Questions About Cancer? 1-800-4-CANCER
  • Posted: 09/27/2013
NCI Perspective

The benefits of looking across many cancer genomes

Cancer is not a single entity, but rather, it is more than one hundred complex and distinct diseases, with most cancer types demanding a unique treatment strategy. This understanding led, in part, to the launch of The Cancer Genome Atlas (TCGA), a joint venture supported by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), both part of NIH.

From the outset, TCGA has been generating and analyzing data according to the organ in the body from which a tumor first arose. To date, the TCGA Research Network has published eight papers, including three this year on acute myeloid leukemia, endometrial cancer and clear cell kidney cancer, each a comprehensive characterization of a type of cancer. The organ-specific findings have frequently been revealing, providing new information on cancer development and behavior, as well as new insights into molecular pathways and genetic alterations. Just as importantly, in many cases, researchers have uncovered shared molecular patterns among cancers, including similar genomic changes occurring across tumor types. For example, TCGA’s 2012 breast cancer analysis found evidence that a subtype of breast cancer shows marked similarity to a form of ovarian cancer. The subtype, Basal-like breast cancer, and high-grade serous ovarian cancer shared similar mutation characteristics as well as other genomic features, suggesting that the two cancers are of a similar molecular origin and may be susceptible to the same treatments. In fact, Basal-like breast cancer has more similarities, genomically speaking, to high-grade serous ovarian cancer than to other subtypes of breast cancer.

Line graph with parabolic line and shading beneath it showing long tail on far right of graph with long tail region shaded in yellow and higher frequencies on right shaded in light green
Long tail diagram depicts the individual mutations, ordered by number of occurrences on the x-axis and number of mutations (frequency) on the y-axis.

In addition, data from TCGA’s analyses show that most cancer types possess a great number of mutations that occur at a low frequency. The collection of mutations has been termed the “long tail” because in a graph of the frequency of specific changes, they represent a lengthy but low section of the chart. The long tail and the shared inter-tumor molecular patterns are the first suggestions that a cross tumor analysis may yield clinically meaningful new findings. Researchers found that, across samples from hundreds of patients, tumors from different organs could be similar, while cancer samples from the same organ could be noticeably different.

With such similarities increasingly apparent, TCGA researchers developed a formal project for a cross tumor analysis, called Pan-Cancer. Its goal was to assemble TCGA’s wealth of data across tumor types, analyze and interpret those data, and finally, make both the analyses and the data freely available. The group, led by Josh Stuart, Ph.D., University of California Santa Cruz, decided to analyze 12 cancer types based upon numbers of samples and comprehensiveness of the data.  The 12 types were glioblastoma multiforme, acute myeloid leukemia, lung squamous cell carcinoma, lung adenocarcinoma, colon and rectal adenocarcinomas, head and neck squamous cell carcinoma and ovarian, breast, clear cell kidney, endometrial and bladder cancers. Because of the breadth and depth of TCGA data, the Pan-Cancer group believed the analysis would have great statistical power to detect genomic changes across the cancers, and find changes specific to each organ-of-origin as well as molecular commonalities across tumor types.

The culmination of this effort will be a series of manuscripts tied together through “threads” featured on the website of Nature (see http://www.nature.com/tcga ), similar to what was done for an array of papers resulting from the similarly expansive project, the Encyclopedia of DNA Elements (ENCODE). The Pan-Cancer threads will cover five topics and each thread will be centered on a specific theme and comprises relevant information across papers and journals.  Stuart said, “Each cross-cutting piece will offer perspectives on a topic discussed in several papers. This is a new exciting way to organize information to help bring out themes that unite the work.”

The Pan-Cancer group expects that this batch of papers represents just the first of several iterations of analysis. As TCGA collects and analyzes more samples, researchers will be better able to detect rare mutations that may apply to numerous tumor types.

This new perspective of analyzing cancers according to their genomic profiles may signal a shift from organizing cancer by organ of origin.  Many clinicians are beginning to imagine a future where cancers are described by their mutations, such as an ERBB2 amplified tumor or a PI3K-pathway mutant carcinoma. As Stuart wrote in the Nature Genetics  perspective article which accompanied two of the group of Pan-Cancer research papers, “Only time will tell whether the integration of molecular characteristics with data on histology, organ site and metastatic location will contribute to an improvement in patient outcomes. But the balance is shifting in this direction.”

Two research papers published in Nature Genetics as part of the first round of Pan-Cancer papers also point to the growing focus on profiling tumors. In one paper, researchers at Memorial Sloan-Kettering Cancer Center, New York, analyzed data on more than 3,000 tumor samples from 12 cancer types from TCGA, and determined that a limited number of genetic alterations are responsible for most cancer subtypes. These alterations, no matter what tissue they originated in, fall into two general categories of “oncogenic” signatures: genetic mutations and copy number changes, with many smaller subclasses.   The scientists hope that these results will eventually help to tailor treatment strategies to subsets of patients, resulting in clinical trials based on matching individual patients whose tumors have been profiled – and oncogenic signatures identified and classified – with a corresponding drug or combination of therapies. 

The second study, also appearing in Nature Genetics, examined patterns of changes in the number of gene copies in cells, one of the most common types of mutations that lead to cancer.  Investigators at The Broad Institute, Cambridge, Mass., and Dana-Farber Cancer Institute, Boston, compiled a database of gene copy number changes across genes in 5,000 tumors and 12 cancer types. They used this database to identify 140 regions where these mutations tend to occur most often, pointing to genes in these regions that are likely to contribute to cancer formation. The scientists showed that the patterns of mutations can provide clues as to how these genes contribute to cancer.  These findings clarify how cancers develop and identify genes that are particularly important in cancer initiation, and which may serve as effective therapeutic targets.

A grid of blue and red rectangles, with Pan-Cancer integrated subtypes with high scores depicted in red, indicating over-activity, while low scores are depicted in blue, indicating lower activity compared to normal, and with lines interconnecting commonalities
Representation of integrated tissue subtypes (e.g., a BRCA breast gene subtype is depicted in the third row from the bottom) compared to various pathways, depicted vertically ; scores are for the Pan-Cancer integrated subtypes with high scores (red) indicating over-activity while low scores (blue) indicating lower activity compared to normal.

The Pan-Cancer project also brings up a number of directions for the future of cross-tumor analysis, several of which are highlighted in Stuart’s commentary article.  These may include integrating data sources to increase the power of genomic analyses, using molecular profiles to categorize cancers for making treatment decisions , figuring out if “predictive signatures” derived from genes transcend tissue types, and whether or not comprehensive protein analyses using tools such as mass spectrometry can extend the power of  genomic analyses from TCGA.

Most importantly, the answers to many of these questions should help in the design of novel therapies and clinical trials, with the ultimate goal of improving patient care. The dozens of articles expected to comprise the Pan-Cancer research effort in the near future may be key to these answers.