Clinical outcome of maraviroc-containing therapy in heavily pre-treated HIV-1-infected patients.

Available data on the use of maraviroc (MVC) in clinical settings are limited. In this cohort study, the clinical outcomes of HIV-1-infected patients treated with MVC were analysed and the predictive values of different tropism assays were compared. Baseline viral tropism was assessed and compared by phenotypic (Trofile and MT-2) and genotypic assays. Virological and immunological responses were evaluated. In total, 62 predominantly extensively pre-treated patients started MVC [median GSS 2.0 (IQR 2.0-2.5)]. Tropism assays were performed on baseline samples of 58 patients (93.5%). Thirty-two samples (80.0%) were classified as R5 by Trofile, 41 (80.4%) by genotypic tropism test (GTT) and 17 (81.0%) by MT-2. At least two types of tropism assay were performed on samples from 39 patients, whereas in 15 patients all three assays were performed (concordance 84.8-94.1%). Plasma HIV-RNA was <50 copies/mL in 82.1%, 85.0% and 68.8% of patients after 12, 24 and 36 months, respectively; median CD4 cell increase was 199 (IQR 108-283), 291 (IQR 187-413) and 234 (IQR 106-444)cells/µL. The predictive values of different tropism assays were comparably high: at Month 24, 92.9% (Trofile and GTT) and 100.0% (MT-2) of patients had plasma HIV-RNA <50 copies/mL. Three patients stopped MVC treatment because of suspected side effects. Five patients died during follow-up. In this heavily pre-treated cohort, treatment with MVC was well tolerated and resulted in good immunological and virological responses. Results generated by the different tropism assays correlated well with each other and had a high predictive value.

Comparison of digital PCR platforms and semi-nested qPCR as a tool to determine the size of the HIV reservoir.

HIV persists in latently infected cells of patients on antiretroviral therapy (ART). This persistent proviral DNA reservoir is an important predictor of viral rebound upon therapy failure or interruption and forms a major obstacle towards cure. Accurate quantification of the low levels of persisting HIV DNA may aid patient monitoring and cure research. Digital PCR is a promising tool that enables direct absolute quantification with high sensitivity. With recent technological advances, several platforms are available to implement digital PCR in a clinical setting. Here, we compared two digital PCR platforms, the Quantstudio 3D (Life Technologies) and the QX100 (Bio-Rad) with a semi-nested qPCR on serial HIV DNA dilutions and DNA isolated from PBMCs of ART-suppressed patients. All three methods were able to detect target to the lowest levels of 2.5 HIV DNA copies. The QX100 excelled in having the least bias and highest precision, efficiency and quantitative linearity. Patient sample quantifications by the QX100 and semi-nested qPCR were highly agreeable by Bland-Altman analysis (0.01±0.32 log10). Due to the observation of false-positive signals with current digital PCR platforms however, semi-nested qPCR may still be preferred in a setup of low quantity detection to discriminate between presence or absence of HIV DNA.

Primary resistance to integrase strand-transfer inhibitors in Europe.

OBJECTIVES: The objective of this study was to define the natural genotypic variation of the HIV-1 integrase gene across Europe for epidemiological surveillance of integrase strand-transfer inhibitor (InSTI) resistance. METHODS: This was a multicentre, cross-sectional study within the European SPREAD HIV resistance surveillance programme. A representative set of 300 samples was selected from 1950 naive HIV-positive subjects newly diagnosed in 2006-07. The prevalence of InSTI resistance was evaluated using quality-controlled baseline population sequencing of integrase. Signature raltegravir, elvitegravir and dolutegravir resistance mutations were defined according to the IAS-USA 2014 list. In addition, all integrase substitutions relative to HXB2 were identified, including those with a Stanford HIVdb score ≥ 10 to at least one InSTI. To rule out circulation of minority InSTI-resistant HIV, 65 samples were selected for 454 integrase sequencing. RESULTS: For the population sequencing analysis, 278 samples were retrieved and successfully analysed. No signature resistance mutations to any of the InSTIs were detected. Eleven (4%) subjects had mutations at resistance-associated positions with an HIVdb score ≥ 10. Of the 56 samples successfully analysed with 454 sequencing, no InSTI signature mutations were detected, whereas integrase substitutions with an HIVdb score ≥ 10 were found in 8 (14.3%) individuals. CONCLUSIONS: No signature InSTI-resistant variants were circulating in Europe before the introduction of InSTIs. However, polymorphisms contributing to InSTI resistance were not rare. As InSTI use becomes more widespread, continuous surveillance of primary InSTI resistance is warranted. These data will be key to modelling the kinetics of InSTI resistance transmission in Europe in the coming years.

