Background: Exosome-mediated crosstalk between cancer cells and immune cells contributes to tumor growth. In this study, we investigated the mechanism underlying the exosome-mediated immune escape of colorectal cancer (CRC) cells from natural killer (NK) cells via the transfer of long noncoding RNAs (lncRNAs). Methods: An epithelial–mesenchymal transition (EMT) model of SW480 cells was established by transforming growth factor beta (TGF-β), followed by the assessment of the effect of EMT-derived exosomes (EMT-exo) on the functions of NK cells. RNA sequencing was performed to identify exosomal lncRNAs and target genes. The function of exosomal lncRNAs in tumor growth was further verified in vivo. Results: EMT-exo suppressed the proliferation, cytotoxicity, IFN-γ production, and perforin-1 and granzyme B secretion of NK cells. RNA sequencing revealed that SNHG10 expression was upregulated in EMT-exo compared with that in non-EMT-exo. Moreover, SNHG10 expression was upregulated in tumor tissues in CRC, which was associated with poor prognosis. Overexpression of SNHG10 in exosomes (oe-lnc-SNHG10 exo) significantly suppressed the viability and cytotoxicity of NK cells. Transcriptome sequencing of NK cells revealed that the expression levels of 114 genes were upregulated in the oe-lnc-SNHG10 exo group, including inhibin subunit beta C (INHBC), which was involved in the TGF-β signaling pathway. Si-INHBC treatment abrogated the effect of oe-lnc-SNHG10 exo on NK cells. oe-lnc-SNHG10 exo induced tumor growth and upregulated INHBC expression in mice and downregulated the expression of perforin, granzyme B, and NK1.1 in tumor tissues. Conclusions: The CRC cell-derived exosomal lncRNA SNHG10 suppresses the function of NK cells by upregulating INHBC expression. This study provides evidence that exosomal lncRNAs contribute to immune escape by inducing NK cell inhibition and proposes a potential treatment strategy for CRC.

Background: Colorectal cancer (CRC) is the second most common cancer in China. Autophagy plays an important role in the initiation and development of CRC. Here, we assessed the prognostic value and potential functions of autophagy-related genes (ARGs) using integrated analysis using single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA).Methods: We analyzed GEO-scRNA-seq data from GEO using various single-cell technologies, including cell clustering, and identification of differentially expressed genes (DEGs) in different cell types. Additionally, we performed gene set variation analysis (GSVA). The differentially expressed ARGs among different cell types and those between CRC and normal tissues were identified using TCGA-RNA-seq data, and the hub ARGs were screened. Finally, a prognostic model based on the hub ARGs was constructed and validated, and patients with CRC in TCGA datasets were divided into high- and low-risk groups based on their risk-score, and immune cells infiltration and drug sensitivity analyses between the two groups were performed.Results: We obtained single-cell expression profiles of 16,270 cells, and clustered them into seven types of cells. GSVA revealed that the DEGs among the seven types of cells were enriched in many signaling pathways associated with cancer development. We screened 55 differentially expressed ARGs, and identified 11 hub ARGs. Our prognostic model revealed that the 11 hub ARGs including CTSB, ITGA6, and S100A8, had a good predictive ability. Moreover, the immune cell infiltrations in CRC tissues were different between the two groups, and the hub ARGs were significantly correlated with the enrichment of immune cell infiltration. The drug sensitivity analysis revealed that the patients in the two risk groups had difference in their response to anti-cancer drugs.Conclusion: We developed a novel prognostic 11-hub ARG risk model, and these hubs may act as potential therapeutic targets for CRC.

