Germline variation in ADAMTSL1 is associated with prognosis following breast cancer treatment in young women

Harnessing innovation in microneedle technology for Women's healthcare

Women's health management plays a crucial role in modern healthcare, encompassing the prevention, detection, and treatment of female diseases. However, existing technologies often face challenges, such as the invasiveness and discomfort associated with serological testing and injection-based therapies. Microneedles, as an emerging technology in biomedical engineering, demonstrate significant advantages. These micron-sized transdermal devices are applicable in a range of applications, from drug delivery to interstitial fluid sampling, and their painless, minimally invasive nature significantly enhances medication compliance. In recent years, microneedles have been widely utilized in women's health management, showing promising results in early disease prevention and subsequent treatment. Although there are reviews about microneedles applied in disease treatment management, few of them focus on the application of microneedles in the prevention and early detection of women's disease. Herein, we present a comprehensive overview of the current application status of microneedles in women's health management, with a special emphasis on their design and mechanism for disease prevention, and treatment in women. Finally, we discuss the advantages and limitations of microneedles in women's health management, and propose suggestions for future research direction.

ProtVar: mapping and contextualizing human missense variation

Genomic variation can impact normal biological function in complex ways and so understanding variant effects requires a broad range of data to be coherently assimilated. Whilst the volume of human variant data and relevant annotations has increased, the corresponding increase in the breadth of participating fields, standards and versioning mean that moving between genomic, coding, protein and structure positions is increasingly complex. In turn this makes investigating variants in diverse formats and assimilating annotations from different resources challenging. ProtVar addresses these issues to facilitate the contextualization and interpretation of human missense variation with unparalleled flexibility and ease of accessibility for use by the broadest range of researchers. By precalculating all possible variants in the human proteome it offers near instantaneous mapping between all relevant data types. It also combines data and analyses from a plethora of resources to bring together genomic, protein sequence and function annotations as well as structural insights and predictions to better understand the likely effect of missense variation in humans. It is offered as an intuitive web server https://www.ebi.ac.uk/protvar where data can be explored and downloaded, and can be accessed programmatically via an API.

Secreted ADAMTS-like proteins as regulators of connective tissue function

The extracellular matrix (ECM) determines functional properties of connective tissues through structural components, such as collagens, elastic fibers, or proteoglycans. The ECM also instructs cell behavior through regulatory proteins, including proteases, growth factors, and matricellular proteins, which can be soluble or tethered to ECM scaffolds. The secreted a disintegrin and metalloproteinase with thrombospondin type 1 repeats/motifs-like (ADAMTSL) proteins constitute a family of regulatory ECM proteins that are related to ADAMTS proteases but lack their protease domains. In mammals, the ADAMTSL protein family comprises seven members, ADAMTSL1-6 and papilin. ADAMTSL orthologs are also present in the worm, Caenorhabditis elegans, and the fruit fly, Drosophila melanogaster. Like other matricellular proteins, ADAMTSL expression is characterized by tight spatiotemporal regulation during embryonic development and early postnatal growth and by cell type- and tissue-specific functional pleiotropy. Although largely quiescent during adult tissue homeostasis, reexpression of ADAMTSL proteins is frequently observed in the context of physiological and pathological tissue remodeling and during regeneration and repair after injury. The diverse functions of ADAMTSL proteins are further evident from disorders caused by mutations in individual ADAMTSL proteins, which can affect multiple organ systems. In addition, genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) in ADAMTSL genes to complex traits, such as lung function, asthma, height, body mass, fibrosis, or schizophrenia. In this review, we summarize the current knowledge about individual members of the ADAMTSL protein family and highlight recent mechanistic studies that began to elucidate their diverse functions.

