Lymphatic Invasion of Plakoglobin-Dependent Tumor Cell Clusters Drives Formation of Polyclonal Lung Metastases in Colon Cancer.

BACKGROUND & AIMS: Patients with colon cancer with liver metastases may be cured with surgery, but the presence of additional lung metastases often precludes curative treatment. Little is known about the processes driving lung metastasis. This study aimed to elucidate the mechanisms governing lung vs liver metastasis formation. METHODS: Patient-derived organoid (PDO) cultures were established from colon tumors with distinct patterns of metastasis. Mouse models recapitulating metastatic organotropism were created by implanting PDOs into the cecum wall. Optical barcoding was applied to trace the origin and clonal composition of liver and lung metastases. RNA sequencing and immunohistochemistry were used to identify candidate determinants of metastatic organotropism. Genetic, pharmacologic, in vitro, and in vivo modeling strategies identified essential steps in lung metastasis formation. Validation was performed by analyzing patient-derived tissues. RESULTS: Cecum transplantation of 3 distinct PDOs yielded models with distinct metastatic organotropism: liver only, lung only, and liver and lung. Liver metastases were seeded by single cells derived from select clones. Lung metastases were seeded by polyclonal clusters of tumor cells entering the lymphatic vasculature with very limited clonal selection. Lung-specific metastasis was associated with high expression of desmosome markers, including plakoglobin. Plakoglobin deletion abrogated tumor cell cluster formation, lymphatic invasion, and lung metastasis formation. Pharmacologic inhibition of lymphangiogenesis attenuated lung metastasis formation. Primary human colon, rectum, esophagus, and stomach tumors with lung metastases had a higher N-stage and more plakoglobin-expressing intra-lymphatic tumor cell clusters than those without lung metastases. CONCLUSIONS: Lung and liver metastasis formation are fundamentally distinct processes with different evolutionary bottlenecks, seeding entities, and anatomic routing. Polyclonal lung metastases originate from plakoglobin-dependent tumor cell clusters entering the lymphatic vasculature at the primary tumor site.

Spatiotemporal regulation of clonogenicity in colorectal cancer xenografts.

Cancer evolution is predominantly studied by focusing on differences in the genetic characteristics of malignant cells within tumors. However, the spatiotemporal dynamics of clonal outgrowth that underlie evolutionary trajectories remain largely unresolved. Here, we sought to unravel the clonal dynamics of colorectal cancer (CRC) expansion in space and time by using a color-based clonal tracing method. This method involves lentiviral red-green-blue (RGB) marking of cell populations, which enabled us to track individual cells and their clonal outgrowth during tumor initiation and growth in a xenograft model. We found that clonal expansion largely depends on the location of a clone, as small clones reside in the center and large clones mostly drive tumor growth at the border. These dynamics are recapitulated in a computational model, which confirms that the clone position within a tumor rather than cell-intrinsic features, is crucial for clonal outgrowth. We also found that no significant clonal loss occurs during tumor growth and clonal dispersal is limited in most models. Our results imply that, in addition to molecular features of clones such as (epi-)genetic differences between cells, clone location and the geometry of tumor growth are crucial for clonal expansion. Our findings suggest that either microenvironmental signals on the tumor border or differences in physical properties within the tumor, are major contributors to explain heterogeneous clonal expansion. Thus, this study provides further insights into the dynamics of solid tumor growth and progression, as well as the origins of tumor cell heterogeneity in a relevant model system.

A mouse model for peritoneal metastases of colorectal origin recapitulates patient heterogeneity.

