NCI Scientists Create Model That Predicts Follicular Lymphoma Survival
Scientists at the National Cancer Institute (NCI), part of the
National Institutes of Health, have created a model that predicts
the survival of follicular lymphoma patients based on the molecular
characteristics of their tumors at diagnosis. The model is based
on two sets of genes called survival-associated signatures
whose activity was found to be associated with good or poor
prognosis for patients with the cancer. The scientists' results,
to be published in the November 19, 2004, New England Journal
of Medicine *, suggest that immune
cells infiltrating follicular lymphoma tumors have an important
impact on survival both signatures came from such immune
The progression rate of follicular lymphoma, the most common non-Hodgkin
lymphoma, varies widely. "In some patients the disease progresses
slowly over many years, whereas in others progression is rapid,
with the cancer transforming into aggressive lymphoma and leading
to early death," explained principle investigator Louis M.
Staudt, M.D., Ph.D., of NCI's Center for Cancer Research. "Understanding
the molecular causes of such differences in survival could provide
a more accurate method to determine patient risk, which could be
used to guide treatment and may suggest new therapeutic approaches."
To create their model, Staudt and associates used follicular lymphoma
biopsies taken from 191 untreated patients. The biopsies were taken
between 1974 and 2001 and came from North American and European
institutions that are part of the NCI-sponsored Lymphoma/Leukemia
Molecular Profiling Project **.
Following their biopsies, all patients received standard treatments.
The NCI scientists examined their subsequent medical records to
determine survival. Biopsies were divided into two groups balanced
for survival and institution: 95 went into a group used to uncover
gene expression patterns associated with survival; the other 95
were used to test the predictive power of these patterns.
NCI scientists first used a DNA micro array to determine which genes
were expressed (active) in the first group of 95 tumor biopsies,
and at what levels. They then determined which of these genes were
statistically associated with survival. They called those associated
with long survival "good prognosis genes" and those associated
with short survival "poor prognosis genes."
Next, the researchers identified subsets of both kinds of genes
that tended to be expressed together. These they named "survival-associated
signatures." Two signatures one which indicated poor prognosis,
the other good had strong synergy and together predicted survival
better than any other model tested. Unexpectedly, both came from
nonmalignant immune cells infiltrating the tumors. The good prognosis
signature genes reflect a mixture of immune cells that is dominated
by T cells. T cells react to specific threats to the body's health.
In contrast, the poor prognosis signature genes reflect a different
group of immune cells dominated by macrophages and/or dendritic
cells which react to nonspecific threats rather than T cells.
The two signature model allowed NCI scientists to divide patients
into four equal groups with disparate average survival rates of
3.9, 10.8, 11.1, and 13.6 years. For the 75 percent of patients
with survival rates 10 years or longer, "watchful waiting is
appropriate," Staudt said. "These patients would benefit
from knowing that they may not need treatment for quite some time.
On the other hand, those patients in the group with the lowest survival
rate should be considered for newer treatments and clinical trials,"
The fact that the most predictive signatures came from immune cells
suggests an important interplay between the host immune system and
malignant cells in follicular lymphoma. "One possibility is
that the immune cells with the good-prognosis signature are attacking
the lymphoma and keeping it in check," Staudt speculated. "Another
possibility is that these immune cells may provide signals that
encourage the cancer cells not to leave the lymph node, preventing
or delaying the spread of the cancer," he added. Knowing more
about the signals that may delay the spread of follicular lymphoma
could provide new therapeutic targets.
For more information about cancer, please visit the NCI Web
site at http://www.cancer.gov
or call NCI's Cancer Information Service at 1-800-4-CANCER (1-800-422-6237).
* Dave SS, Wright G, et al. A Molecular
Predictor of Survival Following Diagnosis of Follicular Lymphoma Based
on the Profile of Non-Malignant Tumor-Infiltrating Immune Cells. New
England Journal of Medicine. November 18, 2004.
** Participating institutions in the
Lymphoma/Leukemia Molecular Profiling Project include: Center for
Cancer Research, National Cancer Institute, USA; University of Nebraska
Medical Center, USA; Southwest Oncology Group, USA; British Columbia
Cancer Agency, Canada; Norwegian Radium Hospital, Norway; University
of Wuerzburg, Germany; University of Barcelona, Spain; and St. Bartholomew's