Impact of Tumor Progression on Cancer Incidence Curves.

Publication Type:

Journal Article

Source:

Cancer research (2012)

Keywords:

October 2012, Public Health Sciences Division

Abstract:

Cancer arises through a multistage process, but it is not fully clear how this process influences the age-specific incidence curve. Studies of colorectal and pancreatic cancer using the multistage-clonal-expansion (MSCE) model have identified two phases of the incidence curves. One phase is linear beginning about age of 60, suggesting that at least two rare rate-limiting mutations occur prior to clonal expansion of premalignant cells. A second phase is exponential, seen in earlier-onset cancers occurring before the age of 60 that are associated with premalignant clonal expansion. Here we extend the MSCE model to include clonal expansion of malignant cells, an advance that permits study of the effects of tumor growth and extinction on the incidence of colorectal, gastric, pancreatic and esophageal adenocarcinomas in the digestive tract. After adjusting the age-specific incidence for birth-cohort and calendar-year trends, we found that initiating mutations and premalignant cell kinetics can explain the primary features of the incidence curve. However, we also found that the incidence data of these cancers harbored information on the kinetics of malignant clonal expansion prior to clinical detection, including tumor growth rates and extinction probabilities on three characteristic time scales for tumor progression. Additionally, the data harbored information on the mean sojourn times for premalignant clones until occurrence of either the first malignant cell or the first persistent (surviving) malignant clone. Lastly, the data also harbored information on the mean sojourn time of persistent malignant clones to the time of diagnosis. In conclusion, cancer incidence curves can harbor significant information about hidden processes of tumor initiation, premalignant clonal expansion and malignant transformation, and even some limited information on tumor growth before clinical detection.