Prognostic impact of immune gene expression signature and tumor infiltrating immune cells in localized clear cell renal cell carcinoma

Integration of proteomics and transcriptomics to construct a prognostic signature of renal clear cell carcinoma

Background: Protein information is often replaced by RNA data in studies to understand cancer-related biological processes or molecular functions, and proteins of prognostic significance in Kidney clear cell carcinoma (KIRC) remain to be mined. Methods: The cancer genome atlas program (TCGA) data was utilized to screen for proteins that are prognostically significant in KIRC. Machine learning algorithms were employed to develop protein prognostic models. Additionally, immune infiltration abundance, somatic mutation differences, and immunotherapeutic responses were analyzed in various protein risk subgroups. Ultimately, the validation of protein-coding genes was confirmed by utilizing an online database and implementing quantitative real-time PCR (qRT-PCR). Results: The patients were divided into two risk categories based on prognostic proteins, and notable disparities in both overall survival (OS) and progression free interval (PFI) were observed between the two groups. The OS was more unfavorable in the high-risk group, and there was a noteworthy disparity in the level of immune infiltration observed between the two groups. In addition, the nomogram showed high accuracy in predicting survival in KIRC patients. Conclusion: In this research, we elucidated the core proteins associated with prognosis in terms of survival prediction, immunotherapeutic response, somatic mutation, and immune microenvironment. Additionally, we have developed a reliable prognostic model with excellent predictive capabilities.

Biomimetic Hydrogel-Mediated Mechano-Immunometabolic Therapy for Inhibition of ccRCC Recurrence After Surgery

The unique physical tumor microenvironment (TME) and aberrant immune metabolic status are two obstacles that must be overcome in cancer immunotherapy to improve clinical outcomes. Here, an in situ mechano-immunometabolic therapy involving the injection of a biomimetic hydrogel is presented with sequential release of the anti-fibrotic agent pirfenidone, which softens the stiff extracellular matrix, and small interfering RNA IDO1, which disrupts kynurenine-mediated immunosuppressive metabolic pathways, together with the multi-kinase inhibitor sorafenib, which induces immunogenic cell death. This combination synergistically augmented tumor immunogenicity and induced anti-tumor immunity. In mouse models of clear cell renal cell carcinoma, a single-dose peritumoral injection of a biomimetic hydrogel facilitated the perioperative TME toward a more immunostimulatory landscape, which prevented tumor relapse post-surgery and prolonged mouse survival. Additionally, the systemic anti-tumor surveillance effect induced by local treatment decreased lung metastasis by inhibiting epithelial-mesenchymal transition conversion. The versatile localized mechano-immunometabolic therapy can serve as a universal strategy for conferring efficient tumoricidal immunity in "cold" tumor postoperative interventions.

Exploring the role of CD8+ T cells in clear renal cell carcinoma metastasis

Clear cell renal cell carcinoma (ccRCC) accounts for approximately 75-80% of all patients with renal cell carcinoma. Despite its prevalence, little is known regarding the key components involved in ccRCC metastasis. In this study, scRNA-seq analysis was employed to classify CD8+ T cells into four sub-clusters based on their genetic profiles and immunofluorescence experiments were used to validate two key clusters. Through gene set enrichment analysis, these newly identified sub-clusters were found to exhibit distinct biological characteristics. Notably, TYMP, TOP2A, CHI3L2, CDKN3, CENPM, and RZH2 were highly expressed in these sub-clusters, indicating a correlation with poor prognosis. Among these sub-clusters, CD8+ T cells (MT-ND4) were identified as potentially playing a critical role in mediating ccRCC metastasis. These results contribute to our understanding of CD8+ T cell heterogeneity in ccRCC and shed light on the mechanisms underlying the loss of immune response against cancer.

Function of NEK2 in clear cell renal cell carcinoma and its effect on the tumor microenvironment

BACKGROUND

Previous studies have revealed the critical functions of NEK2 in controlling the cell cycle which is linked to poor prognosis in multiple tumor types, but less research has been devoted to clear cell renal cell carcinoma (ccRCC).

METHODS

We downloaded clinical data from the gene expression omnibus (GEO) and TCGA databases together with transcriptional and mutational datasets. Strongly coexpressed genes with NEK2 were extracted from TCGA-KIRC cohort, and were submitted to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional analyses. According to NEK2 levels, the survival status, mutational characteristics, response to immunotherapy and sensitivity to drugs of the patients were studied. The potential correlations between NEK2 levels and immune cell state as well as immune cell infiltration were examined using the GEPIA, TIMER and TISIDB databases. Double immunofluorescence (IF) was performed to identify the NEK2 overexpression and relationship with CD8 in ccRCC.

RESULTS

The NEK2 gene was overexpressed and would enhance the nuclear division and cell cycle activities in ccRCC. ccRCC patients with high NEK2 expression had worse clinical outcomes, higher mutation burden and better therapeutic response. Moreover, NEK2 gene overexpression was positively related to various immune cell marker sets, which was also proved by validation cohort, and more infiltration of various immune cells.

CONCLUSION

ccRCC patients with NEK2 high expression have a poorer prognosis than those with NEK2 low expression, resulting from its function of promoting proliferation, accompanied by increased infiltration of CD8 + T cells and Tregs and T-cell exhaustion and will respond better to proper treatments.

Tumor microenvironmental determinants of high-risk DCIS progression

Ductal carcinoma in situ (DCIS) constitutes an array of morphologically recognized intraductal neoplasms in the mammary ductal tree defined by an increased risk for subsequent invasive carcinomas at or near the site of biopsy detection. However, only 15-45% of untreated DCIS cases progress to invasive cancer, so understanding mechanisms that prevent progression is key to avoid overtreatment and provides a basis for alternative therapies and prevention. This study was designed to characterize the tumor microenvironment and molecular profile of high-risk DCIS that grew to a large size but remained as DCIS. All patients had DCIS lesions >5cm in size with at least one additional high-risk feature: young age (<45 years), high nuclear grade, hormone receptor negativity, HER2 positivity, the presence of comedonecrosis, or a palpable mass. The tumor immune microenvironment was characterized using multiplex immunofluorescence to identify immune cells and their spatial relationships within the ducts and stroma. Gene copy number analysis and whole exome DNA sequencing identified the mutational burden and driver mutations, and quantitative whole-transcriptome/gene expression analyses were performed. There was no association between the percent of the DCIS genome characterized by copy number variants (CNAs) and recurrence events (DCIS or invasive). Mutations, especially missense mutations, in the breast cancer driver genes PIK3CA and TP53 were common in this high-risk DCIS cohort (47% of evaluated lesions). Tumor infiltrating lymphocyte (TIL) density was higher in DCIS lesions with TP53 mutations (p=0.0079) compared to wildtype lesions, but not in lesions with PIK3CA mutations (p=0.44). Immune infiltrates were negatively associated with hormone receptor status and positively associated with HER2 expression. High levels of CD3+CD8- T cells were associated with good outcomes with respect to any subsequent recurrence (DCIS or invasive cancer), whereas high levels of CD3+Foxp3+ Treg cells were associated with poor outcomes. Spatial proximity analyses of immune cells and tumor cells demonstrated that close proximity of T cells with tumor cells was associated with good outcomes with respect to any recurrence as well as invasive recurrences. Interestingly, we found that myoepithelial continuity (distance between myoepithelial cells surrounding the involved ducts) was significantly lower in DCIS lesions compared to normal tissue (p=0.0002) or to atypical ductal hyperplasia (p=0.011). Gene set enrichment analysis identified several immune pathways associated with low myoepithelial continuity and a low myoepithelial continuity score was associated with better outcomes, suggesting that gaps in the myoepithelial layer may allow access/interactions between immune infiltrates and tumor cells. Our study demonstrates the immune microenvironment of DCIS, in particular the spatial proximity of tumor cells and T cells, and myoepithelial continuity are important determinants for progression of disease.

GHITM regulates malignant phenotype and sensitivity to PD-1 blockade of renal cancer cells via Notch signalling

Growth hormone inducible transmembrane protein (GHITM), one member of Bax inhibitory protein-like family, has been rarely studied, and the clinical importance and biological functions of GHITM in kidney renal clear cell carcinoma (KIRC) still remain unknown. In the present study, we found that GHITM was downregulated in KIRC. Aberrant GHITM downregulation related to clinicopathological feature and unfavourable prognosis of KIRC patients. GHITM overexpression inhibited KIRC cell proliferation, migration and invasion in vitro and in vivo. Mechanistically, GHITM overexpression could induce the downregulation of Notch1, which acts as an oncogene in KIRC. Overexpression of Notch1 effectively rescued the inhibitory effect induced by GHITM upregulation. More importantly, GHITM could regulate PD-L1 protein abundance and ectopic overexpression of GHITM enhanced the antitumour efficiency of PD-1 blockade in KIRC, which provided new insights into antitumour therapy. Furthermore, we also showed that YY1 could decrease GHITM level via binding to its promoter. Taken together, our study revealed that GHITM was a promising therapeutic target for KIRC, which could modulate malignant phenotype and sensitivity to PD-1 blockade of renal cancer cells via Notch signalling pathway.

A novel risk signature based on liquid-liquid phase separation-related genes reveals prognostic and tumour microenvironmental features in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma(ccRCC) is one of the most common malignancies. However, there are still many barriers to its underlying causes, early diagnostic techniques and therapeutic approaches.

MATERIALS AND METHODS

The Cancer Genome Atlas (TCGA)- Kidney renal clear cell (KIRC) cohort differentially analysed liquid-liquid phase separation (LLPS)-related genes from the DrLLPS website. Univariate and multivariate Cox regression analyses and LASSO regression analyses were used to construct prognostic models. The E-MTAB-1980 cohort was used for external validation. Then, potential functions, immune infiltration analysis, and mutational landscapes were analysed for the high-risk and low-risk groups. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) experiments as well as single-cell analyses validated the genes key to the model.

