Radiomic signature accurately predicts the risk of metastatic dissemination in late-stage non-small cell lung cancer.

Background: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and the median overall survival (OS) is approximately 2-3 years among patients with stage III disease. Furthermore, it is one of the deadliest types of cancer globally due to non-specific symptoms and the lack of a biomarker for early detection. The most important decision that clinicians need to make after a lung cancer diagnosis is the selection of a treatment schedule. This decision is based on, among others factors, the risk of developing metastasis. Methods: A cohort of 115 NSCLC patients treated using chemotherapy and radiotherapy (RT) with curative intent was retrospectively collated and included patients for whom positron emission tomography/computed tomography (PET/CT) images, acquired before RT, were available. The PET/CT images were used to compute radiomic features extracted from a region of interest (ROI), the primary tumor. Radiomic and clinical features were then classified to stratify the patients into short and long time to metastasis, and regression analysis was used to predict the risk of metastasis. Results: Classification based on binarized metastasis-free survival (MFS) was applied with moderate success. Indeed, an accuracy of 0.73 was obtained for the selection of features based on the Wilcoxon test and logistic regression model. However, the Cox regression model for metastasis risk prediction performed very well, with a concordance index (C-index) score equal to 0.84. Conclusions: It is possible to accurately predict the risk of metastasis in NSCLC patients based on radiomic features. The results demonstrate the potential use of features extracted from cancer imaging in predicting the risk of metastasis.

Impact of government policies on the COVID-19 pandemic unraveled by mathematical modelling.

Since the very beginning of the COVID-19 pandemic, control policies and restrictions have been the hope for containing the rapid spread of the virus. However, the psychological and economic toll they take on society entails the necessity to develop an optimal control strategy. Assessment of the effectiveness of these interventions aided with mathematical modelling remains a non-trivial issue in terms of numerical conditioning due to the high number of parameters to estimate from a highly noisy dataset and significant correlations between policy timings. We propose a solution to the problem of parameter non-estimability utilizing data from a set of European countries. Treating a subset of parameters as common for all countries and the rest as country-specific, we construct a set of individualized models incorporating 13 different pandemic control measures, and estimate their parameters without prior assumptions. We demonstrate high predictive abilities of these models on an independent validation set and rank the policies by their effectiveness in reducing transmission rates. We show that raising awareness through information campaigns, providing income support, closing schools and workplaces, cancelling public events, and maintaining an open testing policy have the highest potential to mitigate the pandemic.

Impact of renin-angiotensin system inhibitors on the survival of patients with rectal cancer.

BACKGROUND: Renin-angiotensin system inhibitors (RASIs) are widely used in the treatment of hypertension. However, their impact on the outcome of the combined treatment of rectal cancer is poorly understood. The aim of this study was to assess the effect of RASIs on the survival of rectal cancer patients with associated hypertension after neoadjuvant treatment and radical resection. METHODS: Between 2008 and 2016, 242 radical (R0) rectal resections for cancer were performed after neoadjuvant treatment in patients with associated hypertension. At the time of treatment, 158 patients were on RASIs, including 35 angiotensin-receptor antagonists (ARB) users and 123 angiotensin-converting enzyme inhibitors (ACEI) users. Eighty-four patients were on drugs other than RASIs (non-RASI users). The survival analysis was performed using the Kaplan-Meier estimator with the log-rank test and the Cox proportional hazards model. RESULTS: The log-rank test showed a significantly worse overall survival (OS) in the group of ACEI users compared to ARB users (p = 0.009) and non-RASI users (p = 0.013). Disease-free survival (DFS) was better in the group of ARB users compared to ACEI users. However, the difference was not statistically significant (p = 0.064). The Multivariate Cox analysis showed a significant beneficial effect of ARBs on OS (HR: 0.326, 95% CI: 0.147-0.724, p = 0.006) and ARBs on DFS (HR: 0.339, 95% CI: 0.135-0.850, p = 0.021) compared to ACEIs. Other factors affecting OS included age (HR: 1.044, 95% CI: 1.016-1.073, p = 0.002), regional lymph node metastasis (ypN +) (HR: 2.157, 95% CI: 1.395-3.334, p = 0.001) and perineural invasion (PNI) (HR: 3.864, 95% CI: 1.799-8.301, p = 0.001). Additional factors affecting DFS included ypN + (HR: 2.310, 95% CI: 1.374-3.883, p = 0.002) and PNI (HR: 4.351, 95% CI: 1.584-11.954, p = 0.004). CONCLUSIONS: The use of ARBs instead of ACEIs may improve the outcome of the combined therapy for rectal cancer patients with associated hypertension.

p38 Mediates Resistance to FGFR Inhibition in Non-Small Cell Lung Cancer.

FGFR signalling is one of the most prominent pathways involved in cell growth and development as well as cancer progression. FGFR1 amplification occurs in approximately 20% of all squamous cell lung carcinomas (SCC), a predominant subtype of non-small cell lung carcinoma (NSCLC), indicating FGFR as a potential target for the new anti-cancer treatment. However, acquired resistance to this type of therapies remains a serious clinical challenge. Here, we investigated the NSCLC cell lines response and potential mechanism of acquired resistance to novel selective FGFR inhibitor CPL304110. We found that despite significant genomic differences between CPL304110-sensitive cell lines, their resistant variants were characterised by upregulated p38 expression/phosphorylation, as well as enhanced expression of genes involved in MAPK signalling. We revealed that p38 inhibition restored sensitivity to CPL304110 in these cells. Moreover, the overexpression of this kinase in parental cells led to impaired response to FGFR inhibition, thus confirming that p38 MAPK is a driver of resistance to a novel FGFR inhibitor. Taken together, our results provide an insight into the potential direction for NSCLC targeted therapy.

Evaluation of the Role of ITGBL1 in Ovarian Cancer.

In our previous microarray study we identified two subgroups of high-grade serous ovarian cancers with distinct gene expression and survival. Among differentially expressed genes was an Integrin beta-like 1 (ITGBL1), coding for a poorly characterized protein comprised of ten EGF-like repeats. Here, we have analyzed the influence of ITGBL1 on the phenotype of ovarian cancer (OC) cells. We analyzed expression of four putative ITGBL1 mRNA isoforms in five OC cell lines. OAW42 and SKOV3, having the lowest level of any ITGBL1 mRNA, were chosen to produce ITGBL1-overexpressing variants. In these cells, abundant ITGBL1 mRNA expression could be detected by RT-PCR. Immunodetection was successful only in the culture media, suggesting that ITGBL1 is efficiently secreted. We found that ITGBL1 overexpression affected cellular adhesion, migration and invasiveness, while it had no effect on proliferation rate and the cell cycle. ITGBL1-overexpressing cells were significantly more resistant to cisplatin and paclitaxel, major drugs used in OC treatment. Global gene expression analysis revealed that signaling pathways affected by ITGBL1 overexpression were mostly those related to extracellular matrix organization and function, integrin signaling, focal adhesion, cellular communication and motility; these results were consistent with the findings of our functional studies. Overall, our results indicate that higher expression of ITGBL1 in OC is associated with features that may worsen clinical course of the disease.