Prognostic Matrisomal Gene Panel and Its Association with Immune Cell Infiltration in Head and Neck Carcinomas

Squamous cell carcinoma of the head and neck (SCCHN) is common worldwide and related to several risk factors including smoking, alcohol consumption, poor dentition and human papillomavirus (HPV) infection. Different etiological factors may influence the tumor microenvironment and play a role in dictating response to therapeutics. Here, we sought to investigate whether an early-stage SCCHN-specific prognostic matrisome-derived gene signature could be identified for HPV-negative SCCHN patients (n = 168), by applying a bioinformatics pipeline to the publicly available SCCHN-TCGA dataset. We identified six matrisome-derived genes with high association with prognostic outcomes in SCCHN. A six-gene risk score, the SCCHN TMI (SCCHN-tumor matrisome index: composed of MASP1, EGFL6, SFRP5, SPP1, MMP8 and P4HA1) was constructed and used to stratify patients into risk groups. Using machine learning-based deconvolution methods, we found that the risk groups were characterized by a differing abundance of infiltrating immune cells. This work highlights the key role of immune infiltration cells in the overall survival of patients affected by HPV-negative SCCHN. The identified SCCHN TMI represents a genomic tool that could potentially aid patient stratification and selection for therapy in these patients.

Development of a multi-species SNP array for serrasalmid fish Colossoma macropomum and Piaractus mesopotamicus

Scarce genomic resources have limited the development of breeding programs for serrasalmid fish Colossoma macropomum (tambaqui) and Piaractus mesopotamicus (pacu), the key native freshwater fish species produced in South America. The main objectives of this study were to design a dense SNP array for this fish group and to validate its performance on farmed populations from several locations in South America. Using multiple approaches based on different populations of tambaqui and pacu, a final list of 29,575 and 29,612 putative SNPs was selected, respectively, to print an Axiom AFFYMETRIX (THERMOFISHER) SerraSNP array. After validation, 74.17% (n = 21,963) and 71.25% (n = 21,072) of SNPs were classified as polymorphic variants in pacu and tambaqui, respectively. Most of the SNPs segregated within each population ranging from 14,199 to 19,856 in pacu; and from 15,075 to 20,380 in tambaqui. Our results indicate high levels of genetic diversity and clustered samples according to their hatchery origin. The developed SerraSNP array represents a valuable genomic tool approaching in-depth genetic studies for these species.

The extracellular milieu of Toxoplasma’s lytic cycle drives lab-adaptation and promotes changes in lipid metabolism primarily driven by transcriptional reprogramming

To map host-independent in vitro virulence traits of Toxoplasma gondii, evolve and resequencing (E&R) during the lab-adaption was applied. Phenotypic assessments of the lytic cycle revealed that only traits needed in the extracellular milieu evolved. Surprisingly, only non-synonymous mutations in a P4 flippase fixed in two populations. However, dramatic changes in the transcriptional signature of extracellular parasites revealed a “pro-tachyzoite” profile as well as upregulation of fatty acid biosynthesis (FASII) pathway genes. More general, a set of 300 genes which expression profile changes during evolution mapped to specific traits. Validation of a select number of genes in this set by knock-outs indeed confirmed their role in lab-adaptation. Finally, assembly of an ApiAP2 and Myb transcription factor network revealed the transcriptional program underlying the adapting extracellular state. Overall, E&R is a new genomic tool successfully applied to map the development of polygenic traits underlying in vitro virulence of T. gondii.

Metagenomics-Based Proficiency Test of Smoked Salmon Spiked with a Mock Community

An inter-laboratory proficiency test was organized to assess the ability of participants to perform shotgun metagenomic sequencing of cold smoked salmon, experimentally spiked with a mock community composed of six bacteria, one parasite, one yeast, one DNA, and two RNA viruses. Each participant applied its in-house wet-lab workflow(s) to obtain the metagenomic dataset(s), which were then collected and analyzed using MG-RAST. A total of 27 datasets were analyzed. Sample pre-processing, DNA extraction protocol, library preparation kit, and sequencing platform, influenced the abundance of specific microorganisms of the mock community. Our results highlight that despite differences in wet-lab protocols, the reads corresponding to the mock community members spiked in the cold smoked salmon, were both detected and quantified in terms of relative abundance, in the metagenomic datasets, proving the suitability of shotgun metagenomic sequencing as a genomic tool to detect microorganisms belonging to different domains in the same food matrix. The implementation of standardized wet-lab protocols would highly facilitate the comparability of shotgun metagenomic sequencing dataset across laboratories and sectors. Moreover, there is a need for clearly defining a sequencing reads threshold, to consider pathogens as detected or undetected in a food sample.

