Next Article in Journal
The Role of miRNAs in the Differential Diagnosis of Alzheimer’s Disease and Major Depression: A Bioinformatics-Based Approach
Previous Article in Journal
A Perspective on the Role of Mitochondrial Biomolecular Condensates (mtBCs) in Neurodegenerative Diseases and Evolutionary Links to Bacterial BCs
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 26
Issue 17
10.3390/ijms26178219
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Profiling of Breast Cancer Stem Cell Types/States Shows the Role of CD44hi/CD24lo-ALDH1hi as an Independent Prognostic Factor After Neoadjuvant Chemotherapy

by
Hazem Ghebeh
1,2,*,
Jumanah Y. Mirza
1,
Taher Al-Tweigeri
3,
Monther Al-Alwan
1,2 and
Asma Tulbah
4
1
Cell Therapy and Immunobiology Department, King Faisal Specialist Hospital & Research Centre, P.O. Box 3354, Riyadh 11211, Saudi Arabia
2
College of Medicine, Al-Faisal University, Riyadh 11533, Saudi Arabia
3
Oncology Centre, King Faisal Specialist Hospital & Research Centre, Riyadh 11211, Saudi Arabia
4
Department of Pathology, King Faisal Specialist Hospital & Research Centre, Riyadh 11211, Saudi Arabia
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2025, 26(17), 8219; https://doi.org/10.3390/ijms26178219
Submission received: 17 July 2025 / Revised: 7 August 2025 / Accepted: 22 August 2025 / Published: 24 August 2025
(This article belongs to the Section Molecular Oncology)
Browse Figures
Review Reports Versions Notes

Abstract

Multiple markers exist for breast cancer stem cells (CSCs), which are believed to represent the phenotypes of various CSC types and/or states. The relationship between each CSC subpopulation/state and the primary hallmarks of cancer has not been sufficiently clarified. In this study, six CSC markers (CD44hi/CD24lo, CD24, Ep-CAM, ALDH1, CD10, and BMI1) were assessed in a surgical cohort of 73 breast cancer patients. The expression of a single or multiple CSC markers was correlated with clinicopathological parameters, including markers of immune evasion, proliferation, epithelial–mesenchymal transition (EMT), and survival. All CSC phenotypes, except for CD10, correlated with markers indicative of higher proliferation. The CD44hi/CD24lo phenotype correlated with markers of EMT and PD-L1 expression, unlike ALDH1hi. Both Ep-CAMhi and CD24hi breast cancer were associated with indicators of immune evasion, including PD-L1 expression, and the infiltration of FOXP3+ and PD-1+ tumor-infiltrating lymphocytes (TIL). While the CD44hi/CD24lo, Ep-CAMhi, and ALDH1hi phenotypes correlated with shorter overall survival (OS), CD24hi correlated with reduced disease-free survival (DFS). Interestingly, among all tested CSC markers, the CD44hi/CD24lo-ALDH1hi combination phenotype correlated with the worst DFS (HR 2.8, p = 0.014 in univariate/multivariate analysis) and OS (p < 0.001, HR 6.4 in univariate and 5.4 in multivariate analysis). A side-by-side comparison of multiple CSC markers demonstrated the differential linkage of CSC phenotype/state with distinct features of breast cancer. This comparison demonstrates the advantage of the CD44hi/CD24lo-ALDH1hi combination marker for prognostication, especially after neoadjuvant chemotherapy. In the future, distinct markers of CSCs can hopefully be leveraged to trace/monitor different disease characteristics or treatment outcomes.

1. Introduction

A subpopulation of cancer cells, known as cancer stem cells (CSCs), is responsible for maintaining and regenerating tumors. In principle, CSCs are therapy-resistant and have higher metastatic capabilities [1]. The CD44hi/CD24lo phenotype and the ALDH1hi trait are the most commonly used markers to identify CSCs in breast cancer [1]. Additionally, other markers for CSCs in breast cancer have been reported, including Ep-CAMhi [2], the CD44hi/CD24lo-Ep-CAMhi combination [3,4,5], CD10 [6], CD24hi [7], and BMI1 [8]. While one could assume that CSCs are a single population with multiple markers, several reports have demonstrated the existence of different CSC subpopulations [9]. The demonstration of a dynamic relationship between these subpopulations [10] suggests the existence of diverse CSCs in different dynamic states.
The role of the immune response in the surveillance and elimination of cancer cells is well-established [11]. However, strong evidence indicates that CSCs can interact with immune cells differently from the bulk of the tumor cells [12]. Despite this, the specific CSC subpopulation or state correlating with immunosuppressive cells or environments remains understudied. We have previously shown that the immune checkpoint PD-L1 is overexpressed in CSCs and is correlated with CD44hi/CD24lo in breast cancer cell lines [13,14]. In contrast, there was no correlation between PD-L1 expression and ALDHhi cancer cells [14]. The CSC type or state linked to PD-L1 expression has not been sufficiently explored.
In this study, we utilized immunohistochemistry to characterize CSCs in breast cancer patients using multiple reported CSC markers. We investigated the correlation of each CSC type/state with markers of immune evasion (including PD-L1 expression and the infiltration of FOXP3+ and PD-1+ TIL), cell proliferation, and Epithelial-to-Mesenchymal Transition (EMT). Additionally, we evaluated the prognostic significance of these markers individually and in conjunction with other clinicopathological parameters. While CD44hi/CD24lo, Ep-CAMhi, and their combination (i.e., CD44hi/CD24lo-Ep-CAMhi) showed significant correlation with PD-L1 expression, a marker of immune evasion, ALDH1, CD10, or BMI1 did not. The combination of CD44hi/CD24lo-ALDH1hi emerged as the most prognostic among all tested CSC markers. These markers could serve as valuable tools for monitoring disease progression during treatment, and the combined targeting of ALDH1hi and CD44hi/CD24lo phenotypes may represent the most effective strategy to eliminate CSCs and address breast cancer at its roots.

2. Results

2.1. Patient Characteristics

All patients were females with breast cancer and a median age of 43 years. A substantial proportion (47%) had large tumors (≥4 cm), and nearly half (49%) had histologic grade 3 tumors. The majority (64%) showed lymph node involvement. Most patients (63%) had luminal (A or B) subtype tumors, while 16% had the HER2-enriched subtype, and 21% had triple-negative breast cancer (TNBC) (Supplementary Table S1).
Among the cohort, 43 patients received neoadjuvant chemotherapy. Of these, 37 were treated with a combination of doxorubicin (Adriamycin®, Pfizer, New York, NY, USA) and cyclophosphamide (AC), while 6 received other regimens. Among the 37 patients who received AC, 21 also received fluorouracil as part of the FAC regimen, +/− docetaxel, 9 received only docetaxel following AC, while the remaining 7 received AC alone.

2.2. CD44hi/CD24lo CSCs Phenotype Correlates with EMT, Proliferation, and PD-L1 Expression

Combined high expression of CD44 with low or absent expression of CD24 (CD44hi/CD24lo) is one of the most commonly used markers to identify CSCs in breast cancer [3]. The CD44hi/CD24lo phenotype was positive in 33% of the tested cohort of breast cancer patients (Figure 1A). The CD44hi/CD24lo phenotype partially correlated with markers of immune evasion, showing significance with PD-L1 expression (p = 0.001), but not with FOXP3+ or PD-1+ TIL (Table 1A). Moreover, the CD44hi/CD24lo phenotype significantly correlated with Ki-67-positive status (p = 0.024) (Table 1A), high histological grade (p = 0.013), and estrogen receptor (ER) negative status (p = 0.002) (Table 1B). Notably, CD44hi/CD24lo significantly correlated with markers of EMT, including vimentin overexpression (p < 0.001), loss of E-cadherin (p = 0.015), and the combination of vimentin overexpression and loss of E-cadherin (p < 0.001) (Table 1B).
Around half (55%) of tumors had cancer cells that were double positive for CD44 and CD24. There was no significant correlation between this double positive and any of the tested bad prognostic factors.

2.3. Ep-CAMhi Phenotype Correlates with EMT, Proliferation, and Immune Evasion

Ep-CAM was overexpressed in 43% of the examined breast cancer cases (Figure 1A). Ep-CAMhi cases significantly correlated with markers of immune evasion, namely PD-L1 expression (p = 0.019), FOXP3+ TIL (p = 0.012), and higher TIL (p = 0.024) in general, along with a borderline correlation with PD-1+ TIL (p = 0.052, Table 1A). There was a significant association between Ep-CAMhi cells and markers of proliferation, namely Ki-67 (p = 0.018), loss of the cell cycle inhibitor p27 expression (p = 0.031), and the combined loss of p21 and p27 expression (p = 0.029). Furthermore, Ep-CAMhi significantly correlated with larger tumor size (p = 0.036), negative status for ER (p = 0.008) and progesterone receptors (PR, p = 0.005), and TNBC status (p = 0.008) (Table 1B). Additionally, Ep-CAMhi expression significantly correlated with breast cancer cases exhibiting combined vimentin overexpression and loss of E-cadherin (p = 0.045) (Table 1B), a strong feature of EMT.
We have further examined cases that had combined overexpression of Ep-CAM and the CD44hi/CD24lo phenotype (CD44hi/CD24lo-Ep-CAMhi), which was present in 16% of the studied cases. CD44hi/CD24lo-Ep-CAMhi significantly correlated with PD-L1 expression (p = 0.008) and the proliferation marker Ki-67 (p = 0.024) (Table 1A). In addition, the CD44hi/CD24lo-Ep-CAMhi phenotype significantly correlated with the negativity status of ER (p = 0.007) and PR (p = 0.009), and TNBC status (p = 0.002) (Table 1B). Importantly, there was a significant correlation between CD44hi/CD24lo-Ep-CAMhi and markers of EMT, as demonstrated by vimentin overexpression (p = 0.005), loss of E-cadherin (p = 0.005), and cases with combined vimentin overexpression and loss of E-cadherin (p = 0.002) (Table 1B).
Altogether, CD44hi/CD24lo, Ep-CAM overexpression, and/or their combination (CD44hi/CD24lo-Ep-CAMhi) correlated with PD-L1 expression, higher proliferation, EMT, and ER-negative status.

