The State of Cancer Research: Where Oncology Is Heading Next

Cancer research is currently undergoing a major change in the way we think about cancer. Research now looks at many factors contributing to the development and growth of cancer, including the cancer's molecular profile, genetic alterations, and the tumor's behavior and the surrounding immune environment.

The ways in which we diagnose and treat cancer continue to evolve with the introduction of new technologies, from cancer immunotherapies to genomic and artificial intelligence platforms.

These changes in technology have led to the FDA approving over 20 new cancer therapies in 2025.

However, many of the newer cancer therapies focus on targeting individual mutations. The largest advances in cancer therapy could come from the ability to determine how these mutations will interact.

In the case of immunotherapies, individual mutations or a collection of mutations lead to cancers primarily being different in the way they behave.

Immunotherapy: Helping the Immune System Fight Cancer

Immunotherapy is one of the major innovations in cancer care.

Unlike traditional chemotherapies that destroy cells that rapidly divide, immunotherapies help the body's immune system target and destroy cancer cells.

Many of the early successes in immunotherapy were due to the use of immune checkpoint inhibitors.

Some immune checkpoint inhibitors target proteins such as PD-1, PD-L1, and CTLA-4. Removal of these biological "brakes" has led to dramatic responses in melanoma, lung, and blood cancers.

There are, however, many challenges to immunotherapy.

While these checkpoint inhibitors have been a major advancement, they are still not beneficial to all patients.

The main difficulty in the research is no longer whether immunotherapy is efficacious. The main issue is how to tell which patients would benefit the most from immunotherapy. If reliable markers are predictive of a patient's response to a treatment, we'd be able to select patients with greater precision and avoid the use of ineffective treatments and their consequent side effects.

CAR-T Cells Climb Beyond Blood Cancers

Immunotherapy is also widely studying CAR-T cells.

The first step is to collect a patient's immune cells.

The cells are then genetically manipulated to recognize cancer cells.

The final step is to return the modified cells to the patient.

CAR-T cells have been successful against many blood cancers. Scientists have expanded their focus to solid cancers.

Modifying immune cells as a strategy to respond to solid cancers is far more difficult. Because of the dense and complex nature of solid cancers, immune cells have a hard time reaching and destroying solid cancer cells.

There are multiple strategies to control engineered immune cells. One of the strategies is focusing on locally activated CAR-T cells.

Precision Medicine Climbs Beyond the Location of the Tumor

In the past, the organization of cancer treatment reflected the organ in which cancer was found, such as breast cancer, lung cancer, colorectal cancer, and pancreatic cancer.

Precision oncology further encourages us to think about cancer in a different way.

We are left asking:

What is biologically driving this particular cancer?

Next generation sequencing (NGS) can identify genomic changes in cancer cells. Some of these changes are biomarkers. With some changes, cancers can be targeted using new therapies.

We are moving from an organ-focused model of oncology to a model that is more informed by the molecular details of cancer.

Genomics is only a part of this evolution.

A broad range of biological layers are being examined simultaneously by researchers:

• DNA and genomic alterations
• RNA and gene expression
• proteins
• epigenetic changes (e.g. DNA methylation)
• immune characteristics
• tumour microenvironment
• metabolic and other molecular signals

Adopting this broader frame of reference (sometimes referred to as multi-omics) is often very helpful for understanding tumour biology beyond the study of just the DNA.

Liquid Biopsy: Looking for Cancer Signals in Blood

Another area of research is liquid biopsy.

In this case, instead of removing tissue through surgery or conducting a traditional biopsy, liquid biopsy looks for biological materials in blood or other fluids.

An example would be circulating tumor DNA (ctDNA).

These systems provide possibilities for detecting the evolution of tumors, identifying molecular changes, signs of residual disease, and determining how cancer responds to treatment.

Extracellular vesicles and other circulating biomarkers are currently under investigation as possible early detection methods for cancer.

Pancreatic cancer is a good example of a cancer for which early detection is crucial, since roughly 85% of patients have their cancer diagnosed at an advanced stage.

However, research that leads to extensive validation to produce actionable screening methods must be distinguished. There are a great deal of emerging liquid biopsy technologies that, although promising, require extensive clinical validation before even population-based screening can be justified.

