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Aim: To define high tumor burden (HTB) in non-small-cell lung cancer. Methods: A total of five oncologists initiated the project, selecting 66 participants, and elaborated a questionnaire with 26 statements using the Delphi method with a 9-point Likert scale of agreement. Results: Factors with moderate strength of consensus were identified, including a sum of the longest diameter of lesions ≥10 cm, elevated LDH, hepatic involvement, lymphangitis carcinomatosis, brain involvement unapproachable with local techniques and pericardial effusion. There was a consensus against increases in tumor markers and asymptomatic brain involvement being related to HTB. HTB was considered a relevant factor for treatment selection supporting the choice of combination regimens versus immunotherapy only. Conclusion: In this Delphi study, experts defined several factors associated with HTB in non-small cell lung cancer.

Supplementary Figure 1. CYP3A4.25 protein stability assessment

Purpose: Neuropathy is the dose-limiting toxicity of paclitaxel and a major cause for decreased quality of life. Genetic factors have been shown to contribute to paclitaxel neuropathy susceptibility; however, the major causes for interindividual differences remain unexplained. In this study, we identified genetic markers associated with paclitaxel-induced neuropathy through massive sequencing of candidate genes.Experimental Design: We sequenced the coding region of 4 EPHA genes, 5 genes involved in paclitaxel pharmacokinetics, and 30 Charcot–Marie–Tooth genes, in 228 cancer patients with no/low neuropathy or high-grade neuropathy during paclitaxel treatment. An independent validation series included 202 paclitaxel-treated patients. Variation-/gene-based analyses were used to compare variant frequencies among neuropathy groups, and Cox regression models were used to analyze neuropathy along treatment.Results: Gene-based analysis identified EPHA6 as the gene most significantly associated with paclitaxel-induced neuropathy. Low-frequency nonsynonymous variants in EPHA6 were present exclusively in patients with high neuropathy, and all affected the ligand-binding domain of the protein. Accumulated dose analysis in the discovery series showed a significantly higher neuropathy risk for EPHA5/6/8 low-frequency nonsynonymous variant carriers [HR, 14.60; 95% confidence interval (CI), 2.33–91.62; P = 0.0042], and an independent cohort confirmed an increased neuropathy risk (HR, 2.07; 95% CI, 1.14–3.77; P = 0.017). Combining the series gave an estimated 2.5-fold higher risk of neuropathy (95% CI, 1.46–4.31; P = 9.1 × 10−4).Conclusions: This first study sequencing EPHA genes revealed that low-frequency variants in EPHA6, EPHA5, and EPHA8 contribute to the susceptibility to paclitaxel-induced neuropathy. Furthermore, EPHA's neuronal injury repair function suggests that these genes might constitute important neuropathy markers for many neurotoxic drugs. Clin Cancer Res; 23(5); 1227–35. ©2016 AACR.

Supplementary Table 1. Non synonymous coding and splicing site variants in the discovery series targeted sequencing. Supplementary Table 2. Association of common non-synonymous coding variants with paclitaxel-induced neuropathy.

Supplementary Figure 3. CYP3A4*22 association with paclitaxel-induced neuropathy and paclitaxel dose modifications.

Supplementary Figure 2. Neuropathy risk conditions confer an increased risk of paclitaxel-induced neuropathy and a trend towards treatment modifications.

Supplementary Figures S1-S4; Supplementary Tables S1-S3.

Purpose: Paclitaxel, a widely used chemotherapeutic drug, can cause peripheral neuropathies leading to dose reductions and treatment suspensions and decreasing the quality of life of patients. It has been suggested that genetic variants altering paclitaxel pharmacokinetics increase neuropathy risk, but the major causes of interindividual differences in susceptibility to paclitaxel toxicity remain unexplained. We carried out a whole-exome sequencing (WES) study to identify genetic susceptibility variants associated with paclitaxel neuropathy.Experimental Design: Blood samples from 8 patients with severe paclitaxel-induced peripheral neuropathy were selected for WES. An independent cohort of 228 cancer patients with complete paclitaxel neuropathy data was used for variant screening by DHPLC and association analysis. HEK293 cells were used for heterologous expression and characterization of two novel CYP3A4 enzymes.Results: WES revealed 2 patients with rare CYP3A4 variants, a premature stop codon (CYP3A4*20 allele) and a novel missense variant (CYP3A4*25, p.P389S) causing reduced enzyme expression. Screening for CYP3A4 variants in the independent cohort revealed three additional CYP3A4*20 carriers, and two patients with missense variants exhibiting diminished enzyme activity (CYP3A4*8 and the novel CYP3A4*27 allele, p.L475V). Relative to CYP3A4 wild-type patients, those carrying CYP3A4 defective variants had more severe neuropathy (2- and 1.3-fold higher risk of neuropathy for loss-of-function and missense variants, respectively, P = 0.045) and higher probability of neuropathy-induced paclitaxel treatment modifications (7- and 3-fold higher risk for loss-of-function and missense variants, respectively, P = 5.9 × 10−5).Conclusion: This is the first description of a genetic marker associated with paclitaxel treatment modifications caused by neuropathy. CYP3A4 defective variants may provide a basis for paclitaxel treatment individualization. Clin Cancer Res; 21(2); 322–8. ©2014 AACR.

