Immunoaffinity Intact-Mass Spectrometry for the Detection of Endogenous Concentrations of the Acetylated Protein Tumor Biomarker Neuron Specific Enolase.

Intact-mass spectrometry has huge potential for clinical application, as it enables both quantitative and qualitative analysis of intact proteins and possibly unlocks additional pathophysiological information via, e.g., detection of specific post-translational modifications (PTMs). Such valuable and clinically useful selectivity is typically lost during conventional bottom-up mass spectrometry. We demonstrate an innovative immunoprecipitation protein enrichment assay coupled to ultrahigh performance liquid chromatography quadrupole time-of-flight high resolution mass spectrometry (UPLC-QToF-HRMS) for the fast and simple identification of the protein tumor marker Neuron Specific Enolase Gamma (NSEγ) at low endogenous concentrations in human serum. Additionally, using the combination of immunoaffinity purification with intact mass spectrometry, the presence of NSEγ in an acetylated form in human serum was detected. This highlights the unique potential of immunoaffinity intact mass spectrometry in clinical diagnostics.

Strengths and challenges in current lung cancer care: Timeliness and diagnostic procedures in six Dutch hospitals.

OBJECTIVES: Timely diagnosis of lung cancer (LC) is crucial to achieve optimal patient care and outcome. Moreover, the number of procedures required to obtain a definitive diagnosis can have a large influence on the life expectancy of a patient. Here, adherence with existing Dutch guidelines for timeliness and type and number of invasive and imaging procedures was assessed. MATERIALS AND METHODS: 1096 patients with suspected LC were enrolled in this multicenter prospective study (NL9146). The overall survival, time from referral to the first appointment with the pulmonologist, time to diagnosis and treatment, and the number of imaging and invasive procedures were evaluated. Patients were divided into different diagnostic groupsearly- and advanced stage non-small-cell lung cancer (NSCLC), small-cell lung cancer (SCLC), large cell neuroendocrine carcinoma of the lung (LCNEC), patients without LC and patients without a definitive diagnosis. RESULTS: The majority of patients (66 %) received a definitive diagnosis within 5 weeks, although the time to diagnosis of early-stage LC patients and patients without LC was significantly longer comparted to advanced stage LC. An increase in invasive procedures was seen for early-stage LC compared to advanced stage LC and for 13 % of the advanced stage non-squamous NSCLC patients up to three additional invasive procedures were performed solely to obtain sufficient material for NGS. For patients without a definitive diagnosis, 50 % did undergo at least one invasive procedure, while 11 % did not wish to undergo any invasive procedures. CONCLUSION: These insights could aid in improved LC diagnostics and efficient implementation of new techniques like liquid biopsy and artificial intelligence. This may lead to more timely LC care, a decreased number of invasive procedures, less variability between the diagnostic trajectory of different patients and aid in obtaining a definitive diagnosis for all patients.

Quantification of the lung cancer tumor marker CYFRA 21-1 using protein precipitation, immunoaffinity bottom-up LC-MS/MS.

OBJECTIVES: Numerous studies have proven the potential of cytokeratin 19 fragment 21-1 (CYFRA 21-1) detection in the (early) diagnosis and treatment monitoring of non-small cell lung cancer (NSCLC). Conventional immunoassays for CYFRA 21-1 quantification are however prone to interferences and lack diagnostic sensitivity and standardization. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an emerging approach based on a different, often superior, detection principle, which may improve the clinical applicability of CYFRA 21-1 in cancer diagnostics. Therefore, we developed and validated a protein precipitation, immunoaffinity (IA) LC-MS/MS assay for quantitative analysis of serum CYFRA 21-1. METHODS: Selective sample preparation was performed using ammonium sulfate (AS) precipitation, IA purification, tryptic digestion and LC-MS/MS quantification using a signature peptide and isotopically labeled internal standard. The workflow was optimized and validated according to EMA guidelines and results were compared to a conventional immunoassay. RESULTS: Significant interference effects were seen during IA purification, which were sufficiently solved by performing AS precipitation prior to IA purification. A linear calibration curve was obtained in the range of 1.0-100 ng/mL (R2=0.98). Accuracy and precision were well within acceptance criteria. In sera of patients suspected of lung cancer, the method showed good correlation with the immunoassay. CONCLUSIONS: A robust AS precipitation-IA LC-MS/MS assay for the quantification of serum CYFRA 21-1 was developed. With this assay, the clinically added value of LC-MS/MS-based detection over immunoassays can be further explored.

