Welcome to the VarSeq VSClinical AMP Tutorial!
This tutorial covers a basic VSClinical AMP workflow with an emphasis on understanding and exploring VSClinical AMP classification tools.
To complete this tutorial you will need to download and unzip the following file, which includes a starter project.
The majority of the workflow described in this tutorial requires VarSeq with the VSClinical AMP algorithm. You can go to Discover VarSeq and request a viewer or evaluation license.
Files included in the above ZIP file: VarSeq VSClinical AMP Tutorial – Starter project containing 1 VCF sample file for the AMP Guidelines example.
The most recent version of VarSeq can be downloaded from here: VarSeq Download.
Select your operating system and download. Additional information for platform specific installation can be found in the Installing and Initializing section of the manual.
The Setup Wizard will then guide you through the setup process.
On the final page of the Setup Wizard, select Finish with the Launch VarSeq option checked.
This will bring up the introductory VarSeq page where new users can register their information. This will lead to a confirmation email being sent to confirm the email address.
Once the email has been confirmed, users can select the Login tab and enter their login email and password.
At this point, the VarSeq Viewer mode is accessed and can be used. If the user already has a license key, this can be activated by selecting Help on the title bar and then selecting Activate a VarSeq License Key.
This will bring up a dialog where the license key can be entered. Enter you license key, select and select Verify.
Once the license key is verified, select the I accept the license agreement after reading the agreement, and select Verify.
Congratulations! At this point, the product license is activated and you are ready to start an example project or a tutorial!
During the initial installation process, the user will be asked where to store the AppData folder. Although this location can be changed after installation, it is recommended that multiple-user organizations select a shared drive location to increase ease of project sharing and to decrease redundancy.
VarSeq VSClinical AMP
The VSClinical workflow is used to first pass selected variants through a user-defined filter chain, analyze the filtered variants according to industry standard guidelines in a streamlined fashion to reach an interpretation and then generate a clinical report. The user-defined filter chain can be included to eliminate low quality, common, or known benign variants for example and then the filtered variants can be pulled into VSClincial for the processing of somatic and germline variants according to the AMP and ACMG guidelines, respectively. Users will be guided through all the available evidence for the variant or biomarker in a streamlined fashion that locks in a consistent interpretation process. After reaching the final classification and interpretation, a clinical report can rapidly be generated. Please view the VSClinical ACMG Guidelines tutorial for workflow generation and details specific to the ACMG Guidelines and germline variant analysis.
The VSClinical AMP guidelines differ from the ACMG Guidelines by analyzing the oncogenicity of somatic biomarkers. These biomarkers include single nucleotide variants, insertions or deletions, copy number variants, gene fusions, and considerations for wild type genes. Furthermore, the goal is to not only account for the various biomarkers but to store the final classifications and interpretations and supply treatment options for the patient in a clinical setting. This means the drug sensitivity and resistance information, and prognostic and diagnostic information will be used to determine the biomarker classification and oncogenicity score.
Oncogenicity and AMP Tiers
VSClinical serves as the ACMG and AMP guideline interpretation hub and allows for creating more intuitive workflows and higher consistency in results. In the case of the ACMG Guidelines, VSClinical provides a workflow that integrates the exact criteria and classification rules to follow the guidelines like shown below.
The Golden Helix Oncogenicity Score was developed to provide a criteria-based scoring system similar to the ACMG guidelines but with the numeric pathogenicity scale introduced by Invitae’s Sherloc scoring system. Many of the scoring criteria are similar if not identical to those used by the ACMG guidelines, while others are specialized to match somatic annotations and clinical evidence. For example, missense variants are checked against the cancer hotspot annotation as well as active binding sites as these are often present for activating missense mutations. The criteria and strengths were developed in consultation with the GA4GH Variant Interpretation in Cancer Consortium (VICC).
Similar to the Pathogenicity Score produced by the ACMG Guidelines, the Oncogenicity Score allows the user to get a quick snapshot of how much evidence is pushing the variant in a direction that warrants more careful review or whether it can be safely ignored as Benign. In fact, the Benign and Likely Benign classifications utilize the exact same criteria, rules and thresholds as the ACMG scoring system. Because it is based on numeric criteria, the summation of all scored criteria place the variant on a scale from Benign to Oncogenic.
