Cell shape is a valuable indicator of cell health status and interactions with the extracellular materials. With the aim to investigate how individual cells respond to chemical microenvironments, we employed 2D monomolecular layers of small organic molecules, characterized by very low roughness. MCF10A cells were grown on these surfaces and characterized by using scanning electrochemical microscopy. The single cell morphologies were analyzed to define a "figure of merit" for the different cell-surface interactions. Such "figure of merit" quantifies the interaction with the microenvironment. This method is applicable to any cell state (metastatic, physiological or pathological) and any surface.The shape of cells changes according to their physiological status and the interactions established with the surface where they adhere. [1] Both surface structuration and surface functionalization drive cell morphology. [2,3] An understanding of the phenomena affecting its characteristics is strongly needed for several applications. [4] The assessment of cell status from a single cell shape can be a powerful diagnostic source to screen materials for nanoand bio-technological applications (implantable sensors and devices, materials for drug-delivery) and to investigate cell phenotype (e. g. metastatic cells versus normal cells). Confocal microscopy and super-resolution imaging can be applied to analyze cell shapes. In these methods, fluorescent stains or tags are required and even if there is an increasing interest in the synthesis and development of not toxic compounds, it is not trivial to mark the whole volume of the cell. Moreover, the photo-toxicity caused by the high-power lasers used for the excitation of the fluorescence cannot be avoided. Scanning electrochemical microscopy (SECM) allows for a tag free analysis in physiological conditions of cell morphologies. At the same time, SECM can be used to investigate the local reactivity of the substrates where the cells adhere.When dealing with single entities, a great deal of information can be acquired, including access to stochastic phenomena and to data regarding the heterogeneity and the statistics of the system. [5][6][7][8] Here we assess cell-surface interactions by investigating the morphology of individual cells imaged by SECM. The procedure consists in a "training" phase, during which several single cell conformations belonging to three different cell-surface interaction regimes were examined, to learn how to recognize a specific cell condition. The method is an example of "learning process" applied to single entity electrochemistry investigation.In order to train the system, we employed three different kinds of mono-molecular layers of small organic molecules grown on native SiO x . The selected organic materials can be prepared to form surfaces with extremely low roughness (ca. 2 Å ) that differ in chemical functionality. Specifically, Pentacene (P5), [9] a-Sexithiophene (6T) [10] and N,N'-bis(n-octyl)-dicyanoperylene-3,4 : 9,10-bis(dicarboximide) (PDI8-CN 2 ) ...