Targeting CLIC6 with theaflavin enhances radiotherapy sensitivity in ER⁺/HER2⁻ breast cancer

Introduction

Breast cancer is the most common cancer in women and a leading cause of cancer-related death worldwide (1). The estrogen receptor-positive (ER⁺)/human epidermal growth factor receptor-negative (HER2⁻) subtype accounts for over half of all breast cancer cases (2-4). Radiotherapy is key to the treatment of ER⁺/HER2⁻ breast cancer, reducing recurrence and improving survival (5-7). However, many such tumors are radioresistant, limiting the clinical benefit of radiotherapy (8) and highlighting the need to identify molecular determinants of radiosensitivity.

Clinical factors like progesterone receptor (PR) positivity and a low Ki67 index are linked to radioresistance in luminal A-like tumors (9-11), but the mechanisms underlying this resistance are unclear. The development of radiosensitizers represents a promising treatment approach (12,13); however, to date, few targets for these tumors have been identified.

Chloride intracellular channel 6 (CLIC6) is a protein involved in ion homeostasis and cancer (14,15). Unlike other CLIC members, its role in breast cancer is poorly understood. Theaflavin, a black tea polyphenol (16), has not previously been investigated for its ability to target CLIC6 or influence radiosensitivity.

We re-analyzed single-cell RNA sequencing (scRNA-seq) data from ER⁺/HER2⁻ tumors before and after radiotherapy, integrated with data from The Cancer Genome Atlas (TCGA; https://portal.gdc.cancer.gov/). A high-dimensional weighted gene co-expression network analysis (hdWGCNA) identified a luminal A-associated module in which CLIC6 emerged as a prominent hub gene. Molecular docking indicated high-affinity binding between CLIC6 and theaflavin. Functional assays showed that CLIC6 overexpression conferred radioresistance in the ER⁺ cells (MCF-7 and T47D), while theaflavin restored radiosensitivity in a CLIC6-dependent manner. No such effects were observed in the ER-negative (ER⁻) MDA-MB-231 cells, highlighting the potential role of CLIC6 in radioresistant phenotypes and suggesting that theaflavin may function as a natural radiosensitizer for ER⁺/HER2⁻ breast cancer. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-aw-2466/rc).

Methods

Data collection and processing

Breast Invasive Carcinoma (BRCA) dataset comprising transcriptomic and clinical data for breast cancer was obtained from the TCGA database. The data were preprocessed by removing genes with zero expression in more than 50% of samples and imputing missing values using the k-nearest neighbors’ method (impute.KNN, R package impute version 1.72.3; k=10). A total of 1,211 BRCA cases were included in the analysis. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

scRNA-seq analysis of radiotherapy samples

The scRNA-seq data [22 breast tumor samples pre- and post-radiotherapy; BioProject PRJNA818695 (17)] were downloaded from the National Center for Biotechnology Information Sequence Read Archive (SRR18458885–SRR18458906). The raw reads were processed with Cell Ranger (version 9.0.1) for demultiplexing (mkfastq), alignment to GRCh38, and unique molecular identifier (UMI) quantification (count). The resulting gene-barcode matrix was imported into Seurat for quality control, normalization, and clustering. After filtering low-quality cells, 78,859 high-quality cells remained. Batch effects were corrected with Harmony. Dimensionality reduction using principal component analysis and t-distributed stochastic neighbor embedding (t-SNE), followed by cell annotation into six major types (i.e., epithelial, myeloid, T, fibroblast, endothelial, and B cells), was performed based on marker gene expression.

hdWGCNA

To identify the key genes in the tumor cell radioresponse, we conducted a hdWGCNA of the post-radiotherapy tumor cells. Gene co-expression networks were constructed, modules were identified, and their correlations with clinical traits were examined. One module was found to be strongly positively correlated with PR expression and negatively correlated with Ki67 expression. The hub genes in the module were selected based on high intramodular connectivity (K_ME). These hub genes were then intersected with PR-associated differentially expressed genes (DEGs) from TCGA-BRCA ER⁺/HER2⁻ cohort, yielding seven candidate hub genes putatively linked to radiotherapy response. To determine the appropriate soft-thresholding power, we calculated the scale-free topology fit index and mean connectivity across β values ranging from 1 to 30. A power of β=4 satisfied the approximate scale-free topology criterion (R²≈0.90) and maintained low mean connectivity, following standard WGCNA guidelines. Robustness analysis across the full β range confirmed that network topology and module structure were stable.

