hrd-analysis-agent

name	hrd-analysis-agent
description	AI-powered homologous recombination deficiency (HRD) analysis for PARP inhibitor response prediction using genomic scarring signatures and BRCA pathway assessment.

HRD Analysis Agent

The HRD Analysis Agent provides comprehensive analysis of homologous recombination deficiency for predicting response to PARP inhibitors and platinum chemotherapy. It integrates genomic scarring signatures (LOH, TAI, LST), BRCA1/2 status, and HRD gene pathway analysis.

When to Use This Skill

• When determining HRD status for PARP inhibitor eligibility.
• To calculate genomic instability scores (GIS) from tumor sequencing.
• For analyzing BRCA1/2 and HRD gene mutations.
• When predicting response to PARP inhibitors or platinum chemotherapy.
• To identify "BRCAness" phenotype in BRCA wild-type tumors.

Core Capabilities

1. Genomic Scar Scoring: Calculate LOH, TAI, and LST scores from copy number data.

2. BRCA Pathway Analysis: Assess mutations in BRCA1, BRCA2, and 13 other HRD genes.

3. HRD Classification: Determine HRD-positive vs. HRD-negative status.

4. PARP Inhibitor Prediction: Predict response to olaparib, niraparib, rucaparib, talazoparib.

5. Platinum Sensitivity: Predict platinum chemotherapy sensitivity.

6. Reversion Detection: Identify BRCA reversion mutations restoring HR function.

HRD Scoring Components

Score	Definition	Biological Basis
LOH	Loss of heterozygosity regions >15 Mb	Genomic scarring
TAI	Telomeric allelic imbalance	End-to-end fusions
LST	Large-scale state transitions	Break-induced repair
GIS	Combined LOH + TAI + LST	Overall HRD score

HRD-Positive Threshold: GIS ≥ 42 (Myriad myChoice) or equivalent

HRD Gene Panel

Gene	Function	HRD Contribution
BRCA1	HR core component	Major
BRCA2	RAD51 loading	Major
PALB2	BRCA2 partner	Moderate-Major
RAD51C/D	HR mediators	Moderate
ATM	DNA damage sensing	Moderate
CHEK2	Cell cycle checkpoint	Moderate
BARD1	BRCA1 partner	Moderate
BRIP1	Fanconi pathway	Moderate
CDK12	Transcription	Variable
RAD51B	HR mediator	Low-Moderate

Workflow

1. Input: Copy number segments, somatic mutations, germline variants.

2. Scar Calculation: Compute LOH, TAI, LST from segmented CNV data.

3. Gene Analysis: Assess pathogenic variants in HRD genes.

4. Score Integration: Calculate composite GIS score.

5. Classification: Determine HRD status.

6. Reversion Check: Screen for reversion mutations.

7. Output: HRD score, classification, gene mutations, treatment recommendations.

Example Usage

User: "Analyze HRD status for this ovarian cancer patient to guide PARP inhibitor selection."

Agent Action:

python3 Skills/Oncology/HRD_Analysis_Agent/hrd_analyzer.py \
    --cnv_segments tumor_segments.tsv \
    --mutations somatic_variants.maf \
    --germline germline_variants.vcf \
    --tumor_type ovarian \
    --purity 0.65 \
    --ploidy 2.1 \
    --output hrd_report.json

Commercial HRD Tests

Test	Components	Threshold	FDA Status
myChoice CDx	GIS + BRCA	≥42 or BRCA+	FDA approved
FoundationOne	LOH	≥16%	FDA approved
SOPHiA DDM HRD	GIS + BRCA	≥42 or BRCA+	CE-IVD

Clinical Indications

FDA-Approved PARP Inhibitor Indications:

• Ovarian: HRD+ or BRCA+ (maintenance, later-line)
• Breast: gBRCA+ (HER2-, metastatic)
• Pancreatic: gBRCA+ (maintenance)
• Prostate: HRR gene mutated (mCRPC)

Response Prediction

Status	PARP Response	Platinum Response
BRCA mutated	Very high	High
HRD+ / BRCA WT	High	Moderate-High
HRD- / BRCA WT	Limited	Standard
Reversion+	Poor	Poor

AI/ML Components

GIS Calculation:

• ASCAT/FACETS for allele-specific CNV
• HRDetect algorithm integration
• ML refinement of thresholds

Reversion Detection:

• Frameshift restoration analysis
• Splice site reversion
• Secondary deletion removing stop

Response Prediction:

• Multi-feature model (GIS + genes + expression)
• HRDetect signature scoring
• Clinical outcome integration

Resistance Mechanisms

Mechanism	Detection	Implication
BRCA reversion	Sequencing	Acquired resistance
53BP1 loss	Expression/mutation	Rescued HR
ABCB1 upregulation	Expression	Drug efflux
PARP1 loss	Expression	Target loss

Prerequisites

• Python 3.10+
• ASCAT/FACETS for CNV
• HRDetect implementation
• Germline/somatic variant callers

Related Skills

• Variant_Interpretation - For BRCA classification
• Liquid_Biopsy_Analytics_Agent - For ctDNA HRD monitoring
• Pan_Cancer_MultiOmics_Agent - For multi-omic context

Special Considerations

1. Tumor Purity: Low purity affects scar detection
2. Prior Therapy: Platinum may select resistant clones
3. Germline Testing: Important for family counseling
4. Reversion Monitoring: Serial testing recommended

Author

AI Group - Biomedical AI Platform