Abstract
Background:
The renin–angiotensin–aldosterone system (RAAS) is implicated in the initiation, progression, and therapeutic response of several solid malignancies. RAAS inhibitors (angiotensin system inhibitors) exhibit potential antitumor effects; however, their impact on patients with esophageal squamous cell carcinoma (ESCC) undergoing neoadjuvant therapy remains scarce.
Objectives:
To investigate whether incidental ASI use during neoadjuvant treatment is associated with enhanced pathological response and survival outcomes in patients with ESCC.
Design:
A retrospective study.
Methods:
We retrospectively analyzed 391 ESCC patients who underwent neoadjuvant therapy followed by R0 resection between 2015 and 2022, stratified according to incidental use of ASIs during neoadjuvant chemotherapy (NAC). Baseline characteristics, major pathologic response (MPR), and long-term survival outcomes were compared. MPR rates were compared using the Chi-square test and multivariable logistic regression. Kaplan–Meier analysis was used to estimate overall survival (OS) and disease-free survival (DFS), and multivariable Cox proportional hazards models were applied to adjust for potential confounders. Sensitivity analyses were performed using propensity score matching (PSM).
Results:
Overall, 67 (17.1%) patients were administered ASIs. Compared with non-users, ASI users were older (p = 0.006) with a higher prevalence of hypertension (p < 0.001), while other characteristics were comparable. Overall, ASI use was significantly associated with improved OS (hazard ratio (HR) = 0.48, 95% confidence interval (CI): 0.29–0.79, p = 0.004) and DFS (HR = 0.56, 95% CI: 0.36–0.90, p = 0.015). The MPR rate was also higher in the ASI group (31.3% vs 17.0%, p = 0.007) and consistent with the results of the multivariable analysis (odds ratio = 2.19, 95% CI: 1.21–3.97, p = 0.010). After PSM, the survival benefit of ASI use remained significant for OS (HR = 0.38, p = 0.003) and DFS (HR = 0.54, p = 0.038).
Conclusion:
In ESCC patients receiving NAC, incidental ASI use correlated with better pathological response and improved long-term survival. RAAS inhibition shows promise as a perioperative therapeutic approach and warrants postoperative validation.
Keywords: esophageal squamous cell carcinoma, neoadjuvant therapy, propensity score matching, renin–angiotensin system inhibitors, survival analysis
Plain language summary
Can common blood-pressure medicines improve response and survival in esophageal squamous cell cancer treated before surgery?
Why was this study done? Some people with esophageal squamous cell carcinoma (a cancer of the food pipe) receive chemotherapy before surgery. ACE inhibitors and angiotensin receptor blockers (ARBs) are common blood-pressure medicines. They act on the renin–angiotensin system, which helps control blood pressure. Researchers wondered whether taking these medicines during pre-surgery chemotherapy is linked to better cancer outcomes.
What did the researchers do? They looked back at records from one hospital (2015–2022). The study included 391 people who all received the same pre-surgery chemotherapy (paclitaxel plus cisplatin) and then surgery. During chemotherapy, 67 people continued an ACE inhibitor or ARB; the others did not.
What did they find? Major pathologic response (MPR) means that, after surgery, less than 10% of the removed tumor tissue is still living cancer cells. MPR occurred in about 31 out of 100 people who used these medicines during chemotherapy, compared with about 17 out of 100 people who did not. At 5 years after surgery, about 72 out of 100 medicine users were alive versus about 53 out of 100 non-users. About 67 out of 100 users were alive without the cancer coming back or getting worse versus about 50 out of 100 non-users.
What do the findings mean? This was a single-center retrospective study. It shows an association, not proof that the medicines caused the benefit. Randomized trials are needed. Do not start, stop, or change blood-pressure medicines for cancer reasons without medical advice.
Introduction
Esophageal cancer is among the most lethal gastrointestinal malignancies worldwide. The two predominant histologic types of esophageal cancer are adenocarcinoma and squamous cell carcinoma (ESCC). 1 In China and other East Asian countries, ESCC is the more predominant type, with incidence rates that are markedly higher than those in Western populations. In recent years, the combination of neoadjuvant therapy and surgery has become the standard of care for locally advanced ESCC, as it improves both disease-free survival (DFS) and local tumor control.2,3 However, despite advances in multimodal treatment, long-term survival remains suboptimal, highlighting the urgent need to optimize therapeutic regimens and explore novel targeted or combinatory strategies.4–6
The renin–angiotensin–aldosterone system (RAAS), traditionally recognized for its role in blood pressure regulation and electrolyte homeostasis, has been increasingly implicated in the biology of various solid tumors. 7 Preclinical studies have demonstrated that RAAS signaling influences tumor angiogenesis, epithelial–mesenchymal transition (EMT), and the modulation of the immune tumor microenvironment, thereby affecting tumor aggressiveness and treatment responsiveness.8–10 Renin–angiotensin system inhibitors (ASIs), including angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs), are widely prescribed antihypertensive agents with well-established safety and tolerability profiles.11,12 Clinical evidence suggests that ASI use correlates with improved outcomes in multiple solid tumors such as lung, breast, and pancreatic cancers, fueling interest in their potential as adjunctive anticancer therapies.13,14
Specifically, for ESCC, Chen et al. 15 reported that long-term ACEI/ARB use was associated with prolonged survival. Recently, Geller et al. 16 reported that incidental ASI use during neoadjuvant therapy in patients with esophageal adenocarcinoma correlated with improved overall survival (OS) and DFS. However, ESCC and adenocarcinoma represent distinct biological entities with divergent epidemiological profiles, tumor microenvironments, and responses to neoadjuvant therapy. 2 While existing evidence has largely been derived from adenocarcinoma or mixed cohorts, no study to date has systematically evaluated the clinical impact of ASI use specifically in patients with ESCC undergoing neoadjuvant chemotherapy (NAC). This study aims to investigate, using real-world data, whether incidental ASI use during neoadjuvant treatment is associated with enhanced pathological response and survival outcomes in patients with ESCC, thereby providing clinical evidence to support integration of RAAS inhibition into multimodal treatment paradigms.
