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PubMed2002

Sharper tools and simpler methods.

In this issue of The Chipping Forecast, we are witnesses to the adolescence of a class of technologies that are enabling us to monitor globally aspects of gene expression. Chip-based technologies are specific examples of a more general trend toward the implementation of systematic and comprehensive methods in biological research. We need to recognize, however, that these technologies, while seductive, can sometimes be corruptive. In other words, we must guard against committing the mortal sin of genomics by confusing throughput with output, which too often blurs the distinction between data and knowledge. Instead, we must maintain the necessary focus to achieve an ever-more operational understanding of all the molecular components and the interactions that define a cell or an organism.

DNA, Complementary↗

PubMed2025

Oncogenic EME1 promotes tumor progression and immune modulation in human cancers with therapeutic targeting potential.

BACKGROUND: EME1, a critical DNA repair endonuclease, has emerged as a potential oncogene implicated in genome instability and cancer progression. However, its pan-cancer roles, prognostic significance, immune interactions, and therapeutic targeting remain underexplored. METHODS: We conducted a comprehensive pan-cancer analysis integrating multi-omics data from public databases, including TIMER2.0, GEPIA2, TISIDB, and cBioPortal, to evaluate EME1 expression, genetic alterations, and their association with clinical outcomes, immune infiltration, and molecular pathways. Virtual screening of 3180 FDA-approved drugs and molecular dynamics (MD) simulations were employed to identify and validate potential EME1 inhibitors. RESULTS: EME1 was significantly overexpressed in various human cancers and positively associated with advanced tumor grade and stage. High EME1 expression and mutations were linked to poor overall and disease-free survival. Immunogenomic profiling revealed strong positive correlations between EME1 and myeloid-derived suppressor cells (MDSCs), alongside a negative association with endothelial cell function, suggesting immunosuppressive roles. Machine learning models based on EME1-associated genes demonstrated high predictive accuracy for liver hepatocellular carcinoma (AUC > 0.90). Virtual screening identified eight promising drug candidates, including Everolimus and Dioscin, with strong binding affinities. MD simulations confirmed the stability of these interactions, particularly for Dioscin. CONCLUSION: This study reveals the multifaceted oncogenic roles of EME1 in tumor progression, immune evasion, and prognosis. It proposes EME1 as a promising biomarker and therapeutic target across multiple cancer types. The identified drug candidates warrant further in vitro and in vivo validation for potential repurposing in EME1-targeted cancer therapy.

EME1↗

PubMed2005

Prospects for personalized cardiovascular medicine: the impact of genomics.

Sequencing of the human genome has ushered in prospects for individualizing cardiovascular health care. There is growing evidence that the practice of cardiovascular medicine might soon have a new toolbox to predict and treat disease more effectively. The Human Genome Project has spawned several important "omic" technologies that allow "whole genome" interrogation of sequence variation (re-sequencing, genotyping, comparative genome hybridization), transcription (expression profiling, tissue arrays), proteins (gas or liquid chromatography and tandem mass spectroscopy [MS]), and metabolites (MS or nuclear magnetic resonance profiling); deoxyribonucleic acid, ribonucleic acid, protein, and metabolic approaches all provide more exacting detail of cardiovascular disease mechanisms and, in some cases, are redefining its taxonomy. Pharmacogenomic approaches are emerging across broad classes of cardiovascular therapeutics to assist practitioners in making more precise decisions about which drugs to give to which patients to optimize the benefit-to-risk ratio. Molecular imaging is developing chemical and biological probes that can sense molecular pathway mechanisms that will allow us to monitor health and disease. Together, these tools will enable a paradigm shift from genetic medicine--on the basis of the study of individual inherited characteristics, most often single genes--to genomic medicine, which by its nature is comprehensive and focuses on the functions and interactions of multiple genes and gene products, among themselves and with their environment. The information gained from such analyses, in combination with clinical data, is now allowing us to assess individual risks and guide clinical management and decision-making, all of which form the basis for cardiovascular genomic medicine.

Cardiology↗

PubMed2006

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data.

INTRODUCTION: Diverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells. METHODS: Malignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays. RESULTS: MPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours. CONCLUSION: Using highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.

