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Translational Cancer Research logoLink to Translational Cancer Research
. 2026 Aug 14;15(9):702. doi: 10.21037/tcr-2026-1409

Telmisartan enhances anti-PD-1 efficacy in MSS colorectal cancer via modulation of PD-L1 and STAT3 signaling

Xin Lin 1, Jingying Li 2, Wei Lin 3,✉
PMCID: PMC13657849  PMID: 42870843

Abstract

Background

Microsatellite stable (MSS) colorectal cancer (CRC), accounting for over 85% of advanced cases, shows intrinsic resistance to immune checkpoint inhibitors due to an immunosuppressive tumor microenvironment. The renin-angiotensin system (RAS), particularly angiotensin II type 1 receptor (AT1R), has been implicated in tumor progression and immune evasion. This study investigated whether telmisartan, a selective AT1R antagonist, modulates programmed death-ligand 1 (PD-L1) expression and enhances anti-tumor immunity in MSS CRC.

Methods

Mismatch repair (MMR) protein expression was characterized in human (SW480, HT29, HCT116) and murine (CT26) CRC cell lines. The effects of telmisartan on cell viability, PD-L1 expression, STAT3 signaling, and migration were evaluated using Cell Counting Kit-8 (CCK-8), Western blotting, and Transwell assays. A CT26 tumor model in BALB/c mice was used to assess therapeutic efficacy alone or combined with pembrolizumab, with immunohistochemical analysis of tumor-infiltrating lymphocytes. Public transcriptomic analysis of The Cancer Genome Atlas (TCGA) CRC data and immune infiltration analysis using the CIBERSORT (Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts) algorithm were further performed.

Results

Telmisartan (10–20 μM) reduced PD-L1 expression in both MSS and MSI-H CRC cell lines without significant cytotoxicity. It was associated with increased signal transducer and activator of transcription 3 (STAT3) phosphorylation and reduced cell migration. In vivo, telmisartan inhibited tumor growth, while the combination with pembrolizumab resulted in enhanced antitumor efficacy. These effects were accompanied by increased infiltration of CD3⁺, CD4⁺, and CD8⁺ T cells. Transcriptomic analysis demonstrated positive correlations among AGTR1, STAT3, and CD274 expression, while CIBERSORT analysis revealed AGTR1-associated alterations in immune cell infiltration.

Conclusions

Telmisartan may remodel the tumor immune microenvironment, potentially through modulation of PD-L1 expression associated with STAT3 signaling, thereby enhancing the response of MSS CRC to immune checkpoint blockade. These findings suggest that telmisartan could serve as a potential immunotherapy adjuvant for MSS CRC.

Keywords: Telmisartan, microsatellite stable colorectal cancer (MSS CRC), programmed death-ligand 1 (PD-L1), tumor immune microenvironment, signal transducer and activator of transcription 3 signaling (STAT3 signaling)


Highlight box.

Key findings

• Telmisartan reduced programmed death-ligand 1 (PD-L1) expression and inhibited colorectal cancer cell migration. In a microsatellite stable (MSS) colorectal cancer mouse model, telmisartan enhanced intratumoral T-cell infiltration and significantly improved the antitumor efficacy of anti-PD-1 therapy. These effects were associated with increased signal transducer and activator of transcription 3 (STAT3) phosphorylation and remodeling of the tumor immune microenvironment.

What is known and what is new?

• Immune checkpoint inhibitors are effective in deficient mismatch repair (dMMR)/high microsatellite instability (MSI-H) colorectal cancer but have limited efficacy in MSS colorectal cancer because of its immunologically “cold” tumor microenvironment. Previous studies have shown that the renin-angiotensin system contributes to tumor progression, metastasis, and immune regulation, and angiotensin receptor blockers may have anti-tumor potential.

• This study demonstrates that telmisartan downregulates PD-L1 expression, inhibits colorectal cancer cell migration, promotes intratumoral CD3+, CD4+, and CD8+ T-cell infiltration, and enhances the efficacy of anti-PD-1 therapy in MSS colorectal cancer. Furthermore, telmisartan-induced PD-L1 downregulation was associated with increased STAT3 phosphorylation, suggesting a potential novel immunomodulatory mechanism.

• Public transcriptomic analyses further supported the association between the angiotensin II type 1 receptor (AT1R)-STAT3-PD-L1 axis and alterations in the colorectal cancer immune microenvironment.

What is the implication, and what should change now?

• MSS colorectal cancer accounts for the majority of advanced colorectal cancer cases and remains largely resistant to current immunotherapy strategies. As a widely used and well-tolerated antihypertensive drug, telmisartan may represent a practical and cost-effective approach for improving immunotherapy responsiveness in MSS colorectal cancer. Further mechanistic studies and prospective clinical trials are warranted to validate its role as an immunotherapy adjuvant.

Introduction

Background

Colorectal cancer (CRC) ranks third in cancer incidence and second in mortality globally, with approximately 1.93 million new cases and 940,000 deaths reported in 2022 (1). Despite advances in systemic therapies, advanced CRC remains challenging to treat, particularly given the limited efficacy of conventional chemotherapy and targeted agents such as cetuximab and bevacizumab, which primarily serve as chemotherapy adjuncts rather than curative options (2).

Immune checkpoint inhibitors (ICIs) targeting the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis have revolutionized cancer treatment. However, their efficacy in CRC is largely restricted to tumors with deficient mismatch repair (dMMR) or high microsatellite instability (MSI-H), which account for only 10–15% of advanced CRC cases, with even lower proportions (5.5–7.3%) observed in Asian populations (3,4). The CheckMate-142 trial demonstrated an objective response rate of approximately 40% in dMMR/MSI-H CRC patients receiving nivolumab, whereas proficient mismatch repair (pMMR)/microsatellite stable (MSS) tumors showed virtually no response (5). This resistance is attributed to the immunologically “cold” tumor microenvironment (TME) of MSS CRC, characterized by low tumor mutational burden, limited neoantigen presentation, and poor T-cell infiltration (6).

Rationale and knowledge gap

Accumulating evidence suggests that the renin-angiotensin system (RAS), beyond its classical cardiovascular functions, plays important roles in tumor biology. The RAS comprises angiotensinogen, renin, angiotensin-converting enzyme (ACE), and angiotensin II (Ang II), which exerts biological effects primarily through angiotensin II type 1 receptor (AT1R) and type 2 receptor (AT2R) (7). Notably, AT1R is overexpressed in various solid tumors, including colorectal, hepatocellular, gastric, bladder, and lung cancers, where it promotes tumor angiogenesis, cell proliferation, and metastasis (8,9).

