Three genes tied to lactylation and lactate metabolism may flag prostate cancer recurrence risk

Researchers have built a risk model that uses just three genes — MKI67, MIPEP and CCNA2 — to predict biochemical recurrence in prostate cancer, linking the genes to lactylation and lactate metabolism. The study, published in Discover Oncology on 27 October 2026, combined bulk RNA sequencing data from public databases with single-cell RNA sequencing to identify which of these genes carry prognostic weight.

The team started with a candidate pool of 23 genes, derived by intersecting differentially expressed genes from the TCGA prostate cancer dataset with the union of lactylation-related genes and lactate metabolism-related genes. To narrow this list, they applied univariate Cox analysis, tested the proportional hazards assumption, and used least absolute shrinkage and selection operator regression. Three genes survived this filtering as prognostic markers connected to lactylation or lactate metabolism.

Using these three genes, the researchers constructed a random survival forest model for biochemical recurrence risk prediction and validated it externally in the GSE21034 dataset, where it showed robust predictive performance. An exploratory nomogram integrating the risk score with Gleason score demonstrated favorable calibration and discrimination, suggesting a practical way to combine molecular and clinical information for risk stratification.

Beyond the core model, the analysis connected risk scores to G2M checkpoint activity, immune-cell infiltration patterns, predicted immunotherapy response, and predicted drug sensitivity. In the GSE153892 dataset, single-cell RNA sequencing was used to identify key cell types and expression patterns of the prognostic genes, adding a cellular-level view of where these markers are active within tumors.

The authors also validated gene expression experimentally using reverse transcription-quantitative polymerase chain reaction in a small clinical cohort. MIPEP and CCNA2 were significantly upregulated, while MKI67 showed a non-significant increasing trend. The modest cohort size means these expression findings should be read as preliminary, and the authors note that further multicenter clinical and mechanistic validation is required before any clinical translation.

The study’s conclusion is deliberately measured: MKI67, MIPEP and CCNA2 may serve as lactylation- or lactate metabolism-related biomarkers for biochemical recurrence risk stratification in prostate cancer. As a computational, database-driven analysis with limited experimental validation, it identifies candidate biomarkers rather than establishing clinical utility, and the nomogram remains exploratory until tested in independent patient populations.

Subject of Research: Prognostic genes related to lactylation and lactate metabolism in prostate cancer

Article Title: Integrated analysis of bulk RNA sequencing and single-cell RNA sequencing to identify prognostic genes related to lactylation and lactate metabolism in prostate cancer

Article References: Zhi, Y., Long, X., Zhou, Y., Shi, X., Yang, B., Yang, J., Ou, Y., Zhang, H., Wang, D., & Guo, H. (2026). Integrated analysis of bulk RNA sequencing and single-cell RNA sequencing to identify prognostic genes related to lactylation and lactate metabolism in prostate cancer. Discover Oncology. https://doi.org/10.1007/s12672-026-06001-0

Image Credits: AI Generated

DOI: 10.1007/s12672-026-06001-0

Keywords: prostate cancer, lactylation, lactate metabolism, biochemical recurrence, RNA sequencing, random survival forest, MKI67, MIPEP, CCNA2, biomarkers, nomogram, single-cell RNA sequencing