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Some Actionable Biomarkers Can Be Detected in Multiple Types of Tumors

Learn more about select biomarkers

Detecting NTRK gene fusions

NTRK gene fusions can be detected with various testing methods1,2

Next-generation sequencing (NGS)

  • Multigene parallel sequencing assay1
  • Provides information about multiple biomarkers, including rare and common mutations, and can typically use less tissue1,3
  • Can detect fusions in all 3 NTRK genes, as well as other genetic alterations2
  • Can detect NTRK fusion partner and position2
  • Turnaround time for results may be longer than with IHC or FISH4

Immunohistochemistry (IHC)

  • Uses specific antibodies to detect overexpression of the TRK fusion protein1
  • Can be used to screen patients for NTRK gene fusions, if included in panels1
  • Requires dedicated tissue and limits multiplexing3,5
  • Only detects the NTRK component of the fusion protein; molecular confirmation is necessary1

Fluorescence in situ hybridization (FISH)

  • Uses “break-apart” probes to show NTRK gene rearrangement1
  • Requires dedicated tissue3,6
  • Delivers rapid results4
  • Cannot distinguish fusion variants4
  • May be labor intensive, possibly more expensive for multiple assays1

TRK=tropomyosin receptor kinase; NTRK=neurotrophic tyrosine receptor kinase.

Microsatellite instability (MSI) is an established biomarker in colorectal cancer, and an emerging biomarker for several other cancer types7-9

MSI can increase the risk of developing certain cancers10

  • Microsatellites are tandem repeats of nucleotides, usually a dinucleotide repeat of cytosine and adenine, which are prone to errors during DNA replication10-12
  • MSI is a hypermutable phenotype caused by the loss of DNA mismatch repair activity, usually caused by gene mutations10,12
  • MSI is detected in ≈15% of all colorectal cancers10,13

Polymerase chain reaction (PCR) and next-generation sequencing (NGS) can test for MSI7

Tumors that undergo MSI testing can be classified as7:

Chart comparing MSI-L and MSS

For colon cancer, NCCN Guidelines® consider IHC for mismatch repair (MMR) and DNA analysis for MSI to be different assays measuring different biological effects caused by deficient MMR function.8

PCR-based MSI testing can be conducted in combination with MMR IHC13

  • DNA from tumor samples can be tested for microsatellite instability using a panel consisting of mono- and di-nucleotide markers recommended by Bethesda/National Cancer Institute (BAT-25, BAT-26, D2S123, D5S346, D17S250)7,12
  • However, other markers are in use (eg, BAT-40, MONO-27, NR-21, NR-24)7,12,14

NGS-based MSI testing enables massive parallel sequencing of MMR genes8

  • The development of NGS enables more in-depth sequencing; however, it can potentially lead to identification of variants of unknown significance7
    • Mutations with unknown clinical significance may be detected that were at levels too low to identify with other methods7

Many different tumor types can be MSI-H, but prevalence is low12

Investigators identified over 386,000 microsatellite repeats in a recent study retrospectively analyzing 7,919 exomes and 1,000 whole genomes from The Cancer Genome Atlas (TCGA)12

  • The goal of the study was to develop a profile of MSI mutation patterns across tumor types and understand the affected pathways as well as how they correlate with epigenomic features12
  • Tumor-type specificity of frameshift MSI is evident for some well-known targets of MSI, such as ACVR2A (52% of MSI-H tumors) and TGFBR2 (44%) (enriched in both colon adenocarcinoma and stomach adenocarcinoma; P<0.05, one-tailed Fisher’s exact test) as well as RPL22 (31%), RNF43 (31%), MLL3 (27%), PRDM2 (21%), JAK1 (16%), and APC (3%)12

The graph shows the frequency of MSI-H samples from the 16 most prevalent tumor types in the dataset.

Prevalence of MSI-H tumors seen in a retrospective analysis of 7,919 matched tumor and somatic tissue pairs from the Cancer Genome Atlas12*

MSI-H tumors

*MSI-H predicted at a confidence level of 0.75.12
IHC=immunohistochemistry; MMR=mismatch repair; MSI=microsatellite instability; MSI-H=MSI-high; MSI-L=MSI-low; MSS=microsatellite stable; NCCN=National Comprehensive Cancer Network; NGS=next-generation sequencing; PCR=polymerase chain reaction.

Tumor mutational burden (TMB) is an investigational biomarker for response to cancer immunotherapy15,16

TMB can be detected in solid tumors or blood by next-generation sequencing (NGS).16-19

TMB has been determined using both broad and targeted panels and detected by mutational load in cfDNA samples and liquid biopsies.17-20

TMB is the total number of mutations per coding area of a tumor genome15

Tumor genome

TMB=tumor mutational burden.

The relationship between MSI and TMB is still being evaluated15

The relationship between TMB and microsatellite instability (MSI), both markers of genetic instability, was evaluated for 62,150 tumor samples.15

  • A majority of tumors with microsatellite high (MSI-H) also showed high TMB (>20 mutations/Mb, 83%)15
  • Only 16% of tumors that showed high TMB were also MSI-H15
  • The co-occurrence of high TMB and MSI-H was dependent on the tumor type15

TMB levels vary across tumor type12,15

  • The figure shows whole genome sequencing results from 27 tumor types from 3,083 paired tumor and normal tissue samples21
  • Mutation frequency can vary across cancer types, as well as across patients within a cancer type21
    • Pediatric and hematologic malignancies have the lowest frequencies, while tumors driven by environmental factors have higher mutation burdens21

Identification of mutational burden in 27 tumor types using whole genome sequencing21

Chart of identification of mutation burden in 27 tumor types using whole genome sequencing

Mb=megabases.
Republished with permission of Nature Publishing Group, from Lawrence MS, et al. Nature. 2013;499(7457):214-218; permission conveyed through Copyright Clearance Center, Inc.

Tumors with high TMB may potentially be more immunogenic15,16,22

High levels of somatic mutations within tumor cells may result in expression of neoantigens that can induce a T cell response.23

Increased mutation burden may be associated with a higher number of antigens, which may result in greater tumor immunogenicity.9,12,23,24

Ongoing research is being conducted to evaluate TMB as a predictive biomarker for immunotherapy24

The biologic rationale behind TMB’s potential as a biomarker is that tumors with high TMB are likely to accumulate neoantigens, making the tumors susceptible to activated immune cells.9,24

cfDNA=circulating free DNA; NGS=next-generation sequencing; TMB=tumor mutational burden.

    • Murphy DA, et al. Detecting gene rearrangements in patient populations through a 2-step diagnostic test comprised of rapid IHC enrichment followed by sensitive next-generation sequencing. Appl Immunohistochem Mol Morphol. 2017;25(7):513-523.

      Murphy DA, et al. Detecting gene rearrangements in patient populations through a 2-step diagnostic test comprised of rapid IHC enrichment followed by sensitive next-generation sequencing. Appl Immunohistochem Mol Morphol. 2017;25(7):513-523.

    • Vaishnavi A, Le AT, Doebele RC. TRKing down an old oncogene in a new era of targeted therapy. Cancer Discov. 2015;5(1):25-34.

      Vaishnavi A, Le AT, Doebele RC. TRKing down an old oncogene in a new era of targeted therapy. Cancer Discov. 2015;5(1):25-34.

    • Su D, et al. High performance of targeted next generation sequencing on variance detection in clinical tumor specimens in comparison with current conventional methods. J Exp Clin Cancer Res. 2017;36(1):121.

      Su D, et al. High performance of targeted next generation sequencing on variance detection in clinical tumor specimens in comparison with current conventional methods. J Exp Clin Cancer Res. 2017;36(1):121.

    • Hechtman JF, et al. Pan-Trk immunohistochemistry is an efficient and reliable screen for the detection of NTRK fusions. Am J Surg Pathol. 2017;41(11):1547-1551.

      Hechtman JF, et al. Pan-Trk immunohistochemistry is an efficient and reliable screen for the detection of NTRK fusions. Am J Surg Pathol. 2017;41(11):1547-1551.

    • Stack EC, Wang C, Roman KA, Hoyt CC. Multiplexed immunohistochemistry, imaging, and quantitation: a review, with an assessment of tyramide signal amplification, multispectral imaging and multiplex analysis. Methods. 2014;70(1):46-58.

      Stack EC, Wang C, Roman KA, Hoyt CC. Multiplexed immunohistochemistry, imaging, and quantitation: a review, with an assessment of tyramide signal amplification, multispectral imaging and multiplex analysis. Methods. 2014;70(1):46-58.

    • Rogers TM, et al. Multiplexed transcriptome analysis to detect ALK, ROS1 and RET rearrangements in lung cancer. Sci Rep. 2017;7:42259.

      Rogers TM, et al. Multiplexed transcriptome analysis to detect ALK, ROS1 and RET rearrangements in lung cancer. Sci Rep. 2017;7:42259.

    • Richman S. Deficient mismatch repair: read all about it. Int J Oncol. 2015;47(4):1189-1202.

      Richman S. Deficient mismatch repair: read all about it. Int J Oncol. 2015;47(4):1189-1202.

    • Referenced from the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) for Colon Cancer V.4.2020. © National Comprehensive Cancer Network, Inc 2020. All rights reserved. Accessed June 15, 2020. To view the most recent and complete version of the guideline, go online to NCCN.org. NCCN makes no warranties of any kind whatsoever regarding their content, use or application and disclaims any responsibility for their application or use in any way.

