Skip to content
  • About
  • Contact
  • Contribute
  • Book
  • Careers
  • Podcast
  • Recommended
  • Speaking
  • All
  • Physician
  • Practice
  • Policy
  • Finance
  • Conditions
  • .edu
  • Patient
  • Meds
  • Tech
  • Social
  • Video
    • All
    • Physician
    • Practice
    • Policy
    • Finance
    • Conditions
    • .edu
    • Patient
    • Meds
    • Tech
    • Social
    • Video
    • About
    • Contact
    • Contribute
    • Book
    • Careers
    • Podcast
    • Recommended
    • Speaking

What Netflix can teach us about treating cancer

Elana Fertig, PhD
Conditions
May 4, 2017
Share
Tweet
Share

Two years ago, former President Barack Obama announced the Precision Medicine initiative in his State of the Union Address. The initiative aspired to a “new era of medicine” where disease treatments could be specifically tailored to each patient’s genetic code.

This resonated soundly in cancer medicine. Patients can already manage their cancer with therapies that target the specific genes that are altered in their particular tumor. For example, women with a type of breast cancer caused by the amplification of gene HER2 are often treated with a therapeutic called herceptin. Because these targeted therapeutics are specific to cancer cells, they tend to have fewer side effects than traditional cancer treatments with chemotherapy or radiation.

However, such treatments are not available for most cancer patients. In many cancers, the specific genetic alterations that are responsible for a cancer remain unknown. To create individualized cancer treatments, we must know more about the functional genetic alterations.

With data on cancer genetics growing rapidly, mathematics and statistics can now help unlock the hidden patterns in this data to find the genes that are responsible for an individual’s cancer. With this knowledge, physicians can select appropriate treatments that block the action of these genes to personalize therapies for individual patients. My research aims to improve precision medicine in cancer – by building on the same methods that have been used to find patterns in Netflix movie ratings.

Sifting through the data

Today, there is unprecedented public access to cancer genetics data. These data come from generous patients who donate their tumor samples for research. Scientists then apply sequencing technologies to measure the mutations and activity in each of the 20,000 genes in the human genome.

All these data are a direct result of the Human Genome Project in 2003. That project determined the sequence for all the genes that make up healthy human DNA. Since the completion of that project, the cost of sequencing the human genome has more than halved every year, surpassing the growth of computing power described in Moore’s Law. This cost reduction enables researches to collect unprecedented genetics data from cancer patients.

Most scientific studies on cancer genetics performed worldwide release their data to a centralized, public database provided by the U.S. National Institutes of Health (NIH) National Library of Medicine. The NIH National Cancer Institute and National Human Genome Research Institute have also freely released genetic data from over 11,000 tumors in 33 cancer types through a project called The Cancer Genome Atlas.

Every biological function – from extracting energy from food to healing a wound – results from activity in different combinations of genes. Cancers hijack the genes that enable people to grow to adulthood and that protect the body from the immune system. Researchers dub these the “hallmarks of cancer.” This so-called gene dysregulation enables a tumor to grow uncontrollably and form metastases in distant organs from the original tumor site.

Researchers are actively using these public data to find the set of gene alterations that are responsible for each tumor type. But this problem is not as simple is identifying a single dysregulated gene in each tumor. Hundreds, if not thousands, of the 20,000 genes in the human genome are dysregulated in cancer. The group of dysregulated genes varies in each patient’s tumor, with smaller sets of commonly reused genes enabling each cancer hallmark.

Precision medicine relies on finding the smaller groups of dysregulated genes that are responsible for biological function in each patient’s tumor. But, genes may have multiple biological functions in different contexts. Therefore, researchers must uncover a set of “overlapping” genes that have common functions in a set of cancer patients.

Linking gene status to function requires complex mathematics and immense computing power. This knowledge is essential to predict of outcome to therapies that would block the function of these genes. So, how can we uncover those overlapping features to predict individual outcomes for patients?

What Netflix can teach us

Fortunately for us, this problem has already been solved in computer science. The answer is a class of techniques called “matrix factorization” – and you’ve likely already interacted with these techniques in your everyday life.

In 2009, Netflix held a challenge to personalize movie ratings for each Netflix user. On Netflix, each user has a distinct set of ratings of different movies. While two users may have similar tastes in movies, they may vary wildly in specific genres. Therefore, you cannot rely on comparing ratings from similar users.

ADVERTISEMENT

Instead, a matrix factorization algorithm finds movies with similar ratings among a smaller group of users. The group of users will vary for each movie. The computer associates each user with a group of movies to a different extent, based upon their individual tastes. The relationships among users are referred to as “patterns.” These patterns are learned from the data, and may find common rankings unforeseen by movie genre alone – for example, users may share a preference for a particular director or actor.

