Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups.

The rates and routes of lethal systemic spread in breast cancer are poorly understood owing to a lack of molecularly characterized patient cohorts with long-term, detailed follow-up data. Long-term follow-up is especially important for those with oestrogen-receptor (ER)-positive breast cancers, which can recur up to two decades after initial diagnosis1-6. It is therefore essential to identify patients who have a high risk of late relapse7-9. Here we present a statistical framework that models distinct disease stages (locoregional recurrence, distant recurrence, breast-cancer-related death and death from other causes) and competing risks of mortality from breast cancer, while yielding individual risk-of-recurrence predictions. We apply this model to 3,240 patients with breast cancer, including 1,980 for whom molecular data are available, and delineate spatiotemporal patterns of relapse across different categories of molecular information (namely immunohistochemical subtypes; PAM50 subtypes, which are based on gene-expression patterns10,11; and integrative or IntClust subtypes, which are based on patterns of genomic copy-number alterations and gene expression12,13). We identify four late-recurring integrative subtypes, comprising about one quarter (26%) of tumours that are both positive for ER and negative for human epidermal growth factor receptor 2, each with characteristic tumour-driving alterations in genomic copy number and a high risk of recurrence (mean 47-62%) up to 20 years after diagnosis. We also define a subgroup of triple-negative breast cancers in which cancer rarely recurs after five years, and a separate subgroup in which patients remain at risk. Use of the integrative subtypes improves the prediction of late, distant relapse beyond what is possible with clinical covariates (nodal status, tumour size, tumour grade and immunohistochemical subtype). These findings highlight opportunities for improved patient stratification and biomarker-driven clinical trials.

Long Non-Coding RNA H19 Acts as an Estrogen Receptor Modulator that is Required for Endocrine Therapy Resistance in ER+ Breast Cancer Cells.

BACKGROUND/AIMS: Blocking estrogen signaling with endocrine therapies (Tamoxifen or Fulverstrant) is an effective treatment for Estrogen Receptor-α positive (ER+) breast cancer tumours. Unfortunately, development of endocrine therapy resistance (ETR) is a frequent event resulting in disease relapse and decreased overall patient survival. The long noncoding RNA, H19, was previously shown to play a significant role in estrogen-induced proliferation of both normal and malignant ER+ breast epithelial cells. We hypothesized that H19 expression is also important for the proliferation and survival of ETR cells. METHODS: Here we utilized established ETR cell models; the Tamoxifen (Tam)-resistant LCC2 and the Fulvestrant and Tam cross-resistant LCC9 cells. Gain and loss of H19 function were achieved through lentiviral transduction as well as pharmacological inhibitors of the Notch and c-Met receptor signaling pathways. The effects of altered H19 expression on cell viability and ETR were assessed using three-dimensional (3D) organoid cultures and 2D co-cultures with low passage tumour-associated fbroblasts (TAFs). RESULTS: Here we report that treating ETR cells with Tam or Fulvestrant increases H19 expression and that it's decreased expression overcomes resistance to Tam and Fulvestrant in these cells. Interestingly, H19 expression is regulated by Notch and HGF signaling in the ETR cells and pharmacological inhibitors of Notch and c-MET signaling together significantly reverse resistance to Tam and Fulvestrant in an H19-dependent manner in these cells. Lastly, we demonstrate that H19 regulates ERα expression at the transcript and protein levels in the ETR cells and that H19 protects ERα against Fulvestrant-mediated downregulation of ERα protein. We also observed that blocking Notch and the c-MET receptor signaling also overcomes Fulvestrant and Tam resistance in 3D organoid cultures by decreasing ERα and H19 expression in the ETR cells. CONCLUSION: In endocrine therapy resistant breast cancer cells Fulvestrant is ineffective in decreasing ERα levels. Our data suggest that in the ETR cells, H19 expression acts as an ER modulator and that its levels and subsequently ERα levels can be substantially decreased by blocking Notch and c-MET receptor signaling. Consequently, treating ETR cells with these pharmacological inhibitors helps overcome resistance to Fulvestrant and Tamoxifen.

Genes and functions from breast cancer signatures.

BACKGROUND: Breast cancer is a heterogeneous disease and personalized medicine is the hope for the improvement of the clinical outcome. Multi-gene signatures for breast cancer stratification have been extensively studied in the past decades and more than 30 different signatures have been reported. A major concern is the minimal overlap of genes among the reported signatures. We investigated the breast cancer signature genes to address our hypothesis that the genes of different signature may share common functions, as well as to use these previously reported signature genes to build better prognostic models. METHODS: A total of 33 signatures and the corresponding gene lists were investigated. We first examined the gene frequency and the gene overlap in these signatures. Then the gene functions of each signature gene list were analysed and compared by the KEGG pathways and gene ontology (GO) terms. A classifier built using the common genes was tested using the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) data. The common genes were also tested for building the Yin Yang gene mean expression ratio (YMR) signature using public datasets (GSE1456 and GSE2034). RESULTS: Among a total of 2239 genes collected from the 33 breast cancer signatures, only 238 genes overlapped in at least two signatures; while from a total of 1979 function terms enriched in the 33 signature gene lists, 429 terms were common in at least two signatures. Most of the common function terms were involved in cell cycle processes. While there is almost no common overlapping genes between signatures developed for ER-positive (e.g. 21-gene signature) and those developed for ER-negative (e.g. basal signatures) tumours, they have common function terms such as cell death, regulation of cell proliferation. We used the 62 genes that were common in at least three signatures as a classifier and subtyped 1141 METABRIC cases including 144 normal samples into nine subgroups. These subgroups showed different clinical outcome. Among the 238 common genes, we selected those genes that are more highly expressed in normal breast tissue than in tumours as Yang genes and those more highly expressed in tumours than in normal as Yin genes and built a YMR model signature. This YMR showed significance in risk stratification in two datasets (GSE1456 and GSE2034). CONCLUSIONS: The lack of significant numbers of overlapping genes among most breast cancer signatures can be partially explained by our discovery that these signature genes represent groups with similar functions. The genes collected from these previously reported signatures are valuable resources for new model development. The subtype classifier and YMR signature built from the common genes showed promising results.

The exploration of contrasting pathways in Triple Negative Breast Cancer (TNBC).

BACKGROUND: Triple Negative Breast Cancers (TNBCs) lack the appropriate targets for currently used breast cancer therapies, conferring an aggressive phenotype, more frequent relapse and poorer survival rates. The biological heterogeneity of TNBC complicates the clinical treatment further. We have explored and compared the biological pathways in TNBC and other subtypes of breast cancers, using an in silico approach and the hypothesis that two opposing effects (Yin and Yang) pathways in cancer cells determine the fate of cancer cells. Identifying breast subgroup specific components of these opposing pathways may aid in selecting potential therapeutic targets as well as further classifying the heterogeneous TNBC subtype. METHODS: Gene expression and patient clinical data from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used for this study. Gene Set Enrichment Analysis (GSEA) was used to identify the more active pathways in cancer (Yin) than in normal and the more active pathways in normal (Yang) than in cancer. The clustering analysis was performed to compare pathways of TNBC with other types of breast cancers. The association of pathway classified TNBC sub-groups to clinical outcomes was tested using Cox regression model. RESULTS: Among 4729 curated canonical pathways in GSEA database, 133 Yin pathways (FDR < 0.05) and 71 Yang pathways (p-value <0.05) were discovered in TNBC. The FOXM1 is the top Yin pathway while PPARα is the top Yang pathway in TNBC. The TNBC and other types of breast cancers showed different pathways enrichment significance profiles. Using top Yin and Yang pathways as classifier, the TNBC can be further subtyped into six sub-groups each having different clinical outcomes. CONCLUSION: We first reported that the FOMX1 pathway is the most upregulated and the PPARα pathway is the most downregulated pathway in TNBC. These two pathways could be simultaneously targeted in further studies. Also the pathway classifier we performed in this study provided insight into the TNBC heterogeneity.

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA­RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 'CNA-devoid' subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.

A 16 Yin Yang gene expression ratio signature for ER+/node- breast cancer.

Breast cancer is one of the leading causes of cancer death in women. It is a complex and heterogeneous disease with different clinical outcomes. Stratifying patients into subgroups with different outcomes could help guide clinical decision making. In this study, we used two opposing groups of genes, Yin and Yang, to develop a prognostic expression ratio signature. Using the METABRIC cohort we identified a16-gene signature capable of stratifying breast cancer patients into four risk levels with intention that low-risk patients would not undergo adjuvant systemic therapy, intermediate-low-risk patients will be treated with hormonal therapy only, and intermediate-high- and high-risk groups will be treated by chemotherapy in addition to the hormonal therapy. The 16-gene signature for four risk level stratifications of breast cancer patients has been validated using 14 independent datasets. Notably, the low-risk group (n = 51) of 205 estrogen receptor-positive and node negative (ER+/node-) patients from three different datasets who had not had any systemic adjuvant therapy had 100% 15-year disease-specific survival rate. The Concordance Index of YMR for ER+/node negative patients is close to the commercially available signatures. However, YMR showed more significance (HR = 3.7, p = 8.7e-12) in stratifying ER+/node- subgroup than OncotypeDx (HR = 2.7, p = 1.3e-7), MammaPrint (HR = 2.5, p = 5.8e-7), rorS (HR = 2.4, p = 1.4e-6), and NPI (HR = 2.6, p = 1.2e-6). YMR signature may be developed as a clinical tool to select a subgroup of low-risk ER+/node- patients who do not require any adjuvant hormonal therapy (AHT).

The mechanistic target for rapamycin pathway is related to the phosphorylation score for estrogen receptor-α in human breast tumors in vivo.

INTRODUCTION: A phosphorylation score for estrogen receptor-alpha (ERα), called P7 score, was shown previously to be an independent prognostic factor in breast cancer patients treated with tamoxifen. Since mechanistic target of rapamycin (mTOR) activation is implicated in resistance to endocrine therapy in breast cancer we determined whether mechanistic target of rapamycin complex 1 (mTORC1) activation, measured by phosphorylation on S2448 (p-mTOR), was associated with the P7-score and/or clinical outcome in the same cohort. METHODS: mTOR phosphorylation status was determined at S2448 residue in vivo by immunohistochemistry in a cohort of more than 400 well-characterized ERα positive breast tumors. MCF7 cells were treated with estrogen and activation of mTOR pathway was determined by Western blotting. RESULTS: Contrary to earlier reports, p-mTOR expression, measured by immunohistochemistry, was negatively associated with size and nodal status. Additionally, p-S2448 mTOR expression was positively correlated with p-S118- ERα, p-S167-ERα and p-S282-ERα but negatively correlated with p-T311- ERα. Consistent with these, p-S2448 mTOR was negatively associated with P7-score and was significantly associated with overall survival (OS) (hazard ratio (HR) = 0.61, P = 0.028, 95% confidence interval (CI) 0.39 to 0.95, n = 337) and relapse-free survival (HR = 0.58, P = 0.0032, 95% CI 0.41 to 0.83, n = 337) following univariate but not multivariate analysis. Furthermore, we show that estrogen can regulate phosphorylation of mTOR and its down stream target p70S6 kinase. Additionally, recombinant mTOR can phosphorylate ERα in vitro. CONCLUSIONS: These data suggest that in breast tumors where there is intact estrogen regulated signaling, mTOR is regulated by estrogen and therefore associated with an increased likelihood of responsiveness to endocrine therapy.

ERß splice variant expression in four large cohorts of human breast cancer patient tumors.

Though the role of Estrogen Receptor (ER)α in breast cancer has been studied extensively, there is little consensus about the role of alternative ER isoform ERß in breast cancer biology. ERß has significant sequence homology to ERα but is located on a different chromosome and maintains both overlapping and unique functional attributes. Five variants exist, resulting from alternative splicing of the C-terminal region of ERß. The relevance of ERß variants in breast cancer outcomes and response to therapy is difficult to assess because of conflicting reports in the literature, likely due to variable methods used to assess ERß in patient tumors. Here, we quantitatively assess expression of ERß splice variants on over 2,000 breast cancer patient samples. Antibodies against ERß variants were validated for staining specificity in cell lines by siRNA knockdown of ESR2 and staining reproducibility on formalin-fixed paraffin-embedded tissue by quantitative immunofluorescence (QIF) using AQUA technology. We found antibodies against splice variants ERß1 and ERß5, but not ERß2/cx, which were sensitive, specific, and reproducible. QIF staining of validated antibodies showed both ERß1 and ERß5 QIF scores, which have a normal (bell shaped) distribution on most cohorts assessed, and their expression is significantly associated with each other. Extensive survival analyses show that ERß1 is not a prognostic or predictive biomarker for breast cancer. ERß5 appears to be a context-dependent marker of worse outcome in HER2-positive and triple-negative patients, suggesting an unknown biological function in the absence of ERα.

Origin of initial burst in activity for Trichoderma reesei endo-glucanases hydrolyzing insoluble cellulose.

The kinetics of cellulose hydrolysis have long been described by an initial fast hydrolysis rate, tapering rapidly off, leading to a process that takes days rather than hours to complete. This behavior has been mainly attributed to the action of cellobiohydrolases and often linked to the processive mechanism of this exo-acting group of enzymes. The initial kinetics of endo-glucanases (EGs) is far less investigated, partly due to a limited availability of quantitative assay technologies. We have used isothermal calorimetry to monitor the early time course of the hydrolysis of insoluble cellulose by the three main EGs from Trichoderma reesei (Tr): TrCel7B (formerly EG I), TrCel5A (EG II), and TrCel12A (EG III). These endo-glucanases show a distinctive initial burst with a maximal rate that is about 5-fold higher than the rate after 5 min of hydrolysis. The burst is particularly conspicuous for TrCel7B, which reaches a maximal turnover of about 20 s(-1) at 30 °C and conducts about 1200 catalytic cycles per enzyme molecule in the initial fast phase. For TrCel5A and TrCel12A the extent of the burst is 2-300 cycles per enzyme molecule. The availability of continuous data on EG activity allows an analysis of the mechanisms underlying the initial kinetics, and it is suggested that the slowdown is linked to transient inactivation of enzyme on the cellulose surface. We propose, therefore, that the frequency of structures on the substrate surface that cause transient inactivation determine the extent of the burst phase.

Claudin 1 expression in basal-like breast cancer is related to patient age.

BACKGROUND: Defects in tight junctions, gate-keepers of the integrity of the epidermal barrier function, are known to contribute to cancer development. As such, enhancing our understanding of how the expression of proteins involved in these junctions is regulated in cancer, remains a priority. Although the expression of one of these proteins, claudin 1, is down regulated in most invasive human breast cancers (HBC), we have recently shown that high levels of claudin 1, characterized tumors belonging to the very aggressive basal-like breast cancer (BLBC) subtype. In these tumors, the claudin 1 protein, usually localized in the cell membrane, is often mislocalized to the cytoplasm. METHODS: To examine the clinical relevance of this observation, we have generated and analyzed an invasive HBC tissue microarray consisting of 151 breast tumor samples; 79 of which presented a basal-like phenotype (i.e. ER-ve, PR-ve HER2-ve, CK5/6 or EGFR+ve). We also interrogated the outcome of claudin 1 knockdown in a human BLBC cell line, BT-20. RESULTS: Immunohistochemical analysis of this patient cohort revealed a significant association between high claudin 1 expression and BLBCs in women 55 years of age and older. Interestingly, no significant association was found between claudin 1 and nodal involvement, tumor grade or tumor size. Regression analysis however, showed a significant positive association between claudin 1 and claudin 4, even though claudin 4 did not significantly correlate with patient age. Claudin 1 knockdown in BT-20 cells resulted in decreased cell migration. It also significantly altered the expression of several genes involved in epithelial-mesenchymal-transition (EMT); in particular, SERPINE 1 (PAI1) and SSP1 (osteopontin), known to inhibit EMT and cancer cell migration. Conversely, genes known to maintain EMT through their interaction, SNAIL2, TCF4 and FOXC2 were significantly down regulated. CONCLUSIONS: The association of high claudin 1 protein levels observed in tumors derived from older women with BLBC, suggests that claudin 1 has the potential to serve as a marker which can identify a specific subgroup of patients within the BLBC subtype and thus, further contribute to the characterization of these ill-defined breast cancers. More importantly, our studies strongly suggest that claudin 1 directly participates in promoting breast cancer progression, possibly through the alteration of expression of EMT genes.

Development and validation of a prognostic 15-gene signature for stratifying HER2+/ER+ breast cancer.

Background: Human epidermal growth receptor 2-positive (HER2+) breast cancer (BC) is a heterogeneous subgroup. Estrogen receptor (ER) status is emerging as a predictive marker within HER2+ BCs, with the HER2+/ER+ cases usually having better survival in the first 5 years after diagnosis but have higher recurrence risk after 5 years compared to HER2+/ER-. This is possibly because sustained ER signaling in HER2+ BCs helps escape the HER2 blockade. Currently HER2+/ER+ BC is understudied and lacks biomarkers. Thus, a better understanding of the underlying molecular diversity is important to find new therapy targets for HER2+/ER+ BCs. Methods: In this study, we performed unsupervised consensus clustering together with genome-wide Cox regression analyses on the gene expression data of 123 HER2+/ER+ BC from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) cohort to identify distinct HER2+/ER+ subgroups. A supervised eXtreme Gradient Boosting (XGBoost) classifier was then built in TCGA using the identified subgroups and validated in another two independent datasets (Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO) (accession number GSE149283)). Computational characterization analyses were also performed on the predicted subgroups in different HER2+/ER+ BC cohorts. Results: We identified two distinct HER2+/ER+ subgroups with different survival outcomes using the expression profiles of 549 survival-associated genes from the Cox regression analyses. Genome-wide gene expression differential analyses found 197 differentially expressed genes between the two identified subgroups, with 15 genes overlapping the 549 survival-associated genes.XGBoost classifier, using the expression values of the 15 genes, achieved a strong cross-validated performance (Area under the curve (AUC) = 0.85, Sensitivity = 0.76, specificity = 0.77) in predicting the subgroup labels. Further investigation partially confirmed the differences in survival, drug response, tumor-infiltrating lymphocytes, published gene signatures, and CRISPR-Cas9 knockout screened gene dependency scores between the two identified subgroups. Conclusion: This is the first study to stratify HER2+/ER+ tumors. Overall, the initial results from different cohorts showed there exist two distinct subgroups in HER2+/ER+ tumors, which can be distinguished by a 15-gene signature. Our findings could potentially guide the development of future precision therapies targeted on HER2+/ER+ BC.

Obesity-associated changes in molecular biology of primary breast cancer.

Obesity is associated with an increased risk of developing breast cancer (BC) and worse prognosis in BC patients, yet its impact on BC biology remains understudied in humans. This study investigates how the biology of untreated primary BC differs according to patients' body mass index (BMI) using data from >2,000 patients. We identify several genomic alterations that are differentially prevalent in overweight or obese patients compared to lean patients. We report evidence supporting an ageing accelerating effect of obesity at the genetic level. We show that BMI-associated differences in bulk transcriptomic profile are subtle, while single cell profiling allows detection of more pronounced changes in different cell compartments. These analyses further reveal an elevated and unresolved inflammation of the BC tumor microenvironment associated with obesity, with distinct characteristics contingent on the estrogen receptor status. Collectively, our analyses imply that obesity is associated with an inflammaging-like phenotype. We conclude that patient adiposity may play a significant role in the heterogeneity of BC and should be considered for BC treatment tailoring.

Nuclear TIGAR mediates an epigenetic and metabolic autoregulatory loop via NRF2 in cancer therapeutic resistance.

Metabolic and epigenetic reprogramming play important roles in cancer therapeutic resistance. However, their interplays are poorly understood. We report here that elevated TIGAR (TP53-induced glycolysis and apoptosis regulator), an antioxidant and glucose metabolic regulator and a target of oncogenic histone methyltransferase NSD2 (nuclear receptor binding SET domain protein 2), is mainly localized in the nucleus of therapeutic resistant tumor cells where it stimulates NSD2 expression and elevates global H3K36me2 mark. Mechanistically, TIGAR directly interacts with the antioxidant master regulator NRF2 and facilitates chromatin recruitment of NRF2, H3K4me3 methylase MLL1 and elongating Pol-II to stimulate the expression of both new (NSD2) and established (NQO1/2, PRDX1 and GSTM4) targets of NRF2, independent of its enzymatic activity. Nuclear TIGAR confers cancer cell resistance to chemotherapy and hormonal therapy in vitro and in tumors through effective maintenance of redox homeostasis. In addition, nuclear accumulation of TIGAR is positively associated with NSD2 expression in clinical tumors and strongly correlated with poor survival. These findings define a nuclear TIGAR-mediated epigenetic autoregulatory loop in redox rebalance for tumor therapeutic resistance.

Data-driven identification of plasma metabolite clusters and metabolites of interest for potential detection of early-stage non-small cell lung cancer cases versus cancer-free controls.

BACKGROUND: Metabolomics is a potential means for biofluid-based lung cancer detection. We conducted a non-targeted, data-driven assessment of plasma from early-stage non-small cell lung cancer (ES-NSCLC) cases versus cancer-free controls (CFC) to explore and identify the classes of metabolites for further targeted metabolomics biomarker development. METHODS: Plasma from 250 ES-NSCLC cases and 250 CFCs underwent ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive and negative electrospray ionization (ESI) modes. Molecular feature extraction, formula generation, and find-by-ion tools annotated metabolic entities. Analysis was restricted to endogenous metabolites present in ≥ 80% of samples. Unsupervised hierarchical cluster analysis identified clusters of metabolites. The metabolites with the strongest correlation with the principal component of each cluster were included in logistic regression modeling to assess discriminatory performance with and without adjustment for clinical covariates. RESULTS: A total of 1900 UHPLC-QTOF-MS assessments identified 1667 and 2032 endogenous metabolites in the ESI-positive and ESI-negative modes, respectively. After data filtration, 676 metabolites remained, and 12 clusters of metabolites were identified from each ESI mode. Multivariable logistic regression using the representative metabolite from each cluster revealed effective classification of cases from controls with overall diagnostic accuracy of 91% (ESI positive) and 94% (ESI negative). Metabolites of interest identified for further targeted analysis include the following: 1b, 3a, 12a-trihydroxy-5b-cholanoic acid, pyridoxamine 5'-phosphate, sphinganine 1-phosphate, gamma-CEHC, 20-carboxy-leukotriene B4, isodesmosine, and 18-hydroxycortisol. CONCLUSIONS: Plasma-based metabolomic detection of early-stage NSCLC appears feasible. Further metabolomics studies targeting phospholipid, steroid, and fatty acid metabolism are warranted to further develop noninvasive metabolomics-based detection of early-stage NSCLC.

Advantages of isothermal titration calorimetry for xylanase kinetics in comparison to chemical-reducing-end assays.

In lignocellulosic raw materials for biomass conversion, hemicelluloses constitute a substantial fraction, with xylan being the primary part. Although many pretreatments reduce the amount or change the distribution of xylan, it is important to degrade residual xylan so as to improve the overall yield. Typically, xylanase reaction rates are measured in stopped assays by chemical quantification of the reducing ends. With isothermal titration calorimetry (ITC), the heat flow of the hydrolysis can be measured in continuous fashion, with the reaction rate being directly proportional to the heat flow. Reaction enthalpies for carbohydrate hydrolysis are typically below 5kJ/mol, which is the limiting factor for straight forward calorimetric quantification of enzymatic reaction rates using current ITC technology. To increase the apparent reaction enthalpy, we employed a subsequent oxidation of hydrolysis products by carbohydrate oxidase and catalase. Here we show that the coupled assay with carbohydrate oxidase and catalase can be used to measure enzyme kinetics of a GH10 xylanase from Aspergillus aculeatus on birch xylan and wheat arabinoxylan. Results are discussed in the light of a critical analysis of the sensitivity of four chemical-reducing-end quantification methods using well-characterized substrates.

Increasing the relative expression of endogenous non-coding Steroid Receptor RNA Activator (SRA) in human breast cancer cells using modified oligonucleotides.

Products of the Steroid Receptor RNA Activator gene (SRA1) have the unusual property to modulate the activity of steroid receptors and other transcription factors both at the RNA (SRA) and the protein (SRAP) level. Balance between these two genetically linked entities is controlled by alternative splicing of intron-1, whose retention alters SRAP reading frame. We have previously found that both fully-spliced SRAP-coding and intron-1-containing non-coding SRA RNAs co-exist in breast cancer cell lines. Herein, we report a significant (Student's t-test, P < 0.003) higher SRA-intron-1 relative expression in breast tumors with higher progesterone receptor contents. Using an antisense oligoribonucleotide, we have successfully reprogrammed endogenous SRA splicing and increased SRA RNA-intron-1 relative level in T5 breast cancer cells. This increase is paralleled by significant changes in the expression of genes such as plasminogen urokinase activator and estrogen receptor beta. Estrogen regulation of other genes, including the anti-metastatic NME1 gene, is also altered. Overall, our results suggest that the balance coding/non-coding SRA transcripts not only characterizes particular tumor phenotypes but might also, through regulating the expression of specific genes, be involved in breast tumorigenesis and tumor progression.

Computational Prediction of the Pathogenic Status of Cancer-Specific Somatic Variants.

