Abstract
Simple Summary Tribbles proteins possess the structure of protein kinases but function by forming protein complexes rather than phosphorylating substrates. Here we review the structure-function relationship of TRIB1 in cancers. Of the Tribbles proteins, TRIB1 is currently the most well characterised structurally. TRIB1 has different states that could potentially be targeted by small-molecule inhibitors and well-established relevance in acute myeloid leukaemia through degradation of transcription factors. Less is understood about the role of TRIB1 in solid tumours. Further research is required to fully realise the potential of TRIB1 as either a direct target of small-molecule drugs or a biomarker of treatment response across diverse cancer types. The Tribbles family of proteins-comprising TRIB1, TRIB2, TRIB3 and more distantly related STK40-play important, but distinct, roles in differentiation, development and oncogenesis. Of the four Tribbles proteins, TRIB1 has been most well characterised structurally and plays roles in diverse cancer types. The most well-understood role of TRIB1 is in acute myeloid leukaemia, where it can regulate C/EBP transcription factors and kinase pathways. Structure-function studies have uncovered conformational switching of TRIB1 from an inactive to an active state when it binds to C/EBP alpha. This conformational switching is centred on the active site of TRIB1, which appears to be accessible to small-molecule inhibitors in spite of its inability to bind ATP. Beyond myeloid neoplasms, TRIB1 plays diverse roles in signalling pathways with well-established roles in tumour progression. Thus, TRIB1 can affect both development and chemoresistance in leukaemia; glioma; and breast, lung and prostate cancers. The pervasive roles of TRIB1 and other Tribbles proteins across breast, prostate, lung and other cancer types, combined with small-molecule susceptibility shown by mechanistic studies, suggests an exciting potential for Tribbles as direct targets of small molecules or biomarkers to predict treatment response.