Purpose: Metagenomic next-generation sequencing (mNGS) is a powerful yet unbiased method to identify pathogens in suspected infections. However, little is known about its clinical effectiveness. The present study aimed to assess the efficacy of mNGS in routine clinical practice. Patients and Methods: In this single-center retrospective cohort study, 518 patients with suspected infectious diseases were assessed for inclusion. Among them, each patient had undergone mNGS testing; 407 patients had undergone both microbial culture and mNGS testing. The result of mNGS testing was compared to microbial culture performed concurrently. The diagnostic performance of mNGS was evaluated using the comprehensive clinical diagnosis as the reference standard. Results: There was a significant difference in the positive detection rates of pathogens between mNGS and culture (331/407, 81.3% vs 79/407, 19.4%, P < 0.001). The sensitivity of mNGS was much higher than the culture method (79.5% vs 21.3%, P < 0.001), especially in sample types of sputum and bronchoalveolar lavage fluid (BALF). Notably, the sensitivity of blood mNGS was relatively lower than other sample types (67.4% vs 88.9– 93.8%). Pathogen cfDNA load based on standardized stringently mapped read number at the species level of microorganisms (SDSMRN) was significantly lower in blood than in other sample types from the same patient (P = 0.0003). Importantly, mNGS directly led to a change of treatment regimen in 142 (27.4%) cases, including antibiotic escalation (15.3%), antibiotic de-escalation (9.1%), and early definitive diagnosis to initiate appropriate treatment (3.1%). Conclusion: Our in-house mNGS platform significantly improved the sensitivity for the diagnosis of infectious diseases. mNGS has the potential to improve clinical outcomes by optimizing antimicrobial therapy.

We have previously found that TdT-interacting factor 1 (TdIF1) is a potential oncogene expressed in non-small cell lung cancer (NSCLC) and is associated with poor prognosis. However, its exact mechanism is still unclear. The lysine-specific demethylase 1 (LSD1) is a crucial mediator of the epithelial–mesenchymal transition (EMT), an important process triggered during cancer metastasis. Here, we confirm that TdIF1 is highly expressed in NSCLC and related to lymph node metastasis through The Cancer Genome Atlas (TCGA) analysis of clinical samples. Silencing TdIF1 can regulate the expression of EMT-related factors and impair the migration and invasion ability of cancer cells in vitro. An analysis of tumor xenografts in nude mice confirmed that silencing TdIF1 inhibits tumor growth. Furthermore, we determined the interaction between TdIF1 and LSD1 using immunoprecipitation. Chromatin immunoprecipitation (ChIP) revealed that TdIF1 was enriched in the E-cadherin promoter region. The knockdown of TdIF1 repressed the enrichment of LSD1 at the E-cadherin promoter region, thereby regulating the level of promoter histone methylation and modulating E-cadherin transcription activity, ultimately leading to changes in EMT factors and cancer cell migration and invasion ability. The LSD1 inhibitor and TdIF1 knockdown combination showed a synergistic effect in inhibiting the growth, migration, and invasion of NSCLC cells. Taken together, this is the first demonstration that TdIF1 regulates E-cadherin transcription by recruiting LSD1 to the promoter region, thereby promoting EMT and tumor metastasis and highlighting the potential of TdIF1 as a therapeutic target for NSCLC.

Solid-state nanopore sequencing, a key third-generation sequencing technology, offers considerable potential for genomics and diagnostics due to its long read lengths, real-time detection, and amplification-free operation. The technology identifies DNA sequences by measuring characteristic changes in ionic current as single-stranded DNA translocates through a nanoscale pore. However, its practical development faces challenges including limited spatiotemporal resolution, pore clogging from nonspecific adsorption, and significant electrical noise. This review systematically examines strategies developed to address these limitations. We discuss the use of ultrathin two-dimensional materials such as graphene and molybdenum disulfide to improve spatial resolution, and methods to modulate DNA translocation through optimized solution conditions, pore geometry, surface charge engineering, and bio-solid hybrid pore designs. Furthermore, we detail noise suppression strategies targeting key sources like thermal noise, 1/f noise, and dielectric noise. These approaches encompass careful material selection, surface coatings, innovations in chip and amplifier design, and machine learning–based signal processing. The review also outlines surface functionalization techniques that reduce clogging and enhance analytical specificity. While challenges remain, continued convergence of materials science, nanofabrication, and data science is advancing solid-state nanopore technology toward reliable, high-precision sequencing platforms, promising to significantly impact personalized medicine and biological research.

Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world and contributes to a high cancer mortality globally. The multistep progression of HCC is highly related to the activation of oncogenes and the deactivation of cancer suppressor genes. The cyclin-dependent kinase 7 (CDK7) gene is responsible for maintaining a normal cell cycle, acting as a gatekeeper, and plays an important part in RNA transcription. Although previous studies demonstrate that CDK7 is highly expressed in multiple cancers and is associated with the progression and prognosis of these cancers, the potential role of CDK7 in HCC still needs to be explored. Methods: Data consisting of CDK7 expression levels, patient phenotypes and their matched survival were acquired from The Cancer Genome Atlas (TCGA) database. The associations of the CDK7 expression level with clinicopathological factors and cell proliferation were analyzed. The HCC transcriptome data in the GEO database were inquired and analyzed using GEO2R. Two representative HCC cell models were built to observe the proliferation capacity of HCC cells when CDK7 expression was inhibited by either shCDK7 or THZ1. Results: Based on the transcriptome and survival data in the TCGA database, the CDK7 expression level was inversely proportional to the overall survival of the HCC patients (pooled HR =1.51, 95% CI =1.06–2.15). For further investigation, the clinical features of HCC were integrated with the expression level of CDK7. A high expression of CDK7 was proportional to the survival time of the HCC patients (P=2.38×10⁻³), the neoplasm histologic grade (P<1×10⁻⁴) and cell proliferation (P<1×10⁻³). Moreover, CDK7 expression in the liver tumor was higher than that in non-tumor tissues (t-test =6.04, P=2.27×10⁻⁸). For HCC patients, CDK7 expression was higher in the tumor tissues than in the para-carcinoma tissues, based on five GEO datasets (Z score =−6.20, P=5.64×10⁻¹⁰). In the SMMC-7721 and Huh7 cell lines, CDK7 shRNA-transfected cells showed significantly lower capabilities of cell growth and proliferation than those of the shRNA control group after 48 hours of cell culture. Furthermore, the cell proliferation capacity was also inhibited when the SMMC-7721 cells (P=6.47×10⁻⁴) or Huh7 cells (P=2.52×10⁻²) were exposed to THZ1. Conclusions: The CDK7 expression level in HCC is associated with HCC progression, prognosis and the cell proliferation capacity. CDK7 may act as a potential target for HCC, and THZ1 might be a potent medicine for HCC treatment.

The combination of mRNA and lncRNA profiles for establishing an integrated mRNA–lncRNA prognostic signature has remained unexplored in cholangiocarcinoma (CCA) patients. We utilized a training dataset of 36 samples from The Cancer Genome Atlas dataset and a validation cohort (GSE107943) of 30 samples from Gene Expression Omnibus. Two mRNAs (CFHR3 and PIWIL4) and 2 lncRNAs (AC007285.1 and AC134682.1) were identified to construct the integrated signature through a univariate Cox regression (P-value = 1.35E−02) and a multivariable Cox analysis (P-value = 3.07E−02). Kaplan–Meier curve showed that patients with low risk scores had notably prolonged overall survival than those with high risk scores (P-value = 4.61E−03). Subsequently, the signature was validated in GSE107943 cohort with an area under the curve of 0.750 at 1-year and 0.729 at 3-year. The signature was not only independent from diverse clinical features (P-value = 3.07E−02), but also surpassed other clinical characteristics as prognostic biomarkers with area under the curve of 0.781 at 3-year. Moreover, the weighted gene co-expression network analysis and gene enrichment analyses found that the integrated signature were associated with metabolic-related biological process and lipid metabolism pathway, which has been implicated in the pathogenesis of CCA. Taken together, we developed an integrated mRNA–lncRNA signature that had an independent prognostic value in the risk stratification of patients with CCA.