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A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies
Published on: April 12, 2017
NECSO-based classification predicts immunotherapy efficacy and identifies FLAD1 as therapeutic target in kidney renal
Yitong Pan1,2, Rui Wu3, Xueyi Zhu4
1Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China.
Background:
A new type of regulated cell death known as Necrosis by Sodium Overload (NECSO) has been discovered recently. There is growing evidence indicating that NECSO is essential in both anti-tumor immune responses and the proliferation of cancer cells. Nonetheless, the underlying mechanisms and clinical relevance of NECSO are still not well understood, especially regarding its prognostic significance in kidney renal clear cell carcinoma (KIRC).
Methods:
We utilized Non-negative Matrix Factorization (NMF) to distinguish unique NECSO patterns derived from NECSO-associated genes within the TCGA dataset, which led to the identification of three distinct subgroups. Furthermore, we created an innovative NECSO score (NECSOS) utilizing machine learning techniques and confirmed its clinical relevance through validation in several independent datasets, which comprised one transcriptomic cohort of immune checkpoint inhibitor (ICI)-treated KIRC patients, three pan-cancer ICI-treated cohorts, two single-cell RNA sequencing datasets of KIRC patients, and one single-cell dataset from patients treated with PD-1 inhibitors. To characterize FLAD1, we performed gain- and loss-of-function assays for proliferation, migration, and invasion, sodium overload (NC1) sensitivity assays, subcutaneous xenograft models, and CD8+ T cell co-culture cytokine profiling.
Results:
The genetic landscape and immune microenvironment of these subgroups were thoroughly characterized, uncovering important insights into the heterogeneity of the tumor microenvironment (TME) and its response to immunotherapy. The NECSO model we developed exhibited strong predictive accuracy for prognosis and immunotherapy responses in patients with KIRC, with validation conducted in diverse pan-cancer ICI cohorts. FLAD1 was identified as a novel prognostic biomarker, and its oncogenic roles in proliferation, migration, and invasion were experimentally confirmed. Mechanistically, FLAD1 regulated cellular sensitivity to TRPM4-mediated sodium overload, promoted tumor growth in vivo, and modulated the secretion of T cell-recruiting chemokines and pro-inflammatory cytokines, positioning it as a mechanistic driver within the NECSO-immunity axis rather than merely a prognostic marker.
Discussion:
This study has established a robust NECSO-based classification system and prognostic model for KIRC while identifying FLAD1 as a novel biomarker and functional driver of the necrosis-immunity axis. These integrated approaches provide clinically actionable tools for predicting patient outcomes and immunotherapy efficacy.
Insights
Necrosis by Sodium Overload (NECSO) plays a role in kidney cancer immunity and growth. This study developed a NECSO score for prognosis and immunotherapy response prediction in kidney renal clear cell carcinoma (KIRC).
Area of Science:
- Oncology
- Immunology
- Cell Death Research
Background:
- Necrosis by Sodium Overload (NECSO) is a newly identified regulated cell death pathway.
- Emerging evidence suggests NECSO's involvement in anti-tumor immunity and cancer cell proliferation.
- The precise mechanisms and clinical significance of NECSO, particularly its prognostic value in kidney renal clear cell carcinoma (KIRC), remain under-investigated.
Purpose of the Study:
- To investigate the role and prognostic significance of NECSO in KIRC.
- To develop a predictive model for patient prognosis and immunotherapy response based on NECSO.
- To identify novel biomarkers associated with NECSO and its impact on the tumor microenvironment.
Main Methods:
- Non-negative Matrix Factorization (NMF) was used to classify KIRC patients into distinct NECSO subgroups.
- A machine learning-based NECSO score (NECSOS) was developed and validated across multiple independent KIRC and pan-cancer cohorts, including single-cell and ICI-treated datasets.
- Functional assays, including gain/loss-of-function studies and cytokine profiling, were performed to characterize the role of FLAD1.
Main Results:
- Three distinct NECSO-associated subgroups were identified, revealing heterogeneity in the tumor microenvironment and immunotherapy response.
- The developed NECSO model demonstrated high accuracy in predicting prognosis and response to immunotherapy in KIRC and pan-cancer settings.
- FLAD1 was identified as a novel prognostic biomarker, promoting KIRC cell proliferation, migration, and invasion, and modulating the immune microenvironment by influencing T cell-recruiting chemokines and cytokines.
Conclusions:
- A robust NECSO-based classification and prognostic model for KIRC has been established.
- FLAD1 is validated as a prognostic biomarker and a functional driver of the necrosis-immunity axis in KIRC.
- These findings offer clinically actionable tools for predicting KIRC patient outcomes and optimizing immunotherapy strategies.
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