Previous analysis suggested that the relative contribution of individual bones to regional skull lengths differ between inbred mouse strains. If the negative correlation of adjacent bone lengths is associated with genetic variation in a heterogeneous population, it would be an example of negative pleiotropy, which occurs when a genetic factor leads to opposite effects in two phenotypes. Confirming negative pleiotropy and determining its basis may reveal important information about the maintenance of overall skull integration and developmental constraint on skull morphology.Camkmt and Six2.We identified negative correlations between the lengths of the frontal and parietal bones in the midline cranial vault as well as the zygomatic bone and zygomatic process of the maxilla, which contribute to the zygomatic arch. Through gene association mapping of a large heterogeneous population of Diversity Outbred (DO) mice, we identified a quantitative trait locus on chromosome 17 driving the antagonistic contribution of these two zygomatic arch bones to total zygomatic arch length. Candidate genes in this region were identified and real-time PCR of the maxillary processes of DO founder strain embryos indicated differences in the RNA expression levels for two of the candidate genes, A genomic region underlying negative pleiotropy of two zygomatic arch bones was identified, which provides a mechanism for antagonism in component bone lengths while constraining overall zygomatic arch length. This type of mechanism may have led to variation in the contribution of individual bones to the zygomatic arch noted across mammals. Given that similar genetic and developmental mechanisms may underlie negative correlations in other parts of the skull, these results provide an important step toward understanding the developmental basis of evolutionary variation and constraint in skull morphology.The online version of this article (10.1186/s13227-018-0092-3) contains supplementary material, which is available to authorized users. The skull is a complex structure that supports and protects tissues critical for survival, including the brain, sense organs, and masticatory apparatus. While a wide range of skull morphology has evolved across mammalian species, fundamental patterns of skull bone integration are generally conserved –4. This Random pairs of linear distances across the skull are expected to display positive correlations driven by the overall growth of the integrated head. Negative correlations between raw linear distance measurements are rare and can be evidence of scale-independent negative pleiotropy, which exists when genetic variation leads to an opposite phenotypic effect on two traits , 12. WitA previous analysis of adult skull variation indicated that linear dimensions of the cranial vault, zygomatic arch, and cranial base vary strongly among the eight inbred mouse founder strains of the Collaborative Cross (CC). Furthermore, that analysis indicated that pairs of bones within each of these regions display negative correlations in relative size . Here, wPrevious quantitative trait locus (QTL) analyses of mouse craniofacial variation have illustrated the ubiquity of pleiotropy in the genetics of craniofacial form –22 and iWithin our mapping results, we expect that a locus driving negative pleiotropy will have a significant haplotype effect on the linear distances of each adjacent bone. Furthermore, we expect that variation in founder strain haplotypes at this locus will be associated with opposite phenotypic effects for each bone . Third, if this locus represents a developmental constraint on the morphology of the combined length of both bones, we expect that local haplotype variation will have no effect on overall regional length. Identifying a genomic region associated with negative pleiotropy and candidate genes within it is a critical first step in understanding an important genetic and developmental basis for both developmental constraint and variation in the relative contribution of bones to regional skull morphology. Although our analyses are regionally specific, identifying the general mechanisms underlying negative pleiotropy of adjacent skeletal elements is an important step toward understanding the developmental basis for evolutionary change in the skull.Our measurements of the Collaborative Cross (CC) founder strains and their F1 crosses derive from craniofacial landmarks collected from 1211 specimens for a previous analysis . The DivA sample of 472 DO mice of generations 19, 21, and 23, raised at the Scripps Research Institute (IACUC #08-0150-3), were used to validate relevant QTLs identified by genome-wide association in our primary sample. This validation sample was chosen because it includes mice from later DO generations with greater recombination, which might allow for the refinement of any validated QTL . After collection, adult specimens were stored at −20 °C. Receipt and imaging of specimens from other institutions was conducted in accordance with approved IACUC protocol #AC13-0268 at the University of Calgary.Embryonic specimens from A/WySnJ (AWS), C57BL/6J (C57), and WSB/EiJ (WSB) inbred backgrounds were collected at the University of Calgary at embryonic day (E) 11.5 and processed as recently described . BrieflyNegative relationships between the length of bones making up the zygomatic arch, sagittal cranial vault, and posterior cranial base were previously identified among the eight CC founder strains from plots of relative linear dimensions that differ strongly between a given founder strain and several of the other founder strains . Unlike www.mayo.edu/bir/).Micro-computed tomography (µCT) images of heads were obtained in the 3D Morphometrics Centre at the University of Calgary with a Scanco vivaCT40 scanner  at 0.035 mm voxel dimensions at 55 kV and 145 µA. Three dimensional coordinates of 54 adult landmarks , as previously defined , were coWe calculated linear distances associated with zygomatic arch length, sagittal cranial vault length, and midline cranial base length from raw landmark coordinates collected on both CC founder/F1 specimens and DO specimens Fig. . Full zyr) for each pair of component linear distances  and between each component linear distance and the overall trait length  was calculated to identify correlation direction and strength. A t test of whether the r is different from 0 was completed for each pair to determine whether their correlation is significant, after Bonferroni correction to account for multiple testing (α = 0.0028). The coefficient of determination (R2) is interpreted as a measure of how much variance in one length in a pair is explained by the other.The Pearson’s correlation coefficient , Lincoln, NE] , while tAssociation mapping was performed using DOQTL  for bothThe E11.5 maxillary process was chosen for RT-PCR because both the maxilla and zygomatic bones are derived from mesenchymal condensations within this process see “”, startiGapdh—Mm.PT.39a.1, Camkmt—Mm.PT.58.7890215, Six3os1—Mm.PT.58.43925739, Six2—Mm.PT.58.22007192), an ABI Taqman assay (18s—Mm0477571_s1), and custom Six3 primers  [Gapdh and 18 s RNA runs. Reference genes were selected based on stability from previous experiments and RNAseq data from this region of the face.Following a recently published analysis , RNA wasAGTA-3′) . AdditioCamkmt, Six2, Six3, and Six3OS1 using Graphpad Prisim (Version 6) software. If there were differences in expression between genotypes, we looked for similarities between variation in RNA expression and the phenotypic effects of A-strain, C57, and WSB haplotypes on relative zygomatic bone length, which might indicate that variation in expression of these candidate genes is associated with the identified negative correlation in zygomatic bone lengths. This was done by using a post-test for linear trend.Since C57 mice had an intermediate phenotypic effect, mean C57 RNA expression was used as the baseline upon which to compare the expression of all specimens (measured as fold change). One-way ANOVA tests of fold-change values between genotypes were completed for We explicitly tested whether the lengths of adjacent bones within the cranial base, cranial vault, and zygomatic arch were negatively correlated. While we expected that most linear distances in the skull would be positively correlated, a negative correlation is evidence for a developmental constraint in how component bones  contribute to a larger overall trait . All component bone lengths were significantly positively correlated with corresponding overall trait lengths Table . The lenGiven the negative correlations between the length of bones contributing to the zygomatic arch and cranial vault, we completed genome-wide association mapping to look for evidence of a genomic region that might drive these correlations based on the mechanism of negative pleiotropy. Our association mapping analysis revealed two intervals on chromosome 17 that were associated with zygomatic bone length variation , while the second of these intervals (85.30648–85.88324 Mb) was also associated with zygomatic process of the maxilla length variation  and one well-studied non-coding RNA (Six3os1). We noted that the WSB and A/J founder haplotypes are associated with opposite phenotypic effects for zygomatic bone and zygomatic process of the maxilla lengths, while the C57 haplotype effect is intermediate  indicates there are 19 known or predicted genes in this region  11.5 embryos of AWS, C57, and WSB mice, which had been stage matched by tail somite number. We then completed RT-PCR on these tissue samples using three replicates for each sample to quantify RNA expression levels for Within a sample of DO mice, we confirmed negative correlations between the lengths of bones contributing to the cranial vault and found strong evidence for negative pleiotropy between the length of the zygomatic bone and the zygomatic process of the maxilla. A genomic interval on chromosome 17 85.3–85.9 Mb) met all our expectations for a genetic basis of negative correlation between these adjacent zygomatic arch bones. Specifically, there were significant and opposite haplotype effects on zygomatic and zygomatic process length  is greater than the amount of variation explained by the negative correlation between the two zygomatic components . FurtheCamkmt, Six3, and Six2) and one non-coding RNA with known function (Six3os1) are found under our candidate region of interest  is expressed across a wide range of tissues and plays a pivotal role in the methylation of calmodulin, which changes across developmental stages and varies in a tissue specific manner . Deletioenotypes . Since Cenotypes . CAMKMT SIX2 (sine oculus-related homeobox 2) is known to play a significant role in the skeletal development of pharyngeal arch derivatives. SIX2 is upregulated in neural crest-derived cranial mesenchyme in mice at E8.5  and E9.5Six3 can lead to craniofacial dysmorphology of maxillofacial bones [SIX3 can cause holoprosencephaly in humans, a condition associated with forebrain malformation, intellectual disability, ophthalmological abnormalities, and craniofacial features including cyclopia, nasal dysmorphology, and cleft lip/palate [SIX3 (sine oculus-related homeobox 3) interacts with BMP, WNT, and NODAL, is critical during eye development –52, and al bones , particup/palate . A combip/palate ). SIX3OSp/palate . SIX3OS1p/palate . SIX3 anSix2 is particularly tantalizing because it is a major player in facial bone ossification and is associated with RNA expression level differences between founder strain maxillary prominences. Assuming that variation in Six2 or one of its cis-regulatory factors is responsible, we speculate about how variation in SIX2 expression might modify development to produce zygomatic arch variation in our DO mice and across mammalian clades.Although all four candidate genes have been previously associated with craniofacial dysmorphology, Dlx genes and related factors are associated with determining upper and lower jaw fates within the first pharyngeal arch [All bones that contribute to the mouse zygomatic arch form from neural crest-derived mesenchyme , 60 witheal arch , what deDlx expression patterns that distinguish them from maxillary cell populations. It is possible that one of these cues is the spatiotemporal pattern of Six2 expression. Supporting this perspective, loss of SIX1 results in a partial transformation of the zygomatic process of the maxilla into a mandible, possibly through downstream effects on Dlx gene expression [Heuzé and colleagues  recentlypression . This papression . As two Dlx genes are expressed, it is possible that the variation in the contribution of maxilla and zygomatic to the zygomatic arch  is first noted in the fossil record as one of the circumorbital bones within the dermal skeleton of agnathans. Within the presumed ancestral tetrapod, the jugal was a narrow bone of the inferior orbital margin that articulated with facial bones including the lacrimal, maxilla, and squamosal . ThAlthough a wide range of morphologies occur across mammals, our results specifically relate to variation in the relative contribution of bones to zygomatic arch length between the main bodies of the maxilla and squamosal bones. The zygomatic process of the maxilla, the zygomatic bone, and the zygomatic process of the squamous temporal typically contribute to form the zygomatic arch. Because only a short squamous temporal portion exists in laboratory mice, our analysis focused on the zygomatic and maxillary bone contributions to overall arch length. Mouse strain haplotype variation noted under a genomic interval on mouse chromosome 17 (85.3–85.9 Mb) is responsible for significant variation in the relative contribution of these bones to arch length.Analogous genetic variation may underlie variation in the relative contribution of zygomatic arch elements to total arch length across mammalian species. This sort of phenotypic variation is common across mammalian taxa. For example, carnivorans including felids and canids typically have a very short zygomatic process of the maxilla, an anteriorly placed zygomatic bone, and a relatively long zygomatic process of the temporal , 84 Figa. On theTwo clades that were commonly thought to lack a zygomatic bone illustrate how an extreme imbalance in two zygomatic arch elements might manifest. First, moles  may represent the logical extreme of the proposed mechanism. Although moles lack a separate zygomatic bone as adults , 86 Figc, one ofIf the modified expression of a factor like SIX2 leads to the expansion of one arch bone at the expense of another, a fusion of the arch bones together and/or a displacement of the smaller bone may occur. In fact, SIX1 null mutant mice with the enlarged zygomatic process of the maxilla also display either a smaller displaced zygomatic bone or fusion of zygomatic and maxillary portions of the developing arch . It is tInvestigating how genetic factors constrain the range of possible skull variation is critical for identifying mechanisms of integration and developmental constraint. Out of three cranial regions studied, we identified a genomic region underlying negative pleiotropy within the zygomatic arch. Association mapping and subsequent RT-PCR analysis identified candidate genes that might underlie this pattern. Further study is required to determine how the responsible genetic factor modifies developmental processes to limit overall zygomatic arch length while allowing for variation in the relative length of contributing zygomatic bones. This pattern of negative pleiotropy may have contributed to the evolution of mammalian zygomatic arch diversity. Identifying the particular developmental basis for this negative pleiotropy has implications beyond the zygomatic arch, because changes in similar instances of negative pleiotropy underlie significant evolutionary variation in the relative contribution of adjacent bones to larger morphological features in other regions like the cranial vault and upper jaw. These results provide a significant toe-hold in unraveling an example of negative pleiotropy and developmental constraint, which is an important step toward understanding the developmental basis for evolutionary change in the skull.Additional file 1. A.csv file with sequence details and identification of primers used during RT-PCR analysis.Additional file 2.Validation Sample Haplotype Effects CC founder strain specific phenotype coefficients (above) and LOD scores from genome-wide scan (below) for significant association between haplotype and A) zygomatic process of the maxilla length and B) zygomatic bone length across Chromosome 17. Phenotypic coefficients are the effect of having a certain founder strain genotype at a specific genomic location on a measurement.Additional file 3. A.csv phenotype file with linear distance measures and covariates for the CC Parental/F1 sample discussed in this analysis.Additional file 4. A.csv phenotype file with linear distance measures and covariates for the primary DO sample discussed in this analysis.Additional file 5. A.csv phenotype file with linear distance measures and covariates for the validation DO sample discussed in this analysis.


Breast™), hereafter referred to as MetaSite Score (MS). The objectives were to determine the association between MS and distant relapse free interval (DRFI) and relapse free interval (RFI). MS was not associated with tumor size or nodal status, and correlated poorly with Oncotype DX Recurrence Score (r = 0.29) in 297 patients with HR+/HER2- disease. Proportional hazards models revealed a significant positive association between continuous MS and DRFI (p = 0.001) and RFI (p = 0.00006) in HR+/HER2- disease in years 0–5, and by MS tertiles for DRFI (p = 0.04) and RFI (p = 0.01), but not after year 5 or in triple negative or HER2+ disease. Multivariate models in HR+/HER- disease including continuous MS, clinical covariates, and categorical Recurrence Score  showed MS is an independent predictor for 5-year RFI (p = 0.05). MetaSite Score provides prognostic information for early recurrence complementary to clinicopathologic features and Recurrence Score.Metastasis is the primary cause of death in early-stage breast cancer. We evaluated the association between a metastasis biomarker, which we call “Tumor Microenviroment of Metastasis” (TMEM), and risk of recurrence. TMEM are microanatomic structures where invasive tumor cells are in direct contact with endothelial cells and macrophages, and which serve as intravasation sites for tumor cells into the circulation. We evaluated primary tumors from 600 patients with Stage I–III breast cancer treated with adjuvant chemotherapy in trial E2197 (NCT00003519), plus endocrine therapy for hormone receptor (HR)+ disease. TMEM were identified and enumerated using an analytically validated, fully automated digital pathology/image analysis method . They used a digital image analysis test called MetaSite  We used a prospective-retrospective study design that utilized biospecimens from a well annotated and uniformly treated clinical trial cohort, an approach that provides a high level of evidence supporting the clinical validity of a biomarker.p = 0.001) or the HER2+ subtype , while the difference between triple negative and HER2+ was not significant . As expected, virtually all patients with triple negative disease (99.5%) and most with HER2+ disease (69%) had a high Recurrence Score of >30 because low ER and high HER2 expression contribute to a higher Recurrence Score.29The characteristics of the study cohort, overall and by breast cancer subtype, is shown in Table p = 0.02) and older than 60 years , ER  and PR  expression, and any grade , but not tumor size or axillary nodal metastases. These findings are consistent with the observation of significantly higher MetaSite Scores in the triple negative and HER2+ compared with HR+/HER2- breast cancer.The empirical tertile cutpoints for the entire cohort in the weighted distribution were 0 to 5 , 6 to 17  and 18 to 199 . The characteristics of patients in each MetaSite Score empirical tertile group are shown in Table p = 0.0002, two degree-of-freedom overall test for association), and the hazards were not proportional over time (p = 0.01)  but not overall survival (OS) (p = 0.21) in the HR+/HER2- group in the time-varying coefficient model, which may be explained by the high proportion of deaths in this group that were not due to breast cancer (48/85 [56%]). The association between MetaSite Score and breast cancer death was not significantly time-dependent in the time-varying coefficient model (p = 0.54), but was significantly associated with breast cancer death in the proportional hazards model not adjusted for time (p = 0.04).The proportional hazards model including only MetaSite Score as a continuous covariate and the time-varying coefficient model that adds the variable time*MetaSite Score was fit overall and for each of the three breast cancer subtypes. Although there was no significant association between MetaSite Score and distant recurrence overall, there was strong evidence of an effect in the time-varying coefficient model in the HR+/HER2- group  (p = 0.001) and relapse free interval (RFI) (P = 0.00006), but not triple negative or HER2 + disease. The estimated coefficient was negative  in all of the subsets in the 5–10 year period, suggesting that any effects are limited to the earlier time period. Kaplan–Meier analysis revealed a significant association between MetaSite Score and DRFI (p = 0.04) and RFI (p = 0.01) in the HR+/HER2- group when evaluated by empirical tertiles  for the entire cohort with follow-up truncated at 5 years  and RFI (p = 0.0004), and also when using TAILORx cutpoints  for DRFI (p = 0.007) and RFI (p = 0.003), although there was somewhat better separation among the low, intermediate, and high-risk categories using the latter definition  for DRFI  and borderline association with DRFI (p = 0.08). If Recurrence Score (continuous linear variable) was included in the model instead of MetaSite Score, it was not significant for RFI (p = 0.51) or for DRFI (p = 0.90). If categorical Recurrence Score  was added to the model including MetaSite Score (continuous linear variable) and clinical covariates, there remained significant association with RFI (p = 0.05) and a borderline association with DRFI (p = 0.10). If categorical rather than continuous MetaSite Score was used in the model, the association was not significant.Because the association between MetaSite Score and recurrence was time-dependent, proportional hazards models for DRFI and RFI in the HR+/HER2- subset using follow-up through 5 years were fit Table . ClinicaThe complementary prognostic information provided by MetaSite Score was further examined by evaluating the hazard ratio for recurrence by Recurrence Score categories of low, intermediate and high risk, using both the classical Fig.  and TAILHi/VEGFHi), and (3) secretion of VEGF from TMEM macrophages leads to TMEM-associated transient blood vessel permeability, tumor cell intravasation, and an increase in circulating tumor cells.23 Prior proof-of-concept studies indicated that TMEM structures could be identified in human breast cancer using a triple immunohistochemical stain for Mena over-expressing tumor cells, macrophages, and endothelial cells all in direct contact,25 and that identification and enumeration of TMEM structures by manual methods was prognostic for distant recurrence in HR+/HER2- breast cancer independent of classical clinicopathologic features using primary tumor samples derived from a population-based cohort.26 Here, we report a second