A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity

Intrinsic PARG inhibitor sensitivity is mimicked by TIMELESS haploinsufficiency and rescued by nucleoside supplementation

A subset of cancer cells are intrinsically sensitive to inhibitors targeting PARG, the poly(ADP-ribose) glycohydrolase that degrades PAR chains. Sensitivity is accompanied by persistent DNA replication stress, and can be induced by inhibition of TIMELESS, a replisome accelerator. However, the nature of the vulnerability responsible for intrinsic sensitivity remains undetermined. To understand PARG activity dependency, we analysed Timeless model systems and intrinsically sensitive ovarian cancer cells. We show that nucleoside supplementation rescues all phenotypes associated with PARG inhibitor sensitivity, including replisome speed and fork stalling, S-phase completion and mitotic entry, proliferation dynamics and clonogenic potential. Importantly nucleoside supplementation restores PARG inhibitor resistance despite the continued presence of PAR chains, indicating that sensitivity does not correlate with PAR levels. In addition, we show that inhibition of thymidylate synthase, an enzyme required for dNTP homeostasis, induces PARG-dependency. Together, these observations suggest that PARG inhibitor sensitivity reflects an inability to control replisome speed and/or maintain helicase-polymerase coupling in response to nucleotide imbalances.

Oncogenic Pathways and Targeted Therapies in Ovarian Cancer

Epithelial ovarian cancer (EOC) is one of the most aggressive forms of gynaecological malignancies. Survival rates for women diagnosed with OC remain poor as most patients are diagnosed with advanced disease. Debulking surgery and platinum-based therapies are the current mainstay for OC treatment. However, and despite achieving initial remission, a significant portion of patients will relapse because of innate and acquired resistance, at which point the disease is considered incurable. In view of this, novel detection strategies and therapeutic approaches are needed to improve outcomes and survival of OC patients. In this review, we summarize our current knowledge of the genetic landscape and molecular pathways underpinning OC and its many subtypes. By examining therapeutic strategies explored in preclinical and clinical settings, we highlight the importance of decoding how single and convergent genetic alterations co-exist and drive OC progression and resistance to current treatments. We also propose that core signalling pathways such as the PI3K and MAPK pathways play critical roles in the origin of diverse OC subtypes and can become new targets in combination with known DNA damage repair pathways for the development of tailored and more effective anti-cancer treatments.

Specialized replication mechanisms maintain genome stability at human centromeres

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

The reckoning of chromosomal instability: past, present, future

Quantitative measures of CIN are crucial to our understanding of its role in cancer. Technological advances have changed the way CIN is quantified, offering increased accuracy and insight. Here, we review measures of CIN through its rise as a field, discuss considerations for its measurement, and look forward to future quantification of CIN.

Chromosomal instability in aneuploid acute lymphoblastic leukemia associates with disease progression

Chromosomal instability (CIN) lies at the core of cancer development leading to aneuploidy, chromosomal copy-number heterogeneity (chr-CNH) and ultimately, unfavorable clinical outcomes. Despite its ubiquity in cancer, the presence of CIN in childhood B-cell acute lymphoblastic leukemia (cB-ALL), the most frequent pediatric cancer showing high frequencies of aneuploidy, remains unknown. Here, we elucidate the presence of CIN in aneuploid cB-ALL subtypes using single-cell whole-genome sequencing of primary cB-ALL samples and by generating and functionally characterizing patient-derived xenograft models (cB-ALL-PDX). We report higher rates of CIN across aneuploid than in euploid cB-ALL that strongly correlate with intraclonal chr-CNH and overall survival in mice. This association was further supported by in silico mathematical modeling. Moreover, mass-spectrometry analyses of cB-ALL-PDX revealed a "CIN signature" enriched in mitotic-spindle regulatory pathways, which was confirmed by RNA-sequencing of a large cohort of cB-ALL samples. The link between the presence of CIN in aneuploid cB-ALL and disease progression opens new possibilities for patient stratification and offers a promising new avenue as a therapeutic target in cB-ALL treatment.

The drug efficacy testing in 3D cultures platform identifies effective drugs for ovarian cancer patients

Most patients with advanced ovarian cancer (OC) relapse and progress despite systemic therapy, pointing to the need for improved and tailored therapy options. Functional precision medicine can help to identify effective therapies for individual patients in a clinically relevant timeframe. Here, we present a scalable functional precision medicine platform: DET3Ct (Drug Efficacy Testing in 3D Cultures), where the response of patient cells to drugs and drug combinations are quantified with live-cell imaging. We demonstrate the delivery of individual drug sensitivity profiles in 20 samples from 16 patients with ovarian cancer in both 2D and 3D culture formats, achieving over 90% success rate in providing results six days after operation. In this cohort all patients received carboplatin. The carboplatin sensitivity scores were significantly different for patients with a progression free interval (PFI) less than or equal to 12 months and those with more than 12 months (p < 0.05). We find that the 3D culture format better retains proliferation and characteristics of the in vivo setting. Using the DET3Ct platform we evaluate 27 tailored combinations with results available 10 days after operation. Notably, carboplatin and A-1331852 (Bcl-xL inhibitor) showed an additive effect in four of eight OC samples tested, while afatinib and A-1331852 led to synergy in five of seven OC models. In conclusion, our 3D DET3Ct platform can rapidly define potential, clinically relevant data on efficacy of existing drugs in OC for precision medicine purposes, as well as provide insights on emerging drugs and drug combinations that warrant testing in clinical trials.

Centromere: A Trojan horse for genome stability

Centromeres play a key role in the maintenance of genome stability to prevent carcinogenesis and diseases. They are specialized chromosome loci essential to ensure faithful transmission of genomic information across cell generations by mediating the interaction with spindle microtubules. Nonetheless, while fulfilling these essential roles, their distinct repetitive composition and susceptibility to mechanical stresses during cell division render them susceptible to breakage events. In this review, we delve into the present understanding of the underlying causes of centromere fragility, from the mechanisms governing its DNA replication and repair, to the pathways acting to counteract potential challenges. We propose that the centromere represents a "Trojan horse" exerting vital functions that, at the same time, potentially threatens whole genome stability.

Predicting the likelihood of a BRCA1/2 pathogenic variant being somatic by testing only tumour DNA in non-mucinous high-grade epithelial ovarian cancer

AIMS

Clinical guidelines recommend testing both germline and tumour DNA for BRCA1/2 pathogenic variants (PVs) in non-mucinous high-grade epithelial ovarian cancer (NMEOC). In this study, we show that some tumour BRCA1/2 PVs are highly likely to be somatic based on certain clinical and variant characteristics, meaning it may not be necessary to test all NMEOC cases for germline BRCA1/2 PVs.

METHODS

An observational study that included all tumour BRCA1/2 PVs detected in cases of NMEOC in the Northwest of England between July 2017 and February 2022. All tumour BRCA1/2 PVs were compared with PVs recorded in a prospectively gathered pan-cancer germline BRCA1/2 (gBRCA) testing database for the same geographical region (gBRCA1 PVs=910 and gBRCA2 PVs=922). Tumour BRCA1/2 PVs were categorised as common (≥1%), uncommon (<1%) or absent from the germline database.

RESULTS

One hundred and thirteen tumour BRCA1/2 PVs were detected in 111 NMEOC cases. There were 69 germline and 44 somatic variants. The mean age at diagnosis for gBRCA and somatic BRCA1/2 (sBRCA) PVs was 56.9 and 68.5 years, respectively (Student's t-test p<0.0001). All sBRCA PVs were detected in non-familial cases. All tumour BRCA1/2 PVs with a variant allele frequency (VAF) <35% in non-familial cases were somatic variants. Eighty-one per cent of germline-tumour BRCA1/2 PVs were present (common=31, uncommon=25) in the gBRCA testing database, while 89% of somatic-tumour BRCA1/2 PVs were absent (n=39).

CONCLUSIONS

We predict the likelihood of a tumour BRCA1/2 PV being somatic is 99.8% in non-familial cases of NMEOC diagnosed aged ≥75, where the VAF is ≤30% and there is no regional germline commonality.

