Cumulative haploinsufficiency and triplosensitivity drive aneuploidy patterns and shape the cancer genome

Prolonged mitosis: A key indicator for detecting stressed and damaged cells

During mitosis, chromosomes condense, align to form a metaphase plate and segregate to the two daughter cells. Mitosis is one of the most complex recurring transformations in the life of a cell and requires a high degree of reliability to ensure the error-free transmission of genetic information to the next cell generation. An abnormally prolonged mitosis indicates potential defects that compromise genomic integrity. The mitotic stopwatch pathway detects even moderately prolonged mitoses by integrating memories of mitotic durations, ultimately leading to p53-mediated cell cycle arrest or death. This mechanism competes with mitogen signaling to stop the proliferation of damaged and potentially dangerous cells at a pre-oncogenic stage. Mitosis is a highly vulnerable phase, which is affected by multiple types of cellular damages and diverse stresses. We discuss the hypothesis that the duration of mitosis serves as an indicator of cell health.

Clinical implications of DNA ploidy, stroma, and nucleotyping in predicting peritoneal metastasis risk for gastric cancer

BACKGROUND

Gastric cancer peritoneal metastasis lacks effective predictive indices. This article retrospectively explored predictive values of DNA ploidy, stroma, and nucleotyping in gastric cancer peritoneal metastasis.

METHODS

A comprehensive analysis was conducted on specimens obtained from 80 gastric cancer patients who underwent gastric resection at the Department of Gastrointestinal Surgery of Wuhan University Renmin Hospital. Tumor tissues were sectioned and stained. DNA ploidy, stroma, and nucleotyping were quantified using microscopy and digital analysis software. Data analysis was employed by Pearson Chi-square, continuous correction Chi-square, and binary logistic regression.

RESULTS

Using both univariate and multivariate analysis, pathological T stage and nucleotyping exhibited a positive correlation with peritoneal metastasis. DNA ploidy and stroma showed a positive correlation in univariate analysis. Chi-square tests demonstrated a positive correlation of DNA ploidy, stroma, and nucleotyping with peritoneal metastasis. The combined application of these three indicators displayed heightened predictive value for peritoneal metastasis. Non-diploid status, high stroma, and chromosomal heterogeneity emerged as positive factors for peritoneal metastasis in gastric cancer.

CONCLUSIONS

DNA ploidy, stroma, and nucleotyping prove to be predictive factors for peritoneal metastasis, with enhanced predictive efficacy when combined in pairs.

Transposon mediated functional genomic screening for BRAF inhibitor resistance reveals convergent Hippo and MAPK pathway activation events

Genotype-informed anticancer therapies such as BRAF inhibitors can show remarkable clinical efficacy in BRAF-mutant melanoma; however, drug resistance poses a major hurdle to successful cancer treatment. Many resistance events to targeted therapies have been identified, suggesting a complex path to improve therapeutics. Here, we showed the utility of a piggyBac transposon activation mutagenesis screen for the efficient identification of genes that are resistant to BRAF inhibition in melanoma. Although several forward genetic screens performed in the same context have identified a broad range of resistance genes that poorly overlap, an integrative analysis revealed a much smaller functional diversity of resistance mechanisms, including reactivation of the MAPK pathway, PI3K-AKT pathway, and Hippo pathway, suggesting that a relatively small number of therapeutic strategies might overcome resistance manifested by a large gene set. Moreover, we illustrated the pivotal role of the Hippo pathway effector TAZ (encoded by the WWTR1 gene) in mediating BRAF inhibition resistance through transcriptional regulation of receptor tyrosine kinases and through interactions with the E3 ubiquitin ligase NEDD4L.

Comprehensive analysis of H3K27me3 LOCKs under different DNA methylation contexts reveal epigenetic redistribution in tumorigenesis

BACKGROUND

Histone modification H3K27me3 plays a critical role in normal development and is associated with various diseases, including cancer. This modification forms large chromatin domains, known as Large Organized Chromatin Lysine Domains (LOCKs), which span several hundred kilobases.

RESULT

In this study, we identify and categorize H3K27me3 LOCKs in 109 normal human samples, distinguishing between long and short LOCKs. Our findings reveal that long LOCKs are predominantly associated with developmental processes, while short LOCKs are enriched in poised promoters and are most associated with low gene expression. Further analysis of LOCKs in different DNA methylation contexts shows that long LOCKs are primarily located in partially methylated domains (PMDs), particularly in short-PMDs, where they are most likely responsible for the low expressions of oncogenes. We observe that in cancer cell lines, including those from esophageal and breast cancer, long LOCKs shift from short-PMDs to intermediate-PMDs and long-PMDs. Notably, a significant subset of tumor-associated long LOCKs in intermediate- and long-PMDs exhibit reduced H3K9me3 levels, suggesting that H3K27me3 compensates for the loss of H3K9me3 in tumors. Additionally, we find that genes upregulated in tumors following the loss of short LOCKs are typically poised promoter genes in normal cells, and their transcription is regulated by the ETS1 transcription factor.

CONCLUSION

These results provide new insights into the role of H3K27me3 LOCKs in cancer and underscore their potential impact on epigenetic regulation and disease mechanisms.

The effects of loss of Y chromosome on male health

Loss of Y chromosome (LOY) is the most commonly occurring post-zygotic (somatic) mutation in male individuals. The past decade of research suggests that LOY has important effects in shaping the activity of the immune system, and multiple studies have shown the effects of LOY on a range of diseases, including cancer, neurodegeneration, cardiovascular disease and acute infection. Epidemiological findings have been corroborated by functional analyses providing insights into the mechanisms by which LOY modulates the immune system; in particular, a causal role for LOY in cardiac fibrosis, bladder cancer and Alzheimer disease has been indicated. These insights show that LOY is a highly dynamic mutation (such that LOY clones expand and contract with time) and has pleiotropic, cell-type-specific effects. Here, we review the status of the field and highlight the potential of LOY as a biomarker and target of new therapeutics that aim to counteract its negative effects on the immune system.

