DNA methylation and BLC-2 are potential therapeutic targets in acute myeloid leukemia (AML). We investigated pharmacologic interaction between the DNA methyltransferase inhibitor 5-azacytidine (5-AZA) and the BCL-2 inhibitor ABT-737. Increased BCL-2 expression determined by reverse phase protein analysis was associated with poor survival in AML patients with unfavorable cytogenetics (n=195). We found that 5-AZA, which itself has modest apoptotic activity, acts synergistically with ABT-737 to induce apoptosis. The 5-AZA/ABT-737 combination enhanced mitochondrial outer membrane permeabilization, as evidenced by effective conformational activation of BAX and Δψm loss. Although absence of p53 limited apoptotic activities of 5-AZA and ABT-737 as single agents, the combination synergistically induced apoptosis independent of p53 expression. 5-AZA down-regulated MCL-1, known to mediate resistance to ABT-737, in a p53-independent manner. The 5-AZA/ABT-737 combination synergistically induced apoptosis in AML cells from 7 of 8 patients. 5-AZA significantly reduced MCL-1 levels in 2 of 3 samples examined. Our data provide a molecular rationale for this combination strategy in AML therapy.
AML; 5-azacytidine; ABT-737; BCL-2; MCL-1; p53
Motivation: Identifying genes altered in cancer plays a crucial role in both understanding the mechanism of carcinogenesis and developing novel therapeutics. It is known that there are various mechanisms of regulation that can lead to gene dysfunction, including copy number change, methylation, abnormal expression, mutation and so on. Nowadays, all these types of alterations can be simultaneously interrogated by different types of assays. Although many methods have been proposed to identify altered genes from a single assay, there is no method that can deal with multiple assays accounting for different alteration types systematically.
Results: In this article, we propose a novel method, integration using item response theory (integIRTy), to identify altered genes by using item response theory that allows integrated analysis of multiple high-throughput assays. When applied to a single assay, the proposed method is more robust and reliable than conventional methods such as Student’s t-test or the Wilcoxon rank-sum test. When used to integrate multiple assays, integIRTy can identify novel-altered genes that cannot be found by looking at individual assay separately. We applied integIRTy to three public cancer datasets (ovarian carcinoma, breast cancer, glioblastoma) for cross-assay type integration which all show encouraging results.
Availability and implementation: The R package integIRTy is available at the web site http://bioinformatics.mdanderson.org/main/OOMPA:Overview.
Supplementary data are available at Bioinformatics online.
Acute myeloid leukemia (AML) is believed to arise from leukemic stem-like cells (LSC) making understanding the biological differences between LSC and normal stem cells (HSC) or common myeloid progenitors (CMP) crucial to understanding AML biology. To determine if protein expression patterns were different in LSC compared to other AML and CD34+ populations, we measured the expression of 121 proteins by Reverse Phase Protein Arrays (RPPA) in 5 purified fractions from AML marrow and blood samples: Bulk (CD3/CD19 depleted), CD34-, CD34+(CMP), CD34+CD38+ and CD34+CD38-(LSC). LSC protein expression differed markedly from Bulk (n=31 cases, 93/121 proteins) and CD34+ cells (n= 30 cases, 88/121 proteins) with 54 proteins being significantly different (31 higher, 23 lower) in LSC than in either Bulk or CD34+ cells. Sixty-seven proteins differed significantly between CD34+ and Bulk blasts (n=69 cases). Protein expression patterns in LSC and CD34+ differed markedly from normal CD34+ cells. LSC were distinct from CD34+ and Bulk cells by principal component and by protein signaling network analysis which confirmed individual protein analysis. Potential targetable submodules in LSC included the proteins PU.1(SP1), P27, Mcl1, HIF1α, cMET, P53, Yap, and phospho-Stats 1, 5 and 6. Protein expression and activation in LSC differs markedly from other blast populations suggesting that studies of AML biology should be performed in LSC.
