For much of the history of oncology, cancer was classified and treated primarily according to the organ in which it originated. Lung cancer, breast cancer, colon cancer, or kidney cancer were approached as a single disease. However, advances in molecular biology have shown that even two tumors located in the same organ can behave in completely different ways, to the point of responding oppositely to the same treatment. This reality has driven the development of precision medicine, a model that seeks to select therapies according to the specific biological characteristics of the tumor and the patient.
Precision medicine is based on a fundamental idea: each cancer has a specific combination of genetic alterations, changes in gene expression, abnormal proteins, immune signals, and characteristics of its own microenvironment. These differences influence the speed of tumor growth, its ability to invade other tissues, its sensitivity to medications, and the mechanisms it uses to escape the immune system. For this reason, modern diagnosis is no longer limited to observing cells under a microscope, but also seeks to include molecular analyses and other types of testing aimed at discovering what drives disease growth within a broader landscape.
From the organ of origin to the molecular profile
Traditionally, treatments were selected according to the location and histological type of the tumor. Although this information remains essential, it can now be complemented with tests that look for mutations, amplifications, gene fusions, and other molecular alterations. Some of these abnormalities act as true “switches” that keep cancer-cell proliferation signals activated. When a relevant alteration is identified, a drug designed to block it may be used.
This change has made it possible to move from an approach focused exclusively on tumor type toward biomarker-driven strategies. In certain situations, the same molecular alteration may appear in tumors originating in different organs. This means that patients with apparently different cancers could benefit from the same targeted treatment. This gave rise to so-called histology-independent therapies, in which the therapeutic decision is based on a shared molecular characteristic and not only on the part of the body where the cancer appeared.
One of the most representative historical examples is the development of imatinib for Philadelphia chromosome-positive chronic myeloid leukemia. This alteration produces an abnormal protein called BCR-ABL, which continuously sends growth signals to leukemia cells, promoting disease progression. By blocking this protein, imatinib transformed a very unfavorable prognosis into a condition that, in many patients, can be controlled for years. This case demonstrated that identifying and targeting a specific molecular alteration could radically change the course of a cancer.
The tools of precision oncology
Next-generation sequencing, known as NGS, makes it possible to analyze dozens, hundreds, or even thousands of genes simultaneously. Using a tumor sample, these tests can detect alterations potentially related to cancer growth or to the response to certain medications. However, finding a mutation does not automatically mean that an effective treatment exists. Some alterations are true drivers of the disease, while others are secondary changes without a clear therapeutic role.
In addition to genomics, precision medicine uses other layers of information. Transcriptomics studies the RNA molecules produced by genes and makes it possible to determine which genes are active or inactive at a given time. This is useful because a gene may be present in the DNA but not necessarily expressed at a meaningful level. Proteomics, in turn, analyzes the proteins produced by cells, which are responsible for carrying out many biological functions. Integrating DNA, RNA, and protein data can provide a more complete view of tumor behavior.
Immune information has also become increasingly important. Biomarkers such as PD-L1 expression, immune infiltration, microsatellite instability caused by defects in DNA repair systems, and tumor mutational burden can help estimate the likelihood of response to certain immune checkpoint inhibitors. However, none of these markers is perfect. Some patients with apparently favorable results do not respond, while others may benefit even when they do not meet the expected criteria.
Liquid Biopsy: Tumor information in the blood
One of the most promising technologies is liquid biopsy. Tumors can release small fragments of DNA into the bloodstream, known as circulating tumor DNA, or ctDNA. Through a blood sample, it is possible to detect certain genetic alterations without the need to perform a conventional surgical biopsy. This may be especially useful when the tumor is located in a difficult-to-reach area or when insufficient tissue is available.
Liquid biopsy can also help monitor the molecular evolution of the disease. A tumor does not remain static: it changes over time and under the pressure of treatments. Some sensitive cells may disappear, while resistant subclones survive and expand. Repeated ctDNA analysis could reveal these changes and guide a therapeutic modification before progression becomes evident through imaging studies.
However, this technology also has limitations. Some tumors release very small amounts of DNA into the blood, especially when their volume is low. In addition, an alteration detected in plasma must be interpreted within the clinical context, because not all identified variants necessarily come from the tumor. For this reason, liquid biopsy generally complements, but does not completely replace, tumor tissue analysis.
Immunotherapy and personalized treatment
Precision medicine is not limited to drugs directed against genes. It also includes strategies aimed at improving the immune response against cancer. Checkpoint inhibitors, such as antibodies against PD-1, PD-L1, or CTLA-4, help remove certain inhibitory signals used by the tumor to suppress lymphocyte activity. In some patients, they produce profound and durable responses, although a considerable proportion do not obtain significant clinical benefit.
Personalized cell therapies are also being developed. In tumor-infiltrating lymphocyte therapy, immune cells present within the lesion are extracted, expanded in the laboratory, and then administered back to the patient. CAR-T cells are genetically modified to recognize specific proteins on malignant cells. Therapies based on T-cell receptors and NK cells represent other strategies under investigation, especially for tumors that do not respond to conventional treatments; however, they will not be discussed in detail in this blog.
