<i>miR-122-5p</i> as a novel biomarker for alpha-fetoprotein-producing gastric cancer

Maruyama, Suguru; Furuya, Shinichi; Shiraishi, Kensuke; Shimizu, Hiroki; Akaike, Hidenori; Hosomura, Naohiro; Kawaguchi, Yoshihiko; Amemiya, Hidetake; Kawaida, Hiromichi; Sudo, Makoto; Inoue, Satoshi; Kono, Hiroshi; Ichikawa, Daisuke

doi:10.4251/wjgo.v10.i10.344

Cited by 20 publications

(18 citation statements)

References 27 publications

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“…In addition, miR-122 promotes aggression and epithelial-mesenchymal transition in TNBC [ 57 ] and cell survival in radio-resistance cells [ 58 ]. High plasma miR-122 levels have been detected in AFP-producing gastric cancer [ 59 ].…”

Section: Discussionmentioning

confidence: 99%

Machine Learning-Based Ensemble Recursive Feature Selection of Circulating miRNAs for Cancer Tumor Classification

Lopez-Rincon

Mendoza‐Maldonado

Martínez‐Archundia

et al. 2020

Cancers

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Circulating microRNAs (miRNA) are small noncoding RNA molecules that can be detected in bodily fluids without the need for major invasive procedures on patients. miRNAs have shown great promise as biomarkers for tumors to both assess their presence and to predict their type and subtype. Recently, thanks to the availability of miRNAs datasets, machine learning techniques have been successfully applied to tumor classification. The results, however, are difficult to assess and interpret by medical experts because the algorithms exploit information from thousands of miRNAs. In this work, we propose a novel technique that aims at reducing the necessary information to the smallest possible set of circulating miRNAs. The dimensionality reduction achieved reflects a very important first step in a potential, clinically actionable, circulating miRNA-based precision medicine pipeline. While it is currently under discussion whether this first step can be taken, we demonstrate here that it is possible to perform classification tasks by exploiting a recursive feature elimination procedure that integrates a heterogeneous ensemble of high-quality, state-of-the-art classifiers on circulating miRNAs. Heterogeneous ensembles can compensate inherent biases of classifiers by using different classification algorithms. Selecting features then further eliminates biases emerging from using data from different studies or batches, yielding more robust and reliable outcomes. The proposed approach is first tested on a tumor classification problem in order to separate 10 different types of cancer, with samples collected over 10 different clinical trials, and later is assessed on a cancer subtype classification task, with the aim to distinguish triple negative breast cancer from other subtypes of breast cancer. Overall, the presented methodology proves to be effective and compares favorably to other state-of-the-art feature selection methods.

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Section: Discussionmentioning

confidence: 99%

Machine Learning-Based Ensemble Recursive Feature Selection of Circulating miRNAs for Cancer Tumor Classification

Lopez-Rincon

Mendoza‐Maldonado

Martínez‐Archundia

et al. 2020

Cancers

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“…Although α-fetoprotein-producing gastric cancer (AFPGC) has been recognized as an aggressive gastric cancer (11,12), to the best of our knowledge no comprehensive molecular analysis has been reported for this uncommon subtype. We previously identified that miR-122-5p was significantly highly expressed in AFPGC tissues and could be a useful plasma biomarker in patients (9). Moreover, we revealed that miR-122-5p exhibited a strong correlation with malignant potential in clinical settings (9).…”

Section: Discussionmentioning

confidence: 81%

“…Therefore, we hypothesized that some specific miRNAs may play crucial roles in AFPGC. Previously, we demonstrated that miR-122-5p was significantly higher in AFPGC tissues and that the plasma expression level may be a useful biomarker in patients with AFPGC (9). In the present study, we examined the biological function of miR-122-5p and the molecular mechanism underlying tumor progression in AFPGC.…”

Section: Introductionmentioning

confidence: 84%

“…We previously identified that miR-122-5p was significantly highly expressed in AFPGC tissues and could be a useful plasma biomarker in patients (9). Moreover, we revealed that miR-122-5p exhibited a strong correlation with malignant potential in clinical settings (9). In the present study, we confirmed that the expression level of miR-122-5p was significantly increased in the AFPGC cell line than in common gastric cancer (GC) cell lines, and also inhibition of miR-122-5p significantly reduced AFP levels in the AFPGC cell line.…”

