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High levels of unfolded protein response component CHAC1 associates with cancer progression signatures in malignant breast cancer tissues

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Abstract

Purpose

The aberrant mRNA expression of a UPR component Cation transport regulator homolog 1 (CHAC1) has been reported to be associated with poor survival in breast and ovarian cancer patients, however, the expression of CHAC1 at protein levels in malignant breast tissues is underreported. The following study aimed at analyzing CHAC1 protein expression in malignant breast cancer tissues.

Methods

Evaluation of CHAC1 expression in invasive ductal carcinomas (IDCs) with known ER, PR, and HER2 status was carried out using immunohistochemistry (IHC) with CHAC1 specific antibody. The Human breast cancer tissue microarray (TMA, cat# BR1503f, US Biomax, Inc., Rockville, MD) was used to determine CHAC1 expression. The analysis of CHAC1 IHC was done to determine its expression in terms of molecular subtypes of breast cancer, lymph node status, and proliferation index using Qu-Path software. Survival analysis was studied with a Kaplan–Meier plotter.

Results

Immunohistochemical analysis of CHAC1 in breast cancer tissues showed significant up-regulation of CHAC1 as compared to the adjacent normal and benign tissues. Interestingly, CHAC1 immunostaining revealed high expression in tumor tissues with high proliferation and positive lymph node metastasis suggesting that CHAC1 might have an important role to play in breast cancer progression. Furthermore, high CHAC1 expression is associated with poor overall survival (OS) in large breast cancer patient cohorts.

Conclusion

As a higher expression of CHAC1 was observed in tissue cores with high Ki67 index and positive lymph node metastasis it may be concluded that enhanced CHAC1 expression correlates with proliferation and metastasis. The further analysis of breast cancer patients’ survival data through KM plot indicated that high CHAC1 expression is associated with a bad prognosis hinting that CHAC1 may have a possible prognostic significance in breast cancer.

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References:

  1. T Avril E Vauleon E Chevet 2017 Endoplasmic reticulum stress signaling and chemotherapy resistance in solid cancers Oncogenesis 6 8 e373 https://doi.org/10.1038/oncsis.2017.72

  2. Clarke HJ, Chambers JE, Liniker E, Marciniak SJ. Endoplasmic reticulum stress in malignancy. Cancer Cell. 2014;25(5):563–73. https://doi.org/10.1016/j.ccr.2014.03.015.

    Article  CAS  PubMed  Google Scholar 

  3. Madden E, Logue SE, Healy SJ, Manie S, Samali A. The role of the unfolded protein response in cancer progression: from oncogenesis to chemoresistance. Biol Cell. 2019;111(1):1–17. https://doi.org/10.1111/boc.201800050.

    Article  PubMed  Google Scholar 

  4. Chevet E, Hetz C, Samali A. Endoplasmic reticulum stress–activated cell reprogramming in oncogenesis. Cancer Discov. 2015;5(6):586–97. https://doi.org/10.1158/2159-8290.CD-14-1490.

    Article  CAS  PubMed  Google Scholar 

  5. McGrath EP, Logue SE, Mnich K, Deegan S, Jäger R, Gorman AM, et al. The unfolded protein response in breast cancer. Cancers. 2018;10(10):344. https://doi.org/10.3390/cancers10100344.

    Article  CAS  PubMed Central  Google Scholar 

  6. Mungrue IN, Pagnon J, Kohannim O, Gargalovic PS, Lusis AJ. CHAC1/MGC4504 is a novel proapoptotic component of the unfolded protein response, downstream of the ATF4-ATF3-CHOP cascade. J Immunol. 2009;182(1):466–76. https://doi.org/10.4049/jimmunol.182.1.466.

    Article  CAS  PubMed  Google Scholar 

  7. Kumar A, Tikoo S, Maity S, Sengupta S, Sengupta S, Kaur A, et al. Mammalian proapoptotic factor ChaC1 and its homologues function as γ-glutamyl cyclotransferases acting specifically on glutathione. EMBO Rep. 2012;13(12):1095–101. https://doi.org/10.1038/embor.2012.156.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Gargalovic PS, Imura M, Zhang B, Gharavi NM, Clark MJ, Pagnon J, et al. Identification of inflammatory gene modules based on variations of human endothelial cell responses to oxidized lipids. Proc Natl Acad Sci. 2006;103(34):12741–6. https://doi.org/10.1073/pnas.0605457103.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Perra L, Balloy V, Foussignière T, Moissenet D, Petat H, Mungrue IN, et al. CHAC1 is differentially expressed in normal and cystic fibrosis bronchial epithelial cells and regulates the inflammatory response induced by Pseudomonas aeruginosa. Front Immunol. 2018;9:2823. https://doi.org/10.3389/fimmu.2018.02823.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Li S, Jia Y, Xue M, Hu F, Zheng Z, Zhang S, et al. Inhibiting Rab27a in renal tubular epithelial cells attenuates the inflammation of diabetic kidney disease through the miR-26a-5p/CHAC1/NF-kB pathway. Life Sci. 2020;261: 118347. https://doi.org/10.1016/j.lfs.2020.118347.

    Article  CAS  PubMed  Google Scholar 

  11. Chen M-S, Wang S-F, Hsu C-Y, Yin P-H, Yeh T-S, Lee H-C, et al. CHAC1 degradation of glutathione enhances cystine-starvation-induced necroptosis and ferroptosis in human triple negative breast cancer cells via the GCN2-eIF2α-ATF4 pathway. Oncotarget. 2017;8(70): 114588. https://doi.org/10.18632/oncotarget.23055.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Wang N, Zeng G-Z, Yin J-L, Bian Z-X. Artesunate activates the ATF4-CHOP-CHAC1 pathway and affects ferroptosis in Burkitt’s Lymphoma. Biochem Biophys Res Commun. 2019;519(3):533–9. https://doi.org/10.1016/j.bbrc.2019.09.023.

    Article  CAS  PubMed  Google Scholar 

  13. Ogawa T, Wada Y, Takemura K, Board PG, Uchida K, Kitagaki K, et al. CHAC1 overexpression in human gastric parietal cells with Helicobacter pylori infection in the secretory canaliculi. Helicobacter. 2019;24(4): e12598. https://doi.org/10.1111/hel.12598.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wada Y, Takemura K, Tummala P, Uchida K, Kitagaki K, Furukawa A, et al. Helicobacter pylori induces somatic mutations in TP 53 via overexpression of CHAC 1 in infected gastric epithelial cells. FEBS Open Bio. 2018;8(4):671–9. https://doi.org/10.1002/2211-5463.12402.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Liu Y, Li M, Shi D, Zhu Y. Higher expression of cation transport regulator-like protein 1 (CHAC1) predicts of poor outcomes in uveal melanoma (UM) patients. Int Opthalmol. 2019;39(12):2825–32. https://doi.org/10.1007/s10792-019-01129-1.

    Article  Google Scholar 

  16. Stelzer Y, Yanuka O, Benvenisty N. Global analysis of parental imprinting in human parthenogenetic induced pluripotent stem cells. Nat Struct Biol. 2011;18(6):735. https://doi.org/10.1038/nsmb.2050.

    Article  CAS  Google Scholar 

  17. Chen X, Iliopoulos D, Zhang Q, Tang Q, Greenblatt MB, Hatziapostolou M, et al. XBP1 promotes triple-negative breast cancer by controlling the HIF1α pathway. Nature. 2014;508(7494):103–7. https://doi.org/10.1038/nature13119.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Cook KL, Clarke R. Role of GRP78 in promoting therapeutic-resistant breast cancer. Future Med Chem. 2015;7(12):1529–34. https://doi.org/10.4155/FMC.15.80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Goebel G, Berger R, Strasak A, Egle D, Müller-Holzner E, Schmidt S, et al. Elevated mRNA expression of CHAC1 splicing variants is associated with poor outcome for breast and ovarian cancer patients. Br J Cancer. 2012;106(1):189–98. https://doi.org/10.1038/bjc.2011.510.

    Article  CAS  PubMed  Google Scholar 

  20. Jahn B, Arvandi M, Rochau U, Fiegl H, Goebel G, Marth C, et al. Development of a novel prognostic score for breast cancer patients using mRNA expression of CHAC1. J Comp Eff Res. 2017;6(7):563–74. https://doi.org/10.2217/cer-2017-0015.

