Gene Expression Profiling Signature PAM50 Utility as a Biomarker

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August 9, 2023

The Need for Gene Expression Profiling

Gene expression profiling has emerged as a genomic tool that can help decipher the complexity of cancer subtyping. Conceptually, cancer is a fairly simple disease: cell growth regulation is disrupted, allowing cells to grow indefinitely while dedifferentiating. However, in practice, cancer is highly complex due to the complicated and redundant nature of the cellular machinery necessary for regulating and maintaining proper cell growth. Oncogenesis therefore requires multiple events to overcome the complexity of growth regulation. Add in the variety of cell types in a tissue with the potential to become malignant, creating multiple subtypes of cancer, and the issue is further complicated. Therefore, identifying and characterizing exact subtypes of cancer via its particular molecular signature is a critical challenge making this conceptually simple disease exceptionally complicated to treat.

The Advent of Gene Expression Profiling

Recent years have seen decades of cancer research pay off in the development of more effective treatments that have fewer side effects. Fewer side effects are a consequence of precisely engineered treatments targeted to directly destroy cancer cells, avoiding the indiscriminate killing of all dividing cells. However, the complexity and variety of cancers, even within a tissue such as the breast, means targeted therapies are most effective against only a subset of cancers. It is therefore critical to identify a patient’s particular cancer subtype to select the appropriate treatment. Fortunately, biomarkers for identifying such subtypes have become more sophisticated, especially those comprised of gene expression profiling (GEP).

Understanding Breast Cancer Subtypes with PAM50 Gene Expression Profiling Signature

One of the most effective biomarkers for distinguishing between subtypes of breast cancer is the PAM50 gene expression profiling signature, which consists of 50 genes (plus 8 reference genes) selected to optimize the accuracy of identifying the four major breast cancer subtypes (Luminal A, Luminal B, HER2-enriched, and Basal-like¹). These gene expression-based “intrinsic” subtypes, identified through PAM50 analysis of over 500 archived FFPE breast cancer samples and validated with thousands more samples, have improved not only breast cancer prognosis, but also predictions of patients’ response to therapy.² Its value in distinguishing between subtypes of breast cancer have made it the key component of the FDA-clinically-approved Prosigna™ assay from Veracyte. Moreover, PAM50 is a valuable resource for RUO studies, including translational pharmaceutical research and exploratory endpoints in clinical trials.

The PAM50 gene expression assay differentiates breast cancer into 4 distinct subgroups: Luminal A, Luminal B, HER-2, and Basal-like. A distinct gene expression profile characterizes each breast cancer subtype:

Luminal A tumors have the distinct characteristic of higher levels of estrogen receptor, ER, and therefore tumors belonging to this subtype have increased expressions of genes associated with ER function (PgR, Bcl2, EsR1, and FOXA1).
Luminal B tumors also have higher expression of genes associated with ER function (Bcl2, FOXA1, CCND1, and GATA3); however, they also have higher expression of proliferative genes (CCNB1, CCND1, CCNE1, MYBL2, and MKi67) relative to Luminal A tumors.
HER-2 tumors are characterized by higher expression of ErbB2, epidermal growth factor receptor-2, and genes associated with the HER2 pathway. As a receptor tyrosine kinase, HER-2 promotes cell survival, proliferation, and migration. Proliferative genes include BIRC5, CCND1, CCNE1, ORC6L, and MKi67. In addition, HER-2 subtype tumors overexpress GRB7 which can promote sustained proliferative signaling. Tumors belonging to this subtype are often associated with being more aggressive.
Basal-like tumors do not express ER, PR, and HER2; these tumors overexpress basal cytokeratin 5, 14, and 17 and as such are not sensitive to many conventional therapies, though tumors of this subtype have a better response to chemotherapy compared to other subtypes. EGFR is often overexpressed and correlates with poor patient survival. These tumors display dysregulation in PI3K/AKT, JAK/STAT, and ERK/MAP signaling pathways and have high expression of proliferative genes, such as FOXM1, c-MYC, CCNE1, BIRC5, and CCND1. These tumors also overexpress genes involved in cell cycle progression (CDC20, CDC6) and genes involved in the EGFR pathway.

Heatmap of PAM50 genes in breast cancer subtypes. Gene expression level for each molecular profile are shown in different color according to their relative expression level for each subtype. Highest (red), lowest (green), average expression level (black).
From Bernhardt SM et al., *Front. Oncol.* 14 November 2016:6:241

Exploring Mechanisms of Action

PAM50 has been instrumental in translational research areas, aiding in the discovery of new therapies and further understanding the mechanisms underlying breast cancer. By classifying tumor samples based on PAM50 subtypes, researchers can study candidate drug compounds, identify molecular pathways involved in oncogenesis, tumor suppression, and metastasis. For example, recent studies have utilized PAM50 subtyping to identify novel molecular features and potential target pathways for breast and prostate cancer treatments.³ ⁴ ⁵ Additionally, PAM50 gene expression profile levels can shed light on the mechanisms of action in response to different tumor subtypes. Analysis of the intersection of PAM50 subtype classification with PCS1 classification of prostate cancer was used to identify the ribonuclease reductase small subunit M2 (RRM2) as a potential target pathway for treatment.⁴ These studies can be viewed as a model for PAM50 use in pre-clinical translational cancer research and in early drug development efforts.

