Purpose: CD70 is a costimulatory molecule known to activate CD27-expressing T cells. CD27–CD70 interaction leads to the release of soluble CD27 (sCD27). Clear-cell renal cell carcinoma (ccRCC) expresses the highest levels of CD70 among all solid tumors; however, the clinical consequences of CD70 expression remain unclear. Experimental Design: Tumor tissue from 25 patients with ccRCC was assessed for the expression of CD27 and CD70 in situ using multiplex immunofluorescence. CD27+ T-cell phenotypes in tumors were analyzed by flow cytometry and their gene expression profile were analyzed by single-cell RNA sequencing then confirmed with public data. Baseline sCD27 was measured in 81 patients with renal cell carcinoma (RCC) treated with immunotherapy (35 for training cohort and 46 for validation cohort). Results: In the tumor microenvironment, CD27+ T cells interacted with CD70-expressing tumor cells. Compared with CD27− T cells, CD27+ T cells exhibited an apoptotic and dysfunctional signature. In patients with RCC, the intratumoral CD27–CD70 interaction was significantly correlated with the plasma sCD27 concentration. High sCD27 levels predicted poor overall survival in patients with RCC treated with anti–programmed cell death protein 1 in both the training and validation cohorts but not in patients treated with antiangiogenic therapy. Conclusions: In conclusion, we demonstrated that sCD27, a surrogate marker of T-cell dysfunction, is a predictive biomarker of resistance to immunotherapy in RCC. Given the frequent expression of CD70 and CD27 in solid tumors, our findings may be extended to other tumors.

Three drug combinations, ipilimumab-nivolumab (Ipi-Nivo), pembrolizumab-axitinib (Pembro-Axi), and avelumab-axitinib (Ave-Axi), have received regulatory approval in the USA and Europe for the treatment of metastatic renal cell carcinoma with clear cell component (mRCC). However, no head-to-head comparison data are available to identify the best option. Therefore, we aimed to compare these new treatments in a first-line setting. We conducted a systematic search in PubMed, the Cochrane Library, and clinicaltrials.gov for any randomized controlled trials of treatment-naïve patients with mRCC, from January 2015 to October 2019. The process was performed according to PRISMA guidelines. We performed a Bayesian network meta-analysis with two different approaches, a contrast-based model comparing HRs and ORs between studies and arm-based using parametric modeling. The outcomes for the analysis were overall survival, progression-free survival (PFS), and objective response rate. Our search identified 3 published phase 3 randomized clinical trials (2835 patients). In the contrast-based model, Ave-Axi (SUCRA = 83%) and Pembro-Axi (SUCRA = 80%) exhibited the best ranking probabilities for PFS. For overall survival (OS), Pembro-Axi (SUCRA = 96%) was the most preferable option against Ave-Axi and Ipi-Nivo. Objective response rate analysis showed Ave-Axi as the best (SUCRA: 94%) and Pembro-Axi as the second best option. In the parametric models, the risk of progression was comparable for Ave-Axi and Ipi-Nivo, whereas Pembro-Axi exhibited a lower risk during the first 6 months of treatment and a higher risk afterwards. Furthermore, Pembro-Axi exhibited a net advantage in terms of OS over the two other regimens, while Ave-Axi was the least preferable option. Overall evidence suggests that pembrolizumab plus axitinib seems to have a slight advantage over the other two combinations.

Background: Three drug-combinations, ipilimumab-nivolumab (Ipi-Nivo), pembrolizumab-axitinib (Pembro-Axi) and avelumab-axitinib (Ave-Axi), have received regulatory approvals in USA and Europe for the treatment of metastatic renal cell carcinoma with clear cell component (mRCC). However, no head-to-head comparison data are available to identify the best option. Therefore, we aimed to compare these new treatments in the first-line setting. Methods: We conducted a systematic search in Pubmed, the Cochrane library and clinicaltri-al.gov website from January 2015 to October 2019, for any randomized controlled trials of treatment-naïve patients with mRCC. The process was performed according to PRISMA guide-lines. We performed a Bayesian network meta-analysis with two different approaches. The out-comes for analysis were overall survival, progression-free survival, and objective response rate. Results: Our search identified 3 published phase 3 randomized clinical trials (2835 patients). In the contrast-based model, Ave-Axi (SUCRA: 83%) and Pembro-Axi (SUCRA: 80%) exhibited the best ranking probabilities for PFS. For OS, Pembro-Axi (SUCRA: 96%) was the most pref-erable option against Ave-Axi and Ipi-Nivo. Objective response rate analysis showed Ave-Axi as the best (SUCRA= 94%) and Pembro-Axi as second best option. In the parametric models, risk of progression was comparable for Ave-Axi and Ipi-Nivo, whereas Pembro-Axi exhibited a lower risk during the first 6 months of treatment and a higher risk afterward. Furthermore, Pembro-Axi exhibited a net advantage in terms of OS over the two other regimens, while Ave-Axi was the least preferable option. Conclusions: Overall evidences suggested pembrolizumab plus axitinib may be the best option.

The management of non-small cell lung cancer (NSCLC), including lung adenocarcinomas (LUAD), has been revolutionized with the advent of precision oncology. While advanced cancers often carry poor prognosis, those harboring specific molecular alterations sensitive to targeted therapy (notably tyrosine kinase inhibitor [TKI]) have experienced improved response to treatment and survival outcomes. Consequently, detecting these alterations through molecular screening panel has become standard in several countries, although this necessitates high-quality tissue sampling to inform optimal therapeutic decisions. Oncologic imaging occupies a pivotal role in the routine care of patients, in particular at diagnosis, with a wealth of information gathered but underutilized, as medical imaging reflects the disease in its entirety at a given time point. Moreover, recent advancements in imaging quantitative analysis, including radiomics and artificial intelligence, could aid in better integration and understanding of this information that has been overlooked for years. Several radiological phenotypes (or radiophenotypes) have been linked to tumor genomic alterations, both in standard radiology relying on semantic features and metastatic patterns, and in radiomics. Ultimately, understanding the relationships between imaging and targetable genomic alterations via accurate imaging biomarkers could complement ambiguous tumor or liquid biopsy, detect emerging new alterations, and even substitute biopsy through ‘virtual biopsy’. During the past decade, there has been a surge in research focused on radiogenomic assessment of NSCLC and especially LUAD. However, due to the low prevalence of many oncogenic drivers, the scientific literature may lack clarity or present conflicting findings. This comprehensive review aims to provide a summary of the current state of this research, offering insights into the complex interplay between imaging and genomic alterations in lung adenocarcinoma.

Supplementary Table from Plasma CD27, a Surrogate of the Intratumoral CD27–CD70 Interaction, Correlates with Immunotherapy Resistance in Renal Cell Carcinoma