Inter-assay precision of clonogenic assays for radiosensitivity in cancer cell line A549

Modelling radiobiology

Radiotherapy has played an essential role in cancer treatment for over a century, and remains one of the best-studied methods of cancer treatment. Because of its close links with the physical sciences, it has been the subject of extensive quantitative mathematical modelling, but a complete understanding of the mechanisms of radiotherapy has remained elusive. In part this is because of the complexity and range of scales involved in radiotherapy-from physical radiation interactions occurring over nanometres to evolution of patient responses over months and years. This review presents the current status and ongoing research in modelling radiotherapy responses across these scales, including basic physical mechanisms of DNA damage, the immediate biological responses this triggers, and genetic- and patient-level determinants of response. Finally, some of the major challenges in this field and potential avenues for future improvements are also discussed.

Protective effect of avicularin against lung cancer via inhibiting inflammation, oxidative stress, and induction of apoptosis: an in vitro and in vivo study

The purpose of this research was to investigate whether or not avicularin (AVL) possesses any anticancer properties when tested against lung cancer. In the beginning, the effect that it had on the cellular viability of A549 cells was investigated, and it was discovered that AVL has a considerable negative impact on cellular viability. Following that, an investigation using flow cytometry was carried out to investigate its function in the process of apoptosis and the cell cycle of A549 cells. It has been discovered that AVL significantly promotes apoptosis and stops the cell cycle at the G2/M phase. The colony-forming capacity of A549 cells was observed to be greatly suppressed as the AVL concentration increased compared to the group that received no treatment. In addition to this, the benzo(a)pyrene in vivo model was established in order to investigate the pharmacological value of AVL. The findings revealed that AVL greatly prevented the formation of pro-inflammatory cytokines, in addition to the reduction in oxidative stress, which was evidenced by a reduction in the concentration of TNF-α, IL-1β, IL-6, and MDA with an improvement in the concentration of SOD and GPx, respectively. Our results successfully demonstrated the pharmacological benefit of avicularin against lung cancer, and it has been suggested that it showed a multifactorial effect.

A time-resolved clonogenic assay for improved cell survival and RBE measurements

Purpose

The in vitro clonogenic assay (IVCA) is the mainstay of quantitative radiobiology. Here, we investigate the benefit of a time-resolved IVCA version (trIVCA) to improve the quantification of clonogenic survival and relative biological effectiveness (RBE) by analyzing cell colony growth behavior.

Materials & Methods

In the IVCA, clonogenicity classification of cell colonies is performed based on a fixed colony size threshold after incubation. In contrast, using trIVCA, we acquire time-lapse microscopy images during incubation and track the growth of each colony using neural-net-based image segmentation. Attributes of the resulting growth curves are then used as predictors for a decision tree classifier to determine clonogenicity of each colony. The method was applied to three cell lines, each irradiated with 250 kV X-rays in the range 0-8 Gy and carbon ions of high LET (100 keV/μm, dose-averaged) in the range 0-2 Gy. We compared the cell survival curves determined by trIVCA to those from the classical IVCA across different size thresholds and incubation times. Further, we investigated the impact of the assaying method on RBE determination.

Results

Size distributions of abortive and clonogenic colonies overlap consistently, rendering perfect separation via size threshold unfeasible at any readout time. This effect is dose-dependent, systematically inflating the steepness and curvature of cell survival curves. Consequently, resulting cell survival estimates show variability between 3% and 105%. This uncertainty propagates into RBE calculation with variability between 8% and 25% at 2 Gy.Determining clonogenicity based on growth curves has an accuracy of 95% on average.

Conclusion

The IVCA suffers from substantial uncertainty caused by the overlap of size distributions of delayed abortive and clonogenic colonies. This impairs precise quantification of cell survival and RBE. By considering colony growth over time, our method improves assaying clonogenicity.

