Agendia N.v.

Agendia B.v.

Annuska Maria Glas

Iris Simon

Paul Roepman

Rene Bernards

Oscar Krijgsman

Tian Sun

Nico Van Zandwijk

Laura Johanna Van 'T Veer

Arno Nicolaas Floore

The present disclosure provides methods and systems using machine learning to assess one or more of a patient's biomarkers to analyze various conditions, including cancers, such as breast cancer. The present systems and methods can be trained to analyze patient's biomarker data to form prognoses, diagnoses, and treatment suggestions. Further, the present systems and methods can use biomarker feature data and clinical feature data to create novel correlations in order to provide more accurate, patient-specific diagnoses, prognoses, and treatment suggestions.

Methods of assessing diseases using image classifiers

The invention relates to a method of typing a sample from a breast cancer patient. More specifically, the invention relates to a method for classification of breast cancer according to the presence or absence of Estrogen Receptor (ER), Progesterone Receptor (PR) and Human Epidermal growth factor Receptor 2 (ERBB2; HER2). More specifically, the invention provides methods and means to classify breast cancer as ER positive, triple negative (ER, PRand HER2) and HER2+.

Means and methods for molecular classification of breast cancer

The invention relates to a method of typing a sample from a breast cancer patient. More specifically, the invention relates to a method for classification of breast cancer according to the presence or absence of Estrogen Receptor (ER), Progesterone Receptor (PR) and Human Epidermal growth facto Receptor 2 (ERBB2; HER2). More specifically, the invention Provides methods and means to classify breast cancer as ER positive, triple negative (ER, PRand HER2) and HER2+.

The invention relates to a method of typing non-small cell lung cancer by determining RNA levels for a set of genes. The typing can be used for determining a metastasizing potential of the cancer cells. The invention further relates to a set of probes and a set of primers for typing non-small cell cancer cells.

Prognostic gene expression signature for non small cell lung cancer patients

The invention relates to a method of typing colorectal cancer cells by determining the RNA levels of a set of signature genes. Said typing can be use for predicting a risk for recurrence of said colorectal cancer. The invention further relates to a set of genes that can be used for normalizing the RNA levels of said set of signature genes, and to micro-array comprising said set of signature genes.

Methods and means for typing a sample comprising colorectal cancer cells

The invention provides a method for determining the percentage of tumor cells in a sample of an individual, preferably a breast sample. More specifically, the invention provides one or more genes than can be used to determine the percentage of tumor cells. The invention further provides a set of probes, a set of primers, and uses thereof for detection of said one or more genes.

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Assendelft, Netherlands

Annuska Maria Glas