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10780432ccr120596-sup-tab1.pdf (39.48 kB)

Supplementary Table 1 from Gene Expression Signature–Based Prognostic Risk Score in Patients with Primary Central Nervous System Lymphoma

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posted on 2023-03-31, 17:01 authored by Atsushi Kawaguchi, Yasuo Iwadate, Yoshihiro Komohara, Masakazu Sano, Koji Kajiwara, Naoki Yajima, Naoto Tsuchiya, Jumpei Homma, Hiroshi Aoki, Tsutomu Kobayashi, Yuko Sakai, Hiroaki Hondoh, Yukihiko Fujii, Tatsuyuki Kakuma, Ryuya Yamanaka

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ARTICLE ABSTRACT

Purpose: Better understanding of the underlying biology of primary central nervous system lymphomas (PCNSL) is critical for the development of early detection strategies, molecular markers, and new therapeutics. This study aimed to define genes associated with survival of patients with PCNSL.Experimental Design: Expression profiling was conducted on 32 PCNSLs. A gene classifier was developed using the random survival forests model. On the basis of this, prognosis prediction score (PPS) using immunohistochemical analysis is also developed and validated in another data set with 43 PCNSLs.Results: We identified 23 genes in which expressions were strongly and consistently related to patient survival. A PPS was developed for overall survival (OS) using a univariate Cox model. Survival analyses using the selected 23-gene classifiers revealed a prognostic value for high-dose methotrexate (HD-MTX) and HD-MTX–containing polychemotherapy regimen–treated patients. Patients predicted to have good outcomes by the PPS showed significantly longer survival than those with poor predicted outcomes (P < 0.0001). PPS using immunohistochemical analysis is also significant in test (P = 0.0004) and validation data set (P = 0.0281). The gene-based predictor was an independent prognostic factor in a multivariate model that included clinical risk stratification (P < 0.0001). Among the genes, BRCA1 protein expressions were most strongly associated with patient survival.Conclusion: We have identified gene expression signatures that can accurately predict survival in patients with PCNSL. These predictive genes should be useful as molecular biomarkers and they could provide novel targets for therapeutic interventions. Clin Cancer Res; 18(20); 5672–81. ©2012 AACR.

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