Cancer stem cells: advances in knowledge and implications for cancer therapy

AI Blood Test Can Detect Breast Cancer Early

A groundbreaking screening method combining laser technology and artificial intelligence (AI) has shown promise in detecting breast cancer at its earliest stage, according to researchers at the University of Edinburgh.

This non-invasive technique can identify subtle changes in the bloodstream that occur during the initial phases of the disease, known as stage 1a—changes that current tests cannot detect.

The researchers believe this method could revolutionize early detection and monitoring for breast cancer and pave the way for screening multiple types of cancer.

Early diagnosis is critical, as most cancer-related deaths occur when the disease is identified at a later stage, often after symptoms appear.

Traditional breast cancer screening methods include physical exams, mammograms, ultrasounds, and biopsies. These approaches often depend on factors like age or high-risk group classifications.

In contrast, the new method, which combines laser-based Raman spectroscopy with machine learning, is designed to detect the disease earlier and more effectively.

How the New Test Works

The process begins with shining a laser beam into blood plasma samples. As the light interacts with the blood, a spectrometer analyzes how its properties change.

These changes reveal minute alterations in the chemical makeup of cells and tissues, which are potential indicators of cancer.

Next, a machine learning algorithm analyzes the results. By identifying patterns and features within the data, the AI system helps classify the samples, distinguishing between healthy individuals and those with early-stage breast cancer.

In a pilot study, this technique demonstrated remarkable accuracy. Out of 24 blood samples—12 from breast cancer patients and 12 from healthy controls—the test identified breast cancer at stage 1a with 98% accuracy.

Moreover, it could distinguish between the four main subtypes of breast cancer with over 90% accuracy. This level of precision could enable more personalized treatment plans tailored to each patient's specific cancer type.

Why This Matters

Detecting cancer at such an early stage offers a significant advantage. Treatment is typically more effective when cancer is found early, increasing the chances of survival and reducing the intensity of therapy required.

The ability to identify different cancer subtypes also means treatments can be better targeted, improving outcomes further.

Previous attempts to use similar laser and AI-based approaches for cancer detection have only been able to identify cancers at stage two or later. This new method represents a major step forward.

Future Implications

The researchers aim to expand their work by involving more participants and testing for other cancers in their earliest stages. If successful, this approach could lead to a multi-cancer screening test capable of identifying several types of cancer early.

Dr. Andy Downes, who led the study, explained the importance of the findings: "Early diagnosis is key to long-term survival, and we finally have the technology required.

This test could help find cancers at a stage where they are far more easily treated. The next step is to apply this method to other cancer types and build a comprehensive database."

The study, published in the Journal of Biophotonics, highlights the potential of combining advanced technology with medical research.

Blood samples for the study were provided by the Northern Ireland Biobank and Breast Cancer Now Tissue Bank, and the project involved collaborations with the University of Aberdeen, Rhine-Waal University of Applied Sciences, and other institutions.

While this is an early-stage study with a small sample size, its success shows promise for a future where cancer detection is faster, less invasive, and more accurate.

If developed further, this technology could significantly improve survival rates by identifying cancers before symptoms even appear.

If you care about cancer, please read studies about vitamin D and bowel cancer, and a cautionary note about peanuts and cancer.

For more health information, please see recent studies about the link between ultra-processed foods and cancer, and everyday foods to ward off pancreatic cancer.

The research findings can be found in the Journal of Biophotonics.

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AI-Backed Blood Test Spots Early Breast Cancer Signs

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A new screening method that combines laser analysis with a type of AI is the first of its kind to identify patients in the earliest stage of breast cancer, a study suggests.

The fast, non-invasive technique reveals subtle changes in the bloodstream that occur during the initial phases of the disease, known as stage 1a, which are not detectable with existing tests, the team says.

Edinburgh researchers say their new method could improve early detection and monitoring of the disease and pave the way for a screening test for multiple forms of cancer. 

Disease testing

Standard tests for breast cancer can include a physical examination, x-ray or ultrasound scans or analysis of a sample of breast tissue, known as a biopsy. Existing early detection strategies rely upon screening people based on their age or if they are in at-risk groups.

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Subscribe for FREE Using the new method, researchers were able to spot breast cancer at the earliest stage by optimising a laser analysis technique – known as Raman spectroscopy – and combining it with machine learning, a form of AI. 