Small cell lung cancer (SCLC) is an aggressive malignancy distinct from non-small cell lung cancer (NSCLC) in its metastatic potential and treatment response. Using an integrative proteomic and transcriptomic analysis, we investigated molecular differences contributing to the distinct clinical behavior of SCLC and NSCLC. SCLC demonstrated lower levels of several receptor tyrosine kinases and decreased activation of PI3K and Ras/MEK pathways, but significantly increased levels of E2F1-regulated factors including EZH2, thymidylate synthase, apoptosis mediators, and DNA repair proteins. Additionally, poly (ADP-ribose) polymerase 1 (PARP1), a DNA repair protein and E2F1 co-activator, was highly expressed at the mRNA and protein levels in SCLC. SCLC growth was inhibited by PARP1 and EZH2 knockdown. Furthermore, SCLC was significantly more sensitive to PARP inhibitors than NSCLC, and PARP inhibition downregulated key components of the DNA repair machinery and enhanced the efficacy of chemotherapy.
On the basis of reversal of taxane resistance with AKT inhibition, we initiated a phase I trial of the AKT inhibitor perifosine with docetaxel in taxane and platinum-resistant or refractory epithelial ovarian cancer.
Patients with pathologically confirmed high-grade epithelial ovarian cancer (taxane resistant, n = 10; taxane refractory, n = 11) were enrolled. Peripheral blood samples and tumor biopsies were obtained and 18F-FDG-PET and DCE-MRI scans were performed for pharmacodynamic and imaging studies.
Patients received a total of 42 treatment cycles. No dose-limiting toxicity was observed. The median progression-free survival and overall survival were 1.9 months and 4.5 months, respectively. One patient with a PTEN mutation achieved a partial remission (PR) for 7.5 months, and another patient with PIK3CA mutation had stable disease (SD) for 4 months. Two other patients without apparent PI3K pathway aberrations achieved SD. Two patients with RAS mutations demonstrated rapid progression. Decreased phosphorylated S6 correlated with 18F-FDG-PET responses.
Patients tolerated perifosine 150 mg PO daily plus docetaxel at 75 mg/m2 every 4 weeks. Further clinical evaluation of effects of perifosine with docetaxel on biological markers and efficacy in patients with ovarian cancer with defined PI3K pathway mutational status is warranted.
Peroxisome proliferator-activated receptor-γ (PPARγ) is a member of the nuclear receptor family of transcription factors with important regulatory roles in cellular growth, differentiation and apoptosis. Using proteomic analysis, we demonstrated expression of PPARγ protein in a series of 260 newly diagnosed primary AML samples. Forced expression of PPARγ enhanced the sensitivity of myeloid leukemic cells to PPARγ agonists CDDO- or 15d15DPGJ2-induced apoptosis, through preferential cleavage of caspase-8. No effects on cell cycle distribution or differentiation were noted, despite prominent induction of p21 in PPARγ-transfected cells. In turn, antagonizing PPARγ function by siRNA or pharmacological PPARγ inhibitor significantly diminished apoptosis induction by CDDO. Overexpression of co-activator protein DRIP205 resulted in enhanced differentiation induction by CDDO in AML cells through PPARγ activation. Studies with DRIP205 deletion constructs demonstrated that the NR boxes of DRIP205 are not required for this co-activation. In a Phase I clinical trial of CDDO (RTA-401) in leukemia, CDDO induced an increase in PPARγ mRNA expression in 6 of 9 patient samples; of those, induction of differentiation was documented in 4, and of p21 in 3 patients, all expressing DRIP205 protein. In summary, these findings suggest that cellular levels of PPARγ regulate induction of apoptosis via caspase-8 activation, while the co-activator DRIP205 is a determinant of induction of differentiation, in response to PPARγ agonists in leukemic cells.
PPARgamma; DRIP205; AML; CDDO; differentiation; apoptosis
With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services.
NoSQL database; copy number variation; drug-target interaction; data integration
Mutations in the v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) play a critical role in cancer cell growth and resistance to therapy. Most mutations occur at codons 12 and 13. In colorectal cancer, the presence of any mutant KRas amino acid substitution is a negative predictor of patient response to targeted therapy. However, in non–small cell lung cancer (NSCLC), the evidence that KRAS mutation is a predictive factor is conflicting.
