Laura L. Meijer

Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets

Summary Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92–0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83–0.95; p < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.

FOLFIRINOX and translational studies: Towards personalized therapy in pancreatic cancer

Pancreatic cancer is an extremely aggressive disease; although progress has been made in the last few years, the prognosis of these patients remains dismal. FOLFIRINOX is now considered a standard treatment in first-line setting, since it demonstrated an improved overall and progression-free survival vs gemcitabine alone. However, the enthusiasm over the benefit of this three-drug regimen is tempered by the associated increased toxicity profile, and many efforts have been made to improve the feasibility of this schedule. After a more recent phase III trial showing an improved outcome over gemcitabine, the combination of gemcitabine/nab-paclitaxel emerged as another standard first-line treatment. However, this treatment is also associated with more side effects. In addition, despite initial promising data on the predictive role of SPARC levels, recent studies showed that these levels are not associated with nab-paclitaxel efficacy. The choice to use this treatment over FOLFIRINOX is therefore a topic of debate, also because no validated biomarkers to guide FOLFIRINOX treatment are available. In the era of actionable mutations and target agents it would be desirable to identify molecular factors or biomarkers to predict response to therapy in order to maximize the efficacy of treatment and avoid useless toxic effects for non-responding patients. However, until today the milestone of treatment for pancreatic cancer remains chemotherapy combinations, without predictive or monitoring tools existing to optimize therapy. This review analyzes the state-of-the-art treatments, promises and limitations of targeted therapies, ongoing trials and future perspectives, including potential role of microRNAs as predictive biomarkers.

Circulating microRNAs as diagnostic biomarkers for pancreatic cancer.

There is an urgent need for novel and reliable biomarkers for the diagnosis and prognostication of pancreatic ductal adenocarcinoma (PDAC). Circulating microRNAs (miRNAs) have been extensively profiled in PDAC blood samples, but few studies have performed adequate validation of candidate markers. The evaluated study by Xu et al. investigated pre-operative plasma miRNAs from PDAC patients over three phases and three surgical centers. They revealed miR-486-5p and miR-938 were able to discriminate PDAC patients from healthy controls and those with chronic pancreatitis. The diagnostic ability of miR-486-5p for identifying PDAC from healthy controls was comparable to that of CA 19-9. This study provides further evidence for the use of blood-based miRNAs as diagnostic biomarkers in PDAC. However, as these have not been identified in previous studies these require further validation and methodology needs to be standardized if these are ever to be used in the clinic.

Outcomes and Treatment Options for Duodenal Adenocarcinoma: A Systematic Review and Meta-Analysis

BackgroundDuodenal adenocarcinoma (DA) is a rare tumor for which survival data per treatment modality and disease stage are unclear. This systematic review and meta-analysis aims to summarize the current literature on patient outcome after surgical, (neo)adjuvant, and palliative treatment in patients with DA.MethodsA systematic search was performed according to the preferred reporting items for systematic reviews and meta-analyses guidelines, to 25 April 2017. Primary outcome was overall survival (OS), specified for treatment strategy or disease stage. Random-effects models were used for the calculation of pooled odds ratios per treatment modality. Included papers were also screened for prognostic factors.ResultsA total of 26 observational studies, comprising 6438 patients with DA, were included. Of these, resection with curative intent was performed in 71% (range 53–100%) of patients, and 29% received palliative treatment (range 0–61%). The pooled 5-year OS rate was 46% after curative resection, compared with 1% in palliative-treated patients (OR 0.04, 95% confidence interval [CI] 0.02–0.09, p < 0.0001). Both segmental resection and pancreaticoduodenectomy allowed adequate assessment of lymph node involvement and resulted in similar OS. Lymph node involvement correlated with worse OS (pooled 5-year survival rate 21% for nodal metastases vs. 65% for node-negative disease; OR 0.17, 95% CI 0.11–0.27, p < 0.0001). In the current literature, no survival benefit for adjuvant therapy after curative resection was found.ConclusionResection with curative intent, either pancreaticoduodenectomy or segmental resection, and lack of nodal metastases, favors survival for DA. Further studies exploring multimodality (neo)adjuvant therapy are warranted to investigate their benefit.

