With the rapid development of cloud computing, the privacy security incidents occur frequently, especially data security issues. Cloud users would like to upload their sensitive information to cloud service providers in encrypted form rather than the raw data, and to prevent the misuse of data. The main challenge is to securely process or analyze these encrypted data without disclosing any useful information, and to achieve the rights management efficiently. In this paper, we propose the encrypted data processing protocols for cloud computing by utilizing additively homomorphic encryption and proxy cryptography. For the traditional homomorphic encryption schemes with many limitations, which are not suitable for cloud computing applications. We simulate a cloud computing scenario with flexible access control and extend the original homomorphic cryptosystem to suit our scenario by supporting various arithmetical calculations. We also prove the correctness and security of our protocols, and analyze the advantages and performance by comparing with some latest works.
Background: Colorectal cancer (CRC) is the third most common cancer and the fourth most common cause of cancer-related death worldwide. Advanced stage CRC, during the recent past, had a dismal prognosis and only a few available treatments. Pumilio homologous protein 1 (PUM1) is reportedly aberrant in human malignancies, including CRC. However, the role of PUM1 in the regulation of tumor-initiating cells (T-ICs) remains unknown. Methods: The levels of messenger RNAs (mRNAs) were determined by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunoblot analyses. Statistical analyses were performed to determine the associations between the levels of PUM1 and tumor features and patient outcomes. Whether PUM1 is a downstream target of miR-218-5p was verified by bioinformatics target gene prediction and qRT-PCR. Results: Herein, it was found that T-ICs, chemoresistance, and recurrent CRC samples all manifest increased PUM1 expression. Functional investigations have shown that PUM1 increased the self-renewal, tumorigenicity, malignant proliferation, and chemoresistance of colorectal cells. PUM1 activates the phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT) signaling pathway biochemically. Furthermore, it was discovered that miR-218-5p specifically targets T-ICs' PUM1 3'-untranslated region (3'-UTR). More importantly, the PUM1/PI3K/AKT axis regulates CRC cells' responses to treatment with cetuximab, and PUM1 overexpression increased cetuximab resistance. More evidence points to the possibility that low PUM1 may predict cetuximab benefits in CRC patients after analysis of the patient cohort, patient-derived tumor organoids, and patient-derived xenografts (PDXs). Conclusions: Taken together, the result of this work points to the critical function of the miR-218-5p/PUM1/PI3K/AKT regulatory circuit in regulating T-ICs characteristics and thus suggests possible therapeutic targets for CRC.
BACKGROUND
Currently, there are many therapeutic methods for lung adenocarcinoma (LUAD), but the 5-year survival rate is still only 15% at later stages. Epithelial– mesenchymal transition (EMT) has been shown to be closely associated with local dissemination and subsequent metastasis of solid tumors. However, the role of EMT in the occurrence and development of LUAD remains unclear.
AIM
To further elucidate the value of EMT-related genes in LUAD prognosis.
METHODS
Univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were applied to establish and validate a new EMT-related gene signature for predicting LUAD prognosis. The risk model was evaluated by Kaplan–Meier survival analysis, principal component analysis, and functional enrichment analysis and was used for nomogram construction. The potential structures of drugs to which LUAD is sensitive were discussed with respect to EMT-related genes in this model.
RESULTS
Thirty-three differentially expressed genes related to EMT were found to be highly associated with overall survival (OS) by using univariate Cox regression analysis (log2FC ≥ 1, false discovery rate < 0.001). A prognostic signature of 7 EMT-associated genes was developed to divide patients into two risk groups by high or low risk scores. Kaplan–Meier survival analysis showed that the OS of patients in the high-risk group was significantly poorer than that of patients in the low-risk group (
P
< 0.05). Multivariate Cox regression analysis showed that the risk score was an independent risk factor for OS (HR > 1,
P
< 0.05). The results of receiver operator characteristic curve analysis suggested that the 7-gene signature had a perfect ability to predict prognosis (all area under the curves > 0.5).
CONCLUSION
The EMT-associated gene signature classifier could be used as a feasible indicator for predicting OS.
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