RESULTS

We screened 174 LLPS-related genes in ccRCC and constructed a risk signature consisting of five genes (CLIC5, MXD3, NUF2, PABPC1L, PLK1). The high-risk group was found to be associated with worse prognosis in different subgroups. A nomogram constructed by combining age and tumour stage had a strong predictive power for the prognosis of ccRCC patients. In addition, there were differences in pathway enrichment, immune cell infiltration, and mutational landscapes between the two groups. The results of qRT-PCR in renal cancer cell lines and renal cancer tissues were consistent with the biosignature prediction. Three single-cell data of GSE159115, GSE139555, and GSE121636 were analysed for differences in the presence of these five genes in different cells.

CONCLUSIONS

We developed a risk signature constructed based on the five LLPS-related genes and can have a high ability to predict the prognosis of ccRCC patients, further providing a strong support for clinical decision-making.

Impact of immunotherapy time-of-day infusion on survival and immunologic correlates in patients with metastatic renal cell carcinoma: a multicenter cohort analysis

BACKGROUND

Recent studies have demonstrated that earlier time-of-day infusion of immune checkpoint inhibitors (ICIs) is associated with longer progression-free survival (PFS) and overall survival (OS) among patients with metastatic melanoma and non-small cell lung cancer. These data are in line with growing preclinical evidence that the adaptive immune response may be more effectively stimulated earlier in the day. We sought to determine the impact of time-of-day ICI infusions on outcomes among patients with metastatic renal cell carcinoma (mRCC).

METHODS

The treatment records of all patients with stage IV RCC who began ICI therapy within a multicenter academic hospital system between 2015 and 2020 were reviewed. The associations between the proportion of ICI infusions administered prior to noon (denoting morning infusions) and PFS and OS were evaluated using univariate and multivariable Cox proportional hazards regression.

RESULTS

In this study, 201 patients with mRCC (28% women) received ICIs and were followed over a median of 18 months (IQR 5-30). The median age at the time of ICI initiation was 63 years (IQR 56-70). 101 patients (50%) received ≥20% of their ICI infusions prior to noon (Group A) and 100 patients (50%) received <20% of infusions prior to noon (Group B). Across the two comparison groups, initial ICI agents consisted of nivolumab (58%), nivolumab plus ipilimumab (34%), and pembrolizumab (8%). On univariate analysis, patients in Group A had longer PFS and OS compared with those in Group B (PFS HR 0.67, 95% CI 0.48 to 0.94, Punivar=0.020; OS HR 0.57, 95% CI 0.34 to 0.95, Punivar=0.033). These significant findings persisted following multivariable adjustment for age, sex, performance status, International Metastatic RCC Database Consortium risk score, pretreatment lactate dehydrogenase, histology, and presence of bone, brain, and liver metastases (PFS HR 0.70, 95% CI 0.50 to 0.98, Pmultivar=0.040; OS HR 0.57, 95% CI 0.33 to 0.98, Pmultivar=0.043).

CONCLUSIONS

Patients with mRCC may benefit from earlier time-of-day receipt of ICIs. Our findings are consistent with established mechanisms of chrono-immunology, as well as with preceding analogous studies in melanoma and lung cancer. Additional prospective randomized trials are warranted.

Distinct spatial landscapes in clear-cell renal cell carcinoma as revealed by whole transcriptome analysis

Background

Clear-cell renal cell carcinoma (ccRCC) is the most common and aggressive form of renal cancer and a paradigm of inter- and intratumor heterogeneity. We carried out an exploratory digital spatial profiling of the tumor interior and periphery of two ccRCC tumor specimens and mapped spatially the molecular and cellular composition of their tumor microenvironment and ecosystem.

Materials and methods

Digital spatial profiling of the whole transcriptome of 19 regions of interest (ROIs) was carried out from two selected highly immunogenic stage pT3a/grade 3 (G3) and stage pT3a/grade 4 (G4) ccRCC. A total of 9-10 ROIs were selected from distinct areas from each tumor, including tumor interior and tumor periphery, and differences in gene expression were analyzed by RNA sequencing, pathway enrichment analysis, and cell deconvolution.

Results

The distinct areas from the two locally advanced tumors displayed unique gene expression spatial patterns defining distinct biological pathways. Dimensional reduction analysis showed that the G3 ccRCC, compared to the G4 ccRCC, correlated with more variability between regions from the tumor interior and tumor periphery. Cell deconvolution analysis illustrated higher abundance of immune cells, including macrophages, myeloid dendritic cells, and CD4 T cells, and lower abundance of regulatory T cells in the tumor periphery compared to the tumor interior.

Conclusions

Transcriptome spatial profiling revealed high inter- and intratumor heterogeneity in the analyzed tumors and provided information with potential clinical utility. This included the finding of less intratumor heterogeneity and more tumor-infiltrated T cells in the ccRCC tumor specimen with a higher grade.

A promising natural killer cell-based model and a nomogram for the prognostic prediction of clear-cell renal cell carcinoma

BACKGROUND

Clear-cell renal cell carcinoma (ccRCC) is one of prevalent kidney malignancies with an unfavorable prognosis. There is a need for a robust model to predict ccRCC patient survival and guide treatment decisions.

METHODS

RNA-seq data and clinical information of ccRCC were obtained from the TCGA and ICGC databases. Expression profiles of genes related to natural killer (NK) cells were collected from the Immunology Database and Analysis Portal database. Key NK cell-related genes were identified using consensus clustering algorithms to classify patients into distinct clusters. A NK cell-related risk model was then developed using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression to predict ccRCC patient prognosis. The relationship between the NK cell-related risk score and overall survival, clinical features, tumor immune characteristics, as well as response to commonly used immunotherapies and chemotherapy, was explored. Finally, the NK cell-related risk score was validated using decision tree and nomogram analyses.

RESULTS

ccRCC patients were stratified into 3 molecular clusters based on expression of NK cell-related genes. Significant differences were observed among the clusters in terms of prognosis, clinical characteristics, immune infiltration, and therapeutic response. Furthermore, six NK cell-related genes (DPYSL3, SLPI, SLC44A4, ZNF521, LIMCH1, and AHR) were identified to construct a prognostic model for ccRCC prediction. The high-risk group exhibited poor survival outcomes, lower immune cell infiltration, and decreased sensitivity to conventional chemotherapies and immunotherapies. Importantly, the quantitative real-time polymerase chain reaction (qRT-PCR) confirmed significantly high DPYSL3 expression and low SLC44A4 expression in ACHN cells. Finally, the decision tree and nomogram consistently show the dramatic prediction performance of the risk score on the survival outcome of the ccRCC patients.

CONCLUSIONS

The six-gene model based on NK cell-related gene expression was validated and found to accurately mirror immune microenvironment and predict clinical outcomes, contributing to enhanced risk stratification and therapy response for ccRCC patients.

Disulfidptosis status influences prognosis and therapeutic response in clear cell renal cell carcinoma

Disulfidptosis is a recently identified type of programmed cell death. It is characterized by aberrant accumulation of intracellular disulfides. The clinical implications of disulfidptosis in clear cell renal cell carcinoma (ccRCC) remain unclear. A series of bioinformatics approaches were employed to analyze ten disulfidptosis-related molecules. Firstly, the expression patterns of the disulfidptosis-related molecules were different between normal and ccRCC tissues. A comprehensive cohort of patients with ccRCC was then assembled from three public databases and subjected to cluster analysis based on disulfidptosis-related molecules. Consensus cluster analysis revealed three distinct disulfidptosis clusters. We then conducted weighted gene co-expression network analysis (WGCNA) to identify highly correlated genes. 267 hub genes were screened out through WGCNA, and three gene clusters were then determined. Finally, we identified 87 genes with prognostic value and then used them to develop a disulfidptosis scoring (DSscore) system, which was proven to independently predict survival in ccRCC. Patients in the high-DSscore group exhibited a significant survival advantage and better immunotherapeutic responses compared with those in the low-DSscore group. However, the patients in the low-DSscore group exhibited a greater degree of chemotherapeutic response. In addition, the expression of disulfidptosis-related molecules was validated by qRT-PCR, and the potential of disulfidptosis-related molecules to indicate distinct cell subtypes were validated by single-cell RNA-sequencing. In conclusion, DSscore is a promising index for predicting the prognosis and efficacy of immunotherapy in patients with ccRCC and may provide a basis for novel strategies for future studies.

P2RY13 is a prognostic biomarker and associated with immune infiltrates in renal clear cell carcinoma: A comprehensive bioinformatic study

Background and Aims

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive form of cancer with a high incidence globally. This study aimed to investigate the role of P2RY13 in the progression of ccRCC and elucidate its mechanism of action.

Methods

Gene Expression Omnibus and The Cancer Genome Atlas databases were used to extract gene expression profiles of ccRCC. These profiles were annotated and visualized by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses, as well as Gene Set Enrichment Analysis (GSEA). The STRING database was used to establish a protein-protein interaction network and to analyze the functional similarity. The GEPIA2 database was used to predict survival associated with hub genes. Meanwhile, the TIMER2.0 database was used to assess immune cell infiltration and its link with the hub genes. Immunohistochemistry (IHC) was used to determine the difference between ccRCC and adjacent normal tissue.

Results

We identified 272 differentially expressed genes (DEGs). GO and KEGG analyses suggested that DEGs were primarily involved in lymphocyte activation, inflammatory response, immunological effector mechanism pathways. By cytohubba, the 20 highest-scoring hub genes were screened to identify critical genes in the protein-protein interaction network linked with ccRCC. Resting dendritic cells, CD8 T cells, and activated mast cells all showed a significant positive correlation with these hub genes. Moreover, a higher immune score was associated with increased prognostic risk scores, which in turn correlated with a poorer prognosis. IHC revealed that P2RY13 was expressed at higher levels in ccRCC compared to para-cancer tissues.

