DAPK2 activates NF-κB through autophagy-dependent degradation of I-κBα during thyroid cancer development and progression

The role of DAPK2 as a key regulatory element in various human cancers: a systematic review

Cancer is considered the uncontrolled growth and spread of cells into neighboring tissues, a process governed at the molecular level by many different factors, including abnormalities in the protein family's death-associated kinase (DAPK). DAPK2 is a member of the DAPK protein family, which plays essential roles in several cellular processes. DAPK2 acts as a tumor suppressor, interacting with several proteins, such as TNF, IFN, etc. during apoptosis and autophagy. Expression of DAPK2 causes changes in the structure of the cell, ultimately leading to cell death by apoptosis. In this essay, studies are obtained from Scopus, PubMed, and the Web of Science. According to these investigations, DAPK2 activates autophagy by interacting with AMPK, mTORC1, and p73. Furthermore, DAPK2 induces apoptosis pathway via interacting with the p73 family and JNK. In general, due to the vital role of DAPK2 in cell physiology and its effect on various factors and signaling pathways, it can be a potent target in the treatment of various cancers, including gastric, ovarian, breast, and other prominent cancers.

The new insights into autophagy in thyroid cancer progression

In recent decades, the incidence of thyroid cancer keeps growing at a shocking rate, which has aroused increasing concerns worldwide. Autophagy is a fundamental and ubiquitous biological event conserved in mammals including humans. Basically, autophagy is a catabolic process that cellular components including small molecules and damaged organelles are degraded for recycle to meet the energy needs, especially under the extreme conditions. The dysregulated autophagy has indicated to be involved in thyroid cancer progression. The enhancement of autophagy can lead to autophagic cell death during the degradation while the produced energies can be utilized by the rest of the cancerous tissue, thus this influence could be bidirectional, which plays either a tumor-suppressive or oncogenic role. Accordingly, autophagy can be suppressed by therapeutic agents and is thus regarded as a drug target for thyroid cancer treatments. In the present review, a brief description of autophagy and roles of autophagy in tumor context are given. We have addressed summary of the mechanisms and functions of autophagy in thyroid cancer. Some potential autophagy-targeted treatments are also summarized. The aim of the review is linking autophagy to thyroid cancer, so as to develop novel approaches to better control cancer progression.

Exosomal miR-133a-3p Derived from BMSCs Alleviates Cerebral Ischemia-Reperfusion Injury via Targeting DAPK2

Background

Cerebral ischemia-reperfusion (CI/R) injury is a subtype of complication after treatment of ischemic stroke. It has been reported that exosomes derived from BMSCs could play an important role in CI/R injury. However, whether BMSCs-derived exosomes could regulate CI/R injury via carrying miRNAs remains to be further explored.

Methods

RNA sequencing was performed to identify the differentially expressed miRNAs. To mimic CI/R in vitro, SH-SY5Y cells were exposed to oxygen glucose deprivation/reoxygenation (OGD/R). The viability of SH-SY5Y cells was tested by CCK8 assay, and TUNEL staining was performed to detect the cell apoptosis.

Results

MiR-133a-3p was identified to be reduced in exosomes derived from the plasma of patients with IS. Upregulation of miR-133a-3p significantly reversed OGD/R-induced SH-SY5Y cell growth inhibition. Consistently, BMSCs-derived exosomal miR-133a-3p could restore OGD/R-decreased SH-SY5Y cell proliferation via inhibiting apoptosis. Meanwhile, DAPK2 was a direct target of miR-133a-3p. In addition, OGD/R notably upregulated the level of DAPK2 and weakened the expressions of p-Akt and p-mTOR in SH-SY5Y cells, whereas exosomal miR-133a-3p derived from BMSCs notably reversed these phenomena. Exosomal miR-133a-3p derived from BMSCs could reverse OGD/R-induced cell apoptosis via inhibiting autophagy. Furthermore, exosomal miR-133a-3p derived from BMSCs markedly alleviated the symptom of CI/R injury in vivo.

Conclusion

Exosomal miR-133a-3p derived from BMSCs alleviates CI/R injury via targeting DAPK2/Akt signaling. Thus, our study might shed new light on discovering new strategies against CI/R injury.

Identification and Validation of Anoikis-Related Signatures for Predicting Prognosis in Lung Adenocarcinoma with Machine Learning

Background

Lung adenocarcinoma (LUAD) is an aggressive cancer that has an extremely poor prognosis. As well as facilitating the detachment of cancer cells from the primary tumor site, anoikis plays an important role in cancer metastasis. Few studies to date, however, have examined the role of anoikis in LUAD, in patient prognosis.

