Category: 8. Health

Introduction

The most prevalent malignancy among women is breast cancer (BC).¹ Metabolic reprogramming and immune evasion are two main features of the malignant transformation of BC, which facilitate cancer cell proliferation.² The accumulation of reactive oxygen species (ROS) and oxidative stress are associated with many risk factors, including age, genetic susceptibility, exposure to ionizing radiation, and estrogen metabolism.³

Aldolase A (ALDOA) is a crucial enzyme within the glycolytic pathway. The process enables the reversible conversion of fructose-1,6-bisphosphate into glyceraldehyde 3-phosphate and dihydroxyacetone phosphate. Vertebrates possess three aldolase isozymes, ALDOA, ALDOB, and ALDOC, characterized by distinct electrophoretic and catalytic properties. ALDOA represents the primary aldolase isozyme in tumor tissues, and the systemic increase in aldolase activity due to ALDOA upregulation in these tissues is a distinctive characteristic of cancer.^4,5 ALDOA has been observed to be overexpressed in a variety of malignant tumors, including gastric cancer,⁶ hepatocellular carcinoma,⁷ colorectal cancer,⁸ cervical cancer,⁹ kidney cancer¹⁰ and triple-negative BC.^11,12 Numerous studies indicate that ALDOA may be an independent prognostic factor.^13–15 Chang et al reported ALDOA was overexpressed in breast cancer tissues and a correlation between ALDOA expression levels and overall survival.¹⁶ However, the potential correlation between ALDOA expression and clinicopathological features remains elusive and needs further evaluation.

To ascertain the clinical implications of ALDOA in BC, this study examined any potential correlation between its expression and clinicopathological traits. Furthermore, we assessed the predictive significance of ALDOA in BC using the Kaplan-Meier plotter.

Methods

ALDOA Expression Analysis

The mRNA expression of ALDOA in pan-cancer data was analyzed by using the Tumor Immune Estimate Resource (TIMER) database (https://cistrome.shinyapps.io/timer/). The data of ALDOA expression in BC tissue and in normal tissue was analyzed using the Gene Expressing Profiling Interactive Analysis (GEPIA; http://gepia.cancer-pku.cn/) platform, the UALCAN web portal (http://ualcan.path.uab.edu/), and the BC Gene-expression miner (bc-GenExminer) v5.1 (http://bcgenex.ico.unicancer.fr).

Correlation Analysis of ALDOA and Clinicopathological Features

The Gene Expressing Profiling Interactive Analysis (GEPIA; http://gepia.cancer-pku.cn/) platform, the UALCAN web portal (http://ualcan.path.uab.edu/), and the BC Gene-expression miner (bc-GenExminer) v5.1 (http://bcgenex.ico.unicancer.fr) were used to analyze the correlation of ALDOA and clinicopathological features of BC patients. We used these databases based on the Pearson χ² test to analyze ALDOA mRNA expression among tumor and normal samples and P values < 0.05 to evaluate the statistical significance. The user-friendly web portal bc-GenExminer v5.1 includes BC patients’ clinicopathological data based on microarray and RNA-seq (Jézéquel et al, 2012). The expression of GSTMs according to Scarff-Bloom-Richardson (SBR) grade and intrinsic molecular subtypes was identified by the Prediction Analysis of Microarray 50 (PAM50) test. The significant P value (P < 0.05) was determined using Dunnett-Tukey-Kramer test and Welch’s t-test.

Survival Analysis

The association between ALDOA mRNA expression and BC patient survival, including overall survival (OS), recurrence-free survival (RFS) and distance metastasis-free survival (DMFS), was evaluated while using the Kaplan-Meier (K-M) Plotter (https://kmplot.com) database. P < 0.05 were considered as significant.

Human BC Tissues

The Department of General Surgery at Soochow University’s First Affiliated Hospital collected 96 BC and 50 adjacent healthy samples from BC patients with histological diagnoses who had radical surgery. None of the participants had chemotherapy or radiotherapy before surgery. The ethics board of the relevant institution approved this study (IRB number is 2022-083), which was conducted in compliance with the Declaration of Helsinki. Written informed consent was obtained from all patients prior to study commencement.

Immunohistochemistry (IHC)

Following defined procedures, the paraffin-embedded tissues were sectioned to a thickness of 5 μm, incubated at 4°C overnight with a monoclonal human ALDOA antibody (dilution 1:100; #11305-1-AP, Proteintech), stained using a staining kit (Zhongshan Biotechnology, Bei-jing, China), followed by visualization. After this, the staining score was evaluated based on positive cell rate and color intensity.^17,18 The staining was divided by color intensity into not colored, light yellow, brown, and tan and is recorded as 0, 1, 2, and 3, respectively. Positive cell rate of <25% was a score of 1, positive cell rate of 25–50% was a score of 2, positive cell rate of 51–75% was a score of 3, positive cell rate of >75% was a score of 4. The final score was calculated by the multiple of the intensity and extent score. A final score of 0 was considered as −; 1–4 as +; 5–8 as ++; 9–12 as +++. In our study, ++ or +++ was considered as high expression, and – or + as no or low expression.

Statistical Analysis

The statistical significance was assessed by one-way analysis of variance or Student’s t-test (paired, unpaired, or two-tailed). The difference in mRNA expression between groups was made by Welch’s and Dunnett-Turkey-Kramer’s tests. The associations between ALDOA expression and clinicopathologic variables were examined using the Pearson χ² test. K-M analysis was used for survival analysis. It was determined that P < 0.05 was statistically significant.

Results

ALDOA Expression Levels are Higher in BC Tumor Tissues Compared to Normal Tissues

The RNA-seq data analysis from the TIMER database shows that most cancer tissues had ALDOA expression higher than in normal tissues, including 13 malignancies like BC (Figure 1A). According to the UALCAN database and the bc-GenExMiner v5.1 cohort, BC tissues had a considerably higher amount of ALDOA than normal tissues (Figure 1B and C, P < 0.001). ALDOA expression was higher in BC tumors than in normal breast tissues in the GEPIA dataset (Figure 1D; insignificant but marginal).

Figure 1 ALDOA expression in human BC tissues. (A) ALDOA expression in tumor and normal tissues in TIMER database. (B–D) ALDOA expression in BC tumor and normal tissues in bc‐GenExMiner v5.1 (B), UALCAN (C) and GEPIA (D) databases. (E) Representative IHC staining of ALDOA in human BC tissues and normal tissues. (F) Analysis of ALDOA IHC scores in human BC tissues and normal tissues. ***P < 0.001.

Furthermore, IHC was used to assess the expression of the ALDOA protein in BC tissues and normal breast tissues. In BC tissue, ALDOA protein-positive staining increased (Figure 1E). Importantly, human BC tissues had higher IHC scores than normal tissues (Figure 1F; P < 0.001).

Relationship Between ALDOA Expression and BC Patients’ Clinicopathological Features

This study used the bc-GenExMiner v5.1 (Table 1) and UALCAN (Table 2) databases to examine the relationship between ALDOA expression and clinicopathological variables. Higher expression of ALDOA was linked to micropapillary BC, lymph node metastasis (LNM), older age, and high Ki67 expression. However, the correlations between ALDOA expressions with the staging of LNM patient’s gender and TNM stage were not significant (Figure 2).

Table 1 The Correlation Between ALDOA Expression and Clinicopathological Features of BC Patients Using the bc‐GenExMiner v5.1 Database

Table 2 The Correlation Between ALDOA Expression and Clinicopathological Features of BC Patients Using the UALCAN Database

Figure 2 ALDOA expression in different subgroups of human BC tumor tissues in bc‐GenExMiner v5.1 and UALCAN databases. (A) ALDOA expression in BC tumors of different histological types in bc‐GenExMiner v5.1 database. (B and C) ALDOA expression in BC tumors with or without LNM in bc‐GenExMiner v5.1 (B) and UALCAN (C) databases. (D and E) ALDOA expression in BC tumors based on patient’s age in bc‐GenExMiner v5.1 (D) and UALCAN (E) databases. (F) ALDOA expression in BC tumors based on patient’s gender in UALCAN database. (G) ALDOA expression in BC tumors based on ki-67 status in bc‐GenExMiner v5.1 database. (H and I) ALDOA expression in BC tumors based on tumor stages in bc‐GenExMiner v5.1 (H) and UALCAN (I) databases. ***P < 0.001. Abbreviation: ns, nonsignificant.

