Context is everything: aneuploidy in cancer

Modeling metastatic progression from cross-sectional cancer genomics data

MOTIVATION

Metastasis formation is a hallmark of cancer lethality. Yet, metastases are generally unobservable during their early stages of dissemination and spread to distant organs. Genomic datasets of matched primary tumors and metastases may offer insights into the underpinnings and the dynamics of metastasis formation.

RESULTS

We present metMHN, a cancer progression model designed to deduce the joint progression of primary tumors and metastases using cross-sectional cancer genomics data. The model elucidates the statistical dependencies among genomic events, the formation of metastasis, and the clinical emergence of both primary tumors and their metastatic counterparts. metMHN enables the chronological reconstruction of mutational sequences and facilitates estimation of the timing of metastatic seeding. In a study of nearly 5000 lung adenocarcinomas, metMHN pinpointed TP53 and EGFR as mediators of metastasis formation. Furthermore, the study revealed that post-seeding adaptation is predominantly influenced by frequent copy number alterations.

AVAILABILITY AND IMPLEMENTATION

All datasets and code are available on GitHub at https://github.com/cbg-ethz/metMHN.

Integrated bulk and single-cell RNA sequencing identifies an aneuploidy-based gene signature to predict sensitivity of lung adenocarcinoma to traditional chemotherapy drugs and patients' prognosis

Background

Patients with lung adenocarcinoma (LUAD) often develop a poor prognosis. Currently, researches on prognostic and immunotherapeutic capacity of aneuploidy-related genes in LUAD are limited.

Methods

Genes related to aneuploidy were screened based on bulk RNA sequencing data from public databases using Spearman method. Next, univariate Cox and Lasso regression analyses were performed to establish an aneuploidy-related riskscore (ARS) model. Results derived from bioinformatics analysis were further validated using cellular experiments. In addition, typical LUAD cells were identified by subtype clustering, followed by SCENIC and intercellular communication analyses. Finally, ESTIMATE, ssGSEA and CIBERSORT algorithms were employed to analyze the potential relationship between ARS and tumor immune environment.

Results

A five-gene ARS signature was developed. These genes were abnormally high-expressed in LUAD cell lines, and in particular the high expression of CKS1B promoted the proliferative, migratory and invasive phenotypes of LUAD cell lines. Low ARS group had longer overall survival time, higher degrees of inflammatory infiltration, and could benefit more from receiving immunotherapy. Patients in low ASR group responded more actively to traditional chemotherapy drugs (Erlotinib and Roscovitine). The scRNA-seq analysis annotated 17 cell subpopulations into seven cell clusters. Core transcription factors (TFs) such as CREB3L1 and CEBPD were enriched in high ARS cell group, while TFs such as BCLAF1 and UQCRB were enriched in low ARS cell group. CellChat analysis revealed that high ARS cell groups communicated with immune cells via SPP1 (ITGA4-ITGB1) and MK (MDK-NCl) signaling pathways.

Conclusion

In this research, integrative analysis based on the ARS model provided a potential direction for improving the diagnosis and treatment of LUAD.

Selection forces underlying aneuploidy patterns in cancer

Aneuploidy, the presence of an aberrant number of chromosomes, has been associated with tumorigenesis for over a century. More recently, advances in karyotyping techniques have revealed its high prevalence in cancer: About 90% of solid tumors and 50-70% of hematopoietic cancers exhibit chromosome gains or losses. When analyzed at the level of specific chromosomes, there are strong patterns that are observed in cancer karyotypes both pan-cancer and for specific cancer types. These specific aneuploidy patterns correlate strongly with outcomes for tumor initiation, progression, metastasis formation, immune evasion and resistance to therapeutic treatment. Despite their prominence, understanding the basis underlying aneuploidy patterns in cancer has been challenging. Advances in genetic engineering and bioinformatic analyses now offer insights into the genetic determinants of aneuploidy pattern selection. Overall, there is substantial evidence that expression changes of particular genes can act as the positive selective forces for adaptation through aneuploidy. Recent findings suggest that multiple genes contribute to the selection of specific aneuploid chromosomes in cancer; however, further research is necessary to identify the most impactful driver genes. Determining the genetic basis and accompanying vulnerabilities of specific aneuploidy patterns is an essential step in selectively targeting these hallmarks of tumors.

Tumor initiation and early tumorigenesis: molecular mechanisms and interventional targets

Tumorigenesis is a multistep process, with oncogenic mutations in a normal cell conferring clonal advantage as the initial event. However, despite pervasive somatic mutations and clonal expansion in normal tissues, their transformation into cancer remains a rare event, indicating the presence of additional driver events for progression to an irreversible, highly heterogeneous, and invasive lesion. Recently, researchers are emphasizing the mechanisms of environmental tumor risk factors and epigenetic alterations that are profoundly influencing early clonal expansion and malignant evolution, independently of inducing mutations. Additionally, clonal evolution in tumorigenesis reflects a multifaceted interplay between cell-intrinsic identities and various cell-extrinsic factors that exert selective pressures to either restrain uncontrolled proliferation or allow specific clones to progress into tumors. However, the mechanisms by which driver events induce both intrinsic cellular competency and remodel environmental stress to facilitate malignant transformation are not fully understood. In this review, we summarize the genetic, epigenetic, and external driver events, and their effects on the co-evolution of the transformed cells and their ecosystem during tumor initiation and early malignant evolution. A deeper understanding of the earliest molecular events holds promise for translational applications, predicting individuals at high-risk of tumor and developing strategies to intercept malignant transformation.

The yin and yang of chromosomal instability in prostate cancer

Metastatic prostate cancer remains an incurable lethal disease. Studies indicate that prostate cancer accumulates genomic changes during disease progression and displays the highest levels of chromosomal instability (CIN) across all types of metastatic tumours. CIN, which refers to ongoing chromosomal DNA gain or loss during mitosis, and derived aneuploidy, are known to be associated with increased tumour heterogeneity, metastasis and therapy resistance in many tumour types. Paradoxically, high CIN levels are also proposed to be detrimental to tumour cell survival, suggesting that cancer cells must develop adaptive mechanisms to ensure their survival. In the context of prostate cancer, studies indicate that CIN has a key role in disease progression and might also offer a therapeutic vulnerability that can be pharmacologically targeted. Thus, a comprehensive evaluation of the causes and consequences of CIN in prostate cancer, its contribution to aggressive advanced disease and a better understanding of the acquired CIN tolerance mechanisms can translate into new tumour classifications, biomarker development and therapeutic strategies.

Surviving the Storm: The Role of Poly- and Depolyploidization in Tissues and Tumors

Polyploidization and depolyploidization are critical processes in the normal development and tissue homeostasis of diploid organisms. Recent investigations have revealed that polyaneuploid cancer cells (PACCs) exploit this ploidy variation as a survival strategy against anticancer treatment and for the repopulation of tumors. Unscheduled polyploidization and chromosomal instability in PACCs enhance malignancy and treatment resistance. However, their inability to undergo mitosis causes catastrophic cellular death in most PACCs. Adaptive ploid reversal mechanisms, such as multipolar mitosis, centrosome clustering, meiosis-like division, and amitosis, counteract this lethal outcome and drive cancer relapse. The purpose of this work is to focus on PACCs induced by cytotoxic therapy, highlighting the latest discoveries in ploidy dynamics in physiological and pathological contexts. Specifically, by emphasizing the role of "poly-depolyploidization" in tumor progression, the aim is to identify novel therapeutic targets or paradigms for combating diseases associated with aberrant ploidies.

VGLL1 stabilization of cytoplasmic TAZ promotes EGFR expression and maintains tumor initiating cells in breast cancer independent of TEAD

Vestigial-like family member 1 (VGLL1) is one of the X-linked genes whose expression is elevated in basal-like breast cancer (BLBC) because of X-chromosome isodisomy. As an approach towards understanding its function, we performed correlation study using transcript data of breast cancer patients from cBioPortal for Cancer Genomics. Our analysis identified EGFR as the most correlated transcript with VGLL1. We demonstrate that VGLL1 promotes EGFR expression and increases the frequency of breast tumor initiating cells (CD44high/+CD24low/-). These findings are crucial because an elevated EGFR expression and high frequency of CD44high/+CD24low/- cells are defining features of BLBC, and we provide a new mechanistic insight into how their expressions are controlled. Importantly, VGLL1 regulation of EGFR and CD44high/+CD24low/- population is mediated by the hippo-transducer TAZ which exerts its oncogenic roles by binding and activating TEAD transcription factors. A crucial finding is that TEAD-binding domain of TAZ is dispensable for its regulation of EGFR and CD44high/+CD24low/- cells. Instead, VGLL1 stabilization of cytoplasmic TAZ is essential for these functions. Also, we show that VGLL1/TAZ restricts the surface expression of CD24 which contributes to the increased number of CD44high/+CD24low/- cells. In addition, we observed that VGLL1 represses AXL expression and suppresses claudin-low phenotype, and that is caused by the VGLL1 mediated nuclear expulsion of TAZ. Therefore, EGFR and AXL seem to represent two different breast tumor subtypes, and their differential expressions is controlled by VGLL1.

TPX2 overexpression promotes sensitivity to dasatinib in breast cancer by activating YAP transcriptional signaling

Chromosomal instability (CIN) is a hallmark of cancer aggressiveness, providing genetic plasticity and tumor heterogeneity that allows the tumor to evolve and adapt to stress conditions. CIN is considered a cancer therapeutic biomarker because healthy cells do not exhibit CIN. Despite recent efforts to identify therapeutic strategies related to CIN, the results obtained have been very limited. CIN is characterized by a genetic signature where a collection of genes, mostly mitotic regulators, are overexpressed in CIN-positive tumors, providing aggressiveness and poor prognosis. We attempted to identify new therapeutic strategies related to CIN genes by performing a drug screen, using cells that individually express CIN-associated genes in an inducible manner. We find that the overexpression of targeting protein for Xklp2 (TPX2) enhances sensitivity to the proto-oncogene c-Src (SRC) inhibitor dasatinib due to activation of the Yes-associated protein 1 (YAP) pathway. Furthermore, using breast cancer data from The Cancer Genome Atlas (TCGA) and a cohort of cancer-derived patient samples, we find that both TPX2 overexpression and YAP activation are present in a significant percentage of cancer tumor samples and are associated with poor prognosis; therefore, they are putative biomarkers for selection for dasatinib therapy.

Antiparallel microtubule bundling supports KIF15-driven mitotic spindle assembly

The spindle is a bipolar microtubule-based machine that is crucial for accurate chromosome segregation. Spindle bipolarity is generated by Eg5 (a kinesin-5), a conserved motor that drives spindle assembly by localizing to and sliding apart antiparallel microtubules. In the presence of Eg5 inhibitors (K5Is), KIF15 (a kinesin-12) can promote spindle assembly, resulting in K5I-resistant cells (KIRCs). However, KIF15 is a less potent motor than Eg5, suggesting that other factors may contribute to spindle formation in KIRCs. Protein Regulator of Cytokinesis 1 (PRC1) preferentially bundles antiparallel microtubules, and we previously showed that PRC1 promotes KIF15-microtubule binding, leading us to hypothesize that PRC1 may enhance KIF15 activity in KIRCs. Here, we demonstrate that: 1) loss of PRC1 in KIRCs decreases spindle bipolarity, 2) overexpression of PRC1 increases spindle formation efficiency in KIRCs, 3) overexpression of PRC1 protects K5I naïve cells against the K5I S-trityl-L-cysteine (STLC), and 4) PRC1 overexpression promotes the establishment of K5I resistance. These effects are not fully reproduced by a TPX2, a microtubule bundler with no known preference for microtubule orientation. These results suggest a model wherein PRC1-mediated bundling of microtubules creates a more favorable microtubule architecture for KIF15-driven mitotic spindle assembly in the context of Eg5 inhibition.

Natural proteome diversity links aneuploidy tolerance to protein turnover

Accessing the natural genetic diversity of species unveils hidden genetic traits, clarifies gene functions and allows the generalizability of laboratory findings to be assessed. One notable discovery made in natural isolates of Saccharomyces cerevisiae is that aneuploidy-an imbalance in chromosome copy numbers-is frequent1,2 (around 20%), which seems to contradict the substantial fitness costs and transient nature of aneuploidy when it is engineered in the laboratory3-5. Here we generate a proteomic resource and merge it with genomic1 and transcriptomic6 data for 796 euploid and aneuploid natural isolates. We find that natural and lab-generated aneuploids differ specifically at the proteome. In lab-generated aneuploids, some proteins-especially subunits of protein complexes-show reduced expression, but the overall protein levels correspond to the aneuploid gene dosage. By contrast, in natural isolates, more than 70% of proteins encoded on aneuploid chromosomes are dosage compensated, and average protein levels are shifted towards the euploid state chromosome-wide. At the molecular level, we detect an induction of structural components of the proteasome, increased levels of ubiquitination, and reveal an interdependency of protein turnover rates and attenuation. Our study thus highlights the role of protein turnover in mediating aneuploidy tolerance, and shows the utility of exploiting the natural diversity of species to attain generalizable molecular insights into complex biological processes.

Genomic linkages dictate cancer evolution

Aneuploidy, a state of chromosome imbalance frequently found in cancer, results in convoluted cancer genomes. Here, Kuzmin and colleagues1 identify how the aneuploid genome in triple-negative breast cancer is being shaped by unique genome network interactions.

Spindle architecture constrains karyotype in budding yeast

The eukaryotic cell division machinery must rapidly and reproducibly duplicate and partition the cell's chromosomes in a carefully coordinated process. However, chromosome number varies dramatically between genomes, even on short evolutionary timescales. We sought to understand how the mitotic machinery senses and responds to karyotypic changes by using a series of budding yeast strains in which the native chromosomes have been successively fused. Using a combination of cell biological profiling, genetic engineering, and experimental evolution, we show that chromosome fusions are well tolerated up until a critical point. Cells with fewer than five centromeres lack the necessary number of kinetochore-microtubule attachments needed to counter outward forces in the metaphase spindle, triggering the spindle assembly checkpoint and prolonging metaphase. Our findings demonstrate that spindle architecture is a constraining factor for karyotype evolution.

