The evolution of single cell-derived colorectal cancer cell lines is dominated by the continued selection of tumor-specific genomic imbalances, despite random chromosomal instability

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.

Investigating the suitability of in vitro cell lines as models for the major subtypes of epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is the most fatal gynaecological malignancy, accounting for over 200,000 deaths worldwide per year. EOC is a highly heterogeneous disease, classified into five major histological subtypes-high-grade serous (HGSOC), clear cell (CCOC), endometrioid (ENOC), mucinous (MOC) and low-grade serous (LGSOC) ovarian carcinomas. Classification of EOCs is clinically beneficial, as the various subtypes respond differently to chemotherapy and have distinct prognoses. Cell lines are often used as in vitro models for cancer, allowing researchers to explore pathophysiology in a relatively cheap and easy to manipulate system. However, most studies that make use of EOC cell lines fail to recognize the importance of subtype. Furthermore, the similarity of cell lines to their cognate primary tumors is often ignored. Identification of cell lines with high molecular similarity to primary tumors is needed in order to better guide pre-clinical EOC research and to improve development of targeted therapeutics and diagnostics for each distinctive subtype. This study aims to generate a reference dataset of cell lines representative of the major EOC subtypes. We found that non-negative matrix factorization (NMF) optimally clustered fifty-six cell lines into five groups, putatively corresponding to each of the five EOC subtypes. These clusters validated previous histological groupings, while also classifying other previously unannotated cell lines. We analysed the mutational and copy number landscapes of these lines to investigate whether they harboured the characteristic genomic alterations of each subtype. Finally we compared the gene expression profiles of cell lines with 93 primary tumor samples stratified by subtype, to identify lines with the highest molecular similarity to HGSOC, CCOC, ENOC, and MOC. In summary, we examined the molecular features of both EOC cell lines and primary tumors of multiple subtypes. We recommend a reference set of cell lines most suited to represent four different subtypes of EOC for both in silico and in vitro studies. We also identify lines displaying poor overall molecular similarity to EOC tumors, which we argue should be avoided in pre-clinical studies. Ultimately, our work emphasizes the importance of choosing suitable cell line models to maximise clinical relevance of experiments.

How to build a tumor: An industry perspective

During the past 15 years, a plethora of innovative 3D in vitro systems has been developed. They offer the possibility of identifying crucial cellular and molecular contributors to the disease by permitting manipulation of each in isolation. However, improvements are needed particularly with respect to the predictivity and validity of those models. The major challenge now is to identify which assay and readout combination(s) best suits the current scientific question(s). A deep understanding of the different platforms along with their pros and cons is a prerequisite to make this decision. This review aims to give an overview of the most prominent systems with a focus on applications, translational relevance and adoption drivers from an industry perspective.

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.

Hepatocyte Polyploidy: Driver or Gatekeeper of Chronic Liver Diseases

Polyploidy, also known as whole-genome amplification, is a condition in which the organism has more than two basic sets of chromosomes. Polyploidy frequently arises during tissue development and repair, and in age-associated diseases, such as cancer. Its consequences are diverse and clearly different between systems. The liver is a particularly fascinating organ in that it can adapt its ploidy to the physiological and pathological context. Polyploid hepatocytes are characterized in terms of the number of nuclei per cell (cellular ploidy; mononucleate/binucleate hepatocytes) and the number of chromosome sets in each nucleus (nuclear ploidy; diploid, tetraploid, octoploid). The advantages and disadvantages of polyploidy in mammals are not fully understood. About 30% of the hepatocytes in the human liver are polyploid. In this review, we explore the mechanisms underlying the development of polyploid cells, our current understanding of the regulation of polyploidization during development and pathophysiology and its consequences for liver function. We will also provide data shedding light on the ways in which polyploid hepatocytes cope with centrosome amplification. Finally, we discuss recent discoveries highlighting the possible roles of liver polyploidy in protecting against tumor formation, or, conversely, contributing to liver tumorigenesis.

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.

Newly established gastrointestinal cancer cell lines retain the genomic and immunophenotypic landscape of their parental cancers