Molecular docking

Candidate compound structures were downloaded from PubChem and converted to Protein Data Bank (PDB) format using OpenBabel. The crystal structure of CLIC6 (18) was obtained from the PDB and prepared in PyMOL by removing water and ions. Ligand and protein files were converted to PDBQT [PDB, Partial Charge (Q), and Atom Type (T)] format for docking with AutoDock Vina, and the top binding poses were visualized in PyMOL to assess interactions and binding modes. No experimentally validated small-molecule ligands for CLIC6 have been reported in the literature; therefore, no positive-control ligand could be included. Several structurally unrelated natural compounds from the screening library were used as negative controls and showed weaker binding energies (>−5.0 kcal/mol), supporting the relative selectivity of theaflavin (table available at https://cdn.amegroups.cn/static/public/tcr-2025-aw-2466-1.xlsx). A binding energy threshold of −6.0 kcal/mol was used to define high-affinity interactions, consistent with widely adopted criteria in AutoDock Vina-based virtual screening studies.

Cell culture

The HEK 293T cell line was obtained from American Type Culture Collection (ATCC) (Washington, DC, USA). The MCF-7, T47D, and MDA-MB-231 cell lines were obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). All cell lines were authenticated by short tandem repeat (STR) profiling before use, and were routinely tested and confirmed to be free of mycoplasma contamination. The HEK293T, MCF-7, T47D, and MDA-MB-231 cells were cultured in Dulbecco’s modified Eagle medium (DMEM) (Gibco, Grand Island, NY, USA) or RPMI-1640 (Gibco) supplemented with 10% fetal bovine serum (FBS) and penicillin-streptomycin (P/S) at 37 ℃ in a 5% CO₂ incubator. All the procedures followed institutional biosafety and ethical guidelines.

Establishment of stable cell lines

The human CLIC6 coding sequence was synthesized and cloned into the pLV-EF1α-MCS-IRES-puro vector (Biosettia, San Diego, CA, USA) for overexpression, while a pLV-H1-EF1α-puro short-hairpin RNA (shRNA) vector (Biosettia, San Diego, CA, USA) targeting CLIC6 was used for knockdown in the MCF-7, T47D, and MDA-MB-231 cells. Stable cell lines were generated by puromycin selection (10 µg/mL, 7 days). The primer and shRNA sequences are listed in Table S1.

Irradiation

For the irradiation experiments, the MCF-7, T47D, and MDA-MB-231 cells (control or genetically modified) were exposed to X-rays using a Faxitron MultiRad 225 irradiator at a dose rate of ~0.5 Gy/min. A single dose of 6 Gy was delivered to the cells, after which they were returned to culture for downstream assays.

Colony formation assays

The MCF-7, T47D, and MDA-MB-231 cells were harvested by trypsinization, rinsed twice with phosphate-buffered saline, and counted before plating at 500 cells per well in six-well plates. After irradiation and drug treatment, the cells were maintained for 8 days to enable colony growth. The resulting colonies were fixed with 1% paraformaldehyde and stained using 0.1% crystal violet for 30 min at room temperature. All the experiments were performed in triplicate to ensure reproducibility.

Quantitative real-time polymerase chain reaction

Total RNA was extracted with TRIzol (Thermo Fisher Scientific, Waltham, MA, USA) and reverse-transcribed using a premix kit (Yeasen Biotech, Shanghai, China). Quantitative polymerase chain reaction was performed with SYBR Green Master Mix (Yeasen Biotech) on an Applied Biosystems system. CLIC6 expression was quantified relative to β-actin using the 2^−ΔΔCT method. The primer sequences are listed in Table S1. All the experiments were performed in triplicate to ensure reproducibility.

Cell Counting Kit-8 (CCK-8) proliferation assays

The cells were plated in 96-well plates at a density of 5×10³ cells/well. Following interventions, 10 µL of CCK-8 (Yeasen Biotech) solution was added to each well and incubated for 2 hours at 37 ℃. The absorbance (optical density) at 450 nm was directly measured using a microplate reader. All experiments were performed in triplicate to ensure reproducibility.

Statistical analysis

All the statistical analyses were performed using GraphPad Prism 8.0 (GraphPad Software). The results are presented as the mean ± standard deviation. Group differences were evaluated using a two-tailed Student’s t-test, assuming the data were normally distributed. One-way analysis of variance (ANOVA) was applied for experiments involving three or more groups, whereas two-way ANOVA was applied for experiments involving multiple variables. When ANOVA indicated overall significance, post-hoc comparisons were performed using the Holm-Sidak method. A P value less than 0.05 was considered statistically significant. Appendix 1 contains all exact P values.

Results

Single-cell transcriptomic profiling revealed the cellular heterogeneity of untreated ER⁺/HER2⁻ breast tumors

We extracted the scRNA-seq data from 22 ER⁺/HER2⁻ breast cancer samples (11 pre- and 11 post-radiotherapy). After quality control filtering and exclusion of cells with high mitochondrial gene content, a total of 78,859 single cells and approximately 51,000 gene features were retained. To delineate the transcriptomic landscape of ER⁺/HER2⁻ disease, we performed unsupervised clustering and visualized the cells using t-SNE. All the cells were initially partitioned into 23 clusters, which were further annotated into seven major lineages based on the canonical marker genes and DEGs (Figure 1A-1C). Epithelial cells were the predominant population (69.7%). Other lineages included T cells (7.4%), B cells (1.3%), myeloid cells (13.6%), fibroblasts (6.1%), and endothelial cells (1.9%) (Figure 1D). Notably, the relative proportions of these cell types varied substantially across individuals, highlighting the marked inter-patient heterogeneity of ER⁺/HER2⁻ tumors (Figure 1E).

Figure 1 Single-cell atlas of ER⁺/HER2⁻ breast cancer pre- and post-radiotherapy. (A) t-SNE plot showing the seven major cell types in ER⁺/HER2⁻ breast cancer. (B) Dot plot illustrating lineage marker gene expression across different cell types. (C) Donut charts illustrating the cellular composition of the seven major lineages. (D) Bar plot showing the proportion of each cell type in individual patient samples. (E) t-SNE feature plots depicting the expression (color intensity from light to dark blue) of representative marker genes for each of the seven lineages. ER⁺, estrogen receptor-positive; HER2⁻, human epidermal growth factor receptor-negative; t-SNE, t-distributed stochastic neighbor embedding.

hdWGCNA identified a luminal A-like gene module associated with radiotherapy exposure

To identify the molecular features of the tumor cells associated with radiotherapy exposure, we applied hdWGCNA to the single-cell data. A comparison of the tumor cells pre- vs. post-radiotherapy revealed distinct transcriptional patterns and increased cellular heterogeneity after treatment (Figure 2A,2B). During network construction, we determined that a soft-thresholding power of four achieved a scale-free topology fit index of ~0.90 (Figure 2C), providing an optimal balance between network sensitivity and scale-free topology. In total, 15 gene co-expression modules were detected (Figure 2D). The module-trait correlation analysis highlighted one module in particular, that is, the “turquoise” module (module 5). This module was strongly positively correlated with PR status and negatively correlated with Ki67 status (Figure 2E)—features characteristic of luminal A tumors—indicating that this module is associated with radioresistant phenotypes in ER⁺/HER2⁻ disease. We next characterized the hub genes in the PR-high/Ki67-low (“turquoise”) module that were associated with radioresistant phenotypes. Violin plots and module eigengene scoring demonstrated that the hub genes of module 5 were most highly expressed in epithelial cells (Figure 2F,2G). This finding suggests that the hub genes of this module were associated with transcriptional programs observed in radiotherapy-exposed tumor cells.