Glucocorticoid receptor regulates the epithelial-mesenchymal transition process through GR/ZEB1/E-cad and is involved in breast cancer endocrine drug resistance-a bioinformatics analysis

Background

Studies have shown that there is a connection between estrogen receptor (ER) and glucocorticoid receptor (GR), which can impact the epithelial-mesenchymal transition (EMT) process and contribute to endocrine resistance in breast cancer. However, the specific mechanism is unclear. It is crucial to investigate this mechanism further.

Methods

This study aimed to confirm the role of GR in breast cancer endocrine resistance. Based on our hypothesis, GR is linked to a gene involved in the EMT process, and thus contributes to endocrine resistance in breast cancer. We obtained survival data and GR expression data from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). Additionally, we gathered GR expression data from Gene Expression Omnibus (GEO). Using Cytoscape, we constructed a protein-protein interaction (PPI) network and identified key genes. Data of Vimentin, E-cad, and Wnt/β-catenin expression were obtained from The Cancer Genome Atlas (TCGA). We used the co-expression method to identify key proteins. UALCAN and cBioPortal were utilized to verify the function of the key protein.

Results

In ER+ breast cancer, GR (P=3.12780899271121E-08) and zinc finger E-box binding homeobox 1 (ZEB1) (P=1.716157E-01) were lowly expressed and down-regulated genes of GR differentially expressed genes were enriched in cell adhesion molecules. We screened for the key protein ZEB1 and found high levels of it was positively associated with prolonged recurrence-free survival (RFS) in patients receiving endocrine therapy (P=0.0024), while high levels of E-cad were negatively associated (P=0.0038). GR expression was positively associated with ZEB1 (Spearman =0.29, P=8.50e-21), negatively associated with E-cad (Spearman =-0.13, P=5.17e-5), and negatively associated with the SETD1B (Spearman =-0.14, P=1.527e-5), a gene downstream of ZEB1. In contrast, ZEB1 expression was negatively correlated with E-cad (Spearman =-0.081, P=3.132e-3) and negatively correlated with SET domain-containing 1B (SETD1B) (Spearman =-0.177, P=9.07e-11).

Conclusions

In ER+ breast cancers, GR expression is suppressed, and the EMT process is inhibited by suppressing ZEB1 expression and thus promoting E-cad expression. For the investigation of endocrine medication resistance in breast cancer, it is crucial to identify the mechanisms by how GR participates in the EMT process.

A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study

Previous studies suggest associations of metabolic syndromes with breast cancer prognosis, yet the evidence is mixed. In recent years, the maturation of genome-wide association study findings has led to the development of polygenic scores (PGS) for many common traits, making it feasible to use Mendelian randomization to examine associations between metabolic traits and breast cancer outcomes. In the Pathways Study of 3,902 patients and a median follow-up time of 10.5 years, we adapted a Mendelian randomization approach to calculate PGS for 55 metabolic traits and tested their associations with seven survival outcomes. Multivariable Cox proportional hazards models were used to derive HRs and 95% confidence intervals (CI) with adjustment for covariates. The highest tertile (T3) of PGS for cardiovascular disease was associated with shorter overall survival (HR = 1.34, 95% CI = 1.11-1.61) and second primary cancer-free survival (HR = 1.31, 95% CI = 1.12-1.53). PGS for hypertension (T3) was associated with shorter overall survival (HR = 1.20, 95% CI = 1.00-1.43), second primary cancer-free survival (HR = 1.24, 95% CI = 1.06-1.45), invasive disease-free survival (HR = 1.18, 95% CI = 1.01-1.38), and disease-free survival (HR = 1.21, 95% CI = 1.04-1.39). PGS for serum cystatin C levels (T3) was associated with longer disease-free survival (HR = 0.82, 95% CI = 0.71-0.95), breast event-free survival (HR = 0.74, 95% CI = 0.61-0.91), and breast cancer-specific survival (HR = 0.72, 95% CI = 0.54-0.95). The above associations were significant at a nominal P < 0.05 level but not after correcting for multiple testing (Bonferroni P < 0.0009). Our analyses revealed notable associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with breast cancer survival outcomes. These findings implicate metabolic traits in breast cancer prognosis.

