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Sanja Mijatović, Milica Pešić, Marija Mojić, Jasna Banković, Đorde Miljković, Paolo Fagone, Katia Mangano, Ferdinando Nicoletti, James McCubrey, Nikola Tanić and Danijela Maksimović-Ivanić

Summary

Background: The NO-modified form of the HIV inhibitor saquinavir (Saq-NO) inhibited the growth of a variety of can- cer cell lines in vitro and in vivo more potently than the orig- inal compound in a nontoxic fashion. In addition, chemo- and immunosensitizing properties were observed. The aim of the present study was to evaluate its anticancer action against non-small cell lung carcinoma cells in their doxoru- bicin (DOXO) sensitive and resistant phenotype (NCI-H460 and NCI-H460/R).

Methods: The viability of cells was analyzed by MTT and crystal violet assays. DR5 expression was estimated by real time RT-PCR and flow cytometry. Activity of P-glycoprotein (P-gp) pumps was evaluated by the Rho123 accumulation assay.

Results: Saq-NO diminished the viability of lung cancer cells through induction of cell cycle arrest in the Gq/G1 phase in- dependently of the overexpression of the P-gp pumps. In addition, Saq-NO elevated or completely reconstituted the doxorubicin efficacy in NCI-H460 and NCI-H460/R, respec- tively. The chemosensitizing effect in DOXO resistant cells was a consequence of P-gp inhibition which was found to be more potent than that observed with dex-verapamil, a con- ventional inhibitor of P-gp. Sensitization to DOXO upon Saq- NO was accompanied by elevated DR5 expression, but the resistance to TRAIL was not abrogated.

Conclusions: The NO-modified HIV inhibitor saquinavir dis- played equal antiproliferative and chemosensitizing proper- ties in DOXO sensitive and resistant non-small cell lung car- cinoma cells, suggesting the importance of the evaluation of this drug as an antineoplastic agent.

Open access

Miodrag Dragoj, Jasna Bankovic, Ana Podolski-Renic, Sonja Stojkovic Buric, Milica Pesic, Nikola Tanic and Tijana Stankovic

Summary

Background: C-Myc is one of the major cellular oncogenes overexpressed in non-small cell lung carcinoma (NSCLC). Its deregulated expression is necessary but not sufficient for malignant transformation. We evaluated expression of MYC gene in NSCLC patients and its association with alterations in the genes previously identified to be related to NSCLC pathogenesis, PHACTR3 and E2F4.

Methods: We analyzed MYC gene expression by qRT-PCR in 30 NSCLC patients’ samples and paired normal lung tissue. MYC expression was further statistically evaluated in relation to histopathological parameters, PHACTR3 and E2F4 gene alterations and survival. Alterations in aforementioned genes were previously detected and identified based on AP-PCR profiles of paired normal and tumor DNA samples, selection of DNA bands with altered mobility in tumor samples and their characterization by the reamplification, cloning and sequencing.

Results: MYC expression was significantly increased in NSCLC samples and its overexpression significantly associated with squamous cell carcinoma subtype. Most importantly, MYC overexpression significantly coincided with mutations in PHACTR3 and E2F4 genes, in group of all patients and in squamous cell carcinoma subtype. Moreover, patients with jointly overexpressed MYC and altered PHACTR3 or E2F4 showed trend of shorter survival.

Conclusions: Overall, MYC is frequently overexpressed in NSCLC and it is associated with mutated PHACTR3 gene, as well as mutated E2F4 gene. These joint gene alterations could be considered as potential molecular markers of NSCLC and its specific subtypes.

Open access

Víctor M. Pérez-García, Susan Fitzpatrick, Luis A. Pérez-Romasanta, Milica Pesic, Philippe Schucht, Estanislao Arana and Pilar Sánchez-Gómez

Abstract

Applied mathematics and nonlinear sciences have an enormous potential for application in cancer. Mathematical models can be used to raise novel hypotheses to test, develop optimized treatment schedules and personalize therapies. However. this potential is yet to be proven in real-world applications to specific cancer types. In this paper we discuss how we think mathematical knowledge may be better used to improve cancer patients’ outcome.