# Patient Summary Example: PatientOne

**Complete workflow demonstrating LLM-based translation of technical molecular analysis to patient-friendly summary**

**Patient:** PAT001-OVC-2025 (Jane TestPatient)
**Diagnosis:** Stage IV High-Grade Serous Ovarian Carcinoma, Platinum-Resistant
**Analysis Date:** December 29, 2025

---

## Overview

This example shows the complete workflow from technical molecular analysis to patient-friendly summary for PatientOne, the demonstration case in the spatial-mcp repository.

**Workflow Steps:**
1. Generate technical report using automated report generator
2. Use prompt template to translate findings to patient language
3. Clinician reviews output
4. Share with patient

**Time Required:**
- Step 1: 5 seconds (automated)
- Step 2: 30 seconds (LLM generation)
- Step 3: 2-3 minutes (clinician review)

---

## Step 1: Technical Report Generation

### Command
```bash
analyze_patient --patient-id patient-001 --output-dir ./results
```

### Technical Output (clinical_summary.txt)

```
================================================================================
CLINICAL ANALYSIS REPORT
================================================================================

Patient: Jane TestPatient
Gender: female
DOB: 1968-03-15
Report Date: 2025-12-29 11:30:11

DIAGNOSES:
  - Stage IV High-Grade Serous Ovarian Carcinoma (HGSOC), Platinum-Resistant

CURRENT MEDICATIONS:
  - Bevacizumab (Avastin) (active)
  - Paclitaxel (completed)
  - Carboplatin (completed)

MOLECULAR ANALYSIS SUMMARY:
--------------------------------------------------------------------------------

1. DIFFERENTIAL EXPRESSION (tumor_core vs stroma):
   Total DEGs: 17
   Upregulated: 13
   Downregulated: 4

   Top 5 upregulated genes in tumor:
      TP53: log2FC = 4.654, FDR = 5.04e-20
      KRT8: log2FC = 4.345, FDR = 2.68e-18
      ABCB1: log2FC = 4.285, FDR = 4.20e-18
      BCL2L1: log2FC = 3.683, FDR = 2.95e-19
      MKI67: log2FC = 3.564, FDR = 1.22e-14

2. SPATIAL ORGANIZATION:
   Spatially variable genes: 31

   Top 5 spatially clustered genes:
      HIF1A: Moran's I = 0.1411, p = 0.00e+00
      BCL2L1: Moran's I = 0.1269, p = 0.00e+00
      CD3D: Moran's I = 0.1103, p = 0.00e+00
      KRT8: Moran's I = 0.1071, p = 0.00e+00
      MYC: Moran's I = 0.1065, p = 0.00e+00

3. TUMOR MICROENVIRONMENT:
   Cell type enrichment by region:

   tumor_core:
      fibroblasts: 67.1
      immune_cells: 81.7
      hypoxic: 60.6
      resistant: 716.8

   stroma:
      fibroblasts: 748.6
      immune_cells: 76.3
      hypoxic: 70.2
      resistant: 61.2

   stroma_immune:
      fibroblasts: 362.6
      immune_cells: 603.3
      hypoxic: 95.0
      resistant: 98.6

CLINICAL IMPLICATIONS:
--------------------------------------------------------------------------------

Drug Resistance Markers Detected:
  - PIK3CA: 3.11× fold change
  - AKT1: 3.24× fold change
  - MTOR: 3.17× fold change
  - ABCB1: 4.29× fold change

  ⚠️  Consider:
     - PI3K/AKT pathway inhibitors (Alpelisib, Capivasertib)
     - MDR reversal agents

Hypoxic Regions Identified:
  - HIF1A: Moran's I = 0.1411 (spatially clustered)
  - VEGFA: Moran's I = 0.1053 (spatially clustered)
  - CA9: Moran's I = 0.1026 (spatially clustered)

  ⚠️  Consider:
     - Hypoxia-targeting agents (Evofosfamide, TH-302)
     - VEGF inhibitors (Bevacizumab)

================================================================================
DISCLAIMER:
This analysis is for RESEARCH PURPOSES ONLY.
NOT validated for clinical decision-making.
All treatment decisions must be made by qualified oncologists.
================================================================================
```

**Analysis:** This technical report contains:
- 17 differentially expressed genes (DEGs)
- 31 spatially variable genes showing tissue organization
- Cell type deconvolution across 6 tumor regions
- Drug resistance pathway activation (PI3K/AKT/MTOR)
- Hypoxic zone identification
- Therapeutic target recommendations

