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1.
Introduction
The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures.Methods
We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes).Results
The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis.Conclusion
This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies. 相似文献2.
Rebeca Sanz-Pamplona Antoni Berenguer David Cordero Samantha Riccadonna Xavier Solé Marta Crous-Bou Elisabet Guinó Xavier Sanjuan Sebastiano Biondo Antonio Soriano Giuseppe Jurman Gabriel Capella Cesare Furlanello Victor Moreno 《PloS one》2012,7(11)
Introduction
The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets.Methods
A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples.Results
Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system.Conclusions
The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic. 相似文献3.
Purpose
This study aims to explore gene expression signatures and serum biomarkers to predict intrinsic chemoresistance in epithelial ovarian cancer (EOC).Patients and Methods
Gene expression profiling data of 322 high-grade EOC cases between 2009 and 2010 in The Cancer Genome Atlas project (TCGA) were used to develop and validate gene expression signatures that could discriminate different responses to first-line platinum/paclitaxel-based treatments. A gene regulation network was then built to further identify hub genes responsible for differential gene expression between the complete response (CR) group and the progressive disease (PD) group. Further, to find more robust serum biomarkers for clinical application, we integrated our gene signatures and gene signatures reported previously to identify secretory protein-encoding genes by searching the DAVID database. In the end, gene-drug interaction network was constructed by searching Comparative Toxicogenomics Database (CTD) and literature.Results
A 349-gene predictive model and an 18-gene model independent of key clinical features with high accuracy were developed for prediction of chemoresistance in EOC. Among them, ten important hub genes and six critical signaling pathways were identified to have important implications in chemotherapeutic response. Further, ten potential serum biomarkers were identified for predicting chemoresistance in EOC. Finally, we suggested some drugs for individualized treatment.Conclusion
We have developed the predictive models and serum biomarkers for platinum/paclitaxel response and established the new approach to discover potential serum biomarkers from gene expression profiles. The potential drugs that target hub genes are also suggested. 相似文献4.
Haiping Yang Ruihua Mi Qian Wang Xudong Wei Qingsong Yin Lin Chen Xinghu Zhu Yongping Song 《PloS one》2014,9(5)
Objective
To determine the expression of neuron-specific enolase (NSE) in patients with multiple myeloma (MM) and to evaluate its clinical value as a tumor marker and, an indicator of disease progression and treatment efficacy.Methods
Using electrochemiluminescence immunoassay (ECLIA), we measured the serum levels of NSE in 47 healthy subjects (control group), 25 patients with small cell lung cancer (lung cancer group), and 52 patients with MM (MM group). For the MM group, serum NSE levels were measured and other disease indicators and related symptoms were monitored before and after chemotherapy. The relationship between NSE expression and other MM-related factors was analyzed. In addition, immunohistochemical staining was performed on bone marrow biopsy specimens from patients with MM.Results
In the control group, serum NSE levels were within the normal range as previously reported, while the lung cancer group and the untreated MM group exhibited NSE levels that were significantly higher relative to the control group (P<0.05). The difference in NSE expression between the lung cancer group and untreated MM group was statistically significant (P<0.05). NSE levels were significantly decreased in MM patients after chemotherapy and were positively correlated with an MM disease index [beta-2 microglobulin (β2-MG)]. Changes in NSE were not related to the response rate to chemotherapy but rather were correlated with progression-free survival.Conclusions
Patients with MM may have increased serum NSE levels, and changes in NSE may provide insight into treatment efficacy of chemotherapy and disease progression. Perhaps NSE expression is a viable biomarker for MM and can be a useful reference for the design and adjustment of clinical MM treatment programs. 相似文献5.
Simone S. Riedel Anja Mottok Christian Brede Carina A. B?uerlein Ana-Laura Jordán Garrote Miriam Ritz Katharina Mattenheimer Andreas Rosenwald Hermann Einsele Bjarne Bogen Andreas Beilhack 《PloS one》2012,7(12)
Background
Multiple myeloma (MM) is a B-cell malignancy, where malignant plasma cells clonally expand in the bone marrow of older people, causing significant morbidity and mortality. Typical clinical symptoms include increased serum calcium levels, renal insufficiency, anemia, and bone lesions. With standard therapies, MM remains incurable; therefore, the development of new drugs or immune cell-based therapies is desirable. To advance the goal of finding a more effective treatment for MM, we aimed to develop a reliable preclinical MM mouse model applying sensitive and reproducible methods for monitoring of tumor growth and metastasis in response to therapy.Material and Methods
A mouse model was created by intravenously injecting bone marrow-homing mouse myeloma cells (MOPC-315.BM) that expressed luciferase into BALB/c wild type mice. The luciferase in the myeloma cells allowed in vivo tracking before and after melphalan treatment with bioluminescence imaging (BLI). Homing of MOPC-315.BM luciferase+ myeloma cells to specific tissues was examined by flow cytometry. Idiotype-specific myeloma protein serum levels were measured by ELISA. In vivo measurements were validated with histopathology.Results
Strong bone marrow tropism and subsequent dissemination of MOPC-315.BM luciferase+ cells in vivo closely mimicked the human disease. In vivo BLI and later histopathological analysis revealed that 12 days of melphalan treatment slowed tumor progression and reduced MM dissemination compared to untreated controls. MOPC-315.BM luciferase+ cells expressed CXCR4 and high levels of CD44 and α4β1 in vitro which could explain the strong bone marrow tropism. The results showed that MOPC-315.BM cells dynamically regulated homing receptor expression and depended on interactions with surrounding cells.Conclusions
This study described a novel MM mouse model that facilitated convenient, reliable, and sensitive tracking of myeloma cells with whole body BLI in living animals. This model is highly suitable for monitoring the effects of different treatment regimens. 相似文献6.
