dataesr/scientific-paragraphs-categorization huggingface dataset:
For intrinsic subtype classification, we carried out the following analysis: for luminal genes, ESR1 and PGR1 presented a bimodal distribution. We used package mclust to fit a mixture of normal distributions with two components and obtain the posterior probability that each patient belongs to the luminal low and luminal high components. A patient was considered luminal low if the posterior probability of belonging to this group was 480%. The same criterion was used for luminal high. When a patient was neither luminal high nor luminal low, it was considered luminal intermediate. Proliferation status (Prol) and ERBB2 expression did not present a bimodal distribution. Therefore, half of the patients with lowest mean values were considered proliferation low. The rest were considered proliferation high.
After defining high and low populations for each parameter, the subtypes were constructed as follows: luminal A: For Curtis data set patients, RNA was extracted from 1,980 tumours as described  3. RNA hybridizations were performed using Illumina HT-12 v3 platform and analysed using the bioconductor bead array package  67. The BASH algorithm  68  was applied to correct for spatial artefacts in the arrays. Bead-level data were summarized and re-annotated as described in ref. 3. Log-intensity values for PML expression were scaled to z scores. Probe selection was performed on the basis of probe quality, 3 0 -position, no other genomic matches and no single-nucleotide polymorphisms in the region. On the basis of these criteria, PML probe ILMN_1731299 was selected for analysis. Survival analysis was done using as endpoints MFS at 5 years (distant metastasis as event).
Two groups were compared using mean PML expression values as the cutoff between PML high and low. We used the log-rank test as implemented in the survival R package  69. For therapy response analysis, publicly available data sets (GSE22093 and GSE23988) were downloaded from Gene Expression Omnibus (GEO), and subjected to background correction, log 2 transformation and quartile normalization. For correlation analysis with STAT3 signatures, gene sets were extracted (ref. 37, and http://software. broadinstitute. org/gsea/msigdb/cards/V$STAT3_01) and average signal value in the MSK/EMC data set was calculated. These values were used to perform the correlation analysis with PML signal values (Pearson correlation). No statistics were applied to determine sample size. The experiments were not randomized.
(h,i) Representative western blot out of three independent experiments depicting the downregulation of SOX9 protein upon PML silencing (h) and 150 nM ATO treatment (i) in PDX44 cells. (j) PML and SOX9 immunoreactivity assed by immunohistochemistry in a panel of PDX samples (Table1). (k) SOX9 immunoreactivity in patient biopsies with varying expression of PML in the Marseille cohort (n ¼ 737). (l) Cluster score of DNA-binding proteins in SOX9 promoter region using ENCODE database. (m) SOX9 promoter region abundance in chromatin immunoprecipitation (ChIP) of exogenous HA-PMLIV using HA-tag antibody in MDA-MB-231 cells after induction with 50 ng ml À 1 doxycycline for 3 days (n ¼ 4). Data were normalized to IgG (negative-binding control). Error bars represent s. e. m. , P value (*Po0. 05, **Po0.
Acknowledgements Apologies to those whose related publications were not cited due to space limitations. We thank  Dr Miquel Angel Pujana  for insightful discussions,  Dr Monika Gonza  ´lez for technical help,  Dr Miriam Ra  ´bano for technical help with flow cytometry cell sorting and  Dr Aleix Prat  for the evaluation of the intrinsic subtypes in PDX. The work of A. C. is supported by the  Ramon y Cajal award , the  Basque Department of Industry, Tourism and Trade (Etortek) ,  Health  (2012111086) and Education ( PI2012-03 ),  Marie Curie  ( 277043 ),  Movember Foundation  ( GAP1 ),  ISCIII  ( PI10/01484 ,  PI13/00031 ),  FERO (VIII Fellowship)  and  ERC  ( 336343 ). N. M. -M. and P. A. are supported by the  Spanish Association Against Cancer (AECC) ,  AECC JP Vizcaya and Guipuzcoa , respectively.
