Proteome-Wide Analysis Reveals TFEB Targets for Establishment of a Prognostic Signature to Predict Clinical Outcomes of Colorectal Cancer

SIMPLE SUMMARY: Transcription factor EB (TFEB) is a master modulator of autophagy and lysosomal biogenesis. Dephosphorylation of TFEB at Ser142 and Ser138 determines its nuclear localization and transcriptional activity. The link between TFEB-associated genes and colorectal cancer (CRC) progression and prognosis remains unclear; thus, we performed data-independent acquisition (DIA)-based quantitative proteomics to systematically identify the targets of TFEB. Using stringent statistical criteria, 60 proteins associated with vesicular endocytic trafficking were identified as TFEB targets. Moreover, a prognosis-linked TFEB-related gene signature was developed, showing that patients with higher risk scores had higher epithelial–mesenchymal transition (EMT) scores with worse prognosis. Additionally, a nomogram was constructed by combining clinicopathological parameters and the gene signature to enhance the quantification capacity in risk assessment for individual patients. This research facilitates further mechanistic studies of TFEB, and the TFEB gene signature-based model may provide important information for assisting clinicians to predict CRC patient prognosis. ABSTRACT: Dephosphorylation of transcription factor EB (TFEB) at Ser142 and Ser138 determines its nuclear localization and transcriptional activity. The link between TFEB-associated genes and colorectal cancer (CRC) progression and prognosis remains unclear. To systematically identify the targets of TFEB, we performed data-independent acquisition (DIA)-based quantitative proteomics to compare global protein changes in wild-type (WT) DLD1 cells and TFEB(WT)- or TFEB(S142A/S138A) (activated status)-expressing DLD1 cells. A total of 6048 proteins were identified and quantified in three independent experiments. The differentially expressed proteins in TFEB(S142A/S138A) versus TFEB(WT) and TFEB(WT) versus control groups were compared, and 60 proteins were identified as products of TFEB transcriptional regulation. These proteins were significantly associated with vesicular endocytic trafficking, the HIF-1 signaling pathway, and metabolic processes. Furthermore, we generated a TFEB-associated gene signature using a univariate and LASSO Cox regression model to screen robust prognostic markers. An eight-gene signature (PLSCR3, SERPINA1, ATP6V1C2, TIMP1, SORT1, MAP2, KDM4B, and DDAH2) was identified. According to the signature, patients were assigned to high-risk and low-risk groups. Higher risk scores meant worse overall survival and higher epithelial–mesenchymal transition (EMT) scores. Additionally, as per the clinicopathological parameters and gene signature, a nomogram was constructed that was utilized to enhance the quantification capacity in risk assessment for individual patients. This research shows that TFEB directly mediates network effects in CRC, and the identified TFEB gene signature-based model may provide important information for the clinical judgment of prognosis.