Significance

To our knowledge, this is the largest study of PGS for metabolic traits with breast cancer prognosis. The findings revealed significant associations of PGS for cardiovascular disease, hypertension, and cystatin C levels with several breast cancer survival outcomes. These findings implicate an underappreciated role of metabolic traits in breast cancer prognosis that would warrant further exploration.

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.

Establishment of a Cell Necroptosis Index to Predict Prognosis and Drug Sensitivity for Patients With Triple-Negative Breast Cancer

Background: Necroptosis has been an alternatively identified mechanism of programmed cancer cell death, which plays a significant role in cancer. However, research about necroptosis-related long noncoding RNAs (lncRNAs) in cancer are still few. Moreover, the potentially prognostic value of necroptosis-related lncRNAs and their correlation with the immune microenvironment remains unclear. The present study aimed to explore the potential prognostic value of necroptosis-related lncRNAs and their relationship to immune microenvironment in triple-negative breast cancer (TNBC).

Methods: The RNA expression matrix of patients with TNBC was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Finally, 107 patients of GSE58812, 159 patients of TCGA, and 143 patients of GSE96058 were included. Necroptosis-related lncRNAs were screened by Cox regression and Pearson correlation analysis with necroptosis-related genes. By LASSO regression analysis, nine necroptosis-related lncRNAs were employed, and a cell necroptosis index (CNI) was established; then, we evaluated its prognostic value, clinical significance, pathways, immune infiltration, and chemotherapeutics efficacy.

Results: Based on the CNI value, the TNBC patients were divided into high- and low-CNI groups, and the patients with high CNI had worse prognosis, more lymph node metastasis, and larger tumor (p < 0.05). The receiver operating characteristic (ROC) analysis showed that the signature performed well. The result of the infiltration proportion of different immune cell infiltration further explained that TNBC patients with high CNI had low immunogenicity, leading to poor therapeutic outcomes. Moreover, we found significant differences of the IC50 values of various chemotherapeutic drugs in the two CNI groups, which might provide a reference to make a personalized chemotherapy for them.

Conclusion: The novel prognostic marker CNI could not only precisely predict the survival probability of patients with TNBC but also demonstrate a potential role in antitumor immunity and drug sensitivity.

UACA locus is associated with breast cancer chemoresistance and survival

Few germline genetic variants have been robustly linked with breast cancer outcomes. We conducted trans-ethnic meta genome-wide association study (GWAS) of overall survival (OS) in 3973 breast cancer patients from the Pathways Study, one of the largest prospective breast cancer survivor cohorts. A locus spanning the UACA gene, a key regulator of tumor suppressor Par-4, was associated with OS in patients taking Par-4 dependent chemotherapies, including anthracyclines and anti-HER2 therapy, at a genome-wide significance level (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 1.27 \times 10^{ - 9}$$\end{document}P=1.27×10−9). This association was confirmed in meta-analysis across four independent prospective breast cancer cohorts (combined hazard ratio = 1.84, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 1.28 \times 10^{ - 11}$$\end{document}P=1.28×10−11). Transcriptome-wide association study revealed higher UACA gene expression was significantly associated with worse OS (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P = 4.68 \times 10^{ - 7}$$\end{document}P=4.68×10−7). Our study identified the UACA locus as a genetic predictor of patient outcome following treatment with anthracyclines and/or anti-HER2 therapy, which may have clinical utility in formulating appropriate treatment strategies for breast cancer patients based on their genetic makeup.

Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

BACKGROUND

Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients.

METHODS

We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15).

RESULTS

Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy.

CONCLUSIONS

We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited.