Afterward, this study examined the correlation between ALDOA expression and the pathological factors of BC. In the bc‐GenExMiner v5.1 database, elevated expression of ALDOA was associated with ER+ (Figure 3A), PR+ (Figure 3B), and ER+/PR+ (Figure 3C). However, the correlations between ALDOA expression and HER2 status were insignificant (Figure 3D). ALDOA expression in BC tumors based on PAM50 molecular subtypes was also investigated, and results showed that non-basal-like (including HER2-enriched (HER2-E), Luminal A and Luminal B subgroups) BC possessed higher ALDOA expression than the basal-like subtype (Figure 3E and F). The ALDOA expression of non-triple negative breast cancer (TNBC) tissue was higher than that of TNBC (including LAR, MLIA, BLIA, and BLIS subgroups) tissue (P = 0.0043, Figure 3G and H). Among different subtypes of TNBC, the luminal androgen receptor (LAR) subgroup showed higher ALDOA expression than other subtypes (P < 0.0001, Figure 3H and I).

Figure 3 ALDOA expression in different subgroups of human BC tumor tissues in bc‐GenExMiner v5.1 database. (A–D) ALDOA expression in BC tumors based on ER (A), PR (B), ER/PR (C) and HER2 (D) status. (E) ALDOA expression in BC tumors based on PAM50 molecular subtypes. (F and G) ALDOA expression in BC tumors based on basal-like (PAM50 (F)) and TNBC (G) and status. (H and I) ALDOA expression in BC tumors based on non-TNBC and TNBC subtypes.

In the bc‐GenExMiner v5.1 database, the correlations between ALDOA expression in BC tumors with breast cancer susceptibility gene (BRCA) 1 (Figure 4A, P = 0.9913), BRCA2 (Figure 4B, P = 0.3623) or BRCA1/2 status (Figure 4C, P = 0.3494) were not significant. The GES analysis from bc-GenExMiner database revealed that the ALDOA expression level of p53 wild-type BC was higher than p53 mutated (Figure 4D, P = 0.0002). However, in the IHC analysis from bc-GenExMiner database and the UALCAN database, the status of P53 was not related to the ALDOA expression in BC (Figure 4E and F). Moreover, higher ALDOA levels were substantially correlated with higher Scarff-Bloom-Richardson (SBR) grade (Figure 4G, P = 0.002) and Nottingham Prognostic Index (NPI) (Figure 4H, P = 0.0004). Asian patients showed the highest ALDOA expression among all three races (Figure 4I, P < 0.001).

Figure 4 ALDOA expression in different subgroups of human BC tumor tissues in bc‐GenExMiner v5.1 and UALCAN databases. (A–C) ALDOA expression in BC tumors based on BRCA1 (A), BRCA2 (B) AND BRCA1/2 status in bc‐GenExMiner v5.1 database. (D and E) ALDOA expression in BC tumors based on p53 (GES (D)), p53 (IHC (E)) status in bc‐GenExMiner v5.1 database. (F) ALDOA expression in BC tumors based on p53 status in UALCAN database. (G and H) ALDOA expression in BC tumors based on Scarff-Bloom-Richardson (SBR (G)) grade and NPI (Nottingham prognostic index (H)) status in bc‐GenExMiner v5.1 database. (I) ALDOA expression in BC tumors based on patient’s race in UALCAN database. ***P < 0.001. Abbreviation: ns, nonsignificant.

Moreover, the relationship between ALDOA expression and the clinical characteristics in 96 BC patients who underwent radical surgery was investigated using IHC (Table 3). Increased ALODA expression was shown to be significantly associated with higher histological grade (Table 3, P < 0.001) and lymph node metastasis (Table 3, P = 0.043). However, no significant correlation was found between ALDOA expression and TNM stage, vascular invasion, tumor location, tumor size, or age (Table 3, P > 0.05).

Table 3 The Relationships Between ALDOA and Clinicopathological Factors in 96 Patients with Breast Cancer

The OS of BC Patients is Correlated with ALDOA Expression in Various Subgroups

The correlation between ALDOA mRNA expression in various subgroups and OS of BC patients was determined using the K-M survival curve analysis from the K-M Plotter database. In BC patients, shorter OS was predicted by higher ALDOA expression (Figure 5A, HR = 1.34, P = 0.0027). The results of the subgroup analysis showed that in the ER-positive (Figure 5B, HR = 1.42, P = 0.003), ER-negative (Figure 5C, HR = 1.6, P = 0.0067), PR-positive (Figure 5D, HR = 2.89, P = 0.006), and HER2-positive (Figure 5F, HR = 1.57, P = 0.014) subgroups, a shorter OS rate was associated with higher ALDOA expression. ALDOA expression did not, however, significantly correlate with the OS of BC patients who were PR negative (Figure 5E, HR = 1.56, P = 0.071) or HER2 negative (Figure 5G, HR = 1.23, P = 0.076). Higher ALDOA level was significantly associated with shorter overall survival in lymph node-negative patients (Figure 5I, HR = 1.58, P = 0.0086), this correlation was not significant in the lymph node-positive cohort (Figure 5H, HR = 1.23, P = 0.23).

Figure 5 ALDOA expression in different subgroups correlates with overall survival (OS) of patients with BC from Kaplan-Meier plotter database. (A) Kaplan-Meier survival curve analysis shows OS of BC patients. (B and C) Kaplan-Meier survival curve analysis shows OS of BC patients based on ER status ((B) ER positive; (C) ER negative). (D and E) Kaplan-Meier survival curve analysis shows OS of BC patients based on PR status ((D) PR positive; (E) PR negative). (F and G) Kaplan-Meier survival curve analysis shows OS of BC patients based on HER2 status ((F) HER2 positive; (G) HER2 negative). (H and I) Kaplan-Meier survival curve analysis shows OS of BC patients with LNM (H) or without LNM (I). Abbreviation: HR, hazard ratio.

OS was significantly shortened in high ALDOA expressing basal (Figure 6A, HR = 1.94, P = 0.0011), luminal A (Figure 6B, HR = 1.42, P = 0.033), and luminal B (Figure 6C, HR = 1.56, P = 0.017) BC patients when taking StGallen molecular subtypes into account. However, there was no significant correlation between the OS of BC patients with HER2 and ALDOA expression (Figure 6D, HR = 1.64, P = 0.086). Patients with p53 wild-type tumors exhibiting high ALDOA expression demonstrated significantly shorter overall survival (Figure 6F, HR = 1.95, P = 0.032). This association was not significant in the p53-mutated subgroup (Figure 6E, HR = 2.2, P = 0.094). Furthermore, high ALDOA expression is related to shorter OS in histological grade 1 (Figure 6G, HR = 2.29, P = 0.053, not significant, but marginal) and grade 2 (Figure 6H, HR = 1.67, P = 0.011) subgroups. Still, there was no discernible correlation between the OS of the histological grade 3 subgroup and the expression of ALDOA mRNA (Figure 6I, HR = 1.23, P = 0.26).

Figure 6 ALDOA expression in different subgroups correlates with OS of patients with BC from Kaplan-Meier plotter database. (A–D) Kaplan-Meier survival curve analysis shows OS of BC patients based on StGallen molecular subtypes ((A) basal; (B) luminal A; (C) luminal B; (D) HER2 positive). (E and F) Kaplan-Meier survival curve analysis shows OS of BC patients based on p53 status ((E) mutated; (F) wild type). (G–I) Kaplan-Meier survival curve analysis shows OS of BC patients based on histological grade ((G) grade 1; (H) grade 2; (I) grade 3).

The RFS of BC Patients is Correlated with ALDOA Expression in Various Subgroups

K-M survival curve analysis employing the K-M Plotter database showed that ALDOA mRNA expression was linked to relapse-free survival (RFS) of BC patients in several categories. BC patients with high ALDOA expression generally had significantly shorter RFS than those with low ALDOA expression (Figure 7A, HR = 1.15, P = 0.0085). Considering different pathological subgroups, shortened RFS was related to higher ALDOA expression regardless of the ER and PR status (Figure 7B–E), and also in HER2 positive BC patients (Figure 7F, HR = 1.42, P = 0.0017). However, among HER2-negative patients, there was no significant correlation between ALDOA expression and RFS (Figure 7G, HR = 1.09, P = 0.12). Elevated ALDOA expression corresponded to reduced RFS in LNM negative breast cancer cases (Figure 7I, HR = 1.22, P = 0.018). Conversely, nodal metastasis-positive patients exhibited no statistically association between ALDOA levels and RFS outcomes (Figure 7H, HR = 1.17, P = 0.13). Considering LNM status, shortened RFS was related to higher ALDOA expression in BC patients without LNM (Figure 7I, HR = 1.22, P = 0.018). In contrast, in patients with LNM, the correlation was not significant (Figure 7H, HR = 1.17, P = 0.13).

