Article Figures & Data
Figures
- Figure 1
The flow chart of patient selection, PD-L1 expression, and bioinformatics analysis. (A) The flow charts and treatment flow chart. We selected 24 cases in this retrospective analysis. The treatment strategy included mono anti-PD-1 therapy (n = 3), anti-PD-1 + apatinib combined therapy (n = 20), and anti-PD-1 + radiotherapy (n = 1). The PD-L1 detective flow chart: among 24 patients, only 13 patients received PD-L1 expression testing. The positive ratio was 23% (3/13). The gene mutation flow chart: the large mutation landscape was composed of the panel detection data of 20 cases and whole exome sequencing (WES) data of 8 cases. We also used bioinformatics analyses, such as some biomarkers, using WES data. The transcriptome analysis flow chart: we had accompanied studies using transcriptome data of 7 cases, including key signal pathways and the immune microenvironment. (B) Specific information of patients in biomarker exploring. Before treatment, there were 8 patients with whole exon sequencing, 7 patients with RNA sequencing, and 8 patients with panel sequencing data.
- Figure 2
Efficacy of treatment based on PD-1 inhibitors in patients with sarcomas. (A) Maximum changes in target lesions in patients with stage IV sarcomas who were treated with PD-1 inhibitor-based therapy. A total of 14 patients (77.8%, 14/18) responded to the treatment, no patients achieved complete remission, 4 patients (22.2%, 4/18) achieved partial remission, 10 patients (55.6%, 10/18) achieved stable disease, and 4 patients (22.2%, 4/18) suffered from PD. Up to 77.8% (14/18) of patients had responses to anti-PD-1-based treatments. (B) Changes of the target lesions in 18 patients with measurable lesions. Red lines: target lesions increased ≥20% from baseline; purple lines: target lesions initially increased ≤ 20% and shrank by 0%–40%; green lines: target lesion changes shrank by 5%–30%; and blue lines: target lesions shrank ≥ 30%. (C) Overall responses of 24 patients with stage IV sarcomas. The patients received a treatment of mono PD-1 inhibitor with or without apatinib. By the end of the observation period, 6 patients died from progressive disease. (D, E) The survival curves of progression-free survival (PFS) and overall survival (OS) in patients with anti PD-1 based treatment. The median PFS was 7.59 months and the median OS was not reached.
- Figure 3
Biomarker exploring for anti-PD-1 based therapy. (A) The landscape map with whole exome sequencing data of 8 cases before treatment combined with TMB/TNB/MSI and other information. From top to bottom are as follows: TMB, TNB, MSI, HLA-LOH, or not, sarcoma subtype, efficacy, PD-L1, and the top 19 genes with the highest mutation frequency. (B) Tumor mutational burden (TMB) in 8 patients is described using a histogram. It was divided into TMB-clones and TMB-subclones. The percentage of subclones present in the percentages of neoantigens. (C) Tumor neoantigen burden in 8 patients is described using a histogram. Two patients had the phenomenon of HLA-LOH, but it had an effect on only 1 patient because half of the neoantigens could not be presented. (D) Intertumoral heterogeneity (ITH) in 8 patients using a histogram. The patients with PD showed the highest percentage of ITH.
- Figure 4
The analysis of RNA data of 7 patients. (A) Heat map of immunity-related gene expressions. (B) The analysis of infiltration percentages of tumor immunocytes. The whole cell percentages in the response (PR + SD) and nonresponse (PD) groups. (C) The heat map of immune cells in 7 patients. (D) The heat map of monocytes in 7 patients. (E) Variation analysis of the different immunocytes between the response and nonresponse groups, including B cells, M1/M2 macrophages, monocytes, neutrophils, NK cells, CD4+ T cells, CD8+ T cells, Tregs, and dendritic cells. (F) Heat map of clustering analysis of these 8 patients. The patient with apartial response showed normal stroma subtype, and patients with PD showed an activated stroma subtype according to stroma signature genes.
- Figure 5
The analysis of transcriptome data. (A) The gene set enrichment analysis of the signal pathway. (B) The increasing expressions of genes mainly belong to cytokine-cytokine receptor interaction, cell adhesion molecules, the calcium signal pathway, and proteoglycans in cancer. (C) The decreased expressions of genes mainly belonged to neuroactive ligand-receptor interaction and the calcium signal pathway. (D) The gene set enrichment analysis of signal pathway-related immunity. The increased TGF-β signaling pathways had reverse correlations with anti-PD1 efficacies, while the decreased inflammation responses of signaling pathways had positive correlations with anti-PD-1 efficacies. (E) Key tumor-associated signaling pathways such as PI3K-AKT, PTEN, and MAPK showed no outstanding difference among different response patients.
Tables
Characteristics n (%) Age Average 43 years Range 15–78 years Gender Male 14 (58) Female 10 (42) ECOG performance status 0 3 (12.5) 1 15 (62.5) 2 5 (20.8) 3 1 (4.2) Tumor type Soft tissue sarcoma 17 (70.8) Synovial sarcoma 3 Liposarcoma 4 UPS 3 Rhabdomyosarcoma 2 Leiomyosarcoma 2 Clear cell sarcoma 2 MPNST 1 Non-soft tissue sarcoma 7 (29.2) Osteosarcoma 5 Chondrosarcoma 2 Primary location Extremity 12 (50.0) Abdominal/pelvis 2 (8.3) Chest 2 (8.3) Axial 8 (33.4) Treatment strategy Mono pembrolizumab 3 Camrilizumab combined with apatinib 20 Pembrolizumab combined with radiotherapy 1 ECOG, Eastern Cooperative Oncology Group; UPS, undifferentiated pleomorphic sarcoma; MPNST, malignant peripheral nerve sheath tumor.
