Fortunato, A. | bioRxiv Science

bioRxiv2021

Sponges are highly resistant to radiation exposure and cancer

There are no reports of cancer in sponges, despite them having somatic cell turnover, long lifespans and no specialized adaptive immune cells. In order to investigate whether sponges are cancer resistant, we exposed a species of sponge, Tethya wilhelma, to X-rays. We found that T. wilhelma can withstand 600 Gy of X-ray radiation. That is approximately 100 times the lethal dose for humans. A single high dose of X-rays did not induce cancer in sponges, providing the first experimental evidence of cancer resistance in the phylum, Porifera. Following X-ray exposure, we found an overexpression of genes involved in DNA repair, signaling transduction pathways and epithelial to mesenchymal transition. Sponges have the highest level of radiation resistance that has yet been observed in animals that have sustained somatic cell turnover. This may make them an excellent model system for studying cancer resistance and developing new approaches for cancer prevention and treatment.

evolutionary biology↗

bioRxiv2020

Radiation resistance in Placozoa: Trichoplax adhaerens upregulates DNA repair genes and extrudes cells after exposure.

Trichoplax adhaerens is the simplest multicellular animal with tissue differentiation and somatic cell turnover. Like all other multicellular organisms, it should be vulnerable to cancer, yet there have been no reports of cancer in T. adhaerens, or any other placozoan. We investigated the cancer resistance of T. adhaerens, discovering that they are able to tolerate high levels of radiation damage (218.6 Gy). To investigate how T. adhaerens survive levels of radiation that are lethal to other animals, we examined gene expression after the X-ray exposure, finding overexpression of genes involved in DNA repair and apoptosis including the MDM2 gene. We also discovered that T. adhaerens extrudes clusters of inviable cells after X-ray exposure. T. adhaerens is a valuable model organism for studying the molecular, genetic and tissue-level mechanisms underlying cancer suppression.

cancer biology↗

bioRxiv2020

A new method to accurately identify single nucleotide variants using small FFPE breast samples.

Most tissue collections of neoplasms are composed of formalin-fixed and paraffin-embedded (FFPE) excised tumor samples used for routine diagnostics. DNA sequencing is becoming increasingly important in cancer research and clinical management; however, it is difficult to accurately sequence DNA from FFPE samples. We developed and validated a new bioinformatic algorithm to robustly identify somatic single nucleotide variants (SNVs) from whole exome sequencing using small amounts of DNA extracted from archival FFPE samples of breast cancers. We optimized this strategy using 28 pairs of technical replicates. After optimization, the mean similarity between replicates increased 5-fold, reaching 88% (range 0-100%), with a mean of 21.4 SNVs (range 1-68) per sample, representing a markedly superior performance to existing algorithms. We found that the SNV-identification accuracy declined when there was less than 40ng of DNA available and that insertion-deletion variant calls are less reliable than single base substitutions. As the first application of the new algorithm, we compared samples of ductal carcinoma in situ (DCIS) of the breast to their adjacent invasive ductal carcinoma (IDC) samples. We observed an increased number of mutations (paired-samples sign test, p<0.05), and a higher genetic divergence in the invasive samples (paired-samples sign test, p<0.01). Our algorithm provides a significant improvement in detecting SNVs in FFPE samples over previous approaches. Key PointsO_LIThe sequencing of reduced quantities of DNA extracted from FFPE samples leads to substantial sequencing errors that require correction in order to obtain accurate detection of somatic mutations. C_LIO_LIWe developed and validated a new bioinformatic algorithm to robustly identify somatic single nucleotide variants using small amounts of DNA extracted from archival FFPE samples of breast cancers. C_LIO_LIVariant calling software packages need to be optimized to reduce the impact of sequencing errors. Our bioinformatics pipeline represents a significant methodological advance compared to the currently available bioinformatic tools used for the analysis of small FFPE samples. C_LI

genomics↗