Precision medicine is about matching the right drugs to the right patients. Although this approach is technology agnostic, in cancer there is a tendency to make precision medicine synonymous with genomics. However, genome-based cancer therapeutic matching is limited by incomplete biological understanding of the relationship between phenotype and cancer genotype. This limitation can be addressed by functional testing of live patient tumour cells exposed to potential therapies. Recently, several ‘next-generation’ functional diagnostic technologies have been reported, including novel methods for tumour manipulation, molecularly precise assays of tumour responses and device-based in situ approaches; these address the limitations of the older generation of chemosensitivity tests. The promise of these new technologies suggests a future diagnostic strategy that integrates functional testing with next-generation sequencing and immunoprofiling to precisely match combination therapies to individual cancer patients.

During immune challenge, T lymphocytes engage pathways of anabolic metabolism to support clonal expansion and the development of effector functions. Here we report a critical role for the non-essential amino acid serine in effector T cell responses. Upon activation, T cells upregulate enzymes of the serine, glycine, one-carbon (SGOC) metabolic network, and rapidly increase processing of serine into one-carbon metabolism. We show that extracellular serine is required for optimal T cell expansion even in glucose concentrations sufficient to support T cell activation, bioenergetics, and effector function. Restricting dietary serine impairs pathogen-driven expansion of T cells in vivo, without affecting overall immune cell homeostasis. Mechanistically, serine supplies glycine and one-carbon units for de novo nucleotide biosynthesis in proliferating T cells, and one-carbon units from formate can rescue T cells from serine deprivation. Our data implicate serine as a key immunometabolite that directly modulates adaptive immunity by controlling T cell proliferative capacity.

The enzyme serine hydroxymethyltransferse (SHMT) converts serine into glycine and a tetrahydrofolate-bound one-carbon unit. Folate one-carbon units support purine and thymidine synthesis, and thus cell growth. Mammals have both cytosolic SHMT1 and mitochondrial SHMT2, with the mitochondrial isozyme strongly up-regulated in cancer. Here we show genetically that dual SHMT1/2 knockout blocks HCT-116 colon cancer tumor xenograft formation. Building from a pyrazolopyran scaffold that inhibits plant SHMT, we identify small-molecule dual inhibitors of human SHMT1/2 (biochemical IC ∼ 10 nM). Metabolomics and isotope tracer studies demonstrate effective cellular target engagement. A cancer cell-line screen revealed that B-cell lines are particularly sensitive to SHMT inhibition. The one-carbon donor formate generally rescues cells from SHMT inhibition, but paradoxically increases the inhibitor's cytotoxicity in diffuse large B-cell lymphoma (DLBCL). We show that this effect is rooted in defective glycine uptake in DLBCL cell lines, rendering them uniquely dependent upon SHMT enzymatic activity to meet glycine demand. Thus, defective glycine import is a targetable metabolic deficiency of DLBCL.

To evaluate the specificity of long dsRNAs used in high-throughput RNA interference (RNAi) screens performed at the Drosophila RNAi Screening Center (DRSC), we performed a global analysis of their activity in 30 genome-wide screens completed at our facility. Notably, our analysis predicts that dsRNAs containing > or = 19-nucleotide perfect matches identified in silico to unintended targets may contribute to a significant false positive error rate arising from off-target effects. We confirmed experimentally that such sequences in dsRNAs lead to false positives and to efficient knockdown of a cross-hybridizing transcript, raising a cautionary note about interpreting results based on the use of a single dsRNA per gene. Although a full appreciation of all causes of false positive errors remains to be determined, we suggest simple guidelines to help ensure high-quality information from RNAi high-throughput screens.