Prognostic and predictive value of a microRNA signature in adults with T-cell lymphoblastic lymphoma

The AC010247.2/miR-125b-5p axis triggers the malignant progression of acute myelocytic leukemia by IL-6R

AML is a malignant tumor derived from the hematopoietic system, which has a poor prognosis and its incidence is increasing recent years. LncRNAs bind to miRNAs as competitive endogenous RNAs to regulate the occurrence and progression of AML， with IL-6R playing a crucial role in hematological malignancies. However, the mechanism by which noncoding RNAs regulate IL6R expression in AML remains unclear. This study found that the AC010247.2/miR-125b-5p axis promotes AML progression by regulating IL-6R expression. Specifically, knocking down or inhibiting AC010247.2 and miR-125b-5p affected IL6R and its downstream genes. Mechanistically, AC010247.2 acts as a ceRNA for miR-125b-5p, influencing IL-6R expression. Additionally, AC010247.2's regulation of AML progression partially depends on miR-125b-5p. Notably, the AC010247.2/miR-125b-5p/IL6R axis serves as a better polygenic diagnostic marker for AML. Our study identifies a key ceRNA regulatory axis that modulates IL6R expression in AML, providing a reliable multigene diagnostic method and potential therapeutic target.

Notch3-regulated microRNAs impair CXCR4-dependent maturation of thymocytes allowing maintenance and progression of T-ALL

Malignant transformation of T-cell progenitors causes T-cell acute lymphoblastic leukemia (T-ALL), an aggressive childhood lymphoproliferative disorder. Activating mutations of Notch, Notch1 and Notch3, have been detected in T-ALL patients. In this study, we aimed to deeply characterize hyperactive Notch3-related pathways involved in T-cell dynamics within the thymus and bone marrow to propose these processes as an important step in facilitating the progression of T-ALL. We previously generated a transgenic T-ALL mouse model (N3-ICtg) demonstrating that aberrant Notch3 signaling affects early thymocyte maturation programs and leads to bone marrow infiltration by CD4+CD8+ (DP) T cells that are notably, Notch3highCXCR4high. Newly, our in vivo results suggest that an anomalous immature thymocyte subpopulation, such as CD4-CD8- (DN) over-expressing CD3ɛ, but with low CXCR4 expression, dominates N3-ICtg thymus-resident DN subset in T-ALL progression. MicroRNAs might be of significance in T-ALL pathobiology, however, whether required for leukemia maintenance is not fully understood. The selection of specific DN subsets demonstrates the inverse correlation between CXCR4 expression and a panel of Notch3-deregulated miRNAs. Interestingly, we found that within DN thymocyte subset hyperactive Notch3 inhibits CXCR4 expression through the cooperative effects of miR-139-5p and miR-150-5p, thus impinging on thymocyte differentiation with accumulation of DNCD3ɛ+CXCR4- cells. These data point out that deregulation of Notch3 in T-ALL, besides its role in sustaining dissemination of abnormal DP T cells, as we previously demonstrated, could play a role in selecting specific DN immature T cells within the thymus, thus impeding T cell development, to facilitate T-ALL progression inside the bone marrow.

MicroRNAs utilization as effective factors on hematopoietic stem cell transplantation, its outcomes and prognosis; a comprehensive systematic review

INTRODUCTION

The therapeutic method for many malignant and non-malignant diseases is hematopoietic stem cell transplantation (HSCT), but it is not always fully successful in all patients. Indeed, HSCT can be influenced by a variety of factors. Here we reviewed the effect of microRNAs (miRs) on HSCT-related outcomes, like survival, infections, relapse, engraftment, and so on, systematically.

METHOD

WOS, Scopus, PubMed, Google Scholar, and ProQuest databases were searched. The PRISMA guideline was performed, and 24 studies were included through quality assessment. Classified data extraction was done based on the type of disease.

RESULTS

The systematic review identified 47 miRs effective on HSCT. The role of miRs as tumor suppressors or oncogenes is reported in acute myeloblastic and lymphoblastic leukemia patients undergoing HSCT due to their effects on overall or event-free survival. Additionally, relapse after HSCT in multiple myeloma is correlated with miRs expression. Also, recovery from post-autologous HSCT cytopenia or platelet and neutrophil engraftment can be influenced by miRs. We highlighted here reports on specific miRs.

CONCLUSION

We reported prognostic miRs for in-depth clinical management of the HSCT process and its outcomes. Also, miRs are introduced for the prevention of HSCT-related complications, and future studies are suggested to evaluate personalized medicine's utilization of miRs in therapeutic methods like HSCT in neoplasia.

Targeting P21-activated kinase suppresses proliferation and enhances chemosensitivity in T-cell lymphoblastic lymphoma

T-cell lymphoblastic lymphoma (T-LBL) is a highly aggressive non-Hodgkin lymphoma with a poor prognosis. P21-activated kinase (PAK) is a component of the gene expression-based classifier that can predict the prognosis of T-LBL. However, the role of PAK in T-LBL progression and survival remains poorly understood. Herein, we found that the expression of PAK1 was significantly higher in T-LBL cell lines (Jurkat, SUP-T1, and CCRF-CEM) compared to the human T-lymphoid cell line. Moreover, PAK2 mRNA level of 32 relapsed T-LBL patients was significantly higher than that of 37 cases without relapse (P = .012). T-LBL patients with high PAK1 and PAK2 expression had significantly shorter median RFS than those with low PAK1 and PAK2 expression (PAK1, P = .028; PAK2, P = .027; PAK1/2, P = .032). PAK inhibitors, PF3758309 (PF) and FRAX597, could suppress the proliferation of T-LBL cells by blocking the G1/S cell cycle phase transition. Besides, PF could enhance the chemosensitivity to doxorubicin in vitro and in vivo. Mechanistically, through western blotting and RNA sequencing, we identified that PF could inhibit the phosphorylation of PAK1/2 and downregulate the expression of cyclin D1, NF-κB and cell adhesion signaling pathways in T-LBL cell lines. These findings suggest that PAK might be associated with T-LBL recurrence and further found that PAK inhibitors could suppress proliferation and enhance chemosensitivity of T-LBL cells treated with doxorubicin. Collectively, our present study underscores the potential therapeutic effect of inhibiting PAK in T-LBL therapy.

The β-catenin-LINC00183-miR-371b-5p-Smad2/LEF1 axis promotes adult T-cell lymphoblastic lymphoma progression and chemoresistance

BACKGROUND

High-intensity chemotherapy regimens are often used in adult T-cell lymphoblastic lymphoma (T-LBL) patients. Nevertheless, the response rate remains unsatisfactory due to emergence of chemoresistance. Growing evidence has shown that long non-coding RNAs (lncRNAs) are involved in tumor progression and chemoresistance. Herein, we investigated the potential role of lncRNAs in T-LBLs.

METHODS

RNAseq was used to screen and identify candidate lncRNAs associated with T-LBL progression and chemoresistance. Luciferase reporter assay was used to examine the binding of miR-371b-5p to the 3'UTR of Smad2 and LEF1, and the binding of TCF-4/LEF1 to the promoter of LINC00183. Chromatin immunoprecipitation assay was undertaken to analyze the connection between LEF1 and the LINC00183 promoter region. RNA immunoprecipitation assays were used to explore the mechanism whereby LINC00183 regulated miR-371b-5p. MTT and flow cytometry assays were used to measure apoptosis of T-LBL cells.

RESULTS

LINC00183 was upregulated in T-LBL progression and chemoresistant tissues in both the Sun Yat-sen University Cancer Center dataset and the First Affiliated Hospital of Anhui Medical University dataset. High expression of LINC00183 was correlated with poorer overall survival and progression-free survival of T-LBL patients compared to those with low expression of LINC00183. Furthermore, miR-371b-5p was negatively regulated by LINC00183. In vivo and in vitro assays showed that LINC00183-mediated T-LBL chemoresistance depended on miR-371b-5p expression. The direct binding of miR-371b-5p to Smad2 and LEF1 was verified by luciferase assays. It was shown that TCF4/LEF1 could bind to the LINC00183 promoter site and increase its transcript level. Downregulation of miR-371b-5p led to increased expression of Smad2/LEF1, and in turn increased LINC00183 expression. Additionally, phospho-Smad2 promotes nuclear translocation of β-catenin, LINC00183 downregulation decreased chemoresistance induced by β-catenin and TGF-β1 in T-LBL cells.

CONCLUSION

We unraveled a β-catenin-LINC00183-miR-371b-5p-Smad2/LEF1 feedback loop that promotes T-LBL progression and chemoresistance, indicating that LINC00183 may serve as a potential therapeutic target in T-LBLs.

Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review

In the last years, liquid biopsy gained increasing clinical relevance for detecting and monitoring several cancer types, being minimally invasive, highly informative and replicable over time. This revolutionary approach can be complementary and may, in the future, replace tissue biopsy, which is still considered the gold standard for cancer diagnosis. "Classical" tissue biopsy is invasive, often cannot provide sufficient bioptic material for advanced screening, and can provide isolated information about disease evolution and heterogeneity. Recent literature highlighted how liquid biopsy is informative of proteomic, genomic, epigenetic, and metabolic alterations. These biomarkers can be detected and investigated using single-omic and, recently, in combination through multi-omic approaches. This review will provide an overview of the most suitable techniques to thoroughly characterize tumor biomarkers and their potential clinical applications, highlighting the importance of an integrated multi-omic, multi-analyte approach. Personalized medical investigations will soon allow patients to receive predictable prognostic evaluations, early disease diagnosis, and subsequent ad hoc treatments.

Identification and Validation of Three PDAC Subtypes and Individualized GSVA Immune Pathway-Related Prognostic Risk Score Formula in Pancreatic Ductal Adenocarcinoma Patients

Background

With the progress of precision medicine treatment in pancreatic ductal adenocarcinoma (PDAC), individualized cancer-related medical examination and prediction are of great importance in this high malignant tumor and tumor-immune microenvironment with changed pathways highly enrolled in the carcinogenesis of PDAC.

Methods

High-throughput data of pancreatic ductal adenocarcinoma were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. After batch normalization, the enrichment pathway and relevant scores were identified by the enrichment of immune-related pathway signature using gene set variation analysis (GSVA). Then, cancerous subtype in TCGA and GEO samples was defined through the NMF methods by cancertypes packages in R software, respectively. Subsequently, the significance between the characteristics of each TCGA sample and cancer type and the significant prognosis-related pathway with risk score formula is calculated through t-test and univariate Cox analysis. Next, the prognostic value of gained risk score formula and each significant prognosis-related pathway were validated in TCGA and GEO samples by survival analysis. The pivotal hub genes in the enriched significant prognosis-related pathway are identified and validated, and the TIMER database was used to identify the potential role of hub genes in the PDAC immune environment. The potential role of hub genes is promoting the transdifferentiation of cancer-associated fibroblasts.

Results

The enrichment pathway and relevant scores were identified by GSVA, and 3 subtypes of pancreatic ductal adenocarcinoma were defined in TCGA and GEO samples. The clinical stage, tumor node metastasis classification, and tumor grade are strongly relative to the subtype above in TCGA samples. A risk formula about GSVA significant pathway “GSE45365_WT_VS_IFNAR_KO_CD11B_DC_MCMV_INFECTION_DN ∗ 0.80 + HALLMARK_GLYCOLYSIS ∗ 16.8 + GSE19888_CTRL_VS_T_CELL_MEMBRANES_ACT_MAST_CELL_DN ∗ 14.4” was identified and validated in TCGA and GEO samples through survival analysis with significance. DCN, VCAN, B4GALT7, SDC1, SDC2, B3GALT6, B3GAT3, SDC3, GPC1, and XYLT2 were identified as hub genes in these GSVA significant pathways and validated in silico.

Conclusions

Three pancreatic ductal adenocarcinoma subtypes are identified, and an individualized GSVA immune pathway score-related prognostic risk score formula with 10 hub genes is identified and validated. The predicted function of the 10 upregulated hub genes in tumor-immune microenvironment was promoting the infiltration of cancer-associated fibroblasts. These findings will contribute to the precision medicine of pancreatic ductal adenocarcinoma treatment and tumor immune-related basic research.

A nomogram prognostic index for risk-stratification in diffuse large B-cell lymphoma in the rituximab era: a multi-institutional cohort study

BACKGROUND

We aimed to establish a predictive prognostic risk-stratification model for diffuse large B-cell lymphoma (DLBCL) in the rituximab era.

METHODS

The data of 1406 primary DLBCL patients from the Sun Yat-Sen University Cancer Center were analysed to establish a nomogram prognostic index (NPI) model for predicting overall survival (OS) based on pre-treatment indicators. An independent cohort of 954 DLBCL patients from three other hospitals was used for external validation.

RESULTS

Age, performance status, stage, lactate dehydrogenase, number of extranodal sites, BCL2, CD5 expression, B symptoms and absolute lymphocyte and monocyte count were the main factors of the NPI model and could stratify the patients into four distinct categories based on their predicted OS. The calibration curve demonstrated satisfactory agreement between the predicted and actual 5-year OS of the patients. The concordance index of the NPI model (0.794) was higher than the IPI (0.759) and NCCN-IPI (0.750), and similar results were obtained upon external validation. For CD5 + DLBCL patients, systemic treatment with high-dose methotrexate was associated with superior OS compared to R-CHOP-based immunochemotherapy alone.

CONCLUSIONS

We established and validated an accurate prediction model, which performed better than IPI and NCCN-IPI for prognostic stratification of DLBCL patients.

Integration of Genomic and Transcriptomic Markers Improves the Prognosis Prediction of Acute Promyelocytic Leukemia

PURPOSE

The current stratification system for acute promyelocytic leukemia (APL) is based on the white blood cell (WBC) and the platelet counts (i.e., Sanz score) over the past two decades. However, the borderlines among different risk groups are sometimes ambiguous, and for some patients, early death and relapse remained challenges. Besides, with the evolving of the treatment strategy from all-trans-retinoic acid (ATRA) and chemotherapy to ATRA-arsenic trioxide-based synergistic targeted therapy, the precise risk stratification with molecular markers is needed.

EXPERIMENTAL DESIGN

This study performed a systematic analysis of APL genomics and transcriptomics to identify genetic abnormalities in 348 patients mainly from the APL2012 trial (NCT01987297) to illustrate the potential molecular background of Sanz score and further optimize it. The least absolute shrinkage and selection operator algorithm was used to analyze the gene expression in 323 cases to establish a scoring system (i.e., APL9 score).

RESULTS

Through combining NRAS mutations, APL9 score, and WBC, 321 cases can be stratified into two groups with significantly different outcomes. The estimated 5-year overall (P = 0.00031), event-free (P < 0.0001), and disease-free (P = 0.001) survival rates in the revised standard-risk group (95.6%, 93.8%, and 98.1%, respectively) were significantly better than those in the revised high-risk group (82.9%, 77.4%, and 88.4%, respectively), which could be validated using The Cancer Genome Atlas dataset.

CONCLUSIONS

We have proposed a two-category system for improving prognosis in patients with APL. Molecular markers identified in this study may also provide genomic insights into the disease mechanism for improved therapy.

Circulating plasma exosomal miRNA profiles serve as potential metastasis-related biomarkers for hepatocellular carcinoma

Exosomes carry functional molecules that can regulate cancer progression. Understanding the function of exosomal markers may provide invaluable insights into the mechanism of metastasis in hepatocellular carcinoma (HCC). The aim of the present study was to identify metastasis-associated microRNAs (miRNAs/miRs) expressed in plasma exosomes. A miRNA microarray and reverse transcription-quantitative PCR were used to analyze the plasma exosome miRNA expression profiles of patients with metastatic or non-metastatic HCC. Receiver operating characteristic (ROC) curve and Kaplan-Meier analyses were used to evaluate the predictive performance and prognostic efficacy of candidate miRNAs identified in the Gene Expression Omnibus database (dataset accession no. GSE67140). Bioinformatics analysis was used to examine the role of exosomal miRNAs in HCC metastasis. A total of 32 miRNAs were differentially expressed in plasma exosomes of patients with metastatic HCC compared with in those of patients with non-metastatic HCC. Additionally, the expression levels of six miRNAs were consistent between plasma exosome samples and matched tissue samples. ROC analysis demonstrated that miR-18a, miR-27a and miR-20b could discriminate metastatic HCC from non-metastatic HCC. Furthermore, the prognostic efficacy of the combination of three miRNAs (miR-18a, miR-20b and miR-221) was superior to that of individual miRNAs. Survival analysis demonstrated that high expression levels of the candidate miRNAs were associated with poor prognosis. Bioinformatics analysis indicated that the potential target genes of these miRNAs were involved in biological processes, molecular functions and cellular components that were associated with metastasis. The present findings suggested that these exosomal miRNAs may serve important roles in HCC lung metastasis and could represent a complementary clinical tool for the assessment of HCC prognosis.

Identification of a miRNA based model to detect prognostic subgroups in patients with aggressive B-cell lymphoma

In order to differentiate prognostic subgroups of patients with aggressive B-cell lymphoma, we analyzed the expression of 800 miRNAs with the NanoString nCounter human miRNA assay on a cohort of 228 FFPE samples of patients enrolled in the RICOVER-60 and MegaCHOEP trials. We identified significant miRNA signatures for overall survival (OS) and progression-free survival (PFS) by LASSO-penalized linear Cox-regression. High expression levels of miR-130a-3p and miR-423-5p indicate a better prognosis, whereas high levels of miR-374b-5p, miR-590-5p, miR-186-5p, and miR-106b-5p increase patients' risk levels for OS. Regarding PFS high expression of miR-365a-5p in addition to the other two miRNAs improves the prognosis and high levels of miR374a-5p, miR-106b-5p, and miR-590-5p, connects with increased risk and poor prognosis. We identified miRNA signatures to subdivide patients into two different risk groups. These prognostic models may be used in risk stratification in future clinical trials and help making personalized therapy decisions.

Indication and benefit of upfront hematopoietic stem cell transplantation for T-cell lymphoblastic lymphoma in the era of ALL-type induction therapies

Since the introduction of leukemia-type induction therapies for T-cell lymphoblastic lymphoma (T-LBL), improvements in the long-term outcomes of T-LBL have been reported. However, indications for and the appropriate timing of hematopoietic stem cell transplantation (HSCT) have not yet been established. Therefore, we performed a multicenter retrospective cohort study of patients with T-LBL treated using leukemia-type initial therapies to compare the outcomes after HSCT at different disease stages. We enrolled 21 patients with T-LBL from a total of 11 centers, and all patients received hyper-CVAD as a leukemia-type initial regimen. HSCT was performed during the CR1/PR1 (standard disease) stage in 11 patients, while it was completed at a later or non-remission (advanced disease) stage in 10 patients. Following HSCT, the overall survival rate was significantly greater in standard disease than in advanced-disease patients (79.5% vs. 30.0% at 5 years; hazard ratio (HR) 5.97; p = 0.03), with trend to the lower incidence of relapse in the former group (27.3% vs. 60.0% at 5 years; HR 2.29; p = 0.19). A prognostic difference was not detected between cases treated with allogeneic and autologous HSCTs. Our study suggests that frontline HSCT may be a feasible treatment option for T-LBL, even in the era of leukemia-type initial therapy.

The Therapeutic Potential of MicroRNAs in Cancer: Illusion or Opportunity?

The functional involvement of microRNAs in human neoplasia has raised in the last years an increasing interest in the scientific community toward the potential application in clinics as therapeutic tools. Indeed, the possibility to modulate their expression to re-establish a lost equilibrium and counteract tumor growth and dissemination, and/or to improve responsiveness to standard therapies, is promising and fascinating. However, several issues need to be taken into account such as factors related to miRNA stability in the blood, tissue penetration and potential off-target effects, which might affect safety, tolerability and efficacy of an miRNA-based therapy. Here we describe the most relevant challenges related to miRNA-based therapy, review the delivery strategies exploited to date and the on-going clinical trials.

Epigenetic signature predicts overall survival clear cell renal cell carcinoma

BACKGROUND

Recently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC).

METHODS

We used the DNA methylation dataset of The Cancer Genome Atlas (TCGA) database to construct a 31-CpG-based signature which could accurately predict the overall survival of ccRCC. Meanwhile, we constructed a nomogram to predict the prognosis of patients with ccRCC.

RESULT

Through LASSO Cox regression analysis, we obtained the 31-CpG-based epigenetic signature which were significantly related to the prognosis of ccRCC. According to the epigenetic signature, patients were divided into two groups with high and low risk, and the predictive value of the epigenetic signature was verified by other two sets. In the training set, hazard ratio (HR) = 13.0, 95% confidence interval (CI) 8.0-21.2, P < 0.0001; testing set: HR = 4.1, CI 2.2-7.7, P < 0.0001; entire set: HR = 7.2, CI 4.9-10.6, P < 0.0001, Moreover, combined with clinical indicators, the prediction of 5-year survival of ccRCC reached an AUC of 0.871.

CONCLUSIONS

Our study constructed a 31-CpG-based epigenetic signature that could accurately predicted overall survival of ccRCC and staging progression of ccRCC. At the same time, we constructed a nomogram, which may facilitate the prediction of prognosis for patients with ccRCC.

Identification of an Immune-Related Gene Signature Based on Immunogenomic Landscape Analysis to Predict the Prognosis of Adult Acute Myeloid Leukemia Patients

Acute myeloid leukemia (AML) is a hematopoietic malignancy characterized by highly heterogeneous molecular lesions and cytogenetic abnormalities. Immune disorders in AML and impaired immune cell function have been found to be associated with abnormal karyotypes in AML patients. Immunotherapy has become an alternative therapeutic method that can improve the outcomes of AML patients. For solid tumors, the expression patterns of genes associated with the immune microenvironment provide valuable prognostic information. However, the prognostic roles of immune genes in AML have not been studied as yet. In this study, we identified 136 immune-related genes associated with overall survival in AML patients through a univariate Cox regression analysis using data from TCGA-AML and GTEx datasets. Next, we selected 24 hub genes from among the 136 genes based on the PPI network analysis. The 24 immune-related hub genes further underwent multivariate Cox regression analysis and LASSO regression analysis. Finally, a 6 immune-related gene signature was constructed to predict the prognosis of AML patients. The function of the hub IRGs and the relationships between hub IRGs and transcriptional factors were investigated. We found that higher levels of expression of CSK, MMP7, PSMA7, PDCD1, IKBKG, and ISG15 were associated with an unfavorable prognosis of AML patients. Meanwhile, patients in the TCGA-AML datasets were divided into a high risk score group and a low risk score group, based on the median risk score value. Patients in the high risk group tended to show poorer prognosis [P = 0.00019, HR = 1.89 (1.26–2.83)]. The area under the curve (AUC) was 0.6643. Multivariate Cox Regression assay confirmed that the 6 IRG signature was an independent prognostic factor for AML. The prognostic role of the immune related-gene signature was further validated using an independent AML dataset, GSE37642. In addition, patients in the high risk score group in the TCGA dataset were found to be of an advanced age, IDH mutation, and M5 FAB category. These results suggested that the proposed immune related-gene signature may serve as a potential prognostic tool for AML patients.

Establishing and validating a pathway prognostic signature in pancreatic cancer based on miRNA and mRNA sets using GSVA

Pancreatic cancer (PC) is a severe disease with the highest mortality rate among various cancers. It is urgent to find an effective and accurate way to predict the survival of PC patients. Gene set variation analysis (GSVA) was used to establish and validate a miRNA set-based pathway prognostic signature for PC (miPPSPC) and a mRNA set-based pathway prognostic signature for PC (mPPSPC) in independent datasets. An optimized miPPSPC was constructed by combining clinical parameters. The miPPSPC, optimized miPPSPC and mPPSPC were established and validated to predict the survival of PC patients and showed excellent predictive ability. Four metabolic pathways and one oxidative stress pathway were identified in the miPPSPC, whereas linoleic acid metabolism and the pentose phosphate pathway were identified in the mPPSPC. Key factors of the pentose phosphate pathway and linoleic acid metabolism, G6PD and CYP2C8/9/18/19, respectively, are related to the survival of PC patients according to our tissue microarray. Thus, the miPPSPC, optimized miPPSPC and mPPSPC can predict the survival of PC patients efficiently and precisely. The metabolic and oxidative stress pathways may participate in PC progression.

A gene-expression-based signature predicts survival in adults with T-cell lymphoblastic lymphoma: a multicenter study

We aimed to establish a discriminative gene-expression-based classifier to predict survival outcomes of T-cell lymphoblastic lymphoma (T-LBL) patients. After exploring global gene-expression profiles of progressive (n = 22) vs. progression-free (n = 28) T-LBL patients, 43 differentially expressed mRNAs were identified. Then an eleven-gene-based classifier was established using LASSO Cox regression based on NanoString quantification. In the training cohort (n = 169), high-risk patients stratified using the classifier had significantly lower progression-free survival (PFS: hazards ratio 4.123, 95% CI 2.565-6.628; p < 0.001), disease-free survival (DFS: HR 3.148, 95% CI 1.857-5.339; p < 0.001), and overall survival (OS: HR 3.790, 95% CI 2.237-6.423; p < 0.001) compared with low-risk patients. The prognostic accuracy of the classifier was validated in the internal testing (n = 84) and independent validation cohorts (n = 360). A prognostic nomogram consisting of five independent variables including the classifier, lactate dehydrogenase levels, ECOG-PS, central nervous system involvement, and NOTCH1/FBXW7 status showed significantly greater prognostic accuracy than each single variable alone. The addition of a five-miRNA-based signature further enhanced the accuracy of this nomogram. Furthermore, patients with a nomogram score ≥154.2 significantly benefited from the BFM protocol. In conclusion, our nomogram comprising the 11-gene-based classifier may make contributions to individual prognosis prediction and treatment decision-making.