Single-Cell Sequencing Lets You See Into a Tumor

When people think of tumors, they usually think of a malignant growth made up of the same types of cells — however, this is not true.

A tumor can be a mixture of many different populations of cells, including cancer cells and other immune cells, fibroblasts, blood vessel cells, and various other components of the tumor.

This is just one of the many reasons why treating cancer is very difficult.

Thanks to advances in technology, researchers are able to sequence every single cancer cell in the population instead of just looking at the average cell.

Researchers can now detect cell subpopulations that would usually be very difficult to identify.

This can help researchers better understand why cancer cells are resistant to therapy, how cancer cells are evading the immune system, and which cell subpopulations are contributing to treatment failure and tumor recurrence.

Artificial Intelligence Technology Focused on Oncology

In today's world of modern diagnostics, a single patient can generate an abundance of data, including genomic sequencing, pathology images, scans, laboratory results, numerous therapies, and several layers of molecular data.

It can be very overwhelming to make sense of all this data.

This is where artificial intelligence and machine learning are becoming very relevant.

AI models can be used in numerous areas like:

• Analyzing pathology and medical imaging
• Recognizing patterns in genomic and multi-omics data
• Making prognostic estimates
• Determining the likelihood of potential biomarkers
• Helping estimate treatment responses
• Identifying potential new drug targets

Research models such as Stanford's MUSK show ways that different types of medical data can be integrated using multiple forms of AI to help in predicting cancer prognoses and treatments.

The potential for AI in oncology is more likely to predict cancer treatment outcomes in order to help clinicians rather than to replace oncologists.

A New Generation of Cancer Treatments

While the foundation of modern cancer treatment remains traditional surgery, radiotherapy and chemotherapy, new treatment modalities are rapidly being developed.

Antibody-Drug Conjugates

Antibody-Drug Conjugates (ADCs) are molecules where an antibody is conjugated with an anti-cancer drug.

The antibodies direct the drug to cancer cells.

ADCs have been the focus of active research in the last few years following approved clinical studies.

Bispecific Antibodies

Bispecific antibodies can engage two distinctive cell types.

Some can engage immune cells and target cancer cells.

New therapeutics using bispecific antibodies have been developed to target many resistant and difficult-to-treat tumors, such as lung cancers.

mRNA Cancer Vaccines

Another area adapting new technologies developed for vaccines is oncology.

Unlike preventive vaccines, therapeutic cancer vaccines work by teaching the immune system to recognize components of an existing tumor.

Personalized mRNA vaccines could be designed to target mutations of an individual patient's cancer.

Promising clinically relevant results have been found when personalized mRNA vaccines are administered with checkpoint inhibition in melanoma, further encouraging the extension of these therapies to more extensive clinical trials.

PROTACs

In the field of oncology, PROTAC design is based on proteolysis-targeting chimeras (PROTACs).

Unlike conventional drugs, which typically aim to block the disease-associated protein, PROTACs aim to be a part of the cell's protein degradation machinery and induce the targeted protein to be degraded.

Unconventional targets of cancer-associated proteins could therefore potentially be addressed.

Cancer Research Is Becoming More Disease-Specific

While the focus of cancer research is largely still on systemic methods, more targeted methods are beginning to develop.

There are ADCs with HER2-targeted delivery for breast cancer that provide a new avenue for many breast cancer patients.

With targeted therapies and immunotherapies, there are biomarkers for gastric cancer that are HER2, PD-L1, and the presence of microsatellite instability that aid in guiding therapies.

Cervical cancer still has many opportunities in prevention with better HPV prevention, with newer methods of cervical cancer screening through molecular means and DNA methylation, as well as with the growing presence and integration of AI in medicine.

For cancers that are difficult to treat, like pancreatic cancer, research is looking at many biological aspects of the cancer, especially genomic, transcriptomic, proteomic, immune and circulating biomarkers.

How Treatment Resistance Makes Cancer Difficult to Treat

Cancer remains challenging to treat for many reasons, but one of them is the malignancy of cancer cells.

Due to the nature of how cancer cells are, they inevitably become more chemoresistant over time, meaning that treatment may work for a short period of time on a population of the cells, but the treatment will not be effective in the long run.

