Oncotarget

Research Papers:

Complementary utility of targeted next-generation sequencing and immunohistochemistry panels as a screening platform to select targeted therapy for advanced gastric cancer

PDF |  HTML  |  Supplementary Files  |  Order a Reprint

Oncotarget. 2017; 8:38389-38398. https://doi.org/10.18632/oncotarget.16409

Metrics: PDF 1038 views  |   HTML 1165 views  |   ?  

Hyo Song Kim, Hanna Lee, Su-Jin Shin, Seung-Hoon Beom, Minkyu Jung, Sujin Bae, Eun Young Lee, Kyu Hyun Park, Yoon Young Choi, Taeil Son, Hyoung-Il Kim, Jae-Ho Cheong, Woo Jin Hyung, Jun Chul Park, Sung Kwan Shin, Sang Kil Lee, Yong Chan Lee, Woong Sub Koom, Joon Seok Lim, Hyun Cheol Chung, Sung Hoon Noh, Sun Young Rha, Hyunki Kim and Soonmyung Paik _

Abstract

Hyo Song Kim1,*, Hanna Lee2,*, Su-Jin Shin3,*, Seung-Hoon Beom1, Minkyu Jung1, Sujin Bae2, Eun Young Lee2, Kyu Hyun Park4, Yoon Young Choi5, Taeil Son5, Hyoung-Il Kim5, Jae-Ho Cheong5, Woo Jin Hyung5, Jun Chul Park6, Sung Kwan Shin6, Sang Kil Lee6, Yong Chan Lee6, Woong Sub Koom7, Joon Seok Lim8, Hyun Cheol Chung1,4, Sung Hoon Noh5, Sun Young Rha1,4, Hyunki Kim3, Soonmyung Paik2

1Division of Medical Oncology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea

2Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea

3Hanyang University, College of Medicine, Seoul, Republic of Korea

4Cancer Metastasis Research Center, Song Dang Institute for Cancer Research, Yonsei University College of Medicine, Seoul, Republic of Korea

5Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea

6Division of Gastroenterology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea

7Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Republic of Korea

8Department of Radiology, Yonsei University College of Medicine, Seoul, Republic of Korea

*These authors contributed equally to this work as co-first authors

Correspondence to:

Soonmyung Paik, email: SOONMYUNGPAIK@yuhs.ac

Hyunki Kim, email: kimhyunki@yuhs.ac

Sun Young Rha, email: rha7655@ yuhs.ac

Keywords: gastric cancer, molecular subtypes, next-generation sequencing, immunohistochemistry, matched therapy

Received: November 23, 2016     Accepted: February 20, 2017     Published: March 21, 2017

ABSTRACT

We tested the clinical utility of combined profiling of Ion Torrent PGM based next-generation sequencing (NGS) and immunohistochemistry (IHC) for assignment to molecularly targeted therapies. A consecutive cohort of 93 patients with advanced/metastatic GC who underwent palliative chemotherapy between March and December 2015 were prospectively enrolled. Formalin fixed paraffin embedded tumor biopsy specimens were subjected to a 10 GC panels [Epstein Barr virus encoding RNA in-situ hybridization, IHC for mismatch repair proteins (MMR; MLH1, PMS2, MSH2, and MSH6), receptor tyrosine kinases (HER2, EGFR, and MET), PTEN, and p53 protein], and a commercial targeted NGS panel of 52 genes (Oncomine Focus Assay). Treatment was based on availability of targeted agents at the time of molecular diagnosis. Among the 81 cases with available tumor samples, complete NGS and IHC profiles were successfully achieved in 66 cases (81.5%); only IHC results were available for 15 cases. Eight cases received matched therapy based on sequencing results; ERBB2 amplification, trastuzumab (n = 4); PIK3CA mutation, Akt inhibitor (n = 2); and FGFR2 amplification, FGFR2b inhibitor (n = 2). Eleven cases received matched therapy based on IHC; ERBB2 positivity, trastuzumab (n = 5); PTEN loss (n = 2), PI3Kβ inhibitor; MMR deficiency (n = 2), PD-1 inhibitor; and EGFR positivity (n = 2), pan-ERBB inhibitor. A total of 19 (23.5%) and 62 (76.5%) cases were treated with matched and non-matched therapy, respectively. Matched therapy had significantly higher overall response rate than non-matched therapy (55.6% vs 13.1%, P = 0.001). NGS and IHC markers provide complementary utility in identifying patients who may benefit from targeted therapies.


Complementary utility of targeted next-generation sequencing and immunohistochemistry panels as a screening platform to select targeted therapy for advanced gastric cancer | Kim | Oncotarget

INTRODUCTION

Despite combined treatment with surgical resection and adjuvant chemotherapy, 25–40% of patients with stage II-IV Gastric cancer (GC) experience relapse [1, 2]. Large-scale molecular profiling of GC, as reported in The Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG), identified multiple cancer drivers as potential therapeutic targets [3, 4]. However, chemotherapy remains the only treatment option for patients diagnosed with advanced GCs with dismal outcome, with the exception of trastuzumab for a HER2-positive GC subset, based on the results of the TOGA trial [5].

