Genetically Guided Treatment For Cancer

Two critical characteristics of breast cancer that are important to treatment can be identified by measuring gene expression in the tumor, a research team led by scientists at The University of Texas M. D. Anderson Cancer Center reports in Lancet Oncology online.

Researchers developed and validated a new genomic microarray test that identifies whether a tumor’s growth is fueled by the female hormone estrogen and the role of a growth factor receptor known as HER-2 that makes a tumor vulnerable to a specific drug.

“This is one important step towards personalized diagnosis and treatment planning based on an integrated genomic test of an individual tumor,” said senior author W. Fraser Symmans, M.D., associate professor in the M. D. Anderson Department of Pathology.

The Lancet Oncology paper results are the latest in an effort by the research team to develop a single test to quickly and efficiently determine the characteristics and vulnerabilities of a patient’s breast cancer and ultimately to guide treatment.

About 70 percent of breast cancers are estrogen-receptor positive and another 15 to 25 percent are human epidermal growth factor receptor-2 (HER-2) positive. Each receptor status requires different types of treatment.

“This moves us closer to developing an integrated single genomic test that could estimate the risk of cancer relapse after surgery, determine the ER and HER2 receptor status, and also gauge the sensitivity of the tumor to hormone therapy and chemotherapy,” says Lajos Pusztai, M.D., Ph.D., associate professor in the M. D. Anderson Department of Breast Medical Oncology, and team leader with Symmans.

Last fall, the group published a study showing that a genomic microarray test can also predict a patient’s response to chemotherapy. They also presented a paper in December showing that another genomic index predicts how an ER-positive patient will respond to hormonal therapy.

The study was funded by the National Cancer Institute, the Breast Cancer Research Foundation and the Goodwin Foundation.

Co-authors with Symmans and Pusztai are: first author Yun Gong, M.D., and Nour Sneige, M.D., of the M. D. Anderson Department of Pathology; Kai Yan, Keith Anderson, and Kenneth Hess, of the M. D. Anderson Department of Biostatistics; Feng Lin, M.D., Vicente Valero, M.D., Daniel Booser, M.D., Jaime Mejia, M.D., and Gabriel Hortobagyi, M.D., of the M. D. Anderson Department of Breast Medical Oncology; Christos Sotiriou, M.D., Ph.D., Institut Jules Bordet, Brussels, Belgium; Fabrice Andre, M.D., of Institut Gustave Roussy, Villejuif, France; Frankie Holmes, M.D., John Pippen Jr., M.D., and Svetislava Vukelja, M.D., of U.S. Oncology-Texas Oncology; Henry Gomez, M.D., of the Instituto Nacional de Enfermedades Neoplasicas, Lima, Peru; and Luis Barajas, M.D., Departmento de Ginecologia Oncologica, Instituto Mexicano del Seguro Social, Guadalajara, Mexico.

Contact: Scott Merville
University of Texas M. D. Anderson Cancer Center

The Insider -Code inside Codes : Scientists Discover Parallel Codes in Genes

Researchers from The Weizmann Institute of Science report the discovery of two new properties of the genetic code. Their work, which appears online in Genome Research, shows that the genetic code—used by organisms as diverse as reef coral, termites, and humans—is nearly optimal for encoding signals of any length in parallel to sequences that code for proteins. In addition, they report that the genetic code is organized so efficiently that when the cellular machinery misses a beat during protein synthesis, the process is promptly halted before energy and resources are wasted.

DNA sequences that code for proteins need to convey, in addition to the protein-coding information, several different signals at the same time. These “parallel codes” include binding sequences for regulatory and structural proteins, signals for splicing, and RNA secondary structure. Here, we show that the universal genetic code can efficiently carry arbitrary parallel codes much better than the vast majority of other possible genetic codes. This property is related to the identity of the stop codons. We find that the ability to support parallel codes is strongly tied to another useful property of the genetic code—minimization of the effects of frame-shift translation errors. Whereas many of the known regulatory codes reside in nontranslated regions of the genome, the present findings suggest that protein-coding regions can readily carry abundant additional information.

“Our findings open the possibility that genes can carry additional, currently unknown codes,” explains Dr. Uri Alon, principal investigator on the project. “These findings point at possible selection forces that may have shaped the universal genetic code.”

The genetic code consists of 61 codons—tri-nucleotide sequences of DNA—that encode 20 amino acids, the building blocks of proteins. In addition, three codons signal the cellular machinery to stop protein synthesis after a full-length protein is built.

While the best-known function of genes is to code for proteins, the DNA sequences of genes also harbor signals for folding, organization, regulation, and splicing. These DNA sequences are typically a bit longer: from four to 150 or more nucleotides in length.

 

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