High expression of dedicator of cytokinesis 1 (DOCK1) confers poor prognosis in acute myeloid leukemia

High DOCK1 expression identifies a distinct prognostic subgroup of pediatric acute myeloid leukemia: Results of the Japanese Pediatric Leukemia/Lymphoma Study Group AML-05 trial

BACKGROUND

The molecular pathogenesis of acute myeloid leukemia (AML) was dramatically clarified over the latest two decades. Several important molecular markers were discovered in patients with AML that have helped to improve the risk stratification. However, developing new treatment strategies for relapsed/refractory acute myeloid leukemia (AML) is crucial due to its poor prognosis.

PROCEDURE

To overcome this difficulty, we performed an assay for transposase-accessible chromatin with sequencing (ATAC-seq) in 10 AML patients with various gene alterations. ATAC-seq is based on direct in vitro sequencing adaptor transposition into native chromatin, and is a rapid and sensitive method for integrative epigenomic analysis. ATAC-seq analysis revealed increased accessibility of the DOCK1 gene in patients with AML harboring poor prognostic factors. Following the ATAC-seq results, quantitative reverse transcription polymerase chain reaction was used to measure DOCK1 gene expression levels in 369 pediatric patients with de novo AML.

RESULTS

High DOCK1 expression was detected in 132 (37%) patients. The overall survival (OS) and event-free survival (EFS) among patients with high DOCK1 expression were significantly worse than those patients with low DOCK1 expression (3-year EFS: 34% vs. 60%, p < .001 and 3-year OS: 60% vs. 80%, p < .001). To investigate the significance of high DOCK1 gene expression, we transduced DOCK1 into MOLM14 cells, and revealed that cytarabine in combination with DOCK1 inhibitor reduced the viability of these leukemic cells.

CONCLUSIONS

Our results indicate that a DOCK1 inhibitor might reinforce the effects of cytarabine and other anti-cancer agents in patients with AML with high DOCK1 expression.

T cell-mediated tumor killing sensitivity gene signature-based prognostic score for acute myeloid leukemia

BACKGROUND AND OBJECTIVE

Acute myeloid leukemia (AML) is an aggressive, heterogenous hematopoetic malignancies with poor long-term prognosis. T-cell mediated tumor killing plays a key role in tumor immunity. Here, we explored the prognostic performance and functional significance of a T-cell mediated tumor killing sensitivity gene (GSTTK)-based prognostic score (TTKPI).

METHODS

Publicly available transcriptomic data for AML were obtained from TCGA and NCBI-GEO. GSTTK were identified from the TISIDB database. Signature GSTTK for AML were identified by differential expression analysis, COX proportional hazards and LASSO regression analysis and a comprehensive TTKPI score was constructed. Prognostic performance of the TTKPI was examined using Kaplan-Meier survival analysis, Receiver operating curves, and nomogram analysis. Association of TTKPI with clinical phenotypes, tumor immune cell infiltration patterns, checkpoint expression patterns were analysed. Drug docking was used to identify important candidate drugs based on the TTKPI-component genes.

RESULTS

From 401 differentially expressed GSTTK in AML, 24 genes were identified as signature genes and used to construct the TTKPI score. High-TTKPI risk score predicted worse survival and good prognostic accuracy with AUC values ranging from 75 to 96%. Higher TTKPI scores were associated with older age and cancer stage, which showed improved prognostic performance when combined with TTKPI. High TTKPI was associated with lower naïve CD4 T cell and follicular helper T cell infiltrates and higher M2 macrophages/monocyte infiltration. Distinct patterns of immune checkpoint expression corresponded with TTKPI score groups. Three agents; DB11791 (Capmatinib), DB12886 (GSK-1521498) and DB14773 (Lifirafenib) were identified as candidates for AML.

CONCLUSION

A T-cell mediated killing sensitivity gene-based prognostic score TTKPI showed good accuracy in predicting survival in AML. TTKPI corresponded to functional and immunological features of the tumor microenvironment including checkpoint expression patterns and should be investigated for precision medicine approaches.

Machine Learning-Based Integrated Analysis of PANoptosis Patterns in Acute Myeloid Leukemia Reveals a Signature Predicting Survival and Immunotherapy

Objective

We conducted a meticulous bioinformatics analysis leveraging expression data of 226 PANRGs obtained from previous studies, as well as clinical data from AML patients derived from the HOVON database.

Methods

Through meticulous data analysis and manipulation, we were able to categorize AML cases into two distinct PANRG clusters and subsequently identify differentially expressed genes (PRDEGs) with prognostic significance. Furthermore, we organized the patient data into two corresponding gene clusters, allowing us to investigate the intricate relationship between the risk score, patient prognosis, and the immune landscape.

Results

Our findings disclosed significant associations between the identified PANRGs, gene clusters, patient survival, immune system, and cancer-related biological processes and pathways. Importantly, we successfully constructed a prognostic signature comprising nineteen genes, enabling the stratification of patients into high-risk and low-risk groups based on individually calculated risk scores. Furthermore, we developed a robust and practical nomogram model, integrating the risk score and other pertinent clinical features, to facilitate accurate patient survival prediction. Our comprehensive analysis demonstrated that the high-risk group exhibited notably worse prognosis, with the risk score proving to be significantly correlated with infiltration of most immune cells. The qRT-PCR results revealed significant differential expression patterns of LGR5 and VSIG4 in normal and human leukemia cell lines (HL-60 and MV-4-11).

Conclusions

Our findings underscore the potential utility of PANoptosis-based molecular clustering and prognostic signatures as predictive tools for assessing patient survival in AML.

Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes

Background

One of the most prevalent hematological system cancers is acute myeloid leukemia (AML). Efferocytosis-related genes (ERGs) and N6-methyladenosine (m6A) have an important significance in the progression of cancer, and the metastasis of tumors.

Methods

The AML-related data were collected from The Cancer Genome Atlas (TCGA; TCGA-AML) database and Gene Expression Omnibus (GEO; GSE9476, GSE71014, and GSE13159) database. The "limma" R package and Venn diagram were adopted to identify differentially expressed ERGs (DE-ERGs). The m6A related-DE-ERGs were obtained by Spearman analysis. Subsequently, univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) were used to construct an m6A related-ERGs risk signature for AML patients. The possibility of immunotherapy for AML was explored. The pRRophetic package was adopted to calculate the IC50 of drugs for the treatment of AML. Finally, the expression of characterized genes was validated by quantitative reverse transcription-PCR (qRT-PCR).

Results

Based on m6A related-DE-ERGs, a prognostic model with four characteristic genes (UCP2, DOCK1, SLC14A1, and SLC25A1) was constructed. The risk score of model was significantly associated with the immune microenvironment of AML, with four immune cell types, 14 immune checkpoints, 20 HLA family genes and, immunophenoscore (IPS) all showing differences between the high- and low-risk groups. A total of 56 drugs were predicted to differ between the two groups, of which Erlotinib, Dasatinib, BI.2536, and bortezomib have been reported to be associated with AML treatment. The qRT-PCR results showed that the expression trends of DOCK1, SLC14A1 and SLC25A1 were consistent with the bioinformatics analysis.

Conclusion

In summary, 4 m6A related- ERGs were identified and the corresponding prognostic model was constructed for AML patients. This prognostic model effectively stratified the risk of AML patients.

Comprehensive analysis of aberrantly expressed circRNAs, mRNAs and lncRNAs in patients with nasopharyngeal carcinoma

BACKGROUND

The location of nasopharyngeal cancer is hidden, so it is difficult to diagnose at an early stage. In this study, we aimed to investigate the expression profiles of circRNAs, mRNAs and IncRNAs and to provide some basis for further studies.

METHODS

Expression profiles of circRNAs, mRNAs, and lncRNAs were analyzed using microarray techniques. The differentially expressed ncRNA was calculated by bioinformatics.