After a variant is suspected to be Oncogenic, the next level of evaluation is to consider the variant as a Biomarker for the current patient’s tumor type. This requires a review of many sources of clinical evidence that may contain links between this biomarker and targeted therapies as well as potential diagnostic and prognostic implications.
The AMP Guidelines provide a rubric to grade the summation of this clinical evidence and categorize these into “tiers”. To reach Tier 1, a variant of strong clinical significance would require Level A and B evidence i.e. known FDA approved therapies or well powered studies with expert consensus respectively. While Tier II variants of potential significance require level C and D evidence which is FDA approved treatments for different tumor types, investigational therapies, multiple published studies with consensus, or preclinical trials with case reports. Tier III variants of unknown clinical significance will have little or no presence in general frequency, nor cancer specific databases and no publications with cancer association. Lastly, Tier IV variants are benign or likely benign due to high allele frequency in population databases and have no published evidence for association to cancer.
The capture of all this relevant evidence to determine the tier is a large undertaking, but VSClinical creates the ability to not only automate the classification process but also automate the presentation of all relevant content in a final report.
CancerKB and Annotations Databases
The AMP Guidelines paper provides several tables of public and proprietary databases that contain information about variant frequencies, known somatic mutations, functional predictions, and treatment/clinical trial information. These categorized lists are meant as a non-exhaustive survey of resources that clinical labs may reference when following the AMP guidelines. VarSeq and VSClinical includes all of these sources that are publicly available and many of the proprietary sources (some are not available through commercial licensing).
The first table from the AMP paper enumerates population databases that can be used to determine common variants versus rare variants.
Many cancer variants recur in specific types of cancer, and somatic catalogs allow annotating how many samples and in which tumor types a variant has previously been observed. Clinical databases such as CIViC and PMKB catalog evidence statements and clinical interpretations about mutations and specific tumor types. Finally, other cancer-specific sources such as mutation hot-spots and clinical trials for relevant cancer drugs are referenced.
Sequence repositories are used for sequence alignments and the definition of genes and transcripts on the reference sequence.
We also support Clinical, Drug and Prediction annotations such as DrugBank, ClinVar, the Clinical Genomics Database and the Genetics Home Reference. DrugBank in particular provides critical information about FDA approved drugs with indications for a given gene or biomarker.
The next group of annotations is used to highlight splice site regions and incorporate functional prediction scores for possible sequence disruption.
An additional feature of the VSClinical AMP Guidelines is the GoldenHelix CancerKB catalog which is accessible for any GoldenHelix user with purchase of the AMP Guidelines. This catalog is manually curated dataset containing assessments of biomarkers and genes in the context of specific cancers, including information on the Gene, Biomarker and available treatments. This catalog is built by an expert panel of curators and professionals in the clinical context that aggregate and write up interpretations the most commonly seen biomarkers and genes. For example, CancerKB will contain interpretations for the clinically relevant BRAF V600E mutation in melanoma. Interpretations provided by CancerKB are a great starting point, and as you save your own lab interpretations, your internal knowledgebase will grow to cover more and more of the biomarkers seen in each new sample. Additionally, users of the AMP feature can choose to share their interpretations back to the GHI curators anonymously. CancerKB will be updated on a regular basis to serve as an ever-growing cancer resource.
The CancerKB catalog can be used as a starting point for a lab to finalize an interpretation and streamline the progress to final report, which we will see in the following examples.
This tutorial was accompanied by a VarSeq project contained in a ZIP file. Before starting, download the ZIP file, and extract the contents to a convenient location. Then open up the project, AMP Tutorial Example, by double clicking on the file.
This is a premade project where variants have been imported, a filter chain composed, and biomarkers selected. Upon first opening the project, you can see a filter chain on the left and larger variant table on the right. Looking to the upper right-hand corner will show the summation of this project which contains data from 4 samples and a total of 126,966 variants.
- Filter field = PASS
- Genotype Quality >= 90
- Read Depth >= 200
- Variant Allele Frequency < 0.1
- Effect is LoF or Missense OR 2+ out of 4 predicted splicing disruptive
- Is in the COSMIC database
- Classified by the ACMG Classifier as Pathogenic.
Overall, this filter chain is used to first reduce the large amount of variants down to higher quality variants, then variants that look to be causing problems like LoF or splice disrupting. And finally, variants are filtered to those that are present in the COSMIC are classified to be Pathogenic. For the sample displayed on opening, this reduces the pool of variants from over 100,000 to 4 candidates.
These filters where chosen to provide interesting examples in our final filter list and not as an example production filtering workflow. For example, you most likely want to include all VUS and Likely Pathogenic variants in the Classification filter.
Once we have determined a smaller selection of variants to explore further, we will open up the AMP Guidelines. This is done by selecting the plus sign next to the Variants tab and selecting VSClinical.
From the drop-down menu on this new VSClinical tab, select AMP Guidelines.
The first dialog that appears on the new tab is the VSClinical AMP Options dialog. This dialog prompts the user to choose the assessment catalogs for saving Cancer Interpretations, Somatic Variants, and Germline ACMG Variants. If assessment catalogs for any category already exist, they can be found or navigated to from the corresponding drop-down menu, but we want to create new assessment catalogs for this tutorial by selecting Create first for the Internal Database of Cancer Interpretations section.
The create catalog will first ask you to determine the database type. The options are SQLite, PostgreSQL, MySQL, or if you have the added feature connected, VSWarehouse.
If not using VSWarehouse, a common choice is using the SQLite type and saving the catalog locally. In either case, select a name or location for the new assessment catalog and select, OK.
Repeat this step for the Internal Database of Classified Somatic Variants and Internal Database of Classified Germline ACMG Variants. The example below shows 3 created SQLite assessment catalogs called Cancer AC, Somatic AC. and Germline AC.
The next dialog is the Annotations Versions and Download dialog. Download all of the Required sources.
It should also be noted that users may have previous versions of dependencies already saved. If so, the blue Update All icon will show up, and and orange update arrow will indicate which source(s) have updates available. The user can choose to update, by selecting the Update All icon or continue with the older version of the annotation source. to download the current version. Make your download selection and select the Download button. Download progress will be displayed and once complete, select Close .
The last dialog prompts the user to set up record sets to not only track variants in the project but also to assign reporting sections for variants. These are optional and do not have to be created. For this tutorial leave the default No Record Sets and select Apply.
As one last step before we explore the AMP Guidelines, we will stash the filter chain by hovering the mouse over the upper left-hand corner of the filter chain tab and click on the arrow icon that appears.
Start by clicking on Start New Evaluation underneath the sample information section.
The top of the AMP Guidelines screen has a title bar that shows the tab navigation between the Evaluation , Genes, Variants, Biomarker, Drugs & Trials and Report tabs. The three lines on the right side of the title bar will show a summary of the evaluation, close evaluation option, and the option to view the annotation sources used for the evaluation. The AMP Guidelines initially opens on the Evaluation tab where the sample and collection data can be entered, and patient information can be added (this has already been done for this tutorial). This information will be used to automatically populate the report information.
Scrolling down the screen, the next section is the Tumor Type. The tumor type can be selected by first narrowing down the tissue type on the left side of the selection menu, by searching for the tumor type directly in the Search Tumor Type search bar, or by using the tumor type acronym (for example (NSCLC) for Non-Small Cell Lung Cancer). It is important to select the tumor type at this stage as future analysis will use this to collect relevant data. This tutorial is examining a melanoma tissue sample.
The right side of the screen also has a quick access list of common tumor types to select.
The next section below tumor type is made of 2 sections: Included Somatic Variants and Biomarkers and Genes with Significant Wild-Types. First, the Included Somatic Variants is the table that displays all of the variants to be analyzed. The top of the table lists the different variant types which include Small Variants, CNVs, Fusions, and Wild-Types. To add variants to the evaluation, start by choosing Add Variants from Project. Four variants should auto-populate from the project. Then select the BRAF p.V600E variant at the top and choose Select. Once the variant is added on the right, select Add 1 Variants.
Next, select Manually Enter Variants and enter RAF1 S257L. Under Mutation Origin, select Germline Suspected instead of Somatic. Then choose Select and Add 1 Variants.
When a variant is added manually, the AMP workflow automatically navigates to the Variants tab for germline variants, or the Biomarkers tab for somatic variants, CNVs, and fusions. Since we are adding a few more variants to the workflow, navigate back to the Evaluations tab to add more variants.