ADAM and ADAMTS Proteins, New Players in the Regulation of Hepatocellular Carcinoma Microenvironment

Simple Summary

Members of the adamalysin family are multi-domain proteins involved in many cancer-related functions. In this review, we will examine the literature on the involvement of adamalysins in hepatocellular carcinoma progression and their importance in the tumor microenvironment where they regulate the inflammatory response and the epithelial–mesenchymal transition. We complete this review with an analysis of adamalysin expression in a large cohort of patients with hepatocellular carcinoma from The Cancer Genome Atlas (TCGA) database. These original results give a new insight into the involvement of all adamalysins in the primary liver cancer.

Abstract

The tumor microenvironment plays a major role in tumor growth, invasion and resistance to chemotherapy, however understanding how all actors from microenvironment interact together remains a complex issue. The tumor microenvironment is classically represented as three closely connected components including the stromal cells such as immune cells, fibroblasts, adipocytes and endothelial cells, the extracellular matrix (ECM) and the cytokine/growth factors. Within this space, proteins of the adamalysin family (ADAM for a disintegrin and metalloproteinase; ADAMTS for ADAM with thrombospondin motifs; ADAMTSL for ADAMTS-like) play critical roles by modulating cell–cell and cell–ECM communication. During last decade, the implication of adamalysins in the development of hepatocellular carcinoma (HCC) has been supported by numerous studies however the functional characterization of most of them remain unsettled. In the present review we propose both an overview of the literature and a meta-analysis of adamalysins expression in HCC using data generated by The Cancer Genome Atlas (TCGA) Research Network.

The Unique Biology behind the Early Onset of Breast Cancer

Breast cancer commonly affects women of older age; however, in developing countries, up to 20% of breast cancer cases present in young women (younger than 40 years as defined by oncology literature). Breast cancer in young women is often defined to be aggressive in nature, usually of high histological grade at the time of diagnosis and negative for endocrine receptors with poor overall survival rate. Several researchers have attributed this aggressive nature to a hidden unique biology. However, findings in this aspect remain controversial. Thus, in this article, we aimed to review published work addressing somatic mutations, chromosome copy number variants, single nucleotide polymorphisms, differential gene expression, microRNAs and gene methylation profile of early-onset breast cancer, as well as its altered pathways resulting from those aberrations. Distinct biology behind early-onset of breast cancer was clear among estrogen receptor-positive and sporadic cases. However, further research is needed to determine and validate specific novel markers, which may help in customizing therapy for this group of patients.

A Ten-N6-Methyladenosine (m6A)-Modified Gene Signature Based on a Risk Score System Predicts Patient Prognosis in Rectum Adenocarcinoma

OBJECTIVES

The study aims to analyze the expression of N6-methyladenosine (m6A)-modified genes in rectum adenocarcinoma (READ) and identify reliable prognostic biomarkers to predict the prognosis of READ.

MATERIALS AND METHODS

RNA sequence data of READ and corresponding clinical survival data were obtained from The Cancer Genome Atlas (TCGA) database. N6-methyladenosine (m6A)-modified genes in READ were downloaded from the "m6Avar" database. Differentially expressed m6A-modified genes in READ stratified by different clinicopathological characteristics were identified using the "limma" package in R. Protein-protein interaction (PPI) network and co-expression analysis of differentially expressed genes (DEGs) were performed using "STRING" and Cytoscape, respectively. Principal component analysis (PCA) was done using R. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to functionally annotate the differentially expressed genes in different subgroups. Univariate Cox regression analyses were conducted to identify the powerful independent prognostic factors in READ associated with overall survival (OS). A robust likelihood-based survival model was built using the "rbsurv" package to screen for survival-associated signature genes. The Support Vector Machine (SVM) was used to predict the prognosis of READ through the risk score of survival-associated signature genes. Correlation analysis were carried out using GraphPad prism 8.

