Abstract 368P
Background
Oral Submucous Fibrosis (OSMF) is a chronic debilitating disease more frequently found in the South East Asian population. This disease poses a public health priority, as it is grouped under oral potentially malignant disorders, with malignant transformation rates of around 7 to 13%. Hence, early identification of high-risk OSMF patients is of the utmost importance to prevent malignant transformation. mRNA expression profiling is a promising method for identifying differentially expressed genes for disease prognosis in OSMF. The genetic profiling was performed using Tumor Signaling (TS) 360 Panel (Nanostring platform) to profile 780 humans across 40+ annotated pathways.
Methods
The RNA was initially isolated from patient tissue samples in different clinical stages of OSMF (n=8), OSMF transformed into oral squamous cell carcinoma (OSCC) (n=5) and healthy controls (HC) (n=5). The analysis of gene expression was conducted on the nCounter® TS 360™ Panel and NanoString platform. The raw transcriptome data were subjected to housekeeping-gene normalization using the geNorm algorithm in nCounter Advanced Analysis ver. 2.0.115. Normalized data were log2-transformed for analysis. A quality check of raw data was conducted using nSolver Analysis Software ver. 4.0 and NanoStringQCpro ver. 1.14.0.
Results
Among the 780 genes, AR, RPTOR and PRDX6 showed the highest differential expression between OSMF and OSCC (2.48, 1.1 and 0.76 fold change, respectively; p < 0.05). While, MLANA, WEE1 and MYB showed the highest differential expression between HC and OSCC (5.16, 2.61 and 2.11 fold change, respectively; p < 0.05). The upregulated genes were further validated using real time PCR which showed significant upregulation in OSMF and OSCC.
Conclusions
The present study is the first of its kind in India to the best of our knowledge, assessing the gene expression using the Nanostring platform in different clinical stages of OSMF. with validation in a large series of cases. The currenty study has evolved a panel of biomarkers, namely PRDX6, MLANA and AR to be potentially useful in identifying high-risk OSMF patients with an increased risk of OSCC development.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
C.V. Divyambika; R. Vijayalakshmi.
Funding
Indian Council of Medical Research (ICMR): 5/4/2-4/Oral Health/2021/NCD-II.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
5P - Clinicopathologic features and genomic profiling of occult breast cancer
Presenter: Liansha Tang
Session: Poster Display
Resources:
Abstract
6P - Tumor cell-released autophagosomes (TRAPs) promote lung metastasis through inducing PD-L1 high expression of pulmonary vascular endothelial cells (PVECs) in breast cancer
Presenter: Xuru Wang
Session: Poster Display
Resources:
Abstract
7P - Tumor cell-released autophagosomes (TRAPs) promote breast cancer lung metastasis by modulating neutrophil extracellular traps formation
Presenter: Xiaohe Zhou
Session: Poster Display
Resources:
Abstract
9P - Clinicopathological features and prognosis of mucinous breast cancer: A retrospective analysis of 358 patients in Vietnam
Presenter: Hoai Hoang
Session: Poster Display
Resources:
Abstract
10P - Comparison of 28-gene and 70-gene panel in risk-prediction of Chinese women with early-stage HR-positive and HER2-negative breast cancer
Presenter: Lei Lei
Session: Poster Display
Resources:
Abstract
11P - Multimodal analysis of methylation and fragmentomic profiles in plasma cell-free DNA for differentiation of benign and malignant breast tumors
Presenter: Hanh Nguyen
Session: Poster Display
Resources:
Abstract
12P - Plasma cell-free mRNA profiles enable early detection of breast cancer
Presenter: Chi Nguyen
Session: Poster Display
Resources:
Abstract
13P - Relationship of distress and quality of life with gut microbiome composition in newly diagnosed breast cancer patients: A prospective, observational study
Presenter: Chi-Chan Lee
Session: Poster Display
Resources:
Abstract
14P - Classification of molecular subtypes of breast cancer in whole-slide histopathological images using a novel deep learning algorithm
Presenter: Hyung Suk Kim
Session: Poster Display
Resources:
Abstract
15P - The regulation of pregnenolone in breast cancer
Presenter: Hyeon-Gu Kang
Session: Poster Display
Resources:
Abstract