Tae-jin Ahn

Personalized identification of altered pathways in cancer using accumulated normal tissue data.

Motivation: Identifying altered pathways in an individual is important for understanding disease mechanisms and for the future application of custom therapeutic decisions. Existing pathway analysis techniques are mainly focused on discovering altered pathways between normal and cancer groups and are not suitable for identifying the pathway aberrance that may occur in an individual sample. A simple way to identify individual’s pathway aberrance is to compare normal and tumor data from the same individual. However, the matched normal data from the same individual are often unavailable in clinical situation. Therefore, we suggest a new approach for the personalized identification of altered pathways, making special use of accumulated normal data in cases when a patient’s matched normal data are unavailable. The philosophy behind our method is to quantify the aberrance of an individual samples pathway by comparing it with accumulated normal samples. We propose and examine personalized extensions of pathway statistics, overrepresentation analysis and functional class scoring, to generate individualized pathway aberrance score. Results: Collected microarray data of normal tissue of lung and colon mucosa are served as reference to investigate a number of cancer individuals of lung adenocarcinoma (LUAD) and colon cancer, respectively. Our method concurrently captures known facts of cancer survival pathways and identifies the pathway aberrances that represent cancer differentiation status and survival. It also provides more improved validation rate of survival-related pathways than when a single cancer sample is interpreted in the context of cancer-only cohort. In addition, our method is useful in classifying unknown samples into cancer or normal groups. Particularly, we identified ‘amino acid synthesis and interconversion’ pathway is a good indicator of LUAD (Area Under the Curve (AUC) 0.982 at independent validation). Clinical importance of the method is providing pathway interpretation of single cancer, even though its matched normal data are unavailable. Availability and implementation: The method was implemented using the R software, available at our Web site: http://bibs.snu.ac.kr/ipas. Contact: tspark@stat.snu.ac.kr or namhuh@samsung.com Supplementary information: Supplementary data are available at Bioinformatics online.

No-Reference Compression of Genomic Data Stored in FASTQ Format

In this paper, we propose a system to compress Next Generation Sequencing (NGS) information stored in a FASTQ file. A FASTQ file contains text, DNA read and quality information for millions or billions of reads. The proposed system first parses the FASTQ file into its component fields. In a partial first pass it gathers statistics which are then used to choose a representation for each field that can give the best compression. Text data is further parsed into repeating and variable components and entropy coding is used to compress the latter. Similarly, Markov encoding and repeat finding based methods are used for DNA read compression. Finally, we propose several run length based methods to encode quality data choosing the method that gives the best performance for a given set of quality values. The compression system provides features for loss less and nearly loss less compression as well as compressing only read and read + quality data. We compare its performance to bzip2 text compression utility and an existing benchmark algorithm. We observe that the performance of the proposed system is superior to that of both the systems.

Mutational profiling of brain metastasis from breast cancer: matched pair analysis of targeted sequencing between brain metastasis and primary breast cancer

Although breast cancer is the second most common cause of brain metastasis with a notable increase of incidence, genes that mediate breast cancer brain metastasis (BCBM) are not fully understood. To study the molecular nature of brain metastasis, we performed gene expression profiling of brain metastasis and matched primary breast cancer (BC). We used the Ion AmpliSeq Cancer Panel v2 covering 2,855 mutations from 50 cancer genes to analyze 18 primary BC and 42 BCBM including 15 matched pairs. The most common BCBM subtypes were triple-negative (42.9%) and basal-like (36.6%). In a total of 42 BCBM samples, 32 (76.2%) harbored at least one mutation (median 1, range 0–7 mutations). Frequently detected somatic mutations included TP53 (59.5%), MLH1 (14.3%), PIK3CA (14.3%), and KIT (7.1%). We compared BCBM with patient-matched primary BC specimens. There were no significant differences in mutation profiles between the two groups. Notably, gene expression in BCBM such as TP53, PIK3CA, KIT, MLH1, and RB1 also seemed to be present in primary breast cancers. The TP53 mutation frequency was higher in BCBM than in primary BC (59.5% vs 38.9%, respectively). In conclusion, we found actionable gene alterations in BCBM that were maintained in primary BC. Further studies with functional testing and a delineation of the role of these genes in specific steps of the metastatic process should lead to a better understanding of the biology of metastasis and its susceptibility to treatment.

