Myriam Remmelink

Nuclear galectin-3 expression is an independent predictive factor of recurrence for adenocarcinoma and squamous cell carcinoma of the lung

The tumor stage is the most powerful prognostic tool for predicting the survival rates of lung carcinoma patients. However, prognosis of individual patients is difficult in part because of the marked clinical heterogeneity among such patients. Galectins are involved in cell growth, apoptosis and cell migration features, and their diagnostic and prognostic values have already been demonstrated in various types of cancers. In the present paper we analyze the potential prognostic value of immunohistochemical galectin-3 expression in lung adenocarcinomas and squamous cell carcinomas. In all, 165 squamous cell carcinomas and 121 adenocarcinomas were immunostained for galectin-3. In each case the immunohistochemical analyses consisted of an evaluation of the percentage of tumor cells stained and the intensity of staining. An IP score (ie Intensity × Percentage) was thus determined for each lung carcinoma. A large majority of cases displayed galectin-3 expression. While the cytoplasmic staining in the squamous cell carcinomas was focal and moderately intense, the staining in the adenocarcinomas was diffuse and intense. The IP scores were significantly (P=0.0001) higher in the adenocarcinomas than in the squamous cell carcinomas. The difference in nuclear expression profiles between the two cancer types was statistically significant (P=0.0005). Cox multivariate analysis carried out on the patients genders, the TNM classification and the galectin-3-related variables showed that of the galectin-3-related variables, only the nuclear location of galectin-3 was identified as a prognostic indicator of recurrence independent of the clinicopathological features characterizing the patients (P=0.02). The prognostic contribution of this latter variable was enhanced when the patients with relapse-free follow-ups longer than 8 months were considered (P=0.005). Galectin-3 immunohistochemical expression differs between squamous cell carcinomas and adenocarcinomas, but the nuclear expression of galectin-3 behaves as a significant prognostic predictor for all the cases as a group.

Methodological aspects of using decision trees to characterise leiomyomatous tumors.

The aim of the present work is to present the potential uses of a classification technique labeled the decision tree for tumor characterisation when faced with a large number of features. The decision tree technique enables multifeature logical classification rules to be produced by determining discriminatory values for each feature selected. In this report, we propose a methodology that used decision trees to compare and evaluate the information contributed by different types of features for tumor characterisation. This methodology is able to produce a set of hypotheses related to a diagnosis and or prognosis problem. For example, hypotheses can be producted (on the basis of a set of descriptive features) to explain why tumor cases belong to a given histopathological group. To illustrate our purpose, this methodology was applied to the difficult problem of leiomyomatous tumour diagnosis. The aim was to illustrate what kind of diagnostic information can be extracted from a sample data set including 23 smooth muscle tumors (14 benign leiomyomas and 9 malignant leiomyosarcomas) described by a large set of computer-assisted, microscope-generated features. Three groups of features were used relating to: (1) ploidy level determination (10 features), (2) quantitative chromatin pattern description (15 features), and (3) immunohistochemically related antigen specificities (6 features). All these features were quantified by digital cell image analysis. The results suggest that an objective distinction between leiomyomas and leiomyosarcomas can be established by means of simple logical rules depending on only a few features among which the immunohistochemically revealed antigen expression of desmin plays a preponderant part. One of the combinations of features proposed by the methodology is interesting for pathologists, because it includes two features describing the appearance of a nucleus in terms of chromatin distribution homogeneity and density, two features widely used by pathologists in tumor-grading systems.

Determination of DNA ploidy, nuclear size, and proliferative activity by means of the computer-assisted image analysis of feulgen-stained nuclei in 68 soft tissue tumors of adults

The diagnostic values of the ploidy level, the proliferative activity, and the nuclear size in a series of 68 soft tissue tumors of adults were determined by digital cell image analysis of Feulgen-stained nuclei from formalin-fixed, paraffin-embedded tissues. The DNA ploidy level was characterized by calculating the DNA index (DI) and the percentage of the diploid and polyploid cells, and by typing the DNA histogram. Proliferative activity assessments were a function of the determination of the proliferation index (PI), ie, the percentage of cells engaged in the S phase of the cell cycle (SPF value). The present series included 19 benign and 49 malignant soft tissue tumors. The results show that DNA aneuploidy, as assessed by both the DI and the DNA histogram type, cannot be used as a discriminatory parameter for distinguishing between benign and malignant soft tissue tumors. Indeed, some benign cases may be highly aneuploid, whereas some highly malignant soft tissue tumors may be definitely diploid. In contrast, the determination of the percentage of polyploid cell nuclei seems to be a useful parameter in distinguishing between benign and malignant cases. In fact, the benign soft tissue tumors showed a very significantly lower mean percentage value of polyploid cell nuclei than the malignant cases. The determination of the proliferative activity also discriminated significantly between the benign and the malignant cases, the former proliferating more slowly than the latter. Lastly, the determination of nuclear size made it possible to differentiate the primary malignant soft tissue tumors, whether recurrent or not, that were associated with metastasis from those free of metastasis.

The chromatin pattern of cell nuclei is of prognostic value for renal cell carcinomas

Using a series of 105 renal cell carcinomas (RCCs) we investigated whether features quantitatively describing the appearance of Feulgen‐stained nuclei and, more particularly, of their chromatin (on the basis of computer‐assisted microscopy) can contribute any significant prognostic information. Thirty morphonuclear and 8 nuclear DNA content‐related variables were thus generated. The actual prognostic values of this set of cytometric variables was compared (by means of discriminant statistical analysis) to conventional diagnostic and/or prognostic markers including histopathological grades, tumour invasion levels and the presence or absence of metastases. We obtained complete clinical follow‐ups for 49 of the 105 RCC patients under study, making it possible to define a subset of patients with a bad prognosis (i.e., who died in the 12 months following nephrectomy) and a subset of patients with a good prognosis (i.e., who survived at least 24 months following nephrectomy). An original method of data analysis related to artificial intelligence (decision tree induction) enabled a strong prognostic model to be set up. In the case of 10 new patients, this model identified all the dead patients as having a bad survival status, with a total of 8 correct predictions. Another prognostic model similarly generated enabled the correct predictions to be confirmed.