8 research outputs found

    Global expression analysis of cancer/testis genes in uterine cancers reveals a high incidence of BORIS expression

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    Abstract Purpose: Cancer/testis (CT) genes predominantly expressed in the testis (germ cells) and generally not in other normal tissues are aberrantly expressed in human cancers. This highly restricted expression provides a unique opportunity to use these CTgenes for diagnostics, immunotherapeutic, or other targeted therapies. The purpose of this study was to identify those CT genes with the greatest incidence of expression in uterine cancers. Experimental Design: We queried the expression of known and putative CT gene transcripts (representing 79 gene loci) using whole genome gene expression arrays. Specifically, the global gene expressions of uterine cancers (n = 122) and normal uteri (n = 10) were determined using expression data from the Affymetrix HG-U133A and HG-U133B chips. Additionally, we also examined the brother of the regulator of imprinted sites (BORIS) transcript by reverse transcription-PCR and quantitative PCR because its transcript was not represented on the array. Results: Global microarray analysis detected many CT genes expressed in various uterine cancers; however, no individual CT gene was expressed in more than 25% of all cancers. The expression of the two most commonly expressed CT genes on the arrays, MAGEA9 (24 of 122 cancers and 0 of10 normal tissues) and Down syndrome critical region 8 (DSCR8)/MMA1 (16 if 122 cancers and 0 of 10 normal tissues), was confirmed by reverse transcription-PCR methods, validating the array screening approach. In contrast to the relatively low incidence of expression of the other CTgenes, BORIS expression was detected in 73 of 95 (77%) endometrial cancers and 24 of 31 (77%) uterine mixed mesodermal tumors. Conclusions: These data provide the first extensive survey of multiple CT genes in uterine cancers. Importantly, we detected a high frequency of BORIS expression in uterine cancers, suggesting its potential as an immunologic or diagnostic target for these cancers. Given the high incidence of BORIS expression and its possible regulatory role, an examination of BORIS function in the etiology of these cancers is warranted

    NUAK1 (ARK5) is Associated with Poor Prognosis in Ovarian Cancer.

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    Background and Objective: Nua kinase 1 (NUAK1) was identified in multigene signatures of survival and suboptimal debulking in high grade serous ovarian cancer (HGSOC). This study investigates the individual clinical and biologic contributions of NUAK1 in HGSOC patients and cell lines.Methods: Public transcript expression, clinical, and outcome data were used to interrogate the relationship between NUAK1 and clinicopathologic factors and patient outcomes including progression-free survival (PFS) and molecular subtypes using logistic and Cox modeling. Analysis of NUAK1 transcript expression was performed in primary tumors from 34 HGSOC patients with < or ≥ 2 years PFS. The impact of silencing NUAK1 by RNA interference on the migratory potential and chemosensitivity of SOC cells was assessed in vitro.Results: Elevated NUAK1 transcript expression was associated with worse PFS (hazard ratio=1.134), advanced stage (odds ratio, OR=1.7), any residual disease (OR=1.58), and mesenchymal disease subtype (OR=7.79 ± 5.89). Elevated NUAK1 transcript expression was observed in HGSOC patients with < vs. ≥ 2 years PFS (p<0.045). RNA interference (RNAi)-mediated silencing of NUAK1 expression attenuated migration of OV90 and E3 HGSOC cells in vitro, but did not modulate sensitivity to cisplatin or paclitaxel.Conclusions. Elevated NUAK1 was associated with poor survival as well as advanced stage, residual disease after cytoreductive surgery and mesenchymal molecular subtype. NUAK1 impacted migration, but not chemosensitivity in vitro. Additional studies are needed to further develop the concept of NUAK1 as a clinically deployable biomarker and therapeutic target in HGSOC

    Gene Expression Analysis of Early Stage Endometrial Cancers Reveals Unique Transcripts Associated with Grade and Histology but Not Depth of Invasion

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    Endometrial cancer is the most common gynecologic malignancy in the United States but it remains poorly understood at the molecular level. This investigation was conducted to specifically assess whether gene expression changes underlie the clinical and pathologic factors traditionally used for determining treatment regimens in women with stage I endometrial cancer. These include the effect of tumor grade, depth of myometrial invasion and histotype. We utilized oligonucleotide microarrays to assess the transcript expression profile in epithelial glandular cells laser microdissected from 79 endometrioid and 12 serous stage I endometrial cancers with a heterogeneous distribution of grade and depth of myometrial invasion, along with 12 normal post-menopausal endometrial samples. Unsupervised multidimensional scaling analyses revealed that serous and endometrioid stage I cancers have similar transcript expression patterns when compared to normal controls where 900 transcripts were identified to be differentially expressed by at least 4-fold (univariate t-test, p &lt;0.001) between the cancers and normal endometrium. This analysis also identified transcript expression differences between serous and endometrioid cancers and tumor grade, but no apparent differences were identified as a function of depth of myometrial invasion. Four genes were validated by quantitative PCR on an independent set of cancer and normal endometrium samples. These findings indicate that unique gene expression profiles are associated with histologic type and grade, but not myometrial invasion among early stage endometrial cancers. These data provide a comprehensive perspective on the molecular alterations associated with stage I endometrial cancer, particularly those subtypes that have the worst prognosis

    Improving Risk Assessment for Metastatic Disease in Endometrioid Endometrial Cancer Patients Using Molecular and Clinical Features: An NRG Oncology/Gynecologic Oncology Group Study

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    Objectives: A risk assessment model for metastasis in endometrioid endometrial cancer (EEC) was developed using molecular and clinical features, and prognostic association was examined. Methods: Patients had stage I, IIIC, or IV EEC with tumor-derived RNA-sequencing or microarray-based data. Metastasis-associated transcripts and platform-centric diagnostic algorithms were selected and evaluated using regression modeling and receiver operating characteristic curves. Results: Seven metastasis-associated transcripts were selected from analysis in the training cohorts using 10-fold cross validation and incorporated into an MS7 classifier using platform-specific coefficients. The predictive accuracy of the MS7 classifier in Training-1 was superior to that of other clinical and molecular features, with an area under the curve (95% confidence interval) of 0.89 (0.80–0.98) for MS7 compared with 0.69 (0.59–0.80) and 0.71 (0.58–0.83) for the top evaluated clinical and molecular features, respectively. The performance of MS7 was independently validated in 245 patients using RNA sequencing and in 81 patients using microarray-based data. MS7 + MI (myometrial invasion) was preferrable to individual features and exhibited 100% sensitivity and negative predictive value. The MS7 classifier was associated with lower progression-free and overall survival (p ≤ 0.003). Conclusion: A risk assessment classifier for metastasis and prognosis in EEC patients with primary tumor derived MS7 + MI is available for further development and optimization as a companion clinical support tool

    Elevated AKAP12 in Paclitaxel-Resistant Serous Ovarian Cancer Cells Is Prognostic and Predictive of Poor Survival in Patients

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    A majority of high-grade (HG) serous ovarian cancer (SOC) patients develop resistant disease despite high initial response rates to platinum/paclitaxel-based chemotherapy. We identified shed/secreted proteins in preclinical models of paclitaxel-resistant human HGSOC models and correlated these candidate proteins with patient outcomes using public data from HGSOC patients. Proteomic analyses of a HGSOC cell line secretome was compared to those from a syngeneic paclitaxel-resistant variant and from a line established from an intrinsically chemorefractory HGSOC patient. Associations between the identified candidate proteins and patient outcome were assessed in a discovery cohort of 545 patients and two validation cohorts totaling 795 independent SOC patients. Among the 81 differentially abundant proteins identified (<i>q</i> < 0.05) from paclitaxel-sensitive vs -resistant HGSOC cell secretomes, AKAP12 was verified to be elevated in all models of paclitaxel-resistant HGSOC. Furthermore, elevated AKAP12 transcript expression was associated with worse progression-free and overall survival. Associations with outcome were observed in three independent cohorts and remained significant after adjusted multivariate modeling. We further provide evidence to support that differential gene methylation status is associated with elevated expression of AKAP12 in taxol-resistant ovarian cancer cells and ovarian cancer patient subsets. Elevated expression and shedding/secretion of AKAP12 is characteristic of paclitaxel-resistant HGSOC cells, and elevated AKAP12 transcript expression is a poor prognostic and predictive marker for progression-free and overall survival in SOC patients
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