2.4. CD24 Overexpression Correlates with Markers of Immune Evasion and Higher Proliferation

CD24 was expressed in the luminal epithelial cells of the normal-like breast ducts. CD24 was overexpressed in 34% of the tested breast cancer cases (Figure 1B). Interestingly, CD24 overexpression significantly correlated with markers of immune evasion including PD-L1 (p = 0.013), FOXP3+ CD3 + TIL (p = 0.001), and PD-1+ TIL (p = 0.032) as well as markers of proliferation Ki-67 (p = 0.048) and SKP2 (p = 0.002) expression, and the combined loss of p21/p27 (p = 0.014) (Supplementary Table S2A). Moreover, CD24 overexpression significantly correlated with high histological grade (p = 0.007), ER-negative status (p = 0.005), and vimentin overexpression (p = 0.030) (Supplementary Table S2B).

2.5. ALDH1hi Phenotype Correlates with Higher Proliferation

ALDH1 expression is another very important marker that is used to identify CSCs in breast cancer. In our cohort of breast cancer patients, ALDH1 was mostly expressed by the mesenchymal cells and some normal mammary glands with hyperplasia. ALDH1 expression in tumor cells was observed in 30% of the breast cancer cases (Figure 1B). ALDH1 expression correlated with markers of higher proliferation, including loss of p27 (p = 0.041), and borderline correlation with Ki-67 (p = 0.074) (Table 2A), larger tumor size (p < 0.001), and higher histological grade (p = 0.011) (Table 2B). There was no significant correlation between ALDH1hi and PD-L1 expression or other markers of immune evasion (Table 2A). Interestingly, there was a correlation between ALDH1hi and higher TIL (p = 0.015).
Cases that had combined overexpression of the CD44hi/CD24lo phenotype and ALDH1hi (CD44hi/CD24lo-ALDH1hi) were observed in 11% of examined cases. Similar to what has been observed with ALDH1hi alone, there was no significant correlation between CD44hi/CD24lo-ALDH1hi and PD-L1 expression or other markers of immune evasion (Table 2A). However, it showed a significant correlation with larger tumor size (p = 0.022) and higher histological grade (p = 0.028) (Table 2B). CD44hi/CD24lo-ALDH1hi significantly correlated with ER-negative status (p = 0.045) and vimentin overexpression (p = 0.049) (Table 2B).
On the other hand, having a combined Ep-CAMhi and ALDH1hi phenotype constituted 15% of the breast cancer cases. Like ALDHhi tumors, Ep-CAMhi/ALDH1hi breast cancers significantly correlated with markers of higher proliferation, including Ki-67 positivity status, combined loss of p21/p27 (p = 0.002) (Table 2A), and larger tumor size (p = 0.019) (Table 2B) in addition to ER negative status (p = 0.015). Similarly, Ep-CAMhi/ALDH1hi cases did not correlate with PD-L1 expression or other markers of immune evasion, despite a significant correlation with higher TIL infiltration (p = 0.011) (Table 2A).
Altogether, ALDH1hi alone and in combination with CD44hi/CD24lo or Ep-CAMhi correlated with a higher proliferation rate, while it showed no consistent correlation with markers of immune evasion.
CD10 was mainly expressed by the myoepithelial/basal cells of normal-like breast ducts and stroma/mesenchymal cells in some breast cancer tissues. CD10 was overexpressed in cancer cells in 15% of breast cancer cases (Figure 1C). CD10 overexpression did not correlate with PD-L1 expression, other markers of immune evasion (Supplementary Table S2A), or any other clinicopathological parameter (Supplementary Table S2B). On the other hand, BMI1 overexpression (27% of cases, Figure 1C) showed paradoxically significant inverse correlation with FOXP3+ CD3+ TIL (p = 0.008), loss of p27 (p = 0.002), and the combined loss of p21/p27 expression (p = 0.006) (Supplementary Table S2A), tumor size (p = 0.003), and ER negative status (p = 0.049) (Supplementary Table S2B). Altogether, CD10 showed no correlation with any of the tested markers, while BMI1 overexpression inversely correlated with some markers of immune evasion and cell proliferation.

2.6. The CD44hi/CD24lo-ALDHhi Combination Correlated with Shorter DFS and OS in Neoadjuvant Chemotherapy-Receiving Patients

We then tested the correlation between different CSC markers and patient outcomes by assessing disease-free survival (DFS) and overall survival (OS). Among all tested CSC markers, CD44hi/CD24lo-ALDHhi and CD24hi correlated significantly with shorter DFS (p = 0.019 and p = 0.010, respectively) (Figure 2A). On the other hand, CD44hi/CD24lo, Ep-CAMhi, and ALDHhi CSC markers significantly correlated with shorter OS (p = 0.033, p = 0.028, and p = 0.005, respectively). Meanwhile, the correlation significance of Ep-CAMhi/ALDHhi with OS was borderline (p = 0.051) (Figure 2B). Remarkably, the CD44hi/CD24lo-ALDHhi combination marker correlated significantly with shorter OS (p < 0.001). Paradoxically, BMI1 did not behave as a CSC marker as its overexpression showed significant inverse correlation with DFS and OS (p = 0.037 and p = 0.022, respectively).
As the CD44hi/CD24lo-ALDHhi combination significantly correlated with DFS and OS, we performed a subgroup analysis to determine in which subpopulations this CD44hi/CD24lo-ALDHhi combination would show correlation with survival. Data stratification analysis revealed a highly significant correlation between CD44hi/CD24lo-ALDH1hi tumors and DFS and OS (p < 0.001) in patients receiving neoadjuvant chemotherapy. On the other hand, in neoadjuvant chemo-naïve patients, CD44hi/CD24lo-ALDH1hi significantly correlated with OS (p = 0.016) but not with DFS (Figure 3A).
Further stratification of patients receiving specific types of neoadjuvant chemotherapy revealed that CD44hi/CD24lo-ALDHhi tumors were significantly associated with DFS (p = 0.001) and OS (p < 0.001) among patients treated with Adriamycin/cyclophosphamide (AC; n = 37), and also showed significant associations with DFS (p = 0.025) and OS (p < 0.001) among those treated with fluorouracil/Adriamycin/cyclophosphamide (FAC; n = 21) (Supplementary Figure S1).
To understand the contribution of each CSC marker component, subgroup analysis was performed for ALDHhi and CD44hi/CD24lo, separately, revealing that ALDH1hi tumors significantly correlated with OS (p < 0.001) and DFS (p = 0.012) in patients receiving neoadjuvant chemotherapy, but not in neoadjuvant chemotherapy-naïve patients (Supplementary Figure S2A). Similarly, CD44hi/CD24lo significantly correlated with OS (p = 0.017) in neoadjuvant chemo patients and not chemo-naïve patients (Supplementary Figure S2B). However, the separation in Kaplan–Meier curves was more significant in CD44hi/CD24lo-ALDHhi tumors than in ALDHhi tumors or CD44hi/CD24lo tumors.
Further subgrouping into breast cancer subtypes within neoadjuvant chemotherapy-receiving patients demonstrated that CD44hi/CD24lo-ALDHhi significantly correlated with DFS and OS in both triple-negative breast cancer (TNBC) patients (p = 0.006 and p < 0.001, respectively) and non-TNBC patients (p < 0.001 for both DFS and OS) (Figure 3B).
Altogether, only the CD44hi/CD24lo-ALDHhi CSC combination marker correlated significantly with shorter DFS and OS, which was more pronounced in patients who received neoadjuvant chemotherapy.

2.7. CD44hi/CD24lo-ALDH1hi Is an Independent Prognostic Factor for Worse Survival

In univariate analysis, breast cancer cases with CD24hi or CD44hi/CD24lo-ALDH1hi positive phenotype significantly correlated with DFS (p = 0.014 and p = 0.022, respectively) (Table 3). In multivariate analysis, CD44hi/CD24lo-ALDH1hi showed a significant correlation with DFS (p = 0.014), as well as CD24hi (p = 0.023).
Since several CSC markers showed significant correlation with survival using Kaplan–Meier survival analysis, we conducted a Cox proportional hazards analysis to further identify CSC markers that can serve as independent prognostic factors. Initially, univariate Cox regression of individual CSC markers and their combinations revealed that CD44hi/CD24lo, Ep-CAMhi, ALDH1hi, and the CD44hi/CD24lo-ALDH1hi combination were significantly associated with shorter OS (Table 3). However, BMI1 showed an inverse correlation with OS (p = 0.027), which was inconsistent with its role as a CSC marker, leading to its exclusion from further analysis. In multivariate analysis, we included CSC markers that showed significant correlation with survival in our univariate analysis, except CD44hi/CD24lo-ALDH1hi (excluded to avoid multicollinearity with its individual components). CD44hi/CD24lo (p = 0.039) and ALDH1hi (p = 0.009) showed significant correlations with OS, whereas Ep-CAMhi lost significance. Rerunning the multivariate analysis while including the CD44hi/CD24lo-ALDH1hi combination CSC marker and avoiding its individual components (ALDHhi and CD44hi/CD24lo) demonstrated a significant correlation with OS (p < 0.001) while Ep-CAMhi lost significance (Table 3). Altogether, CD44hi/CD24lo-ALDH1hi was an independent prognostic factor for worse DFS and OS, as shown by univariate and multivariate Cox regression hazards analysis.
In summary, the vast majority of CSC markers and their combinations were significantly associated with the expression of proliferation markers (Table 4), with the exception of CD10, while BMI1 correlated inversely with proliferation. Similarly, almost all CSC phenotypes correlated with ER-negative status. On the other hand, significant correlations were observed with EMT and immune evasion markers for CD44hi/CD24lo, Ep-CAMhi, the CD44hi/CD24lo-Ep-CAMhi combination, and CD24hi, but not for ALDH1hi, the combinations CD44hi/CD24lo-ALDH1hi, or Ep-CAMhi/ALDH1hi. Overall, the CD44hi/CD24lo-ALDH1hi combination CSC marker was an independent prognostic factor for survival, which was more significant in patients receiving neoadjuvant chemotherapy.

