Breast Cancer: Signs for the Good, the Bad and the Ugly
Breast cancer is a very heterogeneous disease. Prognosis can be different depending on the type of cancer. Due to a range of biomarkers, therapy outcome nowadays can be estimated quite accurately.
Every breast cancer is of different nature, said presenter Elizabeth Morris from New York, USA. To better handle the many varieties, breast tumors are divided into subgroups. Most common cancer types are luminal A and B tumors that make up around 70% of all breast cancers and have a comparably good prognosis. More aggressiveness is seen in HER2-positive cancers, while poorest prognoses are observed in triple negative cancers, just like basal-like tumors.
All these cancer types have certain biologic characteristics, just like the estrogen and progesterone receptor status or the HER2 status. An additional well-established biomarker is Ki-67 that describes cellular proliferation. “In our institute we don’t use it, but I wish we did,” said Morris, because Ki-67 expression helps to estimate treatment response (TR), as it is positively associated with neoadjuvant therapy (NAC). Ki-67 also helps to discriminate between luminal A and B cancers: Luminal A comes with low Ki-67, while the latter has a high status. “With imaging we can’t differentiate them,” Morris further noted.
Another option to differentiate the two different luminal breast cancer types is using gene expression-based assays like OncotypeDx, Mammaprint or PAM-50. OncotypeDX results reflect a certain risk level being very useful for planning the individual treatment strategy: Low risk tumors, for example, can be treated with hormone therapy only, while high risk tumors definitely need to be treated with chemotherapy.
What MRI is Able to Contribute
Thanks to technical progress, MRI has become a powerful diagnostic tool for breast cancer assessment. Morris highlighted radiomics, a technique that combines imaging data with genomic details. “Radiomic analyses extract information out of the images, that can’t be seen with the eye,” explained Morris. Radiomics allows predicting breast cancer progress almost as accurate as OncotypeDX or PAM50 gene assays.
Radiomics also has become a powerful tool for monitoring neoadjuvant chemotherapy (NAC), as it is able to predict pathologically complete response (pCR) by analyzing texture values before and after chemotherapy. Differences in the texture reflect changes in the tumor and its microenvironment. Morris studied this in 47 patients with operable invasive ductal carcinoma and found significant texture differences in the patients with pCR and without (P<0.001). MRI might also be of help to finally diagnose pCR after NAC by using percutaneous breast MRI biopsy. Currently Morris is evaluating this method. Preliminary results of 15 patients are available. “So far, with those 15 women, we have been dead-on accurate,” she said.
Another MRI biomarker is the background parenchymal enhancement (BPE). Studies indicate that a high BPE corresponds with better treatment outcome. Other signs with predictive value are: spiculated margin, rim enhancement and peritumoral edema; spiculated margins stand for a better outcome, while rim enhancement is associated with worse outcome and peritumoral edema with early metastases. With help of these three features, even triple negative breast tumors can be divided by their disease progress.
According to Morris, the next promising technical developments in MRI will be due to machine learning. Artificial intelligence algorithms may soon predict the malignancy of a lesion and provide great number of details to finally treat women individually.
Elizabeth Morris expects MRI biomarkers to become important tools for predicting the progress of the many cancer varieties non-invasively.
Presentation Title: MR imaging biomarkers for the clinical setting
Speaker: Elizabeth Morris, New York, USA
Date: Thursday, February 28th, 2019
Session Code: RC 502 – A 0234