We used data from a molecularly targeted clinical trial for 215 patients with tissues available out of 268 evaluable patients with refractory NSCLC to examine associations between specific mutant KRas proteins and progression-free survival and tumor gene expression. Transcriptome microarray studies of patient tumor samples and reverse-phase protein array studies of a panel of 67 NSCLC cell lines with known substitutions in KRas and in immortalized human bronchial epithelial cells stably expressing different mutant KRas proteins were used to investigate signaling pathway activation. Molecular modeling was used to study the conformations of wild-type and mutant KRas proteins. Kaplan–Meier curves and Cox regression were used to analyze survival data. All statistical tests were two-sided.
Patients whose tumors had either mutant KRas-Gly12Cys or mutant KRas-Gly12Val had worse progression-free survival compared with patients whose tumors had other mutant KRas proteins or wild-type KRas (P = .046, median survival = 1.84 months) compared with all other mutant KRas (median survival = 3.35 months) or wild-type KRas (median survival = 1.95 months). NSCLC cell lines with mutant KRas-Gly12Asp had activated phosphatidylinositol 3-kinase (PI-3-K) and mitogen-activated protein/extracellular signal-regulated kinase kinase (MEK) signaling, whereas those with mutant KRas-Gly12Cys or mutant KRas-Gly12Val had activated Ral signaling and decreased growth factor–dependent Akt activation. Molecular modeling studies showed that different conformations imposed by mutant KRas may lead to altered association with downstream signaling transducers.
Not all mutant KRas proteins affect patient survival or downstream signaling in a similar way. The heterogeneous behavior of mutant KRas proteins implies that therapeutic interventions may need to take into account the specific mutant KRas expressed by the tumor.
The requirement of frozen tissues for microarray experiments limits the clinical usage of genome-wide expression profiling using microarray technology. The goal of this study is to test the feasibility of developing lung cancer prognosis gene signatures using genome-wide expression profiling of formalin-fixed paraffin-embedded (FFPE) samples, which are widely available and provide a valuable rich source for studying the association of molecular changes in cancer and associated clinical outcomes.
We randomly selected 100 Non-Small-Cell lung cancer (NSCLC) FFPE samples with annotated clinical information from the UT-Lung SPORE Tissue Bank. We micro dissected tumor area from FFPE specimens, and used Affymetrix U133 plus 2.0 arrays to attain gene expression data. After strict quality control and analysis procedures, a supervised principal component analysis was used to develop a robust prognosis signature for NSCLC. Three independent published microarray data sets were used to validate the prognosis model.
This study demonstrated that the robust gene signature derived from genome-wide expression profiling of FFPE samples is strongly associated with lung cancer clinical outcomes, can be used to refine the prognosis for stage I lung cancer patients and the prognostic signature is independent of clinical variables. This signature was validated in several independent studies and was refined to a 59-gene lung cancer prognosis signature.
We conclude that genome-wide profiling of FFPE lung cancer samples can identify a set of genes whose expression level provides prognostic information across different platforms and studies, which will allow its application in clinical settings.
Lung Cancer Prognosis; Gene Expression Signature; Formalin Fixed Paraffin Embedded Samples
High-throughtput technologies enable the testing of tens of thousands of measurements simultaneously. Identification of genes that are differentially expressed or associated with clinical outcomes invokes the multiple testing problem. False Discovery Rate (FDR) control is a statistical method used to correct for multiple comparisons for independent or weakly dependent test statistics. Although FDR control is frequently applied to microarray data analysis, gene expression is usually correlated, which might lead to inaccurate estimates. In this paper, we evaluate the accuracy of FDR estimation.
Using two real data sets, we resampled subgroups of patients and recalculated statistics of interest to illustrate the imprecision of FDR estimation. Next, we generated many simulated data sets with block correlation structures and realistic noise parameters, using the Ultimate Microarray Prediction, Inference, and Reality Engine (UMPIRE) R package. We estimated FDR using a beta-uniform mixture (BUM) model, and examined the variation in FDR estimation.
The three major sources of variation in FDR estimation are the sample size, correlations among genes, and the true proportion of differentially expressed genes (DEGs). The sample size and proportion of DEGs affect both magnitude and precision of FDR estimation, while the correlation structure mainly affects the variation of the estimated parameters.
We have decomposed various factors that affect FDR estimation, and illustrated the direction and extent of the impact. We found that the proportion of DEGs has a significant impact on FDR; this factor might have been overlooked in previous studies and deserves more thought when controlling FDR.
Vascular endothelial growth factor-2 (VEGFR-2 or KDR) is a known endothelial target also expressed in NSCLC tumor cells. We investigated the association between alterations in the KDR gene and clinical outcome in patients with resected NSCLC (n=248). KDR copy number gains (CNGs), measured by quantitative PCR and fluorescence in situ hybridization, were detected in 32% of tumors and associated with significantly higher KDR protein and higher microvessel density than tumors without CNGs. KDR CNGs were also associated with significantly increased risk of death (HR=5.16; P=0.003) in patients receiving adjuvant platinum-based chemotherapy, but no differences were observed in patients not receiving adjuvant therapy. To investigate potential mechanisms for these associations we assessed NSCLC cell lines and found that KDR CNGs were significantly associated with in vitro resistance to platinum chemotherapy as well as increased levels of nuclear HIF-1α in both NSCLC tumor specimens and cell lines. Furthermore, KDR knockdown experiments using small interfering RNA reduced platinum resistance, cell migration, and HIF-1α levels in cells bearing KDR CNGs, providing evidence for direct involvement of KDR. No KDR mutations were detected in exons 7, 11 and 21 by PCR-based sequencing; however, two variant SNP genotypes were associated with favorable overall survival in adenocarcinoma patients. Our findings suggest that tumor cell KDR CNGs may promote a more malignant phenotype including increased chemoresistance, angiogenesis, and HIF-1α levels, and that KDR CNGs may be a useful biomarker for identifying patients at high risk for recurrence after adjuvant therapy, a group that may benefit from VEGFR-2 blockade.
Translation initiation and activity of eukaryotic initiation factor-alpha (eIF2α), the rate-limiting step of translation initiation, is often overactivated in malignant cells. Here, we investigated the regulation and role of eIF2α in acute promyelocytic (APL) and acute myeloid leukemia (AML) cells in response to all-trans retinoic acid (ATRA) and arsenic trioxide (ATO), the front-line therapies in APL. ATRA and ATO induce Ser-51 phosphorylation (inactivation) of eIF2α, through the induction of protein kinase C delta (PKCδ) and PKR, but not other eIF2α kinases, such as GCN2 and PERK in APL (NB4) and AML cells (HL60, U937, and THP-1). Inhibition of eIF2α reduced the expression of cellular proteins that are involved in apoptosis (DAP5/p97), cell cycle (p21Waf1/Cip1), differentiation (TG2) and induced those regulating proliferation (c-myc) and survival (p70S6K). PI3K/Akt/mTOR pathway is involved in regulation of eIF2α through PKCδ/PKR axis. PKCδ and p-eIF2α protein expression levels revealed a significant association between the reduced levels of PKCδ (P = 0.0378) and peIF2 (P = 0.0041) and relapses in AML patients (n = 47). In conclusion, our study provides the first evidence that PKCδ regulates/inhibits eIF2α through induction of PKR in AML cells and reveals a novel signaling mechanism regulating translation initiation.
The Forkhead transcription factors (FOXO) are tumor suppressor genes regulating differentiation, metabolism, and apoptosis that functionally interact with signal transduction pathways shown to be deregulated and prognostic in acute myelogenous leukemia (AML). This study evaluated the level of expression and the prognostic relevance of total and phosphorylated FOXO3A protein in AML.
We used reverse-phase protein array methods to measure the level of total and phosphoprotein expression of FOXO3A, in leukemia-enriched protein samples from 511 newly diagnosed AML patients.
The expression range was similar to normal CD34+ cells and similar in blood and marrow. Levels of total FOXO3A were higher at relapse compared with diagnosis. Levels of pFOXO3A or the ratio of phospho to total (PT) were not associated with karyotpe but were higher in patients with FLT3 mutations. Higher levels of pFOXO3A or PT-FOXO3A were associated with increased proliferation evidenced by strong correlation with higher WBC, percent marrow, and blood blasts and by correlation with higher levels of Cyclins B1, D1 and D3, pGSK3, pMTOR, and pStat5. Patients with High levels of pFOXO3A or PT-FOXO3A had higher rates of primary resistance and shorter remission durations, which combine to cause an inferior survival experience (P = 0.0002). This effect was independent of cytogenetics. PT-FOXO3A was a statistically significant independent predictor in multivariate analysis.
