PreprintCited by 12Caveolin-1 and cellular processesMechanisms of cancer metastasisCancer Cells and Metastasis

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Caveolin-1 Knockout Mitigates Breast Cancer Metastasis to the Lungs via Integrin α3 Dysregulation.

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Preprint — published as 10.1038/s41417-024-00821-4 · Paper page

Abstract

Caveolin-1 (Cav-1) is a critical lipid raft protein playing divergent roles as both a tumor suppressor and promoter. While its role in tumorigenesis, progression, and metastasis is recognized, explicit contribution of Cav-1 to the onset of lung metastasis from primary breast malignancies remained vague. We exhibit here, the first-ever evidence of Cav-1 knockout in epithelial cells leading to a significant reduction in lung metastasis in syngeneic mouse models of breast cancer. In vitro, Cav-1 knockout in 4T1 cells suppressed extracellular vesicles secretion, cellular motility, and MMP secretion vis-à-vis the controls. Complementing this, our in vivo analyses demonstrated a marked reduction in lung metastatic foci in mice injected with Cav-1 knockout 4T1 cells as compared to wild-type mice, which was further corroborated by mRNA profiling of the primary tumor. We discerned 21 epithelial cell migration genes exhibiting varied expression in tumors derived from Cav-1 knockout versus wild-type 4T1 cells. Correlation analysis and immunoblotting further divulged that Cav-1 regulates metastasis via integrin α3 (ITGα3). In silico protein docking anticipated an interaction between Cav-1 and ITGα3, substantiated by co-immunoprecipitation. Furthermore, ITGα3 knockdown corroborated its role in metastasis in a cell migration assay. Therefore, it can be inferred that Cav-1 plays a pivotal role in the pre-metastatic niche establishment and facilitates lung-specific cell migration.

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Fig. 1 Characterization of the effects of Cav-1 deficiency in 4T1 cells. CRISPR/Cas9 was used to target Cav-1 in 4T1 cells. A Immunoblot showing absence of Cav-1 protein expression in purified Cav-1 knockout cells as compared to control 4T1 cells. B MTT assay showing that knocking out Cav-1 did not affect cell viability at 48 h. C Cell cycle assay showing no significant differences in the diverse phases of cell growth using flow cytometry. D The cell mitochondrial stress assay showed no significant effect on mitochondrial respiration in Cav-1 KO mice compared to control 4T1 cells using an Agilent Seahorse XF Analyzer. E SEM Image showing comparative cell surface morphology. F TEM images show altered membrane morphology and vesicle release. G Immunoblot showing reduced expression of exosome markers in the extracellular vesicles isolated from Cav-1 KO cell growth media and control after 24 h. H Densitometry data showing reduced expression of Annexin V and Alix in Cav-1 KO conditioned media compared to WT 4T1 conditioned media. I Wound healing assay showing reduced migration ability of Cav-1 KO cells compared to control 4T1 cells. J MMP fluorometric assay showed significantly reduced secretion of MMPs in Cav-1 KO mice compared to control 4T1 cells in conditioned media. Statistical analysis was performed using unpaired Student’s t-test *P < 0.05; ***P < 0.001.
Fig. 1 Characterization of the effects of Cav-1 deficiency in 4T1 cells. CRISPR/Cas9 was used to target Cav-1 in 4T1 cells. A Immunoblot showing absence of Cav-1 protein expression in purified Cav-1 knockout cells as compared to control 4T1 cells. B MTT assay showing that knocking out Cav-1 did not affect cell viability at 48 h. C Cell cycle assay showing no significant differences in the diverse phases of cell growth using flow cytometry. D The cell mitochondrial stress assay showed no significant effect on mitochondrial respiration in Cav-1 KO mice compared to control 4T1 cells using an Agilent Seahorse XF Analyzer. E SEM Image showing comparative cell surface morphology. F TEM images show altered membrane morphology and vesicle release. G Immunoblot showing reduced expression of exosome markers in the extracellular vesicles isolated from Cav-1 KO cell growth media and control after 24 h. H Densitometry data showing reduced expression of Annexin V and Alix in Cav-1 KO conditioned media compared to WT 4T1 conditioned media. I Wound healing assay showing reduced migration ability of Cav-1 KO cells compared to control 4T1 cells. J MMP fluorometric assay showed significantly reduced secretion of MMPs in Cav-1 KO mice compared to control 4T1 cells in conditioned media. Statistical analysis was performed using unpaired Student’s t-test *P < 0.05; ***P < 0.001.CC BY · PubMed Central
Fig. 2 Cav-1 regulates 4T1 growth and lung metastasis in vivo. 4T1 cells were injected into the mammary pads of BALB/c mice. Tumor progression and lung metastasis were followed for 4 weeks: A Green arrow in the image showing delayed tumor growth in Cav-1 KO injected mice compared to WT 4T1 injected mice at the end of week 1; B comparative tumor area (length × width) at the end of weeks 2 and 3; C Graph showing relative tumor weight at the end of weeks 2 and 3; D Image showing visible metastatic lesions in the WT lungs at the end of week 4, which were not present in the Cav-1 KO cell-injected mice; E H&E staining of lungs, yellow arrows show metastatic foci in WT, but no metastasis was seen in Cav-1 KO cells injected lungs at different time points. Statistical analysis was performed using unpaired Student’s t-test *P < 0.05; ***P < 0.001.
