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BACKGROUND: A recent trend in postoperative analgesia for lung cancer surgery relies on regional nerve blocks with decreased opioid administration. Our study aims to critically assess the continuous ultrasound-guided erector spinae plane block (ESPB) at our institution and compare it to a standard regional anesthetic technique, the intercostal nerve block (ICNB). PATIENTS AND METHODS: A prospective randomized-control study was performed to compare outcomes of patients, scheduled for video-assisted thoracoscopic (VATS) lung cancer resection, allocated to the ESPB or ICNB group. Primary outcomes were total opioid consumption and subjective pain scores at rest and cough each hour in 48 h after surgery. The secondary outcome was respiratory muscle strength, measured by maximal inspiratory and expiratory pressures (MIP/MEP) after 24 h and 48 h. RESULTS: 60 patients met the inclusion criteria, half ESPB. Total opioid consumption in the first 48 h was 21. 64 ± 14.22 mg in the ESPB group and 38.34 ± 29.91 mg in the ICNB group (p = 0.035). The patients in the ESPB group had lower numerical rating scores at rest than in the ICNB group (1.19 ± 0.73 vs. 1.77 ± 1.01, p = 0.039). There were no significant differences in MIP/MEP decrease from baseline after 24 h (MIP p = 0.088, MEP p = 0.182) or 48 h (MIP p = 0.110, MEP p = 0.645), time to chest tube removal or hospital discharge between the two groups. CONCLUSIONS: In the first 48 h after surgery, patients with continuous ESPB required fewer opioids and reported less pain than patients with ICNB. There were no differences regarding respiratory muscle strength, postoperative complications, and time to hospital discharge. In addition, continuous ESPB demanded more surveillance than ICNB.

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BACKGROUND: Treatment of early-stage non-small cell lung cancer (NSCLC) is rapidly evolving. When introducing novelties, real-life data on effectiveness of currently used treatment strategies are needed. The present study evaluated outcomes of stage I-IIIA NSCLC patients treated with upfront radical surgery in everyday clinical practice, between 2010-2017. PATIENTS AND METHODS: Data of 539 consecutive patients were retrieved from a prospective hospital-based registry. All diagnostic, treatment and follow-up procedures were performed at the same thoracic oncology centre according to the valid guidelines. The primary outcome was overall survival (OS) analysed by clinical(c) and pathological(p) TNM (tumour, node, metastases) stage. The impact of clinicopathological characteristics on OS was evaluated using univariable (UVA) and multivariable regression analysis (MVA). RESULTS: With a median follow-up of 53.9 months, median OS and 5-year OS rate in the overall population were 90.4 months and 64.4%. Five-year OS rates by pTNM stage I, II and IIIA were 70.2%, 60.21%, and 49.9%, respectively. Both cTNM and pTNM stages were associated with OS; but only pTNM retained its independent prognostic value (p = 0.003) in MVA. Agreement between cTNM and pTNM was 69.0%. Next to pTNM, age (p = 0.001) and gender (p = 0.004) retained their independent prognostic value for OS. CONCLUSIONS: The study showed favourable outcomes of resectable stage I-IIIA NSCLC treated with upfront surgery in real-life. Relatively low agreement between cTNM and pTNM stages and independent prognostic value of only pTNM, observed in real-life data, suggest that surgery remains the most accurate provider of the anatomical stage of disease and important upfront therapy.

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Early diagnosis of colorectal cancer (CRC) is of high importance as prognosis depends on tumour stage at the time of diagnosis. Detection of tumour-specific DNA methylation marks in cfDNA has several advantages over other approaches and has great potential for solving diagnostic needs. We report here the identification of DNA methylation biomarkers for CRC and give insights in our methylation-sensitive restriction enzyme coupled qPCR (MSRE-qPCR) system. Targeted microarrays were used to investigate the DNA methylation status of 360 cancer-associated genes. Validation was done by qPCR-based approaches. A focus was on investigating marker performance in cfDNA from 88 patients (44 CRC, 44 controls). Finally, the workflow was scaled-up to perform 180plex analysis on 110 cfDNA samples, to identify a DNA methylation signature for advanced colonic adenomas (AA). A DNA methylation signature (n = 44) was deduced from microarray experiments and confirmed by quantitative methylation-specific PCR (qMSP) and by MSRE-qPCR, providing for six genes' single areas under the curve (AUC) values of >0.85 (WT1, PENK, SPARC, GDNF, TMEFF2, DCC). A subset of the signatures can be used for patient stratification and therapy monitoring for progressed CRC with liver metastasis using cfDNA. Furthermore, we identified a 35-plex classifier for the identification of AAs with an AUC of 0.80.

