Relating mutational signature exposures to clinical data in cancers via signeR 2.0.

BACKGROUND: Cancer is a collection of diseases caused by the deregulation of cell processes, which is triggered by somatic mutations. The search for patterns in somatic mutations, known as mutational signatures, is a growing field of study that has already become a useful tool in oncology. Several algorithms have been proposed to perform one or both the following two tasks: (1) de novo estimation of signatures and their exposures, (2) estimation of the exposures of each one of a set of pre-defined signatures. RESULTS: Our group developed signeR, a Bayesian approach to both of these tasks. Here we present a new version of the software, signeR 2.0, which extends the possibilities of previous analyses to explore the relation of signature exposures to other data of clinical relevance. signeR 2.0 includes a user-friendly interface developed using the R-Shiny framework and improvements in performance. This version allows the analysis of submitted data or public TCGA data, which is embedded in the package for easy access. CONCLUSION: signeR 2.0 is a valuable tool to generate and explore exposure data, both from de novo or fitting analyses and is an open-source R package available through the Bioconductor project at ( https://doi.org/10.18129/B9.bioc.signeR ).

A mixture model for determining SARS-Cov-2 variant composition in pooled samples.

MOTIVATION: Despite of the fast development of highly effective vaccines to control the current COVID-19 pandemics, the unequal distribution and availability of these vaccines worldwide and the number of people infected in the world lead to the continuous emergence of Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) variants of concern. Therefore, it is likely that real-time genomic surveillance will be continuously needed as an unceasing monitoring tool, necessary to follow the spread of the disease and the evolution of the virus. In this context, new genomic variants of SARS-CoV-2, including variants refractory to current vaccines, makes genomic surveillance programs tools of utmost importance. Nevertheless, the lack of appropriate analytical tools to quickly and effectively access the viral composition in meta-transcriptomic sequencing data, including environmental surveillance, represent possible challenges that may impact the fast adoption of this approach to mitigate the spread and transmission of viruses. RESULTS: We propose a statistical model for the estimation of the relative frequencies of SARS-CoV-2 variants in pooled samples. This model is built by considering a previously defined selection of genomic polymorphisms that characterize SARS-CoV-2 variants. The methods described here support both raw sequencing reads for polymorphisms-based markers calling and predefined markers in the variant call format. Results obtained using simulated data show that our method is quite effective in recovering the correct variant proportions. Further, results obtained by considering longitudinal data from wastewater samples of two locations in Switzerland agree well with those describing the epidemiological evolution of COVID-19 variants in clinical samples of these locations. Our results show that the described method can be a valuable tool for tracking the proportions of SARS-CoV-2 variants in complex mixtures such as waste water and environmental samples. AVAILABILITY AND IMPLEMENTATION: http://github.com/rvalieris/LCS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Systems-level Characterization of the Differentiation of Human Embryonic Stem Cells into Mesenchymal Stem Cells.

Mesenchymal stem/stromal cells (MSCs) are self-renewing multipotent cells with regenerative, secretory and immunomodulatory capabilities that are beneficial for the treatment of various diseases. To avoid the issues that come with using tissue-derived MSCs in therapy, MSCs may be generated by the differentiation of human embryonic stems cells (hESCs) in culture. However, the changes that occur during the differentiation process have not been comprehensively characterized. Here, we combined transcriptome, proteome and phosphoproteome profiling to perform an in-depth, multi-omics study of the hESCs-to-MSCs differentiation process. Based on RNA-to-protein correlation, we determined a set of high confidence genes that are important to differentiation. Among the earliest and strongest induced proteins with extensive differential phosphorylation was AHNAK, which we hypothesized to be a defining factor in MSC biology. We observed two distinct expression waves of developmental HOX genes and an AGO2-to-AGO3 switch in gene silencing. Exploring the kinetic of noncoding ORFs during differentiation, we mapped new functions to well annotated long noncoding RNAs (CARMN, MALAT, NEAT1, LINC00152) as well as new candidates which we identified to be important to the differentiation process. Phosphoproteome analysis revealed ESC and MSC-specific phosphorylation motifs with PAK2 and RAF1 as top predicted upstream kinases in MSCs. Our data represent a rich systems-level resource on ESC-to-MSC differentiation that will be useful for the study of stem cell biology.