    Article  PubMed  Google Scholar 

  21. Chander H, Truesdell P, Meens J, Craig AW. Transducer of Cdc42-dependent actin assembly promotes breast cancer invasion and metastasis. Oncogene. 2013;32(25):3080–90. https://doi.org/10.1038/onc.2012.317.

    Article  CAS  PubMed  Google Scholar 

  22. Suman P, Mehta V, Craig AW, Chander H. Wild-type p53 suppresses formin-binding protein-17 (FBP17) to reduce invasion. Carcinogenesis. 2022;43(5):494–503. https://doi.org/10.1093/carcin/bgac015.

    Article  PubMed  Google Scholar 

  23. Bankhead P, Loughrey MB, Fernandez JA, Dombrowski Y, McArt DG, Dunne PD, et al. QuPath: open source software for digital pathology image analysis. Sci Rep. 2017;7(1):16878. https://doi.org/10.1038/s41598-017-17204-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Ramachandran P, Dobie R, Wilson-Kanamori J, Dora E, Henderson B, Luu N, et al. Resolving the fibrotic niche of human liver cirrhosis at single-cell level. Nature. 2019;575(7783):512–8. https://doi.org/10.1038/s41586-019-1631-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Györffy B, Lanczky A, Eklund AC, Denkert C, Budczies J, Li Q, et al. An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients. Breast Cancer Res Treat. 2010;123(3):725–31. https://doi.org/10.1007/s10549-009-0674-9.

    Article  CAS  PubMed  Google Scholar 

  26. Rivenbark AG, O’Connor SM, Coleman WB. Molecular and cellular heterogeneity in breast cancer: challenges for personalized medicine. Am J Pathol. 2013;183(4):1113–24. https://doi.org/10.1016/j.ajpath.2013.08.002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Butti R, Das S, Gunasekaran VP, Yadav AS, Kumar D, Kundu GC. Receptor tyrosine kinases (RTKs) in breast cancer: signaling, therapeutic implications and challenges. Mol Cancer. 2018;17(1):34. https://doi.org/10.1186/s12943-018-0797-x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Du Z, Lovly CM. Mechanisms of receptor tyrosine kinase activation in cancer. Mol Cancer. 2018;17(1):58. https://doi.org/10.1186/s12943-018-0782-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Weigelt B, Ng CK, Shen R, Popova T, Schizas M, Natrajan R, et al. Metastatic breast carcinomas display genomic and transcriptomic heterogeneity. Mod Pathol. 2015;28(3):340–51. https://doi.org/10.1038/modpathol.2014.163.

    Article  CAS  PubMed  Google Scholar 

  30. Mehta V, Chander H, Munshi A. Complex roles of discoidin domain receptor tyrosine kinases in cancer. Clin TranslOncol. 2021;23(8):1497–1510. https://doi.org/10.1007/s12094-021-02552-6.

    Article  CAS  Google Scholar 

  31. Prat A, Pineda E, Adamo B, Galván P, Fernández A, Gaba L, et al. Clinical implications of the intrinsic molecular subtypes of breast cancer. The Breast. 2015;24:S26–35. https://doi.org/10.1016/j.breast.2015.07.008.

    Article  PubMed  Google Scholar 

  32. Cheang MC, Chia SK, Voduc D, Gao D, Leung S, Snider J, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst. 2009;101(10):736–50. https://doi.org/10.1093/jnci/djp082.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Feeley LP, Mulligan AM, Pinnaduwage D, Bull SB, Andrulis IL. Distinguishing luminal breast cancer subtypes by Ki67, progesterone receptor or TP53 status provides prognostic information. Mod Pathol. 2014;27(4):554–61. https://doi.org/10.1038/modpathol.2013.153.

    Article  CAS  PubMed  Google Scholar 

  34. De Azambuja E, Cardoso F, de Castro G, Colozza M, Mano MS, Durbecq V, et al. Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12 155 patients. Br J Cancer. 2007;96(10):1504–13. https://doi.org/10.1038/sj.bjc.6603756.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Hashmi AA, Hashmi KA, Irfan M, Khan SM, Edhi MM, Ali JP, et al. Ki67 index in intrinsic breast cancer subtypes and its association with prognostic parameters. BMC Res Notes. 2019;12(1):1–5. https://doi.org/10.1186/s13104-019-4653-x.

