High Expression of CLEC11A Predicts Favorable Prognosis in Acute Myeloid Leukemia

Yin, Chengliang; Zhang, Junyan; Guan, Wei; Dou, Liping; Liu, Yuchen; Shen, Ming; Jia, Xiaodong; Xu, Lei; Wu, Rilige; Li, Yan

doi:10.3389/fonc.2021.608932

Cited by 15 publications

(17 citation statements)

References 41 publications

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“…Although the biological function of CLEC11A has not been revealed in CRC, several studies have reported that CLEC11A is significantly associated with the clinical outcomes of cancer patients. [24,25] The prognostic value of CYRAB has been demonstrated in CRC. [26,27] In addition, CYRAB can promote the invasion and metastasis of CRC via the regulation of the epithelial-mesenchymal transition.…”

Section: Discussionmentioning

confidence: 99%

CAF signature predicts the prognosis of colorectal cancer patients: A retrospective study based on bulk RNA sequencing and single-cell RNA sequencing data

Liang

Ji²,

Feng³

et al. 2023

Medicine

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The incidence rate and mortality rate of colorectal cancer (CRC) ranks third and second globally. Cancer-associated fibroblasts (CAFs) are the major constituent of the stromal cells in the tumor microenvironment (TME) and are closely associated with patients’ prognoses. Our study intended to establish a prognostic model for CRC using hallmark genes of CAFs. The expression values of genes and clinicopathological characteristics of patients were enrolled from the cancer genome atlas database as well as the gene expression omnibus database. The single-cell RNA sequencing data were collected and analyzed in the deeply integrated human single-cell omics database and cancer single-cell expression map databases. The ESTIMATE algorithm was applied to access the infiltration levels of immune and stromal cells. The prognostic genes were selected by the Cox regression analysis and the prognostic signature was constructed by the least absolute shrinkage and selection operator algorithm. gene set enrichment analysis was used to explore the enriched gene sets. In this study, based on bulk RNA sequencing and single-cell RNA sequencing data, and we found that more CAFs were infiltrated in the tumor microenvironment and consisted of 3 subtypes. Then we constructed a prognostic signature for CRC using hallmark genes of CAFs and proved that this signature exhibited high values to predict the overall survival of CRC patients in independent training and validating cohorts. Besides, function enrichment analysis revealed that our prognostic model was significantly associated with immune regulation. Further analysis showed that the infiltrated levels of tumor-suppressing immune cells and the expression of higher immune checkpoint genes in CRC tissues were higher in patients with high-risk scores. Furthermore, immunohistochemistry analysis exhibited that these genes in our prognostic signature were markedly upregulated in CRC tissues. We first constructed a signature based on CAFs hallmark genes to predict the survival of CRC patients and further revealed that the tumor-suppressing microenvironment and dysregulated immune checkpoint genes in CRC tissues were partly responsible for the poor prognosis of patients.

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Section: Discussionmentioning

confidence: 99%

CAF signature predicts the prognosis of colorectal cancer patients: A retrospective study based on bulk RNA sequencing and single-cell RNA sequencing data

Liang

Ji²,

Feng³

et al. 2023

Medicine

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“…Inhibition of CKLF1-related pathways can enhance the anti-tumor e cacy of cisplatin and reduce the nephrotoxicity induced by cisplatin [37,38]. Yin C et al found that CLEC11A was highly expressed in AML and associated with a favorable outcome [39]. High levels of CLEC11A DNA methylation were found in patients with poor prognosis, and DNA methylation affected gene expression, suggesting that inhibition of DNA methylation may be used to treat AML [40].…”

Section: Discussionmentioning

confidence: 99%

The potential novel immune-related prognostic factors for acute myeloid leukemia

Zheng

et al. 2022

Preprint

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Background The pathological progression in acute myeloid leukemia (AML) was significantly affected by the immune microenvironment of bone marrow, where the immune-related genes (IRGs) and immune cells are involved in the prognosis of the disease. Studying immune-related components provide new ideas for treatment. Methods The transcriptome data and clinical information of 151 TCGA-LAML and 337 GTEx-whole-blood cohorts were downloaded from the UCSC Xena database. The IRGs were obtained from ImmPort database. Differentially expressed IRGs (DEIGs) were obtained from differentially expressed genes (DEGs). A prognostic model was constructed by COX regression analysis and verified by Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves in the training and validation cohorts (GEO37642 cohort). The relationship between gene expression level and prognosis was analyzed by K-M method. The independent prognostic factors were screened by univariate and multivariate Cox regression analysis. Relative immune cell composition of AML and healthy samples was calculated using the CIBERSORT algorithm. Results Enrichment analysis revealed that the immune cells and immune-related biology functions participated in AML progression. A prognostic model containing eight genes was constructed. In the training and validation cohorts, the survival rate of the low-risk group was significantly higher than that of the high-risk group. The area under the curve (AUC) values of ROC curves were ≥ 0.7. Among the model, high expression of CANX (P = 0.012), CLEC11A (P = 0.016), and TRH (P = 1.256E-04) was associated with a higher survival rate, while high expression of IL3RA (P = 0.038), KIR2DS4 (P = 0.016), APOBEC3G (P = 1.426E-04), and CKLF (P = 0.015) was associated with lower survival rate. The CANX expression level may affect the sensitivity of some drugs. Age, karyotype, and risk score are independent prognostic factors for AML. The differential level of 17 immune cells was observed between the AML and healthy samples. The levels of Macrophages M1, T cells follicular helper, and T cells CD8 were positively correlated with survival rate. Discussions The prognostic model may be helpful in predicting patient outcomes and 7 IRGs and 3 immune cells may be potential biomarkers and immunotherapy targets for AML in the future.

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“…CLEC11A-expressing lung cancer cells have been shown to promote the growth of tumors in mice while inhibition of CLEC11A expression prevented tumor growth [ 12 ]. Interestingly, Yin and colleagues recently reported that increased methylation of CLEC11A , corresponding to decreased gene and protein expression, led to poor survival in AML patients [ 13 ]. These conflicting reports indicate that further studies are needed to elucidate the role of CLEC11A in cancer, with specific attention to the role of methylation.…”

Section: Introductionmentioning

confidence: 99%

“…Survival rates incorporate many different factors: the age of patients, type of chemotherapy, stage of cancer, race, gender, and time from diagnosis to treatment [ 4 ]. While previous studies showed a relationship between CLEC11A and survival, these other factors were not considered specific to methylation of CLEC11A [ 12 , 13 ]. Therefore, the goal of this study was to examine the relationship between CLEC11A methylation, staging, genetic risk factors, and demographic data to determine whether CLEC11A can be used as a prognostic factor in AML patients.…”

Section: Introductionmentioning

confidence: 99%

CLEC11A methylation is correlated to AML subtypes and cytogenetic risk factors but not patient demographics

Swanson,

Rogowski,

Bishop

et al. 2024

PLoS ONE

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Acute myeloid leukemia (AML) is an aggressive and lethal cancer of the blood, which leads to the death of over 11,000 patients in the United States each year. Research on identifying, characterizing, and treating AML is crucial in the fight against this deadly disease. Recent studies have examined the role of CLEC11A in cancer, including AML. However, there have been conflicting reports related to tumor progression and survival. Because survival is based on a variety of factors, including classification of the tumor, genetic risk factors, and demographics, it is imperative that we determine what role CLEC11A may have in cancer survival. Therefore, utilizing data from the Genomic Data Commons, we analyzed CLEC11A methylation in 108 AML patients compared to FAB classification, cytogenetic risk factors, age, race, and gender. Our results show statistically significant correlations between methylation of CLEC11A and FAB classification as well as poor genetic risk factors. However, no difference was observed in CLEC11A methylation when compared to demographic data. Our results, matched with a known biological function of CLEC11A in early hematopoiesis, indicate that CLEC11A may be an important marker for AML diagnosis and prognosis and provide relevant data in the ongoing search for novel therapeutics to improve AML survival.

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High Expression of CLEC11A Predicts Favorable Prognosis in Acute Myeloid Leukemia

Cited by 15 publications

References 41 publications

CAF signature predicts the prognosis of colorectal cancer patients: A retrospective study based on bulk RNA sequencing and single-cell RNA sequencing data

CAF signature predicts the prognosis of colorectal cancer patients: A retrospective study based on bulk RNA sequencing and single-cell RNA sequencing data

The potential novel immune-related prognostic factors for acute myeloid leukemia

CLEC11A methylation is correlated to AML subtypes and cytogenetic risk factors but not patient demographics

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