Research ArticleExperimental Studies
Open Access

Luminal B Breast Cancer Coexpressing p62 and ALDH1A3 Is Less Susceptible to Radiotherapy

AYAKA OZAKI, AKARI MATSUDA, YUKI MAEMURA, YUNA TADA, TAKAHIRO KASAI, YUKA NAGASHIMA, CHOTARO ONAGA, YASUSHI HARA, KAZUKI KITABATAKE, MITSUTOSHI TSUKIMOTO, SHOMA TAMORI, KAZUNORI SASAKI, SHIGEO OHNO and KAZUNORI AKIMOTO
Anticancer Research January 2024, 44 (1) 37-47; DOI: https://doi.org/10.21873/anticanres.16786

Abstract

Background/Aim: We have reported that p62 (also known as sequestosome 1) is needed for survival/proliferation and tumor formation by aldehyde dehydrogenase 1 (ALDH1) -positive cancer stem cells (CSCs) and that p62high ALDH1A3high expression is associated with a poor prognosis in luminal B breast cancer. However, the association between p62high ALDH1A3high and the benefit from radiotherapy in patients with luminal B breast cancer remains unclear. Materials and Methods: Datasets from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas (TCGA) were downloaded, and data from p62high ALDH1A3high luminal B patients treated without or with radiotherapy were analyzed by Kaplan–Meier and multivariate Cox regression analyses. We also performed an in vitro tumor sphere formation assay after X-ray irradiation using p62-knockdown ALDH1high luminal B BT-474 cells. Results: p62high ALDH1A3high patients had poorer clinical outcomes than other luminal B breast cancer patients treated with radiotherapy. The combination of p62 DsiRNA KD and X-ray irradiation suppressed in vitro tumor sphere formation by ALDH1high BT-474 cells. These results suggest that p62 is involved in the reduced effect of X-ray irradiation on ALDH1-positive luminal B breast CSCs. Conclusion: p62 and ALDH1A3 may serve as prognostic biomarkers for luminal B breast cancer patients treated with radiotherapy. Additionally, the combination of p62 inhibition and radiotherapy could be useful for targeted strategies against ALDH1-positive luminal B breast CSCs.

Key Words:

Breast cancer occurs most often and is the leading cause of cancer-associated mortality in women worldwide (1). Breast cancer is commonly treated with surgery, radiotherapy, endocrine therapy, chemotherapy, and molecular targeted therapy.

X-ray irradiation is considered a major radiotherapy for breast cancer and is effective in reducing recurrence and patient death (2-5). However, relapse after radiotherapy is observed in a certain population of patients with breast cancer, and there are few biomarkers that can predict the effectiveness of radiotherapy. Therefore, it is important to identify effective biomarkers for predicting the effectiveness of radiotherapy for breast cancer at the time of diagnosis.

There are several means of classification of breast cancer including prediction analysis of microarray 50 (PAM50), based on gene expression patterns (6-10). PAM50 classifies breast cancer into six subtypes, including luminal A and luminal B (7, 8, 10). Both the luminal A and luminal B types are estrogen receptor-positive and account for 70-80% of breast cancer cases (11). In addition, many luminal B tumors highly express human epidermal growth factor receptor type 2 and proliferation markers such as Ki-67 (MKI67) (12-14). Luminal B breast cancer is associated with a poorer prognosis and does not show significant responses to radiotherapy, unlike luminal A breast cancer (4, 5, 12-17).

Cancer cell populations contain a small number of cancer stem cells (CSCs), which have stem cell-like properties, such as self-renewal, multipotency and tumorigenicity, and are resistant to chemotherapy and radiotherapy (18-20). Aldehyde dehydrogenase 1 (ALDH1) is known as a CSC marker in several cancer types, including breast cancer (21-26). ALDH1A3, an ALDH1 isoform, contributes significantly to ALDH1 activity in breast cancer cells (27, 28). Patients with high expression of ALDH1 who have received radiotherapy for rectal cancer, head and neck squamous cell carcinoma and squamous cell cervical carcinoma have shown poor outcomes (29-31). Moreover, ALDH1-positive breast CSCs are radioresistant (32-34).

We have previously reported that p62 (sequestosome 1) is essential for survival/proliferation and tumor formation by ALDH1-positive CSCs in luminal B breast cancer and that p62 is involved in cancer progression and contributes to the poor prognosis in p62high ALDH1A3high luminal B breast cancer patients (35). p62 is a multifunctional adapter protein that is involved in various physiological functions, including nuclear factor-Embedded ImageB signaling, antioxidant responses and autophagy (36-44). The p62 level predicts radiotherapy resistance in hypopharyngeal carcinoma (45). However, the association between the expression of p62 and the benefit from radiotherapy in patients with ALDH1-positive luminal B breast CSCs remains unclear.

The present study examined the association between the gene expression of p62 and ALDH1A3 and the benefit from radiotherapy in patients with luminal A and B breast cancer. Furthermore, we also examined the combined effect of p62 deficiency and X-ray irradiation on ALDH1-positive CSCs in luminal B breast cancer.

Materials and Methods

Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset. The METABRIC dataset (46, 47) was downloaded from cBioPortal (48, 49) on January 12, 2021. The clinicopathological data of these patients have been summarized previously (50-52). The METABRIC dataset has disease-specific survival (DSS) data with mRNA expression levels (n=1,423) and data regarding radiotherapy (luminal A: without radiotherapy, n=192, with radiotherapy, n=269; luminal B: without radiotherapy, n=115, with radiotherapy, n=224).

The Cancer Genome Atlas (TCGA) PanCancer Atlas dataset. TCGA PanCancer Atlas (53-56) data were downloaded from cBioPortal on April 5, 2023. The clinicopathological data of these patients have been summarized previously (51). The TCGA PanCancer Atlas dataset contains DSS data with mRNA expression levels (n=880) and data regarding radiotherapy (luminal A: without radiotherapy, n=205, with radiotherapy, n=250; luminal B: without radiotherapy, n=77, with radiotherapy, n=97).

Prognostic analyses. The Kaplan–Meier method, log-rank (Cochran–Mantel–Haenszel) test and multivariate Cox regression analyses of DSS were performed as previously described (35, 50-52, 57-64). Briefly, to divide patients into groups of high and low p62 and ALDH1A3 gene expression, receiver operating characteristic curves were drawn using DSS data, and the Youden index was used as the optimal cutoff threshold (Table I). In multivariate Cox regression analyses, age at diagnosis was used as a confounding factor. Two-sided p-values below 0.05 were considered to indicate a significant difference. The statistical analyses were carried out using BellCurve for Excel ver. 4.05 (Social Survey Research Information Co., Ltd., SSRI, Tokyo, Japan).

View this table:
Table I.

Optimal cutoff thresholds determined using Youden index by drawing receiver operating characteristic curves using disease-specific survival (DSS).

Cell culture. BT-474 human luminal B breast cancer cells were obtained from the American Type Culture Collection (Manassas, VA, USA) and cultured as previously described (35) with 10% fetal bovine serum (FBS; Nichirei Biosciences Inc., Tokyo, Japan).

DsiRNA knockdown. p62 knockdown (KD) in BT-474 cells was performed using Dicer-Substrate siRNA (DsiRNA), which led to long-term suppression of gene expression (65). The sequences were as follows. p62 DsiRNA: sense strand: 5′-GUGAACUCCAGUC CCUACAGAUGCC-3′ and antisense strand: 5′-GGCAUCUGUA GGGACUGGAGUUCACCU-3′; and negative control DsiRNA: sense strand: 5′-CGUUAAUCGCGUAUAAUACGCGUAT-3′ and antisense strand: 5′-AUACGCGUAUUAUACGCGAUUAACGAC-3′ (Integrated DNA Technologies, Inc., IDT, Coralville, IA, USA). Transfection was performed using Lipofectamine RNAiMAX (Thermo Fisher Scientific, Inc., Waltham, MA, USA) and OPTI-MEM (Gibco, Thermo Fisher Scientific Inc.). The cells were transfected two times, 48 and 24 h before the ALDEFLUOR assay. KD efficiency was monitored using western blotting as previously described (35, 50, 57, 59). The following primary antibodies were used: mouse monoclonal anti-p62 (610833, 1:10,000; BD Biosciences, San Jose, CA, USA); mouse monoclonal anti-β-actin (60008-1-Ig, 1:10,000; ProteinTech Group, Inc., Rosemont, IL, USA). Goat anti-mouse IgG (7076S, 1:5,000; Cell Signaling Technology, Inc., Danvers, MA, USA) was used as secondary antibody.

X-ray irradiation and in vitro tumor sphere formation. ALDH1high cells were isolated from BT-474 cells after p62 DsiRNA KD using the ALDEFLUOR assay according to our previous reports (35, 50, 57-59, 61-63, 66). The in vitro tumor sphere formation assay was then conducted with ALDH1high cells upon p62 KD as previously described (35). The isolated ALDH1high BT-474 cells were plated in ultralow-attachment 96-well plates (5×103 cells/well) (Greiner Bio-One GmbH, Frickenhausen, Germany). After 20 h, the plated cells were irradiated with 4 or 8 Gy of X-ray (0.596 Gy/min) using Faxitron CellRad (Faxitron, Tucson, AZ, USA). The irradiated cells were cultured for 9 days after the day of seeding. Whole-well and tiled images were acquired and analyzed using a BZ-X800 microscope (Keyence, Osaka, Japan) and BZ-X800 analyzer (Keyence). The area of tumor-spheres larger than 1,256 μm2 was analyzed.

Bar graph data are presented as the mean±standard error of the mean (SEM) of three independent experiments, and data were analyzed by two-way ANOVA followed by Tukey’s test for post hoc analysis. Two-sided p-values below 0.05 were considered to indicate significant difference. In the beeswarm plots, all sphere sizes larger than 1,256 μm2 in all wells from three independent experiments were plotted. Beeswarm plots show the size distribution of individual spheres in detail. Bar graphs were drawn in GraphPad Prism ver. 9.5.1 (GraphPad Software, Boston, MA, USA) and beeswarm plots were drawn in R ver. 4.2.1 (The R Foundation for Statistical Computing, Vienna, Austria). The representative images of the tumor spheres were edited to brightness +50 with Microsoft photo ver.2023.11090.12017.0 (Microsoft Corporation, Redmond, WA, USA). The statistical analyses were carried out using BellCurve for Excel ver. 4.05 (SSRI).

Results

Luminal B breast cancer patients with high p62 expression had poorer clinical outcomes after radiotherapy than those with low expression. To assess the relationship between p62 expression and the benefit from radiotherapy in the luminal A and B subtypes, we analyzed the METABRIC and TCGA datasets by the Kaplan–Meier method and log-rank tests. Both without and with radiotherapy, p62high patients had poorer clinical outcomes than p62low patients in the luminal A group in the METABRIC dataset (Figure 1A). There was no significant difference in the survival rate of p62high or p62low patients treated either without or with radiotherapy in the luminal A group in the TCGA dataset (Figure 1B). However, there was no significant difference in the survival rate of p62high and p62low patients treated without radiotherapy, whereas p62high patients had poorer clinical outcomes than p62low patients treated with radiotherapy in the luminal B group in both datasets (Figure 1A and B).

Figure 1.
Figure 1.

Patients with high expression of p62 (p62high) treated with radiotherapy exhibit poor clinical outcomes in luminal B breast cancer. (A, B) Kaplan–Meier analyses comparing disease-specific survival (DSS) between p62high and p62low patients with luminal A and luminal B breast cancer treated without or with radiotherapy. (A) METABRIC data. (B) TCGA data. p-Values were calculated with the log-rank (Cochran–Mantel–Haenszel) test.

Next, multivariate Cox regression analyses were performed with age at diagnosis as a confounding factor. p62high patients tended to have worse clinical outcomes than p62low patients treated with radiotherapy in the luminal B group in both datasets (Table II).

View this table:
Table II.

Multivariate Cox regression analysis of the prognosis of p62high or p62high ALDH1A3high patients with luminal A or luminal B breast cancer treated without or with radiotherapy.

These results suggest that p62high luminal B breast cancer patients may not benefit from radiotherapy, whereas there is no association between p62high expression and the benefit of radiotherapy in luminal A breast cancer patients.

p62high and ALDH1A3high patients treated with radiotherapy had poorer clinical outcomes than other patients with luminal B breast cancer. We previously reported that p62high ALDH1A3high patients had poorer clinical outcomes than other patients with luminal B breast cancer (35). Therefore, we examined the prognosis of p62high ALDH1A3high patients treated without or with radiotherapy. p62high ALDH1A3high patients treated without and with radiotherapy had poorer clinical outcomes than other luminal A breast cancer patients in the METABRIC dataset (Figure 2A). However, there was no significant difference in the survival rate of p62high ALDH1A3high patients and other patients treated without or with radiotherapy in the luminal A group in the TCGA dataset (Figure 2B). However, there was no significant difference in the survival rate of p62high ALDH1A3high patients and other patients treated without radiotherapy, whereas p62high ALDH1A3high patients had poorer clinical outcomes than other patients treated with radiotherapy in the luminal B group in both the METABRIC and TCGA datasets (Figure 2A and B). The multivariate Cox regression analyses with age at diagnosis as a confounding factor using the same datasets showed worse clinical outcomes in p62high ALDH1A3high patients than other patients treated with radiotherapy in the luminal B group in the METABRIC dataset, and the same trend was observed in the TCGA dataset (Table II).

Figure 2.
Figure 2.

Patients with high expression of p62 (p62high) and ALDH1A3 (ALDH1A3high) treated with radiotherapy exhibit poor clinical outcomes in luminal B breast cancer. (A, B) Upper: Kaplan–Meier analyses comparing disease-specific survival (DSS) between p62high ALDH1A3high patients and others (p62high ALDH1A3low, p62low ALDH1A3high and p62low ALDH1A3low) with luminal A and luminal B breast cancer treated without or with radiotherapy; lower: survival curves of DSS with p62high ALDH1A3high, p62high ALDH1A3low, p62low ALDH1A3high and p62low ALDH1A3low patients with luminal A and luminal B breast cancer treated without or with radiotherapy by the Kaplan–Meier method. (A) METABRIC data. (B) TCGA data. p-Values were calculated with the log-rank (Cochran–Mantel–Haenszel) test.

These results suggest that p62high contributes to the reduced efficacy of radiotherapy in patients with ALDH1A3high luminal B breast cancer, whereas there is no relationship between p62high and the benefit of radiotherapy in ALDH1A3high luminal A breast cancer.

The combination of p62 DsiRNA KD and X-ray irradiation suppressed in vitro tumor sphere formation by ALDH1high BT-474 cells. Based on the above results, we examined whether p62 is involved in the reduced efficacy of X-ray irradiation against ALDH1-positive luminal B breast CSCs. Therefore, we performed an in vitro tumor sphere formation assay using p62-deficient ALDH1high luminal B BT-474 cells exposed to X-ray irradiation. p62 is highly expressed in BT-474 cells (35). Western blotting analysis confirmed that the transfection of p62 DsiRNA into BT-474 cells efficiently reduced the p62 protein expression (Figure 3A). p62 DsiRNA suppressed the area of tumor sphere formation by ALDH1high BT-474 cells, consistent with our previous study (35) (main effect for p62 DsiRNA KD: p<0.001, Figure 3A and B). Tumor sphere formation by ALDH1high BT-474 cells was also suppressed by X-ray irradiation in a Gy-dependent manner (main effect for X-ray irradiation: p<0.001, Figure 3A and B). Furthermore, the combination of p62 DsiRNA KD and X-ray irradiation additively suppressed tumor sphere formation by ALDH1high BT-474 cells (interaction between p62 DsiRNA KD and X-ray irradiation was not statistically significant, Figure 3A and B). We also showed the size distribution of individual spheres as beeswarm plots (Figure 3C).

Figure 3.
Figure 3.

The combination of p62 DsiRNA KD and X-ray irradiation leads to the suppression of in vitro tumor sphere formation by ALDH1high luminal B cells. (A-C) In vitro tumor sphere formation by p62-deficient ALDH1high luminal B BT-474 cells exposed to the indicated doses of X-ray irradiation. (A) The western blot panels on the left show the efficiency of KD. β-actin was used as a loading control. Representative images are shown on the right; scale bar, upper: 1,000 μm, lower: 100 μm. (B, C) Quantitative analysis of the area of tumor spheres. (B) The bar graph data are presented as the mean±standard error of the mean (SEM) of three independent experiments; *p<0.05, **p<0.01, ***p<0.001 by two-way ANOVA followed by Tukey’s test for post hoc analysis. (C) In the beeswarm plots, all spheres larger than 1,256 μm2 in all wells from three independent experiments of (B) are plotted.

These results suggest that p62 is involved in the reduced efficacy of X-ray irradiation against ALDH1-positive luminal B breast CSCs.

Discussion

In this study, we showed that p62 deficiency and X-ray irradiation additively suppressed tumor sphere formation by ALDH1-positive luminal B breast CSCs. X-rays damage cancer cells by causing direct DNA double strand breaks and inducing production of reactive oxygen species (ROS) (67-70). Reports on the relationship between p62 expression and the effects of radiation are as follows: Arai et al. reported that p62 is involved in radiotherapy resistance via p62-dependent antioxidant signaling in hypopharyngeal carcinoma (45). Moreover, Li et al. reported that activation of the p62-Keap1-NRF2 pathway protects A549 cells against radiation-induced ferroptosis (71). However, there have also been reports that p62 contributes to radiosensitivity through suppressing chromatin ubiquitination and delaying DNA damage repair (72) or promoting autophagy-dependent senescence (73). Thus, the reduced effect of X-ray irradiation on ALDH1-positive luminal B breast CSCs may be due to protection from ROS damage by p62-Keap1-NRF2 antioxidant signals.

p62 is a multifunctional scaffold protein that binds to PKCλ/ι (36-44). Interestingly, we have reported that PKCλ/ι is involved in the regulation of the stemness properties of ALDH1A3-positive CSCs in breast and pancreatic cancer (58, 59, 63, 66). Thus, PKCλ/ι may contribute to the reduced effectiveness of radiotherapy against ALDH1A3-positive luminal B CSCs via interaction with p62.

In the present study, we revealed that p62high ALDH1A3high luminal B breast cancer is less susceptible to radiotherapy by analyzing two gene expression datasets. It has been reported that ALDH1high patients receiving radiotherapy for rectal cancer, head and neck squamous cell carcinoma and squamous cell cervical carcinoma have poorer outcomes (29-31). Thus, further research into the prognosis of p62high ALDH1A3high patients who receive radiotherapy for those cancers is needed. In addition to radiotherapy, luminal B breast cancer is usually treated by endocrine therapy, chemotherapy, and molecular targeted therapy. Therefore, revealing the effect of these drug therapies on p62high ALDH1A3high luminal B breast cancer is important.

Conclusion

In the present study, we revealed that p62high ALDH1A3high luminal B breast cancer is less susceptible to radiotherapy. We also showed that p62 deficiency and X-ray irradiation additively suppressed tumor sphere formation by ALDH1-positive luminal B breast CSCs. Therefore, we can conclude that p62 and ALDH1A3 are potential prognostic biomarkers for use in luminal B breast cancer patients treated with radiotherapy and that the combination of p62 inhibition and radiotherapy could be useful for targeted therapy against ALDH1-positive luminal B breast CSCs.

Acknowledgements

The Authors are extremely grateful to Dr. Nozaki Y. of Tokyo University of Science for the helpful discussion.

Footnotes

  • Authors’ Contributions

    A.O., Y.M., Y.T., Y.N. C.O., and K.S. performed bioinformatic analyses; A.O., A.M., T.K. and Y.H. performed experiments; K.K, and M.T. performed X-ray irradiation; A.O., A.M., Y.M., Y.T. and K.S. performed data analyses; M.T., S.T., K.S. and S.O. supplied experimental materials and resources; A.O. and K.A. conceived the study; A.O. and K.A. drafted the manuscript; all the Authors contributed to the discussion and review of the final manuscript; and all the Authors approved the final manuscript.

  • Conflicts of Interest

    The Authors declare that they have no conflicts of interest related to the contents of this article.

  • Funding

    This work was supported by a Grant-in-Aid for Scientific Research (C) from the JSPS (20K07207) (K.A.), the JST Moonshot R&D (JPMJPS2022) (S.O.), a Tokyo University of Science Grant for President’s Research Promotion (K.A.), a Grant-in-Aid for Research Activity Start-up (21K20732) (S.T.), a Grant-in-Aid for Early-Career Scientists (23K14352) (S.T.), a Grant-in-Aid for Special Research in Subsidies for ordinary expenses of private schools from The Promotion and Mutual Aid Corporation for Private Schools of Japan (K.S.), a Grant from the Institute for Environmental & Gender-specific Medicine, Juntendo University (K.S.), JST SPRING (JPMJSP2151) (A.O., Y.N.), and Nagai Memorial Research Scholarship from the Pharmaceutical Society of Japan (A.O.).

