Identification Of Pathway Leading To Ototoxicity By The Use Of Cisplatin

Ototoxicity refers to the condition of ear poisoning that results from exposure to drugs and chemicals that damage the internal ear or hear-able nerve leading to the impairment of hearing and balance. Serious dosing of Cisplatin, a platinum-based drug that is used in chemotherapy in the treatment of malignant tumor's has been known to cause ototoxicity. Mrinal Bamhotra and Yachita Gupta, two of our Research Fellows at Pine Biotech performed a research project that aims to identify the genes and pathways related to the side effects of Cisplatin using the gene expression data from lung cancer which was also used to verify if the ill effects of Cisplatin are generic or specific to cochlear cells.


OmicsLogic Learn Profile


Mrinal Bamhotra and Yachita Gupta are the students of M.Sc. Bioinformatics from Panjab University, Chandigarh, India. To explore the pathways leading to ototoxicity by the use of Cisplatin, they joined the Bioinformatics Research Fellowship Program where they worked as a team under the guidance of Dr. Raghavendran Lakshminarayanan, Research Consultant and Mentor at Pine Biotech and Mr. Elia Brodsky, CEO of Pine Biotech. 


During the duration of the program, they worked on the following introductory courses of bioinformatics: Course 1: Introduction to Bioinformatics and Course 2: Bytes and Molecules.


Followed by this they completed the intermediate courses to gain in-depth knowledge of specific sub-disciplines of bioinformatics and data science. The following were the intermediate courses they had completed: Course 5: Transcriptomics, R-Coding Course 2: Introduction to Data Science (BioML), Python Course 2: Introduction to Data Science (BioML) and Course 9: Designing a Bioinformatics Research Project


To apply the knowledge and skills gained so far from studying the courseworks, they also completed the example projects on Project 01: COVID-19 Origin & Pathogenesis of SARS-COV2 and Project 03: TCGA Liver Cancer - Precision Oncology.


To view their OmicsLogic student profile and learn more about the various courses and projects they have completed, visit the links — 


Yachita Gupta - 

Mrinal Bamhotra - 


Pipeline Graph


A dataset with 133 samples consisting of Adenocarcinoma (ADC), Squamous Cell Carcinoma (SQCC), and Large Cell Undifferentiated Carcinoma (LCUC) was used for the project. This dataset is available under the GEO Accession ID: GSE14814. Upon performing Principal Component Analysis using the Utilities Pipeline from the T-BioInfo server, it was observed that the separation of the ADC-SQCC group was much better than including LCUC which had fewer samples. Hence, the study further focused only on the ADC-SQCC group. Next, differential expression analysis of the genes of the ADC-SQCC group was done using statistical comparison with a T-test in MS-Excel. The functional annotation was done using DAVID and the enriched pathways were identified using the Human GAGE Pipeline from the T-BioInfo server


Several genes that were differentially expressed between ADC and SQCC lung cancer were associated with cell differentiation, tumorigenesis, and DNA replication. Among the enriched pathways, the Glutathione metabolism pathway was identified. This pathway is implicated in a form of defence against cisplatin-induced ototoxicity in cells from the human inner ear. Hereby, the team concluded that it is possible to identify specific gene expression patterns and pathways related to the side effects of cisplatin treatment in lung cancer.


Here is what Mrinal and Yachita had to say about their research fellowship experience: 


Mrinal Bamhotra:

“I am truly delighted to tell you that I have completed my research fellowship at Pine Biotech. It has been a great learning and instructive experience for me. All the learning process is very unique, amazing and related to real-life skill development which I believe will help me in my future endeavours. The courses provided helped me a lot with transcriptomic data analysis, MS-Excel, R coding, and many other topics related to my research. The weekly research fellowship meetings with our mentor Dr. Raghavendran Lakshminarayanan helped me at every point of the research wherever I got stuck whether it was checking the dataset or helping me with the coding. I would also like to extend my special thanks to Ms. Sonalika Ray for helping me with every technical difficulty related to the T-BioInfo sever. I am also extremely grateful to the entire team and looking forward to working with them again.”


Yachita Gupta: 

“I am excited to tell you that I have completed my research fellowship at pine biotech. In these 6 months, I have learned a lot about transcriptomics and bioinformatics that are related to my research project. Also, I would like to thank Mr. Ojasvi Dutta for helping me come out of my comfort zone and help me achieve my goals. During the research fellowship program, Dr. Raghavendran Lakshminarayanan’s guidance was invaluable and the way he wonderfully cleared our doubts during weekly research fellowship meetings is praiseworthy. 

I would also like to extend my special thanks to Ms. Sonalika Ray for coming in all those extra hours and helping me with my doubts related to the T-BioInfo server. Thank you all for being great mentors and I am grateful to the whole team and looking forward to working with Pine Biotech again.”


To learn more about their research project, visit the link - 


Feeling motivated to work on your own research project? Then don't miss the chance to register yourself for the Bioinformatics Research Fellowship Program


Research Fellowship Program


The Bioinformatics Research Fellowship Program is a structured program that guides students through various areas of Big Data Bioinformatics Research using practical examples. During this program, we go through several high-quality research publications and learn about applications of computational biology in projects these publications describe. This allows beginners to try computational biology techniques on public domain data, making it possible to work with large files and extract meaningful information from patient samples, animal models, cell lines, and microbiota. The program provides support and mentorship, therefore it is an intensive research program involving training tasks, access to our online sessions and a guide on the implementation of learned skills to proposed research ideas. 


To learn more about the program, please visit the link: