Top

Journal of Translational Medicine

Published in:

Open Access 01-12-2024 | Ovarian Cancer | Research

Cancer-associated fibroblast-secreted FGF7 as an ovarian cancer progression promoter

Authors: Songwei Feng, Bo Ding, Zhu Dai, Han Yin, Yue Ding, Sicong Liu, Ke Zhang, Hao Lin, Zhongdang Xiao, Yang Shen

Published in: Journal of Translational Medicine | Issue 1/2024

Abstract

Background

Ovarian cancer (OC) is distinguished by its aggressive nature and the limited efficacy of current treatment strategies. Recent studies have emphasized the significant role of cancer-associated fibroblasts (CAFs) in OC development and progression.

Methods

Employing sophisticated machine learning techniques on bulk transcriptomic datasets, we identified fibroblast growth factor 7 (FGF7), derived from CAFs, as a potential oncogenic factor. We investigated the relationship between FGF7 expression and various clinical parameters. A series of in vitro experiments were undertaken to evaluate the effect of CAFs-derived FGF7 on OC cell activities, such as proliferation, migration, and invasion. Single-cell transcriptomic analysis was also conducted to elucidate the interaction between FGF7 and its receptor. Detailed mechanistic investigations sought to clarify the pathways through which FGF7 fosters OC progression.

Results

Our findings indicate that higher FGF7 levels correlate with advanced tumor stages, increased vascular invasion, and poorer prognosis. CAFs-derived FGF7 significantly enhanced OC cell proliferation, migration, and invasion. Single-cell analysis and in vitro studies revealed that CAFs-derived FGF7 inhibits the ubiquitination and degradation of hypoxia-inducible factor 1 alpha (HIF-1α) via FGFR2 interaction. Activation of the FGF7/HIF-1α pathway resulted in the upregulation of mesenchymal markers and downregulation of epithelial markers. Importantly, in vivo treatment with neutralizing antibodies targeting CAFs-derived FGF7 substantially reduced tumor growth.

Conclusion

Neutralizing FGF7 in the medium or inhibiting HIF-1α signaling reversed the effects of FGF7-mediated EMT, emphasizing the dependence of FGF7-mediated EMT on HIF-1α activation. These findings suggest that targeting the FGF7/HIF-1α/EMT axis may offer new therapeutic opportunities to intervene in OC progression.

Available only for authorised users

Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(2018):394–424.PubMedCrossRef

Zhang M, Chen Z, Wang Y, Zhao H, Du Y. The role of cancer-associated fibroblasts in ovarian cancer. Cancers (Basel). 2022. https://doi.org/10.3390/cancers14112637.CrossRefPubMedPubMedCentral

Feng S, Xu Y, Dai Z, Yin H, Zhang K, Shen Y. Integrative analysis from multicenter studies identifies a WGCNA-derived cancer-associated fibroblast signature for ovarian cancer. Front Immunol. 2022;13: 951582.PubMedPubMedCentralCrossRef

Wang Y, Chen Z, Zhao G, Li Q. Cancer-associated fibroblast risk model for prediction of colorectal carcinoma prognosis and therapeutic responses. Mediators Inflamm. 2023;2023:3781091.PubMedPubMedCentralCrossRef

Wang S, Fan G, Li L, He Y, Lou N, Xie T, Dai L, Gao R, Yang M, Shi Y, Han X. Integrative analyses of bulk and single-cell RNA-seq identified cancer-associated fibroblasts-related signature as a prognostic factor for immunotherapy in NSCLC. Cancer Immunol Immunother. 2023;72:2423–42.PubMedCrossRef

Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10:57–63.PubMedPubMedCentralCrossRef

Galbo PM Jr, Zang X, Zheng D. Molecular features of cancer-associated fibroblast subtypes and their implication on cancer pathogenesis, prognosis, and immunotherapy resistance. Clin Cancer Res. 2021;27:2636–47.PubMedPubMedCentralCrossRef

Hegab AE, Ozaki M, Kameyama N, Gao J, Kagawa S, Yasuda H, Soejima K, Yin Y, Guzy RD, Nakamura Y, Ornitz DM, Betsuyaku T. Effect of FGF/FGFR pathway blocking on lung adenocarcinoma and its cancer-associated fibroblasts. J Pathol. 2019;249:193–205.PubMedCrossRef

Eckert MA, Coscia F, Chryplewicz A, Chang JW, Hernandez KM, Pan S, Tienda SM, Nahotko DA, Li G, Blazenovic I, Lastra RR, Curtis M, Yamada SD, Perets R, McGregor SM, Andrade J, Fiehn O, Moellering RE, Mann M, Lengyel E. Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts. Nature. 2019;569:723–8.PubMedPubMedCentralCrossRefADS

10.

Flavell RA, Sanjabi S, Wrzesinski SH, Licona-Limon P. The polarization of immune cells in the tumour environment by TGFbeta. Nat Rev Immunol. 2010;10:554–67.PubMedCrossRef

11.

Ko SY, Barengo N, Ladanyi A, Lee JS, Marini F, Lengyel E, Naora H. HOXA9 promotes ovarian cancer growth by stimulating cancer-associated fibroblasts. J Clin Invest. 2012;122:3603–17.PubMedPubMedCentralCrossRef

12.

Deying W, Feng G, Shumei L, Hui Z, Ming L, Hongqing W. CAF-derived HGF promotes cell proliferation and drug resistance by up-regulating the c-Met/PI3K/Akt and GRP78 signalling in ovarian cancer cells. 2017. Biosci Rep. https://doi.org/10.1042/BSR20160470.

13.

Gao Q, Yang Z, Xu S, Li X, Yang X, Jin P, Liu Y, Zhou X, Zhang T, Gong C, Wei X, Liu D, Sun C, Chen G, Hu J, Meng L, Zhou J, Sawada K, Fruscio R, Grunt TW, Wischhusen J, Vargas-Hernandez VM, Pothuri B, Coleman RL. Heterotypic CAF-tumor spheroids promote early peritoneal metastatis of ovarian cancer. J Exp Med. 2019;216:688–703.PubMedPubMedCentralCrossRef

14.

Zhang R, Qi F, Zhao F, Li G, Shao S, Zhang X, Yuan L, Feng Y. Cancer-associated fibroblasts enhance tumor-associated macrophages enrichment and suppress NK cells function in colorectal cancer. Cell Death Dis. 2019;10:273.PubMedPubMedCentralCrossRef

15.

Zhang J, Wong CC, Leung KT, Wu F, Zhou Y, Tong JHM, Chan RCK, Li H, Wang Y, Yan H, Liu L, Wu WKK, Chan MWY, Cheng ASL, Yu J, Wong N, Lo KW, To KF, Kang W. FGF18-FGFR2 signaling triggers the activation of c-Jun-YAP1 axis to promote carcinogenesis in a subgroup of gastric cancer patients and indicates translational potential. Oncogene. 2020;39:6647–63.PubMedPubMedCentralCrossRef

16.

Hua Y, Yin H, Liu X, Xie J, Zhan W, Liang G, Shen Y. Salt-inducible kinase 2-triggered release of its inhibitor from hydrogel to suppress ovarian cancer metastasis. Adv Sci (Weinh). 2022;9: e2202260.PubMedCrossRef

17.

Lu Y, Chen Y, Hu W, Wang M, Wen X, Yang J. Inhibition of ACSS2 attenuates alcoholic liver steatosis via epigenetically regulating de novo lipogenesis. Liver Int. 2023;43:1729–40.PubMedCrossRef

18.

Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Holko M, Yefanov A, Lee H, Zhang N, Robertson CL, Serova N, Davis S, Soboleva A. NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Res. 2013;41:D991–5.PubMedCrossRef

19.

Xu J, Fang Y, Chen K, Li S, Tang S, Ren Y, Cen Y, Fei W, Zhang B, Shen Y, Lu W. Single-cell RNA sequencing reveals the tissue architecture in human high-grade serous ovarian cancer. Clin Cancer Res. 2022;28:3590–602.PubMedPubMedCentralCrossRef

20.

Korsunsky I, Millard N, Fan J, Slowikowski K, Zhang F, Wei K, Baglaenko Y, Brenner M, Loh PR, Raychaudhuri S. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat Methods. 2019;16:1289–96.PubMedPubMedCentralCrossRef

21.

Jin S, Guerrero-Juarez CF, Zhang L, Chang I, Ramos R, Kuan CH, Myung P, Plikus MV, Nie Q. Inference and analysis of cell-cell communication using cell chat. Nat Commun. 2021;12:1088.PubMedPubMedCentralCrossRefADS

22.

Wang Z, Jensen MA, Zenklusen JC. A practical guide to The Cancer Genome Atlas (TCGA). Methods Mol Biol. 2016;1418:111–41.PubMedCrossRef

23.

Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. 2012;28:882–3.PubMedPubMedCentralCrossRef

24.

Zeng D, Ye Z, Shen R, Yu G, Wu J, Xiong Y, Zhou R, Qiu W, Huang N, Sun L, Li X, Bin J, Liao Y, Shi M, Liao W. IOBR: multi-omics immuno-oncology biological research to decode tumor microenvironment and signatures. Front Immunol. 2021;12: 687975.PubMedPubMedCentralCrossRef

25.

Zhao W, Langfelder P, Fuller T, Dong J, Li A, Hovarth S. Weighted gene coexpression network analysis: state of the art. J Biopharm Stat. 2010;20:281–300.MathSciNetPubMedCrossRef

26.

Hu JY, Wang Y, Tong XM, Yang T. When to consider logistic LASSO regression in multivariate analysis? Eur J Surg Oncol. 2021;47:2206.PubMedCrossRef

27.

Binder H, Allignol A, Schumacher M, Beyersmann J. Boosting for high-dimensional time-to-event data with competing risks. Bioinformatics. 2009;25:890–6.PubMedCrossRef

28.

Rigatti SJ. Random forest. J Insur Med. 2017;47:31–9.PubMedCrossRef

29.

Zhou J, Lee S, Liu Y, Chan JSK, Li G, Wong WT, Jeevaratnam K, Cheng SH, Liu T, Tse G, Zhang Q. Predicting stroke and mortality in mitral regurgitation: a machine learning approach. Curr Probl Cardiol. 2023;48: 101464.PubMedCrossRef

30.

Van Belle V, Pelckmans K, Van Huffel S, Suykens JA. Improved performance on high-dimensional survival data by application of survival-SVM. Bioinformatics. 2011;27:87–94.PubMedCrossRef

31.

Lee D, Lee W, Lee Y, Pawitan Y. Super-sparse principal component analyses for high-throughput genomic data. BMC Bioinformatics. 2010;11:296.PubMedPubMedCentralCrossRef

32.

Arashi M, Roozbeh M, Hamzah NA, Gasparini M. Ridge regression and its applications in genetic studies. PLoS ONE. 2021;16: e0245376.PubMedPubMedCentralCrossRef

33.

Nygard S, Borgan O, Lingjaerde OC, Storvold HL. Partial least squares Cox regression for genome-wide data. Lifetime Data Anal. 2008;14:179–95.MathSciNetPubMedCrossRef

34.

Vidyasagar M. Machine learning methods in the computational biology of cancer. Proc Math Phys Eng Sci. 2014;470:20140081.MathSciNetPubMedPubMedCentral

35.

Liu Z, Liu L, Weng S, Guo C, Dang Q, Xu H, Wang L, Lu T, Zhang Y, Sun Z, Han X. Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer. Nat Commun. 2022;13:816.PubMedPubMedCentralCrossRefADS

36.

