Biological Roles and Therapeutic Applications of IDH2 Mutations in Human Cancer

Guo, Jiahao; Zhang, Ruyue; Yang, Zhe; Duan, Zhenfeng; Yin, De-Tao; Zhou, Yubing

doi:10.3389/fonc.2021.644857

Cited by 19 publications

(15 citation statements)

References 90 publications

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“…It is an important enzyme of the tricarboxylic acid cycle, whose mutated genes are associated with several tumors. Targeted drugs have been developed for these mutations and are being studied [20]. Once again, these drugs are not approved in case of gene CNV, nor in breast cancer.…”

Section: Resultsmentioning

confidence: 99%

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Next-Generation Sequencing of Breast Cancer in the Neoadjuvant Setting

Mesquita,

Ferro,

Machado

et al. 2023

Pathobiology

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Introduction: Many patients with locally advanced breast cancer are proposed to neoadjuvant chemotherapy (NAT) before surgery. Only some of them achieve a pathological complete response (pCR). The determination of gene somatic alterations using next-generation sequencing (NGS) in the non-pCR tumors is important, in order to identify potential opportunities of treatment for the patients, if targeted therapies are available. Methods: Breast cancer tissue samples of 31 patients, collected before NAT, were analyzed by NGS using the Oncomine™ Comprehensive Assay Plus (OCA-Plus) panel. Results: Twelve patients achieved pCR after NAT. ERBB2 gene alterations were the most frequent in this cohort of pCR patients, followed by BRCA 1 and 2, MYC, TP53, PIK3CA, and MET alterations. Tumors that did not achieve a pCR were mainly triple negative. In this subgroup some BRCA 1 and 2 and PIK3CA gene alterations were identified, as well as TP53 mutations. The NGS panel employed in this study also allowed for the determination of tumor mutation burden (TMB). Conclusion: This study showcases the significance of employing comprehensive genomic testing in breast cancer cases, primarily due to the scarcity of specific target assays. The detection of somatic mutations, coupled with the availability of targeted therapies, holds promise as a potential therapeutic avenue to enhance tumor response rates during NAT, or as a complementary treatment following surgery. Moreover, evaluating the TMB in non-pCR samples could serve as a valuable criterion for selecting patients suitable for immunotherapy. Further exploration through clinical trials is imperative to investigate these prospects.

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Section: Resultsmentioning

confidence: 99%

“…Pathobiology 2024;91:114-120 DOI: 10.1159/000533810 drugs have been developed for these mutations and are being studied [20]. Once again, these drugs are not approved in case of gene CNV, nor in breast cancer.…”

Section: Ngs In Breast Cancermentioning

confidence: 99%

Next-Generation Sequencing of Breast Cancer in the Neoadjuvant Setting

Mesquita,

Ferro,

Machado

et al. 2023

Pathobiology

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“…In our system, the reduction of TGFB1 expression via MM might be related to increased stiffness of the culture due to the upregulation of fibrogenic genes and culturing in collagen gel. Recently, Bronsard et al generated a 3D multicellular liver organoid using HepaRG cells, primary human macrophages and LX-2 cells, aiming to mimic MASLD and investigate drug discovery and toxicology [47] . Using this system, they were able to improve in vitro detection of drugs likely to be toxic in fatty liver [47] .…”

Section: Discussionmentioning

confidence: 99%

MASLD-mimicking microenvironment drives an aggressive phenotype and represses IDH2 expression in hepatocellular carcinoma