prospective-retrospective biomarker study confirming the clinical validity of the association between TMEM Score and distant recurrence, specifically early recurrence within 5 years of diagnosis, now in a uniformly treated clinical trial cohort of patients with HR+/HER2- early-stage breast cancer using an automated, high-throughput analytically validated assay (MetaSite Breast™) in a Clinical Laboratory Improvement Amendments (CLIA)-certified clinical diagnostic laboratory; hence, we use the term MetaSite Score to describe the assay and results here. Although MetaSite Score was not prognostic in triple negative or HER2+ breast cancer in this cohort, it is noteworthy that the scores were significantly higher in this high-risk subtypes compared with HR+/HER2-negative disease, which is consistent with the hypothesis that higher TMEM Score is associated with greater distant recurrence risk. Potential explanations for lack of prognostic association in poor risk breast cancer subtypes include the relatively small sample size and limited statistical power for these subtypes, and a threshold effect below which TMEM Score is prognostic, and above which higher TMEM Score is not associated with higher recurrence risk.Using high-resolution two-photon microscopy in the MMTV-PyMT mammary carcinoma and patient-derived xenograft models, we have shown that: (1) transient blood vessel permeability induced by vascular endothelial growth factor (VEGF) and accompanying tumor cell intravasation occur exclusively at TMEM sites, (2) TMEM-associated macrophages are a subpopulation of tumor-associated macrophages that are pro-angiogenic  in node-negative disease and an Recurrence Score of 11–25, and the RxPONDER (NCT01272037)32 and OPTIMA (ISRCTN42400492) trials in patients with up to nine positive axillary nodes and low to mid-range Recurrence Score (</=25).34Another objective of this study was to evaluate whether MetaSite Score provided clinically useful prognostic information beyond that provided by Recurrence Score. Here, we show for the first time that MetaSite Score correlates poorly with Recurrence Score and provides complementary prognostic information for early recurrence, including patients with a mid-range Recurrence Score for whom uncertainty still exists about the benefit of chemotherapy.35 Thus, although there was only a borderline association between MetaSite Score and distant recurrence in the multivariate models including clinical covariates and categorical Recurrence Score, the significant association between MetaSite Score and all recurrences supports the robustness of the prognostic information provided by MetaSite Score.Because TMEM are believed to serve as the doorway for hematogenous dissemination and distant metastasis, the primary study endpoint in this analysis was distant recurrence as a first event, which accounted for 70% of the recurrences; the remaining 30% were localregional recurrences without concurrent distant recurrence as a first event. A limitation of our study was that distant recurrence occurring after localregional recurrence was not recorded, thus potentially underestimating the proportion of patients who eventually developed a distant recurrence. Isolated localregional recurrence without concurrent distant recurrence is known to be associated with a high risk of subsequent distant recurrence and breast cancer mortality.®TM, Prosigna™, Breast Cancer Index℠).36 Although these signatures include different genes, they provide similar prognostic information that is driven largely by proliferation and estrogen-dependent genes and not by the intrinsic propensity of tumor cells to metastasize or interact with their microenvironment.39 Although direct comparison of the prognostic classification provided by some of these gene expression assays in the same cohort showed comparable prognostic information, they often provide discordant recurrence risk classification.33 Since MetaSite Score correlates poorly with Recurrence Score, captures different biologic information, and provides complementary prognostic information, it offers the potential to more accurately determine prognosis when added to multiparameter gene expression assays.In addition to the Recurrence Score assay, several other multiparameter gene expression assays are commercially available  or docetaxel (AT) (which were comparably effective28), whereas only 43% of patients in the population-based cohort received adjuvant chemotherapy. Since adjuvant chemotherapy  prevents mainly early recurrence within the first 5 years, and sequentially administered regimens of longer duration are generally more effective than shorter regimens,40 a biomarker prognostic for early recurrence could be predictive for benefit from adjuvant chemotherapy, or more prolonged course of sequential anthracycline-taxane therapy. Moreover, early recurrence is associated with more aggressive disease and shorter survival than later recurrence,41 providing additional evidence that a biomarker prognostic for early recurrence provides clinically meaningful information. Additional studies in other cohorts will be required to determine the optimal MetaSite Score cutpoints for prognosis, and for prediction of chemotherapy benefit. Furthermore, studies are ongoing that are evaluating whether an a multiparameter biomarker that integrates TMEM Score with assessment of invasive Mena isoforms43 improves the accuracy of the prognostic information provided by the MetaSite Score alone.The tertiles of MetaSite Scores in the entire study population study were comparable in this clinical trial cohort using a fully automated assay in a clinical diagnostic laboratory  to the prior population-based cohort using a manual assay in an academic research laboratory ;Hi/VEGFHi macrophage, and is responsible for the local release of VEGF from TMEM-associated macrophages causing vascular permeability specifically at TMEM sites.23 This offers the potential to use TMEM Score and other biomarkers reflecting TMEM function as predictive biomarkers for therapies targeting the Tie2-VEGF axis; a clinical trial testing this strategy for the first time is currently in progress (NCT02824575).Although we have focused on MetaSite Score as a prognostic biomarker in this study, and also described its potential for predicting chemotherapy benefit, it may also serve as a biomarker for agents targeting tumor-stromal interactions. For example, the TIE2 receptor is highly expressed in the TMEM-associated TIE226 and the current clinical trial cohort, we used a high-throughput analytically validated assay (MetaSite Breast™) in a CLIA-certified clinical diagnostic laboratory for identification and enumeration of TMEM. Additional studies will be required to define the clinical utility of this assay in clinical practice.In conclusion, we report the results of a second prospective-retrospective validation study demonstrating the clinical validity of MetaSite Score in patients with ER+/HER2- breast cancer and show for the first time that it provides complementary prognostic information to Recurrence Score, specifically for early recurrence within 5 years of diagnosis. In both the original population-based cohort28 Briefly, 2952 eligible patients (of whom 2603 consented to future research) were randomly assigned to receive four 3-week cycles of doxorubicin 60 mg/m2 and cyclophosphamide 600 mg/m2 (AC) or docetaxel 60 mg/m2 (AT). Methods for selection of 776 cases  in the cohort have been previously described , and summarized in Supplemental Fig. 47 All specimens underwent analysis for tumor grade, and for ER, progesterone receptor (PR), and HER2 protein expression in a central lab as previously described47 (including HER2 assessment by 2007 ASCO-CAP guidelines used at the time48), and for Oncotype DX Recurrence Score in the Genomic Health, Inc.  laboratory. The weighted distributions of the characteristics of the patients in the sample of 600 cases and the E2197 cases not in the sample are compared in Supplemental Table The study utilized tumor specimens and clinical information from patients enrolled on trial E2197 , coordinated by the Eastern Cooperative Oncology Group (ECOG), details of which have been reported.The parent E2197 clinical trial was approved by the institutional review boards of all participating institutions and was carried out in accordance with the Declaration of Helsinki, Food and Drug Administration Good Clinical Practices, and local ethical and legal requirements. The use of specimens for this project was approved the North American Intergroup Correlative Science Committee, by the MD Anderson Cancer Center Institutional Review Board , and by the Albert Einstein College of Medicine Institutional Review Board .Breast™ assay was for identifying and enumerating TMEM was performed in a commercial CLIA-certified laboratory , as previously described.31 Briefly, tissue sections  were derived from tumor blocks at the ECOG-ACRIN Central Biorepository and Pathology Facility (CBPF), sent to MetaStat, and upon receipt were dipped in paraffin and stored under non-oxidizing and non-hydrolyzing conditions until stained. Tissue samples were stained using a modified triple chromogen immunohistochemical stain for CD31-positive blood vessels using a rabbit anti-CD31 monoclonal antibody (AbCam/Epitomics Clone EP3095), for CD68-positive macrophages using an anti-CD68 mouse monoclonal antibody (Thermo Scientific Clone PGM1), and for Mena-positive tumor cells using an anti-Pan-Mena mouse monoclonal antibody . CD31-positive blood vessels were visualized using blue chromogen, CD68-positive macrophages visualized using brown chromogen, and Mena using red chromogen. A pathologist reviewed each sample for quality and specific staining patterns based on established specificity criteria in addition to image capture of invasive cancer alone. Imaging was conducted using the Perkin Elmer Vectra 2 multispectral microscopy system , which allows for spectral un-mixing of chromogens enabling highly accurate imaging and image analysis. For whole tissue imaging, up to 100 20X high-resolution images were acquired in areas of invasive tumor using established and validated image analysis algorithms. All images used in analysis were reviewed by trained pathologists for image quality and histologic specificity. TMEM identification and enumeration were accomplished through a combination of InForm (PerkinElmer) and VisioPharm (VisioPharm) image analysis software. InForm generates spectrally unmixed composite images representing spectrally pure chromogen channels for CD31, CD68, and Pan-Mena. These images were then used in a VisioPharm MetaSite identification algorithm where TMEM were identified as microanatomic structures that meet established criteria for direct contact of all three cells. The number of TMEM for each image were quantified and reported as MetaSite Score. MetaSite Score was defined as the sum of TMEM sites from each of the top three highest density 20X fields-of-view. Prior to evaluation of samples from the E2197 trial, the analytical precision, reproducibility, and accuracy of the fully automated MetaSite Breast™ clinical assay was demonstrated in an analytical validation study using formalin-fixed, paraffin-embedded (FFPE) tissue samples from patients with invasive breast cancer.31The MetaSite 49 The number of events for each subgroup, overall and by follow-up time, are shown in Supplemental Table The primary endpoint for analysis was distant recurrence-free interval (DRFI), defined as time from entry on E2197 to first distant recurrence. DRFI is censored at the time last known to be free of distant recurrence. Because only the first recurrence of any type was recorded in the database, for patients with local or regional recurrence (before distant), DRFI is censored at the date of first recurrence. Other endpoints