M. Taghi Mostafavi

Correlation Analysis of HOX, ErbB and IGFBP Family Gene Expression in Ovarian Cancer

Utilizing microarray gene expression data in cancer research possesses the ability to identify deregulated cellular pathways involved in malignant development. This study investigated the relationships of three gene families, HOX, ErbB and IGFBP, with regard to the development of ovarian cancer. These families were of interest because of similar chromosomal locations and their deregulated expression in ovarian cancer. Higher level statistics were used to differentially analyze microarray data in 65 ovarian samples to assess correlation and relationships among the gene families of interest. Fifteen genes in the three families were found to be significantly deregulated. Thirty-eight significant correlations were found within and between the genes of interest. Our data indicates that the significantly modeled relationships between HOX, ErbB and IGFBP gene pairs could provide insight into the underlying biological mechanisms in ovarian cancer.

Downregulation of HOXC6 in Serous Ovarian Cancer

Homeobox (HOX) genes encode transcription factors critical to morphogenesis and cell differentiation. Although dysregulation of several HOX genes in ovarian cancer has been reported, little is known about HOXC6 expression in epithelial ovarian cancer. In this report, analysis of laser capture microdissected samples determined HOXC6 expression patterns in normal versus malignant serous ovarian carcinoma tissues. HOXC6 protein was quantified by ELISA in parallel serum samples and further validated in a larger cohort of serum samples collected from women with and without serous ovarian carcinoma. These data demonstrate significant downregulation of HOXC6 in serous ovarian cancer.

Interactive Segmentation and Analysis of Fetal Ultrasound Images

The ability of ultrasound scanners to image anatomical structures in real time have led to their use in two important applications of medicine, (1) for monitoring the unborn baby (fetal ultrasound), and, (2) coronary treatment of blockages in blood vessels (intravascular ultrasound). The generated images (in the form of a continuous video) are typically noisy and contain numerous artifacts, making it difficult to isolate and measure features of interest. We explore the use of two algorithms, region growing and a variant of split/merge algorithm for segmenting sequences of fetal ultrasound images. We describe an interactive system that can rapidly process and segment an arbitrary number of features. The system exploits frame to frame coherence for accelerating the segmentation process, while at the same time combining the strengths of these algorithms and some post-processing for accurate and robust detection of features.

Abstract 4188: Association of HOX gene expression with osteopontin in ovarian cancer: Implications for biomarker development

Ovarian cancer is characterized by poor early detection and serves as an excellent model system to develop potential markers for early diagnosis. Osteopontin is a glycophosphoprotein known to demonstrate multiple functions including mediation of cellular adhesion, suppression of macrophage interleukin production, prevention of angiogenesis, apoptosis, and inhibition of anchorage-dependent growth. Studies of Osteopontin in ovarian cancer have described increased expression and a role as a candidate biomarker. Secretion of Osteopontin into the extra cellular matrix is reported to facilitate metastasis and has been reported to be inhibited by the presence of cytoplasmic Homeobox proteins (HOX). The HOX family of genes encodes transcription factors involved in basic developmental processes and has been linked to oncogenesis. Dysregulation of HOX genes may be an early event in malignant transformation making the HOX gene family appealing for biomarker investigation. In this study we characterize HOX gene expression in malignant tumors of the ovary compared to Osteopontin, a known biomarker for ovarian cancer. Methods: Microarray analysis of mRNA from human ovarian tissues was performed on samples of normal, benign, and malignant ovarian tissues. These samples were analyzed using the Affymetrix Human Genome Focus GeneChip (HG-Focus) microarray to distinguish the differential pattern of mRNA expression between the three types of samples. Immunohistochemistry staining of ovarian tissue samples was utilized to analyze confirmatory protein expression of the microarray findings. Results: Microarray analysis demonstrated up-regulation of HOXB2, HOXB7, and Osteopontin genes in malignant ovarian tumor samples compared to normal ovarian tissue controls. Conversely, HOXC6 was down-regulated in malignant tissue samples. Immunohistochemistry was performed for HOXB2, HOXC6 and Osteopontin on OCT embedded tissues samples. Similarly, increased protein expression was shown for HOXB2 and Osteopontin in malignant samples and increased HOXC6 in non-cancerous samples. Conclusion: Our results demonstrate multiple HOX genes to be up-regulated in ovarian cancer. Increased expression of HOXB2 and HOXB7, correlated with increased Osteopontin expression found in malignant ovarian tissue samples. HOXC6 demonstrated an inverse relationship with Osteopontin in non-cancerous ovarian tissue samples. The association of these HOX genes with Osteopontin expression warrants further investigation into the role of HOX genes as candidate biomarkers for ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4188. doi:10.1158/1538-7445.AM2011-4188

