Purine salvage–associated metabolites as biomarkers for early diagnosis of esophageal squamous cell carcinoma: a diagnostic model–based study Article Swipe
Yawen Sun
,
Wenjuan Liu
,
Mu Su
,
Tao Zhang
,
Xia Li
,
Wenbin Liu
,
Yuping Cai
,
Deli Zhao
,
Ming Yang
,
Zheng‐Jiang Zhu
,
Jialin Wang
,
Jinming Yu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1038/s41420-024-01896-6
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1038/s41420-024-01896-6
Esophageal squamous cell carcinoma (ESCC) remains an important health concern in developing countries. Patients with advanced ESCC have a poor prognosis and survival rate, and achieving early diagnosis remains a challenge. Metabolic biomarkers are gradually gaining attention as early diagnostic biomarkers. Hence, this multicenter study comprehensively evaluated metabolism dysregulation in ESCC through an integrated research strategy to identify key metabolite biomarkers of ESCC. First, the metabolic profiles were examined in tissue and serum samples from the discovery cohort ( n = 162; ESCC patients, n = 81; healthy volunteers, n = 81), and ESCC tissue-induced metabolite alterations were observed in the serum. Afterward, RNA sequencing of tissue samples ( n = 46) was performed, followed by an integrated analysis of metabolomics and transcriptomics. The potential biomarkers for ESCC were further identified by censoring gene-metabolite regulatory networks. The diagnostic value of the identified biomarkers was validated in a validation cohort ( n = 220), and the biological function was verified. A total of 457 dysregulated metabolites were identified in the serum, of which 36 were induced by tumor tissues. The integrated analyses revealed significant alterations in the purine salvage pathway, wherein the abundance of hypoxanthine/xanthine exhibited a positive correlation with HPRT1 expression and tumor size. A diagnostic model was developed using two purine salvage–associated metabolites. This model could accurately discriminate patients with ESCC from normal individuals, with an area under the curve (AUC) (95% confidence interval (CI): 0.680–0.843) of 0.765 in the external cohort. Hypoxanthine and HPRT1 exerted a synergistic effect in terms of promoting ESCC progression. These findings are anticipated to provide valuable support in developing novel diagnostic approaches for early ESCC and enhance our comprehension of the metabolic mechanisms underlying this disease.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41420-024-01896-6
- https://www.nature.com/articles/s41420-024-01896-6.pdf
- OA Status
- gold
- Cited By
- 7
- References
- 59
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392804848
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4392804848Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1038/s41420-024-01896-6Digital Object Identifier
- Title
-
Purine salvage–associated metabolites as biomarkers for early diagnosis of esophageal squamous cell carcinoma: a diagnostic model–based studyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-03-14Full publication date if available
- Authors
-
Yawen Sun, Wenjuan Liu, Mu Su, Tao Zhang, Xia Li, Wenbin Liu, Yuping Cai, Deli Zhao, Ming Yang, Zheng‐Jiang Zhu, Jialin Wang, Jinming YuList of authors in order
- Landing page
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https://doi.org/10.1038/s41420-024-01896-6Publisher landing page
- PDF URL
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https://www.nature.com/articles/s41420-024-01896-6.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.nature.com/articles/s41420-024-01896-6.pdfDirect OA link when available
- Concepts
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Metabolite, Metabolomics, Hypoxanthine, Cohort, Medicine, Biomarker, Internal medicine, Purine, Oncology, Transcriptome, Cancer research, Biology, Bioinformatics, Gene expression, Biochemistry, Gene, EnzymeTop concepts (fields/topics) attached by OpenAlex
- Cited by
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7Total citation count in OpenAlex
- Citations by year (recent)
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2025: 5, 2024: 2Per-year citation counts (last 5 years)
- References (count)
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59Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.This | 215 |
| abstract_inverted_index.area | 228 |
| abstract_inverted_index.cell | 3 |
| abstract_inverted_index.from | 75, 223 |
| abstract_inverted_index.have | 18 |
| abstract_inverted_index.poor | 20 |
| abstract_inverted_index.this | 43, 282 |
| abstract_inverted_index.were | 68, 98, 129, 166, 174 |
| abstract_inverted_index.with | 15, 199, 221, 226 |
| abstract_inverted_index.(AUC) | 232 |
| abstract_inverted_index.(CI): | 236 |
| abstract_inverted_index.0.765 | 239 |
| abstract_inverted_index.220), | 153 |
| abstract_inverted_index.ESCC. | 63 |
| abstract_inverted_index.HPRT1 | 200, 246 |
| abstract_inverted_index.These | 257 |
| abstract_inverted_index.could | 217 |
| abstract_inverted_index.curve | 231 |
| abstract_inverted_index.early | 27, 39, 271 |
| abstract_inverted_index.model | 207, 216 |
| abstract_inverted_index.novel | 267 |
| abstract_inverted_index.rate, | 24 |
| abstract_inverted_index.serum | 73 |
| abstract_inverted_index.size. | 204 |
| abstract_inverted_index.study | 45 |
| abstract_inverted_index.terms | 252 |
| abstract_inverted_index.total | 161 |
| abstract_inverted_index.tumor | 177, 203 |
| abstract_inverted_index.under | 229 |
| abstract_inverted_index.using | 210 |
| abstract_inverted_index.value | 139 |
| abstract_inverted_index.which | 172 |
| abstract_inverted_index.(ESCC) | 5 |
| abstract_inverted_index.First, | 64 |
| abstract_inverted_index.Hence, | 42 |
| abstract_inverted_index.cohort | 78, 149 |
| abstract_inverted_index.effect | 250 |
| abstract_inverted_index.health | 9 |
| abstract_inverted_index.normal | 224 |
| abstract_inverted_index.purine | 187, 212 |
| abstract_inverted_index.serum, | 170 |
| abstract_inverted_index.serum. | 102 |
| abstract_inverted_index.tissue | 71, 107 |
| abstract_inverted_index.cohort. | 243 |
| abstract_inverted_index.concern | 10 |
| abstract_inverted_index.enhance | 274 |
| abstract_inverted_index.exerted | 247 |
| abstract_inverted_index.further | 130 |
| abstract_inverted_index.gaining | 36 |
| abstract_inverted_index.healthy | 88 |
| abstract_inverted_index.induced | 175 |
| abstract_inverted_index.provide | 262 |
| abstract_inverted_index.remains | 6, 29 |
| abstract_inverted_index.salvage | 188 |
| abstract_inverted_index.samples | 74, 108 |
| abstract_inverted_index.support | 264 |
| abstract_inverted_index.through | 52 |
| abstract_inverted_index.wherein | 190 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Patients | 14 |
| abstract_inverted_index.advanced | 16 |
| abstract_inverted_index.analyses | 181 |
| abstract_inverted_index.analysis | 119 |
| abstract_inverted_index.disease. | 283 |
| abstract_inverted_index.examined | 69 |
| abstract_inverted_index.external | 242 |
| abstract_inverted_index.findings | 258 |
| abstract_inverted_index.followed | 115 |
| abstract_inverted_index.function | 157 |
| abstract_inverted_index.identify | 58 |
| abstract_inverted_index.interval | 235 |
| abstract_inverted_index.observed | 99 |
| abstract_inverted_index.pathway, | 189 |
| abstract_inverted_index.patients | 220 |
| abstract_inverted_index.positive | 197 |
| abstract_inverted_index.profiles | 67 |
| abstract_inverted_index.research | 55 |
| abstract_inverted_index.revealed | 182 |
| abstract_inverted_index.squamous | 2 |
| abstract_inverted_index.strategy | 56 |
| abstract_inverted_index.survival | 23 |
| abstract_inverted_index.tissues. | 178 |
| abstract_inverted_index.valuable | 263 |
| abstract_inverted_index.Metabolic | 32 |
| abstract_inverted_index.abundance | 192 |
| abstract_inverted_index.achieving | 26 |
| abstract_inverted_index.attention | 37 |
| abstract_inverted_index.carcinoma | 4 |
| abstract_inverted_index.censoring | 133 |
| abstract_inverted_index.developed | 209 |
| abstract_inverted_index.diagnosis | 28 |
| abstract_inverted_index.discovery | 77 |
| abstract_inverted_index.evaluated | 47 |
| abstract_inverted_index.exhibited | 195 |
| abstract_inverted_index.gradually | 35 |
| abstract_inverted_index.important | 8 |
| abstract_inverted_index.metabolic | 66, 279 |
| abstract_inverted_index.networks. | 136 |
| abstract_inverted_index.patients, | 84 |
| abstract_inverted_index.potential | 125 |
| abstract_inverted_index.prognosis | 21 |
| abstract_inverted_index.promoting | 254 |
| abstract_inverted_index.validated | 145 |
| abstract_inverted_index.verified. | 159 |
| abstract_inverted_index.Afterward, | 103 |
| abstract_inverted_index.Esophageal | 1 |
| abstract_inverted_index.accurately | 218 |
| abstract_inverted_index.approaches | 269 |
| abstract_inverted_index.biological | 156 |
| abstract_inverted_index.biomarkers | 33, 61, 126, 143 |
| abstract_inverted_index.challenge. | 31 |
| abstract_inverted_index.confidence | 234 |
| abstract_inverted_index.countries. | 13 |
| abstract_inverted_index.developing | 12, 266 |
| abstract_inverted_index.diagnostic | 40, 138, 206, 268 |
| abstract_inverted_index.expression | 201 |
| abstract_inverted_index.identified | 131, 142, 167 |
| abstract_inverted_index.integrated | 54, 118, 180 |
| abstract_inverted_index.mechanisms | 280 |
| abstract_inverted_index.metabolism | 48 |
| abstract_inverted_index.metabolite | 60, 96 |
| abstract_inverted_index.performed, | 114 |
| abstract_inverted_index.regulatory | 135 |
| abstract_inverted_index.sequencing | 105 |
| abstract_inverted_index.underlying | 281 |
| abstract_inverted_index.validation | 148 |
| abstract_inverted_index.alterations | 97, 184 |
| abstract_inverted_index.anticipated | 260 |
| abstract_inverted_index.biomarkers. | 41 |
| abstract_inverted_index.correlation | 198 |
| abstract_inverted_index.metabolites | 165 |
| abstract_inverted_index.multicenter | 44 |
| abstract_inverted_index.significant | 183 |
| abstract_inverted_index.synergistic | 249 |
| abstract_inverted_index.volunteers, | 89 |
| abstract_inverted_index.Hypoxanthine | 244 |
| abstract_inverted_index.discriminate | 219 |
| abstract_inverted_index.dysregulated | 164 |
| abstract_inverted_index.individuals, | 225 |
| abstract_inverted_index.metabolites. | 214 |
| abstract_inverted_index.metabolomics | 121 |
| abstract_inverted_index.progression. | 256 |
| abstract_inverted_index.comprehension | 276 |
| abstract_inverted_index.dysregulation | 49 |
| abstract_inverted_index.0.680–0.843) | 237 |
| abstract_inverted_index.tissue-induced | 95 |
| abstract_inverted_index.comprehensively | 46 |
| abstract_inverted_index.gene-metabolite | 134 |
| abstract_inverted_index.transcriptomics. | 123 |
| abstract_inverted_index.salvage–associated | 213 |
| abstract_inverted_index.hypoxanthine/xanthine | 194 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 94 |
| corresponding_author_ids | https://openalex.org/A5100648209 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 12 |
| corresponding_institution_ids | https://openalex.org/I4210100830, https://openalex.org/I4210163399 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/17 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Partnerships for the goals |
| citation_normalized_percentile.value | 0.95698012 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |