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Background Herein, we report results from a genome-wide study conducted to identify protein quantitative trait loci (pQTL) for circulating angiogenic and inflammatory protein markers in patients with metastatic colorectal cancer (mCRC). The study was conducted using genotype, protein marker, and baseline clinical and demographic data from CALGB/SWOG 80405 (Alliance), a randomized phase III study designed to assess outcomes of adding VEGF or EGFR inhibitors to systemic chemotherapy in mCRC patients. Germline DNA derived from blood was genotyped on whole-genome array platforms. The abundance of protein markers was quantified using a multiplex enzyme-linked immunosorbent assay from plasma derived from peripheral venous blood collected at baseline. A robust rank-based method was used to assess the statistical significance of each variant and protein pair against a strict genome-wide level. A given pQTL was tested for validation in two external datasets of prostate (CALGB 90401) and pancreatic cancer (CALGB 80303) patients. Bioinformatics analyses were conducted to further establish biological bases for these findings. Results The final analysis was carried out based on data from 540,021 common typed genetic variants and 23 protein markers from 869 genetically estimated European patients with mCRC. Correcting for multiple testing, the analysis discovered a novel cis -pQTL in LINC02869 , a long non-coding RNA gene, for circulating TGF- β 2 levels (rs11118119; AAF = 0.11; P -value < 1.4e-14). This finding was validated in a cohort of 538 prostate cancer patients from CALGB 90401 (AAF = 0.10, P -value < 3.3e-25). The analysis also validated a cis -pQTL we had previously reported for VEGF-A in advanced pancreatic cancer, and additionally identified trans -pQTLs for VEGF-R3, and cis -pQTLs for CD73. Conclusions This study has provided evidence of a novel cis germline genetic variant that regulates circulating TGF- β 2 levels in plasma of patients with advanced mCRC and prostate cancer. Moreover, the validation of previously identified pQTLs for VEGF-A, CD73, and VEGF-R3, potentiates the validity of these associations.

Objective. This study was designed to explore the clinical efficacy of methotrexate combined with iguratimod on patients with rheumatoid arthritis (RA) and its influence on the expression levels of HOTAIR in serum. Methods. A total of 268 RA patients were selected as research objects, 145 patients received methotrexate alone were used as a control group (CG), 123 patients received methotrexate combined with iguratimod were taken as a research group (RG), and serum of 60 healthy people undergoing physical examination was selected as a healthy control group (HCG). The therapeutic value of two therapeutic methods for RA was compared, and the HOTAIR expression in serum was detected by qRT-PCR. Results. Compared with methotrexate used alone, the joint use of methotrexate and iguratimod could provide better clinical efficacy for RA patients and would not increase the incidence of adverse events. HOTAIR was highly expressed in the serum of RA patients, and its expression decreased after treatment. Conclusion. Combination therapy of methotrexate and iguratimod is a safe and effective way to treat RA patients, which can be popularized clinically.

Background and Objectives. Lymph node metastasis (LNM) is common in hepatocellular carcinoma (HCC). In order to intervene HCC LNM in advance, we developed a prediction nomogram based on serum long noncoding RNA (lncRNA). Methods. Serum samples from 242 HCC patients were gathered and randomly enrolled into the training and validation cohorts. LncRNAs screened out from microarray were quantified with qRT-PCR. Univariate and multivariate analyses were applied for screening independent risk factors. A prediction nomogram was ultimately developed for HCC LNM. The nomogram was estimated by discrimination and calibration tests in the validation cohort. The effects of the candidate lncRNA on the malignant phenotypes of HCC cells were further explored by wound healing assay and colony formation assay. Results. ENST00000418803, lnc-ZNF35-4:1, lnc-EPS15L1-2:1, BCLC stage, and vascular invasion were selected as components of the nomogram according to the adjusted multivariate analysis. The nomogram effectively predicted the HCC LNM risk among the cohorts with suitable calibration fittings and displayed high discrimination with C-index of 0.89 and 0.85. Moreover, the abnormally high expression of lnc-EPS15L1-2:1 in HCC cell lines showed significant carcinogenic effects. Conclusions. The noninvasive nomogram may provide more diagnostic basis for treatments of HCC. The biomarkers identified can bring new clues to basic researches.

