The origins of the components of genetic coding are examined in the present study. Genetic information arose from replicator induction by metabolite in accordance with the metabolic expansion law. Messenger RNA and transfer RNA stemmed from a template for binding the aminoacyl-RNA synthetase ribozymes employed to synthesize peptide prosthetic groups on RNAs in the Peptidated RNA World. Coevolution of the genetic code with amino acid biosynthesis generated tRNA paralogs that identify a last universal common ancestor (LUCA) of extant life close to Methanopyrus, which in turn points to archaeal tRNA introns as the most primitive introns and the anticodon usage of Methanopyrus as an ancient mode of wobble. The prediction of the coevolution theory of the genetic code that the code should be a mutable code has led to the isolation of optional and mandatory synthetic life forms with altered protein alphabets.

The presence of loss-of-heterozygosity (LOH) mutations in cancer cell genomes is commonly encountered. Moreover, the occurrences of LOHs in tumor suppressor genes play important roles in oncogenesis. However, because the causative mechanisms underlying LOH mutations in cancer cells yet remain to be elucidated, enquiry into the nature of these mechanisms based on a comprehensive examination of the characteristics of LOHs in multiple types of cancers has become a necessity. We performed next-generation sequencing on inter-Alu sequences of five different types of solid tumors and acute myeloid leukemias, employing the AluScan platform which entailed amplification of such sequences using multiple PCR primers based on the consensus sequences of Alu elements; as well as the whole genome sequences of a lung-to-liver metastatic cancer and a primary liver cancer. Paired-end sequencing reads were aligned to the reference human genome to identify major and minor alleles so that the partition of LOH products between homozygous-major vs. homozygous-minor alleles could be determined at single-base resolution. Strict filtering conditions were employed to avoid false positives. Measurements of LOH occurrences in copy number variation (CNV)-neutral regions were obtained through removal of CNV-associated LOHs. We found: (a) average occurrence of copy-neutral LOHs amounting to 6.9 % of heterologous loci in the various cancers; (b) the mainly interstitial nature of the LOHs; and (c) preference for formation of homozygous-major over homozygous-minor, and transitional over transversional, LOHs. The characteristics of the cancer LOHs, observed in both AluScan and whole genome sequencings, point to the formation of LOHs through repair of double-strand breaks by interhomolog recombination, or gene conversion, as the consequence of a defective DNA-damage response, leading to a unified mechanism for generating the mutations required for oncogenesis as well as the progression of cancer cells.

Massive occurrences of interstitial loss of heterozygosity (LOH) likely resulting from gene conversions were found by us in different cancers as a type of single-nucleotide variations (SNVs), comparable in abundance to the commonly investigated gain of heterozygosity (GOH) type of SNVs, raising the question of the relationships between these two opposing types of cancer mutations. In the present study, SNVs in 12 tetra sample and 17 trio sample sets from four cancer types along with copy number variations (CNVs) were analyzed by AluScan sequencing, comparing tumor with white blood cells as well as tissues vicinal to the tumor. Four published “nontumor”-tumor metastasis trios and 246 pan-cancer pairs analyzed by whole-genome sequencing (WGS) and 67 trios by whole-exome sequencing (WES) were also examined. Widespread GOHs enriched with CG-to-TG changes and associated with nearby CNVs and LOHs enriched with TG-to-CG changes were observed. Occurrences of GOH were 1.9-fold higher than LOH in “nontumor” tissues more than 2 cm away from the tumors, and a majority of these GOHs and LOHs were reversed in “paratumor” tissues within 2 cm of the tumors, forming forward-reverse mutation cycles where the revertant LOHs displayed strong lineage effects that pointed to a sequential instead of parallel development from “nontumor” to “paratumor” and onto tumor cells, which was also supported by the relative frequencies of 26 distinct classes of CNVs between these three types of cell populations. These findings suggest that developing cancer cells undergo sequential changes that enable the “nontumor” cells to acquire a wide range of forward mutations including ones that are essential for oncogenicity, followed by revertant mutations in the “paratumor” cells to avoid growth retardation by excessive mutation load. Such utilization of forward-reverse mutation cycles as an adaptive mechanism was also observed in cultured HeLa cells upon successive replatings. An understanding of forward-reverse mutation cycles in cancer development could provide a genomic basis for improved early diagnosis, staging, and treatment of cancers.