APOBEC-mediated DNA alterations: A possible new mechanism of carcinogenesis in EBV-positive gastric cancer.

Mechanisms of viral oncogenesis are diverse and include the off-target activity of enzymes expressed by the infected cells, which evolved to target viral genomes for controlling their infection. Among these enzymes, the single-strand DNA editing capability of APOBECs represent a well-conserved viral infection response that can also cause untoward mutations in the host DNA. Here we show, after evaluating somatic single-nucleotide variations and transcriptome data in 240 gastric cancer samples, a positive correlation between APOBEC3s mRNA-expression and the APOBEC-mutation signature, both increased in EBV+ tumors. The correlation was reinforced by the observation of APOBEC mutations preferentially occurring in the genomic loci of the most active transcripts. This EBV infection and APOBEC3 mutation-signature axis were confirmed in a validation cohort of 112 gastric cancer patients. Our findings suggest that APOBEC3 upregulation in EBV+ cancer may boost the mutation load, providing further clues to the mechanisms of EBV-induced gastric carcinogenesis. After further validation, this EBV-APOBEC axis may prove to be a secondary driving force in the mutational evolution of EBV+ gastric tumors, whose consequences in terms of prognosis and treatment implications should be vetted.

signeR: an empirical Bayesian approach to mutational signature discovery.

MOTIVATION: Mutational signatures can be used to understand cancer origins and provide a unique opportunity to group tumor types that share the same origins and result from similar processes. These signatures have been identified from high throughput sequencing data generated from cancer genomes by using non-negative matrix factorisation (NMF) techniques. Current methods based on optimization techniques are strongly sensitive to initial conditions due to high dimensionality and nonconvexity of the NMF paradigm. In this context, an important question consists in the determination of the actual number of signatures that best represent the data. The extraction of mutational signatures from high-throughput data still remains a daunting task. RESULTS: Here we present a new method for the statistical estimation of mutational signatures based on an empirical Bayesian treatment of the NMF model. While requiring minimal intervention from the user, our method addresses the determination of the number of signatures directly as a model selection problem. In addition, we introduce two new concepts of significant clinical relevance for evaluating the mutational profile. The advantages brought by our approach are shown by the analysis of real and synthetic data. The later is used to compare our approach against two alternative methods mostly used in the literature and with the same NMF parametrization as the one considered here. Our approach is robust to initial conditions and more accurate than competing alternatives. It also estimates the correct number of signatures even when other methods fail. Results on real data agree well with current knowledge. AVAILABILITY AND IMPLEMENTATION: signeR is implemented in R and C ++, and is available as a R package at http://bioconductor.org/packages/signeR CONTACT: itojal@cipe.accamargo.org.brSupplementary information: Supplementary data are available at Bioinformatics online.

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data.

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic 'novel' lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.

Detection of oxaliplatin- and cisplatin-DNA lesions requires different global genome repair mechanisms that affect their clinical efficacy.

The therapeutic efficacy of cisplatin and oxaliplatin depends on the balance between the DNA damage induction and the DNA damage response of tumor cells. Based on clinical evidence, oxaliplatin is administered to cisplatin-unresponsive cancers, but the underlying molecular causes for this tumor specificity are not clear. Hence, stratification of patients based on DNA repair profiling is not sufficiently utilized for treatment selection. Using a combination of genetic, transcriptomics and imaging approaches, we identified factors that promote global genome nucleotide excision repair (GG-NER) of DNA-platinum adducts induced by oxaliplatin, but not by cisplatin. We show that oxaliplatin-DNA lesions are a poor substrate for GG-NER initiating factor XPC and that DDB2 and HMGA2 are required for efficient binding of XPC to oxaliplatin lesions and subsequent GG-NER initiation. Loss of DDB2 and HMGA2 therefore leads to hypersensitivity to oxaliplatin but not to cisplatin. As a result, low DDB2 levels in different colon cancer cells are associated with GG-NER deficiency and oxaliplatin hypersensitivity. Finally, we show that colon cancer patients with low DDB2 levels have a better prognosis after oxaliplatin treatment than patients with high DDB2 expression. We therefore propose that DDB2 is a promising predictive marker of oxaliplatin treatment efficiency in colon cancer.

Cervical Cancer Stem-Like Cell Transcriptome Profiles Predict Response to Chemoradiotherapy.

Cervical cancer (CC) represents a major global health issue, particularly impacting women from resource constrained regions worldwide. Treatment refractoriness to standard chemoradiotheraphy has identified cancer stem cells as critical coordinators behind the biological mechanisms of resistance, contributing to CC recurrence. In this work, we evaluated differential gene expression in cervical cancer stem-like cells (CCSC) as biomarkers related to intrinsic chemoradioresistance in CC. A total of 31 patients with locally advanced CC and referred to Mário Penna Institute (Belo Horizonte, Brazil) from August 2017 to May 2018 were recruited for the study. Fluorescence-activated cell sorting was used to enrich CD34+/CD45- CCSC from tumor biopsies. Transcriptome was performed using ultra-low input RNA sequencing and differentially expressed genes (DEGs) using Log2 fold differences and adjusted p-value < 0.05 were determined. The analysis returned 1050 DEGs when comparing the Non-Responder (NR) (n=10) and Responder (R) (n=21) groups to chemoradiotherapy. These included a wide-ranging pattern of underexpressed coding genes in the NR vs. R patients and a panel of lncRNAs and miRNAs with implications for CC tumorigenesis. A panel of biomarkers was selected using the rank-based AUC (Area Under the ROC Curve) and pAUC (partial AUC) measurements for diagnostic sensitivity and specificity. Genes overlapping between the 21 highest AUC and pAUC loci revealed seven genes with a strong capacity for identifying NR vs. R patients (ILF2, RBM22P2, ACO16722.1, AL360175.1 and AC092354.1), of which four also returned significant survival Hazard Ratios. This study identifies DEG signatures that provide potential biomarkers in CC prognosis and treatment outcome, as well as identifies potential alternative targets for cancer therapy.

Mutational Signatures Driven by Epigenetic Determinants Enable the Stratification of Patients with Gastric Cancer for Therapeutic Intervention.

DNA mismatch repair deficiency (dMMR) is associated with the microsatellite instability (MSI) phenotype and leads to increased mutation load, which in turn may impact anti-tumor immune responses and treatment effectiveness. Various mutational signatures directly linked to dMMR have been described for primary cancers. To investigate which mutational signatures are associated with prognosis in gastric cancer, we performed a de novo extraction of mutational signatures in a cohort of 787 patients. We detected three dMMR-related signatures, one of which clearly discriminates tumors with MLH1 gene silencing caused by promoter hypermethylation (area under the curve = 98%). We then demonstrated that samples with the highest exposure of this signature share features related to better prognosis, encompassing clinical and molecular aspects and altered immune infiltrate composition. Overall, the assessment of the prognostic value and of the impact of modifications in MMR-related genes on shaping specific dMMR mutational signatures provides evidence that classification based on mutational signature exposure enables prognosis stratification.

In Situ DESI-MSI Lipidomic Profiles of Breast Cancer Molecular Subtypes and Precursor Lesions.

Clinically meaningful molecular subtypes for classification of breast cancers have been established, however, initiation and progression of these subtypes remain poorly understood. The recent development of desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) facilitates the convergence of analytical chemistry and traditional pathology, allowing chemical profiling with minimal tissue pretreatment in frozen samples. Here, we characterized the chemical composition of molecular subtypes of breast cancer with DESI-MSI. Regions of interest were identified, including invasive breast cancer (IBC), ductal carcinoma in situ (DCIS), and adjacent benign tissue (ABT), and metabolomic profiles at 200 µm elaborated using Biomap software and the Lasso method. Top ions identified in IBC regions included polyunsaturated fatty acids, deprotonated glycerophospholipids, and sphingolipids. Highly saturated lipids, as well as antioxidant molecules [taurine (m/z 124.0068), uric acid (m/z 167.0210), ascorbic acid (m/z 175.0241), and glutathione (m/z 306.0765)], were able to distinguish IBC from ABT. Moreover, luminal B and triple-negative subtypes showed more complex lipid profiles compared with luminal A and HER2 subtypes. DCIS and IBC were distinguished on the basis of cell signaling and apoptosis-related ions [fatty acids (341.2100 and 382.3736 m/z) and glycerophospholipids (PE (P-16:0/22:6, m/z 746.5099, and PS (38:3), m/z 812.5440)]. In summary, DESI-MSI identified distinct lipid composition between DCIS and IBC and across molecular subtypes of breast cancer, with potential implications for breast cancer pathogenesis. SIGNIFICANCE: These findings present the first in situ metabolomic findings of the four molecular subtypes of breast cancer, DCIS, and normal tissue, and add to the understanding of their pathogenesis.

Influence of BRCA1 Germline Mutations in the Somatic Mutational Burden of Triple-Negative Breast Cancer.

The majority of the hereditary triple-negative breast cancers (TNBCs) are associated with BRCA1 germline mutations. Nevertheless, the understanding of the role of BRCA1 deficiency in the TNBC tumorigenesis is poor. In this sense, we performed whole-exome sequencing of triplet samples (leucocyte, tumor, and normal-adjacent breast tissue) for 10 cases of early-onset TNBC, including 5 hereditary (with BRCA1 germline pathogenic mutation) and 5 sporadic (with no BRCA1 or BRCA2 germline pathogenic mutations), for assessing the somatic mutation repertoire. Protein-affecting somatic mutations were identified for both mammary tissues, and Ingenuity Pathway Analysis was used to investigate gene interactions. BRCA1 and RAD51C somatic promoter methylation in tumor samples was also investigated by bisulfite sequencing. Sporadic tumors had higher proportion of driver mutations (≥25% allele frequency) than BRCA1 hereditary tumors, whereas no difference was detected in the normal breast samples. Distinct gene networks were obtained from the driver genes in each group. The Cancer Genome Atlas data analysis of TNBC classified as hereditary and sporadic reinforced our findings. The data presented here indicate that in the absence of BRCA1 germline mutations, a higher number of driver mutations are required for tumor development and that different defective processes are operating in the tumorigenesis of hereditary and sporadic TNBC in young women.

A total transcriptome profiling method for plasma-derived extracellular vesicles: applications for liquid biopsies.

Extracellular vesicles (EVs) are key mediators of intercellular communication. Part of their biological effects can be attributed to the transfer of cargos of diverse types of RNAs, which are promising diagnostic and prognostic biomarkers. EVs found in human biofluids are a valuable source for the development of minimally invasive assays. However, the total transcriptional landscape of EVs is still largely unknown. Here we develop a new method for total transcriptome profiling of plasma-derived EVs by next generation sequencing (NGS) from limited quantities of patient-derived clinical samples, which enables the unbiased characterization of the complete RNA cargo, including both small- and long-RNAs, in a single library preparation step. This approach was applied to RNA extracted from EVs isolated by ultracentrifugation from the plasma of five healthy volunteers. Among the most abundant RNAs identified we found small RNAs such as tRNAs, miRNAs and miscellaneous RNAs, which have largely unknown functions. We also identified protein-coding and long noncoding transcripts, as well as circular RNA species that were also experimentally validated. This method enables, for the first time, the full spectrum of transcriptome data to be obtained from minute patient-derived samples, and will therefore potentially allow the identification of cell-to-cell communication mechanisms and biomarkers.

Genomics and epidemiology for gastric adenocarcinomas (GE4GAC): a Brazilian initiative to study gastric cancer

Gastric cancer (GC) is the fifth most common type of cancer worldwide with high incidences in Asia, Central, and South American countries. This patchy distribution means that GC studies are neglected by large research centers from developed countries. The need for further understanding of this complex disease, including the local importance of epidemiological factors and the rich ancestral admixture found in Brazil, stimulated the implementation of the GE4GAC project. GE4GAC aims to embrace epidemiological, clinical, molecular and microbiological data from Brazilian controls and patients with malignant and pre-malignant gastric disease. In this letter, we summarize the main goals of the project, including subject and sample accrual and current findings

Identification of new ABA- and MEJA-activated sugarcane bZIP genes by data mining in the SUCEST database.

Sugarcane is generally propagated by cuttings of the stalk containing one or more lateral buds, which will develop into a new plant. The transition from the dormant into the active stage constitutes a complex phenomenon characterized by changes in accumulation of phytohormones and several other physiological aspects. Abscisic acid (ABA) and methyl-jasmonate (MeJA) are major signaling molecules, which influence plant development and stress responses. These plant regulators modulate gene expression with the participation of many transcriptional factors. Basic leucine zipper proteins (bZIPs) form a large family of transcriptional factors involved in a variety of plant physiological processes, such as development and responses to stress. Query sequences consisting of full-length protein sequence of each of the Arabidopsis bZIP families were utilized to screen the sugarcane EST database (SUCEST) and 86 sugarcane assembled sequences (SAS) coding for bZIPs were identified. cDNA arrays and RNA-gel blots were used to study the expression of these sugarcane bZIP genes during early plantlet development and in response to ABA and MeJA. Six bZIP genes were found to be differentially expressed during development. ABA and MeJA modulated the expression of eight sugarcane bZIP genes. Our findings provide novel insights into the expression of this large protein family of transcriptional factors in sugarcane.

Transcriptionally active transposable elements in recent hybrid sugarcane.

Transposable elements (TEs) are considered to be important components of the maintenance and diversification of genomes. The recent increase in genome sequence data has created an opportunity to evaluate the impact of these active mobile elements on the evolution of plant genomes. Analysis of the sugarcane transcriptome identified 267 clones with significant similarity to previously described plant TEs. After full cDNA sequencing, 68 sugarcane TE clones were assigned to 11 families according to their best sequence alignment against a fully characterized element. Expression was further investigated through a combined study utilizing electronic Northerns, macroarray, transient and stable sugarcane transformation. Newly synthesized cDNA probes from flower, leaf roll, apical meristem and callus tissues confirm previous results. Callus was identified as the tissue with the highest number of TEs being expressed, revealing that tissue culture drastically induced the expression of different elements. No tissue-specific family was identified. Different representatives within a TE family displayed differential expression patterns, showing that each family presented expression in almost every tissue. Transformation experiments demonstrated that most Hopscotch clone-derived U3 regions are, indeed, active promoters, although under a strong transcriptional regulation. This is a large-scale study about the expression pattern of TEs and indicates that mobile genetic elements are transcriptionally active in the highly polyploid and complex sugarcane genome.

