The clonal evolution of metastatic colorectal cancer

Neutral selection and clonal expansion during the development of colon cancer metastasis

Intratumour heterogeneity has been shown to play a role in the malignant progression of cancer. The clonal evolution in primary cancer has been well studied, however, that in metastatic tumorigenesis is not fully understood. In this study, we established human colon cancer-derived organoids and investigated clonal dynamics during liver metastasis development by tracking barcode-labelled subclones. Long-term subclone co-cultures showed clonal drift, with a single subclone becoming dominant in the cell population. Interestingly, the selected subclones were not always the same, suggesting that clonal selection was not based on cell intrinsic properties. Furthermore, liver tumours developed by co-transplantation of organoid subclones into the immunodeficient mouse spleen showed a progressive drastic reduction in clonal diversity, and only one or two subclones predominated in the majority of large metastatic tumours. Importantly, selections were not limited to particular subclones but appeared to be random. A trend towards a reduction in clonal diversity was also found in liver metastases of multiple colour-labelled organoids of mouse intestinal tumours. Based on these results, we propose a novel mechanism of metastasis development, i.e. a subclone population of the disseminated tumour cells in the liver is selected by neutral selection during colonization and constitutes large metastatic tumours.

Tryptophan 2,3-dioxygenase-positive matrix fibroblasts fuel breast cancer lung metastasis via kynurenine-mediated ferroptosis resistance of metastatic cells and T cell dysfunction

BACKGROUND

Tumor metastasis is a major threat to cancer patient survival. The organ-specific niche plays a pivotal role in tumor organotropic metastasis. Fibroblasts serve as a vital component of the metastatic microenvironment, but how heterogeneous metastasis-associated fibroblasts (MAFs) promote organotropic metastasis is poorly characterized. Here, we aimed to decipher the heterogeneity of MAFs and elucidate the distinct roles of these fibroblasts in pulmonary metastasis formation in breast cancer.

METHODS

Mouse models of breast cancer pulmonary metastasis were established using an in vivo selection method of repeated injections of metastatic cells purified from the mouse lung. Single-cell RNA-sequencing (scRNA-seq) was employed to investigate the heterogeneity of MAFs. Transgenic mice were used to examine the contribution of tryptophan 2,3-dioxygenase-positive matrix fibroblasts (TDO2+ MFs) in lung metastasis.

RESULTS

We uncovered 3 subtypes of MAFs in the lung metastatic microenvironment, and their transcriptome profiles changed dynamically as lung metastasis evolved. As the predominant subtype, MFs were exclusively marked by platelet-derived growth factor receptor alpha (PDGFRA) and mainly located on the edge of the metastasis, and T cells were enriched around MFs. Notably, high MF signatures were significantly associated with poor survival in breast cancer patients. Lung metastases were markedly diminished, and the suppression of T cells was dramatically attenuated in MF-depleted experimental metastatic mouse models. We found that TDO2+ MFs controlled pulmonary metastasis by producing kynurenine (KYN), which upregulated ferritin heavy chain 1 (FTH1) level in disseminated tumor cells (DTCs), enabling DTCs to resist ferroptosis. Moreover, TDO2+ MF-secreted chemokines C-C motif chemokine ligand 8 (CCL8) and C-C motif chemokine ligand 11 (CCL11) recruited T cells. TDO2+ MF-derived KYN induced T cell dysfunction. Conditional knockout of Tdo2 in MFs diminished lung metastasis and enhanced immune activation.

CONCLUSIONS

Our study reveals crucial roles of TDO2+ MFs in promoting lung metastasis and DTCs' immune evasion in the metastatic niche. It suggests that targeting the metabolism of lung-specific stromal cells may be an effective treatment strategy for breast cancer patients with lung metastasis.

Determinants of Metastatic Colorectal Cancer With Permanent Liver- Limited Disease

Colorectal cancer (CRC) is a complex and genetically heterogeneous disease presenting a specific metastatic pattern, with the liver being the most common site of metastasis. Around 20%-25% of patients with CRC will develop exclusively hepatic metastatic disease throughout their disease history. With its specific characteristics and therapeutic options, liver-limited disease (LLD) should be considered as a specific entity. The identification of these patients is particularly relevant in view of the growing interest in liver transplantation in selected patients with advanced CRC. Identifying why some patients will develop only LLD remains a challenge, mainly because of a lack of a systemic understanding of this complex and interlinked phenomenon given that cancer has traditionally been investigated according to distinct physiological compartments. Recently, multidisciplinary efforts and new diagnostic tools have made it possible to study some of these complex issues in greater depth and may help identify targets and specific treatment strategies to benefit these patients. In this review we analyze the underlying biology and available tools to help clinicians better understand this increasingly common and specific disease.

Mechanisms of metastatic colorectal cancer

Despite extensive research and improvements in understanding colorectal cancer (CRC), its metastatic form continues to pose a substantial challenge, primarily owing to limited therapeutic options and a poor prognosis. This Review addresses the emerging focus on metastatic CRC (mCRC), which has historically been under-studied compared with primary CRC despite its lethality. We delve into two crucial aspects: the molecular and cellular determinants facilitating CRC metastasis and the principles guiding the evolution of metastatic disease. Initially, we examine the genetic alterations integral to CRC metastasis, connecting them to clinically marked characteristics of advanced CRC. Subsequently, we scrutinize the role of cellular heterogeneity and plasticity in metastatic spread and therapy resistance. Finally, we explore how the tumour microenvironment influences metastatic disease, emphasizing the effect of stromal gene programmes and the immune context. The ongoing research in these fields holds immense importance, as its future implications are projected to revolutionize the treatment of patients with mCRC, hopefully offering a promising outlook for their survival.

