Pre-analytical stability of the CEA, CYFRA 21.1, NSE, CA125 and HE4 tumor markers.

BACKGROUND: For lung cancer, circulating tumor markers (TM) are available to guide clinical treatment decisions. To ensure adequate accuracy, pre-analytical instabilities need to be known and addressed in the pre-analytical laboratory protocols. OBJECTIVE: This study investigates the pre-analytical stability of CA125, CEA, CYFRA 21.1, HE4 and NSE for the following pre-analytical variables and procedures; i) whole blood stability, ii) serum freeze-thaw cycles, iii) electric vibration mixing and iv) serum storage at different temperatures. METHODS: Left-over patient samples were used and for every investigated variable six patient samples were used and analysed in duplicate. Acceptance criteria were based on analytical performance specifications based on biological variation and significant differences with baseline. RESULTS: Whole blood was stable for at least 6 hours for all TM except for NSE. Two freeze-thaw cycles were acceptable for all TM except CYFRA 21.1. Electric vibration mixing was allowed for all TM except for CYFRA 21.1. Serum stability at 4°C was 7 days for CEA, CA125, CYFRA 21.1 and HE4 and 4 hours for NSE. CONCLUSIONS: Critical pre-analytical processing step conditions were identified that, if not taken into account, will result in reporting of erroneous TM results.

A Micro-Costing Framework for Circulating Tumor DNA Testing in Dutch Clinical Practice.

Circulating tumor DNA (ctDNA) is a promising new biomarker with multiple potential applications in cancer care. Estimating total cost of ctDNA testing is necessary for reimbursement and implementation, but challenging because of variations in workflow. We aimed to develop a micro-costing framework for consistent cost calculation of ctDNA testing. First, the foundation of the framework was built, based on the complete step-wise diagnostic workflow of ctDNA testing. Second, the costing method was set up, including costs for personnel, materials, equipment, overhead, and failures. Third, the framework was evaluated by experts and applied to six case studies, including PCR-, mass spectrometry-, and next-generation sequencing-based platforms, from three Dutch hospitals. The developed ctDNA micro-costing framework includes the diagnostic workflow from blood sample collection to diagnostic test result. The framework was developed from a Dutch perspective and takes testing volume into account. An open access tool is provided to allow for laboratory-specific calculations to explore the total costs of ctDNA testing specific workflow parameters matching the setting of interest. It also allows to straightforwardly assess the impact of alternative prices or assumptions on the cost per sample by simply varying the input parameters. The case studies showed a wide range of costs, from €168 to €7638 ($199 to $9124) per sample, and generated information. These costs are sensitive to the (coverage of) platform, setting, and testing volume.

Combining variant detection and fragment length analysis improves detection of minimal residual disease in postsurgery circulating tumour DNA of stage II-IIIA NSCLC patients.

Stage II-IIIA nonsmall cell lung cancer (NSCLC) patients receive adjuvant chemotherapy after surgery as standard-of-care treatment, even though only approximately 5.8% of patients will benefit. Identifying patients with minimal residual disease (MRD) after surgery using tissue-informed testing of postoperative plasma circulating cell-free tumour DNA (ctDNA) may allow adjuvant therapy to be withheld from patients without MRD. However, the detection of MRD in the postoperative setting is challenging, and more sensitive methods are urgently needed. We developed a method that combines variant calling and a novel ctDNA fragment length analysis using hybrid capture sequencing data. Among 36 stage II-IIIA NSCLC patients, this method distinguished patients with and without recurrence of disease in a 20 times repeated 10-fold cross validation with 75% accuracy (P = 0.0029). In contrast, using only variant calling or only fragment length analysis, no signification distinction between patients was shown (P = 0.24 and P = 0.074 respectively). In addition, a variant-level fragmentation score was developed that was able to classify variants detected in plasma cfDNA into tumour-derived or white-blood-cell-derived variants with 84% accuracy. The findings in this study may help drive the integration of various types of information from the same data, eventually leading to cheaper and more sensitive techniques to be used in this challenging clinical setting.

An Automated Correction Algorithm (ALPACA) for ddPCR Data Using Adaptive Limit of Blank and Correction of False Positive Events Improves Specificity of Mutation Detection.

BACKGROUND: Bio-Rad droplet-digital PCR is a highly sensitive method that can be used to detect tumor mutations in circulating cell-free DNA (cfDNA) of patients with cancer. Correct interpretation of ddPCR results is important for optimal sensitivity and specificity. Despite its widespread use, no standardized method to interpret ddPCR data is available, nor have technical artifacts affecting ddPCR results been widely studied. METHODS: False positive rates were determined for 6 ddPCR assays at variable amounts of input DNA, revealing polymerase induced false positive events (PIFs) and other false positives. An in silico correction algorithm, known as the adaptive LoB and PIFs: an automated correction algorithm (ALPACA), was developed to remove PIFs and apply an adaptive limit of blank (LoB) to individual samples. Performance of ALPACA was compared to a standard strategy (no PIF correction and static LoB = 3) using data from commercial reference DNA, healthy volunteer cfDNA, and cfDNA from a real-life cohort of 209 patients with stage IV nonsmall cell lung cancer (NSCLC) whose tumor and cfDNA had been molecularly profiled. RESULTS: Applying ALPACA reduced false positive results in healthy cfDNA compared to the standard strategy (specificity 98 vs 88%, P = 10-5) and stage IV NSCLC patient cfDNA (99 vs 93%, P = 10-11), while not affecting sensitivity in commercial reference DNA (70 vs 68% P = 0.77) or patient cfDNA (82 vs 88%, P = 0.13). Overall accuracy in patient samples was improved (98 vs 92%, P = 10-7). CONCLUSIONS: Correction of PIFs and application of an adaptive LoB increases specificity without a loss of sensitivity in ddPCR, leading to a higher accuracy in a real-life cohort of patients with stage IV NSCLC.

