Prognostic Gene Expression Profiles in Breast Cancer

Kristina Pilekær Sørensen

Publikation: AfhandlingPh.d.-afhandling


Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group and offered systemic adjuvant therapy, and 50% of these patients receive chemotherapy. However, approximately 25-30% of the lymph node negative and 50% of the lymph node positive high risk patients would experience recurrence if left untreated with systemic adjuvant therapy. Consequently, considerable overtreatment occurs, especially in the lymph node negative group of patients. There is still a lack of robust biomarkers to predict prognosis and the benefits from different treatments.
Long non-coding RNAs represent a novel class of non-coding RNAs, which are differentially expressed in cancer with different clinical courses, and they may be useful as novel prognostic biomarkers in breast cancer.
The aim of the present project was to predict the development of metastasis in lymph node negative breast cancer patients by RNA profiling. We collected and analyzed 82 primary breast tumors from patients who developed metastasis and 82 primary breast tumors from patients who remained metastasis-free, by microarray gene expression profiling. We employed a nested case-control design, where samples were matched, in this study one-to-one, to exclude differences in gene expression based on tumor type, tumor size, hormone receptor status, histological grade, age of patient at diagnosis, and year of surgery. All patients included in the study had not received any kind of systemic adjuvant therapy; hence, the study results were not influenced by treatment response.
We compared lncRNA expression in metastatic and non-metastatic primary tumor samples and showed that lncRNA expression profiles could distinguish metastatic patients from non-metastatic patients with an accuracy of 76%. Furthermore, we found that the classification within estrogen receptor (ER) positive patients was independent of traditional prognostic markers and the time of event.
Previous findings have shown that high expression of the lncRNA HOTAIR is correlated with poor survival in breast cancer. We validated this finding by demonstrating that high HOTAIR expression in our primary tumors was significantly associated with worse prognosis independent of prognostic markers, an association that was even stronger when looking only at ER positive tumor samples.
In addition, we examined the protein-coding RNA expression in the 82 pairs of tumor samples and validated the performance of existing RNA profiles in the present dataset.
This retrospective study, presents a valuable dataset for detecting independent prognostic markers not influenced by treatment response.
In the future, breast cancer treatment will increasingly be based on the molecular profiling of tumors, which hopefully will reduce overtreatment in the large group of lymph node negative breast cancer patients.
StatusUdgivet - 14. feb. 2014