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Liquid biopsies of circulating tumor DNA offer a non-invasive tool with many potential applications in oncology, including early cancer detection, profiling, disease prognosis, prediction of therapy response and monitoring disease status. A growing body of literature and clinical trials support an increasingly valuable role for liquid biopsies in the care of patients with solid malignancies.

Recent progress indicates a considerably improved mechanistic understanding of CAR T cell biology and delivers important insights into why some patients achieve durable remissions and others do not. In addition, although most success has been achieved in the context of CAR T cells targeted to B cell tumor antigens, namely CD19 and BCMA, we are seeing promising clinical trial outcomes for solid tumor malignancies.

As guidelines, therapies and literature on cancer variants expand, the lack of consensus variant interpretations impedes clinical applications. CIViC is a public-domain, crowd-sourced and adaptable knowledgebase of evidence for the clinical interpretation of variants in cancer, designed to reduce barriers to knowledge sharing and alleviate the variant-interpretation bottleneck.

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.

Recent advances in cancer neuroscience necessitate the systematic analysis of neural influences in cancer as potential therapeutic targets in oncology. Here we outline recommendations for future preclinical and translational research in this field.

The risks posed to patients with cancer by the current COVID-19 pandemic demand rapid structural changes in healthcare delivery, with many positive changes likely to continue long term. An immediate critical reassessment of trial methodology based on clinical and scientific priorities is essential to ensure the resilience of clinical cancer research and optimize patient-centered care.

The COVID-19 pandemic has disrupted the spectrum of cancer care, including delaying diagnoses and treatment and halting clinical trials. In response, healthcare systems are rapidly reorganizing cancer services to ensure that patients continue to receive essential care while minimizing exposure to SARS-CoV-2 infection.

Crowdsourcing efforts are currently underway to collect and analyze data from patients with cancer who are affected by the COVID-19 pandemic. These community-led initiatives will fill key knowledge gaps to tackle crucial clinical questions on the complexities of infection with the causative coronavirus SARS-Cov-2 in the large, heterogeneous group of vulnerable patients with cancer.

Low- and middle-income countries share the greatest burden of cancer mortality globally but lag behind high-income countries in terms of clinical trials. Here we discuss the challenges facing low- and middle-income countries and the opportunities for conducting trials of affordable, accessible and effective interventions relevant to the local population.

By integrating discovery science with clinical practice and therapeutic intervention, clinician-scientists fulfil a unique role in cancer research. However, their numbers are in decline, which is creating the need for flexible training and research opportunities to ensure their future.

Intratumoral genetic heterogeneity of driver somatic mutations is present in a variety of tumor types, yet the extent of heterogeneity is variable. We propose that this variation is a reflection of the inherent biology of a given tumor type, representing the pace of metastatic dissemination and hence clinical disease course.