Prediction of Ewing Sarcoma treatment outcome using attenuated tissue reflection FTIR tissue spectroscopy

Advancements in medical research: Exploring Fourier Transform Infrared (FTIR) spectroscopy for tissue, cell, and hair sample analysis

BACKGROUND

Fourier Transform Infrared (FTIR) spectroscopy has emerged as a powerful analytical tool in medical research, offering non-invasive and precise examination of the molecular composition of biological samples. The primary objective of this review is to underscore the benefits of FTIR spectroscopy in medicinal research, emphasizing its ability to delineate molecular fingerprints and assist in the identification of biochemical structures and key peaks in biological samples.

METHODS

This review comprehensively explores the diverse applications of FTIR spectroscopy in medical investigations, with a specific focus on its utility in analyzing tissue, cells, and hair samples. Various sources, including Google Scholar, PubMed, WorledCat and Scopus, were utilized to conduct this comprehensive literature review.

RESULTS

Recent advancements showcase the versatility of FTIR spectroscopy in elucidating cellular and molecular processes, facilitating disease diagnostics, and enabling treatment monitoring. Notably, FTIR spectroscopy has found significant utility in clinical assessment, particularly in screening counterfeit medicines, owing to its user-friendly operation and minimal sample preparation requirements. Furthermore, customs officials can leverage this technique for preliminary analysis of suspicious samples.

CONCLUSION

This review aims to bridge a gap in the literature and serve as a valuable resource for future research endeavors in FTIR spectroscopy within the medical domain. Additionally, it presents fundamental concepts of FTIR spectroscopy and spectral data interpretation, highlighting its utility as a tool for molecular analysis using Mid-Infrared (MIR) radiation.

Pelvic Ewing sarcoma: Should all patients receive pre-operative radiotherapy, or should it be delivered selectively?

BACKGROUND

Locally recurrent disease following surgical resection of Ewing sarcoma (ES) confers a poor prognosis. Limited evidence is available evaluating non-selective use of pre-operative radiotherapy (RT) for patients with pelvic ES and its effect on local control and survival.

PATIENTS AND METHODS

49 consecutive patients with pelvic ES were identified retrospectively from a prospectively collated database. Patients either received non-selective pre-operative RT and surgery (n = 27), or selective post-operative RT (n = 22) (surgery alone (n = 11) or surgery and post-operative RT (n = 11)).

RESULTS

Patients who had non-selective pre-operative radiotherapy appeared to have a higher LRFS, 88.0% compared to 66.5% in the selective RT group (p = 0.096, Kaplan Meier; p = 0.028, Chi-squared). Administration of non-selective, pre-operative RT to all patients with pelvic ES elevates the LFRS to that of the good responder group (≥90% tumour necrosis and margins, p = 0.880). There was no difference in metastasis-free survival, 60.0% and 54.5% (p = 0.728) and overall survival (OS), 57.7% and 63.6% (p = 0.893). The majority of pre-operative RT patients had both good necrosis (≥90%) (p = 0.003) and widely excised tumours, 81.5% vs 59.1% (p = 0.080). Tumour volume ≥250 ml was associated with worse LRFS (p = 0.045) and post-operative complications (p = 0.017). There may be improved LRFS (p = 0.057) with pre-operative proton-beam RT compared to surgery and selective post-operative RT.

CONCLUSION

Pre-operative photon or proton-beam RT to all pelvic ES may improve LRFS compared to the selective delivery of post-operative RT. Radiotherapy delivered to all patients results in a greater percentage of highly necrotic tumours at surgical excision, enabling a greater proportion of patients with wide resection margins.

A Preliminary Study of FTIR Spectroscopy as a Potential Non-Invasive Screening Tool for Pediatric Precursor B Lymphoblastic Leukemia

Early detection of the most common pediatric neoplasm, B-cell precursor lymphoblastic leukemia (BCP-ALL), is challenging and requires invasive bone marrow biopsies. The purpose of this study was to establish new biomarkers for early screening to detect pediatric leukemia. In this small cohort study, Fourier transform infrared (FTIR) spectra were obtained from blood sera of 10 patients with BCP-ALL and were compared with the control samples from 10 children with some conditions other than neoplasm. Using various analytical approaches, including a new physical model, some significant differences were observable. The most important include: the different peak area ratio 2965/1645 cm⁻¹ (p = 0.002); the lower average percentage of both β-sheet and β-turn protein structures in the sera of BCP-ALL patients (p = 0.03); an AdaBoost-based predictive model for classifying healthy vs. BCP-ALL patients with 85% accuracy; and the phase shift of the first derivative in the spectral range 1050–1042 cm⁻¹ correlating with white blood cell (WBC) and blast cell count in BCP-ALL patients contrary to the samples obtained from healthy controls. Although verification in larger groups of patients will be necessary, these promising results suggest that FTIR spectroscopy may have future potential for the early screening of BCP-ALL.

