Functional dissection of SPOP on the amino acid level reveals a comprehensive functional landscape of variants during tumorigenesis

Numerous proteins display pleiotropic functions in different clinical contexts. However, molecular mechanism underlying such effects is rarely understood. Speckle-type POZ protein (SPOP) is a typical example, exhibiting tumor-suppressing or -promoting effects in different tumor types in accordance with different amino acid changes; specifically, two distinct sets of variants in SPOP are commonly found in subsets of prostate cancer and endometrial cancer patients. To comprehensively characterize the functional landscape of SPOP alteration, we performed a deep mutational screening (DMS), elucidating the functionality of 7,933 out of 8,228 possible single amino acid changes (96.4% coverage). Leveraging the observation that overexpression of human SPOP leads to yeast growth arrest, we assessed the functionality of each variant using a yeast proliferation assay. In addition, our approach combined long-read and short-read sequencing. Finally, our DMS model enables a clear distinction of likely-loss-of-function (LoF) variants that are enriched in prostate cancers and reveals their differential characteristics in both protein structure and genetic assessments. These results demonstrate the utility of our approach in high resolution mapping and amino-acid-level interpretation of protein function. Significance statementGenetic mutations often play different roles in cancer, driving or suppressing tumor growth depending on their molecular context. The protein SPOP is a striking example that acts as either a tumor-suppressor or oncogene depending on the specific mutation and tissue. However, understanding how thousands of possible mutations alter its function has been a major challenge. Here, we applied deep mutational scanning to experimentally measure the functional effects of nearly every possible amino acid change in SPOP. This work provides the first comprehensive functional map of SPOP variants, not only advancing basic knowledge of cancer biology but also establishing a framework for interpreting patient mutations in precision medicine.