A research team led by Floryne O. Buishand, Phoebe Y. K. Chan, Dong Xia and Lucy J. Davison at the Royal Veterinary College turned to single-cell RNA sequencing, a technique that reads the gene expression of individual cells rather than averaging signals across a bulk tumour sample. This matters because tumours are not uniform populations; they contain rare subpopulations that may underlie treatment resistance or drive metastasis. Bulk RNA sequencing of canine insulinomas had previously shown that early-stage primary tumours resemble normal pancreas, while late-stage tumours resemble metastatic lymph nodes, but such bulk approaches cannot resolve the internal diversity of a tumour. By profiling cells one by one, the team could detect distinct clusters within each sample and identify marker genes that would be diluted into invisibility in a bulk measurement.

The researchers applied this technology to four insulinoma cell lines spanning three species: canINS, a canine line established from a spontaneously occurring insulinoma; CM, a human insulinoma line; INS-1, a rat line derived from a radiation-induced tumour; and MIN6, a murine line from a transgenic mouse expressing the large T antigen under the rat insulin promoter. Each line carries its own history and its own limitations. CM has large chromosomal rearrangements involving the insulin gene that abolished insulin secretion from early passages. MIN6 and INS-1 both secrete insulin, but their artificial genetic backgrounds do not resemble spontaneous insulinoma. Canine insulinoma, sharing clinical and molecular features with the human malignant disease, has been proposed as a translational model, and earlier work showed that Notch pathway inhibition could target chemoresistant cancer stem cells in both canINS and CM cells.

Between 5,427 and 9,423 cells were analysed per cell line, with a median of 3,606 to 5,964 genes detected per cell and 43,042 to 68,959 mean reads per cell. Computational clustering in R and Seurat revealed five or six distinct cell clusters in each line. All four lines expressed neuroendocrine markers, including ENO2, MAP2 and NCAM1, confirming their neuroendocrine identity, but a striking split emerged in their differentiation status. INS-1 and MIN6 expressed the full panel of islet hormones and mature beta-cell markers tested, including insulin genes Ins1 and Ins2, glucagon, Mafa and Pdx1. In contrast, canINS and CM expressed only ACVR1C, and in the case of CM also MAFA, among the mature beta-cell markers, and neither expressed insulin. Instead, canINS and CM expressed genes normally activated during pancreatic development or in early endocrine progenitors, such as GATA4 and ISL1, which were the only lineage-specific pancreatic progenitor markers detected in canINS.

This differentiation landscape has direct practical value. Dedifferentiation of pancreatic beta cells in adherent monolayer culture, with loss of insulin-secretory capacity, is one of the main obstacles to building representative preclinical insulinoma models. Notably, canINS cells have previously regained insulin expression and secretion when grown in non-adherent conditions, suggesting that their epigenetic memory remains intact and that the absence of insulin expression in monolayer culture does not disqualify a cell line as an insulinoma model. The study’s single-cell maps now allow researchers to make informed choices: INS-1 and MIN6 for questions requiring mature, insulin-producing beta-cell features, and canINS and CM, with their spontaneous-tumour origins, for studies closer to the clinical disease.

The team also examined epithelial-mesenchymal status, a critical axis in cancer metastasis. When cultured in monolayers, pancreatic beta cells undergo epithelial-mesenchymal transition, becoming highly proliferative cells that can re-differentiate into insulin producers. All four lines expressed the epithelial or ductal markers ANXA4, CDH1 and SLC4A4, but vimentin, a mesenchymal marker, was detected in all lines except MIN6 and was significantly higher in canINS and CM than in INS-1. This means canINS and CM contain substantial populations of hybrid epithelial/mesenchymal cells, a state previously observed in prostate, lung and colorectal cancer lines. Hybrid E/M cells are thought to migrate collectively as clusters of circulating tumour cells, enhancing metastatic potential compared with individually migrating cells, making canINS and CM the preferred models for studying how insulinoma cells acquire metastatic behaviour.

Perhaps the most tantalising discovery came from the cross-species comparison. Because single-cell analysis exposes genes robustly expressed in subpopulations that bulk methods would miss, the researchers catalogued the top ten marker genes for each of the 23 clusters identified across the four lines. Nineteen of these clusters were characterised by genes consistently expressed across all cell lines. Filtering for unique cluster markers with plausible cancer-related functions that were conserved across species and expressed in all four lines yielded eight candidate genes: DEPTOR, BICC1, GHR, CCNB2, CENPA, LMO4, VANGL1 and L1CAM. Several of these have documented pro-tumour roles in other cancers. BICC1 drives pancreatic cancer stemness and chemoresistance, L1CAM promotes perineural invasion in pancreatic cancer, CENPA has been implicated in chromosomal instability of pancreatic neuroendocrine tumours, and LMO4 is overexpressed in late-stage pancreatic cancer.

