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BACKGROUND: Iron deficiency (ID) is the most common nutritional deficiency affecting young children. Serum ferritin concentration is the preferred biomarker for measuring iron status because it reflects iron stores; however, blood collection can be distressing for young children and can be logistically difficult. A noninvasive means to measure iron status would be attractive to either diagnose or screen for ID in young children. OBJECTIVES: This study aimed to determine the correlation between urinary and serum ferritin concentrations in young children; to determine whether correcting urinary ferritin for creatinine and specific gravity improves the correlation; and to determine a urine ferritin cut point to predict ID. METHODS: Validation study was conducted using paired serum and urine collected from 3-y-old children (n = 142) participating in a longitudinal birth cohort study: the ORIGINS project in Perth, Western Australia. We calculated the sensitivity, specificity, positive, and negative predictive values of urinary ferritin amount in identifying those with ID at the clinical cut point used by the World Health Organization (serum ferritin concentration of <12 ng/mL). RESULTS: Urine ferritin, corrected for creatinine, correlated moderately with serum ferritin [r = 0.53 (0.40-0.64)] and performed well in predicting those with ID (area under the curve: 0.85; 95% confidence interval: 0.75, 0.94). Urine ferritin <2.28 ng/mg creatinine was sensitive (86%) and specific (77%) in predicting ID and had a high negative predictive value of 97%; however, the positive predictive value was low (40%) owing to the low prevalence of ID in the sample (16%). CONCLUSIONS: Urine ferritin shows good diagnostic performance for ID. This noninvasive biomarker maybe a useful screening tool to exclude ID in healthy young children; however, further research is needed in other populations.

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BACKGROUND: Single-nucleotide variations (SNVs; formerly SNPs) are inherited genetic variants that can be easily determined in routine clinical practice using a simple blood or saliva test. SNVs have potential to serve as noninvasive biomarkers for predicting cancer-specific patient outcomes after resection of pancreatic ductal adenocarcinoma (PDAC). Two recent analyses led to the identification and validation of three SNVs in the CD44 and CHI3L2 genes (rs187115, rs353630, and rs684559), which can be used as predictive biomarkers to help select patients most likely to benefit from pancreatic resection. These variants were associated with an over 2-fold increased risk for tumor-related death in three independent PDAC study cohorts from Europe and the United States, including The Cancer Genome Atlas cohorts (reaching a P value of 1×10-8). However, these analyses were limited by the inherent biases of a retrospective study design, such as selection and publication biases, thereby limiting the clinical use of these promising biomarkers in guiding PDAC therapy. OBJECTIVE: To overcome the limitations of previous retrospectively designed studies and translate the findings into clinical practice, we aim to validate the association of the identified SNVs with survival in a controlled setting using a prospective cohort of patients with PDAC following pancreatic resection. METHODS: All patients with PDAC who will undergo pancreatic resection at three participating hospitals in Switzerland and fulfill the inclusion criteria will be included in the study consecutively. The SNV genotypes will be determined using standard genotyping techniques from patient blood samples. For each genotyped locus, log-rank and Cox multivariate regression tests will be performed, accounting for the relevant covariates American Joint Committee on Cancer stage and resection status. Clinical follow-up data will be collected for at least 3 years. Sample size calculation resulted in a required sample of 150 patients to sufficiently power the analysis. RESULTS: The follow-up data collection started in August 2019 and the estimated end of data collection will be in May 2027. The study is still recruiting participants and 142 patients have been recruited as of November 2023. The DNA extraction and genotyping of the SNVs will be performed after inclusion of the last patient. Since no SNV genotypes have been determined, no data analysis has been performed to date. The results are expected to be published in 2027. CONCLUSIONS: This is the first prospective study of the CD44 and CHI3L2 SNV-based biomarker signature in PDAC. A prospective validation of this signature would enable its clinical use as a noninvasive predictive biomarker of survival after pancreatic resection that is readily available at the time of diagnosis and can assist in guiding PDAC therapy. The results of this study may help to individualize treatment decisions and potentially improve patient outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54042.

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Lupus nephritis (LN) is one of the most severe clinical manifestations of systemic lupus erythematosus (SLE). Notably, the clinical manifestations of LN are not always consistent with the histopathological findings. Therefore, the diagnosis and activity monitoring of this disease are challenging and largely depend on invasive renal biopsy. Renal biopsy has side effects and is associated with the risk of bleeding and infection. There is a growing interest in the development of novel noninvasive biomarkers for LN. In this review, we summarize most of the LN biomarkers discovered so far by correlating current knowledge with future perspectives. These biomarkers fundamentally reflect the biological processes of kidney damage and repair during disease. Furthermore, this review highlights the role of urinary cell phenotype detection in the diagnosis, monitoring, and treatment of LN and summarizes the limitations and countermeasures of this test.

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BACKGROUND: A grim prognosis of pancreatic cancer (PCa) was attributed to the difficulty in early diagnosis of the disease. AIMS: Identifying novel biomarkers for early detection of PCa is thus urgent to improve the overall survival rates of patients. METHODS: The study was performed firstly by identification of candidate microRNAs (miRNAs) in formalin-fixed, paraffin-embedded tissues using microarray profiles, and followed by validation in a serum-based cohort study to assess clinical utility of the candidates. In the cohorts, a total of 1273 participants from four centers were retrospectively recruited as two cohorts including training and validation cohort. The collected serum specimens were analyzed by real-time polymerase chain reaction. RESULTS: We identified 27 miRNAs expressed differentially in PCa tissues as compared to the benign. Of which, the top-four was selected as a panel whose diagnostic efficacy was fully assessed in the serum specimens. The panel exhibited superior to CA19-9, CA125, CEA and CA242 in discriminating patients with early stage PCa from healthy controls or non-PCa including chronic pancreatitis as well as pancreatic cystic neoplasms, with the area under the curves (AUC) of 0.971 (95% CI 0.956-0.987) and 0.924 (95% CI 0.899-0.949), respectively. Moreover, the panel eliminated interference from other digestive tumors with a specificity of 90.2%. CONCLUSIONS: A panel of four serum miRNAs was developed showing remarkably discriminative ability of early stage PCa from either healthy controls or other pancreatic diseases, suggesting it may be developed as a novel, noninvasive approach for early screening of PCa in clinic.

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OBJECTIVE: To estimate the performance of the FibroTouch-based ultrasound attenuation parameter (UAP) for assessing hepatic steatosis in nonalcoholic fatty liver disease (NAFLD), with magnetic resonance imaging proton density fat fraction (MRI-PDFF) as the reference standard. METHODS: This prospective, cross-sectional study included 275 individuals in the training group and 110 individuals in the validation group, all of whom completed a standardized research visit, laboratory tests, MRI-PDFF, and UAP measurements over 1 month. Pearson correlation coefficient and Bland-Altman analysis were used to assess the agreement between UAP and MRI-PDFF for the detection of hepatic steatosis. The diagnostic value of UAP was evaluated by the area under the receiver operating characteristic (ROC) curve (AUROC). Confounding factors to UAP performance were identified by ROC curves and regression analyses. RESULTS: The AUROC of UAP for detecting MRI-PDFF at ≥5%, ≥10%, and ≥20% were 0.95 (95% confidence interval [CI] 0.92-0.97), 0.86 (95% CI 0.81-0.90), and 0.90 (95% CI 0.86-0.93), respectively, and their optimal thresholds were 259, 274, and 295 dB/m, respectively. The UAP measurements had higher diagnostic accuracy in participants with lower waist circumference (≤90 cm for men and ≤80 cm for women) compared to those with higher waist circumference (AUROC values: 0.97 vs 0.84, P < 0.05). Bland-Altman analysis showed good agreement between UAP and MRI-PDFF (bias 0.00021). According to established regression analyses, hepatic steatosis could be accurately diagnosed using UAP estimation. CONCLUSIONS: FibroTouch-UAP has a high diagnostic potential for hepatic steatosis in NAFLD patients and helps clinical assessment and monitoring.

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Ribonucleic acids (RNAs) are important regulators of gene expression and crucial for the progression of hepatocellular carcinoma (HCC). This study was designed to determine the diagnostic and prognostic utility of the circulating long miscellaneous RNAs; LINC01419, AK021443, and AF070632 in HCV-related HCC patients. Real-time PCR was used to measure their relative expression levels in the plasma of 194 HCV patients, 120 HCV-related HCC patients and 120 healthy controls. LINC01419 and AK021443 expression levels had significantly increasing linear trend estimates while AF070632 was dramatically downregulated in HCC compared to HCV. Interestingly, LINC01419 and AK021443 served as more significant diagnostic biomarkers for HCC than AF070632 and AFP. Multivariate analysis with cox regression revealed that the high expression of AK021443 [HR = 10.06, CI95%: 3.36-30.07], the high expression of LINC01419 [HR 4.13, CI95%: 1.32-12.86], and the low expression of AF070632 [HR = 2.70, CI95%: 1.07-6.81] were significant potential prognostic factors for HCC. Besides, the Kaplan-Meier analysis showed that HCC patients with high LIN01419 and AK021443 and low AF070632 expression levels had shorter OS. The circulating LINC01419 and AK021443 can be used as noninvasive potential biomarkers for diagnosis and prognosis of HCV-related HCC patients than AF070632 providing new targets for limiting the progression of the disease.

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While studies have shown an association between microRNAs and cardiac rejection, the clinical relevance of a preidentified miRNA signature as a noninvasive biomarker has never been assessed in prospective multicentric unselected cohorts. To address this unmet need, we designed a prospective study (NCT02672683) including recipients from 11 centers between August 2016 to March 2018. The objective was to validate the association between 3 previously identified circulating microRNA (10a, 92a, 155) and the histopathological diagnosis of rejection. Both relative and absolute (sensitivity analysis) quantifications of microRNAs were performed. Overall, 461 patients were included (831 biopsies, 79 rejections). A per-protocol interim analysis (258 biopsies, 49 rejections) did not find any association between microRNA and rejection (microRNA 10a: odds ratio (OR) = 1.05, 95% confidence intervals (CI) = 0.87-1.27, p = 0.61; 92a: OR = 0.98, 95%CI = 0.87-1.10, p = 0.68; 155: OR = 0.91, 95%CI = 0.76-1.10, p = 0.33). These results were confirmed in the sensitivity analysis. The analysis of the remaining sera was stopped for futility. This study shows no clinical utility of circulating microRNAs 10a, 92a, and 155 monitoring in heart allograft recipients.

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Non-alcoholic fatty liver disease (NAFLD), a metabolic-related disorder, is the most common cause of chronic liver disease which, if left untreated, can progress from simple steatosis to advanced fibrosis and eventually cirrhosis or hepatocellular carcinoma, which is the leading cause of hepatic damage globally. Currently available diagnostic modalities for NAFLD and hepatocellular carcinoma are mostly invasive and of limited precision. A liver biopsy is the most widely used diagnostic tool for hepatic disease. But due to its invasive procedure, it is not practicable for mass screening. Thus, noninvasive biomarkers are needed to diagnose NAFLD and HCC, monitor disease progression, and determine treatment response. Various studies indicated that serum miRNAs could serve as noninvasive biomarkers for both NAFLD and HCC diagnosis because of their association with different histological features of the disease. Although microRNAs are promising and clinically useful biomarkers for hepatic diseases, larger standardization procedures and studies are still required.

