Immunotherapy for metastatic renal cell carcinoma: A systematic review

A novel prognostic predictor of immune microenvironment and therapeutic response in clear cell renal cell carcinoma based on angiogenesis-immune-related gene signature

Background

Clear cell renal cell carcinoma (ccRCC), the most common type of RCC, typically produces no symptoms initially. Patients with ccRCC are at increased risk of developing advanced metastatic disease due to the absence of dependable and effective prognostic biomarkers. Therefore, it is particularly urgent to find optimal stratification of patients with ccRCC to distinguish the clinical benefits of different malignant degrees. Angiogenesis has a profound impact on the malignant behavior of renal cancer cells, and anti-angiogenic drugs have been applied to metastatic renal cancer patients. Moreover, immune function dysregulation is also a significant factor in tumorigenesis. We aim to construct a predictive model that combines angiogenesis and immune-related genes (AIRGs) to aid clinicians in predicting ccRCC prognosis.

Methods

We gathered transcriptome and clinicopathology data from two datasets, the E-MTAB-1980 dataset and the Cancer Genome Atlas (TCGA). We utilized consensus clustering to find new molecular subgroups. A predictive model for the prognosis of angiogenesis-immune-associated genes (AIRGs) was conducted by the lasso and multivariate Cox regression analysis. The signature's predictive ability was then tested in different datasets. Meticulous scrutiny and comprehensive assessment were undertaken, both internally and externally, to establish the prognostic model. Analyses of immunogenomics were carried out to examine the relationship between risk scores and clinical/immune features, including immune cell infiltration, genomic alterations, and response to targeted and immunotherapy therapy.

Results

Our prognostic signature, comprising 4 AIRGs, stood as an independent prognostic factor for ccRCC, while risk scores emerged as a novel indicator for forecasting overall survival. Risk scores exhibited significant associations with various immunophenotypic factors, such as oncogenic pathways, antitumor response, different immune cell infiltration, antitumor immunity, and response to targeted and immunotherapy therapy.

Conclusions

AIRGs-based prognostic prediction model could effectively predict immunotherapy responses and survival outcomes of ccRCC.

Construction of a nomogram to predict the survival of metastatic gastric cancer patients that received immunotherapy

Background

Immunotherapy has shown promising results for metastatic gastric cancer (MGC) patients. Nevertheless, not all patients can benefit from anti-PD-1 treatment. Thus, this study aimed to develop and validate a prognostic nomogram for MGC patients that received immunotherapy.

Methods

Herein, MGC patients treated with anti-PD-1 between 1 October 2016 and 1 June 2022 at two separate Chinese PLA General Hospital centers were enrolled and randomly divided into training and validation sets (186 and 80 patients, respectively). The nomogram was constructed based on a multivariable Cox model using baseline variables from the training cohort. Its predictive accuracy was validated by the validation set. The consistency index (C-index) and calibration plots were used to evaluate the discriminative ability and accuracy of the nomogram. The net benefit of the nomogram was evaluated using decision curve analysis (DCA). Finally, we stratified patients by median total nomogram scores and performed Kaplan–Meier survival analyses.

Results

We developed the nomogram based on the multivariate analysis of the training cohort, including four parameters: surgery history, treatment line, lung immune prognostic index (LIPI), and platelet-to-lymphocyte ratio (PLR). The C-index of the nomogram was 0.745 in the training set. The calibration curve for 1- and 2-year survival showed good agreement between nomogram predictions and actual observations. In the validation group, the calibration curves demonstrated good performance of the nomogram, with a C-index for overall survival (OS) prediction of 0.713. The OS of patients with a score greater than the median nomogram score was significantly longer than patients with a score lower or equal to the median (p < 0.001).

Conclusion

We constructed a nomogram to predict the outcomes of MGC patients that received immunotherapy. This nomogram might facilitate individualized survival predictions and be helpful during clinical decision-making for MGC patients under anti-PD-1 therapy.

