Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies.
Traditionally, scientific research has focused on studying individual events, such as single mutations, gene function or the effect of the manipulation of one protein on a biological phenotype. A range of technologies, combined with the ability to develop robust and predictive mathematical models, is beginning to provide information that will enable a holistic view of how the genomic and epigenetic aberrations in cancer cells can alter the homeostasis of signalling networks within these cells, between cancer cells and the local microenvironment, at the organ and organism level. This systems biology process needs to be integrated with an iterative approach wherein hypotheses and predictions that arise from modelling are refined and constrained by experimental evaluation. Systems biology approaches will be vital for developing and implementing effective strategies to deliver personalized cancer therapy. Specifically, these approaches will be important to select those patients most likely to benefit from targeted therapies as well as for the development and implementation of rational combinatorial therapies. Systems biology can help to increase therapy efficacy or bypass the emergence of resistance, thus converting the current (often short term) effects of targeted therapies into durable responses, ultimately to improve quality of life and provide a cure.
The serine/threonine kinase AKT is a key mediator of cancer cell survival. We demonstrate that transient glucose deprivation modestly induces AKT phosphorylation at both Thr308 and Ser473. In contrast, prolonged glucose deprivation induces selective AKTThr308 phosphorylation and phosphorylation of a distinct subset of AKT downstream targets leading to cell survival under metabolic stress. Glucose deprivation-induced AKTThr308 phosphorylation is dependent on PDK1 and PI3K but not EGFR or IGF1R. Prolonged glucose deprivation induces the formation of a complex of AKT, PDK1, and the GRP78 chaperone protein, directing phosphorylation of AKTThr308 but AKTSer473. Our results reveal a novel mechanism of AKT activation under prolonged glucose deprivation that protects cells from metabolic stress. The selective activation of AKTThr308 phosphorylation that occurs during prolonged nutrient deprivation may provide an unexpected opportunity for the development and implementation of drugs targeting cell metabolism and aberrant AKT signaling.
glucose deprivation; site specific AKT phosphorylation; substrate specific AKT activation; cell survival
Lysophosphatidic acid (LPA, 1- or 2-acyl-sn-glycerol 3-phosphate) mediates a plethora of physiological and pathological activities via interactions with a series of high affinity G protein-coupled receptors (GPCR). Both LPA receptor family members and autotaxin (ATX/LysoPLD), the primary LPA-producing enzyme, are aberrantly expressed in many human breast cancers and several other cancer lineages. Using transgenic mice expressing either an LPA receptor or ATX, we recently demonstrated that the ATX-LPA receptor axis plays a causal role in breast tumorigenesis and cancer-related inflammation, further validating the ATX-LPA receptor axis as a rich therapeutic target in cancer.
Breast cancer; ATX; LPA; G protein-coupled receptor; inflammation; cytokines; target therapy
Neoangiogenesis is an important feature in tumor growth and progression, and combining chemotherapy and antiangiogenic drugs have demonstrated clinical efficacy. However, as treatment induced resistance often develops our goal was to identify pathways indicating response and/or evolving resistance to treatment, and inhibit these pathways to optimize the treatment strategies.
To identify markers of response and/or resistance Reverse Phase Protein Array (RPPA) was utilized to characterize treatment-induced changes in a bevacizumab responsive and a nonresponsive human breast cancer xenograft. Results were combined with bioinformatic modeling to predict druggable targets for optimization of the treatment.
RPPA analysis showed that both tumor models responded to bevacizumab with an early (day 3) upregulation of growth factor receptors and downstream signaling pathways, with persistent mTOR signaling until the end of the in vivo experiment. Adding doxorubicin to bevacizumab showed significant and superior growth inhibition of basal-like tumors, whereas no additive effect was seen in the luminal-like model. The combination treatment corresponded to a continuous late attenuation of mTOR signaling in the basal-like model, while the inhibition was temporary in the luminal-like model. Integrating the bevacizumab-induced dynamic changes in protein levels with bioinformatic modeling predicted inhibition of PI3K-pathway to increase the efficacy of bevacizumab monotherapy. In vivo experiments combining bevacizumab and the PI3K/mTOR inhibitor BEZ235 confirmed their significant and additive growth inhibitory effect in the basal-like model.
Treatment with bevacizumab caused compensatory upregulation of several signaling pathways. Targeting such pathways increased the efficacy of antiangiogenic therapy.
