The present invention relates to a method of analyzing a corrected TMB and a method for predicting a response to immune checkpoint inhibitors in a cancer patient using the same. According to a method, a computer-readable recording medium and an analyzing apparatus, for providing information according to an aspect, since the corrected TMB of the present invention is markedly highly predictive of the response to cancer immunotherapy in the cancer patient, compared to the conventional TMB, a patient group predicted to show a therapeutic effect can be selected and an appropriate treatment can be administered, thereby alleviating pain and treatment costs from the cancer patient.

A method of diagnosing lung cancer in a subject-in-need thereof is provided. The method comprises: (a) providing a biological sample of the subject which comprises peripheral blood mononuclear cells (PBMCs); (b) in vitro contacting the PBMCs with a stimulant selected from the group consisting of the stimulants listed in Tables 3 and 4; and (c) measuring metabolic activity of the PBMCs having been contacted according to (b), wherein a statistically significant change in the metabolic activity of the PBMCs as compared to a control sample is indicative of lung cancer.

The technology described herein is directed to methods of treating and diagnosing bronchial premalignant lesions, e.g. by determining the lesion subtype using one or more biomarkers described herein.

The invention provides biomarkers for predicting the response to checkpoint inhibitors. The inventors demonstrate that a PD-1/PD-L1 inhibitor exerts antitumor activity against tumor with low PD-L1 expression and immune-desert phenotype through blocking PD-L1 in the lymph nodes. The invention provides novel combinations of intratumoral markers for antigen cross-presenting cells and T cell chemokines which are expected to be superior efficacy-predicting biomarkers compared to existing methods.

Described herein are methods for screening for a disease state. The method may include obtaining multiple data sets, and identifying the disease state based on a combination of the data sets. The data sets may include biomolecule measurements obtained by multiple methods, such as through the use of particles and reference biomolecules.

The present disclosure provides a method of treating cancer by immune checkpoint blockade, or selecting patients for treatment with immune checkpoint blockers, by detecting tumors with high levels of T-lymphocytes with low levels of activation and proliferation. In various embodiments the tissue sample may be from a conventional biopsy. In various embodiments the cancer may be non-small cell lung cancer.

A method of distinguishing between lung squamous cell carcinoma and head and neck squamous cell carcinoma using a 22-gene biomarker signature is presented.

The present invention relates to an assay for detecting secreted proteome acidic and rich in cysteine (SPARC), and more specifically to its use in evaluating lung cancer.

Subject matter of the present invention is a method for predicting the risk of getting cancer in a female subject that does not suffer from cancer or alternatively diagnosing cancer in a female subject comprising: determining the level of Pro-Enkephalin or fragments thereof including Leu-Enkephalin and Met-Enkephalin of at least 5 amino acids in a bodily fluid obtained from said female subject; and correlating said level of Pro-Enkephalin or fragments thereof with a risk for getting cancer, wherein a reduced level is predictive for an enhanced risk of getting cancer or alternatively diagnosing cancer wherein an reduced level is correlated with the diagnosis of cancer.

Isolated or recombinant EphA5 or GRP78 targeting antibodies are provided. In some cases, antibodies of the embodiments can be used for the detection, diagnosis and/or therapeutic treatment of human diseases, such as cancer. A method of rapidly identifying antibodies or antibody fragments for the treatment of cancer using a combination of in vitro and in vivo methodologies is also provided.