BMB Reports 2024; 57(3): 125-134
Whole-genome doubling is a double-edged sword: the heterogeneous role of whole-genome doubling in various cancer types
Eunhyong Chang1,2 & Joon-Yong An1,2,3,*
1Department of Integrated Biomedical and Life Science, Korea University, Seoul 02841, 2L-HOPE Program for Community-Based Total Learning Health Systems, Korea University, Seoul 02841, 3School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul 02841, Korea
Correspondence to: Tel: +82-2-3290-5646; Fax: +82-2-916-5943; E-mail:
Received: December 12, 2023; Revised: February 1, 2024; Accepted: February 1, 2024; Published online: February 14, 2024.
© Korean Society for Biochemistry and Molecular Biology. All rights reserved.

cc This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Whole-genome doubling (WGD), characterized by the duplication of an entire set of chromosomes, is commonly observed in various tumors, occurring in approximately 30-40% of patients with different cancer types. The effect of WGD on tumorigenesis varies depending on the context, either promoting or suppressing tumor progression. Recent advances in genomic technologies and large-scale clinical investigations have led to the identification of the complex patterns of genomic alterations underlying WGD and their functional consequences on tumorigenesis progression and prognosis. Our comprehensive review aims to summarize the causes and effects of WGD on tumorigenesis, highlighting its dualistic influence on cancer cells. We then introduce recent findings on WGD-associated molecular signatures and genetic aberrations and a novel subtype related to WGD. Finally, we discuss the clinical implications of WGD in cancer subtype classification and future therapeutic interventions. Overall, a comprehensive understanding of WGD in cancer biology is crucial to unraveling its complex role in tumorigenesis and identifying novel therapeutic strategies.
Keywords: Cancer genomics, Genome instability, Pan-cancer, Personalized medicine, Whole-genome doubling

Whole-genome doubling (WGD), characterized by the duplication of a complete set of chromosomes, is prevalent in human cancers. It occurs in 30-40% of patients with different cancer types (1-3). Genomic studies have primarily focused on chromosomal alterations, including aneuploidy or somatic copy number alterations (SCNA), in tumor genomes. In contrast, WGD is a more specific phenomenon in which amplification occurs on the entire chromosome, involving molecular signatures and biological pathways in certain patients or cancer subtypes. WGD mitigates the detrimental effects of mutations and facilitates the rapid accrual of genetic aberrations, playing a pivotal role in tumorigenesis (2, 4-7). Conversely, cancer cells harboring WGD exhibit genomic instability that can culminate in apoptosis, senescence, and immune-mediated clearance (8-10). Therefore, WGD exerts a dualistic influence on cancer cells, concurrently conferring advantages and disadvantages. The precise influence of WGD on tumor advancement remains controversial and may profoundly vary with the specific tumor type under consideration. Although WGD has been implicated as a negative prognostic factor in colorectal, pancreatic, and breast cancers, contrasting studies have shown its association with improved survival outcomes in bladder urothelial carcinomas (1, 4, 11). Furthermore, the prevalence of WGD in different cancer types exhibits substantial heterogeneity (1, 2). Therefore, adopting a context-specific perspective when evaluating the role of WGD in cancer is imperative.

In this comprehensive review, we summarize the potential triggers of WGD and the mechanisms by which WGD influences tumor progression. Moreover, we highlight recent discoveries regarding WGD-associated molecular signatures across pan-cancer studies and diverse cancer types. Finally, we discuss the clinical applications of WGD with respect to cancer subtype classification and future therapeutic interventions.


Cause of WGD

Various scenarios that cause WGD can be divided into two categories: one in which the entire genome doubles within a single nucleus, and the other in which there are two or more nuclei within a single cell. Endoreduplication (mitotic bypass) and endomitosis (mitotic slippage) are the primary mechanisms driving genome doubling within a single nucleus (Fig. 1). These processes are triggered by replicative stress from various sources. A study illustrated that extensive telomere shortening in p53-deficient cells leads to replicative stress and prolonged DNA damage signaling, initiating endoreduplication, including bypassing mitosis and cell transitioning from G2 to G1. Subsequently, cells can enter a second S phase even without conventional mitosis, leading to WGD facilitated by the degradation of the replication inhibitors geminin and Wip1 through the action of APC/Cdh1 (12, 13). Moreover, in cells with functional p53, replicative stress resulting from CCNE1 amplification can activate APC/Cdh1, promoting endoreduplication (14). This indicates that regardless of p53 status, cells under replicative stress may undergo endoreduplication through APC/Cdh1 activation.

Endomitosis is similar to endoreduplication in that the cell division process is omitted, but the cells enter mitosis. If kinetochores are not properly attached to the mitotic spindles, the spindle assembly checkpoint (SAC) induces mitotic arrest before entering anaphase. Following SAC activation, cyclin B is continuously degraded via proteolysis, causing cells to exit mitosis and enter the G1 phase, eventually leading to a WGD event (15).

The presence of multiple nuclei within a single cell causes WGD in various instances, as observed during failure of cytokinesis, cell fusion, and entosis (Fig. 1). Cytokinesis is the last step of the cell cycle, involving the division of a cell into two daughter cells, and failure of this step generates cells with two nuclei, doubling the genome. Cytokinesis failure is one of the mechanisms that induces errors in chromosome segregation, such as chromosome non-disjunction, where one daughter cell contains both chromosome copies, promoting cleavage furrow defects and eventually leading to the formation of binucleated cells (16).

Cell fusion has also been implicated in WGD. The activation of oncogenes or inactivation of p53, combined with viral-induced cell fusion, can produce tetraploid primary human cells (17). This suggests that seemingly harmless viral infections can initiate cancer development by inducing WGD.

Entosis (cell cannibalism) is defined as a large cell engulfing a smaller cell, creating a cell-in-cell structure. The term “entosis” was coined after the Greek word entos, which means inside, into, or within. During entosis, two epithelial cells establish adherent junctions, facilitated by E-cadherin, followed by engulfment through a mechanism dependent on Rho-GTPase and Rho-kinase (18). Notably, entosis induces WGD by interfering with cell division, leading to the formation of binucleate engulfing cells, potentially contributing to tumor progression (19). Therefore, WGD may occur due to various circumstances, including errors in the cell cycle and the unification of two cells, ultimately contributing to tumorigenesis.

WGD promotes tumorigenesis

WGD plays a crucial role in promoting tumorigenesis, and several mechanisms and consequences contribute to its impact on cancer development. Initially considered an event predominantly relevant to evolution and certain physiological processes in specialized cell types, WGD is increasingly recognized as a crucial driver of tumorigenesis in humans. Unlike fish and amphibians, where polyploidization is well tolerated, WGD is not well tolerated in humans (20, 21). However, specialized human cell types, including hepatocytes, megakaryocytes, myoblasts, and trophoblasts, undergo physiological polyploidy to support wound healing and tissue regeneration (21). This physiological polyploidy provides the foundation for understanding the potential role of WGD in cancer development.

WGD promotes tumorigenesis due to an increase in the genetic material, conferring redundancy and genetic diversity to cancer cells. WGD may be a crucial evolutionary step that offers redundant genes, creating opportunities for new evolutionary pathways. Normal cells may exploit WGD as a short-term strategy to expand gene function for adapting to environmental stressors (22). Conversely, cancer cells, known for their rapid evolution, often undergo WGD events to mitigate detrimental somatic alterations and foster clonal evolution. This is particularly evident in cancers with a high rate of deleterious alterations, such as lung squamous cell carcinoma and triple-negative breast cancer (5).

The role of WGD in promoting tumorigenesis is associated with chromosomal instability (CIN). Most cancer cells are extensively aneuploid and exhibit dynamic karyotypic alterations involving the gain or loss of entire chromosomes. WGD often occurs early in cancer development, contributing to CIN, which expedites the gain of oncogenes and removal of tumor suppressor genes, driving tumorigenesis. This process involves the generation of tetraploid cells that serve as intermediates in promoting CIN and aneuploidy. Further, the existence of supernumerary centrosomes, a characteristic feature of tetraploid cells, contributes to aggressive tumor behavior and tumorigenesis (2, 17, 23-25).

Moreover, WGD-induced genomic instability can lead to the generation of multinucleated giant cells with proliferative potential and stem-like characteristics. These cells can undergo multipolar mitosis and revert to diploids, contributing to tumor relapse after initial therapy. This multistep process of evading cell death through WGD, followed by depolyploidization, has been implicated in tumor formation and therapy resistance (26-28).

Furthermore, a recent study revealed how WGD-positive cells acquire oncogenic properties by investigating the 3D chromatin architecture of mononucleate WGD cells lacking p53. In normal cells, chromosomes are spatially highly organized because their structure is crucial for normal gene expression. However, when cells undergo WGD, the boundaries between the active transcription site (compartment A) and the suppressed site (compartment B) become less distinct, resulting in the repositioning of chromatin sites linked to oncogenes into compartment A, whereas tumor suppressors are shifted to compartment B, leading to oncogenesis (9, 29).

Overall, tumorigenesis promotion by WGD involves diverse mechanisms, including expansion of genetic material, CIN, aneuploidy, and breakdown of conserved genomic topologies. This genomic complexity provides cancer cells with the raw materials and evolutionary flexibility necessary for rapid evolution and adaptation, making WGD a critical player in cancer development and progression.

WGD induces tumor suppressor pathways

A recent study revealed that cells accumulate significant DNA damage in the initial S phase after WGD, regardless of its origin (endoreduplication, endomitosis, or cytokinesis failure). Using single-cell DNA sequencing, this study revealed that WGD cells in S phase already exhibited aberrant karyotypes with several amplified and deleted genomic regions before their first division. This was attributed to a shortage of DNA replication factors during the S phase in WGD cells, leading to a reduction in replication sites and an increase in replication stress (30). This study demonstrated that DNA damage occurs immediately after WGD. In response to this damage signal, cells employ various mechanisms to suppress the proliferation of WGD cells by halting the cell cycle by activating the p53 and Hippo tumor suppressor pathways.

The tumor suppressor p53 plays a central role in inducing cell cycle arrest in genome-doubled cells resulting from various cellular events, as evidenced by several studies (1, 2, 10, 14). One study focused on p21WAF1, a transcriptional product of p53 that causes a G2 delay following DNA damage. Cells adapted to DNA damage after G2 delay, progressed to mitosis, experienced insufficient chromosome segregation, and re-entered the G1 phase in a tetraploid state. However, p21WAF1 again induced G1 arrest, blocking further cell proliferation (31). Notably, elevated levels of p21WAF1 and repression of Skp2 for CDK2 inactivation, hypophosphorylation of pRb, and elevated concentrations of cyclin E collectively prevent the dissemination of errors in mitosis (10, 32).

In addition to the DNA damage response, p53 is also activated by the Hippo tumor suppressor pathway. WGD activates LATS2 kinase, a key player in the Hippo tumor suppressor pathway, which inactivates the transcriptional regulators YAP and TAZ and stabilizes p53 (8). In addition, LATS2, in coordination with ASPP1, shunts p53 to pro-apoptotic promoters, promoting the death of polyploid cells (33). Collectively, these findings highlight the role of the Hippo tumor suppressor pathway and p53 in orchestrating cell cycle arrest and preventing the proliferation of WGD cells arising from replication stress.

Bypass of tumor suppressor pathway in WGD

WGD employs intricate strategies to circumvent tumor-suppressive effects, primarily through mutations in TP53 or other genes that disrupt the G1 arrest capabilities. Numerous studies have consistently identified TP53 mutations as the predominant gene alterations associated with WGD (1, 2, 34). Notably, even in TP53 wild-type tumors, WGD can emerge with a high SCNA background, including amplifications in MDM2, CCNE1, and CCND1 and deletions in CDKN2A, all of which are intricately linked to the E2F-mediated G1 to S transition (1, 34). These findings underscore the adaptability of WGD in navigating diverse genetic landscapes, employing alternative mechanisms to bypass tumor suppressor pathways and ensuring its progression in both TP53-mutated and wild-type contexts.



Several large-scale genomic studies have systematically investigated the genomic characteristics of WGD in various cancer types (Table 1). Quinton et al. analyzed approximately 10,000 primary tumor samples across 32 different tumor types from The Cancer Genome Atlas (TCGA) and found that approximately 36% of primary tumors experienced at least one WGD event during their evolutionary trajectory (2). Further, they estimated the WGD fraction in the entire genome using the ABSOLUTE algorithm (34, 35) and determined the WGD status of the tumors. WGD-positive tumors were significantly enriched for TP53 and PPPR21A mutations. Although genes involved in inflammatory processes were downregulated, WGD-positive tumors showed increased gene expression in cell proliferation and DNA repair pathways. Notably, KIF18A, a mitotic kinesin protein-encoding gene, was crucial for WGD-positive cell viability. Recently, Steele et al. scrutinized copy number alterations across 9,873 tumors and 33 cancer types from TCGA and found eight copy number signatures associated with WGD (36). These signatures included high ploidy (CN2, CN3), a focal LOH signature prior to genome doubling events (CN10, CN11), chromosomal instability in conjunction with one genome doubling event (CN12), and chromosomal- or arm-scale losses before WGD events (CN14, CN15, CN16).

Bielski et al. prospectively collected data from patients with advanced cancer (9,692 panel-based sequenced samples) and found that approximately 30% of the cases were WGD-positive (1). Similar to the findings of Quinton et al., WGD-positive tumors were significantly associated with TP53 mutations. However, a substantial proportion (46%) of WGD-positive tumors were TP53-wild-type and were enriched for RB1 and BAP1 mutations and CCNE1 amplification, indicating a deficiency in E2F-mediated G1 arrest.

In addition to the availability of large-scale genomic datasets, significant advances have been made in bioinformatics tools for predicting WGD in tumors. The FACETS algorithm, applicable to whole-genome sequencing (WGS), whole-exome sequencing (WES), and targeted sequencing data (37), was employed for WGD detection. Samples were defined as WGD-positive if the fraction of major allele copy number exceeded 2 across more than half of the autosomal genome. In a parallel study, the PURPLE algorithm was used to successfully detect WGD events in 56% of the cases from 2,520 pairs of metastatic solid tumors and normal tissue (38, 39). This algorithm is a purity ploidy estimator for WGS data and provides a comprehensive assessment of WGD status (39). Overall, these studies collectively are a valuable resource for WGD in tumors and the genetic associations and signatures of WGD across diverse cancer landscapes.

Lung cancer

Among all cancer types, lung cancer is the most common and exhibits one of the highest WGD frequencies. Notably, small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) were the second and seventh most frequent bearers of WGD events, respectively, in prospectively sequenced cohorts of patients with advanced cancer (1). Subtypes of NSCLC: lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LSCC) showed 59 and 55% prevalence of WGD, respectively, in TCGA datasets (2). Complementary insights gleaned from the TRACERx initiative, which offers multi-regional data, indicate that 77% of patients with NSCLC experience at least one WGD event during the course of tumor progression, with 19% of tumors harboring subclonal WGD events, suggesting that WGD predominantly constitutes an early event in NSCLC tumorigenesis (40).

The high incidence of WGD in lung cancer may be due to the high rate of LOH within these tumors (5). Analysis of the TRACERx and TCGA datasets revealed that LOH precedes WGD and that haploid LOH and the frequency of WGD events were correlated across various tumor types. Notably, LSCC exhibited an enrichment of widespread LOH and concurrent WGD. Using a simulation model to gain insights into the progression of lung cancer, this study revealed that the positive correlation between LOH and WGD arises from their complementary roles, whereas deleterious mutations within the LOH region have the potential to trigger cell death. The subsequent occurrence of WGD following LOH serves as a buffering mechanism by increasing the number of genome copies, thereby enhancing cell viability (5).

Further evidence suggests that oncogene co-mutations play a pivotal role in the context of WGD in lung cancer, with these driver mutations preceding WGD events. In particular, patients with EGFR/RB1/TP53-mutant lung cancer exhibit a higher propensity for WGD than patients with other lung cancers (41). Evolutionary history reconstructions employing timing models have underscored that mutations in TP53, RBM10, KRAS, and EGFR manifest earlier than WGD in lung cancer among never-smokers (42). In addition, multi-region sequencing of Asian patients with LUAD has revealed that several truncal alterations in TP53, CDKN2A, and RB1 collectively contribute to the dysregulation of the cell cycle and consequently to WGD (43). Moreover, multi-region sequencing of 401 patients with NSCLC showed that WGD in NSCLC is preceded by the TP53 mutation (40).

Smoking and high cytosine deaminase APOBEC-induced mutation loads are major risk factors for lung cancer. Notably, WGD is more likely to occur in tumors with smoking and APOBEC signatures in their genome. A truncal event of single-base substitution 4, a signature of smoking-induced mutations, increases the likelihood of subsequent WGD events in NSCLC (40). In ex-smokers with NSCLC, WGD tends to arise in the context of the smoking signature before subclonal diversification. However, in current smokers with sustained carcinogen exposure, the prevalence of smoking-related mutations diminished over time, whereas a signature representing the oncogenic mutations generated by some APOBEC family members increased, resulting in WGD after subclonal separation (44). Another study observed a correlation between APOBEC-associated mutations and EGFR/RB1/TP53 triple-mutant lung cancers, which were also associated with an increased risk of WGD events (41).

Therefore, although WGD is an early event in tumorigenesis, haploid LOH, co-mutations in oncogenes, smoking signatures, and APOBEC mutation signatures occur earlier than WGD in lung cancer. Despite the prevalence of WGD in lung cancers, the relationship between WGD and overall survival remains unclear, except for the notable observation that subclonal WGD appears to be a negative prognostic factor for NSCLC (40).

Breast cancer

Breast cancer is a malignancy frequently associated with WGD. WGD has been observed in approximately 44 and 58% of patients with primary and metastatic breast cancer, respectively (2, 38). Clinically, breast cancer is classified as hormone receptor-positive (characterized by the presence of the estrogen receptor or progesterone receptor), HER2-positive (regardless of the hormone receptor status), or triple-negative breast cancer (TNBC). The prevalence of WGD varies across these subtypes. TNBC and HER2-positive breast cancers exhibit a higher incidence of WGD than hormone receptor-positive breast cancer (5, 45). Furthermore, analysis of the haploid LOH proportion in these breast cancer subtypes has revealed interesting patterns. TNBC and hormone receptor-positive samples displayed high and low proportions of haploid LOH, respectively, corresponding to their WGD prevalence. However, HER2-positive breast cancer exhibited a high proportion of WGD despite a low proportion of haploid LOH, indicating a unique genomic landscape (5).

WGD is more likely to occur in metastatic or recurrent breast tumors than in primary breast cancers, and its role may differ between primary and recurrent tumors (2, 38, 46). Single-cell DNA sequencing of eight primary TNBC samples revealed that after multiple LOH events and WGD, chromosomal aberrations continued to develop during primary tumor growth in TNBC (47). Although WGD promotes tumor growth in primary tumors, WGD in recurrent tumors is associated with decreased cell proliferation and increased survival under stress conditions, decelerating tumor formation and tumor growth in HER2-driven breast cancer (46). Similar to lung cancer, LOH and oncogene mutations, including those in TP53, GATA3, PIK3CA, AKT1, and ERBB2, have been reported to occur before WGD in breast cancer (5, 47-49). Notably, sustained activation of the PI3K pathway due to PIK3CA mutations induces centrosome amplification and increases tolerance to spontaneous WGD (48).

WGD is associated with poor survival in patients with breast cancer (1, 45). In particular, among patients with ER-positive/HER2-negative breast cancer, those with TP53-wild-type tumors significantly associated with a worse prognosis, whereas TP53-mutant samples did not show such significance (1). As mutation load is not a predictive factor for prognosis in these patients, WGD is an independent predictor of survival in TP53-wild-type ER-positive and HER2-negative breast cancers (1). WGD frequently occurs in breast cancer, particularly in TNBC and HER2-positive breast cancers, and is more common in metastatic and relapsed tumors than in primary tumors. Both lung and breast cancers experience oncogenic mutations before WGD. However, although the prevalence of WGD in breast cancer is lower than that in lung cancer, it contributes to worse survival in breast cancer, which is not necessarily the case in lung cancer. This suggests that although WGD is prevalent in many types of cancer, its impact can vary among different cancer types.

Colorectal cancer

Previous research has consistently emphasized the pivotal role of WGD as a critical prognostic factor in colorectal cancer (CRC). Notably, one study revealed that among KRAS-mutant CRCs, patients undergoing WGD exhibited a notably worse prognosis than those without WGD. Notably, WGD itself, rather than the accompanying chromosomal aberrations, can be used to predict prognostic outcomes (1). WGD has a better predictive performance than aneuploidy, making it a valuable prognostic marker for high-risk CRCs (4).

Although patients with CRC have been classified into molecular subtypes (50), a recent study revealed a distinct subtype of a non-hypermutated WGD event. This subtype is characterized by focal amplification in MYC, IRS2, and EGFR, along with early functional loss of TP53. Additionally, WGD is more prevalent in early-onset CRC, suggesting unique genomic alterations in specific CRC subgroups (51). Mutation timing analysis revealed that WGD often occurs as an early event preceding copy number losses in the majority of CRC cases, with subsequent selection favoring the loss of chromosome 4q (4). Notably, tolerance to aneuploidy and chromosome segregation errors is increased in WGD tumors (4, 52), due to the deletion of several genes (52). For example, the loss of SPINT2 correlates with the bypassing of G1 arrest, and deletion of USP28 promotes centrosome clustering and facilitates cell proliferation.

Previous studies have demonstrated the clinical implications of WGD in CRC. A recent study analyzed the WES data of circulating tumor DNA (ctDNA) from 833 patients with CRC and found that WGD was associated with a 53% increased likelihood of detecting ctDNA (53). Therefore, WGD significantly enhances ctDNA detection, particularly in the early stages of disease, thereby aiding in the early detection of CRC. Another study revealed increased phosphorylation of the mitotic proteins KIF20B, TPX2, AURKA, and PLK1 in WGD cells through quantitative proteomic analysis of colorectal adenocarcinoma cell lines. Importantly, WGD in CRC cells exhibits heightened sensitivity to compounds targeting PLK1, suggesting that applying PLK1 inhibitors in patients with WGD-positive colon cancer may be a promising therapeutic strategy (54). Therefore, a comprehensive understanding of WGD may further delineate better diagnostic and therapeutic strategies, ultimately improving the outcomes for patients with CRC with WGD.

Pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC), characterized by its aggressiveness and limited therapeutic options, is a formidable adversary in the field of oncology. Recent studies have found a positive correlation between WGD and the metastatic potential of PDAC (55, 56). One study identified five distinct subtypes of PDAC, each associated with unique molecular signatures (55). Notably, basal-like-A and -B subtypes demonstrated intriguing links between KRAS imbalance and ploidy status, with minor and major imbalances in diploid and tetraploid tumors, respectively. Furthermore, a high frequency of KRAS imbalance and WGD was observed in metastatic PDAC tumors, indicating the role of WGD in fostering KRAS imbalance during metastatic progression.

Additionally, WGD in PDAC is intricately linked to the evolutionary dynamics of the disease. WGD tumors have a high incidence of TP53 mutations and chromothripsis, a phenomenon of catastrophic genome rearrangement. A study revealed that chromothripsis occurred on chromosomes 8 and 15 before WGD and on chromosomes 13, 16, and 18 after WGD. Further, patients with chromothripsis had worse overall survival, indicating the clinical implications of these genomic aberrations (57). Another study further elucidated genomic evolution during PDAC development. The sequential phases involved LOH in TP53, accretion of deletions, WGD, and increased amplification, suggesting stepwise progression of genomic alterations and a complex landscape in advanced PDAC (58). Owing to its association with metastasis and involvement in the evolutionary dynamics of the disease, WGD has emerged as a central player in the intricate interplay of genetic alterations in PDAC.


Despite the small fraction of patients with WGD (2, 34, 38), investigations have consistently reported instances of chromosomal amplification in glioblastomas. A comprehensive analysis of 40 glioblastomas using fluorescence in situ hybridization (FISH) identified 26 cases with an excess of chromosome 7 copies, of which 17 exhibited high-level EGFR gene amplification as extra-chromosomal circular DNA (ecDNA) (59). This was further delineated by a copy number signature (CN8) that was strongly correlated with ecDNA (36). In glioblastomas, this signature is enriched on chromosome 7, where the EGFR is located. This signature has also been described as a large-amplicon phenotype, referred to as tyfonas (60). Chromosome 7 amplification occurs before WGD in glioblastoma (34). Chromosomal 12q amplification has also been frequently reported in glioblastomas. WGS and FISH data from glioblastoma showed that CDK4 and MDM2 were located in 12q, possibly due to chromothripsis (61), which further showed an association with the large-amplicon phenotype, tyfonas (60). A patient with 12q amplification showed substantial disease remission after personalized treatment with the CDK4/6 inhibitors, nelfinavir, and leflunomide (62).

Therefore, understanding intratumor heterogeneity within glioblastomas and its relationship with WGD is essential. One study revealed a correlation between the co-occurrence of EGFR and CDK4 amplification and increased infiltration of immunosuppressive macrophages in glioblastoma using spatial protein profiling and single-cell spatial mapping of FISH (63). This highlights the importance of high-throughput assessment at the single-cell level for predicting the immune state of glioblastoma, which is a critical factor in devising effective therapeutic strategies. The evolution and clonal dynamics of WGD in glioblastomas have also been investigated. An in-depth analysis of a recurrent glioblastoma case revealed that a clonal IDH1 mutation was later supplanted by a WGD event and translocation between the PDGFRA and CDK4 regions of amplification. The disease progressed despite rapid sequencing and targeted therapy, underscoring the complexity of WGD-driven glioblastoma and the challenges in managing its evolution (64).


Understanding the mechanisms underlying WGD in cancer has significant implications for developing novel therapeutic interventions. Targeting the vulnerabilities associated with WGD, such as specific genes or pathways, holds promise for more effective and selective cancer treatments. A notable example is the identification of KIF18A as a potential therapeutic target for WGD-positive tumors (2). Furthermore, multi-omics studies integrating genomic and proteomic datasets of cancer patients (65) have revealed some proliferative subtypes characterized by chromosomal instability and upregulated cell cycle or proliferation pathways (3, 66-72). This implicates WGD as the underlying biological mechanism of these subtypes. Further investigation is required to elucidate the key phospho-signaling pathways and guide the development of targeted therapies for WGD subtypes.

Moreover, the clinical impact of WGD extends to the prediction of patient responses to antitumor treatments. Recent research has indicated that patients with metastatic melanoma with WGD exhibit better responses to immune checkpoint blockade (73). This observation highlights the potential utility of WGD as a predictive marker for treatment response in specific cancers. To further elucidate the role of WGD in cancer, in-depth investigations into tumor microenvironments and intratumor heterogeneity are crucial. Single-cell DNA or RNA-seq data may be useful for providing insight into how WGD influences these aspects of cancer biology. Continued research in this direction will contribute to a more comprehensive understanding of the role of WGD in cancer and its potential applications in personalized medicine.


WGD can emerge in various scenarios, and its impact on tumor progression varies greatly. Recent discoveries leveraging large-cohort genomics and transcriptomics have demonstrated how WGD shapes the development of malignancies in each tumor type and how it can be used for personalized therapies. Further studies are warranted to understand how WGD affects the tumor microenvironment and identify novel therapeutic target proteins to cure tumors with WGD. In addition, as WGD occurs early in tumorigenesis, more research is required to employ WGD for the early detection of tumors.


This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2019M3E5D3073568 and NRF-2021R1A4A1029097 to J.Y.A.) and Korea University to J.Y.A. E.H.C. received a scholarship from the Kwanjeong Educational Foundation and the Brain Korea (BK21) FOUR education program.


The authors have no conflicting interests.

Fig. 1. Possible causes and effects of WGD. WGD can arise from diverse scenarios, categorized into introduction within a single nucleus and introduction by multiple nuclei. WGD exhibits dual effects, either promoting or suppressing tumors. Tumor-suppressing pathways can induce cell death, but these can be bypassed through TP53 mutations or other genetic alterations associated with E2F-mediated G1 to S transition. The figure is created with

Findings and genetic alterations associated with WGD in diverse cancer types

Study Cancer type Description Genomic associations
Quinton et al. (2021) Pan-cancer Up-regulation of a spindle-assembly checkpoint, DNA-replication factors, and proteasome pathways in WGD tumors TP53/PPPR21A mutations
Priestley et al. (2019) Pan-cancer A high frequency of WGD in metastatic tumors
Lopez et al. (2020) Pan-cancer WGD is caused by the high rate of LOH, especially in LSCC and TNBC TP53/PTEN/ZNF750, NOTCH1/SMAD4 mutations in LOH region
Bielski et al. (2018) Pan-cancer Association of WGD in wild-type TP53 with G1 arrest defect me diated by E2F CCNE1 amplification, RB1/BAP1 mutations
Carter et al. (2012) Pan-cancer A high frequency of WGD in epithelial cancers, such as colorectal, breast, lung, ovarian, and esophageal cancers; a high incidence of WGD in recurrent tumors LOH in chromosome 9 and 10, and gains of chromosome 7 in glioblastoma
Offin et al. (2019) Lung cancer APOBEC-associated mutations and EGFR/RB1/TP53 triple mutants EGFR/RB1/TP53 mutations
Zhang et al. (2021) NSCLC WGD in never smokers with tumor-suppressor gene mutations TP53/RBM10/KRAS/EGFR mutations
Frankell et al. (2023) NSCLC Negative prognosis associated with sub-clonal WGD TP53 mutation, SBS4 signature
Bruin et al. (2014) NSCLC APOBEC signature related to WGD after sub-clonal separation in smokers APOBEC signature
Nahar et al. (2018) LUAD WGD in EGFR-mutant Asian LUADs with truncal alterations including TP53, and loss of CDKN2A and RB1 TP53/CDKN2A/RB1 mutations
Berenjeno et al. (2017) Breast cancer Centrosome amplification and WGD led by PIK3CA activation PIK3CA mutation
Choudhary et al. (2016) Breast cancer A high frequency of TNBC and Her2 positive tumors; a higher risk of recurrence and death in WGD tumors
Yates et al. (2017) Breast cancer Oncogene mutations including TP53, GATA3, PI3KCA, AKT1, and ERBB2 occur before WGD in primary breast cancers TP53/GATA3/PI3KCA, AKT1/ERBB2 mutations
Newcomb et al. (2021) Her2-driven breast cancer A frequency of WGD in recurrent tumors and decreased tumor growth
Minussi et al. (2021) TNBC WGD caused by clonal TP53 mutation and LOH in primary TNBC and consequent transient genomic instability after WGD TP53 mutation and LOH
Kim et al. (2021) CRC A higher frequency of WGD in early-onset CRC than in late-onset CRC, especially in non-hypermutated early-onset CRC TP53/APC mutations; focal amplifications in MYC, IRS2, and EGFR
Kabel et al. (2023) CRC Increased ctDNA detection likelihood, especially in early-stage disease, significantly augments with WGD presence
Dewhurst et al. (2014) CRC WGD’s early occurrence in CRC enhances aneuploidy tolerance and chromosome segregation error resilience, correlating with poorprognosis and heightened sensitivity for high-risk CRC detection compared to aneuploidy alone Chromosome 4q loss
Benhard et al. (2021) CRC WGD enhances cell proliferation by boosting mitogenic signaling, establishing bipolar spindles, and reducing cell cycle inhibitor and DNA damage signaling SPINT2 and USP28 loss
Vigano et al. (2018) COAD Up-regulation of stress and interferon signaling pathways in WGD; increased phosphorylation of mitotic proteins (KIF20B, TPX2, AURKA, and PLK1)
Chan-seng-yue et al. (2020) PDAC High frequency of WGD in metastatic PDAC and its association with mutant KRAS imbalance KRAS mutation
Baslan et al. (2022) PDAC Genomic progression in the development of PDAC via WGD LOH in TP53
Notta et al. (2016) PDAC A high frequency of chromothripsis in WGD associated with poor outcome and metastasis TP53 mutation
Sakamoto et al. (2020) PDAC A high frequency of WGD in metastatic tumors
Favero et al. (2015) Glioblastoma Subsequent replacement of clonal IDH1 mutation by WGD in recurrent tumors Translocation between PDGFRA-CDK4 amplification

WGD: Whole-genome doubling; NSCLC: Non-small cell lung cancer; LUAD: Lung adenocarcinoma; TNBC: Triple-negative breast cancer; CRC: Colorectal cancer; COAD: Colorectal adenocarcinoma; PDAC: Pancreatic ductal adenocarcinoma; ctDNA: Circulating tumor DNA; LOH: Loss-of-heterozygosity; SBS4 signature: Single base substitution signature 4. It is one of the mutation signatures documented by the Catalogue Of Somatic Mutations In Cancer (COSMIC). This signature indicates direct DNA damage by mutagens in tobacco smoke (74).

  1. Bielski CM, Zehir A and Penson AV et al (2018) Genome doubling shapes the evolution and prognosis of advanced cancers. Nat Genet 50, 1189-1195.
    Pubmed KoreaMed CrossRef
  2. Quinton RJ, DiDomizio A and Vittoria MA et al (2021) Whole-genome doubling confers unique genetic vulnerabilities on tumour cells. Nature 590, 492-497.
    Pubmed KoreaMed CrossRef
  3. Gillette MA, Satpathy S and Cao S et al (2020) Proteogenomic characterization reveals therapeutic vulnerabilities in lung adenocarcinoma. Cell 182, 200-225.
    Pubmed KoreaMed CrossRef
  4. Dewhurst SM, McGranahan N and Burrell RA et al (2014) Tolerance of whole-genome doubling propagates chromosomal instability and accelerates cancer genome evolution. Cancer Discov 4, 175-185.
    Pubmed KoreaMed CrossRef
  5. Lopez S, Lim EL and Horswell S et al (2020) Interplay between whole-genome doubling and the accumulation of deleterious alterations in cancer evolution. Nat Genet 52, 283-293.
    Pubmed KoreaMed CrossRef
  6. Ganem NJ and Pellman D (2007) Limiting the proliferation of polyploid cells. Cell 131, 437-440.
    Pubmed CrossRef
  7. Fujiwara T, Bandi M, Nitta M, Ivanova EV, Bronson RT and Pellman D (2005) Cytokinesis failure generating tetraploids promotes tumorigenesis in p53-null cells. Nature 437, 1043-1047.
    Pubmed CrossRef
  8. Ganem NJ, Cornils H and Chiu SY et al (2014) Cytokinesis failure triggers hippo tumor suppressor pathway activation. Cell 158, 833-848.
    Pubmed KoreaMed CrossRef
  9. Senovilla L, Vitale I and Martins I et al (2012) An immunosurveillance mechanism controls cancer cell ploidy. Science 337, 1678-1684.
    Pubmed CrossRef
  10. Andreassen PR, Lohez OD, Lacroix FB and Margolis RL (2001) Tetraploid state induces p53-dependent arrest of nontransformed mammalian cells in G1. Mol Biol Cell 12, 1315-1328.
    Pubmed KoreaMed CrossRef
  11. Sanz-Gomez N, Gonzalez-Alvarez M, De Las Rivas J and de Carcer G (2023) Whole-genome doubling as a source of cancer: how, when, where, and why?. Front Cell Dev Biol 11, 1209136.
    Pubmed KoreaMed CrossRef
  12. Davoli T, Denchi EL and de Lange T (2010) Persistent telomere damage induces bypass of mitosis and tetraploidy. Cell 141, 81-93.
    Pubmed KoreaMed CrossRef
  13. Jeong HC, Gil NY and Lee HS et al (2015) Timely degradation of Wip1 phosphatase by APC/C activator protein Cdh1 is necessary for normal mitotic progression. J Cell Biochem 116, 1602-1612.
    Pubmed CrossRef
  14. Zeng J, Hills SA, Ozono E and Diffley JFX (2023) Cyclin E-induced replicative stress drives p53-dependent whole-genome duplication. Cell 186, 528-542.
    Pubmed CrossRef
  15. Brito DA and Rieder CL (2006) Mitotic checkpoint slippage in humans occurs via cyclin B destruction in the presence of an active checkpoint. Curr Biol 16, 1194-1200.
    Pubmed KoreaMed CrossRef
  16. Shi Q and King RW (2005) Chromosome nondisjunction yields tetraploid rather than aneuploid cells in human cell lines. Nature 437, 1038-1042.
    Pubmed CrossRef
  17. Duelli DM, Padilla-Nash HM, Berman D, Murphy KM, Ried T and Lazebnik Y (2007) A virus causes cancer by inducing massive chromosomal instability through cell fusion. Curr Biol 17, 431-437.
    Pubmed CrossRef
  18. Overholtzer M, Mailleux AA and Mouneimne G et al (2007) A nonapoptotic cell death process, entosis, that occurs by cell-in-cell invasion. Cell 131, 966-979.
    Pubmed CrossRef
  19. Krajcovic M, Johnson NB and Sun Q et al (2011) A non-genetic route to aneuploidy in human cancers. Nat Cell Biol 13, 324-330.
    Pubmed KoreaMed CrossRef
  20. Gjelsvik KJ, Besen-McNally R and Losick VP (2019) Solving the polyploid mystery in health and disease. Trends Genet 35, 6-14.
    Pubmed KoreaMed CrossRef
  21. Edgar BA, Zielke N and Gutierrez C (2014) Endocycles: a recurrent evolutionary innovation for post-mitotic cell growth. Nat Rev Mol Cell Biol 15, 197-210.
    Pubmed CrossRef
  22. Duncan AW, Taylor MH and Hickey RD et al (2010) The ploidy conveyor of mature hepatocytes as a source of genetic variation. Nature 467, 707-710.
    Pubmed KoreaMed CrossRef
  23. Al-Rawi DH and Bakhoum SF (2022) Chromosomal instability as a source of genomic plasticity. Curr Opin Genet Dev 74, 101913.
    Pubmed KoreaMed CrossRef
  24. Olaharski AJ, Sotelo R and Solorza-Luna G et al (2006) Tetraploidy and chromosomal instability are early events during cervical carcinogenesis. Carcinogenesis 27, 337-343.
    Pubmed CrossRef
  25. Song S, Jung S and Kwon M (2023) Expanding roles of centrosome abnormalities in cancers. BMB Rep 56, 216-224.
    Pubmed KoreaMed CrossRef
  26. King RW (2008) When 2+2=5: the origins and fates of aneuploid and tetraploid cells. Biochim Biophys Acta 1786, 4-14.
    Pubmed KoreaMed CrossRef
  27. Coward J and Harding A (2014) Size does matter: why polyploid tumor cells are critical drug targets in the war on cancer. Front Oncol 4, 123.
    Pubmed KoreaMed CrossRef
  28. Zhang J, Qiao Q, Xu H, Zhou R and Liu X (2022) Human cell polyploidization: the good and the evil. Semin Cancer Biol 81, 54-63.
    Pubmed CrossRef
  29. Lambuta RA, Nanni L and Liu Y et al (2023) Whole-genome doubling drives oncogenic loss of chromatin segregation. Nature 615, 925-933.
    Pubmed KoreaMed CrossRef
  30. Gemble S, Wardenaar R and Keuper K et al (2022) Genetic instability from a single S phase after whole-genome duplication. Nature 604, 146-151.
    Pubmed KoreaMed CrossRef
  31. Andreassen PR, Lacroix FoB, Lohez OD and Margolis RL (2001) Neither p21WAF1 nor 14-3-3σ prevents G2 progression to mitotic catastrophe in human colon carcinoma cells after DNA damage, but p21WAF1 induces stable G1 arrest in resulting tetraploid cells. Cancer Res 61, 7660-7668.
  32. Jo Y and Shin DY (2017) Repression of the F-box protein Skp2 is essential for actin damage-induced tetraploid G1 arrest. BMB Rep 50, 379-383.
    Pubmed KoreaMed CrossRef
  33. Aylon Y, Ofir-Rosenfeld Y and Yabuta N et al (2010) The Lats2 tumor suppressor augments p53-mediated apoptosis by promoting the nuclear proapoptotic function of ASPP1. Genes Dev 24, 2420-2429.
    Pubmed KoreaMed CrossRef
  34. Carter SL, Cibulskis K and Helman E et al (2012) Absolute quantification of somatic DNA alterations in human cancer. Nat Biotechnol 30, 413-421.
    Pubmed KoreaMed CrossRef
  35. Taylor AM, Shih J and Ha G et al (2018) Genomic and functional approaches to understanding cancer aneuploidy. Cancer Cell 33, 676-689.
    Pubmed KoreaMed CrossRef
  36. Steele CD, Abbasi A and Islam SMA et al (2022) Signatures of copy number alterations in human cancer. Nature 606, 984-991.
    Pubmed KoreaMed CrossRef
  37. Shen R and Seshan VE (2016) FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic Acids Res 44, e131.
    Pubmed KoreaMed CrossRef
  38. Priestley P, Baber J and Lolkema MP et al (2019) Pan-cancer whole-genome analyses of metastatic solid tumours. Nature 575, 210-216.
    Pubmed KoreaMed CrossRef
  39. Cameron DL, Baber J and Shale C et al (2019) GRIDSS, PURPLE, LINX: unscrambling the tumor genome via integrated analysis of structural variation and copy number. BioRxiv, 781013.
  40. Frankell AM, Dietzen M and Al Bakir M et al (2023) The evolution of lung cancer and impact of subclonal selection in TRACERx. Nature 616, 525-533.
    Pubmed KoreaMed CrossRef
  41. Offin M, Chan JM and Tenet M et al (2019) Concurrent RB1 and TP53 alterations define a subset of EGFR-mutant lung cancers at risk for histologic transformation and inferior clinical outcomes. J Thorac Oncol 14, 1784-1793.
    Pubmed KoreaMed CrossRef
  42. Zhang T, Joubert P and Ansari-Pour N et al (2021) Genomic and evolutionary classification of lung cancer in never smokers. Nat Genet 53, 1348-1359.
    Pubmed KoreaMed CrossRef
  43. Nahar R, Zhai W and Zhang T et al (2018) Elucidating the genomic architecture of Asian EGFR-mutant lung adenocarcinoma through multi-region exome sequencing. Nat Commun 9, 216.
    Pubmed KoreaMed CrossRef
  44. De Bruin EC, McGranahan N and Mitter R et al (2014) Spatial and temporal diversity in genomic instability processes defines lung cancer evolution. Science 346, 251-256.
    Pubmed KoreaMed CrossRef
  45. Choudhary A, Zachek B and Lera RF et al (2016) Identification of selective lead compounds for treatment of high-ploidy breast cancer. Mol Cancer Ther 15, 48-59.
    Pubmed KoreaMed CrossRef
  46. Newcomb R, Dean E, McKinney BJ and Alvarez JV (2021) Context-dependent effects of whole-genome duplication during mammary tumor recurrence. Sci Rep 11, 14932.
    Pubmed KoreaMed CrossRef
  47. Minussi DC, Nicholson MD and Ye H et al (2021) Breast tumours maintain a reservoir of subclonal diversity during expansion. Nature 592, 302-308.
    Pubmed KoreaMed CrossRef
  48. Berenjeno IM, Pineiro R and Castillo SD et al (2017) Oncogenic PIK3CA induces centrosome amplification and tolerance to genome doubling. Nat Commun 8, 1773.
    Pubmed KoreaMed CrossRef
  49. Yates LR, Knappskog S and Wedge D et al (2017) Genomic evolution of breast cancer metastasis and relapse. Cancer Cell 32, 169-184.
    Pubmed KoreaMed CrossRef
  50. Guinney J, Dienstmann R and Wang X et al (2015) The consensus molecular subtypes of colorectal cancer. Nat Med 21, 1350-1356.
    Pubmed KoreaMed CrossRef