Chromosomal instability induced in cancer can enhance macrophage-initiated immune responses that include anti-tumor IgG

Solid tumors generally exhibit chromosome copy number variation, which is typically caused by chromosomal instability (CIN) in mitosis. The resulting aneuploidy can drive evolution and associates with poor prognosis in various cancer types as well as poor response to T-cell checkpoint blockade in melanoma. Macrophages and the SIRPα-CD47 checkpoint are understudied in such contexts. Here, CIN is induced in poorly immunogenic B16F10 mouse melanoma cells using spindle assembly checkpoint MPS1 inhibitors that generate persistent micronuclei and diverse aneuploidy while skewing macrophages toward a tumoricidal 'M1-like' phenotype based on markers and short-term anti-tumor studies. Mice bearing CIN-afflicted tumors with wild-type CD47 levels succumb similar to controls, but long-term survival is maximized by SIRPα blockade on adoptively transferred myeloid cells plus anti-tumor monoclonal IgG. Such cells are the initiating effector cells, and survivors make de novo anti-cancer IgG that not only promote phagocytosis of CD47-null cells but also suppress tumor growth. CIN does not affect the IgG response, but pairing CIN with maximal macrophage anti-cancer activity increases durable cures that possess a vaccination-like response against recurrence.

Copy number alterations: a catastrophic orchestration of the breast cancer genome

Breast cancer (BCa) is a prevalent malignancy that predominantly affects women around the world. Somatic copy number alterations (CNAs) are tumor-specific amplifications or deletions of DNA segments that often drive BCa development and therapy resistance. Hence, the complex patterns of CNAs complement BCa classification systems. In addition, understanding the precise contributions of CNAs is essential for tailoring personalized treatment approaches. This review highlights how tumor evolution drives the acquisition of CNAs, which in turn shape the genomic landscapes of BCas. It also discusses advanced methodologies for identifying recurrent CNAs, studying CNAs in BCa and their clinical impact.

Genome-wide loss of heterozygosity predicts aggressive, treatment-refractory behavior in pituitary neuroendocrine tumors

Pituitary neuroendocrine tumors (PitNETs) exhibiting aggressive, treatment-refractory behavior are the rare subset that progress after surgery, conventional medical therapies, and an initial course of radiation and are characterized by unrelenting growth and/or metastatic dissemination. Two groups of patients with PitNETs were sequenced: a prospective group of patients (n = 66) who consented to sequencing prior to surgery and a retrospective group (n = 26) comprised of aggressive/higher risk PitNETs. A higher mutational burden and fraction of loss of heterozygosity (LOH) was found in the aggressive, treatment-refractory PitNETs compared to the benign tumors (p = 1.3 × 10-10 and p = 8.5 × 10-9, respectively). Within the corticotroph lineage, a characteristic pattern of recurrent chromosomal LOH in 12 specific chromosomes was associated with treatment-refractoriness (occurring in 11 of 14 treatment-refractory versus 1 of 14 benign corticotroph PitNETs, p = 1.7 × 10-4). Across the cohort, a higher fraction of LOH was identified in tumors with TP53 mutations (p = 3.3 × 10-8). A machine learning approach identified loss of heterozygosity as the most predictive variable for aggressive, treatment-refractory behavior, outperforming the most common gene-level alteration, TP53, with an accuracy of 0.88 (95% CI: 0.70-0.96). Aggressive, treatment-refractory PitNETs are characterized by significant aneuploidy due to widespread chromosomal LOH, most prominently in the corticotroph tumors. This LOH predicts treatment-refractoriness with high accuracy and represents a novel biomarker for this poorly defined PitNET category.

To explore the mechanism of Yigong San anti-gastric cancer and immune regulation

BACKGROUND

Yigong San (YGS) is a representative prescription for the treatment of digestive disorders, which has been used in clinic for more than 1000 years. However, the mechanism of its anti-gastric cancer and regulate immunity are still remains unclear.

AIM

To explore the mechanism of YGS anti-gastric cancer and immune regulation.

METHODS

Firstly, collect the active ingredients and targets of YGS, and the differentially expressed genes of gastric cancer. Secondly, constructed a protein-protein interaction network between the targets of drugs and diseases, and screened hub genes. Then the clinical relevance, mutation and repair, tumor microenvironment and drug sensitivity of the hub gene were analyzed. Finally, molecular docking was used to verify the binding ability of YGS active ingredient and hub genes.

RESULTS

Firstly, obtained 55 common targets of gastric cancer and YGS. The Kyoto Encyclopedia of Genes and Genomes screened the microtubule-associated protein kinase signaling axis as the key pathway and IL6, EGFR, MMP2, MMP9 and TGFB1 as the hub genes. The 5 hub genes were involved in gastric carcinogenesis, staging, typing and prognosis, and their mutations promote gastric cancer progression. Finally, molecular docking results confirmed that the components of YGS can effectively bind to therapeutic targets.

CONCLUSION

YGS has the effect of anti-gastric cancer and immune regulation.

Cell Competition Eliminates Aneuploid Human Pluripotent Stem Cells

Human pluripotent stem cells (hPSCs) maintain diploid populations for generations despite a persistently high rate of mitotic errors that cause aneuploidy, or chromosome imbalances. Consequently, to maintain genome stability, aneuploidy must inhibit hPSC proliferation, but the mechanisms are unknown. Here, we surprisingly find that homogeneous aneuploid populations of hPSCs proliferate unlike aneuploid non-transformed somatic cells. Instead, in mosaic populations, cell non-autonomous competition between neighboring diploid and aneuploid hPSCs eliminates less fit aneuploid cells. Aneuploid hPSCs with lower Myc or higher p53 levels relative to diploid neighbors are outcompeted but conversely gain a selective advantage when Myc and p53 relative abundance switches. Thus, although hPSCs frequently missegregate chromosomes and inherently tolerate aneuploidy, Myc- and p53-driven cell competition preserves their genome integrity. These findings have important implications for the use of hPSCs in regenerative medicine and for how diploid human embryos are established despite the prevalence of aneuploidy during early development.

Cellular senescence in cancer: molecular mechanisms and therapeutic targets

Aging exhibits several hallmarks in common with cancer, such as cellular senescence, dysbiosis, inflammation, genomic instability, and epigenetic changes. In recent decades, research into the role of cellular senescence on tumor progression has received widespread attention. While how senescence limits the course of cancer is well established, senescence has also been found to promote certain malignant phenotypes. The tumor-promoting effect of senescence is mainly elicited by a senescence-associated secretory phenotype, which facilitates the interaction of senescent tumor cells with their surroundings. Targeting senescent cells therefore offers a promising technique for cancer therapy. Drugs that pharmacologically restore the normal function of senescent cells or eliminate them would assist in reestablishing homeostasis of cell signaling. Here, we describe cell senescence, its occurrence, phenotype, and impact on tumor biology. A "one-two-punch" therapeutic strategy in which cancer cell senescence is first induced, followed by the use of senotherapeutics for eliminating the senescent cells is introduced. The advances in the application of senotherapeutics for targeting senescent cells to assist cancer treatment are outlined, with an emphasis on drug categories, and the strategies for their screening, design, and efficient targeting. This work will foster a thorough comprehension and encourage additional research within this field.

