Seven HudsonAlpha researchers have analyzed the role of cell proliferation across 19 cancers using tissue-based RNA sequencing data from The Cancer Genome Atlas (TCGA) project. Their results, published April 8 in Oncotarget, provide a comprehensive characterization of tumor proliferation indices and their association with disease progression and prognosis in multiple cancer types.

“We showed – in agreement with the field – that increased cell proliferation was correlated with increased somatic mutation burden,” said Brittany Lasseigne, PhD, one of the lead authors on the paper. “We also showed that the proliferative index was correlated with mutations in individual driver genes, an important area of future study.”

To complete the analysis, the researchers applied an index, or summarized expression of a gene set associated with cell proliferation. They found that this proliferation index was associated with patient survival in seven of the 19 cancers examined, according to lead authors Ryne Ramaker and Lasseigne. The analysis also highlights specific cancers that may be susceptible to targeting of cell proliferation, a classic cancer hallmark, and others in which targeted agents, such as immunotherapy, may be more effective. Most importantly, the study shows the value of accounting for cell proliferation rates when looking for signatures associated with survival across cancers.

In addition to Ramaker and Lasseigne, Andrew Hardigan, Laura Palacio and David Gunther (a former BioTrain intern) contributed to work on the project, which was conducted in the labs of HudsonAlpha faculty investigators Richard Myers, PhD, and Sara Cooper, PhD.

“Many groups have published gene expression signatures associated with patient outcomes. They are variable and not always easy to interpret,” Cooper said. “We have explored one possible explanation or mechanism for those signatures, increased cell proliferation. Future analysis can account for this factor in the cancers where it is most important and allow exploration of other possible factors in those where it does not explain outcome.”

According to Ramaker, this study is part of ongoing research at HudsonAlpha using TCGA data. “This study just scratches the surface of the kinds of questions you can ask about characteristics common to multiple cancer types with the data publicly available in TCGA,” he said. “There are several projects in the works that combine TCGA data with data generated at HudsonAlpha to reach the statistical power necessary to generate findings that weren’t possible before.”

Read the paper online at Oncotarget.

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