A novel multi-mode fiber optic accelerometer: an intelligent sensor

This paper presents an architectural design of a novel intelligent accelerometer sensor, constructed from a multi- mode fiber optic cable, and studied its performances. Experimental proofs are provided to demonstrate that as a multi-mode fiber deforms, variation in the shape and structure of speckle patterns will provide deterministic information for measuring the deformation parameters. We used a deep learning approach to analyze the shape of speckle patterns. A multilayer feed-forward convolutional neural network (CNN) has been used to utilize and classify images of speckle pattern into distinct pre-known classes of acceleration vectors. A pendulum setup is used for collecting repeatable and predictable sample data. The presented intelligent sensor is compared with a Micro Electromechanical Machine System (MEMS) accelerometer performances. Estimation of magnitude and direction of the acceleration vector in one plane of motion is achieved with high accuracy (over 97%), when the CNN was trained for 150 epochs. The results confirm that this novel accelerometer sensor performs as well as a MEMS accelerometer. With proper manufacturing, this novel fiber accelerometer has the potential to overcome the limitations associated with conventional accelerometer sensors, normally due to their physical characteristic, accuracies or performances. The potential sensor resulting from this research is expected to be simple, compact, and economically feasible. Moreover, the sensing approach can easily be generalized to measure other physical phenomenal including vibration and displacement.

Use of Structural Properties of Underlying Graphs in Pathway Enrichment Analysis of Genomic Data

Common methods for the functional inference of genomic data, such as Gene Sent Enrichment Analysis (GSEA) and Over Representation Analysis (ORA), often discard the interactions between the biomolecular entities. Recent studies have explored this issue through a variety of techniques and show that using evidence from the interactions produces a more relevant and insightful inference. In this article, we introduce a method, referred to as Causal Disturbance (Cdist), for enrichment analysis. Cdist utilizes the underlying graph of pathways in combination with experimental data to detect the pathway dysregulations. To test our methodology, we utilized a public microarray data from colorectal cancer. We show that Cdist identifies the dysregulated pathways of colorectal cancer that are not detectable by other conventional methods. Some of the detected pathways by Cdist, such as apoptosis and Ras signaling, are critical for their roles in cancer. We conclude that our method facilitates a more informative inference of the disease data by incorporating the topological features of the pathway graphs. Using these features will help to detect the pathway dysregulations that are not observable through conventional models.

Abstract 875: PAX8 protein detection in serum of patients with serous ovarian cancer

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Introduction: The paired-box (PAX) genes encode a family of transcription factors (TFs) with critical roles in the formation of tissues and organs during embryogenesis. These TFs regulate expression of gene products that control cell proliferation and differentiation. Since these processes are also essential to the development of cancer, it shows that PAX genes may participate in the initiation and proliferation of cancer. PAX8 gene expression has been demonstrated in ovarian and other malignancies of Mullerian origin and identified as a marker specific to gynecologic malignancy. Determination of tissue PAX8 protein expression by IHC is used as a clinical diagnostic tool for gynecologic cancer. However, little is known about PAX8 protein expression in serum. Identification of PAX8 in the serum of patients with ovarian cancer would be important in developing an ovarian cancer-specific biomarker. We have previously reported up-regulation of PAX8 gene in ovarian cancer using Human Focus microarrays to characterize differences in gene expression between normal and malignant tissue types. In this study, microarray (MA) and qRT-PCR were performed on human ovarian tissue from patients with normal ovaries and serous ovarian carcinoma to determine PAX8 gene expression. To determine PAX8 protein expression in serum, ELISA was used to analyze serum samples collected from patients with and without serous ovarian cancer. Methods: MA analysis of mRNA from LCM captured cells from human ovarian tissues was performed on normal and malignant ovarian tissues. These samples were analyzed using the Affymetrix Human EXON 1.0 ST microarray to distinguish the differential pattern of mRNA expression between malignant and normal samples. qRT-PCR was utilized to confirm up-regulation of PAX8 genes as determined by MA analysis. PAX8 protein on 17 normal and malignant serum samples were evaluated by indirect sandwich ELISA. RESULTS: MA analysis demonstrated up-regulation of PAX8 in serous ovarian cancer tissue in comparison with normal tissues (p=3.99E-6). This finding then was confirmed using qRT-PCR. Detection of PAX8 protein in serum was determined by ELISA and notably different between normal and malignant serum samples (p<0.03). CONCLUSIONS: This study comparing PAX8 expression in normal and serous ovarian cancer samples shows up-regulation of PAX8 in serous carcinoma of the ovary, in tissue and serum. In particular ELISA suggests that the expression patterns of PAX8 in ovarian tissues is translated to the protein component of these tissues. This resulting protein can be detectable in serum, with higher levels in malignant samples as compared to serum samples of normal human subjects. These findings warrant further study of PAX8 in additional ovarian cancers subtypes and corresponding serum, to better characterize the role of PAX8 up-regulation in ovarian cancer and validation of ELISA as diagnostic biomarker for detection of ovarian cancer. Citation Format: Zahra Bahrani-Mostafavi, Pourya Naderi Yeganeh, Megan E. Parrott, Christine Richardson, David L. Tait, M. Taghi Mostafavi. PAX8 protein detection in serum of patients with serous ovarian cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 875. doi:10.1158/1538-7445.AM2014-875

Abstract 3007: Down-regulation of HOXC6 in serous ovarian cancer.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Objective: The Homeobox (HOX) family of genes consists of 39 genes encoding transcription factors important to morphogenesis and cell differentiation. Usually inactive in normal differentiated tissues, dysregulation of HOX genes has been reported in several malignancies. HOX genes have been linked to genes important in malignant transformation including vascular endothelial growth factor, Ras, interleukin-8, and fibroblast growth factor. We have previously reported up-regulation of HOXA2, HOXA7 and HOXB7 in ovarian cancer. Little is known about HOXC6 gene expression in ovarian cancer. In this study we evaluated HOXC6 expression in normal and malignant human ovarian tissue to characterize expression of HOXC6 in serous ovarian cancer. Methods: Microarray analysis of mRNA from LCM captured cells from human ovarian tissues was performed on 11 samples of normal, and malignant ovarian tissues. These samples were analyzed using the Affymetrix Human EXON 1.0 ST microarray to distinguish the differential pattern of mRNA expression between malignant and normal samples. Real-time reverse transcription PCR was utilized to confirm down-regulation of HOXC6 genes as determined by microarray analysis. HOXC6 protein in tissue was evaluated by immunohistochemistry. Results: Microarray analysis demonstrated significant down-regulation of the HOXC6 gene in malignant serous ovarian tumor samples compared to normal ovarian epithelial cells of control samples. RT-PCR and immunohistochemistry confirmed HOXC6 down-regulation in malignant samples. A 115-fold difference in malignant and normal primary tissue samples and cell lines was seen in the RT-PCR analysis. By immunohistochemistry nuclear staining of HOXC6 protein was seen in the nuclei of normal ovarian surface epithelial tissues but significantly reduced or absent in malignant ovarian samples. Conclusion: HOXC6 is significantly differentially expressed comparing normal ovarian tissue and serous malignant ovarian tissue based on both tissue mRNA and protein analysis. This finding of HOXC6 down-regulation in ovarian cancer is unique and opposite of the up-regulation of other HOX genes previously reported. Down-regulation of HOXC6 in serous ovarian cancer may be an important finding relative to oncogenic pathways and biomarker development. This suggests dysregulation of HOXC6 genes may be an early event in malignant transformation and additional studies to validate the role of the HOXC6 gene in ovarian cancer are warranted. Citation Format: David L. Tait, Zahra Bahrani-Mostafavi, Carol Vestal, Christine Richardson, M. Taghi Mostafavi. Down-regulation of HOXC6 in serous ovarian cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3007. doi:10.1158/1538-7445.AM2013-3007

Abstract 1999: Aberrant expression of HOX transcript in ovarian carcinoma

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC Ovarian cancer is a complex disease phenotype that is challenging to diagnose, primarily because patients tend to remain non-symptomatic until after metastasis has initiated. For those individuals identified early in the disease progression the survival rate is promising, but for the majority, diagnosed late, the 5-year survival rate is dismal. Our eventual goal is to identify a panel of circulating markers that distinguish early onset of the disease. In particular, we have examined the homeobox (HOX) transcript family of genes, known to be involved in cancer progression. These genes are intrinsic cellular factors regulating positional development during embryogenesis and bone formation, and are documented upstream regulators of 16 signaling pathways. Methods: The tissue-specific gene expression from 35 human ovarian tissue samples, using Affymetrix GeneFocusTM microarrays was examined. The microarray analysis was performed on tissues from 8 normal ovaries, 12 benign and 15 malignant epithelial tumors. Microarray output was processed with a stringent data cleansing pipeline to ensure the investigated genes can be unambiguously interpreted. Results: ANOVA analysis reveals a significant alteration in the HOX expression profiles between ovarian tumorous and non-tumorous tissues. While several members of the homeobox gene family are reported to be differentially expressed, we observed a significant shift from healthy HOXC6 expression to an aberrant HOXB2 expression. Whereas non-tumorous tissue demonstrated elevated levels of HOXC6 mRNA transcript, the malignant tissues demonstrated elevated levels of HOXB2 transcript. A possible consequence of the aberrant HOX expression levels is to increase the production and hence the paracrine signaling of osteopontin (SPP1), which is reported to be negatively regulated by a SMAD-HOX interaction. Osteopontin has been correlated to cancer progression, metastasis, and patient survival. We observed a significant correlation between elevated SPP1 expression and the observed HOX disregulation. Conclusion: We demonstrated a correlation between malignant associated SPP1 upregulation and aberrant HOX transcript regulation. These alterations in transcript and protein levels are significant to the epithelial microenvironment. These results have been validated by qRT-PCR and IHC and confirmed with additional patient specimens. The correlation between these two events needs to be further investigated as to their significance in the progression of the disease and as potential candidate biomarkers for ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1999.