Identification and validation of serum metabolite biomarkers for endometrial cancer diagnosis.

Endometrial cancer (EC) stands as the most prevalent gynecological tumor in women worldwide. Notably, differentiation diagnosis of abnormity detected by ultrasound findings (e.g., thickened endometrium or mass in the uterine cavity) is essential and remains challenging in clinical practice. Herein, we identified a metabolic biomarker panel for differentiation diagnosis of EC using machine learning of high-performance serum metabolic fingerprints (SMFs) and validated the biological function. We first recorded the high-performance SMFs of 191 EC and 204 Non-EC subjects via particle-enhanced laser desorption/ionization mass spectrometry (PELDI-MS). Then, we achieved an area-under-the-curve (AUC) of 0.957-0.968 for EC diagnosis through machine learning of high-performance SMFs, outperforming the clinical biomarker of cancer antigen 125 (CA-125, AUC of 0.610-0.684, p < 0.05). Finally, we identified a metabolic biomarker panel of glutamine, glucose, and cholesterol linoleate with an AUC of 0.901-0.902 and validated the biological function in vitro. Therefore, our work would facilitate the development of novel diagnostic biomarkers for EC in clinics.

Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core-Shells in Laser Desorption/Ionization Mass Spectrometry.

Effective detection of bio-molecules relies on the precise design and preparation of materials, particularly in laser desorption/ionization mass spectrometry (LDI-MS). Despite significant advancements in substrate materials, the performance of single-structured substrates remains suboptimal for LDI-MS analysis of complex systems. Herein, designer Au@SiO2@ZrO2 core-shell substrates are developed for LDI-MS-based early diagnosis and prognosis of pancreatic cancer (PC). Through controlling Au core size and ZrO2 shell crystallization, signal amplification of metabolites up to 3 orders is not only achieved, but also the synergistic mechanism of the LDI process is revealed. The optimized Au@SiO2@ZrO2 enables a direct record of serum metabolic fingerprints (SMFs) by LDI-MS. Subsequently, SMFs are employed to distinguish early PC (stage I/II) from controls, with an accuracy of 92%. Moreover, a prognostic prediction scoring system is established with enhanced efficacy in predicting PC survival compared to CA19-9 (p < 0.05). This work contributes to material-based cancer diagnosis and prognosis.

Self-Assembled Hyperbranched Gold Nanoarrays Decode Serum United Urine Metabolic Fingerprints for Kidney Tumor Diagnosis.

Serum united urine metabolic analysis comprehensively reveals the disease status for kidney diseases in particular. Thus, the precise and convenient acquisition of metabolic molecular information from united biofluids is vitally important for clinical disease diagnosis and biomarker discovery. Laser desorption/ionization mass spectrometry (LDI-MS) presents various advantages in metabolic analysis; however, there remain challenges in ionization efficiency and MS signal reproducibility. Herein, we constructed a self-assembled hyperbranched black gold nanoarray (HyBrAuNA) assisted LDI-MS platform to profile serum united urine metabolic fingerprints (S-UMFs) for diagnosis of early stage renal cell carcinoma (RCC). The closely packed HyBrAuNA afforded strong electromagnetic field enhancement and high photothermal conversion efficacy, enabling effective ionization of low abundant metabolites for S-UMF collection. With a uniform nanoarray, the platform presented excellent reproducibility to ensure the accuracy of S-UMFs obtained in seconds. When it was combined with automated machine learning analysis of S-UMFs, early stage RCC patients were discriminated from the healthy controls with an area under the curve (AUC) > 0.99. Furthermore, we screened out a panel of 9 metabolites (4 from serum and 5 from urine) and related pathways toward early stage kidney tumor. In view of its high-throughput, fast analytical speed, and low sample consumption, our platform possesses potential in metabolic profiling of united biofluids for disease diagnosis and pathogenic mechanism exploration.

Diagnosis of Esophageal Squamous Cell Carcinoma by High-Performance Serum Metabolic Fingerprints: A Retrospective Study.

