The present invention provides methods of detecting cancer using biomarkers.

The subject disclosure presents systems and computer-implemented methods for providing reliable risk stratification for early-stage cancer patients by predicting a recurrence risk of the patient and to categorize the patient into a high or low risk group. A series of slides depicting serial sections of cancerous tissue are automatically analyzed by a digital pathology system, a score for the sections is calculated, and a Cox proportional hazards regression model is used to stratify the patient into a low or high risk group. The Cox proportional hazards regression model may be used to determine a whole-slide scoring algorithm based on training data comprising survival data for a plurality of patients and their respective tissue sections. The coefficients may differ based on different types of image analysis operations applied to either whole-tumor regions or specified regions within a slide.

Provided are methods for evaluating the risk of an adverse clinical outcome in a subject, deciding whether to discharge or continue treating a subject (e.g., treatment on an inpatient basis), or to initiate or terminate treatment, selecting a subject for participation in a clinical study, and selecting a therapeutic treatment for a subject that include determining a level of ST2 in a biological sample from the subject and determining a level of galectin-3 in a biological sample from the subject. Kits are also provided that contain an antibody that specifically binds to ST2, an antibody that specifically binds to galectin-3, and instructions for using the kit to evaluate the risk of an adverse clinical outcome in a subject, to decide whether to discharge or continue treating a subject (e.g., treatment on an inpatient basis) or to initiate or terminate treatment, to select a subject for participation in a clinical study, and/or to select treatment for a subject.

Heterogeneity for biomarkers in a tissue sample can be calculated. A heterogeneity score can be combined with an immunohistochemistry combination score to provide breast cancer recurrence prognosis. Heterogeneity can be based on percent positivity determinations for a plurality of biomarkers according to how many cells in the sample stain positive. An immunohistochemistry combination score can be calculated. An imaging tool can support a digital pathologist workflow that includes designating fields of view in an image of the tissue sample. Based on the fields of view, a heterogeneity metric can be calculated and combined with an immunohistochemistry combination score to generate a breast cancer recurrence prognosis score.

The present invention provides assays and methods for predicting the post-operative survival of a subject having an early stage gastric cancer after tumor surgery. The present invention also provides methods for treating a subject having an early stage gastric cancer by administering a combination therapy tailored to the signal transduction biomarkers that are activated in the cancer. In particular embodiments, the methods of the invention rely on the detection of the activation state or level of a specific combination of signal transducer analytes in a cancer cell obtained from the subject. Thus, the methods of the invention are particularly useful for predicting the survival or prognosis of a subject having an early stage gastric cancer and for guiding both pre- and post-operative treatment decisions by identifying subjects who would benefit from combination therapy as opposed to monotherapy.

Genetic biomarkers for left side colon cancer (LCC) (such as expression levels of an RNA transcript or expression product of NOX4, MMP3, or a combination) and right side colon cancer (RCC) (such as expression levels of an RNA transcript or expression product of CDCX2, FAM69A, or a combination), are disclosed. Methods for using the biomarkers in providing a prognosis of relapse-free survival probability in patients having LCC or RCC are also presented. Prognostic panels using gene expression values of the biomarkers are also presented. Computer implemented methods employing the biomarkers, and as well as for determining relapse-free survival probability in a patient having RCC or LCC are provided. A genetic method for classifying a colon cancer tissue as a RCC or as a LCC is also disclosed.

The present invention provides a method for diagnosing of colorectal cancer in a subject and a method for determining risk of recurrence of colorectal cancer among colorectal cancer patients by detecting overexpression of the RNF6 gene, which in some cases is due to a higher than normal copy number of the genomic sequence of this gene. A kit and device useful for such methods are also provided. In addition, the present invention provides a method for treating colon cancer by suppressing RNF6 gene expression or activity.

A method for prediction of the susceptibility of an at risk patient to developing or redeveloping an infection with Clostridium difficile, having the determination by immunoassay, in a stool sample from said patient, of the level of antibody IgA anti-toxin B of Clostridium difficile, and comparing this level with a reference value S determined beforehand using two populations of patients exposed to the bacterium, one population not having developed or redeveloped such an infection and the other population having developed or redeveloped such an infection, —a level lower than said reference value S signifying that the patient is a patient with a heightened risk of developing or redeveloping a Clostridium difficile infection, and —a level higher than said reference value S signifying that the patient is not a patient with a heightened risk of developing or redeveloping a Clostridium difficile infection.

The present invention generally relates, in some embodiments, to methods of determining a patient's prognosis for recurrence of prostate cancer and/or determining a course of treatment for prostate cancer following a radical prostatectomy.

The present invention relates to methods for prognosis and monitoring of a cancer, preferably bladder cancer, by measuring the proportion of CD8+ T Lymphocytes expressing ILT-2 and the plasma level of soluble HLA-G. The invention also relates to anti HLA-G antibodies for use for treating a cancer in which tumor cells express HLA-G, preferably bladder cancer.