Dataset Information

Computational Biology Helps Understand How Polyploid Giant Cancer Cells Drive Tumor Success.

ABSTRACT: Precision and organization govern the cell cycle, ensuring normal proliferation. However, some cells may undergo abnormal cell divisions (neosis) or variations of mitotic cycles (endopolyploidy). Consequently, the formation of polyploid giant cancer cells (PGCCs), critical for tumor survival, resistance, and immortalization, can occur. Newly formed cells end up accessing numerous multicellular and unicellular programs that enable metastasis, drug resistance, tumor recurrence, and self-renewal or diverse clone formation. An integrative literature review was carried out, searching articles in several sites, including: PUBMED, NCBI-PMC, and Google Academic, published in English, indexed in referenced databases and without a publication time filter, but prioritizing articles from the last 3 years, to answer the following questions: (i) "What is the current knowledge about polyploidy in tumors?"; (ii) "What are the applications of computational studies for the understanding of cancer polyploidy?"; and (iii) "How do PGCCs contribute to tumorigenesis?"

SUBMITTER: Casotti MC

PROVIDER: S-EPMC10137723 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Computational Biology Helps Understand How Polyploid Giant Cancer Cells Drive Tumor Success.

Casotti Matheus Correia MC Meira Débora Dummer DD Zetum Aléxia Stefani Siqueira ASS Araújo Bruno Cancian de BC Silva Danielle Ribeiro Campos da DRCD Santos Eldamária de Vargas Wolfgramm Dos EVWD Garcia Fernanda Mariano FM Paula Flávia de F Santana Gabriel Mendonça GM Louro Luana Santos LS Alves Lyvia Neves Rebello LNR Braga Raquel Furlani Rocon RFR Trabach Raquel Silva Dos Reis RSDR Bernardes Sara Santos SS Louro Thomas Erik Santos TES Chiela Eduardo Cremonese Filippi ECF Lenz Guido G Carvalho Elizeu Fagundes de EF Louro Iúri Drumond ID

Genes 20230326 4

Precision and organization govern the cell cycle, ensuring normal proliferation. However, some cells may undergo abnormal cell divisions (neosis) or variations of mitotic cycles (endopolyploidy). Consequently, the formation of polyploid giant cancer cells (PGCCs), critical for tumor survival, resistance, and immortalization, can occur. Newly formed cells end up accessing numerous multicellular and unicellular programs that enable metastasis, drug resistance, tumor recurrence, and self-renewal or ...[more]

PMID: 37107559

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Project description:The microbiome, by virtue of its interactions with the host, is implicated in various host functions including its influence on nutrition and homeostasis. Many chronic diseases such as diabetes, cancer, inflammatory bowel diseases are characterized by a disruption of microbial communities in at least one biological niche/organ system. Various molecular mechanisms between microbial and host components such as proteins, RNAs, metabolites have recently been identified, thus filling many gaps in our understanding of how the microbiome modulates host processes. Concurrently, high-throughput technologies have enabled the profiling of heterogeneous datasets capturing community level changes in the microbiome as well as the host responses. However, due to limitations in parallel sampling and analytical procedures, big gaps still exist in terms of how the microbiome mechanistically influences host functions at a system and community level. In the past decade, computational biology and machine learning methodologies have been developed with the aim of filling the existing gaps. Due to the agnostic nature of the tools, they have been applied in diverse disease contexts to analyze and infer the interactions between the microbiome and host molecular components. Some of these approaches allow the identification and analysis of affected downstream host processes. Most of the tools statistically or mechanistically integrate different types of -omic and meta -omic datasets followed by functional/biological interpretation. In this review, we provide an overview of the landscape of computational approaches for investigating mechanistic interactions between individual microbes/microbiome and the host and the opportunities for basic and clinical research. These could include but are not limited to the development of activity- and mechanism-based biomarkers, uncovering mechanisms for therapeutic interventions and generating integrated signatures to stratify patients.

Project description:BackgroundBreast cancer is the most common cancer among women. Accumulated evidence over the past decades indicates a very high prevalence of human cytomegalovirus (HCMV) in breast cancer. High-risk HCMV strains possess a direct oncogenic effect displayed by cellular stress, polyploid giant cancer cells (PGCCs) generation, stemness, and epithelial-to-mesenchymal transition (EMT) leading to cancer of aggressive phenotype. Breast cancer development and progression have been regulated by several cytokines where the latter can promote cancer cell survival, help in tumor immune evasion, and initiate the EMT process, thereby resulting in invasion, angiogenesis, and breast cancer metastasis. In the present study, we screened cytokines expression in cytomegalovirus-transformed HMECs (CTH cells) cultures infected with HCMV high-risk strains namely, HCMV-DB and BL, as well as breast cancer biopsies, and analyzed the association between cytokines production, PGCCs count, and HCMV presence in vitro and in vivo.MethodsIn CTH cultures and breast cancer biopsies, HCMV load was quantified by real-time qPCR. PGCCs count in CTH cultures and breast cancer biopsies was identified based on cell morphology and hematoxylin and eosin staining, respectively. CTH supernatants were evaluated for the production of TGF-β, IL-6, IL1-β, and IL-10 by ELISA assays. The above-mentioned cytokines expression was assessed in breast cancer biopsies using reverse transcription-qPCR. The correlation analyses were performed using Pearson correlation test.ResultsThe revealed PGCCs/cytokine profile in our in vitro CTH model matched that of the breast cancer biopsies, in vivo. Pronounced cytokine expression and PGCCs count were detected in particularly CTH-DB cultures and basal-like breast cancer biopsies.ConclusionsThe analysis of cytokine profiles in PGCCs present mostly in basal-like breast cancer biopsies and derived from CTH cells chronically infected with the high-risk HCMV strains might have the potential to provide novel therapies such as cytokine-based immunotherapy which is a promising field in cancer treatments.

Project description:Our recent perplexing findings that polyploid giant cancer cells (PGCCs) acquired embryonic-like stemness and were capable of tumor initiation raised two important unanswered questions: how do PGCCs acquire such stemness, and to which stage of normal development do PGCCs correspond. Intriguingly, formation of giant cells due to failed mitosis/cytokinesis is common in the blastomere stage of the preimplantation embryo. However, the relationship between PGCCs and giant blastomeres has never been studied. Here, we tracked the fate of single PGCCs following paclitaxel-induced mitotic failure. Morphologically, early spheroids derived from PGCCs were indistinguishable from human embryos at the blastomere, polyploid blastomere, compaction, morula and blastocyst-like stages by light, scanning electron or three-dimensional confocal scanning microscopy. Formation of PGCCs was associated with activation of senescence, while budding of daughter cells was associated with senescence escape. PGCCs showed time- and space-dependent activation of expression of the embryonic stem cell markers OCT4, NANOG, SOX2 and SSEA1 and lacked expression of Xist. PGCCs acquired mesenchymal phenotype and were capable of differentiation into all three germ layers in vitro. The embryonic-like stemness of PGCCs was associated with nuclear accumulation of YAP, a key mediator of the Hippo pathway. Spheroids derived from single PGCCs grew into a wide spectrum of human neoplasms, including germ cell tumors, high-grade and low-grade carcinomas and benign tissues. Daughter cells derived from PGCCs showed attenuated capacity for invasion and increased resistance to paclitaxel. We also observed formation of PGCCs and dedifferentiation in ovarian cancer specimens from patients treated with chemotherapy. Taken together, our findings demonstrate that PGCCs represent somatic equivalents of blastomeres, the most primitive cancer stem cells reported to date. Thus, our studies reveal an evolutionarily conserved archaic embryonic program in somatic cells that can be de-repressed for oncogenesis. Our work offers a new paradigm for cancer origin and disease relapse.

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Computational Biology Helps Understand How Polyploid Giant Cancer Cells Drive Tumor Success.

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Computational Biology Helps Understand How Polyploid Giant Cancer Cells Drive Tumor Success.

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