      Referenced from the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) for Colon Cancer V.4.2020. © National Comprehensive Cancer Network, Inc 2020. All rights reserved. Accessed June 15, 2020. To view the most recent and complete version of the guideline, go online to NCCN.org. NCCN makes no warranties of any kind whatsoever regarding their content, use or application and disclaims any responsibility for their application or use in any way.

    • Le DT, et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med. 2015;372(26):2509-2520.

      Le DT, et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med. 2015;372(26):2509-2520.

    • Peltomäki P. Update on Lynch syndrome genomics. Fam Cancer. 2016;15(3):385-393.

      Peltomäki P. Update on Lynch syndrome genomics. Fam Cancer. 2016;15(3):385-393.

    • Vilar E, et al. Microsatellite instability in colorectal cancer—the stable Evidence. Nat Rev Clin Oncol. 2010;7(3):153–162.

      Vilar E, et al. Microsatellite instability in colorectal cancer—the stable Evidence. Nat Rev Clin Oncol. 2010;7(3):153–162.

    • Cortes-Ciriano I, et al. A molecular portrait of microsatellite instability across multiple cancers. Nat Commun. 2017;8:15180.

      Cortes-Ciriano I, et al. A molecular portrait of microsatellite instability across multiple cancers. Nat Commun. 2017;8:15180.

    • Boyle TA, Bridge JA, Sabatini LM, et al. Summary of microsatellite instability test results from laboratories participating in proficiency surveys: proficiency survey results from 2005 to 2012. Arch Pathol Lab Med. 2014;138(3):363-370.

      Boyle TA, Bridge JA, Sabatini LM, et al. Summary of microsatellite instability test results from laboratories participating in proficiency surveys: proficiency survey results from 2005 to 2012. Arch Pathol Lab Med. 2014;138(3):363-370.

    • US Food and Drug Administration. https://www.accessdata.fda.gov/cdrh_docs/pdf17/P170019C.pdf. Accessed December 12, 2019.

      US Food and Drug Administration. https://www.accessdata.fda.gov/cdrh_docs/pdf17/P170019C.pdf. Accessed December 12, 2019.

    • Chalmers ZR, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9(1):34.

      Chalmers ZR, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9(1):34.

    • Tran E, et al. ‘Final common pathway’ of human cancer immunotherapy: targeting random somatic mutations. Nat Immunol. 2017;18(3):255-262.

      Tran E, et al. ‘Final common pathway’ of human cancer immunotherapy: targeting random somatic mutations. Nat Immunol. 2017;18(3):255-262.

    • Roszik J, et al. Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set. BMC Med. 2016;14(1):168.

      Roszik J, et al. Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set. BMC Med. 2016;14(1):168.

    • Clinical implications of circulating tumor DNA tumor mutational burden (ctDNA TMB) in non-small cell lung cancer. Oncologist. 2019;24(6):820-828.

      Clinical implications of circulating tumor DNA tumor mutational burden (ctDNA TMB) in non-small cell lung cancer. Oncologist. 2019;24(6):820-828.

    • Tumor mutational burden (TMB) in plasma from mCRPC patients using two commercial NGS assays. Sci Rep. 2019:14;9(1):114. doi: 10.1038/s41598-018-37128-y.

      Tumor mutational burden (TMB) in plasma from mCRPC patients using two commercial NGS assays. Sci Rep. 2019:14;9(1):114. doi: 10.1038/s41598-018-37128-y.

    • Koeppel F, et al. Whole exome sequencing for determination of tumor mutation load in liquid biopsy from advanced cancer patients. PLoS One. 2017;12:e0188174.

      Koeppel F, et al. Whole exome sequencing for determination of tumor mutation load in liquid biopsy from advanced cancer patients. PLoS One. 2017;12:e0188174.

    • Lawrence MS, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499(7457):214-218.

      Lawrence MS, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499(7457):214-218.

    • Rizvi NA, et al. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science. 2015;348(6230):124-128.

      Rizvi NA, et al. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science. 2015;348(6230):124-128.

    • Kim JM, Chen DS. Immune escape to PD-L1/PD-1 blockade: seven steps to success (or failure). Ann Oncol. 2016;27(8):1492-1504.

      Kim JM, Chen DS. Immune escape to PD-L1/PD-1 blockade: seven steps to success (or failure). Ann Oncol. 2016;27(8):1492-1504.

    • Goodman AM, et al. Tumor mutational burden as an independent predictor of response to immunotherapy in diverse cancers. Mol Cancer Ther. 2017;16(11):2598-2608.

      Goodman AM, et al. Tumor mutational burden as an independent predictor of response to immunotherapy in diverse cancers. Mol Cancer Ther. 2017;16(11):2598-2608.

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