Different lactate metabolism subtypes reveal heterogeneity in clinical outcomes and immunotherapy in lung adenocarcinoma patients.

Background: The excessive accumulation of lactate within the tumor microenvironment (TME) has been demonstrated to facilitate tumor advancement and evade the immune system. Nonetheless, the metabolic status of lactate in lung adenocarcinoma (LUAD) remains uncertain. Method: By analyzing the transcriptome profile of patients with LUAD, we created a lactate metabolism score (LMS) to predict survival. We then conducted a comprehensive examination of the biological functions and immune infiltration among different LMS patient groups. Moreover, we assessed the LMS predictive efficacy in chemotherapy and immunotherapy. Finally, we validated the detrimental phenotypic effects of SLC16A3 on LUAD cell lines (PC9 and A549) through in vitro experiments. We collected clinical samples to assess the prognostic impact of SLC16A3. Results: We constructed an LMS model with 6 lactate metabolism regulatory factors using LASSO regression. The high LMS model indicates worse clinical outcomes for LUAD patients. High LMS patients are associated with metabolic dysregulation and increased infiltration of M0 and M1 macrophages. Low LMS patients are related to upregulated citric acid metabolism pathways and memory immune cells. High LMS patients are suitable for traditional chemotherapy, while patients with low LMS are more likely to benefit from immunotherapy. Lastly, downregulating SLC16A3 significantly reduces the proliferative and invasive capabilities of LUAD cell lines. Clinical cohort shows that patients with high expression of SLC16A3 have a worse prognosis. Conclusions: The LMS model constructed based on the lactate metabolism pathway displays high effectiveness in predicting the outcome of patients with LUAD. LMS can offer direction regarding chemotherapy as well as immunotherapy in LUAD.