scholarly journals Transcriptional Profiling of Advanced Urothelial Cancer Predicts Prognosis and Response to Immunotherapy

2020 ◽  
Vol 21 (5) ◽  
pp. 1850 ◽  
Author(s):  
Seung-Woo Baek ◽  
In-Hwan Jang ◽  
Seon-Kyu Kim ◽  
Jong-Kil Nam ◽  
Sun-Hee Leem ◽  
...  

Recent investigations reported that some subtypes from the Lund or The Cancer Genome Atlas (TCGA) classifications were most responsive to PD-L1 inhibitor treatment. However, the association between previously reported subtypes and immune checkpoint inhibitor (ICI) therapy responsiveness has been insufficiently explored. Despite these contributions, the ability to predict the clinical applicability of immune checkpoint inhibitor therapy in patients remains a major challenge. Here, we aimed to re-classify distinct subtypes focusing on ICI responsiveness using gene expression profiling in the IMvigor 210 cohort (n = 298). Based on the hierarchical clustering analysis, we divided advanced urothelial cancer patients into three subgroups. To confirm a prognostic impact, we performed survival analysis and estimated the prognostic value in the IMvigor 210 and TCGA cohort. The activation of CD8+ T effector cells was common for patients of classes 2 and 3 in the TCGA and IMvigor 210 cohort. Survival analysis showed that patients of class 3 in the TCGA cohort had a poor prognosis, while patients of class 3 showed considerably prolonged survival in the IMvigor 210 cohort. One of the distinct characteristics of patients in class 3 is the inactivation of the TGFβ and YAP/TAZ pathways and activation of the cell cycle and DNA replication and DNA damage (DDR). Based on our identified transcriptional patterns and the clinical outcomes of advanced urothelial cancer patients, we constructed a schematic summary. When comparing clinical and transcriptome data, patients with downregulation of the TGFβ and YAP/TAZ pathways and upregulation of the cell cycle and DDR may be more responsive to ICI therapy.

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Junyu Long ◽  
Dongxu Wang ◽  
Xu Yang ◽  
Anqiang Wang ◽  
Yu Lin ◽  
...  

Abstract Background Immune checkpoint inhibitor (ICI) therapy elicits durable antitumor responses in patients with many types of cancer. Genomic mutations may be used to predict the clinical benefits of ICI therapy. NOTCH homolog-4 (NOTCH4) is frequently mutated in several cancer types, but its role in immunotherapy is still unclear. Our study is the first to study the association between NOTCH4 mutation and the response to ICI therapy. Methods We tested the predictive value of NOTCH4 mutation in the discovery cohort, which included non-small cell lung cancer, melanoma, head and neck squamous cell carcinoma, esophagogastric cancer, and bladder cancer patients, and validated it in the validation cohort, which included non-small cell lung cancer, melanoma, renal cell carcinoma, colorectal cancer, esophagogastric cancer, glioma, bladder cancer, head and neck cancer, cancer of unknown primary, and breast cancer patients. Then, the relationships between NOTCH4 mutation and intrinsic and extrinsic immune response mechanisms were studied with multiomics data. Results We collected an ICI-treated cohort (n = 662) and found that patients with NOTCH4 mutation had better clinical benefits in terms of objective response rate (ORR: 42.9% vs 25.9%, P = 0.007), durable clinical benefit (DCB: 54.0% vs 38.1%, P = 0.021), progression-free survival (PFS, hazard ratio [HR] = 0.558, P < 0.001), and overall survival (OS, HR = 0.568, P = 0.006). In addition, we validated the prognostic value of NOTCH4 mutation in an independent ICI-treated cohort (n = 1423). Based on multiomics data, we found that NOTCH4 mutation is significantly associated with enhanced immunogenicity, including a high tumor mutational burden, the expression of costimulatory molecules, and activation of the antigen-processing machinery, and NOTCH4 mutation positively correlates activated antitumor immunity, including infiltration of diverse immune cells and various immune marker sets. Conclusions Our findings indicated that NOTCH4 mutation serves as a novel biomarker correlated with a better response to ICI therapy.


2021 ◽  
Vol 160 (6) ◽  
pp. S-337
Author(s):  
Fangwen Zou ◽  
Anusha Shirwaikar Thomas ◽  
Barbara E. Dutra ◽  
Shruti Khurana ◽  
Isabella C. Glitza Oliva ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
So Yeon Oh ◽  
Soyeon Kim ◽  
Bhumsuk Keam ◽  
Tae Min Kim ◽  
Dong-Wan Kim ◽  
...  

AbstractCirculating soluble programmed death-1 ligand (sPD-L1) is measurable in the serum of cancer patients. This study aimed to investigate the significance of sPD-L1 in cancer patients receiving immune checkpoint inhibitor therapy. Blood samples were obtained before and after immune checkpoint inhibitor therapy (January 2015 to January 2019). The study cohort consisted of 128 patients who were diagnosed with non-small cell lung cancer (n = 50), melanoma (n = 31), small cell lung cancer (n = 14), urothelial carcinoma (n = 13), and other cancers (n = 20). Patients with a high level (> 11.0 pg/μL) of sPD-L1 were more likely to exhibit progressive disease compared with those with a low level (41.8% versus 20.7%, p = 0.013). High sPD-L1 was also associated with worse prognosis; the median PFS was 2.9 (95% confidence interval [CI] 2.1–3.7) months versus 6.3 (95% CI 3.0–9.6) months (p = 0.023), and the median OS was 7.4 (95% CI 6.3–8.5) months versus 13.3 (95% CI 9.2–17.4) months (p = 0.005). In the multivariate analyses, high sPD-L1 was an independent prognostic factor for both decreased PFS (HR 1.928, p = 0.038) and OS (HR 1.788, p = 0.004). sPD-L1 levels did not correlate with tissue PD-L1 expression. However, sPD-L1 levels were positively correlated with neutrophil to lymphocyte ratios and negatively correlated with both the proportion and the total number of lymphocytes. We found that high pretreatment sPD-L1 levels were associated with progressive disease and were an independent prognostic factor predicting lower PFS and OS in these patients.


2019 ◽  
Vol 22 (4) ◽  
pp. 555-562 ◽  
Author(s):  
B. Fox ◽  
M. de Toro Carmena ◽  
R. Álvarez Álvarez ◽  
A. Calles Blanco ◽  
C. López López ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document