Gene Expression Profiles in Peripheral Blood Mononuclear Cells Can Distinguish Patients with Non–Small Cell Lung Cancer from Patients with Nonmalignant Lung Disease

Abstract

Early diagnosis of lung cancer followed by surgery presently is the most effective treatment for non-small cell lung cancer (NSCLC). An accurate, minimally invasive test that could detect early disease would permit timely intervention and potentially reduce mortality. Recent studies have shown that the peripheral blood can carry information related to the presence of disease, including prognostic information and information on therapeutic response. We have analyzed gene expression in peripheral blood mononuclear cell samples including 137 patients with NSCLC tumors and 91 patient controls with nonmalignant lung conditions, including histologically diagnosed benign nodules. Subjects were primarily smokers and former smokers. We have identified a 29-gene signature that separates these two patient classes with 86% accuracy (91% sensitivity, 80% specificity). Accuracy in an independent validation set, including samples from a new location, was 78% (sensitivity of 76% and specificity of 82%). An analysis of this NSCLC gene signature in 18 NSCLCs taken presurgery, with matched samples from 2 to 5 months postsurgery, showed that in 78% of cases, the signature was reduced postsurgery and disappeared entirely in 33%. Our results show the feasibility of using peripheral blood gene expression signatures to identify early-stage NSCLC in at-risk populations. [Cancer Res 2009;69(24):9202-10]

A novel gene expression signature in peripheral blood mononuclear cells for early detection of colorectal cancer

“…11,12 Tumour-recruited BMDC are likely to initiate differentiation and effector programs during their mobilisation from the bone marrow, which might be detectable during their transition in the blood. 13,14 The report of signatures derived from peripheral blood mononuclear cells (PBMC) gene expression profiles and associated with breast, 15 renal, 16,17 pulmonary, 18 bladder 19 and digestive cancers 8,9,20 further corroborates these observations. The aim of this study was to demonstrate whether the feasibility of identifying gene expression signatures in PBMC was able to discriminate patients with AP and CRC from subjects without these lesions.…”

“…20 Similar results have been reported for other type of tumours, such as breast, bladder, small cell lung cancer and renal carcinoma. [15][16][17][18][19] In particular, different panels of peripheral blood biomarkers based on gene expression have been described in recent studies to differentiate CRC from controls. Han et al identified and validated a five-gene combination that could discriminate CRC from non-CRC samples with sensitivity and specificity of 94% and 77% respectively.…”

RNA-Stabilized Whole Blood Samples but Not Peripheral Blood Mononuclear Cells Can Be Stored for Prolonged Time Periods Prior to Transcriptome Analysis

“…Moreover, it has been suggested that blood-based GEP can be used as a powerful tool for early diagnosis of certain solid cancer entities, [32][33][34][35][36] as well as infectious, 37,38 autoimmune, 39,40 and neurodegenerative 41 disease. Nevertheless, prospective clinical studies are still needed to validate these promising but still preliminary results in larger cohorts of patients or in individuals at risk for the respective diseases.…”

Exosomes as divine messengers: are they the Hermes of modern molecular oncology?

“…75 It would be very useful to develop new mechanisms to monitor the transcriptome expression pattern based on the use of noninvasive biological fluids. [76][77][78] As the composition of nucleic acids (specifically RNA) reflect in most cases the nature and origin of the parental cell, exosomes may be considered valuable carriers of cell-specific information because their content provides an insight glance of the proteins being transcribed in the original tissue. [79][80][81] In this manner, exosomes may be used in the clinic to achieve early diagnostics and prognosis information, but also to stratify and separate patients into different clinical categories in order to determine specific targeted therapies.…”