Clonal Origin and Lineage Ambiguity in Mixed Neuroendocrine Carcinoma of the Uterine Cervix.

Small-cell neuroendocrine carcinoma (SCNEC) of the cervix is a rare disease characterized by a high incidence of mixed tumors with other types of cancer. The mechanism underlying this mixed phenotype is not well understood. This study established a panel of organoid lines from patients with SCNEC of the cervix and ultimately focused on one line, which retained a mixed tumor phenotype, both in vitro and in vivo. Histologically, both organoids and xenograft tumors showed distinct differentiation into either SCNEC or adenocarcinoma in some regions and ambiguous differentiation in others. Tracking single cells indicated the existence of cells with bipotential differentiation toward SCNEC and adenocarcinomas. Single-cell transcriptional analysis identified three distinct clusters: SCNEC-like, adenocarcinoma-like, and a cluster lacking specific differentiation markers. The expression of neuroendocrine markers was enriched in the SCNEC-like cluster but not exclusively. Human papillomavirus 18 E6 was enriched in the SCNEC-like cluster, which showed higher proliferation and lower levels of the p53 pathway. After treatment with anticancer drugs, the expression of adenocarcinoma markers increased, whereas that of SCNEC decreased. Using a reporter system for keratin 19 expression, changes in the differentiation of each cell were shown to be associated with the shift in differentiation induced by drug treatment. These data suggest that mixed SCNEC/cervical tumors have a clonal origin and are characterized by an ambiguous and flexible differentiation state.

High-throughput screening in colorectal cancer tissue-originated spheroids.

Patient-derived cancer organoid culture is an important live material that reflects clinical heterogeneity. However, the limited amount of organoids available for each case as well as the considerable amount of time and cost to expand in vitro makes it impractical to perform high-throughput drug screening using organoid cultures from multiple patients. Here, we report an advanced system for the high-throughput screening of 2427 drugs using the cancer tissue-originated spheroid (CTOS) method. In this system, we apply the CTOS method in an ex vivo platform from xenograft tumors, using machines to handle CTOS and reagents, and testing a CTOS reference panel of multiple CTOS lines for the hit drugs. CTOS passages in xenograft tumors resulted in minimal changes of morphological and genomic status, and xenograft tumor generation efficiently expanded the number of CTOS to evaluate multiple drugs. Our panel of colorectal cancer CTOS lines exhibited diverse sensitivities to the hit compounds, demonstrating the usefulness of this system for investigating highly heterogeneous disease.

Recent Advances in Liquid Biopsy in Precision Oncology Research.

Liquid biopsy is a minimally invasive test for cancer genetic status based on circulating tumor DNA (ctDNA), circulating tumor cells, or other tumor-derived materials in blood plasma. Although the minimal invasiveness and time resolution are attractive features of liquid biopsy, the limited amount of ctDNA in plasma poses problems. Recent developments in digital PCR and next-generation sequencing (NGS)-based technology have improved the accuracy of liquid biopsy. In particular, molecular barcoding technology in NGS-based methods, i.e., tagging of molecular barcodes to cell-free DNA before amplification, reduces technical errors by validating the consensus of sequences originating from a single molecule, leading to marked improvement of the accuracy and detection limit. However, substitutions caused by DNA damage and somatic mutations originating from normal cells are still obstacles to the sensitive detection of mutations on ctDNA. Since there have been only a few clinical applications, a deeper understanding of ctDNA biology and more advanced analytical technology are needed for the practical application of liquid biopsy.

HLA genotyping by next-generation sequencing of complementary DNA.

