Volatilomic profiles of gastric juice in gastric cancer patients.

Volatilomics is a powerful tool capable of providing novel biomarkers for the diagnosis of gastric cancer. The main objective of this study was to characterize the volatilomic signatures of gastric juice in order to identify potential alterations induced by gastric cancer. Gas chromatography with mass spectrometric detection, coupled with headspace solid phase microextraction as the pre-concentration technique, was used to identify volatile organic compounds (VOCs) released by gastric juice samples collected from 78 gastric cancer patients and two cohorts of controls (80 and 96 subjects) from four different locations (Latvia, Ukraine, Brazil, and Colombia). 1440 distinct compounds were identified in samples obtained from patients and 1422 in samples provided by controls. However, only 6% of the VOCs exhibited an incidence higher than 20%. Amongst the volatiles emitted, 18 showed differences in their headspace concentrations above gastric juice of cancer patients and controls. Ten of these (1-propanol, 2,3-butanedione, 2-pentanone, benzeneacetaldehyde, 3-methylbutanal, butylated hydroxytoluene, 2-pentyl-furan, 2-ethylhexanal, 2-methylpropanal and phenol) appeared at significantly higher levels in the headspace of the gastric juice samples obtained from patients; whereas, eight species showed lower abundance in patients than found in controls. Given that the difference in the volatilomic signatures can be explained by cancer-related changes in the activity of certain enzymes or pathways, the former set can be considered potential biomarkers for gastric cancer, which may assist in developing non-invasive breath tests for the diagnosis of this disease. Further studies are required to elucidate further the mechanisms that underlie the changes in the volatilomic profile as a result of gastric cancer.

Fusion Cell Markers in Circulating Tumor Cells from Patients with High-Grade Ovarian Serous Carcinoma.

Cancer is primarily a disease in which late diagnosis is linked to poor prognosis, and unfortunately, detection and management are still challenging. Circulating tumor cells (CTCs) are a potential resource to address this disease. Cell fusion, an event discovered recently in CTCs expressing carcinoma and leukocyte markers, occurs when ≥2 cells become a single entity (hybrid cell) after the merging of their plasma membranes. Cell fusion is still poorly understood despite continuous evaluations in in vitro/in vivo studies. Blood samples from 14 patients with high-grade serous ovarian cancer (A.C. Camargo Cancer Center, São Paulo, Brazil) were collected with the aim to analyze the CTCs/hybrid cells and their correlation to clinical outcome. The EDTA collected blood (6 mL) from patients was used to isolate/identify CTCs/hybrid cells by ISET. We used markers with possible correlation with the phenomenon of cell fusion, such as MC1-R, EpCAM and CD45, as well as CEN8 expression by CISH analysis. Samples were collected at three timepoints: baseline, after one month (first follow-up) and after three months (second follow-up) of treatment with olaparib (total sample = 38). Fourteen patients were included and in baseline and first follow-up all patients showed at least one CTC. We found expression of MC1-R, EpCAM and CD45 in cells (hybrid) in at least one of the collection moments. Membrane staining with CD45 was found in CTCs from the other cohort, from the other center, evaluated by the CellSearch® system. The presence of circulating tumor microemboli (CTM) in the first follow-up was associated with a poor recurrence-free survival (RFS) (5.2 vs. 12.2 months; p = 0.005). The MC1-R expression in CTM in the first and second follow-ups was associated with a shorter RFS (p = 0.005). CEN8 expression in CTCs was also related to shorter RFS (p = 0.035). Our study identified a high prevalence of CTCs in ovarian cancer patients, as well as hybrid cells. Both cell subtypes demonstrate utility in prognosis and in the assessment of response to treatment. In addition, the expression of MC1-R and EpCAM in hybrid cells brings new perspectives as a possible marker for this phenomenon in ovarian cancer.

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.

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.

Deep Learning Predicts Underlying Features on Pathology Images with Therapeutic Relevance for Breast and Gastric Cancer.

DNA repair deficiency (DRD) is an important driver of carcinogenesis and an efficient target for anti-tumor therapies to improve patient survival. Thus, detection of DRD in tumors is paramount. Currently, determination of DRD in tumors is dependent on wet-lab assays. Here we describe an efficient machine learning algorithm which can predict DRD from histopathological images. The utility of this algorithm is demonstrated with data obtained from 1445 cancer patients. Our method performs rather well when trained on breast cancer specimens with homologous recombination deficiency (HRD), AUC (area under curve) = 0.80. Results for an independent breast cancer cohort achieved an AUC = 0.70. The utility of our method was further shown by considering the detection of mismatch repair deficiency (MMRD) in gastric cancer, yielding an AUC = 0.81. Our results demonstrate the capacity of our learning-base system as a low-cost tool for DRD detection.