Validation of In Vitro Trained Transcriptomic Radiosensitivity Signatures in Clinical Cohorts

Transcriptomic personalisation of radiation therapy has gained considerable interest in recent years. However, independent model testing on in vitro data has shown poor performance. In this work, we assess the reproducibility in clinical applications of radiosensitivity signatures. Agreement between radiosensitivity predictions from published signatures using different microarray normalization methods was assessed. Control signatures developed from resampled in vitro data were benchmarked in clinical cohorts. Survival analysis was performed using each gene in the clinical transcriptomic data, and gene set enrichment analysis was used to determine pathways related to model performance in predicting survival and recurrence. The normalisation approach impacted calculated radiosensitivity index (RSI) values. Indeed, the limits of agreement exceeded 20% with different normalisation approaches. No published signature significantly improved on the resampled controls for prediction of clinical outcomes. Functional annotation of gene models suggested that many overlapping biological processes are associated with cancer outcomes in RT treated and non-RT treated patients, including proliferation and immune responses. In summary, different normalisation methods should not be used interchangeably. The utility of published signatures remains unclear given the large proportion of genes relating to cancer outcome. Biological processes influencing outcome overlapped for patients treated with or without radiation suggest that existing signatures may lack specificity.

Characterization of Intrinsic Radiation Sensitivity in a Diverse Panel of Normal, Cancerous and CRISPR-Modified Cell Lines

Intrinsic radiosensitivity is a major determinant of radiation response. Despite the extensive amount of radiobiological data available, variability among different studies makes it very difficult to produce high-quality radiosensitivity biomarkers or predictive models. Here, we characterize a panel of 27 human cell lines, including those derived from lung cancer, prostate cancer, and normal tissues. In addition, we used CRISPR-Cas9 to generate a panel of lines with known DNA repair defects. These cells were characterised by measuring a range of biological features, including the induction and repair of DNA double-strand breaks (DSBs), cell cycle distribution, ploidy, and clonogenic survival following X-ray irradiation. These results offer a robust dataset without inter-experimental variabilities for model development. In addition, we used these results to explore correlations between potential determinants of radiosensitivity. There was a wide variation in the intrinsic radiosensitivity of cell lines, with cell line Mean Inactivation Doses (MID) ranging from 1.3 to 3.4 Gy for cell lines, and as low as 0.65 Gy in Lig4^-/- cells. Similar substantial variability was seen in the other parameters, including baseline DNA damage, plating efficiency, and ploidy. In the CRISPR-modified cell lines, residual DSBs were good predictors of cell survival (R² = 0.78, p = 0.009), as were induced levels of DSBs (R² = 0.61, p = 0.01). However, amongst the normal and cancerous cells, none of the measured parameters correlated strongly with MID (R² < 0.45), and the only metrics with statistically significant associations are plating efficiency (R² = 0.31, p = 0.01) and percentage of cell in S phase (R² = 0.37, p = 0.005). While these data provide a valuable dataset for the modelling of radiobiological responses, the differences in the predictive power of residual DSBs between CRISPR-modified and other subgroups suggest that genetic alterations in other pathways, such as proliferation and metabolism, may have a greater impact on cellular radiation response. These pathways are often neglected in response modelling and should be considered in the future.

Human Cancer Cell Radiation Response Investigated through Topological Analysis of 2D Cell Networks

Clonogenic assays are routinely used to evaluate the response of cancer cells to external radiation fields, assess their radioresistance and radiosensitivity, estimate the performance of radiotherapy. However, classic clonogenic tests focus on the number of colonies forming on a substrate upon exposure to ionizing radiation, and disregard other important characteristics of cells such their ability to generate structures with a certain shape. The radioresistance and radiosensitivity of cancer cells may depend less on the number of cells in a colony and more on the way cells interact to form complex networks. In this study, we have examined whether the topology of 2D cancer-cell graphs is influenced by ionizing radiation. We subjected different cancer cell lines, i.e. H4 epithelial neuroglioma cells, H460 lung cancer cells, PC3 bone metastasis of grade IV of prostate cancer and T24 urinary bladder cancer cells, cultured on planar surfaces, to increasing photon radiation levels up to 6 Gy. Fluorescence images of samples were then processed to determine the topological parameters of the cell-graphs developing over time. We found that the larger the dose, the less uniform the distribution of cells on the substrate-evidenced by high values of small-world coefficient (cc), high values of clustering coefficient (cc), and small values of characteristic path length (cpl). For all considered cell lines, [Formula: see text] for doses higher or equal to 4 Gy, while the sensitivity to the dose varied for different cell lines: T24 cells seem more distinctly affected by the radiation, followed by the H4, H460 and PC3 cells. Results of the work reinforce the view that the characteristics of cancer cells and their response to radiotherapy can be determined by examining their collective behavior-encoded in a few topological parameters-as an alternative to classical clonogenic assays.