Advances in genome sequencing technology have allowed the identification of potential therapeutic targets using formalin fixed paraffin embedded (FFPE) tumor biopsy specimens within a timeframe compatible with clinical practice [6]. Using a genome forward designs, clinical trials have been conducted to investigate the efficacy of targeted agents against specific molecular aberrations in a single or multiple tumor types [711]. Findings from histology-agonistic approaches demonstrated improved progression free survival (PFS) and overall survival (OS) compared to those achieved with non-matched therapy [11, 12]. However, in randomized trial with heavily treated solid tumors, targeted agents did not improve the PFS over physician’s choice [9]. As a histology-dependent approach, BATTLE and SAFIRO01 trials established the feasibility of a genome forward approach in lung and breast cancer patients [7, 13].

Regarding GC, despite recent studies with comprehensive molecular profiling [3, 4, 14, 15], no clinical data demonstrating target-drug efficacy in the context of umbrella studies have been published yet. In addition, the very small sizes of FFPE gastric biopsy specimens pose practical and technical challenges often result in sequencing assay failures due to low yield and poor quality of extracted DNA. Therefore, we combined Ion Torrent PGM based amplicon sequencing (Oncomine Focus Assay, Thermo Fisher Scientific, Waltham, MA, USA) with an immunohistochemistry (IHC) panel to maximize the chance of assignment of enrolled patients to potentially beneficial targeted therapies. We also aimed to assess whether our genome forward umbrella approach could improve patient outcomes when compared to non-matched, standard chemotherapy for advanced/metastatic GC.

RESULTS

Patients and molecular aberrations

Sample set and clinicopathologic characteristics

Among the total 81 patients, 50 (61.7%) were male with the median age of 57 years (range 28–76). Biopsy samples (50 endoscopic biopsies and 8 excisional biopsies for metastatic sites) were used for two-thirds of cases (n = 58, 71.6%). Nineteen patients (23.5%) were treated with matched therapy and 62 (76.5%) were treated with non-matched therapy (Table 1).

Table 1: Clinicopathological characteristics

Characteristics

No.

%

Matched (%)

Non-matched (%)

P

Total

81

19 (23.5%)

62 (76.5%)

Age, years

 Median (range)

57 (28–76)

59 (29–73)

57 (28–76)

0.95

Gender

 Male

50

61.7

12 (63.2%)

38 (61.3%)

0.88

 Female

31

38.3

7 (36.8%)

24 (38.7%)

Differentiation

 Well

1

1.2

1 (5.3%)

0

0.20

 Moderate

24

29.6

8 (42.1%)

16 (25.8%)

 Poorly

38

46.9

7 (36.8%)

31 (50.0%)

 Signet ring cell

16

19.8

3 (15.8%)

13 (21.0%)

 Others

2

2.5

0

2 (3.2%)

Tumor location

 Upper

8

9.9

1 (5.3%)

7 (11.3%)

0.87

 Body

27

33.3

6 (31.6%)

21 (33.9%)

 Antrum

38

46.9

10 (52.6%)

28 (45.2%)

 Entire

8

9.9

2 (10.5%)

6 (9.7%)

Tissue samples

 Gastrectomy

23

28.4

2 (10.5%)

21 (33.9%)

0.14

 Endoscopic biopsy

50

61.7

15 (78.9%)

35 (56.5%)

Biopsy for
metastatic sites

8

9.9

2 (10.5%)

6 (9.7%)

Stage at diagnosis

 I

3

3.7

1 (5.3%)

2 (3.2%)

0.55

 II

7

8.6

1 (5.3%)

6 (9.7%)

 III

11

13.6

1 (5.3%)

10 (16.1%)

 IV

60

74.1

16 (84.2%)

44 (71.0%)

Metastatic site

 Peritoneum

45

55.6

9 (47.4%)

36 (58.1%)

0.41

 Lymph node

26

32.1

9 (47.4%)

17 (27.4%)

0.06

 Liver

23

28.4

9 (47.4%)

14 (22.6%)

0.05

 Lung

5

6.2

2 (10.5%)

3 (4.8%)

0.37

 Bone

2

2.5

1 (5.3%)

2 (3.2%)

0.87

Prior therapies

 Treatment naive

33

40.7

9 (47.4%)

24 (38.7%)

0.50

 1–2

48

59.3

10 (52.6%)

38 (61.3%)

Molecular profiling: mutation, amplification, and overexpression

For all 81 cases, we profiled 10 molecular markers using IHC and in situ hybridization (ISH). From a combination of markers, we observed a median of 1 genomic aberration per case (range 0–4). Of those, Epstein-Barr virus (EBV) was identified by ISH in 3 (3.7%) case, and 2 of those harbored the PIK3CA Q546K mutation upon NGS. Mismatch repair (MMR) deficiency was demonstrated in 5 (6.2%) cases, all of which exhibited simultaneous losses of MLH1 and PMS2 expression. Receptor tyrosine kinase (RTK) overexpression occurred in 46 (56.8%) cases, when scores of 2+ and 3+ were defined as positive expression. [16] PTEN loss was observed in 15 patients (18.5%).

Complete NGS and IHC profiles were available for 66 cases (81.5%). At least 1 mutation or amplification was found in 30 (45.5%), of which 26 (86.7%) harbored single aberrations and 4 (13.3%) had multiple aberrations (Figure 1). The most common mutations were as follows; PIK3CA (n = 6, 9.1%) TP53 [n = 4, 40% among 10 cases with Oncomine Comprehensive Assay (OCA)], and KRAS (n = 3, 4.5%). All PIK3CA mutations, including Q546K (n = 3), K111E (n = 1), R93Q (n = 1), H1047R (n = 1), V344M (n = 1), and 3 were co-occurrence mutations with KRAS (G12D), PIK3CA (E726K), and ERBB3 (V104M). Non-V600E BRAF mutation (D594E) was detected in 1 case.

Mutation, amplification, and protein expression profiles.

Figure 1: Mutation, amplification, and protein expression profiles. Vertical lines indicate gene names; horizontal lines indicate the cases. Red and blue arrows indicate cases with concordant IHC and NGS, respectively. Empty squares indicate false-positive ERBB2 amplification on NGS. Squares with diagonal lines indicate false-negative RTK amplification on NGS. Asterisks denote representative cases treated with matched therapy.

Amplification was detected in 17 cases (25.8%) and was mutually exclusive with mutation. Among those, 16 cases (94.1%) exhibiting amplification on NGS also exhibited gene amplification on SISH or FISH assay (Appendix Table 2 and Figure 2A2E). One case exhibited ERBB2 amplification on NGS but neither SISH amplification nor HER2 expression RTK (#32 in Figure 1). Among the 10 cases that exhibited receptor tyrosine kinase (RTK) overexpression via IHC (3+) in the absence of corresponding gene amplification (Appendix Table 3), 5 cases exhibited ERBB2 (n = 2), MET (n = 2), or EGFR (n = 1) amplification by SISH concordant with the IHC results (Appendix Figure 2F2G, red arrows in Figure 1). However, the other 5 cases did not exhibit gene amplification in agreement with the NGS results (Appendix Figure 2H2I, blue arrows in Figure 1).

CONSORT diagram.

Figure 2: CONSORT diagram. T: paclitaxel, X: capecitabine, C: cisplatin.

Treatment assignment and clinical outcomes

Patients with or without molecular aberrations

Of the 30 cases with NGS-detected genetic aberrations, 9 were treated with matched therapy and 21 were treated with non-matched therapy (Figure 2). Among those matched therapy, ERBB2 amplification (n = 4) were treated with trastuzumab-containing chemotherapy (trastuzumab, capecitabine, and cisplatin), and PIK3CA mutation (n = 2) were treated with oral Akt inhibitor, afuresertib in combined with paclitaxel (ClinicalTrials.gov Identifier: NCT02240212). FGFR2 amplification (n = 2) were treated with FPA144 monotherapy, antibody to FGFR2b receptor, (ClinicalTrials.gov Identifier: NCT02318329), and PTEN loss (n = 1) received matched therapy with GSK2636771, PI3Kβ inhibitor in combined with paclitaxel (ClinicalTrials.gov Identifier: NCT02615730).

For the 51 remaining cases, 10 were treated with matched therapy according to the IHC results; trastuzumab containing chemotherapy for ERBB2 positivity (3+, n = 5), PI3Kβ inhibitor for PTEN loss (n = 1), pan-ERBB tyrosine kinase inhibitor, afatinib with paclitaxel (ClinicalTrials.gov Identifier: NCT02501603) for EGFR positivity (n = 2), and pembrolizumab-containing regimen, a monoclonal antibody to programmed cell death 1 (PD-1) inhibitor for MMR-deficiency (n = 2).

Responses and survival

Of the 79 evaluable patients, 18 patients (22.8%) had confirmed partial responses (cPR) and 50 (63.3%) had stable diseases (Appendix Table 4). Patients who received matched therapy had a higher overall response rate (ORR) of 55.6%, compared with 13.1% for those treated with non-matched therapy (Figure 3A, P = 0.001). With median 19.6 months of follow-up, the median PFS were 7.1 months for matched therapy [95% confidence interval (CI), 3.0–11.2], 4.6 months for non-matched ramucirumab/paclitaxel group (95% CI, 3.8–5.4), and 6.9 months for non-matched chemotherapy group (95% CI, 4.8–9.0), respectively (P = 0.033, Figure 3B). The median PFS was slightly longer for matched group compared to non-matched group (7.1 vs 5.2 months, P = 0.07).

Figure 3:

Figure 3: Efficacy data based on molecular profiling (A) Waterfall plot of all patients demonstrating the maximum percent change with respect to baseline. Progression-free survival (B) and overall survival (C). T; trastuzumab, P; pembrolizumab, A; Akt inhibitor, B; PI3Kβ inhibitor, E; pan-ERBB inhibitor.

Clinical response to matched therapy

Two patients with PIK3CA Q546K mutation were enrolled in a phase IB clinical trial with Akt inhibitor. The first GC patient (Case #3 in Figure 1) presented with hepatic metastases was treated with 200 mg of daily afuresertib combined with weekly paclitaxel as second line treatment. A computed tomography (CT) scan at the end of cycle 3 (12 weeks) showed cPR to treatment with a 41.8 % reduction (Figure 4A). The patient was removed from the study with a time to progression of 25 weeks. Second case (Case #1 in Figure 1) was 67-year-old male with paraaortic and hepatic metastases. He was treated with afuresertib and paclitaxel. A CT scan at 16 weeks demonstrated cPR with a 37.7% tumor reduction (Figure 4B), and he remains on treatment after 17 weeks.

Representative clinical responses of 2 PIK3CA mutant cases in the matched group that were treated with the combination of an Akt inhibitor and paclitaxel.

Figure 4: Representative clinical responses of 2 PIK3CA mutant cases in the matched group that were treated with the combination of an Akt inhibitor and paclitaxel. CT images of case #3 during the treatment course. The initial liver metastasis (A1) exhibited a significant size reduction (A2) after 12 weeks. (A3) PIK3CA exon 9 Q546K mutation was detected by pyrosequencing. CT images of case #1 at the time of baseline (B1) and at 16 weeks (B2). CT: computed tomography.

The third case (Case #10 in Figure 1) developed multiple hepatic recurrences 7 months after curative resection (initially stage IB). The tumor was PTEN loss (with H-score 60 out of 300) and he was treated with 300 mg of daily GSK2636771 in combined with weekly paclitaxel. A CT scan at 12 weeks demonstrated stable disease with a 24% tumor reduction (Figure 5A) and he remains on treatment after 25 weeks.

Representative clinical responses in the matched group.

Figure 5: Representative clinical responses in the matched group. CT images of case #10 at baseline (A1) and 12 weeks (A2) after treatment with a PI3Kβ inhibitor and paclitaxel. (B) CT images of case #68 at baseline and 12 weeks (B2) after pembrolizumab treatment. Immunohistochemistry images indicating PTEN loss in case #10 (A3) and MMR deficiency in #68 (B3).

A 53-year-old female patient with a MMR deficiency (Case #68 in Figure 1) was also treated with the PD-1 inhibitor, pembrolizumab (200 mg) every 3 weeks combination with TS-1 monotherapy (50 mg bid, days 1–14). A CT scan at 12 weeks indicated cPR with a 49.8% tumor reduction; she is on treatment after 34 weeks (Figure 5B).

DISCUSSION

In recognition of inter-patient molecular tumor heterogeneity, NGS-based basket trials with specific molecular aberrations across multiple tumor types were widely studied [911]. However, in SHIVA trial, the off-label use of molecularly targeted agents did not improve PFS in heavily pretreated cancer patients when compared with physician’s choice [9]. As demonstrated by the different efficacy of BRAF inhibitors in melanoma and colon cancer [17], the inclusion of multiple tumor types with the same molecular target in a basket trial might introduce an important source of heterogeneity and could lead to negative results.

These observations justify a shift toward a histology dependent approach involving targeted agents. The BATTLE study demonstrated the feasibility and utility of umbrella approach for advanced non-small cell lung cancer (NSCLC) [13]. TCGA classified GCs into four molecular subtypes; EBV-positive tumors (8.8%), microsatellite instability-high (MSI-H) tumors (21.6%), genomically stable tumors (GS, 19.6%), and tumors with chromosomal instability (CIN, 49.6%) [3]. In our study, combination of OFA and IHC panels covered most of the key druggable targets for each subgroup. Our pilot study results demonstrated that the matched group experienced significantly better responses and survival and provides justifying the need for further umbrella trials in GC. We await the results of two ongoing umbrella trials PANGEA and VIKTORY We await the results of 3 ongoing umbrella trials for GC(ClinicalTrials.gov Identifier: NCT02213289, NCT02299648 and NCT02951091). (ClinicalTrials.gov Identifier: NCT02213289 and NCT02299648).

Genomic profiling of biopsied metastatic lesions often presents practical challenges because of the small quantities of available samples. The OCA, which is based on Ion Torrent PGM amplicon sequencing platform is currently used as a screening platform for the NCI MATCH study because of its low sample requirement (20 ng DNA and 10ng RNA from FFPE specimens), and ability to detect CNAs and gene fusions as well as SNVs. The OFA is a subset of OCA that mainly targets actionable cancer drivers. The success rate of our genomic analyses (71%, 66 /93) was similar to those reported trials that used large-scale genomic analyses, with main reason of failure being low cellularity and DNA contents [7, 9, 12].

Despite the known difficulty of reliable CNA detection from amplicon-based targeted sequencing data (because of variable amplification efficiency across targets) [14, 18], OFA with a proprietary analysis pipeline with in silico reference normal tissue data could identify 17 CNAs, 16 (94.1%) of which were validated by ISH. However, the IHC panel was able to identify an additional 5 ERBB2 amplified cases, which were confirmed by ISH. OFA alone would have missed 23% of the CNAs. On the other hand, the additional 5 candidate CNAs identified by the IHC panel (no NGS amplification, 3+ RTK overexpression by the IHC panel) were not detected by ISH or NGS. Overall, more than a half (n = 11) of the decisions regarding matched therapy were made based on IHC, underscoring the importance of combining NGS with an IHC panel. By applying a more sophisticated approach that incorporated both IHC and NGS, our cancer profiling led to the use of matching therapy in a greater proportion of cases (23.5%), as well as a higher ORR than with previous studies [7, 9].

There are some important issues must be considered when interpreting of this study. First, this was not a randomized study, and therefore results must be interpreted cautiously. However, PFS of the non-matched (control) group in our study was consistent with those reported in phase III randomized trials in support of our results; for example, our study showed a PFS of 4.6 months in the non-matched ramucirumab/paclitaxel group, compared with 4.4 months in the ramucirumab/paclitaxel group from the RAINBOW trial [19]. Second, approximately 40% cases receiving matched therapy is ERBB2 amplified cases, which is already been identified as a standard biomarker of advanced GC. However, we believe that the inclusion of ERBB2 amplified cases in our analyses is justified as the primary purpose of the umbrella approach is the identification of all therapeutic targets at the time of diagnosis, thus avoiding the need to successively evaluate single markers over time. Accordingly, ERBB2 positivity, a main genetic aberration of GC, should be included in this type of study. In support of our approach, two-thirds of matched group was treated according to clinical practice in the NEXT-1 trial [18], and EGFR-mutant NSCLCs were also included in the analyses of the BATTLE and CUSTOM trials [10, 13]. Interestingly, one case (case #25) has co-occurrence of EBV positivity and FGFR2 amplification. Tumor was not responded to FGFR2 inhibitor and efficacy of immune checkpoint inhibitor needs to be determined. Finally, the algorithms used to interpret genomic data and assign targeted therapies need to be improved in the era of immunotherapy and DNA repair modulation.

In this study, we have demonstrated that a combined NGS and IHC analysis of FFPE samples is a feasible method for the identification of targetable genomic alterations in patients with metastatic GC. In addition, identification of specific molecular aberrations and assignment of targeted therapy were associated with better responses and survival supportive for future randomized trial.

MATERIALS AND METHODS

Study design and subjects

This study had the following objectives: (1) to test the feasibility of NGS based genomic profiling of small FFPE tumor biopsies routinely produced for diagnostic purpose, in a time frame feasible for clinical practice; (2) to assign patients to matched therapy based on genomic aberrations; and (3) to explore the potential clinical benefit of a genome-forward approach over conventional chemotherapy.

The study scheme is outline in Appendix Figure 1. A consecutive cohort of 93 patients with advanced/metastatic GC who underwent palliative chemotherapy at Severance Hospital, Yonsei University College of Medicine, Seoul, Korea between March 2015 and December 2015 was enrolled in this study. Of those, 12 were excluded from genomic analysis [insufficient tumor cellularity, 11 patients (11.8%); lost to follow-up, 1 patient (1.0%)]. Among the remaining 81 patients, complete NGS and IHC profile were successfully obtained for 66 cases (81.5%). For the remaining 15 cases (18.5%), only IHC data were available because of failed quality control for the NGS analyses (insufficient DNA yield, 8 patients; poor DNA quality, 7 patients). The study was approved by the institutional review board (IRB. 4–2014-0349).

Biomarker methodology

Nucleic acid extraction from FFPE

Ten 4-mm-thick FFPE sections were used for the IHC panel and 2–4 sections were used for NGS. Using hematoxylin and eosin (H&E)-stained sections for guidance, tumor rich areas were reviewed and macrodissected by two experienced pathologists (H.K. and S.J.S) to achieve a final tumor content per sample over 10%. DNA was isolated using the Ambion RecoverAll™ Multi-sample DNA workflow (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions. DNA was quantified using the Qubit 2.0 fluorometer High sensitivity kit (Thermo Fisher Scientific).

Library construction and sequencing

Ten to twenty nanograms of DNA were amplified using Oncomine Comprehensive Assay (OCA, case #1–10 in Figure 1) or Oncomine Focus Assay (OFA, case 11–66) DNA panels targeting 143 and 52 genes, respectively, according to manufacturer’s instruction (Appendix Table 1). RNA analysis for fusion transcript was not performed, given the lack of clinically important fusion events in GC.

Data analysis

Sequenced data were initially aligned and mapped to the human hg19 reference genome using the Torrent Suite Server (ver 4.4) with default parameters. Amplicon coverage summary files were generated results using the Coverage Analysis plug-in (version 4.4.12–1). The Ion Reporter Workflow (version 5.0) was used to perform variant calling of the DNA libraries. In detail, gene annotation was performed using the Oncomine Panel v1.1 Annotations set and copy number baseline was performed using the Oncomine Panel v2.0. Baseline and Oncomine Variant annotator v2.0 plugin was used for analysis. Analyzed variants were re-categorized using the Oncomine knowledgebase, which includes currently approved drugs and clinical trials. We used the following cutoff values: coverage, > 1000×; and proportion of reads on target, > 80%.

Immunohistochemical staining, epstein–barr virus-encoded small RNA-In Situ hybridization, and evaluation

IHC was performed on a Ventana XT automated staining instrument (Ventana Medical Systems, Tucson, AZ, USA). The following target-specific antibodies were used according to the manufacturer’s instructions and a previous study [20]: MutL homolog 1 (MLH1, ready to use, clone M1, Roche, Basel, Switzerland), MutS protein homolog 2 (MSH2, ready to use, clone G219-1129, Roche), MutS homolog 6 (MSH6, 1:100, clone 44, Cell Marque, Rocklin, CA, USA), postmeiotic segregation increased 2 (PMS2, 1:40, clone MRQ28, Cell Marque), ERBB2 (ready to use, clone 4B5, Roche), EGFR (1:100, EP38Y, Abcam, Cambridge, UK), c-MET (ready to use, clone SP44, Roche), PTEN (1:100, clone 138G6, Cell Signaling, Danvers, MA, USA), and p53 (1:300, DO7, Novocastra, Newcastle, UK). Epstein-Barr virus-encoded small RNAs (EBER) in situ hybridization (ISH) was performed using a Ventana Benchmark ISH system and ISH iView kit (Ventana Medical Systems, Tucson, AZ, USA).

In situ hybridization for amplification

Gene amplifications identified via OCA and OFA were confirmed using silver ISH (SISH) and fluorescence ISH (FISH). Gene amplification was defined as > 6 gene copies per nucleus or a gene signal/centromere signal ratio > 2.0 according to previous study. [2127] Probes recognizing the following targets were used: HER2 (INFORM® HER2 DNA and Chr 17 SISH probes, Roche), EGFR (INFORM® EGFR DNA and Chr 7 SISH probes, Roche), MET (INFORM® MET DNA and Chr 7 SISH probes, Roche), FGFR2 (FGFR2/CEN10p FISH probe; Abnona Corporation, Taipei, Taiwan), C-myc (MYC DNP and Chr 8 probe, Roche), and CCND1 (CCND1/CEP11 FISH probe, Vysis, Downers Grove, IL, USA).

Therapy

Assignment to a matched therapy was determined after reviewing the clinical, laboratory, and pathologic data from all available patient records. Patients whose tumors harbored molecular aberrations were preferably considered for clinical trials with a matched therapy, when available with the following prioritization criteria. (1) Actionable molecular aberrations, wherein any mutation, deletion, or amplification was deemed to be of greater importance; in case with no aberrations, loss of protein of IHC expression was selected. (2) The allocation of patients to investigational treatment varied over time according to the availability of ongoing clinical trials, and off-label treatment, as well as the patient’s or physician’s preference.

Statistical analysis

The χ2 test was used to assess the correlation between marker status and clinical significance. All the tests were 2-sided, and P values of < 0.05 were considered significant. Responses were assessed according to the Response Evaluation Criteria in Solid Tumors (RECIST) criteria version 1.1 [28]. PFS was defined from the first day of treatment to the time of disease progression or death. OS was measured from the time of surgery to death or the last follow-up date and evaluated by survival analysis using the Kaplan-Meier method with a log-rank test. All statistical analyses were performed using SPSS version 18.0 (IBM, Chicago, IL, USA).

CONFLICTS OF INTEREST

The authors have no potential conflicts of interest to disclose.

GRANT SUPPORT

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number : HI13C2162, Soonmyung Paik), a grant from the National R&D Program for Cancer Control, Ministry of Health and Welfare, Republic of Korea (grant number : 1520190, Sun Young Rha), and a grant supported by the “Dongwha Holdings” Faculty Research Assistance Program of Yonsei University College of Medicine for 2015 (6-2015-0169, Hyo Song Kim).

