Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology

Abstract

Background: This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation.Methods: Patients with oral epithelial dysplasia at one hospital were selected as the 'training set' (n=56) whilst those at another hospital were selected for the 'test set' (n=66). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies and analysed using the NanoString nCounter platform. A targeted panel of 42 genes selected on their association with oral carcinogenesis was used to develop a prognostic gene signature. Following data normalisation, uni-and multivariable analysis, as well as prognostic modelling, were employed to develop and validate the gene signature. Results: A prognostic classifier composed of 11 genes was developed using the training set. The multivariable prognostic model was used to predict patient risk scores in the test set. The prognostic gene signature was an independent predictor of malignant transformation when assessed in the test set, with the high-risk group showing worse prognosis [Hazard ratio = 12.65, p = 0.0003]. Conclusions:This study demonstrates proof of principle that RNA extracted from FFPE diagnostic biopsies of OPMD, when analysed on the NanoString nCounter platform, can be used to generate a molecular classifier that stratifies the risk of malignant transformation with promising clinical utility.

Genetic Changes Driving Immunosuppressive Microenvironments in Oral Premalignancy

“…Sathasivam et al. used a 42 targeted gene Nanostring panel to identify an 11 gene expression signature associated with malignant progression ( 65 ). Importantly, this signature employed genes commonly altered during HNSCC carcinogenesis including TP53, NOTCH1 and CDKN2A which increases the likelihood of this signature being robust across multiple cohorts.…”

“…However, many of these genes were not canonical drivers of carcinogenesis suggesting that this gene signature reflected changes of genes expression that did not likely cause malignant transformation. Sathasivam et al used a 42 targeted gene Nanostring panel to identify an 11 gene expression signature associated with malignant progression (65). Importantly, this signature employed genes commonly altered during HNSCC carcinogenesis including TP53, NOTCH1 and CDKN2A which increases the likelihood of this signature being robust across multiple cohorts.…”

Microenvironment in Oral Potentially Malignant Disorders: Multi-Dimensional Characteristics and Mechanisms of Carcinogenesis

“…Meanwhile, the nervous system plays a regulatory role in these microenvironments [ 7 ]. Furthermore, there are extensive and profound interactions among microenvironments, which amplify the carcinogenic effects [ 12 , 13 ]. Therefore, it is significant to elucidate the dynamic changes in microenvironments and look for targets for cancer chemoprevention.…”

Molecular Signatures of Tumour and Its Microenvironment for Precise Quantitative Diagnosis of Oral Squamous Cell Carcinoma: An International Multi-Cohort Diagnostic Validation Study

“…Although OPMDs may exhibit different molecular signature to that found in tumour, it is known that high-risk OPMDs exhibit chromosomal and genomic instability alterations indicative of malignant transformation [25]. As chromosomal, epigenomic and genomic perturbations would likely lead to altered transcriptome profile, utilising a panel of gene expression signature as surrogate disease markers as in qMIDS [24] or others [26][27][28][29] has shown to be effective for predicting risk of early malignant transformation in OPMDs.…”