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TP53 mutations are ubiquitous in high‐grade serous ovarian carcinomas (HGSOC), and the presence of TP53 mutation discriminates between high and low‐grade serous carcinomas and is now an important biomarker for clinical trials targeting mutant p53. p53 immunohistochemistry (IHC) is widely used as a surrogate for TP53 mutation but its accuracy has not been established. The objective of this study was to test whether improved methods for p53 IHC could reliably predict TP53 mutations independently identified by next generation sequencing (NGS). Four clinical p53 IHC assays and tagged‐amplicon NGS for TP53 were performed on 171 HGSOC and 80 endometrioid carcinomas (EC). p53 expression was scored as overexpression (OE), complete absence (CA), cytoplasmic (CY) or wild type (WT). p53 IHC was evaluated as a binary classifier where any abnormal staining predicted deleterious TP53 mutation and as a ternary classifier where OE, CA or WT staining predicted gain‐of‐function (GOF or nonsynonymous), loss‐of‐function (LOF including stopgain, indel, splicing) or no detectable TP53 mutations (NDM), respectively. Deleterious TP53 mutations were detected in 169/171 (99%) HGSOC and 7/80 (8.8%) EC. The overall accuracy for the best performing IHC assay for binary and ternary prediction was 0.94 and 0.91 respectively, which improved to 0.97 (sensitivity 0.96, specificity 1.00) and 0.95 after secondary analysis of discordant cases. The sensitivity for predicting LOF mutations was lower at 0.76 because p53 IHC detected mutant p53 protein in 13 HGSOC with LOF mutations. CY staining associated with LOF was seen in 4 (2.3%) of HGSOC. Optimized p53 IHC can approach 100% specificity for the presence of TP53 mutation and its high negative predictive value is clinically useful as it can exclude the possibility of a low‐grade serous tumour. 4.1% of HGSOC cases have detectable WT staining while harboring a TP53 LOF mutation, which limits sensitivity for binary prediction of mutation to 96%.

Lower respiratory tract infections are characterized by high morbidity and mortality, the latter associated with the low sensitivity and long turnaround time (TAT) of traditional diagnostic methods. Advances in next-generation sequencing (NGS) offers a promising solution, but in the face of so many different NGS products, how to use them appropriately remains a great challenge for clinicians. This study included 205 patients with suspected lower respiratory tract infections from the department of respiratory and critical care medicine, and collected their lower respiratory tract samples for metagenomic NGS (mNGS) and two different targeted NGS (tNGS), amplification-based tNGS and capture-based tNGS. We analyzed their microorganisms reported, and evaluated their detection performance based on the comprehensive clinical diagnosis. Compared to the two tNGS, mNGS showed significant higher cost ($840) and longer TAT (20 h). Conversely, it identified the highest number of species, totaling 80, compared to 71 species identified by capture-based tNGS and 65 species by amplification-based tNGS. When benchmarked against the comprehensive clinical diagnosis, the capture-based tNGS demonstrated significantly higher diagnostic performance than the other two NGS, with an accuracy of 93.17% and a sensitivity of 99.43%. However, it showed lower specificity compared to the amplification-based tNGS in identifying DNA virus (74.78% vs. 98.25%). The amplification-based tNGS exhibited a poor sensitivity for both gram-positive (40.23%) and gram-negative bacteria (71.74%). Moreover, tNGS was able to identify genotypes, antimicrobial resistance genes and virulence factors. In conclusion, mNGS is suited for the detection of rare pathogens; the capture-based tNGS is preferable for routine diagnostic testing; the amplification-based tNGS can be an alternative in situations requiring rapid results and constrained by limited resources.

As sequencing technology transitions from research to clinical settings, due to technological maturity and cost reductions, metagenomic next-generation sequencing (mNGS) is increasingly used. This shift underscores the growing need for more cost-effective and universally accessible sequencing assays to improve patient care and public health. Therefore, targeted NGS (tNGS) is gaining prominence. tNGS involves enrichment of target pathogens in patient samples based on multiplex PCR amplification or probe capture with excellent sensitivity. It is increasingly used in clinical diagnostics due to its practicality and efficiency. The present review compares the principles of different enrichment methods. The high positivity rate of tNGS in the detection of pathogens was found in respiratory samples with specific instances. tNGS maintains high sensitivity (70.8-95.0%) in samples with low pathogen loads, including blood and cerebrospinal fluid. Furthermore, tNGS is effective in detecting drug-resistant strains of Mycobacterium tuberculosis, allowing identification of resistance genes and guiding clinical treatment decisions, which is difficult to achieve with mNGS. In the present review, the application of tNGS in clinical settings and its current limitations are assessed. The continued development of tNGS has the potential to refine diagnostic accuracy and treatment efficacy and improving infectious disease management. However, further research to overcome technical challenges such as workflow time and cost is required.

