dataesr/scientific-paragraphs-categorization huggingface dataset:
In Petel dataset only a trend was found in ER--or HER2+ group but this was caused by a lack of association with outcome in HER2+ subgroups whilst the association was strong and significant in ER--HER2--subgroup (Supplementary Figure  14 ). Similar results were obtained in the Desmedt dataset. The number of HER2+ samples was too small to plot meaningful Kaplan--Meier curves but, as can be noted in Supplementary Figure  15 , the performance of the CTM in the combined group was poorer than in ER--HER2--group only. Patients achieving a pCR are known to have an excellent outcome, in particular in ER--HER2--and HER2+ tumors. However the double role (prognostic and predictive) of the CTM allows a significant stratification of the long--term risk also in patients with a residual disease after neoadjuvant treatment (Supplementary Figure  16 ).
As reported previously, the prognostic value seems to be stronger in ER--HER2--tumors. Besides Kaplan--Meier analysis, the immune metagene was evaluated in the different datasets and in the different subgroups by univariable Cox regression analysis that traced the conclusions above (Supplementary Table  8 ). 2A --B in the main manuscript) were compared in the same set of data with performances of two previously published immune signatures: LCK  [4]  and Tfh  [5]  metagenes.
Predictive and prognostic value of combined proliferation and ER--related metagenes in chemo--endocrine receiving ER+HER2--patients In ER+HER2--subtype, high, intermediate and low risk groups where defined as described in the main manuscript and section 5 of this supplementary information. Association with response to treatment, looking at pCR as surrogate, was evaluated by logistic regression analysis in the Hatzis (n=250) and Horak (n=107) datasets. High--risk group was significantly associated with higher pCR rate in Hatzis dataset but not in Horak dataset (Supplementary Figure  20 ). Although high--risk group seems to benefit the most from CT, it still showed the worst outcome in the Hatzis dataset as well as in the Petel dataset. Only ER+HER2--patients that actually received endocrine therapy were included in this analysis (Supplementary Figure  21 ).
ACKNOWLEDGMENTS PDC is a research associate at  FRS-FNRS  ( Fonds de la Recherche Scientifique ),  Belgium. PDC was the recipient of grants from  FNRS  (convention J. 0084. 15, convention 3. 4579. 11), PDR (Projet de Recherche , convention:  T. 0138. 14 )and  ARC  ( Action de Recherche Concertée e Communauté française de Belgique convention :  12/17-047 ). This work was supported by the  Fonds de la Recherche Scientifique e FNRS for the FRFS-WELBIO  under grant:  WELBIO-CR-2012S-02R. This work was supported in part by the  Funds Baillet Latour  (Grant for Medical Research 2015). PDC was a recipient of an  ERC Starting Grant  in 2013 ( European Research Council , Starting grant  336452-ENIGMO ). CK was the recipient of grants from the  Societe Francaise de Nutrition (SFN) , the  Fondation Recherche Médicale (FRM)  (Grant  ING20150532586 ), and the  Societe Francophone du Diabète  (Allocations Exceptionnelles 2016).
Global transcriptomic analyses identify subsets of lncRNAs whose expression is altered in ovarian carcinoma With the accumulation of transcriptomic data from high-throughput methods such as microarrays and deep-sequencing, several studies have sought to identify lncRNAs whose expression is deregulated in ovarian carcinomas. In a study integrating the expression profiles of 10 207 lncRNAs from publicly available databases in several cancers  [41] , it was shown that 1749 lncRNAs displayed an expression specific to one of the four transcriptional subtypes of ovarian cancer (immunoreactive, mesenchymal, proliferative and differentiated) defined by a study on TCGA datasets  [42]. Another study reanalyzed TCGA data and showed that 455 lncRNAs were up-or down-regulated in a transcriptional subtype-specific manner  [43].
Network analysis identifies a subset of lncRNAs possibly involved in ceRNA networks in ovarian cancer By taking into consideration the ceRNA hypothesis and using published lncRNA-disease associations, available CLIP-Seq data and miRNA-lncRNA interaction databases, Zhou et al. [50]  attempted to reconstruct disease-lncRNA networks. They designed an algorithm to analyze the possible involvement of lncRNAs within ceRNAs interactions in association with ovarian cancer and ranked them in accordance with the probability of their involvement. Interestingly, MALAT1, MEG3 and HOTAIR were among the top-ranked candidates. The implication of HOTAIR and MEG3 in ovarian cancer is discussed below, whereas MALAT1 has been only partly related to ovarian cancer. Indeed, MALAT1 has been reported to be overexpressed in SKOV3ip ovarian cancer cells, a cell line derived from SKOV3 and harboring a more metastatic phenotype, but the functional implication of MALAT1 overexpression has not yet been investigated  [51].
