We conducted a comprehensive search of published pharmacogenomic research on the clinical application related to the metabolism, transport, and analgesic targets of opioid analgesics; the specific search scope included the following: CPIC guidelines, genetic information databases (PharmGKB, Table of Pharmacogenomic Biomarkers in Drug Labeling, and SNPedia database), the PubMed database, and Chinese literature databases (such as CNKI). We collected published pharmacogenomic research evidence on the in vivo transport, drug metabolism, and analgesic-related targets of opioid analgesics and systematically summarized and screened gene loci related to the efficacy and toxic side effects of opioid analgesics. After evaluating and screening the data, the importance of different gene loci was evaluated based on PharmGKB’s pharmacogenomic clinical evidence strength scoring system to screen out target genes with strong correlation.

The research subjects are cancer pain patients who used opioid analgesics at a tertiary hospital in Shandong Province, China, from September 2021 to March 2024. The study was approved and filed following a review by the hospital’s medical ethics committee (filing number: KYLL-20211115). The study was divided into the ADR research group and the dose demand research group, with safety and drug dose demand research conducted in each group. To ensure baseline consistency, a 1:1 screening was adopted for enrollment. The inclusion and exclusion criteria for each group are as follows.

ADR research group: The inclusion criteria for the observation subgroup (patients who experienced ADR) were as follows: ① age range of 18–85 years; ② cancer pain patients who only use opioid analgesics for pain relief have an initial NRS score of 4–10; and ③ occurrence of ADR after using opioid analgesics. Exclusion criteria were as follows: ① individuals with a history of mental or neurological disorders; ② patients with unclear consciousness or in a coma; ③ combined use of other types of analgesic drugs including combination preparations; ④ long-term use of glucocorticoids; and ⑤ individuals with a history of narcotic drug abuse or allergies to opioid analgesics. The inclusion criteria for the control subgroup (non ADR group) were as follows: ① age range of 18–85 years; ② cancer patients who only use opioid analgesics for pain relief have an initial NRS score of 4–10; and ③ those who did not experience ADRs after using opioid analgesics. The exclusion criteria are the same as above.

Dose demand research group: The Edmonton classification system sets the grading criteria for oral morphine as follows: low dose < 60 mg/d, medium dose 60–300 mg/d, and high dose > 300 mg/d. However, in clinical practice, except for a few advanced cancer patients, there are relatively few patients with a daily dose greater than 300 mg. Therefore, considering the sample size, the dose range is divided into oral morphine ≥150 mg and <150 mg.

The inclusion criteria for the observation subgroup (high-dose group) were as follows: ① age range of 18–85 years; ② cancer patients who only use opioid analgesics for pain relief have an initial NRS score of 4–10; ③ the daily dose of the drug (calculated as oral morphine) is ≥150 mg; and ④ no serious adverse drug reactions have occurred. Exclusion criteria were as follows: ① individuals with a history of mental or neurological disorders; ② patients with unclear consciousness or in a coma; ③ combined use of other types of analgesic drugs including combination preparations; ④ long-term use of glucocorticoids; and ⑤ individuals with a history of narcotic drug abuse or allergies to opioid analgesics. The inclusion criteria for the control subgroup (low-dose group) were as follows: ① age range of 18–85 years; ② cancer patients who only use opioid analgesics for pain relief have an initial NRS score of 4–10; ③ the daily dose of the drug (calculated as morphine) is less than 150 mg; and ④ no serious adverse drug reactions have occurred. The exclusion criteria are the same as above.

We used the Karch–Lasagna method, which is commonly applied both domestically and internationally, to evaluate the causal relationship of ADRs and accurately identify those caused by opioid analgesics (Liu, 2023). The evaluation results are classified as follows: positive (the time sequence since medication is reasonable; the reaction is the same as the known ADR type of the drug, or the adverse reaction disappears after discontinuation and reappears after readministration); very likely (adverse reactions may occur after the patient takes the medication and cannot be explained by other diseases the patient is suffering from. The reaction disappears after discontinuation, but the reaction is different from the known ADR type of the drug or has not been repeated); and probably (conditional and suspicious). ADR types are divided into general and severe. Severe ADR refers to one of the following situations: causing death; carcinogenesis, teratogenicity, and birth defects; being dangerous to life and capable of causing permanent or significant disability to the human body; causing permanent damage to organ function; and causing hospitalization or prolonged hospital stay.

In addition to obtaining basic patient information and medication status through the electronic medical record system for ADR evaluation and medication efficacy evaluation, a patient information collection form is used to inquire with patients and their families before sampling to further determine the actual medication dosage, pain control status, ADR presentation type, severity, and outcome of the patient. Patients whose causal evaluation results of ADR are positive or highly likely to be included in the observation subgroup of the ADR research group are selected. The dose demand research group needs to exclude cases of patients with severe ADRs.

SNP analysis was performed using fluorescence in situ hybridization (FISH) or polymerase chain reaction (PCR). To reduce trauma through non-invasive sampling and increase patient acceptance, the FISH method uses oral exfoliated cells as a substitute for blood samples. The method for detecting oral exfoliated cells is as follows: ① after rinsing the mouth thrice with water, the mucosa on both sides of the oral cavity is scraped using a specialized throat swab (30 times on each side) to collect oral exfoliated cells. ② The swab is placed back into the swab tube, taking care not to let it come into contact with any other person or object during this process. The collected oral swabs can be temporarily refrigerated but should not exceed 7 days. ③ A volume of 400 μl of the CQ-ENH type sample extract (mainly composed of 0.74% ammonium chloride solution) is slowly added into the throat swab tube. ④ The solution is thoroughly shaken and mixed. After standing at room temperature for 1 min, the extract is transferred to a 1.5-mL centrifuge tube. ⑤ It is centrifuged at 12,000 r/min for 5 min, and the supernatant is then prepared for inspection. ⑥ A measure of 1.0 μl of the upper-layer sample solution (3–4 mm below the liquid level) is taken and added to the wall of the detection reagent tube for testing on the machine. Samples can be processed and used immediately (within 1 h) and cannot be used beyond the time limit. ⑦ The FISH method uses double Z-shaped probes, which hybridize with the target sequence through the tandem connection of two independent Z-shaped probes. Then, the signal amplification precursor sequence can bind to the 28 bases in the upstream region of the double Z-shaped probe, resulting in a change in the stereo configuration of the final sequence and amplification of the signal. ⑧ The signals are recorded, and the detection site information is output.

CYP2D6 (rs1065852, rs1135822, rs16947, rs28371725, and rs28371735) was detected via PCR. In particular, the total volume of the PCR reaction is 5 μL, including 0.5 μL of 10 × PCR buffer, 0.4 μL of 25 mmol/L MgCl₂, 0.1 μL of 25 mmol/L dNTP mix, 1 μL of 0.5 μmol/L specific amplification primer mix, 0.2 μL of 5 U/μL PCR enzyme, 0.8 μL of ddH₂O, and 2 μL of DNA template. The PCR amplification procedure is as follows: preheating at 95 °C for 2 min, followed by 35 cycles at 95 °C for 30 s, 56 °C for 30 s, and 72 °C for 1 min; 72 °C for 5 min and maintained at 4 °C. The primer sequence is as follows: rs1065852: F: GCC​CAT​TTG​GTA​GTG​AGG​CAG​GTA and R: AGC​AGT​ATG​GTG​TGT​TCT​GGA​AGT​C; rs1135822: F: CTCCAGCGACTTCTTGCC and R: GCT​AAT​GCC​TTC​ATG​GCC​ACG; rs16947: F: GTC​ACC​ATC​CCG​GCA​GAG​A and R: CCG​TTC​TGT​CCC​GAG​TAT​GC; rs28371725: F: GGG​TGT​CCC​AGC​AAA​GTT​CAT and R: CCG​TTC​TGT​CCC​GAG​TAT​GC; rs28371725: F: GGG​TGT​CCC​AGC​AAA​GTT​CAT and R: GAT​CCT​ACA​TCC​GGA​TGT​GCA​G; and rs28371735: F: GCA​CAG​CAC​AAA​GCT​CAT​AGG​G and R: CAC​TTC​AGC​TTC​TCG​GTG​CC.

Experimental instruments and reagents: a multi-channel fluorescence quantitative analyzer (FasCan 48S, Shanxi Medical Equipment Injection Standard No. 20182400043); a real-time fluorescence quantitative PCR instrument (7500 model, Applied Biosystems, United States); and detection reagents purchased from Guangyin Medical Technology Co., Ltd.

Statistical analysis was conducted using SPSS 26.0 software, and chi-square tests were used to analyze genotype and allele frequencies. The Hardy–Weinberg equilibrium (HWE) was assessed using the HWE program; a P-value > 0.05 indicates that the data are consistent with a population in genetic equilibrium, suggesting that the sample comes from the same Mendelian population. Further correlation analysis was conducted on the detection results using the SNPStats genetic model (https://www.snpstats.net/snpstats/start.htm). In the measurement data, if it follows a normal distribution and is represented by x̄ ± s, the t-test should be performed for intergroup comparison. If it is a skewed distribution, the median (minimum, maximum) [M (xmin, xmax)] is used to represent it, and the rank-sum test is performed for intergroup comparison. Count data are represented as n (%), and comparison between groups is performed using the chi-square test. If P < 0.05, it is considered that there is a significant statistical difference between the two sets of data.

Nine related genes were initially retrieved, and finally, four target genes related to ADR and drug efficacy were identified from gene loci recommended by a CPIC rating of B or above, a PharmGKB rating of 3 or above, and low-bias risk studies. The correlation between the gene and the ADR or efficacy is shown in Table 1.