PATENT CLAIM ANALYSIS

Application Number: 15948908
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-10
Patent Classification: ["435", "006100"]

Abstract:
Methods for predicting clinical outcome for a human subject diagnosed with squamous cell lung carcinoma using a panel of molecular markers that includes CDKN2A and CCND1. The markers are related to the subject's increased likelihood of a negative clinical outcome.

Claim (Index 25):
A method of providing a clinical outcome predictor for a human subject diagnosed with early stage squamous cell lung carcinoma comprising:\n a) detecting whether a loss of function mutation or a deletion of the cyclin-dependent kinase inhibitor 2A (CDKN2A) is present in the subject by determining the presence or absence of a loss of function mutation or a deletion in the CDKN2A gene by next generation sequence examination in a biological sample comprising early stage squamous cell lung carcinoma cancer cells obtained from a human subject; and b) detecting whether an increase in the copy number of the G1/S-specific cyclin-D1 (CCND1) gene is present in the subject by determining the presence or absence of an increase in the copy number of the CCND1 gene in the biological sample by comparative genomic hybridization examination; and c) providing a clinical outcome predictor for said human subject, wherein the presence of a loss of function mutation or deletion in the CDKN2A gene and/or the presence of an increase in the copy number of the CCND1 gene is a predictor of a negative clinical outcome, and wherein the absence of a loss of function mutation or deletion in the CDKN2A gene and the absence of an increase in the copy number of the CCND1 gene is a predictor of a positive clinical outcome.

Metadata:
- Claim Count in Document: 59.0
- Percentile: 91.0
- Lexical Diversity: 1.26471
- Patent Class: 435.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13958502', '15200088', '13868745', '15354854', '13407165']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5500076873814694
- 35 USC 102 Novelty (BERT): 0.5369861275150943
- Combined Prediction Score: 0.5487055313948319
- Mean Citation Score: 305.5848420000001
- Max Citation Score: 367.76343
- Similarity Product: 246.95628785913703

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test