Hollow Cu2-xS@NiFe Layered Double Hydroxide Core-Shell S-Scheme Heterojunctions with Broad-Spectrum Response and Enhanced Photothermal-Photocatalytic Performance.

Designing a reasonable heterojunction is an efficient path to improve the separation of photogenerated charges and enhance photocatalytic activity. In this study, Cu2-xS@NiFe-LDH hollow nanoboxes with core-shell structure are successfully prepared. The results show that Cu2-xS@NiFe-LDH with broad-spectrum response has good photothermal and photocatalytic activity, and the photocatalytic activity and stability of the catalyst are enhanced by the establishment of unique hollow structure and core-shell heterojunction structure. Transient PL spectra (TRPL) indicates that constructing Cu2-xS@NiFe-LDH heterojunction can prolong carrier lifetime obviously. Cu2-xS@NiFe-LDH shows a high photocatalytic hydrogen production efficiency (5176.93 µmol h-1 g-1), and tetracycline degradation efficiency (98.3%), and its hydrogen production rate is ≈10-12 times that of pure Cu2-xS and NiFe-LDH. In situ X-ray photoelectron spectroscopy (XPS) and electron spin resonance (ESR) provide proofs of the S-scheme electron transfer path. The S-scheme heterojunction achieves high spatial charge separation and exhibits strong photoredox ability, thus improving the photocatalytic performance.

Hollow Nanoboxes Cu2-x S@ZnIn2 S4 Core-Shell S-Scheme Heterojunction with Broad-Spectrum Response and Enhanced Photothermal-Photocatalytic Performance.

Major issues in photocatalysis include improving charge carrier separation efficiency at the interface of semiconductor photocatalysts and rationally developing efficient hierarchical heterostructures. Surface continuous growth deposition is used to make hollow Cu2-x S nanoboxes, and then simple hydrothermal reaction is used to make core-shell Cu2-x S@ZnIn2 S4 S-scheme heterojunctions. The photothermal and photocatalytic performance of Cu2-x S@ZnIn2 S4 is improved. In an experimental hydrogen production test, the Cu2-x S@ZnIn2 S4 photocatalyst produces 4653.43 µmol h-1 g-1 of hydrogen, which is 137.6 and 13.8 times higher than pure Cu2-x S and ZnIn2 S4 , respectively. Furthermore, the photocatalyst exhibits a high tetracycline degradation efficiency in the water of up to 98.8%. For photocatalytic reactions, the hollow core-shell configuration gives a large specific surface area and more reactive sites. The photocatalytic response range is broadened, infrared light absorption enhanced, the photothermal effect is outstanding, and the photocatalytic process is promoted. Meanwhile, characterizations, degradation studies, active species trapping investigations, energy band structure analysis, and theoretical calculations all reveal that the S-scheme heterojunction can efficiently increase photogenerated carrier separation. This research opens up new possibilities for future S-scheme heterojunction catalyst design and development.

Identification immunophenotyping of lung adenocarcinomas based on the tumor microenvironment.

The tumor immune microenvironment is heterogeneous, and its impact on treatment responses is not well understood. It is still a challenge to analyze the interaction between malignant cells and the tumor microenvironment to apply suitable immunotherapy in lung adenocarcinoma. We performed the nonnegative matrix factorization method to 513 messenger RNA expression profiles of lung adenocarcinomas (LUADs) from The Cancer Genome Atlas (TCGA) to obtain an immune-related expression pattern. Subsequently, we characterized the immune-related gene signatures and clinical and survival characteristics. We used 576 patients from Gene Expression Omnibus to confirm our findings. Of the patients in the training cohort, 51% had a high immune enrichment score, high expression of immune cell signaling, cytolytic activity, and interferon (IFN)-related signatures (all P < .05). We denoted these as the Immune Class. We further subdivided the Immune Class into two subclasses based on the tumor microenvironment. These were denoted the Active Immune Class and Exhausted Immune Class. The former showed significant IFN, T-cells, M1 macrophage signatures, and better prognosis (all P < .05), while the latter presented an exhausted immune response with activated stromal enrichment, M2 macrophage signatures, and immunosuppressive factors such as WNT/transforming growth factor-ß (all P < .05). Furthermore, we predicted the response of our immunophenotypes to immunological checkpoint inhibitors (P < .05). Our findings provide a novel insight into the immune-related state of LUAD and can identify the patients who will be receptive to suitable immunotherapeutic treatments.

