JunD/AP-1 Antagonizes the Induction of DAPK1 To Promote the Survival of v-Src-Transformed Cells

Tumor Suppressor DAPK1 Catalyzes Adhesion Assembly on Rigid but Anoikis on Soft Matrices

Cancer cells normally grow on soft surfaces due to impaired mechanosensing of the extracellular matrix rigidity. Upon restoration of proper mechanosensing, cancer cells undergo apoptosis on soft surfaces (anoikis) like most normal cells. However, the link between mechanosensing and activation of anoikis is not clear. Here we show that death associated protein kinase 1 (DAPK1), a tumor suppressor that activates cell death, is directly linked to anoikis activation through rigidity sensing. We find that when rigidity sensing is decreased through inhibition of DAPK1 activity, cells are transformed for growth on soft matrices. Further, DAPK1 catalyzes matrix adhesion assembly and is part of adhesions on rigid surfaces. This pathway involves DAPK1 phosphorylation of tropomyosin1.1, the talin1 head domain, and tyrosine phosphorylation of DAPK1 by Src. On soft surfaces, DAPK1 rapidly dissociates from the adhesion complexes and activates apoptosis as catalyzed by PTPN12 activity and talin1 head. Thus, DAPK1 is important for adhesion assembly on rigid surfaces and the activation of anoikis on soft surfaces through its binding to rigidity-sensing modules.

The Role of Autophagy in Tumor Immune Infiltration in Colorectal Cancer

Objective. This study is aimed at exploring the association between autophagy and tumor immune infiltration (TII) in colorectal cancer (CRC). Methods and Materials. We downloaded the transcriptome profiling and clinical data for CRC from The Cancer Genome Atlas (TCGA) database and obtained the normal colon transcriptome profiling data from Genotype-Tissue Expression Project (GTEx) database. The list of autophagy-related signatures was obtained from the Human Autophagy Database. We isolated the autophagy-related genes from the CRC gene expression matrix and constructed an autophagy-related prognostic (ARP) risk model. Then, we constructed a multiROC curve to validate the prognostic ability of the ARP risk model. CIBERSORT was used to determine the fractions of 22 immune cells in each CRC sample, and the association between these TII cells and CRC clinical variables was further investigated. Finally, we estimated the association of 3 hub-ARP signatures and 20 different types of TII cell distribution. Results. We classified 447 CRC patients into 224 low-risk and 223 high-risk patients using the median ARP risk score. According to the univariate survival test results, except for gender ( $P=0.672$ ), age ( $P=0.008$ ), cancer stage, and pathological stage T, M, and N were closely correlated with the prognosis of CRC patients ( $P<0.001$ ). Multivariate survival analysis results indicate that age and rescore were the only independent prognostic indicators with significant differences ( $P<0.05$ ). After merging the immune cell distribution (by CIBERSORT) with the CRC clinical data, the results indicate that activated macrophage M0 cells exhibited the highest clinical response, which included cancer stage and stage T, N, and M. Additionally, six immune cells were closely associated with cancer stage, including regulatory T cells (Tregs), gamma delta T cells, follicular helper T cells, activated memory CD4 T cells, activated NK cells, and resting dendritic cells. Finally, we evaluated the correlation of ARP signatures with TII cell distribution. Compared with the other correlation, NRG1 and plasma cells (↑), risk score and macrophage M1 (↑), NRG1 and dendritic cell activated (↑), CDKN2A and T cell CD4 memory resting (↓), risk score and T cell CD8 (↑), risk score and T cell CD4 memory resting (↓), and DAPK1 and T cell CD4 memory activated (↓) exhibited a stronger association ( $P<0.0001$ ). Conclusions. In summary, we explored the correlation between the risk of autophagy and the TII microenvironment in CRC patients. Furthermore, we integrated different CAR signatures with tumor-infiltrating immune cells and found robust associations between different levels of CAR signature expression and immune cell infiltrating density.

A Tale of Two States: Normal and Transformed, With and Without Rigidity Sensing

For many years, major differences in morphology, motility, and mechanical characteristics have been observed between transformed cancer and normal cells. In this review, we consider these differences as linked to different states of normal and transformed cells that involve distinct mechanosensing and motility pathways. There is a strong correlation between repeated tissue healing and/or inflammation and the probability of cancer, both of which involve growth in adult tissues. Many factors are likely needed to enable growth, including the loss of rigidity sensing, but recent evidence indicates that microRNAs have important roles in causing the depletion of growth-suppressing proteins. One microRNA, miR-21, is overexpressed in many different tissues during both healing and cancer. Normal cells can become transformed by the depletion of cytoskeletal proteins that results in the loss of mechanosensing, particularly rigidity sensing. Conversely, the transformed state can be reversed by the expression of cytoskeletal proteins-without direct alteration of hormone receptor levels. In this review, we consider the different stereotypical forms of motility and mechanosensory systems. A major difference between normal and transformed cells involves a sensitivity of transformed cells to mechanical perturbations. Thus, understanding the different mechanical characteristics of transformed cells may enable new approaches to treating wound healing and cancer.

Transregulation of microRNA miR-21 promoter by AP-1 transcription factor in cervical cancer cells

Background

Gene expression profiles have demonstrated that miR-21 expression is altered in almost all types of cancers and it has been classified as an oncogenic microRNA. Persistent HPV infection is the main etiologic agent in cervical cancer and induces genetic instability, including disruption of microRNA gene expression. In the present study, we analyzed the underlying mechanism of how AP-1 transcription factor can active miR-21 gene expression in cervical cancer cells.

Methods

To identify that c-Fos and c-Jun regulate the expression of miR-21 we performed RT-qPCR and western blot assays. We analyzed the interaction of AP-1 with miR-21 promoter by EMSA and ChIP assays and determined the mechanism of its regulation by reporter construct plasmids. We identified the nuclear translocation of c-Fos and c-Jun by immunofluorescence microscopy assays.

Results

We demonstrated that c-Fos and c-Jun proteins are expressed and regulate the expression of miR-21 in cervical cancer cells. DNA sequence analysis revealed the presence of AP-1 DNA-binding sites in the human miR-21 promoter region. EMSA analyses confirmed the interactions of the miR-21 upstream transcription factor AP-1. ChIP assays further showed the binding of c-Fos to AP-1 sequences from the miR-21 core promoter in vivo. Functional analysis of AP-1 sequences of miR-21 in reporter plasmids demonstrated that these sequences increase the miR-21 promoter activation.

Conclusions

Our findings suggest a physical interaction and functional cooperation between AP-1 transcription factor in the miR-21 promoter and may explain the effect of AP-1 on miR-21 gene expression in cervical cancer cells.