RadSigBench: a framework for benchmarking functional genomics signatures of cancer cell radiosensitivity

Multiple transcriptomic predictors of tumour cell radiosensitivity (RS) have been proposed, but they have not been benchmarked against one another or to control models. To address this, we present RadSigBench, a comprehensive benchmarking framework for RS signatures. The approach compares candidate models to those developed from randomly resampled control signatures and from cellular processes integral to the radiation response. Robust evaluation of signature accuracy, both overall and for individual tissues, is performed. The NCI60 and Cancer Cell Line Encyclopaedia datasets are integrated into our workflow. Prediction of two measures of RS is assessed: survival fraction after 2 Gy and mean inactivation dose. We apply the RadSigBench framework to seven prominent published signatures of radiation sensitivity and test for equivalence to control signatures. The mean out-of-sample R2 for the published models on test data was very poor at 0.01 (range: -0.05 to 0.09) for Cancer Cell Line Encyclopedia and 0.00 (range: -0.19 to 0.19) in the NCI60 data. The accuracy of both published and cellular process signatures investigated was equivalent to the resampled controls, suggesting that these signatures contain limited radiation-specific information. Enhanced modelling strategies are needed for effective prediction of intrinsic RS to inform clinical treatment regimes. We make recommendations for methodological improvements, for example the inclusion of perturbation data, multiomics, advanced machine learning and mechanistic modelling. Our validation framework provides for robust performance assessment of ongoing developments in intrinsic RS prediction.

Six-well plate-based colony-forming efficacy assay and Co-Culture application to assess toxicity of metal oxide nanoparticles

The development of a universal, label-free, and reliable in vitro toxicity testing method for nanoparticles is urgent because most nanoparticles can interfere with toxicity assays. In this regard, the colony-forming efficacy (CFE) assay has been suggested as a suitable in vitro toxicity assay for testing nanoparticles without such interference. Recently, the Organisation for Economic Co-operation and Development (OECD) developed a 60 × 15 mm Petri dish-based CFE assay for testing nanoparticles in MDCK-1 cells. However, further investigations are needed, including testing with other cell types, at a smaller scale for greater efficiency, and the application of the co-culture technique. In this study, we selected TiO₂, CuO, CeO₂, and SiO₂ as test nanoparticles and successfully developed a 6-well plate-based CFE assay using HepG2 and A549 cells and a co-culture assay for combinations of HepG2 cells and THP-1 macrophages or A549 cells and THP-1 monocytes. The results suggest that the 6-wellplate-based CFE assay for HepG2 and A549 cells can be applied to nanoparticles, but the co-culture CFE assay has limitations in that it is not different from the single culture study, and it inhibits colony-formation by A549 cells in the presence of macrophages; this warrant further study.

Analysis of clonogenic growth in vitro

The clonogenic assay measures the capacity of single cells to form colonies in vitro. It is widely used to identify and quantify self-renewing mammalian cells derived from in vitro cultures as well as from ex vivo tissue preparations of different origins. Varying research questions and the heterogeneous growth requirements of individual cell model systems led to the development of several assay principles and formats that differ with regard to their conceptual setup, 2D or 3D culture conditions, optional cytotoxic treatments and subsequent mathematical analysis. The protocol presented here is based on the initial clonogenic assay protocol as developed by Puck and Marcus more than 60 years ago. It updates and extends the 2006 Nature Protocols article by Franken et al. It discusses different strategies and principles to analyze clonogenic growth in vitro and presents the clonogenic assay in a modular protocol framework enabling a diversity of formats and measures to optimize determination of clonogenic growth parameters. We put particular focus on the phenomenon of cellular cooperation and consideration of how this can affect the mathematical analysis of survival data. This protocol is applicable to any mammalian cell model system from which single-cell suspensions can be prepared and which contains at least a small fraction of cells with self-renewing capacity in vitro. Depending on the cell system used, the entire procedure takes ~2-10 weeks, with a total hands-on time of <20 h per biological replicate.

Characterization of a custom-made 241Am alpha-source for radiobiological studies

A compact in-house alpha particle source has been developed and fully characterized. The irradiation source is a large area, 25 cm², 5.4 MeV average energy ²⁴¹Am source, above which a Mylar dish containing a monolayer of target cells can be placed at defined positions. The source uniformity, flux, particle energy and dose rate were determined experimentally. The dose rate to the nucleus at the closest position was 1.57 Gy/min. Furthermore, a 3D printed collimator was tested and found to improve the uniformity of the energy spectra of particles reaching the target. For validation, prostate PC-3 cells were irradiated in our experimental setup with absorbed doses up to 2 Gy and for reference compared with cells irradiated with conventional X-rays with doses up to 8 Gy. The Relative Biological Effectiveness for alpha particles at 10% survival was 3.66± 0.40 agreeing with previously published data. Data presented here show the feasibility of utilising a low-cost alpha-irradiation source for accurate in vitro assays to better understand the radiobiological effects of high LET alpha particles.

