MYC Activity Inference Captures Diverse Mechanisms of Aberrant MYC Pathway Activation in Human Cancers

Enhancing protein production and growth in chinese hamster ovary cells through miR-107 overexpression

Chinese Hamster Ovary (CHO) cells are widely employed as host cells for biopharmaceutical production. The manufacturing of biopharmaceuticals poses several challenges, including restricted growth potential and inadequate productivity of the host cells. MicroRNAs play a crucial role in regulating gene expression and are considered highly promising tools for cell engineering to enhance protein production. Our study aimed to evaluate the effects of miR-107, which is recognized as an onco-miR, on erythropoietin-producing CHO cells (CHO-hEPO). To assess the impact of miR-107 on CHO cells, a DNA plasmid containing miR-107 was introduced to CHO-hEPO cells through transfection. Cell proliferation and viability were assessed using the trypan blue dye exclusion method. Cell cycle analysis was conducted by utilizing propidium iodide (PI) staining. The quantification of EPO was determined using an immunoassay test. Moreover, the impact of miR-107 on the expression of downstream target genes was evaluated using qRT-PCR. Our findings highlight and underscore the substantial impact of transient miR-107 overexpression, which led to a remarkable 2.7-fold increase in EPO titers and a significant 1.6-fold increase in the specific productivity of CHO cells (p < 0.01). Furthermore, this intervention resulted in significant enhancements in cell viability and growth rate (p < 0.05). Intriguingly, the overexpression of miR‑107 was linked to the downregulation of LATS2, PTEN, and TSC1 genes while concurrently driving upregulation in transcript levels of MYC, YAP, mTOR, and S6K genes within transgenic CHO cells. In conclusion, this study collectively underscores the feasibility of utilizing cancer-associated miRNAs as a powerful tool for CHO cell engineering. However, more in-depth exploration is warranted to unravel the precise molecular intricacies of miR-107's effects in the context of CHO cells.

Recent advances in targeting the "undruggable" proteins: from drug discovery to clinical trials

Undruggable proteins are a class of proteins that are often characterized by large, complex structures or functions that are difficult to interfere with using conventional drug design strategies. Targeting such undruggable targets has been considered also a great opportunity for treatment of human diseases and has attracted substantial efforts in the field of medicine. Therefore, in this review, we focus on the recent development of drug discovery targeting "undruggable" proteins and their application in clinic. To make this review well organized, we discuss the design strategies targeting the undruggable proteins, including covalent regulation, allosteric inhibition, protein-protein/DNA interaction inhibition, targeted proteins regulation, nucleic acid-based approach, immunotherapy and others.

Caprin-1 plays a role in cell proliferation and Warburg metabolism of esophageal carcinoma by regulating METTL3 and WTAP

BACKGROUND

Cytoplasmic activation/proliferation-associated protein-1 (Caprin-1) is implicated in cancer cell proliferation and tumorigenesis; however, its role in the development of esophageal carcinoma (ESCA) has not been examined.

METHODS

Biological methods and data analysis were used to investigate the expression of Caprin-1 in ESCA tissue and cell lines. We comprehensively analyzed the mRNA expression and prognostic values, signalling pathways of CAPRIN1 in ESCA using public databases online. Biological functions of CAPRIN1 were performed by clorimetric growth assay, EdU staining, colony formation, flow cytometry, apoptosis analysis, Western blot, lactate detection assay, extracellular acidification rates. The underlying mechanism was determined via flow cytometric analysis, Western blot and rescue experiments. In addition, xenograft tumor model was constructed to verify the phenotypes upon CAPRIN1 silencing.

