Large-scale chemical-genetics yields new M. tuberculosis inhibitor classes.

New antibiotics are needed to combat rising levels of resistance, with new Mycobacterium tuberculosis (Mtb) drugs having the highest priority. However, conventional whole-cell and biochemical antibiotic screens have failed. Here we develop a strategy termed PROSPECT (primary screening of strains to prioritize expanded chemistry and targets), in which we screen compounds against pools of strains depleted of essential bacterial targets. We engineered strains that target 474 essential Mtb genes and screened pools of 100-150 strains against activity-enriched and unbiased compound libraries, probing more than 8.5 million chemical-genetic interactions. Primary screens identified over tenfold more hits than screening wild-type Mtb alone, with chemical-genetic interactions providing immediate, direct target insights. We identified over 40 compounds that target DNA gyrase, the cell wall, tryptophan, folate biosynthesis and RNA polymerase, as well as inhibitors that target EfpA. Chemical optimization yielded EfpA inhibitors with potent wild-type activity, thus demonstrating the ability of PROSPECT to yield inhibitors against targets that would have eluded conventional drug discovery.

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.

Genetic investigation of syndromic forms of obesity.

BACKGROUND: Syndromic obesity (SO) refers to obesity with additional phenotypes, including intellectual disability (ID)/developmental delay (DD), dysmorphic features, or organ-specific abnormalities. SO is rare, has high phenotypic variability, and frequently follows a monogenic pattern of inheritance. However, the genetic etiology of most cases of SO has not been elucidated. SUBJECTS AND METHODS: In this study, we investigated 20 SO patients by whole-exome sequencing (WES) trios to identify causal genetic variants. RESULTS: 4/20 patients had negative results for array comparative genomic hybridization (aCGH) analyses. In the remaining 15 patients, in addition to SNVs and indels, CNVs were also evaluated. Pathogenic/likely pathogenic (P/LP) SNVs/indels were detected in 6/20 patients (involving MED13L, AHDC1, EHMT1, MYT1L, GRIA3, and SETD1A), while two patients carried an inherited VUS. In addition, P/LP CNVs were observed in 3/15 patients (involving SATG2, KIAA0442, and MEIS2). CONCLUSIONS: All nine detected P/LP variants involved genes already known to lead to syndromic ID/DD; however, for only two genes (EHMT1 and MYT1L) is the link with obesity well established. This is the first study applying a comprehensive genomic investigation of an SO cohort, showing a high diagnostic yield (~47%). Additionally, our findings suggested that several known ID/DD genes may also predispose individuals to SO.

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.

Identification of DNA mutations in gastric washes from gastric adenocarcinoma patients: Possible implications for liquid biopsies and patient follow-up.

Whereas cancer patients have benefited from liquid biopsies, the scenario for gastric adenocarcinoma (GAC) is still dismal. We used next-generation deep sequencing of TP53-a highly mutated and informative gene in GAC-to assess mutations in tumor biopsies, plasma (PL) and stomach fluids (gastric wash-GW). We evaluated their potential to reveal tumor-derived mutations, useful for monitoring mutational dynamics at diagnosis, progression and treatment. Exon-capture libraries were constructed from 46 patients including tumor biopsies, GW and PL pre and post-treatment (196 samples), with high vertical coverage >8,000×. At diagnosis, we detected TP53 mutations in 15/46 biopsies (32.6%), 7/46 GW- (15.2%) and 6/46 PL-samples (13%). Biopsies and GW were concordant in 38/46 cases (82.6%) for the presence/absence of mutations and, furthermore, four GW-exclusive mutations were identified, suggesting tumor heterogeneity. Considering the combined analysis of GW and PL, TP53 mutations found in biopsies were also identified in 9/15 (60%) of cases, the highest detection level reported for GAC. Our study indicates that GW could be useful to track DNA alterations, especially if anchored to a comprehensive gene-panel designed for this malignancy.

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.

A Plasmodium falciparum MORC protein complex modulates epigenetic control of gene expression through interaction with heterochromatin.

Dynamic control of gene expression is critical for blood stage development of malaria parasites. Here, we used multi-omic analyses to investigate transcriptional regulation by the chromatin-associated microrchidia protein, MORC, during asexual blood stage development of the human malaria parasite Plasmodium falciparum. We show that PfMORC (PF3D7_1468100) interacts with a suite of nuclear proteins, including APETALA2 (ApiAP2) transcription factors (PfAP2-G5, PfAP2-O5, PfAP2-I, PF3D7_0420300, PF3D7_0613800, PF3D7_1107800, and PF3D7_1239200), a DNA helicase DS60 (PF3D7_1227100), and other chromatin remodelers (PfCHD1 and PfEELM2). Transcriptomic analysis of PfMORCHA-glmS knockdown parasites revealed 163 differentially expressed genes belonging to hypervariable multigene families, along with upregulation of genes mostly involved in host cell invasion. In vivo genome-wide chromatin occupancy analysis during both trophozoite and schizont stages of development demonstrates that PfMORC is recruited to repressed, multigene families, including the var genes in subtelomeric chromosomal regions. Collectively, we find that PfMORC is found in chromatin complexes that play a role in the epigenetic control of asexual blood stage transcriptional regulation and chromatin organization.

