Bladder urothelial carcinoma (BLCA) presents a persistent challenge in clinical management. Despite recent advancements demonstrating the BLCA efficacy of immune checkpoint inhibitors (ICI)

in BLCA patients, there remains a critical need to identify and expand the subset of individuals who benefit from this treatment. Mitochondria, as pivotal regulators of various cell death

pathways in eukaryotic cells, exert significant influence over tumor cell fate and survival. In this study, our objective was to investigate biomarkers centered around mitochondrial function

and cell death mechanisms to facilitate prognostic prediction and guide therapeutic decision-making in BLCA. Utilizing ssGSEA and LASSO regression, we developed a prognostic signature

assays, RT-qPCR, and immunohistochemistry to validate the differential expression of genes comprising the mtPCD signature. The mtPCD signature comprises a panel of 10 highly influential

genes, strongly correlated with survival outcomes in BLCA patients and exhibiting robust predictive capabilities. Importantly, individuals classified as high-risk according to mtPCD score

displayed a subdued overall immune response, characterized by diminished immunotherapeutic efficacy. In summary, our findings highlight the development of a novel prognostic signature, which

not only holds promise as a biomarker for BLCA prognosis but also offers insights into the immune landscape of BLCA. This paradigm may pave the way for personalized treatment strategies in

BLCA management.

BLCA is responsible for more than 573,000 new cases and approximately 213,000 deaths in 2020, ranking it as the tenth most common cancer and represents a significant cause of morbidity and

mortality1. Programmed cell death (PCD) is a vital biological process that plays an important role in maintaining tissue homeostasis, development, and immunity. This tightly regulated

mechanism allows multicellular organisms to eliminate unwanted or damaged cells in a controlled manner, ensuring proper growth and function. PCD can be divided into apoptotic cell death and

non-apoptotic cell death based on morphological characteristics and molecular mechanisms. The former maintains cell membrane integrity and occurs in a caspase dependent manner, while the

latter experiences cell membrane rupture and is caspase independent2. Classic examples of apoptotic cell death include apoptosis and anoikis, while emerging research has unveiled various

non-apoptotic cell death modalities, enriching our understanding of cellular demise mechanisms3.

The mitochondria, as the central hub of cellular metabolism, undergo structural and functional changes closely associated with cellular fate4. Mitochondrial outer membrane permeabilization

(MOMP) is a critical event in apoptosis initiation5,6. Even in instances of mitochondrial dysfunction, inhibition of caspase activity in the presence of MOMP can still lead to non-apoptotic

cell death, highlighting the paramount importance of OMM integrity as the primary determinant of cellular fate7. Mitochondria also play a crucial role in some newly discovered forms of

non-apoptotic PCD. Necroptosis is a form of PCD with the same morphological features as necrosis. It has been shown that progressive mitochondrial dysfunction may predispose cells to

necroptosis8. Ferroptosis, characterized by iron-dependent lipid peroxidation, represents a novel mode of PCD. Given the pivotal role of mitochondria in iron utilization, catalysis, anabolic

pathways, and iron homeostasis regulation, they stand at the forefront of ferroptosis regulation9. Similarly, cuproptosis, a copper-dependent form of cell death, is driven by mitochondrial

stress and injury10. In essence, mitochondrial function intricately intertwines with the mechanisms of PCD, forming an inseparable entity.

It is widely acknowledged that tumor cells possess the capability to evade PCD, primarily through the suppression of the immune clearance mechanism. Consequently, reversing the

immunosuppressive state within the body emerges as pivotal in facilitating PCD of tumor cells, thus constituting a crucial direction in tumor immunotherapy research11. In recent years, the

advent of ICI grounded on this premise has heralded a significant breakthrough in BLCA treatment, eliciting the anticancer potential of T cells by obstructing the interaction between

programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte antigen 4 (CTLA-4) with their cognate ligands12. Presently, pembrolizumab and atezolizumab have garnered approval from the

US Food and Drug Administration (FDA) for first-line therapy in advanced BLCA patients ineligible for platinum-based chemotherapy13. Nonetheless, delineating the target beneficiary cohort

remains a formidable challenge14. Intriguingly, PCD assumes a pivotal role in shaping ICI immunotherapy efficacy. Studies have observed that CD8 T cells can inhibit tumor cells by inducing

ferroptosis and pyroptosis, while concurrently modulating T cell functionality through ferroptosis, thus exerting a pivotal impact on tumor immunotherapy15. Consequently, investigations

probing this intricate interplay promise to deepen insights into the underlying oncogenic mechanisms of BLCA and offer novel avenues for refining BLCA immunotherapeutic strategies.

In this study, we defined a new concept, mitochondrial function and cell death (mtPCD), and developed a prognostic signature associated with mtPCD to predict the prognosis of BLCA patients.

Notably, we verified that the mtPCD signature could improve the accuracy of BLCA prognosis prediction. In addition, we performed functional analysis, tumor immune microenvironment (TIME) and

immunotherapy response analysis, drug sensitivity analysis, and single-cell analysis to more fully understand the significance of the mtPCD score. Ultimately, our findings may point to new

directions for the diagnosis and treatment of BLCA.

To explore the relationship between mtPCD and BLCA, we performed ssGSEA to assess the enrichment scores of the mtPCD gene set in TCGA samples and divided the cohort into mtPCD high and low

subgroups (Supplementary Table S1). According to the Kaplan–Meier curve, patients in the high subgroup had a significantly reduced survival time (P  1 and adj.P