AHNAK2 Is Associated with Poor Prognosis and Cell Migration in Lung Adenocarcinoma

AHNAK2 Regulates NF-κB/MMP-9 Signaling to Promote Pancreatic Cancer Progression

Early metastasis of pancreatic cancer (PaC) is a major cause of its high mortality rate. Previous studies have shown that AHNAK2 is involved in the progression of some tumors and is predicted to be an independent prognostic factor for PaC; however, the specific mechanisms through which AHNAK2 regulates PaC remain unclear. In this study, we examined the role of AHNAK2 in PaC and its potential molecular mechanisms. AHNAK2 mRNA and protein expression in PaC tissues and cells were measured using qRT-PCR and western blot analysis. After AHNAK2 knockdown using small interfering RNA, PaC cells were subjected to CCK-8 scratch, and Transwell assays to assess cell proliferation, migration, and invasion, respectively. Furthermore, the validation of the mechanistic pathway was achieved by western blot analysis. AHNAK2 mRNA and protein levels were up-regulated in PaC and silencing AHNAK2 significantly inhibited the proliferation, migration, and invasion of PaC cells. Mechanistically, AHNAK2 knockdown decreased the expression of phosphorylated p65, phosphorylated IκBα, and matrix metalloproteinase-9 (MMP-9), suggesting that activation of the NF-κB/MMP-9 signaling pathway was inhibited. Importantly, activation of NF-κB reversed the effects of AHNAK2 knockdown. Our findings indicate that AHNAK2 promotes PaC progression through the NF-kB/MMP-9 pathway and provides a theoretical basis for targeting AHNAK2 for the treatment of PaC.

Integrin β4 Regulates Cell Migration of Lung Adenocarcinoma Through FAK Signaling

The role of the integrin family in malignancy has received increasing attention. Many studies have confirmed that ITGB4 could activate multiple signal pathways and promote cell migration in various cancers. However, the regulatory role of integrin β4 (ITGB4) in lung adenocarcinoma (LUAD) is still unclear. Examination of the expression or survival analysis of ITGB4 in cells, pathological samples, and bioinformatics lung adenocarcinoma databases showed ITGB4 was highly expressed in LUAD and significantly associated with poor prognosis. Small interfering RNA and plasmids were performed to investigate the effect of changes in ITGB4 expression on lung adenocarcinoma. Focal adhesion kinase (FAK) inhibitor defactinib was used to further explore the molecular mechanism of ITGB4. The results showed depletion of ITGB4 inhibited migration and activation of FAK signaling pathways in lung adenocarcinoma cells. Moreover, increased ITGB4 expression activated FAK signaling and promoted cell migration, which can be reversed by defactinib. In addition, ITGB4 could interact with FAK in lung adenocarcinoma cells. ITGB4 may promote cell migration of lung adenocarcinoma through FAK signaling pathway and has the potential to be a biomarker for lung adenocarcinoma.

AHNAK2 Promotes the Progression of Differentiated Thyroid Cancer through PI3K/AKT Signaling Pathway

AIMS

AHNAK2 may be used as a candidate marker for TC diagnosis and treatment.

BACKGROUND

Thyroid cancer (TC) is the most frequent malignancy in endocrine carcinoma, and the incidence has been increasing for decades.

OBJECTIVE

To understand the molecular mechanism of DTC, we performed next-generation sequencing (NGS) on 79 paired DTC tissues and normal thyroid tissues. The RNA-sequencing (RNA-seq) data analysis results indicated that AHNAK nucleoprotein 2 (AHNAK2) was significantly upregulated in the thyroid cancer patient's tissue.

METHODS

We also analyzed AHNAK2 mRNA levels of DTC tissues and normal tissues from The Cancer Genome Atlas (TCGA). The association between the expression level of AHNAK2 and clinicopathological features was evaluated in the TCGA cohort. Furthermore, AHNAK2 gene expression was analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) in 40 paired DTC tissues and adjacent normal thyroid tissues. The receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic value of AHNAK2. For cell experiments in vitro, AHNAK2 was knocked down using small interfering RNA (siRNA), and the biological function of AHNAK2 in TC cell lines was investigated. The expression of AHNAK2 was significantly upregulated in both the TCGA cohort and the local cohort.

