Genome-wide profiling of rare tumors is crucial for improvement of diagnosis, treatment, and, consequently, achieving better outcomes. Desmoplastic small round cell tumor (DSRCT) is a rare type of sarcoma arising from mesenchymal cells of abdominal peritoneum that usually develops in male adolescents and young adults. A specific translocation, t(11;22)(p13;q12), resulting in EWS and WT1 gene fusion is the only recurrent molecular hallmark and no other genetic factor has been associated to this aggressive tumor. Here, we present a comprehensive genomic profiling of one DSRCT affecting a 26-year-old male, who achieved an excellent outcome. We investigated somatic and germline variants through whole-exome sequencing using a family based approach and, by array CGH, we explored the occurrence of genomic imbalances. Additionally, we performed mate-paired whole-genome sequencing for defining the specific breakpoint of the EWS-WT1 translocation, allowing us to develop a personalized tumor marker for monitoring the patient by liquid biopsy. We identified genetic variants leading to protein alterations including 12 somatic and 14 germline events (11 germline compound heterozygous mutations and 3 rare homozygous polymorphisms) affecting genes predominantly involved in mesenchymal cell differentiation pathways. Regarding copy number alterations (CNA) few events were detected, mainly restricted to gains in chromosomes 5 and 18 and losses at 11p, 13q, and 22q. The deletions at 11p and 22q indicated the presence of the classic translocation, t(11;22)(p13;q12). In addition, the mapping of the specific genomic breakpoint of the EWS-WT1 gene fusion allowed the design of a personalized biomarker for assessing circulating tumor DNA (ctDNA) in plasma during patient follow-up. This biomarker has been used in four post-treatment blood samples, 3 years after surgery, and no trace of EWS-WT1 gene fusion was detected, in accordance with imaging tests showing no evidence of disease and with the good general health status of the patient. Overall, our findings revealed genes with potential to be associated with risk assessment and tumorigenesis of this rare type of sarcoma. Additionally, we established a liquid biopsy approach for monitoring patient follow-up based on genomic information that can be similarly adopted for patients diagnosed with a rare tumor.

Background: A variant of unknown significance (VUS) is a variant form of a gene that has been identified through genetic testing, but whose significance to the organism function is not known. An actual challenge in precision medicine is to precisely identify which detected mutations from a sequencing process have a suitable role in the treatment or diagnosis of a disease. The average accuracy of pathogenicity predictors is 85%. However, there is a significant discordance about the identification of mutational impact and pathogenicity among them. Therefore, manual verification is necessary for confirming the real effect of a mutation in its casuistic. Methods: In this work, we use variables categorization and selection for building a decision tree model, and later we measure and compare its accuracy with four known mutation predictors and seventeen supervised machine-learning (ML) algorithms. Results: The results showed that the proposed tree reached the highest precision among all tested variables: 91% for True Neutrals, 8% for False Neutrals, 9% for False Pathogenic, and 92% for True Pathogenic. Conclusions: The decision tree exceptionally demonstrated high classification precision with cancer data, producing consistently relevant forecasts for the sample tests with an accuracy close to the best ones achieved from supervised ML algorithms. Besides, the decision tree algorithm is easier to apply in clinical practice by non-IT experts. From the cancer research community perspective, this approach can be successfully applied as an alternative for the determination of potential pathogenicity of VOUS.

Coronavirus disease 2019 (COVID-19) rapidly transformed into a global pandemic, for which a demand for developing antivirals capable of targeting the SARS-CoV-2 RNA genome and blocking the activity of its genes has emerged. In this work, we presented a database of SARS-CoV-2 targets for small interference RNA (siRNA) based approaches, aiming to speed the design process by providing a broad set of possible targets and siRNA sequences. The siRNAs sequences are characterized and evaluated by more than 170 features, including thermodynamic information, base context, target genes and alignment information of sequences against the human genome, and diverse SARS-CoV-2 strains, to assess possible bindings to off-target sequences. This dataset is available as a set of four tables, available in a spreadsheet and CSV (Comma-Separated Values) formats, each one corresponding to sequences of 18, 19, 20, and 21 nucleotides length, aiming to meet the diversity of technology and expertise among laboratories around the world. A metadata table (Supplementary Table S1), which describes each feature, is also provided in the aforementioned formats. We hope that this database helps to speed up the development of new target antivirals for SARS-CoV-2, contributing to a possible strategy for a faster and effective response to the COVID-19 pandemic.