Objective This study aimed to compare the performance of hybrid capture-based targeted next-generation sequencing (hc-tNGS) and metagenomic next-generation sequencing (mNGS) in detecting the causative pathogens of infectious keratitis. Methods A total of 60 patients with clinically diagnosed infectious keratitis were enrolled between January and December 2024. Corneal scraping samples were analyzed using hc-tNGS and mNGS. Detection rates, pathogen spectra, normalized reads, turnaround time (TAT), and costs were compared between the two techniques. Results hc-tNGS exhibited a significantly higher overall detection rate than mNGS (86.7% versus 73.3%, P  < 0.001). In particular, hc-tNGS detected 29 pathogens (13 bacteria, 9 viruses, and 7 fungi), whereas mNGS detected 22 pathogens (9 bacteria, 7 viruses, and 6 fungi). Furthermore, hc-tNGS detected additional low-abundance pathogens in 17 mNGS-positive patients (28.3%, 17/60) and 8 mNGS-negative patients (11.3%, 8/60). The normalized reads for viruses, bacteria, and fungi in hc-tNGS were 57.2-, 2.7-, and 3.3-fold higher than those in mNGS, respectively ( P  < 0.001, P  = 0.003, and P  = 0.028). Moreover, hc-tNGS reduced TAT by 11.3% (18.0 versus 20.3 h) and costs by 22.4–48.8%. The median of sequencing data size of mNGS was 29.8 million (29.8 M) reads, which was significantly higher than that of tNGS (1.5 M, P  < 0.001). Conclusion hc-tNGS demonstrates superior performance and cost-effectiveness in detecting potential pathogens of infectious keratitis, especially low-abundance pathogens, whereas mNGS remains valuable for detecting novel pathogens. Owing to its enhanced performance, faster TAT, and reduced costs, hc-tNGS is a promising clinical tool for pathogen detection.

Next-generation sequencing (NGS) has revolutionized clinical microbiology, particularly in diagnosing respiratory infectious diseases and conducting epidemiological investigations. This narrative review summarizes conventional methods for routine respiratory infection diagnosis, including culture, smear microscopy, immunological assays, image techniques as well as polymerase chain reaction(PCR). In contrast to conventional methods, there is a new detection technology, sequencing technology, and here we mainly focus on the next-generation sequencing NGS, especially metagenomic NGS(mNGS). NGS offers significant advantages over traditional methods. Firstly, mNGS eliminates assumptions about pathogens, leading to faster and more accurate results, thus reducing diagnostic time. Secondly, it allows unbiased identification of known and novel pathogens, offering broad-spectrum coverage. Thirdly, mNGS not only identifies pathogens but also characterizes microbiomes, analyzes human host responses, and detects resistance genes and virulence factors. It can complement targeted sequencing for bacterial and fungal classification. Unlike traditional methods affected by antibiotics, mNGS is less influenced due to the extended survival of pathogen DNA in plasma, broadening its applicability. However, barriers to full integration into clinical practice persist, primarily due to cost constraints and limitations in sensitivity and turnaround time. Despite these challenges, ongoing advancements aim to improve cost-effectiveness and efficiency, making NGS a cornerstone technology for global respiratory infection diagnosis.

PurposesRapid and accurate identification of non-tuberculous mycobacteria (NTM) is crucial yet challenging, promoting the development of novel molecular techniques such as amplification-based targeted high-throughput sequencing and metagenomic unbiased high-throughput sequencing. We aimed to evaluate the diagnostic value of these molecular techniques for NTM infection.MethodsA total of 115 clinical specimens from patients with confirmed NTM infection were subjected to multiplex polymerase chain reaction detection techniques (multi-PCR), metagenomic Next-Generation Sequencing (mNGS), targeted Next-Generation Sequencing (tNGS), and targeted Nanopore sequencing (tNanopore). Positivity rates and species identification were compared among these techniques.ResultsThe sensitivity of mNGS, tNGS, and multi-PCR in NTM-infection diagnosis was 44.3%, 42.6%, and 36.5%, respectively, while the sensitivity of the three methods in combination increased to 54.8%. The pathogen identification results of mNGS, tNGS and multi-PCR were matched in 80.6% (25/31) samples at the species level, among which 14 samples (45.2%) was completely matched at the subspecies level. The results of tNanopore, tNGS and mNGS at the species level were completely matched in 73.3% (22/30) samples.ConclusionsThese molecular assays demonstrated comparable performance in precisely identifying NTM species in clinical specimens, showing their promising potential as efficient and alternative tools for the rapid diagnosis of NTM disease.