  51. Kim JE, Choi J and Sung CO et al (2021) High prevalence of TP53 loss and whole-genome doubling in early-onset colorectal cancer. Exp Mol Med 53, 446-456.
    Pubmed KoreaMed CrossRef
  52. Cohen-Sharir Y, McFarland JM and Abdusamad M et al (2021) Aneuploidy renders cancer cells vulnerable to mitotic checkpoint inhibition. Nature 590, 486-491.
    Pubmed KoreaMed CrossRef
  53. Kabel J, Henriksen TV and Demuth C et al (2023) Impact of whole genome doubling on detection of circulating tumor DNA in colorectal cancer. Cancers 15, 1136.
    Pubmed KoreaMed CrossRef
  54. Vigano C, von Schubert C and Ahrne E et al (2018) Quantitative proteomic and phosphoproteomic comparison of human colon cancer DLD-1 cells differing in ploidy and chromosome stability. Mol Biol Cell 29, 1031-1047.
    Pubmed KoreaMed CrossRef
  55. Chan-Seng-Yue M, Kim JC and Wilson GW et al (2020) Transcription phenotypes of pancreatic cancer are driven by genomic events during tumor evolution. Nat Genet 52, 231-240.
    Pubmed CrossRef
  56. Sakamoto H, Attiyeh MA and Gerold JM et al (2020) The evolutionary origins of recurrent pancreatic cancer. Cancer Discov 10, 792-805.
    Pubmed KoreaMed CrossRef
  57. Notta F, Chan-Seng-Yue M and Lemire M et al (2016) A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns. Nature 538, 378-382.
    Pubmed KoreaMed CrossRef
  58. Baslan T, Morris JPt and Zhao Z et al (2022) Ordered and deterministic cancer genome evolution after p53 loss. Nature 608, 795-802.
    Pubmed KoreaMed CrossRef
  59. Lopez-Gines C, Gil-Benso R and Ferrer-Luna R et al (2010) New pattern of EGFR amplification in glioblastoma and the relationship of gene copy number with gene expression profile. Mod Pathol 23, 856-865.
    Pubmed CrossRef
  60. Hadi K, Yao X and Behr JM et al (2020) Distinct classes of complex structural variation uncovered across thousands of cancer genome graphs. Cell 183, 197-210.
    Pubmed KoreaMed CrossRef
  61. Furgason JM, Koncar RF and Michelhaugh SK et al (2015) Whole genome sequence analysis links chromothripsis to EGFR, MDM2, MDM4, and CDK4 amplification in glioblastoma. Oncoscience 2, 618.
    Pubmed KoreaMed CrossRef
  62. Castro MP, Khanlou N and Fallah A et al (2022) Targeting chromosome 12q amplification in relapsed glioblastoma: the use of computational biological modeling to identify effective therapy-a case report. Ann Transl Med 10, 1289.
    Pubmed KoreaMed CrossRef
  63. Walentynowicz KA, Engelhardt D and Cristea S et al (2023) Single-cell heterogeneity of EGFR and CDK4 co-amplification is linked to immune infiltration in glioblastoma. Cell Rep 42, 112235.
    Pubmed KoreaMed CrossRef
  64. Favero F, McGranahan N and Salm M et al (2015) Glioblastoma adaptation traced through decline of an IDH1 clonal driver and macro-evolution of a double-minute chromosome. Ann Oncol 26, 880-887.
    Pubmed KoreaMed CrossRef
  65. Heo YJ, Hwa C, Lee GH, Park JM and An JY (2021) Integrative multi-omics approaches in cancer research: from biological networks to clinical subtypes. Mol Cells 44, 433-443.
    Pubmed KoreaMed CrossRef
  66. Satpathy S, Krug K and Jean Beltran PM et al (2021) A proteogenomic portrait of lung squamous cell carcinoma. Cell 184, 4348-4371.
    Pubmed KoreaMed CrossRef
  67. Krug K, Jaehnig EJ and Satpathy S et al (2020) Proteogenomic landscape of breast cancer tumorigenesis and targeted therapy. Cell 183, 1436-1456.
    Pubmed KoreaMed CrossRef
  68. Huang C, Chen L and Savage SR et al (2021) Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma. Cancer Cell 39, 361-379.
    Pubmed KoreaMed CrossRef
  69. Dou Y, Kawaler EA and Cui Zhou D et al (2020) Proteogenomic characterization of endometrial carcinoma. Cell 180, 729-748.
    Pubmed KoreaMed CrossRef
  70. Cao L, Huang C and Cui Zhou D et al (2021) Proteogenomic characterization of pancreatic ductal adenocarcinoma. Cell 184, 5031-5052.
    Pubmed KoreaMed CrossRef
  71. Wang LB, Karpova A and Gritsenko MA et al (2021) Proteogenomic and metabolomic characterization of human glioblastoma. Cancer Cell 39, 509-528.
    Pubmed KoreaMed CrossRef
  72. Vasaikar S, Huang C and Wang X et al (2019) Proteogenomic analysis of human colon cancer reveals new therapeutic opportunities. Cell 177, 1035-1049.
    Pubmed KoreaMed CrossRef
  73. Tarantino G, Ricker CA and Wang A et al (2022) Genomic heterogeneity and ploidy identify patients with intrinsic resistance to PD-1 blockade in metastatic melanoma. BioRxiv, 2022.2012. 2011.519808.
  74. Alexandrov LB, Kim J and Haradhvala NJ et al (2020) The repertoire of mutational signatures in human cancer. Nature 578, 94-101.
    Pubmed KoreaMed CrossRef

This Article

Cited By Articles
  • CrossRef (0)

Funding Information
  • National Research Foundation of Korea
      NRF-2019M3E5D3073568 and NRF-2021R1A4A1029097
  • Ministry of Science and ICT, South Korea
  • Kwanjeong Educational Foundation
  • Brain Korea (BK21)


Social Network Service