This latter finding may be of some importance as spreading in the intraperitoneal cavity and peritoneal carcinomatosis invasion is a very common feature of ovarian cancer  [57]. Ab073614 is an lncRNA that was recently found to be overexpressed in ovarian cancer versus normal tissue in publicly available databases. The authors also checked for AB073614 expression in cancer tissue versus normal adjacent tissue in a cohort of 75 ovarian cancer patients and observed that AB073614 high expression was correlated with a shorter 5-year overall survival (17. 2 vs 30. 0 month, p = 0. 025). In vivo, AB073614 downregulation in xenografted mice led to reduced tumor growth and reduced expression of proliferationand invasion-related proteins (PCNA and MMP2 and MMP9 respectively). In vitro, AB073614 was greatly overexpressed in HO-8910 and OVCAR3 cell lines and its downregulation decreased proliferation and induced cell death in them.
In addition, PCNA, MMP2 and MMP9 were also decreased in vitro in response to AB073614 downregulation, as well as members of key signaling pathways such as the phosphorylated forms of AKT and ERK. Although the mechanisms of action of AB073614 remain to be identified, it appears to be a key regulator of critical processes in ovarian carcinoma cells  [58]. Host2 is one of the five human ovarian cancer specific transcripts (HOSTs) identified by a SAGE study from a database of 137 SAGE libraries of normal and neoplastic ovarian tissue. Five tags were specifically expressed in ovarian cancer with one of them, HOST2, corresponding to a transcript lacking a coding capacity  [59]. HOST2 was confirmed to be overexpressed in ovarian cancer and shown to promote proliferation and migration in cancer cells as well as tumor growth in xenografted mice.
Pvt1 is an lncRNA located in the 8q24 chromosomal region. This region also harbors myc, which is amplified in 45% of ovarian carcinomas. Guan et al. [62]  reported independent oncogenic roles for MYC and PVT1 in breast and ovarian cancer cell lines, but a recent study by Tseng et al. [63]  challenged the independence of these roles. They demonstrated that the elevated MYC protein levels in cell lines with 8q24 amplification were dependent on the presence of PVT1 RNA. This codependence was further supported by the association of both pvt1 and myc duplication in almost every tumor bearing myc amplification. Their analysis included more than 30 000 tumors from the Progenetix dataset and more than 10 000 from TCGA. When all cancers were considered, more than 18% of them presented the duplication of both pvt1 and myc, whereas fewer than 0.
concludInG reMArks As was the case with miRNAs a decade ago, lncRNAs now represent a new layer of complexity in the regulation of gene expression. Although only a small subset of lncRNAs has been functionally characterized, it is clear that they are at the center of the most critical physiological and pathological biological processes. In ovarian carcinoma, data already available underline their importance and it can be reasonably expected that future studies will unravel the ever-growing role of lncRNAs in the biology of this malignancy. In addition, increasing evidence of the existence of miRNA-lncRNAs interactions through ceRNAs relationships constitutes another potentially significant regulatory mechanism that needs further exploration and characterization. From a clinical perspective, lncRNAs expression profiles could improve the stratification of ovarian cancer patients.
AcknowledGMents We apologize for our inability to cite all the contributing literature. This work was supported by the  « Ligue Contre le Cancer » (Calvados and Orne committees) , the  "Conseil Régional de Basse-Normandie ", the  French State, INSERM (National Institute for Health and Medical Research) , the  University of Caen Normandy  and the  Comprehensive Cancer Center F. Baclesse (Caen, France). N. V. is a recipient of a doctoral fellowship from the  French Ministry of Higher Education and Research. This work was supported by a grant from  "l'Ecole de l'Inserm " (N. V. ). We also wish to thank  Mégane Vernon  and  Charlène Duboc  for helpful comments on the manuscript.
Study design and treatment This was a phase II, multicenter, open-label, single-arm clinical trial in patients with MTC and RR-DTC (Clinicaltrials. gov Trial Registration ID: NCT00784303). These are two distinct diseases with different prognoses; therefore, the study was designed with distinct entry criteria for each disease and to analyze and report the outcomes separately. The study was conducted at 30 sites in the United States, United Kingdom, Australia, France, Italy, and Poland, approved by the Institutional Review Board or Ethics Committee at each participating site and carried out in accordance with the Declaration of Helsinki. All patients provided written informed consent. Treatment consisted of once-daily oral lenvatinib administered at a starting dose of 24 mg in 28-day treatment cycles for 8 cycles in the absence of disease progression, unmanageable toxicities, withdrawal, or death.
