Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma
IntroductionIntra-tumoral heterogeneity is a prominent characteristic of hepatocellular carcinoma (HCC). However, it remains unexplored whether intra-tumoral transcriptomic differences can capture crucial information regarding HCC evolution and be utilized to derive a predictive signature for patien...
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Bioinformatics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbinf.2025.1669236/full |
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| author | Shangyi Luo Li Liu Yang Sun Jian Shi Yajing Zhang Yajing Zhang Yajing Zhang |
| author_facet | Shangyi Luo Li Liu Yang Sun Jian Shi Yajing Zhang Yajing Zhang Yajing Zhang |
| author_sort | Shangyi Luo |
| collection | DOAJ |
| description | IntroductionIntra-tumoral heterogeneity is a prominent characteristic of hepatocellular carcinoma (HCC). However, it remains unexplored whether intra-tumoral transcriptomic differences can capture crucial information regarding HCC evolution and be utilized to derive a predictive signature for patient’s clinical trajectories.MethodsWe quantified transcriptomic heterogeneity using four multiregional HCC cohorts comprising 172 samples from 37 patients, and validated transcriptomic heterogeneity and spatial dynamics using multiregional single-cell transcriptomic profiling of 110,817 cells from 34 liver specimens. The HCC evolutionary signature (HCCEvoSig) was developed and assessed across six cross-platform HCC cohorts.ResultsGenes exhibiting high intra- and inter-tumor expression variation were significantly enriched in a gene set associated with HCC prognosis, from which we developed and validated a reproducible and robust transcriptomic signature, HCCEvoSig. Multiregional single-cell data confirmed the high intra- and inter-tumoral heterogeneity of HCCEvoSig genes across different cell types, and importantly, demonstrated that the dysregulation of HCCEvoSig genes exhibited a geospatially gradual transition from the non-tumor region to the tumor border and tumor core, as well as from non-malignant to malignant epithelial cells. HCCEvoSig showed significant positive associations with adverse features of HCC, and a high HCCEvoSig risk score predicted increased risks of disease progression and mortality, independent of established clinicopathological indices. Furthermore, HCCEvoSig outperformed 15 published signatures in discriminative ability and prognostic accuracy, particularly regarding 1-year survival rates. Notably, HCCEvoSig demonstrated predictive utility for responses to immunotherapy and trans-arterial chemoembolization. Additionally, we established a well-calibrated predictive nomogram that integrates HCCEvoSig and TNM stage to generate an individualized numerical probability of mortality.ConclusionOur study reveals that regional transcriptional heterogeneity within tumors is substantial enough to capture survival signals, and the constructed and validated HCCEvoSig provides reliable prognostic information for HCC patients. |
| format | Article |
| id | doaj-art-e35f90e577a245b985d6961972e98511 |
| institution | Kabale University |
| issn | 2673-7647 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioinformatics |
| spelling | doaj-art-e35f90e577a245b985d6961972e985112025-08-20T03:46:46ZengFrontiers Media S.A.Frontiers in Bioinformatics2673-76472025-08-01510.3389/fbinf.2025.16692361669236Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinomaShangyi Luo0Li Liu1Yang Sun2Jian Shi3Yajing Zhang4Yajing Zhang5Yajing Zhang6Interdisciplinary Institute for Medical Engineering, Fuzhou University, Fuzhou, Fujian, ChinaInterdisciplinary Institute for Medical Engineering, Fuzhou University, Fuzhou, Fujian, ChinaClinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaSchool of Basic Medical Sciences, Chongqing Medical University, Chongqing, ChinaInterdisciplinary Institute for Medical Engineering, Fuzhou University, Fuzhou, Fujian, ChinaNHC and CAMS Key Laboratory of Molecular Probe and Targeted Theranostics, Harbin Medical University, Harbin, Heilongjiang, ChinaHeilongjiang Province Key Laboratory of Child Development and Genetic Research, Harbin Medical University, Harbin, Heilongjiang, ChinaIntroductionIntra-tumoral heterogeneity is a prominent characteristic of hepatocellular carcinoma (HCC). However, it remains unexplored whether intra-tumoral transcriptomic differences can capture crucial information regarding HCC evolution and be utilized to derive a predictive signature for patient’s clinical trajectories.MethodsWe quantified transcriptomic heterogeneity using four multiregional HCC cohorts comprising 172 samples from 37 patients, and validated transcriptomic heterogeneity and spatial dynamics using multiregional single-cell transcriptomic profiling of 110,817 cells from 34 liver specimens. The HCC evolutionary signature (HCCEvoSig) was developed and assessed across six cross-platform HCC cohorts.ResultsGenes exhibiting high intra- and inter-tumor expression variation were significantly enriched in a gene set associated with HCC prognosis, from which we developed and validated a reproducible and robust transcriptomic signature, HCCEvoSig. Multiregional single-cell data confirmed the high intra- and inter-tumoral heterogeneity of HCCEvoSig genes across different cell types, and importantly, demonstrated that the dysregulation of HCCEvoSig genes exhibited a geospatially gradual transition from the non-tumor region to the tumor border and tumor core, as well as from non-malignant to malignant epithelial cells. HCCEvoSig showed significant positive associations with adverse features of HCC, and a high HCCEvoSig risk score predicted increased risks of disease progression and mortality, independent of established clinicopathological indices. Furthermore, HCCEvoSig outperformed 15 published signatures in discriminative ability and prognostic accuracy, particularly regarding 1-year survival rates. Notably, HCCEvoSig demonstrated predictive utility for responses to immunotherapy and trans-arterial chemoembolization. Additionally, we established a well-calibrated predictive nomogram that integrates HCCEvoSig and TNM stage to generate an individualized numerical probability of mortality.ConclusionOur study reveals that regional transcriptional heterogeneity within tumors is substantial enough to capture survival signals, and the constructed and validated HCCEvoSig provides reliable prognostic information for HCC patients.https://www.frontiersin.org/articles/10.3389/fbinf.2025.1669236/fullhepatocellular carcinomamulti-region sequencingexpression dynamicstumor evolutionprognostication |
| spellingShingle | Shangyi Luo Li Liu Yang Sun Jian Shi Yajing Zhang Yajing Zhang Yajing Zhang Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma Frontiers in Bioinformatics hepatocellular carcinoma multi-region sequencing expression dynamics tumor evolution prognostication |
| title | Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma |
| title_full | Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma |
| title_fullStr | Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma |
| title_full_unstemmed | Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma |
| title_short | Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma |
| title_sort | spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma |
| topic | hepatocellular carcinoma multi-region sequencing expression dynamics tumor evolution prognostication |
| url | https://www.frontiersin.org/articles/10.3389/fbinf.2025.1669236/full |
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