Tumor-Infiltrating and Peripheral Blood T-cell Immunophenotypes Predict Early Relapse in Localized Clear Cell Renal Cell Carcinoma

Immunomodulatory role of tumor microenvironment on oncological outcomes in advanced laryngeal cancer

BACKGROUND

The study evaluated the prognostic impact of the immune microenvironment in LSCC with markers of major immune cells to identify the key determinants of short-term disease-free survival (ST DFS) and reveal factors related to disease progression.

METHODS

The study cohort included 61 patients who underwent total laryngectomy, 83.6% of whom were male with a mean age of 64.3 years at the time of surgery. Twenty-five patients had long term DFS (over 5 years), 8 - had moderate DFS (between 2 and 5 years), and 28 had short-term DFS (less than 2 years). Immunohistochemical staining and evaluation were performed on samples collected after the laryngectomy.

RESULTS

The samples' assessment revealed that the mean expression of all analysed markers was the highest both in stroma and the tumor compartment for short term DFS (ST DFS) patients. Analysis confirmed that a high stromal density of CD8 cells (p = 0.038) significantly correlated with DFS, and that the increased presence of CD57 cells (p = 0.021) was significantly associated with ST DFS. Moreover, the high density of CD68 cells in the tumor epithelial compartment had a negative prognostic impact on DFS (p = 0.032). Analysis of overall survival in the studied cohort with Kaplan-Meyer curves revealed that a high stromal density of CD68 cells was a significant negative predictor of OS (p = 0.008).

CONCLUSIONS

The observed associations of CD68 cells infiltration with progression and prognosis in patients with LSCC provide potential screening and therapeutic opportunities for patients with unfavourable outcomes.

PD1/PD-L1 blockade in clear cell renal cell carcinoma: mechanistic insights, clinical efficacy, and future perspectives

The advent of PD1/PD-L1 inhibitors has significantly transformed the therapeutic landscape for clear cell renal cell carcinoma (ccRCC). This review provides an in-depth analysis of the biological functions and regulatory mechanisms of PD1 and PD-L1 in ccRCC, emphasizing their role in tumor immune evasion. We comprehensively evaluate the clinical efficacy and safety profiles of PD1/PD-L1 inhibitors, such as Nivolumab and Pembrolizumab, through a critical examination of recent clinical trial data. Furthermore, we discuss the challenges posed by resistance mechanisms to these therapies and potential strategies to overcome them. We also explores the synergistic potential of combination therapies, integrating PD1/PD-L1 inhibitors with other immunotherapies, targeted therapies, and conventional modalities such as chemotherapy and radiotherapy. In addition, we examine emerging predictive biomarkers for response to PD1/PD-L1 blockade and biomarkers indicative of resistance, providing a foundation for personalized therapeutic approaches. Finally, we outline future research directions, highlighting the need for novel therapeutic strategies, deeper mechanistic insights, and the development of individualized treatment regimens. Our work summarizes the latest knowledge and progress in this field, aiming to provide a valuable reference for improving clinical efficacy and guiding future research on the application of PD1/PD-L1 inhibitors in ccRCC.

Influence of cryoablation versus operation on circulating lymphocyte subsets in patients with early-stage renal cell carcinoma

Immune response is known to play an important role in local tumor control especially in renal cell carcinoma (RCC), which is considered highly immunogenic. For localized tumors, operative resection or local ablative procedures such as cryoablation are common therapeutical options. For thermal ablative procedures such as cryoablation, additional immunological anti-tumor effects have been described.The purpose of this prospective study was to determine changes in peripheral blood circulating lymphocytes and various of their subsets in RCC patients treated with cryoablation or surgery in a longitudinal approach using extensive flow cytometry. Additionally, lymphocytes of RCC patients were compared to a healthy control group.We included 25 patients with RCC. Eight underwent cryoablation and 17 underwent surgery. Univariate and multivariable analysis revealed significantly lower values of B cells, CD4 and CD8 T cells, and various of their subsets in the treatment groups versus the healthy control group. Comparing the two different therapeutical approaches, a significant decline of various lymphocyte subsets with a consecutive normalization after three months was seen for the surgery group, whereas cryoablation led to increased values of CD69 + CD4 + and CD69 + CD8 + cell counts as well as memory CD8 + cells after three months.Treatment-naïve RCC patients showed lower peripheral blood lymphocyte counts compared to healthy controls. The post-treatment course revealed different developments of lymphocytes in the surgery versus cryoablation group, and only cryoablation seems to induce a sustained immunological response after three months.

Immune Phenotype-Genotype Associations in Primary Clear Cell Renal Cell Carcinoma and Matched Metastatic Tissue

Adjuvant immunotherapy has been recently recommended for patients with metastatic clear cell renal cell carcinoma (ccRCC), but there are no tissue biomarkers to predict treatment response in ccRCC. Potential predictive biomarkers are mainly assessed in primary tumor tissue, whereas metastases (METs) remain understudied. To explore potential differences between genomic alterations and immune phenotypes in primary tumors and their matched METs, we analyzed primary tumors (PTs) of 47 ccRCC patients and their matched distant METs by comprehensive targeted parallel sequencing, whole-genome copy number variation analysis, determination of microsatellite instability, and tumor mutational burden. We quantified the spatial distribution of tumor-infiltrating CD8+ T cells and coexpression of the T-cell-exhaustion marker thymocyte selection-associated high mobility group box (TOX) by digital immunoprofiling and quantified tertiary lymphoid structures. Most METs were pathologically "cold." Inflamed, pathologically "hot" PTs were associated with decreased disease-free survival, worst for patients with high levels of CD8+TOX+ T cells. Interestingly, inflamed METs showed a relative increase in exhausted CD8+TOX+ T cells and increased accumulative size of tertiary lymphoid structures compared with PTs. Integrative analysis of molecular and immune phenotypes revealed BAP1 and CDKN2A/B deficiency to be associated with an inflamed immune phenotype. Our results highlight the distinct spatial distribution and differentiation of CD8+ T cells at metastatic sites, and the association of an inflamed microenvironment with specific genomic alterations.

Effect of HLA Genotype on Anti-PD-1 Antibody Treatment for Advanced Renal Cell Carcinoma in the SNiP-RCC Study

Immune checkpoint blockade therapies are widely used for cancer treatment, including advanced renal cell carcinoma (RCC). This study aimed to investigate the impact of zygosity in HLA genes and individual HLA genotypes on the efficacy of an anti-PD-1 Ab, nivolumab, in treating advanced RCC. Patient enrollment was conducted across 23 institutions in Japan from August 19, 2019, to September 30, 2020, with follow-up concluding on March 31, 2021. HLA genotype imputation of HLA-A, B, and C, DQB1, and DRB1 loci was performed. Among 222 patients, the presence of at least one homozygosity of the HLA-II allele significantly improved the best objective response (hazard ratio, 0.34; 95% confidence interval, 0.21-0.96; p = 0.042). The HLA evolutionary divergence (HED) of the HLA-A and HLA-B loci was higher than the HLA-C (p < 0.0001 and p < 0.0001, respectively), with high HED of the HLA-B locus correlating to clinical benefits in nivolumab treatment (hazard ratio, 0.44; 95% confidence interval, 0.21-0.90; p = 0.024) and improving cancer-specific survival compared with the low group (p = 0.0202). Additionally, high HED of the HLA-B locus was correlated with the number of infiltrated CD8+ cells in the tumor microenvironment (correlation coefficient, 0.4042). These findings indicate that the diversity of the HLA-B locus plays a significant role in the anti-tumor effect of nivolumab treatment in advanced RCC, potentially offering insights for improved risk stratification in nivolumab treatment and leading to better medical management of advanced RCC.

Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours

Although more than a decade has passed since the approval of immune checkpoint inhibitors (ICIs) for the treatment of melanoma and non-small-cell lung, breast and gastrointestinal cancers, many patients still show limited response. US Food and Drug Administration (FDA)-approved biomarkers include programmed cell death 1 ligand 1 (PDL1) expression, microsatellite status (that is, microsatellite instability-high (MSI-H)) and tumour mutational burden (TMB), but these have limited utility and/or lack standardized testing approaches for pan-cancer applications. Tissue-based analytes (such as tumour gene signatures, tumour antigen presentation or tumour microenvironment profiles) show a correlation with immune response, but equally, these demonstrate limited efficacy, as they represent a single time point and a single spatial assessment. Patient heterogeneity as well as inter- and intra-tumoural differences across different tissue sites and time points represent substantial challenges for static biomarkers. However, dynamic biomarkers such as longitudinal biopsies or novel, less-invasive markers such as blood-based biomarkers, radiomics and the gut microbiome show increasing potential for the dynamic identification of ICI response, and patient-tailored predictors identified through neoadjuvant trials or novel ex vivo tumour models can help to personalize treatment. In this Perspective, we critically assess the multiple new static, dynamic and patient-specific biomarkers, highlight the newest consortia and trial efforts, and provide recommendations for future clinical trials to make meaningful steps forwards in the field.