    Article  CAS  Google Scholar 

  36. Yerushalmi R, Woods R, Ravdin PM, Hayes MM, Gelmon KA. Ki67 in breast cancer: prognostic and predictive potential. Lancet Oncol. 2010;11(2):174–83. https://doi.org/10.1016/S1470-2045(09)70262-1.

    Article  CAS  PubMed  Google Scholar 

  37. Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6(269):pl1-pl1. https://doi.org/10.1126/scisignal.2004088.

  38. Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. AACR; 2012.

  39. Ji R-C. Lymph nodes and cancer metastasis: new perspectives on the role of intranodal lymphatic sinuses. Int J Mol Sci. 2017;18(1):51. https://doi.org/10.3390/ijms18010051.

    Article  CAS  Google Scholar 

  40. Stacker SA, Achen MG, Jussila L, Baldwin ME, Alitalo K. Lymphangiogenesis and cancer metastasis. Nat Rev Cancer. 2002;2(8):573–83. https://doi.org/10.1038/nrc863.

    Article  CAS  PubMed  Google Scholar 

  41. Mehta V, Meena J, Kasana H, Munshi A, Chander H. Prognostic significance of CHAC1 expression in breast cancer. Mol Biol Rep. 2022:1–10. doi:https://doi.org/10.1007/s11033-022-07673-x

  42. Russnes HG, Navin N, Hicks J, Borresen-Dale A-L. Insight into the heterogeneity of breast cancer through next-generation sequencing. J Clin Invest. 2011;121(10):3810–8. https://doi.org/10.1172/JCI57088.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Kalinowski L, Saunus JM, Reed AEM, Lakhani SR. Breast Cancer Heterogeneity in Primary and Metastatic Disease. Breast Cancer Metastasis and Drug Resistance. Springer; 2019. p. 75–104.

  44. Riggio AI, Varley KE, Welm AL. The lingering mysteries of metastatic recurrence in breast cancer. Br J Cancer. 2020;124(1):1–14. https://doi.org/10.1038/s41416-020-01161-4.

    Article  Google Scholar 

  45. Turashvili G, Brogi E. Tumor heterogeneity in breast cancer. Front Med. 2017;4:227. https://doi.org/10.3389/fmed.2017.00227.

    Article  Google Scholar 

  46. Pece S, Tosoni D, Confalonieri S, Mazzarol G, Vecchi M, Ronzoni S, et al. Biological and molecular heterogeneity of breast cancers correlates with their cancer stem cell content. Cell. 2010;140(1):62–73. https://doi.org/10.1016/j.cell.2009.12.007.

    Article  CAS  PubMed  Google Scholar 

  47. Kamdje AHN, Etet PFS, Vecchio L, Muller JM, Krampera M, Lukong KE. Signaling pathways in breast cancer: therapeutic targeting of the microenvironment. Cell Signal. 2014;26(12):2843–56. https://doi.org/10.1016/j.cellsig.2014.07.034.

    Article  CAS  Google Scholar 

  48. Eroles P, Bosch A, Pérez-Fidalgo JA, Lluch A. Molecular biology in breast cancer: intrinsic subtypes and signaling pathways. Cancer Treat Rev. 2012;38(6):698–707. https://doi.org/10.1016/j.ctrv.2011.11.005.

    Article  CAS  PubMed  Google Scholar 

  49. Scriven P, Coulson S, Haines R, Balasubramanian S, Cross S, Wyld L. Activation and clinical significance of the unfolded protein response in breast cancer. Br J Cancer. 2009;101(10):1692–8. https://doi.org/10.1038/sj.bjc.6605365.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Suman P, Mishra S, Chander H. High formin binding protein 17 (FBP17) expression indicates poor differentiation and invasiveness of ductal carcinomas. Sci Rep. 2020;10(1):1–10. https://doi.org/10.1038/s41598-020-68454-9.

    Article  CAS  Google Scholar 

  51. Giudici F, Petracci E, Nanni O, Bottin C, Pinamonti M, Zanconati F, et al. Elevated levels of eEF1A2 protein expression in triple negative breast cancer relate with poor prognosis. PLoS ONE. 2019;14(6): e0218030. https://doi.org/10.1371/journal.pone.0218030.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Cerqueira OL, Truesdell P, Baldassarre T, Vilella-Arias SA, Watt K, Meens J, et al. CIP4 promotes metastasis in triple-negative breast cancer and is associated with poor patient prognosis. Oncotarget. 2015;6(11):9397. https://doi.org/10.18632/oncotarget.3351.

    Article  PubMed  PubMed Central  Google Scholar 

  53. van de Vijver MJ, Peterse JL, Mooi WJ, Wisman P, Lomans J, Dalesio O, et al. Neu-protein overexpression in breast cancer. N Engl J Med. 1988;319(19):1239–45. https://doi.org/10.1056/NEJM198811103191902.

    Article  PubMed  Google Scholar 

  54. Zhang K, Liu H, Song Z, Jiang Y, Kim H, Samavati L, et al. The UPR Transducer IRE1 promotes breast cancer malignancy by degrading tumor suppressor microRNAs. Iscience. 2020;23(9): 101503. https://doi.org/10.1016/j.isci.2020.101503.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Li H, Chen X, Gao Y, Wu J, Zeng F, Song F. XBP1 induces snail expression to promote epithelial-to-mesenchymal transition and invasion of breast cancer cells. Cell Signal. 2015;27(1):82–9. https://doi.org/10.1016/j.cellsig.2014.09.018.

    Article  CAS  PubMed  Google Scholar 

  56. Pathmanathan N, Balleine RL. Ki67 and proliferation in breast cancer. J Clin Pathol. 2013;66(6):512–6. https://doi.org/10.1136/jclinpath-2012-201085.

    Article  CAS  PubMed  Google Scholar 

  57. van Diest PJ, van der Wall E, Baak JP. Prognostic value of proliferation in invasive breast cancer: a review. J Clin Pathol. 2004;57(7):675–81. https://doi.org/10.1136/jcp.2003.010777.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Gerashchenko TS, Novikov NM, Krakhmal NV, Zolotaryova SY, Zavyalova MV, Cherdyntseva NV, et al. Markers of cancer cell invasion: are they good enough? J Clin Med. 2019;8(8):1092. https://doi.org/10.3390/jcm8081092.

    Article  CAS  PubMed Central  Google Scholar 

  59. Wu J, Wang X, Wang N, Ma L, Xie X, Zhang H, et al. Identification of novel antioxidant gene signature to predict the prognosis of patients with gastric cancer. World J Surg Oncol. 2021;19(1):1–11. https://doi.org/10.1186/s12957-021-02328-w.

    Article  CAS  Google Scholar 

  60. Xiao R, Wang S, Guo J, Liu S, Ding A, Wang G, et al. Ferroptosis-related gene NOX4, CHAC1 and HIF1A are valid biomarkers for stomach adenocarcinoma. J Cell Mol Med. 2022. https://doi.org/10.1111/jcmm.17171.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Hong Y, Lin M, Ou D, Huang Z, Shen P. A novel ferroptosis-related 12-gene signature predicts clinical prognosis and reveals immune relevancy in clear cell renal cell carcinoma. BMC Cancer. 2021;21(1):1–14. https://doi.org/10.1186/s12885-021-08559-0.

    Article  CAS  Google Scholar 

  62. Tang W, Xu F, Zhao M, Zhang S. Ferroptosis regulators, especially SQLE, play an important role in prognosis, progression and immune environment of breast cancer. BMC Cancer. 2021;21(1):1–19. https://doi.org/10.1186/s12885-021-08892-4.

    Article  CAS  Google Scholar 

  63. Liu C, Liu Y, Yu Y, Zhao Y, Yu A. Comprehensive analysis of ferroptosis-related genes and prognosis of cutaneous melanoma. BMC Med Genomics. 2022;15(1):1–17. https://doi.org/10.1186/s12920-022-01194-z.

    Article  CAS  Google Scholar 

  64. Xu Z, Xie Y, Mao Y, Huang J, Mei X, Song J et al. Ferroptosis-related gene signature predicts the prognosis of skin cutaneous melanoma and response to immunotherapy. Front Genet. 2021;12. doi:https://doi.org/10.3389/fgene.2021.758981.

