Asparaginase‐like protein 1 expression in curettage independently predicts lymph node metastasis in endometrial carcinoma: a multicentre study

Fonnes, Tina; Trovik, Jone; Edqvist, Per‐Henrik; Fasmer, Kristine Eldevik; Marcickiewicz, Janusz; Tingulstad, Solveig; Staff, Anne Cathrine; Bjørge, Line; Amant, Frédéric; Haldorsen, Ingfrid S.; Werner, Henrica M.J.; Akslen, Lars A.; Tangen, Ingvild L.; Krakstad, Camilla

doi:10.1111/1471-0528.15403

Cited by 8 publications

(8 citation statements)

References 49 publications

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“…Notably, PHGDH and ASRGL1 expression were associated with four or more clinicopathologic features ( p < 0.05) (Figure S5F–O), which indicates that PHGDH and ASRGL1 promote the initiation and development of EC. Several studies reported that loss of ASRGL1 is an independent prognostic factor in endometrial cancer 24,25 . PHGDH has been reported to be a potential target in many cancers including breast cancer, 26 colorectal cancer, 27 and melanoma 28 .…”

Section: Resultsmentioning

confidence: 99%

“…ASRGL, has been reported to promote cell proliferation and suppress apoptosis in various tumors, including breast, ovarian, cervical, and EC 46 . In EC, it is shown to be a reliable negative prognostic biomarker that is related to overall survival, lymph‐node metastasis, and aggressive clinicopathologic features 24,25 . Interestingly, studies indicate the relationship of ASRGL1 expression with hormone receptor status, 46 which builds a link between glutamine and amino acid metabolism with hormone homeostasis, as EC is hormone‐dependent tumor.…”

Section: Discussionmentioning

confidence: 99%

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Glutamine and amino acid metabolism as a prognostic signature and therapeutic target in endometrial cancer

et al. 2023

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IntroductionEndometrial cancer (EC) is the most common female reproductive system cancer in developed countries with growing incidence and associated mortality, which may be due to the growing prevalence of obesity. Metabolism reprogramming including glucose, amino acid, and lipid remodeling is a hallmark of tumors. Glutamine metabolism has been reported to participate in tumor proliferation and development. This study aimed to develop a glutamine metabolism‐related prognostic model for EC and explore potential targets for cancer treatment.MethodTranscriptomic data and survival outcome of EC were retrieved from The Cancer Genome Atlas (TCGA). Differentially expressed genes related to glutamine metabolism were recognized and utilized to build a prognostic model by univariate and multivariate Cox regressions. The model was confirmed in the training, testing, and the entire cohort. A nomogram combing prognostic model and clinicopathologic features was established and tested. Moreover, we explored the effect of a key metabolic enzyme, PHGDH, on the biological behavior of EC cell lines and xenograft model.ResultsFive glutamine metabolism‐related genes, including PHGDH, OTC, ASRGL1, ASNS, and NR1H4, were involved in prognostic model construction. Kaplan–Meier curve suggested that patients recognized as high risk underwent inferior outcomes. The receiver operating characteristic (ROC) curve showed the model was sufficient to predict survival. Enrichment analysis recognized DNA replication and repair dysfunction in high‐risk patients whereas immune relevance analysis revealed low immune scores in the high‐risk group. Finally, a nomogram integrating the prognostic model and clinical factors was created and verified. Further, knockdown of PHGDH showed cell growth inhibition, increasing apoptosis, and reduced migration. Promisingly, NCT‐503, a PHGDH inhibitor, significantly repressed tumor growth in vivo (p = 0.0002).ConclusionOur work established and validated a glutamine metabolism‐related prognostic model that favorably evaluates the prognosis of EC patients. DNA replication and repair may be the crucial point that linked glutamine metabolism, amino acid metabolism, and EC progression. High‐risk patients stratified by the model may not be sufficient for immune therapy. PHGDH might be a crucial target that links serine metabolism, glutamine metabolism as well as EC progression.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Glutamine and amino acid metabolism as a prognostic signature and therapeutic target in endometrial cancer

et al. 2023

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“…AKR1B10 encodes a member of the aldo–keto reductase (AKR) 1B subfamily and exerts variable or even opposing roles in different tumor contexts [ 28 , 29 ]. ASRGL1 encodes the enzyme that catalyzes the hydrolysis of l -asparagine to l -aspartic acid and ammonia and plays a protective role in endometrial carcinoma [ 30 ]. ABCC2, ATP Binding Cassette Subfamily C Member 2, acts as a key transporter in support of cell energy transition and proliferation and was identified as a pro-oncogenic factor in colorectal cancer [ 31 ].…”

Section: Discussionmentioning

confidence: 99%

Metabolic classifications of renal cell carcinoma reveal intrinsic connections with clinical and immune characteristics

