Metastasis, the dissemination and growth of neoplastic cells in an organ distinct from that in which they originated, is the most common cause of death in cancer patients. This is particularly true for pancreatic cancers, where most patients are diagnosed with metastatic disease and few show a sustained response to chemotherapy or radiation therapy. Whether the dismal prognosis of patients with pancreatic cancer compared to patients with other types of cancer is a result of late diagnosis or early dissemination of disease to distant organs is not known. Here we rely on data generated by sequencing the genomes of seven pancreatic cancer metastases to evaluate the clonal relationships among primary and metastatic cancers. We find that clonal populations that give rise to distant metastases are represented within the primary carcinoma, but these clones are genetically evolved from the original parental, non-metastatic clone. Thus, genetic heterogeneity of metastases reflects that within the primary carcinoma. A quantitative analysis of the timing of the genetic evolution of pancreatic cancer was performed, indicating at least a decade between the occurrence of the initiating mutation and the birth of the parental, non-metastatic founder cell. At least five more years are required for the acquisition of metastatic ability and patients die an average of two years thereafter. These data provide novel insights into the genetic features underlying pancreatic cancer progression and define a broad time window of opportunity for early detection to prevent deaths from metastatic disease.

SF-010-4 Distant metastasis occurs late during the genetic evolution of pancreatic cancer

Molecular docking is an established in silico structure-based method widely used in drug discovery. Docking enables the identification of novel compounds of therapeutic interest, predicting ligand-target interactions at a molecular level, or delineating structure-activity relationships (SAR), without knowing a priori the chemical structure of other target modulators. Although it was originally developed to help understanding the mechanisms of molecular recognition between small and large molecules, uses and applications of docking in drug discovery have heavily changed over the last years. In this review, we describe how molecular docking was firstly applied to assist in drug discovery tasks. Then, we illustrate newer and emergent uses and applications of docking, including prediction of adverse effects, polypharmacology, drug repurposing, and target fishing and profiling, discussing also future applications and further potential of this technique when combined with emergent techniques, such as artificial intelligence.

https://www.mdpi.com/1422-0067/20/18/4331/pdf

Molecular Docking: Shifting Paradigms in Drug Discovery.

The Drug-Gene Interaction Database (DGIdb, www.dgidb.org) is a web resource that provides information on drug-gene interactions and druggable genes from publications, databases, and other web-based sources. Drug, gene, and interaction data are normalized and merged into conceptual groups. The information contained in this resource is available to users through a straightforward search interface, an application programming interface (API), and TSV data downloads. DGIdb 4.0 is the latest major version release of this database. A primary focus of this update was integration with crowdsourced efforts, leveraging the Drug Target Commons for community-contributed interaction data, Wikidata to facilitate term normalization, and export to NDEx for drug-gene interaction network representations. Seven new sources have been added since the last major version release, bringing the total number of sources included to 41. Of the previously aggregated sources, 15 have been updated. DGIdb 4.0 also includes improvements to the process of drug normalization and grouping of imported sources. Other notable updates include the introduction of a more sophisticated Query Score for interaction search results, an updated Interaction Score, the inclusion of interaction directionality, and several additional improvements to search features, data releases, licensing documentation and the application framework.

/pdf/integration-of-the-drug-gene-interaction-database-dgidb-4-0-5dy3jioy3j.pdf

Integration of the Drug-Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts.

Head and neck squamous cell carcinoma (HNSCC) is a common, morbid, and frequently lethal malignancy. To uncover its mutational spectrum, we analyzed whole-exome sequencing data from 74 tumor-normal pairs. The majority exhibited a mutational profile consistent with tobacco exposure; human papillomavirus was detectable by sequencing DNA from infected tumors. In addition to identifying previously known HNSCC genes (TP53, CDKN2A, PTEN, PIK3CA, and HRAS), our analysis revealed many genes not previously implicated in this malignancy. At least 30% of cases harbored mutations in genes that regulate squamous differentiation (for example, NOTCH1, IRF6, and TP63), implicating its dysregulation as a major driver of HNSCC carcinogenesis. More generally, the results indicate the ability of large-scale sequencing to reveal fundamental tumorigenic mechanisms.

The Mutational Landscape of Head and Neck Squamous Cell Carcinoma

Limited clinical activity has been seen in osteosarcoma (OS) patients treated with immune checkpoint inhibitors (ICI). To gain insights into the immunogenic potential of these tumors, we conducted whole genome, RNA, and T-cell receptor sequencing, immunohistochemistry and reverse phase protein array profiling (RPPA) on OS specimens from 48 pediatric and adult patients with primary, relapsed, and metastatic OS. Median immune infiltrate level was lower than in other tumor types where ICI are effective, with concomitant low T-cell receptor clonalities. Neoantigen expression in OS was lacking and significantly associated with high levels of nonsense-mediated decay (NMD). Samples with low immune infiltrate had higher number of deleted genes while those with high immune infiltrate expressed higher levels of adaptive resistance pathways. PARP2 expression levels were significantly negatively associated with the immune infiltrate. Together, these data reveal multiple immunosuppressive features of OS and suggest immunotherapeutic opportunities in OS patients. The efficacy of immune checkpoint inhibitors (ICI) in osteosarcoma has been limited. Here, the authors investigate the immunogenomic landscape of osteosarcoma, and integrated analyses highlight features related to a suppressed immune microenvironment.

/pdf/immuno-genomic-landscape-of-osteosarcoma-xtxku2038a.pdf

Immuno-genomic landscape of osteosarcoma

Quality control (QC) for lab-designed primers is crucial for the success of a polymerase chain reaction (PCR). Here, we present MFEprimer-3.0, a functional primer quality control program for checking non-specific amplicons, dimers, hairpins and other parameters. The new features of the current version include: (i) more sensitive binding site search using the updated k-mer algorithm that allows mismatches within the k-mer, except for the first base at the 3' end. The binding sites of each primer with a stable 3' end are listed in the output; (ii) new algorithms for rapidly identifying self-dimers, cross-dimers and hairpins; (iii) the command-line version, which has an added option of JSON output to enhance the versatility of MFEprimer by acting as a QC step in the 'primer design → quality control → redesign' pipeline; (iv) a function for checking whether the binding sites contain single nucleotide polymorphisms (SNPs), which will affect the consistency of binding efficiency among different samples. In summary, MFEprimer-3.0 is updated with the well-tested PCR primer QC program and it can be integrated into various PCR primer design applications as a QC module. The MFEprimer-3.0 server is freely accessible without any login requirement at: https://mfeprimer3.igenetech.com/ and https://www.mfeprimer.com/. The source code for the command-line version is available upon request.

/pdf/mfeprimer-3-0-quality-control-for-pcr-primers-rfp2r7npzc.pdf

MFEprimer-3.0: quality control for PCR primers.

Chromothripsis is a recently observed phenomenon in cancer cells in which one or several chromosomes shatter into pieces with subsequent inaccurate reassembly and clonal propagation. This type of event generates a potentially vast number of mutations within a relatively short-time period, and has been considered as a new paradigm in cancer development. Despite recent advances, much work is still required to better understand the molecular mechanisms of this phenomenon, and thus an easy-to-use tool is in urgent need for automatically detecting and annotating chromothripsis. Here we present CTLPScanner, a web server for detection of chromothripsis-like pattern (CTLP) in genomic array data. The output interface presents intuitive graphical representations of detected chromosome pulverization region, as well as detailed results in table format. CTLPScanner also provides additional information for associated genes in chromothripsis region to help identify the potential candidates involved in tumorigenesis. To assist in performing meta-data analysis, we integrated over 50 000 pre-processed genomic arrays from The Cancer Genome Atlas and Gene Expression Omnibus into CTLPScanner. The server allows users to explore the presence of chromothripsis signatures from public data resources, without carrying out any local data processing. CTLPScanner is freely available at http://cgma.scu.edu.cn/CTLPScanner/.

/pdf/ctlpscanner-a-web-server-for-chromothripsis-like-pattern-29bsd9wcz4.pdf

CTLPScanner: a web server for chromothripsis-like pattern detection

Objectives
Autophagy, a highly conserved lysosomal degradation process in eukaryotic cells, can digest long-lived proteins and damaged organelles through vesicular trafficking pathways. Nowadays, mechanisms of autophagy have been gradually elucidated and thus the discovery of small-molecule drugs targeting autophagy has always been drawing much attention. So far, some autophagy-related web servers have been available online to facilitate scientists to obtain the information relevant to autophagy conveniently, such as HADb, CTLPScanner, iLIR server and ncRDeathDB. However, to the best of our knowledge, there is not any web server available about the autophagy-modulating compounds.

Methods
According to published articles, all the compounds and their relations with autophagy were anatomized. Subsequently, an online Autophagic Compound Database (ACDB) (http://www.acdbliulab.com/) was constructed, which contained information of 357 compounds with 164 corresponding signalling pathways and potential targets in different diseases.

Results
We achieved a great deal of information of autophagy-modulating compounds, including compounds, targets/pathways and diseases. ACDB is a valuable resource for users to access to more than 300 curated small-molecule compounds correlated with autophagy.

Conclusions
Autophagic compound database will facilitate to the discovery of more novel therapeutic drugs in the near future.

/pdf/autophagic-compound-database-a-resource-connecting-autophagy-3prxz3wmd5.pdf

Autophagic compound database: A resource connecting autophagy-modulating compounds, their potential targets and relevant diseases.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide. Somatic copy number alterations (CNAs) play a significant role in the development of this lethal cancer. In this study, we present a meta-analysis of CNAs for a total of 1,395 HNSCC samples. Publicly available R packages and in-house scripts were used for genomic array data processing, including normalization, segmentation and CNA calling. We detected 125 regions of significant gains or losses using GISTIC algorithm and found several potential driver genes in these regions. The incidence of chromothripsis in HNSCC was estimated to be 6%, and the chromosome pulverization hotspot regions were detected. We determined 323 genomic locations significantly enriched for breakpoints, which indicate HNSCC-specific genomic instability regions. Unsupervised clustering of genome-wide CNA data revealed a sub-cluster predominantly composed of nasopharynx tumors and presented a large proportion of HPV-positive samples. These results will facilitate the discovery of therapeutic candidates and extend our molecular understanding of HNSCC.

/pdf/the-landscape-of-somatic-copy-number-alterations-in-head-and-2eg38emwie.pdf

The Landscape of Somatic Copy Number Alterations in Head and Neck Squamous Cell Carcinoma.

Autophagy (macroautophagy) is well known as an evolutionarily conserved lysosomal degradation process for long-lived proteins and damaged organelles. Recently, accumulating evidence has revealed a series of small-molecule compounds that may activate or inhibit autophagy for therapeutic potential on human diseases. However, targeting autophagy for drug discovery still remains in its infancy. In this study, we developed a webserver called Autophagic Compound-Target Prediction (ACTP) (http://actp.liu-lab.com/) that could predict autophagic targets and relevant pathways for a given compound. The flexible docking of submitted small-molecule compound (s) to potential autophagic targets could be performed by backend reverse docking. The webpage would return structure-based scores and relevant pathways for each predicted target. Thus, these results provide a basis for the rapid prediction of potential targets/pathways of possible autophagy-activating or autophagy-inhibiting compounds without labor-intensive experiments. Moreover, ACTP will be helpful to shed light on identifying more novel autophagy-activating or autophagy-inhibiting compounds for future therapeutic implications.

/pdf/actp-a-webserver-for-predicting-potential-targets-and-23n4w8kbif.pdf

Haoyang Cai

Papers

MFEprimer-3.0: quality control for PCR primers.

CTLPScanner: a web server for chromothripsis-like pattern detection

Autophagic compound database: A resource connecting autophagy-modulating compounds, their potential targets and relevant diseases.

The Landscape of Somatic Copy Number Alterations in Head and Neck Squamous Cell Carcinoma.

ACTP: A webserver for predicting potential targets and relevant pathways of autophagy-modulating compounds