This is largely due to some of the cells surviving the treatment.

The focus of much research is finding ways to detect these cells and create therapies for all of the resistance mechanisms.

One of the draws of combination therapy is the idea that if there are multiple therapies attacking different biological mechanisms of the same cancer, then the inherent resistance will not be enough to defeat the therapies.

The Future of Cancer Research Relies on Integration

It is unlikely that the best opportunities to advance cancer research will stem solely from one innovation.

DNA sequencing yields incredible amounts of data that help in understanding a patient's cancer. However, DNA sequencing data does not provide a complete understanding of a patient's tumor.

Two tumors that share the same mutation may behave differently due to a multitude of factors, such as the tumors' individual gene expression, protein activity, the tumor microenvironment, and other biological factors.

The next generation of precision oncology is focused on the interdisciplinary integration of multiple data sources.

Each of the "omics" platforms describes a different aspect of the tumor: genomics describes the tumor DNA; transcriptomics describes active tumor genes; and proteomics describes tumor proteins, as well as signaling pathways.

Single-cell technologies describe the cells where a biological signal is produced.

Liquid biopsies may characterize how the tumor may have changed and evolved over time.

These multi-omics datasets may be extremely large and impossible to fully understand, but thanks to artificial intelligence, rudimentary analyses of these datasets may be possible to perform.

Integrating multiple data sources may help clinicians shift from simply understanding cancer types to better understanding the individualized tumor drivers.

Major Challenges Remain

While scientific innovations continue to emerge, many obstacles remain before realizing their potential to improve patient outcomes.

Immunotherapy is quite effective for some cancers, but for many patients, it is not. Cellular therapies are beginning to penetrate solid tumors, but drug resistance and cancer's intrinsic plasticity continue to be an obstacle.

Cost and accessibility are also major considerations.

Advanced diagnostics are significantly more expensive and technologically advanced, while many potentially curative cancer therapies are available only in high-income countries. Meanwhile, lower- and middle-income countries have a disproportionate global burden from cancer and do not have adequate screening, pathology, diagnostics, and therapeutics.

This next phase of innovation also has to figure out how to get these things to the clinic, and how to price them appropriately and in an accessible manner.

Evolving from Curing Cancer to Knowing Cancer

This is perhaps the most important mental concept in oncology.

Understanding that cancer is about as far from being a single disease — or even hundreds of diseases — as you can get. Cancer is more precisely understood as thousands of different biological systems that can change over time for each person or population.

The future of cancer treatment will probably be continued personalized, data-driven and multi-disciplinary.

Immunotherapy can be used. Genomic data can be used. Further layers in the biology of a tumour can be encompassed by multiple omics techniques. Cancer can be monitored by liquid biopsy. The complex datasets can be integrated by AI. The difficulties of targeting various aspects of cancer biology are likely to be alleviated with the introduction of new therapeutic technologies.

Considering that these emerging technologies are inadequate for targeting cancer on their own, wild speculation would suggest that the true value of these technologies is in their ability to be integrated synergistically.

This thinking is likely to sum up some of the more innovative projects in cancer research.

Rather than treating cancers of the same type in the same manner, these new research projects hope to discover the unique biology of an individual's cancer.

References

Recent findings on the progress in therapeutics for cancer, as well as immunotherapy, precision oncology, and genomic and multi-omic technologies, as well as single-cell sequencing, epigenetic modifications, cancer vaccines, nanotechnology-based theranostics, and research on oncology specific to different illnesses, have been the basis for the development of this article. This includes the works of Krishnatreya et al. (2026), Oluwajembola & Zakari (2025), Kumar & Raza (2025), Kciuk et al. (2023), Huang & Ma (2023), Lavoro & Ricci (2025), Akram & Abdullah (2025), Chekaoui & Garofalo (2024), Gupta & Roy (2024), Xu & Cao (2024), Guan & He (2023), Vincze & Spada (2025), and Dowling & Efstathiou (2023).

This article is not a substitute for medical care. It is for educational and informational purposes only. No medical treatment is being recommended for any type of cancer, and no medical advice is being provided. Treatment is best decided by a qualified health care professional.