By Professor Adrian Lee
How can heterogeneity in breast cancer metastasis highlighted research in transcriptomics help patients? So this year at SABCS (San Antonio Breast Cancer Symposium) we learned a lot about the heterogeneity of breast cancer. It's helped us to understand the heterogeneity, and there was lots of talks and posters on new techniques and allow us to unravel the molecular features that have gone wrong in breast cancer and that's helping us then direct therapies to them, and many of the clinical trials are using these new targets and then new drugs and showing incredible outcomes. Some of the trials that were positive were super exciting against these new targets that we've now discovered. Some on the estrogen receptor, some on HER2, and then many new targets that are being identified.
So one of the new technologies that's allowing us to interrogate breast cancers is Spatial Transcriptomics, and that's where you look at RNA expression actually spatially in a tumor, say for instance, on a section. Traditionally, we crushed everything up into a blender and you got an average of a signal across a tumor, and now you can actually visualize it.
This allows us to interrogate RNA across the tumor in space and time, and then it's getting us greater kind of granularity about what's gone wrong in the tumor. And that, of course we believe is going to tell us about, the underpinnings of that tumor, new targets, and then how to treat it. This is a brand new technology new in development, quite expensive, but there were lots of posters on it here, some poster discussions. And clearly it's a growing technology that's going to change how we understand breast cancer and then ultimately how we treat breast cancer.
Breast cancer treatment has been aided by understanding different subtypes of breast cancer (e.g. metastatic breast cancer). So we have ER positive versus estrogen receptor negative, which helps us give endocrine therapy. Triple-negative breast cancers get neoadjuvant chemotherapy. That's one type of heterogeneity, but actually within each cancer, there's different types of heterogeneity, different types of tumor cells in that cancer. And the idea is that these new techniques, a better resolution of the different types of cells within the cancer is going to better help us resolve which tumors, which should receive which therapy than ultimately predicting who's going to respond. And then, who's not going to respond. And so a lot of that basic science in the next few years we hope, is going to educate treatments. And there were some studies at this one showing how this heterogeneity is importantly in understanding treatment response.
Breast cancer is a heterogeneous disease, meaning it consists of various tumor forms (e.g. in the tumor microenvironment) with distinct molecular and genetic properties. This heterogeneity has major consequences for the diagnosis, treatment, and prognosis of breast cancer (e.g. metastatic breast cancer).
There are various forms of breast cancer, such as ductal carcinoma in situ (DCIS), invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and inflammatory breast cancer (IBC). Several factors, such as hormone receptor status (estrogen and progesterone receptors) and HER2 status, influence treatment decisions for each subtype (human epidermal growth factor receptor 2).
On the basis of gene expression profiling, breast cancer can also be divided into molecular subgroups. They include the Luminal A, Luminal B, HER2-enriched, and Triple-Negative/Basal cells-like subtypes. Each subtype has distinct molecular characteristics and responds to treatment differently.
In breast cancer, heterogeneity can also be observed within individual tumors, with diverse molecular profiles in various parts of the same tumor. This intratumoral heterogeneity might result in treatment resistance and recurrence of the disease.
Current improvements in genomic research have made it possible to identify additional subtypes and genetic alterations that contribute to the heterogeneity of breast cancer. This has led to the creation of tailored therapy strategies that target the precise molecular abnormalities present in each patient's tumor.
In conclusion, heterogeneity in breast cancer is a difficult subject requiring a thorough comprehension of the disease's molecular and genetic diversity. Classification of breast cancer subtypes (e.g. metastatic breast cancer) and individual tumor heterogeneity is crucial for optimizing treatment methods and enhancing patient outcomes.
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It was a very important study of Spatial Transcriptomics in triple-negative breast cancer and how that associates with clinical outcome. One of the groups from Christo Sotiriou had nearly a hundred triple-negative breast cancers where they did spatial Transcriptomics, looked at the heterogeneity cell types and correlated that with patient response and then recurrence and what they found was now you have this ability to see this resolution that we never had. There was incredible heterogeneity. They found all these different types of cells. I think there was a million of these four different types of clusters within each tumor, and they named these things called ecotypes, which are these types of cells that have special types of features associated with them and correlated that with bad outcome.
And so by understanding which tumors have these ecotypes or bad players in them, we could then think about how those correlate with prognosis like they did in their study, and then maybe how we can then start to target them or identify them and try and interfere with them.
Transcriptomics is the study of the transcriptome, which is the total amount of ribonucleic acid (RNA) present in a sample (cell, tissue, or organ) at a given time. RNA performs a variety of activities within the cell, and analyzing the transcriptome reveals how genes function and whether proteins are created as expected.
