cBioPortal Newsletter April 2024

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Tali Mazor

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Apr 2, 2024, 10:02:10 AM4/2/24

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April, 2024

Hello, cBioPortal community!

It’s been a while since we last sent out a newsletter, but we’ve been hard at work adding lots of great new features and data to cBioPortal. We’re highlighting some of the features and data we’ve added over the past year below. Before we get to those, we have some exciting announcements:

We’ll be at the AACR Annual Meeting in San Diego!

Come visit us in the Exhibition Hall at Booth 3854 (in the non-profit row behind the AACR Central booth). Stop by to ask questions, request features or data, let us know how you use cBioPortal, or just say hi and grab a cBioPortal sticker or a pen.

We’ll also be giving two talks:

Saturday, April 6th at 12:30pm, Nikolaus Schultz, MSK: Learning from real world patient data to inform precision oncology: Variant interpretation and outcome prediction
Sunday, April 7th at 3pm, Ino de Bruijn, MSK: cBioPortal for Cancer Genomics

Check out our new paper in Cancer Research

Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal

Google Summer of Code

We’re also pleased to announce we’ve been accepted to Google Summer of Code 2024. Our list of project ideas is here.

Here’s just some of what we’ve been working on. For the full list, visit our News page.

In 2023 we added data from 12,080 samples across 25 studies including:

Diffuse Glioma (GLASS Consortium, 2022): 329 patients with longitudinal profiling of tumor diffuse glioma specimens, each with multiple sequenced samples and treatment histories.
Lung Adenocarcinoma Met Organotropism (MSK, Cancer Cell 2023): 2,298 patients with clinicopathological features associated with metastasis and genomic information obtained from a combination of broad-panel targeted DNA sequencing and whole-exome sequencing (WES)
Nerve Sheath Tumors (Johns Hopkins, Sci Data 2020): the first hg38 study in cBioPortal

New features in the Study View (exploring a study):

It is now possible to add a chart to display the copy number status of a specific gene across the cohort. All levels of copy number alterations are shown. See screenshot. An equivalent feature for gene-specific mutation status is coming soon.
The custom data feature now supports numerical data (previously only categorical data was allowed). See screenshot.
When filtering the data, you can now disable the automatic submission of each filter and instead queue up multiple filters and apply them together. Manual submission can help improve performance when applying multiple filters to a large dataset. See screenshot.

New features in the Results View (after submitting a query):

A new Structural Variants tab displays information about structural variants in the query gene(s). Structural variants are also still visible in the Mutations tab. See example.
The Mutations tab now includes annotations from the Repository of Variants with Unexpected Effects (reVUE). See screenshot.
OncoPrint now provides the option to see alteration frequencies per subgroup. Subgroups can be defined by any clinical track with categorical data - click on the 3 dots menu next to the track name and select ‘Show gaps’ to enable this view. See example.
OncoPrint also now supports custom colors for categorical clinical data values. Click on the 3 dots menu next to the track name and select ‘Edit colors’. See screenshot.

The Survival tab (available within the Group Comparison page and in the Results View) now supports landmark analysis and hazard ratios. See screenshot.

When viewing multiple patients in the Patient View, there is now an option to exclude the patient currently being viewed from the cohort by clicking the new minus icon (located next to the controls to switch between patients). To explore the updated cohort in Study View, click the total number of patients in the controls. See screenshot.

Trying to find studies with specific types of data? Two recent improvements help with this:

The Datasets page now lists which studies have samples profiled for Structural Variants. See screenshot.
The homepage now supports filtering studies based on available data types. See screenshot.

Updates to features for local installations of cBioPortal:

Mutational signature data on a patient page now includes a visualization of the reference COSMIC signatures. See screenshot. Mutational signature data can be uploaded as Generic Assay data in a local installation.
Sites that utilize the custom driver annotation feature can now customize how these custom annotations are displayed in the website. See screenshot.

cBioPortal version 6 has been released with a major repackaging of the cBioPortal backend code to improve the development experience. The backend has been upgraded to use Java Spring Boot v3.1.4. The CORE and MAF modules have been moved to new repositories. All other modules have been compacted into a single source repository. We have also updated the JVM to 21 and many libraries have been updated to address security and performance issues. See more information in the v6.0.0 release notes.

The cBioPortal documentation has been updated and reorganized. The documentation has information for everyone, whether you are a user of the website or the API, a data curator, a developer or someone who maintains a local instance.

New Feature Highlight: Mutations tab in Group Comparison

The cBioPortal group comparison functionality already supported comparing the frequency at which genes are altered by mutations, copy number or structural variants between groups of samples. The new Mutations tab now allows you to compare the specific mutations in a gene between two groups.

In this example, we are using the MSK-IMPACT Clinical Sequencing Cohort to examine samples from individuals with prostate adenocarcinoma, comparing samples taken from primary sites of disease to those taken from metastatic sites of disease.

At the top, you can select your gene of interest - here we’re looking at the androgen receptor (AR), a key gene in prostate adenocarcinoma. The two-sided lollipop chart clearly shows the low frequency of mutations in samples acquired from primary sites of disease, most of which are variants of unknown significance. In contrast, the samples taken from metastatic sites of disease have more mutations in AR, most of which are predicted to be driver events.

In the table below, a statistical analysis identifies which, if any, of the specific mutations are enriched in either group. From this, we can see that while the lollipop plot shows H878Y is present in both groups, it is statistically enriched in the group of samples taken from metastatic sites.

To learn more about cBioPortal, review our documentation which includes FAQs, webinars and tutorials. If you have questions, please don't hesitate to reach out to us at cbiop...@googlegroups.com.

Stay tuned for more updates, and thank you for your continued support in advancing cancer genomics research with cBioPortal.