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Highly expressed of BID indicates poor prognosis and mediates different tumor microenvironment characteristics in clear cell renal cell carcinoma

BACKGROUND

Studies have found that BH3 interacting domain death agonist (BID) is closely related to the occurrence and development of many kinds of tumors. However, little attention has been paid to the situation of BID in clear cell renal cell carcinoma (ccRCC). So, our aim was to explore the effect of BID in ccRCC.

METHODS

Survival analysis, ROC curve, correlation analysis and Cox regression analysis were executed to analyze the prognostic value and clinical correlation of BID in ccRCC. The risk prognosis model was constructed in the training cohort and further validated in the internal testing cohort, ICGC cohort, and GEO cohort. Transcriptome sequencing and immunohistochemical staining of clinical specimens were used to validate the results of bioinformatics analysis. The GSEA, ESTIMATE algorithm, CIBERSORT algorithm, ssGSEA, TIDE score, correlation and difference analysis were used to analyze the effects of BID on immune infiltration in tumor microenvironment (TME).

RESULTS

BID was highly expressed in ccRCC tissues, which was verified by transcriptome sequencing and immunohistochemical staining of clinical specimens. Patients with high expression of BID had a worse prognosis. BID is an independent prognostic factor for ccRCC. The prognostic model based on BID can accurately predict the prognosis of patients in different cohorts. In addition, the expression levels of BID was closely related to immunomodulatory molecules such as PD-1, LAG3, and CTLA4. Enrichment analysis indicated that BID was significantly enriched in immune-related responses and cancer-related pathways. The change of BID expression mediates different characteristics of immune infiltration in TME.

CONCLUSIONS

BID is highly expressed in ccRCC, which is a reliable biomarker of ccRCC prognosis. It is closely related to TME, and may be a potential target for immunotherapy in patients with ccRCC.

Combination of plasma MMPs and PD-1-binding soluble PD-L1 predicts recurrence in gastric cancer and the efficacy of immune checkpoint inhibitors in non-small cell lung cancer

Background

The tumor microenvironment (TME) impacts the therapeutic efficacy of immune checkpoint inhibitors (ICIs). No liquid biomarkers are available to evaluate TME heterogeneity. Here, we investigated the clinical significance of PD-1-binding soluble PD-L1 (bsPD-L1) in gastric cancer (GC) patients and non-small cell lung cancer (NSCLC) patients treated with PD-1/PD-L1 blockade.

Methods

We examined bsPD-L1, matrix metalloproteinases (MMPs), and IFN-γ levels in plasma samples from GC patients (n = 117) prior to surgery and NSCLC patients (n = 72) prior to and 2 months after ICI treatment. We also examined extracellular matrix (ECM) integrity, PD-L1 expression, and T cell infiltration in tumor tissues from 25 GC patients by Elastica Masson-Goldner staining and immunohistochemical staining for PD-L1 and CD3, respectively.

Results

bsPD-L1 was detected in 17/117 GC patients and 16/72 NSCLC patients. bsPD-L1 showed strong or moderate correlations with plasma MMP13 or MMP3 levels, respectively, in both GC and NSCLC patients. bsPD-L1 expression in GC was associated with IFN-γ levels and intra-tumoral T cell infiltration, whereas MMP13 levels were associated with loss of ECM integrity, allowing tumor cells to access blood vessels. Plasma MMP3 and MMP13 levels were altered during ICI treatment. Combined bsPD-L1 and MMP status had higher predictive accuracy to identify two patient groups with favorable and poor prognosis than tumor PD-L1 expression: bsPD-L1+MMP13high in GC and bsPD-L1+(MMP3 and MMP13)increased in NSCLC were associated with poor prognosis, whereas bsPD-L1+MMP13low in GC and bsPD-L1+(MMP3 or MMP13)decreased in NSCLC were associated with favorable prognosis.

Conclusion

Plasma bsPD-L1 and MMP13 levels indicate T cell response and loss of ECM integrity, respectively, in the TME. The combination of bsPD-L1 and MMPs may represent a non-invasive tool to predict recurrence in GC and the efficacy of ICIs in NSCLC.

FOXO1 enhances CAR T cell stemness, metabolic fitness and efficacy

Chimeric antigen receptor (CAR) T cell therapy has transformed the treatment of haematological malignancies such as acute lymphoblastic leukaemia, B cell lymphoma and multiple myeloma1-4, but the efficacy of CAR T cell therapy in solid tumours has been limited5. This is owing to a number of factors, including the immunosuppressive tumour microenvironment that gives rise to poorly persisting and metabolically dysfunctional T cells. Analysis of anti-CD19 CAR T cells used clinically has shown that positive treatment outcomes are associated with a more 'stem-like' phenotype and increased mitochondrial mass6-8. We therefore sought to identify transcription factors that could enhance CAR T cell fitness and efficacy against solid tumours. Here we show that overexpression of FOXO1 promotes a stem-like phenotype in CAR T cells derived from either healthy human donors or patients, which correlates with improved mitochondrial fitness, persistence and therapeutic efficacy in vivo. This work thus reveals an engineering approach to genetically enforce a favourable metabolic phenotype that has high translational potential to improve the efficacy of CAR T cells against solid tumours.

Predictive and Prognostic Relevance of Tumor-Infiltrating Immune Cells: Tailoring Personalized Treatments against Different Cancer Types

TIICs are critical components of the TME and are used to estimate prognostic and treatment responses in many malignancies. TIICs in the tumor microenvironment are assessed and quantified by categorizing immune cells into three subtypes: CD66b+ tumor-associated neutrophils (TANs), FoxP3+ regulatory T cells (Tregs), and CD163+ tumor-associated macrophages (TAMs). In addition, many cancers have tumor-infiltrating M1 and M2 macrophages, neutrophils (Neu), CD4+ T cells (T-helper), CD8+ T cells (T-cytotoxic), eosinophils, and mast cells. A variety of clinical treatments have linked tumor immune cell infiltration (ICI) to immunotherapy receptivity and prognosis. To improve the therapeutic effectiveness of immune-modulating drugs in a wider cancer patient population, immune cells and their interactions in the TME must be better understood. This study examines the clinicopathological effects of TIICs in overcoming tumor-mediated immunosuppression to boost antitumor immune responses and improve cancer prognosis. We successfully analyzed the predictive and prognostic usefulness of TIICs alongside TMB and ICI scores to identify cancer's varied immune landscapes. Traditionally, immune cell infiltration was quantified using flow cytometry, immunohistochemistry, gene set enrichment analysis (GSEA), CIBERSORT, ESTIMATE, and other platforms that use integrated immune gene sets from previously published studies. We have also thoroughly examined traditional limitations and newly created unsupervised clustering and deconvolution techniques (SpatialVizScore and ProTICS). These methods predict patient outcomes and treatment responses better. These models may also identify individuals who may benefit more from adjuvant or neoadjuvant treatment. Overall, we think that the significant contribution of TIICs in cancer will greatly benefit postoperative follow-up, therapy, interventions, and informed choices on customized cancer medicines.

Immune Cytolytic Activity and Strategies for Therapeutic Treatment

Intratumoral immune cytolytic activity (CYT), calculated as the geometric mean of granzyme-A (GZMA) and perforin-1 (PRF1) expression, has emerged as a critical factor in cancer immunotherapy, with significant implications for patient prognosis and treatment outcomes. Immune checkpoint pathways, the composition of the tumor microenvironment (TME), antigen presentation, and metabolic pathways regulate CYT. Here, we describe the various methods with which we can assess CYT. The detection and analysis of tumor-infiltrating lymphocytes (TILs) using flow cytometry or immunohistochemistry provide important information about immune cell populations within the TME. Gene expression profiling and spatial analysis techniques, such as multiplex immunofluorescence and imaging mass cytometry allow the study of CYT in the context of the TME. We discuss the significant clinical implications that CYT has, as its increased levels are associated with positive clinical outcomes and a favorable prognosis. Moreover, CYT can be used as a prognostic biomarker and aid in patient stratification. Altering CYT through the different methods targeting it, offers promising paths for improving treatment responses. Overall, understanding and modulating CYT is critical for improving cancer immunotherapy. Research into CYT and the factors that influence it has the potential to transform cancer treatment and improve patient outcomes.

Association of lymphocyte subsets with the efficacy and prognosis of PD‑1 inhibitor therapy in advanced gastric cancer: results from a monocentric retrospective study

PURPOSE

This retrospective study aimed to investigate the changes in peripheral blood lymphocyte subsets before and after immunotherapy in patients with advanced gastric cancer and their relationship n with the therapeutic efficacy and clinical prognosis.

METHODS

Peripheral blood lymphocyte subsets, including CD4 + T cells, CD8 + T cells, CD4+/CD8 + ratio, NK cells, Treg cells, and B cells, were collected from 195 patients with advanced gastric cancer who were admitted to the First Hospital of Shanxi Medical University with immunotherapy from January 2020 to October 2021, at the time of diagnosis of advanced gastric cancer, before immunotherapy and after 3 cycles of immunotherapy. T-tests were used to examine the factors influencing the patients' peripheral blood lymphocyte subsets and the changes after immunotherapy. To examine the relationship between lymphocyte subsets and treatment outcomes, ROC curves were plotted using a logistic regression. Kaplan-Meier curve was drawn, and the Log Rank test was carried out to compare the differences in PFS between the different groups. Cox proportional hazards regression model was used to analyze the factors affecting PFS after calibration of other variables.

RESULTS

The proportion of peripheral blood lymphocyte subsets in patients with advanced gastric cancer was affected by age and PD-L1 level. Compared to the baseline, the treatment effective group had higher proportions of CD4 + T cells, a higher CD4+/CD8 + ratio, NK cells and Treg cells, and lower proportions of CD8 + T cells and B cells in the peripheral blood after three cycles of immunotherapy. In the treatment-naive group, there were no significant differences in the lymphocyte subsets. With cut-off values of 30.60% and 18.00%, baseline CD4 + T cell and NK cell ratios were independent predictors of immunotherapy efficacy and PFS. Treg cell ratio, gender, PD-L1 levels, and MMR status all predicted PFS independently.

CONCLUSION

The proportion of peripheral blood lymphocyte subsets was modified in patients who responded to PD-1 inhibitors. Different lymphocyte subpopulation levels can be used as biomarkers to predict immunotherapy efficacy and clinical prognosis in patients with advanced gastric cancer.

Identification of key immune cells infiltrated in lung adenocarcinoma microenvironment and their related long noncoding RNA

LncRNA associated with immune cell infiltration in tumor microenvironment (TME) may be a potential therapeutic target for lung adenocarcinoma. We established a machine learning (ML) model based on 3896 samples characterized by the degree of immune cell infiltration, and further screened the key lncRNA. In vitro experiments were applied to validate the prediction. Treg is the key immune cell in the TME of lung adenocarcinoma, and the degree of infiltration is negatively correlated with the prognosis. PCBP1-AS1 may affect the infiltration of Tregs by regulating the TGF-β pathway, which is a potential predictor of clinical response to immunotherapy. PCBP1-AS1 regulates cell proliferation, cell cycle, invasion, migration, and apoptosis in lung adenocarcinoma. The results of clinical sample staining and in vitro experiments showed that PCBP1-AS1 was negatively correlated with Treg infiltration and TGF-β expression. Tregs and related lncRNA PCBP1-AS1 can be used as targets for the diagnosis and treatment of lung adenocarcinoma.

Single-cell and Bulk RNA-Seq reveal angiogenic heterogeneity and microenvironmental features to evaluate prognosis and therapeutic response in lung adenocarcinoma

Background

Angiogenesis stands as a pivotal hallmark in lung adenocarcinoma (LUAD), intricately shaping the tumor microenvironment (TME) and influencing LUAD progression. It emerges as a promising therapeutic target for LUAD, affecting patients' prognosis. However, its role in TME, LUAD prognosis, and its clinical applicability remain shrouded in mystery.

Methods

We employed integrated single-cell and bulk transcriptome sequencing to unravel the heterogeneity of angiogenesis within LUAD cells. Through "consensus clustering", we delineated distinct angiogenic clusters and deciphered their TME features. "Monocle2" was used to unravel divergent trajectories within malignant cell subpopulations of LUAD. Additionally, regulon submodules and specific cellular communication patterns of cells in different angiogenic states were analyzed by "pyscenic" and "Cellchat" algorithms. The "univariate Cox" and "LASSO" algorithms were applied to build angiogenic prognostic models. Immunohistochemistry (IHC) on clinical samples validated the role of model factors in LUAD angiogenesis. We utilized CTRP 2.0 and PRISM databases for pinpointing sensitive drugs against lung adenocarcinoma.

Results

Two clusters for the activation of angiogenesis were identified, with Cluster 1 showing a poor prognosis and a pro-cancerous TME. Three differentiated states of malignant epithelial LUAD cells were identified, which had different degrees of angiogenic activation, were regulated by three different regulon submodules, and had completely different crosstalk from other cells in TME. The experiments validate that SLC2A1 promotes angiogenesis in LUAD. ARS (Angiogenesis related score) had a high prognostic value; low ARSs showed immunotherapy benefits, whereas high ARSs were sensitive to 15 chemotherapeutic agents.

Conclusion

The assessment of angiogenic clusters helps to determine the prognostic and TME characteristics of LUAD. Angiogenic prognostic models can be used to assess the prognosis, immunotherapeutic response, and chemotherapeutic drug sensitivity of LUAD.

Macrophage-Related Gene Signatures for Predicting Prognosis and Immunotherapy of Lung Adenocarcinoma by Machine Learning and Bioinformatics

Background

In recent years, the immunotherapy of lung adenocarcinoma has developed rapidly, but the good therapeutic effect only exists in some patients, and most of the current predictors cannot predict it very well. Tumor-infiltrating macrophages have been reported to play a crucial role in lung adenocarcinoma (LUAD). Thus, we want to build novel molecular markers based on macrophages.

Methods

By non-negative matrix factorization (NMF) algorithm and Cox regression analysis, we constructed macrophage-related subtypes of LUAD patients and built a novel gene signature consisting of 12 differentially expressed genes between two subtypes. The gene signature was further validated in Gene-Expression Omnibus (GEO) datasets. Its predictive effect on prognosis and immunotherapy outcome was further evaluated with rounded analyses. We finally explore the role of TRIM28 in LUAD with a series of in vitro experiments.

Results

Our research indicated that a higher LMS score was significantly correlated with tumor staging, pathological grade, tumor node metastasis stage, and survival. LMS was identified as an independent risk factor for OS in LUAD patients and verified in GEO datasets. Clinical response to immunotherapy was better in patients with low LMS score compared to those with high LMS score. TRIM28, a key gene in the gene signature, was shown to promote the proliferation, invasion and migration of LUAD cell.

Conclusion

Our study highlights the significant role of gene signature in predicting the prognosis and immunotherapy efficacy of LUAD patients, and identifies TRIM28 as a potential biomarker for the treatment of LUAD.

Single-cell combined bioinformatics analysis: construction of immune cluster and risk prognostic model in kidney renal clear cells based on CD8+ T cell-associated genes

BACKGROUND

Kidney cancer is an immunogenic solid tumor, characterized by high tumor burden and infiltration of CD8+ T cells. Although immunotherapy targeting the PD1/CTLA-4 axis has demonstrated excellent clinical efficacy, clinical outcomes in most patients are poor.

METHODS

We used the RNA sequencing data from the GEO database for KIRC GSE121636 and normal kidney tissue GSE131685, and performed single-cell analysis for cluster identification, pathway enrichment, and CD8+ T cell-associated gene identification. Subsequently, the significance of different CD8+ T-cell associated gene subtypes was elucidated by consensus clustering, pathway analysis, mutated gene analysis, and KIRC immune microenvironment analysis in the TCGA-KIRC disease cohort. Single gene analysis identified LAG3 as the most critical CD8+ T-cell-associated gene and its function was verified by cell phenotype and immunohistochemistry in KIRC.

RESULTS

In the present study, CD8+ T-cell associated genes in KIRC were screened, including GZMK, CD27, CCL4L2, FXYD2, LAG3, RGS1, CST7, DUSP4, CD8A, and TRBV20-1 and an immunological risk prognostic model was constructed (risk score =  - 0.291858656434841*GZMK - 0.192758342489394*FXYD2 + 0.625023643446193*LAG3 + 0.161324477181591*RGS1 - 0.380169045328895*DUSP4 - 0.107221347575037*TRBV20-1). LAG3 was identified and proved as the most critical CD8+ T cell-associated gene in KIRC.

CONCLUSION

We proposed and constructed an immunological risk prognostic model for CD8+ T cell-associated genes and identified LAG3 as a pivotal gene for KIRC progression and CD8+ T-cell infiltration. The model comprehensively explained the immune microenvironment and provided novel immune-related therapeutic targets and biomarkers in KIRC.

