BackgroundFree fatty acids (FFAs) are associated with insulin secretion and insulin resistance. However, the associations among FFAs, obesity, and progression from a normal to a prediabetic state are unclear.MethodsNondiabetic subjects (5,952) were divided in two groups according to their body mass index (BMI): obese subjects (BMI ≥24 kg/m2) and nonobese subjects (BMI <24 kg/m2). Clinical and multiple glucolipid metabolism data were collected. The homeostasis model assessment for insulin resistance (HOMA-IR) and β-cell function (HOMA-β) was used. HbA1c level between 5.7% and 6.4% was considered prediabetic. Nonparametric tests, one-way ANOVA, and linear correlation analysis were performed. R and SPSS 23.0 software programs were used to analyze the results.ResultsA U-shaped relationship between FFAs and HOMA-IR was observed. After adjusting for potential confounders, the turning points of FFA levels in the curves were 0.54 mmol/L in the nonobese group and 0.61 mmol/L in the obese group. HOMA-IR levels decreased with increasing FFA concentrations before the turning points (regression coefficient [β]= – 0.9, P=0.0111, for the nonobese group; β=0.2, P=0.5094, for the obese group) and then increased (β=0.9, P=0.0069, for the nonobese group; β=1.5, P=0.0263 for the obese group) after the points. Additionally, our study also identified that FFAs were associated with the prediabetes status in obese individuals.ConclusionFFA levels were associated with insulin resistance in nondiabetic subjects, and HOMA-IR in nonobese individuals was more sensitive to FFA changes. Monitoring and controlling plasma FFA levels in obese subjects is significant in decreasing insulin resistance and preventing diabetes.

BackgroundLung cancer (LC) is the most common malignancy in the world. Many long non‐coding RNAs (lncRNAs) have been reported to be associated with LC; however, the function of KCNQ1OT1 in LC requires exploration.MethodsWe conducted in silico analysis with data from The Cancer Genome Atlas to investigate the association between KCNQ1OT1 and LC. A Kaplan–Meier plotter was used to analyze the function of KCNQ1OT1 on LC patient prognosis. Quantitative reverse transcription‐PCR (qRT‐PCR) was performed to confirm previous results. An A549 lung cancer cell was transfected with pcDNA‐KCNQ1OT1, and methyl thiazolyl tetrazolium assay was performed to investigate the function of KCNQ1OT1 on cell proliferation. in vivo assay was performed with nude mice.ResultsBioinformatics analysis and qRT‐PCR indicated that KCNQ1OT1 expression was higher in stage I LC patients (P < 0.01), and survival analysis showed that high expression of KCNQ1OT1 in LC patients was associated with better prognosis (P < 0.05). qRT‐PCR showed a negative correlation between KCNQ1OT1 and Ki67 expression and tumor size (P < 0.01), which indicated that KCNQ1OT1 is associated with tumor growth in LC. There was no significant correlation between KCNQ1OT1 level and lymph node metastasis (P > 0.05). KCNQ1OT1 overexpression significantly inhibited cell proliferation and tumor growth in vitro and in vivo (P < 0.05).ConclusionOur preliminary data showed that KCNQ1OT1 is overexpressed in early stage LC and is correlated with better prognosis in LC patients, possibly by suppressing cell proliferation.

Lung cancer leads to the most cancer-related death in the world. It was shown from the increasing evidences that long non-coding RNAs (lncRNAs) are emerging as molecules for diagnosis, prognosis and even therapy of lung cancer and other malignancies. The biological functions or involved signaling pathways of lncRNAs are always found to be inconsistent among different types of malignancies.However, no available literature has systemically summarized differences in the functions and underlying molecular mechanisms of lncRNAs between lung cancer and other cancers. In this review, the biological functions and molecular mechanisms of lncRNAs in lung cancer were introduced. Furthermore, their functional differences between lung cancer and other malignancies were discussed. Finally, their potential clinical applications in future lung cancer therapy were focused on.

Background: Circular RNA has been revealed as a potential biomarker in multiple malignancies. However, few studies have focused on its potential to be prognostic markers in lung squamous cell carcinoma (LSCC).In this work, we aimed to build a prognostic model of resected LSCC based on circular RNA pyruvate dehydrogenase kinase 1 (circPDK1) and other clinicopathological factors.Methods: circPDK1 was identified via next-generation sequencing. Three hundred two cases of LSCC tissue and their adjacent normal lung tissues were obtained from multiple medical centers and divided into study cohort (n=232) and validation cohort (n=70). The expression of circPDK1 was detected for analyzing its potential prognostic value for recurrence-free survival (RFS) and overall survival (OS) in LSCC. Finally, combined with circPDK1, T staging, lymph nodes (LN) metastasis status, age, and serum squamous cell Carcinoma Antigen (SCCAg), we built a prognostic model by nomograms method and confirmed it in the validation cohort.Results: CircPDK1 was identified to be overexpressed (P<0.01) in LSCC. Through analysis in study cohort, circPDK1 low patients (less than the mean expression, n=124) showed more lymph nodes metastasis (P=0.025), more vascular invasion (VI) (P=0.047), more visceral pleural invasion (VPI) (P=0.015) and poorer prognosis (P=0.003) than circPDK1 high ones (n=108). Univariate and multivariate analysis showed that circPDK1, T staging, LN status, age, and SCCAg were significant prognostic factors for RFS and OS. The prognostic model based on these factors showed the concordance index (C-index) of 0.8214 and 0.8359 for predicting 5-year RFS and OS, respectively. Finally, the calibration curves were performed in the study cohort and a validation cohort to evaluate the model's efficiency.Conclusions: circPDK1 was identified as a potential biomarker of resected LSCC. The prognostic model including circPDK1, T staging, LN status, age, and SCCAg could effectively predict prognosis of resected LSCC.

Background: As a common endocrine gland malignancy worldwide, papillary thyroid cancer (PTC) shows a relatively high survival of PTC patients, but their prognosis becomes worse as soon as the lymph nodes are invaded. In our study, we found that a long non-coding RNA (lncRNA) X-inactive specific transcript (XIST) was associated with lymph node metastasis in PTC. Our purpose was to explore the functions and underlying mechanisms of this lncRNA in PTC.Methods: Bioinformatics analyses were performed with data from The Cancer Genome Atlas (TCGA) database. We confirmed the results in PTC tissues using quantitative real time polymerase chain reaction (qRT-PCR) and in situ hybridization (ISH), and then studied the functions using Transwell ® invasion and migration assays in vitro with TPC-1 and BCPAP cells. The correlation between XIST and the TGF-β pathway was confirmed using qRT-PCR and western blotting of PTC cell samples. All data were analyzed with SPSS software.Results: Using bioinformatics analyses and RNA detection techniques, we found that lncRNA XIST was associated with lymph node metastasis in PTC. The in vitro assays showed that XIST inhibited PTC cell invasion and migration. Furthermore, we found that XIST expression was correlated with Smad4, a core protein in the TGF-β pathway. Through co-transfection assays in PTC cells, we showed that XIST expression was inhibited by TGF-β, and this promoted PTC cell invasion and migration. Conclusions:We found that lncRNA XIST functioned as an inhibitor of PTC metastasis. Furthermore, TGF-β suppressed the expression of this lncRNA in PTC cells. As XIST is regulated by TGF-β and functions as an inhibitor of PTC metastasis, it may serve as a new biomarker of PTC patient metastasis and prognosis.