Calsequestrin 2 overexpression in breast cancer increases tumorigenesis and metastasis by modulating the tumor microenvironment

Kim, Ju Hee; Lee, Eun-Shin; Yun, Jihui; Ryu, Han Suk; Kim, Hoon Yub; Ju, YeoJin; Kim, Kwangsoo; Kim, Jong‐Il; Moon, Hyeong‐Gon

doi:10.1002/1878-0261.13136

Cited by 13 publications

(3 citation statements)

References 55 publications

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“…The CASQ2 could prevent the activation of IRE1a by binding directly to the luminal (of the ERS sensor) in the junctional sarcoplasmic reticulum (20). Previous studies have shown that CASQ2 has a significant impact on several cellular processes associated with breast cancer, including the proliferation, migration and invasion (21). In a bioinformatics study, it served crucial roles in lymph node metastasis and was substantially correlated with survival in bladder cancer patients (22).…”

Section: Discussionmentioning

confidence: 99%

Correlation of endoplasmic reticulum stress patterns with the immune microenvironment in hepatocellular carcinoma: a prognostic signature analysis

Zhan,

Yang,

et al. 2023

Front. Immunol.

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BackgroundsThe extended duration of endoplasmic reticulum stress (ERS) can impact the progression of hepatocellular carcinoma (HCC) and the efficacy of immunotherapies by interacting with immune cells that have infiltrated the tumor microenvironment (TME).Methods and resultsThe study utilized a training cohort of 364 HCC patients with complete information from The Cancer Genome Atlas Program (TCGA) database, and a validation cohort of 231 HCC patients from the International Cancer Genome Consortium (ICGC) database. The genes related to ERS exhibiting a strong correlation with overall survival (OS) were identified using univariate Cox regression analysis. A 13-gene predictive signature was then produced through the least absolute shrinkage and selection operator (LASSO) regression approach. The data revealed that the ERS-associated gene signature effectively stratified patients into high- or low-risk groups regarding OS in both the training and validation cohorts (P < 0.0001 and P = 0.00029, respectively). Using the multivariate method, it is still an independent prognostic factor in both the training and validation cohorts (P < 0.001 and P = 0.008, respectively). Moreover, several metabolic pathways were identified to be enriched among the 13 genes in the predictive signature. When the ERS-associated gene signature was combined with the tumor-node-metastasis (TNM) stage, the ERS nomogram performed better than either the gene signature or the TNM stage alone (C-index values: 0.731, 0.729, and 0.573, respectively). Further analysis revealed that patients in the high-risk group exhibited increased infiltration of immune cells. Additionally, GP6 was downregulated in HCC tissues among these signature genes (P < 0.05), which was related to poor OS.ConclusionsThe data suggest that this novel ERS-associated gene signature could contribute to personalized cancer management for HCC. Moreover, targeting GP6 inhibition might be a potential method for HCC therapy.

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Section: Discussionmentioning

confidence: 99%

Correlation of endoplasmic reticulum stress patterns with the immune microenvironment in hepatocellular carcinoma: a prognostic signature analysis

Zhan,

Yang,

et al. 2023

Front. Immunol.

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“…CASQ1 , which is a type of Ca 2+ binding protein in the skeletal muscle ( 39 ), has rarely been studied in malignant tumors. However, the overexpression of CASQ2 was shown to increase tumorigenesis and metastasis in breast cancer ( 40 ).…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics analysis of prognosis and immune microenvironment of immunological cell death-related gemcitabine-resistance genes in bladder cancer