A comparison between SOLiD 5500XLand Ion Torrent PGM-derived miRNA expression profiles in two breast cell lines.

Next-generation sequencing (NGS) platforms allow the analysis of hundreds of millions of molecules in a single sequencing run, revolutionizing many research areas. NGS-based microRNA studies enable expression quantification in unprecedented scale without the limitations of closed-platforms. Yet, whereas a massive amount of data produced by these platforms is available, comparisons of quantification/discovery capabilities between platforms are still lacking. Here we compare two NGS-platforms: SOLiD and PGM, by evaluating their microRNA identification/quantification capabilities using two breast-derived cell-lines. A high expression correlation (R2 > 0.9) was achieved, encompassing 97% of the miRNAs, and the few discrepancies in miRNA counts were attributable to molecules that have very low expression. Quantification divergences indicative of artefactual representation were seen for 14 miRNAs (higher in SOLiD-reads) and another 10 miRNAs more abundant in PGM-data. An inspection of these revealed an increased and statistically significant count of uracyls and uracyl-stretches for PGM-enriched miRNAs, compared to SOLiD and to the miRBase. In parallel, adenines and adenine-stretches were enriched for SOLiDderived miRNA reads. We conclude that, whereas both platforms are overall consistent and can be used interchangeably for microRNA expression studies, particular sequence features appear to be indicative of specific platform bias, and their presence in microRNAs should be considered for database-analyses.

Suicide journey of H. pylori through gastric carcinogenesis: the role of non-H. pylori microbiome and potential consequences for clinical practice.

Despite being one of the most studied cancer-related infections, the relationship between Helicobacter pylori infection and gastric adenocarcinoma (GC) remains, in some points, obscure. Based on a critical analysis of the available literature regarding stomach microbiota, we aimed to shed light to a possible new interpretation of the current understanding about the Helicobacter pylori-related GC carcinogenesis. We analyzed data from the literature on Helicobacter pylori and other potential carcinogenic pathogens, in both benignant conditions and gastric adenocarcinoma. Helicobacter pylori is the dominant microorganism in benignant conditions as non-complicated gastritis. In atrophic gastritis, metaplasia and, mainly, in gastric adenocarcinoma, a strong reduction in Helicobacter pylori abundance, and increased occurrence of other microorganisms is strongly demonstrated by metagenomic experiments. While causing peptic disease and keeping the stomach's high acidity, Helicobacter pylori infection avoids gastric infection by carcinogenic intestinal microbiota. Nevertheless, Helicobacter pylori persistence may also provoke an atrophic gastritis, a condition that causes its own decline, due to a microenvironment modification, including reduced acidity, resulting in Helicobacter pylori substitution by a cancer-prone microbiota. This new interpretation might result in a dramatic modification on clinical management of Helicobacter pylori-related gastric disease.

The Potential Clinical Implications of Circulating Tumor Cells and Circulating Tumor Microemboli in Gastric Cancer.

BACKGROUND: Gastric adenocarcinoma (GAC) is the third deadliest malignant neoplasm worldwide, mostly because of late disease diagnosis, low chemotherapy response rates, and an overall lack of tumor biology understanding. Therefore, tools for prognosis and prediction of treatment response are needed. Quantification of circulating tumor cells (CTCs) and circulating tumor microemboli (CTM) and their expression of biomarkers has potential clinical relevance. Our aim was to evaluate CTCs and CTM and their expression of HER2 and plakoglobin in patients with nonmetastatic GAC, correlating the findings to clinicopathological data. MATERIALS AND METHODS: CTC enrichment was performed with isolation by size of epithelial tumor cells, and the analysis was performed with immunocytochemistry and microscopy. Two collections were made: one at diagnosis (55 samples before neoadjuvant treatment) and one after surgery and before adjuvant therapy (33 samples). RESULTS: A high detection rate of CTCs (90%) was observed at baseline. We evaluated HER2 expression in 45/55 biopsy samples and in 42/55 CTC samples, with an overlap of 36 subjects. Besides the good agreement observed for HER2 expression in primary tumors and paired CTCs for 36 cases (69.4%; κ = 0.272), the analysis of HER2 in CTCs showed higher positivity (43%) compared with primary tumors (11%); 3/5 patients with disease progression had HER2-negative primary tumors but HER2-positive CTCs. A significant CTC count drop in follow-up was seen for CTC-HER2-positive cases (4.45 to 1.0 CTCs per mL) compared with CTC-HER2-negative cases (2.6 to 1.0 CTCs per mL). The same was observed for CTC-plakoglobin-positive cases (2.9 to 1.25 CTCs per mL). CONCLUSION: CTC analysis, including their levels, plakoglobin, and HER2 expression, appears to be a promising tool in the understanding the biology and prognosis of GAC. IMPLICATIONS FOR PRACTICE: The analysis of circulating tumor cell levels from the blood of patients with gastric adenocarcinoma, before and after neoadjuvant treatment, is useful to better understand the behavior of the disease as well as the patients more likely to respond to treatment.

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.

Exome sequencing of multiple-sclerosis patients and their unaffected first-degree relatives.

OBJECTIVES: The understanding of complex multifactorial diseases requires the availability of a variety of data for a large-number of affected individuals. In this data note here we provide whole exome sequencing data from a set of non-familiar multiple-sclerosis (MS) patients as well as their unaffected first-degree relatives. This data might help the identification of genomic alterations, including single nucleotide polymorphisms, de novo variations and structural genomic variations, such as copy-number alterations that may impact this disease. DATA DESCRIPTION: This dataset comprises the full exome of 28 Brazilian subjects grouped in eight distinct families, consisting of four complete trios (mother-patient-father) plus another four complete trios with one added unaffected sibling. In total, we present the full exome data of eight patients diagnosed with recurrent remittent multiple sclerosis. Diagnoses were made by experienced neurologists and all enrolled patients had at least 5 years of follow up and specific MS treatment. Exomes were sequenced from leukocyte-derived DNA, after the capture of exons using biotinylated probes, in the Ion Proton platform. For each exome we generated an average of 66.1 million good quality mapped reads with an average length of ~ 160nt. On average, for 90% of the exome a vertical coverage above 20× was reached.

Linear mRNA amplification approach for RNAseq from limited amount of RNA.

Whole-transcriptome evaluation by next-generation sequencing (NGS) has been widely applied in the investigation of diverse transcriptional scenarios. In many clinical situations, including needle biopsy samples or laser microdissected cells, limited amounts of RNA are usually available for the assessment of the whole transcriptome. Here, we describe an mRNA amplification protocol based on in vitro T7 transcription for transcriptome evaluation by NGS. Initially, we performed RNAseq from two human mammary epithelial cell lines and evaluated several aspects of the transcriptomes generated by linear amplification of Poly (A)(+) mRNA species, including transcript representation, variability and abundance. Our protocol showed to be efficient with respect to full-length transcript coverage and quantitative expression levels. We then evaluated the applicability of using this protocol in a more realistic research scenario, analyzing tumor tissue samples microdissected by laser capture. In order to increase the quantification power of the libraries only the 3' end of transcripts were sequenced. We found highly reproducible RNAseq data among amplified tumor samples, with a median Spearman's correlation of 80%, strongly suggesting that the amplification step and library protocol preparation lead to a consistent transcriptional profile. Altogether, we established a robust protocol for assessing the polyadenylated transcriptome derived from limited amounts of total RNA that is applicable to all NGS platforms.

Alcohol and tobacco consumption affects bacterial richness in oral cavity mucosa biofilms.

BACKGROUND: Today there are more than 2 billion alcohol users and about 1.3 billion tobacco users worldwide. The chronic and heavy use of these two substances is at the heart of numerous diseases and may wreak havoc on the human oral microbiome. This study delves into the changes that alcohol and tobacco may cause on biofilms of the human oral microbiome. To do so, we used swabs to sample the oral biofilm of 22 subjects; including 9 control-individuals with no or very low consumption of alcohol and no consumption of tobacco, 7 who were chronic and heavy users of both substances and 6 active smokers that reported no significant alcohol consumption. DNA was extracted from swabs and the V1 region of the 16S rRNA gene was PCR amplified and sequenced using the Ion Torrent PGM platform, generating 3.7 million high quality reads. DNA sequences were clustered and OTUs were assigned using the ARB SILVA database and Qiime. RESULTS: We found no differences in species diversity and evenness among the groups. However, we found a significant decrease in species richness in only smokers and in smokers/drinkers when compared to controls. We found that Neisseria abundance was significantly decreased in both groups when compared to controls. Smokers had significant increases in Prevotella and Capnocytophaga and reductions in Granulicatella, Staphylococcus, Peptostreptococcus and Gemella when compared to the two other groups. Controls showed higher abundance of Aggregibacter, whilst smokers/drinkers had lower abundances of Fusobacteria. Samples from only smokers clustered closer together than to controls and smokers/drinkers, and also had a significant reduction in inter-group dissimilarity distances, indicating a more homogenous group than controls. CONCLUSIONS: Our results indicate that the continued use of tobacco or alcohol plus tobacco significantly reduces bacterial richness, which apparently leads to a reduction in inter-group variability, turning the respective biofilms into a more homogenous microenvironment in terms of bacterial community composition, with possible consequences for human oral diseases.