Among these candidates, the growth hormone receptor gene GHR stands out for its translational potential. GHR expression has previously been demonstrated by immunohistochemistry in canine primary insulinomas and their metastases, and growth hormone and insulin-like growth factor 1 expression were increased in metastases compared with primary tumours. This has led to the hypothesis that targeting the GH/IGF-1 axis might inhibit insulinoma proliferation and prevent micrometastatic outgrowth after surgery. Pegvisomant, currently the only clinically available GHR antagonist, is FDA approved for acromegaly, and promising preclinical results have been obtained with pegvisomant and a variant called compound G against pancreatic cancer xenografts, particularly in combination with gemcitabine. Because GHR emerged as a cross-species conserved cluster marker in all four insulinoma lines, the study provides a direct rationale for testing GHR inhibition in these models.

The second major achievement of the study addresses a logistical bottleneck that has long hampered single-cell research on rare tumours. Ideally, fresh patient samples are dissociated into single-cell suspensions immediately upon retrieval to prevent ischaemia-related gene expression changes and RNA degradation, then loaded onto droplet-based platforms within minutes. For rare diseases, where samples arrive sporadically and often far from sequencing facilities, this workflow is difficult to sustain. Cryopreservation offers an obvious solution, but only if freezing does not distort the transcriptomic picture. To test this, the team froze canINS and CM cells in 90 percent fetal calf serum with 10 percent dimethyl sulfoxide, stored them at minus 80 degrees Celsius for four weeks, thawed them, and sequenced them alongside fresh counterparts.

The verdict was emphatically reassuring. Cryopreserved samples yielded five canINS clusters and seven CM clusters, and most clusters matched their fresh counterparts closely, sharing five to nine of the top ten marker genes. Merged datasets showed near-equal distribution of fresh and frozen cells across all clusters, and expression of neuroendocrine, epithelial-mesenchymal, islet hormone and progenitor markers was fully maintained. Differential expression analysis identified 1,395 genes changed in cryopreserved canINS, but only six exceeded a log2 fold change of one, with BTF3, MEI4, NUPR1, FOS and SLC25A6 upregulated; in CM, 1,484 genes were differentially expressed and 29 exceeded the threshold, with TNFRSF12A, CKS1B and PTTG1 upregulated. Only FOS upregulation had previously been linked to DMSO cryopreservation in other cell types. These modest perturbations, the authors note, will need consideration but do not compromise data quality. The message for the field is twofold: insulinoma researchers now have a validated, species-spanning toolkit of cell lines matched to specific experimental questions, and banks of cryopreserved patient samples can finally enter single-cell studies without sacrificing fidelity, reducing assay-based variability and opening the door to larger, multi-centre studies of one of veterinary and human medicine’s most stubborn tumours.

Subject of Research: Single-cell transcriptomic analysis of fresh and cryopreserved multispecies insulinoma cell lines

Article Title: Single-cell transcriptome conservation in a multispecies comparative analysis of fresh and cryopreserved insulinoma cell lines

Article References: Buishand, F. O., Chan, P. Y. K., Xia, D., & Davison, L. J. (2025). Single-cell transcriptome conservation in a multispecies comparative analysis of fresh and cryopreserved insulinoma cell lines. Veterinary Oncology, 2(1), Article 14. https://doi.org/10.1186/s44356-025-00025-4

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00025-4

Keywords: insulinoma, single-cell RNA sequencing, cryopreservation, canine cancer, pancreatic neuroendocrine tumour, beta cells, transcriptomics, comparative oncology, GHR, oncogenes, cell lines, veterinary oncology

The research, led by corresponding authors Zhe Yang and Rudi Mao, with Pengfei Zhang, Ying Zhang and Chen Li as co-first authors, set out to answer a question that has long frustrated oncologists: why do seemingly similar esophageal tumors respond so differently to the same dose of radiation? The answer, the study suggests, lies not in a single mutation or pathway but in the collective behavior of distinct subpopulations of tumor cells, and in the way those cells reshape the immune landscape around them when radiation pressure is applied.

Methodologically, the study is a showcase of how modern computational biology can extract signal from the enormous noise of cancer genomics. The team combined single-cell RNA sequencing, which profiles gene expression in individual cells and thereby reveals the full cellular diversity of a tumor, with bulk RNA sequencing, which measures average gene expression across an entire tissue sample. Each approach has well-known limitations on its own: single-cell data are rich in resolution but expensive and technically demanding, while bulk data are abundant and clinically practical but blur the contributions of individual cell types together. Integrating the two is widely regarded as one of the most powerful strategies in contemporary oncology research, because it allows findings made at single-cell resolution to be tested against large patient cohorts.

To perform that integration, the researchers used an algorithm called scAB, which is designed to fuse transcriptomic datasets of different resolutions and identify genes associated with a specific biological condition, in this case the response of esophageal cancer cells to radiotherapy. The scAB analysis revealed significant cellular and molecular heterogeneity within esophageal squamous cell carcinoma, with distinct subpopulations of tumor cells linked to radiation resistance. In other words, within a single patient’s tumor, there exist cells that are intrinsically better equipped to survive a course of radiation, and these cells carry a recognizable transcriptional fingerprint.

