丝氨酸蛋白酶抑制剂 Kazal 1 型，一种用于肝细胞癌早期检测、靶向及免疫检查点阻断治疗反应预测的潜在生物标志物

We aimed to characterize serine protease inhibitor Kazal type 1 ( SPINK1 ) as a gene signature for the early diagnosis, molecular targeting, and prediction of immune checkpoint blockade (ICB) treatment response of hepatocellular carcinoma (HCC).

The transcriptomics, proteomics, and phenotypic analyses were performed separately or in combination.

We obtained the following findings on SPINK1 . Firstly, in the transcriptomic training dataset, which included 279 stage I and II tumor samples (out of 1,884 stage I-IV HCC specimens) and 259 normal samples, significantly higher area under curve (AUC) values and increased integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were demonstrated for HCC discrimination in SPINK1 -associated models compared with those of alpha-fetoprotein (AFP). The calibration of both SPINK1 -related curves fitted significantly better than that of AFP. In the two independent transcriptomic validation datasets, which included 201, 103 stage I-II tumor and 192, 169 paired non-tumor specimens, respectively, the obtained results were consistent with the above-described findings. In the proteomic training dataset, which included 98 stage I and II tumor and 165 normal tissue samples, the analyses also revealed better AUCs and increased IDI and NRI in the aforementioned SPINK1 -associated settings. A moderate calibration was shown for both SPINK1 -associated models relative to the poor results of AFP. Secondly, in the in vitro and/or in vivo murine models, the wet-lab experiments demonstrated that SPINK1 promoted the proliferation, clonal formation, migration, chemoresistance, anti-apoptosis, tumorigenesis, and metastasis of HCC cells, while the anti- SPINK1 antibody inhibited the growth of the cells, suggesting that SPINK1 has "tumor marker" and "targetable" characteristics in the management of HCC. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that SPINK1 was engaged in immunity-related pathways, including T-cell activation. Thirdly, in the transcriptomic analyses of the 368 HCC specimens from The Cancer Genome Atlas (TCGA) cohort, the high abundance of SPINK1 was positively correlated with the high levels of activated tumor-infiltrating CD4 + and CD8 + T lymphocytes and dendritic and natural killer cells, while there were also positive correlations between SPINK1 and immune checkpoints, including PD-1, LAG-3, TIM-3, TIGIT, HAVCR2, and CTLA-4. The ESTIMATE algorithm calculated positive correlations between SPINK1 and the immune and ESTIMATE scores, suggesting a close correlation between SPINK1 and the immunogenic microenvironment within HCC tissues, which may possibly help in predicting the response of patients to ICB therapy.

SPINK1 could be a potential biomarker for the early detection, targeted therapy, and prediction of ICB treatment response in the management of HCC.