Figure 7 ALDOA expression in different subgroups correlates with relapse‐free survival (RFS) of patients with BC from Kaplan-Meier plotter database. (A) Kaplan-Meier survival curve analysis shows RFS of BC patients. (B and C) Kaplan-Meier survival curve analysis shows RFS of BC patients based on ER status ((B) ER positive; (C) ER negative). (D and E) Kaplan-Meier survival curve analysis shows RFS of BC patients based on PR status ((D) PR positive; (E) PR negative). (F and G) Kaplan-Meier survival curve analysis shows RFS of BC patients based on HER2 status ((F) HER2 positive; (G) HER2 negative). (H and I) Kaplan-Meier survival curve analysis shows RFS of BC patients with LNM (H) or without LNM (I). Abbreviation: HR, hazard ratio.

In the luminal A (Figure 8B, HR = 1.28, P = 0.0044), basal (Figure 8A, HR = 1.32, P = 0.014), and luminal B (Figure 8C, HR = 1.21, P = 0.033) cohorts, pronounced RFS reduction is significantly related to high ALDOA expression. In contrast, the association between ALDOA expression and the RFS of HER2-positive BC patients (Figure 8D, HR = 1.39, P = 0.067) was not significant. RFS was remarkably shortened in high ALDOA expressing p53 mutated BC patients (Figure 8E, HR = 3.61, P = 3.1e-05) and in the p53 wild type individuals (Figure 8F, HR = 1.39, P = 0.17), the association was not significant. Considering histological grade status, shortened RFS was related to higher ALDOA expression in BC patients with grade 1 subgroup (Figure 8G, HR = 1.65, P = 0.054, not significant, but marginal). The ALDOA mRNA expression and RFS of the histological grade 2 (Figure 8H, HR = 1.2, P = 0.1) and grade 3 (Figure 8I, HR = 1.19, P = 0.12) subgroups showed no discernible correlation.

Figure 8 ALDOA expression in different subgroups correlates with RFS of patients with BC from Kaplan-Meier plotter database. (A–D) Kaplan-Meier survival curve analysis shows RFS of BC patients based on StGallen molecular subtypes ((A) basal; (B) luminal A; (C) luminal B; (D) HER2 positive). (E and F) Kaplan-Meier survival curve analysis shows RFS of BC patients based on p53 status ((E) mutated; (F) wild type). (G–I) Kaplan-Meier survival curve analysis shows RFS of BC patients based on histological grade ((G) grade 1; (H) grade 2; (I) grade 3).

The DMFS of BC Patients is Correlated with ALDOA Expression in Various Subgroups

We then investigated the connection between ALDOA expression in different subgroups and the DMFS of BC patients using the K-M survival curve analysis from the K-M Plotter database. In general, the association between ALDOA expression and the distant metastasis-free survival (DMFS) of BC patients was insignificant (Figure 9A, HR = 0.93, P = 0.37). Shorter DMFS was linked to increased ALDOA expression in BC patients with both ER-positive (Figure 9B, HR = 1.2, P = 0.066, insignificant, but marginal) and ER-negative (Figure 9C, HR = 1.34, P = 0.039) subgroups. Regardless of PR and HER2 status, there was no discernible correlation between DMFS and ALDOA mRNA expression in BC patients (Figure 9D–G). Unexpected, prolonged DMFS was related to higher ALDOA expression in BC patients with LNM (Figure 9H, HR = 0.72, P = 0.01), while in patients without LNM, the correlation was not significant (Figure 9I, HR = 1.19, P = 0.18).

Figure 9 ALDOA expression in different subgroups correlates with distance metastasis-free survival (DMFS) of patients with BC from Kaplan-Meier plotter database. (A) Kaplan-Meier survival curve analysis shows DMFS of BC patients. (B and C) Kaplan-Meier survival curve analysis shows DMFS of BC patients based on ER status ((B) ER positive; (C) ER negative). (D and E) Kaplan-Meier survival curve analysis shows DMFS of BC patients based on PR status ((D) PR positive; (E) PR negative). (F and G) Kaplan-Meier survival curve analysis shows DMFS of BC patients based on HER2 status ((F) HER2 positive; (G) HER2 negative). (H and I) Kaplan-Meier survival curve analysis shows DMFS of BC patients with LNM (H) or without LNM (I). Abbreviation: HR, hazard ratio.

Regarding the StGallen molecular subtypes, DMFS was significantly shortened in high ALDOA expressing basal (Figure 10A, HR = 1.64, P = 0.014) and luminal A (Figure 10B, HR = 1.4, P = 0.017) BC patients. The correlation between ALDOA expression and DMFS in the luminal B (Figure 10C, HR = 1.14, P = 0.36) and HER2 positive subgroups (Figure 10D, HR = 0.75, P = 0.32) was not statistically significant. Shortened DMFS was associated with high ALDOA expression in both p53 mutated (Figure 10E, HR = 3.29, P = 0.019) and p53 wild type (Figure 10F, HR = 2.19, P = 0.029) subgroups. Additionally, high ALDOA expression was related to shorter DMFS in histological grade 1 BC patients (Figure 10G, HR = 3.91, P = 0.00039). Still, the ALDOA mRNA expression and DMFS of histological grade 2 (Figure 10H, HR = 0.85, P = 0.28) and grade 3 (Figure 10I, HR = 0.85, P = 0.21) BC patients showed no significant correlation.

Figure 10 ALDOA expression in different subgroups correlates with DMFS of patients with BC from Kaplan-Meier plotter database. (A–D) Kaplan-Meier survival curve analysis shows DMFS of BC patients based on StGallen molecular subtypes ((A) basal; (B) luminal A; (C) luminal B; (D) HER2 positive). (E and F) Kaplan-Meier survival curve analysis shows DMFS of BC patients based on p53 status ((E) mutated; (F) wild type). (G–I) Kaplan-Meier survival curve analysis shows DMFS of BC patients based on histological grade ((G) grade 1; (H) grade 2; (I) grade 3).

Discussion

Despite extensive research on molecular targeted drugs, chemotherapy and hormone therapy are still the first line of BC treatment.¹ However, an improved comprehension of the mechanisms by which malignant cells evade the immune system and the advancement of specific immune checkpoint antagonists has introduced novel therapeutic options.¹⁹ It is necessary to identify new molecular targets. This study offers insight into ALDOA’s potential function as a BC biomarker.

Initially, data from internet datasets were analyzed to compare ALDOA expression. ALDOA mRNA levels were observed to be elevated in breast tumors relative to normal and tumor-adjacent tissues, corroborating prior studies that demonstrated a significant increase in ALDOA transcript expression across all breast tumor subtypes compared to normal tissues, suggesting that ALDOA may represent a novel oncogene.¹² The above conclusion was verified by IHC. Comparative analysis of various breast cancer subtypes revealed elevated ALDOA expression in specific subtypes, including micropapillary, luminal B, non-basal-like, non-TNBC, and LAR, influencing therapeutic strategies and prognostic outcomes.

Following this, the bc-GenExMiner v5.1 and UALCAN databases were employed to systematically analyze the correlation between ALDOA expression and several clinicopathological variables. Overexpression of ALDOA was linked to LNM, older age, and high Ki67 expression. There was no statistical significance in gender, cancer stage, or HER2 status in the analysis. Notably, although ALDOA expression was correlated with LNM, the stage of LNM did not affect it. Aside from that, high ALDOA expression was found to follow ER and PR positivity, while decreased ALDOA mRNA levels were associated with TNBC and basal‐like BC, which might indicate that steroids increase the levels of ALDOA in breast epithelial cells. Tubule formation, nuclear characteristics of pleiomorphism, and the mitotic index are all assessed by the SBR grade, a histological grade.²⁰ NPI grade is a clinicopathological grading system based on tumor size, histopathological grade, and lymph node stage.²¹ Our study showed that ALDOA expression was higher with BC patients’ advanced SBR grade and NPI. Consistent with previous findings,²² ALDOA may predict a poorer prognosis in BC. Although a strong correlation between age and ALDOA expression was demonstrated in both databases, no such correlation was observed in the patient samples collected from individuals who underwent surgery. This is probably due to selection bias and a low sample size, because the clinical information for all 96 patients who underwent surgery was obtained from the same center. The clinicopathological information of BC patients from multiple centers need to be obtained in future subsequent studies.