In CRC specifically, multiple lines of evidence support the oncogenic role of AT1R signaling. Clinical studies have demonstrated that AT1R expression in colorectal adenocarcinoma tissues is significantly higher than in adjacent normal mucosa, with expression levels inversely correlated with tumor differentiation grade (10). Furthermore, ACE mRNA expression is elevated in poorly differentiated and metastatic CRC compared with well-differentiated, non-metastatic tumors (11). Mechanistically, Ang II stimulates matrix metalloproteinase (MMP-2, MMP-9) expression through AT1R activation, promoting tumor invasion and metastasis (12).

Beyond direct tumor-promoting effects, emerging evidence indicates that RAS components modulate anti-tumor immunity. The JAK2/STAT3 pathway represents a critical signaling node downstream of AT1R activation (13). Importantly, recent studies have revealed that STAT3 can function as both a transcriptional activator and repressor depending on the cellular context and target gene promoter architecture (14,15). While STAT3 activation typically promotes PD-L1 expression in many cancer types, emerging evidence suggests that enhanced STAT3 phosphorylation under certain conditions may negatively regulate PD-L1 transcription through binding to inhibitory regulatory elements (16).

RAS inhibitors, including angiotensin receptor blockers (ARBs), have demonstrated potential to reprogram the TME. A landmark phase II clinical trial showed that combining losartan with FOLFIRINOX in locally advanced pancreatic cancer converted immunologically “cold” tumors to “hot” tumors, significantly improving R0 resection rates (17). Recent mechanistic studies revealed that ARBs suppress RhoA-YAP signaling in cancer-associated fibroblasts (CAFs), reducing type I collagen deposition and facilitating T-cell infiltration (18,19).

Epidemiological observations further support the anti-tumor potential of RAS inhibitors. Long-term captopril use has been associated with reduced prostate cancer risk (20), and a prospective cohort study following 7,679 individuals demonstrated that RAS inhibitor use was associated with decreased breast cancer incidence (21). Retrospective analyses have shown that patients treated with ACE inhibitors have lower rates of advanced gastrointestinal malignancies (11).

Telmisartan, with its prolonged half-life, high AT1R affinity, and selective receptor blockade, represents an ideal candidate for investigating RAS-mediated anti-tumor effects (22). However, whether telmisartan can modulate PD-L1 expression and enhance immunotherapy efficacy in MSS CRC remains unexplored. To further evaluate the clinical relevance of the proposed mechanism, transcriptomic and immune infiltration analyses based on public CRC datasets were also performed.

Objective

This study aimed to investigate the effects of telmisartan on PD-L1 expression, cellular migration, and the potential involvement of STAT3-associated signaling in CRC cells, and to evaluate its therapeutic potential alone or in combination with anti-PD-1 therapy in an MSS CRC mouse model. We present this article in accordance with the ARRIVE and MDAR reporting checklists (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1409/rc).

Methods

Cell lines and culture conditions

Human CRC cell lines SW480 (pMMR/MSS), HT29 (dMMR/MSI-H), and HCT116 (dMMR/MSI-H) were obtained from the American Type Culture Collection (ATCC). The murine CRC cell line CT26 (pMMR/MSS, syngeneic to BALB/c mice) was purchased from the Cell Bank of the Chinese Academy of Sciences. All cell lines were authenticated by short tandem repeat (STR) profiling and confirmed to be mycoplasma-free. Cells were cultured in RPMI-1640 medium (Gibco) supplemented with 10% fetal bovine serum (FBS, Gibco) and 1% penicillin-streptomycin at 37 ℃ in a humidified atmosphere containing 5% CO₂. The mismatch repair (MMR) status of the CRC cell lines used in this study was characterized before functional experiments. SW480 and CT26 cells were classified as pMMR/MSS models, whereas HT29 and HCT116 cells were classified as dMMR/microsatellite instability-high (MSI-H) models based on the expression status of the major MMR proteins (MLH1, MSH2, MSH6, and PMS2).

Characterization of MMR status by Western blotting

To classify cell lines as MSS or MSI-H, total protein was extracted using RIPA lysis buffer containing protease and phosphatase inhibitors. Protein concentrations were determined using the BCA Protein Assay Kit (Thermo Fisher Scientific). Equal amounts of protein (30 μg per lane) were separated by 10% SDS-PAGE and transferred onto PVDF membranes (Millipore). Membranes were blocked with 5% non-fat milk and incubated overnight at 4 ℃ with primary antibodies against MLH1 (1:1,000, ab92312, Abcam), MSH2 (1:2,000, ab227941, Abcam), MSH6 (1:1,000, ab92471, Abcam), and PMS2 (1:1,000, ab110638, Abcam). Following incubation with HRP-conjugated secondary antibodies (1:5,000, Cell Signaling Technology), protein bands were visualized using enhanced chemiluminescence (ECL) and quantified using ImageJ software. According to established clinical criteria, loss of one or more MMR proteins indicates dMMR/MSI-H status, whereas intact expression of all four proteins indicates pMMR/MSS status (23).

Cell viability assay

Cytotoxic effects of telmisartan (Sigma-Aldrich) were assessed using the Cell Counting Kit-8 (CCK-8, Dojindo Laboratories) according to the manufacturer’s protocol. Cells were seeded in 96-well plates at a density of 5,000 cells per well in 100 μL complete medium and allowed to adhere overnight. The medium was then replaced with fresh medium containing various concentrations of telmisartan (0, 10, 20, 30, and 50 μM). After 24 hours of treatment, the medium was removed, and cells were washed once with PBS. CCK-8 solution (10 μL per well) was added, and plates were incubated at 37 ℃ for 2 hours. Absorbance was measured at 450 nm using a microplate reader (Molecular Devices). Cell viability was calculated as a percentage relative to untreated controls. All experiments were performed in triplicate.

Western blot analysis of signaling pathways

Cells were treated with telmisartan (0, 10, or 20 μM) for 24 hours. Total protein was extracted and subjected to Western blotting as described above. Primary antibodies included anti-PD-L1 (1:1,000, ab213524, Abcam), anti-STAT3 (1:2,000, #9139, Cell Signaling Technology), anti-phospho-STAT3 (Tyr705) (1:1,000, #9145, Cell Signaling Technology), and anti-β-actin (1:5,000, #4970, Cell Signaling Technology). Band intensities were quantified using ImageJ and normalized to β-actin.

