KCNN4 Antibodies

Intermediate conductance calcium-activated potassium channel protein 4 (KCNN4)

Forms a voltage-independent potassium channel that is activated by intracellular calcium (PubMed:26148990). Activation is followed by membrane hyperpolarization which boosts calcium influx.

Required for maximum calcium influx and proliferation throughout the reactivation of innocent T-cells (PubMed:17157250, PubMed:18796614). Plays a role in the late stages of EGF-induced macropinocytosis (PubMed:24591580).

Gene Information

Human
Gene Name:	KCNN4
Uniprot:	O15554
Entrez:	3783

Family

Belongs to:
potassium channel KCNN family

Alternative Names

hIKCa1; hKCa4; hSK4; IK1; IKCa1; intermediate conductance calcium-activated potassium channel protein 4; KCa3.1IKCA1; KCa4; KCA4SKCa4; potassium intermediate/small conductance calcium-activated channel, subfamilyN, member 4; putative erythrocyte intermediate conductance calcium-activated potassiumGardos channel; Putative Gardos channel; SK4SKCa 4

Molecular Weight

Mass (kDA):
47.696 kDA

Genomic Context

Human
Location:	19q13.31
Sequence:	19; NC_000019.10 (43766533..43782139, complement)

Tissue Specificity

Widely expressed in non-excitable tissues.

Subcellular Localizations

Cell membrane; Multi-pass membrane protein.

Diseases

• Fibrosis
• Cystic Fibrosis
• Anemia, Sickle Cell
• Autoimmune Reaction
• Dehydration
• Malignant Neoplasms
• Autoimmune Diseases
• Retinoblastoma
• Inflammation
• Infarction
• Brain Injuries
• Anemia
• Multiple Sclerosis

• Neoplasms
• Cardiovascular Diseases
• Diarrhea
• Edema
• Nervousness
• Atherosclerosis
• Hyperplasia

Interacting Proteins

• CFTR
• PHPT1

Pathways

• Secretion
• Transport
• Cell Proliferation
• Cell Activation
• Cell Cycle
• Ion Transport
• Localization
• Membrane Hyperpolarization
• Pathogenesis
• Cell Migration
• Cell Differentiation
• Immune Response
• Cytokine Production

• T Cell Activation
• Lymphocyte Activation
• Translation
• Endocytosis
• Cell Death
• Macrophage Activation
• S Phase

PTMs

• Phosphorylation
• Dephosphorylation

• Nitration
• Ubiquitination

• Nitrosylation

For details, visit:
bosterbio.com/bosterbio-gene-info-cards/KCNN4

Boster Bio: Best Uses Of The KCNN4 Marker

Proper controls are an important tip for optimizing Boster Bio. Statistics were used to assess KCNN4 expression in tumors and in control tissues. This will allow you to make better decisions and improve your research. But, every researcher runs into difficulties while performing experiments. These problems are usually due to poor control. Boster Bio troubleshooting guides will assist you in identifying and eliminating them.

The KCNN4 might be an accurate indicator of KIRC prognosis

KCNN4 expression in tumors and normal tissues was assessed and associated with different TIC types. Expression of KCNN4 was associated positive and negative relationships with resting memory CD4 T mast cells, NK cells, as well as regulatory T and B cells. Expression of KCNN4 was also associated with tumor grade and T or M classification. The authors conclude that KCNN4 could be a reliable indicator of KIRC prognosis.

The KCNN4 potassium channel is a voltage-dependent channel, activated by intracellular calcium. It is expressed in various types of cancer and has been strongly associated with tumor invasion, metastasis, and epithelial-mesenchymal transition (TME). The stromal components of the TME are believed to regulate KCNN4 expression.

This study showed that knocking down the KCNN4 gene slowed the growth of PTCand KTC-1 cell line lines. Moreover, knockdown KCNN4 significantly reduced the number cell death and PTC cells. KCNN4 could be a reliable indicator of KIRC prognosis. These findings will require further research.

This study identified 173 genes, 25 microRNAs and 136 mRNAs that are closely related to KIRC. By using a K-M survival analysis we identified 83 genes that are extremely relevant to the survival of KIRC patients. PVT1, AC005154.1 and hsa–miR-204-5p were three of the most significant miRNAs or lncRNAs that are associated with overall survival. KCNN4 is the most significant miRNA of these genes.

