Cell Competition Shapes Metastatic Latency and Relapse

How much do we know about the metastatic process?

Cancer cells can leave their primary sites and travel through the circulation to distant sites, where they lodge as disseminated cancer cells (DCCs), even during the early and asymptomatic stages of tumor progression. In experimental models and clinical samples, DCCs can be detected in a non-proliferative state, defined as cellular dormancy. This state can persist for extended periods until DCCs reawaken, usually in response to niche-derived reactivation signals. Therefore, their clinical detection in sites like lymph nodes and bone marrow is linked to poor survival. Current cancer therapy designs are based on the biology of the primary tumor and do not target the biology of the dormant DCC population and thus fail to eradicate the initial or subsequent waves of metastasis. In this brief review, we discuss the current methods for detecting DCCs and highlight new strategies that aim to target DCCs that constitute minimal residual disease to reduce or prevent metastasis formation. Furthermore, we present current evidence on the relevance of DCCs derived from early stages of tumor progression in metastatic disease and describe the animal models available for their study. We also discuss our current understanding of the dissemination mechanisms utilized by genetically less- and more-advanced cancer cells, which include the functional analysis of intermediate or hybrid states of epithelial-mesenchymal transition (EMT). Finally, we raise some intriguing questions regarding the clinical impact of studying the crosstalk between evolutionary waves of DCCs and the initiation of metastatic disease.

CD146, a therapeutic target involved in cell plasticity

Since its identification as a marker for advanced melanoma in the 1980s, CD146 has been found to have multiple functions in both physiological and pathological processes, including embryonic development, tissue repair and regeneration, tumor progression, fibrosis disease, and inflammations. Subsequent research has revealed that CD146 is involved in various signaling pathways as a receptor or co-receptor in these processes. This correlation between CD146 and multiple diseases has sparked interest in its potential applications in diagnosis, prognosis, and targeted therapy. To better comprehend the versatile roles of CD146, we have summarized its research history and synthesized findings from numerous reports, proposing that cell plasticity serves as the underlying mechanism through which CD146 contributes to development, regeneration, and various diseases. Targeting CD146 would consequently halt cell state shifting during the onset and progression of these related diseases. Therefore, the development of therapy targeting CD146 holds significant practical value.

ENO2 promotes anoikis resistance in anaplastic thyroid cancer by maintaining redox homeostasis

Background

Anoikis presents a significant barrier in the metastasis of cancer. As the most aggressive type of thyroid cancer, anaplastic thyroid cancer (ATC) exhibits a high risk of metastasis and is characterized by high mortality. Therefore, investigating the molecular mechanisms of anoikis resistance in ATC is important for devising therapeutic targets in clinical research.

Methods

Differentially Expressed Genes were screened in ATC cells under attached and detached culture conditions with RNA-seq. Investigate the impact of enolase 2 (ENO2) on apoptosis and spheroid formation by gain and loss of function. Changes of reactive oxygen species (ROS), glutathione (GSH) and nicotinamide adenine dinucleotide phosphate (NADPH) were detected to assess redox balance. The transcriptional regulatory role of signal transducer and activator of transcription 1 (STAT1) on ENO2 was validated through Dual-Luciferase Reporter Gene Assay. Explore the impact of ENO2 expression on the formation of lung metastases in nude mice.

Results

We found that the glycolysis process was activated in detached ATC cells. Several genes in the glycolysis process, particularly ENO2, a member of the enolase superfamily was upregulated in ATC cells cultured in suspension. The upregulation of ENO2 enabled the maintenance of redox balance by supplying GSH and NADPH, thereby preventing cells from undergoing anoikis. In terms of mechanism, the expression of STAT1 was enhanced in anoikis resistance cells, which in turn positively regulated the expression of ENO2. In vivo, ENO2-suppressed ATC cells resulted in a significantly lower rate of lung colonization compared to control ATC cells.

Conclusions

Stable expression of ENO2 and the maintenance of redox balance played a pivotal role in facilitating anoikis resistance of ATC.

Cellular spartans at the pass: Emerging intricacies of cell competition in early and late tumorigenesis

Cell competition is a mechanism for cellular quality control based on cell-cell comparisons of fitness. Recent studies have unveiled a central and complex role for cell competition in cancer. Early tumors exploit cell competition to replace neighboring normal epithelial cells. Intestinal adenomas, for example, use cell competition to outcompete wild-type epithelial cells. However, oncogenic mutations do not always confer an advantage: wild-type cells can identify mutant cells and enforce their extrusion through cell competition, a process termed "epithelial defense against cancer". A particularly interesting situation emerges in metastasis: supercompetitive tumor cells encounter heterotypic partners and engage in reciprocal competition with diverging outcomes. This article sheds light on the emerging complexity of cell competition by highlighting recent studies that unveil its context dependency. Finally, we propose that tissue histomorphology implies a crucial role for cell competition at tumor invasion fronts particularly in metastases, warranting increased attention in future studies.