Chao

et al. 2023

J Transl Med

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Background Kidney cancer undergoes a dramatic metabolic shift and has demonstrated responsiveness to immunotherapeutic intervention. However, metabolic classification and the associations between metabolic alterations and immune infiltration in Renal cell carcinoma still remain elucidative. Methods Unsupervised consensus clustering was conducted on the TCGA cohorts for metabolic classification. GESA, mRNAsi, prognosis, clinical features, mutation load, immune infiltration and differentially expressed gene differences among different clusters were compared. The prognosis model and nomograms were constructed based on metabolic gene signatures and verified using external ICGC datasets. Immunohistochemical results from Human Protein Atlas database and Tongji hospital were used to validate gene expression levels in normal tissues and tumor samples. CCK8, apoptosis analysis, qPCR, subcutaneously implanted murine models and flowcytometry analysis were applied to investigate the roles of ACAA2 in tumor progression and anti-tumor immunity. Results Renal cell carcinoma was classified into 3 metabolic subclusters and the subcluster with low metabolic profiles displayed the poorest prognosis, highest invasiveness and AJCC grade, enhanced immune infiltration but suppressive immunophenotypes. ACAA2, ACAT1, ASRGL1, AKR1B10, ABCC2, ANGPTL4 were identified to construct the 6 gene-signature prognosis model and verified both internally and externally with ICGC cohorts. ACAA2 was demonstrated as a tumor suppressor and was associated with higher immune infiltration and elevated PD-1 expression of CD8+ T cells. Conclusions Our research proposed a new metabolic classification method for RCC and revealed intrinsic associations between metabolic phenotypes and immune profiles. The identified gene signatures might serve as key factors bridging tumor metabolism and tumor immunity and warrant further in-depth investigations.

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“…Furthermore, the high-risk IW4 group had worse outcome and a higher prevalence of LNM (53%), compared to the high-risk ESMO group (17%). [11,32,33], and a few have also incorporated preoperative imaging findings [34][35][36][37][38]. Reijnen et al have presented a Bayesian network (ENDORISK) that includes molecular and clinical biomarkers, including lymphadenopathy on imaging, yielding AUCs of 0.82-0.84 for predicting LNM [38].…”

Section: Discussionmentioning

confidence: 99%

Preoperative pelvic MRI and 2-[18F]FDG PET/CT for lymph node staging and prognostication in endometrial cancer—time to revisit current imaging guidelines?

et al. 2022

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Objective This study presents the diagnostic performance of four different preoperative imaging workups (IWs) for prediction of lymph node metastases (LNMs) in endometrial cancer (EC): pelvic MRI alone (IW1), MRI and [18F]FDG-PET/CT in all patients (IW2), MRI with selective [18F]FDG-PET/CT if high-risk preoperative histology (IW3), and MRI with selective [18F]FDG-PET/CT if MRI indicates FIGO stage ≥ 1B (IW4). Methods In 361 EC patients, preoperative staging parameters from both pelvic MRI and [18F]FDG-PET/CT were recorded. Area under receiver operating characteristic curves (ROC AUC) compared the diagnostic performance for the different imaging parameters and workups for predicting surgicopathological FIGO stage. Survival data were assessed using Kaplan-Meier estimator with log-rank test. Results MRI and [18F]FDG-PET/CT staging parameters yielded similar AUCs for predicting corresponding FIGO staging parameters in low-risk versus high-risk histology groups (p ≥ 0.16). The sensitivities, specificities, and AUCs for LNM prediction were as follows: IW1—33% [9/27], 95% [185/193], and 0.64; IW2—56% [15/27], 90% [174/193], and 0.73 (p = 0.04 vs. IW1); IW3—44% [12/27], 94% [181/193], and 0.69 (p = 0.13 vs. IW1); and IW4—52% [14/27], 91% [176/193], and 0.72 (p = 0.06 vs. IW1). IW3 and IW4 selected 34% [121/361] and 54% [194/361] to [18F]FDG-PET/CT, respectively. Employing IW4 identified three distinct patient risk groups that exhibited increasing FIGO stage (p < 0.001) and stepwise reductions in survival (p ≤ 0.002). Conclusion Selective [18F]FDG-PET/CT in patients with high-risk MRI findings yields better detection of LNM than MRI alone, and similar diagnostic performance to that of MRI and [18F]FDG-PET/CT in all. Key Points • Imaging by MRI and [18F]FDG PET/CT yields similar diagnostic performance in low- and high-risk histology groups for predicting central FIGO staging parameters. • Utilizing a stepwise imaging workup with MRI in all patients and [18F]FDG-PET/CT in selected patients based on MRI findings identifies preoperative risk groups exhibiting significantly different survival. • The proposed imaging workup selecting ~54% of the patients to [18F]FDG-PET/CT yield better detection of LNMs than MRI alone, and similar LNM detection to that of MRI and [18F]FDG-PET/CT in all.

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Asparaginase‐like protein 1 expression in curettage independently predicts lymph node metastasis in endometrial carcinoma: a multicentre study

Abstract: Low ASRGL1 expression in curettage predicts lymph node metastasis and poor survival in endometrial carcinoma.

Cited by 8 publications

References 49 publications

Glutamine and amino acid metabolism as a prognostic signature and therapeutic target in endometrial cancer

Glutamine and amino acid metabolism as a prognostic signature and therapeutic target in endometrial cancer

Metabolic classifications of renal cell carcinoma reveal intrinsic connections with clinical and immune characteristics

Preoperative pelvic MRI and 2-[18F]FDG PET/CT for lymph node staging and prognostication in endometrial cancer—time to revisit current imaging guidelines?

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