Transwell migration assay

Cell migration was assessed using Transwell chambers with 8-μm pore polycarbonate membranes (Corning). Cells (5×10⁴) were resuspended in 200 μL serum-free medium containing telmisartan (0, 10, or 20 μM) with or without Ang II (100 nM, Sigma-Aldrich) and seeded into the upper chamber. The lower chamber was filled with 600 μL complete medium containing 30% FBS as a chemoattractant. After 24 hours, non-migrated cells on the upper surface were removed with cotton swabs. Migrated cells on the lower surface were fixed with 4% paraformaldehyde for 15 minutes, stained with 0.1% crystal violet for 20 minutes, and counted in five random fields per membrane under a light microscope at 20× magnification.

Animal studies

All animal experiments were performed under a project license (No. IACUC-2013-012) granted by the Ethics Committee of Fujian Provincial Hospital (Fuzhou University Affiliated Provincial Hospital), in compliance with the National Institutes of Health Guide (8th edition, 2011) and relevant institutional guidelines for the care and use of animals. Male BALB/c mice (6–8 weeks old, 20–22 g) were purchased from Shanghai SLAC Laboratory Animal Co., Ltd. and housed under specific pathogen-free (SPF) conditions with ad libitum access to food and water. CT26 cells (1×10⁶ cells in 100 μL PBS) were subcutaneously injected into the right flank of each mouse. When tumors reached approximately 50–100 mm³ (day 7 post-inoculation), mice were randomly assigned to four groups (n=5 per group): (I) PBS control (100 μL, intragastric gavage daily); (II) telmisartan (10 mg/kg/day, intragastric gavage); (III) pembrolizumab (200 μg/mouse, intraperitoneal injection every 3 days); and (IV) combination therapy. Tumor dimensions were measured every 2 days using digital calipers, and tumor volume was calculated as V = 0.5 × length × width². Body weight was recorded simultaneously. Mice were euthanized on day 12 post-treatment initiation, and tumors and major organs were harvested for histological analysis (24). Mice were randomly allocated using a computer-generated random number sequence. Sample size was determined based on previous studies using CT26 syngeneic CRC models and practical considerations for exploratory preclinical experiments; no formal a priori sample size calculation was performed. No predefined exclusion criteria were applied, and no animals or experimental data were excluded from the final analysis. Animals were monitored daily for signs of distress. Humane endpoints included severe weight loss (>20%), impaired mobility, ulcerated tumors, or tumor volume exceeding institutional limits. No animals reached humane endpoints before scheduled euthanasia.

Histological and immunohistochemical analysis

Tumor tissues and major organs were fixed in 4% paraformaldehyde, paraffin-embedded, and sectioned at 4 μm thickness. Hematoxylin and eosin (H&E) staining was performed for morphological assessment. Immunohistochemistry (IHC) was conducted using primary antibodies against PD-L1 (1:200, ab213524, Abcam), p-STAT3 (1:100, #9145, Cell Signaling Technology), CD3 (1:200, ab16669, Abcam), CD4 (1:100, ab183685, Abcam), and CD8 (1:200, ab217344, Abcam). Images were captured at 20× and 320× magnification using an Olympus BX53 microscope. Positive staining was quantified using ImageJ software.

Public transcriptomic and immune infiltration analysis

To further investigate the association between AGTR1 expression and the CRC immune microenvironment, RNA sequencing data and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov), including TCGA-COAD and TCGA-READ cohorts. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Gene expression data were extracted in TPM format and normalized using the log2(TPM+1) transformation.

Tumor samples were stratified into AGTR1-high and AGTR1-low groups according to the median AGTR1 expression level. Adjacent normal tissues were retained as the normal tissue reference group.

Spearman correlation analysis was performed to evaluate the relationships among AGTR1, STAT3, and CD274 (PD-L1) expression levels. Immune cell infiltration profiles were estimated using the CIBERSORT algorithm with the LM22 signature matrix. Differences in immune cell fractions among AGTR1-high tumor tissues, AGTR1-low tumor tissues, and adjacent normal tissues were evaluated using the Kruskal-Wallis test, followed by pairwise Wilcoxon rank-sum tests with Benjamini-Hochberg correction for multiple comparisons. The FDR-adjusted P values for pairwise comparisons of all 22 immune cell subsets are provided in Table S1.

Statistical analysis

Data are presented as mean ± standard deviation (SD). Statistical analyses were performed using GraphPad Prism 9.0. Comparisons between two groups were conducted using unpaired Student’s t-test, while multiple group comparisons were analyzed using one-way ANOVA followed by Tukey’s post-hoc test. P<0.05 was considered statistically significant. Blinding was not performed in this exploratory study.

Results

Identification of MSS and MSI-H CRC cell lines and cytotoxicity of telmisartan

The MMR status of CRC cell lines was determined by Western blot analysis of four key MMR proteins (MLH1, MSH2, MSH6, and PMS2). SW480 cells retained the expression of all four MMR proteins, supporting their classification as pMMR/MSS cells (Figure 1A). In contrast, HCT116 cells exhibited loss of MLH1 and PMS2 expression, whereas HT29 cells showed reduced MSH6 expression, consistent with their dMMR/MSI-H status (Figure 1B). Similarly, the murine CRC cell line CT26 demonstrated intact expression of all four MMR proteins (Figure 1B), indicating a pMMR/MSS phenotype. These findings confirmed the successful establishment of MSS models (SW480 and CT26) and MSI-H models (HCT116 and HT29), which were subsequently used for comparative analyses in this study (25,26).

Figure 1.

Figure 1

Classification of CRC cell lines by mismatch repair protein expression and cytotoxicity assessment of telmisartan. (A) Western blot analysis of MLH1, MSH2, MSH6, and PMS2 expression in CRC cell lines. SW480 and CT26 showed intact expression of all four MMR proteins, indicating pMMR/MSS status. HCT116 showed loss of MLH1 and PMS2 expression, and HT29 showed loss of MSH6 expression, indicating dMMR/MSI-H status. (B) MMR protein expression in murine CT26 cells, showing intact expression (MSS). (C-E) Cell viability following telmisartan treatment (0–50 μM) for 24 hours in SW480 (C), HCT116 (D), and CT26 (E) cells as determined by CCK-8 assays. Data represent mean ± SD (n=5, three independent experiments). β-actin served as loading control. CCK-8, Cell Counting Kit-8; CRC, colorectal cancer; dMMR, deficient mismatch repair; DMSO, dimethyl sulfoxide; MMR, mismatch repair; MSI-H, high microsatellite instability; MSS, microsatellite stable; pMMR, proficient mismatch repair; SD, standard deviation.

The cytotoxic effects of telmisartan were evaluated using CCK-8 assays. After 24 hours of treatment, telmisartan at concentrations up to 50 μM did not significantly reduce cell viability in SW480 (Figure 1C), HCT116 (Figure 1D), or CT26 (Figure 1E) cells, with viability remaining above 80% across all tested concentrations. In addition, Transwell migration assays showed that telmisartan treatment at 10–20 μM significantly inhibited CRC cell migration (Figure 2). Therefore, the 10–20 μM concentration range was selected for subsequent mechanistic experiments. Similar micromolar concentrations have been widely adopted in previous in vitro studies investigating the anti-tumor effects of telmisartan, supporting the use of this concentration range for mechanistic investigations (27,28). The general clinical dosage of telmisartan for adults is 20–80 mg/day, and the in vitro concentrations used in this study were selected to evaluate direct cellular pharmacological effects rather than to represent plasma drug concentrations in patients.

Figure 2.

Figure 2

Telmisartan inhibits CRC cell migration and counteracts Ang II-induced effects. (A,B) Representative images (A) and quantification (B) of Transwell migration assays in SW480 (MSS) cells treated with vehicle control, telmisartan (10 or 20 μM), Ang II (100 nM), or combinations for 16 hours. (C,D) Representative images (C) and quantification (D) of migration assays in HCT116 (MSI-H) cells under identical conditions. Migrated cells were stained with crystal violet and counted in five random fields per membrane. Data represent mean ± SD from three independent experiments. Scale bar =100 μm. Ang, angiotensin; CRC, colorectal cancer; MSS, microsatellite stable; MSI-H, high microsatellite instability; SD, standard deviation.

Telmisartan is associated with reduced PD-L1 expression and increased STAT3 phosphorylation

To evaluate the effects of telmisartan on PD-L1 expression, CRC cell lines were treated with different concentrations of telmisartan. Treatment with 20 μM telmisartan markedly decreased PD-L1 protein expression in both MSS CRC cells (SW480 and CT26; Figure 3A,3B) and MSI-H CRC cells (HCT116; Figure 3C) compared with the control group.

Figure 3.

Figure 3

Telmisartan is associated with reduced PD-L1 expression and increased STAT3 phosphorylation. (A-C) Western blot analysis of PD-L1 protein expression in SW480 (MSS) (A), CT26 (MSS) (B), and HCT116 (MSI-H) (C) cells following treatment with telmisartan (0, 10, 20 μM) for 24 hours. (D) Western blot analysis of total STAT3 and phosphorylated STAT3 (p-STAT3, Tyr705) in SW480 cells treated with increasing concentrations of telmisartan (0–30 μM) for 24 hours. Densitometric quantification of p-STAT3/total STAT3 ratio is shown. β-actin served as loading control. Representative of three independent experiments. MSI-H, high microsatellite instability; MSS, microsatellite stable; PD-L1, programmed death-ligand 1; STAT3, signal transducer and activator of transcription 3.

To elucidate the underlying molecular mechanism, we assessed the STAT3 signaling pathway. As shown in Figure 3D, total STAT3 expression remained unchanged, whereas phosphorylated STAT3 (p-STAT3, Tyr705) levels were significantly increased following telmisartan treatment in a dose-dependent manner compared with controls. These findings suggest that telmisartan may modulate PD-L1 expression in association with STAT3 phosphorylation, indicating a potential negative association between p-STAT3 and PD-L1 expression in this context.

Inhibitory effects of telmisartan on CRC cell migration

The effects of telmisartan on CRC cell migration were assessed using Transwell assays. SW480 and HCT116 cells were treated with telmisartan (10 or 20 μM) alone or in combination with Ang II (100 nM). HCT116 was selected as the representative MSI-H model due to its well-characterized genetic background.

In SW480 cells, 20 μM telmisartan significantly reduced migrated cell numbers by approximately 67% compared with controls (Figure 2A,2B; P<0.01). Furthermore, compared with using Ang II alone, administering telmisartan in the presence of Ang II still reduced the number of migrating cells, particularly at a concentration of 20 μM, where it decreased by approximately 61% (Figure 2A,2B; P<0.01). Similar results were observed in HCT116 cells, where telmisartan (20 μM) reduced migration by approximately 78% (Figure 2C,2D; P<0.01). Similarly, compared with Ang II alone, telmisartan co-administered with Ang II also reduced cell migration, with a reduction of approximately 58% at 20 μM (Figure 2C,2D; P<0.01). These results demonstrate that telmisartan effectively inhibits both basal and Ang II-stimulated CRC cell migration.

Safety profile of telmisartan in mice

After 12 days of drug administration, histological examination of major organs (heart, liver, spleen, lung, and kidney) by H&E staining revealed no significant pathological changes in any treatment group compared with PBS controls (Figure 4). Representative images confirmed the absence of cardiomyocyte necrosis, hepatocyte damage, splenic abnormalities, pulmonary inflammation, or renal tubular injury. These results demonstrate that telmisartan is well-tolerated without inducing detectable systemic toxicity.

Figure 4.

Figure 4

Histopathological evaluation demonstrates absence of systemic toxicity. Representative H&E-stained sections of heart, liver, spleen, lung, and kidney from CT26 tumor-bearing mice treated with PBS, telmisartan (10 mg/kg/day), pembrolizumab (200 μg/mouse every 3 days), or combination therapy for 12 days. No treatment-related histopathological abnormalities were observed. Scale bar =100 μm (n=5 per group). H&E, hematoxylin and eosin; PBS, phosphate buffered saline.

Antitumor efficacy of telmisartan in an MSS CRC mouse model

In vivo experiments were conducted using a CT26-derived subcutaneous tumor model in male BALB/c mice. The PBS control group exhibited rapid tumor progression, with mean tumor volume reaching 1,250±25 mm³ by day 12 (Figure 5A). Pembrolizumab monotherapy showed only marginal tumor growth inhibition (1,100±27 mm³; P>0.05 vs. PBS), consistent with MSS tumor resistance to immune checkpoint blockade. In contrast, telmisartan monotherapy significantly suppressed tumor growth (750±25 mm³; P<0.01 vs. PBS), achieving approximately 40% tumor growth inhibition. Notably, the combination therapy (telmisartan + pembrolizumab) demonstrated the most pronounced anti-tumor effect (460±25 mm³; P<0.01 vs. PBS), with statistically significant reduction compared to all other groups (****P<0.001). Meanwhile, compared to telmisartan alone, the combination therapy also showed visible anti-tumor effect (P<0.05), with approximately 38.5% tumor growth inhibition.

Figure 5.

