Molecular subtyping of endometrial carcinoma cell lines uncovers subtype-specific targetable vulnerabilities

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Li, Rebecca Ho, Ran Tao, Yannes W. Choi, Chae Young Shin, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6536216/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Jul, 2025 Read the published version in npj Precision Oncology → Version 1 posted 10 You are reading this latest preprint version Abstract Endometrial carcinoma (EC), the most common gynecologic cancer type, encompasses multiple molecular subtypes that have consistent prognostic values and are being adopted in clinical practice to guide treatment decisions. However, it remains unclear whether each of these molecular subtypes have unique therapeutic vulnerabilities that can be exploited for advancing the management of ECs. Through analyzing the genomic features of a panel of 39 EC cell lines, we identified multiple tumor cell lines representing each molecular subtype. Histologic and immunochemical analyses of xenografted tumors from these cell lines confirmed their resemblance of cognate primary EC molecular subtypes, both by histology and the protein expression status of mismatch repair genes, p53 and SWI/SNF members in corresponding subtypes. Further investigation of the publicly available genome-wide CRISPR data for EC cell lines identified multiple specific genetic vulnerabilities in mismatch repair-deficient, p53-abnormal and ARID1A and ARID1B-dual deficient EC cell lines, respectively. Particularly, ARID1A and ARID1B-dual deficient EC cells selectively rely on mitochondria oxidative phosphorylation in vitro and in vivo . Therefore, our study demonstrates the utility of EC cell line models for uncovering and validating therapeutic vulnerabilities of each EC molecular subtype. Biological sciences/Cancer/Cancer models Biological sciences/Cancer/Cancer therapy Biological sciences/Cancer/Gynaecological cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Endometrial carcinoma (EC) is the most common form of gynecologic cancers worldwide, with increased incidence and mortality rates globally. While it can be grouped into two types, an estrogen-dependent type I that pertains to the majority of EC and a more aggressive estrogen-independent type II EC (1), the inconsistency of pathologic categorization often results in poor risk stratification for treatment. To overcome this challenge, The Cancer Genome Atlas (TCGA) and others has characterized the genomic landscape of ECs for molecular classification. Mismatch repair (MMR) deficiency and mutations of PTEN, ARID1A, PIK3CA, CTNNB1, TP53 and POLE genes occur frequently in EC (2,3). Based on their gene mutation pattern and frequency, copy number variation, and microsatellite stability, TCGA classified common ECs into four distinct molecular subtypes: POLE ultra-mutated, microsatellite instable (MSI)/ hypermutated, copy‑number low and copy‑number high (2,4). These molecularly defined groups are associated with distinct prognoses (2,4). Building on TCGA’s genomic analyses, novel clinically applicable molecular genotyping strategies, such as the ProMisE classifier (5,6) and the ESMO guideline (7), have been recently developed to stratify patients by risk into molecular subtypes. According to the ProMisE classification tree, EC can be classified into POLE -mutant, MMR deficient (MMRd), p53 abnormal (p53abn), and no specific molecular phenotype (NSMP, lacking all prior three features) molecular subtypes. The hierarchy of classification that the ProMisE tree provides has been further supported by a recent study, in which p53 abnormal ECs with either MMR defect or POLE mutations are best classified under MMRd or POLE -mutant subtypes, respectively (8). The prognosis of POLE -mutant subtype is excellent in contrast with the p53abn subtype, which has the most unfavorable outcome with a 5-year overall survival of approximately 40%, which highlights the need for effective treatments. Moreover, while the MMRd and NSMP subtypes have intermediate prognosis, some of these tumors can dedifferentiate and progress to highly aggressive dedifferentiated or undifferentiated endometrial carcinoma (DD/UDEC), diseases that lack biology-informed effective treatments. DD/UDEC is often diagnosed with a peak age of 55 years. DDEC occurs when an undifferentiated carcinoma arises clonally from low-grade (9-11) or sometimes high-grade (12,13) endometrioid endometrial carcinoma that are often mismatch repair (MMR)-deficient. The differentiated component is eclipsed in about 40% cases, likely due to an outgrowth of the undifferentiated component, and the tumor overall appears as a pure undifferentiated endometrial carcinoma (UDEC) (9,14). The endometrioid components, generally low-grade, often express estrogen receptor (ER), progesterone receptor (PR) and PAX8, whereas the undifferentiated components are usually negative with occasional focal positivity for ER and PAX8. Recent studies identified frequent inactivating mutations with protein loss in the members of the SWI/SNF chromatin-remodeling complexes such as SMARCA4 (encoding a core ATPase of all types of SWI/SNF), ARID1B (encoding a scaffold protein alternate to ARID1A in BAF-type of SWI/SNF), and SMARCB1 (encoding a core member of BAF and PBAF-types of SWI/SNF) in the undifferentiated components of DD/UDEC (15-18). Furthermore, SMARCA4 inactivation is accompanied by the protein loss of SMARCA2, the only known alternate ATPase; and the inactivation of ARID1B occurs along with ARID1A genetic inactivation, in which the latter is usually present in both differentiated and undifferentiated components of DDEC. These findings suggest that inactivation of canonical BAF-type of SWI/SNF complexes is one major driving force underlying the development of DDEC/UDEC. Additionally, these SWI/SNF-mutant DD/UDECs are typically associated with an extremely poor outcome (19,20), thus demanding novel effective treatments. Cancer cell lines established from patients’ tumor specimens remain the most used models in cancer research. There are dozens of EC cell lines that were established and reported over the past several decades. However, the lack of genomic profiles for most EC cell lines at the time of their establishment posed a barrier for proper pathological and molecular classification. The Broad-Novartis Cancer Cell Line Encyclopedia (CCLE) project has profiled the genomic features of about 1000 cancer cell lines of most common cancer types and centralized the data in the DepMap database at the Broad Institute. This study utilizes this resource, and the genomic information of several in-house developed EC lines, to stratify these EC cell lines molecularly for molecular subtype-specific cancer research. Based on this molecular classification framework, we analyzed the DepMap genome-wide CRISPR knockout screen database and uncovered molecular subtype-specific genetic vulnerabilities. Results Molecular subtyping of EC cell lines. To correlate the genomic features of EC cell lines with the molecular subtypes of EC primary tumors, we determined mutation status of POLE, mismatch repair genes and TP53 using the exome-sequencing data (32 from DepMap database, 5 sequenced in-house), cancer gene panel sequencing (2 sequenced in-house),and the microsatellite stability information (Cell Model Passports database) ( Fig. 1A) . Among 39 EC cell lines, HEC251 and JHUEM7 harbor pathogenic POLE mutations and 23 have microsatellite instability and/or mutant mismatch repair genes, including AN3CA, COLO704, EN, HEC1 (HEC1A, HEC1B), HEC108, HEC116, HEC151, HEC265, HEC59, HEC6, HHUA, HOUA-I, ISHIKAWA, JHUEM1, MFE296, MFE319, RL962, SNGM, VOA12371, and VOA14590H ( Fig. 1B, Supplementary Table S1 ). For the remaining 14 cell lines, 12 have p53 pathogenic mutations and one (VOA8492) has a homozygous deletion at p53 loci ( Fig. 1B ). Immunoblotting analysis of 7 p53abn cell lines available for testing validated the aberrant p53 expression in all lines ( Fig. 1C ). Therefore, our analysis identified all four molecular subtypes of ECs, including 5.2% (2/39), 59% (23/39), 33.3% (13/39) and 2.6% (1/39) for POLEmut , MMRd, p53abn and NSMP, respectively. The mutation burden correlates well with the molecular classification, ranging from 180-200 in two POLEmut cell lines, 10-132 in MMRd cell lines, 1-20 in p53abn cell lines, and 7.5 in the NSMP cell line (VOA1066). The mutation burden of MMRd EC cell lines is significantly higher than that in p53abn EC cell lines ( Fig. 1D, p <0.0001 ). P53abn EC cell lines share common genomic features with their primary tumors. As p53abn EC represents the most lethal group of the four molecularly defined EC molecular subtypes, we sought to address whether the identified p53abn EC cell lines recapitulate the genomic features of primary tumors of p53abn EC. Among the 60 TCGA copy number-high ECs where nearly all were p53abn (2), somatic mutations of PIK3CA, FBXW7, PPP2R1A, PIK3R1, ARHGAP35 and PTEN were present in 47%, 22%, 22%, 13%, 10% and 12% of samples ( Fig. 2A, Supplementary Table S2 ), respectively. FBXW7 and PPP2R1A mutations were nearly mutually exclusive (Fisher’s Exact test). Moreover, amplification of multiple cancer genes were found in >15% of samples ( Fig. 2A, Supplementary Table S3 ), including those at genomic loci 3q25-29 (15-36.7%: TERC, MECOM, PIK3CA, SOX2 ), 17q12 ( ERBB2 and GRB7 , 25%), 8q24.21 ( MYC, 23.3%), 19p13 ( NOTCH3, BRD4, SMARCA4, KEAP1, 20-26.7%), 19q12 ( CCNE1, 23.3%),1q21-22 (MCL1, 20%; MUC1: 23.3%), 8p11.21 (18.7%: KAT6A), 20q13 ( ZNF217 , 16.7%), 20q11 (ASXL1, 21.7%), 16p11.2 ( SETD1A, 16.7%), 5p13.3 (15%, DROSHA), 2p23 (PPP1CB, 15%). These findings are largely recapitulated in our recent targeted cancer gene mutation and shallow whole genome analysis of 186 p53abn EC primary tumors (21). Based on these genomic features, about 75% of p53abn ECs contain one or more of the four following targetable features: ERBB2 amplification, CCNE1 amplification, PPP2R1A/FBXW7 mutations, and homologous recombination deficiency. Among all 12 p53abn EC cell lines, two (HTMMT, SPAC1L) have inactivating PTEN and two (TEN and MFE280) have activating PIK3CA mutations ( Fig. 2B ). Three cell lines, including TEN, MFE280 and VOA8492, have amplification of ERBB2 ( Fig. 2C ). MYC is amplified at least 1.5-fold in 4 cell lines, including SNU685, VOA14581, JHUEM3 and SNU1077 cells. Remarkably, CCNE1 is amplified at least 1.5-fold in 7 seven cell lines, including TEN, EMTOKA, KLE, VOA14581, MFE280, VOA8492 and SNU1077 cell lines. Western blotting analysis confirmed elevated CCNE1 expression in four CCNE1 -amplified cell lines, including TEN, KLE, VOA14581 and VOA8492, in comparison to HEC50B and VOA1066, two cell lines with normal CCNE1 copy numbers ( Fig. 2D ). Notably, SPAC1L also expressed abundant CCNE1 despite of no CCNE1 amplification, which may be due to a hotspot mutation (p.R505S) in WD40 domains of FBXW7 ( Fig. 2B ), which impair the recognition of its substrates (e.g. CCNE1) and subsequent substrate degradation through E3 ligase. In addition, such FBXW7 mutations were identified in four additional cell lines, EMTOKA (p.R505C), JHUEM3 (p.R465H), VOA8492 (p.R505C) and KLE (p.R479Q) ( Fig. 2B ). The hotspot mutation of PPP2R1A at p.P179, p.R183 or p.S256 sites, which occurs in >20% p53abn EC and mutually exclusive to FBXW7 mutation, was only detected in HEC50B (p.R183W) ( Fig. 2B ). No mutations were found in homologous recombinationrepair genes, e. g. BRCA1 or BRCA2 . Although ARID1A mutation is rare in p53abn EC, its co-occurrence has been shown to drive the development of aggressive EC in mice (22). Analysis of p53abn EC cell lines revealed that EFE184, HMMT, JHUEM3 and SPAC1L cells have ARID1A deleterious mutations ( Fig. 1B ). Western blotting analysis verified the complete loss of ARID1A in SPAC1L and EFE-184 cells ( Fig. 1C ), indicating that these two cell lines represent ARID1A-deficient p53abn EC cell lines. Taken together, these data highlight the genomic similarity between p53abn EC primary tumors and cell lines, the latter serving as a powerful resource for translational research. MMRd EC cell