There is growing evidence that cancer-initiation could result from epigenetic changes. Y-box binding protein-1 (YB-1) is a transcription/translation factor that promotes the formation of tumors in transgenic mice; however, the underlying molecular events are not understood. To explore this in a human model system, YB-1 was expressed in mammary epithelial cells under the control of a tetracycline-inducible promoter. The induction of YB-1 promoted phenotypes associated with malignancy in three-dimensional breast acini cultures. This was attributed to YB-1 enhancing the expression and activity of the histone acetyltransferase p300 leading to chromatin remodeling. Specifically, this relaxation of chromatin allowed YB-1 to bind to the BMI1 promoter. The induction of BMI1 engaged the Polycomb complex resulting in histone H2A ubiquitylation and repression of the CDKN2A locus. These events manifested functionally as enhanced self-renewal capacity that occurred in a BMI1-dependent manner. Conversely, p300 inhibition with anacardic acid prevented YB-1 from binding to the BMI1 promoter and thereby subverted self-renewal. Despite these early changes, full malignant transformation was not achieved until RSK2 became overexpressed concomitant with elevated hTERT activity. The YB-1/RSK2/hTERT expressing cells formed tumors in mice that were molecularly subtyped as basal-like breast cancer. We conclude that YB-1 cooperates with p300 to allow BMI1 to over-ride p16INK4a-mediated cell cycle arrest enabling self-renewal and the development of aggressive breast tumors.
Neoplastic cell transformation; Epigenetics; Breast cancer; Cancer stem cells; Human mammary epithelial cells (HMEC); Y-box binding protein-1 (YB-1)
Lysophosphatidic acid (LPA) acts through high affinity G protein-coupled receptors to mediate a plethora of physiological and pathological activities associated with tumorigenesis. LPA receptors and autotaxin (ATX/LysoPLD), the primary enzyme producing LPA, are aberrantly expressed in multiple cancer lineages. However, the role of ATX and LPA receptors in the initiation and progression of breast cancer has not been evaluated. We demonstrate that expression of ATX or each Edg-family LPA receptor in mammary epithelium of transgenic mice is sufficient to induce a high frequency of late-onset, estrogen receptor (ER) positive, invasive and metastatic mammary cancer. Thus ATX and LPA receptors can contribute to the initiation and progression of breast cancer.
LPA; ATX; Transgenic mouse model; Breast cancer; Metastasis
Acquired uniparental disomy (aUPD) can lead to homozygosity for tumor suppressor genes or oncogenes. Our purpose is to determine the frequency and profile aUPD regions in serous ovarian cancer (SOC) and investigated the association of aUPD with clinical features and patient outcomes.
We analyzed single nucleotide polymorphism (SNP) array-based genotyping data on 532 SOC specimens from The Cancer Genome Atlas database to identify aUPD regions. Cox univariate regression and Cox multivariate proportional hazards analyses were performed for survival analysis.
We found that 94.7% of SOC samples harbored aUPD; the most common aUPD regions were in chromosomes 17q (76.7%), 17p (39.7%), and 13q (38.3%). In Cox univariate regression analysis, two independent regions of aUPD on chromosome 17q (A and C), and whole-chromosome aUPD were associated with shorter overall survival (OS), and five regions on chromosome 17q (A, D-G) and BRCA1 were associated with recurrence-free survival time. In Cox multivariable proportional hazards analysis, whole-chromosome aUPD was associated with shorter OS. One region of aUPD on chromosome 22q (B) was associated with unilateral disease. A statistically significant association was found between aUPD at TP53 loci and homozygous mutation of TP53 (p < 0.0001).
aUPD is a common event and some recurrent loci are associated with a poor outcome for patients with serous ovarian cancer.
Electronic supplementary material
The online version of this article (doi:10.1186/s12943-015-0289-1) contains supplementary material, which is available to authorized users.
Acquired uniparental disomy; Ovarian cancer; Overall survival; Recurrence-free survival
Mutations in BRCA1/2 increase the risk of developing breast and ovarian cancer. Germline BRCA1/2 mutations occur in 8.6-13.7% of unselected epithelial ovarian cancers, somatic mutations are also frequent. BRCA1/2 mutated or dysfunctional cells may be sensitive to PARP inhibition by synthetic lethality. The aim of this study is to comprehensively characterise the BRCA1/2 status of a large panel of ovarian cancer cell lines available to the research community to assist in biomarker studies of novel drugs and in particular of PARP inhibitors.