Understanding Human Oncogene Function and Cooperativity in Myeloid Malignancy Using iPSCs

Myeloid malignancies are a spectrum of clonal disorders driven by genetic alterations that cooperatively confer aberrant self-renewal and differentiation of hematopoietic stem and progenitor cells (HSPCs). Induced pluripotent stem cells (iPSCs) can be differentiated into HSPCs and have been widely explored for modeling hematologic disorders and cell therapies. More recently, iPSCs models have been applied to study the origins and pathophysiology of myeloid malignancies, motivated by the appreciation for the differences in human oncogene function and the need for genetically defined models that recapitulate leukemia development. In this review, we will provide a broad overview of the rationale, the challenges, practical aspects, history, and recent advances of iPSC models for modeling myeloid neoplasms. We will focus on the insights into the previously unknown aspects of human oncogene function and cooperativity gained through the use of these models. It is now safe to say that iPSC models are a mainstay of leukemia modeling "toolbox" alongside primary human cells from normal and patient sources.

Pan-cancer analysis of biallelic inactivation in tumor suppressor genes identifies KEAP1 zygosity as a predictive biomarker in lung cancer

The canonical model of tumor suppressor gene (TSG)-mediated oncogenesis posits that loss of both alleles is necessary for inactivation. Here, through allele-specific analysis of sequencing data from 48,179 cancer patients, we define the prevalence, selective pressure for, and functional consequences of biallelic inactivation across TSGs. TSGs largely assort into distinct classes associated with either pan-cancer (Class 1) or lineage-specific (Class 2) patterns of selection for biallelic loss, although some TSGs are predominantly monoallelically inactivated (Class 3/4). We demonstrate that selection for biallelic inactivation can be utilized to identify driver genes in non-canonical contexts, including among variants of unknown significance (VUSs) of several TSGs such as KEAP1. Genomic, functional, and clinical data collectively indicate that KEAP1 VUSs phenocopy established KEAP1 oncogenic alleles and that zygosity, rather than variant classification, is predictive of therapeutic response. TSG zygosity is therefore a fundamental determinant of disease etiology and therapeutic sensitivity.

53BP1-mediated activation of the tumor suppressor p53

In recent years, the role of 53BP1 as a cell cycle regulator has come into the spotlight. 53BP1 is best understood for its role in controlling DNA double-strand break repair. However, 53BP1 was initially discovered as an interaction partner of the tumor suppressor p53, which proved to be independent of DNA repair. The importance of this interaction is becoming increasingly clear. 53BP1 responds to mitotic stress, which prolongs mitosis, or to DNA damage and triggers the stabilization of p53 by the deubiquitinase USP28 to stop the proliferation of potentially damaged cells. The ability of 53BP1 to respond to mitotic stress or DNA damage is controlled by cell cycle-specific post-translational modifications and is therefore restricted to specific cell cycle phases. 53BP1-mediated p53 activation is likely involved in tumor suppression and is associated with genetic diseases such as primary microcephaly. This review emphasizes the importance of these mechanisms for the development and maintenance of healthy tissues.

SHARPIN is a novel gene of colorectal cancer that promotes tumor growth potentially via inhibition of p53 expression

Colorectal cancer (CRC) is widely prevalent and represents a significant contributor to global cancer‑related mortality. There remains a pressing demand for advancements in CRC treatment modalities. The E3 ubiquitin ligase is a critical enzyme involved in modulating protein expression levels via posttranslational ubiquitin‑mediated proteolysis, and it is reportedly involved in the progression of various cancers, making it a target of recent interest in anticancer therapy. In the present study, using comprehensive expression analysis involving spatial transcriptomic analysis with single‑cell RNA sequencing in clinical CRC datasets, the ubiquitin‑associated protein Shank‑associated RH domain interactor (SHARPIN) was identified, located on amplified chromosome 8q, which could promote CRC progression. SHARPIN was found to be upregulated in tumor cells, with elevated expression observed in tumor tissues. This heightened expression of SHARPIN was positively associated with lymphatic invasion and served as an independent predictor of a poor prognosis in patients with CRC. In vitro and in vivo analyses using SHARPIN‑overexpressing or ‑knockout CRC cells revealed that SHARPIN overexpression upregulated MDM2, resulting in the downregulation of p53, while SHARPIN silencing or knockout downregulated MDM2, leading to p53 upregulation, which affects cell cycle progression, tumor cell apoptosis and tumor growth in CRC. Furthermore, SHARPIN was found to be overexpressed in several cancer types, exerting significant effects on survival outcomes. In conclusion, SHARPIN represents a newly identified novel gene with the potential to promote tumor growth following apoptosis inhibition and cell cycle progression in part by inhibiting p53 expression via MDM2 upregulation; therefore, SHARPIN represents a potential therapeutic target for CRC.

Towards simplified graph neural networks for identifying cancer driver genes in heterophilic networks

The identification of cancer driver genes is crucial for understanding the complex processes involved in cancer development, progression, and therapeutic strategies. Multi-omics data and biological networks provided by numerous databases enable the application of graph deep learning techniques that incorporate network structures into the deep learning framework. However, most existing methods do not account for the heterophily in the biological networks, which hinders the improvement of model performance. Meanwhile, feature confusion often arises in models based on graph neural networks in such graphs. To address this, we propose a Simplified Graph neural network for identifying Cancer Driver genes in heterophilic networks (SGCD), which comprises primarily two components: a graph convolutional neural network with representation separation and a bimodal feature extractor. The results demonstrate that SGCD not only performs exceptionally well but also exhibits robust discriminative capabilities compared to state-of-the-art methods across all benchmark datasets. Moreover, subsequent interpretability experiments on both the model and biological aspects provide compelling evidence supporting the reliability of SGCD. Additionally, the model can dissect gene modules, revealing clearer connections between driver genes in cancers. We are confident that SGCD holds potential in the field of precision oncology and may be applied to prognosticate biomarkers for a wide range of complex diseases.

Epigenome Reprogramming Through H3K27 and H3K4 Trimethylation as a Resistance Mechanism to DNA Methylation Inhibition in BRAFV600E-Mutated Colorectal Cancer

PURPOSE

BRAFV600E-mutated colorectal cancer exhibits a strong correlation with DNA hypermethylation, suggesting that this subgroup of tumors presents unique epigenomic phenotypes. Nonetheless, 5-azacitidine, which inhibits DNA methyltransferase activity, is not efficacious in BRAFV600E colorectal cancer in vivo.

EXPERIMENTAL DESIGN

We randomized and treated mice implanted with patient-derived tumor xenografts harboring BRAFV600E mutation with control, 5-azacitidine, vemurafenib (BRAF inhibitor), or the combination. Comprehensive epigenomic profiling was conducted on control and 5-azacitidine-treated tumor samples, including DNA methylation, histone modifications, chromatin accessibility, and gene expression. Combinations of epigenetic agents were explored in preclinical BRAFV600E colorectal cancer models.

RESULTS

A profound reduction of DNA methylation levels upon 5-azacitidine treatment was confirmed, however, transcriptional repression was not relieved. This study unbiasedly explored the adaptive engagement of other epigenomic modifications upon 5-azacitidine treatment. A loss of histone acetylation and a gain of histone methylations, including H3K27 and H3K4 trimethylation, were observed around these hypomethylated regions, suggesting the involvement of polycomb repressive complex (PRC) activity around the genome with loss of DNA methylation, therefore maintaining the repression of key tumor-suppressor genes. Combined inhibition of PRC activity through EZH2 inhibition with 5-azacitidine treatment additively improved efficacies in BRAFV600E colorectal cancer cells.

CONCLUSIONS

In conclusion, DNA hypomethylation by 5-azacitidine exhibits a close association with H3K27me3 and PRC activity in BRAFV600E colorectal cancer, and simultaneous blockade of DNA methyltransferase and EZH2 holds promise as a potential therapeutic strategy for patients with BRAFV600E-mutated colorectal cancer.

Relationship Between Loss of Y Chromosome and Urologic Cancers: New Future Perspectives

Background: The Y chromosome (ChrY) is essential for male sex determination and spermatogenesis. However, recent studies have revealed its broader role in various physiological processes and disease susceptibility, including cancer. Methods: A comprehensive literature review was conducted using databases like MEDLINE, Scopus, Web of Science, and Google Scholar. The review included clinical and preclinical studies in animals and humans focusing on the role of LoY in urological tumors. Data on the frequency of LoY, its clinical implications, and underlying mechanisms were extracted and analyzed. Results: The evidence suggests that LoY is associated with an increased risk of urologic neoplasms, potentially serving as an early marker of genomic instability. Studies reveal that LoY in urologic cancers correlates with worse survival outcomes and may contribute to tumor progression. LoY may interfere with chromatin structure and epigenetic regulation, suggesting its role as a contributor to early tumorigenesis. Conclusions: LoY appears to be a structural aberration with unique biological and clinical relevance in urologic cancers, possibly serving as a biomarker for genomic instability. Further research is necessary to identify specific Y-linked genes affected by LoY, potentially informing targeted therapies and early diagnostic strategies for these cancers.

WRAD core perturbation impairs DNA replication fidelity promoting immunoediting in pancreatic cancer

It is unclear how cells counteract the potentially harmful effects of uncoordinated DNA replication in the context of oncogenic stress. Here, we identify the WRAD (WDR5/RBBP5/ASH2L/DPY30) core as a modulator of DNA replication in pancreatic ductal adenocarcinoma (PDAC) models. Molecular analyses demonstrated that the WRAD core interacts with the replisome complex, with disruption of DPY30 resulting in DNA re-replication, DNA damage, and chromosomal instability (CIN) without affecting cancer cell proliferation. Consequently, in immunocompetent models, DPY30 loss induced T cell infiltration and immune-mediated clearance of highly proliferating cancer cells with complex karyotypes, thus improving anti-tumor efficacy upon anti-PD-1 treatment. In PDAC patients, DPY30 expression was associated with high tumor grade, worse prognosis, and limited response to immune checkpoint blockade. Together, our findings indicate that the WRAD core sustains genome stability and suggest that low intratumor DPY30 levels may identify PDAC patients who will benefit from immune checkpoint inhibitors.

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 be maintained only 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 cumulative cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of small nucleolar RNAs (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.

The History of Chromosomal Instability in Genome-Doubled Tumors

Tumors frequently display high chromosomal instability and contain multiple copies of genomic regions. Here, we describe Gain Route Identification and Timing In Cancer (GRITIC), a generic method for timing genomic gains leading to complex copy number states, using single-sample bulk whole-genome sequencing data. By applying GRITIC to 6,091 tumors, we found that non-parsimonious evolution is frequent in the formation of complex copy number states in genome-doubled tumors. We measured chromosomal instability before and after genome duplication in human tumors and found that late genome doubling was followed by an increase in the rate of copy number gain. Copy number gains often accumulate as punctuated bursts, commonly after genome doubling. We infer that genome duplications typically affect the landscape of copy number losses, while only minimally impacting copy number gains. In summary, GRITIC is a novel copy number gain timing framework that permits the analysis of copy number evolution in chromosomally unstable tumors. Significance: Complex genomic gains are associated with whole-genome duplications, which are frequent across tumors, span a large fraction of their genomes, and are linked to poorer outcomes. GRITIC infers when these gains occur during tumor development, which will help to identify the genetic events that drive tumor evolution. See related commentary by Taylor, p. 1766.

Recent insights into the causes and consequences of chromosome mis-segregation

Mitotic cells face the challenging task of ensuring accurate and equal segregation of their duplicated, condensed chromosomes between the nascent daughter cells. Errors in the process result in chromosome missegregation, a significant consequence of which is the emergence of aneuploidy-characterized by an imbalance in chromosome number-and the associated phenomenon of chromosome instability (CIN). Aneuploidy and CIN are common features of cancer, which leverages them to promote genome heterogeneity and plasticity, thereby facilitating rapid tumor evolution. Recent research has provided insights into how mitotic errors shape cancer genomes by inducing both numerical and structural chromosomal changes that drive tumor initiation and progression. In this review, we survey recent findings regarding the mitotic causes and consequences of aneuploidy. We discuss new findings into the types of chromosome segregation errors that lead to aneuploidy and novel pathways that protect genome integrity during mitosis. Finally, we describe new developments in our understanding of the immediate consequences of chromosome mis-segregation on the genome stability of daughter cells.

Aneuploidy as a driver of human cancer

Aneuploidy, an abnormal chromosome composition, is a major contributor to cancer development and progression and an important determinant of cancer therapeutic responses and clinical outcomes. Despite being recognized as a hallmark of human cancer, the exact role of aneuploidy as a 'driver' of cancer is still largely unknown. Identifying the specific genetic elements that underlie the recurrence of common aneuploidies remains a major challenge of cancer genetics. In this Review, we discuss recurrent aneuploidies and their function as drivers of tumor development. We then delve into the context-dependent identification and functional characterization of the driver genes underlying driver aneuploidies and examine emerging strategies to uncover these driver genes using cancer genomics data and cancer models. Lastly, we explore opportunities for targeting driver aneuploidies in cancer by leveraging the functional consequences of these common genetic alterations.