Conclusion

Identifying the DEGs will aid in the understanding of the causes and molecular mechanisms involved in ccRCC. P2RY13 may play a pivotal role in the progression and prognosis of ccRCC, potentially driving carcinogenesis though immune system mechanisms.

Construction of the prognostic model in non-metastatic renal cancer patients with venous tumor thrombus

Background

Venous system invasion is a prominent characteristic of local progression in renal cancer and treatment-naïve renal cancer patients with venous tumor thrombus (VTT) gained short natural course and poor prognosis. This study aimed to investigate the efficacy of the surgery and prognostic factors in non-metastatic renal cancer patients with VTT and to construct a nomogram prognostic model.

Methods

Clinical data of 114 non-metastatic renal cancer patients with VTT who underwent surgical treatment from January 2011 to September 2022 were retrospectively analyzed. In order to find independent risk factors of prognosis, survival analysis was performed via univariate and multivariate Cox regression models and Kaplan-Meier method. Nomogram prognostic model was established to calculate patients' risk scores. Receiver operating characteristic curve and decision curve analysis were conducted to evaluate the efficacy of the prognostic model.

Results

A total of 114 patients were included in this study and there were 48, 12, 25, 23, and 6 cases of grade 0-IV VTT. No perioperative death occurred. The 3-year probabilities of overall survival (OS) and 5-year probabilities of OS were 67% and 43.8%, respectively. Multivariate Cox regression analysis revealed that kidney tumor diameter, preoperative lactate dehydrogenase (LDH), and preoperative neutrophils were independent risk factors. Nomogram was constructed to predict prognosis in renal cancer patients with VTT based on above indicators and Mayo VTT grading. The area under the ROC curve of 1-, 2-, 3-, and 5-year OS of the patients were 0.82, 0.67, 0.57, and 0.55 respectively.

Conclusions

Surgical treatment enables renal cancer patients with VTT to gain a better prognosis. Kidney tumor diameter, preoperative LDH, and preoperative neutrophils were independent risk factors. The nomogram perfects the Mayo grading, and provides a reliable reference for evaluation of prognosis of renal cancer patients with VTT.

OSM May Serve as a Biomarker of Poor Prognosis in Clear Cell Renal Cell Carcinoma and Promote Tumor Cell Invasion and Migration

Background

Currently, the role of oncostatin M (OSM) in clear cell renal cell carcinoma (ccRCC) has not been investigated. This study will explore the impact of OSM on ccRCC expression, prognosis, and cell function.

Materials and Methods

In this study, we used The Cancer Genome Atlas (TCGA) database to evaluate OSM expression characteristics, pathogenic factor distribution, and prognostic aspects in ccRCC. We also combined this analysis with qRT-PCR to verify OSM mRNA expression levels at the tissue level. Then, the effects of OSM on the proliferation, invasion, and migration abilities of ccRCC cells were explored through CCK8, Transwell, Western blotting, and immunofluorescence experiments. Finally, the oncogenic mechanisms associated with OSM in ccRCC were explored through signaling pathway enrichment and single-cell analysis.

Results

The results demonstrated that OSM was significantly more expressed in ccRCC than in normal tissues. According to the survival analysis, OSM in ccRCC was considerably worse in the group with high expression than in the group with low expression. Also, the univariate and multivariate Cox analyses of clinical characteristics show that OSM in ccRCC may be able to predict a poor prognosis on its own as a biomarker. In vitro cellular experiments demonstrated that high OSM expression had no discernible impact on ccRCC cell proliferation compared to the control group, but it did promote tumor cell invasion and migration. Signaling pathways and single-cell analysis revealed that OSM might promote ccRCC invasion and migration through M2 macrophages.

Conclusion

In conclusion, OSM may serve as an independent poor prognostic biomarker in ccRCC and promote tumor cell invasion and migration. This discovery is expected to provide a new therapeutic target for patients with recurrent and metastatic ccRCC.

Identification of disulfidptosis-related subtypes and development of a prognosis model based on stacking framework in renal clear cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor with an unsatisfactory prognosis. This study aims to identify the expression patterns of disulfidptosis-related genes (DRGs), develop a prognostic model, and predict immunological profiles.

METHODS

First, we identified differentially expressed DRGs in TCGA-KIRC cohort and analyzed their mutational profiles, methylation levels, and interaction networks. Subsequently, we identified disulfidptosis-associated molecular subtypes and investigated their prognostic and immunological characteristics. Simultaneously, a disulfidptosis-related prognostic signature (DRPS) was developed using a two-stage stacking framework consisting of 5 machine learning models. The effect of DRPS on immune cell infiltration levels was explored using seven different algorithms, and the status and function of T cells for distinct risk-score groups were evaluated based on T cell exhaustion and dysfunction scores. Additionally, the study also examined differences in clinical characteristics and therapy efficacy between high- and low-risk groups.

RESULTS

We found two disulfidptosis-associated clusters, one of which had a poor prognosis and was linked to high immune cell infiltration but impaired T cell function. DRPS showed excellent predictive performance in all four cohorts and could accurately identified disulfidptosis-related molecular subtypes. The DRPS-based risk score was positively associated with poor prognosis, malignant pathological features, high immune cell infiltration levels, and T cell exhaustion or dysfunction, and better respond to immunotherapy and targeted therapy. Additionally, we have identified a close association between ISG20 and disulfidptosis as well as tumor immunity.

CONCLUSION

Our study identified distinct disulfidptosis-related subtypes in ccRCC patients, and constructed the highly accurate and robust DRPS based on an ensemble learning framework, which has critical reference value in clinical decision-making and individualized treatment. And this work also revealed ISG20 exhibits promising potential as a therapeutic target for ccRCC.

Genes associated with inflammation for prognosis prediction for clear cell renal cell carcinoma: a multi-database analysis

Background

Clear cell renal cell carcinoma (ccRCC) is the largest subtype of kidney tumour, with inflammatory responses characterising all stages of the tumour. Establishing the relationship between the genes related to inflammatory responses and ccRCC may help the diagnosis and treatment of patients with ccRCC.

Methods

First, we obtained the data for this study from a public database. After differential analysis and Cox regression analysis, we obtained the genes for the establishment of a prognostic model for ccRCC. As we used data from multiple databases, we standardized all the data using the surrogate variable analysis (SVA) package to make the data from different sources comparable. Next, we used a least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model of genes related to inflammation. The data used for modelling and internal validation came from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) series (GSE29609) databases. ccRCC data from the International Cancer Genome Consortium (ICGC) database were used for external validation. Tumour data from the E-MTAB-1980 cohort were used for external validation. The GSE40453 and GSE53757 datasets were used to verify the differential expression of inflammation-related gene model signatures (IRGMS). The immunohistochemistry of IRGMS was queried through the Human Protein Atlas (HPA) database. After the adequate validation of the IRGM, we further explored its application by constructing nomograms, pathway enrichment analysis, immunocorrelation analysis, drug susceptibility analysis, and subtype identification.

Results

The IRGM can robustly predict the prognosis of samples from patients with ccRCC from different databases. The verification results show that nomogram can accurately predict the survival rate of patients. Pathway enrichment analysis showed that patients in the high-risk (HR) group were associated with a variety of tumorigenesis biological processes. Immune-related analysis and drug susceptibility analysis suggested that patients with higher IRGM scores had more treatment options.

Conclusions

The IRGMS can effectively predict the prognosis of ccRCC. Patients with higher IRGM scores may be better candidates for treatment with immune checkpoint inhibitors and have more chemotherapy options.

Multi-center validation of an immune-related lncRNA signature for predicting survival and immune status of patients with renal cell carcinoma: an integrating machine learning-derived study

BACKGROUND

Long noncoding RNAs (lncRNAs) have been reported to play an important role in tumor immune modification. Nonetheless, the clinical implication of immune-associated lncRNAs in renal cell carcinoma (RCC) remains to be further explored.

METHODS

76 combinations of machine learning algorithms were integrated to develop and validate a machine learning-derived immune-related lncRNA signature (MDILS) in five independent cohorts (n = 801). We collected 28 published signatures and collated clinical variables for comparison with MDILS to verify its efficacy. Subsequently, molecular mechanisms, immune status, mutation landscape, and pharmacological profile were further investigated in different stratified patients.

RESULTS

Patients with high MDILS displayed worse overall survival than those with low MDILS. The MDILS could independently predict overall survival and convey robust performance across five cohorts. MDILS has a significantly better performance compared with traditional clinical variables and 28 published signatures. Patients with low MDILS exhibited more abundant immune infiltration and higher potency of immunotherapeutic response, while patients with high MDILS might be more sensitive to multiple chemotherapeutic drugs (e.g., sunitinib and axitinib).

CONCLUSION

MDILS is a robust and promising tool to facilitate clinical decision-making and precision treatment of RCC.

Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states

Clear cell renal cell carcinoma (ccRCC) is molecularly heterogeneous, immune infiltrated, and selectively sensitive to immune checkpoint inhibition (ICI). However, the joint tumor-immune states that mediate ICI response remain elusive. We develop spatially aware deep-learning models of tumor and immune features to learn representations of ccRCC tumors using diagnostic whole-slide images (WSIs) in untreated and treated contexts (n = 1,102 patients). We identify patterns of grade heterogeneity in WSIs not achievable through human pathologist analysis, and these graph-based "microheterogeneity" structures associate with PBRM1 loss of function and with patient outcomes. Joint analysis of tumor phenotypes and immune infiltration identifies a subpopulation of highly infiltrated, microheterogeneous tumors responsive to ICI. In paired multiplex immunofluorescence images of ccRCC, microheterogeneity associates with greater PD1 activation in CD8+ lymphocytes and increased tumor-immune interactions. Our work reveals spatially interacting tumor-immune structures underlying ccRCC biology that may also inform selective response to ICI.