In humans, DNA segments are converted into RNA through a process known as transcription, which enables a cell to carry out the "instructions" recorded in the DNA genome. Messenger RNA (mRNA) is created during gene expression as an intermediary between DNA and proteins, whereas non-protein-coding RNAs influence a range of biological processes. The transcriptome of a cell is constantly changing based on its demands.
Either exploratory examination of the complete transcriptome, typically through RNA sequencing (RNA-seq), or selective analysis of known RNAs using techniques such as gene expression panels can be referred to as transcriptomics (GEPs).
GEP tests that assess a subset of RNAs have showed promise in determining prognosis and directing treatment options in cancer, and are currently utilized for this purpose in breast cancer.
In the clinic, GEP tests are already in use, and many more are under development. They are less expensive and simpler to do than entire transcriptome analysis using RNA-seq, which is costly and difficult to run and understand, but they are still useful for identifying possible novel targets for GEPs.
RNA-seq has diagnostic potential, particularly in rare disease contexts where disease-relevant targets are difficult to find and validate. However, clinical implementation necessitates the deployment of particular sequencing technology, the capacity to do the necessary bioinformatics analysis, and the storage of vast amounts of data.
Targeted RNA tests are now the most applicable form of transcriptome analysis for clinical usage, and RNA-seq may be most valuable for informing the development of these tests in many instances. Although RNA-seq has the potential to be a powerful diagnostic tool for certain illnesses, it is not yet suitable for routine usage on patients, and its utility remains to be determined. Some samples have been preserved by the 100,000 Genomes Project for future transcriptome analysis, which should inform the future clinical deployment of transcriptomics.
So he also had a study on lobular breast cancer where he looked at the different cell types and heterogeneity in, in lobular breast cancer, and had this interesting finding where tumor cells interacting with other tumor cells, and the stroma actually then correlates with prognosis. We also had a poster discussion as well where we interrogated mixed lobular ductile cancers, which are incredibly complex and poorly understood. But with this new technology, we can start to resolve these different cell types. And in that we found similar to their studies they're incredibly complex, but we can now start to define the features of them. And we believe that understanding the features of this mix, ductal, lobular, will help the physician understand, okay, should I be treating the lobular component or the doctoral component? And ultimately done in bigger studies and bigger subsets, we believe this is going to educate treatment.
I think we're going to see more of these studies in the next SABCS (San Antonio Breast Cancer Symposium). I think for a while we are going to uncover more heterogeneity of breast cancer. This is a good thing, we're going to understand the basics of the disease and the different cell types and the different molecular pathways. This will get complicated for physicians to understand. There's no doubt about that, but we hope that's going to lead to new treatment targets and ultimately, we will then resolve that and reduce that down to simplicity such that we can then move those into clinical tests and then help direct therapies and give predictive and prognostic biomarkers.
Adrian Lee, PhD - About The Author, Credentials, and Affiliations
Professor Adrian Lee is the Director of the Institute for Precision Medicine, a collaboration between UPMC and the University of Pittsburgh to advance scientific research into customized health and clinical care.
Dr. Lee joined the University of Pittsburgh in 2010 as a Professor of Pharmacology and Chemical Biology, as well as a Professor of Human Genetics. Dr. Lee earned his B.Sc. and Ph.D. in England before moving to San Antonio for postdoctoral research. He was then recruited by Baylor College of Medicine and, more recently, the University of Pittsburgh.
Dr. Lee has played a vital role in defining precision medicine research at the University of Pittsburgh and individualized care at UPMC since his arrival in 2010. Early success in precision medicine at Pitt and UPMC includes pharmacogenomics research and application, as well as the creation of computational systems and architecture for clinical and genomic data exchange at both the University of Pittsburgh and the UPMC healthcare system.
Dr. Lee's lab seeks to apply fundamental cell and molecular research findings to the understanding and treatment of breast cancer. This includes research into the role of insulin-like growth factors in breast cancer, as well as the discovery of biomarkers for these targeted therapies. Dr. Lee has investigated the impact of intratumor heterogeneity on breast cancer prognostic tests and is currently leading an initiative to DNA sequence metastatic tumors of the breast in order to find vulnerabilities for innovative precision medicines.
Dr. Lee has over 120 peer-reviewed academic articles to his credit. His lab is also financed by the Department of Defense, Susan G. Komen for the Cure, the Breast Cancer Research Foundation, and other organizations. Dr. Lee is on the Susan G. Komen for the Cure Scientific Advisory Council. Dr. Lee is a member of various national peer-review committees and the Editorial Boards of several periodicals.