Esophageal squamous cell carcinoma (ESCC) is a highly prevalent and aggressive malignancy, and timely diagnosis of ESCC contributes to an increased cancer survival rate. However, current detection methods for ESCC mainly rely on endoscopic examination, limited by a relatively low participation rate. Herein, ferric-particle-enhanced laser desorption/ionization mass spectrometry (FPELDI MS) is utilized to record the serum metabolic fingerprints (SMFs) from a retrospective cohort (523 non-ESCC participants and 462 ESCC patients) to build diagnostic models toward ESCC. The PFELDI MS achieved high speed (≈30 s per sample), desirable reproducibility (coefficients of variation < 15%), and high throughput (985 samples with ≈124 200 data points for each spectrum). Desirable diagnostic performance with area-under-the-curves (AUCs) of 0.925-0.966 is obtained through machine learning of SMFs. Further, a metabolic biomarker panel is constructed, exhibiting superior diagnostic sensitivity (72.2-79.4%, p < 0.05) as compared with clinical protein biomarker tests (4.3-22.9%). Notably, the biomarker panel afforded an AUC of 0.844 (95% confidence interval [CI]: 0.806-0.880) toward early ESCC diagnosis. This work highlighted the potential of metabolic analysis for accurate screening and early detection of ESCC and offered insights into the metabolic characterization of diseases including but not limited to ESCC.

Efficient plasma metabolic fingerprinting as a novel tool for diagnosis and prognosis of gastric cancer: a large-scale, multicentre study.

OBJECTIVE: Metabolic biomarkers are expected to decode the phenotype of gastric cancer (GC) and lead to high-performance blood tests towards GC diagnosis and prognosis. We attempted to develop diagnostic and prognostic models for GC based on plasma metabolic information. DESIGN: We conducted a large-scale, multicentre study comprising 1944 participants from 7 centres in retrospective cohort and 264 participants in prospective cohort. Discovery and verification phases of diagnostic and prognostic models were conducted in retrospective cohort through machine learning and Cox regression of plasma metabolic fingerprints (PMFs) obtained by nanoparticle-enhanced laser desorption/ionisation-mass spectrometry (NPELDI-MS). Furthermore, the developed diagnostic model was validated in prospective cohort by both NPELDI-MS and ultra-performance liquid chromatography-MS (UPLC-MS). RESULTS: We demonstrated the high throughput, desirable reproducibility and limited centre-specific effects of PMFs obtained through NPELDI-MS. In retrospective cohort, we achieved diagnostic performance with areas under curves (AUCs) of 0.862-0.988 in the discovery (n=1157 from 5 centres) and independent external verification dataset (n=787 from another 2 centres), through 5 different machine learning of PMFs, including neural network, ridge regression, lasso regression, support vector machine and random forest. Further, a metabolic panel consisting of 21 metabolites was constructed and identified for GC diagnosis with AUCs of 0.921-0.971 and 0.907-0.940 in the discovery and verification dataset, respectively. In the prospective study (n=264 from lead centre), both NPELDI-MS and UPLC-MS were applied to detect and validate the metabolic panel, and the diagnostic AUCs were 0.855-0.918 and 0.856-0.916, respectively. Moreover, we constructed a prognosis scoring system for GC in retrospective cohort, which can effectively predict the survival of GC patients. CONCLUSION: We developed and validated diagnostic and prognostic models for GC, which also contribute to advanced metabolic analysis towards diseases, including but not limited to GC.

Multifunctional Imaging of Vessels, Brown Adipose Tissue, and Bones in the Visible and Second Near-infrared Region Using Dual-Emitting Polymer Dots.

Dual-emitting polymer dots (dual-Pdots) in the visible and second near-infrared (NIR-II) region can facilitate the high-resolution imaging of the fine structure and improve the signal-to-noise ratio in in vivo imaging. Herein, combining high brightness of Pdots and multi-scale imaging, we synthesized dual-Pdots using a simple nano-coprecipitation method and performed multi-functional imaging of vessels, brown adipose tissue, and bones. Results showed that in vivo blood vessel imaging had a high resolution of up to 5.9 µm and bone imaging had a signal-to-noise ratio of 3.9. Moreover, dual-Pdots can accumulate in the interscapular brown adipose tissue within 2 min with a signal-to-noise ratio of 5.8. In addition, the prepared dual-Pdots can image the lymphatic valves and the frequency of contraction. Our study provides a feasible method of using Pdots as nanoprobes for multi-scale imaging in the fields of metabolic disorders, skeletal system diseases, and circulatory systems.

Imaging of fluorescent polymer dots in relation to channels and immune cells in the lymphatic system.

Polymer dots (Pdots) have been applied to imaging lymph nodes (LNs) and lymphatic vessels (LVs) in living mice and rats. However, the mechanism of absorption, distribution, metabolism, and excretion of Pdots in LNs and LVs is still unclear. Therefore, the relationship between Pdots and immune cells, LVs and collagen fibers in lymphatics was studied by multiple in vivo and ex vivo microscopic imaging methods and detection techniques. Flow cytometry showed that Pdots could be phagocytosed by macrophages and monocytes, and had no relationship with B cells, T cells and dendric cells in LNs. Silver staining, immunofluorescence and two-photon microscope showed that Pdots gathered in collagen fibers and LVs of LNs. Furthermore, immunofluorescence imaging results verified that Pdots were distributed in the extracellular space of collecting LVs endothelial cells. In addition, Pdots in the collecting LVs were basically cleared by leaking into the surrounding tissue or draining LNs after 21 days of injection. During the long-time observation, Pdots also helped monitor the contraction frequency and variation range of LV. Our study lays a foundation on the research of Pdots as the carrier to study lymphatic structure and function in the future.