Figure 2 hdWGCNA uncovered key gene modules in post-radiotherapy ER⁺ breast tumors. (A,B) Comparison of cell type distributions in tumors before and after radiotherapy. (C) A scale-free topology analysis identified β=4 as the optimal soft-thresholding power for network construction. (D) Dendrogram of co-expressed genes grouped into 15 modules via hdWGCNA. (E) Heatmap of correlations between each module’s eigengene and clinical traits (PR positivity and Ki67 status), highlighting the turquoise module’s positive association with PR and negative association with Ki67. Asterisks indicate the statistical significance of the module-trait correlations (*, P<0.05; **, P<0.01; ***, P<0.001). (F) Violin plot showing the expression distribution of the module 5 hub genes across different cell lineages, with higher expression levels observed in tumor cells. (G) t-SNE plot of tumor cells colored by the module 5 eigengene expression level. cN, clinical node; ER⁺, estrogen receptor-positive; hdWGCNA, high-dimensional weighted gene co-expression network analysis; hME, high module eigengene; PR, progesterone receptor; RT, radiotherapy; t-SNE, t-distributed stochastic neighbor embedding.

Validation of the high-affinity binding between theaflavin and CLIC6

We next performed a pathway enrichment analysis of the hub genes in module 5. The results revealed significant enrichment in the ubiquitin-mediated proteolysis, MAPK, Wnt, Hedgehog, and Notch signaling pathways (Kyoto Encyclopedia of Genes and Genomes; Figure 3A). These pathways are associated with DNA repair, cell proliferation, stemness, and tumor-microenvironment crosstalk, indicating potential links to transcriptional programs related to DNA damage response and apoptosis regulation. The Gene Ontology analysis indicated hub gene enrichment in RNA metabolism, organelle and cytoskeletal organization, and metabolic regulation, primarily localized to the cytosol and nucleoplasm (Figure 3B), implying broad reprogramming supporting radioprotection.

Figure 3 Functional profiling of a radioresistance-associated hub gene network identified CLIC6. (A) KEGG pathway enrichment of module 5 hub genes. (B) GO enrichment analysis. (C) Overlap between module 5 hub genes and PR⁺vs. PR⁻ DEGs in TCGA-BRCA, identifying seven candidates. (D) Expression changes of candidate genes in epithelial cells before and after radiotherapy. Blue bars indicate genes upregulated after radiotherapy (post − pre >0), whereas red bars indicate genes downregulated after radiotherapy (post − pre <0). (E) Violin plot of CLIC6 expression pre- and post-radiotherapy. (F) Differential expression of hub genes and association between CLIC6 and the IRDS score. Blue bars indicate genes upregulated after radiotherapy (post − pre >0), whereas red bars indicate genes downregulated after radiotherapy (post − pre <0). (G) Violin plot showing higher IRDS scores in CLIC6-positive cells. (H,I) Predicted 3D docking pose and 2D interaction diagram of theaflavin binding to CLIC6. *, P<0.05. 2D, two-dimensional; 3D, three-dimensional; BRCA, breast invasive carcinoma; CLIC6, chloride intracellular channel 6; DEG, differentially expressed gene; Expr, expression; GO, Gene Ontology; hdWGCNA, high-dimensional weighted gene co-expression network analysis; IRDS, interferon-related DNA damage resistance signature; KEGG, Kyoto Encyclopedia of Genes and Genomes; PR⁺, progesterone receptor-positive; PR⁻, progesterone receptor-negative; TCGA, The Cancer Genome Atlas.

We intersected these hub genes with the DEGs between PR-positive (PR⁺) and PR-negative (PR⁻) ER⁺/HER2⁻ tumors in the TCGA-BRCA dataset, and identified seven candidate genes associated with radiotherapy response; that is, CLIC6, LINC01768, GREB1, RGS22, GRIA2, CDHR3, and PI15 (Figure 3C). To investigate the potential roles of these hub genes in radiotherapy resistance, we examined their expression levels in epithelial cells before and after radiotherapy. The results showed that CLIC6, GREB1, RGS22, and CDHR3 were upregulated after radiotherapy, exhibiting a radioresistant expression pattern (Figure 3D). The violin plot further showed the expression changes in CLIC6 before and after radiotherapy (Figure 3E). Meanwhile, a published single-cell study provided a well-established interferon-related DNA damage resistance signature (IRDS) score, for which a higher score indicates stronger radioresistance (19). The differential expression analysis between the IRDS-high and IRDS-low groups revealed that CLIC6 showed the most statistically significant difference (Figure 3F). The violin plot further demonstrated the expression pattern of CLIC6 in relation to the IRDS score (Figure 3G).