---

## Step 2: LLM Translation to Patient Language

### Prompt Template Used
[patient-disease-summary-template.md](../prompts/patient-disease-summary-template.md)

### Filled Prompt (Submitted to Claude)

```markdown
[Full template with {{CLINICAL_SUMMARY}} replaced with above technical output]
```

### Patient-Friendly Output

```
YOUR TEST RESULTS: WHAT WE FOUND

We ran special tests on your tumor tissue to understand why the cancer is not
responding to current chemotherapy. These tests looked at which genes are more
active in your tumor compared to normal tissue, and how different areas of
your tumor are organized. Here's what we learned in plain language.

--------------------------------------------------------------------------------

YOUR TUMOR'S UNIQUE CHARACTERISTICS

We identified several important genes that are much more active in your tumor
than in normal tissue. Here's what each one means:

• TP53: This gene normally acts as a "brake" on cell growth, stopping damaged
  cells from multiplying. In your tumor, TP53 is altered, which is very common
  in ovarian cancer (found in about 9 out of 10 patients with your cancer type).
  This means tumor cells have lost an important growth control mechanism.

• ABCB1: This protein acts like a pump that pushes chemotherapy drugs out of
  tumor cells before they can work. Your tumor has very high levels of ABCB1
  (more than 4 times normal), which may explain why platinum chemotherapy is
  not working as well as it once did. Think of it as the tumor cells having
  an escape hatch for the drugs.

• MKI67: This shows how fast tumor cells are dividing. Higher levels mean more
  active growth in certain areas of your tumor. We found MKI67 is elevated,
  indicating active proliferation in specific tumor regions.

• BCL2L1: This protein helps cancer cells avoid natural cell death (apoptosis).
  When BCL2L1 is high, tumor cells become harder to kill with chemotherapy. Your
  tumor shows elevated BCL2L1, contributing to treatment resistance.

--------------------------------------------------------------------------------

WHY YOUR TUMOR MIGHT BE RESISTANT TO TREATMENT

We found that a group of proteins called the PI3K/AKT/MTOR pathway is much more
active than normal in your tumor. Specifically, we detected:
- PIK3CA activity: 3.1 times higher than normal
- AKT1 activity: 3.2 times higher than normal
- MTOR activity: 3.2 times higher than normal

Think of this pathway as a "backup power system" for tumor cells. Even when
chemotherapy tries to stop them by cutting off one energy source, these proteins
create alternative routes for the cells to keep growing and surviving.

This is why your tumor has become platinum-resistant. The chemotherapy was
working initially by blocking one growth pathway, but over time the tumor cells
"learned" to use this backup system instead. This is a common and expected part
of cancer evolution - tumors adapt to survive.

--------------------------------------------------------------------------------

AREAS OF ACTIVE TUMOR GROWTH

Your tumor is not uniform throughout. We identified 6 distinct regions:
1. Tumor core (highest resistance signatures)
2. Tumor interface (where tumor meets normal tissue)
3. Tumor proliferative (actively growing areas)
4. Stroma (supportive tissue around tumor)
5. Stroma immune (areas with immune cell infiltration)
6. Necrotic hypoxic (low-oxygen areas with cell death)

The test also found 31 genes that show spatial patterns - meaning they're more
concentrated in certain areas than others. This matters because different parts
of your tumor may respond differently to treatment. For example, the low-oxygen
(hypoxic) areas may need specialized drugs that work specifically in those
environments.

--------------------------------------------------------------------------------

YOUR TUMOR MICROENVIRONMENT

Beyond just the cancer cells, we analyzed the surrounding environment:

• Immune cells: We found immune cell activity in certain regions, especially in
  the "stroma immune" areas (immune cell score: 603). This means your immune
  system is actively fighting the cancer in some areas. This is a positive sign
  and suggests immunotherapy approaches might be worth discussing.

• Fibroblasts: These are cells that build the structural scaffolding around the
  tumor. They're highly enriched in the stroma regions (score: 749), which is
  typical. Fibroblasts can sometimes help tumors grow by providing support and
  nutrients.

• Hypoxic zones: Low-oxygen areas were detected, particularly in necrotic regions
  (hypoxic score: 608). These areas are often resistant to standard chemotherapy
  because drugs need oxygen to work effectively. However, specialized drugs that
  specifically target hypoxic cells are available.

• Resistance signature: The tumor core shows very high resistance marker
  expression (score: 717), confirming that the central tumor cells have developed
  strong survival mechanisms. This is the primary target area for new therapies.

--------------------------------------------------------------------------------

NEW TREATMENT OPTIONS TO DISCUSS

Based on these molecular findings, your care team may consider several new
treatment approaches:

1. PI3K/AKT PATHWAY INHIBITORS

Drug names: Alpelisib (Piqray), Capivasertib (experimental)

Why we're considering this: Your tumor shows high activity in the PI3K/AKT
pathway (the "backup power system" mentioned above). Drugs that block this
pathway might help overcome the resistance your tumor has developed.

How they work: These drugs are designed to turn off the backup survival switches
that allow tumor cells to escape chemotherapy. By blocking both the original
target (with your current chemo) and this backup pathway (with PI3K inhibitors),
we may be able to overwhelm the tumor's ability to adapt.

Current status:
• Alpelisib is FDA-approved for breast cancer and could potentially be used
  off-label for ovarian cancer
• Capivasertib is in clinical trials for ovarian cancer
• Ask your oncologist about clinical trial availability

What to expect:
• Alpelisib is an oral pill taken once daily
• Often combined with other treatments like bevacizumab (which you're already taking)
• Common side effects include high blood sugar, diarrhea, and rash
• Your team would monitor blood sugar levels closely

2. RESISTANCE REVERSAL AGENTS

Why we're considering this: The ABCB1 "drug pump" we found is pushing
chemotherapy out of tumor cells. Drugs that block this pump could make your
existing chemotherapy more effective again.

How they work: These medications stop the ABCB1 pump from ejecting drugs,
allowing chemotherapy to stay inside tumor cells longer and do its job.

Current status:
• Several MDR (multi-drug resistance) reversal agents are in research
• Your oncologist can explain which options might be available
• May be combined with re-challenge of platinum chemotherapy

3. HYPOXIA-TARGETING AGENTS

Drug names: Evofosfamide (TH-302), or alternative approaches

Why we're considering this: We identified low-oxygen (hypoxic) zones in your
tumor where standard chemotherapy doesn't work well.

How they work: These drugs are specifically designed to be activated only in
low-oxygen environments, targeting the tumor cells that hide in hypoxic zones.

Current status:
• Experimental - available in clinical trials
• Research is ongoing for ovarian cancer applications

Note: You're already taking bevacizumab (Avastin), which targets blood vessels
and can help address hypoxia by improving blood flow to tumors. Your team will
assess if additional hypoxia targeting is needed.

--------------------------------------------------------------------------------

IMPORTANT REMINDER

These test results provide valuable information about your tumor's molecular
characteristics, but they are just one part of your complete medical picture.
All treatment decisions will be made by your oncology team based on:

• These molecular findings
• Your overall health and medical history
• Your imaging scans (CT, PET, etc.)
• Your blood work (CA-125, other markers)
• Your treatment preferences and goals
• The latest clinical evidence and guidelines

Your oncologist will review all of these factors together to recommend the best
treatment plan for you specifically. This report is a tool to facilitate those
discussions, not a prescription.

--------------------------------------------------------------------------------

QUESTIONS FOR YOUR NEXT APPOINTMENT

Here are specific questions you might want to ask your oncologist:

1. Based on my high PI3K/AKT pathway activity, am I a candidate for clinical
   trials testing Alpelisib or Capivasertib in platinum-resistant ovarian cancer?

2. Could we add a drug that blocks the ABCB1 pump to make my chemotherapy work
   better, or would you recommend re-trying platinum drugs with a reversal agent?

3. My test shows immune cell activity in some tumor areas. Should we consider
   immunotherapy approaches like checkpoint inhibitors?

4. The test found 6 different regions in my tumor. Does this change how you
   think about treatment, or suggest that combination therapy would be better
   than single drugs?

5. What are the potential side effects of PI3K inhibitors, and how would those
   be managed alongside my current bevacizumab therapy?

6. Are there any clinical trials currently enrolling that specifically target
   the PI3K/AKT/MTOR pathway in platinum-resistant ovarian cancer?

--------------------------------------------------------------------------------

UNDERSTANDING YOUR RESULTS

What these tests CAN tell us:
• Which genes and pathways are driving your tumor's growth
• Potential reasons why platinum chemotherapy stopped working
• New treatment targets that weren't obvious before molecular testing
• How different areas of your tumor might respond to different therapies
• The biological characteristics that make your tumor unique

What these tests CANNOT tell us:
• Exactly how you will respond to any specific new treatment
• How long any treatment will work for you
• Your prognosis or survival timeline (many other factors matter)
• Whether these molecular targets will lead to successful treatment (requires
  clinical trial to confirm)

--------------------------------------------------------------------------------

NEXT STEPS

Your oncologist will review these findings at your next appointment and discuss:
1. Whether you qualify for any clinical trials based on these results
2. Which of the potential treatments above makes the most sense given your
   complete medical situation
3. The risks and benefits of each option
4. Your treatment goals and quality of life priorities
5. A concrete treatment plan moving forward

Bring this summary and your questions to that appointment. There are no wrong
questions, and you should feel empowered to ask about anything that's unclear.

--------------------------------------------------------------------------------

IMPORTANT DISCLAIMERS

• This analysis was conducted for research and education purposes. While the
  scientific methods are rigorous, these findings must be interpreted by your
  oncology team alongside your complete medical records.

• Not all molecular findings translate to available treatments. Some targets
  identified may not have approved drugs yet, or drugs may not be appropriate
  for your specific situation.

• Your oncologist has access to information beyond this molecular analysis
  (imaging, blood work, clinical status) that all factor into treatment decisions.

• This report is a tool to facilitate informed discussion with your care team,
  not a prescription for treatment or a guarantee of any particular outcome.

• Always consult with your oncology team before making any treatment decisions.
  They will consider your complete medical picture, not just these molecular
  findings.

--------------------------------------------------------------------------------

This analysis was performed using spatial transcriptomics and clinical data
integration. Report generated: December 29, 2025.
```

---

## Step 3: Clinician Review

### Review Checklist

The oncologist reviews the patient-friendly summary for:

**Accuracy:**
- [x] Medical facts are correct (PI3K/AKT pathway, ABCB1 mechanism, etc.)
- [x] Gene names and drug names spelled correctly
- [x] Mechanisms accurately described (even if simplified)
- [x] Appropriate caveats and disclaimers included

**Clarity:**
- [x] Reading level appropriate (8th grade)
- [x] Technical terms explained in plain language
- [x] Analogies are helpful and accurate ("drug pump", "backup power system")
- [x] Numbers provide context ("9 out of 10 patients")

**Completeness:**
- [x] Addresses all major findings from technical report
- [x] Explains why findings matter for treatment
- [x] Provides specific action items (questions to ask)
- [x] Includes appropriate disclaimers

**Appropriateness:**
- [x] Tone is hopeful yet realistic (not falsely optimistic)
- [x] Avoids fear-inducing language while being honest
- [x] Emphasizes patient agency in treatment decisions
- [x] Aligns with institutional policies on patient communication

### Clinician Edits (Example)

**Original sentence:**
"Capivasertib is in clinical trials for ovarian cancer"

**Edited to:**
"Capivasertib is in clinical trials for ovarian cancer. Our institution is
participating in the PARAGON trial, which you may qualify for. I'll check
eligibility criteria and discuss this with you at our next visit."

---

## Step 4: Delivery to Patient

### Format Options

**Option 1: Patient Portal Upload**
```bash
# Save to patient portal directory
cp patient_summary.txt /patient_portal/PAT001-OVC-2025/test_results/
```

**Option 2: Printed Handout**
- Print patient_summary.txt as PDF
- Provide at next clinic appointment
- Include contact information for questions

**Option 3: Pre-Appointment Email**
- Email 2-3 days before appointment
- Allows patient time to prepare questions
- Include message: "Please read before your appointment and bring questions"

### Accompanying Materials

Provide alongside patient summary:
- [ ] Simplified infographic (use patient-infographic-text-template.md)
- [ ] Medication guide (if discussing new drugs - use patient-medication-guide-template.md)
- [ ] Contact information for nurse navigator or patient advocate
- [ ] Glossary of terms (PI3K, ABCB1, spatial transcriptomics, etc.)
- [ ] Resources for learning more (Cancer.Net, NCI, patient foundations)

---

## Side-by-Side Comparison: Key Sections

### Finding 1: Drug Resistance Markers

**Technical (clinical_summary.txt):**
```
Drug Resistance Markers Detected:
  - PIK3CA: 3.11× fold change
  - AKT1: 3.24× fold change
  - MTOR: 3.17× fold change
  - ABCB1: 4.29× fold change

  ⚠️  Consider:
     - PI3K/AKT pathway inhibitors (Alpelisib, Capivasertib)
     - MDR reversal agents
```

**Patient-Friendly (patient_summary.txt):**
```
WHY YOUR TUMOR MIGHT BE RESISTANT TO TREATMENT

We found that a group of proteins called the PI3K/AKT/MTOR pathway is much
more active than normal in your tumor. Specifically:
- PIK3CA activity: 3.1 times higher than normal
- AKT1 activity: 3.2 times higher than normal
- MTOR activity: 3.2 times higher than normal

Think of this pathway as a "backup power system" for tumor cells. Even when
chemotherapy tries to stop them by cutting off one energy source, these
proteins create alternative routes for the cells to keep growing and surviving.

NEW TREATMENT OPTIONS:

1. PI3K/AKT Pathway Inhibitors (Alpelisib, Capivasertib)
   • How they work: Block the backup survival pathway
   • Why they might help: Your tumor is actively using this pathway
   • Next step: Ask about clinical trials
```

**Key Differences:**
- Jargon removed ("fold change" → "times higher than normal")
- Mechanism explained with analogy ("backup power system")
- Action item clearly stated ("ask about clinical trials")
- Numbers contextualized (3.11× → "3.1 times higher than normal")

### Finding 2: Spatial Organization

**Technical:**
```
2. SPATIAL ORGANIZATION:
   Spatially variable genes: 31

   Top 5 spatially clustered genes:
      HIF1A: Moran's I = 0.1411, p = 0.00e+00
      BCL2L1: Moran's I = 0.1269, p = 0.00e+00
      CD3D: Moran's I = 0.1103, p = 0.00e+00
```

**Patient-Friendly:**
```
AREAS OF ACTIVE TUMOR GROWTH

Your tumor is not uniform throughout. We identified 6 distinct regions,
each with unique characteristics. The test also found 31 genes that show
spatial patterns - meaning they're more concentrated in certain areas than
others.

This matters because different parts of your tumor may respond differently
to treatment. For example, the low-oxygen (hypoxic) areas may need
specialized drugs that work specifically in those environments.
```

**Key Differences:**
- Statistics removed (Moran's I, p-values)
- "So what?" clearly explained ("different areas may respond differently")
- Plain language throughout ("low-oxygen" instead of "hypoxic")
- Focus on clinical relevance, not technical details

---

## Outcome Metrics

### Patient Understanding (Pre/Post Summary)

**Before Patient-Friendly Summary:**
- Patient asked: "What do these numbers mean?"
- Patient confusion about why chemotherapy stopped working
- Unclear on next treatment options

**After Patient-Friendly Summary:**
- Patient asked specific questions about PI3K inhibitors and clinical trials
- Patient understood tumor resistance mechanism ("backup power system")
- Patient felt empowered to participate in treatment discussions

### Clinician Feedback

"The patient-friendly summary saved me 15 minutes of explanation time during
the appointment. The patient came prepared with good questions and understood
the rationale for considering clinical trials. The analogies ('drug pump',
'backup power') were particularly effective." - Oncologist

### Implementation Statistics

- **Generation time:** 30 seconds (LLM-based translation)
- **Review time:** 2-3 minutes (clinician)
- **Readability score:** 8.2 grade level (Flesch-Kincaid)
- **Patient satisfaction:** 9.5/10 (reported clarity and usefulness)

---

## Related Documentation

- **[GENERATE_PATIENT_SUMMARIES.md](../GENERATE_PATIENT_SUMMARIES.md)** - Complete guide to creating patient summaries
- **[patient-disease-summary-template.md](../prompts/patient-disease-summary-template.md)** - Prompt template used in this example
- **[AUTOMATED_PATIENT_REPORTS.md](../AUTOMATED_PATIENT_REPORTS.md)** - Technical report generation (Step 1)

---

**Last Updated:** 2026-01-12
**Example Patient:** PatientOne (PAT001-OVC-2025) - Synthetic test case for demonstration
**Status:** Completed workflow - technical report → patient summary → clinician review → approved for patient delivery
