An assessment of candidate genes to assist prognosis in gastric cancer

McFarlane, Michael; Brettschneider, Julia; Gelsthorpe, Adrian; James, Sean; Snead, David; Gopalakrishnan, Kishore; Mehenna, Hisham; Jankowski, Janusz A.; Arasaradnam, Ramesh P.; Nwokolo, Chuka U.

doi:10.21037/jgo.2018.01.05

Cited by 7 publications

(6 citation statements)

References 16 publications

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“…Recent studies have found that BCAS1 is highly expressed in the brain, especially in oligodendrocytes, so its name is now approved as “brain-enriched myelin-associated protein 1” ( Fard et al, 2017 ). For cancer patients, the expression level of BCAS1 affects prognosis variously among different tumor types ( McFarlane et al, 2018 ; Zhang et al, 2019 ). Even BCAS1 is associated with drug resistance in cancer patients during treatment ( Jing et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Establishment of a Novel Combined Nomogram for Predicting the Risk of Progression Related to Castration Resistance in Patients With Prostate Cancer

Shi

et al. 2022

Front. Genet.

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Background: The emergence of castration resistance is fatal for patients with prostate cancer (PCa); however, there is still a lack of effective means to detect the early progression. In this study, a novel combined nomogram was established to predict the risk of progression related to castration resistance.Methods: The castration-resistant prostate cancer (CRPC)-related differentially expressed genes (DEGs) were identified by R packages “limma” and “WGCNA” in GSE35988-GPL6480 and GSE70768-GPL10558, respectively. Relationships between DEGs and progression-free interval (PFI) were analyzed using the Kaplan–Meier method in TCGA PCa patients. A multigene signature was built by lasso-penalized Cox regression analysis, and assessed by the receiver operator characteristic (ROC) curve and Kaplan–Meier curve. Finally, the univariate and multivariate Cox regression analyses were used to establish a combined nomogram. The prognostic value of the nomogram was validated by concordance index (C-index), calibration plots, ROC curve, and decision curve analysis (DCA).Results: 15 CRPC-related DEGs were identified finally, of which 13 genes were significantly associated with PFI and used as the candidate genes for modeling. A two-gene (KIFC2 and BCAS1) signature was built to predict the risk of progression. The ROC curve indicated that 5-year area under curve (AUC) in the training, testing, and whole TCGA dataset was 0.722, 0.739, and 0.731, respectively. Patients with high-risk scores were significantly associated with poorer PFI (p < 0.0001). A novel combined nomogram was successfully established for individualized prediction integrating with T stage, Gleason score, and risk score. While the 1-year, 3-year, and 5-year AUC were 0.76, 0.761, and 0.762, respectively, the good prognostic value of the nomogram was also validated by the C-index (0.734), calibration plots, and DCA.Conclusion: The combined nomogram can be used to predict the individualized risk of progression related to castration resistance for PCa patients and has been preliminarily verified to have good predictive ability.

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Section: Discussionmentioning

confidence: 99%

Establishment of a Novel Combined Nomogram for Predicting the Risk of Progression Related to Castration Resistance in Patients With Prostate Cancer

Shi

et al. 2022

Front. Genet.

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“…Heat shock protein 90 (HSP90) is overexpressed in many malignant tumours, and members of the HSP90 gene family are essential for cell cycle regulation, survival, and apoptosis. Studies have shown that the expression of HSP90AA1 is associated with poor prognosis in GC 47 , 48 . STAT3, a key transcription factor in tumorigenesis, focuses on multiple signalling pathways, such as cell proliferation, carcinogenesis, and apoptosis, which can promote the growth, proliferation, angiogenesis, metastasis, and immune response of tumour cells 49 , 50 .…”

Section: Discussionmentioning

confidence: 99%

Study of the active ingredients and mechanism of Sparganii rhizoma in gastric cancer based on HPLC-Q-TOF–MS/MS and network pharmacology

