with the M-C2 state.
RESULTS: Marked malignant-cell heterogeneity was identified. A high-CNV compartment displayed dark-zone-like transcriptional programmes, enrichment of proliferation- and survival-associated features, and reduced antigen-presentation capacity. Subclustering resolved three malignant states, among which M-C2 showed the highest inferred CNV burden and a distinct germinal-centre regulatory programme marked by enhanced BCL6, TCF3, and PAX5 activity. M-C2 was enriched for DLBCL susceptibility-associated signals, and its higher abundance was consistently associated with inferior overall survival across independent bulk cohorts. Integrative prioritisation identified an eight-gene M-C2-associated panel comprising IRF4, AKT1S1, PIEZO1, POLR1A, EML6, TTN, FCRL5, and IGHG2. An exploratory prognostic model integrating molecular and clinical features further supported the potential predictive value of this programme.
CONCLUSIONS: This study identifies a high-CNV, dark-zone-enriched malignant cell state within GCB-DLBCL, represented by the M-C2 subpopulation, associated with impaired antigen presentation and adverse prognosis. This framework improves understanding of malignant heterogeneity and warrants further validation for risk stratification.
METHODS: Single-cell transcriptomic data were integrated with inferred copy-number variation (CNV) analysis to characterise malignant B-cell states. Regulatory programmes, functional features, and genetic associations were investigated using regulon analysis, functional profiling, and scPAGWAS. Single-cell-derived signatures were projected onto three independent bulk transcriptomic cohorts by deconvolution to evaluate clinical relevance. Integrative analyses were then performed to identify candidate molecular features associated with the M-C2 state.
RESULTS: Marked malignant-cell heterogeneity was identified. A high-CNV compartment displayed dark-zone-like transcriptional programmes, enrichment of proliferation- and survival-associated features, and reduced antigen-presentation capacity. Subclustering resolved three malignant states, among which M-C2 showed the highest inferred CNV burden and a distinct germinal-centre regulatory programme marked by enhanced BCL6, TCF3, and PAX5 activity. M-C2 was enriched for DLBCL susceptibility-associated signals, and its higher abundance was consistently associated with inferior overall survival across independent bulk cohorts. Integrative prioritisation identified an eight-gene M-C2-associated panel comprising IRF4, AKT1S1, PIEZO1, POLR1A, EML6, TTN, FCRL5, and IGHG2. An exploratory prognostic model integrating molecular and clinical features further supported the potential predictive value of this programme.
CONCLUSIONS: This study identifies a high-CNV, dark-zone-enriched malignant cell state within GCB-DLBCL, represented by the M-C2 subpopulation, associated with impaired antigen presentation and adverse prognosis. This framework improves understanding of malignant heterogeneity and warrants further validation for risk stratification.