Comprehensive Profiling of Primary and Metastatic ccRCC Reveals a High Homology of the Metastases to a Subregion of the Primary Tumour

DNMT3a-mediated upregulation of the stress inducible protein sestrin-2 contributes to malignant transformation of human bronchial epithelial cells following nickel exposure

BACKGROUND

Nickel is a confirmed human lung carcinogen. Nonetheless, the molecular mechanisms driving its carcinogenic impact on lung tissue remain poorly defined. In this study, we assessed SESN2 expression and the signaling pathways responsible for cellular transformation in human bronchial epithelial cells (HBECs) as a result of nickel exposure.

METHODS

We employed the Western blotting to determine the induction of SESN2 by nickel. To clarify the signaling pathways leading to cellular transformation following nickel exposure, we applied techniques such as gene knockdown, methylation-specific PCR, and chromatin immunoprecipitation.

RESULT

Exposure to nickel results in the upregulation of SESN2 and the initiation of autophagy in human bronchial epithelial cells (HBECs). This leads to degradation of HUR protein and consequently downregulation of USP28 mRNA, PP2AC protein, β-catenin protein, and diminished VHL transcription, culminating in the accumulation of hypoxia-inducible factor-1α (HIF-1α) and the malignant transformation of these cells. Mechanistic studies revealed that the increased expression of SESN2 is attributed to the demethylation of the SESN2 promoter induced by nickel, a process facilitated by decreased DNA methyl-transferase 3 A (DNMT3a) expression, while The downregulation of VHL transcription is linked to the suppression of the PP2A-C/GSK3β/β-Catenin/C-Myc pathway. Additionally, we discovered that SESN2-mediated autophagy triggers the degradation of HUR protein, which subsequently reduces the stability of USP28 mRNA and inhibits the PP2A-C/GSK3β/β-Catenin pathway and c-Myc transcription in HBECs post nickel exposure.

CONCLUSION

Our results reveal that nickel exposure leads to the downregulation of DNMT3a, resulting in the hypomethylation of the SESN2 promoter and its protein induction. This triggers autophagy-dependent suppression of the HUR/USP28/PP2A/β-Catenin/c-Myc pathway, subsequently leading to reduced VHL transcription, accumulation of HIF-1α protein, and the malignant transformation of human bronchial epithelial cells (HBECs). Our research offers novel insights into the molecular mechanisms that underlie the lung carcinogenic effects of nickel exposure. Specifically, nickel induces aberrant DNA methylation in the SESN2 promoter region through the decrease of DNMT3a levels, which ultimately leads to HIF-1α protein accumulation and the malignant transformation of HBECs. Specifically, nickel initiates DNA-methylation of the SESN2 promoter region by decreasing DNMT3a, ultimately resulting in HIF-1α protein accumulation and malignant transformation of HBECs. This study highlights DNMT3a as a potential prognostic biomarker or therapeutic target to improve clinical outcomes in lung cancer patients.

Identification of key genes of the ccRCC subtype with poor prognosis

Clear cell renal carcinoma has been reported in many research studies as a rather heterogeneous disease. Identification of different subtypes and their molecular characteristics can help in choosing a more effective treatment and predicting a response to it. In this study, using multi-omics clustering of RNA-Seq data of patients with clear cell renal carcinoma from TCGA. Specific genes were identified for the most aggressive ccRCC subtype associated with metastasis and a subtype associated with a more favorable course of the disease. Among them were genes associated with blood clotting (FGA, FGG) and genes associated with changes in the immune characteristics of a tumor (ENAM, IGFBP1, IL6). In addition, an association of hub genes of poor survival ccRCC subtype with the levels of infiltration of endothelial cells, hematopoietic stem cells, T cells NK and mast cells was revealed. It was shown that MFI2, CP, FGA, and FGG expression can predict the response to sunitinib, while the APOB, ENAM, IGFBP1, and MFI2 expression predict the response to nivolumab. The results obtained provide insight into the genetic characteristics underlying the aggressive subtype of ccRCC and may help develop new approaches to the treatment of this disease.

Evaluation of a seven gene mutational profile as a prognostic factor in a population-based study of clear cell renal cell carcinoma

In this study, we investigate the influence of the seven genes (VHL, PBRM1, SETD2, BAP1, KDM5C, MTOR and TP53) most frequently mutated in clear cell renal cell cancer (ccRCC) on cancer-specific survival (CSS) in the prospective Netherlands Cohort Study on diet and cancer. DNA isolated from routinely archived formalin-fixed paraffin-embedded tumour blocks from 252 incident ccRCC cases was available for targeted next generation sequencing. Based on the sequencing quality and the completeness of information on clinical characteristics and follow-up, we could use 110 cases for survival analysis. The association with CSS for each mutated gene in these cases was tested using multivariable Cox proportional hazards models to estimate hazards ratios (HR) and confidence intervals (CIs), and we observed mutations in one or more of the seven genes in 64 out of 110 cases (58%). In the multivariable-adjusted analyses, mutations in VHL and PBRM1 were associated with better CSS (HRs (95% CI) 0.34 (0.13‒0.89) and 0.17 (0.04–0.66), respectively), although these results were not statistically significant after multiple testing correction. No association was observed for the other five genes, which may be attributable to limited power.

Prediction of overall survival based upon a new ferroptosis-related gene signature in patients with clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common and lethal renal cell carcinoma (RCC) histological subtype. Ferroptosis is a newly discovered programmed cell death and serves an essential role in tumor occurrence and development. The purpose of this study is to analyze ferroptosis-related gene (FRG) expression profiles and to construct a multi-gene signature for predicting the prognosis of ccRCC patients.

METHODS

RNA-sequencing data and clinicopathological data of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed FRGs between ccRCC and normal tissues were identified using 'limma' package in R. GO and KEGG enrichment analyses were conducted to elucidate the biological functions and pathways of differentially expressed FRGs. Consensus clustering was used to investigate the relationship between the expression of FRGs and clinical phenotypes. Univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to screen genes related to prognosis and construct the optimal signature. Then, a nomogram was established to predict individual survival probability by combining clinical features and prognostic signature.

RESULTS

A total of 19 differentially expressed FRGs were identified. Consensus clustering identified two clusters of ccRCC patients with distinguished prognostic. Functional analysis revealed that metabolism-related pathways were enriched, especially lipid metabolism. A 7-gene ferroptosis-related prognostic signature was constructed to stratify the TCGA training cohort into high- and low-risk groups where the prognosis was significantly worse in the high-risk group. The signature was identified as an independent prognostic indicator for ccRCC. These findings were validated in the testing cohort, the entire cohort, and the International Cancer Genome Consortium (ICGC) cohort. We further demonstrated that the signature-based risk score was highly associated with the ccRCC progression. Further stratified survival analysis showed that the high-risk group had a significantly lower overall survival (OS) rate than those in the low-risk group. Moreover, we constructed a nomogram that had a strong ability to forecast the OS of the ccRCC patients.

CONCLUSIONS

We constructed a ferroptosis-related prognostic signature, which might provide a reliable prognosis assessment tool for the clinician to guide clinical decision-making and outcomes research.

Transcriptome Profiling Reveals B-Lineage Cells Contribute to the Poor Prognosis and Metastasis of Clear Cell Renal Cell Carcinoma

Although immune therapy can improve the treatment of clear cell renal cell carcinoma (ccRCC) significantly, there are still a large proportion of ccRCC patients who progress to metastasis. Targeting the pro-metastatic immune cell in the ccRCC microenvironment could provide a solution to this problem. In this study, B cells in ccRCC biopsies were identified by using scRNA-seq and flow cytometry. The findings indicated the presence of a pro-metastatic B cell type which could be further classified into 3 subpopulations, MARCH3, B2M and DTWD1, based on their large-scaled genetic profiles, rather than traditional Immature/Mature ones. Although all of the 3 subpopulations appeared to contribute to distant metastasis, B cell (B2M) was deemed to be the most essential. Moreover, STX16, CLASRP, ATIC, ACIN1 and SEMA4B, were genes found to be commonly up-regulated in the 3 subpopulations and this was correlated to a poor prognosis of ccRCC. Furthermore, the heterogeneity of plasma cells in ccRCC was also found to contribute to metastasis of the disease. This study offers potential novel therapeutic targets against distant metastasis of cancers, and can help to improve the therapeutic efficiency of ccRCC patients.

Characterization of Renal Cell Carcinoma Heterotypic 3D Co-Cultures with Immune Cell Subsets

Two-dimensional cell culture-based platforms are easy and reproducible, however, they do not resemble the heterotypic cell-cell interactions or the complex tumor microenvironment. These parameters influence the treatment response and the cancer cell fate. Platforms to study the efficacy of anti-cancer treatments and their impact on the tumor microenvironment are currently being developed. In this study, we established robust, reproducible, and easy-to-use short-term spheroid cultures to mimic clear cell renal cell carcinoma (ccRCC). These 3D co-cultures included human endothelial cells, fibroblasts, immune cell subsets, and ccRCC cell lines, both parental and sunitinib-resistant. During spheroid formation, cells induce the production and secretion of the extracellular matrix. We monitored immune cell infiltration, surface protein expression, and the response to a treatment showing that the immune cells infiltrated the spheroid co-cultures within 6 h. Treatment with an optimized drug combination or the small molecule-based targeted drug sunitinib increased immune cell infiltration significantly. Assessing the therapeutic potential of this drug combination in this platform, we revealed that the expression of PD-L1 increased in 3D co-cultures. The cost- and time-effective establishment of our 3D co-culture model and its application as a pre-clinical drug screening platform can facilitate the treatment validation and clinical translation.

Multiple metastatic clones assessed by an integrative multiomics strategy in clear cell renal carcinoma: a case study

The dynamics of metastatic evolution in clear cell renal cell carcinoma (ccRCC) are complex. We report a case study where tumour heterogeneity resulting from clonal evolution is a frequent feature and could play a role in metastatic dissemination.We used an integrative multiomics strategy combining genomic and transcriptomic data to classify fourteen specimens from spatially different areas of a kidney tumour and three non-primary sites including a vein thrombus and two adrenal metastases.All sites were heterogeneous and polyclonal, each tumour site containing two different aggressive subclonal populations, with differentially expressed genes implicated in distinct biological functions. These are rare primary metastatic samples prior to any medical treatment, where we showed a multiple metastatic seeding of two subclonal populations.Multiple interdependent lineages could be the source of metastatic heterogeneity in ccRCC. By sampling metastases, patients with resistance to therapies could benefit a combination of targeted therapies based on more than one aggressive clone.

Establishment and characterisation of testicular cancer patient-derived xenograft models for preclinical evaluation of novel therapeutic strategies

Testicular cancer (TC) is the most common solid tumour in young men. While cisplatin-based chemotherapy is highly effective in TC patients, chemoresistance still accounts for 10% of disease-related deaths. Pre-clinical models that faithfully reflect patient tumours are needed to assist in target discovery and drug development. Tumour pieces from eight TC patients were subcutaneously implanted in NOD scid gamma (NSG) mice. Three patient-derived xenograft (PDX) models of TC, including one chemoresistant model, were established containing yolk sac tumour and teratoma components. PDX models and corresponding patient tumours were characterised by H&E, Ki-67 and cyclophilin A immunohistochemistry, showing retention of histological subtypes over several passages. Whole-exome sequencing, copy number variation analysis and RNA-sequencing was performed on these TP53 wild type PDX tumours to assess the effects of passaging, showing high concordance of molecular features between passages. Cisplatin sensitivity of PDX models corresponded with patients' response to cisplatin-based chemotherapy. MDM2 and mTORC1/2 targeted drugs showed efficacy in the cisplatin sensitive PDX models. In conclusion, we describe three PDX models faithfully reflecting chemosensitivity of TC patients. These models can be used for mechanistic studies and pre-clinical validation of novel therapeutic strategies in testicular cancer.

Proteomic analysis reveals distinctive protein expression patterns of thrombus in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a type of malignant tumor of the urinary system. The renal vein or vena cava thrombus can be found in a subset of ccRCC patients in whom it leads to worse prognosis. However, the protein expression profile and molecular features of ccRCC thrombus remain largely unclear. Here, a comparative proteomic analysis was performed using the 2D-LC-MS strategy for the thrombus-tumor-normal tissue triples of 15 ccRCC patients. Statistical analysis, GO enrichment analysis, protein-protein interaction network construction, and mRNA-based survival analysis were used to interpret the proteomic data. Three dysregulated proteins, GGT5 (gamma-glutamyl transferase 5), KRT7 (keratin 7) and CFHR1 (complement factor H related 1), were analyzed using western blot (WB) and immunohistochemistry (IHC) to validate the reliability of the proteomic analysis. The result of this analysis revealed 251 dysregulated proteins, which could be divided into 11 clusters depending on the changing trends, among the thrombus, tumor, and normal tissues. Several pathways and regulation networks were found to be associated with the thrombus, and some dysregulated proteins showed potential values for prognosis prediction. WB and IHC results were in accordance with the proteomic results, further validating the reliability of this study. In conclusion, our findings provide an overview of the thrombus at the molecular level as well as valuable information for further pathological studies or research on biomarkers and therapeutic targets.

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Proteomic analysis was performed using thrombus-tumor-normal tissue triples of 15 ccRCC patients.

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Statistical and bioinformatic analyses were performed to better interpret the proteomic data.

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Our findings provided an overview of the molecular landscape of thrombus.

Integrated analysis of optical mapping and whole-genome sequencing reveals intratumoral genetic heterogeneity in metastatic lung squamous cell carcinoma

Background

Intratumoral heterogeneity is a crucial factor to the outcome of patients and resistance to therapies, in which structural variants play an indispensable but undiscovered role.

Methods

We performed an integrated analysis of optical mapping and whole-genome sequencing on a primary tumor (PT) and matched metastases including lymph node metastasis (LNM) and tumor thrombus in the pulmonary vein (TPV). Single nucleotide variants, indels and structural variants were analyzed to reveal intratumoral genetic heterogeneity among tumor cells in different sites.

Results

Our results demonstrated there were less nonsynonymous somatic variants shared with PT in LNM than in TPV, while there were more structural variants shared with PT in LNM than in TPV. More private variants and its affected genes associated with tumorigenesis and progression were identified in TPV than in LNM. It should be noticed that optical mapping detected an average of 77.1% (74.5-78.5%) large structural variants (>5,000 bp) not detected by whole-genome sequencing and identified several structural variants private to metastases.

Conclusions

Our study does demonstrate structural variants, especially large structural variants play a crucial role in intratumoral genetic heterogeneity and optical mapping could make up for the deficiency of whole-genome sequencing to identify structural variants.

G6PD facilitates clear cell renal cell carcinoma invasion by enhancing MMP2 expression through ROS‑MAPK axis pathway

Glucose-6-phosphate dehydrogenase (G6PD) is crucial rate-limiting enzyme of the pentose phosphate pathway (PPP). G6PD dysregulation has been reported in various types of human cancer, and the role of G6PD in cancer progression was demonstrated in numerous studies. A previous study from our laboratory described the prognostic significance of G6PD in clear cell renal cell carcinoma (ccRCC), and demonstrated its proliferative role through positive feedback regulation of the phosphorylated form of signal transducer and activator of transcription 3. However, the role of G6PD in ccRCC invasion remains unclear. In the present study, reverse transcription-quantitative (RT-q) PCR, western blotting, enzyme activity assay, transwell assay and immunohistochemistry analysis in cell model, xenograft mice model and human specimen studies were performed to evaluate the role of G6PD in ccRCC invasion. The results from the present study demonstrated that G6PD may promote ccRCC cell invasive ability by increasing matrix metalloproteinase 2 (MMP2) mRNA and protein expression both in vitro and in vivo. In addition, a positive correlation between G6PD and MMP2 expression was demonstrated by RT-qPCR and western blotting in twenty pairs of ccRCC tumor specimens and matched adjacent normal tissues. Furthermore, G6PD promoted reactive oxygen species (ROS) generation and activated the MAPK signaling pathway in ccRCC cells. In addition, ROS significantly promoted the MAPK signaling pathway activation, which in turn contributed to MMP2 overexpression in ccRCC cells. In conclusion, the present study demonstrated that G6PD may facilitate ccRCC cell invasive ability by enhancing MMP2 expression through ROS-MAPK axis pathway.

Mutational heterogeneity between different regional tumour grades of clear cell renal cell carcinoma

Only a limited number of studies have explored the possible associations between tumour grade and mutated genes in clear cell renal cell carcinoma (ccRCC), and we set out to investigate this further using a multiple sampling and next generation sequencing (NGS) approach in a series of ccRCCs. Multiple regions were sampled from formalin-fixated paraffin-embedded ccRCC tumour blocks from seven patients. In 27 samples from six patients, we performed targeted NGS using a custom 42-gene panel based on the most frequently mutated genes in ccRCC reported in public databases. In four samples from the seventh patient, we performed whole exome sequencing (WES) and array comparative genomic hybridisation for detection of copy number variants (CNVs). Mutated genes and the tumour grades of the samples in which they had been identified were compared both within and between all individual tumours. CNVs were compared across all samples from patient 7. We identified clear genetic heterogeneity within and across tumours, but VHL mutations were seen in all patients. Looking across all samples, we identified eleven genes that were only mutated in samples with one particular tumour grade. However, these genes were never mutated in all samples with that tumour grade. Increasing chromosomal instability corresponded with increasing tumour grade, but we observed minimal association between tumour grade and total mutational load in the WES data. Our study confirms the genetic heterogeneity and tumour grade heterogeneity of ccRCC. Although a relatively small number of samples was analysed, genes were identified that could potentially be specific, though insensitive, markers of higher ccRCC tumour grades.

Phylogenetic Tree Inference: A Top-Down Approach to Track Tumor Evolution

Recently, an increasing number of studies sequence multiple biopsies of primary tumors, and even paired metastatic tumors to understand heterogeneity and the evolutionary trajectory of cancer progression. Although several algorithms are available to infer the phylogeny, most tools rely on accurate measurements of mutation allele frequencies from deep sequencing, which is often hard to achieve for clinical samples (especially FFPE samples). In this study, we present a novel and easy-to-use method, PTI (Phylogenetic Tree Inference), which use an iterative top-down approach to infer the phylogenetic tree structure of multiple tumor biopsies from same patient using just the presence or absence of somatic mutations without their allele frequencies. Therefore PTI can be used in a wide range of cases even when allele frequency data is not available. Comparison with existing state-of-the-art methods, such as LICHeE, Treeomics, and BAMSE, shows that PTI achieves similar or slightly better performance within a short run time. Moreover, this method is generally applicable to infer phylogeny for any other data sets (such as epigenetics) with a similar zero and one feature-by-sample matrix.