Despite advances in screening and therapeutics cancer continues to be one of the major causes of morbidity and mortality worldwide. The molecular profile of tumor is routinely assessed by surgical or bioptic samples, however, genotyping of tissue has inherent limitations: it represents a single snapshot in time and it is subjected to spatial selection bias owing to tumor heterogeneity. Liquid biopsy has emerged as a novel, non-invasive opportunity of detecting and monitoring cancer in several body fluids instead of tumor tissue. Circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), RNA (mRNA and microRNA), microvesicles, including exosomes and tumor “educated platelets” were recently identified as a source of genomic information in cancer patients which could reflect all subclones present in primary and metastatic lesions allowing sequential monitoring of disease evolution. In this review, we summarize the currently available information concerning liquid biopsy in breast cancer, colon cancer, lung cancer and melanoma. These promising issues still need to be standardized and harmonized across laboratories, before fully adopting liquid biopsy approaches into clinical practice.

Background Androgen receptor (AR) signaling inhibitors represent the standard treatment in metastatic castration resistance prostate cancer (mCRPC) patients. However, some patients display a primary resistance, and several studies investigated the role of the AR as a predictive biomarker of response to treatment. This study is aimed to evaluate the role of AR in liquid biopsy to predict clinical outcome to AR signaling inhibitors in mCRPC patients. Methods Six milliliters of plasma samples were collected before first-line treatment with abiraterone or enzalutamide. Circulating free DNA (cfDNA) and exosome-RNA were isolated for analysis of AR gain and AR splice variant 7 (AR-V7), respectively, by digital droplet PCR. Results Eighty-four mCRPC patients received abiraterone (n = 40) or enzalutamide (n = 44) as first-line therapy. Twelve patients (14.3%) presented AR gain and 30 (35.7%) AR-V7+ at baseline. Median progression-free survival (PFS) and overall survival (OS) were significantly longer in AR-V7− vs AR-V7+ patients (24.3 vs 5.4 months, p < 0.0001; not reached vs 16.2 months, p = 0.0001, respectively). Patients carrying the AR gain had a median PFS of 4.8 vs 24.3 months for AR normal patients (p < 0.0001). Median OS was significantly longer in AR normal vs patients with AR gain (not reached vs 8.17 months, p < 0.0001). A significant correlation between AR-V7 and AR gain was observed (r = 0.28; p = 0.01). The AR gain/AR-V7 combined analysis confirmed a strong predictive effect for biomarkers combination vs patients without any AR aberration (PFS 3.8 vs 28 month, respectively; OS 6.1 vs not reached, respectively; p < 0.0001). Conclusions The present study demonstrates that cfDNA and exosome-RNA are both a reliable source of AR variants and their combined detection in liquid biopsy predicts resistance to AR signaling inhibitors.

Background It is still unclear how to combine biomarkers to identify patients who will truly benefit from anti-PD-1 agents in NSCLC. This study investigates exosomal mRNA expression of PD-L1 and IFN-γ, PD-L1 polymorphisms, tumor mutational load (TML) in circulating cell-free DNA (cfDNA) and radiomic features as possible predictive markers of response to nivolumab and pembrolizumab in metastatic NSCLC patients. Methods Patients were enrolled and blood (12 ml) was collected at baseline before receiving anti-PD-1 therapy. Exosome-derived mRNA and cfDNA were extracted to analyse PD-L1 and IFN-γ expression and tumor mutational load (TML) by digital droplet PCR (ddPCR) and next-generation sequencing (NGS), respectively. The PD-L1 single nucleotide polymorphisms (SNPs) c.-14-368 T > C and c.*395G > C, were analysed on genomic DNA by Real-Time PCR. A radiomic analysis was performed on the QUIBIM Precision® V3.0 platform. Results Thirty-eight patients were enrolled. High baseline IFN-γ was independently associated with shorter median PFS (5.6 months vs. not reached p = 0.0057), and levels of PD-L1 showed an increase at 3 months vs. baseline in patients who progressed (p = 0.01). PD-L1 baseline levels showed significant direct and inverse relationships with radiomic features. Radiomic features also inversely correlated with PD-L1 expression in tumor tissue. In subjects receiving nivolumab, median PFS was shorter in carriers of c.*395GG vs. c.*395GC/CC genotype (2.3 months vs. not reached, p = 0.041). Lastly, responders had higher non-synonymous mutations and more links between co-occurring genetic somatic mutations and ARID1A alterations as well. Conclusions A combined multiparametric approach may provide a better understanding of the molecular determinants of response to immunotherapy.

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The advances in understanding the inherited biological mechanisms of non-small cell lung cancer harbouring epidermal growth factor receptor (EGFR) mutations led to a significant improvement in the outcomes of patients treated with EGFR tyrosine kinase inhibitors. Despite these clinically impressive results, clinical results are not always uniform, suggesting the need for deepening the molecular heterogeneity of this molecularly defined subgroup of patients beyond the clinical and biological surface.The availability of tissue and blood-based tumour genotyping allows us to improve the understanding of molecular and genetic intratumor heterogeneity, driving the measurement of clonal evaluation in patients with lung cancer carrying EGFR mutations. Genetic diversification, clonal expansion and selection are highly variable patterns of genetic diversity, resulting in different biological entities, also a prerequisite for Darwinian selection and therapeutic failure.Such emerging pieces of evidence on the genetic diversity, including adaptive and immunomodulated aspects, provide further evidence for the role of the tumour microenvironment (TME) in drug-resistance and immune-mediated mechanisms. Matching in daily clinical practice, the detailed genomic profile of lung cancer disease and tracking the clonal evolution could be the way to individualise the further target treatments in EGFR-positive disease. Characterising the tumour and immune microenvironment during the time of the cancer evaluation could be the way forward for the qualitative leap needed from bench to bedside. Such a daring approach, aiming at personalising treatment selection in order to exploit the TME properties and weaken tumour adaptivity, should be integrated into clinical trial design to optimise patient outcome.