3. Discussion

Cancer stem cells (CSCs) can exist in different types or states within the same tumor, which can be identified by specific phenotypic or functional markers [10]. Both intrinsic and extrinsic factors drive the capacity of CSCs to self-renew, proliferate, and metastasize [15]. The state/type that is associated with a specific cancer trait has not been well established. In the current study, we investigated the association between various CSC markers and key oncogenic traits in breast cancer. This report shows that the most common feature of all tested CSC markers was their association with higher proliferation and estrogen receptor negativity. Importantly, we have demonstrated for the first time that breast tumors with CD24hi or Ep-CAMhi CSCs were associated with markers of immune evasion, while CD44hi/CD24lo and Ep-CAMhi CSCs were associated with features of EMT. On the other hand, the combination of CD44hi/CD24lo-ALDH1hi correlated with worse survival, especially in patients receiving neoadjuvant chemotherapy.
We have previously shown, using multi-parametric flow cytometry, that the expression of PD-L1 is higher in breast CSC-like cells with the CD44hi/CD24lo phenotype, but not in ALDHhi cells. Whether this could be validated in breast cancer patients remained an intriguing question. In this report, we demonstrated, using breast cancer patient samples, that PD-L1 expression significantly correlates with CD44hi/CD24lo but not with ALDH1hi. The results in this report align with the previously reported correlation between PD-L1 and CD44hi/CD24lo [16], but contradict the earlier reported correlation of PD-L1 with ALDH1 by Flores et al. [17]. This discrepancy could be due to the variation in the anti-ALDH1 antibody used. We utilized the ALDH1 antibody (clone 44/ALDH), while Flores et al. employed an antibody from Abcam (the clone was not specified). Additionally, we report for the first time that PD-L1 expression in breast cancer correlates with Ep-CAMhi, another marker for CSCs, and the combination of CD44hi/CD24lo-Ep-CAMhi, as well as CD24hi. Specifically, Ep-CAMhi and CD24hi showed association with multiple markers of immune evasion.
Our findings were consistent with previous data showing a correlation between CD44hi/CD24lo phenotype and high histological grade [18], ER negativity status [18,19,20], Ki-67 positivity status [20,21], and vimentin upregulation [22]. In the process of EMT, epithelial cells upregulate CD44 and downregulate CD24 [23]. Indeed, in the current study, breast cancer with CD44hi/CD24lo cells showed a significant correlation with standard markers of EMT, specifically the upregulation of vimentin and downregulation of E-cadherin, which is consistent with previous reports on the relationship between EMT and CSCs [23,24,25]. On the other hand, the effect of CD44hi/CD24lo on survival has been inconsistent in previous studies. While a few reports have demonstrated a correlation with survival [19,26], the majority did not [27]. In this report, we have shown a correlation with OS but not with DFS. The discrepancy in the results of CD44hi/CD24lo previously reported in breast cancer was possibly due to differences in the (1) scoring method, (2) the CD24 antibody used especially clone SN3b, which is not very specific [28], (3) the intensity of CD44 or CD24 that was considered positive, and (4) whether the cohort of breast cancer patients used have received neoadjuvant chemotherapy therapy or not. In the current study, we have used a very well-established CD24 antibody (clone ML5) [28]. Scorings of CD24 were considered low/negative (CD24lo) if they were totally negative or below the intensity of normal epithelial ducts, which is considered +1 intensity of CD24, and neoadjuvant patients were analyzed separately, demonstrating that the correlation of CD44hi/CD24lo was with patients who received neoadjuvant chemotherapy (Supplementary Figure S2B).
In this report, overexpression of Ep-CAM (Ep-CAMhi) was associated with higher tumor size, hormone receptor negativity status, and Ki-67 positivity status, which is consistent with previous reports that used the exact antibody clone (VU-1D9) and scoring method (H-score) [29,30,31]. We have further shown for the first time the correlation of Ep-CAMhi with the loss of p27 and the loss of both p21/p27 in breast cancer, consistent with the correlation of Ep-CAM with a higher proliferation rate. We have shown in this report for the first time the correlation of Ep-CAMhi with makers of immune evasion, namely higher expression of PD-L1, higher infiltration with FOXP3 + TIL (T-reg), and PD-1+ TIL. Indeed, Chen et al. demonstrated the role of Ep-CAM signaling in promoting PD-L1 expression and the significant correlation of Ep-CAM expression with PD-L1 expression in lung cancer [32]. Furthermore, Zheng et al. have shown that Ep-CAM, as a tumor-associated antigen, promoted a Th2 type of immune response and tumor immune evasion [33]. Ep-CAM overexpression significantly correlated with worse OS, which was consistent with previously reported data [30,31,34,35].
CD24 has an established role in immune evasion through the binding to Siglec-10 in macrophages [36] and natural killer cells [37]. To our knowledge, this is the first study to report on the correlation of CD24 expression with immune evasion in breast cancer, including PD-L1 expression, FOXP3 + TIL, and PD-1 + TIL. Further studies are warranted to investigate whether such interaction creates an appropriate microenvironment for the accumulation of immune suppressive lymphocytes like FOXP3 + TIL and PD-1 + TIL, and whether CD24 expression can functionally affect the clinical outcomes.
The fact that CD24 is an important driver of cell proliferation in many types of cancer [38], including breast cancer [39,40], is consistent with its correlation with Ki-67, SKP2 expression, and the lack of p21 and p27 cell cycle checkpoints expression that we observed in our breast cancer samples. In addition, CD24 was reported to be downregulated by estrogen [41], which is consistent with the correlation between CD24 overexpression and ER negativity status we observed in this report.
While previous studies have shown a significant association between ALDH1 expression and overall survival, the data in the literature have not been consistent on this correlation. Our finding that ALDH1 was highly associated with both DFS and OS only in neoadjuvant chemotherapy-receiving patients (Supplementary Figure S2A) is consistent with previous reports [42,43]. Importantly, this is the first report to demonstrate a highly significant correlation between CD44hi/CD24lo-ALDH1hi and survival (OS and DFS) in patients receiving neoadjuvant chemotherapy. The fact that the tissues were surgical samples suggests that CSCs with the CD44hi/CD24lo-ALDH1hi phenotypes are resistant to chemotherapy, as their existence had the highest prognostication ability among all other tested CSC markers.
Our findings of no correlation between ALDH1 and other immune evasion markers, such as FOXP3 + TIL and PD-1 + TIL, disagree with those of Seo et al. [44], which demonstrated a significant correlation between ALDH1 and FOXP3 + TIL. This discrepancy is most likely due to the scoring method Seo et al. used, which only considered high-intensity ALDH1 and a 10% cutoff. Indeed, if we used their scoring method, we would obtain a significant correlation with FOXP3 + TIL but not with PD-L1 or PD-1 + TIL in our dataset. Similar to Seo et al., this scoring method will give a positivity rate of 10% in our cohort of breast cancer patients, but this percentage is far from the average positivity of 20–50% seen in most of the 15 studies related to ALDH1 in breast cancer that were reviewed by Liu et al. [45]. In contrast to our study, Seo et al. [44] did not study PD-1 + TIL or PD-L1 in cancer cells. It is worth mentioning in this regard that several studies have demonstrated a correlation between ALDH1 expression and other immune evasion markers, such as the myeloid suppressor-derived cells (MSDC) [46], which was not studied in this report.
CD10 did not correlate with any clinicopathological parameters, although it showed a trend of correlation with ER and PR negativity status, as previously reported [47]. A larger cohort of breast cancer patients may be needed, as only a small percentage (15%; n = 11) of our breast cancer patients showed CD10 positivity.
BMI1 is a component of the polycomb group complex 1, an essential epigenetic repressor of multiple regulatory genes and a driver for breast CSCs [8,48]. The literature has been inconsistent on the prognostic role of BMI1 in breast cancer. Choi et al. [49] have shown that BMI1 is a good prognostic factor, which is consistent with the results in the current report. Conversely, Wang et al. [50] have shown that BMI1 is a bad prognostic factor in breast cancer. Althobiti et al. [51] attempted to reconcile the difference by demonstrating that the prognostic effect of BMI1 is breast cancer subtype-dependent, as it is a favorable prognostic factor in luminal breast cancer and an unfavorable prognostic factor in TNBC. However, even if the patients in this report were segregated into different subtypes, the trend is still towards good prognosis in all subtypes, although the significance would be lost due to the small number in each subtype.
Previously, it was shown that patients with multiple CSC markers have worse survival [21]. However, which combination has the most significant correlation with survival was not addressed. In our study, we have shown that only the CD44hi/CD24lo and ALDH1 combination significantly correlates with DFS and OS, especially in neoadjuvant chemotherapy-receiving breast cancer patients, and this was observed in both TNBC and non-TNBC subtypes.
One limitation of our study is that it relies on a small cohort of breast cancer patients who were treated between 2004 and 2010, an era before immunotherapy and before neoadjuvant anti-HER2 therapy, which might affect the DFS and OS. Therefore, findings in this report should be confirmed in an independent recent cohort of breast cancer patients. On the other hand, the advantage of this cohort is the long-term survival data and the accumulated data we had from previous studies. Another limitation of this study is that we have studied breast cancer as a whole, although we tried our best to mitigate this by subgroup analysis; however, subtype-focused studies should be carried out in the future to confirm these findings.

