ABSTRACT
We have developed an integrated, multidisciplinary methodology, termed systems pathology, to generate highly accurate predictive tools for complex diseases, using prostate cancer for the prototype. To predict the recurrence of prostate cancer following radical prostatectomy, defined by rising serum prostate-specific antigen (PSA), we used machine learning to develop a model based on clinicopathologic variables, histologic tumor characteristics, and cell type-specific quantification of biomarkers. The initial study was based on a cohort of 323 patients and identified that high levels of the androgen receptor, as detected by immunohistochemistry, were associated with a reduced time to PSA recurrence. The model predicted recurrence with high accuracy, as indicated by a concordance index in the validation set of 0.82, sensitivity of 96%, and specificity of 72%. We extended this approach, employing quantitative multiplex immunofluorescence, on an expanded cohort of 682 patients. The model again predicted PSA recurrence with high accuracy, concordance index being 0.77, sensitivity of 77% and specificity of 72%. The androgen receptor was selected, along with 5 clinicopathologic features (seminal vesicle invasion, biopsy Gleason score, extracapsular extension, preoperative PSA, and dominant prostatectomy Gleason grade) as well as 2 histologic features (texture of epithelial nuclei and cytoplasm in tumor only regions). This robust platform has broad applications in patient diagnosis, treatment management, and prognostication.
Subject(s)
Neoplasm Recurrence, Local/diagnosis , Neoplasm Recurrence, Local/pathology , Pathology/methods , Prostatic Neoplasms/pathology , Systems Biology/methods , Cell Nucleus/metabolism , Disease-Free Survival , Humans , Male , Models, Biological , Neoplasm Recurrence, Local/metabolism , Prostate-Specific Antigen/blood , Prostatic Neoplasms/metabolism , Receptors, Androgen/metabolism , Sensitivity and Specificity , Survival Rate , Tissue Array AnalysisABSTRACT
PURPOSE: Canine malignant melanoma (CMM) is a spontaneous, aggressive, and metastatic neoplasm. Preclinical mouse studies have shown that xenogeneic DNA vaccination with genes encoding tyrosinase family members can induce antibody and cytotoxic T-cell responses, resulting in tumor rejection. These studies provided the rationale for a trial of xenogeneic DNA vaccination in CMM using the human tyrosinase gene. EXPERIMENTAL DESIGN: Three cohorts of three dogs each with advanced (WHO stage II, III, or IV) CMM received four biweekly i.m. injections (dose levels 100, 500, or 1500 micro g, respectively/vaccination) of human tyrosinase plasmid DNA i.m. via the Biojector2000 delivery device. RESULTS: Mild local reactions at injection sites were the only toxicities observed, with no signs of autoimmunity. One dog with stage IV disease had a complete clinical response in multiple lung metastases for 329 days. Two dogs with stage IV disease had long-term survivals (421 and 588+ days) in the face of significant bulky metastatic disease, and two other dogs with locally controlled stage II/III disease had long-term survivals (501 and 496 days) with no evidence of melanoma on necropsy. Four other dogs were euthanized because of progression of the primary tumor. The Kaplan-Meier median survival time for all nine dogs was 389 days. CONCLUSIONS: The results of this trial demonstrate that xenogeneic DNA vaccination of dogs with advanced malignant melanoma is a safe and potentially therapeutic modality. On the basis of these results, additional evaluation of this novel therapeutic is warranted in locally controlled CMM and advanced human melanoma.
Subject(s)
Cancer Vaccines/therapeutic use , Melanoma/therapy , Vaccines, DNA/therapeutic use , Animals , Cohort Studies , DNA, Complementary/metabolism , Dogs , Female , Humans , Immunotherapy/methods , Male , Melanoma/mortality , Monophenol Monooxygenase/genetics , Plasmids/metabolism , Radiography, Thoracic , Time FactorsABSTRACT
We developed a robust multiplex fluorescent in situ hybridization (FISH) technique in archival formalin-fixed, paraffin-embedded (FFPE) human tissue sections while preserving the microanatomical context. This identifies single-cell gene expression patterns by probing multiple, unique nascent RNA transcripts and yields predictive quantitative gene expression signatures.