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SPCS, a Novel Classifier System Based on Senescence Axis Regulators Reveals Tumor Microenvironment Heterogeneity and
Aimin Jiang1, Ying Liu1, Baohua Zhu1
1Department of Urology, Changhai Hospital, Naval Medical University (Second Military Medical University), Shanghai, China.
Rationale:
The emerging evidence suggested that senescence regulator genes were involved in multi cancers, which may be utilized as new targets for cancers. However, the dysregulation and clinical impact of senescence regulator genes in clear cell renal cell cancer (ccRCC) were still in foggy.
Methods:
Using multiomics data from TCGA-KIRC and other datasets, we comprehensively investigated the function of senescence regulator genes in ccRCC. ccRCC patients could be remodeled into 2 significant different groups basing on senescence regulators expression: senescence-pattern cancer subtype1 (SPCS1) and subtype2 (SPCS2). We further explored clinical characteristics, functional analysis, tumor immune microenvironment, immunotherapy response, genomic mutation and drug sensitivity between the 2 subtypes. Besides, senescence-pattern related risk model was established to determine the patient's prognosis of ccRCC. Finally, the overview of MECP2 function was investigated in multi cancers.
Results:
ccRCC patients could be divided into SPCS1 (normal aging group) and SPCS2 (Aging disorder group). The 2 subtypes showed significant different clinical characteristics and biological process in ccRCC. SPCS2, an aggressive subtype, comprised higher clinical stage and worse prognosis of ccRCC patients. SPCS2 subtype indicated activated oncogenic signaling pathway and metabolic signatures to prompt cancer expansion. SPCS2 subgroup owned immunocompromised status, which induced immune dysfunction and low ICI therapy response. The genome-copy numbers of SPCS2, including arm-gain and arm-loss was significantly more frequent than SPCS1. In addition, the 2 subtypes argue contrasting drug sensitivity profiles in clinical specimens and matched cell lines. Finally, we constructed a prognostic risk model consisted of each subtype's leading biomarkers, which exerted a satisfied performance for ccRCC patients.
Conclusion:
Senescence regulator-related signature could modify functional pathways and tumor immune microenvironment by genome mutation and pathway interaction. Senescence regulator-related molecular subtype strengthen the understanding of ccRCC' characterization and guide clinical treatment. Targeting senescence regulators may be regard as a proper way in ccRCC.
Insights
Senescence regulator genes define two clear cell renal cell carcinoma (ccRCC) subtypes with distinct clinical and immune profiles. Targeting these genes offers a potential therapeutic strategy for ccRCC.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Senescence regulator genes are implicated in various cancers, yet their role in clear cell renal cell carcinoma (ccRCC) remains unclear.
- Understanding their dysregulation is crucial for identifying novel therapeutic targets in ccRCC.
Purpose of the Study:
- To comprehensively investigate the function and clinical impact of senescence regulator genes in ccRCC.
- To classify ccRCC patients into distinct subtypes based on senescence regulator expression.
- To explore the biological, clinical, and therapeutic implications of these subtypes.
Main Methods:
- Utilized multiomics data from TCGA-KIRC and other datasets for comprehensive analysis.
- Classified ccRCC patients into two subtypes (SPCS1 and SPCS2) based on senescence regulator expression.
- Analyzed clinical characteristics, functional pathways, tumor immune microenvironment, immunotherapy response, genomic mutations, and drug sensitivity for each subtype.
- Developed a senescence-pattern related risk model for ccRCC prognosis.
Main Results:
- ccRCC patients were divided into SPCS1 (normal aging) and SPCS2 (aging disorder) subtypes with significant differences in clinical characteristics and biological processes.
- SPCS2, an aggressive subtype, exhibited higher clinical stage, worse prognosis, activated oncogenic pathways, immunocompromised status, and lower immunotherapy response.
- SPCS2 showed increased genome copy number alterations and distinct drug sensitivity profiles compared to SPCS1.
- A prognostic risk model was constructed with satisfactory performance for predicting ccRCC patient outcomes.
Conclusions:
- Senescence regulator-related signatures influence functional pathways and the tumor immune microenvironment through genomic mutations and pathway interactions.
- These molecular subtypes enhance the understanding of ccRCC characterization and can guide clinical treatment strategies.
- Targeting senescence regulators presents a promising therapeutic avenue for ccRCC.
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