  • Received October 27, 2023.
  • Revision received November 21, 2023.
  • Accepted November 22, 2023.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Sung H,
    2. Ferlay J,
    3. Siegel RL,
    4. Laversanne M,
    5. Soerjomataram I,
    6. Jemal A,
    7. Bray F
    : Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71(3): 209-249, 2021. DOI: 10.3322/caac.21660
    OpenUrlCrossRefPubMed
  2. ↵
    1. Fisher B,
    2. Anderson S,
    3. Bryant J,
    4. Margolese RG,
    5. Deutsch M,
    6. Fisher ER,
    7. Jeong J,
    8. Wolmark N
    : Twenty-year follow-up of a randomized trial comparing total mastectomy, lumpectomy, and lumpectomy plus irradiation for the treatment of invasive breast cancer. N Engl J Med 347(16): 1233-1241, 2002. DOI: 10.1056/NEJMoa022152
    OpenUrlCrossRefPubMed
    1. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG),
    2. Darby S,
    3. McGale P,
    4. Correa C,
    5. Taylor C,
    6. Arriagada R,
    7. Clarke M,
    8. Cutter D,
    9. Davies C,
    10. Ewertz M,
    11. Godwin J,
    12. Gray R,
    13. Pierce L,
    14. Whelan T,
    15. Wang Y,
    16. Peto R
    : Effect of radiotherapy after breast-conserving surgery on 10-year recurrence and 15-year breast cancer death: meta-analysis of individual patient data for 10,801 women in 17 randomised trials. Lancet 378(9804): 1707-1716, 2011. DOI: 10.1016/S0140-6736(11)61629-2
    OpenUrlCrossRefPubMed
  4. ↵
    1. Langlands FE,
    2. Horgan K,
    3. Dodwell DD,
    4. Smith L
    : Breast cancer subtypes: response to radiotherapy and potential radiosensitisation. Br J Radiol 86(1023): 20120601, 2013. DOI: 10.1259/bjr.20120601
    OpenUrlAbstract/FREE Full Text
  5. ↵
    1. Laurberg T,
    2. Tramm T,
    3. Nielsen T,
    4. Alsner J,
    5. Nord S,
    6. Myhre S,
    7. Sørlie T,
    8. Leung S,
    9. Fan C,
    10. Perou C,
    11. Gelmon K,
    12. Overgaard J,
    13. Voduc D,
    14. Prat A,
    15. Cheang MCU
    : Intrinsic subtypes and benefit from postmastectomy radiotherapy in node-positive premenopausal breast cancer patients who received adjuvant chemotherapy – results from two independent randomized trials. Acta Oncol 57(1): 38-43, 2018. DOI: 10.1080/0284186X.2017.1401735
    OpenUrlCrossRef
  6. ↵
    1. Perou CM,
    2. Sørlie T,
    3. Eisen MB,
    4. van de Rijn M,
    5. Jeffrey SS,
    6. Rees CA,
    7. Pollack JR,
    8. Ross DT,
    9. Johnsen H,
    10. Akslen LA,
    11. Fluge O,
    12. Pergamenschikov A,
    13. Williams C,
    14. Zhu SX,
    15. Lønning PE,
    16. Børresen-Dale AL,
    17. Brown PO,
    18. Botstein D
    : Molecular portraits of human breast tumours. Nature 406(6797): 747-752, 2000. DOI: 10.1038/35021093
    OpenUrlCrossRefPubMed
  7. ↵
    1. Herschkowitz JI,
    2. Simin K,
    3. Weigman VJ,
    4. Mikaelian I,
    5. Usary J,
    6. Hu Z,
    7. Rasmussen KE,
    8. Jones LP,
    9. Assefnia S,
    10. Chandrasekharan S,
    11. Backlund MG,
    12. Yin Y,
    13. Khramtsov AI,
    14. Bastein R,
    15. Quackenbush J,
    16. Glazer RI,
    17. Brown PH,
    18. Green JE,
    19. Kopelovich L,
    20. Furth PA,
    21. Palazzo JP,
    22. Olopade OI,
    23. Bernard PS,
    24. Churchill GA,
    25. Van Dyke T,
    26. Perou CM
    : Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors. Genome Biol 8(5): R76, 2007. DOI: 10.1186/gb-2007-8-5-r76
    OpenUrlCrossRefPubMed
  8. ↵
    1. Parker JS,
    2. Mullins M,
    3. Cheang MC,
    4. Leung S,
    5. Voduc D,
    6. Vickery T,
    7. Davies S,
    8. Fauron C,
    9. He X,
    10. Hu Z,
    11. Quackenbush JF,
    12. Stijleman IJ,
    13. Palazzo J,
    14. Marron JS,
    15. Nobel AB,
    16. Mardis E,
    17. Nielsen TO,
    18. Ellis MJ,
    19. Perou CM,
    20. Bernard PS
    : Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 27(8): 1160-1167, 2009. DOI: 10.1200/JCO.2008.18.1370
    OpenUrlAbstract/FREE Full Text
    1. Blows FM,
    2. Driver KE,
    3. Schmidt MK,
    4. Broeks A,
    5. van Leeuwen FE,
    6. Wesseling J,
    7. Cheang MC,
    8. Gelmon K,
    9. Nielsen TO,
    10. Blomqvist C,
    11. Heikkilä P,
    12. Heikkinen T,
    13. Nevanlinna H,
    14. Akslen LA,
    15. Bégin LR,
    16. Foulkes WD,
    17. Couch FJ,
    18. Wang X,
    19. Cafourek V,
    20. Olson JE,
    21. Baglietto L,
    22. Giles GG,
    23. Severi G,
    24. McLean CA,
    25. Southey MC,
    26. Rakha E,
    27. Green AR,
    28. Ellis IO,
    29. Sherman ME,
    30. Lissowska J,
    31. Anderson WF,
    32. Cox A,
    33. Cross SS,
    34. Reed MW,
    35. Provenzano E,
    36. Dawson SJ,
    37. Dunning AM,
    38. Humphreys M,
    39. Easton DF,
    40. García-Closas M,
    41. Caldas C,
    42. Pharoah PD,
    43. Huntsman D
    : Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med 7(5): e1000279, 2010. DOI: 10.1371/journal.pmed.1000279
    OpenUrlCrossRefPubMed
  10. ↵
    1. Prat A,
    2. Parker JS,
    3. Karginova O,
    4. Fan C,
    5. Livasy C,
    6. Herschkowitz JI,
    7. He X,
    8. Perou CM
    : Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res 12(5): R68, 2010. DOI: 10.1186/bcr2635
    OpenUrlCrossRefPubMed
  11. ↵
    1. Waks AG,
    2. Winer EP
    : Breast cancer treatment. JAMA 321(3): 288, 2019. DOI: 10.1001/jama.2018.19323
    OpenUrlCrossRefPubMed
  12. ↵
    1. Prat A,
    2. Cheang MC,
    3. Martín M,
    4. Parker JS,
    5. Carrasco E,
    6. Caballero R,
    7. Tyldesley S,
    8. Gelmon K,
    9. Bernard PS,
    10. Nielsen TO,
    11. Perou CM
    : Prognostic significance of progesterone receptor-positive tumor cells within immunohistochemically defined luminal A breast cancer. J Clin Oncol 31(2): 203-209, 2013. DOI: 10.1200/JCO.2012.43.4134
    OpenUrlAbstract/FREE Full Text
    1. Ades F,
    2. Zardavas D,
    3. Bozovic-Spasojevic I,
    4. Pugliano L,
    5. Fumagalli D,
    6. de Azambuja E,
    7. Viale G,
    8. Sotiriou C,
    9. Piccart M
    : Luminal B breast cancer: Molecular characterization, clinical management, and future perspectives. J Clin Oncol 32(25): 2794-2803, 2014. DOI: 10.1200/JCO.2013.54.1870
    OpenUrlAbstract/FREE Full Text
  14. ↵
    1. Prat A,
    2. Pineda E,
    3. Adamo B,
    4. Galvan P,
    5. Fernandez A,
    6. Gaba L,
    7. Diez M,
    8. Viladot M,
    9. Arance A,
    10. Munoz M
    : Clinical implications of the intrinsic molecular subtypes of breast cancer. Breast 24 Suppl 2: S26-35, 2015. DOI: 10.1016/j.breast.2015.07.008
    OpenUrlCrossRefPubMed
    1. Chia SK,
    2. Bramwell VH,
    3. Tu D,
    4. Shepherd LE,
    5. Jiang S,
    6. Vickery T,
    7. Mardis E,
    8. Leung S,
    9. Ung K,
    10. Pritchard KI,
    11. Parker JS,
    12. Bernard PS,
    13. Perou CM,
    14. Ellis MJ,
    15. Nielsen TO
    : A 50-gene intrinsic subtype classifier for prognosis and prediction of benefit from adjuvant tamoxifen. Clin Cancer Res 18(16): 4465-4472, 2012. DOI: 10.1158/1078-0432.CCR-12-0286
    OpenUrlAbstract/FREE Full Text
    1. Dowsett M,
    2. Sestak I,
    3. Lopez-Knowles E,
    4. Sidhu K,
    5. Dunbier AK,
    6. Cowens JW,
    7. Ferree S,
    8. Storhoff J,
    9. Schaper C,
    10. Cuzick J
    : Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol 31(22): 2783-2790, 2013. DOI: 10.1200/JCO.2012.46.1558
    OpenUrlAbstract/FREE Full Text
  17. ↵
    1. Pu M,
    2. Messer K,
    3. Davies SR,
    4. Vickery TL,
    5. Pittman E,
    6. Parker BA,
    7. Ellis MJ,
    8. Flatt SW,
    9. Marinac CR,
    10. Nelson SH,
    11. Mardis ER,
    12. Pierce JP,
    13. Natarajan L
    : Research-based PAM50 signature and long-term breast cancer survival. Breast Cancer Res Treat 179(1): 197-206, 2020. DOI: 10.1007/s10549-019-05446-y
    OpenUrlCrossRefPubMed
  18. ↵
    1. Reya T,
    2. Morrison SJ,
    3. Clarke MF,
    4. Weissman IL
    : Stem cells, cancer, and cancer stem cells. Nature 414(6859): 105-111, 2001. DOI: 10.1038/35102167
    OpenUrlCrossRefPubMed
    1. Visvader JE,
    2. Lindeman GJ
    : Cancer stem cells: Current status and evolving complexities. Cell Stem Cell 10(6): 717-728, 2012. DOI: 10.1016/j.stem.2012.05.007
    OpenUrlCrossRefPubMed
  20. ↵
    1. Nguyen NP,
    2. Almeida FS,
    3. Chi A,
    4. Nguyen LM,
    5. Cohen D,
    6. Karlsson U,
    7. Vinh-Hung V
    : Molecular biology of breast cancer stem cells: Potential clinical applications. Cancer Treat Rev 36(6): 485-491, 2010. DOI: 10.1016/j.ctrv.2010.02.016
    OpenUrlCrossRefPubMed
  21. ↵
    1. Ginestier C,
    2. Hur MH,
    3. Charafe-Jauffret E,
    4. Monville F,
    5. Dutcher J,
    6. Brown M,
    7. Jacquemier J,
    8. Viens P,
    9. Kleer CG,
    10. Liu S,
    11. Schott A,
    12. Hayes D,
    13. Birnbaum D,
    14. Wicha MS,
    15. Dontu G
    : ALDH1 is a marker of normal and malignant human mammary stem cells and a predictor of poor clinical outcome. Cell Stem Cell 1(5): 555-567, 2007. DOI: 10.1016/j.stem.2007.08.014
    OpenUrlCrossRefPubMed
    1. Jiang F,
    2. Qiu Q,
    3. Khanna A,
    4. Todd NW,
    5. Deepak J,
    6. Xing L,
    7. Wang H,
    8. Liu Z,
    9. Su Y,
    10. Stass SA,
    11. Katz RL
    : Aldehyde dehydrogenase 1 is a tumor stem cell-associated marker in lung cancer. Mol Cancer Res 7(3): 330-338, 2009. DOI: 10.1158/1541-7786.MCR-08-0393
    OpenUrlAbstract/FREE Full Text
    1. Tanei T,
    2. Morimoto K,
    3. Shimazu K,
    4. Kim SJ,
    5. Tanji Y,
    6. Taguchi T,
    7. Tamaki Y,
    8. Noguchi S
    : Association of breast cancer stem cells identified by aldehyde dehydrogenase 1 expression with resistance to sequential paclitaxel and epirubicin-based chemotherapy for breast cancers. Clin Cancer Res 15(12): 4234-4241, 2009. DOI: 10.1158/1078-0432.CCR-08-1479
    OpenUrlAbstract/FREE Full Text
    1. Landen CN Jr.,
    2. Goodman B,
    3. Katre AA,
    4. Steg AD,
    5. Nick AM,
    6. Stone RL,
    7. Miller LD,
    8. Mejia PV,
    9. Jennings NB,
    10. Gershenson DM,
    11. Bast RC Jr.,
    12. Coleman RL,
    13. Lopez-Berestein G,
    14. Sood AK
    : Targeting aldehyde dehydrogenase cancer stem cells in ovarian cancer. Mol Cancer Ther 9(12): 3186-3199, 2010. DOI: 10.1158/1535-7163.MCT-10-0563
    OpenUrlAbstract/FREE Full Text
    1. Su Y,
    2. Qiu Q,
    3. Zhang X,
    4. Jiang Z,
    5. Leng Q,
    6. Liu Z,
    7. Stass SA,
    8. Jiang F
    : Aldehyde dehydrogenase 1 A1-positive cell population is enriched in tumor-initiating cells and associated with progression of bladder cancer. Cancer Epidemiol Biomarkers Prev 19(2): 327-337, 2010. DOI: 10.1158/1055-9965.EPI-09-0865
    OpenUrlAbstract/FREE Full Text
  26. ↵
    1. Kim MP,
    2. Fleming JB,
    3. Wang H,
    4. Abbruzzese JL,
    5. Choi W,
    6. Kopetz S,
    7. McConkey DJ,
    8. Evans DB,
    9. Gallick GE
    : ALDH activity selectively defines an enhanced tumor-initiating cell population relative to CD133 expression in human pancreatic adenocarcinoma. PLoS One 6(6): e20636, 2011. DOI: 10.1371/journal.pone.0020636
    OpenUrlCrossRefPubMed
  27. ↵
    1. Marcato P,
    2. Dean CA,
    3. Pan D,
    4. Araslanova R,
    5. Gillis M,
    6. Joshi M,
    7. Helyer L,
    8. Pan L,
    9. Leidal A,
    10. Gujar S,
    11. Giacomantonio CA,
    12. Lee PWK
    : Aldehyde dehydrogenase activity of breast cancer stem cells is primarily due to isoform ALDH1A3 and its expression is predictive of metastasis. Stem Cells 29(1): 32-45, 2011. DOI: 10.1002/stem.563
    OpenUrlCrossRefPubMed
  28. ↵
    1. Croker AK,
    2. Rodriguez-Torres M,
    3. Xia Y,
    4. Pardhan S,
    5. Leong HS,
    6. Lewis JD,
    7. Allan AL
    : Differential functional roles of ALDH1A1 and ALDH1A3 in mediating metastatic behavior and therapy resistance of human breast cancer cells. Int J Mol Sci 18(10): 2039, 2017. DOI: 10.3390/ijms18102039
    OpenUrlCrossRefPubMed
  29. ↵
    1. Avoranta ST,
    2. Korkeila EA,
    3. Ristamäki RH,
    4. Syrjänen KJ,
    5. Carpén OM,
    6. Pyrhönen SO,
    7. Sundström JT
    : ALDH1 expression indicates chemotherapy resistance and poor outcome in node-negative rectal cancer. Hum Pathol 44(6): 966-974, 2013. DOI: 10.1016/j.humpath.2012.10.003
    OpenUrlCrossRef
    1. Dubey P,
    2. Kumar N,
    3. Gupta R,
    4. Mishra A,
    5. Bhadauriya S,
    6. Kumar V,
    7. Bhatt MB
    : Association of ALDH1 with response to radiotherapy and its impact on survival in patients with advanced stage of head and neck squamous cell carcinoma (HNSCC). Asian Pac J Cancer Prev 23(2): 419-427, 2022. DOI: 10.31557/APJCP.2022.23.2.419
    OpenUrlCrossRef
  31. ↵
    1. Fahmi MN,
    2. Kusuma F,
    3. Hellyanti T,
    4. Kekalih A,
