Literature DB >> 30742731

Feasibility and utility of a panel testing for 114 cancer-associated genes in a clinical setting: A hospital-based study.

Kuniko Sunami1, Hitoshi Ichikawa2,3, Takashi Kubo1,2,3, Mamoru Kato4, Yutaka Fujiwara5, Akihiko Shimomura5, Takafumi Koyama5, Hiroki Kakishima1, Mayuko Kitami1, Hiromichi Matsushita1, Eisaku Furukawa4, Daichi Narushima4, Momoko Nagai4, Hirokazu Taniguchi1, Noriko Motoi1, Shigeki Sekine1, Akiko Maeshima1, Taisuke Mori1, Reiko Watanabe1, Masayuki Yoshida1, Akihiko Yoshida1, Hiroshi Yoshida1, Kaishi Satomi1, Aoi Sukeda1, Taiki Hashimoto1, Toshio Shimizu5, Satoru Iwasa5, Kan Yonemori5, Ken Kato6, Chigusa Morizane7, Chitose Ogawa8, Noriko Tanabe9, Kokichi Sugano9,10, Nobuyoshi Hiraoka1, Kenji Tamura11, Teruhiko Yoshida9, Yasuhiro Fujiwara11,12, Atsushi Ochiai13, Noboru Yamamoto5, Takashi Kohno3,14.   

Abstract

Next-generation sequencing (NGS) of tumor tissue (ie, clinical sequencing) can guide clinical management by providing information about actionable gene aberrations that have diagnostic and therapeutic significance. Here, we undertook a hospital-based prospective study (TOP-GEAR project, 2nd stage) to investigate the feasibility and utility of NGS-based analysis of 114 cancer-associated genes (the NCC Oncopanel test). We examined 230 cases (comprising more than 30 tumor types) of advanced solid tumors, all of which were matched with nontumor samples. Gene profiling data were obtained for 187 cases (81.3%), 111 (59.4%) of which harbored actionable gene aberrations according to the Clinical Practice Guidelines for Next Generation Sequencing in Cancer Diagnosis and Treatment (Edition 1.0) issued by 3 major Japanese cancer-related societies. Twenty-five (13.3%) cases have since received molecular-targeted therapy according to their gene aberrations. These results indicate the utility of tumor-profiling multiplex gene panel testing in a clinical setting in Japan. This study is registered with UMIN Clinical Trials Registry (UMIN 000011141).
© 2019 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

Entities:  

Keywords:  NCC Oncopanel; actionable gene aberration; clinical sequencing; gene panel test; insurance reimbursement

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Year:  2019        PMID: 30742731      PMCID: PMC6447843          DOI: 10.1111/cas.13969

Source DB:  PubMed          Journal:  Cancer Sci        ISSN: 1347-9032            Impact factor:   6.716


INTRODUCTION

In a clinical setting, massively parallel next‐generation sequencing (NGS) has enabled simultaneous examination of more than 100 genes to detect “actionable” mutations that help oncologists with respect to diagnosis and selection of potential treatment regimens involving molecular‐targeted drugs.1, 2 Such systems are referred to as “tumor‐profiling multiplex gene panel tests” or more simply “gene panel tests.” Clinical Laboratory Improvement Amendments (CLIA)‐certified laboratories in the USA have implemented a variety of NGS‐based gene panel tests. For example, scientists at the Memorial Sloan Kettering Cancer Center implemented the MSK‐IMPACT (Integrated Mutation Profiling of Actionable Cancer Targets) test to examine 348 genes and reported that 37% of 10 000 investigated patients harbored at least 1 actionable mutation and that 11% of the first 5009 patients who received an MSK‐IMPACT test were subsequently enrolled in genomically matched clinical trials.3 Foundation Medicine (Cambridge, MA, USA) developed the FoundationOne CDx test to examine 324 genes and the tumor mutational burden (TMB),4 which is an emerging biomarker of sensitivity to immune checkpoint blockade therapy.5, 6 These 2 tests have now been approved by the FDA, further facilitating cancer genome medicine in the USA by promoting insurance reimbursement.7 Gene panel tests have not yet been implemented in routine oncological practice in Japan; ie, they have not been reimbursed by the national insurance system run by the Japanese Ministry of Health, Labor, and Welfare (MHLW).8 However, several academic institutions have examined the feasibility and utility of gene panel tests,1, 2 and 3 major Japanese cancer‐related societies (the Japanese Society of Medical Oncology, the Japanese Society of Clinical Oncology, and the Japanese Cancer Association) have issued consensus clinical practice guidance for NGS‐based cancer tests (the Consensus Clinical Practice Guidelines for Next Generation Sequencing in Cancer Diagnosis and Treatment [Edition 1.0];9 http://www.jsmo.or.jp/about/kanko.html#guideline) . Therefore, it is likely that implementation of gene panel tests in Japan will happen soon. We have been undertaking a prospective hospital‐based cohort study to investigate the feasibility and utility of NGS‐based analysis of 114 cancer‐associated genes using the National Cancer Center (NCC) Oncopanel test (Table 1). Many different cases of advanced solid tumors were analyzed at a quality‐assured laboratory at the NCC Hospital (NCCH; Tokyo, Japan). Detected gene aberrations and their annotations were reported to the treating physicians. This study formed the second stage of the TOP‐GEAR project (Trial of Onco‐Panel for Gene‐profiling to Estimate both Adverse events and Response during cancer treatment; UMIN 000011141). This follows the first10 stage in which tumor samples were analyzed at the NCC Research Institute.
Table 1

Genes examined by the NCC Oncopanel test (n = 114)

Mutations and copy number alterations for all exonsFusions
ABL1 CRKL IDH2 NF1 RAC2 ALK
ACTN4 CREBBP IGF1R NFE2L2/Nrf2 RAD51C AKT2
AKT1 CTNNB1 IGF2 NOTCH1 RAF1/CRAF BRAF
AKT2 CUL3 IL7R NOTCH2 RB1 ERBB4
AKT3 DDR2 JAK1 NOTCH3 RET FGFR2
ALK EGFR JAK2 NRAS RHOA FGFR3
APC ENO1 JAK3 NRG1 ROS1 NRG1
ARAF EP300 KDM6A/UTX NTRK1 SETBP1 NTRK1
ARID1A ERBB2/HER2 KEAP1 NTRK2 SETD2 NTRK2
ARID2 ERBB3 KIT NTRK3 SMAD4 PDGFRA
ATM ERBB4 KRAS NT5C2 SMARCA4/BRG1 RET
AXIN1 ESR1/ER MAP2K1/MEK1 PALB2 SMARCB1 ROS1
AXL EZH2 MAP2K2/MEK2 PBRM1 SMO
BAP1 FBXW7 MAP2K4 PDGFRA STAT3
BARD1 FGFR1 MAP3K1 PDGFRB STK11/LKB1
BCL2L11/BIM FGFR2 MAP3K4 PIK3CA TP53
BRAF FGFR3 MDM2 PIK3R1 TSC1
BRCA1 FGFR4 MDM4 PIK3R2 VHL
BRCA2 FLT3 MET POLD1
CCND1 GNA11 MLH1 POLE
CD274/PD‐L1 GNAQ MTOR PRKCI
CDK4 GNAS MSH2 PTCH1
CDKN2A HRAS MYC PTEN
CHEK2 IDH1 MYCN RAC1    
Genes examined by the NCC Oncopanel test (n = 114) Here, we summarize the results of the first 230 cases analyzed during the second stage of TOP‐GEAR. The results indicate the feasibility and utility of the gene panel test in a clinical oncology setting. From April 2018, the NCC Oncopanel test is being tested by 50 Core and Liaison Hospitals for Cancer Genomic Medicine in Japan (within the Advanced Medical Care B system) to validate its feasibility and utility.11

PATIENTS AND METHODS

Patient population

Patients aged 16 years or older, diagnosed histopathologically with a solid tumor, and who would finish or had finished standard chemotherapy were enrolled in the TOP‐GEAR study (n = 248). Next, the availability of archival formalin‐fixed paraffin‐embedded (FFPE) tumor tissues with tumor cell content 10% or higher was checked for each case (pathologists estimated tumor cell content by counting the nuclei of tumor and nontumor cells within each tissue); appropriate cases were analyzed in the study to address the feasibility and utility of the NCC Oncopanel test (n = 230). The study was approved by the NCC Institutional Review Board, and all patients provided written informed consent for the use of genomic and clinical data for research purposes. When consent was obtained, patients were also asked whether they will be reported for the results of somatic and germline gene alteration, respectively, from treating physicians. Among the 230 analyzed cases, 228 (99.1%) and 219 cases (95.2%) gave consent to receive results of somatic and germline tests, respectively; therefore, results were returned to patients accordingly.

Next‐generation sequencing‐based multiplex gene assay (NCC Oncopanel test)

The NCC Oncopanel test is a hybridization capture‐based NGS assay designed to examine mutations, amplifications, and homozygous deletions of the entire coding region of 114 genes of clinical or preclinical relevance, along with rearrangements of 12 oncogenes included in the panel (Table 1). For the analysis, 5 10‐μm sections or 10 4‐5‐μm sections were prepared from FFPE tumor tissues. Peripheral blood (5 mL) collected from the same patients was used as a control to allow discrimination of somatic and germline mutations. Genomic DNA was extracted from tumor tissues and peripheral blood cells using a QIAamp DNA FFPE Tissue kit (Qiagen, Hilden, Germany) and a Maxwell RSC Blood DNA kit (Promega, Fitchburg, WI, USA), respectively. The extracted DNA was quantified using a Qubit dsDNA BR Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA) and a Qubit 3.0 Fluorometer (Thermo Fisher Scientific). Quantitative PCR analysis of the RPPH1 (RNase P) locus was carried out, and the ratio of PCR‐amplifiable DNA to total double‐stranded DNA was used to indicate DNA quality. When this value (Q‐value) was greater than or equal to 0.1, the DNA was sent for sequencing.10 The Q‐value reflects the fraction of PCR‐active DNA molecules in each sample. Our previous clinical sequencing study10 verified empirically that, in the cases with high‐quality DNA, it is possible to reduce the amount of input DNA to 50 ng. However, in cases with poor‐quality DNA, use of large amounts of DNA (more than 800 ng) did not efficiently improve the results; this was likely due to saturation of the DNA capture‐based system. Therefore, the threshold for DNA quantity was set according to DNA quality: the threshold was 50 ng or more for samples with a Q‐value less than or equal to 0.8; 100 ng or more for samples with a Q‐value greater than or equal to 0.4 and less than 0.8; 200 ng or more for samples with a Q‐value greater than or equal to 0.2 and less than 0.4; and 400 ng or more for samples with a Q‐value greater than or equal to 0.1 and less than 0.2. Sequencing libraries were prepared from 50‐800 ng DNA (depending on the Q‐value) using the SureSelect XT reagent (Agilent Technologies, Santa Clara, CA, USA) and a KAPA Hyper Prep kit (KAPA Biosystems, Wilmington, MA, USA) and then analyzed on the Illumina MiSeq or NextSeq platform (Illumina, San Diego, CA, USA) with 150 bp paired‐end reads.

Bioinformatics analysis

Mapping of NGS reads to the human reference genome was carried out using the Burrows‐Wheeler Aligner12 and the Burrows‐Wheeler Aligner‐Smith‐Waterman algorithm13 after removal of adapter sequences using a Cutadapt program.14 Thresholds for mean read depth of coverage for gene aberration calls were set according to tumor cell content, as defined by pathological examination; the threshold was 200 for samples with more than 50% cellularity, 250 for samples with 20%‐50% cellularity, and 500 for samples with less than 20% cellularity. For samples with a mean read depth of coverage above these thresholds, somatic mutations (single nucleotide variants and short insertions and deletions (indels)), gene amplifications, homozygous deletions, and gene fusions were detected using the cisCall program (version 7.1.5).15 Mutations with 5% or more variant allele frequencies and amplifications with more than 4‐fold copy number increases were defined as positive. Genes with less than 0.5‐fold copy number decreases were considered as homozygous deletion candidates and judged by manual inspection using the Integrative Genomics Viewer (IGV).16 Data from the refGene (20150219), ensGene (20140406), and COSMIC (version 71)17 databases were used to annotate each gene aberration. The level of cross‐individual contamination in tumor tissues was estimated by the ContEst program,18 as well as by manual inspection of single nucleotide polymorphism sites using IGV.16 Tumor samples thought to show cross‐individual contamination were removed from the study. Germline mutations in 13 genes responsible for hereditary cancers (APC, BRCA1, BRCA2, MLH1, MSH2, PTEN, RB1, RET, SMAD4, STK11, TP53, TSC1, and VHL), for which the American College of Medical Genetics and Genomics (ACMG) recommends reporting of incidental or secondary findings,19 were detected by the GATK program20 (version 3) using NGS data obtained from peripheral blood DNA. Single nucleotide polymorphisms were removed if they showed a threshold of 0.01 or more allele frequency in any of the following databases: 1000 Genomes (1 kgp, 201204) (http://www.1000genomes.org); the NHLBI GO Exome Sequencing Project (ESP6500) (http://evs.gs.washington.edu/EVS/); the Human Genetic Variation Database (HGVD, 20131010) (http://www.genome.med.kyoto-u.ac.jp/SnpDB); and the Integrative Japanese Genome Variation Database (iJGVD, 20151218) (https://ijgvd.megabank.tohoku.ac.jp/).21 All somatic and germline aberrations judged to be positive were validated by manual inspection on IGV.16

