2.1

Study design

This was a prospective observational case-controlled study conducted between August 2019 and January 2023 at a tertiary care academic institution after obtaining approval from the institute ethics committee (IEC- 321/03.05.2019). Study population included patients with a diagnosis of RCC based on imaging and postoperative histopathology (HPE). Age and sex matched healthy individuals who hailed from the same geographical location were included as controls via a structured questionnaire. The control group included relatives of patients when available who preferably lived in the same household and did not have any occupational exposure to heavy metals. This ensured similar environmental exposure of heavy metals in cases and controls. Patients with chronic kidney or liver disease were excluded. The study was approved by the IEC and written informed consent was taken from all the participants. This research was funded by Indian Council of Medical Research (ICMR), Government of India.

2.2

Outcomes

The primary outcome was to compare the concentration of heavy metals such as As, copper (Cu), Mn, Selenium (Se), Cd, Pb, and Hg in the blood, urine, and tissue. These 7 heavy metals were chosen as they were shown in previous studies, individually, to have a possible association with RCC [ ]. As, Cd, Pb and Hg are class I carcinogens which have been implicated in RCC [ ]. Cu, Mn and Se are micronutrients which are required in small quantities for physiological functions but can be deleterious in high concentrations [ ]. Secondary outcomes were comparison of serum levels of glutathione peroxidase (GPX), lipid peroxidase (LPO) and superoxide dismutase (SOD) between 2 groups; comparison of heavy metal concentration between tumor tissue and adjacent normal parenchyma; and comparison of the genetic expression of VHL , glutathione peroxidase ( GPX1 ), catalase ( CAT) and superoxide dismutase ( SOD1 ) gens in the tumor tissue with that of the adjacent normal renal parenchyma.

2.3

Sample collection and analysis

Peripheral blood samples (10ml) collected in an ultra-pure (Ethylenediaminetetraacetic acid) EDTA coated tubes were evaluated for heavy metal concentration by inductively coupled plasma mass-spectroscopy (ICP-MS). Urine samples (10ml) collected in a sterile metal-free plastic container were evaluated for the concentration of heavy metals by ICP-MS. Samples were collected in the early morning after an overnight fast. Oxidative stress markers and antioxidant levels were measured by commercially available colorimetric ELISA kits (Elabscience, USA). The samples were subjected to acid digestion which digests chelation complexes, proteins, and cellular components. These samples were then subjected to ICP-MS to measure heavy metal concentration where extreme temperatures ensured all components existed in their atomic form.

Tumour tissue and surrounding normal parenchyma were collected from operative specimens after a radical nephrectomy in a sterile, metal-free plastic container with RNAlater storage solution (Thermo Fischer Scientific, USA). The tissues were stored at -80°C till further evaluation of heavy metals by ICP-MS and gene expression of VHL, GPX1 , catalase and SOD1 genes by qPCR (Quantitative polymerase chain reaction) and RT-PCR (Reverse transcriptase polymerase chain reaction). In patients who underwent partial nephrectomy, tissue analysis was not feasible as there was not enough available normal renal parenchyma in the specimen. Tissue analysis of heavy metals by ICP-MS involved in drying of ∼50mg of tissue at 60°C followed by digestion in 70% nitric acid and hydrogen peroxide. The resulting solution was incubated a microwave digestion system (Anton paar Multiwave ECO, Austria). The digested tissue solution was used to measure heavy metal concentration with ICP-MS. Clinico-pathological data were collected from the study population including demographics and biopsy reports.