High levels of phosphorylation of FOXO3A is a therapeutically targetable, independent adverse prognostic factor in AML.
The identification of key pathways dysregulated in non-small cell lung cancer (NSCLC) is an important step toward understanding lung pathogenesis and developing new therapeutic approaches.
Toward this goal, reverse-phase protein lysate arrays (RPPA) were used to compare signaling pathways between NSCLC tumors and paired normal lung tissue from 46 patients and assess their association with clinical outcome.
After RPPA quantification of 63 proteins and phosphoproteins, tissue pairs were randomized to a training set (n = 25 pairs) and test set (n = 21 pairs). In the training set, 15 protein markers were differentially expressed between tumors and normal lung (p ≤ 0.01), including markers in the PI3K/AKT and p38 MAPK signaling pathways (e.g., p70S6K, S6, p38, and phospho-p38), as well as caveolin-1 and β-catenin. A four-protein signature (p70S6K, cyclin B1, pSrc(Y527), and caveolin-1) independent of histology classified specimens as tumor versus normal with a predicted accuracy of 83%, sensitivity of 67%, and specificity of 100%. The signature was validated in the test set, correctly classifying all normal tissues and 14 of 21 tumor tissues. RPPA results were confirmed by immunohistochemistry for caveolin-1 and p70S6K. In tumors from patients with resected NSCLC, expression of proteins in the energy-sensing AMPK pathway (pLKB1, AMPK, p-Acetyl-CoA, pTSC2), adhesion, EGFR, and Rb signaling pathways was inversely associated with NSCLC recurrence.
These data provide evidence for dysregulation of several pathways including those involving energy sensing and adhesion that are potentially associated with NSCLC pathogenesis and disease recurrence.
NSCLC; Proteomics; Recurrence; AMPK; Adhesion
Cleft Lip and Palate Transmembrane Protein 1-Like (CLPTM1L), resides in a region of chromosome 5 for which copy number gain has been found to be the most frequent genetic event in the early stages of non-small cell lung cancer (NSCLC). This locus has been found by multiple genome wide association studies to be associated with lung cancer in both smokers and non-smokers. CLPTM1L has been identified as an overexpressed protein in human ovarian tumor cell lines that are resistant to cisplatin, which is the only insight thus far into the function of CLPTM1L. Here we find CLPTM1L expression to be increased in lung adenocarcinomas compared to matched normal lung tissues and in lung tumor cell lines by mechanisms not exclusive to copy number gain. Upon loss of CLPTM1L accumulation in lung tumor cells, cisplatin and camptothecin induced apoptosis were increased in direct proportion to the level of CLPTM1L knockdown. Bcl-xL accumulation was significantly decreased upon loss of CLPTM1L. Expression of exogenous Bcl-xL abolished sensitization to apoptotic killing with CLPTM1L knockdown. These results demonstrate that CLPTM1L, an overexpressed protein in lung tumor cells, protects from genotoxic stress induced apoptosis through regulation of Bcl-xL. Thus, this study implicates anti-apoptotic CLPTM1L function as a potential mechanism of susceptibility to lung tumorigenesis and resistance to chemotherapy.
The regulation of Protein Kinase B (AKT) is a dynamic process that depends on the balance between phosphorylation by upstream kinases for activation and inactivation by dephosphorylation by protein phosphatases. Phosphorylated AKT is commonly found in acute myeloid leukemia (AML) and confers an unfavorable prognosis. Understanding the relative importance of upstream kinases and AKT phosphatase in the activation of AKT is relevant for the therapeutic targeting of this signaling axis in AML. The B55α subunit of Protein Phosphatase 2A (PP2A) has been implicated in AKT dephosphorylation but its role in regulating AKT in AML is unknown. We examined B55α protein expression in blast cells derived from 511 AML patients using Reverse Phase Protein Analysis (RPPA). B55α protein expression was lower in AML cells compared to normal CD34+ cells. B55α protein levels negatively correlated with T308 phosphorylation levels. Low levels of B55α were associated with shorter complete remission duration demonstrating that decreased expression is an adverse prognostic factor in AML. These findings suggest that decreased B55α expression in AML is at least partially responsible for increased AKT signaling in AML and suggests that therapeutic targeting of PP2A could counteract this.