4. Materials and Methods

4.1. Patients

This study was conducted under the Helsinki Declaration and approved by the Institutional Review Board of King Faisal Specialist Hospital and Research Centre (KFSH&RC). The archived FFPE tissues were surgical tumor tissues excised as lumpectomy or mastectomy from patients diagnosed with invasive ductal carcinoma (IDC), as previously described [52,53]. All patients provided informed consent.

4.2. Immunohistochemistry

Sections (4 microns) of formalin-fixed paraffin-embedded (FFPE) breast cancer tissue blocks were dewaxed in xylene and rehydrated with gradients of alcohol and water. Antigen retrieval took place in the Decloaking Chamber pressure cooker (Biocare, Pacheco, CA, USA), as detailed in Table 5. Endogenous peroxidase was quenched using 0.9% H2O2, while endogenous biotin was blocked with biotin and avidin, along with three washes in between. Primary antibodies, diluted in 1% BSA, were incubated overnight at 4 °C. For the CD44/CD24 analysis, the two-species double-staining method was employed (CD44 is a rabbit antibody, while CD24 is a mouse antibody). A biotinylated streptavidin Alkaline Phosphatase (AP) anti-mouse secondary antibody was utilized, followed by Envision anti-rabbit horseradish peroxidase (HRP) (Agilent, Dako, Glostrup, Denmark). In the case of single staining for Ep-CAM, ALDH1, and BMI1, the secondary antibody used was either Envision anti-mouse or a biotinylated antibody (Jackson Laboratories, Bar Harbor, ME, USA) (Table 5). Color development was accomplished using Fast Red (30 min) and/or DAB (10 min). All washes were conducted using TBST. CD10, PD-L1, and Vimentin immunohistochemistry were performed using the fully automated Ventana Benchmark Ultra system with Ventana primary antibodies, as previously described in detail [52,54]. Data on Vimentin/E-cadherin expression, as well as SKP2/p21/p27, were obtained from two previously published studies on the same patient cohort [52,55]. On the other hand, FOXP3 and PD-1 data were derived from prior work conducted on frozen tissue sections from the same cohort [56].
Scoring of CSCs was performed by an anatomical pathologist (AT) using 5–10% increments. Borderline CD44hi (i.e., 10%) was considered positive only if the intensity was ≥2+. Due to high heterogeneity, we used the H-score system to score ALDH1, Ep-CAM, and CD24 expression in cancer cells. The data were further dichotomized using 35, 200, and 140 as cutoffs for ALDH1, Ep-CAM, and CD24, respectively. All cutoffs were determined using the receiver operating characteristic (ROC) curve/Youden index.

4.3. Statistical Analysis

The correlation between CSC markers and hallmarks of cancer (categorical variables) was evaluated using Fisher’s exact test. Survival plots were generated using the Kaplan–Meier method, and the curves were compared using the log-rank test. The univariate and multivariate Cox proportional hazards models were used to test the correlation with survival. Time was censored for patients who were alive or disease-free at the last follow-up, including patients lost to follow-up. All analyses, including the ROC curve/Youden index analyses, were performed using JMP statistical software (version 15; SAS Institute, Cary, NC, USA), and a p-value of 0.05 was set as the threshold for significance.

5. Conclusions

Multiple markers have been identified for breast cancer stem cells (CSCs), reflecting the heterogeneity of their phenotypes and states. Despite their differences, CSCs defined by these markers share common oncogenic characteristics, such as their association with estrogen receptor (ER) negativity and markers of higher proliferative rate. Certain phenotypes—including CD44hi/CD24lo, EpCAMhi, and CD24hi, and the CD44hi/CD24lo-EpCAMhi combination—are also associated with features of epithelial-to-mesenchymal transition (EMT) and immune evasion. Moreover, certain CSC markers, such as CD44hi/CD24lo, EpCAMhi, and ALDH1hi, have been linked to poorer overall survival. Notably, the CD44hi/CD24lo-ALDH1hi combination emerged as the most significant independent prognostic factor for survival, particularly in patients who received neoadjuvant chemotherapy. The choice of CSC marker depends on the features/hallmarks features or hallmarks under investigation. In the future, distinct CSC markers can be leveraged to trace/monitor various disease characteristics or treatment outcomes.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms26178219/s1.

Author Contributions

H.G. (the principal investigator) conceived and designed the study, collected and analyzed the data, performed data analysis and interpretation, including statistical analysis, supervised all study aspects, and wrote the manuscript; J.Y.M. collected, analyzed, and interpreted data (IHC); T.A.-T. and M.A.-A. edited the manuscript; A.T. (anatomical pathologist) analyzed and interpreted the data (scoring and reading all IHC sections). All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the King Faisal Specialist Hospital & Research Centre project (under RAC# 2190-002).

Institutional Review Board Statement

This study was conducted under the Helsinki Declaration and approved by the Institutional Review Board of King Faisal Specialist Hospital and Research Centre (KFSH&RC). This work was reviewed by the designated IRB of the King Faisal Specialist Hospital & Research Centre project (RAC# 2190-002), approved 3 March 2019.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data generated in this current study are included in this published article (and its supplementary information files), otherwise available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

PD-L1Programmed death ligand-1
CSCsCancer Stem Cells
EMTEpithelial-to-Mesenchymal Transition