The BRCA1/2 genes were sequenced in 41 ovarian cell lines, mRNA expression of BRCA1/2 and gene methylation status of BRCA1 was also examined. The cytotoxicity of PARP inhibitors olaparib and veliparib was examined in 20 cell lines.
The cell line SNU-251 has a deleterious BRCA1 mutation at 5564G>A, and is the only deleterious BRCA1/2 mutant in the panel. Two cell lines (UPN-251 and PEO1) had deleterious mutations as well as additional reversion mutations that restored the protein functionality. Heterozygous mutations in BRCA1/2 were relatively common, found in 14.6% of cell lines. BRCA1 was methylated in two cell lines (OVCAR8, A1847) and there was a corresponding decrease in gene expression. The BRCA1 methylated cell lines were more sensitive to PARP inhibition than wild-type cells. The SNU-251 deleterious mutant was more sensitive to PARP inhibition, but only in a long-term exposure to correct for its slow growth rate. Cell lines derived from metastatic disease are significantly more resistant to veliparib (2.0 fold p = 0.03) compared to those derived from primary tumours. Resistance to olaparib and veliparib was correlated Pearsons-R 0.5393, p = 0.0311.
The incidence of BRCA1/2 deleterious mutations 1/41 cell lines derived from 33 different patients (3.0%) is much lower than the population incidence. The reversion mutations and high frequency of heterozygous mutations suggest that there is a selective pressure against BRCA1/2 in cell culture similar to the selective pressure seen in the clinic after treatment with chemotherapy. PARP inhibitors may be useful in patients with BRCA1 deleterious mutations or gene methylation.
BRCA1/2; ovarian; mutation; methylation; parp inhibitor; olaparib; veliparib
Although breast cancers are known to be molecularly heterogeneous, their metabolic phenotype is less well understood and may predict response to chemotherapy. This study aimed to evaluate metabolic genes as individual predictive biomarkers in breast cancer.
mRNA microarray data from breast cancer cell lines were used to identify bimodal genes – those with highest potential for robust high/low classification in clinical assays. Metabolic function was evaluated in vitro for the highest scoring metabolic gene, lactate dehydrogenase B (LDHB). Its expression was associated with neoadjuvant chemotherapy response and relapse within clinical and PAM50-derived subtypes.
LDHB was highly expressed in cell lines with glycolytic, basal-like phenotypes. Stable knockdown of LDHB in cell lines reduced glycolytic dependence, linking LDHB expression directly to metabolic function. Using patient datasets, LDHB was highly expressed in basal-like cancers and could predict basal-like subtype within clinical groups (odds ratio = 21 for hormone-receptor (HR)-positive/HER2-negative; odds ratio = 10 for triple-negative). Furthermore, high LDHB predicted pathological complete response (pCR) to neoadjuvant chemotherapy for both HR-positive/HER2-negative (odds ratio = 4.1, P < .001) and triple-negative (odds ratio = 3.0, P = .003) cancers. For triple-negative tumors without pCR, high LDHB post-treatment also identified proliferative tumors with increased risk of recurrence (hazard ratio = 2.2, P = .006).
Expression of LDHB predicted response to neoadjuvant chemotherapy within clinical subtypes independently of standard prognostic markers and PAM50-subtyping. These observations support prospective clinical evaluation of LDHB as a predictive marker of response for breast cancer patients receiving neoadjuvant chemotherapy.
breast cancer; LDHB; lactate; glycolysis; Warburg
Signals from the tumor suppressors PTEN and LKB1 converge on mTOR to negatively regulate its function in cancer cells. Notably, both of these suppressors are attenuated in a significant fraction of human endometrial tumors. In this study, we generated a genetic mouse model of endometrial cancer driven by concomitant loss of these suppressors to gain pathophysiological insight into this disease. Dual loss of Pten and Lkb1 in the endometrial epithelium led to rapid development of advanced endometrioid endometrial tumors with 100% penetrance and short host survival. The tumors displayed dysregulated PI3K/Akt and Lkb1/Ampk signaling with hyperactivation of mTOR signaling. Treatment with a dual PI3K/mTOR inhibitor, BEZ235, extended the time before tumor onset and prolonged overall survival. The PI3K inhibitor GDC-0941 used as a single agent reduced the growth rate of primary tumor implants in Pten/Lkb1-deficient mice, and the mTOR inhibitor RAD001 was unexpectedly as effective as BEZ235 in triggering tumor regression. In parallel, we also found that ectopic expression of LKB1 in PTEN/LKB1-deficient human endometrial cancer cells increased their sensitivity to PI3K inhibition. Together, our results demonstrated that Pten/Lkb1-deficient endometrial tumors rely strongly on deregulated mTOR signaling, and they provided evidence that LKB1 status may modulate the response of PTEN-deficient tumors to PI3K or mTOR inhibitors.