NormAE: Deep Adversarial Learning Model to Remove Batch Effects in Liquid Chromatography Mass Spectrometry-Based Metabolomics Data.

Untargeted metabolomics based on liquid chromatography-mass spectrometry is affected by nonlinear batch effects, which cover up biological effects, result in nonreproducibility, and are difficult to be calibrate. In this study, we propose a novel deep learning model, called Normalization Autoencoder (NormAE), which is based on nonlinear autoencoders (AEs) and adversarial learning. An additional classifier and ranker are trained to provide adversarial regularization during the training of the AE model, latent representations are extracted by the encoder, and then the decoder reconstructs the data without batch effects. The NormAE method was tested on two real metabolomics data sets. After calibration by NormAE, the quality control samples (QCs) for both data sets gathered most closely in a PCA score plot (average distances decreased from 56.550 and 52.476 to 7.383 and 14.075, respectively) and obtained the highest average correlation coefficients (from 0.873 and 0.907 to 0.997 for both). Additionally, NormAE significantly improved biomarker discovery (median number of differential peaks increased from 322 and 466 to 1140 and 1622, respectively). NormAE was compared with four commonly used batch effect removal methods. The results demonstrated that using NormAE produces the best calibration results.

All-Solid Z-Scheme Bi-BiOCl/AgCl Heterojunction Microspheres for Improved Electron-Hole Separation and Enhanced Visible Light-Driven Photocatalytic Performance.

All-solid Z-scheme Bi-BiOCl/AgCl heterojunction microspheres are successfully prepared via hydrothermal, NaBH4 reduction and chemical deposition strategy. They are tested by various characterization methods, and they show that metal Bi is present after reduction and AgCl nanoparticles are successfully compounded onto BiOCl. Bi plays the role of a bridge connecting the two semiconductors of BiOCl and AgCl. All-solid Z-scheme heterojunction structures are formed successfully. The narrow band gap of the Z-scheme Bi-BiOCl/AgCl heterojunction microspheres is about 2.17 eV, which can expand the optical response range. Moreover, the photocatalytic hydrogen production rate still reaches 198.2 µmol h-1 g-1, extends the electron transport life, inhibits the recombination of electron hole pairs, and improves the photocatalytic activity.

Promoted spatial charge separation of plasmon Ag and co-catalyst Co x P decorated mesoporous g-C3N4 nanosheet assembly for unexpected solar-driven photocatalytic performance.

Plasmon Ag and co-catalyst Co x P decorated mesoporous graphite carbon nitride nanosheet assemblies have been synthesized via a template-calcination and ball milling strategy combined with photoreduction. The obtained composites are characterized by x-ray diffraction, Fourier transmission infrared spectroscopy, x-ray photoelectron spectroscopy, transmission electron microscopy, and UV-vis diffuse reflectance spectroscopy. The results show that the sample assembly with mesoporous structure has specific surface area of 50.4 m2 g-1, pore size of 11.3 nm and pore volume of 0.21 cm3 g-1. The Ag and Co x P nanoparticles are decorated on the surface of graphite carbon nitride uniformly. Under solar light irradiation, the photocatalytic degradation rate of ceftazidime for the prepared sample assembly is up to ∼92%, and the photocatalytic reaction rate constant is about 10 times higher than that of bare graphite carbon nitride. Moreover, the sample assembly also exhibits a solar-driven photocatalytic hydrogen production rate of 96.66 µmol g-1 h-1. It can attributed to the surface plasmon resonance effect of Ag nanoparticles and Co x P co-catalyst promoting the spatial charge separation and the mesoporous structure providing more surface active sites and favoring mass transfer. This special structure offers new insights for fabricating other high-performance photocatalysts with high spatial charge separation.

Identification of pathway-based recurrence-associated signatures in optimally debulked patients with serous ovarian cancer.

Serous ovarian cancer (SOC) is the most common form of the histological subtype of epithelial ovarian cancer, with the worst clinical outcome. Despite improvements in surgery and chemotherapy, most patients with SOC experience recurrence within 12-18 months of first-line treatment. Current studies are unable to robustly predict the recurrence of SOC, and more accurate predictive models are urgently required. We have, therefore, developed a novel pathway-structured model to predict the recurrence of SOC. We trained the model on a set of 333 patients and validated it in 3 diversified validation datasets of 403 patients. Genes significantly associated with recurrence within each pathway were identified using a Cox proportional hazards model based on LASSO estimation in the training dataset. Next, a pathway-structured scoring matrix was obtained after computation of the prognostic score for each pathway by fitting to the Cox proportional hazards model. With the pathway-structure scoring matrix as an input, the pathway-based recurrent signatures were identified using the Cox proportional hazards model based on LASSO estimation and the significant pathway-based signatures were externally validated in 3 independent datasets. Meanwhile, our pathway-structured model was compared with a commonly used gene-based model. Our results revealed that our 12 pathway-based signatures successfully predicted the recurrence of SOC with high accuracy in the training dataset and in the 3 validation datasets. Moreover, our pathway-structured model was superior to the gene-based model in 4 datasets. The pathways selected in our study will provide new insights into the pathogenesis and clinical treatments of SOC.

