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?"

Keywords: bioinformatics; polyploid giant cancer cells (PGCCs); systems biology; tumor evolution.

Figure 1

Giant cell cycle outcomes. Under stress, the cell responds in various ways to maintain balance. When chemotherapy treated tumor cells are isolated, large numbers of cells die; surviving cells may start an altered cell cycle, capable of generating PGCCs, which follow four phases or other unusual divisions; PGCCs exhibit abnormal shapes similar to single-celled organisms such as amoebas, or embryonic cells at the blastomere stage; that (A) can undergo diapause, dormancy, relapse, and generate multilineages; (B) tumor cells use these means to survive and generate resistant daughter cells by budding, fragmentation (bursting), sporulation or encystment; (C) new genetic and epigenetic characteristics create unlimited potential for more aggressive, resistant and immortal phenotypes. Terms are shown in Box A1 (Appendix A). Note: created with BioRender.com (accessed on 15 March 2023).

Figure 2

PGCC mediated tumor evolution. Cell division errors, such as mitotic arrest, can cause whole-genome duplications (WGD), which is represented by a reversible polyploidy, originated from biological processes such as endocycling, endomitosis, cell fusion, cellular cannibalism, emperipolesis, cytokinesis failure, reductive mitosis, budding, fragmentation (bursting), nucleophagy, and sporulation. Reversible polyploidy may create resistance to tumor extinction. Terms are shown in Box A1 (Appendix A).

Figure 3

Paradoxical cancer life cycle. Normal cells (a) follow a linear ontogenetic process towards cell death interspersed with senescence (b), in a pathway called “road of death” (A). Some tumor cells may undergo reprogramming (c) and self-organization (d) either by mitotic catastrophe or by neosis or by mitotic slippage, because of genome, epigenome and quantum chaos (e), resulting in changes in cell fate. Tumor undergoes a macroevolutionary process (genomic and epigenomic instability (B)). Polyploid tumor cells undergo epigenetic and genetic regression, causing incongruent cell fragmentation (f), to achieve trans-immortal diversity (access to immortalization capacity, resistance to extinction and heterogeneous profile in the formation of multilineages of more apt tumor aneuploid cells) (g) new tumor cells follow a Darwinian evolution (microevolution (C)) and maintain a “triploid/tetraploid bridge” (*), between states 2n and pn–“triploid/tetraploid bridge” (h). Terms shown in Box A1 (Appendix A).

Figure 4

Integrated scheme of computational resources in oncology and polyploidy. The biological computational era has provided numerous advances on the amount of biological data and their significance. Crosstalk between computing and research laboratory is needed to create personalized medicine through multi-omics. Note: created with BioRender.com (accessed on 15 March 2023).