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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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 |
doi_str_mv | 10.1007/s10142-024-01521-w |
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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 & 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 & 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 & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Functional & integrative genomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Bin</au><au>Zeng, Tao</au><au>Chen, Cui</au><au>Wu, Yuankai</au><au>Huang, Shuying</au><au>Deng, Jing</au><au>Pang, Jiahui</au><au>Cai, Xiang</au><au>Lin, Yuxi</au><au>Sun, Yina</au><au>Chong, Yutian</au><au>Li, Xinhua</au><au>Gong, Jiao</au><au>Tang, Guofang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>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</atitle><jtitle>Functional & integrative genomics</jtitle><stitle>Funct Integr Genomics</stitle><addtitle>Funct Integr Genomics</addtitle><date>2025-12-01</date><risdate>2025</risdate><volume>25</volume><issue>1</issue><spage>11</spage><pages>11-</pages><artnum>11</artnum><issn>1438-793X</issn><issn>1438-7948</issn><eissn>1438-7948</eissn><abstract>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.</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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