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Personalized Medicine for Diagnosis and Therapies of Cancer

Cancer is among the leading causes of death all over the world. Every year, millions of cancer patients are enrolled for cancer treatment in which only few patients survive with present cancer therapy. There are various types of cancers, and it has been reported that cancer mortality is higher in men than in women. Overall estimated expenditure on cancer treatment is around USD 147 billion every year, but it may increase because of increase in cancer incidence and the cost of medicines.

However, since last two decades but with the innovation in various new technology developments, including completion of human genome project by Dr Fransis Colins, a revolution has occurred in the healthcare industry. This project has introduced molecular profiling of individual cancer patients to diagnose cancer more precisely than by any other method. It also allows clinicians to prescribe appropriate therapies which match with the patient’s own profile. This new form of medicine is termed as personalized medicine. Personalized medicine offers potential of improving the health of cancer patients. Worldwide, personalized medicine programs have focused on analysis of genetic profile of patients by using whole genome sequencing of cancer patients to get precise advice for cancer treatment. However, it is understood that the outcome of cancer treatment is not determined only by the variation in the genetic makeup of a tumor, but also by inter-patient differences in pharmacokinetics which may pose drug resistance. Therefore, personalized medicine requires not only the characterization of tumor cells but also watching the individualized drug resistance effect on these patients.

It is well reported that protein kinase activity is significantly increased in most of cancers and thus the protein kinase inhibitors play a very important role in treatment of various cancers. Seventeen small molecules and four antibodies are approved as protein kinase inhibitors, as cancer therapeutic drugs. These drugs interact with specific site of cancer cells and bring out significant inhibition of cancer cell growth. Most of these drugs are focused on only eight common linkage targets, i.e., VEGF or VEGFR, PI3K, EGFR2 (HER2), mTOR, EGFR, MET, PDGF or PDGFR and KIT. Presently, HER2 antibody trastuzumab is used in HER2-positive breast-cancer patients. Similarly, BCR-ABL1 inhibitor imatinib is used in chronic myeloid leukemia whereas gefitinib and erlotinib, which are EGFR kinase inhibitors, are used in non-small-cell lung cancer (NSCLC). BRAF inhibitor vemurafenib is used in melanoma and the dual ALK-MET inhibitor crizotinib is used in NSCLC. It is now well-known that use of kinase inhibitors for cancer therapy is very much dependent on predictive biomarkers expressed on a cancer patient’s cells. Thus, the presence or absence of these predictive markers is directly linked to the response rates of particular targeted therapies with small-molecule kinase inhibitors or antibodies.
With recent introduction of next-generation sequencer (NGS), whole-exome sequencing has become faster, affordable, and is being very much used in common clinical practice. Introduction of liquid biopsy has also given a non-invasive platform for doing molecular profiling of cancer patients without taking biopsy. Next-generation sequencing potentiates the sequencing of circulating tumor cells or cell-free DNA in liquid biopsies of cancer patients, which helps in diagnosis and therapy of cancer.

So overall roadmap for diagnosis and therapy of cancer contains four major steps: Indian government should take initiative to introduce personalized medicine in diagnosis and therapies of cancer and provide necessary funds for purchase of innovative instruments like PCR, real-time PCR, DNA sequencers, NGS, etc.; all cancer hospitals should work in close coordination with one another for following treatment of each patient; all cancer patients should be given proper knowledge about the treatment protocol and advised to do follow up as per the advice of his or her clinician; and we should initiate to collect this unique population-wide Omic database which may help us in future in the practice of personalized medicine for diagnosis and therapy of cancer. We are confident that in the near future we shall be able to implement personalized medicine treatment to counteract with the cellular and molecular heterogeneity of cancer and its drug resistance to cure this dreaded disease.

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