Li Y, Niu JH, Wang Y. Machine learning-based neddylation landscape indicates different prognosis and immune microenvironment in endometrial cancer. Front Oncol. 2023;13:1084523.PubMedPubMedCentralCrossRef

37.

Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28:27–30.PubMedPubMedCentralCrossRef

38.

Hanzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinform. 2013;14:7.CrossRef

39.

Sakaguchi S, Yamaguchi T, Nomura T, Ono M. Regulatory T cells and immune tolerance. Cell. 2008;133:775–87.PubMedCrossRef

40.

Chen Z, Han F, Du Y, Shi H, Zhou W. Hypoxic microenvironment in cancer: molecular mechanisms and therapeutic interventions. Signal Transduct Target Ther. 2023;8:70.PubMedPubMedCentralCrossRef

41.

Najafi M, Farhood B, Mortezaee K. Extracellular matrix (ECM) stiffness and degradation as cancer drivers. J Cell Biochem. 2019;120:2782–90.PubMedCrossRef

42.

Rashid M, Zadeh LR, Baradaran B, Molavi O, Ghesmati Z, Sabzichi M, Ramezani F. Up-down regulation of HIF-1alpha in cancer progression. Gene. 2021;798: 145796.PubMedCrossRef

43.

Zhu J, Huang Z, Zhang M, Wang W, Liang H, Zeng J, Wu K, Wang X, Hsieh JT, Guo P, Fan J. Erratum: HIF-1alpha promotes ZEB1 expression and EMT in a human bladder cancer lung metastasis animal model. Oncol Lett. 2021;22:599.PubMedPubMedCentralCrossRef

44.

Zhang W, Shi X, Peng Y, Wu M, Zhang P, Xie R, Wu Y, Yan Q, Liu S, Wang J. HIF-1alpha promotes epithelial-mesenchymal transition and metastasis through direct regulation of ZEB1 in colorectal cancer. PLoS ONE. 2015;10: e0129603.PubMedPubMedCentralCrossRef

45.

Yoshimoto S, Tanaka F, Morita H, Hiraki A, Hashimoto S. Hypoxia-induced HIF-1alpha and ZEB1 are critical for the malignant transformation of ameloblastoma via TGF-beta-dependent EMT. Cancer Med. 2019;8:7822–32.PubMedPubMedCentralCrossRef

46.

Reel PS, Reel S, Pearson E, Trucco E, Jefferson E. Using machine learning approaches for multi-omics data analysis: a review. Biotechnol Adv. 2021;49: 107739.PubMedCrossRef

47.

Picard M, Scott-Boyer MP, Bodein A, Perin O, Droit A. Integration strategies of multi-omics data for machine learning analysis. Comput Struct Biotechnol J. 2021;19:3735–46.PubMedPubMedCentralCrossRef

48.

Cai Z, Poulos RC, Liu J, Zhong Q. Machine learning for multi-omics data integration in cancer. iScience. 2022;25: 103798.PubMedPubMedCentralCrossRefADS

49.

Beenken A, Mohammadi M. The FGF family: biology, pathophysiology and therapy. Nat Rev Drug Discov. 2009;8:235–53.PubMedPubMedCentralCrossRef

50.

Finch PW, Rubin JS, Miki T, Ron D, Aaronson SA. Human KGF is FGF-related with properties of a paracrine effector of epithelial cell growth. Science. 1989;245:752–5.PubMedCrossRefADS

51.

Zinkle A, Mohammadi M. Structural biology of the FGF7 subfamily. Front Genet. 2019;10:102.PubMedPubMedCentralCrossRef

52.

Cui Y, Li Q. Effect of mammogenic hormones on the expression of FGF7, FGF10 and their receptor in mouse mammary gland. Sci China C Life Sci. 2008;51:711–7.PubMedCrossRef

53.