Korhan,

Bağırsakçı,

Islakoğlu

et al. 2024

Hepatoma Res

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Aim: Hepatocellular carcinoma (HCC) in patients with Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly NAFLD) is expected to be a significant public health issue in the near future. Therefore, understanding the tumor microenvironment interactions in MASLD-induced HCC is crucial, and the development of relevant preclinical models is needed. Hence, we aimed to determine the effects of a MASLD-mimicking microenvironment (ME) on the aggressiveness of HCC cells and identify target genes that drive HCC by developing a 3D-in vitro co-culture system. Methods: A 3D co-culture system mimicking the MASLD-ME was created with LX-2 liver stellate cells embedded in 3D collagen gel in the lower and SNU-449 HCC cells on the upper parts of Boyden chambers, and cells were grown in an optimized metabolic medium (MM). The effects of NAFLD-ME on motility, sphere formation, proliferation, and cell cycle of SNU-449 cells were tested by Boyden chamber, 3D sphere formation, XTT, and Flow cytometry, respectively. The protein expression/activation profiles of motile SNU-449 cells that passed the membrane toward NAFLD-ME or control condition were investigated using a multiplex protein profiling system DigiWest and confirmed with RT-PCR, WB, and Flow cytometry. IDH2 levels were examined in primary human HCC and adjacent liver tissues by IHC and in TCGA and CPTAC cohorts by bioinformatics tools. Results: MM treatment increased fat accumulation, motility, and spheroid formation of both SNU-449 and LX-2 cells. MASLD-ME induced activation of LX2 cells, leading to the formation of bigger colonies with many intrusions compared to related controls. DigiWest analysis showed that metabolism-related proteins such as IDH2 were the most affected molecules in SNU-449 cells that migrated toward the MASLD-ME compared to those that migrated toward the control condition. Downregulation of IDH2 expression was confirmed in SNU-449 cells grown in MASLD-ME, in primary HCC tumor samples by IHC, and in HCC patient cohorts by bioinformatics analysis. Conclusion: This study reports the potential involvement of MASLD-ME in the downregulation of IDH2 expression and promoted motility and colonization capacity of HCC cells. The 3D MASLD model presented in this study may be useful in investigating the mechanistic roles of MASLD-ME in HCC.

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“…It was consistent with our conclusion in this study. Isocitrate dehydrogenase 2 (IDH2) is a member of the IDH family which is a key component of the tricarboxylic acid cycle [ 38 , 39 ]. It was always reported as oncogene and played an important role in the biological mechanisms and progression in multiple tumor types [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of potential diagnostic and prognostic biomarkers for papillary thyroid microcarcinoma (PTMC) based on TMT-labeled LC–MS/MS and machine learning

Ran

et al. 2022

J Endocrinol Invest

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Objectives To explore the molecular mechanisms underlying aggressive progression of papillary thyroid microcarcinoma and identify potential biomarkers. Methods Samples were collected and sequenced using tandem mass tag-labeled liquid chromatography–tandem mass spectrometry. Differentially expressed proteins (DEPs) were identified and further analyzed using Mfuzz and protein–protein interaction analysis (PPI). Parallel reaction monitoring (PRM) and immunohistochemistry (IHC) were performed to validate the DEPs. Results Five thousand, two hundred and three DEPs were identified and quantified from the tumor/normal comparison group or the N1/N0 comparison group. Mfuzz analysis showed that clusters of DEPs were enriched according to progressive status, followed by normal tissue, tumors without lymphatic metastases, and tumors with lymphatic metastases. Analysis of PPI revealed that DEPs interacted with and were enriched in the following metabolic pathways: apoptosis, tricarboxylic acid cycle, PI3K-Akt pathway, cholesterol metabolism, pyruvate metabolism, and thyroid hormone synthesis. In addition, 18 of the 20 target proteins were successfully validated with PRM and IHC in another 20 paired validation samples. Based on machine learning, the five proteins that showed the best performance in discriminating between tumor and normal nodules were PDLIM4, ANXA1, PKM, NPC2, and LMNA. FN1 performed well in discriminating between patients with lymph node metastases (N1) and N0 with an AUC of 0.690. Finally, five validated DEPs showed a potential prognostic role after examining The Cancer Genome Atlas database: FN1, IDH2, VDAC1, FABP4, and TG. Accordingly, a nomogram was constructed whose concordance index was 0.685 (confidence interval: 0.645–0.726). Conclusions PDLIM4, ANXA1, PKM, NPC2, LMNA, and FN1 are potential diagnostic biomarkers. The five-protein nomogram could be a prognostic biomarker.

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Biological Roles and Therapeutic Applications of IDH2 Mutations in Human Cancer

Cited by 19 publications

References 90 publications

Next-Generation Sequencing of Breast Cancer in the Neoadjuvant Setting

Next-Generation Sequencing of Breast Cancer in the Neoadjuvant Setting

MASLD-mimicking microenvironment drives an aggressive phenotype and represses IDH2 expression in hepatocellular carcinoma

Identification of potential diagnostic and prognostic biomarkers for papillary thyroid microcarcinoma (PTMC) based on TMT-labeled LC–MS/MS and machine learning

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