In addition, recent advances in management of classical cytotoxic agents underline the possibility to administrate the three cytotoxic drugs as first-line of colorectal cancer treatment  [14, 15]. While all these treatments improve overall survival, the optimal sequence of therapy still needs to be determined. Anti-EGFR therapy was first designed for patients who developed resistance to chemotherapy, explaining why it is frequently used as second or third-line. In such case it is not known if a previous antiangiogenic administration could modify the efficacy of anti-EGFR therapy. To address this question, we used our patients' database treated for a metastatic colorectal cancer, with a restriction to population with current approval for anti-EGFR therapy, i. e. KRAS and NRAS wild type population.
Patients' characteristics We selected 198 patients who received cetuximab or panitumumab as second or third-line therapy for mCRC from our cohort treated at Georges Francois Leclerc Cancer Center. We completed KRAS and NRAS genotyping for all patients and retained 128 patients with wild type status for KRAS and NRAS genes. Of these patients, 76 (59%) received bevacizumab based chemotherapy during the first-line therapy for metastatic disease. Patients and tumors characteristics are shown in Table  1. We did not observe significant difference between the two groups of patients who received bevacizumab or not in first-line for the main clinical and biological characteristics, except for age which was significantly younger in the non-bevacizumab group (59 vs 66 years, P = 0. 02). Median follow-up at the data cut-off point was 24 months in bevacizumab group and 28 months in chemotherapy group.
DISCUSSION Patients with metastatic colorectal cancer treated with anti-EGFR with or without chemotherapy usually develop resistance within 6 to 12 months after the beginning of the therapy. However, very few studies evaluate the importance of a previous treatment on the efficacy of anti-EGFR therapy. In our retrospective database, we observed that a previous anti-VEGF therapy decreases anti-EGFR efficacy in metastatic colorectal cancer with a wild type status for KRAS and NRAS genes. Patients treated with bevacizumab before anti-EGFR therapy had a poorer PFS on anti-EGFR therapy compared to patients without a previous anti-VEGF therapy. However, no difference was observed on OS. VEGFR and EGFR are membrane receptors involved in two independent signaling pathways with specific ligands and specific downstream pathways but are however closely interconnected.
Patients and methods We used our database of 399 patients treated for a metastatic colorectal cancer at Georges Francois Leclerc Cancer Center from January 2001 to December 2013. In this database we selected all patients (198) treated as second or third-line by cetuximab or panitumumab alone or in association with chemotherapy. We completed molecular biology testing if not performed previously and tested tissue samples for KRAS (exons 2, 3 and 4), NRAS (exons 2, 3 and 4). We only included 128 patients treated with anti-EGFR therapy with a KRAS and NRAS wild type status. The following data were collected and analyzed: age, performance status (according to WHO criteria) at the time of the first cycle, gender, primary tumor site (colon or rectum), localization of metastatic sites, previous anticancer drugs received, CEA and Lactate Deshydrogenase (LDH), Alkaline Phosphatase level and leukocytes count at the time of the first cycle, the type of chemotherapy used with anti-EGFR chemotherapies.
Clinical data statistical analysis All patients were followed up until death or the end of data recording (December 31st 2013). Progression free survival on anti-EGFR therapy was calculated from the date when the therapy started to the date of disease progression, and overall survival was calculated from the date of the beginning of treatment for the metastatic disease to the date of death. Median follow-up with its 95% confidence interval (CI) was calculated using the reverse Kaplan-Meier method. Patient or disease characteristics were examined using the Chi2 test or Fisher's exact test for qualitative variables, and the Student t or Mann-Whitney tests for continuous variables, as appropriate to compare the group of patient treated with bevacizumab in first line or not. Survival probabilities were estimated using the Kaplan-Meier method and survival curves were compared using the log-rank test.
