Abstract 2671
Background
Homeobox (HOX) family consists of 39 genes which act as master regulators in embryonic development. Each of the genes is also known to play key roles in progression of breast cancer, including epithelial to mesenchymal transition, tumor angiogenesis and endocrine therapy resistance. Although there are numerous reports on individual HOX genes and cancer, none of them have comprehensively analyzed the whole gene family. Since HOX genes strongly coordinate within the family during the embryonic period, we considered that the analysis of the whole HOX family is also indispensable in breast cancer.
Methods
We collected 702 breast cancer data from four publicly available array datasets (GSE11121, GSE7390, GSE3494, GSE2990) and performed unsupervised hierarchal clustering into two clusters by the expression of HOX genes. We constructed model formulas for cluster prediction by dividing the samples into learning and validation groups. We used three machine learning methods: support-vector machine (SVM), neural network and Bayes. The model formulas were validated by validation samples. We also used 512 TCGA breast cancer data to calculate covariations of the genes in breast cancer.
Results
By the clustering of four array datasets, the DFS of the two clusters in PAM50-classified luminal B patients were statistically different (p = 0.016), and the gene ontology analysis revealed that the Wnt pathway was activated in the poor prognostic cluster. All cluster prediction models for luminal B sample achieved accuracies of over 90%. From TCGA breast cancer data, we found that HOX genes covariate the most with other HOX genes, especially within the chromosomally proximal groups.
Conclusions
Comprehensive analysis of the whole HOX family lead to the prediction of luminal B breast cancer prognosis. Considering that Wnt signaling controls HOX genes during the embryonic stage, we suppose a Wnt pathway activated, poor prognostic subgroup in luminal B breast cancer which can be identified by the expression of HOX genes. The cluster prediction model by machine learning was acceptable for its future adaptation in clinical settings. We also proved that HOX genes strongly covariate within the gene family in cancer, not only during the embryonic stage.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
5383 - A pilot trial to investigate the impact of a personalised self-management lifestyle programme using mobile technology on the health and wellbeing of cancer survivors
Presenter: Mary Grace Kelly
Session: Poster Display session 3
Resources:
Abstract
5084 - The BRIGHTLIGHT national survey of the impact of specialist teenage and young adult cancer care on caregivers’ information and support needs
Presenter: Rachel Taylor
Session: Poster Display session 3
Resources:
Abstract
4328 - Life beyond cancer: Occupational health care service support in returning work experienced by cancer survivals
Presenter: Minna Nurmi
Session: Poster Display session 3
Resources:
Abstract
3337 - Investigating the factors related to primary caregivers' burden in oncology patients in Greece
Presenter: Ourania Govina
Session: Poster Display session 3
Resources:
Abstract
3387 - Factors Influencing the Level of Emotional Support from Nurses Perceived by Patients Undergoing Haematopoietic Stem Cell Transplantation in Protective Isolation
Presenter: Michela Piredda
Session: Poster Display session 3
Resources:
Abstract
935 - Progressive Muscle Relaxation and Guided Imagery Techniques and the Way of Coping of Parents of Children with Malignancies: A randomized controlled trial
Presenter: Tsitsi Theologia
Session: Poster Display session 3
Resources:
Abstract
3457 - Pharmacist and Nurse Led Melanoma Immunotherapy Clinic
Presenter: Dharmisha Chauhan
Session: Poster Display session 3
Resources:
Abstract
5160 - Measuring the impact of the Irish Cancer Society's Cancer Information Services
Presenter: Aileen McHale
Session: Poster Display session 3
Resources:
Abstract
4297 - It's Great to Talk
Presenter: Noreen Andersen
Session: Poster Display session 3
Resources:
Abstract
4444 - Impact of Burn-Out Syndrome in Oncology personnel and its improvement through specific interventions
Presenter: Inmaculada Ortega
Session: Poster Display session 3
Resources:
Abstract