Identifying a gene signature of metastatic potential by linking pre-metastatic state to ultimate metastatic fate

Identifying the key molecular pathways that enable metastasis by analyzing the eventual metastatic tumor is challenging because the state of the founder subclone likely changes following metastatic colonization. To address this challenge, we labeled primary mouse pancreatic ductal adenocarcinoma (PDAC) subclones with DNA barcodes to characterize their pre-metastatic state using ATAC-seq and RNA-seq and determine their relative in vivo metastatic potential prospectively. We identified a gene signature separating metastasis-high and metastasis-low subclones orthogonal to the normal-to-PDAC and classical-to-basal axes. The metastasis-high subclones feature activation of IL-1 pathway genes and high NF-κB and Zeb/Snail family activity and the metastasis-low subclones feature activation of neuroendocrine, motility, and Wnt pathway genes and high CDX2 and HOXA13 activity. In a functional screen, we validated novel mediators of PDAC metastasis in the IL-1 pathway, including the NF-κB targets Fos and Il23a, and beyond the IL-1 pathway including Myo1b and Tmem40. We scored human PDAC tumors for our signature of metastatic potential from mouse and found that metastases have higher scores than primary tumors. Moreover, primary tumors with higher scores are associated with worse prognosis. We also found that our metastatic potential signature is enriched in other human carcinomas, suggesting that it is conserved across epithelial malignancies. This work establishes a strategy for linking cancer cell state to future behavior, reveals novel functional regulators of PDAC metastasis, and establishes a method for scoring human carcinomas based on metastatic potential.

Global trends and projections of colorectal, esophageal and stomach cancer burden among youth associated with diet: A analysis of 204 countries and territories from 1990 to 2019 and until 2040

BACKGROUND

Unhealthy diets significantly contribute to stomach, colorectal and esophageal cancer burden globally. Western diets high in processed and red meats promote carcinogenesis in these gastrointestinal cancers. However, adolescent and young adult (AYA) patients' unique needs regarding these cancers have been neglected.

METHODS

Data from the 2019 Global Burden of Disease study was used to quantify stomach, colorectal and esophageal cancer burden among AYAs from 1990 to 2040 across 204 countries. Correlations between the burden of these cancers and the Socio-demographic Index were examined.

RESULTS

High SDI locations experienced the largest reduction in cancer DALY rate change from 1990 to 2019 (-22% [-12 to -33]), compared to a small increase in low-middle SDI regions. Middle SDI areas saw the largest reduction in DALY rate change from 1990 to 2019 (-62% [-32 to -75]), compared to a small decrease in low-middle SDI locations (-9% [-27 to 10]) in esophageal cancer. From 1990-2019, stomach cancer deaths and DALYs declined across all SDI regions, with the largest reductions in high SDI locations (-61% [-57 to -69]) and smallest in low-middle SDI areas (-25% [-13 to -34]). Colorectal cancer deaths and DALYs rose across all SDI regions except high SDI locations, which showed a slight decrease.

CONCLUSION

This study demonstrates the evolving global burden of stomach, colorectal and esophageal cancers among AYAs. The highest burden was in high-middle and high SDI regions, underscoring the need to prioritize initiatives targeting these gastrointestinal malignancies in youth.

Unveiling acquired resistance to anti-EGFR therapies in colorectal cancer: a long and winding road

Emergence of acquired resistance limits the efficacy of the anti-EGFR therapies cetuximab and panitumumab in metastatic colorectal cancer. In the last decade, preclinical and clinical cohort studies have uncovered genomic alterations that confer a selective advantage to tumor cells under EGFR blockade, mainly downstream re-activation of RAS-MEK signaling and mutations in the extracellular domain of EGFR (EGFR-ECD). Liquid biopsies (genotyping of ctDNA) have been established as an excellent tool to easily monitor the dynamics of genomic alterations resistance in the blood of patients and to select patients for rechallenge with anti-EGFR therapies. Accordingly, several clinical trials have shown clinical benefit of rechallenge with anti-EGFR therapy in genomically-selected patients using ctDNA. However, alternative mechanisms underpinning resistance beyond genomics -mainly related to the tumor microenvironment-have been unveiled, specifically relevant in patients receiving chemotherapy-based multi-drug treatment in first line. This review explores the complexity of the multifaceted mechanisms that mediate secondary resistance to anti-EGFR therapies and potential therapeutic strategies to circumvent acquired resistance.

The Molecular Evolution of Melanoma Distant Metastases

The evolution of primary melanoma to lymph node and distant metastasis is incompletely understood. We examined the genomic diversity in melanoma progression in matched primary melanomas and lymph node and distant metastases from 17 patients. FISH analysis revealed cancer cell fractions with monotonic copy number alterations, including PHIP gain and PTEN loss, in the metastatic cascade. By contrast, the cancer cell fraction with copy number alterations for BPTF and MITF was reduced in lymph node metastases but increased in distant metastases. Separately, the cancer cell fraction with NCOA3 copy number alteration was comparable between primary tumors and lymph node metastases yet increased in distant metastases. These results suggest enrichment of the phosphoinositide 3-kinase and MITF pathways in the transition through the metastatic cascade. By contrast, next-generation sequencing analysis did not identify a consistent pattern of changes in variant allele frequency while revealing several intriguing findings, including decreased variant allele frequency in distant metastases and distinct drivers in lymph node versus distant metastases. These results provide evidence that distant melanoma metastasis does not always emanate from lymph node metastasis. These results enhance our understanding of clonal patterns of melanoma metastasis, with possible implications for targeted therapy and metastasis competency.

