A multi-modality approach for enhancing the diagnosis of cholangiocarcinoma

Background: Cholangiocarcinoma (CC) is a malignancy of the bile ducts and mortality is high as patients present too late for curative surgery. In most cases of CC the aetiology is unknown, whilst diagnosis and staging are challenging. The hepatobiliary system excretes carcinogenic toxins and genetic mutations in biliary transporters lead to dysfunction and cholestasis, potentially contributing to cholangiocarcinogenesis. Polymorphisms in the NKG2D receptor have previously been associated with CC in primary sclerosing cholangitis (PSC). Such a role has not been investigated in sporadic CC. CC is difficult to diagnose, particularly in those with PSC. The transition from benign to malignant biliary disease is likely to be reflected in changes to the plasma proteome. However, current plasma biomarkers do not reliably distinguish benign from malignant biliary strictures. Elevation of neutrophil gelatinase-associated lipocalin (NGAL) has been demonstrated in the bile of patients with CC but has not been investigated as a plasma protein biomarker. Staging of CC is inaccurate, with only a minority of operated patients cured. Higher resolution MRI would improve diagnosis and staging. The work presented in this thesis represents a multimodality approach to enhance the diagnosis of CC: Genetic studies: Genetic variation in major biliary transporter proteins, and the NKG2D receptor, were investigated. Single nucleotide polymorphisms (SNPs) in candidate genes were selected using HapMap. DNA from 173 CC patients and 265 healthy controls was genotyped. SNPs in ABCB11, MDR3 and ATP8B1 were nominally associated with altered susceptibility to CC, suggesting a potential role in cholangiocarcinogenesis. The previous association of NKG2D variation with CC in PSC was not replicated in sporadic CC, suggesting a possible difference in pathogenesis. Protein studies: Plasma from subjects with CC, benign disease, and from healthy controls was studied. Two proteomic techniques, liquid chromatography-tandem mass spectrometry (LCMS/ MS) and surfaced enhanced laser desorption ionization time-of-flight MS (SELDITOF MS), were utilised. Differentially expressed proteins were identified where possible. LC-MS/MS fully identified six proteins that were differentially expressed in CC compared to gall stone disease patients. SELDI-TOF MS identified seven m/z peaks that showed significant utility in discriminating CC from PSC controls. An ELISA approach was used to study plasma NGAL levels in CC. Although differentially expressed between CC and healthy control groups, the utility of NGAL in discriminating CC from PSC was limited. Imaging studies: An endoscope-mounted MR coil and intraductal MR detector coil were developed. Quantitative resolution and signal-to-noise-ratio (SNR) testing, and qualitative tissue discrimination appraisal, were undertaken. Sub-0.7mm resolution and excellent SNRs have been demonstrated. High-resolution has been demonstrated in imaged tissue. Imaging with the new devices compares favourably with endoscopic ultrasound imaging

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed