Prelude to malignancy: A gene expression signature in normal mammary gland from breast cancer patients suggests pre-tumorous alterations and is associated with adverse outcomes.
breast cancer
gene signature
mortality
unfavorable outcome
uninvolved margin
Journal
International journal of cancer
ISSN: 1097-0215
Titre abrégé: Int J Cancer
Pays: United States
ID NLM: 0042124
Informations de publication
Date de publication:
08 Jun 2024
08 Jun 2024
Historique:
revised:
15
04
2024
received:
19
10
2023
accepted:
22
04
2024
medline:
8
6
2024
pubmed:
8
6
2024
entrez:
8
6
2024
Statut:
aheadofprint
Résumé
Despite advances in early detection and treatment strategies, breast cancer recurrence and mortality remain a significant health issue. Recent insights suggest the prognostic potential of microscopically healthy mammary gland, in the vicinity of the breast lesion. Nonetheless, a comprehensive understanding of the gene expression profiles in these tissues and their relationship to patient outcomes remain missing. Furthermore, the increasing trend towards breast-conserving surgery may inadvertently lead to the retention of existing cancer-predisposing mutations within the normal mammary gland. This study assessed the transcriptomic profiles of 242 samples from 83 breast cancer patients with unfavorable outcomes, including paired uninvolved mammary gland samples collected at varying distances from primary lesions. As a reference, control samples from 53 mammoplasty individuals without cancer history were studied. A custom panel of 634 genes linked to breast cancer progression and metastasis was employed for expression profiling, followed by whole-transcriptome verification experiments and statistical analyses to discern molecular signatures and their clinical relevance. A distinct gene expression signature was identified in uninvolved mammary gland samples, featuring key cellular components encoding keratins, CDH1, CDH3, EPCAM cell adhesion proteins, matrix metallopeptidases, oncogenes, tumor suppressors, along with crucial genes (FOXA1, RAB25, NRG1, SPDEF, TRIM29, and GABRP) having dual roles in cancer. Enrichment analyses revealed disruptions in epithelial integrity, cell adhesion, and estrogen signaling. This signature, named KAOS for Keratin-Adhesion-Oncogenes-Suppressors, was significantly associated with reduced tumor size but increased mortality rates. Integrating molecular assessment of non-malignant mammary tissue into disease management could enhance survival prediction and facilitate personalized patient care.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Swedish Medical Research Council
ID : 2020-02010
Organisme : Cancerfonden
ID : 200889PjF
Organisme : Fundacja na rzecz Nauki Polskiej
ID : MAB/2018/6
Informations de copyright
© 2024 The Author(s). International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.
Références
Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209‐249. doi:10.3322/caac.21660
Wilkinson L, Gathani T. Understanding breast cancer as a global health concern. Br J Radiol. 2022;95(1130):20211033. doi:10.1259/bjr.20211033
Loibl S, Poortmans P, Morrow M, Denkert C, Curigliano G. Breast cancer. Lancet. 2021;397(10286):1750‐1769. doi:10.1016/S0140‐6736(20)32381‐3
Waks AG, Winer EP. Breast cancer treatment: a review. Jama. 2019;321(3):288‐300. doi:10.1001/jama.2018.19323
Early Breast Cancer Trialists' Collaborative Group (EBCTCG), Darby S, McGale P, et al. 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. 2011;378(9804):1707‐1716. doi:10.1016/S0140‐6736(11)61629‐2
Early Breast Cancer Trialists' Collaborative Group (Ebctcg). Comparisons between different polychemotherapy regimens for early breast cancer: meta‐analyses of long‐term outcome among 100 000 women in 123 randomised trials. Lancet. 2012;379(9814):432‐444. doi:10.1016/S0140‐6736(11)61625‐5
Danforth DN. Genomic changes in normal breast tissue in women at normal risk or at high risk for breast cancer. Breast Cancer Basic Clin Res. 2016;10:109‐146. doi:10.4137/BCBCR.S39384
Kostecka A, Nowikiewicz T, Olszewski P, et al. High prevalence of somatic PIK3CA and TP53 pathogenic variants in the normal mammary gland tissue of sporadic breast cancer patients revealed by duplex sequencing. npj Breast Cancer. 2022;8(1):1‐10. doi:10.1038/s41523‐022‐00443‐9