Rare Epithelial Ovarian Cancers: Low Grade Serous and Mucinous Carcinomas

The ovarian epithelial cancer histotypes can be divided into common and rare types. Common types include high-grade serous ovarian carcinomas and the endometriosis-associated cancers, endometrioid and clear-cell carcinomas. The less common histotypes are mucinous and low-grade serous, each comprising less than 10% of all epithelial carcinomas. Although histologically and epidemiologically distinct from each other, these histotypes share some genetic and natural history features that distinguish them from the more common types. In this review, we will consider the similarities and differences of these rare histological types, and the clinical challenges they pose.

Exploiting a living biobank to delineate mechanisms underlying disease-specific chromosome instability

Chromosome instability (CIN) is a cancer hallmark that drives tumour heterogeneity, phenotypic adaptation, drug resistance and poor prognosis. High-grade serous ovarian cancer (HGSOC), one of the most chromosomally unstable tumour types, has a 5-year survival rate of only ~30% - largely due to late diagnosis and rapid development of drug resistance, e.g., via CIN-driven ABCB1 translocations. However, CIN is also a cell cycle vulnerability that can be exploited to specifically target tumour cells, illustrated by the success of PARP inhibitors to target homologous recombination deficiency (HRD). However, a lack of appropriate models with ongoing CIN has been a barrier to fully exploiting disease-specific CIN mechanisms. This barrier is now being overcome with the development of patient-derived cell cultures and organoids. In this review, we describe our progress building a Living Biobank of over 120 patient-derived ovarian cancer models (OCMs), predominantly from HGSOC. OCMs are highly purified tumour fractions with extensive proliferative potential that can be analysed at early passage. OCMs have diverse karyotypes, display intra- and inter-patient heterogeneity and mitotic abnormality rates far higher than established cell lines. OCMs encompass a broad-spectrum of HGSOC hallmarks, including a range of p53 alterations and BRCA1/2 mutations, and display drug resistance mechanisms seen in the clinic, e.g., ABCB1 translocations and BRCA2 reversion. OCMs are amenable to functional analysis, drug-sensitivity profiling, and multi-omics, including single-cell next-generation sequencing, and thus represent a platform for delineating HGSOC-specific CIN mechanisms. In turn, our vision is that this understanding will inform the design of new therapeutic strategies.

High-grade serous ovarian carcinoma organoids as models of chromosomal instability

High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterized by ubiquitous TP53 mutation, profound chromosomal instability, and heterogeneity. The mutational processes driving chromosomal instability in HGSOC can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and characterized them using bulk transcriptomic, bulk genomic, single-cell genomic, and drug sensitivity assays. We show that HGSOC PDOs comprise communities of different clonal populations and represent models of different causes of chromosomal instability including homologous recombination deficiency, chromothripsis, tandem-duplicator phenotype, and whole genome duplication. We also show that these PDOs can be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide validated genomic models for studies of specific mutational processes and precision therapeutics.

Insights into high-grade serous carcinoma pathobiology using three-dimensional culture model systems

Epithelial ovarian cancer (EOC) research has become more complex as researchers try to fully understand the metastatic process. Especially as we delve into the concept of tumour dormancy, where cells transition between proliferative and dormant states to survive during disease progression. Thus, the in vitro models used to conduct this research need to reflect this vast biological complexity. The innovation behind the many three-dimensional (3D) spheroid models has been refined to easily generate reproducible spheroids so that we may understand the various molecular signaling changes of cells during metastasis and determine therapeutic efficacy of treatments. This ingenuity was then used to develop the 3D ex vivo patient-derived organoid model, as well as multiple co-culture model systems for EOC research. Although, researchers need to continue to push the boundaries of these current models for in vitro and even in vivo work in the future. In this review, we describe the 3D models already in use, where these models can be developed further and how we can use these models to gain the most knowledge on EOC pathogenesis and discover new targeted therapies.

Patient Derived Organoids (PDOs), Extracellular Matrix (ECM), Tumor Microenvironment (TME) and Drug Screening: State of the Art and Clinical Implications of Ovarian Cancer Organoids in the Era of Precision Medicine

Ovarian cancer (OC) has the highest mortality rate of all gynecological malignancies due to the high prevalence of advanced stages of diagnosis and the high rate of recurrence. Furthermore, the heterogeneity of OC tumors contributes to the rapid development of resistance to conventional chemotherapy. In recent years, in order to overcome these problems, targeted therapies have been introduced in various types of tumors, including gynecological cancer. However, the lack of predictive biomarkers showing different clinical benefits limits the effectiveness of these therapies. This requires the development of preclinical models that can replicate the histological and molecular characteristics of OC subtypes. In this scenario, organoids become an important preclinical model for personalized medicine. In fact, patient-derived organoids (PDO) recapture tumor heterogeneity with the possibility of performing drug screening. However, to best reproduce the patient’s characteristics, it is necessary to develop a specific extracellular matrix (ECM) and introduce a tumor microenvironment (TME), which both represent an actual object of study to improve drug screening, particularly when used in targeted therapy and immunotherapy to guide therapeutic decisions. In this review, we summarize the current state of the art for the screening of PDOs, ECM, TME, and drugs in the setting of OC, as well as discussing the clinical implications and future perspectives for the research of OC organoids.

Tumor organoid biobank-new platform for medical research

Organoids are a new type of 3D model for tumor research, which makes up for the shortcomings of cell lines and xenograft models, and promotes the development of personalized precision medicine. Long-term culture, expansion and storage of organoids provide the necessary conditions for the establishment of biobanks. Biobanks standardize the collection and preservation of normal or pathological specimens, as well as related clinical information. The tumor organoid biobank has a good quality control system, which is conducive to the clinical transformation and large-scale application of tumor organoids, such as disease modeling, new drug development and high-throughput drug screening. This article summarized the common tumor types of patient-derived organoid (PDO) biobanks and the necessary information for biobank construction, such as the number of organoids, morphology, success rate of culture and resuscitation, pathological types. In our results, we found that patient-derived tumor organoid (PDTO) biobanks were being established more and more, with the Netherlands, the United States, and China establishing the most. Biobanks of colorectal, pancreas, breast, glioma, and bladder cancers were established more, which reflected the relative maturity of culture techniques for these tumors. In addition, we provided insights on the precautions and future development direction of PDTO biobank building.

A targetable MYBL2-ATAD2 axis governs cell proliferation in ovarian cancer

The chromatin-modifying enzyme ATAD2 confers oncogenic competence and proliferative advantage in malignances. We previously identified ATAD2 as a marker and driver of cell proliferation in ovarian cancer (OC); however, the mechanisms whereby ATAD2 is regulated and involved in cell proliferation are still unclear. Here, we disclose that ATAD2 displays a classical G2/M gene signature, functioning to facilitate mitotic progression. ATAD2 ablation caused mitotic arrest and decreased the ability of OC cells to pass through nocodazole-arrested mitosis. ChIP-seq data analyses demonstrated that DREAM and MYBL2-MuvB (MMB), two switchable MuvB-based complexes, bind the CHR elements in the ATAD2 promoter, representing a typical feature and principle mechanism of the periodic regulation of G2/M genes. As a downstream target of MYBL2, ATAD2 deletion significantly impaired MYBL2-driven cell proliferation. Intriguingly, ATAD2 silencing also fed back to destabilize the MYBL2 protein. The significant coexpression of MYBL2 and ATAD2 at both the bulk tissue and single-cell levels highlights the existence of the MYBL2-ATAD2 signaling in OC patients. This signaling is activated during tumorigenesis and correlated with TP53 mutation, and its hyperactivation was found especially in high-grade serous and drug-resistant OCs. Disrupting this signaling by CRISPR/Cas9-mediated ATAD2 ablation inhibited the in vivo growth of OC in a subcutaneous tumor xenograft mouse model, while pharmacologically targeting this signaling with an ATAD2 inhibitor demonstrated high therapeutic efficacy in both drug-sensitive and drug-resistant OC cells. Collectively, we identified a novel MYBL2-ATAD2 proliferative signaling axis and highlighted its potential application in developing new therapeutic strategies, especially for high-grade serous and drug-resistant OCs.

Misaligned Chromosomes are a Major Source of Chromosomal Instability in Breast Cancer

Chromosomal instability (CIN), the persistent reshuffling of chromosomes during mitosis, is a hallmark of human cancers that contributes to tumor heterogeneity and has been implicated in driving metastasis and altering responses to therapy. Though multiple mechanisms can produce CIN, lagging chromosomes generated from abnormal merotelic attachments are the major cause of CIN in a variety of cell lines, and are expected to predominate in cancer. Here, we quantify CIN in breast cancer using a tumor microarray, matched primary and metastatic samples, and patient-derived organoids from primary breast cancer. Surprisingly, misaligned chromosomes are more common than lagging chromosomes and represent a major source of CIN in primary and metastatic tumors. This feature of breast cancers is conserved in a majority of breast cancer cell lines. Importantly, though a portion of misaligned chromosomes align before anaphase onset, the fraction that remain represents the largest source of CIN in these cells. Metastatic breast cancers exhibit higher rates of CIN than matched primary cancers, primarily due to increases in misaligned chromosomes. Whether CIN causes immune activation or evasion is controversial. We find that misaligned chromosomes result in immune-activating micronuclei substantially less frequently than lagging and bridge chromosomes and that breast cancers with greater frequencies of lagging chromosomes and chromosome bridges recruit more stromal tumor-infiltrating lymphocytes. These data indicate misaligned chromosomes represent a major mechanism of CIN in breast cancer and provide support for differential immunostimulatory effects of specific types of CIN.

Significance

We surveyed the single-cell landscape of mitotic defects that generate CIN in primary and metastatic breast cancer and relevant models. Misaligned chromosomes predominate, and are less immunostimulatory than other chromosome segregation errors.

The Development of a Three-Dimensional Platform for Patient-Derived Ovarian Cancer Tissue Models: A Systematic Literature Review

There is an unmet biomedical need for ex vivo tumour models that would predict drug responses and in turn help determine treatment regimens and potentially predict resistance before clinical studies. Research has shown that three dimensional models of ovarian cancer (OvCa) are more realistic than two dimensional in vitro systems as they are able to capture patient in vivo conditions in more accurate manner. The vast majority of studies aiming to recapitulate the ovarian tumour morphology, behaviors, and study chemotherapy responses have been using ovarian cancer cell lines. However, despite the advantages of utilising cancer cell lines to set up a platform, they are not as informative as systems applying patient derived cells, as cell lines are not able to recapitulate differences between each individual patient characteristics. In this review we discussed the most recent advances in the creation of 3D ovarian cancer models that have used patient derived material, the challenges to overcome and future applications.

Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer

Chromosomal instability is a major challenge to patient stratification and targeted drug development for high-grade serous ovarian carcinoma (HGSOC). Here we show that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes significantly correlate with gene expression and methylation status. We identify five prevalent clonal driver SCNAs (chromosomal amplifications encompassing MYC, PIK3CA, CCNE1, KRAS and TERT) from multi-regional HGSOC data and reason that their strong selection should prioritise them as key biomarkers for targeted therapies. We use primary HGSOC spheroid models to test interactions between in vitro targeted therapy and SCNAs. MYC chromosomal copy number is associated with in-vitro and clinical response to paclitaxel and in-vitro response to mTORC1/2 inhibition. Activation of the mTOR survival pathway in the context of MYC-amplified HGSOC is statistically associated with increased prevalence of SCNAs in genes from the PI3K pathway. Co-occurrence of amplifications in MYC and genes from the PI3K pathway is independently observed in squamous lung cancer and triple negative breast cancer. In this work, we show that identifying co-occurrence of clonal driver SCNA genes could be used to tailor therapeutics for precision medicine.

Elucidating tumor heterogeneity from spatially resolved transcriptomics data by multi-view graph collaborative learning

Spatially resolved transcriptomics (SRT) technology enables us to gain novel insights into tissue architecture and cell development, especially in tumors. However, lacking computational exploitation of biological contexts and multi-view features severely hinders the elucidation of tissue heterogeneity. Here, we propose stMVC, a multi-view graph collaborative-learning model that integrates histology, gene expression, spatial location, and biological contexts in analyzing SRT data by attention. Specifically, stMVC adopting semi-supervised graph attention autoencoder separately learns view-specific representations of histological-similarity-graph or spatial-location-graph, and then simultaneously integrates two-view graphs for robust representations through attention under semi-supervision of biological contexts. stMVC outperforms other tools in detecting tissue structure, inferring trajectory relationships, and denoising on benchmark slices of human cortex. Particularly, stMVC identifies disease-related cell-states and their transition cell-states in breast cancer study, which are further validated by the functional and survival analysis of independent clinical data. Those results demonstrate clinical and prognostic applications from SRT data.

A novel cell line panel reveals non-genetic mediators of platinum resistance and phenotypic diversity in high grade serous ovarian cancer

OBJECTIVES

Resistance to cancer therapy is an enduring challenge and accurate and reliable preclinical models are lacking. We interrogated this unmet need using high grade serous ovarian cancer (HGSC) as a disease model.

METHODS

We created five in vitro and two in vivo platinum-resistant HGSC models and characterised the entire cell panel via whole genome sequencing, RNASeq and creation of intraperitoneal models.

RESULTS

Mutational signature analysis indicated that platinum-resistant cell lines evolved from a pre-existing ancestral clone but a unifying mutational cause for drug resistance was not identified. However, cisplatin-resistant and carboplatin-resistant cells evolved recurrent changes in gene expression that significantly overlapped with independent samples obtained from multiple patients with relapsed HGSC. Gene Ontology Biological Pathways (GOBP) related to the tumour microenvironment, particularly the extracellular matrix, were repeatedly enriched in cisplatin-resistant cells, carboplatin-resistant cells and also in human resistant/refractory samples. The majority of significantly over-represented GOBP however, evolved uniquely in either cisplatin- or carboplatin-resistant cell lines resulting in diverse intraperitoneal behaviours that reflect different clinical manifestations of relapsed human HGSC.

CONCLUSIONS

Our clinically relevant and usable models reveal a key role for non-genetic factors in the evolution of chemotherapy resistance. Biological pathways relevant to the extracellular matrix were repeatedly expressed by resistant cancer cells in multiple settings. This suggests that recurrent gene expression changes provide a fitness advantage during platinum therapy and also that cancer cell-intrinsic mechanisms influence the tumour microenvironment during the evolution of drug resistance. Candidate genes and pathways identified here could reveal therapeutic opportunities in platinum-resistant HGSC.

Multiple-low-dose therapy: effective killing of high-grade serous ovarian cancer cells with ATR and CHK1 inhibitors

High-grade serous ovarian cancer (HGSOC) is an aggressive disease that typically develops drug resistance, thus novel biomarker-driven strategies are required. Targeted therapy focuses on synthetic lethality—pioneered by PARP inhibition of BRCA1/2-mutant disease. Subsequently, targeting the DNA replication stress response (RSR) is of clinical interest. However, further mechanistic insight is required for biomarker discovery, requiring sensitive models that closely recapitulate HGSOC. We describe an optimized proliferation assay that we use to screen 16 patient-derived ovarian cancer models (OCMs) for response to RSR inhibitors (CHK1i, WEE1i, ATRi, PARGi). Despite genomic heterogeneity characteristic of HGSOC, measurement of OCM proliferation was reproducible and reflected intrinsic tumour-cell properties. Surprisingly, RSR targeting drugs were not interchangeable, as sensitivity to the four inhibitors was not correlated. Therefore, to overcome RSR redundancy, we screened the OCMs with all two-, three- and four-drug combinations in a multiple-low-dose strategy. We found that low-dose CHK1i-ATRi had a potent anti-proliferative effect on 15 of the 16 OCMs, and was synergistic with potential to minimise treatment resistance and toxicity. Low-dose ATRi-CHK1i induced replication catastrophe followed by mitotic exit and post-mitotic arrest or death. Therefore, this study demonstrates the potential of the living biobank of OCMs as a drug discovery platform for HGSOC.