RESULTS

The analysis results of the TCGA cohort indicated that the upregulation of AHNAK2 was associated with tumor size (P < 0.001), lymph node metastasis (P < 0.001), and disease stage (P < 0.001). The area under the curve (AUC, TCGA: P < 0.0001; local validated cohort: P < 0.0001) in the ROC curve revealed that AHNAK2 might be considered a diagnostic biomarker for TC. The knockdown of AHNAK2 reduced TC cell proliferation, colony formation, migration, invasion, cell cycle, and induced cell apoptosis.

CONCLUSION

Furthermore, the protein levels of phospho-PI3 Kinase p85 and phospho-AKT were downregulated in the transfected TC cell. Our study results indicate that AHNAK2 may promote metastasis and proliferation of thyroid cancer through PI3K/AKT signaling pathway. Thus, AHNAK2 may be used as a candidate marker for TC diagnosis and treatment.

AHNAKs roles in physiology and malignant tumors

The AHNAK family currently consists of two members, namely AHNAK and AHNAK2, both of which have a molecular weight exceeding 600 kDa. Homologous sequences account for approximately 90% of their composition, indicating a certain degree of similarity in terms of molecular structure and biological functions. AHNAK family members are involved in the regulation of various biological functions, such as calcium channel modulation and membrane repair. Furthermore, with advancements in biological and bioinformatics technologies, research on the relationship between the AHNAK family and tumors has rapidly increased in recent years, and its regulatory role in tumor progression has gradually been discovered. This article briefly describes the physiological functions of the AHNAK family, and reviews and analyzes the expression and molecular regulatory mechanisms of the AHNAK family in malignant tumors using Pubmed and TCGA databases. In summary, AHNAK participates in various physiological and pathological processes in the human body. In multiple types of cancers, abnormal expression of AHNAK and AHNAK2 is associated with prognosis, and they play a key regulatory role in tumor progression by activating signaling pathways such as ERK, MAPK, Wnt, and MEK, as well as promoting epithelial-mesenchymal transition.

AHNAK2 is a biomarker and a potential therapeutic target of adenocarcinomas

Adenocarcinoma is the second largest histological type of cervical cancer, second only to cervical squamous cell carcinoma. At present, despite the clinical treatment strategies of cervical adenocarcinoma and cervical squamous cell carcinoma being similar, the outcome and prognosis of cervical adenocarcinoma are significantly poor. Therefore, it is urgent to find specific biomarker and therapeutic target for cervical adenocarcinoma. In this study, we aim to reveal and verify the potential biomarkers and therapeutic targets of cervical adenocarcinoma. Weighted correlation network analysis (WGCNA) reveals the differentially-expressed genes significantly related to the histological characteristics of the two cervical cancer subtypes. We select the genes with the top 20 significance for further investigation. Through microarray and immunohistochemical (IHC) analyses of a variety of tumor tissues, we find that among these 20 genes, AHNAK2 is highly expressed not only in cervical adenocarcinoma, but also in multiple of adenocarcinoma tissues, including esophagus, breast and colon, while not in normal gland tissues. In vitro, AHNAK2 knockdown significantly inhibits cell proliferation and migration of adenocarcinoma cell lines. In vivo, AHNAK2 knockdown significantly inhibits tumor progression and metastasis of various adenocarcinomas. RNA-sequencing and bioinformatics analyses suggest that the inhibitory effect of AHNAK2 knockdown on tumor progression is achieved by regulating DNA replication and upregulating Bim expression. Together, we demonstrate that AHNAK2 is a biomarker and a potential therapeutic target for adenocarcinomas.

Inhibition of AHNAK nucleoprotein 2 alleviates pulmonary fibrosis by downregulating the TGF-β1/Smad3 signaling pathway

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic and advanced interstitial lung disease with poor prognosis. AHNAK nucleoprotein 2 (AHNAK2) is a macromolecular protein that is important for cell migration and muscle membrane repair. The protein acts via epithelial-mesenchymal transition (EMT), which is a key mechanism in the pathogenesis of IPF. However, very few studies have elucidated the effect of AHNAK2 in the development of IPF. Therefore, we aimed to determine the role of AHNAK2 in IPF development.