Serum-Derived microRNAs as Prognostic Biomarkers in Osteosarcoma: A Meta-Analysis

Recent reports suggest that microRNAs (miRNAs) may serve as prognostic biomarkers in osteosarcoma. Due to osteosarcoma's early metastasis and poor prognosis, it is very important to find novel prognostic biomarkers for improving osteosarcoma's prognosis. Herein we propose a meta-analysis for serum miRNA's prognostic value in osteosarcoma. In this study, the literature available from PubMed, Web of Science, Embase, and Cochrane Library databases was reviewed. The pooled hazard ratios (HRs) with their 95% confidence intervals (CIs) were calculated to evaluate miRNAs prognostic values. A total of 20 studies investigating serum miRNAs were included in this meta-analysis; the initial terminal point of these reports included overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), and recurrence-free survival (RFS). For prognostic meta-analyses, the pooled HR for terminal events of higher expression of miRNAs and lower expression of miRNAs were 5.68 (95% CI 4.73-6.82, P < 0.05) and 3.78 (95% CI 3.27-4.37, P < 0.05), respectively. Additionally, subgroup analyses were conducted based on the analysis methods applied and clinicopathological features reported. In the pooled analyses, the miRNA expression levels are associated with poor prognosis according to both univariate and multivariate analyses. Furthermore, serum miRNAs (miRNA-195, miRNA-27a, miRNA-191, miRNA-300, miRNA-326, miRNA-497, miRNA-95-3p, miRNA-223, miRNA-491-5p, miRNA-124, miRNA-101, miRNA-139-5p, miRNA-194) were associated with poor OS and found to be closely correlated with clinical stage and distant metastasis in osteosarcoma. The results illustrate that low or high expression of these specific miRNAs are both potentially useful as prognostic serum biomarkers in osteosarcoma, and miRNAs (miRNA-195, miRNA-27a, miRNA-191, miRNA-300, miRNA-326, miRNA-497, miRNA-95-3p, miRNA-223, miRNA-491-5p, miRNA-124, miRNA-101, miRNA-139-5p, miRNA-194) may indicate clinical stage and metastasis in this form of cancer.

Event-free survival at 24 months is a robust surrogate endpoint for long-term survival in pediatric, adolescent, and adult T cell lymphoblastic lymphoma

T cell lymphoblastic lymphoma (T-LBL) has an aggressive clinical behavior. To date, powerful and consistent prognostic factors have not been established for T-LBL. In this study, we first evaluated the association of event-free survival (EFS) at 24 months (EFS24) with overall survival (OS) in T-LBL patients. Besides, we sought to identify clinical factors of prognostic importance in this rare entity. Between January 2006 and December 2017, ninety-one patients with newly diagnosed T-LBL were retrospectively analyzed. EFS was defined as the time from diagnosis to relapse or progression, unplanned retreatment, death from any cause, or to the last follow-up. In total, 91 patients with a median age of 24 years were enrolled. At a median follow-up of 40.4 months (range, 1.4 to 163.3 months), the 5-year OS and EFS was 47.9% and 43.2%, respectively. Of all patients, 45 (49.5%) achieved EFS24 and 46 (50.5%) did not. Patients who achieved EFS24 showed a markedly superior outcome, compared with those who failed to achieve EFS24 (5-year OS, 90.5% vs 3%, P < 0.001). Univariate analysis indicated bone marrow involvement, response to induction treatment, and stem cell transplantation (SCT) consolidation to be prognostic factors for EFS and OS. In addition, compared with the patients receiving non-Hodgkin's lymphoma (NHL)-like treatment protocols, patients treated with hyper-CVAD showed significantly improved EFS and OS. Such survival advantage in terms of EFS and OS was also observed of BMF-90 regimens over NHL-like therapy, despite that the difference in EFS did not reach statistical significance (P = 0.056). Multivariate analysis demonstrated that achievement of complete remission (CR) after induction therapy and SCT consolidation were independent prognostic indicators for both EFS and OS. We confirm that EFS24 is a strong surrogate endpoint for long-term survival in T-LBL, which is clinically useful for individualized risk reassessment, future clinical trial design, and biomarker discovery validation. Further validation in the context of directed prospective clinical trials is warranted.

A CpG Methylation Classifier to Predict Relapse in Adults with T-Cell Lymphoblastic Lymphoma

PURPOSE

Adults with T-cell lymphoblastic lymphoma (T-LBL) generally benefit from treatment with acute lymphoblastic leukemia (ALL)-like regimens, but approximately 40% will relapse after such treatment. We evaluated the value of CpG methylation in predicting relapse for adults with T-LBL treated with ALL-like regimens.

EXPERIMENTAL DESIGN

A total of 549 adults with T-LBL from 27 medical centers were included in the analysis. Using the Illumina Methylation 850K Beadchip, 44 relapse-related CpGs were identified from 49 T-LBL samples by two algorithms: least absolute shrinkage and selector operation (LASSO) and support vector machine-recursive feature elimination (SVM-RFE). We built a four-CpG classifier using LASSO Cox regression based on association between the methylation level of CpGs and relapse-free survival in the training cohort (n = 160). The four-CpG classifier was validated in the internal testing cohort (n = 68) and independent validation cohort (n = 321).

RESULTS

The four-CpG-based classifier discriminated patients with T-LBL at high risk of relapse in the training cohort from those at low risk (P < 0.001). This classifier also showed good predictive value in the internal testing cohort (P < 0.001) and the independent validation cohort (P < 0.001). A nomogram incorporating five independent prognostic factors including the CpG-based classifier, lactate dehydrogenase levels, Eastern Cooperative Oncology Group performance status, central nervous system involvement, and NOTCH1/FBXW7 status showed a significantly higher predictive accuracy than each single variable. Stratification into different subgroups by the nomogram helped identify the subset of patients who most benefited from more intensive chemotherapy and/or sequential hematopoietic stem cell transplantation.