The peritoneum is a common site of dissemination in patients with colorectal cancer. In order to identify high-risk patients and improve therapeutic strategies, a better understanding of the peritoneal dissemination process and the reasons behind the high heterogeneity that is observed between patients is required. We aimed to create a murine model to further elucidate the process of peritoneal dissemination and to provide an experimental platform for further studies. We developed an in vivo model to assess patterns of peritoneal dissemination of 15 colorectal cancer cell lines. Immune deficient mice were intraperitoneally injected with 10,000 human colorectal cancer cells. Ten weeks after injection, or earlier in case of severe discomfort, the mice were sacrificed followed by dissection including assessment of the outgrowth and localization of peritoneal metastases. Furthermore, using a color-based clonal tracing method, the clonal dynamics of peritoneal nodules were observed. The different cell lines showed great variation in the extent of peritoneal outgrowth, ranging from no outgrowth to localized or widespread outgrowth of cells. An association between KRAS pathway activation and the formation of peritoneal metastases was identified. Also, cell line specific tumor location preferences were observed, with similar patterns of outgrowth in anatomically related areas. Furthermore, different patterns regarding clonal dynamics were found, varying from monoclonal or polyclonal outgrowth to extensively dispersed polyclonal lesions. The established murine model recapitulates heterogeneity as observed in human peritoneal metastases, which makes it a suitable platform for future (intervention) studies.

Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis.

The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.

A consensus molecular subtypes classification strategy for clinical colorectal cancer tissues.

Consensus Molecular Subtype (CMS) classification of colorectal cancer (CRC) tissues is complicated by RNA degradation upon formalin-fixed paraffin-embedded (FFPE) preservation. Here, we present an FFPE-curated CMS classifier. The CMSFFPE classifier was developed using genes with a high transcript integrity in FFPE-derived RNA. We evaluated the classification accuracy in two FFPE-RNA datasets with matched fresh-frozen (FF) RNA data, and an FF-derived RNA set. An FFPE-RNA application cohort of metastatic CRC patients was established, partly treated with anti-EGFR therapy. Key characteristics per CMS were assessed. Cross-referenced with matched benchmark FF CMS calls, the CMSFFPE classifier strongly improved classification accuracy in two FFPE datasets compared with the original CMSClassifier (63.6% versus 40.9% and 83.3% versus 66.7%, respectively). We recovered CMS-specific recurrence-free survival patterns (CMS4 versus CMS2: hazard ratio 1.75, 95% CI 1.24-2.46). Key molecular and clinical associations of the CMSs were confirmed. In particular, we demonstrated the predictive value of CMS2 and CMS3 for anti-EGFR therapy response (CMS2&3: odds ratio 5.48, 95% CI 1.10-27.27). The CMSFFPE classifier is an optimized FFPE-curated research tool for CMS classification of clinical CRC samples.

Exploiting a subtype-specific mitochondrial vulnerability for successful treatment of colorectal peritoneal metastases.

Peritoneal metastases (PMs) from colorectal cancer (CRC) respond poorly to treatment and are associated with unfavorable prognosis. For example, the addition of hyperthermic intraperitoneal chemotherapy (HIPEC) to cytoreductive surgery in resectable patients shows limited benefit, and novel treatments are urgently needed. The majority of CRC-PMs represent the CMS4 molecular subtype of CRC, and here we queried the vulnerabilities of this subtype in pharmacogenomic databases to identify novel therapies. This reveals the copper ionophore elesclomol (ES) as highly effective against CRC-PMs. ES exhibits rapid cytotoxicity against CMS4 cells by targeting mitochondria. We find that a markedly reduced mitochondrial content in CMS4 cells explains their vulnerability to ES. ES demonstrates efficacy in preclinical models of PMs, including CRC-PMs and ovarian cancer organoids, mouse models, and a HIPEC rat model of PMs. The above proposes ES as a promising candidate for the local treatment of CRC-PMs, with broader implications for other PM-prone cancers.

Using picoliter droplet deposition to track clonal competition in adherent and organoid cancer cell cultures.

Clonal growth and competition underlie processes of key relevance in etiology, progression and therapy response across all cancers. Here, we demonstrate a novel experimental approach, based on multi-color, fluorescent tagging of cell nuclei, in combination with picoliter droplet deposition, to study the clonal dynamics in two- and three-dimensional cell cultures. The method allows for the simultaneous visualization and analysis of multiple clones in individual multi-clonal colonies, providing a powerful tool for studying clonal dynamics and identifying clonal populations with distinct characteristics. Results of our experiments validate the utility of the method in studying clonal dynamics in vitro, and reveal differences in key aspects of clonal behavior of different cancer cell lines in monoculture conditions, as well as in co-cultures with stromal fibroblasts.

The landscape of cell-free mitochondrial DNA in liquid biopsy for cancer detection.

BACKGROUND: Existing methods to detect tumor signal in liquid biopsy have focused on the analysis of nuclear cell-free DNA (cfDNA). However, non-nuclear cfDNA and in particular mitochondrial DNA (mtDNA) has been understudied. We hypothesize that an increase in mtDNA in plasma could reflect the presence of cancer, and that leveraging cell-free mtDNA could enhance cancer detection. RESULTS: We survey 203 healthy and 664 cancer plasma samples from three collection centers covering 12 cancer types with whole genome sequencing to catalogue the plasma mtDNA fraction. The mtDNA fraction is increased in individuals with cholangiocarcinoma, colorectal, liver, pancreatic, or prostate cancer, in comparison to that in healthy individuals. We detect almost no increase of mtDNA fraction in individuals with other cancer types. The mtDNA fraction in plasma correlates with the cfDNA tumor fraction as determined by somatic mutations and/or copy number aberrations. However, the mtDNA fraction is also elevated in a fraction of patients without an apparent increase in tumor-derived cfDNA. A predictive model integrating mtDNA and copy number analysis increases the area under the curve (AUC) from 0.73 when using copy number alterations alone to an AUC of 0.81. CONCLUSIONS: The mtDNA signal retrieved by whole genome sequencing has the potential to boost the detection of cancer when combined with other tumor-derived signals in liquid biopsies.

Real-time analysis of the cancer genome and fragmentome from plasma and urine cell-free DNA using nanopore sequencing.

Cell-free DNA (cfDNA) can be isolated and sequenced from blood and/or urine of cancer patients. Conventional short-read sequencing lacks deployability and speed and can be biased for short cfDNA fragments. Here, we demonstrate that with Oxford Nanopore Technologies (ONT) sequencing we can achieve delivery of genomic and fragmentomic data from liquid biopsies. Copy number aberrations and cfDNA fragmentation patterns can be determined in less than 24 h from sample collection. The tumor-derived cfDNA fraction calculated from plasma of lung cancer patients and urine of bladder cancer patients was highly correlated (R = 0.98) with the tumor fraction calculated from short-read sequencing of the same samples. cfDNA size profile, fragmentation patterns, fragment-end composition, and nucleosome profiling near transcription start sites in plasma and urine exhibited the typical cfDNA features. Additionally, a high proportion of long tumor-derived cfDNA fragments (> 300 bp) are recovered in plasma and urine using ONT sequencing. ONT sequencing is a cost-effective, fast, and deployable approach for obtaining genomic and fragmentomic results from liquid biopsies, allowing the analysis of previously understudied cfDNA populations.

Subtype-specific kinase dependency regulates growth and metastasis of poor-prognosis mesenchymal colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) can be divided into four consensus molecular subtypes (CMS), each with distinct biological features. CMS4 is associated with epithelial-mesenchymal transition and stromal infiltration (Guinney et al., Nat Med 21:1350-6, 2015; Linnekamp et al., Cell Death Differ 25:616-33, 2018), whereas clinically it is characterized by lower responses to adjuvant therapy, higher incidence of metastatic spreading and hence dismal prognosis (Buikhuisen et al., Oncogenesis 9:66, 2020). METHODS: To understand the biology of the mesenchymal subtype and unveil specific vulnerabilities, a large CRISPR-Cas9 drop-out screen was performed on 14 subtyped CRC cell lines to uncover essential kinases in all CMSs. Dependency of CMS4 cells on p21-activated kinase 2 (PAK2) was validated in independent 2D and 3D in vitro cultures and in vivo models assessing primary and metastatic outgrowth in liver and peritoneum. TIRF microscopy was used to uncover actin cytoskeleton dynamics and focal adhesion localization upon PAK2 loss. Subsequent functional assays were performed to determine altered growth and invasion patterns. RESULTS: PAK2 was identified as a key kinase uniquely required for growth of the mesenchymal subtype CMS4, both in vitro and in vivo. PAK2 plays an important role in cellular attachment and cytoskeletal rearrangements (Coniglio et al., Mol Cell Biol 28:4162-72, 2008; Grebenova et al., Sci Rep 9:17171, 2019). In agreement, deletion or inhibition of PAK2 impaired actin cytoskeleton dynamics in CMS4 cells and, as a consequence, significantly reduced invasive capacity, while it was dispensable for CMS2 cells. Clinical relevance of these findings was supported by the observation that deletion of PAK2 from CMS4 cells prevented metastatic spreading in vivo. Moreover, growth in a model for peritoneal metastasis was hampered when CMS4 tumor cells were deficient for PAK2. CONCLUSION: Our data reveal a unique dependency of mesenchymal CRC and provide a rationale for PAK2 inhibition to target this aggressive subgroup of colorectal cancer.

Molecular characterization of colorectal cancer related peritoneal metastatic disease.

A significant proportion of colorectal cancer (CRC) patients develop peritoneal metastases (PM) in the course of their disease. PMs are associated with a poor quality of life, significant morbidity and dismal disease outcome. To improve care for this patient group, a better understanding of the molecular characteristics of CRC-PM is required. Here we present a comprehensive molecular characterization of a cohort of 52 patients. This reveals that CRC-PM represent a distinct CRC molecular subtype, CMS4, but can be further divided in three separate categories, each presenting with unique features. We uncover that the CMS4-associated structural protein Moesin plays a key role in peritoneal dissemination. Finally, we define specific evolutionary features of CRC-PM which indicate that polyclonal metastatic seeding underlies these lesions. Together our results suggest that CRC-PM should be perceived as a distinct disease entity.

Marker-free lineage tracing reveals an environment-instructed clonogenic hierarchy in pancreatic cancer.

Effective treatments for pancreatic ductal adenocarcinoma (PDAC) are lacking, and targeted agents have demonstrated limited efficacy. It has been speculated that a rare population of cancer stem cells (CSCs) drives growth, therapy resistance, and rapid metastatic progression in PDAC. These CSCs demonstrate high clonogenicity in vitro and tumorigenic potential in vivo. However, their relevance in established PDAC tissue has not been determined. Here, we use marker-independent stochastic clonal labeling, combined with quantitative modeling of tumor expansion, to uncover PDAC tissue growth dynamics. We find that in contrast to the CSC model, all PDAC cells display clonogenic potential in situ. Furthermore, the proximity to activated cancer-associated fibroblasts determines tumor cell clonogenicity. This means that the microenvironment is dominant in defining the clonogenic activity of PDAC cells. Indeed, manipulating the stroma by Hedgehog pathway inhibition alters the tumor growth mode, revealing that tumor-stroma crosstalk shapes tumor growth dynamics and clonal architecture.

Continuous clonal labeling reveals uniform progenitor potential in the adult exocrine pancreas.

The tissue dynamics that govern maintenance and regeneration of the pancreas remain largely unknown. In particular, the presence and nature of a cellular hierarchy remains a topic of debate. Previous lineage tracing strategies in the pancreas relied on specific marker genes for clonal labeling, which left other populations untested and failed to account for potential widespread phenotypical plasticity. Here we employed a tracing system that depends on replication-induced clonal marks. We found that, in homeostasis, steady acinar replacement events characterize tissue dynamics, to which all acinar cells have an equal ability to contribute. Similarly, regeneration following pancreatitis was best characterized by an acinar self-replication model because no evidence of a cellular hierarchy was detected. In particular, rapid regeneration in the pancreas was found to be driven by an accelerated rate of acinar fission-like events. These results provide a comprehensive and quantitative model of cell dynamics in the exocrine pancreas.

Chromosomal copy number heterogeneity predicts survival rates across cancers.

Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

A cancer drug atlas enables synergistic targeting of independent drug vulnerabilities.

Personalized cancer treatments using combinations of drugs with a synergistic effect is attractive but proves to be highly challenging. Here we present an approach to uncover the efficacy of drug combinations based on the analysis of mono-drug effects. For this we used dose-response data from pharmacogenomic encyclopedias and represent these as a drug atlas. The drug atlas represents the relations between drug effects and allows to identify independent processes for which the tumor might be particularly vulnerable when attacked by two drugs. Our approach enables the prediction of combination-therapy which can be linked to tumor-driving mutations. By using this strategy, we can uncover potential effective drug combinations on a pan-cancer scale. Predicted synergies are provided and have been validated in glioblastoma, breast cancer, melanoma and leukemia mouse-models, resulting in therapeutic synergy in 75% of the tested models. This indicates that we can accurately predict effective drug combinations with translational value.

Cancer stem cells: here, there, and everywhere.

By using marker-free lineage tracing in combination with quantitative analysis, we recently revealed cancer stem cell functionality in established human colon cancer is not intrinsically defined, but fully spatiotemporally regulated.

A marker-independent lineage-tracing system to quantify clonal dynamics and stem cell functionality in cancer tissue.

Lineage tracing is a powerful tool that can be used to uncover cell fates. Here, we describe a novel method for the quantitative analysis of clonal dynamics in grafted cancer tissues. The protocol involves the preparation and validation of cells for lineage tracing, establishment of grafts and label induction, analysis of clone-size distribution and fitting of the experimental data to a mathematical tumor growth model. In contrast to other lineage-tracing strategies, the method described here assesses stem cell functionality and infers tumor expansion dynamics independently of molecular markers such as putative cancer stem cell (CSC)-specific genes. The experimental system and analytical framework presented can be used to quantify clonal advantages that specific mutations provide, in both the absence and presence of (targeted) therapeutic agents. This protocol typically takes ~20 weeks to complete from cell line selection to inference of growth dynamics, depending on the grafted cancer growth rate.

Stem cell functionality is microenvironmentally defined during tumour expansion and therapy response in colon cancer.

Solid malignancies have been speculated to depend on cancer stem cells (CSCs) for expansion and relapse after therapy. Here we report on quantitative analyses of lineage tracing data from primary colon cancer xenograft tissue to assess CSC functionality in a human solid malignancy. The temporally obtained clone size distribution data support a model in which stem cell function in established cancers is not intrinsically, but is entirely spatiotemporally orchestrated. Functional stem cells that drive tumour expansion predominantly reside at the tumour edge, close to cancer-associated fibroblasts. Hence, stem cell properties change in time depending on the cell location. Furthermore, although chemotherapy enriches for cells with a CSC phenotype, in this context functional stem cell properties are also fully defined by the microenvironment. To conclude, we identified osteopontin as a key cancer-associated fibroblast-produced factor that drives in situ clonogenicity in colon cancer.

Cancer stem cells don't waste their time cleaning-low proteasome activity, a marker for cancer stem cell function.

A population of stem-like cells in tumors, the so-called cancer stem cells (CSCs), are being held responsible for therapy resistance and tumor recurrence. In analogy with normal stem cells, CSCs possess the capacity of long term self-renewal and multilineage differentiation. CSCs are believed to be more resistant to various therapies compared to their differentiated offspring and therefore the cause of tumor relapse. Markers for CSCs have been identified using xenograft transplantation assays and lineage tracing in mouse models, however the specificity and validity of many of these markers is under debate. Recently, low proteasome activity has been postulated as a novel CSC marker. In several solid malignancies a small subset of low proteasomal activity cells with CSC characteristics were identified, suggesting that proteasomal activity might be a functional marker for CSCs. In this perspective, we will discuss a recent study by Munakata et al., describing a population of colorectal cancer cells with CSC properties, characterized by low proteasome activity and treatment resistance. We will put this finding in a broader view by discussing the challenges and issues inherent with CSC identification, as well as some emerging insights in the CSC concept.