Definition of actionable

Actionable gene aberrations for drug selection were those predicted to confer sensitivity/resistance to either an approved targeted agent or an experimental targeted agent currently in clinical trials. Evidence levels were added to each gene aberration according to Clinical Practice Guidance for Next Generation Sequencing in Cancer Diagnosis and Treatment (issued by the Japanese Society of Medical Oncology, Japan Society of Clinical Oncology, and the Japanese Cancer Association).9 The guidance cites the following levels of evidence for each gene aberration: level 1A, a Pharmaceuticals and Medical Devices Agency (PMDA)‐approved biomarker for the tumor type; 1B, an FDA‐approved biomarker for the tumor type (not approved by the PMDA) or a biomarker verified by a prospective molecularly driven clinical trial; 2A, a biomarker identified by subgroup analysis in a prospective clinical trial; 2B, an approved biomarker for a different tumor type or a biomarker with evidence supporting its clinical utility; 3A, a biomarker with evidence of proof‐of‐concept in at least one case report; 3B, a biomarker with evidence obtained from in vitro/in vivo experiments; and 4, other gene mutations in cancer. In the present study, gene aberrations with evidence levels 1A‐3A were judged as actionable for drug selection. Evidence levels 1A‐3A correspond to evidence levels A‐C listed in guidance documents published by the Association for Molecular Pathology, ACMG, the American Society of Clinical Oncology, and the College of American Pathologists.22 In addition, actionable aberrations for diagnosis and prognosis were also considered according to Japanese guidelines. As for germline mutations in the above‐mentioned 13 genes, truncating mutations and mutations deposited as “pathogenic” in the ClinVar database23 (20150629) (https://www.ncbi.nlm.nih.gov/clinvar/) were judged as deleterious and, therefore, significant.

Tumor mutational burden

Tumor mutational burden was defined as the number of somatic, coding, base substitutions, and indel mutations per megabase of genome examined (ie, the total number of mutations divided by 1.38 Mb [the genome size of target regions covered by the NCC Oncopanel assay]). All base substitutions and indels in the coding region of targeted genes, including synonymous alterations, were counted. DNAs extracted from tumor and nontumor tissues of lung, breast, and ovarian cancers (n = 20), whose TMBs were measured previously by whole exome sequencing,24, 25, 26 were subjected to NCC Oncopanel analysis to verify their utility for estimating TMB.

Molecular tumor board (expert panel)

Actionable gene aberrations and possible treatments were discussed at the molecular tumor board meeting by a multidisciplinary team at NCCH, called the “expert panel,” which met twice per month. The board included medical oncologists, pediatric oncologists, pathologists, genome researchers, bioinformaticians, and genetic counselors. Board members discussed genetically informed treatment options and other issues such as authorization of pathological diagnoses and interpretation of somatic/germline variants. The report was returned to the treating physicians, who explained the details to their patients.

RESULTS

Feasibility of testing

Between May 2016 and May 2017, 248 patients were enrolled in TOP‐GEAR and the availability of appropriate tumor tissues was checked (Figure 1A, Table S1). Eighteen cases were excluded due to lack of sufficient tumor tissue sample (n = 16) or diagnosis of a benign tumor upon pathological re‐review (n = 2). Thus, 230 cases were analyzed to test the feasibility and utility of the NCC Oncopanel test. The 230 cases comprised 140 surgical (60.9%) and 90 (39.1%) biopsy specimens (Figure 1A). Eighteen of these were removed due to low DNA yield (n = 8) or quality (n = 10), measured according to the criteria described above10 (Figure 1A). Therefore, 212 (92.2%) of the 230 cases were subjected to NGS analysis. After analysis, 9 (3.9%) cases were judged as having tissue cross‐contamination. ContEst program analysis revealed that 2 of these had >5% tissue cross‐contamination; the remaining 7 cases were inferred by IGV inspection (Figure S1). In addition, the mean read depth in another 16 (7.0%) cases was below the set thresholds. Thus, gene profiling data were obtained for 187 (88.2%) of 212 patients (Table S1), making the success rate 81.3%. In these samples, medians for the mean read depth and allele frequencies of detected mutations were 626 and 27.2%, respectively (Figure S2). The average turnaround time, defined as the interval between the date of sample arrival and the date of the molecular tumor board meeting, was 37 days (median, 32 days; range, 9‐84 days).
Figure 1

Feasibility of the NCC Oncopanel test for 114 cancer‐associated genes in a cohort of Japanese patients with solid tumors who would complete or had completed standard chemotherapy. A, Success rate. Among the 230 cases analyzed, 18 were excluded due to insufficient quantity or quality of DNAs. Then 212 cases were subjected next‐generation sequencing analysis and gene profiling data were obtained for 187 cases (success rate, 81.3%). B, Tumor types of the 187 cases for which gene profiling data were available

Feasibility of the NCC Oncopanel test for 114 cancer‐associated genes in a cohort of Japanese patients with solid tumors who would complete or had completed standard chemotherapy. A, Success rate. Among the 230 cases analyzed, 18 were excluded due to insufficient quantity or quality of DNAs. Then 212 cases were subjected next‐generation sequencing analysis and gene profiling data were obtained for 187 cases (success rate, 81.3%). B, Tumor types of the 187 cases for which gene profiling data were available The 187 cases comprised more than 30 types of tumor. The major tumor types are shown in Figure 1B and listed in Table S2. Sarcoma was the most common tumor type, accounting for 22.5% (n = 42) of cases, followed by non‐small‐cell lung cancer (n = 26, 13.9%), ovarian cancer (n = 12, 6.4%), and pancreatic cancer (n = 10, 5.3%). Notably, 97 cases (51.9%) were rare cancers (defined as those with an incidence rate of fewer than 6 per 100 000 persons per year) (Table S2).

Percentage of cases harboring actionable gene aberrations

At least 1 genetic aberration was detected in 156 of the 187 cases for which gene profiling data were obtained (83.4%) (Figure 2A, detailed data in Table S3). Frequently altered genes were TP53 (40.1%, 75/187), KRAS (15.5%, 29/187), PIK3CA (11.8%, 22/187), and APC (5.3%, 10/187). Notably, EGFR mutations were detected in 6 lung cancer cases that received companion diagnostics for EGFR mutations and 3 of them were judged to be negative. All of these EGFR mutations detected by the NCC Oncopanel test were rare variants not detected by existing companion diagnostics. The NCC Oncopanel test also detected an Asian‐specific polymorphism in BCL2L11/BIM, which is thought to be associated with resistance of lung cancer to epidermal growth factor receptor tyrosine kinase inhibitors.27 The deletion allele conferring resistance was observed in 24 (12.8%) cases, which is consistent with the percentage in the Asian population.28
Figure 2

Utility of the NCC Oncopanel test in a cohort of Japanese patients with solid tumors who would complete or had completed standard chemotherapy. A, Gene aberration detected in 187 cases. Cases are categorized according to maximum evidence for drug selection. The percentage of cases with actionable gene aberrations was calculated taking (or not) into account a high tumor mutational burden (TMB; defined as ≥10 mutations/Mb). B, Percentage of cases with actionable gene aberrations according to tumor type. The number of cases is presented on the graph according to maximum evidence for drug selection

Utility of the NCC Oncopanel test in a cohort of Japanese patients with solid tumors who would complete or had completed standard chemotherapy. A, Gene aberration detected in 187 cases. Cases are categorized according to maximum evidence for drug selection. The percentage of cases with actionable gene aberrations was calculated taking (or not) into account a high tumor mutational burden (TMB; defined as ≥10 mutations/Mb). B, Percentage of cases with actionable gene aberrations according to tumor type. The number of cases is presented on the graph according to maximum evidence for drug selection According to evidence levels 1A‐3A, 109 cases (58.2%) harbored at least 1 actionable gene aberration (Figure 2A). The 156 cases were ranked according to the strongest (maximum) evidence as follows: 14 (7.4%) cases harbored level 1A aberrations; 9 (4.8%) harbored level 1B aberrations; 9 (4.8%) harbored level 2A aberrations; 33 (17.6%) harbored level 2B aberrations; and 44 (23.5%) harbored level 3A aberrations. The other 47 cases harbored level 3B aberrations (n = 25; 13.3%) or level 4 aberrations (n = 22; 11.8%). Next, we examined the percentage of cases with each tumor type (Figure 2B). When the 187 cases were categorized as carcinoma or sarcoma, we found that the percentage of carcinoma cases with actionable gene aberrations was greater than that of sarcoma cases (95/145, 65.5% vs 14/42, 33.3%, respectively). The difference was statistically significant (P = 2.0 × 10−4; χ2 test). In agreement with previous genome‐wide sequencing studies,29, 30, 31 we frequently identified actionable aberrations (>80%) in cases of non‐small‐cell lung cancer, biliary cancer, and breast cancer.

Fraction of cases with a high TMB

To examine the ability of the NCC Oncopanel test to evaluate the TMB, we used the NCC Oncopanel test to examine 20 additional cancer cases in which the TMB had been measured in previous studies by whole exome sequencing.24, 25, 26 We then compared the TMB values generated by the 2 assays. The TMB values (the number of somatic mutations per megabase after subtracting germline variations detected in the corresponding peripheral blood DNA) generated by the NCC Oncopanel test showed a strong correlation (R 2 = 0.98) with those by whole exome sequencing, indicating that the NCC Oncopanel test is more appropriate than other gene panel tests4 as a tool for evaluating the TMB (Figure 3). Among the 187 cases for which gene profiling data were available, 17 (9.1%) showed high TMB values according to a recently proposed threshold (10 or more mutations/Mb).32, 33, 34 These 17 cases included melanoma, non‐small‐cell lung cancer, and colorectal cancer, and are thus consistent with a recent report of tumor types with a high TMB34 (Table S4). In particular, 8 cases with a TMB value of more than 20 mutations/Mb had endogenous or exogenous risk factors linked to a high TMB. Mismatch repair deficiency, an endogenous factor causing a high TMB,34 occurred in 2 of 8 cases that harbored loss of function mutations (a somatic P415 fs mutation and a germline Q341* mutation) in the MSH2 gene. Temozolomide, a mutagenic alkylate agent,35 was used to treat 1 case of glioma and the tumor sample obtained after treatment was subjected to the NCC Oncopanel test. The remaining 4 patients had been considered exposed to exogenous mutagenic factors (ie, UV light and cigarette smoke).36 A prospective clinical trial study showed that a high TMB phenotype (defined by 10 or more mutations/Mb) is a biomarker for responses to immune checkpoint blockade therapy;32 therefore, a high TMB was defined as evidence level 1B for drug selection. Among the 17 high TMB cases, 2 had been judged as negative for original actionable gene aberrations. Thus, taking high TMB into account meant that the fraction of cases with actionable gene aberrations was 59.4% (111/187).
Figure 3

Assessment of tumor mutation burden by the NCC Oncopanel test in a cohort of Japanese patients with solid tumors who had completed standard chemotherapy. Comparison of tumor mutation burden measured by whole exome sequencing vs that by NCC Oncopanel testing. Tumor mutation burden (mutations [Mut]/Mb) was measured in 20 samples assessed previously by whole exome sequencing, and the results were compared. The NCC Oncopanel test assessed matched tumor and nontumor samples. The line y = x is plotted in red