The KM plotter was used in this study to assess the relationship between BC patients’ survival and ALDOA expression. The survival curves showed higher ALDOA mRNA levels were generally linked to worse OS, worse RFS, and worse DMFS. This is in line with earlier findings that suggested high ALDOA levels are linked to poor patient survival in a variety of solid tumors, including BC.²³ However, ALDOA expression was correlated to better DMFS of BC patients with LNM, which disagreed with the overall tendency and previous study.²²

Tu et al found that ALDOA can control tumor progression through the ALDOA-adenosine-50-monophosphate (AMP) activated protein kinase (AMPK) pathway, a nutrient sensor linked to aberrant activation of metabolic pathways, mitochondrial dynamics and functions, and epigenetic regulation. Depending on the specific cellular context, AMPK can be an oncogene or a tumor suppressor. Studies have shown the significance of ALDOA in cancers, but the underlying mechanisms are still unclear.^22,24 In intrahepatic cholangiocarcinoma and radioresistance cervical cancer, ALDOA promotes tumor proliferation and migration by enhancing tumor cell glycolysis.^9,25 According to Gu et al, ADOLA controlled the activity of the EGFR receptor and its downstream targets, ERK1/2 and AKT. Through the EGFR pathway, overexpression of ALDOA increased gastric cancer cells’ proliferation and cisplatin resistance.²⁶ Research conducted by Lu et al has shown that ALDOA promoted the proliferation and metastasis of colorectal cancer through its interaction with and regulation of the protein COPS6, thereby activating the mitogen-activated protein kinase (MAPK) signaling pathway and initiating EMT.²⁷ By suppressing miR-145 expression and activating the Oct4/DUSP4/TRAF4 pathway, ALDOA enhances the stemness of lung cancer.²⁸

There are some limitations in our study. Firstly, more research is necessary to understand the fundamental molecular process of ALDOA in BC cells. Secondly, more BC tumor tissues should be collected to further explore the expression and prognostic value of ALDOA in BC.

These findings indicated that ALDOA expression was much higher in BC tissues and closely correlated with clinical characteristics. For BC patients, a higher ALDOA indicated a lower chance of survival. The current research suggests that ALDOA may be a significant prognostic factor and a potential target for BC treatment.

Abbreviations

ALODA, Aldolase A; BC, breast cancer; BLIA, basal-like immune-activated; BLIS, basal-like immune-suppressed; BRCA, breast cancer susceptibility gene; DMFS, distant metastasis-free survival; ER, estrogen receptor; FP, first progression; GES, gene expression signature; HER2, human epidermal growth factor receptor 2; IDC, invasive ductal carcinoma; IHC, immunohistochemistry staining; ILC, invasive lobular carcinoma; KM, Kaplan-Meier; LAR, luminal androgen receptor; LNM, lymph node metastasis; MLIA, mesenchymal-like immune-altered; NPI, Nottingham Prognostic Index; OS, overall survival; PAM50, intrinsic molecular subtypes from Parker’s SSP; PPS, post-progression survival; PR, progesterone receptor; RFS, relapse-free survival; SBR, Scarff-Bloom-Richardson; TNBC, triple negative breast cancer.

Data Sharing Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics Statement

The study was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University.

Acknowledgments

Yuning Dai, Yong Yang, Xiaohua Li, and Guojian Shi are co-first authors for this study. The authors greatly acknowledge the Central Research Laboratory, the First Affiliated Hospital of Soochow University, for their excellent support and assistance in this work, and thank MJEditor (www.mjeditor.com) for its linguistic assistance during the preparation of this manuscript.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This study was supported by the fund from the National Nature Science Foundation of China (82103362), the Project of Science and Technology Development Plan of Suzhou City of China (SKY2023151, SKY2023155 and SKJY2021073), the Reserve Talent Project of the First Affiliated Hospital of Soochow University, the Project of Jiangsu Maternal and Child Health Association (FYX202216), the Project of “Gusu Medical Star” Youth Talent of Suzhou City of China, and the Project of Beijing Science and Technology Medical Development Foundation (KC2021-JF-0167-09).

Disclosure

The authors declare no competing interests in this work.

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Introduction

Epilepsy incidence rises significantly during late adulthood, peaking among individuals over 50 years of age at nearly double that of young adults.¹ The majority of elderly individuals diagnosed with late-onset epilepsy (LOE) exhibit risk factors for seizures such as neurovascular trauma, tumor, encephalitis, or other brain injuries,² but over one quarter of LOE cases remain without an identifiable etiology despite extensive diagnostic evaluations, termed late-onset epilepsy of unknown etiology (LOEU).³ Recent studies have demonstrated that LOE is independently associated with cognitive decline and increased risk of dementia, particularly Alzheimer’s disease (AD).⁴ According to epidemiological data, roughly 30% of LOEU patients with active seizures exhibit deposition of amyloid-β (Aβ) and hyperphosphorylated Tau protein, the core neuropathological signs of AD.⁵ Consequently, it is now acknowledged that LOEU may be a prodromal phase of AD. These findings suggest a potential chain effect wherein amyloidosis acts as a critical intermediary in the bidirectional exacerbation of LOE and AD.

Chronic insomnia is defined as difficulty falling asleep, maintaining sleep, and (or) awakening early in the morning, and often leads to fatigue, attention deficits, and emotional instability during the daytime.⁶ Sleep disturbances, including chronic insomnia, are highly prevalent among patients with LOE.⁷ Seizures alone can reduce sleep efficiency and total sleep duration while exacerbating sleep fragmentation,⁸ and this chronic insomnia or sleep deprivation may in turn worsen seizure control.⁹ Moreover, both epileptic activity and chronic insomnia accelerate brain Aβ plaque deposition,¹⁰ suggesting that LOEU and chronic insomnia can act synergistically to accelerate age-related neurodegeneration and cognitive decline.

The glymphatic system (GS) is the primary clearance pathway for metabolic waste products in the central nervous system (CNS) and so is implicated in numerous disorders associated with the accumulation of neurotoxic byproducts such as AD and epilepsy.^11,12 The clearance of waste products by the GS is mediated by glial cells expressing aquaporin-4 (AQP-4) water channels that direct the flow of cerebrospinal fluid (CSF) from the arterial perivascular space to the interstitial compartment and subsequently into surrounding veins, deep cervical lymphatic vessels, and meningeal lymphatic vessels, providing a bulk-flow pathway for movement of metabolic waste from the interstitium to the systemic circulation.¹³ Animal experiments have demonstrated that impaired GS function results in the accumulation of Aβ and tau proteins within the CNS parenchyma,¹⁴ suggesting that GS dysfunction may link LOE, chronic insomnia, and cognitive impairment. Notably, preclinical intervention studies have demonstrated that accelerating GS clearance can reduce epileptic discharge frequency and improve cognitive performance.¹⁵

Extending these findings to humans requires a non-invasive and safe method for the assessment of GS function. Taoka et al¹⁶ introduced diffusion tensor image analysis along the perivascular space (DTI-ALPS) as a novel method to assess the efficiency of GS function in clinical studies.^17,18 The DTI-ALPS index measures water molecule movement within the perivascular space (PVS) by quantifying diffusivity¹⁹ and is based on the premise that the PVS is predominantly oriented orthogonally to white matter association and projection tracts located near the body of the lateral ventricle.¹⁹ The DTI-ALPS index is then calculated based on the diffusion coefficients of projection fibers along the x-axis (Dxxproj) plus association fibers along the x-axis (Dxxassoc), and is further refined by incorporating the diffusion coefficients of association fibers along the z-axis and well as projection fibers along the y-axis.¹⁹ Consequently, a lower DTI-ALPS index value signifies reduced PVS diffusivity, which may in turn indicate GS dysfunction. This method eliminates the need for tracer injection while still demonstrating strong intergroup consistency.

