ARHGAP4 promotes colon cancer metastasis through the TGF-ß signaling pathway and may be associated with T cell exhaustion.

BACKGROUND: Colon cancer is a prevalent invasive neoplasm in the gastrointestinal system with a high degree of malignancy. Despite extensive research, the underlying mechanisms of its recurrence and metastasis remain elusive.Rho GTPase activating protein 4 (ARHGAP4), a member of the small GTPases protein family, may be closely related to tumor metastasis, and its expression is increased in colon cancer. However, the role of ARHGAP4 in colon cancer metastasis is uncertain. This study investigates the impact of ARHGAP4 on the metastasis of colon cancer cells. Our objective is to determine the role of ARHGAP4 in regulating the invasive behavior of colon cancer cells. METHODS: We downloaded colon adenocarcinoma (COAD) data from the Cancer Genome Atlas (TCGA), and performed differential analysis and survival analysis. By using the CIBERSORT algorithm, we evaluated the proportion of infiltrating immune cells in colon cancer. We further analyzed whether ARHGAP4 is associated with T cell exhaustion. Finally, we investigated the impact of ARHGAP4 knockdown on the migration and invasion of colon cancer cells through in vitro cell experiments. Additionally, we utilized western blotting to assess the expression of protein related to the TGF-ß signaling pathway and epithelial-mesenchymal transition (EMT). RESULTS: We found that ARHGAP4 is upregulated in colon cancer. Subsequent survival analysis revealed that the high-expression group had significantly lower survival rates compared to the low-expression group. Immune infiltration analysis showed that ARHGAP4 was not only positively correlated with CD8+ T cells, but also positively correlated with T cell exhaustion markers programmed cell death 1 (PDCD-1), cytotoxic T-lymphocyte associated protein 4 (CTLA-4), and lymphocyte activating 3 (LAG-3). In vitro cell experiments, the knockdown of ARHGAP4 inhibited the migration and invasion of colon cancer cells. Among EMT-related proteins, when ARHGAP4 was knocked down, the expression of E-cadherin was increased, while the expression of N-cadherin and Vimentin was decreased. Meanwhile, the expression of TGF-ß1, p-Smad2, and p-Smad3, which are associated with the TGF-ß/Smad pathway, all decreased. CONCLUSION: ARHGAP4 promotes colon cancer metastasis through the TGF-ß/Smad signaling pathway and may be associated with T cell exhaustion. It plays an important role in the progression of colon cancer and may serve as a potential target for diagnosis and treatment of colon cancer.

OLFM2 promotes epithelial-mesenchymal transition, migration, and invasion in colorectal cancer through the TGF-ß/Smad signaling pathway.

BACKGROUND: Colorectal cancer (CRC) is an aggressive tumor of the gastrointestinal tract, which is a major public health concern worldwide. Despite numerous studies, the precise mechanism of metastasis behind its progression remains elusive. As a member of the containing olfactomedin domains protein family, olfactomedin 2 (OLFM2) may play a role in tumor metastasis. It is highly expressed in colorectal cancer, and its role in the metastasis of CRC is still unclear. As such, this study seeks to explore the function of OLFM2 on CRC metastasis and its potential mechanisms. METHODS: Real-time fluorescence quantitative PCR and western blotting were used to study the expression of OLFM2 in human CRC and adjacent normal tissues. Knockdown and overexpression OLFM2 cell lines were constructed using siRNA and overexpression plasmids to explore the role of OLFM2 in the migration and invasion of CRC through transwell, and wound healing experiments. Finally, the expression of epithelial-mesenchymal transition (EMT) -related proteins and TGF-ß/Smad signaling pathway-related proteins was investigated using western blotting. RESULTS: In this study, we observed an elevation of OLFM2 expression levels in CRC tissues. To investigate the function of OLFM2, we overexpressed and knocked down OLFM2. We discovered that OLFM2 knockdown inhibited migration and invasion of colon cancer cells. Furthermore, E-cadherin expression increased while N-cadherin and Vimentin expression were opposite. It is no surprise that overexpressing OLFM2 had the opposite effects. We also identified that OLFM2 knockdown resulted in reduced TGF-ßR1 and downstream molecules p-Smad2 and p-Smad3, which are related to the TGF-ß / Smad pathway. In contrast, overexpressing OLFM2 significantly boosted their expression levels. CONCLUSION: The protein OLFM2 has been identified as a crucial determinant in the progression of CRC. Its mechanism of action involves the facilitation of EMT through the TGF-ß/Smad signaling pathway. Given its pivotal role in CRC, OLFM2 has emerged as a promising diagnostic and therapeutic target for the disease. These results indicate the potential of OLFM2 as a valuable biomarker for CRC diagnosis and treatment and highlight the need for further research exploring its clinical significance.

Analyzing risk factors and constructing a predictive model for superficial esophageal carcinoma with submucosal infiltration exceeding 200 micrometers.

OBJECTIVE: Submucosal infiltration of less than 200 µm is considered an indication for endoscopic surgery in cases of superficial esophageal cancer and precancerous lesions. This study aims to identify the risk factors associated with submucosal infiltration exceeding 200 micrometers in early esophageal cancer and precancerous lesions, as well as to establish and validate an accompanying predictive model. METHODS: Risk factors were identified through least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. Various machine learning (ML) classification models were tested to develop and evaluate the most effective predictive model, with Shapley Additive Explanations (SHAP) employed for model visualization. RESULTS: Predictive factors for early esophageal invasion into the submucosa included endoscopic ultrasonography or magnifying endoscopy> SM1(P<0.001,OR = 3.972,95%CI 2.161-7.478), esophageal wall thickening(P<0.001,OR = 12.924,95%CI,5.299-33.96), intake of pickled foods(P=0.04,OR = 1.837,95%CI,1.03-3.307), platelet-lymphocyte ratio(P<0.001,OR = 0.284,95%CI,0.137-0.556), tumor size(P<0.027,OR = 2.369,95%CI,1.128-5.267), the percentage of circumferential mucosal defect(P<0.001,OR = 5.286,95%CI,2.671-10.723), and preoperative pathological type(P<0.001,OR = 4.079,95%CI,2.254-7.476). The logistic regression model constructed from the identified risk factors was found to be the optimal model, demonstrating high efficacy with an area under the curve (AUC) of 0.922 in the training set, 0.899 in the validation set, and 0.850 in the test set. CONCLUSION: A logistic regression model complemented by SHAP visualizations effectively identifies early esophageal cancer reaching 200 micrometers into the submucosa.

Identification of potential key genes associated with osteosarcoma based on integrated bioinformatics analyses.

Due to high rates of metastasis and poor clinical outcomes for patients, it is important to study the pathomechanisms of osteosarcoma. However, due to the fact that osteosarcoma shows significant interindividual variation and high heterogeneity, the identification of differentially expressed genes (DEGs) at the population level cannot answer many important questions related to osteosarcoma tumorigenesis. Therefore, a new strategy to identify dysregulated genes in osteosarcoma samples is required. The aim of this study was to improve our understanding of osteosarcoma pathogenesis by identifying genes with universal aberrant expression in osteosarcoma samples. Because the relative expression ordering of genes is stable in normal bone tissues but is disrupted in osteosarcoma tissues, we used the RankComp algorithm to identify DEGs in normal and osteosarcoma tissue samples. We then calculated the dysregulation frequency for each gene. Genes with deregulation frequencies above 80% were deemed to be universal DEGs. Next, coexpression, pathway enrichment, and protein-protein interaction network analyses were performed to characterize the functions of these genes. From 188 samples of osteosarcoma obtained from four datasets measured on different platforms, 51 universal DEGs were identified, including 4 universally upregulated genes and 47 universally downregulated genes. Genes that were differentially coexpressed with these universal DEGs were found to be enriched in 46 cancer-related pathways. In addition, functional and network analyses showed that genes with high dysregulation frequencies were involved in cancer-related functions. Thus, the commonly aberrant genes identified in osteosarcoma tissues may be important targets for osteosarcoma diagnosis and therapy.

