Molecular and clinical features of papillary thyroid cancer in adult patients with a non-classical phenotype.

Purpose: Genotyping is fundamental in papillary thyroid cancer (PTC) and helps to enhance diagnosis and prognosis and determine appropriate treatments. The phenotype-genotype association in PTC was previously studied, with BRAF V600E characterizing classic PTC and tall-cell PTC and RAS mutations characterizing follicular-variant PTC. In clinic, some non-classical histological subtypes of PTC were also identified, however, their genotype remains unclear. In this study, we collected samples of these non-classical PTC after the exclusion of classic phenotypes and examined their phenotypes, genotype and the relationship between phenotype and genotype. Methods: We screened out non-classical PTC by excluding classical PTC from 1,059 different thyroid samples, and a total of 24 cases was obtained and described from the morphological features, which is rare in differentiated PTC. DNA/RNA sequencing was performed using 18 available samples to describe the genetic features. Results: PTC with the non-classical phenotype were characterized cuboidal to low columnar tumor cells with subtle nuclear features of PTC and without discernible nuclear elongation, concurrently with dense microfollicles, delicate papillae or solid nodules with delicate fibrovascular cores. They were associated with lymphatic vessel invasion (P<0.001) but not with a worse prognosis (P=0.791). Gene fusions were identified in 14 of 18 (77.8%) cases, including eight fusions of NTRK and six fusions of RET. The high percentage of fusions in this papillary thyroid cancer subgroup suggested a correlation of gene fusions with the phenotype that does not belong to the BRAF V600E-mutant or RAS-mutant group. Conclusions: Our study retrospectively screened a large cohort of different thyroid tissue samples, and presented the histopathological and genetic features of a non-classical phenotype of PTC from 24 patients. It may contribute to diagnose in PTC, and patients of these non-classical phenotype may benefit from targeted therapy, compared to a natural patient cohort without selection.

Molecular characterization of genomic breakpoints of ALK rearrangements in non-small cell lung cancer.

ALK rearrangement is called the 'diamond mutation' in non-small cell lung cancer (NSCLC). Accurately identifying patients who are candidates for ALK inhibitors is a key step in making clinical treatment decisions. In this study, a total of 783 ALK rearrangement-positive NSCLC cases were identified by DNA-based next-generation sequencing (NGS), including 731 patients with EML4-ALK and 52 patients with other ALK rearrangements. Diverse genomic breakpoints of ALK rearrangements were identified. Approximately 94.4% (739/783) of the cases carried ALK rearrangements with genomic breakpoints in the introns of ALK and its partner genes, and 2.8% (21/739) of these cases resulted in frameshift transcripts of ALK. Meanwhile, 5.6% (44/783) of the ALK rearrangement-positive cases had breakpoints in the exons that would be expected to result in abnormal transcripts. RNA-based NGS was performed to analyse the aberrant fusions at the transcript level. Some of these rearranged DNAs were not transcribed, and the others were fixed by some mechanisms so that the fusion kinase proteins could be expressed. Altogether, these findings emphasize that, when using DNA-based NGS, functional RNA fusions should be confirmed in cases with uncommon/frameshift rearrangement by RNA-based assays.

Screening and identification of potential novel lipid biomarkers for non-small cell lung cancer using ultra-high performance liquid chromatography tandem mass spectrometry.

Lung cancer is characterized by a high incidence rate and low survival rate. It is important to achieve early diagnosis of the disease. We applied ultra-high performance liquid chromatography tandem mass spectrometry to screen plasma lipid spectrum in non-small cell lung cancer (NSCLC) patients, healthy controls (HC), and community-acquired pneumonia (CAP) patients. Modeling employing orthogonal partial least squares-discriminant analysis combined with t-test was used to screen the differential lipids. Logistic regression analysis was used to establish the diagnostic model, while the accuracy was verified by 10-fold cross-validation. The results showed that the abnormal metabolism of lipid in NSCLC mainly comprised fatty acid metabolism, phospholipid metabolism, and glyceride metabolism. Four potential biomarkers, including LPC (14:0/0:0), LPI (14:1/0:0), DG (14:0/18:2/0:0), and LPC (16:1/0:0), were fitted by the receiver operating characteristic curve model with the area under curve (AUC) value of 0.856, and the specificity and sensitivity were 87.0 and 78.0%, respectively. The results of cross validation showed that the AUC value of the model was 0.812, the sensitivity was 72.9%, and the specificity was 82.6%. The positive rate of four potential lipid biomarkers in this study (>60.0%) was higher than that of existing tumor biomarkers in the clinical application. We investigated the plasma lipid profile of NSCLC patients and identified lipid biomarkers with potential diagnostic values. From the lipidomics perspective, our study may lay a foundation for the biomarker-based early diagnosis of lung cancer.