Tetraploidy as a metastable state towards malignant cell transformation within a systemic approach of cancer development

Tetraploidy, a condition in which a cell has four homologous sets of chromosomes, may be a natural physiological condition or pathophysiological such as in cancer cells or stress induced tetraploidisation. Its contribution to cancer development is well known. However, among the many models proposed to explain the causes, mechanisms and steps of malignant cell transformation, only few integrate tetraploidization into a systemic multistep approach of carcinogenesis. Therefore, we will i) describe the molecular and cellular characteristics of tetraploidy; ii) assess the contribution of stress-induced tetraploidy in cancer development; iii) situate tetraploidy as a metastable state leading to cancer development in a systemic cell-centered approach; iiii) consider knowledge gaps and future perspectives. The available data shows that stress-induced tetraploidisation/polyploidisation leads to p53 stabilisation, cell cycle arrest, followed by cellular senescence or apoptosis, suppressing the proliferation of tetraploid cells. However, if tetraploid cells escape the G1-tetraploidy checkpoint, it may lead to uncontrolled proliferation of tetraploid cells, micronuclei induction, aneuploidy and deploidisation. In addition, tetraploidization favors 3D-chromatin changes and epigenetic effects. The combined effects of genetic and epigenetic changes allow the expression of oncogenic gene expression and cancer progression. Moreover, since micronuclei are inducing inflammation, which in turn may induce additional tetraploidization, tetraploidy-derived genetic instability leads to a carcinogenic vicious cycle. The concept that polyploid cells are metastable intermediates between diploidy and aneuploidy is not new. Metastability denotes an intermediate energetic state within a dynamic system other than the system's state at least energy. Considering in parallel the genetic/epigenetic changes and the probable entropy levels induced by stress-induced tetraploidisation provides a new systemic approach to describe cancer development.

Chromosome evolution screens recapitulate tissue-specific tumor aneuploidy patterns

Whole chromosome and arm-level copy number alterations occur at high frequencies in tumors, but their selective advantages, if any, are poorly understood. Here, utilizing unbiased whole chromosome genetic screens combined with in vitro evolution to generate arm- and subarm-level events, we iteratively selected the fittest karyotypes from aneuploidized human renal and mammary epithelial cells. Proliferation-based karyotype selection in these epithelial lines modeled tissue-specific tumor aneuploidy patterns in patient cohorts in the absence of driver mutations. Hi-C-based translocation mapping revealed that arm-level events usually emerged in multiples of two via centromeric translocations and occurred more frequently in tetraploids than diploids, contributing to the increased diversity in evolving tetraploid populations. Isogenic clonal lineages enabled elucidation of pro-tumorigenic mechanisms associated with common copy number alterations, revealing Notch signaling potentiation as a driver of 1q gain in breast cancer. We propose that intrinsic, tissue-specific proliferative effects underlie tumor copy number patterns in cancer.

Characterization of polyploidy in cancer: Current status and future perspectives

Various cancers frequently exhibit polyploidy, observed in a condition where a cell possesses more than two sets of chromosomes, which is considered a hallmark of the disease. The state of polyploidy often leads to aneuploidy, where cells possess an abnormal number or structure of chromosomes. Recent studies suggest that oncogenes contribute to aneuploidy. This finding significantly underscores its impact on cancer. Cancer cells exposed to certain chemotherapeutic drugs tend to exhibit an increased incidence of polyploidy. This occurrence is strongly associated with several challenges in cancer treatment, including metastasis, resistance to chemotherapy and the recurrence of malignant tumors. Indeed, it poses a significant hurdle to achieve complete tumor eradication and effective cancer therapy. Recently, there has been a growing interest in the field of polyploidy related to cancer for developing effective anti-cancer therapies. Polyploid cancer cells confer both advantages and disadvantages to tumor pathogenicity. This review delineates the diverse characteristics of polyploid cells, elucidates the pivotal role of polyploidy in cancer, and explores the advantages and disadvantages it imparts to cancer cells, along with the current approaches tried in lab settings to target polyploid cells. Additionally, it considers experimental strategies aimed at addressing the outstanding questions within the realm of polyploidy in relation to cancer.

NestedBD: Bayesian inference of phylogenetic trees from single-cell copy number profiles under a birth-death model

Copy number aberrations (CNAs) are ubiquitous in many types of cancer. Inferring CNAs from cancer genomic data could help shed light on the initiation, progression, and potential treatment of cancer. While such data have traditionally been available via "bulk sequencing," the more recently introduced techniques for single-cell DNA sequencing (scDNAseq) provide the type of data that makes CNA inference possible at the single-cell resolution. We introduce a new birth-death evolutionary model of CNAs and a Bayesian method, NestedBD, for the inference of evolutionary trees (topologies and branch lengths with relative mutation rates) from single-cell data. We evaluated NestedBD's performance using simulated data sets, benchmarking its accuracy against traditional phylogenetic tools as well as state-of-the-art methods. The results show that NestedBD infers more accurate topologies and branch lengths, and that the birth-death model can improve the accuracy of copy number estimation. And when applied to biological data sets, NestedBD infers plausible evolutionary histories of two colorectal cancer samples. NestedBD is available at https://github.com/Androstane/NestedBD .

Genomic landscape of diploid and aneuploid microsatellite stable early onset colorectal cancer

Although colorectal cancer (CRC) remains the second leading cause of cancer-related death in the United States, the overall incidence and mortality from the disease have declined in recent decades. In contrast, there has been a steady increase in the incidence of CRC in individuals under 50 years of age. Hereditary syndromes contribute disproportionately to early onset CRC (EOCRC). These include microsatellite instability high (MSI+) tumors arising in patients with Lynch Syndrome. However, most EOCRCs are not associated with familial syndromes or MSI+ genotypes. Comprehensive genomic profiling has provided the basis of improved more personalized treatments for older CRC patients. However, less is known about the basis of sporadic EOCRC. To define the genomic landscape of EOCRC we used DNA content flow sorting to isolate diploid and aneuploid tumor fractions from 21 non-hereditary cases. We then generated whole exome mutational profiles for each case and whole genome copy number, telomere length, and EGFR immunohistochemistry (IHC) analyses on subsets of samples. These results discriminate the molecular features of diploid and aneuploid EOCRC and provide a basis for larger population-based studies and the development of effective strategies to monitor and treat this emerging disease.

Evolution of chromosome-arm aberrations in breast cancer through genetic network rewiring

The basal breast cancer subtype is enriched for triple-negative breast cancer (TNBC) and displays consistent large chromosomal deletions. Here, we characterize evolution and maintenance of chromosome 4p (chr4p) loss in basal breast cancer. Analysis of The Cancer Genome Atlas data shows recurrent deletion of chr4p in basal breast cancer. Phylogenetic analysis of a panel of 23 primary tumor/patient-derived xenograft basal breast cancers reveals early evolution of chr4p deletion. Mechanistically we show that chr4p loss is associated with enhanced proliferation. Gene function studies identify an unknown gene, C4orf19, within chr4p, which suppresses proliferation when overexpressed-a member of the PDCD10-GCKIII kinase module we name PGCKA1. Genome-wide pooled overexpression screens using a barcoded library of human open reading frames identify chromosomal regions, including chr4p, that suppress proliferation when overexpressed in a context-dependent manner, implicating network interactions. Together, these results shed light on the early emergence of complex aneuploid karyotypes involving chr4p and adaptive landscapes shaping breast cancer genomes.

The prognostic and immunological role of MCM3 in pan-cancer and validation of prognosis in a clinical lower-grade glioma cohort

Background: Previous studies have shown that MCM3 plays a key role in initiating DNA replication. However, the mechanism of MCM3 function in most cancers is still unknown. The aim of our study was to explore the expression, prognostic role, and immunological characteristics of MCM3 across cancers. Methods: We explored the expression pattern of MCM3 across cancers. We subsequently explored the prognostic value of MCM3 expression by using univariate Cox regression analysis. Spearman correlation analysis was performed to determine the correlations between MCM3 and immune-related characteristics, mismatching repair (MMR) signatures, RNA modulator genes, cancer stemness, programmed cell death (PCD) gene expression, tumour mutation burden (TMB), microsatellite instability (MSI), and neoantigen levels. The role of MCM3 in predicting the response to immune checkpoint blockade (ICB) therapy was further evaluated in four immunotherapy cohorts. Single-cell data from CancerSEA were analysed to assess the biological functions associated with MCM3 in 14 cancers. The clinical correlation and independent prognostic significance of MCM3 were further analysed in the TCGA and CGGA lower-grade glioma (LGG) cohorts, and a prognostic nomogram was constructed. Immunohistochemistry in a clinical cohort was utilized to validate the prognostic utility of MCM3 expression in LGG. Results: MCM3 expression was upregulated in most tumours and strongly associated with patient outcomes in many cancers. Correlation analyses demonstrated that MCM3 expression was closely linked to immune cell infiltration, immune checkpoints, MMR genes, RNA modulator genes, cancer stemness, PCD genes and the TMB in most tumours. There was an obvious difference in outcomes between patients with high MCM3 expression and those with low MCM3 expression in the 4 ICB treatment cohorts. Single-cell analysis indicated that MCM3 was mainly linked to the cell cycle, DNA damage and DNA repair. The expression of MCM3 was associated with the clinical features of LGG patients and was an independent prognostic indicator. Finally, the prognostic significance of MCM3 in LGG was validated in a clinical cohort. Conclusion: Our study suggested that MCM3 can be used as a potential prognostic marker for cancers and may be associated with tumour immunity. In addition, MCM3 is a promising predictor of immunotherapy responses.

Machine-learning analysis reveals an important role for negative selection in shaping cancer aneuploidy landscapes

BACKGROUND

Aneuploidy, an abnormal number of chromosomes within a cell, is a hallmark of cancer. Patterns of aneuploidy differ across cancers, yet are similar in cancers affecting closely related tissues. The selection pressures underlying aneuploidy patterns are not fully understood, hindering our understanding of cancer development and progression.

RESULTS

Here, we apply interpretable machine learning methods to study tissue-selective aneuploidy patterns. We define 20 types of features corresponding to genomic attributes of chromosome-arms, normal tissues, primary tumors, and cancer cell lines (CCLs), and use them to model gains and losses of chromosome arms in 24 cancer types. To reveal the factors that shape the tissue-specific cancer aneuploidy landscapes, we interpret the machine learning models by estimating the relative contribution of each feature to the models. While confirming known drivers of positive selection, our quantitative analysis highlights the importance of negative selection for shaping aneuploidy landscapes. This is exemplified by tumor suppressor gene density being a better predictor of gain patterns than oncogene density, and vice versa for loss patterns. We also identify the importance of tissue-selective features and demonstrate them experimentally, revealing KLF5 as an important driver for chr13q gain in colon cancer. Further supporting an important role for negative selection in shaping the aneuploidy landscapes, we find compensation by paralogs to be among the top predictors of chromosome arm loss prevalence and demonstrate this relationship for one paralog interaction. Similar factors shape aneuploidy patterns in human CCLs, demonstrating their relevance for aneuploidy research.

CONCLUSIONS

Our quantitative, interpretable machine learning models improve the understanding of the genomic properties that shape cancer aneuploidy landscapes.

Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model

Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will only be maintained if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74-94% of the variance in aneuploid strains' growth rates is explained by the additive cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of snoRNAs and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.

Measuring cancer driving force of chromosomal aberrations through multi-layer Boolean implication networks

Multi-layer Complex networks are commonly used for modeling and analysing biological entities. This paper presents the advantage of using COMBO (Combining Multi Bio Omics) to suggest a new role of the chromosomal aberration as a cancer driver factor. Exploiting the heterogeneous multi-layer networks, COMBO integrates gene expression and DNA-methylation data in order to identify complex bilateral relationships between transcriptome and epigenome. We evaluated the multi-layer networks generated by COMBO on different TCGA cancer datasets (COAD, BLCA, BRCA, CESC, STAD) focusing on the effect of a specific chromosomal numerical aberration, broad gain in chromosome 20, on different cancer histotypes. In addition, the effect of chromosome 8q amplification was tested in the same TCGA cancer dataset. The results demonstrate the ability of COMBO to identify the chromosome 20 amplification cancer driver force in the different TCGA Pan Cancer project datasets.

Tubulin alpha-1b chain was identified as a prognosis and immune biomarker in pan-cancer combing with experimental validation in breast cancer

The α-tubulin subtype, Tubulin α-1b chain (TUBA1B), has been shown to influence immune cell infiltration, cancer growth, and survival across various malignancies. However, a comprehensive study has not yet been undertaken examining the immunological and predictive effects of TUBA1B in a pan-carcinoma context. Using data from TCGA, GEO, and other databases, we analyzed TUBA1B expression across various carcinoma types using transcriptional profiling, prognostic implications, genetic and epigenetic alterations, methylation patterns, and immunological significance. To validate our findings, we conducted Western blot analysis to assess TUBA1B protein levels in matched breast cancer tissue samples and performed CCK-8 proliferation assay, flow cytometry, transwell invasion, and migration assays to comprehensively examine the functional impact of TUBA1B on breast cancer cells. Our pan-cancer analysis found TUBA1B upregulation across most tumor types, with varying expression patterns in distinct immune and molecular subtypes. High TUBA1B expression was an independent risk factor and associated with poor prognoses in several cancers, including BRCA, KICH, LGG, LUAD, and MESO. TUBA1B also demonstrates moderate to high diagnostic accuracy in most tumor types. Increased m6A methylation levels were observed in the TUBA1B gene, while its promoter region displayed low methylation levels. TUBA1B's expression impacted some cancers by elevating tumor mutation burden, microsatellite instability, neoantigen formation, immune cell infiltration, and the modulation of immune checkpoints. Functional enrichment analysis highlights TUBA1B's involvement in important cellular processes such as the cell cycle, p53 signaling, cell senescence, programmed cell death, and the regulation of immune-related pathways. Moreover, our study reveals higher TUBA1B protein expression in breast cancer tissues compared to adjacent tissues. In vitro experiments confirm that TUBA1B deletion reduces breast cancer cell proliferation, invasion, and migration while increasing apoptosis. In conclusion, our study suggests that TUBA1B could potentially serve as a diagnostic marker for predicting cancer immunological profiles and survival outcomes and shed light on the expression and role of TUBA1B in breast cancer, providing a solid foundation for considering it as a promising therapeutic target for breast cancer patient treatment.

An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy

Aneuploidy is a hallmark of cancers, but the role of aneuploidy-related genes in lung adenocarcinoma (LUAD) and their prognostic value remain elusive. Gene expression and copy number variation (CNV) data were enrolled from TCGA and GEO database. Consistency clustering analysis was performed for molecular cluster. Tumor microenvironment was assessed by the xCell and ESTIMATE algorithm. Limma package was used for selecting differentially expressed genes (DEGs). LASSO and stepwise multivariate Cox regression analysis were used to establish an aneuploidy-related riskscore (ARS) signature. GDSC database was conducted to predict drug sensitivity. A nomogram was designed by rms R package. TCGA-LUAD patients were stratified into 3 clusters based on CNV data. The C1 cluster displayed the optimal survival advantage and highest inflammatory infiltration. Based on integrated intersecting DEGs, we constructed a 6-gene ARS model, which showed effective prediction for patient's survival. Drug sensitivity test predicted possible sensitive drugs in two risk groups. Additionally, the nomogram exhibited great predictive clinical treatment benefits. We established a 6-gene aneuploidy-related signature that could effectively predict the survival and therapy for LUAD patients. Additionally, the ARS model and nomogram could offer guidance for the preoperative estimation and postoperative therapy of LUAD.

CINner: modeling and simulation of chromosomal instability in cancer at single-cell resolution

Cancer development is characterized by chromosomal instability, manifesting in frequent occurrences of different genomic alteration mechanisms ranging in extent and impact. Mathematical modeling can help evaluate the role of each mutational process during tumor progression, however existing frameworks can only capture certain aspects of chromosomal instability (CIN). We present CINner, a mathematical framework for modeling genomic diversity and selection during tumor evolution. The main advantage of CINner is its flexibility to incorporate many genomic events that directly impact cellular fitness, from driver gene mutations to copy number alterations (CNAs), including focal amplifications and deletions, missegregations and whole-genome duplication (WGD). We apply CINner to find chromosome-arm selection parameters that drive tumorigenesis in the absence of WGD in chromosomally stable cancer types. We found that the selection parameters predict WGD prevalence among different chromosomally unstable tumors, hinting that the selective advantage of WGD cells hinges on their tolerance for aneuploidy and escape from nullisomy. Direct application of CINner to model the WGD proportion and fraction of genome altered (FGA) further uncovers the increase in CNA probabilities associated with WGD in each cancer type. CINner can also be utilized to study chromosomally stable cancer types, by applying a selection model based on driver gene mutations and focal amplifications or deletions. Finally, we used CINner to analyze the impact of CNA probabilities, chromosome selection parameters, tumor growth dynamics and population size on cancer fitness and heterogeneity. We expect that CINner will provide a powerful modeling tool for the oncology community to quantify the impact of newly uncovered genomic alteration mechanisms on shaping tumor progression and adaptation.

Remarkable chromosomes and karyotypes: A top 10 list

Chromosomes and karyotypes are particularly rich in oddities and extremes. Described below are 10 remarkable chromosomes and karyotypes sprinkled throughout the tree of life. These include variants in chromosome number, structure, and dynamics both natural and engineered. This versatility highlights the robustness and tolerance of the mitotic and meiotic machinery to dramatic changes in chromosome and karyotype architecture. These examples also illustrate that the robustness comes at a cost, enabling the evolution of chromosomes that subvert mitosis and meiosis.

The two sides of chromosomal instability: drivers and brakes in cancer

Chromosomal instability (CIN) is a hallmark of cancer and is associated with tumor cell malignancy. CIN triggers a chain reaction in cells leading to chromosomal abnormalities, including deviations from the normal chromosome number or structural changes in chromosomes. CIN arises from errors in DNA replication and chromosome segregation during cell division, leading to the formation of cells with abnormal number and/or structure of chromosomes. Errors in DNA replication result from abnormal replication licensing as well as replication stress, such as double-strand breaks and stalled replication forks; meanwhile, errors in chromosome segregation stem from defects in chromosome segregation machinery, including centrosome amplification, erroneous microtubule-kinetochore attachments, spindle assembly checkpoint, or defective sister chromatids cohesion. In normal cells, CIN is deleterious and is associated with DNA damage, proteotoxic stress, metabolic alteration, cell cycle arrest, and senescence. Paradoxically, despite these negative consequences, CIN is one of the hallmarks of cancer found in over 90% of solid tumors and in blood cancers. Furthermore, CIN could endow tumors with enhanced adaptation capabilities due to increased intratumor heterogeneity, thereby facilitating adaptive resistance to therapies; however, excessive CIN could induce tumor cells death, leading to the "just-right" model for CIN in tumors. Elucidating the complex nature of CIN is crucial for understanding the dynamics of tumorigenesis and for developing effective anti-tumor treatments. This review provides an overview of causes and consequences of CIN, as well as the paradox of CIN, a phenomenon that continues to perplex researchers. Finally, this review explores the potential of CIN-based anti-tumor therapy.

Human Papillomavirus-Induced Chromosomal Instability and Aneuploidy in Squamous Cell Cancers

Chromosomal instability (CIN) and aneuploidy are hallmarks of cancer. CIN is defined as a continuous rate of chromosome missegregation events over the course of multiple cell divisions. CIN causes aneuploidy, a state of abnormal chromosome content differing from a multiple of the haploid. Human papillomavirus (HPV) is a well-known cause of squamous cancers of the oropharynx, cervix, and anus. The HPV E6 and E7 oncogenes have well-known roles in carcinogenesis, but additional genomic events, such as CIN and aneuploidy, are often required for tumor formation. HPV+ squamous cancers have an increased frequency of specific types of CIN, including polar chromosomes. CIN leads to chromosome gains and losses (aneuploidies) specific to HPV+ cancers, which are distinct from HPV- cancers. HPV-specific CIN and aneuploidy may have implications for prognosis and therapeutic response and may provide insight into novel therapeutic vulnerabilities. Here, we review HPV-specific types of CIN and patterns of aneuploidy in squamous cancers, as well as how this impacts patient prognosis and treatment.

Specialized replication mechanisms maintain genome stability at human centromeres

The high incidence of whole-arm chromosome aneuploidy and translocations in tumors suggests instability of centromeres, unique loci built on repetitive sequences and essential for chromosome separation. The causes behind this fragility and the mechanisms preserving centromere integrity remain elusive. We show that replication stress, hallmark of pre-cancerous lesions, promotes centromeric breakage in mitosis, due to spindle forces and endonuclease activities. Mechanistically, we unveil unique dynamics of the centromeric replisome distinct from the rest of the genome. Locus-specific proteomics identifies specialized DNA replication and repair proteins at centromeres, highlighting them as difficult-to-replicate regions. The translesion synthesis pathway, along with other factors, acts to sustain centromere replication and integrity. Prolonged stress causes centromeric alterations like ruptures and translocations, as observed in ovarian cancer models experiencing replication stress. This study provides unprecedented insights into centromere replication and integrity, proposing mechanistic insights into the origins of centromere alterations leading to abnormal cancerous karyotypes.