From this pool of candidate genes, the team applied two machine learning methods to narrow the field: random forest and LASSO regression. Both are standard tools for feature selection in high-dimensional biological data, where thousands of genes must be evaluated and only a handful are likely to be genuinely informative. Random forest builds many decision trees on random subsets of the data and identifies genes that consistently predict the outcome of interest, while LASSO applies a penalization technique that drives the coefficients of uninformative genes to zero, leaving only the strongest predictors. The convergence of these two independent algorithms on the same shortlist gave the researchers confidence that the genes they identified were not statistical artifacts.

Two genes emerged from this computational gauntlet: MAP1LC3B and HSD17B10. MAP1LC3B encodes a protein central to autophagy, the cellular recycling process by which cells break down damaged components and, crucially, survive periods of severe stress. Radiation kills cells largely by inducing catastrophic DNA damage and oxidative stress, and autophagy is one of the principal mechanisms by which stressed cells hold themselves together long enough to repair or adapt. HSD17B10, by contrast, encodes an enzyme involved in mitochondrial metabolism, participating in the breakdown of fatty acids and amino acids and influencing the energy economy of the cell. A tumor cell that can rewire its metabolism under radiation stress has a marked survival advantage, which makes HSD17B10 a plausible contributor to treatment resistance.

The functional importance of these two genes was not left at the level of correlation. The researchers carried out experiments both in vitro, using cultured cells, and in vivo, using animal models, to test whether MAP1LC3B and HSD17B10 actually drive the behaviors predicted by the sequencing data. The results supported a dual role: the two genes regulate cell survival under radiation stress and also contribute to tumor metastasis, the process by which cancer cells detach from the primary tumor, travel through the body and establish new colonies. The link between treatment resistance and metastatic potential is one of the most clinically troubling aspects of cancer biology, because it means that surviving radiotherapy may select for cells that are also better at spreading.

Equally significant was what the study found when it examined the tumor microenvironment, the complex ecosystem of immune cells, fibroblasts and blood vessels that surrounds and infiltrates a tumor. Immune infiltration analysis showed altered patterns of immune cell presence in tumors with high expression of the two signature genes, suggesting that the microenvironment itself may contribute to radiation resistance. This observation fits into a broader and rapidly growing body of evidence that the immune context of a tumor is not a passive backdrop but an active participant in treatment response. Radiation does not act on tumor cells in isolation; it also reshapes inflammatory and immune signaling, and a tumor microenvironment that suppresses immune attack can shield residual cancer cells from both radiation and immunotherapy.

The clinical implications of the study rest on a striking expression pattern: MAP1LC3B and HSD17B10 were found to be significantly overexpressed in esophageal squamous cell carcinoma tumor tissues compared with healthy tissue, and high expression of both genes correlated with poor prognosis and radiotherapy resistance. This combination of properties, differential expression in tumors, association with survival outcomes and mechanistic involvement in resistance, is precisely the profile sought in a biomarker. If validated in larger and more diverse patient cohorts, a test based on these two genes could eventually help clinicians identify, before treatment begins, which patients are unlikely to benefit from radiotherapy alone and might instead require intensified multimodal therapy, dose escalation or alternative strategies such as immunotherapy combinations.

The study also points toward therapeutic intervention. Genes that actively promote resistance are, in principle, druggable targets, and inhibiting their function could sensitize tumors to radiation. Autophagy modulation, in particular, has long been explored as a strategy to enhance the efficacy of cancer therapy, and the new findings give that effort a specific, data-driven anchor in esophageal cancer. Metabolic enzymes such as HSD17B10 are similarly attractive targets, although the authors are careful to frame their work as identifying potential biomarkers and informing future strategies rather than delivering a ready-made treatment. The research was supported by funding from the Shandong Medical Association, the Beijing Life Oasis Public Service Center and the Wu Jieping Medical Foundation, and was conducted with institutional ethics approval and informed patient consent.

Esophageal squamous cell carcinoma remains a devastating diagnosis worldwide, with particularly high incidence in parts of East Asia, and resistance to radiotherapy is a major reason why long-term survival rates have been so difficult to improve. What this study demonstrates is that the tools now exist to dissect that resistance at single-cell resolution, to validate the resulting hypotheses with machine learning and laboratory experiments, and to translate the findings into a short list of genes that could guide patient stratification and drug development. The convergence of single-cell genomics, bulk sequencing and machine learning, exemplified by this work, is rapidly becoming the standard playbook for attacking one of oncology’s most stubborn problems: the tumor that refuses to die under the beam. Whether MAP1LC3B and HSD17B10 ultimately become the basis of a clinical test or a therapeutic target will depend on the validation studies that must now follow, but the road map from radiation resistance to its molecular roots has rarely been drawn so clearly.