Identification of an immune-related eRNA prognostic signature for clear cell renal cell carcinoma

BACKGROUND

Immune-related enhancer RNAs (eRNAs) have garnered significant attention in cancer metabolism research, yet their specific roles in ccRCC have remained elusive.

METHODS

We retrieved eRNA expression profiles from TCGA database and identified immune-related eRNAs (IREs) by assessing their co-expression with immune genes. Utilizing consensus clustering, we organized these IREs into two distinct clusters. The construction of an IREs signature was accomplished through the LASSO and multivariate Cox analysis. Furthermore, we performed Cell Counting Kit-8 and clonogenic assays to assess changes in the proliferative capacity of Caki-1 and 769-P cells.

RESULTS

The existence of two clusters of immune-related eRNAs in ccRCC, each with distinctive prognostic and immunological attributes. Cluster B exhibited immunosuppressive properties and displayed a positive correlation with immunosuppressive cells. Functional enrichment analysis unveiled their involvement in several tumor-promoting pathways, metabolic pathways and immune pathways. The IREs signature demonstrated its potential to accurately predict patient immune and prognostic characteristics. AC003092.1, an eRNA strongly associated with patient survival, emerged as a potential oncogene significantly linked to adverse prognosis and the presence of immunosuppressive cells and checkpoints in ccRCC patients. Notably, AC003092.1 displayed marked upregulation in ccRCC tissues and cell lines, and its knockdown substantially inhibited the proliferation of Caki-1 and 769-P cells.

CONCLUSION

We established a robust predictive model that played a vital role in determining the prognosis, clinicopathological characteristics and immune cell infiltration patterns of ccRCC patients. IRE, particularly AC003092.1, which was strongly associated with survival, hold promise as novel immunotherapeutic targets for ccRCC.

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.

Non-Metastatic Clear Cell Renal Cell Carcinoma Immune Cell Infiltration Heterogeneity and Prognostic Ability in Patients Following Surgery

Predicting which patients will progress to metastatic disease after surgery for non-metastatic clear cell renal cell carcinoma (ccRCC) is difficult; however, recent data suggest that tumor immune cell infiltration could be used as a biomarker. We evaluated the quantity and type of immune cells infiltrating ccRCC tumors for associations with metastatic progression following attempted curative surgery. We quantified immune cell densities in the tumor microenvironment and validated our findings in two independent patient cohorts with multi-region sampling to investigate the impact of heterogeneity on prognostic accuracy. For non-metastatic ccRCC, increased CD8+ T cell infiltration was associated with a reduced likelihood of progression to metastatic disease. Interestingly, patients who progressed to metastatic disease also had increased percentages of exhausted CD8+ T cells. Finally, we evaluated the spatial heterogeneity of the immune infiltration and demonstrated that patients without metastatic progression had CD8+ T cells in closer proximity to ccRCC cells. These data strengthen the evidence for CD8+ T cell infiltration as a prognostic biomarker in non-metastatic ccRCC and demonstrate that multi-region sampling may be necessary to fully characterize immune infiltration within heterogeneous tumors. Tumor CD8+ T cell infiltration should be investigated as a biomarker in adjuvant systemic therapy clinical trials for high-risk non-metastatic RCC.

CXCL14 as a potential marker for immunotherapy response prediction in renal cell carcinoma

Background

Epigenetic mechanisms play vital roles in the activation, differentiation, and effector function of immune cells. The breast and kidney-expressed chemokine (CXCL14) mainly contributes to the regulation of immune cells. However, its role in shaping the tumor immune microenvironment (TIME) is yet to be elucidated in renal cell carcinoma (RCC).

Objectives

This study aimed to elucidate the role of CXCL14 in predicting the efficacy of immunotherapy in patients with RCC.

Methods

CXCL14 expression and RNA-sequencing, single-cell RNA-sequencing (scRNA-seq), and survival datasets of RCC from public databases were analyzed, and survival was compared between different CXCL14 levels. The correlation between CXCL14 and immune infiltration and human leukocyte antigen (HLA) gene expression was analyzed with TIMER2.0 and gene expression profiling interactive analysis. Institutional scRNA-seq and immunohistochemical staining analyses were used to verify the relationship between CXCL14 expression level and the efficacy of immunotherapy.

Results

CXCL14 was expressed in fibroblast and malignant cells in RCC, and higher expression was associated with better survival. Enrichment analysis revealed that CXCL14 is involved in immune activation, primarily in antigen procession, antigen presentation, and major histocompatibility complex assemble. CXCL14 expression was positively correlated with T-cell infiltration as well as HLA-related gene expression. Among the RCC cohort receiving nivolumab in Checkmate 025, the patients with CXCL14 high expression had better overall survival than those with CXCL14 low expression after immunotherapy. scRNA-seq revealed a cluster of CXCL14+ fibroblast in immunotherapy responders. Immunohistochemistry analysis verified that the patients with high CXCL14 expression had an increased proportion of high CD8 expression simultaneously. The expression level of CXCL14 was associated with CXCR4 expression in RCC.

Conclusion

CXCL14 expression is associated with immunotherapy response in RCC. It is a promising biomarker for immunotherapy response prediction and may be an effective epigenetic modulator in combination with immunotherapy approaches.

The immunometabolic ecosystem in cancer

Our increased understanding of how key metabolic pathways are activated and regulated in malignant cells has identified metabolic vulnerabilities of cancers. Translating this insight to the clinics, however, has proved challenging. Roadblocks limiting efficacy of drugs targeting cancer metabolism may lie in the nature of the metabolic ecosystem of tumors. The exchange of metabolites and growth factors between cancer cells and nonmalignant tumor-resident cells is essential for tumor growth and evolution, as well as the development of an immunosuppressive microenvironment. In this Review, we will examine the metabolic interplay between tumor-resident cells and how targeted inhibition of specific metabolic enzymes in malignant cells could elicit pro-tumorigenic effects in non-transformed tumor-resident cells and inhibit the function of tumor-specific T cells. To improve the efficacy of metabolism-targeted anticancer strategies, a holistic approach that considers the effect of metabolic inhibitors on major tumor-resident cell populations is needed.

CD4+CCR8+ Tregs in ovarian cancer: a potential effector Tregs for immune regulation

BACKGROUND

Tregs are key drivers of immunosuppression in solid tumors. As an important chemokine receptor on Tregs, the regulatory effect of CCR8 on tumor immunity has received more and more attention. However, the current research on CCR8 in the immune microenvironment of ovarian cancer has not been clear.

METHODS

Bioinformatics analysis was used to compare the transcriptome differences between CD4+ T cells in the peripheral circulation and infiltrated in ovarian tumor tissues. RT-PCR was used to detect the expression levels of chemokine receptor-related differential genes on CD4+ T cells in peripheral blood and ovarian tumor tissues. Multiparameter flow cytometry was used to detect the proportion and phenotypic characteristics of CD4+CCR8+ Tregs and CD4+CCR8- Tregs in different sample types. The expression level of CCR8 ligands was detected at multiple levels. To explore the important role of CCR8-CCL1 and CCR8-CCL18 axis in the migration and invasion of CD4+CCR8+ Tregs into ovarian tumor tissues by establishing a chemotaxis system in vitro.

RESULTS

In this study, significantly different gene expression profiles were found between peripheral circulating CD4+ T cells and infiltrating CD4+ T cells in ovarian tumor tissues, in which chemokine-chemokine receptor signaling pathway was significantly enriched in all three groups of differential genes. The expression level of CCR8 in infiltrating CD4+ T cells of ovarian cancer tissue was significantly higher than that in peripheral blood of healthy controls and ovarian cancer patients, and high expression of CCR8 was significantly correlated with advanced tumor stage and poor differentiation. CD4+CCR8+ Tregs are the main type of infiltrating CD4+ Tregs in ovarian tumor tissues, which have stronger immunosuppressive phenotypes, secrete more inhibitory cytokines and have stronger proliferation ability. The ligands CCL1 and CCL18 corresponding to CCR8 were significantly overexpressed in ovarian tumor tissues, and the CCR8-CCL1 and CCR8-CCL18 axis played a key role in the migration and infiltration of CD4+CCR8+ Tregs into ovarian tumor tissues.

CONCLUSIONS

The results of this study may help to understand the phenotypic characteristics and recruitment process of Tregs in the tumor, and provide new ideas for improving the immunosuppressive status of the ovarian cancer microenvironment.

The genes regulating sensitivity of tumor cells to T cell-mediated killing: could they be potential personalized immunotherapeutic targets in head and neck squamous cell carcinoma?