Zheng C, Cotrim AP, Rowzee A, Swaim W, Sowers A, Mitchell JB, Baum BJ. Prevention of radiation-induced salivary hypofunction following hKGF gene delivery to murine submandibular glands. Clin Cancer Res. 2011;17:2842–51.PubMedPubMedCentralCrossRef

54.

Wirth K, Mertelsmann R. Cytoprotective function of keratinocyte growth factor in tumour therapy-induced tissue damage. Br J Haematol. 2002;116:505–10.PubMedCrossRef

55.

Li J, Lu R, Yang K, Sun Q. circCCT3 enhances invasion and epithelial-mesenchymal transition (EMT) of non-small-cell lung cancer (NSCLC) via the miR-107/Wnt/FGF7 axis. J Oncol. 2022;2022:7020774.PubMedPubMedCentral

56.

Fan EW, Li CC, Wu WJ, Huang CN, Li WM, Ke HL, Yeh HC, Wu TF, Liang PI, Ma LJ, Li CF. FGF7 over expression is an independent prognosticator in patients with urothelial carcinoma of the upper urinary tract and bladder. J Urol. 2015;194:223–9.PubMedCrossRef

57.

Zhu Y, Yang L, Chong QY, Yan H, Zhang W, Qian W, Tan S, Wu Z, Lobie PE, Zhu T. Long noncoding RNA Linc00460 promotes breast cancer progression by regulating the miR-489-5p/FGF7/AKT axis. Cancer Manag Res. 2019;11:5983–6001.PubMedPubMedCentralCrossRef

58.

Liu Z, Liu J, Chen T, Wang Y, Shi A, Li K, Li X, Qiu B, Zheng L, Zhao L, Shu L, Lian S, Huang S, Zhang Z, Xu Y. Wnt-TCF7-SOX9 axis promotes cholangiocarcinoma proliferation and pemigatinib resistance in a FGF7-FGFR2 autocrine pathway. Oncogene. 2022;41:2885–96.PubMedCrossRef

59.

Zhang X, Ibrahimi OA, Olsen SK, Umemori H, Mohammadi M, Ornitz DM. Receptor specificity of the fibroblast growth factor family. The complete mammalian FGF family. J Biol Chem. 2006;281:15694–700.PubMedCrossRef

60.

Mason IJ, Fuller-Pace F, Smith R, Dickson C. FGF-7 (keratinocyte growth factor) expression during mouse development suggests roles in myogenesis, forebrain regionalisation and epithelial-mesenchymal interactions. Mech Dev. 1994;45:15–30.PubMedCrossRef

61.

Mieczkowski K, Kitowska K, Braun M, Galikowska-Bogut B, Gorska-Arcisz M, Piasecka D, Stawiski K, Zaczek AJ, Nejc D, Kordek R, Romanska HM, Sadej R. FGF7/FGFR2-JunB signalling counteracts the effect of progesterone in luminal breast cancer. Mol Oncol. 2022;16:2823–42.PubMedPubMedCentralCrossRef

62.

Milton CI, Selfe J, Aladowicz E, Man SYK, Bernauer C, Missiaglia E, Walters ZS, Gatz SA, Kelsey A, Generali M, Box G, Valenti M, de Haven-Brandon A, Galiwango D, Hayes A, Clarke M, Izquierdo E, Gonzalez De Castro D, Raynaud FI, Kirkin V, Shipley JM. FGF7-FGFR2 autocrine signaling increases growth and chemoresistance of fusion-positive rhabdomyosarcomas. Mol Oncol. 2022;16:1272–89.PubMedCrossRef

63.

Jin Y, Bian S, Wang H, Mo J, Fei H, Li L, Chen T, Jiang H. CRMP2 derived from cancer associated fibroblasts facilitates progression of ovarian cancer via HIF-1alpha-glycolysis signaling pathway. Cell Death Dis. 2022;13:675.PubMedPubMedCentralCrossRef

64.

Semenza GL. HIF-1 mediates metabolic responses to intratumoral hypoxia and oncogenic mutations. J Clin Invest. 2013;123:3664–71.PubMedPubMedCentralCrossRef

65.

