Is genomic grading
killing histological grading ?
Sotiriou C,
Wirapati P, Loi S, Desmedt C, Haibe-Kains B, Piette F, Buyse M,
Bontempi G, Delorenzi M, Piccart M
The histologic grade of breast carcinomas has long provided clinically
important prognostic information. However, despite recommendations by
the College of American Pathologists that tumor grade be used as a
prognostic factor in breast cancer, the latest Breast Task Force of the
American Joint Committee on Cancer did not include histologic tumor
grade in its staging criteria, because of insurmountable
inconsistencies in histologic grading between institutions. Concordance
between two pathologists has been investigated and found to range from
50% to 85%. With the advent of new unified methods, such as the Elston
and Ellis modification of the Bloom and Richardson method, the
reproducibility of histologic grading has been improved. Although about
half of all breast cancers are assigned histologic grade 1 or 3 status
(with a low or high risk of recurrence, respectively), a substantial
percentage of tumors (30%-60%) are classified as histologic grade 2,
which is not informative for clinical decision making because of its
intermediate risk of recurrence. This high percentage histologic grade
2 tumors is still observed when grading is performed by a single
pathologist.
Recently, gene expression profiling has resulted in a paradigm shift in
the way that researchers view breast cancer biology. In a previous work
we have demonstrated, for example, that the ER status of the tumor was,
indeed, the most important discriminator of expression subtypes, and
that tumor grade came in second. Interestingly, other clinical
features, namely positive lymph node status, menopausal status, and
tumor size were not strongly reflected in the expression patterns.
Following our previous observation that tumor grade was an important
discriminator of expression subtypes we sought whether grade could be
refined by using gene expression profiling. In a recent work we have
demonstrated that ``genomic'' tumor grade, which reflects
differentiation and tumor progression on the basis of gene expression
profiles (GEP), is effectively associated with distinct GEP and disease
outcome in breast cancer far beyond the currently used
clinico-pathological parameters. For that purpose we established a
scoring system, referred to as the ``gene-expression grade index''
(GGI), and tested it on various independent validation datasets. We
found that poorly differentiated compared with well-differentiated
tumors are associated with distinct GEP and GGI and have statistically
different clinical outcomes. Many of the markers are genes involved in
cell cycle progression and proliferation, including CCNB2, CDC2, BUB1B,
CDC25A and TPX2. We further demonstrated that intermediate grade tumors
contain a mixture of well-differentiated and poorly differentiated
expression patterns rather than a distinct or intermediate profile.
This observation challenges the existence and clinical relevance of an
intermediate grade classification. Interestingly, we also found that
grade-related genes may encompass a significant portion of the
predictive power of previously published prognostic signatures. Notably, we also found that genomic grade was also associated with the
different molecular subtypes (previously identified by our group and
others): basal-like, erbB2-like and luminal A, B and C subgroups. While
the luminal A subgroup showed lower GGI levels, the basal-like,
erbB2-like and luminal B and C subgroups had the worst clinical outcome
in keeping with higher GGI levels. These results may suggest that the genomic grade, which essentially
captures the degree of differentiation, may reflect the origin of the
different cell lineages involved in breast cancer development.
We are currently validating our findings in the TRANSBIG series of 300
tumor samples from 5 different European institutions from which grading
was determined based on a central pathology review. Additionally, we
are in the process to convert genomic grade into a user-friendly RT-PCR
tool which will assist clinicians and patients in optimizing treatment
of early breast cancer.