Methods

A total of 316 anoikis-related genes (ANRGs) integrated from Genecards and Harmonizome portals. LUAD transcriptome data were retrieved from the Genotype-Tissue Expression Project (GEO) and The Cancer Genome Atlas (TCGA). Anoikis-related prognostic genes (ANRGs) were primarily screened by univariate Cox regression. All ANRGs were included in the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model to construct the powerful prognostic signature. This signature was validated and assessed using the Kaplan-Meier method as well as univariate and multivariate Cox regression analyses. Anoikis-related regulators of risk score were identified using a XG-boost machine learning model. The expression of ITGB4 protein was examined in a ZhengZhou University (ZZU) tissue cohort by immunohistochemistry, and the potential mechanisms of action of ITGB4 in LUAD were explored by GO, KEGG, and ingenuity pathway analyses and by GSEA.

Results

A risk score signature was constructed based on eight ANRGs, with high risk scores found to closely correlate with unfavorable clinical features. ITGB4 expression may be associated with 5-year over survival, with immunohistochemistry showed that the expression of ITGB4 was higher in LUAD than in nontumor tissues. Enrichment analysis suggested that ITGB4 may promote LUAD development by targeting E2F, MYC, and oxidative phosphorylation signaling pathways.

Conclusion

Our anoikis-related signature from RNA-seq data may be a novel prognostic biomarker in patients with LUAD. It may help physicians develop personalized LUAD treatments in clinical practice. Moreover, ITGB4 may affect the development of LUAD through the oxidative phosphorylation pathway.

Non-Apoptotic Programmed Cell Death in Thyroid Diseases

Thyroid disorders are among the most common endocrinological conditions. As the prevalence of thyroid diseases increases annually, the exploration of thyroid disease mechanisms and the development of treatments are also gradually improving. With the gradual advancement of therapies, non-apoptotic programmed cell death (NAPCD) has immense potential in inflammatory and neoplastic diseases. Autophagy, pyroptosis, ferroptosis, and immunogenic cell death are all classical NAPCD. In this paper, we have compiled the recent mechanistic investigations of thyroid diseases and established the considerable progress by NAPCD in thyroid diseases. Furthermore, we have elucidated the role of various types of NAPCD in different thyroid disorders. This will help us to better understand the pathophysiology of thyroid-related disorders and identify new targets and mechanisms of drug resistance, which may facilitate the development of novel diagnostic and therapeutic strategies for patients with thyroid diseases. Here, we have reviewed the advances in the role of NAPCD in the occurrence, progression, and prognosis of thyroid diseases, and highlighted future research prospects in this area.

A seven-autophagy-related gene signature for predicting the prognosis of differentiated thyroid carcinoma

Background

Numerous studies have implicated autophagy in the pathogenesis of thyroid carcinoma. This investigation aimed to establish an autophagy-related gene model and nomogram that can help predict the overall survival (OS) of patients with differentiated thyroid carcinoma (DTHCA).

Methods

Clinical characteristics and RNA-seq expression data from TCGA (The Cancer Genome Atlas) were used in the study. We also downloaded autophagy-related genes (ARGs) from the Gene Set Enrichment Analysis website and the Human Autophagy Database. First, we assigned patients into training and testing groups. R software was applied to identify differentially expressed ARGs for further construction of a protein-protein interaction (PPI) network for gene functional analyses. A risk score-based prognostic risk model was subsequently developed using univariate Cox regression and LASSO-penalized Cox regression analyses. The model’s performance was verified using Kaplan-Meier (KM) survival analysis and ROC curve. Finally, a nomogram was constructed for clinical application in evaluating the patients with DTHCA. Finally, a 7-gene prognostic risk model was developed based on gene set enrichment analysis.

Results

Overall, we identified 54 differentially expressed ARGs in patients with DTHCA. A new gene risk model based on 7-ARGs (CDKN2A, FGF7, CTSB, HAP1, DAPK2, DNAJB1, and ITPR1) was developed in the training group and validated in the testing group. The predictive accuracy of the model was reflected by the area under the ROC curve (AUC) values. Univariate and multivariate Cox regression analysis indicated that the model could independently predict the prognosis of patients with THCA. The constrained nomogram derived from the risk score and age also showed high prediction accuracy.

Conclusions

Here, we developed a 7-ARG prognostic risk model and nomogram for differentiated thyroid carcinoma patients that can guide clinical decisions and individualized therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02590-6.