RESULTS

A total of 3048 circRNAs, 2179 lncRNAs, and 2015 mRNAs were detected to be significantly differentially expressed in NPC. The most upregulated circRNAs, lncRNAs, and mRNAs were hsa-circ-0067562, NONHSAT232922.1, and HOXB13, respectively. And, the most downregulated circRNAs, lncRNAs, and mRNAs were hsa_circ_0078837, lnc-TTC8-4:3, and LTF, respectively. The number of upregulated DE lncRNAs was more than twice than those downregulated. Our data showed that 80.44% of pairs of lncRNAs and cis-mRNAs demonstrated positive correlations. For lncRNAs and trans-mRNAs pairs, 53.7% of pairs showed positive correlation. LncRNA-mediated cis regulation is a prevalent regulatory mode in the development of nasopharyngeal carcinoma. CR1, LRMP and SORBS2 are predicted to be mediated not only by cis-acting lncRNA modes of action, but also by trans-acting lncRNA mechanisms. Additionally, we constructed a diagnostic prediction model with a high sensitivity and specificity.

CONCLUSION

Our study characterized the landscape of circRNAs, mRNAs and lncRNAs in NPC tissue and provided novel insights into the molecular mechanisms of NPC.

Distinct noncoding RNAs and RNA binding proteins associated with high-risk pediatric and adult acute myeloid leukemias detected by regulatory network analysis

BACKGROUND

Acute myeloid leukemia (AML) is a heterogeneous disease in both children and adults. Although it is well-known that adult and pediatric AMLs are genetically distinct diseases, the driver genes for high-risk pediatric and adult AMLs are still not fully understood. Particularly, the interactions between RNA binding proteins (RBPs) and noncoding RNAs (ncRNAs) for high-risk AMLs have not been explored.

AIM

To identify RBPs and noncoding RNAs (ncRNAs) that are the master regulators of high-risk AML.

METHODS

In this manuscript, we identify over 400 upregulated genes in high-risk adult and pediatric AMLs respectively with the expression profiles of TCGA and TARGET cohorts. There are less than 5% genes commonly upregulated in both cohorts, highlighting the genetic differences in adult and childhood AMLs. A novel distance correlation test is proposed for gene regulatory network construction. We build RBP-based regulatory networks with upregulated genes in high-risk adult and pediatric AMLs, separately.

RESULTS

We discover that three RBPs, three snoRNAs, and two circRNAs function together and regulate over 100 upregulated RNA targets in adult AML, whereas two RBPs are associated with 17 long noncoding RNAs (lncRNAs), and all together regulate over 90 upregulated RNA targets in pediatric AML. Of which, two RBPs, MLLT3 and RBPMS, and their circRNA targets, PTK2 and NRIP1, are associated with the overall survival (OS) in adult AML (p ≤ 0.01), whereas two different RBPs, MSI2 and DNMT3B, and 13 (out of 17) associated lncRNAs are prognostically significant in pediatric AML.

CONCLUSIONS

Both RBPs and ncRNAs are known to be the major regulators of transcriptional processes. The RBP-ncRNA pairs identified from the regulatory networks will allow better understanding of molecular mechanisms underlying high-risk adult and pediatric AMLs, and assist in the development of novel RBPs and ncRNAs based therapeutic strategies.

Comprehensive analysis for cellular senescence-related immunogenic characteristics and immunotherapy prediction of acute myeloid leukemia