BACKGROUND: Genotyping of the human leucocyte antigen (HLA) is indispensable for various medical treatments. However, unambiguous genotyping is technically challenging due to high polymorphism of the corresponding genomic region. Next-generation sequencing is changing the landscape of genotyping. In addition to high throughput of data, its additional advantage is that DNA templates are derived from single molecules, which is a strong merit for the phasing problem. Although most currently developed technologies use genomic DNA, use of cDNA could enable genotyping with reduced costs in data production and analysis. We thus developed an HLA genotyping system based on next-generation sequencing of cDNA. METHODS: Each HLA gene was divided into 3 or 4 target regions subjected to PCR amplification and subsequent sequencing with Ion Torrent PGM. The sequence data were then subjected to an automated analysis. The principle of the analysis was to construct candidate sequences generated from all possible combinations of variable bases and arrange them in decreasing order of the number of reads. Upon collecting candidate sequences from all target regions, 2 haplotypes were usually assigned. Cases not assigned 2 haplotypes were forwarded to 4 additional processes: selection of candidate sequences applying more stringent criteria, removal of artificial haplotypes, selection of candidate sequences with a relaxed threshold for sequence matching, and countermeasure for incomplete sequences in the HLA database. RESULTS: The genotyping system was evaluated using 30 samples; the overall accuracy was 97.0% at the field 3 level and 98.3% at the G group level. With one sample, genotyping of DPB1 was not completed due to short read size. We then developed a method for complete sequencing of individual molecules of the DPB1 gene, using the molecular barcode technology. CONCLUSION: The performance of the automatic genotyping system was comparable to that of systems developed in previous studies. Thus, next-generation sequencing of cDNA is a viable option for HLA genotyping.

Dynamics of circulating tumor DNA represented by the activating and resistant mutations in epidermal growth factor receptor tyrosine kinase inhibitor treatment.

Circulating tumor DNA (ctDNA) is an emerging field of cancer research. For lung cancer, non-invasive genotyping of EGFR is the foremost application. The activating mutations represent the ctDNA from all cancer cells, and the T790M-resistant mutation represents that from resistant cells. We examined the ctDNA dynamics of EGFR mutations by using deep sequencing with a massively parallel DNA sequencer. We obtained 190 plasma samples from 57 patients at various times during the treatment course and classified them according to treatment status. The mutation detection rate of exon 19 deletion/L858R in plasma was high at the initiation of treatment with epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI; P = 0.001), suppressed during EGFR-TKI treatment before disease progression, and elevated after the onset of disease progression (P = 0.023). The mutation detection rate of T790M was low until the onset of disease progression and elevated thereafter (P = 0.01). Samples across the development of disease progression were obtained from 10 patients and showed a correlation between increased ctDNA level and disease progression. Decreased ctDNA level in response to the initiation of EGFR-TKI was observed in 4 of 6 eligible patients. In two patients, the ctDNA dynamics suggested the presence of cancer cell populations only with the T790M mutation. In another patient, the T790M ctDNA represented cell subpopulations that respond to cytotoxic agents differently from the major population. Considering the high incidence, ctDNA could be a clinical parameter to complement information from image analyses.

Diagnostic Accuracy of Noninvasive Genotyping of EGFR in Lung Cancer Patients by Deep Sequencing of Plasma Cell-Free DNA.

BACKGROUND: Genotyping of EGFR (epidermal growth factor receptor) mutations is indispensable for making therapeutic decisions regarding whether to use EGFR tyrosine kinase inhibitors (TKIs) for lung cancer. Because some cases might pose challenges for biopsy, noninvasive genotyping of EGFR in circulating tumor DNA (ctDNA) would be beneficial for lung cancer treatment. METHODS: We developed a detection system for EGFR mutations in ctDNA by use of deep sequencing of plasma DNA. Mutations were searched in >100 000 reads obtained from each exon region. Parameters corresponding to the limit of detection and limit of quantification were used as the thresholds for mutation detection. We conducted a multi-institute prospective study to evaluate the detection system, enrolling 288 non-small cell lung cancer (NSCLC) patients. RESULTS: In evaluating the performance of the detection system, we used the genotyping results from biopsy samples as a comparator: diagnostic sensitivity for exon 19 deletions, 50.9% (95% CI 37.9%-63.9%); diagnostic specificity for exon 19 deletions, 98.0% (88.5%-100%); sensitivity for the L858R mutation, 51.9% (38.7%-64.9%); and specificity for L858R, 94.1% (83.5%-98.6%). The overall sensitivities were as follows: all cases, 54.4% (44.8%-63.7%); stages IA-IIIA, 22.2% (11.5%-38.3%); and stages IIIB-IV, 72.7% (60.9%-82.1%). CONCLUSIONS: Deep sequencing of plasma DNA can be used for genotyping of EGFR in lung cancer patients. In particular, the high specificity of the system may enable a direct recommendation for EGFR-TKI on the basis of positive results with plasma DNA. Because sensitivity was low in early-stage NSCLC, the detection system is preferred for stage IIIB-IV NSCLC.

Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region.

BACKGROUND: O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is reported to be a prognostic and predictive factor of alkylating chemotherapy for glioblastoma patients. Methylation specific PCR (MSP) has been most commonly used when the methylation status of MGMT is assessed. However, technical obstacles have hampered the implementation of MSP-based diagnostic tests. We quantitatively analyzed the methylation status of the entire MGMT promoter region and applied this information for prognostic prediction using sequencing technology. METHODS: Between 1998 and 2012, the genomic DNA of 85 tumor samples from newly diagnosed glioblastoma patients was subjected to bisulfite treatment and subdivided into a training set, consisting of fifty-three samples, and a test set, consisting of thirty-two samples. The training set was analyzed by deep Sanger sequencing with a sequencing coverage of up to 96 clones per sample. This analysis quantitatively revealed the degree of methylation of each cytidine phosphate guanosine (CpG) site. Based on these data, we constructed a prognostic prediction system for glioblastoma patients using a supervised learning method. We then validated this prediction system by deep sequencing with a next-generation sequencer using a test set of 32 samples. RESULTS: The methylation status of the MGMT promoter was correlated with progression-free survival (PFS) in our patient population in the training set. The degree of correlation differed among the CpG sites. Using the data from the top twenty CpG sites, we constructed a prediction system for overall survival (OS) and PFS. The system successfully classified patients into good and poor prognosis groups in both the training set (OS, p = 0.0381; PFS, p = 0.00122) and the test set (OS, p = 0.0476; PFS, p = 0.0376). Conventional MSP could not predict the prognosis in either of our sets. (training set: OS; p = 0.993 PFS; p = 0.113, test set: OS; p = 0.326 PFS; p = 0.342). CONCLUSIONS: The prognostic ability of our prediction system using sequencing data was better than that of methylation-specific PCR (MSP). Advances in sequencing technologies will make this approach a plausible option for diagnoses based on MGMT promotor methylation.

Analytical Performance of a Highly Sensitive System to Detect Gene Variants Using Next-Generation Sequencing for Lung Cancer Companion Diagnostics.

The recent increase in the number of molecular targeted agents for lung cancer has led to the demand for the simultaneous testing of multiple genes. Although gene panels using next-generation sequencing (NGS) are ideal, conventional panels require a high tumor content, and biopsy samples often do not meet this requirement. We developed a new NGS panel, called compact panel, characterized by high sensitivity, with detection limits for mutations of 0.14%, 0.20%, 0.48%, 0.24%, and 0.20% for EGFR exon 19 deletion, L858R, T790M, BRAF V600E, and KRAS G12C, respectively. Mutation detection also had a high quantitative ability, with correlation coefficients ranging from 0.966 to 0.992. The threshold for fusion detection was 1%. The panel exhibited good concordance with the approved tests. The identity rates were as follows: EGFR positive, 100% (95% confidence interval, 95.5-100); EGFR negative, 90.9 (82.2-96.3); BRAF positive, 100 (59.0-100); BRAF negative, 100 (94.9-100); KRAS G12C positive, 100 (92.7-100); KRAS G12C negative, 100 (93.0-100); ALK positive, 96.7 (83.8-99.9); ALK negative, 98.4 (97.2-99.2); ROS1 positive, 100 (66.4-100); ROS1 negative, 99.0 (94.6-100); MET positive, 98.0 (89.0-99.9); MET negative 100 (92.8-100); RET positive, 93.8 (69.8-100); RET negative, 100 (94.9-100). The analytical performance showed that the panel could handle various types of biopsy samples obtained by routine clinical practice without requiring strict pathological monitoring, as in the case of conventional NGS panels.

A strategy for large-scale phosphoproteomics and SRM-based validation of human breast cancer tissue samples.

Protein phosphorylation is a key mechanism of cellular signaling pathways and aberrant phosphorylation has been implicated in a number of human diseases. Thus, approaches in phosphoproteomics can contribute to the identification of key biomarkers to assess disease pathogenesis and drug targets. Moreover, careful validation of large-scale phosphoproteome analysis, which is lacking in the current protein-based biomarker discovery, significantly increases the value of identified biomarkers. Here, we performed large-scale differential phosphoproteome analysis using IMAC coupled with the isobaric tag for relative quantification (iTRAQ) technique and subsequent validation by selected/multiple reaction monitoring (SRM/MRM) of human breast cancer tissues in high- and low-risk recurrence groups. We identified 8309 phosphorylation sites on 3401 proteins, of which 3766 phosphopeptides (1927 phosphoproteins) were able to be quantified and 133 phosphopeptides (117 phosphoproteins) were differentially expressed between the two groups. Among them, 19 phosphopeptides were selected for further verification and 15 were successfully quantified by SRM using stable isotope peptides as a reference. The ratio of phosphopeptides between high- and low-risk groups quantified by SRM was well correlated with iTRAQ-based quantification with a few exceptions. These results suggest that large-scale phosphoproteome quantification coupled with SRM-based validation is a powerful tool for biomarker discovery using clinical samples.

Strategy for SRM-based verification of biomarker candidates discovered by iTRAQ method in limited breast cancer tissue samples.

Since LC-MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications over the past decade, numerous studies have performed relative and/or absolute abundance determinations across large sets of proteins. In this study, we discovered prognostic biomarker candidates from limited breast cancer tissue samples using discovery-through-verification strategy combining iTRAQ method followed by selected reaction monitoring/multiple reaction monitoring analysis (SRM/MRM). We identified and quantified 5122 proteins with high confidence in 18 patient tissue samples (pooled high-risk (n=9) or low-risk (n=9)). A total of 2480 proteins (48.4%) of them were annotated as membrane proteins, 16.1% were plasma membrane and 6.6% were extracellular space proteins by Gene Ontology analysis. Forty-nine proteins with >2-fold differences in two groups were chosen for further analysis and verified in 16 individual tissue samples (high-risk (n=9) or low-risk (n=7)) using SRM/MRM. Twenty-three proteins were differentially expressed among two groups of which MFAP4 and GP2 were further confirmed by Western blotting in 17 tissue samples (high-risk (n=9) or low-risk (n=8)) and Immunohistochemistry (IHC) in 24 tissue samples (high-risk (n=12) or low-risk (n=12)). These results indicate that the combination of iTRAQ and SRM/MRM proteomics will be a powerful tool for identification and verification of candidate protein biomarkers.

Genetic and epigenetic characteristics of human multiple hepatocellular carcinoma.

BACKGROUND: Multiple carcinogenesis is one of the major characteristics of human hepatocellular carcinoma (HCC). The history of multiple tumors, that is, whether they derive from a common precancerous or cancerous ancestor or individually from hepatocytes, is a major clinical issue. Multiple HCC is clinically classified as either intratumor metastasis (IM) or multicentric carcinogenesis (MC). Molecular markers that differentiate IM and MC are of interest to clinical practitioners because the clinical diagnoses of IM and MC often lead to different therapies. METHODS: We analyzed 30 multiple tumors from 15 patients for somatic mutations of cancer-related genes, chromosomal aberrations, and promoter methylation of tumor suppressor genes using techniques such as high-resolution melting, array-comparative genomic hybridization (CGH), and quantitative methylation-specific PCR. RESULTS: Somatic mutations were found in TP53 and CTNNB1 but not in CDKN2A or KRAS. Tumors from the same patient did not share the same mutations. Array-CGH analysis revealed variations in the number of chromosomal aberrations, and the detection of common aberrations in tumors from the same patient was found to depend on the total number of chromosomal aberrations. A promoter methylation analysis of genes revealed dense methylation in HCC but not in the adjacent non-tumor tissue. The correlation coefficients (r) of methylation patterns between tumors from the same patient were more similar than those between tumors from different patients. In total, 47% of tumor samples from the same patients had an r ≥ 0.8, whereas, in contrast, only 18% of tumor samples from different patients had an r ≥ 0.8 (p = 0.01). All IM cases were highly similar; that is, r ≥ 0.8 (p = 0.025). CONCLUSIONS: The overall scarcity of common somatic mutations and chromosomal aberrations suggests that biological IM is likely to be rare. Tumors from the same patient had a methylation pattern that was more similar than those from different patients. As all clinical IM cases exhibited high similarity, the methylation pattern may be applicable to support the clinical diagnosis of IM and MC.

Clinical utility of the 70-gene MammaPrint profile in a Japanese population.