PP2A; AKT; AML; B55 alpha
We developed and validated a two-gene signature that predicts prognosis in previously-untreated chronic lymphocytic leukemia (CLL) patients. Using a 65 sample training set, from a cohort of 131 patients, we identified the best clinical models to predict time-to-treatment (TTT) and overall survival (OS). To identify individual genes or combinations in the training set with expression related to prognosis, we cross-validated univariate and multivariate models to predict TTT. We identified four gene sets (5, 6, 12, or 13 genes) to construct multivariate prognostic models. By optimizing each gene set on the training set, we constructed 11 models to predict the time from diagnosis to treatment. Each model also predicted OS and added value to the best clinical models. To determine which contributed the most value when added to clinical variables, we applied the Akaike Information Criterion. Two genes were consistently retained in the models with clinical variables: SKI (v-SKI avian sarcoma viral oncogene homolog) and SLAMF1 (signaling lymphocytic activation molecule family member 1; CD150). We optimized a two-gene model and validated it on an independent test set of 66 samples. This two-gene model predicted prognosis better on the test set than any of the known predictors, including ZAP70 and serum β2-microglobulin.
The lack of large panels of validated antibodies, tissue handling variability, and intratumoral heterogeneity potentially hamper comprehensive study of the functional proteome in non-microdissected solid tumors. The purpose of this study was to address these concerns and to demonstrate clinical utility for the functional analysis of proteins in non-microdissected breast tumors using reverse phase protein arrays (RPPA).
Herein, 82 antibodies that recognize kinase and steroid signaling proteins and effectors were validated for RPPA. Intraslide and interslide coefficients of variability were <15%. Multiple sites in non-microdissected breast tumors were analyzed using RPPA after intervals of up to 24 h on the benchtop at room temperature following surgical resection.
Twenty-one of 82 total and phosphoproteins demonstrated time-dependent instability at room temperature with most variability occurring at later time points between 6 and 24 h. However, the 82-protein functional proteomic “fingerprint” was robust in most tumors even when maintained at room temperature for 24 h before freezing. In repeat samples from each tumor, intratumoral protein levels were markedly less variable than intertumoral levels. Indeed, an independent analysis of prognostic biomarkers in tissue from multiple tumor sites accurately and reproducibly predicted patient outcomes. Significant correlations were observed between RPPA and immunohistochemistry. However, RPPA demonstrated a superior dynamic range. Classification of 128 breast cancers using RPPA identified six subgroups with markedly different patient outcomes that demonstrated a significant correlation with breast cancer subtypes identified by transcriptional profiling.
Thus, the robustness of RPPA and stability of the functional proteomic “fingerprint” facilitate the study of the functional proteome in non-microdissected breast tumors.
Functional proteome; RPPA; Breast cancer; Kinase signaling; Steroid signaling
The low prevalence of ovarian cancer demands both high sensitivity (>75%) and specificity (99.6%) to achieve a positive predictive value of 10% for successful early detection. Utilizing a two stage strategy where serum marker(s) prompt the performance of transvaginal sonography (TVS) in a limited number (2%) of women could reduce the requisite specificity for serum markers to 98%. We have attempted to improve sensitivity by combining CA125 with proteomic markers.
Sera from 41 patients with early stage (I/II) and 51 with late stage (III/IV) epithelial ovarian cancer, 40 with benign disease and 99 healthy individuals, were analyzed to measure 7 proteins [Apolipoprotein A1 (Apo-A1), truncated transthyretin (TT), transferrin, hepcidin, ß-2-microglobulin (ß2M), Connective Tissue Activating Protein III (CTAPIII), and Inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4)]. Statistical models were fit by logistic regression, followed by optimization of factors retained in the models determined by optimizing the Akaike Information Criterion. A validation set included 136 stage I ovarian cancers, 140 benign pelvic masses and 174 healthy controls.
In a training set analysis, the 3 most effective biomarkers (Apo-A1, TT and CTAPIII) exhibited 54% sensitivity at 98% specificity, CA125 alone produced 68% sensitivity and the combination increased sensitivity to 88%. In a validation set, the marker panel plus CA125 produced a sensitivity of 84% at 98% specificity (P= 0.015, McNemar's test).
