Understanding Tumor Cell Evolution to Target Metastasis

Reading time: 4 minutes

Megan Majocha

Breast cancer is the most common cancer and it is the second leading cause of cancer-related deaths among women in the United States1. Women with breast cancer have a 5-year survival rate of 99% if the tumor remains localized in the breast, but survival drops to 30% if women have distant metastatic disease2. Metastasis occurs when tumors in one anatomical site like the breast spread to other secondary sites, such as the brain, bone, liver, and lung. Metastasis is a complex, multi-step process where tumor cells survive and adapt to the environment of the secondary site before colonizing to form lesions. While treatment for non-metastatic cancers is improving, cancer metastasis remains a challenge to overcome. This highlights the need for a better understanding of the processes that regulate and drive metastasis to improve patient survivability. 

Cancer initiates from changes to the DNA sequence that cause cells to grow uncontrollably, and tumors continue to acquire more mutations as they evolve over time. It was originally suggested by Peter Nowell in the 1970s that this accumulation of mutations may drive metastasis3, however, this explanation is not as simple as it sounds. Primary tumors are heterogeneous and consist of several different populations of cells whose genetics are distinct from each other, which are known as subclones, each of which may have different biological properties3. These subclonal populations may either grow or become extinct as tumor cells evolve. The most commonly accepted theory is that late-arising clones eventually acquire all the necessary characteristics to disseminate and colonize secondary sites, though there is also evidence of early dissemination in some tumor types4. Genetic heterogeneity between primary tumors and metastases offers insight into the biology of metastatic processes by highlighting metastasis-specific genetic events that may play a role in their formation. However, gaining a comprehensive understanding of the process is complicated because not all patients have the same genetic alterations in metastases, and these changes continue to accumulate as a tumor cell clone multiplies into a cluster of tumor cells. 

Tumor cells can disseminate from the primary site either very early or late in the metastatic cascade. Tumor cells that disseminate too early can reach a metastatic site before surgery or successful treatment. It has been shown that early disseminating cells are more metastatically competent than late disseminating cells in mouse models of a subtype of breast cancer5,6. The ability of tumor cells to disseminate early has clearly been shown, but whether clinically relevant metastases can be formed from these cells remains uncertain. In contrast, other studies argued that tumor cells disseminate from the primary site late within the metastatic cascade. For example, a study showed that there were very few mutations unique to primary tumors compared to their matched metastases, suggesting that these tumor cells disseminated late during the primary tumor evolution7. These studies suggest that there is no universal model for metastatic spread. The timing of dissemination can vary from patient to patient and may depend on their given disease subtype, which also makes treating metastases more challenging.

More recently, a study was performed in mouse models of metastatic breast cancer comparing the DNA sequence between primary mammary tumors and metastases arising within the same animal. Analysis of this sequencing data identified several mutations occurring in the metastatic tumor but not the original mammary tumor, suggesting their importance in metastasis specifically, and not tumor initiation. Interestingly, several of these recurrent metastasis-specific mutations were found in genes that participate in the same cellular growth pathway. This suggests that specific DNA mutations can drive metastasis, and single genes or pathways exist that may be viable targets for treating metastatic disease. 

While targeted therapies are effective in targeting and attacking specific types of cancer cells, metastases are heterogeneous and consist of different tumor cell clone populations. One targeted therapy does not fit all. Today, prognostic tests are used in the clinic to identify specific gene expressions based on research showing that transcriptional profiles from primary tumor tissues can predict patient outcomes. However, a majority of information in current clinical trials is obtained from primary tumor tissue, not metastases. Therefore, understanding genetic heterogeneity in metastasis is critical in improving the design of metastasis-targeted therapies. The sequencing of primary tumor samples has identified genes that are frequently mutated across tissue types, likely representing “tumor drivers”, mutations that cause cancer cells to evolve. To develop metastasis-specific therapies, larger-scale studies and more samples derived from patient metastatic lesions are needed to identify genetic driver events that contribute to the evolution of subclones during the metastatic progression.

Edited by Gabrielle Dardis


  1. American Cancer Society. (n.d.). Retrieved October 25, 2022, from https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2022.html
  2. Cancer of the breast (female) – cancer stat facts. SEER. (n.d.). Retrieved October 25, 2022, from https://seer.cancer.gov/statfacts/html/breast.html 
  3. Nowell PC. The clonal evolution of tumor cell populations. Science 194, 23–28 (1976).
  4. Hunter KW, Amin R, Deasy S, Ha NH, Wakefield L. Genetic insights into the morass of metastatic heterogeneity. Nat Rev Cancer 4, 211-223 (2018). 
  5. Hosseini H et al. Early dissemination seeds metastasis in breast cancer. Nature 540, 552–558 (2016).
  6. Harper KL et al. Mechanism of early dissemination and metastasis in Her2+ mammary cancer. Nature 540, 588–592 (2016).
  7. Yates LR et al. Genomic evolution of breast cancer metastasis and relapse. Cancer Cell 32, 169184.e7 (2017). 

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