Author
Chris Sander
Other affiliations: Purdue University, University of Leeds, Baylor College of Medicine ...read more
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.
Papers published on a yearly basis
Papers
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TL;DR: In this article, the authors measured long-range azimuthal correlations in photonuclear collisions using 1.7 nb$^{-1}$ of 5.02 TeV Pb+Pb collision data collected by the ATLAS experiment at the LHC.
Abstract: Two-particle long-range azimuthal correlations are measured in photonuclear collisions using 1.7 nb$^{-1}$ of 5.02 TeV Pb+Pb collision data collected by the ATLAS experiment at the LHC. Candidate events are selected using a dedicated high-multiplicity photonuclear event trigger, a combination of information from the zero-degree calorimeters and forward calorimeters, and from pseudorapidity gaps constructed using calorimeter energy clusters and charged-particle tracks. Distributions of event properties are compared between data and Monte Carlo simulations of photonuclear processes. Two-particle correlation functions are formed using charged-particle tracks in the selected events, and a template-fitting method is employed to subtract the non-flow contribution to the correlation. Significant nonzero values of the second- and third-order flow coefficients are observed and presented as a function of charged-particle multiplicity and transverse momentum. The results are compared with flow coefficients obtained in proton-proton and proton-lead collisions in similar multiplicity ranges, and with theoretical expectations. The unique initial conditions present in this measurement provide a new way to probe the origin of the collective signatures previously observed only in hadronic collisions.
10 citations
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TL;DR: A comprehensive atlas of genomic alterations is developed that reveals key molecular differences differentiating ILC (FOXA1) from IDC (GATA3) tumorigenesis, a potential therapeutic target for I LC (Akt), and novel ILC subclasses based on underlying biological events.
Abstract: Invasive lobular breast cancer (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of invasive breast tumors. ILC is typically ER+ and beyond the known mutation and/or loss of E-cadherin function, which contributes to a highly discohesive morphology, little is known about the additional mechanisms driving ILC tumorigenesis, or alterations that differentiate ILC from invasive ductal carcinomas (IDC). Methods A dataset of 817 breast tumors from the TCGA Project, including 490 IDC, 127 ILC and 88 samples with a mixed IDC-ILC histology, were profiled on six genomic platforms to develop a comprehensive atlas of mutational, epigenetic, transcriptional and proteomic data. Integrative genomic analyses, both supervised and unsupervised, of ILC tumors and across histological subtypes were performed to identify genomic drivers of ILC oncogenesis. Results Comprehensive multi-platform analyses identified distinct molecular events associated with ILC tumors. As expected, lack of E-cadherin protein, as determined by Reverse Phase Protein Array (RPPA), and CDH1 mRNA expression was uniformly observed in ILC cases associated with distinct alterations targeting CDH1. In addition to previously reported CDH1 and PIK3CA mutations, we identified a number of novel ILC-enriched recurrent mutations targeting PTEN, RUNX1, TBX3, and FOXA1. An increased incidence of PTEN inactivating events, both mutations and copy number changes, were identified in ILC (13%) compared to IDC ER+ (7%), which corresponded with altered PTEN protein expression. These alterations were largely mutually exclusive with PIK3CA mutations and correlate with increased Akt activation as evident by increased Akt phosphorylation (pS473 and pT308), thus identifying a potential therapeutic opportunity for ILC patients. GATA3 signaling, which regulates epithelial cell differentiation, is frequently altered in luminal/ER+ breast cancers. Our analyses determined GATA3 mutations are more frequent in IDC luminal tumors as compared to ILC (19 % vs 5%). ILC luminal tumors show significantly lower GATA3 protein expression, but a higher frequency of mutations in FOXA1 (9% vs 2% in Luminal IDC), a transcription factor required to promote ER transcriptional programs. Within ILC tumors, FOXA1 mutations were found to cluster into a specific region of the Forkhead (FK) DNA binding domain. A broader analysis of FOXA1 mutations in breast and prostate cancer confirm two specific hotspots in the FK domain and the C-terminal transactivation domain. Interestingly, these mutational classes are associated with distinct transcriptional changes suggesting different functional effects. Finally, mRNA-seq analyses identified three robust molecular subclasses that are characterized by distinct genetic, genomic and proteomic patterns, including an increased immune-related group (Class 2), as well as differences in prognosis. Conclusions In this study, we developed a comprehensive atlas of genomic alterations that reveals key molecular differences differentiating ILC (FOXA1) from IDC (GATA3) tumorigenesis, a potential therapeutic target for ILC (Akt), and novel ILC subclasses based on underlying biological events. These findings provide further insight into the molecular heterogeneity of ER+ breast cancer. Citation Format: Giovanni Ciriello, Michael L Gatza, Katherine A Hoadley, Hailei Zhang, Suhn K Rhie, Reanne Bowlby, Matthew D Wilkerson, Cyriac Kandoth, Michael McLellan, Andrew Cherniack, Peter W Laird, Chris Sander, Tari A King, Charles M Perou. Comprehensive molecular characterization of invasive lobular breast tumors [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr S2-04.
9 citations
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TL;DR: In this article, a search for excited electrons produced in pp collisions at root s = 13 TeV via a contact interaction q (q) over bar → ee* is presented.
Abstract: A search for excited electrons produced in pp collisions at root s = 13 TeV via a contact interaction q (q) over bar -> ee* is presented. The search uses 36.1 fb(-1) of data collected in 2015 an ...
9 citations
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TL;DR: Using evolutionary coupling analysis, residue interactions in good agreement with contacts in the crystal structures are inferred, confirming genetic encoding of structural constraints in the selected sequences and opening the door to a new experimental method for the determination of protein structures.
Abstract: Natural evolution encodes rich information about the structure and function of biomolecules in the genetic record. Previously, statistical analysis of co-variation patterns in natural protein families has enabled the accurate computation of 3D structures. Here, we explored whether similar information can be generated by laboratory evolution, starting from a single gene and performing multiple cycles of mutagenesis and functional selection. We evolved two bacterial antibiotic resistance proteins, β-lactamase PSE1 and acetyltransferase AAC6, and obtained hundreds of thousands of diverse functional sequences. Using evolutionary coupling analysis, we inferred residue interactions in good agreement with contacts in the crystal structures, confirming genetic encoding of structural constraints in the selected sequences. Computational protein folding with contact constraints yielded 3D structures with the same fold as that of natural relatives. Evolution experiments combined with inference of residue interactions from sequence information opens the door to a new experimental method for the determination of protein structures.
9 citations
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TL;DR: In a first pan-cancer application, 260 cell lines from the Cancer Cell Line Encyclopaedia and 1914 tumors of six different cancer types from The Cancer Genome Atlas are compared, using weights to emphasize genomic alterations that frequently recur in tumors.
Abstract: Cancer cell lines are often used in laboratory experiments as models of tumors, although they can have substantially different genetic and epigenetic profiles compared to tumors. We have developed a general computational method, TumorComparer, to systematically quantify similarities and differences between tumor material when detailed genetic and molecular profiles are available. The comparisons can be flexibly tailored to a particular biological question by placing a higher weight on functional alterations of interest (weighted similarity). In a first pan-cancer application, we have compared 260 cell lines from the Cancer Cell Line Encyclopaedia (CCLE) and 1914 tumors of six different cancer types from The Cancer Genome Atlas (TCGA), using weights to emphasize genomic alterations that frequently recur in tumors. We report the potential suitability of particular cell lines as tumor models and identify apparently unsuitable outlier cell lines, some of which are in wide use, for each of the six cancer types. In future, this weighted similarity method may be generalized for use in a clinical setting to compare patient profiles consisting of genomic patterns combined with clinical attributes, such as diagnosis, treatment and response to therapy.
9 citations
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TL;DR: 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.
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.
70,111 citations
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TL;DR: The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved and modifications are incorporated into a new program, CLUSTAL W, which is freely available.
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.
63,427 citations
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TL;DR: ClUSTAL X is a new windows interface for the widely-used progressive multiple sequence alignment program CLUSTAL W, providing an integrated system for performing multiple sequence and profile alignments and analysing the results.
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.
38,522 citations
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TL;DR: MUSCLE is a new computer program for creating multiple alignments of protein sequences that includes fast distance estimation using kmer counting, progressive alignment using a new profile function the authors call the log-expectation score, and refinement using tree-dependent restricted partitioning.
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.
37,524 citations
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TL;DR: 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.
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.
35,225 citations