ITCH as a potential therapeutic target in human cancers.

The ITCH/AIP4 ubiquitin E3 ligase was discovered independently by two groups searching for atrophin-1 interacting proteins and studying the genetics of mouse coat color alteration, respectively. ITCH is classified as a NEDD4 family E3 ligase featured with the C-terminal HECT domain for E3 ligase function and WW domains for substrate recruiting. ITCH deficiency in the mouse causes severe multi-organ autoimmune disease. Its roles in maintaining a balanced immune response have been extensively characterized over the past two and a half decades. A wealth of reports demonstrate a multifaceted role of ITCH in human cancers. Given the versatility of ITCH in catalyzing both proteolytic and non-proteolytic ubiquitination of its over fifty substrates, ITCH's role in malignancies is believed to be context-dependent. In this review, we summarize the downstream substrates of ITCH, the functions of ITCH in both tumor cells and the immune system, as well as the implications of such functions in human cancers. Moreover, we describe the upstream regulatory mechanisms of ITCH and the efforts have been made to target ITCH using small molecule inhibitors.

Leveraging transcriptional dynamics to improve BRAF inhibitor responses in melanoma.

BACKGROUND: Melanoma is a heterogeneous tumour, but the impact of this heterogeneity upon therapeutic response is not well understood. METHODS: Single cell mRNA analysis was used to define the transcriptional heterogeneity of melanoma and its dynamic response to BRAF inhibitor therapy and treatment holidays. Discrete transcriptional states were defined in cell lines and melanoma patient specimens that predicted initial sensitivity to BRAF inhibition and the potential for effective re-challenge following resistance. A mathematical model was developed to maintain competition between the drug-sensitive and resistant states, which was validated in vivo. FINDINGS: Our analyses showed melanoma cell lines and patient specimens to be composed of >3 transcriptionally distinct states. The cell state composition was dynamically regulated in response to BRAF inhibitor therapy and drug holidays. Transcriptional state composition predicted for therapy response. The differences in fitness between the different transcriptional states were leveraged to develop a mathematical model that optimized therapy schedules to retain the drug sensitive population. In vivo validation demonstrated that the personalized adaptive dosing schedules outperformed continuous or fixed intermittent BRAF inhibitor schedules. INTERPRETATION: Our study provides the first evidence that transcriptional heterogeneity at the single cell level predicts for initial BRAF inhibitor sensitivity. We further demonstrate that manipulating transcriptional heterogeneity through personalized adaptive therapy schedules can delay the time to resistance. FUNDING: This work was funded by the National Institutes of Health. The funder played no role in assembly of the manuscript.