Epithelial to Mesenchymal Transition (EMT) is a multi-state process. Here, we investigated phenotypic state transition dynamics of Epidermal Growth Factor (EGF)-induced EMT in a breast cancer cell line MDA-MB-468. We have defined phenotypic states of these cells in terms of their morphologies and have shown that these cells have three distinct morphological states—cobble, spindle, and circular. The spindle and circular states are the migratory phenotypes. Using quantitative image analysis and mathematical modeling, we have deciphered state transition trajectories in different experimental conditions. This analysis shows that the phenotypic state transition during EGF-induced EMT in these cells is reversible, and depends upon the dose of EGF and level of phosphorylation of the EGF receptor (EGFR). The dominant reversible state transition trajectory in this system was cobble to circular to spindle to cobble. We have observed that there exists an ultrasensitive on/off switch involving phospho-EGFR that decides the transition of cells in and out of the circular state. In general, our observations can be explained by the conventional quasi-potential landscape model for phenotypic state transition. As an alternative to this model, we have proposed a simpler discretized energy-level model to explain the observed state transition dynamics.

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Summary The analysis of molecular signatures of antigen‐driven affinity selection of B cells is of immense use in studies on normal and abnormal B cell development. Most of the published literature compares the expected and observed frequencies of replacement (R) and silent (S) mutations in the complementarity‐determining regions (CDRs) and the framework regions (FRs) of antibody genes to identify the signature of antigenic selection. The basic assumption of this statistical method is that antigenic selection creates a bias for R mutations in the CDRs and for S mutations in the FRs. However, it has been argued that the differences in intrinsic mutability among different regions of an antibody gene can generate a statistically significant bias even in the absence of any antigenic selection. We have modified the existing statistical method to include the effects of intrinsic mutability of different regions of an antibody gene. We used this method to analyse sequences of several B cell‐derived monoclonals against T‐dependent antigens, T‐independent antigens, clones derived from lymphoma and amyloidogenic clones. Our sequence analysis indicates that even after correcting for the intrinsic mutability of antibody genes, statistical parameters fail to reflect the role of antigen‐driven affinity selection in maturation of many clones. We suggest that, contrary to the basic assumption of such statistical methods, selection can act both for and against R mutations in the CDR as well as in the FR regions. In addition we have identified different methodological difficulties in the current uses of such statistical analysis of antibody genes.

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