Impact of triplicate testing on HIV genotypic tropism prediction in routine clinical practice.

Guidelines state that the CCR5-inhibitor Maraviroc should be prescribed to patients infected with R5-tropic HIV-1 only. Therefore, viral tropism needs to be assessed phenotypically or genotypically. Preliminary clinical trial data suggest that genotypic analysis in triplicate is associated with improved prediction of virological response by increasing the detection of X4-tropic variants. Our objective was to evaluate the impact of triplicate genotypic analysis on prediction of co-receptor usage in routine clinical practice. Samples from therapy-naive and therapy-experienced patients were collected for routine tropism testing at three European clinical centres. Viral RNA was isolated from plasma and proviral DNA from peripheral blood mononuclear cells. Gp120-V3 was amplified in a triplicate nested RT-PCR procedure and sequenced. Co-receptor usage was predicted using the Geno2Pheno([coreceptor]) algorithm and analysed with a false-positive rate (FPR) of 5.75%, 10%, or an FPR of 20% and according to the current European guidelines on the clinical management of HIV-1 tropism testing. A total of 266 sequences were obtained from 101 patient samples. Discordance in tropism prediction for the triplicates was observed in ten samples using an FPR of 10%. Triplicate testing resulted in a 16.7% increase in X4-predicted samples and to reclassification from R5 to X4 tropism for four cases rendering these patients ineligible for Maraviroc treatment. In conclusion, triplicate genotypic tropism testing increases X4 tropism detection in individual cases, which may prove to be pivotal when CCR5-inhibitor therapy is applied.

Tracking of migrating cells under phase-contrast video microscopy with combined mean-shift processes.

In this paper, we propose a combination of mean-shift-based tracking processes to establish migrating cell trajectories through in vitro phase-contrast video microscopy. After a recapitulation on how the mean-shift algorithm permits efficient object tracking we describe the proposed extension and apply it to the in vitro cell tracking problem. In this application, the cells are unmarked (i.e., no fluorescent probe is used) and are observed under classical phase-contrast microscopy. By introducing an adaptive combination of several kernels, we address several problems such as variations in size and shape of the tracked objects (e.g., those occurring in the case of cell membrane extensions), the presence of incomplete (or noncontrasted) object boundaries, partially overlapping objects and object splitting (in the case of cell divisions or mitoses). Comparing the tracking results automatically obtained to those generated manually by a human expert, we tested the stability of the different algorithm parameters and their effects on the tracking results. We also show how the method is resistant to a decrease in image resolution and accidental defocusing (which may occur during long experiments, e.g., dozens of hours). Finally, we applied our methodology on cancer cell tracking and showed that cytochalasin-D significantly inhibits cell motility.

Galectin-8 expression decreases in cancer compared with normal and dysplastic human colon tissue and acts significantly on human colon cancer cell migration as a suppressor.

BACKGROUND AND AIMS: Galectins are beta-galactoside binding proteins. This ability may have a bearing on cell adhesion and migration/proliferation in human colon cancer cells. In addition to galectins-1 and -3 studied to date, other members of this family not investigated in detail may contribute to modulation of tumour cell features. This evident gap has prompted us to extend galectin analysis beyond the two prototypes. The present study deals with the quantitative determination of immunohistochemical expression of galectin-8 in normal, benign, and malignant human colon tissue samples and in four human colon cancer models (HCT-15, LoVo, CoLo201, and DLD-1) maintained both in vitro as permanent cell lines and in vivo as nude mice xenografts. The role of galectin-8 (and its neutralising antibody) in cell migration was investigated in HCT-15, LoVo, CoLo201, and DLD-1 cell lines. METHODS: Immunohistochemical expression of galectin-8 and its overall ability to bind to sugar ligands (revealed glycohistochemically by means of biotinylated histochemically inert carrier bovine serum albumin with alpha- and beta-D-galactose, alpha-D-glucose, and lactose derivatives as ligands) were quantitatively determined using computer assisted microscopy. The presence of galectin-8 mRNA in the four human colon cancer cell lines was examined by reverse transcriptase-polymerase chain reaction. In vitro, cellular localisation of exogenously added galectin-8 in the culture media of these colon cancer cells was visualised by fluorescence microscopy. In vitro galectin-8 mediated effects (and the influence of its neutralising antibody) on migration levels of living HCT-15, LoVo, CoLo201, and DLD-1 cells were quantitatively determined by computer assisted phase contrast microscopy. RESULTS: A marked decrease in immunohistochemical expression of galectin-8 occurred with malignancy development in human colon tissue. Malignant colon tissue exhibited a significantly lower galectin-8 level than normal or benign tissue colon cancers; those with extensive invasion capacities (T3-4/N+/M+) harboured significantly less galectin-8 than colon cancers with localised invasion capacities (T1-2/N0/M0). The four experimental models (HCT-15, LoVo, CoLo201, and DLD-1) had more intense galectin-8 dependent staining in vitro than in vivo. Grafting the four experimental human colon cancer models onto nude mice enabled us to show that the immunohistochemical expression of galectin-8 was inversely related to tumour growth rate. In vitro, galectin-8 reduced the migration rate of only those human experimental models (HCT-15 and CoLo201) that exhibited the lowest growth rate in vivo. CONCLUSIONS: Expression of galectin-8 correlated with malignancy development, with suppressor activity, as shown by analysis of clinical samples and xenografts. In vitro, only the two models with low growth rates were sensitive to the inhibitory potential of this galectin. Future investigations in this field should involve fingerprinting of these newly detected galectins, transcending the common focus on galectins-1 and -3.

Computer-assisted analysis of epiluminescence microscopy images of pigmented skin lesions.

BACKGROUND: Epiluminescence microscopy (ELM) is a noninvasive clinical tool recently developed for the diagnosis of pigmented skin lesions (PSLs), with the aim of improving melanoma screening strategies. However, the complexity of the ELM grading protocol means that considerable expertise is required for differential diagnosis. In this paper we propose a computer-based tool able to screen ELM images of PSLs in order to aid clinicians in the detection of lesion patterns useful for differential diagnosis. METHODS: The method proposed is based on the supervised classification of pixels of digitized ELM images, and leads to the construction of classes of pixels used for image segmentation. This process has two major phases, i.e., a learning phase, where several hundred pixels are used in order to train and validate a classification model, and an application step, which consists of a massive classification of billions of pixels (i.e., the full image) by means of the rules obtained in the first phase. RESULTS: Our results show that the proposed method is suitable for lesion-from-background extraction, for complete image segmentation into several typical diagnostic patterns, and for artifact rejection. Hence, our prototype has the potential to assist in distinguishing lesion patterns which are associated with diagnostic information such as diffuse pigmentation, dark globules (black dots and brown globules), and the gray-blue veil. CONCLUSIONS: The system proposed in this paper can be considered as a tool to assist in PSL diagnosis.

In vitro motility evaluation of aggregated cancer cells by means of automatic image processing.

BACKGROUND: Set up of an automatic image processing based method that enables the motility of in vitro aggregated cells to be evaluated for a number of hours. METHODS: Our biological model included the PC-3 human prostate cancer cell line growing as a monolayer on the bottom of Falcon plastic dishes containing conventional culture media. Our equipment consisted of an incubator, an inverted phase contrast microscope, a Charge Coupled Device (CCD) video camera, and a computer equipped with an image processing software developed in our laboratory. This computer-assisted microscope analysis of aggregated cells enables global cluster motility to be evaluated. This analysis also enables the trajectory of each cell to be isolated and parametrized within a given cluster or, indeed, the trajectories of individual cells outside a cluster. RESULTS: The results show that motility inside a PC-3 cluster is not restricted to slight motion due to cluster expansion, but rather consists of a marked cell movement within the cluster. CONCLUSIONS: The proposed equipment enables in vitro aggregated cell motility to be studied. This method can, therefore, be used in pharmacological studies in order to select anti-motility related compounds. The compounds selected by the equipment described could then be tested in vivo as potential anti-metastatic.

Setting up of an original computer-assisted methodology to characterize in vitro drug-induced anti-angiogenic effects.

The development of angiogenesis within a tumor brings on a sequence of extremely complex molecular events. We have developed a methodology which enables a wide set of biological parameters to be quantitatively determined in the field of anti-angiogenesis pharmacology. This methodology which includes a video cell tracking device, is unique because it offers the possibility of evaluating the specific influence of a given compound with potential anti-angiogenic properties on cell cycle kinetics, cell death, global cell line growth, and cell motility. We chose TNP-470, a synthetic analogue of fumagilin, to test our methodology on HUVEC cell lines taken from various human umbilical cord veins. The experiments carried out with TNP-470 did not confirm all the data reported in the literature. Our results show that i) TNP-470 could be considered as a cytotoxic agent; ii) this compound had an apparently marginal cytostatic effect; and iii) it did not increase the apoptosis level. Our methodology also revealed that the HUVEC cell lines are very heterogeneous in terms of different biological parameters. This highlights the problem of the reproductibility of the result.

Gastrin inhibits motility, decreases cell death levels and increases proliferation in human glioblastoma cell lines.

Whether they are of low or high histopathological grade, human astrocytic tumors are characterized by a marked propensity to diffuse into large areas of normal brain parenchyma. This invasion relates mainly to cell motility, which enables individual cell migration to take place. The present study characterizes in vitro the gastrin-mediated effects on both the growth (cell proliferation vs. cell death) and motility dynamics of the human U87 and U373 glioblastoma cell lines. A computer-assisted phase-contrast microscope was used to track the number of mitoses versus cell deaths every 4 min over a 72-h period and so to quantitatively describe the trajectories of living U373 and U87 cells growing on plastic supports in culture media both with and without the addition of 0.1, 5, or 100 nM gastrin. While 5 or 100 nM gastrin only weakly (p < .05 to p < .01) increased cell proliferation in the U87 cell line and not in U373 one, it very significantly (p < .001) inhibited the amount of cell death at 5 and 100 nM in both the U87 and U373 lines. In addition, 5 nM gastrin markedly inhibited cell mobility in U87 (p < .00001) and U373 (p < .0001) glioblastoma models. All these data strongly suggest that gastrin plays a major role in the biological behavior of the in vitro U87 and U373 human glioblastoma cell lines in matters concerning their levels of cell motility and growth dynamics.

Characterization of astroglial versus oligodendroglial phenotypes in glioblastomas by means of quantitative morphonuclear variables generated by computer-assisted microscopy.

The current WHO classification places glioblastomas in the astrocytoma category. However, whether or not glioblastomas also show oligodendroglial differentiation remains a matter of controversy. This study investigates, at the morphonuclear level, the hypothesis that some glioblastomas (GBMs) may also represent the ultimate level of malignancy in the oligodendroglial lineage. Using a series of 164 GBMs, we sought to ascertain whether any of these GBMs exhibited phenotypical characteristics that were more closely related to oligodendroglial lineages than astrocytic lineages. Phenotypical features were quantitatively determined by means of the computer-assisted microscope analysis of Feulgen-stained nuclei, a process that made it possible to quantitatively describe the patterns of the cell nuclei (and, more specifically, of their chromatin) through 16 variables, and the distribution of the nuclear DNA content (DNA ploidy) through 8 variables. The phenotypical characteristics typical of astrocytic and oligodendroglial tumors were analyzed by means of Discriminant Analysis, a statistical multivariate analysis, performed on a series of 65 astrocytic and oligodendroglial tumors. This series consisted of 14 WHO grade II and 19 grade III astrocytomas and 24 WHO grade II and 8 grade III oligodendrogliomas. This multivariate analysis enabled an accurate model to be produced that distinguished between astrocytomas and oligodendrogliomas on the basis of 5 cytometry-generated variables. This model was used to characterize the phenotype of each of the 164 glioblastomas. The results show that of these 164 glioblastomas, 6 (about 3.5%) displayed phenotypes that were very similar to oligodendrogliomas, and 141 displayed phenotypes that were very similar to astrocytomas. The phenotypes of the 17 remaining GBMs were too ambiguous to be categorized as having a pure astrocytic or oligodendroglial lineage.