Germline variants in early and late-onset Brazilian prostate cancer patients.

BACKGROUND: The median age for Prostate Cancer (PCa) diagnosis is 66 years, but 10% are diagnosed before 55 years. Studies on early-onset PCa remain both limited and controversial. This investigation sought to identify and characterize germline variants within Brazilian PCa patients classified as either early or later onset disease. METHODS: Peripheral blood DNA from 71 PCa patients: 18 younger (≤ 55 years) and 53 older (≥ 60 years) was used for Targeted DNA sequencing of 20 genes linked to DNA damage response, transcriptional regulation, cell cycle, and epigenetic control. Subsequent genetic variant identification was performed and variant functional impacts were analyzed with in silico prediction. RESULTS: A higher frequency of variants in the BRCA2 and KMT2C genes across both age groups. KMT2C has been linked to the epigenetic dysregulation observed during disease progression in PCa. We present the first instance of KMT2C mutation within the blood of Brazilian PCa patients. Furthermore, out of the recognized variants within the KMT2C gene, 7 were designated as deleterious. Thirteen deleterious variants were exclusively detected in the younger group, while the older group exhibited 37 variants. Within these findings, 4 novel variants emerged, including 1 designated as pathogenic. CONCLUSIONS: Our findings contribute to a deeper understanding of the genetic factors associated with PCa susceptibility in different age groups, especially among the Brazilian population. This is the first investigation to explore germline variants specifically in younger Brazilian PCa patients, with high relevance given the genetic diversity of the population in Brazil. Additionally, our work presents evidence of functionally deleterious germline variants within the KMT2C gene among Brazilian PCa patients. The identification of novel and functionally significant variants in the KMT2C gene emphasizes its potential role in PCa development and warrants further investigation.

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.

Mutational landscape of intestinal crypt cells after long-term in vivo exposure to high fat diet.

Obesity is a modifiable risk factor in cancer development, especially for gastrointestinal cancer. While the etiology of colorectal cancer is well characterized by the adenoma-carcinoma sequence, it remains unclear how obesity influences colorectal cancer development. Dietary components of a high fat diet along with obesity have been shown to modulate the cancer risk by perturbing the homeostasis of intestinal stem cells, yet how adiposity impacts the development of genomic instability has not been studied. Mutational signatures are a powerful way to understand how a complex biological response impacts genomic stability. We utilized a mouse model of diet-induced obesity to study the mutational landscape of intestinal crypt cells after a 48-week exposure to an experimental high fat diet in vivo. By clonally enriching single crypt derived cells in organoid culture and obtaining whole genome sequences, we analyzed and compared the mutational landscape of intestinal epithelial cells from normal diet and high fat diet mice. Single nucleotide substitution signatures and indel signatures present in our cohort are found equally active in both diet groups and reflect biological processes of normal aging, cellular replication, and oxidative stress induced during organoid culturing. Thus, we demonstrate that in the absence of activating mutations or chemical exposure, high fat diet alone is not sufficient to increase genomic instability.

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.

Premature ovarian insufficiency is associated with global alterations in the regulatory landscape and gene expression in balanced X-autosome translocations.

BACKGROUND: Patients with balanced X-autosome translocations and premature ovarian insufficiency (POI) constitute an interesting paradigm to study the effect of chromosome repositioning. Their breakpoints are clustered within cytobands Xq13-Xq21, 80% of them in Xq21, and usually, no gene disruption can be associated with POI phenotype. As deletions within Xq21 do not cause POI, and since different breakpoints and translocations with different autosomes lead to this same gonadal phenotype, a "position effect" is hypothesized as a possible mechanism underlying POI pathogenesis. OBJECTIVE AND METHODS: To study the effect of the balanced X-autosome translocations that result in POI, we fine-mapped the breakpoints in six patients with POI and balanced X-autosome translocations and addressed gene expression and chromatin accessibility changes in four of them. RESULTS: We observed differential expression in 85 coding genes, associated with protein regulation, multicellular regulation, integrin signaling, and immune response pathways, and 120 differential peaks for the three interrogated histone marks, most of which were mapped in high-activity chromatin state regions. The integrative analysis between transcriptome and chromatin data pointed to 12 peaks mapped less than 2 Mb from 11 differentially expressed genes in genomic regions not related to the patients' chromosomal rearrangement, suggesting that translocations have broad effects on the chromatin structure. CONCLUSION: Since a wide impact on gene regulation was observed in patients, our results observed in this study support the hypothesis of position effect as a pathogenic mechanism for premature ovarian insufficiency associated with X-autosome translocations. This work emphasizes the relevance of chromatin changes in structural variation, since it advances our knowledge of the impact of perturbations in the regulatory landscape within interphase nuclei, resulting in the position effect pathogenicity.