Assessment of tumor mutation burden by the NCC Oncopanel test in a cohort of Japanese patients with solid tumors who had completed standard chemotherapy. Comparison of tumor mutation burden measured by whole exome sequencing vs that by NCC Oncopanel testing. Tumor mutation burden (mutations [Mut]/Mb) was measured in 20 samples assessed previously by whole exome sequencing, and the results were compared. The NCC Oncopanel test assessed matched tumor and nontumor samples. The line y = x is plotted in red Evidence levels 1A‐3A in the Clinical Practice Guidelines for Next Generation Sequencing in Cancer Diagnosis and Treatment9 correspond to evidence levels A‐C in the guidelines published by the Association for Molecular Pathology, ACMG, American Society of Clinical Oncology, and College of American Pathologists.22 Therefore, the same percentage (ie, 59.4%) of cases was also judged as positive for aberrations based on evidence levels A‐C; ie, they had clinically significant gene aberrations.

Drug treatment according to actionable gene aberrations

Drug treatment according to actionable gene aberrations detected by the NCC Oncopanel test was examined as of May 31, 2018, ie, approximately 1 year after enrollment of the last case. In total, 25 (13.4%) cases received molecular‐targeted drugs in accordance with their identified gene aberrations (Table 2). A number of cases (n = 19, 76.0%) received therapy with drugs that were not approved for their particular tumor. Among these, 15 (60.0%) received investigational drugs after enrollment into clinical trials matched to their gene aberrations, and the remaining 4 (16.0%) received kinase inhibitory drugs approved for treatment of different tumor types in Japan (ie, off‐label use). The remaining 6 (24%) cases were prescribed PMDA‐approved molecular‐targeted drugs. By contrast, 86 cases with actionable gene aberrations (including a high TMB) did not receive genomically matched therapies. Among these, 9 cases were dead or had poor performance status at the time that the results were returned. For the majority of the remaining cases (n = 77), there were no available/accessible genomically matched clinical trials or drugs.
Table 2

Cancer cases that received molecular‐targeted therapy according to their actionable gene aberrations (n = 25)

No.TOP‐GEAR IDTumor typeAge (years)GenderAYARare cancerActionable gene aberrationDrugDrug type
15022Ovarian cancer37FYY KRAS mutationPan‐RAF inhibitorInvestigational drug
25025Colorectal cancer69Mnn KRAS mutationPan‐RAF inhibitorInvestigational drug
35010Colorectal cancer44Mnn BRAF mutationPan‐RAF inhibitorInvestigational drug
45058Pancreatic cancer47Mnn KRAS mutationPan‐RAF inhibitorInvestigational drug
55004Pancreatic cancer58Fnn KRAS mutationERK inhibitorInvestigational drug
65054Esophageal carcinoma61Mnn FGFR2 amplificationFGFR2 inhibitorInvestigational drug
75017Soft tissue sarcoma (Malignant cardiac tumor)28FYY MDM2 amplificationHDM2 inhibitorInvestigational drug
85130Soft tissue sarcoma (Liposarcoma)54FnY MDM2 amplificationHDM2 inhibitorInvestigational drug
95076Non‐small‐cell lung cancer67MnnTumor mutation burden highImmunocheckpoint inhibitorInvestigational drug
105160Non‐small‐cell lung cancer42MnnTumor mutation burden highImmunocheckpoint inhibitorInvestigational drug
115078Non‐small‐cell lung cancer67Fnn CCDC6‐RET fusionAlectinibInvestigational drug
125164Breast cancer35FYn HER2 amplificationHER2 ADCInvestigational drug
135215Biliary cancer68Mnn HER2 amplificationHER2 ADCInvestigational drug
145227Tumors of unknown primary site65FnY PIK3CA mutationTORC1/2 inhibitorInvestigational drug
155208Apocrine adenocarcinoma70MnY FGFR2‐CLIP1 fusionFGFR inhibitorInvestigational drug
165060Inflammatory myofibroblastic tumor51MnY CLTC‐ALK fusionAlectinibOff‐label use
175219Mastocytoma39MYY KIT mutationImatinibOff‐label use
185003Non‐small‐cell lung cancer36MYn CCDC6‐RET fusionLenvatinibOff‐label use
195077Histiocytic sarcoma18MYY MAP2K1 mutationTrametinibOff‐label use
205098Non‐small‐cell lung cancer46Mnn EML4‐ALK fusionAlectinibApproved drug
215041Non‐small‐cell lung cancer51Fnn EGFR mutation (p.V769_D770insGQR)AfatinibApproved drug
225162Non‐small‐cell lung cancer54Fnn EGFR mutation (p.E746_T751delinsI)AfatinibApproved drug
235109Non‐small‐cell lung cancer64Fnn EGFR mutation (p.S752_I759del)GefitinibApproved drug
245115Non‐small‐cell lung cancer35MYn CD74‐ROS1 fusionCrizotinibApproved drug
255071Melanoma60MnYTumor mutation burden highNivolumabApproved drug

ADC, antibody‐drug conjugate; AYA, adolescent and young adult (15‐39 years); F, female; FGFR, fibroblast growth factor receptor; HDM2, human double minute 2 homolog; HER2, human epidermal growth factor receptor 2; M, male; TOP‐GEAR, Trial of Onco‐Panel for Gene‐profiling to Estimate both Adverse events and Response during cancer treatment; TORC1/2, target of rapamycin complex 1/2; Y, yes; n, no.

Cancer cases that received molecular‐targeted therapy according to their actionable gene aberrations (n = 25) ADC, antibody‐drug conjugate; AYA, adolescent and young adult (15‐39 years); F, female; FGFR, fibroblast growth factor receptor; HDM2, human double minute 2 homolog; HER2, human epidermal growth factor receptor 2; M, male; TOP‐GEAR, Trial of Onco‐Panel for Gene‐profiling to Estimate both Adverse events and Response during cancer treatment; TORC1/2, target of rapamycin complex 1/2; Y, yes; n, no.

Diagnosis and prognosis based on actionable gene aberrations

The results of gene profiling using the NCC Oncopanel test were also used for diagnosis and prognosis. Germline mutations causing hereditary cancers were identified in 6/187 (3.2%) patients (Table 3). All were defined at evidence level 1 for diagnosis. The diagnoses were as follows: hereditary breast and ovarian cancer based on deleterious BRCA1 or BRCA2 mutations (n = 4), Lynch syndrome based on a deleterious MSH2 mutation (n = 1), and Li‐Fraumeni syndrome based on a deleterious TP53 mutation (n = 1). Subsequently, 3 patients received genetic counseling from Genetic Medicine and Services at NCCH. Two dedifferentiated liposarcomas showed amplification of MDM2, a biomarker (evidence level 2) for diagnosis of this tumor type. Therefore, these results supported pathological diagnosis of these tumors. In addition, a hotspot IDH1 mutation (R132H) was detected in 2 glioma cases. This is a biomarker (evidence level 2) for predicting a good prognosis.
Table 3

Germline mutations detected in 6 patients with solid tumor who had undergone standard chemotherapy

No.TOP‐GEAR IDTumor typeAgeGenderGeneGermline mutation (nucleotide change, effect)ClinVarGenetic counseling
15018Cardiac angiosarcoma38M MSH2 c.C1120T, p.Q374XRCV000076043Done
25126Ovarian cancer48F BRCA1 c.T188A, p.L63XRCV000077499Done
35110Ovarian cancer64F BRCA1 c.4338_4339insAGAA, p.Q1447 fs*16Not yet
45158Breast cancer36F BRCA2 c.5574_5577del, p.I1859 fsRCV000168442Not yet
55019Breast cancer61F BRCA2 c.517‐2A>T, splicingDone
65161Thymic cancer46F TP53 c.833_834insT, p.P278 fsNot yet

–, not registered; F, female; M, male; TOP‐GEAR, Trial of Onco‐Panel for Gene‐profiling to Estimate both Adverse events and Response during cancer treatment.

Germline mutations detected in 6 patients with solid tumor who had undergone standard chemotherapy –, not registered; F, female; M, male; TOP‐GEAR, Trial of Onco‐Panel for Gene‐profiling to Estimate both Adverse events and Response during cancer treatment.

DISCUSSION

Here, we present the results of a prospective study designed to analyze 114 cancer‐related genes using the NCC Oncopanel test. The test, including bioinformatics analysis, was carried out in a quality‐assured laboratory at NCCH. Among the 230 analyzed cases, gene profiling data were obtained for 187 (81.3%). Corresponding peripheral blood DNAs were used to accurately address somatic and germline mutations, as well as TMBs. The 187 samples comprised surgical or biopsy FFPE specimens used in daily clinics and covered more than 30 cancer types, including rare cancers. Approximately half of the specimens (n = 112, 48.7%) were obtained from hospitals in Japan other than NCCH. The success rate was similar to that reported for other gene panel tests undertaken at CLIA‐assured laboratories (80%‐85%)2, 37 in the USA. At least 1 genetic aberration was detected in 83.4% of analyzed cases, and 59.4% had actionable gene aberrations, including a high TMB. This result is also comparable with those reported by prospective studies in the USA that used different gene panel tests; these tests detected actionable gene aberrations in approximately half of cases examined (40%‐60%).3, 38 Thus, we conclude that the NCC Oncopanel test is feasible in the clinical setting in Japan. Reasons for test failure included DNA of low quality/quantity and tissue cross‐contamination. Tissue cross‐contamination was detected in 3.9% of the study samples; this was a major pre‐analytical issue as recently discussed.39 This rate of our study is consistent with a recent report indicating that 3% of cases showed clinically significant (ie, more than 5%) levels of cross‐contamination during routine clinical sequencing.39 In our study, most of the cross‐contaminated tissue samples yielded poor quality and/or low yields of DNA (Table S5). Some tumor samples with poor‐quality DNA also failed due to low read depth. In fact, DNAs from tumor samples stored for long periods (more than 3 years) often yielded poor‐quality DNA; therefore, selecting tumor specimens appropriate for NGS (ie, fresh and large samples) as well as careful laboratory processing is critical for accurate and robust analysis using the NCC Oncopanel test. The percentage of carcinoma cases with actionable gene aberrations related to drug selection was greater (65.5%) than that of sarcoma cases (33.3%). These percentages for all types of tumor will be increased in future by developing drugs that target currently “undruggable” alterations, such as deleterious mutations in SWI/SNF chromatin regulator genes,40, 41, 42 which are detected in tumors such as sarcoma. In addition, we classified several detected mutations in currently druggable genes as “variants of unknown significance” due to lack of biological and clinical evidence. Annotation of those variants of unknown significance will also increase the percentage of patients with detected gene aberrations linked to molecular‐targeted therapy. Aside from identifying druggable gene aberrations, the gene panel test proved useful for diagnosis (6 hereditary tumors and 2 liposarcomas) and prognosis (2 gliomas). Detection of germline mutations in cancer‐predisposing genes provides doctors with valuable information about hereditary cancers. Detection of typical gene aberrations in a few cases facilitated diagnosis or prognosis assessment by treating physicians. The NCC Oncopanel test led to drug treatment according to actionable gene aberrations in 25 cases (13.4%). These included 7 cases of adolescent and young adult (aged 15‐39 years) and rare cancers (Table 2). The prognosis for adolescent and young adult and rare cancers has improved more slowly than that for other groups; therefore, efficient therapeutic regimens for these cancers are needed urgently.43 Drug treatment according to gene panel test results will facilitate development of drugs by promoting drug repositioning and clinical trials. Unfortunately, at present, identification of actionable gene aberrations related to drug selection does not mean that the patient receives treatment with a therapeutic agent specific for his/her aberration. Indeed, there was a large difference between the percentage of patients with actionable gene aberrations (59.4%) and the percentage that received therapy with a drug targeting that aberration (13.4%). Unfortunately, there were no available/accessible genomically matched clinical trials or drugs for the majority of patients with actionable gene aberrations. A recent prospective cohort study in the USA revealed that only 11% of patients receiving the MSK‐IMPACT gene panel test were subsequently enrolled on genomically matched clinical trials.3 The gaps between the number of patients with actionable mutations and those receiving genomically matched therapy indicate the need to develop drugs targeting new genes covering not only druggable kinase genes but also nonkinase genes such as epigenomic and transcriptional regulator genes, which are often mutated in a variety of tumors.1, 44 Developing drugs that target such currently undruggable molecules will be of great help. The NCC Oncopanel test has recently been approved by the PMDA in the SAKIGAKE program of the MHLW45 (OncoGuide NCC Oncopanel System) and will be reimbursed by the national insurance system. After implementation, several challenges will remain. First, the amount of cancer genomic data increases daily; therefore, the significance of gene aberrations with respect to therapy, diagnosis, and prognosis requires continuous re‐evaluation. Clinical oncologists and molecular tumor board members must keep up‐to‐date with information about actionable gene aberrations and investigational drugs. The cancer knowledge database being established by the Center for Cancer Genomics and Advanced Therapeutics at the NCC, Japan, will be a great help (https://www.ncc.go.jp/en/information/2018/0601/index.html). Second, the NCC Oncopanel test analyzes both tumor and nontumor DNA; therefore, germline mutations will be identified. Germline mutations responsible for hereditary disease are present in a small percentage of East Asians.46 Therefore, appropriate annotation of germline mutations and subsequent genetic counseling, coupled with a total care package, must be undertaken by each hospital. Routine performance of gene panel tests will improve patient experiences in oncology clinics and promote drug development.