A multivariate Cox model was used to estimate the effects of a previous bevacizumab regimen on progression free survival and on overall survival after adjusting with clinical parameters selected in univariate analysis. In the multivariate model only variable with p < 0. 1 in the univariate model were retained. The level of significance to retain a variable was set at p < 0. 05. Statistical analyses were performed using MedCalc Software. All tests were two sided, and P values < 0. 05 were considered statistically significant.
Materials and Methods Cell lines and cell culture DA3-TM mouse mammary tumor cells transfected with, and expressing cDNA coding for fulllength MUC1-TM  [17] , DA3-PAR non-transfected parental DA3 cells  [17] , human breast carcinoma cell lines T47D and ZR75  [17] , and human pancreatic carcinoma cell line Colo357  [17]  were grown in Dulbecco's Modified Eagle's Medium (DMEM), RPMI and DMEM: F12 (1:1) culture media. Human cell lines were authenticated by Short Tandem Repeat (STR) analysis (PowerPlexW 1. 2 System, Promega, WI, US) and the STR profiles were matched to the German Collection of Microorganisms and Cell Cultures (DSMZ) database. Prior to treatment with cytokine, Colo357 cells were incubated in serum-free medium for 24 hrs. Cells were then treated at the following concentrations: IL-1beta (20ng/ml), IL-6 (40 ng/ml), TNF-alpha (20 ng/ml), or Interferon-gamma (10 ng/ml).
Peptides were separated with a four hour gradient from 5 to 65% acetonitrile (buffer A, 5% acetonitrile, 0. 1% formic acid and 0. 005% TFA; buffer B, 90% acetonitrile, 0. 2% formic acid and 0. 005%TFA). The voltage applied to the union to produce an electrospray was 1. 2 kV. The mass spectrometer was operated in the data-dependent mode. Survey mass spectrometry scans were acquired in the Orbitrap with the resolution set to a value of 60,000. The seven most intense ions per scan were fragmented and analyzed in the linear ion trap. Raw data files were searched with MASCOT (Matrix Science) against a Swissprot database. Search parameters included a fixed modification of 57. 02146 Da (carboxyamidomethylation) on Cys, and variable modifications 15. 99491 Da (oxidation) on Met, and 0. 984016 Da (deamidation) on Asn and Gln.
Neighboring side chains in L1 and ␣CT are as labeled. Coordinates were obtained from PDB code 4OGA  (39). G, model of wild-type insulin in its receptor-free conformation overlaid onto the structure of the insulin-bound IR  (71). The L1 domain and part of CR domain are shown in powder blue; ␣CT is shown in purple. Residues Phe B24 and Tyr B26 are as in A. The B chain of IR-bound insulin is shown in dark gray (B6 -B19); the brown tube indicates classical location within the overlay of residues B20 -B30 of insulin in its receptor-free conformation, highlighting steric clash of B26 -B30 with ␣CT. In the IR co-crystal structure, insertion of the insulin B20 -B27 segment between L1 and ␣CT peptide is associated with a small rotation of the B20 -B23 ␤-turn and changes in main-chain dihedral angles flanking Phe B24  (39).
H, inverted V-shaped assembly of IR ectodomain homodimer. One monomer is in ribbon representation (labeled), the second in surface representation. Domains are labeled as follows: L1, first leucine-rich repeat domain; CR, cysteine-rich domain; L2, second leucine-rich repeat domain; FnIII-1, -2, and -3, first, second, and third fibronectin type III domains, respectively; ID, insert domain; and ␣CT, ␣-chain C-terminal segment. Coordinates were obtained from PDB code 4ZXB  (42). and the ␣-helical subdomain (Fig. 1C ). The contribution of this side chain to the stability of the insulin monomer has recently been investigated by molecular dynamics (MD) simulations  (31)  and mutagenesis  (32). Insulin undergoes a change in conformation to "open" on receptor binding  (33) (34) (35) (36) (37). A recent structural advance exploited domain-minimized models of the ␣-subunit of the insulin receptor (IR)  (38)  containing the primary insulin-binding elements (leucine-rich domain 1 (L1) and the C-terminal segment of the ␣-subunit (␣CT))  (39).
Multipole-based MD Simulations Predicted Structural Features of an Iodinated Insulin Analog Side-chain conformations were further probed by analyzing 20 ns of four MTP-based MD simulations as follows: the WT and 3-[iodo-Tyr B26 ]insulin dimers, each in R 2 or T 2 states (supplemental Figs. S1 and S2, respectively). Initial coordinates were obtained from PDB entries 1DPH (T 2 ) and 1ZNJ (as extracted from a WT R 6 zinc insulin hexamer). We first analyzed respective ( 1 , 2 ) occupancies, P( 1 , 2 ), of residues Tyr A19 , Tyr B16 , Phe B24 , Phe B25 , and Tyr B26. Of these, A19 provided a probe of the ␣-helical core within component protomers, whereas B16 and B24 -B26 provided probes of the asymmetric dimer interface. The resulting dihedral angle distributions P( 1 , 2 ) demonstrated that these side chains each adopted conformations consistent with experiments (see symbols in supplemental Figs.
Baseline r. m. s. d. values in the WT T 2 dimer (PDB code 1DPH) were calculated following a control MD simulation (i. e. in the absence of a modified B26). For residues in the WT anti-parallel ␤-sheet (residues B24 -B28 and their dimer-related mates), the average main-chain r. m. s. d. was 0. 1 Å, and the average sidechain r. m. s. d. was 0. 3 Å relative to starting structure (Table  1 ). Corresponding values for the modified T 2 dimer were 0. 3 and 0. 9 Å, also relative to the WT crystal structure; similar values were obtained on comparison of the modified R 2 dimer. The larger r. m. s. d. values in the modified dimers reflected consistent conformational adjustments required to accommodate core packing of the iodine atom in the 3-I conformation.
Comparison of Observed and Predicted Conformations of 3-I-Tyr B26 The average r. m. s. d. across the dimer interface was calculated for the three 3-I-Tyr B26 insulin R 2 dimers with respect to WT R 2 dimers (PDB code 1ZNJ; Table  1 ). The deviation in the 3-I-Tyr B26 R 2 dimers (0. 7 and 0. 9 Å) arises from the packing of iodine in the hydrophobic pocket. The average r. m. s. d. across the dimer interface was also calculated with respect to the crys-.
3-I-Tyr B26 WT insulin tal structure of the WT T 2 dimer (PDB code 1DPH). Because in the T state Gly B8 lies within a ␤-turn (with positive angle) whereas the R state has B8 in an ␣-helix (negative angle), the T 2 -related r. m. s. d. was calculated only for backbone atoms of the ␤-sheets at the dimer interface (␤/␤Ј). The 1 and 2 dihedral angles of selected side chains in the three dimers in the crystallographic hexamer were compared with the predicted dimer dihedral angle distribution from WTand 3-[iodo-Tyr B26 ]insulin T 2 dimers (black stars for dimer 1, black squares for dimer 2, and black circles for dimer 3; see supplemental Fig. S2 ). In the crystallographic hexamer, the aromatic residues locally re-organize such that B24 and B24Ј always have opposite 2 angles (this is observed for all the dimers in the crystal); in contrast, the B25 side chains are disordered.
Simulations, 20 ns in length, based on the R 2 structure (PDB code 1ZNJ) established that the R 2 dimer samples all experimentally observed states. As a control to test whether such consistency would be affected by the TR transition, corresponding trajectories based on a crystallographic T 2 dimer (PDB code 1DPH) were undertaken (supplemental Fig. S2 ). Although sampling of B25 side-chain conformations (and to some extent that of Phe B24 ) differed in the T 2 trajectory (supplemental Fig. S2 ), the results were in good overall agreement with the R 2 -based simulations (supplemental Fig. S1 ).