These findings support the continued investigation of lenvatinib for the management of advanced MTC. dose. At baseline [cycle 1 day 1 (C1D1)] and every 4 cycles, bone scans were performed. Archival tumor tissues were available and obtained from 24 of 59 patients. Exploratory correlative analyses of tumor genetics, serum levels of 51 circulating cytokine and angiogenic factors (CAF), calcitonin (Ct), and carcinoembryonic antigen (CEA) with tumor responses to lenvatinib treatment were conducted. A total of 32 genes and 443 mutations were assessed using the Sequenom Mass ARRAY iPLEX OncoCarta v1. 0 and v3. 0 Platform (Sequenom, Inc. ). A panel of 51 CAFs was assayed using ELISA and multiplex assays. Sample data acquisition and analysis were performed on either an ELISA plate reader using SoftmaxPro software (Molecular Devices) or the BioRad Bio-Plex System (Bio-Rad Laboratories) using Bio-Plex Manager 4.
All patients received at least one lenvatinib dose and had at least one posttreatment safety assessment and were therefore included in both the intent-to-treat (ITT) and safety populations. The ITT population was used for the primary efficacy analyses. For the primary efficacy endpoint, ORR was calculated at the time of data cut offeither when all treated patients completed !8 cycles or discontinued treatment prior to the eighth cycle. Two-sided 95% confidence intervals (CI) for the ORR were calculated using Clopper and Pearson method. Descriptive statistics were used to summarize patient demographic data and safety parameters. PFS, estimation of PFS at 6 and 12 months, OS, and duration of response (for responders) were calculated using Kaplan-Meier productlimit estimates. Mutation analyses were designed to test relationships between tumor mutation status and maximum change in tumor size, ORR, and PFS; for these analyses, the Mann-Whitney test, Fisher exact test, and log-rank test were applied, respectively.
PSL* Research University. B. B. was funded by  ANR-08-SYSC-005 ,  ANR-08-BLAN-0023 , and  PEPS CNRS-PSL. D. H. was supported by a  EU  grant ( CEREBNET FP7-ITN238686 ). N. B. was funded by  ANR-08-SYSC-005  and  NSF  ( IIS-1430296 ). G. B. was funded by  Region Ile de France, FRM , and  Labex MEMOLIFE. We thank  FRC   AOE-6 Rotary 2010  and  France Bio  imaging for funding. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
35 indicated severe segregation distortion. Two to four SNP markers were randomly selected within each of the distorted regions on LGs 2, 5 and 10 of PEAR3 and LGs 1, 9, 10 and 16 of 'Moonglow', and high-resolution melting (HRM) markers were developed from these SNPs (Supplementary Table  1 ). Polymerase chain reaction (PCR) primers were designed around SNPs using Primer3 software  34  (http:// primer3. ut. ee/) with the following criteria: (i) PCR product size between 50 and 200 base pairs (bp); (ii) primer size between 18 and 25 bases; (iii) optimal melting temperature (Tm) of 59  6  C; (iv) GC content of each primer between 40% and 55%; (v) maximum alignment score and global alignment score for self-complementarity and complementarity between primer pairs set to 4 and 1, respectively. The quality of the primers was controlled by BLASTn queries against the 'Bartlett' v1.
Genetic linkage map analysis The new HRM markers and the genotypes of the necrotic seedlings were added to the SNP and SSR dataset described in Montanari et al,  33  and updated parental genetic maps were constructed for the target LGs using JoinMap v4. 0 software  38  following the double-pseudo testcross mapping strategy. 39 The LGs were determined with a minimum LOD score of 4 for grouping, and the Kosambi function was used for map calculation. Maps were drawn using MapChart 2. 2. 40.
The observed 'Type 2':'Type 3' ratio fitted well the 1:1 Mendelian ratio at a risk of a 5 0. 05 (r 5 0. 699, r 5 0. 127 and r 5 0. 064, respectively for Motueka 2010, Angers 2011 and Motueka 2014), and the three experiments were rather homogeneous for these data, with a pooled dataset generating a significant ratio (r 5 0. 051) (Table  1 ). Detection of candidate genomic regions linked to HN Segregation distortion was detected on seven LGs: 2, 5 and 10 of PEAR3 and 1, 9, 10 and 16 of 'Moonglow', on the basis of deviation The segregation ratios of the combined genotypic classes for the markers on PEAR3 LG5 and on 'Moonglow' LG1 are compared between 'Type 1' and 'Type 2' 1 'Type 3' progeny. The segregation ratios of the genotypic classes for the marker on PEAR3 LG2 are compared between 'Type 2' and 'Type 3' progeny.
