The Expression and Prognostic Significance of Claudin-8 and Androgen Receptor in Breast Cancer

Significance and Possible Biological Mechanism for CLDN8 Downregulation in Kidney Renal Clear Cell Carcinoma Tissues

Background

The clinical role of claudin 8 (CLDN8) in kidney renal clear cell carcinoma (KIRC) remains unclarified. Herein, the expression level and potential molecular mechanisms of CLDN8 underlying KIRC were determined.

Methods

High-throughput datasets of KIRC were collected from GEO, ArrayExpress, SRA, and TCGA databases to determine the mRNA expression level of the CLDN8. In-house tissue microarrays and immunochemistry were performed to examine CLDN8 protein expression. A summary receiver operating characteristic curve (SROC) and standardized mean difference (SMD) forest plot were generated using Stata v16.0. Single-cell analysis was conducted to further prove the expression level of CLDN8. A clustered regularly interspaced short palindromic repeats knockout screen analysis was executed to assess the growth impact of CLDN8. Functional enrichment analysis was conducted using the Metascape database. Additionally, single-sample gene set enrichment analysis was implied to explore immune cell infiltration in KIRC.

Results

A total of 17 mRNA datasets comprising 1,060 KIRC samples and 452 non-cancerous control samples were included in this study. Additionally, 105 KIRC and 16 non-KIRC tissues were analyzed using in-house immunohistochemistry. The combined SMD was -5.25 (95% confidence interval (CI): -6.13 to -4.37), and CLDN8 downregulation yielded an SROC area under the curve (AUC) close to 1.00 (95% CI: 0.99 - 1.00). CLDN8 downregulation was also confirmed at the single-cell level. Knocking out CLDN8 stimulated KIRC cell proliferation. Lower CLDN8 expression was correlated with worse overall survival of KIRC patients (hazard ratio of CLDN8 downregulation = 1.69, 95% CI: 1.2 - 2.4). Functional pathways associated with CLDN8 co-expressed genes were centered on carbon metabolism obstruction, with key hub genes ACADM, ACO2, NDUFS1, PDHB, SDHD, SUCLA2, SUCLG1, and SUCLG2.

Conclusions

CLDN8 is downregulated in KIRC and is considered a potential tumor suppressor. CLDN8 deficiency may promote the initiation and progression of KIRC, potentially in conjunction with metabolic dysfunction.

Claudins in Cancer: A Current and Future Therapeutic Target

Claudins are a family of 27 proteins that have an important role in the formation of tight junctions. They also have an important function in ion exchange, cell mobility, and the epithelial-to-mesenchymal transition, the latter being very important in cancer invasion and metastasis. Therapeutic targeting of claudins has been investigated to improve cancer outcomes. Recent evidence shows improved outcomes when combining monoclonal antibodies against claudin 18.2 with chemotherapy for patients with gastroesophageal junction cancer. Currently, chimeric antigen receptor T-cells targeting claudin 18 are under investigation. In this review, we will discuss the major functions of claudins, their distribution in the normal as well as cancerous tissues, and their effect in cancer metastasis, with a special focus on the therapeutic targeting of claudins to improve cancer outcomes.

Expression patterns of claudins in cancer

Claudins are four-transmembrane proteins, which were found in tight junctions. They maintain cell barriers and regulate cell differentiation and proliferation. They are involved in maintaining cellular polarity and normal functions. Different claudins show different expression patterns. The expression level and localization of claudins are altered in various cancers. They promote or inhibit proliferation, invasion, and migration of cancer cells through multiple signaling pathways. Therefore, claudins may serve as diagnostic markers, novel therapeutic targets, and prognostic risk factors. The important roles of claudins in cancer aroused our great interest. In the present review, we provide a summary of insights into expression patterns of claudins in cancer, which is more comprehensive and provides new ideas for further research.

Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women

Introduction: Although the risk of breast cancer increases with advancing age, some regions have larger number of young breast cancer patients (≤45 years-old), such as the Middle East, Eastern Asia, and North Africa, with more aggressive and poorly differentiated tumors. We aimed to conduct an in-silico analysis in an attempt to understand the aggressive nature of early-onset breast cancer, and to identify potential drivers of early-onset breast cancer using gene expression profiling datasets in a population-dependent manner. Methods: Functional genomics experiments data were acquired from cBioPortal database for cancer genomics, followed by the stratification of patients based on the age at representation of breast cancer and race. Differential gene expression analysis and gene amplification status analysis were carried out, followed by hub gene, transcription factor, and signalling pathway identification. Results: PAM50 subtype analysis revealed that young patients (≤45 years-old) had four-fold more basal tumors and worst progression-free survival (median of 101 months), compared with the 45-65 years group (median of 168 months). Fourteen genes were amplified in more than 14% of patients with an early-onset breast cancer. Interestingly, FREM2, LINC00332, and LINC00366 were exclusively amplified in younger patients. Gene expression data from three different populations (Asian, White, and African) revealed a unique transcriptomic profile of young patients, which was also reflected on the PAM50 subtype analysis. Our data indicates a higher tendency of young African patients to develop basal tumors, while young Asian patients are more prone to developing Luminal A tumors. Most genes that were found to be upregulated in younger patients are involved in important signaling pathways that promote cancer progression and metastasis, such as MAPK pathway, Reelin pathway and the PI3K/Akt pathway. Conclusion: This study provides strong evidence that the molecular profile of tumors derived from young breast cancer patients of different populations is unique and may explain the aggressiveness of these tumors, stressing the need to conduct population- based multi-omic analyses to identify the potential drivers for tumorigenesis and molecular profiles of young breast cancer patients.

HER2 classification in breast cancer cells: A new explainable machine learning application for immunohistochemistry

The immunohistochemical (IHC) evaluation of epidermal growth factor 2 (HER2) for the diagnosis of breast cancer is still qualitative with a high degree of inter-observer variability, and thus requires the incorporation of complementary techniques such as fluorescent in situ hybridization (FISH) to resolve the diagnosis. Implementing automatic algorithms to classify IHC biomarkers is crucial for typifying the tumor and deciding on therapy for each patient with better performance. The present study aims to demonstrate that, using an explainable Machine Learning (ML) model for the classification of HER2 photomicrographs, it is possible to determine criteria to improve the value of IHC analysis. We trained a logistic regression-based supervised ML model with 393 IHC microscopy images from 131 patients, to discriminate between upregulated and normal expression of the HER2 protein. Pathologists' diagnoses (IHC only) vs. the final diagnosis complemented with FISH (IHC + FISH) were used as training outputs. Basic performance metrics and receiver operating characteristic curve analysis were used together with an explainability algorithm based on Shapley Additive exPlanations (SHAP) values to understand training differences. The model could discriminate amplified IHC from normal expression with better performance when the training output was the IHC + FISH final diagnosis (IHC vs. IHC + FISH: area under the curve, 0.94 vs. 0.81). This may be explained by the increased analytical impact of the membrane distribution criteria over the global intensity of the signal, according to SHAP value interpretation. The classification model improved its performance when the training input was the final diagnosis, downplaying the weighting of the intensity of the IHC signal, suggesting that to improve pathological diagnosis before FISH consultation, it is necessary to emphasize subcellular patterns of staining.

High Expression of Claudin-4 Is Associated with Synchronous Tumors in Patients with Early Gastric Cancer

Claudin (CLDN) is a tight junction protein found in human epithelial cells and its altered expression is known to be associated with the progression of gastric cancer. We aimed to investigate the differential expression of CLDN-4 in early gastric cancer (EGC) according to its clinicopathological characteristics. We enrolled 53 patients with EGC who underwent surgical gastric resection from January 2007 to December 2018. The staining intensity of the tumor cells was scored as 0–3, and the percentage of staining was scored as 0–5; high expression was defined if the intensity plus percentage score was 7 or 8, and low expression was defined if the score was 0–6. Among the 53 patients, 16 (30.2%) showed low CLDN-4 expression, while 37 (69.8%) had high CLDN-4 expression. High CLDN-4 expression was significantly associated with intestinal-type EGC (low: 12.5% vs. high: 56.8%, p = 0.003), open-type atrophic change (low: 60.0% vs. high: 90.9%, p = 0.011), and the presence of synchronous tumors (0 vs. 32.4%, p = 0.010), and all 12 EGCs with synchronous tumors showed high CLDN-4 expression. However, expression of CLDN-3, a typical intestinal phenotype CLDN, was neither correlated with CLDN-4 expression nor associated with synchronous tumors. Taken together, high CLDN-4 expression may be considered as an auxiliary tool for screening synchronous tumors in patients with EGC.