Development and Validation of a Genomic Tool to Predict Seminal Vesicle Invasion in Adenocarcinoma of the Prostate

PURPOSE Pretreatment estimates of seminal vesicle invasion (SVI) are challenging and significantly influence the management of prostate cancer. We sought to improve current models to predict SVI through the development of an SVI prediction genomic signature. PATIENTS AND METHODS A total of 15,889 patients who underwent radical prostatectomy (RP) with available baseline clinical, pathology, and transcriptome data were retrieved from the GRID registry (ClinicalTrials.gov identifier: NCT02609269 ) and other retrospective cohorts. These data were divided into a training (n = 6,766), test (n = 3,363), and two validation (n = 5,062 and 698) cohorts. Multivariable logistic regression was performed to assess the predictive effect of the genomic SVI (gSVI) classifier in the presence of established nomograms (Partin Tables and Memorial Sloan Kettering Cancer Center [MSKCC]). RESULTS In the training cohort, univariable filtering identified 2,132 genes that were differentially expressed between RP tumors with and without SVI. Model parameters were tuned to maximize the area under the curve (AUC) in the testing cohort, resulting in a logistic generalized linear model with 581 genes. The gSVI model scores range from 0 to 1. In the first validation set, gSVI showed superior discrimination of patients with and without SVI at RP compared with other prognostic signatures trained to predict distant metastasis or clinical recurrence. Of the 698 patients in the second validation set, gSVI combined with the MSKCC nomogram had a superior AUC (0.86) compared with either nomogram individually (0.81). CONCLUSION The gSVI represents a novel and validated expression signature to predict the presence of SVI before treatment with surgery. This genomic tool adds discriminatory power to existing clinical predictive nomograms and may help with pretreatment counseling and decision making.

Tumor sequencing aids to identify individuals with hereditary cancer.

e13678 Background: Early identification of individuals with hereditary cancer significantly improves survival in patients and relatives. New genomic tools can identify germline pathogenic variants via tumor-only genomic sequencing in addition to treatment guiding biomarkers. Methods: Our tumor sequencing protocol in medical practice since 2018 via Oncomine Comprehensive Assay (OCA) interrogates several hereditary cancer associated genes; therefore, we aimed to evaluate OCA’s capacity to point out individuals’ with hereditary cancer. But first, OCA’s technical validity was evaluated by testing up to 20 year old FFPE block isolated tumor genomes of individuals known to carry 19 pathogenic variants. Results: All variants were present in the OCA raw dataset but 26% were not called by the commercial software due to specificity of the variant calling algorithm and bias caused by amplicon-based enrichment and limited coverage. Even with this limitation, OCA’s clinical utility was evaluated next. A pathogenic variant candidate to be germline was identified in 5% (26/510) of tumor genomes routinely tested looking for treatment guiding biomarkers, but up to 8% (26/317) when excluding lung cancer patients. Importantly, 73% (14/19) of the ones that were followed-up by peripheral blood testing were confirmed to be germline, so inherited nature of the cancer was confirmed in 9% of ovarian, 8% of endometrium, 5% of biliary tract, 4% of breast, 1% of colorectal and 1% of lung cancer patients whose tumor genome was tested for routine treatment guiding biomarker identification. Conclusions: OCA is a useful genomic tool for identifying individuals with hereditary cancer that opens a new era in clinical practice in oncology. An increased awareness among physicians about this new genomic tool includes understanding the importance of peripheral blood confirmation to define the germline nature of the OCA-identified candidate variant; and proper genetic counseling and germline testing when OCA does not find a candidate variant in a patient with strong family history due to the lack of comprehensive identification of every type of pathogenic variants in all known genes associated with inherited cancer via tumor sequencing tools like OCA.

Comparative Genomic Characterization of the Multimammate Mouse Mastomys coucha

Mastomys are the most widespread African rodent and carriers of various diseases such as the plague or Lassa virus. In addition, mastomys have rapidly gained a large number of mammary glands. Here, we generated a genome, variome, and transcriptomes for Mastomys coucha. As mastomys diverged at similar times from mouse and rat, we demonstrate their utility as a comparative genomic tool for these commonly used animal models. Furthermore, we identified over 500 mastomys accelerated regions, often residing near important mammary developmental genes or within their exons leading to protein sequence changes. Functional characterization of a noncoding mastomys accelerated region, located in the HoxD locus, showed enhancer activity in mouse developing mammary glands. Combined, our results provide genomic resources for mastomys and highlight their potential both as a comparative genomic tool and for the identification of mammary gland number determining factors.