TIMP1 shapes an immunosuppressive microenvironment by regulating anoikis to promote the progression of clear cell renal cell carcinoma

BACKGROUND

The association between ccRCC and Anoikis remains to be thoroughly investigated.

METHODS

Anoikis-related clusters were identified using NMF. To identify prognostic anoikis-related genes (ARGs) and establish an optimal prognostic model, univariate Cox and LASSO regression were employed. The E-MTAB-1980 cohort was utilized for external validation. Multiple algorithms were used to evaluate the immune properties of the model. GO, KEGG and GSVA analyses were employed to analyze biological pathway functions. qRT-PCR was employed to measure RNA levels of specific genes. Cell Counting Kit-8, wound healing, and Transwell chamber assays were performed to determine changes in the proliferative and metastatic abilities of A498 and 786-O cells.

RESULTS

Based on the expression of 21 prognostic ARGs, we constructed anoikis-related clusters with different prognostic and immune characteristics. The cluster A1 showed a worse prognosis, higher infiltration of immunosuppressive cells and enrichment of several oncogenic pathways. We also calculated the Anoikis Index (AI). Patients in high AI group had a worse prognosis, higher infiltration of immunosuppressive cells and higher expression of immunosuppressive checkpoints. TIMP1 exerted a tumor-promoting role in ccRCC and was significantly associated with immunosuppressive cells and checkpoints. The downregulation of TIMP1 negatively regulated ccRCC cell proliferation and metastasis.

CONCLUSIONS

ARGs played crucial roles in tumorigenesis and progression and were positively associated with a poor prognosis. AI had great accuracy in predicting the prognosis and immune characteristics of ccRCC patients. TIMP1 was significantly associated with clinicopathological variables and the immunosuppressive microenvironment, which could be exploited to design novel immunotherapies for ccRCC patients.

Circulating antigen-primed cytotoxic T-cells in patients with renal tumors treated with surgery

INTRODUCTION

Systemic immunotherapy has changed the paradigm of treatment of advanced renal cell carcinoma, but nephrectomy continues to benefit selected patients. While we continue to identify mechanisms behind drug resistance, the effect of surgery on natural anti-tumor immunity is poorly understood. Specifically, peripheral blood mononuclear cell (PBMC) profile and tumor reactive cytotoxic T lymphocytes changes secondary to tumor resection have not been extensively characterized. Hence, we aimed to evaluate the effect of nephrectomy on PMBC profile and circulating antigen-primed CD8+ T-cells for patients undergoing solid renal mass resection.

METHODS

Patients with localized or metastatic solid renal masses who underwent nephrectomy from 2016 to 2018 were enrolled. Blood samples were collected at 3 timepoints for PBMCs analysis (pre-op, 1 day, and 3 months post-op). Flow cytometry was used to identify CD11ahigh CD8+ T lymphocytes that were then further characterized according to the expression of CX3CR1/GZMB, Ki67, Bim, and PD-1. Changes in circulating CD8+ T-cells from pre-op to 1 day and 3 months post-op were evaluated using Wilcoxon signed rank tests.

RESULTS

Antigen-primed CX3CR1+GZMB+ T-cells significantly increased by 3 months after surgery among patients with RCC (0.8 × 109 cells; P = 0.01). In contrast, there was a decrease in absolute numbers of Bim+ T-cells at 3 months (-1.9 × 109 cells; P = 0.02). There were no significant absolute changes in PD-1+ (-1.4 × 109; P = 0.7) and CD11ahigh CD8+ T lymphocytes (1.3 × 109; P = 0.9). Ki67+ T-cells decreased by 3 months (-0.8 × 109; P < 0.001).

CONCLUSIONS

Nephrectomy is associated with an increase in cytolytic antigen-primed CD8+ T-cells and specific PBMC profile changes. Further studies are warranted to ascertain the role surgery may have in the restoration of anti-tumor immunity.

The effect of resveratrol, curcumin and quercetin combination on immuno-suppression of tumor microenvironment for breast tumor-bearing mice

Resveratrol, curcumin, and quercetin are the secondary metabolites from medicinal food homology plants, that have been proven their potency in cancer treatment. However, the antitumor effect of a single component is weak. So, herein, we designed an antitumor compound named RCQ composed of resveratrol, curcumin, and quercetin. This study examined the effect on tumorigenesis and development of 4T1 breast cancer-bearing mice following administering RCQ by intragastric administration. RCQ increased the recruitment of T cells and reduced the accumulation of neutrophils and macrophages in the tumor microenvironment. Meanwhile, RCQ suppressed the development of tumor-infiltrating lymphocytes into immunosuppressive cell subpopulations, including CD4+ T cells to T helper Type 2 type (Th2), tumor-associated neutrophils (TANs) to the N2 TANs, and tumor-associated macrophages (TAMs) cells to M2 TAMs. RCQ reversed the predominance of immunosuppressive infiltrating cells in the tumor microenvironment and tipped the immune balance toward an immune activation state. In vitro the study showed that RCQ significantly increased reactive oxygen species (ROS), reduce mitochondrial membrane potentials in cancer cells, and modulate pro-apoptotic Bcl-2 family members. In conclusion, RCQ can promote the ROS apoptosis mechanism of tumor cells and alleviate immunosuppression of the tumor microenvironment to enhance the anti-tumor effect.

Unraveling the transcriptome-based network of tfh cells in primary sjogren syndrome: insights from a systems biology approach

Background

Primary Sjogren Syndrome (pSS) is an autoimmune disease characterized by immune cell infiltration. While the presence of follicular T helper (Tfh) cells in the glandular microenvironment has been observed, their biological functions and clinical significance remain poorly understood.

Methods

We enrolled a total of 106 patients with pSS and 46 patients without pSS for this study. Clinical data and labial salivary gland (LSG) biopsies were collected from all participants. Histological staining was performed to assess the distribution of Tfh cells and B cells. Transcriptome analysis using RNA-sequencing (RNA-seq) was conducted on 56 patients with pSS and 26 patients without pSS to uncover the underlying molecular mechanisms of Tfh cells. To categorize patients, we employed the single-sample gene set enrichment analysis (ssGSEA) algorithm, dividing them into low- and high-Tfh groups. We then utilized gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), and deconvolution tools to explore functional and immune infiltration differences between the low- and high-Tfh groups.

Results

Patients with pSS had a higher positive rate of the antinuclear antibody (ANA), anti-Ro52, anti-SSA, anti-SSB and hypergammaglobulinaemia and higher levels of serum IgG compared to the non-pSS. Histopathologic analyses revealed the presence of Tfh cells (CD4+CXCR5+ICOS+) in germinal centers (GC) within the labial glands of pSS patients. GSEA, WGCNA, and correlation analysis indicated that the high-Tfh group was associated with an immune response related to virus-mediated IFN response and metabolic processes, primarily characterized by hypoxia, elevated glycolysis, and oxidative phosphorylation levels. In pSS, most immune cell types exhibited significantly higher infiltration levels in the high-Tfh group compared to the low-Tfh group. Additionally, patients in the Tfh-high group demonstrated a higher positive rate of the ANA, rheumatoid factor (RF), and hypergammaglobulinaemia, as well as higher serum IgG levels.

Conclusion

Our study suggests that Tfh cells may play a crucial role in the pathogenesis of pSS and could serve as potential therapeutic targets in pSS patients.

Mitochondria-related genes and metabolic profiles of innate and adaptive immune cells in primary Sjögren's syndrome

Background

Primary Sjogren's syndrome (pSS) is a prototypical systemic autoimmune disease characterised by lymphocyte infiltration and immune-complex deposition in multiple organs. The specific distribution of immune cell populations and their relationship with mitochondria remain unknown.

Methods

Histological analysis was performed to assess the specific distribution of innate and adaptive immune cell populations in labial salivary gland (LSG) samples from 30 patients with pSS and 13 patients with non-pSS. The ultrastructural morphometric features of mitochondria within immune cells were observed under the transmission electron microscope (TEM). RNA sequencing was performed on LSG samples from 40 patients with pSS and 7 non-pSS patients. The Single-sample Gene Set Enrichment Analysis (ssGSEA), ESTIMATE, and CIBERSORT algorithms and Pearson correlation coefficients were used to examine the relationship between mitochondria-related genes and immune infiltration. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify the mitochondria-specific genes and the related pathways based on the immune cell types.

Results

HE staining revealed a massive infiltration of plasma cells with abundant immunoglobulin protein distributed around phenotypically normal-appearing acinar and ductal tissues of patients with pSS. Immunohistochemical analyses revealed that innate immune cells (macrophages, eosinophils and NK cells) were distributed throughout the glandular tissue. Dominant adaptive immune cell infiltration composed of B cells, CD4⁺T cells and CD8⁺ T cells or ectopic lymphoid follicle-like structures were observed in the LSGs of patients with pSS. TEM validated the swelling of mitochondria with disorganised cristae in some lymphocytes that had invaded the glandular tissue. Subsequently, bioinformatic analysis revealed that innate and adaptive immune cells were associated with different mitochondrial metabolism pathways. Mitochondrial electron transport and respiratory chain complexes in the glandular microenvironment were positively correlated with innate immune cells, whereas amino acid and nucleic acid metabolism were negatively correlated with adaptive immune cells. In addition, mitochondrial biogenesis and mitochondrial apoptosis in the glandular microenvironment were closely associated with adaptive immune cells.

Conclusion

Innate and adaptive immune cells have distinct distribution profiles in the salivary gland tissues of patients with pSS and are associated with different mitochondrial metabolic pathways, which may contribute to disease progression.

The combination of NDUFS1 with CD4+ T cell infiltration predicts favorable prognosis in kidney renal clear cell carcinoma

Background: Kidney renal clear cell carcinoma (KIRC) is an immunogenic tumor, and immune infiltrates are relevant to patients' therapeutic response and prognosis. NDUFS1, the core subunit of mitochondrial complex I, has been reported to be associated with KIRC patients' prognosis. However, the upstream regulator for NDUFS1 and their correlations with immune infiltration remain unclear. Methods: The expression of NDUFS genes in KIRC and their influences on patients' survival were investigated by UALCAN, ENCORI, Oncomine, TIMER as well as Kaplan-Meier Plotter. miRNAs regulating NDUFS1 were predicted and analyzed by TargetScan and ENCORI. The correlations between NDUFS1 expression and immune cell infiltration or gene marker sets of immune infiltrates were analyzed via TIMER. The overall survival in high/low NDUFS1 or hsa-miR-320b expressed KIRC patients with or without immune infiltrates were analyzed via Kaplan-Meier Plotter. The combined NDUFS1 expression and/or CD4⁺ T cell infiltration on KIRC patients' overall survival were validated by multiplexed immunofluorescence (mIF) staining in tissue microarray (TMA). Furthermore, the influences of NDUFS1 expression on the chemotaxis of CD4⁺ T cells to KIRC cells were performed by transwell migration assays. Results: We found that the low expression of NDUFS1 mRNA and protein in KIRC was correlated with unfavorable patients' survival and poor infiltration of CD4⁺ T cells. In patients with decreased CD4⁺ T cell infiltration whose pathological grade less than III, TMA mIF staining showed that low expression of NDUFS1 had significantly poor OS than that with high expression of NDUFS1 did. Furthermore, hsa-miR-320b, a possible negative regulator of NDUFS1, was highly expressed in KIRC. And, low NDUFS1 or high hsa-miR-320b consistently correlated to unfavorable outcomes in KIRC patients with decreased CD4⁺ T cell infiltration. In vitro, NDUFS1 overexpression significantly increased the chemotaxis of CD4⁺ T cell to KIRC cells. Conclusion: Together, NDUFS1, upregulated by decreased hsa-miR-320b expression in KIRC patients, might act as a biomarker for CD4⁺ T cell infiltration. And, the combination of NDUFS1 with CD4⁺ T cell infiltration predicts favorable prognosis in KIRC.

Immunologic Characterization and T cell Receptor Repertoires of Expanded Tumor-infiltrating Lymphocytes in Patients with Renal Cell Carcinoma

The successful use of expanded tumor-infiltrating lymphocytes (TIL) in adoptive TIL therapies has been reported, but the effects of the TIL expansion, immunophenotype, function, and T cell receptor (TCR) repertoire of the infused products relative to the tumor microenvironment (TME) are not well understood. In this study, we analyzed the tumor samples (n = 58) from treatment-naïve patients with renal cell carcinoma (RCC), "pre-rapidly expanded" TILs (pre-REP TIL, n = 15) and "rapidly expanded" TILs (REP TIL, n = 25) according to a clinical-grade TIL production protocol, with single-cell RNA (scRNA)+TCRαβ-seq (TCRαβ sequencing), TCRβ-sequencing (TCRβ-seq), and flow cytometry. REP TILs encompassed a greater abundance of CD4⁺ than CD8⁺ T cells, with increased LAG-3 and low PD-1 expressions in both CD4⁺ and CD8⁺ T cell compartments compared with the pre-REP TIL and tumor T cells. The REP protocol preferentially expanded small clones of the CD4⁺ phenotype (CD4, IL7R, KLRB1) in the TME, indicating that the largest exhausted T cell clones in the tumor do not expand during the expansion protocol. In addition, by generating a catalog of RCC-associated TCR motifs from >1,000 scRNA+TCRαβ-seq and TCRβ-seq RCC, healthy and other cancer sample cohorts, we quantified the RCC-associated TCRs from the expansion protocol. Unlike the low-remaining amount of anti-viral TCRs throughout the expansion, the quantity of the RCC-associated TCRs was high in the tumors and pre-REP TILs but decreased in the REP TILs. Our results provide an in-depth understanding of the origin, phenotype, and TCR specificity of RCC TIL products, paving the way for a more rationalized production of TILs.

Significance

TILs are a heterogenous group of immune cells that recognize and attack the tumor, thus are utilized in various clinical trials. In our study, we explored the TILs in patients with kidney cancer by expanding the TILs using a clinical-grade protocol, as well as observed their characteristics and ability to recognize the tumor using in-depth experimental and computational tools.

Identification of immune cell infiltration profiles in renal cell carcinoma and their clinical significance

Renal cell carcinoma (RCC) is the most common malignancy of the urinary system, accounting for 3.7% of all new malignancies. The prognosis of RCC patients is still poor, especially patients in advanced stage. Limited studies have fully clarified the role of immune cell infiltration profiles in the prognosis and immunotherapy of RCC. In current study, we evaluated the abundance of the 22 tumor-infiltrating immune cells (TIICs) with CIBERSORT methods. The correlation between TIICs and clinicopathological parameters, tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS) of RCC patients were also explored. Significant correlations were obtained between TIICs subpopulation and specific clinicopathologic parameters of RCC, including age, gender, tumor grade, clinical stage, T stage and distant metastasis. Moreover, RCC patients with high level of memory activated CD4 T cells, follicular helper T cells and regulatory T cells had a worse overall survival (OS) rate. RCC patients with high level of CD 8 + T cells and M1 macrophages had a lower TIDE score and higher anti-CTLA IPS, higher anti-PD1 IPS as well as higher anti-PD1/CTLA4 IPS. Our results clarified the immune cell infiltration profiles of RCC. RCC patients with high level of CD 8 + T cell and M1 macrophages had a lower TIDE score and higher IPS, suggesting that RCC patients with high level of CD 8 + T cell and M1 macrophages may benefit from immunotherapy.

Understanding the Tumor Immune Microenvironment in Renal Cell Carcinoma

Scientific understanding of how the immune microenvironment interacts with renal cell carcinoma (RCC) has substantially increased over the last decade as a result of research investigations and applying immunotherapies, which modulate how the immune system targets and eliminates RCC tumor cells. Clinically, immune checkpoint inhibitor therapy (ICI) has revolutionized the treatment of advanced clear cell RCC because of improved outcomes compared to targeted molecular therapies. From an immunologic perspective, RCC is particularly interesting because tumors are known to be highly inflamed, but the mechanisms underlying the inflammation of the tumor immune microenvironment are atypical and not well described. While technological advances in gene sequencing and cellular imaging have enabled precise characterization of RCC immune cell phenotypes, multiple theories have been suggested regarding the functional significance of immune infiltration in RCC progression. The purpose of this review is to describe the general concepts of the anti-tumor immune response and to provide a detailed summary of the current understanding of the immune response to RCC tumor development and progression. This article describes immune cell phenotypes that have been reported in the RCC microenvironment and discusses the application of RCC immunophenotyping to predict response to ICI therapy and patient survival.

Adjuvant therapy options in renal cell carcinoma - targeting the metastatic cascade

Localized renal cell carcinoma (RCC) is primarily managed with nephrectomy, which is performed with curative intent. However, disease recurs in ~20% of patients. Treatment with adjuvant therapies is used after surgery with the intention of curing additional patients by disrupting the establishment, maturation or survival of micrometastases, processes collectively referred to as the metastatic cascade. Immune checkpoint inhibitors and vascular endothelial growth factor receptor (VEGFR)-targeting tyrosine kinase inhibitors (TKIs) have shown efficacy in the treatment of metastatic RCC, increasing the interest in the utility of these agents in the adjuvant setting. Pembrolizumab, an inhibitor of the immune checkpoint PD1, is now approved by the FDA and is under review by European regulatory agencies for the adjuvant treatment of patients with localized resected clear cell RCC based on the results of the KEYNOTE-564 trial. However, the optimal use of immunotherapy and VEGFR-targeting TKIs for adjuvant treatment of RCC is not completely understood. These agents disrupt the metastatic cascade at multiple steps, providing biological rationale for further investigating the applications of these therapeutics in the adjuvant setting. Clinical trials to evaluate adjuvant therapeutics in RCC are ongoing, and clinical considerations must guide the practical use of immunotherapy and TKI agents for the adjuvant treatment of localized resected RCC.

Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states

Clear cell renal cell carcinoma (ccRCC) is molecularly heterogeneous, immune infiltrated, and selectively sensitive to immune checkpoint inhibition (ICI). Established histopathology paradigms like nuclear grade have baseline prognostic relevance for ccRCC, although whether existing or novel histologic features encode additional heterogeneous biological and clinical states in ccRCC is uncertain. Here, we developed spatially aware deep learning models of tumor- and immune-related features to learn representations of ccRCC tumors using diagnostic whole-slide images (WSI) in untreated and treated contexts (n = 1102 patients). We discovered patterns of nuclear grade heterogeneity in WSI not achievable through human pathologist analysis, and these graph-based "microheterogeneity" structures associated with PBRM1 loss of function, adverse clinical factors, and selective patient response to ICI. Joint computer vision analysis of tumor phenotypes with inferred tumor infiltrating lymphocyte density identified a further subpopulation of highly infiltrated, microheterogeneous tumors responsive to ICI. In paired multiplex immunofluorescence images of ccRCC, microheterogeneity associated with greater PD1 activation in CD8+ lymphocytes and increased tumor-immune interactions. Thus, our work reveals novel spatially interacting tumor-immune structures underlying ccRCC biology that can also inform selective response to ICI.

Research Progress of Tumor Microenvironment Targeted Therapy for Clear Cell Renal Cell Carcinoma

Renal clear cell carcinoma (ccRCC) and the tumor microenvironment (TME) influence each other, leading to the tumor microenvironment that can guide the corresponding treatment. With the deepening of research, some treatment options have achieved good results, such as tyrosine kinase inhibitors, immune checkpoint inhibitors, and so on. As the link between TME and malignancy is constantly discovered, more targeted studies on different components of TME are increasing, and this targeted therapy is a new method for treating ccRCC, and also a current research hotspot. This review summarizes the characteristics of the ccRCC tumor microenvironment, the outcomes of different treatments, and some potential targets.

