119 genes tested include ABL1, AFF3, AKT1, AKT2, AKT3, ALK*, APC, AR, ATM, ATRX, BAP1, BCL2L1, BRAF, BRCA1, BRCA2, BRIP1, CCND1, CDH1, CDK12, CDK6, CDKN1A, CDKN1B, CDKN2A, CHEK2, CREBBP, CSF1R, CTNNB1, DAXX, DDR2, EGFR, ERBB2, ERBB3, ERBB4, ERCC2, ESR1, ESR2, FANCA, FAT1, FGFR1, FGFR2*, FGFR3*, FGFR4, FLT1, FLT3, FLT4, FOXL2, GATA4, GNAS, H3F3A, HIST1H3B, HRAS, IDH1, IDH2, JAK1, JAK2, KDM5C, KDR, KEAP1, KIT, KLF4, KMT2C, KMT2D, KRAS, MAP2K1, MAP2K2, MAP3K3, MCL1, MED12, MET, MLH1, MN1, MTOR, MYB, MYBL1, MYC, NF1, NF2, NFE2L2, NOTCH1, NOTCH2, NRAS, NTRK1*, NTRK2, PALB2, PBRM1, PDGFRA, PDGFRB, PIK3C2B, PIK3CA, PIK3R1, PIK3R2, PPARG, PPP2R1A, PTEN, RAD54B, RAF1, RB1, RET*, RIT1,ROS1*, RXRA, SETD2, SHOC2, SMAD2, SMAD4, SMARCA4, SMARCB1, SOS1, SPRED1, STK11, TEK, TERT, TGFBR2, TP53, TRAF7, TSC1, TSC2, VHL and WT1 (*rearrangements also detected).
Genomics and Pathology Services (GPS) offers somatic variant analysis by next-generation sequencing for a variety of solid tumors and hematopoietic disorders.
Results provide physicians with useful information for cancer diagnosis, prognosis (disease stratification) and treatment selection.
Testing updates – effective February 14th, 2017
In addition to our Solid Tumors (119 genes) and Hematopoietic Disorders (54 genes) Gene Sets, we offer testing based on cancer type. These include:
- Breast tumors (42 genes)
- CNS tumors (48 genes)
- Genitourinary tumors (44 genes)
- Gynecologic tumors (50 genes)
- Head and neck tumors (41 genes)
- Melanoma (38 genes)
- Thoracic tumors (36 genes)
Download the complete list of genes tested.
Indications for Testing
For solid tumors indications for testing include cancer cases in early stage disease where a mutational profile from multiple genes informs diagnosis or disease stratification, prognosis, or treatment options. For late stage cancers, the test is designed to evaluate options for alternative treatments, including targeted therapies.
For hematopoietic disorders indications for testing include myelodysplastic and suspected neoplastic disease where a mutational profile from multiple genes informs diagnosis or disease stratification, prognosis, or treatment options. For leukemias, the test is designed to evaluate options for therapies targeting signaling pathways and DNA methylation.
54 genes tested include ABL1, ASXL1, ATM, BCOR, BIRC3, BRAF, CALR, CBL, CEBPA, CREBBP, CSF1R, CSF3R, DNMT3A, EP300, ETV6, EZH2, FBXW7, FGFR4, FLT3, GATA1, GATA2, GATA3, IDH1, IDH2, IL7R, JAK2, JAK3, KDM6A, KIT, KRAS, KMT2A*, MPL, NF1, NOTCH1, NOTCH2, NPM1, NRAS, NSD1, PAX5, PDGFRA, PDGFRB, PTPN11, RUNX1, SETBP1, SF3B1, SRSF2, STAG2, TERT, TET1, TET2, TP53, TSLP, U2AF1 and ZRSR2 (*rearrangements also detected).
42 genes tested include AKT1, ATM, BRAF, BRCA1, BRCA2, BRIP1, CDH1, CDK4, CDK6, CDKN2A, CHEK2, EGFR, ERBB2, ERBB3, ERBB4, ESR1, ESR2, FANCA, FBXW7, FGFR1, FGFR2*, GATA3, HRAS, IDH1, IDH2, KDR, KIT, KRAS, MAP2K1, MAP2K2, MET, PALB2, PIK3CA, PIK3R1, PTEN, RAC1, RAD54B, RB1, RET*, RUNX1, STK11 and TP53 (*rearrangements also detected).
48 genes tested include AKT1, ATRX, BRAF, CDKN2A, CIC, CTNNB1, DAXX, DNMT3A, EGFR, ERBB2, FGFR1, FGFR2*, FUBP1, H3F3A, HIST1H3B, IDH1, IDH2, KLF4, KRAS, MED12, MET, MN1, MTOR, MYB, MYBL1, MYC, NF1, NF2, NOTCH1, NTRK1*, NTRK2, PDGFRA, PIK3CA, PIK3R1, PTCH1, PTEN, RB1, SETD2, SHH, SMARCA4, SMARCB1, SMO, SUFU, TERT, TP53, TRAF7, WNT1 and WT1 (*rearrangements also detected).
44 genes tested include AKT1, AKT2, AKT3, AR, ATM, BAP1, BRAF, BRCA1, BRCA2, CDKN1A, CDKN2A, CREBBP, EGFR, ERBB2, ERBB3, ERCC2, FBXW7, FGFR2*, FGFR3*, HRAS, KDM5C, KDM6A, KMT2C, KMT2D, MED12, MET, MLH1, MTOR, NF1, NRAS, PBRM1, PIK3CA, PIK3R1, PPARG, PTCH1, PTEN, RXRA, SETD2, STAG2, TERT, TP53, TSC1, TSC2 and VHL (*rearrangements also detected).
50 genes tested include ABL1, AKT1, AKT2, AKT3, APC, ATM, BCOR, BRAF, BRCA1, BRCA2, CCND1, CDK12, CDKN2A, CTNNB1, EGFR, EP300, ERBB2, ERBB4, FAT1, FBXW7, FGFR1, FGFR2*, FGFR3*, FOXL2, HRAS, JAK3, KDR, KIT, KRAS, MAP2K1, MAP2K2, MED12, MET, MLH1, MTOR, NF1, NRAS, PIK3CA, PIK3R1, PIK3R2, POLD1, POLE, PPP2R1A, PTEN, RB1, SMAD4, SMO, STK11, TP53 and VHL (*rearrangements also detected).
Head & Neck Tumors
41 genes tested include AFF3, AKT1, AKT2, AKT3, APC, ASXL1, ATM, BCL2L1, BRCA1, BRCA2, CCND1, CDKN2A, EGFR, EP300, ERBB2, FAT1, FBXW7, GATA4, HRAS, KDM6A, KMT2C, KMT2D, KRAS, MCL1, MTOR, NF1, NFE2L2, NOTCH1, NOTCH2, NRAS, NSD1, PIK3C2B, PIK3CA, PIK3R1, PTEN, RAC1, RB1, RHOA, SMAD4, TGFBR2 and TP53.
38 genes tested include AKT1, ALK*, BAP1, BRAF, CCND1, CDK4, CDKN2A, CTNNB1, EGFR, ERBB2, ERBB4, FGFR1, FGFR2*, FGFR3*, GNA11, GNAQ, HRAS, KIT, KMT2C, KMT2D, KRAS, MAP2K1, MAP2K2, MED12, MET, MTOR, NF1, NRAS, PDGFRA, PDGFRB, PIK3CA, PTEN, RAC1, RB1, RET*, ROS1*, TERT and TP53 (*rearrangements also detected).
36 genes tested include AKT1, AKT2, AKT3, ALK*, ATM, BAP1, BRAF, CDKN1B, CDKN2A, DDR2, ERBB2, ERBB3, FANCA, FGFR1, FLT1, FLT4, HRAS, KDR, KEAP1, KMT2C, KMT2D, KRAS, MED12, MET, NF1, NRAS, NTRK1*, RB1, RET*, RIT1, ROS1*, SMARCA4, STK11, TP53, TSC1 and TSC2 (*rearrangements also detected).
Tests are performed using targeted hybridization capture of tumor-derived genomic DNA coupled with next-generation sequencing (NGS). This approach enables deep, comprehensive coverage of all coding exons and key introns of ordered genes, and allows assessment of the molecular complexity of each DNA specimen, minimizing sampling bias even in cases of low DNA mass or quality.
Types of variation detected include single nucleotide variants (SNVs), small insertions and deletions (indels), selected larger indels, and structural rearrangements involving selected genes.
For solid tumors, this test is routinely performed using formalin fixed paraffin embedded (FFPE) tissues and is able to detect SNVs under 10% allelic fraction in the sequenced tissue.
Results and Interpretation
DNA sequence data are analyzed by GPS’ clinically validated bioinformatics pipeline to identify and annotate somatic variants associated with cancer.
Identified tumor mutations are interpreted by a board-certified clinical genomicist in the context of the patient’s disease and other clinical findings, highlighting mutations associated with specific treatment options based on evidence from the medical literature.
Results are returned to the ordering physician in a concise clinical report.
The turnaround time for testing and interpretation is three weeks from the time the specimen is acquired.
Specimen types accepted include excisional biopsies, core needle biopsies, cell blocks, leukemic blood or bone marrow aspirate.
Acceptable materials for submission include tumor-containing formalin fixed paraffin embedded (FFPE) blocks, unstained slides from tumor-containing FFPE block, or blood/bone marrow in a lavender-top EDTA tube.
Tissue fixation protocols must be compatible with molecular testing; EDTA decalcification is acceptable, acid decalcification is not.
Kits for testing on hematopoietic samples are available upon request.
Genetic testing in oncology provides information useful for diagnosis, prognosis (disease stratification), and treatment selection. Indeed, a single mutation may impact all of these areas.
The vast majority of this clinically relevant information applies to the effects of isolated mutations, and the current challenge is to understand how recurrent isolated mutations behave in different combinations.
A much greater challenge is to discover important cryptic oncogenic mutations and to learn how they interact with other non-oncogenic alleles and polymorphisms that modify the cancer phenotype.
There are long-standing examples of somatic mutations or rearrangements that are considered diagnostic for a particular solid tumor; translocations involving the EWSR1 locus on ch. 22 in Ewing’s sarcoma, or the presence of the BRAF V600E mutation in a suspected papillary thyroid carcinoma.
Today, the presence of recurrent somatic mutations in combinations affords the possibility of detailed molecular fingerprinting that can identify important diagnostic subtypes.
Mutations in TP53 and KRAS are common in lung adenocarcinoma compared to squamous carcinoma, particularly in smokers, the presence of a BRAF mutation in colorectal tumor showing high microsatellite instability suggests the tumor is sporadic, and not a case of hereditary non-polyposis colorectal cancer (Lynch syndrome).
Mutational profiles are important in disease stratification. For example, activating mutations in KRAS impart a poor prognosis in adenocarcinomas of the lung, colon and pancreas, independent from their effect on targeted therapies such as the anti-EGFR monoclonal antibodies cetuximab and panitumumab.
Sometimes the prognostic effect is dependent on the cancer; loss-of-function mutations in PTEN impart a poor prognosis in breast cancer and oligodendroglioma, but are associated with a better prognosis in endometrial cancers, where mutations in PIK3CA are associated with advanced and invasive disease.
There are now dozens of somatic mutations that have been identified primarily in carcinomas that indicate whether the tumor will be susceptible or resistant to anti-cancer therapy.
In addition, so-called ‘pharmacogenomic’ alleles in germ line DNA also contribute to therapeutic responses.
Activating mutations in kinase genes such as EGFR, KIT, BRAF, and MET, or translocations that lead to overexpression of kinases such as ABL1 and ALK, often result in susceptibility of the tumor cells to small molecule inhibitors that are selective for the affected kinase.
For example, in lung adenocarcinoma, afatinib and erlotininb potently inhibit mutated EGFR, and in gastrointestinal stromal tumors, imatinib and sunitinib inhibit the frequently mutated KIT kinase in this tumor. Crizotinib targets the ALK kinase in lung cancers that harbor the EML4-ALK rearrangement (an inversion on ch. 2p).
Many of these kinase inhibitors exhibit activity against multiple kinases; imatinib was initially developed for its potent inhibition of ABL1 that is overexpressed in leukemias with the canonical t(9;22), resulting in the BCR-ABL1 gene fusion.
Unfortunately, treatment with these targeted agents often leads to acquired resistance as the result of selection for additional somatic mutations, such as the T790M missense mutation of EGFR.
As the number of informative variants in recurrently mutated genes grows, NGS testing becomes a more powerful technology to manage patients with cancer.