However, despite numerous studies on the contributions of the GS to diverse age-related neurodegenerative diseases,^20,21 there is limited research on the associations of GS function with LOE and comorbidities. Furthermore, the plasma Aβ42: Aβ40 concentration ratio (Aβ42/40), a biomarker of brain amyloid plaque load and AD risk, may also indicate elevated LOE risk.²² Therefore, the current retrospective study investigated the potential contributions of GS dysfunction to LOE with comorbid chronic insomnia by evaluating associations of the DTI-ALPS index with various clinical markers and age-associated cognitive decline.

Methods

Participants

Associations among epilepsy, the DTI-ALPS index, sleep quality, plasma Aβ42/40, and cognitive deficits were assessed by retrospectively reviewing the clinical findings of LOE patients (n = 42) enrolled from our hospital’s epilepsy center from January 2022 to October 2024. Selection criteria for newly diagnosed LOE with or without chronic insomnia were as follows: (1) age 50 years old and older; (2) meeting 2017 ILAE diagnostic criteria for LOE;²³ (3) chronic insomnia compliant according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5);²⁴ (4) no evident responsible lesions for epilepsy (eg, tumors, cortical or lobar injuries) identified upon visual evaluation of routine 3.0-T brain magnetic resonance imaging (MRI) scans; (5) DTI data of sufficient quality for quantitative analysis; (6) no systemic or mental illnesses; (7) clinical data including cognitive, sleep, and neuropsychological assessments. In addition, healthy controls (HCs, n = 22) matched for sex ratio and age distribution and demonstrating no evidence of severe structural lesions on brain 3.0-T MRI scans were enrolled from the hospitalization database. All participants were right-handed.

Clinical Evaluations

General cognitive function was assessed using the Chinese version of the Mini-Mental State Examination (MMSE),²⁵ while anxiety was assessed using the Hamilton Anxiety Scale (HAMA), insomnia by the Pittsburgh Sleep Quality Index (PSQI), and depression using the Hamilton Depression Scale (HAMD).

It is worth noting that the MMSE scales have been authorized from PAR Inc. Reproduced with explicit permission from the Publisher, Psychological Assessment Resources, Inc. (PAR), located at 16204 North Florida Avenue, Lutz, Florida 33549. This material is excerpted from the MMSE developed by Marshal Folstein and Susan Folstein. Copyright 1975, 1998, 2001 by Mini Mental LLC, Inc. First published in 2001 by PAR. Unauthorized reproduction or distribution without the prior written consent of PAR is strictly prohibited. For copyright inquiries, please contact [[email protected]].

Quantification of Plasma Aβ42/Aβ40 Concentrations

Peripheral blood samples were collected from all participants in anticoagulant tubes the morning after an overnight fast and centrifuged for 10 min at 4000 g to isolate plasma. Plasma samples was stored at −80°C until analysis. Concentrations of Aβ₄₂ and Aβ₄₀ were measured using digital immunoassay technology (Simoa) on an HD-X analyzer (Quanterix Corp., Billerica, MA, USA). Plasma samples were diluted fourfold as per the manufacturer’s protocol for the Human Neuro 3-Plex A kit (Quanterix, #101995).

MRI Acquisition and Processing

Diffusion tensor images were acquired from all participants using a 3.0-T MRI scanner (GE Healthcare) equipped with a 32-channel head coil. Images were obtained by a single echo planar imaging (EPI) sequence of the following parameters: 32 diffusion-weighted directions; b-values of 0 and 1000 s/mm²; flip angle of 90°; repetition time (TR) = 8620 ms; matrix size, 120 × 120; echo time (TE) = 85 ms; slice thickness of 2.25 mm; field of view (FOV) of 240×240 mm²; interslice gap of 1 mm.

Images data were processed using the 2021 version of DSI Studio Software (available at http://dsi-studio.labsolver.org). The DTI-ALPS index was calculated using established protocols (Figure 1). Briefly, the processing pipeline encompassed opening source images, correcting for vortex and phase distortion artifacts, determining processing parameters (smoothing, thresholds, defragmentation, etc.), recreating the DTI data, and fiber tracking. The left hemisphere projection fibers (Dxxproj) and association fibers (Dxxassoc) at the lateral ventricle body level were selected to define 5-mm diameter regions of interest (ROIs). Subsequently, fiber orientations and diffusivities were extracted from the ROIs along the x-, y-, and z-axes at the voxel level. The ROIs with the highest directional coherence were selected for each fiber type (projection, subcortical fibers, association, etc.) based on the same diffusivity along the x-axis. The DTI-ALPS index was then computed according to the formula,

Figure 1 The process for obtaining DTI analysis along the perivascular space index. (A) Place the region of interests in the areas with projection and association fibers. (B) The direction of the paravascular space (gray columns) and the orientation of the three neural fiber tracts. (C) The directions of the projection fiber tracts (blue; z-axis), association fibers tracts (green, Y-axis), and subcortical fibers tracts (red, X-axis). (D) Flowchart illustrating the process of calculating DTI-ALPS index.

where the numerators Dxxproj and Dxxassoci are the diffusivities of the projection and association fibers along the x-axis, and the denominators Dyyproj and Dzzassoc are the diffusivities of the projection fibers along the y-axis and association fibers along the z-axis, respectively.

Statistical Analysis

Group differences in categorical variables were evaluated by chi-squared tests, while group differences in continuous variables were evaluated by analysis of variance (ANOVA). Associations between the DTI-ALPS index and clinical parameters (age, PSQI, scores of MMSE, HAMA and HAMD, Aβ42/40, and frequency and duration of seizures) were evaluated by calculating Spearman correlation coefficients. Diffusivities along fiber axes were corrected for multiple comparisons using the Bonferroni method (P =0.05/9 =0.0055). Independent risk factors associated with the DTI-ALPS index were identified by linear regression models. MedCalc^® Statistical Software (version 20) and GraphPad Prism (version 7) were employed for statistical analyses and mapping, respectively. A P < 0.05 (two-tailed) was considered statistically significant for all tests.

Results

Clinical Characteristics of Participants

The LOE group (n = 42) included 25 patients without chronic insomnia and 17 patients with chronic insomnia. Average age, sex ratio, mean years of education, and cerebrovascular risk factors did not differ significantly among LOE patient subgroups and HCs (Table 1). As expected, PSQI scores were significantly higher among LOE patients with chronic insomnia than patients without chronic insomnia and HCs (P < 0.05). In addition, both HAMD and HAMA scores were higher, while MMSE scores were lower in the comorbid LOE subgroup (P < 0.05). Thus, the comorbid subgroup exhibited more severe symptoms of depression, anxiety, and cognitive decline. Moreover, both the frequency and duration of seizures were higher in the chronic insomnia subgroup (P < 0.05). However, antiseizure medication load did not differ between LOE subgroups (P > 0.05). The Aβ42/40 was lower in the chronic insomnia subgroup compared to LOE patients with normal sleep, suggest that comorbid patients were at higher risk of AD.

Table 1 Demographic and Clinical Characteristics of LOE Patients and Healthy Controls

Comparative Analysis of Diffusivities and the DTI-ALPS Index

Table 2 summarizes the fiber diffusion coefficients along the x-, y-, and z-axes as well as the DTI-ALPS indices for all groups. Dxxproj was significantly lower in LOE patients than HCs while Dxxassoc, Dyyassoc, and Dzzproj did not differ among groups. The DTI-ALPS index was significantly lower in LOE patients than HCs. Additionally, the DTI-ALPS index was lower among comorbid LOE patients than LOE patients without comorbid chronic insomnia.

Table 2 Comparison of the Diffusivities Among LOE Patients and HCs

Correlation Analysis

There was a significant negative correlation between the DTI-ALPS index and age for the entire participant cohort (r = −0.700, P < 0.001, Figure 2A). In the total LOE patient group, there were significant positive correlations between DTI-ALPS index and both Aβ42/40 (r=0.752, P < 0.001, Figure 2B) and MMSE score (r = 0.803, P < 0.001, Figure 2C). There were also significant negative correlations between DTI-ALPS index and disease duration (r = −0.026, P < 0.001, Figure 2D), HAMA score (r = −0.725, P < 0.001, Figure 2E), and PSQI score (r = −0.786, P <0.001, Figure 2F).