Combining a panel of proteomic markers with CA125 could provide a first step in a sequential two-stage strategy with TVS for early detection of ovarian cancer.
To determine whether functional proteomics improves breast cancer classification and prognostication and can predict pathological complete response (pCR) in patients receiving neoadjuvant taxane and anthracycline-taxane-based systemic therapy (NST).
Reverse phase protein array (RPPA) using 146 antibodies to proteins relevant to breast cancer was applied to three independent tumor sets. Supervised clustering to identify subgroups and prognosis in surgical excision specimens from a training set (n = 712) was validated on a test set (n = 168) in two cohorts of patients with primary breast cancer. A score was constructed using ordinal logistic regression to quantify the probability of recurrence in the training set and tested in the test set. The score was then evaluated on 132 FNA biopsies of patients treated with NST to determine ability to predict pCR.
Six breast cancer subgroups were identified by a 10-protein biomarker panel in the 712 tumor training set. They were associated with different recurrence-free survival (RFS) (log-rank p = 8.8 E-10). The structure and ability of the six subgroups to predict RFS was confirmed in the test set (log-rank p = 0.0013). A prognosis score constructed using the 10 proteins in the training set was associated with RFS in both training and test sets (p = 3.2E-13, for test set). There was a significant association between the prognostic score and likelihood of pCR to NST in the FNA set (p = 0.0021).
We developed a 10-protein biomarker panel that classifies breast cancer into prognostic groups that may have potential utility in the management of patients who receive anthracycline-taxane-based NST.
Breast Cancer; Functional Proteomics; Prognosis; Prediction
Patients with prolonged myelosuppression require frequent platelet and occasional granulocyte transfusions. Multi-donor transfusions induce alloimmunization, thereby increasing morbidity and mortality. Therefore, an autologous or HLA-matched allogeneic source of platelets and granulocytes is needed. To determine whether nonhematopoietic cells can be reprogrammed into hematopoietic cells, human mesenchymal stromal cells (MSCs) and skin fibroblasts were incubated with the demethylating agent 5-azacytidine (Aza) and the growth factors (GF) granulocyte-macrophage colony-stimulating factor and stem cell factor. This treatment transformed MSCs to round, non-adherent cells expressing T-, B-, myeloid-, or stem/progenitor-cell markers. The transformed cells engrafted as hematopoietic cells in bone marrow of immunodeficient mice. DNA methylation and mRNA array analysis suggested that Aza and GF treatment demethylated and activated HOXB genes. Indeed, transfection of MSCs or skin fibroblasts with HOXB4, HOXB5, and HOXB2 genes transformed them into hematopoietic cells. Further studies are needed to determine whether transformed MSCs or skin fibroblasts are suitable for therapy.
Zeta-associated protein-70 (ZAP70) expression measured by flow cytometry has been proposed as a surrogate marker of the somatic mutation status of the immunoglobulin heavy chain variable region genes in chronic lymphocytic leukemia. However, attempts to implement this approach in clinical flow cytometry laboratories have been problematic; many commercially available antibodies give unreliable results. Assessment of ZAP70 protein expression by immunohistochemistry in chronic lymphocytic leukemia tissue sections is an easy, alternative approach, although lack of quantitation and subjective interpretation of results are potential pitfalls. In this study, we correlated ZAP70 protein expression, assessed by immunohistochemistry, with ZAP70 messenger RNA transcript expression, assessed by semi-quantitative real-time reverse transcriptase-polymerase chain reaction assay, with the somatic mutation status of the immunoglobulin heavy chain variable region genes in previously untreated patients with chronic lymphocytic leukemia. Expression of ZAP70 protein and messenger RNA transcripts correlated strongly (p=8.238x10−12). Expression of ZAP70 protein and messenger RNA transcripts also correlated strongly with the somatic mutation status of the immunoglobulin heavy chain variable region genes (p=0.000071 and p=0.00076, respectively). Further, ZAP70 positivity by immunohistochemistry was associated with an increased risk of progression to therapy requirement (3 year risk 83% vs. 31% for ZAP70 negative by immunohistochemistry, p=0.03). These results show that ZAP70 expression assessed by immunohistochemistry is a reliable surrogate marker of the somatic mutation status of the immunoglobulin heavy chain variable region genes, and predicts time to progression.
chronic lymphocytic leukemia; ZAP70; immunohistochemistry; QRT-PCR; somatic mutation status; immunoglobulin heavy chain variable region genes
This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.