Human cancer cell lines are frequently used as model systems to study molecular mechanisms and genetic changes in cancer. However, the model is repeatedly criticized for its lack of proximity to original patient tumors. Therefore, understanding to what extent cell lines cultured under artificial conditions reflect the phenotypic and genomic profiles of their corresponding parental tumors is crucial when analyzing their biological properties. To directly compare molecular alterations between patient tumors and derived cell lines, we have established new cancer cell lines from four patients with gastrointestinal tumors. Tumor entities comprised esophageal cancer, colon cancer, rectal cancer and pancreatic cancer. Phenotype and genotype of both patient tumors and derived low-passage cell lines were characterized by immunohistochemistry (22 different antibodies), array-based comparative genomic hybridization and targeted next generation sequencing (48-gene panel). The immunophenotype was highly consistent between patient tumors and derived cell lines; the expression of most markers in cell lines was concordant with the respective parental tumor and characteristic for the respective tumor entities in general. The chromosomal aberration patterns of the parental tumors were largely maintained in the cell lines and the distribution of gains and losses was typical for the respective cancer entity, despite a few distinct differences. Cancer gene mutations (e.g., KRAS, TP53) and microsatellite status were also preserved in the respective cell line derivates. In conclusion, the four examined newly established cell lines exhibited a phenotype and genotype closely recapitulating their parental tumor. Hence, newly established cancer cell lines may be useful models for further pharmacogenomic studies.

Intratumor heterogeneity: A new perspective on colorectal cancer research

Colorectal cancers generally consist of multiple subclones. These subclones have their own unique characteristics, resulting in intratumor heterogeneity (ITH). As the discussion of ITH has advanced, a model describing the relationship of ITH to the tumor has gradually emerged. ITH can be divided into two types of intraprimary tumor heterogeneity and intraindividual tumor heterogeneity, the former for further understanding of tumor composition, and the latter for providing more information about evolutionary patterns. With the rapid development of new methods, such as next‐generation, polyguanine region sequencing, and Image detection, researchers may unravel the secrets underlying ITH. The higher the ITH of the tumor, the richer the interaction between the subclones maybe, or the greater the chance of the tumor getting more powerful subclones may be, thus increasing the malignant potential of the tumor. Existing evidence suggests that ITH may increase the ability of tumors to resist treatment and can be used as an independent influence on the prognosis of colorectal cancer. We reviewed 80 recent studies to give researchers a new perspective on colorectal cancer. There is still a limited amount of research in this area. Further study of the relationship between ITH and clinical endpoints may lead to the development of new treatment strategies.

Single-Cell-Derived Primary Rectal Carcinoma Cell Lines Reflect Intratumor Heterogeneity Associated with Treatment Response

PURPOSE

The standard treatment of patients with locally advanced rectal cancer consists of preoperative chemoradiotherapy (CRT) followed by surgery. However, the response of individual tumors to CRT is extremely diverse, presenting a clinical dilemma. This broad variability in treatment response is likely attributable to intratumor heterogeneity (ITH).

EXPERIMENTAL DESIGN

We addressed the impact of ITH on response to CRT by establishing single-cell-derived cell lines (SCDCL) from a treatment-naïve rectal cancer biopsy after xenografting.

RESULTS

Individual SCDCLs derived from the same tumor responded profoundly different to CRT in vitro. Clonal reconstruction of the tumor and derived cell lines based on whole-exome sequencing revealed nine separate clusters with distinct proportions in the SCDCLs. Missense mutations in SV2A and ZWINT were clonal in the resistant SCDCL, but not detected in the sensitive SCDCL. Single-cell genetic analysis by multiplex FISH revealed the expansion of a clone with a loss of PIK3CA in the resistant SCDCL. Gene expression profiling by tRNA-sequencing identified the activation of the Wnt, Akt, and Hedgehog signaling pathways in the resistant SCDCLs. Wnt pathway activation in the resistant SCDCLs was confirmed using a reporter assay.

CONCLUSIONS

Our model system of patient-derived SCDCLs provides evidence for the critical role of ITH for treatment response in patients with rectal cancer and shows that distinct genetic aberration profiles are associated with treatment response. We identified specific pathways as the molecular basis of treatment response of individual clones, which could be targeted in resistant subclones of a heterogenous tumor.

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

High-grade serous ovarian carcinoma is characterised by TP53 mutation and extensive chromosome instability (CIN). Because our understanding of CIN mechanisms is based largely on analysing established cell lines, we developed a workflow for generating ex vivo cultures from patient biopsies to provide models that support interrogation of CIN mechanisms in cells not extensively cultured in vitro. Here, we describe a "living biobank" of ovarian cancer models with extensive replicative capacity, derived from both ascites and solid biopsies. Fifteen models are characterised by p53 profiling, exome sequencing and transcriptomics, and karyotyped using single-cell whole-genome sequencing. Time-lapse microscopy reveals catastrophic and highly heterogeneous mitoses, suggesting that analysis of established cell lines probably underestimates mitotic dysfunction in advanced human cancers. Drug profiling reveals cisplatin sensitivities consistent with patient responses, demonstrating that this workflow has potential to generate personalized avatars with advantages over current pre-clinical models and the potential to guide clinical decision making.

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Most models of cancer cell population expansion assume exponential growth kinetics at low cell densities, with deviations to account for observed slowing of growth rate only at higher densities due to limited resources such as space and nutrients. However, recent preclinical and clinical observations of tumor initiation or recurrence indicate the presence of tumor growth kinetics in which growth rates scale positively with cell numbers. These observations are analogous to the cooperative behavior of species in an ecosystem described by the ecological principle of the Allee effect. In preclinical and clinical models, however, tumor growth data are limited by the lower limit of detection (i.e., a measurable lesion) and confounding variables, such as tumor microenvironment, and immune responses may cause and mask deviations from exponential growth models. In this work, we present alternative growth models to investigate the presence of an Allee effect in cancer cells seeded at low cell densities in a controlled in vitro setting. We propose a stochastic modeling framework to disentangle expected deviations due to small population size stochastic effects from cooperative growth and use the moment approach for stochastic parameter estimation to calibrate the observed growth trajectories. We validate the framework on simulated data and apply this approach to longitudinal cell proliferation data of BT-474 luminal B breast cancer cells. We find that cell population growth kinetics are best described by a model structure that considers the Allee effect, in that the birth rate of tumor cells increases with cell number in the regime of small population size. This indicates a potentially critical role of cooperative behavior among tumor cells at low cell densities with relevance to early stage growth patterns of emerging and relapsed tumors.

This study applied principles that describe the growth dynamics of species within an ecosystem in a novel attempt to understand the growth of tumors. At low cell densities, cooperative interactions among cancer cells may influence growth in a manner reminiscent of the ecological “Allee effect,” in contrast to conventional logistic growth models.

Intra-tumor heterogeneity for endometrial cancer and its clinical significance

BACKGROUND

Management of tumors has become more complex owing to tumor heterogeneity. Fewer studies have been performed on intra-tumor heterogeneity of endometrial cancer (EC) until now. Therefore, it is of great clinical value to explore the intra-tumor heterogeneity of EC based on clinical features and gene expression profiles.

METHODS

A total of 1688 patients with EC were screened and 114 patients were finally selected, including specimens from 84 patients with primary EC without relapse (PE) and the paired metastases (P-M) specimens, as well as specimens from 30 patients with primary EC with relapse (RPE) and the paired relapsed EC (P-RE) specimens. Microarray and RNA-seq were used to detect gene expression of EC samples. Clinicopathological characteristics and molecular data were compared between PE and P-M groups and between RPE and P-RE groups to explore the intra-tumor heterogeneity of EC.

RESULTS

The clinical intra-tumor spatial heterogeneity of pathological type, grade, ER status, and PR status between PE and P-M were 17.9%, 13.1%, 28.6%, and 28.6%, respectively. The clinical intra-tumor spatiotemporal heterogeneity of pathological type, grade, ER status, and PR status between RPE and P-RE were 16.7%, 33.3%, 25.0%, and 37.5%, respectively. Cluster analysis sorts EC samples based on progression type of lesion and their pathological type. There were differentially expressed genes between PE and P-M and between RPE and P-RE, of which gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis were mainly enriched in cell proliferation, the p53 signaling pathway, etc. CONCLUSIONS:: Clinical and molecular data showed that there was spatiotemporal heterogeneity in intra-tumor of EC, which may add to the complexity of diagnosis and therapeutics for EC. Considering the intra-tumor heterogeneity, sequential chemotherapy and precision medicine may be a more suitable treatment plan for EC.

Role of aneuploidy in the carcinogenic process: Part 3 of the report of the 2017 IWGT workgroup on assessing the risk of aneugens for carcinogenesis and hereditary diseases

Aneuploidy is regarded as a hallmark of cancer, however, its role is complex with both pro- and anti-carcinogenic effects evident. In this IWGT review, we consider the role of aneuploidy in cancer biology; cancer risk associated with constitutive aneuploidy; rodent carcinogenesis with known chemical aneugens; and chemotherapy-related malignant neoplasms. Aneuploidy is seen at various stages in carcinogenesis. However, the relationship between induced aneuploidy occurring after exposure and clonal aneuploidy present in tumours is not clear. Recent evidence indicates that the induction of chromosomal instability (CIN), may be more important than aneuploidy per se, in the carcinogenic process. Down Syndrome, trisomy 21, is associated with altered hematopoiesis in utero which, in combination with subsequent mutations, results in an increased risk for acute megakaryoblastic and lymphoblastic leukemias. In contrast, there is reduced cancer risk for most solid tumours in Down Syndrome. Mouse models with high levels of aneuploidy are also associated with increased cancer risk for particular tumours with long latencies, but paradoxically other types of tumour often show decreased incidence. The aneugens reviewed that induce cancer in humans and animals all possess other carcinogenic properties, such as mutagenicity, clastogenicity, cytotoxicity, organ toxicities, hormonal and epigenetic changes which likely account for, or interact with aneuploidy, to cause carcinogenesis. Although the role that aneuploidy plays in carcinogenesis has not been fully established, in many cases, it may not play a primary causative role. Tubulin-disrupting aneugens that do not possess other properties linked to carcinogenesis, were not carcinogenic in rodents. Similarly, in humans, for the tubulin-disrupting aneugens colchicine and albendazole, there is no reported association with increased cancer risk. There is a need for further mechanistic studies on agents that induce aneuploidy, particularly by mechanisms other than tubulin disruption and to determine the role of aneuploidy in pre-neoplastic events and in early and late stage neoplasia.

