|Technical Information||Next-Generation Sequencing|
|Sample Requirements||FFPE block or 10 unstained slides with a minimum of 20% malignant origin for DNA.|
Needle biopsy is also acceptable (4-6 cores).
|Tumor Enrichment (when necessary)||Microdissection to isolate and increase the number of cancer cells to improve test performance|
and increase the chance for successful testing from small tumor samples
|Number of Genes||~22,000 genes|
|Average Depth of Coverage||1,000x for 700+ clinical and research genes; 400-500x for all other genes|
|Positive Percent Agreement (PPA)||> 95% for base substitutions at ≥ 5% mutant allele frequency;|
> 95% for indels at ≥ 5% mutant allele frequency;
>90% for copy number alterations (amplifications ≥ 6 copies)
|Negative Percent Agreement (NPA)||>97%|
|Genomic Signatures||Microsatellite Instability (MSI),|
Tumor Mutational Burden (TMB)
MI FOLFOXai™ – AI predictor of FOLFOX response in metastatic colorectal adenocarcinoma
MI GPS™ Genomic Prevalence Score – CUP, atypical presentation or clinical ambiguity cases
Earlier studies have associated MSI-High status with benefit to immunotherapy in metastatic colorectal cancer. Recent data, however, show that MSI is a useful indicator for predicting response to pembrolizumab in any solid tumor type.1
Traditionally, MSI is detected through polymerase chain reaction (PCR) by fragment analysis (FA) of five conserved satellite regions and comparing cancer tissue to normal tissue to identify differences in tandem repeats. To validate MSI testing via NGS, Caris evaluated more than 7,000 target microsatellite loci and compared the results from PCR for 2,189 cases across 26 different tumor types. This data was published in Cancer Medicine and demonstrated that MSI testing with Caris’ NGS platform is highly concordant with the traditional standard method of PCR-FA and is a more efficient and cost-effective approach to identifying patient candidates for immunotherapy.2
Traditional Approach: normal and cancer tissue required.
Caris Approach: no normal tissue required; saving resources, costs and time.
TMB is a Pan-Tumor Biomarker for IO Response
TMB by Whole Exome Sequencing measures the total number of non-synonymous, somatic mutations identified per megabase
(Mb) of the genome coding area of DNA (a megabase is 1,000,000 DNA basepairs).
TMB has emerged as an important biomarker when considering immunotherapy in solid tumors. This is highlighted by the recent U.S. FDA accelerated approval of pembrolizumab (KEYTRUDA®) for the treatment of adult and pediatric patients with unresectable or metastatic tumor mutational burden-high (TMB-H) [≥10 mutations/megabase (mut/Mb)] solid tumors that have progressed following prior treatment and who have no satisfactory alternative treatment options. This approval is based on the results of the KEYNOTE-158 trial, which achieved an overall response rate of 29% (95% CI: 21, 39), with a 4% complete response rate and 25% partial response rate.5
TMB is included with all Caris Molecular Intelligence orders (MI Profile™ and MI Tumor Seek™) and is performed using Whole Exome Sequencing
Genomic profiling with Caris Molecular Intelligence can help you make more informed therapy decisions when
considering immune checkpoint inhibitors.
In addition, Caris has been working in collaboration with the Friends of Cancer Research TMB Harmonization Project to systematically characterize and standardize TMB testing and reporting to a common industry standard6. Based on this collective work and exciting KEYNOTE-158 result and drug approval, Caris has updated the TMB high/low threshold to reflect greater than or equal to 10 mutations per megabase across all solid tumors, aligning the testing results to pembrolizumab for TMB-H cases.5
1. Snyder A. N Engl J Med. 2014; 371:2189-2199. doi:10.1056/ NEJMoa1406498
2. Le DT. N Engl J Med. 2015;372:2509-2520. doi:10.1056/NEJMoa1500596
3. Rosenberg JE. The Lancet. 2016; 387(10031):1909-1920. doi:10.1016/S0140-6736(16)00561-4.
4. Stewart TJ. Oncogene. 2008;27:5894-5903. doi:10.1038/onc.2008.268
5. U.S. Food and Drug Administration. (2020, June 16). FDA approves pembrolizumab for adults and children with TMB-H solid tumors [Press release].
6. Stenzinger, A, Allen, JD, Maas, J, et al. Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions. Genes Chromosomes Cancer. 2019; 58: 578– 588. https://doi.org/10.1002/gcc.22733
|Technical Information||Whole Transcriptome Sequencing|
|Sample Requirements||FFPE block or 2-5 unstained slides with a minimum of 20% malignant origin. Needle biopsy is also acceptable (4-6 cores).|
|Tumor Enrichment (when necessary)||Microdissection to isolate and increase the number of cancer cells to improve test performance and increase the chance for successful testing from small tumor samples|
|Number of Genes||~22,000 genes|
|Average Read Count||60 million|
|Positive Percent Agreement (PPA)||>97%|
|Negative Percent Agreement (NPA)||>99%|
|Genomic Signatures||MI GPS™ Genomic Prevalence Score – CUP, atypical presentation or clinical ambiguity cases|
|MET Exon 14 Skipping|
MI FOLFOXai™, from Caris Life Sciences®, is an Artificial Intelligence-powered predictor of FOLFOX response that utilizes Caris Molecular Intelligence® tumor profiling results. It is intended to be used as an aid in gauging a patient’s likelihood to benefit from FOLFOX chemotherapy (in combination with bevacizumab) as the first-line chemotherapy regimen in metastatic colorectal adenocarcinoma.
MI FOLFOXai™ is included for all metastatic colorectal adenocarcinoma cases. The MI FOLFOXai™ results appear on the front page of the Caris report as INCREASED BENEFIT or DECREASED BENEFIT – with additional detail provided about the results on page two of the report. This information provides additional insight for patient response to FOLFOX as a first-line therapeutic option.
MI FOLFOXai™ was validated using two independent data sets:
Patients predicted to have increased benefit to FOLFOX may achieve optimal results by receiving a FOLFOX regimen first in their chemotherapy sequencing plan. Patients predicted to have decreased benefit to FOLFOX may achieve results by receiving an alternate regimen, such as FOLFOXIRI or FOLFIRI, prior to the administration of a FOLFOX regimen.
Decisions on patient care and treatment must be based on the independent medical judgment of the treating physician, taking into consideration all available information concerning the patient’s condition.
Caris has one of the largest and most comprehensive databases of combined molecular and clinical outcomes data in the world, and we are actively employing advanced machine learning capabilities with the database to identify unique molecular signatures. These molecular signatures can be used to better identify cancer subtypes and predict patient response to certain therapies. We are pleased to introduce a tool to help manage cancer of unknown primary (CUP) or cases identified by the ordering physician with atypical clinical presentation or clinical ambiguity.
MI GPSai™ provides a cancer type similarity assessment that compares the genomic (DNA) and transcriptomic (RNA) characteristics of the patient’s tumor against other tumors in the Caris database (e.g. lung cancer tumor submitted for testing has a similar molecular signature as the lung cancers found in the Caris Database, or conversely the molecular signature is not similar to lung cancer, but similar to another tumor type’s molecular signature).
MI GPS ai™ can be added to any solid tumor order by selecting the appropriate box on the tumor profiling requisition. The result is presented as a prevalence score in a convenient tabular format and is populated onto the final Caris report. These results will provide additional insight by assessing how closely tumors match the genomic and transcriptomic signatures of tissue types to help you make more informed treatment decisions.
Caris Molecular Artificial Intelligence (MAI™) uses the power of DEAN (Deliberation Analytics) and machine learning technology to provide oncologists with the most thorough genomic and transcriptomic classifications to inform decision making. Caris MAI™ analyzes historical clinical and outcome data and learns from the past to provide for a better future via molecular subtyping.