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pmid:34322380

Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer.

Yang Liu · Hefen Sun · Xuan Li · Qiqi Liu · Yuanyuan Zhao · Liangdong Li · Baojin Xu · Yifeng Hou · Wei Jin

Frontiers in oncology · 2021 doi:10.3389/fonc.2021.663556

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Data

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title
Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer.
doi
10.3389/fonc.2021.663556
pmid
34322380
authors array · 9 items
[0]
Yang Liu
[1]
Hefen Sun
[2]
Xuan Li
[3]
Qiqi Liu
[4]
Yuanyuan Zhao
[5]
Liangdong Li
[6]
Baojin Xu
[7]
Yifeng Hou
[8]
Wei Jin
journal
Frontiers in oncology
year
2021
abstract
BACKGROUND: To date, breast cancer remains the primary cause of tumor-related death among women, even though some leap-type developments of oncology have been done to slash the mortality. Considering the tumor heterogeneity and individual variation, the more reliable biomarkers are required to be identified for supporting the development of precision medicine in breast cancer. METHODS: Based on the TCGA-BRCA and METABRIC databases, the differently expressed RNA binding proteins (RBPs) between tumor and normal tissues were investigated. In this study, we focused on the communal differently expressed RBPs in four subtypes of breast cancer. Lasso-penalized Cox analysis, Stepwise-multivariate Cox analysis and Kaplan-Meier survival curve were performed to identify the hub RBP-coding genes in predicting prognosis of breast cancer, and a prognostic model was established. The efficiency of this model was further validated in other independent GSE20685, GSE4922 and FUSCC-TNBC cohorts by calculating the risk score and performing survival analysis, ROC and nomogram. Moreover, pathologic functions of the candidate RBPs in breast cancer were explored using some routine experiments in vitro, and the potential compounds targeting these RBPs were predicted by reviewing the Comparative Toxicogenomics Database. RESULTS: Here, we identified 62 RBPs which were differently expressed between the tumor and normal tissues. Thereinto, three RBPs (MRPL12, MRPL13 and POP1) acted as independent risk factors, and their expression pattern also correlated with poor prognosis of patients. A prognostic model, built with these 3-RBPs, possessed statistical significance to predict the survival probability of patients with breast cancer. Furthermore, experimental validations showed that down-regulating the expression of endogenous MRPL12, MRPL13 or POP1 could dramatically suppress the cellular viability and migration of breast cancer cells in vitro. Besides, some compounds (such as the Acetaminophen, Urethane and Tunicamycin) were predicted for curing breast cancer via targeting MRPL12, MRPL13 and POP1 simultaneously. CONCLUSION: This study identified and established a 3-RBPs-based signature and nomogram for predicting the survival probability of patients with breast cancer. MRPL12, MRPL13 and POP1 might act as oncogenes in maintaining cellular viability and accelerating metastasis of breast cancer cells, implying the possibility of which to be designed as biomarkers and/or therapeutic targets for breast cancer.
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Meanwhile, Kaplan–Meier curves and Cox regression analysis with log-rank p test were applied into survival analysis, in which p <0.05 was considered as statistically significant.
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
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[29]
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[30]
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[31]
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[32]
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[33]
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[34]
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[35]
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[36]
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[37]
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[38]
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[39]
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[40]
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[41]
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[42]
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[43]
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[44]
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[45]
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[46]
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[47]
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[48]
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[49]
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[50]
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[51]
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[52]
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[53]
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[54]
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[55]
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[56]
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[57]
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[58]
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[59]
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[60]
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[61]
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[62]
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[63]
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[64]
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[65]
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[66]
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[67]
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[68]
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[69]
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[70]
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[71]
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[72]
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[73]
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[74]
GSM519191
[75]
GSM519192
[76]
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[77]
GSM519194
[78]
GSM519195
[79]
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[80]
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[81]
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[82]
GSM519199
[83]
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[84]
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[85]
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[86]
GSM519203
[87]
GSM519204
[88]
GSM519205
[89]
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[90]
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[91]
GSM519208
[92]
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[93]
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[94]
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[95]
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[96]
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[97]
GSM519214
[98]
GSM519215
[99]
GSM519216
[100]
GSM519217
[101]
GSM519218
[102]
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[103]
GSM519220
[104]
GSM519221
[105]
GSM519222
[106]
GSM519223
[107]
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[108]
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[109]
GSM519226
[110]
GSM519227
[111]
GSM519228
[112]
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[113]
GSM519230
[114]
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[115]
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[116]
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[117]
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[118]
GSM519235
[119]
GSM519236
[120]
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[121]
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[122]
GSM519239
[123]
GSM519240
[124]
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[125]
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[126]
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[127]
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[128]
GSM519245
[129]
GSM519246
[130]
GSM519247
[131]
GSM519248
[132]
GSM519249
[133]
GSM519250
[134]
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[135]
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[136]
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[137]
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[138]
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[139]
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[140]
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[141]
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[142]
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[143]
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[144]
GSM519261
[145]
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[146]
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[147]
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[148]
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[149]
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[150]
GSM519267
[151]
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[152]
GSM519269
[153]
GSM519270
[154]
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[155]
GSM519272
[156]
GSM519273
[157]
GSM519274
[158]
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[159]
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[160]
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[161]
GSM519278
[162]
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[163]
GSM519280
[164]
GSM519281
[165]
GSM519282
[166]
GSM519283
[167]
GSM519284
[168]
GSM519285
[169]
GSM519286
[170]
GSM519287
[171]
GSM519288
[172]
GSM519289
[173]
GSM519290
[174]
GSM519291
[175]
GSM519292
[176]
GSM519293
[177]
GSM519294
[178]
GSM519295
[179]
GSM519296
[180]
GSM519297
[181]
GSM519298
[182]
GSM519299
[183]
GSM519300
[184]
GSM519301
[185]
GSM519302
[186]
GSM519303
[187]
GSM519304
[188]
GSM519305
[189]
GSM519306
[190]
GSM519307
[191]
GSM519308
[192]
GSM519309
[193]
GSM519310
[194]
GSM519311
[195]
GSM519312
[196]
GSM519313
[197]
GSM519314
[198]
GSM519315
[199]
GSM519316
[200]
GSM519317
[201]
GSM519318
[202]
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[203]
GSM519320
[204]
GSM519321
[205]
GSM519322
[206]
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[207]
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[208]
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[209]
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[210]
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[211]
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[212]
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[213]
GSM519330
[214]
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[215]
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[216]
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[217]
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[218]
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[219]
GSM519336
[220]
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[221]
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[222]
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[223]
GSM519340
[224]
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[225]
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[226]
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[227]
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[228]
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[229]
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[230]
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[231]
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[232]
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[233]
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[234]
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[235]
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[236]
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[237]
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[238]
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[239]
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[240]
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[241]
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[242]
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[243]
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[244]
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[245]
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[246]
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[247]
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[248]
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[249]
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[250]
