MicroRNA study opens potential revolution in cancer diagnosis

Collaborative effort develops novel tool and discovers surprising correlation of microRNA expression and cancer type

Despite significant progress in understanding the genetic changes in many different cancers, diagnosis and classification of tumor type remain, at best, an imperfect art. This could change quickly, thanks to the findings of a group of researchers from the Broad Institute of MIT and Harvard, the Dana-Farber Cancer Institute, MIT, and St. Jude’s Children’s Research Hospital in Memphis, TN.

In the June 9 issue of Nature, the scientists describe two important breakthroughs: (1) a surprisingly accurate correlation of the 217 known human microRNAs (miRNAs – small noncoding RNA molecules that control the levels of proteins made from transcribed genes) with the development and differentation of tumors, and (2) the development of a technology that not only enabled this exciting discovery but that could be the basis for an easy and inexpensive diagnostic test.

“This study opened our eyes to how much more there is to learn about genomic approaches to cancer,” said Todd Golub, senior author of the paper. Golub is a core faculty member and director of the Cancer Program at Broad Institute, the Charles A. Dana Investigator in Human Cancer Genetics at the Dana-Farber Cancer Institute, and a Howard Hughes Medical Institute (HHMI) investigator at Harvard Medical School. “That microRNA profiles have such potential diagnostic utility was a big surprise to us, and one we’re keen to validate in future studies.”

MiRNAs were first identified in the worm C. elegans, and were shown to control development and differentiation of cells: When absent, certain cells went into abnormal rounds of cell division rather than differentiations. “Since the discovery that microRNAs control specific cell divisions in the nematode C. elegans, I have wondered if there might be a relationship between microRNAs and human cancer,” said H. Robert Horvitz, co-author and David H. Koch Professor of Biology at MIT and HHMI investigator at Harvard. “This work establishes a striking correlation between patterns of microRNA expression and cancer and offers the prospect of using microRNA expression patterns to help in the diagnosis and treatment of cancer.”

To determine the expression pattern of all the known human miRNAs, the researchers first had to develop an accurate, fast, reproducible and inexpensive method for doing so. Given the small size of miRNA (~21 nucleotides) as well as their close resemblance to each other, previous attempts to use array-type technologies have been unsuccessful. Instead, the scientists developed an ingenious bead-based miRNA capture method, where each individual bead was marked with fluorescence “tags” that could tell which miRNA was bound as well as its abundance in the sample.

Testing a host of tumor samples on the miRNA-specific beads revealed that the expression patterns of miRNA not only correlated with the developmental origins of the tumors samples (e.g., epithelial cell, hematopoietic cell, etc.), but it also subdivided specific tumor types based on known genetic alterations. They also found that miRNA levels are generally lower across tumor types than in the corresponding normal tissue, again supporting the idea that miRNA is critical to reaching and maintaining the differentiated state.

Finally, the researchers tested their discoveries against a panel of tumor samples of histologically uncertain cellular origin (but which had been determined by the anatomical location). Again, the miRNA classification provided amazing accuracy, especially compared techniques relying on messenger RNA (mRNA) expression patterns.

Although this is a preliminary study, its validation could have significant impact on the clinical diagnosis of cancer.

In addition to Golub and Horvitz, authors on the Nature paper “MicroRNA expression profiles classify human cancers” include Gad Getz, Justin Lamb and David Peck from the Broad Institute; Benjamin L. Ebert, Jun Lu and Raymond H. Mak from the Broad Institute and Dana-Farber Cancer Institute, Alejandro Sweet-Cordero from the Broad Institute and the MIT Center for Cancer Research; Eric A. Miska and Ezequiel Alvarez-Saavedra from the Howard Hughes Medical Institute at the Department of Biology at MIT; Tyler Jacks from MIT Center for Cancer Research and the Howard Hughes Medical Institute at the Department of Biology of MIT; Adolfo A. Ferrando from the Dana-Farber Cancer Institute, and; James R. Downing from St. Jude Children’s Research Hospital, Memphis, TN.

Jun Lu, Gad Getz and Eric Miska are listed as co-first authors on the Nature paper.