Establishment and validation of circulating cell-free DNA signatures for nasopharyngeal carcinoma detection

BACKGROUND

Early detection of nasopharyngeal carcinoma (NPC) poses a significant challenge. The absence of highly sensitive and specific diagnostic biomarkers for nasopharyngeal carcinoma contributes to the unfavourable prognosis of NPC patients. Here, we aimed to establish a non-invasive approach for detecting NPC using circulating cell-free DNA (cfDNA).

METHODS

We investigated the potential of next-generation sequencing (NGS) of peripheral blood cells as a diagnostic tool for NPC. We collected data on genome-wide nucleosome footprint (NF), 5'-end motifs, fragmentation patterns, CNV information, and EBV content from 553 Chinese subjects, including 234 NPC patients and 319 healthy individuals. Through case-control analysis, we developed a diagnostic model for NPC, and validated its detection capability.

FINDINGS

Our findings revealed that the frequencies of NF, fragmentation, and motifs were significantly higher in NPC patients compared to healthy controls. We developed an NPC score based on these parameters that accurately distinguished NPC from non-NPC cases according to the American Joint Committee on Cancer staging system from non-NPC (validation set: area under curve (AUC) = 99.9% (95% CI: 99.8%-100%), se: 98.15%, sp: 100%). This model showed superior performance over plasma EBV DNA. Additionally, the NPC score effectively differentiated between NPC patients and healthy controls, even after clinical treatment. Furthermore, the NPC score was found to be independent of potential confounders such as age, sex, or TNM stage.

INTERPRETATION

We have developed and verified a non-invasive approach with substantial potential for clinical application in detecting NPC.

FUNDING

A full list of funding bodies that contributed to this study can be found in Funding section.

Association of autosomal mosaic chromosomal alterations with risk of bladder cancer in Chinese adults: a prospective cohort study

Little is known about the prospective association between autosomal mosaic chromosomal alterations (mCAs), a group of large-scale somatic mutations on autosomes, and bladder cancer. Here we utilized data from 99,877 participants who were free of physician-diagnosed cancer at baseline (2004-2008) of the China Kadoorie Biobank to estimate the associations between autosomal mCAs and bladder cancer (ICD-10: C67). A total of 2874 autosomal mCAs events among 2612 carriers (2.6%) were detected. After a median follow-up of 12.4 years, we discovered that participants with all autosomal mCAs exhibited higher risks of bladder cancer, with a multivariable-adjusted hazard ratio (HR) (95% confidence interval [CI]) of 2.60 (1.44, 4.70). The estimate of such association was even stronger for mosaic loss events (HR [95% CI]: 6.68 [2.92, 15.30]), while it was not significant for CN-LOH events. Both expanded (cell fraction ≥10%) and non-expanded autosomal mCAs, as well as mosaic loss, were associated with increased risks of bladder cancer. Of interest, physical activity (PA) significantly modified the associations of autosomal mCAs and mosaic loss (Pinteraction = 0.038 and 0.012, respectively) with bladder cancer. The increased risks of bladder cancer were only observed with mCAs and mosaic loss among participants with a lower level of PA (HR [95% CI]: 5.11 [2.36, 11.09] and 16.30 [6.06, 43.81]), but not among participants with a higher level of PA. Our findings suggest that peripheral leukocyte autosomal mCAs may represent a novel risk factor for bladder cancer, and PA may serve as a potential intervention target for mCAs carriers.

Proteogenomic characterization of skull-base chordoma

Skull-base chordoma is a rare, aggressive bone cancer with a high recurrence rate. Despite advances in genomic studies, its molecular characteristics and effective therapies remain unknown. Here, we conduct integrative genomics, transcriptomics, proteomics, and phosphoproteomics analyses of 187 skull-base chordoma tumors. In our study, chromosome instability is identified as a prognostic predictor and potential therapeutic target. Multi-omics data reveals downstream effects of chromosome instability, with RPRD1B as a putative target for radiotherapy-resistant patients. Chromosome 1q gain, associated with chromosome instability and upregulated mitochondrial functions, lead to poorer clinical outcomes. Immune subtyping identify an immune cold subtype linked to chromosome 9p/10q loss and immune evasion. Proteomics-based classification reveals subtypes (P-II and P-III) with high chromosome instability and immune cold features, with P-II tumors showing increased invasiveness. These findings, confirmed in 17 paired samples, provide insights into the biology and treatment of skull-base chordoma.

Regulation of p53 by the mitotic surveillance/stopwatch pathway: implications in neurodevelopment and cancer

The transcription factor p53 (encoded by TP53) plays diverse roles in human development and disease. While best known for its role in tumor suppression, p53 signaling also influences mammalian development by triggering cell fate decisions in response to a wide variety of stresses. After over 4 decades of study, a new pathway that triggers p53 activation in response to mitotic delays was recently identified. Termed the mitotic surveillance or mitotic stopwatch pathway, the USP28 and 53BP1 proteins activate p53 in response to delayed mitotic progression to control cell fate and promote genomic stability. In this Minireview, I discuss its identification, potential roles in neurodevelopmental disorders and cancer, as well as explore outstanding questions about its function, regulation and potential use as a biomarker for anti-mitotic therapies.

SSCI: Self-Supervised Deep Learning Improves Network Structure for Cancer Driver Gene Identification

The pathogenesis of cancer is complex, involving abnormalities in some genes in organisms. Accurately identifying cancer genes is crucial for the early detection of cancer and personalized treatment, among other applications. Recent studies have used graph deep learning methods to identify cancer driver genes based on biological networks. However, incompleteness and the noise of the networks will weaken the performance of models. To address this, we propose a cancer driver gene identification method based on self-supervision for graph convolutional networks, which can efficiently enhance the structure of the network and further improve predictive accuracy. The reliability of SSCI is verified by the area under the receiver operating characteristic curves (AUROC), the area under the precision-recall curves (AUPRC), and the F1 score, with respective values of 0.966, 0.964, and 0.913. The results show that our method can identify cancer driver genes with strong discriminative power and biological interpretability.