RESULTS

We screened 974 differentially expressed m6A-modified genes among four types of READ samples. Two READ subgroups (group 1 and group 2) were identified by K means clustering according to the expression of DEGs. The two subgroups were significantly different in overall survival and pathological stages. Next, 118 differentially expressed genes between the two subgroups were screened and the expression of 112 genes was found to be related to the prognosis of READ. Next, a panel of 10 survival-associated signature genes including adamtsl1, csmd2, fam13c, fam184a, klhl4, olfml2b, pdzd4, sec14l5, setbp1, tmem132b was constructed. The signature performed very well for prognosis prediction, time-dependent receiver-operating characteristic (ROC) analysis displaying an area under the curve (AUC) of 0.863, 0.8721, and 0.8752 for 3-year survival rate, prognostic status, and pathological stage prediction, respectively. Correlation analysis showed that the expression levels of the 10 m6A-modified genes were positively correlated with that of m6A demethylase FTO and ALKBH5.

CONCLUSION

This study identified potential m6A-modified genes that may be involved in the pathophysiology of READ and constructed a novel gene expression panel for READ risk stratification and prognosis prediction.

Identification of critical genetic variants associated with metabolic phenotypes of the Japanese population

We performed a metabolome genome-wide association study for the Japanese population in the prospective cohort study of Tohoku Medical Megabank. By combining whole-genome sequencing and nontarget metabolome analyses, we identified a large number of novel associations between genetic variants and plasma metabolites. Of the identified metabolite-associated genes, approximately half have already been shown to be involved in various diseases. We identified metabolite-associated genes involved in the metabolism of xenobiotics, some of which are from intestinal microorganisms, indicating that the identified genetic variants also markedly influence the interaction between the host and symbiotic bacteria. We also identified five associations that appeared to be female-specific. A number of rare variants that influence metabolite levels were also found, and combinations of common and rare variants influenced the metabolite levels more profoundly. These results support our contention that metabolic phenotyping provides important insights into how genetic and environmental factors provoke human diseases.

Comprehensive Cohort Analysis of Mutational Spectrum in Early Onset Breast Cancer Patients

Early onset breast cancer (EOBC), diagnosed at age ~40 or younger, is associated with a poorer prognosis and higher mortality rate compared to breast cancer diagnosed at age 50 or older. EOBC poses a serious threat to public health and requires in-depth investigation. We studied a cohort comprising 90 Taiwanese female patients, aiming to unravel the underlying mechanisms of EOBC etiopathogenesis. Sequence data generated by whole-exome sequencing (WES) and whole-genome sequencing (WGS) from white blood cell (WBC)-tumor pairs were analyzed to identify somatic missense mutations, copy number variations (CNVs) and germline missense mutations. Similar to regular breast cancer, the key somatic mutation-susceptibility genes of EOBC include TP53 (40% prevalence), PIK3CA (37%), GATA3 (17%) and KMT2C (17%), which are frequently reported in breast cancer; however, the structural protein-coding genes MUC17 (19%), FLG (16%) and NEBL (11%) show a significantly higher prevalence in EOBC. Furthermore, the top 2 genes harboring EOBC germline mutations, MUC16 (19%) and KRT18 (19%), encode structural proteins. Compared to conventional breast cancer, an unexpectedly higher number of EOBC susceptibility genes encode structural proteins. We suspect that mutations in structural proteins may increase physical permeability to environmental hormones and carcinogens and cause breast cancer to occur at a young age.

A functional variant near XCL1 gene improves breast cancer survival via promoting cancer immunity

