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Figure 5. Gene set enrichment analysis (GSEA) showed that high ANXA1 expression tumors
significantly enriched inflammatory response, TNF- signaling via NF B, epithelial-mesenchymal
transition, TGF- signaling, hypoxia, and angiogenesis gene sets in TNBC in both TCGA and
METABRIC cohorts.
3. Discussion
ANXA1 is known to be related to inflammatory pathways , cell proliferation, and the regulation
of cell death signaling . However, there have been controversies in its role in breast cancer and
survival. To our knowledge, this is the first study to investigate the association between ANXA1
expression and cancer using two large independent cohorts. We found that ANXA1 high tumors
enriched inflammation and EMT gene sets, which suggest that previously reported mechanisms using
in vitro and in vivo experiments are in place in human cancer and are clinically relevant.
Strikingly, we found that ANXA1 high tumors significantly enriched angiogenesis gene sets
were associated with high infiltration of activated mast cells. The role of tumor-infiltrating mast
cells has been drawing attention in recent years. However, their impact on patients’ prognosis has
been controversial . It was reported that the density of mast cells increases in breast tumors
after neoadjuvant chemotherapy, suggesting a strong association with tumor immunity . Taken
together, we cannot help but speculate that ANXA1 expression may play a role in mast cell-induced
inflammation and angiogenesis in breast cancer, which is a di erent mechanism compared to that seen
in other cancers, such as colon cancer, and that may be one of the reasons why clinical trials using
anti-angiogenesis therapy have failed in breast cancer.
ANXA1 continues to attract attention, and some reported that the expression of ANXA1 may be
associated with chemotherapy response in TNBC . Other authors reported that ANXA1 plays an
important role in the tumor microenvironment .
Our study has several limitations. The first and biggest was that while our research has
demonstrated the association between ANXA1 expression and mast cell infiltration, we have no data
to suggest causality. The second was that TCGA and METABRIC databases have substantial missing
values, especially information regarding metastasis. In addition, immune cells were assessed with a
computational algorithm alone and not with flow cytometry or immunohistochemical staining (IHC)
in this study. It would have been ideal to validate the association of ANXA1 expression and mast cell
infiltration with protein expression as was previously done in survival analyses; however, no sample
Int. J. Mol. Sci. 2019, 20, 4197 7 of 11
was available for flow cytometry that would allow such analyses. In the future, we hope to conduct a
prospective study with a larger sample volume to overcome these issues.
4. Materials and Methods
4.1. Patient Cohorts
The patient clinical data and gene expression data (mRNA expression z-score of RNA-seq) were
downloaded through cBioPortal from the latest The Cancer Genome Atlas (TCGA) cohort (TCGA
provisional) as described previously . Among 1081 female breast cancer patients with mRNA
expression from RNA sequence data, survival data were available in 1079 patients. Level 3 Z-score
normalized gene expression data, as well as overall survival data from 1904 patients in a Molecular
Taxonomy of Breast Cancer International Consortium (METABRIC) cohort , were also downloaded
from cBioPortal. Patients were classified as either high or low ANXA1 expression using the median of
their mRNA expression as the cut-o . Disease-free survival (DFS) was defined from the time of
completion of primary treatment until clinical confirmation of tumor recurrence. Overall survival (OS)
was defined using time of death. For disease-specific survival (DSS) analyses, the patients who died of
other causes were excluded. CYT is the immune cytolytic activity score. It has previously been defined
by calculating the geometric mean expression values of granzyme A (GZMA) and perforin (PRF1) .
These proteins are pivotal cytolytic e ector molecules. MATH is the mutant-allele tumor heterogeneity
level. This is derived by calculating the median of its mutant-allele fractions at tumor-specific mutated
loci, which has been described in detail .
4.2. CIBERSORT
CIBERSORT, a bioinformatic algorithm that allows calculation of immune cell composition from
gene expression profiles, was invented to estimate tumor-infiltrating immune cells in tumors and
was applied as described previously . Immune cell fraction data was downloaded through The
Cancer Imaging Archive (TCIA) (https://tcia.at/home) .
4.3. Gene Set Enrichment Analysis
GSEA was performed on TCGA and METABRIC cohorts using software provided by the
Broad Institute (http://software.broadinstitute.org/gsea/index.jsp), as described previously .
We classified the patients into two groups according to ANXA1 expression using the mean of their
gene expression range.
4.4. Clinical Samples for Protein Expression
All cases analyzed with immunohistochemistry underwent surgical resection at Fukushima
Medical University between 2002 and 2011. The present study was approved by the Institutional
Review Board and the Ethics Committee of Fukushima Medical University.
4.5. Immunohistochemical Staining and Evaluation
The immunohistochemical staining approach involved immunostaining formalin-fixed
para n-embedded (FFPE) sections for ANXA1. The staining intensity was analyzed using previously
reported methods . These methods involve taking breast cancer specimens and fixing them in
10% formalin and embedding them in para n. The fixed specimens are then cut into 4 m sections
and stained with anti-ANXA1 antibody (clone 29; BD Biosciences, San Jose, CA, USA). ANXA1
expression was defined as high when more than 5% of cells per high-power field stained positive by
immunohistochemistry, following the criteria used in our previous report . Less than 5% staining
of ANXA1 was defined as low expression.

