Amplification of the human epidermal growth factor receptor 2 (HER2) gene is associated with a microsatellite stable status in Chinese gastric cancer patients

Introduction

Gastric cancer (GC) is one of the most common cancers worldwide, with the highest rates observed in Europe and Eastern Asia (1). Surgical resection is the primary treatment for GC with good efficacy in patients who are diagnosed early. However, the survival rate of late-stage cancer patients is still extremely low (2,3). To date, a series of next-generation sequencing (NGS) studies, including those from The Cancer Genome Atlas (TCGA), have revealed several genes that are frequently mutated in GC (4,5), facilitating the development of targeted gene therapy to effectively improve the overall survival of GC patients (6,7).

Human epidermal growth factor receptor 2 (HER2), also known as erb-b2 receptor tyrosine kinase 2 (ERBB2), is a human growth factor receptor that regulates cell growth and differentiation (8). High levels of HER2 amplification can induce the overexpression of cell membrane proteins and subsequently, the cells acquire the characteristics of malignant cells (9). Trastuzumab is a drug that targets the HER2 protein to improve the survival rate of patients with primary and metastatic HER2-positive breast cancer (10). Mutations of HER2 often occur in a variety of cancers, such as breast cancer, lung cancer, and GC (11). The positive rate of HER2 in GC increased with age and was positively correlated with the intestinal type (12). HER2 protein expression also associated with tumor differentiation, Lauren classification, Borrmann type, and P53 expression in GC (13). Many reports have shown a poor prognosis for patients with HER2-positive tumors compared to those with HER2-negative tumors (14-16). Unlike breast cancer, the correlation between HER2 and prognosis in GC patients remains controversial. Some studies have shown that HER2-positive tumors are associated with a significantly deteriorating prognosis, while others have shown that HER2 status is not related to prognosis (16-20).

Microsatellite instability (MSI) is a description of genomic instability caused by the inactivation of DNA mismatch repair genes (21). MSI is considered to be a positive prognosis biomarker and high MSI (MSI-H) is associated with a good prognosis in many cancers, especially in colorectal cancer (CRC) (22,23). MSI has also been associated with good prognosis and low lymph node metastasis in GC patients (24,25).

The prognostic predictions of MSI and HER2 amplification are different. HER2 amplification is associated with a poor prognosis, while MSI is associated with a good prognosis. In patients with HER2 positive gastric cancer, the addition of trastuzumab in the first-line chemotherapy can improve the survival rate (26,27). HER2 targeted therapy in gastric cancer was selected as the first-line treatment in HER2 positive patients. MSI is also considered in adjuvant immunotherapy (27). However, little is known regarding the combination of these two indicators in GC. This study identified the mutational profiling of 192 GC cases and analyzed the relationship between HER2 and MSI, and the relationship between HER2 and TMB, and aimed to guide the selection and effectiveness of targeted therapy for gastric cancer patients.

We present the following article in accordance with the MDAR reporting checklist (available at http://dx.doi.org/10.21037/jgo-21-47).

Methods

Patient enrollment and sample collection

All procedures performed in this study involving human participants were in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by institutional ethics committee of The First Hospital of Shanxi Medical University (No.: 2020-K008) and informed consent was taken from all the patients. A total of 192 Chinese GC patients were randomly enrolled in this study. Both formalin-fixed and paraffin-embedded (FFPE) tumor tissues, and matched blood samples were collected from patients for the detection of genomic alterations (GAs) using the NGS-based YuanSuTM450 gene panel (OrigiMed, Shanghai, China). Genomic DNA was isolated using the QIAamp DNA FFPE Tissue Kit and the QIAamp DNA Blood Midi Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. The concentration of DNA was measured by Qubit (Life Technologies) and normalized to 20–50 ng/µL.

Identification of GAs, TMB, and MSI

The genomic profile was produced using the YuanSuTM450 gene panel (Appendix 1), which covers all the coding exons of the 450 cancer-related genes, and 64 selected introns in the 39 genes that are frequently rearranged in solid tumors (28). The genes were captured and sequenced with a mean depth of 800× by using Illumina NextSeq 500 (Illumina, Inc., CA). Single nucleotide variants (SNVs) were identified by MuTect (v1.17). Insertion-deletion polymorphisms (indels) were identified by using PINDEL (V0.2.4). The functional impact of these mutations was annotated by SnpEff3.0. Copy number variation (CNV) regions were identified by Control-FREEC (v9.4) with the following parameters: window =50,000, and steP =10,000. Gene fusions were detected through an in-house pipeline. Gene rearrangements were assessed by Integrative Genomics Viewer (IGV). TMB is a measure of the number of somatic mutations per megabase of genome coding region. With the reference to previous method (29), TMB was estimated by counting the somatic mutations in coding area, including SNVs and indels, per megabase of the sequence examined. MSI status was inferred based on the MANTIS (Microsatellite Analysis for Normal Tumor InStability) score (30), and microsatellite regions were manually reviewed using the Integrated Genomics Viewer (IGV) for confirmation.

Statistical analysis

Statistical analyses were performed using SPSS version 22.0 (SPSS Inc., Chicago, IL, USA). Fisher’s exact test was used to analyze significant differences. P<0.05 was considered statistically significant.

Results

Characteristics of Chinese GC patients

In this cohort, a total of 192 Chinese GC patients, including 130 (67.71%) males and 62 (32.29%) females, were enrolled. The median age was 62 years old (range, 27–86 years old). Samples from 179 (93.23%) original primary tumors and 13 (6.77%) metastatic tumors were collected. The degree of tumor differentiation was identified for 159 samples. There were 30 well or moderately differentiated samples and 129 poorly differentiated or undifferentiated samples (Table 1).

Table 1 Clinicopathologic features of 192 Chinese GC patients
Full table

The mutational landscape and the frequency of high MSI (MSI-H) and HER2 amplification in Chinese GC patients

According to the sequencing results of the tumor samples, 1,670 clinically relevant GAs were identified in 361 genes, with a mean of 8.70 GAs per sample (range, 1–59) (Table S1). Among these alterations, 74.67% (1,247/1,670) were SNV/short indels, 20.36% (340/1,670) were CNVs, 2.22% (37/1,670) were fusion, and 2.75% (46/1,670) were long indel variations (Figure 1). The most frequently mutated genes with mutation frequencies greater than 10% included tumor protein P53 (TP53; 68.23%, 131/192), AT-rich interactive domain-containing protein 1A (ARID1A; 18.75%, 36/192), low-density lipoprotein receptor-related protein 1B (LRP1B; 17.19%, 33/192), ERBB2 (14.58%, 28/192), protocadherin fat 4 (FAT4; 13.54%, 26192), cadherin 1 (CDH1; 12.50%, 24/192), and cyclin E1 (CCNE1; 10.94%, 21/192) (Figure 2). The most frequently amplified genes included CCNE1, HER2, fibroblast growth receptor 2 (FGFR2), cyclin D1 (CCND1), fibroblast growth factor 19 (FGF19), fibroblast growth factor 3 (FGF3), fibroblast growth factor 4 (FGF4), GATA binding protein 4 (GATA4), retinoic acid receptor alpha (RARA), and DNA topoisomerase 2-alpha (TOP2A). For HER2, there were 18 gene amplification mutations and 10 CNVs. The frequency of HER2 amplification was 9.38% (18/192) (Table S1).

Figure 1 Statistical distribution map of variation types. SNV, single nucleotide variant; CNV, copy number variation; LONG, long insertion/deletion; FUS, gene fusion.

Figure 2 Mutational profiling of 192 Chinese gastric cancer patients. The X-axis represents each case sample and the Y-axis represents each mutated gene. The bar graph above shows the gene mutations of each sample, and the bar graph on the right shows the mutation frequency of each mutated gene in this cohort. In between the upper and lower panel, primary tumors are shown in light green, metastatic lesions are depicted in yellow, microsatellite stable (MSS) status is shown in blue, and the high level of microsatellite instability (MSI-H) is shown in red. The lower panel shows the genetic alterations for each sample. Green represents substitution/indel mutations, red represents gene amplification mutations, blue represents gene homozygous deletion mutations, yellow represents fusion/rearrangement mutations, and purple represents truncation mutations.

