scholarly journals Robustness of Clonogenic Assays as a Biomarker for Cancer Cell Radiosensitivity

2019 ◽  
Vol 20 (17) ◽  
pp. 4148 ◽  
Author(s):  
Toshiaki Matsui ◽  
Endang Nuryadi ◽  
Shuichiro Komatsu ◽  
Yuka Hirota ◽  
Atsushi Shibata ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Cell Lines ◽  
Cancer Cell ◽  
Predictive Biomarkers ◽  
Photon Radiation ◽  
Published Data ◽  
Gold Standard Method ◽  
Clonogenic Assays ◽  
Survival Endpoints ◽  
Number Of Publications

Photon radiation therapy is a major curative treatment for cancer. However, the lack of robust predictive biomarkers for radiosensitivity precludes personalized radiation therapy. Clonogenic assays are the gold standard method for measuring the radiosensitivity of cancer cells. Although a large number of publications describe the use of clonogenic assays to measure cancer cell radiosensitivity, the robustness of results from different studies is unclear. To address this, we conducted a comprehensive detailed literature search of 256 common cancer cell lines and identified the eight cell lines most-frequently examined for photon sensitivity using clonogenic assays. Survival endpoints and experimental parameters from all 620 relevant experiments were compiled and analyzed. We found that the coefficients of variation for SF2 (surviving fraction after 2 Gy irradiation) and for D10 (dose that yields a surviving fraction of 10%) were below 30% for all cell lines, indicating that SF2 and D10 have acceptable inter-assay precision. These data support further analysis of published data on clonogenic assays using SF2 and D10 as survival endpoints, which facilitates robust identification of biological profiles representative of cancer cell sensitivity to photons.

scholarly journals Photon versus carbon ion irradiation: immunomodulatory effects exerted on murine tumor cell lines

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Laura Hartmann ◽  
Philipp Schröter ◽  
Wolfram Osen ◽  
Daniel Baumann ◽  
Rienk Offringa ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Ion Irradiation ◽  
Dose Range ◽  
Cancer Cell Line ◽  
Surface Expression ◽  
Photon Radiation ◽  
Immunomodulatory Effects ◽  
Carbon Ion ◽  
Dose Dependent

AbstractWhile for photon radiation hypofractionation has been reported to induce enhanced immunomodulatory effects, little is known about the immunomodulatory potential of carbon ion radiotherapy (CIRT). We thus compared the radio-immunogenic effects of photon and carbon ion irradiation on two murine cancer cell lines of different tumor entities. We first calculated the biological equivalent doses of carbon ions corresponding to photon doses of 1, 3, 5, and 10 Gy of the murine breast cancer cell line EO771 and the OVA-expressing pancreatic cancer cell line PDA30364/OVA by clonogenic survival assays. We compared the potential of photon and carbon ion radiation to induce cell cycle arrest, altered surface expression of immunomodulatory molecules and changes in the susceptibility of cancer cells to cytotoxic T cell (CTL) mediated killing. Irradiation induced a dose-dependent G2/M arrest in both cell lines irrespective from the irradiation source applied. Likewise, surface expression of the immunomodulatory molecules PD-L1, CD73, H2-Db and H2-Kb was increased in a dose-dependent manner. Both radiation modalities enhanced the susceptibility of tumor cells to CTL lysis, which was more pronounced in EO771/Luci/OVA cells than in PDA30364/OVA cells. Overall, compared to photon radiation, the effects of carbon ion radiation appeared to be enhanced at higher dose range for EO771 cells and extenuated at lower dose range for PDA30364/OVA cells. Our data show for the first time that equivalent doses of carbon ion and photon irradiation exert similar immunomodulating effects on the cell lines of both tumor entities, highlighted by an enhanced susceptibility to CTL mediated cytolysis in vitro.

scholarly journals Synergy between Non-Thermal Plasma with Radiation Therapy and Olaparib in a Panel of Breast Cancer Cell Lines

Cancers ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 348 ◽  
Author(s):  
Julie Lafontaine ◽  
Jean-Sébastien Boisvert ◽  
Audrey Glory ◽  
Sylvain Coulombe ◽  
Philip Wong
Keyword(s):  
Breast Cancer ◽  
Radiation Therapy ◽  
Synergistic Effect ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Thermal Plasma ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines ◽  
Non Thermal Plasma

Cancer therapy has evolved to a more targeted approach and often involves drug combinations to achieve better response rates. Non-thermal plasma (NTP), a technology rapidly expanding its application in the medical field, is a near room temperature ionized gas capable of producing reactive species, and can induce cancer cell death both in vitro and in vivo. Here, we used proliferation assay to characterize the plasma sensitivity of fourteen breast cancer cell lines. These assays showed that all tested cell lines were sensitive to NTP. In addition, a good correlation was found comparing cell sensitivity to NTP and radiation therapy (RT), where cells that were sensitive to RT were also sensitive to plasma. Moreover, in some breast cancer cell lines, NTP and RT have a synergistic effect. Adding a dose of PARP-inhibitor olaparib to NTP treatment always increases the efficacy of the treatment. Olaparib also exhibits a synergistic effect with NTP, especially in triple negative breast cancer cells. Results presented here help elucidate the position of plasma use as a potential breast cancer treatment.

MicroRNAs related to intrinsic resistance to oxaliplatin and the irinotecan metabolite SN-38 in 10 colorectal cancer cell lines.

2012 ◽  
Vol 30 (4_suppl) ◽  
pp. 524-524 ◽  
Author(s):  
Niels Frank Jensen ◽  
Rolf Soekilde ◽  
Jan Stenvang ◽  
Birgitte Sander Nielsen ◽  
Thomas Litman ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Drug Sensitivity ◽  
Predictive Biomarkers ◽  
Cancer Cell Lines ◽  
Colorectal Cancer Cell ◽  
Intrinsic Resistance ◽  
Short Term ◽  
Colorectal Cancer Cell Lines

524 Background: Chemotherapy of metastatic colorectal cancer is based on 5-flourouracil combined with either oxaliplatin or irinotecan (active metabolite: SN-38). Identification of predictive biomarkers of drug response is needed to provide a better personalized treatment. In this study we aimed to identify microRNAs related to intrinsic resistance to oxaliplatin or irinotecan in a panel of ten colorectal cancer cell lines. Methods: Drug sensitivity towards oxaliplatin and SN-38 was determined for ten colorectal cancer cell lines (Colo-205, DLD-1, HCC-2998, HCT-15, HCT-116, HT-29, KM12, LoVo, LS-174T, and SW620), using the cell viability MTT assay and the cell death LDH assay. In addition, two cell lines (DLD-1 and LoVo) were exposed to the drugs for 6, 24 or 48 hours. MicroRNA expression profiles were generated using the Exiqon miRCURY LNA microarray platform (including 840 microRNAs), and four differentially expressed microRNAs were validated by independent qRT-PCR measurements. Results: The drug sensitivities of the ten colorectal cancer cell lines varied about 50 times between the least and most sensitive cell lines. Correlation of drug sensitivity data to microRNA expression data across the ten cell lines yielded about 25 microRNA biomarker candidates, for each of the drug/assay combinations. Following short-term drug treatment 10-20 microRNAs were altered for each drug/cell line combination. Validation by qRT-PCR showed a very good correlation to the microarray data. MicroRNAs identified by correlation to drug sensitivity and by short-term treatment were compared, and less than 10% were identified by both approaches, perhaps representing the most promising candidates. These candidates are for SN-38 miR-15a, miR-22, miR-24, miR-98, miR-142-3p, miR-1290, and let-7b, and for oxaliplatin miR-23b, miR-27a, miR-192, miR-200a, miR-222, miR-886-5p, and miR-1308. Conclusions: In the present study we identified a number of microRNAs that are potentially involved in intrinsic resistance and/or could be predictive biomarkers for either irinotecan or oxaliplatin.

scholarly journals SYNERGxDB: an integrative pharmacogenomic portal to identify synergistic drug combinations for precision oncology

2020 ◽  
Vol 48 (W1) ◽  
pp. W494-W501 ◽  
Author(s):  
Heewon Seo ◽  
Denis Tkachuk ◽  
Chantal Ho ◽  
Anthony Mammoliti ◽  
Aria Rezaie ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Drug Combination ◽  
Predictive Biomarkers ◽  
Cancer Cell Lines ◽  
Drug Combinations ◽  
Drug Synergism ◽  
Precision Oncology ◽  
Synergistic Drug Combinations ◽  
Pharmacological Profiles

Abstract Drug-combination data portals have recently been introduced to mine huge amounts of pharmacological data with the aim of improving current chemotherapy strategies. However, these portals have only been investigated for isolated datasets, and molecular profiles of cancer cell lines are lacking. Here we developed a cloud-based pharmacogenomics portal called SYNERGxDB (http://SYNERGxDB.ca/) that integrates multiple high-throughput drug-combination studies with molecular and pharmacological profiles of a large panel of cancer cell lines. This portal enables the identification of synergistic drug combinations through harmonization and unified computational analysis. We integrated nine of the largest drug combination datasets from both academic groups and pharmaceutical companies, resulting in 22 507 unique drug combinations (1977 unique compounds) screened against 151 cancer cell lines. This data compendium includes metabolomics, gene expression, copy number and mutation profiles of the cancer cell lines. In addition, SYNERGxDB provides analytical tools to discover effective therapeutic combinations and predictive biomarkers across cancer, including specific types. Combining molecular and pharmacological profiles, we systematically explored the large space of univariate predictors of drug synergism. SYNERGxDB constitutes a comprehensive resource that opens new avenues of research for exploring the mechanism of action for drug synergy with the potential of identifying new treatment strategies for cancer patients.

Sign in / Sign up

Export Citation Format

Share Document