Anterior gradient protein 3 is associated with less aggressive tumors and better outcome of breast cancer patients

Over-expression of Anterior Gradient 3 Is Associated With Tumor Progression and Poor Survival in Gastric Cancer

BACKGROUND/AIM

Anterior gradient (AGR) proteins, including AGR1, AGR2, and AGR3, which are members of the protein disulfide isomerase family, have been reported as biomarkers for various carcinogenesis processes. Although AGR2 and AGR1 have been demonstrated to be associated with gastric cancer (GC) progression and poor survival, the effect of AGR3 on the progression and prognosis of GC remains unknown. Therefore, our study aimed to examine the expression and prognostic significance of AGR3 in patients with GC.

PATIENTS AND METHODS

We investigated 271 GC patients receiving curative surgery. Formalin-fixed and paraffin-embedded tissue blocks were obtained, and long-term survival analysis was performed. The expression of AGR3 in GC tissues was investigated by quantitative reverse transcription-polymerase chain reaction, western blotting, and immunohistochemistry.

RESULTS

AGR3 was over-expressed in GC tissue compared with paired normal tissue at the mRNA and protein levels. AGR3 over-expression was significantly associated with larger tumor size, deeper tumor invasion, lymph node metastasis, and advanced tumor stage. The overall survival of patients with positive AGR3 expression was significantly lower than that of patients without positive AGR3 expression. Multivariate analysis demonstrated that AGR3 and age were independent prognostic factors associated with overall survival.

CONCLUSION

Over-expression of AGR3 was significantly associated with tumor progression and poor survival of GC patients. Therefore, AGR3 may be a novel biomarker and prognostic factor for GC.

Choice of High-Throughput Proteomics Method Affects Data Integration with Transcriptomics and the Potential Use in Biomarker Discovery

In recent years, several advances have been achieved in breast cancer (BC) classification and treatment. However, overdiagnosis, overtreatment, and recurrent disease are still significant causes of complication and death. Here, we present the development of a protocol aimed at parallel transcriptome and proteome analysis of BC tissue samples using mass spectrometry, via Data Dependent and Independent Acquisitions (DDA and DIA). Protein digestion was semi-automated and performed on flowthroughs after RNA extraction. Data for 116 samples were acquired in DDA and DIA modes and processed using MaxQuant, EncyclopeDIA, or DIA-NN. DIA-NN showed an increased number of identified proteins, reproducibility, and correlation with matching RNA-seq data, therefore representing the best alternative for this setup. Gene Set Enrichment Analysis pointed towards complementary information being found between transcriptomic and proteomic data. A decision tree model, designed to predict the intrinsic subtypes based on differentially abundant proteins across different conditions, selected protein groups that recapitulate important clinical features, such as estrogen receptor status, HER2 status, proliferation, and aggressiveness. Taken together, our results indicate that the proposed protocol performed well for the application. Additionally, the relevance of the selected proteins points to the possibility of using such data as a biomarker discovery tool for personalized medicine.

Estrogen-regulated AGR3 activates the estrogen receptor signaling pathway to promote tamoxifen resistance in breast cancer

PURPOSE

Anterior gradient 3 (AGR3) is associated with breast cancer progression, but its relationship with estrogen and tamoxifen resistance in breast cancer is still unclear. This study was designed to investigate the correlation of ARG3 and estrogen as well as the roles of ARG3 in tamoxifen resistance in breast cancer.

METHODS

Online database including GEPIA, UALCAN, and TCGA and rVista predictive tool were applied to analyze the expression patterns of AGR3 and its relationship with estrogen receptor 1. AGR3 knockdown and overexpression cell models were constructed. Luciferase reporter assay and ChIP were performed to investigate intermolecular interactions. Western blotting and qPCR were applied to assess targets at mRNA and protein levels, respectively. Cell counting and MTT assay were applied to determine the cell proliferation.

RESULTS

An elevation of AGR3 was observed in patients with breast cancer, especially in the patients with estrogen receptor (ER)-positive breast cancer. The TCGA dataset and in vitro data supported that AGR3 was positively correlated to ER. Further results demonstrated that ER protein bound to AGR3 promoter sites. AGR3 expression exhibited a positive correlation to cell viability. Besides, AGR3 promoted tamoxifen resistance in breast cancer.

