Determination of spatial proximity between features of interest in biological tissue

1. A computer-implemented method for determining a relationship between biomarker expression levels of morphological units in biological tissue and spatial distance from a morphological feature, the method comprising:

identifying a morphological feature in an image of the biological tissue based on expression levels of a first biomarker indicative of the morphological feature;

receiving a result of a segmentation analysis performed on the image of the biological tissue, the result identifying a first set of morphological units in the image external to the morphological feature, the first set of morphological units including cells and/or sub-cellular components;

determining an expression level of a second biomarker corresponding to each unit in the first set of morphological units in the image of the biological tissue;

determining a spatial distance between the morphological feature and each unit in the first set of morphological units; and

automatically rendering, on a user interface displayed on a visual display device, a representation of a relationship between the expression levels of the second biomarker and the corresponding spatial distance from the morphological feature of the first set of morphological units wherein the representation of the expression levels of the second biomarker in the first set of morphological units includes overlaid renderings of:

a representation of densities of the morphological units at different spatial distances from the morphological feature and at different expression levels of the second biomarker; and

median expression levels of the second biomarker in the morphological units at different spatial distances from the morphological feature.

2. The method of claim 1 , wherein the morphological feature includes a blood vessel that is the closest blood vessel to each unit in the first set of morphological units.

3. The method of claim 1 , wherein the morphological feature includes a plurality of blood vessels in the vicinity of each unit in the first set of morphological units.

4. The method of claim 1 , wherein the morphological feature includes necrotic tissue.

5. The method of claim 1 , wherein the morphological feature includes a basement membrane.

6. The method of claim 1 , wherein the morphological feature includes a collection of cells of a predetermined morphological or functional type.

7. The method of claim 1 , wherein the first set of morphological units includes cells.

8. The method of claim 1 , wherein the first set of morphological units includes sub-cellular components.

9. The method of claim 1 , wherein the first set of morphological units includes cells of a single tissue type.

10. The method of claim 1 , wherein the representation of the expression levels of the second biomarker in the first set of morphological units includes a representation of densities of the morphological units at different spatial distances from the morphological feature and at different expression levels of the second biomarker.

11. The method of claim 1 , wherein the representation of the expression levels of the second biomarker in the first set of morphological units includes median expression levels of the second biomarker in the morphological units at different spatial distances from the morphological feature.

12. The method of claim 1 , wherein the representation of the expression levels of the second biomarker in the first set of morphological units includes user-specified percentile expression levels of the second biomarker in the morphological units at different spatial distances from the morphological feature.

13. The method of claim 1 , wherein the representation of the expression levels of the second biomarker in the first set of morphological units further comprises overlaid renderings of:

expression levels of the second biomarker within a predetermined first range of percentiles of expression levels at different spatial distances from the morphological feature; and

expression levels of the second biomarker within a predetermined second range of percentiles of expression levels at different spatial distances from the morphological feature.

14. The method of claim 1 , further comprising:

determining an expression level of a third biomarker in each unit in the first set of morphological units in the image of the biological tissue;

determining a second set of morphological units within the first set of morphological units in which the expression levels of the second biomarker satisfy one or more predetermined level criteria and the expression levels of the third biomarker satisfy one or more predetermined level criteria;

determining a spatial distance between the morphological feature and each unit in the second set of morphological units; and

automatically rendering, on the visual display device, a representation of the second set of morphological units and a representation of the corresponding spatial distance from the morphological feature for each unit in the second set of morphological units.

15. The method of claim 1 , further comprising:

automatically determining a clinical outcome corresponding to the biological tissue of a cohort based on the relationship between the expression levels of the second biomarker and the corresponding spatial distance from the morphological feature of the first set of morphological units.

16. The method of claim 1 , wherein the relationship includes a result of a correlation analysis.

17. The method of claim 1 , further comprising:

generating a predictive model for a clinical outcome corresponding to the biological tissue of the cohort based on the relationship between the expression levels of the second biomarker and the corresponding spatial distance from the morphological feature of the first set of morphological units.

18. A computer system for determining a relationship between biomarker expression levels of morphological units in biological tissue and spatial distance from a morphological feature, the system comprising:

a storage device; and

a processor configured to:

identify a morphological feature in an image of biological tissue based on expression levels of a first biomarker indicative of the morphological feature,

receive a result of a segmentation analysis performed on the image of the biological tissue, the result identifying a first set of morphological units in the image external to the morphological feature, the first set of morphological units including cells and/or sub-cellular components,

determine an expression level of a second biomarker corresponding to each unit in the first set of morphological units in the image of the biological tissue,

determine a spatial distance between the morphological feature and each unit in the first set of morphological units,

determine a representation of a relationship between the expression levels of the second biomarker and the corresponding spatial distance from the morphological feature of the first set of morphological units wherein the representation of the expression levels of the second biomarker in the first set of morphological units includes overlaid renderings of:

a representation of densities of the morphological units at different spatial distances from the morphological feature and at different expression levels of the second biomarker; and

median expression levels of the second biomarker in the morphological units at different spatial distances from the morphological feature, and

store a representation of the relationship on the storage device.