Acute lymphoblastic leukemia (ALL) is the most common malignancy in childhood. Despite enormous improvement of prognosis during the last half century, ALL remains a major cause of childhood cancer-related mortality. During the past decade, whole genomic methods have enhanced our knowledge of disease biology. Stratification of therapy according to early treatment response measured by minimal residual disease allows risk group assignment into different treatment arms, ranging from reduction to intensification of treatment. Progress has been achieved in academic clinical trials by optimization of combined chemotherapy, which continues to be the mainstay of contemporary treatment. The availability of suitable volunteer main histocompatibility antigen-matched unrelated donors has increased the rates of hematopoietic stem cell transplantation (HSCT) over the past two decades. Allogeneic HSCT has become an alternative treatment for selected, very-high-risk patients. However, intensive treatment burdens children with severe acute toxic effects that can cause permanent organ damage and even toxic death. Immunotherapeutic approaches have recently come to the forefront in ALL therapy. Monoclonal antibodies blinatumomab and inotuzumab ozogamicin as well as gene-modified T cells directed to specific target antigens have shown efficacy against resistant/relapsed leukemia in phase I/II studies. Integration of these newer modalities into combined regimens with chemotherapy may rescue a subset of children not curable by contemporary therapy. Another major challenge will be to incorporate less toxic regimens into the therapy of patients with low-risk disease who have a nearly 100% chance of being cured, and the ultimate goal is to improve their quality of life while maintaining a high cure rate. The outcome continues to improve at the beginning of the 21st century. Moreover, this progress takes place not only in high-income countries but also in countries with limited resources because conventional chemotherapy is inexpensive and readily available worldwide3.Acute lymphoblastic leukemia (ALL) accounts for 25% of all childhood cancers and its outcome significantly influences the overall treatment results in pediatric oncology. The improvement of prognosis in childhood ALL is one of the most successful stories of modern medicine. An almost uniformly fatal disease at the beginning of the 1960s has transformed into a curable disorder in more than 90% of children with contemporary therapy. The major reason for improved survival is a decreased risk of relapseIgH/TCR (heavy immunoglobulin/T-cell receptor)4. MRD has been confirmed in multivariate analysis as the most significant prognostic factor within all immunophenotypes and genetic subgroups. MRD is first monitored during and at the end of induction6. Patients with a slow early response are stratified into the high-risk group. They profit from a more intensive post-induction treatment and augmented delayed intensification10. Rapid early responders to combined chemotherapy with B-cell precursor (BCP)-ALL benefit from early intensification of post-induction therapy, not from a prolonged double-delayed (augmented) intensification12. MRD performed about 3 months from diagnosis—that is, after early post-induction treatment—identifies a subset of patients with inferior outcome on Berlin-Frankfurt-Münster (BFM) protocols14. Treatment of T-cell (T)-ALL stratified according to treatment response has led to the excellent event-free survival (EFS) and overall survival (OS) of 85% and over 90%, respectively15, although T-cell immunophenotype remains an adverse risk factor in multivariate analyses of clinical trials14. Stratification according to MRD response helps to improve prognosis of T-ALL patients in general but also in subsets, such as in the recently identified early T-cell precursor (ETP)-ALL. ETP-ALL patients tend to respond more slowly to induction therapy, and initial studies reported poor outcome16. When stratified according to MRD response, their outcome is comparable to those with non-ETP-ALL17.Since the beginning of the 2000s, patients have been stratified into risk groups according to the early treatment response evaluated by minimal residual disease (MRD). It has been determined by detection of aberrant leukemic phenotype by flow cytometry or by specific rearrangements of immunoreceptor genes18. On the other hand, dexamethasone also accounts for both long- and short-term side effects, many of which are dependent on dose intensity19. The immunosuppressive action of dexamethasone, alongside the use of anthracyclines, contributed to higher incidence of infection-related mortality compared with prednisone and thus resulted in no difference in OS between both arms. High-dose methotrexate 5 g/m2 (HD MTX) in consolidation reduces bone marrow (BM) and extramedullary relapses more efficiently than lower escalating doses of intravenous MTX without leucovorin rescue  in BCP-ALL20.l-asparaginase has been a key component of all treatment regimens for childhood ALL since the 1960s. Its optimal dose, preparation, and route of administration remain uncertain21. Prolonged and intensified therapy withl-asparaginase improves the outcome of children with ALL. Administration ofl-asparaginase can be hampered by allergic reactions. Clinical allergy is associated with inactivation ofl-asparaginase by antibodies. Apart from overt allergy, antibodies can also cause a so-called silent inactivation, in whichl-asparaginase is neutralized subclinically. Monitoring ofl-asparaginase blood levels is useful because it detects silent inactivation22. PegylatedEscherichia colil-asparaginase (l-asparaginase coupled to polyethylene glycol) has a longer half-life and is potentially less immunogenic than nativeE. colil-asparaginase and has been used with increasing frequency in frontline pediatric treatment regimens23. Following allergy to pegylatedl-asparaginase, Erwinial-asparaginase can be substituted and achieves therapeutic activity24.Optimization of standard chemotherapy in academic randomized clinical studies improves the outcome even at the beginning of the 21st century. Substituting dexamethasone for prednisone for 3 weeks in the context of 2 years of BFM multi-agent therapy reduced the relapse risk by one-third26. The use of dexamethasone, HD MTX, and intrathecal triple therapy in central nervous system (CNS) leukemia treatment has enabled reduction or even omission of cranial irradiation without compromising OS28. In a recently published meta-analysis, cranial radiotherapy (CRT) was associated with reduced risk of relapse only in patients with overt CNS leukemia at diagnosis29. Omission of CRT from childhood ALL therapy results in improved cognitive outcome. However, despite this improvement, survivors continue to demonstrate the elevated risk for attention deficits when compared with a reference population of children30.Cranial irradiation is associated with a higher incidence of secondary malignancies and cognitive impairment in young children32.The indication of hematopoietic stem cell transplantation (HSCT) in first complete remission (CR) is recommended for a subgroup of children (approximately 5%) who are resistant to current chemotherapy 33. The addition of vincristine plus steroid pulses in maintenance treatment still may be useful in cases where less intensive early therapy is used34. Children with intermediate-risk ALL who received intensive chemotherapy on the basis of BFM protocols did not benefit from intensification of the maintenance therapy with pulses of vincristine and dexamethasone35. Some subgroups of patients with unfavorable biology, like deletion of the gene for transcription factorIKZF1, might benefit from pulses during maintenance even on treatment with BFM backbone36.Maintenance treatment with mercaptopurine and MTX is an integral part of ALL treatment. Lower adherence to oral mercaptopurine increases relapse risk38. Lower socioeconomic status, non-compliance to therapy, and (in countries with limited resources) malnutrition all increase the risk of treatment failure40.The incidence of treatment-related mortality (TRM) on contemporary ALL trials is reported to be between 2 and 4%. The most common cause of death is infection. The 5-year EFS of children with low-risk ALL who have favorable cytogenetics and good response to treatment is higher than 90%, and death from TRM is as common as relapse. As such, reducing infection-related mortality is a paramount concern when improving outcomes in childhood ALL. Patients at highest risk of infection-related TRM are children older than 10 years, slow early responders, and those with Down syndrome (DS)41. Patients with either of these abnormalities have a 5-year OS of over 90%. Five chromosomal abnormalities—MLL (KMT2A) translocations, t (BCR-ABL1), t (TCF3-HLF), near haploidy (fewer than 30 chromosomes), and low hypodiploidy (30–39 chromosomes)—are well-recognized prognostic biomarkers of high-risk disease at all ages42. Previously reported uniformly poor outcome of patients with hypodiploidy of less than 45 chromosomes might be improved by MRD-stratified treatment43. Approximately 30% of pediatric patients with BCP-ALL are screened negative for established diagnostic and prognostic markers. They are referred to as B-other ALL. Approximately 50% of B-other cases have a gene expression profile similar to that of BCR-ABL1-positive ALL. These cases form a subgroup that has been termed BCR-ABL1-like or Ph-like45. They frequently harbor alterations ofIKZF1 or other B-lymphoid transcription factor genes. Stratification of these patients according to MRD helps to improve previously reported poor outcome of this subgroup46. Kinase-activating gene fusions detected in this subgroup are collectively found in 1 to 2% of BCP-ALL cases and can be targeted with tyrosine kinase inhibitors (TKIs)47. Patients failing initial treatment might profit from the introduction of TKIs to high-risk chemotherapy. Up to 5% of childhood ALL cases have JAK-STAT signaling pathway-activating fusions , which appear to be targetable by JAK inhibitors48.Good risk prognostic genetic biomarkers of BCP-ALL are t (ETV6-RUNX1) and high hyperdiploidy (51–65 chromosomes)+) ALL since the 1990s; however, its importance may change in the era of TKIs. The onset of targeted therapy exemplified by TKIs has revolutionized the therapy of Ph+ ALL. TKIs are introduced early in induction and continue through maintenance treatment. Length of treatment and cumulative dose of TKIs seems to play a role in the achievement of a better outcome50. MRD is considered to be essential for risk group stratification. Discrepancies in MRD usingIgH/TCR and BCR-ABL1 fusion indicate that lineages other than BCP may also be affected by the disease51. The best way to incorporate TKIs, conventional chemotherapy, and HSCT is still unclear. With current approaches, which are developed from high-risk protocols, acute toxicity is a significant problem. Future trials will examine the necessary chemotherapy dose intensity alongside TKI therapy and address in which subgroups HSCT is needed; with regard to TKIs, which agent to use, how long application should be, and what the role of post-HSCT is must be further investigated52.HSCT has been the gold standard treatment for maintaining CR in Philadelphia chromosome-positive  than non-DS patients. They have low incidence of prognostically advantageous genetic subtypes . Higher risk of toxic complications puts pressure on physicians to reduce the treatment intensity in DS-ALL. However, even in DS, unmodified risk-adjusted ALL treatment, combined with good supportive care, is indicated58. Irrespective of the definition, the prognosis of children with this type of ambiguity was slightly poorer when compared with other cases receiving the same treatment60. Much rarer subtypes are bilineal  leukemias, in which two or more clones belonging to different lineages coexist at diagnosis. Interestingly, emerging studies show that despite phenotypic differences, the two clones often share genetic features . The existing definitions are arbitrary and sometimes are criticized for including too few markers  or too many markers 67. When diagnosed, most ALL cases are oligoclonal. A patient’s sensitivity or resistance to therapy is affected by genetic variations in individual subclones, and these can influence a subsequent clonal evolution during treatment as well68. Major diagnostic clone at diagnosis is eradicated by chemotherapy in the majority of cases. A substantial part of relapsed ALL cases arise from minor subclones already present at diagnosis. Some abnormalities gained under chemotherapy pressure confer resistance to important components of combined chemotherapy, like nucleoside analogues  and glucocorticoids (CREBBP mutation)72. Despite this, the optimization of combined chemotherapy might improve the outcome. The UK ALL R3 randomized trial for patients in first relapse compared two anthracyclines, mitoxantrone and idarubicin, in induction. Relapse incidence was significantly lower in the group treated with mitoxantrone and translated into a clear survival advantage of more than 20%, one of the largest improvements ever achieved by a single drug. Surprisingly, no difference in MRD could be detected between two randomized groups. Three-year OS was 69% in the mitoxantrone group73. The most frequent type of relapse is late BM relapse, more than 6 months from completion of treatment in BCP-ALL. Contemporary chemotherapy combined with HSCT in MRD poor responders to induction treatment is able to cure 70% of children74. In this group, deletion ofIKZF1 transcription factor and alteration ofTP53 identify patients with significantly inferior outcome75. The outcome of early BM relapses of BCP-ALL (during treatment or less than 6 months from the completion of treatment) and all BM relapses of T-ALL is worse. HSCT is indicated in all of these patients achieving remission. Only one-third of them are cured76. Deletion ofIKZF1 is strongly predictive of a second relapse after HSCT75.IKZF1 andTP53 represent relevant prognostic factors that should be considered in the assessment of children with relapsed ALL. The outcome of isolated and combined extramedullary relapses depends on the interval between diagnosis and relapse. HSCT may improve the outcome of those with highest risk.Relapse is diagnosed in fewer than 15% of children. Relapsed disease tends to be more drug resistant than is newly diagnosed ALL, as shown by lower disease clearance and reduced CR rate, especially in early relapses31. Standard conditioning regimens include total body irradiation, which is associated with significant risk of secondary cancer. Substituting chemotherapy for total body irradiation is currently being evaluated by a randomized study.The results of allogeneic HSCT are steadily improving. There is no difference in outcome between HSCT from matched sibling donors (MSDs) and unrelated main histocompatibility antigen-identical 9–10/10 volunteers (matched unrelated donor [MUD]). Transplant-related mortality is now below 10% in MSD and 20% in MUD HSCT. The likelihood of being cured by HSCT performed in second remission is about 60%in vitro prior to transfer to express an artificial signaling molecule designated chimeric antigen receptor (CAR). The CAR redirects the specificity of the modified T lymphocytes to surface antigens expressed by malignant cells. The most successful example of CAR-based immunotherapy is the treatment of BCP-ALL by targeting of the surface antigen CD19. In a pilot study, CR was achieved in 90% of 30 children and adults with highly refractory disease77. CAR cells can cross the blood-brain barrier and eliminate leukemic cells in the cerebrospinal fluid. CAR cells of the third generation are able to engraft and persist for at least several months78. The most common acute toxicity of CAR T cells is cytokine release syndrome. A wide variety of cytokines, including interleukin-6, interferon-gamma, and tumor necrosis factor, are elevated in the serum of patients experiencing fever, tachycardia, hypotension, and other toxicities. Higher disease burden predicts more toxicity. The interleukin-6 receptor antagonist tocilizumab is widely used for toxicity following CAR infusion79. Randomized studies are needed to demonstrate whether they will be able to substitute HSCT.The intensity of current front-line therapy has reached its threshold. Further intensification is not realistic. The majority of children with early BM relapse currently have little chance to be cured. There is growing evidence that targeted treatment and immunotherapy have the potential to improve the outcome of childhood ALL with reduced toxicity. A novel method of cellular therapy is based on the use of adoptively transferred T lymphocytes which were modified81.Blinatumomab, a bi-specific anti-CD19/CD3 chimeric antibody, draws malignant B cells in close proximity to CD3-positive T cells. Activated T cells effectively induce serial target cell killing. In current clinical trials, blinatumomab is administered over a 28-day continuous infusion, followed by a 14-day rest period. In a phase I/II study of blinatumomab in children, objective responses were noted in 43% patients, including negative MRD in 39% of patients. Optimal placement of immunotherapy with blinatumomab or other conventional immunomodulating approaches or both has yet to be determined82.The anti-CD22 immunoconjugate inotuzumab ozogamicin is an antibody-drug conjugate, consisting of humanized anti-CD22 monoclonal antibody joined to the cytotoxic agent calicheamicin by a non-immunogenic linker. After inotuzumab calicheamicin binds to CD22, rapid internalization of the conjugated calicheamicin occurs, targeting tubulin and inducing DNA breakage, apoptosis, and cell death. The response rate in adults with refractory/relapsed ALL is 80%, and clinical studies in children were launched recentlyDespite advances in targeted therapy approaches, conventional chemotherapy is unlikely to be replaced and this is because of its impressive cure rate in ALL. The task in coming years will be to compare immunotherapy with standard chemotherapy on a randomized basis in frontline treatment and in the treatment of first relapse. The goals are to also cure those children in whom combined chemotherapy fails and to reduce the toxicity that is responsible for reducing the quality of life for those who are cured.+ ALL, Philadelphia chromosome-positive acute lymphoblastic leukemia; T-ALL, T-cell acute lymphoblastic leukemia; TKI, tyrosine kinase inhibitor; TRM, treatment-related mortality.ALL, acute lymphoblastic leukemia; BCP, B-cell precursor; BCP-ALL, B-cell precursor acute lymphoblastic leukemia; BFM, Berlin-Frankfurt-Münster (study group); BM, bone marrow; CAR, chimeric antigen receptor; CNS, central nervous system; CR, complete remission; CRT, cranial radiotherapy; DS, Down syndrome; DS-ALL; acute lymphoblastic leukemia in children with Down syndrome; EFS; event-free survival; ETP, early T-cell precursor; ETP-ALL, early T-cell precursor acute lymphoblastic leukemia; HD, high-dose; HSCT, hematopoietic stem cell transplantation; IgH/TCR, heavy immunoglobulin/T-cell receptor; MRD, minimal residual disease; MSD, matched sibling donor; MTX, methotrexate; MUD, matched unrelated donor; OS, overall survival; Ph


Scientific Reports 10.1038/s41598-018-19526-4, published online 19 January 2018Correction to: In this Article, the authors neglected to include some potential conflicts of interest. The Competing Interests section should read:“Dr. Muotri is a co-founder and has equity interest in TISMOO, a company dedicated to genetic analysis focusing on therapeutic applications customized for the disorder autism spectrum and other neurological disorders origin genetics. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies.”


