Functional relationship and gene ontology classification of breast cancer biomarkers

Pregnancy-associated plasma protein-A (PAPPA) promotes breast cancer progression

Breast cancer is the most common malignancy in females and poses a significant health threat to women. Pregnancy-associated plasma protein-A (PAPPA) is highly expressed in pregnancy-associated breast cancer (PABC) tissues. In this study, we investigated the functional role of PAPPA in regulating the malignant phenotype of breast cancer. We first examined the expression level of PAPPA in PABC tissue and breast cancer cell lines using quantitative real-time polymerase-chain reaction (qRT-PCR) and western blot. Next, the functional role of PAPPA in breast cancer cells was validated by overexpression and knockdown experiments. Cell counting kit-8 (CCK-8) proliferation assay, 5-ethynyl-2'-deoxyuridine (EdU) incorporation assay, wound healing and transwell invasion assay were used to examine cell proliferation, migration, and invasion ability. We further identified the microRNA target regulating PAPPA and studied its functional role. Finally, we examined the impact of PAPPA on the tumorigenesis and metastasis of breast cancer in mice model. Our study revealed that PAPPA was upregulated in PABC tissues and breast cancer cells. Overexpression of PAPPA promoted cell proliferation, motility, invasion, and epithelial-mesenchymal transition (EMT). We further identified miR-497-5p as a negative regulator of PAPPA, which suppressed cell proliferation, migration, invasion, and EMT in breast cancer cells. We also validated the oncogenic role of PAPPA in the mouse xenograft model. Collectively, our study suggests that PAPPA is an oncogenic protein highly expressed in PABC tissues and promotes breast cancer progression, which could serve as a novel therapeutic target for breast cancer.

Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance

Gene ontology (GO) is an eminent knowledge base frequently used for providing biological interpretations for the analysis of genes or gene sets from biological, medical and clinical problems. Unfortunately, the interpretation of such results is challenging due to the large number of GO terms, their hierarchical and connected organization as directed acyclic graphs (DAGs) and the lack of tools allowing to exploit this structural information explicitly. For this reason, we developed the R package GOxploreR. The main features of GOxploreR are (I) easy and direct access to structural features of GO, (II) structure-based ranking of GO-terms, (III) mapping to reduced GO-DAGs including visualization capabilities and (IV) prioritizing of GO-terms. The underlying idea of GOxploreR is to exploit a graph-theoretical perspective of GO as manifested by its DAG-structure and the containing hierarchy levels for cumulating semantic information. That means all these features enhance the utilization of structural information of GO and complement existing analysis tools. Overall, GOxploreR provides exploratory as well as confirmatory tools for complementing any kind of analysis resulting in a list of GO-terms, e.g., from differentially expressed genes or gene sets, GWAS or biomarkers. Our R package GOxploreR is freely available from CRAN.

Heat-induced hyperthermia impacts the follicular fluid proteome of the periovulatory follicle in lactating dairy cows

We hypothesized that heat-induced perturbations in cumulus cells surrounding the maturing oocyte may extend to the mural granulosa of the periovulatory follicle in the heat-stressed cow to subsequently the follicular fluid proteome. Lactating Holsteins were pharmacologically stimulated to have a dominant follicle that was capable of responding to a gonadotropin releasing hormone-induced luteinizing hormone surge. Following gonadotropin releasing hormone administration, cows were maintained at ~67 temperature humidity index (THI; thermoneutral conditions) or exposed to conditions simulating an acute heat stress event (71 to 86 THI; heat stress for ~12 h). Dominant follicle collection was conducted in the periovulatory period ~16 h after gonadotropin releasing hormone. Follicular fluid proteome from thermoneutral (n = 5) and hyperthermic (n = 5) cows was evaluated by quantitative tandem mass spectrometry (nano LC-MS/MS). We identified 35 differentially-abundant proteins. Functional annotation revealed numerous immune-related proteins. Subsequent efforts revealed an increase in levels of the proinflammatory mediator bradykinin in follicular fluid (P = 0.0456) but not in serum (P = 0.9319) of hyperthermic cows. Intrafollicular increases in transferrin (negative acute phase protein) in hyperthermic cows (P = 0.0181) coincided with a tendency for levels to be increased in the circulation (P = 0.0683). Nine out of 15 cytokines evaluated were detected in follicular fluid. Heat stress increased intrafollicular interleukin 6 levels (P = 0.0160). Whether hyperthermia-induced changes in the heat-stressed cow's follicular fluid milieu reflect changes in mural granulosa, cumulus, other cell types secretions, and/or transudative changes from circulation remains unclear. Regardless of origin, heat stress/hyperthermia related changes in the follicular fluid milieu may have an impact on components important for ovulation and competence of the cumulus-oocyte complex contained within the periovulatory follicle.

Classifying patients for breast cancer by detection of autoantibodies against a panel of conformation-carrying antigens

Patients with breast cancer elicit an autoantibody response against cancer proteins, which reflects and amplifies the cellular changes associated with tumorigenesis. Detection of autoantibodies in plasma may provide a minimally invasive mechanism for early detection of breast cancer. To identify cancer proteins that elicit a humoral response, we generated a cDNA library enriched for breast cancer genes that encode membrane and secreted proteins, which are more likely to induce an antibody response compared with intracellular proteins. To generate conformation-carrying antigens that are efficiently recognized by patients' antibodies, a eukaryotic expression strategy was established. Plasma from 200 patients with breast cancer and 200 age-matched healthy controls were measured for autoantibody activity against 20 different antigens designed to have conformational epitopes using ELISA. A conditional logistic regression model was used to select a combination of autoantibody responses against the 20 different antigens to classify patients with breast cancer from healthy controls. The best combination included ANGPTL4, DKK1, GAL1, MUC1, GFRA1, GRN, and LRRC15; however, autoantibody responses against GFRA1, GRN, and LRRC15 were inversely correlated with breast cancer. When the autoantibody responses against the 7 antigens were added to the base model, including age, BMI, race and current smoking status, the assay had the following diagnostic capabilities: c-stat (95% CI), 0.82 (0.78-0.86); sensitivity, 73%; specificity, 76%; and positive likelihood ratio (95% CI), 3.04 (2.34-3.94). The model was calibrated across risk deciles (Hosmer-Lemeshow, P = 0.13) and performed well in specific subtypes of breast cancer including estrogen receptor positive, HER-2 positive, invasive, in situ and tumor sizes >1 cm.

Selenium-responsive proteins in the sera of selenium-enriched yeast-supplemented healthy African American and Caucasian men

BACKGROUND

Studies have shown that supplementation of adult men with selenium-enriched yeast (SY) was protective against prostate cancer (PCa) and also reduced oxidative stress and levels of prostate-specific antigen. Here, we determined the effect of SY supplementation on global serum protein expression in healthy men to provide new insights into the mechanism of selenium chemoprevention; such proteins may also serve as biomarkers of disease progression.

METHODS

Serum samples from 36 adult men were obtained from our previous SY clinical trial, 9 months after supplementation with either SY (247 microg/d; n = 17) or placebo (nonenriched yeast; n = 19).

RESULTS

Proteomic profiling using two-dimensional difference in gel electrophoresis followed by liquid chromatography-tandem mass spectrometry revealed a total of 1,496 candidate proteins, of which, 11 were differentially expressed in the SY group as compared with placebo. Eight proteins were upregulated [clusterin isoform 1 (CLU), transthyretin, alpha-1B-glycoprotein, transferrin, complement component 4B proprotein, isocitrate dehydrogenase, haptoglobin, and keratin 1] and three proteins were downregulated [alpha-1 antitrypsin (AAT), angiotensin precursor, and albumin precursor] by SY. All of the identified proteins were redox-sensitive or involved in the regulation of redox status. Because both AAT and CLU have been previously linked to PCa development, their identities were confirmed by two-dimensional Western blot analysis.