lines accumulate frequent p53 and SWI/SNF mutations. The high mutation rate in MMRd EC due to microsatellite instability can lead to the accumulation of additional oncogenic mutations, including TP53 and SWI/SNF genes, that are prevalent in DD/UDECs (mostly MMRd EC) (23). In all 23 MMRd cell lines, 14 have at least one hotspot missense or deleterious TP53 mutation ( Fig. 1B ), suggesting a selective pressure for accumulating TP53 mutations during tumor progression or prolonged cell culture. Moreover, multiple cell lines contain mutations of SWI/SNF genes commonly occurred in DD/UDECs. In particular, ARID1A and ARID1B are mutated in 91% (21/23) and 74% (17/23) of these cell lines, respectively ( Fig. 1B ). In addition to the VOA1066 cell line that we previously established from a UDEC patient with ARID1A/B dual loss (24), AN3CA, EN, MFE-296 and VOA14590H cell lines all harbor two deleterious mutations in each of ARID1A and ARID1B genes ( Fig. 1B ). VOA14590H was derived from a DDEC primary tumor and formed subcutaneous xenograft tumor with undifferentiated histology and dual loss of ARID1A/B protein ( Fig. 3A ), indicating that VOA14590H is a bona fide ARID1A/B-dual deficient DDEC cell line. Western blotting analyses confirmed ARID1A/1B dual loss in AN3CA and EN cells, but not those with only one deleterious mutation ( Fig. 3B). Like VOA1066 cells, both AN3CA and EN cell lines do not express PAX8 ( Fig. 3B ), a lineage marker of differentiated endometrial epithelium,suggesting that they were potentially derived from ARID1A/B-dual deficient DD/UDEC tumors.MFE-296 was previously confirmed to be negative for both ARID1A and ARID1B (25), thus representing another UD/DDEC line.Furthermore, a single SMARCA4 inactivating mutation was found in two cell lines, HEC1A and HEC59, but no accompanying protein loss was identified in HEC59 cells by Western blotting ( Fig. 3B ). Thus, MMRd EC cell lines exhibited a high tendency to accumulate additional progression events, particularly TP53 and ARID1B mutations, mirroring those in primary tumors. Tumorigenicity of EC cell lines. Next, we inoculated all available MMRd and p53abn cell lines into immunodeficient mice to determine their tumorigenicity and histological features. All of the 8 MMRd cell lines available for xenografting, including HEC59, HEC1B, HEC116, VOA12371, AN3CA, EN, HOUA-I, and VOA14590H, developed subcutaneous tumors at various latency and doubling time ( Fig. 4A ). Histology assessment revealed diverse histology, ranging from intermediate (HEC59, HOUA-I) or poorly differentiated (HEC1B, HEC116, VOA12371) to undifferentiated (AN3CA, EN, VOA14590H) ( Fig. 4B and 3A, Supplementary Fig. S1A ), further supporting that AN3CA, EN and VOA14590H are representative cell lines of ARID1A/B-dual deficient DD/UDEC. Furthermore, Western blotting and IHC staining validated the mutant p53 status in 5 out of 9 tested cell lines, including HEC59, HEC1B, HEC116, EN and AN3CA ( Supplementary Fig. S1B, Fig. 4B ). Among the 7 p53abn EC cell lines tested, including VOA8492, VOA14581, SPAC1L, HEC50B, KLE, EFE-184 and TEN, 4 (HEC50B, SPAC1L, VOA8492 and TEN) developed subcutaneous tumors ( Fig. 4A ). Histology assessment revealed that SPAC1L and VOA8492 xenografted tumors exhibited papillary serous endometrial carcinoma histology ( Fig. 4C ), corresponding to the diagnosis of their primary tumors (26) ( Supplementary Fig. S2 ), whereas HEC50B and TEN displayed features of high grade endometrioid carcinoma and clear cell endometrial carcinoma, respectively ( Fig. 4C, Supplementary Fig. 1C ), consistent with the diagnosis of their primary tumors (27,28). Immunostaining revealed negative p53 staining in VOA8492 and HEC50B cells and a mutant p53 staining pattern in SPAC1L cells ( Fig. 4C ). SPAC1L was also negative for ARID1A staining ( Fig. 4C ), supporting it as an ARID1A -mutant p53abn EC cell line. Selective genetic vulnerabilities in p53abn and MMRd EC cells. Next,we endeavored to identify preferential essential genes for each non- POLEmut molecular subtype using the DepMap CRISPR screen database, which included the data for 25 endometrial cancer cell lines. When comparing MMRd to p53abn cell lines, we identified multiple genes whose deletion was selectively lethal to MMRd or p53abn EC cells ( Fig. 5A , Supplementary Table S4 ). This includes WRN for MMRd cells and CDK2, CCNE1 and KIF18A for p53abn cells. WRN was previously shown to be a selective vulnerability in cancer cells with microsatellite instability (29) and inhibition of KIF18A was known to preferentially suppress the growth of p53-mutant ovarian and breast cancer cells (30). As many of the p53abn EC cell lines have CCNE1 amplification or FBXW7 inactivating mutations ( Fig. 2B and 2C ), it is also not surprising that these cell lines were more vulnerable to the depletion of either CCNE1 or CDK2 , the latter encoding the canonical interacting partner of CCNE1. Therefore, these findings confirm the validity of our analysis approach in identifying molecular subtype-specific lethal targets. Notably, our analysis identified PELO as the top one synthetic lethal target for MMRd EC cell lines. Using CRISPR/Cas9, we demonstrated that PELO deletion selectively suppressed the growth of MMRd EC cell lines, HEC1B and HEC116, but not p53abn EC cell lines, HEC50B and TEN ( Fig. 5B and 5C ). Therefore, our approach was able to identify novel synthetic lethal targets for specific molecular subtypes of EC. ARID1A/B-dual deficient DD/UDEC cells rely on mitochondria oxidative phosphorylation. Because DD/UDEC represents one highly lethal histologic subtype of EC that is under-studied, there is an unmet need to identify specific lethal targets in ARID1A/B-dual deficient DD/UDEC. Since the DepMap CRISPR/Cas9 database only included two identified ARID1A/B-dual deficient DD/UDEC cell lines, EN and MFE-296, we searched all CCLE cell lines for ARID1A and ARID1B deleterious mutations ( Supplementary Table S5 ), leading to the identification of two more cell lines, EFO-27 and SKUT1, each harboring 2 deleterious mutations for ARID1A and ARID1B, respectively.EFO-27 was derived from ovarian endometrioid ovarian cancers, which arise from extra-uterine endometrial epithelial cells and share histopathological and genomic features with endometrial endometrioid cancers. Immunoblotting confirmed ARID1A/B dual loss in EFO-27 ( Supplementary Fig. S3 ). SKUT1 was derived from uterine tumors with carcinosarcoma features in 1977 (31). As uterine carcinosarcomas share common features with DDEC (32) and DD/UDEC has only been recognized in the past 2 decades, it remains possible that the original tumor from which SKUT1 cells were derived was a DDEC or contained a minor undifferentiated component with ARID1A/B dual deficiency. Therefore, these two cell lines were grouped with EN and AN3CA for preferential essential gene analysis. In comparison to 27 EC cell lines without ARID1A/B dual loss, ARID1A/B-dual deficient cell lines are selectively lethal to the loss of genes that are enriched for mitochondria function ( Fig. 6A, Supplementary Table S6 ), which is in line with our previous finding that SMARCA4/2-deficient ovarian and lung tumors rely on mitochondria phosphorylation (33). To assess the potential dependency on mitochondria oxidative phosphorylation in ARID1A/1B-dual deficient DDEC, we evaluated the efficacy of IACS-010759, a highly selective mitochondria electron transport chain Complex I inhibitor (34), in a panel of EC cell lines. IACS-010759 inhibited mitochondria respiration ( Fig. 6B, Supplementary Fig. S4 ) and the growth of ARID1A/1B-dual deficient DDEC cells ( Fig. 6C and 6D ), but had little effect on the growth of ARID1A/1B-proficient EC cells ( Fig. 6C ). In addition, daily treatment of IACS-010759 for 10 days significantly suppressed the tumor growth of VOA1066 cell line-xenograft tumors in immunodeficient mice ( Fig. 6E and 6F ) without observable toxicity at necropsy. Lastly, to assess whether dual loss of ARID1A/B creates a dependence on mitochondria function, we inactivated ARID1B by CRISPR/Cas9 in HEC1B ( Fig. 6G ), an ARID1A-deficient/ARID1B-proficient EC cell line, which significantly increased the cellular sensitivity to IACS-010759 treatment ( Fig. 6H ). Taken together, these data indicate that ARID1A/1B-dual deficiency conferred increased cellular sensitivity to the inhibition of mitochondria electron transport chain activity. Discussion Cancer cell lines are crucial tools in cancer research as they provide consistent and reproducible models for studying disease biology and developing therapeutics. However, the reliability of cancer cell lines in modelling disease depends on the original diagnosis when the cell lines were established and may be questioned as our understanding of the disease evolves. Therefore, the proper classification of cell lines is critical for their application in basic and translational cancer research. We have previously reclassified multiple gynecologic cancer cell lines based on genomic understanding of the relevant diseases and histologic reassessment (13), leading to improved representation of molecularly defined ovarian cancer cell lines in large scale functional genomic screen studies and subsequent identification of targetable vulnerabilities in those molecularly defined ovarian cancer subtypes (33). In this study, we classified EC cell lines into lately recognized clinically relevant molecular subtypes, which will guide the future use of these cell lines for identifying and/or validating novel therapeutics for each molecular subtype. Accordingly, utilizing publicly available genome-wide CRISPR knockout screen database on these cell lines, we identified putative targetable features in several molecular subtypes of EC. In particular, we validated that MMRd EC cells are highly sensitive to PELO deletion, which supports a recent report describing PELO dependency in microsatellite instable cells by Borck et al. (35) during the preparation of this manuscript. We also demonstrated that ARID1A/B dual deficiency, mimicking SMARCA4/2-dual deficiency (33), creates a dependency on oxidative phosphorylation, indicating that patients with these highly lethal SWI/SNF-deficient cancers may be grouped together for clinical trials testing the efficacy of mitochondria-targeting therapeutic approaches, e.g., electron transport complex I inhibitors. ARID1A/B-dual deficient DD/UDEC has been recently recognized as a highly lethal EC subtype. We have previously established the first UDEC cell line, VOA1066, from a primary tumor with ARID1A/B dual deficiency (24). This cell line has a low mutation burden, normal p53 expression and is classified as an NSMP cell line, supporting the notion that DD/UDEC can arise from NSMP ECs, and represents a highly lethal outlier of NSMP ECs that are otherwise innocent. Our present study further established the VOA14590H cell line from an ARID1A/B-dual deficient primary DDEC tumor and identified three more ARID1A/B-dual deficient EC cell lines, EN, AN3CA and MFE-296. All these four cell lines are MMRd and representative models of ARID1A/B-dual deficient DD/UDECs with MMRd. Notably, VOA14590H was developed independently from the same primary tumor that was utilized for developing the DDEC-3 cell line by Wong et al.