FOXP4-AS1 May be a Potential Prognostic Biomarker in Human Cancers: A Meta-Analysis and Bioinformatics Analysis

Background

Cancer is one of the leading causes of death worldwide. Early diagnosis can significantly lower cancer-related mortality. Studies have shown that the lncRNA Forkhead box P4 antisense RNA 1 (FOXP4-AS1) is aberrantly expressed in various solid tumors. A meta-analysis was performed to evaluate the correlation of FOXP4-AS1 with the prognosis of cancer patients and determine the clinical value of FOXP4-AS1 as a potential diagnostic marker.

Methods

Correlational studies from the Web of Science, Embase, OVID, Cochrane and PubMed databases were screened (up to April 1, 2021). Meta-analysis was performed using Stata SE12.0 software.

Results

Eleven original studies with 1,332 patients who were diagnosed with a solid cancer (nasopharyngeal carcinoma, hepatocellular carcinoma, colorectal cancer, gastric cancer, osteosarcoma, mantle cell lymphoma, prostate cancer, and pancreatic ductal adenocarcinoma) were included in the meta-analysis. High expression of FOXP4-AS1 was correlated with poor overall survival (OS) (HR = 1.77, 95% CI 1.29-2.44, P < 0.001) and shorter disease-free survival (DFS) (HR = 1.66, 95% CI 1.01-2.72, P = 0.044). Subgroup analysis based on sample size, follow-up time and Newcastle-Ottawa Scale (NOS) score revealed significant differences between FOXP4-AS1 levels and OS (P < 0.05). However, the expression level of FOXP4-AS1 was not significantly correlated with the OS of gastric cancer patients (P = 0.381). High expression of FOXP4-AS1 was predictive of a larger tumor size (OR = 3.82, 95% CI 2.3-6.3, P < 0.001).

Conclusions

Overexpression of FOXP4-AS1 correlates with poor prognosis of cancer patients, and is a potential prognostic biomarker and therapeutic target.

Systematic Review Registration

PROSPERO, identifier CRD42021245267.

Neutrophil-to-Lymphocyte Ratio (NLR) Predicts PD-1 Inhibitor Survival in Patients with Metastatic Gastric Cancer

Background and Aims

Biomarkers for systemic inflammation have been introduced into clinical practice for risk-rating in cancer patients' treatment. This study is aimed at confirming the prognostic role of the neutrophil-to-lymphocyte ratio (NLR) as an effective biomarker for patients with metastatic gastric cancer (MGC) receiving anti-PD-1 agents.

Method

Patients with MGC who received anti-PD-1 treatment at the Chinese PLA General Hospital between January 2016 and November 2020 were reviewed. The study analyzed the association of NLR and overall survival (OS) or progression-free survival (PFS) and antitumor response rate with PD-1 inhibitors.

Results

137 patients were included in the final analysis. The area under the curve value of NLR for 6-month OS was 0.71. The best cut-off value for NLR was 3.23. NLR < 3.23 was associated with longer OS (HR = 0.38, 95% CI, 0.26-0.57, p < 0.001) and PFS (HR = 0.42, 95% CI, 0.29-0.62, p < 0.001) in patients with MGC. No significant difference was observed in the objective response rate (ORR) (35.8% vs. 28.6%, p = 0.377) and disease control rate (DCR) (86.4% vs. 78.6%, p = 0.229) in the NLR < 3.23 group and in the NLR ≥ 3.23 group, respectively. Univariate analysis and multivariate analysis found that NLR was an independent prognosis biomarker for PFS and OS.

Conclusions

Pretreatment elevated NLR was significantly associated with inferior PFS and OS in patients with MGC who received anti-PD-1 inhibitors. Clinicians need to consider patients with elevated NLR for decisions on immunotherapy strategy.

Clinicopathological and Prognostic Significance of Long Non-coding RNA MIAT in Human Cancers: A Review and Meta-Analysis

Background: Although the treatment of cancer has made evident progress, its morbidity and mortality are still high. A tumor marker is a critical indicator for early cancer diagnosis, and timely cancer detection can efficiently help improve the prognosis of patients. Therefore, it is necessary to identify novel markers associated with cancer. LncRNA myocardial infarction associated transcript (MIAT) is a newly identified tumor marker, and in this study, we aimed to explore the relationship between MIAT and clinicopathological features and patient prognosis.

Methods: We searched PubMed, Embase, Web of Science, and The Cochrane Library from inception to September 2020 to identify correlational studies. Then, we extracted valid data and used Stata software to make forest plots. We used the hazard ratio (HR) or odds ratio (OR) with 95% CI to evaluate the relationship between aberrant expression of MIAT and patients' prognosis and clinicopathological features.

Results: The study included 21 studies, containing 2,048 patients. Meta-analysis showed that overexpression of lncRNA MIAT was associated with poor overall survival (OS) (HR = 1.60, 95% CI, 1.31–1.96, p < 0.001). In addition, high expression of MIAT could forecast tumor size (OR = 2.26, 95% CI 1.34–3.81, p = 0.002), distant metastasis (OR = 2.54, 95% CI 1.84–3.50, p < 0.001), TNM stage (OR = 2.38, 95% CI 1.36–4.18, p = 0.002), lymph node metastasis (OR = 2.59, 95% CI 1.25–5.36, p = 0.011), and the degree of differentiation (OR = 2.65, 95% CI 1.54–4.58, p < 0.001). However, other clinicopathological features, including age (OR = 1.07, 95% CI 0.87–1.32, p = 0.516), gender (OR = 0.95, 95% CI 0.77–1.19, p = 0.668), and histology (OR = 0.72, 95% CI 0.48–1.10, p = 0.128) were not significantly different from high expression of MIAT.

Conclusions: Our study showed that overexpression of MIAT is related to poor overall survival and clinicopathological features. MIAT can be considered a novel tumor marker to help diagnose tumors earlier and improve patient prognosis.

Correlation Between Prognostic Biomarker SLC1A5 and Immune Infiltrates in Various Types of Cancers Including Hepatocellular Carcinoma

Background

Solute carrier family 1 member 5 (SLC1A5) is a major glutamine transporter and plays a key role in tumor growth. The main objectives of this study were to visualize the prognostic landscape of SLC1A5 in multiple cancers and determine the relations between SLC1A5 expression and tumor immunity.

Methods

SLC1A5 expression and its effect on tumor prognosis were analyzed using multiple online tools Oncomine, Gene Expression Profiling Interactive Analysis, PrognoScan, and Kaplan-Meier plotter with their own datasets as well as the data from The Cancer Genome Atlas. The correlations between SLC1A5 and tumor immune infiltrates were determined via TIMER.

Results

SLC1A5 expression was significantly higher in several types of cancers, including hepatocellular carcinoma (HCC), compared with corresponding normal tissues. High SLC1A5 expression correlated with poor overall survival and with disease-free survival related to alcohol consumption. Moreover, SLC1A5 expression correlated positively with the numbers of tumor-infiltrating B cells, CD4⁺ T and CD8⁺ T cells, macrophages, neutrophils, and dendritic cells in HCC and in lower-grade glioma (LGG). Also, SLC1A5 expression showed strong correlations with diverse immune marker sets in HCC and LGG, indicating its role in regulating tumor immunity.

Conclusions

SLC1A5 represents a useful prognostic biomarker in multiple cancers, and its expression correlates highly with tumor immune-cell infiltration, especially in HCC and LGG.

The Prognostic Value of Pre-treatment Hemoglobin (Hb) in Patients With Advanced or Metastatic Gastric Cancer Treated With Immunotherapy

Background

Biomarkers such as prevailing PD-L1 expression and TMB have been proposed as a way of predicting the outcome of immunotherapy in patients with advanced gastric cancer (AGC) and metastatic gastric cancer (MGC). Our study aims to investigate whether there is a link between pretreatment hemoglobin (Hb) levels and survival to immunotherapy in patients with AGC and MGC.

Methods

We retrospectively reviewed patients with AGC or MGC treated at the oncology department of the Chinese PLA general hospital receiving PD-1 inhibitor. The Propensity Score Matching (PSM) (1:1) was performed to balance potential baseline confounding factors. Progression-free survival (PFS) and overall survival (OS) was analyzed among different Hb level (normal Hb group and decreased Hb group). Objective response rate (ORR), disease control rate (DCR) were also analyzed. Univariate analysis and multivariate analysis were performed further to validate the prognostic value of Hb level.

Results

We included 137 patients with AGC and MGC who received PD-1 inhibitors (including Pembrolizumab, Nivolumab, Sintilimab, Toripalimab) in this study. After PSM matching, there were no significant differences between the two groups for baseline characteristics. Within the matched cohort, the median PFS was 7.8 months in the normal Hb level group and 4.3 months in the decreased Hb group (HR 95% CI 0.5(0.31, 0.81), P=0.004). The OS was 14.4 months with normal Hb level as compared with 8.2 months with decreased Hb level(HR 95% CI 0.59(0.37, 0.94), P=0.024). The ORR was 40.7% and DCR was 83.0% in the normal Hb group, while the ORR was 25.5% and DCR was 85.1% in the decreased Hb group. No significant differences were found in the ORR and DCR between the two groups (P=0.127, P=0.779). Univariate analysis and multivariate analysis showed that Hb level was only independent predictor for PFS and baseline Hb level was significant prognostic factor influencing the OS. Only when patients had normal Hb level, anti-pd-1 monotherapy or combined with chemotherapy was superior to anti-pd-1 plus anti-angiogenic therapy with respect to PFS (10.3 m vs 2.8 m, HR 95% CI 0.37(0.15, 0.95), P=0.031) and OS(15 m vs 5.7 m, HR 95% CI 0.21 (0.08, 0.58), P=0.001).

Conclusions

Our study have demonstrated that pretreatment Hb level was an independent prognostic biomarker in term of PFS and OS with immunotherapy for AGC and MGC patients. Correction of anemia for GC patients as immunotherapy would be a strategy to improve the survival. More data was warranted to further influence this finding.

The Diagnostic and Immunotherapeutic Value of CD248 in Renal Cell Carcinoma

Background: Renal cell carcinoma (RCC) is the most common malignancy in the urinary system. Despite substantial improvements in available treatment options, the survival outcome of advanced RCC is unsatisfactory. Identifying novel biomarkers to assist in early diagnosis and to screen patients who are sensitive to immunotherapy would be beneficial. CD248 is a promising candidate that deserves to be investigated.

Methods: The Cancer Genome Atlas (TCGA) data set and clinical specimens were adopted to analyze the expression of CD248 between normal and tumor tissues. Univariate and multivariate Cox regression analyses were employed to identify independent prognostic factors and construct a CD248-based prognostic signature. The correlation among the present signature, tumor-infiltrating immune cells (TIICs), the tumor mutation burden (TMB), and immunomodulatory molecules was evaluated. The weighted gene co-expression network analysis (WGCNA), the enrichment analysis, and the miRNA correlation analysis were performed to explore the underlying mechanism of CD248 in the progression of RCC.

Results: The overexpression of CD248 in RCC was related to a poor prognosis, and a CD248-based prognostic signature could precisely stratify patients with RCC with different survival outcomes regardless of the training or testing cohort. The present signature could reflect the immunosuppressive landscape of RCC (i.e., increased infiltration of regulatory T cells and upregulated immune checkpoints), accompanied by deteriorated clinicopathologic indexes. The TMB and immunostimulatory molecules expression also increased with the risk score generated from the present signature. CD248 co-expressed gene sets were identified through the WGCNA algorithm, and several immunosuppressive Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched. The result of CD248-correlated miRNA further emphasized the importance of CD248 in RCC.

Conclusion: CD248 is a valuable biomarker to improve the diagnostic and therapeutic efficiency of RCC. The immunosuppressive effect of CD248 co-expressed genes may provide insight for the present study, and miRNA would help to reveal the mechanism of the expressive regulation of CD248.

Mechanisms of Pharmaceutical Therapy and Drug Resistance in Esophageal Cancer

Pharmaceutical therapies are essential for esophageal cancer (EC). For the advanced EC, the neoadjuvant therapy regimen, including chemotherapy plus radiotherapy and/or immunotherapy, is effective to achieve clinical benefit, even pathological complete response. For the unresectable, recurrent, and metastatic EC, the pharmaceutical therapy is the limited effective regimen to alleviate the disease and prolong the progression-free survival and overall survival. In this review, we focus on the pharmaceutical applications in EC treatment including cytotoxic agents, molecular targeted antibodies, and immune checkpoint inhibitors (ICIs). The chemotherapy regimen is based on cytotoxic agents such as platinum-based complexes, fluorinated pyrimidines and taxenes. Although the cytotoxic agents have been developed in past decades, the standard chemotherapy regimen is still the cisplatin and 5-FU or paclitaxel because the derived drugs have no significant advantages of overcoming the shortcomings of side effects and drug resistance. The targeted molecular therapy is an essential supplement for chemotherapy; however, there are only a few targeted therapies available in clinical practice. Trastuzumab and ramucirumab are the only two molecular therapy drugs which are approved by the US Food and Drug Administration to treat advanced and/or metastatic EC. Although the targeted therapy usually achieves effective benefits in the early stage therapy of EC, the patients will always develop drug resistance during treatment. ICIs have had a significant impact on routine clinical practice in cancer treatment. The anti-programmed cell death-1 monoclonal antibodies pembrolizumab and nivolumab, as the ICIs, are recommended for advanced EC by several clinical trials. However, the significant issues of pharmaceutical treatment are still the dose-limiting side effects and primary or secondary drug resistance. These defects of pharmaceutical therapy restrain the clinical application and diminish the effectiveness of treatment.

A Novel Immune-Related lncRNA-Based Model for Survival Prediction in Clear Cell Renal Cell Carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer whose incidence and mortality rate are increasing. Identifying immune-related lncRNAs and constructing a model would probably provide new insights into biomarkers and immunotherapy for ccRCC and aid in the prognosis prediction.

METHODS

The transcription profile and clinical information were obtained from The Cancer Genome Atlas (TCGA). Immune-related gene sets and transcription factor genes were downloaded from GSEA website and Cistrome database, respectively. Tumor samples were divided into the training set and the testing set. Immune-related differentially expressed lncRNAs (IDElncRNAs) were identified from the whole set. Univariate Cox regression, LASSO, and stepwise multivariate Cox regression were performed to screen out ideal prognostic IDElncRNAs (PIDElncRNAs) from the training set and develop a multi-lncRNA signature.

RESULTS

Consequently, AC012236.1, AC078778.1, AC078950.1, AC087318.1, and AC092535.4 were screened to be significantly related to the prognosis of ccRCC patients, which were used to establish the five-lncRNA signature. Its wide diagnostic capacity was revealed in different subgroups of clinical parameters. Then AJCC-stage, Fuhrman-grade, pharmaceutical, age, and risk score regarded as independent prognostic factors were integrated to construct a nomogram, whose good performance in predicting 3-, 5-, and 7-year overall survival of ccRCC patients was revealed by time-dependent ROC curves and verified by the testing sets and ICGC dataset. The calibration plots showed great agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis showed the signature and each lncRNA were mainly enriched in pathways associated with regulation of immune response. Several kinds of tumor-infiltrating immune cells like regulatory T cells, T follicular helper cells, CD8⁺ T cells, resting mast cells, and naïve B cells were significantly correlated with the signature.

CONCLUSION

Therefore, we constructed a five-lncRNA model integrating clinical parameters to help predict the prognosis of ccRCC patients. The five immune-related lncRNAs could potentially be therapeutic targets for immunotherapy in ccRCC in the future.

Comparative Effects Between Direct Oral Anticoagulants for Acute Venous Thromboembolism: Indirect Comparison From Randomized Controlled Trials

Background: There is no direct comparison from clinical trials amongst the direct oral anticoagulants (DOACs) in patients with acute venous thromboembolism (VTE), leaving an evidence gap in decision-making regarding the choice of a DOAC.

Methods: We performed a systematic review for an indirect comparison from randomized controlled trials (RCTs) for comparative effects amongst DOACs in the patients with acute VTE.

Results: A total of 16 RCTs were included for analyses, among which three for dabigatran (n = 7,963 patients), six rivaroxaban (n = 17,935), five apixaban (n = 12,823), and two edoxaban (n = 9,286). There was no significant difference in risk of recurrent VTE (evidence quality: low) and major bleeding (evidence quality: very low) for treatment effects between the four DOACs. Albeit non-significantly, apixaban seemed to have a lowest risk of major bleeding while rivaroxaban had a smallest risk of VTE. Although in general all the included trials were comparable, data from the included trials indicated that the assumption of transitivity may be challenged. Further methodological research including simulation studies, using a net-benefit or benefit-harm approach, running ranking probability analysis, and developing decision aids with machine-learning may be a worthwhile endeavor to help with the choice of DOACs in patients with acute VTE.

Conclusions: To conclude, based on results from the indirect comparison no significant difference in the efficacy and safety was found among the DOACs in patients with acute VTE. More evidence from direct comparative trials is needed to further inform the choice of DOACs in patients with acute VTE.

Immune Checkpoint Inhibitors in the Treatment of Renal Cancer: Current State and Future Perspective

Systemic treatment of renal cancer (RCC) has undergone remarkable changes over the past 20 years with the introduction of immunotherapeutic agents targeting programmed cell death (PD-1)/programmed death-ligand 1 (PD-L1) axis, as a single-agent or combined with anti-CTLA-4 monoclonal antibodies (MoAbs) or a multi-target vascular endothelial growth factor-(VEGF) tyrosine kinase inhibitor (TKI). In this paper, we review the main evidence on the use of Immune Checkpoint Inhibitors (ICIs) for RCC treatment from the first demonstration of activity of a nivolumab single agent in a phase I trial to the novel combination strategies (anti-PD-1 plus anti-CTLA4 or anti-PD-1 plus TKI). In addition, we discuss the use of anti-PD-1/PD-L1 agents in patients with non-clear cells and rare histological subtype RCC. Then, we critically examine the current findings in biomarkers that have been proposed to be prognostic or predictive to the response of immunotherapy including immune gene expression signature, B7-H1 expression, PBRM1 loss of function, PD-L1 expression, frame shift indel count, mutations in bromodomain-containing genes in patients with MiT family translocation RCC (tRCC), high expression of the T-effector gene signature, and a high myeloid inflammation gene expression pattern. To date, a single biomarker as a predictor of response has not been established. Since the dynamic behavior of the immune response and the different impact of ICI treatment on patients with specific RCC subtypes, the integration of multiple biomarkers and further validation in clinical trials are needed.