Sites of distant metastases and overall survival in ovarian cancer: A study of 1481 patients.

OBJECTIVE: To assess the association between patterns of distant metastases and overall survival in metastatic ovarian cancer and identify prognostic factors for site-specific distant metastases. METHODS: Data was obtained from the SEER database between 2010 and 2014. Univariate and multivariate Cox proportional hazard models were used to identify variables associated with overall survival. Survival times between different groups were compared using Kaplan-Meier analysis and log-rank tests. RESULTS: We analyzed 1481 patients. The most common distant metastatic site was liver, followed by distant lymph nodes, lung, bone, and brain. The site of distant metastases was an independent prognostic factor for overall survival. Using liver metastases as reference, overall survival was lower for lung metastases (p = 0.0297) and higher for distant lymph node metastases (p = 0.0006). Using distant lymph nodes as reference, distant metastases to the liver (p = 0.0006), lung (p < 0.0001), brain (p = 0.0455), and bone (p = 0.0138) were all associated with worse overall survival. The number of metastatic sites did not affect overall survival. We also found that surgery and chemotherapy affected overall survival for patients with distant lymph node metastases only; age, histological subtype, surgery, and chemotherapy affected overall survival for patients with liver metastases only, while histological subtype and chemotherapy affected overall survival for patients with lung metastases only. CONCLUSIONS: The site of distant metastases affected overall survival in metastatic ovarian cancer. Patients with specific distant metastatic sites should receive special treatment and management. The identified prognostic factors can help clinician evaluate the prognosis for ovarian cancer patients with distant metastases.

Agreement Between Magnetic Resonance Imaging and Pathologic Findings in the Tumor Size Evaluation Before and After Neoadjuvant Chemotherapy Treatment: A Prospective Study.

OBJECTIVES: To compare the agreement between magnetic resonance imaging (MRI) results and postsurgical pathologic findings for tumor size evaluation in cervical cancer patients before and after neoadjuvant chemotherapy (NACT) treatment. METHODS: The study analyzed the agreement between pretreatment MRI results and postsurgical pathologic findings about the tumor size in 100 cervical cancer patients without NACT and 397 cervical cancer patients with NACT, respectively. RESULTS: In general, the agreement between pretreatment MRI results and postsurgical pathologic findings of tumor size was 0.855 (95% confidence interval [CI], 0.763-0.909) in cervical cancer patients without NACT, whereas the agreement between posttreatment MRI results and postsurgical pathologic findings was 0.503 (95% CI, 0.421-0.576). Only 62.72% (249/397) of patients who underwent NACT treatment have the same chemotherapy response evaluation results; the κ coefficient was 0.384(95% CI, 0.310-0.457) between posttreatment MRI and postsurgical pathologic findings. We still found International Federation of Gynecology and Obstetrics stage is associated with the chemotherapy response evaluation. CONCLUSIONS: Our data suggest that pretreatment MRI can be a surrogate indicator for postsurgical pathologic findings. However, posttreatment MRI could not be a surrogate indicator for postsurgical pathologic findings. The chemotherapy response evaluation based on only MRI is not so reliable. More indicators should be developed for chemotherapy response evaluation.

Twinned crystal Cd0.9Zn0.1S/MoO3 nanorod S-scheme heterojunctions as promising photocatalysts for efficient hydrogen evolution.

