Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
Rapid progress in the molecular characterization of cancer genomes has been enabled by technology and computational analysis, and large databases now exist. Novel cancer therapeutics have resulted that more precisely target the vulnerabilities revealed by genomic analysis. Emergent efforts that link the two, using machine learning approaches and circulating DNA from cancer cells, are furthering cancer diagnosis and precision medicine.
The COVID-19 pandemic has impacted cancer care globally, the consequences of which are still not well understood. Through the lens of the impact in India, we emphasize the importance of continuing cancer care even during extenuating public health circumstances, and of strengthening health systems as a global priority.
Cancer multi-omics data has greatly expanded over recent decades, surpassing the human ability to extract meaningful information. The successful implementation of artificial intelligence systems into clinical pipelines to interpret complex datasets, and improve the outcomes of patients with cancer, demands strong validation using real-world evidence while also being mindful of ethical and social aspects.
Recent advances in single-cell multiomics have provided holistic views of the multifaceted state of a cell and its interaction with the environment. The rapid development of these technologies has offered a unique opportunity to analyse the molecular and cellular heterogeneity in cancer, and could lead to better cancer diagnosis, treatment and prognosis.
The deployment of molecular biomarkers that are indicative of sensitivity to tumor-targeted or immune-targeted cancer therapies improves the outcome of individual patients and increases the chances of successful drug approval. However, for many lethal malignancies, the majority of clinical trials are conducted with patients who do not have biomarkers and hence they miss the target.
Cancer research has undergone transformational changes over the past several decades. On the occasion of the 20th anniversary of the establishment of the NCI Center for Cancer Research, we highlight some elements that enable successful institutional approaches to solving the most pressing problems in cancer research.
The COVID-19 pandemic, caused by the SARS-CoV-2 coronavirus, poses a clear and present danger to the health and well-being of populations. Here we discuss its indirect impact on global cancer prevention and control efforts, particularly for cervical cancer. We suggest some comparisons between the COVID-19 pandemic and the human papillomavirus–induced cancer burden, as well as opportunities for translating pandemic-control strategies into effective cancer control.
Precision oncology trials based on cancer biomarkers have the potential to improve outcomes by guiding the optimal choice of therapies for patients. For this to be truly achieved, computational methods such as virtual molecular tumor boards, dynamic precision medicine and digital twins are needed to support cohort selection and trial enrollment at scale.