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Background: Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults; AML is highly heterogeneous and involves abnormalities at multiple omics levels. Small non-coding RNAs (sncRNAs) present in body fluids are important regulatory molecules and considered promising non-invasive clinical diagnostic biomarkers for disease. However, the signature of sncRNA profile alteration in AML patient serum and bone marrow supernatant is still under exploration. Methods: We examined data for blood and bone marrow samples from 80 consecutive, newly-diagnosed patients with AML and 12 healthy controls for high throughput small RNA-sequencing. Differentially expressed sncRNAs were analysed to reveal distinct patterns between AML patients and controls. Machine learning methods were used to evaluate the efficiency of specific sncRNAs in discriminating individuals with AML from controls. The altered expression level of individual sncRNAs was evaluated by RT-PCR, Q-PCR, and northern blot. Correlation analysis was employed to assess sncRNA patterns between serum and bone marrow supernatant. Results: We identified over 20 types of sncRNA categories beyond miRNAs in both serum and bone marrow supernatant, with highly coordinated expression patterns between them. Non-classical sncRNAs, including rsRNA (62.86%), ysRNA (14.97%), and tsRNA (4.22%), dominated among serum sncRNAs and showed sensitive alteration patterns in AML patients. According to machine learning-based algorithms, the tsRNA-based signature robustly discriminated subjects with AML from controls and was more reliable than that comprising miRNAs. Our data also showed that serum tsRNAs to be closely associated with AML prognosis, suggesting the potential application of serum tsRNAs as biomarkers to assist in AML diagnosis. Conclusions: We comprehensively characterized the expression pattern of circulating sncRNAs in blood and bone marrow and their alteration signature between healthy controls and AML patients. This study enriches research of sncRNAs in the regulation of AML, and provides insights into the role of sncRNAs in AML.

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BACKGROUND: Embryo implantation in a receptive endometrium is crucial for successful pregnancy. Endometrial receptivity (ER) prediction tools based on endometrial transcriptome biomarkers by endometrial biopsy have been used to guide successful embryo implantation in in vitro fertilization (IVF) patients. However, no reliable noninvasive ER prediction method has been established, and one is greatly needed. We aimed to identify biomarkers from uterine fluid transcriptomic sequencing data for establishing noninvasive ER prediction tool and to evaluate its clinical application potential in patients undergoing IVF. METHODS: The non-invasive RNA-seq based endometrial receptivity test (nirsERT) was established by analyzing transcriptomic profile of 144 uterine fluid specimens (LH + 5, LH + 7, and LH + 9) at three different receptive status from 48 IVF patients with normal ER in combination with random forest algorithm. Subsequently, 22 IVF patients who underwent frozen-thaw blastocyst transfer were recruited and analyzed the correlation between the predicted results of nirsERT and pregnancy outcomes. RESULTS: A total of 864 ER-associated differentially expressed genes (DEGs) involved in biological processes associated with endometrium-embryo crosstalk, including protein binding, signal reception and transduction, biomacromolecule transport and cell-cell adherens junctions, were selected. Subsequently, a nirsERT model consisting of 87 markers and 3 hub genes was established using a random forest algorithm. 10-fold cross-validation resulted in a mean accuracy of 93.0%. A small cohort (n = 22) retrospective observation shows that 77.8% (14/18) of IVF patients predicted with a normal WOI had successful intrauterine pregnancies, while none of the 3 patients with a displaced WOI had successful pregnancies. One patient failed due to poor sequencing data quality. CONCLUSIONS: NirsERT based on uterine fluid transcriptome biomarkers can predict the WOI period relatively accurately and may serve as a noninvasive, reliable and same cycle test for ER in reproductive clinics. TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR-DDD-17013375. Registered 14 November 2017, http://www.chictr.org.cn/index.aspx .

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IgA nephropathy (IgAN) is one of the most common glomerulonephritides. The disease is characterized by haematuria, proteinuria, deposition of galactose-deficient IgA1 in the glomerular mesangium and mesangial hypercellularity, further leading to extracellular matrix expansion. Kidney biopsy is the gold standard for IgAN diagnosis. Due to the invasiveness of renal biopsy, there is an unmet need for noninvasive biomarkers to diagnose and estimate the severity of IgAN. Understanding the role of RNA molecules as genetic markers to target diseases may allow developing therapeutic and diagnostic markers. In this review we have focused on intrarenal, extrarenal and extracellular noncoding RNAs involved in the progression of IgAN. This narrative review summarizes the pathogenesis of IgAN along with the correlation of noncoding RNA molecules such as microRNAs, small interfering RNAs, circular RNAs and long non-coding RNAs that play an important role in regulating gene expression, and that represent another type of regulation affecting the expression of specific glycosyltranferases, a key element contributing to the development of IgAN.

