Personalized Medicine: The Road Ahead

被引:32
|
作者
Mehta, Rutika [1 ]
Jain, Rohit K. [1 ]
Badve, Sunil [1 ]
机构
[1] Indiana Univ Sch Med, Dept Pathol, Indianapolis, IN 46202 USA
关键词
Future directions; Prognostic factors; PATHOLOGICAL PROGNOSTIC-FACTORS; BREAST-CANCER PATIENTS; GROWTH-FACTOR RECEPTOR; GENE-EXPRESSION; ESTROGEN-RECEPTOR; HISTOLOGIC GRADE; MOLECULAR CLASSIFICATION; MONOCLONAL-ANTIBODY; FOLLOW-UP; ADJUVANT;
D O I
10.3816/CBC.2011.n.004
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
With breast cancer now being recognized as a heterogeneous disease, the concept of personalized medicine demands that the tumor of every individual be treated uniquely. This has lead to ever-expanding use of existing prognostic and predictive markers, and the search for better ones is ongoing. The classic prognostic tools such as tumor size, lymph node status, grade, hormone receptors, and HER2 status are now supplemented by gene expression based tools such as PAM50 and MammaPrint. However, the overdependence of these tools on proliferation-related genes is a significant handicap. Although pathway-based signatures hold great promise in future breast cancer prognostication, the fact that every tumor has multiple functional pathways significantly limits the utility of this approach. Developed by the integration of estrogen receptor (ER), HER2, proliferation-related, and other genes, the Oncotype DX assay has been able to provide valuable prognostic information for ER-positive tumors. Newer molecular markers based on cancer stem cells, single-nucleotide polymorphisms (SNPs), and miRNAs are becoming available, but their importance needs to be validated. It is clear that breast cancer is a multifaceted process and that none of the tools can reliably predict a binary outcome (recurrence or no recurrence). The breast cancer community is still awaiting an ideal prognostic tool that can integrate knowledge from classic variables such as tumor size and grade with new throughput technology and principles of pharmacogenomics. Such a tool will not only define prognostic subgroups but also be able to predict therapeutic efficacy and/or resistance based on molecular profiling.
引用
收藏
页码:20 / 26
页数:7
相关论文
共 50 条
  • [1] Personalized Medicine The Road Ahead
    Sznajder, Jacob I.
    Ciechanover, Aaron
    [J]. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2012, 186 (10) : 945 - 947
  • [2] From proteomics to personalized medicine: the road ahead
    Nice, E. C.
    [J]. EXPERT REVIEW OF PROTEOMICS, 2016, 13 (04) : 341 - 343
  • [3] Mitochondrial disorders: Emerging paradigms and the road ahead to personalized medicine
    Gropman, Andrea
    Carver, Bharatendu Chandra
    [J]. NEUROTHERAPEUTICS, 2024, 21 (01)
  • [4] From Omic Layers to Personalized Medicine in Colorectal Cancer: The Road Ahead
    Romero-Garmendia, Irati
    Garcia-Etxebarria, Koldo
    [J]. GENES, 2023, 14 (07)
  • [5] The Road Ahead for Personalized Firearms
    Simonetti, Joseph A.
    Rowhani-Rahbar, Ali
    Rivara, Frederick P.
    [J]. JAMA INTERNAL MEDICINE, 2017, 177 (01) : 9 - 10
  • [6] Steps on the road to personalized medicine
    Jones, Dan
    [J]. NATURE REVIEWS DRUG DISCOVERY, 2007, 6 (10) : 770 - 771
  • [7] The Road to Personalized and Predictive Medicine
    Martin, Greg
    Jones, Dean
    [J]. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2013, 188 (02) : 257 - 257
  • [8] Privacy on the Road to Personalized Medicine
    Boffa, Daniel J.
    Nelson, Heidi
    Mullett, Timothy
    Opelka, Frank
    Turner, Patricia L.
    Shulman, Lawrence N.
    [J]. JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK, 2024, 22 (1D):
  • [9] Steps on the road to personalized medicine
    Dan Jones
    [J]. Nature Reviews Drug Discovery, 2007, 6 : 770 - 771
  • [10] Hurdles on the road to personalized medicine
    Tursz, Thomas
    Bernards, Rene
    [J]. MOLECULAR ONCOLOGY, 2015, 9 (05) : 935 - 939