Integrated Single-cell RNA-seq and Bulk RNA-seq Identify Diagnostic Biomarkers for Postmenopausal Osteoporosis.

AIM: We aimed to explore diagnostic biomarkers of postmenopausal osteoporosis (PMOP). BACKGROUND: PMOP brings enormous physical and economic burden to elderly women. OBJECTIVES: This study aims to screen new biomarkers for osteoporosis, providing insights for early diagnosis and therapeutic targets of osteoporosis. METHODS: Weighted gene co-expression network analysis (WGCNA) was applied to identify osteoporosis-related hub genes. Single-cell transcriptomic atlas of osteoporosis was depicted and the heterogeneity of monocytes was analyzed, based on which the biomarkers for osteoporosis were screened. Gene set enrichment analysis (GSEA) was conducted on the biomarkers. The diagnostic model (nomogram) was established and evaluated based on the expression levels of biomarkers. Additionally, the transcription factor (TF) regulatory network was constructed to predict the potential TF and targeted miRNA of biomarkers. The drugs with significant correlation with biomarkers were identified by Spearman correlation analysis. RESULTS: We obtained 30 osteoporosis-associated hub genes. 9 cell types were identified, and the monocytes were subdivided to 4 subtypes. Three biomarkers, DHX29, LSM5, and UBE2V2, were screened. DHX29 and UBE2V2 were highly expressed in non-classical monocytes, while LSM5 exhibited the highest expression in other monocytes, followed by non-classical monocytes. GSEA indicated that osteoporosis may be correlated with vascular calcification and the biomarkers may be involved in the formation of immune cells. Then, nomogram was constructed and exhibited good robustness. In addition, MYC and SETDB1 were the shared IF in three biomarkers, which may play critical regulatory roles in the progression of osteoporosis. Moreover, 41, 49, and 68 drugs appeared significant correlations with DHX29, LSM5, and UBE2V2, respectively. CONCLUSION: This study provided a basis for early diagnosis and targeted treatment of osteoporosis.

Unveiling esophageal cancer treatment mechanisms: network pharmacology and molecular docking of Physcion.

This study investigates the effects of Physcion on esophageal cancer and its possible mechanisms of action. Potential Physcion targets were identified using databases. Transcriptomic data from 17 esophageal cancer and adjacent tissues were analyzed to find differentially expressed genes, intersecting with potential targets to select 16 key genes. Their expression and distribution were evaluated in patient sequencing data. Diagnostic potential was assessed through differential gene expression and ROC curves. Pathway enrichment analysis was performed using KEGG, and molecular docking simulations were conducted to assess Physcion's binding affinity to key genes. In vitro assays complemented these findings. A total of 161 drug targets were identified, narrowing down to 16 pivotal genes. Expression patterns were examined across cell populations, and enrichment analysis showed significant PI3K/AKT pathway involvement. Molecular docking indicated strong binding of Physcion to HSP90AA1 and MMP2. In vitro assays confirmed Physcion's dose- and time-dependent impact on esophageal cancer cells, with significant DAPI staining effects. Physcion shows promise as a therapeutic agent for esophageal cancer. The study supports its potential for clinical development and future research in esophageal cancer treatment.

Development and validation of a machine-learning model for preoperative risk of gastric gastrointestinal stromal tumors.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) have malignant potential, and treatment varies according to risk. However, no specific protocols exist to preoperatively assess the malignant potential of gastric stromal tumors (gGISTs). This study aimed to use machine learning (ML) to develop and validate clinically relevant preoperative models to predict the malignant potential of gGISTs. METHODS: We screened patients diagnosed with gGISTs at the Affiliated Hospital of North Sichuan Medical College. We employed the Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to identify risk factors. Subsequently, an ensemble of ML models was deployed to determine the optimal classifier. Additionally, we harnessed SHapley Additive exPlanations (SHAP) for tailored risk profiling. RESULTS: We enrolled 318 patients with gGISTs. Utilizing LASSO regression and multifactorial logistic regression, we analyzed the training dataset, revealing that the presence of endoscopic ultrasound (EUS) high-risk features, tumor border clarity, tumor diameter, and monocyte-to-lymphocyte ratio (MLR) were significant predictors of high malignancy risk in gGIST. As determined by our ML approach, the logistic classification model demonstrated optimal performance, with an area under the receiver operating characteristic curve of 0.919 and 0.925 for the training and test sets, respectively. Furthermore, decision curve analysis substantiated the clinical relevance of the model. CONCLUSION: High-risk EUS features, ill-defined tumor margins, larger tumor diameters, and elevated MLR independently predicted heightened malignant potential in gGIST. We developed logistic regression models based on these factors, which were further interpreted using the SHAP methodology. This analytical approach facilitated personalized therapeutic decision-making for diverse patient populations.

