NPY1R exerts inhibitory action on estradiol-stimulated growth and predicts endocrine sensitivity and better survival in ER-positive breast cancer

The EstroGene2.0 database for endocrine therapy response and resistance in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities ( https://estrogeneii.web.app/ ). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed transcriptomic landscape and substantial diversity in response to different classes of ER modulators. Endocrine-resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signalings, which is recapitulated clinically. Dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of cell model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer's response to endocrine therapies and explore resistance mechanisms.

TFAP2C Activates CST1 Transcription to Facilitate Breast Cancer Progression and Suppress Ferroptosis

Cystatin SN (CST1) appears to have pro-tumor effects in breast cancer (BC) and is involved in ferroptosis; however, there is no report on the regulation of ferroptosis by CST1 for BC development. The purpose of this study is to investigate the functions and mechanisms operated by CST1 in BC development and ferroptosis. Transcription Factor Activator Protein 2γ (TFAP2C) and CST1 levels in BC tissues and estrogen receptor (ER)+ cells were quantified by RT-qPCR and western blotting. After knocking down TFAP2C and CST1 expression in MCF7 and T47D cells, the proliferation, colony formation ability, apoptosis, and cell cycle were assessed. Ferroptosis was verified by detecting glutathione peroxidase 4 (GPX4) and 4-hydroxy-2-nonenal (4HNE) levels. The kits were used to test Fe2+, reactive oxygen species, malondialdehyde, and glutathione levels, and ultrastructure of mitochondria was observed through transmission electron microscope. Dual-luciferase reporter assay and chromatin immunoprecipitation test were carried out to investigate the interaction of TFAP2C and CST1. A transplanted tumor model was established to explore the function of TFAP2C in tumorigenesis by quantifying TFAP2C, CST1, Ki67, and GPX4 levels through western blotting and immunochemistry after silencing TFAP2C. TFAP2C and CST1 were predominantly expressed in BC cells. Silencing of TFAP2C or CST1 expression suppressed ER+ BC cell proliferation, promoted apoptosis and ferroptosis, and blocked cell cycle transition from G1 phase to S phase. TFAP2C knockdown in transplanted tumors inhibited tumor growth and GPX4 level. Upregulating CST1 nullified the anti-tumor effects of TFAP2C knockdown and TFAP2C promoted CST1 expression through transcription activation. TFAP2C activates CST1 transcription to facilitate BC development and block ferroptosis.

A glycolysis-related signature to improve the current treatment and prognostic evaluation for breast cancer

Background

As a heterogeneous malignancy, breast cancer (BRCA) shows high incidence and mortality. Discovering novel molecular markers and developing reliable prognostic models may improve the survival of BCRA.

Methods

The RNA-seq data of BRCA patients were collected from the training set The Cancer Genome Atlas (TCGA)-BRCA and validation set GSE20685 in the Gene Expression Omnibus (GEO) databases. The "GSVA" R package was used to calculate the glycolysis score for each patient, based on which all the patients were divided into different glycolysis groups. The "limma" package was employed to perform differentially expression genes (DEGs) analysis. Key signature genes were selected by performing un/multivariate and least absolute shrinkage and selection operator (LASSO) C regression and used to develop a RiskScore model. The ESTIMATE and MCP-Counter algorithms were used for quantifying immune infiltration level. The functions of the genes were validated using Western blot, colony formation, transwell and wound-healing assay.

Results

The glycolysis score and prognostic analysis showed that high glycolysis score was related to tumorigenesis pathway and a poor prognosis in BRCA as overactive glycolysis inhibited the normal functions of immune cells. Subsequently, we screened five key prognostic genes using the LASSO Cox regression analysis and used them to establish a RiskScore with a high classification efficiency. Based on the results of the RiskScore, it was found that patients in the high-risk group had significantly unfavorable immune infiltration and prognostic outcomes. A nomogram integrating the RiskScore could well predict the prognosis for BRCA patients. Knockdown of PSCA suppressed cell proliferation, invasion and migration of BRCA cells.

Conclusion

This study developed a glycolysis-related signature with five genes to distinguish between high-risk and low-risk BRCA patients. A nomogram developed on the basis of the RiskScore was reliable to predict BRCA survival. Our model provided clinical guidance for the treatment of BRCA patients.

EstroGene2.0: A multi-omic database of response to estrogens, ER-modulators, and resistance to endocrine therapies in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Understanding the molecular mechanisms is thus key to optimize the existing drugs and to develop new ER-modulators. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities (https://estrogeneii.web.app/). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed substantial diversity in response to different classes of ER-modulators including SERMs, SERDs, SERCA and LDD/PROTAC. Notably, endocrine resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signaling, which is recapitulated clinically. Furthermore, dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of genome-edited versus ectopic overexpression model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer's response to endocrine therapies and explore resistance mechanisms.

Neuropeptide Y Peptide Family and Cancer: Antitumor Therapeutic Strategies

Currently available data on the involvement of neuropeptide Y (NPY), peptide YY (PYY), and pancreatic polypeptide (PP) and their receptors (YRs) in cancer are updated. The structure and dynamics of YRs and their intracellular signaling pathways are also studied. The roles played by these peptides in 22 different cancer types are reviewed (e.g., breast cancer, colorectal cancer, Ewing sarcoma, liver cancer, melanoma, neuroblastoma, pancreatic cancer, pheochromocytoma, and prostate cancer). YRs could be used as cancer diagnostic markers and therapeutic targets. A high Y1R expression has been correlated with lymph node metastasis, advanced stages, and perineural invasion; an increased Y5R expression with survival and tumor growth; and a high serum NPY level with relapse, metastasis, and poor survival. YRs mediate tumor cell proliferation, migration, invasion, metastasis, and angiogenesis; YR antagonists block the previous actions and promote the death of cancer cells. NPY favors tumor cell growth, migration, and metastasis and promotes angiogenesis in some tumors (e.g., breast cancer, colorectal cancer, neuroblastoma, pancreatic cancer), whereas in others it exerts an antitumor effect (e.g., cholangiocarcinoma, Ewing sarcoma, liver cancer). PYY or its fragments block tumor cell growth, migration, and invasion in breast, colorectal, esophageal, liver, pancreatic, and prostate cancer. Current data show the peptidergic system's high potential for cancer diagnosis, treatment, and support using Y2R/Y5R antagonists and NPY or PYY agonists as promising antitumor therapeutic strategies. Some important research lines to be developed in the future will also be suggested.

A meta-analysis of mRNA expression profiling studies in sheep with different FecB genotypes

The FecB mutation in the sheep BMPRIB is strongly correlated with high ovulation traits but its mechanism remains unclear. This study explored differentially expressed genes (DEGs) and their associated molecular mechanisms that may be involved in FecB mutation-induced high ovulation from the perspective of the hypothalamic-pituitary-gonadal (HPG) axis by conducting a systematic review and meta-analysis. The PubMed, EMBASE, CNKI, WanFang, and CBM databases were searched for eligible articles published before August 2022, focusing on mRNA sequencing of different tissues in the HPG axis in sheep with different FecB genotypes. A total of 6555 DEGs were identified from the analysis of six published articles and experimental results from our laboratory. The DEGs were screened by vote-counting rank and robust rank aggregation. Among these, in the follicular phase, FKBP5, CDCA7 and CRABP1 were upregulated in the hypothalamus. INSM2 was upregulated, while LDB3 was downregulated in the pituitary. CLU, SERPINA14, PENK, INHA and STAR were upregulated, while FERMT2 and NPY1R were downregulated in the ovary. On the HPG axis, TAC1 was upregulated and NPNT was downregulated. Many DEGs were found in sheep with different FecB genotypes. The genes FKBP5, CDCA7, CRABP1, INSM2, LDB3, CLU, SERPINA14, PENK, INHA, STAR, FERMT2, NPY1R, TAC1 and NPNT, may be associated with FecB mutation-induced high ovulation in different tissues. These candidate genes will further improve the mechanism of multiple fertility traits induced by the FecB mutation from the perspective of the HPG axis.

Upregulation of TIMM8A is correlated with prognosis and immune regulation in BC

Backgrounds

Breast cancer is a common malignant tumors in women. TIMM8A was up-regulated in different cancers. The aim of this work was to clarify the value of TIMM8A in the diagnosis, prognosis of Breast Cancer (BC), and its association with immune cells and immune detection points. Gene mutations.

Methods

The transcription and expression profile of TIMM8A between BC and normal tissues was downloaded from The Cancer Genome atlas (TCGA). The expression of TIMM8A protein was evaluated by human protein map. The correlation between TIMM8A and clinical features was analyzed using the R package to establish a ROC diagnostic curve. cBioPortal and MethSurv were used to identify gene alterations and DNA methylation and their effects on prognosis. The tumor immune estimation resource (TIMER) database and tumor immune system interaction database (TISIDB) database were used to determine the relationship between TIMM8A gene expression levels and immune infiltration. The CTD database was used to predict related drugs that inhibit TIMM8A, and the PubChem database was used to determine the molecular structure of potentially effective drug small molecules.

Results

The expression of TIMM8A in breast cancer tissues was significantly higher than that in normally adjacent tissues to cancer. ROC curve analysis showed that the AUC value of TIMM8A was 0.679. Kaplan-Meier method showed that patients with high TIMM8A had a lower prognosis (Overall Survival HR = 1.83 (1.31 − 2.54), P < 0.001) than patients with low TIMM8A expression of breast cancer (148.5 months vs. 115.4 months, P < 0.001). Methylation levels at seven CpG were associated with prognosis. Correlation analysis showed that TIMM8A expression was associated with tumor immune cell infiltration. There was a significant positive correlation of TIMM8A with PDL-1, and CTLA-4 in BC. In addition, CTD database analysis identified 15 small molecular drugs that target TIMM8A, such as Cyclosporine, Leflunomide, and Tretinoin, which might be effective therapies for targeted inhibition of TIMM8A.

Conclusion

In breast cancer, up-regulated TIMM 8A was significantly related to lower survival rate and higher immune invasiveness. Our research showed that TIMM 8A could be used as a biomarker for poor prognosis of breast cancer and a potential target of immunotherapy.

Delineation of Pathogenomic Insights of Breast Cancer in Young Women

The prognosis of breast cancer (BC) in young women (BCYW) aged ≤40 years tends to be poorer than that in older patients due to aggressive phenotypes, late diagnosis, distinct biologic, and poorly understood genomic features of BCYW. Considering the estimated predisposition of only approximately 15% of the BC population to BC-promoting genes, the underlying reasons for an increased occurrence of BCYW, at large, cannot be completely explained based on general risk factors for BC. This underscores the need for the development of next-generation of tissue- and body fluid-based prognostic and predictive biomarkers for BCYW. Here, we identified the genes associated with BCYW with a particular focus on the age, intrinsic BC subtypes, matched normal or normal breast tissues, and BC laterality. In young women with BC, we observed dysregulation of age-associated cancer-relevant gene sets in both cancer and normal breast tissues, sub-sets of which substantially affected the overall survival (OS) or relapse-free survival (RFS) of patients with BC and exhibited statically significant correlations with several gene modules associated with cellular processes such as the stroma, immune responses, mitotic progression, early response, and steroid responses. For example, high expression of COL1A2, COL5A2, COL5A1, NPY1R, and KIAA1644 mRNAs in the BC and normal breast tissues from young women correlated with a substantial reduction in the OS and RFS of BC patients with increased levels of these exemplified genes. Many of the genes upregulated in BCYW were overexpressed or underexpressed in normal breast tissues, which might provide clues regarding the potential involvement of such genes in the development of BC later in life. Many of BCYW-associated gene products were also found in the extracellular microvesicles/exosomes secreted from breast and other cancer cell-types as well as in body fluids such as urine, saliva, breast milk, and plasma, raising the possibility of using such approaches in the development of non-invasive, predictive and prognostic biomarkers. In conclusion, the findings of this study delineated the pathogenomics of BCYW, providing clues for future exploration of the potential predictive and prognostic importance of candidate BCYW molecules and research strategies as well as a rationale to undertake a prospective clinical study to examine some of testable hypotheses presented here. In addition, the results presented here provide a framework to bring out the importance of geographical disparities, to overcome the current bottlenecks in BCYW, and to make the next quantum leap for sporadic BCYW research and treatment.