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INTRODUCTION: Breast cancer (BC) is the most common cancer in women, with a high disease burden, especially in the advanced disease stages. Our study investigated the metabolomic profile of breast cancer patients' serum with the aim of identifying novel diagnostic biomarkers that could be used, especially for early disease detection. MATERIALS AND METHODS: Using targeted metabolomic serum profiling based on high-performance liquid chromatography mass spectrometry, women with BC (n = 39) and a control group (n = 21) were examined for 232 endogenous metabolites. RESULTS: The top performing biomarkers included acylcarnitines (ACs) and 9,12-linoleic acid. A combined panel of the top 4 biomarkers achieved 83% sensitivity and 81% specificity, with an area under the curve (AUC) of 0.839 (95% confidence interval, 0.811-0.867). Individual markers also provided significant predictive values: AC 12:0, sensitivity of 72%, specificity of 67%, and AUC of 0.71; AC 14:2, sensitivity of 74%, specificity of 71%, and AUC of 0.73; AC 14:0: sensitivity of 67%, specificity of 81%, and AUC of 0.73; and 9,12-linoleic acid, sensitivity of 69%, specificity of 67%, and AUC of 0.71. The individual markers, however, did not reach the high sensitivity and specificity of the 4-biomarker combination. CONCLUSION: Using mass spectrometry-targeted metabolomic profiling, ACs and 9,12-linoleic acid were identified as potential diagnostic biomarkers for breast cancer. Additionally, these identified metabolites could provide additional insight into cancer cell metabolism.

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PURPOSE: Endometrial cancer (EC) is the most common gynecological malignancy with high disease burden especially in advanced stages of the disease. Our study investigated the metabolomic profile of EC patient's serum with the aim of identifying novel diagnostic biomarkers that could be used especially in early disease detection. MATERIAL AND METHODS: Using targeted metabolomic serum profiling based on HPLC-TQ/MS, women with EC (n â€‹= â€‹15) and controls (n â€‹= â€‹21) were examined for 232 endogenous metabolites. RESULTS: Top performing biomarkers included ceramides, acylcarnitines and 1-methyl adenosine. Top 4 biomarkers combined achieved 94% sensitivity with 75% specificity with AUC 92.5% (CI 90.5-94.5%). Individual markers also provided significant predictive values: C16-ceramide achieved sensitivity 73%, specificity 81%, AUC 0.83, C22-ceramide sensitivity 67%, specificity 81%, AUC 0.77, hydroxyhexadecenoylcarnitine sensitivity 60%, specificity 96%, AUC 0.76 and 1-methyladenosine sensitivity 67%, specificity 81%, AUC 0.75. The individual markers, however, did not reach the high sensitivity and specificity of the 4-biomarker combination. CONCLUSIONS: Using mass spectrometry targeted metabolomic profiling, ceramides, acylcarnitines and 1-methyladenosine were identified as potential diagnostic biomarkers for EC. Additionally, these identified metabolites may provide additional insight into cancer cell metabolism.

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The data presented here are related to the research paper entitled "Metabolomic profiling suggests long chain ceramides and sphingomyelins as a possible diagnostic biomarker of epithelial ovarian cancer." (Kozar et al., 2018) [1]. Metabolomic profiling was performed on 15 patients with ovarian cancer, 21 healthy controls and 21 patients with benign gynecological conditions. HPLC-TQ/MS was performed on all samples. PLS-DA was used for the first line classification of epithelial ovarian cancer and healthy control group based on metabolomic profiles. Random forest algorithm was used for building a prediction model based over most significant markers. Univariate analysis was performed on individual markers to determine their distinctive roles. Furthermore, markers were also evaluated for their biological significance in cancer progression.

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INTRODUCTION: Epithelial ovarian cancer (EOC) is a disease with a poor survival rate mostly due to its discovery in late stages. The aim of this study was to investigate the metabolomic profile of ovarian cancer with the intention of identifying and describing novel biomarkers with diagnostic potential. MATERIAL AND METHODS: Targeted serum metabolomic profiling was performed on 15 patients with ovarian cancer, 21 healthy controls and 21 patients with benign ovarian conditions, using HPLC-TQ/MS. RESULTS: Panel of 49 top performing biomarkers shows separation between EOC and controls with 87% specificity and 87% sensitivity with AUC of 93% (CI 90%-95%). Using only 5 top biomarkers, specificity of 80% and sensitivity of 83% was achieved on extended sample set. Most significant biomarkers belong to sphingolipid classes, especially long chain ceramides and sphingomyelins. Different concentrations of various fatty acid chain lengths ceramides and sphingomyelins are also implying their respective roles in cell proliferation and growth inhibition. CONCLUSION: Long chain ceramides and sphingomyelins may serve as a novel biomarker for epithelial ovarian cancer detection and may also offer insight into the role of sphingolipid metabolism in cell proliferation.

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Layered ZnO microspheric particles were prepared by the thermal decomposition of layered hydrozincite (LZnHC), which was synthesized from zinc nitrate and urea in a water/PEG400 mixture. The influence of the starting reagents, their concentrations, and the amount of PEG in the water/PEG400 mixture on the particle growth was observed. The chemical aspect of the particle growth was proposed in the frame of the partial charge model (PCM), and the formation of [Zn(OH)(2)(OH(2))(4)](0) and [Zn(OH)(HCO(3))(OH(2))(3)](0) was predicted for the solid phase. The assumed growth mechanism, which follows the "nonclassical crystallization" concept of a self-assembling mechanism, was observed in situ by small-angle X-ray scattering (SAXS) and predicts the rapid formation of approximately 6 nm sized building units. The size of these nano building units, stable only in the reaction medium, remains nearly constant during the synthesis, as the concentration of the nano building units increases throughout the reaction. The nano building units connect into leaves of LZnHC with a thickness of 20 nm. These leaves of LZnHC are further agglomerated into porous, microsphere-like particles with sizes up to 4 µm.