The homogeneity and heterogeneity in somatic mutations, copy number alterations and methylation across different cancer types have been extensively explored. However, the related exploration based on transcriptome data is lacking. In this study we explored gene expression profiles across 33 human cancer types using The Cancer Genome Atlas (TCGA) data. We identified consistently upregulated genes  and consistently downregulated genes  across various cancers. The dysregulation of these genes is likely to be associated with poor clinical outcomes in cancer. The dysregulated pathways commonly in cancers include cell cycle, DNA replication, repair, and recombination, Notch signaling, p53 signaling, Wnt signaling, TGFβ signaling, immune response etc. We also identified genes consistently upregulated or downregulated in highly-advanced cancers compared to lowly-advanced cancers. The highly (low) expressed genes in highly-advanced cancers are likely to have higher (lower) expression levels in cancers than in normal tissue, indicating that common gene expression perturbations drive cancer initiation and cancer progression. In addition, we identified a substantial number of genes exclusively dysregulated in a single cancer type or inconsistently dysregulated in different cancer types, demonstrating the intertumor heterogeneity. More importantly, we found a number of genes commonly dysregulated in various cancers such as PLP1, MYOM1, NKAPL and USP2 which were investigated in few cancer related studies, and thus represent our novel findings. Our study provides comprehensive portraits of transcriptional landscape of human cancers. It has been recognized that cancer is associated with the genetic and genomic changes . With thCancers originating from different tissues or cell types vary in terms of their genomic profiles. Lawrence et al analyzed 27 cancer types and found that the median frequency of non-synonymous mutations varied by more than 1,000-fold across different cancer types . The varDue to the varied genomic profiles, different cancer types may show different prognosis. Among all cancer types, pancreatic, lung, liver and esophageal cancers have the worst survival prognosis while prostate, thyroid and skin cancers have the best survival prognosis . Moreovehttp://icgc.org/) [https://gdc-portal.nci.nih.gov/), the homogeneity and heterogeneity across different cancer types have been extensively explored [With the emergence of large-scale cancer genomics projects such as the International Cancer Genome Consortium   and The explored , 20, 21.explored , 18, SCNexplored , and metexplored , 13. HowIn this study we explored gene expression profiles across 33 human cancer types in TCGA Table . We idenWe compared gene expression levels between cancer and normal samples in 18 cancer types each of which contains at least five normal samples  software , we idenWe compared overall survival (OS) and disease-free survival (DFS) between patients with higher expression levels and patients with lower expression levels of the 11 protein kinase genes and seven TF genes in 30 cancer types . Kaplan-Meier survival curves show that higher expression levels of these genes are associated with significantly worse OS and DFS prognoses in various cancers Figure . For exaWe identified 11 genes  which are consistently downregulated in all the 18 cancer types compared to normal tissue. Among the 11 genes, SCARA5 expression has been shown to be frequently downregulated in various cancers , and hasWe compared OS and DFS between patients with higher expression levels and patients with lower expression levels of the 11 genes in the 30 cancer types. Kaplan-Meier survival curves show that higher expression levels of most of these genes are associated with better OS and DFS prognoses in multiple cancer types Figure . For exaIn addition, we identified 53 genes which are consistently downregulated in 17 of the 18 cancer types . PathwayWe compared gene expression levels between early-stage (stage I-II) and late-stage (stage III-IV) cancers, and between low-grade G1-2) and high-grade (G3-4) cancers, respectively. We refer to early-stage or low-grade cancers as lowly-advanced cancers, and late-stage or high-grade cancers highly-advanced cancers. There are 27 and 12 cancer types whose clinical data contain stage and grade information, respectively , collagen formation , cell surface interactions at the vascular wall , and integrin cell surface interactions . Obviously, these pathways are associated with cancer progression and metastasis characteristics such as cell interaction, cell adhesion, and cell motility. Some of the LSA genes have been shown to be overexpressed in advanced cancers and be associated with unfavorable clinical outcomes such as SOX11 [We identified 71 genes which are upregulated in late-stage compared to early-stage cancers in more than three cancer types . We callas SOX11 , 74, PTPas SOX11 , PNCK [7as SOX11  and HMGAas SOX11 –79. In aas SOX11 , 9.-16). Similarly, there are much more LSA genes upregulated in cancers than LSA genes downregulated in cancers compared to normal tissue. For example, in more than nine (50%) of the 18 cancer types, 26 (37%) of the 71 LSA genes are upregulated in cancers, compared to 9 (13%) of the 71 LSA genes downregulated in cancers . These results indicate that cancer initiation  and cancer progression  may depend on many common changes in gene expression profiles. In fact, we found a number of genes whose expression follows this pattern: late-stage cancers > early-stage cancers > normal tissue. For example, in the eight cancer types  with both stage phenotype information and normal control samples, SOX11 expression follows the pattern in four cancer types   of the 18 cancer types, 128 (60%) of the 212 HGA genes are upregulated in cancers, compared to 15 (7%) of the 212 HGA genes downregulated in cancers  Figure . Similar) Figure . These r% of the -16). In more than nine (50%) of the 18 cancer types, 128 (60%) of the HGA genes are more highly expressed in cancers than in normal tissue, compared to 26 (37%) of the LSA genes . It is consistent with a recent study showing that cancer grade, but not stage, was driven by transcriptional alterations [Surprisingly, very few (only seven) genes are common between the LSA gene list and the HGA gene list. In fact, the gene expression profiling alteration (GEPA) from normal tissue to cancers is closer to the GEPA from low-grade to high-grade cancers than to that from early-stage to late-stage cancers. For example, 42 82%) of the 51 genes overexpressed in all the 18 cancer types are included in the HGA gene list, compared to one (2%) of the 51 genes included in the LSA gene list  of the 18 cancer types, 9 (16%) of the 58 HGiA genes are downregulated in cancers, compared to 3 (5%) of the 58 HGiA genes upregulated in cancers . Similarly, there are more LSiA genes downregulated in cancers than LSiA genes upregulated in cancers, although the difference is not significant. Likewise, we found a number of genes whose expression follows this pattern: late-stage cancers < early-stage cancers < normal tissue Figure , such asAgain, very few genes  are common between the LSiA gene list and the HGiA gene list. It strongly suggests that although both stage and grade reflect the status of cancer advancement in phenotype, they are markedly different in molecular levels.We used GSEA software  to perfoPathway analyses of the DE genes between early-stage and late-stage cancers in each of the 13 cancer types identified 28 and 48 significant KEGG pathways associated only with the upregulated genes and only with the downregulated genes in late-stage cancers in at least one cancer type, respectively  and protein kinase genes  are overexpressed in various cancers, and their overexpression is associated with poor clinical outcomes in cancer . ClearlyThe commonly dysregulated genes and pathways identified in various cancers may involve attractive therapeutic targets for cancer. For example, since the cell cycle pathway is consistently hyperactivated in cancers, development of cell-cycle inhibitors may be effective in treatment of a wide type of cancers. We have identified a number of protein kinase genes which are upregulated commonly in cancers and are involved in the cell cycle regulation such as PLK1, TTK, BUB1, BUB1B, and PKMYT1. Development of small molecule inhibitors targeting these protein kinases could be a promising direction for curing cancer. On the other hand, the identification of a number of genes exclusively dysregulated in a single cancer type indicates that an individual cancer type may need its own specific therapeutic strategies in addition to the common strategies in cancer therapy. Furthermore, the identification of a considerable number of genes commonly dysregulated across various cancers while with different directions indicates the complexities of cancer therapy unless the dysregulation of these genes is a passenger event.A limitation of the present study is that a small number of normal samples in some cancer types such as GBM and CHOL could compromise the validity of the results from the analyses of DE genes between normal and cancer samples. To overcome the limitation, the method of merging samples based on the body sites of cancer initiation  can be used. This is a direction for our future studies.In addition, many upstream factors may affect expression of mRNAs (genes) in cancers such as gene mutations, DNA copy number alterations, DNA methylation, microRNA expression, and expression change of regulators. Combined analysis of other genomic profiles with gene expression profiles may gain more in-depth insights into the mechanism underlying oncogenesis . Besideshttps://gdc-portal.nci.nih.gov/). For survival analyses we used clinical data from FireBrowse (http://gdac.broadinstitute.org/).We downloaded RNA-Seq gene expression data (Level 3), and clinical data for all of the 33 cancer types for which data are available from the TCGA data portal (t test. We used FDR to adjust for multiple tests. The FDR was estimated using the Benjami and Hochberg (BH) method [We first normalized the gene expression data by base-2 log transformation, and then identified DE genes between two classes of samples using Student's ) method . We usedWe performed pathway analysis of gene sets using the GSEA tool , and netWe performed survival analyses of TCGA patients based on gene expression data. Kaplan-Meier survival curves were used to show the survival (OS or DFS) differences between gene higher-expression-level patients and lower-expression-level patients. Gene higher-expression-level and lower-expression-level patients were determined by the median values of gene expression levels. If the gene expression level in a patient was higher than the median value, the patient was classified as gene higher-expression-level; otherwise as gene lower-expression-level. We used the log-rank test to calculate the significance of survival-time differences between two classes of patients with a threshold of P-value < 0.05.The present study provides comprehensive portraits of transcriptional landscape of human cancers, showing extensive intertumor homogeneity and heterogeneity in genomic profiles. This work would bring new insights into the biology of human cancers.