Biomarkers, Tumor↗

PubMed1998

Transcriptional profiling on all open reading frames of Saccharomyces cerevisiae.

Open reading frames (6116) of the budding yeast Saccharomyces cerevisiae were PCR-amplified from genomic DNA using 12,232 primers specific to the ends of the coding sequences; the success rate of amplification was 97%. PCR-products were made accessible to hybridization by being arrayed at very high density on solid support media using various robotic devices. Probes made from total RNA preparations were hybridized for the analysis of the transcriptional activity of yeast under various growth conditions and of different strains. Experimental factors that proved critical to the performance, such as different RNA isolation procedures and the assessment of hybridization results, for example, were investigated in detail. Various software tools were developed that permit convenient handling and sound analysis of the large data quantities obtained from transcriptional profiling studies. Comprehensive arrays are being distributed within the European Yeast Functional Analysis Network (EUROFAN) and beyond.

Blotting, Western↗

PubMed2004

Quantitative genetic variation: a post-modern view.

It has become commonplace to map individual quantitative trait loci (QTL) in experimental organisms; the means (line-crosses and dense maps of markers) and motivation (the close relationship between continuous physiological traits and common, complex diseases) are self-evident. Progress in mapping human QTL has been more gradual, an inevitable consequence of genetic mapping in a natural population setting. The common objective of these studies has been to understand the molecular mechanisms underlying individual QTL. Recent theoretical and practical advances shift this focus to a more comprehensive or genomic perspective on quantitative variation. Fisher's infinitesimal model of adaptive evolution, which satisfied quantitative geneticists for over 50 years, has been modified in the light of data from QTL mapping experiments in plants and animals. The resulting exponential model provides a pleasing empirical fit to the distribution of QTL effect sizes, predicts that a large amount of quantitative variation will be explained by a limited number of genes and suggests a new mathematical framework for linkage mapping. Molecular analysis of QTL suggests that coding variants (e.g. allozymes) underlie a fraction of quantitative variation and that variants that affect gene expression (expression QTL, eQTL) have a substantial role. This is supported by genomic experiments that combine expression profiling with classical genetic mapping approaches to reveal a remarkable wealth of quantitative heritable variation in the transcriptome and that cis-and trans-acting regulatory factors are organized in networks reflecting pleiotropy. It is hoped that these advances will enhance our understanding of the genetic basis of complex inherited diseases.

Animals↗

PubMed2002

Using array hybridization to monitor gene expression at the single cell level.

Advances in high-throughput genome sequencing demand the development of more efficient ways of examining gene expression at a cellular level. During recent years, polymerase chain reaction (PCR)-based methods have been developed that allow the amplification of mRNA from small amounts of material, even from single animal cells. In parallel, several analytical tools permit a global monitoring of gene expression. To date, high throughput analysis methods have not been accessible for single plant cell samples. In the protocol described here, cDNA array hybridization (expression profiling) and an amplification strategy using reverse transcriptase PCR are merged with high spatial resolution sampling from undamaged plant tissue. This protocol gives us a new tool to examine tissue-specific gene expression patterns on a comprehensive scale. To demonstrate the usefulness of this tool, gene expression patterns in samples from Arabidopsis thaliana L. cv. C24 leaf epidermal and mesophyll cells were measured; several differentially expressed genes were identified when single cell samples were compared. The protocol described has the potential of increasing the efficiency of tissue-specific expression analysis by combining high-throughput profiling with straightforward sampling and amplification procedures.

Arabidopsis↗

PubMed1998

Comprehensive Sequence Analyses of 5' Flanking Regions of Primate Alu Elements.

