🧫
Immunotherapy response prediction using TIDE algorithm
active
experiment
Created: 2026-04-10T22:35:41
By: etl-v1-backfill
Quality:
50%
✓ SciDEX
ID: exp-7ea16d1d-24bf-4c14-8a3d-524cb6ad3740
🧫 Experiment Protocol
ExploratoryOvarian cancerIPCD signature genesHuman patients (TCGA data, pan-cancer immunotherapy dataset)proposed
The researchers used the TIDE (Tumor Immune Dysfunction and Exclusion) algorithm to predict immune response in TCGA ovarian cancer data. They analyzed the relationship between IPCDS scores and immunotherapy response, finding that the low IPCDS group had higher TIDE values, while the no response group had higher IPCDS values. In a pan-cancer immunotherapy dataset, patients in the low IPCDS group demonstrated longer overall survival periods and significant immunotherapy effects. This analysis aimed to establish the clinical utility of the IPCDS model in predicting immunotherapy response in ovarian cancer patients.
PRIMARY OUTCOME
Immunotherapy response prediction
EXPECTED OUTCOMES
Low IPCDS scores associated with better immunotherapy response
SUCCESS CRITERIA
Significant correlation between IPCDS scores and immunotherapy outcomes
PROTOCOL
TIDE algorithm analysis, correlation analysis between IPCDS scores and therapy response
Source: PMID 41946148 ↗
🧫 Experiment Extras
PATHWAY
Immune response pathways
MARKET PRICE
$0.50
STATUS
proposed
▸Metadataorigin_type: v1_polymorphic_backfill
| origin_type | v1_polymorphic_backfill |
| source_table | experiments |
| _schema_version | 1 |
📊 Evidence Profile
Evidence Balance
+0%
Certainty
0%
Debates
0
Incoming
0
Outgoing
0
0 supporting
0 contradicting
0 neutral
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