Chris Sander

Bio: Chris Sander is an academic researcher from Harvard University. The author has contributed to research in topics: Large Hadron Collider & Protein structure. The author has an hindex of 178, co-authored 713 publications receiving 233287 citations. Previous affiliations of Chris Sander include Purdue University & University of Leeds.

MYC cooperates with AKT in prostate tumorigenesis and alters sensitivity to mTOR inhibitors.

Abstract: MYC and phosphoinositide 3-kinase (PI3K)-pathway deregulation are common in human prostate cancer. Through examination of 194 human prostate tumors, we observed statistically significant co-occurrence of MYC amplification and PI3K-pathway alteration, raising the possibility that these two lesions cooperate in prostate cancer progression. To investigate this, we generated bigenic mice in which both activated human AKT1 and human MYC are expressed in the prostate (MPAKT/Hi-MYC model). In contrast to mice expressing AKT1 alone (MPAKT model) or MYC alone (Hi-MYC model), the bigenic phenotype demonstrates accelerated progression of mouse prostate intraepithelial neoplasia (mPIN) to microinvasive disease with disruption of basement membrane, significant stromal remodeling and infiltration of macrophages, B- and T-lymphocytes, similar to inflammation observed in human prostate tumors. In contrast to the reversibility of mPIN lesions in young MPAKT mice after treatment with mTOR inhibitors, Hi-MYC and bigenic MPAKT/Hi-MYC mice were resistant. Additionally, older MPAKT mice showed reduced sensitivity to mTOR inhibition, suggesting that additional genetic events may dampen mTOR dependence. Since increased MYC expression is an early feature of many human prostate cancers, these data have implications for treatment of human prostate cancers with PI3K-pathway alterations using mTOR inhibitors.

The prediction of protein contacts from multiple sequence alignments.

Abstract: We have studied the question of how much extra predictive power the correlated mutational behaviour of pairs of amino acid residues separated along a sequence has concerning the likelihood of those residues being in contact in the folded protein. The mutational behaviour is deduced from multiple sequence alignments. Our findings are that there is, indeed, some valuable information available from this source and that it is sufficient to make a significant improvement in our ability to predict contacts, when compared with earlier methods that do not take into account the correlations between the mutations. This improvement is approximately twice as large as can be obtained by the more economical method of simply averaging pair preferences over the same sequence alignment. Even when using a method based on pair preferences, a further significant improvement can be made by penalizing more variable regions (on the reasonable assumption that invariant residues are relatively more likely to be in contact), though we have found no way of improving the pair preference method to the extent that it matches the method based on correlated behaviour. Our new method is thought to be the best data-based method of contact prediction developed so far, achieving, on average, an improvement over a random (i.e. information-free) prediction of a factor of five when the number of contacts predicted is chosen to match the number that actually occur.

CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics.

Abstract: CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH and MD Anderson Cancer Center (MDACC). We present CellMinerCDB 1.2 with updates to datasets from NCI-60, Broad Cancer Cell Line Encyclopedia and Sanger/MGH, and the addition of new datasets, including NCI-ALMANAC drug combination, MDACC Cell Line Project proteomic, NCI-SCLC DNA copy number and methylation data, and Broad methylation, genetic dependency and metabolomic datasets. CellMinerCDB (v1.2) includes several improvements over the previously published version: (i) new and updated datasets; (ii) support for pattern comparisons and multivariate analyses across data sources; (iii) updated annotations with drug mechanism of action information and biologically relevant multigene signatures; (iv) analysis speedups via caching; (v) a new dataset download feature; (vi) improved visualization of subsets of multiple tissue types; (vii) breakdown of univariate associations by tissue type; and (viii) enhanced help information. The curation and common annotations (e.g. tissues of origin and identifiers) provided here across pharmacogenomic datasets increase the utility of the individual datasets to address multiple researcher question types, including data reproducibility, biomarker discovery and multivariate analysis of drug activity.

SARS-CoV-2 infects blood monocytes to activate NLRP3 and AIM2 inflammasomes, pyroptosis and cytokine release

Abstract: SARS-CoV-2 causes acute respiratory distress that can progress to multiorgan failure and death in some patients. Although severe COVID-19 disease is linked to exuberant inflammation, how SARS-CoV-2 triggers inflammation is not understood. Monocytes are sentinel blood cells that sense invasive infection to form inflammasomes that activate caspase-1 and gasdermin D (GSDMD) pores, leading to inflammatory death (pyroptosis) and processing and release of IL-1 family cytokines, potent inflammatory mediators. Here we show that ~10% of blood monocytes in COVID-19 patients are dying and infected with SARS-CoV-2. Monocyte infection, which depends on antiviral antibodies, activates NLRP3 and AIM2 inflammasomes, caspase-1 and GSDMD cleavage and relocalization. Signs of pyroptosis (IL-1 family cytokines, LDH) in the plasma correlate with development of severe disease. Moreover, expression quantitative trait loci (eQTLs) linked to higher GSDMD expression increase the risk of severe COVID-19 disease (odds ratio, 1.3, p One sentence summary Antibody-mediated SARS-CoV-2 infection of monocytes activates inflammation and cytokine release.

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

Abstract: The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSIBLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.

Clustal w: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice

Abstract: The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved for the alignment of divergent protein sequences. Firstly, individual weights are assigned to each sequence in a partial alignment in order to down-weight near-duplicate sequences and up-weight the most divergent ones. Secondly, amino acid substitution matrices are varied at different alignment stages according to the divergence of the sequences to be aligned. Thirdly, residue-specific gap penalties and locally reduced gap penalties in hydrophilic regions encourage new gaps in potential loop regions rather than regular secondary structure. Fourthly, positions in early alignments where gaps have been opened receive locally reduced gap penalties to encourage the opening up of new gaps at these positions. These modifications are incorporated into a new program, CLUSTAL W which is freely available.

The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools.

Abstract: CLUSTAL X is a new windows interface for the widely-used progressive multiple sequence alignment program CLUSTAL W. The new system is easy to use, providing an integrated system for performing multiple sequence and profile alignments and analysing the results. CLUSTAL X displays the sequence alignment in a window on the screen. A versatile sequence colouring scheme allows the user to highlight conserved features in the alignment. Pull-down menus provide all the options required for traditional multiple sequence and profile alignment. New features include: the ability to cut-and-paste sequences to change the order of the alignment, selection of a subset of the sequences to be realigned, and selection of a sub-range of the alignment to be realigned and inserted back into the original alignment. Alignment quality analysis can be performed and low-scoring segments or exceptional residues can be highlighted. Quality analysis and realignment of selected residue ranges provide the user with a powerful tool to improve and refine difficult alignments and to trap errors in input sequences. CLUSTAL X has been compiled on SUN Solaris, IRIX5.3 on Silicon Graphics, Digital UNIX on DECstations, Microsoft Windows (32 bit) for PCs, Linux ELF for x86 PCs, and Macintosh PowerMac.

MUSCLE: multiple sequence alignment with high accuracy and high throughput

Abstract: We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using treedependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

Gene Ontology: tool for the unification of biology

Abstract: Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.