Poly (A)+ transcriptome assessment of ERBB2-induced alterations in breast cell lines.

We report the first quantitative and qualitative analysis of the poly (A)⁺ transcriptome of two human mammary cell lines, differentially expressing (human epidermal growth factor receptor) an oncogene over-expressed in approximately 25% of human breast tumors. Full-length cDNA populations from the two cell lines were digested enzymatically, individually tagged according to a customized method for library construction, and simultaneously sequenced by the use of the Titanium 454-Roche-platform. Comprehensive bioinformatics analysis followed by experimental validation confirmed novel genes, splicing variants, single nucleotide polymorphisms, and gene fusions indicated by RNA-seq data from both samples. Moreover, comparative analysis showed enrichment in alternative events, especially in the exon usage category, in ERBB2 over-expressing cells, data indicating regulation of alternative splicing mediated by the oncogene. Alterations in expression levels of genes, such as LOX, ATP5L, GALNT3, and MME revealed by large-scale sequencing were confirmed between cell lines as well as in tumor specimens with different ERBB2 backgrounds. This approach was shown to be suitable for structural, quantitative, and qualitative assessment of complex transcriptomes and revealed new events mediated by ERBB2 overexpression, in addition to potential molecular targets for breast cancer that are driven by this oncogene.

Large-scale transcriptome analyses reveal new genetic marker candidates of head, neck, and thyroid cancer.

A detailed genome mapping analysis of 213,636 expressed sequence tags (EST) derived from nontumor and tumor tissues of the oral cavity, larynx, pharynx, and thyroid was done. Transcripts matching known human genes were identified; potential new splice variants were flagged and subjected to manual curation, pointing to 788 putatively new alternative splicing isoforms, the majority (75%) being insertion events. A subset of 34 new splicing isoforms (5% of 788 events) was selected and 23 (68%) were confirmed by reverse transcription-PCR and DNA sequencing. Putative new genes were revealed, including six transcripts mapped to well-studied chromosomes such as 22, as well as transcripts that mapped to 253 intergenic regions. In addition, 2,251 noncoding intronic RNAs, eventually involved in transcriptional regulation, were found. A set of 250 candidate markers for loss of heterozygosis or gene amplification was selected by identifying transcripts that mapped to genomic regions previously known to be frequently amplified or deleted in head, neck, and thyroid tumors. Three of these markers were evaluated by quantitative reverse transcription-PCR in an independent set of individual samples. Along with detailed clinical data about tumor origin, the information reported here is now publicly available on a dedicated Web site as a resource for further biological investigation. This first in silico reconstruction of the head, neck, and thyroid transcriptomes points to a wealth of new candidate markers that can be used for future studies on the molecular basis of these tumors. Similar analysis is warranted for a number of other tumors for which large EST data sets are available.

Caracterização de novos genes humanos envolvidos no processo de regulação da expressão de genes homeóticos / Characterization of new human genes involved in the process of regulation of the expression of homeotic genes

A identidade na segmentação do corpo de diversos organismos, durante o desenvolvimento, é devida, em grande parte, à ação das proteínas homeóticas. Em especial, dois grupos de proteínas, Trithorax (trxG) e Polycomb (PcG) têm um papel fundamental na manutenção, respectivamente, da ativação e da repressão da transcrição gênica, associando-se à cromatina. A importância das PcG nos estimulou a buscar a caracterização das proteínas humanas ortólogas ao Enhancer of Polycomb (Epc) de Drosophila, até então não descritas no genoma humano. Para tanto, buscamos: ­ obter a seqüência completa e mapear o cDNA do novo gene humano homólogo ao Enhancer of Polycomb de Drosophila; ­ analisar sua expressão em tecidos fetais, adultos e tumorais e fazer estudos buscando sua caracterização funcional...