Cancer is a disease of the genome, originating from an accumulation of changes in a cell’s DNA. These alterations, known as mutations, are like typos in the body’s instruction manual. Not all genetic mutations carry the same weight; some are inconsequential, while others can initiate the uncontrolled cell growth that characterizes cancer. The process begins when a single cell acquires a mutation that allows it to divide more rapidly than its neighbors. As this cell and its descendants divide, they accumulate more mutations, creating a diverse population of cells within a tumor.
Distinguishing Passenger from Driver Mutations
At the heart of cancer genetics is the difference between two categories of mutations: drivers and passengers. A driver mutation is a genetic alteration that provides a direct growth advantage to a cell, actively contributing to cancer development. These mutations often occur in genes responsible for controlling cell division, repairing DNA damage, or initiating programmed cell death. For example, a mutation in a proto-oncogene like KRAS can act like a stuck accelerator pedal, causing constant cell division, while a mutation in a tumor suppressor gene like TP53 is like disabling the brakes.
In contrast, a passenger mutation is a genetic change that does not confer any selective growth advantage and has no direct role in promoting cancer. These mutations are effectively “along for the ride” in a cell that is already dividing uncontrollably due to one or more driver mutations. As a cancer cell lineage expands, its DNA replication machinery can become faulty, leading to a higher overall mutation rate. Passenger mutations are the byproducts of this genomic instability, accumulating randomly across the genome.
Identifying Mutations in the Genome
Scientists distinguish between driver and passenger mutations through large-scale DNA sequencing and computational analysis. The process begins by reading the complete DNA sequence, or genome, of cancer cells from a patient’s tumor. This cancer genome is then compared to the DNA from the patient’s healthy, non-cancerous cells. This comparison reveals the somatic mutations—those acquired during a person’s lifetime that are present only in the tumor.
Once this list of mutations is generated, bioinformaticians use algorithms to determine which are drivers and which are passengers. A primary indicator of a driver mutation is recurrence; if the same mutation is found in the same gene across many patients with the same type of cancer, it is likely a driver. For instance, specific mutations in the BRAF gene are found in over half of all melanomas, strongly suggesting they drive the disease. Passenger mutations, on the other hand, appear more randomly and are less likely to be shared among patients.
The Cumulative Effect of Passenger Mutations
While individual passenger mutations are neutral, their sheer number can have significant consequences. A high accumulation of these mutations is referred to as a high “tumor mutational burden” (TMB). The collective presence of passenger mutations can contribute to genomic instability, making the cancer cell’s DNA more fragile and prone to acquiring even more mutations. This process can inadvertently create a more aggressive cancer by increasing the probability that a new driver mutation will arise.
This accumulation of mildly damaging mutations can also create a “tug-of-war” within the cancer cell. Some evidence suggests that a very high passenger load can become detrimental to the cancer itself, slowing its progression. Each mutation, even if it has a small, slightly negative effect, adds to a cumulative burden that can impair the function of various proteins. The cancer cell must balance the growth advantage from its driver mutations against the collective drag created by thousands of passenger mutations.
This concept refines the simple “harmless” definition of passenger mutations. The total number of mutations provides insights into the tumor’s history and the processes that have shaped its evolution. For example, cancers caused by specific mutagens, like ultraviolet light in melanoma, often have an extremely high mutational burden, with the vast majority being passenger mutations. Understanding this burden is an important aspect of cancer biology.
Therapeutic and Research Applications
The landscape of passenger mutations within a tumor has practical applications in medicine. One of the most significant is in immunotherapy. The immune system identifies and attacks cells that display foreign-looking proteins on their surface. Passenger mutations can alter a cell’s proteins, creating novel fragments called neoantigens that the immune system can recognize as “non-self.”
Tumors with a high mutational burden, and therefore many passenger mutations, produce a wider variety of these neoantigens. This makes the cancer more visible to the immune system and a better candidate for treatments like immune checkpoint inhibitors. These drugs work by releasing the natural brakes on immune cells, allowing them to attack the tumor more effectively. In this context, passenger mutations serve as the targets that enable the body’s defenses to eliminate the cancer.
The unique pattern of passenger mutations in a tumor can also act as a “barcode” or “fingerprint” for that cancer. Researchers use this signature to track the cancer’s evolution over time. By sequencing different parts of a tumor or analyzing samples taken at different times, scientists can trace how a cancer spreads and how its genetic makeup changes in response to treatment. This information helps in understanding drug resistance and tumor recurrence, guiding the development of more adaptive treatment strategies.