References

  1. McDermott, S.P.; Wicha, M.S. Targeting breast cancer stem cells. Mol. Oncol. 2010, 4, 404–419. [Google Scholar] [CrossRef]
  2. Hiraga, T.; Ito, S.; Nakamura, H. EpCAM expression in breast cancer cells is associated with enhanced bone metastasis formation. Int. J. Cancer 2016, 138, 1698–1708. [Google Scholar] [CrossRef]
  3. Al-Hajj, M.; Wicha, M.S.; Benito-Hernandez, A.; Morrison, S.J.; Clarke, M.F. Prospective identification of tumorigenic breast cancer cells. Proc. Natl. Acad. Sci. USA 2003, 100, 3983–3988. [Google Scholar] [CrossRef]
  4. Ghebeh, H.; Sleiman, G.M.; Manogaran, P.S.; Al-Mazrou, A.; Barhoush, E.; Al-Mohanna, F.H.; Tulbah, A.; Al-Faqeeh, K.; Adra, C.N. Profiling of normal and malignant breast tissue show CD44high/CD24low phenotype as a predominant stem/progenitor marker when used in combination with Ep-CAM/CD49f markers. BMC Cancer 2013, 13, 289. [Google Scholar] [CrossRef] [PubMed]
  5. Fillmore, C.M.; Kuperwasser, C. Human breast cancer cell lines contain stem-like cells that self-renew, give rise to phenotypically diverse progeny and survive chemotherapy. Breast Cancer Res. 2008, 10, R25. [Google Scholar] [CrossRef] [PubMed]
  6. Maguer-Satta, V.; Besancon, R.; Bachelard-Cascales, E. Concise review: Neutral endopeptidase (CD10): A multifaceted environment actor in stem cells, physiological mechanisms, and cancer. Stem Cells 2011, 29, 389–396. [Google Scholar] [CrossRef] [PubMed]
  7. Deng, X.; Apple, S.; Zhao, H.; Song, J.; Lee, M.; Luo, W.; Wu, X.; Chung, D.; Pietras, R.J.; Chang, H.R. CD24 Expression and differential resistance to chemotherapy in triple-negative breast cancer. Oncotarget 2017, 8, 38294–38308. [Google Scholar] [CrossRef]
  8. Srinivasan, M.; Bharali, D.J.; Sudha, T.; Khedr, M.; Guest, I.; Sell, S.; Glinsky, G.V.; Mousa, S.A. Downregulation of Bmi1 in breast cancer stem cells suppresses tumor growth and proliferation. Oncotarget 2017, 8, 38731–38742. [Google Scholar] [CrossRef]
  9. Liu, S.; Cong, Y.; Wang, D.; Sun, Y.; Deng, L.; Liu, Y.; Martin-Trevino, R.; Shang, L.; McDermott, S.P.; Landis, M.D.; et al. Breast cancer stem cells transition between epithelial and mesenchymal states reflective of their normal counterparts. Stem Cell Rep. 2014, 2, 78–91. [Google Scholar] [CrossRef]
  10. Warrier, N.M.; Kelkar, N.; Johnson, C.T.; Govindarajan, T.; Prabhu, V.; Kumar, P. Understanding cancer stem cells and plasticity: Towards better therapeutics. Eur. J. Cell Biol. 2023, 102, 151321. [Google Scholar] [CrossRef]
  11. Butterfield, L.H.; Howard, L.; Kaufman, M.D.F.; Francesco, M.; Marincola, M.D.F. Cancer Immunotherapy Principles and Practice, 2nd ed.; Springer Publishing Company: New York, NY, USA, 2021. [Google Scholar]
  12. Guha, A.; Goswami, K.K.; Sultana, J.; Ganguly, N.; Choudhury, P.R.; Chakravarti, M.; Bhuniya, A.; Sarkar, A.; Bera, S.; Dhar, S.; et al. Cancer stem cell-immune cell crosstalk in breast tumor microenvironment: A determinant of therapeutic facet. Front. Immunol. 2023, 14, 1245421. [Google Scholar] [CrossRef]
  13. Almozyan, S.; Colak, D.; Mansour, F.; Alaiya, A.; Al-Harazi, O.; Qattan, A.; Al-Mohanna, F.; Al-Alwan, M.; Ghebeh, H. PD-L1 promotes OCT4 and Nanog expression in breast cancer stem cells by sustaining PI3K/AKT pathway activation. Int. J. Cancer 2017, 141, 1402–1412. [Google Scholar] [CrossRef]
  14. Mansour, F.A.; Al-Mazrou, A.; Al-Mohanna, F.; Al-Alwan, M.; Ghebeh, H. PD-L1 is overexpressed on breast cancer stem cells through notch3/mTOR axis. Oncoimmunology 2020, 9, 1729299. [Google Scholar] [CrossRef]
  15. Ponomarev, A.; Gilazieva, Z.; Solovyeva, V.; Allegrucci, C.; Rizvanov, A. Intrinsic and Extrinsic Factors Impacting Cancer Stemness and Tumor Progression. Cancers 2022, 14, 970. [Google Scholar] [CrossRef] [PubMed]
  16. Polónia, A.; Pinto, R.; Cameselle-Teijeiro, J.F.; Schmitt, F.C.; Paredes, J. Prognostic value of stromal tumour infiltrating lymphocytes and programmed cell death-ligand 1 expression in breast cancer. J. Clin. Pathol. 2017, 70, 860–867. [Google Scholar] [CrossRef]
  17. Flores, M.L.; Franco, E.H.; Cousido, L.F.S.; Minguito-Carazo, C.; Guadarrama, O.S.; González, L.L.; Pascual, M.E.V.; de la Torre, A.J.M.; Palomo, A.G.; González, A.L. Relationship between Aldehyde Dehydrogenase, PD-L1 and Tumor-Infiltrating Lymphocytes with Pathologic Response and Survival in Breast Cancer. Cancers 2022, 14, 4418. [Google Scholar] [CrossRef]
  18. Guler, G.; Balci, S.; Costinean, S.; Ussakli, C.H.; Irkkan, C.; Suren, D.; Sari, E.; Altundag, K.; Ozisik, Y.; Jones, S.; et al. Stem cell-related markers in primary breast cancers and associated metastatic lesions. Mod. Pathol. 2012, 25, 949–955. [Google Scholar] [CrossRef] [PubMed]
  19. Chen, Y.; Song, J.; Jiang, Y.; Yu, C.; Ma, Z. Predictive value of CD44 and CD24 for prognosis and chemotherapy response in invasive breast ductal carcinoma. Int. J. Clin. Exp. Pathol. 2015, 8, 11287–11295. [Google Scholar]
  20. Lee, H.E.; Kim, J.H.; Kim, Y.J.; Choi, S.Y.; Kim, S.W.; Kang, E.; Chung, I.Y.; Kim, I.A.; Kim, E.J.; Choi, Y.; et al. An increase in cancer stem cell population after primary systemic therapy is a poor prognostic factor in breast cancer. Br. J. Cancer 2011, 104, 1730–1738. [Google Scholar] [CrossRef]
  21. Ali, H.R.; Dawson, S.J.; Blows, F.M.; Provenzano, E.; Pharoah, P.D.; Caldas, C. Cancer stem cell markers in breast cancer: Pathological, clinical and prognostic significance. Breast Cancer Res. 2011, 13, R118. [Google Scholar] [CrossRef] [PubMed]
  22. Ricardo, S.; Vieira, A.F.; Gerhard, R.; Leitao, D.; Pinto, R.; Cameselle-Teijeiro, J.F.; Milanezi, F.; Schmitt, F.; Paredes, J. Breast cancer stem cell markers CD44, CD24 and ALDH1: Expression distribution within intrinsic molecular subtype. J. Clin. Pathol. 2011, 64, 937–946. [Google Scholar] [CrossRef]
  23. Mani, S.A.; Guo, W.; Liao, M.J.; Eaton, E.N.; Ayyanan, A.; Zhou, A.Y.; Brooks, M.; Reinhard, F.; Zhang, C.C.; Shipitsin, M.; et al. The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell 2008, 133, 704–715. [Google Scholar] [CrossRef]
  24. Blick, T.; Hugo, H.; Widodo, E.; Waltham, M.; Pinto, C.; Mani, S.A.; Weinberg, R.A.; Neve, R.M.; Lenburg, M.E.; Thompson, E.W. Epithelial mesenchymal transition traits in human breast cancer cell lines parallel the CD44(hi/)CD24 (lo/-) stem cell phenotype in human breast cancer. J. Mammary Gland. Biol. Neoplasia 2010, 15, 235–252. [Google Scholar] [CrossRef]
  25. May, C.D.; Sphyris, N.; Evans, K.W.; Werden, S.J.; Guo, W.; Mani, S.A. Epithelial-mesenchymal transition and cancer stem cells: A dangerously dynamic duo in breast cancer progression. Breast Cancer Res. 2011, 13, 202. [Google Scholar] [CrossRef] [PubMed]
  26. Zhao, H.S.; Tang, H.T.; Xiao, Q.H.; He, M.; Zhao, L.; Fu, Y.Z.; Wu, H.Z.; Yu, Z.J.; Jiang, Q.; Yan, Y.Y.; et al. The Hedgehog signaling pathway is associated with poor prognosis in breast cancer patients with the CD44/CD24 phenotype. Mol. Med. Rep. 2016, 14, 5261–5270. [Google Scholar] [CrossRef]
  27. Wang, Z.; Wang, Q.Q.; Wang, Q.; Wang, Y.P.; Chen, J. Prognostic significance of CD24 and CD44 in breast cancer: A meta-analysis. Int. J. Biol. Marker 2017, 32, E75–E82. [Google Scholar] [CrossRef] [PubMed]
  28. Kristiansen, G.; Machado, E.; Bretz, N.; Rupp, C.; Winzer, K.J.; Konig, A.K.; Moldenhauer, G.; Marme, F.; Costa, J.; Altevogt, P. Molecular and clinical dissection of CD24 antibody specificity by a comprehensive comparative analysis. Lab. Investig. 2010, 90, 1102–1116. [Google Scholar] [CrossRef]
  29. Abd El-Maqsoud, N.M.; Abd El-Rehim, D.M. Clinicopathologic implications of EpCAM and Sox2 expression in breast cancer. Clin. Breast Cancer 2014, 14, e1–e9. [Google Scholar] [CrossRef]
  30. Agboola, A.J.; Paish, E.C.; Rakha, E.A.; Powe, D.G.; Macmillan, R.D.; Ellis, I.O.; Green, A.R. EpCAM expression is an indicator of recurrence in basal-like breast cancer. Breast Cancer Res. Tr. 2012, 133, 575–582. [Google Scholar] [CrossRef]
  31. Soysal, S.D.; Muenst, S.; Barbie, T.; Fleming, T.; Gao, F.; Spizzo, G.; Oertli, D.; Viehl, C.T.; Obermann, E.C.; Gillanders, W.E. EpCAM expression varies significantly and is differentially associated with prognosis in the luminal B HER2+, basal-like, and HER2 intrinsic subtypes of breast cancer. Br. J. Surg. 2013, 100, 11–12. [Google Scholar] [CrossRef] [PubMed]
  32. Chen, H.N.; Liang, K.H.; Lai, J.K.; Lan, C.H.; Liao, M.Y.; Hung, S.H.; Chuang, Y.T.; Chen, K.C.; Tsuei, W.W.F.; Wu, H.C. EpCAM Signaling Promotes Tumor Progression and Protein Stability of PD-L1 through the EGFR Pathway. Cancer Res. 2020, 80, 5035–5050. [Google Scholar] [CrossRef]
  33. Zheng, X.; Fan, X.; Fu, B.; Zheng, M.; Zhang, A.; Zhong, K.; Yan, J.; Sun, R.; Tian, Z.; Wei, H. EpCAM Inhibition Sensitizes Chemoresistant Leukemia to Immune Surveillance. Cancer Res. 2017, 77, 482–493. [Google Scholar] [CrossRef]
  34. Spizzo, G.; Went, P.; Dirnhofer, S.; Obrist, P.; Simon, R.; Spichtin, H.; Maurer, R.; Metzger, U.; von Castelberg, B.; Bart, R.; et al. High Ep-CAM expression is associated with poor prognosis in node-positive breast cancer. Breast Cancer Res. Treat. 2004, 86, 207–213. [Google Scholar] [CrossRef] [PubMed]
  35. Gastl, G.; Spizzo, G.; Obrist, P.; Dünser, M.; Mikuz, G. Ep-CAM overexpression in breast cancer as a predictor of survival. Lancet 2000, 356, 1981–1982. [Google Scholar] [CrossRef]
  36. Barkal, A.A.; Brewer, R.E.; Markovic, M.; Kowarsky, M.; Barkal, S.A.; Zaro, B.W.; Krishnan, V.; Hatakeyama, J.; Dorigo, O.; Barkal, L.J.; et al. CD24 signalling through macrophage Siglec-10 is a target for cancer immunotherapy. Nature 2019, 572, 392–396. [Google Scholar] [CrossRef] [PubMed]
  37. Zhang, P.; Lu, X.M.; Tao, K.X.; Shi, L.; Li, W.; Wang, G.B.; Wu, K. Siglec-10 is associated with survival and natural killer cell dysfunction in hepatocellular carcinoma. J. Surg. Res. 2015, 194, 107–113. [Google Scholar] [CrossRef] [PubMed]