Fig. 2 Cav-1 regulates 4T1 growth and lung metastasis in vivo. 4T1 cells were injected into the mammary pads of BALB/c mice. Tumor progression and lung metastasis were followed for 4 weeks: A Green arrow in the image showing delayed tumor growth in Cav-1 KO injected mice compared to WT 4T1 injected mice at the end of week 1; B comparative tumor area (length × width) at the end of weeks 2 and 3; C Graph showing relative tumor weight at the end of weeks 2 and 3; D Image showing visible metastatic lesions in the WT lungs at the end of week 4, which were not present in the Cav-1 KO cell-injected mice; E H&E staining of lungs, yellow arrows show metastatic foci in WT, but no metastasis was seen in Cav-1 KO cells injected lungs at different time points. Statistical analysis was performed using unpaired Student’s t-test *P < 0.05; ***P < 0.001.CC BY · PubMed Central
Fig. 3 RNA was isolated from each tumor group, and mRNA sequencing analysis was performed. A Heat map showing cluster analysis of differentially expressed genes in Cav-1 KO and WT 4T1 cell-induced tumors; B Volcano plot showing differential gene expression between Cav-1 KO and WT 4T1 cell-induced tumors at weeks 2 and 3. DEG were also plotted between WT with WT and KO with KO between week 2 and 3 (C). DEG (padj < 0.05) were categorized into biological processes (BP), cellular component (CC), and molecular function (MF). DESeq at threshold DESeq2, P-value ≤ 0.05.
Fig. 3 RNA was isolated from each tumor group, and mRNA sequencing analysis was performed. A Heat map showing cluster analysis of differentially expressed genes in Cav-1 KO and WT 4T1 cell-induced tumors; B Volcano plot showing differential gene expression between Cav-1 KO and WT 4T1 cell-induced tumors at weeks 2 and 3. DEG were also plotted between WT with WT and KO with KO between week 2 and 3 (C). DEG (padj < 0.05) were categorized into biological processes (BP), cellular component (CC), and molecular function (MF). DESeq at threshold DESeq2, P-value ≤ 0.05.CC BY · PubMed Central
Fig. 4 Knocking out Cav-1 affects gene expression involved in epithelial cell migration. A Heatmap demonstrating that knocking out Cav-1 expression significantly affected 53 genes at week 2 and 49 genes at week 3. B Heatmap showing DEG, which is known to be involved in epithelial cell migration and expressed at specific time points in either week 2 or week 3. DESeq at threshold DESeq2, P-value ≤ 0.05.
Fig. 4 Knocking out Cav-1 affects gene expression involved in epithelial cell migration. A Heatmap demonstrating that knocking out Cav-1 expression significantly affected 53 genes at week 2 and 49 genes at week 3. B Heatmap showing DEG, which is known to be involved in epithelial cell migration and expressed at specific time points in either week 2 or week 3. DESeq at threshold DESeq2, P-value ≤ 0.05.CC BY · PubMed Central
Fig. 5 The deletion of Cav-1 significantly altered the expression of epithelial cell migration genes at weeks 2 and 3. A Heatmap showing a set of epithelial migration genes that might play a regulatory role in Cav-1 KO-hampered lung metastasis at weeks 2 and 3. The Y-axis represents the metastatic genes, whereas the X-axis represents the different groups. B Graphical representation of epithelial migration genes at week 2 and C week 3. Y-axis represents FPKM value, and X-axis represents the gene name. DESeq at threshold DESeq2, P-value ≤ 0.05.
Fig. 5 The deletion of Cav-1 significantly altered the expression of epithelial cell migration genes at weeks 2 and 3. A Heatmap showing a set of epithelial migration genes that might play a regulatory role in Cav-1 KO-hampered lung metastasis at weeks 2 and 3. The Y-axis represents the metastatic genes, whereas the X-axis represents the different groups. B Graphical representation of epithelial migration genes at week 2 and C week 3. Y-axis represents FPKM value, and X-axis represents the gene name. DESeq at threshold DESeq2, P-value ≤ 0.05.CC BY · PubMed Central
Fig. 6 Data mining from the Human Breast Cancer Gene Expression Miner (Breast Cancer Gene-Expression Miner v4.8) database showed that Cav-1 expression was correlated with patient outcome and mortality in TNBC. A Correlation analysis between Cav-1 and 21 significantly differentially expressed genes in the human breast cancer patient database. B Significant correlation between Cav-1 and CDH13, KDR, MMRN2 (n = 317), and PECAM-1 (n = 254) expression in TNBC patients with breast cancer. C Immunoblot showing variable gene expression between Cav-1 KO and WT 4T1 injected tumors, which was more prominent at the end of week 3.
Fig. 6 Data mining from the Human Breast Cancer Gene Expression Miner (Breast Cancer Gene-Expression Miner v4.8) database showed that Cav-1 expression was correlated with patient outcome and mortality in TNBC. A Correlation analysis between Cav-1 and 21 significantly differentially expressed genes in the human breast cancer patient database. B Significant correlation between Cav-1 and CDH13, KDR, MMRN2 (n = 317), and PECAM-1 (n = 254) expression in TNBC patients with breast cancer. C Immunoblot showing variable gene expression between Cav-1 KO and WT 4T1 injected tumors, which was more prominent at the end of week 3.CC BY · PubMed Central
Fig. 7 Cav-1 promotes epithelial cell migration by interacting with ITGα3. A Interaction between Cav-1 and ITGα3, as predicted using the in silico protein interaction ZDOCK server (https://zdock.umassmed.edu/). B Coimmunoprecipitation of Cav-1 and ITGα3 confirmed their physical interactions. C Wound healing assay of Cav-1 and ITGα3 knock down 4T1 cells showed impaired epithelial cell migration after 24 and 48 h of scratch formation. Graph showing wound closure in the different groups at these time points. Statistical analysis was performed using unpaired Student’s t-test *P < 0.05; ***P < 0.001.
Fig. 7 Cav-1 promotes epithelial cell migration by interacting with ITGα3. A Interaction between Cav-1 and ITGα3, as predicted using the in silico protein interaction ZDOCK server (https://zdock.umassmed.edu/). B Coimmunoprecipitation of Cav-1 and ITGα3 confirmed their physical interactions. C Wound healing assay of Cav-1 and ITGα3 knock down 4T1 cells showed impaired epithelial cell migration after 24 and 48 h of scratch formation. Graph showing wound closure in the different groups at these time points. Statistical analysis was performed using unpaired Student’s t-test *P < 0.05; ***P < 0.001.CC BY · PubMed Central

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Research works printed but not linked: 62

  1. Siegel RL, Miller KD, Fuchs HE, Jemal A: Cancer statistics, 2022. CA Cancer J Clin 2022, 72(1):7–33. · DOI · Paper page
  2. Cava E, Marzullo P, Farinelli D, Gennari A, Saggia C, Riso S, Prodam F: Breast Cancer Diet "BCD": A Review of Healthy Dietary Patterns to Prevent Breast Cancer Recurrence and Reduce Mortality. Nutrients 2022, 14(3):476. · DOI
  3. Schick J, Ritchie RP, Restini C: Breast Cancer Therapeutics and Biomarkers: Past, Present, and Future Approaches. Breast Cancer (Auckl) 2021, 15:1178223421995854. · DOI
  4. Fares J, Fares MY, Khachfe HH, Salhab HA, Fares Y: Molecular principles of metastasis: a hallmark of cancer revisited. Signal Transduct Target Ther 2020, 5(1):28. · DOI
  5. Dillekas H, Rogers MS, Straume O: Are 90% of deaths from cancer caused by metastases? Cancer Med 2019, 8(12):5574–5576. · DOI
  6. Chen W, Hoffmann AD, Liu H, Liu X: Organotropism: new insights into molecular mechanisms of breast cancer metastasis. NPJ precision oncology 2018, 2(1):1–12. · DOI
  7. Huang QY, Liu GF, Qian XL, Tang LB, Huang QY, Xiong LX: Long Non-Coding RNA: Dual Effects on Breast Cancer Metastasis and Clinical Applications. Cancers (Basel) 2019, 11(11). · DOI
  8. Luo H, Tu G, Liu Z, Liu M: Cancer-associated fibroblasts: a multifaceted driver of breast cancer progression. Cancer Lett 2015, 361(2):155–163. · DOI
  9. Guo Y, Ji X, Liu J, Fan D, Zhou Q, Chen C, Wang W, Wang G, Wang H, Yuan W et al: Effects of exosomes on pre-metastatic niche formation in tumors. Mol Cancer 2019, 18(1):39. · DOI
  10. Eric D. Young LL, Fariba Behbod, Danny R. Welch: Fundamental Relationships Between Cancer Stem Cells, the Cancer Stem Cell Niche and Metastasis, vol. 3; 2016.
  11. Wani NA: Abstract 1166: CXCR7-mediated signaling axis regulates breast cancer growth and metastasis by modulating tumor microenvironment. Cancer Research 2014, 74(19_Supplement):1166–1166. · DOI
  12. Min W: Abstract 129: AIP1 suppresses tumor metastasis by regulating tumor microenvironment and metastatic niche. Cancer Research 2014, 74(19_Supplement):129–129. · DOI
  13. Brena D, Huang MB, Bond V: Extracellular vesicle-mediated transport: Reprogramming a tumor microenvironment conducive with breast cancer progression and metastasis. Transl Oncol 2022, 15(1):101286. · DOI
  14. Qian XL, Pan YH, Huang QY, Shi YB, Huang QY, Hu ZZ, Xiong LX: Caveolin-1: a multifaceted driver of breast cancer progression and its application in clinical treatment. Onco Targets Ther 2019, 12:1539–1552. · DOI
  15. Ketteler J, Klein D: Caveolin-1, cancer and therapy resistance. Int J Cancer 2018, 143(9):2092–2104. · DOI
  16. Diaz-Valdivia NI, Calderon CC, Diaz JE, Lobos-Gonzalez L, Sepulveda H, Ortiz RJ, Martinez S, Silva V, Maldonado HJ, Silva P et al: Anti-neoplastic drugs increase caveolin-1-dependent migration, invasion and metastasis of cancer cells. Oncotarget 2017, 8(67):111943–111965. · DOI
  17. Karam JA, Lotan Y, Roehrborn CG, Ashfaq R, Karakiewicz PI, Shariat SF: Caveolin-1 overexpression is associated with aggressive prostate cancer recurrence. The Prostate 2007, 67(6):614–622. · DOI
  18. Low JY, Laiho M: Caveolae-Associated Molecules, Tumor Stroma, and Cancer Drug Resistance: Current Findings and Future Perspectives. Cancers (Basel) 2022, 14(3):589. · DOI
  19. Martinez-Outschoorn UE, Pavlides S, Whitaker-Menezes D, Daumer KM, Milliman JN, Chiavarina B, Migneco G, Witkiewicz AK, Martinez-Cantarin MP, Flomenberg N et al: Tumor cells induce the cancer associated fibroblast phenotype via caveolin-1 degradation: implications for breast cancer and DCIS therapy with autophagy inhibitors. Cell Cycle 2010, 9(12):2423–2433. · DOI
  20. Du C, Chen L, Zhang H, Wang Z, Liu W, Xie X, Xie M: Caveolin-1 limits the contribution of BKCa channel to MCF-7 breast cancer cell proliferation and invasion. Int J Mol Sci 2014, 15(11):20706–20722. · DOI
  21. Godina C, Chandran VI, Barbachowska M, Tryggvadottir H, Nodin B, Visse E, Borgquist S, Jirström K, Isaksson K, Bosch A: Interplay between Caveolin-1 and body and tumor size affects clinical outcomes in breast cancer. Translational Oncology 2022, 22:101464. · DOI
  22. Sotgia F, Martinez-Outschoorn UE, Howell A, Pestell RG, Pavlides S, Lisanti MP: Caveolin-1 and cancer metabolism in the tumor microenvironment: markers, models, and mechanisms. Annu Rev Pathol 2012, 7:423–467. · DOI
  23. Shi Y-B, Li J, Lai X-N, Jiang R, Zhao R-C, Xiong L-X: Multifaceted Roles of Caveolin-1 in Lung Cancer: A New Investigation Focused on Tumor Occurrence, Development and Therapy. In: Cancers. vol. 12; 2020.
  24. Singh DD, Lee H-J, Yadav DK: Recent Clinical Advances on Long Non-Coding RNAs in Triple-Negative Breast Cancer. In: Cells. vol. 12; 2023. · DOI
  25. Wang Y, Li Y, Zhong J, Li M, Zhou Y, Lin Q, Zong S, Luo W, Wang J, Wang K et al: Tumor-derived Cav-1 promotes pre-metastatic niche formation and lung metastasis in breast cancer. Theranostics 2023, 13(5):1684–1697. · DOI
  26. Yang H, Guan L, Li S, Jiang Y, Xiong N, Li L, Wu C, Zeng H, Liu Y: Mechanosensitive caveolin-1 activation-induced PI3K/Akt/mTOR signaling pathway promotes breast cancer motility, invadopodia formation and metastasis in vivo. Oncotarget 2016, 7(13):16227–16247. · DOI
  27. Godina C, Tryggvadottir H, Bosch A, Borgquist S, Belting M, Isaksson K, Jernstrom H: Caveolin-1 genotypes as predictor for locoregional recurrence and contralateral disease in breast cancer. Breast Cancer Res Treat 2023, 199(2):335–347. · DOI
  28. Sloan EK, Stanley KL, Anderson RL: Caveolin-1 inhibits breast cancer growth and metastasis. Oncogene 2004, 23(47):7893–7897. · DOI
  29. Burrows AD, Restall C, Sloan EK, Anderson RL: Abstract 1486: The contribution of stromal caveolin-1 to breast cancer metastasis. Cancer Research 2012, 72(8_Supplement):1486–1486. · DOI
  30. Zhang Q, Zhang S, Chen J, Xie Z: The Interplay between Integrins and Immune Cells as a Regulator in Cancer Immunology. Int J Mol Sci 2023, 24(7). · DOI
  31. Au - Hu X, Au - Villodre ES, Au - Woodward WA, Au - Debeb BG: Modeling Brain Metastasis Via Tail-Vein Injection of Inflammatory Breast Cancer Cells. JoVE 2021(168):e62249.
  32. Au - Thies KA, Au - Steck S, Au - Knoblaugh SE, Au - Sizemore ST: Pathological Analysis of Lung Metastasis Following Lateral Tail-Vein Injection of Tumor Cells. JoVE 2020(159):e61270.
  33. Laskowski RA, Jablonska J, Pravda L, Varekova RS, Thornton JM: PDBsum: Structural summaries of PDB entries. Protein Sci 2018, 27(1):129–134. · DOI
  34. Rose PW, Prlic A, Altunkaya A, Bi C, Bradley AR, Christie CH, Costanzo LD, Duarte JM, Dutta S, Feng Z et al: The RCSB protein data bank: integrative view of protein, gene and 3D structural information. Nucleic Acids Res 2017, 45(D1):D271-D281.
  35. Pierce BG, Wiehe K, Hwang H, Kim BH, Vreven T, Weng Z: ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers. Bioinformatics 2014, 30(12):1771–1773. · DOI
  36. Singh DP, Begum R, Kaur G, Bagam P, Kambiranda D, Singh R, Batra S: E-cig vapor condensate alters proteome and lipid profiles of membrane rafts: impact on inflammatory responses in A549 cells. Cell Biol Toxicol 2021, 37(5):773–793. · DOI
  37. Wu PH, Gilkes DM, Phillip JM, Narkar A, Cheng TW, Marchand J, Lee MH, Li R, Wirtz D: Single-cell morphology encodes metastatic potential. Sci Adv 2020, 6(4):eaaw6938. · DOI · Paper page
  38. Kleiner DE, Stetler-Stevenson WG: Matrix metalloproteinases and metastasis. Cancer Chemother Pharmacol 1999, 43 Suppl(1):S42-51.