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Biliary tract cancer (BTC) is a highly aggressive malignant tumor. Serum microRNAs (ser-miRNAs) serve as noninvasive biomarkers to identify high risk individuals, thereby facilitating the design of precision therapies. The study is to prioritize key synergistic ser-miRNAs for the diagnosis of early BTC. Sampling technology, significant analysis of microarrays, Pearson Correlation Coefficients, t-test, decision tree, and entropy weight were integrated to develop a global optimization algorithm of decision forest. The source code is available at https://github.com/SuFei-lab/GOADF.git. Four key synergistic ser-miRNAs were prioritized and the synergistic classification performance was better than the single miRNA' s. In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. In the independent test dataset, the single AUC was 0.7280, 0.8313, 0.8957, and 0.8303, and the synergistic AUC was 0.9110 for discriminating between BTC patients and healthy controls. The AUC for discriminating BTC from pancreatic cancer was 0.9000. Hsa-miR-26a-5p was a predictor of prognosis, patients with high expression had shorter survival than those with low expression. In conclusion, hsa-let-7c-5p, hsa-miR-16-5p, hsa-miR-17-5p, and hsa-miR-26a-5p may act as key synergistic biomarkers and provide important molecular mechanisms that contribute to pathogenesis of BTC.

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BACKGROUND: Acute promyelocytic leukaemia (APL) is a unique subtype of acute myeloid leukaemia (AML) characterized by haematopoietic failure caused by the accumulation of abnormal promyelocytic cells in bone marrow (BM). However, indispensable BM biopsy frequently afflicts patients in leukaemia surveillance, which increases the burden on patients and reduces compliance. This study aimed to explore whether the novel circulating long noncoding RNA LOC100506453 (lnc-LOC) could be a target in diagnosis, assess the treatment response and supervise the minimal residual disease (MRD) of APL, thereby blazing a trail in noninvasive lncRNA biomarkers of APL. METHODS: Our study comprised 100 patients (40 with APL and 60 with non-APL AML) and 60 healthy donors. BM and peripheral blood (PB) sample collection was accomplished from APL patients at diagnosis and postinduction. Quantitative real-time PCR (qRT-PCR) was conducted to evaluate lnc-LOC expression. A receiver operating characteristic (ROC) analysis was implemented to analyse the value of lnc-LOC in the diagnosis of APL and treatment monitoring. For statistical analysis, the Mann-Whitney U test, a t test, and Spearman's rank correlation test were utilized. RESULTS: Our results showed that BM lnc-LOC expression was significantly different between APL and healthy donors and non-APL AML. lnc-LOC was drastically downregulated in APL patients' BM after undergoing induction therapy. Lnc-LOC was upregulated in APL cell lines and downregulated after all-trans retinoic acid (ATRA)-induced myeloid differentiation, preliminarily verifying that lnc-LOC has the potential to be considered a treatment monitoring biomarker. PB lnc-LOC was positively correlated with BM lnc-LOC in APL patients, non-APL AML patients and healthy donors and decreased sharply after complete remission (CR). However, upregulated lnc-LOC was manifested in relapsed-refractory patients. A positive correlation was revealed between PB lnc-LOC and PML-RARα transcript levels in BM samples. Furthermore, we observed a positive correlation between PB lnc-LOC and BM lnc-LOC expression in APL patients, suggesting that lnc-LOC can be utilized as a noninvasive biomarker for MRD surveillance. CONCLUSIONS: Our study demonstrated that PB lnc-LOC might serve as a novel noninvasive biomarker in the treatment surveillance of APL, and it innovated the investigation and application of newly found lncRNAs in APL noninvasive biomarkers used in diagnosis and detection.

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Immune checkpoint inhibitors (ICIs), especially anti-programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) antibodies, have made dramatic progress in the treatment of lung cancer, especially for patients with cancers not driven by oncogenes. However, responses are limited to a subset of patients, and which subset of patients will optimally benefit from ICI remains unknown. With the advantage of being minimally invasive and dynamic, noninvasive biomarkers are promising candidates to predict response, monitor resistance, and track the evolution of lung cancer during ICI treatment. In this review, we focus on the application of circulating tumor DNA (ctDNA) in plasma in immunotherapy. We examine the potential of pre- and on-treatment features of ctDNA as biomarkers, and following multiparameter analysis, we determine the potential clinical value of integrating predictive liquid biomarkers of ICIs to optimize patient management. We further discuss the role of ctDNA in monitoring treatment resistance, as well as challenges in clinical translation.