In-silico classification of the pathogenic status of somatic variants is shown to be promising in promoting the clinical utilization of genetic tests. Majority of the available classification tools are designed based on the characteristics of germline variants or the combination of germline and somatic variants. Significance of somatic variants in cancer initiation and progression urges for development of classifiers specialized for classifying pathogenic status of cancer somatic variants based on the model trained on cancer somatic variants. We established a gold standard exclusively for cancer somatic single nucleotide variants (SNVs) collected from the catalogue of somatic mutations in cancer. We developed two support vector machine (SVM) classifiers based on genomic features of cancer somatic SNVs located in coding and non-coding regions of the genome, respectively. The SVM classifiers achieved the area under the ROC curve of 0.94 and 0.89 regarding the classification of the pathogenic status of coding and non-coding cancer somatic SNVs, respectively. Our models outperform two well-known classification tools including FATHMM-FX and CScape in classifying both coding and non-coding cancer somatic variants. Furthermore, we applied our models to predict the pathogenic status of somatic variants identified in young breast cancer patients from METABRIC and TCGA-BRCA studies. The results indicated that using the classification threshold of 0.8 our "coding" model predicted 1853 positive SNVs (out of 6,910) from the TCGA-BRCA dataset, and 500 positive SNVs (out of 1882) from the METABRIC dataset. Interestingly, through comparative survival analysis of the positive predictions from our models, we identified a young-specific pathogenic somatic variant with potential for the prognosis of early onset of breast cancer in young women.

Comparative metabolomics studies of blood collected in streck and heparin tubes from lung cancer patients.

Metabolomics analysis of blood from patients (n = 42) undergoing surgery for suspected lung cancer was performed in this study. Venous and arterial blood was collected in both Streck and Heparin tubes. A total of 96 metabolites were detected, affected by sex (n = 56), collection tube (n = 33), and blood location (n = 8). These metabolites belonged to a wide array of compound classes including lipids, acids, pharmaceutical agents, signalling molecules, vitamins, among others. Phospholipids and carboxylic acids accounted for 28% of all detected compounds. Out of the 33 compounds significantly affected by collection tube, 18 compounds were higher in the Streck tubes, including allantoin and ketoleucine, and 15 were higher in the Heparin tubes, including LysoPC(P-16:0), PS 40:6, and chenodeoxycholic acid glycine conjugate. Based on our results, it is recommended that replicate blood samples from each patient should be collected in different types of blood collection tubes for a broader range of the metabolome. Several metabolites were found at higher concentrations in cancer patients such as lactic acid in Squamous Cell Carcinoma, and lysoPCs in Adenocarcinoma and Acinar Cell Carcinoma, which may be used to detect early onset and/or to monitor the progress of the cancer patients.

DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation.

DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, reduced representation bisulfite sequencing (RRBS) profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, this study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors.

Assay development for the determination of phosphorylation stoichiometry using multiple reaction monitoring methods with and without phosphatase treatment: application to breast cancer signaling pathways.

We have developed a phosphatase-based phosphopeptide quantitation (PPQ) method for determining phosphorylation stoichiometry in complex biological samples. This PPQ method is based on enzymatic dephosphorylation, combined with specific and accurate peptide identification and quantification by multiple reaction monitoring (MRM) with stable-isotope-labeled standard peptides. In contrast with classical MRM methods for the quantitation of phosphorylation stoichiometry, the PPQ-MRM method needs only one nonphosphorylated SIS (stable isotope-coded standard) and two analyses (one for the untreated sample and one for the phosphatase-treated sample), from which the expression and modification levels can accurately be determined. From these analyses, the percent phosphorylation can be determined. In this manuscript, we compare the PPQ-MRM method with an MRM method without phosphatase and demonstrate the application of these methods to the detection and quantitation of phosphorylation of the classic phosphorylated breast cancer biomarkers (ERalpha and HER2), and for phosphorylated RAF and ERK1, which also contain phosphorylation sites of biological importance. Using synthetic peptides spiked into a complex protein digest, we were able to use our PPQ-MRM method to accurately determine the total phosphorylation stoichiometry on specific peptides as well as the absolute amount of the peptide and phosphopeptide present. Analyses of samples containing ERalpha protein revealed that the PPQ-MRM method is capable of determining phosphorylation stoichiometry in proteins from cell lines, and is in good agreement with determinations obtained using the direct MRM approach in terms of phosphorylation and total protein amount.