include recurrence-free interval (RFI), defined to be time from study entry to first recurrence of breast cancer at any site, censored at the date last known to be free of recurrence, and OS, defined to be the time from entry on E2197 to death from any cause, censored at the date last known to be alive. DRFI and RFI were defined in accordance with STEEP guidelines.50 While standard software can be used to compute the weighted estimates, special routines are often needed to compute correct standard errors. Distributions of the characteristics of patients were estimated using weighted proportions and weighted averages. Time to event distributions were estimated using weighted Kaplan–Meier estimators. Hazard ratios were estimated and regression analyses performed by fitting weighted partial likelihood models. All analyses were performed in R 3.2.3. Weighted partial likelihood models were fit using the coxph function with weights. A locally written function was used to compute the corrected variance using the score residuals from the fitted model. For time-varying coefficient models, start and stop arguments are used to create data sets for the contribution at each event time. Evaluation of prognosis associated with categorical Recurrence Score included the classical definitions of low, intermediate, and high , and also the definitions  used in the Trial Assigning Individualized Options for Treatment (TAILORx).29 Based on the assumption that 621 specimens would be available , it was estimated that the study would have 80% power using a two-sided 5% significance level to detect a hazard ratio of 2.0–2.2 associated with DRFI between the highest and the lowest tertile TMEM Score level, which was comparable to that observed in the original TMEM validation study .26 The study was conducted in accordance with reporting recommendations for tumor marker prognostic studies (REMARK) guidelines.51As previously described, although a biased sample was used, unbiased estimates of effect were obtained by weighting the contributions of observations by the inverse of the sampling fractions in the sampling groups (the strata by recurrence status combinations).The data sets generated during and/or analyzed during the current study are available in the NCTN/NCORP Data Archive (https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fnctn-data-archive.nci.nih.gov%2F&data=02%7C01%7CJSPARANO%40montefiore.org%7C882c9b32175548ab7eef08d4e7faffa1%7C9c01f0fd65e040c089a82dfd51e62025%7C0%7C0%7C636388512604292871&sdata=ACdv92L8ftF9KtBhkQLpCNh9zLPX3qhdDWN1WIp%2FH88%3D&reserved=0).Supplementary Tables 1–3Supplementary Figures 1Supplementary Figure 2


Long noncoding RNAs (lncRNAs) are emerging as an important controller affecting metabolic tissue development, signaling, and function. However, little is known about the function and profile of lncRNAs in osteoblastic differentiation in mice. Here, we analyzed the RNA-sequencing (RNA-Seq) datasets obtained for 18 days in two-day intervals from neonatal mouse calvarial pre-osteoblast-like cells. Over the course of osteoblast differentiation, 4058 mRNAs and 3948 lncRNAs were differentially expressed, and they were grouped into 12 clusters according to the expression pattern by fuzzy c-means clustering. Using weighted gene coexpression network analysis, we identified 9 modules related to the early differentiation stage (days 2–8) and 7 modules related to the late differentiation stage (days 10–18). Gene ontology and KEGG pathway enrichment analysis revealed that the mRNA and lncRNA upregulated in the late differentiation stage are highly associated with osteogenesis. We also identified 72 mRNA and 89 lncRNAs as potential markers including several novel markers for osteoblast differentiation and activation. Our findings provide a valuable resource for mouse lncRNA study and improves our understanding of the biology of osteoblastic differentiation in mice. Ossification is a tightly regulated process which is performed by specialized cells called osteoblasts differentiated from mesenchymal progenitors. The osteoblast differentiation process is regulated by several key factors and signaling pathways. Runt-related transcription factor 2 (Runx2) is the master switch in the commitment of mesenchymal progenitors to osteoblast lineage . Runx2 iLong noncoding RNAs (lncRNAs) are a class of RNA transcripts longer than 200 nucleotides, lacking open reading frames and protein-coding possibilities . Tens ofIn order to fully understand the lncRNA biology including its role in osteogenesis, it is necessary to characterize the expression pattern of lncRNA during osteoblast differentiation. In this study, we analyzed RNA-sequencing datasets obtained at nine different time points in the osteoblast differentiation of preosteoblasts isolated from neonatal mouse calvaria, using various bioinformatic approaches. We focused on identifying differentially expressed lncRNAs and mRNAs throughout the process and finding potential markers that exhibited significant changes in expression during the osteoblast differentiation.http://www.noncode.org) annotations were used. Since NONCODE v4 annotations were based on mm9 mouse genome assembly, the positions of lncRNAs of NONCODE were converted from mm9 to mm10 using the LiftOver utility in UCSC. To assess gene expression, RPKM (reads per kilobase of exon per million mapped reads) values were calculated [p values using the Benjamini–Hochberg algorithm. Differentially expressed genes were defined as those with FDR less than 5% with an absolute value of fold change ≥ 2. Similar differential expression analyses were performed for lncRNAs.We analyzed the RNA-Seq data generated by Kemp et al.   were processed and mapped against mouse genome reference (mm10) sequence, and uniquely mapped reads  were used for further analysis . Based oComparing the expression of individual genes at different time points using all possible combinations, 46% of the mapped genes  were differentially expressed over time . For example, a comparison of gene expression between the two time points selected in the early and late stages (day 2 and day 18) is shown in During the differentiation process, several genes are dynamically expressed via complex regulatory mechanisms. To characterize temporal gene expression changes and patterns, we identified genes that were differentially expressed across the time course of osteoblast differentiation. A number of rules were applied to establish significant differential expression of genes at different time points: (1) statistical significance of temporal gene expression changes assessed via edgeR and DESeq methods (FDR < 0.05), (2) absolute fold change between day 2 and at least one other time point ≥ 2, and (3) maximum RPKM across the time series ≥ 3.In total, 4058 genes were significantly differentially expressed during osteoblast differentiation. They were associated with osteogenesis processes, such as “extracellular matrix organization,” “osteoblast proliferation,” “osteoblast differentiation,” “positive regulation of osteoblast differentiation,” and “actin cytoskeleton and bone mineralization.” Principal component analysis (PCA) of these genes revealed that 95% of the variations in gene expression could be explained by the first two principal components (PCs)  cell proliferation, (2) matrix maturation, and (3) matrix mineralization . Here, wDifferentially expressed genes identified by time series analysis were clustered according to their expression profiles  using the fuzzy c-means algorithm implemented in R Mfuzz package. Genes with similar time-specific expression patterns were clustered into 12 groups, each containing 191–570 genes . Eight aWe focused on clusters 1, 7, 9, and 10, each containing 511, 570, 243, and 297 genes with high expression patterns in the late differentiation stage . AssessmWe determined the common function among the three clusters through GO and KEGG enrichment analysis. As shown in Gene coexpression patterns may provide information on gene networks or pathways related to different biological phenomena. We constructed a coexpression network of genes using time series gene expression data. The weighted gene coexpression network analysis (WGCNA) generated a total of 16 network modules . The eigr > 0.6), and they were enriched with the following KEGG pathways and GO terms, besides “cell adhesion” and “osteoclast differentiation,” as mentioned above: PPAR signaling, subset of extracellular matrix, calcium metabolism, glucose homeostasis, cell signaling, and regulation of bone mineralization. This indicates that these two modules are strongly associated with late osteoblast differentiation (day 18). Thus, from the two modules , we extracted 36 and 62 hub genes, respectively, with high connectivity (MM > 0.9), and these genes were used to find biomarkers for osteoblast differentiation as described below.Notably, the genes belonging to the cyan and salmon modules exhibited high trait association correlation  and late differentiation (average expression from samples of days 10–18) must be >2 and at least one of the samples should have an RPKM value > 5 for the gene.We identified a total of 72 genes as potentially useful marker candidates for osteoblast differentiation  . Dcn de. AlthougThe NONCODE (v4) database was used for lncRNA annotations, and at least one read was mapped onto 37,431 lncRNAs during osteoblast differentiation. Hierarchical clustering was performed based on the expression profiles in each sample. Upon application of similar approaches for known Ensembl genes to lncRNAs, we identified that 54% of the total lncRNAs  were differentially expressed across the stages of osteoblast differentiation. Similar to the expression profile of mRNA described above, the expression patterns of lncRNAs were different between the early differentiation stage (2–8 days) and the late differentiation stage (10–18 days) . The numExamination of the temporal expression changes of lncRNAs revealed that levels of 3948 out of 37,431 lncRNAs were dynamically altered over the course of osteoblast differentiation. In PCA analysis using 3948 time series lncRNAs, 97% of the variations in lncRNA expression patterns could be explained by the first two principal components (PCs) . Some ofUsing R package Mfuzz , differeExpression patterns of lncRNAs belonging to cluster 5 were not only very similar but also significantly increased over time, especially between 10 and 18 days. Thus, we focused on cluster 5 to find the lncRNAs markers associated with late differentiation of osteoblasts. Cut-off values were set for lncRNAs  of the 89 lncRNAs with background controls generated from all NONCODE lncRNA promoter regions. We performed the motif enrichment analysis using MEME Suite package  and the We employed public RNA-Seq data (NCBI GEO accession number GSE54461) to profile mRNA and lncRNA expression and identified a series of biomarkers potentially associated with bone differentiation. Data from the current study showed that a combination of bioinformatic approaches, including (1) time series, (2) clustering, and (3) coexpression network analyses, provides an effective means to identify novel candidate markers associated with osteoblast differentiation. Expression patterns of mRNA and lncRNA during osteoblast differentiation were defined as two distinct stages (early and late osteoblast differentiation). Functional annotation showed that the members in the late stage are involved in osteogenesis processes. Notably, common transcription factor binding motifs were enriched in the identified lncRNA markers. Our findings provide a valuable resource for lncRNA study and understanding of the mechanism of mouse osteoblast differentiation. Further research is needed to determine the functions of lncRNA and mRNA identified as potential markers in this study.


The value of sentinel lymph node biopsy (SLNB) in post-neoadjuvant chemotherapy (NCT) patients is still controversial. We aimed to identify predictors and construct a nomogram for predicting the pathologically complete response (pCR) of axillary lymph nodes (ALNs) after NCT in node positive breast cancer patients. In total, 426 patients with pathologically proven ALN metastasis before NCT were enrolled, randomized 1:1 and divided into a training set and a validation set. We developed a nomogram based on independent predictors for ALN pCR identified by multivariate logistic regression as well as clinical significant predictors. The multivariate logistic regression analysis showed that hormone receptor (HR) status, human epidermal growth factor 2 (HER2) status and Ki67 index were independent predictors. The nomogram was thereby constructed by those independent predictors as well as tumor size and NCT regimens. The areas under the receiver operating characteristic curve of the training set and the validation set were 0.804 and 0.749, respectively. We constructed a nomogram for predicting ALN pCR in patients who received NCT. Our nomogram can improve risk stratification, accurately predict post-NCT ALN status and avoid unnecessary ALN dissection. Breast cancer has been reported to be the most common malignant tumor and the second leading cause of cancer death among women in America. The incidence of breast cancer is increasingMastectomy together with routine axillary lymph node (ALN) dissection used to be the standard type of surgery for breast cancer patients46The use of SLNB in patients after receiving NCT is still in doubt because chemotherapy can cause fibrosis of the lymphatic duct leading to the sentinel lymph nodes, thus interfering with the accuracy of SLNB91011Our current research is intended to identify possible predictors and construct a nomogram for predicting pCR of ALN post-NCT among node positive breast cancer patients, which will increase the accuracy of SLNB post-NCT. In combination with SLNB and nomogram prediction, it may be possible for patients with a high probability of ALN pCR to avoid ALN dissection.Relevant clinical information , ALN status, core needle biopsy (CNB) samples from primary tumors and surgical specimens were collected from 1244 consecutive patients who received NCT as well as standard surgery at the Fudan University Shanghai Cancer Center (FUSCC) between January 1, 2003 and April 30, 2015.The eligibility criteria included: 1) diagnosed with primary breast cancer, 2) received NCT, and 3) had pre-NCT axillary nodal disease confirmed by pathology. Patients with missing data, uncertain pre-NCT axillary nodal status or negative nodal disease confirmed by pathology, or with distant metastatic disease were excluded. The eligible patients were randomized 1:1 and divided into a training set (nomogram construction) and a validation set .in situ hybridization (FISH) analyses, which were performed on formalin-fixed, paraffin-embedded tissue sections by the pathology department of FUSCC using standard protocols for specimens from CNB. The cut-off value for estrogen receptor (ER) positivity and progesterone receptor (PR) positivity was set at 1%. The absence of both ER and PR was defined as HR negative; the presence of either was defined as HR positive. HER2 positive was defined as 3(+) according to IHC analysis or amplification confirmed by FISH; lower scores were defined as HER2 negative. The Ki67 expression was divided into two groups: Ki67 > 20% and Ki67 ≤ 20%The ALN status before NCT was evaluated by fine needle biopsy. The hormone receptor (HR) status, the human epithelial growth factor receptor 2 (HER2) status and the Ki67 index were evaluated by immunohistochemical (IHC) and fluorescence The pCR of the ALN was defined as the complete disappearance of invasive carcinoma of the regional lymph nodes after the patients received mastectomy with axillary lymph node dissection14The patients in our cohort received an NCT regimen consisting of epirubicin + paclitaxel contained  and PC (paclitaxel and carboplatin or paclitaxel and cisplatin) for a median of 4 cycles . After 2007, trastuzumab  was recommended for HER2 positive patients combined with chemotherapy as the neoadjuvant therapy regimen.To develop a well-calibrated nomogram for predicting the probability of pCR of the ALN, we performed univariate as well as multivariate logistic regression analyses to screen the fit predictorsThe nomogram was validated internally in the training set and externally in the validation set. The internal validation was performed by a calibration method and the area under the receiver operating characteristic (ROC) curve (AUC). The external validation was performed by calculating the AUC. The calibration plot with bootstrapping was used to illustrate the association between the actual probability and the predicted probabilityhttp://www.r-project.org). The R package with the rms, pROC, Hmisc, and ggplot2 (available at URL: http://cran.r-project.org/web/packages/) was used . All relevant R code were shown in All reported P values are two-sided. The statistical analysis was carried out using SPSS  and R software version 3.13  of the World Medical Association. This study was approved by the Ethics Committee of FUSCC, and each participant signed an informed consent document.Among 1244 patients, 605 of them were pathologically confirmed ALN metastasis before NCT. After excluding 179 patients with incomplete relevant information, 426 eligible patients were included in the study . The 426Multivariate logistic regression analysis was performed to identify independent variables for predicting the pCR of the ALN post-NCT . PredictIndependent predictors identified in the multivariate logistic regression analysis (P < 0.05), including HR status, HER2 status and Ki67 index as well as tumor size and NCT regimens were utilized to construct the nomogram. The total points were summed up by the points of each variable . The ALN pCR probability was subject to the total points . The P-value for the Hosmer and Lemeshow test was 0.626, indicting a good fit to the model. The final nomogram is shown in The calibration of the nomogram was performed internally by a calibration plot with bootstrap sampling (n = 1000) . CalibraNext, the ROC was performed to validate the nomogram internally in the training set  and exteValues of sensitivity, specificity, and predictive values of the predicted probability at different cutoff values of the nomogram were shown in To display the application of the nomogram, we took two pathologically proven node positive breast cancer patients who had received NCT as examples. The first patient’s tumor size was T1 (75 points). Her HR status was negative (100 points), and her HER2 status was positive and she received H for treatment (75 points). Her Ki67 index was more than 20% (53 points). Her NCT regimen was PC (46 points). According to her total points (349 points), she had a high probability (>0.9) of showing ALN pCR post-NCT, and her actual ALN status after NCT was pCR. The second patient’s tumor size was T4 (0 points). Her HR status was negative (100 points), and her HER2 status was negative (0 points). Her Ki67 index was no more than 20% (0 points). Her NCT regimen was E + P (0 points). According to her total points (100 points), she had a relatively low probability of reaching ALN pCR post-NCT (0.1–0.2), and her actual ALN status after NCT was not pCR.In our current research, we first randomized the population containing 426 pathologically proven ALN positive patients who received NCT into a training set and a validation set. Based on the multivariate logistic regression analysis, we identified independent variables for predicting the ALN pCR after NCT. Patients who were HR positive were less likely to show ALN pCR than those who were HR negative. Patients who were HER2 positive and reveived H were more likely to show ALN pCR than those who were HER2 negative, and patients with Ki67 > 20% were more likely to show ALN pCR than those with Ki67 ≤ 20%. Tumor size and NCT regimens did not showed statistically significance in the multivariate logistic regression analysis. Next, we constructed a nomogram on the basis of these predictors as well as clinical significant predictors (tumor size and NCT regimens). The AUCs of the ROCs in the training  and validation sets  were 0.804 and 0.749, respectively.At present because of the lack of reliable diagnostic approaches to evaluate lymph node status after receiving NCT for pathologically proven node positive breast cancer patients422232425et al. reported that HER2 positive patients had a higher rate of ALN pCR than HER2 negative patients, which was consistent with our dataet al. enrolled 291 patients with clinically proven node positive breast cancerAccording to our results, patients who were HR negative, HER2 positive and reveived H or had higher Ki67 expression were more likely to show ALN pCR than the other patients. Previous studies showed high concordance rates of receptor status  between primary and ALN metastatic lesions27293031The nomogram, a simple graphical prediction tool, allows oncologists to assess the predictive risk of individuals911et al. evaluated the diagnostic value of ultrasound, MRI and PET/CT for ALN metastases after NCTRecently, You Combined with our nomogram, the accuracy of SLNB post-NCT can be further improved. According to our nomogram, patients with high points were more likely to show ALN pCR. If their SLNB post-NCT showed no metastases in the lymph nodes, they could safely avoid receiving ALN dissection.One major limitation of our study was that the design was a single-center retrospective analysis and we did not compare the predictive power of SLNB together with the nomogram with the SLNB alone because of the lack of data. In the future, two related randomized prospective clinical trials in progress may help to validate the nomogram. The first one is NCT01901094, which evaluates the efficacy of ALN dissection compared with ALN radiation therapy in ALN positive breast cancer patients convert to negative after NCT. The second one is NSABP B-51 (NCT01872975), which evaluates whether comprehensive radiation therapy in ALN after surgery may improve prognosis in ALN positive breast cancer patients convert to negative after NCT. Those researches will also investigate the survival benefits of avoiding ALN dissection for some patients.We constructed a nomogram for predicting post-NCT ALN pCR. With the nomogram, we can predict post-NCT ALN status accurately and avoid unnecessary ALN dissection.How to cite this article: Jin, X. et al. A Nomogram for Predicting the Pathological Response of Axillary Lymph Node Metastasis in Breast Cancer Patients. Sci. Rep.6, 32585; doi: 10.1038/srep32585 (2016).