OBJECTIVE: van't Veer and colleagues developed a 70-gene prognosis profile known as MammaPrint to identify breast cancer patients who were at low risk of developing metastases. We evaluated the prognostic value of the 70-gene MammaPrint profile in Japanese women with node-negative breast cancer. METHODS: Frozen tumour samples from 102 eligible node-negative breast cancer patients aged 70 or younger were characterized with the MammaPrint array. The patients were treated with breast-conserving therapy or mastectomy with axillary lymph node dissection between December 1998 and August 2001. About 73 percent received adjuvant hormonal therapy and 28 percent received adjuvant chemotherapy. The gene expression profiles obtained by MammaPrint classified the patients as high- or low-genomic risk. The median follow-up was 7.1 years. RESULTS: Among the 102 patients, 20 (20%) were classified as low-genomic risk and 82 (80%) were classified as high-genomic risk. The probability of distant metastasis-free survival at five years was 100% for the low-risk group and 94% for the high-risk group. CONCLUSIONS: The 70-gene MammaPrint prognosis profile accurately identified Japanese breast cancer patients at low risk of developing recurrences. In fact, 100% of the individuals in the low-risk category remained metastasis-free for the duration of the observation period.

Using gene expression profiling to identify a prognostic molecular spectrum in gliomas.

Histopathological classification of gliomas is often clinically inadequate due to the diversity of tumors that fall within the same class. The goal of the present study was to identify prognostic molecular features in diffusely infiltrating gliomas using gene expression profiling. We selected 3456 genes expressed in gliomas, including 3012 genes found in a gliomal expressed sequence tag collection. The expression levels of these genes in 152 gliomas (100 glioblastomas, 21 anaplastic astrocytomas, 19 diffuse astrocytomas, and 12 anaplastic oligodendrogliomas) were measured using adapter-tagged competitive polymerase chain reaction, a high-throughput reverse transcription-polymerase chain reaction technique. We applied unsupervised and supervised principal component analyses to elucidate the prognostic molecular features of the gliomas. The gene expression data matrix was significantly correlated with the histological grades, oligo-astro histology, and prognosis. Using 110 gliomas, we constructed a prediction model based on the expression profile of 58 genes, resulting in a scheme that reliably classified the glioblastomas into two distinct prognostic subgroups. The model was then tested with another 42 tissues. Multivariate Cox analysis of the glioblastoma patients using other clinical prognostic factors, including age and the extent of surgical resection, indicated that the gene expression profile was a strong and independent prognostic parameter. The gene expression profiling identified clinically informative prognostic molecular features in astrocytic and oligodendroglial tumors that were more reliable than the traditional histological classification scheme.

Quantitative detection of ALK fusion breakpoints in plasma cell-free DNA from patients with non-small cell lung cancer using PCR-based target sequencing with a tiling primer set and two-step mapping/alignment.

BACKGROUND: Tyrosine kinase inhibitors targeted to anaplastic lymphoma kinase (ALK) have been demonstrated to be effective for lung cancer patients with an ALK fusion gene. Application of liquid biopsy, i.e., detection and quantitation of the fusion product in plasma cell-free DNA (cfDNA), could improve clinical practice. To detect ALK fusions, because fusion breakpoints occur somewhere in intron 19 of the ALK gene, sequencing of the entire intron is required to locate breakpoints. RESULTS: We constructed a target sequencing system using an adapter and a set of primers that cover the entire ALK intron 19. This system can amplify fragments, including breakpoints, regardless of fusion partners. The data analysis pipeline firstly detected fusions by alignment to selected target sequences, and then quantitated the fusion alleles aligning to the identified breakpoint sequences. Performance was validated using 20 cfDNA samples from ALK-positive non-small cell lung cancer patients and samples from 10 healthy volunteers. Sensitivity and specificity were 50 and 100%, respectively. CONCLUSIONS: We demonstrated that PCR-based target sequencing using a tiling primer set and two-step mapping/alignment quantitatively detected ALK fusions in cfDNA from lung cancer patients. The system offers an alternative to existing approaches based on hybridization capture.

Intratumor heterogeneity of epidermal growth factor receptor mutations in lung cancer and its correlation to the response to gefitinib.