To identify and validate copy number aberrations in early-stage primary breast tumors associated with bone or non-bone metastasis.
Patients and Methods
Whole-genome molecular inversion probe arrays were used to evaluate copy number imbalances (CNIs) in breast tumors from 960 early-stage patients with information about site of metastasis. The CoxBoost algorithm was used to select metastasis site-related CNIs and to fit a Cox proportional hazards model.
Gains at 1q41 and 1q42.12 and losses at 1p13.3, 8p22, and Xp11.3 were significantly associated with bone metastasis. Gains at 2p11.2, 3q21.3–22.2, 3q27.1, 10q23.1, and 14q13.2–3 and loss at 7q21.11 were associated with non-bone metastasis. To examine the joint effect of CNIs and clinical predictors, patients were stratified into three risk groups (low, intermediate, and high) based on the sum of predicted linear hazard ratios (HRs). For bone metastasis, the hazard (95% confidence interval) for the low-risk group was 0.32 (0.11–0.92) compared to the intermediate-risk group and 2.99 (1.74–5.11) for the high-risk group. For non-bone metastasis, the hazard for the low-risk group was 0.34 (0.17–0.66) and 2.33 (1.59–3.43) for the high-risk group. The prognostic value of loss at 8p22 for bone metastasis and gains at 10q23.1 for non-bone metastasis, and gain at 11q13.5 for both bone and non-bone metastases were externally validated in 335 breast tumors pooled from four independent cohorts.
Distinct CNIs are independently associated with bone and non-bone metastasis for early-stage breast cancer patients across cohorts. These data warrant consideration for tailoring surveillance and management of metastasis risk.
Breast cancer; bone metastasis; non-bone metastasis; copy number imbalances; molecular inversion probe array
Molecular profiling of tumors promises to advance the clinical management of cancer, but the benefits of integrating molecular data with traditional clinical variables have not been systematically studied. Here we retrospectively predict patient survival using diverse molecular data (somatic copy-number alteration, DNA methylation and mRNA, miRNA and protein expression) from 953 samples of four cancer types from The Cancer Genome Atlas project. We found that incorporating molecular data with clinical variables yielded statistically significantly improved predictions (FDR < 0.05) for three cancers but those quantitative gains were limited (2.2–23.9%). Additional analyses revealed little predictive power across tumor types except for one case. In clinically relevant genes, we identified 10,281 somatic alterations across 12 cancer types in 2,928 of 3,277 patients (89.4%), many of which would not be revealed in single-tumor analyses. Our study provides a starting point and resources, including an open-access model evaluation platform, for building reliable prognostic and therapeutic strategies that incorporate molecular data.
The AMP-activated protein kinase (AMPK) functions to monitor and maintain energy homeostasis at the cellular and organismal level. AMPK was perceived historically primarily as a component of the LKB1/STK11 tumor suppressor (LKB1 mutations cause the Peutz Jegher’s cancer predisposition syndrome, PJS) cascade upstream of the TSC1/2/mTOR pathway and thus likely to be a tumor suppressor. However, AMPK has recently been demonstrated to promote cancer cell survival in the face of extrinsic and intrinsic stressors including bioenergetic, growth factor and oncogene stress(1-3), compatible with studies showing that AMPK is required for oncogenic transformation(4). Thus whether AMPK acts as a bona fide tumor suppressor or a contextual oncogene and, of particular importance, whether AMPK should be targeted for activation or inhibition during cancer therapy is controversial and requires clarification. We aim to initiate discussions of these critical questions by reviewing the role of AMPK with an emphasis on cancer cell adaptation to microenvironment stress and therapeutic intervention. Overall AMPK function is the topic of several comprehensive reviews(5-7).
Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumors. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyze 3,467 patient samples from 11 TCGA “Pan-Cancer” diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data is integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumor lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumor lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome.
