The existence of breast cancer stem cells (BCSCs) is a major reason underlying cancer metastasis and recurrence after chemotherapy and radiotherapy. Targeting BCSCs may ameliorate breast cancer relapse and therapy resistance. Here we report that expression of the pseudokinase Tribble 3 (TRIB3) positively associates with breast cancer stemness and progression. Elevated TRIB3 expression supports BCSCs by interacting with AKT to interfere with the FOXO1-AKT interaction and suppress FOXO1 phosphorylation, ubiquitination, and degradation by E3 ligases SKP2 and NEDD4L. The accumulated FOXO1 promotes transcriptional expression of SOX2, a transcriptional factor for cancer stemness, which in turn, activates FOXO1 transcription and forms a positive regulatory loop. Disturbing the TRIB3-AKT interaction suppresses BCSCs by accelerating FOXO1 degradation and reducing SOX2 expression in mouse models of breast cancer. Our study provides insights into breast cancer development and confers a potential therapeutic strategy against TRIB3-overexpressed breast cancer.

Impaired macroautophagy/autophagy is involved in the pathogenesis of hepatic fibrosis. However, how aberrant autophagy promotes fibrosis is far from understood. Here, we aimed to define a previously unrevealed pro-fibrotic mechanism for the stress protein TRIB3 (tribbles pseudokinase 3)-mediated autophagy dysfunction. Human fibrotic liver tissues were obtained from patients with cirrhosis who underwent an open surgical repair process. The functional implications of TRIB3 were evaluated in mouse models of hepatic fibrosis induced by bile duct ligation (BDL) or thioacetamide (TAA) injection. Human fibrotic liver tissues expressed higher levels of TRIB3 and selective autophagic receptor SQSTM1/ p62 (sequestosome 1) than nonfibrotic tissues and the elevated expression of TRIB3 and SQSTM1 was positively correlated in the fibrotic tissues. Silencing Trib3 protected against experimentally induced hepatic fibrosis, accompanied by restored autophagy activity in fibrotic liver tissues. Furthermore, TRIB3 interacted with SQSTM1 and hindered its binding to MAP1LC3/LC3, which caused the accumulation of SQSTM1 aggregates and obstructed autophagic flux. The TRIB3-mediated autophagy impairment not only suppressed autophagic degradation of late endosomes but also promoted hepatocellular secretion of INHBA/Activin A-enriched exosomes which caused migration, proliferation and activation of hepatic stellate cells (HSCs), the effector cells of liver fibrosis. Disrupting the TRIB3-SQSTM1 interaction with a specific helical peptide exerted potent protective effects against hepatic fibrosis by restoring autophagic flux in hepatocytes and HSCs. Together, stress-elevated TRIB3 expression promotes hepatic fibrosis by interacting with SQSTM1 and interfering with its functions in liver-parenchymal cells and activating HSCs. Targeting this interaction is a promising strategy for treating fibroproliferative liver diseases.

Aim: Prostate cancer (PCa) is the most common malignancy found in males worldwide. Although it is mostly indolent, PCa still poses a serious threat to long-term health. Materials & methods: The Cancer Genome Atlas data were randomly divided into training and validation groups. Least absolute shrinkage and selection operator regression on DNA methylation data in the training group was conducted to build the model, which was validated in the validation group. Weighted correlation network analysis was conducted on RNA-seq data to identify the therapy target. Functional validation (western blot, quantitative real-time PCR, cell transfection, Cell Counting Kit-8 assay, colony formation assay, wound healing assay and transwell invasion assay) for the target was conducted. Results: The model is an independent predictor of prognosis. The knockdown of FOXD1 inhibits cell proliferation, migration and invasion of PCa. Conclusion: The risk of patients could be evaluated by the model, which revealed that FOXD1 might promote poor prognosis.

