Unraveling the potential mechanism and prognostic value of pentose phosphate pathway in hepatocellular carcinoma: a comprehensive analysis integrating bulk transcriptomics and single-cell sequencing data

Hepatocellular carcinoma (HCC) remains a malignant and life-threatening tumor with an extremely poor prognosis, posing a significant global health challenge. Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drug...

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Veröffentlicht in:Functional & integrative genomics 2025-12, Vol.25 (1), p.11, Article 11
Hauptverfasser: Li, Bin, Zeng, Tao, Chen, Cui, Wu, Yuankai, Huang, Shuying, Deng, Jing, Pang, Jiahui, Cai, Xiang, Lin, Yuxi, Sun, Yina, Chong, Yutian, Li, Xinhua, Gong, Jiao, Tang, Guofang
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container_title Functional & integrative genomics
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creator Li, Bin
Zeng, Tao
Chen, Cui
Wu, Yuankai
Huang, Shuying
Deng, Jing
Pang, Jiahui
Cai, Xiang
Lin, Yuxi
Sun, Yina
Chong, Yutian
Li, Xinhua
Gong, Jiao
Tang, Guofang
description Hepatocellular carcinoma (HCC) remains a malignant and life-threatening tumor with an extremely poor prognosis, posing a significant global health challenge. Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drugs and overall prognosis. The pentose phosphate pathway (PPP) is highly activated in various tumor cells and plays a pivotal role in tumor metabolic reprogramming. This study aimed to construct a model based on PPP-related Genes for risk assessment and prognosis prediction in HCC patients. We integrated RNA-seq and microarray data from TCGA, GEO, and ICGC databases, along with single-cell RNA sequencing (scRNA-seq) data obtained from HCC patients via GEO. Based on the “Seurat” R package, we identified distinct gene clusters related to the PPP within the scRNA-seq data. Using a penalized Cox regression model with least absolute shrinkage and selection operator (LASSO) penalties, we constructed a risk prognosis model. The validity of our risk prognosis model was further confirmed in external cohorts. Additionally, we developed a nomogram capable of accurately predicting overall survival in HCC patients. Furthermore, we explored the predictive potential of our risk model within the immune microenvironment and assessed its relevance to biological function, particularly in the context of immunotherapy. Subsequently, we performed in vitro functional validation of the key genes (ATAD2 and SPP1) in our model. A ten-gene signature associated with the PPP was formulated to enhance the prediction of HCC prognosis and anti-tumor treatment response. Following this, the ROC curve, nomogram, and calibration curve outcomes corroborated the model’s robust clinical predictive capability. Functional enrichment analysis unveiled the engagement of the immune system and notable variances in the immune infiltration landscape across the high and low-risk groups. Additionally, tumor mutation frequencies were observed to be elevated in the high-risk group. Based on our analyses, the IC50 values of most identified anticancer agents demonstrated a correlation with the RiskScore. Additionally, the high-risk and low-risk groups exhibited differential sensitivity to various drugs. Cytological experiments revealed that silencing ATAD2 or SPP1 suppresses malignant phenotypes, including viability and migration, in liver cancer cells. In this study, a novel gene signature related to the PPP was de
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Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drugs and overall prognosis. The pentose phosphate pathway (PPP) is highly activated in various tumor cells and plays a pivotal role in tumor metabolic reprogramming. This study aimed to construct a model based on PPP-related Genes for risk assessment and prognosis prediction in HCC patients. We integrated RNA-seq and microarray data from TCGA, GEO, and ICGC databases, along with single-cell RNA sequencing (scRNA-seq) data obtained from HCC patients via GEO. Based on the “Seurat” R package, we identified distinct gene clusters related to the