Call for Paper

CAE solicits original research papers for the July 2023 Edition. Last date of manuscript submission is June 30, 2023.

Read More

Bio-Informatics – Review on Current Research and Evolution of Cancer Targeted Therapies

Ayan Chatterjee, Uttam Kumar Roy, Nibedita Pahari. Published in Artificial Intelligence.

Communications on Applied Electronics
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Ayan Chatterjee, Uttam Kumar Roy, Nibedita Pahari

Ayan Chatterjee, Uttam Kumar Roy and Nibedita Pahari. Article: Bio-Informatics – Review on Current Research and Evolution of Cancer Targeted Therapies. Communications on Applied Electronics 4(3):48-55, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {Ayan Chatterjee and Uttam Kumar Roy and Nibedita Pahari},
	title = {Article: Bio-Informatics – Review on Current Research and Evolution of Cancer Targeted Therapies},
	journal = {Communications on Applied Electronics},
	year = {2016},
	volume = {4},
	number = {3},
	pages = {48-55},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


The statistics shows that 7 million people die each year worldwide from cancer related cases & by 2020 this number will be more than around 16 million as methods of cancer treatment & cancer classification have become most challenging. So, cancer has become a noted disease responsible for major death rate. 200 different types of cancers are identified but some of them like lung, liver, stomach, colorectal, breast, oesophagal are leading death count. More than 60% of world’s total new cases occur in Africa, Asia and Central and South America per annum. These regions account for 70% of the world’s cancer deaths by oesophagal cancers as reported by World Health Organization.

This article reviews and discusses recent improvement in the treatment of cancer and the challenges that exist, in reduced cost & time. Development and use of bioinformatics, nanotechnology is essential for the future cancer therapeutics. Most cancer treatments work for limited number of patients and this is likely to remain true for many molecularly-targeted drugs. As a consequence, a large proportion of patients are deprived of effective treatments and it is a huge financial burden on our health care system. It is essential to develop accurate tools for delivering the right treatment to the right patient based on biological characterization of each patient's tumor. The integration of wet experiments and the use of bio-informatics analysis have become an important part of biological and clinical research of this century. If we don’t pay attention to it in future we will find a cancer patient in each family across the world. Cancer cure is really difficult but not complete hopeless. A lot of researches are being carried out in the field of bio-informatics to open up new possibilities for cancer treatments.


  1. Gibbs, W. Wayt. 2003. Untangling the roots of cancer. Scientific American, July, 57–65. New evidence challenges old theories of how cancer develops.
  2. Han-Chung Wu1, De-Kuan Chang, and Chia-Ting Huang. Journal of Cancer Molecules 2(2): 57-66, 2006. Targeted Therapy for Cancer.
  3. Harris M. Monoclonal antibodies as therapeutic agents for cancer. Lancet Oncol 5: 292-302, 2004.
  4. Wilson, J. F. 2001. A dual role for CDK inhibitors. The Scientist 16[6]:20. Discusses approaches to cancer treatment using cells’ cycle inhibitors.
  5. G Roti and K Stegmaier. British Journal of Cancer (2012) 106, 254 – 261. Genetic and proteomic approaches to identify cancer drug targets
  6. Chung CH, Levy S, Chaurand P, Carbone DP. 2007. Genomics and proteomics: Emerging technologies in clinical cancer research. Crit Rev Oncol Hematol 61:1-25.
  7. Galvão ER, Martins LM, Ibiapina JO, Andrade HM, Monte SJ. 2011. Breast cancer proteomics: a review for clinicians. J Cancer Res Clin Oncol. 137(6):915-25.
  8. Kihara D, Yang YD, Hawkins T. 2007. Bioinformatics resources for cancer research with an emphasis on gene function and structure prediction tools. Cancer Inform 7;2:25-35.
  9. Swen Hoelder, Paul A. Clarke, Paul Workman. MOLECULAR ONCOLOGY 6 (2012) 155-176. Discovery of small molecule cancer drugs: Successes, challenges and opportunities.
  10. Veggeberg, S. 2002. Fighting cancer with angiogenesis inhibitors. The Scientist 16[11]:41. Discussion of a class of drugs that helps to prevent angiogenesis.
  11. Dvorak HF, Nagy JA, Dvorak AM. Structure of solid tumors and their vasculature: implications for therapy with monoclonal antibodies. Cancer Cell 3: 77-85, 1991.
  12. Shockley TR, Lin K, Nagy JA, Tompkins RG, Dvorak HF, Yarmush ML. Penetration of tumor tissue by antibodies and other immunoproteins. Ann N Y Acad Sci 618: 367-382, 1991.
  13. Alicia S. Chung, John Lee & Napoleone Ferrara. Nature Reviews Cancer 10, 505-514 (July 2010) doi:10.1038/nrc2868. Targeting the tumor vasculature: insights from physiological angiogenesis.
  14. Shanju Sankar, Sangeetha K Nayanar, Satheesan Balasubramanian. Asian Pac J Cancer Prev, 14 (7), 4041-4047. DOI: current Trends in Cancer Vaccine - a Bioinformatics Perspective.
  15. Christoph Bock and Thomas Lengauer. Vol. 24 no. 1 2008, pages 1–10.doi:10.1093/bioinformatics/btm546. Computational epigenetics.
  16. Thomas Lengauer and Ralf Zimmer. Henry Stewart Publications 1467-5463. BRIEFING IN BIOINFORMATICS. Vol 1,No 3, 275-288, September 2000. Protein structure prediction methods for drug design.
  17. Azuaje. Interpretation of genome expression patterns: computational challenges and opportu-nities. IEEE Engineering in Medicine and Biology, 2000.
  18. Berns. Cancer: Gene expression in diagnosis. Nature, pages 491–492, Feb 2000.
  19. Wang XD, Liotta L. 2011. Clinical bioinformatics: a new emerging science. J Clin Bioinforma 2011, 1(1):1.
  20. Ayan Chatterjee & Dr. Uttam Kumar Roy, International Journal of Current Engineering and Technology 12/2015; 5(6):3866. DOI: 10.14741/Ijcet/22774106/5.6.2015.66
  21. Ayan Chatterjee & Dr. Uttam Kumar Roy, International Journal of Scientific and Engineering Research 11/2015; 6(11):612. DOI: 10.14299/ijser.2015.11.006


Ligand, Microarray, Target, PDB, cell cycle, Oncogenes, Tumor, Peptide, DNA/Gene, Tumor Suppressor, Kinase etc.