Abstract: Described herein are innovations for classifying subtypes of DLBCL, as well as using the results of classification for diagnosis, prognosis, and therapy selection. In this way, the classifier can effectively classify subtypes of DLBCL and provide meaningful output for the benefit of medical practices and DLBCL patients. Also described are arrays and kits that can be used to measure expression of DLBCL signatures genes.

Abstract: 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.

Abstract: 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.

Abstract: The present invention relates to therapeutic methods and medical uses comprising the identification and use of cancer marker surrogates for increased polyamine expression. These markers may be used to identify patients who may be treated for diseases and disorders that are susceptible to polyamine synthesis inhibitors, and they can also be used to monitor therapeutic responses when such agents are used.

Abstract: The present invention relates to therapeutic methods and medical uses comprising the identification and use of cancer marker surrogates for increased polyamine expression. These markers may be used to identify patients who may be treated for diseases and disorders that are susceptible to polyamine synthesis inhibitors, and they can also be used to monitor therapeutic responses when such agents are used.

Abstract: The present disclosure relates to therapeutic methods and medical uses comprising the identification and use of cancer marker surrogates for increased polyamine expression. These markers may be used to identify patients who may be treated for diseases and disorders that are susceptible to polyamine synthesis inhibitors, and they can also be used to monitor therapeutic responses when such agents are used. More specifically, reduced levels of let-7 miRNA and elevated levels of LIN28 and HMGA2 proteins were found to correlate with elevated levels of polyamines and may be used for predicting the efficacy of cancer therapy using an ornithine decarboxylase (ODC1) inhibitor such as eflornithine (DFMO), suitably in combination with an NSAID such as sulindac.

Abstract: Described herein are innovations for classifying subtypes of DLBCL, as well as using the results of classification for diagnosis, prognosis, and therapy selection. In this way, the classifier can effectively classify subtypes of DLBCL and provide meaningful output for the benefit of medical practices and DLBCL patients. Also described are arrays and kits that can be used to measure expression of DLBCL signatures genes.

Abstract: 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.

Abstract: Provided herein are methods of analyzing stage II colorectal cancer (CRC) samples (such as those that are mis-match repair proficient, pMMR), by scoring G-alpha interacting vesicle associated protein (GIV, also known as girdin) full-length (GIV-fl) expression in combination with lymphovascular invasion (LVI) status or clinical variables. The disclosed methods can be used to identify GIV-fl expressing tumors that are likely to recur (high risk) and those that are not likely to recur (high risk). Subjects identified as having a high risk CRC can be selected to receive chemotherapy or biotherapy for the CRC. Thus, in some examples, the disclosed methods can be used to identify CRC tumors that are likely to respond to chemotherapy or biotherapy. Also provided are computer implemented methods, systems, and kits that can be used with these methods.

Abstract: The present disclosure relates to therapeutic methods and medical uses comprising the identification and use of cancer marker surrogates for increased polyamine expression. These markers may be used to identify patients who may be treated for diseases and disorders that are susceptible to polyamine synthesis inhibitors, and they can also be used to monitor therapeutic responses when such agents are used. More specifically, reduced levels of let-7 miRNA and elevated levels of LIN28 and HMGA2 proteins were found to correlate with elevated levels of polyamines and may be used for predicting the efficacy of cancer therapy us ing an ornithine decarboxylase (ODC1) inhibitor such as eflornithine (DFMO), suitably in combination with an NSAID such as sulindac.