Proteomics; TCGA; Pan-Cancer; protein expression; protein networks
Autophagy is a process in which cellular contents are captured in specialized, membrane-bounded vesicles and delivered to lysosomes for final degradation. Most studies support an inherent connection between autophagy and survival, but increasing evidence also suggests an association between autophagy and cell death. The therapeutic potential of targeting the autophagy pathway in cancer seems clear, but specific strategies for achieving successful eradication of cancer cells are less obvious. Recent developments in the fields of autophagy and programmed cell death, nevertheless, have shed light on therapeutic strategies with significant potential. In this review, we provide an overview of the autophagy process, pathways that modulate autophagy, and promising autophagy-based therapeutic strategies for cancer.
SCLC is an aggressive malignancy affecting nearly 30,000 people annually in the United States. We have previously identified elevated PARP1 levels in SCLC and demonstrated in vitro sensitivity to the PARP inhibitors AZD 2281 and AG014699. Here, we evaluate activity of a novel, potent PARP inhibitor, BMN 673, and identify markers of response as a basis for developing predictive markers for clinical application.
Inhibition of SCLC proliferation by BMN 673 was assayed in vitro and effects on tumor growth were measured in SCLC xenograft models. Protein expression and pathway activation was assessed by reverse phase protein array and western blot analysis. PARP inhibition was confirmed using a PAR ELISA.
We demonstrate striking, single agent activity of BMN 673 in SCLC cell lines and xenografts, with single agent BMN 673 exhibiting in vivo activity similar to cisplatin. Sensitivity to BMN 673 was associated with elevated baseline expression levels of several DNA repair proteins, whereas greater drug resistance was observed in SCLC models with baseline activation of the PI3K/mTOR pathway. Furthermore, we developed and confirmed these data with a novel “DNA repair score” consisting of a group of 17 DNA repair proteins.
Elevated expression of multiple DNA repair proteins, as well as a corresponding “DNA repair protein score,” predict response to BMN 673 in in vitro SCLC models. These observations complement recent work in which PI3K inhibition sensitizes breast cancer models to PARP inhibition, suggesting cooperation between DNA repair and PI3K pathways.
PARP1; small cell lung cancer; DNA repair
We conducted a phase II feasibility study of a 6 month behavioral weight loss intervention in postmenopausal overweight and obese women at increased risk for breast cancer and the effects of weight loss on anthropomorphic, blood, and benign breast tissue biomarkers. 67 women were screened by random peri-areolar fine needle aspiration (RPFNA), 27 were registered and 24 participated in the interventional phase. The 24 biomarker evaluable women had a median baseline BMI of 34.2 kg/m2 and lost a median of 11% of their initial weight. Significant tissue biomarker modulation after the 6 month intervention was noted for Ki-67 (if restricted to the 15 women with any Ki-67 at baseline, p=0.041), adiponectin to leptin ratio (p=0.003); and cyclin B1 (p=0.001), phosphorylated retinoblastoma (p=0.005), and ribosomal S6 (p=0.004) proteins. Favorable modulation for serum markers was observed for sex hormone binding globulin (p<0.001), bioavailable estradiol (p<0.001), bioavailable testosterone (p=0.033), insulin (p=0.018), adiponectin (p=0.001), leptin (p<0.001), the adiponectin to leptin ratio (p<0.001), C-reactive protein (p=0.002) and hepatocyte growth factor (p=0.011). When subdivided by < or > 10% weight loss, change in percent total body and android (visceral) fat, physical activity and the majority of the serum and tissue biomarkers were significantly modulated only for women with >10% weight loss from baseline. Some factors such as serum PAI-1 and breast tissue pS2 (estrogen inducible gene) mRNA were not significantly modulated overall but were when considering only those with >10% weight loss. In conclusion, a median weight loss of 11% over 6 months resulted in favorable modulation of a number of anthropomorphic, breast tissue and serum risk and mechanistic markers. Weight loss of 10% or more should likely be the goal for breast cancer risk reduction studies in obese women.
Breast Cancer Risk Biomarkers; Weight Loss
Epithelial ovarian cancer (EOC) is the second most common gynecologic malignancy and the leading cause of death from gynecologic cancer in the United States. EOC is an exquisitely chemo-sensitive disease with response rates of over 75% in the upfront setting. Despite this, due to high rates of recurrence and development of chemo-resistance, the overall survival of EOC remains about 25%. Thus, there is a great need for new therapeutic approaches to render more durable responses. Based on preclinical and early phase clinical studies, key targeted pathways include targets that drive angiogenesis and chemo-resistance. Receptor tyrosine kinases and non-receptor tyrosine kinases play important roles in these processes and several small molecule tyrosine kinase inhibitors (TKIs) are in clinical development.
This review summarizes clinical rationale, mechanisms of action, and clinical data for the TKIs under evaluation in the phase III setting for EOC.
