KCNN4 is a Potential Biomarker for Predicting Cancer Prognosis and an Essential Molecule that Remodels Various Components in the Tumor Microenvironment: A Pan-Cancer Study

Genomic analysis of genotype-environment interaction in age at first calving of Murrah buffaloes

Age at first calving (AFC) is a measure of sexual maturity associated with the start of productive life of dairy animals. Additionally, a lower AFC reduces the generation interval and early culling of females. However, AFC has low heritability, making it a trait highly influenced by environmental factors. In this scenario, one way to improve the reproductive performance of buffalo cows is to select robust animals according to estimated breeding value (EBV) using models that include genotype-environment interaction (GEI) with the application of reaction norm models (RNMs). This can be achieved by understanding the genomic basis related to GEI of AFC. Thus, in this study, we aimed to predict EBV considering GEI via the RNM and identify candidate genes related to this component in dairy buffaloes through genome-wide association studies (GWAS). We used 1795 AFC records from three Murrah buffalo herds and formed environmental gradients (EGs) from contemporary group solutions obtained from genetic analysis of 270-day cumulative milk yield. Heritability estimates ranged from 0.15 to 0.39 along the EG. GWAS of the RNM slope parameter identified important genomic regions. The genomic window that explained the highest percentage of genetic variance of the slope (0.67%) was located on BBU1. After functional analysis, five candidate genes were detected, involved in two biological processes. The results suggested the existence of a GEI for AFC in Murrah buffaloes, with reclassification of animals when different environmental conditions were considered. The inclusion of genomic information increased the accuracy of breeding values for the intercept and slope of the reaction norm. GWAS analysis suggested that important genes associated with the AFC reaction norm slope were possibly also involved in biological processes related to lipid metabolism and immunity.

Intermediate conductance calcium-activated potassium channel (KCa3.1) in cancer: Emerging roles and therapeutic potentials

The KCa3.1 channel (also known as the KCNN4, IK1, or SK4 channel) is an intermediate-conductance calcium-activated potassium channel that regulates the membrane potential and maintains calcium homeostasis. Recently, KCa3.1 channels have attracted increasing attention because of their diverse roles in various types of cancers. In cancer cells, KCa3.1 channels regulate key processes, including cell proliferation, cell cycle, migration, invasion, tumor microenvironments, and therapy resistance. In addition, abnormal KCa3.1 expression in cancers is utilized to distinguish between tumor and normal tissues, classify cancer stages, and predict patient survival outcomes. This review comprehensively examines the current understanding of the contribution of KCa3.1 channels to tumor formation, metastasis, and its mechanisms. We evaluated the potential of KCa3.1 as a biomarker for cancer diagnosis and prognosis. Finally, we discuss the advances and challenges of applying KCa3.1 modulators in cancer treatment and propose approaches to overcome these obstacles. In summary, this review highlights the importance of this ion channel as a potent therapeutic target and prognostic biomarker of cancer.

ACYP2 functions as an innovative nano-therapeutic target to impede the progression of hepatocellular carcinoma by inhibiting the activity of TERT and the KCNN4/ERK pathway

An increasing body of evidence suggests that acylphosphatase-2 (ACYP2) polymorphisms are correlated with an increased susceptibility to a range of malignancies. Nevertheless, its potential functions, molecular mechanisms in hepatocellular carcinoma (HCC) and whether it can be act as a therapeutic target remain uninvestigated. Herein, ACYP2 was found to be lowly expressed in HCC and was negatively correlated with tumor size, tumor differentiation, microvascular invasion and the prognosis of HCC patients. Functional investigations revealed that overexpression of ACYP2 inhibited the proliferation and metastasis of HCC cells while promoting apoptosis; knockdown of ACYP2 had the exact opposite effect. Additionally, it was observed that ACYP2 was distributed in both the cytoplasm and nucleus of HCC cells. According to the mechanistic studies, the expression of potassium calcium-activated channel subfamily N member 4 (KCNN4) was negatively regulated by cytoplasmic ACYP2, resulting in the inhibition of K+ outflow and subsequent inactivation of the ERK pathway, which impeded the growth and metastasis of HCC. Furthermore, the activity of telomerase reverse transcriptase (TERT) was inhibited by nuclear ACYP2, leading to the reduction in length of telomeres and consequent reversal of HCC cell immortalization. Additionally, a novel targeted nanotherapy strategy was developed wherein the pcDNA-ACYP2 vector was encapsulated within polyetherimide nanoparticles (PEI/NPs), which were subsequently coated with HCC cell membranes (namely pcDNA/PEI/NPs@M). Safety and targeting characteristics abound for these nanocomposites, in both subcutaneous graft tumor models and orthotopic mouse models, they inhibited the progression of HCC by impeding TERT activity and the KCNN4/ERK pathway. In conclusion, our research identifies novel molecular mechanisms involving cytoplasmic and nuclear ACYP2 that inhibit the progression of HCC. Moreover, pcDNA/PEI/NPs@M represents a targeted therapeutic strategy for HCC that holds great promising.

Expression of KCNN4 in adult-type diffuse gliomas and its correlations with clinicopathological features and patient prognosis

BACKGROUND

The KCa3.1 channel (KCNN4) is extensively investigated as an oncogene in human cancers. The current study aimed to explore the clinicopathological significance of KCNN4 expression in patients with primary adult-type diffuse gliomas.

METHODS

Demographic, RNA-seq, and follow-up data of 477 patients were retrospectively reviewed. Patients were divided into the experimental and validation groups (278 and 199). KCNN4-related genes were determined by Pearson correlation analysis, and enrichment analyses and tumor-infiltrating immune cell assessments were applied to explore the potential mechanisms of KCNN4 involving glioma progression. The Kaplan-Meier method and the Cox regression analysis were used to evaluate the prognostic value of KCNN4 expression.

RESULTS

KCNN4 showed significantly higher expression level in glioblastoma, IDH-wildtype, followed by astrocytoma, IDH-mutant and oligodendroglioma, IDH-mutant and 1p/19q-codeleted (p < 0.001). Enrichment analyses and tumor-infiltrating immune cell assessments suggested that KCNN4 could involve glioma progression through extracellular regulation, affecting immune response, and modulating subcellular trafficking. At last, the Kaplan-Meier analysis showed that high KCNN4 expression was significantly correlated with poor progression-free and overall survival (p < 0.001 for both). While multivariate Cox regression analysis obtained an insignificant result.

CONCLUSIONS

KCNN4 was identified to be overexpressed in glioma cells and its expression level is positively related to tumor malignancy. It potentially participates in glioma biology by affecting extracellular regulation, subcellular trafficking, and immune escape. Additionally, high KCNN4 expression was correlated with poor survival outcomes of patients. The results can shed new light on the mechanisms of glioma progression, and provide a potential therapeutic target for treating gliomas.

A Systematic Immune and Prognostic Analysis of CD48 Interaction with Tumor Microenvironment in Pan-Cancer

Background

The cluster of differentiation 48 (CD48) is a member of the signaling lymphocyte activation molecule family, constitutively expressed on most hematopoietic cells. CD48 was reported to affect immune regulation in certain tumors, thereby influencing tumor development and prognosis, but its impact on the prognosis and immune infiltration in pan-cancer remains unclear.

Material and Methods

We systematically analyzed the raw data from The Cancer Genome Atlas (TCGA), Tumor Immune Estimation Resource (TIMER), and Tumor Immune Dysfunction and Exclusion (TIDE) databases. Initially, we investigated the differences in CD48 expression between pan-cancer and adjacent normal tissues. Then, the correlation analysis of CD48 with tumor mutational burden (TMB), microsatellite instability (MSI), tumor microenvironment (TME), and immune-related genes was evaluated. Moreover, bioinformatics tools: ESTIMATE and gene set enrichment analysis (GSEA) were used for tumor immunology analysis in pan-cancer. We performed validation studies including quantitative real-time PCR (qPCR) and Western blotting.

Results

Differential analysis revealed that CD48 was significantly altered in pan-cancer as compared with normal tissues. Meanwhile, the survival analysis demonstrated that CD48 strongly correlated with overall survival (OS), disease-free interval (DFI), progression-free interval (PFI), and disease-specific survival (DSS), indicating its crucial role in the tumor patients' prognosis. CD48 expression was also associated with TMB and MSI levels in 17 and 14 types of pan-cancers, respectively. Moreover, CD48 was linked to immune infiltrating cells and stromal components in the TME.

Conclusion

Concludingly, patients with pan-cancer may benefit from evaluating CD48 as a prognostic and immunotherapy response biomarker.

Non-conducting functions of potassium channels in cancer and neurological disease

Cancer and neurodegenerative disease, albeit fundamental differences, share some common pathogenic mechanisms. Accordingly, both conditions are associated with aberrant cell proliferation and migration. Here, we review the causative role played by potassium (K+) channels, a fundamental class of proteins, in cancer and neurodegenerative disease. The concept that emerges from the review of the literature is that K+ channels can promote the development and progression of cancerous and neurodegenerative pathologies by dysregulating cell proliferation and migration. K+ channels appear to control these cellular functions in ways that not necessarily depend on their conducting properties and that involve the ability to directly or indirectly engage growth and survival signaling pathways. As cancer and neurodegenerative disease represent global health concerns, identifying commonalities may help understand the molecular basis for those devastating conditions and may facilitate the design of new drugs or the repurposing of existing drugs.

Uncovering the Achilles heel of genetic heterogeneity: machine learning-based classification and immunological properties of necroptosis clusters in Alzheimer's disease

Background

Alzheimer's disease (AD) is an age-associated neurodegenerative disease, and the currently available diagnostic modalities and therapeutic agents are unsatisfactory due to its high clinical heterogeneity. Necroptosis is a common type of programmed cell death that has been shown to be activated in AD.

Methods

In this study, we first investigated the expression profiles of necroptosis-related genes (NRGs) and the immune landscape of AD based on GSE33000 dataset. Next, the AD samples in the GSE33000 dataset were extracted and subjected to consensus clustering based upon the differentially expressed NRGs. Key genes associated with necroptosis clusters were identified using Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm, and then intersected with the key gene related to AD. Finally, we developed a diagnostic model for AD by comparing four different machine learning approaches. The discrimination performance and clinical relevance of the diagnostic model were assessed using various evaluation metrics, including the nomogram, calibration plot, decision curve analysis (DCA), and independent validation datasets.

Results

Aberrant expression patterns of NRGs and specific immune landscape were identified in the AD samples. Consensus clustering revealed that patients in the GSE33000 dataset could be classified into two necroptosis clusters, each with distinct immune landscapes and enriched pathways. The Extreme Gradient Boosting (XGB) was found to be the most optimal diagnostic model for the AD based on the predictive ability and reliability of the models constructed by four machine learning approaches. The five most important variables, including ACAA2, BHLHB4, CACNA2D3, NRN1, and TAC1, were used to construct a five-gene diagnostic model. The constructed nomogram, calibration plot, DCA, and external independent validation datasets exhibited outstanding diagnostic performance for AD and were closely related with the pathologic hallmarks of AD.

Conclusion

This work presents a novel diagnostic model that may serve as a framework to study disease heterogeneity and provide a plausible mechanism underlying neuronal loss in AD.

Potassium channels, tumorigenesis and targeted drugs

Potassium channels play an important role in human physiological function. Recently, various molecular mechanisms have implicated abnormal functioning of potassium channels in the proliferation, migration, invasion, apoptosis, and cancer stem cell phenotype formation. Potassium channels also mediate the association of tumor cells with the tumor microenvironment. Meanwhile, potassium channels are important targets for cancer chemotherapy. A variety of drugs exert anti-cancer effects by modulating potassium channels in tumor cells. Therefore, there is a need to understand how potassium channels participate in tumor development and progression, which could reveal new, novel targets for cancer diagnosis and treatment. This review summarizes the roles of voltage-gated potassium channels, calcium-activated potassium channels, inwardly rectifying potassium channels, and two-pore domain potassium channels in tumorigenesis and the underlying mechanism of potassium channel-targeted drugs. Therefore, the study lays the foundation for rational and effective drug design and individualized clinical therapeutics.

Potassium channels: Novel targets for tumor diagnosis and chemoresistance

In recent years, the role of potassium channels in tumors has been intensively studied. Potassium channel proteins are widely involved in various physiological and pathological processes of cells. The expression and dysfunction of potassium channels are closely related to tumor progression. Potassium channel blockers or activators present antitumor effects by directly inhibiting tumor growth or enhancing the potency of classical antitumor agents in combination therapy. This article reviews the mechanisms by which potassium channels contribute to tumor development in various tumors in recent years, introduces the potential of potassium channels as diagnostic targets and therapeutic means for tumors, and provides further ideas for the proper individualized treatment of tumors.

The Ion Channel Gene KCNAB2 Is Associated with Poor Prognosis and Loss of Immune Infiltration in Lung Adenocarcinoma

The malignancy with the greatest global mortality rate is lung cancer. Lung adenocarcinoma (LUAD) is the most common subtype. The evidence demonstrated that voltage-gated potassium channel subunit beta-2 (KCNAB2) significantly participated in the initiation of colorectal cancer and its progression. However, the biological function of KCNAB2 in LUAD and its effect on the tumor immune microenvironment are still unknown. In this study, we found that the expression of KCNAB2 in tissues of patients with LUAD was markedly downregulated, and its downregulation was linked to accelerated cancer growth and poor clinical outcomes. In addition, low KCNAB2 expression was correlated with a deficiency in immune infiltration. The mechanism behind this issue might be that KCNAB2 influenced the immunological process such that the directed migration of immune cells was affected. Furthermore, overexpression of KCNAB2 in cell lines promoted the expression of CCL2, CCL3, CCL4, CCL18, CXCL9, CXCL10, and CXCL12, which are necessary for the recruitment of immune cells. In conclusion, KCNAB2 may play a key function in immune infiltration and can be exploited as a predictive biomarker for evaluating prognosis and a possible immunotherapeutic target.

Predicting prognosis and immunotherapeutic response of clear cell renal cell carcinoma

Immune checkpoint inhibitors have emerged as a novel therapeutic strategy for many different tumors, including clear cell renal cell carcinoma (ccRCC). However, these drugs are only effective in some ccRCC patients, and can produce a wide range of immune-related adverse reactions. Previous studies have found that ccRCC is different from other tumors, and common biomarkers such as tumor mutational burden, HLA type, and degree of immunological infiltration cannot predict the response of ccRCC to immunotherapy. Therefore, it is necessary to further research and construct corresponding clinical prediction models to predict the efficacy of Immune checkpoint inhibitors. We integrated PBRM1 mutation data, transcriptome data, endogenous retrovirus data, and gene copy number data from 123 patients with advanced ccRCC who participated in prospective clinical trials of PD-1 inhibitors (including CheckMate 009, CheckMate 010, and CheckMate 025 trials). We used AI to optimize mutation data interpretation and established clinical prediction models for survival (for overall survival AUC: 0.931; for progression-free survival AUC: 0.795) and response (ORR AUC: 0.763) to immunotherapy of ccRCC. The models were internally validated by bootstrap. Well-fitted calibration curves were also generated for the nomogram models. Our models showed good performance in predicting survival and response to immunotherapy of ccRCC.