Leveraging solar energy through photocatalytic hydrogen production from water stands out as one of the most promising approaches to address the energy and environmental challenges. The choice of catalyst profoundly influences the outcomes of photocatalytic reactions, and constructing heterojunctions has emerged as a widely applied strategy to overcome the limitations associated with single-phase photocatalysts. MoO3, renowned for its high chemical stability, encounters issues such as low photocatalytic efficiency and fast recombination of photogenerated electrons and holes. To tackle these challenges, the morphology of MoO3 has been controlled to form nanorods, simultaneously suppressing the aggregation of the catalyst and increasing the number of surface-active sites. Moreover, to facilitate the separation of photogenerated charge carriers, Cd0.9Zn0.1S nanoparticles with a twin crystal structure are deposited on the surface of MoO3, establishing an S-scheme heterojunction. Experimental findings demonstrate that the synergistic effects arising from the well-defined morphology and interface interactions extend the absorption range to visible light response, improve charge transfer activity, and prolong the lifetime of charge carriers. Consequently, Cd0.9Zn0.1S/MoO3 S-scheme heterojunctions exhibit outstanding photocatalytic hydrogen production performance (3909.79 µmol g-1 h-1) under visible light irradiation, surpassing that of MoO3 by nearly nine fold.

Surface and interface engineering of BiOCl nanomaterials and their photocatalytic applications.

BiOCl materials have received much attention because of their unique optical and electrical properties. Still, their unsatisfactory catalytic performance has been troubling researchers, limiting the application of BiOCl-based photocatalysts. Therefore, many researchers have studied the adjustment of BiOCl-based materials to enhance photocatalytic efficiency. This review focuses on surface and interface engineering strategies for boosting the photocatalytic performance of BiOCl-based nanomaterials, including forming oxygen vacancy defects, constructing metal/BiOCl, and the fabrication of semiconductor/BiOCl nanocomposites. The photocatalytic applications of the above composites are also concluded in photodegradation of aqueous pollutants, photocatalytic NO removal, photo-induced H2 production, and CO2 reduction. Special emphasis has been given to the modification methods of BiOCl and photocatalytic mechanisms to provide a more detailed understanding for researchers in the fields of energy conversion and materials sciences.

Integrated Cyano Groups into the Skeleton of Conjugated Polymers to Activate Molecular Oxygen for Boosting Photocatalytic H2O2 Efficiency.

Conjugated polymers (CPs) have shown promising potential in the field of hydrogen peroxide (H2O2) photosynthesis. However, a deeper understanding of the interactions between building units and specific functional groups within the molecular skeleton is necessary to elucidate the mechanisms driving H2O2 generation. Herein, a series of typical donor-acceptor (D-A) conjugated polymers (B-B, B-CN, B-DCN) were synthesized by introducing different amounts of cyano groups (-CN) into the molecular skeleton. The strong electron withdrawing properties of cyano can greatly promote the effective separation and transfer of photogenerated charges between building units, resulting in an impressive efficiency of H2O2 generation (2128.5 µmol g-1 h-1) for B-DCN, representing a 96-fold enhancement compared to B-B. More importantly, experimental results and theoretical calculations further revealed that the introduction of -CN can markedly reduce the adsorption energy (Ead) of O2, while serving as an active site to induce the conversion of crucial intermediate superoxide anions (.O2-) into singlet oxygen (1O2), achieving dual-channel H2O2 generation (O2→.O2-→H2O2, O2→.O2-→1O2→H2O2). This work provides valuable insights into the design of efficient H2O2 photosynthesis materials.

Identification of potential biomarkers for ovarian cancer by urinary metabolomic profiling.

To evaluate the application of urinary metabolomics on discovering potential biomarkers for epithelial ovarian cancer (EOC), urine samples from 40 preoperative EOC patients, 62 benign ovarian tumor (BOT) patients, and 54 healthy controls were collected and analyzed with ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS). Good separations were obtained for EOC vs BOT, EOC vs healthy controls analyzed by partial least-squares discriminant analysis, or principal component analysis. Twenty-two ascertained metabolomic biomarkers were found to be disturbed in several metabolic pathways among EOC patients, including nucleotide metabolism (pseudouridine, N4-acetylcytidine), histidine metabolism (L-histidine, imidazol-5-yl-pyruvate), tryptophan metabolism (3-indolelactic acid), and mucin metabolism (3'-sialyllactose and 3-sialyl-N-acetyllactosamine). In addition, the concentrations of some urinary metabolites of 18 postoperative EOC patients among the 40 EOC patients changed significantly compared with those of their preoperative condition, and four of them suggested recovery tendency toward normal level after surgical operation, including N4-acetylcytidine, pseudouridine, urate-3-ribonucleoside, and succinic acid. These metabolites would be highly postulated to be associated with EOC. In conclusion, our study demonstrated that urinary metabolomics analysis by UPLC-QTOF/MS, performed in a minimally noninvasive and convenient manner, possessed great potential in biomarker discovery for EOC.

Recent Advances in Black TiO2 Nanomaterials for Solar Energy Conversion.

