SMARCA4 promotes benign skin malignant transformation into melanoma through Adherens junction signal transduction

Liu, S.-R.; Yang, Xiaoyu; Qi, Ling; Zhu, Zhe; Ji, Yisheng

doi:10.1007/s12094-020-02453-0

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…The VEGF signaling pathway is a major regulator of angiogenesis and vascular permeability (35). These pathways are involved in tumorigenesis, progression, invasion, and metastasis (36)(37)(38)(39). The results indicated that the tumors were developing and metastasizing.…”

Section: Discussionmentioning

confidence: 99%

Leveraging various extracellular matrix levels to assess prognosis and sensitivity to immunotherapy in patients with ovarian cancer

et al. 2023

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BackgroundOvarian cancer (OC) is the fifth leading cause of cancer-related deaths among women. Late diagnosis and heterogeneous treatment result in a poor prognosis for patients with OC. Therefore, we aimed to develop new biomarkers to predict accurate prognoses and provide references for individualized treatment strategies.MethodsWe constructed a co-expression network applying the “WGCNA” package and identified the extracellular matrix-associated gene modules. We figured out the best model and generated the extracellular matrix score (ECMS). The ECMS’ ability to predict accurate OC patients’ prognoses and responses to immunotherapy was evaluated.ResultsThe ECMS was an independent prognostic factor in the training [hazard ratio (HR) = 3.132 (2.068–4.744), p< 0.001] and testing sets [HR = 5.514 (2.084–14.586), p< 0.001]. The receiver operating characteristic curve (ROC) analysis showed that the AUC values for 1, 3, and 5 years were 0.528, 0.594, and 0.67 for the training set, respectively, and 0.571, 0.635, and 0.684 for the testing set, respectively. It was found that the high ECMS group had shorter overall survival than the low ECMS group [HR = 2 (1.53–2.61), p< 0.001 in the training set; HR = 1.62 (1.06–2.47), p = 0.021 in the testing set; HR = 1.39 (1.05–1.86), p = 0.022 in the training set]. The ROC values of the ECMS model for predicting immune response were 0.566 (training set) and 0.572 (testing set). The response rate to immunotherapy was higher in patients with low ECMS.ConclusionWe created an ECMS model to predict the prognosis and immunotherapeutic benefits in OC patients and provided references for individualized treatment of OC patients.

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Section: Discussionmentioning

confidence: 99%

Leveraging various extracellular matrix levels to assess prognosis and sensitivity to immunotherapy in patients with ovarian cancer

et al. 2023

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“…PKP1 was identified as a new potential tumor suppressor in human melanoma, likely through regulating calcium signaling pathways [ 12 ]. Another study screened out SMARCA4 associated with metastasis melanoma, which in turn affects the signal transduction of the adherens junction [ 13 ]. Other genes CCNB2 , ARHGAP30 , and SEMA4D were also identified by WGCNA, which associated with survival as potential prognostic predictors and molecular targets of treatment [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

RTP4 is a novel prognosis-related hub gene in cutaneous melanoma

Yang

2021

Hereditas

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Objective Melanoma accounts for 80% of skin cancer deaths. The pathogenesis of melanoma is regulated by gene networks. Thus, we aimed here to identify gene networks and hub genes associated with melanoma and to further identify their underlying mechanisms. Methods GTEx (normal skin) and TCGA (melanoma tumor) RNA-seq datasets were employed for this purpose. We conducted weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes associated with melanoma. Log-rank analysis and multivariate Cox model analysis were performed to identify prognosis genes, which were validated using two independent melanoma datasets. We also evaluated the correlation between prognostic gene and immune cell infiltration. Results The blue module was the most relevant for melanoma and was thus considered the key module. Intersecting genes were identified between this module and differentially expressed genes (DEGs). Finally, 72 genes were identified and verified as hub genes using the Oncomine database. Log-rank analysis and multivariate Cox model analysis identified 13 genes that were associated with the prognosis of the metastatic melanoma group, and RTP4 was validated as a prognostic gene using two independent melanoma datasets. RTP4 was not previously associated with melanoma. When we evaluated the correlation between prognostic gene and immune cell infiltration, we discovered that RTP4 was associated with immune cell infiltration. Further, RTP4 was significantly associated with genes encoding components of immune checkpoints (PDCD1, TIM-3, and LAG3). Conclusions RTP4 is a novel prognosis-related hub gene in cutaneous melanoma. The novel gene RTP4 identified here will facilitate the exploration of the molecular mechanism of the pathogenesis and progression of melanoma and the discovery of potential new target for drug therapy.

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SWI/SNF complexes and cancers

Wang

Tang²

2023

Gene

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SMARCA4 promotes benign skin malignant transformation into melanoma through Adherens junction signal transduction

Cited by 3 publications

References 28 publications

Leveraging various extracellular matrix levels to assess prognosis and sensitivity to immunotherapy in patients with ovarian cancer

Leveraging various extracellular matrix levels to assess prognosis and sensitivity to immunotherapy in patients with ovarian cancer

RTP4 is a novel prognosis-related hub gene in cutaneous melanoma

SWI/SNF complexes and cancers

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