Background:Celecoxib is widely used in the prevention and treatment of colorectal cancer (CRC). Although its mechanism of action involves both cyclooxygenase-2 (COX-2)-dependent and COX-2-independent pathways, the non-COX-2 targets of celecoxib remain poorly understood. Preliminary experiments revealed that celecoxib can inhibit the expression of the propionyl-CoA carboxylase alpha chain (PCCA); hence, this study aimed to investigate the role and underlying mechanisms of PCCA as a non-COX-2 target of celecoxib. Methods:Wound-healing, transwell, and Cell Counting Kit-8 assays were conducted to evaluate the effects of celecoxib on migration, invasion, and proliferation in PCCA-overexpressing CRC cell lines. Western blotting was performed to assess the expression of epithelial-mesenchymal transition (EMT) markers. In vivo tumor growth and angiogenesis were examined by using mouse models. Quantitative polymerase chain reaction was used to analyse the transcriptional levels of placental growth factor (PLGF). Results:Celecoxib inhibited PCCA expression in CRC and suppressed PCCA-mediated migration, invasion, and proliferation in COX-2-deficient CRC cell lines (HCT116 and DLD1). These effects were associated with the reversal of PCCA-induced downregulation of E-cadherin and upregulation of N-cadherin and vimentin. In addition, celecoxib inhibited PCCA-driven tumor growth and angiogenesis in HCT116 cells, which correlated with altered PLGF expression. Conclusion:Celecoxib suppresses PCCA-induced EMT and angiogenesis via a COX-2-independent mechanism. These findings suggest that celecoxib may offer additional therapeutic benefits for patients with CRC with elevated PCCA expression and reveal a novel potential antitumor mechanism of celecoxib.

Fusion genes, arising from aberrant genomic rearrangements, represent critical oncogenic drivers with distinct oncogenic functions. Although relatively uncommon in breast cancer, accumulating evidence suggests that fusion genes contribute to tumor initiation, progression, and therapeutic resistance. This review first summarizes the molecular mechanisms underlying fusion gene formation, their frequency and subtype distribution, and advances in detection technologies in breast cancer. We then discuss how fusion genes reprogram oncogenic signaling pathways and mediate resistance to conventional and targeted therapies. Finally, we evaluate their translational potential as diagnostic biomarkers and therapeutic targets, emphasizing opportunities for precision oncology. By integrating current insights, this review underscores the multifaceted roles of fusion genes in breast cancer biology and highlights their promise for guiding the development of more effective, personalized treatment strategies.

Angiogenesis is a hallmark of cancer. However, the efficacy of antiangiogenic therapy is hindered by drug resistance. The underlying mechanisms are complex and multifactorial, and the practical strategies to overcome resistance remain limited. By establishing single cell clones (SCCs) from EO771 breast tumor cell line, we classified SCCs as resistant and sensitive to Anlotinib, a new antiangiogenic agent. Resistant and sensitive SCCs were then mixed in different ways to uncover novel mechanisms of antiangiogenic resistance by integrating orthotopic tumor models, RNA sequencing (RNA-seq), immunohistochemistry, blocking antibodies, and recombinant proteins. Increasing the diversity and quantity of sensitive SCCs overcame the influences of resistant SCCs and improved Anlotinib efficacy. Sensitive SCC tumors exhibited a more normalized vasculature and increased intratumoral CD8+ T cells compared to resistant SCC tumors. Moreover, elevated vessel perfusion was significantly correlated with better Anlotinib efficacy. RNA-seq data revealed upregulation of dual-function genes (e.g., Ifng, Cxcl9, and Vcam1) linking angiostasis and immune activation. Strikingly, the addition of an angiostatic factor (e.g., recombinant murine IFN-γ or Endostar) converted resistant breast tumors to sensitive to Anlotinib treatment and induced vascular normalization, whereas neutralizing IFNγ, a key angiostatic factor in sensitive SCC tumors, impeded their responses to Anlotinib. The downregulation of angiostatic factors promotes breast tumor vascular abnormalization and resistance to antiangiogenic therapy. Therefore, integrating angiostatic factors with pro-angiogenic blockers may overcome resistance, offering a translatable approach to improve antiangiogenic outcomes in breast cancer.

Background: The progression and metastasis of colorectal cancer (CRC) remain major clinical challenges due to a lack of effective therapeutic targets. Our preliminary study identified the upregulation of the propionyl-CoA carboxylase alpha chain (PCCA) gene in CRC, prompting further investigation into its functional roles. Methods: Bioinformatics analysis, colorectal tumor tissues, and CRC cell lines were used to determine PCCA expression. Wound healing, Transwell, and cell counting kit-8 (CCK-8) assays were conducted to evaluate the impacts of PCCA expression on CRC cell migration, invasion, and proliferation. Western blotting was used to assess epithelial-mesenchymal transition (EMT) markers and associated signaling pathways. Mouse models, flow cytometry, and quantitative polymerase chain reaction (PCR) were performed to investigate the influences of PCCA on CRC tumor growth, lung metastasis, and macrophage polarization. Results: PCCA is highly expressed in CRC tumor tissues compared to normal tissues and is associated with a poor prognosis. Knocking down PCCA reduced CRC cell migration, invasion, and proliferation, which were associated with the upregulation of E-cadherin, the downregulation of N-cadherin, Vimentin, and Fibronectin, as well as the inactivation of the extracellular signal-regulated kinase (ERK)/glycogen synthase kinase 3 beta (GSK3I3) signaling pathway. Moreover, PCCA knockdown suppressed CRC tumor growth and lung metastasis, accompanied by an increase in M1-macrophage polarization. Conclusion: Knockdown PCCA inhibits the progression and metastasis of CRC, which is associated with EMT reversion, ERK/GSK3I3 signaling inactivation, and M1-macrophage polarization. These findings suggest that PCCA is a potential target for controlling CRC.

Background:Although immune checkpoint inhibitors (ICIs) have shown durable clinical benefits in a subset of patients with non-small cell lung cancer (NSCLC), robust biomarkers for predicting treatment response and guiding individualized immunotherapy remain lacking. Current prognostic models based on programmed death-ligand 1 (PD-L1) expression and clinical factors are insufficient for precise risk stratification. The aim of this study was to develop and validate a multi-institutional habitat imaging-based model to predict clinical outcomes of first-line immunotherapy in advanced NSCLC. Methods:This retrospective multi-cohort study included a discovery cohort of 128 stage IIIB-IV NSCLC patients treated with anti-PD-(L)1 combination therapy from the ORIENT-11 trial, and two external validation cohorts consisting of 60 and 32 real‑world patients, respectively. Progression-free survival (PFS) was used as the primary outcome. For each patient, arterial‑phase contrast-enhanced computed tomography (CECT) images were processed using a habitat analysis approach to segment intratumoral subregions, extract radiomic features, and construct machine learning models. The predictive value of habitat imaging alone and in combination with PD-L1 tumor proportion score (TPS) and clinical factors was evaluated using the area under the receiver operating characteristic curve (AUC). Results:Across the three cohorts, the mean age ranged from 59.8±9.1 to 62.4±9.7 years, with a predominance of male patients (77-92%), stage IV disease, and adenocarcinoma histology; the distribution of PD-L1 TPS was comparable among cohorts. Patients with high and low risk of disease progression showed significantly different proportions of specific intratumoral habitat clusters. Using intratumoral habitat imaging alone, the model achieved an AUC of 0.758 in predicting response to anti-PD-(L)1 combination therapy. When integrating habitat imaging with PD-L1 TPS and clinical metrics, the AUC reached 0.869. Furthermore, Kaplan-Meier survival analysis for PFS showed a statistically significant difference for grouping based on TPS ≥50% (P=0.03) and for grouping based on intratumoral habitat imaging (P=0.007). Conclusions:Habitat imaging is a potential valuable approach for predicting ICI efficacy in NSCLC patients. While this approach stratifies patients into distinct prognostic groups, its clinical utility requires further validation in larger prospective, multi center studies, inclusion of lymph node and metastatic lesions, and assessment across different histological subtypes.

OBJECTIVE:To explore the construction method of a resistant multiple myeloma (MM) patient-derived xenotransplantation (PDX) model. METHODS:1.0×107 MM patient-derived mononuclear cells (MNCs), 2.0×106 MM.1S cells and 2.0×106 NCI-H929 cells were respectively subcutaneously inoculated into NOD.CB17-Prkdcscid Il2rgtm1/Bcgen (B-NDG) mice with a volume of 100 μl per mouse to establish mouse model. The morphologic, phenotypic, proliferative and genetic characteristics of PDX tumor were studied by hematoxylin-eosin staining, immunohistochemical staining (IHC), cell cycle analysis, flow cytometry and fluorescence in situ hybridization (FISH). The sensitivity of PDX tumor to bortezomib and anlotinib monotherapy or in combination was investigated through cell proliferation, apoptosis and in vitro and in vivo experiments. The effects of anlotinib therapy on tumor blood vessel and cell apoptosis were analyzed by IHC, TUNEL staining and confocal fluorescence microscope. RESULTS:MM PDX model was successfully established by subcutaneously inoculating primary MNCs. The morphologic features of tumor cells from MM PDX model were similar to those of mature plasma cells. MM PDX tumor cells positively expressed CD138 and CD38, which presented 1q21 amplification, deletion of Rb1 and IgH rearrangement, and had a lower proliferative activity than MM cell lines. in vitro, PDX, MM.1S and NCI-H929 cells were treated by bortezomib and anlotinib for 24 hours, respectively. Cell viability assay showed that the IC50 value of bortezomib were 5 716.486, 1.025 and 2.775 nmol/L, and IC50 value of anlotinib were 5 5107.337, 0.706 and 5.13 μmol/L, respectively. Anlotinib treatment increased the apoptosis of MM.1S cells (P < 0.01), but did not affect PDX tumor cells (P >0.05). in vivo, there was no significant difference in PDX tumor growth between bortezomib monotherapy group and control group (P >0.05), while both anlotinib monotherapy and anlotinib combined with bortezomib effectively inhibited PDX tumor growth (both P < 0.05). The vascular perfusion and vascular density of PDX tumor were decreased in anlotinib treatment group (both P < 0.01). The apoptotic cells in anlotinib treatment group were increased compared with those in control group (P < 0.05). CONCLUSION:Bortezomib-resistant MM PDX model can be successfully established by subcutaneous inoculation of MNCs from MM patients in B-NDG mice. This PDX model, which retains the basic biological characteristics of MM cells, can be used to study the novel therapies.

Radiation therapy (RT) plays important roles in cancer treatment, and the efficacy of RT depends on the abscopal effect, which results in the regression of distant and untreated tumors through localized irradiation of a single tumor lesion. This effect is mediated by effector tumor antigen-specific T cells (ETASTs) activated by RT. Monitoring the radiation-induced changes in ETASTs can be used to predict the abscopal effect. However, no precise and sensitive methods have been developed due to significant challenges. This is challenging because tumor antigens are highly heterogeneous, and thus, ETASTs are polyclonal and highly diverse. No structural differences exist between ETASTs and other T cells. Therefore, it is difficult to detect ETASTs in whole T cells. To overcome these limitations, we developed T cell-activating whole tumor-antigen-loaded nanoparticles (TATAN) to dynamically monitor RT-induced ETASTs. Tumor antigens in TATAN can specifically activate ETASTs in vitro during coincubation. Thus, the differences between ETASTs and other T cells are transformed into activated and nonactivated states. By measuring markers of the activated status and cytotoxic function of ETASTs, we can distinguish ETASTs from other T cells. In both breast cancer and lung cancer models, RT significantly enhanced the amount of ETASTs in the abscopal effect group in both tumor-draining lymph nodes (TDLNs) and splenocytes. Bulk RNA sequencing confirmed these results. This study establishes a new efficient biomarker for predicting the abscopal effect after RT. These findings potentially can be used to optimize RT strategies and understand the mechanisms underlying the abscopal effect.

Immune checkpoint blockade (ICB) therapy only induces durable responses in a subset of cancer patients. The underlying mechanisms of such selective efficacy remain largely unknown. By analyzing the expression profiles of immune checkpoint molecules in different statuses of murine tumors, we found that tumor progression generally randomly upregulated multiple immune checkpoints, thus increased the Heterogeneity of Immune checkpoint Signature (HIS) and resulted in immunotherapeutic resistance. Interestingly, overexpressing one pivotal immune checkpoint in a tumor hindered the upregulation of a majority of other immune checkpoint genes during tumor progression via suppressing interferon γ, resulting in HIS-low. Indeed, PD-L1 high-expression sensitized baseline large tumors to anti-PD1 therapy without altering the sensitivity of baseline small tumors. In line with these preclinical results, a retrospective analysis of a phase III study involving patients with non-small cell lung cancer (NSCLC) revealed that PD-L1 tumor proportion score (TPS) ≥ 50% more reliably predicted therapeutic response in NSCLC patients with baseline tumor volume (BTV)-large compared to patients with BTV-small. Notably, TPS combined with BTV significantly improved the predictive accuracy. Collectively, the data suggest that HIS reflects the dynamic features of tumor immune evasion and dictates the selective efficacy of ICB in a tumor size-dependent manner, providing a potential novel strategy to improve precision ICB. These findings highlight the application of ICB to earlier stages of cancer patients. The integration of PD-L1 with BTV may immediately improve patient stratification and prediction performance in the clinic.

Combined hepatocellular carcinoma-cholangiocarcinoma (HCC-CCA) is a rare liver tumor comprising histologic features of both HCC and CCA. Due to its heterogeneous nature, treatment of combined HCC-CCA is a significant clinical challenge and prognosis remains poor. Therefore, further understanding of the tumor biology underlying the individual subtypes of this mixed tumor is required to improve treatment stratification and optimize treatment strategies. This study sought to identify altered epigenetic regulation and gene expression patterns in the individual components of combined HCC-CCA. Formalin fixed paraffin embedded (FFPE) tumor specimens from 9 patients diagnosed with combined HCC-CCA were utilized in this study. Hematoxylin and eosin (H&E) staining was performed for each sample, and regions representative of the individual HCC and CCA components were delineated. Adjacent unstained slides were cut and dissected to separate HCC and CCA components. DNA and RNA extraction was performed for each sample for DNA methylation (n = 7 HCC and 7 CCA) and gene expression (n = 7 HCC and 8 CCA) profiling via reduced representation bisulfite sequencing (RRBS) and RNA-seq, respectively. Samples did not cluster by tumor type when comparing genome-wide DNA methylation or gene expression patterns. Of the 5 patients with DNA methylation data available for both subtypes, 4 clustered by patient as opposed to cancer subtype, suggesting similar epigenetic regulatory patterns arising from development in the same microenvironment and genetic background. Differential analysis resulted in the identification of 57 differentially expressed genes (DEGs) and 808 differentially methylated regions (DMRs) between the HCC and CCA subtypes. Genes associated with DMRs were associated with Wnt signaling, voltage-gated channels, metal binding, and cellular regulation. Finally, increased expression of several genes previously implicated in tumor aggressiveness, prognosis, and treatment responses were identified. These results highlight the potential importance of accounting for underlying HCC and CCA tumor biology when determining the optimal course of treatment for this deadly disease.

Background and purpose Bone metastasis is common for breast cancer and associated with poor prognosis. Currently, radiotherapy (RT) serves as the standard treatment for patients exhibiting symptoms of bone metastasis to alleviate pain. Whether earlier application of RT will better control bone metastasis remains unclear.Methods We utilized a mouse model of breast cancer bone metastasis by intra-femoral injection of 4T1-luc breast tumor cells. The bone metastasis was treated by RT using various doses, timings, and modalities. Tumor growth was assessed through bioluminescence imaging, and lung metastases was quantified following lung tissue fixation. Flow cytometry was employed to analyze alterations in immune cell populations.Results Single high-dose RT suppressed tumor growth of bone metastases, but caused severe side effects. Conversely, fractionated RT mitigated tumor growth in bone metastases with fewer adverse effects. Fractioned RT initiated at the early stage of bone metastasis effectively inhibited tumor growth in the bone, suppressed secondary lung metastases, and prolonged mouse survival. In line with the known pro- and anti-metastatic effects of neutrophils and T cells in breast cancer, respectively, earlier fractioned RT consistently decreased the proportions of neutrophils while increased the proportions of T cells in both the bone and the lung tissues.Conclusion The data suggest that fractionated RT can inhibit the progression of early stage of bone metastasis and reduce secondary lung metastasis, leading to favorable outcomes. Therefore, these findings provide preclinical evidence to support the application of fractionated RT to treat patients with bone metastasis as earlier as possible.

Objective Current biomarkers for predicting immunotherapy response in non-small-cell lung cancer (NSCLC) are derived from invasive procedures with limited predictive accuracy. Thus, identifying a non-invasive predictive biomarker would improve patient stratification and precision immunotherapy.Methods and analysis In this retrospective multicohort study, the discovery cohort included 205 NSCLC patients screened from ORIENT-11 and an external validation (EV) cohort included 99 real-world NSCLC patients. The ‘onion-mode segmentation’ method was developed to extract ‘onion-mode perfusion’ (OMP) from contrast-enhanced CT images. The predictive performance of OMP or its combination with the PD-L1 Tumour Proportion Score (TPS) was evaluated by the area under the curve (AUC).Results High baseline OMP was associated with significantly longer survival and predicted patient response to combination anti-PD-(L)1 therapy in the discovery and EV cohorts. OMP complemented the PD-L1 TPS with superior predictive sensitivity (p=0.02). In the PD-L1 TPS<50% subgroup, OMP achieved an AUC of 0.77 for the estimation of treatment response (95% CI 0.66 to 0.86, p<0.0001). A simple bivariate model of OMP/PD-L1 robustly predicted therapeutic response in both the discovery (AUC 0.82, 95% CI 0.74 to 0.88, p<0.0001) and EV (AUC 0.80, 95% CI 0.67 to 0.89, p<0.0001) cohorts.Conclusion OMP, derived from routine CT examination, could serve as a non-invasive and cost-effective biomarker to predict NSCLC patient response to immune checkpoint inhibitor-based therapy. OMP could be used alone or in combination with other biomarkers to improve precision immunotherapy.

PurposeTo correlate epigenetic patterns to ethnoracial status and locoregional therapy (LRT) response in patients with hepatocellular carcinoma (HCC).Materials and MethodsDeoxyribo- (DNA) and ribonucleic acid (RNA) were extracted from 47 distinct formalin-fixed paraffin-embedded tumor samples from 42 HCC patients (n=14 Black, n=19 White, n=9 Hispanic). LRT response was determined using computed tomography or magnetic resonance imaging 3 months post-treatment of 35 tumors (n=22 complete response, n=13 retreatment candidates). RNA expression and DNA methylation were used to stratify patients by ethnoracial status and treatment response using partial least-squares discriminant analysis (PLS-DA). Results were validated using hierarchical clustering. Ingenuity pathway analysis was performed to identify upstream regulators and pathways.ResultsPLS-DA identified 100 genes and 12 methylated regions that differentiated tumors from Black from White/Hispanic patients. Hierarchical clustering clustered samples with the top 16 genes or the top 5 methylation regions. Dysregulated pathways included adrenomedullin pathway(p = 0.0302), EIF2 signaling(p=0.00724), and several metabolic pathways. AGTR1(log2fold = 1.59) and GSTM3(log2fold = 2.53) represented potential differentially expressed therapeutic targets. PLS-DA identified 100 genes and 150 methylation regions that differentiated between complete responders and retreatment candidates. Hierarchical clustering clustered samples with the top 30 genes or the top 13 methylation regions. Dysregulated pathways included metabolic and DNA repair-related pathways. ASAP2(log2fold = 0.29) and RAD50(log2fold = 0.22) represented potential differentially expressed therapeutic targets.ConclusionVariation in gene expression and DNA methylation patterns in HCC patients corresponded to ethnoracial status and LRT response. These initial results suggest tumor profiling has the potential to close ethnoracial disparities and improve treatment stratification.

RATIONALE AND OBJECTIVES:Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of non-small cell lung cancer (NSCLC) and programmed cell death-ligand 1 (PD-L1) is a companion biomarker. This study aims to use baseline arterial-phase enhanced CT (APECT) to construct efficient radiomic models for predicting PD-L1 expression and immunotherapy prognosis in NSCLC. MATERIALS AND METHODS:We extracted radiomics features from the baseline APECT images of 204 patients enrolled in a published multicenter clinical trial that commenced on August 23, 2018, and concluded on November 15, 2019 (ClinicalTrials.gov: NCT03607539). Of these patients, 146 patients from selected centers were assigned to the training cohort. The least absolute shrinkage and selection operator (LASSO) method was used to reduce dimensionality of radiomics features and calculate tumor scores. Models were created using naive bayes, decision trees, XGBoost, and random forest algorithms according to tumor scores. These models were then validated in an independent validation cohort comprising 58 patients from the remaining centers. RESULTS:The random forest algorithm outperformed the other methods. In the three-classification scenario, the random forest model achieving the area under the curve (AUC) values of 0.98 and 0.94 in the training and validation cohorts, respectively. In the two-classification scenario, the random forest model achieved AUCs of 0.99 (95%CI: 0.97-1.0, P < 0.0001) and 0.93 (95%CI: 0.83-0.98, P < 0.0001) in the training and validation cohorts, respectively. Furthermore, patients classified as PD-L1 high-expression by this model can predict treatment response (AUC=0.859, 95%CI: 0.7-0.96, P < 0.001) and improved survival (HR=0.2, 95%CI: 0.08-0.53, P = 0.001) only in validation sintilimab arm. CONCLUSION:Radiomics models based on APECT represent a potential non-invasive approach to robustly predict PD-L1 expression and ICI treatment outcomes in patients with NSCLC, which could significantly improve precision cancer immunotherapy.

Anti-PD-L1 therapy exhibits durable efficacy, but only in a small fraction of cancer patients. The immunosuppressive tumor microenvironment (TME) is a crucial obstacle that impedes cancer immunotherapy. Here, we found that anti-PD-L1 therapy coupled with CD4+ T cell depletion induced colorectal tumor regression and vascular normalization, while monotherapy only retarded tumor growth without affecting the tumor vasculature. Moreover, simultaneous PD-L1 blockade and CD4+ T cell depletion eradicated intratumoral PD-L1+ lymphoid and myeloid cell populations, while additively elevating the proportions of CD44+CD69+CD8+, central memory CD44+CD62L+CD8+, and effector memory CD44+CD62L-CD8+ T cells, suggesting a reduction in immunosuppressive cell populations and the activation of CD8+ T cells in the TME. Moreover, anti-PD-L1 therapy reduced the proportions of intratumoral PD-L1+ immune cells and suppressed tumor growth in a CD8+ T cell dependent manner. Together, these results suggest that anti-PD-L1 therapy induces tumor vascular normalization and colorectal tumor regression via CD8+ T cells, which is antagonized by CD4+ T cells. Our findings unveil the positive correlation of tumor regression and vascular normalization in colorectal tumor models upon anti-PD-L1 therapy, providing a potential new strategy to improve its efficacy.

Supplementary Tables S1-S2.

Supplementary Tables S1 - S6. Supplementary Table S1. CT values for demosplasia-related genes in PAN02 tumors. Data obtained from PCR array. Supplementary Table S2. CT values for demosplasia-related genes in AK4.4 tumors. Data obtained from PCR array. Supplementary Table S3. Univariate analysis of prognostic factors for resected pancreatic cancer patients with body mass index (BMI) {less than or equal to}25. Supplementary Table S4. Multivariate analysis of prognostic factors for resected pancreatic cancer patients with body mass index (BMI) {less than or equal to}25. Supplementary Table S5. Univariate analysis of prognostic factors for resected pancreatic cancer patients with body mass index (BMI) >25. Supplementary Table S6. Multivariate analysis of prognostic factors for resected pancreatic cancer patients with body mass index (BMI) >25.

Background: Dexmedetomidine is a widely used anaesthetic adjuvant for cancer resection surgeries. However, recent reports suggest that it may promote tumour growth or metastasis, so it is essential to clarify its tumour-related effects.Methods: Seven syngeneic murine tumour models were used to assess the impact of dexmedetomidine on primary tumour growth, spontaneous tumour metastasis, and surgical resection-associated metastasis. Cancer cell proliferation and apoptosis experiments, terminal deoxynucleotidyl transferase dUTP nick-end labelling assays, immune cell analysis, specific T-cell depletion experiments, and gene transcription analysis were conducted to identify the underlying mechanisms.Results: Dexmedetomidine did not affect growth of EO771 or 4T1 breast tumours, LAP0297 or LLC lung tumours, MCA205 fibrosarcoma, or their spontaneous lung metastases. It did not promote lung metastasis after breast cancer resection. Dexmedetomidine significantly suppressed MCA38 and CT26 colorectal tumour growth (P<0.01) and promoted apoptosis in MCA38 tumour tissues (P<0.05) without affecting proliferation and apoptosis of MCA38 tumour cells in vitro, suggesting indirect anti-tumour effects. Dexmedetomidine increased the proportions of intratumour CD4+ T (P<0.01), CD8+ T (P<0.001), and natural killer cells (P<0.01), and it upregulated transcription of the cytotoxicity-related genes Infg, Tnfa, and Cxcl9 (P<0.05) in MCA38 tumours. Either CD8+ or CD4+ T-cell depletion reversed the anti-tumour effects of dexmede-tomidine on MCA38 tumours (P<0.05).Conclusions: Dexmedetomidine conferred colorectal tumour-type specific suppression by modulation of tumour CD4+ and CD8+ T cells without tumour-enhancing effects.