Methods
Study population
This single-center retrospective cohort study included patients with ESCC who underwent NAC followed by curative-intent surgery at Fujian Medical University Union Hospital between January 2015 and December 2022. The inclusion criteria were as follows: (1) histologically confirmed ESCC based on endoscopic biopsy; (2) receipt of NAC; (3) completion of R0 resection; and (4) availability of complete clinical records and follow-up data. The exclusion criteria were as follows: (1) receipt of NAC regimens other than paclitaxel plus cisplatin (TP regimen) and (2) coexistence of other primary malignancies. This study was reviewed and approved by the Ethics Committee of Fujian Medical University Union Hospital (Approval No. 2025KY669). Given the retrospective nature of the analysis and use of de-identified patient data, the Ethics Committee waived the requirement for written informed consent. The data from January 2015 and December 2022 were retrospectively analyzed in September 2025. The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement 17 (Supplemental Appendix 1).
Group definition and data collection
Use of ASIs, including ACEIs and ARBs, during NAC was ascertained by reviewing the patients’ complete electronic medical records and medication histories. In this study, “incidental ASI use” was defined as the continuous administration of an ACEI or ARB prescribed for underlying chronic conditions that were initiated prior to the commencement of NAC. These medications were maintained without interruption throughout the entire neoadjuvant treatment period. Patients who met this criterion were assigned to the ASI-positive (ASI+) group, whereas those who did not receive ASIs during the same period were classified as ASI-negative (ASI−). For ASI users, agent type (ACEIs vs ARBs) and duration of use during NAC were recorded.
All patients received a uniform NAC regimen consisting of two cycles of paclitaxel plus cisplatin, prescribed by experienced medical oncologists and administered in accordance with current clinical practice guidelines. Surgery was performed using the standard three-incision McKeown esophagectomy with two-field systematic lymphadenectomy. Selective cervical lymph node dissection was performed in those with suspected cervical lymph node metastases.
Baseline clinical and demographic data collected included age, sex, body mass index (BMI), smoking status, alcohol consumption, and comorbidities (hypertension, diabetes mellitus, coronary artery disease, cerebrovascular disease, peripheral vascular disease, and chronic obstructive pulmonary disease (COPD)). Tumor-related variables included primary tumor location, clinical TNM (cTNM) stage, post-treatment pathological TNM (ypTNM) stage, receipt of adjuvant therapy, and postoperative complications. Postoperative follow-up included routine imaging (thoracoabdominal computed tomography, ultrasonography, and positron emission tomography–computed tomography) and tumor marker assessments.
Study endpoints
The primary endpoints were OS and DFS. OS was defined as the interval from surgery to death from any cause, and the DFS interval was defined as the time from surgery to the first radiological or clinical evidence of recurrence or death from any cause. Secondary endpoints included major pathologic response (MPR), time to recurrence (TTR), and perioperative outcomes. MPR was defined as a residual viable tumor cell proportion of less than 10% in the resected specimen. All pathological assessments were independently reviewed by two senior pathologists to ensure consistency and reliability. TTR was defined as the interval from surgery to the first evidence of tumor relapse. For patients without recurrence, data were censored at the last follow-up or death. Recurrence was ascertained through routine surveillance, including CT, ultrasound, or PET-CT, and confirmed by biopsy when clinically indicated.
Statistical analysis
All analyses were performed using R software (version 4.1.0; R Foundation for Statistical Computing, Vienna, Austria). Continuous variables were expressed as mean ± standard deviation or median with interquartile range (IQR). Between-group differences were compared using the independent-samples t-test or the Wilcoxon rank-sum test, depending on data distribution. Categorical variables, including major pathologic response (MPR) and perioperative complications, were presented as frequencies and percentages and compared using the Chi-square test or Fisher’s exact test, as appropriate.
To minimize potential confounding, propensity score matching (PSM) was applied. Propensity scores were calculated using a logistic regression model including baseline variables such as age, BMI, smoking status, alcohol consumption, hypertension, diabetes mellitus, coronary artery disease, cerebrovascular disease, peripheral vascular disease, and COPD. Nearest-neighbor matching was performed at a 1:1 ratio with a caliper width of 0.2, yielding 60 patients in each group after matching. Covariate balance was assessed using absolute standardized differences (ASDs). An ASD value of less than 0.2 was pre-specified as the criterion for achieving an acceptable balance between the matched groups, thereby minimizing residual confounding from baseline characteristics.
Survival outcomes (OS and DFS) and TTR were estimated using the Kaplan–Meier method and compared using the log-rank test. Cox proportional hazards regression models were constructed to evaluate the independent association between ASI use and OS or DFS, with results reported as hazard ratios (HRs) and 95% confidence intervals (CIs). For the analysis of MPR, multivariable logistic regression models were applied to identify independent predictors and calculate odds ratios (ORs).
All statistical tests were two-sided, and p-values <0.05 were considered statistically significant. Missing data were addressed as follows: patients with incomplete primary outcome data or missing follow-up records (approximately 3% of the initial cohort) were excluded. For other clinical variables with low missingness (<1%), such as BMI or specific comorbidities, missing values were handled using simple imputation, employing the median for continuous variables and the mode for categorical variables.
Results
Patients’ characteristics
A total of 391 patients with ESCC who underwent neoadjuvant therapy followed by curative resection were included in the analysis. Among them, 67 patients (17.1%) received ASIs during the perioperative period. Baseline characteristics were generally well balanced between the two groups, except that the ASI group was slightly older (mean age: 63.21 ± 6.33 vs 60.48 ± 7.51 years, p = 0.006) and had a significantly higher prevalence of hypertension (97.0% vs 20.1%, p < 0.001). No significant differences were observed between groups in terms of sex distribution, BMI, smoking status, or other comorbidities. Likewise, there were no statistically significant differences in clinical tumor stage (p = 0.328) or surgical approach (p > 0.05; Table 1). Median duration of ASI exposure during neoadjuvant therapy was 8 weeks (IQR, 7–10 weeks). Subgroup analysis within the ASI cohort showed that survival outcomes were not significantly influenced by the specific duration of pre-NAC ASI therapy (p > 0.05). Detailed distribution of specific ASI agents is shown in Table S1.
Table 1.
Comparison of baseline characteristics of the patients.
| Variables | Total (n = 391) | ASI− (n = 324) | ASI+ (n = 67) | p |
|---|---|---|---|---|
| Age, mean ± SD | 60.94 ± 7.39 | 60.48 ± 7.51 | 63.21 ± 6.33 | 0.006 |
| BMI, mean ± SD | 22.00 ± 3.11 | 21.88 ± 3.04 | 22.59 ± 3.40 | 0.087 |
| Gender, male, n (%) | 279 (71.36) | 235 (72.53) | 44 (65.67) | 0.258 |
| Smoking, n (%) | 232 (59.34) | 196 (60.49) | 36 (53.73) | 0.305 |
| Drinking, n (%) | 204 (52.17) | 173 (53.40) | 31 (46.27) | 0.288 |
| Hypertension, n (%) | 130 (33.25) | 65 (20.06) | 65 (97.01) | <0.001 |
| Diabetes, n (%) | 50 (12.79) | 39 (12.04) | 11 (16.42) | 0.328 |
| CAD, n (%) | 35 (8.95) | 26 (8.02) | 9 (13.43) | 0.158 |
| CVD, n (%) | 8 (2.05) | 5 (1.54) | 3 (4.48) | 0.284 |
| PVD, n (%) | 12 (3.07) | 8 (2.47) | 4 (5.97) | 0.261 |
| COPD, n (%) | 6 (1.53) | 4 (1.23) | 2 (2.99) | 0.606 |
| Tumor location, n (%) | 0.671 | |||
| Upper | 59 (15.09) | 49 (15.12) | 10 (14.93) | |
| Middle | 222 (56.78) | 181 (55.86) | 41 (61.19) | |
| Lower | 110 (28.13) | 94 (29.01) | 16 (23.88) | |
| cT stage, n (%) | 0.777 | |||
| 2 | 105 (26.85) | 87 (26.85) | 18 (26.87) | |
| 3 | 204 (52.17) | 167 (51.54) | 37 (55.22) | |
| 4 | 82 (20.97) | 70 (21.60) | 12 (17.91) | |
| cN stage, n (%) | 0.182 | |||
| 0 | 67 (17.14) | 61 (18.83) | 6 (8.96) | |
| 1 | 116 (29.67) | 94 (29.01) | 22 (32.84) | |
| 2 | 158 (40.41) | 126 (38.89) | 32 (47.76) | |
| 3 | 50 (12.79) | 43 (13.27) | 7 (10.45) | |
| Clinical TNM stage, n (%) | 0.167 | |||
| II | 48 (12.28) | 43 (13.27) | 5 (7.46) | |
| III | 224 (57.29) | 179 (55.25) | 45 (67.16) | |
| IVA | 119 (30.43) | 102 (31.48) | 17 (25.37) | |
| ypT, n (%) | 0.258 | |||
| T 0–2 | 112 (28.64) | 89 (27.47) | 23 (34.33) | |
| T 3–4 | 279 (71.36) | 235 (72.53) | 44 (65.67) | |
| ypN, n (%) | 0.311 | |||
| ypN− | 226 (57.80) | 191 (58.95) | 35 (52.24) | |
| ypN+ | 165 (42.20) | 133 (41.05) | 32 (47.76) | |
| Pathology TNM stage, n (%) | 0.438 | |||
| I | 125 (31.97) | 103 (31.79) | 22 (32.84) | |
| II | 91 (23.27) | 78 (24.07) | 13 (19.40) | |
| IIIA | 45 (11.51) | 38 (11.73) | 7 (10.45) | |
| IIIB | 112 (28.64) | 88 (27.16) | 24 (35.82) | |
| IVA | 18 (4.60) | 17 (5.25) | 1 (1.49) | |
| Robot-assisted, n (%) | 77 (19.69) | 59 (18.21) | 18 (26.87) | 0.105 |
| Total LNs retrieved, mean ± SD | 36.23 ± 15.14 | 35.66 ± 14.68 | 38.97 ± 17.03 | 0.103 |
| Positive LNs, mean ± SD | 1.28 ± 2.34 | 1.26 ± 2.43 | 1.37 ± 1.87 | 0.710 |
| Postoperative hospital stay, mean ± SD | 12.81 ± 8.75 | 12.51 ± 8.46 | 14.28 ± 10.00 | 0.132 |
| Clavien–Dindo grade ⩾3, n (%) | 69 (17.65) | 54 (16.67) | 15 (22.39) | 0.263 |
| Pneumonia, n (%) | 125 (31.97) | 99 (30.56) | 26 (38.81) | 0.187 |
| Anastomotic leakage, n (%) | 44 (11.25) | 34 (10.49) | 10 (14.93) | 0.296 |
| Pleural effusion, n (%) | 31 (7.93) | 24 (7.41) | 7 (10.45) | 0.402 |
| Pneumothorax, n (%) | 7 (1.79) | 5 (1.54) | 2 (2.99) | 0.761 |
| Chylothorax, n (%) | 4 (1.02) | 4 (1.23) | 0 (0.00) | 1.000 |
| Thrombosis, n (%) | 4 (1.02) | 4 (1.23) | 0 (0.00) | 1.000 |
| Adjuvant therapy, n (%) | 237 (60.61) | 195 (60.19) | 42 (62.69) | 0.703 |
For binary variables, only the counts and percentages for the positive modality are presented, as the negative modality is complementary.
CAD, coronary artery disease; COPD, chronic obstructive pulmonary disease; CVD, cerebrovascular disease; LN, lymph node; PVD, peripheral vascular disease; SD, standard deviation.
Surgical quality and perioperative safety were comparable between the two cohorts. The mean number of total lymph nodes harvested (38.97 ± 17.03 vs 35.66 ± 14.68, p = 0.710) and positive lymph nodes (1.37 ± 1.87 vs 1.26 ± 2.43, p = 0.710) identified showed no statistical differences. Regarding perioperative outcomes, the incidence of major complications (Clavien–Dindo grade ⩾3) and the mean postoperative hospital stay were statistically similar between the ASI+ and ASI− groups (all p > 0.05). Notably, 90-day mortality occurred in three patients (0.8%), all of whom were in the ASI-negative group.
Survival analysis
The median follow-up duration was 47 months. Kaplan–Meier survival analysis demonstrated significantly better OS (p = 0.002) and DFS (p = 0.007) among ASI users compared with non-users. The median OS and DFS were not reached in the ASI group, whereas they were 63.8 months (IQR, 24.0 months–NR) and 61.0 months (IQR, 16.0 months–NR), respectively, in the non-ASI group. The 5-year OS rate was 71.5% in the ASI group but was 53.4% in the non-ASI group; the corresponding 5-year DFS rates were 66.9% and 49.8%, respectively (Figure 1). A comprehensive subgroup analysis demonstrated consistent survival benefits of ASI use across multiple clinically relevant variables, including gender, age, tumor location, and clinical stage (Figure S1).
Figure 1.
Overall (a) and disease-free (b) survival comparing ASI users to ASI non-users in the unmatched cohort.
ASI, angiotensin system inhibitor.
The results of the univariate and multivariable Cox regression analyses are detailed in Table 2. In univariate analysis, ASI use was significantly associated with improved OS (p = 0.002) and DFS (p = 0.008). After adjusting for age, BMI, concomitant antihypertensive medications, comorbidities, tumor stage, and postoperative adjuvant therapy in multivariate Cox proportional hazards models, ASI use remained independently associated with superior OS (HR = 0.48, 95% CI: 0.29–0.79, p = 0.004) and DFS (HR = 0.56, 95% CI: 0.36–0.90, p = 0.015). Pathologic lymph node positivity (HR = 1.58, 95% CI: 1.15–2.18, p = 0.005) and higher pathologic T stage (ypT3–4 vs ypT0–2: HR = 2.06, 95% CI: 1.34–3.17, p < 0.001) were identified as independent adverse prognostic factors.
Table 2.
Univariate and multivariate Cox regression models of overall and disease-free survival in the unmatched cohort.
| Variables | OS | DFS | ||||||
|---|---|---|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | Univariate analysis | Multivariate analysis | |||||
| HR (95% CI) | p | HR (95% CI) | p | HR (95% CI) | p | HR (95% CI) | p | |
| ASI | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) | ||||
| Yes | 0.45 (0.27–0.75) | 0.002 | 0.48 (0.29–0.79) | 0.004 | 0.54 (0.34–0.85) | 0.008 | 0.56 (0.36–0.90) | 0.015 |
| β-Blocker | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 0.86 (0.50–1.50) | 0.604 | 0.86 (0.51–1.46) | 0.573 | ||||
| CCB | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 1.12 (0.76–1.65) | 0.576 | 1.11 (0.76–1.61) | 0.585 | ||||
| Smoking | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) | ||||
| Yes | 1.48 (1.06–2.06) | 0.021 | 1.38 (0.99–1.93) | 0.058 | 1.46 (1.07–2.01) | 0.018 | 1.36 (0.99–1.87) | 0.061 |
| Drinking | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 1.20 (0.88–1.64) | 0.256 | 1.07 (0.79–1.44) | 0.675 | ||||
| Hypertension | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 0.95 (0.68–1.32) | 0.759 | 1.01 (0.73–1.38) | 0.965 | ||||
| Diabetes | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 1.41 (0.92–2.16) | 0.118 | 1.48 (0.99–2.22) | 0.058 | ||||
| CAD | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 0.60 (0.31–1.17) | 0.135 | 0.83 (0.47–1.46) | 0.519 | ||||
| CVD | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 0.89 (0.28–2.80) | 0.845 | 0.80 (0.26–2.51) | 0.703 | ||||
| PVD | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 0.45 (0.14–1.42) | 0.174 | 0.42 (0.13–1.31) | 0.136 | ||||
| COPD | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 0.39 (0.05–2.79) | 0.349 | 0.70 (0.17–2.84) | 0.623 | ||||
| Age | ||||||||
| <60 | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) | |||||
| ⩾60 | 0.74 (0.54–1.02) | 0.067 | 0.72 (0.53–0.97) | 0.030 | 0.76 (0.56–1.03) | 0.078 | ||
| Gender | ||||||||
| Male | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Female | 0.74 (0.51–1.07) | 0.109 | 0.74 (0.52–1.05) | 0.096 | ||||
| BMI | ||||||||
| <19 | 1.00 (Reference) | 1.00 (Reference) | ||||||
| 19–25 | 0.85 (0.53–1.35) | 0.487 | 0.74 (0.48–1.14) | 0.171 | ||||
| ⩾25 | 0.73 (0.41–1.30) | 0.283 | 0.68 (0.40–1.17) | 0.166 | ||||
| Location | ||||||||
| Upper | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Middle | 1.14 (0.72–1.81) | 0.585 | 1.11 (0.72–1.71) | 0.648 | ||||
| Lower | 1.38 (0.84–2.27) | 0.206 | 1.25 (0.78–2.01) | 0.357 | ||||
| ypT | ||||||||
| T 0–2 | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) | ||||
| T 3–4 | 2.26 (1.47–3.47) | <0.001 | 2.06 (1.34–3.17) | <0.001 | 2.32 (1.54–3.48) | <0.001 | 2.08 (1.38–3.13) | <0.001 |
| ypN | ||||||||
| ypN− | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) | 1.00 (Reference) | ||||
| ypN+ | 1.60 (1.16–2.20) | 0.004 | 1.58 (1.15–2.18) | 0.005 | 1.72 (1.27–2.34) | <0.001 | 1.72 (1.27–2.34) | <0.001 |
| Differentiation | ||||||||
| G1 | 1.00 (Reference) | 1.00 (Reference) | ||||||
| G2 | 0.89 (0.59–1.33) | 0.564 | 0.94 (0.63–1.40) | 0.772 | ||||
| G3 or x | 0.85 (0.56–1.27) | 0.424 | 0.99 (0.66–1.47) | 0.947 | ||||
| Adjuvant | ||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||
| Yes | 0.79 (0.57–1.09) | 0.149 | 0.90 (0.66–1.23) | 0.527 | ||||
ASI, angiotensin system inhibitors; BMI, body mass index; CAD, coronary artery disease; CCB, calcium channel blocker; CI, confidence interval; COPD, chronic obstructive pulmonary disease; CVD, cerebrovascular disease; DFS, disease-free survival; HR, hazard ratio; OS, overall survival; PVD, peripheral vascular disease; ypN, pathologic lymph node positivity; ypT, post-treatment pathologic T.
Regarding disease failure patterns, 92 patients (28.4%) in the non-ASI group and 13 patients (19.4%) in the ASI group experienced confirmed recurrence (Table S2). Although the distribution of recurrence patterns (locoregional vs distant vs both) was similar between groups (p = 0.963), the median TTR was significantly prolonged in ASI users compared to non-users (not reached vs 61.0 months, p = 0.007).
Pathologic response
MPR was achieved in 19.44% of the overall cohort, with a significantly higher rate in the ASI group compared with the non-ASI group (31.34% vs 16.98%, p = 0.007, Table 3). In univariate analysis, ASI use was significantly associated with a higher likelihood of MPR (p = 0.008). This association persisted in multivariate logistic regression after adjusting for age, sex, tumor location, and clinical stage (OR = 2.19, 95% CI: 1.21–3.97, p = 0.010, Table 4).
Table 3.
Pathological response comparison between groups.
| Variables | Total (n = 391) | ASI− (n = 324) | ASI+ (n = 67) | p |
|---|---|---|---|---|
| MPR, n (%) | 0.007 | |||
| No | 315 (80.56) | 269 (83.02) | 46 (68.66) | |
| Yes | 76 (19.44) | 55 (16.98) | 21 (31.34) | |
| PCR, n (%) | 0.374 | |||
| No | 368 (94.12) | 307 (94.75) | 61 (91.04) | |
| Yes | 23 (5.88) | 17 (5.25) | 6 (8.96) | |
ASI, angiotensin system inhibitors; MPR, major pathologic response.
Table 4.
Univariate and multivariate analyses of major pathological responses after surgery.
| Variables | Univariate | Multivariate | ||
|---|---|---|---|---|
| OR (95% CI) | p | OR (95% CI) | p | |
| ASI | ||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||
| Yes | 2.23 (1.24–4.04) | 0.008 | 2.19 (1.21–3.97) | 0.010 |
| Smoking | ||||
| No | 1.00 (Reference) | |||
| Yes | 0.93 (0.56–1.54) | 0.776 | ||
| Drinking | ||||
| No | 1.00 (Reference) | |||
| Yes | 1.33 (0.81–2.20) | 0.260 | ||
| Hypertension | ||||
| No | 1.00 (Reference) | |||
| Yes | 1.12 (0.66–1.88) | 0.675 | ||
| Diabetes | ||||
| No | 1.00 (Reference) | |||
| Yes | 1.37 (0.68–2.76) | 0.384 | ||
| Gender | ||||
| Male | 1.00 (Reference) | |||
| Female | 1.19 (0.69–2.05) | 0.529 | ||
| Age | ||||
| <60 | 1.00 (Reference) | 1.00 (Reference) | ||
| ⩾60 | 1.73 (1.02–2.95) | 0.043 | 1.70 (0.99–2.91) | 0.053 |
| BMI | ||||
| <19 | 1.00 (Reference) | |||
| 19–25 | 1.77 (0.72–4.39) | 0.214 | ||
| ⩾25 | 1.87 (0.67–5.24) | 0.231 | ||
| Location | ||||
| Upper | 1.00 (Reference) | |||
| Middle | 0.75 (0.37–1.53) | 0.433 | ||
| Lower | 0.99 (0.46–2.12) | 0.974 | ||
| cT stage | ||||
| 2 | 1.00 (Reference) | |||
| 3 | 0.60 (0.34–1.06) | 0.077 | ||
| 4 | 0.59 (0.29–1.23) | 0.159 | ||
| cN stage | ||||
| cN− | 1.00 (Reference) | |||
| cN+ | 0.72 (0.39–1.36) | 0.314 | ||
ASI, angiotensin system inhibitors; BMI, body mass index; CI, confidence interval; OR, odds ratio.
Propensity score-matched analysis
To further reduce potential confounding, a 1:1 PSM yielded 60 matched pairs of ASI users and non-users. Baseline characteristics were well balanced between the groups after matching (Table S3). In the matched cohort, Kaplan–Meier analysis showed that OS and DFS remained significantly longer in ASI users; the median OS was not reached in the ASI group but was 56.8 months in the non-ASI group (p = 0.005), while the median DFS was not reached in the ASI group but was 54.0 months in the non-ASI group (p = 0.019; Figure 2). Multivariate Cox regression confirmed ASI use as an independent protective factor for OS (HR = 0.38, 95% CI: 0.20–0.72, p = 0.003) and DFS (HR = 0.54, 95% CI: 0.30–0.97, p = 0.038) in the matched cohort. Pathologic lymph node positivity (ypN⁺) remained an independent adverse predictor of OS after matching (Table S4).
Figure 2.
Overall (a) and disease-free (b) survival comparing ASI users to ASI non-users in propensity score-matched analysis.
ASI, angiotensin system inhibitor.
Discussion
In this large-scale, long-term, real-world cohort study, we systematically evaluated, for the first time, the impact of incidental perioperative use of ASIs during NAC on pathological response and long-term survival outcomes in patients with ESCC. Our findings demonstrate that ASI use was significantly associated with higher rates of MPR and prolonged OS and DFS, with these associations remaining statistically robust after PSM. Our results suggest that the RAAS may play a critical modulatory role in both neoadjuvant treatment response and tumor progression in ESCC, offering a clinical rationale for integrating RAAS inhibition strategies in the perioperative settings.
Preclinical and translational research has shown that, beyond its established role in maintaining blood pressure and fluid homeostasis, RAAS—via angiotensin II type 1 receptor (AGTR1) signaling—regulates tumor angiogenesis, EMT, extracellular matrix (ECM) remodeling, and immune suppression.7,18 Inhibition of this pathway reduces vascular endothelial growth factor (VEGF) expression, thereby suppressing neovascularization.19,20 Furthermore, RAAS hyperactivation promotes stromal collagen deposition and increases interstitial fluid pressure through profibrotic signaling, such as transforming growth factor-β, which can hinder the effective delivery of chemotherapeutic agents to the tumor core.
Recent studies further support the concept that microenvironmental modulation can enhance therapeutic efficacy. For example, normalization of tumor vasculature and ECM remodeling has been shown to alleviate hypoxia and improve drug delivery, while immune microenvironment reprogramming augments cytotoxic T-cell activity and chemosensitivity.21,22 Consistently, AGTR1 antagonists, such as losartan, have been shown to lower interstitial pressure and improve vascular perfusion, thereby enhancing chemosensitivity. 10 Immunologically, losartan has been reported to downregulate immunosuppressive gene expression, reduce regulatory T-cell (Treg) populations, and promote CD8⁺ T-cell infiltration, effectively reprogramming the immune microenvironment and augmenting anti-tumor responses. 23
In our cohort, ASI users achieved a significantly higher MPR rate compared with non-users; moreover, ASI use remained an independent predictor of MPR in multivariable analyses. This is consistent with the proposed mechanisms described above, suggesting that RAAS inhibition may enhance neoadjuvant chemosensitivity by improving drug delivery, suppressing angiogenesis, and alleviating immune suppression, ultimately facilitating pathological response. As MPR has been validated as a reliable surrogate endpoint for long-term survival in multiple solid tumors, our findings not only highlight the potential of RAAS-related molecules as predictive biomarkers for treatment response but also provide clinical justification for considering RAAS inhibition as a perioperative therapeutic target. Biological variability may arise from differences in ASI type, dose, and exposure duration; in our cohort, both ACEIs and ARBs were used, with a median neoadjuvant exposure of 8 weeks. Most patients had been prescribed ASIs for hypertension before cancer diagnosis and continued therapy uninterrupted. Future prospective studies with standardized ASI regimens are needed to clarify optimal timing and agent selection.
Survival analyses revealed that ASI use was associated with significantly improved 5-year OS and DFS in the unmatched cohort (5-year OS: 71.5% vs 53.4%), and this benefit persisted after PSM. Although only 17% of patients received ASIs, potentially limiting statistical precision, the association remained robust after multivariate adjustment and PSM. Compared with previous studies on ASI use in esophageal cancer, including Wang et al., 24 which reported no survival advantage—potentially due to heterogeneous cohorts combining adenocarcinoma and squamous cell carcinoma and lack of standardized treatment—our study is novel in focusing specifically on incidental ASI use during NAC in ESCC and linking it to both pathological response and long-term outcomes. 24 This underscores the possibility that RAAS inhibition may modulate both the local tumor microenvironment and systemic immune status to alter disease trajectories. 15 For patients with ESCC and coexisting hypertension, careful selection of ACEIs or ARBs may offer not only cardiovascular benefits but also potential oncologic advantages—highlighting the need for multidisciplinary collaboration between oncology and cardiology teams in treatment planning.
Our findings warrant further validation and mechanistic exploration through translational research. Prospective trials should incorporate histopathologic and molecular analyses of tumor samples to assess the impact of ASI use on angiogenic markers (e.g., VEGF, CD31), immune cell infiltration (e.g., CD8⁺ T cells, Tregs), interstitial pressure, and fibrosis.25,26 Single-cell RNA sequencing could be applied to pre- and post-treatment samples to dissect cellular and transcriptional changes in the tumor microenvironment, with complementary spatial or multiplex assays to confirm tissue localization. These approaches would provide insight into how ASIs modulate immune and stromal interactions and help identify patients most likely to benefit from perioperative therapy.
This study has several limitations. First, as a single-center retrospective study, findings may be influenced by institutional practices and patient demographics, which could limit generalizability. Second, a notable inherent selection bias exists as our cohort only includes patients who successfully completed NAC and proceeded to surgery. Consequently, patients who experienced severe toxicity or rapid disease progression during neoadjuvant treatment were excluded. Third, while ASIs were prescribed for underlying cardiovascular conditions, the retrospective design cannot entirely rule out the influence of baseline health, nor was medication adherence directly measured. Finally, comparisons between ASI types, dosage effects, and molecular tumor characteristics were not evaluated. Future multi-center, prospective studies with standardized ASI monitoring and tumor profiling are warranted to confirm these findings and optimize perioperative therapeutic strategies for patients with ESCC.
Conclusion
This study demonstrated that incidental ASI use during neoadjuvant treatment in patients with ESCC is significantly associated with higher pathological response rates and improved long-term survival outcomes, supporting RAAS signaling as a potential perioperative therapeutic target. Given the favorable safety profile of ASIs, as well as their accessibility and cost-effectiveness, well-designed randomized controlled trials are warranted to confirm these clinical benefits and to investigate individualized treatment approaches based on RAAS activation status, with the goal of maximizing patient benefit through precision therapy.
