Relationship between the oncogene activation profiles and the tumor suppressor gene inactivation profiles in 19 human neoplasias - a regression analysis study of the intercancer linkage with the world cancer incidence data.
This study represents an extension of our statistical studies of age-adjusted incidence rates (AAIRs) of 19 neoplasias from 47 population units of the world. We have invented 2 data manipulation methods (topological data conversion and sequential regression analysis method) to estimate separately the intensities of each oncogene activation and tumor suppressor gene inactivation of a given tumor (marker tumor) relative to a counterpart tumor (reference tumor) in terms of r seq value. This study prepared the r seq table of all permutations of tumor pairs for each of the 2 cancer genes and for each sex first, and then investigated the relation between the r seq profile of oncogene activation and that of tumor suppressor gene inactivation for each tumor. A profile containing 16 (male) or 17 (female) r seq data was prepared for each tumor pair, for each cancer gene, and for each sex. The extent of similarity between 2 r seq profiles was assessed by the 1st order regression analysis in terms of the correlation coefficient r value. Results obtained are given as follows: a) The proportions of both the tumor pairs with r seq values of less than -0.90 in the oncogene activation tables of two sexes and those with r seq values of more than +0.90 in the tumor suppressor gene inactivation tables of the two sexes were all more than 50%. A small number of tumor pairs in both the oncogene activation tables and the tumor suppressor gene inactivation tables have invaded deep into each the plus- and the minus-areas to constitute the very end of long tails of the r seq profiles. b) In spite of the above symmetry of data distribution between the 2 cancer-gene tables, individual cancer pairs very rarely gave 2 cancer-gene profiles that fit the definition of symmetry. Taken together, our data manipulation was a success in presenting an oncogene activation profile and a tumor suppressor gene inactivation profile separately. c) The similarity test was conducted with all combinations of tumor pair profiles for each cancer gene and for each sex. The frequency distributions of r values in the oncogene activation tables of both sexes looked normal with long tails to both the plus- and the minus-areas. In contrast, the corresponding frequency distributions of r in the tumor suppressor gene inactivation tables of both sexes were skewed towards the direction of +1.0. It was indicated that the morphological specificity of the oncogene activation profiles was much higher than that of the tumor suppressor gene inactivation profiles. d) Male versus female comparison in 2 neoplasias with sex discrimination of cancer risk revealed that the combination of the general depression of r seq values in the oncogene profile of dominant gender and the general elevation of r seq values in the oncogene profile of recessive gender was the common trait of female-dominant breast cancer and male-dominant laryngeal cancer. It is suggested that the predominance of oncogene activation impact over the tumor suppressor gene inactivation impact was implicated in the creation of sex discrimination of cancer risk. e) Application of a new test method (reciprocal regression analysis) to the r seq table data led to the conclusion that the 2 cancer genes are interfering with each other, and that the balance of power between the 2 cancer genes varies from one marker tumor to the other. f) The results obtained in this study together with the consistency of data interpretation is discussed in light of thermodynamics.
Kodama
M
M
Kodama Research Institute of Preventive Medicine, 50-5 Chiyogaoka, Chikusaku, Nagoya, 464, Japan.
Murakami
M
M
Kodama
T
T
D005260:Female; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics*; D016147:Genes, Tumor Suppressor / Q000235:genetics*; D014943:Global Health; D012739:Gonadal Steroid Hormones; D006801:Humans; D015994:Incidence; D008297:Male; D009369:Neoplasms / Q000453:epidemiology / Q000235:genetics*; D011518:Proto-Oncogene Proteins / Q000235:genetics*; D012044:Regression Analysis; D017678:Sex Distribution
D012739:Gonadal Steroid Hormones; D011518:Proto-Oncogene Proteins