Figure 5

Telmisartan enhances pembrolizumab efficacy in MSS-CRC without systemic toxicity. (A) Tumor growth curves in BALB/c mice bearing CT26 tumors over 12 days. Tumor volume calculated as V = 0.5 × length × width². Data represent mean ± SD (n=5 per group). ****P<0.001 by two-way repeated-measures ANOVA. (B) Body weight monitoring throughout treatment, showing no significant differences among groups. Data represent mean ± SD (n=5 per group). (C) Gross morphology of excised tumors at day 12 from each treatment group: PBS, pembrolizumab, telmisartan, and combination therapy. ANOVA, analysis of variance; CRC, colorectal cancer; MSS, microsatellite stable; PBS, phosphate buffered saline; SD, standard deviation.

Body weight monitoring throughout the treatment period showed no significant differences among groups (Figure 5B; n=5 per group), indicating good treatment tolerability. Gross examination of excised tumors at day 12 confirmed visibly smaller tumor sizes in telmisartan and combination therapy groups compared with PBS and pembrolizumab controls, with the most pronounced size reduction observed in the combination therapy group (Figure 5C).

Telmisartan promotes intratumoral T-cell infiltration in vivo

H&E staining and immunofluorescence analysis were performed to assess immune cell infiltration within tumor tissues. As shown in Figure 6, increased infiltration of CD3⁺, CD4⁺, and CD8⁺ T cells was observed in tumors from mice treated with telmisartan and/or pembrolizumab compared with the PBS control group (n=5 tumors per group, five fields per tumor). Telmisartan monotherapy induced modest increases in T-cell infiltration, while pembrolizumab monotherapy showed minimal change. Combination therapy demonstrated the most substantial enhancement of intratumoral T-cell accumulation across all three T-cell markers, particularly notable for CD4⁺ and CD8⁺ populations. These findings suggest that telmisartan promotes transformation of the immunologically “cold” MSS TME into an immune-inflamed phenotype, thereby potentiating pembrolizumab efficacy.

Figure 6.

Figure 6

Telmisartan promotes intratumoral T-cell infiltration in MSS-CRC. Representative H&E staining (top row) and immunofluorescence staining of tumor sections showing CD3⁺ (second and third rows), CD4⁺ (fourth and fifth rows), and CD8⁺ (sixth and seventh rows) T-cell infiltration in CT26 tumors following treatment with PBS, telmisartan, pembrolizumab, or combination therapy. Lower-magnification overview images show regions of interest (yellow boxes labeled “Enlarge“) with corresponding high-magnification images below. T-cell markers visualized in red (Alexa Fluor 594); nuclei counterstained with DAPI (blue). Scale bars =100 μm (n=5 tumors per group, five fields per tumor). CRC, colorectal cancer; DAPI, 4',6-diamidino-2-phenylindole; H&E, hematoxylin and eosin; MSS, microsatellite stable; PBS, phosphate buffered saline.

Public transcriptomic analysis supports the association between AGTR1, STAT3, PD-L1 and immune infiltration

To further explore the clinical relevance of the proposed AT1R-STAT3-PD-L1 axis, transcriptomic data from the TCGA CRC cohort were analyzed. Significant positive correlations were observed between AGTR1 and STAT3, STAT3 and CD274, and AGTR1 and CD274, supporting the proposed signaling axis (Figure 7A). To further characterize the immune microenvironment, CIBERSORT analysis was performed by stratifying patients into AGTR1-high and AGTR1-low groups according to the median AGTR1 expression level. Compared with the AGTR1-low group, tumors with high AGTR1 expression exhibited significant differences in the infiltration of CD8⁺ T cells, CD4⁺ memory resting T cells, CD4⁺ memory activated T cells, and M2 macrophages (Figure 7B). The complete immune infiltration profiles of all 22 immune cell subsets are presented in Figure S1.

Figure 7.

Figure 7

Transcriptomic association of the AT1R-STAT3-PD-L1 axis and its relationship with immune cell infiltration in colorectal cancer. (A) Spearman correlation analysis of AGTR1, STAT3, and CD274 (PD-L1) expression levels in colorectal cancer samples from the TCGA cohort. (B) Comparison of representative immune cell fractions, including CD8⁺ T cells, CD4⁺ memory resting T cells, CD4⁺ memory activated T cells, and M2 macrophages, among AGTR1-high tumor tissues, AGTR1-low tumor tissues, and adjacent normal tissues estimated using the CIBERSORT algorithm. The X-axis represents immune cell subsets, and the y-axis represents the estimated CIBERSORT infiltration score. Statistical significance was evaluated using the Kruskal-Wallis test followed by pairwise Wilcoxon rank-sum tests with Benjamini-Hochberg correction for multiple comparisons. Significance levels were based on FDR-adjusted P values: ns, P≥0.05; *adjusted P<0.05, **adjusted P<0.01, ***adjusted P<0.001, and ****adjusted P<0.0001. AGTR1, angiotensin II receptor type 1; AT1R, angiotensin II type 1 receptor; CIBERSORT, Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts; FDR, false discovery rate; ns, not significant; PD-L1, programmed death-ligand 1; STAT3, signal transducer and activator of transcription 3; TCGA, The Cancer Genome Atlas.

Discussion

Key findings

The present study provides compelling evidence that telmisartan, a widely used antihypertensive agent with selective AT1R antagonist activity, may exert immunomodulatory effects, potentially involving STAT3-associated modulation of PD-L1 expression. Our findings demonstrate that telmisartan may sensitize MSS CRC to immune checkpoint blockade, offering a potential strategy to overcome immunotherapy resistance in this challenging patient population.