RAD21 promotes oncogenesis and lethal progression of prostate cancer

Higher levels of aneuploidy, characterized by imbalanced chromosome numbers, are associated with lethal progression in prostate cancer. However, how aneuploidy contributes to prostate cancer aggressiveness remains poorly understood. In this study, we assessed in patients which genes on chromosome 8q, one of the most frequently gained chromosome arms in prostate tumors, were most strongly associated with long-term risk of cancer progression to metastases and death from prostate cancer (lethal disease) in 403 patients and found the strongest candidate was cohesin subunit gene, RAD21, with an odds ratio of 3.7 (95% CI 1.8, 7.6) comparing the highest vs. lowest tertiles of mRNA expression and adjusting for overall aneuploidy burden and Gleason score, both strong prognostic factors in primary prostate cancer. Studying prostate cancer driven by the TMPRSS2-ERG oncogenic fusion, found in about half of all prostate tumors, we found that increased RAD21 alleviated toxic oncogenic stress and DNA damage caused by oncogene expression. Data from both organoids and patients indicate that increased RAD21 thereby enables aggressive tumors to sustain tumor proliferation, and more broadly suggests one path through which tumors benefit from aneuploidy.

Identifying cooperating cancer driver genes in individual patients through hypergraph random walk

OBJECTIVE

Identifying cancer driver genes, especially rare or patient-specific cancer driver genes, is a primary goal in cancer therapy. Although researchers have proposed some methods to tackle this problem, these methods mostly identify cancer driver genes at single gene level, overlooking the cooperative relationship among cancer driver genes. Identifying cooperating cancer driver genes in individual patients is pivotal for understanding cancer etiology and advancing the development of personalized therapies.

METHODS

Here, we propose a novel Personalized Cooperating cancer Driver Genes (PCoDG) method by using hypergraph random walk to identify the cancer driver genes that cooperatively drive individual patient cancer progression. By leveraging the powerful ability of hypergraph in representing multi-way relationships, PCoDG first employs the personalized hypergraph to depict the complex interactions among mutated genes and differentially expressed genes of an individual patient. Then, a hypergraph random walk algorithm based on hyperedge similarity is utilized to calculate the importance scores of mutated genes, integrating these scores with signaling pathway data to identify the cooperating cancer driver genes in individual patients.

RESULTS

The experimental results on three TCGA cancer datasets (i.e., BRCA, LUAD, and COADREAD) demonstrate the effectiveness of PCoDG in identifying personalized cooperating cancer driver genes. These genes identified by PCoDG not only offer valuable insights into patient stratification correlating with clinical outcomes, but also provide an useful reference resource for tailoring personalized treatments.

CONCLUSION

We propose a novel method that can effectively identify cooperating cancer driver genes for individual patients, thereby deepening our understanding of the cooperative relationship among personalized cancer driver genes and advancing the development of precision oncology.

Tumor evolution metrics predict recurrence beyond 10 years in locally advanced prostate cancer

Cancer evolution lays the groundwork for predictive oncology. Testing evolutionary metrics requires quantitative measurements in controlled clinical trials. We mapped genomic intratumor heterogeneity in locally advanced prostate cancer using 642 samples from 114 individuals enrolled in clinical trials with a 12-year median follow-up. We concomitantly assessed morphological heterogeneity using deep learning in 1,923 histological sections from 250 individuals. Genetic and morphological (Gleason) diversity were independent predictors of recurrence (hazard ratio (HR) = 3.12 and 95% confidence interval (95% CI) = 1.34-7.3; HR = 2.24 and 95% CI = 1.28-3.92). Combined, they identified a group with half the median time to recurrence. Spatial segregation of clones was also an independent marker of recurrence (HR = 2.3 and 95% CI = 1.11-4.8). We identified copy number changes associated with Gleason grade and found that chromosome 6p loss correlated with reduced immune infiltration. Matched profiling of relapse, decades after diagnosis, confirmed that genomic instability is a driving force in prostate cancer progression. This study shows that combining genomics with artificial intelligence-aided histopathology leads to the identification of clinical biomarkers of evolution.

Large-scale copy number alterations are enriched for synthetic viability in BRCA1/BRCA2 tumors

BACKGROUND

Pathogenic BRCA1 or BRCA2 germline mutations contribute to hereditary breast, ovarian, prostate, and pancreatic cancer. Paradoxically, bi-allelic inactivation of BRCA1 or BRCA2 (bBRCA1/2) is embryonically lethal and decreases cellular proliferation. The compensatory mechanisms that facilitate oncogenesis in bBRCA1/2 tumors remain unclear.

METHODS

We identified recurrent genetic alterations enriched in human bBRCA1/2 tumors and experimentally validated if these improved proliferation in cellular models. We analyzed mutations and copy number alterations (CNAs) in bBRCA1/2 breast and ovarian cancer from the TCGA and ICGC. We used Fisher's exact test to identify CNAs enriched in bBRCA1/2 tumors compared to control tumors that lacked evidence of homologous recombination deficiency. Genes located in CNA regions enriched in bBRCA1/2 tumors were further screened by gene expression and their effects on proliferation in genome-wide CRISPR/Cas9 screens. A set of candidate genes was functionally validated with in vitro clonogenic survival and functional assays to validate their influence on proliferation in the setting of bBRCA1/2 mutations.

RESULTS

We found that bBRCA1/2 tumors harbor recurrent large-scale genomic deletions significantly more frequently than histologically matched controls (n = 238 cytobands in breast and ovarian cancers). Within the deleted regions, we identified 277 BRCA1-related genes and 218 BRCA2-related genes that had reduced expression and increased proliferation in bBRCA1/2 but not in wild-type cells in genome-wide CRISPR screens. In vitro validation of 20 candidate genes with clonogenic proliferation assays validated 9 genes, including RIC8A and ATMIN (ATM-Interacting protein). We identified loss of RIC8A, which occurs frequently in both bBRCA1/2 tumors and is synthetically viable with loss of both BRCA1 and BRCA2. Furthermore, we found that metastatic homologous recombination deficient cancers acquire loss-of-function mutations in RIC8A. Lastly, we identified that RIC8A does not rescue homologous recombination deficiency but may influence mitosis in bBRCA1/2 tumors, potentially leading to increased micronuclei formation.

CONCLUSIONS

This study provides a means to solve the tumor suppressor paradox by identifying synthetic viability interactions and causal driver genes affected by large-scale CNAs in human cancers.

Patterns of Aneuploidy and Signaling Consequences in Cancer

Aneuploidy, or a change in the number of whole chromosomes or chromosome arms, is a near-universal feature of cancer. Chromosomes affected by aneuploidy are not random, with observed cancer-specific and tissue-specific patterns. Recent advances in genome engineering methods have allowed the creation of models with targeted aneuploidy events. These models can be used to uncover the downstream effects of individual aneuploidies on cancer phenotypes including proliferation, apoptosis, metabolism, and immune signaling. Here, we review the current state of research into the patterns of aneuploidy in cancer and their impact on signaling pathways and biological processes.

Aberrant generation of dentate gyrus granule cells is associated with epileptic susceptibility in p53 conditional knockout mice

Neuronal apoptosis is a mechanism used to clear the cells of oxidative stress or DNA damage and refine the final number of neurons for a functional neuronal circuit. The tumor suppressor protein p53 is a key regulator of the cell cycle and serves as a checkpoint for eliminating neurons with high DNA damage, hyperproliferative signals or cellular stress. During development, p53 is largely expressed in progenitor cells. In the adult brain, p53 expression is restricted to the neurogenic niches where it regulates cell proliferation and self-renewal. To investigate the functional consequences of p53 deletion in the cortex and hippocampus, we generated a conditional mutant mouse (p53-cKO) in which p53 is deleted from pallial progenitors and their derivatives. Surprisingly, we did not find any significant change in the number of neurons in the mutant cortex or CA region of the hippocampus compared with control mice. However, p53-cKO mice exhibit more proliferative cells in the subgranular zone of the dentate gyrus and more granule cells in the granular cell layer. Glutamatergic synapses in the CA3 region are more numerous in p53-cKO mice compared with control littermates, which correlates with overexcitability and higher epileptic susceptibility in the mutant mice.

The effect of trisomic chromosomes on spatial genome organization and global transcription in embryonic stem cells

Aneuploidy frequently occurs in cancer and developmental diseases such as Down syndrome, with its functional consequences implicated in dosage effects on gene expression and global perturbation of stress response and cell proliferation pathways. However, how aneuploidy affects spatial genome organization remains less understood. In this study, we addressed this question by utilizing the previously established isogenic wild-type (WT) and trisomic mouse embryonic stem cells (mESCs). We employed a combination of Hi-C, RNA-seq, chromosome painting and nascent RNA imaging technologies to compare the spatial genome structures and gene transcription among these cells. We found that trisomy has little effect on spatial genome organization at the level of A/B compartment or topologically associating domain (TAD). Inter-chromosomal interactions are associated with chromosome regions with high gene density, active histone modifications and high transcription levels, which are confirmed by imaging. Imaging also revealed contracted chromosome volume and weakened transcriptional activity for trisomic chromosomes, suggesting potential implications for the transcriptional output of these chromosomes. Our data resources and findings may contribute to a better understanding of the consequences of aneuploidy from the angle of spatial genome organization.

Inference of chromosome selection parameters and missegregation rate in cancer from DNA-sequencing data

Aneuploidy is frequently observed in cancers and has been linked to poor patient outcome. Analysis of aneuploidy in DNA-sequencing (DNA-seq) data necessitates untangling the effects of the Copy Number Aberration (CNA) occurrence rates and the selection coefficients that act upon the resulting karyotypes. We introduce a parameter inference algorithm that takes advantage of both bulk and single-cell DNA-seq cohorts. The method is based on Approximate Bayesian Computation (ABC) and utilizes CINner, our recently introduced simulation algorithm of chromosomal instability in cancer. We examine three groups of statistics to summarize the data in the ABC routine: (A) Copy Number-based measures, (B) phylogeny tip statistics, and (C) phylogeny balance indices. Using these statistics, our method can recover both the CNA probabilities and selection parameters from ground truth data, and performs well even for data cohorts of relatively small sizes. We find that only statistics in groups A and C are well-suited for identifying CNA probabilities, and only group A carries the signals for estimating selection parameters. Moreover, the low number of CNA events at large scale compared to cell counts in single-cell samples means that statistics in group B cannot be estimated accurately using phylogeny reconstruction algorithms at the chromosome level. As data from both bulk and single-cell DNA-sequencing techniques becomes increasingly available, our inference framework promises to facilitate the analysis of distinct cancer types, differentiation between selection and neutral drift, and prediction of cancer clonal dynamics.

A pan-cancer interrogation of intronic polyadenylation and its association with cancer characteristics

3'UTR-APAs have been extensively studied, but intronic polyadenylations (IPAs) remain largely unexplored. We characterized the profiles of 22 260 IPAs in 9679 patient samples across 32 cancer types from the Cancer Genome Atlas cohort. By comparing tumor and paired normal tissues, we identified 180 ~ 4645 dysregulated IPAs in 132 ~ 2249 genes in each of 690 patient tumors from 22 cancer types that showed consistent patterns within individual cancer types. We selected 2741 genes that showed consistently patterns across cancer types, including 1834 pan-cancer tumor-enriched and 907 tumor-depleted IPA genes; the former were amply represented in the functional pathways such as deoxyribonucleic acid damage repair. Expression of IPA isoforms was associated with tumor mutation burden and patient characteristics (e.g. sex, race, cancer stages, and subtypes) in cancer-specific and feature-specific manners, and could be a more accurate prognostic marker than gene expression (summary of all isoforms). In summary, our study reveals the roles and the clinical relevance of tumor-associated IPAs.

Multitarget Pharmacology of Sulfur-Nitrogen Heterocycles: Anticancer and Antioxidant Perspectives

Cancer and oxidative stress are interrelated, with reactive oxygen species (ROS) playing crucial roles in physiological processes and oncogenesis. Excessive ROS levels can induce DNA damage, leading to cancer, and disrupt antioxidant defenses, contributing to diseases like diabetes and cardiovascular disorders. Antioxidant mechanisms include enzymes and small molecules that mitigate ROS damage. However, cancer cells often exploit oxidative conditions to evade apoptosis and promote tumor growth. Antioxidant therapy has shown mixed results, with timing and cancer-type influencing outcomes. Multifunctional drugs targeting multiple pathways offer a promising approach, reducing side effects and improving efficacy. Recent research focuses on sulfur-nitrogen heterocyclic derivatives for their dual antioxidant and anticancer properties, potentially enhancing therapeutic efficacy in oncology. The newly synthesized compounds often do not demonstrate both antioxidant and anticancer properties simultaneously. Heterocyclic rings are typically combined with phenyl groups, where hydroxy substitutions enhance antioxidant activity. On the other hand, electron-withdrawing substituents, particularly at the p-position on the phenyl ring, tend to enhance anticancer activity.

