A comprehensive evaluation of full-spectrum cell-free RNAs highlights cell-free RNA fragments for early-stage hepatocellular carcinoma detection.

Various studies have reported cell-free RNAs (cfRNAs) as noninvasive biomarkers for detecting hepatocellular carcinoma (HCC). However, they have not been independently validated, and some results are contradictory. We provided a comprehensive evaluation of various types of cfRNA biomarkers and a full mining of the biomarker potential of new features of cfRNA. We first systematically reviewed reported cfRNA biomarkers and calculated dysregulated post-transcriptional events and cfRNA fragments. In 3 independent multicentre cohorts, we further selected 6 cfRNAs using RT-qPCR, built a panel called HCCMDP with AFP using machine learning, and internally and externally validated HCCMDP's performance. We identified 23 cfRNA biomarker candidates from a systematic review and analysis of 5 cfRNA-seq datasets. Notably, we defined the cfRNA domain to describe cfRNA fragments systematically. In the verification cohort (n = 183), cfRNA fragments were more likely to be verified, while circRNA and chimeric RNA candidates were neither abundant nor stable as qPCR-based biomarkers. In the algorithm development cohort (n = 287), we build and test the panel HCCMDP with 6 cfRNA markers and AFP. In the independent validation cohort (n = 171), HCCMDP can distinguish HCC patients from control groups (all: AUC = 0.925; CHB: AUC = 0.909; LC: AUC = 0.916), and performs well in distinguishing early-stage HCC patients (all: AUC = 0.936; CHB: AUC = 0.917; LC: AUC = 0.928). This study comprehensively evaluated full-spectrum cfRNA biomarker types for HCC detection, highlighted the cfRNA fragment as a promising biomarker type in HCC detection, and provided a panel HCCMDP. National Natural Science Foundation of China, and The National Key Basic Research Program (973 program).

Ning C ，Cai P ，Liu X ，Li G ，Bao P ，Yan L ，Ning M ，Tang K ，Luo Y ，Guo H ，Wang Y ，Wang Z ，Chen L ，Lu ZJ ，Yin J ... -  《EBioMedicine》

Integrative analysis of long extracellular RNAs reveals a detection panel of noncoding RNAs for liver cancer.

Rationale: Long extracellular RNAs (exRNAs) in plasma can be profiled by new sequencing technologies, even with low abundance. However, cancer-related exRNAs and their variations remain understudied. Methods: We investigated different variations (i.e. differential expression, alternative splicing, alternative polyadenylation, and differential editing) in diverse long exRNA species (e.g. long noncoding RNAs and circular RNAs) using 79 plasma exosomal RNA-seq (exoRNA-seq) datasets of multiple cancer types. We then integrated 53 exoRNA-seq datasets and 65 self-profiled cell-free RNA-seq (cfRNA-seq) datasets to identify recurrent variations in liver cancer patients. We further combined TCGA tissue RNA-seq datasets and validated biomarker candidates by RT-qPCR in an individual cohort of more than 100 plasma samples. Finally, we used machine learning models to identify a signature of 3 noncoding RNAs for the detection of liver cancer. Results: We found that different types of RNA variations identified from exoRNA-seq data were enriched in pathways related to tumorigenesis and metastasis, immune, and metabolism, suggesting that cancer signals can be detected from long exRNAs. Subsequently, we identified more than 100 recurrent variations in plasma from liver cancer patients by integrating exoRNA-seq and cfRNA-seq datasets. From these datasets, 5 significantly up-regulated long exRNAs were confirmed by TCGA data and validated by RT-qPCR in an independent cohort. When using machine learning models to combine two of these validated circular and structured RNAs (SNORD3B-1, circ-0080695) with a miRNA (miR-122) as a panel to classify liver cancer patients from healthy donors, the average AUROC of the cross-validation was 89.4%. The selected 3-RNA panel successfully detected 79.2% AFP-negative samples and 77.1% early-stage liver cancer samples in the testing and validation sets. Conclusions: Our study revealed that different types of RNA variations related to cancer can be detected in plasma and identified a 3-RNA detection panel for liver cancer, especially for AFP-negative and early-stage patients.

Zhu Y ，Wang S ，Xi X ，Zhang M ，Liu X ，Tang W ，Cai P ，Xing S ，Bao P ，Jin Y ，Zhao W ，Chen Y ，Zhao H ，Jia X ，Lu S ，Lu Y ，Chen L ，Yin J ，Lu ZJ ... -  《Theranostics》

