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pmid:38256104

Identification and Validation of a Prognostic Signature Derived from the Cancer Stem Cells for Oral Squamous Cell Carcinoma.

Mingxuan Shi · Ke Huang · Jiaqi Wei · Shiqi Wang · Weijia Yang · Huihui Wang · Yi Li

International journal of molecular sciences · 2024 doi:10.3390/ijms25021031

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

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title
Identification and Validation of a Prognostic Signature Derived from the Cancer Stem Cells for Oral Squamous Cell Carcinoma.
doi
10.3390/ijms25021031
pmid
38256104
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[0]
Mingxuan Shi
[1]
Ke Huang
[2]
Jiaqi Wei
[3]
Shiqi Wang
[4]
Weijia Yang
[5]
Huihui Wang
[6]
Yi Li
journal
International journal of molecular sciences
year
2024
abstract
The progression and metastasis of oral squamous cell carcinoma (OSCC) are highly influenced by cancer stem cells (CSCs) due to their unique self-renewal and plasticity. In this study, data were obtained from a single-cell RNA-sequencing dataset (GSE172577) in the GEO database, and LASSO-Cox regression analysis was performed on 1344 CSCs-related genes to establish a six-gene prognostic signature (6-GPS) consisting of ADM, POLR1D, PTGR1, RPL35A, PGK1, and P4HA1. High-risk scores were significantly associated with unfavorable survival outcomes, and these features were thoroughly validated in the ICGC. The results of nomograms, calibration plots, and ROC curves confirmed the good prognostic accuracy of 6-GPS for OSCC. Additionally, the knockdown of ADM or POLR1D genes may significantly inhibit the proliferation, migration, and invasion of OSCC cells through the JAK/HIF-1 pathway. Furthermore, cell-cycle arrest occurred in the G1 phase by suppressing Cyclin D1. In summary, 6-GPS may play a crucial role in the occurrence and development of OSCC and has the potential to be developed further as a diagnostic, therapeutic, and prognostic tool for OSCC.
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To mitigate overfitting, prognostic gene analysis was performed using the LASSO-Cox proportional hazards regression, utilizing the “survival” package [version 3.2-10] and the “glmnet” package [version 4.1-2].
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To mitigate overfitting, prognostic gene analysis was performed using the LASSO-Cox proportional hazards regression, utilizing the “survival” package [version 3.2-10] and the “glmnet” package [version 4.1-2].
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The results shown here are based on data generated by the ICGC database: https://dcc.icgc.org/releases/current/Projects (accessed on 3 November 2022), the GEO database: https://www.ncbi.nlm.nih.gov/geo (accessed on 17 October 2022) under the accession numbers GSE172577, and the HPA database: https://www.proteinatlas.org (accessed on 21 January 2023).
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The results shown here are based on data generated by the ICGC database: https://dcc.icgc.org/releases/current/Projects (accessed on 3 November 2022), the GEO database: https://www.ncbi.nlm.nih.gov/geo (accessed on 17 October 2022) under the accession numbers GSE172577, and the HPA database: https://www.proteinatlas.org (accessed on 21 January 2023).
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In this study, data were obtained from a single-cell RNA-sequencing dataset (GSE172577) in the GEO database, and LASSO-Cox regression analysis was performed on 1344 CSCs-related genes to establish a six-gene prognostic signature (6-GPS) consisting of ADM, POLR1D, PTGR1, RPL35A, PGK1, and P4HA1.
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In this study, data were obtained from a single-cell RNA-sequencing dataset (GSE172577) in the GEO database, and LASSO-Cox regression analysis was performed on 1344 CSCs-related genes to establish a six-gene prognostic signature (6-GPS) consisting of ADM, POLR1D, PTGR1, RPL35A, PGK1, and P4HA1.
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In this study, data were obtained from a single-cell RNA-sequencing dataset (GSE172577) in the GEO database, and LASSO-Cox regression analysis was performed on 1344 CSCs-related genes to establish a six-gene prognostic signature (6-GPS) consisting of ADM, POLR1D, PTGR1, RPL35A, PGK1, and P4HA1.
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Single-cell profiling of tumor-infiltrating TCF7+ T cells reveals a T lymphocyte subset associated with tertiary lymphoid structures and superior prognosis in oral cancer
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ccuracy of 6-GPS for OSCC. Additionally, the knockdown of ADM or POLR1D genes may significantly inh
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