Aldehyde dehydrogenase 1A1 (ALDH1A1) is a marker of cancer stem-like cells (CSCs), but knowledge about the molecular mechanism of ALDH1A1 in maintaining the properties of CSCs remains limited. ALDH1A1 immunohistochemistry was performed in esophageal squamous cell carcinoma (ESCC) tissues, Western blotting was used to detect relationship between ALDH1A1 and AKT or β-catenin. Subcutaneous transplantation of tumors and drug resistance, spherogenesis experiments were used to test the ESCC cell stemness. Co-IP and confocal were used to detected the co-localization of LADH1A1 and β-catenin. ALDH1A1 expression maintained the CSC properties of ESCC cells. It enhanced the chemo-resistance ability, clonogenicity, and spherogenesis in vitro and tumorigenicity in vivo. High ALDH1A1 expression is an adverse prognostic factor of ESCC patients. Small-molecule inhibitor NCT-501 down-regulates ALDH1A1 expression and inhibits the AKT-β-catenin signaling pathway. ALDH1A1 overexpression activates the AKT signaling pathway. ALDH1A1 interacts with β-catenin, co-localization in KYS-510 cells.

The homeotic protein SIX3 is a transcription factor vital for neurogenesis and has a bivalent promoter. We previously showed that SIX3 can be transcriptionally silenced by DNA hypermethylation, functions as a tumor suppressor gene, and inhibits human glioblastoma transcriptionally. Here, we show that the activation of epidermal growth factor (EGFR) induces DNA methylation of SIX3 promoter through the MAPK pathway. ERK, when activated, binds with ZNF263, consequently abrogating the ubiquitination of ZNF263 and leading to its stabilization. ZNF263 binds to the core promoter region of SIX3 and recruits the KAP1/HATS/DNMT corepressor complex to induce transcriptional silencing of SIX3 through H3K27me3 and methylation of SIX3 promoter. Activation of the EGFR-ZNF263 signaling axis in phenotypically normal astrocytes or glioblastoma cells triggers or enhances tumorigenic activities, while elevated expression of the EGFR-ZNF263 signaling components in glioblastoma tissues is associated with poor prognosis of the patients. Together, our findings demonstrate that epigenetic silencing of SIX3 is controlled by a sophisticated and highly ordered oncogenic signaling pathway and therefore provide new insights into initiation and progression of glioblastoma.

Migrasomes, a newly discovered organelle produced by migrating cells, are vesicles with membranous structure that form on the tips and intersections of retraction fibers (RFs). These structures are released into the extracellular environment or taken up by surrounding cells, mediating the release of cytoplasmic contents and intercellular communication. Retractosomes, a new type of small extracellular vesicles generated from broken-off RFs, are closely related to migrasomes in their physical location and origin, but were defined later. Despite their widespread existence in cells and biological organisms, little is known about the regulatory mechanisms underlying their formation and potential function. In this review, we provide an overview of the discovery, biogenesis, distribution, and functions of migrasomes and retractosomes, as well as their differences from exosomes.

Background. Syndecan-1 (SDC1/CD138) is a key cell surface adhesion molecule essential for maintaining cell morphology and the interactions with the surrounding microenvironment. SDC1 tumor immunoexpression may be increased or decreased in epithelial malignant neoplasms compared to that in adjacent non-neoplastic tissue, depending on the type of carcinoma, and it has been correlated with various clinicopathological parameters and patient prognosis. SDC1 expression is decreased in colorectal cancer (CRC) tissue, but the relationship between prognosis and SDC1 expression in CRC patients is controversial. Methods. In this study, SDC1 expression was detected in 65 adjacent non-neoplastic colorectal tissues, 477 CRCs, and 79 metastatic lymph nodes using tissue microarray. Results. The data show that SDC1 decreased in CRC tissues (p≤0.001) and metastatic lymph node tissues (p≤0.001) compared to that in adjacent non-neoplastic colorectal tissues. Loss of SDC1 protein expression is associated with poor overall (p<0.0001) and disease-free survival (p<0.0001), differentiation (p=0.017), stage (p≤0.001), and lymph node metastasis (p≤0.001) in CRC patients. Conclusions. These data suggest that the loss of SDC1 plays an important role in CRC malignant progression. Loss of SDC1 expression indicates poor prognosis in patients from northern China with CRC.

Background: Lymph node metastasis (LNM) significantly impacts the prognosis of individuals diagnosed with cervical cancer, as it is closely linked to disease recurrence and mortality, thereby impacting therapeutic schedule choices for patients. However, accurately predicting LNM prior to treatment remains challenging. Consequently, this study seeks to utilize digital pathological features extracted from histopathological slides of primary cervical cancer patients to preoperatively predict the presence of LNM.Methods: A deep learning (DL) model was trained using the Vision transformer (ViT) and recurrent neural network (RNN) frameworks to predict LNM. This prediction was based on the analysis of 554 histopathological whole‐slide images (WSIs) obtained from Qilu Hospital of Shandong University. To validate the model's performance, an external test was conducted using 336 WSIs from four other hospitals. Additionally, the efficiency of the DL model was evaluated using 190 cervical biopsies WSIs in a prospective set.Results: In the internal test set, our DL model achieved an area under the curve (AUC) of 0.919, with sensitivity and specificity values of 0.923 and 0.905, respectively, and an accuracy (ACC) of 0.909. The performance of the DL model remained strong in the external test set. In the prospective cohort, the AUC was 0.91, and the ACC was 0.895. Additionally, the DL model exhibited higher accuracy compared to imaging examination in the evaluation of LNM. By utilizing the transformer visualization method, we generated a heatmap that illustrates the local pathological features in primary lesions relevant to LNM.Conclusion: DL‐based image analysis has demonstrated efficiency in predicting LNM in early operable cervical cancer through the utilization of biopsies WSI. This approach has the potential to enhance therapeutic decision‐making for patients diagnosed with cervical cancer.

Background: Post-resistance progress in paclitaxel (PTX) treatment remains a major challenge in tumor treatment. A high dose of PTX was used for cell lines to analyze the changes in molecular expression. The miR-378d was sharply reduced in surviving cells, but the role of miR-378d in Esophageal squamous cell carcinoma (ESCC) remained unclear. Methods: We analyzed the relationship between miR-378d expression and the clinicopathological features of ESCC. We constructed miR-378d silent expression cell lines to study phenotypes and molecular mechanisms. Results: The miR-378d expression was associated with good prognosis in patients with ESCC. miR-378d inhibition promoted chemo-resistance, monoclonal formation, EMT, migration, invasion, stemness, and metastasis of ESCC cells. miR-378d can target downregulated AKT1. Conclusions: Therefore, miR-378d expression is a good prognostic factor of patients with ESCC and regulates the malignant phenotype of tumor cells through AKT.