Plos: Normally, the cells in human tissues and organs only reproduce (a
process called cell division) when new cells are needed for growth or to
repair damaged tissues. But sometimes a cell somewhere in the body
acquires a genetic change (mutation) that disrupts the control of cell
division and allows the cell to grow continuously. As the mutated cell
grows and divides, it accumulates additional mutations that allow it to
grow even faster and eventually from a lump, or tumor (cancer).
Other
mutations subsequently allow the tumor to spread around the body
(metastasize) and destroy healthy tissues. Tumors can arise anywhere in
the body—there are more than 200 different types of cancer—and about one
in three people will develop some form of cancer during their lifetime.
Many cancers can now be successfully treated, however, and people often
survive for years after a diagnosis of cancer before, eventually, dying
from another disease.
Why Was This Study Done?
The
gradual acquisition of mutations by tumor cells leads to the formation
of subpopulations of cells, each carrying a different set of mutations.
This “intra-tumor heterogeneity” can produce tumor subclones that grow
particularly quickly, that metastasize aggressively, or that are
resistant to cancer treatments. Consequently, researchers have
hypothesized that high intra-tumor heterogeneity leads to worse clinical
outcomes and have suggested that a simple measure of this heterogeneity
would be a useful addition to the cancer staging system currently used
by clinicians for predicting the likely outcome (prognosis) of patients
with cancer. Here, the researchers investigate whether a measure of
intra-tumor heterogeneity called “mutant-allele tumor heterogeneity”
(MATH) is related to mortality (death) among patients with head and neck
squamous cell carcinoma (HNSCC)—cancers that begin in the cells that
line the moist surfaces inside the head and neck, such as cancers of the
mouth and the larynx (voice box). MATH is based on whole-exome
sequencing (WES) of tumor and matched normal DNA. WES uses powerful
DNA-sequencing systems to determine the variations of all the coding
regions (exons) of the known genes in the human genome (genetic
blueprint).
What Did the Researchers Do and Find?
The
researchers obtained clinical and WES data for 305 patients who were
treated in 14 institutions, primarily in the US, after diagnosis of
HNSCC from The Cancer Genome Atlas, a catalog established by the US
National Institutes of Health to map the key genomic changes in major
types and subtypes of cancer. They calculated tumor MATH values for the
patients from their WES results and retrospectively analyzed whether
there was an association between the MATH values and patient survival.
Despite the patients having tumors at various subsites and being given
different treatments, every 10% increase in MATH value corresponded to
an 8.8% increased risk (hazard) of death. Using a previously defined
MATH-value cutoff to distinguish high- from low-heterogeneity tumors,
compared to patients with low-heterogeneity tumors, patients with
high-heterogeneity tumors were more than twice as likely to die (a
hazard ratio of 2.2). Other statistical analyses indicated that MATH
provided improved prognostic information compared to that provided by
established clinical and molecular characteristics and human
papillomavirus (HPV) status (HPV-positive HNSCC at some subsites has a
better prognosis than HPV-negative HNSCC). In particular, MATH provided
prognostic information beyond that provided by standard disease staging
among patients with mouth or laryngeal cancers.
What Do These Findings Mean?
By
using data from more than 300 patients treated at multiple
institutions, these findings validate the use of MATH as a measure of
intra-tumor heterogeneity in HNSCC. Moreover, they provide one of the
first large-scale demonstrations that intra-tumor heterogeneity is
clinically important in the prognosis of any type of cancer. Before the
MATH metric can be used in clinical trials or in clinical practice as a
prognostic tool, its ability to predict outcomes needs to be tested in
prospective studies that examine the relation between MATH and the
outcomes of patients with identically treated HNSCC at specific head and
neck subsites, that evaluate the use of MATH for prognostication in
other tumor types, and that determine the influence of cancer treatments
on MATH values. Nevertheless, these findings suggest that MATH should
be considered as a biomarker for survival in HNSCC and other tumor
types, and raise the possibility that clinicians could use MATH values
to decide on the best treatment for individual patients and to choose
patients for inclusion in clinical trials.