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      PLK4 is a key molecule in the formation of PGCCs and promotes invasion and migration of progeny cells derived from PGCCs

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          Abstract

          Purpose: Cancer stem cells (CSCs) are the evil source of tumor metastasis and recurrence. Polyploid giant cancer cells (PGCCs) that exhibit the characteristics of CSCs produced daughter cells via asymmetric division. The molecular mechanisms of daughter cells derived from PGCCs with high migration, invasion, and proliferation abilities in colorectal cancer (CRC) are explored in this paper based on the bioinformatics analysis.

          Materials and Methods: We characterized the expression of CSC-related genes in CRCs by analyzing the mRNAsi of The Cancer Genome Atlas and survival time. Weighted gene co-expression network analysis was performed to identify the modules of the hub and key genes. The migration, invasion, and proliferation abilities of cells, the expression of epithelial-mesenchymal transition (EMT)-related proteins and polo-like kinase 4 (PLK4) were compared in LoVo and Hct116 cells with and without bufalin treatment. In addition, the expression and subcellular location of cell division cycle 25C (CDC25C) in cells before and after PLK4 knockdown were assessed.

          Results: Eight hub genes were screened out and positively association with mRNAsi in CRCs based on bioinformatic analysis. Among them, checkpoint Kinase-1 ( CHEK1), budding uninhibited by benzimidazoles 1 Homolog Beta ( BUB1B) and PLK4 were closely associated with the prognosis of CRC patients. Bufalin could induce the formation of PGCCs in LoVo and Hct116 cell lines. PLK4 was overexpressed in PGCCs with progeny cells and progeny cells derived from PGCCs had strong migration and invasion abilities by expressing epithelial-mesenchymal transition (EMT)-related proteins. PLK4 could interact with CDC25C and promote CDC25C phosphorylation which was associated with the formation of PGCCs. Decreasing CDC25C expression in both LoVo and Hct116 PGCCs with progeny cells, while levels of pCDC25C-ser216 and pCDC25C-ser198 were increased in LoVo and decreased in Hct116 PGCCs with progeny cells. pCDC25C-ser216 located in the cytoplasm and pCDC25C-ser198 located in the nucleus in cells after bufalin treatment. Furthermore, expression of CDC25C, pCDC25C-ser216, and pCDC25C-ser198 was downregulated after PLK4 knockdown. Furthermore, the expression level of PLK4 was associated with differentiated degree, and lymph node metastasis in human CRC tissues.

          Conclusion: PLK4 contributes to the formation of PGCCs by regulating the expression of CDC25C and is associated with the expression and subcellular location of CDC25C, pCDC25C-ser216 and pCDC25C-ser198.

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          Most cited references44

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation

            Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.
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              Evaluation of time profile reconstruction from complex two-color microarray designs

              Background As an alternative to the frequently used "reference design" for two-channel microarrays, other designs have been proposed. These designs have been shown to be more profitable from a theoretical point of view (more replicates of the conditions of interest for the same number of arrays). However, the interpretation of the measurements is less straightforward and a reconstruction method is needed to convert the observed ratios into the genuine profile of interest (e.g. a time profile). The potential advantages of using these alternative designs thus largely depend on the success of the profile reconstruction. Therefore, we compared to what extent different linear models agree with each other in reconstructing expression ratios and corresponding time profiles from a complex design. Results On average the correlation between the estimated ratios was high, and all methods agreed with each other in predicting the same profile, especially for genes of which the expression profile showed a large variance across the different time points. Assessing the similarity in profile shape, it appears that, the more similar the underlying principles of the methods (model and input data), the more similar their results. Methods with a dye effect seemed more robust against array failure. The influence of a different normalization was not drastic and independent of the method used. Conclusion Including a dye effect such as in the methods lmbr_dye, anovaFix and anovaMix compensates for residual dye related inconsistencies in the data and renders the results more robust against array failure. Including random effects requires more parameters to be estimated and is only advised when a design is used with a sufficient number of replicates. Because of this, we believe lmbr_dye, anovaFix and anovaMix are most appropriate for practical use.
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                Author and article information

                Journal
                J Cancer
                J Cancer
                jca
                Journal of Cancer
                Ivyspring International Publisher (Sydney )
                1837-9664
                2022
                18 July 2022
                : 13
                : 9
                : 2954-2969
                Affiliations
                [1 ]Department of Pathology, Tianjin Union Medical Center, Nankai University, Tianjin, 300121, P.R. China.
                [2 ]Nankai University School of Medicine, Nankai University, Tianjin, 300071, P.R. China.
                [3 ]Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, P.R. China.
                [4 ]Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, P.R. China.
                [5 ]Department of Thyroid Surgery, Tianjin Union Medical Center, Tianjin, P.R. China.
                Author notes
                ✉ Corresponding authors: Shiwu Zhang, M.D., Ph.D., Department of Pathology, Tianjin Union Medical Center, Tianjin, 300121, China; Tel: (086)13652136865; Fax: (86)022-87721989; Email: zhangshiwu666@ 123456aliyun.com . Ming Gao, M.D., Ph.D., Thyroid Surgery, Tianjin Union Medical Center, Tianjin, P.R. China. Tel: (086)18622221110; Fax: (86)022-87721989; Email: gaoming68@ 123456aliyun.com .

                # These authors equally contributed to the paper.

                Competing Interests: The authors have declared that no competing interest exists.

                Article
                jcav13p2954
                10.7150/jca.74211
                9330457
                35912011
                d92a6d63-2172-4bc1-9b07-08dece5c2963
                © The author(s)

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.

                History
                : 20 April 2022
                : 9 July 2022
                Categories
                Research Paper

                Oncology & Radiotherapy
                plk4,cdc25c,bufalin,colorectal cancer,polyploid giant cancer cells,epithelial-mesenchymal transition

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