Structural variants (SVs) in human genomes are implicated in a variety of human diseases. Long-read sequencing delivers much longer read lengths than short-read sequencing and may greatly improve SV detection. However, due to the relatively high cost of long-read sequencing, it is unclear what coverage is needed and how to optimally use the aligners and SV callers.In this study, we developed NextSV, a meta-caller to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purposes. We evaluated SV calling performance of NextSV under different PacBio coverages on two personal genomes, NA12878 and HX1. Our results showed that, compared with running any single SV caller, NextSV stringent call set had higher precision and balanced accuracy (F1 score) while NextSV sensitive call set had a higher recall. At 10X coverage, the recall of NextSV sensitive call set was 93.5 to 94.1% for deletions and 87.9 to 93.2% for insertions, indicating that ~10X coverage might be an optimal coverage to use in practice, considering the balance between the sequencing costs and the recall rates. We further evaluated the Mendelian errors on an Ashkenazi Jewish trio dataset.Our results provide useful guidelines for SV detection from low coverage whole-genome PacBio data and we expect that NextSV will facilitate the analysis of SVs on long-read sequencing data.The online version of this article (10.1186/s12859-018-2207-1) contains supplementary material, which is available to authorized users. Structural variants (SVs) represent genomic rearrangements , and SVs may play important roles in human diversity and disease susceptibility –3. Many Two popular SV software tools have been developed specifically for long-read sequencing: PBHoney  and SnifTo address these challenges, we developed NextSV, an automated SV detection pipeline integrating multiple tools. NextSV automatically execute these software tools with optimized parameters for user-specified coverage, then integrates results of each caller and generates a sensitive call set and a stringent call set, for different analysis purposes.Recently, the Genome in a Bottle (GIAB) consortium and the 1000 Genome Project Consortium released high-confidence SV calls for the NA12878 genome, an extensively sequenced genome by different platforms, enabling benchmarking of SV callers , 18. TheFive whole-genome PacBio sequencing data sets were used to test the performance of SV calling pipelines Table . Data sePacBio subreads were iteratively aligned to the human reference genome  using the BLASR aligner (parameter: -bestn 1). Each read’s single best alignment was stored in the SAM output. Unmapped portions of each read were extracted from the alignments and remapped to the reference genome. The alignments in SAM format were converted to BAM format and sorted by SAMtools. PBHoney-Tails and PBHoney-Spots (from PBSuite-15.8.24) were run with slightly modified parameters  to increase sensitivity and to discover SVs under low coverages (2-15X). The reference FASTA files used in this study were downloaded from the FTP sites of 1000 Genome Project  (GRCh37)PacBio subreads were aligned to the reference genome, using BWA-MEM (bwa mem -M -x pacbio) or NGMLR (default parameters) to generate the BAM file. The BAM file was sorted by SAMtools, then used as input of Sniffles (version 1.0.5). Sniffles was run with slightly modified parameters  to increase sensitivity and discover SVs under low fold of coverages (2-15X).As shown in Fig. Users can choose to run any of the four aligner/SV caller combination. By default, NextSV will enable BLASR/PBHoney-Spots, BLASR/PBHoney-Tails and NGMLR/Sniffles and integrate the results to generate the sensitive calls and stringent calls. We do not enable BWA/Sniffles by default because Sniffles works better with NGMLR in our evaluation and alignment is a time consuming step. SVs that are shorter than reads may result in intra-read discordances while larger SVs may result in soft-clipped tails of long reads. We suggest running both PBHoney-Spots and PBHoney-Tails because they are two complementary algorithms designed to detect intra-read discordances and soft-clipped tails, respectively. Sniffles uses multiple evidences to detect SV so it should be suitable for both types of SVs.NextSV sensitive call set is generated as:SNIF ∪ (SPOT ∪ TAIL),and NextSV stringent call set is generated as:SNIF ∩ (SPOT ∪ TAIL),where SNIF denotes the call set of Sniffles , SPOT denotes the call set of BLASR / PBHoney-Spots and TAIL denotes the call set of BLASR / PBHoney-Tails.delta. Delta used by NIST/GIAB analysis team was 1000 bp and used by Pendleton et al.  was 100The high-confidence deletion call set of the NA12878 genome was release by the Genome In A Bottle (GIAB) consortium , in whicThe SV calls of each caller were compared with the high-confidence SV set. Precision, recall, and F1 score were used to evaluate the performance of the callers. Precision, recall, and F1 were calculated asTo determine the optimal coverage for SV detection on PacBio data, we evaluated the performance of NextSV under several different coverages. We downloaded a recently published PacBio data set of NA12878  and downFirst, we examined how many calls in the high-confidence set can be discovered. As shown in Fig. Second, we examined the precision and balanced accuracy F1 scores) under different coverages Fig. . The pre scores uTo verify the performance of SV detection on different individuals, we also performed evaluation on a Chinese genome HX1, which was sequenced by us recently  at 103X As the de novo mutation rate is very low , 28, MenTo evaluate the computational resources consumed by NextSV, we used the whole genome sequencing data set of HX1 (10X coverage) for benchmarking. All aligners and SV callers in NextSV were tested using a machine equipped with 12-core Intel Xeon 2.66 GHz CPU and 48 Gigabytes of memory. As shown in Table Long-read sequencing such as PacBio sequencing has clear advantages over short-read sequencing on SV discovery . HoweverThe high-confidence call set of HX1 genome was generated using two steps. First, we used a call set from a previously validated local assembly-based approach , 20, 31 There is often a trade-off between recall and precision. NextSV generates a sensitive call set and a stringent call set, for different purposes. NextSV sensitive call set is suitable for users who consider recall more important than precision and who can afford extensive downstream analysis (such as Sanger sequencing) to validate the candidate variants. This is often the case when doing disease-casual variant discovery on personal genomes. NextSV stringent call set has the highest precision, F1 score. It is suitable for users who aim to perform genome-wide analysis of SVs on a collection of samples, with limited downstream validation.The performance of SV callers are affected by the parameter settings. The number of supporting reads is a key parameter that affect the trade-off between recall and precision. By default, PBHoney requires a minimal read support of 3 for an SV event and Sniffles requires a minimal read support of 10 for an SV event. However, this may be too high for low coverage data set. In our evaluation of recall and precision, we changed this setting to require a minimal read support of 2. This allows detection of SVs from very low coverage regions, with an acceptable precision. Thus, substantially higher number of true positives would be detected and less variants of interest would be missed. For users who consider precision to be more important than recall, they can either use the NextSV stringent call set or specify a stricter parameter (e.g. requiring more supporting reads) when running the NextSV pipeline. The F1 score is a balance between recall and precision. Therefore, its correlation with coverage is affected by the two aspects. In general, as the coverage increases, the recall increases but the precision decreases. Therefore, the F1 score may either increase or decrease as the coverage increases.In addition to test recalls and precisions, we examined the allele drop-in (ADI) errors, which represent the SV calls that in the offspring but not appear in either parent. Since the de novo mutation rate is very low, the ADI errors may mainly come from errors of sequencing and subsequent SV detection. In our results, the ADI rates of insertions are higher than those of deletion calls, which is consistent with the fact that PacBio sequencing has higher per-base insertion errors than deletion errors. Another source of ADI may come from the SV callers. SV detection from PacBio data set is still in its early stage. The currently available SV callers are not carefully designed for low-coverage data sets. For example, Sniffles requires 10 reads to support a SV under default settings, which means at least 20X coverage is required to detect a heterozygous SV. We expect the improvement of SV callers in the future.NextSV currently supports four aligner / SV caller combinations: BLASR / PBHoney-Spots, BLASR / PBHoney-Tails, BWA / Sniffles, NGMLR / Sniffles, but we expect to continuously expand the support for other aligner / caller combinations. In the future, if more aligners/SV callers are supported, we will evaluate the performance of each combination and find the best aligner for each SV caller. The NextSV sensitive call will be the union call set of all SV callers; the NextSV stringent calls will be the calls that are detected by at least two SV callers. If one SV caller can work with multiple aligners, only the call set of its best aligner will be used.In this study, we only evaluated the performance for insertions and deletions because we only have the high-confidence calls of insertions and deletions. This is another limitation of the study. We will evaluate the performance on other types of SVs in the future when more high-confidence SV calls are available. Nonetheless, NextSV generates SV calls of all types. The output of NextSV is in ANNOVAR-compatible format. Users can easily perform downstream annotation using ANNOVAR and disease gene discovery using Phenolyzer . NextSV In this study, we proposed NextSV, a comprehensive, user-friendly and efficient meta-caller to perform SV calling from low coverage long-read sequencing data. NextSV integrates multiple aligners and SV callers and performs better than running a single SV caller. We also showed that ~10X PacBio coverage can be an optimal coverage to use in practice, considering the balance between the sequencing costs and the recall rates. Our results provide useful guidelines for SV detection from low coverage whole-genome PacBio data and we expect that NextSV will facilitate the analysis of SVs on long-read sequencing data.Additional file 1:Tables S1-S24. Performances of BLASR/PBHoney-Spots, BLASR/PBHoney-Tails, BWA/Sniffles, NGMLR/Sniffles and NextSV on the NA12878 genome and the HX1 genome. (PDF 472 kb)


