Nav: Home

Machine learning improves the diagnosis of patients with head and neck cancers

September 12, 2019

Researchers from Charité - Universitätsmedizin Berlin and the German Cancer Consortium (DKTK) have successfully solved a longstanding problem in the diagnosis of head and neck cancers. Working alongside colleagues from Technische Universität (TU) Berlin, the researchers used artificial intelligence to develop a new classification method which identifies the primary origins of cancerous tissue based on chemical DNA changes. The potential for introduction into routine medical practice is currently being tested. Results from this research have been published in Science Translational Medicine*.

Every year, more than 17,000 people in Germany are diagnosed with head and neck cancers. These include cancers of the oral cavity, larynx and nose, but can also affect other areas of the head and neck. Some head and neck cancer patients will also develop lung cancer. "In the large majority of cases, it is impossible to determine whether these represent pulmonary metastases of the patient's head and neck cancer or a second primary cancer, i.e. primary lung cancer," explains Prof. Dr. Frederick Klauschen of Charité's Institute of Pathology, who co-led the study alongside Prof. Dr. David Capper of Charité's Department of Neuropathology. "This distinction is hugely important in the treatment of people affected by these cancers," emphasizes Prof. Klauschen, adding: "While surgery may provide a cure in patients with localized lung cancers, patients with metastatic head and neck cancers fare significantly worse in terms of survival and will require treatments such as chemoradiotherapy."

When trying to distinguish between metastases and a second primary tumor, pathologists will usually use established techniques such as analyzing the cancer's microstructure and detecting characteristic proteins in the tissue. However, due to the marked similarities between head and neck cancers and lung cancers in this regard, these tests are usually inconclusive. "In order to solve this problem, we tested tissue samples for a specific chemical alteration known as DNA methylation," explains Prof. Capper who, like Prof. Klauschen, is a Scientific Member of the DKTK in Berlin. He adds: "We know from earlier studies that DNA methylation patterns in cancer cells are highly dependent on the organ in which the cancer originated."

Working with Prof. Dr. Klaus-Robert Müller, Professor for Machine Learning at TU Berlin, the research group employed artificial intelligence-based methods to render this information useful in practice. The researchers used DNA methylation data from several hundred head and neck and lung cancers in order to train a deep neural network to distinguish between the two types of cancer. "Our neural network is now able to distinguish between lung cancers and head and neck cancer metastases in the majority of cases, achieving an accuracy of over 99 percent," emphasizes Prof. Klauschen. He continues: "To ensure that patients with head and neck cancers and additional lung cancers will benefit from the results of our study as quickly as possible, we are currently in the process of testing the implementation of this diagnostic method in routine practice. This will include a prospective validation study to ensure that the new method can be made available to all affected patients."

Having worked alongside the researchers from Charité, the Director of the Berlin Center for Machine Learning (BZML), Prof. Müller, is similarly delighted at their results: "Artificial intelligence is playing an increasingly important role, not only in our daily lives and in industry, but also in natural sciences and medical research. The use of artificial intelligence is, however, particularly complex within the medical field; this is why, until now, research findings have only rarely delivered direct benefits for patients. This could now be about to change."
-end-
*Jurmeister P & Bockmayr M et al., Machine learning analysis of DNA methylation profiles distinguishes primary lung squamous cell carcinomas from head and neck metastases. Sci Transl Med. 2019 Sep 11. doi: 10.1126/scitranslmed.aaw8513

Charité - Universitätsmedizin Berlin

Related Cancer Articles:

Cancer mortality continues steady decline, driven by progress against lung cancer
The cancer death rate declined by 29% from 1991 to 2017, including a 2.2% drop from 2016 to 2017, the largest single-year drop in cancer mortality ever reported.
Stress in cervical cancer patients associated with higher risk of cancer-specific mortality
Psychological stress was associated with a higher risk of cancer-specific mortality in women diagnosed with cervical cancer.
Cancer-sniffing dogs 97% accurate in identifying lung cancer, according to study in JAOA
The next step will be to further fractionate the samples based on chemical and physical properties, presenting them back to the dogs until the specific biomarkers for each cancer are identified.
Moffitt Cancer Center researchers identify one way T cell function may fail in cancer
Moffitt Cancer Center researchers have discovered a mechanism by which one type of immune cell, CD8+ T cells, can become dysfunctional, impeding its ability to seek and kill cancer cells.
More cancer survivors, fewer cancer specialists point to challenge in meeting care needs
An aging population, a growing number of cancer survivors, and a projected shortage of cancer care providers will result in a challenge in delivering the care for cancer survivors in the United States if systemic changes are not made.
New cancer vaccine platform a potential tool for efficacious targeted cancer therapy
Researchers at the University of Helsinki have discovered a solution in the form of a cancer vaccine platform for improving the efficacy of oncolytic viruses used in cancer treatment.
American Cancer Society outlines blueprint for cancer control in the 21st century
The American Cancer Society is outlining its vision for cancer control in the decades ahead in a series of articles that forms the basis of a national cancer control plan.
Oncotarget: Cancer pioneer employs physics to approach cancer in last research article
In the cover article of Tuesday's issue of Oncotarget, James Frost, MD, PhD, Kenneth Pienta, MD, and the late Donald Coffey, Ph.D., use a theory of physical and biophysical symmetry to derive a new conceptualization of cancer.
Health indicators for newborns of breast cancer survivors may vary by cancer type
In a study published in the International Journal of Cancer, researchers from the UNC Lineberger Comprehensive Cancer Center analyzed health indicators for children born to young breast cancer survivors in North Carolina.
Few women with history of breast cancer and ovarian cancer take a recommended genetic test
More than 80 percent of women living with a history of breast or ovarian cancer at high-risk of having a gene mutation have never taken the test that can detect it.
More Cancer News and Cancer Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Listen Again: Reinvention
Change is hard, but it's also an opportunity to discover and reimagine what you thought you knew. From our economy, to music, to even ourselves–this hour TED speakers explore the power of reinvention. Guests include OK Go lead singer Damian Kulash Jr., former college gymnastics coach Valorie Kondos Field, Stockton Mayor Michael Tubbs, and entrepreneur Nick Hanauer.
Now Playing: Science for the People

#562 Superbug to Bedside
By now we're all good and scared about antibiotic resistance, one of the many things coming to get us all. But there's good news, sort of. News antibiotics are coming out! How do they get tested? What does that kind of a trial look like and how does it happen? Host Bethany Brookeshire talks with Matt McCarthy, author of "Superbugs: The Race to Stop an Epidemic", about the ins and outs of testing a new antibiotic in the hospital.
Now Playing: Radiolab

Dispatch 6: Strange Times
Covid has disrupted the most basic routines of our days and nights. But in the middle of a conversation about how to fight the virus, we find a place impervious to the stalled plans and frenetic demands of the outside world. It's a very different kind of front line, where urgent work means moving slow, and time is marked out in tiny pre-planned steps. Then, on a walk through the woods, we consider how the tempo of our lives affects our minds and discover how the beats of biology shape our bodies. This episode was produced with help from Molly Webster and Tracie Hunte. Support Radiolab today at Radiolab.org/donate.