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Malignancy prediction among tissues from Oral SCC patients including neck invasions: a 1H HRMAS NMR based metabolomic study

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Abstract

Introduction

Oral cancer is a sixth commonly occurring cancer globally. The use of tobacco and alcohol consumption are being considered as the major risk factors for oral cancer. The metabolic profiling of tissue specimens for developing carcinogenic perturbations will allow better prognosis.

Objectives

To profile and generate precise 1H HRMAS NMR spectral and quantitative statistical models of oral squamous cell carcinoma (OSCC) in tissue specimens including tumor, bed, margin and facial muscles. To apply the model in blinded prediction of malignancy among oral and neck tissues in an unknown set of patients suffering from OSCC along with neck invasion.

Methods

Statistical models of 1H HRMAS NMR spectral data on 180 tissues comprising tumor, margin and bed from 43 OSCC patients were performed. The combined metabolites, lipids spectral intensity and concentration-based malignancy prediction models were proposed. Further, 64 tissue specimens from twelve patients, including neck invasions, were tested for malignancy in a blinded manner.

Results

Forty-eight metabolites including lipids have been quantified in tumor and adjacent tissues. All metabolites other than lipids were found to be upregulated in malignant tissues except for ambiguous glucose. All of three prediction models have successfully identified malignancy status among blinded set of 64 tissues from 12 OSCC patients with an accuracy of above 90%.

Conclusion

The efficiency of the models in malignancy prediction based on tumor induced metabolic perturbations supported by histopathological validation may revolutionize the OSCC assessment. Further, the results may enable machine learning to trace tumor induced altered metabolic pathways for better pattern recognition. Thus, it complements the newly developed REIMS-MS iKnife real time precession during surgery.

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Abbreviations

OSCC:

Oral squamous cell carcinoma

HRMAS:

High Resolution Magic Angle Spinning

CPMG Spectra:

CPMG 1H HRMAS NMR Spectra

NOESY Spectra:

NOESY 1H HRMAS NMR Spectra

OPLS-DA:

Orthogonal Partial Least Square Discriminant Analysis

PLS-DA:

Partial Least Square Discriminant Analysis

QUANTAS:

QUANTification by Artificial Signal

CustomCSI:

Custom Chemical Shift Index

SHi-PUFA:

Sum of Higher Polyunsaturated Fatty Acids

MUFA:

Monounsaturated Fatty Acid

SFA:

Saturated Fatty Acids

TG:

Triglycerides

FFA:

Free Fatty Acids

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Acknowledgements

The authors are thankful to Division of SAIF, CSIR-Central Drug Research Institute, Lucknow where the 1H HRMAS NMR measurement were conducted. Mr. Anup Paul would like to thank UGC (SRF Award No. 18-12/2011(ii)EU-V) for financial assistance.

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Author notes

  1. Shatakshi Srivastava

    Present address: Apeejay Stya University, Sohna, Gurugram, 122103, Haryana, India

Authors and Affiliations

  1. Centre of Biomedical Research, Formerly Centre of Biomedical Magnetic Resonance (CBMR), Sanjay Gandhi Postgraduate Institute of Medical Sciences Campus, Rae Bareli Road, Lucknow, 226014, India

    Anup Paul, Shatakshi Srivastava & Raja Roy

  2. Department of General Surgery, Kings George’s Medical (KGMU), Lucknow, 226003, India

    Akshay Anand, Kushagra Gaurav & Abhinav A. Sonkar

  3. Department of Pathology, Dr. Ram Manohar Lohia Institute of Medical Science, Lucknow, 226010, India

    Nuzhat Husain

  4. Department of Chemistry, University of Lucknow, University Road, Lucknow, 226007, India

    Anup Paul & Sudha Jain

  5. Department of General Surgery, King Georges Medical College (KGMU), Lucknow, 226001, India

    Abhinav A. Sonkar

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Contributions

AAS, AA, KG and RR designed the study. AA, KG and AAS performed the surgery and sampled the tissue specimens. SS and RR conducted the experiments. AP, and RR processed and analyzed the spectral data. NH performed the histopathology. Initial draft written by AP. AAS and RR edited and revised the paper. Project administration of the study have carried under AAS, SJ and RR. All authors carefully read and agree to be accountable for all aspects of the work.

Corresponding authors

Correspondence to Raja Roy or Abhinav A. Sonkar.

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Conflict of interest

The authors have no potential conflict of interest. The disclosure of potential conflict of interest in the prescribed format has been obtained from all the author.

Ethical approval

The study was ethically approved and the work was performed in strict accordance with the guidelines of Institutional Ethical Committee of King George’s Medical University (KGMU) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The subjects were explained the study procedure and written and informed consent were obtained from them prior to the study. The authors: Anup Paul, Shatakshi Srivastava, Raja Roy, Akshay Anand, Kushagra Gaurav, Nuzzat Hussain, Sudha Jain and Abhinav A. Sonkar are aware of the ethical policy.

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Paul, A., Srivastava, S., Roy, R. et al. Malignancy prediction among tissues from Oral SCC patients including neck invasions: a 1H HRMAS NMR based metabolomic study. Metabolomics 16, 38 (2020). https://doi.org/10.1007/s11306-020-01660-8

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