Background

MutPanning is designed to detect rare cancer driver genes from aggregated whole-exome sequencing data. Most approaches detect cancer genes based on their mutational excess, i.e. they search for genes with an increased number of nonsynonymous mutations above the background mutation rate. MutPanning further accounts for the nucleotide context around mutations and searches for genes with an excess of mutations in unusual sequence contexts that deviate from the characteristic sequence context around passenger mutations.

The name MutPanning is inspired by the words "mutation" and "panning". The goal of the MutPanning algorithm is to discover new tumor genes in aggregated sequencing data, i.e. to "pan" the few tumor-relevant driver mutations from the abundance of functionally neutral passenger mutations in the background. Previous approaches for cancer gene discovery were mostly based on mutational recurrence, i.e. they detected cancer genes based on their excess of nonsynonymous mutation above the local background mutation rate. Further, they search for mutations that occur in functionally important genomic positions, as predicted by bioinformatical scores). These approaches are highly effective in tumor types, for which the average background mutation rate (i.e., the total mutational burden) is low or moderate.

The ability to detect driver genes can be increased by considering the nucleotide context around mutations in the statistical model. MutPanning utilizes the observation that most passenger mutations are surrounded by characteristic nucleotide sequence contexts, reflecting the background mutational process active in a given tumor. In contrast, driver mutations are localized towards functionally important positions, which are not necessarily surrounded by the same nucleotide contexts as passenger mutations. Hence, in addition to mutational excess, MutPanning searches for genes with an excess of mutations in unusual sequence contexts that deviate from the characteristic sequence context around passenger mutations. That way, MutPanning actively suppresses mutations in its test statistics that are likely to be passenger mutations based on their surrounding nucleotide contexts. Considering the nucleotide context is particularly useful in tumor types with high background mutation rates and high nucleotide context specificity (e.g., melanoma, bladder, endometrial, or colorectal cancer).

Algorithm

Most passenger mutations occur in characteristic nucleotide contexts that reflect the mutational process active in a given tumor. MutPanning searches for mutations in “unusual” nucleotide contexts that deviate from this background mutational process. In these positions, passenger mutations are rare and mutations are thus a strong indicator of the shift of driver mutations towards functionally important positions.

The main steps of MutPanning are as follows (adopted from Dietlein et al.):

(i) Model the mutation probability of each genomic position in the human exome depending on its surrounding nucleotide context and the regional background mutation rate.

(ii) Given a gene with n nonsynonymous mutations, use a Monte Carlo simulation approach to simulate a large number of random “scenarios” in which n or more nonsynonymous mutations are randomly distributed along the same gene .

(iii) Compare the number and positions of mutations in each random scenario with the observed mutations in gene . Based on these comparisons, derive a p-value for the gene.

(iv) Combine this p-value with additional statistical components that account for insertions and deletions, the abundance of deleterious mutations, and mutational clustering.

The following figure (adopted from Dietlein et al.) illustrates how MutPanning works.

Running MutPanning

You have two options to run MutPanning. You can either run MutPanning as a module on the GenePattern platform (genepattern.org). Registration to GenePattern is free and you can conveniently launch MutPanning from your webbrowser and add files via drag and drop.

Further, we provide an interactive desktop version of MutPanning, which allows you to run MutPanning on your own computer (at least 8 GB memory required) and add files through a dialog window

Input Files

A detailed description of the input file formats of MutPanning can be found in the MutPanning Software User Manual, which can be downloaded under the Downloads section. In brief, MutPanning needs the following two input files.

Each row in this file corresponds to an individual mutation that was detected in one of the tumor samples. This file should have the following columns: Hugo_Symbol, Chromosome, Start_Position, End_Position, Strand, Variand_Classification, Variant_Type, Reference_Allele, Tumor_Seq_Allele1, Tumor_Seq_Allele2, Tumor_Sample_Barcode

Each row in this file corresponds to an individual sample. This file should have the following columns: ID, Sample, Cohort

Output Files

The output of MutPanning is a zip folder that contains a tab-delimited significance file for each cancer type, contained in the sample annotation file. This file lists the significance of each gene in the respective tumor type. Further, the zip folder contains a significance file for the pan-cancer cohort that lists the significance of each gene across the entire cohort. Each row in these files annotates the signifificance of a gene. These files contain the following columns:

gene: gene name in HUGO nomenclature

target_n: nonsynonymous target size

target_s: synonymous target size

count_n: nonsynonymous mutation count

count_s: synonymous mutation count

p: p-value derived by the MutPanning method

q: q-value (false-discovery rate) derived by correcting the p-value for multiple hypothesis testing.

MutPanning Software

MutPanning is distributed under the BSD-3-Clause open source license. By downloading the MutPanning software, you acknowledge and agree to the terms of this license.

Instead of downloading the software, MutPanning is also publically available as a module on the GenePattern server. After free registration, you can run MutPanning as an interactive module on genepattern.org from your browser.

Sequencing Datasets

The sequencing datasets from our study can be downloaded below. Sequencing data in the maf file have been compiled from different sequencing studies. Differences in tissue collection protocols, variant calling pipelines and mutation reports (e.g., synonymous mutations were not reported in 6.1% of the samples) may represent a potential source of heterogeneity. Please keep this limitation in mind when using this dataset.

The full whole-exome sequencing dataset from 11,873 tumors that we used in the study can be downloaded below. MutPanning needs approx. 2 hrs 10 min to run on these data.

If you would like to test MutPanning, you can use the subset of 582 melanoma samples below. MutPanning needs approx. 20 min to run on these data.

Even if you do not intend to use these data for testing purposes, we encourage you downloading these data, in order to familiarize yourself with the format and prepare your own data accordingly. Detailed instructions on how to prepare your data for MutPanning are provided in the MutPanning software dialog

Using MutPanning?

If you use MutPanning or any of the tumor genes shown on this website, please cite our preprint on biorxiv.org, while the MutPanning manuscript is under review. We will update this reference, as soon as the MutPanning manuscript has been accepted for publication at a scientific journal.

Contact

If you have any questions, suggestions or feedback, we would love to hear them. Further, if you need any technical assistance with the MutPanning software, the sequencing dataset, or the findings reported on this website, we are there to help. Please contact us via email under help@cancer-genes.org

Disclaimer

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MutPanning is distributed under the BSD-3-Clause open source license. By downloading the MutPanning software, you acknowledge and agree to the terms of this license.