Expression Profiling, mRNA



Expression Profiling, mRNA










GEP is performed by mixing labeled tumor RNA with reference RNA and hybridizing to complementary sequences. Relative RNA expression may be increased (red), decreased (green), or unchanged (yellow).






GEP data are analyzed to find biologically meaningful patterns based on similar patterns of gene expression. This approach was used to develop the intrinsic molecular classification of breast cancers.


TERMINOLOGY


Abbreviations



  • Gene expression profiling (GEP)


Definitions



  • Methods that measure relative amounts of mRNA in cancers; overall pattern is referred to as the gene profile or signature


GENE EXPRESSION PROFILING


Introduction



  • GEP uses cDNA microarrays or quantitative RT-PCR on clinical samples of breast tumor tissue to detect mRNA levels



    • Simultaneous examination of global changes in patterns of gene expression


    • Ability to molecularly profile breast tumors at the level of the expression of 20,000-25,000 genes


  • GEP has added greatly to our understanding of biologic diversity of breast cancer



    • Provides important insights into breast tumor biology


    • Provides clinically meaningful molecular tumor classification


    • Identifies good and poor prognostic groups


    • Defines cancers more susceptible to specific types of therapy


  • GEP has potential to provide value beyond traditional clinical/pathologic prognostic and predictive factors


GEP, Unsupervised “Cluster” Analysis



  • Requires fresh or snap-frozen tissue samples from cohort of breast cancer patients with outcome data



    • RNA isolated from tumor tissue


    • Analyzed using cDNA microarrays



      • Determines level of mRNA gene expression relative to reference RNA


      • Data on expression levels for thousands of genes collected for analysis


      • Computer and statistical analysis needed to look for biologically meaningful patterns


  • Unsupervised cluster analysis (class discovery approach)



    • Sorts tumors into related clusters based on similarities in gene expression profiles


    • “Dendrograms” used to illustrate degree of relatedness between different tumors


    • Sorts tumors into different groups of imputed biologic significance


  • This approach used to develop intrinsic molecular classification of breast cancer


CLINICAL IMPLICATIONS


GEP Identifies Four Major Types of Cancer



  • Microarrays and unsupervised analysis group breast cancers into distinctive subsets using patterns of mRNA levels


  • Reproducible differences in gene expression patterns help define distinct subtypes of breast cancer



    • Likely represent different distinct tumor types



      • Reflect underlying differences in biology


      • Influence clinical course, likelihood of recurrence, and overall survival


      • Influence response to therapy


  • Results of GEP support that groups of cancers defined by ER, PR, HER2, and proliferation also share a much broader range of gene expression patterns


Luminal Subtype A



  • Gene expression pattern (˜ 55% of breast cancers)



    • High levels of ER



      • Genes regulated by ER (including PR) and genes associated with ER activation


    • Luminal cytokeratins (e.g., cytokeratins 8/18)


    • Does not overexpress HER2



    • Lower expression of proliferation-related genes


  • Clinical features



    • Indolent clinical course of disease


    • Better prognosis compared with luminal B cancers or other subtypes


    • Metastatic pattern is to bone, often after a long disease-free interval


Luminal Subtype B



  • Gene expression pattern (˜ 15% of breast cancers)



    • Generally lower level of expression of ER and ER-related genes


    • Often negative for PR or low-level expression


    • HER2 overexpressed in 30-50% of cases


    • May overexpress EGFR (HER1)


    • Higher expression of proliferation-related genes



      • Ki-67 proliferation index may be useful to help separate luminal B from luminal A tumors


  • Clinical features



    • More aggressive clinical course, worse prognosis


HER2 Subtype



  • Gene expression pattern (15-20% of breast cancers)



    • HER2 overexpressed



      • Also overexpresses adjacent genes on HER2 amplicon; number of genes varies in different cancers


      • May include TOP2-α (associated with sensitivity to anthracyclines) and GRB7


    • Does not express ER or PR


    • Higher expression of proliferation-related genes


  • Clinical features



    • More likely to have multiple involved lymph nodes


    • More aggressive clinical course; poor prognosis but modified by HER2-targeted therapy


  • Identification of HER2 subtype by GEP confirmed that these cancers represent a clinically distinct subset



    • HER2(+) tumors defined by GEP do not completely overlap with HER2(+) tumors defined by IHC &/or FISH


Basal Subtype

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Jul 6, 2016 | Posted by in PATHOLOGY & LABORATORY MEDICINE | Comments Off on Expression Profiling, mRNA

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