Spatial multi-omics revealed the impact of tumor ecosystem heterogeneity on immunotherapy efficacy in patients with advanced non-small cell lung cancer treated with bispecific antibody

BACKGROUND

Immunotherapy for malignant tumors has made great progress, but many patients do not benefit from it. The complex intratumoral heterogeneity (ITH) hindered the in-depth exploration of immunotherapy. Conventional bulk sequencing has masked intratumor complexity, preventing a more detailed discovery of the impact of ITH on treatment efficacy. Hence, we initiated this study to explore ITH at the multi-omics spatial level and to seek prognostic biomarkers of immunotherapy efficacy considering the presence of ITH.

METHODS

Using the segmentation strategy of digital spatial profiling (DSP), we obtained differential information on tumor and stromal regions at the proteomic and transcriptomic levels. Based on the consideration of ITH, signatures constructed by candidate proteins in different regions were used to predict the efficacy of immunotherapy.

RESULTS

Eighteen patients treated with a bispecific antibody (bsAb)-KN046 were enrolled in this study. The tumor and stromal areas of the same samples exhibited distinct features. Signatures consisting of 11 and 18 differentially expressed DSP markers from the tumor and stromal areas, respectively, were associated with treatment response. Furthermore, the spatially resolved signature identified from the stromal areas showed greater predictive power for bsAb immunotherapy response (area under the curve=0.838). Subsequently, our stromal signature was validated in an independent cohort of patients with non-small cell lung cancer undergoing immunotherapy.

CONCLUSION

We deciphered ITH at the spatial level and demonstrated for the first time that genetic information in the stromal region can better predict the efficacy of bsAb treatment.

TRIAL REGISTRATION NUMBER

NCT03838848.

Construction and verification of a novel prognostic risk model for kidney renal clear cell carcinoma based on immunity-related genes

Background: Currently, there are no useful biomarkers or prognostic risk markers for the diagnosis of kidney renal clear cell carcinoma (KIRC), although recent research has shown that both, the onset and progression of KIRC, are substantially influenced by immune-associated genes (IAGs). Objective: This work aims to create and verify the prognostic value of an immune risk score signature (IRSS) based on IAGs for KIRC using bioinformatics and public databases. Methods: Differentially expressed genes (DEGs) related to the immune systems (IAGs) in KIRC tissues were identified from The Cancer Genome Atlas (TCGA) databases. The DEGs between the tumor and normal tissues were identified using gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, a prognostic IRSS model was constructed and its prognostic and predictive performance was analyzed using survival analyses and nomograms. Kidney renal papillary cell carcinoma (KIRP) sets were utilized to further validate this model. Results: Six independent immunity-related genes (PAEP, PI3, SAA2, SAA1, IL20RB, and IFI30) correlated with prognosis were identified and used to construct an IRSS model. According to the Kaplan-Meier curve, patients in the high-risk group had significantly poorer prognoses than those of patients in the low-risk group in both, the verification set (p <0.049; HR = 1.84; 95% CI = 1.02-3.32) and the training set (p < 0.001; HR = 3.12, 95% CI = 2.23-4.37). The numbers of regulatory T cells (Tregs) were significantly positively correlated with the six immunity-related genes identified, with correlation coefficients were 0.385, 0.415, 0.399, 0.451, 0.485, and 0.333, respectively (p <0.001). Conclusion: This work investigated the association between immune infiltration, immunity-related gene expression, and severity of KIRC to construct and verify a prognostic risk model for KIRC and KIRP.

Identification and Validation of the Prognostic Panel in Clear Cell Renal Cell Carcinoma Based on Resting Mast Cells for Prediction of Distant Metastasis and Immunotherapy Response

Clear cell renal cell carcinoma (ccRCC) has a high metastatic rate, and its incidence and mortality are still rising. The aim of this study was to identify the key tumor-infiltrating immune cells (TIICs) affecting the distant metastasis and prognosis of patients with ccRCC and to construct a relevant prognostic panel to predict immunotherapy response. Based on ccRCC bulk RNA sequencing data, resting mast cells (RMCs) were screened and verified using the CIBERSORT algorithm, survival analysis, and expression analysis. Distant metastasis-associated genes were identified using single-cell RNA sequencing data. Subsequently, a three-gene (CFB, PPP1R18, and TOM1L1) panel with superior distant metastatic and prognostic performance was established and validated, which stratified patients into high- and low-risk groups. The high-risk group exhibited lower infiltration of RMCs, higher tumor mutation burden (TMB), and worse prognosis. Therapeutically, the high-risk group was more sensitive to anti-PD-1 and anti-CTLA-4 immunotherapy, whereas the low-risk group displayed a better response to anti-PD-L1 immunotherapy. Furthermore, two immune clusters revealing distinct immune, clinical, and prognosis heterogeneity were distinguished. Immunohistochemistry of ccRCC samples verified the expression patterns of the three key genes. Collectively, the prognostic panel based on RMCs is able to predict distant metastasis and immunotherapy response in patients with ccRCC, providing new insight for the treatment of advanced ccRCC.

Regulatory T Cells but Not Tumour-Infiltrating Lymphocytes Correlate with Tumour Invasion Depth in Basal Cell Carcinoma

Basal cell carcinoma (BCC) is the most common skin malignancy worldwide. Current evidence suggests tumour-infiltrating lymphocytes (TILs) may influence the clinical outcomes of patients with BCC. The present study aimed to profile the infiltrative characteristics of stromal TILs and regulatory T cells (Treg cells) in the tumour centre (TC), tumour periphery (TP), and normal adjacent tissue (NAT) of BCC. A total of 111 samples from 43 cutaneous BCC cases were examined for TIL (CD3+) and Treg cell (FOXP3+/CD3+) expression using immunohistochemical techniques. The correlations of Treg cells with TILs, invasion depth, and tumour morphological risk were analysed. We identified a high mean proportion of Treg cells within the tumour (TC = 46.9%, TP = 56.1%, NAT = 51.8%) despite a relatively low median of TILs (TC = 12.7%, TP = 10.3%, NAT = 3.6%), supporting the classification of BCC as a cold tumour. A significant positive correlation was observed between the proportion of Treg cells and sTILs (ρ = 0.325, p < 0.001), suggesting a predominant role of TILs in the infiltration of Treg cells. An inverse correlation discovered between Treg cells and tumour invasion depth (r = −0.36, p = 0.017) might indicate Treg cells’ anti-tumour capacity in BCC.

Prognostic Model for Clear-cell Renal Cell Carcinoma Based on Natural Killer Cell-related Genes

BACKGROUND

Natural killer (NK) cells are a key factor affecting progression and immune surveillance of clear-cell renal cell carcinoma (ccRCC). This study sought to construct a natural killer cell-related prognostic signature (NKRPS) to predict the outcome of ccRCC patients and to furnish guidance for finding appropriate treatment strategies.

METHODS

From the TCGA and ArrayExpress databases, transcriptomic profiles and relevant clinical information of ccRCC patients were downloaded for the TCGA cohort (n = 515) and the E-MTAB-1980 cohort (n = 101). With the univariate Cox analysis and LASSO-Cox regression algorithm, a NKRPS was built to evaluate patients' prognosis. Receiver operating characteristic (ROC) curves and calibration curves were drawn to estimate the predictive power of the prognostic model. Then, tumor microenvironment (TME), tumor mutational burden (TMB), sensitization to immune checkpoint inhibitors (ICIs) therapy and targeted drug treatment were analyzed in ccRCC patients.

RESULTS

Nine genes (BID, CCL7, CSF2, IL23A, KNSTRN, RHBDD3, PIK3R3, RNF19B and VAV3) were identified to construct a NKRPS. High-risk group displayed undesirable survival compared to low-risk group (P < .05). Moreover, the area under the curve (AUC) of ROC at 1-, 3- and 5-year were 0.766, 0.755, and 0.757, respectively. High-risk group was characterized by superior immune infiltration, higher TMB, and higher expression of 5 ICI-related genes. Additionally, this model enabled to predict the sensitivity of patients to chemotherapy drugs.

CONCLUSION

NKRPS had a strong predictive power on prognosis of ccRCC patients, which may facilitate individualized treatment and medical decision making.

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

LTB4R Promotes the Occurrence and Progression of Clear Cell Renal Cell Carcinoma (ccRCC) by Regulating the AKT/mTOR Signaling Pathway

ccRCC is highly immunogenic, yet its underlying immune-related molecular mechanisms are unknown. Leukotriene B4 Receptor 1 (LTB4R), a novel immune-related gene associated in our previous research with the prognosis of ccRCC patients, has been found in many cancers; however, its potential mechanism in renal clear carcinoma is unclear. This study was conducted to investigate LTB4R's action mechanism in renal clear cell carcinoma. First, a CCK8 assay was performed to verify LTB4R's effect on the proliferation viability of renal clear cell carcinoma cells. Scratch and transwell assays verified LTB4R's effect on the migration and invasion ability of renal clear cell carcinoma cells. Flow cytometry validated LTB4R's effect on renal clear cell carcinoma cells' apoptosis and cell cycle. A Western blot assay was conducted to further investigate LTB4R's effect on apoptosis, cell cycle, EMT process, and AKT/mTOR signaling pathway in renal clear cell carcinoma at the protein level. In vitro experiments showed that LTB4R knockdown inhibited the proliferation, migration, and invasion of renal clear cell carcinoma cells and promoted their apoptosis, whereas LTB4R overexpression promoted the proliferation, migration, and invasion of renal clear cell carcinoma cells and inhibited their apoptosis. In addition, we found that LTB4R regulated the proliferation and apoptosis of renal clear cell carcinoma cells by regulating the AKT/mTOR signaling pathway's phosphorylation process. Furthermore, we verified some of these results using bioinformatic analysis. LTB4R plays an oncogenic role in renal clear cell carcinoma; it is expected to be a molecular target for renal clear cell carcinoma treatment and a predictive biomarker for prognosis.

TLR3 serves as a novel diagnostic and prognostic biomarker and is closely correlated with immune microenvironment in three types of cancer

Background: Toll-like receptor 3 (TLR3) plays an important role in both innate and adaptive immunity, but the prognostic value of TLR3 in heterogeneous tumors and the correlations between TLR3 expression and immune infiltration of heterogeneous tumors remain unclear. Methods: We investigated the expression of TLR3 in a variety of tumors and focused on the diagnostic and prognostic values of TLR3 in kidney renal clear cell carcinoma (KIRC), pancreatic adenocarcinoma (PAAD) and brain lower grade glioma (LGG) by GEPIA, DriverDBv3, UALCAN, TIMER, LinkedOmics, STRING, GeneMANIA and FunRich, as well as the possible mechanisms of TLR3 affecting tumor prognosis were discussed. Additionally, real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was used to validate TLR3 expression in early KIRC. We also compared the expression of TLR3 in the plasma of early KIRC patients and normal controls by enzyme linked immunosorbent assay (ELISA). Results: TLR3 expression was significantly different in multiple tumors compared with paracancerous nontumor tissues. Elevated expression of TLR3 contributed to the prolonged survival outcome in KIRC patients. Suppressed expression of TLR3 contributed to the prolonged survival outcome in LGG and PAAD patients. Moreover, TLR3 was significantly elevated in stage1, grade1 and N0 of KIRC. The expression and function of TLR3 in KIRC, LGG and PAAD were closely related to tumor immune microenvironment. TRAF6 was a key gene in the interactions between TLR3 and its interacting genes. Finally, the results of RT-qPCR and ELISA indicated that TLR3 expression levels were significantly raised in renal tissue and plasma of early KIRC patients. Conclusion: TLR3 has the potential to be a diagnostic biomarker of KIRC, LGG and PAAD as well as a biomarker for evaluating the prognosis of KIRC, LGG and PAAD, particularly for the early diagnosis of KIRC. TLR3 affects tumors mainly by acting on the immune microenvironment of KIRC, LGG and PAAD. These findings could lead to new insights into the immunotherapeutic targets for KIRC, LGG, and PAAD.

A Robust and Generalizable Immune-Related Signature for Sepsis Diagnostics

High-throughput sequencing can detect tens of thousands of genes in parallel, providing opportunities for improving the diagnostic accuracy of multiple diseases including sepsis, which is an aggressive inflammatory response to infection that can cause organ failure and death. Early screening of sepsis is essential in clinic, but no effective diagnostic biomarkers are available yet. Here, we present a novel method, Recurrent Logistic Regression, to identify diagnostic biomarkers for sepsis from the blood transcriptome data. A panel including five immune-related genes, LRRN3, IL2RB, FCER1A, TLR5, and S100A12, are determined as diagnostic biomarkers (LIFTS) for sepsis. LIFTS discriminates patients with sepsis from normal controls in high accuracy (AUROC = 0.9959 on average; IC = [0.9722-1.0]) on nine validation cohorts across three independent platforms, which outperforms existing markers. Our analysis determined an accurate prediction model and reproducible transcriptome biomarkers that can lay a foundation for clinical diagnostic tests and biological mechanistic studies.

Construction of a novel prognostic signature based on the composition of tumor-infiltrating immune cells in clear cell renal cell carcinoma

Emerging evidence has uncovered that tumor-infiltrating immune cells (TIICs) play significant roles in regulating the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the exact composition of TIICs and their prognostic values in ccRCC have not been well defined. A total of 534 ccRCC samples with survival information and TIIC data from The Cancer Genome Atlas (TCGA) dataset were included in our research. The ImmuCellAI tool was employed to estimate the abundance of 24 TIICs and further survival analysis explored the prognostic values of TIICs in ccRCC. In addition, the expression levels of immunosuppressive molecules (PDL1, PD1, LAG3, and CTLA4) in the high- and low-risk groups were explored. Various subtypes of TIICs had distinct infiltrating features and most TIICs exhibited dysregulated abundance between normal and tumor tissues. Moreover, specific kinds of TIICs had encouraging prognostic values in ccRCC. Further analysis constructed a 4-TIICs signature to evaluate the prognosis of ccRCC patients. Cox regression analyses confirmed the independent prognostic role of the signature in ccRCC. Moreover, immunosuppressive molecules, including PD1, LAG3, and CTLA4, were significantly upregulated in the high-risk group and predicted poor prognosis. However, PDL1 was not changed between high- and low-risk groups and could not predict poor prognosis. To sum up, our research explored the landscape of TIICs in ccRCC and established a novel 4-TIIC prognostic signature, which could effectively predict the prognosis for patients with ccRCC. Based on this signature, we also concluded that PDL1 may not predict prognosis in ccRCC.

Strategies to overcome DC dysregulation in the tumor microenvironment

Dendritic cells (DCs) play a key role to modulate anti-cancer immunity in the tumor microenvironment (TME). They link innate to adaptive immunity by processing and presenting tumor antigens to T cells thereby initiating an anti-tumor response. However, subsets of DCs also induce immune-tolerance, leading to tumor immune escape. In this regard, the TME plays a major role in adversely affecting DC function. Better understanding of DC impairment mechanisms in the TME will lead to more efficient DC-targeting immunotherapy. Here, we review the different subtypes and functions of DCs in the TME, including conventional DCs, plasmacytoid DC and the newly proposed subset, mregDC. We further focus on how cancer cells modulate DCs to escape from the host's immune-surveillance. Immune checkpoint expression, small molecule mediators, metabolites, deprivation of pro-immunogenic and release of pro-tumorigenic cytokine secretion by tumors and tumor-attracted immuno-suppressive cells inhibit DC differentiation and function. Finally, we discuss the impact of established therapies on DCs, such as immune checkpoint blockade. Creative DC-targeted therapeutic strategies will be highlighted, including cancer vaccines and cell-based therapies.

A signature based on chromatin regulation and tumor microenvironment infiltration in clear cell renal cell carcinoma

Aims: This research aimed to construct a signature based on chromatin regulation in localized clear cell renal cell carcinoma (ccRCC). Materials & methods: Non-negative matrix factorization clustering was performed on 438 localized ccRCC cases. The immune infiltration was generated by the single-sample gene set enrichment analysis algorithm. Survival analyses were performed using the Kaplan-Meier method, and the significance of the differences was determined using the log-rank test. The risk score was constructed based on the expression of chromatin regulators to quantify chromatin modification. Results: A score system based on chromatin modification was established. The high-risk subtype was characterized by increased tumor mutation burden, whereas a low-risk score was characterized by an increase in chromatin regulator expression and better overall survival. Conclusion: This research has constructed a signature based on chromatin regulation in localized ccRCC.

Prognostic value of TIGIT in East Asian patients with solid cancers: A systematic review, meta-analysis and pancancer analysis

Background

T-cell immunoreceptor with Ig and ITIM domains (TIGIT) participates in tumor immune escape by delivering inhibitory signals to T cells. The purpose of this article was to assess the prognostic value of TIGIT and its immunological function in solid cancers.

Methods

Three databases were searched for relevant articles. The main endpoints were overall survival (OS), progression-free survival (PFS), recurrence-free survival (RFS), and disease-free survival (DFS). Hazard ratios (HR) were pooled by using fixed-effects or random-effects models. Pancancer analysis of TIGIT was performed based on public online databases, mainly The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and UCSC Xena. The possible relationships between TIGIT expression and the tumor microenvironment (TME), infiltration of immune cells, immune-related genes, tumor mutation burden (TMB), and microsatellite instability (MSI) were revealed in this article.

Results

Sixteen studies met the inclusion criteria. High expression of TIGIT was associated with worse OS [HR= 1.73, 95% confidence interval (CI) 1.50, 1.99], PFS (HR = 1.53, 95% CI [1.25, 1.88]), RFS (HR = 2.40, 95% CI [1.97, 2.93]), and DFS (HR= 6.57, 95% CI [0.73, 59.16]) in East Asian patients with solid cancers. TIGIT expression was positively correlated with immune infiltration scores and infiltration of CD8 T lymphocytes in all of the cancers included. TIGIT was found to be coexpressed with the genes encoding immunostimulators, immunoinhibitors, chemokines, chemokine receptors, and major histocompatibility complex (MHC), especially in gastroesophageal cancer. TMB and MSI were also associated with TIGIT upregulation in diverse kinds of cancers.

Conclusion

High expression of TIGIT is associated with poorer prognosis in East Asian patients with solid cancers. TIGIT is a novel prognostic biomarker and immunotherapeutic target for various solid cancers because of its activity in cancer immunity and tumorigenesis.

Clinical significance and oncogenic function of NR1H4 in clear cell renal cell carcinoma

BACKGROUND

Nuclear receptor subfamily 1 group H member 4 (NR1H4) have been reported in various cancer types, however, little is known about the clinical values and biological function in clear cell Renal cell carcinoma (ccRCC).

METHODS

The expression pattens of NR1H4 in ccRCC were investigated in clinical specimens, cell lines and publicly‑available databases. Cell Counting Kit-8 (CCK-8), colony formation, 5-ethynyl-2' -deoxyuridine (EdU), transwell and cell wound healing assays were performed to assess the biological functions of NR1H4 in 786-O ccRCC cells. Gene set enrichment analysis (GSEA), Flow Cytometry, quantitative real-time PCR (qRT-PCR), western blot and immunofluorescence were performed to explore the molecular mechanism of NR1H4 in ccRCC. We explored the early diagnostic value, prognostic value, genetic mutation and DNA methylation of NR1H4 by a comprehensive bioinformatics analysis based on the data published in the following databases: The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Kaplan-Meier Plotter, Gene Expression Profiling Interactive Analysis (GEPIA), UNIVERSITY OF CALIFORNIA SANTA CRUZ Xena (UCSC Xena), cBio Cancer Genomics Portal, MethSurv, SurvivalMeth and The University of ALabama at Birmingham CANcer data analysis Portal (UALCAN). Its correlation with tumor-infiltrating immune cells in ccRCC was analyzed by Tumor Immune Estimation Resource 2.0 (TIMER2.0) and Tumor Immune System Interactions Database (TISIDB).