Retrotransposons have been generally known to integrate randomly into host genomes. Jurka (Proc. Natl. Acad. Sci. USA 94: 1872-1877, 1977), however, showed consensus sequence patterns at integration sites of certain mammalian retrotransposons, and suggested involvement of sequence specific enzymes that mediate integration. We have conducted comprehensive sequence analyses of 5' flanking regions of primate Alu elements. In contrast to the small but clean data set Jurka (1977) used, (1) larger number of samples were used, (2) wider region of 5' end of Alu elements was analyzed, and (3) comparisons were made among different subfamilies for comprehensive analyses in order to identify characteristic sequence pattern(s) preceding 5' end of Alu elements. The nucleotide occurrences at each position within 500 bases of 5' end of Alus were counted to obtain profiles. Information content at each nucleotide position in the same region was, then, computed. Distinctive difference in the nucleotide composition and information content values that divides the region into two was observed. The region between -20 and 5' end of Alu elements is found to be highly adenine-rich and shows significantly higher information content values compared to the rest of the region, implying the existence of certain characteristic sequence pattern in this region. Also, younger subfamilies of Alu elements show higher information content values than older subfamilies. This implies that certain characteristic sequence pattern already existed in the region between -20 and 5' end of Alu elements at the time of Alu integration, and accumulation of mutation in the course of time resulted in the less distinctive sequence pattern in older sequences. Frequencies of all possible triplets (total of 64) were measured in the same region in order to identify characteristic sequence pattern(s). Observation that frequencies of triplets aaa, taa and tta in the 5' flanking sequences were high is consistent with Jurka (1977). Frequencies of some other triplets such as gaa, caa, aac, ctt, gtt, atg, etc. which do not comprise the primary candidates for the nick site in Jurka (1977) also show significantly high frequencies.

Journal Article↗

PubMed2024

Protocol to decode the role of transcriptionally active microbes in SARS-CoV-2-positive patients using an RNA-seq-based approach.

The elucidation of the role of microorganisms in human infections has been hindered by difficulties using conventional culture-based techniques. Here, we present a protocol for the investigation of transcriptionally active microbes (TAMs) using an RNA sequencing (RNA-seq)-based approach. We describe the steps for RNA isolation, viral genome sequencing, RNA-seq library preparation, and metatranscriptomic and transcriptomic analysis. This protocol permits a comprehensive evaluation of TAMs' contributions to the differential severity of infectious diseases, with a particular focus on diseases such as COVID-19. For complete details on the use and execution of this protocol, please refer to Devi et al.1.

Humans↗

PubMed2025

PATTY corrects open chromatin bias for improved bulk and single-cell CUT&Tag profiling.

Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells and at the single-cell level. With its growing adoption, CUT&Tag datasets spanning diverse biological systems are rapidly accumulating in the field. CUT&Tag assays use the hyperactive transposase Tn5 for DNA tagmentation. Tn5's preference toward accessible chromatin alters CUT&Tag sequence read distributions in the genome and introduces open chromatin bias that can confound downstream analysis, an issue more substantial in sparse single-cell data. We show that open chromatin bias extensively exists in published CUT&Tag datasets, including those generated with recently optimized high-salt protocols. To address this challenge, we present PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), a comprehensive computational method that corrects open chromatin bias in CUT&Tag data by leveraging accompanying ATAC-seq. By integrating transcriptomic and epigenomic data using machine learning and integrative modeling, we demonstrate that PATTY enables accurate and robust detection of occupancy sites for both active and repressive histone modifications, including H3K27ac, H3K27me3, and H3K9me3, with experimental validation. We further develop a single-cell CUT&Tag analysis framework built on PATTY and show improved cell clustering when using bias-corrected single-cell CUT&Tag data compared to using uncorrected data. Beyond CUT&Tag, PATTY sets a foundation for further development of bias correction methods for improving data analysis for all Tn5-based high-throughput assays.

Journal Article↗

PubMed2026

Prognostic value and immune landscape implications of using a novel homologous recombination repair pathway signature in prostate cancer: A retrospective cohort study.

