Dataset Information

An optical photothermal infrared investigation of lymph nodal metastases of oral squamous cell carcinoma.

ABSTRACT: In this study, optical photothermal infrared (O-PTIR) spectroscopy combined with machine learning algorithms were used to evaluate 46 tissue cores of surgically resected cervical lymph nodes, some of which harboured oral squamous cell carcinoma nodal metastasis. The ratios obtained between O-PTIR chemical images at 1252 cm^-1 and 1285 cm^-1 were able to reveal morphological details from tissue samples that are comparable to the information achieved by a pathologist's interpretation of optical microscopy of haematoxylin and eosin (H&E) stained samples. Additionally, when used as input data for a hybrid convolutional neural network (CNN) and random forest (RF) analyses, these yielded sensitivities, specificities and precision of 98.6 ± 0.3%, 92 ± 4% and 94 ± 5%, respectively, and an area under receiver operator characteristic (AUC) of 94 ± 2%. Our findings show the potential of O-PTIR technology as a tool to study cancer on tissue samples.

SUBMITTER: Al Jedani S

PROVIDER: S-EPMC11239877 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An optical photothermal infrared investigation of lymph nodal metastases of oral squamous cell carcinoma.

Al Jedani Safaa S Lima Cassio C Smith Caroline I CI Gunning Philip J PJ Shaw Richard J RJ Barrett Steve D SD Triantafyllou Asterios A Risk Janet M JM Goodacre Royston R Weightman Peter P

Scientific reports 20240711 1

In this study, optical photothermal infrared (O-PTIR) spectroscopy combined with machine learning algorithms were used to evaluate 46 tissue cores of surgically resected cervical lymph nodes, some of which harboured oral squamous cell carcinoma nodal metastasis. The ratios obtained between O-PTIR chemical images at 1252 cm<sup>-1</sup> and 1285 cm<sup>-1</sup> were able to reveal morphological details from tissue samples that are comparable to the information achieved by a pathologist's interpre ...[more]

PMID: 38992088

Similar Datasets

Project description:BackgroundEarly-stage oral squamous cell carcinoma (OSCC) patients have a one-in-four risk of regional metastasis (LN+), which is also the most significant prognostic factor for survival. As there are no validated biomarkers for predicting LN+ in early-stage OSCC, elective neck dissection often leads to over-treatment and under-treatment. We present a machine-learning-based model using the quantitative nuclear phenotype of cancer cells from the primary tumor to predict the risk of nodal disease.Methods and findingsTumor specimens were obtained from 35 patients diagnosed with primary OSCC and received surgery with curative intent. Of the 35 patients, 29 had well (G1) or moderately (G2) differentiated tumors, and six had poorly differentiated tumors. From each, two consecutive sections were stained for hematoxylin & eosin and Feulgen-thionin staining. The slides were scanned, and images were processed to curate nuclear morphometric features for each nucleus, measuring nuclear morphology, DNA amount, and chromatin texture/organization. The nuclei (n = 384,041) from 15 G1 and 14 G2 tumors were randomly split into 80% training and 20% test set to build the predictive model by using Random Forest (RF) analysis which give each tumor cell a score, NRS. The area under ROC curve (AUC) was 99.6% and 90.7% for the training and test sets, respectively. At the cutoff score of 0.5 as the median NRS of each region of interest (n = 481), the AUC was 95.1%. We then developed a patient-level model based on the percentage of cells with an NRS ≥ 0.5. The prediction performance showed AUC of 97.7% among the 80% (n = 23 patient) training set and with the cutoff of 61% positive cells achieved 100% sensitivity and 91.7% specificity. When applying the 61% cutoff to the 20% test set patients, the model achieved 100% accuracy.ConclusionsOur findings may have a clinical impact with an easy, accurate, and objective biomarker from routine pathology tissue, providing an unprecedented opportunity to improve neck management decisions in early-stage OSCC patients.

Project description:Background Oral squamous cell carcinoma (OSCC), an HPV-negative head and neck cancer, frequently metastasizes to the regional lymph nodes but only occasionally beyond. Initial phases of metastasis are associated with an epithelial–mesenchymal transition (EMT), while the consolidation phase is associated with mesenchymal–epithelial transition (MET). This dynamic is referred to as epithelial–mesenchymal plasticity (EMP). While it is known that EMP is essential for cancer cell invasion and metastatic spread, less is known about the heterogeneity of EMP states and even less about the heterogeneity between primary and metastatic lesions. Methods To assess both the heterogeneity of EMP states in OSCC cells and their effects on stromal cells, we performed single-cell RNA sequencing (scRNAseq) of 5 primary tumors, 9 matching metastatic and 5 tumor-free lymph nodes and re-analyzed publicly available scRNAseq data of 9 additional primary tumors. For examining the cell type composition, we performed bulk transcriptome sequencing. Protein expression of selected genes were confirmed by immunohistochemistry. Results From the 23 OSCC lesions, the single cell transcriptomes of a total of 7263 carcinoma cells were available for in-depth analyses. We initially focused on one lesion to avoid confounding inter-patient heterogeneity and identified OSCC cells expressing genes characteristic of different epithelial and partial EMT stages. RNA velocity and the increase in inferred copy number variations indicated a progressive trajectory towards epithelial differentiation in this metastatic lesion, i.e., cells likely underwent MET. Extension to all samples revealed a less stringent but essentially similar pattern. Interestingly, MET cells show increased activity of the EMT-activator ZEB1. Immunohistochemistry confirmed that ZEB1 was co-expressed with the epithelial marker cornifin B in individual tumor cells. The lack of E-cadherin mRNA expression suggests this is a partial MET. Within the tumor microenvironment we found immunomodulating fibroblasts that were maintained in primary and metastatic OSCC. Conclusions This study reveals that EMP enables different partial EMT and epithelial phenotypes of OSCC cells, which are endowed with capabilities essential for the different stages of the metastatic process, including maintenance of cellular integrity. During MET, ZEB1 appears to be functionally active, indicating a more complex role of ZEB1 than mere induction of EMT.

Dataset Information

An optical photothermal infrared investigation of lymph nodal metastases of oral squamous cell carcinoma.

Publications

An optical photothermal infrared investigation of lymph nodal metastases of oral squamous cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets