Avinash Bajaj

Rapid and effective differentiation between normal and cancer cells is an important challenge for the diagnosis and treatment of tumors. Here, we describe an array-based system for identification of normal and cancer cells based on a "chemical nose/tongue" approach that exploits subtle changes in the physicochemical nature of different cell surfaces. Their differential interactions with functionalized nanoparticles are transduced through displacement of a multivalent polymer fluorophore that is quenched when bound to the particle and fluorescent after release. Using this sensing strategy we can rapidly (minutes/seconds) and effectively distinguish (i) different cell types; (ii) normal, cancerous and metastatic human breast cells; and (iii) isogenic normal, cancerous and metastatic murine epithelial cell lines.

This feature article describes the recent developments in the design of cationic lipids and their applications in gene delivery. Various structure-activity investigations explaining the variations in gene transfection efficacies with respect to different molecular structures of the cationic lipids have been discussed. Gene transfer abilities are presented in relation to aggregation properties of different aqueous formulations such as cationic liposomes and surfactant aggregates from various amphiphiles and cationic lipids, as a function of their hydrophobic parts, linkers and head groups.

A family of conjugated fluorescent polymers was used to create an array for cell sensing. Fluorescent conjugated polymers with pendant charged residues provided multivalent interactions with cell membranes, allowing the detection of subtle differences between different cell types on the basis of cell surface features. Highly reproducible characteristic patterns were obtained from different cell types as well as from isogenic cell lines, enabling the identification of the cell type as well differentiating between normal, cancerous, and metastatic isogenic cell types with high accuracy.

Supramolecular complexes of a family of positively charged conjugated polymers (CPs) and green fluorescent protein (GFP) create a fluorescence resonance energy transfer (FRET)-based ratiometric biosensor array. Selective multivalent interactions of the CPs with mammalian cell surfaces caused differential change in FRET signals, providing a fingerprint signature for each cell type. The resulting fluorescence signatures allowed the identification of 16 different cell types and discrimination between healthy, cancerous, and metastatic cells, with the same genetic background. While the CP-GFP sensor array completely differentiated between the cell types, only partial classification was achieved for the CPs alone, validating the effectiveness of the ratiometric sensor. The utility of the biosensor was further demonstrated in the detection of blinded unknown samples, where 121 of 128 samples were correctly identified. Notably, this selectivity-based sensor stratified diverse cell types in minutes, using only 2000 cells, without requiring specific biomarkers or cell labeling.