The Genomic Landscape of Early-Stage Ovarian High-Grade Serous Carcinoma

PURPOSE

Ovarian high-grade serous carcinoma (HGSC) is usually diagnosed at late stage. We investigated whether late-stage HGSC has unique genomic characteristics consistent with acquisition of evolutionary advantage compared with early-stage tumors.

EXPERIMENTAL DESIGN

We performed targeted next-generation sequencing and shallow whole-genome sequencing (sWGS) on pretreatment samples from 43 patients with FIGO stage I-IIA HGSC to investigate somatic mutations and copy-number (CN) alterations (SCNA). We compared results to pretreatment samples from 52 patients with stage IIIC/IV HGSC from the BriTROC-1 study.

RESULTS

Age of diagnosis did not differ between early-stage and late-stage patients (median 61.3 years vs. 62.3 years, respectively). TP53 mutations were near-universal in both cohorts (89% early-stage, 100% late-stage), and there were no significant differences in the rates of other somatic mutations, including BRCA1 and BRCA2. We also did not observe cohort-specific focal SCNA that could explain biological behavior. However, ploidy was higher in late-stage (median, 3.0) than early-stage (median, 1.9) samples. CN signature exposures were significantly different between cohorts, with greater relative signature 3 exposure in early-stage and greater signature 4 in late-stage. Unsupervised clustering based on CN signatures identified three clusters that were prognostic.

CONCLUSIONS

Early-stage and late-stage HGSCs have highly similar patterns of mutation and focal SCNA. However, CN signature analysis showed that late-stage disease has distinct signature exposures consistent with whole-genome duplication. Further analyses will be required to ascertain whether these differences reflect genuine biological differences between early-stage and late-stage or simply time-related markers of evolutionary fitness. See related commentary by Yang et al., p. 2730.

Prospective Real-World Gynaecological Cancer Clinical Registry with Associated Biospecimens: A Collaborative Model to Promote Translational Research between GEICO and the Spanish Biobank Network

Patient registries linked to biorepositories constitute a valuable asset for clinical and translational research in oncology. The Spanish Group of Ovarian Cancer Research (GEICO), in collaboration with the Spanish Biobank Network (RNBB), has developed a multicentre, multistakeholder, prospective virtual clinical registry (VCR) associated with biobanks for the collection of real-world data and biological samples of gynaecological cancer patients. This collaborative project aims to promote research by providing broad access to high-quality clinical data and biospecimens for future research according to the needs of investigators and to increase diagnostic and therapeutic opportunities for gynaecological cancer patients in Spain. The VCR will include the participation of more than 60 Spanish hospitals entering relevant clinical information in harmonised electronic case report forms (eCRFs) in four different cohorts: ovarian, endometrial, cervical, and rare gynaecological cancers (gestational trophoblastic disease). Initial data for the cases included till December 2021 are presented. The model described herein establishes a real-world win-win collaboration between multicentre structures, promoted and supported by GEICO, that will contribute to the success of translational research in gynaecological cancer.

Quantifying chromosomal instability from intratumoral karyotype diversity using agent-based modeling and Bayesian inference

Chromosomal instability (CIN)-persistent chromosome gain or loss through abnormal mitotic segregation-is a hallmark of cancer that drives aneuploidy. Intrinsic chromosome mis-segregation rate, a measure of CIN, can inform prognosis and is a promising biomarker for response to anti-microtubule agents. However, existing methodologies to measure this rate are labor intensive, indirect, and confounded by selection against aneuploid cells, which reduces observable diversity. We developed a framework to measure CIN, accounting for karyotype selection, using simulations with various levels of CIN and models of selection. To identify the model parameters that best fit karyotype data from single-cell sequencing, we used approximate Bayesian computation to infer mis-segregation rates and karyotype selection. Experimental validation confirmed the extensive chromosome mis-segregation rates caused by the chemotherapy paclitaxel (18.5 ± 0.5/division). Extending this approach to clinical samples revealed that inferred rates fell within direct observations of cancer cell lines. This work provides the necessary framework to quantify CIN in human tumors and develop it as a predictive biomarker.

Single-Cell RNA Sequencing Reveals the Role of Phosphorylation-Related Genes in Hepatocellular Carcinoma Stem Cells

Abnormal activation of protein kinases and phosphatases is implicated in various tumorigenesis, including hepatocellular carcinoma (HCC). Advanced HCC patients are treated with systemic therapy, including tyrosine kinase inhibitors, which extend overall survival. Investigation of the underlying mechanism of protein kinase signaling will help to improve the efficacy of HCC therapy. Combining single-cell RNA sequencing data and TCGA RNA-seq data, we profiled the protein kinases, phosphatases, and other phosphorylation-related genes (PRGs) of HCC patients in this study. We found nine protein kinases and PRGs with high expression levels that were mainly detected in HCC cancer stem cells, including POLR2G, PPP2R1A, POLR2L, PRC1, ITBG1BP1, MARCKSL1, EZH2, DTYMK, and AURKA. Survival analysis with the TCGA dataset showed that these genes were associated with poor prognosis of HCC patients. Further correlation analysis showed that these genes were involved in cell cycle-related pathways that may contribute to the development of HCC. Among them, AURKA and EZH2 were identified as two hub genes by Ingenuity Pathway Analysis. Treatment with an AURKA inhibitor (alisertib) and an EZH2 inhibitor (gambogenic) inhibited HCC cell proliferation, migration, and invasion. We also found that both AURKA and EZH2 were highly expressed in TP53-mutant HCC samples. Our comprehensive analysis of PRGs contributes to illustrating the mechanisms underlying HCC progression and identifying potential therapeutic targets for future clinical trials.

Chromosome Missegregation as a Modulator of Radiation Sensitivity

Chromosome missegregation over the course of multiple cell divisions, termed chromosomal instability (CIN), is a hallmark of cancer. Multiple causes of CIN have been identified, including defects in the mitotic checkpoint, altered kinetochore-microtubule dynamics, centrosome amplification, and ionizing radiation. Here we review the types, mechanisms, and cellular implications of CIN. We discuss the evidence that CIN can promote tumors, suppress them, or do neither, depending on the rates of chromosome missegregration and the cellular context. Very high rates of chromosome missegregation lead to cell death due to loss of essential chromosomes; thus elevating CIN above a tolerable threshold provides a mechanistic opportunity to promote cancer cell death. Lethal rates of CIN can be achieved by a single insult or through a combination of insults. Because ionizing radiation induces CIN, additional therapies that increase CIN may serve as useful modulators of radiation sensitivity. Ultimately, quantifying the intrinsic CIN in a tumor and modulating this level pharmacologically as well as with radiation may allow for a more rational, personalized radiation therapy prescription, thereby decreasing side effects and increasing local control.

Chromatin bridges, not micronuclei, activate cGAS after drug-induced mitotic errors in human cells

Mitotic errors can activate cyclic GMP-AMP synthase (cGAS) and induce type I interferon (IFN) signaling. Current models propose that chromosome segregation errors generate micronuclei whose rupture activates cGAS. We used a panel of antimitotic drugs to perturb mitosis in human fibroblasts and measured abnormal nuclear morphologies, cGAS localization, and IFN signaling in the subsequent interphase. Micronuclei consistently recruited cGAS without activating it. Instead, IFN signaling correlated with formation of cGAS-coated chromatin bridges that were selectively generated by microtubule stabilizers and MPS1 inhibitors. cGAS activation by chromatin bridges was suppressed by drugs that prevented cytokinesis. We confirmed cGAS activation by chromatin bridges in cancer lines that are unable to secrete IFN by measuring paracrine transfer of 2'3'-cGAMP to fibroblasts, and in mouse cells. We propose that cGAS is selectively activated by self-chromatin when it is stretched in chromatin bridges. Immunosurveillance of cells that fail mitosis, and antitumor actions of taxanes and MPS1 inhibitors, may depend on this effect.

