A doctor speaks to a group of residents


As the organization that represents and connects the global community of clinicians who discover new treatments for cancer and deliver the latest advances to patients, each year, ASCO issues its list of top Research Priorities to Accelerate Progress Against Cancer. As cancer care becomes more complex and personalized, the research behind new advances must include the representation of all populations who stand to benefit and consider social determinants of health, such as the social, economic, and cultural factors that influence cancer risk and outcomes.

Research priorities for 2021, listed below in no particular order, represent promising areas of research that have the potential to significantly improve the knowledge base for clinical decision making and address vital unmet needs in cancer care. This year’s list includes a newly added priority on artificial intelligence, recognizing its growing potential to solve complex problems and drive diagnostic, therapeutic, and translational research across the spectrum of cancer prevention and care.

Develop and Integrate Artificial Intelligence and Deep Learning in Cancer Research

Artificial intelligence (AI) is a rapidly growing and complex field of medical research, with the potential to integrate innumerable data points into a clinically useful context. There are several types of AI, including deep learning methods, which use algorithms in an iterative process to identify relationships within data to solve complex problems. AI has the potential to drive diagnostic, therapeutic, and translational research across the spectrum of cancer prevention and care. It will be critical to educate oncologists about the fundamentals, advantages, and potential pitfalls of AI and deep learning techniques to support effective application in real-world cancer care.

Primary focus areas:

  • Develop deep learning methodologies that aid in cancer diagnosis based on biospecimen analysis, including the detection of molecular variants that may affect prognosis or treatment decisions.
  • Investigate the utility of AI to enhance and improve radiographic imaging, analysis, and reporting.
  • Implement and assess AI systems that integrate large amounts of clinical data to aid clinical decision making and measurement of clinical outcomes.

Identify Strategies That Predict Response and Resistance to Immunotherapies

Cancer immunotherapy encompasses a broad range of medicines and treatment approaches, including vaccines, immune checkpoint inhibitors, and, most recently, cellular therapies. These interventions have improved the outlook for multiple cancers by producing long-lasting remissions. For others, however, despite initial response to immunotherapy, resistance to treatment can develop and the cancer can recur. Immunotherapies can also cause substantial adverse effects that can be life-threatening and, in some cases, permanent. The ability to adequately assess, and potentially predict, response and resistance to immunotherapy will lead to better outcomes for patients.

Priority focus areas:

  • Identify blood-and tissue-based biomarkers relevant to immunotherapies that can predict initial response, long-term disease control, adverse events, and resistance.
  • Develop predictive models and algorithms that assign risk of severe immune-related toxicities based on readily available patient data.

Optimize Multimodality Treatment for Solid Tumors

A wide range of therapies are recommended to patients around the time of surgery (perioperative) as well as before and after it (neoadjuvant and adjuvant treatment). These therapies aim to achieve local control of the tumor as well as reduce the risk of recurrence and cancer-related death associated with microscopic tumor spread. Although such therapy has been associated with dramatic improvements in survival for some patients, studies have shown that the risks can outweigh the benefits for others. It is important to ensure that patients who receive these therapies are the ones most likely to benefit. Limiting their use in those who are unlikely to benefit will be an important step in optimizing care and eliminating unnecessary adverse effects and costs for patients in whom the benefits are unlikely to outweigh the risks.

 Priority focus areas:

  • Develop analytically and clinically valid biomarker tests with proven clinical utility to identify recurrence risk after treatment of the primary tumor and determine the best options for patients with different degrees of risk.
  • Define the patient populations that benefit from perioperative, neoadjuvant, and adjuvant therapies, including clinical, pathologic, genomic, biochemical, immunologic, and environmental or social factors that affect the likelihood of benefit.
  • Study treatment de-escalation strategies that maximize benefit while reducing risk.

Increase Precision Medicine Research and Treatment Approaches in Pediatric and Other Rare Cancers

Genomic tools have been widely deployed in adult patients with cancer to characterize the tumor mutation profile and guide therapy selection. In certain cancers, the use of these tools has accelerated the development of new targeted therapies that have improved and extended patients’ lives. Despite this success in adult patients, precision medicine treatment approaches have yet to be widely integrated into the treatment of pediatric cancers as well as other rare cancers.

Priority focus areas:

  • Identify genomic and other molecular alterations in pediatric and rare cancers that can serve as potentially actionable treatment targets.
  • Develop effective therapeutic agents that can target genomic or other molecular alterations in childhood and rare cancers.
  • Explore the efficacy of existing targeted therapies in pediatric patients and patients with rare cancers that have mutations shown to be responsive to medicines that work in adult populations.

Optimize Care for Older Adults With Cancer

Although adults age 65 years and older represent the majority of people with cancer, few cancer clinical trials focus specifically on this population. Older patients who do participate in clinical trials are generally not representative of the older patients that oncologists typically see in daily practice. As a result, clinicians face challenges applying clinical trial data to older patients who may have additional health conditions, varying levels of functional ability, and different goals from younger clinical trial participants. Researchers must make use of available practice-based, real-world data to study and drive improvements in caring for older adults with cancer. The lack of evidence combined with the inherent diversity of aging populations impedes the delivery of high-quality care for the largest and most rapidly growing segment of patients with cancer.