Similar approaches have been trialled to screen for other types of cancer, but the earliest they could detect disease was at stage two, the team says. 

Blood samples

The new technique works by first shining a laser beam into blood plasma taken from patients. 

The properties of the light after it interacts with the blood are then analysed using a device called a spectrometer to reveal tiny changes in the chemical make-up of cells and tissues, which are early indicators of disease.

A machine learning algorithm is then used to interpret the results, identifying similar features and helping to classify samples. 

Early diagnosis

In the pilot study involving 12 samples from breast cancer patients and 12 healthy controls, the technique was 98 per cent effective at identifying breast cancer at stage 1a. 

The test could also distinguish between each of the four main subtypes of breast cancer with an accuracy of more than 90 per cent, which could enable patients to receive more effective, personalised treatment, the team says.

Implementing this as a screening test would help identify more people in the earliest stages of breast cancer and improve the chances of treatment being successful, the team says. They aim to expand the work to involve more participants and include tests for early forms of other cancer types.

Most deaths from cancer occur following a late-stage diagnosis after symptoms become apparent, so a future screening test for multiple cancer types could find these at a stage where they can be far more easily treated. Early diagnosis is key to long-term survival, and we finally have the technology required. We just need to apply it to other cancer types and build up a database, before this can be used as a multi-cancer test. - Dr Andy Downes, School of Engineering

The study is published in the Journal of Biophotonics. Blood samples used in the study were provided by the Northern Ireland Biobank and Breast Cancer Now Tissue Bank. It also involved researchers from the University of Aberdeen, the Rhine-Waal University of Applied Sciences and the Graduate School for Applied Research in North Rhine-Westphalia.

Reference: Tipatet KS, Hanna K, Davison-Gates L, Kerst M, Downes A. Subtype-specific detection in stage ia breast cancer: integrating Raman spectroscopy, machine learning, and liquid biopsy for personalised diagnostics. J Biophoton. 2024:e202400427. Doi: 10.1002/jbio.202400427

This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source. Our press release publishing policy can be accessed here.

What Patients With Breast Cancer Can Learn From Germline Testing

An expert spoke with CURE® about the importance of information that can be gained from genetic testing for patients with breast cancer.

Germline testing, or genetic testing of the DNA that a person inherits from their parents, can be a source of information for patients with breast cancer, an expert explained in an interview with CURE®.

"It can tell them if they're positive about their risk for additional breast cancers, so-called second primary breast cancers," explained Dr. Marie Wood. "It can also tell them about [their] risk for other cancers, if they have a mutation that puts them at risk for, say, colon cancer, ovarian cancer, melanoma or pancreatic cancer. This is important because they can then undergo screening or preventative treatments for these cancers."

Despite its importance, uptake of germline testing has been found to be low. A study published in JAMA in 2023 found that, among nearly 1.4 million patients who received a diagnosis of cancer between 2013 and 2019 in California and Georgia, only 6.8% in total underwent germline testing.

Glossary Bilateral mastectomy: the surgical removal of both breasts, an operation also known as a double mastectomy.

Wood is a professor and medical oncologist in the Division of Medical Oncology at UCHealth University of Colorado Hospital in Aurora, Colorado and serves as the medical director for the Hereditary Cancer Program at the University of Colorado Cancer Center. She spoke with CURE® about the importance of obtaining information from germline testing for patients with breast cancer and what these individuals can learn from it.

Transcript:

For screening, patients who have high-risk mutations such as BRCA1 and BRCA2 — and there are others — can instead of just doing annual mammograms after their diagnosis, [can have] annual MRIs. Commonly, we sequence those every six months. For patients who have a high risk of a second primary breast cancer as identified by a germline mutation, they might want to consider bilateral mastectomies at the time of their diagnosis to reduce the risk of additional breast cancers. They might also think about other options, such as removing ovaries if you're at risk for ovarian cancer. Last but not least, we have a new category of drugs called PARP inhibitors. For patients with BRCA2 or BRCA1 mutations, they can take them after diagnosis and reduce the risk for recurrence; if they have metastatic disease and have BRCA1, or BRCA2, or actually a third gene, PALB2, that also offers them treatment options.

Transcript was edited for clarity and conciseness.

For more news on cancer updates, research and education, don't forget to subscribe to CURE®'s newsletters here.

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