Effect of smoking, hypertension and lifestyle factors on kidney cancer — perspectives for prevention and screening programmes

Campi, Riccardo; Rebez, Giacomo; Klatte, Tobias; Roussel, Eduard; Ouizad, Idir; Ingels, Alexander; Pavan, Nicola; Kara, Onder; Erdem, Selcuk; Bertolo, Riccardo; Capitanio, Umberto; Mir, Maria Carmen

doi:10.1038/s41585-023-00781-8

Cited by 26 publications

(7 citation statements)

References 196 publications

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“…Frontiers in Genetics frontiersin.org hypertension (Campi et al, 2023), and body mass index (BMI) (Liu et al, 2018) as covariates to elucidate the positive influences of LC, independent of UC-related risk factors. After adjusting for the effects of the remaining four leukocyte subtypes, we then used MVMR to explain the role of individual leukocyte subtypes on UC, taking into account the direct modulation between leukocyte subtypes.…”

Section: Discussionmentioning

confidence: 99%

A causal link between circulating leukocytes and three major urologic cancers: a mendelian randomization investigation

Zhi-gang,

Han-dong

2024

Front. Genet.

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PurposeThis study aimed to explore the influence of serum leukocytes on urologic cancers (UC) using observation-based investigations. In the present study, Mendelian randomization (MR) was employed to assess the link between leukocyte count (LC) and the risk of UC development.MethodsFive LC and three major UC patient prognoses were obtained for MR analysis from genome-wide association studies (GWAS). Furthermore, in order to evaluate reverse causality, bidirectional studies were conducted. Finally, a sensitivity analysis using multiple methods was carried out.ResultsThere was no significant correlation found in the genetic assessment of differential LC between the co-occurrence of bladder cancer (BCA) and renal cell carcinoma (RCC). Conversely, an individual 1-standard deviation (SD) rise in neutrophil count was strongly linked to a 9.3% elevation in prostate cancer (PCA) risk ([odd ratio]OR = 1.093, 95% [confidence interval]CI = 0.864–1.383, p = 0.002). Reverse MR analysis suggested that PCA was unlikely to cause changes in neutrophil count. Additional sensitivity studies revealed that the outcomes of all MR evaluations were similar, and there was no horizontal pleiotropy. Primary MR analysis using inverse-variance weighted (IVW) revealed that differential lymphocyte count significantly influenced RCC risk (OR = 1.162, 95%CI = 0.918–1.470, p = 0.001). Moreover, altered basophil count also affected BCA risk (OR = 1.249, 95% CI = 0.904–1.725, p = 0.018). Nonetheless, these causal associations were not significant in the sensitivity analysis.ConclusionIn summary, the results revealed that increased neutrophil counts represent a significant PCA risk factor. The current research indicates a significant relationship between immune cell activity and the cause of UC.

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Section: Discussionmentioning

confidence: 99%

A causal link between circulating leukocytes and three major urologic cancers: a mendelian randomization investigation

Zhi-gang,

Han-dong

2024

Front. Genet.

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“…Previous observational studies have shown that smoking was a major contributing factor to the development of RCC. ( Bukavina et al, 2022 ; Li and Hecht, 2022 ; Campi et al, 2023 ). The majority of research indicates that individuals who smoke are twice as likely to develop renal cell cancer.…”

Section: Discussionmentioning

confidence: 99%

The causal relationship between smoking, alcohol consumption, and renal clear cell carcinoma: a Mendelian randomization study

Cui,

Du,

Xue

et al. 2024

Front. Genet.