Supplementary data. Supplementary figure legends and supplementary tables

Purpose: Preoperative chemoradiotherapy (CRT) is the treatment of choice for rectal cancer (RC), but half of the patients do not respond, suffer unnecessary toxicities, and surgery delays. We aimed to develop a model that could predict a clinically meaningful response to CRT by using formalin-fixed paraffin-embedded (FFPE) biopsies.Experimental Design: We first carried out an exploratory screening of candidate genes by using SAGE technology to evaluate dynamic changes in the RC transcriptome in selected refractory patients before and after CRT. Next, 53 genes (24 from SAGE and 29 from the literature) were analyzed by qPCR arrays in FFPE initial biopsies from 94 stage II/III RC patients who were preoperatively treated with CRT. Tumor response was defined by using Dworak's tumor regression grade (2–3–4 vs. 0–1). Multivariate Cox methods and stepwise algorithms were applied to generate an optimized predictor of response and outcome.Results: In the training cohort (57 patients), a 13-gene signature predicted tumor response with 86% accuracy, 87% sensitivity, and 82% specificity. In a testing cohort (37 patients), the model correctly classified 6 of 7 nonresponders, with an overall accuracy of 76%. A signature-based score identified patients with a higher risk of relapse in univariate (3-year disease-free survival 64% vs. 90%, P = 0.001) and multivariate analysis (HR = 4.35 95% CI: 1.2–15.75, P = 0.02), in which it remained the only statistically significant prognostic factor.Conclusions: A basal 13-gene signature efficiently predicted CRT response and outcome. Multicentric validation by the GEMCAD collaborative group is currently ongoing. If confirmed, the predictor could be used to improve patient selection in RC studies. Clin Cancer Res; 17(12); 4145–54. ©2011 AACR.

Tumor molecular profiling upon disease progression enables investigations of the tumor evolution. Next-generation sequencing (NGS) of liquid biopsies constitutes a noninvasive readily available source of tumor molecular information. In this study, 124 plasma samples from advanced EGFR-positive NSCLC patients, treated with a first-line EGFR tyrosine kinase inhibitor (EGFR-TKI) were collected upon disease progression. The circulating cell-free DNA (cfDNA) was sequenced using the Oncomine Pan-Cancer Cell-Free Assay™. Excluding EGFR mutations, the most frequently mutated gene was TP53 (57.3%), followed by APC (11.3%), FGFR3 (7.3%), and KRAS (5.6%). Different molecular alterations were observed upon disease progression depending on the location of the original EGFR-sensitizing mutation. Specifically, the detection of the p.T790M mutation was significantly associated with the presence of exon 19 mutations in EGFR (Fisher p-value: 0.028). All KRAS activating mutations (n = 8) were detected in tumors with EGFR mutations in exons 18 and 21 (Fisher p-value < 0.001). Similarly, mutations in NRAS and HRAS were more frequently detected in samples from tumors harboring mutations in exons 18 or 21 (Fisher p-value: 0.050 and Fisher p-value: 0.099, respectively). In conclusion, our data suggest that the mechanisms underlying EGFR-TKI resistance could be dependent on the exon location of the original EGFR-sensitizing mutation.

Tumor molecular profiling upon disease progression enables investigations of the tumor evolution. Next-generation sequencing (NGS) of liquid biopsies constitutes a noninvasive readily available source of tumor molecular information. In this study, 124 plasma samples from advanced

Lung cancer is the leading cause of cancer death worldwide and the majority of the patients have advanced/metastatic disease on presentation. In clinical practice, several biomarkers and clinical factors are taken into account when choosing the best treatment option in advanced non-small-cell lung cancer (NSCLC). One potential marker may be tumor burden (TB). However, this concept is not specifically defined in NSCLC, and usually, it is used as a synonymous for aggressive disease.A non-systematic literature review was conducted. We searched for eligible randomized controlled trials from PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials with a cutoff at February 2021. The keywords included non-small-cell lung cancer, tumor burden, aggressive disease, prognosis biomarker, predictive biomarker, and immunotherapy.This review addresses the definition of TB in advanced NSCLC, the pathophysiology of high TB lesions, and the role of TB as a prognosis biomarker.The concept of aggressive disease, as high tumor burden definition, remains poorly defined and rarely considered in clinical research or clinical practice in oncology. The identification of this subgroup of patients could be interesting for defining and optimizing a more aggressive treatment strategy.