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Year : 2021  |  Volume : 1  |  Issue : 2  |  Page : 51-52

Toward personalized treatment for head and neck cancers: The role of SNPs

Postgraduate Institute of Medical Education and Research, Chandigarh, India

Date of Submission22-Jul-2022
Date of Acceptance23-Jul-2022
Date of Web Publication24-Aug-2022

Correspondence Address:
Sushmita Ghoshal
Postgraduate Institute of Medical Education and Research, Chandigarh
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/bjoc.bjoc_8_22

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How to cite this article:
Ghoshal S, Pal A. Toward personalized treatment for head and neck cancers: The role of SNPs. Bengal J Cancer 2021;1:51-2

How to cite this URL:
Ghoshal S, Pal A. Toward personalized treatment for head and neck cancers: The role of SNPs. Bengal J Cancer [serial online] 2021 [cited 2023 Mar 25];1:51-2. Available from: http://www.bengaljcancer.org/text.asp?2021/1/2/51/354416

“A,” “C,” “G,” and “T” are four alphabets of the English language, but their immensely powerful combinations make the living world amazingly diverse. These four bases found in the DNA of any living organism make them fascinating in terms of unity in diversity. In contrast, the deviation from their correct code in the DNA, commonly known as a mutation, literally leads to adverse clinical conditions such as genetic diseases as well as cancers. The genetic basis of cancers is often used for the diagnosis as well as prognosis of various cancers. In the field of modern medicine, these genetic bases often play an important role as molecular markers.

The latest 8th edition of the AJCC staging system proposed to incorporate molecular biomarkers for more accurate risk stratification would eventually lead to personalized therapy in cancer patients. With this vision, the 8th edition was expanded to include the Personalized Medicine Core (PMC). The charter of PMC is to provide a comprehensive, web-based model to predict the prognosis of individual patients. Head and neck cancers are one of the cancers to be evaluated in the initial phase of this task.[1]

The response of cancer to a given treatment depends on many tumors as well as various patient-related factors. While the extent of the disease is a major prognostic factor, not all patients in the same stage group have identical outcomes. This heterogeneity of outcome can be due to a combination of various demographic or genetic factors. It is well known now that the presence of the HPV virus in oropharyngeal carcinoma or the depth of invasion in oral carcinoma significantly alters treatment outcomes. These factors are incorporated in the latest staging system. However, not all such hosts or tumor-related factors can independently predict outcome as yet. In addition, the tumor microenvironment, the host immune system, and the tumor’s ability to avoid detection play a significant role, and these factors are dynamic with temporal variation. The current TNM classification has stage grouping based on a bin model, which has limitations in integrating so many newer variables. In its attempt to individualize prognosis calculation, the PMC proposes to devise a comprehensive web-based prognostic model for major cancer sites. Several biological and molecular biomarkers have been identified, and their predictive and prognostic values are being validated in order to arrive at a reliable risk model.[2] These biomarkers can help in diagnosis, determining prognosis, or deciding the treatment option best suited for the individual.

Single nucleotide polymorphisms (SNPs) are one of the most common genomic variants in which a single base is altered in the exonic coding or non-coding intronic region of a gene. As a result, gene expression and functioning can be affected in a given individual. SNPs in the genes, whose expression change may lead to oncogenesis, can be utilized as biomarkers for cancer diagnosis and prognosis, leading to identifying the individuals at a higher risk of developing cancers. Similarly, individuals with a higher chance of progression from pre-malignant conditions to invasive malignancies can also be identified. The persons at higher risk would be treated and monitored differently when compared with those at lower risk.

Some SNPs are associated with DNA repair pathways. In irradiated normal cells, SNPs may compromise the process of repair of sublethal damage. This leads to excessive acute and late radiation-induced toxicities and perhaps can be why some patients tolerate the radiation doses poorly when compared with others. As a result, the analysis of the SNPs prior to therapy will identify potential individuals susceptible to increased radiation toxicity. This strategy will not only identify the potential patients prone to higher radiotoxicity but also advance planning for personalized therapy for individuals. Similarly, a genome-wide screening of predictive SNPs, instead of the candidate SNP approach by the SNP array, is proposed to act as a predictive marker for oral mucositis patients treated by radiotherapy.[3]

Most cancer hospitals in our country have a very high volume of head and neck cancer patients. Not all of them have access to highly conformal radiation like intensity modulated radiotherapy (IMRT)/image guided radiotherapy (IGRT). When resources are limited, proper triaging of patients is essential for optimal use of facilities. In this context, prior assessment of genetic basis of toxicity will definitely add value to the strategy for decision-making.

In head and neck cancers, in which radiotherapy acts as one of the mainstays of treatment, radio resistance often plays an important role in the overall outcome of the treatment. Identification and stratification of treatment strategy on the basis of genetic signature like associated SNPs could be one of the important steps toward personalized therapy.[4],[5]

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Kattan MW, Hess KR, Amin MB, Lu Y, Moons KG, Gershenwald JE, et al; Members of the AJCC Precision Medicine Core. American Joint Committee on cancer acceptance criteria for inclusion of risk models for individualized prognosis in the practice of precision medicine. CA Cancer J Clin 2016;66:370-4.  Back to cited text no. 1
Patil DJ, Nagaraju R Personalized precision medicine—A novel approach for oral cancer management. In: Sridharan G, editor. Oral Cancer—Current Concepts and Future Perspectives [Internet]. London: IntechOpen; 2021 [cited July 18, 2022]. Available from: https://www.intechopen.com/chapters/78142. doi: 10.5772/intechopen.99558  Back to cited text no. 2
Le Z, Niu X, Chen Y, Ou X, Zhao G, Liu Q, et al. Predictive single nucleotide polymorphism markers for acute oral mucositis in patients with nasopharyngeal carcinoma treated with radiotherapy. Oncotarget 2017;8:63026-37.  Back to cited text no. 3
Drobin K, Marczyk M, Halle M, Danielsson D, Papiez A, Sangsuwan T, et al. Molecular profiling for predictors of radiosensitivity in patients with breast or head-and-neck cancer. Cancers 2020;12:753. https://doi.org/10.3390/cancers12030753  Back to cited text no. 4
Alsahafi E, Begg K, Amelio I, Raulf N, Lucarelli P, Sauter T, et al. Clinical update on head and neck cancer: Molecular biology and ongoing challenges. Cell Death Dis 2019;10:540.  Back to cited text no. 5


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