2.4

RNA extraction and complementary DNA library preparation protocol

For RT-PCR analysis, the tissue samples were minced and homogenized in lysis buffer (Qiagen, USA). Total RNA was extracted using TRIZOL-l reagent (Invitrogen, USA) according to the manufacturer’s protocol. The concentration and purity of total RNA was determined by measuring the absorption using NanoDrop-2000 (Thermo Fisher, USA) at 260 and 280 nm. First-strand cDNA was prepared from total RNA using Agilent reverse transcription system (Agilent Technologies, USA) based on the manufacturer’s instructions. The cDNA thus obtained was used immediately or stored at −80°Csss until use [ ]. The reaction mixture for cDNA library was prepared by mixing 4µL of iscript 5x reaction mix (Bio-Rad, USA) with 1µL of reverse transcriptase enzyme and 4-5µL of RNA in a PCR tube. The total volume was made up to 20µL using nuclease free water. The reaction mixture was incubated in a thermal cycler by priming for 5 minutes, reverse transcription for 20 minutes and RT inactivation for 1 minute. Two microliters of cDNA were used for qPCR.

2.5

Primer designing

Primers were designed for VHL , oxidative stress genes ( CAT, SOD1, GPX1) and 1 house-keeping gene ( GAPDH ) using NCBI NIH Primer Blast tool ( Supplementary Table S1 ). The specificity of primer was determined by agarose gel electrophoresis run. Each primer was standardized for its melting temperature and quantitative amplification.

2.6

qPCR protocol

To interpret the upregulation and downregulation levels of all mRNA Quantitative analysis of the genes VHL, CAT, SOD1 and GPX1 was performed in a CFX96 real-time system (Bio-Rad, USA) using Brilliant III Ultra-Fast SYBR® Green QPCR Master Mix (Agilent, USA). The cDNA were amplified in a 20μL reaction volume containing the specific primers ( Supplementary Table S1 ) [ ]. The mRNA expression levels of all genes were expressed as a ratio relative to GAPDH present in each sample. The level of expression of genes was normalized to that of the GAPDH gene expression (housekeeping gene) and was determined by the 2-ΔΔCt method [ ].

2.7

Quality control

For biochemical assays, each sample was analysed twice. In each run of analysis samples were analysed 3 times by default using MassHunter4 software and each analysis include 50 reading (50 × 3 = 150 readings in single run). For the accuracy and quality control of the analysis the calibration was done from blank (zero) to 1,000 high concentration standards (1,000 ppb) and linearity of calibration graph having R = 0.98 and above was accepted. For the reproducibility and accuracy of the analytical run, an internal standard having different mass range elements was parallelly run in the same matrix (which is used for sample digestion) to maintain the stability of the analytical run. For quality assurance, blood and urine standards with known concentration of elements was analysed after every 10 test samples. Genetic analyses involved qPCR and RT-PCR, where each assay was validated by assessing the efficiency and specificity of the primers through melting curve analysis and agarose gel electrophoresis. For gene expression studies, we used house-keeping genes as internal controls to normalize the data and compensate for any potential variations in sample quality or experimental conditions. Each batch of experiments included negative controls, and all assays were performed in triplicate to verify reproducibility.

2.8

Statistical analysis

Mean ± standard deviation (SD) was used to express continuous variables which were compared using Student’s t-test. Categorical variables expressed as frequency (percentage) were compared using Chi-square or Fischer’s Exact test. Statistical analysis was done with Stata, v.14.0 (StataCorp, USA). The confounding factors like age and gender were adjusted with frequency matching. A P -value of < 0.05 was considered statistically significant.

3.1

Heavy metals in blood

Patients with RCC had significantly elevated mean levels of As, Cu, Mn, Cd, Pb and Hg in blood compared to the control group ( Table 2 ). 60% (92) of cases had elevated Pb in the blood which was the most common heavy metal to have high concentrations. Likewise, 23.7% (36), 25.7% (39), 54.12% (82), 10.56% (16) and 1.32% (2) of patients had concentrations above the permitted levels for Cd, Cu, Mn, Hg and As respectively. Patients with RCC had significantly lower levels of Se compared to the control group ( Fig. 1 A). On subgroup analysis of cases, there was no significant difference in blood heavy metals with respect to age, gender, smoking habit, diet, T stage of the tumor, and histopathological type of RCC ( Supplementary Table S2 ).

Table 2

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