Background: Few studies have focused on predicting the overall survival (OS) of patients affected by SARS-CoV-2 (i.e., COVID-19) using radiomic features (RFs) extracted from computer tomography (CT) images. Reconstruction of CT scans might potentially affect the values of RFs. Methods: Out of 435 patients, 239 had the scans reconstructed with a single modality, and hence, were used for training/testing, and 196 were reconstructed with two modalities were used as validation to evaluate RFs robustness to reconstruction. During training, the dataset was split into train/test using a 70/30 proportion, randomizing the procedure 100 times to obtain 100 different models. In all cases, RFs were normalized using the z-score and then given as input into a Cox proportional-hazards model regularized with the Least Absolute Shrinkage and Selection Operator (LASSO-Cox), used for feature selection and developing a robust model. The RFs retained multiple times in the models were also included in a final LASSO-Cox for developing the predictive model. Thus, we conducted sensitivity analysis increasing the number of retained RFs with an occurrence cut-off from 11% to 60%. The Bayesian information criterion (BIC) was used to identify the cut-off to build the optimal model. Results: The best BIC value indicated 45% as the optimal occurrence cut-off, resulting in five RFs used for generating the final LASSO-Cox. All the Kaplan-Meier curves of training and validation datasets were statistically significant in identifying patients with good and poor prognoses, irrespective of CT reconstruction. Conclusions: The final LASSO-Cox model maintained its predictive ability for predicting the OS in COVID-19 patients irrespective of CT reconstruction algorithms.
e15588 Background: Chemotherapy (CT) and chemoradiotherapy (CTRT) both in neoadjuvant (neoadj) or adjuvant (adj) setting are associated with better overall survival (OS) over surgery alone in patients (pts) with resectable gastroesophageal (GE) adenocarcinoma (ADK). The best sequence and timing of treatments have still not been defined. A large cohort of GE ADKs derived from 2 high-volume Italian centers was analyzed to describe clinical outcomes and prognostic factors. Methods: 497 patients (pts) diagnosed with GE ADK who underwent surgery with curative intent from 2007 to 2016 were considered. Variables analyzed were: age, sex, tumor location, histology, T, N, M, R, G, HER-2, Helicobacter Pylori (HP) infection, (neo)adj CT, and adj CTRT. Analysis was performed according to ITT principle. Results: Median age at diagnosis was 71 years (range 35-92). At 26.7 months (mo) median follow-up, median OS was 27.6 mo (range 1-127) and median time to recurrence (TTR) 10.8 mo (range 7.8-13.1). Adj CT was administered in 203 cases (41%); 116 pts (23%) had adj CTRT and 47 (9%) neoadj CT. Statistically significant variables for OS and/or TTR at 12 months at univariate analysis were: age, T, N, M, R, G, adj CTRT, neoadj CT and adj CT. Results of multivariate analysis (MVA) are shown in Table 1. Conclusions: Despite a short follow-up, our analysis performed on a very large cohort of consecutive pts confirms the prognostic value of T and N for both OS and TTR. Adj CT and CTRT had a significant impact on 1 year OS, while neoadj CT gave only a 12 months TTR significant benefit. Based on these results, perioperative treatment strategies should always be considered in the management of resectable GE cancer. [Table: see text]
Background Preclinical in vivo studies using small animals are considered crucial in translational cancer research and clinical implementation of novel treatments. This is of paramount relevance in radiobiology, especially for any technological developments permitted to deliver high doses in single or oligo-fractionated regimens, such as stereotactic ablative radiotherapy (SABR). In this context, clinical success in cancer treatment needs to be guaranteed, sparing normal tissue and preventing the potential spread of disease or local recurrence. In this work we introduce a new dose-response relationship based on relevant publications concerning preclinical models with regard to delivered dose, fractionation schedule and occurrence of biological effects on non-irradiated tissue, abscopal effects. Methods We reviewed relevant publications on murine models and the abscopal effect in radiation cancer research following PRISMA methodology. In particular, through a log-likelihood method, we evaluated whether the occurrence of abscopal effects may be related to the biologically effective dose (BED). To this aim, studies accomplished with different tumor histotypes were considered in our analysis including breast, colon, lung, fibrosarcoma, pancreas, melanoma and head and neck cancer. For all the tumors, the α / β ratio was assumed to be 10 Gy, as generally adopted for neoplastic cells. Results Our results support the hypothesis that the occurrence rate of abscopal effects in preclinical models increases with BED. In particular, the probability of revealing abscopal effects is 50% when a BED of 60 Gy is generated. Conclusion Our study provides evidence that SABR treatments associated with high BEDs could be considered an effective strategy in triggering the abscopal effect, thus shedding light on the promising outcomes revealed in clinical practice.
