Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and mul...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Yuhao Xu [verfasserIn] Yaoqiang Du [verfasserIn] Qinghui Zheng [verfasserIn] Tao Zhou [verfasserIn] Buyun Ye [verfasserIn] Yihao Wu [verfasserIn] Qiuran Xu [verfasserIn] Xuli Meng [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	breast cancer ferroptosis relapse-free survival neoadjuvant chemotherapy immune microenvironment

Übergeordnetes Werk:	In: Frontiers in Immunology - Frontiers Media S.A., 2011, 13(2022)
Übergeordnetes Werk:	volume:13 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fimmu.2022.895110

Katalog-ID:	DOAJ032247516

Internformat


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520			\|a PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future.
650		4	\|a breast cancer
650		4	\|a ferroptosis
650		4	\|a relapse-free survival
650		4	\|a neoadjuvant chemotherapy
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allfields	10.3389/fimmu.2022.895110 doi (DE-627)DOAJ032247516 (DE-599)DOAJb5dbf395bdac40c8beb3e231dec74861 DE-627 ger DE-627 rakwb eng RC581-607 Yuhao Xu verfasserin aut Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future. breast cancer ferroptosis relapse-free survival neoadjuvant chemotherapy immune microenvironment Immunologic diseases. Allergy Yuhao Xu verfasserin aut Yaoqiang Du verfasserin aut Qinghui Zheng verfasserin aut Tao Zhou verfasserin aut Buyun Ye verfasserin aut Yihao Wu verfasserin aut Qiuran Xu verfasserin aut Xuli Meng verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 13(2022) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:13 year:2022 https://doi.org/10.3389/fimmu.2022.895110 kostenfrei https://doaj.org/article/b5dbf395bdac40c8beb3e231dec74861 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2022.895110/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
spelling	10.3389/fimmu.2022.895110 doi (DE-627)DOAJ032247516 (DE-599)DOAJb5dbf395bdac40c8beb3e231dec74861 DE-627 ger DE-627 rakwb eng RC581-607 Yuhao Xu verfasserin aut Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future. breast cancer ferroptosis relapse-free survival neoadjuvant chemotherapy immune microenvironment Immunologic diseases. Allergy Yuhao Xu verfasserin aut Yaoqiang Du verfasserin aut Qinghui Zheng verfasserin aut Tao Zhou verfasserin aut Buyun Ye verfasserin aut Yihao Wu verfasserin aut Qiuran Xu verfasserin aut Xuli Meng verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 13(2022) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:13 year:2022 https://doi.org/10.3389/fimmu.2022.895110 kostenfrei https://doaj.org/article/b5dbf395bdac40c8beb3e231dec74861 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2022.895110/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
allfields_unstemmed	10.3389/fimmu.2022.895110 doi (DE-627)DOAJ032247516 (DE-599)DOAJb5dbf395bdac40c8beb3e231dec74861 DE-627 ger DE-627 rakwb eng RC581-607 Yuhao Xu verfasserin aut Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future. breast cancer ferroptosis relapse-free survival neoadjuvant chemotherapy immune microenvironment Immunologic diseases. Allergy Yuhao Xu verfasserin aut Yaoqiang Du verfasserin aut Qinghui Zheng verfasserin aut Tao Zhou verfasserin aut Buyun Ye verfasserin aut Yihao Wu verfasserin aut Qiuran Xu verfasserin aut Xuli Meng verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 13(2022) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:13 year:2022 https://doi.org/10.3389/fimmu.2022.895110 kostenfrei https://doaj.org/article/b5dbf395bdac40c8beb3e231dec74861 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2022.895110/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
allfieldsGer	10.3389/fimmu.2022.895110 doi (DE-627)DOAJ032247516 (DE-599)DOAJb5dbf395bdac40c8beb3e231dec74861 DE-627 ger DE-627 rakwb eng RC581-607 Yuhao Xu verfasserin aut Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future. breast cancer ferroptosis relapse-free survival neoadjuvant chemotherapy immune microenvironment Immunologic diseases. Allergy Yuhao Xu verfasserin aut Yaoqiang Du verfasserin aut Qinghui Zheng verfasserin aut Tao Zhou verfasserin aut Buyun Ye verfasserin aut Yihao Wu verfasserin aut Qiuran Xu verfasserin aut Xuli Meng verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 13(2022) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:13 year:2022 https://doi.org/10.3389/fimmu.2022.895110 kostenfrei https://doaj.org/article/b5dbf395bdac40c8beb3e231dec74861 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2022.895110/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