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Immune checkpoint blockade (ICB) therapies exhibit substantial clinical benefit in different cancers, but relatively low response rates in the majority of patients highlight the need to understand mutual relationships among immune features. Here, we reveal overall positive correlations among immune checkpoints and immune cell populations. Clinically, patients benefiting from ICB exhibited increases for both immune stimulatory and inhibitory features after initiation of therapy, suggesting that the activation of the immune microenvironment might serve as the biomarker to predict immune response. As proof-of-concept, we demonstrated that the immune activation score (IS Δ) based on dynamic alteration of interleukins in patient plasma as early as two cycles (4-6 weeks) after starting immunotherapy can accurately predict immunotherapy efficacy. Our results reveal a systematic landscape of associations among immune features and provide a noninvasive, cost-effective, and time-efficient approach based on dynamic profiling of pre- and on-treatment plasma to predict immunotherapy efficacy.

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(1) Background: Graft-cell-free DNA (cfDNA) in the circulation of liver transplant recipients has been proposed as a noninvasive biomarker of organ rejection. The aim of this study was to detect donor-specific cfDNA (ds-cfDNA) in the recipient's serum after either liver damage or rejection using a qPCR-based method. (2) Methods: We proposed a qPCR method based on the amplification of 10 specific insertion-deletion (InDel) polymorphisms to detect donor-specific circulating DNA diluted in the recipient cfDNA. ds-cfDNA from 67 patients was evaluated during the first month post-transplantation. (3) Results: Graft rejection in the first month post-transplantation was reported in 13 patients. Patients without liver complications showed a transitory increase in ds-cfDNA levels at transplantation. Patients with rejection showed significant differences in ds-cfDNA increase over basal levels at both the rejection time point and several days before rejection. Receiver operator characteristic (ROC) analysis showed that ds-cfDNA levels discriminated rejection, with an AUC of 0.96. Maximizing both sensitivity and specificity, a threshold cutoff of 8.6% provided an estimated positive and negative predictive value of 99% and 60%, respectively. (4) Conclusions: These results suggest that ds-cfDNA may be a useful marker of graft integrity in liver transplant patients to screen for rejection and liver damage.

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Circulating tumor DNA (ctDNA) has demonstrated great potential as a noninvasive biomarker to assess minimal residual disease (MRD) and profile tumor genotypes in patients with non-small-cell lung cancer (NSCLC). However, little is known about its dynamics during and after tumor resection, or its potential for predicting clinical outcomes. Here, we applied a targeted-capture high-throughput sequencing approach to profile ctDNA at various disease milestones and assessed its predictive value in patients with early-stage and locally advanced NSCLC. We prospectively enrolled 33 consecutive patients with stage IA to IIIB NSCLC undergoing curative-intent tumor resection (median follow-up: 26.2 months). From 21 patients, we serially collected 96 plasma samples before surgery, during surgery, 1-2 weeks postsurgery, and during follow-up. Deep next-generation sequencing using unique molecular identifiers was performed to identify and quantify tumor-specific mutations in ctDNA. Twelve patients (57%) had detectable mutations in ctDNA before tumor resection. Both ctDNA detection rates and ctDNA concentrations were significantly higher in plasma obtained during surgery compared with presurgical specimens (57% versus 19% ctDNA detection rate, and 12.47 versus 6.64 ng·mL-1 , respectively). Four patients (19%) remained ctDNA-positive at 1-2 weeks after surgery, with all of them (100%) experiencing disease progression at later time points. In contrast, only 4 out of 12 ctDNA-negative patients (33%) after surgery experienced relapse during follow-up. Positive ctDNA in early postoperative plasma samples was associated with shorter progression-free survival (P = 0.013) and overall survival (P = 0.004). Our findings suggest that, in early-stage and locally advanced NSCLC, intraoperative plasma sampling results in high ctDNA detection rates and that ctDNA positivity early after resection identifies patients at risk for relapse.

