Purpose: A minority of patients currently respond to single-agent immune-checkpoint blockade (ICB), and strategies to increase response rates are urgently needed. AXL is a receptor tyrosine kinase commonly associated with drug resistance and poor prognosis in many cancer types, including in clear-cell renal cell carcinoma (ccRCC). Recent experimental cues in breast, pancreatic, and lung cancer models have linked AXL with immune suppression and resistance to antitumor immunity. However, its role in intrinsic and acquired resistance to ICB remains largely unexplored. Experimental Design: In this study, tumoral expression of AXL was examined in ccRCC specimens from 316 patients who were metastatic receiving the PD-1 inhibitor nivolumab in the GETUG AFU 26 NIVOREN trial after failure of antiangiogenic therapy. We assessed associations between AXL and patient outcomes following PD-1 blockade, as well as the relationship with various markers, including PD-L1; VEGFA; the immune markers CD3, CD8, CD163, and CD20; and the mutational status of the tumor-suppressor gene von Hippel-Lindau (VHL). Results: Our results show that high AXL-expression level in tumor cells is associated with lower response rates and a trend to shorter progression-free survival following anti–PD-1 treatment. AXL expression was strongly associated with tumor–PD-L1 expression, especially in tumors with VHL inactivation. Moreover, patients with tumors displaying concomitant PD-L1 expression and high AXL expression had the worst overall survival. Conclusions: Our findings propose AXL as candidate factor of resistance to PD-1 blockade, and provide compelling support for screening both AXL and PD-L1 expression in the management of advanced ccRCC.

Association of AXL and PD-L1 expression with clinical outcomes in patients with advanced renal cell carcinoma treated with PD-1 blockade

Abstract Objective Ovarian cancer has the highest mortality rate among gynecological malignant tumors, and it preferentially metastasizes to omental tissue, leading to intestinal obstruction and death. scRNA-seq is a powerful technique to reveal tumor heterogeneity. Analyzing omentum metastasis of ovarian cancer at the single-cell level may be more conducive to exploring and understanding omentum metastasis and prognosis of ovarian cancer at the cellular function and genetic levels. Methods The omentum metastasis site scRNA-seq data of GSE147082 were acquired from the GEO (Gene Expression Omnibus) database, and single cells were clustered by the Seruat package and annotated by the SingleR package. Cell differentiation trajectories were reconstructed through the monocle package. The ovarian cancer microarray data of GSE132342 were downloaded from GEO and were clustered by using the ConsensusClusterPlus package into omentum metastasis-associated clusters according to the marker genes gained from single-cell differentiation trajectory analysis. The tumor microenvironment (TME) and immune infiltration differences between clusters were analyzed by the estimate and CIBERSORT packages. The expression matrix of genes used to cluster GSE132342 patients was extracted from bulk RNA-seq data of TCGA-OV (The Cancer Genome Atlas ovarian cancer), and least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were performed to establish an omentum metastasis-associated gene (OMAG) signature. The signature was then tested by GSE132342 data. Finally, the clinicopathological characteristics of TCGA-OV were screened by univariate and multivariate Cox regression analysis to draw the nomogram. Results A total of 9885 cells from 6 patients were clustered into 18 cell clusters and annotated into 14 cell types. Reconstruction of differentiation trajectories divided the cells into 5 branches, and a total of 781 cell trajectory-related characteristic genes were obtained. A total of 3769 patients in GSE132342 were subtyped into 3 clusters by 74 cell trajectory-related characteristic genes. Kaplan-Meier (K-M) survival analysis showed that the prognosis of cluster 2 was the worst, P &lt; 0.001. The TME analysis showed that the ESTIMATE score and stromal score in cluster 2 were significantly higher than those in the other two clusters, P &lt; 0.001. The immune infiltration analysis showed differences in the fraction of 8 immune cells among the 3 clusters, P &lt; 0.05. The expression data of 74 genes used for GEO clustering were extracted from 379 patients in TCGA-OV, and combined with survival information, 10 candidates for OMAGs were filtered by LASSO. By using multivariate Cox regression, the 6-OMAGs signature was established as RiskScore = 0.307*TIMP3 + 3.516*FBN1–0.109*IGKC + 0.209*RPL21 + 0.870*UCHL1 + 0.365*RARRES1. Taking TCGA-OV as the training set and GSE132342 as the test set, receiver operating characteristic (ROC) curves were drawn to verify the prognostic value of 6-OMAGs. Screened by univariate and multivariate Cox regression analysis, 3 (age, cancer status, primary therapy outcome) of 5 clinicopathological characteristics were used to construct the nomogram combined with risk score. Conclusion We constructed an ovarian cancer prognostic model related to omentum metastasis composed of 6-OMAGs and 3 clinicopathological features and analyzed the potential mechanism of these 6-OMAGs in ovarian cancer omental metastasis. 

