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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2019, Vol. 13 Issue (1) : 24-31    https://doi.org/10.1007/s11684-019-0679-7
REVIEW |
Screening responsive or resistant biomarkers of immune checkpoint inhibitors based on online databases
Zhen Xiang, Yingyan Yu()
Department of Surgery, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine; Shanghai Key Laboratory of Gastric Neoplasms, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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Abstract

Immune checkpoint inhibitors are a promising strategy in the treatment of cancer, especially advanced types. However, not all patients are responsive to immune checkpoint inhibitors. The response rate depends on the immune microenvironment, tumor mutational burden (TMB), expression level of immune checkpoint proteins, and molecular subtypes of cancers. Along with the Cancer Genome Project, various open access databases, including The Cancer Genome Atlas and Gene Expression Omnibus, provide large volumes of data, which allow researchers to explore responsive or resistant biomarkers of immune checkpoint inhibitors. In this review, we introduced some methodologies on database selection, biomarker screening, current progress of immune checkpoint blockade in solid tumor treatment, possible mechanisms of drug resistance, strategies of overcoming resistance, and indications for immune checkpoint inhibitor therapy.

Keywords immune checkpoint blockade      sensitivity      resistance      data mining     
Corresponding Authors: Yingyan Yu   
Just Accepted Date: 28 December 2018   Online First Date: 18 January 2019    Issue Date: 12 March 2019
 Cite this article:   
Zhen Xiang,Yingyan Yu. Screening responsive or resistant biomarkers of immune checkpoint inhibitors based on online databases[J]. Front. Med., 2019, 13(1): 24-31.
 URL:  
http://academic.hep.com.cn/fmd/EN/10.1007/s11684-019-0679-7
http://academic.hep.com.cn/fmd/EN/Y2019/V13/I1/24
Fig.1  Immune checkpoint inhibitors approved by the FDA. From left to right, the six immune checkpoint inhibitors are listed. Ipilimumab targets CTLA-4. Pembrolizumab and nivolumab target PD-1. Atezolizumab, avelumab, and durvalumab target PD-L1. The drugs are presented according to the chronological order of FDA approval.
Drug name Trade name Target Structure Company Indications
Ipilimumab Yervoy CTLA-4 IgG1 Bristol-Myers Squibb Unresectable or metastatic melanoma (first or second line)
Stage III cutaneous melanoma (adjuvant therapy, first line)
Pembrolizumab Keytruda PD-1 IgG4 Bristol-Myers Squibb Unresectable or metastatic melanoma (first line)
Metastatic non-small cell lung cancer (TPS*≥1%, second line; TPS≥50%, first line)
Recurrent or metastatic head and neck squamous cell carcinoma (second line)
Refractory classical Hodgkin lymphoma (second or more lines)
Metastatic nonsquamous non-small cell lung cancer (plus pemetrexed and carboplatin, first line)
Locally advanced or metastatic urothelial carcinoma (second line)
Unresectable or metastatic solid tumor with high MSI (second line). Advanced gastric cancer (second line)
Nivolumab Opdivo PD-1 IgG4 MSD Unresectable or metastatic melanoma (alone or with ipilimumab, second line)
Metastatic squamous non-small cell lung cancer (second line or third line)
Renal cell carcinoma (second line)
Classical Hodgkin lymphoma (second line)
Adult classical Hodgkin lymphoma (second or more lines)
Recurrent or metastatic squamous cell carcinoma of the head and neck (second line)
Locally advanced or metastatic urothelial carcinoma (second line)
Unresectable or metastatic solid tumor with high MSI (second line). Hepatocellular carcinoma (second or more lines)
Atezolizumab Tecentriq PD-L1 IgG1 Roche Locally advanced or metastatic urothelial carcinoma (second line)
Metastatic non-small cell lung cancer (second line)
Avelumab Bavencio PD-L1 IgG1 Pfizer/MERCK Adult and pediatric metastatic Merkel cell carcinoma in patients (second line)
Locally advanced or metastatic urothelial carcinoma (second line)
Durvalumab Imfinzi PD-L1 IgG1 AstraZeneca Locally advanced or metastatic urothelial carcinoma (second line)
Unresectable stage III non-small cell lung cancer (second line)
Tab.1  Immune checkpoint inhibitors approved by the FDA (https://www.fda.gov/default.htm)
Fig.2  Analytical flowchart of data mining for transcriptomic data from GEO and TCGA databases. All data are processed by different packages of R software. Step 1: Affy package (rma method); step 2: Sva package; step 3: survival package; step 4: Limma package; step 5: edgeR package; step 6: GSEA software; step 7: WGCNA package; step 8: ConsensusClusterPlus package; step 9: pheatmap package; step 10: ClusterProfiler package; step 11: Rbsurv package (model with minimal AIC); step 12: Cytoscape software; step 13: glmnet package (Lasso regression). GEO: gene expression omnibus; GSEA: Gene Set Enrichment Analysis; WGCNA: weighted gene co-expression network analysis; GO: Gene Ontology; DEGs: differentially expressed genes.
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