Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity

Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The for...
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Autor*in:	Zhang, Yuting [verfasserIn] Ye, Yinghui Xu, Anping Luo, Yulou Sun, Yutian Zhang, Wei Ji, Ling

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Breast cancer Disulfidptosis Cysteine metabolism Prognosis Immune infiltration Single-cell analysis

Anmerkung:	© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: Journal of cancer research and clinical oncology - Berlin : Springer, 1904, 149(2023), 13 vom: 08. Juli, Seite 11979-11994
Übergeordnetes Werk:	volume:149 ; year:2023 ; number:13 ; day:08 ; month:07 ; pages:11979-11994

Links:	Volltext

DOI / URN:	10.1007/s00432-023-05028-y

Katalog-ID:	SPR052906361

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520			\|a Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA). Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment. Conclusion Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA.
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700	1		\|a Ji, Ling \|4 aut
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allfields	10.1007/s00432-023-05028-y doi (DE-627)SPR052906361 (SPR)s00432-023-05028-y-e DE-627 ger DE-627 rakwb eng Zhang, Yuting verfasserin aut Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA). Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment. Conclusion Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA. Breast cancer (dpeaa)DE-He213 Disulfidptosis (dpeaa)DE-He213 Cysteine metabolism (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Immune infiltration (dpeaa)DE-He213 Single-cell analysis (dpeaa)DE-He213 Ye, Yinghui aut Xu, Anping aut Luo, Yulou aut Sun, Yutian aut Zhang, Wei aut Ji, Ling aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 149(2023), 13 vom: 08. Juli, Seite 11979-11994 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:149 year:2023 number:13 day:08 month:07 pages:11979-11994 https://dx.doi.org/10.1007/s00432-023-05028-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 149 2023 13 08 07 11979-11994
spelling	10.1007/s00432-023-05028-y doi (DE-627)SPR052906361 (SPR)s00432-023-05028-y-e DE-627 ger DE-627 rakwb eng Zhang, Yuting verfasserin aut Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA). Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment. Conclusion Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA. Breast cancer (dpeaa)DE-He213 Disulfidptosis (dpeaa)DE-He213 Cysteine metabolism (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Immune infiltration (dpeaa)DE-He213 Single-cell analysis (dpeaa)DE-He213 Ye, Yinghui aut Xu, Anping aut Luo, Yulou aut Sun, Yutian aut Zhang, Wei aut Ji, Ling aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 149(2023), 13 vom: 08. Juli, Seite 11979-11994 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:149 year:2023 number:13 day:08 month:07 pages:11979-11994 https://dx.doi.org/10.1007/s00432-023-05028-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 149 2023 13 08 07 11979-11994
allfields_unstemmed	10.1007/s00432-023-05028-y doi (DE-627)SPR052906361 (SPR)s00432-023-05028-y-e DE-627 ger DE-627 rakwb eng Zhang, Yuting verfasserin aut Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA). Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment. Conclusion Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA. Breast cancer (dpeaa)DE-He213 Disulfidptosis (dpeaa)DE-He213 Cysteine metabolism (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Immune infiltration (dpeaa)DE-He213 Single-cell analysis (dpeaa)DE-He213 Ye, Yinghui aut Xu, Anping aut Luo, Yulou aut Sun, Yutian aut Zhang, Wei aut Ji, Ling aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 149(2023), 13 vom: 08. Juli, Seite 11979-11994 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:149 year:2023 number:13 day:08 month:07 pages:11979-11994 https://dx.doi.org/10.1007/s00432-023-05028-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 149 2023 13 08 07 11979-11994
allfieldsGer	10.1007/s00432-023-05028-y doi (DE-627)SPR052906361 (SPR)s00432-023-05028-y-e DE-627 ger DE-627 rakwb eng Zhang, Yuting verfasserin aut Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA). Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment. Conclusion Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA. Breast cancer (dpeaa)DE-He213 Disulfidptosis (dpeaa)DE-He213 Cysteine metabolism (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Immune infiltration (dpeaa)DE-He213 Single-cell analysis (dpeaa)DE-He213 Ye, Yinghui aut Xu, Anping aut Luo, Yulou aut Sun, Yutian aut Zhang, Wei aut Ji, Ling aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 149(2023), 13 vom: 08. Juli, Seite 11979-11994 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:149 year:2023 number:13 day:08 month:07 pages:11979-11994 https://dx.doi.org/10.1007/s00432-023-05028-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 149 2023 13 08 07 11979-11994
allfieldsSound	10.1007/s00432-023-05028-y doi (DE-627)SPR052906361 (SPR)s00432-023-05028-y-e DE-627 ger DE-627 rakwb eng Zhang, Yuting verfasserin aut Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA). Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment. Conclusion Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA. Breast cancer (dpeaa)DE-He213 Disulfidptosis (dpeaa)DE-He213 Cysteine metabolism (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Immune infiltration (dpeaa)DE-He213 Single-cell analysis (dpeaa)DE-He213 Ye, Yinghui aut Xu, Anping aut Luo, Yulou aut Sun, Yutian aut Zhang, Wei aut Ji, Ling aut Enthalten in Journal of cancer research and clinical oncology Berlin : Springer, 1904 149(2023), 13 vom: 08. Juli, Seite 11979-11994 (DE-627)253769515 (DE-600)1459285-X 1432-1335 nnns volume:149 year:2023 number:13 day:08 month:07 pages:11979-11994 https://dx.doi.org/10.1007/s00432-023-05028-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 149 2023 13 08 07 11979-11994
language	English
source	Enthalten in Journal of cancer research and clinical oncology 149(2023), 13 vom: 08. Juli, Seite 11979-11994 volume:149 year:2023 number:13 day:08 month:07 pages:11979-11994
sourceStr	Enthalten in Journal of cancer research and clinical oncology 149(2023), 13 vom: 08. Juli, Seite 11979-11994 volume:149 year:2023 number:13 day:08 month:07 pages:11979-11994
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Breast cancer Disulfidptosis Cysteine metabolism Prognosis Immune infiltration Single-cell analysis
isfreeaccess_bool	false
container_title	Journal of cancer research and clinical oncology
authorswithroles_txt_mv	Zhang, Yuting @@aut@@ Ye, Yinghui @@aut@@ Xu, Anping @@aut@@ Luo, Yulou @@aut@@ Sun, Yutian @@aut@@ Zhang, Wei @@aut@@ Ji, Ling @@aut@@
publishDateDaySort_date	2023-07-08T00:00:00Z
hierarchy_top_id	253769515
id	SPR052906361
language_de	englisch
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Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. 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author	Zhang, Yuting
spellingShingle	Zhang, Yuting misc Breast cancer misc Disulfidptosis misc Cysteine metabolism misc Prognosis misc Immune infiltration misc Single-cell analysis Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity
authorStr	Zhang, Yuting
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topic_title	Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity Breast cancer (dpeaa)DE-He213 Disulfidptosis (dpeaa)DE-He213 Cysteine metabolism (dpeaa)DE-He213 Prognosis (dpeaa)DE-He213 Immune infiltration (dpeaa)DE-He213 Single-cell analysis (dpeaa)DE-He213
topic	misc Breast cancer misc Disulfidptosis misc Cysteine metabolism misc Prognosis misc Immune infiltration misc Single-cell analysis
topic_unstemmed	misc Breast cancer misc Disulfidptosis misc Cysteine metabolism misc Prognosis misc Immune infiltration misc Single-cell analysis
topic_browse	misc Breast cancer misc Disulfidptosis misc Cysteine metabolism misc Prognosis misc Immune infiltration misc Single-cell analysis
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title	Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity
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title_full	Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity
author_sort	Zhang, Yuting
journal	Journal of cancer research and clinical oncology
journalStr	Journal of cancer research and clinical oncology
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author_browse	Zhang, Yuting Ye, Yinghui Xu, Anping Luo, Yulou Sun, Yutian Zhang, Wei Ji, Ling
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doi_str_mv	10.1007/s00432-023-05028-y
title_sort	prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity
title_auth	Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity
abstract	Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA). Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment. Conclusion Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstractGer	Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA). Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment. Conclusion Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstract_unstemmed	Purpose The rise of female breast cancer has created a significant global public health issue that requires effective solutions. Disulfidptosis, a recently identified form of cell death characterized by an excessive accumulation of disulfides, has unique initiatory and regulatory mechanisms. The formation of disulfide bonds is a metabolic event typically associated with cysteines. This study aims to explore the potential of the affinity between cysteine metabolism and disulfidptosis in risk stratification for breast invasive carcinoma (BRCA). Methods We used correlation analysis to decipher co-relation genes between cysteine metabolism and disulfidptosis (CMDCRGs). Both LASSO regression analysis and multivariate Cox regression analysis were employed to construct the prognostic signature. Additionally, we conducted investigations concerning subtype identification, functional enhancement, mutation landscape, immune infiltration, drug prioritization, and single-cell analysis. Results We developed and validated a six-gene prognostic signature as an independent prognostic predictor for BRCA. The prognostic nomogram, based on risk score, demonstrated a favorable capability in predicting survival outcomes. We identified distinct gene mutations, functional enhancements, and immune infiltration patterns between the two risk groups. Four clusters of drugs were predicted as potentially effective for patients in the low-risk group. We identified seven cell clusters within the tumor microenvironment of breast cancer, and RPL27A was found to be widely expressed in this environment. Conclusion Multidimensional analyses confirmed the clinical utility of the cysteine metabolism-disulfidptosis affinity-based signature in risk stratification and guiding personalized treatment for patients with BRCA. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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container_issue	13
title_short	Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity
url	https://dx.doi.org/10.1007/s00432-023-05028-y
remote_bool	true
author2	Ye, Yinghui Xu, Anping Luo, Yulou Sun, Yutian Zhang, Wei Ji, Ling
author2Str	Ye, Yinghui Xu, Anping Luo, Yulou Sun, Yutian Zhang, Wei Ji, Ling
ppnlink	253769515
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hochschulschrift_bool	false
doi_str	10.1007/s00432-023-05028-y
up_date	2024-07-03T15:39:29.272Z
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Prognosis stratification of patients with breast invasive carcinoma based on cysteine metabolism-disulfidptosis affinity

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