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Items: 12

1.

A unique insert in the genomes of high-risk human papillomaviruses with a predicted dual role in conferring oncogenic risk.

Auslander N, Wolf YI, Shabalina SA, Koonin EV.

Version 2. F1000Res. 2019 Jul 2 [revised 2019 Jan 1];8:1000. doi: 10.12688/f1000research.19590.2. eCollection 2019.

2.

In silico learning of tumor evolution through mutational time series.

Auslander N, Wolf YI, Koonin EV.

Proc Natl Acad Sci U S A. 2019 May 7;116(19):9501-9510. doi: 10.1073/pnas.1901695116. Epub 2019 Apr 23.

3.

Predicting Complete Remission of Acute Myeloid Leukemia: Machine Learning Applied to Gene Expression.

Gal O, Auslander N, Fan Y, Meerzaman D.

Cancer Inform. 2019 Mar 15;18:1176935119835544. doi: 10.1177/1176935119835544. eCollection 2019.

4.

Publisher Correction: Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma.

Auslander N, Zhang G, Lee JS, Frederick DT, Miao B, Moll T, Tian T, Wei Z, Madan S, Sullivan RJ, Boland G, Flaherty K, Herlyn M, Ruppin E.

Nat Med. 2018 Dec;24(12):1942. doi: 10.1038/s41591-018-0247-8.

PMID:
30333558
5.

Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma.

Auslander N, Zhang G, Lee JS, Frederick DT, Miao B, Moll T, Tian T, Wei Z, Madan S, Sullivan RJ, Boland G, Flaherty K, Herlyn M, Ruppin E.

Nat Med. 2018 Oct;24(10):1545-1549. doi: 10.1038/s41591-018-0157-9. Epub 2018 Aug 20. Erratum in: Nat Med. 2018 Dec;24(12):1942.

6.

Urea Cycle Dysregulation Generates Clinically Relevant Genomic and Biochemical Signatures.

Lee JS, Adler L, Karathia H, Carmel N, Rabinovich S, Auslander N, Keshet R, Stettner N, Silberman A, Agemy L, Helbling D, Eilam R, Sun Q, Brandis A, Malitsky S, Itkin M, Weiss H, Pinto S, Kalaora S, Levy R, Barnea E, Admon A, Dimmock D, Stern-Ginossar N, Scherz A, Nagamani SCS, Unda M, Wilson DM 3rd, Elhasid R, Carracedo A, Samuels Y, Hannenhalli S, Ruppin E, Erez A.

Cell. 2018 Sep 6;174(6):1559-1570.e22. doi: 10.1016/j.cell.2018.07.019. Epub 2018 Aug 9.

7.

Harnessing synthetic lethality to predict the response to cancer treatment.

Lee JS, Das A, Jerby-Arnon L, Arafeh R, Auslander N, Davidson M, McGarry L, James D, Amzallag A, Park SG, Cheng K, Robinson W, Atias D, Stossel C, Buzhor E, Stein G, Waterfall JJ, Meltzer PS, Golan T, Hannenhalli S, Gottlieb E, Benes CH, Samuels Y, Shanks E, Ruppin E.

Nat Commun. 2018 Jun 29;9(1):2546. doi: 10.1038/s41467-018-04647-1.

8.

An integrated computational and experimental study uncovers FUT9 as a metabolic driver of colorectal cancer.

Auslander N, Cunningham CE, Toosi BM, McEwen EJ, Yizhak K, Vizeacoumar FS, Parameswaran S, Gonen N, Freywald T, Bhanumathy KK, Freywald A, Vizeacoumar FJ, Ruppin E.

Mol Syst Biol. 2017 Dec 1;13(12):956. doi: 10.15252/msb.20177739.

9.

Co-targeting the tumor endothelium and P-selectin-expressing glioblastoma cells leads to a remarkable therapeutic outcome.

Ferber S, Tiram G, Sousa-Herves A, Eldar-Boock A, Krivitsky A, Scomparin A, Yeini E, Ofek P, Ben-Shushan D, Vossen LI, Licha K, Grossman R, Ram Z, Henkin J, Ruppin E, Auslander N, Haag R, Calderón M, Satchi-Fainaro R.

Elife. 2017 Oct 4;6. pii: e25281. doi: 10.7554/eLife.25281.

10.

Chemoradiotherapy Resistance in Colorectal Cancer Cells is Mediated by Wnt/β-catenin Signaling.

Emons G, Spitzner M, Reineke S, Möller J, Auslander N, Kramer F, Hu Y, Beissbarth T, Wolff HA, Rave-Fränk M, Heßmann E, Gaedcke J, Ghadimi BM, Johnsen SA, Ried T, Grade M.

Mol Cancer Res. 2017 Nov;15(11):1481-1490. doi: 10.1158/1541-7786.MCR-17-0205. Epub 2017 Aug 15.

11.

Data-Driven Metabolic Pathway Compositions Enhance Cancer Survival Prediction.

Auslander N, Wagner A, Oberhardt M, Ruppin E.

PLoS Comput Biol. 2016 Sep 27;12(9):e1005125. doi: 10.1371/journal.pcbi.1005125. eCollection 2016 Sep.

12.

A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer.

Auslander N, Yizhak K, Weinstock A, Budhu A, Tang W, Wang XW, Ambs S, Ruppin E.

Sci Rep. 2016 Jul 13;6:29662. doi: 10.1038/srep29662.

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