cBioPortal

Public cBioPortal

• Accessibility:
  
  A public deployment of cBioPortal, like the one hosted by Memorial Sloan Kettering Cancer Center (MSKCC), is accessible to anyone with internet access. It is designed to serve the global research community by providing access to a wide range of cancer genomics data from public sources.
  
• Data
  The data available on a public cBioPortal is often aggregated from multiple public repositories, such as The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and other publicly available datasets. This data is anonymized and standardized to ensure privacy and consistency.
  
• Use Cases:
  The public version is mainly used by researchers, clinicians, and students who need access to large, well-curated datasets for research, hypothesis generation, or clinical interpretation.
  
• Customization
  Public deployments are generally less customizable by end-users since they serve a broad audience and must maintain consistency and integrity across the datasets provided.

Private cBioPortal Deployment

• Accessibility
  A private deployment is typically hosted within an institution, organization, or private network and is only accessible to authorized users. Research institutions, hospitals, or companies often use this setup to keep their data secure and accessible only to specific users or groups.
• Data
  In a private deployment, the institution can upload and manage its proprietary data, including unpublished research data, patient-specific clinical data, or sensitive information that must be kept confidential. The data can be customized, controlled, and secured according to the organization's policies.
  
• Use Case
  Private deployments are used for internal research, data sharing among collaborators within the same institution, or integrating and analyzing proprietary data. They provide the flexibility to include internal and public datasets while maintaining data security and privacy.
  
• Customization
  Private deployments allow for extensive customization. Users can tailor the portal to their needs by adjusting the data types (supported by cBioPortal), annotations, visualizations, and user interfaces. Additionally, private deployments can be configured to comply with institutional data governance policies.

Public cBioPortal Use Cases

1. Academic Research:
   • Example: A cancer researcher studying lung cancer wants to explore genetic alterations across different subtypes of lung cancer. They use the public cBioPortal to access TCGA lung cancer datasets, enabling them to identify commonly mutated genes, copy number variations, or expression patterns associated with specific subtypes.
   • Benefit: The researcher benefits from having access to a large, curated dataset without needing to generate or manage this data themselves.
2. Education and Training:
   • Example: An instructor teaching a graduate-level course on cancer genomics uses the public cBioPortal to demonstrate how to analyze cancer genomics data. Students are assigned to explore datasets for specific cancer types, analyze the frequency of mutations in key oncogenes, and generate hypotheses about their functional roles.
   • Benefit: Students gain hands-on experience with real-world data, enhancing their understanding of cancer genomics.
3. Clinical Hypothesis Generation:
   • Example: A clinician is interested in investigating whether a particular genetic mutation observed in a patient is commonly associated with poor prognosis in breast cancer. By querying the public cBioPortal, they find that this mutation is linked with shorter overall survival in a subset of patients from the TCGA dataset.
   • Benefit: The clinician can use this information to inform further research or clinical decision-making, although more than the public data is required for direct clinical application.
4. Benchmarking and Validation:
   • Example: A bioinformatics team developing a new algorithm for detecting driver mutations in cancer uses public cBioPortal datasets to benchmark their tool. They compare the results generated by their algorithm with known mutations documented in public data.
   • Benefit: Access to well-characterized public datasets allows for robust validation without needing in-house data collection.

Private cBioPortal Use Cases

1. Internal Research and Development:
   • Example: A pharmaceutical company is developing targeted therapies for a specific mutation found in a rare cancer type. It deploys a private cBioPortal to integrate and analyze internal clinical trial data, preclinical research, and any proprietary genomic data it's gathered.
   • Benefit: The company can securely analyze and share sensitive data across its R&D teams and easily compare them to the publicly available cBioPortal data, facilitating drug development while protecting intellectual property.
2. Clinical Decision Support:
   • Example: A hospital deploys a private cBioPortal to manage and analyze genomic data from its cancer patients. Oncologists use the portal to explore patient-specific data, such as somatic mutations, copy number alterations, and expression profiles, alongside clinical records. This helps them tailor treatment plans to individual patients.
   • Benefit: The hospital can provide personalized medicine while ensuring patient data remains secure and compliant with regulatory standards (e.g., HIPAA in the US).
3. Collaborative Research Projects:
   • Example: A consortium of cancer research institutions establishes a private cBioPortal to share data among its members. This portal includes unpublished datasets, allowing members to analyze data collaboratively while controlling data access and usage.
   • Benefit: Researchers can collaborate effectively across institutions without risking the exposure of sensitive or proprietary data.
4. Translational Research:
   • Example: A research hospital studies the molecular mechanisms underlying treatment resistance in metastatic melanoma. They use a private cBioPortal to integrate genomic data from patients who responded poorly to standard treatments, allowing researchers to identify potential biomarkers or novel therapeutic targets.
   • Benefit: Combining clinical outcomes with genomic data facilitates this targeted analysis, leading to insights that could inform future clinical trials.