In malignancies, cellular senescence is critical for carcinogenesis, development, and immunological regulation. Patients with acute myeloid leukemia (AML) have not investigated a reliable cellular senescence-associated profile and its significance in outcomes and therapeutic response. Cellular senescence-related genes were acquired from the CellAge database, while AML data were obtained from the GEO and TCGA databases. The TCGA-AML group served as a training set to construct a prognostic risk score signature, while the GSE71014 set was used as a testing set to validate the accuracy of the signature. Through exploring the expression profiles of cellular senescence-related genes (SRGs) in AML patients, we used Lasso and Cox regression analysis to establish the SRG-based signature (SRGS), which was validated as an independent prognostic predictor for AML patients via clinical correlation. Survival analysis showed that AML patients in the low-risk score group had a longer survival time. Tumor immune infiltration and functional enrichment analysis demonstrated that AML patients with low-risk scores had higher immune infiltration and active immune-related pathways. Meanwhile, drug sensitivity analysis and the TIDE algorithm showed that the low-risk score group was more susceptible to chemotherapy and immunotherapy. Cell line analysis in vitro further confirmed that the SRGs in the proposed signature played roles in the susceptibility to cytarabine and YM155. Our results indicated that SRGS, which regulates the immunological microenvironment, is a reliable predictor of the clinical outcome and immunotherapeutic response in AML.

Combinatorial genetics reveals the Dock1-Rac2 axis as a potential target for the treatment of NPM1;Cohesin mutated AML

Acute myeloid leukemia (AML) is driven by mutations that occur in numerous combinations. A better understanding of how mutations interact with one another to cause disease is critical to developing targeted therapies. Approximately 50% of patients that harbor a common mutation in NPM1 (NPM1cA) also have a mutation in the cohesin complex. As cohesin and Npm1 are known to regulate gene expression, we sought to determine how cohesin mutation alters the transcriptome in the context of NPM1cA. We utilized inducible Npm1cAflox/+ and core cohesin subunit Smc3flox/+ mice to examine AML development. While Npm1cA/+;Smc3Δ/+ mice developed AML with a similar latency and penetrance as Npm1cA/+ mice, RNA-seq suggests that the Npm1cA/+; Smc3Δ/+ mutational combination uniquely alters the transcriptome. We found that the Rac1/2 nucleotide exchange factor Dock1 was specifically upregulated in Npm1cA/+;Smc3Δ/+ HSPCs. Knockdown of Dock1 resulted in decreased growth and adhesion and increased apoptosis only in Npm1cA/+;Smc3Δ/+ AML. Higher Rac activity was also observed in Npm1cA/+;Smc3Δ/+ vs. Npm1cA/+ AMLs. Importantly, the Dock1/Rac pathway is targetable in Npm1cA/+;Smc3Δ/+ AMLs. Our results suggest that Dock1/Rac represents a potential target for the treatment of patients harboring NPM1cA and cohesin mutations and supports the use of combinatorial genetics to identify novel precision oncology targets.

Survival prediction in acute myeloid leukemia using gene expression profiling

BACKGROUND

Acute myeloid leukemia (AML) is a genetically heterogeneous blood disorder. AML patients are associated with a relatively poor overall survival. The objective of this study was to establish a machine learning model to accurately perform the prognosis prediction in AML patients.

METHODS

We first screened for prognosis-related genes using Kaplan-Meier survival analysis in The Cancer Genome Atlas dataset and validated the results in the Oregon Health & Science University dataset. With a random forest model, we built a prognostic risk score using patient's age, TP53 mutation, ELN classification and normalized 197 gene expression as predictor variable. Gene set enrichment analysis was implemented to determine the dysregulated gene sets between the high-risk and low-risk groups. Similarity Network Fusion (SNF)-based integrative clustering was performed to identify subgroups of AML patients with different clinical features.

RESULTS

The random forest model was deemed the best model (area under curve value, 0.75). The random forest-derived risk score exhibited significant association with shorter overall survival in AML patients. The gene sets of pantothenate and coa biosynthesis, glycerolipid metabolism, biosynthesis of unsaturated fatty acids were significantly enriched in phenotype high risk score. SNF-based integrative clustering indicated three distinct subsets of AML patients in the TCGA cohort. The cluster3 AML patients were characterized by older age, higher risk score, more frequent TP53 mutations, higher cytogenetics risk, shorter overall survival.

