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Identifying Prognostic Markers of Non-small Cell Lung Carcinoma Using Bioinformatics

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Proceedings of International Conference on Industrial Instrumentation and Control

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 815))

Abstract

We present a transcriptomics pipeline for performing the functional analysis of array expression profiling data of normal and adenocarcinoma lung tissue. Our aims are twofold, firstly to elucidate molecular processes that transform normal tissue, to a lung adenocarcinoma. Following this, we perform functional analysis to screen potential hub genes and demonstrate their value in cancer prognosis. Analysis was performed on a total of 500 differentially expressed genes (DEG), screened for their regulation and transcriptional modulation in a female population carrying non–small cell lung carcinoma (NSCLC). Key pathways like cytokine-cytokine receptors, ECM receptor interactions, and TNF signaling were identified suggesting a potential role in lung tumorigenesis.

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Acknowledgements

Center for Integrated Research Computing (CIRC) at University of Rochester for computational resources. There are no funding disclosures.

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Authors and Affiliations

  1. Department of Biomedical Engineering, University of Rochester, Rochester, NY, 14627, USA

    Siladitya Khan

  2. Goergen Institute for Data Science, University of Rochester, Rochester, NY, 14627, USA

    Siladitya Khan

  3. Materials Science Graduate Program, University of Rochester, Rochester, NY, 14627, USA

    Debamitra Chakraborty

Authors
  1. Siladitya Khan
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  2. Debamitra Chakraborty
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Corresponding author

Correspondence to Siladitya Khan .

Editor information

Editors and Affiliations

  1. Department of Aerospace Engineering and Applied Mechanics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, West Bengal, India

    Subhasis Bhaumik

  2. Department of Electrical Engineering, National Institute of Technical Teachers’ Training & Research, Kolkata, West Bengal, India

    Subrata Chattopadhyay

  3. TCS Research and Innovation Lab, Kolkata, West Bengal, India

    Tanushyam Chattopadhyay

  4. Department of Applied Electronics and Instrumentation Engineering, RCC Institute of Information Technology, Kolkata, West Bengal, India

    Srijan Bhattacharya

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Khan, S., Chakraborty, D. (2022). Identifying Prognostic Markers of Non-small Cell Lung Carcinoma Using Bioinformatics. In: Bhaumik, S., Chattopadhyay, S., Chattopadhyay, T., Bhattacharya, S. (eds) Proceedings of International Conference on Industrial Instrumentation and Control. Lecture Notes in Electrical Engineering, vol 815. Springer, Singapore. https://doi.org/10.1007/978-981-16-7011-4_51

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  • DOI: https://doi.org/10.1007/978-981-16-7011-4_51

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7010-7

  • Online ISBN: 978-981-16-7011-4

  • eBook Packages: EngineeringEngineering (R0)

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