Perhaps you can use inverse probability weighting techniques for this, which seem to be supported by some packages from a quick search.
But I was wondering what exactly is it that you want to show/calculate? Just the cumulative incidence rates at one or a few timepoints? Or do you want to generate some graphical results, e.g. sort of a Kaplan-Meier-like plot with curves stratified by the genetic variant?
Intuitively, I am somewhat worried about the power/sample size and the uncertainty in your estimates after weighting/weighing. I’m not an expert in the topic, but I know weighting costs statistical power and your sample size is not that large, which could be further compounded by the frequency of your genetic variants (i.e. although the cases have a higher frequency of the variants, this frequency might still be comparatively low).
You were interested in discovering genetic variants related to thrombosis risk in cancer patients and you’ve succeeded in this. Maybe that’s enough for your current study/project and you could measure the specific variants you discovered in more people now (hopefully at lower cost than just measuring all the variants) and postpone the sort of calculations/visualizations you want to do to a next project?