The same process can work in cancer. In this case, the measurements of gene dysregulation are analogous to movie ratings, movie genres to biological function and users to patients’ tumors. The computer searches across patient tumors to find patterns in gene dysregulation that cause the malignant biological function in each tumor.

From movies to tumors

The analogy between movie ratings and cancer genetics breaks down in the details. Unless they are minors, Netflix users are not constrained in the movies they watch. But, our bodies instead prefer to minimize the number of genes used for any single function. There are also substantial redundancies between genes. To protect a cell, one gene may easily substitute for another to serve a common function. Gene functions in cancer are even more complex. Tumors are also highly complex and rapidly evolving, depending upon random interactions between the cancer cells and the adjacent healthy organ.

To account for these complexities, we have developed a matrix factorization approach called Coordinated Gene Activity in Pattern Sets – or CoGAPS for short. Our algorithm accounts for biology’s minimalism by incorporating as few genes as possible into the patterns for each tumor.

Different genes can also substitute for one another, each serving a similar function in a different context. To account for this, CoGAPS simultaneously estimates a statistic for the so-called “patterns” of gene function. This allows us to compute the probability of each gene being used in each biological function in a tumor.

For example, many patients take a targeted therapeutic called cetuximab to prolong survival in colorectal, pancreatic, lung and oral cancers. Our recent work found that these patterns can distinguish gene function in cancer cells that respond to the targeted therapeutic agent cetuximab from those that do not.

The future

Unfortunately, cancer therapies that target genes usually cannot cure a patient’s disease. They can only delay progression for a few years. Most patients then relapse, with tumors that are no longer responsive to the treatment.

Our own recent work found that the patterns that distinguish gene function in cells that are responsive to cetuximab include the very genes that give rise to resistance. Emerging immunotherapies are promising and appear to cure some cancers. Yet, far too often, patients with these treatments also relapse. New data that track the cancer genetics after treatment is essential to determine why patients no longer respond.

Along with these data, cancer biology also requires a new generation of scientists who can bridge mathematics and statistics to determine the genetic changes occurring over time in drug resistance. In other fields of mathematics, computer programs are able to forecast long-term outcomes. These models are used commonly in weather prediction and investment strategies.

In these fields and my own previous research, we have found that updates to the models from large datasets – such as satellite data in the case of weather – improve long-term forecasts. We have all seen the effect of these updates, with weather predictions improving the closer that we are to a storm.

Just as tools from computer science used can be adapted to both movie recommendations and cancer, the future generation of computational scientists will adopt prediction tools from an array of fields for precision medicine. Ultimately, with these computational tools, we hope to predict tumors’ response to therapy as commonly as we predict the weather, and perhaps more reliably.

Elana Fertig is an assistant professor of oncology biostatistics and bioinformatics, Johns Hopkins University, Baltimore, MD. This article was originally published on The Conversation. Read the original article.

Image credit: Shutterstock.com 

The Conversation

Prev

Widespread hype gives false hope to many cancer patients

May 3, 2017 Kevin 5
…
Next

Doctors aren't cops: We need to change gunshot reporting

May 4, 2017 Kevin 21
…

Tagged as: Oncology/Hematology

Post navigation

< Previous Post
Widespread hype gives false hope to many cancer patients
Next Post >
Doctors aren't cops: We need to change gunshot reporting

ADVERTISEMENT

ADVERTISEMENT

ADVERTISEMENT

Related Posts

  • Hormone replacement therapy is still linked to cancer

    Martha Rosenberg
  • Cancer care costs everyone too much. What can we do about it?

    Andrew Hertler, MD
  • We have a shot at preventing cervical cancer

    Lisa N. Abaid, MD, MPH
  • Including the patient perspective on tumor boards

    Don S. Dizon, MD
  • Obstruction of medical justice: How health care fails patients with cancer

    Miriam A. Knoll, MD
  • Despite progress in cancer care, cost and equity challenges still must be addressed

    David M. Aboulafia, MD

More in Conditions

  • Nurses aren’t eating their young — we’re starving the profession

    Adam J. Wickett, BSN, RN
  • What if medicine had an exit interview?

    Lynn McComas, DNP, ANP-C
  • Finding healing in narrative medicine: When words replace silence

    Michele Luckenbaugh
  • Why coaching is not a substitute for psychotherapy

    Maire Daugharty, MD
  • Why doctors stay silent about preventable harm

    Jenny Shields, PhD
  • Why gambling addiction is America’s next health crisis

    Safina Adatia, MD
  • Most Popular

  • Past Week

    • Why removing fluoride from water is a public health disaster

      Steven J. Katz, DDS | Conditions
    • When did we start treating our lives like trauma?