Personalized therapeutic vaccines are another area of development. Tumor mutations can produce abnormal proteins called neoantigens, which are not found in healthy cells. Through genomic analyses and computational tools, it is possible to select some of these neoantigens and create vaccines specifically designed to train the patient’s immune system. Although numerous challenges remain, this concept demonstrates the extent to which treatment can be adapted to the individual biology of each cancer.
Clinical trials designed for a new reality
Clinical trials have also had to evolve. Traditional studies usually test a drug in patients with the same type of tumor. However, when relevant molecular alterations appear in small and scattered groups, this design may be insufficient. Basket trials group patients with different cancers that share a molecular alteration. Umbrella trials, on the other hand, include a single tumor type but assign different treatments according to each patient’s biomarkers.
Master protocols and adaptive studies also exist, allowing several therapies or subgroups to be evaluated within the same structure. Some designs progressively modify patient assignment according to the results obtained during the trial. The goal is to make research more flexible and better aligned with the true complexity of cancer.
The most individualized model is known as “N-of-1,” in which each patient is considered a unique biological case. Instead of using the same combination for everyone, treatment is built around the person’s specific molecular, immune, and clinical alterations. In this context, what is evaluated is not only a particular drug, but the strategy of assigning therapies according to the profile of each tumor.
Figure 1. Genomic, transcriptomic, proteomic, immune, laboratory, clinical, and computational analyses are combined to characterize tumor biology, identify relevant biomarkers, and support personalized treatment decisions.
The major challenge: tumor heterogeneity
One of the main obstacles in precision medicine is that a tumor is not made up of a uniform population of cells. Different subclones with distinct alterations may coexist within the same lesion. In addition, metastases may present molecular differences compared with the primary tumor. A biopsy taken from a single region represents only a small part of a much more complex disease.
This heterogeneity promotes resistance. A treatment may eliminate cells that depend on a specific molecular pathway while allowing other populations capable of using alternative routes to survive. For this reason, blocking a single alteration is not always sufficient. Combination therapies seek to simultaneously target several mechanisms of growth, survival, and immune evasion. However, combining medications can also increase toxicity, drug interactions, and treatment costs.
Another problem is the timing of molecular testing. Many patients undergo sequencing when the disease is already very advanced and their clinical condition has deteriorated. This may prevent them from receiving the selected treatment. Performing molecular profiling earlier, reducing analysis times, and improving access to targeted drugs could increase the likelihood of benefit.
Greater precision does not mean absolute certainty
Precision medicine should not be interpreted as a guarantee of response. The presence of a biomarker may increase the probability that a treatment will work, but it does not eliminate uncertainty. The activity of an alteration depends on the biological context of the tumor, the presence of other mutations, the microenvironment, the immune system, prior exposure to treatments, and the patient’s overall characteristics.
Economic and logistical barriers also exist. Comprehensive genomic tests can be expensive, are not available in every center, and require specialized teams to interpret the results. Molecular tumor boards bring together oncologists, pathologists, geneticists, bioinformaticians, and other professionals to determine which alterations are clinically relevant. Even after a possible option is identified, the drug may not be approved for that indication, may not be available in the country, or may only be accessible through a clinical trial.
The future of cancer treatment
The future of oncology will probably depend on the integration of multiple sources of information. The analysis of tissue, ctDNA, gene expression, proteins, immune cells, and the tumor microenvironment will make it possible to build increasingly detailed models. Artificial intelligence and the analysis of large clinical databases could help recognize response patterns, anticipate resistance mechanisms, and select more rational therapeutic combinations.
Even so, technology must be used with clinical judgment. The objective is not to accumulate molecular data, but to convert it into decisions that improve survival, reduce toxicity, and preserve quality of life. Precision medicine represents a profound transformation in cancer treatment: moving from asking only, “Where did the tumor originate?” to also investigating, “What mechanisms keep it alive, and how can we block them in this patient?”
Each tumor can be considered an ecosystem in constant evolution. Understanding that ecosystem requires examining all of its characteristics in detail. Precision oncology still faces major limitations, but it is bringing medicine closer to a goal that seemed distant for decades: providing the right treatment to the right patient at the right time.
Main reference:
Tsimberidou, A. M., Fountzilas, E., Nikanjam, M., & Kurzrock, R. (2020). Review of precision cancer medicine: Evolution of the treatment paradigm. Cancer treatment reviews, 86, 102019. https://doi.org/10.1016/j.ctrv.2020.102019
Other references:
Tsimberidou A. M. (2015). Targeted therapy in cancer. Cancer chemotherapy and pharmacology, 76(6), 1113–1132. https://doi.org/10.1007/s00280-015-2861-1
Fountzilas, E., Tsimberidou, A. M., Vo, H. H., & Kurzrock, R. (2022). Clinical trial design in the era of precision medicine. Genome medicine, 14(1), 101. https://doi.org/10.1186/s13073-022-01102-1
