• HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
Thursday, October 2, 2025
BIOENGINEER.ORG
No Result
View All Result
  • Login
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
No Result
View All Result
Bioengineer.org
No Result
View All Result
Home NEWS Science News Cancer

A new approach to detecting cancer earlier from blood tests: Study

Bioengineer by Bioengineer
November 15, 2018
in Cancer
Reading Time: 3 mins read
0
Share on FacebookShare on TwitterShare on LinkedinShare on RedditShare on Telegram

(TORONTO, Canada, Nov. 14, 2018) – Cancer scientists led by principal investigator Dr. Daniel De Carvalho at Princess Margaret Cancer Centre have combined "liquid biopsy", epigenetic alterations and machine learning to develop a blood test to detect and classify cancer at its earliest stages.

The findings, published online today in Nature, describe not only a way to detect cancer, but hold promise of being able to find it earlier when it is more easily treated and long before symptoms ever appear, says Dr. De Carvalho, Senior Scientist at the cancer centre, University Health Network.

"We are very excited at this stage," says Dr. De Carvalho. "A major problem in cancer is how to detect it early. It has been a 'needle in the haystack' problem of how to find that one-in-a-billion cancer-specific mutation in the blood, especially at earlier stages, where the amount of tumour DNA in the blood is minimal."

By profiling epigenetic alterations instead of mutations, the team was able to identify thousands of modifications unique to each cancer type. Then, using a big data approach, they applied machine learning to create classifiers able to identify the presence of cancer-derived DNA within blood samples and to determine what cancer type. This basically turns the 'one needle in the haystack' problem into a more solvable 'thousands of needles in the haystack', where the computer just needs to find a few needles to define which haystack has needles.

The scientists tracked the cancer origin and type by comparing 300 patient tumour samples from seven disease sites (lung, pancreatic, colorectal, breast, leukemia, bladder and kidney) and samples from healthy donors with the analysis of cell-free DNA circulating in the blood plasma. In every sample, the "floating" plasma DNA matched the tumour DNA. The team has since expanded the research and has now profiled and successfully matched more than 700 tumour and blood samples from more cancer types.

Beyond the lab, next steps to further validate this approach include analysing data from large population health research studies already under way in several countries, where blood samples were collected months to years before cancer diagnosis. Then the approach will need to be ultimately validated in prospective studies for cancer screening.

###

Dr. De Carvalho is a trained immunologist (University of Sao Paulo, Brazil) with postdoctoral training in cancer epigenomics (University of Southern California, USA) whose research focuses on cancer epigenetics. He holds the Canada Research Chair in Cancer Epigenetics and Epigenetic Therapy and is an Associate Professor in Cancer Epigenetics, Department of Medical Biophysics, University of Toronto.

The research was supported by University of Toronto's McLaughlin Centre, Canadian Institutes of Health Research, Canadian Cancer Society, Ontario Institute for Cancer Research through the Province of Ontario, and The Princess Margaret Cancer Foundation.

About Princess Margaret Cancer Centre, University Health Network

The Princess Margaret Cancer Centre has achieved an international reputation as a global leader in the fight against cancer and delivering personalized cancer medicine. The Princess Margaret, one of the top five international cancer research centres, is a member of the University Health Network, which also includes Toronto General Hospital, Toronto Western Hospital, Toronto Rehabilitation Institute and the Michener Institute for Education; all affiliated with the University of Toronto. For more information, go to http://www.theprincessmargaret.ca or http://www.uhn.ca .

Media Contact

Jane Finlayson
[email protected]
416-946-2846
@UHN_News

http://www.uhn.on.ca/

Share12Tweet7Share2ShareShareShare1

Related Posts

Enhancing CAR T Cell Therapy for Solid Tumors

October 2, 2025

Mayo Clinic Advances Dense Breast Cancer Screening and Early Detection Through Innovative Research

October 2, 2025

Dynamic Nomogram Predicts Brain Metastasis in NSCLC

October 2, 2025

Study Reveals Sudan Ebola Virus Can Persist for Months in Survivors, Finds WSU Researchers

October 2, 2025
Please login to join discussion

POPULAR NEWS

  • New Study Reveals the Science Behind Exercise and Weight Loss

    New Study Reveals the Science Behind Exercise and Weight Loss

    91 shares
    Share 36 Tweet 23
  • New Study Indicates Children’s Risk of Long COVID Could Double Following a Second Infection – The Lancet Infectious Diseases

    79 shares
    Share 32 Tweet 20
  • Physicists Develop Visible Time Crystal for the First Time

    74 shares
    Share 30 Tweet 19
  • How Donor Human Milk Storage Impacts Gut Health in Preemies

    64 shares
    Share 26 Tweet 16

About

We bring you the latest biotechnology news from best research centers and universities around the world. Check our website.

Follow us

Recent News

Haya Farmers’ Views on Climate Change Risks in Agriculture

Exploring Amanita Mitochondrial Genomes and Phylogeny

AI-Driven Design of MMP-13 Inhibitors via Docking

Subscribe to Blog via Email

Success! An email was just sent to confirm your subscription. Please find the email now and click 'Confirm' to start subscribing.

Join 60 other subscribers
  • Contact Us

Bioengineer.org © Copyright 2023 All Rights Reserved.

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In
No Result
View All Result
  • Homepages
    • Home Page 1
    • Home Page 2
  • News
  • National
  • Business
  • Health
  • Lifestyle
  • Science

Bioengineer.org © Copyright 2023 All Rights Reserved.