PPP within the scRNA-seq data. Using a penalized Cox regression model with least absolute shrinkage and selection operator (LASSO) penalties, we constructed a risk prognosis model. The validity of our risk prognosis model was further confirmed in external cohorts. Additionally, we developed a nomogram capable of accurately predicting overall survival in HCC patients. Furthermore, we explored the predictive potential of our risk model within the immune microenvironment and assessed its relevance to biological function, particularly in the context of immunotherapy. Subsequently, we performed in vitro functional validation of the key genes (ATAD2 and SPP1) in our model. A ten-gene signature associated with the PPP was formulated to enhance the prediction of HCC prognosis and anti-tumor treatment response. Following this, the ROC curve, nomogram, and calibration curve outcomes corroborated the model’s robust clinical predictive capability. Functional enrichment analysis unveiled the engagement of the immune system and notable variances in the immune infiltration landscape across the high and low-risk groups. Additionally, tumor mutation frequencies were observed to be elevated in the high-risk group. Based on our analyses, the IC50 values of most identified anticancer agents demonstrated a correlation with the RiskScore. Additionally, the high-risk and low-risk groups exhibited differential sensitivity to various drugs. Cytological experiments revealed that silencing ATAD2 or SPP1 suppresses malignant phenotypes, including viability and migration, in liver cancer cells. In this study, a novel gene signature related to the PPP was developed, demonstrating favorable predictive performance. This signature holds significant guiding value for assessing the prognosis of HCC patients and directing individualized treatment strategies.</description><identifier>ISSN: 1438-793X</identifier><identifier>ISSN: 1438-7948</identifier><identifier>EISSN: 1438-7948</identifier><identifier>DOI: 10.1007/s10142-024-01521-w</identifier><identifier>PMID: 39798003</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Animal Genetics and Genomics ; Antineoplastic drugs ; Biochemistry ; Bioinformatics ; Biomarkers, Tumor - genetics ; Biomedical and Life Sciences ; Carcinoma, Hepatocellular - genetics ; Cell Biology ; Cell migration ; DNA microarrays ; Gene clusters ; Gene Expression Regulation, Neoplastic ; Gene set enrichment analysis ; Genes ; Hepatocellular carcinoma ; Hepatocytes ; Humans ; Immune system ; Immunosuppressive agents ; Immunotherapy ; Life Sciences ; Liver cancer ; Liver Neoplasms - genetics ; Liver Neoplasms - pathology ; Medical prognosis ; Metastases ; Microbial Genetics and Genomics ; Microenvironments ; Nomograms ; Patients ; Pentose phosphate pathway ; Pentose Phosphate Pathway - genetics ; Phenotypes ; Plant Genetics and Genomics ; Prognosis ; Public health ; Risk assessment ; Risk groups ; Single-Cell Analysis ; Transcriptome ; Transcriptomics ; Tumor cells ; Tumor Microenvironment - genetics ; Tumors</subject><ispartof>Functional &amp; integrative genomics, 2025-12, Vol.25 (1), p.11, Article 11</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025 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.</rights><rights>2025. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><rights>Copyright Springer Nature B.V. Dec 2025</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c256t-4c3d88f226b5a9cd7431f07fe85f0d8a0fb5a5675e086241a35fc8bcf13562c53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10142-024-01521-w$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10142-024-01521-w$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39798003$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Bin</creatorcontrib><creatorcontrib>Zeng, Tao</creatorcontrib><creatorcontrib>Chen, Cui</creatorcontrib><creatorcontrib>Wu, Yuankai</creatorcontrib><creatorcontrib>Huang, Shuying</creatorcontrib><creatorcontrib>Deng, Jing</creatorcontrib><creatorcontrib>Pang, Jiahui</creatorcontrib><creatorcontrib>Cai, Xiang</creatorcontrib><creatorcontrib>Lin, Yuxi</creatorcontrib><creatorcontrib>Sun, Yina</creatorcontrib><creatorcontrib>Chong, Yutian</creatorcontrib><creatorcontrib>Li, Xinhua</creatorcontrib><creatorcontrib>Gong, Jiao</creatorcontrib><creatorcontrib>Tang, Guofang</creatorcontrib><title>Unraveling