DNA Replication Vulnerabilities Render Ovarian Cancer Cells Sensitive to Poly(ADP-Ribose) Glycohydrolase Inhibitors

Inhibitors of poly(ADP-ribose) polymerase (PARP) have demonstrated efficacy in women with BRCA-mutant ovarian cancer. However, only 15%-20% of ovarian cancers harbor BRCA mutations, therefore additional therapies are required. Here, we show that a subset of ovarian cancer cell lines and ex vivo models derived from patient biopsies are sensitive to a poly(ADP-ribose) glycohydrolase (PARG) inhibitor. Sensitivity is due to underlying DNA replication vulnerabilities that cause persistent fork stalling and replication catastrophe. PARG inhibition is synthetic lethal with inhibition of DNA replication factors, allowing additional models to be sensitized by CHK1 inhibitors. Because PARG and PARP inhibitor sensitivity are mutually exclusive, our observations demonstrate that PARG inhibitors have therapeutic potential to complement PARP inhibitor strategies in the treatment of ovarian cancer.

Clonal evolution through genetic bottlenecks and telomere attrition: Potential threats to in vitro data reproducibility

Tissue cultures of immortalized human cells, also known as established cell lines, are broadly accessible and cost-efficient tools for biomedical research. We here review potential genetic sources of systematic error in cell line experiments due to clonal evolution in vitro. In particular, the authors highlight alterations in telomere function over prolonged culture and population bottlenecks, respectively, as two commonly overlooked phenomena that can result in significant alterations in cell line genotypes over just one or a few passages in vitro. These alterations may include changes in mutation status of oncogenes and large scale chromosomal imbalances. We introduce a simple list of factors to be avoided in order to reduce the risk of data misinterpretation due to clonal evolution, including unacknowledged in vitro selection pressures, prolonged culture per se, harsh population size reductions, experiments at early phases after establishment, and the employment of cell lines not sufficiently analyzed by high resolution genetic techniques.

Speciation Theory of Carcinogenesis Explains Karyotypic Individuality and Long Latencies of Cancers

It has been known for over 100 years that cancers have individual karyotypes and arise only years to decades after initiating carcinogens. However, there is still no coherent theory to explain these definitive characteristics of cancer. The prevailing mutation theory holds that cancers are late because the primary cell must accumulate 3–8 causative mutations to become carcinogenic and that mutations, which induce chromosomal instability (CIN), generate the individual karyotypes of cancers. However, since there is still no proven set of mutations that transforms a normal to a cancer cell, we have recently advanced the theory that carcinogenesis is a form of speciation. This theory predicts carcinogens initiate cancer by inducing aneuploidy, which automatically unbalances thousands of genes and thus catalyzes chain-reactions of progressive aneuploidizations. Over time, these aneuploidizations have two endpoints, either non-viable karyotypes or very rarely karyotypes of new autonomous and immortal cancers. Cancer karyotypes are immortalized despite destabilizing congenital aneuploidy by clonal selections for autonomy—similar to those of conventional species. This theory predicts that the very low probability of converting the karyotype of a normal cell to that of a new autonomous cancer species by random aneuploidizations is the reason for the karyotypic individuality of new cancers and for the long latencies from carcinogens to cancers. In testing this theory, we observed: (1) Addition of mutagenic and non-mutagenic carcinogens to normal human and rat cells generated progressive aneuploidizations months before neoplastic transformation. (2) Sub-cloning of a neoplastic rat clone revealed heritable individual karyotypes, rather than the non-heritable karyotypes predicted by the CIN theory. (3) Analyses of neoplastic and preneoplastic karyotypes unexpectedly identified karyotypes with sets of 3–12 new marker chromosomes without detectable intermediates, consistent with single-step origins. We conclude that the speciation theory explains logically the long latencies from carcinogen exposure and the individuality of cancers. In addition, the theory supports the single-step origins of cancers, because karyotypic autonomy is all-or-nothing. Accordingly, we propose that preneoplastic aneuploidy and clonal neoplastic karyotypes provide more reliable therapeutic indications than current analyses of thousands of mutations.