Immune escape of colorectal tumours via local LRH-1/Cyp11b1-mediated synthesis of immunosuppressive glucocorticoids.

Control of tumour development and growth by the immune system critically defines patient fate and survival. What regulates the escape of colorectal tumours from destruction by the immune system remains currently unclear. Here, we investigated the role of intestinal synthesis of glucocorticoids in the tumour development during an inflammation-induced mouse model of colorectal cancer. We demonstrate that the local synthesis of immunoregulatory glucocorticoids has dual roles in the regulation of intestinal inflammation and tumour development. In the inflammation phase, LRH-1/Nr5A2-regulated and Cyp11b1-mediated intestinal glucocorticoid synthesis prevents tumour development and growth. In established tumours, however, tumour-autonomous Cyp11b1-mediated glucocorticoid synthesis suppresses anti-tumour immune responses and promotes immune escape. Transplantation of glucocorticoid synthesis-proficient colorectal tumour organoids into immunocompetent recipient mice resulted in rapid tumour growth, whereas transplantation of Cyp11b1-deleted and glucocorticoid synthesis-deficient tumour organoids was characterized by reduced tumour growth and increased immune cell infiltration. In human colorectal tumours, high expression of steroidogenic enzymes correlated with the expression of other immune checkpoints and suppressive cytokines, and negatively correlated with overall patients' survival. Thus, LRH-1-regulated tumour-specific glucocorticoid synthesis contributes to tumour immune escape and represents a novel potential therapeutic target.

Prehospital blood transfusion in Brazil: results of the first year of implementation in an emergency medical service.

INTRODUCTION: Hemorrhagic shock is the main cause of death in the prehospital environment, which highlights the need to standardize measures aiming at bleeding control and volume replacement in this environment. In Brazil, the first prehospital packed red blood cell transfusion service started in September 2020, in Bragança Paulista, state of São Paulo. OBJECTIVES: Describe the trends and characteristics of patients who received prehospital transfusions prior to hospital treatment during the first year of operation. METHODS: A retrospective data review was made of all patients who received transfusions from the mobile intensive care unit in Bragança Paulista over one year. RESULTS: In this period, 19 patients were transfused. Since activation, the average response time was 20 min. The mean shock indexes before and after blood transfusion were 2.16 and 1.1, respectively. During the course of the 1st year of prehospital transfusions, no blood was wasted and there were no adverse effects. CONCLUSION: Introduction of the prehospital packed red blood cell transfusion service was successful, with significant improvement in hemodynamic parameters.

High-throughput sequencing of black pepper root transcriptome.

BACKGROUND: Black pepper (Piper nigrum L.) is one of the most popular spices in the world. It is used in cooking and the preservation of food and even has medicinal properties. Losses in production from disease are a major limitation in the culture of this crop. The major diseases are root rot and foot rot, which are results of root infection by Fusarium solani and Phytophtora capsici, respectively. Understanding the molecular interaction between the pathogens and the host's root region is important for obtaining resistant cultivars by biotechnological breeding. Genetic and molecular data for this species, though, are limited. In this paper, RNA-Seq technology has been employed, for the first time, to describe the root transcriptome of black pepper. RESULTS: The root transcriptome of black pepper was sequenced by the NGS SOLiD platform and assembled using the multiple-k method. Blast2Go and orthoMCL methods were used to annotate 10338 unigenes. The 4472 predicted proteins showed about 52% homology with the Arabidopsis proteome. Two root proteomes identified 615 proteins, which seem to define the plant's root pattern. Simple-sequence repeats were identified that may be useful in studies of genetic diversity and may have applications in biotechnology and ecology. CONCLUSIONS: This dataset of 10338 unigenes is crucially important for the biotechnological breeding of black pepper and the ecogenomics of the Magnoliids, a major group of basal angiosperms.

Human endogenous retrovirus and multiple sclerosis: A review and transcriptome findings.

Multiple Sclerosis is an autoimmune disease with an unknown etiology. Both genetic and environmental factors are believed to trigger MS autoimmunity. Among the environmental factors, infectious agents have been extensively investigated, and the Human Endogenous Retroviruses (HERVs), especially HERV-W, are believed to be associated with MS pathogenesis. HERVs are derived from ancestral infections and comprise around 8% of the human genome. Although most HERVs are silenced, retroviral genes may be expressed with virion formation. There is extensive evidence of the relationship between HERV-W and MS, including higher levels of HERV-W expression in MS patients, HERV-W protein detection in MS plaques, and the HERV-W env protein inducing an inflammatory response in in vitro and in vivo models. Here we discuss possible links of HERVs and the pathogenesis of MS and present new data regarding the diversity of HERVs expression in samples derived from MS patients.