Dongre A, Weinberg RA. New insights into the mechanisms of epithelial-mesenchymal transition and implications for cancer. Nat Rev Mol Cell Biol. 2019;20:69–84.PubMedCrossRef

66.

Krebs AM, Mitschke J, Lasierra Losada M, Schmalhofer O, Boerries M, Busch H, Boettcher M, Mougiakakos D, Reichardt W, Bronsert P, Brunton VG, Pilarsky C, Winkler TH, Brabletz S, Stemmler MP, Brabletz T. The EMT-activator Zeb1 is a key factor for cell plasticity and promotes metastasis in pancreatic cancer. Nat Cell Biol. 2017;19:518–29.PubMedCrossRef

67.

Mohammadi Ghahhari N, Sznurkowska MK, Hulo N, Bernasconi L, Aceto N, Picard D. Cooperative interaction between ERalpha and the EMT-inducer ZEB1 reprograms breast cancer cells for bone metastasis. Nat Commun. 2022;13:2104.PubMedPubMedCentralCrossRefADS

Title: Cancer-associated fibroblast-secreted FGF7 as an ovarian cancer progression promoter
Authors: Songwei Feng
Bo Ding
Zhu Dai
Han Yin
Yue Ding
Sicong Liu
Ke Zhang
Hao Lin
Zhongdang Xiao
Yang Shen
Publication date: 01-12-2024
Publisher: BioMed Central
Keywords: Ovarian Cancer
Ovarian Cancer
Published in: Journal of Translational Medicine / Issue 1/2024
Electronic ISSN: 1479-5876
DOI: https://doi.org/10.1186/s12967-024-05085-y

Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin

Prof. Florian Limbourg

Prof. Anoop Chauhan

Developed by: Springer Medicine

Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Pediatric Cardiology Video

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

Cardiopulmonary Comorbidity Video

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Valvular Heart Disease Video

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Heart Failure Video

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Heart Failure Video

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.

Watch now

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

16-04-2024 Type 2 Diabetes News

Incentivised to exercise

11-04-2024 Lifestyle Modifications News

New intervention for STEMI-related cardiogenic shock

10-04-2024 Myocardial Infarction News

» View more highlights on the ACC 2024 congress hub page

Image Credits

Illustration of figure on mountain summit/© Orapun / Stock.adobe.com, STEP AAG HeroTeaserCollection image/© Tarek / Generated with AI / Stock.adobe.com, ACC 2024 Pediatric and Congenital Heart Disease: Year in Review/© 2024 American College of Cardiology, ACC 2024 Pulmonary Vascular Disease: Year in Review/© 2024 American College of Cardiology, ACC 2024 Valvular Heart Disease: Year in Review/© 2024 American College of Cardiology, ACC 2024 HF and Cardiomyopathies: Year in Review/© 2024 American College of Cardiology, Woman out walking/© Seventyfour / stock.adobe.com (symbolic image with model), Woman checking smartwatch /© saltdium / stock.adobe.com (symbolic image with model), Cardiac catheterization/© Damian / stock.adobe.com

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 1/2024

Characterizing neuroinflammation and identifying prenatal diagnostic markers for neural tube defects through integrated multi-omics analysis

RBBP7, regulated by SP1, enhances the Warburg effect to facilitate the proliferation of hepatocellular carcinoma cells via PI3K/AKT signaling

Pathogenomics for accurate diagnosis, treatment, prognosis of oncology: a cutting edge overview

Integrated lipid metabolomics and proteomics analysis reveal the pathogenesis of polycystic ovary syndrome

Fatigue and symptom-based clusters in post COVID-19 patients: a multicentre, prospective, observational cohort study

Single-nucleus transcriptomic analysis reveals the relationship between gene expression in oligodendrocyte lineage and major depressive disorder

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

Highlights from the ACC 2024 Congress

ACC 2024 Congress Coverage