> For the complete documentation index, see [llms.txt](https://docs.owkin.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.owkin.com/what-you-can-do-with-k-pro/target-identification-and-indication-discovery/rank-candidate-targets.md).
# Rank candidate targets
**What to do:** Compare a candidate gene's expression across cancer types to identify indications where it's overexpressed. Ask for a comparison with healthy tissue from GTEx for more meaningful results. Once you have candidate indications, you can check tractability, safety, and protein-level evidence for the target.
**Example prompt:**
> Compare the expression of NECTIN4 across all TCGA cancer types. Show me a pan-cancer overview ranked by median expression level, and highlight which indications show overexpression compared to normal tissue from GTEx.
**Expected result:** A ranked visualization of NECTIN4 expression across TCGA indications, with tumor vs. normal comparisons.
**Follow-up:**
> For the top 3 indications with highest NECTIN4 overexpression, show the association between NECTIN4 expression (high vs. low) and overall survival.
[**A-S-R-T-C breakdown**](https://docs.owkin.com/getting-started/prompting-guide-and-prompt-library)**:** Compare \[A] NECTIN4 \[S] at Bulk RNA level \[R] as a ranked table \[T] across all TCGA cancer types vs. GTEx normal tissue \[C].
**Go further:**
> What is known about NECTIN4 tractability, safety liabilities, and approved or clinical-stage drugs targeting it?
K-Pro queries curated knowledge bases (such as Open Targets, ChEMBL, and the Human Protein Atlas) to summarize tractability, known safety signals, and existing drugs for the target.
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://docs.owkin.com/what-you-can-do-with-k-pro/target-identification-and-indication-discovery/rank-candidate-targets.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