Transcriptome profiling and proteomic validation reveals targets of the androgen receptor signaling in the BT-474 breast cancer cell line

BACKGROUND

Accumulating evidence suggests that the androgen receptor (AR) and its endogenous ligands influence disease progression in breast cancer (BCa). However, AR-mediated changes in BCa differ among the various BCa subtypes according to their hormone receptor profile [i.e., presence/absence of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2, (HER2)]. Thus, we explored the androgen-regulated transcriptomic changes in the ER⁺PR⁺HER2⁺ BCa cell line, BT-474, and compared them with PR-mediated changes.

METHODS

We performed RNA sequencing analysis in treated BT-474 cells with dihydrotestosterone (DHT) and progesterone. Validation of the top ten differentially androgen-regulated genes and a number of other genes found in enriched signaling pathways was performed by qRT-PCR in BT-474 and other BCa cell lines. In addition, a parallel reaction monitoring targeted proteomic approach was developed to verify selected transcripts at the protein level.

RESULTS

In total 19,450 transcripts were detected, of which 224 were differentially regulated after DHT treatment. The increased expression of two well-known androgen-regulated genes, KLK2 (p < 0.05) and KLK3 (p < 0.001), confirmed the successful androgen stimulation in BT-474 cells. The transcription factor, ZBTB16, was the most highly upregulated gene, with ~ 1000-fold change (p < 0.001). Pathway enrichment analysis revealed downregulation of the DNA replication processes (p < 0.05) and upregulation of the androgen signaling and fatty acid metabolism pathways (p < 0.05). Changes related to progesterone treatment showed opposite effects in gene expression than DHT treatment. Similar expression profiles were observed among other BCa cell lines expressing high levels of AR (ZR75.1 and MBA-MB-453). The parallel reaction monitoring targeted proteomic analysis further confirmed that altered protein expression (KLK3, ALOX15B) in the supernatant and cell lysate of DHT-treated BT-474 cells, compared to control cells.

DISCUSSION

Our findings suggest that AR modulates the metabolism of BT-474 cells by affecting the expression of a large number of genes and proteins. Based on further pathway analysis, we suggest that androgen receptor acts as a tumor suppressor in the BT-474 cells.

Prognostic Value and Potential Biological Functions of CLDN8 in Patients with Clear Cell Renal Cell Carcinoma

Purpose

Clear cell renal cell carcinoma (ccRCC) is among the most common malignant tumors worldwide, with a high incidence rate and poor prognosis. Currently, there are no biomarkers that can accurately guide prognostic evaluation and therapeutic strategy for ccRCC. The prognostic value and potential biological function of claudin-8 (CLDN8), a critical component of tight junctions in ccRCC, remain unclear.

Methods

Sequencing data were obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, and Gene Expression Omnibus databases. R packages were used to explore CLDN8 mRNA expression levels and analyze differentially expressed genes. Results were validated in clinical specimens and cell lines, and bioinformatics analyses were conducted to explore the potential biological functions of CLDN8. Finally, functional analyses were carried out using 786–O ccRCC cell line.

Results

Both CLDN8 mRNA and protein expression levels were significantly lower in ccRCC compared with the normal control tissues. Kaplan–Meier analyses showed that low CLDN8 expression levels were associated with the poor overall survival, while univariate and multivariate Cox regression indicated that CLDN8 could serve as an independent prognostic factor in patient with ccRCC. Bioinformatic and Western blot analyses showed that CLDN8 suppressed proliferation, migration, and invasion of 786–O ccRCC cells through the epithelial–mesenchymal transition and AKT pathways.

Conclusion

CLDN8 could serve as an independent prognostic factor in ccRCC, in which it suppresses 786–O proliferation, migration, and invasion through EMT and AKT pathways.