Homologous Recombination Deficiency Scar: Mutations and Beyond-Implications for Precision Oncology.

Homologous recombination deficiency (HRD) is a prevalent in approximately 17% of tumors and is associated with enhanced sensitivity to anticancer therapies inducing double-strand DNA breaks. Accurate detection of HRD would therefore allow improved patient selection and outcome of conventional and targeted anticancer therapies. However, current clinical assessment of HRD mainly relies on determining germline BRCA1/2 mutational status and is insufficient for adequate patient stratification as mechanisms of HRD occurrence extend beyond functional BRCA1/2 loss. HRD, regardless of BRCA1/2 status, is associated with specific forms of genomic and mutational signatures termed HRD scar. Detection of this HRD scar might therefore be a more reliable biomarker for HRD. This review discusses and compares different methods of assessing HRD and HRD scar, their advances into the clinic, and their potential implications for precision oncology.

Selectively Targeting Tumor Hypoxia With the Hypoxia-Activated Prodrug CP-506.

Hypoxia-activated prodrugs (HAP) are a promising class of antineoplastic agents that can selectively eliminate hypoxic tumor cells. This study evaluates the hypoxia-selectivity and antitumor activity of CP-506, a DNA alkylating HAP with favorable pharmacologic properties. Stoichiometry of reduction, one-electron affinity, and back-oxidation rate of CP-506 were characterized by fast-reaction radiolytic methods with observed parameters fulfilling requirements for oxygen-sensitive bioactivation. Net reduction, metabolism, and cytotoxicity of CP-506 were maximally inhibited at oxygen concentrations above 1 µmol/L (0.1% O2). CP-506 demonstrated cytotoxicity selectively in hypoxic 2D and 3D cell cultures with normoxic/anoxic IC50 ratios up to 203. Complete resistance to aerobic (two-electron) metabolism by aldo-keto reductase 1C3 was confirmed through gain-of-function studies while retention of hypoxic (one-electron) bioactivation by various diflavin oxidoreductases was also demonstrated. In vivo, the antitumor effects of CP-506 were selective for hypoxic tumor cells and causally related to tumor oxygenation. CP-506 effectively decreased the hypoxic fraction and inhibited growth of a wide range of hypoxic xenografts. A multivariate regression analysis revealed baseline tumor hypoxia and in vitro sensitivity to CP-506 were significantly correlated with treatment response. Our results demonstrate that CP-506 selectively targets hypoxic tumor cells and has broad antitumor activity. Our data indicate that tumor hypoxia and cellular sensitivity to CP-506 are strong determinants of the antitumor effects of CP-506.

Lymphocyte-Sparing Radiotherapy: The Rationale for Protecting Lymphocyte-rich Organs When Combining Radiotherapy With Immunotherapy.

There is now strong clinical and preclinical evidence that lymphocytes, for example, CD8+ T cells, are key effectors of immunotherapy and that irradiation of large blood vessels, the heart, and lymphoid organs (including nodes, spleen, bones containing bone marrow, and thymus in children) causes transient or persistent lymphopenia. Furthermore, there is extensive clinical evidence, across multiple cancer sites and treatment modalities, that lymphopenia correlates strongly with decreased overall survival. At the moment, we lack quantitative evidence to establish the relationship between dose-volume and dose-rate to critical normal structures and lymphopenia. Therefore, we propose that data should be systematically recorded to characterise a possible quantitative relationship. This might enable us to improve the efficacy of radiotherapy and develop strategies to predict and prevent treatment-related lymphopenia. In anticipation of more quantitative data, we recommend the application of the principle of As Low As Reasonably Achievable to lymphocyte-rich regions for radiotherapy treatment planning to reduce the radiation doses to these structures, thus moving toward "Lymphocyte-Sparing Radiotherapy."

Human fibronectin extra domain B as a biomarker for targeted therapy in cancer.

The extracellular matrix protein fibronectin contains a domain that is rarely found in healthy adults and is almost exclusively expressed by newly formed blood vessels in tumours, particularly in solid tumours, different types of lymphoma and some leukaemias. This domain, called the extra domain B (ED-B), thus has broad therapeutic potential. The antibody L19 has been developed to specifically target ED-B and has shown therapeutic potential when combined with cytokines, such as IL-2. In this review article, we discuss the preclinical research and clinical trials that highlight the potential of ED-B targeting for the imaging and treatment of various types of cancer. ED-B-centred studies also highlight how proper patient stratification is of utmost importance for the successful implementation of novel antibody-based targeted therapies.

Radiomics: from qualitative to quantitative imaging.

Historically, medical imaging has been a qualitative or semi-quantitative modality. It is difficult to quantify what can be seen in an image, and to turn it into valuable predictive outcomes. As a result of advances in both computational hardware and machine learning algorithms, computers are making great strides in obtaining quantitative information from imaging and correlating it with outcomes. Radiomics, in its two forms "handcrafted and deep," is an emerging field that translates medical images into quantitative data to yield biological information and enable radiologic phenotypic profiling for diagnosis, theragnosis, decision support, and monitoring. Handcrafted radiomics is a multistage process in which features based on shape, pixel intensities, and texture are extracted from radiographs. Within this review, we describe the steps: starting with quantitative imaging data, how it can be extracted, how to correlate it with clinical and biological outcomes, resulting in models that can be used to make predictions, such as survival, or for detection and classification used in diagnostics. The application of deep learning, the second arm of radiomics, and its place in the radiomics workflow is discussed, along with its advantages and disadvantages. To better illustrate the technologies being used, we provide real-world clinical applications of radiomics in oncology, showcasing research on the applications of radiomics, as well as covering its limitations and its future direction.