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We evaluated the prognostic value of hypoalbuminemia in context of various biomarkers at baseline, including clinical, genomic, transcriptomic, and blood-based markers, in patients with metastatic melanoma treated with anti-PD-1 monotherapy or anti-PD-1/anti-CTLA-4 combination therapy (n = 178). An independent validation cohort (n = 79) was used to validate the performance of hypoalbuminemia compared to serum LDH (lactate dehydrogenase) levels. Pre-treatment hypoalbuminemia emerged as the strongest predictor of poor outcome for both OS (HR = 4.01, 95% CI 2.10–7.67, Cox P = 2.63e−05) and PFS (HR = 3.72, 95% CI 2.06–6.73, Cox P = 1.38e−05) in univariate analysis. In multivariate analysis, the association of hypoalbuminemia with PFS was independent of serum LDH, IFN-γ signature expression, TMB, age, ECOG PS, treatment line, treatment type (combination or monotherapy), brain and liver metastasis (HR = 2.76, 95% CI 1.24–6.13, Cox P = 0.0131). Our validation cohort confirmed the prognostic power of hypoalbuminemia for OS (HR = 1.98, 95% CI 1.16–3.38; Cox P = 0.0127) and was complementary to serum LDH in analyses for both OS (LDH-adjusted HR = 2.12, 95% CI 1.2–3.72, Cox P = 0.00925) and PFS (LDH-adjusted HR = 1.91, 95% CI 1.08–3.38, Cox P = 0.0261). In conclusion, pretreatment hypoalbuminemia was a powerful predictor of outcome in ICI in melanoma and showed remarkable complementarity to previously established biomarkers, including high LDH. [ABSTRACT FROM AUTHOR]

In contrast to primary colorectal cancer (CRC) little is known about the genomic landscape of metastasized CRC. Here we present whole genome sequencing data of metastases of 429 CRC patients participating in the pan-cancer CPCT-02 study (NCT01855477). Unsupervised clustering using mutational signature patterns highlights three major patient groups characterized by signatures known from primary CRC, signatures associated with received prior treatments, and metastasis-specific signatures. Compared to primary CRC, we identify additional putative (non-coding) driver genes and increased frequencies in driver gene mutations. In addition, we identify specific genes preferentially affected by microsatellite instability. CRC-specific 1kb-10Mb deletions, enriched for common fragile sites, and LINC00672 mutations are associated with response to treatment in general, whereas FBXW7 mutations predict poor response specifically to EGFR-targeted treatment. In conclusion, the genomic landscape of mCRC shows defined changes compared to primary CRC, is affected by prior treatments and contains features with potential clinical relevance. Molecular landscapes of metastatic colorectal cancers (mCRC) have often been restricted to coding regions or low numbers of patients. Here the authors present a whole-genome landscape of 429 mCRC patients, revealing the mutational impact of prior therapies and potential actionable targets. [ABSTRACT FROM AUTHOR]

Purpose: To support future dosing recommendations, the effect of food on the pharmacokinetics of adavosertib, a first-in-class, small-molecule reversible inhibitor of WEE1 kinase, was assessed in patients with advanced solid tumors.Methods: In this Phase I, open-label, randomized, two-period, two-sequence crossover study, the pharmacokinetics of a single 300 mg adavosertib dose were investigated in fed versus fasted states.Results: Compared with the fasted state, a high-fat, high-calorie meal (fed state) decreased adavosertib maximum plasma concentration (Cmax) by 16% and systemic exposure (area under the plasma concentration-time curve [AUC]) by 6%; AUC0-t decreased by 7% and time to maximum plasma concentration was delayed by 1.97 h (P = 0.0009). The 90% confidence interval of the geometric least-squares mean treatment ratio for AUC and AUC0-t was contained within the no-effect limits (0.8-1.25), while that of Cmax crossed the lower bound of the no-effect limits. Adverse events (AEs) related to adavosertib treatment were reported by 20 (64.5%) of the 31 patients treated in this study. Grade ≥ 3 AEs were reported by four (12.9%) patients (one in the fed state, three in the fasted state); two of these AEs were considered treatment-related by the investigator. Three serious AEs were reported in three (9.7%) patients; these were not considered treatment-related. No patients discontinued because of treatment-related AEs, and no new safety signals were reported.Conclusion: A high-fat meal did not have a clinically relevant effect on the systemic exposure of adavosertib, suggesting that adavosertib can be administered without regard to meals. [ABSTRACT FROM AUTHOR]

