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iCAGES-guided Precision Therapy for Cancers in Contrast to Standard Care or IHC-guided Theray

Multicentre Perspective Non-interventional Study of Survival Benefits of iCAGES-guided Therapy in Contrast to Standard Therapy or IHC-guided Therapy for Advanced Cancers

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03192501
Enrollment
250
Registered
2017-06-20
Start date
2017-07-01
Completion date
2039-07-01
Last updated
2024-06-25

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cancer, Gene Abnormality, Gene Product Sequence Variation, Lung Cancer

Keywords

lung cancer, iCAGES, gene mutation, precision medicine, advanced cancers, IHC, Targeted therapy

Brief summary

This study prospectively evaluates whether the use of iCAGES (integrated CAncer GEnome Score) tool in guiding the treatment of advanced cancers is superior to current standard care or IHC-guided therapy in progress free survival (PFS),overall survival (OS),and improvement of life quality.

Detailed description

Cancer is a fatal disease caused by the accumulation of various oncogene and tumor suppressor gene mutations. Studies of high-throughput sequencing for patients who suffered from cancer has found that different mutations play a different role in the occurrence and development of different cancers. Several gene panels already exist to help identify mutations in a few genes that may have corresponding FDA-approved drugs or drugs under clinical trials. However, given whole-genome/exome sequencing data, the suitable clinical analysis tool to analyze individualized cancer-related gene mutations, and recommend the most appropriate targeted treatment options among hundreds of possible drugs therapy is absent currently. The recently proposed iCAGES is a precise biomedical informatics analysis tool, which could help increase the accuracy of cancer driver gene detection and prioritization, bridge the gap between personal cancer genomic data and prior cancer research knowledge,and facilitate cancer molecular diagnosis as well as personalized precision therapy. IHC detection of multiple molecules such as EGFR, HER2-3, TROP3, NECTIN4, MET, B7-H3-4, B1-H7, Claudin18.2, FGFR1-4, Mesothelin, ROR1, BCMA, AXL, TF, FRα, CD70, PPARα, HIF-2α, RET, ROS1, NTRK, CDK4/6, FLT3, EZH2 are also scheduled for appropriate targeted therapy and comparison if available.

Interventions

DRUGinhibitors, ADC drugs such as tarceva, capmatinib, padcev et al for A/C group.

Choose appropriate targeted drugs according to NGS/IHC results.

Sponsors

The First Affiliated Hospital of Guangzhou Medical University
CollaboratorOTHER
Sun Yat-sen University
CollaboratorOTHER
Second Affiliated Hospital of Guangzhou Medical University
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 70 Years
Healthy volunteers
No

Inclusion criteria

* Pathological and clinical diagnosis of recurrence / metastatic lung cancer or other advanced cancers. * There are PACS images available at the Second Affiliated Hospital of Guangzhou Medical University and the collaborated Hospitals. * The patient is informed consent and signed a written consent.

Exclusion criteria

* Age \> 70 or \<18 years old. * Previous history of malignant tumors. * Pregnant or lactating female patients. * Any serious concomitant disease that is expected to have an adverse effect on prognosis, including the heart disease that treatment is required, unsatisfactory controlled diabetes and psychiatric disorders.

Design outcomes

Primary

MeasureTime frameDescription
PFS2 yearsThe PFS will be recorded during the follow up time.
OS2 yearsThe OS will be recorded during the follow up time.

Secondary

MeasureTime frameDescription
Quality of life.2 yearsPhysicians Global Assessment to measure quality of life
Painone yearVisual Analog Score for pain

Countries

China

Contacts

Primary ContactZhenfeng Zhang, MD,PhD
zhangzhf@gzhmu.edu.cn+86-020-34153532
Backup ContactDeji Chen, MD,PhD
chendeji2003@163.com+86-020-34153532

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026