New method identifies genes that can predict prognoses of cancer patients

January 25, 2013

In recent years, it has been thought that select sets of genes might reveal cancer patients' prognoses. However, a study published last year examining breast cancer cases found that most of these "prognostic signatures" were no more accurate than random gene sets in determining cancer prognoses. While many saw this as a disappointment, investigators at Beth Israel Deaconess Medical Center (BIDMC), the Dana-Farber Cancer Institute, and the Institut de Recherches Cliniques de Montréal (IRCM) saw this as an opportunity to design a new method to identify gene sets that could yield more significant prognostic value.

Led by Andrew Beck, MD, Director of the Molecular Epidemiology Research Laboratory at BIDMC, the team has developed SAPS (Significance Analysis of Prognostic Signatures), a new algorithm that makes use of three specific criteria to more accurately identify prognostic signatures associated with patient survival.

Their results, the largest analysis of its kind ever performed, are reported in the January 24 on-line issue of the journal .

"SAPS makes use of three specific criteria," explains Beck, who is also an Assistant Professor of Pathology at Harvard Medical School. "First, the gene set must be enriched for that are associated with survival. In addition, the gene set must separate patients into groups that show survival differences. Lastly, it must also perform significantly better than sets of random genes at these tasks."

In the new study, the scientific team applied the SAPS algorithm to data from the study's senior author Benjamin Haibe-Kains, PhD, Director of the Bioinformatics and Computational Genomics Laboratory at IRCM and an Assistant Research Professor at the University of Montreal. The first collection of data was obtained from 19 published studies (including approximately 3800 patients), and the second included 12 published gene expression profiling studies in ovarian (including data from approximately 1700 patients).

When the investigators used SAPS to analyze these previously identified prognostic signatures in breast and ovarian cancer, they found that only a small subset of the signatures that were considered statistically significant by standard measurements also achieved statistical significance when evaluated by SAPS.

"Our work shows that when using prognostic associations to identify biological signatures that drive cancer progression, it is important to not rely solely on a gene set's association with patient survival," says Beck. "A gene set may appear to be important based on its survival association, when in reality it does not perform significantly better than random genes. This can be a serious problem, as it can lead to false conclusions regarding the biological and clinical significance of a gene set."

By using SAPS, Beck and his colleagues found that they could overcome this problem. "The SAPS procedure ensures that a significant prognostic gene set is not only associated with patient survival but also performs significantly better than random gene sets," says Beck. His team revealed new prognostic signatures in subtypes of breast cancer and ovarian cancer and demonstrated a striking similarity between signatures in estrogen receptor negative breast cancer and ovarian cancer, suggesting new shared therapeutic targets for these aggressive malignancies.

The findings also indicate that the prognostic signatures identified with SAPS will not only help predict patient outcomes but might also help in the development of new anti-cancer drugs. "We hope that markers identified in our analysis will provide new insights into the biological pathways driving cancer progression in breast and subtypes, and will one day lead to improvements in targeted diagnostics and therapeutics," says Beck. "We also hope the method proves widely useful to other researchers." To that end, the team would like to create a web-accessible tool to enable investigators with little knowledge of statistical software and programming to identify significantly associated with patient outcomes in different diseases.

"We also plan to soon release a software package, which includes all the code and corresponding documentation of our analysis pipeline," adds Haibe-Kains. "This will allow others to fully reproduce our results while enabling the bioinformatics and computational biology communities to take over and potentially adapt and improve our pipeline to address important new issues in biomedicine."

Beck and his collaborators are currently working to further validate the prognostic signatures they identified in breast and ovarian cancers, with the hopes of bringing them closer to the clinic through the development of new diagnostics and treatments. "We are also extending our approach to other common cancers that lack robust prognostic signatures," he notes.

Explore further: Researchers identify genes that may help in ovarian cancer diagnosis and prognosis

Related Stories

Researchers identify genes that may help in ovarian cancer diagnosis and prognosis

April 9, 2012
Scientists from Duke University Medical Center have determined that genes acting as molecular "on/off" switches can define clinically relevant molecular subtypes of ovarian cancer, providing ideal potential targets for use ...

Scientists identify genetic signatures for aggressive form of prostate cancer

October 8, 2012
Scientists have discovered two separate genetic 'signatures' for prostate cancer that appear to be able to predict the severity of the disease, leading to hopes that in future, accuracy of prognosis and treatment of the disease ...

Genetic predictor of breast cancer response to chemotherapy

May 10, 2012
Chemotherapy is a major first line defense against breast cancer. However a patient's response is often variable and unpredictable. A study published in BioMed Central's open access journal BMC Medical Genomics shows that ...

Researchers find malignancy-risk gene signature for early-stage non-small cell lung cancer

January 6, 2012
A malignancy-risk gene signature developed for breast cancer has been found to have predictive and prognostic value for patients with early stage non-small cell lung cancer. The advancement was made by researchers at Moffitt ...

Recommended for you

Genome analysis with near-complete privacy possible, say researchers

August 17, 2017
It is now possible to scour complete human genomes for the presence of disease-associated genes without revealing any genetic information not directly associated with the inquiry, say Stanford University researchers.

Science Says: DNA test results may not change health habits

August 17, 2017
If you learned your DNA made you more susceptible to getting a disease, wouldn't you work to stay healthy?

Genetic variants found to play key role in human immune system

August 16, 2017
It is widely recognized that people respond differently to infections. This can partially be explained by genetics, shows a new study published today in Nature Communications by an international collaboration of researchers ...

Phenotype varies for presumed pathogenic variants in KCNB1

August 16, 2017
(HealthDay)—De novo KCNB1 missense and loss-of-function variants are associated with neurodevelopmental disorders, with or without seizures, according to a study published online Aug. 14 in JAMA Neurology.

Active non-coding DNA might help pinpoint genetic risk for psychiatric disorders

August 16, 2017
Northwestern Medicine scientists have demonstrated a new method of analyzing non-coding regions of DNA in neurons, which may help to pinpoint which genetic variants are most important to the development of schizophrenia and ...

Evolved masculine and feminine behaviors can be inherited from social environment

August 15, 2017
The different ways men and women behave, passed down from generation to generation, can be inherited from our social environment - not just from genes, experts have suggested.

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.