C. elegans synapses as a test case. By population-wide comparisons, we identified subtle but relevant differences inaccessible to subjective conceptualization. Furthermore, the models generated testable hypotheses of how individual alleles relate to known mechanisms or belong to new pathways. We show that our model not only recapitulates current knowledge in synaptic patterning but also identifies novel alleles overlooked by traditional methods.Discovering mechanistic insights from phenotypic information is critical for the understanding of biological processes. For model organisms, unlike in cell culture, this is currently bottlenecked by the non-quantitative nature and perceptive biases of human observations, and the limited number of reporters that can be simultaneously incorporated in live animals. An additional challenge is that isogenic populations exhibit significant phenotypic heterogeneity. These difficulties limit genetic approaches to many biological questions. To overcome these bottlenecks, we developed tools to extract complex phenotypic traits from images of fluorescently labelled subcellular landmarks, using  Experimenter scoring of cellular imaging data can be biased. This study describes an automated and unbiased multidimensional phenotyping method that relies on machine learning and complex feature computation of imaging data, and identifies weak alleles affecting synapse morphology in live C. elegans. Understanding gene function and the structure of biological networks relies heavily on identifying morphological, functional or behavioural phenotypic changes upon genetic perturbations. With deep-sequencing and the recent advances in genome-editing tools, the bottleneck for discovery of cellular functions now is phenotypic analyses123479111in vitro cell models13141516171819202122in vivo models , the number of markers  that can be simultaneously used is usually small, thus limiting the dimensions of the phenotype to be scored. There is also inherent complexity of working with intact animals, for instance, forward genetic screens in small model organisms are usually performed by phenotyping single animals, not populations of clones as in cell culture. These difficulties have prevented extensive use of large-scale high-resolution image-based studies. In Caenorhabditis elegans, live phenotyping has mostly focused on drastic changes exhibited on gross features 2425152729531323334353637While image-processing tools have been increasingly applied to perform quantitative analysis, this has been mostly useful for C. elegans as a test case for the general strategy. Here we present an approach to perform comprehensive multidimensional phenotypic profiling using fluorescently labelled synaptic puncta in C. elegans. Our combined computational and experimental approach addresses the major challenges to isolate and characterize subtle alleles by quantifying micron-sized subcellular landmarks in an unbiased manner from a single genetically encoded reporter. This integrative approach is based on applying statistical methods to capture the phenotypic heterogeneity in isogenic populations, creating phenotypic profiles containing multiple and complex features, and developing models to place subtle alleles in the phenotypic space. We demonstrate an approach to identify genetic alterations that give rise to subtle and varying phenotypic changes, unintuitive to and difficult to assess by human perception, but nonetheless relevant in the nematode C. elegans. Because of the large dimensions of the phenospace available to the computational approach, we can now identify changes from an ensemble of phenotype characteristics, use them to cluster alleles and give rise to new hypotheses of genetic relations. Using this method, we identified a new allele with a surprising role in C. elegans synapse morphology and function.One particularly challenging area for quantitative phenotypic profiling is synaptic patterning in C. elegans, synaptic patterning is thought to be stereotypical394041424445464748In Using a modified large-scale imaging and sorting system455051524243444647495439404156To identify new alleles that affect morphology, particularly those that may be subtle or of previously unidentified phenotypes, we conducted an automated unbiased forward genetic screen . Becausearl-8) and one subtle mutant found from the screen (a178). For arl-8, a visually identifiable phenotype, the logistic regression model resembles a step function, perfectly separating the mutant from wild type , while also having a larger number of puncta (feature 1), although these two features alone are insufficient to describe how a178 differs from wild type , which will certainly elude the eye , especially for classical visually apparent mutants , pct-1(wy575), cdk-5(ok626), cdka-1(tm648), a090 and a115), which is somewhat surprising since we did not image the ventral side of the worms; this suggests that the amount of synaptic material and their distribution are likely controlled, such that ventral mislocalization affects dorsal synapse morphology. For these animals, visual inspection of the dorsal axon typically cannot differentiate these animals from wild type (jnk-1(gk7) and jkk-1(km2). These were previously identified from suppressor screens of arl-8 (ref. mtm-6(ok330) (ref. We next examined the discriminatory power of each pairwise model for previously identified mutants and for those isolated in our screens . Overlapild type . Nonethel-8 ref.  and show30) ref.  is perfea175, which has a posteriorly shifted synaptic pattern, none of the isolated mutants display a visually apparent phenotype. According to logistic regression models, however, some  are as easy to identify as the known mutant collection, and others are much more subtle , likely because of two reasons: the model's ability to take into account multiple phenotypic features, and features that are statistical in nature (such as variability), both changes difficult to assess by human perception. Notably, the model for a220 can almost perfectly discern between mutant and wild-type populations (AUC=0.94), although visual inspection detects no obvious defects  also phenocopied a178 using both the models for the original isolate and the three times outcrossed population , a178 exhibits a much subtler phenotype. Without confirmation of a functional defect, it would be difficult to positively argue that a178, although morphologically different from wild type, is a relevant mutation that affects synaptic function. Notably, posterior to isolation, we identified a drastic behavioural phenotype exhibited by a178. These animals display a distinct swimming phenotype when transferred to liquid media. Although no difference was observed in initial swimming speed, a178 reduces thrashing frequency drastically over time a178 could be defective in rates of neurotransmitter release or reuptake while maintaining rapid and sustained neuronal activation rates. The two sax-2 alleles also reduce swimming locomotion faster than wild type, although to a smaller extent  and specificity . Because they were built to differentiate the mutants from wild-type animals, the model can be used to classify animals in a binary manner, but can be tuned to meet different false-positive or false-negative criteria  phenotype is specific. It is conceivable that the model to describe a weak phenotype  may pick up many other genotypes, and would indicate that the weak phenotype may be describing noise in the measurements instead. When applying the SWLR model to images from animals of all other genotypes, none other than the original isolate and the three times outcrossed strain had a probably higher than 0.5, indicating that the model is specific against all other genotypes , whereas the arl-8 model is extremely selective. In contrast, subtle mutants isolated in this work are mostly only identified by their phenotype-specific models. For instance, a178 is exclusively identified by its own model and by the model for a178(x3), and vice versa , a176 connects with a176-R2 (an independent imaging set of a176); similarly, the two alleles for lin-44 (including a175 isolated here) are linked; mutants cyy-1, cdka-1, cdk-5 and pct-1, which are all part of parallel pathways that regulate targeting of presynaptic components to the axona218, suggesting that a218 may participate in the same pathway of synapse elimination and formation.Because promiscuous models suggest that high-probability mutants using these models may share a set of features in the phenospace, we next explored the information contained in these model–data relationships. In a178 and wild type, we see that a178 shows a lower variability in puncta brightness (more homogeneous colouring), in addition to a slightly larger number of synaptic sites; this is difficult to articulate when just looking at raw images of both populations .Hierarchical clustering recapitulates known relationships between genotypes, as well as predicting novel relationships . Further466566jnk-1 and jkk-1, each visually indistinguishable to wild type, also cluster together. These genes are known to work in the same pathway: JNK-1 activity is dependent upon JKK-1 activationarl-8, not a direct visual screencdka-1 and cdk-5) are also clustered together, even though the analysis is performed solely on the axonal synaptic domain. cdka-1 and cdk-5 are not only similar in their dendritic mislocalization, but are also known to work in the same pathway . Bond cdk-5 : both inC. elegans to search for alleles with very subtle but significant differences, extremely difficult to perceive by human vision. For genetic model systems, visual screens for subtle phenotypes is generally challenging because it is experimentally difficult to use many markers and to phenotype a large number of animals in isogenic populations. The approach we present here can address these challenges. Our high-throughput live imaging set-up enables fast acquisition of images leading to large sample numbers. Furthermore, coupling computer vision tools with the extraction of complex non-intuitive ‘meta-features', a thorough quantitative reconstruction of phenotypic profiles is built, in addition to the improved speed and reduced human bias. These high-content profiles include far more information than what is perceptible to human vision, particularly those statistical in nature. We showed that this multidimensional phenotypic profiling overcame the confounding effects of phenotypic heterogeneity exhibited by isogenic populations, and enabled the identification and characterization of subtle mutants. Finding significant and relevant changes in the subtle mutants was enabled by stepwise feature selection applied to build logistic regression models and the pairwise population comparisons against wild type. We discovered extremely subtle mutants that also display striking behavioural phenotypes, such as a178, impossible to identify by visual inspection, which illustrated the power of this approach to explore potentially previously unavailable phenospace.In this work we have applied an integrated approach to perform quantitative and unbiased phenotyping of synaptic morphology in C. elegans, can lead the way to develop analysis tools able to link phenotype to genotype in the complex but common scenarios of multigenicity and phenotypic pleiotropy, and reveal qualitatively uncovered phenotypic connections between genotypes.Conventionally, mutants are traditionally considered interesting if they give a large enough phenotypic alteration, usually obvious to the eye; those alleles that have small changes, particularly where the heterogeneity of the samples drowns the difference, would be considered false-positives. The method presented extends the boundary of accessible phenospace to identify mutants, particularly those inaccessible via conventional manual scoring. This becomes more important as the work using genetic model systems move into problems relevant to human psychiatric diseases, for instance, where the morphological changes in the nervous system are extremely subtle11Escherichia coli bacteria using standard methodswyIs85 (Pitr-1pB::gfp::rab-3). The following mutants were used syd-2 (wy5)X, sad-1 (ky330)X, mtm-6 (ok330)III, jnk-1 (gk7)IV, jkk-1 (km2)X, cdka-1 (tm648)III, cyy-1 (wy302), pct-1 (wy575), cdk-5 (ok626)III, lin-44 (n1792)I, arl-8 (wy271), sax-2 (ky216)III and sax-2 (ot10)III. Mutants found in a previous screenWorms were cultured on nematode growth medium (NGM) plates seeded with OP50 Microfluidic chips were made by polydimethylsiloxane (PDMS) replica molding from an SU-8 master mold fabricated by photolithography, as previously describedOff-chip components include an in-house built pressure control box with a digital I/O card , solenoid valves  for off-chip on/off flow control and a custom in-house built cooling system consisting of a peristaltic pump for flow of the cooling liquid, a Peltier and an in-house built heat exchanger. Actuation of the solenoid valves, the pressure box, the