BackgroundFirst-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets.ResultsWe used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples.ConclusionsThese results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.

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Summary Somatic mutations in cancer are more frequent in heterochromatic and late-replicating regions of the genome. We report that regional disparities in mutation density are virtually abolished within transcriptionally silent genomic regions of cutaneous squamous cell carcinomas (cSCCs) arising in an XPC−/− background. XPC−/− cells lack global genome nucleotide excision repair (GG-NER), thus establishing differential access of DNA repair machinery within chromatin-rich regions of the genome as the primary cause for the regional disparity. Strikingly, we find that increasing levels of transcription reduce mutation prevalence on both strands of gene bodies embedded within H3K9me3-dense regions, and only to those levels observed in H3K9me3-sparse regions, also in an XPC-dependent manner. Therefore, transcription appears to reduce mutation prevalence specifically by relieving the constraints imposed by chromatin structure on DNA repair. We model this novel relationship between transcription, chromatin state and DNA repair, revealing a new, personalized determinant of cancer risk.

Melanoma is difficult to treat once it becomes metastatic. However, the precise ancestral relationship between primary tumors and their metastases is not well understood. We performed whole-exome sequencing of primary melanomas and multiple matched metastases from eight patients to elucidate their phylogenetic relationships. In six of eight patients, we found that genetically distinct cell populations in the primary tumor metastasized in parallel to different anatomic sites, rather than sequentially from one site to the next. In five of these six patients, the metastasizing cells had themselves arisen from a common parental subpopulation in the primary, indicating that the ability to establish metastases is a late-evolving trait. Interestingly, we discovered that individual metastases were sometimes founded by multiple cell populations of the primary that were genetically distinct. Such establishment of metastases by multiple tumor subpopulations could help explain why identical resistance variants are identified in different sites after initial response to systemic therapy. One primary tumor harbored two subclones with different oncogenic mutations in CTNNB1, which were both propagated to the same metastasis, raising the possibility that activation of wingless-type mouse mammary tumor virus integration site (WNT) signaling may be involved, as has been suggested by experimental models.A s in many other solid tumors, melanoma metastases often first present in lymph nodes in the draining area of the primary, whereas distant metastases tend to appear later (1). The conclusion that melanoma follows a linear progression from primary tumor to regional to distant metastases has supported preemptive surgical removal of regional lymph nodes with curative intent (2). However, several observations suggest that distant metastases are seeded early, contemporaneously with regional metastases. Patients who undergo resection of lymph node basins harboring metastasis do not experience a significantly extended life expectancy (3, 4). Furthermore, circulating melanoma cells were detected in the blood of 26% of patients who only have metastases detected regionally (5, 6).Melanoma, like other cancers, arises and evolves through the accumulation of genetic alterations within tumor cells (7-9). Comparing somatic mutations in primary tumor and regional and distant metastases from the same patient can provide insight into the phylogenetic relationships between these distinct tumor cell populations and the order of metastatic dissemination (8, 10). These analyses may also establish whether cells in the primary tumor that metastasize acquired this ability to disseminate and seed other anatomic sites by a newly acquired genetic alteration, or whether metastatic colonization is simply a stochastic process of which all cells in the primary are capable but few succeed.Using whole-exome sequencing (for discovery) and targeted sequencing (for validation), we analyzed mutation patterns of primary melanomas and two or more metastases in each of e...

Targeted capture massively parallel sequencing is increasingly being used in clinical settings, and as costs continue to decline, use of this technology may become routine in health care. However, a limited amount of tissue has often been a challenge in meeting quality requirements. To offer a practical guideline for the minimum amount of input DNA for targeted sequencing, we optimized and evaluated the performance of targeted sequencing depending on the input DNA amount. First, using various amounts of input DNA, we compared commercially available library construction kits and selected Agilent’s SureSelect-XT and KAPA Biosystems’ Hyper Prep kits as the kits most compatible with targeted deep sequencing using Agilent’s SureSelect custom capture. Then, we optimized the adapter ligation conditions of the Hyper Prep kit to improve library construction efficiency and adapted multiplexed hybrid selection to reduce the cost of sequencing. In this study, we systematically evaluated the performance of the optimized protocol depending on the amount of input DNA, ranging from 6.25 to 200 ng, suggesting the minimal input DNA amounts based on coverage depths required for specific applications.