Response 12W Overall response CR 0 0 PR 4 3 SD 9 7 PD 5 8 Excluded 6 6 ORR 22.2% (4/18) 16.7% (3/18) DCR 72.2% (13/18) 55.6% (10/18) PFR−12W = 49.8% mPFS = 7.59 month mOS unreached CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease; DCR, disease control rate; ORR, objective response rate; PFR, progression-free survival; mPFS, median progression-free survival.
Patient Pathologic type Treatment 8w 12w Overall PD-L1 MSI LYC OS Pembrolizumab SD PR PR − MSS WJH OS Combined SD SD SD − XX OS Combined SD SD SD ZWY OS Combined PD PD PD − 5.74 LY OS Combined SD PD PD ZFL LPS Combined SD SD PD − WHX LPS Combined SD SD SD − 7.19 XMC LPS Combined PD − MXW LPS Combined SD + 2.7 ZX SS Pembrolizumab SD SD SD − WY SS Combined SD SD SD TMM SS Combined SD SD SD DLY UPS Combined PD PD PD MRH UPS Combined SD + 2.56 KZP UPS Combined PD - 0.9 CMJ RMS Combined PD GXS RMS Combined SD PD PD YHB CDS Combined SD SD SD LLL CDS Combined SD PR PR 1.71 SHY LMS Pembrolizumab+radiotherapy PD PR PD + GJJ LMS Combined SD SD SD − 4.69 PFL CCS Pembrolizumab PD WB CCS Combined SD PD PD MYT MPNST Combined SD SD PD − 4.11 OS, osteosarcoma; SS, synovial sarcoma; RMS, rhabdomyosarcoma; CDS, chondrosarcoma; LMS, leiomyosarcoma; CCS, clear cell sarcoma; LPS, liposarcoma; MPNST, malignant peripheral nerve sheath tumor; UPS, undifferentiated pleomorphic sarcoma. Combined treatment (camrelizumab+apatinib).
Adverse event Grade1* Grade2 Grade3 Grade4 Total RCCEP 7 0 0 0 7 (17.9%) Fatigue and weakness 5 0 0 0 5 (12.8%) Digestive dysfunction 3 0 0 0 3 (7.7%) Fever 3 0 0 0 3 (7.7%) Anemia 3 0 0 0 3 (7.7%) Leukopenia 2 0 1 0 3 (7.7%) Pain 2 0 0 0 2 (5.1%) Hypertension 1 0 0 1 2 (5.1%) Rash 2 0 0 0 2 (5.1%) HFSR 1 1 0 0 2 (5.1%) Hypohepatia 1 1 0 0 2 (5.1%) Diarrhea 1 0 0 0 1 (2.6%) Albuminuria 1 0 0 0 1 (2.6%) Limb edema 1 0 0 0 1 (2.6%) Anorexia 1 0 0 0 1 (2.6%) Hypothyroidism 1 0 0 0 1 (2.6%) *According to the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE, version 3.0). RCCEP, reactive capillary hyperplasia; HFSR, hand and foot syndrome.
Sample GJJ.T0_WES KZP.T0_WES LLL.T0_WES MRH.T0_WES MXW.T0_WES MYT.T0_WES WHX.T0_WES ZWY.T0_WES DDR – – – – – – – BRIP1, p. Ile1209Met TMB TMB-L:1.35 TMB-M:3.45 TMB-L:1.12 TMB-L:1.73 TMB-M:3.07 TMB-L:1.91 TMB-L:1.43 TMB-L:1.32 TNB TNB-M:0.72 TNB-M:1.13 TNB-L:0.44 TNB-M:0.63 TNB-M:1.53 TNB-M:0.72 TNB-M:0.69 TNB-L:0.31 MSI 4.69 0.9 1.71 2.56 2.7 4.11 7.19 5.74 HLA mutation – – – – – – – – B2M mutation – – – – – – – – ALK fusion – – – – – – – – EGFR mutation – – – – – – – – JAK1/2 mutation – – – – – – – – PTEN mutation – – – – – – – – STK11mutation – – – – STK11, p. Met18Ile – – – MDM2 amplification – MDM2, amp8 – – – – – – MDM4 amplification – – – – – – – – DNMT3A mutation – – – – – – – – HLA-LOH HLA-A*30:01 HLA-C*03:03 – – – HLA-A*24:02 HLA-C*01:02 – – – Class Pathway name Gene UP/DOWN VEGF REACTOME_SIGNALING_BY_VEGF AXL, ITPR3 UP PAK3, PRKCA DOWN VEGF2 REACTOME_VEGFR2_MEDIATED_CELL_PROLIFERATION ITPR3 UP PRKCA DOWN ANGIOGENESIS HALLMARK_ANGIOGENESIS S100A4, LUM, VCAN UP APOPTOSIS REACTOME_APOPTOSIS TNFSF10 UP BCL2 DOWN AUTOPHAGY REACTOME_AUTOPHAGY TUBA4A UP MET REACTOME_SIGNALING_BY_MET COL1A1, COL5A3, COL1A2, COL5A1 UP EMT TGF-beta_receptor_signaling_in_EMT CGN DOWN Drug resistance related BIOCARTA_PKC_PATHWAY PRKCA DOWN REACTOME_MAPK_FAMILY_SIGNALING_CASCADES APBB1IP, FGF16, CAMK2A UP NEFL, NRG3, PAK3, RASGRF1, NRTN DOWN REACTOME_PI3K_AKT_SIGNALING_IN_CANCER FFGF16, CD86, RAC2, CD28D UP NRG3 DDOWN REACTOME_PI3K_CASCADE REACTOME_PTEN_REGULATION ST_STAT3_PATHWAY
In this issue
Jump to section
Related Articles
Cited By...
- No citing articles found.