ObjectiveAlthough the homologous recombination repair (HRR) pathway plays a critical role in the treatment of prostate cancer, its prognostic value remains incompletely understood. This study aimed to identify HRR pathway-related biomarkers with clinical utility for prognosis prediction and treatment guidance.MethodsWe analyzed genomic data from The Cancer Genome Atlas and Chinese patients with prostate cancer in a retrospective cohort study using a comprehensive multiomics approach to characterize a novel HRR-related prognostic signature and its immune implications.ResultsIn the Chinese cohort, 25.6% of the patients exhibited homologous recombination deficiency scores >42, whereas 27.3% carried ≥1 HRR gene mutation. We established a prognostic HRR signature (homologous recombination deficiency score >32, HRR gene mutations, and Signature 3) associated with poor outcomes. Compared with The Cancer Genome Atlas data, the Chinese cohort demonstrated a higher prevalence of HRR signature. Patients with HRR signatures demonstrated significantly increased genomic instability markers, including segment number, alteration burden, aneuploidy score, and intratumor heterogeneity. The HRR signature was associated with higher neoantigen load but reduced T cell receptor (TCR) evenness. Immunologically, HRR-positive tumors were associated with computationally inferred immune profiles suggestive of reduced immune activity, characterized by depletion of T-helper 17 cell; downregulation of TLR4/PDCD1LG2 expression; and upregulation of ARG1, IFNG, KIR2DL3, and CXCL9. However, these findings are descriptive and require experimental validation.ConclusionOur findings identify a clinically relevant HRR signature that warrants investigation as a potential predictive biomarker for prostate cancer prognosis and treatment response. This biomarker provides new insights for personalized therapy and may help optimize patient outcomes.

Humans↗

PubMed2024

Identification of miRNA expression profile in middle ear cholesteatoma using small RNA-sequencing.

BACKGROUND: The present study aims to identify the differential miRNA expression profile in middle ear cholesteatoma and explore their potential roles in its pathogenesis. METHODS: Cholesteatoma and matched normal retroauricular skin tissue samples were collected from patients diagnosed with acquired middle ear cholesteatoma. The miRNA expression profiling was performed using small RNA sequencing, which further validated by quantitative real-time PCR (qRT-PCR). Target genes of differentially expressed miRNAs in cholesteatoma were predicted. The interaction network of 5 most significantly differentially expressed miRNAs was visualized using Cytoscape. Further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses were processed to investigate the biological functions of miRNAs in cholesteatoma. RESULTS: The miRNA expression profile revealed 121 significantly differentially expressed miRNAs in cholesteatoma compared to normal skin tissues, with 56 upregulated and 65 downregulated. GO and KEGG pathway enrichment analyses suggested their significant roles in the pathogenesis of cholesteatoma. The interaction network of the the 2 most upregulated (hsa-miR-21-5p and hsa-miR-142-5p) and 3 most downregulated (hsa-miR-508-3p, hsa-miR-509-3p and hsa-miR-211-5p) miRNAs identified TGFBR2, MBNL1, and NFAT5 as potential key target genes in middle ear cholesteatoma. CONCLUSIONS: This study provides a comprehensive miRNA expression profile in middle ear cholesteatoma, which may aid in identifying therapeutic targets for its management.

Humans↗

PubMed2026

Methylation profiling in CNS tumor diagnostics: a single-centre real-world experience from Central Europe.

Genome-wide DNA methylation profiling has transformed neuro-oncology by providing an objective, machine learning-based taxonomy that mitigates interobserver variability and refines the histo-molecular criteria of the current WHO classification. We evaluate the real-world diagnostic performance and clinical utility of this modality in a prospective, consecutively accrued three-year cohort of 291 central nervous system (CNS) tumors across a mixed adult-pediatric population. Successful profiling was completed in 95.9% of cases. Using the Epignostix classifier, a high-confidence diagnostic match (calibrated score [CS] ≥ 0.84) was achieved in 70.3% of analyzable samples, while 26.5% returned lower-confidence scores (≥ 0.3 to < 0.84) and only 3.2% remained completely unclassifiable (CS < 0.3). When integrated into a comprehensive diagnostic framework, methylation profiling provided clinically useful results in 81.1% of cases, establishing diagnoses in 70 cases submitted for molecular subclassification and resolving diagnostic uncertainty or prompting major revisions in 149 histologically challenging tumors. Within truly ambiguous lesions, integration of methylome data dictated tumor grade modifications in 38.8% of cases (upgrading in 29.4% and downgrading in 9.4%), shifting patient risk stratification. Crucially, over half (52.7%) of the lower-confidence cases yielded meaningful clinical integration when supported by histomorphology and ancillary genetic or immunohistochemical markers, demonstrating that rigid score cutoffs should not dictate assay failure. Discrepant or misleading classifications occurred in 1.9%. Updating bioinformatic pipelines from version 11b4 to 12.8 rescued multiple ambiguous entries, increasing overall clinical utility to 84.1%. These findings demonstrate that integrating computational epigenomics with classical neuropathology enhances diagnostic precision, while highlighting the ongoing need for careful clinical-pathological correlation.

