Comprehensive investigation of the clinical significance of long non-coding RNA HOXA-AS2 in acute myeloid leukemia using genome-wide RNA sequencing dataset

Huang, Rui; Liao, Xiwen; Wang, Xiangkun; Li, Qiaochuan

doi:10.7150/jca.48045

Cited by 8 publications

(5 citation statements)

References 68 publications

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“…Temozolomide [48] is lower IC50 score in subtype 2, and PCI − 34051 [49], Carmustine [50], KRAS (G12C) Inhibitor-12 [51] is higher IC50 score in subtype2. KRAS (G12C) Inhibitor-12 [51] is higher IC50 score in subtype2.…”

Section: Discussionmentioning

confidence: 99%

Machine learning-based integration develops multi regulated cell death-related signatures for improving outcomes and immune response in acute myeloid leukemia

Li,

Zhang,

2023

Preprint

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Acute myeloid leukemia (AML) presents an unpredictable and complex prognosis. Researchers have been exploring different ways to determine the death of cancer cells, including various forms of regulated cell death such as apoptosis, autophagy, cuproptosis, disulfidptosis, ferroptosis, necroptosis, panoptosis, and pyrotosis. However, there have been limited studies on combining these cell death modalities in AML. This study aimed to identify clinically relevant molecular classification of AML based on genes related to multiple programmed cell death signaling pathways. Machine learning techniques were used to identify these subtypes and provide guidance on medication for each subtype using transcriptome data. The subtypes differed in immune and drug response. A robust prognostic model MPCDPG was developed based on gene pairs and validated in multiple test sets. In conclusion, this study identified three clinically relevant subtypes of AML and developed a reliable prognostic model based on gene pairs regulated cell death-related genes.

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Section: Discussionmentioning

confidence: 99%

Machine learning-based integration develops multi regulated cell death-related signatures for improving outcomes and immune response in acute myeloid leukemia

Li,

Zhang,

2023

Preprint

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“…AGAP2‐AS1 facilitates the occurrence and progression of certain tumors, including intrahepatic cholangiocarcinoma, breast cancer, and lung cancer, and its upregulation is linked to a poor prognosis 38–40 . HOXA‐AS2 is upregulated in cervical cancer, acute myeloid leukemia, and hepatoblastoma, promoting malignant biological behavior 41–43 . AC131097.4 is related to genomic instability of LGG, and its high expression suggests the possibility of a wild‐type IDH1 gene 44 .…”

Section: Discussionmentioning

confidence: 99%

“… 38 , 39 , 40 HOXA‐AS2 is upregulated in cervical cancer, acute myeloid leukemia, and hepatoblastoma, promoting malignant biological behavior. 41 , 42 , 43 AC131097.4 is related to genomic instability of LGG, and its high expression suggests the possibility of a wild‐type IDH1 gene. 44 DRAIC is a suppressor in gastric and colorectal cancer cells.…”

Section: Discussionmentioning

confidence: 99%

A TGF‐β signaling‐related lncRNA signature for prediction of glioma prognosis, immune microenvironment, and immunotherapy response