RESULTS

Caprin-1 expression was significantly elevated in both ESCA tumor tissues and cell lines compared with that in normal adjacent tissues and fibroblasts. Increased CAPRIN1 mRNA expression was significantly associated with clinical prognosis and diagnostic accuracy. The GO enrichment and KEGG pathway analysis CAPRIN1 might be related to immune-related terms, protein binding processes, and metabolic pathways. A significant positive correlation was observed between high Caprin-1 protein levels and lymph node metastasis (P = 0.031), ki-67 (P = 0.023), and 18F- FDG PET/CT parameters (SUVmax (P = 0.002) and SUV mean (P = 0.005)) in 55 ESCA patients. At cut-off values of SUVmax 17.71 and SUVmean 10.14, 18F- FDG PET/CT imaging predicted Caprin-1 expression in ESCA samples with 70.8% sensitivity and 77.4% specificity. In vitro and in vivo assays showed that Caprin-1 knockdown affected ESCA tumor growth. Silencing Caprin-1 inhibited ESCA cell proliferation and glycolysis, and decreased the expression of methyltransferase-like 3 (METTL3) and Wilms' tumor 1-associating protein (WTAP). However, this effect could be partially reversed by the restoration of METTL3 and WTAP expression.

CONCLUSIONS

Our data suggest that Caprin-1 could serve as a prognostic biomarker and has an oncogenic role in ESCA.

Application of two-dimensional difference gel electrophoresis to identify protein changes between center, margin, and adjacent non-tumor tissues obtained from non-small-cell lung cancer with adenocarcinoma or squamous cell carcinoma subtype

Lung cancer is responsible for the most cancer-related mortality worldwide and the mechanism of its development is poorly understood. Proteomics has become a powerful tool offering vital knowledge related to cancer development. Using a two-dimensional difference gel electrophoresis (2D-DIGE) approach, we sought to compare tissue samples from non-small-cell lung cancer (NSCLC) patients taken from the tumor center and tumor margin. Two subtypes of NSCLC, adenocarcinoma (ADC) and squamous cell carcinoma (SCC) were compared. Data are available via ProteomeXchange with identifier PXD032736 and PXD032962 for ADC and SCC, respectively. For ADC proteins, 26 significant canonical pathways were identified, including Rho signaling pathways, a semaphorin neuronal repulsive signaling pathway, and epithelial adherens junction signaling. For SCC proteins, nine significant canonical pathways were identified, including hypoxia-inducible factor-1α signaling, thyroid hormone biosynthesis, and phagosome maturation. Proteins differentiating the tumor center and tumor margin were linked to cancer invasion and progression, including cell migration, adhesion and invasion, cytoskeletal structure, protein folding, anaerobic metabolism, tumor angiogenesis, EMC transition, epithelial adherens junctions, and inflammatory responses. In conclusion, we identified several proteins that are important for the better characterization of tumor development and molecular specificity of both lung cancer subtypes. We also identified proteins that may be important as biomarkers and/or targets for anticancer therapy.

AutoEncoder-Based Computational Framework for Tumor Microenvironment Decomposition and Biomarker Identification in Metastatic Melanoma

Melanoma is one of the most aggressive cancer types whose prognosis is determined by both the tumor cell-intrinsic and -extrinsic features as well as their interactions. In this study, we performed systematic and unbiased analysis using The Cancer Genome Atlas (TCGA) melanoma RNA-seq data and identified two gene signatures that captured the intrinsic and extrinsic features, respectively. Specifically, we selected genes that best reflected the expression signals from tumor cells and immune infiltrate cells. Then, we applied an AutoEncoder-based method to decompose the expression of these genes into a small number of representative nodes. Many of these nodes were found to be significantly associated with patient prognosis. From them, we selected two most prognostic nodes and defined a tumor-intrinsic (TI) signature and a tumor-extrinsic (TE) signature. Pathway analysis confirmed that the TE signature recapitulated cytotoxic immune cell related pathways while the TI signature reflected MYC pathway activity. We leveraged these two signatures to investigate six independent melanoma microarray datasets and found that they were able to predict the prognosis of patients under standard care. Furthermore, we showed that the TE signature was also positively associated with patients' response to immunotherapies, including tumor vaccine therapy and checkpoint blockade immunotherapy. This study developed a novel computational framework to capture the tumor-intrinsic and -extrinsic features and identified robust prognostic and predictive biomarkers in melanoma.