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The number of key carcinogenic events can be predicted from cancer incidence.

ABSTRACT: The widely accepted multiple-hit hypothesis of carcinogenesis states that cancers arise after several successive events. However, no consensus has been reached on the quantity and nature of these events, although "driver" mutations or epimutations are considered the most probable candidates. By using the largest publicly available cancer incidence statistics (20 million cases), I show that incidence of 20 most prevalent cancer types in relation to patients' age closely follows the Erlang probability distribution (R2?=?0.9734-0.9999). The Erlang distribution describes the probability y of k independent random events occurring by the time x, but not earlier or later, with events happening on average every b time intervals. This fits well with the multiple-hit hypothesis and potentially allows to predict the number k of key carcinogenic events and the average time interval b between them, for each cancer type. Moreover, the amplitude parameter A likely predicts the maximal populational susceptibility to a given type of cancer. These parameters are estimated for 20 most common cancer types and provide numerical reference points for experimental research on cancer development.

SUBMITTER: Belikov AV

PROVIDER: S-EPMC5610194 | biostudies-other | 2017 Sep

REPOSITORIES: biostudies-other

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The number of key carcinogenic events can be predicted from cancer incidence.

Belikov Aleksey V AV

Scientific reports 20170922 1

The widely accepted multiple-hit hypothesis of carcinogenesis states that cancers arise after several successive events. However, no consensus has been reached on the quantity and nature of these events, although "driver" mutations or epimutations are considered the most probable candidates. By using the largest publicly available cancer incidence statistics (20 million cases), I show that incidence of 20 most prevalent cancer types in relation to patients' age closely follows the Erlang probabi ...[more]

PMID: 28939880

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Project description:Background: Prostate cancer (PCa) is occurred with increasing incidence and heterogeneous pathogenesis. Although clinical strategies are accumulated for PCa prevention, there is still a lack of sensitive biomarkers for the holistic management in PCa occurrence and progression. Based on systems biology and artificial intelligence, translational informatics provides new perspectives for PCa biomarker prioritization and carcinogenic survey. Methods: In this study, gene expression and miRNA-mRNA association data were integrated to construct conditional networks specific to PCa occurrence and progression, respectively. Based on network modeling, hub miRNAs with significantly strong single-line regulatory power were topologically identified and those shared by the condition-specific network systems were chosen as candidate biomarkers for computational validation and functional enrichment analysis. Results: Nine miRNAs, i.e., hsa-miR-1-3p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-182-5p, hsa-miR-198, hsa-miR-22-3p, hsa-miR-24-3p, hsa-miR-34a-5p, and hsa-miR-499a-5p, were prioritized as key players for PCa management. Most of these miRNAs achieved high AUC values (AUC > 0.70) in differentiating different prostate samples. Among them, seven of the miRNAs have been previously reported as PCa biomarkers, which indicated the performance of the proposed model. The remaining hsa-miR-22-3p and hsa-miR-499a-5p could serve as novel candidates for PCa predicting and monitoring. In particular, key miRNA-mRNA regulations were extracted for pathogenetic understanding. Here hsa-miR-145-5p was selected as the case and hsa-miR-145-5p/NDRG2/AR and hsa-miR-145-5p/KLF5/AR axis were found to be putative mechanisms during PCa evolution. In addition, Wnt signaling, prostate cancer, microRNAs in cancer etc. were significantly enriched by the identified miRNAs-mRNAs, demonstrating the functional role of the identified miRNAs in PCa genesis. Conclusion: Biomarker miRNAs together with the associated miRNA-mRNA relations were computationally identified and analyzed for PCa management and carcinogenic deciphering. Further experimental and clinical validations using low-throughput techniques and human samples are expected for future translational studies.

Project description:The incidence of carcinoma increases greatly with aging, but the cellular and molecular mechanisms underlying this correlation are only partly known. It is established that senescent fibroblasts promote the malignant progression of already-transformed cells through secretion of inflammatory mediators. We investigated here whether the senescent fibroblast secretome might have an impact on the very first stages of carcinogenesis. We chose the cultured normal primary human epidermal keratinocyte model, because after these cells reach the senescence plateau, cells with transformed and tumorigenic properties systematically and spontaneously emerge from the plateau. In the presence of medium conditioned by autologous senescent dermal fibroblasts, a higher frequency of post-senescence emergence was observed and the post-senescence emergent cells showed enhanced migratory properties and a more marked epithelial-mesenchymal transition. Using pharmacological inhibitors, siRNAs, and blocking antibodies, we demonstrated that the MMP-1 and MMP-2 matrix metalloproteinases, known to participate in late stages of cancer invasion and metastasis, are responsible for this enhancement of early migratory capacity. We present evidence that MMPs act by activating the protease-activated receptor 1 (PAR-1), whose expression is specifically increased in post-senescence emergent keratinocytes. The physiopathological relevance of these results was tested by analyzing MMP activity and PAR-1 expression in skin sections. Both were higher in skin sections from aged subjects than in ones from young subjects. Altogether, our results suggest that during aging, the dermal and epidermal skin compartments might be activated coordinately for initiation of skin carcinoma, via a paracrine axis in which MMPs secreted by senescent fibroblasts promote very early epithelial-mesenchymal transition of keratinocytes undergoing transformation and oversynthesizing the MMP-activatable receptor PAR-1.

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The number of key carcinogenic events can be predicted from cancer incidence.

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The number of key carcinogenic events can be predicted from cancer incidence.

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