microscope stage and the camera for image acquisition was controlled by a Graphical User Interface (GUI) developed in MATLAB (Mathworks). Automated operation during imaging or screening was performed with pre-built worm detection, imaging, phenotyping and sorting functions called from the GUI, as well as with error-handling functions.Genetic screens were performed by imaging an age-synchronized F2 population as previously describeda178 were assessed on the same seeded NGM plate. N=20. Aldicarb sensitivity assays were performed as described elsewhereN=20. Swimming assays were performed by transferring single animals at the start of egg-laying to wells fabricated on agarose pads filled with water. Videos were acquired of the swimming animals  or outcrossed mutant populations (a178(x3)). Sample sizes account for all analysed images. Details of sample sizes are reported in Imaging sample sizes were chosen to ensure adequate power to detect changes in the variables contained in the phenotypic profiles . Images https://github.com/asanmiguel/SynapsePhenotyping, under an MIT licence. The raw data set of phenotypic profiling is also included at the github repository. Raw images are available upon request.Software and code for high-throughput imaging, phenotypic profiling and SWLR model construction are publicly available at github at: How to cite this article: San-Miguel, A. et al. Deep phenotyping unveils hidden traits and genetic relations in subtle mutants. Nat. Commun.7, 12990 doi: 10.1038/ncomms12990 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary Figures 1-10, Supplementary Notes 1-11 and Supplementary ReferencesWildtype animals swimming in agarose wells, immediately after transfer from NGM platesWildtype animals swimming in agarose wells, after 40 minutes of transfer from NGM platesa178(x3) animals swimming in agarose wells, immediately after transfer from NGM platesa178(x3) animals swimming in agarose wells, after 40 minutes of transfer from NGM plates


Tg to around room temperature and an increase in the elongation at break of PLA from 14% to 165% and 460%, respectively, were determined. The crystallinity was increased from 2.1% to 8.4% for PLA/PBSA and even more, to 10.6%, for PLA-CA-PBSA. Due to the inherent poor miscibility between the PBSA and PLA, phase separation occurred in the blend, while PLA-CA-PBSA showed no phase separation which, together with the higher crystallinity, led to better oxygen barrier properties compared to neat PLA and PLA/PBSA. A higher resistance to migration during hydrolytic degradation for the PLA-CA-PBSA compared to the PLA/PBSA indicated that the plasticization effect of PBSA in the coupled material would be retained for a longer time period.Plasticized polylactide (PLA) with increased crystallization ability and prolonged life-span in practical applications due to the minimal plasticizer migration was prepared. Branched plasticized PLA was successfully obtained by coupling poly(butylene succinate-co-adipate) (PBSA) to crotonic acid (CA) functionalized PLA. The plasticization behavior of PBSA coupled PLA (PLA-CA-PBSA) and its counterpart PBSA blended PLA (PLA/PBSA) were fully elucidated. For both PLA-CA-PBSA and PLA/PBSA, a decrease of  In contrast to neat PLA, after 2 weeks of hydrolysis, the main series of peaks in the case of PLA/PBSA were both [o-LA + 2Na]+ and PBSA or PBSA hydrolysis products which were marked with green ovals. This indicates that PBSA migrated from the PLA/PBSA blends already after 2 weeks of hydrolysis and this migration increased further after 4 weeks. The main series of peaks after 4 weeks of hydrolysis were adducts of PBSA. PLA-CA-PBSA had a different hydrolysis product pattern compared to PLA/PBSA. Adducts of linear lactic acid oligomers were the main series of peaks in the mass spectrum after 2 weeks. Unreacted PBSA or PBSA hydrolysis products were detected but with low intensity. After 4 weeks, adducts of linear lactic acid oligomers were still the main series of peaks. The intensity of the PBSA adducts increased as hydrolysis proceeded, especially in the low molecular weight range. This is perceived as evidence that the increasing intensity of PBSA was the consequence of PBSA hydrolysis instead of the migration of unreacted PBSA.The hydrolytic degradation and plasticizer migration behavior of the compression molded films were studied for up to 4 weeks in water at 60 °C. After 2 and 4 weeks of hydrolysis, linear lactic acid oligomers were detected in all samples. The main series of peaks in the mass spectra of neat PLA after 2 weeks of hydrolysis were adducts of linear lactic acid oligomers [o-LA + 2Na]Tg of PLA significantly. Elongation at break was remarkably increased from 14% to 460% when PBSA was blended with PLA. PLA-CA-PBSA had 165% as its elongation at break, which was 10 times higher than neat PLA. Together with the immiscible molten droplets of PBSA or PBSA coupling points which acted as nucleating agents, both PLA/PBSA and PLA-CA-PBSA showed higher crystallinity in DSC measurement. An increased nucleation ability and crystal growth rate of plasticized PLA conformed with POM observation of isothermally crystallized samples. PLA-CA-PBSA showed the highest nucleation ability, followed by PLA/PBSA. WAXD results for isothermally crystallized materials indicated that the observed crystals originated from crystallization of PLA chains. Moreover, enhanced gas barrier properties were achieved after PLA was coupled with PBSA, as a result of higher crystallinity and enhanced miscibility between PLA and PBSA. Last but not least, higher migration resistance of PLA-CA-PBSA in comparison with PLA/PBSA was confirmed by hydrolytic degradation study.Plasticized PLA was obtained by blending PLA with low molecular weight PBSA and coupling PBSA to carboxylic-functionalized PLA. As expected, blended PBSA and grafted PBSA both increased the flexibility and decreased the


Supplemental Digital Content is available in the text. 18F-fluoride or 18F-fluorodeoxyglucose can identify culprit and high-risk carotid plaque.Combined positron emission tomography (PET) and computed tomography (CT) can assess both anatomy and biology of carotid atherosclerosis. We sought to assess whether 18F-fluoride and 18F-fluorodeoxyglucose PET/CT in 26 patients after recent transient ischemic attack or minor ischemic stroke: 18 patients with culprit carotid stenosis awaiting carotid endarterectomy and 8 controls without culprit carotid atheroma. We compared standardized uptake values in the clinically adjudicated culprit to the contralateral asymptomatic artery, and assessed the relationship between radiotracer uptake and plaque phenotype or predicted cardiovascular risk (ASSIGN score [Assessing Cardiovascular Risk Using SIGN Guidelines to Assign Preventive Treatment]). We also performed micro PET/CT and histological analysis of excised plaque. On histological and micro PET/CT analysis, 18F-fluoride selectively highlighted microcalcification. Carotid 18F-fluoride uptake was increased in clinically adjudicated culprit plaques compared with asymptomatic contralateral plaques  and compared with control patients . 18F-Fluoride uptake correlated with high-risk plaque features , and predicted cardiovascular risk ). Carotid 18F-fluorodeoxyglucose uptake appeared to be increased in 7 of 16 culprit plaques, but no overall differences in uptake were observed in culprit versus contralateral plaques or control patients. However, 18F-fluorodeoxyglucose did correlate with predicted cardiovascular risk , but not with plaque phenotype.We performed 18F-Fluoride PET/CT highlights culprit and phenotypically high-risk carotid plaque. This has the potential to improve risk stratification and selection of patients who may benefit from intervention. Such biomarkers could also assess the response of plaque biology to novel pharmacological interventions and provide a way of identifying culprit lesions in patients with multiple plaques.Although carotid endarterectomy reduces risk of ipsilateral stroke in people with symptomatic carotid artery stenosis, the number needed to treat to prevent one stroke is large,Tawakol et alSee Editorial by See Clinical Perspective18F-fluorodeoxyglucose (18F-FDG)14: Recently, we have described another radiotracer, 18F-fluoride, in atherosclerosis imaging.16 We18 and others23 have shown that this tracer has major potential in cardiovascular disease. 18F-Fluoride can highlight culprit plaque in patients after myocardial infarction and high-risk plaques in patients with apparently stable coronary heart disease.16 We have shown that this is because 18F-fluoride can highlight areas of microcalcification indicative of necrotic atheroma.24 The ability to identify high risk or culprit plaque in the cephalic circulation has the potential to improve risk stratification in patients at high risk of stroke with a view to more targeted interventions. Our study aims were to compare and contrast the identification of clinically adjudicated culprit and high-risk plaque at the carotid bifurcation using 18F-fluoride and 18F-FDG PET/CT.Hybrid positron emission tomography and computed tomography (PET/CT) is a molecular imaging modality that has high sensitivity for noninvasive in vivo detection of radiolabeled biomolecules tuned to a variety of pathophysiological processes. In carotid atherosclerosis imaging, the most widely used tracer has been 25 criteria for men, ≥70% for women) scheduled to undergo carotid endarterectomy and a control cohort in whom the cause of stroke was not attributed to carotid atheroma. Participants were recruited from outpatient clinics in National Health Service Lothian between January 2013 and June 2014 . Research ethics committee approval  and the written and informed consent of all participants were obtained.Two cohorts of people with a recent transient ischemic attack (TIA) or minor ischemic stroke were recruited: a case cohort with a high-grade internal carotid artery stenosis . Predicted cardiovascular risk was estimated using the ASSIGN score: a validated Scottish cardiovascular risk score that is similar to the Framingham risk score but includes additional factors, such as social deprivation and family history.18F-FDG PET/CT was acquired using a hybrid scanner  90 minutes after the intravenous administration of a target dose of 200 MBq. A rigid neck collar was fitted to minimize movement and standardize position. An attenuation-correction CT scan  was then performed followed by PET acquisition covering 2 bed positions with the first upper bed centered over the carotid bifurcation in 3-dimensional mode for 20 minutes per bed. Patients were fasted for 6 hours before scanning.Static 18F-Fluoride PET/CT was undertaken the subsequent day 60 minutes after administering 250 MBq 18F-fluoride. A neck collar was fitted and an attenuation-correction CT scan was performed. This was followed by PET acquisition covering 2 similar bed positions to the 18F-FDG scan allowing 15 minutes per bed. A subset of 5 patients underwent fully dynamic 18F-fluoride PET/CT with pharmacokinetic analysis as described previously.24 Dynamic PET provides a quantitative assessment of uptake and these data were used to validate the semiquantitative static imaging data.After PET acquisition, a CT carotid angiogram was performed without moving the subject .24 and a Ki value was calculated using Patlak analysis.28Static PET data were reconstructed using the Siemens UltraHD algorithm: ordered subset expectation maximization+point spread function modeling+time-of-flight; 2 iterations and 21 subsets; matrix size 200×200; 5 mm full-width half-maximum Gaussian smoothing. Dynamic PET data were similarly reconstructed but only using coincident events from the 60- to 75-minute time-bin. Dynamic data were analyzed as reported previously18F-fluoride binding patterns (see Appendix in the Data Supplement for detailed methods).At the time of endarterectomy, plaques were collected immediately after