Subject of Research: Molecular mechanisms of radiotherapy resistance in esophageal squamous cell carcinoma identified through integrated single-cell and bulk RNA sequencing with machine learning

Article Title: Machine learning-driven single-cell and bulk RNA sequencing integration unveils key genes modulating radiosensitivity and tumor progression in esophageal squamous cell carcinoma

Article References: Zhang, P., Zhang, Y., Li, C., Li, M., Liao, J., Liu, T., Zhou, Y., Zhang, Y., Yang, Z., & Mao, R. (2026). Machine learning-driven single-cell and bulk RNA sequencing integration unveils key genes modulating radiosensitivity and tumor progression in esophageal squamous cell carcinoma. Cancer Cell International. https://doi.org/10.1186/s12935-026-04476-z

Image Credits: AI Generated

DOI: 10.1186/s12935-026-04476-z

Keywords: esophageal squamous cell carcinoma, radiotherapy resistance, single-cell RNA sequencing, bulk RNA sequencing, machine learning, MAP1LC3B, HSD17B10, autophagy, tumor microenvironment, immune infiltration, tumor metastasis, biomarkers

The finding is striking precisely because CSN3 has historically been studied in an entirely different context. Kappa-casein is essential for the formation and stability of casein micelles in mammary epithelial cells, and the gene has long been a subject of interest in animal breeding and dairy science, where polymorphisms in CSN3 influence milk composition in cattle and water buffalo. Yet accumulating evidence has suggested that dysregulated casein gene expression may extend beyond lactation. Previous work has linked abnormal CSN3 activity to tumorigenesis in other tissues, including a recent report that CSN3 promotes gastric cancer progression and is associated with immune infiltration and inflammatory signaling. The new study extends that emerging picture to the lower gastrointestinal tract, where colorectal cancer remains a leading cause of cancer-related death globally.

To establish the clinical relevance of CSN3 in colorectal cancer, the research team, led by Cheng Chen and Tingting Tu of the hospital’s Department of Radiotherapy, with correspondence to Yingzhi Lu and Guanhong Huang, combined large-scale public data with direct tissue analysis. They interrogated gene expression datasets from the Gene Expression Omnibus and The Cancer Genome Atlas, and complemented these computational surveys with immunohistochemistry and quantitative reverse transcription polymerase chain reaction on patient samples. Across these independent approaches, CSN3 messenger RNA and protein levels were consistently higher in colorectal cancer tissues than in normal counterparts. Crucially, the elevated expression was not merely a molecular curiosity: patients whose tumors expressed high levels of CSN3 were more likely to have cancer that had spread to lymph nodes and to present at an advanced TNM stage, and their overall outcomes were poorer.

Correlation alone, however, does not establish causation, and this is where the study’s functional experiments become central. The researchers used gain- and loss-of-function approaches in a panel of colorectal cancer cell lines, overexpressing CSN3 in HT29 and SW480 cells while silencing it with small interfering RNA in HCT116 and SW620 cells. They then measured the consequences using a battery of standard assays: Cell Counting Kit-8 assays for proliferation, Annexin V/propidium iodide flow cytometry for apoptosis, wound-healing assays for migratory capacity, and Transwell assays for both migration and invasion. The results were unambiguous. When CSN3 was overexpressed, colorectal cancer cells proliferated faster, moved farther, invaded more aggressively, and resisted programmed cell death. When CSN3 was knocked down, all of these malignant behaviors were reversed. The team also validated their knockdown results with an independent siRNA sequence, a methodological safeguard that strengthens confidence that the observed effects were genuinely attributable to CSN3 rather than off-target artifacts.

A particularly important dimension of the work concerns epithelial-mesenchymal transition, or EMT, the developmental program that cancer cells hijack to become motile and invasive. During EMT, epithelial cells lose their adhesive, polarized character and acquire the deformability and migratory behavior of mesenchymal cells, a transformation widely regarded as a key step in metastatic dissemination. Western blot analysis in the study tracked the canonical molecular signature of this transition, showing changes in E-cadherin, the epithelial adhesion molecule, and in N-cadherin and vimentin, hallmark mesenchymal markers, in response to CSN3 manipulation. CSN3 overexpression promoted the EMT program, while its knockdown suppressed it, linking the milk protein gene directly to the machinery that colorectal tumors use to invade surrounding tissue and seed distant sites.

The mechanistic heart of the paper lies in the identification of the signaling pathway through which CSN3 exerts these effects. Using transcriptomic enrichment analysis of the GEO dataset GSE21510, the researchers identified CSN3-associated signaling pathways, and western blotting then confirmed that CSN3 activates the PI3K/AKT/mTOR axis. This pathway functions as a central growth-control circuit in cells: phosphoinositide 3-kinase generates lipid second messengers that recruit and activate AKT, also known as protein kinase B, which in turn activates mechanistic target of rapamycin and its downstream effectors p70S6K and 4EBP1, driving protein synthesis, cell growth, survival, and proliferation. In the study, CSN3 manipulation was accompanied by increased phosphorylation of PI3K, AKT, mTOR, p70S6K, and 4EBP1, indicating that the entire cascade was switched on in cells with high CSN3 and dialed down when CSN3 was removed.

To test whether this pathway activation was functionally responsible for CSN3’s tumor-promoting effects, the researchers turned to pharmacological inhibition. MK-2206, a selective AKT inhibitor, was applied to CSN3-overexpressing cells, and the results were decisive: the drug attenuated CSN3-induced proliferation, migration, and invasion, partially restored apoptosis, and reduced AKT phosphorylation. In other words, when the AKT node of the pathway was blocked, CSN3 lost much of its power to drive malignant behavior, satisfying a key criterion for causal mechanism. The PI3K/AKT/mTOR pathway is already recognized as a major therapeutic target in colorectal cancer, and this work positions CSN3 as an upstream contributor to its activation in a subset of tumors.

Perhaps the most intriguing mechanistic discovery, however, involves a second casein family member. Protein-protein interaction analysis using the STRING database, together with co-immunoprecipitation experiments, supported a physical association between CSN3 and CSN1S1, the gene encoding alpha-S1 casein. When the researchers knocked down CSN1S1, the tumor-promoting effects of CSN3 were attenuated: proliferation, migration, invasion, EMT, and AKT activation all diminished. This rescue-style experiment suggests that CSN1S1 contributes to CSN3-mediated AKT activation, hinting at a cooperative role for casein proteins within cancer cells that echoes, in a distorted form, their cooperative function in milk production. The idea that two milk structural proteins may physically interact to activate a growth signaling pathway inside a tumor cell is among the more unexpected findings to emerge from colorectal cancer research in recent years.

The study also touched on the tumor immune microenvironment, using the CIBERSORT algorithm to explore correlations between CSN3 and immune-infiltrating cell populations, an analysis that follows the authors’ earlier work linking CSN3 to immune infiltration in gastric cancer. While the abstract’s conclusions center on the AKT-dependent malignant phenotypes, the immune dimension adds a further layer of potential relevance, given the importance of immunological context in colorectal cancer prognosis and treatment response. The retrospective study was approved by the Ethics Committee of the Second People’s Hospital of Lianyungang, and the authors declare no competing interests.

As with any cell-line and tissue-based investigation, the findings will need to be extended through larger clinical cohorts and in vivo models before they translate into clinical practice, and the authors themselves frame CSN3 as having potential prognostic relevance rather than presenting it as an established therapeutic target. Even so, the study adds a genuinely novel name to the growing catalog of molecules that drive colorectal cancer through PI3K/AKT/mTOR signaling, a pathway already targeted by existing drug classes. If subsequent work confirms CSN3’s role and clarifies how the casein protein complex engages AKT signaling in tumor cells, a gene long confined to dairy science textbooks could find itself on the shortlist of biomarkers used to stratify colorectal cancer patients, and perhaps even as a point of therapeutic vulnerability in tumors that depend on it.

Subject of Research: The role of the kappa-casein gene CSN3 and the PI3K/AKT/mTOR pathway in colorectal cancer progression

Article Title: CSN3 promotes colorectal cancer cell progression through activation of the PI3K/AKT/mTOR pathway

Article References: Chen, C., Tu, T., Xu, H., Wang, G., Lu, Y., & Huang, G. (2026). CSN3 promotes colorectal cancer cell progression through activation of the PI3K/AKT/mTOR pathway. Molecular Biology Reports, 53(1), Article 1666. https://doi.org/10.1007/s11033-026-12825-4

Image Credits: AI Generated

DOI: 10.1007/s11033-026-12825-4

Keywords: colorectal cancer, CSN3, kappa-casein, PI3K/AKT/mTOR pathway, AKT signaling, CSN1S1, epithelial-mesenchymal transition, metastasis, MK-2206, tumor biomarker, Molecular Biology Reports, cell signaling

The technological revolution behind this reframing is worth appreciating. For most of the history of cancer biology, fibroblasts were studied in bulk, and their heterogeneity was invisible. The advent of single-cell RNA sequencing allowed researchers to profile the gene expression of individual fibroblasts within a tumor, revealing a startling mosaic of states. Spatial transcriptomics then added geography to the picture, showing where each fibroblast subtype resides relative to cancer cells, blood vessels, and immune cells. Multi-omics approaches that layer epigenetic, proteomic, and metabolic data on top of these maps have now made it possible to trace how fibroblast identities shift as tumors evolve. What has emerged is a taxonomy of recurring CAF programs: myofibroblastic CAFs marked by alpha-smooth muscle actin and contractile machinery, inflammatory CAFs that secrete cytokines such as interleukin-6 and CXCL12, antigen-presenting CAFs that display MHC class II molecules, interferon-response CAFs, and vascular-associated CAFs that hug the tumor’s blood supply.

Each of these states maps onto specific steps of the metastatic cascade, the multi-stage journey that carries a tumor cell from its primary site to a distant organ. The first step, local invasion, depends heavily on extracellular matrix remodeling. Myofibroblastic CAFs are master builders and demolition crews of the matrix, depositing collagen and cross-linking it with enzymes such as lysyl oxidase. This stiffened, realigned matrix does not merely form a physical scaffold; it generates mechanical cues that activate signaling pathways like FAK, YAP/TAZ, and ROCK in neighboring cancer cells, promoting epithelial-mesenchymal transition, the program by which epithelial tumor cells acquire motile, invasive properties. In pancreatic ductal adenocarcinoma, one of the most fibroblast-dense malignancies known, this dense stroma creates both a barrier to immune infiltration and a highway for invasion, illustrating how a single fibroblast program can simultaneously enable multiple metastatic steps.