Patient-derived cell models as preclinical tools for genome-directed targeted therapy

Background In this study, we established patient-derived tumor cell (PDC) models using tissues collected from patients with metastatic cancer and assessed whether these models could be used as a tool for genome-based cancer treatment. Methods PDCs were isolated and cultured from malignant effusions including ascites and pleural fluid. Pathological examination, immunohistochemical analysis, and genomic profiling were performed to compare the histological and genomic features of primary tumors, PDCs. An exploratory gene expression profiling assay was performed to further characterize PDCs. Results From January 2012 to May 2013, 176 samples from patients with metastatic cancer were collected. PDC models were successfully established in 130 (73.6%) samples. The median time from specimen collection to passage 1 (P1) was 3 weeks (range, 0.5–4 weeks), while that from P1 to P2 was 2.5 weeks (range, 0.5–5 weeks). Sixteen paired samples of genomic alterations were highly concordant between each primary tumor and progeny PDCs, with an average variant allele frequency (VAF) correlation of 0.878. We compared genomic profiles of the primary tumor (P0), P1 cells, P2 cells, and patient-derived xenografts (PDXs) derived from P2 cells and found that three samples (P0, P1, and P2 cells) were highly correlated (0.99–1.00). Moreover, PDXs showed more than 100 variants, with correlations of only 0.6–0.8 for the other samples. Drug responses of PDCs were reflective of the clinical response to targeted agents in selected patient PDC lines. Conclusion(s) Our results provided evidence that our PDC model was a promising model for preclinical experiments and closely resembled the patient tumor genome and clinical response.

Fine-Scale Map of Encyclopedia of DNA Elements Regions in the Korean Population

The International HapMap Project aims to generate detailed human genome variation maps by densely genotyping single-nucleotide polymorphisms (SNPs) in CEPH, Chinese, Japanese, and Yoruba samples. This will undoubtedly become an important facility for genetic studies of diseases and complex traits in the four populations. To address how the genetic information contained in such variation maps is transferable to other populations, the Korean government, industries, and academics have launched the Korean HapMap project to genotype high-density Encyclopedia of DNA Elements (ENCODE) regions in 90 Korean individuals. Here we show that the LD pattern, block structure, haplotype diversity, and recombination rate are highly concordant between Korean and the two HapMap Asian samples, particularly Japanese. The availability of information from both Chinese and Japanese samples helps to predict more accurately the possible performance of HapMap markers in Korean disease-gene studies. Tagging SNPs selected from the two HapMap Asian maps, especially the Japanese map, were shown to be very effective for Korean samples. These results demonstrate that the HapMap variation maps are robust in related populations and will serve as an important resource for the studies of the Korean population in particular.

Gene Expression Profiling of Breast Cancer Brain Metastasis

The biology of breast cancer brain metastasis (BCBM) is poorly understood. We aimed to explore genes that are implicated in the process of brain metastasis of primary breast cancer (BC). NanoString nCounter Analysis covering 252 target genes was used for comparison of gene expression levels between 20 primary BCs that relapsed to brain and 41 BCBM samples. PAM50-based intrinsic subtypes such as HER2-enriched and basal-like were clearly over-represented in BCBM. A panel of 22 genes was found to be significantly differentially expressed between primary BC and BCBM. Five of these genes, CXCL12, MMP2, MMP11, VCAM1, and MME, which have previously been associated with tumor progression, angiogenesis, and metastasis, clearly discriminated between primary BC and BCBM. Notably, the five genes were significantly upregulated in primary BC compared to BCBM. Conversely, SOX2 and OLIG2 genes were upregulated in BCBM. These genes may participate in metastatic colonization but not in primary tumor development. Among patient-matched paired samples (n = 17), a PAM50 molecular subtype conversion was observed in eight cases (47.1%), with a trend toward unfavorable subtypes in patients with the distinct gene expression. Our findings, although not conclusive, reveal differentially expressed genes that might mediate the brain metastasis process.

Role of HER2 mutations in refractory metastatic breast cancers: targeted sequencing results in patients with refractory breast cancer

In women with metastatic breast cancer (MBC), introduction of the anti-HER2 (human epidermal growth factor receptor-2) directed therapies including trastuzumab, pertuzumab, lapatinib, and/or trastuzumab-DM1 has markedly improved overall survival. However, not all cases of HER2-positive breast tumours derive similar benefit from HER2-directed therapy, and a significant number of patients experience disease progression because of primary or acquired resistance to anti-HER2-directed therapies. We integrated genomic and clinicopathological analyses in a cohort of patients with refractory breast cancer to anti-HER2 therapies to identify the molecular basis for clinical heterogeneity. To study the molecular basis underlying refractory MBC, we obtained 36 MBC tumours tissues and used next-generation sequencing to investigate the mutational and transcriptional profiles of 83 genes. We focused on HER2 mutational sites and HER2 pathways to identify the roles of HER2 mutations and the HER2 pathway in the refractoriness to anti-HER2 therapies. Analysis using massively parallel sequencing platform, CancerSCAN™, revealed that HER2 mutations were found in six of 36 patients (16.7%). One patient was ER (estrogen receptor)-positive and HER2-negative and the other five HER2 mutated patients were HER2-positive and HR (hormone receptor)-negative. Most importantly, four of these five patients did not show any durable clinical response to HER2-directed therapies. The HER2 pathway score obtained through transcriptional analyses identified that Growth Receptor Biding protein 2 (GRB2) was the most significantly down regulated gene in the HER2 mutated samples. Detection of HER2 mutations using higher deep DNA sequencing may identify a predictive biomarker of resistance to HER2-directed therapy. Functional validation is warranted.

