Gene expression profiling in cancer

Classification of cancers has been dominated by the fields of histology and histopathology which aim to leverage morphological markers for accurate identification of a tumor type.

Histological methods rely on chemical staining of tissues with pigments such as haematoxylin and eosin and microscopy-based visualization by a pathologist.

[1] Furthermore, the clinical outcomes of tumors classified as DLBCLs is highly variable[1] suggesting that there are multiple subtypes of DLBCL that cannot be distinguished based on these histological markers.

In a particular type of cell or tissue, only a small subset of an organism's genomic DNA will be expressed as mRNAs at any given time.

Microarray analysis can provide quantitative gene expression information allowing for the generation of a molecular signature, each unique to a particular class of tumor.

A hierarchical clustering algorithm was used to group cell lines based on the similarity by which the pattern of gene expression varied.

A more powerful result of gene expression profiling is the ability to further classify tumors into subtypes having distinct biological properties and affect prognoses.

For example, some diffuse large B-cell lymphomas (DLBCLs) are indistinguishable based on histological methods yet are clinically heterogeneous: 40% of patients respond well and exhibit prolonged survival while the remaining 60% do not.

[9] The goal of the study was to identify patterns of gene expression that could be used to describe the phenotypic diversity of breast tumors by comparing the profiles of the biopsies to those of cultured cell lines and relating this information to clinical data.

Within the ER-negative group, additional clusters were identified based on expression of Erb-B2 and keratin 5- and 17-enriched basal epithelial-like genes.

These groups reflect distinct molecular features as related to mammary epithelial biology, based on the outcome of disease.

The authors further found once they performed survival analyses that tumors belonging to the various groups showed significantly different outcomes when treated uniformly.

It is agreed upon that patients with tumors exhibiting poor prognostic features would benefit the most from adjuvant therapy as these treatments substantially improve overall survival for women with breast cancer.