Genetic and transcriptomic analyses of diffuse large B-cell lymphoma patients with poor outcomes within two years of diagnosis.

Despite the improvements in clinical outcomes for DLBCL, a significant proportion of patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. To further elucidate the underlying mechanism of R/R disease and to develop methods for identifying patients at risk of early disease progression, we integrated clinical, genetic and transcriptomic data derived from 2805 R-CHOP-treated patients from seven independent cohorts. Among these, 887 patients exhibited R/R disease within two years (poor outcome), and 1918 patients remained in remission at two years (good outcome). Our analysis identified four preferentially mutated genes (TP53, MYD88, SPEN, MYC) in the untreated (diagnostic) tumor samples from patients with poor outcomes. Furthermore, transcriptomic analysis revealed a distinct gene expression pattern linked to poor outcomes, affecting pathways involved in cell adhesion/migration, T-cell activation/regulation, PI3K, and NF-κB signaling. Moreover, we developed and validated a 24-gene expression score as an independent prognostic predictor for treatment outcomes. This score also demonstrated efficacy in further stratifying high-risk patients when integrated with existing genetic or cell-of-origin subtypes, including the unclassified cases in these models. Finally, based on these findings, we developed an online analysis tool ( https://lymphprog.serve.scilifelab.se/app/lymphprog ) that can be used for prognostic prediction for DLBCL patients.

Ex vivo evaluation of tumor cell specific drug responses in malignant pleural effusions.

The effect of chemotherapy may be improved by combining the most effective drugs based on testing the sensitivity of the individual tumor ex vivo. Such estimations of tumor cells from effusions have so far not been implemented in the clinical routine as a basis for individualized choice of therapy. One obstacle for such analyses is the admixture of benign cells that might obscure the results. In this paper we test and compare two ways of performing the analysis specifically on tumor cells. First we enrich the tumor cells, using antibody labeled magnetic separation, and measure the effects of subsequent drug exposure with the metabolic activity assays WST-1 and alamar blue. The second way of estimating drug effects specifically on tumor cells employs multi parameter flow cytometry, measuring apoptosis with the propidium iodide / AnnexinV technique and, particularly for pemetrexed, possible effects on cell cycle progression in immunologically identified tumor cells. The two techniques produce similar results, indicating a possible use in personalized medicine. The possible predictive role of the analysis remains to be shown.