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Introduction: Observational studies have found a correlation between the consumption of tobacco and alcohol and the likelihood of developing renal cell carcinoma. However, whether these associations indicate causal relationships is unclear.Methods: To establish if these connections indicate causal relationships, we performed a Mendelian Randomization (MR) analysis using a two-sample approach. For the number of daily cigarettes, lifetime smoking index, smoking initiation, and weekly drinking, we employed 44, 108, 174, and 76 single nucleotide polymorphisms (SNPs) as instrumental variables. Outcome data were obtained from the FinnGen Alliance, which included a combined total of 429,290 individuals. The MR analysis was conducted using the inverse-variance weighted (IVW) method to estimate causal effects. To address potential violations of MR assumptions due to directional pleiotropy, we performed MR-Egger regression and MR-PRESSO (Mendelian Randomization Pleiotropy RESidual Sum and Outlier) analysis.Results: Genetically influenced smoking initiation was directly associated with the risk of developing renal cell carcinoma (OR = 1.55, 95% CI: 1.04–2.33; p = 0.03). No causal relationship was found between daily cigarette consumption and lifetime smoking index with the risk of renal cell cancer. Genetic predisposition for weekly alcohol consumption showed a reduced risk of renal cell cancer (OR = 0.45, 95% CI: 0.26–0.81; p = 0.007).Discussion: Our study suggests a potential causal relationship between alcohol consumption and reduced risk of renal cell cancer, while no such association was observed with smoking. Further research is needed to confirm these findings.

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“…Renal cell carcinoma (RCC) is one of the most common malignant urologic tumors worldwide, accounting for more than 430,000 cases and 180,000 deaths annually 1 , 2 . Clear cell renal cell carcinoma (ccRCC) is the main histopathological subtype and has a high mortality rate 3 .…”

Section: Introductionmentioning

confidence: 99%

A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs

Chen,

Zhang,

et al. 2024

J. Cancer

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Background: Tumor angiogenesis is closely related to the progression of clear cell renal cell carcinoma (ccRCC). Long non-coding RNAs (lncRNAs) regulating angiogenesis could be potential biomarkers for predicting ccRCC prognosis. With this study, we aimed to construct a prognostic model based on lncRNAs and explore its underlying mechanisms. Methods: RNA data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Angiogenesis-related genes (ARGs) were extracted from the Molecular Signatures database. Pearson correlation and LASSO and COX regression analyses were performed to identify survival-related AR-lncRNAs (sAR-lncRNAs) and construct a prognostic model. The predictive power of the prognostic model was verified according to Kaplan-Meier curve, receiver operating characteristic (ROC) curve and nomogram analyses. The correlation between the prognostic model and clinicopathological characteristics was assessed via univariate and multivariate analyses. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was subsequently performed to elucidate the mechanisms of the sAR-lncRNAs. In vitro qPCR, immunohistochemistry, migration and invasion assays were conducted to confirm the angiogenic function of sAR-lncRNAs. Results: Three sAR-lncRNAs were used to construct a prognostic model. The model was moderately accurate in predicting 1-, 3-and 5-year ccRCC prognosis, and the risk score according to this model was closely related to clinicopathological characteristics such as T grade and T stage. A nomogram was constructed to precisely estimate the overall survival of ccRCC patients. KEGG enrichment analysis indicated that the MAPK and Notch pathways were highly enriched in high-risk patients. Additionally, we found that the expression of the lncRNAs AC005324.4 and AC104964.4 in the prognostic model was lower in ccRCC cell lines and cancer tissues than in the HK-2 cell line and paracancerous tissues, while the expression of the lncRNA AC087482.1 showed the opposite trend. In a coculture model, knockdown of lncRNA AC005324.4 and lncRNA AC104964.4 significantly promoted the migration and invasion of human umbilical vein endothelial cells (HUVECs), but siR-AC087482.1 transfection alleviated these effects. Conclusions:We constructed a prognostic model based on 3 sAR-lncRNAs and validated its value in clinicopathological characteristics and prognostic prediction of ccRCC patients, providing a new perspective for ccRCC treatment decision making.

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Effect of smoking, hypertension and lifestyle factors on kidney cancer — perspectives for prevention and screening programmes

Cited by 26 publications

References 196 publications

A causal link between circulating leukocytes and three major urologic cancers: a mendelian randomization investigation

A causal link between circulating leukocytes and three major urologic cancers: a mendelian randomization investigation

The causal relationship between smoking, alcohol consumption, and renal clear cell carcinoma: a Mendelian randomization study

A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs

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