Monitoring the Progression of Liver Fluke-Induced Cholangiocarcinoma in a Hamster Model Using Synchrotron FTIR Microspectroscopy and Focal Plane Array Infrared Imaging

FTIR microspectroscopic study of gastric cancer AGS cells apoptosis induced by As2O3

As2O3 has shown significant anti-gastric cancer effects, but the mechanism is still unclear. Thus, biomacromolecular changes induced by As2O3 were investigated by using human gastric cancer AGS cells as the model. Flow cytometry results confirmed that As2O3 induced AGS cells apoptosis. Fourier transform infrared (FTIR) microspectroscopy detected biomacromolecular changes during As2O3-induced AGS cells apoptosis sensitively: IR spectra showed significant changes in the lipids content and the proteins and DNA structure. Peak-area ratios indicated obvious changes in the lipids and DNA content and the proteins structure, while also showing a relatively good linear relationship between A1733/A969 and the apoptosis rate. PCA exhibited significant alteration in nucleic acids while curve fitting further revealed the changes in nucleic acids and proteins. On the whole, our study explored As2O3-induced gastric cancer cells apoptosis in depth on the basis of analyzing biomacromolecular changes, in addition, it also suggested FTIR microspectroscopy to be possibly useful in the research of apoptosis.

A radiomics model based on magnetic resonance imaging to predict cytokeratin 7/19 expression and liver fluke infection of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. HCC with liver fluke infection could harbor unique biological behaviors. This study was aimed at investigating radiomics features of HCC with liver fluke infection and establishing a model to predict the expression of cytokeratin 7 (CK7) and cytokeratin 19 (CK19) as well as prognosis at the same time. A total of 134 HCC patients were included. Gadoxetic acid-enhanced magnetic resonance imaging (MRI) images of all patients were acquired. Radiomics features of the tumor were extracted and then data dimensionality was reduced. The radiomics model was established to predict liver fluke infection and the radiomics score (Radscore) was calculated. There were 11 features in the four-phase combined model. The efficiency of the combined model increased significantly compared to each single-phase MRI model. Radscore was an independent predictor of liver fluke infection. It was also significantly different between different expression of CK7/ CK19. Meanwhile, liver fluke infection was associated with CK7/CK19 expression. A cut-off value was set up and all patients were divided into high risk and low risk groups of CK7/CK19 positive expression. Radscore was also an independent predictor of these two biomarkers. Overall survival (OS) and recurrence free survival (RFS) of negative liver fluke infection group were significantly better than the positive group. OS and RFS of negative CK7 and CK19 expression were also better, though not significantly. Positive liver fluke infection and CK19 expression prediction groups harbored significantly worse OS and RFS, survival of positive CK7 expression prediction was unsatisfying as well. A radiomics model was established to predict liver fluke infection among HCC patients. This model could also predict CK7 and CK19 expression. OS and RFS could be foreseen by this model at the same time.

Detection of Human Cholangiocarcinoma Markers in Serum Using Infrared Spectroscopy

Simple Summary

Cholangiocarcinoma is a form of liver cancer that is found, predominantly, in Thailand. Due to the non-specific symptoms and laboratory investigation, it is difficult to rule out cholangiocarcinoma from other liver conditions. Here, we demonstrate the development of a diagnostic tool for cholangiocarcinoma, based on the ATR-FTIR analyses of sera, coupled with multivariate analyses and machine learning tools to obtain a better specificity. The innovative approach that shows highly promising results for this otherwise difficult to diagnose cancer.

Abstract

Cholangiocarcinoma (CCA) is a malignancy of the bile duct epithelium. Opisthorchis viverrini infection is a known high-risk factor for CCA and in found, predominantly, in Northeast Thailand. The silent disease development and ineffective diagnosis have led to late-stage detection and reduction in the survival rate. Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) is currently being explored as a diagnostic tool in medicine. In this study, we apply ATR-FTIR to discriminate CCA sera from hepatocellular carcinoma (HCC), biliary disease (BD) and healthy donors using a multivariate analysis. Spectral markers differing from healthy ones are observed in the collagen band at 1284, 1339 and 1035 cm⁻¹, the phosphate band (vsPO2−) at 1073 cm⁻¹, the polysaccharides band at 1152 cm⁻¹ and 1747 cm⁻¹ of lipid ester carbonyl. A Principal Component Analysis (PCA) shows discrimination between CCA and healthy sera using the 1400–1000 cm⁻¹ region and the combined 1800—1700 + 1400–1000 cm⁻¹ region. Partial Least Square-Discriminant Analysis (PLS-DA) scores plots in four of five regions investigated, namely, the 1400–1000 cm⁻¹, 1800–1000 cm⁻¹, 3000–2800 + 1800–1000 cm⁻¹ and 1800–1700 + 1400–1000 cm⁻¹ regions, show discrimination between sera from CCA and healthy volunteers. It was not possible to separate CCA from HCC and BD by PCA and PLS-DA. CCA spectral modelling is established using the PLS-DA, Support Vector Machine (SVM), Random Forest (RF) and Neural Network (NN). The best model is the NN, which achieved a sensitivity of 80–100% and a specificity between 83 and 100% for CCA, depending on the spectral window used to model the spectra. This study demonstrates the potential of ATR-FTIR spectroscopy and spectral modelling as an additional tool to discriminate CCA from other conditions.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Probing the Anti-Cancer Potency of Sulfated Galactans on Cholangiocarcinoma Cells Using Synchrotron FTIR Microspectroscopy, Molecular Docking, and In Vitro Studies

Sulfated galactans (SG) isolated from red alga Gracilaria fisheri have been reported to inhibit the growth of cholangiocarcinoma (CCA) cells, which was similar to the epidermal growth factor receptor (EGFR)-targeted drug, cetuximab. Herein, we studied the anti-cancer potency of SG compared to cetuximab. Biological studies demonstrated SG and cetuximab had similar inhibition mechanisms in CCA cells by down-regulating EGFR/ERK pathway, and the combined treatment induced a greater inhibition effect. The molecular docking study revealed that SG binds to the dimerization domain of EGFR, and this was confirmed by dimerization assay, which showed that SG inhibited ligand-induced EGFR dimer formation. Synchrotron FTIR microspectroscopy was employed to examine alterations in cellular macromolecules after drug treatment. The SR-FTIR-MS elicited similar spectral signatures of SG and cetuximab, pointing towards the bands of RNA/DNA, lipids, and amide I vibrations, which were inconsistent with the changes of signaling proteins in CCA cells after drug treatment. Thus, this study demonstrates the underlined anti-cancer mechanism of SG by interfering with EGFR dimerization. In addition, we reveal that FTIR signature spectra offer a useful tool for screening anti-cancer drugs’ effect.