Comparison of invasive intubation and noninvasive mechanical ventilation in patients with chronic obstructive pulmonary disease and obstructive sleep apnoea syndrome.

OBJECTIVE: The concurrence of chronic obstructive pulmonary disease (COPD) and obstructive sleep apnoea syndrome (OSAS) is defined as overlap syndrome (OS), but investigations into predictors of OS in patients with COPD remain limited. Here, potential markers of OS in patients with COPD were investigated, and results of intubation were compared between patients with COPD only or OS. METHODS: This retrospective study included patients with COPD who were divided according to OS diagnosis: COPD only (COPD group) or OS (OS group). RESULTS: Among 206 patients with COPD, 120 were diagnosed with OS. Mean body mass index (BMI) was significantly higher in the OS versus COPD group (28.95 ± 2.96 versus 23.84 ± 4.06, respectively). Receiver operating characteristic curve analyses revealed that BMI was associated with OS (area under the curve, 0.835). The rate of invasive intubation within 48 h was lower in the OS versus COPD group (9.2% versus 20.9%, respectively), and the duration of noninvasive ventilation was longer in the OS versus COPD group. CONCLUSIONS: BMI may be a predictor of OS in patients with COPD. The duration of noninvasive ventilation was longer in patients with OS than in patients with COPD alone.

LncRNA NKX2-1-AS1 promotes tumor progression and angiogenesis via upregulation of SERPINE1 expression and activation of the VEGFR-2 signaling pathway in gastric cancer.

Long noncoding RNAs (lncRNAs) can compete with endogenous RNAs to modulate the gene expression and contribute to oncogenesis and tumor metastasis. lncRNA NKX2-1-AS1 (NKX2-1 antisense RNA 1) plays a pivotal role in cancer progression and metastasis; however, the contribution of aberrant expression of NKX2-1-AS1 and the mechanism by which it functions as a competing endogenous RNA (ceRNA) in gastric cancer (GC) remains elusive. NKX2-1-AS1 expression was detected in paired tumor and nontumor tissues of 178 GC patients by quantitative reverse transcription PCR (qRT-PCR). Using loss-of-function and gain-of-function experiments, the biological functions of NKX2-1-AS1 were evaluated both in vitro and in vivo. Further, to assess that NKX2-1-AS1 regulates angiogenic processes, tube formation and co-culture assays were performed. RNA binding protein immunoprecipitation (RIP) assay, a dual-luciferase reporter assay, quantitative PCR, Western blot, and fluorescence in situ hybridization (FISH) assays were performed to determine the potential molecular mechanism underlying this ceRNA. The results indicated that NKX2-1-AS1 expression was upregulated in GC cell lines and tumor tissues. Overexpression of NKX2-1-AS1 was significantly associated with tumor progression and enhanced angiogenesis. Functionally, NKX2-1-AS1 overexpression promoted GC cell proliferation, metastasis, invasion, and angiogenesis, while NKX2-1-AS1 knockdown restored these effects, both in vitro and in vivo. RIP and dual-luciferase assays revealed that the microRNA miR-145-5p is a direct target of NKX2-1-AS1 and that NKX2-1-AS1 serves as a ceRNA to sponge miRNA and regulate angiogenesis in GC. Moreover, serpin family E member 1 (SERPINE1) is an explicit target for miR-145-5p; besides, the NKX2-1-AS1/miR-145-5p axis induces the translation of SERPINE1, thus activating the VEGFR-2 signaling pathway to promote tumor progression and angiogenesis. NKX2-1-AS1 overexpression is associated with enhanced tumor cell proliferation, angiogenesis, and poor prognosis in GC. Collectively, NKX2-1-AS1 functions as a ceRNA to miR-145-5p and promotes tumor progression and angiogenesis by activating the VEGFR-2 signaling pathway via SERPINE1.

LncRNA MYLK-AS1 facilitates tumor progression and angiogenesis by targeting miR-424-5p/E2F7 axis and activating VEGFR-2 signaling pathway in hepatocellular carcinoma.

BACKGROUND: Long non-coding RNAs (lncRNAs) are crucial in the invasion, angiogenesis, progression, and metastasis of hepatocellular carcinoma (HCC). The lncRNA MYLK-AS1 promotes the growth and invasion of HCC through the EGFR/HER2-ERK1/2 signaling pathway. However, the clinical significance of MYLK-AS1 in HCC still needs to be further determined. METHODS: Bioinformatic analysis was performed to determine the potential relationship among MYLK-AS1, miRNAs and mRNAs. A total of 156 samples of normal liver and paired HCC tissues from HCC patients were used to evaluate MYLK-AS1 expression by qRT-PCR. Human HCC cell lines were used to evaluate the colony formation, cell proliferation, migration, invasion, cell cycle and apoptosis after transfection of lentiviral short-hairpin RNAs (shRNAs) targeting MYLK-AS1 or MYLK-AS1 vectors. The competitive endogenous RNA (ceRNA) mechanism was clarified using fluorescence in situ hybridization (FISH), Western blotting, qPCR, RNA binding protein immunoprecipitation (RIP), and dual luciferase reporter analysis. RESULTS: MYLK-AS1 up-regulation was detected in the HCC tumor tissues and cell lines associated with the enhancement of the angiogenesis and tumor progression. The down-regulation of MYLK-AS1 reversed the effects on angiogenesis, proliferation, invasion and metastasis in the HCC cells and in vivo. MYLK-AS1 acted as ceRNA, capable of regulating the angiogenesis in HCC, while the microRNA miR-424-5p was the direct target of MYLK-AS1. Promoting the angiogenesis and the tumor proliferation, the complex MYLK-AS1/miR-424-5p activated the VEGFR-2 signaling through E2F7, whereas the specific targeting of E2F transcription factor 7 (E2F7) by miR-424-5p, was indicated by the mechanism studies. CONCLUSIONS: MYLK-AS1 and E2F7 are closely related to some malignant clinicopathological features and prognosis of HCC, thus the MYLK-AS1/ miR-424-5p/E2F7 signaling pathway might represent a promising treatment strategy to combat HCC.

Toxicity, uptake and transport mechanisms of dual-modal polymer dots in penny grass (Hydrocotyle vulgaris L.).

The use of polymers such as plastic has become an important part of daily life, and in aqueous environments, these polymers are considered as pollutants. When macropolymers are reduced to the nanoscale, their small particle size and large specific surface area facilitate their uptake by plants, which has a significant impact on aquatic plants. Therefore, it is essential to study the pollution of nanoscale polymers in the aquatic environment. In this work, we prepared nanoscale polymer dots (Pdots) and explored their toxicity, uptake and transport mechanisms in penny grass. From toxicological studies, in the absence of other nutrients, the cell structure, physiological parameters (total soluble protein and chlorophyll) and biochemical parameters (malondialdehyde) do not show significant changes over at least five days. Through in vivo fluorescence and photoacoustic (PA) imaging, the transport location can be visually detected accurately, and the transport rate can be analyzed without destroying the plants. Moreover, through ex vivo fluorescence imaging, we found that different types of Pdots have various uptake and transport mechanisms in stems and blades. It may be due to the differences in ligands, particle sizes, and oil-water partition coefficients of Pdots. By understanding how Pdots interact with plants, a corresponding method can be developed to prevent them from entering plants, thus avoiding the toxicity from accumulation. Therefore, the results of this study also provide the basis for subsequent prevention work.

The Effect of Polymer Dots During Mammalian Early Embryo Development and Their Biocompatibility on Maternal Health.

Conjugated polymer dots have excellent fluorescence properties in terms of their structural diversity and functional design, showing broad application prospects in the fields of biological imaging and biosensing. Polymer dots contain no heavy metals and are thought to be of low toxicity and good biocompatibility. Therefore, systematic studies on their potential toxicity are needed. Herein, the biocompatibility of poly[(9,9-dioctylfluorenyl-2,7diyl)-co-(1,4-benzo-{2,1',3}-thiadiazole)],10% benzothiadiazole(y) (PFBT) and poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV) polymer dots on early embryo development as well as maternal health is studied in detail. The results show that prepared polymer dots are dose-dependently toxic to preimplantation embryos, and low-dose polymer dots can be used for cell labeling of early embryos without affecting the normal development of embryos into blastocysts. In addition, the in vivo distribution data show that the polymer dots accumulate mainly in the maternal liver, spleen, kidney, placenta, ovary, and lymph nodes of the pregnant mice. Histopathological examination and blood biochemical tests demonstrate that exposure of the maternal body to polymer dots at a dosage of 14 µg g-1 does not affect the normal function of the maternal organs and early fetal development. The research provides a safe basis for the wide application of polymer dots.