High definition cytogenetics and oligonucleotide aCGH analyses of cisplatin-resistant ovarian cancer cells.

Array comparative genomic hybridization (aCGH) is a key platform to assess cancer genomic profiles. Many structural genomic aberrations cannot be detected by aCGH alone. We have applied molecular cytogenetic analyses including spectral karyotyping, multicolor banding, and fluorescence in situ hybridization with aCGH to comprehensively investigate the genomic aberrations associated with cisplatin resistance in A2780 ovarian cancer cells. A2780 is a well-established model of chemotherapeutic resistance with distinct karyotypic abnormalities in the parental and cisplatin-resistant cells. Cytogenetic analysis revealed that two unbalanced translocations, der(8)t(1;8) and der(X)t(X;1), and loss of chromosome 13 were present only in the resistant line. Our aCGH analyses detected imbalances affecting an additional 10.59% of the genome in the cisplatin-resistant cells compared with the parental. DNA copy number changes included deletions at 1p10-p22.1, 8p23.3, and Xq13.1-pter, and a duplication of 8q11.22-q23. Cryptic genomic aberrations associated with concurrent localized changes of specific gene expression included a homozygous deletion of 0.38 Mb at 1p21.3 adjacent to SNX7, and an insertional transposition of 0.85 Mb from 13q12.12 into chromosome 22. This latter rearrangement led to an overexpression of four contiguous genes that flanked one of the breakpoint regions in chromosome 13. Furthermore, 17 genes showed differential expression correlating with genomic gain or loss between the resistant and parent lines, validated by a second expression array platform. These results highlight the integration of comprehensive profiling to determine relationships of genomic aberrations and genes associated with an in vitro drug resistance model in ovarian cancer. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

Effects of THBS3, SPARC and SPP1 expression on biological behavior and survival in patients with osteosarcoma.

BACKGROUND: Osteosarcoma is a very aggressive tumor with a propensity to metastasize and invade surrounding tissue. Identification of the molecular determinants of invasion and metastatic potential may guide the development of a rational strategy for devising specific therapies that target the pathways leading to osteosarcoma. METHODS: In this study, we used pathway-focused low density expression cDNA arrays to screen for candidate genes related to tumor progression. Expression patterns of the selected genes were validated by real time PCR on osteosarcoma patient tumor samples and correlated with clinical and pathological data. RESULTS: THBS3, SPARC and SPP1 were identified as genes differentially expressed in osteosarcoma. In particular, THBS3 was expressed at significantly high levels (p = 0.0001) in biopsies from patients with metastasis at diagnosis, which is a predictor of worse overall survival, event-free survival and relapse free survival at diagnosis. After chemotherapy, patients with tumors over-expressing THBS3 have worse relapse free survival. High SPARC expression was found in 51/55 (96.3%) osteosarcoma samples derived from 43 patients, and correlated with the worst event-free survival (p = 0.03) and relapse free survival (p = 0.07). Overexpression of SPP1 was found in 47 of 53 (89%) osteosarcomas correlating with better overall survival, event-free survival and relapse free survival at diagnosis. CONCLUSION: In this study three genes were identified with pattern of differential gene expression associated with a phenotypic role in metastasis and invasion. Interestingly all encode for proteins involved in extracellular remodeling suggesting potential roles in osteosarcoma progression. This is the first report on the THBS3 gene working as a stimulator of tumor progression. Higher levels of THBS3 maintain the capacity of angiogenesis. High levels of SPARC are not required for tumor progression but are necessary for tumor growth and maintenance. SPP1 is not necessary for tumor progression in osteosarcoma and may be associated with inflammatory response and bone remodeling, functioning as a good biomarker.

High-resolution mapping of genomic imbalance and identification of gene expression profiles associated with differential chemotherapy response in serous epithelial ovarian cancer.

Array comparative genomic hybridization (aCGH) and microarray expression profiling were used to subclassify DNA and RNA alterations associated with differential response to chemotherapy in ovarian cancer. Two to 4 Mb interval arrays were used to map genomic imbalances in 26 sporadic serous ovarian tumors. Cytobands 1p36, 1q42-44, 6p22.1-p21.2, 7q32.1-q34 9q33.3-q34.3, 11p15.2, 13q12.2-q13.1, 13q21.31, 17q11.2, 17q24.2-q25.3, 18q12.2, and 21q21.2-q21.3 were found to be statistically associated with chemotherapy response, and novel regions of loss at 15q11.2-q15.1 and 17q21.32-q21.33 were identified. Gene expression profiles were obtained from a subset of these tumors and identified a group of genes whose differential expression was significantly associated with drug resistance. Within this group, five genes (GAPD, HMGB2, HSC70, GRP58, and HMGB1), previously shown to form a nuclear complex associated with resistance to DNA conformation-altering chemotherapeutic drugs in in vitro systems, may represent a novel class of genes associated with in vivo drug response in ovarian cancer patients. Although RNA expression change indicated only weak DNA copy number dependence, these data illustrate the value of molecular profiling at both the RNA and DNA levels to identify small genomic regions and gene subsets that could be associated with differential chemotherapy response in ovarian cancer.

Expression of SRY proteins in both normal and sex-reversed XY fetal mouse gonads.

Sry, a single-copy gene on the Y-chromosome, acts dominantly to trigger differentiation of a testis from a gonadal primordium that otherwise develops into an ovary in mammals. Sry encodes a protein with a DNA-binding domain and probably acts as a transcription factor. However, the mode of SRY action in testis determination remains largely unknown. In the present study, we detected the endogenous SRY protein in normal XY fetal mouse gonads by Western blotting and immunohistochemistry. The tissue-specificity and ontogeny of the detected protein were consistent with those of Sry transcripts. Immunofluorescent double labeling revealed that the SRY protein was detected in the Sertoli cell lineage and was swiftly down-regulated concurrently with testis cord organization. Surprisingly, however, the SRY protein was detected in the entire gonad from the onset of its expression, not in parallel to the spatiotemporal pattern of testis cord organization. The SRY protein was also detected in the entire region of all B6.Y(TIR) fetal gonads, which were anticipated to undergo either partial or complete sex reversal. SRY down-regulation was considerably delayed, compared with control B6.XY gonads and was not associated with testis cord organization in B6.Y(TIR) gonads. We conclude that the testis-determining pathway is impaired at the site of SRY action in the B6.Y(TIR) gonad.

Using microarrays to predict resistance to chemotherapy in cancer patients.

Chemotherapy resistance remains a major obstacle to successful treatment and better outcome in cancer patients. The advent of whole genome experimental strategies, such as DNA microarrays, has transformed the way researchers approach cancer research. There is considerable hope that microarray technology will lead to the identification of new targets for therapeutic intervention, a better understanding of the disease process, and, ultimately, to higher survival rates and more personalized medicine. The question at hand is what is the best approach to apply these new technologies to the study of anticancer drug resistance, and how can the results obtained in the laboratory be quickly moved to a clinical setting? This review offers an overview of the microarray technology, including its recently associated strategies, such as array comparative genomic hybridization and promoter arrays. It also highlights some recent examples of microarray studies, which represent a first step toward a better understanding of drug resistance in cancer and, ultimately, personalized medicine.