TP53 loss initiates chromosomal instability in fallopian tube epithelial cells

High-grade serous ovarian cancer (HGSOC) originates in the fallopian tube epithelium and is characterized by ubiquitous TP53 mutation and extensive chromosomal instability (CIN). However, direct causes of CIN, such as mutations in DNA replication and mitosis genes, are rare in HGSOC. We therefore asked whether oncogenic mutations that are common in HGSOC can indirectly drive CIN in non-transformed human fallopian tube epithelial cells. To model homologous recombination deficient HGSOC, we sequentially mutated TP53 and BRCA1 then overexpressed MYC. Loss of p53 function alone was sufficient to drive the emergence of subclonal karyotype alterations. TP53 mutation also led to global gene expression changes, influencing modules involved in cell cycle commitment, DNA replication, G2/M checkpoint control and mitotic spindle function. Both transcriptional deregulation and karyotype diversity were exacerbated by loss of BRCA1 function, with whole-genome doubling events observed in independent p53/BRCA1-deficient lineages. Thus, our observations indicate that loss of the key tumour suppressor TP53 is sufficient to deregulate multiple cell cycle control networks and thereby initiate CIN in pre-malignant fallopian tube epithelial cells. This article has an associated First Person interview with the first author of the paper.

Antimicrobial, antioxidant and cytotoxic properties of Chenopodium glaucum L

We evaluated phytochemical composition, antibacterial, antifungal, anti-oxidant and cytotoxic properties of aqueous (water) and organic extracts (methanol, ethyl acetate and n-hexane) of Chenopodium glaucum. Highest phenolic content 45 mg gallic acid equivalents (GAE)/g d.w was found in aqueous extract followed by ethyl acetate (41mg GAE/g d.w) and methanol extract (34.46 mg GAE/g d.w). Antibacterial potential of aqueous and organic extracts of C. glaucum was examined against Acinetobacter baumannii, Klebsiella pneumoniae, Escherichia coli and Staphylococcus epidermidis. The aqueous, methanolic, ethyl acetate, and n-hexane extract showed antibacterial activity against A. baumannii, K. pneumoniae, E. coli and S. epidermidis. However, against A. baumannii significantly higher inhibition zone (19 mm and 18.96 mm respectively) was shown by ethyl acetate and methanol extracts. Aqueous extract possessed highest growth inhibition (11 mm) against E. coli. Aqueous, ethyl acetate and methanol extracts showed 9 mm, 10 mm, and 10.33 mm zone of inhibition against the K. pneumoniae. For antifungal activity, the extracts were less effective against Aspergillus niger but showed strong antifungal activity against Aspergillus flavus (A. flavus). The antioxidant activity was measured as DPPH (2, 2-diphenyl-1-picrylhydrazyl), H2O2 and ABTS (2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) scavenging activity of free radicals. All the organic extracts of C. glaucum possessed ABTS, DPPH and H2O2 scavenging properties. The highest cytotoxic activity measured as half maximal inhibitory concentration (IC50) against human lungs carcinoma cells was recorded for methanolic (IC50 = 16 μg/mL) and n-hexane (IC50 = 25 μg/mL) extracts, respectively. The Gas chromatography-mass spectrometry (GC-MS) analysis showed 4 major and 26 minor compounds in n-hexane extract and 4 major and 7 minor compounds in methanol extract of the C. glaucum. It is concluded that aqueous and organic extracts of C. glaucum would be potential therapeutic agents and could be exploited on a pilot scale to treat human pathogenic diseases.

Replication catastrophe is responsible for intrinsic PAR glycohydrolase inhibitor-sensitivity in patient-derived ovarian cancer models

BACKGROUND

Patients with ovarian cancer often present at advanced stage and, following initial treatment success, develop recurrent drug-resistant disease. PARP inhibitors (PARPi) are yielding unprecedented survival benefits for women with BRCA-deficient disease. However, options remain limited for disease that is platinum-resistant and/or has inherent or acquired PARPi-resistance. PARG, the PAR glycohydrolase that counterbalances PARP activity, is an emerging target with potential to selectively kill tumour cells harbouring oncogene-induced DNA replication and metabolic vulnerabilities. Clinical development of PARG inhibitors (PARGi) will however require predictive biomarkers, in turn requiring an understanding of their mode of action. Furthermore, differential sensitivity to PARPi is key for expanding treatment options available for patients.

METHODS

A panel of 10 ovarian cancer cell lines and a living biobank of patient-derived ovarian cancer models (OCMs) were screened for PARGi-sensitivity using short- and long-term growth assays. PARGi-sensitivity was characterized using established markers for DNA replication stress, namely replication fibre asymmetry, RPA foci, KAP1 and Chk1 phosphorylation, and pan-nuclear γH2AX, indicating DNA replication catastrophe. Finally, gene expression in sensitive and resistant cells was also examined using NanoString or RNAseq.

RESULTS

PARGi sensitivity was identified in both ovarian cancer cell lines and patient-derived OCMs, with sensitivity accompanied by markers of persistent replication stress, and a pre-mitotic cell cycle block. Moreover, DNA replication genes are down-regulated in PARGi-sensitive cell lines consistent with an inherent DNA replication vulnerability. However, DNA replication gene expression did not predict PARGi-sensitivity in OCMs. The subset of patient-derived OCMs that are sensitive to single-agent PARG inhibition, includes models that are PARPi- and/or platinum-resistant, indicating that PARG inhibitors may represent an alternative treatment strategy for women with otherwise limited therapeutic options.

CONCLUSIONS

We discover that a subset of ovarian cancers are intrinsically sensitive to pharmacological PARG blockade, including drug-resistant disease, underpinned by a common mechanism of replication catastrophe. We explore the use of a transcript-based biomarker, and provide insight into the design of future clinical trials of PARGi in patients with ovarian cancer. However, our results highlight the complexity of developing a predictive biomarker for PARGi sensitivity.

Loss of haspin suppresses cancer cell proliferation by interfering with cell cycle progression at multiple stages

Our recent studies have shown that haspin, a protein kinase imperative for mitosis, is engaged in the interphase progression of HeLa and U2OS cancer cells. In this investigation, we employed the Fucci reporter system and time-lapse imaging to examine the impact of haspin gene silencing on cell cycle progressions at a single-cell level. We found that the loss of haspin induced multiple cell cycle defects. Specifically, the S/G2 duration was greatly prolonged by haspin gene depletion or inhibition in synchronous HeLa cells. Haspin gene depletion in asynchronous HeLa and U2OS cells led to a similarly protracted S/G2 phase, followed by mitotic cell death or postmitotic G1 arrest. In addition, haspin deficiency resulted in robust induction of the p21^CIP1/WAF1 checkpoint protein, a target of the p53 activation. Also, co-depleting haspin with either p21 or p53 could rescue U2OS cells from postmitotic G1 arrest and partially restore their proliferation. These results substantiate the haspin's capacity to regulate interphase and mitotic progression, offering a broader antiproliferative potential of haspin loss in cancer cells.

Attenuated Chromosome Oscillation as a Cause of Chromosomal Instability in Cancer Cells

Simple Summary

Chromosomal instability (CIN), a condition in which chromosome missegregation occurs at high rates, is widely seen in cancer cells. Causes of CIN in cancer cells are not fully understood. A recent report suggests that chromosome oscillation, an iterative chromosome motion typically seen in metaphase around the spindle equator, is attenuated in cancer cells, and is associated with CIN. Chromosome oscillation promotes the correction of erroneous kinetochore-microtubule attachments through phosphorylation of Hec1, a kinetochore protein that binds to microtubules, by Aurora A kinase residing on the spindle. In this review, we focused on this unappreciated link between chromosome oscillation and CIN.

