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Multi-photon Imaging of Tumor Cell Invasion in an Orthotopic Mouse Model of Oral Squamous Cell Carcinoma
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Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics.

Nenghao Jin1,2, Bo Qiao1,2, Min Zhao3,4

  • 1Medical School of Chinese PLA, Beijing, China.

Cancer Medicine
|August 28, 2023
PubMed
Summary

Computed tomography (CT) radiomics and gene expression reveal insights into oral squamous cell carcinoma (OSCC) metastasis. Specific CT features correlate with gene expression, aiding in understanding cervical lymph node metastasis (LNM) in OSCC patients.

Keywords:
computed tomography imaging (CT imaging)3genomics4lymph node metastasis (LNM)2oral squamous cell carcinoma (OSCC)1ribonucleic acid sequencing (RNA-seq)5

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Area of Science:

  • Oncology
  • Radiology
  • Genomics

Background:

  • Oral squamous cell carcinoma (OSCC) poses a significant challenge due to cervical lymph node metastasis (LNM).
  • Understanding the molecular drivers of LNM is crucial for improving patient outcomes.
  • Computed tomography (CT) radiomics offers a non-invasive method to assess tumor characteristics.

Purpose of the Study:

  • To explore the relationship between CT-derived radiomic features and key genes associated with LNM in OSCC.
  • To identify potential imaging biomarkers for predicting LNM risk.
  • To correlate radiomic signatures with gene expression profiles in OSCC.

Main Methods:

  • Radiomic features were extracted from enhanced CT images of 140 OSCC patients.
  • RNA sequencing was performed on pathological samples from 20 patients to identify differentially expressed genes.
  • Weighted gene co-expression network analysis and pathway enrichment analysis (KEGG, GO) were employed.
  • Pearson correlation was used to link radiomic features with key genes and LNM status.

Main Results:

  • Seven radiomic features significantly correlated with cervical LNM in OSCC (p < 0.01).
  • RNA sequencing identified 3527 differentially expressed RNAs.
  • The radiomic feature 'original_glrlm_RunVariance' showed a significant positive correlation with most long noncoding RNAs.

Conclusions:

  • Cervical LNM in OSCC is associated with the salivary hair bump signaling pathway and specific biological processes.
  • The radiomic feature 'original_glrlm_RunVariance' is linked to LNM and the expression of numerous long noncoding RNAs.