ESMO 2017: Strong Association Exists Between Tumour Type and Survival in Early Breast Cancer

Cohort of over 10,000 patients is being followed to determine which of their genetic components associate with metastasis

The risk of death varies in patients diagnosed with early breast cancer depending upon the type of tumour they have, according to findings from an analysis of a large patient cohort in an ongoing study presented at ESMO 2017, the Annual Congress of the European Society for Medical Oncology in Madrid, Spain.

These results also demonstrated that patients with triple negative disease experienced the shortest survival time from progression to metastatic disease and death.

David G. Cox, Cancer Research Center of Lyon (INSERM U1052), Centre Léon Bérard, Lyon, France, and colleagues are conducting this large genome wide association study in 1250 women in the SToRM (NCT01460186) study who experienced metastatic progression from March 2012 to May 2014. The investigators used the Illumina HumanCore Exome chip set, which is composed of over 250,000 variants and was designed to capture common variation across the genome, as well as over 200,000 variants in coding regions.

SToRM was planned to complement the SIGNAL/PHARE (NCT00381901/RECF1098) cohort of over 10,000 patients with early breast cancer, who are being followed through contact with their clinical team to capture information about their treatment and survival to gain information regarding the contribution of the patient’s genetic background to clinically relevant phenotypes in breast cancer metastasis.

Progression to metastasis is observed on an average of just under 6 years from diagnosis

In the SToRM cohort, the average (standard deviation) duration between the primary diagnosis of early breast cancer and the development of metastasis was 58.5 (±73.5) months. A total of 747 patients had the luminal-like tumour type, 249 were HER2-positive, and 194 patients had triple negative breast cancer (TNBC).

As of April 2017, 875 deaths had occurred in the SToRM cohort, and as of July 2017, the median follow-up in the SIGNAL cohort was 3.8 years, and median follow-up was 7 years in the PHARE cohort. In the combined SIGNAL/PHARE cohorts, 1497 patients had progressed by this time, and 154 patients have died.

The investigators found that survival probability was highly associated with tumour type (p = 2.27x10-38), with patients having TNBC demonstrating the shortest median survival after metastatic diagnosis of less than 24 months, whereas median survival for luminal and HER2-positive patients exceeded 36 months.

Thus far, no variants have demonstrated association with survival. However, borderline associations have emerged between a number of variants and survival among patients with TNBC and HER2-positive disease.

Conclusions

According to the authors, knowing how genetic variants influence outcomes in patients with breast cancer may lead to better understanding of breast cancer in general. They are using the SIGNAL/PHARE and SToRM clinical cohorts to determine the genetics and their relationship to treatment response and survival among breast cancer patients.

Furthermore, they concluded that genetic variants associated with response to treatment, and may be useful as stratification variables in future clinical trials.

Aleix Prat of the Medical Oncology Department, Hospital Clínic of Barcelona, University of Barcelona who discussed the study results said that it is probably the first study to link germline SNPs with risk of M1 disease. Identification of DNA regions as prognostic biomarkers seems promising. Further validation in independent cohorts is needed. Further studies looking at the association of SNPs with specific sites of relapse, response to treatment and survival is warranted. Identification of the genes and the biology behind these observations is needed.

Disclosure

This trial was funded by Foundation Cancer de Sein-Parlons On!, INCa.

Reference

LBA15 – Cox D, et al. SToRM: a clinical cohort to identify genetic variability related to metastatic phenotypes.