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Rebecca Lamb Matthew P. Ablett Katherine Spence G?ran Landberg Andrew H. Sims Robert B. Clarke 《PloS one》2013,8(7)
Introduction
Wnt signalling has been implicated in stem cell regulation however its role in breast cancer stem cell regulation remains unclear.Methods
We used a panel of normal and breast cancer cell lines to assess Wnt pathway gene and protein expression, and for the investigation of Wnt signalling within stem cell-enriched populations, mRNA and protein expression was analysed after the selection of anoikis-resistant cells. Finally, cell lines and patient-derived samples were used to investigate Wnt pathway effects on stem cell activity in vitro.Results
Wnt pathway signalling increased in cancer compared to normal breast and in both cell lines and patient samples, expression of Wnt pathway genes correlated with estrogen receptor (ER) expression. Furthermore, specific Wnt pathway genes were predictive for recurrence within subtypes of breast cancer. Canonical Wnt pathway genes were increased in breast cancer stem cell-enriched populations in comparison to normal breast stem cell-enriched populations. Furthermore in cell lines, the ligand Wnt3a increased whilst the inhibitor DKK1 reduced mammosphere formation with the greatest inhibitory effects observed in ER+ve breast cancer cell lines. In patient-derived metastatic breast cancer samples, only ER-ve mammospheres were responsive to the ligand Wnt3a. However, the inhibitor DKK1 efficiently inhibited both ER+ve and ER-ve breast cancer but not normal mammosphere formation, suggesting that the Wnt pathway is aberrantly activated in breast cancer mammospheres.Conclusions
Collectively, these data highlight differential Wnt signalling in breast cancer subtypes and activity in patient-derived metastatic cancer stem-like cells indicating a potential for Wnt-targeted treatment in breast cancers. 相似文献9.
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Adam Szulkin Gustav Nilsonne Filip Mundt Agata M. Wasik Pega Souri Anders Hjerpe Katalin Dobra 《PloS one》2013,8(6)
Background
Malignant mesothelioma cells have an epithelioid or sarcomatoid morphology, both of which may be present in the same tumor. The sarcomatoid phenotype is associated with worse prognosis and heterogeneity of mesothelioma cells may contribute to therapy resistance, which is often seen in mesothelioma. This study aimed to investigate differences in sensitivity between mesothelioma cell lines to anti-cancer drugs. We studied two novel drugs, selenite and bortezomib and compared their effect to four conventional drugs. We also investigated the immunoreactivity of potential predictive markers for drug sensitivity; Pgp, MRP-1, ERCC1, RRM1, TS, xCT and proteasome 20S subunit.Materials and methods
We treated six mesothelioma cell lines with selenite, bortezomib, carboplatin, pemetrexed, doxorubicin or gemcitabine as single agents and in combinations. Viability was measured after 24 and 48 hours. Immunocytochemistry was used to detect predictive markers.Results
As a single agent, selenite was effective on four out of six cell lines, and in combination with bortezomib yielded the greatest response in the studied mesothelioma cell lines. Cells with an epithelioid phenotype were generally more sensitive to the different drugs than the sarcomatoid cells. Extensive S-phase arrest was seen in pemetrexed-sensitive cell lines. MRP-1 predicted sensitivity of cell lines to treatment with carboplatin and xCT predicted pemetrexed effect.Conclusions
The observed heterogeneity in sensitivity of mesothelioma cell lines with different morphology highlights the need for more individualized therapy, requiring development of methods to predict drug sensitivity of individual tumors. Selenite and bortezomib showed a superior effect compared to conventional drugs, motivating clinical testing of these agents as future treatment regime components for patients with malignant mesothelioma. 相似文献11.
Purpose
Cancer drug resistance is a major obstacle for the success of chemotherapy. Since most clinical anticancer drugs could induce drug resistance, it is desired to develop candidate drugs that are highly efficacious but incompetent to induce drug resistance. Numerous previous studies have proven that shikonin and its analogs not only are highly tumoricidal but also can bypass drug-transporter and apoptotic defect mediated drug resistance. The purpose of this study is to investigate if or not shikonin is a weak inducer of cancer drug resistance.Experimental Design
Different cell lines (K562, MCF-7, and a MDR cell line K562/Adr), after repeatedly treated with shikonin for 18 months, were assayed for drug resistance and gene expression profiling.Results
After 18-month treatment, cells only developed a mere 2-fold resistance to shikonin and a marginal resistance to cisplatin and paclitaxel, without cross resistance to shikonin analogs and other anticancer agents. Gene expression profiles demonstrated that cancer cells did strongly respond to shikonin treatment but failed to effectively mobilize drug resistant machineries. Shikonin-induced weak resistance was associated with the up-regulation of βII-tubulin, which physically interacted with shikonin.Conclusion
Taken together, apart from potent anticancer activity, shikonin and its analogs are weak inducers of cancer drug resistance and can circumvent cancer drug resistance. These merits make shikonin and its analogs potential candidates for cancer therapy with advantages of avoiding induction of drug resistance and bypassing existing drug resistance. 相似文献12.
