A snapshot of 3649 Web-based services published between 1994 and 2017 shows a decrease in availability after 2 years.

BACKGROUND: The long-term availability of online Web services is of utmost importance to ensure reproducibility of analytical results. However, because of lack of maintenance following acceptance, many servers become unavailable after a short period of time. Our aim was to monitor the accessibility and the decay rate of published Web services as well as to determine the factors underlying trends changes. METHODS: We searched PubMed to identify publications containing Web server-related terms published between 1994 and 2017. Automatic and manual screening was used to check the status of each Web service. Kruskall-Wallis, Mann-Whitney and Chi-square tests were used to evaluate various parameters, including availability, accessibility, platform, origin of authors, citation, journal impact factor and publication year. RESULTS: We identified 3649 publications in 375 journals of which 2522 (69%) were currently active. Over 95% of sites were running in the first 2 years, but this rate dropped to 84% in the third year and gradually sank afterwards (P < 1e-16). The mean half-life of Web services is 10.39 years. Working Web services were published in journals with higher impact factors (P = 4.8e-04). Services published before the year 2000 received minimal attention. The citation of offline services was less than for those online (P = 0.022). The majority of Web services provide analytical tools, and the proportion of databases is slowly decreasing. Conclusions. Almost one-third of Web services published to date went out of service. We recommend continued support of Web-based services to increase the reproducibility of published results.

TPMCalculator: one-step software to quantify mRNA abundance of genomic features.

SUMMARY: The quantification of RNA sequencing (RNA-seq) abundance using a normalization method that calculates transcripts per million (TPM) is a key step to compare multiple samples from different experiments. TPMCalculator is a one-step software to process RNA-seq alignments in BAM format and reports TPM values, raw read counts and feature lengths for genes, transcripts, exons and introns. The program describes the genomic features through a model generated from the gene transfer format file used during alignments reporting of the TPM values and the raw read counts for each feature. In this paper, we show the correlation for 1256 samples from the TCGA-BRCA project between TPM and FPKM reported by TPMCalculator and RSeQC. We also show the correlation for raw read counts reported by TPMCalculator, HTSeq and featureCounts. AVAILABILITY AND IMPLEMENTATION: TPMCalculator is freely available at https://github.com/ncbi/TPMCalculator. It is implemented in C++14 and supported on Mac OS X, Linux and MS Windows. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

KRAS driven expression signature has prognostic power superior to mutation status in non-small cell lung cancer.

KRAS is the most frequently mutated oncogene in non-small cell lung cancer (NSCLC). However, the prognostic role of KRAS mutation status in NSCLC still remains controversial. We hypothesize that the expression changes of genes affected by KRAS mutation status will have the most prominent effect and could be used as a prognostic signature in lung cancer. We divided NSCLC patients with mutation and RNA-seq data into KRAS mutated and wild type groups. Mann-Whitney test was used to identify genes showing altered expression between these cohorts. Mean expression of the top five genes was designated as a "transcriptomic fingerprint" of the mutation. We evaluated the effect of this signature on clinical outcome in 2,437 NSCLC patients using univariate and multivariate Cox regression analysis. Mutation of KRAS was most common in adenocarcinoma. Mutation status and KRAS expression were not correlated to prognosis. The transcriptomic fingerprint of KRAS include FOXRED2, KRAS, TOP1, PEX3 and ABL2. The KRAS signature had a high prognostic power. Similar results were achieved when using the second and third set of strongest genes. Moreover, all cutoff values delivered significant prognostic power (p < 0.01). The KRAS signature also remained significant (p < 0.01) in a multivariate analysis including age, gender, smoking history and tumor stage. We generated a "surrogate signature" of KRAS mutation status in NSCLC patients by computationally linking genotype and gene expression. We show that secondary effects of a mutation can have a higher prognostic relevance than the primary genetic alteration itself.

