{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T17:52:57Z","timestamp":1780595577187,"version":"3.54.1"},"reference-count":61,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T00:00:00Z","timestamp":1773014400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Pharmacol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Colorectal cancer (CRC) remains a major cause of cancer-related morbidity and mortality, with high recurrence rates and limited treatment options for metastatic disease. The tumor microenvironment (TME) and metabolic reprogramming are critical drivers of CRC progression, influencing immune responses, therapeutic resistance, and patient outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study explores the interplay between metabolic reprogramming and the TME in CRC using transcriptomic data and bioinformatics approaches to identify metabolically and microenvironmentally defined CRC subtypes and candidate biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Gene expression and clinical data were obtained from TCGA colorectal adenocarcinoma (COAD), rectal adenocarcinoma (READ), and six GEO CRC datasets. Immunohistochemistry (IHC) was performed to validate PDE2A and CKMT2 expression in CRC tissues. Bioinformatic analyses were conducted using R software v4.0.3.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We identified 220 TME- and 40 metabolism-related differentially expressed genes (DEGs) in CRC. Consensus clustering of these TMET genes revealed two distinct subtypes: Cluster 1 (C1), associated with poorer survival, an immune-mesenchymal phenotype, and frequent mutations in TTN and BRAF, and Cluster 2 (C2), characterized by enriched TP53 and APC mutations, classic tumor suppressor pathway activation, and higher genomic instability. Metabolically, C1 was characterized by lipid metabolism and extracellular matrix remodeling, whereas C2 showed enrichment of nucleotide and amino acid metabolism linked to cell cycle progression and DNA repair. Single-cell RNA sequencing confirmed these distinctions, revealing that C1-upregulated genes were predominantly expressed in immune and stromal compartments, whereas C2-upregulated genes were enriched in epithelial and malignant cells. PDE2A, primarily expressed by endothelial cells, was identified as a metabolic biomarker of C1, while CKMT2, expressed in malignant cells, defined C2. These genes serve as key metabolic markers distinguishing CRC subtypes based on molecular heterogeneity and prognosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>PDE2A and CKMT2 were identified as critical metabolic biomarkers associated with distinct CRC subtypes and TME compositions. These findings highlight the intricate relationship between metabolic reprogramming, the tumor microenvironment, and tumor heterogeneity, providing insights into CRC molecular subtypes and their prognostic significance.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fphar.2026.1732137","type":"journal-article","created":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T06:46:24Z","timestamp":1773038784000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Metabolic profiling of the TME uncovers the contrasting impacts of CKMT2 and PDE2A in CRC progression and therapeutic response"],"prefix":"10.3389","volume":"17","author":[{"given":"Yuxiang","family":"Fu","sequence":"first","affiliation":[{"name":"Department of Gastrointestinal Surgery, Shenzhen People\u2019s Hospital, The Second Clinical Medical College, Jinan University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianbo","family":"Lai","sequence":"additional","affiliation":[{"name":"Department of Gastrointestinal Surgery, Shenzhen People\u2019s Hospital, The Second Clinical Medical College, Jinan University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaibin","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Gastrointestinal Surgery, Shenzhen People\u2019s Hospital, The Second Clinical Medical College, Jinan University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liping","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Hepatobiliary and Pancreas Surgery, Shenzhen People\u2019s Hospital, The Second Clinical Medical College, Jinan University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guixiang","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Shenzhen People\u2019s Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology)","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,3,9]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1186\/s13059-017-1349-1","article-title":"xCell: digitally portraying the tissue cellular heterogeneity landscape","volume":"18","author":"Aran","year":"2017","journal-title":"Genome Biol."},{"key":"B2","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1186\/s13059-016-1070-5","article-title":"Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression","volume":"17","author":"Becht","year":"2016","journal-title":"Genome Biol."},{"key":"B3","doi-asserted-by":"publisher","first-page":"1814","DOI":"10.1200\/JCO.2008.18.2071","article-title":"Microsatellite instability predicts improved response to adjuvant therapy with irinotecan, fluorouracil, and leucovorin in stage III colon cancer: cancer and leukemia group B protocol 89803","volume":"27","author":"Bertagnolli","year":"2009","journal-title":"J. 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