GNIP1 functions both as a scaffold protein and an E3 ubiquitin ligase to regulate autophagy in lung cancer

Advances of E3 ligases in lung cancer

Lung cancer is a leading cause of cancer-related death, and the most common type of lung cancer is non-small cell lung cancer, which accounts for approximately 85 % of lung cancer diagnoses. Recent studies have revealed that ubiquitination acts as a crucial part of the development and progression of lung cancer. The E1-E2-E3 three-enzyme cascade has a core function in ubiquitination, so targeted adjustments of E3 ligases could be used in lung cancer treatment. Hence, we elucidate research advances in lung cancer-related E3 ligases by briefly describing the structure and categorization of E3 ligases. Here, we provide a detailed review of the mechanisms by which lung cancer-related E3 ligases modify substrate proteins and regulate signaling pathways to facilitate or suppress cancer progression. We hope to show a new perspective on targeted precision therapy for lung cancer.

The myokine CCL5 recruits subcutaneous preadipocytes and promotes intramuscular fat deposition in obese mice

Intramuscular fat (IMF) refers to the lipid stored in skeletal muscle tissue. The number and size of intramuscular adipocytes are the primary factors that regulate IMF content. Intramuscular adipocytes can be derived from either in situ or ectopic migration. In this study, it was discovered that the regulation of IMF levels is achieved through the chemokine (C-C motif) ligand 5 (CCL5)/chemokine (C-C motif) receptor 5 (CCR5) pathway by modulating adipocyte migration. In coculture experiments, C2C12 myotubes were more effective in promoting the migration of 3T3-L1 preadipocytes than C2C12 myoblasts, along with increasing CCL5. Correspondingly, overexpressing the CCR5, one of the receptors of CCL5, in 3T3-L1 preadipocytes facilitated their migration. Conversely, the application of the CCL5/CCR5 inhibitor, MARAVIROC (MVC), reduced this migration. In vivo, transplanted experiments of subcutaneous adipose tissue (SCAT) from transgenic mice expressing green fluorescent protein (GFP) provided evidence that injecting recombinant CCL5 (rCCL5) into skeletal muscle promotes the migration of subcutaneous adipocytes to the skeletal muscle. The level of CCL5 in skeletal muscle increased with obesity. Blocking the CCL5/CCR5 axis by MVC inhibited IMF deposition, whereas elevated skeletal muscle CCL5 promoted IMF deposition in obese mice. These results establish a link between the IMF and the CCL5/CCR5 pathway, which could have a potential application for modulating IMF through adipocyte migration.NEW & NOTEWORTHY C2C12 myotubes attract 3T3-L1 preadipocyte migration regulated by the chemokine (C-C motif) ligand 5 (CCL5)/ chemokine (C-C motif) receptor 5 (CCR5) axis. High levels of skeletal muscle-specific CCL5 promote the migration of subcutaneous adipocytes to skeletal muscle and induce the intramuscular fat (IMF) content.

The E3 ubiquitin ligase RNF135 modulates chemotherapy resistance to oxaliplatin for colorectal cancer by modulating autophagy

BACKGROUND

RING finger protein 135 plays an important role in tumorigenesis and is associated with drug resistance.

METHODS

Bioinformatics analysis showed that RNF135 was significantly differentially expressed in colorectal cancer. RT-qPCR and western blot were used to detect the expression of RNF135. Immunohistochemical analysis were used to measure the expression of RNF135 and Ki-67.

RESULTS

The expression of RNF135 was up-regulated in human tissue samples and colorectal cancer and was positively correlated with Ki-67. Compared with oxaliplatin sensitive patients, RNF135 expression levels were higher in the tissue of resistant patients. The regulatory effect of RNF135 on colorectal cancer cells was further investigated in vitro. Therefore, inhibition of autophagy by down-regulating RNF135 can partially increase its susceptibility to oxaliplatin.

A contrast set mining based approach for cancer subtype analysis

The task of detecting common and unique characteristics among different cancer subtypes is an important focus of research that aims to improve personalized therapies. Unlike current approaches mainly based on predictive techniques, our study aims to improve the knowledge about the molecular mechanisms that descriptively led to cancer, thus not requiring previous knowledge to be validated. Here, we propose an approach based on contrast set mining to capture high-order relationships in cancer transcriptomic data. In this way, we were able to extract valuable insights from several cancer subtypes in the form of highly specific genetic relationships related to functional pathways affected by the disease. To this end, we have divided several cancer gene expression databases by the subtype associated with each sample to detect which gene groups are related to each cancer subtype. To demonstrate the potential and usefulness of the proposed approach we have extensively analysed RNA-Seq gene expression data from breast, kidney, and colon cancer subtypes. The possible role of the obtained genetic relationships was further evaluated through extensive literature research, while its prognosis was assessed via survival analysis, finding gene expression patterns related to survival in various cancer subtypes. Some gene associations were described in the literature as potential cancer biomarkers while other results have been not described yet and could be a starting point for future research.