4.6. Statistical Analysis
The di erences in OS and DSS between ANXA high and low groups were analyzed using a
Kaplan–Meier method with the log–rank test as described previously . The clinicopathological
characteristics were compared statistically using the chi-square test or the Fisher exact test.
The di erences between continuous values were compared using the Student’s t-test. A p < 0.05 was
considered statistically significant. All statistical analyses were performed using Microsoft Excel 2010,
R software (http:///www.rproject.org/) and Bioconductor (http://bioconductor.org/).
5. Conclusions
These results prove that high expression of ANXA1 is significantly associated with mast cell
infiltration in TNBC, which can explain the strong association with angiogenesis. Our report reinforces
the fact that breast cancer and inflammation show a strong relationship, which can add a new dimension
to the future research and treatment of TNBC.
Supplementary Materials: Supplementary materials can be found at http://www.mdpi.com/1422-0067/20/17/
4197/s1.
Author Contributions: M.O. conceptualized the study design, performed analysis, and prepared the article. M.O.,
E.K., K.T., K.S., H.O., X.P., L.Y. performed the analysis. A.L.B. prepared the article. K.K., T.O. supervised the
analysis. K.T. provided supervision of the analysis and prepared the article.
Funding: This work was supported by NIH grant R01CA160688 to K.T., and National Cancer Institute (NCI)
grant P30CA016056 involving the use of Roswell Park Cancer Institute’s Resources.
Conflicts of Interest: The authors declare no conflict of interest.
Abbreviations
ANXA1 Annexin A1
TNBC Triple-Negative Breast Cancer
ER Estrogen Receptor
PgR Progesterone Receptor
HER2 Human Epithelial growth factor Receptor 2
TCGA The Cancer Genome Atlas
METABRIC Molecular Taxonomy of Breast Cancer International Consortium
GSEA Gene Set Enrichment Analysis
IHC Immunohistochemistry
CYT Cytolytic Activity
MATH Mutant-Allele Tumor Heterogeneity
References
1. Foulkes, W.D.; Smith, I.E.; Reis-Filho, J.S. Triple-negative breast cancer. N. Engl. J. Med. 2010, 1938–1948.

2. Rouzier, R.; Perou, C.M.; Symmans, W.F.; Ibrahim, N.; Cristofanilli, M.; Anderson, K.; Hess, K.R.; Stec, J.;
Ayers, M.; Wagner, P.; et al. Breast Cancer Molecular Subtypes Respond Di erently to Preoperative
Chemotherapy. Clin. Cancer Res. 2005, 11, 5678–5685.
3. Turner, N.C.; Reis-Filho, J.S. Tackling the Diversity of Triple-Negative Breast Cancer. Clin. Cancer Res. 2013,
19, 6380–6388.
4. Zhang, Z.; Huang, L.; Zhao,W.; Rigas, B. Annexin 1 induced by anti-inflammatory drugs binds to NF-kappaB
and inhibits its activation: Anticancer e ects in vitro and in vivo. Cancer Res. 2010, 2379–2388.

5. Dalli, J.; Norling, L.V.; Renshaw, D.; Cooper, D.; Leung, K.-Y.; Perretti, M. Annexin 1 mediates the rapid
anti-inflammatory e ects of neutrophil-derived microparticles. Blood 2008, 112, 2512–2519.

46. McDonald, K.-A.; Kawaguchi, T.; Qi, Q.; Peng, X.; Asaoka, M.; Young, J.; Opyrchal, M.; Yan, L.; Patnaik, S.;
Otsuji, E.; et al. Tumor Heterogeneity Correlates with Less Immune Response and Worse Survival in Breast
Cancer Patients. Ann. Surg. Oncol. 2019, 26, 2191–2199.
47. Newman, A.M.; Liu, C.L.; Green, M.R.; Gentles, A.J.; Feng,W.; Xu, Y.; Hoang, C.D.; Diehn, M.; Alizadeh, A.A.
Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 2015, 12, 453–457.
48. Okano, M.; Oshi, M.; Butash, A.L.; Asaoka, M.; Katsuta, E.; Peng, X.; Qi, Q.; Yan, L.; Takabe, K. Estrogen
Receptor Positive Breast Cancer with High Expression of Androgen Receptor has Less Cytolytic Activity
and Worse Response to Neoadjuvant Chemotherapy but Better Survival. Int. J. Mol. Sci. 2019, 20, 2655.

49. Charoentong, P.; Finotello, F.; Angelova, M.; Mayer, C.; Efremova, M.; Rieder, D.; Hackl, H.; Trajanoski, Z.
Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of
Response to Checkpoint Blockade. Cell Rep. 2017, 18, 248–262.
50. Subramanian, A.; Tamayo, P.; Mootha, V.K.; Mukherjee, S.; Ebert, B.L.; Gillette, M.A.; Paulovich, A.;
Pomeroy, S.L.; Golub, T.R.; Lander, E.S.; et al. Gene set enrichment analysis: A knowledge-based approach for
interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 2005, 102, 15545–15550.
51. Takahashi, H.; Katsuta, E.; Yan, L.; Dasgupta, S.; Takabe, K. High expression of Annexin A2 is associated
with DNA repair, metabolic alteration, and worse survival in pancreatic ductal adenocarcinoma. Surgery
2019, 166, 150–156.
52. Katsuta, E.; Qi, Q.; Peng, X.; Hochwald, S.N.; Yan, L.; Takabe, K. Pancreatic adenocarcinomas with mature
blood vessels have better overall survival. Sci. Rep. 2019, 9, 1310.
53. Sporn, J.C.; Katsuta, E.; Yan, L.; Takabe, K. Expression of MicroRNA-9 is Associated with Overall Survival in
Breast Cancer Patients. J. Surg. Res. 2019, 233, 426–435.
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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_____________________________________________________________________________________________________________________
Cardinal Station Newburg Center for Primary Care
215 Central Avenue, Suite 100 1941 Bishop Lane, Suite 900 215 Central Avenue, Suite 205
Louisville, KY 40208 Louisville, KY 40218 Louisville, Ky 40208
I:FCMPhyllis HarrisFormsNew Patient Pkg Components
UofL Department of Family & Geriatric Medicine
Dear New Patient,
Welcome to your University of Louisville Physicians Family practice! We
are offering patient-centered medical care and are enthusiastic about our
relationships with our patients. In order to better serve your needs, we are
enclosing several forms and ask that you completely fill each form out.
The first sheet will help us learn more about you; please completely fill out this
form about your family history. The next sheet is titled, “Authorization for the
use and/or Disclosure of Protected Health Information”, and you will need to
completely fill that out for our doctors to treat you to the best of their ability; it
gives us permission to review your medical records from your previous primary
medical facilities.
Following, please completely fill out the Registration, Social Services & Consent
Form. Next, you will find our Privacy Notice, followed by an acknowledgement that
you have received and understand our Privacy Policies. Finally, the last form is the
Office Acknowledgements and Policies form. Please read carefully and sign
your name at the bottom of the letter.
Please make sure to bring all of these forms with you to your first office visit.
Do not mail them back to the office. Also, please remember to always
bring your picture ID, current insurance cards and your co-payment. If your
health insurance requires you to select a primary care doctor please do so prior to
your office visit. Please bring in any and all medication you take, in their
original bottles, to your appointment.
If the patient is under 18 years of age he or she must be accompanied by an
adult and will need to bring a copy of their current immunization certificate.
Please arrive 15 minutes ahead of your scheduled appointment time so that if
you have questions about these forms or we need more information, we can
address it all prior to your appointment.
We look forward to seeing you!
University of Louisville Physicians
UofL Family and Geriatric Medicine

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RESEARCH ARTICLE

Noise as a risk factor in the delivery room: A

clinical study

Kristiane Roed JensenID1

*, Lone Hvidman2

, Ole Kierkegaard1

, Henrik Gliese3

,Tanja Manser4

, Niels Uldbjerg2

, Lise Brogaard1

1 Department of Obstetrics and Gynecology, HEH-Horsens Regional Hospital, Horsens, Denmark,2 Department of Obstetrics and Gynecology, Aarhus University Hospital, Aarhus, Denmark,3 ArbejdsmiljøEksperten A/S, Occupational and environmental consultants, Esbjerg, Denmark, 4 School ofApplied Psychology FHNW, University of Applied Sciences and Arts Northwestern Switzerland, Olten,Switzerland

* kristiane@roedjensen.com

Abstract

Introduction

We aimed to investigate whether noise in delivery rooms is associated with impaired performance of obstetric teams managing major (�1000 mL) postpartum hemorrhage.

Material and methods

We included video recordings of 96 obstetric teams managing real-life major postpartumhemorrhage. Exposure was noise defined as the occurrence of sound level pressures (SPL)above 90 dB. The outcome was high clinical performance assessed through expert ratingsusing the TeamOBS-PPH tool.

Results

The 23 teams unexposed to noise had a significantly higher chance of high clinical performance than the 73 teams exposed to noise: 91.3% (95% CI; 72.0–98.9) versus 58.9% (95%CI; 46.8–70.3) (p < 0.001). The results remained significant when adjusting for the followingpossible confounders: team size, non-technical performance, bleeding velocity, hospitaltype, etiology of bleeding, event duration and time of day. Typical sources of noise above 90dB SPL were mother or baby crying, dropping of instruments, and slamming of cupboarddoors.

Conclusion

Noise in delivery rooms may be an independent source of impaired clinical performance.

PLOS ONE | https://doi.org/10.1371/journal.pone.0221860 August 30, 2019 1 / 10a1111111111

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a1111111111

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OPEN ACCESS

Citation: Jensen KR, Hvidman L, Kierkegaard O,

Gliese H, Manser T, Uldbjerg N, et al. (2019) Noise

as a risk factor in the delivery room: A clinical

study. PLoS ONE 14(8): e0221860. https://doi.org/

10.1371/journal.pone.0221860

Editor: Guillaume Ducarme, Centre Hospitalier

Departementai Vendee, FRANCE

Received: January 31, 2019

Accepted: August 18, 2019

Published: August 30, 2019

Copyright: © 2019 Jensen et al. This is an open

access article distributed under the terms of the

Creative Commons Attribution License, which

permits unrestricted use, distribution, and

reproduction in any medium, provided the original

author and source are credited.

Data Availability Statement: All data files are

available from the Figshare database DOI: https://

doi.org/10.6084/m9.figshare.8111390.v1.

Funding: The study was funded by Tryg

Foundation (Trygfonden) (grant ID no. 109507),

https://www.trygfonden.dk; the Regional Hospital

in Horsens, Department of Obstetrics and

Gynecology and the Regional Postgraduate

Medical Education Administration Office North. The

funders had no role in study design, data collection

and analysis, decision to publish, or preparation of

the manuscript.

Introduction

Over the past decades, noise has increased at hospitals throughout the world. The estimatedincrease is 15 dB(A), which is considerable as an increase of 10 dB corresponds to a doublingof the perceived noise level. Noise is associated with adverse health outcomes, stress andimpaired performance. Especially sudden, unpredictable noise can cause a startledresponse and thus lead to work disruption.

We know little about how noise affects healthcare providers managing acute events in thehospital setting. However, studies point at increased levels of stress and impaired performancewith cognitive tasks and motor coordination for healthcare workers and other professionalsbeing affected. Accordingly, a pediatric surgery department tried to implement a noisereduction program. They managed to reduce the overall operation theatre sound levelsfrom 63dB(A) to 60 dB(A) and observed a significant decrease in complication rates duringthe same period of time. Labor wards are even noisier with average noise levels reaching 87 dB(A) and maximum noise levels reaching 122 dB(A). Even though this is not experiencedby all personnel every day, these levels are actually within the range where hearing protectionis recommended by the WHO. Such high noise levels may be critical when managingemergencies like postpartum hemorrhage where providing the correct treatment promptly isof paramount importance.

If noise has the potential to impair the clinical performance of obstetric teams, precautionsshould be taken. To our knowledge, no study of the impact of noise on the clinical performance of real-life obstetric emergency teams has previously been published. We thereforeaimed to investigate whether exposure to noise impairs clinical performance in obstetric teamsmanaging real-life major (�1000 mL) postpartum hemorrhage.

—-Sg;apkh;nhg

uva.nl/praat/manual/Time_step_settings___.html

20. Morgan PJ, Tregunno D, Pittini R, Tarshis J, Regehr G, Desousa S, et al. Determination of the psychometric properties of a behavioural marking system for obstetrical team training using high-fidelity simulation. BMJ Qual Saf. 2012; 21(1):78–82. https://doi.org/10.1136/bmjqs-2011-000296 PMID: 2199435821. Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of eventsper variable in logistic regression analysis. J Clin Epidemiol. 1996 Dec; 49(12):1373–9. PMID: 897048722. Senn SJ. Power is indeed irrelevant in interpreting completed studies. BMJ. 2002; 325(7375):1304.

23. Hoenig JM, Heisey DM. The Abuse of Power. Am Stat. 2001; 55(1):19–24.

24. Hancock M, Kent P. Interpretation of dichotomous outcomes: risk, odds, risk ratios, odds ratios andnumber needed to treat. J Physiother. 2016 Jul; 62(3):172–4. https://doi.org/10.1016/j.jphys.2016.02.

016 PMID: 27320830

25. Cleveland WS, Devlin SJ. Locally Weighted Regression: An Approach to Regression Analysis by LocalFitting. J Am Stat Assoc. 1988; 83(403):596–610.

26. Cleveland WS. Robust locally weighted regression and smoothing scatterplots. J Am Stat Assoc. 1979;74(368):829–36.

27. Harrell FE. Regression Modeling Strategies. Cham: Springer International Publishing; 2015. 63–102 p.

(Springer Series in Statistics).

28. Van Pelt M, Weinger MB. Distractions in the anesthesia work environment: Impact on patient safety?

Report of a meeting sponsored by the anesthesia patient safety foundation. Anesth Analg. 2017; 125(1):347–50.

29. Mentis HM, Chellali A, Manser K, Cao CGL, Schwaitzberg SD. A systematic review of the effect of distraction on surgeon performance: directions for operating room policy and surgical training. SurgEndosc. 2016; 30(5):1713–24. https://doi.org/10.1007/s00464-015-4443-z PMID: 2619426130. Healey AN, Sevdalis N, Vincent CA. Measuring intra-operative interference from distraction and interruption observed in the operating theatre. Ergonomics. 2006; 49(5):589.

31. Savoldelli GL, Thieblemont J, Clergue F, Waeber J-L, Forster A, Garnerin P, et al. Incidence and impactof distracting events during induction of general anaesthesia for urgent surgical cases. Eur J Anaesthesiol. 2010; 27(8):683–9. PMID: 19923992Noise and clinical performance

PLOS ONE | https://doi.org/10.1371/journal.pone.0221860 August 30, 2019 9 / 1032. Folscher L-L, Goldstein LN, Wells M, Rees D. Emergency department noise: mental activation or mental stress? Emerg Med J. 2015; 32(6):468–73 https://doi.org/10.1136/emermed-2014-203735 PMID:25001235

33. Everest FA, Pohlmann Ken C. Master Handbook of Acoustics. 5th ed. 2009. 30 p.

34. St. Pierre Jr. RL, Maguire DJ. The Impact of A-weighting Sound Pressure Level Measurements duringthe Evaluation of Noise Exposure. Noise-Con 2004, Baltimore, Maryland.

35. Irgens-Hansen K, Gundersen H, Sunde E, Baste V, Harris A, Bråtveit M, et al. Noise Exposure and Cognitive Performance: A Study on Personnel on Board Royal Norwegian Navy Vessels. Noise Health.

2015; 17(78):320–27. https://doi.org/10.4103/1463-1741.165057 PMID: 2635637436. Schlittmeier SJ, Feil A, Liebl A, Hellbru¨ck J. The impact of road traffic noise on cognitive performance inattention-based tasks depends on noise level even within moderate-level ranges. Noise Heal. 2015; 17(76):148–57.

37. Jones DM, Smith AP, Broadbent DE. Effects of Moderate Intensity Noise on the Bakan Vigilance Task.

J Appl Psychol. 1979; 64(6):627–34. PMID: 528438

38. Murthy VS, Malhotra SK, Bala I, Raghunathan M. Detrimental effects of noise on anaesthetists. Can JAnaesth. 1995; 42(7):608–11. https://doi.org/10.1007/BF03011878 PMID: 755399739. Hansen CH, Goelzer BIF. Engineering Noise Control. 1996. 245–297 p.

Noise and clinical performance

PLOS ONE | https://doi.org/10.1371/journal.pone.0221860 August 30, 2019 10 / 10

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