Abstract: The present disclosure provides a diagnostic method based on pairwise comparison of cancers using transcriptome expression data. In one embodiment, the method comprises the steps of: obtaining a first gene expression profile of a first cancer sample having a first cancer type; obtaining a second gene expression profile of a second cancer sample having a second cancer type, wherein the second cancer type is different from the first cancer type; comparing said first gene expression profile with said second gene expression profile; and selecting N genes that are most differentially expressed in the first and the second gene expression profiles to generate pairwise differentially expressed genes (DEGs), wherein N is an integer between 10 and 100.

Abstract: A panel of gene expression markers for gastric cancer patient treated or to be treated by cetuximab is provided. Methods and compositions are also provided, e.g., kits, for evaluating gene expression levels of the markers and methods of using such gene expression levels to predict a gastric cancer patient's response to cetuximab.

Abstract: Provided in the disclosure relates to a panel of gene expression markers for cancer patient treated or to be treated by karenitecin. The disclosure provides methods and compositions, e.g., kits, for evaluating gene expression levels of the markers and methods of using such gene expression levels to predict a cancer patient's response to karenitecin. Such information can be used in determining prognosis and treatment options for cancer patients.

Abstract: Gene expression signature predictive of cancer patient response to multi-kinase inhibitor is disclosed. Also disclosed are methods predicting the efficacy of the multi-kinase inhibitor for treating cancer in a patient. Also disclosed are methods for distinguishing responders from non-responders to a multi-kinase inhibitor in treating cancer. Also disclosed are methods for treating a cancer patient with a multi-kinase inhibitor.

Abstract: The present disclosure provides non-human animal models of non-alcoholic fatty liver disease (NAFLD). Also provided are methods for producing the non-human animal models and uses of the non-human animal models to screen and evaluate agents for treating or preventing NAFLD.

Abstract: The present disclosure provides methods of detecting a fusion gene of HNF4G and RSPO2 in a nucleic acid-containing sample, and a primer set, a probe set and a kit for detecting the fusion gene are also provided. Animal models for a human disease positive for the fusion gene are also provided herein. In addition, the present disclosure relates to the methods for assessing and identifying an agent effective on the fusion gene of HNF4G and RSPO2 or a human disease positive for a fusion gene of HNF4G and RSPO2 and thereby treating said disease are also provided.

Abstract: A method for predicting the responsiveness of a cancer cell to an MEK inhibitor, comprising detecting the presence of at least one mutation in one or more genes selected from the group consisting of ADAM12, COL14A1, TNN, and TP53, in the cancer cell, by contacting a nucleic acid sample derived from the cancer cell with at least one oligonucleotide which allows specific detection of the mutation; wherein presence of mutation in ADAM12, COL14A1, TNN, TP53 and/or any combination thereof is indicative of decreased responsiveness of the cancer cell to the ERK inhibitor.

Abstract: The present invention relates to methods for treating gastric neoplasias, in particular treating patients who have been previously determined to have an EGFR biomarker. Gastric carcinoma (GC) is one of the most common and deadest cancers with ?1 million diagnoses and ?0.7 million deaths each year worldwide, with high incidence in Eastern Asia.

Abstract: The present disclosure provides a diagnostic method based on pairwise comparison of cancers using transcriptome expression data. In one embodiment, the method comprises the steps of: obtaining a first gene expression profile of a first cancer sample having a first cancer type; obtaining a second gene expression profile of a second cancer sample having a second cancer type, wherein the second cancer type is different from the first cancer type; comparing said first gene expression profile with said second gene expression profile; and selecting N genes that are most differentially expressed in the first and the second gene expression profiles to generate pairwise differentially expressed genes (DEGs), wherein N is an integer between 10 and 100.

Abstract: The present invention provides methods for the treatment of lung cancer patients, especially NSCLC with SCC or PLC using a drug against EGFR, such as an anti-EGFR antibody treatment, e.g., cetuximab. In addition, the present invention provides methods for identification or selection of lung cancer patients for the treatment with a drug against EGFR, such as an anti-EGFR antibody treatment, e.g., cetuximab based on histological determinations.

Abstract: The present invention provides an immuno-deficient animal useful as an animal model for a human disease associated with a first mutation of a target gene, wherein the animal comprises (a) a first human xenograft comprising the target gene comprising the first mutation; (b) a second human xenograft comprising the target gene but lacking the first mutation, wherein the first human xenograft and second human xenograft are isogenic. Also provided here are methods of producing the animal model and methods of using such animal model.

Abstract: A method for predicting the responsiveness of a cancer cell to an MEK inhibitor, comprising detecting the presence of at least one mutation in one or more genes selected from the group consisting of ADAM12, COL14A1, TNN, and TP53, in the cancer cell, by contacting a nucleic acid sample derived from the cancer cell with at least one oligonucleotide which allows specific detection of the mutation; wherein presence of mutation in ADAM12, COL14A1, TNN, TP53 and/or any combination thereof is indicative of decreased responsiveness of the cancer cell to the ERK inhibitor.

Abstract: Gene expression signature predictive of cancer patient response to multi-kinase inhibitor is disclosed. Also disclosed are methods predicting the efficacy of the multi-kinase inhibitor for treating cancer in a patient. Also disclosed are methods for distinguishing responders from non-responders to a multi-kinase inhibitor in treating cancer. Also disclosed are methods for treating a cancer patient with a multi-kinase inhibitor.

Abstract: The present invention relates to methods for treating gastric neoplasias, in particular treating patients who have been previously determined to have an EGFR biomarker. Gastric carcinoma (GC) is one of the most common and deadest cancers with ?1 million diagnoses and ?0.7 million deaths each year worldwide, with high incidence in Eastern Asia.