Sm-cbp1. We found that depleting cbp1 transcript levels with RNA interference (RNAi) resulted in increased neoblast proliferation and cell death, eventually leading to organ degeneration. Based on these observations we speculated this increased rate of neoblast proliferation may be a response to mitigate tissue damage due to increased cell death. Therefore, we tested if mechanical injury was sufficient to stimulate neoblast proliferation. We found that mechanical injury induced both cell death and neoblast proliferation at wound sites, suggesting that schistosome neoblasts are capable of mounting proliferative responses to injury. Furthermore, we observed that the health of cbp1(RNAi) parasites progressively declined during the course of our in vitro experiments. To determine the fate of cbp1(RNAi) parasites in the context of a mammalian host, we coupled RNAi with an established technique to transplant schistosomes into the mesenteric veins of uninfected mice. We found transplanted cbp1(RNAi) parasites were cleared from vasculature of recipient mice and were incapable of inducing measurable pathology in their recipient hosts. Together our data suggest that injury is sufficient to induce neoblast proliferation and that cbp1 is essential for parasite survival in vivo. These studies present a new methodology to study schistosome gene function in vivo and highlight a potential role for schistosome neoblasts in promoting tissue repair following injury.Schistosomiasis is second only to malaria in terms of the global impact among diseases caused by parasites. A striking feature of schistosomes are their ability to thrive in their hosts for decades. We have previously demonstrated that stem cells, called neoblasts, promote homeostatic tissue maintenance in adult schistosomes and suggested these cells likely contribute to parasite longevity. Whether these schistosome neoblasts have functions independent of homeostatic tissue maintenance, for example in processes such as tissue regeneration following injury, remains unexplored. Here we characterize the schistosome CBP/p300 homolog,  cbp1 results in cell death and degeneration of certain schistosome tissues and causes dramatic increases in the level of stem cell proliferation. This result suggested that the parasites might perceive elevations in cell death as a form of injury, which then triggers stem cell proliferation to enhance the rate of tissue repair. To explore this idea further, we physically injured parasites and observed that physical injury was indeed capable of inducing stem cell proliferation. We also found that loss of cbp1 resulted in the progressive decline in the health of parasites cultured in the laboratory, likely as a result of increased cell death and tissue degeneration. To determine if cbp1 was also important for parasites living inside a mammalian host, we coupled our gene disruption approaches with a classic technique to transplant schistosomes into the veins of uninfected mice. Using this novel methodology, we found that reducing cbp1 levels resulted in parasite death inside mice. Taken together, these observations demonstrate that cbp1 is important for parasite survival inside a mammalian host and show that schistosome stem cells are capable of responding to injury. These data have important implications for the development of new therapies and for understanding the roles stem cells play in the biology of schistosome infection.Schistosomes are parasitic flatworms that infect more than 200 million people in the developing world. Once these parasites infect a human, they are capable of living in the bloodstream for decades. Previously, our group has shown that these parasites have stem cells that are capable of renewing worn out cells in these parasites. Although we know these stem cells can continuously restore aging tissues, whether these stem cells can respond to injuries in the parasite is not clear. Here, we show that reducing levels of a gene called  Schistosomes infect over 200 million people and are a major cause of morbidity in the developing world. The primary driver of this morbidity is the prodigious egg production of these parasites, which can lay several hundred eggs every day while living in the vasculature of their hosts . A largein vivo.Schistosomes possess a population of somatic stem cells similar to the neoblasts found in free-living flatworms  , 4. In sSm-cbp1 , a gene that encodes a homolog of the mammalian CBP/p300 family of proteins [cbp1 was previously demonstrated to act as a transcriptional co-activator in vitro [cbp1 function leads to simultaneous increases in cell death and neoblast proliferation. Based on our observation that physical injury similarly induces parasite cell death and neoblast proliferation, we suggest that increases in neoblast proliferation following cbp1(RNAi) is a strategy by the parasite to cope with cell death-mediated tissue damage. In addition, we report a novel application of existing techniques to examine adult schistosome gene function in vivo and show that cbp1 is essential for parasite survival in mice. These data suggest an important function for cbp1 in parasite survival and highlight a potential role for neoblasts in regenerative processes in schistosomes.During the course of a systematic effort to identify factors with the potential to regulate schistosome neoblast function we characterized proteins . In mammproteins . In schiin vitro  and suggin vitro . Here wecbp1 was expressed in adult parasites in a variety of cells throughout the worm’s parenchyma and in cells within the male testes and female ovaries  with two markers of somatic cells residing in the parenchyma: Histone H2B to mark neoblasts [tsp-2 to label tegument-associated cells [Histone H2B+ and tsp-2+ cells, we weakly detected cbp1 transcripts in most cells within the schistosome parenchyma  we found that  ovaries . To chareoblasts  and tsp-ed cells . In addirenchyma . While wcbp1 in regulating schistosome stem cells, we performed RNAi experiments. In comparison to controls, depletion of cbp1 mRNA levels . First, loss of cbp1 could block the ability of neoblasts to differentiate, effectively locking the cells in a proliferative state. This type of behavior is observed following perturbations that block planarian neoblast differentiation [tsp-2. Previously we demonstrated that tsp-2 is expressed in a tegument-associated cell population that is the primary differentiation progeny of schistosome neoblasts [tsp-2+ cells are short lived and rapidly renewed by neoblasts [cbp1(RNAi) parasites maintaining the ability to differentiate, we observed substantial increases in the number of tsp-2+ cells in cbp1(RNAi) parasites  animals. We explored this observation more closely by double FISH for Histone H2B and the esophageal gland marker meg-4 [cbp1(RNAi) parasites (Histone H2B+ neoblasts (cbp1(RNAi) panels). In the most severe cases, the esophageal glands were degenerated and only small numbers of meg-4+ cells remained (cbp1(RNAi) panels). To explore the degeneration of the esophageal glands in more detail, we performed time course analyses examining the expression of meg-4 by WISH. We observed a progressive degeneration of the esophageal gland in cbp1(RNAi) parasites and by D18 cbp1(RNAi) parasites possessed few traces of meg-4+ gland cells  parasites. In principle, the observed masses of neoblasts (meg-4 expression by FISH. In control(RNAi) parasites, neoblast depletion had no observable effect on the morphology of the esophageal gland at D11 (cbp1(RNAi) parasites displayed extensive degeneration of the esophageal glands (cbp(RNAi) parasites, we noted more scattered meg-4+ cells in unirradiated cbp1(RNAi) where neoblasts were present  parasites represent newly born differentiation progeny of the neoblasts.We next explored the relationship between neoblast proliferation and the degeneration of the esophageal glands in eoblasts  could eieoblasts , we belid at D11 . In contl glands , suggestcbp1(RNAi) parasites had large clusters of TUNEL+ cells within their esophageal glands (+ cells were not observed in cbp1(RNAi) parasites with largely intact glands nor in parasites with severely degenerated glands. Rather the presence of large numbers of TUNEL+ cells was restricted to glands that appeared to be in the early to intermediate stages of degeneration. These data suggest that programmed cell death is a likely driver of esophageal gland cell loss.Our data indicated that between D8 and D14 a large fraction of parasites had esophageal glands that were in intermediate stages of degeneration . To detel glands . Visualicbp1(RNAi) parasites we noted elevations in cell proliferation and cell death at roughly similar time points after beginning dsRNA treatment  parasites (cbp1(RNAi) parasites (+ cells in cbp1(RNAi) parasites  parasites: some cbp1(RNAi) parasites possessed levels of TUNEL+ nuclei comparable to controls, whereas in other parasites the number of TUNEL+ nuclei was dramatically elevated (cbp1(RNAi) worms. Unfortunately, given the paucity of cell type-specific markers