Liu¹,

Wang²,

Shen³

et al. 2022

Transl Androl Urol

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Background: Bladder cancer (BC) is the most common malignant tumor of the urinary system.Gemcitabine resistance partly accounts for treatment failure and recurrence in BC. Immunological cell death (ICD) is correlated with chemoresistance. The prognosis of patients with similar tumor stage still varies in response to chemotherapy, recurrence, and disease progression. Therefore, our study aimed to provide a prognostic model based on ICD-related and gemcitabine-resistance genes for BC.Methods: The data of BC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs), and differentially expressed gemcitabine resistance-related genes (DEGRRGs) were identified using the edgeR package.The survival-associated DEGRRGs were identified by univariate Cox analysis. A prognostic model was established by univariate Cox regression analysis and validated by GEO dataset. The outcome of low-risk group and high-risk group was analyzed by the Kaplan-Meier curve. The relationship between risk score and immune cell infiltration was investigated using the TIMER online database. Results:The prognosis of patients in the ICD-high group was significantly better than ICD-low group.A prognostic model containing 5 gemcitabine resistance-related ICD-associated genes, including PTPRR, HOXB3, SIGLEC15, UNC5CL, and CASQ1, was established. In both TCGA prognostic model and GEO validation model, patients in the low-risk group had better outcomes than high-risk group. According to the receiver operating characteristic (ROC) curves, the risk score area under ROC curve (AUC) of the TCGA prognostic model were calculated to be 0.705, while the risk score of the GEO validation model were calculated to be 0.716. Patients in the high-risk group had a significantly higher immune score, stromal score, and infiltration of M0 macrophages, M1 macrophages, M2 macrophages, and activated CD4 + T cells.Patients in the high-risk group had significantly lower infiltration of the regulatory T cells, resting dendritic cell (DCs), and activated DCs. Conclusions:The present study highlighted the functional role of gemcitabine resistance-related ICDassociated genes, constructed a prognostic score for the outcome evaluation and searched for potential targets to overcome gemcitabine chemoresistance in BC.

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“…Using the Adam optimizer, learning rate started with 0.002 and reduced equally within each batch for certain epoch stage. For epochs range [1, 10], [11,20], [21,30], [31,60], the learning rate reduced from [0.002, 0.0008], [0.0008, 0.0006], [0.0006, 0.0005], [0.0005, 0.0001] separately in each range.…”

Section: Hyperparametersmentioning

confidence: 99%

M3NetFlow: A novel multi-scale multi-hop graph AI model for integrative multi-omic data analysis

Zhang

Goedegebuure

et al. 2023

Preprint

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The integration and interpretation of multi-omics data play a crucial role in systems biology for prioritizing key molecular targets and deciphering core signaling pathways of complex diseases, such as cancer, covid-19 and Alzheimer's disease. However, it remains a challenge that has not been adequately addressed. Graph neural networks (GNN) have been emerged as powerful artificial intelligence models for analyzing data with a graphical structure. Nevertheless, GNN models have not been sufficiently designed for integrative and interpretable analysis of multi-omics data. In this study, we propose a novel multi-scale multi-hop modular GNN model, M3NetFlow, to integrate and interpret multi-omics data to rank key targets and infer core signaling pathways. Specifically, we applied the M3NetFlow model to infer cell-line specific core signaling networks explaining drug combination response. The evaluation and comparison results on drug combination prediction showed that the M3NetFlow model achieved significantly higher prediction accuracy than existing GNN models. Furthermore, M3NetFlow can predict key targets and infer essential signaling networks regulating drug combination response. It is critical for investigating mechanisms of synergy, and guiding the development of personalized precision medicine for patients with drug resistance. This model can be applied to general multi-omics data-driven research.

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Calsequestrin 2 overexpression in breast cancer increases tumorigenesis and metastasis by modulating the tumor microenvironment

Cited by 13 publications

References 55 publications

Correlation of endoplasmic reticulum stress patterns with the immune microenvironment in hepatocellular carcinoma: a prognostic signature analysis

Correlation of endoplasmic reticulum stress patterns with the immune microenvironment in hepatocellular carcinoma: a prognostic signature analysis

Bioinformatics analysis of prognosis and immune microenvironment of immunological cell death-related gemcitabine-resistance genes in bladder cancer

M3NetFlow: A novel multi-scale multi-hop graph AI model for integrative multi-omic data analysis

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