To further investigate the role of CLIC6 in breast cancer cell lines and the molecular mechanisms underlying its function, additional validation experiments were conducted. Given the association of CLIC6 with radioresistance, we screened 659 natural compounds (see table available at https://cdn.amegroups.cn/static/public/tcr-2025-aw-2466-1.xlsx) for CLIC6-targeting potential using in silico docking, setting a binding energy of less than −6 kcal/mol as the threshold for high-affinity binding. Theaflavin showed high binding affinity, with theaflavin forming stable interactions within the CLIC6 pocket, including hydrogen bonds with Asp-510, Lys-511, and Lys-514 (2.1–2.2 Å), and hydrophobic contacts with Leu-461 (Figure 3H,3I), suggesting a high-affinity binding mode that may underlie the potential of theaflavin to interact with CLIC6 in a manner relevant to radiosensitivity.

Theaflavin reverses CLIC6-mediated radioresistance in ER+ breast cancer cells

To validate the roles of theaflavin and CLIC6 in ER⁺ breast cancer cells, we established stable overexpression and knockdown cell lines in MCF-7, T47D, and MDA-MB-231 breast cancer models (Figure 4A,4B). RT-qPCR analysis showed that baseline CLIC6 expression was significantly higher in ER⁺ luminal breast cancer cells (MCF-7, T47D) than in the ER⁻ basal-like cell line MDA-MB-231 (Figure S1A). To determine whether theaflavin has intrinsic cytotoxicity independent of irradiation, we included a theaflavin-only control group. In MCF-7 cells, theaflavin treatment alone did not significantly decrease colony formation compared with the vehicle control (P>0.05), indicating minimal intrinsic cytotoxicity at the concentration used (Figure S1B). Functional validation in MCF-7 and T47D models demonstrated that CLIC6 overexpression significantly increased radioresistance, consistent with enhanced cell survival after irradiation. Theaflavin treatment significantly enhanced radiosensitivity in both the wild-type and CLIC6-overexpressing cells, supporting a CLIC6-dependent effect on radiosensitivity. Conversely, the knockdown of CLIC6 alone increased radiosensitivity, and the addition of theaflavin provided no further effect, suggesting that the radiosensitizing function of theaflavin is dependent on the presence of CLIC6 (Figure 4C-4E). Quantitative analysis of colony-forming units was performed by counting colonies containing ≥50 cells and calculating the surviving fraction relative to the non-irradiated vector control. These quantitative data are provided in Figure S1C-S1E. Additionally, in the ER⁻ breast cancer cell line MDA-MB-231, we established stable CLIC6 overexpression and knockdown lines and found that these effects were not observed (Figure 4F-4H). These results suggest that theaflavin reverses radioresistance in a CLIC6-dependent manner, indicating its potential as a radiosensitizer for ER⁺/HER2⁻ breast cancer.

Figure 4 A CLIC6-centric prognostic model and the validation of theaflavin as a radiosensitizer. (A,B) Quantitative real-time polymerase chain reaction confirmation of CLIC6 overexpression in MCF-7, T47D, and MDA-MB-231 cells vs. vector control and CLIC6 knockdown in the MCF-7, T47D, and MDA-MB-231 cells vs. shRNA scramble control. (C-E) Colony formation assay of the MCF-7 (C), T47D (D), and MDA-MB-231 (E) cells under different conditions after 6 Gy irradiation, with colonies stained using 0.1% crystal violet. (F-H) CCK-8 cell viability assay of the MCF-7 (F), T47D (G), and MDA-MB-231 (H) cells under different conditions after 6 Gy irradiation. *, P<0.05; **, P<0.01; ***, P<0.001; ns, not significant (P>0.05). CCK-8, Cell Counting Kit-8; CLIC6, chloride intracellular channel 6; KD, knockdown; mRNA, messenger RNA; OE, overexpression; shRNA, short-hairpin RNA; Thf, theaflavin.

Discussion

This study identified the CLIC6 gene associated with radiotherapy resistance in ER⁺/HER2⁻ breast cancer. By integrating single-cell and bulk transcriptomic data analyses, we identified a gene co-expression module with luminal A characteristics (PR⁺/Ki67-low) that is associated with intrinsic radioresistance. The hub genes of this module were enriched in pathways related to DNA repair, cell cycle regulation, and tumor-stromal interactions, suggesting that these networks may be linked to transcriptional programs associated with the cellular response to radiation-induced stress. We demonstrated that CLIC6 overexpression increases radioresistance, while its pharmacological inhibition with theaflavin restores radiosensitivity.