Immuno-Metabolism and Microenvironment in Cancer: Key Players for Immunotherapy

Immune checkpoint inhibitors (ICIs) have changed therapeutic algorithms in several malignancies, although intrinsic and secondary resistance is still an issue. In this context, the dysregulation of immuno-metabolism plays a leading role both in the tumor microenvironment (TME) and at the host level. In this review, we summarize the most important immune-metabolic factors and how they could be exploited therapeutically. At the cellular level, an increased concentration of extracellular adenosine as well as the depletion of tryptophan and uncontrolled activation of the PI3K/AKT pathway induces an immune-tolerant TME, reducing the response to ICIs. Moreover, aberrant angiogenesis induces a hypoxic environment by recruiting VEGF, T_reg cells and immune-suppressive tumor associated macrophages (TAMs). On the other hand, factors such as gender and body mass index seem to affect the response to ICIs, while the microbiome composition (and its alterations) modulates both the response and the development of immune-related adverse events. Exploiting these complex mechanisms is the next goal in immunotherapy. The most successful strategy to date has been the combination of antiangiogenic drugs and ICIs, which prolonged the survival of patients with non-small-cell lung cancer (NSCLC) and hepatocellular carcinoma (HCC), while results from tryptophan pathway inhibition studies are inconclusive. New exciting strategies include targeting the adenosine pathway, TAMs and the microbiota with fecal microbiome transplantation.

Metastatic Renal Cell Carcinoma Masquerading as a Sphenoid Wing Meningioma

A 47-year-old man who presented with subacute binocular diplopia and a left head turn was found to have a right sixth nerve palsy and right optic disc edema. Radiologic imaging revealed a non-lytic right greater sphenoid wing mass with a dural tail, suggestive of a sphenoid wing meningioma. The patient underwent an orbitotomy with lesion biopsy; histopathologic analysis and subsequent imaging revealed the diagnosis of metastatic clear cell renal cell carcinoma. He developed new metastases despite systemic immunotherapy, and prognosis was guarded at last follow up 3 months after diagnosis. The authors present the first reported case of renal cell carcinoma metastatic to the sphenoid wing without sinus involvement, describing an atypical presentation of an aggressive malignancy that necessitates timely diagnosis for possible survival.

Prognostic value of immune-related genes in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma, and immune-related genes (IRGs) are key contributors to its development. In this study, the gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database and the cBioPortal database, respectively. IRGs were obtained from the ImmPort database. We analyzed the expression of IRGs in ccRCC, and discovered 681 that were differentially expressed between ccRCC and normal kidney tissues. Univariate Cox regression analysis was used to identify prognostic differentially expressed IRGs (PDEIRGs). Using Lasso regression and multivariate Cox regression analyses, we detected seven optimal PDEIRGs (PLAU, ISG15, IRF9, ARG2, RNASE2, SEMA3G and UCN) and used them to construct a risk model to predict the prognosis of ccRCC patients. This model accurately stratified patients with different survival outcomes and precisely identified patients with different mutation burdens. Our findings suggest the seven PDEIRGs identified in this study are valuable prognostic predictors in ccRCC patients. These genes could be used to investigate the developmental mechanisms of ccRCC and to design individualized treatments for ccRCC patients.

Signaling alterations caused by drugs and autophagy

Autophagy is an evolutionary conserved process that recycles cellular materials in times of nutrient restriction to maintain viability. In cancer therapeutics, the role of autophagy in response to multi-kinase inhibitors, alone or when combined with histone deacetylase (HDAC) inhibitors acts, generally, to facilitate the killing of tumor cells. Furthermore, the formation of autophagosomes and subsequent degradation of their contents can reduce the expression of HDAC proteins themselves as well as of other signaling regulatory molecules such as protein chaperones and mutated RAS proteins. Reduced levels of HDAC6 causes the acetylation and inactivation of heat shock protein 90, and, together with reduced expression of the chaperones HSP70 and GRP78, generates a strong endoplasmic reticulum (ER) stress response. Prolonged intense ER stress signaling causes tumor cell death. Reduced expression of HDACs 1, 2 and 3 causes the levels of programed death ligand 1 (PD-L1) to decline and the expression of Class I MHCA to increase which correlates with elevated immunogenicity of the tumor cells in vivo. This review will specifically focus on the downstream implications that result from autophagic-degradation of HDACs, RAS and protein chaperones.