excision, photographed, and snap frozen. A random selection (n=8) of specimens was analyzed by micro PET/CT and histology to explore 18F-FDG and 18F-fluoride uptake was performed on an OsiriX workstation . PET/CT data were reviewed alongside the CT angiogram. Scans were qualitatively assessed for registration, image quality, patient movement, and visual evidence of radiotracer uptake. PET and CT data were individually and carefully manually coregistered by lining up fiducial markers apparent on both modalities . No formal inter-PET registration was performed. Three regions of interests (ROIs) were drawn on the carotid of interest on adjacent 3-mm axial slices. If a plaque was present, the ROIs were centered on the area of highest uptake. If there was no plaque, the uptake in the proximal 1 cm of internal carotid artery, just distal to the bifurcation was quantified. From these, standardized uptake values  were recorded. Blood pool activity was determined from the average of 5 ROIs within the lumen of the superior vena cava to calculate target to background ratios.Static analysis of 18F-FDG and 18F-fluoride uptake in a site unaffected by an acute plaque event. Three ROIs were placed around this vessel and uptake was recorded.Uptake in the proximal left common carotid artery was quantified to explore the relationships between arterial 18F-fluoride uptake measurements were determined using a random selection of 12 patients (24 carotids) by 2 experienced observers  who were blinded to the clinical data during analysis.Inter- and intraobserver reproducibility of The CT angiogram was assessed for image quality, plaque presence, location, and characteristics. Analysis was undertaken on a cardiovascular workstation . A blinded and experienced observer (A.V.) performed the semiautomated CT plaque analysis.t-tests) and nonparametric (Mann–Whitney U or Wilcoxon matched-pairs signed rank) tests were used for normally distributed and skewed data, respectively. Categorical data are presented as n (%) and were compared using Fisher’s exact or Chi-squared tests. Correlation was undertaken with either Pearson’s r or Spearman’s ρ subject to the normality of the variables tested. To quantify inter- and intraobserver reproducibility of 18F-fluoride uptake measurement, the intraclass correlation coefficient was calculated and Bland-Altman analysis was undertaken.Radiotracer uptake, expressed as mean and maximum SUV, was compared between the clinically adjudicated culprit carotid plaque and the contralateral side. Continuous variables are expressed as mean±standard deviation for normally distributed data and median (interquartile range) for skewed distributions. Skewed datasets underwent logarithmic transformation to normalize their distribution. Parametric  and Graph Pad Prism version 6.0 . Statistical significance was defined as a 2-sided Data Supplement). Baseline characteristics . Both on autoradiography and micro PET/CT, 18F-fluoride was observed to bind avidly to areas of microcalcification but only to the surface of large volume stable macrocalcifications. Our previous studies24 would suggest that this was because of the inability of the fluoride ion to penetrate to the deeper layers of a large crystalline mass (with a low surface-area-to-volume ratio). In contradistinction, the powdery deposits of microcalcification (not visible on CT) provide a large area (high surface-area-to-volume ratio) for the fluoride ion to bind.18F-fluoride uptake on static imaging with full dynamic modeling, Ki was most strongly correlated with the SUVmean . These assessments also demonstrated high intraclass correlation coefficients .When comparing the 18F-Fluoride uptake was variably present in most plaques with all culprits showing uptake on visual assessment. In the large majority of patients undergoing carotid endarterectomy who were scanned , there was more visual uptake of 18F-fluoride in the culprit compared with the contralateral side. In the 2 patients without discriminatory uptake, there was heavy uptake bilaterally but more 18F-fluoride uptake on the contralateral side. One patient had grossly ossified carotids and the second, at the time of surgery, was found to have a fibrous stenosis  and was subsequently admitted with a fatal ischemic stroke on the contralateral side  or an unpaired control  irrespective of the method of quantification .Of note, in patients with a stroke in whom the imaging extended to encompass the affected territory of the brain n=3), intense , intense18F-FDG uptake. However, this uptake was generally more diffuse than 18F-fluoride and analysis was more frequently hampered by overspill from sternocleidomastoid, longus colli, tonsillar tissue, and the submandibular salivary glands  or control vessels  irrespective of the method of quantification , although there were also strong correlations with high-risk features such as plaque burden  and positive remodeling .is Table . The str18F-FDG SUVmeanmaxr=0.48, P=0.037; 18F-fluoride SUVmeanr=0.59, P=0.007) and the cardiovascular risk score  but neither was associated with serum C-reactive protein concentration.In terms of baseline cardiovascular risk indices, uptake of both tracers in the vasculature correlated with age  that this is explained by the ability of 18F-fluoride to report microcalcification. Why is this the case? Far from a passive and degenerative process, vessel mineralization is a controlled response to a variety of insults, particularly oxidized inflammatory lipid . It is therefore perhaps no surprise that direct links between atherosclerosis and the induction of extraskeletal osteogenesis have been identified.31 The presence of cellular necrosis and apoptosis32 is also likely to potentiate this relationship further. Hydroxyapatite nanocrystals themselves may also further drive the inflammatory cycle by setting up a positive feedback loop of increasing calcification, increasing inflammation, and increasing cell death.30 Furthermore, by accumulating in the surface of thin fibrous caps, microcalcifications may focally increase mechanical stress and thus promote structural cap failure and plaque rupture.3418F-Fluoride can demonstrate this pathologically important microscopic calcific response.We have previously shown that 18F-fluoride uptake in necrotic brain tissue and merits consideration. Uptake of this and other bone metabolism markers has previously been observed in tissue necrosis.35 This is likely to be because of cell membrane disruption with influx of calcium and formation of nanoscale calcium phosphate complexes. These offer a substrate to which 18F-fluoride can adsorb, allowing us to visualize the microcalcification associated with necrosis. We have also observed the same process in myocardial tissue postinfarction .This is the first observation of 18F-fluoride may have real potential in helping to identify culprit plaque thus helping decision-making. This is exemplified by the case where a plaque with high uptake deemed nonculprit subsequently caused a fatal ischemic stroke.We confirmed identification of culprit plaque in 2 ways. First, we compared the culprit to the ideal internal control, the contralateral carotid artery . Second, we compared the culprit against a valid external control; patients with a TIA or minor ischemic stroke not attributed to carotid plaque. This shows that 18F-fluoride with 18F-FDG. Unlike 18F-fluoride, overall, 18F-FDG uptake was not significantly higher in culprit lesions. Moreover, on a per-lesion basis, 18F-FDG failed to correlate with high-risk plaque morphological features, whereas 18F-fluoride uptake correlated with plaque burden, positive remodeling, and luminal stenosis: all established markers of plaque risk. Other studies have explored the utility of 18F-FDG alone in carotid atherosclerosis and a few have directly compared clinical culprit with nonculprit plaques.13 Our results are consistent with these previous findings with significant uptake noted in some but not all culprit plaques, in part because of spillover from adjacent muscle. Our observations are also influenced by the ubiquity of statin therapy, potentially blunting 18F-FDG uptake. We did, however, note that proximal carotid uptake correlated with cardiovascular risk indicating that 18F-FDG does reflect a major aspect of vessel pathobiology. As others suggest,40 it may be that 18F-FDG better reflects generalized vascular inflammation and that the relationship between the tracer and a single advanced and acute plaque is more complicated. There are increasing data available concerning other more specific markers of inflammation, such as those targeting the macrophage-specific somatostatin receptor.41 These will theoretically be less hampered by overspill.We compared uptake of 23 that explored 18F-fluoride and 18F-FDG uptake in symptomatic patients. They showed that 18F-fluoride uptake appeared to be higher in the symptomatic carotid and that 18-FDG uptake was nondiscriminatory. Taken together with our current larger series, this suggests that 18F-fluoride has the potential to be a useful and robust clinical tool to identify culprit atherosclerotic plaque. Vascular 18F-fluoride imaging could therefore guide clinical management better than the current standard of care, and lead to trials of plaque-specific interventions that go beyond simple assessments of anatomic luminal stenosis severity.Our findings confirm those of a smaller study of 9 patients by Quirce et al18F-fluoride PET/CT will need to be evaluated by prospective studies with patients randomized to intervention based on imaging. 18F-Fluoride PET/CT will need to be compared with other techniques42 (in particular MR or PET/MR) which have the advantages of improved soft tissue definition, reduced radiation, and lack of iodinated contrast. We did not perform prolonged-delayed 18F-FDG imaging which some authors have suggested is advantageous.43 We also acknowledge that quantitative vascular PET has some potential limitations because of the partial volume effects of small vascular structures. Finally, as vascular 18F-fluoride imaging is developed, consideration must be given to harmonizing acquisition and reconstruction protocols,44 as well as achieving consensus on the uptake parameter of choice (SUV versus target to background ratio versus volumetric parameters45) and whether to use manual or automated methods to define ROI. This will reduce variation between scanners and research groups and permit meaningful multicenter studies.This was a small pilot observational study  and findings should be regarded as preliminary. The true utility of 18F-fluoride PET/CT is able to identify culprit or high-risk carotid plaque. In comparison, 18F-FDG, the most widely used tracer in cardiovascular PET imaging, did not reliably identify culprit plaque and did not correlate with high-risk morphological features. 18F-Fluoride PET has major potential to improve how we assess and manage the risk of stroke in patients with atherosclerosis.We have shown that We acknowledge the help and support of the vascular surgical staff at the Royal Infirmary of Edinburgh and the radiography and radiochemistry staff of the Clinical Research Imaging Centre.Dr Vesey and the study were funded by program grants from the British Heart Foundation (PG12/8/29371) and Chest Heart and Stroke Scotland (R13/A147). Dr Jenkins, Vesey, Dweck, and Newby are supported by the British Heart Foundation  and the Wellcome Trust (WT103782AIA). Dr Dweck is the recipient of the Sir Jules Thorn Biomedical Research Award 2015. The Wellcome Trust Clinical Research Facility and the Clinical Research Imaging Centre are supported by National Health Service (NHS) Research Scotland (NRS) through NHS Lothian. Dr Beek is supported by the Scottish Imaging Network—a Platform of Scientific Excellence (SINAPSE). Dr Rudd is part-supported by the National Institute for Health Research Cambridge Biomedical Research Centre, the British Heart Foundation, and the Wellcome Trust.None.


This study assessed the adherence profiles to inhaled therapies and the agreement between two patient self-report adherence methods in stable COPD lpatients from seven Latin American countries.1/FVC] <0.70). Adherence to inhaled therapy was assessed using the specific Test of Adherence to Inhalers (10-item TAI) and the generic 8-item Morisky Medication Adherence Scale (MMAS-8) questionnaires. The percentage agreement and the kappa index were used to compare findings.This observational, cross-sectional, multinational, multicenter study involved 795 COPD patients .59.6% of patients were male (69.5±8.7 years); post-bronchodilator FEVSuboptimal adherence to medication was frequent in COPD patients from Latin America. Low adherence was associated with worse health status impairment and more exacerbations. There was inadequate agreement between the two questionnaires. Greater effort should be made to improve COPD patients’ adherence to treatment, and assessment of adherence with more specific instruments, such as the TAI questionnaire, would be more convenient in these patients.NCT02789540 Chronic obstructive pulmonary disease (COPD) is considered a preventable and treatable disease . The inhDespite the availability of different therapeutic alternatives for COPD, a considerable proportion of patients remain symptomatic or do not achieve treatment goals, which is, in part, due to the poor adherence to inhaled treatment.Several studies have reported that poor adherence to inhaled therapies is common in COPD with non-adherence being associated with poor symptom control, higher healthcare utilization and costs and decreased health-related quality of life (HRQoL) –10. OtheThe Initiative for Chronic Obstructive Lung Disease (GOLD) document specifically recommends evaluation and follow-up of patients’ inhalation technique . HoweverAssessing adherence to treatment is complex and many methods have been proposed in COPD . Patient’s self-report methods accompanied with inhaler technique assessment are considered the most suitable for measuring adherence to medication in clinical practice, even though patients tend to over-estimate adherence.The 8-item Morisky Medication Adherence Scale (MMAS-8) is a generic self-reported, medication-taking behavior scale that is considered the most commonly used self-reporting method to determine adherence in chronic diseases ; howeverLimited information exists regarding adherence to inhaled therapies in COPD patients from Latin America, as well as the degree of agreement between different self-report measures in a large COPD population. We hypothesized that adherence to inhaler medication in COPD patients from Latin America is suboptimal and is associated with worse outcomes. Therefore, the aims of this study were to assess the adherence profiles to inhaled therapies and the level of agreement between two patient self-report adherence questionnaires in stable COPD patients from seven Latin American countries.Latin American Study of 24-hour Symptoms in Chronic Obstructive Pulmonary Disease (LASSYC) study was conducted in seven Latin American countries: Argentina, Chile, Colombia, Costa Rica, Guatemala, Mexico, and Uruguay. This was a prospective observational, multicenter, multinational, cross-sectional, non-interventional study in stable COPD patients.The Site staff collected, retrospectively, the information from patients’ medical records to determine eligibility. Patients were identified consecutively and, if they meet eligibility criteria and provide consent were enrolled. There was only one scheduled study visit in which the physician explained the patient the purpose of the research and invited to participate. At study visit, selected patients were asked to provide data on disease-related symptomatology assessed during a 24-hour day, adherence to inhalers, HRQoL, and physical activity. The physician collected the following data at visit : social demographics, health insurance system, lifestyle, smoking history, comorbidities, level of dyspnea, disease severity, prescribed COPD treatments, exacerbation history, and healthcare resource utilization during the last 12 months.The study was performed in line with the Declaration of Helsinki and approved by the review board and local ethics committee (the name of the committees in each country are listed in Table A in 1/FVC) <0.70 criteria [Inclusion criteria were: male and female outpatients, aged ≥40 years, diagnosis of COPD at least for 1 year, at least one spirometry value with a COPD diagnosis using the post-bronchodilator forced expiratory volume in 1 second/forced vital capacity  was designed to guide clinically the non-adherence patterns. In the present study, we only use the 10-item TAI questionnaire. This includes (patient domain) self-administered and scored from 1 to 5 . The total score for the 10-item questionnaire ranges from 10–50. Adherence is rated as good (score: 50), intermediate (score: 46–49), or poor (score: <45) .www.taitest.com), which classified individuals with an erratic non-adherent pattern (sum of items 1–5: <25 points) or in deliberate non-adherent pattern (sum of items 6–10: <25). The 12-item TAI, also includes items #11 and #12 of the health care professional and scored as 1 or 2 (where 1 was bad and 2 was good), with a range from 2 to 4. The latter items were designed to identify two possible causes of unwitting non-adherent behavior. In the present study, these items were not assessed, therefore unwitting non-adherent behavior could not be determined.In the 10-item TAI questionnaire, items 1 to 5 allow to identify the erratic non-adherence behavior (forgetfulness to take medication) and items 6 to 10 identify deliberate non-adherence behavior (patient decision not to take medication). The profile of individuals with erratic and/or deliberate non-adherence behavior was assessed following the questionnaire instructions (™ 2016 (formerly EXACT-RS) [“Evaluating Respiratory Symptoms in COPD” E-RSXACT-RS)  was usedXACT-RS)  and EarlXACT-RS) .Dichotomous variables for defining daytime, early morning and night-time symptoms were built. For daytime symptoms, we used the third tertile of the score; the early morning symptoms were defined according to the severity of dyspnea, classified as moderate or higher, plus other symptoms, classified as moderate or more severe; for night-time symptoms, we considered those who woke up at least once at night due to COPD symptoms.1 percent predicted (according to PLATINO equations) [Descriptive statistics included the absolute and relative frequencies for categorical variables and mean and standard deviation for numerical ones. For the comparison between MMAS-8 scale and TAI questionnaires, we used the kappa index. To assess the association between adherence , and symptoms (continuous score), Poisson regression models were applied. Adjustments took into account sex, age (complete years), pack-years smoked in life, body mass index, airflow obstruction, dyspnea, exacerbations, BODEx index, modified Medical Research Council (mMRC) scale, COPD comorbidity test (COTE), CAT score, physical activity (min/week) and FEVuations) . All ana1 of 50.0±18.6% predicted. Among these patients, 787 (99%) completed the TAI and 783 (98%) the MMAS-8 questionnaire. The proportion of patients in the different categories of adherence according to MMAS-8 and TAI questionnaires is shown in 795 patients were included, 59.6% were male, mean age of 69.5±8.7 years, with post-bronchodilator FEV1 compared with those with good adherence. Similar results were observed using the MMAS-8 questionnaire.The sample characteristics of subjects according to MMAS-8 and TAI adherence categories are shown in Tables Mean total and by item values for the TAI questionnaire (47.4±4.9) and MMAS-8 (6.8±1.6) scale are shown in The agreement between TAI and MMAS-8 questionnaires is shown in Crude and adjusted associations between adherence categories  with the early morning, daytime and night-time symptoms severity scores and symptoms prevalence are shown in Tables 1; and third, the agreement between the TAI and MMAS-8 questionnaires was moderate.The main findings on adherence to inhaled therapies in COPD patients were: first, around 50% of patients had good adherence to inhaled therapies according to TAI and MMAS-8 questionnaires; second, low adherence was associated with lower smoking history, schooling level, worse health status, more exacerbations, and better post-bronchodilator FEVAlthough inhaler therapy is the cornerstone of COPD management, adherence to COPD medication is generally considered to be low, even in very severe disease. The average adherence rate in COPD clinical trials is estimated to be 70–90%; however, in clinical practice, this rate ranges between 20–60%. Few studies have evaluated adherence to inhaled therapies using self-reported methods in COPD. George et al using the medication adherence report scale found self-reported good adherence was present in 37% of the patients . Ágh et Poor adherence to inhaled therapies is associated with higher morbidity and healthcare utilization, probably as a result of worse and more frequent respiratory symptoms, and more frequent exacerbations –9. VestbMost studies that have evaluated the relationship between adherence and outcomes in COPD relied only on pharmaceutical databases, and have had limited clinical practice information. To our knowledge, no information is available regarding the frequency and severity of respiratory symptoms, health status, or exacerbations among real-life COPD patients with high and low adherence to inhaled treatment.1 (54.2%) compared with patients with intermediate (50%) and high adherence (47.2%). This would mean that more severe patients are more adherent (probably because they are more symptomatic or experience more relief of symptoms).Our results are consistent with those reported in other populations from developed countries showing that patients with low adherence versus those with high adherence had worse health status (CAT score), and more frequent exacerbations in the past year. However, we were unable to find a clear relationship between early morning, daytime and night-time symptoms and treatment adherence. Studies have shown that pharmacologic COPD therapy reduces symptoms, frequency and severity of exacerbations, and improves exercise tolerance and health status; hence, explaining why patients with lower adherence have worse outcomes. Regarding the finding of improved lung function in patients with poor adherence, it is possible that these patients are more likely to have greater erratic and deliberate non-adherence behavior , and self-report measures, but they are all burdened with important limitations. Recently, several methods to objectively quantify adherence to inhaler therapy (electronic audio recording device) have been assessed . Smart iIn the clinical setting, the most convenient approach is using self-report questionnaires because they are easy to use, inexpensive, and not time-consuming. However, compared with data obtained via electronic monitoring, studies have demonstrated that self-reports can be inaccurate because patients generally over-report medication use. To date, there is no “gold standard” self-report questionnaire to assess treatment adherence in COPD patients.® electronic devices compared with the Morisky-Green test  [Very few studies have assessed adherence to treatment in COPD using patients’ self-report methods. One study has used two self-report questionnaires ; here, t = 0.25) . Regardi = 0.25) .We assessed the agreement between TAI and MMAS-8 questionnaires (kappa index = 0.42) and found this was moderate (kappa index between 0.41–0.60). Considering that any agreement less than perfect (1.0) is a measure not only of agreement but also of disagreement, any kappa value below 0.60 indicates an inadequate agreement among the measurements. The lack of agreement between the questionnaires may be accounted for by the differences in adherence aspects assessed by each questionnaire and the greater specificity of the TAI questionnaire for the analysis of adherence to inhaled medication versus the generic MMAS-8. The TAI questionnaire not only evaluates the aspects included in the MMAS-8 but also covers a wider range of situations such as forgotten, lack of need of inhaler use, deliberate non-adherent behavior, and concern about side effects and availability .This study has limitations; one is that medication adherence was only assessed using self-reported measurements and this could lead to an over-estimation of medication use. In the present study, we used the 10-items TAI questionnaire so data from the final two items (#11 and #12) of the 12-item questionnaire were not available. These items were designed to identify unwitting non-adherent behavior . Therefore, it was no possible to analyze whether patients take their inhaler properly or not, so that the pattern of non-adherence was not completely evaluated.In conclusion, our results indicate that suboptimal adherence to medication is frequent in COPD patients from Latin America. Low adherence is associated with worse health status and more exacerbations. There is inadequate agreement between the TAI and MMAS-8 questionnaires, and it would be more convenient to assess adherence to inhaled treatment in COPD with more specific instruments such as the TAI questionnaire.S1 FileTable A. Patients’ demographics or characteristics according to the non-adherence behavior pattern. Table B. Crude and adjusted association between adherence and CAT score . Table C. Crude and adjusted association between adherence and exacerbations in past . Table D. Crude and adjusted association between adherence and exacerbations in past . Table E. Correlation matrix between TAI scale and lung function parameters.(DOCX)Click here for additional data file.S2 FileThis is the file containing the study protocol.(PDF)Click here for additional data file.S3 File(XLSX)Click here for additional data file.