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[251]
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[252]
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[253]
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[254]
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[255]
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[256]
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[257]
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[258]
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[259]
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[260]
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[262]
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[263]
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[264]
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[265]
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[266]
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[267]
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[268]
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[269]
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[270]
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[271]
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[272]
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[273]
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[274]
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[275]
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[277]
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[278]
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[279]
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[280]
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[281]
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[282]
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[283]
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[284]
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[285]
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[286]
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[287]
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[288]
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[289]
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[290]
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[291]
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[292]
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[293]
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[294]
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[295]
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[296]
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[297]
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[298]
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[299]
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[300]
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[301]
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[302]
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[308]
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GSM519426
[310]
GSM519427
[311]
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[312]
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[313]
GSM519430
[314]
GSM519431
[315]
GSM519432
[316]
GSM519433
[317]
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[318]
GSM519435
[319]
GSM519436
[320]
GSM519437
[321]
GSM519438
[322]
GSM519439
[323]
GSM519440
[324]
GSM519441
[325]
GSM519442
[326]
GSM519443
sample_count
327
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Microarray-based molecular subtyping of breast cancer
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[3] object · 15 fields
id
data:geo:GSE4922
role
raw
format
geo-series
media_type
application/vnd.ncbi.geo-series+json
uri
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4922
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE4922
version
null
note
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
access_statement_kind
data_availability_statement
sample_accessions array · 578 items
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GSM110625
[1]
GSM110626
[2]
GSM110627
[3]
GSM110628
[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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[11]
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[12]
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[13]
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[14]
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[15]
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[16]
GSM110641
[17]
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[18]
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[19]
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[20]
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[21]
GSM110646
[22]
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[23]
GSM110648
[24]
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[25]
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[26]
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[27]
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[28]
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[29]
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[30]
GSM110655
[31]
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[32]
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[33]
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[34]
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[35]
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[36]
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[37]
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[38]
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[39]
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[40]
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[41]
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[42]
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[44]
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[46]
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[47]
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[48]
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[51]
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[53]
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[55]
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[56]
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[58]
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[60]
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[62]
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[65]
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[66]
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[67]
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[69]
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[70]
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[71]
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[72]
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[74]
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[75]
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[76]
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[77]
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[78]
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[80]
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[81]
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[82]
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[83]
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[84]
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[85]
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[86]
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[87]
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[88]
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[95]
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[99]
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[102]
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[104]
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[105]
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[107]
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[110]
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[112]
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[113]
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[114]
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[115]
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[116]
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[117]
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[118]
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[119]
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[120]
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[121]
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[122]
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[123]
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[124]
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[125]
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[126]
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[127]
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[128]
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[129]
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[130]
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[131]
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[132]
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[133]
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[134]
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[135]
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[136]
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[137]
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[138]
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[139]
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[140]
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[141]
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[142]
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[143]
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[144]
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[145]
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[146]
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[147]
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[148]
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[149]
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[150]
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[151]
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[152]
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[153]
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[154]
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[155]
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[156]
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[157]
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[158]
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[159]
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[160]
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[161]
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[162]
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[163]
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[164]
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[165]
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[166]
GSM110791
[167]
GSM110792
[168]
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[169]
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[170]
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[171]
GSM110796
[172]
GSM110797
[173]
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[174]
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[175]
GSM110800
[176]
GSM110801
[177]
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[178]
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[179]
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[180]
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[181]
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[182]
GSM110807
[183]
GSM110808
[184]
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[185]
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[186]
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[187]
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[188]
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[189]
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[190]
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[191]
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[192]
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[193]
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[194]
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[195]
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[196]
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[197]
GSM110822
[198]
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[199]
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[200]
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[201]
GSM110826
[202]
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[203]
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[204]
GSM110829
[205]
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[206]
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[207]
GSM110832
[208]
GSM110833
[209]
GSM110834
[210]
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[211]
GSM110836
[212]
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[213]
GSM110838
[214]
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[215]
GSM110840
[216]
GSM110841
[217]
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[218]
GSM110843
[219]
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[220]
GSM110845
[221]
GSM110846
[222]
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[223]
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[224]
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[225]
GSM110850
[226]
GSM110851
[227]
GSM110852
[228]
GSM110853
[229]
GSM110854
[230]
GSM110855
[231]
GSM110856
[232]
GSM110857
[233]
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[234]
GSM110859
[235]
GSM110860
[236]
GSM110861
[237]
GSM110862
[238]
GSM110863
[239]
GSM110864
[240]
GSM110865
[241]
GSM110866
[242]
GSM110867
[243]
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[244]
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[245]
GSM110870
[246]
GSM110871
[247]
GSM110872
[248]
GSM110873
[249]
GSM110874
[250]
GSM110875
[251]
GSM110876
[252]
GSM110877
[253]
GSM110878
[254]
GSM110879
[255]
GSM110880
[256]
GSM110881
[257]
GSM110882
[258]
GSM110883
[259]
GSM110884
[260]
GSM110885
[261]
GSM110886
[262]
GSM110887
[263]
GSM110888
[264]
GSM110889
[265]
GSM110890
[266]
GSM110891
[267]
GSM110892
[268]
GSM110893
[269]
GSM110894
[270]
GSM110895
[271]
GSM110896
[272]
GSM110897
[273]
GSM110898
[274]
GSM110899
[275]
GSM110900
[276]
GSM110901
[277]
GSM110902
[278]
GSM110903
[279]
GSM110904
[280]
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[281]
GSM110906
[282]
GSM110907
[283]
GSM110908
[284]
GSM110909
[285]
GSM110910
[286]
GSM110911
[287]
GSM110912
[288]
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[289]
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[290]
GSM110915
[291]
GSM110916
[292]
GSM110917
[293]
GSM110918
[294]
GSM110919
[295]
GSM110920
[296]
GSM110921
[297]
GSM110922
[298]
GSM110923
[299]
GSM110924
[300]
GSM110925
[301]
GSM110926
[302]
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[303]
GSM110928
[304]
GSM110929
[305]
GSM110930
[306]
GSM110931
[307]
GSM110932
[308]
GSM110933
[309]
GSM110934
[310]
GSM110935
[311]
GSM110936
[312]
GSM110937
[313]
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[314]
GSM110939
[315]
GSM110940
[316]
GSM110941
[317]
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[318]
GSM110943
[319]
GSM110944
[320]
GSM110945
[321]
GSM110946
[322]
GSM110947
[323]
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[324]
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[325]
GSM110950
[326]
GSM110951
[327]
GSM110952
[328]
GSM110953
[329]
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[330]
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[331]
GSM110956
[332]
GSM110957
[333]
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[334]
GSM110959
[335]
GSM110960
[336]
GSM110961
[337]
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[338]
GSM110963
[339]
GSM110964
[340]
GSM110965
[341]
GSM110966
[342]
GSM110967
[343]
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[344]
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[345]
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[346]
GSM110971
[347]
GSM110972
[348]
GSM110973
[349]
GSM110974
[350]
GSM110975
[351]
GSM110976
[352]
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[353]
GSM110978
[354]
GSM110979
[355]
GSM110980
[356]
GSM110981
[357]
GSM110982
[358]
GSM110983
[359]
GSM110984
[360]
GSM110985
[361]
GSM110986
[362]
GSM110987
[363]
GSM110988
[364]
GSM110989
[365]
GSM110990
[366]
GSM110991
[367]
GSM110992
[368]
GSM110993
[369]
GSM110994
[370]
GSM110995
[371]
GSM110996
[372]
GSM110997
[373]
GSM110998
[374]
GSM110999
[375]
GSM111000
[376]
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[377]
GSM111002
[378]
GSM111003
[379]
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[380]
GSM111005
[381]
GSM111006
[382]
GSM111007
[383]
GSM111008
[384]
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[385]
GSM111010
[386]
GSM111011
[387]
GSM111012
[388]
GSM111013
[389]
GSM111014
[390]
GSM111015
[391]
GSM111016
[392]
GSM111017
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sample_count
578
group_sizes
null
group_sizes_basis
null
platform
96;97
taxon
Homo sapiens
title
Genetic Reclassification of Histologic Grade Delineates New Clinical Subtypes of Breast Cancer
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
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licence_read
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[3]
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[4]
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[5]
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quote
Meanwhile, Kaplan–Meier curves and Cox regression analysis with log-rank p test were applied into survival analysis, in which p <0.05 was considered as statistically significant.
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method-2
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survival_analysis
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time_to_event_with_censoring
evidence object · 3 fields
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Kaplan-Meier
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method-3
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survival_analysis
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evidence object · 3 fields
