20.109(F13):Journal club II (Day8)

Logistics of Paper Sign-Up and Presentation

• Once you have decided on a paper for your presentation, please "reserve" it by putting your (initials/lab section/team color) next to the listing here. If you would like to discuss a paper not on the list below, please email it (as .pdf) to 20109.talk AT gmail DOT com with a brief description for approval.
• For visibility, please use the following format to sign up if possible, substituting in your own initials and team color: [ANS/WF/Purple]. Thanks!
• The same paper may be presented by a T/R and a W/F student, but may only be presented once per section.

As you prepare your talk be sure to follow the specific guidelines for oral presentations in this class.

• Please email your finished journal club presentation to 20109.submit AT gmail DOT com no later than 1 pm on the day of your presentation. The order in which your presentations are received will be the order of speakers.
• Both Day 5 and Day 8 presentations will begin at 1:15 pm sharp in room 16-336.may change

Paper Options

The list of papers below is provided as a guideline for the types of papers that might be relevant for your presentation. You are not limited to the primary research articles on this list. The list is provided simply to give you an idea of the kinds of subjects that could make suitable presentations for the class. Search PubMed yourself to find articles of interest to you.

The easiest way to locate each paper is to type the "doi" (digital object identifier) in at the DOI website. If that approach gives you an error for some reason, or in future cases where you might not know the doi, you can try typing the title of your article into PubMed to find it. If you have trouble accessing your article directly from there, go to http://libraries.mit.edu/vera, which is MIT's collection of journals online. Try selecting "exact title" from the search pulldown menu if the name of your journal is a common word such as Science. For older articles, you need to choose the JSTOR rather than Highwire interface.

Cancer Systems Biology

1. Rational engineering of antibody therapeutics targeting multiple oncogene pathways. Fitzgerald J, Lugovskoy A. MAbs. 2011 May-Jun;3(3):299-309. DOI: 10.4161/mabs.3.3.15299
2. Multiscale kinetic modeling of liposomal Doxorubicin delivery quantifies the role of tumor and drug-specific parameters in local delivery to tumors. Hendriks BS, Reynolds JG, Klinz SG, Geretti E, et al. CPT Pharmacometrics Syst Pharmacol. 2012 Nov 21;1:e15. DOI: 10.1038/psp.2012.16
3. Antitumor activity of a novel bispecific antibody that targets the ErbB2/ErbB3 oncogenic unit and inhibits heregulin-induced activation of ErbB3. McDonagh CF, Huhalov A, Harms BD, Adams S, et al. Mol Cancer Ther. 2012 Mar;11(3):582-93. DOI: 10.1158/1535-7163.MCT-11-0820
4. Impact of Tumor HER2/ERBB2 Expression Level on HER2-Targeted Liposomal Doxorubicin-Mediated Drug Delivery: Multiple Low-Affinity Interactions Lead to a Threshold Effect. Hendriks BS, Klinz SG, Reynolds JG, Espelin CW, et al. Mol Cancer Ther. 2013 Sep;12(9):1816-28. DOI: 10.1158/1535-7163.MCT-13-0180
5. Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue. Gerdes MJ, Sevinsky CJ, Sood A, Adak S, et al. Proc Natl Acad Sci U S A. 2013 Jul 16;110(29):11982-7. DOI: 10.1073/pnas.1300136110
6. Fractional proliferation: a method to deconvolve cell population dynamics from single-cell data. Tyson DR, Garbett SP, Frick PL, Quaranta V. Nat Methods. 2012 Sep;9(9):923-8. DOI: 10.1038/nmeth.2138
7. Trait variability of cancer cells quantified by high-content automated microscopy of single cells. Quaranta V, Tyson DR, Garbett SP, Weidow B, et al. Methods Enzymol. 2009;467:23-57. DOI: 10.1016/S0076-6879(09)67002-6
8. Sequential Application of Anticancer Drugs Enhances Cell Death by Rewiring Apoptotic Signaling Networks. Lee MJ, Ye AS, Gardino AK, Heijink AM, et al. Cell. 2012 May 11;149(4):780-94. DOI: 10.1016/j.cell.2012.03.031
9. Profiles of Basal and stimulated receptor signaling networks predict drug response in breast cancer lines. Niepel M, Hafner M, Pace EA, Chung M, et al. Sci Signal. 2013 Sep 24;6(294):ra84. DOI: 10.1126/scisignal.2004379
10. Metrics other than potency reveal systematic variation in responses to cancer drugs. Fallahi-Sichani M, Honarnejad S, Heiser LM, Gray JW, et al. Nat Chem Biol. 2013 Sep 8. DOI: 10.1038/nchembio.1337
11. Subtype and pathway specific responses to anticancer compounds in breast cancer. Heiser LM, Sadanandam A, Kuo WL, Benz SC, et al. Proc Natl Acad Sci U S A. 2012 Feb 21;109(8):2724-9. DOI: 10.1073/pnas.1018854108
12. Basal Subtype and MAPK/ERK Kinase (MEK)-Phosphoinositide 3-Kinase Feedback Signaling Determine Susceptibility of Breast Cancer Cells to MEK Inhibition. Mirzoeva OK, Das D, Heiser LM, Bhattacharya S, et al. Cancer Res. 2009 Jan 15;69(2):565-72. DOI: 10.1158/0008-5472.CAN-08-3389
13. A colorectal cancer classification system that associates cellular phenotype and responses to therapy. Sadanandam A, Lyssiotis CA, Homicsko K, Collisson EA, et al. Nat Med. 2013 May;19(5):619-25. DOI: 10.1038/nm.3175
14. Standardization of epidermal growth factor receptor (EGFR) measurement by quantitative immunofluorescence and impact on antibody-based mutation detection in non-small cell lung cancer. Dimou A, Agarwal S, Anagnostou V, Viray H, et al. Am J Pathol. 2011 Aug;179(2):580-9. DOI: 10.1016/j.ajpath.2011.04.031
15. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Barretina J, Caponigro G, Stransky N, Venkatesan K, et al. Nature. 2012 Mar 28;483(7391):603-7. DOI: 10.1038/nature11003
16. Type-specific cell line models for type-specific ovarian cancer research. Anglesio MS, Wiegand KC, Melnyk N, Chow C, et al. PLoS One. 2013 Sep 4;8(9):e72162. DOI: 10.1371/journal.pone.0072162
17. Evaluating cell lines as tumour models by comparison of genomic profiles. Domcke S, Sinha R, Levine DA, Sander C, Schultz N. Nat Commun. 2013;4:2126. DOI: 10.1038/ncomms3126
18. The receptor AXL diversifies EGFR signaling and limits the response to EGFR-targeted inhibitors in triple-negative breast cancer cells. Meyer AS, Miller MA, Gertler FB, Lauffenburger DA. Sci Signal. 2013 Aug 6;6(287):ra66. DOI: 10.1126/scisignal.2004155
19. Common effector processing mediates cell-specific responses to stimuli. Miller-Jensen K, Janes KA, Brugge JS, Lauffenburger DA. Nature. 2007 Aug 2;448(7153):604-8. DOI:10.1038/nature06001 [MJ/TR/Green]
20. A Systems Model of Signaling Identifies a Molecular Basis Set for Cytokine-Induced Apoptosis. Janes KA, Albeck JG, Gaudet S, Sorger PK, et al. Science. 2005 Dec 9;310(5754):1646-53. DOI: 10.1126/science.1116598

HTS Technologies

1. Tumor cell-specific bioluminescence platform to identify stroma-induced changes to anticancer drug activity. McMillin DW, Delmore J, Weisberg E, Negri JM, et al. Nat Med. 2010 Apr;16(4):483-9. DOI: 10.1038/nm.2112
2. High-throughput Screening Identifies Aclacinomycin as a Radiosensitizer of EGFR-Mutant Non-Small Cell Lung Cancer. Bennett DC, Charest J, Sebolt K, Lehrman M, et al. Transl Oncol. 2013 Jun 1;6(3):382-91. PMID: 23730419
3. Differential Determinants of Cancer Cell Insensitivity to Antimitotic Drugs Discriminated by a One-Step Cell Imaging Assay. Tang Y, Xie T, Florian S, Moerke N, et al. J Biomol Screen. 2013 Jun 20. DOI: 10.1177/1087057113493804
4. Novel split-luciferase-based genetically encoded biosensors for noninvasive visualization of Rho GTPases. Leng W, Pang X, Xia H, Li M, et al. PLoS One. 2013 Apr 16;8(4):e62230. DOI: 10.1371/journal.pone.0062230
5. Identification of novel small molecule inhibitors of adenovirus gene transfer using a high throughput screening approach. Duffy MR, Parker AL, Kalkman ER, White K, et al. J Control Release. 2013 May 20;170(1):132-140. DOI: 10.1016/j.jconrel.2013.05.007
6. Development of a Colorimetric and a Fluorescence Phosphatase-Inhibitor Assay Suitable for Drug Discovery Approaches. Sotoud H, Gribbon P, Ellinger B, Reinshagen J, et al. J Biomol Screen. 2013 Apr 19. DOI: 10.1177/1087057113486000
7. Development of a High-Throughput Fluorescence Polarization DNA Cleavage Assay for the Identification of FEN1 Inhibitors. McWhirter C, Tonge M, Plant H, Hardern I, et al. J Biomol Screen. 2013 Jun;18(5):567-75. DOI: 10.1177/1087057113476551
8. High-throughput molecular imaging for the identification of FADD kinase inhibitors. Khan AP, Schinske KA, Nyati S, Bhojani MS, et al. J Biomol Screen. 2010 Oct;15(9):1063-70. DOI: 10.1177/1087057110380570
9. Bioluminescence-based high-throughput screen identifies pharmacological agents that target neurotransmitter signaling in small cell lung carcinoma. Improgo MR, Johnson CW, Tapper AR, Gardner PD. PLoS One. 2011;6(9):e24132. DOI: 10.1371/journal.pone.0024132
10. Identification of inhibitors of ABCG2 by a bioluminescence imaging-based high-throughput assay. Zhang Y, Byun Y, Ren YR, Liu JO, et al. Cancer Res. 2009 Jul 15;69(14):5867-75. DOI: 10.1158/0008-5472.CAN-08-4866
11. Demonstration of improvements to the bioluminescence resonance energy transfer (BRET) technology for the monitoring of G protein-coupled receptors in live cells. Kocan M, See HB, Seeber RM, Eidne KA, Pfleger KD. J Biomol Screen. 2008 Oct;13(9):888-98. DOI: 10.1177/1087057108324032
12. A high-throughput, homogeneous, bioluminescent assay for Pseudomonas aeruginosa gyrase inhibitors and other DNA-damaging agents. Moir DT, Ming Di, Opperman T, Schweizer HP, Bowlin TL. J Biomol Screen. 2007 Sep;12(6):855-64. Epub 2007 Jul 20. DOI: 10.1177/1087057107304729
13. Identification of selective inhibitors of cancer stem cells by high-throughput screening. Gupta PB, Onder TT, Jiang G, Tao K, et al. Cell. 2009 Aug 21;138(4):645-59. DOI: 10.1016/j.cell.2009.06.034
14. Droplet microfluidic technology for single-cell high-throughput screening. Brouzes E, Medkova M, Savenelli N, Marran D, et al. Proc Natl Acad Sci U S A. 2009 Aug 25;106(34):14195-200. DOI: 10.1073/pnas.0903542106
15. Multiplexed protease activity assay for low-volume clinical samples using droplet-based microfluidics and its application to endometriosis. Chen CH, Miller MA, Sarkar A, Beste MT, et al. J Am Chem Soc. 2013 Feb 6;135(5):1645-8. DOI: 10.1021/ja307866z
16. Proteolytic Activity Matrix Analysis (PrAMA) for simultaneous determination of multiple protease activities. Miller MA, Barkal L, Jeng K, Herrlich A, et al. Integr Biol (Camb). 2011 Apr;3(4):422-38. DOI: 10.1039/c0ib00083c
17. A Multiplexed Fluorescent Assay for Independent Second-Messenger Systems: Decoding GPCR Activation in Living Cells. Tewson PH, Quinn AM, Hughes TE. J Biomol Screen. 2013 Aug;18(7):797-806. DOI: 10.1177/1087057113485427
18. Identification of genes that regulate epithelial cell migration using an siRNA screening approach. Simpson KJ, Selfors LM, Bui J, Reynolds A, et al. Nat Cell Biol. 2008 Sep;10(9):1027-38. DOI: 10.1038/ncb1762
19. A steering model of endothelial sheet migration recapitulates monolayer integrity and directed collective migration. Vitorino P, Hammer M, Kim J, Meyer T. Mol Cell Biol. 2011 Jan;31(2):342-50. DOI: 10.1128/MCB.00800-10
20. Translation of a tumor microenvironment mimicking 3D tumor growth co-culture assay platform to high-content screening. Krausz E, de Hoogt R, Gustin E, Cornelissen F. et al. J Biomol Screen. 2013 Jan;18(1):54-66. DOI: 10.1177/1087057112456874

Day Sign-up

Please put your name under the day you wish to present. There are 9 slots on each day, per lab section. Slot location does not determine speaker order.

Slot	Day 5 (T/R)	Day 8 (T/R)	Day 5 (W/F)	Day 8 (W/F)
1	Hannah Kempton	Carol Davis	Felicia Hsu	Danielle Chow
2	Tiffany Hood	Julie Ramseier	Faith OBrian	Alycia Gardner
3	Jamin Liu		Maryam Zekavat
4	Maria Joh	Prithwis Mukhopadhyay	Hikaru Miyazaki
5	Sophia Li		Jaaron Botello
6			Heejo Choi
7			Chris Omahan
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