MD simulation of 3-I-Tyr B26 and 5-I-Tyr B26 at the IR interface (using PDB code 4OGA as starting structure) supported the plausibility of this model (Fig. 7 ). An iodine at either the 3-or 5-positions (Fig. 7 ) of Tyr B26 could readily be accommodated within the receptor-binding cleft (i. e. with the iodo group directed either toward or away from the IR interface). Whereas the 5-I-Tyr B26 conformation did not appear to offer new favorable interactions, our modeling revealed that a 3-iodo-substituent could participate in three novel contacts (Fig. 8A ) as follows: (i) a halogen bond between its ␦ ϩ region and the backbone oxygen atom of Val-712, and (ii and iii) favorable electrostatic interactions between its ␦ Ϫ equatorial belt (Fig. 2B ) and one hydrogen from the ⑀-NH 2 of Gln-34 and one hydrogen from the ⑀-NH 2 of Arg-14.
We next verified the predicted conformational preference for the 3-I-Tyr B26 state through crystallographic studies. Finally, we investigated possible mechanisms by which 3-I-Tyr B26 enhances IR binding  (7) (8) (9). Such enhancement posed a seeming paradox as a modification that "closes" the free conformation of insulin ]insulin hexamer (A) and WT insulin R 6 zinc hexamer (PDB code 1ZNJ) (B). The three subpanels within A and B correspond to the respective three copies of the dimer interface within the crystallographic asymmetric units of the two structures. Within each subpanel, the side-chain carbon atoms of Phe B24 and its non-crystallographic symmetry equivalents are shown in green, of Phe B25 and its non-crystallographic symmetry equivalents in orange, and of 3-I-Tyr B26 or Tyr B26 and their non-crystallographic symmetry equivalents in light purple, whereas all backbone atoms are in yellow, as are the side-chain atoms of Thr B27 and its non-crystallographic symmetry equivalents.
The arrows on the right assist in identifying the direction of the respective polypeptides within each subpanel. Chains within each subpanel correspond (from left to right) to chains B, D, F, H, J, and L (respectively) within each structure. Overlaid on the three subpanels in A is A -weighted (2F obs Ϫ F calc ) difference electron density contoured at the 0. 75 level and masked to within 2. 5 Å of the side-chain atoms of Phe B25 and its symmetry-related equivalents. The values displayed under the respective chains within the subpanels of B correspond to the side-chain occupancies of the Phe B25 and its respective non-crystallographic symmetry equivalents within PDB code 1ZNJ. The side chain of Nle B29 is not shown. (39, 71). The structure and properties of 3-[iodo-Tyr B26 ]insulin reflect general physico-chemical principles.
3-I-Tyr B26 Modulates Aromatic-Aromatic Interactions The dimer interface of insulin exhibits successive aromaticaromatic interactions involving eight residues: Tyr B16 , Phe B24 , Phe B25 , Tyr B26 , and their dimer-related mates (2). Whereas the two B25 side chains lie at the periphery of this interface (and exhibit alternative or multiple conformations among WT crystal structures (2)), the remaining six aromatic rings conform to favorable pairwise edge-to-face orientations  (44). Respective aromatic-aromatic interactions at the dimer interface of WT insulin and 3-[iodo-Tyr B26 ,Nle B29 ]Insulin are shown in Fig. 10B. Inter-ring centroid distances and orientations are defined as illustrated in Fig. 10A   (44). In a representative WT R 6 structure (determined at a resolution of 2. 0 Å with one hexamer in the asymmetric unit such that the three dimer interfaces are crystallographically independent; PDB code 1ZNJ), the dimer interface contains the following structural relationships.
Circular Dichroism-Far-ultraviolet CD spectra were obtained on an AVIV spectropolarimeter equipped with an automated syringe-driven titration unit. The proteins were made 50 M in 10 mM potassium phosphate (pH 7. 4) and 50 mM KCl. Spectra were obtained from 190 -250 nm as described  (84). Thermodynamic stabilities were probed by guanidine hydrochloride-induced denaturation monitored by CD at 222 nm. Data were fit by non-linear least squares to a two-state model (85) as described  (86). Receptor Binding Assays-Affinities for IR-B were measured by a competitive-displacement scintillation proximity assay. This assay employed solubilized receptor with C-terminal streptavidinbinding protein tags purified by sequential wheat germ agglutinin and StrepTactin-affinity chromatography from detergent lysates of polyclonal stably transfected 293PEAK cell lines expressing each receptor.