Titanium dioxide (TiO2) nanomaterials have been widely used in photocatalytic energy conversion and environmental remediation due to their advantages of low cost, chemical stability, and relatively high photo-activity. However, applications of TiO2 have been restricted in the ultraviolet range because of the wide band gap. Broadening the light absorption of TiO2 nanomaterials is an efficient way to improve the photocatalytic activity. Thus, black TiO2 with extended light response range in the visible light and even near infrared light has been extensively exploited as efficient photocatalysts in the last decade. This review represents an attempt to conclude the recent developments in black TiO2 nanomaterials synthesized by modified treatment, which presented different structure, morphological features, reduced band gap, and enhanced solar energy harvesting efficiency. Special emphasis has been given to the newly developed synthetic methods, porous black TiO2, and the approaches for further improving the photocatalytic activity of black TiO2. Various black TiO2, doped black TiO2, metal-loaded black TiO2 and black TiO2 heterojunction photocatalysts, and their photocatalytic applications and mechanisms in the field of energy and environment are summarized in this review, to provide useful insights and new ideas in the related field.

Defective Cd0.3Zn0.7S twin crystal/Ag3PO4 Z-scheme heterojunctions toward optimized visible-light-driven photocatalytic hydrogen evolution.

To improve the photocatalytic performance of semiconductor catalysts, one of the most widely used strategies is to combine two or more semiconductors with appropriate energy band structures to construct heterojunctions for an extended light absorption range and effective charge separation. Here, a novel Z-scheme heterojunction is fabricated via the Cd0.3Zn0.7S twin crystal and the narrow band gap semiconductor Ag3PO4. The resulting Cd0.3Zn0.7S/1%Ag3PO4 photocatalyst exhibits excellent photocatalytic hydrogen production capability (167.29 µmol h-1), which is two times higher than that of Cd0.3Zn0.7S and 44/7 times higher than that of pristine ZnS/CdS. The excellent photocatalytic performance is not only attributed to the defective twin crystal structure of Cd0.3Zn0.7S but also related to the well-matched Z-scheme interface between Cd0.3Zn0.7S and Ag3PO4, and both factors effectively promote the separation of the photogenerated electron-hole pairs and prolong the lifetime of the carriers, being responsible for the excellent photocatalytic hydrogen evolution performance of the catalysts. This strategy provides new insights into the construction of efficient twin crystal heterojunctions for photocatalytic hydrogen evolution with high performance.

High-Crystallinity BiOCl Nanosheets as Efficient Photocatalysts for Norfloxacin Antibiotic Degradation.

Semiconductor photocatalysts are essential materials in the field of environmental remediation. Various photocatalysts have been developed to solve the contamination problem of norfloxacin in water pollution. Among them, a crucial ternary photocatalyst, BiOCl, has attracted extensive attention due to its unique layered structure. In this work, high-crystallinity BiOCl nanosheets were prepared using a one-step hydrothermal method. The obtained BiOCl nanosheets showed good photocatalytic degradation performance, and the degradation rate of highly toxic norfloxacin using BiOCl reached 84% within 180 min. The internal structure and surface chemical state of BiOCl were analyzed using scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman, Fourier transform infrared spectroscopy (FTIR), UV-visible diffuse reflectance (UV-vis), Brunauer-Emmett-Teller (BET), X-ray photoelectron spectra (XPS), and photoelectric techniques. The higher crystallinity of BiOCl closely aligned molecules with each other, which improved the separation efficiency of photogenerated charges and showed high degradation efficiency for norfloxacin antibiotics. Furthermore, the obtained BiOCl nanosheets possess decent photocatalytic stability and recyclability.

Bi/Mn-Doped BiOCl Nanosheets Self-Assembled Microspheres toward Optimized Photocatalytic Performance.

Doping engineering of metallic elements is of significant importance in photocatalysis, especially in the transition element range where metals possess empty 'd' orbitals that readily absorb electrons and increase carrier concentration. The doping of Mn ions produces dipole interactions that change the local structure of BiOCl, thus increasing the specific surface area of BiOCl and the number of mesoporous distributions, and providing a broader platform and richer surface active sites for catalytic reactions. The combination of Mn doping and metal Bi reduces the forbidden bandwidth of BiOCl, thereby increasing the absorption in the light region and strengthening the photocatalytic ability of BiOCl. The degradation of norfloxacin by Bi/Mn-doped BiOCl can reach 86.5% within 10 min. The synergistic effect of Mn doping and Bi metal can change the internal energy level and increase light absorption simultaneously. The photocatalytic system created by such a dual-technology combination has promising applications in environmental remediation.

