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Genome Biology Jun 2024Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data...
BACKGROUND
Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome.
RESULTS
While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395).
CONCLUSIONS
NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.
Topics: Humans; DNA Copy Number Variations; High-Throughput Nucleotide Sequencing; Software; Neoplasms; Computational Biology; Loss of Heterozygosity; Diploidy; Genome, Human; Cell Line, Tumor; Reproducibility of Results; Sequence Analysis, DNA
PubMed: 38902799
DOI: 10.1186/s13059-024-03294-8 -
Respiratory Research Jun 2024Lower respiratory tract infections(LRTIs) in adults are complicated by diverse pathogens that challenge traditional detection methods, which are often slow and...
A single-center, retrospective study of hospitalized patients with lower respiratory tract infections: clinical assessment of metagenomic next-generation sequencing and identification of risk factors in patients.
INTRODUCTION
Lower respiratory tract infections(LRTIs) in adults are complicated by diverse pathogens that challenge traditional detection methods, which are often slow and insensitive. Metagenomic next-generation sequencing (mNGS) offers a comprehensive, high-throughput, and unbiased approach to pathogen identification. This retrospective study evaluates the diagnostic efficacy of mNGS compared to conventional microbiological testing (CMT) in LRTIs, aiming to enhance detection accuracy and enable early clinical prediction.
METHODS
In our retrospective single-center analysis, 451 patients with suspected LRTIs underwent mNGS testing from July 2020 to July 2023. We assessed the pathogen spectrum and compared the diagnostic efficacy of mNGS to CMT, with clinical comprehensive diagnosis serving as the reference standard. The study analyzed mNGS performance in lung tissue biopsies and bronchoalveolar lavage fluid (BALF) from cases suspected of lung infection. Patients were stratified into two groups based on clinical outcomes (improvement or mortality), and we compared clinical data and conventional laboratory indices between groups. A predictive model and nomogram for the prognosis of LRTIs were constructed using univariate followed by multivariate logistic regression, with model predictive accuracy evaluated by the area under the ROC curve (AUC).
RESULTS
(1) Comparative Analysis of mNGS versus CMT: In a comprehensive analysis of 510 specimens, where 59 cases were concurrently collected from lung tissue biopsies and BALF, the study highlights the diagnostic superiority of mNGS over CMT. Specifically, mNGS demonstrated significantly higher sensitivity and specificity in BALF samples (82.86% vs. 44.42% and 52.00% vs. 21.05%, respectively, p < 0.001) alongside greater positive and negative predictive values (96.71% vs. 79.55% and 15.12% vs. 5.19%, respectively, p < 0.01). Additionally, when comparing simultaneous testing of lung tissue biopsies and BALF, mNGS showed enhanced sensitivity in BALF (84.21% vs. 57.41%), whereas lung tissues offered higher specificity (80.00% vs. 50.00%). (2) Analysis of Infectious Species in Patients from This Study: The study also notes a concerning incidence of lung abscesses and identifies Epstein-Barr virus (EBV), Fusobacterium nucleatum, Mycoplasma pneumoniae, Chlamydia psittaci, and Haemophilus influenzae as the most common pathogens, with Klebsiella pneumoniae emerging as the predominant bacterial culprit. Among herpes viruses, EBV and herpes virus 7 (HHV-7) were most frequently detected, with HHV-7 more prevalent in immunocompromised individuals. (3) Risk Factors for Adverse Prognosis and a Mortality Risk Prediction Model in Patients with LRTIs: We identified key risk factors for poor prognosis in lower respiratory tract infection patients, with significant findings including delayed time to mNGS testing, low lymphocyte percentage, presence of chronic lung disease, multiple comorbidities, false-negative CMT results, and positive herpesvirus affecting patient outcomes. We also developed a nomogram model with good consistency and high accuracy (AUC of 0.825) for predicting mortality risk in these patients, offering a valuable clinical tool for assessing prognosis.
CONCLUSION
The study underscores mNGS as a superior tool for lower respiratory tract infection diagnosis, exhibiting higher sensitivity and specificity than traditional methods.
Topics: Humans; Retrospective Studies; Male; Female; Middle Aged; High-Throughput Nucleotide Sequencing; Metagenomics; Respiratory Tract Infections; Risk Factors; Aged; Adult; Bronchoalveolar Lavage Fluid; Hospitalization; Predictive Value of Tests
PubMed: 38902783
DOI: 10.1186/s12931-024-02887-y -
Journal of Translational Medicine Jun 2024Infectious meningitis/encephalitis (IM) is a severe neurological disease that can be caused by bacterial, viral, and fungal pathogens. IM suffers high morbidity,...
BACKGROUND
Infectious meningitis/encephalitis (IM) is a severe neurological disease that can be caused by bacterial, viral, and fungal pathogens. IM suffers high morbidity, mortality, and sequelae in childhood. Metagenomic next-generation sequencing (mNGS) can potentially improve IM outcomes by sequencing both pathogen and host responses and increasing the diagnosis accuracy.
METHODS
Here we developed an optimized mNGS pipeline named comprehensive mNGS (c-mNGS) to monitor DNA/RNA pathogens and host responses simultaneously and applied it to 142 cerebrospinal fluid samples. According to retrospective diagnosis, these samples were classified into three categories: confirmed infectious meningitis/encephalitis (CIM), suspected infectious meningitis/encephalitis (SIM), and noninfectious controls (CTRL).
RESULTS
Our pipeline outperformed conventional methods and identified RNA viruses such as Echovirus E30 and etiologic pathogens such as HHV-7, which would not be clinically identified via conventional methods. Based on the results of the c-mNGS pipeline, we successfully detected antibiotic resistance genes related to common antibiotics for treating Escherichia coli, Acinetobacter baumannii, and Group B Streptococcus. Further, we identified differentially expressed genes in hosts of bacterial meningitis (BM) and viral meningitis/encephalitis (VM). We used these genes to build a machine-learning model to pinpoint sample contaminations. Similarly, we also built a model to predict poor prognosis in BM.
CONCLUSIONS
This study developed an mNGS-based pipeline for IM which measures both DNA/RNA pathogens and host gene expression in a single assay. The pipeline allows detecting more viruses, predicting antibiotic resistance, pinpointing contaminations, and evaluating prognosis. Given the comparable cost to conventional mNGS, our pipeline can become a routine test for IM.
Topics: Humans; Prognosis; Child; Encephalitis; Child, Preschool; Meningitis, Bacterial; Male; Female; Metagenomics; Infant; High-Throughput Nucleotide Sequencing; RNA
PubMed: 38902725
DOI: 10.1186/s12967-024-05370-w -
BMC Cancer Jun 2024To explore challenges of liquid-based cytology (LBC) specimens for next-generation sequencing (NGS) in lung adenocarcinoma and evaluate the efficacy of targeted therapy.
BACKGROUND
To explore challenges of liquid-based cytology (LBC) specimens for next-generation sequencing (NGS) in lung adenocarcinoma and evaluate the efficacy of targeted therapy.
METHODS
A retrospective analysis was conducted on the NGS test of 357 cases of advanced lung adenocarcinoma LBC specimens and compared with results of histological specimens to assess the consistency. The impact of tumor cellularity on NGS test results was evaluated. The utility of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) was collected. Clinical efficacy evaluation was performed and survival curve analysis was conducted using the Kaplan-Meier method.