CONCLUSIONS

Our four-CpG-based classifier could predict disease relapse in patients with T-LBL, and could be used to guide treatment decision.

BRD2 induces drug resistance through activation of the RasGRP1/Ras/ERK signaling pathway in adult T-cell lymphoblastic lymphoma

BACKGROUND

Adult patients with T-cell lymphoblastic lymphoma (T-LBL) are treated with high-intensity chemotherapy regimens, but the response rate is still unsatisfactory because of frequent drug resistance. We aimed to investigate the potential mechanisms of drug resistance in adults with T-LBL.

METHODS

Gene expression microarray was used to identify differential mRNA expression profiles between chemotherapy-resistant and chemotherapy-sensitive adult T-LBL tissues. Real-time PCR and immunohistochemistry were performed to detect the expression of bromodomain-containing protein 2 (BRD2) and c-Myc in fresh-frozen T-LBL tissues from 85 adult patients. The Ras pull-down assay was performed to monitor Ras activation. Chromatin immunoprecipitation assays were used to analyze the binding of E2F transcription factor 1 (E2F1)/BRD2 to the RAS guanyl releasing protein 1 (RasGRP1) promoter region. The drug resistance effect and mechanism of BRD2 were determined by both in vivo and in vitro studies.

RESULTS

A total of 86 chemotherapy resistance-related genes in adult T-LBL were identified by gene expression microarray. Among them, BRD2 was upregulated in chemotherapy-resistant adult T-LBL tissues and associated with worse progression-free survival and overall survival of 85 adult T-LBL patients. Furthermore, BRD2 suppressed doxorubicin (Dox)-induced cell apoptosis both in vitro and in vivo. The activation of RasGRP1/Ras/ERK signaling might contribute to the Dox resistance effect of BRD2. Besides, OTX015, a bromodomain and extra-terminal (BET) inhibitor, reversed the Dox resistance effect of BRD2. Patient-derived tumor xenograft demonstrated that the sequential use of OTX015 after Dox showed superior therapeutic effects.

CONCLUSIONS

Our data showed that BRD2 promotes drug resistance in adult T-LBL through the RasGRP1/Ras/ERK signaling pathway. Targeting BRD2 may be a novel strategy to improve the therapeutic efficacy and prolong survival of adults with T-LBL.

A gut microbiota score predicting acute graft-versus-host disease following myeloablative allogeneic hematopoietic stem cell transplantation

Although studies have reported that intestinal microbiota are associated with acute graft-versus-host disease (aGVHD), they lacked a satisfactory method for predicting aGVHD. We collected stool and blood samples at day 15 posttransplant from 150 patients from two centers who underwent myeloablative conditioning allogeneic hematopoietic stem cell transplantation (allo-HSCT). Stool microbiota were detected by 16S ribosomal RNA gene sequencing; inflammatory factors and T lymphocytes were detected by multiplex immunoassays and flow cytometry, respectively. A gut microbiota score (GMS) from a LASSO (least absolute shrinkage and selection operator) model was developed and validated to predict aGVHD. In the discovery cohort, the GMS could predict II-IV aGVHD (area under the receiver operating characteristic [ROC] curve [AUC] = 0.904, P < .0001). Furthermore, the validation model was consistent with the discovery set (AUC = 0.887, P < .0001). Regulatory T/T-helper 17 (Treg/Th17) cells ratio in the low GMS subgroup was higher compared with the high GMS (P = .012), and the validation set is consistent with the discovery set (P = .003). In addition, high cytokine levels were associated with high GMS. In conclusion, the GMS at neutrophil engraftment could predict aGVHD, and it was a potential and novel method. The GMS was associated with the inflammatory factor and Treg/Th17 balance.

Acidic leucine-rich nuclear phosphoprotein-32A expression contributes to adverse outcome in acute myeloid leukemia

Background

Acidic leucine-rich nuclear phosphoprotein-32A (ANP32A) is a novel regulator of histone H3 acetylation and promotes leukemogenesis in acute myeloid leukemia (AML). However, its prognostic value in AML remains unclear.

Methods

In this study, we evaluated the prognostic significance of ANP32A expression using two independent large cohorts of cytogenetically normal AML (CN-AML) patients. Multivariable analysis in CN-AML group was also presented. Based on the ANP32A expression, its related genes, dysregulation of pathways, interaction network analysis between microRNAs and target genes, as well as methylation analysis were performed to unveil the complex functions behind ANP32A.

Results

Here we demonstrated overexpression of ANP32A was notably associated with unfavorable outcome in two independent cohorts of CN-AML patients (OS: P=0.012, EFS: P=0.005, n=185; OS: P=0.041, n=232), as well as in European Leukemia Net (ELN) Intermediate-I group (OS: P=0.018, EFS: P=0.045, n=115), National Comprehensive Cancer Network (NCCN) Intermediate Risk AML group (OS: P=0.048, EFS: P=0.039, n=225), and non-M3 AML group (OS: P=0.034, EFS: P=0.011, n=435). Multivariable analysis further validated ANP32A as a high-risk factor in CN-AML group. Multi-omics analysis presented overexpression of ANP32A was associated with aberrant expression of oncogenes and tumor suppressor, up/down-regulation of metabolic and immune-related pathways, dysregulation of microRNAs, and hypomethylation on CpG island and 1st Exon regions.

Conclusions

We proved ANP32A as a novel, potential unfavorable prognosticator and therapeutic target for AML.

DNA Dumbbell and Chameleon Silver Nanoclusters for miRNA Logic Operations

Multiplex miRNA analysis is a fundamental issue for exploring a complex biological system and early diagnosis of miRNA-related diseases. Herein, we have developed a series of novel logic gates for miRNA analysis coupling DNA nanostructures and chameleon silver nanoclusters (AgNCs). DNA dumbbell structures are firstly designed with two independent nucleation sequences for AgNCs at the 5' and 3' ends, respectively. By introducing different miRNA inputs, separations of two AgNCs are controlled and the fluorescence property of AgNCs changes. By studying the ratiometric fluorescence responses, sensitive and selective analysis of multiple miRNAs can be achieved. The present work provides powerful tools for miRNA diagnostics and may also guide future DNA nanostructure-based logic gates.

CircAHNAK1 inhibits proliferation and metastasis of triple-negative breast cancer by modulating miR-421 and RASA1

Background: There is increasing evidence that circular RNAs (circRNAs) participate in regulating cancer progression. However, the function and potential molecular mechanisms of circRNA in triple negative breast cancer (TNBC) are currently largely unclear.

Results: We found that circAHNAK1 was significantly down-regulated in TNBC, and its expression was negatively associated with RFS and OS. Overexpression of circAHNAK1 can inhibit TNBC proliferation, migration and invasion in vitro. In vivo studies confirmed that circAHNAK1 inhibited TNBC tumor growth and metastasis. Mechanistic analysis indicated that circAHNAK1 acted as a miR-421 ceRNA (competitive endogenous RNA) to attenuate the inhibitory effect of miR-421 on its target gene RASA1.

Conclusions: In conclusion, CircAHNAK1 inhibits proliferation and metastasis of TNBC by modulating miR-421 and RASA1.

Methods: CircRNA microarrays were used to screen for differential circRNA expression profiles. qRT-PCR was used to detect the expression levels of circRNAs. The effect of circAHNAK1 on recurrence -free survival (RFS) and overall survival (OS) in patients with TNBC was subsequently analyzed. The role of circAHNKA1 in the progression of TNBC was further evaluated by multiple in vivo and in vitro assays. Finally, we focused on the regulation of circAHNAK1 on miR-421 and its targeted gene RASA1 in TNBC.

Reactive oxygen species metabolism-based prediction model and drug for patients with recurrent glioblastoma

Background: Tumor recurrence is the main cause of poor prognosis of GBM. Finding the characteristics of recurrent GBM that provide early warning of tumor recurrence can provide guidance for the clinical treatment of recurrent GBM.

Results: Reactive oxygen species (ROS) biosynthetic processes was significantly elevated in recurrent GBM. The recurrent risk score based on the ROS biosynthetic process was closely related to tumor purity and tumor immune functions. The quantitative risk assessment system could be used to predict the recurrence time of GBM. Gallic acid, a compound with high anti-oxidation activity and low cytotoxicity, was screened as a potential chemotherapy sensitizer for recurrent GBM.

Conclusion: The quantitative risk assessment system based on ROS biosynthetic process could be used for early warning of GBM recurrence. Combination of low-dose gallic acid and temozolomide could improve therapeutic outcomes in recurrent GBM.

Methods: A total of 663 primary and recurrent GBM samples with clinical and microarray data were included in this study. GSVA, LASSO-COX, and Kaplan-Meier survive curve were performed to construct and verify a quantitative risk assessment system for GBM recurrence prediction. An antioxidant capacity test and cell viability test were used to discover potential drugs for recurrent GBM.

A Four-Pseudogene Classifier Identified by Machine Learning Serves as a Novel Prognostic Marker for Survival of Osteosarcoma

Osteosarcoma is a common malignancy with high mortality and poor prognosis due to lack of predictive markers. Increasing evidence has demonstrated that pseudogenes, a type of non-coding gene, play an important role in tumorigenesis. The aim of this study was to identify a prognostic pseudogene signature of osteosarcoma by machine learning. A sample of 94 osteosarcoma patients’ RNA-Seq data with clinical follow-up information was involved in the study. The survival-related pseudogenes were screened and related signature model was constructed by cox-regression analysis (univariate, lasso, and multivariate). The predictive value of the signature was further validated in different subgroups. The putative biological functions were determined by co-expression analysis. In total, 125 survival-related pseudogenes were identified and a four-pseudogene (RPL11-551L14.1, HR: 0.65 (95% CI: 0.44–0.95); RPL7AP28, HR: 0.32 (95% CI: 0.14–0.76); RP4-706A16.3, HR: 1.89 (95% CI: 1.35–2.65); RP11-326A19.5, HR: 0.52(95% CI: 0.37–0.74)) signature effectively distinguished the high- and low-risk patients, and predicted prognosis with high sensitivity and specificity (AUC: 0.878). Furthermore, the signature was applicable to patients of different genders, ages, and metastatic status. Co-expression analysis revealed the four pseudogenes are involved in regulating malignant phenotype, immune, and DNA/RNA editing. This four-pseudogene signature is not only a promising predictor of prognosis and survival, but also a potential marker for monitoring therapeutic schedule. Therefore, our findings may have potential clinical significance.