Section: Discussionmentioning

confidence: 99%

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Inhibition of apoptosis by miR‑122‑5p in α‑fetoprotein‑producing gastric cancer

et al. 2019

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α-Fetoprotein (AFP)-producing gastric cancer (AFPGC) is recognized as one of the most aggressive tumors with subsequent poor prognosis compared with common gastric cancer (GC) subtypes. However, the molecular mechanism remains to be elucidated. We previously identified that miR-122-5p could be a useful biomarker in AFPGC patients. We examined herein the biological function of miR-122-5p and the molecular mechanism underlying tumor progression in AFPGC. We used the AFPGC cell line (FU97) and miR-122-5p inhibitor to examine the function of miR-122-5p. Moreover, we investigated the possible targets of miR-122-5p. The expression level of miR-122-5p was significantly increased in the FU97 cell line than in common GC cell lines. Also, suppression of miR-122-5p significantly reduced AFP levels and proliferation in AFPGC through an induction of apoptosis. Western blotting revealed that the expression of anti-apoptotic protein (Bcl-2) was decreased and that of pro-apoptotic protein (caspase-3) was increased in miR-122-5p suppression of FU97. Moreover, we revealed that FOXO3 was an important target of miR-122-5p in AFPGC, which inhibited apoptosis and subsequently manifested aggressiveness. In conclusion, miR-122-5p inhibited apoptosis and facilitated tumor progression by targeting FOXO3 in AFPGC, which indicates the possibility of miR-122-5p as a potential therapeutic target in AFPGC.

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“…Furthermore, the association between miR-100-3p and ERK/AKT and Bax-Bcl2-Cas-pase3 pathways was investigated, and the results showed that over-expression of miR-100-3p inhibited the ERK/ AKT pathway and activated the Bax-Bcl2-Caspase3 pathway, whereas knockdown of miR-100-3p activated the ERK/AKT pathway and inhibited the Bax-Bcl2-Caspase3 pathway, likely via BMPR2. miRNA dysregulation has been reported to be valuable for GC diagnosis [30][31][32]. Recently, several studies even demonstrated the potential of miRNA in GC diagnosis and treatment [33,34].…”

Section: Discussionmentioning

confidence: 99%

miR-100-3p inhibits cell proliferation and induces apoptosis in human gastric cancer through targeting to BMPR2

et al. 2019

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Background: miR-100 has been reported to closely associate with gastric cancer (GC) initiation and progression. However, the underlying mechanism of miR-100-3p in GC is still largely unclear. In this study, we intend to study how miR-100-3p regulates GC malignancy. Methods: The expression levels of miR-100-3p in vitro (GES-1 and GC cell lines) and in vivo (cancerous and normal gastric tissues) were examined by quantitative real-time PCR (qRT-PCR). MTT and PE/Annexin V analyses were responsible for measurement of the effects of miR-100-3p on GC cell proliferation and apoptosis. Transwell assay with or without matrigel was used to examine the capacity of migration and invasion in GC cells. The interaction of miR-100-3p with bone morphogenetic protein receptor 2 (BMPR2) was confirmed through transcriptomics analysis and luciferase reporter assay. qRT-PCR and Western blot analyses were applied to determine the expression of ERK/AKT and Bax/Bcl2/Caspase3, which were responsible for the dysfunction of miR-100-3p. Results: miR-100-3p was down-regulated in GC cell lines and cancerous tissues, and was negatively correlated with BMPR2. Loss of miR-100-3p promoted tumor growth and BMPR2 expression. Consistently, the effects of miR-100-3p inhibition on GC cells were partially neutralized by knockdown of BMPR2. Over-expression of miR-100-3p simultaneously inhibited tumor growth and down-regulated BMPR2 expression. Consistently, over-expression of BMPR2 partially neutralized the effects of miR-100-3p over-expression. Further study demonstrated that BMPR2 mediated the effects downstream of miR-100-3p, which might indirectly regulate ERK/AKT and Bax/Bcl2/Caspase3 signaling pathways. Conclusion: miR-100-3p acted as a tumor-suppressor miRNA that down-regulated BMPR2, which consequently inhibited the ERK/AKT signaling and activated Bax/Bcl2/Caspase3 signaling. This finding provided novel insights into GC and could contribute to identify a new diagnostic and therapeutic target.

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miR-122-5p as a novel biomarker for alpha-fetoprotein-producing gastric cancer

Cited by 20 publications

References 27 publications

Machine Learning-Based Ensemble Recursive Feature Selection of Circulating miRNAs for Cancer Tumor Classification

Machine Learning-Based Ensemble Recursive Feature Selection of Circulating miRNAs for Cancer Tumor Classification

Inhibition of apoptosis by miR‑122‑5p in α‑fetoprotein‑producing gastric cancer

miR-100-3p inhibits cell proliferation and induces apoptosis in human gastric cancer through targeting to BMPR2

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