Breast cancer is the second largest cause of cancer-related death amongst women in America. Scientific research suggests that around 80% of these cancers are ER+ and 64% of them are at earlier stages.
Now, researchers have found a way to identify new biomarkers for breast cancer that have the capability of predicting if cancer will return after treatment. The technology can base its findings on routinely checked tissue biopsy samples of early-stage breast cancer. The technology is a huge contribution towards Cancer Biomarkers Market as it would help against the recurrence of cancer and save a lot of female lives that succumb to the deadly disease of breast cancer.
The team stated that the key to determining breast cancer is a collagen which is a common protein present throughout the human body, even breast tissue. Previous studies indicate that college network is related directly to aggressive breast cancer. However, through the present study, researchers have provided concrete evidence of collagen’s critical role. The feat was attained with the aid of standard biopsy slides and artificial Intelligence (AI).
The team used machine-learning technology and analyzed a dataset of digitized tissue samples taken from breast cancer patients. Through experiments, they proved that a well-ordered arrangement of collagens is a prognostic biomarker against the presence of an aggressive tumor and the prevalence of a recurrence of the disease.
Further, researchers showed that broken-down or disordered collagen infrastructure is a positive indication and, in fact, also promotes a better outcome. The team also discovered that a disordered collagen network prevents the tumor from transporting out of the breast tissue denoting a less likely chance of return once cancer treatments like chemotherapy ends.
Collagen fibers play an important role in tumor migration to other body parts. The best way to understand the concept is to consider collagen a ‘highway,’ and if it is in bad shape, the transportation would be hard, and if it is smooth and organized, the tumor will find it easy to migrate.
The team revealed that their project should be considered important as it brings forth two things –
Provides validation to other published work findings that suggested similarly that highly organized collagen would probably lead to a worse prognosis.
The present work was accomplished through digitized images of simple tissue slides indicating that the approach could eventually become an essential tool for a pathologist. At present, methods that examine and investigate the collagen architecture need the use of an electron microscope which is expensive as well as scarce.
At last, the method makes predicting outcomes possible and could be made widely available to doctors and those hospitals which do not have great funding to afford advanced imaging microscopes. Thus, the development is rather interesting as it can provide a physician all the information needed for treating aggressive cancer.
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