METHODS

C57BL/6 mice were induced with bleomycin (BLM), while A549 and Beas-2b pulmonary epithelial cell lines were treated with TGF-β1 to induce IPF model. The expression of AHNAK2 was detected using immunohistochemistry (IHC) staining in vivo, and real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting (WB) in vitro. C57BL/6 mice were injected with adeno-associated virus (AAV)-sh NC or AAV-sh AHNAK2; the pulmonary function and EMT markers expression were measured in mice. The migratory abilities of the two transforming growth factor beta 1 (TGF-β1)-induced cell lines were examined using wound-healing and Transwell assays after transfection with si-NC, si-AHNAK2-1 and -2. EMT markers expression was detected using RT-qPCR and WB. Smad3 and phosphorylated-Smad3 of the two cells were examined using WB. Following Smad3 inhibition by Smad3 phosphorylation inhibitor (SIS3), TGF-β1-induced cell migration and EMT markers expression were evaluated again after different transfections.

RESULTS

AHNAK2 expression was higher in the IPF model than in the normal model in vivo and in vitro. Partial inhibition of AHNAK2 suppressed the EMT process and improved pulmonary ventilation and compliance in the mouse model of IPF. Similarly, knockdown of AHNAK2 suppressed the migration of pulmonary epithelial cells and reversed EMT. Furthermore, Smad3 of the two TGF-β1-induced cell lines was not activated when AHNAK2 was inhibited. When SIS3 inhibited the activation of Smad3, the suppression of AHNAK2 had no effect on A549 and Beas-2b, regardless of TGF-β1 induction.

CONCLUSIONS

Inhibition of AHNAK2 alleviates pulmonary fibrosis and partially reverses EMT by inhibiting the TGF-β1/Smad3 signaling pathway. Therefore, AHNAK2 is a potential therapeutic target for IPF.

Integrative Proteo-Genomic Analysis for Recurrent Survival Prognosis in Colon Adenocarcinoma

Background

The survival prognosis is the hallmark of cancer progression. Here, we aimed to develop a recurrence-related gene signature to predict the prognosis of colon adenocarcinoma (COAD).

Methods

The proteomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and genomic data from the cancer genomic maps [The Cancer Genome Atlas (TCGA)] dataset were analyzed to identify co-differentially expressed genes (cDEGs) between recurrence samples and non-recurrence samples in COAD using limma package. Functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was conducted. Univariate and multivariate Cox regressions were applied to identify the independent prognostic feature cDEGs and establish the signature whose performance was evaluated by Kaplan–Meier curve, receiver operating characteristic (ROC), Harrell’s concordance index (C-index), and calibration curve. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy. GSE17538 and GSE39582 were used for external validation. Quantitative real-time PCR and Western blot analysis were carried out to validate our findings.

Results

We identified 86 cDEGs in recurrence samples compared with non-recurrence samples. These genes were primarily enriched in the regulation of carbon metabolic process, fructose and mannose metabolism, and extracellular exosome. Then, an eight-gene-based signature (CA12, HBB, NCF1, KBTBD11, MMAA, DMBT1, AHNAK2, and FBLN2) was developed to separate patients into high- and low-risk groups. Patients in the low-risk group had significantly better prognosis than those in the high-risk group. Four prognostic clinical features, including pathological M, N, T, and RS model status, were screened for building the nomogram survival model. The PCR and Western blot analysis results suggested that CA12 and AHNAK2 were significantly upregulated, while MMAA and DMBT1 were downregulated in the tumor sample compared with adjacent tissues, and in non-recurrent samples compared with non-recurrent samples in COAD.

Conclusion

These identified recurrence-related gene signatures might provide an effective prognostic predictor and promising therapeutic targets for COAD patients.

FeCO3, constructing the network biomarkers using the inter-feature correlation coefficients and its application in detecting high-order breast cancer biomarkers

Aims:

This study aims to formulate the inter-feature correlation as the engineered features.

Background:

Modern biotechnologies tend to generate a huge number of characteristics of a sample, while an OMIC dataset usually has a few dozens or hundreds of samples due to the high costs of generating the OMIC data. So many bio-OMIC studies assumed the inter-feature independence and selected a feature with a high phenotype-association.

Objective:

However, many features are closely associated with each other due to their physical or functional interactions, which may be utilized as a new view of features.

Method:

This study proposed a feature engineering algorithm based on the correlation coefficients (FeCO3) by utilizing the correlations between a given sample and a few reference samples. A comprehensive evaluation was carried out for the proposed FeCO3 network features using 24 bio-OMIC datasets.

