Double agents: genes with both oncogenic and tumor-suppressor functions

Abstract

The role of genetic components in cancer development is an area of interest for cancer biologists in general. Intriguingly, some genes have both oncogenic and tumor-suppressor functions. In this study, we systematically identified these genes through database search and text mining. We find that most of them are transcription factors or kinases and exhibit dual biological functions, e.g., that they both positively and negatively regulate transcription in cells. Some cancer types such as leukemia are over-represented by them, whereas some common cancer types such as lung cancer are under-represented by them. Across 12 major cancer types, while their genomic mutation patterns are similar to that of oncogenes, their expression patterns are more similar to that of tumor-suppressor genes. Their expression profile in six human organs propose that they mainly function as tumor suppressor in normal tissue. Our network analyses further show they have higher network degrees than both oncogenes and tumor-suppressor genes and thus tend to be the hub genes in the protein-protein interaction network. Our mutation, expression spectrum, and network analyses might help explain why some cancer types are specifically associated with them. Finally, our results suggest that the functionally altering mutations in "double-agent" genes and oncogenes are the main driving force in cancer development, because non-silent mutations are biasedly distributed toward these two gene sets across all 12 major cancer types.

Fig. 1. GO term enrichment analyses of proto-oncogenes with tumor-suppressor function (POTSFs), oncogenes (ONCs), and tumor-suppressor genes (TSGs).

a GO term enrichment results for POTSFs. b GO term enrichment results for ONCs. c GO term enrichment results for TSGs

Fig. 2. The distribution of the associated cancer type numbers in POSTFs.

TP53 is associated with 34 different cancer types and FAS is associated with 15 different cancer types

Fig. 3. The cancer type information for POTSFs and from 2012's global cancer statisitics.

a The percentages of the cancer types associated with POTSFs. b The percentages of the cancer types reported in 2012’s global cancer statistics. The same cancer type is marked with the same color in (a) and (b); e.g., leukemia is marked with red color in both (a) and (b)

Fig. 4. Expression spectrum of POTSFs in five tissues.

Internal and musoskeletal tissue includes lung, kidney, liver, colon, heart, muscle, etc. Blood and immune tissue includes thymus, bone marrow, peripheral blood, lymph node, etc. Secretory tissue includes skin, prostate, placenta, pancreas, etc. Nervous tissue includes forebrain, retina, cerebellum, etc. Reproductive tissue includes testis and ovary. Please see supplemental data for each POTSF-specific expression information

Fig. 5. The distribution of non-silent mutations in POTSFs, ONCs, TSGs, and NCRGs across 12 cancer types.

The star indicates the statistical difference (P-value < 0.05, Kolmogorov–Smirnov test) between two gene sets. The star is placed on the statistically higher gene set and the color of star indicates the corresponding gene set

Fig. 6. The mutation rates of POTSFs, ONCs, TSGs, and NCRGs across 12 cancer types.

The star indicates the statistical difference (P-value < 0.05, Kolmogorov–Smirnov test) between two gene sets. The star is placed on the statistically higher gene set and the color of star indicates the corresponding gene set

Fig. 7. The distribution of the RNA-Seq expression values of POTSFs, ONCs, TSGs, and NCRGs across 12 cancer types.

The star indicates the statistical difference (P-value < 0.05, Kolmogorov–Smirnov test) between two gene sets. The star is placed on the statistically higher gene set and the color of star indicates the corresponding gene set

Fig. 8. The distribution of the RNA-Seq expression values of POTSFs, ONCs, TSGs, and NCRGs in six normal human organs.

The star indicates the statistical difference (P-value < 0.05, Kolmogorov–Smirnov test) between two gene sets. The star is placed on the statistically higher gene set and the color of star indicates the corresponding gene set

Fig. 9. The network property and evolutionary pressure analyses for POTSFs, ONCs, TSGs, and NCRGs.

a The network degrees of four gene sets. b The clustering coefficients of four gene sets. c The d_N/d_S values of four gene sets

Fig. 10. The protein-protein interaction network graph for POTSFs and its most interconnected module.

a Protein–protein interaction network of POTSFs, ONCs, TSGs, and NCRGs. b The most interconnected region of the network. POTSFs are represented by red color. ONCs are represented by yellow color. TSGs are represented by green color. NCRGs are represented by blue color