Monoclonal antibodies (mAbs) are widely used in many fields due to their high specificity and ability to recognize a broad range of antigens. IL-17A can induce a rapid inflammatory response both alone and synergistically with other proinflammatory cytokines. Accumulating evidence suggests that therapeutic intervention of IL-17A signaling offers an attractive treatment option for autoimmune diseases and cancer. Here, we present a combinatorial approach for optimizing the affinity and thermostability of a novel anti-hIL-17A antibody. From a large naïve phage-displayed library, we isolated the anti-IL-17A mAb 7H9 that can neutralize the effects of recombinant human IL-17A. However, the modest neutralization potency and poor thermostability limit its therapeutic applications. In vitro affinity optimization was then used to generate 8D3 by using yeast-displayed random mutagenesis libraries. This resulted in four key amino acid changes and provided an approximately 15-fold potency increase in a cell-based neutralization assay. Complementarity-determining regions (CDRs) of 8D3 were further grafted onto the stable framework of the huFv 4D5 to improve thermostability. The resulting hybrid antibody 9NT/S has superior stabilization and affinities beyond its original antibody. Human fibrosarcoma cell-based assays and in vivo analyses in mice indicated that the anti-IL-17A antibody 9NT/S efficiently inhibited the secretion of IL-17A-induced proinflammatory cytokines. Therefore, this lead anti-IL-17A mAb might be used as a potential best-in-class candidate for treating IL-17A related diseases.

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Background Skin cutaneous melanoma (SKCM) is one of the most highly prevalent and complicated malignancies. Glycolysis and cholesterogenesis pathways both play important roles in cancer metabolic adaptations. The main aims of this study are to subtype SKCM based on glycolytic and cholesterogenic genes and to build a clinical outcome predictive algorithm based on the subtypes. Methods A dataset with 471 SKCM specimens was downloaded from The Cancer Genome Atlas (TCGA) database. We extracted and clustered genes from the Molecular Signatures Database v7.2 and acquired co-expressed glycolytic and cholesterogenic genes. We then subtyped the SKCM samples and validated the efficacy of subtypes with respect to simple nucleotide variations (SNVs), copy number variation (CNV), patients’ survival statuses, tumor microenvironment, and proliferation scores. We also constructed a risk score model based on metabolic subclassification and verified the model using validating datasets. Finally, we explored potential drugs for high-risk SKCM patients. Results SKCM patients were divided into four subtype groups: glycolytic, cholesterogenic, mixed, and quiescent subgroups. The glycolytic subtype had the worst prognosis and MGAM SNV extent. Compared with the cholesterogenic subgroup, the glycolytic subgroup had higher rates of DDR2 and TPR CNV and higher proliferation scores and MK167 expression levels, but a lower tumor purity proportion. We constructed a forty-four-gene predictive signature and identified MST-321, SB-743921, Neuronal Differentiation Inducer III, romidepsin, vindesine, and YM-155 as high-sensitive drugs for high-risk SKCM patients. Conclusions Subtyping SKCM patients via glycolytic and cholesterogenic genes was effective, and patients in the glycolytic-gene enriched group were found to have the worst outcome. A robust prognostic algorithm was developed to enhance clinical decisions in relation to drug administration.

Regeneration and tumorigenesis are indicated as related processes, while regeneration leads to life and the outcome of tumorigenesis is death. Here, we show the upregulation of zfp281 (zinc finger 281) in our adipose de novo regeneration model through RNA-seq analysis. Then, we validated the upregulation of zfp281 in adipose regeneration via immunofluorescence. Following that, we found that ZNF281 (the human homolog of Zfp281) was upregulated in most types of cancer and related to worse prognosis in 10 tumors. We further investigated the role of ZNF281 in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), pancreatic adenocarcinoma (PAAD), and stomach adenocarcinoma (STAD) and confirmed the high accuracy in the clinical diagnostic feature. Beyond that, based on these three types of cancers, we analyzed the ZNF281-related tumor immune infiltration and DNA methylation sites and finally built risk prediction models for future disease diagnosis. Taken together, our findings provide new insights into the dual role of ZNF281, and we found that it was a potential biomarker for regeneration and tumor prognosis.

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