Abstract

Chromosomal instability (CIN) is commonly seen in cancer cells, and related to tumor progression and poor prognosis. Among the causes of CIN, insufficient correction of erroneous kinetochore (KT)-microtubule (MT) attachments plays pivotal roles in various situations. In this review, we focused on the previously unappreciated role of chromosome oscillation in the correction of erroneous KT-MT attachments, and its relevance to the etiology of CIN. First, we provided an overview of the error correction mechanisms for KT-MT attachments, especially the role of Aurora kinases in error correction by phosphorylating Hec1, which connects MT to KT. Next, we explained chromosome oscillation and its underlying mechanisms. Then we introduced how chromosome oscillation is involved in the error correction of KT-MT attachments, based on recent findings. Chromosome oscillation has been shown to promote Hec1 phosphorylation by Aurora A which localizes to the spindle. Finally, we discussed the link between attenuated chromosome oscillation and CIN in cancer cells. This link underscores the role of chromosome dynamics in mitotic fidelity, and the mutual relationship between defective chromosome dynamics and CIN in cancer cells that can be a target for cancer therapy.

Distinct transcriptional programs stratify ovarian cancer cell lines into the five major histological subtypes

BACKGROUND

Epithelial ovarian cancer (OC) is a heterogenous disease consisting of five major histologically distinct subtypes: high-grade serous (HGSOC), low-grade serous (LGSOC), endometrioid (ENOC), clear cell (CCOC) and mucinous (MOC). Although HGSOC is the most prevalent subtype, representing 70-80% of cases, a 2013 landmark study by Domcke et al. found that the most frequently used OC cell lines are not molecularly representative of this subtype. This raises the question, if not HGSOC, from which subtype do these cell lines derive? Indeed, non-HGSOC subtypes often respond poorly to chemotherapy; therefore, representative models are imperative for developing new targeted therapeutics.

METHODS

Non-negative matrix factorisation (NMF) was applied to transcriptomic data from 44 OC cell lines in the Cancer Cell Line Encyclopedia, assessing the quality of clustering into 2-10 groups. Epithelial OC subtypes were assigned to cell lines optimally clustered into five transcriptionally distinct classes, confirmed by integration with subtype-specific mutations. A transcriptional subtype classifier was then developed by trialling three machine learning algorithms using subtype-specific metagenes defined by NMF. The ability of classifiers to predict subtype was tested using RNA sequencing of a living biobank of patient-derived OC models.

RESULTS

Application of NMF optimally clustered the 44 cell lines into five transcriptionally distinct groups. Close inspection of orthogonal datasets revealed this five-cluster delineation corresponds to the five major OC subtypes. This NMF-based classification validates the Domcke et al. analysis, in identifying lines most representative of HGSOC, and additionally identifies models representing the four other subtypes. However, NMF of the cell lines into two clusters did not align with the dualistic model of OC and suggests this classification is an oversimplification. Subtype designation of patient-derived models by a random forest transcriptional classifier aligned with prior diagnosis in 76% of unambiguous cases. In cases where there was disagreement, this often indicated potential alternative diagnosis, supported by a review of histological, molecular and clinical features.

CONCLUSIONS

This robust classification informs the selection of the most appropriate models for all five histotypes. Following further refinement on larger training cohorts, the transcriptional classification may represent a useful tool to support the classification of new model systems of OC subtypes.

Cytotoxic capacity of a novel glycosylated antitumor ether lipid in chemotherapy-resistant high grade serous ovarian cancer in vitro and in vivo

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L-Rham induces apoptosis-independent cell death in high grade serous ovarian cancer (HGSOC) cells.

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L-Rham-induced cell death is dose and time dependent in HGSOC cells grown as 2D or 3D cultures.

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L-Rham is as effective as paclitaxel to reduce tumor burden and metastasis in a CAM model.

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L-Rham significantly reduces tumor formation in a low tumor burden model.

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L-Rham blocks ascites formation.

Chemotherapy resistant high grade serous ovarian cancer remains a clinically intractable disease with a high rate of mortality. We tested a novel glycosylated antitumor ether lipid called l-Rham to assess the in vitro and in vivo efficacy on high grade serous ovarian cancer cell lines and patient samples. l-Rham effectively kills high grade serous ovarian cancer cells grown as 2D or 3D cultures in a dose and time dependent manner. l-Rham efficacy was tested in vivo in a chicken allantoic membrane/COV362 xenograft model, where l-Rham activity was as effective as paclitaxel in reducing tumor weight and metastasis. The efficacy of l-Rham to reduce OVCAR3 tumor xenografts in NRG mice was assessed in low and high tumor burden models. l-Rham effectively reduced tumor formation in the low tumor burden group, and blocked ascites formation in low and high tumor burden animals. l-Rham demonstrates efficacy against OVCAR3 tumor and ascites formation in vivo in NRG mice, laying the foundation for further development of this drug class for the treatment of high grade serous ovarian cancer patients.

LiquidCNA: Tracking subclonal evolution from longitudinal liquid biopsies using somatic copy number alterations

Cell-free DNA (cfDNA) measured via liquid biopsies provides a way for minimally invasive monitoring of tumor evolutionary dynamics during therapy. Here we present liquidCNA, a method to track subclonal evolution from longitudinally collected cfDNA samples sequenced through cost-effective low-pass whole-genome sequencing. LiquidCNA utilizes somatic copy number alteration (SCNA) to simultaneously genotype and quantify the size of the dominant subclone without requiring B-allele frequency information, matched-normal samples, or prior knowledge on the genetic identity of the emerging clone. We demonstrate the accuracy of liquidCNA in synthetically generated sample sets and in vitro mixtures of cancer cell lines. In vivo application in patients with metastatic lung cancer reveals the progressive emergence of a novel tumor subpopulation. LiquidCNA is straightforward to use, is computationally inexpensive, and enables continuous monitoring of subclonal evolution to understand and control-therapy-induced resistance.

Cell cycle regulation by complex nanomachines

The cell cycle is the essential biological process where one cell replicates its genome and segregates the resulting two copies into the daughter cells during mitosis. Several aspects of this process have fascinated humans since the nineteenth century. Today, the cell cycle is exhaustively investigated because of its profound connections with human diseases and cancer. At the heart of the molecular network controlling the cell cycle, we find the cyclin-dependent kinases (CDKs) acting as an oscillator to impose an orderly and highly regulated progression through the different cell cycle phases. This oscillator integrates both internal and external signals via a multitude of signalling pathways involving posttranslational modifications including phosphorylation, protein ubiquitination and mechanisms of transcriptional regulation. These tasks are specifically performed by multi-subunit complexes, which are intensively studied both biochemically and structurally with the aim to unveil mechanistic insights into their molecular function. The scope of this review is to summarise the structural biology of the cell cycle machinery, with specific focus on the core cell cycle machinery involving the CDK-cyclin oscillator. We highlight the contribution of cryo-electron microscopy, which has started to revolutionise our understanding of the molecular function and dynamics of the key players of the cell cycle.

Single-Cell Transcriptome Analysis as a Promising Tool to Study Pluripotent Stem Cell Reprogramming

Cells are the basic units of all organisms and are involved in all vital activities, such as proliferation, differentiation, senescence, and apoptosis. A human body consists of more than 30 trillion cells generated through repeated division and differentiation from a single-cell fertilized egg in a highly organized programmatic fashion. Since the recent formation of the Human Cell Atlas consortium, establishing the Human Cell Atlas at the single-cell level has been an ongoing activity with the goal of understanding the mechanisms underlying diseases and vital cellular activities at the level of the single cell. In particular, transcriptome analysis of embryonic stem cells at the single-cell level is of great importance, as these cells are responsible for determining cell fate. Here, we review single-cell analysis techniques that have been actively used in recent years, introduce the single-cell analysis studies currently in progress in pluripotent stem cells and reprogramming, and forecast future studies.

Radiomics and radiogenomics in ovarian cancer: a literature review

Ovarian cancer remains one of the most lethal gynecological cancers in the world despite extensive progress in the areas of chemotherapy and surgery. Many studies have postulated that this is because of the profound heterogeneity that underpins response to therapy and prognosis. Standard imaging evaluation using CT or MRI does not take into account this tumoral heterogeneity especially in advanced stages with peritoneal carcinomatosis. As such, newly emergent fields in the assessment of tumor heterogeneity have been proposed using radiomics to evaluate the whole tumor burden heterogeneity as opposed to single biopsy sampling. This review provides an overview of radiomics, radiogenomics, and proteomics and examines the use of these newly emergent fields in assessing tumor heterogeneity and its implications in ovarian cancer.

Reduced SKP1 and CUL1 expression underlies increases in Cyclin E1 and chromosome instability in cellular precursors of high-grade serous ovarian cancer

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is the most common and lethal ovarian cancer histotype. Chromosome instability (CIN, an increased rate of chromosome gains and losses) is believed to play a fundamental role in the development and evolution of HGSOC. Importantly, overexpression of Cyclin E1 protein induces CIN, and genomic amplification of CCNE1 contributes to HGSOC pathogenesis in ~20% of patients. Cyclin E1 levels are normally regulated in a cell cycle-dependent manner by the SCF (SKP1-CUL1-FBOX) complex, an E3 ubiquitin ligase that includes the proteins SKP1 and CUL1. Conceptually, diminished SKP1 or CUL1 expression is predicted to underlie increases in Cyclin E1 levels and induce CIN.

METHODS

This study employs fallopian tube secretory epithelial cell models to evaluate the impact diminished SKP1 or CUL1 expression has on Cyclin E1 and CIN in both short-term (siRNA) and long-term (CRISPR/Cas9) studies.

RESULTS

Single-cell quantitative imaging microscopy approaches revealed changes in CIN-associated phenotypes and chromosome numbers and increased Cyclin E1 in response to diminished SKP1 or CUL1 expression.

CONCLUSIONS

These data identify SKP1 and CUL1 as novel CIN genes in HGSOC precursor cells that may drive early aetiological events contributing to HGSOC development.

Consequences of mitotic failure - The penalties and the rewards

Eukaryotic cells are usually diploid, meaning they contain two copies of each chromosome. However, aberrant chromosome numbers due to both, chromosome gains and losses, are often observed in nature. They can occur as a planned developmental step, but are more often an uninvited result of mitotic failure. Recent discoveries have improved our understanding of the cellular effects of aneuploidy - uneven chromosome numbers, and polyploidy - multiplication of entire sets of chromosomes - in eukaryotic cells. The results show that mitotic errors lead to rapid and extensive modifications of many cellular processes and affect proliferation, proteome balance, genome stability and more. The findings picture the cellular response to aneuploidy and polyploidy as a complex, tissue and context dependent network of events. Here I review the latest discoveries, with an emphasis on pathological aspects of aneuploidy and polyploidy in human cells.

Chromosome instability is prevalent and dynamic in high-grade serous ovarian cancer patient samples

OBJECTIVE

High-grade serous ovarian cancer (HGSOC) is the most lethal gynaecological malignancy in women with a high level of mortality, metastatic disease, disease recurrence and multi-drug resistance. Many previous studies have focused on characterising genome instability in recurrent resistant HGSOC and while this has advanced our understanding of HGSOC, our fundamental knowledge of the mechanisms driving genome instability remains limited. Chromosome instability (CIN; an increased rate of chromosome gains and losses) is a form of genome instability that is commonly associated with recurrence and multi-drug resistance in many cancer types but has just begun to be characterised in HGSOC.

METHOD

To examine the relationship between CIN and HGSOC, we employed single-cell quantitative imaging microscopy approaches capable of capturing the cell-to-cell heterogeneity associated with CIN, to assess the prevalence and dynamics of CIN within individual and patient-matched HGSOC ascites and solid tumour samples.

RESULTS

CIN occurs in 90.9% of ascites samples and 100% of solid tumours, while in-depth analyses identified statistically significant temporal dynamics within the serial ascites samples. In general, aneuploidy and CIN increase with disease progression and frequently decrease following chemotherapy treatments in responsive disease. Finally, our work identified higher levels of CIN in solid tumours relative to ascites samples isolated from the same individual, which identifies a novel difference existing between solid tumours and ascites samples.

CONCLUSIONS

Our findings provide novel insight into the relationship between CIN and HGSOC, and uncover a previously unknown relationship existing between CIN in solid tumours and metastatic disease (ascites).

Advances in Engineering Human Tissue Models

Research in cell biology greatly relies on cell-based in vitro assays and models that facilitate the investigation and understanding of specific biological events and processes under different conditions. The quality of such experimental models and particularly the level at which they represent cell behavior in the native tissue, is of critical importance for our understanding of cell interactions within tissues and organs. Conventionally, in vitro models are based on experimental manipulation of mammalian cells, grown as monolayers on flat, two-dimensional (2D) substrates. Despite the amazing progress and discoveries achieved with flat biology models, our ability to translate biological insights has been limited, since the 2D environment does not reflect the physiological behavior of cells in real tissues. Advances in 3D cell biology and engineering have led to the development of a new generation of cell culture formats that can better recapitulate the in vivo microenvironment, allowing us to examine cells and their interactions in a more biomimetic context. Modern biomedical research has at its disposal novel technological approaches that promote development of more sophisticated and robust tissue engineering in vitro models, including scaffold- or hydrogel-based formats, organotypic cultures, and organs-on-chips. Even though such systems are necessarily simplified to capture a particular range of physiology, their ability to model specific processes of human biology is greatly valued for their potential to close the gap between conventional animal studies and human (patho-) physiology. Here, we review recent advances in 3D biomimetic cultures, focusing on the technological bricks available to develop more physiologically relevant in vitro models of human tissues. By highlighting applications and examples of several physiological and disease models, we identify the limitations and challenges which the field needs to address in order to more effectively incorporate synthetic biomimetic culture platforms into biomedical research.

Specific Mechanisms of Chromosomal Instability Indicate Therapeutic Sensitivities in High-Grade Serous Ovarian Carcinoma

Chromosomal instability (CIN) comprises continual gain and loss of chromosomes or parts of chromosomes and occurs in the majority of cancers, often conferring poor prognosis. Because of a scarcity of functional studies and poor understanding of how genetic or gene expression landscapes connect to specific CIN mechanisms, causes of CIN in most cancer types remain unknown. High-grade serous ovarian carcinoma (HGSC), the most common subtype of ovarian cancer, is the major cause of death due to gynecologic malignancy in the Western world, with chemotherapy resistance developing in almost all patients. HGSC exhibits high rates of chromosomal aberrations and knowledge of causative mechanisms would represent an important step toward combating this disease. Here we perform the first in-depth functional characterization of mechanisms driving CIN in HGSC in seven cell lines that accurately recapitulate HGSC genetics. Multiple mechanisms coexisted to drive CIN in HGSC, including elevated microtubule dynamics and DNA replication stress that can be partially rescued to reduce CIN by low doses of paclitaxel and nucleoside supplementation, respectively. Distinct CIN mechanisms indicated relationships with HGSC-relevant therapy including PARP inhibition and microtubule-targeting agents. Comprehensive genomic and transcriptomic profiling revealed deregulation of various genes involved in genome stability but were not directly predictive of specific CIN mechanisms, underscoring the importance of functional characterization to identify causes of CIN. Overall, we show that HGSC CIN is complex and suggest that specific CIN mechanisms could be used as functional biomarkers to indicate appropriate therapy. SIGNIFICANCE: These findings characterize multiple deregulated mechanisms of genome stability that lead to CIN in ovarian cancer and demonstrate the benefit of integrating analysis of said mechanisms into predictions of therapy response.

