Pharmacogenomics – Hope for Cancer Pain?

Controlling pain – a complex and subjective experience – is critical to care of cancer patients. Managing cancer pain with analgesics is complicated by inter-individual variability in efficacy, side-effects and adverse drug reactions. 

Pharmacogenomics – how genetic inheritance affects response to medications – may help explain why some of us respond differently to pain treatments. Subjective responses govern cancer pain perception and there is some genetic contribution to variability. Other influences include biological variations (ethnicity, age and gender); environmental factors (smoking status and perhaps the gut microflora); co-morbidity and concomitant medications (potential for drug-drug interactions).

Opiates remain the major treatment choice for cancer pain, but in some patients they fail or side-effects are intolerable. Dosing traditionally involves carefully escalating and adjusting it based on the clinical response and any side effects or adverse drug reactions. Success is getting enough analgesia, while minimizing adverse effects of taking the drug.

Opiate drugs can cause unpleasant side-effects, such as nausea, vomiting, constipation and sedation. But they can also cause some serious side-effects including strong sedation, respiratory depression and even death if the patient is unable or has reduced ability to metabolize opiates.

Morphine is the most common opiate given. At a population level, morphine has a similar safety profile and efficacy to the other opiates. However, individuals vary in morphine response. Non-responders get little pain control despite increasing the dose. So far only two factors predict non-response to morphine – renal impairment and sepsis.

Giving catecholines enhances opiate efficacy. Catechol-0-methyltransferase inactivates catecholamines (dopamine, adrenaline and norepinephrine); variability in the enzyme’s gene causes differences in pain sensitivity and response.

Identifying known variant alleles that affect the pharmacology of opiates will help tailor treatment and select the best dose.  Codeine – the most researched opiate – exerts analgesia when converted to morphine via the action of cytochrome P450 2D6. The enzyme’s marked genetic variability controls the response to codeine. Some patients produce only a little enzyme, so when given codeine, they don’t make much morphine – up to 10% of Caucasians. Others are very fast or extensive metabolizers have increased enzyme activity but get worse side-effects.

Many genes are likely to play a role; each with just a modest association with pain. So we need sample sizes in the thousands to identify genes involved with any certainty. Most studies performed to date were underpowered to detect modest effects, but will detect strong effects. If we measured all the factors influencing the opiate response, we could perhaps model inter-individual variation to morphine response. Also we could stratify patients according to age, disease process and psychological profile.

Using pharmacogenomics to predict pain management in the clinic is for the future. First we need to define a good clinical response to opioids. Perhaps then we will develop a simple blood test to predict the best opiate and dose for individual patients.

Pharmacogenomic approaches in pain management could lead to individualized therapy to best select the appropriate analgesic from the onset to provide sustained efficacy with the lowest side effect profile.