    5. Sekarutami SM,
    6. Nurrana L,
    7. Purwoto G,
    8. Anggraeni TD
    : High ALDH-1 expression predicts non-complete response of radiotherapy in stage III squamous cell cervical carcinoma patients. Asian Pac J Cancer Prev 24(6): 1863-1868, 2023. DOI: 10.31557/APJCP.2023.24.6.1863
    OpenUrlCrossRef
  32. ↵
    1. Mihatsch J,
    2. Toulany M,
    3. Bareiss PM,
    4. Grimm S,
    5. Lengerke C,
    6. Kehlbach R,
    7. Rodemann HP
    : Selection of radioresistant tumor cells and presence of ALDH1 activity in vitro. Radiother Oncol 99(3): 300-306, 2011. DOI: 10.1016/j.radonc.2011.06.003
    OpenUrlCrossRefPubMed
    1. Croker AK,
    2. Allan AL
    : Inhibition of aldehyde dehydrogenase (ALDH) activity reduces chemotherapy and radiation resistance of stem-like ALDHhiCD44+ human breast cancer cells. Breast Cancer Res Treat 133(1): 75-87, 2012. DOI: 10.1007/s10549-011-1692-y
    OpenUrlCrossRefPubMed
  34. ↵
    1. Dehghan Harati M,
    2. Rodemann HP,
    3. Toulany M
    : Nanog signaling mediates radioresistance in ALDH-positive breast cancer cells. Int J Mol Sci 20(5): 1151, 2019. DOI: 10.3390/ijms20051151
    OpenUrlCrossRef
  35. ↵
    1. Ozaki A,
    2. Motomura H,
    3. Tamori S,
    4. Onaga C,
    5. Nagashima Y,
    6. Kotori M,
    7. Matsuda C,
    8. Matsuda A,
    9. Mochizuki N,
    10. Sato T,
    11. Hara Y,
    12. Sato K,
    13. Miyagi Y,
    14. Nagashima Y,
    15. Hanawa T,
    16. Harada Y,
    17. Xiong Y,
    18. Sasaki K,
    19. Ohno S,
    20. Akimoto K
    : High expression of p62 and ALDH1A3 is associated with poor prognosis in luminal B breast cancer. Anticancer Res 42(7): 3299-3312, 2022. DOI: 10.21873/anticanres.15818
    OpenUrlAbstract/FREE Full Text
  36. ↵
    1. Puls A,
    2. Schmidt S,
    3. Grawe F,
    4. Stabel S
    : Interaction of protein kinase C ζ with ZIP, a novel protein kinase C-binding protein. Proc Natl Acad Sci USA 94(12): 6191-6196, 1997. DOI: 10.1073/pnas.94.12.6191
    OpenUrlAbstract/FREE Full Text
    1. Sanchez P,
    2. De Carcer G,
    3. Sandoval IV,
    4. Moscat J,
    5. Diaz-Meco MT
    : Localization of atypical protein kinase C isoforms into lysosome-targeted endosomes through interaction with p62. Mol Cell Biol 18(5): 3069-3080, 1998. DOI: 10.1128/MCB.18.5.3069
    OpenUrlAbstract/FREE Full Text
    1. Sanz L,
    2. Sanchez P,
    3. Lallena MJ,
    4. Diaz-Meco MT,
    5. Moscat J
    : The interaction of p62 with RIP links the atypical PKCs to NF-kappaB activation. EMBO J 18(11): 3044-3053, 1999. DOI: 10.1093/emboj/18.11.3044
    OpenUrlAbstract
    1. Sanz L,
    2. Diaz-Meco MT,
    3. Nakano H,
    4. Moscat J
    : The atypical PKC-interacting protein p62 channels NF-kappaB activation by the IL-1-TRAF6 pathway. EMBO J 19(7): 1576-1586, 2000. DOI: 10.1093/emboj/19.7.1576
    OpenUrlAbstract
    1. Bjørkøy G,
    2. Lamark T,
    3. Brech A,
    4. Outzen H,
    5. Perander M,
    6. Overvatn A,
    7. Stenmark H,
    8. Johansen T
    : p62/SQSTM1 forms protein aggregates degraded by autophagy and has a protective effect on huntingtin-induced cell death. J Cell Biol 171(4): 603-614, 2005. DOI: 10.1083/jcb.200507002
    OpenUrlAbstract/FREE Full Text
    1. Pankiv S,
    2. Clausen TH,
    3. Lamark T,
    4. Brech A,
    5. Bruun JA,
    6. Outzen H,
    7. Øvervatn A,
    8. Bjørkøy G,
    9. Johansen T
    : p62/SQSTM1 binds directly to Atg8/LC3 to facilitate degradation of ubiquitinated protein aggregates by autophagy. J Biol Chem 282(33): 24131-24145, 2007. DOI: 10.1074/jbc.M702824200
    OpenUrlAbstract/FREE Full Text
    1. Ichimura Y,
    2. Kumanomidou T,
    3. Sou YS,
    4. Mizushima T,
    5. Ezaki J,
    6. Ueno T,
    7. Kominami E,
    8. Yamane T,
    9. Tanaka K,
    10. Komatsu M
    : Structural basis for sorting mechanism of p62 in selective autophagy. J Biol Chem 283(33): 22847-22857, 2008. DOI: 10.1074/jbc.M802182200
    OpenUrlAbstract/FREE Full Text
    1. Moscat J,
    2. Diaz-Meco MT
    : p62 at the crossroads of autophagy, apoptosis, and cancer. Cell 137(6): 1001-1004, 2009. DOI: 10.1016/j.cell.2009.05.023
    OpenUrlCrossRefPubMed
  44. ↵
    1. Jain A,
    2. Lamark T,
    3. Sjøttem E,
    4. Larsen KB,
    5. Awuh JA,
    6. Øvervatn A,
    7. McMahon M,
    8. Hayes JD,
    9. Johansen T
    : p62/SQSTM1 is a target gene for transcription factor NRF2 and creates a positive feedback loop by inducing antioxidant response element-driven gene transcription. J Biol Chem 285(29): 22576-22591, 2010. DOI: 10.1074/jbc.M110.118976
    OpenUrlAbstract/FREE Full Text
  45. ↵
    1. Arai A,
    2. Chano T,
    3. Ikebuchi K,
    4. Hama Y,
    5. Ochi Y,
    6. Tameno H,
    7. Shimada T
    : p62/SQSTM1 levels predicts radiotherapy resistance in hypopharyngeal carcinomas. Am J Cancer Res 7(4): 881-891, 2017.
    OpenUrlPubMed
  46. ↵
    1. Curtis C,
    2. Shah SP,
    3. Chin SF,
    4. Turashvili G,
    5. Rueda OM,
    6. Dunning MJ,
    7. Speed D,
    8. Lynch AG,
    9. Samarajiwa S,
    10. Yuan Y,
    11. Gräf S,
    12. Ha G,
    13. Haffari G,
    14. Bashashati A,
    15. Russell R,
    16. McKinney S, METABRIC Group,
    17. Langerød A,
    18. Green A,
    19. Provenzano E,
    20. Wishart G,
    21. Pinder S,
    22. Watson P,
    23. Markowetz F,
    24. Murphy L,
    25. Ellis I,
    26. Purushotham A,
    27. Børresen-Dale AL,
    28. Brenton JD,
    29. Tavaré S,
    30. Caldas C,
    31. Aparicio S
    : The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486(7403): 346-352, 2012. DOI: 10.1038/nature10983
    OpenUrlCrossRefPubMed
  47. ↵
    1. Pereira B,
    2. Chin SF,
    3. Rueda OM,
    4. Vollan HK,
    5. Provenzano E,
    6. Bardwell HA,
    7. Pugh M,
    8. Jones L,
    9. Russell R,
    10. Sammut SJ,
    11. Tsui DW,
    12. Liu B,
    13. Dawson SJ,
    14. Abraham J,
    15. Northen H,
    16. Peden JF,
    17. Mukherjee A,
    18. Turashvili G,
    19. Green AR,
    20. McKinney S,
    21. Oloumi A,
    22. Shah S,
    23. Rosenfeld N,
    24. Murphy L,
    25. Bentley DR,
    26. Ellis IO,
    27. Purushotham A,
    28. Pinder SE,
    29. Børresen-Dale AL,
    30. Earl HM,
    31. Pharoah PD,
    32. Ross MT,
    33. Aparicio S,
    34. Caldas C
    : The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nat Commun 7: 11479, 2016. DOI: 10.1038/ncomms11479
    OpenUrlCrossRefPubMed
  48. ↵
    1. Cerami E,
    2. Gao J,
    3. Dogrusoz U,
    4. Gross BE,
    5. Sumer SO,
    6. Aksoy BA,
    7. Jacobsen A,
    8. Byrne CJ,
    9. Heuer ML,
    10. Larsson E,
    11. Antipin Y,
    12. Reva B,
    13. Goldberg AP,
    14. Sander C,
    15. Schultz N
    : The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov 2(5): 401-404, 2012. DOI: 10.1158/2159-8290.CD-12-0095
    OpenUrlAbstract/FREE Full Text
  49. ↵
    1. Gao J,
    2. Aksoy BA,
    3. Dogrusoz U,
    4. Dresdner G,
    5. Gross B,
    6. Sumer SO,
    7. Sun Y,
    8. Jacobsen A,
    9. Sinha R,
    10. Larsson E,
    11. Cerami E,
    12. Sander C,
    13. Schultz N
    : Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal 6(269): pl1, 2013. DOI: 10.1126/scisignal.2004088
    OpenUrlAbstract/FREE Full Text
  50. ↵
    1. Tamori S,
    2. Nozaki Y,
    3. Motomura H,
    4. Nakane H,
    5. Katayama R,
    6. Onaga C,
    7. Kikuchi E,
    8. Shimada N,
    9. Suzuki Y,
    10. Noike M,
    11. Hara Y,
    12. Sato K,
    13. Sato T,
    14. Yamamoto K,
    15. Hanawa T,
    16. Imai M,
    17. Abe R,
    18. Yoshimori A,
    19. Takasawa R,
    20. Tanuma SI,
    21. Akimoto K
    : Glyoxalase 1 gene is highly expressed in basal-like human breast cancers and contributes to survival of ALDH1-positive breast cancer stem cells. Oncotarget 9(92): 36515-36529, 2018. DOI: 10.18632/oncotarget.26369
    OpenUrlCrossRefPubMed
  51. ↵
    1. Onaga C,
    2. Tamori S,
    3. Matsuoka I,
    4. Ozaki A,
    5. Motomura H,
    6. Nagashima Y,
    7. Sato T,
    8. Sato K,
    9. Xiong Y,
    10. Sasaki K,
    11. Ohno S,
    12. Akimoto K
    : High expression of SLC20A1 is less effective for endocrine therapy and predicts late recurrence in ER-positive breast cancer. PLoS One 17(5): e0268799, 2022. DOI: 10.1371/journal.pone.0268799
    OpenUrlCrossRefPubMed
  52. ↵
    1. Onaga C,
    2. Tamori S,
    3. Matsuoka I,
    4. Ozaki A,
    5. Motomura H,
    6. Nagashima Y,
    7. Sato T,
    8. Sato K,
    9. Tahata K,
    10. Xiong Y,
    11. Nakano Y,
    12. Mano Y,
    13. Miyazaki S,
    14. Sasaki K,
    15. Ohno S,
    16. Akimoto K
    : High SLC20A1 expression is associated with poor prognosis for radiotherapy of estrogen receptor-positive breast cancer. Cancer Diagn Progn 2(4): 429-442, 2022. DOI: 10.21873/cdp.10126
    OpenUrlCrossRef
  53. ↵
    1. Cancer Genome Atlas Network
    : Comprehensive molecular portraits of human breast tumours. Nature 490(7418): 61-70, 2012. DOI: 10.1038/nature11412
    OpenUrlCrossRefPubMed
    1. Ding L,
    2. Bailey MH,
    3. Porta-Pardo E,
    4. Thorsson V,
    5. Colaprico A,
    6. Bertrand D,
    7. Gibbs DL,
    8. Weerasinghe A,
    9. Huang KL,
    10. Tokheim C,
    11. Cortés-Ciriano I,
    12. Jayasinghe R,
    13. Chen F,
    14. Yu L,
    15. Sun S,
    16. Olsen C,
    17. Kim J,
    18. Taylor AM,
    19. Cherniack AD,
    20. Akbani R,
    21. Suphavilai C,
    22. Nagarajan N,
    23. Stuart JM,
    24. Mills GB,
    25. Wyczalkowski MA,
    26. Vincent BG,
    27. Hutter CM,
    28. Zenklusen JC,
    29. Hoadley KA,
    30. Wendl MC,
    31. Shmulevich L,
    32. Lazar AJ,
    33. Wheeler DA,
    34. Getz G, Cancer Genome Atlas Research Network
    : Perspective on oncogenic processes at the end of the beginning of cancer genomics. Cell 173(2): 305-320.e10, 2018. DOI: 10.1016/j.cell.2018.03.033
    OpenUrlCrossRef
    1. Hoadley KA,
    2. Yau C,
    3. Hinoue T,
    4. Wolf DM,
    5. Lazar AJ,
    6. Drill E,
    7. Shen R,
    8. Taylor AM,
    9. Cherniack AD,
    10. Thorsson V,
    11. Akbani R,
    12. Bowlby R,
    13. Wong CK,
    14. Wiznerowicz M,
    15. Sanchez-Vega F,
    16. Robertson AG,
    17. Schneider BG,
    18. Lawrence MS,
    19. Noushmehr H,
    20. Malta TM, Cancer Genome Atlas Network,
    21. Stuart JM,
    22. Benz CC,
    23. Laird PW
    : Cell-of-origin patterns dominate the molecular classification of 10,000 tumors from 33 types of cancer. Cell 173(2): 291-304.e6, 2018. DOI: 10.1016/j.cell.2018.03.022
    OpenUrlCrossRefPubMed
  56. ↵
    1. Sanchez-Vega F,
    2. Mina M,
    3. Armenia J,
    4. Chatila WK,
    5. Luna A,
    6. La KC,
    7. Dimitriadoy S,
    8. Liu DL,
    9. Kantheti HS,
    10. Saghafinia S,
    11. Chakravarty D,
    12. Daian F,
    13. Gao Q,
    14. Bailey MH,
    15. Liang WW,
    16. Foltz SM,
    17. Shmulevich I,
    18. Ding L,
    19. Heins Z,
    20. Ochoa A,
    21. Gross B,
    22. Gao J,
    23. Zhang H,
    24. Kundra R,
    25. Kandoth C,
    26. Bahceci I,
    27. Dervishi L,
    28. Dogrusoz U,
    29. Zhou W,
    30. Shen H,
    31. Laird PW,
    32. Way GP,
    33. Greene CS,
    34. Liang H,
    35. Xiao Y,
    36. Wang C,
    37. Iavarone A,
    38. Berger AH,
    39. Bivona TG,
    40. Lazar AJ,
    41. Hammer GD,
    42. Giordano T,
    43. Kwong LN,
    44. McArthur G,
    45. Huang C,
    46. Tward AD,
    47. Frederick MJ,
    48. McCormick F,
    49. Meyerson M, Cancer Genome Atlas Research Network,
    50. Van Allen EM,
    51. Cherniack AD,
    52. Ciriello G,
    53. Sander C,
    54. Schultz N
    : Oncogenic signaling pathways in The Cancer Genome Atlas. Cell 173(2): 321-337.e10, 2018. DOI: 10.1016/j.cell.2018.03.035
    OpenUrlCrossRefPubMed
  57. ↵
    1. Nozaki Y,
    2. Tamori S,
    3. Inada M,
    4. Katayama R,
    5. Nakane H,
    6. Minamishima O,
    7. Onodera Y,
    8. Abe M,
    9. Shiina S,
    10. Tamura K,
    11. Kodama D,
    12. Sato K,
    13. Hara Y,
    14. Abe R,
    15. Takasawa R,
    16. Yoshimori A,
    17. Shinomiya N,
    18. Tanuma SI,
    19. Akimoto K
    : Correlation between c-Met and ALDH1 contributes to the survival and tumor-sphere formation of ALDH1 positive breast cancer stem cells and predicts poor clinical outcome in breast cancer. Genes Cancer 8(7-8): 628-639, 2017. DOI: 10.18632/genesandcancer.148
    OpenUrlCrossRefPubMed
  58. ↵
    1. Motomura H,
    2. Nozaki Y,
    3. Onaga C,
    4. Ozaki A,
    5. Tamori S,
    6. Shiina TA,
    7. Kanai S,
    8. Ohira C,
    9. Hara Y,
    10. Harada Y,
    11. Takasawa R,
    12. Hanawa T,
    13. Tanuma SI,
    14. Mano Y,
    15. Sato T,
    16. Sato K,
    17. Akimoto K
    : High expression of c-Met, PKCλ and ALDH1A3 predicts a poor prognosis in late-stage breast cancer. Anticancer Res 40(1): 35-52, 2020. DOI: 10.21873/anticanres.13924
    OpenUrlAbstract/FREE Full Text
  59. ↵
    1. Nozaki Y,
    2. Motomura H,
    3. Tamori S,
    4. Kimura Y,
    5. Onaga C,
    6. Kanai S,
    7. Ishihara Y,
    8. Ozaki A,
    9. Hara Y,
    10. Harada Y,
    11. Mano Y,
    12. Sato T,
    13. Sato K,
    14. Sasaki K,
    15. Ishiguro H,
    16. Ohno S,
    17. Akimoto K
    : High PKCλ expression is required for ALDH1-positive cancer stem cell function and indicates a poor clinical outcome in late-stage breast cancer patients. PLoS One 15(7): e0235747, 2020. DOI: 10.1371/journal.pone.0235747
    OpenUrlCrossRefPubMed
    1. Motomura H,
    2. Ozaki A,
    3. Tamori S,
    4. Onaga C,
    5. Nozaki Y,
    6. Waki Y,
    7. Takasawa R,
    8. Yoshizawa K,
    9. Mano Y,
    10. Sato T,
    11. Sasaki K,
    12. Ishiguro H,
    13. Miyagi Y,
    14. Nagashima Y,
    15. Yamamoto K,
    16. Sato K,
    17. Hanawa T,
    18. Tanuma SI,
    19. Ohno S,
    20. Akimoto K
    : Glyoxalase 1 and protein kinase Cλ as potential therapeutic targets for late-stage breast cancer. Oncol Lett 22(1): 547, 2021. DOI: 10.3892/ol.2021.12808
    OpenUrlCrossRefPubMed
  61. ↵
    1. Onaga C,
    2. Tamori S,
    3. Motomura H,
    4. Ozaki A,
    5. Matsuda C,
    6. Matsuoka I,
    7. Fujita T,
    8. Nozaki Y,
    9. Hara Y,
    10. Kawano Y,
    11. Harada Y,
    12. Sato T,
    13. Mano Y,
    14. Sato K,
    15. Akimoto K
    : High SLC20A1 expression is associated with poor prognoses in claudin-low and basal-like breast cancers. Anticancer Res 41(1): 43-54, 2021. DOI: 10.21873/anticanres.14750
    OpenUrlAbstract/FREE Full Text
    1. Xiong Y,
    2. Motomura H,
    3. Tamori S,
    4. Ozaki A,
    5. Onaga C,
    6. Hara Y,
    7. Sato K,
    8. Tahata K,
    9. Harada Y,
    10. Sasaki K,
    11. Zheng Y,
    12. Ohno S,
    13. Akimoto K
    : High expression of CD58 and ALDH1A3 predicts a poor prognosis in basal-like breast cancer. Anticancer Res 42(11): 5223-5232, 2022. DOI: 10.21873/anticanres.16029
    OpenUrlAbstract/FREE Full Text
  63. ↵
    1. Kasai T,
    2. Tamori S,
    3. Takasaki Y,
    4. Matsuoka I,
    5. Ozaki A,
    6. Matsuda C,
    7. Harada Y,
    8. Sasaki K,
    9. Ohno S,
    10. Akimoto K
    : High expression of PKCλ and ALDH1A3 indicates a poor prognosis, and PKCλ is required for the asymmetric cell division of ALDH1A3-positive cancer stem cells in PDAC. Biochem Biophys Res Commun 669: 85-94, 2023. DOI: 10.1016/j.bbrc.2023.05.086
    OpenUrlCrossRef
  64. ↵
    1. Okamoto T,
    2. Onaga C,
    3. Matsuoka I,
    4. Ozaki A,
    5. Matsuda C,
    6. Kasai T,
    7. Xiong Y,
    8. Harada Y,
    9. Sato T,
    10. Nakano Y,
    11. Mano Y,
    12. Miyazaki S,
    13. Ishiguro H,
    14. Sato K,
    15. Tamori S,
    16. Sasaki K,
    17. Ohno S,
    18. Akimoto K
    : High SLC20A1 expression indicates poor prognosis in prostate cancer. Cancer Diagn Progn 3(4): 439-448, 2023. DOI: 10.21873/cdp.10237
    OpenUrlCrossRef
  65. ↵
    1. Kim DH,
    2. Behlke MA,
    3. Rose SD,
    4. Chang MS,
    5. Choi S,
    6. Rossi JJ
    : Synthetic dsRNA Dicer substrates enhance RNAi potency and efficacy. Nat Biotechnol 23(2): 222-226, 2005. DOI: 10.1038/nbt1051
    OpenUrlCrossRefPubMed
  66. ↵
    1. Motomura H,
    2. Tamori S,
    3. Yatani MA,
    4. Namiki A,
    5. Onaga C,
    6. Ozaki A,
    7. Takasawa R,
    8. Mano Y,
    9. Sato T,
    10. Hara Y,
    11. Sato K,
    12. Xiong Y,
    13. Harada Y,
    14. Hanawa T,
    15. Tanuma SI,
    16. Sasaki K,
    17. Ohno S,
    18. Akimoto K
    : GLO 1 and PKCλ regulate ALDH1-positive breast cancer stem cell survival. Anticancer Res 41(12): 5959-5971, 2021. DOI: 10.21873/anticanres.15415
    OpenUrlAbstract/FREE Full Text
  67. ↵
    1. Santivasi WL,
    2. Xia F
    : Ionizing radiation-induced DNA damage, response, and repair. Antioxid Redox Signal 21(2): 251-259, 2014. DOI: 10.1089/ars.2013.5668
    OpenUrlCrossRefPubMed
    1. Feinendegen LE
    : Reactive oxygen species in cell responses to toxic agents. Hum Exp Toxicol 21(2): 85-90, 2002. DOI: 10.1191/0960327102ht216oa
    OpenUrlCrossRefPubMed
    1. Spitz DR,
    2. Azzam EI,
    3. Jian Li J,
    4. Gius D
    : Metabolic oxidation/reduction reactions and cellular responses to ionizing radiation: A unifying concept in stress response biology. Cancer Metastasis Rev 23(3/4): 311-322, 2004. DOI: 10.1023/B:CANC.0000031769.14728.bc
    OpenUrlCrossRefPubMed
  70. ↵
    1. Kam WW,
    2. Banati RB
    : Effects of ionizing radiation on mitochondria. Free Radic Biol Med 65: 607-619, 2013. DOI: 10.1016/j.freeradbiomed.2013.07.024
    OpenUrlCrossRefPubMed
  71. ↵
    1. Li X,
    2. Chen J,
    3. Yuan S,
    4. Zhuang X,
    5. Qiao T
    : Activation of the P62-Keap1-NRF2 pathway protects against ferroptosis in radiation-induced lung injury. Oxid Med Cell Longev 2022: 8973509, 2022. DOI: 10.1155/2022/8973509
    OpenUrlCrossRef
  72. ↵
    1. Wang Y,
    2. Zhang N,
    3. Zhang L,
    4. Li R,
    5. Fu W,
    6. Ma K,
    7. Li X,
    8. Wang L,
    9. Wang J,
    10. Zhang H,
    11. Gu W,
    12. Zhu W,
    13. Zhao Y
    : Autophagy regulates chromatin ubiquitination in DNA damage response through elimination of SQSTM1/p62. Mol Cell 63(1): 34-48, 2016. DOI: 10.1016/j.molcel.2016.05.027
    OpenUrlCrossRefPubMed
  73. ↵
    1. Lee M,
    2. Nam HY,
    3. Kang HB,
    4. Lee WH,
    5. Lee GH,
    6. Sung GJ,
    7. Han MW,
    8. Cho KJ,
    9. Chang EJ,
    10. Choi KC,
    11. Kim SW,
    12. Kim SY
    : Epigenetic regulation of p62/SQSTM1 overcomes the radioresistance of head and neck cancer cells via autophagy-dependent senescence induction. Cell Death Dis 12(3): 250, 2021. DOI: 10.1038/s41419-021-03539-5
    OpenUrlCrossRef
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Luminal B Breast Cancer Coexpressing p62 and ALDH1A3 Is Less Susceptible to Radiotherapy
AYAKA OZAKI, AKARI MATSUDA, YUKI MAEMURA, YUNA TADA, TAKAHIRO KASAI, YUKA NAGASHIMA, CHOTARO ONAGA, YASUSHI HARA, KAZUKI KITABATAKE, MITSUTOSHI TSUKIMOTO, SHOMA TAMORI, KAZUNORI SASAKI, SHIGEO OHNO, KAZUNORI AKIMOTO
Anticancer Research Jan 2024, 44 (1) 37-47; DOI: 10.21873/anticanres.16786
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