Result:

The experimental data suggested that the newly calculated FeCO3 network features tended to achieve better classification performances than the original features, using the same popular feature selection and classification algorithms. The FeCO3 network features were also consistently supported by the literature. FeCO3 was utilized to investigate the high-order engineered biomarkers of breast cancer, and detected the PBX2 gene (Pre-B-Cell Leukemia Transcription Factor 2) as one of the candidate breast cancer biomarkers. Although the two methylated residues cg14851325 (Pvalue=8.06e-2) and cg16602460 (Pvalue=1.19e-1) within PBX2 did not have statistically significant association with breast cancers, the high-order inter-feature correlations showed a significant association with breast cancers.

Conclusion:

The proposed FeCO3 network features calculated the high-order inter-feature correlations as novel features, and may facilitate the investigations of complex diseases from this new perspective. The source code is available in FigShare at 10.6084/m9.figshare.13550051 or the web site http://www.healthinformaticslab.org/supp/ .

High expression of miR-195 is related to favorable prognosis in cytogenetically normal acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) is a heterogeneous blood disease with poor treatment effect and high recurrence rate. With the deepening of non-coding RNA research, more and more miRNAs have been found to participate in various physiological processes of tumors. In this study, we tried to find the miRNA related to the prognosis of AML.

METHODS

Collect gene expression data and clinical information of AML patients in the Cancer Genome Atlas database for statistical analysis. The expression level of miR-195 of each patient was standardized by logCPM and then produced as a box plot according to subtype classification. TargetScan was used to predict the target genes of miR-195, and these genes were subjected to GO pathway enrichment analysis by Metascape. Differential miRNAs were screened through the DESeq2 package in the R language. Survival rates were estimated using the Kaplan-Meier method and the log-rank test. The multivariate Cox proportional hazard models of EFS and OS were established.

RESULTS

We found that the expression of miR-195 was the lowest in cytogenetically normal (CN-) AML, and high expression of miR-195 only promoted the prognosis of chemotherapy-only CN-AML patients (EFS: P = 0.016; OS: P = 0.035). Multivariate analysis showed that miR-195^high was a favorable and independent factor for CN-AML (both P < 0.05). Further analysis showed that miR-195 may affect signal transduction through ANHAK2 in AML.

CONCLUSION

We found that high expression of miR-195 can increase prognosis time of chemotherapy-only CN-AML patients, providing a new possibility for treatment.

Prognostic Impact of AHNAK2 Expression in Patients Treated with Radical Cystectomy

Data regarding expression levels of AHNAK2 in bladder cancer (BCa) have been very scarce. We retrospectively reviewed clinical data including clinicopathological features in 120 patients who underwent radical cystectomy (RC) for BCa. The expression levels of AHNAK2 in the specimens obtained by RC were classified as low expression (LE) or high expression (HE) by immunohistochemical staining. Statistical analyses were performed to compare associations between the two AHNAK2 expression patterns and the prognoses in terms of recurrence-free survival (RFS) and cancer-specific survival (CSS). A Kaplan-Meier analysis showed that patients with HE had a significantly worse RFS and CSS than those with LE (hazard ratio [HR]: 1.78, 95% confidence interval [CI]: 1.02-2.98, p = 0.027 and HR: 1.91, 95% CI: 1.08-3.38, p = 0.023, respectively). In a multivariate analysis, independent risk factors for worse RFS and CSS were shown as HE (HR: 1.96, 95% CI: 1.08-3.53, p = 0.026 and HR: 2.22, 95% CI: 1.14-4.31, p = 0.019, respectively) and lymph node metastasis (HR: 2.04, 95% CI: 1.09-3.84, p = 0.026 and HR: 1.19, 95% CI: 1.25-4.97, p = 0.009, respectively). The present study showed that AHNAK2 acts as a novel prognostic biomarker in patients with RC for BCa.

Identification of Monotonically Differentially Expressed Genes across Pathologic Stages for Cancers

Given the fact that cancer is a multistage progression process resulting from genetic sequence mutations, the genes whose expression values increase or decrease monotonically across pathologic stages are potentially involved in tumor progression. This may provide insightful clues about how human cancers advance, thereby facilitating more personalized treatments. By replacing the expression values of genes with their GeneRanks, we propose a procedure capable of identifying monotonically differentially expressed genes (MEGs) as the disease advances. Using three real-world gene expression data that cover three distinct cancer types-colon, esophageal, and lung cancers-the proposed procedure has demonstrated excellent performance in detecting the potential MEGs. To conclude, the proposed procedure can detect MEGs across pathologic stages of cancers very efficiently and is thus highly recommended.