JAK2 expression is associated with tumor-infiltrating lymphocytes and improved breast cancer outcomes: implications for evaluating JAK2 inhibitors.

Janus kinase-2 (JAK2) supports breast cancer growth, and clinical trials testing JAK2 inhibitors are under way. In addition to the tumor epithelium, JAK2 is also expressed in other tissues including immune cells; whether the JAK2 mRNA levels in breast tumors correlate with outcomes has not been evaluated. Using a case-control design, JAK2 mRNA was measured in 223 archived breast tumors and associations with distant recurrence were evaluated by logistic regression. The frequency of correct pairwise comparisons of patient rankings based on JAK2 levels versus survival outcomes, the concordance index (CI), was evaluated using data from 2,460 patients in three cohorts. In the case-control study, increased JAK2 was associated with a decreasing risk of recurrence (multivariate P = 0.003, n = 223). Similarly, JAK2 was associated with a protective CI (<0.5) in the public cohorts: NETHERLANDS CI = 0.376, n = 295; METABRIC CI = 0.462, n = 1,981; OSLOVAL CI = 0.452, n = 184. Furthermore, JAK2 was strongly correlated with the favorable prognosis LYM metagene signature for infiltrating T cells (r = 0.5; P < 2 × 10(-16); n = 1,981) and with severe lymphocyte infiltration (P = 0.00003, n = 156). Moreover, the JAK1/2 inhibitor ruxolitinib potently inhibited the anti-CD3-dependent production of IFN-γ, a marker of the differentiation of Th cells along the tumor-inhibitory Th1 pathway. The potential for JAK2 inhibitors to interfere with the antitumor capacities of T cells should be evaluated.

An integrative genomic approach identifies p73 and p63 as activators of miR-200 microRNA family transcription.

Although microRNAs (miRNAs) are important regulators of gene expression, the transcriptional regulation of miRNAs themselves is not well understood. We employed an integrative computational pipeline to dissect the transcription factors (TFs) responsible for altered miRNA expression in ovarian carcinoma. Using experimental data and computational predictions to define miRNA promoters across the human genome, we identified TFs with binding sites significantly overrepresented among miRNA genes overexpressed in ovarian carcinoma. This pipeline nominated TFs of the p53/p63/p73 family as candidate drivers of miRNA overexpression. Analysis of data from an independent set of 253 ovarian carcinomas in The Cancer Genome Atlas showed that p73 and p63 expression is significantly correlated with expression of miRNAs whose promoters contain p53/p63/p73 family binding sites. In experimental validation of specific miRNAs predicted by the analysis to be regulated by p73 and p63, we found that p53/p63/p73 family binding sites modulate promoter activity of miRNAs of the miR-200 family, which are known regulators of cancer stem cells and epithelial-mesenchymal transitions. Furthermore, in chromatin immunoprecipitation studies both p73 and p63 directly associated with the miR-200b/a/429 promoter. This study delineates an integrative approach that can be applied to discover transcriptional regulatory mechanisms in other biological settings where analogous genomic data are available.

Use of a single-chain antibody library for ovarian cancer biomarker discovery.

The discovery of novel early detection biomarkers of disease could offer one of the best approaches to decrease the morbidity and mortality of ovarian and other cancers. We report on the use of a single-chain variable fragment antibody library for screening ovarian serum to find novel biomarkers for the detection of cancer. We alternately panned the library with ovarian cancer and disease-free control sera to make a sublibrary of antibodies that bind proteins differentially expressed in cancer. This sublibrary was printed on antibody microarrays that were incubated with labeled serum from multiple sets of cancer patients and controls. The antibodies that performed best at discriminating disease status were selected, and their cognate antigens were identified using a functional protein microarray. Overexpression of some of these antigens was observed in cancer serum, tumor proximal fluid, and cancer tissue via dot blot and immunohistochemical staining. Thus, our use of recombinant antibody microarrays for unbiased discovery found targets for ovarian cancer detection in multiple sample sets, supporting their further study for disease diagnosis.

DNA methylation profiles of ovarian epithelial carcinoma tumors and cell lines.