Identification of Colorectal Cancer Cell Stemness from Single-Cell RNA Sequencing

Cancer stem cells (CSC) play a critical role in metastasis, relapse, and therapy resistance in colorectal cancer. While characterization of the normal lineage of cell development in the intestine has led to the identification of many genes involved in the induction and maintenance of pluripotency, recent studies suggest significant heterogeneity in CSC populations. Moreover, while many canonical colorectal cancer CSC marker genes have been identified, the ability to use these classical markers to annotate stemness at the single-cell level is limited. In this study, we performed single-cell RNA sequencing on a cohort of 6 primary colon, 9 liver metastatic tumors, and 11 normal (nontumor) controls to identify colorectal CSCs at the single-cell level. Finding poor alignment of the 11 genes most used to identify colorectal CSC, we instead extracted a single-cell stemness signature (SCS_sig) that robustly identified "gold-standard" colorectal CSCs that expressed all marker genes. Using this SCS_sig to quantify stemness, we found that while normal epithelial cells show a bimodal distribution, indicating distinct stem and differentiated states, in tumor epithelial cells stemness is a continuum, suggesting greater plasticity in these cells. The SCS_sig score was quite variable between different tumors, reflective of the known transcriptomic heterogeneity of CRC. Notably, patients with higher SCS_sig scores had significantly shorter disease-free survival time after curative intent surgical resection, suggesting stemness is associated with relapse.

IMPLICATIONS

This study reveals significant heterogeneity of expression of genes commonly used to identify colorectal CSCs, and identifies a novel stemness signature to identify these cells from scRNA-seq data.

Evolving copy number gains promote tumor expansion and bolster mutational diversification

The timing and fitness effect of somatic copy number alterations (SCNA) in cancer evolution remains poorly understood. Here we present a framework to determine the timing of a clonal SCNA that encompasses multiple gains. This involves calculating the proportion of time from its last gain to the onset of population expansion (lead time) as well as the proportion of time prior to its first gain (initiation time). Our method capitalizes on the observation that a genomic segment, while in a specific copy number (CN) state, accumulates point mutations proportionally to its CN. Analyzing 184 whole genome sequenced samples from 75 patients across five tumor types, we commonly observe late gains following early initiating events, occurring just before the clonal expansion relevant to the sampling. These include gains acquired after genome doubling in more than 60% of cases. Notably, mathematical modeling suggests that late clonal gains may contain final-expansion drivers. Lastly, SCNAs bolster mutational diversification between subpopulations, exacerbating the circle of proliferation and increasing heterogeneity.

Chronic arsenic exposure induces malignant transformation of human HaCaT cells through both deterministic and stochastic changes in transcriptome expression

Biological processes are inherently stochastic, i.e., are partially driven by hard to predict random probabilistic processes. Carcinogenesis is driven both by stochastic and deterministic (predictable non-random) changes. However, very few studies systematically examine the contribution of stochastic events leading to cancer development. In differential gene expression studies, the established data analysis paradigms incentivize expression changes that are uniformly different across the experimental versus control groups, introducing preferential inclusion of deterministic changes at the expense of stochastic processes that might also play a crucial role in the process of carcinogenesis. In this study, we applied simple computational techniques to quantify: (i) The impact of chronic arsenic (iAs) exposure as well as passaging time on stochastic gene expression and (ii) Which genes were expressed deterministically and which were expressed stochastically at each of the three stages of cancer development. Using biological coefficient of variation as an empirical measure of stochasticity we demonstrate that chronic iAs exposure consistently suppressed passaging related stochastic gene expression at multiple time points tested, selecting for a homogenous cell population that undergo transformation. Employing multiple balanced removal of outlier data, we show that chronic iAs exposure induced deterministic and stochastic changes in the expression of unique set of genes, that populate largely unique biological pathways. Together, our data unequivocally demonstrate that both deterministic and stochastic changes in transcriptome-wide expression are critical in driving biological processes, pathways and networks towards clonal selection, carcinogenesis, and tumor heterogeneity.

A functional personalised oncology approach against metastatic colorectal cancer in matched patient derived organoids

Globally, colorectal cancer (CRC) is the third most frequently occurring cancer. Progression on to an advanced metastatic malignancy (metCRC) is often indicative of poor prognosis, as the 5-year survival rates of patients decline rapidly. Despite the availability of many systemic therapies for the management of metCRC, the long-term efficacies of these regimens are often hindered by the emergence of treatment resistance due to intratumoral and intertumoral heterogeneity. Furthermore, not all systemic therapies have associated biomarkers that can accurately predict patient responses. Hence, a functional personalised oncology (FPO) approach can enable the identification of patient-specific combinatorial vulnerabilities and synergistic combinations as effective treatment strategies. To this end, we established a panel of CRC patient-derived organoids (PDOs) as clinically relevant biological systems, of which three pairs of matched metCRC PDOs were derived from the primary sites (ptCRC) and metastatic lesions (mCRC). Histological and genomic characterisation of these PDOs demonstrated the preservation of histopathological and genetic features found in the parental tumours. Subsequent application of the phenotypic-analytical drug combination interrogation platform, Quadratic Phenotypic Optimisation Platform, in these pairs of PDOs identified patient-specific drug sensitivity profiles to epigenetic-based combination therapies. Most notably, matched PDOs from one patient exhibited differential sensitivity patterns to the rationally designed drug combinations despite being genetically similar. These findings collectively highlight the limitations of current genomic-driven precision medicine in guiding treatment strategies for metCRC patients. Instead, it suggests that epigenomic profiling and application of FPO could complement the identification of novel combinatorial vulnerabilities to target synchronous ptCRC and mCRC.

Early clonal extinction in glioblastoma progression revealed by genetic barcoding

Glioblastoma progression in its early stages remains poorly understood. Here, we transfer PDGFB and genetic barcodes in mouse brain to initiate gliomagenesis and enable direct tracing of glioblastoma evolution from its earliest possible stage. Unexpectedly, we observe a high incidence of clonal extinction events and progressive divergence in clonal sizes, even after the acquisition of malignant phenotype. Computational modeling suggests these dynamics result from clonal-based cell-cell competition. Through bulk and single-cell transcriptome analyses, coupled with lineage tracing, we reveal that Myc transcriptional targets have the strongest correlation with clonal size imbalances. Moreover, we show that the downregulation of Myc expression is sufficient to drive competitive dynamics in intracranially transplanted gliomas. Our findings provide insights into glioblastoma evolution that are inaccessible using conventional retrospective approaches, highlighting the potential of combining clonal tracing and transcriptomic analyses in this field.

PACT: a pipeline for analysis of circulating tumor DNA

MOTIVATION

Detection of genomic alterations in circulating tumor DNA (ctDNA) is currently used for active clinical monitoring of cancer progression and treatment response. While methods for analysis of small mutations are more developed, strategies for detecting structural variants (SVs) in ctDNA are limited. Additionally, reproducibly calling small-scale mutations, copy number alterations, and SVs in ctDNA is challenging due to the lack to unified tools for these different classes of variants.

RESULTS

We developed a unified pipeline for the analysis of ctDNA [Pipeline for the Analysis of ctDNA (PACT)] that accurately detects SVs and consistently outperformed similar tools when applied to simulated, cell line, and clinical data. We provide PACT in the form of a Common Workflow Language pipeline which can be run by popular workflow management systems in high-performance computing environments.

AVAILABILITY AND IMPLEMENTATION

PACT is freely available at https://github.com/ChrisMaherLab/PACT.

Autologous humanized PDX modeling for immuno-oncology recapitulates features of the human tumor microenvironment

BACKGROUND

Interactions between immune and tumor cells are critical to determining cancer progression and response. In addition, preclinical prediction of immune-related drug efficacy is limited by interspecies differences between human and mouse, as well as inter-person germline and somatic variation. To address these gaps, we developed an autologous system that models the tumor microenvironment (TME) from individual patients with solid tumors.

METHOD

With patient-derived bone marrow hematopoietic stem and progenitor cells (HSPCs), we engrafted a patient's hematopoietic system in MISTRG6 mice, followed by transfer of patient-derived xenograft (PDX) tissue, providing a fully genetically matched model to recapitulate the individual's TME. We used this system to prospectively study tumor-immune interactions in patients with solid tumor.

RESULTS

Autologous PDX mice generated innate and adaptive immune populations; these cells populated the TME; and tumors from autologously engrafted mice grew larger than tumors from non-engrafted littermate controls. Single-cell transcriptomics revealed a prominent vascular endothelial growth factor A (VEGFA) signature in TME myeloid cells, and inhibition of human VEGF-A abrogated enhanced growth.

CONCLUSIONS

Humanization of the interleukin 6 locus in MISTRG6 mice enhances HSPC engraftment, making it feasible to model tumor-immune interactions in an autologous manner from a bedside bone marrow aspirate. The TME from these autologous tumors display hallmarks of the human TME including innate and adaptive immune activation and provide a platform for preclinical drug testing.

Heterogeneity in functional genetic screens: friend or foe?

Functional genetic screens to uncover tumor-intrinsic nodes of immune resistance have uncovered numerous mechanisms by which tumors evade our immune system. However, due to technical limitations, tumor heterogeneity is imperfectly captured with many of these analyses. Here, we provide an overview of the nature and sources of heterogeneity that are relevant for tumor-immune interactions. We argue that this heterogeneity may actually contribute to the discovery of novel mechanisms of immune evasion, given a sufficiently large and heterogeneous set of input data. Taking advantage of tumor cell heterogeneity, we provide proof-of-concept analyses of mechanisms of TNF resistance. Thus, consideration of tumor heterogeneity is imperative to increase our understanding of immune resistance mechanisms.

Colorectal cancer liver metastasis: genomic evolution and crosstalk with the liver microenvironment

Colorectal cancer (CRC) patients frequently develop liver metastases, which are the major cause of cancer-related mortality. The molecular basis and management of colorectal liver metastases (CRLMs) remain a challenging clinical issue. Recent genomic evidence has demonstrated the liver tropism of CRC and the presence of a stricter evolutionary bottleneck in the liver as a target organ compared to lymph nodes. This bottleneck challenging CRC cells in the liver is organ-specific and requires adaptation not only at the genetic level, but also at the phenotypic level to crosstalk with the hepatic microenvironment. Here, we highlight the emerging evidence on the clonal evolution of CRLM and review recent insights into the molecular mechanisms orchestrating the bidirectional interactions between metastatic CRC cells and the unique liver microenvironment.

PINK1 Immunoexpression Predicts Survival in Patients Undergoing Hepatic Resection for Colorectal Liver Metastases

PTEN-induced kinase-1 (PINK1) is the initiator of the canonical mitophagy pathway. Our aim was to study the immunoexpression of PINK1 in surgical specimens from ninety patients with metastatic colorectal adenocarcinoma (CRC) to the liver (CRLM). Tissue arrays were produced, and immunohistochemical studies were analyzed by the H-Score method. The mean immunoexpression of PINK1 in normal tissues was between 40 to 100 points. In tumoral tissues, positive PINK1 immunoexpression was observed in all samples, and no differences were noted between CRCs. In CRLMs, a significant under-expression was noted for PINK1 from the rectum (71.3 ± 30.8; p < 0.042) compared to other sites. Altered PINK1 immunoexpression in CRCs, either higher than 100 points or lower than 40 points, was associated with worse overall survival (OS) (p < 0.012) due to a shorter post-metastatic survival (PMS) (p < 0.023), and it was found to be a significant independent predictor of prognosis in a multivariate model for OS and PMS (HR = 1.972, 95% CI 0.971–4.005; p = 0.022. HR = 2.023, 95% CI 1.003–4.091; p = 0.037, respectively). In conclusion, altered PINK1 immunoexpression determined in CRCs with resected CRLM predicts a worse prognosis, possibly due to the abnormal function of mitophagy.