Analysis of Neuron-Specific enolase isozymes in human serum using immunoaffinity purification and liquid chromatography-tandem mass spectrometry quantification.

Neuron-specific enolase (NSE) is a promising small-cell lung cancer (SCLC) biomarker composed of αγ and γγ isozyme dimers. As the conventional immunoassays are prone to interferences and cannot differentiate between the isozymes, we developed a multiplex immunoaffinity (IA) liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for the quantification of NSEα and NSEγ in human serum. A calibrator was prepared by performing cold denaturation of recombinantly expressed αα and γγ enolase dimers to induce a new dimer equilibrium that was determined to be approximately 1αγ:1γγ:1αα. Selective sample purification was achieved by performing IA extraction using an antibody specific towards NSEγ. The isolated αγ and γγ dimers were denatured and trypsin digested to allow quantification of the selected signature peptides and their corresponding isotopically labelled peptide internal standard. The obtained linear dynamic ranges were determined to be 1.5-56 ng/mL and 0.64-167 ng/mL for NSEα and NSEγ (R2 = 0.88 and 0.97 respectively). Validation of the assay showed acceptable accuracy and precision for NSEα and NSEγ. The method was successfully applied to patient serum in which both isozymes were detected. Compared to the conventional immunoassay, substantially lower total NSE concentrations were measured in IA LC-MS/MS. With this multiplex IA LC-MS/MS assay, the clinical value of quantifying the individual isozymes can be explored. In addition, together with the calibrator described here, it may be applied to standardize NSE immunoassays across different platforms.

Liquid biopsy-based decision support algorithms for diagnosis and subtyping of lung cancer.

OBJECTIVES: Pathologic subtyping of tissue biopsies is the gold standard for the diagnosis of lung cancer (LC), which could be complicated in cases of e.g. inconclusive tissue biopsies or unreachable tumors. The diagnosis of LC could be supported in a minimally invasive manner using protein tumor markers (TMs) and circulating tumor DNA (ctDNA) measured in liquid biopsies (LBx). This study evaluates the performance of LBx-based decision-support algorithms for the diagnosis of LC and subtyping into small- and non-small-cell lung cancer (SCLC and NSCLC) aiming to directly impact clinical practice. MATERIALS AND METHODS: In this multicenter prospective study (NL9146), eight protein TMs (CA125, CA15.3, CEA, CYFRA 21-1, HE4, NSE, proGRP and SCCA) and ctDNA mutations in EGFR, KRAS and BRAF were analyzed in blood of 1096 patients suspected of LC. The performance of individual and combined TMs to identify LC, NSCLC or SCLC was established by evaluating logistic regression models at pre-specified positive predictive values (PPV) of ≥95% or ≥98%. The most informative protein TMs included in the multi-parametric models were selected by recursive feature elimination. RESULTS: Single TMs could identify LC, NSCLC and SCLC patients with 46%, 25% and 40% sensitivity, respectively, at pre-specified PPVs. Multi-parametric models combining TMs and ctDNA significantly improved sensitivities to 65%, 67% and 50%, respectively. CONCLUSION: In patients suspected of LC, the LBx-based decision-support algorithms allowed identification of about two-thirds of all LC and NSCLC patients and half of SCLC patients. These models therefore show clinical value and may support LC diagnostics, especially in patients for whom pathologic subtyping is impossible or incomplete.

Correction of the NSE concentration in hemolyzed serum samples improves its diagnostic accuracy in small-cell lung cancer.

Neuron-specific enolase (NSE) is a well-known biomarker for the diagnosis, prognosis and treatment monitoring of small-cell lung cancer (SCLC). Nevertheless, its clinical applicability is limited since serum NSE levels are influenced by hemolysis, leading to falsely elevated results. Therefore, this study aimed to develop a hemolysis correction equation and evaluate its role in SCLC diagnostics. Two serum pools were spiked with increasing amounts of hemolysate obtained from multiple individuals. A hemolysis correction equation was obtained by analyzing the relationship between the measured NSE concentration and the degree of hemolysis. The equation was validated using intentionally hemolyzed serum samples, which showed that the correction was accurate for samples with an H-index up to 30 µmol/L. Correction of the measured NSE concentration in patients suspected of lung cancer caused an increase in AUC and a significantly lower cut-off value for SCLC detection when compared to uncorrected results. Therefore, a hemolysis correction equation should be used to correct falsely elevated NSE concentrations. Results of samples with an H-index above 30 µmol/L should not be reported to clinicians. Application of the equation illustrates the importance of hemolysis correction in SCLC diagnostics and questions the correctness of the currently used diagnostic cut-off value.