Clinical implications and immune features of CENPN in breast cancer.

BACKGROUND: A number of human diseases have been associated with Centromere protein N (CENPN), but its role in breast cancer is unclear. METHODS: A pan-cancer database of Genotype Tissue Expression (GTEx) and the Cancer Genome Atlas (TCGA) were used to examine the expression of CENPN. Using TCGA clinical survival data and breast cancer specimens from our center for validation, the relationship between CENPN expression, breast cancer prognosis, and clinicopathological characteristics of patients was examined. Bioinformatics was utilized to conduct an enrichment study of CENPN. Additionally, the potential of CENPN as a predictive biomarker for immunotherapy success was confirmed by analyzing the co-expression of CENPN with immune-checkpoint related genes, reviewing the TCGA database, and evaluating the correlation between CENPN expression and immune cell infiltration. Using the CCK8 test and colony formation assay, CENPN was evaluated for its ability to inhibit breast cancer cell proliferation. Transwell assays and scratch tests were used to assess the impact of CENPN on breast cancer cell migration. RESULTS: CENPN is found in a wide range of tumors, including breast cancer. Additional investigation revealed that CENPN was co-expressed with the majority of immune checkpoint-related genes, had the potential to serve as a predictive biomarker for immunotherapy effectiveness, and that high CENPN expression was linked to high Tregs and low CD8 + T cells and NK cells. Breast cancer cells' malignant characteristics, such as migration and cell proliferation, were inhibited by CENPN knockdown. CONCLUSIONS: According to our findings, CENPN may be an oncogene in breast cancer, as well as a new therapeutic target for immune checkpoint inhibitors.

TNFRSF19 promotes endoplasmic reticulum stress-induced paraptosis via the activation of the MAPK pathway in triple-negative breast cancer cells.

TNFRSF19 is a member of the tumor necrosis factor receptor superfamily, and its function exhibits variability among different types of cancers. The influence of TNFRSF19 on triple-negative breast cancer (TNBC) has yet to be definitively established. In this study, bioinformatics analyses revealed that lower TNFRSF19 was associated with the poorer prognosis, higher lymph node metastasis and lower immune infiltration. Subsequently, data obtained from the TCGA database and collection of tissue samples revealed that the mRNA and protein expression levels of TNFRSF19 were observed to be significantly reduced in TNBC tissue compared to normal tissue. Additionally, the results of in vitro experiments have demonstrated that TNFRSF19 possessed the ability to inhibit the proliferation, migration and invasive capabilities of TNBC cells. In vivo trials elucidated that TNFRSF19 could suppress tumor xenografts growth. Mechanistically, TNFRSF19 initiated caspase-independent cell death and induced paraptosis. Moreover, rescue assays demonstrated that TNFRSF19 induced-paraptosis was facilitated by MAPK pathway-mediated endoplasmic reticulum (ER) stress. In conclusion, our findings demonstrated that the upregulation of TNFRSF19 functioned as a tumor suppressor in TNBC by stimulating paraptosis through the activation of the MAPK pathway-mediated ER stress, highlighting its potential to be a new therapeutic target for TNBC.

Highly expressed CENPL is correlated with breast cancer cell proliferation and immune infiltration.

Background: Centromere protein L (CENPL) is associated with a variety of human diseases. However, its function in breast cancer remains uncertain. Methods: The Cancer Genome Atlas (TCGA) and genotype-tissue expression across cancer data were used to investigate CENPL expression. Using TCGA clinical survival data, the relationship between CENPL expression and patient prognosis was assessed. Using the cluster profiler R software tool, enrichment analysis of CENPL was carried out. Additionally, by studying the TCGA database, the relationship between CENPL expression and immune cell infiltration was assessed. To evaluate CENPL's impact on breast cancer cell proliferation, the CCK8 test and colony-formation assay were carried out. Scratch testing and the transwell assay were used to evaluate the effects of CENPL on breast cancer cell migration. Results: Breast cancer was one of numerous tumor forms with high CENPL expression. Significant relationships between high CENPL expression and the cell cycle, nuclear division, organelle fission, and chromosome segregation were found. Further investigation revealed that minimal infiltration of CD8-positive T cells and natural killer (NK) cells and high levels of Tregs and macrophages were correlated with high levels of CENPL expression. CENPL expression was linked to more than half of the ICP genes. Breast cancer cells' ability to proliferate and migrate was decreased by CENPL knockdown. Conclusions: Our findings suggest that CENPL may be an oncogene in breast cancer and a predictor of efficacy of immunotherapy for breast cancer.

Clinical and pathological features analysis of invasive breast cancer with microcalcification.

PURPOSE: Microcalcification (MC) is a valuable diagnostic indicator to detect invasive breast cancer (IBC). This study aimed to determine the clinicopathological features of IBC with MC and detect biomarkers related to the potential mechanism of the MC formation in IBC. METHODS: Data from 364 patients with IBC were collected for the clinical characteristic analysis. The analysis of clinical data helped us to establish a predictive model of axillary node metastasis (ANM) before surgery. In addition, 49 tissue samples of IBC patients were collected to test the protein levels of osteocalcin (OCN) and hypoxia-inducible factor-1α (HIF-1α) by immunohistochemistry. RESULTS: Significant differences were observed in tumor size, age, ANM, HER2+ , TNM stage, and mutant P53 between samples from IBC patients with MC and samples from IBC patients without MC. Younger age, a larger tumor size, a higher number of childbirths, and MC were independent predictors for ANM in IBC. HIF-1α protein level was higher in tumor tissue than in normal tissue. High protein levels of OCN and HIF-1α are related to the complication of MC in IBC. Of the patients that exhibited high HIF-1α protein levels, the percentage of high OCN protein levels was larger in patients with ANM. CONCLUSION: Based on this study, we concluded that patients with MC had a comparatively poor prognosis. MC was an independent predictive factor associated with the risk of ANM. High protein levels of OCN and HIF-1α were associated with MC and ANM, which were also related to poor prognosis. OCN and HIF-1α had a positive correlation in IBC.

PI3K/AKT signaling activates HIF1α to modulate the biological effects of invasive breast cancer with microcalcification.

Microcalcification (MC) is a valuable diagnostic indicator of breast cancer, and it is reported to be associated with increased tumor aggressiveness and poor prognosis. Nevertheless, the exact potential molecular mechanism is not completely understood. Here, we find that the mineralized invasive breast cancer (IBC) cells not only increased their proliferation and migration, but also showed the characteristic of doxorubicin resistance. The PI3K/AKT signaling pathway is associated with the generation of calcification in IBC, and it activates the transcription and translation of its downstream hypoxia-inducible factor 1α (HIF1α). Knockdown of HIF1α protein significantly downregulated cell proliferation and migration while calcification persists. Meanwhile, calcified breast cancer cells restored sensitivity to doxorubicin because of suppressed HIF1α expression. In addition, we provide initial data on the underlying value of HIF1α as a biomarker of doxorubicin resistance. These findings provide a new direction for exploring microcalcifications in IBC.

PDZK1 Interacting Protein 1 Promotes the Progression of Papillary Thyroid Cancer.

BACKGROUND: The incidence of papillary thyroid cancer (PTC) has increased rapidly in recent decades, and tumor progression events are common in PTC. The purpose of our study is to identify the differentially expressed genes (DEGs) correlated with PTC progression and investigate the function of PDZK1IP1 (PDZK1 interacting protein 1) in PTC. METHODS: We first analyzed DEGs associated with PTC progression between paired PTC and normal thyroid tissues in 3 Gene Expression Omnibus data sets (GSE29265, GSE33630, and GSE60542) and The Cancer Genome Atlas (TCGA) database. Data from the TCGA database and our institution were utilized to explore the relationship between PDZK1IP1 expression and clinicopathological characteristics of PTC. The CCK8 cell proliferation assay, clone formation assay, flow cytometry assay, and the xenograft model were used to investigate the function of PDZK1IP1 in PTC. RESULTS: Thirty-nine DEGs associated with PTC progression were identified, in which only PDZK1IP1 was upregulated in PTC tissue at both messenger RNA and protein levels. In addition, we found that high expression of PDZK1IP1 in the TCGA database was associated with poor progression-free survival, extrathyroidal extension, high stage, tall cell variant, and BRAFV600E mutation of the PTC (P < 0.001). In our collected samples, high expression of PDZK1IP1 was only related to lymph node metastasis (P < 0.05). Overexpression of PDZK1IP1 significantly promoted proliferation and inhibited apoptosis of PTC cells. Knockdown of PDZK1IP1 significantly inhibited proliferation, promoted apoptosis, and prevented xenograft formation of PTC cells. CONCLUSION: PDZK1IP1 is an oncogene for tumorigenesis and development of PTC and might be a potential therapeutic target.

A prediction model incorporating the BRAFV600E protein status for determining the risk of cervical lateral lymph node metastasis in papillary thyroid cancer patients with central lymph node metastasis.

BACKGROUND AND OBJECTIVES: Cervical lateral lymph node metastasis (LLNM) is a predictor of poor prognosis for papillary thyroid carcinoma (PTC) patients. However, the risk factors for LLNM remain unclear. The purpose of the study was to examine the risk factors for LLNM and construct a prediction model. METHODS: With Ethics Committee approval, a total of 1198 PTC patients were retrospectively included in our study. Univariate and multivariate analyses were performed to explore the relationship between clinicopathological characteristics and LLNM. A nomogram for predicting LLNM in PTC patients with central lymph node metastasis (CLNM) was constructed and validated. RESULTS: The negative BRAFV600E protein expression was significantly correlated with positive LLNM status in PTC patients. In PTC patients with CLNM, the number of metastatic central lymph nodes (LNN) ≥ 3 and the ratio of metastatic central lymph nodes (LNR) ≥ 0.565 were found to be significantly associated with positive LLNM status. The nomogram for predicting LLNM risk in PTC patients with CLNM incorporated four risk factors: tumor size, the BRAFV600E protein expression, LNN and LNR. The prediction model showed excellent discrimination, with a C-index of 0.714. CONCLUSIONS: The negative BRAFV600E protein expression was more likely to lead to LLNM. LNN ≥3 and LNR ≥0.565 were associated with LLNM risk in PTC patients with CLNM. Our nomogram might assist clinicians in developing individual suitable follow-up strategies for PTC patients with CLNM.