Copy number losses of oncogenes and gains of tumor suppressor genes generate common driver mutations

Cancer driver genes can undergo positive selection for various types of genetic alterations, including gain-of-function or loss-of-function mutations and copy number alterations (CNA). We investigated the landscape of different types of alterations affecting driver genes in 17,644 cancer exomes and genomes. We find that oncogenes may simultaneously exhibit signatures of positive selection and also negative selection in different gene segments, suggesting a method to identify additional tumor types where an oncogene is a driver or a vulnerability. Next, we characterize the landscape of CNA-dependent selection effects, revealing a general trend of increased positive selection on oncogene mutations not only upon CNA gains but also upon CNA deletions. Similarly, we observe a positive interaction between mutations and CNA gains in tumor suppressor genes. Thus, two-hit events involving point mutations and CNA are universally observed regardless of the type of CNA and may signal new therapeutic opportunities. An analysis with focus on the somatic CNA two-hit events can help identify additional driver genes relevant to a tumor type. By a global inference of point mutation and CNA selection signatures and interactions thereof across genes and tissues, we identify 9 evolutionary archetypes of driver genes, representing different mechanisms of (in)activation by genetic alterations.

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.

Liver cancer from the perspective of single-cell sequencing: a review combined with bibliometric analysis

BACKGROUND

Liver cancer (LC) is a prevalent malignancy and a leading cause of cancer-related mortality worldwide. Extensive research has been conducted to enhance patient outcomes and develop effective prevention strategies, ranging from molecular mechanisms to clinical interventions. Single-cell sequencing, as a novel bioanalysis technology, has significantly contributed to the understanding of the global cognition and dynamic changes in liver cancer. However, there is a lack of bibliometric analysis in this specific research area. Therefore, the objective of this study is to provide a comprehensive overview of the knowledge structure and research hotspots in the field of single-cell sequencing in liver cancer research through the use of bibliometrics.

METHOD

Publications related to the application of single-cell sequencing technology to liver cancer research as of December 31, 2023, were searched on the web of science core collection (WoSCC) database. VOSviewers, CiteSpace, and R package "bibliometrix" were used to conduct this bibliometric analysis.

RESULTS

A total of 331 publications from 34 countries, primarily led by China and the United States, were included in this study. The research focuses on the application of single cell sequencing technology to liver cancer, and the number of related publications has been increasing year by year. The main research institutions involved in this field are Fudan University, Sun Yat-Sen University, and the Chinese Academy of Sciences. Frontiers in Immunology and Nature Communications is the most popular journal in this field, while Cell is the most frequently co-cited journal. These publications are authored by 2799 individuals, with Fan Jia and Zhou Jian having the most published papers, and Llovet Jm being the most frequently co-cited author. The use of single cell sequencing to explore the immune microenvironment of liver cancer, as well as its implications in immunotherapy and chemotherapy, remains the central focus of this field. The emerging research hotspots are characterized by keywords such as 'Gene-Expression', 'Prognosis', 'Tumor Heterogeneity', 'Immunoregulation', and 'Tumor Immune Microenvironment'.

CONCLUSION

This is the first bibliometric study that comprehensively summarizes the research trends and developments on the application of single cell sequencing in liver cancer. The study identifies recent research frontiers and hot directions, providing a valuable reference for researchers exploring the landscape of liver cancer, understanding the composition of the immune microenvironment, and utilizing single-cell sequencing technology to guide and enhance the prognosis of liver cancer patients.

Oncogenes and tumor suppressor genes: functions and roles in cancers

Cancer, being the most formidable ailment, has had a profound impact on the human health. The disease is primarily associated with genetic mutations that impact oncogenes and tumor suppressor genes (TSGs). Recently, growing evidence have shown that X-linked TSGs have specific role in cancer progression and metastasis as well. Interestingly, our genome harbors around substantial portion of genes that function as tumor suppressors, and the X chromosome alone harbors a considerable number of TSGs. The scenario becomes even more compelling as X-linked TSGs are adaptive to key epigenetic processes such as X chromosome inactivation. Therefore, delineating the new paradigm related to X-linked TSGs, for instance, their crosstalk with autosome and involvement in cancer initiation, progression, and metastasis becomes utmost importance. Considering this, herein, we present a comprehensive discussion of X-linked TSG dysregulation in various cancers as a consequence of genetic variations and epigenetic alterations. In addition, the dynamic role of X-linked TSGs in sex chromosome-autosome crosstalk in cancer genome remodeling is being explored thoroughly. Besides, the functional roles of ncRNAs, role of X-linked TSG in immunomodulation and in gender-based cancer disparities has also been highlighted. Overall, the focal idea of the present article is to recapitulate the findings on X-linked TSG regulation in the cancer landscape and to redefine their role toward improving cancer treatment strategies.

Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

BACKGROUND

Rare oncogenic driver events, particularly affecting the expression or splicing of driver genes, are suspected to substantially contribute to the large heterogeneity of hematologic malignancies. However, their identification remains challenging.

METHODS

To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from 3760 patients spanning 24 disease entities. Taking advantage of our dataset size, we focused on discovering rare regulatory aberrations. Therefore, we called expression and splicing outliers using an extension of the workflow DROP (Detection of RNA Outliers Pipeline) and AbSplice, a variant effect predictor that identifies genetic variants causing aberrant splicing. We next trained a machine learning model integrating these results to prioritize new candidate disease-specific driver genes.

RESULTS

We found a median of seven expression outlier genes, two splicing outlier genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for already well-characterized driver genes, with odds ratios exceeding three among genes called in more than five samples. On held-out data, our integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Remarkably, we found a truncated form of the low density lipoprotein receptor LRP1B transcript to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B as a novel marker for a HCL-V subclass and a yet unreported functional role of LRP1B within these rare entities.

CONCLUSIONS

Altogether, our census of expression and splicing outliers for 24 hematologic malignancy entities and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.

Context-specific functions of chromatin remodellers in development and disease

Chromatin remodellers were once thought to be highly redundant and nonspecific in their actions. However, recent human genetic studies demonstrate remarkable biological specificity and dosage sensitivity of the thirty-two adenosine triphosphate (ATP)-dependent chromatin remodellers encoded in the human genome. Mutations in remodellers produce many human developmental disorders and cancers, motivating efforts to investigate their distinct functions in biologically relevant settings. Exquisitely specific biological functions seem to be an emergent property in mammals, and in many cases are based on the combinatorial assembly of subunits and the generation of stable, composite surfaces. Critical interactions between remodelling complex subunits, the nucleosome and other transcriptional regulators are now being defined from structural and biochemical studies. In addition, in vivo analyses of remodellers at relevant genetic loci have provided minute-by-minute insights into their dynamics. These studies are proposing new models for the determinants of remodeller localization and function on chromatin.