  39. Lechuga S, Amin PH, Wolen AR, Ivanov AI: Adducins inhibit lung cancer cell migration through mechanisms involving regulation of cell-matrix adhesion and cadherin-11 expression. Biochimica et Biophysica Acta (BBA)-Molecular Cell Research 2019, 1866(3):395–408. · DOI
  40. Yu G, Wang L-G, Han Y, He Q-Y: clusterProfiler: an R package for comparing biological themes among gene clusters. Omics: a journal of integrative biology 2012, 16(5):284–287. · DOI · Paper page
  41. Pijuan J, Barcelo C, Moreno DF, Maiques O, Siso P, Marti RM, Macia A, Panosa A: In vitro Cell Migration, Invasion, and Adhesion Assays: From Cell Imaging to Data Analysis. Front Cell Dev Biol 2019, 7:107. · DOI
  42. Lee H, Carnino JM, Jin Y: Caveolin-1 regulates extracellular vesicle-miRNA packaging. Aging (Albany NY) 2019, 11(20):8733–8735. · DOI
  43. Rothberg KG, Heuser JE, Donzell WC, Ying YS, Glenney JR, Anderson RG: Caveolin, a protein component of caveolae membrane coats. Cell 1992, 68(4):673–682. · DOI
  44. Kogure A, Yoshioka Y, Ochiya T: Extracellular vesicles in cancer metastasis: Potential as therapeutic targets and materials. International Journal of Molecular Sciences 2020, 21(12):4463. · DOI
  45. Yamaguchi H, Takeo Y, Yoshida S, Kouchi Z, Nakamura Y, Fukami K: Lipid rafts and caveolin-1 are required for invadopodia formation and extracellular matrix degradation by human breast cancer cells. Cancer Res 2009, 69(22):8594–8602. · DOI
  46. Gupta VK, Sharma NS, Kesh K, Dauer P, Nomura A, Giri B, Dudeja V, Banerjee S, Bhattacharya S, Saluja A: Metastasis and chemoresistance in CD133 expressing pancreatic cancer cells are dependent on their lipid raft integrity. Cancer letters 2018, 439:101–112. · DOI
  47. Yu H, Shen H, Zhang Y, Zhong F, Liu Y, Qin L, Yang P: CAV1 promotes HCC cell progression and metastasis through Wnt/β-catenin pathway. PLoS One 2014, 9(9):e106451. · DOI
  48. Yokoi A, Yoshioka Y, Yamamoto Y, Ishikawa M, Ikeda S-i, Kato T, Kiyono T, Takeshita F, Kajiyama H, Kikkawa F et al: Malignant extracellular vesicles carrying MMP1 mRNA facilitate peritoneal dissemination in ovarian cancer. Nature Communications 2017, 8(1):14470. · DOI
  49. Su JL, Yang PC, Shih JY, Yang CY, Wei LH, Hsieh CY, Chou CH, Jeng YM, Wang MY, Chang KJ et al: The VEGF-C/Flt-4 axis promotes invasion and metastasis of cancer cells. Cancer Cell 2006, 9(3):209–223. · DOI
  50. Modi SJ, Kulkarni VM: Vascular endothelial growth factor receptor (VEGFR-2)/KDR inhibitors: medicinal chemistry perspective. Medicine in Drug Discovery 2019, 2:100009. · DOI
  51. Ye M, Huang T, Li J, Zhou C, Yang P, Ni C, Chen S: Role of CDH13 promoter methylation in the carcinogenesis, progression, and prognosis of colorectal cancer: A systematic meta-analysis under PRISMA guidelines. Medicine (Baltimore) 2017, 96(4):e5956. · DOI
  52. Andreeva AV, Kutuzov MA: Cadherin 13 in cancer. Genes Chromosomes Cancer 2010, 49(9):775–790. · DOI
  53. Lorenzon E, Colladel R, Andreuzzi E, Marastoni S, Todaro F, Schiappacassi M, Ligresti G, Colombatti A, Mongiat M: MULTIMERIN2 impairs tumor angiogenesis and growth by interfering with VEGF-A/VEGFR2 pathway. Oncogene 2012, 31(26):3136–3147. · DOI
  54. Kurozumi A, Goto Y, Matsushita R, Fukumoto I, Kato M, Nishikawa R, Sakamoto S, Enokida H, Nakagawa M, Ichikawa T: Tumor-suppressive micro RNA‐223 inhibits cancer cell migration and invasion by targeting ITGA 3/ITGB 1 signaling in prostate cancer. Cancer science 2016, 107(1):84–94. · DOI
  55. Idichi T, Seki N, Kurahara H, Fukuhisa H, Toda H, Shimonosono M, Yamada Y, Arai T, Kita Y, Kijima Y et al: Involvement of anti-tumor miR-124-3p and its targets in the pathogenesis of pancreatic ductal adenocarcinoma: direct regulation of ITGA3 and ITGB1 by miR-124-3p. Oncotarget 2018, 9(48):28849–28865. · DOI
  56. Koshizuka K, Hanazawa T, Kikkawa N, Arai T, Okato A, Kurozumi A, Kato M, Katada K, Okamoto Y, Seki N: Regulation of ITGA 3 by the anti-tumor miR‐199 family inhibits cancer cell migration and invasion in head and neck cancer. Cancer science 2017, 108(8):1681–1692. · DOI
  57. Munkácsy G, Santarpia L, Győrffy B: Therapeutic Potential of Tumor Metabolic Reprogramming in Triple-Negative Breast Cancer. In: International Journal of Molecular Sciences. vol. 24; 2023. · DOI
  58. Robb R, Kuo JC, Liu Y, Corrales-Guerrero S, Cui T, Hegazi A, Nagy G, Lee RJ, Williams TM: A novel protein-drug conjugate, SSH20, demonstrates significant efficacy in caveolin-1-expressing tumors. Mol Ther Oncolytics 2021, 22:555–564. · DOI
  59. Khongorzul P, Ling CJ, Khan FU, Ihsan AU, Zhang J: Antibody-Drug Conjugates: A Comprehensive Review. Mol Cancer Res 2020, 18(1):3–19. · DOI
  60. Pereira PMR, Mandleywala K, Monette S, Lumish M, Tully KM, Panikar SS, Cornejo M, Mauguen A, Ragupathi A, Keltee NC et al: Caveolin-1 temporal modulation enhances antibody drug efficacy in heterogeneous gastric cancer. Nat Commun 2022, 13(1):2526. · DOI
  61. Desgrosellier JS, Cheresh DA: Integrins in cancer: biological implications and therapeutic opportunities. Nat Rev Cancer 2010, 10(1):9–22. · DOI
  62. Hegazy M, Cohen-Barak E, Koetsier JL, Najor NA, Arvanitis C, Sprecher E, Green KJ, Godsel LM: Proximity Ligation Assay for Detecting Protein-Protein Interactions and Protein Modifications in Cells and Tissues in Situ. Curr Protoc Cell Biol 2020, 89(1):e115. · DOI

Metadata

Authors
Francis, J., Singh, D., Pathak, R., Pandit, A., Ebenezer, P., Kumar, S., Duplooy, A., White, M., Jambunathan, N., Chintalaramulu, N., & Dharmakumar, R.
Affiliations
  • Louisiana State University (US)
  • Indiana University School of Medicine (US)
  • Midwestern University (US)
Corresponding author
Francis, Joseph
Venue
Cancer Gene Therapy
Published
2023-12-12
Volume
31
Issue
11
Pages
1658-1668
ISSN
0929-1903 (ISSN-L)
OpenAlex
W4402331411
Cited by
12
References
1
Citations by year
2026: 5 · 2025: 5 · 2024: 2
FWCI
2.68
Type
journal article
Language
en
Open access
Locations
  • Cancer Gene Therapy (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • IUScholarWorks (Indiana University) (submittedVersion, cc-by)
Funders
National Institute of General Medical Sciences (P20GM135000)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Caveolin-1 and cellular processes
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Mechanisms of cancer metastasis
  • Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
Keywords
caveolin-1, breast cancer lung metastasis, integrin alpha3, 4T1 cells, extracellular vesicles, cell migration, matrix metalloproteinases, lipid rafts
MeSH terms
Animals, Breast Neoplasms, Cell Movement, Disease Models, Animal, Female, Humans, Lung Neoplasms, Mice, Inbred BALB C, Gene Expression Regulation, Neoplastic, Mice, Knockout, Integrin alpha3, Cell Line, Tumor, Caveolin 1, Mice, Gene Knockout Techniques

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