Dmitri Talantov

Multicenter Validation of a Gene Expression–Based Prognostic Signature in Lymph Node–Negative Primary Breast Cancer

PURPOSE We previously identified in a single-center study a 76-gene prognostic signature for lymph node-negative (LNN) breast cancer patients. The aim of this study was to validate this gene signature in an independent more diverse population of LNN patients from multiple institutions. PATIENTS AND METHODS Using custom-designed DNA chips we analyzed the expression of the 76 genes in RNA of frozen tumor samples from 180 LNN patients who did not receive adjuvant systemic treatment. RESULTS In this independent validation, the 76-gene signature was highly informative in identifying patients with distant metastasis within 5 years (hazard ratio, [HR], 7.41; 95% CI, 2.63 to 20.9), even when corrected for traditional prognostic factors in multivariate analysis (HR, 11.36; 95% CI, 2.67 to 48.4). The actuarial 5- and 10-year distant metastasis-free survival were 96% (95% CI, 89% to 99%) and 94% (95% CI, 83% to 98%), respectively, for the good profile group and 74% (95% CI, 64% to 81%) and 65% (53% to 74%), respectively for the poor profile group. The sensitivity for 5-yr distant metastasis-free survival was 90%, and the specificity was 50%. The positive and negative predictive values were 38% (95% CI, 29% to 47%) and 94% (95% CI, 86% to 97%), respectively. The 76-gene signature was confirmed as a strong prognostic factor in subgroups of estrogen receptor-positive patients, pre- and postmenopausal patients, and patients with tumor sizes 20 mm or smaller. The subgroup of patients with estrogen receptor-negative tumors was considered too small to perform a separate analysis. CONCLUSION Our data provide a strong methodologic and clinical multicenter validation of the predefined prognostic 76-gene signature in LNN breast cancer patients.

Novel Genes Associated with Malignant Melanoma but not Benign Melanocytic Lesions

Purpose: Cutaneous melanoma is a common, aggressive cancer with increasing incidence. The identification of melanoma-specific deregulated genes could provide molecular markers for lymph node staging assays and further insight into melanoma tumorigenesis. Experimental Design: Total RNA isolated from 45 primary melanoma, 18 benign skin nevi, and 7 normal skin tissue specimens were analyzed on an Affymetrix Hu133A microarray containing 22,000 probe sets. Results: Hierarchical clustering revealed a distinct separation of the melanoma samples from the benign and normal specimens. Novel genes associated with malignant melanoma were identified. Differential gene expression of two melanoma-specific genes, PLAB and L1CAM, were tested by a one-step quantitative reverse transcription-PCR assay on primary malignant melanoma, benign nevi, and normal skin samples, as well as on malignant melanoma lymph node metastasis and melanoma-free lymph nodes. The performance of the markers was compared with conventional melanoma markers such as tyrosinase, gp100, and MART1. Conclusion: Our study systematically identified novel melanoma-specific genes and showed the feasibility of using a combination of PLAB and L1CAM in a reverse transcription-PCR assay to differentiate clinically relevant samples containing benign or malignant melanocytes.

Molecular Profiling of Carcinoma of Unknown Primary and Correlation With Clinical Evaluation

PURPOSE To evaluate the feasibility of a 10-gene reverse transcriptase polymerase chain reaction assay to identify the tissue of origin in patients with carcinoma of unknown primary (CUP) site. PATIENTS AND METHODS Diagnostic biopsy formalin-fixed, paraffin-embedded (FFPE) specimens from 120 patients with CUP were collected retrospectively from Sarah Cannon Research Institute, Nashville, TN, and prospectively from The University of Texas M. D. Anderson Cancer Center, Houston, TX. Tissue of origin assignments by the assay were correlated with clinical and pathologic features and with response to therapy. RESULTS The assay was successfully performed in 104 patients (87%), and a tissue of origin was assigned in 63 patients (61%). In the remaining 41 patients (39%), the molecular profiles were not specific for the six tumor types detectable by this assay. The tissues of origin most commonly identified were lung, pancreas, and colon; most of these patients had clinical and pathologic features consistent with these diagnoses. Patients with lung and pancreas profiles had poor response to treatment. Patients with colon cancer profiles had better response to colon cancer-specific therapies than they did to empiric CUP therapy with taxane/platinum regimens. Patients with ovarian cancer profiles were atypical, with widespread visceral metastases and a paucity of overt peritoneal involvement. CONCLUSION This gene expression profiling assay was feasible using FFPE biopsy specimens and identified a putative tissue of origin in 61% of patients with CUP. In most patients, the assigned tissue of origin was compatible with clinicopathologic features and response to treatment. Prospective studies in which assay results are used to direct therapy are indicated.

Gene Based Prediction of Clinically Localized Prostate Cancer Progression After Radical Prostatectomy

PURPOSE Accurate estimates of recurrence risk are needed for optimal treatment of patients with clinically localized prostate cancer. We combined an established nomogram and what to our knowledge are novel molecular predictors into a new prognostic model of prostate specific antigen recurrence. MATERIALS AND METHODS We analyzed gene expression profiles from formalin fixed, paraffin embedded, localized prostate cancer tissues to identify genes associated with prostate specific antigen recurrence. Profiles of the identified markers were reproduced by reverse transcriptase-polymerase chain reaction. We used the profiles of 3 of these genes along with output from the Kattan postoperative nomogram to produce a predictive model of prostate specific antigen recurrence. RESULTS After variable selection we built a model of prostate specific antigen recurrence combining expression values of 3 genes and the postoperative nomogram. The 3-gene plus nomogram model predicted 5-year prostate specific antigen recurrence with a concordance index of 0.77 in a validation set compared to a concordance index of 0.67 for the nomogram. This model identified a subgroup of patients at high risk for recurrence that was not identified by the nomogram. CONCLUSIONS This new gene based classifier has superior predictive power compared to that of the 5-year nomogram to assess the risk of prostate specific antigen recurrence in patients with organ confined prostate cancer. Our classifier should provide more accurate stratification of patients into high and low risk groups for treatment decisions and adjuvant clinical trials.