Somatic mutations introduced into the epidermal growth factor receptor (EGFR) gene in non-small-cell lung cancer (NSCLC) are important factors to determine therapeutic responses to gefitinib. The current diagnostic test measures the overall EGFR mutation status of the cancer tissue, and may ignore the presence of non-mutated, gefitinib-unresponsive cancer cells. Twenty-one NSCLC patients with EGFR mutations were recruited for the study. All patients were treated with gefitinib after surgical treatment. Fifty to sixty areas of NSCLC tumors were sampled from each tissue, and their EGFR mutation states were determined by a primer extension assay. This assay discriminates between EGFR mutation-positive and -negative cancer cells within a single tumor tissue. Fifteen tissues consisted only of cells with EGFR mutations, but the remaining six tissues contained both mutated and non-mutated cells. Time to disease progression and overall survival after gefitinib treatment were significantly shorter in those patients with EGFR heterogeneity (P = 0.009 and P = 0.003, respectively). A considerable proportion of NSCLC contains a heterogeneous population of both EGFR mutated and non-mutated cancer cells, resulting in a reduced response to gefitinib. The intratumor genetic heterogeneity of a target molecule such as EGFR would be an important factor to consider when treating patients with molecular target agents.

Gene expression during the development of experimentally induced cerebral aneurysms.

Cerebral aneurysms are a major cause of subarachnoid hemorrhage, but the mechanism of their development remains unclear. In this study, we investigated candidate genes whose expression is significantly changed during the development of experimentally induced cerebral aneurysms using adaptor-tagged competitive polymerase chain reaction (ATAC-PCR). Twenty-four rats received sham operation (control) or the operation for the induction of experimental cerebral aneurysms. Rats were sacrificed at time 0, 2 weeks, 1 month and 3 months after the operation (n = 6 for each group). RNAs from right anterior cerebral artery/olfactory artery (ACA/OA) bifurcations were assessed via a 191-gene data matrix expression profile by ATAC-PCR. We identified 15 genes whose expression is significantly altered during cerebral aneurysm formation, including major heparan sulfate proteoglycan, cathepsin B, hevin and beta(4)-integrin. We also confirmed protein expression of beta(4)-integrin in rat cerebral aneurysms by quantitative real-time PCR and immunohistochemistry. The ATAC-PCR revealed temporal changes in gene expression during the development of experimental cerebral aneurysms. The genes that were significantly changed in this study would be the candidates for future studies concerning the development of cerebral aneurysms.

Gene expression-based molecular diagnostic system for malignant gliomas is superior to histological diagnosis.

PURPOSE: Current morphology-based glioma classification methods do not adequately reflect the complex biology of gliomas, thus limiting their prognostic ability. In this study, we focused on anaplastic oligodendroglioma and glioblastoma, which typically follow distinct clinical courses. Our goal was to construct a clinically useful molecular diagnostic system based on gene expression profiling. EXPERIMENTAL DESIGN: The expression of 3,456 genes in 32 patients, 12 and 20 of whom had prognostically distinct anaplastic oligodendroglioma and glioblastoma, respectively, was measured by PCR array. Next to unsupervised methods, we did supervised analysis using a weighted voting algorithm to construct a diagnostic system discriminating anaplastic oligodendroglioma from glioblastoma. The diagnostic accuracy of this system was evaluated by leave-one-out cross-validation. The clinical utility was tested on a microarray-based data set of 50 malignant gliomas from a previous study. RESULTS: Unsupervised analysis showed divergent global gene expression patterns between the two tumor classes. A supervised binary classification model showed 100% (95% confidence interval, 89.4-100%) diagnostic accuracy by leave-one-out cross-validation using 168 diagnostic genes. Applied to a gene expression data set from a previous study, our model correlated better with outcome than histologic diagnosis, and also displayed 96.6% (28 of 29) consistency with the molecular classification scheme used for these histologically controversial gliomas in the original article. Furthermore, we observed that histologically diagnosed glioblastoma samples that shared anaplastic oligodendroglioma molecular characteristics tended to be associated with longer survival. CONCLUSIONS: Our molecular diagnostic system showed reproducible clinical utility and prognostic ability superior to traditional histopathologic diagnosis for malignant glioma.

Selective identification of somatic mutations in pancreatic cancer cells through a combination of next-generation sequencing of plasma DNA using molecular barcodes and a bioinformatic variant filter.

The accuracy of next-generation sequencing (NGS) for detecting tumor-specific mutations in plasma DNA is hindered by errors introduced during PCR/sequencing, base substitutions caused by DNA damage, and pre-existing mutations in normal cells that are present at a low frequency. Here, we performed NGS of genes related to pancreatic cancer (comprising 2.8 kb of genomic DNA) in plasma DNA (average 4.5 ng) using molecular barcodes. The average number of sequenced molecules was 900, and the sequencing depth per molecule was 100 or more. We also developed a bioinformatic variant filter, called CV78, to remove variants that were not considered to be tumor-specific, i.e., those that are either absent or occur at low frequencies in the Catalogue of Somatic Mutations in Cancer database. In a cohort comprising 57 pancreatic cancer patients and 12 healthy individuals, sequencing initially identified variants in 31 (54%) and 5 (42%), respectively, whereas after applying the CV78 filter, 19 (33%) and zero were variant-positive. In a validation cohort consisting of 86 patients with pancreatic cancer and 20 patients with intraductal papillary mucinous neoplasm (IPMN), 62 (72%) with pancreatic cancer patients and 10 (50%) IPMN patients were initially variant positive. After CV78 filtering, these values were reduced to 32 (37%) and 1 (5%), respectively. The variant allele frequency of filtered variants in plasma ranged from 0.25% to 76.1%. Therefore, combining NGS and molecular barcodes with subsequent filtering is likely to eliminate most non-tumor-specific mutations.

A novel technique for measuring variations in DNA copy-number: competitive genomic polymerase chain reaction.

BACKGROUND: Changes in genomic copy number occur in many human diseases including cancer. Characterization of these changes is important for both basic understanding and diagnosis of these diseases. Microarrays have recently become the standard technique and are commercially available. However, it is useful to have an affordable technique to complement them. RESULTS: We describe a novel polymerase chain reaction (PCR)-based technique, termed competitive genomic PCR (CGP). The main characteristic of CGP is that different adaptors are added to the sample and control genomic DNAs after appropriate restriction enzyme digestion. These adaptor-supplemented DNAs are subjected to competitive PCR using an adaptor-primer and a locus-specific primer. The amplified products are then separated according to size differences between the adaptors. CGP eliminates the tedious steps inherent in quantitative PCR and achieves moderate throughput. Assays with different X chromosome numbers showed that it can provide accurate quantification. High-resolution analysis of neuroblastoma cell lines around the MYCN locus revealed novel junctions for amplification, which were not detected by a commercial array. CONCLUSION: CGP is a moderate throughput technique for analyzing changes in genomic copy numbers. Because CGP can measure any genomic locus using PCR primers, it is especially useful for detailed analysis of a genomic region of interest.

Prognostic factors for gefitinib-treated postoperative recurrence in non-small cell lung cancer.

BACKGROUND AND OBJECTIVES: The association between epidermal growth factor receptor (EGFR) mutations and response to EGFR tyrosine kinase inhibitor (TKI) has been consistently confirmed in a number of studies. However, it is still unclear whether a response to TKI treatment translates into increased survival for patients with non-small cell lung cancer (NSCLC). METHODS: EGFR mutations were analyzed in 169 primary lung cancer tissues by RT-PCR and sequencing of multiple clones. The association between EGFR mutation status and the clinical outcome of gefitinib treatment was investigated. For mutation-positive cases, the percentage of mutated clones from the total number of clones was calculated. This ratio was used as the quantitative index of EGFR mutations. RESULTS: We identified mutations in 71 of 169 patients with NSCLC. 46 patients were treated with gefitinib for postoperative recurrence. Progression-free survival and overall survival after initial gefitinib were significantly longer in patients with mutation than with wild type (univariate analysis, p < 0.001 for both). Multivariate analyses identified EGFR mutations and longer disease-free intervals after surgery as significant prognostic factors for survival. By quantitative analysis of mutation-positive cases, the increased ratio of mutated EGFR transcripts significantly associated with longer survival after gefitinib. CONCLUSIONS: EGFR mutation status and disease-free interval were associated with prolonged progression-free survival and overall survival after gefitinib treatment for postoperative recurrence of NSCLC. Quantitative analysis of mutated EGFR transcripts provided additional information for the stratification of patients with mutated EGFR.