  65. Nguyen J, Tirla A, Rivera-Fuentes P. Disruption of mitochondrial redox homeostasis by enzymatic activation of a trialkylphosphine probe. Org Biomol Chem. 2021;19(12):2681–7. https://doi.org/10.1039/d0ob02259d.

    Article  CAS  PubMed  Google Scholar 

  66. Wang Z, Li M, Liu Y, Qiao Z, Bai T, Yang L, et al. Dihydroartemisinin triggers ferroptosis in primary liver cancer cells by promoting and unfolded protein response-induced upregulation of CHAC1 expression. Oncol Rep. 2021;46(5):1–14. https://doi.org/10.3892/or.2021.8191.

    Article  CAS  Google Scholar 

  67. Li D, Liu S, Xu J, Chen L, Xu C, Chen F, et al. Ferroptosis-related gene CHAC1 is a valid indicator for the poor prognosis of kidney renal clear cell carcinoma. J Cell Mol Med. 2021;25(7):3610–21.

    Article  CAS  Google Scholar 

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Acknowledgements

The authors are thankful for the help from the faculty and technical staff of the Department of Histopathology, PGIMER Chandigarh, India. We would like to acknowledge ICMR, New Delhi for providing a Senior research fellowship (SRF) to V.M. We thank Prof. Anjana Munshi for her administrative help to V.M.

Funding

The study received funding from the Department of Science and Technology-Science and Engineering Research Board (DST-SERB), India (Grant No. EMR/2015/000761 & EEQ/2017/000794).

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Authors and Affiliations

  1. Laboratory of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Central University of Punjab, Bathinda, 151401, India

    Vikrant Mehta, Prabhat Suman & Harish Chander

  2. Biotherapeutics Division, National Institute of Biologicals, Noida, 201309, India

    Harish Chander

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Contributions

V.M and H.C designed the study. V.M and H.C. performed the experimental work. P.S contributed to experimental work in part. V.M and H.C drafted the figures and prepared the manuscript. All the authors analyzed the data and reviewed the manuscript.

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Correspondence to Harish Chander.

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The public database used in this study includes Kaplan–Meier Plotter for CHAC1 transcripts (https://kmplot.com/analysis/index.php?p=service), cBioportal for correlation analysis between Ki67 and CHAC1 (https://www.cbioportal.org/).

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Fig. S1

Specificity and validation of CHAC1 antibody. (a) Breast Cancer tissue stained with CHAC1 antibody, where CHAC1 antibody showed immunoreactivity. (b) Breast Cancer tissue showed no immunoreactivity towards CHAC1 by the antibody that was incubated with immunoprecipitated CHAC1 from the cell lysate. (c) CHAC1 Immunoblot after siRNA transfection at indicated doses in MCF7 cells. (d) Densitometric analysis of CHAC1 expression in MCF7 cells. (e) CHAC1 Immunoblot after siRNA transfection at indicated doses in SKBR3 cells. (f) Densitometric analysis of CHAC1 expression in SKBR3 cells. Fig. S2a Representative photomicrographs of the malignant cores of low (Ki67<25%) and high (Ki67>25%) index. Fig. S2b Representative photomicrographs of the malignant cores of negative and positive lymph node metastasis. Fig. S3 Correlation analysis of CHAC1 expression shows a positive correlation with Ki67 from cBioportal using (a) microarray and (b) RSEM data (TCGA, Firehose legacy dataset; n=1108). Fig. S4. Analysis of CHAC1 expression with tumor stage. Fig. S5. Distant metastasis-free survival plot as per CHAC1 expression in (a) metastatic (n=889, HR=1.62, logrank p=0.00016) vs (b) non-metastatic patients (n=1309, HR=1.5, logrank p=0.0013). (PDF 205 KB).

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Mehta, V., Suman, P. & Chander, H. High levels of unfolded protein response component CHAC1 associates with cancer progression signatures in malignant breast cancer tissues. Clin Transl Oncol 24, 2351–2365 (2022). https://doi.org/10.1007/s12094-022-02889-6

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