RESULTS
There were 275 TKI-naive and 82 TKI-treated specimens, the mutation rates of cancer-related genes detected in both groups were similar (86.2% vs. 86.6%). The EGFR mutation rate in the TKI treated group was higher than that in the TKI-naive group (69.5% > 54.9%, P = 0.019). There was no significant difference in the EGFR mutation frequency among different tumor cellularity in the TKI-naive group. However, in the TKI treated group, the frequency of EGFR sensitizing mutation and T790M resistance mutation in specimens with < 20% tumor cellularity was significantly lower than that in specimens with ≥ 20% tumor cellularity. Among 22 cases with matched histological specimens, 72.7% (16/22) of LBC specimens were completely consistent with results of histological specimens. Among 92 patients with EGFR-mutant lung adenocarcinoma treated with EGFR-TKIs in the two cohorts, 88 cases experienced progression, and the median progression-free survival (PFS) was 12.1 months.
CONCLUSIONS
Cytological specimens are important sources for gene detection of advanced lung adenocarcinoma. When using LBC specimens for molecular testing, it is recommended to fully evaluate the tumor cellularity of the specimens.
Topics: Humans; Adenocarcinoma of Lung; Female; High-Throughput Nucleotide Sequencing; Male; Middle Aged; Retrospective Studies; Aged; Lung Neoplasms; ErbB Receptors; Protein Kinase Inhibitors; Molecular Targeted Therapy; Mutation; Adult; Liquid Biopsy; Aged, 80 and over; Biomarkers, Tumor; Cytology
PubMed: 38902688
DOI: 10.1186/s12885-024-12520-2 -
Nature Communications Jun 2024While myelodysplastic syndromes with del(5q) (del(5q) MDS) comprises a well-defined hematological subgroup, the molecular basis underlying its origin remains unknown....
While myelodysplastic syndromes with del(5q) (del(5q) MDS) comprises a well-defined hematological subgroup, the molecular basis underlying its origin remains unknown. Using single cell RNA-seq (scRNA-seq) on CD34 progenitors from del(5q) MDS patients, we have identified cells harboring the deletion, characterizing the transcriptional impact of this genetic insult on disease pathogenesis and treatment response. Interestingly, both del(5q) and non-del(5q) cells present similar transcriptional lesions, indicating that all cells, and not only those harboring the deletion, may contribute to aberrant hematopoietic differentiation. However, gene regulatory network (GRN) analyses reveal a group of regulons showing aberrant activity that could trigger altered hematopoiesis exclusively in del(5q) cells, pointing to a more prominent role of these cells in disease phenotype. In del(5q) MDS patients achieving hematological response upon lenalidomide treatment, the drug reverts several transcriptional alterations in both del(5q) and non-del(5q) cells, but other lesions remain, which may be responsible for potential future relapses. Moreover, lack of hematological response is associated with the inability of lenalidomide to reverse transcriptional alterations. Collectively, this study reveals transcriptional alterations that could contribute to the pathogenesis and treatment response of del(5q) MDS.
Topics: Humans; Lenalidomide; Myelodysplastic Syndromes; Hematopoietic Stem Cells; Antigens, CD34; Chromosome Deletion; Chromosomes, Human, Pair 5; Single-Cell Analysis; Male; Female; Aged; Gene Regulatory Networks; Middle Aged; Hematopoiesis; Transcriptome; Aged, 80 and over; RNA-Seq; Gene Expression Profiling
PubMed: 38902243
DOI: 10.1038/s41467-024-49529-x -
Oncotarget Jun 2024
Topics: Humans; Circulating Tumor DNA; Precision Medicine; Neoplasms; Biomarkers, Tumor; Reproducibility of Results; High-Throughput Nucleotide Sequencing
PubMed: 38900651
DOI: 10.18632/oncotarget.28581 -
Applied Microbiology and Biotechnology Jun 2024Despite increased attention to the aquaculture environment, there is still a lack of understanding regarding the significance of water quality. To address this knowledge...