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Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally; it is valuable to predict its prognosis after treatment. Aspartate aminotransferase-to-platelet index (APRI), a non-invasive biomarker consists of two routine test parameters easily available in all the patients. Our study aimed to investigate whether APRI can serve as an independent prognostic marker in the patients with HCC. Methods: We extensively searched PubMed, Embase, and Web of Science databases on June 20, 2021 to determine all relevant literature. The studies that explored the association between the APRI levels and prognosis of patients with HCC and reported risk estimate data were included. The Newcastle-Ottawa Scale was used to assess the quality of the included studies. Results: A total of 1,097 articles were initially identified, of which 28 studies involving 11,041 patients met the eligibility criteria for the meta-analysis. The pooled hazard ratios (HRs) for overall survival (OS) and disease-free survival (DFS) were 1.77 (95% CI: 1.53-2.05, P < 0.001) and 1.59 (95% CI: 1.47-1.71, P < 0.001), respectively, suggesting a significant correlation between the increased APRI levels and poor prognosis in the patients with HCC. In the subgroup analyses, statistical significance of the correlation disappeared in the Korean and Japanese population and in the patients undergoing transarterial chemoembolization (TACE). Of note, the current results may be overestimated due to publication bias, but the conclusion remained unchanged when the bias was adjusted. Conclusion: High APRI levels are associated with poor OS and DFS in the patients with HCC. In most cases, pretreatment APRI can be used as an independent prognostic factor, but it is necessary to incorporate other predictive prognostic systems to ensure accuracy. Further studies are needed to determine the specific beneficiary population and the optimal cutoff value.

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Gastric cancer is one of the most common cancers worldwide, with a bad prognosis associated with late-stage diagnosis, significantly decreasing the overall survival. This highlights the importance of early detection to improve the clinical course of these patients. Although screening programs, based on endoscopic or radiologic approaches, have been useful in countries with high incidence, they are not cost-effective in low-incidence populations as a massive screening strategy. Additionally, current biomarkers used in daily routine are not specific and sensitive enough, and most of them are obtained invasively. Thus, it is imperative to discover new noninvasive biomarkers able to diagnose early-stage gastric cancer. In this context, liquid biopsy is a promising strategy. In this review, we briefly discuss some of the potential biomarkers for gastric cancer screening and diagnosis identified in blood, saliva, urine, stool, and gastric juice.

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High-grade serous ovarian carcinoma is a leading cause of death in female patients worldwide. MicroRNAs (miRNAs) are stable noncoding RNAs in the peripheral blood that reflect a patient's condition, and therefore, they have received substantial attention as noninvasive biomarkers in various diseases. We previously reported the usefulness of serum miRNAs as diagnostic biomarkers. Here, we investigated the prognostic impact of the serum miRNA profile. We used the GSE106817 dataset, which included preoperative miRNA profiles of patients with ovarian malignancies. Excluding patients with other malignancy or insufficient prognostic information, we included 175 patients with high-grade serous ovarian carcinoma. All patients except four underwent surgery and received chemotherapy as initial treatment. The median follow-up period was 54.6 months (range, 3.5-144.1 months). Univariate Cox regression analysis revealed that higher levels of miR-187-5p and miR-6870-5p were associated with both poorer progression-free survival (PFS) and overall survival (OS), and miR-1908-5p, miR-6727-5p, and miR-6850-5p were poor prognostic indicators of PFS. The OS and PFS prognostic indices were then calculated using the expression values of three prognostic miRNAs. Multivariate Cox regression analysis showed that both indices were significantly independent poor prognostic factors (hazard ratio for OS and PFS, 2.343 [P = .015] and 2.357 [P = .005], respectively). In conclusion, circulating miRNA profiles can potentially provide information to predict the prognosis of patients with high-grade serous ovarian carcinoma. Therefore, there is a strong demand for early clinical application of circulating miRNAs as noninvasive biomarkers.

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