By Lina carolina 
Stanford, CA – Breast cancers, long understood to exhibit distinct subtypes with varying prognoses and recurrence risks, can now be more comprehensively classified into three principal groups based on fundamental structural variations in their DNA. This groundbreaking research, led by Christina Curtis, PhD, at Stanford Medicine, reveals that these variations, including amplifications of oncogenes and the presence of extrachromosomal DNA (ecDNA), are established early in tumor development and persist as the disease progresses. The findings, published on January 8 in the prestigious journal Nature, offer a potent new framework for understanding tumor evolution, guiding clinical decision-making, and identifying novel therapeutic targets.
This advanced classification system moves beyond traditional receptor-based categorizations, offering a deeper insight into the genomic underpinnings of breast cancer aggressiveness. By dissecting the structural anomalies within tumor DNA, researchers have identified patterns that correlate strongly with clinical outcomes, potentially allowing physicians to better stratify patients for aggressive early intervention or more conservative treatment approaches, thereby optimizing patient care and improving survival rates.
A Deeper Look at Tumor Evolution
For decades, breast cancer classification has primarily relied on the presence or absence of specific protein receptors: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Tumors expressing ER and/or PR are classified as hormone-receptor positive (HR+), while those overexpressing HER2 are HER2-positive. Cancers lacking all three are termed triple-negative breast cancer (TNBC). While this system has been instrumental in guiding treatment, it has limitations, particularly in predicting long-term recurrence risk for certain subtypes.
"My lab has had a long-standing interest in understanding how aggressive breast tumors arise, why they are resistant to therapy and why they are prone to recur in distant organs," stated Dr. Curtis, who is also the RZ Cao Professor and a professor of oncology, genetics, and biomedical data science at Stanford. "This research shows that breast tumors develop key structural variants that set the tumor on its course very early in its development. In short, some are born to be bad. It emphasizes the importance of robust biomarkers and of intervening early in the course of the disease."
The current study builds upon years of research by Dr. Curtis and her team. In 2012, they employed machine-learning techniques to analyze DNA and RNA sequences from patient tumors and healthy cells. This approach revealed 11 clinically significant breast cancer subgroups, significantly expanding the understanding beyond receptor status alone. These subgroups demonstrated varied prognoses, but the precise mechanisms driving these differences remained elusive.
A subsequent study in 2019, involving 75,000 individuals with ER-positive breast cancer, highlighted a persistent risk of recurrence even years after initial diagnosis and treatment. This observation underscored the need for a more granular understanding of risk stratification. Dr. Curtis and her colleagues found that combining receptor status with their previously defined subgroups could predict which HR+ tumors were more likely to recur late. Notably, four of the eight ER-positive subgroups exhibited a significantly higher likelihood of recurrence 10 to 20 years post-diagnosis. This identified a substantial proportion of women with HR+, HER2-negative breast cancer facing a nearly 50% chance of recurrence decades later, a risk comparable to that of HER2-positive breast cancers before the advent of targeted therapies like trastuzumab (Herceptin).
Furthermore, this approach also identified TNBC patients who were unlikely to experience recurrence beyond five years, as well as those at higher risk. This patient stratification is crucial for tailoring treatment intensity and monitoring schedules, allowing for more aggressive interventions for high-risk individuals while potentially sparing others from unnecessary toxicity.
Unveiling Three Core Genomic Architectures
The critical question that remained was what biological mechanisms underpinned these distinct risk profiles. "We wanted to take a step back," Dr. Curtis explained. "Each of the four higher risk subgroups has copy number events — duplications or amplifications of specific oncogenes involving different regions of the genome. These patterns of genomic copy number change were similar to that seen in HER2-positive disease. If we look at these tumors in an unbiased way and deconstruct these different types of mutations, what could we learn about their processes that give rise to these characteristic events? Would we discover something different?"
To address this, the researchers meticulously examined the genomic architecture—the intricate landscape of mutations and structural variations within a cancer cell’s DNA—of nearly 2,000 breast cancers spanning various stages, from early-stage ductal carcinoma in situ (DCIS) to advanced metastatic disease. This comprehensive analysis allowed them to categorize the tumors into three distinct groups based on unique genomic anomalies.
Group 1: Localized Amplifications and Extrachromosomal DNA (ecDNA)
The first major group identified encompasses tumors characterized by complex but localized amplifications of cancer-driving genes, known as oncogenes. Critically, these tumors also frequently harbor extrachromosomal DNA (ecDNA). These are small, circular DNA molecules that exist independently of the main chromosomal genome. In the context of cancer, ecDNA often contains multiple copies of oncogenes and can be rapidly amplified, leading to aggressive tumor growth and resistance to therapy by evading normal cellular regulatory mechanisms. This group strongly overlaps with previously identified high-risk HR+ subgroups and HER2-positive breast cancers.
"Here we have two different molecular subtypes, which we treat differently in the clinic but that strongly overlap in their patterns of chromosomal instability," Dr. Curtis noted. This convergence suggests a shared underlying genomic instability mechanism driving aggressive behavior in these otherwise distinct clinical categories.
Group 2: Global Genomic Instability
The second group is defined by widespread genomic instability, where alterations accumulate across the entire genome. A subset of tumors within this category also exhibits deficiencies in their DNA repair mechanisms. This global genomic chaos leaves the entire genome "scarred" with widespread mutations, rather than being confined to specific oncogenes. This profile is particularly associated with triple-negative breast cancers, which are notoriously aggressive and challenging to treat.
Group 3: Stable Genomes with Typical Recurrence Risks
The third group comprises the majority of hormone-receptor positive, HER2-negative breast cancers that present with typical risks of recurrence. These tumors are characterized by relatively stable genomes, with fewer structural variations and a less chaotic mutational landscape compared to the other two groups.
Early Origins and Enduring Impact
A pivotal finding of this research is that the structural variations defining these three groups are established very early in tumor development, often decades before a clinical diagnosis. These early genomic blueprints are then maintained as the tumor grows, invades surrounding tissues, and metastasizes to distant organs. This early establishment of genomic architecture dictates the tumor’s trajectory and its inherent aggressiveness.
The study also found that these genomic profiles correlate with the tumor’s microenvironment, influencing whether and how immune cells infiltrate and respond to the cancer. This interaction between the tumor’s genomic makeup and the immune system is a critical factor in treatment response and disease progression.
Implications for Clinical Practice and Future Therapies
The implications of this research are far-reaching. The ability to classify breast cancers into these three core genomic groups provides a more precise tool for predicting prognosis and tailoring treatment. For patients with tumors exhibiting global genomic instability, particularly those with DNA repair deficiencies, existing therapies designed for inherited BRCA mutations—which also impair DNA repair—might offer a new avenue for treatment. The researchers speculate that approximately 13% of patients with DNA repair-deficient, ER-positive breast cancers could potentially benefit from such interventions.
Tumors driven by focal oncogene amplifications and ecDNA may be vulnerable to novel compounds that specifically target these drivers or the replication stress they induce. Furthermore, therapies aimed at disrupting the fundamental mutational processes that propagate these genomic alterations could offer another layer of therapeutic intervention.
"These early, sometimes catastrophic mutational events happen decades prior to the diagnosis of the tumor, emphasizing opportunities for earlier interventions," Dr. Curtis emphasized. "Despite the complexity of their genomes, there are constraints and only so many evolutionary paths for a tumor to follow. We now have an understanding of how and when these complex alterations arise and their accompanying vulnerabilities."
This research not only refines our understanding of breast cancer heterogeneity but also opens doors for the development of more personalized and effective treatments. By targeting the fundamental genomic architecture of cancer, clinicians may be able to intercept aggressive disease earlier, improve treatment efficacy, and ultimately enhance the lives of patients.
The study was supported by grants from the National Institutes of Health (CA261719 and CA252457) and the Breast Cancer Research Foundation. Dr. Curtis is a member of Bio-X, the Stanford Cancer Institute, and a Chan Zuckerberg Biohub investigator, underscoring the collaborative and interdisciplinary nature of this significant scientific advancement.