that are compatible with TUNEL staining, it is presently not possible to determine if this elevated rate of cell death was restricted to a specific cell/tissue type or whether all tissues were undergoing similar levels of cell death. Nevertheless, our data suggest that in addition to being required for preventing cell death, and degeneration of the esophageal gland cells, cbp1 is important for maintaining normal levels of cell death in other tissues within the parasite.In the esophageal glands of ent Figs  and 3C. arasites  we exploarasites . Althougarasites ; by D14 ectively . Intereselevated . This obelevated . TherefoHydra [Drosophila [cbp1(RNAi) parasites could be that cbp1 is required for the survival of various cell types in the worm  and that death of these cells induces neoblast proliferation. Alternatively, cbp1 could be acting in some cells  to promote cell survival and acting independently in neoblasts to repress proliferation. To indirectly distinguish between these possibilities, and examine if tissue injury can induce both cell death and neoblast proliferation in schistosomes, we physically injured male parasites. For these experiments, parasites were immobilized on an agarose pad and poked with a sharpened tungsten needle  tissue osophila . Therefon needle . Consistt-injury . We nextt-injury  and Histeoblasts  surroundeoblasts . Intereseoblasts . This sucbp1(RNAi) parasites became progressively sicker during in vitro culture (cbp1(RNAi) parasites became unpaired and lost the ability to attach to the surface of the tissue culture dish (cbp1(RNAi) parasites was limited to irregular and jerky motions (cbp1(RNAi) parasites were indistinguishable from unirradiated cbp1(RNAi) parasites with regards to male-female pairing and attachment to the substrate  parasites did not display hepatosplenomegaly (cbp1(RNAi) recipient mice (cbp1(RNAi) recipient mice confirmed that control parasites were capable of generating egg-induced pathology whereas no egg-induced inflammation was observed in cbp1(RNAi) recipient mice  recipient mice (cbp1(RNAi) parasites trapped in the liver of these mice (cbp1(RNAi) parasites are incapable of establishing an infection. Based on what we observe in vitro , we knoparasite . This ceHydra, programmed cell death releases Wnt molecules that are required to induce stem cell proliferation and regeneration following amputation [Drosophila, genetic induction of apoptosis stimulates proliferation of intestinal stem cells [While physical injury induces schistosome neoblast proliferation, the precise role apoptosis and other types of cell death  play in this process are not known. In the cnidarian putation . In Drosem cells . In planem cells . Therefocbp1 homologs serve as transcriptional co-activators linking transcription factors to the core transcriptional machinery [cbp1 relatives also possess acetyltransferase activity and can acetylate a variety of substrates including histones and non-histone proteins [cbp1 are important for maintaining schistosome cellular viability is not presently clear. However, previous studies have shown that pharmacological inhibition of histone deacetylase activity induces apoptosis in larval schistosomes [cbp1 possesses histone acetyltransferase activity in vitro [cbp1 may be due to alterations in chromatin landscape in certain cell types. Further exploration of chromatin-modifying enzymes may represent fertile ground for the development of novel therapeutics.Mammalian achinery . These mproteins . Whetherstosomes , 29. Thuin vitro , the celcbp1 is required for parasite survival in vivo. Not only do these studies validate the potential to target cpb1 therapeutically, they provide a novel methodology to explore the functions of schistosome genes in vivo. A potentially useful application of this approach is for studies of schistosome reproduction. Since schistosome reproduction ceases within one week of in vitro culture [in vitro [in vivo is not known. However, as tools to manipulate the schistosome genome  continue to mature, we suggest surgical transplantation could become an invaluable tool to explore gene function in vivo.Here, we combine a previously described method for the surgical transplantation of schistosomes and RNA interference to demonstrate that  culture , this apin vitro , how thiin vivo. The regenerative potential of schistosomes has not been extensively characterized and conflicting reports exist. Senft and Weller reported that schistosomes amputated during recovery from mice were capable of regenerating new tails in vitro [in vitro cultured worms were capable of rapidly healing wounds, but incapable of regeneration [in vivo exposure to sublethal doses of the anthelminthic drug praziquantel [in vivo.Our observation that injury is met with increases in neoblast proliferation indicates schistosomes may possess the capacity to regenerate following certain types of injury in vitro . Howeverneration . Thus, tiquantel . Thus, fIn adherence to the Animal Welfare Act and the Public Health Service Policy on Humane Care and Use of Laboratory Animals, all experiments with and care of vertebrate animals were performed in accordance with protocols approved by the Institutional Animal Care and Use Committee (IACUC) of the UT Southwestern Medical Center .S. mansoni (6–8 weeks post-infection) were obtained from infected female mice by hepatic portal vein perfusion with 37°C DMEM  plus 10% Serum  and heparin. Parasites were cultured as previously described [Adult escribed . Unless in situ hybridization and RNA interference were cloned as previously described [cDNAs used for escribed . Quantitescribed . Oligonuin vitro transcription [137 source. Lectin labeling was performed as previously described [EdU labeling, whole-mount in situ hybridization and fluorescence in situ hybridization analyses were performed as previously described , 5. For cription  and was cription . Sequencescribed . For TUNescribed ), and in+ and TUNEL+ cells, cells were manually counted in maximum intensity projections derived from confocal stacks; to normalize between samples cell counts were divided by the total volume of the stack in μm3. All plots and statistical analyses were performed using GraphPad Prism.Confocal imaging of fluorescently labeled samples and brightfield imaging  were performed using a Zeiss LSM700 Laser Scanning Confocal Microscope or a Zeiss AxioZoom V16 equipped with a transmitted light base and a Zeiss AxioCam 105 Color camera, respectively. All images of fluorescently-labeled samples represent maximum intensity projections. To perform counts of EdU2O. After removal of excess liquid, worms were perforated with a sharpened tungsten needle. The impaled parasites were then carefully removed from the needle into fresh media using a pipette tip. As a control, “mock” injured parasites were similarly transferred to Petri dishes but were not injured; we observed no changes in cell death or cell proliferation in these parasites.For injury, worms were gently pipetted onto the surface of a 35 mm Petri dish filled with solidified 4% agarose diluted in HMethods for surgical transplantation of schistosomes are based on a procedure originally developed for hamsters . 4 to 5 S1 Figcbp1 cDNA (top) and cDNA regions (in bp) targeted by two independent RNAi constructs (pJNC9.1 and pJC259.1). pJNC9.1 contains a cDNA fragment that spans from 2057bp to 3060 bp of the cbp1 cDNA. pJC259.1 contains a cDNA fragment that spans from 4838bp to 5015bp and 5621bp to 5839bp of the cbp1 cDNA; this cDNA appears to be alternatively spliced relative to the cbp1 gene model. Full-length sequences of these cDNA fragments are found in (A) Cartoon of cbp1 in control and cbp1(RNAi) parasites relative to a proteasome subunit (Smp_056500) as measured by qPCR. cbp1(RNAi) treatment using dsRNA produced from pJNC9.1 results in a statistically significant reduction in cbp1 mRNA levels . Similar levels of knockdown were observed with pJC259.1. Error bars represent 95% confidence intervals.(B) Expression of cbp1(RNAi) parasites treated with dsRNA generated from pJC259.1 at D13 of RNAi. cbp1(RNAi) using dsRNA produced from pJC259.1 resulted in elevations in cell proliferation similar to RNAi treatment using dsRNA from pJNC9.1. Parasites were pulsed with EdU overnight prior to fixation. Arrowhead indicates approximate position of esophageal gland where we often noted large numbers of proliferative neoblasts.(C) EdU labeling in control and (TIF)Click here for additional data file.S2 Figcbp1(RNAi) pJNC9.1, and (C) cbp1(RNAi) pJC259.1.(A-C) Shown are sequences used as templates to generate dsRNA for (A) control(RNAi) (B) (TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S1 Moviecbp1(RNAi) parasites declines beginning around D8 of RNAi when parasites become unpaired and fail to attach to the surface of the culture dish. This deterioration of the health of cbp1(RNAi) parasites is not influenced by stem cell number since irradiated cbp1(RNAi) parasites experience similar declines as unirradiated worms.The health of (MP4)Click here for additional data file.