Tumor DNA has been detected in body fluids of cancer patients. Somatic tumor mutations are being used as biomarkers in body fluids to monitor chemotherapy response as a minimally invasive tool. In this study, we evaluated the potential of tracking somatic mutations in free DNA of plasma and urine collected from Wilms tumor (WT) patients for monitoring treatment response. Wilms tumor is a pediatric renal tumor resulting from cell differentiation errors during nephrogenesis. Its mutational repertoire is not completely defined. Thus, for identifying somatic mutations from tumor tissue DNA, we screened matched tumor/leukocyte DNAs using either a panel containing 16 WT‐associated genes or whole‐exome sequencing (WES). The identified somatic tumor mutations were tracked in urine and plasma DNA collected before, during and after treatment. At least one somatic mutation was identified in five out of six WT tissue samples analyzed. Somatic mutations were detected in body fluids before treatment in all five patients (three patients in urine, three in plasma, and one in both body fluids). In all patients, a decrease of the variant allele fraction of somatic mutations was observed in body fluids during neoadjuvant chemotherapy. Interestingly, the persistence of somatic mutations in body fluids was in accordance with clinical parameters. For one patient who progressed to death, it persisted in high levels in serial body fluid samples during treatment. For three patients without disease progression, somatic mutations were not consistently detected in samples throughout monitoring. For one patient with bilateral disease, a somatic mutation was detected at low levels with no support of clinical manifestation. Our results demonstrated the potential of tracking somatic mutations in urine and plasma DNA as a minimally invasive tool for monitoring WT patients. Additional investigation is needed to check the clinical value of insistent somatic mutations in body fluids.

Background: Uterine leiomyosarcoma (uLMS) are rare and malignant tumors that arise in the myometrium cells and whose diagnosis is based on histopathological features. Identifying diagnostic biomarkers for uLMS is a challenge due to molecular heterogeneity and the scarcity of samples. In vivo and in vitro models for uLMS are urgently needed. Knockout female mice for the catalytic subunit of the immunoproteasome PSMB9 (MIM:177045) develop spontaneous uLMS. This study aimed to analyze the role of PSMB9 in uLMS tumorigenesis and patient outcome. Methods: Molecular data from 3 non-related uLMS cohorts were integrated and analyzed by proteotranscriptomic using gene expression and protein abundance levels in 68 normal adjacent myometrium (MM), 66 uterine leiomyoma (LM), and 67 uLMS. Results: the immunoproteasome pathway is upregulated and the gene PMSB9 shows heterogeneous expression values in uLMS. Quartile group analysis showed no significant difference between groups high and low PSMB9 expression groups at 3-years overall survival (OS). Using CYBERSORTx analysis we observed 9 out of 17 samples in the high group clustering together due to high M2 macrophages and CD4 memory resting, and high CD8+/PSMB9 ratio was associated with better OS. The main pathway regulated in the high group is IFNγ and in the low is the ECM pathway dependent on the proto-oncogene SRC. Conclusion: these findings suggest 2 subtypes of uLMS (immune-related and ECM-related) with different candidate mechanisms of malignancy.

Hyphessobrycon heterorhabdus (Ulrey, 1894), popularly known as ‘Flag Tetra’ in English speaking countries, belongs to the genus Hyphessobrycon of the family Characidae, and is widely present in the eastern Amazon basin. Here, using Illumina sequencing, we report the complete mitogenome sequence of H. heterorhabdus. Overall, the mitogenome has 17,021 bp, containing 13 protein-coding, 22 tRNA, and 2 rRNA genes. Non-ambiguous nucleotide compositions of the H. heterorhabdus mitogenome are A: 29.2%, T: 29.4%, G: 15.6%, and C: 25.8%. As recently indicated, the phylogenetic analyses did not support four separate genera (Hemigrammus, Hyphessobrycon, Moenkhausia, and Psalidodon) of Characidae. Understanding the H. heterorhabdus mitogenome is important for taxonomic purposes as well as for the molecular characterization of environmental pollutants. Thus, the mitogenome described here will be a valuable resource for studies on environmental changes, evolutionary genetics, species delimitation, and phylogenetic analyses in Characidae.