Extracellular vesicles (EVs) contain a rich cargo of different RNA species with specialized functions and clinical applications. However, the landscape and characteristics of extracellular vesicle long RNA (exLR) in human blood remain largely unknown. We presented an optimized strategy for exLR sequencing (exLR-seq) of human plasma. The sample cohort included 159 healthy individuals, 150 patients with cancer (5 cancer types), and 43 patients with other diseases. Bioinformatics approaches were used to analyze the distribution and features of exLRs. Support vector machine algorithm was performed to construct the diagnosis classifier, and diagnostic efficiency was evaluated by ROC analysis. More than 10000 exLRs, including mRNA, circRNA, and lncRNA, were reliably detected in each exLR-seq sample from 1-2 mL of plasma. We observed that blood EVs contain a substantial fraction of intact mRNAs and a large number of assembling spliced junctions; circRNA was also enriched in blood EVs. Interestingly, blood exLRs reflected their tissue origins and the relative fractions of different immune cell types. Additionally, the exLR profile could distinguish patients with cancer from healthy individuals. We further showed that 8 exLRs can serve as biomarkers for hepatocellular carcinoma (HCC) diagnosis with high diagnostic efficiency in training [area under the curve (AUC) = 0.9527; 95% CI, 0.9170-0.9883], validation cohort (AUC = 0.9825; 95% CI, 0.9606-1), and testing cohort (AUC = 0.9627; 95% CI, 0.9263-0.9991). In summary, this study revealed abundant exLRs in human plasma and identified diverse specific markers potentially useful for cancer diagnosis.

Liquid biopsy recently became a very promising diagnostic method that has several advantages over conventional invasive methods. Liquid biopsy may serve as a source of several important biomarkers including cell-free nucleic acids (cf-NAs). Cf-DNA is widely used in prenatal testing in order to characterize fetal genetic disorders. Analysis of cf-DNA may provide information about the mutation profile of tumor cells, while cell-free non-coding RNAs are promising biomarker candidates in the diagnosis and prognosis of cancer. Many of these markers have the potential to help clinicians in therapy selection and in the follow-up of patients. Thus, cf-NA-based diagnostics represent a new path in personalized medicine. Although several reviews are available in the field, most of them focus on a limited number of cf-NA types. In this review, we give an overview about all known cf-NAs including cf-DNA, cf-mtDNA and cell-free non-coding RNA (miRNA, lncRNA, circRNA, piRNA, YRNA, and vtRNA) by discussing their biogenesis, biological function and potential as biomarker candidates in liquid biopsy. We also outline possible future directions in the field.

Glioblastoma multiforme (GBM) is the most common and aggressive malignant adult primary brain tumor. Despite surgical resection followed by radiotherapy and chemotherapy, the median survival rate is approximately 14 months. Although experimental therapies are in clinical trials for GBM, there is an urgent need for a peripheral GBM biomarker for measuring treatment response. As we have previously demonstrated that the long noncoding RNA HOX Transcript Antisense Intergenic RNA, or HOTAIR, is dysregulated in GBM and required for GBM cell proliferation, we hypothesized that HOTAIR expression may be utilized as a peripheral biomarker for GBM. HOTAIR expression was measured in serum from 43 GBM and 40 controls using quantitative real-time PCR (qRT-PCR). The PCR products were subsequently subcloned into pCR™4-TOPO®TA vectors for DNA sequencing. A ROC curve was also generated to examine HOTAIR’s prognostic value. The amount of HOTAIR in serum exosomes and exosome-depleted supernatant was calculated by qRT-PCR. The relative HOTAIR expression was also investigated in 15 pairs of GBM serum and tumors. We detected HOTAIR in serum from GBM patients. HOTAIR levels in serum samples from GBM patients was significantly higher than in the corresponding controls ( P  < 0.0001). The area under the ROC curve distinguishing GBM patients from controls was 0.913 (95% CI: 0.845–0.982, P  < 0.0001), with 86.1% sensitivity and 87.5% specificity at the cut-off value of 10.8. HOTAIR expression was significantly correlated with high grade brain tumors. In addition, Pearson correlation analysis indicated a medium correlation of serum HOTAIR levels and the corresponding tumor HOTAIR levels ( r  = 0.734, P  < 0.01). We confirmed via sequencing that the amplified HOTAIR from serum contained the HOTAIR sequence and maps to the known HOTAIR locus at 12q13. The serum-derived exosomes contain HOTAIR and the purified exosomes were validated by western blot and nanoparticle tracking analysis. Importantly, our results demonstrate that serum HOTAIR can be used as a novel prognostic and diagnostic biomarker for GBM.

Currently, resistance to trastuzumab, a human epidermal growth factor receptor 2 (HER2) inhibitor, has become an important obstacle to improving the clinical outcome of patients with advanced HER2+ breast cancer. While cell behavior may be modulated by long non-coding RNAs (lncRNAs), the contributions of lncRNAs within extracellular vesicles (exosomes) are largely unknown. To this end, the involvement and regulatory functions of potential lncRNAs contained within exosomes during the formation of chemoresistance in human breast cancer were investigated. Trastuzumab-resistant cell lines were established by continuously grafting HER2+ SKBR-3 and BT474 cells into trastuzumab-containing culture medium. An lncRNA micro-array assay followed by reverse transcription-quantitative polymerase chain reaction analysis identified that lncRNA-small nucleolar RNA host gene 14 (SNHG14) was upregulated in trastuzumab-resistant cells when compared with parental breast cancer cells. Functional experimentation demonstrated that knockdown of lncRNA-SNHG14 potently promoted trastuzumab-induced cytotoxicity. Furthermore, extracellular lncRNA-SNHG14 was able to be incorporated into exosomes and transmitted to sensitive cells, thus disseminating trastuzumab resistance. Treatment of sensitive cells with exosomes highly expressing lncRNA-SNHG14 induced trastuzumab resistance, while knockdown of lncRNA-SNHG14 abrogated this effect. The Signal Transduction Reporter Array indicated that lncRNA-SNHG14 may promote the effect of trastuzumab by targeting the apoptosis regulator Bcl-2 (Bcl-2)/apoptosis regulator BAX (Bax) signaling pathway. Furthermore, the expression level of serum exosomal lncRNA-SNHG14 was upregulated in patients who exhibited resistance to trastuzumab, compared with patients exhibiting a response. Therefore, lncRNA-SNHG14 may be a promising therapeutic target for patients with HER2+ breast cancer.

Long intergenic non-protein-coding RNA 152 (LINC00152) is one of the long noncoding RNAs (lncRNAs) abnormally expressed in gastric cancer tissues. However, its value in the diagnosis of gastric cancer is unclear. The aim of this study is to evaluate the clinical significance of plasma LINC00152 as a biomarker in the screening of gastric cancer and to explore the possible mechanism underling its stable existence in blood. We analyzed the levels of plasma LINC00152 in patients with gastric cancer and gastric epithelial dysplasia and healthy controls using quantitative reverse transcription polymerase chain reaction and then confirmed by sequencing. We also compared its levels in paired preoperative and postoperative plasma samples. In addition, we compared the levels of LINC00152 in plasma and in exosomes, which were extracted from the same plasma and confirmed by transmission electron microscopy. The levels of plasma LINC00152 were significantly elevated in gastric cancer patients compared with healthy controls. The sensitivity and specificity of plasma LINC00152 in the diagnosis of gastric cancer were 48.1 and 85.2 %, respectively. There were no significant differences of LINC00152 levels between gastric epithelial dysplasia patients and healthy controls. LINC00152 levels in preoperative plasma samples were lower than those in postoperative ones. There were also no differences between LINC00152 levels in plasma and in exosomes. All these results suggested that LINC00152 can be detected in plasma, and one of the possible mechanisms of its stable existence in blood was protected by exosomes. It has the possibility to be applied in gastric cancer diagnosis as a novel blood-based biomarker.

ObjectivePancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose at resectable stage. Recent studies have suggested that extracellular vesicles (EVs) contain long RNAs. The aim of this study was to develop a diagnostic (d-)signature for the detection of PDAC based on EV long RNA (exLR) profiling.DesignWe conducted a case-control study with 501 participants, including 284 patients with PDAC, 100 patients with chronic pancreatitis (CP) and 117 healthy subjects. The exLR profile of plasma samples was analysed by exLR sequencing. The d-signature was identified using a support vector machine algorithm and a training cohort (n=188) and was validated using an internal validation cohort (n=135) and an external validation cohort (n=178).ResultsWe developed a d-signature that comprised eight exLRs, including FGA, KRT19, HIST1H2BK, ITIH2, MARCH2, CLDN1, MAL2 and TIMP1, for PDAC detection. The d-signature showed high accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.960, 0.950 and 0.936 in the training, internal validation and external validation cohort, respectively. The d-signature was able to identify resectable stage I/II cancer with an AUC of 0.949 in the combined three cohorts. In addition, the d-signature showed superior performance to carbohydrate antigen 19-9 in distinguishing PDAC from CP (AUC 0.931 vs 0.873, p=0.028).ConclusionThis study is the first to characterise the plasma exLR profile in PDAC and to report an exLR signature for the detection of pancreatic cancer. This signature may improve the prognosis of patients who would have otherwise missed the curative treatment window.

Colorectal cancer (CRC) is one of the most common cancers worldwide, with a high mortality rate, especially in those that are diagnosed in late stages of the disease. The current screening blood-based markers, such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9), have low sensitivity and specificity. Meanwhile, other modalities are either expensive or invasive. Therefore, recent research has shifted towards a minimally invasive test, namely, liquid biopsy. Exosomes are favorable molecules sought in blood samples, since they are abundant, stable in circulation, and harbor genetic information and other biomolecules that could serve as biomarkers or even therapeutic targets. Furthermore, exosomal noncoding RNAs, such as miRNAs, lncRNAs, and circRNAs, have demonstrated the diagnostic potential to detect CRC at an early stage with a higher sensitivity and specificity than CEA and CA19-9 alone. Moreover, they have prognostic potential that is TNM stage specific and could serve as predictive biomarkers for the most common chemotherapeutic drug and combination regimen in CRC, which are 5-FU and FOLFOX, respectively. Therefore, in this review, we focus on the role of these exosomal noncoding RNAs as diagnostic, prognostic, and predictive biomarkers. In addition, we discuss the advantages and challenges of exosomes as a liquid biopsy target.