Background: The Makorin ring finger protein 1 (MKRN1) gene, also called RNF61, is located on the long arm of chromosome 7 and is a member of the RING finger protein family. The E3 ubiquitin ligase MKRN1 is closely linked to tumour development, but the exact mechanism needs to be elucidated. In this study, we aimed to investigate the specific mechanism and role of MKRN1 in colorectal cancer (CRC) development. Methods: MKRN1 expression in CRC was analysed using the Cancer Cell Line Encyclopaedia and the Cancer Genome Atlas (TCGA) databases. Rectal tumour tissues were frozen to explore the MKRN1 expression in CRC and its clinical significance. The impact of MKRN1 on CRC cell proliferation and migration was observed using CCK8, colony formation, wound healing, and transwell assays. A combination of MKRN1 quantitative proteomics, ubiquitination modification omics analysis, and a string of in vitro and in vivo experiments revealed the potential mechanisms by which MKRN1 regulates CRC metastasis. Results: MKRN1 expression was significantly elevated in CRC tissues compared to paracancerous tissues and was positively linked with prognosis (P < 0.01). MKRN1 downregulation inhibits CRC cell proliferation, migration, and invasion. Conversely, MKRN1 overexpression promotes the proliferation, migration, and invasion of CRC cells. Mechanistically, MKRN1 induces epithelial-mesenchymal transition (EMT) in CRC cells via ubiquitination and degradation of Smad nuclear-interacting protein 1 (SNIP1). Furthermore, SNIP1 inhibits transforming growth factor-β (TGF-β) signalling, and MKRN1 promotes TGF-β signalling by degrading SNIP1 to induce EMT in CRC cells. Finally, using conditional knockout mice, intestinal lesions and metastatic liver microlesions were greatly reduced in the intestinal knockout MKRN1 group compared to that in the control group. Conclusions: High MKRN1 levels promote TGF-β signalling through ubiquitination and degradation of SNIP1, thereby facilitating CRC metastasis, and supporting MKRN1 as a CRC pro-cancer factor. The MKRN1/SNIP1/TGF-β axis may be a potential therapeutic target in CRC.

Purpose: Numerous studies have emphasised the importance of necroptosis in the malignant progression of colorectal cancer (CRC). However, whether necroptosis-related genes (NRGs) can be used to predict the prognosis of CRC remains to be revealed. Methods: Patients with CRC were divided into two clusters based on the expression of NRGs, and prognosis was compared between the two clusters. A prognostic model was established based on NRGs, and its predictive efficiency was validated using Kaplan-Meier (K-M) curves, receiver operating characteristic (ROC) curves and a nomogram. Immune infiltration, single-cell and drug sensitivity analyses were used to examine the effects of NRGs on the prognosis of CRC. Results: The prognostic model served as a valid and independent predictor of CRC prognosis. Immune infiltration and single-cell analyses revealed that the unique immune microenvironment of CRC was regulated by NRGs. Drug sensitivity analysis showed that patients in the high- and low-risk groups were sensitive to different drugs. In addition, H2BC18 was found to play an important role in regulating the malignant progression of CRC. Conclusion: This study provides novel insights into precision immunotherapy based on NRGs in CRC. The NRG-based prognostic model may help to identify targeted drugs and develop more effective and individualised treatment strategies for patients with CRC.

Presented for the MKRN1 f/f group (IHC staining of TGF-β1) was inadvertently incorrect due to an oversight during figure preparation.

Myeloma (MM) is a malignant plasma cell disorder, which is incurable owing to its drug resistance. Autophagy performs an integral function in homeostasis, survival, and drug resistance in multiple myeloma (MM). Therefore, the purpose of the present research was to identify potential autophagy-related genes (ARGs) in patients with MM. We downloaded the transcriptomic data (GSE136400) of patients with MM, as well as the corresponding clinical data from the Gene Expression Omnibus (GEO); the patients were classified at random into two groups in a ratio of 6: 4, with 212 samples in the training dataset and 142 samples in the test dataset. Both multivariate and univariate Cox regression analyses were performed to identify autophagy-related genes. The univariate Cox regression analysis demonstrated that 26 ARGs had a significant correlation with overall survival (OS). We constructed an autophagy-related risk prognostic model based on six ARGs: EIF2AK2 (ENSG00000055332), KIF5B (ENSG00000170759), MYC (ENSG00000136997), NRG2 (ENSG00000158458), PINK1 (ENSG00000158828), and VEGFA (ENSG00000112715) using LASSO-Cox regression analysis to predict risk outcomes, which revealed substantially shortened OS duration in the high-risk cohort in contrast with that in the low-risk cohort. Therefore, the ARG-based model significantly predicted the MM patients’ prognoses and was verified in an internal test set. Differentially expressed genes were found to be predominantly enriched in pathways associated with inflammation and immune regulation. Immune infiltration of tumor cells resulted in the formation of a strong immunosuppressive microenvironment in high-risk patients. The potential therapeutic targets of ARGs were subsequently analyzed via protein–drug network analysis. Therefore, a prognostic model for MM was established via a comprehensive analysis of ARGs, through using the clinical models; we have further revealed the molecular landscape features of multiple myeloma.

Objective: Ubiquitination plays a crucial role in the malignant progression of ovarian cancer. With the advent of proteolysis-targeting chimeras (PROTACs) targeting ubiquitin enzymes, precision therapies are now possible. Therefore, it is imperative to ascertain the prognostic significance of ubiquitination-related genes in ovarian cancer.Methods: A prognostic model based on ubiquitination-related genes was developed using data from TCGA and GTEx databases. Performance was assessed via Kaplan-Meier, ROC curves, and Cox regression; a nomogram was created. The model’s stability was checked using training and test sets. FBXO45 was also experimentally validated in ovarian cancer.Results: The model, based on 17 genes related to ubiquitination, showed high performance (1-year AUC = 0.703, 3-year AUC = 0.704, 5-year AUC = 0.705). The high-risk group had significantly lower overall survival (P < 0.05). Immune analysis showed higher levels of CD8+ T (P < 0.05), M1 (P < 0.01) and follicular (P < 0.05) cells in the low-risk group. High-risk patients had more mutations in MUC17 and LRRK2, while low-risk patients had more RYR2 mutations. FBXO45 is a key E3 ubiquitin ligase in ovarian cancer, promoting growth, spread and migration via the Wnt/β-catenin pathway.Conclusion: Ubiquitination-related markers provide reliable prognostic insights and reflect the immune microenvironment in ovarian cancer, offering a basis for clinical targeting strategies.