CONCLUSIONS

We identified AAT and CLU as potential candidate proteins involved in the mechanism of PCa prevention by SY. Collectively, proteins identified in this study might serve as potential new biomarkers for monitoring and comparing responses to selenium-based chemopreventive agents.

IMPACT

Proteomic analysis of serum might be useful for the early detection and monitoring efficacy of chemopreventive agents.

Efficiency analysis of competing tests for finding differentially expressed genes in lung adenocarcinoma

In this study, we introduce and use Efficiency Analysis to compare differences in the apparent internal and external consistency of competing normalization methods and tests for identifying differentially expressed genes. Using publicly available data, two lung adenocarcinoma datasets were analyzed using caGEDA (http://bioinformatics2.pitt.edu/GE2/GEDA.html) to measure the degree of differential expression of genes existing between two populations. The datasets were randomly split into at least two subsets, each analyzed for differentially expressed genes between the two sample groups, and the gene lists compared for overlapping genes. Efficiency Analysis is an intuitive method that compares the differences in the percentage of overlap of genes from two or more data subsets, found by the same test over a range of testing methods. Tests that yield consistent gene lists across independently analyzed splits are preferred to those that yield less consistent inferences. For example, a method that exhibits 50% overlap in the 100 top genes from two studies should be preferred to a method that exhibits 5% overlap in the top 100 genes. The same procedure was performed using all available normalization and transformation methods that are available through caGEDA. The ‘best’ test was then further evaluated using internal cross-validation to estimate generalizable sample classification errors using a Naïve Bayes classification algorithm. A novel test, termed D1 (a derivative of the J5 test) was found to be the most consistent, and to exhibit the lowest overall classification error, and highest sensitivity and specificity. The D1 test relaxes the assumption that few genes are differentially expressed. Efficiency Analysis can be misleading if the tests exhibit a bias in any particular dimension (e.g. expression intensity); we therefore explored intensity-scaled and segmented J5 tests using data in which all genes are scaled to share the same intensity distribution range. Efficiency Analysis correctly predicted the ‘best’ test and normalization method using the Beer dataset and also performed well with the Bhattacharjee dataset based on both efficiency and classification accuracy criteria.

Proteomic analysis of nipple aspirate fluid from women with early-stage breast cancer using isotope-coded affinity tags and tandem mass spectrometry reveals differential expression of vitamin D binding protein

Background

Isotope-coded affinity tag (ICAT) tandem mass spectrometry (MS) allows for qualitative and quantitative analysis of paired protein samples. We sought to determine whether ICAT technology could quantify and identify differential expression of tumor-specific proteins in nipple aspirate fluid (NAF) from the tumor-bearing and contralateral disease-free breasts of patients with unilateral early-stage breast cancer.

Methods

Paired NAF samples from 18 women with stage I or II unilateral invasive breast carcinoma and 4 healthy volunteers were analyzed using ICAT labeling, sodium dodecyl sulfate-polyacrylamide gel (SDS-PAGE), liquid chromatography, and MS. Proteins were identified by sequence database analysis. Western blot analysis of NAF from an independent sample set from 12 women (8 with early-stage breast cancer and 4 healthy volunteers) was also performed.

Results

353 peptides were identified from tandem mass spectra and matched to peptide sequences in the National Center for Biotechnology Information database. Equal numbers of peptides were up- versus down-regulated. Alpha2HS-glycoprotein [Heavy:Light (H:L) ratio 0.63] was underexpressed in NAF from tumor-bearing breasts, while lipophilin B (H:L ratio 1.42), beta-globin (H:L ratio 1.98), hemopexin (H:L ratio 1.73), and vitamin D-binding protein precursor (H:L ratio 1.82) were overexpressed. Western blot analysis of pooled samples of NAF from healthy volunteers versus NAF from women with breast cancer confirmed the overexpression of vitamin D-binding protein in tumor-bearing breasts.

Conclusion

ICAT tandem MS was able to identify and quantify differences in specific protein expression between NAF samples from tumor-bearing and disease-free breasts. Proteomic screening techniques using ICAT and NAF may be used to find markers for diagnosis of breast cancer.

Integration of the Gene Ontology into an object-oriented architecture

BACKGROUND

To standardize gene product descriptions, a formal vocabulary defined as the Gene Ontology (GO) has been developed. GO terms have been categorized into biological processes, molecular functions, and cellular components. However, there is no single representation that integrates all the terms into one cohesive model. Furthermore, GO definitions have little information explaining the underlying architecture that forms these terms, such as the dynamic and static events occurring in a process. In contrast, object-oriented models have been developed to show dynamic and static events. A portion of the TGF-beta signaling pathway, which is involved in numerous cellular events including cancer, differentiation and development, was used to demonstrate the feasibility of integrating the Gene Ontology into an object-oriented model.

RESULTS

Using object-oriented models we have captured the static and dynamic events that occur during a representative GO process, "transforming growth factor-beta (TGF-beta) receptor complex assembly" (GO:0007181).

CONCLUSION

We demonstrate that the utility of GO terms can be enhanced by object-oriented technology, and that the GO terms can be integrated into an object-oriented model by serving as a basis for the generation of object functions and attributes.

Circulating biomarkers from tumour bulk to tumour machinery: promises and pitfalls

In this paper, we provide a working classification for circulating biomarkers according to their potential clinical application. We broadly divided biomarkers into four groups: (i) biomarkers of cancer risk, (ii) biomarkers of tumour-host interactions, (iii) biomarker of tumour burden, and (iv) function-related biomarkers. We hope this classification will provide a framework to which the results of future studies can be added. We also discuss the promises and pitfalls in the optional use of biomarkers in oncology.

Global search for chromosomal abnormalities in infiltrating ductal carcinoma of the breast using array-comparative genomic hybridization

Array-comparative genomic hybridization (a-CGH) is a molecular cytogenetic technique for detection of multiple chromosomal abnormalities in genomic DNA samples. Using an a-CGH with 287 probes, we examined 14 cases of breast infiltrating ductal carcinoma (IDCA) that had previously been classified by fluorescent in situ hybridization (FISH) as either human epidermal growth factor receptor-2 positive (HER2+) or HER2- and analyzed the data by hierarchical, K-means, and principal component analyses. The aim of the study was to identify the genetic abnormalities that are present in breast IDCAs and determine if the global status of 287 cytogenetic locations could be used as a more objective method for breast IDCA classification. Concordance between FISH and a-CGH at the HER2 locus was 78.6% (11/14). In general, a-CGH detected more abnormalities in HER2+ cases. In HER 2+ cases, chromosomes 1, 2, 3, 7, 9, 17, and 20 had more regions that showed statistically significant (P < or = 0.01) changes in DNA copy number. Among all the aberrant cytogenetic locations detected, 20q13, 7p12.3 approximately p12.1, and 17q23.2 approximately q25.3, which contain among others, genes for TNFRSF6B, EGFR, and TK1 showed statistically significant gains (P < or = 0.01) in 83, 66.7, and 50% of the HER2+ IDCA cases, respectively. Chromosome location 8q24.12 approximately q24.13 was the only region that showed consistent amplification in approximately 50% of the HER2- cases. Unsupervised hierarchical and K-means cluster analyses and principal component analysis using the DNA copy number status of 287 cytogenetic locations or the 177 cytogenetic locations that showed statistically significant differences revealed a cluster consisting of mainly HER2- IDCA cases. Even though this study demonstrates the usefulness of a-CGH in the rapid identification of aberrant DNA regions in tumor samples, we conclude that an array-CGH with more than 287 probes will be needed for a more precise mapping of DNA aberrations at the global level.