Squamous Cell Carcinoma (SCC) occurs in many different organs including the skin, lung, vagina and cervix. More than 90% of the cancers of the head and neck begin in squamous cells with head and neck squamous cell carcinoma (HNSCC) being the sixth most common malignancy worldwide. With currently available treatments, early diagnosis leads to a five-year survival rate close to 90%, however when diagnosis is delayed, the five-year survival rates drop to around 50%.
Approximately 70% of oral cancers such as HNSCC, arise from non-healing mouth ulcers or suspicious growths known as oral premalignant disorders (OPMDs). The majority of OPMDs are benign, however a small percentage - 10 to 12%, develop into malignant conditions. Therefore, the identification of high-risk OPMDs before they develop into malignant conditions will lead to earlier treatment interventions, which in turn will significantly improve five-year survival rates for oral cancers.
At present, patients with suspicious oral lesions are either placed on ‘watchful waiting’ surveillance or are referred for a highly invasive and time-consuming surgical scalpel biopsy procedure. The large biopsy (5 to 20 mm) is then analyzed under the microscope by an oral pathologist in order to identify minute cellular abnormalities. Diagnosis is subjective and relies heavily on the experience of the pathologist. Furthermore, pathology is unable to differentiate between low and high-risk oral premalignant lesions, as early oncogenic changes do not usually produce a histopathological phenotype.
There is therefore a need to develop an affordable, reliable and automatable diagnostic test capable of identifying high-risk OPMDs.
A novel, affordable, high-throughput, qPCR-based diagnostic test called quantitative Malignancy Index Diagnostic System v2 (qMIDSv2) has been developed which can accurately differentiate between low and high-risk OPMDs. The test comprises a panel of 16 biomarker genes – 14 disease-associated genes and 2 reference genes, as well as an algorithm that produces a numerical digital malignancy index ranging from 0 to 20. A score of 0-2 indicates that there is no disease, 2-4 indicates low risk, 4-8 indicates at risk and a score greater than 8 indicates high risk.
The biomarker panel includes the universal cancer gene FOXM1, which is a key gene in 39 different cancer types. The first iteration of the test (qMIDSv1) which was published and patented previously, has been tested on head and neck cancers, vulva and skin cancers with promising results. The qMIDSv2 diagnostic test is an improvement of qMIDSv1; Therefore, there is clear potential for qMIDSv2 to be developed into a universal cancer test.
The qMIDSv1 diagnostic test developed previously was first validated using UK and Norwegian tissue samples, and subsequently validated in China using ethnic Han Chinese specimens. The validation process led to the collection of over 24,000 data points, which allowed further refinement of the biomarker panel. Development of a second iteration of the test called qMIDSv2 followed.
In qMIDSv2, eight less influential biomarkers were replaced with new genes involved in stroma/matrix and immune modulation. A validation study using clinical specimens was then performed to compare the diagnostic efficiency of qMIDSV1 (n = 102) and qMIDSv2 (n = 282). Biopsies from head and neck tissue from patient cohorts in the UK, Norway, India and China, were analysed and scored using both qMIDS tests. The head-to-head comparison demonstrated that the qMIDSv2 biomarker panel has increased sensitivity and accuracy for cancer detection over qMIDSv1. Efficiency of the qMIDSv2 test was as follows: Sensitivity: 88%, Specificity: 96%, Accuracy: 92%, False positive rate: 4.5%, Area under the curve: 0.945.
This technology is a novel qPCR-based diagnostic test comprising 14 target genes for detecting oral cancer risk. It is applicable across multiple types of cancer due to inclusion of universal cancer biomarker.
1. Novel qPCR-based diagnostic test comprising 14 target genes for detecting oral cancer risk.
2. Applicable across multiple types of cancer due to inclusion of universal cancer biomarker.
3. Prediction of patient prognosis with quantitative readout.
4. Minimally invasive test, which requires only 1 mm3 of biopsy material.
5. Low cost and rapid, with potential to automate.