Most genome-wide association studies (GWASs) identify genetic variants for breast cancer occurrence. In contrast, few are for recurrence and mortality. We conducted a GWAS on breast cancer survival after diagnosis in estrogen receptor-positive patients, including 953 Taiwanese patients with 159 events. Through Cox proportional hazard models estimation, we identified 24 risk SNPs with p < 1 × 10^-5 . Based on imputation and integrated analysis, one SNP, rs1024176 (located in 1q24.2, p = 2.43 × 10^-5 ) was found to be a functional variant associated with breast cancer survival and XCL1 gene expression. A series of experimental approaches, including cell-based analyses and CRISPR/Cas9 genome-editing system, were then used and identified the transcription factor MYBL2 was able to discriminately bind to the A allele of rs1024176, the protective variant for breast cancer survival, which promoted XCL1 expression, but not to the G allele of rs1024176. The chemokine XCL1 attracts type 1 dendritic cells (DC1s) to the tumor microenvironment. In breast cancer tissues, we applied a two-step Mendelian randomization analysis, using expression quantitative trait loci as instrumental variables, to confirm higher XCL1 expression was correlated with higher DC1 signatures and favorable disease progression, through the causal effect of rs1024176-A allele. Our study supports the genetic effect on preventing breast cancer survival through XCL1-induced DC1 recruitment in tumor microenvironment.

Local extraction and detection of early stage breast cancers through a microneedle and nano-Ag/MBL film based painless and blood-free strategy

Early diagnosis is the key to the good prognosis of breast cancer. At present, clinical tumor diagnosis is mainly through serum analysis, which is painful and can only detect relatively advanced tumors that have already metastasized from the glands into the blood circulation. Here, we developed an earlier diagnostic method (before tumor cells entering the blood) of breast cancers through a convenient and painless process with blood-free samples. The microneedles were utilized to insert into the animals' testing areas, while the tissue fluid was collected through our synthesized breathable thin film. The obtained tissue fluid sample was then incubated to form blue products. In the area where tumors occurred, the blue changes were more obvious than the healthy area, a semi-localization and semi-quantitative detection of the tumorous area thus could be realized. The results of corresponding animal experiments showed that, after the injection of tumor cells, the proposed nano-Ag based colorimetric method can detect the occurrence of breast cancers in 7 days. What is more, these early tumors could be effectively suppressed through classical DOX treatment. For comparison, the classical blood test needed 14 days to validate the occurrence of breast cancers. The subsequent human tests further demonstrated the feasibility of the present method. The development of this work could provide a more convenient, accurate and comfortable technology to support for the early screening and diagnosis of cancer patients, so as to fundamentally reduce the mortality of the breast cancers.

High WDR34 mRNA expression as a potential prognostic biomarker in patients with breast cancer as determined by integrated bioinformatics analysis

The WD-repeat domain (WDR) family is distributed in the majority of eukaryotes and has several unique biological functions. It serves important roles in signal transduction, cytoskeleton assembly, protein transport, RNA processing, chromatin modification and transcription mechanisms. WD repeat domain 34 (WDR34) has been recently identified as a member of the WDR family. Overexpression of WDR34 was accompanied by the presence of multiple centrioles in the cell, suggesting that it was associated with tumor occurrence. However, its association with breast cancer was unclear. To the best of our knowledge, it has not yet been confirmed whether WDR34 gene expression is associated with breast cancer. Therefore, the current study attempted to clarify this by performing a comprehensive study using multiple datasets in the Oncomine, Breast Cancer Gene-Expression Miner and Kaplan-Meier Plotter databases. The analysis indicated that the mRNA expression levels of WDR34 were increased in breast cancer tissues compared with normal tissues. Consistent with this result, the Broad-Novartis Cancer Cell Line Encyclopedia revealed that WDR34 mRNA expression levels were upregulated in breast cancer cell lines compared with other cancer cells. It was noted that high WDR34 mRNA expression was associated with forkhead box M1 and PTTG1 regulator of sister chromatid separation, securing in co-expression analysis. Expression profile characteristics of WDR34 mRNA were identified in different molecular subtypes of breast cancer. Furthermore, survival analysis revealed that increased expression levels of WDR34 mRNA were associated with poor overall survival in patients with breast cancer, particularly in luminal B, lymph node status-positive and estrogen receptor (ER)-negative subgroups. Additionally, Kaplan-Meier curves revealed that high WDR34 mRNA expression was associated with shorter relapse-free survival in patients with breast cancer, particularly in ER-positive, human epidermal growth factor receptor 2-negative and progesterone receptor-positive subgroups. These results suggested that WDR34 may be used as a prognosis predictor in breast cancer and may provide a novel target for the diagnosis and treatment of breast cancer.