Background Comparing the microbiome compositions obtained under different physiological conditions has frequently been attempted in recent years to understand the functional influence of microbiomes in the occurrence of various human diseases. Methods In the present work, we analyzed 102 microbiome datasets containing tumor- and normal tissue-derived microbiomes obtained from a total of 51 Korean colorectal cancer (CRC) patients using 16S rRNA amplicon sequencing. Two types of comparisons were used: ‘normal versus (vs.) tumor’ comparison and ‘recurrent vs. nonrecurrent’ comparison, for which the prognosis of patients was retrospectively determined. Results As a result, we observed that in the ‘normal vs. tumor’ comparison, three phyla, Firmicutes, Actinobacteria, and Bacteroidetes, were more abundant in normal tissues, whereas some pathogenic bacteria, including Fusobacterium nucleatum and Bacteroides fragilis, were more abundant in tumor tissues. We also found that bacteria with metabolic pathways related to the production of bacterial motility proteins or bile acid secretion were more enriched in tumor tissues. In addition, the amount of these two pathogenic bacteria was positively correlated with the expression levels of host genes involved in the cell cycle and cell proliferation, confirming the association of microbiomes with tumorigenic pathway genes in the host. Surprisingly, in the ‘recurrent vs. nonrecurrent’ comparison, we observed that these two pathogenic bacteria were more abundant in the patients without recurrence than in the patients with recurrence. The same conclusion was drawn in the analysis of both normal and tumor-derived microbiomes. Conclusions Taken together, it seems that understanding the composition of tissue microbiomes is useful for predicting the prognosis of CRC patients.

Customized gene-panel tests, based on next-generation sequencing, have demonstrated their usefulness in a plethora of clinical settings. As with other clinical diagnostic techniques, gene-panel sequencing for clinical purposes requires precise quality control (QC) measures to ensure its reliability. Only detected variants are currently recorded in clinical reports; however, identifying whether a nondetected variant is a true or false negative is regarded essential in a clinical setting and, thus, a comprehensive QC measure is in demand. Conventional QC metrics, such as mean coverage and uniformity, are considered inadequate for such an evaluation. As such, a more specific measure focused on clinically important variants is herein proposed. In this study, we suggest a new scoring method for assessing the quality of clinical gene-panel sequencing data, specifically for the detection of a set of single-nucleotide variants. The performance of the method was analyzed using 2295 clinical samples (1012 formalin-fixed, paraffin-embedded and 1283 fresh-frozen tissues), and was shown to provide additional information that conventional methods do not show, such as mean depth and uniformity. Customized sequencing protocols, which include QC criteria, have been optimized by each genomic laboratory. The pass rate scoring method proposed in this study provides an appropriate QC response variable for the customized panel, which strengthens the reliability of calls on clinically relevant variants implicated in clinical reports.

BackgroundTarget enrichment is a critical component of targeted deep next-generation sequencing for the cost-effective and sensitive detection of mutations, which is predominantly performed by either hybrid selection or PCR. Despite the advantages of efficient enrichment, PCR-based methods preclude the identification of PCR duplicates and their subsequent removal. Recently, this limitation was overcome by assigning a unique molecular identifier(UMI) to each template molecule. Currently, several commercial library construction kits based on PCR enrichment are available for UMIs, but there have been no systematic studies to compare their performances. In this study, we evaluated and compared the performances of five commercial library kits from four vendors: the Archer® Reveal ctDNA™ 28 Kit, NEBNext Direct® Cancer HotSpot Panel, Nugen Ovation® Custom Target Enrichment System, Qiagen Human Comprehensive Cancer Panel(HCCP), and Qiagen Human Actionable Solid Tumor Panel(HASTP).ResultsWe evaluated and compared the performances of the five kits using 50 ng of genomic DNA for the library construction in terms of the library complexity, coverage uniformity, and errors in the UMIs. While the duplicate rates for all kits were dramatically decreased by identifying unique molecules with UMIs, the Qiagen HASTP achieved the highest library complexity based on the depth of unique coverage indicating superb library construction efficiency. Regarding the coverage uniformity, the kits from Nugen and NEB performed the best followed by the kits from Qiagen. We also analyzed the UMIs, including errors, which allowed us to adjust the depth of unique coverage and the length required for sufficient complexity. Based on these comparisons, we selected the Qiagen HASTP for further performance evaluations. The targeted deep sequencing method based on PCR target enrichment combined with UMI tagging sensitively detected mutations present at a frequency as low as 1% using 6.25 ng of human genomic DNA as the starting material.ConclusionThis study is the first systematic evaluation of commercial library construction kits for PCR-based targeted deep sequencing utilizing UMIs. Because the kits displayed significant variability in different quality metrics, our study offers a practical guideline for researchers to choose appropriate options for PCR-based targeted sequencing and useful benchmark data for evaluating new kits.Electronic supplementary materialThe online version of this article (10.1186/s12864-019-5583-7) contains supplementary material, which is available to authorized users.