Increased Expression of UBE2T Predicting Poor Survival of Epithelial Ovarian Cancer: Based on Comprehensive Analysis of UBE2s, Clinical Samples, and the GEO Database

Ubiquitin-conjugating enzymes E2 (UBE2) have been reported in the microenvironment of various malignant tumors, but their correlation with ovarian cancer (OC) remains elusive. This study aimed to systematically analyze the expression patterns, prognostic value, genetic variation, and biological functions of 12 members of the UBE2 gene family in OC through the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier plotter, cBioPortal, and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) databases, respectively. We found that the mRNA levels of UBE2C, UBE2N, UBE2S, and UBE2T were significantly upregulated in OC compared with those in normal ovarian tissue. In patients with serous ovarian cancer (SOC), UBE2A, UBE2B, UBE2C, UBE2G, UBE2R2, and UBE2T upregulation were associated with poor overall survival. Moreover, UBE2A, UBE2N, UBE2R2, and UBE2T upregulation and UBE2G downregulation were associated with poor progression-free survival. UBE2T exhibited a strong correlation with OC and was thus further examined. We found that UBE2T has a high diagnostic accuracy (area under the receiver operating characteristic curve = 0.969) in epithelial ovarian cancer (EOC). Immunohistochemical assays and the Gene Expression Omnibus (GEO) database revealed that UBE2T was significantly upregulated in EOC compared with that in borderline tumors, benign tumors, and normal ovarian tissues, and its high expression was associated with poor prognosis. The Cox model showed that UBE2T upregulation was an independent risk factor affecting the prognosis of EOC and SOC. Furthermore, UBE2T was associated with specific immune cells and was mainly involved in cell cycle-related events. Genomic analysis showed that TP53 and TTN mutations were associated with UBE2T expression. Gene copy number amplification and hypomethylation may be responsible for UBE2T upregulation in OC. In conclusion, UBE2 family members may play a role in the development of OC. Specifically, UBE2T could serve as a new prognostic marker and therapeutic target for this disease. (IRB Approval No. 2020PS533K).

Targeted nanopore sequencing for the identification of ABCB1 promoter translocations in cancer

BACKGROUND

Resistance to chemotherapy is the most common cause of treatment failure in acute myeloid leukemia (AML) and the drug efflux pump ABCB1 is a critical mediator. Recent studies have identified promoter translocations as common drivers of high ABCB1 expression in recurrent, chemotherapy-treated high-grade serous ovarian cancer (HGSC) and breast cancer. These fusions place ABCB1 under the control of a strong promoter while leaving its open reading frame intact. The mechanisms controlling high ABCB1 expression in AML are largely unknown. We therefore established an experimental system and analysis pipeline to determine whether promoter translocations account for high ABCB1 expression in cases of relapsed human AML.

METHODS

The human AML cell line THP-1 was used to create a model of chemotherapy resistance in which ABCB1 expression was driven by a promoter fusion. The THP-1 model was used to establish a targeted nanopore long-read sequencing approach that was then applied to cases of ABCB1high HGSC and AML. H3K27Ac ChIP sequencing was used to assess the activity of native promoters in cases of ABCB1high AML.

RESULTS

Prolonged in vitro daunorubicin exposure induced activating ABCB1 promoter translocations in human THP-1 AML cells, similar to those recently described in recurrent high-grade serous ovarian and breast cancers. Targeted nanopore sequencing proved an efficient method for identifying ABCB1 structural variants in THP-1 AML cells and HGSC; the promoter translocations identified in HGSC were both previously described and novel. In contrast, activating ABCB1 promoter translocations were not identified in ABCB1high AML; instead H3K27Ac ChIP sequencing demonstrated active native promoters in all cases studied.

CONCLUSIONS

Despite frequent high level expression of ABCB1 in relapsed primary AML we found no evidence of ABCB1 translocations and instead confirmed high-level activity of native ABCB1 promoters, consistent with endogenous regulation.

Recycling the Purpose of Old Drugs to Treat Ovarian Cancer

The main challenge in ovarian cancer treatment is the management of recurrences. Facing this scenario, therapy selection is based on multiple factors to define the best treatment sequence. Target therapies, such as bevacizumab and polymerase (PARP) inhibitors, improved patient survival. However, despite their achievements, ovarian cancer survival remains poor; these therapeutic options are highly costly and can be associated with potential side effects. Recently, it has been shown that the combination of repurposed, conventional, chemotherapeutic drugs could be an alternative, presenting good patient outcomes with few side effects and low costs for healthcare institutions. The main aim of this review is to strengthen the importance of repurposed drugs as therapeutic alternatives, and to propose an in vitro model to assess the therapeutic value. Herein, we compiled the current knowledge on the most promising non-oncological drugs for ovarian cancer treatment, focusing on statins, metformin, bisphosphonates, ivermectin, itraconazole, and ritonavir. We discuss the primary drug use, anticancer mechanisms, and applicability in ovarian cancer. Finally, we propose the use of these therapies to perform drug efficacy tests in ovarian cancer ex vivo cultures. This personalized testing approach could be crucial to validate the existing evidences supporting the use of repurposed drugs for ovarian cancer treatment.

Systems Biology and Experimental Model Systems of Cancer

Over the past decade, we have witnessed an increasing number of large-scale studies that have provided multi-omics data by high-throughput sequencing approaches. This has particularly helped with identifying key (epi)genetic alterations in cancers. Importantly, aberrations that lead to the activation of signaling networks through the disruption of normal cellular homeostasis is seen both in cancer cells and also in the neighboring tumor microenvironment. Cancer systems biology approaches have enabled the efficient integration of experimental data with computational algorithms and the implementation of actionable targeted therapies, as the exceptions, for the treatment of cancer. Comprehensive multi-omics data obtained through the sequencing of tumor samples and experimental model systems will be important in implementing novel cancer systems biology approaches and increasing their efficacy for tailoring novel personalized treatment modalities in cancer. In this review, we discuss emerging cancer systems biology approaches based on multi-omics data derived from bulk and single-cell genomics studies in addition to existing experimental model systems that play a critical role in understanding (epi)genetic heterogeneity and therapy resistance in cancer.

Human spermbots for patient-representative 3D ovarian cancer cell treatment

Cellular micromotors are attractive for locally delivering high concentrations of drug, and targeting hard-to-reach disease sites such as cervical cancer and early ovarian cancer lesions by non-invasive means. Spermatozoa are highly efficient micromotors perfectly adapted to traveling up the female reproductive system. Indeed, bovine sperm-based micromotors have shown potential to carry drugs toward gynecological cancers. However, due to major differences in the molecular make-up of bovine and human sperm, a key translational bottleneck for bringing this technology closer to the clinic is to transfer this concept to human material. Here, we successfully load human sperm with Doxorubicin (DOX) and perform treatment of 3D cervical cancer and patient-representative ovarian cancer cell cultures, resulting in strong anticancer cell effects. Additionally, we define the subcellular localization of the chemotherapeutic drug within human sperm, using high-resolution optical microscopy. We also assess drug effects on sperm motility and viability over time, employing sperm samples from healthy donors as well as assisted reproduction patients. Finally, we demonstrate guidance and release of human drug-loaded sperm onto cancer tissues using magnetic microcaps, and show the sperm microcap loaded with a second anticancer drug, camptothecin (CPT), which unlike DOX is not suitable for directly loading into sperm due to its hydrophobic nature. This co-drug delivery approach opens up novel targeted combinatorial drug therapies for future applications.

Applying Single-Cell Analysis to Gonadogenesis and DSDs (Disorders/Differences of Sex Development)

The gonads are unique among the body's organs in having a developmental choice: testis or ovary formation. Gonadal sex differentiation involves common progenitor cells that form either Sertoli and Leydig cells in the testis or granulosa and thecal cells in the ovary. Single-cell analysis is now shedding new light on how these cell lineages are specified and how they interact with the germline. Such studies are also providing new information on gonadal maturation, ageing and the somatic-germ cell niche. Furthermore, they have the potential to improve our understanding and diagnosis of Disorders/Differences of Sex Development (DSDs). DSDs occur when chromosomal, gonadal or anatomical sex are atypical. Despite major advances in recent years, most cases of DSD still cannot be explained at the molecular level. This presents a major pediatric concern. The emergence of single-cell genomics and transcriptomics now presents a novel avenue for DSD analysis, for both diagnosis and for understanding the molecular genetic etiology. Such -omics datasets have the potential to enhance our understanding of the cellular origins and pathogenesis of DSDs, as well as infertility and gonadal diseases such as cancer.