Once tumor cells begin to move, they must evade the immune system, and here the review highlights a particularly insidious role for inflammatory CAFs. Through secretion of chemokines such as CXCL12 and CCL5, these fibroblasts recruit immunosuppressive cells, including regulatory T cells and myeloid-derived suppressor cells, while excluding or exhausting cytotoxic T lymphocytes that would otherwise kill tumor cells. The JAK/STAT and NF-kappa-B signaling pathways are central to this inflammatory choreography. Antigen-presenting CAFs add another layer of complexity: by expressing MHC class II molecules and, in some contexts, immune checkpoints such as PD-L2, they can directly modulate T cell activity in ways that remain incompletely understood but appear to tilt the local immune balance toward tolerance rather than attack. The net effect is a tumor microenvironment in which the stroma itself acts as an immunological shield.

Angiogenesis and vascular dissemination represent the next stage of the journey, and vascular-associated CAFs sit at this frontier. Positioned adjacent to tumor blood vessels, these cells interact with endothelial cells through vascular endothelial growth factor signaling and other pathways, supporting the formation of the leaky, disorganized vasculature that allows circulating tumor cells to enter the bloodstream. The review also describes how fibroblasts contribute to pre-metastatic niche formation, a phenomenon in which the primary tumor sends molecular advance parties, often packaged in extracellular vesicles, to distant organs such as the lung, liver, and bone. These signals condition resident fibroblasts in future metastatic sites, prompting them to remodel the matrix, secrete inflammatory mediators, and lay down a welcoming bed before any cancer cell arrives. Neutrophil extracellular traps and other stromal components recruited in this process further prepare distant tissues for colonization.

Metastatic colonization, the final and often fatal step, is where fibroblast support may matter most. Circulating tumor cells that survive in the bloodstream face a hostile foreign microenvironment, and the success or failure of their settlement depends on the stromal soil they encounter. The review emphasizes that the relationship between CAF states and metastatic progression is bidirectional: not only do distinct fibroblast states regulate specific steps of the cascade, but tumor-derived cues, inflammation, vascular signals, mechanical stress, metabolic conditions, and even therapy itself can reshape the composition and behavior of the fibroblast population. Chemotherapy, for example, can induce fibroblast state transitions that render the microenvironment more permissive to regrowth, a form of therapy-induced plasticity that may explain some treatment failures.

Perhaps the most consequential message of the review concerns the context-dependent duality of CAF function. Fibroblasts are not uniformly villainous. Certain fibroblast states and signals have been shown to restrain tumor growth, maintain tissue architecture, and support anti-tumor immunity. The authors point to clinical lessons from attempts at indiscriminate stromal depletion: in some settings, eliminating fibroblasts or blocking their hallmark signaling pathways worsened outcomes, unleashing more aggressive tumor behavior. The Sonic hedgehog pathway in pancreatic cancer became a cautionary tale in this regard, as its inhibition depleted stroma yet failed to improve, and in some models worsened, disease. Vitamin D receptor signaling, by contrast, has been associated with a tumor-restraining fibroblast phenotype, suggesting that reprogramming fibroblasts toward benign states may be more productive than killing them.

This insight underpins the precision therapeutic strategies the review advocates. Rather than viewing the stroma as a target for demolition, the authors propose selective modulation: identifying which fibroblast states dominate a given tumor, at a given metastatic stage, and intervening to disable their tumor-promoting functions while preserving or enhancing their tumor-restraining ones. Candidate approaches include inhibiting fibroblast activation protein on specific CAF subsets, blocking TGF-beta signaling in myofibroblastic CAFs, reprogramming inflammatory CAFs through agents such as all-trans retinoic acid, and exploiting metabolic vulnerabilities unique to particular fibroblast states. Emerging technologies such as CAR-T cells engineered against CAF-specific antigens and photodynamic therapy aimed at stromal compartments are also evaluated, with the authors stressing that each strategy must account for the risk of pushing plastic fibroblasts into more dangerous states.

The framework proposed by Li and colleagues integrates four dimensions that have often been studied in isolation: cellular state, spatial niche, metastatic stage, and phenotypic plasticity. In this view, a myofibroblastic CAF at the invasive front of a primary tumor, an inflammatory CAF clustered near excluded T cells, and a vascular-associated CAF lining a metastatic niche in the liver are not variations on a theme but distinct therapeutic targets requiring distinct interventions. The authors acknowledge that major questions remain unresolved, including how the reciprocal feedback loops between tumor cells and fibroblasts determine therapeutic response, and how best to monitor CAF state composition in patients over time. Single-cell and spatial technologies are increasingly being applied to clinical samples, raising the prospect that fibroblast-state profiling could one day guide stromal-targeted treatment decisions just as molecular profiling of tumor cells guides targeted therapy today.

For a field that has spent decades focused almost exclusively on the cancer cell itself, the message of this synthesis is quietly radical: the most abundant cell in many tumors is not a passive bystander but an active, plastic, and heterogeneous participant in metastasis, and the tools to map and manipulate it are finally at hand. If the metastasis-oriented framework proposed here proves correct, the future of anti-metastatic therapy may depend less on attacking tumor cells directly and more on negotiating with the fibroblasts that build their roads, guard their borders, and prepare their landing sites. Turning these cellular accomplices from collaborators into inhibitors, the review suggests, could transform how medicine confronts the spread of cancer, the process responsible for the majority of cancer deaths worldwide.

Subject of Research: Heterogeneity of cancer-associated fibroblasts and their roles in tumor metastasis and targeted therapy

Article Title: Heterogeneity of cancer-associated fibroblasts in tumor metastasis: mechanisms and precision therapeutic strategies

Article References: Li, Y., Chen, Y., Shen, X., Lou, J., Zhang, L., Qin, J., Pan, Y., & Wang, S. (2026). Heterogeneity of cancer-associated fibroblasts in tumor metastasis: mechanisms and precision therapeutic strategies. Molecular Cancer. https://doi.org/10.1186/s12943-026-02805-4

Image Credits: AI Generated

DOI: 10.1186/s12943-026-02805-4

Keywords: cancer-associated fibroblasts, tumor metastasis, tumor microenvironment, extracellular matrix remodeling, single-cell RNA sequencing, spatial transcriptomics, pre-metastatic niche, epithelial-mesenchymal transition, angiogenesis, immune evasion, CAF plasticity, stromal-targeted therapy

The review organizes the field around the central concept of writers, erasers and readers. Writer enzymes install modifications on RNA; erasers remove them; and reader proteins recognize the marks and translate them into functional consequences. The best-characterized internal modification is N6-methyladenosine, or m6A, the addition of a methyl group to the sixth nitrogen of adenosine. The core writer complex includes the methyltransferases METTL3 and METTL14 together with accessory factors such as WTAP, VIRMA and METTL16, all drawing their methyl groups from the universal cellular methyl donor S-adenosylmethionine. Removal is handled by two demethylases, FTO and ALKBH5, while recognition is mediated by a family of readers that includes YTHDC1, the YTHDF proteins 1 through 3, and the IGF2BP family of mRNA-binding proteins, as well as HNRNPC and HNRNPA2B1, which respond indirectly to m6A by altering RNA structure. Because each of these components can act on hundreds of different transcripts, a single change in writer or eraser activity can reprogram entire gene-expression networks at once.

Beyond m6A, the review catalogues a growing cast of chemically distinct marks with established roles in cancer. 5-methylcytosine, or m5C, is installed by the NSUN family of methyltransferases and by DNMT2, and is read by proteins such as ALYREF to influence RNA export and stability. N4-acetylcytidine, ac4C, deposited by the acetyltransferase NAT10, enhances mRNA stability and translation efficiency. N1-methyladenosine, m1A, and N7-methylguanosine, m7G, mark transcript start sites and cap structures respectively, with METTL5, ZCCHC4 and TRMT112 among the enzymes implicated in their deposition. Pseudouridine, the most abundant internal RNA modification, is catalyzed by pseudouridine synthases, including the dyskerin complex that also maintains telomeres. Even RNA editing, in which adenosine is converted to inosine by ADAR enzymes, is treated in the review as part of the same post-transcriptional regulatory landscape. Each modification type can affect different RNA classes, from messenger RNAs and microRNAs to long non-coding RNAs, transfer RNAs and ribosomal RNAs, giving cancer cells an enormous combinatorial toolkit.

The mechanistic heart of the review concerns how these marks enable metastasis. Metastasis is not a single event but a sequence of transitions: tumor cells must detach from the primary mass, invade surrounding tissue, enter the circulation, survive immune attack and shear stress, exit at a distant site, and finally adapt to an alien microenvironment. A recurring theme is that RNA modifications regulate phenotypic plasticity, the capacity of tumor cells to switch between epithelial and mesenchymal states. The epithelial-mesenchymal transition, or EMT, is a prime example. The authors describe how m6A machinery components, particularly METTL3 and the demethylases FTO and ALKBH5, modulate the stability and translation of key EMT transcription factors and signaling mediators, tipping cells toward a motile, invasive, stem-like state or back again. Because these modifications are reversible and rapidly responsive to environmental cues, they provide cancer cells with a fast-acting adaptation mechanism that genetic mutations alone cannot match.

The review also emphasizes that RNA modifications act far beyond the tumor cell itself, remodeling the tumor microenvironment. Cancer-associated fibroblasts, endothelial cells, and infiltrating immune cells all carry their own epitranscriptomic programs that tumors can exploit. In the immune compartment, the authors highlight evidence that m6A modification of transcripts in myeloid-derived suppressor cells and other immune populations shapes the immunosuppressive milieu that shields metastasizing cells from immune destruction. Exosomes and other non-coding RNA species exported from tumor cells carry their modification patterns with them, potentially pre-metastatic niches for incoming tumor cells. This systems-level view reframes metastasis as a conversation between tumor and host that is conducted partly in the language of RNA chemistry, and it suggests that targeting modification enzymes in stromal or immune cells could complement direct attacks on the tumor.

Therapy resistance emerges in the review as the second major arena in which RNA modifications exert decisive influence. The authors detail how modification enzymes regulate the classical determinants of drug response, including the ATP-binding cassette transporter family such as ABCB1 and MDR1, which pump chemotherapeutics out of cells, and the DNA damage response pathways that repair the lesions chemotherapy and radiotherapy inflict. They also describe the connection to cancer stem cells, the slow-dividing, self-renewing subpopulations that survive treatment and seed relapse. RNA modification writers and readers help maintain the stem-like state and the drug-tolerant persister phenotypes that characterize minimal residual disease. In targeted therapy contexts, the review notes involvement of pathways such as Bruton’s tyrosine kinase signaling, illustrating that epitranscriptomic dysregulation is not confined to cytotoxic chemotherapy but extends across the modern therapeutic arsenal.

A particularly compelling section of the review traces how the same modification enzymes can produce opposite effects in different cancer types, a phenomenon the authors use to underscore context dependence. METTL3, for instance, has been reported to act as an oncogenic driver in some tumors by stabilizing pro-metastatic transcripts, while in other settings its depletion promotes tumor progression, reflecting differences in the transcriptome it methylates and the readers available to interpret those marks. This duality has direct clinical consequences: any therapeutic strategy aimed at inhibiting or activating a modification enzyme must account for tumor-type-specific substrate repertoires. The review systematically maps these functional landscapes across diverse cancers, providing what the authors describe as a theoretical foundation for identifying which patients might benefit from which epitranscriptomic intervention.

Translational implications form the forward-looking core of the paper. The authors argue that modification enzymes and their marks hold promise as biomarkers at multiple levels. Aberrant expression of writers such as METTL3, NAT10 or NSUN family members can be measured in tumor biopsies and may correlate with metastatic risk, stage, or predicted drug response. Modification patterns themselves, detectable by emerging high-throughput sequencing methods that map m6A, m5C and other marks transcriptome-wide, could serve as a post-transcriptional analog of the mutational profiling that already guides precision oncology. Circulating tumor RNA carrying characteristic modification signatures might eventually support non-invasive monitoring. The review frames these possibilities as grounded in the demonstrated mechanistic links between specific enzymes and specific metastatic or resistance phenotypes, rather than as speculation.

Therapeutically, the review surveys early efforts to drug the epitranscriptome. Small-molecule inhibitors of FTO have entered preclinical and early clinical evaluation, and compounds targeting METTL3 and NAT10 are under active development. The authors stress that the reversibility of RNA modifications makes them pharmacologically attractive: unlike mutated oncogenes, an enzyme’s activity can be tuned up or down, and because normal tissues also rely on these enzymes, selectivity and therapeutic window will be critical challenges. Combination strategies, pairing epitranscriptomic drugs with immunotherapy, chemotherapy or targeted agents, emerge as a rational approach, particularly given the documented roles of modification enzymes in shaping immune evasion and DNA damage repair. The review also flags technical hurdles, including the need for more precise and affordable mapping technologies and better models of metastatic progression in which to test candidate inhibitors.

What distinguishes this synthesis is its insistence that metastasis and resistance be understood as dynamically plastic processes governed by post-transcriptional regulatory networks rather than as fixed genetic outcomes. By cataloguing the writers, erasers and readers of more than a dozen modification types, connecting them to core signaling pathways and downstream effectors, and tracing their consequences across cancer types, Liu and colleagues provide a reference framework for a field that has grown faster than its unifying concepts. The work was supported by the National Natural Science Foundation of China and Chongqing regional science funds, and the authors acknowledge the use of an AI-assisted language tool for polishing while taking full responsibility for the scientific content. As sequencing technologies mature and first-generation epitranscriptomic drugs advance through trials, the picture that emerges is of cancer’s deadliest behaviors being orchestrated, in significant part, by chemistry that most textbooks treated as trivia barely two decades ago. The review suggests that learning to read, and eventually to rewrite, that chemistry may become a central task of precision oncology.

Subject of Research: The role of RNA modifications in tumor metastasis and therapy resistance

Article Title: Exploring the role of RNA modifications in tumor metastasis and therapy resistance: molecular mechanisms and clinical implications

Article References: Exploring the role of RNA modifications in tumor metastasis and therapy resistance: molecular mechanisms and clinical implications. (n.d.). https://doi.org/10.1186/s12943-026-02788-2

Image Credits: AI Generated

DOI: 10.1186/s12943-026-02788-2

Keywords: RNA modifications, m6A, epitranscriptomics, tumor metastasis, therapy resistance, METTL3, FTO, cancer stem cells, tumor microenvironment, EMT, biomarkers, precision oncology