BACKGROUND: Epithelial ovarian carcinoma is a significant cause of cancer mortality in women worldwide and in the United States. Epithelial ovarian cancer comprises several histological subtypes, each with distinct clinical and molecular characteristics. The natural history of this heterogeneous disease, including the cell types of origin, is poorly understood. This study applied recently developed methods for high-throughput DNA methylation profiling to characterize ovarian cancer cell lines and tumors, including representatives of three major histologies. METHODOLOGY/PRINCIPAL FINDINGS: We obtained DNA methylation profiles of 1,505 CpG sites (808 genes) in 27 primary epithelial ovarian tumors and 15 ovarian cancer cell lines. We found that the DNA methylation profiles of ovarian cancer cell lines were markedly different from those of primary ovarian tumors. Aggregate DNA methylation levels of the assayed CpG sites tended to be higher in ovarian cancer cell lines relative to ovarian tumors. Within the primary tumors, those of the same histological type were more alike in their methylation profiles than those of different subtypes. Supervised analyses identified 90 CpG sites (68 genes) that exhibited 'subtype-specific' DNA methylation patterns (FDR<1%) among the tumors. In ovarian cancer cell lines, we estimated that for at least 27% of analyzed autosomal CpG sites, increases in methylation were accompanied by decreases in transcription of the associated gene. SIGNIFICANCE: The significant difference in DNA methylation profiles between ovarian cancer cell lines and tumors underscores the need to be cautious in using cell lines as tumor models for molecular studies of ovarian cancer and other cancers. Similarly, the distinct methylation profiles of the different histological types of ovarian tumors reinforces the need to treat the different histologies of ovarian cancer as different diseases, both clinically and in biomarker studies. These data provide a useful resource for future studies, including those of potential tumor progenitor cells, which may help illuminate the etiology and natural history of these cancers.

Quantitative proteomics analysis integrated with microarray data reveals that extracellular matrix proteins, catenins, and p53 binding protein 1 are important for chemotherapy response in ovarian cancers.

Chemotherapy with carboplatin and paclitaxel is the standard treatment for ovarian cancer patients. Although most patients initially respond to this treatment, few are cured. Resistance to chemotherapy is the major cause of treatment failure. We applied a quantitative proteomic approach based on ICAT/MS/MS technology to analyze tissues harvested at primary debulking surgery before the initiation of combination chemotherapy in order to identify potential naive or intrinsic chemotherapy response proteins in ovarian cancers. We identified 44 proteins that are overexpressed, and 34 proteins that are underexpressed in the chemosensitive tissue compared to the chemoresistant tissue. The overexpressed proteins identified in the chemoresistant tissue include 10 proteins (25.6%) belonging to the extracellular matrix (ECM), including decorin, versican, basigin (CD147), fibulin-1, extracellular matrix protein 1, biglycan, fibronectin 1, dermatopontin, alpha-cardiac actin (smooth muscle actin), and an EGF-containing fibulin-like extracellular matrix protein 1. Interesting proteins identified as overexpressed in the chemosensitive tissue include gamma-catenin (junction plakoglobin) and delta-catenin, tumor suppressor p53-binding protein 1 (53BP1), insulin-like growth factor-binding protein 2 (IGFBP2), proliferating cell nuclear antigen (PCNA), annexin A11, and 53 kDa selenium binding protein 1. Integrative analysis with expression profiling data of eight chemoresistant tissues and 13 chemosensitive tissues revealed that 16 proteins showed consistent changes at both the protein and the RNA levels. These include P53 binding protein 1, catenin delta 1 and plakoglobin, EGF-containing fibulin-like extracellular matrix protein 1 and voltage-dependent anion-selective channel protein 1. Our results suggest that chemotherapy response may be determined by multiple and complex system properties involving extracellular-matrix, cell adhesion and junction proteins.

A mouse to human search for plasma proteome changes associated with pancreatic tumor development.

BACKGROUND: The complexity and heterogeneity of the human plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. Refined genetically engineered mouse (GEM) models of human cancer have been shown to faithfully recapitulate the molecular, biological, and clinical features of human disease. Here, we sought to exploit the merits of a well-characterized GEM model of pancreatic cancer to determine whether proteomics technologies allow identification of protein changes associated with tumor development and whether such changes are relevant to human pancreatic cancer. METHODS AND FINDINGS: Plasma was sampled from mice at early and advanced stages of tumor development and from matched controls. Using a proteomic approach based on extensive protein fractionation, we confidently identified 1,442 proteins that were distributed across seven orders of magnitude of abundance in plasma. Analysis of proteins chosen on the basis of increased levels in plasma from tumor-bearing mice and corroborating protein or RNA expression in tissue documented concordance in the blood from 30 newly diagnosed patients with pancreatic cancer relative to 30 control specimens. A panel of five proteins selected on the basis of their increased level at an early stage of tumor development in the mouse was tested in a blinded study in 26 humans from the CARET (Carotene and Retinol Efficacy Trial) cohort. The panel discriminated pancreatic cancer cases from matched controls in blood specimens obtained between 7 and 13 mo prior to the development of symptoms and clinical diagnosis of pancreatic cancer. CONCLUSIONS: Our findings indicate that GEM models of cancer, in combination with in-depth proteomic analysis, provide a useful strategy to identify candidate markers applicable to human cancer with potential utility for early detection.

Use of high density antibody arrays to validate and discover cancer serum biomarkers.

Perhaps the greatest barrier to translation of serum biomarker discoveries is the inability to evaluate putative biomarkers in high throughput validation studies. Here we report on the development, production, and implementation of a high-density antibody microarray used to evaluate large numbers of candidate ovarian cancer serum biomarkers. The platform was shown to be useful for evaluation of individual antibodies for comparative analysis, such as with disease classification, and biomarker validation and discovery. We demonstrate its performance by showing that known tumor markers behave as expected. We also identify several promising biomarkers from a candidate list and generate hypotheses to support new discovery studies.

10th Biennial Helene Harris Memorial Trust meeting.

Improving the prognosis of ovarian cancer patients is a major challenge to scientists and clinicians. At a recent multidisciplinary meeting in Washington DC, advances in identification of precursor lesions, progress in disease biomarkers and animal models, the promise of nanotechnology, and strategies for manipulation of the innate and adaptive immune response offered prospects for real progress in this difficult-to-treat disease.

Proteins associated with Cisplatin resistance in ovarian cancer cells identified by quantitative proteomic technology and integrated with mRNA expression levels.

Nearly all women diagnosed with ovarian cancer receive combination chemotherapy including cis- or carboplatin. Despite high initial response rates, resistance to cisplatin develops in roughly one-third of women during primary treatment and in all women treated for recurrent disease. ICAT coupled with tandem MS is a quantitative proteomic technique for high throughput protein expression profiling of complex protein mixtures. Using ICAT/MS/MS we profiled the nuclear, cytosolic, and microsomal fractions obtained from IGROV-1 [corrected] (cisplatin-sensitive) and IGROV-1/CP [corrected] (cisplatin-resistant) ovarian cancer cell lines. The proteomes of cisplatin-sensitive and -resistant ovarian cancer cells were compared, and protein expression was correlated with mRNA expression profiles. A total of 1117 proteins were identified and quantified. The relative expression of 121 of these varied between the two cell lines. Sixty-three proteins were overexpressed in cisplatin-sensitive, and 58 were over expressed in cisplatin-resistant cells. Examples of proteins at least 5-fold overexpressed in resistant cells and with biological relevance to cancer include cell recognition molecule CASPR3 (13.3-fold), S100 protein family members (8.7-fold), junction adhesion molecule Claudin 4 (7.2-fold), and CDC42-binding protein kinase beta (5.4-fold). Examples of cancer-related proteins at least 5-fold overexpressed in sensitive cells include hepatocyte growth factor inhibitor 1B (13.3-fold) and programmed cell death 6-interacting protein (12.7-fold). The direction of changes in expression levels between proteins and mRNAs were not always in the same direction, possibly reflecting posttranscriptional control of protein expression. We identified proteins whose expression profiles correlate with cisplatin resistance in ovarian cancer cells. Several proteins may be involved in modulating response to cisplatin and have potential as markers of treatment response or treatment targets.