摘要
Understanding tumor diversity has been a long-lasting and challenging question for researchers in the field of cancer heterogeneity or tumor evolution. Studies have reported that com- pared to normal cells, there is a higher genetic diversity in tumor cells, while higher genetic diversity is associated with higher progression risks of tumor. We thus hypothesized that tumor diversity also holds true at the gene expression level. To test this hypothesis, we used t-test to compare the means of Simpson＇s diversity index for gene expression （SDIG） between tumor and non-tumor samples. We found that the mean SDIG in tumor tissues is significantly higher than that in the non-tumor or normal tissues （P 〈 0.05） for most datasets. We also combined microarrays and next-generation sequencing data for validation. This cross-platform and cross-experimental validation greatly increased the reliability of our results.
Understanding tumor diversity has been a long-lasting and challenging question for researchers in the field of cancer heterogeneity or tumor evolution. Studies have reported that com- pared to normal cells, there is a higher genetic diversity in tumor cells, while higher genetic diversity is associated with higher progression risks of tumor. We thus hypothesized that tumor diversity also holds true at the gene expression level. To test this hypothesis, we used t-test to compare the means of Simpson＇s diversity index for gene expression （SDIG） between tumor and non-tumor samples. We found that the mean SDIG in tumor tissues is significantly higher than that in the non-tumor or normal tissues （P 〈 0.05） for most datasets. We also combined microarrays and next-generation sequencing data for validation. This cross-platform and cross-experimental validation greatly increased the reliability of our results.
基金
supported by University of California, Los Angeles
University of North Texas Health Science Center of the United States