REFERENCES

1. Noh SH, Park SR, Yang HK, Chung HC, Chung IJ, Kim SW, Kim HH, Choi JH, Kim HK, Yu W, Lee JI, Shin DB, Ji J, et al. Adjuvant capecitabine plus oxaliplatin for gastric cancer after D2 gastrectomy (CLASSIC): 5-year follow-up of an open-label, randomised phase 3 trial. Lancet Oncol. 2014; 15:1389–1396.

2. Lee J, Lim do H, Kim S, Park SH, Park JO, Park YS, Lim HY, Choi MG, Sohn TS, Noh JH, Bae JM, Ahn YC, Sohn I, et al. Phase III trial comparing capecitabine plus cisplatin versus capecitabine plus cisplatin with concurrent capecitabine radiotherapy in completely resected gastric cancer with D2 lymph node dissection: the ARTIST trial. J Clin Oncol. 2012; 30:268–273.

3. Cancer Genome Atlas Research N. Comprehensive molecular characterization of gastric adenocarcinoma. Nature. 2014; 513:202–209.

4. Cristescu R, Lee J, Nebozhyn M, Kim KM, Ting JC, Wong SS, Liu J, Yue YG, Wang J, Yu K, Ye XS, Do IG, Liu S, et al. Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes. Nat Med. 2015; 21:449–456.

5. Bang YJ, Van Cutsem E, Feyereislova A, Chung HC, Shen L, Sawaki A, Lordick F, Ohtsu A, Omuro Y, Satoh T, Aprile G, Kulikov E, Hill J, et al. Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer (ToGA): a phase 3, open-label, randomised controlled trial. Lancet. 2010; 376:687–697.

6. Gray SW, Hicks-Courant K, Cronin A, Rollins BJ, Weeks JC. Physicians’ attitudes about multiplex tumor genomic testing. J Clin Oncol. 2014; 32:1317–1323.

7. Andre F, Bachelot T, Commo F, Campone M, Arnedos M, Dieras V, Lacroix-Triki M, Lacroix L, Cohen P, Gentien D, Adelaide J, Dalenc F, Goncalves A, et al. Comparative genomic hybridisation array and DNA sequencing to direct treatment of metastatic breast cancer: a multicentre, prospective trial (SAFIR01/UNICANCER). Lancet Oncol. 2014; 15:267–274.

8. Cho JY, Lim JY, Cheong JH, Park YY, Yoon SL, Kim SM, Kim SB, Kim H, Hong SW, Park YN, Noh SH, Park ES, Chu IS, et al. Gene expression signature-based prognostic risk score in gastric cancer. Clin Cancer Res. 2011; 17:1850–1857.

9. Le Tourneau C, Delord JP, Goncalves A, Gavoille C, Dubot C, Isambert N, Campone M, Tredan O, Massiani MA, Mauborgne C, Armanet S, Servant N, Bieche I, et al. Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open-label, proof-of-concept, randomised, controlled phase 2 trial. Lancet Oncol. 2015; 16:1324–1334.

10. Lopez-Chavez A, Thomas A, Rajan A, Raffeld M, Morrow B, Kelly R, Carter CA, Guha U, Killian K, Lau CC, Abdullaev Z, Xi L, Pack S, et al. Molecular profiling and targeted therapy for advanced thoracic malignancies: a biomarker-derived, multiarm, multihistology phase II basket trial. J Clin Oncol. 2015; 33:1000–1007.

11. Von Hoff DD, Stephenson JJ Jr, Rosen P, Loesch DM, Borad MJ, Anthony S, Jameson G, Brown S, Cantafio N, Richards DA, Fitch TR, Wasserman E, Fernandez C, et al. Pilot study using molecular profiling of patients’ tumors to find potential targets and select treatments for their refractory cancers. J Clin Oncol. 2010; 28:4877–4883.

12. Tsimberidou AM, Wen S, Hong DS, Wheler JJ, Falchook GS, Fu S, Piha-Paul S, Naing A, Janku F, Aldape K, Ye Y, Kurzrock R, Berry D. Personalized medicine for patients with advanced cancer in the phase I program at MD Anderson: validation and landmark analyses. Clin Cancer Res. 2014; 20:4827–4836.

13. Kim ES, Herbst RS, Wistuba II, Lee JJ, Blumenschein GR Jr, Tsao A, Stewart DJ, Hicks ME, Erasmus J Jr, Gupta S, Alden CM, Liu S, Tang X, et al. The BATTLE trial: personalizing therapy for lung cancer. Cancer Discov. 2011; 1:44–53.

14. Kuboki Y, Yamashita S, Niwa T, Ushijima T, Nagatsuma A, Kuwata T, Yoshino T, Doi T, Ochiai A, Ohtsu A. Comprehensive analyses using next-generation sequencing and immunohistochemistry enable precise treatment in advanced gastric cancer. Ann Oncol. 2016; 27:127–133.

15. Deng N, Goh LK, Wang H, Das K, Tao J, Tan IB, Zhang S, Lee M, Wu J, Lim KH, Lei Z, Goh G, Lim QY, et al. A comprehensive survey of genomic alterations in gastric cancer reveals systematic patterns of molecular exclusivity and co-occurrence among distinct therapeutic targets. Gut. 2012; 61:673–684.

16. Nagatsuma AK, Aizawa M, Kuwata T, Doi T, Ohtsu A, Fujii H, Ochiai A. Expression profiles of HER2, EGFR, MET and FGFR2 in a large cohort of patients with gastric adenocarcinoma. Gastric Cancer. 2015; 18:227–238.

17. Yang H, Higgins B, Kolinsky K, Packman K, Bradley WD, Lee RJ, Schostack K, Simcox ME, Kopetz S, Heimbrook D, Lestini B, Bollag G, Su F. Antitumor activity of BRAF inhibitor vemurafenib in preclinical models of BRAF-mutant colorectal cancer. Cancer Res. 2012; 72:779–789.

18. Kim ST, Lee J, Hong M, Park K, Park JO, Ahn T, Park SH, Park YS, Lim HY, Sun JM, Ahn JS, Ahn MJ, Kim HC, et al. The NEXT-1 (Next generation pErsonalized tX with mulTi-omics and preclinical model) trial: prospective molecular screening trial of metastatic solid cancer patients, a feasibility analysis. Oncotarget. 2015; 6:33358–33368. doi: 10.18632/oncotarget.5188.

19. Wilke H, Muro K, Van Cutsem E, Oh SC, Bodoky G, Shimada Y, Hironaka S, Sugimoto N, Lipatov O, Kim TY, Cunningham D, Rougier P, Komatsu Y, et al. Ramucirumab plus paclitaxel versus placebo plus paclitaxel in patients with previously treated advanced gastric or gastro-oesophageal junction adenocarcinoma (RAINBOW): a double-blind, randomised phase 3 trial. Lancet Oncol. 2014; 15:1224–1235.

20. Kim HS, Shin SJ, Beom SH, Jung M, Choi YY, Son T, Kim HI, Cheong JH, Hyung WJ, Noh SH, Chung H, Park JC, Shin SK, et al. Comprehensive expression profiles of gastric cancer molecular subtypes by immunohistochemistry: implications for individualized therapy. Oncotarget. 2016; 7:44608–44620. doi: 10.18632/oncotarget.10115.

21. Choi JS, Seo J, Jung EJ, Kim EJ, Lee GK, Kim WH. c-MYC amplification in mucinous gastric carcinoma: a possible genetic alteration leading to deeply invasive tumors. Anticancer Res. 2012; 32:5031–5037.

22. Jung EJ, Jung EJ, Min SY, Kim MA, Kim WH. Fibroblast growth factor receptor 2 gene amplification status and its clinicopathologic significance in gastric carcinoma. Hum Pathol. 2012; 43:1559–1566.

23. Ruschoff J, Hanna W, Bilous M, Hofmann M, Osamura RY, Penault-Llorca F, van de Vijver M, Viale G. HER2 testing in gastric cancer: a practical approach. Mod Pathol. 2012; 25:637–650.

24. Lee HE, Kim MA, Lee HS, Jung EJ, Yang HK, Lee BL, Bang YJ, Kim WH. MET in gastric carcinomas: comparison between protein expression and gene copy number and impact on clinical outcome. Br J Cancer. 2012; 107:325–333.

25. Oh HS, Eom DW, Kang GH, Ahn YC, Lee SJ, Kim JH, Jang HJ, Kim EJ, Oh KH, Ahn HJ. Prognostic implications of EGFR and HER-2 alteration assessed by immunohistochemistry and silver in situ hybridization in gastric cancer patients following curative resection. Gastric Cancer. 2014; 17:402–411.

26. Park JS, Kim HS, Bae YS, Cheong JH, Rha SY, Noh SH, Kim H. Prognostic significance and frequency of EGFR expression and amplification in surgically resected advanced gastric cancer. Jpn J Clin Oncol. 2016. doi:10.1093/jjco/hyw030.

27. Ooi A, Oyama T, Nakamura R, Tajiri R, Ikeda H, Fushida S, Nakamura H, Dobashi Y. Semi-comprehensive analysis of gene amplification in gastric cancers using multiplex ligation-dependent probe amplification and fluorescence in situ hybridization. Mod Pathol. 2015; 28:861–871.

28. Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, Dancey J, Arbuck S, Gwyther S, Mooney M, Rubinstein L, Shankar L, Dodd L, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009; 45:228–247.


Creative Commons License All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.
PII: 16409