OBJECTIVE

To identify the pivotal genes, specifically the STTK genes, that govern the sensitivity of tumor cells to T cell-mediated killing in Head and Neck Squamous Cell Carcinoma (HNSC).

METHODS

The differentially expressed genes (DEGs) in HNSC and STTK genes were overlapped to obtain the DE-STTK genes. Univariate and LASSO regression analyses were conducted to identify the pivotal DE-STTK genes that serve as hubs in HNSC (i.e., hub DE-STTK genes). The risk model was established to divide HNSC tumor samples into high- and low-risk groups based on the hub DE-STTK genes. Further investigations were carried out by examing the expression level, prognostic values, diagnostic values, enriched signaling pathways, correlation with tumor mutation burden (TMB), and association with tumor immune infiltration cells (TIICs).

RESULTS

A total of 71 genes were found to be overlapped between DEGs in HNSC and STTK genes. Lasso regression analysis identified 9 hub genes which were MYF6, AATF, AURKA, CXCL9, DPM2, MYO1B, NCBP2, TNFRSF12A, and TRAF1. The network analysis of hub DE-STTK genes-pathway reveals that these 9 hub genes exhibit enrichment in multiple signaling pathways, including toll-like receptor signaling, TNF signaling, NF-kappa B signaling, cytokine-cytokine receptor interaction, spliceosome, mRNA surveillance pathway, nucleocytoplasmic transport, GPI-anchor biosynthesis, as well as N-Glycan biosynthesis. The Pearson correlation analysis showed that the majority of correlations between 9 hub DE-STTK genes and immune cells were positive.

CONCLUSION

The 9 identified hub DE-STTK genes (MYF6, AATF, AURKA, CXCL9, DPM2, MYO1B, NCBP2, TNFRSF12A, and TRAF1) are presumptively implicated in the modulation of tumor immunity in HNSC. These genes, along with their enriched pathways, hold promise as potential personalized immunotherapeutic targets for the treatment of HNSC, thereby offering novel avenues for therapeutic intervention in this malignancy.

Immunotherapy with Monoclonal Antibodies for Acute Myeloid Leukemia: A Work in Progress

In the last few years, molecularly targeted agents and immune-based treatments (ITs) have significantly changed the landscape of anti-cancer therapy. Indeed, ITs have been proven to be very effective when used against metastatic solid tumors, for which outcomes are extremely poor when using standard approaches. Such a scenario has only been partially reproduced in hematologic malignancies. In the context of acute myeloid leukemia (AML), as innovative drugs are eagerly awaited in the relapsed/refractory setting, different ITs have been explored, but the results are still unsatisfactory. In this work, we will discuss the most important clinical studies to date that adopt ITs in AML, providing the basis to understand how this approach, although still in its infancy, may represent a promising therapeutic tool for the future treatment of AML patients.

Immunobiology and Metabolic Pathways of Renal Cell Carcinoma

The treatment of advanced renal cell carcinoma (RCC) has changed dramatically with immune checkpoint inhibitors, yet most patients do not have durable responses. There is consequently a tremendous need for novel therapeutic development. RCC, and particularly the most common histology clear cell RCC, is an immunobiologically and metabolically distinct tumor. An improved understanding of RCC-specific biology will be necessary for the successful identification of new treatment targets for this disease. In this review, we discuss the current understanding of RCC immune pathways and metabolic dysregulation, with a focus on topics important for future clinical development.

Regulating the regulatory T cells as cell therapies in autoimmunity and cancer

Regulatory T cells (Tregs), possess a pivotal function in the maintenance of immune homeostasis. The dysregulated activity of Tregs has been associated with the onset of autoimmune diseases and cancer. Hence, Tregs are promising targets for interventions aimed at steering the immune response toward the desired path, either by augmenting the immune system to eliminate infected and cancerous cells or by dampening it to curtail the damage to self-tissues in autoimmune disorders. The activation of Tregs has been observed to have a potent immunosuppressive effect against T cells that respond to self-antigens, thus safeguarding our body against autoimmunity. Therefore, promoting Treg cell stability presents a promising strategy for preventing or managing chronic inflammation that results from various autoimmune diseases. On the other hand, Tregs have been found to be overactivated in several forms of cancer, and their role as immune response regulators with immunosuppressive properties poses a significant impediment to the successful implementation of cancer immunotherapy. However, the targeting of Tregs in a systemic manner may lead to the onset of severe inflammation and autoimmune toxicity. It is imperative to develop more selective methods for targeting the function of Tregs in tumors. In this review, our objective is to elucidate the function of Tregs in tumors and autoimmunity while also delving into numerous therapeutic strategies for reprogramming their function. Our focus is on reprogramming Tregs in a highly activated phenotype driven by the activation of key surface receptors and metabolic reprogramming. Furthermore, we examine Treg-based therapies in autoimmunity, with a specific emphasis on Chimeric Antigen Receptor (CAR)-Treg therapy and T-cell receptor (TCR)-Treg therapy. Finally, we discuss key challenges and the future steps in reprogramming Tregs that could lead to the development of novel and effective cancer immunotherapies.

Prediction of the Peptide-TIM3 Binding Site in Inhibiting TIM3-Galectin 9 Binding Pathways

T-cell immunoglobulin and mucin domain-containing protein-3 (TIM3) is an important receptor protein that modulates the immune system. The binding of TIM3 with Galectin 9 (GAL9) triggers immune system suppression, but the TIM3-GAL9 binding can be inhibited by binding of the peptide P26 to TIM3. A fast and accurate prediction of the P26-TIM3 binding site is crucial and a prerequisite for the investigation of P26-TIM3 interactions and TIM3-GAL9 binding pathways. Here, we present a machine learning approach, which considers protein conformational changes, to quickly identify the ligand-binding site on TIM3. Our results show that the P26 binding site is located near the C″-D loop of TIM3. Further simulations show that the binding pose is stabilized by a variety of electrostatic and hydrophobic interactions. Binding of P26 can alter the conformations of nearby glycan side chains on TIM3, providing possible mechanisms of how P26 inhibits TIM3-GAL9 binding pathways. The insights from this work will facilitate the identification of other peptides or antibodies that may also inhibit the TIM3-GAL9 pathways and eventually lead to improved attempts in the modulation of the TIM3-GAL9 immunosuppression pathways. The strategies and machine learning method can be generalized to study ligand-receptor binding when the conformational changes during the binding are important.

Identification of pyroptosis-related subtypes and comprehensive analysis of characteristics of the tumor microenvironment infiltration in clear cell renal cell carcinoma

Pyroptosis is a kind of programmed cell death triggered by the inflammasome. Growing evidence has revealed the crucial utility of pyroptosis in tumors. However, the potential mechanism of pyroptosis in clear cell renal cell carcinoma (ccRCC) is still unclear. In this research, we systematically analyze the genetic and transcriptional alterations of pyroptosis-related genes (PRGs) in ccRCC, identify pyroptosis-related subtypes, analyze the clinical and microenvironmental differences among different subtypes, develop a corresponding prognostic model to predict the prognosis of patients, and interpret the effect of pyroptosis on ccRCC microenvironment. This study provides a new perspective for a comprehensive understanding of the role of pyroptosis in ccRCC and its impact on the immune microenvironment, and a reliable scoring system was established to predict patients' prognosis.

Radiogenomic Features of GIMAP Family Genes in Clear Cell Renal Cell Carcinoma: An Observational Study on CT Images

GTPases of immunity-associated proteins (GIMAP) genes include seven functional genes and a pseudogene. Most of the GIMAPs have a role in the maintenance and development of lymphocytes. GIMAPs could inhibit the development of tumors by increasing the amount and antitumor activity of infiltrating immunocytes. Knowledge of key factors that affect the tumor immune microenvironment for predicting the efficacy of immunotherapy and establishing new targets in ccRCC is of great importance. A computed tomography (CT)-based radiogenomic approach was used to detect the imaging phenotypic features of GIMAP family gene expression in ccRCC. In this retrospective study we enrolled 193 ccRCC patients divided into two groups: ccRCC patients with GIMAP expression (n = 52) and ccRCC patients without GIMAP expression (n = 141). Several imaging features were evaluated on preoperative CT scan. A statistically significant correlation was found with absence of endophytic growth pattern (p = 0.049), tumor infiltration (p = 0.005), advanced age (p = 0.018), and high Fuhrman grade (p = 0.024). This study demonstrates CT imaging features of GIMAP expression in ccRCC. These results could allow the collection of data on GIMAP expression through a CT-approach and could be used for the development of a targeted therapy.

An Overview of Systemic Targeted Therapy in Renal Cell Carcinoma, with a Focus on Metastatic Renal Cell Carcinoma and Brain Metastases

The most commonly diagnosed malignancy of the urinary system is represented by renal cell carcinoma. Various subvariants of RCC were described, with a clear-cell type prevailing in about 85% of all RCC tumors. Patients with metastases from renal cell carcinoma did not have many effective therapies until the end of the 1980s, as long as hormonal therapy and chemotherapy were the only options available. The outcomes were unsatisfactory due to the poor effectiveness of the available therapeutic options, but then interferon-alpha and interleukin-2 showed treatment effectiveness, providing benefits but only for less than half of the patients. However, it was not until 2004 that targeted therapies emerged, prolonging the survival rate. Currently, new technologies and strategies are being developed to improve the actual efficacy of available treatments and their prognostic aspects. This article summarizes the mechanisms of action, importance, benefits, adverse events of special interest, and efficacy of immunotherapy in metastatic renal cell carcinoma, with a focus on brain metastases.

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.

Computational textural mapping harmonises sampling variation and reveals multidimensional histopathological fingerprints

BACKGROUND

Technical factors can bias H&E digital slides potentially compromising computational histopathology studies. Here, we hypothesised that sample quality and sampling variation can introduce even greater and undocumented technical fallacy.

METHODS

Using The Cancer Genome Atlas (TCGA) clear-cell renal cell carcinoma (ccRCC) as a model disease, we annotated ~78,000 image tiles and trained deep learning models to detect histological textures and lymphocyte infiltration at the tumour core and its surrounding margin and correlated these with clinical, immunological, genomic, and transcriptomic profiles.

RESULTS

The models reached 95% validation accuracy for classifying textures and 95% for lymphocyte infiltration enabling reliable profiling of ccRCC samples. We validated the lymphocyte-per-texture distributions in the Helsinki dataset (n = 64). Texture analysis indicated constitutive sampling bias by TCGA clinical centres and technically suboptimal samples. We demonstrate how computational texture mapping (CTM) can abrogate these issues by normalising textural variance. CTM-harmonised histopathological architecture resonated with both expected associations and novel molecular fingerprints. For instance, tumour fibrosis associated with histological grade, epithelial-to-mesenchymal transition, low mutation burden and metastasis.

CONCLUSIONS

This study highlights texture-based standardisation to resolve technical bias in computational histopathology and understand the molecular basis of tissue architecture. All code, data and models are released as a community resource.

Pan-cancer analysis of kinesin family members with potential implications in prognosis and immunological role in human cancer

Background

Kinesin is a molecular motor for transporting "goods" within cells and plays a key role in many types of tumors. The multi-angle study of kinesin at the pan-cancer level is conducive to understanding its role in tumorigenesis and development and clinical treatment potential.

Methods

We evaluated the expression of KIF genes, performed differential analysis by using the R package limma, and explored the pan-cancer prognosis of KIF genes by univariate Cox regression analysis. To evaluate the pan-cancer role of KIF genes as a whole, we defined the KIFscore with the help of gene set variation analysis (GSVA) and explored the KIFscores across normal tissues, tumor cell lines, and 33 tumor types in TCGA. Next, we used spearman correlation analysis to extensively study the correlation between the KIFscore and tumor prognosis and be-tween the KIFscore and clinical indicators. We also identified the relationship between the KIFscore and genomic variation and immune molecular signatures by multiplatform analysis. Finally, we identified the key genes in clear cell renal cell carcinoma (ccRCC) through machine learning algorithms and verified the candidate genes by CCK8, wound healing assay, Transwell assay, and flow cytometry.

Results

In most cancers, KIFscores are high and they act as a risk factor for cancer. The KIFscore was significantly associated with copy number variation (CNV), tumor mutation burden (TMB), immune subtypes, DNA repair deficiency, and tumor stemness indexes. Moreover, in almost all cancer species, the KIFscore was positively correlated with T cell CD4+ TH2, the common lymphoid pro-genitor, and the T cell follicular helper. In addition, it was negatively correlated with CXCL16, CCL14, TNFSF13, and TNFRSF14 and positively correlated with ULBP1, MICB, and CD276. Machine learning helped us to identify four hub-genes in ccRCC. The suitable gene, KIF14, is highly expressed in ccRCC and promotes tumor cell proliferation, migration, and invasion.

Conclusion

Our study shows that the KIF genes play an important pan-cancer role and may become a potential new target for a variety of tumor treatments in the future. Furthermore, KIF14, a key molecule in the KIF genes, can provide a new idea for the ccRCC treatment.

Biomarkers for Immune Checkpoint Inhibitors in Renal Cell Carcinoma

Immune checkpoint inhibitor (ICI) therapy has revolutionized renal cell carcinoma treatment. Patients previously thought to be palliative now occasionally achieve complete cures from ICI. However, since immunotherapies stimulate the immune system to induce anti-tumor immunity, they often lead to adverse autoimmunity. Furthermore, some patients receive no benefit from ICI, thereby unnecessarily risking adverse events. In many tumor types, PD-L1 expression levels, immune infiltration, and tumor mutation burden predict the response to ICI and help inform clinical decision making to better target ICI to patients most likely to experience benefits. Unfortunately, renal cell carcinoma is an outlier, as these biomarkers fail to discriminate between positive and negative responses to ICI therapy. Emerging biomarkers such as gene expression profiles and the loss of pro-angiogenic proteins VHL and PBRM-1 show promise for identifying renal cell carcinoma cases likely to respond to ICI. This review provides an overview of the mechanistic underpinnings of different biomarkers and describes the theoretical rationale for their use. We discuss the effectiveness of each biomarker in renal cell carcinoma and other cancer types, and we introduce novel biomarkers that have demonstrated some promise in clinical trials.

Spatial heterogeneity of tumor microenvironment influences the prognosis of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is an immunologically and histologically diverse tumor. However, how the structural heterogeneity of tumor microenvironment (TME) affects cancer progression and treatment response remains unclear. Hence, we characterized the TME architectures of ccRCC tissues using imaging mass cytometry (IMC) and explored their associations with clinical outcome and therapeutic response.

METHODS

Using IMC, we profiled the TME landscape of ccRCC and paracancerous tissue by measuring 17 markers involved in tissue architecture, immune cell and immune activation. In the ccRCC tissue, we identified distinct immune architectures of ccRCC tissue based on the mix score and performed cellular neighborhood (CN) analysis to subdivide TME phenotypes. Moreover, we assessed the relationship between the different TME phenotypes and ccRCC patient survival, clinical features and treatment response.

RESULTS

We found that ccRCC tissues had higher levels of CD8⁺ T cells, CD163^- macrophages, Treg cells, endothelial cells, and fibroblasts than paracancerous tissues. Immune infiltrates in ccRCC tissues distinctly showed clustered and scattered patterns. Within the clustered pattern, we identified two subtypes with different clinical outcomes based on CN analysis. The TLS-like phenotype had cell communities resembling tertiary lymphoid structures, characterized by cell-cell interactions of CD8⁺ T cells-B cells and GZMB⁺CD8⁺ T cells-B cells, which exhibited anti-tumor features and favorable outcomes, while the Macrophage/T-clustered phenotype with macrophage- or T cell-dominated cell communities had a poor prognosis. Patients with scattered immune architecture could be further divided into scattered-CN-hot and scattered-CN-cold phenotypes based on the presence or absence of immune CNs, but both had a better prognosis than the macrophage/T-clustered phenotype. We further analyzed the relationship between the TME phenotypes and treatment response in five metastatic ccRCC patients treated with sunitinib, and found that all three responders were scattered-CN-hot phenotype while both non-responders were macrophage/T-clustered phenotype.

CONCLUSION

Our study revealed the structural heterogeneity of TME in ccRCC and its impact on clinical outcome and personalized treatment. These findings highlight the potential of IMC and CN analysis for characterizing TME structural units in cancer research.

Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis

Introduction: Clear cell renal cell carcinoma (ccRCC) is associated with unfavorable clinical outcomes. To identify viable therapeutic targets, a comprehensive understanding of intratumoral heterogeneity is crucial. In this study, we conducted bioinformatic analysis to scrutinize single-cell RNA sequencing data of ccRCC tumor and para-tumor samples, aiming to elucidate the intratumoral heterogeneity in the ccRCC tumor microenvironment (TME). Methods: A total of 51,780 single cells from seven ccRCC tumors and five para-tumor samples were identified and grouped into 11 cell lineages using bioinformatic analysis. These lineages included tumor cells, myeloid cells, T-cells, fibroblasts, and endothelial cells, indicating a high degree of heterogeneity in the TME. Copy number variation (CNV) analysis was performed to compare CNV frequencies between tumor and normal cells. The myeloid cell population was further re-clustered into three major subgroups: monocytes, macrophages, and dendritic cells. Differential expression analysis, gene ontology, and gene set enrichment analysis were employed to assess inter-cluster and intra-cluster functional heterogeneity within the ccRCC TME. Results: Our findings revealed that immune cells in the TME predominantly adopted an inflammatory suppression state, promoting tumor cell growth and immune evasion. Additionally, tumor cells exhibited higher CNV frequencies compared to normal cells. The myeloid cell subgroups demonstrated distinct functional properties, with monocytes, macrophages, and dendritic cells displaying diverse roles in the TME. Certain immune cells exhibited pro-tumor and immunosuppressive effects, while others demonstrated antitumor and immunostimulatory properties. Conclusion: This study contributes to the understanding of intratumoral heterogeneity in the ccRCC TME and provides potential therapeutic targets for ccRCC treatment. The findings emphasize the importance of considering the diverse functional roles of immune cells in the TME for effective therapeutic interventions.

Immunogenicity in renal cell carcinoma: shifting focus to alternative sources of tumour-specific antigens

Renal cell carcinoma (RCC) comprises a group of malignancies arising from the kidney with unique tumour-specific antigen (TSA) signatures that can trigger cytotoxic immunity. Two classes of TSAs are now considered potential drivers of immunogenicity in RCC: small-scale insertions and deletions (INDELs) that result in coding frameshift mutations, and activation of human endogenous retroviruses. The presence of neoantigen-specific T cells is a hallmark of solid tumours with a high mutagenic burden, which typically have abundant TSAs owing to non-synonymous single nucleotide variations within the genome. However, RCC exhibits high cytotoxic T cell reactivity despite only having an intermediate non-synonymous single nucleotide variation mutational burden. Instead, RCC tumours have a high pan-cancer proportion of INDEL frameshift mutations, and coding frameshift INDELs are associated with high immunogenicity. Moreover, cytotoxic T cells in RCC subtypes seem to recognize tumour-specific endogenous retrovirus epitopes, whose presence is associated with clinical responses to immune checkpoint blockade therapy. Here, we review the distinct molecular landscapes in RCC that promote immunogenic responses, discuss clinical opportunities for discovery of biomarkers that can inform therapeutic immune checkpoint blockade strategies, and identify gaps in knowledge for future investigations.

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.

Checkpoint Inhibitors in Acute Myeloid Leukemia

The prognosis of acute myeloid leukemia (AML) remains unsatisfactory. Among the reasons for the poor response to therapy and high incidence of relapse, there is tumor cell immune escape, as AML blasts can negatively influence various components of the immune system, mostly weakening T-cells. Since leukemic cells can dysregulate immune checkpoints (ICs), receptor-based signal transductors that lead to the negative regulation of T-cells and, eventually, to immune surveillance escape, the inhibition of ICs is a promising therapeutic strategy and has led to the development of so-called immune checkpoint inhibitors (ICIs). ICIs, in combination with conventional chemotherapy, hypomethylating agents or targeted therapies, are being increasingly tested in cases of AML, but the results reported are often conflicting. Here, we review the main issues concerning the immune system in AML, the main pathways leading to immune escape and the results obtained from clinical trials of ICIs, alone or in combination, in newly diagnosed or relapsed/refractory AML.

Comprehensive analysis identifies CLEC1B as a potential prognostic biomarker in hepatocellular carcinoma

BACKGROUND

C-type lectin domain family 1 member B (CLEC1B, encoding the CLEC-2 protein), a member of the C-type lectin superfamily, is a type II transmembrane receptor involved in platelet activation, angiogenesis, and immune and inflammatory responses. However, data regarding its function and clinical prognostic value in hepatocellular carcinoma (HCC) remain scarce.

METHODS

The expression of CLEC1B was explored using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. RT-qPCR, western blot, and immunohistochemistry assays were employed to validate the downregulation of CLEC1B. Univariate Cox regression and survival analyses were used to evaluate the prognostic value of CLEC1B. Gene Set Enrichment Analysis (GSEA) was conducted to investigate the potential association between cancer hallmarks and CLEC1B expression. The TISIDB database was applied to search for the correlation between immune cell infiltration levels and CLEC1B expression. The association between CLEC1B and immunomodulators was conducted by Spearman correlation analysis based on the Sangerbox platform. Annexin V-FITC/PI apoptosis kit was used for the detection of cell apoptosis.

RESULTS

The expression of CLEC1B was low in various tumors and exhibited a promising clinical prognostic value for HCC patients. The expression level of CLEC1B was tightly associated with the infiltration of various immune cells in the HCC tumor microenvironment (TME) and positively correlated with a bulk of immunomodulators. In addition, CLEC1B and its related genes or interacting proteins are implicated in multiple immune-related processes and signaling pathways. Moreover, overexpression of CLEC1B significantly influenced the treatment effects of sorafenib on HCC cells.

CONCLUSIONS

Our results reveal that CLEC1B could serve as a potential prognostic biomarker and may be a novel immunoregulator for HCC. However, its function in immune regulation should be further explored.

Cellular and Molecular Players in the Tumor Microenvironment of Renal Cell Carcinoma

Globally, clear-cell renal cell carcinoma (ccRCC) represents the most prevalent type of kidney cancer. Surgery plays a key role in the treatment of this cancer, although one third of patients are diagnosed with metastatic ccRCC and about 25% of patients will develop a recurrence after nephrectomy with curative intent. Molecular-target-based agents, such as tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), are recommended for advanced cancers. In addition to cancer cells, the tumor microenvironment (TME) includes non-malignant cell types embedded in an altered extracellular matrix (ECM). The evidence confirms that interactions among cancer cells and TME elements exist and are thought to play crucial roles in the development of cancer, making them promising therapeutic targets. In the TME, an unfavorable pH, waste product accumulation, and competition for nutrients between cancer and immune cells may be regarded as further possible mechanisms of immune escape. To enhance immunotherapies and reduce resistance, it is crucial first to understand how the immune cells work and interact with cancer and other cancer-associated cells in such a complex tumor microenvironment.

Bioinformatic analyses reveal the prognostic significance and potential role of ankyrin 3 (ANK3) in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most aggressive cancer type of the urinary system. Metastatic KIRC patients have poor prognosis and limited therapeutic options. Ankyrin 3 (ANK3) is a scaffold protein that plays important roles in maintaining physiological function of the kidney and its alteration is implicated in many cancers. In this study, we investigated differential expression of ANK3 in KIRC using GEPIA2, UALCAN, and HPA databases. Survival analysis was performed by GEPIA2, Kaplan-Meier plotter, and OSkirc databases. Genetic alterations of ANK3 in KIRC were assessed using cBioPortal database. Interaction network and functional enrichment analyses of ANK3-correlated genes in KIRC were performed using GeneMANIA and Shiny GO, respectively. Finally, the TIMER2.0 database was used to assess correlation between ANK3 expression and immune infiltration in KIRC. We found that ANK3 expression was significantly decreased in KIRC compared to normal tissues. The KIRC patients with low ANK3 expression had poorer survival outcomes than those with high ANK3 expression. ANK3 mutations were found in 2.4% of KIRC patients and were frequently co-mutated with several genes with a prognostic significance. ANK3-correlated genes were significantly enriched in various biological processes, mainly involved in peroxisome proliferator-activated receptor (PPAR) signaling pathway, in which positive correlations of ANK3 with PPARA and PPARG expressions were confirmed. Expression of ANK3 in KIRC was significantly correlated with infiltration level of B cell, CD8+ T cell, macrophage, and neutrophil. These findings suggested that ANK3 could serve as a prognostic biomarker and promising therapeutic target for KIRC.

Revisiting mechanisms of resistance to immunotherapies in metastatic clear-cell renal-cell carcinoma

Renal-cell carcinoma (RCC) remains a leading cause of cancer-related mortality worldwide. Though newer therapeutic combinations of immune checkpoint inhibitors and targeted therapies have greatly improved outcomes, resistance to these therapies is becoming a challenge for long-term control. Mechanisms of resistance have been explored in a variety of solid tumors, including RCC. Based upon our review of the current literature on the mechanisms of resistance to immunotherapies for the management of metastatic clear-cell renal cell carcinomas (mccRCC), the ensuing conclusions have been made: The management of mccRCC has progressed substantially with the advent of checkpoint inhibitors and targeted oral therapies, alone and/or in combination. Nevertheless, innate or developed resistance to these therapies remains an ongoing challenge, particularly to immune checkpoint inhibitors (ICIs). Several of the known mechanisms of resistance have been well defined, but recent progression in cellular therapies helps to expand the armamentarium of potential combination options that may overcome these modes of resistance and improve long-term disease control and survival for an otherwise dismal disease. In the ensuing review and update of the literature on the mechanisms of resistance to immunotherapies in mccRCC, we have revisited the known resistance mechanisms of immunotherapies in metastatic clear-cell RCC and explored ongoing and future strategies to overcome them.

Targeting copper death genotyping associated gene RARRES2 suppresses glioblastoma progression and macrophages infiltration

BACKGROUND

Copper homeostasis is associated with malignant biological behavior in various tumors. The excessive accumulation of copper can induce tumor death, which is named cuproptosis, and it is also closely related to tumor progression and the formation of the immune microenvironment. However, the associations of cuproptosis with glioblastoma (GBM) prognosis and microenvironment construction are poorly understood.

METHOD

First, TCGA and GEO (GSE83300, GSE74187) merged datasets were used to analyze the association of cuproptosis-related genes (CRGs) with GBM. Then, we performed cluster analysis of CRGs in GBM from the GEO (GSE83300, GSE74187) and TCGA merged datasets. Subsequently, the prognostic risk model was constructed by least absolute shrinkage and selection operator (LASSO) according to gene expression features in CRG clusters. Next, we performed a series of in-depth analyses, including tumor mutational burden (TMB) analysis, cluster analysis, and GBM IDH status prediction. Finally, RARRES2 was identified as a target gene for GBM treatment, especially IDH wild-type GBM. In addition, we further analyzed the correlation of CRG clusters and RARRES2 expression with the GBM immune microenvironment by ESTIMATE and CIBERSORT analyses. In vitro experiments were conducted to demonstrate that targeting RARRES2 inhibits glioblastoma progression and macrophage infiltration, particularly IDH wild-type GBM.

RESULTS

In the present study, we demonstrated that the CRG cluster was closely related to GBM prognosis and immune cell infiltration. Moreover, the prognostic risk model constructed with the three genes (MMP19, G0S2, RARRES2) associated with the CRG clusters could well evaluate the prognosis and immune cell infiltration in GBM. Subsequently, after further analyzing the tumor mutational burden (TMB) in GBM, we confirmed that RARRES2 in the prognostic risk model could be used as a crucial gene signature to predict the prognosis, immune cell infiltration and IDH status of GBM patients.

CONCLUSION

This study fully revealed the potential clinical impact of CRGs on GBM prognosis and the microenvironment, and determined the effect of the crucial gene (RARRES2) on the prognosis and tumor microenvironment construction of GBM, meanwhile, our study also revealed over-expressed RARRES2 is related to the IDH satus of GBM, which provides a novel strategy for the treatment of GBM, particularly IDH wild-type GBM.

Tumor infiltrating lymphocytes and radiological picture of the tumor

Tumor microenvironment (TME) is a complex entity that includes besides the tumor cells also a whole range of immune cells. Among various populations of immune cells infiltrating the tumor, tumor infiltrating lymphocytes (TILs) are a population of lymphocytes characterized by high reactivity against the tumor component. As, TILs play a key role in mediating responses to several types of therapy and significantly improve patient outcomes in some cancer types including for instance breast cancer and lung cancer, their assessment has become a good predictive tool in the evaluation of potential treatment efficacy. Currently, the evaluation of the density of TILs infiltration is performed by histopathological. However, recent studies have shed light on potential utility of several imaging methods, including ultrasonography, magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), and radiomics, in the assessment of TILs levels. The greatest attention concerning the utility of radiology methods is directed to breast and lung cancers, nevertheless imaging methods of TILs are constantly being developed also for other malignancies. Here, we focus on reviewing the radiological methods used to assess the level of TILs in different cancer types and on the extraction of the most favorable radiological features assessed by each method.

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.

The Tumor Immune Microenvironment in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a type of kidney cancer that arises from the cells lining the tubes of the kidney. The tumor immune microenvironment (TIME) of ccRCC is a complex interplay of various immune cells, cytokines, and signaling pathways. One of the critical features of the ccRCC TIME is the presence of infiltrating immune cells, including T cells, B cells, natural killer cells, dendritic cells, and myeloid-derived suppressor cells. Among these cells, CD8+ T cells are particularly important in controlling tumor growth by recognizing and killing cancer cells. However, the TIME of ccRCC is also characterized by an immunosuppressive environment that hinders the function of immune cells. Several mechanisms contribute to the immunosuppressive nature of the ccRCC TIME. For instance, ccRCC cells produce cytokines such as interleukin-10 (IL-10) and transforming growth factor-beta (TGF-β), which suppress immune cell activation and promote the differentiation of regulatory T cells (Tregs). Tregs, in turn, dampen the activity of effector T cells and promote tumor growth. In addition, ccRCC cells can express programmed death-ligand 1 (PD-L1), which interacts with the programmed cell death protein 1 (PD-1) receptor on T cells to inhibit their function. In addition, other immune checkpoint proteins, such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and lymphocyte activation gene 3 (LAG-3), also contribute to the immunosuppressive milieu of the ccRCC TIME. Finally, the hypoxic and nutrient-poor microenvironment of ccRCC can stimulate the production of immunosuppressive metabolites, such as adenosine and kynurenine, which further impair the function of immune cells. Understanding the complex interplay between tumor cells and the immune system in the ccRCC TIME is crucial for developing effective immunotherapies to treat this disease.

HMOX1 pathway signature predicts clinical benefit from immunotherapy plus tyrosine kinase inhibitor therapy in advanced renal cell carcinoma

BACKGROUND

Immunotherapy (IO) plus tyrosine kinase inhibitor (TKI) emerged as standard first-line therapy for advanced renal cell carcinoma (RCC). The heme Oxygenase 1 (HMOX1) pathway is involved in tumor development and treatment resistance, which may affect the efficacy of TKI + IO.

METHODS

Two cohorts from our center (ZS-MRCC, ZS-HRRCC), one cohort from clinical trial (JAVELIN Renal 101) and the Cancer Genome Atlas (TCGA-KIRC) were enrolled. HMOX1 pathway signatures were determined for each sample by RNA-sequencing and gene set enrichment analysis. Immune infiltration was evaluated by flow cytometry. Response and progression-free survival (PFS) were set as primary endpoints.

RESULTS

Patients of low-HMOX1 signature showed higher objective response rate (43.5% vs. 27.3%) in ZS-MRCC cohort and longer PFS in both cohorts (ZS-MRCC cohort, p = 0.019; JAVELIN-101 cohort, p = 0.036). Patients in the high-HMOX1 signature arm also showed greater clinical benefit from TKI + IO, rather than TKI monotherapy (p < 0.001). In high-HMOX1 signature RCC tissues, CD8⁺ T cells showed a dysfunctional phenotype with decreased GZMB expression (Spearman's ρ = -0.32, p = 0.045). A risk score based on HMOX1 signature was further constructed by random forest approach, involving HMOX1 signature and immunologic features. In patients with a low risk level, TKI + IO combination therapy demonstrated longer PFS than TKI monotherapy (p < 0.001), however in individuals with a high risk score group, these two regimens did not give different advantages.

CONCLUSIONS

Our study identified the HMOX1 pathway signature was a potential prognostic factor of progression-free survival for TKI + IO combination therapy in the advanced RCC in different cohort, especially in first-line management of mRCC in the Javelin 101 cohort. Moreover, HMOX1 signature was associated with T-cell function in tumor environment.

Inflammatory Networks in Renal Cell Carcinoma

Cancer-associated inflammation has been established as a hallmark feature of almost all solid cancers. Tumor-extrinsic and intrinsic signaling pathways regulate the process of cancer-associated inflammation. Tumor-extrinsic inflammation is triggered by many factors, including infection, obesity, autoimmune disorders, and exposure to toxic and radioactive substances. Intrinsic inflammation can be induced by genomic mutation, genome instability and epigenetic remodeling in cancer cells that promote immunosuppressive traits, inducing the recruitment and activation of inflammatory immune cells. In RCC, many cancer cell-intrinsic alterations are assembled, upregulating inflammatory pathways, which enhance chemokine release and neoantigen expression. Furthermore, immune cells activate the endothelium and induce metabolic shifts, thereby amplifying both the paracrine and autocrine inflammatory loops to promote RCC tumor growth and progression. Together with tumor-extrinsic inflammatory factors, tumor-intrinsic signaling pathways trigger a Janus-faced tumor microenvironment, thereby simultaneously promoting or inhibiting tumor growth. For therapeutic success, it is important to understand the pathomechanisms of cancer-associated inflammation, which promote cancer progression. In this review, we describe the molecular mechanisms of cancer-associated inflammation that influence cancer and immune cell functions, thereby increasing tumor malignancy and anti-cancer resistance. We also discuss the potential of anti-inflammatory treatments, which may provide clinical benefits in RCCs and possible avenues for therapy and future research.