AluScan combines inter-Alu PCR using multiple Alu-based primers with opposite orientations and next-generation sequencing to capture a huge number of Alu-proximal genomic sequences for investigation. Its requirement of only sub-microgram quantities of DNA facilitates the examination of large numbers of samples. However, the special features of AluScan data rendered difficult the calling of copy number variation (CNV) directly using the calling algorithms designed for whole genome sequencing (WGS) or exome sequencing. In this study, an AluScanCNV package has been assembled for efficient CNV calling from AluScan sequencing data employing a Geary-Hinkley transformation (GHT) of read-depth ratios between either paired test-control samples, or between test samples and a reference template constructed from reference samples, to call the localized CNVs, followed by use of a GISTIC-like algorithm to identify recurrent CNVs and circular binary segmentation (CBS) to reveal large extended CNVs. To evaluate the utility of CNVs called from AluScan data, the AluScans from 23 non-cancer and 38 cancer genomes were analyzed in this study. The glioma samples analyzed yielded the familiar extended copy-number losses on chromosomes 1p and 9. Also, the recurrent somatic CNVs identified from liver cancer samples were similar to those reported for liver cancer WGS with respect to a striking enrichment of copy-number gains in chromosomes 1q and 8q. When localized or recurrent CNV-features capable of distinguishing between liver and non-liver cancer samples were selected by correlation-based machine learning, a highly accurate separation of the liver and non-liver cancer classes was attained. The results obtained from non-cancer and cancerous tissues indicated that the AluScanCNV package can be employed to call localized, recurrent and extended CNVs from AluScan sequences. Moreover, both the localized and recurrent CNVs identified by this method could be subjected to machine-learning selection to yield distinguishing CNV-features that were capable of separating between liver cancers and other types of cancers. Since the method is applicable to any human DNA sample with or without the availability of a paired control, it can also be employed to analyze the constitutional CNVs of individuals.

Background: Cancer subtyping has mainly relied on pathological and molecular means. Massively parallel sequencing-enabled subtyping requires genomic markers to be developed based on global features rather than individual mutations for effective implementation. Methods: In the present study, the whole genome sequences (WGS) of 110 liver cancers of Japanese patients published with different pathologies were analyzed with respect to their single nucleotide variations (SNVs) comprising both gain-of-heterozygosity (GOH) and loss-of-heterozygosity (LOH) mutations, the signatures of combined GOH and LOH mutations, along with recurrent copy number variations (CNVs). Results: The results, obtained based on the WGS sequences as well as the Exome subset within the WGSs that covered ~ 2.0% of the WGS and the AluScan-subset within the WGSs that were amplifiable by Alu element-consensus primers and covered ~ 2.1% of the WGS, indicated that the WGS samples could be employed with the mutational parameters of SNV load, LOH%, the Signature α%, and survival-associated recurrent CNVs (srCNVs) as genomic markers for subtyping to stratify liver cancer patients prognostically into the long and short survival subgroups. The usage of the AluScan-subset data, which could be implemented with sub-micrograms of DNA samples and vastly reduced sequencing analysis task, outperformed the usage of WGS data when LOH% was employed as stratifying criterion. Conclusions: Thus genomic subtyping performed with novel genomic markers identified in this study was effective in predicting patient-survival duration, with cohorts of hepatocellular carcinomas alone and those including intrahepatic cholangiocarcinomas. Such relatively heterogeneity-insensitive genomic subtyping merits further studies with a broader spectrum of cancers.

To delineate the temporal sequence of mutational events, residue-by-residue comparisons of same-patient tetra samples comprising white-blood-cell control, tumor-adjacent morphologically largely normal ‘subnormal’ and ‘paratumor’ regions, and tumor tissue were analyzed. Cells in the ‘subnormal’ region were enriched in single-nucleotide-variations (SNVs), including both gain-of-heterozygosities (GOHs) and loss-of-heterozygosities (LOHs), and copy-number-variations (CNVs); the CpG>TpG GOHs and TpG>CpG LOHs represented the most prominent SNVs especially in early-onset patients, and were found to be located close to recurrent CNVs. A striking fraction of the SNVs and CNVs displayed by the ‘subnormal’ region cells were reverted in the immediately tumor-proximal ‘paratumor’ region cells back to their pre-mutated control genotypes with strong lineage effects particularly in the LOH-reversals. These findings, corroborated by results from previously-reported tumor genomic changes analyzed using whole-exon-sequencing and whole-genome-sequencing, and from sequential samplings of cultured HeLa cells, led to the proposal of a ‘Stage Specific Population’ (SSP) model of carcinogenesis, where cancer development proceeded from control cells to ‘subnormal’-stage cells followed by ‘paratumor’-stage cells and finally the mature tumor cells. On this basis, the ‘subnormal’ and ‘paratumor’ stages, corresponding respectively to a premalignant stage and a premalignant or early malignant stage, are identified as plausibly valuable targets for therapeutic intervention.