MSI-H and TMB are important biomarkers and were investigated in this cohort. According to previous studies, TMB values less than 10 were classified as low TMB (TMB-L) and TMB values greater than 10 were classified as high TMB (TMB-H) (31,32). Among the 192 GC patients in this study, 141 showed TMB-L, 50 showed TMB-H, and 1 patient did not have an available TMB value. The median TMB of this cohort was 5.4 Muts/Mb (range, 0–83.7). In addition, MSI was detected in 13 cases (13/192, 6.77%; Table 1). Together with the incidence rate of HER2 amplification, these results were consistent with previously reported incidence rates (33-36).

The association between HER2 amplification, MSI, TMB value, tumor origin, gender, and age of patients

There were 18 HER2-positive cases, including 9 males and 9 females, aged from 37 to 75 years old. Based on statistical analysis, the detection of HER2 amplification in females was higher than in males, but the difference was not statistically significant (14.52% vs. 6.92%, respectively, P=0.091; Figure 3A). Based on the median age, patients were divided into two groups, those aged less than 62 years and those aged 62 years and older. In the HER2 amplification positive cases, there were 7 patients aged less than 62 years, and 11 patients aged 62 years and older. There were no differences in HER2 amplification between the two age groups (Figure 3B).

Figure 3 Correlation analysis of HER2 amplification status and clinical features. (A) The correlation between HER2 amplification status and gender; (B) the correlation between HER2 amplification status and age of the patients; (C) the correlation between HER2 amplification status and tumor origin; (D) the correlation between HER2 amplification status and tumor mutational burden (TMB) value. HER2, human epidermal growth factor receptor 2.

With the exception of 3 patients who presented with metastases, all tumors were primary lesions. TMB-H was found in 2 HER2-positive cases and TMB-L was found in the remaining 16 cases. The detection rate of HER2 amplification in metastatic foci was higher than that in primary lesions (23.08% vs. 8.38%, respectively, P=0.079), and the frequency of HER2 amplification in patients with TMB-H was lower than in patients with TMB-L (4.0% vs. 11.35%, respectively, P=0.13). However, the association between tumor sites and TMB was not statistically significant (Figure 3C,D).

In the 13 patients with MSI, including 10 males and 3 females, aged 43 to 82 years old, the frequency of MSI detection was higher in males than in females, but the difference was not statistically significant (7.69% vs. 4.84%, respectively, P=0.46; Figure 4A). Similarly, MSI status in the different age groups was investigated. MSI status was detected in 5 patients aged less than 62 years, and 8 patients aged 62 years and older. No significant differences were detected in the MSI status between the two age groups (Figure 4B). The frequency of MSI in metastatic foci was higher than that in primary lesions (15.38% vs. 6.15%, respectively, P=0.20), however this was not statistically significant (Figure 4C). Interestingly, except for 1 patient with an unavailable TMB value, all 12 patients with MSI status also harbored TMB-H. Statistical analysis revealed that MSI status was highly associated with TMB-H (20% vs. 0%, respectively, P=3.66×10⁻⁷; Figure 4D).

Figure 4 Correlation analysis of microsatellite instability (MSI) status and clinical features. (A) The correlation between MSI status and gender; (B) the correlation between MSI status and age of patients; (C) the correlation between MSI status and tumor origin; (D) the correlation between MSI status and tumor mutational burden (TMB) value.

HER2 amplification is negatively correlated with microsatellite status in Chinese gastric patients

A total of 18 HER2 positive and 13 MSI cases were found in this study. However, none of the patients were detected as HER2 positive and MSI positive concurrently. Statistical analysis demonstrated that there was no significant correlation between HER2 positive and MSI (0% vs. 7.47%, respectively, P=0.48).

Interestingly, the proportion of HER2 positive samples was higher in females than in males, while the proportion of MSI positive samples was lower in females than in males (Figures 3A,4A). Unexpectedly, no significant differences were detected between HER2 and MSI in female patients (14.52% vs. 4.84%, respectively, P=0.13; Figure 5A).

Figure 5 Negative correlation between HER2 amplification and MSI status. (A) The different proportions of HER2+ and MSI in female patients; (B) the significantly different proportions of HER2+ and MSI in patients with TMB-H. HER2, human epidermal growth factor receptor 2; MSI, microsatellite instability; TMB-H, high tumor mutational burden.

Due to the significant correlation between MSI and TMB-H, we examined the correlation between HER2 and MSI and TMB-H. As expected, the frequency of HER2 positive cases was significantly lower than the frequency of MSI in TMB-H patients (4.0% vs. 20.0%, respectively, P=0.031) (Figure 5B).

Combining the occurrence of HER2 positive and MSI and their correlation with the patient’s gender and TMB value, we concluded that HER2 amplification is negatively correlated with MSI in Chinese GC patients.

Discussion

GC is characterized by a high degree of biological heterogeneity, suggesting that each GC patient has varied genetic and molecular characteristics. With the development of NGS sequencing technology in the past decade, many studies have been focused on the mutational profiling of GC (5,37-40). In Caucasian patients, mutations were most commonly detected in the following genes: TP53, Kirsten rat sarcoma viral oncogene homolog (KRAS), ARID1A, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), ERBB3, phosphatase and tensin homolog (PTEN), and major histocompatibility complex, class I, B (HLA-B) (5). While in Korean GC patients, mutations were most commonly detected in the following genes: TP53, epidermal growth factor receptor (EGFR), hepatocyte nuclear factor 1-alpha (HNF1A), PIK3CA, and ERBB2 (38). Jia et al. showed that the frequency of mutation in the adenomatous polyposis coli (APC), ARID1A, lysine methyltransferase 2A (KMT2A), PIK3CCA, and PTEN genes were significantly different between Asian and Caucasian GC patients (39). For Chinese GC patients, Wang et al. also reported that the most commonly mutated genes in a cohort of patients from Hong Kong were TP53, ARIK1A, CDH1, APC, ras homolog gene family member A (RHOA), PIK3CA, SMAD4, MYC, and KRAS (40). This current study also identified a high frequency of TP53, ARID1A, ERBB2, and CDH1 gene mutations in 192 Chinese GC patients. In addition, high frequencies of LRP1B, FAT4, and CCNE1 mutations were detected, and these have been shown to be important in GC (41-43). To our knowledge, this is the first study to report LRP1B, FAT4, and CCNE1 as some of the most frequently mutated genes in GC. These differences suggested that the distribution of GC GAs may be varied based on region.

HER2 mutations can be used for determining the prognosis of GC patients. In a study of Korean GC patients, it was found that in HER2-positive patients, loss of PTEN expression, and a low HER2 mean amplification index correlated with resistance to trastuzumab-based therapy and extremely poor prognosis (19). Another study found that Lauren classification combined with HER2 status was a good prognostic factor for Chinese GC patients. HER2 negative patients with intestinal type Lauren classification demonstrated the best survival, while patients who were HER2 positive with diffuse type Lauren classification showed poor survival (44). In this study, the frequency of mutated HER2 was 14.58%, including 9.38% HER2 amplification, suggesting that there may be a high proportion of patients with poor prognosis in the Chinese population.

For GC patients with HER2 mutations, there have been many studies investigating drug therapy. In a single-arm phase II study evaluating the efficacy of combining lapatinib with capecitabine and oxaliplatin as first line neoadjuvant therapy in untreated HER2-overexpressing advanced GC patients, it was found that patients with a high level of HER2 amplification were more likely to respond to therapy compared to those with a low level of amplification (45). Yoshioka et al. demonstrated that HER2-amplified cell lines were highly sensitive to the pan-HER inhibitors afatinib and neratinib (46). In a subpopulation analysis of the JACOB trial (NCT01774786), Chinese patients with HER2-positive metastatic GC or gastroesophageal junction cancer showed numerically improved overall survival, progression-free survival, overall objective response rate, and a similar safety profile when pertuzumab was added to the treatment regimen of trastuzumab and chemotherapy compared to patients receiving trastuzumab and chemotherapy alone (47). All these studies suggested that HER2 can be used as a biomarker for adjuvant therapy to improve patient prognosis.

Wang et al. performed a meta-analysis of the clinicopathological factors associated with HER2-positive GC and found that HER2-positive expression was associated with males, intestinal type GC, and well to moderate differentiation (48). This differs from our study in which HER2 amplification was detected more often in females than in males.

MSI is one of the key factors in GC. Contrary to HER2 amplification, studies have shown that MSI is associated with good prognosis. Kohlruss et al. investigated the role of Epstein-Barr virus (EBV) infections, MSI-H, and MSI-L in 760 GC patients in the context of platinum/5-fluorouricil based preoperative chemotherapy (49). Patients with EBV positive tumors showed the best overall survival, followed by patients who were MSI-H. MSI-L tumors were significantly associated with poor overall survival (50). Cristescu and colleagues found that MSI tumors were hyper-mutated intestinal-subtype tumors occurring in the antrum, and resulted in a better overall prognosis compared to the mesenchymal-like type tumors (51). Liu et al. found that 58.3% of their GC cohort were positive for MSI and concluded that the accumulation of MSI in dysplasia and intestinal metaplasia of gastric mucosa may be an early molecular event during gastric carcinogenesis (52). In this study, MSI was detected in 6.77% of GC patients. This result was consistent with previous reports (35,36), suggesting that MSI can also be used as a biomarker for early detection and prognosis GC patients.

A previous study showed that MSI was significantly associated with females, older patients (mean age of 75 years), distal location, and distal non-diffuse modified Lauren classification in GC. In a survival analysis of patients with stage I–III GC, MSI patients showed a significantly lower risk of cancer-related death (53). However, in the current study, there was no statistical correlation between MSI and gender or age.

Studies on the relationship between HER2 amplification and MSI are limited. In a molecular profiling study of metastatic colorectal tumors using NGS technology, 5.1% of the patients had HER2 amplifications. Most of these tumors were microsatellite stable (MSS), with HER2 copy numbers ranging from 9–190 (54). A retrospective study by Moy et al. showed that there was no significant difference in the mean overall survival in patients with and without MSI. In addition, all tumors with MSI were HER2 negative (55). This was similar to the results in our study where all 13 MSI samples were HER2 negative.

TMB is an emerging biomarker for predicting immunotherapy responses (29,56). Tumors with TMB-H often have more neoantigens which are beneficial for immunotherapy. TMB-H has been reported to be associated with better outcomes in many cancers (57). A study by Cai and colleagues found that TMB was significantly associated with HER2 immunohistochemistry status. Higher median TMB values were seen in HER2 positive tumors, but all TMB-H tumors were HER2 negative (58). This was in agreement with our study showing that the frequency of HER2 amplification was lower in TMB-H compared to TMB-L tumors. In addition, this study demonstrated a significant correlation between TMB-H and MSI. Taken together, all these studies suggest that HER2 amplification is negatively correlated with microsatellite status in Chinese GC patients, and MSI and HER2 amplification may be effective biomarkers for predicting prognosis in GC patients.

Conclusions

This study analyzed the genomic features and identified the HER2 amplification and MSI status in Chinese GC patients. The results revealed that the age of patients was not associated with HER2 amplification or MSI status. A high frequency of HER2 amplification was found in female patients and primary lesions, while MSI was detected more frequently in male patients and metastatic foci. MSI status was significantly associated with TMB-H, while HER2 amplification was not correlated with TMB-H. From this data, we concluded that HER2 amplification is negatively correlated with the MSI status in Chinese GC patients.

Acknowledgments

We thank OrigiMed (Shanghai) Co. Ltd for its contribution to the data analysis of this manuscript.

Funding: None.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at http://dx.doi.org/10.21037/jgo-21-47

Data Sharing Statement: Available at http://dx.doi.org/10.21037/jgo-21-47

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/jgo-21-47). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All procedures performed in this study involving human participants were in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by institutional ethics committee of The First Hospital of Shanxi Medical University (No.: 2020-K008) and informed consent was taken from all the patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015;136:E359-86. [Crossref] [PubMed]
2. Cunningham D, Allum WH, Stenning SP, et al. Perioperative chemotherapy versus surgery alone for resectable gastroesophageal cancer. N Engl J Med 2006;355:11-20. [Crossref] [PubMed]
3. Macdonald JS, Smalley SR, Benedetti J, et al. Chemoradiotherapy after surgery compared with surgery alone for adenocarcinoma of the stomach or gastroesophageal junction. N Engl J Med 2001;345:725-30. [Crossref] [PubMed]
4. Nadauld LD, Ford JM. Molecular profiling of gastric cancer: toward personalized cancer medicine. J Clin Oncol 2013;31:838-9. [Crossref] [PubMed]
5. Cancer Genome Atlas Research Network. Comprehensive molecular characterization of gastric adenocarcinoma. Nature 2014;513:202-9. [Crossref] [PubMed]
6. Lee SY, Oh SC. Changing strategies for target therapy in gastric cancer. World J Gastroenterol 2016;22:1179-89. [Crossref] [PubMed]
7. Chen LT, Oh DY, Ryu MH, et al. Anti-angiogenic Therapy in Patients with Advanced Gastric and Gastroesophageal Junction Cancer: A Systematic Review. Cancer Res Treat 2017;49:851-68. [Crossref] [PubMed]
8. Hudziak RM, Lewis GD, Winget M, et al. p185HER2 monoclonal antibody has antiproliferative effects in vitro and sensitizes human breast tumor cells to tumor necrosis factor. Mol Cell Biol 1989;9:1165-72. [Crossref] [PubMed]
9. Slamon DJ, Godolphin W, Jones LA, et al. Studies of the HER-2/neu proto-oncogene in human breast and ovarian cancer. Science 1989;244:707-12. [Crossref] [PubMed]
10. Verma S, Miles D, Gianni L, et al. Trastuzumab emtansine for HER2-positive advanced breast cancer. N Engl J Med 2012;367:1783-91. [Crossref] [PubMed]
11. Hyman DM, Piha-Paul SA, Won H, et al. HER kinase inhibition in patients with HER2- and HER3-mutant cancers. Nature 2018;554:189-94. [Crossref] [PubMed]
12. Xi Y, Xu C, Liu Y, et al. The age variation of HER2 immunohistochemistry positive rate in biopsy specimens of gastric cancer. Pathol Res Pract 2020;216:152882 [Crossref] [PubMed]
13. Chu Y, Li H, Wu D, et al. HER2 protein expression correlates with Lauren classification and P53 in gastric cancer patients. 2020. DOI: https://doi.org/10.21203/rs.3.rs-45602/v1.
14. Shitara K, Yatabe Y, Matsuo K, et al. Prognosis of patients with advanced gastric cancer by HER2 status and trastuzumab treatment. Gastric Cancer 2013;16:261-7. [Crossref] [PubMed]
15. Minner S, Jessen B, Stiedenroth L, et al. Low level HER2 overexpression is associated with rapid tumor cell proliferation and poor prognosis in prostate cancer. Clin Cancer Res 2010;16:1553-60. [Crossref] [PubMed]
16. Jørgensen JT, Hersom M. HER2 as a Prognostic Marker in Gastric Cancer - A Systematic Analysis of Data from the Literature. J Cancer 2012;3:137-44. [Crossref] [PubMed]
17. Dang HZ, Yu Y, Jiao SC. Prognosis of HER2 over-expressing gastric cancer patients with liver metastasis. World J Gastroenterol 2012;18:2402-7. [Crossref] [PubMed]
18. Janjigian YY, Werner D, Pauligk C, et al. Prognosis of metastatic gastric and gastroesophageal junction cancer by HER2 status: a European and USA International collaborative analysis. Ann Oncol 2012;23:2656-62. [Crossref] [PubMed]
19. Kim C, Lee CK, Chon HJ, et al. PTEN loss and level of HER2 amplification is associated with trastuzumab resistance and prognosis in HER2-positive gastric cancer. Oncotarget 2017;8:113494-501. [Crossref] [PubMed]
20. Motoshima S, Yonemoto K, Kamei H, et al. Prognostic implications of HER2 heterogeneity in gastric cancer. Oncotarget 2018;9:9262-72. [Crossref] [PubMed]
21. Yamamoto H, Adachi Y, Taniguchi H, et al. Interrelationship between microsatellite instability and microRNA in gastrointestinal cancer. World J Gastroenterol 2012;18:2745-55. [Crossref] [PubMed]
22. Nakaji Y, Oki E, Nakanishi R, et al. Prognostic value of BRAF V600E mutation and microsatellite instability in Japanese patients with sporadic colorectal cancer. J Cancer Res Clin Oncol 2017;143:151-60. [Crossref] [PubMed]
23. Yamamoto H, Imai K. Microsatellite instability: an update. Arch Toxicol 2015;89:899-921. [Crossref] [PubMed]
24. Smyth EC, Wotherspoon A, Peckitt C, et al. Mismatch Repair Deficiency, Microsatellite Instability, and Survival: An Exploratory Analysis of the Medical Research Council Adjuvant Gastric Infusional Chemotherapy (MAGIC) Trial. JAMA Oncol 2017;3:1197-203. [Crossref] [PubMed]
25. Kim H, An JY, Noh SH, et al. High microsatellite instability predicts good prognosis in intestinal-type gastric cancers. J Gastroenterol Hepatol 2011;26:585-92. [Crossref] [PubMed]
26. Hsu A, Chudasama R, Almhanna K, et al. Targeted therapies for gastroesophageal cancers. Ann Transl Med 2020;8:1104. [Crossref] [PubMed]
27. Patel TH, Cecchini M. Targeted Therapies in Advanced Gastric Cancer. Curr Treat Options Oncol 2020;21:70. [Crossref] [PubMed]
28. Cao J, Chen L, Li H, et al. An Accurate and Comprehensive Clinical Sequencing Assay for Cancer Targeted and Immunotherapies. Oncologist 2019;24:e1294-e1302. [Crossref] [PubMed]
29. Chalmers ZR, Connelly CF, Fabrizio D, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med 2017;9:34. [Crossref] [PubMed]
30. Kautto EA, Bonneville R, Miya J, et al. Performance evaluation for rapid detection of pan-cancer microsatellite instability with MANTIS. Oncotarget 2017;8:7452-63. [Crossref] [PubMed]
31. Yang P, Javle M, Pang F, et al. Somatic genetic aberrations in gallbladder cancer: comparison between Chinese and US patients. Hepatobiliary Surg Nutr 2019;8:604-14. [Crossref] [PubMed]
32. Hu J, Wang Y, Zhang Y, et al. Comprehensive genomic profiling of small cell lung cancer in Chinese patients and the implications for therapeutic potential. Cancer Med 2019;8:4338-47. [Crossref] [PubMed]
33. Yan B, Yau EX, Bte Omar SS, et al. A study of HER2 gene amplification and protein expression in gastric cancer. J Clin Pathol 2010;63:839-42. [Crossref] [PubMed]
34. Tanner M, Hollmen M, Junttila TT, et al. Amplification of HER-2 in gastric carcinoma: association with Topoisomerase IIalpha gene amplification, intestinal type, poor prognosis and sensitivity to trastuzumab. Ann Oncol 2005;16:273-8. [Crossref] [PubMed]
35. De Craene B, Feng Z, Rondelez E, et al. 697PDetection of microsatellite instability (MSI) with a novel panel of biomarkers in gastric cancer samples. Ann Oncol 2017;28. [Crossref]
36. Polom K, Marano L, Marrelli D, et al. Meta-analysis of microsatellite instability in relation to clinicopathological characteristics and overall survival in gastric cancer. Br J Surg 2018;105:159-67. [Crossref] [PubMed]
37. Chen K, Yang D, Li X, et al. Mutational landscape of gastric adenocarcinoma in Chinese: implications for prognosis and therapy. Proc Natl Acad Sci U S A 2015;112:1107-12. [Crossref] [PubMed]
38. Park J, Yoo HM, Jang W, et al. Distribution of somatic mutations of cancer-related genes according to microsatellite instability status in Korean gastric cancer. Medicine 2017;96:e7224 [Crossref] [PubMed]
39. Jia F, Teer JK, Knepper TC, et al. Discordance of Somatic Mutations Between Asian and Caucasian Patient Populations with Gastric Cancer. Mol Diagn Ther 2017;21:179-85. [Crossref] [PubMed]
40. Wang K, Yuen ST, Xu J, et al. Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer. Nat Genet 2014;46:573-82. [Crossref] [PubMed]
41. Cai J, Feng D, Hu L, et al. FAT4 functions as a tumour suppressor in gastric cancer by modulating Wnt/beta-catenin signalling. Br J Cancer 2015;113:1720-9. [Crossref] [PubMed]
42. Takeda H, Rust AG, Ward JM, et al. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development. Proc Natl Acad Sci U S A 2016;113:E2057-65. [Crossref] [PubMed]
43. Ooi A, Oyama T, Nakamura R, et al. Gene amplification of CCNE1, CCND1, and CDK6 in gastric cancers detected by multiplex ligation-dependent probe amplification and fluorescence in situ hybridization. Hum Pathol 2017;61:58-67. [Crossref] [PubMed]
44. Qiu M, Zhou Y, Zhang X, et al. Lauren classification combined with HER2 status is a better prognostic factor in Chinese gastric cancer patients. BMC Cancer 2014;14:823. [Crossref] [PubMed]
45. Kim ST, Banks KC, Pectasides E, et al. Impact of genomic alterations on lapatinib treatment outcome and cell-free genomic landscape during HER2 therapy in HER2+ gastric cancer patients. Ann Oncol 2018;29:1037-48. [Crossref] [PubMed]
46. Yoshioka T, Shien K, Namba K, et al. Antitumor activity of pan-HER inhibitors in HER2-positive gastric cancer. Cancer Sci 2018;109:1166-76. [Crossref] [PubMed]
47. Liu T, Qin Y, Li J, et al. Pertuzumab in combination with trastuzumab and chemotherapy for Chinese patients with HER2-positive metastatic gastric or gastroesophageal junction cancer: a subpopulation analysis of the JACOB trial. Cancer Commun (Lond) 2019;39:38. [Crossref] [PubMed]
48. Wang HB, Liao XF, Zhang J. Clinicopathological factors associated with HER2-positive gastric cancer: A meta-analysis. Medicine 2017;96:e8437 [Crossref] [PubMed]
49. Kohlruss M, Grosser B, Krenauer M, et al. Prognostic implication of molecular subtypes and response to neoadjuvant chemotherapy in 760 gastric carcinomas: role of Epstein-Barr virus infection and high- and low-microsatellite instability. J Pathol Clin Res 2019;5:227-239. [Crossref] [PubMed]
50. Borderud SP, Li YL, Burkhalter JE, et al. Electronic cigarette use among patients with cancer: characteristics of electronic cigarette users and their smoking cessation outcomes. Cancer 2014;120:3527-35. [Crossref] [PubMed]
51. Cristescu R, Lee J, Nebozhyn M, et al. Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes. Nat Med 2015;21:449-56. [Crossref] [PubMed]
52. Liu P, Zhang XY, Shao Y, et al. Microsatellite instability in gastric cancer and pre-cancerous lesions. World J Gastroenterol 2005;11:4904-7. [Crossref] [PubMed]
53. Martinez-Ciarpaglini C, Fleitas-Kanonnikoff T, Gambardella V, et al. Assessing molecular subtypes of gastric cancer: microsatellite unstable and Epstein-Barr virus subtypes. Methods for detection and clinical and pathological implications. ESMO Open 2019;4:e000470 [Crossref] [PubMed]
54. Gong J, Cho M, Sy M, et al. Molecular profiling of metastatic colorectal tumors using next-generation sequencing: a single-institution experience. Oncotarget 2017;8:42198-213. [Crossref] [PubMed]
55. Moy AP, Shahid M, Ferrone CR, et al. Microsatellite instability in gallbladder carcinoma. Virchows Archiv 2015;466:393-402. [Crossref] [PubMed]
56. Vanderwalde A, Spetzler D, Xiao N, et al. Microsatellite instability status determined by next-generation sequencing and compared with PD-L1 and tumor mutational burden in 11,348 patients. Cancer Med 2018;7:746-56. [Crossref] [PubMed]
57. Maleki Vareki S. High and low mutational burden tumors versus immunologically hot and cold tumors and response to immune checkpoint inhibitors. J Immunother Cancer 2018;6:157. [Crossref] [PubMed]
58. Cai H, Jing C, Chang X, et al. Mutational landscape of gastric cancer and clinical application of genomic profiling based on target next-generation sequencing. J Transl Med 2019;17:189. [Crossref] [PubMed]

(English Language Editor: J. Teoh)