Stability-based methods have been successfully applied in functional genomics to the analysis of the reliability of clusterings characterised by a relatively low number of examples and clusters. The application of these methods to the validation of gene clusters discovered in biomolecular data may lead to computational problems due to the large amount of possible clusters involved. To address this problem, we present a stability-based algorithm to discover significant clusters in hierarchical clusterings with a large number of examples and clusters. The reliability of clusters of genes discovered in gene expression data of patients affected by human myeloid leukaemia is analysed through the proposed algorithm, and their relationships with specific biological processes are tested by means of Gene Ontology-based functional enrichment methods.

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Anti-tumor therapies that seek to exploit and redirect the cytotoxic killing and effector potential of autologous or syngeneic T cells have shown extraordinary promise and efficacy in certain clinical settings. Such cells, when engineered to express synthetic chimeric antigen receptors (CARs) acquire novel targeting and activation properties which are governed and orchestrated by, typically, antibody fragments specific for a tumor antigen of interest. However, it is becoming increasingly apparent that not all antibodies are equal in this regard, with a growing appreciation that ‘optimal’ CAR performance requires a consideration of multiple structural and contextual parameters. Thus, antibodies raised by classical approaches and intended for other applications often perform poorly or not at all when repurposed as CARs. With this in mind, we have explored the potential of an in vitro phenotypic CAR library discovery approach that tightly associates antibody-driven bridging of tumor and effector T cells with an informative and functionally relevant CAR activation reporter signal. Critically, we demonstrate the utility of this enrichment methodology for ‘real world’ de novo discovery by isolating several novel anti-mesothelin CAR-active scFv candidates.