With covalently closed circular structures, circular RNAs (circRNAs) were once misinterpreted as by-products of mRNA splicing. Being abundant, stable, highly conserved, and tissue-specific, circRNAs are recently identified as a type of regulatory RNAs. CircRNAs bind to certain miRNAs or proteins to participate in gene transcription and translation. Emerging evidence has indicated that the dysregulation of circRNAs is closely linked to the tumorigenesis and treatment response of hematological malignancies. CircRNAs play critical roles in various biological processes, including tumorigenesis, drug resistance, tumor metabolism, autophagy, pyroptosis, and ferroptosis. The N6-methyladenosine modification of circRNAs and discovery of fusion-circRNAs provide novel insights into the functions of circRNAs. Targeting circRNAs in hematological malignancies will be an attractive treatment strategy. In this review, we systematically summarize recent advances toward the novel functions and molecular mechanisms of circRNAs in hematological malignancies, and highlight the potential clinical applications of circRNAs as novel biomarkers and therapeutic targets for future exploration.
Background: Systemic inflammation response index (SIRI) is a novel inflammatory hallmark that is proposed as an adverse prognosticator in a variety of malignancies. Nevertheless, the correlation between SIRI and primary gastrointestinal diffuse large B cell lymphoma (PGI-DLBCL) remains unknown. Our study aimed to evaluate the prognostic value of SIRI in PGI-DLBCL patients treated with CHOP-based therapies and establishing a highly discriminating risk prediction model compared with the National Comprehensive Cancer Network-International Prognostic Index (NCCN-IPI) score. Methods: This retrospective analysis incorporated 102 PGI-DCBCL patients (57 patients with gastric DLBCL and 45 patients with intestinal DLBCL) newly diagnosed between January 2011 and June 2020. The SIRI was calculated by utilizing the peripheral blood neutrophil (N), monocyte (M), and lymphocyte (L) counts collected in the last ≤3 days before the initiation of the immunochemotherapy: SIRI= N × M/L. Pretreatment SIRI cutoff that may distinguish the study population into two gatherings with distinctive overall survival (OS) results which was calculated by the receiver operating characteristic (ROC) curve analysis. The prognostic factors associated with OS, the primary endpoint, were screened by multivariate Cox regression analyses and log-rank test as well as progression-free survival (PFS), the secondary endpoint. Performances of the novel model were compared using the area under the curve (AUC) and C-index in the cohort. Results: Among the 102 patients analyzed, there were 64 (62.7%) males and 38 (37.3%) females. The median follow-up time was 39.5 months (95% CI: 30.7-48.2), ranging from 2 to 102 months. A total of 33 patients (32.4%) presented B symptoms at the initial assessment, 74 (72.5%) of patients revealed stage III or IV disease, and 24 (23.5%) of patients had more than one extranodal involvement. Twenty-seven patients (26.5%) showed ECOG PS>2. The optimal SIRI cutoff was identified as 1.34 value by OS outcome, which divided patients into two groups. There were not significant differences in clinical characteristics between two groups (Table 1). Based on the cut-off value of SIRI, the outcomes of patients were distinct within two groups, which was shown in Figure 1. At a median follow-up of 39.5 (95% CI: 30.7-48.2) months, 86 (84.3%) patients were still alive (98.4% for SIRI <1.34 vs 62.5% for SIRI ≥1.34; p < 0.001). Cox regression analysis found three negative prognostic factors on OS: SIRI≥ 1.34 (P=0.001), B symptom (P=0.001), LDH>ULN (P=0.005). Accordingly, SIRI≥ 1.34 (P=0.002), age>60 (P=0.011) and LDH>ULN (P=0.002) emerged to be the indicators in relation to considerably inferior PFS times. Consequences of the multivariate analyses revealed that the prognostic significance of the SIRI on OS and PFS outcomes was independent of other confounders. SIRI could be used to combine with NCCN-IPI and develop a risk score to improve the NCCN-IPI score and identify PGI-DLBCL patients with poor prognosis. Patients with SIRI≥1.34 were allocated 2 points as a risk factor which was calculated in terms of the β coefficients compared with the effect of LDH level (>ULN) in the multivariate analysis of OS. This established an integrated scoring model with a maximum of 10 points when we combined NCCN-IPI with SIRI. Patients were divided into four risk groups and identified as low-risk group (0−3 points), low-intermediate-risk group (4−5 points), high-intermediate-risk group (6−7 points), and high-risk group (≥8 points). As a result, the prognostic and discriminatory capability of the NCCN-IPI plus SIRI was superior to NCCN-IPI alone (AUC: 0.858 vs. 0.814 and C-index: 0.826 vs. 0.801) based on OS in this patient population (Figure 2). Regarding the PFS, SIRI-PI also surpassed the NCCN-IPI with superior AUC (0.766 vs 0.709) and C-index (0.736 vs. 0.709) in discrimination. Conclusion: The results of this retrospective analysis suggested that the pretreatment SIRI was a potent and independent prognostic indicator that may be a potential candidate for identifying patients with poor prognosis in the future clinical practice of PGI-DLBCL. Keywords: Aggressive lymphoma, Clinically relevant, Systemic inflammation response index Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.
Introduction : microRNAs (miRNAs) could be released into the extracellular microenvironment and mediate cellular communication through exosomes. Circulation exosomal miRNAs have recently emerged as complimentary biomarkers and novel approaches for the non-invasive tests of early diagnosis or follow-up of neoplasms. Accumulating evidences have indicated that miR-107 plays vital functions in suppressing tumorigenesis. However, the significance of exosomal miR-107 in DLBCL remains unclear. Thus, this study aimed to explore candidate biomarkers and investigate the role of miR-107 in DLBCL as well as the molecular mechanisms involved. Methods : Differentially expressed miRNAs (DEMs) in DLBCL were identified based on Gene Expression Omnibus (GEO) datasets and verified in a cohort of DLBCL patients. The functions and biological pathways of DEMs were enriched by DAVID. Serum-derived exosomes of 42 DLBCL patients and 31 healthy volunteers were isolated with informed consents by Exo Easy Maxi Kit, and further detected by western blot and transmission electron microscopy (TEM). Receiver operating characteristic curves (ROC) were performed to evaluate the diagnostic value of DEMs. The biological function of miR-107 in DLBCL were evaluated by miR-107 Agomir. Survival analyses were performed by the Kaplan-Meier method. Potential targets genes of miR-107 were predicted by miRDB, PicTar, Targetscan and miRTarBase. Western blotting and confocal staining assay were used to detect the expression of YWHAH. Interaction of miR-107 and YWHAH was confirmed by dual-luciferase reporter assay. Results : 14 DEMs were identified in DLBCL through evaluating the miRNA microarray profile of GSE117063 (Fig. 1A-A) and GSE29493 (Fig. 1A-B). The biological processes of these DEMs mainly enriched in regulatory of transcription, protein phosphorylation and cell proliferation (Fig.1B). In order to explore candidate exosomal biomarkers for DLBCL, we then isolated serum-derived exosomes from DLBCL patients. As depicted in Fig.1C, exosomes not only expressed exosomal biomarkers Tsg101 and CD9 but also shown cup-shape morphology. We further assessed the expression of DEMs on exosomes by qRT-PCR. Compared with normal samples, only two down-regulated miRNAs (miR-107, miR-375) and one up-regulated miRNAs (miR-485) were statistically dysregulated in DLBCL patients (Fig.2A). ROC curve analysis demonstrated that exosomal miR-107, miR-375, and miR-485 might be potential biomarkers for DLBCL patients, with the AUC of 0.854, 0.769, and 0.703, respectively (Fig.2B). In addition, survival analysis revealed that low-expression of miR-107 in DLBCL patients significantly associated with undesirable clinical outcomes (Fig.2C, p<0.05). These data suggested that miR-107 may serve as a valuable prognostic biomarker and participated in progression of DLBCL. Down-regulation of miR-107 was confirmed in DLBCL cell lines by qRT-PCR (Fig.3A). To validate our hypothesis, we up-regulated miR-107 expression by miRNA Agomir, which could significantly reduce cell proliferation and migration, and promote cell apoptosis (Fig.3B-D). The regulatory mechanisms of miR-107 in DLBCL was further explored. 28 target genes of miR-107 were identified and shown in Fig.4A. KEGG pathway analysis revealed that the targeted genes mainly enriched in the PI3K-Akt, Hippo, and AMPK signaling pathways (Fig.4B). We found out that the target gene YWHAH (14-3-3η) was significantly upregulated in the DLBCL cells (Fig.4C-D). Moreover, dual-luciferase assay revealed that miRNA-107 perform anti-tumor effect through targeting the 3'UTR region of YWHAH (Fig.4E-F). As previously reported, YWHAH associated with tumor metastasis, chemoresistance, apoptosis resistance and poor prognosis in DLBCL. Thus, we suggested that miR-107 antagonized DLBCL progression through downregulating YWHAH. Conclusion : In this study, we demonstrated for the first time that serum exosomal miR-107, miR-375, and miR-485 could be applied as potential non-invasive biomarkers in early diagnosis of DLBCL patients. Furthermore, miR-107 inhibited DLBCL progression by targeting YWHAH, which will provide a promising therapeutic approach for DLBCL. Disclosures No relevant conflicts of interest to declare.
Introduction:The current prognostic scoring systems for mature T and NK cell lymphomas are still insufficient in predicting the outcomes of patients. It is urgently needed to identify novel predictors and develop a more accurate risk stratification system. Lipid metabolism accounts for a significant proportion in the tumor energy metabolism and even occupies a dominant position in non-glycolysis-dependent tumors. Dyslipidemia has been confirmed to be related to inferior outcomes of patients with solid tumors and several hematological malignancies. Nevertheless, there has been none prognostic scoring system containing lipid metabolism-related indicator reported at present. Thus, we aimed to investigate the association between lipid metabolism level and clinical outcomes, and further develop a novel lipid-based prognostic model in patients with newly-diagnosed mature T and NK cell lymphomas. Methods:The study was performed retrospectively in Shandong Provincial Hospital. The patients were divided to the training cohort (from January 2006 to December 2016) and the prospective validation cohort (from January 2017 to June 2020). The inclusion criteria contain: (1) pathologically confirmed; (2) newly diagnosed; (3) with complete clinical and follow-up data; (4) without previous malignancies. The basic data comparison of the two cohorts was performed by Studentttest or Mann-Whitney U test for continuous variables and the chi-square test or Fisher's exact test for categorical data. Univariate analysis and multivariate Cox regression analysis were performed to detect independent predictors and generate a novel prognostic staging system. The efficiency and accuracy of the new scoring system were assessed in two cohorts from different aspects, including time-dependent receiver operating characteristic curves, Brier score and decision curve analysis. Results:We developed EnBC score from a retrospective 115-patient training cohort using a multivariate Cox regression model and tested it in a prospective 58-patient validation cohort. The score was calculated by the extranodal involved sites, β2-microglobulin and serum total cholesterol (Table 1). EnBC score divided patients into four risk grades, low risk (0 point), low-intermediate risk (1 point), intermediate-high risk (2 points), high risk (3 points) (Table 2). Kaplan-Meier curves proved that patients in four risk grades presented significantly distinct long-term prognoses (median OS, NA vs. NA vs. 14.0 vs. 4.0 months, P<0.0001; median PFS, 84.0 vs. 19.0 vs. 8.0 vs. 1.5 months, P<0.0001) (Figure 1). Therewith, we examined the efficiency and accuracy of EnBC score in the training and validation cohort, respectively. Its predictive discrimination capacity, as determined by the area under the time-dependent receiver operating characteristic curves, was greater than that of the present commonly used scoring systems (AUCs of OS, EnBC 0.885-0.963 vs. IPI 0.785-0.873 vs. PIT 0.781-0.845; AUCs of PFS, EnBC 0.832-0.922 vs. IPI 0.781-0.842 vs. PIT 0.761-0.799). The Brier score, as an indicator of predictive calibrating performance, was also better or similar to the other models (OS, EnBC 0.146-0.181 vs. IPI 0.155-0.203 vs. PIT 0.167-0.209; PFS, EnBC 0.164-0.189 vs. IPI 0.159-0.183 vs. PIT 0.168-0.190). In addition, the decision curve analysis also proved that EnBC score possessed larger net benefits than IPI and PIT in the entire patient population (Figure 2). Conclusion:We verified for the first time that abnormal serum lipid metabolism level was significantly associated with the prognosis of patients with mature T and NK cell lymphoma. Furthermore, we developed a novel lipid-based EnBC score and proved that this score was more accurate and effective in predicting the prognoses of treat-naïve de novo mature T and NK cell lymphoma patients than other staging systems. This study provided novel evidences for precise prognostic stratification and individualized therapy of mature T and NK cell lymphoma patients. Disclosures No relevant conflicts of interest to declare.
Background: Late years have witnessed that novel targeted treatment modalities are corroborated successful clinical applications in T cell lymphoma (TCL). Yet, there are a considerable proportion of patients suffering from relapse or progression of disease (POD). Early POD (ie, POD within 24 months) has been validated as a novel prognostic indicator in various pathological types of lymphoma. At present, the clinical function of early POD in TCL has not been explored with influencing factors unknown. Herein, we developed a novel risk stratification model for predicting early POD by integrating International Prognostic Index (IPI) score and serum total protein (TP) level. Methods: We retrospectively identified patients diagnosed with TCL in Shandong Provincial Hospital from Mar 2011 to Jan 2021. Patients aged≥18 years with confirmed tissue diagnosis of TCL were included and were divided into a training cohort and a validation cohort. The prognostic role of early POD was evaluated using Cox proportional hazards model. Univariate analysis was applied to identify covariates for a logistic regression model predicting early POD. A clinical point score was generated according to multivariate analysis. The predicting performance was assessed by validation cohort and compared to clinical models. Results: A total of 141 potentially eligible patients were identified. Overfitting was prevented by splitting the data into training (70%) and validation (30%) set. Median follow-up was 32 months. In the training cohort, the median age at diagnosis was 52.2 years (range 18-81), and 70 (67.3%) were under 60 years old. While in validation set, the median age was 55 years (range 21-77), among whom 73% were under 60. In both group combined, there was a male predominance (66.3% vs 73.0%). The most frequently had lymphoma that was NK/T-cell lymphoma (NKTCL) (31.7% vs 35.1%) with peripheral T-cell lymphoma (PTCL) (25.0% vs 24.3%) next. More than half of patients (51.0% vs 59.5%) suffered from early POD. In univariate and multivariate cox regression analysis, early POD was the most independent prognostic factor (p <0.001) with an adjusted HR for PFS of 310.708 (95% CI:27.625-3494.686) and for OS an adjusted HR of 23.416 (95% CI:8.178-67.05). K-M curve indicated a significant difference in both OS and PFS between early-POD and non-POD groups (Figure A). To ask whether early POD prediction could be made by analyzing clinical risk factors at diagnosis, univariate analysis in the training cohort identified variables significantly associated with early POD and were included into the multivariable logistic regression model that were 10-fold cross-validated. We found that IPI score, serum TP level were independent predictors for early POD (AUC 0.775, 95% CI, 0.683-0.866; p<0.001), and the Hosmer-Lemeshow test confirmed good calibration (p=0.635). In the validation set, the model remained strong predictive performance. Figures B, C showed the calibration curves and nomograms of early POD predicted by the model on training and validation cohorts, respectively. Cut-off points of TP level were determined by ROC analysis to simplify the risk model. Selected cut-off points were adjusted to the nearest whole integer to maximize ease of use. Eventually, two independent predictors (IPI score and serum TP≤64 g/L) of early POD were retained through multivariable regression analysis, and the risk score was then calculated for each factor according to the regression coefficient. This resulting algorithm was named as POD-IPI score. Afterwards, patients were stratified into 3 groups: low-risk (0 score, n=13, 12.5%), intermediate-risk (1-3 score, n=49, 47.1%), and high-risk (>3 score, n=42, 40.4%) groups. Compared to IPI score and NCCN-IPI score, the discriminative ability of the proposed score was good in the ROC, thereby outperforming existing clinical models in two cohorts (AUC=0.784, 95% CI: 0.695-0.873, AUC=0.809, 95% CI: 0.667-0.952, respectively). The outcomes of early POD by the stratification of POD-IPI score in training group were represented in Figure D. The curves were well separated, indicating the good discriminatory ability of this novel model. Conclusions: POD-IPI achieved a specific prediction of early POD in TCL patients, which was validated to allow for simplified stratification and comparison of risk distribution. Its use, together with clinical judgment, may provide guidelines on treatment decisions in TCL. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.
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