Background
Developing chemotherapy resistant cell lines can help to identify markers of resistance. Instead of using a panel of highly heterogeneous cell lines, we assumed that truly robust and convergent pattern of resistance can be identified in multiple parallel engineered derivatives of only a few parental cell lines.Methods
Parallel cell populations were initiated for two breast cancer cell lines (MDA-MB-231 and MCF-7) and these were treated independently for 18 months with doxorubicin or paclitaxel. IC50 values against 4 chemotherapy agents were determined to measure cross-resistance. Chromosomal instability and karyotypic changes were determined by cytogenetics. TaqMan RT-PCR measurements were performed for resistance-candidate genes. Pgp activity was measured by FACS.Results
All together 16 doxorubicin- and 13 paclitaxel-treated cell lines were developed showing 2–46 fold and 3–28 fold increase in resistance, respectively. The RT-PCR and FACS analyses confirmed changes in tubulin isofom composition, TOP2A and MVP expression and activity of transport pumps (ABCB1, ABCG2). Cytogenetics showed less chromosomes but more structural aberrations in the resistant cells.Conclusion
We surpassed previous studies by parallel developing a massive number of cell lines to investigate chemoresistance. While the heterogeneity caused evolution of multiple resistant clones with different resistance characteristics, the activation of only a few mechanisms were sufficient in one cell line to achieve resistance. 相似文献13.
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Karn T Pusztai L Holtrich U Iwamoto T Shiang CY Schmidt M Müller V Solbach C Gaetje R Hanker L Ahr A Liedtke C Ruckhäberle E Kaufmann M Rody A 《PloS one》2011,6(12):e28403
Background
Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes.Methodology/Principal Findings
We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases).Conclusions/Significance
Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n = 264 probesets) and a smaller (n = 26 probesets) prognostic gene sets were identified and used as prognostic predictors. Most of these genes were positively associated with poor prognosis and correlated to metagenes for inflammation and angiogenesis. No correlation to other previously published prognostic signatures (recurrence score, genomic grade index, 70-gene signature, wound response signature, 7-gene immune response module, stroma derived prognostic predictor, and a medullary like signature) was observed. In multivariate analyses in the validation cohort the two signatures showed hazard ratios of 4.03 (95% confidence interval [CI] 1.71–9.48; P = 0.001) and 4.08 (95% CI 1.79–9.28; P = 0.001), respectively. The 10-year event-free survival was 70% for the good risk and 20% for the high risk group. The 26-gene signatures had modest predictive value (AUC = 0.588) to predict response to neoadjuvant chemotherapy, however, the combination of a B-cell metagene with the prognostic signatures increased its response predictive value. We identified a 264-gene prognostic signature for TNBC which is unrelated to previously known prognostic signatures. 相似文献17.
Chang-Jiun Wu Tianxi Cai Klarisa Rikova David Merberg Simon Kasif Martin Steffen 《PloS one》2009,4(11)
Background
Aberrant activation of signaling pathways drives many of the fundamental biological processes that accompany tumor initiation and progression. Inappropriate phosphorylation of intermediates in these signaling pathways are a frequently observed molecular lesion that accompanies the undesirable activation or repression of pro- and anti-oncogenic pathways. Therefore, methods which directly query signaling pathway activation via phosphorylation assays in individual cancer biopsies are expected to provide important insights into the molecular “logic” that distinguishes cancer and normal tissue on one hand, and enables personalized intervention strategies on the other.Results
We first document the largest available set of tyrosine phosphorylation sites that are, individually, differentially phosphorylated in lung cancer, thus providing an immediate set of drug targets. Next, we develop a novel computational methodology to identify pathways whose phosphorylation activity is strongly correlated with the lung cancer phenotype. Finally, we demonstrate the feasibility of classifying lung cancers based on multi-variate phosphorylation signatures.Conclusions
Highly predictive and biologically transparent phosphorylation signatures of lung cancer provide evidence for the existence of a robust set of phosphorylation mechanisms (captured by the signatures) present in the majority of lung cancers, and that reliably distinguish each lung cancer from normal. This approach should improve our understanding of cancer and help guide its treatment, since the phosphorylation signatures highlight proteins and pathways whose phosphorylation should be inhibited in order to prevent unregulated proliferation. 相似文献18.
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Xue Lin Jan Stenvang Mads Heilskov Rasmussen Shida Zhu Niels Frank Jensen Line S Tarpgaard Guangxia Yang Kirstine Belling Claus Lindbjerg Andersen Jian Li Lars Bolund Nils Brünner 《BMC genomics》2015,16(1)