Tumor profiling: Shifting from DNA to RNA sequencing


Personalized biopsy-driven treatment based on DNA sequencing are in clinical trial for more than ten years. Unfortunately, the response rate is disappointing with only a small percentage of the patient presenting targetable mutation. Recent study shows that profiling RNA, instead to DNA, allows more advanced cancer patients to benefit from personalized therapies, compared to standard mutation testing DNA alone.


All the cells of the human body (more than 10,000 billion) have the same genome and therefore the same genes. This is at least true for healthy cells. What differs from one tissue to another and therefore from one cell to another is the expression of these genes. A gene can be compared to a sentence in the genetic code: it is quite schematically a functional unit of the genome. But it is clear that it contains infinitely more information than a simple sentence: a human gene contains between 500 and several thousand bases, the famous A, T, C and G letters. It is estimated that our genome contains around 25,000 genes, which represents a total of around 3.2 billion bases.

A cancer cell, whatever its tissue of origin, is a cell whose genome is seriously and irreversibly altered. It has become monstrous, both morphologically and behaviorally: it

is insatiable (feeding on sugar and oxygen), aggressive, invasive, destructive, uncontrollable and more or less permanent. The genome of a cancer cell is, therefore, a corrupt version of that of our own healthy cells: from mutation to mutation, cellular DNA changes until it has the characteristics of an irreversible monster genome.


No two cancers are the same. There are a large number of possible genetic mutations for a same tumor. Each tumor, therefore, each patient, is unique and treatments must be individualized. DNA sequencing performed on tumors make it possible to shed light on genetic mutations that cause the appearance and multiplication of cancer cells. Personalized medicine, also called precision medicine, aims to target these specific genetic differences that cause the development and progression of cancer. It doesn't matter which tumor, as long as the genomic analysis finds the gene known to react with the treatment. Personalized medicine has the advantage of inducing fewer side effects as the most effective and/or best tolerated treatment will be chosen based on the tumor genome. Personalized medicine means offering the right treatment at the right time for the right group of patients.



Personalized biopsy-driven treatment based on DNA sequencing are in clinical trial for many cancer sites for more than ten years. Unfortunately, the response rate is disappointing with only a small percentage of the patient presenting targetable mutation.

In the SAFIR-01 trial, Dr. André and colleagues biopsied a metastatic lesion and performed molecular characterization of the metastatic disease. Therapy could be personalized in only 55 patients (13% of all patients in the trial). In the IMPACT (Initiative for Molecular Profiling and Advanced Cancer Therapy) clinical trial, genetic tests were carried out on the tumors of 3,743 patients. Mutations were seen in 1,307 of them. 711 had access to targeted therapy adapted to the biological change in the tumor and 596 did not change treatment because there was no therapy adapted to their specific gene. To this date, all clinical trials based solely on DNA profiling had identified potential treatments for only 5% to 25% of patients.


A recent study shows that profiling RNA, instead of DNA, allows more advanced cancer patients to benefit from personalized therapies, compared to standard mutation testing DNA alone. If DNA is the carrier of our genetic code, RNA is used in cells as an intermediary of genes to make the proteins they need. Most drugs work on very specific components of our body: proteins. Proteins are made from genes. A gene – we won’t repeat it enough - is a piece of DNA. 

This gene can be read, translated, decoded in a long series of biochemical reactions at the end of which a protein emerges. The relationship "one gene = one protein" is not entirely accurate, the biological facts are actually more complex. To be expressed, a gene needs to copy its information in the form of RNA. Thus, if a mutation is present in a gene that is not expressed, targeting this mutation with a specific treatment will be useless. This can explain the low success rate of personalized medicine based only on DNA sequencing.


A new hope for cancer patient emerges from a study that carried out a transcriptomic analysis (tests of RNA expression) in order to personalize the treatment for a larger number of patients, according to the level of RNA expression in tumors compared to normal tissues. 303 patients, who had already received several treatments, took part in the WINTHER trial, the first study by the WIN Consortium (worldwide innovative networking in personalized cancer medicine) published on April 22 in the journal Nature Medicine. Among them, a quarter had already received five or more therapeutic lines. During this study, an evaluation of the target alterations in the DNA of the tumor was carried out initially. Patients who could not benefit from targeted treatment based on DNA damage were referred to a personalized treatment based on the differences in gene expression (RNA) between the tumor and the healthy tissue. The use of a patented algorithm developed by the WIN Consortium allowed the analysis of these differences. Researchers have shown that RNA expression can be used to increase treatment options for patients.


If genome sequencing (all of the DNA) makes it possible to know the nature of the mutations capable of being transmitted from a cell to another, exploration of the transcriptome (all of the RNA) provides information on the genes which are expressed at a given moment in a cell: which mutations are actually expressed and which, while they are written in the DNA of cells, remain silent. But transcriptomic techniques allow also to estimate the level of expression of each gene, that can be affected by mutations. This information helps to better understand the weight of this or that mutation in the biology of the tumor. Deciphering tumor RNA should make it possible to find more detailed actionable data for each patient.