  38. Li, L.; Chen, J.; Ge, C.; Zhao, F.; Chen, T.; Tian, H.; Li, J.; Li, H. CD24 isoform a promotes cell proliferation, migration and invasion and is downregulated by EGR1 in hepatocellular carcinoma. OncoTargets Ther. 2019, 12, 1705–1716. [Google Scholar] [CrossRef]
  39. Smith, S.C.; Oxford, G.; Wu, Z.; Nitz, M.D.; Conaway, M.; Frierson, H.F.; Hampton, G.; Theodorescu, D. The metastasis-associated gene CD24 is regulated by Ral GTPase and is a mediator of cell proliferation and survival in human cancer. Cancer Res. 2006, 66, 1917–1922. [Google Scholar] [CrossRef]
  40. Lee, K.M.; Ju, J.H.; Jang, K.; Yang, W.; Yi, J.Y.; Noh, D.Y.; Shin, I. CD24 regulates cell proliferation and transforming growth factor beta-induced epithelial to mesenchymal transition through modulation of integrin beta1 stability. Cell Signal 2012, 24, 2132–2142. [Google Scholar] [CrossRef]
  41. Kaipparettu, B.A.; Malik, S.; Konduri, S.D.; Liu, W.; Rokavec, M.; van der Kuip, H.; Hoppe, R.; Hammerich-Hille, S.; Fritz, P.; Schroth, W.; et al. Estrogen-mediated downregulation of CD24 in breast cancer cells. Int. J. Cancer 2008, 123, 66–72, Erratum in Int. J. Cancer 2019, 145, E21. [Google Scholar] [CrossRef]
  42. Khoury, T.; Ademuyiwa, F.O.; Chandrasekhar, R.; Jabbour, M.; Deleo, A.; Ferrone, S.; Wang, Y.; Wang, X. Aldehyde dehydrogenase 1A1 expression in breast cancer is associated with stage, triple negativity, and outcome to neoadjuvant chemotherapy. Mod. Pathol. 2012, 25, 388–397, Erratum in Mod. Pathol. 2012, 25, 917. [Google Scholar] [CrossRef]
  43. Li, J.; Zhang, B.; Yang, Y.F.; Jin, J.; Liu, Y.H. Aldehyde dehydrogenase 1 as a predictor of the neoadjuvant chemotherapy response in breast cancer: A meta-analysis. Medicine 2018, 97, e12056. [Google Scholar] [CrossRef]
  44. Seo, A.N.; Lee, H.J.; Kim, E.J.; Kim, H.J.; Jang, M.H.; Lee, H.E.; Kim, Y.J.; Kim, J.H.; Park, S.Y. Tumour-infiltrating CD8+lymphocytes as an independent predictive factor for pathological complete response to primary systemic therapy in breast cancer. Br. J. Cancer 2013, 109, 2705–2713. [Google Scholar] [CrossRef] [PubMed]
  45. Liu, Y.; Lv, D.L.; Duan, J.J.; Xu, S.L.; Zhang, J.F.; Yang, X.J.; Zhang, X.; Cui, Y.H.; Bian, X.W.; Yu, S.C. ALDH1A1 expression correlates with clinicopathologic features and poor prognosis of breast cancer patients: A systematic review and meta-analysis. BMC Cancer 2014, 14, 444. [Google Scholar] [CrossRef] [PubMed]
  46. Peng, D.; Tanikawa, T.; Li, W.; Zhao, L.; Vatan, L.; Szeliga, W.; Wan, S.; Wei, S.; Wang, Y.; Liu, Y.; et al. Myeloid-Derived Suppressor Cells Endow Stem-like Qualities to Breast Cancer Cells through IL6/STAT3 and NO/NOTCH Cross-talk Signaling. Cancer Res. 2016, 76, 3156–3165. [Google Scholar] [CrossRef] [PubMed]
  47. Louhichi, T.; Saad, H.; Ben Dhiab, M.; Ziadi, S.; Trimeche, M. Stromal CD10 expression in breast cancer correlates with tumor invasion and cancer stem cell phenotype. BMC Cancer 2018, 18, 49. [Google Scholar] [CrossRef]
  48. Lee, Y.C.; Chang, W.W.; Chen, Y.Y.; Tsai, Y.H.; Chou, Y.H.; Tseng, H.C.; Chen, H.L.; Wu, C.C.; Chang-Chien, J.; Lee, H.T.; et al. Hsp90α Mediates BMI1 Expression in Breast Cancer Stem/Progenitor Cells through Facilitating Nuclear Translocation of c-Myc and EZH2. Int. J. Mol. Sci. 2017, 18, 1986. [Google Scholar] [CrossRef]
  49. Choi, Y.J.; Choi, Y.L.; Cho, E.Y.; Shin, Y.K.; Sung, K.W.; Hwang, Y.K.; Lee, S.J.; Kong, G.; Lee, J.E.; Kim, J.S.; et al. Expression of Bmi-1 protein in tumor tissues is associated with favorable prognosis in breast cancer patients. Breast Cancer Res. Tr. 2009, 113, 83–93. [Google Scholar] [CrossRef]
  50. Wang, Y.Y.; Zhe, H.; Ding, Z.; Gao, P.; Zhang, N.M.; Li, G.F. Cancer Stem Cell Marker Bmi-1 Expression is Associated with Basal-like Phenotype and Poor Survival in Breast Cancer. World J. Surg. 2012, 36, 1189–1194. [Google Scholar] [CrossRef]
  51. Althobiti, M.; Muftah, A.A.; Aleskandarany, M.A.; Joseph, C.; Toss, M.S.; Green, A.; Rakha, E. The prognostic significance of BMI1 expression in invasive breast cancer is dependent on its molecular subtypes. Breast Cancer Res. Tr. 2020, 182, 581–589. [Google Scholar] [CrossRef]
  52. Alsuliman, A.; Colak, D.; Al-Harazi, O.; Fitwi, H.; Tulbah, A.; Al-Tweigeri, T.; Al-Alwan, M.; Ghebeh, H. Bidirectional crosstalk between PD-L1 expression and epithelial to mesenchymal transition: Significance in claudin-low breast cancer cells. Mol. Cancer 2015, 14, 149. [Google Scholar] [CrossRef]
  53. Ghebeh, H.; Tulbah, A.; Mohammed, S.; Elkum, N.; Bin Amer, S.M.; Al-Tweigeri, T.; Dermime, S. Expression of B7-H1 in breast cancer patients is strongly associated with high proliferative Ki-67-expressing tumor cells. Int. J. Cancer 2007, 121, 751–758. [Google Scholar] [CrossRef] [PubMed]
  54. Ghebeh, H.; Mansour, F.A.; Colak, D.; Alfuraydi, A.A.; Al-Thubiti, A.A.; Monies, D.; Al-Alwan, M.; Al-Tweigeri, T.; Tulbah, A. Higher PD-L1 Immunohistochemical Detection Signal in Frozen Compared to Matched Paraffin-Embedded Formalin-Fixed Tissues. Antibodies 2021, 10, 24. [Google Scholar] [CrossRef] [PubMed]
  55. Elfoly, M.; Mirza, J.Y.; Alaiya, A.; Al-Hazzani, A.A.; Tulbah, A.; Al-Alwan, M.; Ghebeh, H. PD-L1 intrinsically promotes the proliferation of breast cancer cells through the SKP2-p27/p21 axis. Cancer Cell Int. 2024, 24, 161. [Google Scholar] [CrossRef] [PubMed]
  56. Ghebeh, H.; Barhoush, E.; Tulbah, A.; Elkum, N.; Al-Tweigeri, T.; Dermime, S. FOXP3 Tregs and B7-HI+/PD-I+T lymphocytes co-infiltrate the tumor tissues of high-risk breast cancer patients:: Implication for immunotherapy. BMC Cancer 2008, 8, 57. [Google Scholar] [CrossRef]
Ijms 26 08219 g001aIjms 26 08219 g001b
Figure 1. Expression of cancer stem cell (CSC) markers in breast cancer tissue sections. Representative immunohistochemical images (magnification ×400) showing the expression of CSC-related markers in breast cancer tissues. (A) Dual staining for CD44 and CD24, showing membranous CD44 (brown) and cytoplasmic CD24 (purple) (top) and membranous Ep-CAM (bottom). (B) Cytoplasmic CD24 and ALDH1; note the positivity in stromal cells in the ALDH1lo image. (C) Membranous CD10 and nuclear BMI1.
Figure 1. Expression of cancer stem cell (CSC) markers in breast cancer tissue sections. Representative immunohistochemical images (magnification ×400) showing the expression of CSC-related markers in breast cancer tissues. (A) Dual staining for CD44 and CD24, showing membranous CD44 (brown) and cytoplasmic CD24 (purple) (top) and membranous Ep-CAM (bottom). (B) Cytoplasmic CD24 and ALDH1; note the positivity in stromal cells in the ALDH1lo image. (C) Membranous CD10 and nuclear BMI1.
Ijms 26 08219 g001aIjms 26 08219 g001b
Ijms 26 08219 g002aIjms 26 08219 g002b
Figure 2. Correlation of CSCs expression with the Survival of breast cancer patients. Kaplan-Meier survival curves showing the association between CSCs and disease-free survival (DFS) (A) or overall survival (OS) (B) of breast cancer patients. Statistical significance was determined using the log-rank test.
Figure 2. Correlation of CSCs expression with the Survival of breast cancer patients. Kaplan-Meier survival curves showing the association between CSCs and disease-free survival (DFS) (A) or overall survival (OS) (B) of breast cancer patients. Statistical significance was determined using the log-rank test.
Ijms 26 08219 g002aIjms 26 08219 g002b
Ijms 26 08219 g003
Figure 3. Subgroup analysis in neoadjuvant chemotherapy-receiving patients and TNBC patients. Kaplan–Meier survival curves illustrate the association between CD44hi/CD24lo-ALDHhi breast CSCs and disease-free survival (DFS) or overall survival (OS), depending on neoadjuvant chemotherapy status (A) and breast cancer subtype in neoadjuvant chemotherapy receiving patients (B). Statistical significance was determined using the log-rank test.
Figure 3. Subgroup analysis in neoadjuvant chemotherapy-receiving patients and TNBC patients. Kaplan–Meier survival curves illustrate the association between CD44hi/CD24lo-ALDHhi breast CSCs and disease-free survival (DFS) or overall survival (OS), depending on neoadjuvant chemotherapy status (A) and breast cancer subtype in neoadjuvant chemotherapy receiving patients (B). Statistical significance was determined using the log-rank test.
Ijms 26 08219 g003
Table 1. Correlation between CD44hi/CD24lo or Ep-CAMhi CSCs and immune /proliferation markers (A) or other clinicopathological parameters (B) in 73 breast cancer patients.
Table 1. Correlation between CD44hi/CD24lo or Ep-CAMhi CSCs and immune /proliferation markers (A) or other clinicopathological parameters (B) in 73 breast cancer patients.
(A)
CD44hi/CD24lo Ep-CAMhi CD44hi/CD24lo-Ep-CAMhi
<10%≥10%♣ pH-Score < 200H-Score ≥ 200♣ p−+♣ p
Immune MarkersPD-L1
<5%45 (76) *14 (24)0.00138 (64)21 (36)0.01953 (90)6 (10)0.008
≥5%4 (29)10 (71) 4 (29)10 (71) 8 (57)6 (43)
TIL
Low (Score 1 and 2)40 (70)17 (30)0.36937 (65)20 (35)0.02450 (88)7 (12)0.120
High (Score 3)9 (56)7 (44) 5 (31)11 (69) 11 (69)5 (31)
§ FOXP3 + TIL
<10%27 (73)10 (27)0.78426 (70)11 (30)0.01233 (89)4 (11)0.483
≥10%19 (68)9 (32) 11 (39)17 (61) 23 (82)5 (18)
§ PD-1 + TIL
<10%24 (75)8 (25)0.31423 (72)9 (28)0.05230 (94)2 (6)0.097
≥10%24 (63)14 (37) 18 (47)20 (53) 30 (79)8 (21)
Proliferation MarkersKi-67
<20%29 (81)7 (19)0.02426 (72)10 (28)0.01834 (94)2 (6)0.024
≥20%20 (54)17 (46) 16 (43)21 (57) 27 (73)10 (27)
§ SKP2
<10%35 (76)11 (24)0.06229 (63)17 (37)0.31440 (87)6 (13)0.322
≥10%13 (52)12 (48) 12 (48)13 (52) 19 (76)6 (24)
§ p21
<10%28 (65)15 (35)0.61522 (51)21 (49)0.22134 (79)9 (21)0.341
≥10%20 (71)8 (29) 19 (68)9 (32) 25 (89)3 (11)
§ p27
<50%33 (65)18 (35)0.57425 (49)26 (51)0.03141 (80)10 (20)0.488
≥50%15 (75)5 (25) 16 (80)4 (20) 18 (90)2 (10)
§ Loss of both p21/p27
NO17 (55)14 (45)0.07228 (70)12 (30)0.02923 (74)8 (26)0.112
YES31 (78)9 (23) 13 (42)18 (58) 36 (90)4 (10)
(B)
CD44hi CD24lo Ep-CAMhi CD44hi CD24lo/Ep-CAMhi
<10%≥10%♣ pH-Score < 200H-Score ≥ 200♣ p−+♣ p