Central nervous system tumors↗

PubMed2025

PATTY corrects open-chromatin bias for improved bulk and single-cell CUT&Tag profiling.

Precise profiling of epigenomes is essential for better understanding chromatin biology and gene regulation. Cleavage Under Targets & Tagmentation (CUT&Tag) is an efficient epigenomic profiling technique that can be performed on a low number of cells and at the single-cell level. With its growing adoption, CUT&Tag datasets spanning diverse biological systems are rapidly accumulating in the field. CUT&Tag assays use the hyperactive transposase Tn5 for DNA tagmentation. Tn5's preference toward accessible chromatin alters CUT&Tag sequence read distributions in the genome and introduces open-chromatin bias that can confound downstream analysis, an issue more substantial in sparse single-cell data. We show that open-chromatin bias extensively exists in published CUT&Tag datasets, including those generated with recently optimized high-salt protocols. To address this challenge, we present PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), a comprehensive computational method that corrects open-chromatin bias in CUT&Tag data by leveraging accompanying ATAC-seq. By integrating transcriptomic and epigenomic data using machine learning and integrative modeling, we demonstrate that PATTY enables accurate and robust detection of occupancy sites for both active and repressive histone modifications, including H3K27ac, H3K27me3, and H3K9me3, with experimental validation. We further develop a single-cell CUT&Tag analysis framework built on PATTY and show improved cell clustering when using bias-corrected single-cell CUT&Tag data compared to using uncorrected data. Beyond CUT&Tag, PATTY sets a foundation for further development of bias correction methods for improving data analysis for all Tn5-based high-throughput assays.

Journal Article↗

PubMed2006

Comparison of gene expression profiles among papilla, medulla and cortex in rat kidney.

The aim of this study was to compare gene expression profiles in the different kidney regions as the basis for toxicogenomics. Rat kidney was separated into papilla, medulla and cortex, and total RNA was isolated from these and from the whole slice. Gene expression profiling was performed using Affymetrix Rat Genome 230 2.0 Array. When global normalization was applied, the expression of beta-actin or GAPDH varied among the regions. It was considered that such a comparison could not be made, especially between papilla and other portions, since the production of total mRNA in the former was relatively low. In fact, ANOVA was performed on the gene expression values with global normalization in papilla, medulla, cortex, and whole slice, and the numbers of genes appeared to be the highest in papilla. It was also observed that many genes showed their maximum or minimum in the whole slice, which was theoretically impossible. To overcome the problems associated with global normalization, the "percellome" normalization (a way to obtain the values directly related to the copies of mRNA per cell) was employed to compare the regions. In applying this procedure, probe sets with regional difference in expression were efficiently extracted by ANOVA. When they were sorted by the fold difference to other regions, the higher rank was occupied by genes characteristic of the functions of kidney, i.e., channels, transporters and metabolic enzymes. Some of them were consistent with the literature and were related to pathophysiological phenomena. Comprehensive comparison of data of gene expression in the renal anatomical area will greatly enhance studies of the physiological function and mechanism of toxicity in kidney.

Animals↗

PubMed2003

Millions of years of evolution preserved: a comprehensive catalog of the processed pseudogenes in the human genome.

Processed pseudogenes were created by reverse-transcription of mRNAs; they provide snapshots of ancient genes existing millions of years ago in the genome. To find them in the present-day human, we developed a pipeline using features such as intron-absence, frame-disruption, polyadenylation, and truncation. This has enabled us to identify in recent genome drafts approximately 8000 processed pseudogenes (distributed from http://pseudogene.org). Overall, processed pseudogenes are very similar to their closest corresponding human gene, being 94% complete in coding regions, with sequence similarity of 75% for amino acids and 86% for nucleotides. Their chromosomal distribution appears random and dispersed, with the numbers on chromosomes proportional to length, suggesting sustained "bombardment" over evolution. However, it does vary with GC-content: Processed pseudogenes occur mostly in intermediate GC-content regions. This is similar to Alus but contrasts with functional genes and L1-repeats. Pseudogenes, moreover, have age profiles similar to Alus. The number of pseudogenes associated with a given gene follows a power-law relationship, with a few genes giving rise to many pseudogenes and most giving rise to few. The prevalence of processed pseudogenes agrees well with germ-line gene expression. Highly expressed ribosomal proteins account for approximately 20% of the total. Other notables include cyclophilin-A, keratin, GAPDH, and cytochrome c.

