1
|
Shao J, Xu Y, Olsen RJ, Kasparian S, Sun K, Mathur S, Zhang J, He C, Chen SH, Bernicker EH, Li Z. 5-Hydroxymethylcytosine in Cell-Free DNA Predicts Immunotherapy Response in Lung Cancer. Cells 2024; 13:715. [PMID: 38667328 PMCID: PMC11049556 DOI: 10.3390/cells13080715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 04/04/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed a 5hmC signature that was significantly associated with progression-free survival (PFS). We built a 5hmC predictive model to quantify the 5hmC level and validated the model in the validation, test, and control sets. Low weighted predictive scores (wp-scores) were significantly associated with a longer PFS compared to high wp-scores in the validation [median 7.6 versus 1.8 months; p = 0.0012; hazard ratio (HR) 0.12; 95% confidence interval (CI), 0.03-0.54] and test (median 14.9 versus 3.3 months; p = 0.00074; HR 0.10; 95% CI, 0.02-0.50) sets. Objective response rates in patients with a low or high wp-score were 75.0% (95% CI, 42.8-94.5%) versus 0.0% (95% CI, 0.0-60.2%) in the validation set (p = 0.019) and 80.0% (95% CI, 44.4-97.5%) versus 0.0% (95% CI, 0.0-36.9%) in the test set (p = 0.0011). The wp-scores were also significantly associated with PFS in patients receiving single-agent ICI treatment (p < 0.05). In addition, the 5hmC predictive signature demonstrated superior predictive capability to tumor programmed death-ligand 1 and specificity to ICI treatment response prediction. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. This study provides proof-of-concept evidence that the cfDNA 5hmC signature is a robust biomarker for predicting ICI treatment response in lung cancer.
Collapse
Affiliation(s)
- Jianming Shao
- Department of Pathology and Genomic Medicine, Houston Methodist Hospital, Houston, TX 77030, USA (R.J.O.)
- Houston Methodist Research Institute, Houston, TX 77030, USA (S.M.); (S.-H.C.)
| | - Yitian Xu
- Houston Methodist Research Institute, Houston, TX 77030, USA (S.M.); (S.-H.C.)
| | - Randall J. Olsen
- Department of Pathology and Genomic Medicine, Houston Methodist Hospital, Houston, TX 77030, USA (R.J.O.)
- Houston Methodist Research Institute, Houston, TX 77030, USA (S.M.); (S.-H.C.)
- Weill Cornell Medical College, New York, NY 10065, USA
| | - Saro Kasparian
- Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA (E.H.B.)
- Department of Medical Oncology, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA
| | - Kai Sun
- Weill Cornell Medical College, New York, NY 10065, USA
- Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA (E.H.B.)
| | - Sunil Mathur
- Houston Methodist Research Institute, Houston, TX 77030, USA (S.M.); (S.-H.C.)
- Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA (E.H.B.)
| | - Jun Zhang
- Weill Cornell Medical College, New York, NY 10065, USA
- Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA (E.H.B.)
| | - Chuan He
- Department of Chemistry, Department of Biochemistry and Molecular Biology, Institute for Biophysical Dynamics, The University of Chicago, Chicago, IL 60637, USA
- Howard Hughes Medical Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Shu-Hsia Chen
- Houston Methodist Research Institute, Houston, TX 77030, USA (S.M.); (S.-H.C.)
- Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA (E.H.B.)
| | - Eric H. Bernicker
- Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA (E.H.B.)
| | - Zejuan Li
- Department of Pathology and Genomic Medicine, Houston Methodist Hospital, Houston, TX 77030, USA (R.J.O.)
- Houston Methodist Research Institute, Houston, TX 77030, USA (S.M.); (S.-H.C.)
- Weill Cornell Medical College, New York, NY 10065, USA
| |
Collapse
|
2
|
Li JD, Chen Y, Jing SW, Wang LT, Zhou YH, Liu ZS, Song C, Li DZ, Wang HQ, Huang ZG, Dang YW, Chen G, Luo JY. Triosephosphate isomerase 1 may be a risk predictor in laryngeal squamous cell carcinoma: a multi-centered study integrating bulk RNA, single-cell RNA, and protein immunohistochemistry. Eur J Med Res 2023; 28:591. [PMID: 38102653 PMCID: PMC10724924 DOI: 10.1186/s40001-023-01568-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 12/06/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Although great progress has been made in anti-cancer therapy, the prognosis of laryngeal squamous cell carcinoma (LSCC) patients remains unsatisfied. Quantities of studies demonstrate that glycolytic reprograming is essential for the progression of cancers, where triosephosphate isomerase 1 (TPI1) serves as a catalytic enzyme. However, the clinicopathological significance and potential biological functions of TPI1 underlying LSCC remains obscure. METHODS We collected in-house 82 LSCC tissue specimens and 56 non-tumor tissue specimens. Tissue microarrays (TMA) and immunohistochemical (IHC) experiments were performed. External LSCC microarrays and bulk RNA sequencing data were integrated to evaluate the expression of TPI1. We used a log-rank test and the CIBERSORT algorithm to assess the prognostic value of TPI1 and its association with the LSCC microenvironment. Malignant laryngeal epithelial cells and immune-stromal cells were identified using inferCNV and CellTypist. We conducted a comprehensive analysis to elucidate the molecular functions of TPI1 in LSCC tissue and single cells using Pearson correlation analysis, high dimensional weighted gene co-expression analysis, gene set enrichment analysis, and clustered regularly interspaced short palindromic repeats (CRISPR) screen. We explored intercellular communication patterns between LSCC single cells and immune-stromal cells and predicted several therapeutic agents targeting TPI1. RESULTS Based on the in-house TMA and IHC analysis, TPI1 protein was found to have a strong positive expression in the nucleus of LSCC cells but only weakly positive activity in the cytoplasm of normal laryngeal cells (p < 0.0001). Further confirmation of elevated TPI1 mRNA expression was obtained from external datasets, comparing 251 LSCC tissue samples to 136 non-LSCC tissue samples (standardized mean difference = 1.06). The upregulated TPI1 mRNA demonstrated a high discriminative ability between LSCC and non-LSCC tissue (area under the curve = 0.91; sensitivity = 0.87; specificity = 0.79), suggesting its potential as a predictive marker for poor prognosis (p = 0.037). Lower infiltration abundance was found for plasma cells, naïve B cells, monocytes, and neutrophils in TPI-high expression LSCC tissue. Glycolysis and cell cycle were significantly enriched pathways for both LSCC tissue and single cells, where heat shock protein family B member 1, TPI1, and enolase 1 occupied a central position. Four outgoing communication patterns and two incoming communication patterns were identified from the intercellular communication networks. TPI1 was predicted as an oncogene in LSCC, with CRISPR scores less than -1 across 71.43% of the LSCC cell lines. TPI1 was positively correlated with the half maximal inhibitory concentration of gemcitabine and cladribine. CONCLUSIONS TPI1 is dramatically overexpressed in LSCC than in normal tissue, and the high expression of TPI1 may promote LSCC deterioration through its metabolic and non-metabolic functions. This study contributes to advancing our knowledge of LSCC pathogenesis and may have implications for the development of targeted therapies in the future.
Collapse
Affiliation(s)
- Jian-Di Li
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Yi Chen
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Shu-Wen Jing
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Li-Ting Wang
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Yu-Hong Zhou
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Zhi-Su Liu
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Chang Song
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Da-Zhi Li
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Hai-Quan Wang
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Zhi-Guang Huang
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
- Guangxi Zhuang Autonomous Region Engineering Research Center for Artificial Intelligence Analysis of Multimodal Tumor Images, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Yi-Wu Dang
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
- Guangxi Zhuang Autonomous Region Engineering Research Center for Artificial Intelligence Analysis of Multimodal Tumor Images, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Gang Chen
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
- Guangxi Zhuang Autonomous Region Engineering Research Center for Artificial Intelligence Analysis of Multimodal Tumor Images, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China
| | - Jia-Yuan Luo
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China.
- Guangxi Zhuang Autonomous Region Engineering Research Center for Artificial Intelligence Analysis of Multimodal Tumor Images, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Shuangyong Road 6, Nanning, 530021, People's Republic of China.
| |
Collapse
|
3
|
Zhang X, Mi ZH. Identification of potential diagnostic and prognostic biomarkers for breast cancer based on gene expression omnibus. World J Clin Cases 2023; 11:6344-6362. [PMID: 37900246 PMCID: PMC10600985 DOI: 10.12998/wjcc.v11.i27.6344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 08/18/2023] [Accepted: 08/31/2023] [Indexed: 09/20/2023] Open
Abstract
BACKGROUND Breast cancer is regarded as a highly malignant neoplasm in the female population, posing a significant risk to women's overall well-being. The prevalence of breast cancer has been observed to rise in China, accompanied by an earlier age of onset when compared to Western countries. Breast cancer continues to be a prominent contributor to cancer-related mortality and morbidity among women, primarily due to its limited responsiveness to conventional treatment modalities. The diagnostic process is challenging due to the presence of non-specific clinical manifestations and the suboptimal precision of conventional diagnostic tests. There is a prevailing uncertainty regarding the most effective screening method and target populations, as well as the specificities and execution of screening programs. AIM To identify diagnostic and prognostic biomarkers for breast cancer. METHODS Overlapping differentially expressed genes were screened based on Gene Expression Omnibus (GSE36765, GSE10810, and GSE20086) and The Cancer Genome Atlas datasets. A protein-protein interaction network was applied to excavate the hub genes among these differentially expressed genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, as well as gene set enrichment analyses, were conducted to examine the functions of these genes and their potential mechanisms in the development of breast cancer. For clarification of the diagnostic and prognostic roles of these genes, Kaplan-Meier and Cox proportional hazards analyses were conducted. RESULTS This study demonstrated that calreticulin, heat shock protein family B member 1, insulin-like growth Factor 1, interleukin-1 receptor 1, Krüppel-like factor 4, suppressor of cytokine signaling 3, and triosephosphate isomerase 1 are potential diagnostic biomarkers of breast cancer as well as potential treatment targets with clinical implications. CONCLUSION The screening of biomarkers is of guiding significance for the diagnosis and prognosis of the diseases.
Collapse
Affiliation(s)
- Xiong Zhang
- Department of Pathology, HuLunBuir Peoples’s Hospital, HuLunBuir 010018, Nei Monggol Autonomous Region, China
| | - Zhi-Hui Mi
- Department of Research and Marketing, Inner Mongolia Di An Feng Xin Medical Technology Co., LTD, Huhhot 010010, Nei Monggol Autonomous Region, China
| |
Collapse
|