'Data Gone Wrong': Unreproducible Cancer Genomics Studies

June 30, 2011 — Cancer research is increasingly being defined by genomics, and advances in technology have allowed researchers to identify candidate genes as prognostic, diagnostic, and therapeutic biomarkers for different subtypes of tumors. Genomic platforms also allow for the prediction of therapeutic response, and with it the promise of personalized therapy.

Proteomics and genomics have generated quite a bit of excitement in the scientific community because they bring a new level of complexity to the cancer field. However, this emerging field of research has also brought concerns about validation and reproducibility.

Perhaps the most publicized and glaring case of "data gone wrong" involved Anil Potti, MD, an oncologist and genomics researcher who was forced to retract 4 papers from peer-reviewed journals because of results that could not be reproduced. As previously reported by Medscape Medical News, Dr. Potti's saga involved not only concerns about the validity of his research, but allegations of misconduct. He eventually resigned from his positions at the Duke University School of Medicine and the Duke Institute for Genome Science and Policy in Durham, North Carolina.

Dr. Potti's research was directed at developing gene-expression signatures that predict responses to various cytotoxic chemotherapeutic drugs. The goal was to identify characteristics of individual patients that could be matched with specific. His published papers reported that his signatures had the capacity to predict therapeutic response, but the experiments could not be reproduced and the signatures could not be validated.

"One issue that is coming out is that these papers did get past peer review. Does that mean peer review is broken?" asked Keith Baggerly, PhD, professor in the Department of Bioinformatics and Computational Biology at the University of Texas M.D. Anderson Cancer Center in Houston. "No not really, and peer review is still one of the best methods we have," he answered.

"The types of errors that we are talking are not those that peer review would have caught," he told Medscape Medical News. "The type of data analysis required to find those errors is not really feasible in peer review."