Second-line treatment for primary central nervous system lymphoma

Failure after first-line treatment was reported in 35–60% of immunocompetent patients with primary central nervous system lymphoma (PCNSL). There are currently no reports focusing on salvage therapy. This review analyses prognostic factors and the efficacy of salvage therapy by focusing on data from papers reporting results of first-line treatment in 355 cases. The study group consisted of 173 patients presenting treatment failure. The interval between failure and death (TTD) was compared for age at relapse (≤60 vs >60 years), type of failure (relapse vs progression), time to relapse (≤12 vs >12 months) and salvage treatment (yes vs no). Median TTD was similar in younger and older patients (P = 0.09). Relapsed patients had a longer TTD than patients with progressive disease (P = 0.002). Early relapse led to a shorter TTD than late relapse (P = 0.005). Median TTD was 14 months for patients who underwent salvage therapy and 2 months for untreated cases (P < 0.00001). A multivariate analysis showed an independent prognostic role for salvage therapy and time to relapse. Age and type of failure had no predictive value. Salvage therapy significantly improves outcome and, possibly, quality of life. As many different treatments were used conclusions cannot be made regarding an optimal treatment schedule. © 1999 Cancer Research Campaig

OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models