A Mechanistic DNA Repair and Survival Model (Medras): Applications to Intrinsic Radiosensitivity, Relative Biological Effectiveness and Dose-Rate

Variations in the intrinsic radiosensitivity of different cells to ionizing radiation is now widely believed to be a significant driver in differences in response to radiotherapy. While the mechanisms of radiosensitivity have been extensively studied in the laboratory, there are a lack of models which integrate this knowledge into a predictive framework. This paper presents an overview of the Medras model, which has been developed to provide a mechanistic framework in which different radiation responses can be modelled and individual responses predicted. This model simulates the repair of radiation-induced DNA damage, incorporating the overall kinetics of repair and its fidelity, to predict a range of biological endpoints including residual DNA damage, mutation, chromosome aberration, and cell death. Validation of this model against a range of exposure types is presented, including considerations of varying radiation qualities and dose-rates. This approach has the potential to inform new tools to deliver mechanistic predictions of radiation sensitivity, and support future developments in treatment personalization.

PARP Inhibitors Talazoparib and Niraparib Sensitize Melanoma Cells to Ionizing Radiation

(1) Background: Niraparib and Talazoparib are poly (ADP-ribose) polymerase (PARP) 1/2 inhibitors. It is assumed that combining PARP inhibitors with radiotherapy could be beneficial for cancer treatment. In this study, melanoma cells were treated with Niraparib and Talazoparib in combination with ionizing radiation (IR). (2) Methods: The effects of Talazoparib and Niraparib in combination with IR on cell death, clonogenicity and cell cycle arrest were studied in healthy primary fibroblasts and primary melanoma cells. (3) Results: The melanoma cells had a higher PARP1 and PARP2 content than the healthy fibroblasts, and further increased their PARP2 content after the combination therapy. PARP inhibitors both sensitized fibroblasts and melanoma cells to IR. A clear supra-additive effect of KI+IR treatment was detected in two melanoma cell lines analyzing the surviving fraction. The cell death rate increased in the healthy fibroblasts, but to a larger extent in melanoma cells after combined treatment. Finally, a lower percentage of cells in the radiosensitive G2/M phase is present in the healthy fibroblasts compared to the melanoma cells. (4) Conclusions: Both PARP inhibitors sensitize melanoma cells to IR. Healthy tissue seems to be less affected than melanoma cells. However, the great heterogeneity of the results suggests prior testing of the tumor cells in order to personalize the treatment.

Fatty acid composition, enzyme inhibitory effect, antioxidant and anticancer activity of extract from Saponaria prostrata WILLD. subsp. anatolica HEDGE

This study attempts to evaluate the antioxidant, enzyme inhibitory, and anticancer properties as well as fatty acid compositions of endemic Saponaria prostrata WILLD. subsp. anatolica HEDGE. The gas chromatography-mass spectrometry (GC-MS) was used to determine the fatty acid content of methanol: dichloromethane extract from S. prostrata subsp. anatolica (SPA). Enzymatic activity was measured against acetylcholinesterase, butyrylcholinesterase and α-glucosidase. DPPH (2,2-diphenyl-1-picrylhydrazyl) free radical scavenging activity and Ferric reducing antioxidant power assay (FRAP) were conducted to antioxidant properties. The anticancer effect of SPA on human MCF-7 breast cancer and human HCT116 colorectal cancer cell line was evaluated by WST-1 cell viability assay, colony formation assay and wound healing assay. In addition, human VEGF Elisa method was used to determine the anti-angiogenic effect, and the quantitative real-time PCR (qRT-PCR) method on p53, Bax and Bcl-2 mRNA levels were used to evaluate apoptosis. While high amounts of palmitic acid (40.8%), linoleic acid (17.75%) and α-linolenic acid (16.84%) were detected in the SPA, the total amount of unsaturated fatty acid (51.34%) was higher than the total amount of saturated fatty acid (48.66%). SPA displayed the most promising acetylcholinesterase (AChE), butyrylcholinesterase (BuChE) and α-glycosidase (AG) inhibitory activities (AChE: IC₅₀: 18.03 µg/mL, BuChE: IC₅₀: 44.24 µg/mL and AG: IC₅₀: 210.85 µg/mL). The half maximum inhibitory concentration (IC₅₀) of SPA in MCF-7 and HCT116 cells was determined as 259.79 µg/mL and 97.24 µg/mL, respectively. In addition, it was determined that SPA suppresses colony formation and wound closure, and suppresses angiogenesis as well as triggering apoptosis at a significant level. It is true that endemic S. prostrata subsp. anatolica is a potential source of functional food ingredients, but more analytical and in vivo experiments are needed to explore further secondary metabolite diversity and pharmacological properties.