Figure 2 Linear correlation between DTI-Alps index and clinical indicators. (A) Negative correlation between the DTI-ALPS index and ages in all participants. (B) Positive correlation between the DTI-ALPS index and Aβ42/40 in LOE patients. (C) Positive correlation between DTI-ALPS index and MMSE scores in LOE patients. (D) Negative correlation between DTI-ALPS index and seizure duration in LOE patients. (E) Negative correlation between the DTI-ALPS index and HAMA scores. (F) Negative correlation between the DTI-ALPS index and PSQI scores.

Linear regression model 1 controlling for education level and sex identified a significant independent association between DTI-ALPS and age (β = −0.751, P < 0.001) (Table 3). Model 2 controlling for neuropsychological scores and both frequency and duration of seizures revealed significant independent associations between DTI-ALPS index and age (β = −0.139, P = 0.015), Aβ42/40 (β = 0.238, P = 0.014), MMSE (β = 0.222, P = 0.010), and PSQI score (β = −0.192, P = 0.020), and these associations remained significant in linear regression model 3 adjusted for cerebrovascular risk factors (age, β = −0.109 and P = 0.039; Aβ42/40, β = 0.294 and P = 0.035; MMSE, β = 0.273 and P = 0.025; PSQI, β = −0.338 and P = 0.043).

Table 3 The Multivariable Linear Regression for the DTI-ALPS Index in LOE Patients

Discussion

This study is the first to explore potential GS dysfunction in LOE complicated by chronic insomnia using the DTI-ALPS index. The DTI-ALPS index was significantly lower in LOE patients than HCs and even lower among patients with comorbid chronic insomnia, suggesting that sleep disruption among LOE patients may be associated with GS dysfunction. Additionally, a negative correlation was observed between the DTI-ALPS index and epilepsy duration, indicating a gradual deterioration in GS function during disease progression. Moreover, the DTI-ALPS index was negatively associated with age across all participants, implying that GS function diminishes with age even in the absence of overt pathology. While the DTI-ALPS index was not associated with depression or anxiety among LOE patients, a lower index was associated with greater plaque load as evidenced by the plasma Aβ42/40 ratio. Collectively, these findings suggest that GS dysfunction may ultimately enhance AD risk in LOE patients. Causal associations among DTI-ALPS index, epilepsy severity, insomnia, and AD risk warrant future study.

An age-related decline in GS activity is implicated in several neurodegenerative conditions, including AD.²⁶ Further, LOE patients are more susceptible to cognitive impairments than age-matched controls, suggesting that LOE may exacerbate the underlying neuropathology.^5,27 Increases in tau phosphorylation and Aβ deposition have been detected in LOE patients²⁸ and further implicated in epileptogenicity. Effective nighttime sleep enhances glymphatic clearance, thereby reducing pathological burden.²⁹ However, in LOE with comorbid chronic insomnia, the decline in sleep efficiency may reduce glymphatic clearance of metabolic waste products,³⁰ potentially worsening the neuropathologies underlying epileptogenesis and cognitive decline. Notably, pathogenic Aβ deposition may also disrupt the sleep–wake cycle,³¹ thereby triggering a mutually reinforcing cycle of progressively worsening sleep disruption and Aβ deposition. Glymphatic system insufficiency may also contribute to epileptogenesis long before the deposition of insoluble Aβ.³² Sleep disorders and abnormal electroencephalogram (EEG) activity are often among the earliest signs of dementia.³³ Additionally, recurrent epileptic seizures compromise the integrity of the blood-brain barrier (BBB), resulting in the accumulation of peripheral proinflammatory cytokines in the CNS and triggering potentially neurodegenerative inflammation. Loss of BBB integrity also shifts the intracellular and extracellular ion concentrations in the CSF, contributing to cerebral edema.³⁴ Aquaporin-4 helps mitigate brain edema by facilitating CSF-interstitial fluid (ISF) exchange via GS flow, restoring ionic balance.^34,35 Downregulation of AQP-4 expression and ensuing disruption of ionic homeostasis following seizure activity may further compound GS dysfunction and increase AD risk. For instance, administration of the AQO-4 inhibitor TGN-20 to mice markedly diminished lymphatic CSF-ISF exchange and enhanced amyloid deposition,³⁶ suggesting that the AQP-4 protein as a promising therapeutic target for neurodegenerative conditions like LOE and AD.³⁷ In summary, age-associated reductions in CSF production, proinflammatory/anti-inflammatory imbalances, epileptiform seizure-induced brain edema, and diminished expression or localization of astrocytic AQP-4 may collectively disrupt CSF-ISF flow and reduce the efficiency of metabolic waste removal from the brain.

Extensive studies have corroborated DTI-ALPS detection technology as an effective tool for evaluating GS function. Among its advantages are high sensitivity to molecular micro-motion, non-invasive detection capabilities, and a relatively brief scanning time, making it particularly suitable for clinical application. Clinical investigations of epilepsy in particular, including focal epilepsy, refractory epilepsy, as well as status epilepticus (SE),^12,38 have revealed a strong association between a reduced DTI-ALPS index and impaired GS function. Notably, the DTI-ALPS index was reported to rise significantly in both ASM responders and postoperative patients receiving epilepsy surgery compared to pretreatment baseline.³⁹ Furthermore, Yu et al recently reported lower DTI-ALPS indices among elderly chronic insomnia patients, and even greater reductions among those exhibiting cognitive decline.⁴⁰ In fact, others have reported that shorter N2 sleep duration is both predictive of increased epileptic activity and an independent factor influencing DTI-ALPS decline.⁴¹ However, no previous study had evaluated alterations in GS function among LOE patients with comorbid chronic insomnia. In the current study, the DTI-ALPS index was positively associated MMSE score (implying that lower DTI-ALPS predicts poorer cognition) and negatively associated with Aβ42/40 and PSQI scores (implying that lower DTI-ALPS predicts greater pathological load and poorer sleep). This study thus highlights the importance of cognitive assessment in studies of epilepsy. Moreover, the DTI-ALPS index was negatively correlated with epilepsy duration, implying that a longer disease course and more numerous epileptic seizures may progressively exacerbate GS impairment, that GS dysfunction results in epilepsy progression, or that both processes are mutually reinforcing. Based on these findings, we hypothesize that GS function acts as a crucial mechanism for mitigating cognitive decline and reducing the risk of AD in LOE patients. These findings strongly suggest that enhancing GS function may serve as a promising therapeutic approach for managing epilepsy and associated comorbidities.⁴² In support of this notion, knockout of the Trpm4 gene and treatment with glibenclamide both promoted earlier recovery of GS function and brain edema following SE in mice, and these effects were accompanied by reduced phosphorylated tau protein accumulation and improved cognitive outcomes.⁴²

This study has several limitations. First, the limited sample size and single-center retrospective design limit applicability to other clinical populations and preclude the investigation of other potentially significant associations. However, the same MRI scanner was utilized to maintain inter-data comparability. Second, some LOE patients may exhibit mild white matter lesions or brain atrophy undetectable by DTI that could nonetheless affect the DTI-ALPS index calculation. Third, it is possible that ASM may activate the GS, consequently influencing the DTI-ALPS index. Also, some ASMs can indirectly improve sleep, thereby reducing comorbid psychiatric disorders⁴³ as well as seizures. Therefore, the clinical value of ASMs for improving sleep in LOE patients requires further investigation. Fourth, the retrospective design and lack of follow-up preclude drawing definitive causal associations between GS dysfunction and cognitive decline in LOE patients. Last, other sleep disorder types such as obstructive sleep apnea (OSA), REM sleep behavior disorder, and parasomnia may be associated with GS dysfunction.⁴⁴ Given that our study only evaluated LOE comorbid with chronic insomnia, we cannot not rule out the potential confounding effects of these other sleep disorders.

Conclusions

Measurements of DTI-ALPS revealed weaker GS activity in LOE patients with chronic insomnia. Further, GS insufficiency was associated with more severe disease phenotype, greater AD risk, and cognitive decline, suggesting that the GS is a promising therapeutic target for age-related diseases.

Data Sharing Statement

The data generated and analyzed during the current study are not publicly accessible owing to patient privacy considerations but can be obtained from the corresponding author upon reasonable request.

Ethics Statement and Consent to Participate

The principles outlined in the 2013 revision of the Helsinki Declaration were strictly complied with in this study. The Ethics Committee of the Second People’s Hospital of Hefei issued an approval for the research protocol. As the present study was retrospective, our Institutional Review Board waived the written informed consent. The data of the participants would be anonymized or kept confidential, without infringing upon any of their rights and interests.