Downregulation of RCN1 inhibits esophageal squamous cell carcinoma progression and M2 macrophage polarization.

Reticulocalbin 1 (RCN1) is a calcium-binding protein involved in the regulation of calcium homeostasis in the endoplasmic reticulum. The aim of this study was to explore the clinical value and biological role of RCN1 in esophageal squamous cell carcinoma (ESCC). In addition, we investigated the effect of RCN1 on the polarization of tumor-associated macrophages (TAMs). The GSE53625 dataset from the Gene Expression Omnibus database was used to analyze the expression of RCN1 mRNA and its relationship with clinical value and immune cell infiltration. Immunohistochemistry was used to validate the expression of RCN1 and its correlation with clinicopathological characteristics. Subsequently, transwell and cell scratch assays were conducted to evaluate the migration and invasion abilities of ESCC cells. The expression levels of epithelial-mesenchymal transition (EMT)-related proteins were evaluated by western blot, while apoptosis was detected by flow cytometry and western blot. Additionally, qRT‒PCR was utilized to evaluate the role of RCN1 in macrophage polarization. RCN1 was significantly upregulated in ESCC tissues and was closely associated with lymphatic metastasis and a poor prognosis, and was an independent prognostic factor for ESCC in patients. Knockdown of RCN1 significantly inhibited the migration, invasion, and EMT of ESCC cells, and promoted cell apoptosis. In addition, RCN1 downregulation inhibited M2 polarization. RCN1 is upregulated in ESCC patients and is negatively correlated with patient prognosis. Knocking down RCN1 inhibits ESCC progression and M2 polarization. RCN1 can serve as a potential diagnostic and prognostic indicator for ESCC, and targeting RCN1 is a very promising therapeutic strategy.

RCN1 deficiency inhibits oral squamous cell carcinoma progression and THP-1 macrophage M2 polarization.

Reticulocalbin 1 (RCN1), a calcium-binding protein located in the endoplasmic reticulum (ER) lumen, contains six conserved regions. Its main functions include maintaining intracellular homeostasis and regulating cell proliferation and apoptosis, and it plays an important role in the development of various tumours. However, the exact function of RCN1 in oral squamous cell carcinoma (OSCC) is not fully understood. Therefore, the aim of this study was to investigate the effects of RCN1 on the biological behaviour of OSCC and the regulation of tumour-associated macrophage (TAM) polarization. The expression of RCN1 in OSCC and normal oral mucosa was evaluated through bioinformatics analysis and immunohistochemical staining. The growth, migration, and invasion of OSCC cells were observed after knockdown of RCN1 using CCK-8 and Transwell assays. Apoptosis was detected by flow cytometry. The effect of tumour cell-derived RCN1 on the polarization of THP-1 macrophages was investigated by establishing a coculture model of THP-1 macrophages and OSCC cells. Additionally, changes in the expression levels of relevant proteins were detected using Western blotting. The upregulation of RCN1 in tumour tissues compared to normal oral mucosal tissues is associated with a poor prognosis and can be utilized as a prognostic indicator for OSCC. Knockdown of RCN1 inhibited the proliferation, migration, and invasion of OSCC cells. Additionally, knockdown of RCN1 in Cal-27 and SCC-25 cells resulted in inhibition of the M2 polarization of THP-1 macrophages. RCN1 knockdown inhibits OSCC progression and M2 macrophage polarization. Targeting RCN1 may be a promising approach for OSCC treatment.