Tumor evolution predicts clinical outcomes

Cancer never stands still. Since its nature is self-serving, it is always up to something. Prostate cancer tumor cells busy themselves with multiplying (tumor volume gets bigger) and/or mutating in increasingly dangerous directions (tumor progresses and becomes more aggressive). While there are many proponents of a new theory that Gleason 3+3 prostate cancer may not be a “true” cancer because it does not “behave” like one, I am including it in this article.

Tumor evolution

Both tumor growth and progression are just two aspects of what is called tumor evolution. Tumor evolution is complex, and one of the problems of studying the underlying genomics is the difficulty of getting sequential tumor samples from a patient over time. Because of this, “…most studies have inferred tumor evolution from single time-point samples, providing very indirect information. These data have led to several competing models of tumor evolution: linear, branching, neutral and punctuated.” [i] In brief, here’s what these terms mean:

  1. Linear evolution theorizes that as tumor cells create clones, a dominant type emerges. Then this type clones itself, producing a still more dominant type that outcompetes the previous type. Thus, aggression develops in a linear manner that selects for the most dominant emerging type.
  2. Branching evolution posits that multiple cell types can emerge from a single ancestor clone, with parallel evolution as each type achieves “fitness” with its environment. This leads to diverse cell lines within a single tumor. In the case of prostate cancer, which has been shown to evolve in branching fashion, we often find multiple biopsy samples that contain different clonal lines. DNA sequencing of a cell from each different type reveals that each has a unique mutation history.
  3. Neutral evolution is similar to branching evolution in which multiple mutations occur simultaneously and clone themselves, but with no significant dominant clonal line, or increase in tumor aggression.
  4. Punctuated evolution hypothesizes that instead of sequential mutations developing over time, multiple brief bursts of genomic abnormalities occur during the earliest stage of tumor development, a sort of “big bang” theory. What happens next is that “…one or a few dominant clones stably expand to form the tumor mass.”[ii]

New study uses tumor evolution for prostate cancer prognosis

An ongoing problem in diagnosing prostate cancer is the difficulty in identifying which cancers are unlikely to be life-threatening because they are slow growing – the majority of cases – and which are potentially lethal and require immediate, aggressive treatment. Without the ability to determine which is which, the traditional treatment approach is to clobber the entire prostate gland (surgical removal, radiation, or whole-gland ablation).

A new study offers a model using tumor evolution to accurately predict how an individual’s cancer will behave. A research team from the Canadian Prostate Cancer Genome Network (CPC-GENE) analyzed the whole genome sequences from 293 cases of localized prostate cancer.

Next, they used machine learning (a type of artificial intelligence) to deduce the each tumor’s evolutionary history. They used this information to predict how it would evolve. “They found that those tumours that had evolved to have multiple types of cancer cells, or subclones, were the most aggressive. Fifty-nine percent of tumours in the study had this genetic diversity, with 61 per cent of those leading to relapse following standard therapy.”[iii]

Using this method, the team could identify which patients do not need to be treated at the time of diagnosis, which patients would do well with existing treatments, and which have dangerous cell lines that might benefit from new systemic or immunologic therapies.

The value of tumor evolution

This is an important and unique study because it examines a tumor’s history in order to project its future. Unlike some of the current genomic tests that capture biomarkers at a fixed moment in time, the CPC-GENE analysis views each tumor, together with its clones, as a dynamic process. It’s like the difference between a snapshot and a movie. If it’s possible to extrapolate where it’s been by its trail of mutations, it makes sense that predicting the tumor’s next steps can help doctor and patient match the treatment to the disease.

Next to preventing cancer from ever occurring, beating it at its own selfish evolutionary game is a great strategy.

[i] Davis A, Gao R, Navin N. Tumor evolution: Linear, branching, neurtral or punctuated? Biochim Biophys Acta. 2017 Apr; 1867(2): 151–161.

[ii] Ibid.

[iii] “Landmark study links tumor evolution to prostate cancer severity.” Brinkwire, April 20, 2018.