@Article{biocell.2024.050803,
AUTHOR = {XUEJIA ZHAI, JIE LIU, JINWEI XIAO, TAO ZHANG, JUN WANG, JIANJUN LI, SHICANG YU},
TITLE = {The lactylation index predicts the immune microenvironment and prognosis of pan-cancer patients},
JOURNAL = {BIOCELL},
VOLUME = {48},
YEAR = {2024},
NUMBER = {8},
PAGES = {1223--1239},
URL = {http://www.techscience.com/biocell/v48n8/57510},
ISSN = {1667-5746},
ABSTRACT = { <b>Background:</b> Protein lactylation is a new way for the “metabolic waste” lactic acid to perform novel functions. Nevertheless, our understanding of the contribution of protein lactylation to both tumor progression and therapeutic interventions remains imited. The construction of a scoring system for lactylation to predict the prognosis of pan-cancer patients and to evaluate the tumor immune microenvironment (TIME) would improve our understanding of the clinical significance of lactylation. <b>Methods:</b> Consensus clustering analysis of lactylation-related genes was used to cluster 177 pancreatic adenocarcinoma (PAAD) patients. Subsequently, a scoring system was developed using the least absolute shrinkage and selection operator (LASSO) regression. Internal validation and external validation were both conducted to assess and confirm the predictive accuracy of the scoring system. Finally, leucine rich repeat containing 1 (LRRC1), a newly discovered lactylation-related gene, was analyzed in PAAD <i>in vitro</i>. <b>Results:</b> Utilizing the profiles of 332 lactylation-related genes, a total of 177 patients with PAAD were segregated into two distinct groups. LacCluster<sup>high</sup> patients had a poorer prognosis than LacCluster<sup>low</sup> patients. Through the differential analysis between the LacCluster<sup>high</sup> and LacCluster<sup>low</sup> groups, we identified additional genes associated with lactylation. These genes were then integrated to construct the LacCluster-enhanced system, which enabled more accurate prognosis prediction for patients with PAAD. Then, a lactylation index containing three genes (LacI-3) was constructed using LASSO regression. This was done to enhance the usability of the LacCluster-enhanced system in the clinic. Compared to those in the LacI-3<sup>high</sup> subgroup, patients in the LacI-3<sup>low</sup> subgroup exhibited increased expression of immune checkpoint-related genes, more immune cell infiltration, lower tumor mutation burdens, and better prognoses, indicating a “hot tumor” phenotype. Moreover, knocking down the expression of LRRC1, the hub gene in the LacI-3 scoring system, inhibited PAAD cell invasion, migration, and proliferation <i>in vitro</i>. Ultimately, the significance of LacI-3 across cancers was confirmed. <b>Conclusion:</b> Our findings strongly imply that protein lactylation may represent a new approach to diagnosing and treating malignant tumors.},
DOI = {10.32604/biocell.2024.050803}
}