Supplemental Material
Supplemental material, sj-docx-1-tam-10.1177_17588359261449071 for Angiotensin inhibitors during neoadjuvant chemotherapy improve esophageal squamous cell carcinoma outcomes by Maohui Chen, Yizhou Huang, Felix Liu, Chuanquan Lin, Shuliang Zhang, Taidui Zeng, Jun Yu, Bin Zheng and Chun Chen in Therapeutic Advances in Medical Oncology
Supplemental material, sj-docx-2-tam-10.1177_17588359261449071 for Angiotensin inhibitors during neoadjuvant chemotherapy improve esophageal squamous cell carcinoma outcomes by Maohui Chen, Yizhou Huang, Felix Liu, Chuanquan Lin, Shuliang Zhang, Taidui Zeng, Jun Yu, Bin Zheng and Chun Chen in Therapeutic Advances in Medical Oncology
Acknowledgments
None.
Footnotes
ORCID iDs: Maohui Chen 
https://orcid.org/0000-0002-2064-8715
Yizhou Huang
https://orcid.org/0000-0002-5523-4360
Jun Yu
https://orcid.org/0009-0006-3660-7674
Bin Zheng
https://orcid.org/0000-0001-8429-5384
Supplemental material: Supplemental material for this article is available online.
Contributor Information
Maohui Chen, Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China; Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China; National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China; Clinical Research Center for Thoracic Tumors of Fujian Province, Fuzhou, China.
Yizhou Huang, Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China; Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China; National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China; Clinical Research Center for Thoracic Tumors of Fujian Province, Fuzhou, China.
Felix Liu, Sendelta International Academy Shenzhen, Shenzhen, China.
Chuanquan Lin, Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China; Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China; National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China; Clinical Research Center for Thoracic Tumors of Fujian Province, Fuzhou, China.
Shuliang Zhang, Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China; Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China; National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China; Clinical Research Center for Thoracic Tumors of Fujian Province, Fuzhou, China.
Taidui Zeng, Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China; Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China; National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China; Clinical Research Center for Thoracic Tumors of Fujian Province, Fuzhou, China.
Jun Yu, Department of Thoracic Surgery, Fujian Medical University Union Hospital, No. 29, Xinquan Road, Fuzhou 350001, China; Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China; National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China; Clinical Research Center for Thoracic Tumors of Fujian Province, Fuzhou, China.
Bin Zheng, Department of Thoracic Surgery, Fujian Medical University Union Hospital, No. 29, Xinquan Road, Fuzhou 350001, China; Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China; National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China; Clinical Research Center for Thoracic Tumors of Fujian Province, Fuzhou, China.
Chun Chen, Department of Thoracic Surgery, Fujian Medical University Union Hospital, No. 29, Xinquan Road, Fuzhou 350001, China; Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China; National Key Clinical Specialty of Thoracic Surgery, Fuzhou, China; Clinical Research Center for Thoracic Tumors of Fujian Province, Fuzhou, China.
Declarations
Ethics approval and consent to participate: The study was approved by the Ethics Committee of Fujian Medical University Union Hospital (Approval No. 2025KY669). Given the retrospective nature of the study, the requirement for informed consent was waived. The study was conducted in accordance with the principles of the Declaration of Helsinki.
Consent for publication: Not applicable.
Author contributions: Maohui Chen: Conceptualization; Data curation; Formal analysis; Writing – original draft.
Yizhou Huang: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Writing – original draft.
Felix Liu: Data curation; Methodology; Software; Writing – original draft.
Chuanquan Lin: Investigation; Writing – review & editing.
Shuliang Zhang: Investigation; Resources; Writing – review & editing.
Taidui Zeng: Investigation; Resources; Writing – review & editing.
Jun Yu: Conceptualization; Funding acquisition; Resources; Writing – review & editing.
Bin Zheng: Conceptualization; Supervision; Writing – review & editing.
Chun Chen: Conceptualization; Data curation; Funding acquisition; Supervision; Writing – review & editing.
Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Clinical Research Center for Thoracic Tumors of Fujian Province (grant number 2024YGPT001), The investigator initiation Fund project of Fujian Medical University Union Hospital (grant number 2024XH045), Fujian Provincial Natural Science Foundation of China (grant number 2024J01634) and Joint Funds for the Innovation of Science and Technology, Fujian Province (grant number 2025Y9350).
The authors declare that there is no conflict of interest.
Availability of data and materials: The datasets used and analyzed in this study are available from the corresponding author* upon request.
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Supplementary Materials
Supplemental material, sj-docx-1-tam-10.1177_17588359261449071 for Angiotensin inhibitors during neoadjuvant chemotherapy improve esophageal squamous cell carcinoma outcomes by Maohui Chen, Yizhou Huang, Felix Liu, Chuanquan Lin, Shuliang Zhang, Taidui Zeng, Jun Yu, Bin Zheng and Chun Chen in Therapeutic Advances in Medical Oncology
Supplemental material, sj-docx-2-tam-10.1177_17588359261449071 for Angiotensin inhibitors during neoadjuvant chemotherapy improve esophageal squamous cell carcinoma outcomes by Maohui Chen, Yizhou Huang, Felix Liu, Chuanquan Lin, Shuliang Zhang, Taidui Zeng, Jun Yu, Bin Zheng and Chun Chen in Therapeutic Advances in Medical Oncology