(36). Future genomic analysis is required to determine whether these two cell lines can be considered as the same cell line. Furthermore, our study also identified that SKUT1 may arise from a primary tumor representing or containing a component of DD/UDEC with ARID1A/B dual deficiency, rather than the original diagnosis of carcinosarcoma. This finding is critical as it will allow for the proper use of this cell line for future basic and translational studies. Moreover, our study also demonstrated that EFO-27, which originated from an ovarian endometrioid carcinoma, represents an ARID1A/B-dual deficient DD/UDOC cell line. However, as none of the primary tumors used to establish EN, AN3CA, MFE-296, SKUT1 and EFO-27 are available for reinvestigation, it remains possible that dual-loss of ARID1A and ARID1B may accumulate during prolonged culture as all these cell lines are hyper-mutated, which can facilitate the emergence and selection of these aggressive clones. Nevertheless, we capitalized on the identification of these ARID1A/B-dual deficient cancer cell lines and uncovered that these cancer cells are selectively more sensitive to inhibition of mitochondria oxidative phosphorylation in vitro and in vivo . This observation extends the previous findings from us and others describing the increased reliance on oxidative phosphorylation in SMARCA4-deficient cancers (33,37), suggesting that SWI/SNF-mutant cancers, particularly those with defective canonical BAF, share common metabolic vulnerability and can be grouped together into a basket trial for assessing the clinical benefit of mitochondria-targeting therapeutic approaches, e.g., electron transport complex I inhibitors. In addition to characterizing multiple ARID1A/B-dual deficient DD/UDEC cell lines, our study also identified a number of p53abn EC cell lines. This paves the way for identifying putative druggable targets in p53abn EC, which is often aggressive clinically. Our analysis of genome-wide CRISPR screen data on EC cell lines indicate that p53abn EC cells may rely more on several genes, such as CDK2 and KIF18A. CDK2 is a cyclin-dependent kinase that pairs with E- and A-type cyclins during S and G2 cell cycle phases. It has multiple roles in cell cycle checkpoint control and its function is often redundant with that of CDK1 (38,39). However, in the absence of p53, CDK2 is essential for G2/M checkpoint control and is non-redundant with CDK1 (40). Moreover, previous studies have reported that p53 represses CDK2 during DNA damage or oncogene-induced cellular senescence. Therefore, inhibition of CDK2 can decrease tumor penetrance and delay tumor onset in p53-null pineal tumor cells (41). Notably, a recent study reported that CDK2 is critical for repairing collapsed replication fork in CCNE1-amplified ovarian cancer cells (42). As several of these p53abn EC cell lines have amplified CCNE1 and/or stabilized CCNE1 protein due to FBXW7 inactivation, the dependence on CDK2 in p53abn EC cell lines could be partially attributed to the hyperactivity of CCNE1. Furthermore, KIF18A motor protein utilizes ATP hydrolysis to move along kinetochore-microtube fibers (43). It has been discovered that KIF18A is a selective vulnerability in chromosome instable cancer cell lines, such as p53-mutant cancer cells (30,44-46). Nonetheless, these findings suggest that pharmacologic inhibition of CDK2 or KIF18A may have clinical implications for p53abn EC, which requires further investigation to determine whether all or a subset of p53abn EC can benefit from these approaches. As these cells often have multiple targetable features, like CCNE1 and ERBB2 amplifications in TEN, future studies are also needed to assess whether there is any synergistic effect for co-targeting these oncogenic features. Lastly, our study not only provides the molecular classification for EC cell lines, but also validates or establishes their tumorigenicity in immunodeficient mice. These efforts will facilitate future translational research using these cell lines. Notably, though several p53abn cell lines, including KLE, VOA14581, and EFE-184, failed to develop subcutaneous tumors in our study the tumorgenicity of KLE has been previously reported. Gao et al. isolated CD44 and CD133-positive tumor initiating cells from KLE, which were able to develop subcutaneous tumors in athymic nude mice (47). KLE was also able to develop slow-growing orthotopic tumors (48) or lung metastasis through tail vein injection (49) in nude mice. Therefore, additional studies are necessary to further validate the tumorigenicity of VOA14581 and EFE-184 cell lines in immune compromised mice. Taken together, our study provides the molecular classification of EC cell lines to accelerate basic and translation research in EC. In particular, ARID1A/B-dual deficient DD/UDEC cells are selectively sensitive to pharmacologic inhibition of mitochondria phosphorylation in vitro and in vivo , which warrants clinical investigation to inform the design of optimal treatment approach for these highly aggressive cancers. Materials and Methods Cell lines and patient tissues. HEC50B, TEN, HOUA-I, HEC59, HEC116, HEC1B, KLE, EFE-184, SPAC-1L, AN3CA, EN and EFO-27 cells were grown in RPMI media supplemented with 5% characterized FBS (Corning, cat # CA76322-116) and grown at 37 degrees in a 5% CO 2 incubator. To establish cell lines from patients’ specimens, primary tumor tissues or ascites were collected under the University of British Columbia Ethics Board protocol H02-61375 and H18-01457, at the time of surgery after obtaining an informed consent from the patients. For VOA8492, VOA14581 and VOA14590H cell lines, tumor tissues were minced and digested in 2.5mg/mL Collagenase D (Sigma-Aldrich, cat#11088882001). After 60 minutes, single cells from the solution were placed into Petri dishes with 199:105 media, consisting of a 1:1 ratio of media 199 (Thermofisher Scientific, cat#31100035) and media 105 (Sigma-Aldrich, cat#M6395) fortified with 10% defined FBS (Hyclone, cat#SH30070.03) and 10 mg/mL of Gentamicin (Thermofisher Scientific, cat#15710064). For VOA12371 cell line, cells from ascites were lysed by ammonia chloride to remove red blood cells. Primary cells were left to adhere and grow at 37 degrees in a 5% CO 2 incubator with culture medium replaced every 3-4 days. Cancer cells were enriched by differential trypsinization and subsequent removal of fibroblasts, and continuously passaged for at least 20 passages to ensure the establishment of cell lines. All cell lines were certified by the short tandem repeat (STR) analysis through LabCorp, tested regularly for Mycoplasma (Genetica, DNA Laboratories), and used for the study within 6 months of thawing from liquid nitrogen storage. Exome sequencing, mapping and variant calling. The whole exome sequencing datasets available for EC cell lines were downloaded from the DepMap database (2023Q2). Whole exome data of VOA1066 cell line was obtained from our previous study (24). We also performed whole exome sequencing on SPAC1L and two in-house developed EC cell lines, VOA8492 and VOA15481 as well as their respective normal DNA from buffy coat samples. Briefly, genomic DNA isolated from cells and patients’ buffy coats were fragmented to a target size of 150-200 bp on the Covaris E210 system and the whole-exome was sequenced as previously described (13). Fastq files were aligned with Burrows-Wheeler Aligner (BWA) 0.7.5a to hs37d5, and the SAM output file was converted into a sorted BAM file using SAMtools 0.1.19. BAM files underwent indel realignment, duplicate marking and recalibration steps in this order with the Genome Analysis Toolkit (GATK) 2.8-1, where dpsnp137 was used for known SNPs and Mills_and_1000G_gold_ standard.indels.b37.vcf was used for known indels. Variant calling was carried out in tumor-only mode with HaplotypeCaller, and output VCF files were recalibrated with VariantRecalibrator from GATK 2.8-1. SnpEff 3.2 and SnpSift 1.9c were then used to annotate these VCF files with database version GRCh37.70. Only variants with a minimum quality score of 20 were extracted. Thereafter, we excluded variants with a Global Minor Allele Frequency >= 0.01 and those somatic coding variants (SNVs) that either appeared in the 1000 Genomes Project database, the dbSNP database or the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project database, assuming that these SNVs might be of less importance for tumorigenesis. Somatic copy number analysis was completed following the GATK tutorial “(How to part I) Sensitively detect copy ratio alterations and allelic segments” and verified using Novogene copy number analysis (copy number called using Control-FREEC). Targeted panel sequencing. We performed targeted cancer gene panel sequencing for VOA12371 cell line and VOA14590H xenograft tumor using the QIAseq Comprehensive Cancer Panel as previously described (21). The resulting raw Fastq files were uploaded to QIAseq's cloud-based processing portal GeneGlobe. Using this portal, we ran the QIAseq-developed processing pipeline for trimming, alignment, post-processing, and mutation calling against the reference genome hg38. Subsequently, results for all samples were concatenated and extensive mutation filtering was performed manually to remove artifacts. Output files for all samples were combined so that common germline SNPs and artifacts could be removed. Further filtering using gnomAD and ClinVar (50,51) was performed to filter out more germline SNPs and variants with a Global Minor Allele Frequency >= 0.01. Additionally, all “modifier” mutations occurring far from splice sites were removed. Genome-wide CRISPR screen data analysis. CRISPR/Cas9 knockout data was downloaded from the DepMap database (2023Q2). Differential gene dependency was determined by using two-sided Wilcoxon rank sum test to compare the DepMap CRISPR knockout data gene effect scores between MMRd and p53abn EC cell lines or between ARID1A/B dual-deficient cell lines and the remaining endometrial cancer cell lines with available screen data. Western blotting. Whole cell lysates were extracted using urea lysis buffer (9M urea, 4% CHAPS, 0.5% IPG buffer, 50mM DTT, Sigma-Aldrich). 20 μg of cell lysate was resolved on SDS-PAGE gels for protein detection. Antibodies against SMARCA4 (Abcam, cat# ab11064, 1:5000), SMARCA2 (Cell Signaling Technology, cat#D9E8B, 1:1000), ARID1A (Sigma-Aldrich HPA005456 1:1000), p53 (ProteinTech, 10442-1-AP, 1:3000), PAX8 ( ), PELO (ProteinTech, cat#10582-1-AP, 1:2000). Ponceau S staining and/or Vinculin (Sigma-Aldrich, cat#V9131, 1:10000) were used to confirm equal protein loading. Immunohistochemistry. Formalin fixed, paraffin embedded tissue blocks were sectioned at 4μm thickness onto Superfrost+ glass slides and immunohistochemically stained with the Leica BOND RX system. Antibodies used for immunohistochemistry were previously described (13,23). Staining was evaluated by one or both gynecologic pathologists (L. H., S.M.) . Gene knockout by CRISPR/Cas9 technology. Knockout of ARID1B and PELO were achieved by a pool of 3 GFP-tagged CRISPR/Cas9 KO plasmids targeting ARID1B (Santa Cruz, sc-402365) or 3 individual CRISPR/Cas9 KO plasmids targeting PELO with the following sgRNA sequences: GGCTTGAGAGTCGAAGTCGA, TGGTCCCCTTAACCCGCAGC and AGTCCATAGAAAGCTCGATC. These sgRNA sequences were cloned into LentiCRISPR-v2-puro vector (a gift from Feng Zhang, Addgene #52961) (52). Viral packaging and infection were completed as previously described (13). GFP-positive or puromycin-resistant pooled cells were harvested for western blotting to confirm target depletion. Cell growth assays. For measuring cell growth, cells were seeded at1500 cells/well in quadruplicate in 24-well plates. Plates were fixed when control conditions grew up to 80-100% confluence, which usually takes 8-21 days after plating. To determine cell growth after drug treatment, cells were treated with either vehicle or testing agents 24 hours after plating. Treatments were refreshed every 4 days until the control conditions reached confluence. Cells were fixed with 10% trichloroacetic acid (Sigma-Aldrich cat# T6399-500G) before washing. Once plates were dry, the cells were stained with 0.4% (wt/vol) sulforhodamine B (Sigma-Aldrich cat# 230162) dissolved in 1% acetic acid. The stain was dissolved with 10 mM Tris-base pH 10.5 to quantify cell growth that was normalized to relevant control conditions. Seahorse assays . Mitochondria oxygen consumption rates (OCR) were determined using the XF96 Pro Analyzer (Seahorse Bioscience) as previously described (33). Briefly, cells were seeded at 18,000-40,000 cells/well at 90% confluency in Seahorse XF96 Pro cell culture microplates (Agilent) the day before the experiment. An hour prior to running the assay, cells were refreshed with RPMI supplemented with 2 mM L-glutamine, 10 mM glucose, 1 mM sodium pyruvate and either DMSO or 2 nM of IACS-10759 (ChemieTek, cat# CT-IACS107) adjusted to pH 7.4 and kept in at 37°C in CO 2 -free incubator. Afterwards, plates were loaded on the Seahorse Analyzer followed