Moreover, KCNN4 expression was significantly higher in BRAF-like versus RAS-like KIRC groups. The authors performed an qPCR multiplex (qPCR) and western blots to confirm these findings. Additionally, KCNN4 expression was significantly reduced in a wound-healing assay and decreased PTC migration.

The authors utilized the K-M survival curve analysis to determine whether KCNN4 was an accurate biomarker of the prognosis of KIRC. The relationship between immune cells and the progression of tumors was also examined by the authors. The findings suggested that KCNN4 could be a reliable indicator of KIRC prognosis. However, further research is needed to determine its precise function in KIRC prognosis.

Alongside KCNN4, other gene expression profiles were also identified. The KIAA1324 gene, LINC00894 and BCL6 were positive correlations with mast cells in rest. They also had positive correlations with PDCD1 and BCL6. It is interesting to note that MME and KIAA1324 were found to have low levels of expression in KIRC.

Analysis of statistical significance of KCNN4 expression levels in tumor tissue as well as control tissue

Drug resistance is one of the most significant reasons for a poor prognosis for Ovarian cancer. To identify factors associated with drug resistance, it is vital to comprehend the way KCNN4 expression levels are connected to the tumor of a patient. In this study, 51 OC tumor specimens were immunohistochemically analyzed, and public data from The Cancer Genome Atlas cohort and Oncomine database were obtained. Expression of KCNN3 was lower in OC tumor tissues than in healthy tissues, and lower levels of KCNN3 expression were linked to a shorter overall cancer-free survival.

In the current study, we discovered that the mRNA levels of KCNN3 were significantly associated with poor DFS and OS in patients with OC, and that downregulation of KCNN3 was associated with a lower overall survival in 489 patients. Additionally, we found a direct correlation between lower CA125 and decreased KCNN3 in 395 patients suffering from OC.

We also observed a correlation between KCNN4 and S100A14 mRNA levels. However, we did not observe a direct correlation between CNA status or KCNN4 expression. S100A14, KCNN4 showed a negative correlation to DNA methylation. These two factors were incorporated in our statistical analysis to determine if the genes are functionally related.

Six genes were examined in this study: ADCY3, AMFR CCDC127 HSPA4, MRPS18C, and CCDC127. These genes were directly linked with 25 oncogenes, 18 tumor suppressors, and S100A14. The results of this study are encouraging. Additionally, it could aid in the identification of drugs that target this gene.

This study suggests that KCNN4 expression could be an independent prognostic indicator. Additionally, S100A14 and KCNN4 expression levels were both independently connected with overall survival. These two factors could serve as potential indicators of Ovarian cancer. These genes may play a role in tumor growth and chemotaxis. We conclude that KCNN4 is an important biomarker for ovarian cancer.

Our findings also indicate that KCNN4 and S100A14 are independent markers of the recurrence. Interestingly, KCNN4 and S100A14 expression levels are correlated in six datasets that include GSE26193. This suggests that the two proteins are independent prognostic indicators of the recurrence. The authors recommend investigating both genes together.

Researchers also investigated the effects of an inherited variant of OC on drug resistance in large numbers of patients. In addition to KCNN4, KCNN3 expression levels were strongly associated with p53 mutations in patients with OC. Moreover, KCNN4 is linked to the expression of mTOR, an important signaling protein that plays a role in the apoptotic cell cycle.

A previous study conducted by Berchuck A has compared gene expression in melanoma tissue as well as the control tissue. They found that both tumors had the same levels of KCNN4. In addition, tumor cells that expressed KCNN4 were more likely to grow over non-malignant tissues. This study is an important step in understanding how the KCNN4 gene contributes to the development of melanoma.

Boster Bio optimization tips

The Boster Bio optimization guides for KCNN4 markers will help you improve the performance of your experiments. These guides will address every question you have and help optimize your experiments for the most efficient results. Every researcher has to deal with a variety of problems throughout their research. However, the appropriate controls and optimization strategies can eliminate many of these problems. The strategies in these guides are applicable to all scientists from various disciplines.