Comprehensive evaluation of microRNA as a biomarker for the diagnosis of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. Current guidelines for HCC management recommend surveillance of high-risk patients every 6 mo using ultrasonography. Serum biomarkers, like alpha-fetoprotein (AFP), protein induced by vitamin K absence/antagonist-II (PIVKA-II) and lectin-reactive AFP, show suboptimal performance for detection of HCC, which is crucial for successful resection or treatment. Thus, there is a significant need for new biomarkers to aid early diagnosis of HCC. Studies have shown that the expression level of human microRNAs (miRNAs), a small, non-coding RNA species released into the blood, can serve as an early marker for various diseases, including HCC. To evaluate the diagnostic role of miRNAs in HCC as single markers, signatures or in combination with known protein biomarkers. Our prospective, multicenter, case-control study recruited 660 participants (354 controls with chronic liver disease and 306 participants with HCC) and employed a strategy of initial screening by two independent methods, real-time quantitative PCR (n = 60) and next-generation sequencing (n = 100), to assess a large number of miRNAs. The results from the next-generation sequencing and real-time quantitative PCR screening approaches were then combined to select 26 miRNAs (including two putative novel miRNAs). Those miRNAs were analyzed for their diagnostic potential as single markers or in combination with other miRNAs or established protein biomarkers AFP and PIVKA-II via real-time quantitative PCR in training (n = 200) and validation cohorts (n = 300). We identified 26 miRNAs that differentiated chronic liver disease controls from (early) HCC via two independent discovery approaches. Three miRNAs, miR-21-5p (miR-21), miR-320a and miR-186-5p, were selected by both methods. In the training cohort, only miR-21, miR-320d and miR-423 could significantly distinguish (Q < 0.05) between the HCC and chronic liver disease control groups. In the multivariate setting, miR-21 with PIVKA-II was selected as the best combination, resulting in an area under the curve of 0.87 for diagnosis and area under the curve of 0.74 for early diagnosis of HCC. In the validation cohort, only miR-21 and miR-423 could be confirmed as potential HCC biomarkers. A combination of miRNAs did not perform better than any single miRNA. Improvement of PIVKA-II performance through combination with miRNAs could not be confirmed in the validation panel. Two putative miRs, put-miR-6 and put-miR-99, were tested in the training and validation panels, but their expression could only be detected in very few samples and at a low level (cycle threshold between 31.24 and 34.97). miRNAs alone or as a signature in combination with protein biomarkers AFP and PIVKA-II do not improve the diagnostic performance of the protein biomarkers.

Malik J ，Klammer M ，Rolny V ，Chan HL ，Piratvisuth T ，Tanwandee T ，Thongsawat S ，Sukeepaisarnjaroen W ，Esteban JI ，Bes M ，Köhler B ，Swiatek-de Lange M ... -  《-》

Long noncoding RNA MyD88 functions as a promising diagnostic biomarker in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most frequent malignancies. Alpha-fetoprotein (AFP) has some limitations in diagnosing early HCC. Recently, long noncoding RNAs (lncRNAs) showed great potential as tumor diagnostic biomarkers, and lnc-MyD88 was previously identified as a carcinogen in HCC. Here, we explored its diagnostic value as a plasma biomarker. Quantitative real-time PCR was adopted to detect lnc-MyD88 expression in plasma samples of 98 HCC patients, 52 liver cirrhosis (LC) patients, and 105 healthy people. The correlation between lnc-MyD88 and clinicopathological factors was analyzed through chi-square test. The receiver operating characteristic (ROC) curve was used to analyze the sensitivity, specificity, Youden index, and area under the curve (AUC) of lnc-MyD88 and AFP alone and in combination for the diagnosis of HCC. The relationship between MyD88 and immune infiltration was analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm. Lnc-MyD88 was highly expressed in plasma samples of HCC and hepatitis B virus (HBV)-associated HCC patients. Lnc-MyD88 had better diagnostic value than AFP in HCC patients using healthy people or LC patients as control (healthy people, AUC: 0.776 vs. 0.725; LC patients, AUC: 0.753 vs. 0.727). The multivariate analysis showed that lnc-MyD88 had great diagnostic value for distinguishing HCC from LC and healthy people. Lnc-MyD88 had no correlation with AFP. Lnc-MyD88 and AFP were independent diagnostic factors for HBV-associated HCC. The AUC, sensitivity, and Youden index of the combined diagnosis of lnc-MyD88 and AFP combined were higher than those of lnc-MyD88 and AFP alone. The ROC curve of lnc-MyD88 for the diagnosis of AFP-negative HCC was plotted with a sensitivity of 80.95%, a specificity of 79.59%, and an AUC value of 0.812 using healthy people as control. The ROC curve also presented its great diagnostic value using LC patients as control (sensitivity: 76.19%, specificity: 69.05%, AUC value: 0.769). Lnc-MyD88 expression was correlated with microvascular invasion in HBV-associated HCC patients. MyD88 was positively correlated with infiltrating immune cells and immune-related genes. The high expression of plasma lnc-MyD88 in HCC is distinct and could be utilized as a promising diagnostic biomarker. Lnc-MyD88 had great diagnostic value for HBV-associated HCC and AFP-negative HCC, and it had higher efficacy in combination with AFP.

Wang Z ，Gao P ，Sun W ，Rehman AU ，Jiang J ，Xu S ，Xue C ，Zhu C ，Qin X ... -  《Frontiers in Endocrinology》

Optimisation of quantitative miRNA panels to consolidate the diagnostic surveillance of HBV-related hepatocellular carcinoma.

Tat Trung N ，Duong DC ，Tong HV ，Hien TTT ，Hoan PQ ，Bang MH ，Binh MT ，Ky TD ，Tung NL ，Thinh NT ，Sang VV ，Thao LTP ，Bock CT ，Velavan TP ，Meyer CG ，Song LH ，Toan NL ... -  《PLoS One》