Cell-free DNA in the supernatant of pleural effusion can be used to detect driver and resistance mutations, and can guide tyrosine kinase inhibitor treatment decisions.

OBJECTIVES: Molecular profiling of tumours has become the mainstay of diagnostics for metastasised solid malignancies and guides personalised treatment, especially in nonsmall cell lung cancer (NSCLC). In current practice, it is often challenging to obtain sufficient tumour material for reliable molecular analysis. Cell-free DNA (cfDNA) in blood or other bio-sources could present an alternative approach to obtain genetic information from the tumour. In a retrospective cohort we analysed the added value of cfDNA analysis in pleural effusions for molecular profiling. METHODS: We retrospectively analysed both the supernatant and the cell pellet of 44 pleural effusions sampled from 39 stage IV patients with KRAS (n=23) or EGFR (n=16) mutated tumours to detect the original driver mutation as well as for EGFR T790M resistance mutations. Patients were diagnosed with either NSCLC (n=32), colon carcinoma (n=4), appendiceal carcinoma (n=2) or adenocarcinoma of unknown primary (n=1). Samples collected in the context of routine clinical care were stored at the Netherlands Cancer Institute biobank. We used droplet digital PCR for analysis. RESULTS: The driver mutation could be detected in 36 of the 44 pleural effusions by analysis of both the supernatant (35 out of 44 positive) and the cell pellet (31 out of 44 positive). In seven out of 20 pleural effusions from patients with EGFR mutation-positive tumours, a T790M mutation was detected. All seven supernatants and cell pellets were positive. CONCLUSIONS: cfDNA in pleural effusion can be used to detect driver mutations as well as resistance mechanisms like EGFR T790M in pleural effusion with high accuracy and is therefore a valuable bio-source.

A serum and platelet-rich plasma serotonin assay using liquid chromatography tandem mass spectrometry for monitoring of neuroendocrine tumor patients.

BACKGROUND: Serotonin is used for the diagnosis and follow-up of neuroendocrine tumors (NET). We describe the analytical and clinical validation of a liquid chromatography tandem mass spectrometry (LC-MS/MS) based serotonin assay for serum and platelet-rich plasma (PRP). METHODS: An LC-MS/MS based method for serum and PRP serotonin was validated by determination of assay imprecision, carry-over, linearity, interference, recovery, sample stability and a matrix/method comparison of serum and PRP serotonin was made with whole blood serotonin. Furthermore, upper limits of normal were determined and serotonin concentrations of healthy individuals, 14 NET patients without evidence of disease and 51 NET patients with evidence of disease were compared. RESULTS: For serum and PRP fractions, total assay imprecision was <5%. All correlation coefficients were 0.98 and the serum and platelet-rich serotonin upper limit of normal were 5.5nmol/109 platelet and 5.1nmol/109 platelet, respectively. NET patients with confirmed evidence of disease had significantly higher serum and PRP serotonin levels when compared to NET patients without evidence of disease and healthy volunteers. CONCLUSIONS: LC-MS/MS based serum and PRP serotonin assays were developed with suitable analytical characteristics. Furthermore, serum and PRP serotonin was found to be useful for monitoring NET patients.

Choice of tumour markers in patients with neuroendocrine tumours is dependent on the histological grade. A marker study of Chromogranin A, Neuron specific enolase, Progastrin-releasing peptide and cytokeratin fragments.

BACKGROUND: Chromogranin A (CgA) is the most important tumour marker for well-differentiated neuroendocrine tumours (NET) and neuron specific enolase (NSE) for poorly differentiated neuroendocrine carcinoma (NEC). This study investigated whether the markers progastrin-releasing peptide (proGRP) and cytokeratin fragments (CKfr) CK8, CK18 and CK19 (MonoTotal) can be of additional value to the histological classification and help predict survival in these patients. METHODS: CgA, NSE, proGRP and CKfr were measured in 242 patients with grade 1 NET (G1NET), 38 with grade 2 NET (G2NET), 42 with large cell NEC (LCNEC), 251 with small cell NEC (SCNEC) and in 282 healthy persons. Results were compared with tumour characteristics and survival by means of Receiver Operating Characteristics (ROC) curves and Cox regression analyses. RESULTS: The largest area under the ROC curve was for CgA (0.86, 0.91 and 0.90, respectively) when comparing patients with G1NET, G2NET and LCNEC with healthy persons. ProGRP showed the highest sensitivity (73%) at 95% specificity in patients with SCNEC. In a multivariate survival analysis, only CKfr was associated with survival (P<0.0001) for patients with well-differentiated NET (G1NET and G2NET). For patients with poorly differentiated NEC, both CKfr and NSE were associated with survival (P<0.0001 and P=0.003, respectively). CONCLUSION: Within all histological groups a combination of tumour markers proved to be more informative as diagnostic and prognostic marker than each marker alone. In patients with well-differentiated NET and LCNEC we recommend the use of CgA and CKfr, whilst in patients with SCNEC, proGRP and CKfr are preferred.