Animal experiments remain essential to understand the fundamental mechanisms underpinning malignancy and to discover improved methods to prevent, diagnose and treat cancer. Excellent standards of animal care are fully consistent with the conduct of high quality cancer research. Here we provide updated guidelines on the welfare and use of animals in cancer research. All experiments should incorporate the 3Rs: replacement, reduction and refinement. Focusing on animal welfare, we present recommendations on all aspects of cancer research, including: study design, statistics and pilot studies; choice of tumour models (e.g., genetically engineered, orthotopic and metastatic); therapy (including drugs and radiation); imaging (covering techniques, anaesthesia and restraint); humane endpoints (including tumour burden and site); and publication of best practice.

Imaging biomarkers (IBs) are used extensively in drug development and cancer research, but important differences exist between IBs and biospecimen-derived biomarkers. A tailored 'roadmap' is required for the development of new IBs to be used either in clinical research or for decision-making in healthcare. In this Consensus statement, a group of experts assembled by CRUK and the EORTC present 14 key recommendations for accelerating the clinical translation of IBs. Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.

A functional genomics study revealed that the activity of acetyl-CoA synthetase 2 (ACSS2) contributes to cancer cell growth under low-oxygen and lipid-depleted conditions. Comparative metabolomics and lipidomics demonstrated that acetate is used as a nutritional source by cancer cells in an ACSS2-dependent manner, and supplied a significant fraction of the carbon within the fatty acid and phospholipid pools. ACSS2 expression is upregulated under metabolically stressed conditions and ACSS2 silencing reduced the growth of tumor xenografts. ACSS2 exhibits copy-number gain in human breast tumors, and ACSS2 expression correlates with disease progression. These results signify a critical role for acetate consumption in the production of lipid biomass within the harsh tumor microenvironment.

Introduction: Breast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice. Methods: More than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer ‘stem’ cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account. Results: The 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working. Conclusions: With resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years.

The integrin α_vβ₃ receptor is upregulated on tumor cells and endothelium and plays important roles in angiogenesis and metastasis. Arg-Gly-Asp (RGD) peptide ligands have high affinity for these integrins and can be radiolabeled for PET imaging of angiogenesis or tumor development. We have assessed the safety, stability, and tumor distribution kinetics of a novel radiolabeled RGD-based integrin peptide-polymer conjugate, ¹⁸F-AH111585, and its feasibility to detect tumors in metastatic breast cancer patients using PET. Methods: The biodistribution of ¹⁸F-AH111585 was assessed in 18 tumor lesions from 7 patients with metastatic breast cancer by PET, and the PET data were compared with CT results. The metabolic stability of ¹⁸F-AH111585 was assessed by chromatography of plasma samples. Regions of interest (ROIs) defined over tumor and normal tissues of the PET images were used to determine the kinetics of radioligand binding in tissues. Results: The radiopharmaceutical and PET procedures were well tolerated in all patients. All 18 tumors detected by CT were visible on the ¹⁸F-AH111585 PET images, either as distinct increases in uptake compared with the surrounding normal tissue or, in the case of liver metastases, as regions of deficit uptake because of the high background activity in normal liver tissue. ¹⁸F-AH111585 was either homogeneously distributed in the tumors or appeared within the tumor rim, consistent with the pattern of viable peripheral tumor and central necrosis often seen in association with angiogenesis. Increased uptake compared with background (P = 0.002) was demonstrated in metastases in lung, pleura, bone, lymph node, and primary tumor. Conclusion: ¹⁸F-AH111585 designed to bind the α_vβ₃ integrin is safe, metabolically stable, and retained in tumor tissues and detects breast cancer lesions by PET in most anatomic sites.

Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human eye but can be captured non-invasively on medical imaging as radiomic features, which can form a high dimensional data space amenable to machine learning. Radiomic features can be harnessed and used in an artificial intelligence paradigm to risk stratify patients, and predict for histological and molecular findings, and clinical outcome measures, thereby facilitating precision medicine for improving patient care. Compared to tissue sampling-driven approaches, radiomics-based methods are superior for being non-invasive, reproducible, cheaper, and less susceptible to intra-tumoral heterogeneity. This review focuses on the application of radiomics, combined with artificial intelligence, for delivering precision medicine in lung cancer treatment, with discussion centered on pioneering and groundbreaking works, and future research directions in the area.