Characterization of genetic predisposition to molecular subtypes of breast cancer in Brazilian patients.

Introduction: BRCA1 and BRCA2 germline pathogenic variants (GPVs) account for most of the 5-10% of breast cancer (BC) that is attributable to inherited genetic variants. BRCA1 GPVs are associated with the triple negative subtype, whereas BRCA2 GPVs are likely to result in higher grade, estrogen-receptor positive BCs. The contribution of other genes of high and moderate risk for BC has not been well defined and risk estimates to specific BC subtypes is lacking, especially for an admixed population like Brazilian. Objective: The aim of this study is to evaluate the value of a multigene panel in detecting germline mutations in cancer-predisposing genes for Brazilian BC patients and its relation with molecular subtypes and the predominant molecular ancestry. Patients and methods: A total of 321 unrelated BC patients who fulfilled NCCN criteria for BRCA1/2 testing between 2016-2018 were investigated with a 94-genes panel. Molecular subtypes were retrieved from medical records and ancestry-specific variants were obtained from off-target reads obtained from the sequencing data. Results: We detected 83 GPVs in 81 patients (positivity rate of 25.2%). Among GPVs, 47% (39/83) were identified in high-risk BC genes (BRCA1/2, PALB2 and TP53) and 18% (15/83) in moderate-penetrance genes (ATM, CHEK2 and RAD51C). The remainder of the GPVs (35% - 29/83), were identified in lower-risk genes. As for the molecular subtypes, triple negative BC had a mutation frequency of 31.6% (25/79), with predominance in BRCA1 (12.6%; 10/79). Among the luminal subtypes, except Luminal B HER2-positive, 18.7% (29/155) had GPV with BRCA1/2 genes contributing 7.1% (11/155) and non-BRCA1/2 genes, 12.9% (20/155). For Luminal B HER2-positive subtype, 40% (16/40) had GPVs, with a predominance of ATM gene (15% - 6/40) and BRCA2 with only 2.5% (1/40). Finally, HER2-enriched subtype presented a mutation rate of 30.8% (4/13) with contribution of BRCA2 of 7.5% (1/13) and non-BRCA1/2 of 23% (3/13). Variants of uncertain significance (VUS) were identified in 77.6% (249/321) of the patients and the number of VUS was increased in patients with Asian and Native American ancestry. Conclusion: The multigene panel contributed to identify GPVs in genes other than BRCA1/2, increasing the positivity of the genetic test from 9.6% (BRCA1/2) to 25.2% and, considering only the most clinically relevant BC predisposing genes, to 16.2%. These results indicate that women with clinical criteria for hereditary BC may benefit from a multigene panel testing, as it allows identifying GPVs in genes that directly impact the clinical management of these patients and family members.

Exome and Tissue-Associated Microbiota as Predictive Markers of Response to Neoadjuvant Treatment in Locally Advanced Rectal Cancer.

The clinical and pathological responses to multimodal neoadjuvant therapy in locally advanced rectal cancers (LARCs) remain unpredictable, and robust biomarkers are still lacking. Recent studies have shown that tumors present somatic molecular alterations related to better treatment response, and it is also clear that tumor-associated bacteria are modulators of chemotherapy and immunotherapy efficacy, therefore having implications for long-term survivorship and a good potential as the biomarkers of outcome. Here, we performed whole exome sequencing and 16S ribosomal RNA (rRNA) amplicon sequencing from 44 pre-treatment LARC biopsies from Argentinian and Brazilian patients, treated with neoadjuvant chemoradiotherapy or total neoadjuvant treatment, searching for predictive biomarkers of response (responders, n = 17; non-responders, n = 27). In general, the somatic landscape of LARC was not capable to predict a response; however, a significant enrichment in mutational signature SBS5 was observed in non-responders (p = 0.0021), as well as the co-occurrence of APC and FAT4 mutations (p < 0.05). Microbiota studies revealed a similar alpha and beta diversity of bacteria between response groups. Yet, the linear discriminant analysis (LDA) of effect size indicated an enrichment of Hungatella, Flavonifractor, and Methanosphaera (LDA score ≥3) in the pre-treatment biopsies of responders, while non-responders had a higher abundance of Enhydrobacter, Paraprevotella (LDA score ≥3) and Finegoldia (LDA score ≥4). Altogether, the evaluation of these biomarkers in pre-treatment biopsies could eventually predict a neoadjuvant treatment response, while in post-treatment samples, it could help in guiding non-operative treatment strategies.