Immunotherapy Methods For Patients Whose Tumors Carry A High Passenger Gene Mutation Burden

    公开(公告)号:US20190087538A1

    公开(公告)日:2019-03-21

    申请号:US16135913

    申请日:2018-09-19

    Inventor: Wei Keat Lim

    Abstract: Methods for selecting a cancer patient for immunotherapy comprise establishing a total passenger gene mutation burden from a tumor of a cancer patient, generating a background distribution for the mutational burden of the tumor, normalizing the total passenger gene mutation burden against the background distribution, and categorizing the cancer patient as an immunotherapy responder when the total passenger gene mutation burden is greater than the mean of the background distribution. When the cancer patient is an immunotherapy responder, the patient may be administered an immunotherapy regimen that comprises activation/inhibition of T cell receptors that promote T cell activation and/or prolong immune cytolytic activities.

    Monomeric yellow-green fluorescent protein from cephalochordate

    公开(公告)号:US10221221B2

    公开(公告)日:2019-03-05

    申请号:US13950239

    申请日:2013-07-24

    Abstract: The present disclosure provides isolated nucleic acid sequences encoding a monomeric green/yellow fluorescent proteins, and fragments and derivatives thereof. Also provided is a method for engineering the nucleic acid sequence, a vector comprising the nucleic acid sequence, a host cell comprising the vector, and use of the vector in a method for expressing the nucleic acid sequence. The present invention further provides an isolated nucleic acid, or mimetic or complement thereof, that hybridizes under stringent conditions to the nucleic acid sequence. Additionally, the present invention provides a monomeric green/yellow fluorescent protein encoded by the nucleic acid sequence, as well as derivatives, fragments, and homologues thereof. Also provided is an antibody that specifically binds to the green/yellow fluorescent protein.

    MACHINE LEARNING BASED ANTIBODY DESIGN
    5.
    发明申请

    公开(公告)号:US20190065677A1

    公开(公告)日:2019-02-28

    申请号:US16171596

    申请日:2018-10-26

    Abstract: Described herein are techniques for more precisely identifying antibodies that may have a high affinity to an antigen. The techniques may be used in some embodiments for synthesizing entirely new antibodies for screening for affinity, and for more efficiently synthesizing and screening antibodies by identifying, prior to synthesis, antibodies that are predicted to have a high affinity to the antigen. In some embodiments, a machine learning engine is trained using affinity information indicating a variety of antibodies and affinity of those antibodies to an antigen. The machine learning engine may then be queried to identify an antibody predicted to have a high affinity for the antigen.

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