Activated fibroblasts in cancer: Perspectives and challenges

Activated fibroblasts in tumors, or cancer-associated fibroblasts (CAFs), have become a popular research area over the past decade. As important players in many aspects of tumor biology, with functions ranging from collagen deposition to immunosuppression, CAFs have been the target of clinical and pre-clinical studies that have revealed their potential pro- and anti-tumorigenic dichotomy. In this review, we describe the important role of CAFs in the tumor microenvironment and the technological advances that made these discoveries possible, and we detail the models that are currently available for CAF investigation. Additionally, we present evidence to support the value of encompassing CAF investigation as a future therapeutic avenue alongside immune and cancer cells while highlighting the challenges that must be addressed for successful clinical translation of new findings.

Orchestration of Collective Migration and Metastasis by Tumor Cell Clusters

Metastatic dissemination has lethal consequences for cancer patients. Accruing evidence supports the hypothesis that tumor cells can migrate and metastasize as clusters of cells while maintaining contacts with one another. Collective metastasis enables tumor cells to colonize secondary sites more efficiently, resist cell death, and evade the immune system. On the other hand, tumor cell clusters face unique challenges for dissemination particularly during systemic dissemination. Here, we review recent progress toward understanding how tumor cell clusters overcome these disadvantages as well as mechanisms they utilize to gain advantages throughout the metastatic process. We consider useful models for studying collective metastasis and reflect on how the study of collective metastasis suggests new opportunities for eradicating and preventing metastatic disease.

Towards precision oncology with patient-derived xenografts

Under the selective pressure of therapy, tumours dynamically evolve multiple adaptive mechanisms that make static interrogation of genomic alterations insufficient to guide treatment decisions. Clinical research does not enable the assessment of how various regulatory circuits in tumours are affected by therapeutic insults over time and space. Likewise, testing different precision oncology approaches informed by composite and ever-changing molecular information is hard to achieve in patients. Therefore, preclinical models that incorporate the biology and genetics of human cancers, facilitate analyses of complex variables and enable adequate population throughput are needed to pinpoint randomly distributed response predictors. Patient-derived xenograft (PDX) models are dynamic entities in which cancer evolution can be monitored through serial propagation in mice. PDX models can also recapitulate interpatient diversity, thus enabling the identification of response biomarkers and therapeutic targets for molecularly defined tumour subgroups. In this Review, we discuss examples from the past decade of the use of PDX models for precision oncology, from translational research to drug discovery. We elaborate on how and to what extent preclinical observations in PDX models have confirmed and/or anticipated findings in patients. Finally, we illustrate emerging methodological efforts that could broaden the application of PDX models by honing their predictive accuracy or improving their versatility.

Single-cell sequencing reveals CD133+CD44−-originating evolution and novel stemness related variants in human colorectal cancer

Background

Tumor heterogeneity of human colorectal cancer (CRC)-initiating cells (CRCICs) in cancer tissues often represents aggressive features of cancer progression. For high-resolution examination of CRCICs, we performed single-cell whole-exome sequencing (scWES) and bulk cell targeted exome sequencing (TES) of CRCICs to investigate stemness-specific somatic alterations or clonal evolution.

Methods

Single cells of three subpopulations of CRCICs (CD133⁺CD44⁺, CD133⁻CD44⁺, and CD133⁺CD44⁻ cells), CRC cells (CRCCs), and control cells from one CRC tissue were sorted for scWES. Then, we set up a mutation panel from scWES data and TES was used to validate mutation distribution and clonal evolution in additional 96 samples (20 patients) those were also sorted into the same three groups of CRCICs and CRCCs. The knock-down experiments were used to analyze stemness-related mutant genes. Neoantigens of these mutant genes and their MHC binding affinity were also analyzed.

Findings

Clonal evolution analysis of scWES and TES showed that the CD133⁺CD44⁻ CRCICs were the likely origin of CRC before evolving into other groups of CRCICs/CRCCs. We revealed that AHNAK2, PLIN4, HLA-B, ALK, CCDC92 and ALMS1 genes were specifically mutated in CRCICs followed by the validation of their functions. Furthermore, four predicted neoantigens of AHNAK2 were identified and validated, which might have applications in immunotherapy for CRC patients.

Interpretation

All the integrative analyses above revealed clonal evolution of CRC and new markers for CRCICs and demonstrate the important roles of CRCICs in tumorigenesis and progression of CRCs.

Funding

A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Clonal evolution and expansion associated with therapy resistance and relapse of colorectal cancer

Colorectal cancer (CRC) arises by a continuous process of genetic diversification and clonal evolution. Multiple genes and pathways have a role in tumor initiation and progression. The gradual accumulation of genetic and epigenetic processes leads to the establishment of adenoma and cancer. The important 'driver' mutations in tumor suppressor genes (such as TP53, APC, and SMAD4) and oncogenes (such as KRAS, NRAS, MET, and PIK3CA) confer selective growth advantages and cause CRC advancement. Clonal evolution induced by therapeutic pressure, as well as intra-tumoral heterogeneity, has been a great challenge in the treatment of metastatic CRC. Tumors often develop resistance to treatments as a result of intra-tumor heterogeneity, clonal evolution, and selection. Hence, the development of a multidrug personalized approach should be prioritized to pave the way for therapeutics repurposing and combination therapy to arrest tumor progression. This review summarizes how selective drug pressure can impact tumor evolution, resulting in the formation of polyclonal resistance mechanisms, ultimately promoting cancer progression. Current strategies for targeting clonal evolution are described. By understanding sources and consequences of tumor heterogeneity, customized and effective treatment plans to combat drug resistance may be devised.

