This study aims to evaluate the diagnostic value of human serum cysteine protease inhibitors (cystatin 4 [CST4]) in colorectal cancer (CRC) patients.
A total of 291 patients who were admitted to Zhuzhou Central Hospital for colonoscopy from January 2020 to December 2021 and met the inclusion criteria were selected. Serum samples of the patients were collected, and CST4 was detected by double-antibody sandwich enzyme-linked immunosorbent assay. Simultaneously, CEA and CA19-9 were detected, and the patients were divided into the CRC group, benign lesion group, and healthy control group. An attempt was made to construct a CRC prediction model including CST4 and draw a subject working characteristic curve as a diagnostic threshold for CRC prediction, and evaluate the diagnostic efficacy of the above indicators. At the same time, the expression analysis of CST4, CEA, and CA19-9 was verified by combining the data of CRC in the Tumor Genome Atlas (TCGA).
In this study, the levels of serum CST4, CEA, and CA19-9 in the CRC group were higher than those in the colorectal benign lesion group and healthy control group, with statistical significance (P < .001). The analysis results of the receiver operating characteristic curve showed that the area under the receiver operator characteristic curve (AUC) of CST4 was 0.7739, which was obviously larger than the AUC of CA19-9 and CEA. CRC data from the TCGA expression database showed that CST4 expression and CEA expression were higher in CRC patients than in normal samples. The combined model based on CST4 was successfully constructed, and the AUC for predicting the occurrence of CRC was 0.7851.
CST4 is a novel and improved diagnostic marker for CRC. The combined model based on CST4 has a certain potential value in terms of predicting the occurrence of intestinal cancer.

UNASSIGNED: Renal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumor heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal some potential tumor-specific markers, especially single-cell RNA sequencing (scRNA-seq).
UNASSIGNED: We performed an exploratory study on three pathological types of RCC with a small sample size. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on normal kidneys. Tumor characteristics were well identified by the comparison between different pathological types of RCC and normal kidneys at the scRNA level.
UNASSIGNED: Some new tumor-specific markers for different pathologic types of RCC, such as SPOCK1, PTGIS, REG1A, CP and SPAG4 were identified and validated. We also discovered that NDUFA4L2 both highly expressed in tumor cells of ccRCC and type 2 pRCC. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as POSTN and COL3A1. At last, by applying scRNA-seq results, the activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC.
UNASSIGNED: Taken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC.