Abstract
Recent advances in radiological imaging and genomic analysis are profoundly changing the way to manage lung cancer patients. Screening programs which couple lung cancer risk prediction models and low-dose computed tomography (LDCT) recently showed their effectiveness in the early diagnosis of lung tumors. In addition, the emerging field of radiomics is revolutionizing the approach to handle medical images, i.e., from a “simple” visual inspection to a high-throughput analysis of hundreds of quantitative features of images which can predict prognosis and therapy response. Yet, with the advent of next-generation sequencing (NGS) and the establishment of large genomic consortia, the whole mutational and transcriptomic profile of lung cancer has been unveiled and made publicly available via web services interfaces. This has tremendously accelerated the discovery of actionable mutations, as well as the identification of cancer biomarkers, which are pivotal for development of personalized targeted therapies. In this review, we will describe recent advances in cancer biomarkers discovery for early diagnosis, prognosis, and prediction of chemotherapy response.
Highlights
Recent advances in radiological imaging and genomic analysis are profoundly changing the way to manage lung cancer patients
After the first studies failed to demonstrate a reduction in lung cancer specific mortality by the sole use of chest X-ray, low-dose computed tomography (LDCT) was introduced as an effective diagnostic tool to augment early diagnoses
Minimally invasive strategies, based on radiomics and/or circulating biomarkers, are promising and can complement LDCT to augment the overall performance of screening protocols for lung cancer early detection
Summary
Lung cancer causes ~1.7 million deaths every year due to frequent late diagnoses when the disease is metastatic [1]. Minimally invasive strategies, based on radiomics and/or circulating biomarkers, are promising and can complement LDCT to augment the overall performance of screening protocols for lung cancer early detection. Circulating cell-free microRNAs (cf-miRNAs) represent the most promising and valuable class of non-invasive molecular biomarkers for the detection of several cancers, including lung cancer. Montani et al validated a 13 serum cf-miRNA panel in a large cohort (N = 1115) of high-risk individuals (>20 pack-year smoking history, aged >50 years) enrolled in the COSMOS screening trial, showing a sensitivity of 0.78, specificity of 0.75, and an AUC of 0.85 [14]. Sozzi et al validated a plasma cf-miRNA signature from patients in the MILD screening study, including 939 participants with 0.87 of sensitivity and 0.81 of specificity (Table 1) [15]. CT, asterisks indicate studies which performed validation of biomarkers on actual LD-CT screening trials. § Predicted performance when applied to independent samples; † miRNAs combined with carcinoembryonic antigen (CEA); PubMed identifiers (PubMed ID) are reported to allow retreiving cited publications
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