Rapid advancement in cancer genomic big data in the pursuit of precision oncology

In the current big data era, massive genomic cancer data are available for open access from anywhere in the world. They are obtained from popular platforms, such as The Cancer Genome Atlas, which provides genetic information from clinical samples, and Cancer Cell Line Encyclopedia, which offers genomic data of cancer cell lines. For convenient analysis, user-friendly tools, such as the Tumor Immune Estimation Resource (TIMER), which can be used to analyze tumor-infiltrating immune cells comprehensively, are also emerging. In clinical practice, clinical sequencing has been recommended for patients with cancer in many countries. Despite its many challenges, it enables the application of precision medicine, especially in medical oncology. In this review, several efforts devoted to accomplishing precision oncology and applying big data for use in Indonesia are discussed. Utilizing open access genomic data in writing research articles is also described.

Preparation of Celery Essential Oil-Based Nanoemulsion by Ultrasonication and Evaluation of Its Potential Anticancer and Antibacterial Activity

Introduction

Plants have always been a significant source of natural active components with biological properties. Celery seed oil (extracted from Apium graveolens) has several potential applications, but its therapeutic uses in the form of nanoemulsion formulation need to be investigated further in order to meet the demand in cancer treatment, and to alleviate the prevailing crisis arising from increased antimicrobial resistance.

Methods

The therapeutic potential of celery seed oil was investigated through the formulation and testing of a nanoemulsion developed with Tween 80 (a non-ionic surfactant) and the utilization of an ultrasonication technique. Anticancer and apoptotic properties of the formulation were evaluated through MTT and Annexin V-FITC assays. The clonogenic assay aided in the identification of the antiproliferative properties of the formulation on oral squamous cell carcinoma. The antimicrobial study was supported by agar well diffusion assay, membrane integrity test and scanning electron microscopy.

Results

Experiments identified relevant parameters, including optimal surfactant concentration and emulsification time. GC-MS analysis identified various components in the celery oil, but not their biological activities. A sonication time of 20 min resulted in a droplet diameter of 23.4 ± 1.80 nm. The IC₅₀ concentration of the optimal nanoemulsion formulation against SAS cells was 1.4 µL/mL. At this concentration, cell proliferation was significantly reduced through inhibition of the anchorage-independent cell growth by disrupting colony formation and inducing cell death (apoptosis) of cancer cells. The nanoemulsion was also treated with a microbial suspension of S. aureus, and displayed antibacterial properties through lipid membrane fusion, causing cytoplasmic leakage as verified through agar well diffusion and membrane permeability assays. Scanning electron microscopy revealed complete distortion of the bacterial pathogen.

Conclusion

The results in this study present celery as a possible constituent for cancer therapeutics and as a candidate for aggressive, yet safe cancer treatment. The celery-based nanoemulsion has the potential to act as a key alternative to standard antibiotic therapy.

The clonogenic assay: robustness of plating efficiency-based analysis is strongly compromised by cellular cooperation

BACKGROUND

The clonogenic assay is a versatile and frequently used tool to quantify reproductive cell survival in vitro. Current state-of-the-art analysis relies on plating efficiency-based calculations which assume a linear correlation between the number of cells seeded and the number of colonies counted. The present study was designed to test the validity of this assumption and to evaluate the robustness of clonogenic survival results obtained.

METHODS

A panel of 50 established cancer cell lines was used for comprehensive evaluation of the clonogenic assay procedure and data analysis. We assessed the performance of plating efficiency-based calculations and examined the influence of critical experimental parameters, such as cell density seeded, assay volume, incubation time, as well as the cell line-intrinsic factor of cellular cooperation by auto-/paracrine stimulation. Our findings were integrated into a novel mathematical approach for the analysis of clonogenic survival data.

RESULTS

For various cell lines, clonogenic growth behavior failed to be adequately described by a constant plating efficiency, since the density of cells seeded severely influenced the extent and the dynamics of clonogenic growth. This strongly impaired the robustness of survival calculations obtained by the current state-of-the-art method using plating efficiency-based normalization. A novel mathematical approach utilizing power regression and interpolation of matched colony numbers at different irradiation doses applied to the same dataset substantially reduced the impact of cell density on survival results. Cellular cooperation was observed to be responsible for the non-linear clonogenic growth behavior of a relevant number of cell lines and the impairment of survival calculations. With 28/50 cell lines of different tumor entities showing moderate to high degrees of cellular cooperation, this phenomenon was found to be unexpectedly common.

CONCLUSIONS

Our study reveals that plating efficiency-based analysis of clonogenic survival data is profoundly compromised by cellular cooperation resulting in strongly underestimated assay-intrinsic errors in a relevant proportion of established cancer cell lines. This severely questions the use of plating efficiency-based calculations in studies aiming to achieve more than semiquantitative results. The novel approach presented here accounts for the phenomenon of cellular cooperation and allows the extraction of clonogenic survival results with clearly improved robustness.

Comparison of Clonogenic Survival Data Obtained by Pre- and Post-Irradiation Methods

Clonogenic assays are the gold standard to measure in vitro radiosensitivity, which use two cell plating methods, before or after irradiation (IR). However, the effect of the plating method on the experimental outcome remains unelucidated. By using common cancer cell lines, here we demonstrate that pre-IR and post-IR plating methods have a negligible effect on the clonogenic assay-derived photon sensitivity as assessed by SF₂, SF₄, SF₆, SF₈, D₁₀, or D₅₀ (N.B. SFx indicates the survival at X Gy; Dx indicates the dose providing X% survival). These data provide important biological insight that supports inter-study comparison and integrated analysis of published clonogenic assay data regardless of the plating method used.

Ultrasonic Nanoemulsification of Cuminum cyminum Essential Oil and Its Applications in Medicine

Background and Study

Cumin seed oil (extracted from Cuminum cyminum) has many applications but conclusive evidence of its therapeutic uses has not been presented. This study has explored the anticancer and antibacterial properties of the seed oil.

Methods

The cumin nanoemulsion was prepared with Tween 80 non-ionic surfactant employing ultra-sonication technology. The anticancer activity of the nanoscale-based emulsion was evaluated through cell viability (MTT), antiproliferation evaluation through clonogenic assay, and apoptosis through Annexin V-FITC assay. Agar well diffusion was used to study the antimicrobial activity, and this was supported by membrane integrity analysis.

Results

A thorough study of process parameters, aimed at obtaining the optimal surface concentration and emulsification time, was completed. GC-MS data indicated cumaldehyde as a major component. The resultant droplet diameter after a sonication time of 5 min was 10.4 ± 0.5 nm. MTT assay revealed the IC₅₀ value at 1.5 µL/mL and the early induction of apoptosis was evident. Tongue carcinoma cell line treated with cumin nanoemulsion presented a diminished colony formation. The nanoemulsion exhibited significant antibacterial activity against S. aureus. A significant cytoplasmic leakage was observed on treatment with cumin nanoemulsion. The consequences of the analysis projected cumin as a potential component for cancer therapy.

Conclusion

This study provides definitive evidence for cumin essential oil nanoemulsion as a legitimate plant-based medicine that can bypass the drawbacks of the present aggressive treatment of cancer, can overcome the antimicrobial resistance, and can also meet all prerequisites.

Modeling Cellular Response in Large-Scale Radiogenomic Databases to Advance Precision Radiotherapy

