xiaohongshu
xiaohongshu
---name: chromosomal-instability-agent description: AI-powered analysis of chromosomal instability (CIN) signatures for cancer prognosis, immunotherapy response prediction, and therapeutic vulnerability identification. license: MIT metadata: author: AI Group version: "1.0.0" created: "2026-01-19"...
Full skill instructions
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The Chromosomal Instability Agent analyzes CIN signatures to predict cancer prognosis, immunotherapy response, and therapeutic vulnerabilities. It integrates copy number alterations, aneuploidy scores, and CIN-related gene expression for comprehensive genomic instability assessment.
CIN Scoring: Calculate comprehensive CIN scores from copy number data.
Aneuploidy Quantification: Measure arm-level and focal copy number alterations.
CIN Gene Expression: Analyze CIN70 and other transcriptional signatures.
Immune Correlation: Assess CIN-immune microenvironment relationships.
Therapeutic Vulnerability: Identify CIN-targeted treatment options.
Prognostic Modeling: Predict outcomes based on CIN signatures.
| Metric | Calculation | Interpretation |
|---|---|---|
| Aneuploidy score | Arm-level alterations | Chromosome-level CIN |
| SCNA burden | Total CNV alterations | Overall instability |
| Weighted GII | Fraction altered genome | Focal vs broad changes |
| CIN70 | 70-gene signature | Transcriptional CIN |
| WGII | Weighted genome instability | Comprehensive score |
Core genes reflecting CIN phenotype:
Input: Copy number data (segments), gene expression, mutation data.
CNV Analysis: Calculate arm-level and focal alterations.
Signature Scoring: Compute CIN70 and other transcriptional signatures.
Integration: Combine DNA and RNA-based CIN metrics.
Immune Analysis: Correlate CIN with TME composition.
Vulnerability Assessment: Identify targetable dependencies.
Output: CIN scores, prognosis, treatment recommendations.
User: "Analyze chromosomal instability in this breast cancer sample and identify treatment vulnerabilities."
Agent Action:
python3 Skills/Oncology/Chromosomal_Instability_Agent/cin_analyzer.py \
--cnv_segments tumor_cnv.tsv \
--expression rnaseq_tpm.tsv \
--mutations somatic.maf \
--tumor_type breast_cancer \
--signatures cin70,cin25 \
--output cin_report/
High CIN Associates With:
Mechanisms:
| Target | Agents | CIN Context |
|---|---|---|
| PARP | Olaparib, etc. | High CIN + HRD |
| ATR | Berzosertib | Replication stress |
| WEE1 | Adavosertib | G2/M dependency |
| CHK1 | Prexasertib | Cell cycle checkpoint |
| KIF11 | Ispinesib | Mitotic dependency |
| Aurora kinases | Alisertib | Mitotic errors |
| CIN Level | Prognosis | ICI Response | Alternative Therapy |
|---|---|---|---|
| Low | Better | Better | Standard care |
| Intermediate | Variable | Variable | Combination therapy |
| High | Poor | Poor | CIN-targeted agents |
| Extreme | Very poor | Immune desert | Chemotherapy |
CIN Score Prediction:
Prognosis Modeling:
Therapeutic Matching:
| Cancer Type | Typical CIN Level | Driver Events |
|---|---|---|
| Ovarian HGSOC | Very high | TP53, BRCA |
| Triple-neg breast | High | TP53, PI3K |
| Colorectal MSS | Moderate-high | APC, TP53 |
| Colorectal MSI | Low | MMR deficiency |
| Thyroid (PTC) | Low | BRAF, RAS |
| Melanoma | Moderate | BRAF, NRAS |
AI Group - Biomedical AI Platform
xiaohongshu
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