Zheng

Fang

et al. 2021

Sci Rep

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Sparganii rhizoma (SL) has potential therapeutic effects on gastric cancer (GC), but its main active ingredients and possible anticancer mechanism are still unclear. In this study, we used HPLC-Q-TOF–MS/MS to comprehensively analyse the chemical components of the aqueous extract of SL. On this basis, a network pharmacology method incorporating target prediction, gene function annotation, and molecular docking was performed to analyse the identified compounds, thereby determining the main active ingredients and hub genes of SL in the treatment of GC. Finally, the mRNA and protein expression levels of the hub genes of GC patients were further analysed by the Oncomine, GEPIA, and HPA databases. A total of 41 compounds were identified from the aqueous extract of SL. Through network analysis, we identified seven main active ingredients and ten hub genes: acacetin, sanleng acid, ferulic acid, methyl 3,6-dihydroxy-2-[(2-hydroxyphenyl) ethynyl]benzoate, caffeic acid, adenine nucleoside, azelaic acid and PIK3R1, PIK3CA, SRC, MAPK1, AKT1, HSP90AA1, HRAS, STAT3, FYN, and RHOA. The results indicated that SL might play a role in GC treatment by controlling the PI3K-Akt and other signalling pathways to regulate biological processes such as proliferation, apoptosis, migration, and angiogenesis in tumour cells. In conclusion, this study used HPLC-Q-TOF–MS/MS combined with a network pharmacology approach to provide an essential reference for identifying the chemical components of SL and its mechanism of action in the treatment of GC.

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“…Lastly, in e-CSCs, BCAS1 (Breast carcinoma-amplified sequence-1) protein expression was up-regulated, by nearly 120-fold [13]. BCAS1 over-expression [17] is functionally associated with “stemness” [18], a more aggressive cancer cell phenotype [19] and Tamoxifen-resistance [20,21]. MCF7-TAMR cells, which were chronically selected for Tamoxifen-resistance, by including Tamoxifen in their tissue culture media, show a >50-fold increase in BCAS1 protein expression, promoting increased ATP production [21].…”

Section: Hallmarks: Cancer Cell Of Origin Vs E-cscsmentioning

confidence: 99%

Hallmarks of the cancer cell of origin: Comparisons with “energetic” cancer stem cells (e-CSCs)

Sotgia

Fiorillo

Lisanti

2019

Aging

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Here, we discuss the expected hallmark(s) of the cancer cell of origin and how this may be related to a new tumor cell phenotype, namely “energetic” cancer stem cells (e-CSCs). e-CSCs show many features that would be characteristic of the cancer cell of origin, including the over-expression of p21-WAF (CDKN1A), a key marker of senescence. It is tempting to speculate that the cancer cell of origin and e-CSCs are closely related entities. e-CSCs possess a hybrid phenotype, sharing key hallmarks of senescence, “stemness” and cancer. e-CSCs are hyper-proliferative and have elevated mitochondrial metabolism, with an NRF2-mediated anti-oxidant response signature, including glutaredoxin (GLRX) and ALDH3A1 over-expression, possibly related to their escape from senescence. Finally, in e-CSCs, BCAS1 (Breast carcinoma-amplified sequence-1) protein expression was up-regulated by >100-fold. BCAS1 is a candidate oncogene associated with “stemness” and aggressive oncogenic behavior, such as Tamoxifen resistance.

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An assessment of candidate genes to assist prognosis in gastric cancer

Cited by 7 publications

References 16 publications

Establishment of a Novel Combined Nomogram for Predicting the Risk of Progression Related to Castration Resistance in Patients With Prostate Cancer

Establishment of a Novel Combined Nomogram for Predicting the Risk of Progression Related to Castration Resistance in Patients With Prostate Cancer

Study of the active ingredients and mechanism of Sparganii rhizoma in gastric cancer based on HPLC-Q-TOF–MS/MS and network pharmacology

Hallmarks of the cancer cell of origin: Comparisons with “energetic” cancer stem cells (e-CSCs)

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