| Literature DB >> 28219002 |
Hye Seung Lee1,2, Woo Ho Kim2, Yoonjin Kwak1,2, Jiwon Koh2, Jeong Mo Bae3, Kyoung-Mee Kim4, Mee Soo Chang2,3, Hye Seung Han5, Joon Mee Kim6, Hwal Woong Kim7, Hee Kyung Chang8, Young Hee Choi9, Ji Y Park10, Mi Jin Gu11, Min Jin Lhee12, Jung Yeon Kim13, Hee Sung Kim14, Mee-Yon Cho15.
Abstract
With recent advances in molecular diagnostic methods and targeted cancer therapies, several molecular tests have been recommended for gastric cancer (GC) and colorectal cancer (CRC). Microsatellite instability analysis of gastrointestinal cancers is performed to screen for Lynch syndrome, predict favorable prognosis, and screen patients for immunotherapy. The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor has been approved in metastatic CRCs with wildtype RAS (KRAS and NRAS exon 2-4). A BRAF mutation is required for predicting poor prognosis. Additionally, amplification of human epidermal growth factor receptor 2 (HER2) and MET is also associated with resistance to EGFR inhibitor in metastatic CRC patients. The BRAF V600E mutation is found in sporadic microsatellite unstable CRCs, and thus is helpful for ruling out Lynch syndrome. In addition, the KRAS mutation is a prognostic biomarker and the PIK3CA mutation is a molecular biomarker predicting response to phosphoinositide 3-kinase/AKT/mammalian target of rapamycin inhibitors and response to aspirin therapy in CRC patients. Additionally, HER2 testing should be performed in all recurrent or metastatic GCs. If the results of HER2 immunohistochemistry are equivocal, HER2 silver or fluorescence in situ hybridization testing are essential for confirmative determination of HER2 status. Epstein-Barr virus-positive GCs have distinct characteristics, including heavy lymphoid stroma, hypermethylation phenotype, and high expression of immune modulators. Recent advances in next-generation sequencing technologies enable us to examine various genetic alterations using a single test. Pathologists play a crucial role in ensuring reliable molecular testing and they should also take an integral role between molecular laboratories and clinicians.Entities:
Keywords: Colorectal neoplasms; Gastric neoplasms; Molecular diagnosis; Prognosis; Targeted therapy
Year: 2017 PMID: 28219002 PMCID: PMC5357760 DOI: 10.4132/jptm.2017.01.24
Source DB: PubMed Journal: J Pathol Transl Med ISSN: 2383-7837
Fig. 1.Fragment pattern of microsatellite instability–high case by GeneScan analysis.
Fig. 2.Epidermal growth factor receptor (EGFR)–related signaling pathway in metastatic colorectal cancer. Anti-EGFR antibodies are able to block downstream signal of EGFR in wild type RAS and RAF (left), but unable to block in mutant RAS or RAF (right). mTOR, mammalian target of rapamycin; MAPK, mitogen-activated protein kinase.
Fig. 3.Algorithm of molecular testing in colorectal cancer (CRC) patients. MSI, microsatellite instability; IHC, immunohistochemistry; MSI-H, microsatellite instability–high; MSS, microsatellite stable.
Comparison among various detection methods for gene mutation analysis
| Sanger sequencing | Pyrosequencing | Real-time PCR | PNA-clamp assay | Next generation sequencing | |
|---|---|---|---|---|---|
| Advantage | Gold standard | More rapid and sensitive than Sanger sequencing | Simple and fast | Simple and fast | High-throughput |
| Instrument | Ubiquitous | Not ubiquitous | Depending on kit | Ubiquitous | Costly equipment |
| Sensitivity (%) | 10–20 | 5 | 1 | 0.1 | 1 |
| Method | Labor-intensive, time-consuming | Convenient, closed system | Closed system, one-step process | Closed system, one-step process | Time-consuming |
| Mutant allele quantity (%) | Unmeasurable | Measurable | Unmeasurable | Unmeasurable | Measurable |
| Detect all or new mutation | Yes | No | No | No | Yes |
| Detect specific mutation | Yes | Yes | No | No | Yes |
| Data interpretation | Subjective | Less subjective, but complex | Simple and easy | Simple and easy | Complicated (need statistics) |
PCR, polymerase chain reaction; PNA, peptide nucleic acid.
Fig. 4.Recommended gastric human epidermal growth factor receptor 2 (HER2) testing algorithm. IHC, immunohistochemistry.
Recurrent somatic genetic alteration in gastric cancer analyzed using next-generation sequencing
| Gene | Classification | Core pathway | Process | Mutational rate (%) | Reference | ||
|---|---|---|---|---|---|---|---|
| Previous study | Hypermutated tumor[ | Nonhypermutated tumor[ | |||||
| TSG | Cell cycle/apoptosis, DNA damage control | Cell survival | 14–59 | 35 | 50 | 27,116–118,123–127 | |
| Oncogene | PI3K-AKT | Cell survival | 7–36 | 40 | 12 | 27,116–118,123–127 | |
| TSG | APC | Cell fate | 4–36 | - | 11 | 27,116–118,124–126 | |
| TSG | Chromatin modification | Cell fate | 8–27 | 44 | 14 | 27,116,118,123–126 | |
| TSG | PI3K-AKT | Cell survival | 0–27 | 13 | - | 27,116,123,125,127 | |
| Oncogene | RAS/RAF | Cell survival | 0–27 | 19 | 6 | 27,116,118,125,127 | |
| Oncogene | RHO/ROCK | Cell survival | 0–23 | - | 6 | 27,116,118 | |
| TSG | APC | Cell fate | 3–14 | - | 7 | 27,116,118,123,124 | |
| Oncogene | RTK | Cell survival | 0–10 | 25 | - | 27,116 | |
| Oncogene | RTK | Cell survival | 2–9 | - | 3 | 27,116,118,126,127 | |
| Oncogene | APC | Cell fate | 2–9 | - | 4 | 27,116,118,124 | |
| Oncogene | RTK | Cell survival | 0–9 | - | 116,127 | ||
| TSG | NOTCH | Cell fate | 2–6 | 24 | - | 27,118,127 | |
| TSG | TGF-β | Cell survival | 4–6 | - | 8 | 27,118 | |
| Oncogene | RTK | Cell survival | 0–6 | - | - | 27,116,127 | |
| Oncogene | RAS/RAF | Cell survival | 0–5 | - | - | 116,125,127 | |
TSG, tumour suppressor gene; PI3K, phosphoinositide 3-kinase; RTK, receptor tyrosine kinase; TGF-β, transforming growth factor β.
Data of mutation rates are from The Cancer Genome Atlas database; [25]
More frequently mutated gene in gastric cancer with microsatellite instability–high frequency feature or Epstein-Barr virus positivity;
More frequently mutated gene in gastric cancer with diffuse type of Lauren classification.
Recurrent somatic genetic alteration in colorectal cancer analyzed using next-generation sequencing
| Gene | Classification | Core pathway | Process | Mutational rate (%) | Reference | ||
|---|---|---|---|---|---|---|---|
| Previous study | Hypermutated tumor[ | Nonhypermutated tumor[ | |||||
| TSG | Cell cycle/apoptosis, DNA damage control | Cell survival | 27–65 | 20 | 60 | 119–121,128,129 | |
| Oncogene | RAS/RAF | Cell survival | 33–58 | 30 | 43 | 119–121,128–131 | |
| TSG | APC | Cell fate | 40–56 | 51 | 81 | 121,129 | |
| Oncogene | PI3K-AKT | Cell survival | 14–20 | - | 18 | 119,120,128,129,131 | |
| Oncogene | RAS/RAF | Cell survival | 5–14 | 46 | - | 119,120,128–131 | |
| TSG | PI3K-AKT | Cell survival | 2–13 | - | - | 119,128,129 | |
| Oncogene | RTK | Cell survival | 0–11 | - | - | 128,129,131 | |
| TSG | TGF-β | Cell survival | 2–11 | - | 10 | 119,121,128,129 | |
| TSG | NOTCH | Cell fate | 4–10 | - | 11 | 119,120,128,129 | |
| Oncogene | RAS | Cell survival | 2–7 | - | 9 | 119,120,128–131 | |
| Oncogene | RTK | Cell survival | 2–4 | - | - | 119,120 | |
| Oncogene | APC | Cell fate | 1–4 | - | 5 | 121,128,129 | |
| Oncogene | PI3K | Cell survival | 1–4 | - | - | 119,128,129 | |
| Oncogene | RTK | Cell survival | 1–3 | - | - | 128,129 | |
| Oncogene | RTK | Cell survival | 1–2 | - | - | 120,128,129 | |
| Oncogene | RAS/RAF | Cell survival | 0–2 | - | - | 119–121,128 | |
TSG, tumour suppressor gene; PI3K, phosphoinositide 3-kinase; RTK, receptor tyrosine kinase; TGF-β, transforming growth factor β.
Data of mutation rates are from The Cancer Genome Atlas database; [26]
More frequently mutated gene in nonhypermutated colorectal cancer;
More frequently mutated gene in hypermutated colorectal cancer.