Multi-omics pan-cancer analyses identify MCM4 as a promising prognostic and diagnostic biomarker

Minichromosome Maintenance Complex Component 4 (MCM4) is a vital component of the mini-chromosome maintenance complex family, crucial for initiating the replication of eukaryotic genomes. Recently, there has been a growing interest in investigating the significance of MCM4 in different types of cancer. Despite the existing research on this topic, a comprehensive analysis of MCM4 across various cancer types has been lacking. This study aims to bridge this knowledge gap by presenting a thorough pan-cancer analysis of MCM4, shedding light on its functional implications and potential clinical applications. The study utilized multi-omics samples from various databases. Bioinformatic tools were employed to explore the expression profiles, genetic alterations, phosphorylation states, immune cell infiltration patterns, immune subtypes, functional enrichment, disease prognosis, as well as the diagnostic potential of MCM4 and its responsiveness to drugs in a range of cancers. Our research demonstrates that MCM4 is closely associated with the oncogenesis, prognosis and diagnosis of various tumors and proposes that MCM4 may function as a potential biomarker in pan-cancer, providing a deeper understanding of its potential role in cancer development and treatment.

Single-cell RNA sequencing reveals epithelial cells driving brain metastasis in lung adenocarcinoma

Brain metastases (BM) of lung adenocarcinoma (LUAD) are the most common intracranial malignancy leading to death. However, the cellular origins and drivers of BM from LUAD have not been clarified. Cellular composition was characterized by single-cell sequencing analysis of primary lung adenocarcinoma (pLUAD), BM and lymph node metastasis (LNM) samples in GSE131907. Our study briefly analyzed the tumor microenvironment (TME), focusing on the role of epithelial cells (ECs) in BM. We have discovered a population of brain metastasis-associated epithelial cells (BMAECs) expressing SPP1, SAA1, and CDKN2A, and it has been observed that this population is mainly composed of aneuploid cells from pLUAD, playing a crucial role in brain metastasis. Our study concluded that both LNM and BM in LUAD originated from pLUAD lesions, but there is currently insufficient evidence to prove a direct association between BM lesions and LNM lesions, which provides inspiration for further investigation of the TME in BM.

The antagonistic relationship between apoptosis and polyploidy in development and cancer

One of the important functions of regulated cell death is to prevent cells from inappropriately acquiring extra copies of their genome, a state known as polyploidy. Apoptosis is the primary cell death mechanism that prevents polyploidy, and defects in this apoptotic response can result in polyploid cells whose subsequent error-prone chromosome segregation are a major contributor to genome instability and cancer progression. Conversely, some cells actively repress apoptosis to become polyploid as part of normal development or regeneration. Thus, although apoptosis prevents polyploidy, the polyploid state can actively repress apoptosis. In this review, we discuss progress in understanding the antagonistic relationship between apoptosis and polyploidy in development and cancer. Despite recent advances, a key conclusion is that much remains unknown about the mechanisms that link apoptosis to polyploid cell cycles. We suggest that drawing parallels between the regulation of apoptosis in development and cancer could help to fill this knowledge gap and lead to more effective therapies.

The oncogene cyclin D1 promotes bipolar spindle integrity under compressive force

The mitotic spindle is the bipolar, microtubule-based structure that segregates chromosomes at each cell division. Aberrant spindles are frequently observed in cancer cells, but how oncogenic transformation affects spindle mechanics and function, particularly in the mechanical context of solid tumors, remains poorly understood. Here, we constitutively overexpress the oncogene cyclin D1 in human MCF10A cells to probe its effects on spindle architecture and response to compressive force. We find that cyclin D1 overexpression increases the incidence of spindles with extra poles, centrioles, and chromosomes. However, it also protects spindle poles from fracturing under compressive force, a deleterious outcome linked to multipolar cell divisions. Our findings suggest that cyclin D1 overexpression may adapt cells to increased compressive stress, possibly contributing to its prevalence in cancers such as breast cancer by allowing continued proliferation in mechanically challenging environments.

Centrosome amplification and aneuploidy driven by the HIV-1-induced Vpr•VprBP•Plk4 complex in CD4+ T cells

HIV-1 infection elevates the risk of developing various cancers, including T-cell lymphoma. Whether HIV-1-encoded proteins directly contribute to oncogenesis remains unknown. We observe that approximately 1-5% of CD4+ T cells from the blood of people living with HIV-1 exhibit over-duplicated centrioles, suggesting that centrosome amplification underlies the development of HIV-1-associated cancers by driving aneuploidy. Through affinity purification, biochemical, and cellular analyses, we discover that Vpr, an accessory protein of HIV-1, hijacks the centriole duplication machinery and induces centrosome amplification and aneuploidy. Mechanistically, Vpr forms a cooperative ternary complex with an E3 ligase subunit, VprBP, and polo-like kinase 4 (Plk4). Unexpectedly, however, the complex enhances Plk4's functionality by promoting its relocalization to the procentriole assembly and induces centrosome amplification. Loss of either Vpr's C-terminal 17 residues or VprBP acidic region, the two elements required for binding to Plk4 cryptic polo-box, abrogates Vpr's capacity to induce these events. Furthermore, HIV-1 WT, but not its Vpr mutant, induces multiple centrosomes and aneuploidy in human primary CD4+ T cells. We propose that the Vpr•VprBP•Plk4 complex serves as a molecular link that connects HIV-1 infection to oncogenesis and that inhibiting the Vpr C-terminal motif may reduce the occurrence of HIV-1-associated cancers.

Scrambling the genome in cancer: causes and consequences of complex chromosome rearrangements

Complex chromosome rearrangements, known as chromoanagenesis, are widespread in cancer. Based on large-scale DNA sequencing of human tumours, the most frequent type of complex chromosome rearrangement is chromothripsis, a massive, localized and clustered rearrangement of one (or a few) chromosomes seemingly acquired in a single event. Chromothripsis can be initiated by mitotic errors that produce a micronucleus encapsulating a single chromosome or chromosomal fragment. Rupture of the unstable micronuclear envelope exposes its chromatin to cytosolic nucleases and induces chromothriptic shattering. Found in up to half of tumours included in pan-cancer genomic analyses, chromothriptic rearrangements can contribute to tumorigenesis through inactivation of tumour suppressor genes, activation of proto-oncogenes, or gene amplification through the production of self-propagating extrachromosomal circular DNAs encoding oncogenes or genes conferring anticancer drug resistance. Here, we discuss what has been learned about the mechanisms that enable these complex genomic rearrangements and their consequences in cancer.

Targeting chromosomal instability and aneuploidy in cancer

Cancer development and therapy resistance are driven by chromosomal instability (CIN), which causes chromosome gains and losses (i.e., aneuploidy) and structural chromosomal alterations. Technical limitations and knowledge gaps have delayed therapeutic targeting of CIN and aneuploidy in cancers. However, our toolbox for creating and studying aneuploidy in cell models has greatly expanded recently. Moreover, accumulating evidence suggests that seven conventional antimitotic chemotherapeutic drugs achieve clinical response by inducing CIN instead of mitotic arrest, although additional anticancer activities may also contribute in vivo. In this review, we discuss these recent developments. We also highlight new discoveries, which together show that 25 chromosome arm aneuploidies (CAAs) may be targetable by 36 drugs across 14 types of cancer. Collectively, these advances offer many new opportunities to improve cancer treatment.

DIAPH3 predicts survival of patients with MGMT-methylated glioblastoma

Background

Glioblastoma is one of the most aggressive primary brain tumors, with a poor outcome despite multimodal treatment. Methylation of the MGMT promoter, which predicts the response to temozolomide, is a well-established prognostic marker for glioblastoma. However, a difference in survival can still be detected within the MGMT methylated group, with some patients exhibiting a shorter survival than others, emphasizing the need for additional predictive factors.

Methods

We analyzed DIAPH3 expression in glioblastoma samples from the cancer genome atlas (TCGA). We also retrospectively analyzed one hundred seventeen histological glioblastomas from patients operated on at Saint-Luc University Hospital between May 2013 and August 2019. We analyzed the DIAPH3 expression, explored the relationship between mRNA levels and Patient's survival after the surgical resection. Finally, we assessed the methylation pattern of the DIAPH3 promoter using a targeted deep bisulfite sequencing approach.

Results

We found that 36% and 1% of the TCGA glioblastoma samples exhibit copy number alterations and mutations in DIAPH3, respectively. We scrutinized the expression of DIAPH3 at single cell level and detected an overlap with MKI67 expression in glioblastoma proliferating cells, including neural progenitor-like, oligodendrocyte progenitor-like and astrocyte-like states. We quantitatively analyzed DIAPH3 expression in our cohort and uncovered a positive correlation between DIAPH3 mRNA level and patient's survival. The effect of DIAPH3 was prominent in MGMT-methylated glioblastoma. Finally, we report that the expression of DIAPH3 is at least partially regulated by the methylation of three CpG sites in the promoter region.

Conclusion

We propose that combining the DIAPH3 expression with MGMT methylation could offer a better prediction of survival and more adapted postsurgical treatment for patients with MGMT-methylated glioblastoma.

miR-125 in Breast Cancer Etiopathogenesis: An Emerging Role as a Biomarker in Differential Diagnosis, Regenerative Medicine, and the Challenges of Personalized Medicine

Breast Cancer (BC) is one of the most common cancer types worldwide, and it is characterized by a complex etiopathogenesis, resulting in an equally complex classification of subtypes. MicroRNA (miRNA or miR) are small non-coding RNA molecules that have an essential role in gene expression and are significantly linked to tumor development and angiogenesis in different types of cancer. Recently, complex interactions among coding and non-coding RNA have been elucidated, further shedding light on the complexity of the roles these molecules fulfill in cancer formation. In this context, knowledge about the role of miR in BC has significantly improved, highlighting the deregulation of these molecules as additional factors influencing BC occurrence, development and classification. A considerable number of papers has been published over the past few years regarding the role of miR-125 in human pathology in general and in several types of cancer formation in particular. Interestingly, miR-125 family members have been recently linked to BC formation as well, and complex interactions (competing endogenous RNA networks, or ceRNET) between this molecule and target mRNA have been described. In this review, we summarize the state-of-the-art about research on this topic.

Intraoperative Flow Cytometry for the Rapid Diagnosis and Validation of Surgical Clearance of Non-Melanoma Skin Cancer: A Prospective Clinical Feasibility Study

Non-melanoma skin cancer (NMSC) is the most prevalent cancer in humans, with a high global incidence. We present a prospective clinical feasibility study on the use of intraoperative flow cytometry (iFC) for the instant diagnosis of NMSC and its complete surgical clearance. Flow cytometry, a laser-based technique, quantifies cell features, which has applications in cancer research. This study aim is to explore the potential applicability of iFC in detecting and characterizing NMSC and its surgical margins. In total, 30 patients who underwent diagnosis for NMSC were recruited. The method demonstrated high sensitivity (95.2%) and specificity (87.1%), with an accuracy of 91.1%, as confirmed with a receiver operating characteristic curve analysis. The results also indicated that most tumors were diploid, with two cases being hypoploid. The average G0/G1 fractions for normal and tumor tissue samples were 96.03 ± 0.30% and 88.03 ± 1.29%, respectively, with the tumor index escalating from 3.89 ± 0.30% to 11.95 ± 1.29% in cancerous cells. These findings underscore iFC's capability for precise intraoperative NMSC characterization and margin evaluation, promising enhanced complete tumor excision rates. Given the technique's successful application in various other malignancies, its implementation in NMSC diagnosis and treatment holds significant promise and warrants further research in clinical trials.

Aneuploidy-induced cellular behaviors: Insights from Drosophila

A balanced gene complement is crucial for proper cell function. Aneuploidy, the condition of having an imbalanced chromosome set, alters the stoichiometry of gene copy numbers and protein complexes and has dramatic consequences at the cellular and organismal levels. In humans, aneuploidy is associated with different pathological conditions including cancer, microcephaly, mental retardation, miscarriages, and aging. Over the last century, Drosophila has provided a valuable system for studying the consequences of systemic aneuploidies. More recently, it has contributed to the identification and molecular dissection of aneuploidy-induced cellular behaviors and their impact at the tissue and organismal levels. In this perspective, we review this active field of research, first by comparing knowledge from yeast, mouse, and human cells, then by highlighting the contributions of Drosophila. The aim of these discussions was to further our understanding of the functional interplay between aneuploidy, cell physiology, and tissue homeostasis in human development and disease.

Aneuploid embryonic stem cells drive teratoma metastasis

Aneuploidy, a deviation of the chromosome number from euploidy, is one of the hallmarks of cancer. High levels of aneuploidy are generally correlated with metastasis and poor prognosis in cancer patients. However, the causality of aneuploidy in cancer metastasis remains to be explored. Here we demonstrate that teratomas derived from aneuploid murine embryonic stem cells (ESCs), but not from isogenic diploid ESCs, disseminated to multiple organs, for which no additional copy number variations were required. Notably, no cancer driver gene mutations were identified in any metastases. Aneuploid circulating teratoma cells were successfully isolated from peripheral blood and showed high capacities for migration and organ colonization. Single-cell RNA sequencing of aneuploid primary teratomas and metastases identified a unique cell population with high stemness that was absent in diploid ESCs-derived teratomas. Further investigation revealed that aneuploid cells displayed decreased proteasome activity and overactivated endoplasmic reticulum (ER) stress during differentiation, thereby restricting the degradation of proteins produced from extra chromosomes in the ESC state and causing differentiation deficiencies. Noticeably, both proteasome activator Oleuropein and ER stress inhibitor 4-PBA can effectively inhibit aneuploid teratoma metastasis.

Aneuploidy and complex genomic rearrangements in cancer evolution

Mutational processes that alter large genomic regions occur frequently in developing tumors. They range from simple copy number gains and losses to the shattering and reassembly of entire chromosomes. These catastrophic events, such as chromothripsis, chromoplexy and the formation of extrachromosomal DNA, affect the expression of many genes and therefore have a substantial effect on the fitness of the cells in which they arise. In this review, we cover large genomic alterations, the mechanisms that cause them and their effect on tumor development and evolution.