Radiotherapy is integral to the care of a majority of patients with cancer. Despite differences in tumor responses to radiation (radioresponse), dose prescriptions are not currently tailored to individual patients. Recent large-scale cancer cell line databases hold the promise of unravelling the complex molecular arrangements underlying cellular response to radiation, which is critical for novel predictive biomarker discovery. Here, we present RadioGx, a computational platform for integrative analyses of radioresponse using radiogenomic databases. We fit the dose-response data within RadioGx to the linear-quadratic model. The imputed survival across a range of dose levels (AUC) was a robust radioresponse indicator that correlated with biological processes known to underpin the cellular response to radiation. Using AUC as a metric for further investigations, we found that radiation sensitivity was significantly associated with disruptive mutations in genes related to nonhomologous end joining. Next, by simulating the effects of different oxygen levels, we identified putative genes that may influence radioresponse specifically under hypoxic conditions. Furthermore, using transcriptomic data, we found evidence for tissue-specific determinants of radioresponse, suggesting that tumor type could influence the validity of putative predictive biomarkers of radioresponse. Finally, integrating radioresponse with drug response data, we found that drug classes impacting the cytoskeleton, DNA replication, and mitosis display similar therapeutic effects to ionizing radiation on cancer cell lines. In summary, RadioGx provides a unique computational toolbox for hypothesis generation to advance preclinical research for radiation oncology and precision medicine. SIGNIFICANCE: The RadioGx computational platform enables integrative analyses of cellular response to radiation with drug responses and genome-wide molecular data. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/79/24/6227/F1.large.jpg.See related commentary by Spratt and Speers, p. 6076.

Robustness of Clonogenic Assays as a Biomarker for Cancer Cell Radiosensitivity

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.

Deep learning-assisted literature mining for in vitro radiosensitivity data

BACKGROUND AND PURPOSE

Integrated analysis of existing radiosensitivity data obtained by the gold-standard clonogenic assay has the potential to improve our understanding of cancer cell radioresistance. However, extraction of radiosensitivity data from the literature is highly labor-intensive. To aid in this task, using deep convolutional neural networks (CNNs) and other computer technologies, we developed an analysis pipeline that extracts radiosensitivity data derived from clonogenic assays from the literature.

MATERIALS AND METHODS

Three classifiers (C1-3) were developed to identify publications containing radiosensitivity data derived from clonogenic assays. C1 uses Faster Regions CNN with Inception Resnet v2 (fRCNN-IRv2), VGG-16, and Optical Character Recognition (OCR) to identify publications that contain semi-logarithmic graphs showing radiosensitivity data derived from clonogenic assays. C2 uses fRCNN-IRv2 and OCR to identify publications that contain bar graphs showing radiosensitivity data derived from clonogenic assays. C3 is a program that identifies publications containing keywords related to radiosensitivity data derived from clonogenic assays. A program (iSF₂) was developed using Mask RCNN and OCR to extract surviving fraction after 2-Gy irradiation (SF₂) as assessed by clonogenic assays, presented in semi-logarithmic graphs. The efficacy of C1-3 and iSF₂ was tested using seven datasets (1805 and 222 publications in total, respectively).

RESULTS

C1-3 yielded sensitivity of 91.2% ± 3.4% and specificity of 90.7% ± 3.6%. iSF₂ returned SF₂ values that were within 2.9% ± 2.6% of the SF₂ values determined by radiation oncologists.

CONCLUSION

Our analysis pipeline is potentially useful to acquire radiosensitivity data derived from clonogenic assays from the literature.

Radiosensitivity Differences between EGFR Mutant and Wild-Type Lung Cancer Cells are Larger at Lower Doses

In the era of precision medicine, radiotherapy strategies should be determined based on genetic profiles that predict tumor radiosensitivity. Accordingly, pre-clinical research aimed at discovering clinically applicable genetic profiles is needed. However, how a given genetic profile affects cancer cell radiosensitivity is unclear. To address this issue, we performed a pilot in vitro study by utilizing EGFR mutational status as a model for genetic profile. Clonogenic assays of EGFR mutant (n = 6) and wild-type (n = 9) non-small cell lung carcinoma (NSCLC) cell lines were performed independently by two oncologists. Clonogenic survival parameters SF₂, SF₄, SF₆, SF₈, mean inactivation dose (MID), D₁₀, D₅₀, α, and β were obtained using the linear quadratic model. The differences in the clonogenic survival parameters between the EGFR mutant and wild-type cell lines were assessed using the Mann-Whitney U test. As a result, for both datasets, the p values for SF₂, SF₄, D₅₀, α, and α/β were below 0.05, and those for SF₂ were lowest. These data indicate that a genetic profile of NSCLC cell lines might be predictive for their radiation response; i.e., EGFR mutant cell lines might be more sensitive to low dose- and low fraction sized-irradiation.