Next, select CNVs (0) to add CNVs to the evaluation. Select Manually Add CNVs and enter ERBB2 and make sure Duplication is selected. Then choose Select and Add 1 CNVs.
Lastly, select Fusions (0) and choose Manually Add Fusions. Enter BCR-ABL1, choose Select, Add 1 Fusions .
After all of the variants are added, the evaluation should look like Figure 5-7.
The final section in the Evaluation tab is the NGS Sequencing Summary showing the NGS statistics like the variant allele frequencies and the types of variants being analyzed.
Before taking a closer look at the BRAF and RAF1 small variants in the Variants tab, the Genes tab can be used to analyze the coverage for this sample. Select Genes from the title bar.
The Genes tab not only includes the NGS Coverage of Summary that is also present in the Evaluation tab, but also includes a section on reporting coverage regions, and a deeper analysis of calculated coverage and hotspot analysis.
The coverage region plot allows user to adjust the read depth and mapping quality thresholds, and also allows the switching between showing coverage on a per-gene or per-target region.
As an example, hover over the BRAF gene in the plot and see the coverage statistics on a gene level. If you click on the gene, the plot changes to show each target from the coverage panel.
After ensuring that the coverage of the sample is of high quality for the variants and biomarkers that will be analyzed, we are now ready to take a closer look at the BRAF and RAF1 small variants in the Variants tab.
The Variants tab is arranged with the different scoring and classification sections in the body of the tab, and a variant detail sidebar on the right side. The sidebar contains the variant position and identifiers on the top, the origin and report information as well as the current oncogenicity or pathogenicity score in the middle, and then a list of sections to easily navigate the body of the Variants tab below.
The body of this page is setup to show the Scoring and Evidence Summary on the top, the classification recommendations below, the information section used to populate the report, and finally the rest of the page lists the different criteria used to reach the classification.
For this tutorial, we will first look at the RAF1 germline variant which was the second variant in the list. This variant can be selected by clicking on the number 2 card at the top of the sidebar on the right.
Example 1 SNV RAF1 S257L
Since the RAF1 variant was added as a germline variant, the variant page is formatted to utilize the ACMG Guidelines which were discussed in a previous ACMG tutorial found here. But to review the classification that was reached here, scroll down to the ACMG Criteria Recommendations section and review the criteria that were selected to reach the classification of Pathogenic.
The first criteria selected, PM2 was added since the variant is novel in gnomAD and 1000 Genomes population catalogs. Next, PM1 was selected since nearby variants have shown to be pathogenic as well. The third criteria, PP2 was selected since this RAF1 variant is a missense variant with a high Z-Score and therefore has a higher likelihood to be pathogenic by its very nature. The fourth criteria, PP3 relates that both GERP++ and PhyloP predicted damaging and conserved across different species. The fifth criteria PS1 was selected because the S257L variant results in an amino acid change which is shared by a previously classified pathogenic variant. Finally, last criteria, PM5 confirms pathogenic by showing that this variant has been classified as pathogenic in ClinVar. This was a straight-forward pathogenic variant but note that the scored criteria and the pathogenic classification are reflected in the variant sidebar on the right.
After confirming the classification of this variant, scroll down in the main page to the next section, Variant Interpretation for SampleNA12877-50-Horizon_S1, to create the interpretation that will be used in the final report.
This section shows the variant classification and allows the user to specify the related disorder and inheritance model. Make sure the the Report As dropdown has Secondary Germline selected and In the For disorder dropdown select Noonan syndrome 5. The interpretation was created by adding explanations from the different scoring criteria in the Scored Criteria section of the variant. To include this interpretation in the report, click the blue Add to Interpretation button, then click Review & Save Now…, then Save and Close.
As mentioned previously, the user can scroll down from this section to re-analyze any of the scored criteria in the ACMG analysis of this germline variant. Next, we will look at the other Small Variant, the BRAF variant by selecting the 1 card at the top of the sidebar on this page.
Example 2 SNV BRAF V600E
This BRAF V600E variant represents the first somatic marker to analyze in this project. The variant tab is arranged very similarly as to the other small variant, but due to the somatic nature, the ACMG Criteria section is replaced with an Oncogenicity Scoring Recommendations section. Also, the pathogenicity color scale in the slide bar has been replaced with an Oncogenicity Scale color bar.
Scrolling down to the Oncogenicity Scoring Recommendations section shows that this variant has been scored with an oncogenicity score of +10 by all of the criteria listed on the left, but we will go through each of these separately.
First, scroll down to the Report Variant as Biomarker section of this page.
Like with the previous variant analysis, this section shows the information that will be used in the final report, but this somatic variant has a related tumor type which in this example is, melanoma. From the Tumor Type dropdown, select Skin Neoplasm. Make sure that Biomarker is selected in the Report As: dropdown and that the interpretation on the right is filled in. Your screen should look like Figure 7-6, then click Review and Save Now, then Save and Close.
If there was already an interpretation for this variant saved, the dialog that appears would show the differences and allow the user to select which interpretation to save.
Scrolling down to the next section gets us to the start of our somatic variant classification.
The Somatic Catalogs section asks if this variant appears in COSMIC, and if it does, how often. Since this variant appears in almost 30,000 samples, the highest value, SC+3 is selected. The card on the right shows the tumor type frequency for different catalogs like COSMIC and ICGC.
The next section looks at the frequency of the variant in different Germline Population Catalogs. This variant shows up rarely in gnomAD (only in the South Asian group) and not at all in 1000 Genomes, so PF+0 is selected for this category and the oncogenicity score is not adjusted
The next section, Relevant Clinical Assessments results in the CE+3 criteria being selected since this variant has been previously classified as pathogenic in ClinVar as well as previously classified as oncogenic in CiVIC.
The following sections analyze the impact of the variant on the gene level and since there are multiple pathogenic variants nearby, the NP +1 criteria can be selected. Clinvar gets updated quite frequently, so the numbers reflected here may be different than what is current.
It also turns out that his BRAF variant occur in a cancer hotspot, so we can also select the HR+1 criterion in the Hotspots & Active Binding Sites section. This section also shows us that the variant occurs in an active binding site, so the oncogenicity score is increased when adding the AR+1 criterion.
The final section on this page is Computational Evidence and shows the functional predictions and splice site results.
This section lets us see that all 4 functional prediction scores support that this variant will likely cause a deleterious effect on the gene, so an IP+1 is selected, but there does not appear to be a splice site disruption, so SP+0 was selected.
All of these scores combined give us an oncogenicity score of +10 and confirm that this is indeed an oncogenic variant.
Next, we will move on to the Biomarkers section clicking the tab in the title bar.
The Biomarkers tab has a similar workflow with the biomarker information in the body of the tab and a biomarker snapshot and navigation section on the right sidebar. As the user scrolls down the body of this tab, the sections become more specialized as the sections cover first the gene level and then the biomarker level, and finally incorporate any clinical evidence. The top of the sidebar shows small cards for the biomarkers in this project (taken from the Biomarkers and Genes with Significant Wild-Types section of the Mutation Profile tab). As mentioned previously, we have 3 biomarkers in this project, and the first is the BRAF V600E Small Variant.
The BRAF Gene Summary section is where we collect data about the BRAF gene, especially using the different catalog tools on the right. These descriptions and interpretations can be expanded and then copied using the plus signs at the end of each entry and pasted into the Interpretation on the left. Note that generally this is not a tumor type specific interpretation and will be re-used for all biomarkers in this gene.
The next section is BRAF Alteration Frequency and Outcomes and goal of this section is to analyze the gene in terms of the related tissue and tumor types and describe the frequency of mutation and prognostic outcomes related to biomarkers in this gene.
Also note that the interpretation is tumor type specific and will only populate for new samples with the same tumor type. The drop-down menu on the top of the section allows users to switch to a more broad tumor type if the selected one is too specific for the interpretation being written. Once changes are made to any of these interpretation sections, it is important to select the Review & Save Now… button to compare and save any changes.
To show this, click within the interpretation text box on the left, hit Enter on your keyboard to reach a new line, and paste. Since the entry was adjusted, the option to Review & Save Now… becomes available so select it. If there was already an interpretation for this variant saved, the dialog that appears would show the differences and allow the user to select which interpretation to save.
The other important feature in this dialog is the blue checkbox in the lower left-hand corner. If this is checked, the interpretation will be shared with the Golden Helix Curation Team to improve the CancerKB database. For this example, though, close out of this dialog.
The next section as we scroll down now moves from the broader gene level impact to the more specific biomarker level in BRAF V600E Biomarker Summary.
It is important to note that the biomarker interpretation is still specific to a tumor type as well as a biomarker scope. The scope should be changed at this point if the following clinical interpretation is not specific to the exact variant but more of a class of variants in a region or for the entire gene. For example, a loss-of-function variant in a tumor suppressor gene should be interpreted at the broadest scope of “Gene LoF” so future variants in this gene that are loss-of-function share the same interpretation. In this case, BRAF V600E has specific clinical evidence and we will keep the scope at the level of this mutation.
The tabs on the Variant Classification and Details card present various sources of information about the current biomarker to assist in writting a high level summary of the biomarker (save clinical evidence for the remaining type-specific sections). If there are entries for this variant or other related variants in CancerKB or your own interpretation catalog, the will show up in the Related Interpretations and Related Interpretations in Other Tumor Type cards.
The final section in the biomarker tab assesses the Clinical Evidence for BRAF V600E. This includes information covering Drug Sensitivity, Drug Resistance, Prognostic data, and Diagnostic data. These tables can also be sorted by drug name, tissue type, and type of evidence.
This information is used to start filling in the interpretation for the final report, including important drugs, and specifying the clinical evidence tier value. In this example, there are multiple FDA approved drug therapies for BRAF V600E, so this definitely shows a Tier I biomarker entry. The table contains an integration of relevant clinical sources, specifically DrugBank, PMKB and CIViC and are sorted by the strength of their clinical assertions. The details of each assertion is on the right when selecting each row, and often includes citations.
Next, we will look at the next biomarker by selecting the second card at the top of the right sidebar.
Example 3 CNV ERBB2 Amplification
The next biomarker is a CNV amplification in the ERBB2 gene. Looking at this entry, the ERBB2 information has been switched to apply to the tumor type scope of “All Cancers”. Scrolling down to the ERBB2 Gene Summary section and expanding the ERBB2 Function and Descriptions: section shows multiple entries in the COSMIC database. These COSMIC entries have also been organized into categories like Function Summary, Role in Cancer, and Change of Cellular Energetics.
It is also important to notice the multiple PubMed IDs shown in the Interpretation text box of the ERBB2 Gene Summary section. Since these PubMed IDs have been written in the format (PMID: 12345678), they have been automatically recognized and listed in the Inline References: array below the Interpretation text box. These PubMed IDs and titles will also be automatically included and populated in the final report.
Scroll down to the ERBB2 Amplification Clinical Evidence section and change the filter Disease / Tissue Specific: option to All to look at clinical evidence for this gene within all cancer tumor types. This brings in over 100 clinically relevant drug trial entries for this specific mutation in the ERBB2 gene covering all cancer types.
Data from this table can be used to populate the clinically relevant interpretation section for drug interactions which will be carried to the final report.
Next, we will examine the last biomarker by clicking on the 3 card at the top of the sidebar.
Example 4 Fusion BCR-ABL1
For the last example, we are concerned mainly with trying to collect any drug sensitivity for the ABL1–BCR gene fusion, so scroll to the ABL1 Activating Mutation Clinical Evidence section (or select the Clinical Evidence title in the sidebar).
In the Drug Sensitivity table, make sure the Disease / Tissue Specific: filter is set to All.
From here, we can populate the Drug Sensitivity by selecting first checking the box next to Report ABL1 Fusion with BCR Drug Sensitivity. Then choose the FDA approved entry in the list for Dasatinib and selecting the plus sign next to the drug name in the Selected Clinical Evidence section.
If any changes or interpretations were been added you can select the Review & Save… button.
At this point, we have collected information on the markers of interest and completed our pathogenicity and oncogenicity scoring so we are ready to move on to the final report by selecting Report in the title bar.
Generating a Clinical Report
One of the main value points of VSClinical’s ACMG/AMP reports is in the auto-population of data from your workflow into your clinical reports. In doing so, the results are faster reporting and allowing users to have control over the standardization of the reporting which reduces errors throughout the reporting process.
The report page shows the automatically populated fields and is organized first with Patient and Sample information from the Patient tab, then Biomarker Results from the 3 biomarkers we analyzed, then the Secondary Germline Findings of the germline variant we examined, Coverage Statistics again from the Patient tab, and finally any inline references collected from the entirety of the project with hyperlinks to the source data.
This is a good place to review the data, and any incomplete sections will provide warnings to the user under the Interpretations section in the sidebar. Since we do not have any incomplete or unsaved interpretations, the report is ready to be finalized, so select the green Sign Out & Finalize button.
This will finalize the project and will not allow any changes to be made without first revoking the report freeze. This concept is reiterated with a follow-up dialog that makes sure the user want to finalize, so select Confirm Sign Out.
Next, click on the plus sign next to the Report Exports section and select New Word Export so we can render a Word format report document. Now we need to generate a new report template. To do so, click on the blue +New Report Template button. From the Copy System Template dropdown, choose Cancer Report Template V2.docx, name the new template AMP Tutorial, and click Create.
Now that the report template is defined click the Render icon to generate the final report.
Below is an example of a finalized report. This report is easy to modify as the template is based on Microsoft word, which allows you to orient the template to fit your labs specific branding needs. The report can also integrate sample and patient level information if that data is present in a manifest text file or it can be added manually. Most importantly, the Reports can include interpretations for all variants and genes, somatic and germline, that were added to the VSClinical interface. Lastly, coverage statistics with low quality regions can be incorporated and in-line references are also cited.
Speed, autopopulate fields, standardization, references assessment catalogs, CancerKB boosts clinical report as a starting point, minimizing errors in the process paste and copy mistakes).
Clinical Trials Tab
Example 5 PIK3CA H1047R
VSClinical AMP also provides a simple and efficient means to search for relevant Clinical Trials for sample biomarkers. We’ll explore this feature using additional example biomarkers starting with a PIK3CA H1047R missense variant for invasive breast carcinoma. The first step will be to browse to sample NA12877-05-Horizon_S4
A message will inform you that the sample has changed and confirm the switch. Then open the existing evaluation by selecting Open and Continue.
After the sample change, you will notice an existing evaluation has already been created for this sample. Choose Open and Continue on the evaluation card to open this evaluation. You will then be prompted to update the sources used in the evaluation, at the bottom of the Annotations Versions and Download window, choose Update All, then Rescore Evaluation.
You will also notice in the Evaluation Tab that the Tumor Type is set for Breast – Invasive Breast Carcinoma and the PIK3CA biomarker has already been added.
At this point you can explore the variant oncogenicity score in the Variant Tab, but the primary focus will next be in the Biomarkers Tab. Golden Helix supplies the CancerKB catalog which contains expert reviewed gene and biomarker interpretations. In the Biomarker Tab, the interpretations are not only prefilled from CancerKB but are also matching the interpretation scope for Invasive Breast Carcinoma.
The bottom section of the Biomarker Tab is the assessment of available treatment options which are not only also auto-filled from CancerKB, but are also specific to the tissue type and matching H1047R mutation. The list of these drugs are in hierarchical order for matches in DrugBank, PMKB, and CIViC. This variant has multiple drugs listed such as Alpelisib and Fulvestrant which will be the focus for the clinical trial search.
Moving now to the Drug & Trials Tab, set the zipcode to 59718 (MT zipcode) click on the Alpelisib Matching Trials icon to review available trials for the drug and summary details on trial status and sites.
A new window will pop up with clinical trial matches and the sole trial that is found is for a combination therapy study for Alpelisib with Fulvestrant which is in recruiting status for any PICK3CA mutations.
Clicking on the Sites tab, the nearest site selected to the 59718 zipcode location is in Billings, MT.
Additionally, scrolling to the bottom of the Drug & Trials Tab users will be presented with not only summary details for the final report, but also the selection of inclusion and exclusion criteria relevant for the patient.
Let’s explore another clinical trial search for a different sample.
Example 6 NRAS G12D
Switch to sample NA12877-10-Horizon_S3 and open the existing evaluation, update, and rescore the evaluation. In this sample evaluation the tumor type for this sample is Skin-Melanoma and the biomarker under investigation is G12D missense variant in NRAS.
Moving to the Biomarkers Tab, the interpretations for NRAS and the G12D variant are prefilled from CancerKB for Melanoma. Focusing on the listed treatment options, this specific biomarker does not have matches for FDA-Approved therapies in DrugBank, nor PMKB, but does have multiple treatments found from CIViC with B – Level Evidence and a 5 star confidence score for Binimetinib.
With the preferred treatments selected, this patient also wishes to find clinical trials near their new home in Australia. In the Drugs & Trials tab, select to change Country to Australia.
There is now an updated list of trials in Australia with a match for the treatment Trametinib.
After clicking on Matching Trials, the Summary details list Trametinib as one drug being studied for any biomarkers in NRAS among other genes for lung cancer and melanoma.
Selecting the Sites tab, the patient could potentially enroll in two locations: Melbourne and Prahran.
Now that we’ve covered how to change trial search locations, let us switch to our last sample and variant to show these new features in a final report.
Example 7 EGFR T790M
Switch to the last sample NA12877-25-Horizon_S2 and open the existing evaluation. The sample in this evaluation with the tissue type selection made for Lung-Non-Small Cell Lung Cancer and the search for treatments will be specific for the oncogenic T790M variant in EGFR.
Notice again the pre-filled CancerKB interpretations for EGFR and T790M, as these interpretations will be automatically pulled into the final report. Reviewing treatment options, we see a number of FDA-Approved treatments for T790M.
Unfortunately, many of these drugs also have known submissions for drug resistance. This concern is relevant to the clinical trial search as some trials may take ineffective treatments into consideration as an inclusion criteria.
Moving to the Drug & Trials Tab, change the country back to United States and click on matching trials for Osimertinib. Also, deselect Recruiting Trials Only and select the NCT02917993 trial. You’ll notice that this trial is not currently recruiting but serves as a great example for specific inclusion criteria for troublesome biomarkers like T790M that infer resistance to treatments.
Reviewing the details of the clinical trial at the bottom of the page, select the inclusion criteria as seen in the figure 11-20. Reading through these criteria, you’ll notice the requirements that the patient must have had prior EGFR TKI treatment, and only 1 prior treatment plus also be positive for the T790M mutation before acquiring the Osimertinib Itacinib combination therapy. Based on these inclusion criteria, this patient would be a prime candidate for the clinical trial to overcome issues with drug resistance for T790M.
Now that the trial is selected, click on the Report Tab and confirm the sign out clicking on the green icon. Then select New Word Export.
Now, click on the blue +New Report Template icon. Make sure that the Cancer Drugs and Trials Template V2.docx is selected from the Copy System Template dropdown, and give the report template a new name.
Below is an example of a rendered Drugs and Trails report.
Not only can users open the report in Microsoft word, but also convert the report to a pdf and open directly in VarSeq. Page 7 of the report contains the relevant clinical trial information for the Osimertinib and Itacitinib drug combination therapy.
That concludes the VarSeq VSClinical AMP Guidelines workflow tutorial. More information about the VSClinical AMP Guidelines can be found in the following Golden Helix webcasts. The first is an introduction of the AMP Guidelines and the second is an introduction to the Drugs and Trials addition.
This webcast goes through a VSClinical AMP Guidelines workflow similar to the process shown in this tutorial.
A more in depth look into the Oncogenicity Scoring can be found in the following webcast.
And finally for more details of using CancerKB and building up your lab specific interpretation knowledgebase.
Information can be found from our eBook Library. The eBook that focuses on the AMP Guidelines is Clinical Variant Analysis for Cancer.
If you are interested in getting a demo license to try out additional features that require an active license, such as creating a project, adding annotation sources, and saving project, please request a demo from Golden Helix.
This tutorial was designed to give a taste of all the features and capabilities of VarSeq and a brief orientation to key features. For any additional assistance, please contact our support team (firstname.lastname@example.org).
If you are interested in getting a demo license to try out additional features that require an active license, such as creating a project, adding annotation sources, and saving project, please request a demo from: Discover VarSeq
If you have an active license, we encourage you to try out the intermediate tutorial on Cancer Gene Panels: Cancer Gene Panel Tutorial.
Additional features and capabilities are being added all the time, so if you do not see a feature you need for your workflows please do not hesitate to let us know!