Nano-Motion Analysis for Rapid and Label Free Assessing of Cancer Cell Sensitivity to Chemotherapeutics.

Background and Objectives: Optimization of chemotherapy is crucial for cancer patients. Timely and costly efficient treatments are emerging due to the increasing incidence of cancer worldwide. Here, we present a methodology of nano-motion analysis that could be developed to serve as a screening tool able to determine the best chemotherapy option for a particular patient within hours. Materials and Methods: Three different human cancer cell lines and their multidrug resistant (MDR) counterparts were analyzed with an atomic force microscope (AFM) using tipless cantilevers to adhere the cells and monitor their nano-motions. Results: The cells exposed to doxorubicin (DOX) differentially responded due to their sensitivity to this chemotherapeutic. The death of sensitive cells corresponding to the drop in signal variance occurred in less than 2 h after DOX application, while MDR cells continued to move, even showing an increase in signal variance. Conclusions: Nano-motion sensing can be developed as a screening tool that will allow simple, inexpensive and quick testing of different chemotherapeutics for each cancer patient. Further investigations on patient-derived tumor cells should confirm the method's applicability

Molecular and phenotypic characteristics of patients with phenylketonuria in Serbia and Montenegro

Phenylketonuria (PKU) is the most common inborn error of amino acid metabolism in Caucasians. PKU is caused by mutations in the gene encoding phenylalanine hydroxylase (PAH) enzyme. Here, we report the spectrum and the frequency of mutations in the PAH gene and discuss genotype-phenotype correlation in 34 unrelated patients with PKU from Serbia and Montenegro. Using both polymerase chain reaction-restriction fragment length polymorphism and 'broad-range' denaturing-gradient gel electrophoresis/DNA sequencing analysis, 19 disease-causing mutations were identified, corresponding to mutation detection rate of 97%. The most frequent ones were L48S (21%), R408W (18%), P281L (9%), E390G (7%) and R261Q (6%), accounting for 60% of all mutant alleles. The genotype-phenotype correlation was studied in homozygous and functionally hemizygous patients. We found that the most frequent mutation, L48S, was exclusively associated with the classical (severe) PKU phenotype. The mutation E390G gave rise to mild PKU. For the mutation R261Q, patients had been recorded in two phenotype categories. Considering allele frequencies, PKU in Serbia and Montenegro is heterogeneous, reflecting numerous migrations over the Balkan Peninsula