The first genetic changes leading to breast cancer could appear many decades before it is discovered—as far back as early puberty—according to a Korean study of whole-genome sequences from more than 1000 tumors.
The findings, in Nature, reveal unique insights into the mutational landscape of breast cancer, and the heterogeneous and complex genomics of this disease.
The research highlights novel oncogenic alterations in breast cancer and identifies novel driver genes, recurrent gene fusions, structural variants, and copy number alterations.
It also reveals several pattern-driven genomic features that could potentially be used as biomarkers for predicting the clinical utility of cancer treatments.
“Our findings highlight the potential of whole-genome analysis for advancing precision oncology for breast cancer,” reported Yeon Hee Park, PhD, from Sungkyunkwan University School of Medicine in Seoul, and co-workers.
They added: “Integrating genomic data with detailed clinical outcomes paves the way for more personalized and effective treatment strategies, with the ultimate aim of improving outcomes for patients.”
Recent advances in genomic technology are helping to unravel the genetic complexities of breast cancer, facilitating personalized treatment approaches to improve outcomes. Yet the molecular landscape of breast cancer remains only partially understood.
Traditional approaches, such as those involving targeted sequencing, mostly focus on individual mutations in known cancer genes. They also miss significant information outside the targets and other pattern-based markers, such as most genomic rearrangements, copy number alterations, and mutational signatures.
In contrast, whole-genome sequencing (WGS) captures the full spectrum of genetic changes but its clinical significance to date often remains unclear due to insufficient integration with clinical records.
With this in mind, the researchers sequenced and analyzed the whole genomes of 1364 breast cancers from Korean patients and combined this with information in full medical records.
Results showed that pattern-driven genomic features, including mutational signatures, homologous recombination deficiency, tumor mutational burden and tumor heterogeneity scores, were associated with clinical outcomes.
This highlighted their value of these potential predictive biomarkers for clinical evaluation of treatments such as CDK4/6 and HER2 inhibitors, as well as adjuvant and neoadjuvant chemotherapy.
In particular, the study revealed the potential of homologous recombination DNA repair deficiency (HRD) as a predictive biomarker for treatment response, particularly in adjuvant chemotherapy for triple-negative breast cancer and first-line CDK4/6 inhibitor treatment for patients with advanced hormone receptor-positive breast cancers.
HRD predicted a better response to the former but worse prognosis to the latter, which the researchers say highlights the nuanced role of HRD across different treatment contexts.
A key mutational process in cancer is structural variation, which acts to amplify, delete or reorder chromosomal material at scales that range from single genes to entire chromosomes.
The team found that most of the recurrent long-segmental copy number amplification (CNA) patterns were acquired when recent common ancestral cells of a cancer emerge, which should be decades earlier than tumor diagnosis.
“This implies that acquisition of the long-segmental CNAs is an early evolutionary event in breast cancer, which is presumably acquired in early puberty,“ the researchers reported.
The findings also suggested that full neoplastic transformation can take decades from the first event of genomic instability.
In addition to WGS, transcriptome sequencing data were incorporated for 88.6% of these individuals.
This enabled the expression of acquired genomic variants to be tracked and the stratification of these cancers into five prediction analysis of microarray 50 (PAM50) subtypes: luminal A; luminal B; HER2-enriched; basal-like and normal-like.
These patients were characterized by a younger median age, at 44 years, and lower proportions of estrogen receptor-positive (ER+)/luminal A subtypes compared with breast cancer cases in Western countries, which the researchers say make it a distinct population for investigation.
The researchers noted that WGS offers a more comprehensive approach than traditional pathology assessments using small tumor samples, enabling detection of diverse genetic alternations including subclonal mutations.
“This comprehensive analysis provides a quantitative understanding of tumor heterogeneity, capturing the full genetic diversity within tumors and aiding in the prediction of treatment responses,” they explained.
“Given these advantages, we anticipate that WGS-based quantitative assessment of tumor heterogeneity, both at diagnosis and during progression, will have a critical role in shaping future precision oncology strategies.”
