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IFI30 expression predicts patient prognosis in breast cancer and dictates breast cancer cells proliferation via regulating autophagy.

ABSTRACT: Introduction: Incidence and mortality rates of breast cancer are increasing in women worldwide. Immunotherapy is a relatively popular treatment modality for all malignant tumors including breast cancer in recent years. Interferon γ-inducible protein 30 (IFI30) could catalyze the reduction of disulfide bonds and enhance major histocompatibility complex (MHC) class II-restricted antigen processing. Recent studies showed that IFI30 played an important role in the immune response of malignant tumors. Methods: The Cancer Genome Atlas (TCGA) database and clinical proteomic tumor Analysis consortium (CPTAC) database were applied to predict the role of IFI30 in breast cancer and the relationship between IFI30 and prognosis of breast cancer patients. Then we detected the expression of IFI30 in clinical samples of breast cancer patients, and analyzed the relationship between IFI30 and the prognosis of breast cancer patients. We used lentivirus infection method to construct a stable IFI30 knockdown cell line, and detected the effect of IFI30 in breast cancer cells. Nude mice tumor bearing experiment was performed to investigate the effect of IFI30 on breast cancer cells in vivo. Western blot was used to verify the regulation of autophagy related protein LC3 and p62 by IFI30. Results: We found that IFI30 was highly expressed in breast cancer tissues and was associated with poor outcome of patients. The knockdown of IFI30 could inhibit the proliferation, migration and invasion of breast cancer cells and significantly inhibit tumor growth in vivo. Increased accumulation of LC3-II and p62 suggested impaired autophagy in IFI30 knockdown cells. Discussion: As a result, we suggested that IFI30 might play a key role in the initiation and progression of human breast cancer and might be a new therapeutic target in breast cancer.

SUBMITTER: Fan Y

PROVIDER: S-EPMC8364447 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionGenetic and molecular signatures have been incorporated into cancer prognosis prediction and treatment decisions with good success over the past decade. Clinically, these signatures are usually used in early-stage cancers to evaluate whether they require adjuvant therapy following surgical resection. A molecular signature that is prognostic across more clinical contexts would be a useful addition to current signatures.MethodsWe defined a signature for the ubiquitous tissue factor, E2F4, based on its shared target genes in multiple tissues. These target genes were identified by chromatin immunoprecipitation sequencing (ChIP-seq) experiments using a probabilistic method. We then computationally calculated the regulatory activity score (RAS) of E2F4 in cancer tissues, and examined how E2F4 RAS correlates with patient survival.ResultsGenes in our E2F4 signature were 21-fold more likely to be correlated with breast cancer patient survival time compared to randomly selected genes. Using eight independent breast cancer datasets containing over 1,900 unique samples, we stratified patients into low and high E2F4 RAS groups. E2F4 activity stratification was highly predictive of patient outcome, and our results remained robust even when controlling for many factors including patient age, tumor size, grade, estrogen receptor (ER) status, lymph node (LN) status, whether the patient received adjuvant therapy, and the patient's other prognostic indices such as Adjuvant! and the Nottingham Prognostic Index scores. Furthermore, the fractions of samples with positive E2F4 RAS vary in different intrinsic breast cancer subtypes, consistent with the different survival profiles of these subtypes.ConclusionsWe defined a prognostic signature, the E2F4 regulatory activity score, and showed it to be significantly predictive of patient outcome in breast cancer regardless of treatment status and the states of many other clinicopathological variables. It can be used in conjunction with other breast cancer classification methods such as Oncotype DX to improve clinical outcome prediction.

Project description:Background: Accumulating evidence suggests that circular RNAs (circRNAs) are highly correlated with tumor progression and pathogenesis in breast cancer. Whereas, their regulatory roles and corresponding mechanisms in breast cancer are still not exhaustive. Thus, we intended to establish circRNA-mediated competive endogenous RNA (ceRNA) network to uncover the possible roles and clinical implications of circRNAs in breast cancer. Methods: Microarray and RNA-sequencing (RNA-seq) data were download from GEO and TCGA database to screen for differentially expressed RNAs (DEcircRNAs, DEmiRNAs, DEmRNAs) in breast cancer. By implementing online databases, we established ceRNA networks, performed gene set enrichment analysis, constructed protein-protein interaction (PPI) networks, and assessed the expression levels and prognostic significance of hub genes. Subsequently, we explored the functions of prognosis-related genes and constructed gene-drug interaction networks. Finally, the functional roles of DEcircRNAs in breast cancer were revealed via MTT and colony formation assay. Results: Based on the identified 8 DEcircRNAs, 25 miRNAs and 216 mRNAs, a ceRNA regulatory network was established. Further analysis revealed that prominent enrichments were transcription factor binding, transforming growth factor-beta (TGF-β) and Apelin signaling pathway etc. PPI network and survival curves analysis showed that elevated levels of hub genes (RACGAP1 and KPNA2) were associated with poorer prognosis. They were found to be positively relevant to cell cycle and proliferation. Then a prognostic sub-network of ceRNA was constructed, consisting of 2 circRNAs, 4 miRNAs and 2 mRNAs. The gene-drug interaction network showed that numerous drugs could regulate the expression of these two prognosis-related genes. Functional experiments showed that depletion of circ_0008812 and circ_0001583 could significantly inhibit the proliferation of MCF-7 cells. Conclusion: Our study constructed 4 prognostic regulatory axes that are significantly correlated with tumor prognosis in breast cancer patients, and uncover the roles of circ_0008812 and circ_0001583 in breast cancer, providing a new perspective into the molecular mechanisms of breast cancer pathogenesis.

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IFI30 expression predicts patient prognosis in breast cancer and dictates breast cancer cells proliferation via regulating autophagy.

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