Evaluation of the performance of different plastics used to seal nylon cDNA arrays / Avaliação da performance de diferentes plásticos usados para selar arranjos de cDNA em náilon

cDNA arrays are a powerful tool for discovering gene expression patterns. Nylon arrays have the advantage that they can be re-used several times. A key issue in high throughput gene expression analysis is sensitivity. In the case of nylon arrays, signal detection can be affected by the plastic bags used to keep membranes humid. In this study, we evaluated the effect of five types of plastics on the radioactive transmittance, number of genes with a signal above the background, and data variability. A polyethylene plastic bag 69 μm thick had a strong shielding effect that blocked 68.7 percent of the radioactive signal. The shielding effect on transmittance decreased the number of detected genes and increased the data variability. Other plastics which were thinner gave better results. Although plastics made from polyvinylidene chloride, polyvinyl chloride (both 13 μm thick) and polyethylene (29 and 7 μm thick) showed different levels of transmittance, they all gave similarly good performances. Polyvinylidene chloride and polyethylene 29 mm thick were the plastics of choice because of their easy handling. For other types of plastics, it is advisable to run a simple check on their performance in order to obtain the maximum information from nylon cDNA arrays.

Os arranjos de cDNA são uma poderosa ferramenta para o estudo de padrões de expressão gênica. Os arranjos em membranas de náilon apresentam ainda a vantagem de poderem ser reutilizados diversas vezes. Porém, um ponto bastante delicado em estudos de expressão gênica em larga escala é a sensibilidade. No caso de arranjos em membranas de náilon, a detecção dos sinais pode ser afetada pelo envoltório plástico utilizado para manter as membranas úmidas. Nesse estudo, nós avaliamos os efeitos de cinco tipos de plásticos na transmissão radioativa detectada, no número de genes com sinal acima da emissão de fundo e na variabilidade dos dados. O plástico produzido com polietileno com 69 μm de espessura apresentou uma forte interferência na emissão radioativa, bloqueando 68.7 por cento do sinal detectado. Este bloqueio na transmitância diminuiu o numero de genes detectados e aumentou a variabilidade dos dados. Outros plásticos mais finos tiveram resultados melhores. Apesar de plásticos feitos de cloreto de polivinilideno e cloreto de polivinila (ambos com 13 μm de espessura) e polietileno (29 e 7 μm de espessura) terem diferentes níveis de transmitância, todos apresentaram performances semelhantes nos testes realizados. Cloreto de polivinilideno e polietileno com 29 μm de espessura foram os plásticos escolhidos devido à facilidade de manuseio. Para outros tipos de plásticos, é recomendável realizar um teste de suas performances antes de utilizá-los para envolver membranas de náilon, de forma a obter o máximo de informação dos experimentos com arranjos de cDNA.

Prospecting sugarcane genes involved in aluminum tolerance

Alumínio (Al) é um dos principais fatores que afetam o desenvolvimento de plantas em solos ácidos, reduzindo substancialmente a produtividade agrícola. Na América do Sul, cerca de 66 por cento da superfície do solo apresentam acidez, onde a alta saturaçäo de alumínio é uma das maiores limitações à prática agrícola. Apesar do crescente número de estudos, uma compreensäo completa das bases bioquímicas e moleculares da tolerância ao alumínio em plantas está longe de ser alcançada. No caso da cana-de-açúcar, näo há nada publicado sobre a regulaçäo gênica induzida durante o stress por alumínio. O objetivo deste trabalho foi identificar genes de cana-de-açúcar relacionados com as várias vias metabólicas reconhecidamente envolvidas na resposta à toxidez do alumínio em outras espécies de plantas e leveduras. Para a maioria dos genes relacionados com alumínio em outras espécies foram identificados similares em cana-de-açúcar, tais como aqueles que codificam enzimas que combatem o stress oxidativo ou a infestaçäo por patógenos, proteínas responsáveis pela exudaçäo de ácidos orgânicos e pela transduçäo de sinais. O papel desses genes na tolerância ao alumínio é revisado. Devido ao alto grau de conservaçäo do genoma entre espécies próximas de gramíneas como milho, cevada, sorgo e cana-de-açúcar, esses genes seräo uma ferramenta valiosa para a melhor compreensäo e manipulaçäo da tolerância ao alumínio nestas espécies.