Priority focus areas:

  • Develop standardized methods to characterize physiologic aging, such as geriatric assessment, biomarkers of aging, and clinical pharmacology in older adults, to more reliably predict risk of treatment-related adverse effects in older patients with cancer.
  • Use practice-based data to better understand the efficacy and toxicities of cancer treatments, including the impact on physical function, cognition, and quality of life, particularly among older adults most underrepresented in clinical trials, such as those with impaired functional status, comorbidities, or frailty.
  • Test the role of geriatric assessment-guided management in improving outcomes using personalized care; important focus areas include strategies that minimize undertreatment of fit patients and overtreatment of vulnerable or frail patients, supportive care interventions, and care delivery interventions.

Increase Equitable Access to Cancer Clinical Trials

Certain patient populations are consistently underrepresented in cancer clinical trials. These include patients from racial and ethnic minorities, rural areas, and lower socioeconomic groups and patients older than 65 years as well as adolescents and young adults age 15-39 years. Decreased representation of these groups can limit access to the promising treatments offered through these trials and means that research findings may not fully account for the diversity of biologic, social, and cultural factors that influence outcomes. Additional research is needed to ensure that every patient with cancer, regardless of race, ethnicity, age, geographic location, or socioeconomic status, benefits from research advances.

Priority focus areas:

  • Improve understanding of the barriers to trial enrollment among various under-represented groups,taking into consideration patient, practice, community, and trial-specific factors.
  • Develop and test interventions that enhance clinical trial enrollment among under-represented populations (examples may include use of educational tools, telehealth, and community-based involvement and participatory research).
  • Evaluate novel strategies to improve access to clinical research resources in areas with large proportions of under-represented minorities.
  • Develop mechanisms that improve awareness and education about clinical trials among under-represented groups and the physicians treating them.
  • Make use of clinical practice data to study differences in cancer incidence, prevalence, natural history of disease, and treatment experience, including efficacy and toxicity, among underrepresented populations.

Reduce Adverse Consequences of Cancer Treatment

Advances in cancer treatment have resulted in a record number of cancer survivors—more than 15.5 million in the United States at present. Many survivors face acute and chronic consequences of cancer, including pain and adverse effects of cancer therapies—such as peripheral neuropathy, cognitive impairment, and cardiotoxicity—that affect quality of life and pose a substantial burden not only to patients but also to the healthcare system. Identifying strategies to minimize cancer-associated pain and treatment effects is an urgent area of research.

Priority focus areas:

  • Develop and test strategies to mitigate and manage chronic toxicities associated with cancer treatment, including optimization of drug and radiation dosing.
  • Identify genetic variants associated with increased risk of treatment-related toxicities.
  • Deepen understanding of the underlying mechanisms of toxicities from targeted treatments, determine their contribution to long-term effects, and develop novel strategies to mitigate or eliminate such toxicities.
  • Expand understanding and use of the range of pain management options for patients with cancer.
  • Develop new tools to facilitate long-term tracking of patient outcomes that include patient-reported measures.

Reduce Obesity’s Impact on Cancer Incidence and Outcomes

The incidence of obesity has dramatically increased over the past several decades.122 Despite being the second leading preventable cause of cancer, an ASCO survey found that only 35% of Americans recognize excess body weight as a cancer risk factor.123 Obesity is associated with poorer cancer survival and can contribute to increased risk of treatment-related adverse effects. If current trends continue over the next 20 years, it is estimated that obesity will lead to more than 500,000 additional cases of cancer each year in the United States and will surpass smoking as the leading preventable cause of cancer.

Priority focus areas:

  • Improve the understanding of the mechanisms by which weight and energy balance, including physical activity and dietary factors, contribute to cancer development and progression.
  • Investigate how obesity affects response to therapy, risk of cancer recurrence, and long-term cancer outcomes.
  • Assess the impact of energy balance interventions, such as weight loss, increased physical activity, and improved dietary quality, on cancer risk, recurrence, and mortality.
  • Identify effective interventions that optimize energy balance in people at risk and who are living with cancer.

Better Identify Potentially Malignant Lesions and Predict When Treatment Is Needed

Many cancers begin as high-risk lesions that invariably progress to invasive cancer, whereas other premalignant lesions may never require treatment. Currently, little is known about the genetic makeup, heterogeneity, and microenvironment of premalignant lesions, and what causes some to progress to invasive cancer. Increased knowledge will help guide new approaches to intercept and eradicate high-risk lesions before their transformation to malignancy and to spare patients from unnecessary treatments for lesions with a low risk of progression.

Priority focus areas:

  • Address barriers to screening and early treatment of potentially malignant disease.
  • Identify potentially malignant lesions with a high risk for progression based on specific features and develop appropriate treatment strategies, while also identifying potentially malignant lesions that do not require intervention.
  • Identify specific molecular pathways that drive progression of preinvasive lesions to invasive cancer and develop interventions that can delay or prevent progression to malignancy.
  • Identify features of the microenvironment of potentially malignant lesions that are associated with progression to invasive disease.
  • Investigate novel methods for evaluation of potentially malignant lesions to better inform the risk or likelihood of progression to invasive disease.

Previous SectionNext Section