Colorectal cancer (CRC) is the third most common of cancer-related deaths. Nucleolar protein 14 (NOP14) is known to play different roles in diverse types of cancers. However, little is known about its roles in CRC. Here, we assessed the prognostic value and functions of NOP14 in CRC using the data from The Cancer Genome Atlas (TCGA) and validated them based on the data from Gene Expression Omnibus (GEO). NOP14 mRNA and protein data in CRC was obtained from the TCGA, GEO, human protein atlas (HPA), and UALCAN databases. Survival and Cox regression analysis was performed to assess the prognostic value of NOP14 in CRC patients. Next, to evaluate the potential functions of NOP14, a protein–protein interaction (PPI) network was constructed and gene set enrichment analysis (GSEA) of differential expression genes (DEGs) associated with dysregulated NOP14 was performed. Finally, to investigate the immune response associated with NOP14 expression in CRC, we analyzed the correlations between immune cells infiltration and NOP14 expression level. Additionally, the correlations between immune molecule expression levels with NOP14 expression level were analyzed. High NOP14 mRNA expression was observed in CRC tissues based on the data from TCGA and GEO datasets. Similarly, high NOP14 protein levels were found in CRC tissues according to the immunohistochemical images from HPA. Interestingly, high NOP14 expression level was associated with an improved prognosis in CRC patients. Univariate and multivariate Cox regression analysis indicated that high NOP14 expression level was an independent protective factor for CRC patients. With the support of PPI network analysis, we found several risk genes interacted with NOP14. GSEA revealed that high NOP14 expression inhibited several signal pathways involved in tumor formation and development. Additionally, high NOP14 expression was positively associated with most kinds of immune cell infiltrations and the expression levels of some molecules related to immune activation. Altogether, these results indicated that high NOP14 expression leads to improved prognosis in CRC patients by inhibiting the signaling pathways involved in tumor growth and promoting the immune responses.

Graphene quantum dots (GQDs) have attracted significant attention in biomedicine, while extensive investigations have revealed a reverse regarding the potential biotoxicity of GQDs. In order to supplementing the understanding of the toxicity profile of GQDs, this study employs a molecular dynamics (MD) simulation approach to systematically investigate the potential toxicity of both GQDs and Graphene Oxide Quantum Dots (GOQDs) on the Anterior Gradient Homolog 2 (AGR2) protein, a key protein capable of protecting the intestine. We construct two typical simulation systems, in which an AGR2 protein is encircled by either GQDs or GOQDs. The MD results demonstrate that both GQDs and GOQDs can directly make contact with and even cover the active site (specifically, the Cys81 amino acid) of the AGR2 protein. This suggests that GQDs and GOQDs have the capability to inhibit or interfere with the normal biological interaction of the AGR2 active site with its target protein. Thus, GQDs and GOQDs exhibit potential detrimental effects on the AGR2 protein. Detailed analyses reveal that GQDs adhere to the Cys81 residue due to van der Waals (vdW) interaction forces, whereas GOQDs attach to the Cys81 residue through a combination of vdW (primary) and Coulomb (secondary) interactions. Furthermore, GQDs aggregation typically adsorb onto the AGR2 active site, while GOQDs adsorb to the active site of AGR2 one by one. Consequently, these findings shed new light on the potential adverse impact of GQDs and GOQDs on the AGR2 protein via directly covering the active site of AGR2, providing valuable molecular insights for the toxicity profile of GQD nanomaterials.

Environmental water contamination, particularly by heavy metal ions, has emerged as a worldwide concern due to their non-biodegradable nature and propensity to accumulate in soil and living organisms, posing a significant risk to human health. Therefore, the effective removal of heavy metal ions from wastewater is of utmost importance for both public health and environmental sustainability. In this study, we propose and design a membrane consisting of fluorographene (F-GRA) nanochannels to investigate its heavy metal ion removal capacity through molecular dynamics simulation. Although many previous studies have revealed the good performance of lamellar graphene membranes for desalination, how the zero-charged graphene functionalized by fluorine atoms (fully covered by negative charges) affects the heavy metal ion removal capacity is still unknown. Our F-GRA membrane exhibits an exceptional water permeability accompanied by an ideal heavy metal ion rejection rate. The superior performance of F-GRA membrane in removing heavy metal ions can be attributed to the negative charge of the F-GRA surface, which results in electrostatic attraction to positively charged ions that facilitates the optimal ion capture. Our analysis of the potential of mean force further reveals that water molecule exhibits the lowest free energy barrier relative to ions when passing through the F-GRA channel, indicating that water transport is energetically more favorable than ion. Additional simulations of lamellar graphene membranes show that graphene membranes have higher water permeabilities compared with F-GRA membranes, while robustly compromising the heavy meal ion rejection rates, and thus F-GRA membranes show better performances. Overall, our theoretical research offers a potential design approach of F-GRA membrane for heavy metal ions removal in future industrial wastewater treatment.