Unfortunately it rather seems to be a very hard attempt at fitting in the somatic mutation theory which does not work for the majority of cancers by using superlative terms. For the majority of cancers the apple (mutation) did not work, but maybe the hyper-apple (hyper-mutation) and perhaps, someday, an ultra-apple (ultra-mutation) might explain what has not been explained to date.

But, if we look very carefully, we may recognize that we already have stepped backwards to 1953:

1914 Theodor Boveri - combination of chromosomal defects may result into cancer

1928 Karl-Heinrich Bauer - first suggestion mutations could cause cancer

1953 Carl Nordling - a number of mutated genes cause cancerous cells

1971 Alfred Kudson - 1-hit-theory (a number of mutated genes cause cancerous cells)

Afterwards the 2-hit-theory: a person who inherits a mutant allele must experience a second somatic mutation to initiate carcinogenesis – maybe we call this one “It takes two to Tango”

2014 – we are getting back to Carl Nordling from 1953, but call it hypermutation theory

The recent spate of papers on mutations as the primary causative event in cancer appears to have painted his theory into a corner. Given that little by way of clinical relevance (benefitting the patient) has emerged from the “somatic mutation theory”, proponents added the concept of ‘driver’ mutations and ‘passenger’ mutations and just to be sure that that might be deemed insufficient, now we have the brand new “hyper-mutation” theory to patch over the weak links in the original mutation theory. One would expect scientists to back up and re-think the original paradigm given its inability to show clinical utility.

Abstract

A role for somatic mutations in carcinogenesis is well accepted, but the degree to which mutation rates influence cancerinitiation and development is under continuous debate. Recently accumulated genomic data have revealed that thousands of tumour samples are riddled by hypermutation, broadening support for the idea that many cancers acquire a mutator phenotype. This major expansion of cancer mutation data sets has provided unprecedented statistical power for the analysis of mutation spectra, which has confirmed several classical sources of mutation in cancer, highlighted new prominent mutation sources (such as apolipoprotein B mRNA editing enzyme catalytic polypeptide-like (APOBEC) enzymes) and empowered the search for cancer drivers. The confluence of cancer mutation genomics and mechanistic insight provides great promise for understanding the basic development of cancer through mutations.

Article:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4280484/

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4280484/

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