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id
method-4
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network_analysis
specific
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Network / pathway analysis
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pathway_enrich
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state
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[0] object · 6 fields
capability_id
capability:computational_analysis
label
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assay_families array · 9 items
[0]
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Automated Assays Laravel application and simulated adapters
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nothing:replicable_now
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tier
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cox_ph
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basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 3 items
[0]
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GSE4922
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GSE118527
resolved_accessions array · 3 items
[0]
GSE20685
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GSE118527
statements array · 1 item
[0]
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
basis
The paper names GSE20685, GSE4922, GSE118527 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
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[0]
cox_ph
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[0]
source:pmid:34322380
[1]
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[0]
run_analysis
must_build object · 5 fields
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[0]
data:geo:GSE118527
gaps array · 0 items
review object · 5 fields
state
partial
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kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:33:07Z
independence
single_reader
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method
verbatim
availability
verbatim
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3
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784
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extraction
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complete
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minimax
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execution.not_run
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pmid:34322380
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paper
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pmid:34322380
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id
source:pmid:34322380
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manuscript
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PMID 34322380 full text
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id
data:geo:GSE118527
type
dataset
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GEO GSE118527
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id
activity-reading-sci-2026-11-01
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classification
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paper
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pmid:34322380
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source:pmid:34322380
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PMID 34322380 full text
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data:geo:GSE118527
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dataset
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GEO GSE118527
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agent:corpus-assay-engine
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activity-read-34322380
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extraction
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agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE118527
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accession_resolution
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data:geo:GSE118527
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agent:corpus-assay-engine
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agent:corpus-assay-engine
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Corpus assay engine
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agent:minimax-reader
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[4]
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[5]
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[6]
execution.not_run
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review.human_critique
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Meanwhile, Kaplan–Meier curves and Cox regression analysis with log-rank p test were applied into survival analysis, in which p <0.05 was considered as statistically significant.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34322380", "kind": "science-record", "revision": 8, "content_hash": "sha256:5b7cc39a1015186b1b5f95fc264c2b42c2dd853ce44cf944131a0fca74045338", "created_at": "2026-11-01T15:41:45Z", "updated_at": "2026-11-01T22:47:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer.", "doi": "10.3389/fonc.2021.663556", "pmid": "34322380", "authors": ["Yang Liu", "Hefen Sun", "Xuan Li", "Qiqi Liu", "Yuanyuan Zhao", "Liangdong Li", "Baojin Xu", "Yifeng Hou", "Wei Jin"], "journal": "Frontiers in oncology", "year": 2021, "abstract": "BACKGROUND: To date, breast cancer remains the primary cause of tumor-related death among women, even though some leap-type developments of oncology have been done to slash the mortality. Considering the tumor heterogeneity and individual variation, the more reliable biomarkers are required to be identified for supporting the development of precision medicine in breast cancer.\nMETHODS: Based on the TCGA-BRCA and METABRIC databases, the differently expressed RNA binding proteins (RBPs) between tumor and normal tissues were investigated. In this study, we focused on the communal differently expressed RBPs in four subtypes of breast cancer. Lasso-penalized Cox analysis, Stepwise-multivariate Cox analysis and Kaplan-Meier survival curve were performed to identify the hub RBP-coding genes in predicting prognosis of breast cancer, and a prognostic model was established. The efficiency of this model was further validated in other independent GSE20685, GSE4922 and FUSCC-TNBC cohorts by calculating the risk score and performing survival analysis, ROC and nomogram. Moreover, pathologic functions of the candidate RBPs in breast cancer were explored using some routine experiments in vitro, and the potential compounds targeting these RBPs were predicted by reviewing the Comparative Toxicogenomics Database.\nRESULTS: Here, we identified 62 RBPs which were differently expressed between the tumor and normal tissues. Thereinto, three RBPs (MRPL12, MRPL13 and POP1) acted as independent risk factors, and their expression pattern also correlated with poor prognosis of patients. A prognostic model, built with these 3-RBPs, possessed statistical significance to predict the survival probability of patients with breast cancer. Furthermore, experimental validations showed that down-regulating the expression of endogenous MRPL12, MRPL13 or POP1 could dramatically suppress the cellular viability and migration of breast cancer cells in vitro. Besides, some compounds (such as the Acetaminophen, Urethane and Tunicamycin) were predicted for curing breast cancer via targeting MRPL12, MRPL13 and POP1 simultaneously.\nCONCLUSION: This study identified and established a 3-RBPs-based signature and nomogram for predicting the survival probability of patients with breast cancer. MRPL12, MRPL13 and POP1 might act as oncogenes in maintaining cellular viability and accelerating metastasis of breast cancer cells, implying the possibility of which to be designed as biomarkers and/or therapeutic targets for breast cancer.", "claims": [{"id": "claim-method", "statement": "Meanwhile, Kaplan–Meier curves and Cox regression analysis with log-rank p test were applied into survival analysis, in which p <0.05 was considered as statistically significant.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34322380", "locator": "sections[14] \"Statistical Analysis\" paragraph 2", "quote": "Meanwhile, Kaplan–Meier curves and Cox regression analysis with log-rank p test were applied into survival analysis, in which p <0.05 was considered as statistically significant."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34322380", "locator": "sections[24] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34322380"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE118527"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE118527"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34322380", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2021.663556", "sha256": "sha256:52d558b1afa1f4c968347ec0f80e3726914ffc53445bac07a0fda3a7035e966a", "bytes": 51259, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2021.663556", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8311660", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE118527", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE118527", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE118527", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/ Supplementary Material . 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