Integrated genomic and tumor microenvironment subtyping refines risk stratification in primary central nervous system lymphoma
Year: 2025
Type: conference-abstract
Abstract: Purpose: Primary CNS lymphoma (PCNSL) remains a therapeutic challenge due to limited precision medicine approaches and suboptimal risk stratification. We aimed to establish an integrated classification framework by combining genomic and tumor microenvironment (TME) profiling. Experimental Design: Whole-genome sequencing (WGS) and multiplex immunofluorescence (mIF) were performed on 68 treatment-naïve PCNSL patients. Unsupervised clustering of 271 genomic features (mutations, structural variants, and copy number variations) defined molecular subtypes. TME classification leveraged CD8⁺T/M2 macrophage ratios. Results: We identified four genomic subtypes with distinct driver alterations: C1 (DNA repair defects: BRIP1/MTAP mutations and 3p/16q amps), C2 (apoptotic dysregulation: BCL2/IRF4 mutations), C3 (BCR- MAPK hyperactivation: CD79A/CARD11/EGFR mutations), and C4 (epigenetic dysregulation and mismatch repair deficiency: KMT2A/TET2/MSH6 mutations). These subtypes stratified overall survival (OS, p=0.02), with C4 exhibiting the poorest median OS (26 months). TME classification by CD8⁺T/M2 ratio revealed three groups: High (>1.5), Intermediate (0.8–1.5), and Low (<0.8). Unexpectedly, the Intermediate group showed the worst outcomes (5-year OS: 10% vs. 75% in High and 43% in Low; p=0.005). Integration exposed a lethal C4/Intermediate-TME subgroup (n=6, 9.8%) with catastrophic median OS of 3.0 months (HR=7.24, p=0.006). Multivariate analysis confirmed both systems as independent prognostic factors. Nomograms incorporating genomic/TME subtypes, Han’s classification, and progression of disease within 24 months (POD24) achieved robust prediction (C-index >0.78). Conclusions: Our integrated classification reveals a high-risk biology in C4/Intermediate-TME PCNSL and provides a clinically deployable framework for risk-adapted therapy. The CD8⁺T/M2 ratio refines TME evaluation beyond conventional paradigms, enabling biomarker-driven trials.
Source: Blood
Authors: Xianggui Yuan, Qian Luo, Yurong Huang, Chaoyi Li, Teng Yu, Shanshan Guo, Qunyi Guo, Xueli Jin, Jiefeng Tong, Aiqi Zhao, Wen Lei, Xian Li, Baizhou Li, Shumei Wei, Wenbin Qian, Yun Liang
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4417009590
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