Extrachromosomal DNA Amplification Contributes to Small Cell Lung Cancer Heterogeneity and Is Associated with Worse Outcomes.

Small-cell lung cancer (SCLC) is an aggressive neuroendocrine lung cancer. Oncogenic MYC amplifications drive SCLC heterogeneity, but the genetic mechanisms of MYC amplification and phenotypic plasticity, characterized by neuroendocrine and nonneuroendocrine cell states, are not known. Here, we integrate whole-genome sequencing, long-range optical mapping, single-cell DNA sequencing, and fluorescence in situ hybridization to find extrachromosomal DNA (ecDNA) as a primary source of SCLC oncogene amplifications and driver fusions. ecDNAs bring to proximity enhancer elements and oncogenes, creating SCLC transcription-amplifying units, driving exceptionally high MYC gene dosage. We demonstrate that cell-free nucleosome profiling can noninvasively detect ecDNA amplifications in plasma, facilitating its genome-wide interrogation in SCLC and other cancers. Altogether, our work provides the first comprehensive map of SCLC ecDNA and describes a new mechanism that governs MYC-driven SCLC heterogeneity. ecDNA-enabled transcriptional flexibility may explain the significantly worse survival outcomes of SCLC harboring complex ecDNA amplifications. SIGNIFICANCE: MYC drives SCLC progression, but the genetic basis of MYC-driven SCLC evolution is unknown. Using SCLC as a paradigm, we report how ecDNA amplifications function as MYC-amplifying units, fostering tumor plasticity and a high degree of tumor heterogeneity. This article is highlighted in the In This Issue feature, p. 799.

DNA and RNA Cleavage Complexes and Repair Pathway for TOP3B RNA- and DNA-Protein Crosslinks.

The present study demonstrates that topoisomerase 3B (TOP3B) forms both RNA and DNA cleavage complexes (TOP3Bccs) in vivo and reveals a pathway for repairing TOP3Bccs. For inducing and detecting cellular TOP3Bccs, we engineer a "self-trapping" mutant of TOP3B (R338W-TOP3B). Transfection with R338W-TOP3B induces R-loops, genomic damage, and growth defect, which highlights the importance of TOP3Bcc repair mechanisms. To determine how cells repair TOP3Bccs, we deplete tyrosyl-DNA phosphodiesterases (TDP1 and TDP2). TDP2-deficient cells show elevated TOP3Bccs both in DNA and RNA. Conversely, overexpression of TDP2 lowers cellular TOP3Bccs. Using recombinant human TDP2, we demonstrate that TDP2 can process both denatured and proteolyzed TOP3Bccs. We also show that cellular TOP3Bccs are ubiquitinated by the E3 ligase TRIM41 before undergoing proteasomal processing and excision by TDP2.

Uncovering Potential Therapeutic Targets in Colorectal Cancer by Deciphering Mutational Status and Expression of Druggable Oncogenes.

BACKGROUND: Numerous driver mutations have been identified in colorectal cancer (CRC), but their relevance to the development of targeted therapies remains elusive. The secondary effects of pathogenic driver mutations on downstream signaling pathways offer a potential approach for the identification of therapeutic targets. We aimed to identify differentially expressed genes as potential drug targets linked to driver mutations. METHODS: Somatic mutations and the gene expression data of 582 CRC patients were utilized, incorporating the mutational status of 39,916 and the expression levels of 20,500 genes. To uncover candidate targets, the expression levels of various genes in wild-type and mutant cases for the most frequent disruptive mutations were compared with a Mann-Whitney test. A survival analysis was performed in 2100 patients with transcriptomic gene expression data. Up-regulated genes associated with worse survival were filtered for potentially actionable targets. The most significant hits were validated in an independent set of 171 CRC patients. RESULTS: Altogether, 426 disruptive mutation-associated upregulated genes were identified. Among these, 95 were linked to worse recurrence-free survival (RFS). Based on the druggability filter, 37 potentially actionable targets were revealed. We selected seven genes and validated their expression in 171 patient specimens. The best independently validated combinations were DUSP4 (p = 2.6 × 10-12) in ACVR2A mutated (7.7%) patients; BMP4 (p = 1.6 × 10-04) in SOX9 mutated (8.1%) patients; TRIB2 (p = 1.35 × 10-14) in ACVR2A mutated patients; VSIG4 (p = 2.6 × 10-05) in ANK3 mutated (7.6%) patients, and DUSP4 (p = 7.1 × 10-04) in AMER1 mutated (8.2%) patients. CONCLUSIONS: The results uncovered potentially druggable genes in colorectal cancer. The identified mutations could enable future patient stratification for targeted therapy.