Duan,

Yang,

Liu

et al. 2023

CNS Neurosci Ther

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AimsThe dysregulation of TGF‐β signaling is a crucial pathophysiological process in tumorigenesis and progression. LncRNAs have diverse biological functions and are significant participants in the regulation of tumor signaling pathways. However, the clinical value of lncRNAs related to TGF‐β signaling in glioma is currently unclear.MethodsData on glioma's RNA‐seq transcriptome, somatic mutation, DNA methylation data, and clinicopathological information were derived from the CGGA and TCGA databases. A prognostic lncRNA signature was constructed by Cox and LASSO regression analyses. TIMER2.0 database was utilized to deduce immune infiltration characteristics. “ELMER v.2” was used to reconstruct TF‐methylation‐gene regulatory network. Immunotherapy and chemotherapy response predictions were implemented by the TIDE algorithm and GDSC database, respectively. In vitro and in vivo experiments were conducted to verify the results and clarify the regulatory mechanism of lncRNA.ResultsIn glioma, a TGF‐β signaling‐related 15‐lncRNA signature was constructed, including AC010173.1, HOXA‐AS2, AC074286.1, AL592424.1, DRAIC, HOXC13‐AS, AC007938.1, AC010729.1, AC013472.3, AC093895.1, AC131097.4, AL606970.4, HOXC‐AS1, AGAP2‐AS1, and AC002456.1. This signature proved to be a reliable prognostic tool, with high risk indicating an unfavorable prognosis and being linked to malignant clinicopathological and genomic mutation traits. Risk levels were associated with different immune infiltration landscapes, where high risk was indicative of high levels of macrophage infiltration. In addition, high risk also suggested better immunotherapy and chemotherapy response. cg05987823 was an important methylation site in glioma progression, and AP‐1 transcription factor family participated in the regulation of signature lncRNA expression. AGAP2‐AS1 knockdown in in vitro and in vivo experiments inhibited the proliferation, migration, and invasion of glioma cells, as well as the growth of glioma, by downregulating the expression levels of NF‐κB and ERK 1/2 in the TGF‐β signaling pathway.ConclusionsA prognostic lncRNA signature of TGF‐β signaling was established in glioma, which can be used for prognostic judgment, immune infiltration status inference, and immunotherapy response prediction. AGAP2‐AS1 plays an important role in glioma progression.

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“…We excluded patients with no prognostic or RNA sequencing data, and 130 patients will be included in the follow-up study. The patient inclusion and exclusion criteria can be found in our previous study 56 . The data used in this study met the requirements of TCGA.…”

Section: Methodsmentioning

confidence: 99%

Expression signature of ten small nuclear RNAs serves as novel biomarker for prognosis prediction of acute myeloid leukemia

Zhang,

Huang,

Lai

2023

Sci Rep

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This study aimed to screen for small nuclear RNAs (snRNAs) associated with the prognosis of acute myeloid leukemia (AML) by using The Cancer Genome Atlas (TCGA) whole-transcriptome sequencing dataset. A total of 130 AML patients from TCGA cohort with complete prognostic information and transcriptome data were enrolled in the current study. Comprehensive survival and functional enrichment analyses were performed to explore the prognostic value and potential biological functions of prognostic snRNAs in AML patients. In the current study, we screened 72 snRNAs that were notably associated with the clinical outcome of AML and developed an expression signature consist of ten snRNAs, that can be accurately applied to assess the overall survival of AML patients. Functional mechanism analysis revealed that this expression signature may be strongly linked to some classical tumor-associated pathways, such as Notch and Wnt pathways, as well as being closely related to B and T cell receptor pathways. Furthermore, we screened six compounds (chicago sky blue 6 B, 5230742, clorsulon, nefopam, nicardipine, and streptomycin) that may serve as targeted therapeutic drugs for AML using connectivity maps. Tumor immunoassays indicated significant differences in the immune microenvironment of the bone marrow tissue between high-risk and low-risk AML patients. Immune infiltration analysis also revealed significant differences in the abundance of multiple immune cells in the bone marrow of the two groups of AML patients groups. In conclusion, our results revealed a novel prognostic expression signature of AML consisting of ten snRNAs, and we conducted a preliminary exploration of its potential biological functions and tumor immunity.

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Comprehensive investigation of the clinical significance of long non-coding RNA HOXA-AS2 in acute myeloid leukemia using genome-wide RNA sequencing dataset

Cited by 8 publications

References 68 publications

Machine learning-based integration develops multi regulated cell death-related signatures for improving outcomes and immune response in acute myeloid leukemia

Machine learning-based integration develops multi regulated cell death-related signatures for improving outcomes and immune response in acute myeloid leukemia

A TGF‐β signaling‐related lncRNA signature for prediction of glioma prognosis, immune microenvironment, and immunotherapy response

Expression signature of ten small nuclear RNAs serves as novel biomarker for prognosis prediction of acute myeloid leukemia

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