Ronowicz A, Janaszak‐Jasiecka A, Skokowski J, et al. Concurrent DNA copy‐number alterations and mutations in genes related to maintenance of genome stability in uninvolved mammary glandular tissue from breast cancer patients. Hum Mutat. 2015;36(11):1088‐1099. doi:10.1002/humu.22845
Forsberg LA, Rasi C, Pekar G, et al. Signatures of post‐zygotic structural genetic aberrations in the cells of histologically normal breast tissue that can predispose to sporadic breast cancer. Genome Res. 2015;25(10):1521‐1535. doi:10.1101/gr.187823.114
Huang X, Stern DF, Zhao H. Transcriptional profiles from paired normal samples offer complementary information on cancer patient survival – evidence from TCGA pan‐cancer data. Sci Rep. 2016;6(1):20567. doi:10.1038/srep20567
Gadaleta E, Fourgoux P, Pirró S, et al. Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer. npj Breast Cancer. 2020;6:38. doi:10.1038/s41523‐020‐00182‐9
Aran D, Camarda R, Odegaard J, et al. Comprehensive analysis of normal adjacent to tumor transcriptomes. Nat Commun. 2017;8(1):1077. doi:10.1038/s41467‐017‐01027‐z
Tripathi A, King C, De La Morenas A, et al. Gene expression abnormalities in histologically normal breast epithelium of breast cancer patients. Int J Cancer. 2007;122(7):1557‐1566. doi:10.1002/ijc.23267
Graham K, de LasMorenas A, Tripathi A, et al. Gene expression in histologically normal epithelium from breast cancer patients and from cancer‐free prophylactic mastectomy patients shares a similar profile. Br J Cancer. 2010;102(8):1284‐1293. doi:10.1038/sj.bjc.6605576
Filipowicz N, Drężek K, Horbacz M, et al. Comprehensive cancer‐oriented biobanking resource of human samples for studies of post‐zygotic genetic variation involved in cancer predisposition. PLoS One. 2022;17(4):e0266111. doi:10.1371/journal.pone.0266111
Parker JS, Mullins M, Cheang MCU, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27(8):1160‐1167. doi:10.1200/JCO.2008.18.1370
Paquet ER, Hallett MT. Absolute assignment of breast cancer intrinsic molecular subtype. J Natl Cancer Inst. 2015;107(1):357. doi:10.1093/jnci/dju357
Dobin A, Davis CA, Schlesinger F, et al. STAR: ultrafast universal RNA‐seq aligner. Bioinformatics. 2013;29(1):15‐21. doi:10.1093/bioinformatics/bts635
Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26(1):139‐140. doi:10.1093/bioinformatics/btp616
Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA‐seq data. Genome Biol. 2010;11(3):R25. doi:10.1186/gb‐2010‐11‐3‐r25
Lê S, Josse J, Husson F. FactoMineR: an R package for multivariate analysis. J Stat Softw. 2008;25(1):1‐18. doi:10.18637/jss.v025.i01
Gendoo DMA, Ratanasirigulchai N, Schröder MS, et al. Genefu: an R/Bioconductor package for computation of gene expression‐based signatures in breast cancer. Bioinformatics. 2016;32(7):1097‐1099. doi:10.1093/bioinformatics/btv693
Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284‐287. doi:10.1089/omi.2011.0118
Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD. The sva package for removing batch effects and other unwanted variation in high‐throughput experiments. Bioinformatics. 2012;28(6):882‐883. doi:10.1093/bioinformatics/bts034
Zhang Y, Parmigiani G, Johnson WE. ComBat‐seq: batch effect adjustment for RNA‐seq count data. NAR Genom Bioinform. 2020;2(3):lqaa078. doi:10.1093/nargab/lqaa078
Amin MB, Greene FL, Edge SB, et al. The eighth edition AJCC cancer staging manual: continuing to build a bridge from a population‐based to a more “personalized” approach to cancer staging. CA Cancer J Clin. 2017;67(2):93‐99. doi:10.3322/caac.21388
Giuliano AE, Connolly JL, Edge SB, et al. Breast cancer‐major changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J Clin. 2017;67(4):290‐303. doi:10.3322/caac.21393
Giuliano AE, Edge SB, Hortobagyi GN. Eighth edition of the AJCC cancer staging manual: breast cancer. Ann Surg Oncol. 2018;25(7):1783‐1785. doi:10.1245/s10434‐018‐6486‐6
Román‐Pérez E, Casbas‐Hernández P, Pirone JR, et al. Gene expression in extratumoral microenvironment predicts clinical outcome in breast cancer patients. Breast Cancer Res. 2012;14(2):R51. doi:10.1186/bcr3152
Klebe M, Fremd C, Kriegsmann M, et al. Frequent molecular subtype switching and gene expression alterations in lung and pleural metastasis from luminal A‐type breast cancer. JCO Precis Oncol. 2020;4:848‐859. doi:10.1200/PO.19.00337
Sizemore GM, Sizemore ST, Seachrist DD, Keri RA. GABA(A) receptor pi (GABRP) stimulates basal‐like breast cancer cell migration through activation of extracellular‐regulated kinase 1/2 (ERK1/2). J Biol Chem. 2014;289(35):24102‐24113. doi:10.1074/jbc.M114.593582
Mi L, Liang N, Sun H. A comprehensive analysis of KRT19 combined with immune infiltration to predict breast cancer prognosis. Genes. 2022;13(10):1838. doi:10.3390/genes13101838
Statz E, Jorns JM. Cytokeratin 7, GATA3, and SOX‐10 is a comprehensive panel in diagnosing triple negative breast cancer brain metastases. Int J Surg Pathol. 2021;29(5):470‐474. doi:10.1177/1066896921990717
Zhong P, Shu R, Wu H, Liu Z, Shen X, Hu Y. Low KRT15 expression is associated with poor prognosis in patients with breast invasive carcinoma. Exp Ther Med. 2021;21(4):305. doi:10.3892/etm.2021.9736
Leggett SE, Hruska AM, Guo M, Wong IY. The epithelial‐mesenchymal transition and the cytoskeleton in bioengineered systems. Cell Commun Signal. 2021;19(1):32. doi:10.1186/s12964‐021‐00713‐2
Nieto MA, Huang RYJ, Jackson RA, Thiery JP. EMT: 2016. Cell. 2016;166(1):21‐45. doi:10.1016/j.cell.2016.06.028
Yamashita N, Tokunaga E, Iimori M, et al. Epithelial paradox: clinical significance of coexpression of E‐cadherin and vimentin with regard to invasion and metastasis of breast cancer. Clin Breast Cancer. 2018;18(5):e1003‐e1009. doi:10.1016/j.clbc.2018.02.002
Cheng JM, Volk L, Janaki DKM, Vyakaranam S, Ran S, Rao KA. Tumor suppressor function of Rab25 in triple‐negative breast cancer. Int J Cancer. 2010;126(12):2799‐2812. doi:10.1002/ijc.24900
Chua YL, Ito Y, Pole JCM, et al. The NRG1 gene is frequently silenced by methylation in breast cancers and is a strong candidate for the 8p tumour suppressor gene. Oncogene. 2009;28(46):4041‐4052. doi:10.1038/onc.2009.259
Ye T, Li J, Feng J, et al. The subtype‐specific molecular function of SPDEF in breast cancer and insights into prognostic significance. J Cell Mol Med. 2021;25(15):7307‐7320. doi:10.1111/jcmm.16760
Liu J, Welm B, Boucher KM, Ebbert MTW, Bernard PS. TRIM29 functions as a tumor suppressor in nontumorigenic breast cells and invasive ER+ breast cancer. Am J Pathol. 2012;180(2):839‐847. doi:10.1016/j.ajpath.2011.10.020
Yanagi T, Watanabe M, Hata H, et al. Loss of TRIM29 alters keratin distribution to promote cell invasion in squamous cell carcinoma. Cancer Res. 2018;78(24):6795‐6806. doi:10.1158/0008‐5472.CAN‐18‐1495
Seachrist DD, Anstine LJ, Keri RA. FOXA1: a pioneer of nuclear receptor action in breast cancer. Cancer. 2021;13(20):5205. doi:10.3390/cancers13205205
Onodera Y, Takagi K, Neoi Y, et al. Forkhead box I1 in breast carcinoma as a potent prognostic factor. Acta Histochem Cytochem. 2021;54(4):123‐130. doi:10.1267/ahc.21‐00034
Carracedo A, Cantley LC, Pandolfi PP. Cancer metabolism: fatty acid oxidation in the limelight. Nat Rev Cancer. 2013;13(4):227‐232. doi:10.1038/nrc3483
Kersten S, Desvergne B, Wahli W. Roles of PPARs in health and disease. Nature. 2000;405(6785):421‐424. doi:10.1038/35013000
Bonofiglio D, Gabriele S, Aquila S, et al. Estrogen receptor alpha binds to peroxisome proliferator‐activated receptor response element and negatively interferes with peroxisome proliferator‐activated receptor gamma signaling in breast cancer cells. Clin Cancer Res. 2005;11(17):6139‐6147. doi:10.1158/1078‐0432.CCR‐04‐2453
Connor AE, Schmaltz CL, Jackson‐Thompson J, Visvanathan K. Comorbidities and the risk of cardiovascular disease mortality among racially diverse patients with breast cancer. Cancer. 2021;127(15):2614‐2622. doi:10.1002/cncr.33530
Rahrmann EP, Shorthouse D, Jassim A, et al. The NALCN channel regulates metastasis and nonmalignant cell dissemination. Nat Genet. 2022;54(12):1827‐1838. doi:10.1038/s41588‐022‐01182‐0
Lochhead P, Chan AT, Nishihara R, et al. Etiologic field effect: reappraisal of the field effect concept in cancer predisposition and progression. Mod Pathol. 2015;28(1):14‐29. doi:10.1038/modpathol.2014.81
Slaughter DP, Southwick HW, Smejkal W. Field cancerization in oral stratified squamous epithelium; clinical implications of multicentric origin. Cancer. 1953;6(5):963‐968. doi:10.1002/1097‐0142(195309)6:5<963::aid‐cncr2820060515>3.0.co;2‐q
Finak G, Sadekova S, Pepin F, et al. Gene expression signatures of morphologically normal breast tissue identify basal‐like tumors. Breast Cancer Res. 2006;8(5):R58. doi:10.1186/bcr1608