Our findings extend the understanding of the CLIC protein family in cancer biology. While CLIC1 and CLIC4 have been implicated in tumor progression, metastasis, and therapy resistance, CLIC6 has remained largely unstudied (20-22). We show that CLIC6 confers radioresistance, highlighting its potential as a biomarker for stratifying patients by radiotherapy response. Mechanistically, CLIC6 may contribute to radioresistance by maintaining intracellular ion homeostasis and influencing DNA damage repair pathways. Through virtual screening, we identified theaflavin as a natural inhibitor of CLIC6. Functional assays confirmed that theaflavin enhances radiosensitivity primarily through CLIC6 targeting, as its effect was abrogated upon CLIC6 knockdown. These results suggest that targeting CLIC6 could be a promising strategy for overcoming radioresistance in ER⁺ breast cancer. The lack of theaflavin-induced radiosensitization in MDA-MB-231 cells is most likely due to low endogenous CLIC6 expression, leading to insufficient target availability, rather than differences in ER status. It is important to note that our bioinformatic analyses reveal transcriptomic associations rather than causal relationships, and mechanistic conclusions were restricted to findings directly supported by functional experiments. The identified CLIC6-associated gene modules should therefore be interpreted as correlation-based signatures, and further experimental studies will be required to establish causality.

CLIC family proteins can function as intracellular chloride channels that regulate membrane potential, organellar pH, and cell volume, which are tightly linked to DNA damage response and apoptosis signaling. Previous studies on CLIC1/CLIC4 have implicated these channels in oxidative stress regulation, mitochondrial apoptosis, and therapy resistance in epithelial cancers (21,22). Together with our functional data, these findings support a working model in which CLIC6 promotes radioresistance by modulating ion homeostasis-dependent stress signaling, thereby attenuating radiation-induced apoptosis and/or facilitating DNA damage repair. Future studies will test this hypothesis by examining γ-H2AX foci resolution, RAD51 recruitment, and caspase activation following CLIC6 perturbation under irradiation.

A key strength of this study lies in the integration of single-cell and bulk transcriptomic data, which enabled the dissection of intratumoral heterogeneity and may enhance the clinical translatability of the proposed therapeutic strategy. Unlike traditional bulk analyses, the single-cell resolution enabled the identification of luminal A-specific resistant modules at the epithelial cell level. Further, the workflow connecting bioinformatics, molecular docking, and functional validation provided a complete “target-to-compound” framework, illustrating the integrative and translational depth of this approach. The focus on the PR⁺/Ki67-low luminal A subgroup also ensured higher clinical relevance for precision radiotherapy.

Compared with previous studies on radiosensitizers (23-25), which have mainly focused on ferroptosis, oxidative stress, or DNA damage repair [e.g., dihydroartemisinin (26) or RSL3 (26,27)], our study highlights an alternative perspective centered on chloride ion homeostasis and intracellular channel regulation. This CLIC6-associated pathway broadens the biological spectrum of radioresistance beyond redox signaling and highlights a novel ion-transport-based target for sensitization. Moreover, few previous studies have specifically addressed the luminal A subgroup, making our work one of the first to delineate its radioresistant transcriptomic landscape at the single-cell level.

Our study had a number of limitations. First, the sample size was modest; larger cohorts and additional models are needed to generalize our findings. Second, the downstream mechanisms by which CLIC6 influences DNA repair or apoptosis were not fully elucidated and require further molecular study. Third, the bioavailability of theaflavin in vivo may be limited (28), necessitating formulation improvements or the identification of more potent analogues. Additional multi-algorithm docking validation (e.g., AutoDock4, PLP, ChemScore) may further strengthen the robustness of the computational predictions and will be considered in future work. In addition, validation using more ER⁺ luminal A cell lines and patient-derived models will be incorporated into future experiments to strengthen the robustness of the conclusions. Future single-cell studies should involve larger and better-annotated luminal A patient cohorts, ideally including treatment outcome information, to further enhance the generalizability and translational relevance of our findings.

