Abstract: 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.

Abstract: The invention relates to a PARP inhibitor, an immune checkpoint inhibitor, or a combination thereof, for use as a medicament. The invention further relates to a kit of parts and to a pharmaceutical composition comprising a PARP inhibitor and an immune checkpoint inhibitor, preferably for use in a method of treating a breast cancer.

Abstract: 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.

Abstract: In particular, systems and methods of the invention measure amounts of passenger mutations, and optionally driver mutations, to predict risk of cancer-related pathogenicity. Preferably, the mutations are measured from sequences reads. Sequence reads of patient-derived nucleic acids may be compared with one or more references to identify and measure the amount of passenger mutations and optionally driver mutations. The amount of passenger and driver mutations may be correlated to known associations with recurrent and residual disease to predict a risk of cancer recurrence.

Abstract: 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.

Abstract: The present disclosure provides systems and methods for analyzing circulating hormone receptor transcripts to provide diagnoses, prognoses, and treatment suggestions for patients afflicted with breast cancer. Circulating transcripts can be obtained from patient samples, including blood samples, without the need for invasive tissue biopsies. This may include expression transcripts obtained from extracellular vesicles. Analysis of hormone receptor expression transcripts may include comparison with expression transcripts of patients with known clinical outcomes.

Abstract: This disclosure relates to systems and methods for providing individualized assessments of breast cancer. The assessments are provided in the format of index scores that are prognostic to disease severity and progression. Methods involve measuring gene expression from a patient sample to create a gene expression signature. The gene expression signature is compared with expression signatures from tumors that are associated with known outcomes. The comparison is used to generate an index score that assigns a risk status to the patient. The index score may indicate, for example, risk of distant metastasis or benefit of chemotherapy.

Abstract: 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?, PR? and HER2?) and HER2+.

Abstract: The invention is related to a method of determining whether an individual suffering from cancer is likely to respond to anti-EGFR and/or EGFR pathway therapy. In one aspect, the invention utilizes the expression level of a set of genes for determining said response. In a further aspect, the invention relates to a method of assigning treatment to an individual suffering from cancer.

Abstract: 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?, PR? and HER2?) and HER2+.

Abstract: 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?, PR? and HER2?) and HER2+.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The invention is related to a method of determining whether an individual suffering from cancer is likely to respond to anti-EGFR and/or EGFR pathway therapy. In one aspect, the invention utilizes the expression level of a set of genes for determining said response. In a further aspect, the invention relates to a method of assigning treatment to an individual suffering from cancer.

Abstract: 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?, PR? and HER2?) and HER2+.

Abstract: 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.

Abstract: 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.

Abstract: The invention relates to a method of typing non-small cell lung cancer cells by determining RNA levels for a set of genes. Said 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 that can be used for typing non-small cell lung cancer cells.

Abstract: The present invention relates to arrays comprising between 2 and 12.000 nucleic acid molecules, comprising a first set of nucleic acid molecules that comprise a nucleotide sequence that is able to hybridize to a gene that is used for normalization. The array may further comprise a second set of nucleic acid molecules that comprise nucleic acid sequences capable of hybridizing to nucleic acid molecules that are expressed in clinical relevant samples such as, for example, breast tissue. The invention further relates to a method for normalizing data. Further provided are methods of using an array according to the invention for distinguishing clinical samples.