Data analysis employed XDS  (88). The structure was determined by molecular replacement using PDB code 1ZNJ as a search model, followed by iterative refinement and model building using PHENIX  (89)  and COOT  (90) , respectively. The refinement strategy included both TLS refinement (translation, libration, and screw rotation) and torsional non-crystallographic symmetry (NCS) restraints between related chains. Coordinates were deposited in the Protein Data Bank (code 5EMS). QM-parameterized MM Calculations-MD simulations employed CHARMM version c40a1  (91)  with the "all-atom" force field CHARMM22 (53) using the correction map (CMAP) potential for the backbone dihedral (,) to correct for the ␣-helical bias. To account for electronic anisotropy of orthoiodophenol (employed as a model compound for purposes of MM parametrization), an electrostatic multipole model (MTP) (54) was obtained for the phenolic ring of Tyr B26 and iodophenolic ring of I-Tyr B26.
Starting coordinates of the insulin dimers were first taken from the T 2 zinc-free structure of WT insulin (PDB code 1DPH, resolution 1. 9 Å (97)) and extracted from the R 6 structure of the WT zinc hexamer (PDB 1ZNJ, resolution 2. 0 Å), respectively, and subsequently extended to the present crystal structure of a 3-I-Tyr B26 insulin analog. For corresponding simulations of the variant IR-insulin complex, starting coordinates were obtained from the lowest energy initial model (see below). The systems were first minimized by steepest descent for 5 ϫ 10 4 steps. The proteins were solvated in TIP3P water molecules (96) equilibrated at 300 K and 1 atm (within a 52. 77Å cubic box for the dimers and a 93 Å cubic box for the IR-insulin with sodium and chloride ions added to neutralize the system).
Because the relative stabilities of these conformational isomers were not known a priori, two independent MD dimer simulations of 20 Halogen-based Protein Engineering  DECEMBER 30, 2016  • VOLUME 291 • NUMBER 53 ns each were carried out starting from initial 3-I or 5-I B26 conformations, respectively. These simulations began from a T state crystallographic protomer (PDB code 1DPH (97)) because the conformation of an insulin monomer in solution resembles the T state  (28, 29). Rigid-body Calculations-Naive replacement of B26's H atoms (atomic radius 1. 20 Å and CH bond length 1. 08 Å) by iodine (atomic radius 2. 40 Å and CI bond length 2. 08 Å) in positions 3 and 5 was carried out, starting from the coordinates of T 2 zinc-free structure of WT insulin (PDB code 1DPH, resolution 1. 9 Å (97)).
All ab initio calculations were carried out with Gaussian09 (94), and optimized structures were used. The size of the iodine -hole size was measured as the angular profile of the ESP intersection line of the grid and the halogen boundary (defined as a surface of electron isodensity of 10 Ϫ3 e atomic units Ϫ3 )  (55). Such ab initio calculations were undertaken solely for the purpose of parameterizing an MM model of the modified insulin. Explicit QM/MM simulations were not performed. Modeling of the Variant Hormone-Receptor Complex-To explore how iodo-Tyr B26 might pack within the insulin-IR complex, the potential environment of the modified ring was considered in the context of the WT insulin-IR complex (PDB code 4OGA (39)). Several subsets of residues disordered in the crystal structure (IR residues Cys-159 -Asn-168 and Lys-265-Gln-276 and insulin residues B28 -B30) were included, as were N-linked N-acetylglucosamine modifications at sites Asn-16, Asn-25, Asn-111, Asn-215, and Asn-255  (103).