Autoantibody Signature Enhances the Positive Predictive Power of Computed Tomography and Nodule-Based Risk Models for Detection of Lung Cancer.

Introduction: The incidence of pulmonary nodules is increasing with the movement toward screening for lung cancer by low-dose computed tomography. Given the large number of benign nodules detected by computed tomography, an adjunctive test capable of distinguishing malignant from benign nodules would benefit practitioners. The ability of the EarlyCDT-Lung blood test (Oncimmune Ltd.

Serum autoantibody measurement for the detection of hepatocellular carcinoma.

Background: Individuals with liver disease, and especially those with Hepatitis B or C, are at an increased risk of developing hepatocellular carcinoma (HCC) which is the third most common cause of cancer-related death worldwide. Inadequate screening tests largely account for presentation of advanced tumours and high mortality rates. Early detection of HCC amongst high-risk groups is paramount in improving prognosis.

Signal stratification of autoantibody levels in serum samples and its application to the early detection of lung cancer.

Background: Further signal stratification for the EarlyCDT®-Lung test should facilitate interpretation of the test, leading to more precise interventions for particular patients.

Methods: Samples were measured for the presence of autoantibodies to seven tumor-associated antigens (TAAs) (p53, NY-ESO-1, CAGE, GBU4-5, SOX2, MAGE A4, and HuD). In addition to the current test cut-offs (determined using a previously reported Validation case-control sample set, set A; n=501), new high and low cut-offs were set in order to maximize the test's positive and negative predictive values (PPV and NPV, respectively).

Application of a high throughput method of biomarker discovery to improvement of the EarlyCDT(®)-Lung Test.

Background: The National Lung Screening Trial showed that CT screening for lung cancer led to a 20% reduction in mortality. However, CT screening has a number of disadvantages including low specificity. A validated autoantibody assay is available commercially (EarlyCDT®-Lung) to aid in the early detection of lung cancer and risk stratification in patients with pulmonary nodules detected by CT.

Development and validation of a high throughput system for discovery of antigens for autoantibody detection.

An assay employing a panel of tumor-associated antigens has been validated and is available commercially (EarlyCDT®-Lung) to aid the early detection of lung cancer by measurement of serum autoantibodies. The high throughput (HTP) strategy described herein was pursued to identify new antigens to add to the EarlyCDT-Lung panel and to assist in the development of new panels for other cancers. Two ligation-independent cloning vectors were designed and synthesized, producing fusion proteins suitable for the autoantibody ELISA.

EarlyCDT®-Lung test: improved clinical utility through additional autoantibody assays.

Tumor-associated autoantibodies (AAbs) have been described in patients with lung cancer, and the EarlyCDT®-Lung test that measures such AAbs is available as an aid for the early detection of lung cancer in high-risk populations. Improvements in specificity would improve its cost-effectiveness, as well as reduce anxiety associated with false positive tests. Samples from 235 patients with newly diagnosed lung cancer and matched controls were measured for the presence of AAbs to a panel of six (p53, NY-ESO-1, CAGE, GBU4-5, Annexin I, and SOX2) or seven (p53, NY-ESO-1, CAGE, GBU4-5, SOX2, HuD, and MAGE A4) antigens.

EarlyCDT-Lung: an immunobiomarker test as an aid to early detection of lung cancer.

Recent publications have reported the technical and clinical validation of EarlyCDT-Lung, an autoantibody test which detected elevated autoantibodies in 40% of lung cancers at diagnosis. This manuscript reports the results of EarlyCDT-Lung run on four new (postvalidation) data sets. The following four cohorts of patients (n = 574) with newly diagnosed lung cancer were identified: group 1 (n = 122), 100% small cell lung cancer (SCLC); group 2 (n = 249), 97% non-small cell lung cancer (NSCLC); group 3 (n = 122), 100% NSCLC; group 4 (n = 81), 62% NSCLC.