Strengths and limitations

This study has several strengths. We combined in vitro experiments and an immunocompetent MSS CRC mouse model to evaluate both mechanistic and therapeutic effects of telmisartan. Furthermore, we investigated changes in PD-L1 expression, STAT3 signaling, tumor growth, and immune-cell infiltration, providing a comprehensive assessment of its immunomodulatory activity. Several limitations of the current study should be acknowledged. First, although CIBERSORT analysis provided a broader estimation of immune cell composition, further experimental validation of specific immunosuppressive populations, including regulatory T cells and exhausted CD8⁺ T cells, as well as functional markers of effector T cells, was not performed in the current study. Future studies incorporating multiparameter flow cytometry or multiplex IHC are warranted to further define the immune mechanisms underlying telmisartan-mediated immune modulation. Although public transcriptomic analyses provided supportive evidence for the association between the AT1R-STAT3-PD-L1 axis and the tumor immune microenvironment, currently available public databases do not contain comprehensive information on telmisartan exposure, RAS inhibitor use, or immunotherapy response in patients with CRC. Therefore, direct clinical validation of the effect of telmisartan on immune checkpoint blockade remains unavailable and warrants further prospective investigation. Second, while the CT26 syngeneic model provides an immunocompetent system for evaluating immunotherapy combinations, it may not fully recapitulate the complexity of human MSS CRC, including the heterogeneous TME and diverse immune cell populations (29). Third, the precise molecular mechanism by which enhanced p-STAT3 leads to PD-L1 suppression requires further investigation, including chromatin immunoprecipitation studies to identify specific binding sites and co-factor analysis. Fourth, although telmisartan consistently reduced PD-L1 expression in vitro and enhanced the efficacy of anti-PD-1 therapy in vivo, rescue experiments using PD-L1 overexpression were not performed in the present study. Therefore, whether the immunomodulatory effects of telmisartan are partially mediated by PD-L1 downregulation requires further investigation. Fifth, Previous in vitro studies have commonly employed micromolar concentrations of telmisartan (approximately 10–50 μM) to investigate its anti-tumor mechanisms (27,28). However, these concentrations may not directly reflect clinically achievable plasma levels in patients receiving conventional telmisartan therapy. Therefore, further studies are needed to determine whether clinically achievable concentrations can exert similar regulatory effects on PD-L1 expression. Sixth, our study evaluated short-term tumor growth inhibition; longer-term studies assessing survival outcomes and potential resistance mechanisms are warranted. Seventh, we used pembrolizumab (anti-human PD-1) in the mouse model; while this antibody has some cross-reactivity with murine PD-1, future studies should confirm these findings using species-matched anti-PD-1 antibodies. Finally, the present study focused on the short-term therapeutic effects of telmisartan in combination with anti-PD-1 therapy. The potential development of acquired resistance following prolonged treatment was not investigated. Future studies employing long-term treatment models and clinically relevant preclinical systems are warranted to evaluate the durability of therapeutic responses and the mechanisms underlying resistance.

Comparison with similar research

The connection between RAS signaling and tumor immunity has gained increasing recognition in recent years. AT1R is overexpressed across multiple cancer types and promotes tumor progression through diverse mechanisms including angiogenesis, proliferation, and metastasis (8,12). Beyond these direct tumor-promoting effects, AT1R signaling has been implicated in shaping the immunosuppressive TME through modulation of the JAK2/STAT3 pathway (13). Our findings are consistent with these observations and further extend previous evidence by demonstrating that pharmacological inhibition of AT1R with telmisartan is associated with reduced PD-L1 expression and enhanced responsiveness to anti-PD-1 therapy in MSS CRC.

Recent studies have highlighted the potential of RAS inhibitors as modulators of anti-tumor immunity. Murphy et al. reported that combining losartan with FOLFIRINOX in locally advanced pancreatic cancer significantly improved R0 resection rates and overall survival, accompanied by substantial remodeling of the TME (17). Mechanistic investigations further demonstrated that ARBs suppress the RhoA-YAP signaling axis in CAFs, reduce type I collagen deposition, and facilitate T-cell infiltration into tumors (18,19). These findings support the concept that RAS inhibition may transform immunologically “cold” tumors into more immune-responsive phenotypes. Our study expands this concept to MSS CRC and provides evidence that telmisartan can enhance intratumoral T-cell infiltration and improve the efficacy of immune checkpoint blockade.

Epidemiological and experimental studies have also suggested broader anti-tumor benefits of RAS inhibitors. Long-term use of captopril has been associated with a reduced risk of prostate cancer (20), while a prospective cohort study demonstrated that RAS inhibitor use was associated with decreased breast cancer incidence (21). In addition, retrospective analyses have reported lower rates of advanced gastrointestinal malignancies among patients receiving ACE inhibitors (11). Although these studies primarily focused on cancer incidence and progression, our findings provide mechanistic evidence supporting a role for telmisartan in modulating the tumor immune microenvironment and enhancing anti-tumor immunity.

Explanations of findings

A notable finding of the present study is that telmisartan treatment was associated with increased STAT3 phosphorylation while simultaneously reducing PD-L1 expression. This observation appears inconsistent with the conventional view that STAT3 activation promotes PD-L1 transcription and contributes to tumor immune evasion (30). However, accumulating evidence suggests that STAT3 functions in a context-dependent manner and may act as either a transcriptional activator or repressor depending on cellular conditions, promoter architecture, and the availability of interacting cofactors (14,15). Previous studies have demonstrated that STAT3 can bind to negative regulatory elements and suppress transcription of specific target genes under certain biological contexts (16).

Based on these observations, it is plausible that AT1R blockade by telmisartan alters intracellular signaling networks and shifts STAT3 toward a transcriptional regulatory state associated with PD-L1 suppression. Consistent with this hypothesis, we observed a reproducible association between increased p-STAT3 levels and reduced PD-L1 expression in both in vitro and in vivo experiments. In addition, previous studies have shown that the balance between STAT3 homodimers and STAT1-STAT3 heterodimers may influence whether downstream target genes are activated or repressed (31,32). Although the precise molecular mechanism remains to be determined, our findings suggest that STAT3-associated signaling may contribute to the immunomodulatory effects of telmisartan.

Another important observation was the enhancement of intratumoral T-cell infiltration following telmisartan treatment. Increased infiltration of CD3+, CD4+, and CD8+ T cells was observed in tumors from telmisartan-treated mice, particularly when combined with anti-PD-1 therapy. One possible explanation is that reduced PD-L1 expression weakens PD-1/PD-L1-mediated inhibitory signaling, thereby restoring T-cell activation and effector function within the TME (33). Furthermore, previous studies have shown that RAS inhibition can reduce stromal fibrosis and improve tumor vascular perfusion, potentially facilitating immune-cell trafficking into tumor tissues (18,19). AT1R signaling may also directly influence T-cell activity, as angiotensin II has been reported to suppress T-cell activation and promote an immunosuppressive microenvironment (34).

In addition to its immunomodulatory effects, telmisartan significantly inhibited CRC cell migration in both MSS and MSI-H cell lines. This finding is consistent with previous reports indicating that AT1R signaling promotes tumor cell migration and metastasis through regulation of matrix metalloproteinases, cytoskeletal remodeling, and epithelial-mesenchymal transition (8,12). Therefore, inhibition of AT1R signaling by telmisartan may not only enhance anti-tumor immunity but also reduce the metastatic potential of CRC cells.

To complement the experimental observations, we further analyzed transcriptomic data from the TCGA CRC cohort. The positive correlations among AGTR1, STAT3, and CD274 provide independent clinical transcriptomic support for the proposed signaling axis. Furthermore, CIBERSORT analysis demonstrated that AGTR1 expression was associated with alterations in several immune cell populations, including CD8⁺ T cells, CD4⁺ memory T cells, and M2 macrophages. Although these computational findings do not establish causality, they are consistent with the hypothesis that AT1R signaling contributes to remodeling of the CRC immune microenvironment.

