MOJ ISSN: 2374-6912MOJCSR

Cell Science & Report
Editorial
Volume 1 Issue 1 - 2014
Biomarkers and Personalized Medicine for Disease Diagnosis and Treatment
Jun-Jie Chen*
Department of Medical Research, E-Da Hospital, Taiwan
Received: April 14, 2014 | Published: April 24, 2014
*Corresponding author: Jun-Jie Chen, Department of Medical Research, E-Da Hospital, Rm 10503-2, Incubation and Research Bldg, No. 6, Yi-Da Road, Yan-Chao District, Kaohsiung City 824, Taiwan, Tel: +886-7-615-1100/5913; Email: @
Citation: Chen JJ (2014) Biomarkers and Personalized Medicine for Disease Diagnosis and Treatment. MOJ Cell Sci Report 1(1): 00001. DOI: 10.15406/mojcsr.2014.01.00001

Introduction

Biomarker is an important tool for disease diagnosis and tracking. Blood pressure, lipid, and sugar are simple example of biomarkers. According to the definition by (Food and Drug Administration, FDA), biomarkers can be any analytic method to detect or to predict general physiological response, disease progression, or patient’s therapeutic response and safety to drug treatment. The parameter of metabolite, gene or protein expression regards as an indicator in clinical manifestation [1].
Base on the clinical reports, experience, and statistics, majority patient are not responsive to pharmacological regimen. For example, 4% to 70% asthma patient is non-responsive to bronchodilators; 50% to 75% patient is only little response to oral hypoglycemic agents. Importantly, cancer patient has no effect after chemotherapy. In addition, systemic anaphylaxis is highly associated with patient genomic profiling. Hence, patient biomarker is critical indicator for providing proper drug treatment and preventing adverse effect. This information triggered the developing trend of personalized medicine.
During the past decade, tumor marker is becoming the most important topic in the field cancer research. It is a crucial reference for physician to treat patient with target therapy. With the feature of, simplicity, high sensitivity and accuracy, current medical technology allowed us to characterize specific molecule from patient’s tissue, body fluid, and peripheral blood [2].

Biomarkers for cancer drug

Agents

Biomarker

Indicative Group

Afatinib

EGFR

EGFR exon 19 deletion or exon 21 substitution (L858R) mutation positive

Arsenic Trioxide

PLIURARA

PUIL/RARa (t(15:17)) gene expression positive

Bosutinib

BCR/ABL1

Philadelphia chromosome (t(9:22)) positive

Brentuxirnab

TNFRSF8

CD30 positive

Cetuximab

EGFR

EGFR protein expression positive

Cetuximab

KRAS

KRAS codon 12 and 13 mutation negative

Crizotinib

ALK

ALK gene rearrangement positive

Dabrafenib

BRAF

BRAF V600E mutation positive

Dasatinib

BCR/ABL1

Philadelphia chromosome (t(9:22)) positive; T3151 mutation-positive

Denileukin

IL2RA

CD25 antigen positive

Erlotinib

EGFR

EGFR exon 19 deletion or exon 21 substitution (L858R) positive

Exemestane

ESR1

Estrogen receptor positive

Fulvestrant

ESR1

Estrogen receptor positive

Ibriturnomab

L1S4A1

CD20 positive

Imatinib

BCR/ABL1

Philadelphia chromosome (t(9:22)) positive

Lapatinib

ERBB2

HER2 protein overexpression positive

Letrozole

ESR1. PGR

Hormone receptor positive

Rlilotinib

BCR/ABL1

Philadelphia chromosome (t(9 :22)) positive

Omacetaxine

BCR/ABL1

BCR-ABL T3151

Panitumumab

KRAS

KRAS cotton 12 and 13 mutation negative

Pertuzumab

ERBB2

HER2 protein overexpression positive

Ponatinib

BCR/ABL1

Philadelphia chromosome (t (9; 22)) positive. BCR-ABL T3151 mutation

Rituximab

M S4M

CD20 positive

Tamoxifen

ESR1. PGR

Hormone receptor positive

Trametinib

BRAF

BRAF V600E/K mutation positive

Trastuzumab

ERBB2

HER2 protein overexpression positive

Tretinoin

PMURARA

PM1JRAR0 (t(15;17)) gene expression positive

Vemurafenit

BRAF

BRAF V600E mutation positive

With the development of next generation sequencing, this technology facilitates clinical physician to diagnose the genetic profile and somatic mutation of patient. Bioinformatic data provide a great evidence for disease characterization and pharmacotherapy. In the case of non small cell lung cancer (NSCLC), Erlotinib is a specific inhibitor to block EGFR which is only used for treatment of patient with EGFR mutation or overexpression. Clinical research revealed this drug particularly is effective in the tumor harboring exon 19 or 21 mutation. In the other case, approximately 7% NSCLC patient has EML4-ALK rearrangement, FDA approved ALK inhibitor-Crizotinib for treating this kind indication.
On the other hand, biomarkers can be applicable for understanding the mechanism of drug resistance. Cetuximab is a therapeutic monoclonal antibody which is also targeting EGFR. Its indication is for colon cancer. However, some patient with KRAS gene mutation is not eligible for the utilization of this agent [3].
All these example indicated and emphasized the importance and application of biomarkers in clinical. New diagnostic technology have considerable potential to improve care, target treatment, and reduce the cost of unnecessary prescriptions and the downstream effects of drug resistance and increase the accuracy of pharmacotherapy. The postgenomic era has been launched by significant enthusiasm for therapeutic individualization through the use of pharmacogenomic and other biomarkers. This enthusiasm has been dampened by limited examples of widespread clinical adoption. Future studies of putative biomarkers are likely to give additional information to clearly define which patients receive therapeutic benefit from target therapy.

References

  1. Zineh I, Huang SM (2011) Biomarkers in drug development and regulation: a paradigm for clinical implementation of personalized medicine. Biomark Med 5(6): 705-713.
  2. Godman B, Finlayson AE, Cheema PK, Zebedin-Brandl E, Gutierrez-Ibarluzea I, et al. (2013) Personalizing health care: feasibility and future implications. BMC Med 11: 179.
  3. Stenvang J, Kumler I, Nygard SB, Smith DH, Nielsen D, et al. (2013) Biomarker-guided repurposing of chemotherapeutic drugs for cancer therapy: a novel strategy in drug development. Front Oncol 3: 313.
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