ANXA3 is upregulated by hypoxia-inducible factor 1-alpha and promotes colon cancer growth

The Use of Identified Hypoxia-related Genes to Generate Models for Predicting the Prognosis of Cerebral Ischemia‒reperfusion Injury and Developing Treatment Strategies

Cerebral ischemia‒reperfusion injury (CIRI) is a type of secondary brain damage caused by reperfusion after ischemic stroke due to vascular obstruction. In this study, a CIRI diagnostic model was established by identifying hypoxia-related differentially expressed genes (HRDEGs) in patients with CIRI. The ischemia‒reperfusion injury (IRI)-related datasets were downloaded from the Gene Expression Omnibus (GEO) database ( http://www.ncbi.nlm.nih.gov/geo ), and hypoxia-related genes in the Gene Cards database were identified. After the datasets were combined, hypoxia-related differentially expressed genes (HRDEGs) expressed in CIRI patients were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the HRDEGs were performed using online tools. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed with the combined gene dataset. CIRI diagnostic models based on HRDEGs were constructed via least absolute shrinkage and selection operator (LASSO) regression analysis and a support vector machine (SVM) algorithm. The efficacy of the 9 identified hub genes for CIRI diagnosis was evaluated via mRNA‒microRNA (miRNA) interaction, mRNA-RNA-binding protein (RBP) network interaction, immune cell infiltration, and receiver operating characteristic (ROC) curve analyses. We then performed logistic regression analysis and constructed logistic regression models based on the expression of the 9 HRDEGs. We next established a nomogram and calibrated the prediction data. Finally, the clinical utility of the constructed logistic regression model was evaluated via decision curve analysis (DCA). This study revealed 9 critical genes with high diagnostic value, offering new insights into the diagnosis and selection of therapeutic targets for patients with CIRI. : Not applicable.

ANXA3-Rich Exosomes Derived from Tumor-Associated Macrophages Regulate Ferroptosis and Lymphatic Metastasis of Laryngeal Squamous Cell Carcinoma

Tumor-associated macrophages (TAM) induce immunosuppression in laryngeal squamous cell carcinoma (LSCC). The interaction between LSCC cells and TAMs affects the progression of laryngeal cancer through exosomes, but the underlying molecular mechanism remains unclear. Proteomics analysis of TAMs isolated from human laryngeal tumor tissues obtained from patients with confirmed lymphatic metastasis revealed an upregulation of annexin A3 (ANXA3). In TAMs, ANXA3 promoted macrophages to polarize to an M2-like phenotype by activating the AKT-GSK3β-β-catenin pathway. In addition, ANXA3-rich exosomes derived from TAMs inhibited ferroptosis in laryngeal cancer cells through an ATF2-CHAC1 axis, and this process was associated with lymphatic metastasis. Mechanistically, ANXA3 in exosomes inhibited the ubiquitination of ATF2, whereas ATF2 acted as a transcription factor to regulate the expression of CHAC1, thus inhibiting ferroptosis in LSCC cells. These data indicate that abnormal ANXA3 expression can drive TAM reprogramming and promote an immunosuppressive microenvironment in LSCC. Meanwhile, ANXA3-rich exosomes inhibit ferroptosis of LSCC cells and promote lymphatic metastasis, thus promoting tumor progression.

A Step Toward Personalized Surgical Decision Making: Machine Learning Predicts 1 Versus Numerous Melanoma Lymph Node Metastases Using RNA-sequencing

OBJECTIVE

Develop a predictive model to identify patients with 1 pathologic lymph node (pLN) versus >1 pLN using machine learning applied to gene expression profiles and clinical data as input variables.

BACKGROUND

Standard management for clinically detected melanoma lymph node metastases is complete therapeutic LN dissection (TLND). However, >40% of patients with a clinically detected melanoma lymph node will only have 1 pLN on final review. Recent data suggest that targeted excision of just the single enlarged LN may provide excellent regional control, with less morbidity than TLND. The selection of patients for less morbid surgery requires accurate identification of those with only 1 pLN.

METHODS

The Cancer Genome Atlas database was used to identify patients who underwent TLND for melanoma. Pathology reports in The Cancer Genome Atlas were reviewed to identify the number of pLNs. Patients were included for machine learning analyses if RNA sequencing data were available from a pLN. After feature selection, the top 20 gene expression and clinical input features were used to train a ridge logistic regression model to predict patients with 1 pLN versus >1 pLN using 10-fold cross-validation on 80% of samples. The model was then tested on the remaining holdout samples.

RESULTS

A total of 153 patients met inclusion criteria: 64 with one pLN (42%) and 89 with >1 pLNs (58%). Feature selection identified 1 clinical (extranodal extension) and 19 gene expression variables used to predict patients with 1 pLN versus >1 pLN. The ridge logistic regression model identified patient groups with an accuracy of 90% and an area under the receiver operating characteristic curve of 0.97.

CONCLUSIONS

Gene expression profiles together with clinical variables can distinguish melanoma metastasis patients with 1 pLN versus >1 pLN. Future models trained using positron emission tomography/computed tomography imaging, gene expression, and relevant clinical variables may further improve accuracy and may predict patients who can be managed with a targeted LN excision rather than a complete TLND.

Hypoxic microenvironment in cancer: molecular mechanisms and therapeutic interventions

Having a hypoxic microenvironment is a common and salient feature of most solid tumors. Hypoxia has a profound effect on the biological behavior and malignant phenotype of cancer cells, mediates the effects of cancer chemotherapy, radiotherapy, and immunotherapy through complex mechanisms, and is closely associated with poor prognosis in various cancer patients. Accumulating studies have demonstrated that through normalization of the tumor vasculature, nanoparticle carriers and biocarriers can effectively increase the oxygen concentration in the tumor microenvironment, improve drug delivery and the efficacy of radiotherapy. They also increase infiltration of innate and adaptive anti-tumor immune cells to enhance the efficacy of immunotherapy. Furthermore, drugs targeting key genes associated with hypoxia, including hypoxia tracers, hypoxia-activated prodrugs, and drugs targeting hypoxia-inducible factors and downstream targets, can be used for visualization and quantitative analysis of tumor hypoxia and antitumor activity. However, the relationship between hypoxia and cancer is an area of research that requires further exploration. Here, we investigated the potential factors in the development of hypoxia in cancer, changes in signaling pathways that occur in cancer cells to adapt to hypoxic environments, the mechanisms of hypoxia-induced cancer immune tolerance, chemotherapeutic tolerance, and enhanced radiation tolerance, as well as the insights and applications of hypoxia in cancer therapy.

Annexin A protein family: Focusing on the occurrence, progression and treatment of cancer

The annexin A (ANXA) protein family is a well-known tissue-specific multigene family that encodes Ca²⁺ phospholipid-binding proteins. A considerable amount of literature is available on the abnormal expression of ANXA proteins in various malignant diseases, including cancer, atherosclerosis and diabetes. As critical regulatory molecules in cancer, ANXA proteins play an essential role in cancer progression, proliferation, invasion and metastasis. Recent studies about their structure, biological properties and functions in different types of cancers are briefly summarised in this review. We further discuss the use of ANXA as new class of targets in the clinical diagnosis and treatment of cancer.

Hypoxia signaling in human health and diseases: implications and prospects for therapeutics

Molecular oxygen (O₂) is essential for most biological reactions in mammalian cells. When the intracellular oxygen content decreases, it is called hypoxia. The process of hypoxia is linked to several biological processes, including pathogenic microbe infection, metabolic adaptation, cancer, acute and chronic diseases, and other stress responses. The mechanism underlying cells respond to oxygen changes to mediate subsequent signal response is the central question during hypoxia. Hypoxia-inducible factors (HIFs) sense hypoxia to regulate the expressions of a series of downstream genes expression, which participate in multiple processes including cell metabolism, cell growth/death, cell proliferation, glycolysis, immune response, microbe infection, tumorigenesis, and metastasis. Importantly, hypoxia signaling also interacts with other cellular pathways, such as phosphoinositide 3-kinase (PI3K)-mammalian target of rapamycin (mTOR) signaling, nuclear factor kappa-B (NF-κB) pathway, extracellular signal-regulated kinases (ERK) signaling, and endoplasmic reticulum (ER) stress. This paper systematically reviews the mechanisms of hypoxia signaling activation, the control of HIF signaling, and the function of HIF signaling in human health and diseases. In addition, the therapeutic targets involved in HIF signaling to balance health and diseases are summarized and highlighted, which would provide novel strategies for the design and development of therapeutic drugs.