Background The limited genomic targeting range of current targeted next-generation sequencing (tNGS) workflows results in limited detection of pathogen-derived cell-free DNA (cfDNA), making it challenging to apply this approach to bloodstream infections (BSIs). Here, we developed an ultra-broad hybrid capture-based tNGS method to detect plasma pathogen-derived cfDNA and evaluate its suitability for the diagnosis of BSI. Methods This study introduced an ultra-broad hybrid capture-based tNGS method featuring an ultra-broad pathogen panel (1872 pathogens) and high-density probe coverage. To adequately evaluate its performance, we conducted retrospective tests in 208 suspected BSI patients (139 immunocompromised), comparing tNGS results with mNGS, conventional microbiological testing (CMT), and comprehensive clinical diagnoses. Results In pathogen detection, the concordance between ultra-broad hybrid capture-based tNGS and mNGS results was 93.75%. The diagnostic accuracy of tNGS in BSI was comparable to mNGS (76.44% vs. 75.00%) and significantly higher than CMT (45.67%, p  < 0.0001). In immunocompromised populations, the diagnostic accuracy of tNGS was similar to mNGS (77.70% vs. 76.98%). tNGS detected 92.09% (163/177) of pathogens identified by mNGS. Two of the missed pathogens were not included in the 1872 pathogens panel, and both were from the immunocompromised group. Conclusions Ultra-broad hybrid capture-based tNGS exhibits sensitivity and accuracy comparable to mNGS, effectively covering a relatively wide range of pathogens, and may serve as an economic screening tool for BSI in the future.

Fungal research is experiencing a new wave of methodological improvements that most probably will boost mycology as profoundly as molecular phylogeny has done during the last 15 years. Especially the next generation sequencing technologies can be expected to have a tremendous effect on fungal biodiversity and ecology research. In order to realise the full potential of these exciting techniques by accelerating biodiversity assessments, identification procedures of fungi need to be adapted to the emerging demands of modern large-scale ecological studies. But how should fungal species be identified in the near future? While the answer might seem trivial to most microbiologists, taxonomists working with fungi may have other views. In the present review, we will analyse the state of the art of the so-called barcoding initiatives in the light of fungi, and we will seek to evaluate emerging trends in the field. We will furthermore demonstrate that the usability of DNA barcoding as a major tool for identification of fungi largely depends on the development of high-quality sequence databases that are thoroughly curated by taxonomists and systematists.

The human endometrium is an essential component in human reproduction that has the unique characteristic of undergoing cyclic regeneration during each menstrual cycle. Vigorous regeneration after shedding may be sustained by stem/progenitor cells, for which molecular markers have not been fully identified. Although clonality analysis using X chromosome inactivation patterns has shown that normal human endometrial glands are composed of a monoclonal cell population, whether clonal expansion is derived from stem/progenitor cells remains unclear. Remarkable advances in next‐generation sequencing technology over the past decade have enabled somatic mutations to be detected in not only cancers, but also normal solid tissues. Unexpectedly frequent cancer‐associated mutations have been detected in a variety of normal tissues, and recent studies have clarified the mutational landscape of normal human endometrium. In epithelial glandular cells, representative cancer‐associated mutations are frequently observed in an age‐dependent manner, presumably leading to growth advantage. However, the extremely high mutation loads attributed to DNA mismatch repair deficiency and POLE mutations, as well as structural and copy number alterations, are specific to endometrial cancer, not to normal epithelial cells. The malignant conversion of normal epithelial cells requires these additional genetic hits, which are presumably accumulated during aging, and may therefore be a rare life event. These discoveries could be expected to shed light on the physiology and pathogenesis of the human endometrium and urge caution against the application of genetic screening for the early detection of endometrial cancer. Human endometrial gland exhibits clonal growth in each menstrual cycle possibly via stem/progenitor cells, with harboring frequent somatic gene mutations in cancer‐associated genes. These mutations may plays role in endometrial regeneration and pathogenesis of endometriosis or endometrial cancer.

Although the emerging NGS-based assays, metagenomic next-generation sequencing (mNGS) and targeted next-generation sequencing (tNGS), have been extensively utilized for the identification of pathogens in pulmonary infections, there have been limited studies systematically evaluating differences in the efficacy of mNGS and multiplex PCR-based tNGS in bronchoalveolar lavage fluid (BALF) specimens. In this study, 85 suspected infectious BALF specimens were collected. Parallel mNGS and tNGS workflows to each sample were performed; then, we comparatively compared their consistency in detecting pathogens. The differential results for clinically key pathogens were confirmed using PCR. The microbial detection rates of BALF specimens by the mNGS and tNGS workflows were 95.18% (79/83) and 92.77% (77/83), respectively, with no significant difference. mNGS identified 55 different microorganisms, whereas tNGS detected 49 pathogens. The comparative analysis of mNGS and tNGS revealed that 86.75% (72/83) of the specimens were complete or partial concordance. Particularly, mNGS and tNGS differed significantly in detection rates for some of the human herpesviruses only, including (P<0.001), (P<0.001), (P<0.05) and (P<0.01), in which tNGS always had higher detection rates. Orthogonal testing of clinically critical pathogens showed a total coincidence rate of 50% for mNGS and PCR, as well as for tNGS and PCR. Overall, the performance of mNGS and multiplex PCR-based tNGS assays was similar for bacteria and fungi, and tNGS may be superior to mNGS for the detection of DNA viruses. No significant differences were seen between the two NGS assays compared to PCR.