by sequential injections of oligomycin (Sigma-Aldrich, cat: O4876, FCCP (Sigma-Aldrich, cat#C2920), and a mixture of antimycin A (Sigma-Aldrich, cat#A8674) and rotenone (Sigma-Aldrich, cat#R8875) to a final concentration of 1 μM of oligomycin, 1.5 μM of FCCP, and 1 μM antimycin A, and 100 nM rotenone respectively, at 35, 56, and 77 minutes. OCR were normalized to the DMSO condition. Mouse xenograft studies. All procedures related to animal handling, care and treatment in this study were approved by the Animal Care Committee of the University of British Columbia (A22-0005). Briefly, 5-10x10 6 cells per mouse, with a 1:1 mix of Matrigel (Corning) in a final volume of 200 μl, were injected subcutaneously into the back of NRG (NOD.Rag1KO.IL2RγcKO) mice. Tumor volumes and mouse weights were measured twice weekly. Tumor volume was calculated with the following formula: length x (width) 2 x 0.52. Mice were monitored for health until they reached humane endpoints for tumor isolation. Isolated tumors were fixed in 10% neutral buffered formalin and embedded for histology analysis. Statistical analysis. Unless otherwise specified, the student's t test was used to evaluate the significant difference between 2 groups of data in all in vitro experiments. P < 0.05 was considered significant. Declarations Data Availability The datasets generated for in-house developed cell lines during the current study are not publicly available due to the restriction of research ethics approval but are available from the corresponding author on reasonable request through a material transfer agreement. Author contributions EL and RH: investigation, data analysis, manuscript writing-first draft; RT and CYS: investigation and manuscript editing; YWC, CYS, SYC, JS, BY, LJ, EY, and SDM: investigation; MC and BTH: resource; DGH and RIKG: funding acquisition and supervision; LH: funding acquisition, investigation and supervision; and YW: Conceptualization, supervision, funding acquisition, manuscript writing-first draft and editing. Acknowledgement We thank Ms. Clara Salamanca, Ms. Jingjie Guo and all staffs from the Molecular and Advanced Pathology Core at the University of British Columbia for technical supports. This work was supported by research funds from the Canadian Institutes of Health Research (CIHR) grants (PJT-178179; PJT-197923, to YW), Terry Fox New Frontiers Program Project Grants (TFRI PPG, #1116, to LH, YW and DGH) and Natural Science and Engineering Research Council-discovery grant (RGPIN-2020-05390, to RIKG). R.H., B.Y. and L.J. are recipients of the Canadian Graduate Scholarships-Master’s Program. R.H. is a recipient of the Canadian Cancer Society Training Research Training Award. We also appreciate the generous supports from the British Columbia Cancer Foundation and the VGH/UBC Hospital Foundation to the Ovarian Cancer Research Centre. The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript. Competing interests All authors declare no financial or non-financial competing interests. References Setiawan VW, Yang HP, Pike MC, McCann SE, Yu H, Xiang YB , et al. 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(A) \u003c/strong\u003eSchematic view of molecular subtyping of EC cell lines.\u003cstrong\u003e (B) \u003c/strong\u003eHeatmap of top mutated genes in EC cell lines ordered by their molecular subtypes.\u003cstrong\u003e(C) \u003c/strong\u003eWestern blotting analysis of p53 and ARID1A expression in p53abn EC cells.\u003cstrong\u003e(D) \u003c/strong\u003eComparison of mutation burden between MMRd and p53abn EC cell lines.\u003c/p\u003e","description":"","filename":"Figure11.png","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/6b2d14b1070b41fa1b20ae4e.png"},{"id":82410060,"identity":"8d02a8e8-e159-46ad-baa8-b1fbc4728ecb","added_by":"auto","created_at":"2025-05-10 06:12:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":213089,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterization of p53abn endometrial carcinoma cell lines. \u003c/strong\u003e(A) heatmap of top mutated/amplified genes in primary tumors; (B) heatmap of top mutated genes in cell lines; (C) copy number changes of key genes in cell lines.\u003c/p\u003e","description":"","filename":"Figure22.png","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/6c32f1569c655ff1f510e903.png"},{"id":82410066,"identity":"859e52c3-2327-4232-be72-2e7ada4619d3","added_by":"auto","created_at":"2025-05-10 06:12:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":449878,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of ARID1A/B-dual deficient DD/UDEC cell lines. \u003c/strong\u003e(A) Histology and immunohistochemical features of VOA14590 primary tumor and the cell line-derivative xenograft tumors. (B) Western blotting analysis of SWI/SNF protein and PAX8 expression in EC cell lines.\u003c/p\u003e","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/e9a869dd98d9da1611a173b9.png"},{"id":82410194,"identity":"dafa4b85-32e2-4520-b263-8040a862ada6","added_by":"auto","created_at":"2025-05-10 06:20:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":487281,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTumorigenicity of MMRd and p53abn EC cell lines. (A) \u003c/strong\u003eTumor development latency and growth doubling time of subcutaneous xenograft tumors of indicated EC cell lines.\u003cstrong\u003e(B) \u003c/strong\u003eHistology and immunohistochemical features of xenograft tumors of MMRd EC cell lines. \u003cstrong\u003e(C) \u003c/strong\u003eHistology and immunohistochemical features of xenograft tumors of p53abn EC cell lines.\u003c/p\u003e","description":"","filename":"OnlineFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/1ad8da166f1b7728112af7c8.png"},{"id":82410061,"identity":"a0f5ea48-556f-4ae2-987a-b35afa5cfcfb","added_by":"auto","created_at":"2025-05-10 06:12:55","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":130201,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of selective vulnerabilities in p53abn and MMRd ECs. (A) \u003c/strong\u003eComparison of genetic dependency in 16 MMRd EC cell lines vs 9 p53abn EC cell lines. Genome-wide CRISPR screen data was downloaded from the DepMap database (23Q2). MMRd EC cell lines: COLO684, MFE296, JHUEM1, HEC1B, HEC265, ISHIKAWAHERAKLIO02ER, RL952, SNGM, EN, HEC6, MFE319, HEC59, HEC1, HEC116, HHUA and HOUAI; p53abn EC cell lines: MFE280, KLE, SNU1077, TEN, SNU685, EFE184, HEC50B, EMTOKA and HTMMT. (\u003cstrong\u003eB\u003c/strong\u003e) Western blotting showing PELO knockout by CRISPR/Cas9 in HEC116 cells. (\u003cstrong\u003eD\u003c/strong\u003e) PELO deletion selectively suppressed the growth of MMRd EC cell lines.\u003c/p\u003e","description":"","filename":"OnlineFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/235751081d53c776f6de8ca4.png"},{"id":82410072,"identity":"815924c3-b2b4-4953-bae2-293a172aae64","added_by":"auto","created_at":"2025-05-10 06:12:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":200397,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eARID1A/B-dual deficient DD/UDEC cells depend on oxidative phosphorylation. (A) \u003c/strong\u003eLeft, a volcano plot showing the differential genetic dependency of genes between \u003cem\u003eARID1A/1B\u003c/em\u003e-deficient (n=4: EN, MFE-296, EFO-27 and SKUT-1) and proficient (n=27) EC cell lines, which includes 2 \u003cem\u003ePOLEmut\u003c/em\u003e (HEC251 and JHUEM7), 16 MMRd, and 9 p53abn (detailed in \u003cstrong\u003eFigure 5\u003c/strong\u003e legend). The genetic dependency was calculated using the CERES gene effect data from DepMap genome-wide CRISPR/Cas9 screens. Significance was assessed using Wilcoxon rank-sum test. Each dot denotes a gene. Genes highlighted in blue represent those whose deletion selectively impairs the growth of \u003cem\u003eARID1A/1B\u003c/em\u003e-deficient cell lines and were subjected to Gene Ontology enrichment analysis. Right, bar graph reflecting the GO analysis of the highlighted genes essential for \u003cem\u003eARID1A/1B\u003c/em\u003e-deficient cancer cells. \u003cstrong\u003e\u0026nbsp;(B) \u003c/strong\u003eOxygen consumption rates (OCR) measured with the Seahorse Mito Stress test for VOA14590H cells treated with and without IACS-010759 (2 nM for 1 hour). Bar graphs show relative basal respiration. \u003cstrong\u003e(C) \u003c/strong\u003eRepresentative images of a panel of endometrial cancer cell lines treated with varying concentrations of IACS-010759 for 12-22 days. \u003cstrong\u003e(D) \u003c/strong\u003eRelative growth of ARID1A/B-proficient and dual-deficient cells treated with IACS-010759 for 12-22 days\u003cstrong\u003e. (E, F) \u003c/strong\u003eEffects of IACS-010759 treatment on the growth of VOA1066 cell line-derived xenografted tumors.\u003cstrong\u003e(G) \u003c/strong\u003eWestern blotting showing \u003cem\u003eARID1B\u003c/em\u003e-knockout in HEC1B cells.\u003cstrong\u003e(H) \u003c/strong\u003eBar graph showing relative growth of HEC1B cells, -/+ \u003cem\u003eARID1B\u003c/em\u003e-knockout, treated with IACS-10759 for 10-12 days. Error bars represent SEM and p-values were determined using unpaired t-test, corrected for multiple comparisons using the Bonferroni-Dunn method.\u003c/p\u003e","description":"","filename":"OnlineFigure6.png","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/1c631d05a293c2b8c963f0f5.png"},{"id":87756664,"identity":"6874493d-0cc3-4222-b2fc-2c39ed18476f","added_by":"auto","created_at":"2025-07-28 16:06:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3042381,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/2d840c4c-d3bf-4433-af2b-796d9204df02.pdf"},{"id":82410193,"identity":"f6c1a6c5-d31f-44d4-a60a-a676c90a0878","added_by":"auto","created_at":"2025-05-10 06:20:55","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16055,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/fa5217e6425753cc2af3ef5b.xlsx"},{"id":82410063,"identity":"88efe348-73a7-48d0-a9bd-710317028a9d","added_by":"auto","created_at":"2025-05-10 06:12:55","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":95072,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/4b8d87576d30d7513e4fe001.xlsx"},{"id":82410745,"identity":"69386d5a-a63e-4c70-ac02-6d0b75cfcdd5","added_by":"auto","created_at":"2025-05-10 06:36:56","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":690402,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/9aee334c839b4a0cd69ba406.xlsx"},{"id":82410532,"identity":"5a7343f3-ce61-4eb7-8868-4935d4bc331e","added_by":"auto","created_at":"2025-05-10 06:28:56","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1239950,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/f10cdf128eee9c6262c8845d.xlsx"},{"id":82410197,"identity":"ccb75419-04dc-414f-b1f0-69ebdd117f5e","added_by":"auto","created_at":"2025-05-10 06:20:56","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":32265,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTableS5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/1b9ebd5e6104649f02fb79ca.xlsx"},{"id":82410078,"identity":"5e9f1563-b2b8-4c9c-bcc4-e3f03cb8c6b7","added_by":"auto","created_at":"2025-05-10 06:12:56","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":1000732,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTableS6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/885113248e6ac00553dcd625.xlsx"},{"id":82410534,"identity":"03d2b2b4-d452-4a6e-821b-5e851720a499","added_by":"auto","created_at":"2025-05-10 06:28:56","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":2609652,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures20250425.docx","url":"https://assets-eu.researchsquare.com/files/rs-6536216/v1/9501b3b014a775412d772357.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Molecular subtyping of endometrial carcinoma cell lines uncovers subtype-specific targetable vulnerabilities","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEndometrial carcinoma (EC) is the most common form of gynecologic cancers worldwide, with increased incidence and mortality rates globally. While it can be grouped into two types, an estrogen-dependent type I that pertains to the majority of EC and a more aggressive estrogen-independent type II EC (1), \u0026nbsp;the inconsistency of pathologic categorization often results in poor risk stratification for treatment.\u0026nbsp;To overcome this challenge, The Cancer Genome Atlas (TCGA) and others has characterized the genomic landscape of ECs for molecular classification. Mismatch repair (MMR) deficiency and mutations of \u003cem\u003ePTEN, ARID1A,\u003c/em\u003e \u003cem\u003ePIK3CA, CTNNB1, TP53\u003c/em\u003e and \u003cem\u003ePOLE\u003c/em\u003e genes occur frequently in EC (2,3). Based on their gene mutation pattern and frequency, copy number variation, and microsatellite stability, TCGA classified common ECs into four distinct molecular subtypes: POLE ultra-mutated, microsatellite instable (MSI)/ hypermutated, copy‑number low and copy‑number high (2,4). These molecularly defined groups are associated with distinct prognoses\u0026nbsp;(2,4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBuilding on TCGA\u0026rsquo;s genomic analyses, novel clinically applicable molecular genotyping strategies, such as the ProMisE classifier (5,6) and the ESMO guideline (7), have been recently developed to stratify patients by risk into molecular subtypes. According to the ProMisE classification tree, EC can be classified into \u003cem\u003ePOLE\u003c/em\u003e-mutant, MMR deficient (MMRd), p53 abnormal (p53abn), and\u0026nbsp;no specific molecular phenotype (NSMP, lacking all prior three features) molecular subtypes. The hierarchy of classification that the ProMisE tree provides has been further supported by a recent study, in which p53 abnormal ECs with either MMR defect or \u003cem\u003ePOLE\u0026nbsp;\u003c/em\u003emutations are best classified under MMRd or \u003cem\u003ePOLE\u003c/em\u003e-mutant subtypes, respectively (8). The prognosis of \u003cem\u003ePOLE\u003c/em\u003e-mutant subtype is excellent in contrast with the p53abn subtype, which has the most unfavorable outcome with a 5-year overall survival of approximately 40%, which highlights the need for effective treatments. Moreover, while the MMRd and NSMP subtypes have intermediate prognosis, some of these tumors can dedifferentiate and progress to highly aggressive dedifferentiated or undifferentiated\u0026nbsp;endometrial carcinoma (DD/UDEC), diseases that lack biology-informed effective treatments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDD/UDEC is often diagnosed with a peak age of\u0026nbsp;55 years. DDEC occurs when an undifferentiated carcinoma arises clonally from low-grade\u0026nbsp;(9-11) or sometimes high-grade (12,13)\u0026nbsp;endometrioid endometrial carcinoma\u0026nbsp;that are often mismatch repair (MMR)-deficient. The differentiated component is eclipsed in about 40% cases, likely due to an outgrowth of the undifferentiated component, and the tumor overall appears as a pure undifferentiated endometrial carcinoma (UDEC) (9,14). The\u0026nbsp;endometrioid components, generally low-grade, often express estrogen receptor (ER), progesterone receptor (PR) and PAX8, whereas the undifferentiated components are usually negative\u0026nbsp;with occasional focal positivity\u0026nbsp;for ER and PAX8.\u0026nbsp;Recent studies identified frequent inactivating mutations with protein loss in the members of the SWI/SNF chromatin-remodeling complexes such as \u003cem\u003eSMARCA4\u0026nbsp;\u003c/em\u003e(encoding a core ATPase of all types of SWI/SNF), \u003cem\u003eARID1B\u003c/em\u003e (encoding a scaffold protein alternate to ARID1A in BAF-type of SWI/SNF), and \u003cem\u003eSMARCB1\u003c/em\u003e (encoding a core member of BAF and PBAF-types of SWI/SNF) in the undifferentiated components of DD/UDEC (15-18). Furthermore, SMARCA4 inactivation is accompanied by the protein loss of SMARCA2, the only known alternate ATPase; and the inactivation of ARID1B occurs along with ARID1A genetic inactivation, in which the latter is usually present in both differentiated and undifferentiated components of DDEC. These findings suggest that inactivation of canonical BAF-type of SWI/SNF complexes is one major driving force underlying the development of DDEC/UDEC. Additionally, these SWI/SNF-mutant DD/UDECs are typically\u0026nbsp;associated with an extremely poor outcome\u0026nbsp;(19,20), thus demanding novel effective treatments.\u003c/p\u003e\n\u003cp\u003eCancer cell lines established from patients\u0026rsquo; tumor specimens remain the most used models in cancer research. There are dozens of EC cell lines that were established and reported over the past several decades. However, the lack of genomic profiles for most EC cell lines at the time of their establishment posed a barrier for proper pathological and molecular classification. The Broad-Novartis Cancer Cell Line Encyclopedia (CCLE) project has profiled the genomic features of about 1000 cancer cell lines of most common cancer types and centralized the data in the DepMap database at the Broad Institute. This study utilizes this resource, and the genomic information of several in-house developed EC lines, to stratify these EC cell lines molecularly for molecular subtype-specific cancer research. Based on this molecular classification framework, we analyzed the DepMap genome-wide CRISPR knockout screen database and uncovered molecular subtype-specific genetic vulnerabilities.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eMolecular subtyping of EC cell lines.\u003c/strong\u003e To correlate the genomic features of EC cell lines with the molecular subtypes of EC primary tumors, we determined mutation status of \u003cem\u003ePOLE,\u0026nbsp;\u003c/em\u003emismatch repair genes and\u003cem\u003e\u0026nbsp;TP53\u003c/em\u003e using the exome-sequencing data (32 from DepMap database, 5 sequenced in-house), cancer gene panel sequencing (2 sequenced in-house),and the microsatellite stability information (Cell Model Passports database) (\u003cstrong\u003eFig. 1A)\u003c/strong\u003e. Among 39 EC cell lines, HEC251 and JHUEM7 harbor pathogenic \u003cem\u003ePOLE\u003c/em\u003e mutations and 23 have microsatellite instability and/or mutant mismatch repair genes, including AN3CA, COLO704, EN, HEC1 (HEC1A, HEC1B), HEC108, HEC116, HEC151, HEC265, HEC59, HEC6, HHUA, HOUA-I, ISHIKAWA, JHUEM1, MFE296, MFE319, RL962, SNGM, VOA12371, and VOA14590H (\u003cstrong\u003eFig. 1B, Supplementary Table S1\u003c/strong\u003e). For the remaining 14 cell lines, 12 have p53 pathogenic mutations and one (VOA8492) has a homozygous deletion at p53 loci (\u003cstrong\u003eFig. 1B\u003c/strong\u003e). Immunoblotting analysis of 7 p53abn cell lines available for testing validated the aberrant p53 expression in all lines (\u003cstrong\u003eFig. 1C\u003c/strong\u003e). Therefore, our analysis identified all four molecular subtypes of ECs, including 5.2% (2/39), 59% (23/39), 33.3% (13/39) and 2.6% (1/39) for \u003cem\u003ePOLEmut\u003c/em\u003e, MMRd, p53abn and NSMP, respectively. The mutation burden correlates well with the molecular classification, ranging from 180-200 in two \u003cem\u003ePOLEmut\u003c/em\u003e cell lines, 10-132 in MMRd cell lines, 1-20 in p53abn cell lines, and 7.5 in the NSMP cell line (VOA1066). The mutation burden of MMRd EC cell lines is significantly higher than that in p53abn EC cell lines (\u003cstrong\u003eFig. 1D, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eP53abn EC cell lines share common genomic features with their primary tumors.\u003c/strong\u003e As p53abn EC represents the most lethal group of the four molecularly defined EC molecular subtypes, we sought to address whether the identified p53abn EC cell lines recapitulate the genomic features of primary tumors of p53abn EC. Among the 60 TCGA copy number-high ECs where nearly all were p53abn (2), somatic mutations of \u003cem\u003ePIK3CA, FBXW7, PPP2R1A, PIK3R1, ARHGAP35\u003c/em\u003e and \u003cem\u003ePTEN\u003c/em\u003e were present in 47%, 22%, 22%, 13%, 10% and 12% of samples (\u003cstrong\u003eFig. 2A, Supplementary Table S2\u003c/strong\u003e), respectively. \u003cem\u003eFBXW7\u003c/em\u003e and \u003cem\u003ePPP2R1A\u003c/em\u003e mutations were nearly mutually exclusive (Fisher’s Exact test). Moreover, amplification of multiple cancer genes were found in \u0026gt;15% of samples (\u003cstrong\u003eFig. 2A, Supplementary Table S3\u003c/strong\u003e), including those at genomic loci 3q25-29 (15-36.7%: \u003cem\u003eTERC, MECOM, PIK3CA, SOX2\u003c/em\u003e), 17q12 (\u003cem\u003eERBB2\u0026nbsp;\u003c/em\u003e and \u003cem\u003eGRB7\u003c/em\u003e, 25%), 8q24.21 (\u003cem\u003eMYC,\u0026nbsp;\u003c/em\u003e23.3%), 19p13 (\u003cem\u003eNOTCH3, BRD4, SMARCA4, KEAP1,\u0026nbsp;\u003c/em\u003e20-26.7%), 19q12 (\u003cem\u003eCCNE1,\u0026nbsp;\u003c/em\u003e23.3%),1q21-22 (MCL1, 20%; MUC1: 23.3%), 8p11.21 (18.7%: KAT6A), 20q13 (\u003cem\u003eZNF217\u003c/em\u003e, 16.7%), 20q11 (ASXL1, 21.7%), 16p11.2 (\u003cem\u003eSETD1A,\u003c/em\u003e 16.7%), 5p13.3 (15%, DROSHA), 2p23 (PPP1CB, 15%). These findings are largely recapitulated in our recent targeted cancer gene mutation and shallow whole genome analysis of 186 p53abn EC primary tumors (21). Based on these genomic features, about 75% of p53abn ECs contain one or more of the four following targetable features: \u003cem\u003eERBB2\u003c/em\u003e amplification, \u003cem\u003eCCNE1\u003c/em\u003e amplification, \u003cem\u003ePPP2R1A/FBXW7\u003c/em\u003e mutations, and homologous recombination deficiency.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong all 12 p53abn EC cell lines, two (HTMMT, SPAC1L) have inactivating \u003cem\u003ePTEN\u003c/em\u003e and two (TEN and MFE280) have activating \u003cem\u003ePIK3CA\u003c/em\u003e mutations (\u003cstrong\u003eFig. 2B\u003c/strong\u003e). Three cell lines, including TEN, MFE280 and VOA8492, have amplification of \u003cem\u003eERBB2\u003c/em\u003e (\u003cstrong\u003eFig. 2C\u003c/strong\u003e). \u003cem\u003eMYC\u003c/em\u003e is amplified at least 1.5-fold in 4 cell lines, including SNU685, VOA14581, JHUEM3 and SNU1077 cells. Remarkably, \u003cem\u003eCCNE1\u003c/em\u003e is amplified at least 1.5-fold in 7 seven cell lines, including TEN, EMTOKA, KLE, VOA14581, MFE280, VOA8492 and SNU1077 cell lines. Western blotting analysis confirmed elevated CCNE1 expression in\u0026nbsp;four \u003cem\u003eCCNE1\u003c/em\u003e-amplified cell lines, including TEN, KLE, VOA14581 and VOA8492, in comparison to HEC50B and VOA1066, two cell lines with normal \u003cem\u003eCCNE1\u003c/em\u003e copy numbers (\u003cstrong\u003eFig. 2D\u003c/strong\u003e).\u0026nbsp;Notably, SPAC1L also expressed abundant CCNE1 despite of no \u003cem\u003eCCNE1\u003c/em\u003e amplification, which may be due to a hotspot mutation (p.R505S) in WD40 domains of FBXW7 (\u003cstrong\u003eFig. 2B\u003c/strong\u003e), which impair the recognition of its substrates (e.g. CCNE1) and subsequent substrate degradation through E3 ligase. In addition, such \u003cem\u003eFBXW7\u003c/em\u003e mutations were identified in four additional cell lines, EMTOKA (p.R505C), JHUEM3 (p.R465H), VOA8492 (p.R505C) and KLE (p.R479Q) (\u003cstrong\u003eFig. 2B\u003c/strong\u003e). The hotspot mutation of \u003cem\u003ePPP2R1A\u003c/em\u003e at p.P179, p.R183 or p.S256 sites, which occurs in \u0026gt;20% p53abn EC and mutually exclusive to \u003cem\u003eFBXW7\u003c/em\u003e mutation, was only detected in HEC50B (p.R183W) (\u003cstrong\u003eFig. 2B\u003c/strong\u003e). No mutations were found in homologous recombinationrepair genes,\u003cem\u003e\u0026nbsp;e. g. BRCA1\u003c/em\u003e or \u003cem\u003eBRCA2\u003c/em\u003e. Although \u003cem\u003eARID1A\u003c/em\u003e mutation is rare in p53abn EC, its co-occurrence has been shown to drive the development of aggressive EC in mice (22). Analysis of p53abn EC cell lines revealed that EFE184, HMMT, JHUEM3 and SPAC1L cells have \u003cem\u003eARID1A\u003c/em\u003e deleterious mutations (\u003cstrong\u003eFig. 1B\u003c/strong\u003e). Western blotting analysis verified the complete loss of ARID1A in SPAC1L and EFE-184 cells (\u003cstrong\u003eFig. 1C\u003c/strong\u003e), indicating that these two cell lines represent ARID1A-deficient p53abn EC cell lines. Taken together, these data highlight the genomic similarity between p53abn EC primary tumors and cell lines, the latter serving as a powerful resource for translational research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMMRd EC cell lines accumulate frequent p53 and SWI/SNF mutations.\u0026nbsp;\u003c/strong\u003eThe high mutation rate in MMRd EC due to microsatellite instability can lead to the accumulation of additional oncogenic mutations, including\u003cem\u003eTP53\u003c/em\u003e and SWI/SNF genes, that are prevalent in DD/UDECs (mostly MMRd EC) (23). In all 23 MMRd cell lines, 14 have at least one hotspot missense or deleterious \u003cem\u003eTP53\u003c/em\u003e mutation (\u003cstrong\u003eFig. 1B\u003c/strong\u003e), suggesting a selective pressure for accumulating \u003cem\u003eTP53\u003c/em\u003e mutations during tumor progression or prolonged cell culture. Moreover, multiple cell lines contain mutations of SWI/SNF genes commonly occurred in DD/UDECs. In particular, \u003cem\u003eARID1A\u003c/em\u003e and \u003cem\u003eARID1B\u003c/em\u003e are mutated in 91% (21/23) and 74% (17/23) of these cell lines, respectively (\u003cstrong\u003eFig. 1B\u003c/strong\u003e). In addition to the VOA1066 cell line that we previously established from a UDEC patient with ARID1A/B dual loss (24), \u0026nbsp; AN3CA, EN, MFE-296 and VOA14590H cell lines all harbor two deleterious mutations in each of \u003cem\u003eARID1A\u003c/em\u003e and \u003cem\u003eARID1B\u003c/em\u003e genes (\u003cstrong\u003eFig. 1B\u003c/strong\u003e). VOA14590H was derived from a DDEC primary tumor and formed subcutaneous xenograft tumor with undifferentiated histology and dual loss of ARID1A/B protein (\u003cstrong\u003eFig. 3A\u003c/strong\u003e), indicating that VOA14590H is a \u003cem\u003ebona fide\u003c/em\u003e ARID1A/B-dual deficient DDEC cell line. Western blotting analyses confirmed ARID1A/1B dual loss in AN3CA and EN cells, but not those with only one deleterious mutation (\u003cstrong\u003eFig. 3B).\u0026nbsp;\u003c/strong\u003eLike VOA1066 cells, both AN3CA and EN cell lines do not express PAX8 (\u003cstrong\u003eFig. 3B\u003c/strong\u003e), a lineage marker of differentiated endometrial epithelium,suggesting that they were potentially derived from ARID1A/B-dual deficient DD/UDEC tumors.MFE-296 was previously confirmed to be negative for both ARID1A and ARID1B (25), thus representing another UD/DDEC line.Furthermore, a single \u003cem\u003eSMARCA4\u003c/em\u003e inactivating mutation was found in two cell lines, HEC1A and HEC59, but no accompanying protein loss was identified in HEC59 cells by Western blotting (\u003cstrong\u003eFig. 3B\u003c/strong\u003e). Thus, MMRd EC cell lines exhibited a high tendency to accumulate additional progression events, particularly \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eARID1B\u003c/em\u003e mutations, mirroring those in primary tumors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTumorigenicity of EC cell lines.\u0026nbsp;\u003c/strong\u003eNext, we inoculated all available MMRd and p53abn cell lines into immunodeficient mice to determine their tumorigenicity and histological features.\u0026nbsp;All of the 8 MMRd cell lines available for xenografting,\u0026nbsp;including HEC59, HEC1B, HEC116, VOA12371, AN3CA, EN, HOUA-I, and VOA14590H, developed subcutaneous tumors at various latency and doubling time (\u003cstrong\u003eFig. 4A\u003c/strong\u003e). Histology assessment revealed diverse histology, ranging from intermediate (HEC59, HOUA-I) or poorly differentiated (HEC1B, HEC116, VOA12371) to undifferentiated (AN3CA, EN, VOA14590H) (\u003cstrong\u003eFig. 4B and 3A, Supplementary Fig. S1A\u003c/strong\u003e), further supporting that AN3CA, EN and VOA14590H are representative cell lines of ARID1A/B-dual deficient DD/UDEC. Furthermore, Western blotting and IHC staining validated the mutant \u003cem\u003ep53\u003c/em\u003e status in 5 out of 9 tested cell lines, including HEC59, HEC1B, HEC116, EN and AN3CA (\u003cstrong\u003eSupplementary Fig. S1B, Fig. 4B\u003c/strong\u003e). Among the 7 p53abn EC cell lines tested, including VOA8492, VOA14581, SPAC1L, HEC50B, KLE, EFE-184 and TEN, 4 (HEC50B, SPAC1L, VOA8492 and TEN) developed subcutaneous tumors (\u003cstrong\u003eFig. 4A\u003c/strong\u003e). Histology assessment revealed that SPAC1L and VOA8492 xenografted tumors exhibited papillary serous endometrial carcinoma histology (\u003cstrong\u003eFig. 4C\u003c/strong\u003e), corresponding to the diagnosis of their primary tumors (26) (\u003cstrong\u003eSupplementary Fig. S2\u003c/strong\u003e), whereas HEC50B and TEN displayed features of high grade endometrioid carcinoma and clear cell endometrial carcinoma, respectively (\u003cstrong\u003eFig. 4C, Supplementary Fig. 1C\u003c/strong\u003e), consistent with the diagnosis of their primary tumors (27,28). Immunostaining revealed negative p53 staining in VOA8492 and HEC50B cells and a mutant p53 staining pattern in \u0026nbsp;SPAC1L cells \u0026nbsp; (\u003cstrong\u003eFig. 4C\u003c/strong\u003e). SPAC1L was also negative for ARID1A staining (\u003cstrong\u003eFig. 4C\u003c/strong\u003e), supporting it as an \u003cem\u003eARID1A\u003c/em\u003e-mutant p53abn EC cell line.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelective genetic vulnerabilities in p53abn and MMRd EC cells.\u0026nbsp;\u003c/strong\u003eNext,we endeavored to identify preferential essential genes for each non-\u003cem\u003ePOLEmut\u003c/em\u003e molecular subtype using the DepMap CRISPR screen database, which included the data for 25 endometrial cancer cell lines. When comparing MMRd to p53abn cell lines, we identified multiple genes whose deletion was selectively lethal to MMRd or p53abn EC cells (\u003cstrong\u003eFig. 5A\u003c/strong\u003e, \u003cstrong\u003eSupplementary Table S4\u003c/strong\u003e). This includes WRN for MMRd cells and CDK2, CCNE1 and KIF18A for p53abn cells. WRN was previously shown to be a selective vulnerability in cancer cells with microsatellite instability (29) and inhibition of KIF18A was known to preferentially suppress the growth of p53-mutant ovarian and breast cancer cells (30). As many of the p53abn EC cell lines have \u003cem\u003eCCNE1\u003c/em\u003e amplification or \u003cem\u003eFBXW7\u003c/em\u003e inactivating mutations (\u003cstrong\u003eFig. 2B\u003c/strong\u003e and \u003cstrong\u003e2C\u003c/strong\u003e), it is also not surprising that these cell lines were more vulnerable to the depletion of either \u003cem\u003eCCNE1\u003c/em\u003e or \u003cem\u003eCDK2\u003c/em\u003e, the latter encoding the canonical interacting partner of CCNE1. Therefore, these findings confirm the validity of our analysis approach in identifying molecular subtype-specific lethal targets.\u003c/p\u003e\n\u003cp\u003eNotably, our analysis identified PELO as the top one synthetic lethal target for MMRd EC cell lines. Using CRISPR/Cas9, we demonstrated that \u003cem\u003ePELO\u0026nbsp;\u003c/em\u003edeletion selectively suppressed the growth of MMRd EC cell lines, HEC1B and HEC116, but not p53abn EC cell lines, HEC50B and TEN (\u003cstrong\u003eFig. 5B\u003c/strong\u003e and \u003cstrong\u003e5C\u003c/strong\u003e). \u0026nbsp;Therefore, our approach was able to identify novel synthetic lethal targets for specific molecular subtypes of EC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eARID1A/B-dual deficient DD/UDEC cells rely on mitochondria oxidative phosphorylation.\u0026nbsp;\u003c/strong\u003eBecause DD/UDEC represents one highly lethal histologic subtype of EC that is under-studied, there is an unmet need to identify specific lethal targets in ARID1A/B-dual deficient DD/UDEC. Since the DepMap CRISPR/Cas9 database only included two identified ARID1A/B-dual deficient DD/UDEC cell lines, EN and MFE-296, we searched all CCLE cell lines for \u003cem\u003eARID1A\u0026nbsp;\u003c/em\u003eand \u003cem\u003eARID1B\u003c/em\u003e deleterious mutations (\u003cstrong\u003eSupplementary Table S5\u003c/strong\u003e), leading to the identification of two more cell lines, EFO-27 and SKUT1, each harboring 2 deleterious mutations for \u003cem\u003eARID1A\u0026nbsp;\u003c/em\u003eand \u003cem\u003eARID1B,\u003c/em\u003e respectively.EFO-27 was derived from ovarian endometrioid ovarian cancers, which arise from extra-uterine endometrial epithelial cells and share histopathological and genomic features with endometrial endometrioid cancers. Immunoblotting confirmed ARID1A/B dual loss in EFO-27 (\u003cstrong\u003eSupplementary Fig. S3\u003c/strong\u003e). SKUT1 was derived from uterine tumors with carcinosarcoma features in 1977 (31). As uterine carcinosarcomas share common features with DDEC (32) and DD/UDEC has only been recognized in the past 2 decades, it remains possible that the original tumor from which SKUT1 cells were derived was a DDEC or contained a minor undifferentiated component with ARID1A/B dual deficiency. Therefore, these two cell lines were grouped with EN and AN3CA for preferential essential gene analysis. In comparison to 27 EC cell lines without ARID1A/B dual loss, ARID1A/B-dual deficient cell lines are selectively lethal to the loss of genes that are enriched for mitochondria function (\u003cstrong\u003eFig. 6A, Supplementary Table S6\u003c/strong\u003e), which is in line with our previous finding that SMARCA4/2-deficient ovarian and lung tumors rely on mitochondria phosphorylation (33).\u003c/p\u003e\n\u003cp\u003eTo assess the potential dependency on mitochondria oxidative phosphorylation in ARID1A/1B-dual deficient DDEC, we evaluated the efficacy of IACS-010759, a highly selective mitochondria electron transport chain Complex I inhibitor (34), in a panel of EC cell lines. IACS-010759 inhibited mitochondria respiration (\u003cstrong\u003eFig. 6B, Supplementary Fig. S4\u003c/strong\u003e) and the growth of ARID1A/1B-dual deficient DDEC cells (\u003cstrong\u003eFig. 6C\u0026nbsp;\u003c/strong\u003eand \u003cstrong\u003e6D\u003c/strong\u003e), but had little effect on the growth of ARID1A/1B-proficient EC cells (\u003cstrong\u003eFig. 6C\u003c/strong\u003e). In addition, daily treatment of IACS-010759 for 10 days significantly suppressed the tumor growth of VOA1066 cell line-xenograft tumors in immunodeficient mice (\u003cstrong\u003eFig. 6E and 6F\u003c/strong\u003e) without observable toxicity at necropsy. Lastly, to assess whether dual loss of ARID1A/B creates a dependence on mitochondria function, we inactivated \u003cem\u003eARID1B\u003c/em\u003e by CRISPR/Cas9 in HEC1B (\u003cstrong\u003eFig. 6G\u003c/strong\u003e), an ARID1A-deficient/ARID1B-proficient EC cell line, which significantly increased the cellular sensitivity to IACS-010759 treatment (\u003cstrong\u003eFig. 6H\u003c/strong\u003e). Taken together, these data indicate that ARID1A/1B-dual deficiency conferred increased cellular sensitivity to the inhibition of mitochondria electron transport chain activity.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCancer cell lines are crucial tools in cancer research as they provide consistent and reproducible models for studying disease biology and developing therapeutics. However, the reliability of cancer cell lines in modelling disease depends on the original diagnosis when the cell lines were established and may be questioned as our understanding of the disease evolves. Therefore, the proper classification of cell lines is critical for their application in basic and translational cancer research. We have previously reclassified multiple gynecologic cancer cell lines based on genomic understanding of the relevant diseases and histologic reassessment (13), leading to improved representation of molecularly defined ovarian cancer cell lines in large scale functional genomic screen studies and subsequent identification of targetable vulnerabilities in those molecularly defined ovarian cancer subtypes (33). In this study, we classified EC cell lines into lately recognized clinically relevant molecular subtypes, which will guide the future use of these cell lines for identifying and/or validating novel therapeutics for each molecular subtype. Accordingly, utilizing publicly available genome-wide CRISPR knockout screen database on these cell lines, we identified putative targetable features in several molecular subtypes of EC. In particular, we validated that MMRd EC cells are highly sensitive to PELO deletion, which supports a recent report describing PELO dependency in microsatellite instable cells by Borck et al. (35) during the preparation of this manuscript. We also demonstrated that ARID1A/B dual deficiency, mimicking SMARCA4/2-dual deficiency (33), creates a dependency on oxidative phosphorylation, indicating that patients with these highly lethal SWI/SNF-deficient cancers may be grouped together for clinical trials testing the efficacy of mitochondria-targeting therapeutic approaches, e.g., electron transport complex I inhibitors.\u003c/p\u003e\n\u003cp\u003eARID1A/B-dual deficient DD/UDEC has been recently recognized as a highly lethal EC subtype. We have previously established the first UDEC cell line, VOA1066, from a primary tumor with ARID1A/B dual deficiency (24). This cell line has a low mutation burden, normal p53 expression and is classified as an NSMP cell line, supporting the notion that DD/UDEC can arise from NSMP ECs, and represents a highly lethal outlier of NSMP ECs that are otherwise innocent. Our present study further established the VOA14590H cell line from an ARID1A/B-dual deficient primary DDEC tumor and identified three more ARID1A/B-dual deficient EC cell lines, EN, AN3CA and MFE-296. All these four cell lines are MMRd and representative models of ARID1A/B-dual deficient DD/UDECs with MMRd. Notably, VOA14590H was developed independently from the same primary tumor that was utilized for developing the DDEC-3 cell line by Wong et al.(36). Future genomic analysis is required to determine whether these two cell lines can be considered as the same cell line. Furthermore, our study also identified that SKUT1 may arise from a primary tumor representing or containing a component of DD/UDEC with ARID1A/B dual deficiency, rather than the original diagnosis of carcinosarcoma. This finding is critical as it will allow for the proper use of this cell line for future basic and translational studies. Moreover, our study also demonstrated that EFO-27, which originated from an ovarian endometrioid carcinoma, represents an ARID1A/B-dual deficient DD/UDOC cell line. However, as none of the primary tumors used to establish EN, AN3CA, MFE-296, SKUT1 and EFO-27 are available for reinvestigation, it remains possible that dual-loss of ARID1A and ARID1B may accumulate during prolonged culture as all these cell lines are hyper-mutated, which can facilitate the emergence and selection of these aggressive clones. Nevertheless, we capitalized on the identification of these ARID1A/B-dual deficient cancer cell lines and uncovered that these cancer cells are selectively more sensitive to inhibition of mitochondria oxidative phosphorylation \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. This observation extends the previous findings from us and others describing the increased reliance on oxidative phosphorylation in SMARCA4-deficient cancers (33,37), suggesting that SWI/SNF-mutant cancers, particularly those with defective canonical BAF, share common metabolic vulnerability and can be grouped together into a basket trial for assessing the clinical benefit of mitochondria-targeting therapeutic approaches, e.g., electron transport complex I inhibitors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition to characterizing multiple ARID1A/B-dual deficient DD/UDEC cell lines, our study also identified a number of p53abn EC cell lines. This paves the way for identifying putative druggable targets in p53abn EC, which is often aggressive clinically. Our analysis of genome-wide CRISPR screen data on EC cell lines indicate that p53abn EC cells may rely more on several genes, such as CDK2 and KIF18A. CDK2 is a cyclin-dependent kinase that pairs with E- and A-type cyclins during S and G2 cell cycle phases. It has multiple roles in cell cycle checkpoint control and its function is often redundant with that of CDK1 (38,39). However, in the absence of p53, CDK2 is essential for G2/M checkpoint control and is non-redundant with CDK1 (40). Moreover, previous studies have reported that p53 represses CDK2 during DNA damage or oncogene-induced cellular senescence. Therefore, inhibition of CDK2 can decrease tumor penetrance and delay tumor onset in p53-null pineal tumor cells (41). Notably, a recent study reported that CDK2 is critical for repairing collapsed replication fork in CCNE1-amplified ovarian cancer cells (42). As several of these p53abn EC cell lines have amplified \u003cem\u003eCCNE1\u003c/em\u003e and/or stabilized CCNE1 protein due to FBXW7 inactivation, the dependence on CDK2 in p53abn EC cell lines could be partially attributed to the hyperactivity of CCNE1. Furthermore, KIF18A motor protein utilizes ATP hydrolysis to move along kinetochore-microtube fibers (43). It has been discovered that KIF18A is a selective vulnerability in chromosome instable cancer cell lines, such as p53-mutant cancer cells (30,44-46). \u0026nbsp; Nonetheless, these findings suggest that pharmacologic inhibition of CDK2 or KIF18A may have clinical implications for p53abn EC, which requires further investigation to determine whether all or a subset of p53abn EC can benefit from these approaches. As these cells often have multiple targetable features, like \u003cem\u003eCCNE1\u0026nbsp;\u003c/em\u003eand \u003cem\u003eERBB2\u003c/em\u003e amplifications in TEN, future studies are also needed to assess whether there is any synergistic effect for co-targeting these oncogenic features.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLastly, our study not only provides the molecular classification for EC cell lines, but also validates or establishes their tumorigenicity in immunodeficient mice. These efforts will facilitate future translational research using these cell lines. Notably, though several p53abn cell lines, including KLE, VOA14581, and EFE-184, failed to develop subcutaneous tumors in our study the tumorgenicity of KLE has been previously reported. Gao et al. isolated CD44 and CD133-positive tumor initiating cells from KLE, which were able to develop subcutaneous tumors in athymic nude mice (47). KLE was also able to develop slow-growing orthotopic tumors (48) or lung metastasis through tail vein injection (49) in nude mice. Therefore, additional studies are necessary to further validate the tumorigenicity of VOA14581 and EFE-184 cell lines in immune compromised mice.\u003c/p\u003e\n\u003cp\u003eTaken together, our study provides the molecular classification of EC cell lines to accelerate basic and translation research in EC. In particular, ARID1A/B-dual deficient DD/UDEC cells are selectively sensitive to pharmacologic inhibition of mitochondria phosphorylation \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e, which warrants clinical investigation to inform the design of optimal treatment approach for these highly aggressive cancers.\u0026nbsp;\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eCell lines and patient tissues.\u0026nbsp;\u003c/strong\u003eHEC50B, TEN, HOUA-I, HEC59, HEC116, HEC1B, KLE, EFE-184, SPAC-1L, AN3CA, EN and EFO-27\u0026nbsp;cells were grown in RPMI media supplemented with 5% characterized FBS (Corning, cat # CA76322-116) and grown at 37 degrees in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator.\u003c/p\u003e\n\u003cp\u003eTo establish cell lines from patients\u0026rsquo; specimens, primary tumor tissues or ascites were collected under the\u0026nbsp;University of British Columbia Ethics Board protocol H02-61375 and H18-01457, at the time of surgery after obtaining an informed consent from the patients. For VOA8492, VOA14581 and VOA14590H cell lines, tumor tissues were minced and digested in 2.5mg/mL Collagenase D (Sigma-Aldrich, cat#11088882001). After 60 minutes, single cells from the solution were placed into Petri dishes with 199:105 media, consisting of a 1:1 ratio of media 199 (Thermofisher Scientific, cat#31100035) and media 105 (Sigma-Aldrich, cat#M6395) fortified with 10% defined FBS (Hyclone, cat#SH30070.03) and 10 mg/mL of Gentamicin (Thermofisher Scientific, cat#15710064). For VOA12371 cell line, cells from ascites were lysed by ammonia chloride to remove red blood cells. Primary cells were left to adhere and grow at 37 degrees in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator with culture medium replaced every 3-4 days. Cancer cells were enriched by differential trypsinization and subsequent removal of fibroblasts, and continuously passaged for at least 20 passages to ensure the establishment of cell lines.\u003c/p\u003e\n\u003cp\u003eAll cell lines were certified by the short tandem repeat (STR) analysis through LabCorp, tested regularly for \u003cem\u003eMycoplasma\u003c/em\u003e (Genetica, DNA Laboratories), and used for the study within 6 months of thawing from liquid nitrogen storage.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExome sequencing, mapping and variant calling.\u0026nbsp;\u003c/strong\u003eThe whole exome sequencing datasets available for EC cell lines were downloaded from the DepMap database (2023Q2). Whole exome data of VOA1066 cell line was obtained from our previous study (24).\u0026nbsp;We also performed whole exome sequencing on SPAC1L and two in-house developed EC cell lines, VOA8492 and VOA15481 as well as their respective normal DNA from buffy coat samples. Briefly, genomic DNA isolated from cells and patients\u0026rsquo; buffy coats were fragmented to a target size of 150-200 bp on the Covaris E210 system and the whole-exome was sequenced as previously described (13). Fastq files were aligned with Burrows-Wheeler Aligner (BWA) 0.7.5a to hs37d5, and the SAM output file was converted into a sorted BAM file using SAMtools 0.1.19. BAM files underwent indel realignment, duplicate marking and recalibration steps in this order with the Genome Analysis Toolkit (GATK) 2.8-1, where dpsnp137 was used for known SNPs and Mills_and_1000G_gold_ standard.indels.b37.vcf was used for known indels. Variant calling was carried out in tumor-only mode with HaplotypeCaller, and output VCF files were recalibrated with VariantRecalibrator from GATK 2.8-1. SnpEff 3.2 and SnpSift 1.9c were then used to annotate these VCF files with database version GRCh37.70. Only variants with a minimum quality score of 20 were extracted. Thereafter, we excluded variants with a Global Minor Allele Frequency \u0026gt;= 0.01 and those somatic coding variants (SNVs) that either appeared in the 1000 Genomes Project database, the dbSNP database or the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project database, assuming that these SNVs might be of less importance for tumorigenesis. Somatic copy number analysis was completed following the GATK tutorial \u0026ldquo;(How to part I) Sensitively detect copy ratio alterations and allelic segments\u0026rdquo; and verified using Novogene copy number analysis (copy number called using Control-FREEC).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTargeted panel sequencing.\u003c/strong\u003e We performed targeted cancer gene panel sequencing for VOA12371 cell line and VOA14590H xenograft tumor using\u0026nbsp;the QIAseq Comprehensive Cancer Panel\u0026nbsp;as previously described\u0026nbsp;(21). The resulting raw Fastq files were uploaded to QIAseq\u0026apos;s cloud-based processing portal GeneGlobe. Using this portal, we ran the QIAseq-developed processing pipeline for trimming, alignment, post-processing, and mutation calling against the reference genome hg38. Subsequently, results for all samples were concatenated and extensive mutation filtering was performed manually to remove artifacts. Output files for all samples were combined so that common germline SNPs and artifacts could be removed. Further filtering using gnomAD and ClinVar (50,51) was performed to filter out more germline SNPs and variants with a Global Minor Allele Frequency \u0026gt;= 0.01. \u0026nbsp;Additionally, all \u0026ldquo;modifier\u0026rdquo; mutations occurring far from splice sites were removed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenome-wide CRISPR screen data analysis.