Dataset: Breast Cancer Gene Expression Profiles (METABRIC)

Context

Most of us know someone who struggled with breast cancer, or at least heard about the struggles facing patients who are fighting against breast cancer. Breast cancer is the most frequent cancer among women, impacting 2.1 million women each year. Breast cancer causes the greatest number of cancer-related deaths among women. In 2018 alone, it is estimated that 627,000 women died from breast cancer.

The most important part of a process of clinical decision-making in patients with cancers, in general, is the accurate estimation of prognosis and survival duration. Breast cancer patients with the same stage of the disease and the same clinical characteristics can have different treatment responses and overall survival, but why?

Cancers are associated with genetic abnormalities. Gene expression measures the level of gene activity in a tissue and gives information about its complex activities. Comparing the genes expressed in normal and diseased tissue can bring better insights into the cancer prognosis and outcomes. Using machine learning techniques on genetic data has the potentials of giving the correct estimation of survival time and can prevent unnecessary surgical and treatment procedures.

Content

The Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database is a Canada-UK Project which contains targeted sequencing data of 1,980 primary breast cancer samples. Clinical and genomic data was downloaded from cBioPortal.

The dataset was collected by Professor Carlos Caldas from Cambridge Research Institute and Professor Sam Aparicio from the British Columbia Cancer Centre in Canada and published on Nature Communications (Pereira et al., 2016). It was also featured in multiple papers including Nature and others:

Clinical attributes in the dataset:

Name	Type	Description
patient_id	object	Patient ID
age_at_diagnosis	float	Age of the patient at diagnosis time
type_of_breast_surgery	object	Breast cancer surgery type: 1- MASTECTOMY, which refers to a surgery to remove all breast tissue from a breast as a way to treat or prevent breast cancer. 2- BREAST CONSERVING, which refers to a urgery where only the part of the breast that has cancer is removed
cancer_type	object	Breast cancer types: 1- Breast Cancer or 2- Breast Sarcoma
cancer_type_detailed	object	Detailed Breast cancer types: 1- Breast Invasive Ductal Carcinoma 2- Breast Mixed Ductal and Lobular Carcinoma 3- Breast Invasive Lobular Carcinoma 4- Breast Invasive Mixed Mucinous Carcinoma 5- Metaplastic Breast Cancer
cellularity	object	Cancer cellularity post chemotherapy, which refers to the amount of tumor cells in the specimen and their arrangement into clusters
chemotherapy	int	Whether or not the patient had chemotherapy as a treatment (yes/no)
pam50_+_claudin-low_subtype	object	Pam 50: is a tumor profiling test that helps show whether some estrogen receptor-positive (ER-positive), HER2-negative breast cancers are likely to metastasize (when breast cancer spreads to other organs). The claudin-low breast cancer subtype is defined by gene expression characteristics, most prominently: Low expression of cell–cell adhesion genes, high expression of epithelial–mesenchymal transition (EMT) genes, and stem cell-like/less differentiated gene expression patterns
cohort	float	Cohort is a group of subjects who share a defining characteristic (It takes a value from 1 to 5)
er_status_measured_by_ihc	float	To assess if estrogen receptors are expressed on cancer cells by using immune-histochemistry (a dye used in pathology that targets specific antigen, if it is there, it will give a color, it is not there, the tissue on the slide will be colored) (positive/negative)
er_status	object	Cancer cells are positive or negative for estrogen receptors
neoplasm_histologic_grade	int	Determined by pathology by looking the nature of the cells, do they look aggressive or not (It takes a value from 1 to 3)
her2_status_measured_by_snp6	object	To assess if the cancer positive for HER2 or not by using advance molecular techniques (Type of next generation sequencing)
her2_status	object	Whether the cancer is positive or negative for HER2
tumor_other_histologic_subtype	object	Type of the cancer based on microscopic examination of the cancer tissue (It takes a value of 'Ductal/NST', 'Mixed', 'Lobular', 'Tubular/ cribriform', 'Mucinous', 'Medullary', 'Other', 'Metaplastic' )
hormone_therapy	int	Whether or not the patient had hormonal as a treatment (yes/no)
inferred_menopausal_state	object	Whether the patient is is post menopausal or not (post/pre)
integrative_cluster	object	Molecular subtype of the cancer based on some gene expression (It takes a value from '4ER+', '3', '9', '7', '4ER-', '5', '8', '10', '1', '2', '6')
primary_tumor_laterality	object	Whether it is involving the right breast or the left breast
lymph_nodes_examined_positive	float	To take samples of the lymph node during the surgery and see if there were involved by the cancer
mutation_count	float	Number of gene that has relevant mutations
nottingham_prognostic_index	float	It is used to determine prognosis following surgery for breast cancer. Its value is calculated using three pathological criteria: the size of the tumour; the number of involved lymph nodes; and the grade of the tumour.
oncotree_code	object	The OncoTree is an open-source ontology that was developed at Memorial Sloan Kettering Cancer Center (MSK) for standardizing cancer type diagnosis from a clinical perspective by assigning each diagnosis a unique OncoTree code.
overall_survival_months	float	Duration from the time of the intervention to death
overall_survival	object	Target variable wether the patient is alive of dead.
pr_status	object	Cancer cells are positive or negative for progesterone receptors
radio_therapy	int	Whether or not the patient had radio as a treatment (yes/no)
3-gene_classifier_subtype	object	Three Gene classifier subtype It takes a value from 'ER-/HER2-', 'ER+/HER2- High Prolif', nan, 'ER+/HER2- Low Prolif','HER2+'
tumor_size	float	Tumor size measured by imaging techniques
tumor_stage	float	Stage of the cancer based on the involvement of surrounding structures, lymph nodes and distant spread
death_from_cancer	int	Wether the patient's death was due to cancer or not (yes/no)

Genetic attributes in the dataset:

The genetics part of the dataset contains m-RNA levels z-score for 331 genes, and mutation for 175 genes.

From CBioPortal:

What are mRNA?

The DNA molecules attached to each slide act as probes to detect gene expression, which is also known as the transcriptome or the set of messenger RNA (mRNA) transcripts expressed by a group of genes. To perform a microarray analysis, mRNA molecules are typically collected from both an experimental sample and a reference sample.

What are mRNA Z-Scores?

For mRNA expression data, The calculations of the relative expression of an individual gene and tumor to the gene's expression distribution in a reference population is done. That reference population is all samples in the study . The returned value indicates the number of standard deviations away from the mean of expression in the reference population (Z-score). This measure is useful to determine whether a gene is up- or down-regulated relative to the normal samples or all other tumor samples.

The formula is :

z = (expression in tumor sample - mean expression in reference sample) / standard deviation of expression in reference sample

Acknowledgements

Inspiration

Predict breast cancer survival using machine learning models with clinical data and gene expression profiles.
Clustering genes

Breast Cancer Gene Expression Profiles (METABRIC)

About this Dataset