Bi2Fe4O9@ZnIn2S4 S-scheme laminated heterojunction photocatalyst towards optimized photocatalytic performance.

Reasonable design of heterojunction photocatalysts can effectively promote charge separation, thus improving their photocatalytic performance. Herein, a Bi2Fe4O9@ZnIn2S4 S-scheme laminated heterojunction photocatalyst with 2D/2D interface interaction is prepared via a hydrothermal-annealing-hydrothermal method. The photocatalytic hydrogen production rate of Bi2Fe4O9@ZnIn2S4 is up to 3964.26 µmol h-1 g-1, which is 12.1 times higher than that of pristine ZnIn2S4. In addition, its photocatalytic tetracycline degradation efficiency (99.9%) is also optimized. The enhanced photocatalytic performance can be attributed to the formation of S-scheme laminated heterojunctions that facilitate charge separation as well as strong 2D/2D laminated interface interactions favoring charge transfer. By combining in situ irradiation X-ray photoelectron spectroscopy with other characterization methods, the photoexcited charge transfer mechanism of S-scheme heterojunctions has been proved. Photoelectric chemical tests demonstrate the effectiveness of the S-scheme laminated heterojunction in improving the charge separation. This strategy provides a novel perspective for designing other high-efficient S-scheme laminated heterojunction photocatalysts.

Construction of 2D/2D Mesoporous WO3/CeO2 Laminated Heterojunctions for Optimized Photocatalytic Performance.

Photocatalytic elimination of antibiotics from the environment and drinking water is of great significance for human health. However, the efficiency of photoremoval of antibiotics such as tetracycline is severely limited by the prompt recombination of electron holes and slow charge migration efficacy. Fabrication of low-dimensional heterojunction composites is an efficient method for shortening charge carrier migration distance and enhancing charge transfer efficiency. Herein, 2D/2D mesoporous WO3/CeO2 laminated Z-scheme heterojunctions were successfully prepared using a two-step hydrothermal process. The mesoporous structure of the composites was proved by nitrogen sorption isotherms, in which sorption-desorption hysteresis was observed. The intimate contact and charge transfer mechanism between WO3 nanoplates and CeO2 nanosheets was investigated using high-resolution transmission electron microscopy and X-ray photoelectron spectroscopy measurements, respectively. Photocatalytic tetracycline degradation efficiency was noticeably promoted by the formation of 2D/2D laminated heterojunctions. The improved photocatalytic activity could be attributed to the formation of Z-scheme laminated heterostructure and 2D morphology favoring spatial charge separation, confirmed by various characterizations. The optimized 5WO3/CeO2 (5 wt.% WO3) composites can degrade more than 99% of tetracycline in 80 min, achieving a peak TC photodegradation efficiency of 0.0482 min-1, which is approximately 3.4 times that of pristine CeO2. A Z-scheme mechanism is proposed for photocatalytic tetracycline by from WO3/CeO2 Z-scheme laminated heterojunctions based on the experimental results.

Identification of metabolic biomarkers to diagnose epithelial ovarian cancer using a UPLC/QTOF/MS platform.

BACKGROUND: Currently available tests are insufficient to distinguish patients with epithelial ovarian cancer (EOC) from normal individuals. Metabolomics, a study of metabolic processes in biologic systems, has emerged as a key technology in the measurements of small molecular metabolites in tissues or biofluids. MATERIAL AND METHODS: To investigate the application of metabolomics on selecting EOC-associated biomarkers, 173 plasma specimens (80 newly diagnosed EOC patients and 93 normal individuals) were analyzed using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC/QTOF/MS). A two-step strategy was performed to select EOC-associated biomarkers. The first step was to select potential biomarkers in distinguishing 42 cancer patients from 58 normal controls through partial least-squares discriminant analysis (PLS-DA) and database searching, and the second step was to validate the discrimination performance of these biomarkers in a dataset contained 38 EOCs and 35 controls. RESULTS: Eight candidate biomarkers were selected. The combination of these biomarkers resulted in the area of receiver operating characteristic curve (AUC) of 0.941, a sensitivity of 0.921, and a specificity of 0.886 at the best cut-off point for detecting EOC. DISCUSSION: Our findings suggested that sharp differences in metabolic profiles exist between EOC patients and normal controls. The identified eight metabolites associated with EOC may be served as novel biomarkers for diagnosis.