Heterogeneity in tertiary lymphoid structures predicts distinct prognosis and immune microenvironment characterizations of clear cell renal cell carcinoma.

BACKGROUND: Tertiary lymphoid structures (TLS) are organized aggregates of immune cells that develop postnatally in non-lymphoid tissues and are associated with pathological conditions. TLS typically comprise B-cell follicles containing and are encompassed by T- cell zones and dendritic cells. The prognostic and predictive value of TLS in the tumor microenvironment (TME) as potential mediators of antitumor immunity have gained interest. However, the precise relationship between localization and maturation of TLS and the clinical outcome of their presence in clear cell renal cell carcinoma (ccRCC) is yet to be elucidated. METHODS: Immunohistochemistry and multispectral fluorescence were used to evaluate the TLS heterogeneity along with TME cell-infiltrating characterizations. A thorough investigation of the prognostic implications of the TLS heterogeneity in 395 patients with ccRCC from two independent cohorts was conducted. Associations between TLS heterogeneity and immunologic activity were assessed by quantifying the immune cell infiltration. RESULTS: Infiltrated TLS were identified in 34.2% of the ccRCC samples (N=395). These TLS were found to be tumor-proximal, tumor-distal, or both in 37.8%, 74.1%, and 11.9% of the TLS-positive cases, respectively. A higher proportion of early TLS was found in tumor-distal TLS (p=0.016), while tumor-proximal TLS primarily comprised secondary follicle-like structures (p=0.004). In the main study cohort (Fudan University Shanghai Cancer Center, N=290), Kaplan-Meier analyses revealed a significant correlation between the presence of tumor-proximal TLS and improved progression-free survival (PFS, p<0.001) and overall survival (OS, p=0.002). Conversely, the presence of tumor-distal TLS was associated with poor PFS (p=0.02) and OS (p=0.021). These findings were further validated in an external validation set of 105 patients with ccRCC. Notably, the presence of mature TLS (namely secondary follicle-like TLS, with CD23+ germinal center) was significantly associated with better clinical outcomes in patients with ccRCC. Furthermore, novel nomograms incorporating the presence of tumor-proximal TLS demonstrated remarkable predictability for the 8-year outcomes of resected ccRCC (area under the curve >0.80). Additionally, ccRCC samples with tumor-distal TLS enriched with primary follicle-like TLS exhibited higher programmed death-ligand 1 tumor-associated macrophages levels and regulatory T cells infiltration in the tumor-distal region, indicative of a suppressive TME. CONCLUSION: This study for the first time elucidates the impact of TLS localization and maturation heterogeneities on the divergent clinical outcomes of ccRCC. The findings reveal that most TLS in ccRCC are located in the tumor-distal area and are associated with immature, immunosuppressive characterizations. Furthermore, our findings corroborate previous research demonstrating that tumor-proximal TLS were associated with favorable clinical outcomes.

Hexokinase 3 dysfunction promotes tumorigenesis and immune escape by upregulating monocyte/macrophage infiltration into the clear cell renal cell carcinoma microenvironment.

Purpose: This study aimed to identify the potential prognostic role of HK3 and provide clues about glycolysis and the microenvironmental characteristics of ccRCC. Methods: Based on the Cancer Genome Atlas (TCGA, n = 533) and Gene expression omnibus (GEO) (n = 127) databases, real-world (n = 377) ccRCC cohorts, and approximately 15,000 cancer samples, the prognostic value and immune implications of HK3 were identified. The functional effects of HK3 in ccRCC were analyzed in silico and in vitro. Results: The large-scale findings suggested a significantly higher HK3 expression in ccRCC tissues and the predictive efficacy of HK3 for tumor progression and a poor prognosis. Next, the subgroup survival and Cox regression analyses showed that HK3 serves as a promising and independent predictive marker for the prognosis and survival of patients with ccRCC from bioinformatic databases and real-world cohorts. Subsequently, we found that HK3 could be used to modulate glycolysis and the malignant behaviors of ccRCC cells. The comprehensive results suggested that HK3 is highly correlated with the abundance of immune cells, and specifically stimulates the infiltration of monocytes/macrophages presenting surface markers, regulates the immune checkpoint molecules PD-1 and CTLA-4 of exhaustive T cells, restrains the immune escape of tumor cells, and prompts the immune-rejection microenvironment of ccRCC. Conclusion: In conclusion, the large-scale data first revealed that HK3 could affect glycolysis, promote malignant biologic processes, and predict the aggressive progression of ccRCC. HK3 may stimulate the abundance of infiltrating monocytes/macrophages presenting surface markers and regulate the key molecular subgroups of immune checkpoint molecules of exhaustive T cells, thus inducing the microenvironmental characteristics of active anti-tumor immune responses.

Identification and validation of novel metastasis-related signatures of clear cell renal cell carcinoma using gene expression databases.

Patients with clear cell renal cell carcinoma (ccRCC) typically face aggressive disease progression when metastasis occurs. Here, we screened and identified differentially expressed genes in three microarray datasets from the Gene Expression Omnibus database. We identified 112 differentially expressed genes with functional enrichment as candidate prognostic biomarkers. Lasso Cox regression suggested 10 significant oncogenic hub genes involved in earlier recurrence and poor prognosis of ccRCC. Receiver operating characteristic curves validated the specificity and sensitivity of the Cox regression penalty used to predict prognosis. The area under the curve indexes of the integrated genes scores were 0.758 and 0.772 for overall and disease-free survival, respectively. The prognostic values of ADAMTS9, C1S, DPYSL3, H2AFX, MINA, PLOD2, RUNX1, SLC19A1, TPX2, and TRIB3 were validated through an analysis of 10 hub genes in 380 patients with ccRCC from a real-world cohort. The expression levels of were of high prognostic value for predicting metastatic potential. These findings will likely significantly contribute to our understanding of the underlying mechanisms of ccRCC, which will enhance efforts to optimize therapy.

Genome-wide analyses of the prognosis-related mRNA alternative splicing landscape and novel splicing factors based on large-scale low grade glioma cohort.

Alternative splicing (AS) changes are considered to be critical in predicting treatment response. Our study aimed to investigate differential splicing patterns and to elucidate the role of splicing factor (SF) as prognostic markers of low-grade glioma (LGG). We downloaded RNA-seq data from a cohort of 516 LGG tumors in The Cancer Genome Atlas and analyzed independent prognostic factors using LASSO regression and Cox proportional regression to build a network based on the correlation between SF-related survival AS events. We collected 100 patients from our center for immunohistochemistry and analyzed survival using χ2 test and Cox and Kaplan-Meier analyses. A total of 9,616 AS events related to LGG were screened and identified as well as established related models. Through analyzing specific splicing patterns in LGG, we screened 16 genes to construct a prognostic model to stratify the risk of LGG patients. Validation revealed that the expression level of the prognostic model in LGG tissue was increased, and patients with high expression showed worse prognosis. In summary, we demonstrated the role of SFs and AS events in the progression of LGG, which may provide insights into the clinical significance and aid the future exploration of LGG-associated AS.

Large-scale transcriptome profiles reveal robust 20-signatures metabolic prediction models and novel role of G6PC in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common and highly malignant pathological type of kidney cancer. We sought to establish a metabolic signature to improve post-operative risk stratification and identify novel targets in the prediction models for ccRCC patients. A total of 58 metabolic differential expressed genes (MDEGs) were identified with significant prognostic value. LASSO regression analysis constructed 20-mRNA signatures models, metabolic prediction models (MPMs), in ccRCC patients from two cohorts. Risk score of MPMs significantly predicts prognosis for ccRCC patients in TCGA (P < 0.001, HR = 3.131, AUC = 0.768) and CPTAC cohorts (P = 0.046, HR = 2.893, AUC = 0.777). In addition, G6PC, a hub gene in PPI network of MPMs, shows significantly prognostic value in 718 ccRCC patients from multiply cohorts. Next, G6Pase was detected high expressed in normal kidney tissues than ccRCC tissues. It suggested that low G6Pase expression significantly correlated with poor prognosis (P < 0.0001, HR = 0.316) and aggressive progression (P < 0.0001, HR = 0.414) in 322 ccRCC patients from FUSCC cohort. Meanwhile, promoter methylation level of G6PC was significantly higher in ccRCC samples with aggressive progression status. G6PC significantly participates in abnormal immune infiltration of ccRCC microenvironment, showing significantly negative association with check-point immune signatures, dendritic cells, Th1 cells, etc. In conclusion, this study first provided the opportunity to comprehensively elucidate the prognostic MDEGs landscape, established novel prognostic model MPMs using large-scale ccRCC transcriptome data and identified G6PC as potential prognostic target in 1,040 ccRCC patients from multiply cohorts. These finding could assist in managing risk assessment and shed valuable insights into treatment strategies of ccRCC.