Delineating the intra-patient heterogeneity of molecular alterations in treatment-naïve colorectal cancer with peritoneal carcinomatosis

In a non-negligible number of patients with metastatic colorectal cancer (mCRC), the peritoneum is the predominant site of dissemination. Cure can be achieved by cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC), but this procedure is associated with long-term morbidity and high relapse rates. Thus, there is a pressing need for improved therapeutic strategies and complementary biomarkers. The present study explored the molecular heterogeneity in mCRC with peritoneal carcinomatosis (PC), and the potential clinical implications thereof. Multi-region immunohistochemical profiling and deep targeted DNA-sequencing was performed on chemotherapy-naïve tumours from seven patients with synchronous colorectal PC who underwent CRS and HIPEC. In total, 88 samples (5-19 per patient) were analysed, representing primary tumour, lymph node metastases, tumour deposits, PC and liver metastases. Expression of special AT-rich sequence-binding protein 2 (SATB2), a marker of colorectal lineage, was lacking in the majority of cases, and a conspicuous intra-patient heterogeneity was denoted for expression of the proposed prognostic and predictive biomarker RNA-binding motif protein 3 (RBM3). Loss of mismatch repair proteins MLH1 and PSM2, observed in one case, was concordant with microsatellite instability and the highest tumour mutational burden. When present in a patient, mutations in key CRC driver genes, i.e., KRAS, APC and TP53, were homogenously distributed across all samples, while less common mutations were more heterogenous. On the same note, copy number variations showed intra-patient as well inter-patient heterogeneity. In two out of seven cases, hierarchical clustering revealed that samples from the PC and lymph node metastases were more similar to each other than to the primary tumour. In summary, these findings should encourage additional studies addressing the potential distinctiveness of mCRC with PC, which might pave the way for improved personalized treatment of these patients.

Deciphering clonal dynamics and metastatic routines in a rare patient of synchronous triple-primary tumors and multiple metastases with MPTevol

Multiple primary tumor (MPT) is a special and rare cancer type, defined as more than two primary tumors presenting at the diagnosis in a single patient. The molecular characteristics and tumorigenesis of MPT remain unclear due to insufficient approaches. Here, we present MPTevol, a practical computational framework for comprehensively exploring the MPT from multiregion sequencing (MRS) experiments. To verify the utility of MPTevol, we performed whole-exome MRS for 33 samples of a rare patient with triple-primary tumors and three metastatic sites and systematically investigated clonal dynamics and metastatic routines. MPTevol assists in comparing genomic profiles across samples, detecting clonal evolutionary history and metastatic routines and quantifying the metastatic history. All triple-primary tumors were independent origins and their genomic characteristics were consistent with corresponding sporadic tumors, strongly supporting their independent tumorigenesis. We further showed two independent early monoclonal seeding events for the metastases in the ovary and uterus. We revealed that two ovarian metastases were disseminated from the same subclone of the primary tumor through undergoing whole-genome doubling processes, suggesting metastases-to-metastases seeding occurred when tumors had similar microenvironments. Surprisingly, according to the metastasis timing model of MPTevol, we found that primary tumors of about 0.058–0.124 cm diameter have been disseminating to distant organs, which is much earlier than conventional clinical views. We developed MPT-specialized analysis framework MPTevol and demonstrated its utility in explicitly resolving clonal evolutionary history and metastatic seeding routines with a rare MPT case. MPTevol is implemented in R and is available at https://github.com/qingjian1991/MPTevol under the GPL v3 license.

5-hydroxytryptamine produced by enteric serotonergic neurons initiates colorectal cancer stem cell self-renewal and tumorigenesis

Colorectal cancer stem cells (CSCs) contribute to colorectal tumorigenesis and metastasis. Colorectal CSCs reside within specialized niches and harbor self-renewal and differentiation capacities. However, the niche regulations of CSCs remain unclear. Here, we show that intestinal nerve cells are required for CSC self-renewal and colorectal tumorigenesis. Enteric serotonergic neurons produce 5-hydroxytryptamine (5-HT) to function as a modulator of CSC self-renewal. 5-HT receptors HTR1B/1D/1F are highly expressed in colorectal CSCs and engage with 5-HT to initiate Wnt/β-catenin signaling. Mechanistically, colorectal cancer (CRC)-enriched microbiota metabolite isovalerate suppresses the enrichment of the NuRD complex onto Tph2 promoter to initiate Tph2 expression, leading to 5-HT production. 5-HT signaling is correlated with CRC severity. Blocking 5-HT signaling in mice not only inhibits the self-renewal of colorectal CSCs but also displays therapeutic efficacy against CRC tumors. Our findings reveal a cross talk between intestinal neurons and tumor cells that serves as an additional layer for CSC regulation.

Efficient Algorithms Unlock Understanding of Clonal Evolution in Cancer

In this issue of Blood Cancer Discovery, Wintersinger and colleagues present a new algorithm for quickly and accurately inferring clonal phylogenies from heterogeneous tumors sampled at many timepoints and/or many sites. When coupled with serial sequencing of tumors, this advance promises to increase our understanding of the clonal dynamics that shape tumor evolution and response to therapy. See related article by Wintersinger et al., p. 208 (9).

Challenges in genomic analysis of model systems and primary tumors of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is characterized by aggressive tumor behavior and poor prognosis. Recent next-generation sequencing (NGS)-based genomic studies have provided novel treatment modes for pancreatic cancer via the identification of cancer driver variants and molecular subtypes in PDAC. Genome-wide approaches have been extended to model systems such as patient-derived xenografts (PDXs), organoids, and cell lines for pre-clinical purposes. However, the genomic characteristics vary in the model systems, which is mainly attributed to the clonal evolution of cancer cells during their construction and culture. Moreover, fundamental limitations such as low tumor cellularity and the complex tumor microenvironment of PDAC hinder the confirmation of genomic features in the primary tumor and model systems. The occurrence of these phenomena and their associated complexities may lead to false insights into the understanding of mechanisms and dynamics in tumor tissues of patients. In this review, we describe various model systems and discuss differences in the results based on genomics and transcriptomics between primary tumors and model systems. Finally, we introduce practical strategies to improve the accuracy of genomic analysis of primary tissues and model systems.

Modeling colorectal cancer evolution

Understanding cancer evolution provides a clue to tackle therapeutic difficulties in colorectal cancer. In this review, together with related works, we will introduce a series of our studies, in which we constructed an evolutionary model of colorectal cancer by combining genomic analysis and mathematical modeling. In our model, multiple subclones were generated by driver mutation acquisition and subsequent clonal expansion in early-stage tumors. Among the subclones, the one obtaining driver copy number alterations is endowed with malignant potentials to constitute a late-stage tumor in which extensive intratumor heterogeneity is generated by the accumulation of neutral mutations. We will also discuss how to translate our understanding of cancer evolution to a solution to the problem related to therapeutic resistance: mathematical modeling suggests that relapse caused by acquired resistance could be suppressed by utilizing clonal competition between sensitive and resistant clones. Considering the current rate of technological development, modeling cancer evolution by combining genomic analysis and mathematical modeling will be an increasingly important approach for understanding and overcoming cancer.

Spatiotemporal Immune Landscape of Colorectal Cancer Liver Metastasis at Single-Cell Level

Liver metastasis, the leading cause of colorectal cancer mortality, exhibits a highly heterogeneous and suppressive immune microenvironment. Here, we sequenced 97 matched samples by using single-cell RNA-seq and Spatial Transcriptomics. Strikingly, metastatic microenvironment underwent remarkable spatial reprogramming of immunosuppressive cells such as MRC1+ CCL18+ M2-like macrophages. We further developed scMetabolism, a computational pipeline for quantifying single-cell metabolism, and observed that those macrophages harbored enhanced metabolic activity. Interestingly, neoadjuvant chemotherapy could block this status and restore the antitumor immune balance in responsive patients, while the non-responsive patients deteriorated into a more suppressive one. Our work described the immune evolution of metastasis and uncovered the black box of how tumors respond to neoadjuvant chemotherapy.

Collective metastasis: coordinating the multicellular voyage

The metastatic process is arduous. Cancer cells must escape the confines of the primary tumor, make their way into and travel through the circulation, then survive and proliferate in unfavorable microenvironments. A key question is how cancer cells overcome these multiple barriers to orchestrate distant organ colonization. Accumulating evidence in human patients and animal models supports the hypothesis that clusters of tumor cells can complete the entire metastatic journey in a process referred to as collective metastasis. Here we highlight recent studies unraveling how multicellular coordination, via both physical and biochemical coupling of cells, induces cooperative properties advantageous for the completion of metastasis. We discuss conceptual challenges and unique mechanisms arising from collective dissemination that are distinct from single cell-based metastasis. Finally, we consider how the dissection of molecular transitions regulating collective metastasis could offer potential insight into cancer therapy.

Identification of cis-HOX-HOXC10 axis as a therapeutic target for colorectal tumor-initiating cells without APC mutations

Colorectal cancer (CRC) is one of the most common cancers worldwide, in which adenomatous polyposis coli (APC) mutations are frequently and uniquely observed. Here we find that cis-HOX (circular RNA stabilizing HOXC10) is robustly expressed in colorectal tumor-initiating cells (TICs). cis-HOX knockout decreases colorectal TIC numbers and impairs the self-renewal, tumorigenesis, and metastatic capacities of TICs, whereas cis-HOX overexpression drives colorectal TIC self-renewal and metastasis. Mechanistically, cis-HOX binds to HOXC10 mRNA to attenuate its decay through blocking the K-homology splicing regulatory protein (KSRP)-binding sequence of HOXC10 3' UTR. HOXC10 is highly expressed in colorectal tumors and TICs and triggers Wnt/β-catenin activation by activating FZD3 expression. HOXC10 inhibitor salinomycin exerts efficient therapeutic effects in APC-wild-type colorectal tumors, but not in tumors with APC nonsense mutations. Therefore, the cis-HOX-HOXC10 pathway drives colorectal tumorigenesis, stemness, and metastasis and serves as a potential therapeutic target for APC-wild-type colorectal tumors.

Graphery: interactive tutorials for biological network algorithms

Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Graphery is available at https://graphery.reedcompbio.org/.

Updates on Clinical Use of Liquid Biopsy in Colorectal Cancer Screening, Diagnosis, Follow-Up, and Treatment Guidance

Colorectal cancer (CRC) is one of the most common cancers worldwide, being the third most diagnosed in the world and the second deadliest. Solid biopsy provides an essential guide for the clinical management of patients with colorectal cancer; however, this method presents several limitations, in particular invasiveness, and cannot be used repeatedly. Recently, clinical research directed toward the use of liquid biopsy, as an alternative tool to solid biopsy, showed significant promise in several CRC clinical applications, as (1) detect CRC patients at early stage, (2) make treatment decision, (3) monitor treatment response, (4) predict relapses and metastases, (5) unravel tumor heterogeneity, and (6) detect minimal residual disease. The purpose of this short review is to describe the concept, the characteristics, the genetic components, and the technologies used in liquid biopsy in the context of the management of colorectal cancer, and finally we reviewed gene alterations, recently described in the literature, as promising potential biomarkers that may be specifically used in liquid biopsy tests.

Mechanisms of breast cancer metastasis

Invasive breast cancer tends to metastasize to lymph nodes and systemic sites. The management of metastasis has evolved by focusing on controlling the growth of the disease in the breast/chest wall, and at metastatic sites, initially by surgery alone, then by a combination of surgery with radiation, and later by adding systemic treatments in the form of chemotherapy, hormone manipulation, targeted therapy, immunotherapy and other treatments aimed at inhibiting the proliferation of cancer cells. It would be valuable for us to know how breast cancer metastasizes; such knowledge would likely encourage the development of therapies that focus on mechanisms of metastasis and might even allow us to avoid toxic therapies that are currently used for this disease. For example, if we had a drug that targeted a gene that is critical for metastasis, we might even be able to cure a vast majority of patients with breast cancer. By bringing together scientists with expertise in molecular aspects of breast cancer metastasis, and those with expertise in the mechanical aspects of metastasis, this paper probes interesting aspects of the metastasis cascade, further enlightening us in our efforts to improve the outcome from breast cancer treatments.

