Crosstalk Between Metabolism and Immune Activity Reveals Four Subtypes With Therapeutic Implications in Clear Cell Renal Cell Carcinoma

Stage IV renal cell carcinoma achieves pathologic complete response after two ipilimumab plus nivolumab courses despite severe immune-related adverse events: a case report

BACKGROUND

Ipilimumab (Ipi) plus nivolumab (Nivo) is the recommended first-line treatment for renal cell carcinoma (RCC). This report describes a case where pancreatic metastases disappeared after only two courses of Ipi + Nivo therapy. The primary tumor was cured by surgery, and a pathological Complete Response (pCR) was observed despite multiple serious immune-related Adverse Events (irAEs).

CASE PRESENTATION

A 54-year-old woman with RCC and pancreatic metastasis at stage IV, diagnosed with intermediate risk according to the International Metastatic RCC Database Consortium classification, underwent initiation of Ipi + Nivo therapy. On day 26, she developed hyperthyroidism accompanied by tachycardia, leading to the commencement of metoprolol tartrate treatment. Following the resolution of tachycardia, a second course of Ipi + Nivo therapy was administered on day 50. By day 70, the patient exhibited Grade 3 hepatic dysfunction, followed by the onset of hypothyroidism on day 75, necessitating treatment with steroids and levothyroxine. After positive treatment, a Grade 3 skin disorder emerged on day 87 while tapering steroids, prompting treatment with methylprednisolone (mPSL) pulse therapy. The skin disorder responded to steroids, allowing for tapering. However, on day 113, a recurrence of Grade 3 skin disorder occurred, necessitating another mPSL pulse. The patient responded well to treatment, exhibiting improvement in her condition. On day 131, she presented at the hospital with complaints of respiratory distress, prompting a Computed Tomography (CT) scan that revealed interstitial pneumonia. By day 272, subsequent CT imaging showed the disappearance of pancreatic metastasis and shrinkage of the primary tumor. On day 294, she underwent a laparoscopic left nephrectomy. Pathological analysis confirmed a pCR in the primary tumor, indicating successful eradication of RCC through surgical intervention.

CONCLUSIONS

This case report presents a scenario where multiple severe irAEs appeared in a patient, yet metastases disappeared after only two courses of Ipi + Nivo therapy. The patient was ultimately cured by surgery and achieved a pCR. This case highlights that despite the occurrence of severe irAEs during RCC treatment with Ipi + Nivo therapy, they can be managed appropriately to maximize the therapeutic effects of checkpoint inhibitors.

The value of a dual-energy CT Iodine map radiomics model for the prediction of collagen fiber content in the ccRCC tumor microenvironment

BACKGROUND AND PURPOSE

Renal cell carcinoma (RCC) is a heterogeneous group of cancers. The collagen fiber content in the tumor microenvironment of renal cancer has an important role in tumor progression and prognosis. A radiomics model was developed from dual-energy CT iodine maps to assess collagen fiber content in the tumor microenvironment of ccRCC.

METHODS

A total of 87 patients with ccRCC admitted to our hospital were included in this retrospective study. Among them, 59 cases contained large amounts of collagen fibers and 28 cases contained a small amount of collagen fibers. We established a radiomics model using preoperative dual-energy CT scan Iodine map (IV) imaging to distinguish patients with multiple collagen fibers from those with few collagen fibers in the tumor microenvironment of ccRCC. We extracted features from dual-energy CT Iodine map images to evaluate the effects of six classifiers, namely k-nearest neighbor (KNN), support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), logistic regression (LR), and decision tree (DT). The effects of the models built based on the dynamic and venous phases are also compared. Model performance was evaluated using quintuple cross-validation and area under the receiver operating characteristic curve (AUC). In addition, a clinical model was developed to assess the clinical factors affecting collagen fiber content.

RESULTS

Compared to KNN, SVM, and LR classifiers, RF, DT, and XGBoost classifiers trained with higher AUC values, with training sets of 0.997, 1.0, and 1.0, respectively. In the validation set, the highest AUC was found in the SVM classifier with a size of 0.722. In the comparative test of the active and intravenous phase models, the SVM classifier had the best effect with its validation set AUC of 0.698 and 0.741. In addition, there was a statistically significant effect of patient age and maximum tumor diameter on the collagen fiber content in the tumor microenvironment of kidney cancer.

CONCLUSION

Radionics features based on preoperative dual-energy CT IV can be used to predict the amount of collagen fibers in the tumor microenvironment of renal cancer. This study better informs clinical prognosis and patient management. Iodograms may add additional value to dual-energy CTs.

Small Leucine-Rich Proteoglycan PODNL1 Identified as a Potential Tumor Matrix-Mediated Biomarker for Prognosis and Immunotherapy in a Pan-Cancer Setting

The podocan-like protein 1 (PODNL1), an important member of the small leucine-rich proteoglycans (SLRP) family, is a crucial component of the tumor microenvironment (TME). But its prognostic values and the role in the TME have not been systematically estimated in a pan-cancer setting. Targeting PODNL1, a systematic exploration into the TCGA datasets, reconciling with the analyses of single-cell transcriptomes and immunotherapeutic cohorts in cancers, and validation by tissue microarray-based multiplex immunofluorescence staining was performed. PODNL1 was significantly correlated with the poor prognosis and immunotherapeutic responses in various cancers. In-depth demonstration of molecular mechanisms indicated that PODNL1 expressions were notably positively correlated with cancer-associated fibroblast (CAF) infiltration levels in 33 types of cancers. It also positively correlated with the pan-fibroblast TGF-β response signature score, and the hallmarks including TGF-β, TNF-α, inflammatory response, apical junction, epithelial-mesenchymal transition and hedgehog in pan-cancer. Furthermore, high PODNL1 expressions were positively related with the regulation of tumor-promoting TGF-β signaling through downregulating SMAD2/3:4 heterotrimer regulations transcription and up-regulating the pathway restricted SMAD protein phosphorylation. Single-cell transcriptome analyses and immunofluorescence validations indicated that PODNL1 was predominantly expressed in the cancer cells and CAFs in various cancers. Additionally, the heterogeneity of cancer genotype-phenotype cross-talking was also observed associated with PODNL1. Our systematic study indicates that PODNL1 plays an important role in the complex regulation network of tumor progression, and lays a foundation for further exploration to develop PODNL1 as a valuable matrix-mediated biomarker for cancer immunotherapy and prognosis in a pan-cancer setting.

The expression pattern of pyruvate dehydrogenase kinases predicts prognosis and correlates with immune exhaustion in clear cell renal cell carcinoma

Renal cancer cells constitute a paradigm of tumor cells with a glycolytic reprogramming which drives metabolic alterations favouring cell survival and transformation. We studied the expression and activity of pyruvate dehydrogenase kinases (PDK1-4), key enzymes of the energy metabolism, in renal cancer cells. We analysed the expression, subcellular distribution and clinicopathological correlations of PDK1-4 by immunohistochemistry of tumor tissue microarray samples from a cohort of 96 clear cell renal cell carcinoma (ccRCC) patients. Gene expression analysis was performed on whole tumor tissue sections of a subset of ccRCC samples. PDK2 and PDK3 protein expression in tumor cells correlated with lower patient overall survival, whereas PDK1 protein expression correlated with higher patient survival. Gene expression analysis revealed molecular association of PDK2 and PDK3 expression with PI3K signalling pathway, as well as with T cell infiltration and exhausted CD8 T cells. Inhibition of PDK by dichloroacetate in human renal cancer cell lines resulted in lower cell viability, which was accompanied by an increase in pAKT. Together, our findings suggest a differential role for PDK enzymes in ccRCC progression, and highlight PDK as actionable metabolic proteins in relation with PI3K signalling and exhausted CD8 T cells in ccRCC.

Redox Signaling Modulates Activity of Immune Checkpoint Inhibitors in Cancer Patients

Although immunotherapy is already a staple of cancer care, many patients may not benefit from these cutting-edge treatments. A crucial field of research now focuses on figuring out how to improve treatment efficacy and assess the resistance mechanisms underlying this uneven response. For a good response, immune-based treatments, in particular immune checkpoint inhibitors, rely on a strong infiltration of T cells into the tumour microenvironment. The severe metabolic environment that immune cells must endure can drastically reduce effector activity. These immune dysregulation-related tumour-mediated perturbations include oxidative stress, which can encourage lipid peroxidation, ER stress, and T regulatory cells dysfunction. In this review, we have made an effort to characterize the status of immunological checkpoints, the degree of oxidative stress, and the part that latter plays in determining the therapeutic impact of immunological check point inhibitors in different neoplastic diseases. In the second section of the review, we will make an effort to assess new therapeutic possibilities that, by affecting redox signalling, may modify the effectiveness of immunological treatment.

Endoplasmic Reticulum Stress in Renal Cell Carcinoma

The endoplasmic reticulum is an organelle exerting crucial functions in protein production, metabolism homeostasis and cell signaling. Endoplasmic reticulum stress occurs when cells are damaged and the capacity of this organelle to perform its normal functions is reduced. Subsequently, specific signaling cascades, together forming the so-called unfolded protein response, are activated and deeply impact cell fate. In normal renal cells, these molecular pathways strive to either resolve cell injury or activate cell death, depending on the extent of cell damage. Therefore, the activation of the endoplasmic reticulum stress pathway was suggested as an interesting therapeutic strategy for pathologies such as cancer. However, renal cancer cells are known to hijack these stress mechanisms and exploit them to their advantage in order to promote their survival through rewiring of their metabolism, activation of oxidative stress responses, autophagy, inhibition of apoptosis and senescence. Recent data strongly suggest that a certain threshold of endoplasmic reticulum stress activation needs to be attained in cancer cells in order to shift endoplasmic reticulum stress responses from a pro-survival to a pro-apoptotic outcome. Several endoplasmic reticulum stress pharmacological modulators of interest for therapeutic purposes are already available, but only a handful were tested in the case of renal carcinoma, and their effects in an in vivo setting remain poorly known. This review discusses the relevance of endoplasmic reticulum stress activation or suppression in renal cancer cell progression and the therapeutic potential of targeting this cellular process for this cancer.

Phospholipase C delta 1 inhibits WNT/β-catenin and EGFR-FAK-ERK signaling and is disrupted by promoter CpG methylation in renal cell carcinoma

BACKGROUND

PLCD1, located at 3p22, encodes an enzyme that mediates cellular metabolism and homeostasis, intracellular signal transduction and movement. PLCD1 plays a pivotal role in tumor suppression of several types of cancers; however, its expression and underlying molecular mechanisms in renal cell carcinoma (RCC) pathogenesis remain elusive.

METHODS

RT-PCR and Western blot were used to detect PLCD1 expression in RCC cell lines and normal tissues. Bisulfite treatment, MSP and BGS were utilized to explore the CpG methylation status of PLCD1 promoter. Online databases were analyzed for the association between PLCD1 expression/methylation and patient survival. In vitro experiments including CCK8, colony formation, wound-healing, transwell migration and invasion, immunofluorescence and flow cytometry assays were performed to evaluate tumor cell behavior. Luciferase assay and Western blot were used to examine effect of PLCD1 on WNT/β-catenin and EGFR-FAK-ERK signaling.

RESULTS

We found that PLCD1 was widely expressed in multiple adult normal tissues including kidney, but frequently downregulated or silenced in RCC due to its promoter CpG methylation. Restoration of PLCD1 expression inhibited the viability, migration and induced G2/M cell cycle arrest and apoptosis in RCC cells. PLCD1 restoration led to the inhibition of signaling activation of WNT/β-catenin and EGFR-FAK-ERK pathways, and the EMT program of RCC cells.

CONCLUSIONS

Our results demonstrate that PLCD1 is a potent tumor suppressor frequently inactivated by promoter methylation in RCC and exerts its tumor suppressive functions via suppressing WNT/β-catenin and EGFR-FAK-ERK signaling. These findings establish PLCD1 as a promising prognostic biomarker and treatment target for RCC.

Prognosis and Personalized Treatment Prediction in Different Mutation-Signature Hepatocellular Carcinoma

Introduction

Mutation patterns have been extensively explored to decipher the etiologies of hepatocellular carcinoma (HCC). However, the study and potential clinical role of mutation patterns to stratify high-risk patients and optimize precision therapeutic strategies remain elusive in HCC.

Methods

Using exon-sequencing data in public (n=362) and in-house (n=30) cohorts, mutation signatures were extracted to decipher relationships with the etiology and prognosis in HCC. The proteomics (n=159) and cell-line transcriptome data (n=1019) were collected to screen the implication of sensitive drugs. A novel multi-step machine-learning framework was then performed to construct a classification predictor, including recognizing stable reversed gene pairs, establishing a robust prediction model, and validating the robustness of the predictor in five independent cohorts (n=900).

Results

Two heterogeneous mutation signature clusters were identified, and a high-risk prognosis cluster was recognized for further analysis. Notably, mutation signature cluster 1 (MSC1) was featured by activated anti-tumor immune and metabolism dysfunctional states, higher genomic instability (high TMB, SNV neoantigen, indel neoantigens, and total neoantigens), and a dismal prognosis. Notably, MSC performed as an independent risk factor than clinical traits (eg, stage, vascular invasion). Additionally, afatinib and canertinib were recognized which might have potential therapeutic implications in MSC1, and the targets of these drugs presented a higher expression in both gene and protein levels in HCC.

Discussion

Our studies may provide a promising platform for improving prognosis and tailoring therapy in HCC.

Development and validation of prognostic models for colon adenocarcinoma based on combined immune-and metabolism-related genes

Background

The heterogeneity of tumor tissue is one of the reasons for the poor effect of tumor treatment, which is mainly affected by the tumor immune microenvironment and metabolic reprogramming. But more research is needed to find out how the tumor microenvironment (TME) and metabolic features of colon adenocarcinoma (COAD) are related.

Methods

We obtained the transcriptomic and clinical data information of COAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering analysis was used to identify different molecular subtypes, identify differentially expressed genes (DEGs) associated with immune-and metabolism-related genes (IMRGs) prognosis. Univariate and multivariable Cox regression analysis and Lasso regression analysis were applied to construct the prognostic models based on the IMRG risk score. The correlations between risk scores and TME, immune cell infiltration, and immune checkpoint genes were investigated. Lastly, potential appropriate drugs related to the risk score were screened by drug sensitivity analysis.

Results

By consensus clustering analysis, we identified two distinct molecular subtypes. It was also found that the multilayered IMRG subtypes were associated with the patient's clinicopathological characteristics, prognosis, and TME cell infiltration characteristics. Meanwhile, a prognostic model based on the risk score of IMRGs was constructed and its predictive power was verified internally and externally. Clinicopathological analysis and nomogram give it better clinical guidance. The IMRG risk score plays a key role in immune microenvironment infiltration. Patients in the high-risk groups of microsatellite instability (MSI) and tumor mutational burden (TMB) were found to, although with poor prognosis, actively respond to immunotherapy. Furthermore, IMRG risk scores were significantly associated with immune checkpoint gene expression. The potential drug sensitivity study helps come up with and choose a chemotherapy treatment plan.

Conclusion

Our comprehensive analysis of IMRG signatures revealed a broad range of regulatory mechanisms affecting the tumor immune microenvironment (TIME), immune landscape, clinicopathological features, and prognosis. And to explore the potential drugs for immunotherapy. It will help to better understand the molecular mechanisms of COAD and provide new directions for disease treatment.

Cuproptosis status affects treatment options about immunotherapy and targeted therapy for patients with kidney renal clear cell carcinoma

The development of immunotherapy has changed the treatment landscape of advanced kidney renal clear cell carcinoma (KIRC), offering patients more treatment options. Cuproptosis, a novel cell death mode dependent on copper ions and mitochondrial respiration has not yet been studied in KIRC. We assembled a comprehensive cohort of The Cancer Genome Atlas (TCGA)-KIRC and GSE29609, performed cluster analysis for typing twice using seven cuproptosis-promoting genes (CPGs) as a starting point, and assessed the differences in biological and clinicopathological characteristics between different subtypes. Furthermore, we explored the tumor immune infiltration landscape in KIRC using ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) and the potential molecular mechanisms of cuproptosis in KIRC using enrichment analysis. We constructed a cuproptosis score (CUS) using the Boruta algorithm combined with principal component analysis. We evaluated the impact of CUS on prognosis, targeted therapy, and immunotherapy in patients with KIRC using survival analysis, the predictions from the Cancer Immunome Atlas database, and targeted drug susceptibility analysis. We found that patients with high CUS levels show poor prognosis and efficacy against all four immune checkpoint inhibitors, and their immunosuppression may depend on TGFB1. However, the high-CUS group showed higher sensitivity to sunitinib, axitinib, and elesclomol. Sunitinib monotherapy may reverse the poor prognosis and result in higher progression free survival. Then, we identified two potential CPGs and verified their differential expression between the KIRC and the normal samples. Finally, we explored the effect of the key gene FDX1 on the proliferation of KIRC cells and confirmed the presence of cuproptosis in KIRC cells. We developed a targeted therapy and immunotherapy strategy for advanced KIRC based on CUS. Our findings provide new insights into the relationship among cuproptosis, metabolism, and immunity in KIRC.