Multiple synchronous lung cancers (MSLCs) present a clinical dilemma as to whether individual tumours represent intrapulmonary metastases or independent tumours. In this study we analyse genomic profiles of 15 lung adenocarcinomas and one regional lymph node metastasis from 6 patients with MSLC. All 15 lung tumours demonstrate distinct genomic profiles, suggesting all are independent primary tumours, which are consistent with comprehensive histopathological assessment in 5 of the 6 patients. Lung tumours of the same individuals are no more similar to each other than are lung adenocarcinomas of different patients from TCGA cohort matched for tumour size and smoking status. Several known cancer-associated genes have different mutations in different tumours from the same patients. These findings suggest that in the context of identical constitutional genetic background and environmental exposure, different lung cancers in the same individual may have distinct genomic profiles and can be driven by distinct molecular events. Some patients present with multiple lung tumours but it is unclear whether these are metastases or individual lesions. Here, the authors use genomics techniques to demonstrate in six patients that multiple tumours have individual genetic profiles and represent separate tumours. Lung cancer is a heterogeneous disease, with genomic and phenotypic features that differ between different patients and even between different regions of a tumour. Substantial inter-tumour heterogeneity, probably reflecting distinct genetic backgrounds and different carcinogen exposures in different patients with lung cancer, has been well documented13567MSLCs may represent hematogenous metastases from a single primary cancer, local spread of a single primary lesion or multiple individual primary cancers. In 2007, the American College of Chest Physicians (ACCP) classified MSLCs of the same histology into satellite nodules , multiple primary lung cancers  and hematogenously spread pulmonary metastases 67To determine the genomic heterogeneity of MSLCs and assess the clonal relationships between different tumours within the same patients, we perform whole-genome sequencing (WGS) or whole-exome sequencing in combination with microarray-based comparative genomic hybridization (CGH) on 16 tumour samples  and one regional lymph node metastasis) from six patients with MSLCs. Five patients had satellite nodules, and one had hematogenously spread pulmonary metastasis according to the ACCP criteria . For allIn total, 1,127 nonsynonymous coding and splice site mutations were detected . Of thosKRAS (p.G12V) mutation and a STAG2 nonsense mutation (p.R305X), suggesting that the tumour metastasized to the lymph node , suggesting that these patients had multiple primary lung cancer . In patimph node  and 2. NEGFR p.L858R mutation was the only mutation shared by all three tumours of patient 6  to that in a large cohort of Chinese lung adenocarcinoma patientsP=0.23 by Fisher's exact test). Thus, with no other evidence of shared mutations, the data suggest that patient 6 likely had three primary tumours carrying independent EGFR p.L858R mutations.An atient 6  and 2. TEGFR p.L858R mutation shared by tumours 1 and 2, and an ARHGAP35 p.E25K mutation shared by tumours 1 and 3  one of the two tumours was a metastasis of the other; or (ii) the two tumours arose independently, each acquiring an ARHGAP35 p.E25K mutation during cancer development. The data from patient 1 and previous studies416ARHGAP35 p.E25K independently, we compared our data with The Cancer Genome Atlas (TCGA) data for a series of single primary tumours from 35 unrelated lung adenocarcinoma patients matched for tumour size and smoking statusP=0.72 by Fisher's exact test, In patient 5, two somatic mutations were concordant among the three tumours sequenced: an  1 and 3  and 2. ATo maximize the opportunity to uncover evidence of tumour relatedness in our MSLC cohort, we expanded the mutation data set to include all validated mutations plus all mutations that were called by both VarScanWe then compared the exonic point mutations in the 16 MSLC lesions in our cohort and those in the 35 unrelated lung adenocarcinomas in the TCGA studyEGFR mutations mentioned above, no known cancer gene mutations were shared between any two tumours from the same patients, suggesting that different tumours in the same patients may have been driven by different molecular events. On the other hand, three cancer genes demonstrated different mutations in different tumours of the same patients. In patient 1, tumour 3 (and the associated lymph node metastasis) harboured a KRAS p.G12V mutation, whereas tumour 1 had a KRAS p.G12A mutation. Different mutations were also observed in STK11 in patient 1 (a missense mutation p.K78N in tumour 1 and a nonsense mutation p.Q37X in tumour 2) and in EGFR in patient 4 (p.L858R in tumour 1 and p.S229C in tumour 2). In addition, two different PIK3CA mutations, p.G1007R and p.H1047R, were found in tumour 3 of patient 5.We next examined the pattern of known cancer gene mutations in our series. We defined cancer gene mutations as nonsynonymous mutations identical to those previously reported in known cancer genes or truncating mutations in known tumour suppressor genes1819202122CpW sites, where W is A or T). APOBEC signature enrichment was found in 15 of the 16 tumours, and the enrichment odds ratios were significant in 7 tumours of four patients  profiles of all tumours. In general, SCNAs were relatively few  compared12Eleven exonic small insertions/deletions (indels) were identified . Each indel was detected in no more than one tumour , consistMSLCs have been reported to account for 0.2–8% of lung cancers10122830In addition, several cancer genes had different mutations in different tumours within the same patients. This finding is reminiscent of intratumour heterogeneity observed for clear cell renal cell carcinomaset al. have investigated comprehensive histologic assessment and have shown promising results8351617MSLCs could be multiple primary tumours that are potentially curable or intrapulmonary metastases that could be taken as an indication of unresectable disease. Many attempts have been made to distinguish these clinical entities. Martini–Melamed criteriaSurgical specimens and peripheral blood samples were collected from six patients who were diagnosed with pathologically confirmed multiple synchronous lung adenocarcinomas, with two or three tumours in the same lung, and treated at the Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China. Tumour sizes ranged from 0.5 to 3.6 cm according to pathology reports. All patients were free of extrathoracic metastasis. Patient 1 had metastasis to a mediastinal lymph node, but no other patient had lymph node involvement. None of the patients had pre-operative chemotherapy or radiation therapy. Four patients were never smokers, and two were former smokers. The patients' clinical characteristics are listed in After resection, ten 10 μm fresh frozen sections for each tumour sample or ten 10 μm formalin-fixed paraffin-embedded sections for the regional lymph node metastasis were collected. Haematoxylin–eosin-stained slides  were revGenomic DNAs were fragmented into 500-bp segments by using the Covaris  E210 instrument. The double-stranded DNA fragments consisted of 3′ or 5′ overhangs. T4 DNA polymerase and Klenow enzyme  were then used to convert the overhangs into blunt ends. An A base was added to the 3′-end of the blunt phosphorylated DNA fragments, which was ligated with adapters on both ends. The correctly ligated products were purified by agarose gel electrophoresis and then with the QIAquick Gel Extraction Kit . DNA fragments with adapter molecules on both ends were selected and amplified. After PCR using primers that anneal to the ends of the adapters, the products were checked and purified by agarose gel electrophoresis and sequenced using the HiSeq 2000 system . The average sequencing depth was 35 × per sample .Genomic DNAs from patients 2 to 6 were sheared into fragments with peaks of 150–200 bp, and then adapters were ligated to both ends. The adapter-ligated templates were purified with Agencourt AMPure SPRI beads , and fragments with an insert size of ∼200 bp were excised. Extracted DNA was amplified by ligation-mediated PCR, purified and hybridized to the SureSelect biotinylated RNA library  for enrichment according to the manufacturer's instructions. Paired-end multiplex sequencing of samples was performed with the IlluminaHiSeq 2000 System. The average sequencing depth was 62 × per sample .www.broadinstitute.org/gatk/guide/best-practices.php) for duplicate removal, indel realignment and base recalibration.Paired-end reads in FastQ format generated by the Illumina pipeline were aligned to the reference human genome  using the Burrows-Wheeler Aligner with default settingsP<0.0001 for calling a somatic site. For MuTect, in addition to the build-in filters, the following filtering criteria were applied: (i) total read count in tumour DNA ≥15; (ii) total read count in germline DNA ≥6; (iii) presence of variant on both strands; (iv) variant allele frequency in tumour DNA ≥10%; (v) variant allele frequency in germline DNA=0; and (vi) removal of variants in positions listed in the dbSNP129 database (www.ncbi.nlm.nih.gov/SNP/). Single-nucleotide variants called by either method were used for further analysis  algorithmNonsynonymous coding and splice site mutations called by either MuTect or VarScan were subjected to mass spectrometry or Sanger sequencing for validation when adequate DNA was available. Mass spectrometry was performed first with the MassArray platform  as previously described2 copy number ratios in reference to the matching normal. Log2 ratios for each tumour sample were then segmented by applying the circular binary segmentation algorithm2 ratio >0.3, and copy number loss was defined as log2 ratio <−0.3. Cancer genes known to be affected by amplification or deletion (http://cancer.sanger.ac.uk/cancergenome/projects/census/) were also screened using these thresholds. Manual inspection was applied to review all segments containing candidate genes in each tumour region to make amplification and deletion calls. We also assessed the clonal relationship between different tumours based on the likelihood ratio against a background reference distribution as previously describedhttp://www.broadinstitute.org/tcga/gistic/browseGisticByTissue;jsessionid=08F9235B734370DB93AF3A4A33D86DB9). Segments overlapping with ≥50% of the recurrently amplified or lost regions were classified as gains or losses, respectively.We performed SCNA analysis using the Human Genome CGH Microarray Kit 244A (Agilent Technologies) with 8.9 kb overall median probe spacing, according to the ULS Labeling Protocol for Agilent Oligonucleotide Array-Based CGH for Genomic DNA Analysis . After scanning with the Agilent Scanner System, the data in each slide were extracted with Feature Extraction 12.0 (Agilent Technologies) for further analysis. The extracted data were subjected to locally weighted scatterplot smoothing to remove potential intensity and/or GC content bias before calculating the logETCW in relation to the strength of mutagenesis at the TCW motif (where W is either A or T) was calculated as in APOBEC mutation signatures were analysed as previously describedTCW is the number of mutated cytosines (and guanines) in a TCW (or WGA) motif, mutationsCorG is the total number of mutated cytosines (or guanines), contextTCW is the total number of TCW (or WGA) motifs within a 41-nucleotide region centred on the mutated cytosines (and guanines) and contextCorG is the total number of cytosines (or guanines) within the 41-nucleotide region centred on the mutated cytosines (or guanines). Only the following substitutions were included in the analysis: TCW to TTW or TGW and WGA to WAA or WCA. Overrepresentation of the APOBEC mutation signature was determined using a two-sided Fisher's exact test comparing the ratio of cytosine-to-thymine or cytosine-to-guanine substitutions with guanine-to-adenine or guanine-to-cytosine substitutions that occurred in and out of the APOBEC target motif (TCW or WGA) to an analogous ratio for all cytosines and guanines inside and outside the TCW or WGA motif within the 41-nucleotide region centred on the mutated cytosine or guanine.where mutationsEGFR p.L858R in our cohort and the Chinese lung adenocarcinoma cohortAnalysis of variance was used to assess the association between mutation burden and the gender or smoking status of each patient. The Pearson product–moment correlation test was used to assess the association between mutation burden and each patient's age or tumour size. The Fisher's exact test was used to assess the significance of differences in mutation spectra between different tumours, and the Pearson product–moment correlation analysis was used to assess the correlation between the mutation spectra of different tumours. The Fisher's exact test was also used to compare the incidences of www.ebi.ac.uk/ega/), which is hosted by the European Bioinformatics Institute (accession number: EGAS00001001572). The aCGH data have been deposited in the GEO database under accession code GSE86607. All other data are included within the Article or Whole-genome and -exome sequencing data have been deposited at the European Genome-phenome Archive .Supplementary Figures 1 - 8 and Supplementary Tables 1-7