CONCLUSIONS

The random forest-based risk score offers an effective method to perform prognosis prediction for AML patients.

LINC00665 promotes the progression of acute myeloid leukemia by regulating the miR-4458/DOCK1 pathway

This study aimed to explore the role of LINC00665, miR-4458 and DOCK1 and their interactions in the development of acute myeloid leukemia (AML). The relative expression of LINC00665, miR-4458 and DOCK1 in AML samples was measured using qRT-PCR, and the protein level of DOCK1 in AML cell lines was examined using western blot. CCK8, BrdU, transwell, cell adhesion, and caspase-3 activity assays were carried out to evaluate the viability, proliferation, migration, adhesion, and apoptosis of AML cells, respectively. Luciferase reporter, RIP, and RNA pull-down assays were also performed to confirm the target relationship among LINC00665, miR-4458 and DOCK1. Findings revealed that LINC00665 and DOCK1 were aberrantly overexpressed in AML tissues and that the expression of miR-4458 was low in AML tissues. Silencing LINC00665 or DOCK1 presented significant restriction to the proliferation, migration and adhesion of AML cells. Apart from that, it was found that inhibiting miR-4458 could enhance the proliferation, migration and adhesion of AML cells but suppress the apoptosis of AML cells. Experimental results also indicated that LINC00665 exerted its positive function on AML cells by sponging miR-4458 and that miR-4458 influenced the progression of AML cells by targeting DOCK1 directly. Overall, this finding not only provided a novel molecular pathway for the diagnosis and treatment of AML but also showed that LINC00665 could enhance the progression of AML by regulating the miR-4458/DOCK1 pathway.

Dysregulation of miR-138-5p/RPS6KA1-AP2M1 Is Associated With Poor Prognosis in AML

Acute myeloid leukemia (AML) is a malignant disease of hematopoietic stem/progenitor cells, and most AML patients are in a severe state. Internal tandem duplication mutations in FLT3 gene (FLT3-ITD) detected in AML stem cells account for 20–30 percent of AML patients. In this study, we attempted to study the impact of the interaction of FLT3-ITD mutation and the CXCL12/CXCR4 axis in AML, and the possible mechanisms caused by the impact by bioinformatics. Gene set variation analysis (GSVA) revealed that the PI3K-Akt-mTOR pathway positively correlated with the status of FLT3-ITD mutation. Multiple survival analyses were performed on TCGA-AML to screen the prognostic-related genes, and RPS6KA1 and AP2M1 are powerful prognostic candidates for overall survival in AML. WGCNA, KEGG/GO analysis, and the functional roles of RPS6KA1 and AP2M1 in AML were clarified by correlation analysis. We found that the expression levels of RPS6KA1 and AP2M1 were significantly associated with chemoresistance of AML, and the CXCL12/CXCR4 axis would regulate RPS6KA1/AP2M1 expression. Besides, miR-138-5p, regulated by the CXCL12/CXCR4 axis, was the common miRNA target of RPS6KA1 and AP2M1. Taken together, the interaction of FLT3-ITD mutation and the CXCL12/CXCR4 axis activated the PI3K-Akt-mTOR pathway, and the increased expression of RPS6KA1 and AP2M1 caused by hsa-miR-138-5p downregulation regulates the multi-resistance gene expression leading to drug indications.

Patent highlights June-July 2020

A snapshot of noteworthy recent developments in the patent literature of relevance to pharmaceutical and medical research and development.