The reproducibility of mass spectrometry (MS) data collected using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) has been questioned. This investigation was designed to test the reproducibility of SELDI data collected over time by multiple users and instruments. Five laboratories prepared arrays once every week for six weeks. Spectra were collected on separate instruments in the individual laboratories. Additionally, all of the arrays produced each week were rescanned on a single instrument in one laboratory. Lab-to-lab and array-to-array variability in alignment parameters were larger than the variability attributable to running samples during different weeks. The coefficient of variance (CV) in spectrum intensity ranged from 25% at baseline, to 80% in the matrix noise region, to about 50% during the exponential drop from the maximum matrix noise. Before normalization, the median CV of the peak heights was 72% and reduced to about 20% after normalization. Additionally, for the spectra from a common instrument, the CV ranged from 5% at baseline, to 50% in the matrix noise region, to 20% during the drop from the maximum matrix noise. Normalization reduced the variability in peak heights to about 18%. With proper processing methods, SELDI instruments produce spectra containing large numbers of reproducibly located peaks, with consistent heights.
mass spectrometry/wavelet; analysis of variance/reproducibility/SELDI
Despite many attempts to establish pre-treatment prognostic markers to understand the clinical biology of esophageal adenocarcinoma (EAC), validated clinical biomarkers or parameters remain elusive. We generated and analyzed tumor transcriptome to develop a practical biomarker prognostic signature in EAC.
Untreated esophageal endoscopic biopsy specimens were obtained from 64 patients undergoing surgery and chemoradiation. Using DNA microarray technology, genome-wide gene expression profiling was performed on 75 untreated cancer specimens from 64 EAC patients. By applying various statistical and informatical methods to gene expression data, we discovered distinct subgroups of EAC with differences in overall gene expression patterns and identified potential biomarkers significantly associated with prognosis. The candidate marker genes were further explored in formalin-fixed, paraffin-embedded tissues from an independent cohort (52 patients) using quantitative RT-PCR to measure gene expression. We identified two genes whose expression was associated with overall survival in 52 EAC patients and the combined 2-gene expression signature was independently associated with poor outcome (P<0.024) in the multivariate Cox hazard regression analysis.
Our findings suggest that the molecular gene expression signatures are associated with prognosis of EAC patients and can be assessed prior to any therapy. This signature could provide important improvement for the management of EAC patients.
Using Reverse Phase Protein Array (RPPA) we measured protein expression associated with response to primary chemotherapy in patients with advanced-stage high-grade serous ovarian cancer.
Tumor samples were obtained from forty-five patients with advanced high-grade serous cancers from the Gynecology Tumor Bank at the British Columbia Cancer Agency. Treatment consisted of platinum-based chemotherapy following debulking surgery. Protein lysates were prepared from fresh frozen tumor samples and 80 validated proteins from signaling pathways implicated in ovarian carcinogenesis were measured by RPPA. Normalization of Ca-125 by the 3rd cycle of chemotherapy was chosen as the primary outcome measure of chemotherapy response. Logistic regression was used for multivariate analysis to identify protein predictors of Ca-125 normalization, and Cox regression to test for the association between protein expression and PFS. A significance level of p ≤ 0.05 was used.
The mean age at diagnosis was 56.8 years. EGFR, YKL-40 and several TGFβ pathway proteins (c-Jun N-terminal kinase JNK, JNK phosphorylated at residues 183 and 185, PAI-1, Smad3, TAZ) showed significant associations with Ca-125 normalization on univariate testing. On multivariate analysis, EGFR (p < 0.02), JNK (p < 0.01), and Smad3 (p < 0.04) were significantly associated with normalization of Ca-125. Contingency table analysis of pathway-classified proteins revealed that the selection of TGFβ pathway proteins was unlikely due to false discovery (p < 0.007, Bonferroni-adjusted).
TGFβ pathway signaling likely plays an important role as a marker or mediator of chemoresistance in advanced serous ovarian cancer. On this basis, future studies to develop and validate a useful predictor of treatment failure are warranted.
ovarian cancer; functional proteomics; chemotherapy response; reverse phase protein array; Ca-125