the potential mechanism and prognostic value of pentose phosphate pathway in hepatocellular carcinoma: a comprehensive analysis integrating bulk transcriptomics and single-cell sequencing data</title><title>Functional &amp; integrative genomics</title><addtitle>Funct Integr Genomics</addtitle><addtitle>Funct Integr Genomics</addtitle><description>Hepatocellular carcinoma (HCC) remains a malignant and life-threatening tumor with an extremely poor prognosis, posing a significant global health challenge. Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drugs and overall prognosis. The pentose phosphate pathway (PPP) is highly activated in various tumor cells and plays a pivotal role in tumor metabolic reprogramming. This study aimed to construct a model based on PPP-related Genes for risk assessment and prognosis prediction in HCC patients. We integrated RNA-seq and microarray data from TCGA, GEO, and ICGC databases, along with single-cell RNA sequencing (scRNA-seq) data obtained from HCC patients via GEO. Based on the “Seurat” R package, we identified distinct gene clusters related to the PPP within the scRNA-seq data. Using a penalized Cox regression model with least absolute shrinkage and selection operator (LASSO) penalties, we constructed a risk prognosis model. The validity of our risk prognosis model was further confirmed in external cohorts. Additionally, we developed a nomogram capable of accurately predicting overall survival in HCC patients. Furthermore, we explored the predictive potential of our risk model within the immune microenvironment and assessed its relevance to biological function, particularly in the context of immunotherapy. Subsequently, we performed in vitro functional validation of the key genes (ATAD2 and SPP1) in our model. A ten-gene signature associated with the PPP was formulated to enhance the prediction of HCC prognosis and anti-tumor treatment response. Following this, the ROC curve, nomogram, and calibration curve outcomes corroborated the model’s robust clinical predictive capability. Functional enrichment analysis unveiled the engagement of the immune system and notable variances in the immune infiltration landscape across the high and low-risk groups. Additionally, tumor mutation frequencies were observed to be elevated in the high-risk group. Based on our analyses, the IC50 values of most identified anticancer agents demonstrated a correlation with the RiskScore. Additionally, the high-risk and low-risk groups exhibited differential sensitivity to various drugs. Cytological experiments revealed that silencing ATAD2 or SPP1 suppresses malignant phenotypes, including viability and migration, in liver cancer cells. In this study, a novel gene signature related to the PPP was developed, demonstrating favorable predictive performance. This signature holds significant guiding value for assessing the prognosis of HCC patients and directing individualized treatment strategies.</description><subject>Animal Genetics and Genomics</subject><subject>Antineoplastic drugs</subject><subject>Biochemistry</subject><subject>Bioinformatics</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biomedical and Life Sciences</subject><subject>Carcinoma, Hepatocellular - genetics</subject><subject>Cell Biology</subject><subject>Cell migration</subject><subject>DNA microarrays</subject><subject>Gene clusters</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Gene set enrichment analysis</subject><subject>Genes</subject><subject>Hepatocellular carcinoma</subject><subject>Hepatocytes</subject><subject>Humans</subject><subject>Immune system</subject><subject>Immunosuppressive agents</subject><subject>Immunotherapy</subject><subject>Life Sciences</subject><subject>Liver cancer</subject><subject>Liver Neoplasms - genetics</subject><subject>Liver Neoplasms - pathology</subject><subject>Medical prognosis</subject><subject>Metastases</subject><subject>Microbial Genetics and Genomics</subject><subject>Microenvironments</subject><subject>Nomograms</subject><subject>Patients</subject><subject>Pentose phosphate pathway</subject><subject>Pentose Phosphate Pathway - genetics</subject><subject>Phenotypes</subject><subject>Plant Genetics and Genomics</subject><subject>Prognosis</subject><subject>Public health</subject><subject>Risk assessment</subject><subject>Risk groups</subject><subject>Single-Cell Analysis</subject><subject>Transcriptome</subject><subject>Transcriptomics</subject><subject>Tumor cells</subject><subject>Tumor Microenvironment - genetics</subject><subject>Tumors</subject><issn>1438-793X</issn><issn>1438-7948</issn><issn>1438-7948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kctu1TAQhiMEoqXwAiyQJTZsAr7EubBDVblIldhQiV00x5mcuCR28Djn6DwjL4XTlCKxYOWx55vfv_1n2UvB3wrOq3ckuChkzmWRc6GlyI-PsnNRqDqvmqJ-_FCr72fZM6JbzrnmjXqanammamrO1Xn268YFOOBo3Z7FAdnsI7poYWQTmgGcpYmB69gc_N55itawA4wLMt-zOZGe0szgaR4gpgricIQTs44NmDbe4DguIwRmIBjr_ATvGTDjpznggI7sAZM8jCeylKYi7gPE1ctuGX-wGMCRCXaOfrKG7oxQ6o6Yr8KM8OeCzqx8BxGeZ096GAlf3K8X2c3Hq2-Xn_Prr5--XH64zo3UZcwLo7q67qUsdxoa01WFEj2veqx1z7saeJ_OdVlp5HUpCwFK96bemV4oXUqj1UX2ZtNNn5IMUGwnS6shcOgXapXQRcFLLVf09T_orV9CevBGyVqqQiZKbpQJnihg387BThBOreDtGnW7Rd2mqNu7qNtjGnp1L73sJuweRv5kmwC1AZRabo_h793_kf0Nm1a7Nw</recordid><startdate>20251201</startdate><enddate>20251201</enddate><creator>Li, Bin</creator><creator>Zeng, Tao</creator><creator>Chen, Cui</creator><creator>Wu, Yuankai</creator><creator>Huang, Shuying</creator><creator>Deng, Jing</creator><creator>Pang, Jiahui</creator><creator>Cai, Xiang</creator><creator>Lin, Yuxi</creator><creator>Sun, Yina</creator><creator>Chong, Yutian</creator><creator>Li, Xinhua</creator><creator>Gong, Jiao</creator><creator>Tang, Guofang</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20251201</creationdate><title>Unraveling the potential mechanism and prognostic value of pentose phosphate pathway in hepatocellular carcinoma: a comprehensive analysis integrating bulk transcriptomics and single-cell sequencing data</title><author>Li, Bin ; Zeng, Tao ; Chen, Cui ; Wu, Yuankai ; Huang, Shuying ; Deng, Jing ; Pang, Jiahui ; Cai, Xiang ; Lin, Yuxi ; Sun, Yina ; Chong, Yutian ; Li, Xinhua ; Gong, Jiao ; Tang, Guofang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c256t-4c3d88f226b5a9cd7431f07fe85f0d8a0fb5a5675e086241a35fc8bcf13562c53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Animal Genetics and Genomics</topic><topic>Antineoplastic drugs</topic><topic>Biochemistry</topic><topic>Bioinformatics</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Biomedical and Life Sciences</topic><topic>Carcinoma, Hepatocellular - genetics</topic><topic>Cell Biology</topic><topic>Cell migration</topic><topic>DNA microarrays</topic><topic>Gene clusters</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Gene set enrichment analysis</topic><topic>Genes</topic><topic>Hepatocellular carcinoma</topic><topic>Hepatocytes</topic><topic>Humans</topic><topic>Immune system</topic><topic>Immunosuppressive agents</topic><topic>Immunotherapy</topic><topic>Life Sciences</topic><topic>Liver cancer</topic><topic>Liver Neoplasms - genetics</topic><topic>Liver Neoplasms - pathology</topic><topic>Medical prognosis</topic><topic>Metastases</topic><topic>Microbial Genetics and Genomics</topic><topic>Microenvironments</topic><topic>Nomograms</topic><topic>Patients</topic><topic>Pentose phosphate pathway</topic><topic>Pentose Phosphate Pathway - genetics</topic><topic>Phenotypes</topic><topic>Plant Genetics and Genomics</topic><topic>Prognosis</topic><topic>Public health</topic><topic>Risk assessment</topic><topic>Risk groups</topic><topic>Single-Cell Analysis</topic><topic>Transcriptome</topic><topic>Transcriptomics</topic><topic>Tumor cells</topic><topic>Tumor Microenvironment - genetics</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Bin</creatorcontrib><creatorcontrib>Zeng, Tao</creatorcontrib><creatorcontrib>Chen, Cui</creatorcontrib><creatorcontrib>Wu, Yuankai</creatorcontrib><creatorcontrib>Huang, Shuying</creatorcontrib><creatorcontrib>Deng, Jing</creatorcontrib><creatorcontrib>Pang, Jiahui</creatorcontrib><creatorcontrib>Cai, Xiang</creatorcontrib><creatorcontrib>Lin, Yuxi</creatorcontrib><creatorcontrib>Sun, Yina</creatorcontrib><creatorcontrib>Chong, Yutian</creatorcontrib><creatorcontrib>Li, Xinhua</creatorcontrib><creatorcontrib>Gong, Jiao</creatorcontrib><creatorcontrib>Tang, Guofang</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health &amp; 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Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drugs and overall prognosis. The pentose phosphate pathway (PPP) is highly activated in various tumor cells and plays a pivotal role in tumor metabolic reprogramming. This study aimed to construct a model based on PPP-related Genes for risk assessment and prognosis prediction in HCC patients. We integrated RNA-seq and microarray data from TCGA, GEO, and ICGC databases, along with single-cell RNA sequencing (scRNA-seq) data obtained from HCC patients via GEO. Based on the “Seurat” R package, we identified distinct gene clusters related to the PPP within the scRNA-seq data. Using a penalized Cox regression model with least absolute shrinkage and selection operator (LASSO) penalties, we constructed a risk prognosis model. The validity of our risk prognosis model was further confirmed in external cohorts. Additionally, we developed a nomogram capable of accurately predicting overall survival in HCC patients. Furthermore, we explored the predictive potential of our risk model within the immune microenvironment and assessed its relevance to biological function, particularly in the context of immunotherapy. Subsequently, we performed in vitro functional validation of the key genes (ATAD2 and SPP1) in our model. A ten-gene signature associated with the PPP was formulated to enhance the prediction of HCC prognosis and anti-tumor treatment response. Following this, the ROC curve, nomogram, and calibration curve outcomes corroborated the model’s robust clinical predictive capability. Functional enrichment analysis unveiled the engagement of the immune system and notable variances in the immune infiltration landscape across the high and low-risk groups. Additionally, tumor mutation frequencies were observed to be elevated in the high-risk group. Based on our analyses, the IC50 values of most identified anticancer agents demonstrated a correlation with the RiskScore. Additionally, the high-risk and low-risk groups exhibited differential sensitivity to various drugs. Cytological experiments revealed that silencing ATAD2 or SPP1 suppresses malignant phenotypes, including viability and migration, in liver cancer cells. In this study, a novel gene signature related to the PPP was developed, demonstrating favorable predictive performance. This signature holds significant guiding value for assessing the prognosis of HCC patients and directing individualized treatment strategies.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>39798003</pmid><doi>10.1007/s10142-024-01521-w</doi></addata></record>
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subjects Animal Genetics and Genomics
Antineoplastic drugs
Biochemistry
Bioinformatics
Biomarkers, Tumor - genetics
Biomedical and Life Sciences
Carcinoma, Hepatocellular - genetics
Cell Biology
Cell migration
DNA microarrays
Gene clusters
Gene Expression Regulation, Neoplastic
Gene set enrichment analysis
Genes
Hepatocellular carcinoma
Hepatocytes
Humans
Immune system
Immunosuppressive agents
Immunotherapy
Life Sciences
Liver cancer
Liver Neoplasms - genetics
Liver Neoplasms - pathology
Medical prognosis
Metastases
Microbial Genetics and Genomics
Microenvironments
Nomograms
Patients
Pentose phosphate pathway
Pentose Phosphate Pathway - genetics
Phenotypes
Plant Genetics and Genomics
Prognosis
Public health
Risk assessment
Risk groups
Single-Cell Analysis
Transcriptome
Transcriptomics
Tumor cells
Tumor Microenvironment - genetics
Tumors
title Unraveling the potential mechanism and prognostic value of pentose phosphate pathway in hepatocellular carcinoma: a comprehensive analysis integrating bulk transcriptomics and single-cell sequencing data
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