Purpose: Myeloid-derived suppressor cells (MDSC) are considered an important T-cell immunosuppressive component in cancer-bearing hosts. The factors that attract these cells to the tumor microenvironment are poorly understood. IL8 (CXCL8) is a potent chemotactic factor for neutrophils and monocytes.Experimental Design: MDSC were characterized and sorted by multicolor flow cytometry on ficoll-gradient isolated blood leucokytes from healthy volunteers (n ¼ 10) and advanced cancer patients (n ¼ 28). In chemotaxis assays, sorted granulocytic and monocytic MDSC were tested in response to recombinant IL8, IL8 derived from cancer cell lines, and patient sera. Neutrophil extracellular traps (NETs) formation was assessed by confocal microscopy, fluorimetry, and time-lapse fluorescence confocal microscopy on short-term MDSC cultures.Results: IL8 chemoattracts both granulocytic (GrMDSC) and monocytic (MoMDSC) human MDSC. Monocytic but not granulocytic MDSC exerted a suppressor activity on the proliferation of autologous T cells isolated from the circulation of cancer patients. IL8 did not modify the T-cell suppressor activity of human MDSC. However, IL8 induced the formation of NETs in the GrMDSC subset.Conclusions: IL8 derived from tumors contributes to the chemotactic recruitment of MDSC and to their functional control.

Changes in serum IL-8 levels could be used to monitor and predict clinical benefit from immune checkpoint blockade in melanoma and NSCLC patients.

Sunitinib is one of the most widely used targeted therapeutics for renal cell carcinoma (RCC), but acquired resistance against targeted therapies remains a major clinical challenge. To dissect mechanisms of acquired resistance and unravel reliable predictive biomarkers for sunitinib in RCC, we sequenced the exons of 409 tumor‐suppressor genes and oncogenes in paired tumor samples from an RCC patient, obtained at baseline and after development of acquired resistance to sunitinib. From newly arising mutations, we selected, using in silico prediction models, six predicted to be deleterious, located in G6PD, LRP1B, SETD2, TET2, SYNE1, and DCC. Consistently, immunoblotting analysis of lysates derived from sunitinib‐desensitized RCC cells and their parental counterparts showed marked differences in the levels and expression pattern of the proteins encoded by these genes. Our further analysis demonstrates essential roles for these proteins in mediating sunitinib cytotoxicity and shows that their loss of function renders tumor cells resistant to sunitinib in vitro and in vivo. Finally, sunitinib resistance induced by continuous exposure or by inhibition of the six proteins was overcome by treatment with cabozantinib or a low‐dose combination of lenvatinib and everolimus. Collectively, our results unravel novel markers of acquired resistance to sunitinib and clinically relevant approaches for overcoming this resistance in RCC.

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field.

Mutation analysis of epidermal growth factor receptor (EGFR) gene is essential for treatment selection in non-small cell lung cancer (NSCLC). Analysis is usually performed in tumor samples. We evaluated the clinical utility of EGFR analysis in plasma cell-free DNA (cfDNA) from patients under treatment with EGFR inhibitors. We selected 36 patients with NSCLC and EGFR-activating mutations. Blood samples were collected at baseline and during treatment with EGFR inhibitors. Wild-type EGFR, L858R, delE746-A750, and T790M mutations were quantified in cfDNA by droplet digital PCR. Stage IV patients had higher total circulating EGFR copy levels than stage I (3523 vs. 1003 copies/mL; p < 0.01). There was high agreement for activating mutations between baseline cfDNA and tumor samples, especially for L858R mutation (kappa index = 0.679; p = 0.001). In 34 % of advanced NSCLC patients, we detected mutations in cfDNA not previously detected in tumor samples and double mutations in 17 %. Patients with baseline total EGFR copy levels above the median presented decreased overall survival (OS) (341 vs. 870 days, p < 0.05) and progression-free survival (PFS) (238 vs. 783 days; p < 0.05) compared with those with total EGFR copy levels below the median. Patients with baseline concentrations of activating mutations above the median (94 copies/mL) had lower OS (317 vs. 805 days; p < 0.05) and PFS (195 vs. 724 days; p < 0.05). During follow-up, T790M resistance mutation was detected in 53 % of patients. Total and mutated EGFR analysis in cfDNA seems a relevant tool to characterize the molecular profile and prognosis of NSCLC patients harboring EGFR mutations.

ObjectivesLiver metastases appear in 20–30% of patients diagnosed with non-small cell lung cancer (NSCLC) and represent a poor prognosis feature of NSCLC and a possibly more treatment-resistant condition. Potential clinical outcome differences in NSCLC patients with liver metastases harboring molecular alterations in EGFR, KRAS and EML4-ALK genes are still to be determined. This study aims to evaluate the incidence of liver metastasis in a single population and look for potential correlations between EGFR mutations, liver infiltration and clinical outcomes.MethodsA total of 236 consecutive stage IV NSCLC patients treated at the Clínica Universidad de Navarra were analyzed.ResultsAt onset, liver metastases were present in 16.9% of patients conferring them a shorter overall survival (OS) compared to those with different metastatic locations excluding liver infiltration (10 vs. 21 months; p = 0.001). Patients with EGFR wild-type tumors receiving standard chemotherapy and showing no liver involvement presented a superior median OS compared to those with liver metastases (23 vs. 13 months; p = 0.001). Conversely, patients with EGFR-mutated tumors treated with EGFR tyrosin-kinase inhibitors (TKI’s) presented no significant differences in OS regardless of liver involvement (median OS not reached vs. 25 months; p = 0.81).ConclusionOverall, liver metastases at onset negatively impact OS of NSCLC patients. EGFR TKIs however, may reverse the effects of an initial negative prognosis of liver metastasis in first-line treatment of EGFR mutated NSCLC patients.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-015-0622-x) contains supplementary material, which is available to authorized users.

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Single nucleotide polymorphisms (SNPs) may modulate individual susceptibility to carcinogens. We designed a genome‐wide association study to characterize individuals presenting extreme phenotypes of high and low risk to develop tobacco‐induced non‐small cell lung cancer (NSCLC), and we validated our results. We hypothesized that this strategy would enrich the frequencies of the alleles that contribute to the observed traits. We genotyped 2.37 million SNPs in 95 extreme phenotype individuals, that is: heavy smokers that either developed NSCLC at an early age (extreme cases); or did not present NSCLC at an advanced age (extreme controls), selected from a discovery set (n = 3631). We validated significant SNPs in 133 additional subjects with extreme phenotypes selected from databases including >39,000 individuals. Two SNPs were validated: rs12660420 (p combined = 5.66 × 10−5; OR combined = 2.80), mapping to a noncoding transcript exon of PDE10A; and rs6835978 (p combined = 1.02 × 10−4; OR combined = 2.57), an intronic variant in ATP10D. We assessed the relevance of both proteins in early‐stage NSCLC. PDE10A and ATP10D mRNA expressions correlated with survival in 821 stage I–II NSCLC patients (p = 0.01 and p < 0.0001). PDE10A protein expression correlated with survival in 149 patients with stage I–II NSCLC (p = 0.002). In conclusion, we validated two variants associated with extreme phenotypes of high and low risk of developing tobacco‐induced NSCLC. Our findings may allow to identify individuals presenting high and low risk to develop tobacco‐induced NSCLC and to characterize molecular mechanisms of carcinogenesis and resistance to develop NSCLC.