Acknowledgments

Natural Science Foundation project of Bengbu Medical University (No. 2025byzd0373) offered support to this study together with the Hefei Second People’s Hospital Doctoral Special Research Fund (Grant No. 2025bszx11).

Disclosure

The authors report no conflicts of interest in this work.

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To meet this unmet medical need, researchers at the University of California San Diego School of Medicine are exploring new approaches to improve the effectiveness of treatments for HNSCC. In a new study of oral cancer, a type of HNSCC, they demonstrate how precisely timing two different treatments can potentially improve treatment outcomes by protecting tumor-draining lymph nodes, which are located close to tumors and have an important role in mediating the immune system’s response to the tumor.

The researchers found:

• In mice with oral cancer, delivering radiation therapy that preserves tumor-draining lymph nodes then later delivering immunotherapy resulted in a complete and durable tumor response, meaning the tumors became undetectable. This happened in 15/20 mice treated with this approach.
• The two treatments synergized to enhance migration of a specific type of immune cell, called activated CCR7+ dendritic cells, from tumors into lymph nodes. These cells helped trigger a stronger immune response to the tumor. This occurred in all treated mice.

The study’s results could have significant implications for the treatment of HNSCC, as well as other cancers that are resistant or unresponsive to current standard treatment approaches. The research also provides valuable biological insight into the role of tumor-draining lymph nodes in cancer biology, which could have further implications for developing new therapies. While it will take further research to fully explore the potential of this timed treatment approach, the findings demonstrate the importance of optimizing the sequence and timing of therapies to maximize their benefit to the patient. The researchers are now conducting clinical trials in collaboration with investigators at Providence Earl Chiles Cancer Center to leverage these strategies to improve outcomes in head and neck cancer patients.

The study, published in Nature Communications, was led by Robert Saddawi-Konefka, M.D., Ph.D.,PGY-8, resident physician and Joseph Califano, M.D., professor and interim chair in the Department of Otolaryngology and Iris and Matthew Strauss Chancellor’s Endowed Chair in Head and Neck Surgery at UC San Diego School of Medicine. Califano is also director of the Hanna and Mark Gleiberman Head and Neck Cancer Center at Moore’s Cancer Center. The study was supported, in part by a National Cancer Institute funded R01 grant led by. Califano and Andrew Sharabi, M.D., Ph.D., associate professor and Jacobs Chancellor’s Endowed Chair in the Department of Radiation Medicine and Applied Sciences at UC San Diego School of Medicine, as well as a member of the Head and Neck Cancer Center at Moores Cancer Center. The authors declare no competing interests.

GLP-1 anti-obesity medications are linked with improvements in testosterone levels and health outcomes for men with obesity or type 2 diabetes, researchers reported in San Francisco at ENDO 2025, the Endocrine Society’s annual meeting.

Weight loss from lifestyle changes or bariatric surgery is known to boost testosterone levels, but the impact of anti-obesity medications has not been widely investigated, study leader Dr. Shellsea Portillo Canales of SSM Health St. Louis University Hospital in Missouri said in a statement.

Portillo Canales and colleagues tracked 110 men with obesity – many also with type 2 diabetes – who were being treated with semaglutide, dulaglutide or tirzepatide, the active ingredients in Novo Nordisk’s Wegovy and Ozempic or Eli Lilly’s Trulicity, Mounjaro, and Zepbound.

The average age was 54. None of the men were receiving other testosterone-boosting medications.

During 18 months of treatment, the proportion of men with testosterone levels in the normal range rose from 53% to 77%.

…

While the study cannot prove GLP-1 drugs caused low testosterone levels to normalize, it does show a direct correlation, Portillo Canales noted.

This is an excerpt. Read the original post here

A combination of healthy activities including exercise, nutritious diet, computer brain games and socialising can improve cognitive performance in people at risk for dementia, according to a large new US study.

The study, conducted in five locations across the US over two years, is the biggest randomised trial to examine whether healthy behaviours protect brain health.

“It confirms that paying attention to things like physical activity and vascular risk factors and diet are all really important ways to maintain brain health,” said Dr Kristine Yaffe, an expert in cognitive ageing at the University of California, San Francisco, who was not involved in the study.

The results were presented laste week at the Alzheimer’s Association International Conference in Toronto and published in the journal JAMA.

The study involved 2,111 people, aged 60 to 79, from diverse racial and ethnic backgrounds. None were cognitively impaired. All had sedentary lifestyles, suboptimal diets and two other dementia risk factors, such as a family history of cognitive decline and high blood pressure.

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Half of the participants followed a structured programme. They were prescribed a healthy diet, socially engaging activities, and a weekly regimen of eight exercise sessions and three sessions of computerised cognitive training. They attended 38 meetings with facilitators and fellow participants.

The other participants followed a self-guided programme. They were given educational materials and resources, and were regularly encouraged to engage in healthy behaviours. They attended six team meetings during the study.

Cognitive scores for both groups improved considerably, with the high-intensity group improving somewhat more than the other group. “The structured intervention had an extra benefit over and above the self-guided,” said Laura Baker, a professor of gerontology, geriatrics and internal medicine at Wake Forest University School of Medicine and a principal investigator of the study.

Still, the study left many questions unanswered.

Dr Lon Schneider, an Alzheimer’s expert at the University of Southern California and a member of the Lancet Commission on dementia prevention, was impressed that “both groups improved quite significantly”. But he noted that the difference in performance between the high-intensity and self-guided groups was “very small”, raising questions about how beneficial an intensive programme truly was.

It was also unclear how much of the cognitive improvement reflected a “practice effect”, a common phenomenon whereby participants learn to do better on assessments simply by taking them several times, Schneider and other experts said.

“This does not demonstrate that any of the lifestyle changes in and of themselves, or the combination of them, is responsible for this level of improvement,” Schneider said. “Or that it is necessarily related to neurodegeneration or Alzheimer’s disease.”

The results cannot be compared with the general population, as the study did not include a group that received no intervention.

“We didn’t believe that it was ethical” to have a “group that would not get anything”, said Heather M Snyder, senior vice-president for medical and scientific relations at the Alzheimer’s Association, which spent $50 million as the lead funder of the study.

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Baker said that even if the structured intervention was only modestly more effective than the self-guided one, “I don’t think we can say a small difference for an at-risk group is not meaningful.” She estimated that, compared with the self-guided group, the structured intervention “slowed the cognitive ageing clock by one to two years”, which might “increase resilience against cognitive decline”.

But several outside experts said that estimating any real-world advantage was difficult. They also questioned whether many people could realistically adopt an intense programme.

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“One of the big questions is how much do you need to do, and what’s cost-effective,” said Kaarin Anstey, director of the Ageing Futures Institute at the University of New South Wales in Australia. “If we only have very intensive interventions only a few people can afford, that’s not actually going to address the bigger issue of population ageing and lots of people developing cognitive impairment.”

The study, called US POINTER, was modelled after the first large randomised trial of lifestyle changes, called FINGER and conducted in Finland a dozen years ago. That study’s intensive group showed 25 per cent greater cognitive improvement than a group receiving minimal intervention.

The goal was to “see if it can work” in a more diverse nation with different health and lifestyle issues, Baker said.

The participants lived in North Carolina, Rhode Island, northern California, Houston and Chicago. More than two-thirds were women and 31 per cent were from racial or ethnic minority groups.

Most had first-degree relatives with memory loss, and 30 per cent had the APOE4 gene mutation, which increases Alzheimer’s risk. All of those subgroups experienced the same degree of cognitive improvement.

Most people participated for the full two years, an indication that they were highly motivated whether or not they received intensive supervision.

Phyllis Jones (66) of Aurora, Illinois, enrolled partly because her mother and grandmother had suffered from vascular dementia. Before the study, she said, stress from being laid off from a software engineering position and other job difficulties sent her to the emergency room with blurry vision and a racing heart. “I was in really bad shape,” Jones said. Participating in the structured intervention “woke me up”.

At first, just 10 minutes of aerobics was exhausting, but she now exercises daily and has lost 30lb, she said. Buoyed by social support from the peer meetings, she found a new job as a software tester.

She befriended another participant, Patty Kelly (81). They encouraged each other, and Kelly overhauled her own diet, sharply limiting sweets, cheese and fried food.

