Abstract: A method for predicting how a cancer patient will respond to an antibody drug conjugate (ADC) therapy involves computing a predictive response score by performing statistical operations on the staining of each cancer cell in a tissue sample. The ADC includes an ADC payload and an ADC antibody that targets the trophoblast antigen 2 (TROP2) protein in the cancer cells. The tissue sample is stained using a dye linked to a diagnostic antibody that binds to the protein. Cancer cells in digital images of tissue are detected. The statistical operations are performed for each cancer cell based on the staining intensities of the dye in the membrane and/or cytoplasm of each cancer cell and/or in the membranes of neighboring cancer cells. The response of the cancer patient to the ADC therapy is predicted based on whether the results of the statistical operations exceed various clinically derived thresholds.

Abstract: A method for predicting how a cancer patient will respond to an antibody drug conjugate (ADC) therapy involves computing a predictive response score based on single-cell ADC scores for each cancer cell. The ADC includes an ADC payload and an ADC antibody that targets a protein on each cancer cell, wherein the protein is human epidermal growth factor receptor 2 (HER2). A tissue sample is immunohistochemically stained using a dye linked to a diagnostic antibody that binds to the protein on cancer cells in the tissue sample. Cancer cells in a digital image of the tissue are detected. For each cancer cell, a single-cell ADC score is computed based on the staining intensities of the dye in the membrane and/or cytoplasm of the cancer cell and/or in the membranes and cytoplasms of neighboring cancer cells. The response of the cancer patient to the ADC therapy is predicted by aggregating all single-cell ADC scores of the tissue sample using a statistical operation.

Abstract: The present invention relates to a method for predicting how a cancer patient will respond to an antibody drug conjugate (ADC) therapy involving computing a predictive response score based on single-cell ADC scores for each cancer cell. For each cancer cell, a single-cell ADC score is computed based on the staining intensities of the dye in the membrane and cytoplasm of the cancer cell and in the membranes and cytoplasms of neighboring cancer cells. The present invention also relates to predicting a response of a cancer patient to ADC therapy by aggregating all single-cell ADC scores of the tissue sample using a statistical operation, and the subsequent treatment of cancer with related antibody-drug conjugates.

Abstract: Provided herein are methods of treating non-small cell lung cancers comprising administering an effective amount of durvalumab (MEDI4736) or an antigen-binding fragment thereof and tremelimumab or an antigen-binding fragment thereof. A combination of durvalumab and tremelimumab was effective at treating non-small cell lung cancers characterized as PD-L1- and having a high level of CD8+ tumor-infiltrating lymphocytes.