RESULTS

In this study, NR1H4 was found to be highly expressed in ccRCC tissues and ccRCC cell lines. Knockdown of NR1H4 significantly suppressed cancer cell proliferation, migration and invasion. Mechanistically, tumor-associated signaling pathways were enriched in the NR1H4 overexpression group and si-NR1H4 could induce the downregulation of Cyclin E2 (CCNE2). By bioinformatics analysis, NR1H4 was identified as highly expressed in stage I ccRCC with a high diagnostic accuracy (area under the receiver operating characteristic curve > 0.8). Genetic alteration and DNA methylation of NR1H4 were significantly associated with prognosis in ccRCC patients. Moreover, NR1H4 expression associated with immune cell infiltration levels in ccRCC, which provides a new idea for immunotherapy.

CONCLUSIONS

Our study indicated that NR1H4 might be a potential tumor biomarker and therapeutic target for ccRCC which could promote cancer cell proliferation, migration and invasion via regulating CCNE2.

T cell proliferation-related genes: Predicting prognosis, identifying the cold and hot tumors, and guiding treatment in clear cell renal cell carcinoma

Background: Immunotherapy has become a new direction of current research because the effect of traditional radiotherapy and chemotherapy on clear cell renal cell carcinoma (ccRCC) is not satisfactory. T cell proliferation-related genes (TRGs) play a pivotal role in tumor progression by regulating the proliferation, activity, and function of immune cells. The purpose of our study is to construct and verify a prognostic model based on TRGs and to identify tumor subtypes that may guide treatment through comprehensive bioinformatics analyses.

Methods: RNA sequencing data, clinical information, and somatic mutation data of ccRCC are obtained from The Cancer Genome Atlas (TCGA) database. We identified the prognosis-related TRGs which were differentially expressed between normal and tumor tissues. After dividing the patients into a train set and a test set according to proportion 1:1 randomly, the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were performed to construct a risk-stratified model. Its prediction performance was verified. Then, Gene Set Enrichment Analysis (GSEA), principal component analysis (PCA), tumor microenvironment (TME) analysis, and the half-maximal inhibitory concentration (IC50) prediction were performed between the different groups of patients. To further discuss the immunotherapy between hot and cold tumors, we divided all patients into two clusters based on TRGs through unsupervised learning. Analyzing the gene mutation and calculating the tumor mutation burden (TMB), we further explored the relationship between somatic mutations and grouping or clustering.

Results: Risk-stratified model and nomogram predict the prognosis of ccRCC patients accurately. Functional enrichment analyses suggested that TRGs mainly focused on the biological pathways related to tumor progression and immune response. Different tumor microenvironment, drug resistance, and TMB can be distinguished clearly according to both risk stratification and tumor subtype clustering.

Conclusion: In this study, a new stratification model of ccRCC based on TRGs was established, which can accurately predict the prognosis of patients. IC50 prediction may guide the application of anti-tumor drugs. The distinction between hot and cold tumors provides a reference for clinical immunotherapy.

Identification of EZH2 as Cancer Stem Cell Marker in Clear Cell Renal Cell Carcinoma and the Anti-Tumor Effect of Epigallocatechin-3-Gallate (EGCG)

The aim of the study was to develop a new therapeutic strategy to target cancer stem cells (CSCs) in clear cell renal cell carcinoma (ccRCC) and to identify typical CSC markers to improve therapy effectiveness. It was found that the corrected-mRNA expression-based stemness index was upregulated in kidney renal clear cell carcinoma (KIRC) tissues compared to non-tumor tissue and increased with higher tumor stage and grade. EZH2 was identified as a CSC marker and prognosis factor for KIRC patients. The expression of EZH2 was associated with several activated tumor-infiltrating immune cells. High expression of EZH2 was enriched in immune-related pathways, low expression was related to several metabolic pathways. Epigallocatechin-3-gallate (EGCG) was identified as the most potent suppressor of EZH2, was able to inhibit viability, migration, and invasion, and to increase the apoptosis rate of ccRCC CSCs. KIF11, VEGF, and MMP2 were identified as predictive EGCG target genes, suggesting a potential mechanism of how EZH2 might regulate invasiveness and migration. The percentages of FoxP3+ Treg cells in the peripheral blood mononuclear cells of ccRCC patients decreased significantly when cultured with spheres pretreated with EGCG plus sunitinib compared to spheres without treatment. Our findings provide new insights into the treatment options of ccRCC based on targeting CSCs.

Immune checkpoint receptor VISTA on immune cells is associated with expression of T-cell exhaustion marker TOX and worse prognosis in renal cell carcinoma with venous tumor thrombus

PURPOSE

The study aimed to determine the expression of VISTA and TOX within venous tumor thrombus and primary clear cell renal cell carcinoma (ccRCC) and to assess their prognostic value.

METHODS

The study enrolled 82 patients with ccRCC and coexisting venous tumor thrombus treated radically from 2012 to 2019 in two tertiary centers. Tissue microarrays were prepared and stained with respective antibodies. The expression of markers was assessed separately on tumor cells (TCs) and/or tumor-associated immune cells (TAICs).

RESULTS

TOX expression was positively correlated with the percentage of VISTA-positive TAICs in venous thrombus (p = 0.011), but not in the primary tumor (p = 0.674). High TOX expression was associated with a higher percentage of PD-L1-positive TAICs in both compartments (p = 0.001, p = 0.011, respectively). Positive expression of VISTA on TAICs was associated with PD-L1 expression on TCs (p = 0.005) and TAICs (p = 0.004) in the primary tumor, and only with PD-L1 on TAICs in thrombus (p = 0.006). The presence of VISTA-positive TAICs in venous thrombus was significantly more common in females (p = 0.034), and positively correlated with metastases (p = 0.028), and tumor necrosis (p = 0.013). The cases with VISTA-positive TAICs in venous tumor thrombi had significantly shorter OS than VISTA-negative cases (p = 0.041).

CONCLUSION

For the first time, we demonstrated the expression of VISTA- and TOX-positive TAICs in the venous tumor thrombus. We found the association between immune checkpoint receptors and T cell exhaustion markers in both tumor mass and venous thrombus. Finally, we demonstrated that abundance of VISTA-positive TAICs in venous tumor thrombus correlates with worse outcomes in ccRCC.

The potential value of cuprotosis (copper-induced cell death) in the therapy of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for 75% of the total incidence of renal cancer, and every year the number of morbidity and mortality increases, posing a serious threat to public health. The current main treatment methods for kidney cancer include drug-targeted therapy and immunotherapy. Although there are many treatment options for kidney cancer, they all have limitations, including drug resistance, unsatisfied long-term benefits, and adverse effects. Therefore, it is crucial to identify more effective therapeutic targets. As a newly discovered mechanism of cell death, copper-induced cell death (cuprotosis) is closely related to changes in cell metabolism, particularly in copper metabolism. Current studies have shown that the key signaling pathway of cuprotosis, the FDX1 (Ferredoxin 1)-LIAS (Lipoic Acid Synthetase) axis, plays an important role in the regulation of cellular oxidative stress, which can directly affect cell survival via inducing or promoting cancer cell death. Therefore, we speculated that this regulatory cell death mechanism might serve as a potential therapeutic target for the clinical treatment of renal cancer. To test this, we first performed a pan-cancer analysis based on cuprotosis-related genomic and transcriptomic levels to reveal the expression of cuprotosis in cancer. Next, GSVA-clustering analysis was performed with data from the Cancer Genome Atlas (TCGA) cohort, and the cohort was divided into three clusters according to the gene enrichment levels of cuprotosis marker genes. In addition, we analyzed the potential of using cuprotosis in clinical treatment from multiple perspectives, including chemotherapeutic drug susceptibility test, immune target inhibition treatment responsiveness, and histone modification. Combining the results of multi-omics analysis, we focused on the feasibility of this novel regulatory cell death mechanism in ccRCC treatment and further constructed a prognostic model. Finally, we verified our results by integrating the patient's gene expression information and radiomics information. Our study provides new insights into the development and clinical application of targeting cuprotosis pathway.

Prognostic Gene Expression-Based Signature in Clear-Cell Renal Cell Carcinoma

The inaccuracy of the current prognostic algorithms and the potential changes in the therapeutic management of localized ccRCC demands the development of an improved prognostic model for these patients. To this end, we analyzed whole-transcriptome profiling of 26 tissue samples from progressive and non-progressive ccRCCs using Illumina Hi-seq 4000. Differentially expressed genes (DEG) were intersected with the RNA-sequencing data from the TCGA. The overlapping genes were used for further analysis. A total of 132 genes were found to be prognosis-related genes. LASSO regression enabled the development of the best prognostic six-gene panel. Cox regression analyses were performed to identify independent clinical prognostic parameters to construct a combined nomogram which includes the expression of CERCAM, MIA2, HS6ST2, ONECUT2, SOX12, TMEM132A, pT stage, tumor size and ISUP grade. A risk score generated using this model effectively stratified patients at higher risk of disease progression (HR 10.79; p < 0.001) and cancer-specific death (HR 19.27; p < 0.001). It correlated with the clinicopathological variables, enabling us to discriminate a subset of patients at higher risk of progression within the Stage, Size, Grade and Necrosis score (SSIGN) risk groups, pT and ISUP grade. In summary, a gene expression-based prognostic signature was successfully developed providing a more precise assessment of the individual risk of progression.