CONCLUSION

AGR3 is associated with estrogen and promotes tamoxifen resistance in breast cancer.

High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers

Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.

AGR3 promotes estrogen receptor-positive breast cancer cell proliferation in an estrogen-dependent manner

Breast cancer is one of the most common malignancies and the leading cause of cancer-associated death among women. Anterior gradient 3 (AGR3) is a cancer-associated gene and is similar to its homologous oncogene AGR2. However, whether AGR3 participates in breast cancer progression remains unclear. The present study aimed to investigate the function of AGR3 in ER-positive breast cancer. In the present study, reverse transcription-quantitative PCR was used to detect AGR3 mRNA expression in breast cancer tissues and cell lines; linear correlation analysis was used to investigate the correlation between AGR3 and estrogen receptor 1 (ESR1) expression in breast cancer via GEO dataset analysis; western blotting was used to assess the levels of AGR3, ER and GAPDH; small interfering (si)RNA transfection was used to knock down AGR3 and ESR1 expression; and finally the Cell Counting Kit-8 assay was used to evaluate cell viability. In the present study, AGR3 expression was markedly increased in estrogen receptor (ER)-positive breast cancer tissues and cell lines compared with that in ER-negative breast cancer. AGR3 expression was upregulated in estrogen-treated T47D cells, whereas 4-hydroxytamoxifen, an inhibitor of estrogen-ER activity in breast cancer cells, downregulated AGR3 expression in T47D cells. Functional assays demonstrated that knockdown of AGR3 using siRNAs inhibited T47D cell proliferation compared with that of the negative control group. Additionally, AGR3 expression was decreased after knocking down ESR1. The present results suggested that AGR3 may serve an important role in estrogen-mediated cell proliferation in breast cancer and that AGR3 knockdown may be a potential therapeutic strategy for ER-positive breast cancer.

Extracellular AGR3 regulates breast cancer cells migration via Src signaling

Human anterior gradient proteins AGR2 and AGR3 are overexpressed in a variety of adenocarcinomas and are often secreted in cancer patients' specimens, which suggests a role for AGR proteins in intra and extracellular compartments. Although these proteins exhibit high sequence homology, AGR2 is predominantly described as a pro-oncogene and a potential prognostic biomarker. However, little is known about the function of AGR3. Therefore, the aim of the present study was to investigate the role of AGR3 in breast cancer. The results demonstrated that breast cancer cells secrete AGR3. Furthermore, it was revealed that extracellular AGR3 (eAGR3) regulates tumor cell adhesion and migration. The current study indicated that the pharmacological and genetic perturbation of Src kinase signaling, through treatment with Dasatinib (protein kinase inhibitor) or investigating cells that express a dominant-negative form of Src, significantly abrogated eAGR3-mediated breast cancer cell migration. Therefore, the results indicated that eAGR3 may control tumor cell migration via activation of Src kinases. The results of the present study indicated that eAGR3 may serve as a microenvironmental signaling molecule in tumor-associated processes.

Apoptotic caspases inhibit abscopal responses to radiation and identify a new prognostic biomarker for breast cancer patients

Caspase 3 (CASP3) has a key role in the execution of apoptosis, and many cancer cells are believed to disable CASP3 as a mechanism of resistance to cytotoxic therapeutics. Alongside, CASP3 regulates stress-responsive immunomodulatory pathways, including secretion of type I interferon (IFN). Here, we report that mouse mammary carcinoma TSA cells lacking Casp3 or subjected to chemical caspase inhibition were as sensitive to the cytostatic and cytotoxic effects of radiation therapy (RT) in vitro as their control counterparts, yet secreted increased levels of type I IFN. This effect originated from the accrued accumulation of irradiated cells with cytosolic DNA, likely reflecting the delayed breakdown of cells experiencing mitochondrial permeabilization in the absence of CASP3. Casp3^-/- TSA cells growing in immunocompetent syngeneic mice were more sensitive to RT than their CASP3-proficient counterparts, and superior at generating bona fide abscopal responses in the presence of an immune checkpoint blocker. Finally, multiple genetic signatures of apoptotic proficiency were unexpectedly found to have robust negative (rather than positive) prognostic significance in a public cohort of breast cancer patients. However, these latter findings were not consistent with genetic signatures of defective type I IFN signaling, which were rather associated with improved prognosis. Differential gene expression analysis on patient subgroups with divergent prognosis (as stratified by independent signatures of apoptotic proficiency) identified SLC7A2 as a new biomarker with independent prognostic value in breast cancer patients. With the caveats associated with the retrospective investigation of heterogeneous, public databases, our data suggest that apoptotic caspases may influence the survival of breast cancer patients (or at least some subsets thereof) via mechanisms not necessarily related to type I IFN signaling as they identify a novel independent prognostic biomarker that awaits prospective validation.

Anterior Gradient 3 Promotes Breast Cancer Development and Chemotherapy Response

PURPOSE

Anterior gradient 3 (AGR3) belongs to human anterior gradient (AGR) family. The function of AGR3 on cancer remains unknown. This research aimed to investigate if AGR3 had prognostic values in invasive ductal carcinoma (IDC) of breast cancer and could promote tumor progression.

Materials and Methods

AGR3 expression was detected in breast benign lesions, ductal carcinoma in situ and IDC by immunohistochemistry analysis. AGR3's correlations with clinicopathological features and prognosis of IDC patients were analyzed. By cell function experiments, collagen gel droplet-embedded culture drug sensitivity test and cytotoxic analysis, AGR3's impacts on proliferation, invasion ability, and chemotherapeutic drug sensitivity of breast cancer cells were also detected.

RESULTS

AGR3 was up-regulated in luminal subtype of histological grade I-II of IDC patients and positively correlated with high risks of recurrence and distant metastasis. AGR3 high expression could lead to bone or liver metastasis and predict poor prognosis of luminal B. In cell lines, AGR3 could promote proliferation and invasion ability of breast cancer cells which were consistent with clinical analysis. Besides, AGR3 could indicate poor prognosis of breast cancer patients treated with taxane but a favorable prognosis with 5-fluoropyrimidines. And breast cancer cells with AGR3 high expression were resistant to taxane but sensitive to 5-fluoropyrimidines.

CONCLUSION

AGR3 might be a potential prognostic indicator in luminal B subtype of IDC patients of histological grade I-II. And patients with AGR3 high expression should be treated with chemotherapy regimens consisting of 5-fluoropyrimidines but no taxane.

Leveraging the Role of the Metastatic Associated Protein Anterior Gradient Homologue 2 in Unfolded Protein Degradation: A Novel Therapeutic Biomarker for Cancer

Effective diagnostic, prognostic and therapeutic biomarkers can help in tracking disease progress, predict patients’ survival, and considerably affect the drive for successful clinical management. The present review aims to determine how the metastatic-linked protein anterior gradient homologue 2 (AGR2) operates to affect cancer progression, and to identify associated potential diagnostic, prognostic and therapeutic biomarkers, particularly in central nervous system (CNS) tumors. Studies that show a high expression level of AGR2, and associate the protein expression with the resilience to chemotherapeutic treatments or with poor cancer survival, are reported. The primary protein structures of the seven variants of AGR2, including their functional domains, are summarized. Based on experiments in various biological models, this review shows an orchestra of multiple molecules that regulate AGR2 expression, including a feedback loop with p53. The AGR2-associated molecular functions and pathways including genomic integrity, proliferation, apoptosis, angiogenesis, adhesion, migration, stemness, and inflammation, are detailed. In addition, the mechanisms that can enable the rampant oncogenic effects of AGR2 are clarified. The different strategies used to therapeutically target AGR2-positive cancer cells are evaluated in light of the current evidence. Moreover, novel associated pathways and clinically relevant deregulated genes in AGR2 high CNS tumors are identified using a meta-analysis approach.

Evaluation of variable selection methods for random forests and omics data sets

Machine learning methods and in particular random forests are promising approaches for prediction based on high dimensional omics data sets. They provide variable importance measures to rank predictors according to their predictive power. If building a prediction model is the main goal of a study, often a minimal set of variables with good prediction performance is selected. However, if the objective is the identification of involved variables to find active networks and pathways, approaches that aim to select all relevant variables should be preferred. We evaluated several variable selection procedures based on simulated data as well as publicly available experimental methylation and gene expression data. Our comparison included the Boruta algorithm, the Vita method, recurrent relative variable importance, a permutation approach and its parametric variant (Altmann) as well as recursive feature elimination (RFE).  In our simulation studies, Boruta was the most powerful approach, followed closely by the Vita method. Both approaches demonstrated similar stability in variable selection, while Vita was the most robust approach under a pure null model without any predictor variables related to the outcome. In the analysis of the different experimental data sets, Vita demonstrated slightly better stability in variable selection and was less computationally intensive than Boruta. In conclusion, we recommend the Boruta and Vita approaches for the analysis of high-dimensional data sets. Vita is considerably faster than Boruta and thus more suitable for large data sets, but only Boruta can also be applied in low-dimensional settings.

Triple Negative Breast Cancer Profile, from Gene to microRNA, in Relation to Ethnicity

Breast cancer is the most frequent cause of cancer-related deaths among women worldwide. It is classified into four major molecular subtypes. Triple-negative breast cancers (TNBCs), a subgroup of breast cancer, are defined by the absence of estrogen and progesterone receptors and the lack of HER-2 expression; this subgroup accounts for ~15% of all breast cancers and exhibits the most aggressive metastatic behavior. Currently, very limited targeted therapies exist for the treatment of patients with TNBCs. On the other hand, it is important to highlight that knowledge of the molecular biology of breast cancer has recently changed the decision-making process regarding the course of cancer therapies. Thus, a number of new techniques, such as gene profiling and sequencing, proteomics, and microRNA analysis have been used to explore human breast carcinogenesis and metastasis including TNBC, which consequently could lead to new therapies. Nevertheless, based on evidence thus far, genomics profiles (gene and miRNA) can differ from one geographic location to another as well as in different ethnic groups. This review provides a comprehensive and updated information on the genomics profile alterations associated with TNBC pathogenesis associated with different ethnic backgrounds.

Crystal structure of human anterior gradient protein 3

Oxidative protein folding in the endoplasmic reticulum is catalyzed by the protein disulfide isomerase family of proteins. Of the 20 recognized human family members, the structures of eight have been deposited in the PDB along with domains from six more. Three members of this family, ERp18, anterior gradient protein 2 (AGR2) and anterior gradient protein 3 (AGR3), are single-domain proteins which share sequence similarity. While ERp18 has a canonical active-site motif and is involved in native disulfide-bond formation, AGR2 and AGR3 lack elements of the active-site motif found in other family members and may both interact with mucins. In order to better define its function, the structure of AGR3 is required. Here, the recombinant expression, purification, crystallization and crystal structure of human AGR3 are described.

Expression of protein disulfide isomerase family members correlates with tumor progression and patient survival in ovarian cancer

Objective

Protein disulfide isomerase (PDI) is an oxidoreductase that is overexpressed in several cancers. PDI family members (PDIs) play a role in various diseases including cancer. Select PDIs were reported as useful markers in other cancers but their expression in ovarian cancer has not been thoroughly assessed. We sought to evaluate the expression of PDI, PDIA6, PDIR, ERp57, ERp72 and AGR3 in ovarian cancer patient samples and examine their prognostic significance.

Methods

TMA samples from 415 tissues collected from three cancer centers (UM, USC, and KCCRI) were used to assess the expression levels of PDI family proteins using IHC.

Results

We observed significant increases in PDI (p = 9.16E-36), PDIA6 (p = 5.51E-33), PDIR (p = 1.81E-12), ERp57 (p = 9.13E-07), ERp72 (p = 3.65E-22), and AGR3 (p = 4.56E-24) expression in ovarian cancers compared to normal tissues. Expression of PDI family members also increases during disease progression (p <0.001). All PDI family members are overexpressed in serous ovarian cancer (p<0.001). However, PDI, PDIA6, PDIR, ERp72 and AGR3 are more significantly overexpressed (p<0.001) than ERp57 (p<0.05) in clear cell ovarian carcinoma. Importantly, overexpression of PDI family members is associated with poor survival in ovarian cancer (p = 0.045 for PDI, p = 0.047 for PDIR, p = 0.037 for ERp57, p = 0.046 for ERp72, p = 0.040 for AGR3) with the exception of PDIA6 (p = 0.381).

Conclusions

Our findings demonstrate that select PDI family members (PDI, PDIR, ERp72, ERp57 and AGR3) are potential prognostic markers for ovarian cancer.