      Maureen Gibbons, MD | Physician
    • Mastering medical presentations: Elevating your impact

      Harvey Castro, MD, MBA | Physician
    • Nurses aren’t eating their young — we’re starving the profession

      Adam J. Wickett, BSN, RN | Conditions
    • Why what doctors say matters more than you think [PODCAST]

      The Podcast by KevinMD | Podcast
    • The hidden incentives driving frivolous malpractice lawsuits

      Howard Smith, MD | Physician
  • Past 6 Months

    • Why tracking cognitive load could save doctors and patients

      Hiba Fatima Hamid | Education
    • What the world must learn from the life and death of Hind Rajab

      Saba Qaiser, RN | Conditions
    • The silent toll of ICE raids on U.S. patient care

      Carlin Lockwood | Policy
    • Addressing the physician shortage: How AI can help, not replace

      Amelia Mercado | Tech
    • Why medical students are trading empathy for publications

      Vijay Rajput, MD | Education
    • Bureaucracy over care: How the U.S. health care system lost its way

      Kayvan Haddadan, MD | Physician
  • Recent Posts

    • Nurses aren’t eating their young — we’re starving the profession

      Adam J. Wickett, BSN, RN | Conditions
    • Why wanting more from your medical career is a sign of strength

      Maureen Gibbons, MD | Physician
    • U.S. health care leadership must prepare for policy-driven change

      Lee Scheinbart, MD | Policy
    • Why the pre-med path is pushing future doctors to the brink

      Jordan Williamson, MEd | Education
    • Why the fear of being forgotten is stronger than the fear of death [PODCAST]

      The Podcast by KevinMD | Podcast
    • How a rainy walk helped an oncologist rediscover joy and bravery

      Dr. Damane Zehra | Physician

Subscribe to KevinMD and never miss a story!

Get free updates delivered free to your inbox.


Find jobs at
Careers by KevinMD.com

Search thousands of physician, PA, NP, and CRNA jobs now.

Learn more

Leave a Comment

Founded in 2004 by Kevin Pho, MD, KevinMD.com is the web’s leading platform where physicians, advanced practitioners, nurses, medical students, and patients share their insight and tell their stories.

Social

  • Like on Facebook
  • Follow on Twitter
  • Connect on Linkedin
  • Subscribe on Youtube
  • Instagram

ADVERTISEMENT

ADVERTISEMENT

ADVERTISEMENT

ADVERTISEMENT

  • Most Popular

  • Past Week

    • Why removing fluoride from water is a public health disaster

      Steven J. Katz, DDS | Conditions
    • When did we start treating our lives like trauma?

      Maureen Gibbons, MD | Physician
    • Mastering medical presentations: Elevating your impact

      Harvey Castro, MD, MBA | Physician
    • Nurses aren’t eating their young — we’re starving the profession

      Adam J. Wickett, BSN, RN | Conditions
    • Why what doctors say matters more than you think [PODCAST]

      The Podcast by KevinMD | Podcast
    • The hidden incentives driving frivolous malpractice lawsuits

      Howard Smith, MD | Physician
  • Past 6 Months

    • Why tracking cognitive load could save doctors and patients

      Hiba Fatima Hamid | Education
    • What the world must learn from the life and death of Hind Rajab

      Saba Qaiser, RN | Conditions
    • The silent toll of ICE raids on U.S. patient care

      Carlin Lockwood | Policy
    • Addressing the physician shortage: How AI can help, not replace

      Amelia Mercado | Tech
    • Why medical students are trading empathy for publications

      Vijay Rajput, MD | Education
    • Bureaucracy over care: How the U.S. health care system lost its way

      Kayvan Haddadan, MD | Physician
  • Recent Posts

    • Nurses aren’t eating their young — we’re starving the profession

      Adam J. Wickett, BSN, RN | Conditions
    • Why wanting more from your medical career is a sign of strength

      Maureen Gibbons, MD | Physician
    • U.S. health care leadership must prepare for policy-driven change

      Lee Scheinbart, MD | Policy
    • Why the pre-med path is pushing future doctors to the brink

      Jordan Williamson, MEd | Education
    • Why the fear of being forgotten is stronger than the fear of death [PODCAST]

      The Podcast by KevinMD | Podcast
    • How a rainy walk helped an oncologist rediscover joy and bravery

      Dr. Damane Zehra | Physician

MedPage Today Professional

An Everyday Health Property Medpage Today
  • Terms of Use | Disclaimer
  • Privacy Policy
  • DMCA Policy
All Content © KevinMD, LLC
Site by Outthink Group

Leave a Comment

Comments are moderated before they are published. Please read the comment policy.

Loading Comments...