Mutations Defining Patient Cohorts With Elevated PD-L1 Expression in Gastric Cancer.

The immunotherapy agent pembrolizumab has been approved for gastric cancer (GC) patients with recurrent or advanced disease who are PD-L1 positive. Mutations in the primary lesion may drive the expression of immune targets thereby priming the tumor to therapeutic sensitivity. In this study, we aimed to uncover mutations associated with elevated PD-L1 expression in GC patients. Data from 410 GC patients were available, including the mutational spectrum of 39,916 genes and expression values of 20,500 genes. PD-L1 gene expression was compared to the mutational status of each gene separately by using a Mann-Whitney U-test and a Receiver Operating Characteristic test. Only mutations with a prevalence over 5% were considered. Significance was accepted in cases of p < 1E-05 and a fold change over 1.44. Mutations in 209 genes were associated with increased PD-L1 expression. These mutations were enriched in genes related to microtubule-based movement (p = 3.4E-4), cell adhesion (p = 4.9E-4), response to DNA-damage (p = 6.9E-4), and double-strand break-repair (p = 1.6E-3). Mutations in TTK (p = 8.8E-10, AUC = 0.77), COL7A1 (p = 2.0E-9, AUC = 0.74), KIF15 (p = 2.5E-9, AUC = 0.75), and BDP1 (p = 3.3E-9, AUC = 0.74) had the strongest link to elevated PD-L1 expression. Finally, we established a decision tree based on mutations in PIK3CA, MEF2C, SLC11A1, and KIF15 capable to separate patient sub-cohorts with elevated PD-L1 expression. In summary, we identified mutations associated with elevated PD-L1 expression that facilitate the development of better prognostic biomarkers for GC, and might offer insight into the underlying tumor biology.

Enhancer mapping uncovers phenotypic heterogeneity and evolution in patients with luminal breast cancer.

The degree of intrinsic and interpatient phenotypic heterogeneity and its role in tumor evolution is poorly understood. Phenotypic drifts can be transmitted via inheritable transcriptional programs. Cell-type specific transcription is maintained through the activation of epigenetically defined regulatory regions including promoters and enhancers. Here we have annotated the epigenome of 47 primary and metastatic estrogen-receptor (ERα)-positive breast cancer clinical specimens and inferred phenotypic heterogeneity from the regulatory landscape, identifying key regulatory elements commonly shared across patients. Shared regions contain a unique set of regulatory information including the motif for transcription factor YY1. We identify YY1 as a critical determinant of ERα transcriptional activity promoting tumor growth in most luminal patients. YY1 also contributes to the expression of genes mediating resistance to endocrine treatment. Finally, we used H3K27ac levels at active enhancer elements as a surrogate of intra-tumor phenotypic heterogeneity to track the expansion and contraction of phenotypic subpopulations throughout breast cancer progression. By tracking the clonality of SLC9A3R1-positive cells, a bona fide YY1-ERα-regulated gene, we show that endocrine therapies select for phenotypic clones under-represented at diagnosis. Collectively, our data show that epigenetic mechanisms significantly contribute to phenotypic heterogeneity and evolution in systemically treated breast cancer patients.