Despite reasonable preclinical activity, small molecule TKIs are unlikely to improve patient survival as single agent therapies in an unselected EOC population. Incorporation of tissue evaluation during ongoing clinical trials is required to identify molecularly defined groups that respond to single agents and direct rational combination strategies based on mechanisms of resistance to improve outcomes in EOC.
Angiogenesis; ovarian cancer; phase III; signaling; targeted therapy; tyrosine kinase inhibitor
Ovarian cancer has the lowest survival rate of all gynaecologic cancers and is characterised by a lack of early symptoms and frequent late stage diagnosis. There is a paucity of robust molecular markers that are independent of and complementary to clinical parameters such as disease stage and tumour grade.
We have developed a user-friendly, web-based system to evaluate the association of genes/miRNAs with outcome in ovarian cancer. The OvMark algorithm combines data from multiple microarray platforms (including probesets targeting miRNAs) and correlates them with clinical parameters (e.g. tumour grade, stage) and outcomes (disease free survival (DFS), overall survival). In total, OvMark combines 14 datasets from 7 different array platforms measuring the expression of ~17,000 genes and 341 miRNAs across 2,129 ovarian cancer samples.
To demonstrate the utility of the system we confirmed the prognostic ability of 14 genes and 2 miRNAs known to play a role in ovarian cancer. Of these genes, CXCL12 was the most significant predictor of DFS (HR = 1.42, p-value = 2.42x10−6). Surprisingly, those genes found to have the greatest correlation with outcome have not been heavily studied in ovarian cancer, or in some cases in any cancer. For instance, the three genes with the greatest association with survival are SNAI3, VWA3A and DNAH12.
OvMark is a powerful tool for examining putative gene/miRNA prognostic biomarkers in ovarian cancer (available at http://glados.ucd.ie/OvMark/index.html). The impact of this tool will be in the preliminary assessment of putative biomarkers in ovarian cancer, particularly for research groups with limited bioinformatics facilities.
Electronic supplementary material
The online version of this article (doi:10.1186/1476-4598-13-241) contains supplementary material, which is available to authorized users.
Loading control (LC) and variance stabilization of reverse-phase protein array (RPPA) data have been challenging mainly due to the small number of proteins in an experiment and the lack of reliable inherent control markers. In this study, we compare eight different normalization methods for LC and variance stabilization. The invariant marker set concept was first applied to the normalization of high-throughput gene expression data. A set of “invariant” markers are selected to create a virtual reference sample. Then all the samples are normalized to the virtual reference. We propose a variant of this method in the context of RPPA data normalization and compare it with seven other normalization methods previously reported in the literature. The invariant marker set method performs well with respect to LC, variance stabilization and association with the immunohistochemistry/florescence in situ hybridization data for three key markers in breast tumor samples, while the other methods have inferior performance. The proposed method is a promising approach for improving the quality of RPPA data.
reverse-phase protein array; RPPA; normalization; proteomics
We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.
Despite numerous therapies that effectively inhibit estrogen signaling in breast cancer, a significant proportion of patients with estrogen receptor (ER)-positive malignancy will succumb to their disease. Herein we demonstrate that long-term estrogen deprivation (LTED) therapy among ER-positive breast cancer cells results in the adaptive increase in ER expression and subsequent activation of multiple tyrosine kinases. Combination therapy with the ER down-regulator fulvestrant and dasatinib, a broad kinase inhibitor, exhibits synergistic activity against LTED cells, by reduction of cell proliferation, cell survival, cell invasion and mammary acinar formation. Screening kinase phosphorylation using protein arrays and functional proteomic analysis demonstrates that the combination of fulvestrant and dasatinib inhibits multiple tyrosine kinases and cancer-related pathways that are constitutively activated in LTED cells. Because LTED cells display increased insulin receptor (InsR)/insulin-like growth factor 1 receptor (IGF-1R) signaling, we added an ant-IGF-1 antibody to the combination with fulvestrant and dasatinib in an effort to further increase the inhibition. However, adding MK0646 only modestly increased the inhibition of cell growth in monolayer culture, but neither suppressed acinar formation nor inhibited cell migration in vitro and invasion in vivo. Therefore, combinations of fulvestrant and dasatinib, but not MK0646, may benefit patients with tyrosine-kinase-activated, endocrine therapy-resistant breast cancer.
breast cancer; targeting therapy; dasatinib; fulvestrant; MK0646