Synthetic lethal screening reveals FGFR as one of the combinatorial targets to overcome resistance to Met-targeted therapy

Met is a receptor tyrosine kinase that promotes cancer progression. In addition, Met has been implicated in resistance of tumors to various targeted therapies such as epidermal growth factor receptor inhibitors in lung cancers, and has been prioritized as a key molecular target for cancer therapy. However, the underlying mechanism of resistance to Met-targeting drugs is poorly understood. Here, we describe screening of 1310 genes to search for key regulators related to drug resistance to an anti-Met therapeutic antibody (SAIT301) by using a small interfering RNA-based synthetic lethal screening method. We found that knockdown of 69 genes in Met-amplified MKN45 cells sensitized the antitumor activity of SAIT301. Pathway analysis of these 69 genes implicated fibroblast growth factor receptor (FGFR) as a key regulator for antiproliferative effects of Met-targeting drugs. Inhibition of FGFR3 increased target cell apoptosis through the suppression of Bcl-xL expression, followed by reduced cancer cell growth in the presence of Met-targeting drugs. Treatment of cells with the FGFR inhibitors substantially restored the efficacy of SAIT301 in SAIT301-resistant cells and enhanced the efficacy in SAIT301-sensitive cells. In addition to FGFR3, integrin β3 is another potential target for combination treatment with SAIT301. Suppression of integrin β3 decreased AKT phosphorylation in SAIT301-resistant cells and restored SAIT301 responsiveness in HCC1954 cells, which are resistant to SAIT301. Gene expression analysis using CCLE database shows that cancer cells with high levels of FGFR and integrin β3 are resistant to crizotinib treatment, suggesting that FGFR and integrin β3 could be used as predictive markers for Met-targeted therapy and provide a potential therapeutic option to overcome acquired and innate resistance for the Met-targeting drugs.

Acquired resistance to LY2874455 in FGFR2 -amplified gastric cancer through an emergence of novel FGFR2-ACSL5 fusion

Background Fibroblast growth factor 2 (FGFR2) amplification, occurring in ~2–9% of gastric cancers (GC), is associated with poor overall survival. Results RNA sequencing identified a novel FGFR2-ACSL5 fusion in the resistant tumor that was absent from the matched pre-treatment tumor. The FGFR2-amplified PDC line was sensitive to FGFR inhibitors whereas the PDC line with concomitant FGFR2 amplification and FGFR2-ACSL5 fusion exhibited resistance. Additionally, the FGFR2-amplified GC PDC line, which was initially sensitive to FGFR2 inhibitors, subsequently also developed resistance. Materials and Methods We identified an FGFR2-amplified patient with GC, who demonstrated a dramatic and long-term response to LY2874455, a pan-FGFR inhibitor, but eventually developed an acquired LY2874455 resistance. Following resistance development, an endoscopic biopsy was performed for transcriptome sequencing and patient-derived tumor cell line (PDC) establishment to elucidate the underlying molecular alterations. Conclusions FGFR inhibitors may function against FGFR2-amplified GC, and a novel FGFR2-ACSL5 fusion identified by transcriptomic characterization may underlie clinically acquired resistance. Implications for Practice Poor treatment response represents a substantial concern in patients with gastric cancer carrying multiple FGFR2 gene copies. Here, we show the utility of a general FGFR inhibitor for initial response prior to treatment resistance and report the first characterization of a potential resistance mechanism involving an FGFR2-ACSL5 fusion protein.

Algorithm for DNA sequence compression based on prediction of mismatch bases and repeat location

For DNA sequence Compression, it has been observed that methods based on Markov modeling and repeats give best results. However, these methods tend to use uniform distribution assumption of mismatches for approximate repeats. We show that these replacements are not uniformly distributed and we can improve compression efficiency by using non uniform distribution for mismatches. We also propose a hash table based method to predict repeat location which works well for block based genomic sequence compression algorithms. The proposed methods give good compression gains. The method can be incorporated into any algorithm that uses approximate repeats to realize similar gains.