Metastatic cells exploit their stoichiometric niche in the network of cancer ecosystems

Metastasis is a nonrandom process with varying degrees of organotropism-specific source-acceptor seeding. Understanding how patterns between source and acceptor tumors emerge remains a challenge in oncology. We hypothesize that organotropism results from the macronutrient niche of cells in source and acceptor organs. To test this, we constructed and analyzed a metastatic network based on 9303 records across 28 tissue types. We found that the topology of the network is nested and modular with scale-free degree distributions, reflecting organotropism along a specificity/generality continuum. The variation in topology is significantly explained by the matching of metastatic cells to their stoichiometric niche. Specifically, successful metastases are associated with higher phosphorus content in the acceptor compared to the source organ, due to metabolic constraints in proliferation crucial to the invasion of new tissues. We conclude that metastases are codetermined by processes at source and acceptor organs, where phosphorus content is a limiting factor orchestrating tumor ecology.

Prognostic model for hepatocellular carcinoma based on anoikis-related genes: immune landscape analysis and prediction of drug sensitivity

Background

Hepatocellular carcinoma (HCC) represents a complex ailment characterized by an unfavorable prognosis in advanced stages. The involvement of immune cells in HCC progression is of significant importance. Moreover, metastasis poses a substantial impediment to enhanced prognostication for HCC patients, with anoikis playing an indispensable role in facilitating the distant metastasis of tumor cells. Nevertheless, limited investigations have been conducted regarding the utilization of anoikis factors for predicting HCC prognosis and assessing immune infiltration. This present study aims to identify hepatocellular carcinoma-associated anoikis-related genes (ANRGs), establish a robust prognostic model for HCC, and delineate distinct immune characteristics based on the anoikis signature. Cell migration and cytotoxicity experiments were performed to validate the accuracy of the ANRGs model.

Methods

Consensus clustering based on ANRGs was employed in this investigation to categorize HCC samples obtained from both TCGA and Gene Expression Omnibus (GEO) cohorts. To assess the differentially expressed genes, Cox regression analysis was conducted, and subsequently, prognostic gene signatures were constructed using LASSO-Cox methodology. External validation was performed at the International Cancer Genome Conference. The tumor microenvironment (TME) was characterized utilizing ESTIMATE and CIBERSORT algorithms, while machine learning techniques facilitated the identification of potential target drugs. The wound healing assay and CCK-8 assay were employed to evaluate the migratory capacity and drug sensitivity of HCC cell lines, respectively.

Results

Utilizing the TCGA-LIHC dataset, we devised a nomogram integrating a ten-gene signature with diverse clinicopathological features. Furthermore, the discriminative potential and clinical utility of the ten-gene signature and nomogram were substantiated through ROC analysis and DCA. Subsequently, we devised a prognostic framework leveraging gene expression data from distinct risk cohorts to predict the drug responsiveness of HCC subtypes.

Conclusion

In this study, we have established a promising HCC prognostic ANRGs model, which can serve as a valuable tool for clinicians in selecting targeted therapeutic drugs, thereby improving overall patient survival rates. Additionally, this model has also revealed a strong connection between anoikis and immune cells, providing a potential avenue for elucidating the mechanisms underlying immune cell infiltration regulated by anoikis.

Development and validation of a novel anoikis-related gene signature for predicting prognosis in ovarian cancer

Anoikis plays a critical role in variable cancer types. However, studies that focus on the prognostic values of anoikis-related genes (ANRGs) in OV are scarce. Cohorts with transcriptome data and corresponding clinicopathologic data of OV patients were collected and consolidated from public databases. Multiple bioinformatics approaches were used to screen key genes from 446 anoikis-related genes, including Cox regression analysis, random survival forest analysis, and Kaplan-Meier analysis of best combinations. A five-gene signature was constructed in the discovery cohort (TCGA) and validated in four validation cohorts (GEO). Risk score of the signature stratified patients into high-risk (HRisk) and low-risk (LRisk) subgroups. Patients in the HRisk group were associated with worse OS than those in the LRisk group in both the TCGA cohort (p<0.0001, HR=2.718, 95%CI:1.872-3.947) and the four GEO cohorts (p<0.05). Multivariate Cox regression analyses confirmed that the risk score served as an independent prognostic factor in both cohorts. The signature's predictive capacity was further demonstrated by the nomogram analysis. Pathway enrichment analysis revealed that immunosuppressive and malignant progression-related pathways were enriched in the HRisk group, including TGF-β, WNT and ECM pathways. The LRisk group was characterized by immune-active signaling pathways (interferon-gamma, T cell activation, etc.) and higher proportions of anti-tumor immune cells (NK, M1, etc.) while HRisk patients were associated with higher stromal scores and less TCR richness. In conclusion, the signature reveals a close relationship between the anoikis and prognosis and may provide a potential therapeutic target for OV patients.