/pdf/establishment-of-an-ovarian-cancer-omentum-metastasis-ja4ux3sr.pdf

Establishment of an ovarian cancer omentum metastasis-related prognostic model by integrated analysis of scRNA-seq and bulk RNA-seq

Tazarotene-induced gene 1 (TIG1) is a retinoid acid receptor-responsive gene involved in cell differentiation and tumorigenesis. Aberrant methylation of CpG islands in the TIG1 promoter is found in multiple cancers. Currently, the exact mechanism underlying the anticancer effect of TIG1 is unknown. Here, we show that TIG1 interacts with cathepsin V (CTSV), which reduces CTSV stability and subsequently affects the production of activated urokinase-type plasminogen activator (uPA), an epithelial-mesenchymal transition-associated protein. Ectopic expression of CTSV increased the expression of activated uPA and the number of migrated and invaded cells, whereas ectopic TIG1 expression reversed the effects of CTSV on the uPA signaling pathway. Similar patterns in the production of activated uPA and number of migrated and invaded cells were also observed in TIG1-expressing and CTSV-knockdown cells. The results suggest that CTSV may participate in TIG1-regulated uPA activity and the associated downstream signaling pathway.

Cathepsin V Mediates the Tazarotene-induced Gene 1-induced Reduction in Invasion in Colorectal Cancer Cells.

One of the common mediator of tumour progression is the oxidative stress induced by inflammatory tumour microenvironment (TME). Activated fibroblasts, local and immune cells produce reactive oxygen species (ROS) supporting tumour cell proliferation and pave the way for metastatic tumour growth. TXNIP regulates ROS generation by inhibiting the antioxidative function of thioredoxin (TXN). The shift of TXNIP/TXN balance towards overexpression of TXNIP is associated with proliferation of endothelial cells during tumor angiogenesis. The oxidative stress activates the hypoxia inducible factor-1 (HIF-1), which plays an important role in the biology of conventional RCC (cRCC). Under oxydative stress TXNIP interacts with NLRP3 inflammasome leading to maturation and secretion of inflammatory cytokine IL1β. To establish the role of TXNIP and downstream genes HIF1α and IL1β in the biology of cRCC, we have applied immunohistochemistry to multi-tissue arrays containing tumours of 691 patients without detectable metastases at the time of operation. We found that cRCC displaying a fine organised capillary network with nuclear translocation of TXNIP and expressing IL1β have a good prognosis. In contrary, we showed a significant correlation between cytoplasmic TXNIP expression, inefficient vascularisation by unorganized and tortuous vessels causing tumour cell necrosis and postoperative tumour relapse of cRCC.

/pdf/expression-of-txnip-is-associated-with-angiogenesis-and-3rtmsefafs.pdf

Expression of TXNIP is associated with angiogenesis and postoperative relapse of conventional renal cell carcinoma

Abstract Objective Ovarian cancer is a gynecological malignant tumor with the highest mortality, it preferentially metastasizes to omental tissue, leading to intestinal obstruction and death. scRNA-Seq is a powerful technique to analyze tumor heterogeneity. Analyzing omentum metastasis of ovarian cancer at the single cell level may be more conducive to analyzing and understanding omentum metastasis and prognosis of ovarian cancer at the cellular function and genetic levels. Methods The scRNA-seq data of omentum metastasis site were acquired from the GEO (Gene Expression Omnibus) database, the data were clustered by Seruat package and annotated by SingleR package. Cell differentiation trajectories were reconstructed through monocle package, and obtained the marker genes of every branch. The microarray data of ovarian cancer were extracted from GEO and were clustered into omentum metastasis associated subpopulations according to the marker genes of single cell differentiation trajectories. The tumor microenvironment and immune infiltration differences between subpopulations were analyzed by estimate package and CIBERSORT. After that, based on the survival information and the intersection of bulk RNA-seq data of TCGA (The Cancer Genome Atlas) and marker genes of GEO subpopulations, univariate Cox and Lasso regression were performed to further establish an omentum metastasis-associated genes (OMAGs) signature, the signature was then tested by GEO data. Finally, the clinicopathological characteristics of TCGA-OV and GEO were screened by univariate and multivariate Cox regression analysis, in order to draw the nomogram. Results The scRNA-seq data (GSE147082) were clustered into 18 cell clusters, and annotated into 14 cell types. Reconstruction of differentiation trajectories divided the cells into 5 branches, a total of 833 cell trajectories related characteristic genes were obtained. Two microarray datasets (GSE132342 and GSE135820) were integrated to gain the expression data of 510 genes in 7846 patients, which were subtyped into 3 subpopulations by the cell trajectories related characteristic genes. K-M survival analysis showed that the prognosis of cluster2 was the worst and cluste1 was the best, p &lt; 0.001. The tumor microenvironment showed that the ESTIMATE Score, Stromal Score in cluster 2 is significantly higher than that in the other two clusters, while Immune Score, Tumor Purity were significantly lower, p &lt; 0.001; The immune infiltration analysis showed differences in the fraction of 10 immune cells among the 3 subpopulations, p &lt; 0.05. Immune checkpoint analysis showed that there were significant differences in the expression levels of 6 genes in the 3 subpopulations, which were significantly correlated with prognosis. Subsequently, the scRNA-seq characteristic genes of 5 branches, GEO characteristic genes of 3 subpopulations were intersected with the bulk RNA-seq of 379 patients in TCGA-OV, and 11 candidate genes of OMAGs (omentum metastasis-associated genes) were obtained by Lasso regression. The composition of OMAGs was further refined by Cox multivariate regression analysis, and established a 6-OMAGs signature (RiskScore = 6.669*VCAN + 0.173*FN1–0.128*IGKC + 0.258*RPL21 + 2.133*UCHL1 + 0.457*RARRES1). Taking TCGA data as training set and geo data as test set, ROC curves were drawn to verify its sensitivity. Ultimately, 5 clinicopathological characteristics (age, tumor status, initial treatment outcome, stage, grade) were screened by univariate and multivariate Cox regression analysis, and the nomogram was drawn. Conclusions Finally, we constructed a clinical prognostic model related to omentum metastasis of ovarian cancer, which was composed of 6-OMAGs and 5 clinicopathological features. 

The Establishment of an Ovarian Cancer Omentum Metastasis Related Prognostic Model by Integrated Analysis of ScRNA-Seq and Bulk RNA-Seq.

Approximately 15% of clinically localised conventional renal cell carcinoma (RCC) will develop metastasis within 5 years of follow-up. The aim of this study was to identify biomarkers predicting the postoperative tumour relapse. Tissue microarrays of conventional RCC from a cohort of 691 patients without metastasis at the time of operation were analysed by immunohistochemistry for the expression of carboxypeptase inhibitor RARRES1 and its substrate carboxypeptidase AGBL2. Univariate and multivariate Cox regression models were addressed to postoperative tumour relapse and the metastasis-free survival time was estimated by Kaplan–Meier analysis. In multivariate analysis, the lack of staining or cytoplasmic staining of RARRES1 was a significant risk factor indicating five times higher risk of cancer relapse. Combining its co-expression with AGBL2, we found that RARRES1 cytoplasmic/negative and AGBL2-positive/negative staining is a significant risk factor for tumour progression indicating 11–15 times higher risk of cancer relapse, whereas the membranous RARRES1 expression, especially its co-expression with AGBL2, associated with excellent disease outcome. RARRES1 and AGBL2 expression defines groups of patients at low and high risk of tumour progression and may direct an active surveillance to detect metastasis as early as possible and to apply adjuvant therapy.

Expression of RARRES1 and AGBL2 and progression of conventional renal cell carcinoma.

BACKGROUND/AIM Despite early detection by widespread use of abdominal imaging more than 40% of patients with conventional renal cell carcinoma (RCC) will die due to metastatic disease. Small kinase inhibitors for AXL receptor tyrosine kinase may delay the progression of metastatic cRCC. PATIENTS AND METHODS We analysed AXL expression by immunohistochemistry on tissue multi arrays of 691 conventional RCC without metastasis at the time of nephrectomy. RESULTS The Kaplan-Meier survival analysis indicated a poor disease-specific survival rates for patients with tumour showing cytoplasmic AXL staining, whereas expression on the cell membrane is associated with excellent disease outcome. Multivariate Cox regression analysis identified cytoplasmic AXL expression as an independent prognostic factor indicating a five-times higher risk of postoperative tumour progression (RR=5.048; 95% CI=2.391-10.657; p<0.001). CONCLUSION Detecting cytoplasmic expression of AXL can be used to define a subset of conventional RCC with high risk of progression, thus identifying patients for more aggressive surveillance and adjuvant AXL inhibitor treatment as early as possible.

Cytoplasmic Expression of AXL Is Associated With High Risk of Postoperative Relapse of Conventional Renal Cell Carcinoma.

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Expression of RARRES1 and AGBL2 and progression of conventional renal cell carcinoma.

Cytoplasmic Expression of AXL Is Associated With High Risk of Postoperative Relapse of Conventional Renal Cell Carcinoma.