Using Innovative Lab Software to Assess Biomarkers in the Seed and Soil Hypothesis of Metastasis

Designed to Cure

seed and soilMetastasis in cancer is serious, and hard to track until it has taken hold. Researchers are working on discovering biomarkers that will help oncologists better predict the destination of new metastases. Image Source: Wikimedia Commons: National Cancer Institute

“Seed and soil” sounds far too benign to ever be used as a term to describe the spread of cancer, but it is the reigning theory around how cancer prepares to plant it’s metastatic seeds. Metastatic cancers continue to be a problem. Scientists are beginning to discover different factors, such as oxygen level, that may contribute to metastasis,1  but earlier predictors are needed to save lives.

By looking at the “seed and soil” hypothesis, it may be possible to draw blood and predict whether cancer is about to go metastatic and where mets will grow based on a variety of different biomarkers. By better predicting the movement of cancer through the body, oncologists will be able to diagnose metastatic cancers more quickly. This may lead to faster and more effective treatments. In recent years, innovative lab software has begun to provide researchers with better insight into this novel set of biomarkers.  

When Cancer Goes Metastatic

The metastasis of cancer to other, more distant body parts, is characteristic of advanced cancer; in fact, metastasis is the main cause of death in those battling cancer. To go from a single tumor to multiple ones, there are a number of hurdles that need to be overcome. These include:

  • Evading immune response,
  • Creating tumor-initiating seeds,
  • Breaking free of the initial tumor and
  • Adapting to supportive niches.2  

Although this sounds like a sophisticated system of evolution, the accuracy/efficiency of the cancer’s development is more akin to a shot in the dark. Since cancer, specifically metastasis, is the product of multiple mutations; most mutations observed in cancerous cells are passenger mutations (along for the ride), whereas very few are driver mutations (confer survival of cancerous cells). It takes a few tries before cells can actually become metastatic and even more before they can find somewhere to create a new home. This is an open window of time where, if spotted early enough, physicians may most proactively prevent the spread of cancer throughout the body.

Metastases are currently treated similarly to primary tumors. Physicians will use broad strokes in attempts to strike down cancer throughout the body. Generally, this uses therapeutics such as chemotherapy, hormone therapy, surgery, biological therapy, radiation therapy or a combination of a few different methods.3 Once things get to an advanced stage, the tumors tend to be treatment resistant. Through the aid of innovative lab software, researchers may be able to isolate cancer biomarkers from the slew of patient specific cancer data that many institutions are collecting and use that information to alter the approach to metastases.

Diagnosing Metastases

Current diagnosis and awareness of metastases depend on things such as auxiliary symptoms related to the location of new tumors and imaging tests, such as MRIs, X-rays, ultrasounds and PET/CT. What if physicians had the means to diagnose and treat metastases before they took hold? A potential indicator that researchers are working to better identify is the presence of circulating tumor cells (CTCs); however, the number of CTCs, which are cancer cells found in the blood of cancer patients, far exceed the number of metastases. In fact, different types of pseudo metastatic cells may be present in patients for years without any development of a secondary tumor. Although it doesn’t guarantee an additional tumor, it can present indicators of the potential for tumors to arise, and perhaps researchers will discover that CTCs in addition to other biomarkers are indicative of a metastatic event.

One theory proposes that cancer prepares a microenvironment more suitable for the growth of cancer. This is the “soil” component to the seed and soil hypothesis. This presents the opportunity for researchers to examine commonalities observed in the body prior to metastasis and potentially designate biomarkers as indicators of an impending metastatic event. This may sound minor, but it would be a huge stride forward in the way both scientists and clinicians approach cancer. Over the course of many years, clinicians and scientists have collected copious amounts of biological information from patients.

With the aid of modern lab software, researchers will be able to look at commonalities between metastases, both site-based and otherwise. For the first time, they will have the capability to model potential therapeutics to prohibit host cells from preparing to nurture metastases. This may come in the form of assessing antibodies and their therapeutic potential. Modern lab software can assist scientists with assessing activity data correlation and developability predictions. Moving forward, it can assist with further predictive analytics and bioinformatic workflow support. Research came move a great distance forward as investigators move towards innovative software and away from standard paper notebooks.

Treating and Preventing Metastases

Among the many abnormalities observed in tumors, primary or otherwise, is the interesting way in which they attempt to deal with angiogenic blood vessels to support their growth. A number of vascular endothelial growth factor-(VEGF)-induced angiogenesis have been developed in hopes of dealing with the growth and spread of tumors. In cases of non-small cell lung cancer (NSCLC) and colon cancer, dramatic pre-clinical results were observed when using bevacizumab (an anti-VEGF monoclonal antibody therapy) in addition to chemotherapy, but researchers have failed to reproduce those results clinically.4  Additionally, There is mounting evidence that both host and tumor cells contribute to the resistance of therapies that are designed to block the VEGF signalling pathway.

There are obviously other factors at play in host cells that contribute to making a cozy environment for new tumors. With the aid of modern lab software, scientists will be able to better track and assess which biomarkers from existing patient data are indicative of a shift in the severity and metastatic nature of the cancer. Processing a tissue sample is the quick part of this process; often, scientists get bogged down in the lengthy analysis trying to sort through and compare results against other samples. Innovative lab software now provides bioinformatic workflow support, which  will allow researchers to automate scientific data analysis and rapidly explore, visualize results, imaging and statistical model information from patient tissue samples. These technological advances may move these endeavors further, faster allowing for retention of R&D dollars for future research.  

Additionally, researchers may be able to create ways to eliminate or target these new sites that cancer attempts to furnish for additional tumors. BIOVIA Designed to Cure can assist in the design and tracking of therapeutics. The Designed to Cure industry solution experience delivers collaborative, knowledge-driven innovation and predictive analytics to address challenges, such as those associated with sifting through decades of patient data to pluck out important commonalities surround metastases. Please contact us today to learn more about how our software options can support the efforts of your lab.

  1. Oxygen Plays a Critical Role in Cancer Metastasis,” August 3, 2016, http://www.genengnews.com/gen-news-highlights/oxygen-plays-critical-role-in-cancer-metastasis/81253040/
  2. “Metastatic colonization by circulating tumor cells,” January 21, 2016,  http://www.nature.com/nature/journal/v529/n7586/full/nature17038.html
  3. “Metastasis,” 2015, http://www.cancercenter.com/terms/metastasis/
  4. “The seed and soil hypothesis revisited – the role of tumor-stroma interactions in metastasis to different organs,” June 1, 2011, http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3075088/