Elements and evolutionary determinants of genomic divergence between paired primary and metastatic tumors

Can metastatic-primary (M-P) genomic divergence measured from next generation sequencing reveal the natural history of metastatic dissemination? This remains an open question of utmost importance in facilitating a deeper understanding of metastatic progression, and thereby, improving its prevention. Here, we utilize mathematical and computational modeling to tackle this question as well as to provide a framework that illuminates the fundamental elements and evolutionary determinants of M-P divergence. Our framework facilitates the integration of sequencing detectability of somatic variants, and hence, paves the way towards bridging the measurable between-tumor heterogeneity with analytical modeling and interpretability. We show that the number of somatic variants of the metastatic seeding cell that are experimentally undetectable in the primary tumor, can be characterized as the path of the phylogenetic tree from the last appearing variant of the seeding cell back to the most recent detectable variant. We find that the expected length of this path is principally determined by the decay in detectability of the variants along the seeding cell's lineage; and thus, exhibits a significant dependence on the underlying tumor growth dynamics. A striking implication of this fact, is that dissemination from an advanced detectable subclone of the primary tumor can lead to an abrupt drop in the expected measurable M-P divergence, thereby breaking the previously assumed monotonic relation between seeding time and M-P divergence. This is emphatically verified by our single cell-based spatial tumor growth simulation, where we find that M-P divergence exhibits a non-monotonic relationship with seeding time when the primary tumor grows under branched and linear evolution. On the other hand, a monotonic relationship holds when we condition on the dynamics of progressive diversification, or by restricting the seeding cells to always originate from undetectable subclones. Our results highlight the fact that a precise understanding of tumor growth dynamics is the sine qua non for exploiting M-P divergence to reconstruct the chronology of metastatic dissemination. The quantitative models presented here enable further careful evaluation of M-P divergence in association with crucial evolutionary and sequencing parameters.

Neothalfine, a potent natural anti-tumor agent against metastatic colorectal cancer and its primary mechanism

Neothalfine is a natural bisbenzylisoquinoline alkaloid with the abundant resource in medicinal plants and has not been reported its anti-tumor efficacy. In the present study, the anti-tumor efficacy was investigated and it showed broad-spectrum activity against several cancer cell lines, especially metastatic colorectal cancer (HCT116, SW620, T84) with the IC₅₀ values of 7.2, 5.9, 8.2 nM, respectively, roughly equal to well-known anti-tumor agent docetaxel (4.0, 4.7, 2.7 nM) and nearly 1000 folds than CPT-11 (4.4, 5.1, 6.9 μM). Furthermore, neothalfine inhibited colorectal cell proliferation by resulting in cell cycle arrest at the G2/M phase and induced apoptosis through the dysfunction of mitochondria to trigger intrinsic apoptotic pathway by untargeted metabolomic method, mitochondrial membrane potential, and caspase-3/7 activity assay. Moreover, neothalfine damaged colorectal cancer clonal spheres expansion significantly at the concentration of 3.5 nM with nearly 1000 folds efficacy than CPT-11 (3.0 µM). The results supported that neothalfine might be an anti-tumor lead for further investigation.

Theoretical and in silico Analyses Reveal MYC as a Dynamic Network Biomarker in Colon and Rectal Cancer

In this article, we make a theoretical and in silico study for uncovering and evaluating biomarkers in colon and rectal cancer (CRC) by the dynamic network biomarker (DNB) theory. We propose a strategy to employ the theoretical concept of UICC TNM classification in CRC. To reveal the critical transition of CRC, the DNB algorithm was implemented to analyze the genome-wide dynamic network through temporal gene expression data. The relationship between gene sets and clinical features was evaluated by weighted gene co-expression network analysis. The results show that MYC was significantly associated with tumor amplification, tumor immune cells, and survival times. The candidate tumor suppressor genes were ZBTB16, MAL, LIFR, and SLIT2. Protein-protein interaction (PPI) analysis shows that these candidate tumor suppressor genes were significant in immune cells. Data from the Human Protein Atlas showed that a high expression of these candidate tumor suppressor genes was associated with favorable prognosis in TNM stages I-IV. In conclusion, this work provides significant and novel information regarding the TNM stage, cause, and consequences of elevated MYC expression in CRC. MYC expression levels had significant negative correlations with tumor suppressor genes and immune cells.

Clonal Evolution and Timing of Metastatic Colorectal Cancer

Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide, where ~50% of patients develop metastasis, despite current improved management. Genomic characterisation of metastatic CRC, and elucidating the effects of therapy on the metastatic process, are essential to help guide precision medicine. Multi-region whole-exome sequencing was performed on 191 sampled tumour regions of patient-matched therapy-naïve and treated CRC primary tumours (n = 92 tumour regions) and metastases (n = 99 tumour regions), in 30 patients. Somatic variants were analysed to define the origin, composition, and timing of seeding in the metastatic progression of therapy-naïve and treated metastatic CRC. High concordance, with few genomic differences, was observed between primary CRC and metastases. Most cases supported a late dissemination model, via either monoclonal or polyclonal seeding. Polyclonal seeding appeared more common in therapy-naïve metastases than in treated metastases. Whereby, treatment prompted for the selection of distinct resistant clones, through monoclonal seeding to distant metastatic sites. Overall, this study reinforces the importance of early clinical detection and surgical excision of the CRC tumour, whilst further highlighting the clinical challenges for metastatic CRC with increased intratumour heterogeneity (either due to early dissemination or polyclonal metastatic spread) and the underlying risk of future therapeutic resistance in treated patients.