CD8(+) T lymphocytes isolated from renal cancer patients recognize tumour cells through an HLA- and TCR/CD3-independent pathway

Advances, limitations and perspectives in the use of celecoxib-loaded nanocarriers in therapeutics of cancer

Cancer is highlighted as a major global health challenge in the XXI century. The cyclooxygenase-2 (COX-2) enzyme rises as a widespread tumor progression marker. Celecoxib (CXB) is a selective COX-2 inhibitor used in adjuvant cancer therapy, but high concentrations are required in humans. In this sense, the development of nanocarriers has been proposed once they can improve the biopharmaceutical, pharmacokinetic and pharmacological properties of drugs. In this context, this article reviews the progress in the development of CXB-loaded nanocarriers over the past decade and their prospects. Recent advances in the field of CXB-loaded nanocarriers demonstrate the use of complex formulations and the increasing importance of in vivo studies. The types of CXB-loaded nanocarriers that have been developed are heterogeneous and based on polymers and lipids together or separately. It was found that the work on CXB-loaded nanocarriers is carried out using established techniques and raw materials, such as poly (lactic-co-glicolic acid), cholesterol, phospholipids and poly(ethyleneglycol). The main improvements that have been achieved are the use of cell surface ligands, the simultaneous delivery of different synergistic agents, and the presence of materials that can provide imaging properties and other advanced features. The combination of CXB with other anti-inflammatory drugs and/or apoptosis inducers appears to hold effective pharmacological promise. The greatest advance to date from a clinical perspective is the ability of CXB to enhance the cytotoxic effects of established chemotherapeutic agents.

What Genetics Can Do for Oncological Imaging: A Systematic Review of the Genetic Validation Data Used in Radiomics Studies

(1) Background: Radiogenomics is motivated by the concept that biomedical images contain information that reflects underlying pathophysiology. This review focused on papers that used genetics to validate their radiomics models and outcomes and assess their contribution to this emerging field. (2) Methods: All original research with the words radiomics and genomics in English and performed in humans up to 31 January 2022, were identified on Medline and Embase. The quality of the studies was assessed with Radiomic Quality Score (RQS) and the Cochrane recommendation for diagnostic accuracy study Quality Assessment 2. (3) Results: 45 studies were included in our systematic review, and more than 50% were published in the last two years. The studies had a mean RQS of 12, and the studied tumors were very diverse. Up to 83% investigated the prognosis as the main outcome, with the rest focusing on response to treatment and risk assessment. Most applied either transcriptomics (54%) and/or genetics (35%) for genetic validation. (4) Conclusions: There is enough evidence to state that new science has emerged, focusing on establishing an association between radiological features and genomic/molecular expression to explain underlying disease mechanisms and enhance prognostic, risk assessment, and treatment response radiomics models in cancer patients.

Development and Validation of a Radiomic Nomogram for Predicting the Prognosis of Kidney Renal Clear Cell Carcinoma

Purpose

The present study aims to comprehensively investigate the prognostic value of a radiomic nomogram that integrates contrast-enhanced computed tomography (CECT) radiomic signature and clinicopathological parameters in kidney renal clear cell carcinoma (KIRC).

Methods

A total of 136 and 78 KIRC patients from the training and validation cohorts were included in the retrospective study. The intraclass correlation coefficient (ICC) was used to assess reproducibility of radiomic feature extraction. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) as well as multivariate Cox analysis were utilized to construct radiomic signature and clinical signature in the training cohort. A prognostic nomogram was established containing a radiomic signature and clinicopathological parameters by using a multivariate Cox analysis. The predictive ability of the nomogram [relative operating characteristic curve (ROC), concordance index (C-index), Hosmer–Lemeshow test, and calibration curve] was evaluated in the training cohort and validated in the validation cohort. Patients were split into high- and low-risk groups, and the Kaplan–Meier (KM) method was conducted to identify the forecasting ability of the established models. In addition, genes related with the radiomic risk score were determined by weighted correlation network analysis (WGCNA) and were used to conduct functional analysis.

Results

A total of 2,944 radiomic features were acquired from the tumor volumes of interest (VOIs) of CECT images. The radiomic signature, including ten selected features, and the clinical signature, including three selected clinical variables, showed good performance in the training and validation cohorts [area under the curve (AUC), 0.897 and 0.712 for the radiomic signature; 0.827 and 0.822 for the clinical signature, respectively]. The radiomic prognostic nomogram showed favorable performance and calibration in the training cohort (AUC, 0.896, C-index, 0.846), which was verified in the validation cohort (AUC, 0.768). KM curves indicated that the progression-free interval (PFI) time was dramatically shorter in the high-risk group than in the low-risk group. The functional analysis indicated that radiomic signature was significantly associated with T cell activation.

Conclusions

The nomogram combined with CECT radiomic and clinicopathological signatures exhibits excellent power in predicting the PFI of KIRC patients, which may aid in clinical management and prognostic evaluation of cancer patients.

Mechanism of Action of the Tumor Vessel Targeting Agent NGR-hTNF: Role of Both NGR Peptide and hTNF in Cell Binding and Signaling

NGR-hTNF is a therapeutic agent for a solid tumor that specifically targets angiogenic tumor blood vessels, through the NGR motif. Its activity has been assessed in several clinical studies encompassing tumors of different histological types. The drug’s activity is based on an improved permeabilization of newly formed tumor vasculature, which favors intratumor penetration of chemotherapeutic agents and leukocyte trafficking. This work investigated the binding and the signaling properties of the NGR-hTNF, to elucidate its mechanism of action. The crystal structure of NGR-hTNF and modeling of its interaction with TNFR suggested that the NGR region is available for binding to a specific receptor. Using 2D TR-NOESY experiments, this study confirmed that the NGR-peptides binds to a specific CD13 isoform, whose expression is restricted to tumor vasculature cells, and to some tumor cell lines. The interaction between hTNF or NGR-hTNF with immobilized TNFRs showed similar kinetic parameters, whereas the competition experiments performed on the cells expressing both TNFR and CD13 showed that NGR-hTNF had a higher binding affinity than hTNF. The analysis of the NGR-hTNF-triggered signal transduction events showed a specific impairment in the activation of pro-survival pathways (Ras, Erk and Akt), compared to hTNF. Since a signaling pattern identical to NGR-hTNF was obtained with hTNF and NGR-sequence given as distinct molecules, the inhibition observed on the survival pathways was presumably due to a direct effect of the NGR-CD13 engagement on the TNFR signaling pathway. The reduced activation of the pro survival pathways induced by NGR-hTNF correlated with the increased caspases activation and reduced cell survival. This study demonstrates that the binding of the NGR-motif to CD13 determines not only the homing of NGR-hTNF to tumor vessels, but also the increase in its antiangiogenic activity.