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.

Dynamics of karyotype evolution

In the evolution of species, the karyotype changes with a timescale of tens to hundreds of thousand years. In the development of cancer, the karyotype often is modified in cancerous cells over the lifetime of an individual. Characterizing these changes and understanding the mechanisms leading to them has been of interest in a broad range of disciplines including evolution, cytogenetics, and cancer genetics. A central issue relates to the relative roles of random vs deterministic mechanisms in shaping the changes. Although it is possible that all changes result from random events followed by selection, many results point to other non-random factors that play a role in karyotype evolution. In cancer, chromosomal instability leads to characteristic changes in the karyotype, in which different individuals with a specific type of cancer display similar changes in karyotype structure over time. Statistical analyses of chromosome lengths in different species indicate that the length distribution of chromosomes is not consistent with models in which the lengths of chromosomes are random or evolve solely by simple random processes. A better understanding of the mechanisms underlying karyotype evolution should enable the development of quantitative theoretical models that combine the random and deterministic processes that can be compared to experimental determinations of the karyotype in diverse settings.

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.

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.

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.

Control of cell proliferation by memories of mitosis

Mitotic duration is tightly constrained, and extended mitosis is characteristic of problematic cells prone to chromosome missegregation and genomic instability. We show here that mitotic extension leads to the formation of p53-binding protein 1 (53BP1)-ubiquitin-specific protease 28 (USP28)-p53 protein complexes that are transmitted to, and stably retained by, daughter cells. Complexes assembled through a Polo-like kinase 1-dependent mechanism during extended mitosis and elicited a p53 response in G1 that prevented the proliferation of the progeny of cells that experienced an approximately threefold extended mitosis or successive less extended mitoses. The ability to monitor mitotic extension was lost in p53-mutant cancers and some p53-wild-type (p53-WT) cancers, consistent with classification of TP53BP1 and USP28 as tumor suppressors. Cancers retaining the ability to monitor mitotic extension exhibited sensitivity to antimitotic agents.

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.

Dynamic interplay between human alpha-satellite DNA structure and centromere functions

Maintenance of genome stability relies on functional centromeres for correct chromosome segregation and faithful inheritance of the genetic information. The human centromere is the primary constriction within mitotic chromosomes made up of repetitive alpha-satellite DNA hierarchically organized in megabase-long arrays of near-identical higher order repeats (HORs). Centromeres are epigenetically specified by the presence of the centromere-specific histone H3 variant, CENP-A, which enables the assembly of the kinetochore for microtubule attachment. Notably, centromeric DNA is faithfully inherited as intact haplotypes from the parents to the offspring without intervening recombination, yet, outside of meiosis, centromeres are akin to common fragile sites (CFSs), manifesting crossing-overs and ongoing sequence instability. Consequences of DNA changes within the centromere are just starting to emerge, with unclear effects on intra- and inter-generational inheritance driven by centromere's essential role in kinetochore assembly. Here, we review evidence of meiotic selection operating to mitigate centromere drive, as well as recent reports on centromere damage, recombination and repair during the mitotic cell division. We propose an antagonistic pleiotropy interpretation to reconcile centromere DNA instability as both driver of aneuploidy that underlies degenerative diseases, while also potentially necessary for the maintenance of homogenized HORs for centromere function. We attempt to provide a framework for this conceptual leap taking into consideration the structural interface of centromere-kinetochore interaction and present case scenarios for its malfunctioning. Finally, we offer an integrated working model to connect DNA instability, chromatin, and structural changes with functional consequences on chromosome integrity.

Evolving copy number gains promote tumor expansion and bolster mutational diversification

The timing and fitness effect of somatic copy number alterations (SCNA) in cancer evolution remains poorly understood. Here we present a framework to determine the timing of a clonal SCNA that encompasses multiple gains. This involves calculating the proportion of time from its last gain to the onset of population expansion (lead time) as well as the proportion of time prior to its first gain (initiation time). Our method capitalizes on the observation that a genomic segment, while in a specific copy number (CN) state, accumulates point mutations proportionally to its CN. Analyzing 184 whole genome sequenced samples from 75 patients across five tumor types, we commonly observe late gains following early initiating events, occurring just before the clonal expansion relevant to the sampling. These include gains acquired after genome doubling in more than 60% of cases. Notably, mathematical modeling suggests that late clonal gains may contain final-expansion drivers. Lastly, SCNAs bolster mutational diversification between subpopulations, exacerbating the circle of proliferation and increasing heterogeneity.

Role of chromosomal cohesion and separation in aneuploidy and tumorigenesis

Cell division is a crucial process, and one of its essential steps involves copying the genetic material, which is organized into structures called chromosomes. Before a cell can divide into two, it needs to ensure that each newly copied chromosome is paired tightly with its identical twin. This pairing is maintained by a protein complex known as cohesin, which is conserved in various organisms, from single-celled ones to humans. Cohesin essentially encircles the DNA, creating a ring-like structure to handcuff, to keep the newly synthesized sister chromosomes together in pairs. Therefore, chromosomal cohesion and separation are fundamental processes governing the attachment and segregation of sister chromatids during cell division. Metaphase-to-anaphase transition requires dissolution of cohesins by the enzyme Separase. The tight regulation of these processes is vital for safeguarding genomic stability. Dysregulation in chromosomal cohesion and separation resulting in aneuploidy, a condition characterized by an abnormal chromosome count in a cell, is strongly associated with cancer. Aneuploidy is a recurring hallmark in many cancer types, and abnormalities in chromosomal cohesion and separation have been identified as significant contributors to various cancers, such as acute myeloid leukemia, myelodysplastic syndrome, colorectal, bladder, and other solid cancers. Mutations within the cohesin complex have been associated with these cancers, as they interfere with chromosomal segregation, genome organization, and gene expression, promoting aneuploidy and contributing to the initiation of malignancy. In summary, chromosomal cohesion and separation processes play a pivotal role in preserving genomic stability, and aberrations in these mechanisms can lead to aneuploidy and cancer. Gaining a deeper understanding of the molecular intricacies of chromosomal cohesion and separation offers promising prospects for the development of innovative therapeutic approaches in the battle against cancer.