CONFLICT OF INTEREST

K.S., T.K., and A.O. are recipients of a collaborative research grant from the Sysmex Corporation. The other authors have no conflicts of interest to declare. Click here for additional data file. Click here for additional data file. Click here for additional data file.
  44 in total

1.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

Authors:  Aaron McKenna; Matthew Hanna; Eric Banks; Andrey Sivachenko; Kristian Cibulskis; Andrew Kernytsky; Kiran Garimella; David Altshuler; Stacey Gabriel; Mark Daly; Mark A DePristo
Journal:  Genome Res       Date:  2010-07-19       Impact factor: 9.043

2.  Lack of progress in teen and young adult cancers concerns researchers, prompts study.

Authors:  Charlie Schmidt
Journal:  J Natl Cancer Inst       Date:  2006-12-20       Impact factor: 13.506

3.  A common BIM deletion polymorphism mediates intrinsic resistance and inferior responses to tyrosine kinase inhibitors in cancer.

Authors:  King Pan Ng; Axel M Hillmer; Charles T H Chuah; Wen Chun Juan; Tun Kiat Ko; Audrey S M Teo; Pramila N Ariyaratne; Naoto Takahashi; Kenichi Sawada; Yao Fei; Sheila Soh; Wah Heng Lee; John W J Huang; John C Allen; Xing Yi Woo; Niranjan Nagarajan; Vikrant Kumar; Anbupalam Thalamuthu; Wan Ting Poh; Ai Leen Ang; Hae Tha Mya; Gee Fung How; Li Yi Yang; Liang Piu Koh; Balram Chowbay; Chia-Tien Chang; Veera S Nadarajan; Wee Joo Chng; Hein Than; Lay Cheng Lim; Yeow Tee Goh; Shenli Zhang; Dianne Poh; Patrick Tan; Ju-Ee Seet; Mei-Kim Ang; Noan-Minh Chau; Quan-Sing Ng; Daniel S W Tan; Manabu Soda; Kazutoshi Isobe; Markus M Nöthen; Tien Y Wong; Atif Shahab; Xiaoan Ruan; Valère Cacheux-Rataboul; Wing-Kin Sung; Eng Huat Tan; Yasushi Yatabe; Hiroyuki Mano; Ross A Soo; Tan Min Chin; Wan-Teck Lim; Yijun Ruan; S Tiong Ong
Journal:  Nat Med       Date:  2012-03-18       Impact factor: 53.440

4.  ContEst: estimating cross-contamination of human samples in next-generation sequencing data.

Authors:  Kristian Cibulskis; Aaron McKenna; Tim Fennell; Eric Banks; Mark DePristo; Gad Getz
Journal:  Bioinformatics       Date:  2011-07-29       Impact factor: 6.937

5.  Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing.

Authors:  Garrett M Frampton; Alex Fichtenholtz; Geoff A Otto; Kai Wang; Sean R Downing; Jie He; Michael Schnall-Levin; Jared White; Eric M Sanford; Peter An; James Sun; Frank Juhn; Kristina Brennan; Kiel Iwanik; Ashley Maillet; Jamie Buell; Emily White; Mandy Zhao; Sohail Balasubramanian; Selmira Terzic; Tina Richards; Vera Banning; Lazaro Garcia; Kristen Mahoney; Zac Zwirko; Amy Donahue; Himisha Beltran; Juan Miguel Mosquera; Mark A Rubin; Snjezana Dogan; Cyrus V Hedvat; Michael F Berger; Lajos Pusztai; Matthias Lechner; Chris Boshoff; Mirna Jarosz; Christine Vietz; Alex Parker; Vincent A Miller; Jeffrey S Ross; John Curran; Maureen T Cronin; Philip J Stephens; Doron Lipson; Roman Yelensky
Journal:  Nat Biotechnol       Date:  2013-10-20       Impact factor: 54.908

6.  Integrative genomics viewer.

Authors:  James T Robinson; Helga Thorvaldsdóttir; Wendy Winckler; Mitchell Guttman; Eric S Lander; Gad Getz; Jill P Mesirov
Journal:  Nat Biotechnol       Date:  2011-01       Impact factor: 54.908

7.  COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer.

Authors:  Simon A Forbes; Nidhi Bindal; Sally Bamford; Charlotte Cole; Chai Yin Kok; David Beare; Mingming Jia; Rebecca Shepherd; Kenric Leung; Andrew Menzies; Jon W Teague; Peter J Campbell; Michael R Stratton; P Andrew Futreal
Journal:  Nucleic Acids Res       Date:  2010-10-15       Impact factor: 16.971

8.  Fast and accurate short read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
Journal:  Bioinformatics       Date:  2009-05-18       Impact factor: 6.937

9.  Fast and accurate long-read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
Journal:  Bioinformatics       Date:  2010-01-15       Impact factor: 6.937

10.  Signatures of mutational processes in human cancer.

Authors:  Ludmil B Alexandrov; Serena Nik-Zainal; David C Wedge; Samuel A J R Aparicio; Sam Behjati; Andrew V Biankin; Graham R Bignell; Niccolò Bolli; Ake Borg; Anne-Lise Børresen-Dale; Sandrine Boyault; Birgit Burkhardt; Adam P Butler; Carlos Caldas; Helen R Davies; Christine Desmedt; Roland Eils; Jórunn Erla Eyfjörd; John A Foekens; Mel Greaves; Fumie Hosoda; Barbara Hutter; Tomislav Ilicic; Sandrine Imbeaud; Marcin Imielinski; Marcin Imielinsk; Natalie Jäger; David T W Jones; David Jones; Stian Knappskog; Marcel Kool; Sunil R Lakhani; Carlos López-Otín; Sancha Martin; Nikhil C Munshi; Hiromi Nakamura; Paul A Northcott; Marina Pajic; Elli Papaemmanuil; Angelo Paradiso; John V Pearson; Xose S Puente; Keiran Raine; Manasa Ramakrishna; Andrea L Richardson; Julia Richter; Philip Rosenstiel; Matthias Schlesner; Ton N Schumacher; Paul N Span; Jon W Teague; Yasushi Totoki; Andrew N J Tutt; Rafael Valdés-Mas; Marit M van Buuren; Laura van 't Veer; Anne Vincent-Salomon; Nicola Waddell; Lucy R Yates; Jessica Zucman-Rossi; P Andrew Futreal; Ultan McDermott; Peter Lichter; Matthew Meyerson; Sean M Grimmond; Reiner Siebert; Elías Campo; Tatsuhiro Shibata; Stefan M Pfister; Peter J Campbell; Michael R Stratton
Journal:  Nature       Date:  2013-08-14       Impact factor: 49.962

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  70 in total

Review 1.  Predictive biomarkers for response to immune checkpoint inhibitors in lung cancer: PD-L1 and beyond.

Authors:  Hironori Uruga; Mari Mino-Kenudson
Journal:  Virchows Arch       Date:  2021-01-24       Impact factor: 4.064

2.  Recurrent YAP1-MAML2 and YAP1-NUTM1 fusions in poroma and porocarcinoma.

Authors:  Shigeki Sekine; Tohru Kiyono; Eijitsu Ryo; Reiko Ogawa; Susumu Wakai; Hitoshi Ichikawa; Koyu Suzuki; Satoru Arai; Koji Tsuta; Mitsuaki Ishida; Yuko Sasajima; Naoki Goshima; Naoya Yamazaki; Taisuke Mori
Journal:  J Clin Invest       Date:  2019-05-30       Impact factor: 14.808

3.  Clinical practice guidance for next-generation sequencing in cancer diagnosis and treatment (edition 2.1).

Authors:  Yoichi Naito; Hiroyuki Aburatani; Toraji Amano; Eishi Baba; Toru Furukawa; Tetsu Hayashida; Eiso Hiyama; Sadakatsu Ikeda; Masashi Kanai; Motohiro Kato; Ichiro Kinoshita; Naomi Kiyota; Takashi Kohno; Shinji Kohsaka; Keigo Komine; Itaru Matsumura; Yuji Miura; Yoshiaki Nakamura; Atsushi Natsume; Kazuto Nishio; Katsutoshi Oda; Naoyuki Oda; Natsuko Okita; Kumiko Oseto; Kuniko Sunami; Hideaki Takahashi; Masayuki Takeda; Shimon Tashiro; Shinichi Toyooka; Hideki Ueno; Shinichi Yachida; Takayuki Yoshino; Katsuya Tsuchihara
Journal:  Int J Clin Oncol       Date:  2020-11-29       Impact factor: 3.402

4.  Establishment and characterization of novel patient-derived extraskeletal osteosarcoma cell line NCC-ESOS1-C1.

Authors:  Fumiko Kito; Rieko Oyama; Rei Noguchi; Emi Hattori; Marimu Sakumoto; Makoto Endo; Eisuke Kobayashi; Akihiko Yoshida; Akira Kawai; Tadashi Kondo
Journal:  Hum Cell       Date:  2019-10-17       Impact factor: 4.174

5.  Maternal to fetal transmission of cancer: implications for molecular tumor testing, immune regulation, and pediatric malignancies.

Authors:  Ramez N Eskander; Razelle Kurzrock
Journal:  Med (N Y)       Date:  2021-03-12

Review 6.  Characteristics and Early Diagnosis of Gastric Cancer Discovered after Helicobacter pylori Eradication.

Authors:  Masanori Ito; Shinji Tanaka; Kazuaki Chayama
Journal:  Gut Liver       Date:  2021-05-15       Impact factor: 4.519

7.  BRAF V600E mutation is a potential therapeutic target for a small subset of synovial sarcoma.

Authors:  Sho Watanabe; Akihiko Shimomura; Takashi Kubo; Masaya Sekimizu; Takuji Seo; Shun-Ichi Watanabe; Akira Kawai; Noboru Yamamoto; Kenji Tamura; Takashi Kohno; Hitoshi Ichikawa; Akihiko Yoshida
Journal:  Mod Pathol       Date:  2020-04-01       Impact factor: 7.842

Review 8.  Milestones of Precision Medicine: An Innovative, Multidisciplinary Overview.

Authors:  Jesús García-Foncillas; Jesús Argente; Luis Bujanda; Victoria Cardona; Bonaventura Casanova; Ana Fernández-Montes; José A Horcajadas; Andrés Iñiguez; Alberto Ortiz; José L Pablos; María Vanessa Pérez Gómez
Journal:  Mol Diagn Ther       Date:  2021-07-30       Impact factor: 4.074

9.  Integrative Analysis of Incongruous Cancer Genomics and Proteomics Datasets.

Authors:  Karla Cervantes-Gracia; Richard Chahwan; Holger Husi
Journal:  Methods Mol Biol       Date:  2021

10.  Next-generation genome sequencing of a matched normal-tumor pair from a patient with intractable gestational choriocarcinoma: A case report.

Authors:  Kaoru Niimi; Eiko Yamamoto; Sachi Morita; Maki Morikawa; Hikaru Hattori; Miki Hatakeyama; Mami Morita; Kimihiro Nishino; Yukari Oda; Eri Watanabe; Toshimichi Yamamoto; Hiroaki Kajiyama; Fumitaka Kikkawa
Journal:  Mol Clin Oncol       Date:  2021-05-23
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