Role of NGS in Oral Squamous Cell Carcinoma

Abstract

A recent advance next generation sequencing (NGS) technology has enabled the identification of potential disease-based biomarkers in saliva or epithelial cells. There has been no effective oral squamous cell carcinoma (OSCC) biomarker or well-organised molecular detection method until now, which make early diagnosis difficult, if not impossible. This chapter summarises advances in cancer research using NGS and proposes biomarkers for screening and diagnosis of OSCC using the NGS technique. As part of our review, we covered four categories: OSCC and salivary biomarkers, Uses of NGS and definitions, present biomarkers in NGS, and Candidate salivary biomarkers for OSCC using NGS.

1. Introduction

Oral cancer belongs to a larger subgroup of tumours termed head and neck cancer, comprising lip, mobile tongue, buccal, labial, floor of the mouth, gingiva, hard palate and soft palate [1]. Buccal malignancies most commonly arise on the buccal posterior-lateral border and ventral surfaces [2]. Squamous cell carcinoma of the oral epithelium accounts for approximately 90% of all oral malignancies. The other 10% are malignant intraoral salivary gland tumours, melanomas, soft tissue and jaw bone sarcomas, non-lymphomas, Hodgkin’s and the extremely rare malignant odontogenic tumours, as well as metastatic tumours of primary cancers situated elsewhere in the body [3].

Oral cancer is the most frequent in India, accounting for 50–70% of global cancer mortality and having the highest prevalence within Asian countries [4]. With an estimated one percent of the population possessing oral premalignant lesions, India is fittingly dubbed “the mouth cancer capital of the world.” Every year, nearly one million persons in India are diagnosed with oral cancer, and half of them die in agony within a year of diagnosis due to late presentation [5]. A small percentage of newly diagnosed mouth cancer patients survive for an extended period of time.

Squamous cell carcinoma accounts for 90% of malignant tumours in the oral mucosa. The prevalence of cancer varies greatly around the global. The United Kingdom and the United States, the rate of all forms of tumours is 4%, however it is nearly 40% in South-East Asian countries [6]. Squamous cell carcinoma could manifest in a variety of clinical presentations. The aim is to recognise it primary because this is a crucial element prompting the clinical prognosis of the patient, and therefore suspicion and vigilance are seen as crucial aspects in cancer diagnosis [7]. Early lesions rarely cause symptoms, however they might manifest as a minor exophytic growth with little erythema or ulceration, a small ulcer, or erythroplakia, a white patch [8]. In clinical terms, characteristics such as induration, ulceration, and tissue fixation to structures could raise the possibility of an primary cancer. A late stage lesion typically manifests as a wide-based protrusion with a nodular, rough, haemorrhagic, warty, or necrotic surface 20, but it can similarly manifest as a destructive crater-like ulcer with rolling, elevated evented borders [6]. Histology of oral squamous cell carcinoma reveals a variety of forms (Figure 1). Despite this, all types exhibit tissue damage and invasion. Squamous cell carcinoma is graded according to its histology into well, moderately, and moderately differentiated groups [8]. Plasma cells and lymphocytic cells are frequently found infiltrating the stroma and aiding the assaulting epithelium. Several tumours occupy with a wide anterior, whilst others are composed of tiny islands or solitary aggressive cells. Cohesive cancer has a broad aggressive anterior, whereas non-cohesive carcinoma has tiny islands or single cells that infiltrate. It have been discovered that non-cohesive assault has a poor prognosis. Vascular, neuronal, and bone invasion all can occur [9]. The metastatic range of cancer in regional lymph nodes is classified into two types: intracapsular spread (when the spread is limited to the node’s capsule) and extracapsular spread (when the cancer spreads to neighbouring tissue near to the capsule). When the cancer develops extracapsular dissemination, the prognosis is poor [10].

Figure 1.

A new cancer classification system could also have an impact on drug development and patient recruitment for clinical trials modified.

2. Next-generation sequencing (NGS) and cancer

The concept of ‘next-generation sequencing’ (NGS) denotes to a range of knowledge that are viewed as the predecessors to the traditional Sanger DNA sequencing technique. Their advancement has enabled the generation of massive amounts of genomic data (almost one billion lines) at a low cost. This enables a wide range of applications, as well as whole-exome sequencing, whole-genome sequencing, including targeted gene sequencing [11]. Exome sequencing (the parts of DNA a certain encode proteins) is especially important from a scientific standpoint because it is believed that deviates in these areas account for around 85 percent of disease-causing mutations [12]. NGS has been used in numerous researchs to analyse the tumour exomes of samples from patients with head and neck SCC (HNSCC) [13]. Stransky et al. discovered a frequency of 130 coding mutations for each tumour and detected alterations in 39 recognised genes across the population studied [14], whereas Agrawal et al. discovered somatic mutations in genes previously linked to OSCC development. Both investigations also found substantial mutations in the signalling gene NOTCH1, that had not previously been linked to HNSC [15].

NGS can be used to analyse the RNA transcriptome in addition to DNA sequencing (RNA-Seq). The transcriptome is the complete set of transcribed RNA in a sample, and sequencing consents for both assessment of relative gene expression and identification of nucleotide polymorphisms [16]. Gene expression microarrays, which rely on the hybridisation and fluorescence of pre-designed probes, have been used in RNA expression studies till recently. Gene expression microarrays, that have well-developed molecular technology and a substantial body of research [17], have major advantages over RNA-Seq. For starters, RNA-Seq does not require a thorough understanding of the genes’ targets, eliminating this need specialised probes. There is no limit to the number of genes that can be analysed simultaneously, unlike gene expression microarrays. Chromosomal translocations, fusion genes, differential splice variants, Single nucleotide polymorphisms, and viral transcripts are among the other transcriptome modifications that can be detected with RNA-Seq [18]. Tuch et al. discovered and proved with real-time quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) that RNA-Seq was superior to gene expression microarray for identifying differential expression in transcripts with low expression levels in their investigation [19]. RNA-Seq has been used in a number of studies to investigate gene expression and transcriptome variation in various forms of HNSCC, including oral, oesophageal, and oropharyngeal. Quantification of differential gene expression, gene ontology analysis to identify over-represented, under-represented, and dysregulated biochemical mechanisms, classification of chromosomal translocations and subsequent fusion genes, attribution of differentially expressed novel mRNA splice variants, and investigation for HPV and other viral mRNA transcripts are all demonstrated applications of RNA-Seq in these studies. The Life TechnologiesTM (Carlsbad, USA) Ion ProtonTM/Ion Personal Genome MachineTM (PGM) system is an NGS platform that uses proton release associated with Gene polymerisation to identify nucleotide sequence (ion semiconductor sequencing). Clonally amplified DNA fragments are challenged with free nucleotides in micro-machined wells equipped with pH sensors. The incorporation of nucleotides results in the release of a proton, resulting in a detectable pH shift. This process is continued with each nucleotide cycle, resulting in the formation of a DNA sequence [20]. Ion semiconductor sequencing is quicker and less costly than other NGS technologies, however it has a shorter read length and a greater error rate. It has, however, been proved to be accurate in detecting nucleotide polymorphism.

Recent genomics studies are focusing on the molecular alterations that underpin the development of HNSCC and OSCC from both the epithelial and immunological compartments. These it has been shown that HNSCC and OSCC are extremely diverse, and despite the paucity of identifiable oncogenic mutations, targetable signalling pathways have been found. Furthermore, developing data from these research can be used to subclassify patients, for example, to those who may be more receptive to immunotherapies. Despite the fact that the majority of these have generated promising therapeutic effects, significant work remains to be done to expand the pharmacological arsenal available to OSCC patients. Some factors to consider when pursuing this would be demonstrating that the molecular mechanisms recognised in all of these genomics research studies in primary lesions are also pertinent in the metastatic and recurrent settings, as drug development is generally decided to focus on tackling recurrent and metastasis disease. Second, parallel research of relevant biomarkers that could detect potential patient subsets receptive to present treatments should be prioritised. In addition to the currently available data on OSCC, the capacity to use genomics to predict drug responses, as well as the introduction of precise gene editing technologies, presents promising potential in the search of quality treatment modalities for OSCC patients [21].

3. Cancer genomics research potentials

Although large-scale research investigations have found a huge number of genetic changes that support the development and evolution of several types of cancer, some tumour types remain poorly understood. Many tumours could benefit from new technology and knowledge gathered from prior genomic research to characterise the full collection of genetic alterations and many other DNA and RNA changes. Researchers can find genomic abnormalities that may promote cancer by comparing genomic information from malignancies and normal tissue from same patient [22].

Another possibility is to broaden the existing use of genomic technologies to study the molecular basis of clinical characteristics. For example, this method could aid researchers in identifying genetic variations that distinguish aggressive malignancies from indolent cancers. Similar methodologies could be utilised to investigate the molecular mechanism of therapeutic response as well as treatment resistance mechanisms.

Patients’ medical history and clinical data will increasingly be combined with the amount of data generated by cancer genomic studies. These combined findings could be utilised to generate more personalised cancer diagnosis and treatment techniques, as well as better methods for forecasting cancer risk, prognosis, and treatment response (Figure 2) [23].

Figure 2.

In the previous 50 years, there have been significant developments in sequencing technology, seminal milestones, and large-cohort investigations modified.

4. Challenges in cancer genomics research

Comprehensive analyses of cancer genomes have revealed a wide range of genetic aberrations within tumours of the same type. Furthermore, only a small minority of these cancers are affected by recurrent genetic changes. Identifying which genetic variations cause cancer and uncovering unusual genetic mutations that cause cancer are thus difficult tasks for the research.

Another problem is obtaining high-quality biological samples for genetic investigations, which is especially difficult for tumour forms that are infrequent or rare, or those that are not treated predominantly with surgery.

Requirements involve establishing cell lines and animal studies that reflect the spectrum of human cancer. Many recurrent genetic lesions in human cancer have no models, and models for rare different types of cancer may be nonexistent or under represented.

Additional hurdles for the profession include managing and analysing the massive amounts of data generated by genetic investigations. This field of study necessitates a strong bioinformatics infrastructure and progressively relies on data and skills from multidisciplinary teams [24].