miR-200c Modulates the Pathogenesis of Radiation-Induced Oral Mucositis

Radiation-induced oral mucositis (RIOM) is one of the most common side effects of radiotherapy in cancer patients, especially in almost all head and neck cancer patients. It presents as severe pain and ulceration. The development of RIOM is composed of five stages: initiation, primary damage response, signal amplification, ulceration, and healing. However, the key regulators involved in the RIOM pathogenesis remain largely unknown. In this study, we reveal a novel role of miR-200c, a member of the miR-200 family, in modulating RIOM pathogenesis. Using a mouse model mimicking RIOM, we found that the miR-200 family numbers (miR-141, miR-200a, miR-200b, and miR-200c) except miR-429 were significantly induced during the RIOM formation. Besides, in RIOM mice, miR-200c expression level was also increased dramatically in the normal human keratinocytes (NHKs) after irradiation. Knockdown of miR-200c expression with miR-200c-3p-shRNA significantly reduced senescence phenotype and enhanced cell proliferation in NHKs after irradiation. The generation of reactive oxygen species (ROS) and p47 enzyme involved in ROS production was increased after irradiation but both were markedly reduced in NHKs by miR-200c inhibition. Knockdown of miR-200c expression in NHKs increased DNA double-strand break repair after irradiation compared with control NHKs. Furthermore, miR-200c inhibition repressed the production of proinflammatory cytokines (TGF-β, TNF-α, and IL-1α) via inhibiting NF-κB and Smad2 activation in NHKs exposed to IR. Additionally, miR-200c inhibition promoted NHK migration and increased the expression of molecules that regulate epithelial to mesenchymal transition, including Snail, Vimentin, Zeb1, and Bmi-1. These results not only identify the key role of miR-200c in the pathogenesis of RIOM but also provide a novel therapeutic target to treat RIOM.

Immunostimulatory plant polysaccharides impede cancer progression and metastasis by avoiding off-target effects

An unexploited homo-polysaccharide (PSM001) isolated from the seed kernel of Kottukonam variety of Mangifera indica, demonstrated selective cytotoxicity against cancer cells both in vitro and in murine models while maintaining the immunostimulatory potential. Galactoxyloglucan (PST001) isolated from the seeds of Tamarindus indica, was previously established to be an effective anticancer and immunomodulatory agent. Cancer metastasis, with key features including invasion, migration, increased angiogenesis and colony formation is only likely to accentuate in the coming decades, considering the ground realities of the modern lifestyle and environmental factors and hence both the polysaccharides were tested towards the management of malignancy. It was a startling observation with both the biopolymers in inhibiting various processes involved in the metastatic cascade. A quick perusal of the issue at hand would throw up the promising ability of both PSM001 and PST001 to inhibit lung metastatic nodules of C57BL/6 mice wherein the combinatorial treatment of these polysaccharides with vincristine delivered superior therapeutic output. Later, vascular endothelial growth factor and multiple matrix metalloproteinases were found to be the lead players in the polysaccharide mediated metastatic inhibition. Having considered the complexities associated with the chemotherapy in metastatic cancer in terms of palpable immunosuppression, the aftermaths with the co-administration of an immunostimulatory agent which itself possess unique anticancer and anti-metastatic potentials with a potent chemotherapeutic agent will be enormously consequential.

Mutational analysis of uterine cervical cancer that survived multiple rounds of radiotherapy

Radiotherapy is an essential component of cancer therapy. Despite advances in cancer genomics, the mutation signatures of radioresistant tumors have not yet been fully elucidated. To address this issue, we analyzed a unique set of clinical specimens from a uterine cervical cancer that repeatedly locally recurred after multiple rounds of radiotherapy. Exon sequencing of 409 cancer-related genes in the treatment-naïve tumor and the tumors that recurred after initial and secondary radiotherapy identified (i) activating mutations in PIK3CA and KRAS, and putative inactivating mutations in SMAD4, as trunk mutation signatures that persisted over the clinical course; and (ii) mutations in KMT2A, TET1, and NLRP1 as acquired mutation signatures observed only in recurrent tumors after radiotherapy. Comprehensive mining of published in vitro genomics data pertaining to radiosensitivity revealed that simultaneous mutations in KRAS and SMAD4, which have not been described previously in uterine cervical cancer, are associated with cancer cell radioresistance. The association between this mutation signature and radioresistance was validated by isogenic cell-based experiments. These results provide proof-of-principle for the analytical pipeline employed in this study, which explores clinically relevant mutation signatures for radioresistance, and demonstrate that this approach is worth pursuing with larger cohorts in the future.