Distinct clinical and biological characteristics of acute myeloid leukemia with higher expression of long noncoding RNA KIAA0125

Expression of long non-coding RNA KIAA0125 has been incorporated in various gene expression signatures for prognostic prediction in acute myeloid leukemia (AML) patients, yet its functions and clinical significance remain unclear. This study aimed to investigate the clinical and biological characteristics of AML bearing different levels of KIAA0125. We profiled KIAA0125 expression levels in bone marrow cells from 347 de novo AML patients and found higher KIAA0125 expression was closely associated with RUNX1 mutation, but inversely correlated with t(8;21) and t(15;17) karyotypes. Among the 227 patients who received standard chemotherapy, those with higher KIAA0125 expression had a lower complete remission rate, shorter overall survival (OS) and disease-free survival (DFS) than those with lower expression. The prognostic significance was validated in both TCGA and GSE12417 cohorts. Subgroup analyses showed that higher KIAA0125 expression also predicted shorter DFS and OS in patients with normal karyotype or non-M3 AML. In multivariable analysis, higher KIAA0125 expression remained an adverse risk factor independent of age, WBC counts, karyotypes, and mutation patterns. Bioinformatics analyses revealed that higher KIAA0125 expression was associated with hematopoietic and leukemic stem cell signatures and ATP-binding cassette transporters, two predisposing factors for chemoresistance.

SETDB1 mediated histone H3 lysine 9 methylation suppresses MLL-fusion target expression and leukemic transformation

Epigenetic regulators play a critical role in normal and malignant hematopoiesis. Deregulation, including epigenetic deregulation, of the HOXA gene cluster drives transformation of about 50% of acute myeloid leukemia. We recently showed that the Histone 3 Lysine 9 methyltransferase SETDB1 negatively regulates the expression of the pro-leukemic genes Hoxa9 and its cofactor Meis1 through deposition of promoter H3K9 trimethylation in MLL-AF9 leukemia cells. Here, we investigated the biological impact of altered SETDB1 expression and changes in H3K9 methylation on acute myeloid leukemia. We demonstrate that SETDB1 expression is correlated to disease status and overall survival in acute myeloid leukemia patients. We recapitulated these findings in mice, where high expression of SETDB1 delayed MLL-AF9 mediated disease progression by promoting differentiation of leukemia cells. We also explored the biological impact of treating normal and malignant hematopoietic cells with an H3K9 methyltransferase inhibitor, UNC0638. While myeloid leukemia cells demonstrate cytotoxicity to UNC0638 treatment, normal bone marrow cells exhibit an expansion of cKit+ hematopoietic stem and progenitor cells. Consistent with these data, we show that bone marrow treated with UNC0638 is more amenable to transformation by MLL-AF9. Next generation sequencing of leukemia cells shows that high expression of SETDB1 induces repressive changes to the promoter epigenome and downregulation of genes linked with acute myeloid leukemia, including Dock1 and the MLL-AF9 target genes Hoxa9, Six1, and others. These data reveal novel targets of SETDB1 in leukemia that point to a role for SETDB1 in negatively regulating pro-leukemic target genes and suppressing acute myeloid leukemia.

Identifying a novel 5-gene signature predicting clinical outcomes in acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) is the most common type of acute leukemia and biologically heterogeneous diseases with poor prognosis. Thus, we aimed to identify prognostic markers to effectively predict the prognosis of AML patients and eventually guide treatment.

METHODS

Prognosis-associated genes were determined by Kaplan-Meier and multivariate analyses using the expression and clinical data of 173 AML patients from The Cancer Genome Atlas database and validated in an independent Oregon Health and Science University dataset. A prognostic risk score was computed based on a linear combination of 5-gene expression levels using the regression coefficients derived from the multivariate logistic regression model. The classification of AML was established by unsupervised hierarchical clustering of CALCRL, DOCK1, PLA2G4A, FCHO2 and LRCH4 expression levels.

RESULTS

High FCHO2 and LRCH4 expression was related to decreased mortality. While high CALCRL, DOCK1, PLA2G4A expression was associated with increased mortality. The risk score was predictive of increased mortality rate in AML patients. Hierarchical clustering analysis of the five genes discovered three clusters of AML patients. The cluster1 AML patients were associated with lower cytogenetics risk than cluster2 or 3 patients, and better prognosis than cluster3 patients (P values < 0.05 for all cases, fisher exact test or log-rank test).

