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Updated: Dec 11, 2025

Author Spotlight: A Selective Luciferase-Based Assay for Monitoring ATG4B 27 Activity in Cells
Published on: June 30, 2023
S100A8 transported by SEC23A inhibits metastatic colonization via autocrine activation of autophagy
Zhiwei Sun1,2, Bin Zeng1,2, Doudou Liu1,2
1Institute of Life Sciences, Chongqing Medical University, Chongqing, China.
Abstract:
Metastasis is the main cause of failure of cancer treatment. Metastatic colonization is regarded the most rate-limiting step of metastasis and is subjected to regulation by a plethora of biological factors and processes. On one hand, regulation of metastatic colonization by autophagy appears to be stage- and context-dependent, whereas mechanistic characterization remains elusive. On the other hand, interactions between the tumor cells and their microenvironment in metastasis have long been appreciated, whether the secretome of tumor cells can effectively reshape the tumor microenvironment has not been elucidated mechanistically. In the present study, we have identified "SEC23A-S1008-BECLIN1-autophagy axis" in the autophagic regulation of metastatic colonization step, a mechanism that tumor cells can exploit autophagy to exert self-restrain for clonogenic proliferation before the favorable tumor microenvironment is established. Specifically, we employed a paired lung-derived oligometastatic cell line (OL) and the homologous polymetastatic cell line (POL) from human melanoma cell line M14 that differ in colonization efficiency. We show that S100A8 transported by SEC23A inhibits metastatic colonization via autocrine activation of autophagy. Furthermore, we verified the clinical relevance of our experimental findings by bioinformatics analysis of the expression of Sec23a and S100A8 and the clinical-pathological associations. We demonstrate that higher Sec23a and Atg5 expression levels appear to be protective factors and favorable diagnostic (TNM staging) and prognostic (overall survival) markers for skin cutaneous melanoma (SKCM) and colon adenocarcinoma (COAD) patients. And we confirm the bioinformatics analysis results with SKCM biopsy samples.
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