allfieldsSound	10.3389/fimmu.2022.895110 doi (DE-627)DOAJ032247516 (DE-599)DOAJb5dbf395bdac40c8beb3e231dec74861 DE-627 ger DE-627 rakwb eng RC581-607 Yuhao Xu verfasserin aut Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future. breast cancer ferroptosis relapse-free survival neoadjuvant chemotherapy immune microenvironment Immunologic diseases. Allergy Yuhao Xu verfasserin aut Yaoqiang Du verfasserin aut Qinghui Zheng verfasserin aut Tao Zhou verfasserin aut Buyun Ye verfasserin aut Yihao Wu verfasserin aut Qiuran Xu verfasserin aut Xuli Meng verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 13(2022) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:13 year:2022 https://doi.org/10.3389/fimmu.2022.895110 kostenfrei https://doaj.org/article/b5dbf395bdac40c8beb3e231dec74861 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2022.895110/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
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Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. 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Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">breast cancer</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">ferroptosis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">relapse-free survival</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">neoadjuvant chemotherapy</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">immune microenvironment</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Immunologic diseases. 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callnumber-first	R - Medicine
author	Yuhao Xu
spellingShingle	Yuhao Xu misc RC581-607 misc breast cancer misc ferroptosis misc relapse-free survival misc neoadjuvant chemotherapy misc immune microenvironment misc Immunologic diseases. Allergy Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
authorStr	Yuhao Xu
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topic_title	RC581-607 Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy breast cancer ferroptosis relapse-free survival neoadjuvant chemotherapy immune microenvironment
topic	misc RC581-607 misc breast cancer misc ferroptosis misc relapse-free survival misc neoadjuvant chemotherapy misc immune microenvironment misc Immunologic diseases. Allergy
topic_unstemmed	misc RC581-607 misc breast cancer misc ferroptosis misc relapse-free survival misc neoadjuvant chemotherapy misc immune microenvironment misc Immunologic diseases. Allergy
topic_browse	misc RC581-607 misc breast cancer misc ferroptosis misc relapse-free survival misc neoadjuvant chemotherapy misc immune microenvironment misc Immunologic diseases. Allergy
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title	Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
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title_full	Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
author_sort	Yuhao Xu
journal	Frontiers in Immunology
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author_browse	Yuhao Xu Yaoqiang Du Qinghui Zheng Tao Zhou Buyun Ye Yihao Wu Qiuran Xu Xuli Meng
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author-letter	Yuhao Xu
doi_str_mv	10.3389/fimmu.2022.895110
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title_sort	identification of ferroptosis-related prognostic signature and subtypes related to the immune microenvironment for breast cancer patients receiving neoadjuvant chemotherapy
callnumber	RC581-607
title_auth	Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
abstract	PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future.
abstractGer	PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future.
abstract_unstemmed	PurposeTo identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.MethodsFerroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future.
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title_short	Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
url	https://doi.org/10.3389/fimmu.2022.895110 https://doaj.org/article/b5dbf395bdac40c8beb3e231dec74861 https://www.frontiersin.org/articles/10.3389/fimmu.2022.895110/full https://doaj.org/toc/1664-3224
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author2	Yuhao Xu Yaoqiang Du Qinghui Zheng Tao Zhou Buyun Ye Yihao Wu Qiuran Xu Xuli Meng
author2Str	Yuhao Xu Yaoqiang Du Qinghui Zheng Tao Zhou Buyun Ye Yihao Wu Qiuran Xu Xuli Meng
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up_date	2024-07-04T00:31:07.228Z
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Receiver operating characteristic curves, Kaplan–Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase–PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.ResultsInternal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.ConclusionsThe FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">breast cancer</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">ferroptosis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">relapse-free survival</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">neoadjuvant chemotherapy</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">immune microenvironment</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Immunologic diseases. 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Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

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