CONCLUSION

The gene panel comprising CALCRL, DOCK1, PLA2G4A, FCHO2 and LRCH4 as well as the risk score may offer novel prognostic biomarkers and classification of AML patients to significantly improve outcome prediction.

Construction of a 14-lncRNA risk score system predicting survival of children with acute myelocytic leukemia

Acute myelocytic leukemia (AML) is a frequent type of acute leukemia. The present study was performed to build a risk score system for the prognostic prediction of AML. AML RNA-sequencing data from samples from 111 children were downloaded from The Cancer Genome Atlas database. Using the DEseq and edgeR packages, the differentially expressed long non-coding RNAs (DE-lncRNAs) between bad and good prognosis groups were identified. A survival package was used to screen prognosis-associated lncRNAs and clinical factors. The optimal lncRNA combination was selected using the penalized package, and the risk-score system was built and evaluated. After the lncRNA-mRNA expression correlation network was constructed, the potential pathways involving the key lncRNAs were enriched using Gene Set Enrichment Analysis. Among the 61 DE-lncRNAs, 48 lncRNAs were significantly associated with prognosis. Relapse was an independent prognostic factor. The optimal 14-lncRNA risk score system was constructed. After 730 differentially expressed mRNAs were identified between the good and bad prognosis groups divided using a prognostic index, the lncRNA-mRNA expression correlation network was constructed. Enrichment analysis showed that semaphorin-3C [SEMA3C; regulated by probable leucine-tRNA ligase, mitochondrial (LARS2-AS1)] and secreted frizzled-related protein 5 [SFRP5; mediated by WASH complex subunit 5 (WASHC5)-antisense RNA 1 (AS1)] were involved in axon guidance and the Wnt signaling pathway, respectively. A 14-lncRNA (including paired box protein Pax8-AS1 and MYB AS1) risk-score system might be effective in predicting the prognosis of AML. Axon guidance (involving SEMA3C and LARS2-AS1) and the Wnt signaling pathway (involving SFRP5 and WASHC5-AS1) might be two important pathways affecting the prognosis of AML.

Circular RNA DOCK1 downregulates microRNA-124 to induce the growth of human thyroid cancer cell lines

BACKGROUND

Both circular RNA DOCK1 (circDOCK1) and microRNA-124 (miR-124) are implicated in carcinogenesis, but functional association between these two molecules remains uncharacterized. Here, we aimed to ascertain the role of circDOCK1-miR-124 node in thyroid cancer cells.

METHODS

circDOCK1 in thyroid cancer specimens from 25 patients was quantified by qRT-PCR. FTC-133 and TPC-1 cells were enforced to overproduce circDOCK1 and miR-124 which were confirmed by qRT-PCR. The alteration in viability, migration and invasion was monitored. Cellular lysis was subjected to Western blot for detecting cyclin D1, p53, matrix metallopeptidase 9 (MMP-9), and vimentin. The phosphorylation of JAK1, STAT3, and AMPK was determined by Western blot.

RESULTS

Results from qRT-PCR showed circDOCK1 was enriched in thyroid carcinoma tissues. circDOCK1 fortified the viability of FTC-133 and TPC-1 cells, as well as their activities to migrate and invade. circDOCK1 increased cyclin D1 and decreased p53, and meanwhile induced the accumulation of MMP-9 and vimentin. miR-124 conferred a reverse effect on the abovementioned alteration. Besides, miR-124 blockaded the phosphorylation of JAK1, STAT3, and AMPK which was induced by circDOCK1.

CONCLUSION

circDOCK1 contributed to thyroid carcinogenesis through inhibition of miR-124 in thyroid cancer cells with dampening signaling transduction of JAK/STAT/AMPK in virtue of miR-124 downregulation.

Genome-wide identification of FHL1 as a powerful prognostic candidate and potential therapeutic target in acute myeloid leukaemia

Background

Acute myeloid leukaemia (AML) is a malignant haematological tumour with high heterogeneity and mortality. A reliable prognostic assessment is critical for treatment strategies. However, the current prognostic evaluation system of AML is insufficient.