Theaflavin and its derivatives may serve as promising candidates as safe, natural radiosensitizers in combination therapy. Future research should include biochemical and biophysical confirmation of direct CLIC6-theaflavin binding (e.g., SPR, ITC, BLI, or MST), as well as mutational validation of key residues such as Asp510, Lys511, Lys514, and Leu461. Moreover, in vivo evaluation using patient-derived xenografts or organoid models will be critical to verify pharmacokinetics, efficacy, and safety of theaflavin require further investigation. Optimization through medicinal chemistry or nanoformulation strategies may further enhance the clinical applicability of CLIC6-targeted radiosensitization.

Conclusions

Our findings suggest that CLIC6 may serve as a novel biomarker and a potential therapeutic target associated with radiotherapy resistance in ER⁺/HER2⁻ breast cancer. We provided proof-of-concept that theaflavin may function as a natural radiosensitizer in a CLIC6-dependent manner. These findings offer novel insights into radiotherapy response and suggest targeted strategies to improve outcomes for patients with this common subtype.

Acknowledgments

We would like to thank the School of Medicine, Nankai University, for providing laboratory support. We would also like to thank Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, for providing computational resources, as well as Aislyn Schalck and colleagues for making their scRNA-seq dataset (BioProject ID: PRJNA818695) publicly available, and TCGA Research Network for generating and providing access to the BRCA dataset.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-aw-2466/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-aw-2466/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-aw-2466/prf

