Dimitrios Spentzos

PURPOSE: To define a gene expression profile of BRCAness that correlates with chemotherapy response and outcome in epithelial ovarian cancer (EOC). METHODS: A publicly available microarray data set including 61 patients with EOC with either sporadic disease or BRCA(1/2) germline mutations was used for development of the BRCAness profile. Correlation with platinum responsiveness was assessed in platinum-sensitive and platinum-resistant tumor biopsy specimens from six patients with BRCA germline mutations. Association with poly-ADP ribose polymerase (PARP) inhibitor responsiveness and with radiation-induced RAD51 foci formation (a surrogate of homologous recombination) was assessed in Capan-1 cell line clones. The BRCAness profile was validated in 70 patients enriched for sporadic disease to assess its association with outcome. RESULTS: The BRCAness profile accurately predicted platinum responsiveness in eight out of 10 patient-derived tumor specimens, and between PARP-inhibitor sensitivity and resistance in four out of four Capan-1 clones. [corrected] When applied to the 70 patients with sporadic disease, patients with the BRCA-like (BL) profile had improved disease-free survival (34 months v 15 months; log-rank P = .013) and overall survival (72 months v 41 months; log-rank P = .006) compared with patients with a non-BRCA-like (NBL) profile, respectively. The BRCAness profile maintained independent prognostic value in multivariate analysis, which controlled for other known clinical prognostic factors. CONCLUSION: The BRCAness profile correlates with responsiveness to platinum and PARP inhibitors and identifies a subset of sporadic patients with improved outcome. Additional evaluation of this profile as a predictive tool in patients with sporadic EOC is warranted.

PURPOSE: To address the progression, metastasis, and clinical heterogeneity of renal cell cancer (RCC). EXPERIMENTAL DESIGN: Transcriptional profiling with oligonucleotide microarrays (22,283 genes) was done on 49 RCC tumors, 20 non-RCC renal tumors, and 23 normal kidney samples. Samples were clustered based on gene expression profiles and specific gene sets for each renal tumor type were identified. Gene expression was correlated to disease progression and a metastasis gene signature was derived. RESULTS: Gene signatures were identified for each tumor type with 100% accuracy. Differentially expressed genes during early tumor formation and tumor progression to metastatic RCC were found. Subsets of these genes code for secreted proteins and membrane receptors and are both potential therapeutic or diagnostic targets. A gene pattern ("metastatic signature") derived from primary tumor was very accurate in classifying tumors with and without metastases at the time of surgery. A previously described "global" metastatic signature derived by another group from various non-RCC tumors was validated in RCC. CONCLUSION: Unlike previous studies, we describe highly accurate and externally validated gene signatures for RCC subtypes and other renal tumors. Interestingly, the gene expression of primary tumors provides us information about the metastatic status in the respective patients and has the potential, if prospectively validated, to enrich the armamentarium of diagnostic tests in RCC. We validated in RCC, for the first time, a previously described metastatic signature and further showed the feasibility of applying a gene signature across different microarray platforms. Transcriptional profiling allows a better appreciation of the molecular and clinical heterogeneity in RCC.

Resistance to platinum-based chemotherapy develops in the majority of patients with epithelial ovarian cancer (EOC). Platinum compounds form electrophilic intermediates that mediate DNA cross-linking and induce double-strand DNA breaks. Because the cellular response to electrophilic xenobiotics is partly mediated by Keap1-Nrf2 pathway, we evaluated the presence of Kelch-like ECH-associated protein 1 (Keap1) mutations and NF-E2-related factor 2 (Nrf2) pathway activation in EOC and correlated these with platinum resistance and clinical outcome. Nrf2 immunohistochemistry revealed nuclear localization (a surrogate of pathway activation) in over half of EOC patient specimens examined, with more common occurrence in the clear cell EOC subtype. Quantitative real-time PCR revealed that Nrf2 target genes were upregulated in tumors with nuclear positivity for Nrf2. Microarray analysis also showed upregulation of Nrf2 target genes in clear cell EOCs compared with other EOC subtypes. In addition, Keap1 sequence analysis revealed genetic mutations in 29% of clear cell samples and 8% of nonclear cell tumors. RNAi-mediated knockdown of Keap1 was associated with Nrf2 pathway activation and resistance to carboplatin in vitro. Importantly, patients with evidence of Nrf2 pathway activation had fewer complete clinical responses to platinum-based therapy, were enriched for platinum resistance, and had shorter median overall survival compared with those who did not show evidence of Nrf2 pathway activation. Our findings identify Keap1 mutations in EOC and they suggest a previously unrecognized role for the Keap1-Nrf2 pathway in mediating chemotherapeutic responses in this disease.

PURPOSE: Currently available clinical and molecular prognostic factors provide an imperfect assessment of prognosis for patients with epithelial ovarian cancer (EOC). In this study, we investigated whether tumor transcription profiling could be used as a prognostic tool in this disease. METHODS: Tumor tissue from 68 patients was profiled with oligonucleotide microarrays. Samples were randomly split into training and validation sets. A three-step training procedure was used to discover a statistically significant Kaplan-Meier split in the training set. The resultant prognostic signature was then tested on an independent validation set for confirmation. RESULTS: In the training set, a 115-gene signature referred to as the Ovarian Cancer Prognostic Profile (OCPP) was identified. When applied to the validation set, the OCPP distinguished between patients with unfavorable and favorable overall survival (median, 30 months v not yet reached, respectively; log-rank P = .004). The signature maintained independent prognostic value in multivariate analysis, controlling for other known prognostic factors such as age, stage, grade, and debulking status. The hazard ratio for death in the unfavorable OCPP group was 4.8 (P = .021 by Cox proportional hazards analysis). CONCLUSION: The OCPP is an independent prognostic determinant of outcome in EOC. The use of gene profiling may ultimately permit identification of EOC patients appropriate for investigational treatment approaches, based on a low likelihood of achieving prolonged survival with standard first-line platinum-based therapy.

PURPOSE: Proteomic profiling using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS) enables the identification of biomarkers for cancer. We evaluated the sensitivity and specificity of SELDI-TOF MS for detection of established hepatocellular cancer (HCC) and compared it against alpha-fetoprotein (AFP), Lens culinaris agglutinin-reactive AFP (AFP-L3), and prothrombin induced by vitamin K absence-II (PIVKA-II). EXPERIMENTAL DESIGN: Forty-one patients with HCC and 51 patients with hepatitis C cirrhosis were enrolled. Serum was analyzed by SELDI-TOF MS using three Ciphergen protein array types. RESULTS: An 11-peak algorithm for HCC detection was identified. Using the AFP cutoff of 20 ng/mL, the sensitivity was 73% and the specificity was 71%. Using the AFP-L3 cutoff of 10% yielded a sensitivity of 63% and a specificity of 94%. Using the PIVKA-II cutoff of 125 milliabsorbance units (mAU), the sensitivity was 84% and the specificity was 69%. Overall, the sensitivity and specificity of SELDI-TOF MS for HCC were 79% and 86%, respectively. In multivariate analysis, the 11-peak SELDI profile was predictive of HCC independent of AFP, PIVKA, and AFP-L3. Among eight patients with the largest tumor size of <2 cm, SELDI-TOF MS correctly identified seven whereas AFP, AFP-L3, and PIVKA-II identified only three, one, and one, respectively. One of the 11 peaks in the SELDI-TOF MS 11-peak predictor from SELDI-TOF MS was identified as cystatin C. CONCLUSIONS: SELDI-TOF MS accurately distinguished patients with HCC from those with hepatitis C virus cirrhosis, was more accurate than traditional biomarkers in identifying small tumors, and should be further evaluated.