Leich, E. and Brodtkorb, Marianne and Schmidt, T. and Altenbuchinger, M. and Lingjaerde, Ole Christian and Lockmer, S. and Holte, H. and Nedeva, T. and Grieb, T. and Sander, B. and Sundstroem, C. and Spang, R. and Kimby, E. and Rosenwald, A. (2023) Gene expression and copy number profiling of follicular lymphoma biopsies from patients treated with first-line rituximab without chemotherapy. LEUKEMIA & LYMPHOMA, 64 (12). pp. 1927-1937. ISSN 1042-8194, 1029-2403
Full text not available from this repository. (Request a copy)Abstract
The Nordic Lymphoma Study Group has performed two randomized clinical trials with chemotherapy-free first-line treatment (rituximab +/- interferon) in follicular lymphoma (FL), with 73% of patients alive and 38% without any need of chemotherapy after 10.6 years median follow-up. In order to identify predictive markers, that may also serve as therapeutic targets, gene expression- and copy number profiles were obtained from 97 FL patients using whole genome microarrays. Copy number alterations (CNAs) were identified, e.g. by GISTIC. Cox Lasso Regression and Lasso logistic regression were used to determine molecular features predictive of time to next therapy (TTNT). A few molecular changes were associated with TTNT (e.g. increased expression of INPP5B, gains in 12q23/q24), but were not significant after adjusting for multiple testing. Our findings suggest that there are no strong determinants of patient outcome with respect to GE data and CNAs in FL patients treated with a chemotherapy-free regimen (i.e. rituximab +/- interferon).
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | HIGH-RISK; TUMOR MICROENVIRONMENT; REGULARIZATION PATHS; T-CELLS; SURVIVAL; CYCLOPHOSPHAMIDE; TRANSFORMATION; PATHOGENESIS; VINCRISTINE; INTEGRATION; Follicular lymphoma; whole genome microarrays; gene expression profiling; copy number profiling; cox models |
| Subjects: | 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang) Informatics and Data Science > Department Computational Life Science > Lehrstuhl für Statistische Bioinformatik (Prof. Spang) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 15 May 2024 04:31 |
| Last Modified: | 15 May 2024 04:31 |
| URI: | https://pred.uni-regensburg.de/id/eprint/60545 |
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