Integration of multiple “OMIC” biomarkers: A precision medicine strategy for lung cancer

Abstract

More than half of all new lung cancer diagnoses are made in patients with locally advanced or metastatic disease, at which point therapeutic options are scarce. It is anticipated, however, that the widespread use of Low-Dose Computed Tomography (LDCT) screening, will lead to a greater proportion of lung cancers being diagnosed at an early, operable, stage. Still, the overall rate of recurrence for surgically treated Stage I lung cancer patients is up to 30% within 5 years of diagnosis. Thus, the identification and clinical application of biomarkers of early stage lung cancer is a pressing medical need. The integrative analysis of “omic,” clinical and epidemiological data for single patients is a core principle of precision medicine. Through rigorous bioinformatics and statistical analyses we have identified biomarkers of early-stage lung cancer based on DNA methylation, expression of mRNA and miRNA, inflammatory cytokines, and urinary metabolites. Beyond a more comprehensive understanding of the molecular taxonomy of lung cancer, these biomarkers can have very practical implications in the context of unmet clinical needs of early stage lung cancer patients: First, current guidelines for LDCT screening broadly include individuals based on age and history of heavy smoking. Tumor-derived circulating biomarkers in the blood and urine associated with lung cancer risk could narrow and prioritize individuals for LDCT screening. Second, a high number of nodules are identified by LDCT, of which fewer than 5% are finally diagnosed as lung cancer. Biomarkers may help discriminate malignant nodules from benign or indolent lesions. Third, the expected rise in the numbers of lung cancer patients diagnosed at an early stage will necessitate new treatment options. Circulating, urinary and tissue-based biomarkers that molecularly categorize Stage I patients after tumor resection can help identify high-risk patients who may benefit from adjuvant chemotherapy or innovative immunotherapy regimens.

Clinical Application of Mass Spectrometry‐Based Proteomics in Lung Cancer Early Diagnosis

“…[39,44] The validation of biomarker accuracy should also be carried out in patients with other oncological conditions, to confirm that it is widely applicable beyond the sample cohort used to generate it. [99] Second, biomarkers for early lung cancer diagnosis should be distinguished from late stage biomarkers, [29,50,22,47] and study on early biomarkers discovery should include patients with stage I disease. Large tumors, such as those at stage III or IV, require a dedicated cardio-circulatory contribution.…”

“…Proteomics patterns could also be intersected with other omics profiles, to obtain a more comprehensice view of the status of the patient, and a more specific panel of biomarkers. For lung cancer, a particularly promising field is breath and urine metabolomics, [99] where volatile organic compounds produced and released by cells are detected. Since these compounds can be excreted from different body fluids (e.g., breath, urine, and sweat), their profile have been evaluated as an expression of the different metabolism characteristics of cancerous cells.…”

Prognostic and predictive biomarkers post curative intent therapy

“…Other attempts to utilize the non-coding genome for prognostic purposes include several studies examining microRNA (miRNA) expression profiles to stratify patients that are at high-risk for relapse (48)(49)(50). miRNA are small, non-coding RNA molecules that can regulate gene expression that effect signaling, growth, differentiation and transformation, and several studies indicate their potential role as biomarkers for disease and progression (48).…”

“…Additionally, multi-omic approaches for the development of prognostic classifiers have also been investigated. For instance, a signature comprised of proteincoding (XPO1, BRCA1, HIF1a and DLC1), non-coding (miR-21) and HOXA9 promoter methylation improved the statistical significance of identifying high-risk therapy naïve stage I lung adenocarcinomas than only utilizing coding or non-coding expression data alone (HR =10.2; P=3×10 −5 ) (25,49,50). Although expansion of the technological approaches allows for a more comprehensive assessment of the tumor landscape is promising, these signatures are also still in preliminary stages of testing and have yet to be clinically validated.…”

Sputum-based DNA methylation biomarkers to guide lung cancer screening decisions

“…The panel of methylated genes should be prospectively validated in the population targeted for LDCT screening. One more tool could be then added to the toolbox of physicians to aid decision-making and bring precision medicine to lung cancer screening (19).…”