Funding: This work was supported by the Tianjin Metrology Science and Technology Project (No. 2025TJMT009), the Tianjin Enterprise Science and Technology Commissioner Support Project (No. 25YDTPJC00050), the Tianjin Major Special Project for Public Health Science and Technology (No. 24ZXGQSY00030), the National Natural Science Foundation of China (No. 82202595), and the Tianjin Municipal Education Commission (No. 2021KJ262).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-aw-2466/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024;74:229-63. [Crossref] [PubMed]
2. López-Velazco JI, Manzano S, Elorriaga K, et al. Molecular characterisation of the residual disease after neoadjuvant endocrine therapy in ER+/HER2- breast cancer uncovers biomarkers of tumour response. Transl Oncol 2025;57:102407. [Crossref] [PubMed]
3. Wang K, Li L, Franch-Expósito S, et al. Integrated multi-omics profiling of high-grade estrogen receptor-positive, HER2-negative breast cancer. Mol Oncol 2022;16:2413-31. [Crossref] [PubMed]
4. Sood N, Maurya R, Gautam S, et al. Comprehensive advances in HER2-positive and HER2-negative breast cancer: unveiling molecular mechanisms and exploring cutting-edge targeted therapies for enhanced patient outcomes. Naunyn Schmiedebergs Arch Pharmacol 2025;398:14877-98. [Crossref] [PubMed]
5. Bruss C, Albert V, Seitz S, et al. Neoadjuvant radiotherapy in ER(+), HER2(+), and triple-negative -specific breast cancer based humanized tumor mice enhances anti-PD-L1 treatment efficacy. Front Immunol 2024;15:1355130. [Crossref] [PubMed]
6. Roncati L. Adjuvant Metronomic Chemotherapy After Surgery in pT1-T2 N0 M0 HER2-Positive and ER/PR-Positive Breast Cancer Plus Targeted Therapy, Anti-Hormonal Therapy, and Radiotherapy, with or Without Immunotherapy: A New Operational Proposal. Cancers (Basel) 2025;17:1323. [Crossref] [PubMed]
7. Kanno M, Kano S, Imamura Y, et al. Palliative systemic therapy for locally advanced or metastatic salivary duct carcinoma: A comprehensive review. Cancer Treat Rev 2025;139:102993. [Crossref] [PubMed]
8. Tsai CJ, Yang JT, Shaverdian N, et al. Standard-of-care systemic therapy with or without stereotactic body radiotherapy in patients with oligoprogressive breast cancer or non-small-cell lung cancer (Consolidative Use of Radiotherapy to Block CURB oligoprogression): an open-label, randomised, controlled, phase 2 study. Lancet 2024;403:171-82.
9. Li Z, Wei H, Li S, et al. The Role of Progesterone Receptors in Breast Cancer. Drug Des Devel Ther 2022;16:305-14. [Crossref] [PubMed]
10. Liu Y, Li J, Li H, et al. Radiotherapy is recommended for hormone receptor-negative older breast cancer patients after breast conserving surgery. Sci Rep 2024;14:21355. [Crossref] [PubMed]
11. Srivastava TP, Dhar R, Karmakar S. Looking beyond the ER, PR, and HER2: what's new in the ARsenal for combating breast cancer? Reprod Biol Endocrinol 2025;23:9. [Crossref] [PubMed]
12. Wei D, Wang L, Zuo X, et al. A Small Molecule with Big Impact: MRTX1133 Targets the KRASG12D Mutation in Pancreatic Cancer. Clin Cancer Res 2024;30:655-62. [Crossref] [PubMed]
13. Zhang Y, Cao S, Zeng F, et al. Dihydroartemisinin enhances the radiosensitivity of breast cancer by targeting ferroptosis signaling pathway through hsa_circ_0001610. Eur J Pharmacol 2024;983:176943. [Crossref] [PubMed]
14. Wojtera B, Ostrowska K, Szewczyk M, et al. Chloride intracellular channels in oncology as potential novel biomarkers and personalized therapy targets: a systematic review. Rep Pract Oncol Radiother 2024;29:258-70. [Crossref] [PubMed]
15. Zhou H, Xi Y, Chen X. Chloride intracellular channel 6 inhibits hepatocellular carcinoma progression by modulating immune cell balance and promoting tumor cell apoptosis. Cytojournal 2025;22:20. [Crossref] [PubMed]
16. O'Neill EJ, Termini D, Albano A, et al. Anti-Cancer Properties of Theaflavins. Molecules 2021;26:987. [Crossref] [PubMed]
17. NCBI BioProject. Radiotherapy Remodeling of the Breast Tumor Microenvironment Identified by Single Cell Omic Analysis. 2022. Available online: https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA818695
18. Ferofontov A, Giladi M, Haitin Y. The crystal structure of mouse chloride intracellular channel protein 6. RCSB Protein Data Bank. 2017. Available online: https://doi.org/10.2210/pdb6ERZ/pdb
19. Schalck A, Tran T, Li J, et al. The impact of breast radiotherapy on the tumor genome and immune ecosystem. Cell Rep 2025;44:115703. [Crossref] [PubMed]
20. Renard HF, Boucrot E. Unconventional endocytic mechanisms. Curr Opin Cell Biol 2021;71:120-9. [Crossref] [PubMed]
21. Goldmann O, Medina E. Revisiting Pathogen Exploitation of Clathrin-Independent Endocytosis: Mechanisms and Implications. Cells 2025;14:731. [Crossref] [PubMed]
22. Doherty GJ, McMahon HT. Mechanisms of endocytosis. Annu Rev Biochem 2009;78:857-902. [Crossref] [PubMed]
23. Beddok A, Willmann J, Embring A, et al. Reirradiation: Standards, challenges, and patient-focused strategies across tumor types. CA Cancer J Clin 2025;75:630-66. [Crossref] [PubMed]
24. Ding Q, Rha H, Yoon C, et al. Regulated cell death mechanisms in mitochondria-targeted phototherapy. J Control Release 2025;382:113720. [Crossref] [PubMed]
25. Wang Y, Yang B, Liu S, et al. Semiconductor-mediated radiosensitizers: progress, challenges and perspectives. Mater Horiz 2025;12:3598-621. [Crossref] [PubMed]
26. Qi Y, Yan J, Huang X, et al. Targeting tumor-associated macrophage polarization with traditional Chinese medicine active ingredients: Dual reversal of chemoresistance and immunosuppression in tumor microenvironment. Pharmacol Res 2025;216:107788. [Crossref] [PubMed]
27. Dawi J, Affa S, Kafaja K, et al. The Role of Ferroptosis and Cuproptosis in Tuberculosis Pathogenesis: Implications for Therapeutic Strategies. Curr Issues Mol Biol 2025;47:99. [Crossref] [PubMed]
28. Li M, Li W, Dong Y, et al. Advances in metabolism pathways of theaflavins: digestion, absorption, distribution and degradation. Crit Rev Food Sci Nutr 2025;65:4195-203. [Crossref] [PubMed]