Clinicopathological MarkersAge
<40 years14 (58) *10 (42)0.29713 (54)11 (46)0.80217 (71)7 (29)0.051
≥40 years35 (71)14 (29) 29 (59)20 (41) 44 (90)5 (10)
Tumor Size
<4 cm30 (77)9 (23)0.08127 (69)12 (31)0.03634 (87)5 (13)0.529
≥4 cm19 (56)15 (44) 15 (44)19 (56) 27 (79)7 (21)
Invasion
Absent21 (70)9 (30)0.80116 (53)14 (47)0.63325 (83)5 (17)1.000
Present28 (65)15 (35) 26 (60)17 (40) 36 (84)7 (16)
Histological Grade
1 and 230 (81)7 (19)0.01325 (68)12 (32)0.10034 (92)3 (8)0.064
319 (53)17 (47) 17 (47)19 (53) 27 (75)9 (25)
§ Lymph Node Metastasis
Absent18 (69)8 (31)1.00014 (54)12 (46)0.81020 (77)6 (23)0.331
Present31 (67)15 (33) 27 (59)19 (41) 40 (87)6 (13)
Neoadjuvant Chemotherapy
Absent21 (70)9 (30)0.80119 (63)11 (37)0.47627 (90)3 (10)0.337
Present28 (65)15 (35) 23 (54)20 (47) 34 (79)9 (21)
BC Subtype MarkersER Status
Negative12 (44)15 (56)0.00210 (37)17 (63)0.00818 (67)9 (33)0.007
Positive37 (80)9 (20) 32 (70)14 (30) 43 (93)3 (7)
PR Status
Negative23 (58)17 (42)0.08017 (42)23 (58)0.00529 (72)11 (28)0.009
Positive26 (79)7 (21) 25 (76)8 (24) 32 (97)1 (3)
HER2/neu Status
Negative33 (67)16 (33)1.00029 (59)20 (41)0.80240 (82)9 (18)0.739
Positive16 (67)8 (33) 13 (54)11 (46) 21 (88)3 (12)
TNBC Status
Negative42 (72)16 (28)0.07138 (66)20 (34)0.00953 (91)5 (9)0.002
Positive7 (47)8 (53) 4 (27)11 (73) 8 (53)7 (47)
EMT MarkersVimentin
Negative42 (82)9 (18)<0.00133 (65)18 (35)0.07447 (92)4 (8)0.005
Positive7 (32)15 (68) 9 (41)13 (59) 14 (64)8 (36)
Loss of E-Cadherin
Negative39 (76)12 (24)0.01532 (63)19 (37)0.20347 (92)4 (8)0.005
Positive10 (45)12 (55) 10 (45)12 (55) 14 (64)8 (36)
Vimentin/Loss of E-Cadherin
Negative47 (76)15 (24)<0.00139 (63)23 (37)0.04556 (90)6 (10)0.002
Positive2 (18)9 (82) 3 (27)8 (73) 5 (45)6 (55)
Abbreviations: * the numbers between brackets are the percentages of patients and ♣ p values in bold and shaded represent significant data. Light shading represents borderline significance. § PD-1 is unknown for 3 samples, FOXP3 is unknown for 6 samples. The status is unknown for SKP2, p21, p27, and loss of both p21/p27 status for 2 cases. The lymph node status is missing for one case.
Table 2. Correlation between ALDH1hi or other CSCs and immune /proliferation markers (A) or other clinicopathological parameters (B) in 73 breast cancer patients.
Table 2. Correlation between ALDH1hi or other CSCs and immune /proliferation markers (A) or other clinicopathological parameters (B) in 73 breast cancer patients.
(A)
ALDH1hi CD44hi/CD24lo-ALDH1hi Ep-CAMhi/ALDH1hi
H-Score < 35H-Score ≥ 35♣ p−+♣ p−+♣ p
Immune MarkersPD-L1
<5%41 (69) *18 (31)1.00054 (92)5 (8)0.17451 (86)8 (14)0.432
≥5%10 (71)4 (29) 11 (79)3 (21) 11 (79)3 (21)
TIL
Low (Score 1 and 2)44 (77)13 (23)0.01553 (93)4 (7)0.06452 (91)5 (9)0.011
High (Score 3)7 (44)9 (56) 12 (75)4 (25) 10 (62)6 (38)
§ FOXP3 + TIL
<10%29 (78)8 (22)0.17034 (92)3 (8)1.00033 (89)4 (11)0.483
≥10%17 (61)11 (39) 25 (89)3 (11) 23 (82)5 (18)
§  PD-1 + TIL
<10%24 (75)8 (25)0.60330 (94)2 (6)0.68129 (91)3 (9)0.494
≥10%26 (68)12 (32) 34 (89)4 (11) 32 (84)6 (16)
Proliferation MarkersKi-67
<20%29 (81)7 (19)0.07435 (97)1 (3)0.05634 (94)2 (6)0.046
≥20%22 (59)15 (41) 30 (81)7 (19) 28 (80)9 (20)
§ SKP2
<10%34 (74)12 (26)0.42342 (91)4 (9)0.44041 (89)5 (11)0.307
≥10%16 (64)9 (36) 21 (84)4 (16) 20 (80)5 (20)
§ p21
<10%29 (67)14 (33)0.59936 (84)7 (16)0.13634 (79)9 (21)0.077
≥10%21 (75)7 (25) 27 (96)1 (4) 27 (96)1 (4)
§ p27
<50%32 (63)19 (37)0.04143 (84)8 (16)0.09541 (80)10 (20)0.053
≥50%18 (90)2 (10) 20 (100)0 (0) 20(100)0 (0)
Loss of both p21/p27
NO19 (61)12 (39)0.19124 (77)7 (23)0.01822 (71)9 (29)0.002
YES31 (78)9 (22) 39 (98)1 (2) 39 (98)1 (3)
(B)
ALDH1hi CD44hi/CD24lo-ALDH1hi ALDH1hi/Ep-CAMhi
H-Score < 35H-Score ≥ 35♣ p−+♣ p−+♣ p
Clinicopathological MarkersAge
<40 years19 (79) *5 (21)0.28421 (88)3 (12)1.00020 (83)4 (17)1.000
≥40 years32 (65)17 (35) 44 (90)5 (10) 42 (86)7 (14)
Tumor Size
<4 cm34 (87)5 (13)<0.00138 (97)1 (3)0.02237 (95)2 (5)0.019
≥4 cm17 (50)17 (50) 27 (79)7 (21) 25 (74)9 (26)
Invasion
Absent22 (73)8 (27)0.61628 (93)2 (7)0.45826 (87)4 (13)1.000
Present29 (67)14 (33) 37 (86)6 (14) 36 (84)7 (16)
Histological Grade
1 and 231 (84)6 (16)0.01136 (97)1 (3)0.02834 (92)3 (8)0.112
320 (56)16 (44) 29 (81)7 (19) 28 (78)8 (22)
§ Lymph Node Metastasis
Absent19 (73)7 (27)0.79425 (96)1 (4)0.41024 (92)2 (8)0.307
Present32 (70)14 (30) 40 (87)6 (13) 37 (80)9 (20)
Neoadjuvant Chemotherapy
Absent17 (57)13 (43)0.06826 (87)4 (13)0.71025 (83)5 (17)0.752
Present34 (79)9 (21) 39 (91)4 (9) 37 (86)6 (14)
BC Subtype MarkersER Status
Negative16 (59)11 (41)0.18721 (78)6 (22)0.04519 (70)8 (30)0.015
Positive35 (76)11 (24) 44 (96)2 (4) 43 (93)3 (7)
PR Status
Negative26 (65)14 (35)0.44333 (83)7 (17)0.06531 (78)9 (23)0.097
Positive25 (76)8 (24) 32 (97)1 (3) 31 (94)2 (6)
HER2/neu Status
Negative37 (76)12 (24)0.17644 (90)5 (10)1.00043 (88)6 (12)0.487
Positive14 (58)10 (42) 21 (88)3 (12) 19 (79)5 (21)
TNBC Status
Negative41 (71)17 (29)0.76053 (91)5 (9)0.34851 (88)7 (12)0.221
Positive10 (67)5 (33) 12 (80)3 (20) 11 (73)4 (27)
EMT MarkersVimentin
Negative35 (69)16 (31)0.78848 (94)3 (6)0.04944 (86)7 (14)0.724
Positive16 (73)6 (27) 17 (77)5 (23) 18 (82)4 (18)
Loss of E-Cadherin
Negative38 (75)13 (25)0.26647 (92)4 (8)0.23246 (90)5 (10)0.077
Positive13 (59)9 (41) 18 (82)4 (18) 16 (72)6 (27)
Vimentin/Loss
of E-Cadherin
Negative44 (71)18 (29)0.72457 (92)5 (8)0.09555 (89)7 (11)0.055
Positive7 (64)4 (36) 8 (73)3 (27) 7 (64)4 (36)
Abbreviations: * The numbers between brackets are the percentages of patients and ♣ p values in bold and shaded represent significant data. Light shading represents borderline significance. § PD-1 is unknown for 3 samples, FOXP3 is unknown for 6 samples. The status is unknown for SKP2, p21, p27, and loss of both p21/p27 status for 2 cases. The lymph node status for one case is missing.
Table 3. Cox proportional hazard regression analysis of clinicopathological features with disease-free survival (DFS) and overall survival (OS) in 73 patients with breast cancer.
Table 3. Cox proportional hazard regression analysis of clinicopathological features with disease-free survival (DFS) and overall survival (OS) in 73 patients with breast cancer.
RelapseRFSDeathOS
UnivariateMultivariateUnivariateMultivariateMultivariate
−+HR95% CI* pHR95%CI♣ p−+HR95% CI* pHR95% CI* p
CD44hi CD24lo
<10%22 (45) *27 (55)1 38 (78)11 (22)1 1
≥10%11 (46)13 (54)1.10.6–2.20.718 12 (50)12 (50)2.41.0–5.40.0392.41.1–5.60.039
Ep-CAMhi
<H-Score 20019 (45)23 (55)1 33 (79)9 (21)1 1 1
≥H-Score 20014 (45)17 (55)1.20.6–2.30.541 17 (55)14 (45)2.51.1–5.70.0341.90.8–4.60.1312.00.8–4.70.113
CD44hi CD24lo-Ep-CAMhi
<H-Score 20027 (44)34 (56)1 44 (72)17 (28)1
≥H-Score 2006 (50)6 (50)1.00.4–2.30.946 6 (50)6 (50)2.00.8–5.10.140
ALDH1hi
<H-Score 3524 (47)27 (53)1 40 (78)11 (22)1 1
≥H-Score 359 (41)13 (59)1.20.6–2.30.630 10 (45)12 (55)3.01.3–6.90.0083.01.3–7.00.009
CD44hi/CD24lo-ALDH1hi
Negative32 (49)33 (51)1 1 49 (75)16 (25)1 1
Positive1 (12)7 (88)2.81.2–6.40.0142.81.2–6.40.0141 (13)7 (87)6.42.6–15.8<0.001 5.42.1–13.6<0.001
Ep-CAMhi/ALDH1hi
Negative29 (47)33 (53)1 45 (73)17 (27)1
Positive4 (36)7 (64)1.40.6–3.20.417 5 (45)6 (55)2.51.0–6.20.059
CD24hi
<H-Score 14025 (52)23 (48)1 1 33 (69)15 (31)1
≥H-Score 1408 (32)17 (68)2.11.1–3.90.0222.21.1–4.30.02317 (68)8 (32)1.40.6–3.30.460
CD10
<10%28 (47)32 (53)1 44 (73)16 (27)1
≥10%4 (36)7 (64)1.30.6–3.00.491 5 (45)6 (55)2.30.9–5.90.081
BMI1
Negative20 (38)32 (62)1 32 (62)20 (38)1
Positive12 (63)7 (37)0.40.2–1.00.043 17 (89)2 (11)0.20.05–0.80.027
Abbreviations: * (+ and −) are the number of positive and negative patients, the numbers between brackets are the percentages of patients, and ♣ p values in bold and shaded areas represent significant data. Light shading represents borderline significance.
Table 4. Summarized results of correlation between CSC types/states with hallmarks of cancer and survival of breast cancer patients (n = 73).
Table 4. Summarized results of correlation between CSC types/states with hallmarks of cancer and survival of breast cancer patients (n = 73).
CD44/CD24Ep-CAMCD44/CD24-
Ep-CAM		ALDH1CD44/CD24-ALDH1Ep-CAM/
ALDH1		CD24CD10
EMT√√√ *√√√√ √ √
Higher Proliferation√√√√√√√√√√√√√
Immune Evasion√√√√√ √√√
Higher Histological Grade√ √√ √
ER negative√√√√√ √√√
Abbreviations: * Number of checks represents the number of markers that demonstrate a significant correlation. Highlighted traits are common in all tested CSC markers except CD10.
Table 5. Conditions used for manual Immunohistochemistry on FFPE tissues.
Table 5. Conditions used for manual Immunohistochemistry on FFPE tissues.
AntibodyAntigen RetrievalPrimary AntibodySecondary Antibody
SolutionConditions *DilutionClone/Cat#
CD44/CD24Tris-EDTA
pH9		121 °C/7 minCD24, 1:100
CD44, 1:500		ML5/
HPA005785		Biotinylated goat anti-mouse AP
and Envision goat anti-rabbit HRP
ALDH1CC1 #121 °C/6 min1:20044/ALDHEnvision goat anti-mouse
Ep-CAMCitrate121 °C/8 min1:500VU-1D9Envision goat anti-mouse
BMI1CC1121 °C/6 min1:500F6Biotinylated goat anti-mouse (1/1000) (JL) ⊥
CD10 #CC1(clone SP67), Ventana Benchmark Ultra system
PD-L1 #(clone SP263), Ventana Benchmark Ultra system, previously described [54]
FOXP3 and PD-1(Clones 236A/E7 and J116, respectively), previously described [56]
Vimentin #/E-Cadherin(Clones V9 and EP700Y, respectively), previously described [52]
SKP2, p21, and p27(Clones D3G5, 12D1, and F-8 respectively), previously described [55]
* Indicated temperature is set point (SP)1, while SP2 is always 95 °C for 10 min. # Obtained from Ventana, AZ, USA. ⊥ Obtained from Jackson Laboratories, USA.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Ghebeh, H.; Mirza, J.Y.; Al-Tweigeri, T.; Al-Alwan, M.; Tulbah, A. Profiling of Breast Cancer Stem Cell Types/States Shows the Role of CD44hi/CD24lo-ALDH1hi as an Independent Prognostic Factor After Neoadjuvant Chemotherapy. Int. J. Mol. Sci. 2025, 26, 8219. https://doi.org/10.3390/ijms26178219

AMA Style

Ghebeh H, Mirza JY, Al-Tweigeri T, Al-Alwan M, Tulbah A. Profiling of Breast Cancer Stem Cell Types/States Shows the Role of CD44hi/CD24lo-ALDH1hi as an Independent Prognostic Factor After Neoadjuvant Chemotherapy. International Journal of Molecular Sciences. 2025; 26(17):8219. https://doi.org/10.3390/ijms26178219

Chicago/Turabian Style

Ghebeh, Hazem, Jumanah Y. Mirza, Taher Al-Tweigeri, Monther Al-Alwan, and Asma Tulbah. 2025. "Profiling of Breast Cancer Stem Cell Types/States Shows the Role of CD44hi/CD24lo-ALDH1hi as an Independent Prognostic Factor After Neoadjuvant Chemotherapy" International Journal of Molecular Sciences 26, no. 17: 8219. https://doi.org/10.3390/ijms26178219

APA Style

Ghebeh, H., Mirza, J. Y., Al-Tweigeri, T., Al-Alwan, M., & Tulbah, A. (2025). Profiling of Breast Cancer Stem Cell Types/States Shows the Role of CD44hi/CD24lo-ALDH1hi as an Independent Prognostic Factor After Neoadjuvant Chemotherapy. International Journal of Molecular Sciences, 26(17), 8219. https://doi.org/10.3390/ijms26178219

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop