Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer.

Histologic grading of breast cancer defines morphologic subtypes informative of metastatic potential, although not without considerable interobserver disagreement and clinical heterogeneity particularly among the moderately differentiated grade 2 (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade 1 (G1) and grade 3 (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with G2 disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable with that of lymph node status and tumor size. When incorporated into the Nottingham prognostic index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low- and high-grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression.

The Prognosis of Survival in Patients with Some Solid Tumors Based on Optimal Partitions of Immunological Parameter Ranges.

New logical and statistical methods were used for the analysis of relationships between survival rate of solid tumor patients and immunological variables. These methods are based on the search of the regularities (syndromes) in the multidimensional space. The syndromes are the elements of partitions of allowable areas of variables. To estimate the statistical validity of found regularities the new technique based on Monte-Carlo computer simulation was used. The broad panel of monoclonal antibodies for lymphocyte differentiation antigens was used for subpopulation analysis. The two tasks are described. The purpose of the first task was the evaluation of significance of immunological parameters for prediction of one-year metastasis-free survival in non-metastatic osteosarcoma of extremities. The second task was the construction of the predicting algorithm for prognosis of two-year survival of patients with stomach cancer. The optimal sets of parameters for prediction of survival were found for both tasks. We found out the high predictive value of HLA DR(+) cells percentage in the 1st task, and the percentage of adhesion cells (CD50(+) lymphocytes) is the most significant parameter in the 2nd task. The predictive algorithms were developed.

Logical and Statistical Approach for the Analysis of Immunological Parameters in Patients with Wilson's Disease.

The immunological tests were performed for blood samples from 30 patients with Wilson's disease and 37 healthy patients. The processed data included conventional statistical analysis and computer programs, consisting of new pattern recognition methods - method of statistically weighted syndromes and that of detecting the informative conjunctions. In Wilson's disease group the significant alterations of parameters were determined: the decrease of T lymphocytes amount and CD4/CD8 ratio; the increase of circulating immune complexes and IgM levels; and B lymphocytes and NK amount. The methods of pattern recognition allowed to generate the rule to discriminate the cases from Wilson's disease and control groups with 87% effectiveness. The most frequently observed combinations of the altered parameters' values were revealed, and then the subgroups of Wilson's disease cases were considered. They were characterised by activation of the humoral immunity and/or depression of the cellular one. The heterogeneity of the immunity modifications may be the reflection of both genetic polymorphism and stages of the immunity violation. Some essential features of the immune status of patients with Wilson's disease are discussed.