Patient Selection and Test Groups

PAM50 has practical applications at all stages of translational research. In pre-clinical research, PAM50 could be valuable by aiding in the identification and selection for test groups in early clinical trials, particularly for combination therapies. It can also assist in selecting appropriate animal models for studying novel treatment combinations.⁶ In translational research programs part of drug discovery and development, analyzing breast cancer subtypes, outcomes, and treatments using PAM50 on archived FFPE patient samples can enhance our understanding of treatment effectiveness for various subtypes.⁷ Such studies can lead to identification of novel treatments or treatment combinations as well as inform clinical trial study design. PAM50’s reliability in breast cancer subtype identification provides valuable information for interpreting results, making PAM50 a valuable gene expression signature. Clinical application of this signatures using Prosigna can help identify patients who would benefit from certain therapies and can avoid associated side effects from ineffective therapies.

Expanding Beyond Breast Cancer

Apart from breast cancer, PAM50 has also been utilized in assessing other types of cancer. The specificity of genes found in the tumor microenvironment allows for considerable overlap in gene expression profiles, molecular mechanisms, of various cancers. Studies have shown PAM50’s prognostic value for specific subtypes in lung and prostate cancers.⁸ ⁹ Similarly, several T cell-specific genes included in the PAM50 signature, including those involved with estrogen receptor signaling, have been identified as part of pan-cancer diagnosis in malignant and nonmalignant tissues.¹⁰ Together, the PAM50 gene expression profile is worth exploring in additional cancer types as a potential biomarker of diagnosis, prognosis, and treatment prediction.

Gene expression profiles are not the only important tumor characteristics. Gene mutations specific to each cancer type play a crucial role as well.¹¹ Classifying breast cancer subtypes for assessing the presence of specific mutations can also be a valuable role when combined with PAM50. Pan-cancer studies such as Nacer et al¹² can be performed for any gene expression profile, including PAM50, to characterize its ability to distinguish between subtypes of any malignant tissue. These uses of PAM50 not only enhance its value, but also contribute to important discoveries about various cancer types, including the identification of potential pathways to target for treatment.

With the increasing prevalence of precision medicine, it is essential to efficiently explore and validate discoveries from basic research and early clinical trials to advance the drug development process. Per Kim et al, “as novel therapeutic agents are developed, the emerging area of investigation that assesses risk-adapted strategies for tailoring the intensity of adjuvant or neoadjuvant therapy with regard to individual risk factors will require accurate and precise biomarkers such as PAM50.”¹³ PAM50 therefore will be a highly useful tool integrating pre-clinical and clinical research, enabling the examination of archived tumor samples, identification of novel candidate drugs, and the exploration of co-therapies and improvements in treatments.

Decoding Single Sample Breast Cancer Biology

Image from the Breast Cancer 360™ Data Analysis Report showing signature scores for a selected sample, with PAM50 subtype in the center.

PAM50 as a Bridge Between Translational and Clinical Research

PAM50, both as the RUO version and Prosigna, serves as a valuable resource for translational researchers. The Prosigna assay provides information about Risk of Recurrence (ROR) for a patient’s breast cancer. Based on the size of the tumor, the molecular subtype, the proliferation status of the tumor, and nodal status, the calculated ROR score is then compared to a validation data (> 2400 pts) for use in prognosis and treatment options. While Prosigna is cleared by the FDA for diagnostic use, PAM50 supports exploratory endpoints in clinical trials and contributes to the understanding of treatment protocols, candidate drugs, and co-therapy options. It plays a crucial role in integrating pre-clinical and clinical research, facilitating advancements in precision medicine.

The Prosigna assay is available via Veracyte. PAM50 is directly accessible through NanoString as a RUO product. PAM50 is supported on the nCounter® Analysis System platform.

Conclusion

As precision medicine continues to advance, biomarkers such as PAM50 will play critical roles in the advancement of patient care. PAM50’s ability to bridge basic research, early translational, and clinical research make it a valuable tool for improving efficiencies in the drug development process. Understanding the comprehensive biomarker information enabled by biomarker assays like PAM50 is crucial for exploring and validating new therapeutic strategies is cancer types exhibiting similar molecular mechanisms.

To learn more about implementing PAM50 in your research, visit our Gene Expression Profiling webpage.

References

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