Health Analytics Logo

10 Disease-Specific Research Challenges in Cancer

Table of Contents

Cancer is a complex and heterogeneous disease with more than 200 distinct histologies. Even within a single cancer type, there can be significant variation in tumor biology and clinical behavior. This heterogeneity has important implications for the design and conduct of cancer research studies. The traditional approach to cancer research has been to focus on specific tumor types or histologies. However, this approach is increasingly being replaced by a more holistic view that considers all aspects of the disease, from its molecular origins to its impact on a patient’s quality of life. In this post, we will discuss some of the unique challenges that cancer researchers face when designing and conducting studies on this complex disease.

What are the challenges in conducting disease-specific research for cancer?

1. Varied cancer subtypes

Cancer is a complex and heterogeneous disease, with hundreds of distinct types that share common fundamental properties. The tissue and cell type from which the disease originates play a crucial role, highlighting the need for a comprehensive understanding of the molecular and metabolic function of cancer cells within their specific context. Furthermore, cancer is characterized by its plasticity and heterogeneity, evolving at genetic, phenotypic, and pathological levels and progressing through different stages clinically.

2. Lack of standardization of data

The volume, velocity, and variety of big data in healthcare make it difficult to store, access, and analyze the data without proper standardization. The concept of “data quality” is crucial in healthcare research, as it determines the fitness of the data for its intended purpose. However, the use of real-world data (RWD) from sources like electronic health records (EHRs) and disease registries presents challenges in terms of data quality.

3. Need for increased research funding

Adequate funding would provide the necessary resources to support deserving research projects, promote a more equitable distribution of funding across research labs, and alleviate the financial strain on scientists. It would also help shift the focus from journal reputation to the intrinsic value and impact of research, encouraging innovative and high-risk projects. Moreover, increased funding could support mentorship programs, facilitate collaboration between researchers, and enable the development of critical infrastructure and core facilities.

4. Lack of access to treatments

Access to cancer treatments is influenced by various socioeconomic and policy-level factors that are beyond the control of the research and public health communities. These factors include limited access to healthcare facilities, state and federal policies on health insurance, and hospital and physician payment rules. Financial barriers also play a role, as insurance companies and health organizations may not reimburse expensive personalized therapies, hindering patients’ ability to receive the most effective treatment options.

5. Difficulty in diagnosing tumors

Conducting disease-specific research for cancer, particularly in the field of tumor diagnosis, presents various challenges. One major difficulty lies in the high cost and potential risks associated with non-invasive imaging techniques such as CT, MRI, and PET scans. Additionally, there is a risk of false-positive results.

6. Need for increased collaboration

Collaborative efforts between pharma and biotech, as well as with academics, can provide shared incentives and resources, leading to more successful research outcomes. Coordinated efforts from multiple fields and the inclusion of both basic and clinical spheres are essential for cancer research to have a direct clinical impact. Improved collaboration can also facilitate the development and utilization of sophisticated tools and technologies, such as genomics and systems biology approaches, in conjunction with other disciplines.

7. Complexity of cancer cell characteristics

Cancer is not a single disease but rather a collection of hundreds of distinct disease types. While these types share fundamental properties, the tissue and cell type from which the disease originates are vital factors in understanding its behavior and response to treatment. This diversity in cancer types necessitates a comprehensive approach to research, considering the unique characteristics of each disease.

8. Need for more research on prevention strategies

The establishment of research priorities would be beneficial for policymakers to target promising areas of research and allocate resources accordingly. Additionally, the design of effective prevention strategies requires a deep understanding of the full spectrum of issues faced by clinicians when treating patients, including financial considerations, patient recruitment difficulties, and compliance with complicated dosing regimens.

9. Need for improved tools for data analysis

Conducting disease-specific research for cancer poses several challenges, particularly in terms of data analysis. These challenges can be summarized as follows:

  1. Data variety and fitness. The volume, velocity, and variety of healthcare data, often referred to as big data, require advanced technology and computational power for storage, access, and analysis.
  2. Real-World Data (RWD) reliance: RWD, collected from sources such as electronic health records (EHRs), disease registries, and claims databases, offers strong external validity and the ability to capture characteristics and outcomes of patients commonly encountered in clinical practice. However, using RWD for clinical care and research requires addressing data quality issues transparently.
  3. Clinician involvement and EHR limitations: Clinicians play a central role in ensuring data quality in EHRs. However, these systems are primarily optimized for patient care and billing documentation rather than population health research and analytics.
  4. Lack of data interoperability. The lack of standardized data formats and communication protocols hinders data interoperability, both syntactically and semantically.

10. Challenge of finding the best treatment for each patient

Key challenges in this area include:

  1. The financial barriers that limit access to personalized therapies due to the lack of reimbursement from insurance companies and health organizations.
  2. The hesitation of big pharmaceutical companies to invest in personalized treatment approaches, which require a different philosophy than the traditional blockbuster drug model.
  3. The struggles of regulatory authorities in developing efficient rules for personalized treatment.
  4. The low success rate of cancer therapeutics in clinical trials.
  5. The need for a multidisciplinary approach to tackle the complex nature of cancer.
  6. Development of more predictive preclinical models of cancer.


In conclusion, disease-specific research in cancer presents numerous challenges, including the complexity and heterogeneity of cancer subtypes, lack of standardized data, funding limitations, limited access to treatments, difficulty in tumor diagnosis, the need for collaboration, cancer cell characteristics, research on prevention strategies, and improved data analysis tools. Overcoming these challenges is crucial to finding personalized treatments, improving patient outcomes, and making significant progress in the fight against cancer.