Metastatic cancer is a major cause of death and is associated with poor treatment efficacy. A better understanding of the characteristics of late-stage cancer is required to help adapt personalized treatments, reduce overtreatment and improve outcomes. Here we describe the largest, to our knowledge, pan-cancer study of metastatic solid tumour genomes, including whole-genome sequencing data for 2,520 pairs of tumour and normal tissue, analysed at median depths of 106× and 38×, respectively, and surveying more than 70 million somatic variants. The characteristic mutations of metastatic lesions varied widely, with mutations that reflect those of the primary tumour types, and with high rates of whole-genome duplication events (56%). Individual metastatic lesions were relatively homogeneous, with the vast majority (96%) of driver mutations being clonal and up to 80% of tumour-suppressor genes being inactivated bi-allelically by different mutational mechanisms. Although metastatic tumour genomes showed similar mutational landscape and driver genes to primary tumours, we find characteristics that could contribute to responsiveness to therapy or resistance in individual patients. We implement an approach for the review of clinically relevant associations and their potential for actionability. For 62% of patients, we identify genetic variants that may be used to stratify patients towards therapies that either have been approved or are in clinical trials. This demonstrates the importance of comprehensive genomic tumour profiling for precision medicine in cancer. The mutational landscape of metastatic cancer genomes is analysed in a large-scale, pan-cancer study of metastatic solid tumours that includes whole-genome sequencing of 2,520 tumour–normal tissue pairs. [ABSTRACT FROM AUTHOR]

Purpose: The prevalence of colorectal cancer is higher among patients with type 2 diabetes mellitus (T2D) than among patients without diabetes. Furthermore, men are at higher risk for developing colorectal cancer than women in the general population and also subsite-specific risks differ per sex. The aim was to evaluate the impact of T2D on these associations.Methods: A population-based matched cohort study was performed using data from the PHARMO Database Network. Patients with T2D were selected and matched (1:4) to diabetes free controls. Cox proportional hazards models were used to estimate hazard ratios (HRs) for CRC and its subsites. HRs were determined per sex and adjusted for age and socioeconomic status. The ratio of distal versus proximal colon cancer was calculated for people with T2D and controls per sex and stratified by age.Results: Over 55,000 people with T2D were matched to > 215,000 diabetes free controls. Men and women with T2D were 1.3 times more likely to develop colorectal cancer compared to controls. Men with T2D were at higher risk to develop distal colon cancer (hazard ratio (95% confidence interval), 1.42 (1.08-1.88)), and women with T2D were at higher risk for developing proximal colon cancer (hazard ratio (95% confidence interval), 1.58 (1.13-2.19)). For rectal cancer, no statistically significant risk was observed for both men and women.Conclusions: Sex-specific screening strategies and prevention protocols should be considered for people with T2D. More tailored screening strategies may optimize the effectiveness of colorectal cancer screening in terms of reducing incidence and mortality. [ABSTRACT FROM AUTHOR]

Purpose: The overall survival rate of patients with advanced gastric cancer is poor. Therefore, there is an urgent need for new treatment options for these patients. The identification of drug target genes located on DNA regions exhibiting high-level copy number gains (CNG) may be an effective approach, as has e.g. previously been shown for HER2. The aim of the present study was to identify putative drug targets in patients with gastric cancer by applying this strategy. Methods: Genome-wide array comparative genomic hybridization (array CGH) data available from 183 primary gastric cancer samples were analyzed through Ingenuity Pathway Analysis (IPA) to assess whether any established or potential anticancer drug target genes showed high-level CNG, including focal amplifications. Results: A total of 147 high-level gained regions were identified in the gastric cancer samples, harboring 167 genes that had previously been annotated as drug target genes. Thirty (18 %) of these genes showed high-level gains in at least 2 % of the tumors. The identified drug target genes included those for drugs known to be active in advanced (gastric) cancer, targets for targeted therapies in clinical development, as well as targets for drugs currently used for other indications but of potential interest for anticancer treatment. In addition, 12 potential drug target genes were identified, including genes involved in growth factor signaling and cell cycle regulation. Conclusion: The majority of gastric cancers carried one or more high-level CNGs or focal amplifications encompassing putative drug target genes. A number of the associated drugs are currently not being considered for treatment of gastric cancer. Based on these results we hypothesize that DNA copy number profiling may be a useful tool to identify new drug targets and to guide individualized treatment strategies in patients with gastric cancer. [ABSTRACT FROM AUTHOR]

Kinases are key enzymes involved in deregulated signal transduction associated with cancer development and progression. The advent of personalized medicine drives the development of new diagnostic tools for patient stratification and therapy selection Ginsburg and Willard (Transl Res 154:277-287, ). Since deregulation of kinase-mediated signal transduction is implied in tumorigenesis, the analysis of all kinases (the kinome) active in a particular tumor may yield tumor-specific information on aberrant cell signalling pathways. Tumor tissue kinase activity profiles may correlate with response to therapy and therefore may be used for future therapy selection. In this Trend paper we describe peptide array and mass spectrometry-based technologies and new developments for kinome profiling, and we present an outlook towards future implementation of therapy selection based on kinome profiling in clinical practice. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

The original version of this Article contained an error in Table 4, in which the coefficients of the LASSO regression model of treatment response corresponded to a version that was performed without non-coding genes. The original version of this Article contained an error in the Methods, section "Whole-genome sequencing; identification of somatic changes", which incorrectly read 'GATK BQSR and Haplotype Caller v3.4.46 were used to call somatic mutations'. [Extracted from the article]