Despite increased attention to the aquaculture environment, there is still a lack of understanding regarding the significance of water quality. To address this knowledge gap, this study utilized high-throughput sequencing of 16S rRNA and 18S rRNA to examine microbial communities (bacteria and eukaryotes) in coastal water over different months through long-term observations. The goal was to explore interaction patterns in the microbial community and identify potential pathogenic bacteria and red tide organisms. The results revealed significant differences in composition, diversity, and richness of bacterial and eukaryotic operational taxonomic units (OTUs) across various months. Principal coordinate analysis (PCoA) demonstrated distinct temporal variations in bacterial and eukaryotic communities, with significant differences (P = 0.001) among four groups: F (January-April), M (May), S (June-September), and T (October-December). Moreover, a strong association was observed between microbial communities and months, with most OTUs showing a distinct temporal preference. The Kruskal-Wallis test (P < 0.05) indicated significant differences in dominant bacterial and eukaryotic taxa among months, with each group exhibiting unique dominant taxa, including potential pathogenic bacteria and red tide organisms. These findings emphasize the importance of monitoring changes in potentially harmful microorganisms in aquaculture. Network analysis highlighted positive correlations between bacteria and eukaryotes, with bacteria playing a key role in network interactions. The key bacterial genera associated with other microorganisms varied significantly (P < 0.05) across different groups. In summary, this study deepens the understanding of aquaculture water quality and offers valuable insights for maintaining healthy aquaculture practices. KEY POINTS: • Bacterial and eukaryotic communities displayed distinct temporal variations. • Different months exhibited unique potential pathogenic bacteria and red tide organisms. • Bacteria are key taxonomic taxa involved in microbial network interactions.
Topics: Bacteria; Aquaculture; RNA, Ribosomal, 16S; Eukaryota; Seawater; RNA, Ribosomal, 18S; High-Throughput Nucleotide Sequencing; Microbiota; Seasons; Biodiversity; Phylogeny
PubMed: 38900314
DOI: 10.1007/s00253-024-13176-5 -
Genome Biology Jun 2024Neuroblastoma is a common pediatric cancer, where preclinical studies suggest that a mesenchymal-like gene expression program contributes to chemotherapy resistance....
BACKGROUND
Neuroblastoma is a common pediatric cancer, where preclinical studies suggest that a mesenchymal-like gene expression program contributes to chemotherapy resistance. However, clinical outcomes remain poor, implying we need a better understanding of the relationship between patient tumor heterogeneity and preclinical models.
RESULTS
Here, we generate single-cell RNA-seq maps of neuroblastoma cell lines, patient-derived xenograft models (PDX), and a genetically engineered mouse model (GEMM). We develop an unsupervised machine learning approach ("automatic consensus nonnegative matrix factorization" (acNMF)) to compare the gene expression programs found in preclinical models to a large cohort of patient tumors. We confirm a weakly expressed, mesenchymal-like program in otherwise adrenergic cancer cells in some pre-treated high-risk patient tumors, but this appears distinct from the presumptive drug-resistance mesenchymal programs evident in cell lines. Surprisingly, however, this weak-mesenchymal-like program is maintained in PDX and could be chemotherapy-induced in our GEMM after only 24 h, suggesting an uncharacterized therapy-escape mechanism.
CONCLUSIONS
Collectively, our findings improve the understanding of how neuroblastoma patient tumor heterogeneity is reflected in preclinical models, provides a comprehensive integrated resource, and a generalizable set of computational methodologies for the joint analysis of clinical and pre-clinical single-cell RNA-seq datasets.
Topics: Neuroblastoma; Humans; Animals; Single-Cell Analysis; Mice; RNA-Seq; Cell Line, Tumor; Gene Expression Regulation, Neoplastic; Drug Resistance, Neoplasm; Transcriptome; Single-Cell Gene Expression Analysis
PubMed: 38898465
DOI: 10.1186/s13059-024-03309-4 -
Scientific Reports Jun 2024This study probes the utility of biomarkers for microsatellite instability (MSI) detection and elucidates the molecular dynamics propelling colorectal cancer (CRC)...