Gold nanoparticles (GNPs) are being proposed in combination with radiotherapy to improve tumor control. However, the exact mechanisms underlying GNP radiosensitization are yet to be understood, thus, we present a new approach to estimate the nanoparticle-driven increase in radiosensitivity.A stochastic radiobiological model, derived from the Local Effect Model (LEM), was coupled with Monte Carlo simulations to estimate the increase in radiosensitivity produced by the interactions between photons and GNPs at nanometric scale. The model was validated using in vitro survival data of MDA-MB-231 breast cancer cells containing different concentrations of 2 nm diameter GNPs receiving different doses using 160 kVp, 6 MV, and 15 MV photons. A closed analytical formulation of the model was also derived and a study of RBE and TCP behavior was conducted.Results support the increased radiosensitivity due to GNP-driven dose inhomogeneities on a nanometric scale. The model is in good agreement with experimental clonogenic survival assays for 160 kVp, 6 MV, and 15 MV photons. The model suggests a RBE and TCP enhancement when lower energies and lower doses per fraction are used in the presence of GNPs.The evolution of the local effect model was implemented to assess cellular radiosensitization in the presence of GNPs and then validated with in vitro data. The model provides a useful framework to estimate the nanoparticle-driven radiosensitivity in treatment irradiations and could be applied to real clinical treatment predictions (described in a second part of this paper).
Mutations in the TP53 (Tumour Protein 53) gene can lead to expression of mutant p53 proteins that accumulate in cancer cells and can induce circulating p53 antibodies in cancer patients. Our aim was to evaluate the presence and prognostic role of these antibodies in lung cancer patients and to investigate whether they were related to p53 expression or TP53 mutations in tumour tissues.A total of 201 lung cancer patients were evaluated for p53 antibodies by ELISA (Enzyme-Linked Immunosorbent Assay) and control was obtained from 54 patients with non-malignant disorders; p53 expression was evaluated in 131 of the lung cancer patients by immunohistochemistry and TP53 mutations were then investigated in 53 tumours positively staining for p53 and in 12 tumours without p53 overexpression, whose DNA was available for direct sequencing.Our results show that 20.4% of cancer patients have positive levels of p53 antibodies, while none of the controls resulted positive. High levels of p53 expression are detected in 57.3% of cases and a significant correlation between serum p53 antibodies and high levels of p53 expression in the corresponding tumours is observed. In non-small cell lung cancer, p53 antibodies are significantly associated with poorly differentiated tumours; furthermore, high levels of p53 expression significantly correlated with squamous cell carcinoma and tumours with highest grade. Survival time of non-small cell lung cancer patients low/negative for serum p53 antibodies was significantly longer compared to patients with positive levels (p = 0.049); in particular, patients with squamous cell carcinoma, but not adenocarcinoma, low/negative for these antibodies show a significant better survival compared to serum-positive patients (p = 0.044).In our study, detection of serum p53 antibodies in non-small cell lung cancer patients has been shown to be useful in identifying subsets of patients with poor prognosis. A significant correlation between the presence of serum p53 antibodies in lung cancer patients and p53 overexpression in the corresponding tumours was also observed. We did not find a significant correlation between levels of serum p53 antibodies and TP53 mutations in the corresponding tumours.