Integrating of genomic and transcriptomic profiles for the prognostic assessment of breast cancer

PURPOSE

To evaluate the prognostic effect of the integration of genomic and transcriptomic profiles in breast cancer.

METHODS

Eight hundred and ten samples from the Cancer Genome Atlas (TCGA) data sets were randomly divided into the training set (540 subjects) and validation set (270 subjects). We first selected single-nucleotide polymorphism (SNPs) and genes associated with breast cancer prognosis in the training set to construct the prognostic prediction model, and then replicated the prediction efficiency in the validation set.

RESULTS

Four SNPs and three genes associated with the prognosis of breast cancer in the training set were included in the prognostic model. Patients were divided into the high-risk group and low-risk group based on the four SNPs and three genes signature-based genetic prognostic index. High-risk patients showed a significant worse overall survival [Hazard Ratio (HR) 9.43, 95% confidence interval (CI) 3.81-23.33, P < 0.001] than the low-risk group. Compared to the model constructed with only gene expression, the C statistics for the signature-based genetic prognostic index [area under curves (AUC) = 0.79, 95% CI 0.72-0.86] showed a significant increase (P < 0.001). Additionally, we further replicated the prognostic prediction model in the validation set as patients in the high-risk group also showed a significantly worse overall survival (HR 4.55, 95% CI 1.50-13.88, P < 0.001), and the C statistics for the signature-based genetic prognostic index was 0.76 (95% CI 0.65-0.86). The following time-dependent ROC revealed that the mean of AUCs were 0.839 and 0.748 in the training set and the validation set, respectively.

CONCLUSIONS

Our findings suggested that integrating genomic and transcriptomic profiles could greatly improve the predictive efficiency of the prognosis of breast cancer patients.

Genome-wide association study of germline variants and breast cancer-specific mortality

BACKGROUND

We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.

METHODS

Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).

RESULTS

We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10-8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10-7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10-7, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.

CONCLUSIONS

We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.

ADAMTSL4, a Secreted Glycoprotein, Is a Novel Immune-Related Biomarker for Primary Glioblastoma Multiforme

Background

Researches on immunotherapy of glioblastoma multiforme (GBM, WHO grade IV) have increased exponentially in recent years. As a targeted therapy, a series of biomarkers have been identified in local tumor tissue, while circulating marker which could be detected in the body fluids is still lacking. ADAMTSL4, a secreted glycoprotein, was earlier found to play a critical role in a prognostic signature for primary GBM (pGBM). We aimed to investigate the role of ADAMTSL4 at transcriptome level and its relationship with clinical practice in pGBM.

Methods

A cohort of 88 pGBM patients with RNA-seq data from the Chinese Glioma Genome Atlas (CGGA) was analyzed, and 168 pGBM patients from TCGA were included as validation. Several bioinformatic methods and predictive tools were applied to investigate the ADAMTSL4-associated immune microenvironment status.

Results

We found that ADAMTSL4 was enriched in GBM (WHO grade IV), especially for those with IDH1/2 wild-type and MGMT unmethylated groups. According to the TCGA classification scheme, ADAMTSL4 can act as a potential marker for subtypes with poorer prognosis. Bioinformatic analyses revealed that ADAMTSL4 was significantly correlated to the immune-related processes in GBM (WHO grade IV), especially representing the infiltration of immune cells and complicated tumor microenvironment. Clinically, high expression of ADAMTSL4 was an independent indicator for poor prognosis.

Conclusion

The expression of ADAMTSL4 is closely related to the clinicopathologic characteristics of pGBM. Meanwhile, it may play a critical role in immune-related processes. As a secreted glycoprotein, ADAMTSL4 is a promising circulating biomarker for pGBM, deserving further investigations.