Both women perceived some cognitive benefit, although they have not been told their scores. Jones felt more able to plan home projects and follow messaging chains at work. Kelly, who retired from a non-profit serving homeless families, said her driving had improved. “I don’t run into the side of the garage any more,” she said.

The computer brain games were “the hardest thing for us to get on board with”, Jones said. That was true for other participants, too, Baker said. “Is it practical to expect people to do this day after day?” Baker said about computerised brain training. “Based on our experience, I’m going to say no.” But she said that any kind of intellectual stimulation could be helpful.

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Since the trial ended last year, Jones has maintained many practices, she said, but found herself backsliding with sugar, and her cholesterol climbed. “I think the structure is important, the accountability,” she said.

The study found that participants who started with lower cognitive scores benefited more. It is unclear why, Anstey said, but could suggest that “we should have more aggressive targeting of interventions for people who have lower cognition, who are more at risk, and less intense or less expensive interventions for those with higher cognition”.

For both groups, the biggest cognitive improvement involved executive function – skills like planning and organising. Memory initially improved in both groups, but then declined, with no significant difference in the groups’ ultimate memory scores. Memory loss is a core Alzheimer’s symptom, Yaffe noted, so cognitive improvements in the trial were likely “less related to Alzheimer’s disease and more related to vascular changes in the brain”.

The researchers will analyse blood, brain scans and other data to see if the activities spurred brain changes, reductions in Alzheimer’s-related proteins or other biological factors, Snyder said. The US Alzheimer’s Association will spend $40 million to follow the participants and help communities adopt locally tailored programmes.

“We now need to translate this and to turn brain health interventions into public health outcomes and solutions,” Snyder said. – This article originally appeared in The New York Times.

From diet and geography to delivery mode and preterm birth, discover how a mother’s journey shapes the unique nutritional profile of her breast milk, potentially influencing lifelong health.

Diagram of factors that may affect macronutrient and energy content of breast milk. Abbreviation: IUGR, intrauterine growth restriction. Factors That May Affect Breast Milk Macronutrient and Energy Content: A Critical Review

In a recent study published in the journal Nutrients, researchers in Portugal reviewed the factors affecting energy and macronutrient content of breast milk.

Breast milk composition may adapt to maternal factors, neonatal characteristics, and obstetrical factors. The impact of changes in breast milk composition on offspring growth and health remains unknown. In the present study, researchers reviewed the factors affecting the energy and macronutrient content of breast milk. They searched medical literature databases using relevant terms and identified 35 studies for a comprehensive review using Levels of Evidence (LOE) classification and focusing on studies published after 2006 for methodological consistency. The factors affecting macronutrient and energy content of breast milk were stratified as maternal, obstetrical, and neonatal.

Maternal factors affecting breast milk energy and macronutrient content were maternal age, socioeconomic status, geographical location, dietary intake, nutritional status, and lactation stage. A study observed that milk from mothers with a lower socioeconomic status was richer in monounsaturated and n-9 fatty acids, while milk from mothers with a higher socioeconomic status was richer in polyunsaturated, n-3, and n-6 fatty acids (PUFAs). Milk from self-employed mothers or those working in the private sector was found to have a higher fat and protein content than that from unemployed mothers or those working in the public sector. Older maternal age has been reported to correlate with more fat in colostrum, transitional, and mature milk.

A study found consistent evidence that breast milk fatty acid content varies by geographical location, likely due to dietary differences. For instance, Swedish mothers’ breast milk was found to have higher eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA; n-3) but lower linoleic acid (n-6) content than Chinese mothers’ breast milk. Maternal obesity has been associated with elevated fat content in breast milk, though transitional milk may show lower fat, with evidence for higher lactose being less consistent and primarily observed in colostrum.

A systematic review found that higher maternal body fat was associated with increased fat content in breast milk. Lower maternal fat intake has been associated with higher eicosapentaenoic acid and docosahexaenoic acid content in breast milk. Higher maternal protein intake has been linked to increased energy, carbohydrate, fat, and protein content. Higher maternal intake of PUFAs has been found to correlate with higher PUFA content in breast milk.

Different lactation stages influence breast milk macronutrient content. A cross-sectional study found lower protein and higher fat content in mature milk than in transitional milk. A meta-analysis of preterm milk reported that during the first 12 weeks postpartum, there is a progressive increase in fat content and a progressive decline in protein content, with carbohydrate and energy content increasing initially before achieving a steady state. This pattern is most consistent for preterm milk, while term milk shows variations (for example, energy may increase continuously).

Obstetrical factors that may impact the energy and macronutrient content of breast milk include parity, preterm delivery, mode of delivery, and pregnancy morbidities (gestational diabetes and hypertensive disorders). Studies have suggested associations between the parity number and the macronutrient content of breast milk. Fat content is reported to increase with parity number up to three, beyond which the trend may reverse.

The extent of prematurity may impact breast milk’s energy and macronutrient content. A study found higher true protein and total energy content in breast milk with increasing prematurity. Another study found higher energy and fat but typically lower carbohydrate content in milk from mothers with preterm delivery than in milk from those who gave birth at term. Breast milk composition could also vary by the mode of delivery.

Milk from mothers who underwent cesarean section had elevated fat content, while milk from those with vaginal delivery had increased carbohydrate content. A systematic review found that mature milk and colostrum from hypertensive mothers had higher protein content compared to normotensive mothers. Hypertensive disorders were also linked to higher energy content (chronic hypertension) and lower DHA (preeclampsia), whereas gestational hypertension was associated with lower milk energy and fat.

A different study reported higher true protein and total energy content in milk from mothers with chronic hypertension. On the other hand, mature milk from mothers with gestational diabetes was found to have a lower energy and fat content compared to euglycemic mothers. A systematic review reported lower lactose and fat content in milk from mothers with diabetes mellitus.

Neonatal factors that affect breast milk’s energy and macronutrient content include sexual dimorphism and anthropometrics. Multiple studies conflict on sexual dimorphism: some report higher energy and fat content in milk for males, while others show the opposite for females. Lower carbohydrate content in milk for males is more consistently observed. Higher birth length was independently correlated with higher energy and fat content in breast milk.

In sum, various obstetrical, maternal, and neonatal factors affect the energy and macronutrient content of breast milk. Milk from obese and overweight mothers has been reported to be fat- and energy-rich, though transitional milk may differ. Increased energy and protein content have been reported in milk from mothers with earlier preterm delivery, especially extremely preterm births. Higher protein and energy content and variable fat changes were reported in milk from mothers with hypertensive disorders, while lower fat characterized milk from diabetic mothers. Though sexual dimorphism findings conflict, male infant sex may be associated with lower milk carbohydrate. The review acknowledges limitations, including heterogeneity in study designs and methodology.

There has been a significant increase in disorders of gut-brain interaction, including irritable bowel syndrome, following the pandemic, a new study has found.

Researchers added to previous studies, analysing data from both 2017 and 2023 to compare, for the first time, prevalence of gut-brain disorders before and after the pandemic.

They found that overall disorders of gut-brain interaction rose from 38.3% to 42.6%.

Other key findings include:

• Irritable bowel syndrome (IBS) rose from 28%, from 4.7% to 6%.
• Functional dyspepsia increased by nearly 44%, from 8.3% to 11.9%.
• People with long COVID were significantly more likely to have a gut-brain interaction disorder and reported worse anxiety, depression, and quality of life.

Irritable bowel syndrome is a chronic gastrointestinal disorder affecting the large intestine. Symptoms can include abdominal pain, bloating, and changes in bowel habits such as diarrhoea, constipation, or both. While it doesn’t cause permanent damage, the impact on quality of life can be significant.

It is not known exactly what causes IBS, but experts say that contributing factors may include gut-brain axis dysregulation, altered gut motility, intestinal inflammation, changes in gut microbiota, and increased sensitivity to certain foods or stress.

Treatment can include changes to diet, managing stress and medicine to ease symptoms.

Another gut-brain disorder is functional dyspepsia, which affects the upper digestive tract. Symptoms include persistent or regular pain/discomfort in the upper abdomen, feeling full quickly, bloating, and nausea.

Specialists believe that altered gastrointestinal motility, visceral hypersensitivity, psychosocial factors, and possibly low-grade inflammation can contribute to symptoms.

Treatment or management of the condition includes changes to diet and lifestyle, psychological therapies, and medication including proton pump inhibitors, prokinetics, or antidepressants.