Animals↗

PubMed2001

Global analysis of the general stress response of Bacillus subtilis.

Gene arrays containing all currently known open reading frames of Bacillus subtilis were used to examine the general stress response of Bacillus. By proteomics, transcriptional analysis, transposon mutagenesis, and consensus promoter-based screening, 75 genes had previously been described as sigma(B)-dependent general stress genes. The present gene array-based analysis confirmed 62 of these already known general stress genes and detected 63 additional genes subject to control by the stress sigma factor sigma(B). At least 24 of these 125 sigma(B)-dependent genes seemed to be subject to a second, sigma(B)-independent stress induction mechanism. Therefore, this transcriptional profiling revealed almost four times as many regulon members as the proteomic approach, but failure of confirmation of all known members of the sigma(B) regulon indicates that even this approach has not yet elucidated the entire regulon. Most of the sigma(B)-dependent general stress proteins are probably located in the cytoplasm, but 25 contain at least one membrane-spanning domain, and at least 6 proteins appear to be secreted. The functions of most of the newly described genes are still unknown. However, their classification as sigma(B)-dependent stress genes argues that their products most likely perform functions in stress management and help to provide the nongrowing cell with multiple stress resistance. A comprehensive screening program analyzing the multiple stress resistance of mutants with mutations in single stress genes is in progress. The first results of this program, showing the diminished salt resistance of yjbC and yjbD mutants compared to that of the wild type, are presented. Only a few new sigma(B)-dependent proteins with already known functions were found, among them SodA, encoding a superoxide dismutase. In addition to analysis of the sigma(B)-dependent general stress regulon, a comprehensive list of genes induced by heat, salt, or ethanol stress in a sigma(B)-independent manner is presented. Perhaps the most interesting of the sigma(B)-independent stress phenomena was the induction of the extracytoplasmic function sigma factor sigma(W) and its entire regulon by salt shock.

Bacillus subtilis↗

PubMed2024

Comprehensive Assessment of the Intrinsic Pancreatic Microbiome.

OBJECTIVE: To sought comprehensively profile tissue and cyst fluid in patients with benign, precancerous, and cancerous conditions of the pancreas to characterize the intrinsic pancreatic microbiome. BACKGROUND: Small studies in pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasm (IPMN) have suggested that intrapancreatic microbial dysbiosis may drive malignant transformation. METHODS: Pancreatic samples were collected at the time of resection from 109 patients. Samples included tumor tissue (control, n = 20; IPMN, n = 20; PDAC, n = 19) and pancreatic cyst fluid (IPMN, n = 30; serous cystadenomas, n = 10; mucinous cystic neoplasm, n = 10). Assessment of bacterial DNA by quantitative polymerase chain reaction and 16S ribosomal RNA gene sequencing was performed. Downstream analyses determined the relative abundances of individual taxa between groups and compared intergroup diversity. Whole-genome sequencing data from 140 patients with PDAC in the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium were analyzed to validate findings. RESULTS: Sequencing of pancreatic tissue yielded few microbial reads regardless of diagnosis, and analysis of pancreatic tissue showed no difference in the abundance and composition of bacterial taxa between normal pancreas, IPMN, or PDAC groups. Low-grade and high-grade dysplasia IPMN were characterized by low bacterial abundances with no difference in tissue composition and a slight increase in Pseudomonas and Sediminibacterium in high-grade dysplasia cyst fluid. Decontamination analysis using the Clinical Proteomic Tumor Analysis Consortium database confirmed a low-biomass, low-diversity intrinsic pancreatic microbiome that did not differ by pathology. CONCLUSIONS: Our analysis of the pancreatic microbiome demonstrated very low intrinsic biomass that is relatively conserved across diverse neoplastic conditions and thus unlikely to drive malignant transformation.

Humans↗