This study probes the utility of biomarkers for microsatellite instability (MSI) detection and elucidates the molecular dynamics propelling colorectal cancer (CRC) progression. We synthesized a primer panel targeting 725 MSI loci, informed by The Cancer Genome Atlas (TCGA) and ancillary databases, to construct an amplicon library for next-generation sequencing (NGS). K-means clustering facilitated the distillation of 8 prime MSI loci, including activin A receptor type 2A (ACVR2A). Subsequently, we explored ACVR2A's influence on CRC advancement through in vivo tumor experiments and hematoxylin-eosin (HE) staining. Transwell assays gauged ACVR2A's role in CRC cell migration and invasion, while colony formation assays appraised cell proliferation. Western blotting illuminated the impact of ACVR2A suppression on CRC's PI3K/AKT/mTOR pathway protein expressions under hypoxia. Additionally, ACVR2A's influence on CRC-induced angiogenesis was quantified via angiogenesis assays. K-means clustering of NGS data pinpointed 32 MSI loci specific to tumor and DNA mismatch repair deficiency (dMMR) tissues. ACVR2A emerged as a pivotal biomarker, discerning MSI-H tissues with 90.97% sensitivity. A curated 8-loci set demonstrated 100% sensitivity and specificity for MSI-H detection in CRC. In vitro analyses corroborated ACVR2A's critical role, revealing its suppression of CRC proliferation, migration, and invasion. Moreover, ACVR2A inhibition under CRC-induced hypoxia markedly escalated MMP3, CyclinA, CyclinD1, and HIF1α protein expressions, alongside angiogenesis, by triggering the PI3K/AKT/mTOR cascade. The 8-loci ensemble stands as the optimal marker for MSI-H identification in CRC. ACVR2A, a central element within this group, deters CRC progression, while its suppression amplifies PI3K/AKT/mTOR signaling and angiogenesis under hypoxic stress.
Topics: Colorectal Neoplasms; Humans; Microsatellite Instability; Activin Receptors, Type II; Disease Progression; Animals; Cell Movement; Mice; Cell Line, Tumor; Cell Proliferation; Biomarkers, Tumor; Signal Transduction; Male; High-Throughput Nucleotide Sequencing; Female; Proto-Oncogene Proteins c-akt
PubMed: 38898042
DOI: 10.1038/s41598-024-62753-1 -
Nature Communications Jun 2024Single-cell RNA sequencing (scRNA-seq) has been widely used to characterize cell types based on their average gene expression profiles. However, most studies do not...
Single-cell RNA sequencing (scRNA-seq) has been widely used to characterize cell types based on their average gene expression profiles. However, most studies do not consider cell type-specific variation across donors. Modelling this cell type-specific inter-individual variation could help elucidate cell type-specific biology and inform genes and cell types underlying complex traits. We therefore develop a new model to detect and quantify cell type-specific variation across individuals called CTMM (Cell Type-specific linear Mixed Model). We use extensive simulations to show that CTMM is powerful and unbiased in realistic settings. We also derive calibrated tests for cell type-specific interindividual variation, which is challenging given the modest sample sizes in scRNA-seq. We apply CTMM to scRNA-seq data from human induced pluripotent stem cells to characterize the transcriptomic variation across donors as cells differentiate into endoderm. We find that almost 100% of transcriptome-wide variability between donors is differentiation stage-specific. CTMM also identifies individual genes with statistically significant stage-specific variability across samples, including 85 genes that do not have significant stage-specific mean expression. Finally, we extend CTMM to partition interindividual covariance between stages, which recapitulates the overall differentiation trajectory. Overall, CTMM is a powerful tool to illuminate cell type-specific biology in scRNA-seq.
Topics: Humans; Single-Cell Analysis; Sequence Analysis, RNA; Induced Pluripotent Stem Cells; Transcriptome; Cell Differentiation; Gene Expression Profiling; RNA-Seq; Endoderm
PubMed: 38898015
DOI: 10.1038/s41467-024-49242-9