Identifying Prognostic Significance of RCL1 and Four-Gene Signature as Novel Potential Biomarkers in HCC Patients.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly malignant disease, and it is characterized by rapid progression and low five-year survival rate. At present, there are no effective methods for monitoring the treatment and prognosis of HCC. METHODS: The transcriptome and gene expression profiles of HCC were obtained from the Cancer Genome Atlas (TCGA) program, International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. The random forest method was applied to construct a four-gene prognostic model based on RNA terminal phosphate cyclase like 1 (RCL1) expression. The Kaplan-Meier method was performed to evaluate the prognostic value of RCL1, long noncoding RNAs (AC079061, AL354872, and LINC01093), and four-gene signature (SPP1, MYBL2, TRNP1, and FTCD). We examined the relationship between RCL1 expression and immune cells infiltration, tumor mutation burden (TMB), and microsatellite instability (MSI). RESULTS: The results of multiple databases indicated that the aberrant expression of RCL1 was associated with clinical outcome, immune cells infiltration, TMB, and MSI in HCC patients. Meanwhile, we found that long noncoding RNAs (AC079061, AL354872, and LINC01093) and RCL1 were significantly coexpressed in HCC patients. We also confirmed that the four-gene signature was an independent prognostic factor for HCC patients. Ferroptosis potential index, immune checkpoint molecules, and clinical feature were found to have obvious correlations with risk score. The area under the receiver operating characteristic curve values for the model were 0.7-0.8 in the training set and the validation set, suggesting high robustness of the four-gene signature. We then built a nomogram for facilitating the use in clinical practice. CONCLUSION: Our study demonstrated that RCL1 and a novel four-gene signature can be used as prognostic biomarkers for predicting clinical outcome in HCC patients; and this model may assist in individualized treatment monitoring of HCC patients in clinical practice.

Research status and prospects of biomarkers for nasopharyngeal carcinoma in the era of high­throughput omics (Review).

As a malignant tumor type, nasopharyngeal carcinoma (NPC) is characterized by distinct geographical, ethnic and genetic differences; presenting a major threat to human health in many countries, especially in Southern China. At present, no accurate and effective methods are available for the early diagnosis, efficacious evaluation or prognosis prediction for NPC. As such, a large number of patients have locoregionally advanced NPC at the time of initial diagnosis. Many patients show toxic reactions to overtreatment and have risks of cancer recurrence and distant metastasis owing to insufficient treatment. To solve these clinical problems, high­throughput '­omics' technologies are being used to screen and identify specific molecular biomarkers for NPC. Because of the lack of comprehensive descriptions regarding NPC biomarkers, the present study summarized the research progress that has been made in recent years to discover NPC biomarkers, highlighting the existing problems that require exploration. In view of the lack of authoritative reports at present, study design factors that affect the screening of biomarkers are also discussed here and prospects for future research are proposed to provide references for follow­up studies of NPC biomarkers.

Identification of potential lipid biomarkers for active pulmonary tuberculosis using ultra-high-performance liquid chromatography-tandem mass spectrometry.

Early diagnosis of active pulmonary tuberculosis (TB) is the key to controlling the disease. Host lipids are nutrient sources for the metabolism of Mycobacterium tuberculosis. In this research work, we used ultra-high-performance liquid chromatography-tandem mass spectrometry to screen plasma lipids in TB patients, lung cancer patients, community-acquired pneumonia patients, and normal healthy controls. Principal component analysis, orthogonal partial least squares discriminant analysis, and K-means clustering algorithm analysis were used to identify lipids with differential abundance. A total of 22 differential lipids were filtered out among all subjects. The plasma phospholipid levels were decreased, while the cholesterol ester levels were increased in patients with TB. We speculate that the infection of M. tuberculosis may regulate the lipid metabolism of TB patients and may promote host-assisted bacterial degradation of phospholipids and accumulation of cholesterol esters. This may be related to the formation of lung cavities with caseous necrosis. The results of receiver operating characteristic curve analysis revealed four lipids such as phosphatidylcholine (PC, 12:0/22:2), PC (16:0/18:2), cholesteryl ester (20:3), and sphingomyelin (d18:0/18:1) as potential biomarkers for early diagnosis of TB. The diagnostic model was fitted by using logistic regression analysis and combining the above four lipids with a sensitivity of 92.9%, a specificity of 82.4%, and the area under the curve (AUC) value of 0.934 (95% CI 0.873 - 0.971). The machine learning method (10-fold cross-validation) demonstrated that the model had good accuracy (0.908 AUC, 85.3% sensitivity, and 85.9% specificity). The lipids identified in this study may serve as novel biomarkers in TB diagnosis. Our research may pave the foundation for understanding the pathogenesis of TB.

Screening and identification of plasma lncRNAs uc.48+ and NR_105053 as potential novel biomarkers for cured pulmonary tuberculosis.

BACKGROUND: Tuberculosis (TB) treatment takes a long time, and a gold standard test to define TB cure is lacking. This may lead to early discharge of TB patients, resulting in an increased risk of disease transmission and drug resistance. Plasma lncRNAs might act as potential biomarkers to evaluate TB cure in an efficient and precise manner. METHODS: A lncRNA microarray assay was used to screen differentially expressed plasma lncRNAs in untreated TB and cured TB subjects. The expression levels of lncRNAs were verified by qPCR. Target genes of lncRNAs were predicted using a coding-non-coding gene co-expression network and mRNA-lncRNA-miRNA interaction network analysis. RESULTS: The expression levels of lncRNAs uc.48+ (p < 0.001) and NR_105053 (p = 0.03) were found to differ significantly between the untreated TB group and the cured TB group. The predicted target genes of uc.48+ were EP300, BAI1 and NR_105053 were TLR9, MYD88, BAI1, respectively. A predictive model for cured TB was established by the combination of uc.48+ and NR_105053 expression, with a sensitivity of 90.00% and specificity of 86.36%, and an area under the curve (AUC) value of 0.945. CONCLUSIONS: lncRNAs uc.48+ and NR_105053 may serve as potential biomarkers to distinguish between untreated TB patients and cured TB subjects. This study provides an experimental basis to evaluate the effect of TB treatment and may also provide new clues to the pathological mechanisms of TB.

Plasma metabolites Xanthine, 4-Pyridoxate, and d-glutamic acid as novel potential biomarkers for pulmonary tuberculosis.

BACKGROUND: The lack of rapid and efficient diagnostic methods has been one of the most frustrating challenges in controlling the pulmonary tuberculosis (TB) epidemic. This study was aimed to identify novel non-invasive biomarkers for pulmonary TB. METHODS: The subjects in this study were divided into four groups: the pulmonary TB group, the community-acquired pneumonia (CAP) group, the lung cancer (LC) group, and the normal control (NC) group. Plasma small molecule metabolites were investigated in each group by using ultra-high performance liquid chromatography coupled with Q Exactive mass spectrometry. Multivariate statistical methods and bioinformatics were used to analyze the data. RESULTS: We identified three differential plasma metabolites such as, Xanthine, 4-Pyridoxate and d-glutamic acid in the pulmonary TB group, compared to the other groups (CAP, LC and NC). The pathway enrichment analysis indicated that the energy source in pulmonary TB was multi-center, which might be involved in maintaining the reproductive ability and virulence of Mycobacterium tuberculosis. CONCLUSION: The results suggested that Xanthine, 4-Pyridoxate, and d-glutamic acid may serve as potential biomarkers for pulmonary TB. The present study provides experimental basis for developing potential biomarkers of pulmonary TB.

l-Histidine, arachidonic acid, biliverdin, and l-cysteine-glutathione disulfide as potential biomarkers for cured pulmonary tuberculosis.

Lack of laboratory standards for cured tuberculosis (TB) can lead to early discharge of untreated TB patients from the hospital, resulting in increased risk of TB spread and of developing drug resistant Mycobacterium tuberculosis (Mtb). We used ultra-high performance liquid chromatography coupled with mass spectrometry (LC-MS) to detect heparin anticoagulant in plasma of untreated TB patients, two-month treated TB patients, cured TB subjects, and healthy controls. Screening of differentially expressed metabolites resulted in identification of four differentially expressed metabolites such as, l-Histidine, Arachidonic acid (AA), Biliverdin, and l-Cysteine-glutathione disulfide after 6 months of TB treatment. Among them, l-Cysteine-glutathione disulfide and AA could be identified after 2 months of TB treatment. We established a cured TB model with an area under the curve (AUC) of 0.909 (95% CI, 0.802-0.970), 86.2% sensitivity, and 85.2% specificity. The diagnostic model fitted from the four differential metabolites in combination (l-Histidine, AA, Biliverdin, and l-Cysteine-glutathione disulfide) can be used as potential biomarkers for cured TB. Our study provided laboratory standards for hospital discharge of TB patients, as well as experimental basis for evaluating the efficacy of anti-TB drugs.

Differential expression and regulation of angiopoietin-2 in mouse uterus during preimplantation period.

Angiogenesis is crucial to successful implantation and decidualization, however, as an important angiogenic growth factor, the effect of Ang-2 in the process of implantation and decidualization is still unknown. This study is to investigate the differential expression of Ang-2 in mouse uterus during early pregnancy and its regulation by steroid hormones using in situ hybridization and RT-PCR. There is no detectable Ang-2 mRNA signal on days 1-5 of pregnancy by in situ hybridization. On days 6-8, Ang-2 mRNA is mainly expressed in the primary decidua of mesometrial side, and the expression gradually increases. By RT-PCR, a significantly higher level of Ang-2 expression is observed on day 8 of pregnancy, although Ang-2 expression can be found through days 1-8. Similarly, Ang-2 is highly expressed in decidualized cells under artificial decidualization. In the ovariectomized mouse uterus, Ang-2 expression gradually increases after estrogen injection and with peak levels at 12 hr, while progesterone injection can cause a decline in uterine Ang-2 mRNA level, which reaches a nadir at 12 hr. These results suggest that Ang-2 may play a key role in the process of mouse decidualization. Estrogen can induce the expression of Ang-2 while progesterone can inhibit its expression in the ovariectomized mouse uterus.