Implications and actions needed

The findings of the present study have important implications for the treatment of MSS CRC. Although ICIs have transformed the management of dMMR/MSI-H CRC, effective immunotherapeutic strategies for MSS CRC remain limited because of its immunologically “cold” TME. Our results suggest that telmisartan may enhance anti-tumor immunity through modulation of PD-L1 expression and promotion of T-cell infiltration, thereby improving responsiveness to PD-1 blockade. Given that MSS tumors account for the majority of advanced CRC cases, strategies capable of overcoming primary immunotherapy resistance are of considerable clinical interest.

An additional advantage of telmisartan is its well-established clinical safety profile. As a widely prescribed antihypertensive agent with decades of clinical use, telmisartan is generally well tolerated and inexpensive compared with many novel anti-cancer agents (22). In our study, no significant systemic toxicity was observed in treated animals, and the dose used corresponded to a clinically relevant human-equivalent dose range (35). These characteristics may facilitate future clinical translation and drug repurposing efforts.

Several actions are needed before clinical implementation can be considered. First, the molecular mechanism underlying the association between increased STAT3 phosphorylation and reduced PD-L1 expression requires further investigation. Future studies should employ approaches such as chromatin immunoprecipitation, transcriptomic profiling, and functional validation experiments to clarify the regulatory network involved. Second, additional preclinical studies are warranted to evaluate long-term therapeutic efficacy, survival benefit, and potential resistance mechanisms. Third, predictive biomarkers, including AT1R expression, PD-L1 status, and immune-cell infiltration patterns, should be explored to identify patients most likely to benefit from telmisartan-based combination therapy (10,36).

Ultimately, prospective clinical trials are required to determine whether the addition of telmisartan to ICIs can improve outcomes in patients with MSS CRC. If validated, this strategy may provide a practical and cost-effective approach to expand the benefits of immunotherapy to a much larger population of CRC patients.

Conclusions

This study provides evidence that telmisartan modulates the tumor immune microenvironment in CRC and may enhance the efficacy of immune checkpoint blockade in MSS CRC. Our findings demonstrate that telmisartan reduced PD-L1 expression and inhibited cell migration in both MSS and MSI-H CRC cell lines without inducing significant cytotoxicity. Telmisartan treatment was associated with increased STAT3 phosphorylation, suggesting a potential role of STAT3-associated signaling in the regulation of PD-L1 expression.

In an immunocompetent MSS CRC mouse model, telmisartan significantly inhibited tumor growth and enhanced the anti-tumor efficacy of anti-PD-1 therapy. These effects were accompanied by increased infiltration of CD3+, CD4+, and CD8+ T cells and changes in intratumoral PD-L1 expression. Collectively, these findings suggest that telmisartan may represent a promising adjunctive strategy for improving immunotherapy responsiveness in MSS CRC.

Further mechanistic investigations and prospective clinical studies are warranted to validate these findings and determine their clinical applicability.

Supplementary

The article’s supplementary files as

tcr-15-9-702-rc.pdf (415.8KB, pdf)
DOI: 10.21037/tcr-2026-1409
tcr-15-9-702-coif.pdf (440.3KB, pdf)
DOI: 10.21037/tcr-2026-1409
DOI: 10.21037/tcr-2026-1409

Acknowledgments

The authors thank all laboratory members for technical assistance and helpful discussions.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. All animal experiments were performed under a project license (No. IACUC-2013-012) granted by the Ethics Committee of Fujian Provincial Hospital (Fuzhou University Affiliated Provincial Hospital), in compliance with the National Institutes of Health Guide (8th edition, 2011) and relevant institutional guidelines for the care and use of animals.

Footnotes

Reporting Checklist: The authors have completed the ARRIVE and MDAR reporting checklists. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1409/rc

Funding: This study was supported by the Natural Science Foundation of Fujian Province (No. 2021J01362).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1409/coif). All authors report funding from the Natural Science Foundation of Fujian Province (No. 2021J01362). The authors have no other conflicts of interest to declare.

Data Sharing Statement

Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1409/dss

tcr-15-9-702-dss.pdf (69.9KB, pdf)
DOI: 10.21037/tcr-2026-1409

References

  • 1. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024;74:229-63.. 10.3322/caac.21834 [DOI] [PubMed] [Google Scholar]
  • 2. Xie YH, Chen YX, Fang JY. Comprehensive review of targeted therapy for colorectal cancer. Signal Transduct Target Ther 2020;5:22.. 10.1038/s41392-020-0116-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Le DT, Uram JN, Wang H, et al. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. N Engl J Med 2015;372:2509-20.. 10.1056/NEJMoa1500596 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Kim ST, Klempner SJ, Park SH, et al. Correlating programmed death ligand 1 (PD-L1) expression, mismatch repair deficiency, and outcomes across tumor types: implications for immunotherapy. Oncotarget 2017;8:77415-23.. 10.18632/oncotarget.20492 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Overman MJ, McDermott R, Leach JL, et al. Nivolumab in patients with metastatic DNA mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142): an open-label, multicentre, phase 2 study. Lancet Oncol 2017;18:1182-91.. 10.1016/S1470-2045(17)30422-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Ganesh K, Stadler ZK, Cercek A, et al. Immunotherapy in colorectal cancer: rationale, challenges and potential. Nat Rev Gastroenterol Hepatol 2019;16:361-75.. 10.1038/s41575-019-0126-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. George AJ, Thomas WG, Hannan RD. The renin-angiotensin system and cancer: old dog, new tricks. Nat Rev Cancer 2010;10:745-59.. 10.1038/nrc2945 [DOI] [PubMed] [Google Scholar]
  • 8. Childers WK. Interactions of the renin-angiotensin system in colorectal cancer and metastasis. Int J Colorectal Dis 2015;30:749-52.. 10.1007/s00384-014-2118-1 [DOI] [PubMed] [Google Scholar]
  • 9. Ager EI, Neo J, Christophi C. The renin-angiotensin system and malignancy. Carcinogenesis 2008;29:1675-84.. 10.1093/carcin/bgn171 [DOI] [PubMed] [Google Scholar]
  • 10. Yang SL, Shen L, Gao JC, et al. Expression of Angiotensin II and AT1R in colorectal cancer. World Chin J Digestol 2012;20:2213-6. [Google Scholar]
  • 11. Röcken C, Neumann K, Carl-McGrath S, et al. The gene polymorphism of the angiotensin I-converting enzyme correlates with tumor size and patient survival in colorectal cancer patients. Neoplasia 2007;9:716-22.. 10.1593/neo.07418 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Deshayes F, Nahmias C. Angiotensin receptors: a new role in cancer?. Trends Endocrinol Metab 2005;16:293-9.. 10.1016/j.tem.2005.07.009 [DOI] [PubMed] [Google Scholar]
  • 13. Huang W, Yu LF, Zhong J, et al. Angiotensin II type 1 receptor expression in human gastric cancer and induces MMP2 and MMP9 expression in MKN-28 cells. Dig Dis Sci 2008;53:163-8.. 10.1007/s10620-007-9838-9 [DOI] [PubMed] [Google Scholar]
  • 14. Yu H, Lee H, Herrmann A, et al. Revisiting STAT3 signalling in cancer: new and unexpected biological functions. Nat Rev Cancer 2014;14:736-46.. 10.1038/nrc3818 [DOI] [PubMed] [Google Scholar]
  • 15. Avalle L, Pensa S, Regis G, et al. STAT1 and STAT3 in tumorigenesis: A matter of balance. JAKSTAT 2012;1:65-72.. 10.4161/jkst.20045 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Timofeeva OA, Chasovskikh S, Lonskaya I, et al. Mechanisms of unphosphorylated STAT3 transcription factor binding to DNA. J Biol Chem 2012;287:14192-200.. 10.1074/jbc.M111.323899 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Murphy JE, Wo JY, Ryan DP, et al. Total Neoadjuvant Therapy With FOLFIRINOX in Combination With Losartan Followed by Chemoradiotherapy for Locally Advanced Pancreatic Cancer: A Phase 2 Clinical Trial. JAMA Oncol 2019;5:1020-7.. 10.1001/jamaoncol.2019.0892 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Mei J, Chu J, Yang K, et al. Angiotensin receptor blocker attacks armored and cold tumors and boosts immune checkpoint blockade. J Immunother Cancer 2024;12:e009327.. 10.1136/jitc-2024-009327 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Diop-Frimpong B, Chauhan VP, Krane S, et al. Losartan inhibits collagen I synthesis and improves the distribution and efficacy of nanotherapeutics in tumors. Proc Natl Acad Sci U S A 2011;108:2909-14. [DOI] [PMC free article] [PubMed]
  • 20. Ronquist G, Rodríguez LA, Ruigómez A, et al. Association between captopril, other antihypertensive drugs and risk of prostate cancer. Prostate 2004;58:50-6.. 10.1002/pros.10294 [DOI] [PubMed] [Google Scholar]
  • 21. van der Knaap R, Siemes C, Coebergh JW, et al. Renin-angiotensin system inhibitors, angiotensin I-converting enzyme gene insertion/deletion polymorphism, and cancer: the Rotterdam Study. Cancer 2008;112:748-57.. 10.1002/cncr.23215 [DOI] [PubMed] [Google Scholar]
  • 22. Michel MC, Foster C, Brunner HR, et al. A systematic comparison of the properties of clinically used angiotensin II type 1 receptor antagonists. Pharmacol Rev 2013;65:809-48.. 10.1124/pr.112.007278 [DOI] [PubMed] [Google Scholar]
  • 23. Boland CR, Goel A. Microsatellite instability in colorectal cancer. Gastroenterology 2010;138:2073-2087.e3.. 10.1053/j.gastro.2009.12.064 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Percie du Sert N, Hurst V, Ahluwalia A, et al. The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research. PLoS Biol 2020;18:e3000410.. 10.1371/journal.pbio.3000410 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Castle JC, Loewer M, Boegel S, et al. Immunomic, genomic and transcriptomic characterization of CT26 colorectal carcinoma. BMC Genomics 2014;15:190.. 10.1186/1471-2164-15-190 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Yurgelun MB, Kulke MH, Fuchs CS, et al. Cancer Susceptibility Gene Mutations in Individuals With Colorectal Cancer. J Clin Oncol 2017;35:1086-95.. 10.1200/JCO.2016.71.0012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Kalali D, Hadjiyianni A. The potential anticancer activities of telmisartan: a literature review. Ann Acad Med Siles 2023;77:176-81. [Google Scholar]
  • 28. Wang Y, Zhang T, Li C, et al. Telmisartan attenuates human glioblastoma cells proliferation and oncogenicity by inducing the lipid oxidation. Asia Pac J Clin Oncol 2022;18:217-23.. 10.1111/ajco.13574 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Olivera I, Sanz-Pamplona R, Bolaños E, et al. A Therapeutically Actionable Protumoral Axis of Cytokines Involving IL-8, TNFα, and IL-1β. Cancer Discov 2022;12:2140-57.. 10.1158/2159-8290.CD-21-1115 [DOI] [PubMed] [Google Scholar]
  • 30. Garcia-Diaz A, Shin DS, Moreno BH, et al. Interferon Receptor Signaling Pathways Regulating PD-L1 and PD-L2 Expression. Cell Rep 2017;19:1189-201.. 10.1016/j.celrep.2017.04.031 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Poli V, Camporeale A. STAT3-Mediated Metabolic Reprograming in Cellular Transformation and Implications for Drug Resistance. Front Oncol 2015;5:121.. 10.3389/fonc.2015.00121 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Wang Y, Shen Y, Wang S, et al. The role of STAT3 in leading the crosstalk between human cancers and the immune system. Cancer Lett 2018;415:117-28.. 10.1016/j.canlet.2017.12.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Topalian SL, Taube JM, Pardoll DM. Neoadjuvant checkpoint blockade for cancer immunotherapy. Science 2020;367:eaax0182.. 10.1126/science.aax0182 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Guzik TJ, Hoch NE, Brown KA, et al. Role of the T cell in the genesis of angiotensin II induced hypertension and vascular dysfunction. J Exp Med 2007;204:2449-60.. 10.1084/jem.20070657 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Nair AB, Jacob S. A simple practice guide for dose conversion between animals and human. J Basic Clin Pharm 2016;7:27-31.. 10.4103/0976-0105.177703 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Schmid P, Adams S, Rugo HS, et al. Atezolizumab and Nab-Paclitaxel in Advanced Triple-Negative Breast Cancer. N Engl J Med 2018;379:2108-21.. 10.1056/NEJMoa1809615 [DOI] [PubMed] [Google Scholar]

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    The article’s supplementary files as

    tcr-15-9-702-rc.pdf (415.8KB, pdf)
    DOI: 10.21037/tcr-2026-1409
    tcr-15-9-702-coif.pdf (440.3KB, pdf)
    DOI: 10.21037/tcr-2026-1409
    DOI: 10.21037/tcr-2026-1409

    Data Availability Statement

    Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1409/dss

    tcr-15-9-702-dss.pdf (69.9KB, pdf)
    DOI: 10.21037/tcr-2026-1409

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