Bioinformatic analysis reveals pancreatic cancer molecular subtypes specific to the tumor and the microenvironment.

ABSTRACT Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by a dense desmoplastic reaction surrounding malignant epithelial cells. Interaction between the epithelial and stromal compartments is suggested to enhance its aggressive nature. Indeed, therapies targeting the stroma, as well as the tumor cells, may improve survival outcomes for patients. The evaluated study by Moffitt et al. used bioinformatic techniques to separate gene expression patterns of normal tissues from PDAC and stroma in a large cohort of samples. The researchers identified two different subtypes of PDAC (‘classical’ and ‘basal-like’) and surrounding stroma (‘normal’ and ‘activated’). The basal-like subtype was associated with worse prognosis and a trend towards better response to adjuvant therapy. Hopefully, the molecular stratification of PDAC will potentially allow more personalized treatment strategies and guide clinical decision making.

Usefulness of Measuring microRNAs in Bile and Plasma for Pancreatic Ductal Adenocarcinoma Diagnosis

Usefulness of Measuring microRNAs in Bile and Plasma for Pancreatic Ductal Adenocarcinoma Diagnosis

Circulating microRNAs as dynamic biomarkers of response to treatment with FOLFIRINOX combination therapy in advanced pancreatic ductal adenocarcinoma

Abstract Background Advanced pancreatic ductal adenocarcinoma remains a clinical challenge. Only a third of patients receiving FOLFIRINOX combination chemotherapy displays tumour downstaging. Because of their high stability in plasma, especially in extracellular vesicles, microRNAs (miRNAs) hold great promise as a new class of minimally invasive biomarkers. Our aim was to identify differently expressed, blood-based miRNAs to select and monitor patients with advanced pancreatic ductal adenocarcinoma who would benefit from FOLFIRINOX. Methods In this prospective, multicentre study, we enrolled 50 patients with locally advanced or metastatic pancreatic ductal adenocarcinoma receiving FOLFIRINOX. The first cohort of 11 patients was selected according to their short versus long progression-free survival, and miRNA profiling was performed to identify differentially expressed circulating-free miRNAs. Emerging miRNAs, as well as various endogenous control miRNAs, were then validated in extracellular vesicles by RT-PCR in a second cohort of 16 non-progressive patients (ie, those with partial response or stable disease). No further analyses were performed in the other 23 patients, who included progressive patients or those without samples available for exosomes extraction. Findings MiR-29a emerged as a potential biomarker both in the profiling and RT-PCR analyses, in the first and second cohorts, respectively. In particular, it was significantly upregulated (2·36-fold change, p=0·0024) in extracellular vesicles after five cycles of FOLFIRINOX therapy in non-progressive disease. Interestingly, the expression of miR-29a was significantly higher in extracellular vesicles than in circulating free miR-29a (p Interpretation We show that altered levels of miR-29a in plasma extracellular vesicles can anticipate progression of pancreatic ductal adenocarcinoma and guide therapeutic options. Higher miR-29a expression in extracellular vesicles than in circulating free miR-29a suggests an active secretion and warrants further studies on its role in tumour–host interactions. These findings open new opportunities to explore blood-based miRNA profiles and specific miRNA candidates to select patients most likely to respond to FOLFIRINOX. Funding Bennink Foundation, Netherlands; Cancer Center Amsterdam Foundation, Netherlands; AIRC Grant Start Up, Italy; FAS grant, Italy; Action Against Cancer, UK; No Surrender Cancer Trust (in memory of Jason Boas), UK.

hENT-1 Expression and Localization Predict Outcome After Adjuvant Gemcitabine in Resected Cholangiocarcinoma Patients

In this letter to the editor, the authors discuss the use of human equilibrative nucleoside transporter 1 (hENT-1) as a biomarker in patients with cholangiocarcinoma. They encourage standardization of techniques to evaluation expression of proteins such as hENT-1 and suggest additional studies investigating the active metabolites of gemcitabine, the use of liquid biopsies, and improved statistical methods.