PRF1 as a prognostic gene for lymphatic metastasis in skin melanoma.

BACKGROUND: Melanoma is a highly aggressive tumor, predominantly found in the skin, recognized as skin cutaneous melanoma (SKCM). Lymph node metastasis is commonly used as the route of metastasis in SKCM, necessitating the discovery of prognostic genes associated with this process for improved prognosis. METHODS: The prognostic significance of lymph node metastasis in SKCM was assessed through Kaplan-Meier analysis in SEER and TCGA-SKCM datasets. Prognostic genes were identified and a prognostic risk model was constructed Enrichment analysis and immune cell infiltration analysis were also carried out.Moreover, a validation in vitro and in vivo were conducted by CCK8,flow cytometry, transwell and animal study. RESULTS: The Kaplan-Meier survival curve revealed that patients with lymph node metastasis had a worse prognosis compared to those without. FCGR3B and PRF1 were screened by TCGA analysis.Additionally, significant differences in nine immune cell types were observed between the two risk groups. Notably, a strong positive association with CD8 T cells and a negative relationship with M2 macrophages were exhibited by PRF1. The validation of our nomogram were conducted in vitro and in vivo, and the results showed the correlations between CD8+ T cell and PRF1. CONCLUSION: In summary, two prognostic genes (FCGR3B and PRF1) were identified, and a prognostic risk model was developed for SKCM. These findings provide a novel approach for the diagnosis and treatment of SKCM.

GloEC: a hierarchical-aware global model for predicting enzyme function.

The annotation of enzyme function is a fundamental challenge in industrial biotechnology and pathologies. Numerous computational methods have been proposed to predict enzyme function by annotating enzyme labels with Enzyme Commission number. However, the existing methods face difficulties in modelling the hierarchical structure of enzyme label in a global view. Moreover, they haven't gone entirely to leverage the mutual interactions between different levels of enzyme label. In this paper, we formulate the hierarchy of enzyme label as a directed enzyme graph and propose a hierarchy-GCN (Graph Convolutional Network) encoder to globally model enzyme label dependency on the enzyme graph. Based on the enzyme hierarchy encoder, we develop an end-to-end hierarchical-aware global model named GloEC to predict enzyme function. GloEC learns hierarchical-aware enzyme label embeddings via the hierarchy-GCN encoder and conducts deductive fusion of label-aware enzyme features to predict enzyme labels. Meanwhile, our hierarchy-GCN encoder is designed to bidirectionally compute to investigate the enzyme label correlation information in both bottom-up and top-down manners, which has not been explored in enzyme function prediction. Comparative experiments on three benchmark datasets show that GloEC achieves better predictive performance as compared to the existing methods. The case studies also demonstrate that GloEC is capable of effectively predicting the function of isoenzyme. GloEC is available at: https://github.com/hyr0771/GloEC.

Evaluation of a Commercial TIMS-Q-TOF Platform for Native Mass Spectrometry.

Mass-spectrometry based assays in structural biology studies measure either intact or digested proteins. Typically, different mass spectrometers are dedicated for such measurements: those optimized for rapid analysis of peptides or those designed for high molecular weight analysis. A commercial trapped ion mobility-quadrupole-time-of-flight (TIMS-Q-TOF) platform is widely utilized for proteomics and metabolomics, with ion mobility providing a separation dimension in addition to liquid chromatography. The ability to perform high-quality native mass spectrometry of protein complexes, however, remains largely uninvestigated. Here, we evaluate a commercial TIMS-Q-TOF platform for analyzing noncovalent protein complexes by utilizing the instrument's full range of ion mobility, MS, and MS/MS (both in-source activation and collision cell CID) capabilities. The TIMS analyzer is able to be tuned gently to yield collision cross sections of native-like complexes comparable to those previously reported on various instrument platforms. In-source activation and collision cell CID were robust for both small and large complexes. TIMS-CID was performed on protein complexes streptavidin (53 kDa), avidin (68 kDa), and cholera toxin B (CTB, 58 kDa). Complexes pyruvate kinase (237 kDa) and GroEL (801 kDa) were beyond the trapping capabilities of the commercial TIMS analyzer, but TOF mass spectra could be acquired. The presented results indicate that the commercial TIMS-Q-TOF platform can be used for both omics and native mass spectrometry applications; however, modifications to the commercial RF drivers for both the TIMS analyzer and quadrupole (currently limited to m/z 3000) are necessary to mobility analyze protein complexes greater than about 60 kDa.

Low-dose IL-2 treatment confers anti-inflammatory effect against subarachnoid hemorrhage in mice.

Objective: Subarachnoid hemorrhage (SAH) was a stroke with high occurrence and mortality. At the early stage, SAH patients have severe cerebral injury which is contributed by inflammation. In this study, we aimed to explore the anti-inflammation effect of low-dose IL-2 in SAH mice. Methods: The 12-week-old C57BL/6J male mice were conducted with SAH surgery (Internal carotid artery puncture method). Different dose of IL-2 was injected intraperitoneally for 1 h, 1 day, and 2 days after SAH. Single-cell suspension and flow cytometry were used for the test of regulatory T (Treg) cells. Immunofluorescence staining was used to investigate the phenotypic polarization of microglia and inflammation response around neurons. Enzyme-Linked Immuno-sorbent Assay (ELISA) was applied to detect the level of pro-inflammatory factors. Results: Low-dose IL-2 could enrich the Treg cells and drive the microglia polarizing to M2. The level of pro-inflammatory factors, IL-1α, IL-6, and TNF-α decreased in the low-dose IL-2 group. The inflammation response around neurons was attenuated. Low-dose IL-2 could increase the number of Treg cells, which could exert a neuroprotective effect against inflammation after SAH. Conclusion: Low-dose IL-2 had the potential to be an effective clinical method to inhibit inflammation after SAH.

Prostate cancer-associated transcript 6 (PCAT6) promotes epithelial-mesenchymal transition and stemness and worsens prognosis in patients with colorectal cancer.

Approximately 20% of colorectal cancer (CRC) patients are first diagnosed with metastatic colorectal cancer (mCRC) because they develop symptoms at an advanced stage. Despite advancements in treatment, patients with metastatic disease still experience inferior survival rates. Our objective is to investigate the association between long noncoding RNAs (lncRNAs) and prognosis and to explore their role in mCRC. In this study, we find that elevated expression of PCAT6 is independently linked to unfavourable survival outcomes in The Cancer Genome Atlas (TCGA) data, and this finding is further confirmed in CRC samples obtained from Fudan University Shanghai Cancer Center. Cell lines and xenograft mouse models are used to examine the impact of PCAT6 on tumor metastasis. Knockdown of PCAT6 is observed to impede the metastatic phenotype of CRC, as evidenced by functional assays, demonstrating the suppression of epithelial-mesenchymal transition (EMT) and stemness. Our findings show the significance of PCAT6 in mCRC and its potential use as a prognostic biomarker.