Classification strategies for the grading of renal cell carcinomas, based on nuclear morphometry and densitometry.

The various grading systems proposed for renal cell carcinomas all suffer from problems related to inter-observer variability. Some of these grading systems are based, either partially or wholly, on morphonuclear criteria, such as nuclear size and shape, anisonucleosis, and chromatin pattern. These criteria can be quantitatively (and thus objectively) evaluated by means of the computer-assisted microscopic analysis of Feulgen-stained nuclei. In the present work, 39 quantitative variables, including two morphometric, 28 chromatin pattern-related, and nine DNA ploidy level-related, were computed for 65 renal cell carcinomas. The actual diagnostic information contributed by each variable was determined by means of multifactorial statistical analysis (discriminant analysis) and two artificial intelligence-related methods of data classification (the decision tree and production rule methods). The results show that quantitative information, as provided by the computer-assisted microscopy of Feulgen-stained nuclei and analysed by means of artificial intelligence-related methods of data classification, contributes significant diagnostic information for the grading of renal cell carcinoma, thus reducing the problem of inter-observer reproducibility.

Decision tree induction: a useful tool for assisted diagnosis and prognosis in tumor pathology.

The aim of the present work is to show that decision tree induction algorithms are a useful tool for extracting reliable information from data series, with the objective of assisting pathologists in identifying specific diagnostic and prognostic markers in various types of tumor pathologies. In terms of accuracy, we show that the decision tree technique exceeds other more sophisticated techniques, such as multilayer neural networks. Furthermore, because of the case with which decision tree results can be interpreted (logical classification rules), new methodologies can be readily developed to further assist in analyzing complex data that mix heterogeneous features. In this paper, we illustrate such capabilities in the context of different complex diagnostic and/or prognostic problems in tumor pathology relating to bladder, astrocytomas, and adipose tissues.

Nearest-neighbor classification for identification of aggressive versus nonaggressive low-grade astrocytic tumors by means of image cytometry-generated variables.

The authors investigated whether cytometry-related variables generated by means of computer-assisted microscopic analysis of Feulgen-stained nuclei can contribute significant information toward the characterization of low-grade astrocytic tumor aggressiveness. This investigation was conducted using the nearest-neighbor rule (a traditional classification method used in pattern recognition) to analyze a series of 250 supratentorial astrocytic tumors from adult patients. This series included 39 low-grade astrocytomas and 211 high-grade astrocytic tumors (including 47 anaplastic astrocytomas and 164 glioblastomas multiforme [GBMs]). The results show that the 3-nearest-neighbors rule enabled a subgroup of "atypical" astrocytomas to be distinguished from the "typical" tumors. The atypical astrocytoma species exhibited a DNA content (DNA ploidy level) and morphonuclear characteristics that were statistically more similar to the characteristics of GBMs than to those exhibited by the typical astrocytomas. An analysis of survival data revealed that patients with atypical astrocytomas survived for a significantly shorter period (p < 0.001) than patients with typical lesions of this kind. In fact, patients with atypical astrocytomas had a survival period similar to that of patients with anaplastic astrocytomas, whereas patients with typical astrocytomas had a survival period significantly longer (p < 0.0001) than those associated with anaplastic astrocytomas and GBMs.

Dynamic characterization of glioblastoma cell motility.

The cell motility dynamic of two glioblastoma cell lines (U373 and U87) was studied by means of an automatic video-cell-tracking-system enabling each cell in a colony to be tracked for several hours. Twenty-five experiments were performed on both models growing on three different supports (glass, plastic and Matrigel). Cell motility was significantly different in each cell line and also for different growth support in a given cell line. We observed that U87 cells are significantly (p < 0.00001) less motile than U373 cells. The most favorable growth supports for cell motility studies were Matrigel and glass. A significant (p < 0.001) correlation between cell colony density and cell motility was highlighted, with isolated cells exhibiting a motility level distinct from the one observed for colonies. The present methodology, which enabled cell motility to be quantified in human glioblastoma cells, represents an original tool for identifying new classes of compounds able to reduce glioblastoma cell motility and cell migration potential into the brain.

The computer-assisted microscope analysis of Feulgen-stained nuclei linked to a supervised learning algorithm as an aid to prognosis assessment in invasive transitional bladder cell carcinomas.

The aim of the present work is to ascertain whether additional information to grading and staging can be obtained for the prognosis of invasive bladder tumours (T2, T3, T4) by means of two computer-assisted methodologies. The first methodology relates to the digital image analysis of Feulgen-stained nuclei and the second to a supervised learning algorithm named Decision Tree. The digital image analysis of Feulgen-stained nuclei generated 11 variables for nuclear DNA content and 15 for quantitatively describing chromatin pattern. These 26 variables were submitted to a Decision Tree technique which produces multi-attribute logical classification rules by selecting informative variables and determining discriminatory values for each of them. A series of 41 patients for which the majority of the T2 bladder tumours (68%) were associated with a 'good' prognosis (remission) while the majority of the T3-T4 ones (77%) were associated with a 'bad' one (clinical progression or death) were submitted to the proposed approach. The results show that the decision tree was able to characterise the tumours associated with a 'bad' prognosis in the T2 sub-group (32%) and the tumours associated with a 'good' prognosis in the T3-T4 one (23%), by using only few image-generated variables (added to the clinical stage).

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.

The use of the decision tree technique and image cytometry to characterize aggressiveness in World Health Organization (WHO) grade II superficial transitional cell carcinomas of the bladder.

The aggressiveness of human bladder tumours can be assessed by means of various classification systems, including the one proposed by the World Health Organization (WHO). According to the WHO classification, three levels of malignancy are identified as grades I (low), II (intermediate), and III (high). This classification system operates satisfactorily for two of the three grades in forecasting clinical progression, most grade I tumours being associated with good prognoses and most grade III with bad. In contrast, the grade II group is very heterogeneous in terms of their clinical behaviour. The present study used two computer-assisted methods to investigate whether it is possible to sub-classify grade II tumours: computer-assisted microscope analysis (image cytometry) of Feulgen-stained nuclei and the Decision Tree Technique. This latter technique belongs to the Supervised Learning Algorithm and enables an objective assessment to be made of the diagnostic value associated with a given parameter. The combined use of these two methods in a series of 292 superficial transitional cell carcinomas shows that it is possible to identify one subgroup of grade II tumours which behave clinically like grade I tumours and a second subgroup which behaves clinically like grade III tumours. Of the nine ploidy-related parameters computed by means of image cytometry [the DNA index (DI), DNA histogram type (DHT), and the percentages of diploid, hyperdiploid, triploid, hypertriploid, tetraploid, hypertetraploid, and polyploid cell nuclei], it was the percentage of hyperdiploid and hypertetraploid cell nuclei which enabled identification, rather than conventional parameters such as the DI or the DHT.

Aneuploidy occurrence in human tumours: a logical-automaton approach.

The search for new, reliable factors of prognosis in cancerology is sadly deficient at the present moment. Of these factors, the measurement of ploidy gives rise to considerable hope. Nevertheless, despite the impressive number of papers currently published, no general law seems to be emerging that associates the ploidy rate of a tumour with its clinical evolution in a patient. The purpose of the present work is firstly to use a logical automation to describe the cell cycle in terms of binary variables (the validation of the methodology), and secondly to demonstrate that a certain 'cancer logic' can be distilled, at least with respect to the genesis of DNA histograms among tumours.