Predicting clinical outcomes using cancer progression associated signatures

Somatic mutation signatures are an informative facet of cancer aetiology, however they are rarely useful for predicting patient outcome. The aim of this study is to evaluate the utility of a panel of 142 mutation-signature–associated metrics (P142) for predicting cancer progression in patients from a ‘TCGA PanCancer Atlas’ cohort. The P142 metrics are comprised of AID/APOBEC and ADAR deaminase associated SNVs analyzed for codon context, strand bias, and transitions/transversions. TCGA tumor-normal mutation data was obtained for 10,437 patients, representing 31 of the most prevalent forms of cancer. Stratified random sampling was used to split patients into training, tuning and validation cohorts for each cancer type. Cancer specific machine learning (XGBoost) models were built using the output from the P142 panel to predict patient Progression Free Survival (PFS) status as either “High PFS” or “Low PFS”. Predictive performance of each model was evaluated using the validation cohort. Models accurately predicted PFS status for several cancer types, including adrenocortical carcinoma, glioma, mesothelioma, and sarcoma. In conclusion, the P142 panel of metrics successfully predicted cancer progression status in patients with some, but not all cancer types analyzed. These results pave the way for future studies on cancer progression associated signatures.

Molecular model linking Th2 polarized M2 tumour-associated macrophages with deaminase-mediated cancer progression mutation signatures

A new and diverse range of somatic mutation signatures are observed in late‐stage cancers, but the underlying reasons are not fully understood. We advance a “combinatorial association model” for deaminase binding domain (DBD) diversification to explain the generation of previously observed cancer‐progression associated mutation signatures. We also propose that changes in the polarization of tumour‐associated macrophages (TAMs) are accompanied by the expression of deaminases with a new and diverse range of DBDs, and thus accounting for the generation of new somatic mutation signatures. The mechanism proposed is molecularly reminiscent of combinatorial association of heavy (H) and light (L) protein chains following V(D)J recombination of immunoglobulin molecules (and similarly for protein chains in heterodimers α/β and γ/δ of V(D)Js of T Cell Receptors) required for pathogen antigen recognition by B cells and T cells, respectively. We also discuss whether extracellular vesicles (EVs) emanating from tumour enhancing M2‐polarized macrophages represent a likely source of the de novo deaminase DBDs. We conclude that M2‐polarized macrophages extruding EVs loaded with deaminase proteins or deaminase‐specific transcription/translation regulatory factors and like information may directly trigger deaminase diversification within cancer cells, and thus account for the many new somatic mutation signatures that are indicative of cancer progression. This hypothesis now has a plausible evidentiary base, and it is worth direct testing in future investigations. A long‐term objective would be to identify molecular biomarkers predicting cancer progression (or metastatic disease) and to support the development of new drug targets before metastatic pathways are activated.

De novo transcriptome assembly for the spiny mouse (Acomys cahirinus)

Spiny mice of the genus Acomys display several unique physiological traits, including menstruation and scar-free wound healing; characteristics that are exceedingly rare in mammals, and of considerable interest to the scientific community. These unique attributes, and the potential for spiny mice to accurately model human diseases, are driving increased use of this genus in biomedical research, however little genetic information is accessible for this species. This project aimed to generate a draft transcriptome for the Common spiny mouse (Acomys cahirinus). Illumina sequencing of RNA from 15 organ types (male and female) produced 451 million, 150 bp paired-end reads (92.4Gbp). An extensive survey of de novo transcriptome assembly approaches using Trinity, SOAPdenovo-Trans, and Oases at multiple kmer lengths was conducted, producing 50 single-kmer assemblies from this dataset. Non-redundant transcripts from all assemblies were merged into a meta-assembly using the EvidentialGene tr2aacds pipeline, producing the largest gene catalogue to date for Acomys cahirinus. This study provides the first detailed characterization of the spiny mouse transcriptome. It validates use of the EvidentialGene tr2aacds pipeline in mammals to augment conventional de novo assembly approaches, and provides a valuable scientific resource for further investigation into the unique physiological characteristics inherent in the genus Acomys.

First evidence of a menstruating rodent: the spiny mouse (Acomys cahirinus)

BACKGROUND

Advances in research relating to menstruation and associated disorders (eg, endometriosis and premenstrual syndrome) have been hindered by the lack of an appropriate animal model. Menstruation, the cyclical shedding of the decidualized endometrium in the absence of pregnancy, is believed to be limited to 78 higher-order primates (human beings and Old World monkeys), 4 species of bat, and the elephant shrew. This represents only 1.5% of the known 5502 mammalian species and <0.09% of these are nonprimates. Thus, many aspects of menstruation remain poorly understood, limiting the development of effective treatments for women with menstrual disorders. Menstruation occurs as a consequence of progesterone priming of the endometrial stroma and a spontaneous decidual reaction. At the end of each infertile cycle as progesterone levels decline the uterus is unable to maintain this terminally differentiated stroma and the superficial endometrium is shed. True menstruation has never been reported in rodents.

OBJECTIVE

Here we describe the first observation of menstruation in a rodent, the spiny mouse (Acomys cahirinus).

STUDY DESIGN

Virgin female spiny mice (n = 14) aged 12-16 weeks were sampled through daily vaginal lavage for 2 complete reproductive cycles. Stage-specific collection of reproductive tissue and plasma was used for histology, prolactin immunohistochemistry, and enzyme-linked immunosorbent assay of progesterone (n = 4-5/stage of the menstrual cycle). Normally distributed data are reported as the mean ± SE and significant differences calculated using a 1-way analysis of variance. Nonnormal data are displayed as the median values of replicates (with interquartile range) and significant differences calculated using Kruskal-Wallis test.

RESULTS

Mean menstrual cycle length was 8.7 ± 0.4 days with red blood cells observed in the lavages over 3.0 ± 0.2 days. Cyclic endometrial shedding and blood in the vaginal canal concluding with each infertile cycle was confirmed in all virgin females. The endometrium was thickest during the luteal phase at 322.6 μm (254.8, 512.2), when plasma progesterone peaked at 102.1 ng/mL (70.1, 198.6) and the optical density for prolactin immunoreactivity was strongest (0.071 ± 0.01 arbitrary units).

CONCLUSION

The spiny mouse undergoes spontaneous decidualization, demonstrating for the first time menstruation in a rodent. The spiny mouse provides a readily accessible nonprimate model to study the mechanisms of menstrual shedding and repair, and may therefore be useful in furthering studies of human menstrual and pregnancy-associated disorders.