If you have 5 biomarkers then you would need to segment to a minimum of 6 clusters: one for each marker and one for tissue that is not one of the biomarkers. kmeans always assigns a cluster to every point, so if you had a point that was not one of the 5 colors and you asked to cluster it, then it would assign it to one of the five anyhow.
Note that the index values returned by kmeans are not in any pre-set order. You cannot assume that index 1 is associated with biomarker color #1. It is common for clusters to change effective identities during processing, so even if you had specified initial cluster centers in the options you passed to kmeans, you should not assume that the numbering of the output will be the same as the order of the initial cluster centers.
Remember too that a cluster centroid can be outside of data that belongs to that cluster. For example consider a perfect unfilled semi-circle of points: its centroid is the centre of the circle but no data points are at that center. You therefore cannot just index the centroid location into the image and look at the pixel value there to figure out what is happening.