\u0026nbsp;\u003c/strong\u003eCRISPR/Cas9 knockout data was downloaded from the DepMap database (2023Q2). Differential gene dependency was determined by using two-sided Wilcoxon rank sum test to compare the DepMap CRISPR knockout data gene effect scores between MMRd and p53abn EC cell lines or between ARID1A/B dual-deficient cell lines and the remaining endometrial cancer cell lines with available screen data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern blotting.\u0026nbsp;\u003c/strong\u003eWhole cell lysates were extracted using urea lysis buffer (9M urea, 4% CHAPS, 0.5% IPG buffer, 50mM DTT, Sigma-Aldrich). 20 \u0026mu;g of cell lysate was resolved on SDS-PAGE gels for protein detection. Antibodies against SMARCA4 (Abcam, cat# ab11064, 1:5000), SMARCA2 (Cell Signaling Technology, cat#D9E8B, 1:1000), ARID1A (Sigma-Aldrich HPA005456 1:1000), p53 (ProteinTech, 10442-1-AP, 1:3000), PAX8 ( ), PELO (ProteinTech, cat#10582-1-AP, 1:2000). Ponceau S staining and/or Vinculin (Sigma-Aldrich, cat#V9131, 1:10000) were used to confirm equal protein loading.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunohistochemistry.\u0026nbsp;\u003c/strong\u003eFormalin fixed, paraffin embedded tissue blocks were sectioned at 4\u0026mu;m thickness onto Superfrost+ glass slides and immunohistochemically stained with the Leica BOND RX system. Antibodies used for immunohistochemistry were previously described (13,23). Staining was evaluated by one or both gynecologic pathologists (L. H., S.M.)\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene knockout by CRISPR/Cas9 technology.\u0026nbsp;\u003c/strong\u003eKnockout of ARID1B and PELO were achieved by a pool of 3 GFP-tagged CRISPR/Cas9 KO plasmids targeting ARID1B (Santa Cruz, sc-402365) or 3 individual CRISPR/Cas9 KO plasmids targeting PELO with the following sgRNA sequences: GGCTTGAGAGTCGAAGTCGA, TGGTCCCCTTAACCCGCAGC and AGTCCATAGAAAGCTCGATC. These sgRNA sequences were cloned into LentiCRISPR-v2-puro vector (a gift from Feng Zhang, Addgene #52961) (52). Viral packaging and infection were completed as previously described (13). GFP-positive or puromycin-resistant pooled cells were harvested for western blotting to confirm target depletion.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell growth assays.\u0026nbsp;\u003c/strong\u003eFor measuring cell growth, cells were seeded at1500 cells/well in quadruplicate in 24-well plates. Plates were fixed when control conditions grew up to 80-100% confluence, which usually takes 8-21 days after plating. To determine cell growth after drug treatment, cells were treated with either vehicle or testing agents 24 hours after plating. Treatments were refreshed every 4 days until the control conditions reached confluence. Cells were fixed with 10% trichloroacetic acid (Sigma-Aldrich cat# T6399-500G) before washing. Once plates were dry, the cells were stained with 0.4% (wt/vol) sulforhodamine B (Sigma-Aldrich cat# 230162) dissolved in 1% acetic acid. The stain was dissolved with 10 mM Tris-base pH 10.5 to quantify cell growth that was normalized to relevant control conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSeahorse assays\u003c/strong\u003e. Mitochondria oxygen consumption rates (OCR) were determined using the XF96 Pro Analyzer (Seahorse Bioscience) as previously described (33). Briefly, cells were seeded at 18,000-40,000 cells/well at 90% confluency in Seahorse XF96 Pro cell culture microplates (Agilent) the day before the experiment. An hour prior to running the assay, cells were refreshed with RPMI supplemented with 2 mM L-glutamine, 10 mM glucose, 1 mM sodium pyruvate and either DMSO or 2 nM of IACS-10759 (ChemieTek, cat# CT-IACS107) adjusted to pH 7.4 and kept in at 37\u0026deg;C in CO\u003csub\u003e2\u003c/sub\u003e-free incubator. Afterwards, plates were loaded on the Seahorse Analyzer followed by sequential injections of oligomycin (Sigma-Aldrich, cat: O4876, FCCP (Sigma-Aldrich, cat#C2920), and a mixture of antimycin A (Sigma-Aldrich, cat#A8674) and rotenone (Sigma-Aldrich, cat#R8875) to a final concentration of 1\u0026thinsp;\u0026mu;M of oligomycin, 1.5\u0026thinsp;\u0026mu;M of FCCP, and 1\u0026thinsp;\u0026mu;M antimycin A, and 100 nM rotenone respectively, at 35, 56, and 77 minutes. OCR were normalized to the DMSO condition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMouse xenograft studies.\u003c/strong\u003e All procedures related to animal handling, care and treatment in this study were approved by the Animal Care Committee of the University of British Columbia (A22-0005). Briefly, 5-10x10\u003csup\u003e6\u003c/sup\u003e cells per mouse, with a 1:1 mix of Matrigel (Corning) in a final volume of 200 \u0026mu;l, were injected subcutaneously into the back of NRG (NOD.Rag1KO.IL2R\u0026gamma;cKO) mice. Tumor volumes and mouse weights were measured twice weekly. Tumor volume was calculated with the following formula: length x (width)\u003csup\u003e2\u003c/sup\u003e x 0.52. Mice were monitored for health until they reached humane endpoints for tumor isolation. Isolated tumors were fixed in 10% neutral buffered formalin and embedded for histology analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis.\u0026nbsp;\u003c/strong\u003eUnless otherwise specified, the student\u0026apos;s \u003cem\u003et\u003c/em\u003e test was used to evaluate the significant difference between 2 groups of data in all \u003cem\u003ein vitro\u003c/em\u003e experiments. \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 was considered significant.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated for in-house developed cell lines during the current study are not publicly available due to the restriction of research ethics approval but are available from the corresponding author on reasonable request through a material transfer agreement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEL and RH: investigation, data analysis, manuscript writing-first draft; RT and CYS: investigation and manuscript editing; YWC, CYS, SYC, JS, BY, LJ, EY, and SDM: investigation; MC and BTH: resource; DGH and RIKG: funding acquisition and supervision; LH: funding acquisition, investigation and supervision; and YW: Conceptualization, supervision, funding acquisition, manuscript writing-first draft and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Ms. Clara Salamanca, Ms. Jingjie Guo and all staffs from the Molecular and Advanced Pathology Core at the University of British Columbia for technical supports. This work was supported by research funds from the Canadian Institutes of Health Research (CIHR) grants (PJT-178179; PJT-197923, to YW), Terry Fox New Frontiers Program Project Grants (TFRI PPG, #1116, to LH, YW and DGH) and Natural Science and Engineering Research Council-discovery grant (RGPIN-2020-05390, to RIKG). R.H., B.Y. and L.J. are recipients of the Canadian Graduate Scholarships-Master’s Program. R.H. is a recipient of the Canadian Cancer Society Training Research Training Award. We also appreciate the generous supports from the British Columbia Cancer Foundation and the VGH/UBC Hospital Foundation to the Ovarian Cancer Research Centre. The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no financial or non-financial competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSetiawan VW, Yang HP, Pike MC, McCann SE, Yu H, Xiang YB\u003cem\u003e, et al.\u003c/em\u003e Type I and II endometrial cancers: have they different risk factors? J Clin Oncol \u003cstrong\u003e2013\u003c/strong\u003e;31:2607-18\u003c/li\u003e\n\u003cli\u003eCancer Genome Atlas Research N, Kandoth C, Schultz N, Cherniack AD, Akbani R, Liu Y\u003cem\u003e, et al.\u003c/em\u003e Integrated genomic characterization of endometrial carcinoma. 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Nat Methods \u003cstrong\u003e2014\u003c/strong\u003e;11:783-4\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-precision-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjprecisiononcology","sideBox":"Learn more about [npj Precision Oncology](http://www.nature.com/npjprecisiononcology/)","snPcode":"41698","submissionUrl":"https://submission.springernature.com/new-submission/41698/3","title":"npj Precision Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6536216/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6536216/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEndometrial carcinoma (EC), the most common gynecologic cancer type, encompasses multiple molecular subtypes that have consistent prognostic values and are being adopted in clinical practice to guide treatment decisions. However, it remains unclear whether each of these molecular subtypes have unique therapeutic vulnerabilities that can be exploited for advancing the management of ECs. Through analyzing the genomic features of a panel of 39 EC cell lines, we identified multiple tumor cell lines representing each molecular subtype. Histologic and immunochemical analyses of xenografted tumors from these cell lines confirmed their resemblance of cognate primary EC molecular subtypes, both by histology and the protein expression status of mismatch repair genes, p53 and SWI/SNF members in corresponding subtypes. Further investigation of the publicly available genome-wide CRISPR data for EC cell lines identified multiple specific genetic vulnerabilities in mismatch repair-deficient, p53-abnormal and ARID1A and ARID1B-dual deficient EC cell lines, respectively. Particularly, ARID1A and ARID1B-dual deficient EC cells selectively rely on mitochondria oxidative phosphorylation \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. Therefore, our study demonstrates the utility of EC cell line models for uncovering and validating therapeutic vulnerabilities of each EC molecular subtype.\u003c/p\u003e","manuscriptTitle":"Molecular subtyping of endometrial carcinoma cell lines uncovers subtype-specific targetable vulnerabilities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-10 06:12:51","doi":"10.21203/rs.3.rs-6536216/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-03T03:37:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-27T03:33:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-23T09:48:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"158291273748073255924651485250609557875","date":"2025-05-05T00:18:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"168368555076533519761131118458376681804","date":"2025-05-02T07:14:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"192382905554018507061645653627372913940","date":"2025-05-01T11:51:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-01T09:12:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-30T03:28:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-29T15:51:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Precision Oncology","date":"2025-04-26T16:37:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-precision-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjprecisiononcology","sideBox":"Learn more about [npj Precision Oncology](http://www.nature.com/npjprecisiononcology/)","snPcode":"41698","submissionUrl":"https://submission.springernature.com/new-submission/41698/3","title":"npj Precision Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e06f6054-5f35-493c-851d-5dd3be716684","owner":[],"postedDate":"May 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":48048950,"name":"Biological sciences/Cancer/Cancer models"},{"id":48048951,"name":"Biological sciences/Cancer/Cancer therapy"},{"id":48048952,"name":"Biological sciences/Cancer/Gynaecological cancer"}],"tags":[],"updatedAt":"2025-07-28T15:59:47+00:00","versionOfRecord":{"articleIdentity":"rs-6536216","link":"https://doi.org/10.1038/s41698-025-01053-x","journal":{"identity":"npj-precision-oncology","isVorOnly":false,"title":"npj Precision Oncology"},"publishedOn":"2025-07-24 15:57:07","publishedOnDateReadable":"July 24th, 2025"},"versionCreatedAt":"2025-05-10 06:12:51","video":"","vorDoi":"10.1038/s41698-025-01053-x","vorDoiUrl":"https://doi.org/10.1038/s41698-025-01053-x","workflowStages":[]},"version":"v1","identity":"rs-6536216","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6536216","identity":"rs-6536216","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}