Interferon-inducible protein 16 may be a biomarker and prognostic factor in renal cell carcinoma by bioinformatics analysis

SLFN11 promotes clear cell renal cell carcinoma progression via the PI3K/AKT signaling pathway

SLFN11 is abnormally expressed and associated with survival outcomes in various human cancers. However, the role of SLFN11 in clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to investigate the clinical value and potential functions of SLFN11 in ccRCC. Comprehensive bioinformatics analyses were performed using online databases. Quantitative real-time PCR (qPCR) and western blotting were used to validate the expression data. CCK8, flow cytometry analysis, and EdU staining were performed to determine the level of cell proliferation. Flow cytometry analysis was also used to detect cell apoptosis. Wound-healing assay and Transwell assays were performed to assess cell migration and invasion capability, respectively. SLFN11 was overexpressed and was an independent prognostic factor in ccRCC. SLFN11 knockdown inhibited cell proliferation, migration, and invasion and promoted apoptosis. Functional and pathway enrichment analyses suggested that SLFN11 may have an impact on tumorigenesis in ccRCC through regulation of the inflammatory response, the PI3K/AKT signaling pathway and other effectors. Furthermore, SLFN11 knockdown inhibited the phosphorylation of the PI3K/AKT signaling pathway and could be activated by 740 Y-P. Finally, we demonstrated that miR-183 may specifically target SLFN11, and miR-183 expression was correlated with predicted survival. SLFN11 may play a critical role in ccRCC progression and may serve as a novel prognostic biomarker in ccRCC.

Single-cell transcriptomic analysis deciphers key transitional signatures associated with oncogenic evolution in human intramucosal oesophageal squamous cell carcinoma

BACKGROUND AND AIMS

The early diagnosis and intervention of oesophageal squamous cell carcinoma (ESCC) are particularly important because of the lack of effective therapies and poor prognosis. Comprehensive research on early ESCC at the single-cell level is rare due to the need for fresh and high-quality specimens obtained from ESD. This study aims to systematically describe the cellular atlas of human intramucosal ESCC.

METHODS

Five paired samples of intramucosal ESCC, para-ESCC oesophageal tissues from endoscopically resected specimens and peripheral blood mononuclear cells were adopted for scRNA-seq analysis. Computational pipeline scMetabolism was applied to quantify the metabolic diversity of single cells.

RESULTS

A total of 164 715 cells were profiled. Epithelial cells exhibited high intra-tumoural heterogeneity and two evolutionary trajectories during ESCC tumorigenesis initiated from proliferative cells, and then through an intermediate state, to two different terminal states of normally differentiated epithelial cells or malignant cells, respectively. The abundance of CD8+ TEX s, Tregs and PD1+ CD4+ T cells suggested an exhausted and suppressive immune microenvironment. Several genes in immune cells, such as CXCL13, CXCR5 and PADI4, were identified as new biomarkers for poor prognosis. A new subcluster of malignant cells associated with metastasis and angiogenesis that appeared at an early stage compared with progressive ESCC was also identified in this study. Intercellular interaction analysis based on ligand-receptor pairs revealed the subcluster of malignant cells interacting with CAFs via the MDK-NCL pathway, which was verified by cell proliferation assay and IHC. This indicates that the interaction may be an important hallmark in the early change of tumour microenvironment and serves as a sign of CAF activation to stimulate downstream pathways for facilitating tumour invasion.

CONCLUSION

This study demonstrates the changes of cell subsets and transcriptional levels in human intramucosal ESCC, which may provide unique insights into the development of novel biomarkers and potential intervention strategies.

DNA and RNA Binding Proteins: From Motifs to Roles in Cancer

DNA and RNA binding proteins (DRBPs) are a broad class of molecules that regulate numerous cellular processes across all living organisms, creating intricate dynamic multilevel networks to control nucleotide metabolism and gene expression. These interactions are highly regulated, and dysregulation contributes to the development of a variety of diseases, including cancer. An increasing number of proteins with DNA and/or RNA binding activities have been identified in recent years, and it is important to understand how their activities are related to the molecular mechanisms of cancer. In addition, many of these proteins have overlapping functions, and it is therefore essential to analyze not only the loss of function of individual factors, but also to group abnormalities into specific types of activities in regard to particular cancer types. In this review, we summarize the classes of DNA-binding, RNA-binding, and DRBPs, drawing particular attention to the similarities and differences between these protein classes. We also perform a cross-search analysis of relevant protein databases, together with our own pipeline, to identify DRBPs involved in cancer. We discuss the most common DRBPs and how they are related to specific cancers, reviewing their biochemical, molecular biological, and cellular properties to highlight their functions and potential as targets for treatment.

DLK2 Acts as a Potential Prognostic Biomarker for Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis

Clear cell renal cell carcinoma (ccRCC) is the most common RCC subtype with a high mortality. It has been reported that delta-like 1 homologue (DLK1) participates in the tumor microenvironmental remodeling of ccRCC, but the relationship between delta-like 2 homologue (DLK2, a DLK1 homologue) and ccRCC is still unclear. Thus, this study aims to investigate the role of DLK2 in the biological function and disease prognosis of ccRCC using bioinformatics analysis. The TNMplot database showed that DLK2 was upregulated in ccRCC tissues. From the UALCAN analysis, the overexpression of DLK2 was associated with advanced stage and high grade in ccRCC. Moreover, the Kaplan-Meier plotter (KM Plotter) database showed that DLK2 upregulation was associated with poor survival outcome in ccRCC. By the LinkedOmics analysis, DLK2 signaling may participated in the modulation of ccRCC extracellular matrix (ECM), cell metabolism, ribosome biogenesis, TGF-β signaling and Notch pathway. Besides, Tumor Immune Estimation Resource (TIMER) analysis showed that the macrophage and CD8⁺ T cell infiltrations were associated with good prognosis in ccRCC patients. Finally, DLK2 overexpression was associated with the reduced macrophage recruitments and the M1–M2 polarization of macrophage in ccRCC tissues. Together, DLK2 may acts as a novel biomarker, even therapeutic target in ccRCC. However, this study lacks experimental validation, and further studies are required to support this viewpoint.