MOLECULAR PATHOLOGY OF SQUAMOUS CARCINOMA INCLUDING HIGHTHROUGHPUT GENE EXPRESSION ARRAYS

A variety of molecular abnormalities are present in squamous
carcinoma that are not necessarily diagnostically useful but
are part of the constellation of changes that accompany malignant
transformation. Genetic changes in squamous tumors
are numerous and can be grouped according to the molecular
pathway they affect. Specific genetic lesions tend to group with
specific histologies. To date, most mutations in squamous carcinoma
are found to be associated with cell cycle genes and less
frequently with tyrosine kinase pathway genes. 84,85 A list of
the most common genetic abnormalities and their frequencies
in specific tumor types is presented in Table 22.4 and discussed
in the context of specific tumor types.
Cell Cycle Genes Genes of the cell cycle were the first
to be evaluated in lung cancer and are the most commonly
mutated genes in squamous carcinoma.
TP53 TP53 is a multifunctional transcription factor that plays
a complex role in a variety of processes including cell cycle regulation,
DNA repair, and apoptosis. Of particular interest is its role
as a cell cycle checkpoint in which TP53 interacts with DNA repair
and recombination enzymes. 86 This allows the cell to correct
DNA damage during replication and the frequency of mutation
and chromosomal rearrangement transmitted to daughter cells
is thereby reduced. TP53 mutation interferes with DNA repair
and may thus result in chromosomal instability, a major factor in
malignant progression and resistance to chemotherapy. TP53 is
the most commonly mutated gene in all lung carcinomas including
squamous carcinoma. 87 TP53 mutation does not appear to
be associated with outcome in squamous carcinoma although it
is associated with reduced survival in adenocarcinoma. 88
CDKN2A (p16) P16 protein inhibits cyclin-dependent kinase
4 (CDK4) and inactivation of this inhibitor removes a
brake on cell proliferation, enhancing tumor growth. P16 is
one of the most frequently affected of the tumor suppressor
genes and may be deleted 89,90 or methylated 91 in lung cancer.
The gene is inactivated in approximately 60% squamous
carcinoma. 92 Methylation of p16 is an independent prognostic
variable in NSCLC regardless of histological subtype. 93
By contrast, in SCLC p16 is usually intact but the RB1 gene,
also affecting progression through the cell cycle, is almost
universally inactivated (see succeeding discussion of SCLC).
Immunohistochemical tests assessing cell cycle–related proteins
have been of more limited prognostic value. In one recent
study, no single cell cycle protein (including p16) was of prognostic
importance 94,95 and only with combinations of markers
could statistical significance be achieved. 95 Prediction of
outcome in individual tumors based on immunohistochemical
testing of cycle proteins is unlikely to be accurate or reliable
and it appears that only direct assessment of p16 gene methylation
provides prognostic information.
Expression Microarrays other High-Throughput
Technologies Until recently, biomarkers have been measured
singly but oligonucleotide expression microarrays have
permitted simultaneous evaluation of virtually all expressed
genes in a single analysis. This technology has not yet found its
way to broad clinical application but several important observations
regarding lung tumors in general and squamous carcinoma
in particular have been made utilizing this technology. First,
microarray profiles strongly correlate with histology and clinical
samples of squamous carcinoma can be distinguished from
adenocarcinoma with a high degree of statistical certainty. 56,96,97
Second, microarray data is reproducible 98 and much of the variation
in the reported literature can be attributed to differences
in data interpretation that may be a complex exercise. Third,
individual biomarkers are discoverable through application of
microarrays and some of these markers may have clinical application.
MAGE genes stand out in microarray experiments as some
of the most highly overexpressed genes in central airway tumors
including squamous carcinomas 99 providing a target for ongoing
immunotherapy trials. 100,101 Fourth, it is possible to identify
prognostically important subsets of genes 102 that may predict response
chemotherapeutic intervention 103–105 or response to targeted
agents. 106 Whether gene expression profiles can be used to
prospectively select appropriate therapy for individual patients is
an important and to date unanswered question.
Additional high-throughput technologies are currently
under investigation including proteomics 107 and rapid largescale
gene sequencing that will permit identification of all mutations
within individual tumors (see succeeding discussion of
adenocarcinoma). These technologies potentially could reach
a level accuracy that will compel their use in the clinical management
of squamous and other non–small cell carcinomas.
However, they require accessing larger amounts of tumor for
clinical study and changes in the way tissue is processed. These
requirements could transform surgical tissue acquisition and
pathology practices but will need careful validation and cost/
benefit analysis before transfer from bench to bedside.