Slow skeletal muscle troponin T, titin and myosin light chain 3 are candidate prognostic biomarkers for Ewing's sarcoma

Ewing's sarcoma (ES) is a common malignant bone tumor in children and adolescents. Although great efforts have been made to understand the pathogenesis and development of ES, the underlying molecular mechanism remains unclear. The present study aimed to identify new key genes as potential biomarkers for the diagnosis, targeted therapy or prognosis of ES. mRNA expression profile chip data sets GSE17674, GSE17679 and GSE45544 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened using the R software limma package, and functional and pathway enrichment analyses were performed using the enrichplot package and GSEA software. The NetworkAnalyst online tool, as well as Cytoscape and its plug-ins cytoHubba and NetworkAnalyzer, were used to construct a protein-protein interaction network (PPI) and conduct module analysis to screen key (hub) genes. LABSO COX regression and overall survival (OS) analysis of the Hub genes were performed. A total of 211 DEGs were obtained by integrating and analyzing the three data sets. The functions and pathways of the DEGs were mainly associated with the regulation of small-molecule metabolic processes, cofactor-binding, amino acid, proteasome and ribosome biosynthesis in eukaryotes, as well as the Rac1, cell cycle and P53 signaling pathways. A total of one important module and 20 hub genes were screened from the PPI network using the Maximum Correlation Criteria algorithm of cytoHubba. LASSO COX regression results revealed that titin (TTN), fast skeletal muscle troponin T, skeletal muscle actin α-actin, nebulin, troponin C type 2 (fast), myosin light-chain 3 (MYL3), slow skeletal muscle troponin T (TNNT1), myosin-binding protein C1 slow-type, tropomyosin 3 and myosin heavy-chain 7 were associated with prognosis in patients with ES. The Kaplan-Meier curves demonstrated that high mRNA expression levels of TNNT1 (P<0.001), TTN (P=0.049), titin-cap (P=0.04), tropomodulin 1 (P=0.011), troponin I2 fast skeletal type (P=0.021) and MYL3 (P=0.017) were associated with poor OS in patients with ES. In conclusion, the DEGs identified in the present study may be key genes in the pathogenesis of ES, three of which, namely TNNT1, TTN and MYL3, may be potential prognostic biomarkers for ES.

Identification of key genes and pathways in Ewing's sarcoma patients associated with metastasis and poor prognosis

Background: Ewing sarcoma (ES) is the second commonest primary malignant bone neoplasm. Metastatic status at diagnosis strongly predicted poor prognosis of Ewing sarcoma patients. Yet little was known about the underlying mechanism of ES metastasis.

Purpose:This study intended to identify the relationship between key genes/pathways and metastasis/poor prognosis in Ewing's sarcoma patients by using bioinformatic method.

Methods: In this study, multi-center sequencing data were obtained from the GEO database, including gene and miRNA expression profile and prognosis information of ES patients. Differentially expressed genes (DEGs) were identified between primary and metastasis ES samples by the GEO2R online tool. Gene ontology (Go) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses of DEGs were performed. And PPI network analyses were conducted. The ES patient’s prognostic information was employed for survival analysis, and the potential relationship between miRNAs and key genes was analyzed.

Results: The results showed that a total of 298 and 428 DEGs were screened out in metastasis samples based on GSE17618 and GSE12102 dataset compared to primary samples respectively. The most significantly enriched KEGG pathway was the mismatch repair (MMR) pathway. MSH2, MSH6, RPA2, and RFC2 that belong to the MMR pathway were identified as key genes. Moreover, the expression of key genes was increased in metastasis samples compared with primary ones and was associated with poor event-free and overall survival of ES patients. The negative correlation of the expression level of the key genes with patients prognosis also supported by TCGA sarcoma database. Furthermore, knockdown of EWSR/FLI1 fusion in ES cell line A673 down-regulates the expression of the 4 key genes was revealed by GDS4962.

Conclusion: In conclusion, the present study indicated that the key genes promote our understanding of the molecular mechanisms underlying the development of ES metastasis, and might be used as molecular targets and diagnostic biomarkers for the treatment of ES.

Predicting Ewing Sarcoma Treatment Outcome Using Infrared Spectroscopy and Machine Learning

Background: Improved outcome prediction is vital for the delivery of risk-adjusted, appropriate and effective care to paediatric patients with Ewing sarcoma—the second most common paediatric malignant bone tumour. Fourier transform infrared (FTIR) spectroscopy of tissues allows the bulk biochemical content of a biological sample to be probed and makes possible the study and diagnosis of disease. Methods: In this retrospective study, FTIR spectra of sections of biopsy-obtained bone tissue were recorded. Twenty-seven patients (between 5 and 20 years of age) with newly diagnosed Ewing sarcoma of bone were included in this study. The prognostic value of FTIR spectra obtained from Ewing sarcoma (ES) tumours before and after neoadjuvant chemotherapy were analysed in combination with various data-reduction and machine learning approaches. Results: Random forest and linear discriminant analysis supervised learning models were able to correctly predict patient mortality in 92% of cases using leave-one-out cross-validation. The best performing model for predicting patient relapse was a linear Support Vector Machine trained on the observed spectral changes as a result of chemotherapy treatment, which achieved 92% accuracy. Conclusion: FTIR spectra of tumour biopsy samples may predict treatment outcome in paediatric Ewing sarcoma patients with greater than 92% accuracy.