ACKNOWLEDGEMENTS SM was funded by the  Fondazione Edmund Mach PhD School. We thank  Chris Morgan  at The  New Zealand Institute for Plant & Food Research Limited  for helping to design the germination protocol in 2014 and for his assistance with the pollination and the seed and plant measurements. We are also grateful to the technicians of the INRA greenhouse facilities, especially  Nicolas Dousset  and  Michel Boucourt , for taking care of the seedling growth in 2010, and to  Helene Muranty  for her help with the statistical analysis. We finally thank the  Sequencing and Genotyping Platform at Fondazione Edmund Mach  for running the capillary electrophoresis.
For the MAD-B patient, for whom rs4641 was homozygous "C" at the genomic level, only the morpholino directed against exon 10 and targeting all the Prelamin A transcripts was used (Table  1 ). For HGPS-L4 a specific morpholino directed against Prelamin A ∆35 was designed and used in combination with Morpholino-Ex10. HGPS C Ex10-allele C 5 1 -GCTACCACTCACGTGGTGGTGATGG-3 1 Ex11-HGPSmut 5 1 -GGGTCCACCCACCTGGGCTCCTGAG-3 1 HGPS-L1 T Ex10-allele T Ex11 5 1 -GCTACCACTCACATGGTGGTGATGG-3 1 5 1 -GGGTCCGCCCACCTGGGCTCCTGAG-3 1 HGPS-L2 T HGPS-L3 T HGPS-L4 C Ex10-allele C 5 1 -GCTACCACTCACGTGGTGGTGATGG-3 1 Ex11-∆35 5 1 -ACTGACCGTGACACTGGAGGCAGAA-3 1 HGPS-L5 C Ex10-allele C 5 1 -GCTACCACTCACGTGGTGGTGATGG-3 1 Ex11 5 1 -GGGTCCGCCCACCTGGGCTCCTGAG-3 1 MAD-B Homozygous C Ex10-allele C 5 1 -GCTACCACTCACGTGGTGGTGATGG-3 1 Negative controls -Ex10-scrambled 5 1 -ATCGGCTTGTCGCGTGAGCGATCGA-3 1 Ex11-scrambled 5 1 -ACCAGTGGCGTCGCCTCGCAGGTCC-3 1 2.
Quantitation of Abnormal Nuclear Morphology Fibroblasts from HGPS and HGPS-like patients were cultured with DMEM medium containing 20 µM AON, or 6 µM of vehicle (Endoporter) for 96 h. Cells stained for Lamin A/C or DAPI were examined by fluorescence microscopy with an Axioplan 2 imaging microscope (Carl Zeiss, Oberkochen, Germany). For quantitation of abnormal nuclear morphology, the percentage of normal nuclei (nuclei with a smooth oval shape) and abnormal nuclei (nuclei with blebs, irregular shape, or multiple folds) was calculated using the Nuclear Irregularity Index (NII) plugin of the Image J Software (Version 1. 6. 0, NIH, USA). The analysis uses measures of nuclear area and of four parameters of irregularity, named Aspect, Area/Box, Radius Ratio and Roundness. These four parameters are used to generate a Nuclear Irregularity Index (NII) which, added to area measurement, classify the nuclei in normal or abnormal morphology.
Statistical Analyses Statistical analyses were performed with GraphPad Prism 6 (GraphPad Software, Inc. San Diego, CA, USA). Differences between groups were assayed using a two-tailed Student's t-test. In all cases the experimental data were assumed to fulfill t-test requirements (normal distribution and similar variance); in those cases, where the assumption of the t-test was not valid, a non-parametric statistical method was used (Mann-Whitney test). A p value less than 0. 05 was considered as significant. Error bars indicate the standard error of the mean.
Acknowledgments: We thank  Françoise Merono  for her excellent support and assistance. Author Contributions:  Karim Harhouri ,  Camille Baquerre ,  Nathalie Da Silva  and  Catherine Bartoli  performed the experiments and analyzed the data. Frank Casey ,  Yassamine Doubaj ,  Guedenon Koffi Mawuse  and  Annachiara De Sandre Giovannoli  provided medical care for the patients and contacts with their families. Karim Harhouri ,  Annachiara De Sandre Giovannoli ,  Claire Navarro  and  Nicolas Levy  conceived and designed the experiments. Karim Harhouri  and  Annachiara De Sandre Giovannoli  wrote the manuscript.
In this context, one main task of optical investigations is to characterize the light transport process determined by multiple scattering. This characterization is typically achieved through repetitive measurements to retrieve meaningful microscopic transport parameters, such as the transport mean free path l t and the absorption length l a , which are directly related to the properties of the investigated medium (that is, the internal structure, composition and/or density), and are key parameters to consider from both the fundamental and the application points of view. Here, we experimentally combine wide-field spatial imaging and sub-picosecond (ps) time resolution and show how the acquired multi-dimensional dataset allows us to characterize previously inaccessible scattering systems and to improve the accuracy of measurements in standard situations.
By comparing the outcome of our analysis with that of the mainstream evaluation model based on the diffusive approximation (DA), we describe how single-domain investigations performed to date are susceptible to particularly deceptive artifacts that can be clearly appreciated in a multi-domain dataset. At the same time, as widely suggested in the literature, we discuss how much more robust interpretations, even within the diffusive framework, can be given in terms of transverse transport, to which we gain direct access through our technique.
We therefore further investigated the sample using our imaging configuration (which could in principle also substitute the photon counter following frame integration, see Fig. 2b ). The mean square width, as extracted by the obtained frames, clearly shows a linear increase (Figures  2c-d ) that can easily be interpreted within the DA, which predicts w 2 (t) = 4Dt. The experimental slope, as obtained from a linear fit, corresponds to D fit exp = 1746 µm 2 ps -1 → l t = 26. 6 µm, which is appreciably larger than the value retrieved from the time-resolved curve. We therefore ran Monte Carlo simulations (see SI) to resolve this discrepancy, and eventually succeeded in simultaneously reproducing both the experimental time-resolved and mean square width evolution datasets using a single transport parameter, l t (Figures  2b  and d ).
The Monte Carlo inversion procedure gives a value of l t = 25. 5 µm (again corresponding to an optical thickness of ∼ 8) which is perfectly compatible with both datasets without introducing absorption. It should be noted that the transport mean free path, as retrieved from the mean square width slope in the diffusive framework, results in just a 4 % overestimation of the actual best value retrieved by the Monte Carlo simulations. Such a level of accuracy is acceptable for a wide number of applications, where UFI techniques could be exploited to extend the applicability of the DA in this intermediate thickness range. Moreover, as widely suggested in the literature  45, 46  , estimating transport properties from the mean square width rather than from time-resolved data is much more accurate and straightforward because in the former case, a priori knowledge of the absorption coefficient, refractive index contrast and sample thickness is not required.
As previously mentioned, our UFI technique is capable of replacing completely integrated measurements with comparable sensitivity (Fig. 2b ). Exploiting the full spatio-temporal information, the resulting set of frames can be decomposed into a mean square width and a time-resolved curve, providing two almost independent datasets in a single measurement session. Indeed, the former does not depend on the integrated intensity of the individual frames, whereas the latter is primarily linked to the transport along the z axis. In this respect, our perfectly matching Monte Carlo validation, which is conducted independently on two experimental datasets that depend differently on different sets of parameters, is a clear indication of the quantitative accuracy and reliability of our setup over many orders of magnitude in both the temporal and spatial domains.
5 µm, l t2 = 21. 5 µm and l t3 = 11 µm, respectively, for the high, low and intermediate-density layers. The absorption coefficients were all set to µ a = 0 µm -1. In this case, the mean square width/time-resolved decomposition clearly allowed an unexpected degree of complexity to be revealed and characterized thanks to the rigid constraints of the double boundary datasets. Resolving this composite structure showed that a layered heterogeneity can, in principle, mimic the effects of anisotropic transport and therefore revealed a previously unaddressed physical effect. This is especially relevant given the pervasiveness of layered media (for example, coatings, atmospheric physics and biological tissues), which often exhibit counter-intuitive features that standard time-resolved techniques are still unable to explain, as in the case of light transport across the human forehead  51.
The set of simulated curves shown in Figure  5c  is obtained for g = 0. 7 and l s = 150 µm (corresponding to an in-plane l t = 500 µm). However, quantitatively accurate figures for this particular specimen would require an analysis involving fully anisotropic simulations. The main purpose of this experiment is to showcase the vast possibilities opened by rich time-and space-resolved outputs. Our g estimation results from a collective fitting routine involving multiple spatio-temporal datasets and stands in contrast to common and less robust g determination techniques involving a single scalar, such as the attenuation coefficient of a collimated beam  52, 53. Accurate determination of single scattering anisotropy is crucial to directly probe the shape, orientation and optical properties of single microscopic scatterers and might therefore be of interest to a broad range of fields, from realistic computer rendering of participating media  54, 55  to photo-therapeutic diagnostics of biological tissues  56, 57.