Methods

Genome-wide univariate Cox regression analysis was performed on three independent AML datasets to screen for the prognostic-related genes. Kaplan–Meier survival analysis was employed to verify the efficacy of FHL1 in evaluating overall survival in 1298 de novo AML patients, 648 non-acute promyelocytic leukaemia AML patients and 407 cytogenetically normal AML patients; the data for some of these patients were also used for EFS and RFS validation. Multivariate Cox regression was performed to validate FHL1 as an independent prognostic indicator. WGCNA, GSEA, and gene correlation analysis were applied to explore the mechanism of FHL1 in AML. The synergistic cytocidal effect of FHL1 knockdown was verified in in vitro experiments.

Findings

Comprehensive genome-wide analyses and large-sample validation showed that FHL1 is a powerful prognostic candidate for overall survival, event-free survival, and relapse-free survival in AML and is independent of prognosis-related clinical factors and genetic abnormalities. The molecular mechanism may occur through regulation of FHL1 in leukaemia stem cells, tumour-associated signalling pathways, and transmembrane transport of chemotherapeutic drugs. FHL1-targeted intervention enhances the sensitivity of AML cells to cytarabine.

Interpretation

FHL1 may serve as an evaluation factor for clinical strategy selection, and its targeted intervention may be beneficial for chemotherapy in AML patients.

High expression of DOCK2 indicates good prognosis in acute myeloid leukemia

DOCK family proteins are evolutionarily conserved guanine nucleotide exchange factors for Rho GTPase with different cellular functions. It has been demonstrated that DOCK1 had adverse prognostic effect in acute myeloid leukemia (AML). We first analyzed data of 85 AML patients who were treated with chemotherapy and had available DOCK1 to DOCK11 expression information and found that DOCK1 and DOCK2 had prognostic significance in AML. In view of the known prognosis of DOCK1 in AML, we then explored the prognostic role of DOCK2. One hundred fifty-six AML patients with DOCK2 expression data were extracted from The Cancer Genome Atlas (TCGA) database and enrolled in this study. Patients were divided based on treatment modality into the chemotherapy group and the allogeneic hematopoietic stem cell transplant (allo-HSCT) group. Each group was divided into two groups by the median expression levels of DOCK2. In the chemotherapy group, high DOCK2 expression was associated with longer event-free survival (EFS, P=0.001) and overall survival (OS, P=0.007). In the allo-HSCT group, EFS and OS were not significantly different between high and low DOCK2 expression groups. Multivariate analysis showed that high DOCK2 expression was an independent favorable prognostic factor for both EFS and OS in all patients (all P<0.05). In conclusion, our results indicated that high DOCK2 expression, in contrast to DOCK1, conferred good prognosis in AML.

High expression of dedicator of cytokinesis 1 adversely influences the prognosis of acute myeloid leukemia patients undergoing allogeneic hematopoietic stem cell transplantation

Background: Overexpression of dedicator of cytokinesis 1 (DOCK1) has been confirmed as an unfavorable prognostic marker in acute myeloid leukemia (AML). Purpose: This study is to explore the clinical implications of DOCK1 on AML patients underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT). Patients and methods: We analyzed 71 de novo AML patients treated with allo-HSCT and divided them into two groups (DOCK1 ^high vs DOCK1 ^low) by the median expression level of DOCK1. Results: High DOCK1 expression was associated with older age (P=0.019), wild-type CEBPA (P=0.002), IDH1/2 mutations (P=0.010) and RUNX1 mutation (P=0.005). Univariate analyses showed that DOCK1 ^high and RUNX1 mutation were associated with shorter OS (P<0.001, P=0.024). Multivariate analysis confirmed the negative effect of high DOCK1 level on overall survival (P=0.010). Conclusion: Our results demonstrate that in AML patients who received allo-HSCT, high DOCK1 expression might have a persistent negative prognostic impact post-transplant.