| Literature DB >> 34187157 |
Peng Wang1, Chuanhao Tang2, Jun Liang1.
Abstract
Immune checkpoint inhibitors (ICI) have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). Biomarkers are essential for guiding precision immunotherapy. Tissue-based programmed death ligand 1 (PD-L1) expression and tumor mutational burden (TMB) are currently widely used biomarkers for selecting patients for immunotherapy. However, tissue specimens are often difficult to reach and couldn't overcome spatial and temporal heterogeneity. Blood biomarkers offer an alternative non-invasive solution that could provide a complete insight on patient's immune status and tumor as well, and show their potential in predicting the outcome as well as in monitoring response to immunotherapy. In this article, we summarize current knowledge on blood biomarkers in NSCLC patients treated with ICI, and we hope to provide more references for development of novel biomarkers. .Entities:
Keywords: Blood biomarkers; Immmune Checkpoint Inhibitors; Immunotherapy; Lung neoplasms
Mesh:
Substances:
Year: 2021 PMID: 34187157 PMCID: PMC8317092 DOI: 10.3779/j.issn.1009-3419.2021.102.24
Source DB: PubMed Journal: Zhongguo Fei Ai Za Zhi ISSN: 1009-3419
检测ctDNA和bTMB的不同研究的比较
Comparison of the different studies testing ctDNA and bTMB
| Author, Year | Design | Population | Treatment | Method(s)/panel | Main findings/Threshold |
| R/P: retrospective/prospective design; NSCLC: non-small cell lung cancer; UM: uveal melanoma; MSI: microsatellite instability; CRC: colorectal cancer; ddPCR: droplet-digital polymerase chain reaction; bi-PAP: bidirectional pyrophosphorolysis activated polymerization; NGS: next generation sequencing; PFS: progression free survival; OS: overall survival; ICI: immune checkpoint inhibitor; CTx: chemotherapy; AF: allele fraction; qPCR: quantitative polymerase chain reaction; TTP: time to progression; TEC-Seq: targeted error corrected sequencing; VAF: variant allele fraction; bTMB: blood tumor mutational burden; CAPP-Seq: cancer personalized profiling by deep sequencing; DCB: durable clinical benefits; ctDNA: circulating tumor DNA; bTMB: blood tumor mutational burden. | |||||
| Cabel, 2017[ | NSCLC ( | Nivolumab | ddPCR, bi-PAP, NGS monogene, 39 genes panel | ctDNA levels undetectable at 8 weeks associated with longer PFS and OS | |
| Goldberg, 2018[ | P | Metastatic NSCLC ( | ICI, not further specified, CTx | NGS 24 genes panel | ctDNA diminution associated with prolonged survival; threshold ctDNA response as a > 50% decrease in AF from baseline |
| Giroux, 2018[ | P | Stage Ⅲb/Ⅳ NSCLC ( | Nivolumab | NGS 22 genes panel | 9% increase of ctDNA at first tumor evaluation correlated with absence of clinical benefit, shorter PFS and poorer OS |
| Passiglia, 2019[ | R | Stage Ⅳ NSCLC ( | Nivolumab | qPCR unknow | cfDNA increase > 20% at 6 weeks associated with worse OS and shorter TTP |
| Guibert, 2019[ | R | Stage Ⅲb/Ⅳ, progressive NSCLC ( | ICI | NGS 36 genes panel | Early changes (increase |
| Anagnostou, 2019[ | R | Metastatic NSCLC ( | ICI | TEC-Seq NGS 58 genes panel | Reduction in ctDNA to undetectable levels was associated with longer PFS and OS |
| Stage Ⅰ-Ⅲ NSCLC ( | Neo-adjuvant nivolumab | Reduction in ctDNA to undetectable levels was associated with major or partial pathological response | |||
| Zhang, 2020[ | R | Advanced lung cancer ( | Durvalumab±tremelimumab | NGS 73 genes panel | Pretreatment VAF was inverse correlated with OS; ctDNA increased during treatment was correlated with poor OS |
| Gandara, 2018[ | R | Advanced NSCLC: OAK ( | Atezolizumab | F1CDx 324 genes | bTMB is positively associated with PFS threshold 16 Mu |
| MYSTIC, 2020[ | R | Metastatic NSCLC: MYSTIC ( | Durvalumab+ tremelimumab | GuardantOMNI 500 genes | bTMB is positively associated superior ORR, PFS and OS; threshold 20 Mu |
| Wang, 2019[ | R | Advanced NSCLC (Line 1: | ICI, non-specified | NCC-GP150 150 genes | bTMB is positively associated with superior ORR and PFS; threshold 6 Mu |
| Nabet, 2020[ | R | Advanced NSCLC ( | ICI | CAPP-Seq 270 genes | High blood based TMB, ctDNA decreased after one infusion, low CD8 are associated with good DCB; threshold 14 Mu |
外周血免疫细胞与非小细胞肺癌免疫治疗反应的关系
Levels of peripheral immune cells correlated with immunotherapy response in NSCLC
| Cell type | Biomarkers | Clinical benefit | Reference |
| ALC: absolute lymphocyte count; ANC: absolute neutrophil count; AEC: absolute eosinophil count, NLR: neutrophil-to-lymphocyte ratio; dNLR: derive neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; PD-1: programmed death-1; TIM-3: T-cell immunoglobulin mucin 3; PR: partial response; SD: stable disease; cm/Eff: central memory/effector memory; TCR: T cell receptor; ICOS: inducible co-stimulator; M-MDSC: monocytic-myeloid-derived suppressor cell; Gr-MDSCs/PMN-MDSCs: granulocytic/polymorphonucear-myeloid-derived suppressor cells. | |||
| Blood routine examination | Baseline ANC < 7, 500/μL, ALC≥1, 000/μL, AEC≥150/μL, NLR < 5 | OS, PFS | [ |
| Cells | Baseline NLR < 6.4, PLR < 441.8, dNLR≤3 | OS | [ |
| Post-treatment NLR < 5 at week 6 | OS, PFS | [ | |
| CD8+ T cells | High baseline expression of immune checkpoints (PD-1) | OS, PFS | [ |
| Low baseline expression of PD-1 | |||
| Decreased expression of PD-1 after treatment | OS, PFS | [ | |
| Without increased expression of immune checkpoints (TIM-3+) after treatment | PFS | [ | |
| High proliferation of PD-1+CD8+ T cells after anti-PD-1 therapy | PR/SD, DCB, PFS | [ | |
| High baseline TCR diversity in PD-1+CD8+ T cells | PFS | [ | |
| Increased TCR diversity in T cells(including CD8+ T)at 2 weeks after treatment | OS | [ | |
| Low baseline frequency of CD28-CD57+KLRG1+ | OS | [ | |
| Expression of CD28 and ICOS after anti-PD-1 therapy | PR/SD | [ | |
| Lack CD28, ICOS and CD40L | PR/SD | [ | |
| Higher baseline memory CD8+ T cells (CM/Eff T cell ratio) | PFS | [ | |
| CD4+ T cells | High baseline expression of immune checkpoints (PD-1) | PFS | [ |
| Higher baseline frequency of functional CD27-CD28-CD4+ T cells | PFS | [ | |
| High frequencies of Treg cells one week after anti-PD-1 therapy | OS, PFS | [ | |
| NK cells | Higher frequency and overall activity of NK cells | PR, SD | [ |
| High baseline number of NK cells | OS, PFS | [ | |
| Low baseline number of NK cells | OS, PFS | [ | |
| MDSCs | Low baseline frequency of PMN-MDSCs and M-MDSCs | OS, PFS | [ |
| Low numbers of M-MDSC 2 weeks after nivolumab therapy | OS | [ | |
| High baseline levels of Gr-MDSC | OS, PFS | [ | |
| Combination cells | Higher baseline (%CD62LlowCD4+ T cells)2/(%Treg cells) ratio PFS and OS | OS, PFS | [ |
| Higher (%Treg cells)/(%LOX-1+ PMN-MDSCs) ratio after the first nivolumab infusion | PFS | [ | |
| (%NK cells)/(%Lox1+ PMN-MDSC) ratio≥5.75)after the first cycle of anti-PD-1 therapy | ORR, OS, PFS | [ | |
免疫检查点抑制剂治疗相关外周血标志物的优缺点
Advantages and limitations of the main blood biomarkers under investigation in the area of immune checkpoint inhibitors-based therapy
| Item | Composition | Advantages | Disadvantages | Level of evidence |
| WES: whole exon sequencing; CTCs: circulating tumor cells. | ||||
| ctDNA levels | Nucleic acid | Highly specific and sensitive, real time quantitative analysis enable dynamic evaluation of tumor at a precise moment, covering spatial and temporal tumor heterogeneity | Lack of standardization of pre-analytical and detection methods, time-consuming | Prospective study |
| bTMB | Nucleic acid | Standardized detection technology: WES is the gold standard while NGS can serve as a sufficiently fast candidate tests, covering spatial and temporal tumor heterogeneity | Lack of standardization of pre-analytical methods. WES: long and very expensive, NGS: optimal gene panel size, algorithm and a consensual cut-off defining high TMB are still to be determined, expensive | Prospective study |
| CTC | Living cells | Specific, single-cell analysis. CellSearch: standardized, semiautomated, covering spatial and temporal tumor heterogeneity | Very rare, hard to keep, variability of technologies, expensive | Retrospective study |
| Exosomes | Nucleic acid, protein | Widely distributed and good stability, unique surface protein and genetic material originated from their parental cells, covering spatial and temporal tumor heterogeneity | Technology for exosomal isolation and tests is not broadly available | Retrospective study |
| Circulating immune cells | Immune cell subpopulations | Reflecting the host's immune status, Simultaneous detection of multiple subpopulations | Lack of standardized methodological approaches, complex classification, highly dynamic and the optimal target and detecting timing are still to be determined, long technical and analysis time | Retrospective study |