Human lung-cancer-cell radioresistance investigated through 2D network topology.

Radiation therapy (RT) is now considered to be a main component of cancer therapy, alongside surgery, chemotherapy and monoclonal antibody-based immunotherapy. In RT, cancer tissues are exposed to ionizing radiation causing the death of malignant cells and favoring cancer regression. However, the efficiency of RT may be hampered by cell-radioresistance (RR)-that is a feature of tumor cells of withstanding RT. To improve the RT performance, it is decisive developing methods that can help to quantify cell sensitivity to radiation. In acknowledgment of the fact that none of the existing methods to assess RR are based on cell graphs topology, in this work we have examined how 2D cell networks, within a single colony, from different human lung cancer lines (H460, A549 and Calu-1) behave in response to doses of ionizing radiation ranging from 0 to 8 Gy. We measured the structure of resulting cell-graphs using well-assessed networks-analysis metrics, such as the clustering coefficient (cc), the characteristic path length (cpl), and the small world coefficient (SW). Findings of the work illustrate that the clustering characteristics of cell-networks show a marked sensitivity to the dose and cell line. Higher-than-one values of SW coefficient, clue of a discontinuous and inhomogeneous cell spatial layout, are associated to elevated levels of radiation and to a lower radio-resistance of the treated cell line. Results of the work suggest that topology could be used as a quantitative parameter to assess the cell radio-resistance and measure the performance of cancer radiotherapy.