Top

Published in:

01-12-2021 | Colorectal Cancer | Research

Prognostic and clinicopathological insights of phosphodiesterase 9A gene as novel biomarker in human colorectal cancer

Authors: Tasmina Ferdous Susmi, Atikur Rahman, Md. Moshiur Rahman Khan, Farzana Yasmin, Md. Shariful Islam, Omaima Nasif, Sulaiman Ali Alharbi, Gaber El-Saber Batiha, Mohammad Uzzal Hossain

Published in: BMC Cancer | Issue 1/2021

Abstract

Background

PDE9A (Phosphodiesterase 9A) plays an important role in proliferation of cells, their differentiation and apoptosis via intracellular cGMP (cyclic guanosine monophosphate) signaling. The expression pattern of PDE9A is associated with diverse tumors and carcinomas. Therefore, PDE9A could be a prospective candidate as a therapeutic target in different types of carcinoma. The study presented here was designed to carry out the prognostic value as a biomarker of PDE9A in Colorectal cancer (CRC). The present study integrated several cancer databases with in-silico techniques to evaluate the cancer prognosis of CRC.

Results

The analyses suggested that the expression of PDE9A was significantly down-regulated in CRC tissues than in normal tissues. Moreover, methylation in the DNA promoter region might also manipulate PDE9A gene expression. The Kaplan–Meier curves indicated that high level of expression of PDE9A gene was associated to higher survival in OS, RFS, and DSS in CRC patients. PDE9A demonstrated the highest positive correlation for rectal cancer recurrence with a marker gene CEACAM7. Furtheremore, PDE9A shared consolidated pathways with MAPK14 to induce survival autophagy in CRC cells and showed interaction with GUCY1A2 to drive CRPC.

Conclusions

Overall, the prognostic value of PDE9A gene could be used as a potential tumor biomarker for CRC.

Available only for authorised users

Rivu SF, Apu MNH, Shabnaz S, Nahid NA, Islam MR, al-Mamun MMA, et al. Association of TP53 codon 72 and CDH1 genetic polymorphisms with colorectal cancer risk in Bangladeshi population. Cancer Epidemiol. 2017;49:46–52. https://doi.org/10.1016/j.canep.2017.05.005.CrossRefPubMed

The, I., T.P.-C.A. of Whole, and G. Consortium. Pan-cancer analysis of whole genomes. Nature. 2020;578(7793):82.CrossRef

Raza AM, Kamal M, Begum F, Yusuf MA, Mohammad D, Begum M, et al. Clinico-demographic characteristics of colorectal carcinoma in Bangladeshi patients. J Curr Adv Med Res. 2016;3(1):22–5. https://doi.org/10.3329/jcamr.v3i1.29388.CrossRef

Kobaek-Larsen M, Thorup I, Diederichsen A, Fenger C, Hoitinga MR. Review of colorectal cancer and its metastases in rodent models: comparative aspects with those in humans. Comparative Med. 2000;50(1):16–26.

Hsiao K-Y, Lin YC, Gupta SK, Chang N, Yen L, Sun HS, et al. Noncoding effects of circular RNA CCDC66 promote colon cancer growth and metastasis. Cancer Res. 2017;77(9):2339–50. https://doi.org/10.1158/0008-5472.CAN-16-1883.CrossRefPubMedPubMedCentral

Tauriello DV, et al. TGFβ drives immune evasion in genetically reconstituted colon cancer metastasis. Nature. 2018;554(7693):538–43. https://doi.org/10.1038/nature25492.CrossRefPubMed

O'keefe SJ. Diet, microorganisms and their metabolites, and colon cancer. Nat Rev Gastroenterol Hepatol. 2016;13(12):691–706. https://doi.org/10.1038/nrgastro.2016.165.CrossRefPubMedPubMedCentral

Hussain SA, Sullivan R. Cancer control in Bangladesh. Jpn J Clin Oncol. 2013;43(12):1159–69. https://doi.org/10.1093/jjco/hyt140.CrossRefPubMedPubMedCentral

Rahman M, et al. Identification of prognostic biomarker signatures and candidate drugs in colorectal cancer: insights from systems biology analysis. Medicina. 2019;55(1):20. https://doi.org/10.3390/medicina55010020.CrossRefPubMedCentral

10.

Haggar FA, Boushey RP. Colorectal cancer epidemiology: incidence, mortality, survival, and risk factors. Clin Colon Rectal Surg. 2009;22(4):191–7. https://doi.org/10.1055/s-0029-1242458.CrossRefPubMedPubMedCentral

11.

Doubeni CA, Corley DA, Quinn VP, Jensen CD, Zauber AG, Goodman M, et al. Effectiveness of screening colonoscopy in reducing the risk of death from right and left colon cancer: a large community-based study. Gut. 2018;67(2):291–8. https://doi.org/10.1136/gutjnl-2016-312712.CrossRefPubMed

12.

Wong JJL, Hawkins NJ, Ward RL. Colorectal cancer: a model for epigenetic tumorigenesis. Gut. 2007;56(1):140–8. https://doi.org/10.1136/gut.2005.088799.CrossRefPubMed

13.

Xu X-L, Yu J, Zhang HY, Sun MH, Gu J, du X, et al. Methylation profile of the promoter CpG islands of 31 genes that may contribute to colorectal carcinogenesis. World J Gastroenterol: WJG. 2004;10(23):3441–54. https://doi.org/10.3748/wjg.v10.i23.3441.CrossRefPubMedPubMedCentral

14.

Levin B, Lieberman DA, McFarland B, Andrews KS, Brooks D, Bond J, et al. Screening and surveillance for the early detection of colorectal cancer and adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US multi-society task force on colorectal Cancer, and the American College of Radiology. Gastroenterology. 2008;134(5):1570–95. https://doi.org/10.1053/j.gastro.2008.02.002.CrossRefPubMed

15.

Świderska M, et al. The diagnostics of colorectal cancer. Contemp Oncol. 2014;18(1):1–6. https://doi.org/10.5114/wo.2013.39995.CrossRef

16.

Ng JM-K, Yu J. Promoter hypermethylation of tumour suppressor genes as potential biomarkers in colorectal cancer. Int J Mol Sci. 2015;16(2):2472–96. https://doi.org/10.3390/ijms16022472.CrossRefPubMedPubMedCentral

17.

Das V, Kalita J, Pal M. Predictive and prognostic biomarkers in colorectal cancer: a systematic review of recent advances and challenges. Biomed Pharmacother. 2017;87:8–19. https://doi.org/10.1016/j.biopha.2016.12.064.CrossRefPubMed

18.

Azevedo MF, Faucz FR, Bimpaki E, Horvath A, Levy I, de Alexandre RB, et al. Clinical and molecular genetics of the phosphodiesterases (PDEs). Endocr Rev. 2014;35(2):195–233. https://doi.org/10.1210/er.2013-1053.CrossRefPubMed

19.

Guipponi M, Scott HS, Kudoh J, Kawasaki K, Shibuya K, Shintani A, et al. Identification and characterization of a novel cyclic nucleotide phosphodiesterase gene (PDE9A) that maps to 21q22. 3: alternative splicing of mRNA transcripts, genomic structure and sequence. Hum Genet. 1998;103(4):386–92. https://doi.org/10.1007/s004390050838.CrossRefPubMed

20.

Lee DI, Zhu G, Sasaki T, Cho GS, Hamdani N, Holewinski R, et al. Phosphodiesterase 9A controls nitric-oxide-independent cGMP and hypertrophic heart disease. Nature. 2015;519(7544):472–6. https://doi.org/10.1038/nature14332.CrossRefPubMedPubMedCentral

21.

Singh N, Patra S. Phosphodiesterase 9: insights from protein structure and role in therapeutics. Life Sci. 2014;106(1–2):1–11. https://doi.org/10.1016/j.lfs.2014.04.007.CrossRefPubMed

22.

Dorner-Ciossek C, Kroker K, Rosenbrock H. Role of PDE9 in Cognition. In: Phosphodiesterases: CNS Functions and Diseases: Springer; 2017. p. 231–54.CrossRef

23.

Savai R, Pullamsetti SS, Banat GA, Weissmann N, Ghofrani HA, Grimminger F, et al. Targeting cancer with phosphodiesterase inhibitors. Expert Opin Investig Drugs. 2010;19(1):117–31. https://doi.org/10.1517/13543780903485642.CrossRefPubMed

24.

Pinto EM, Faucz FR, Paza LZ, Wu G, Fernandes ES, Bertherat J, et al. Germline variants in Phosphodiesterase genes and genetic predisposition to pediatric adrenocortical tumors. Cancers. 2020;12(2):506. https://doi.org/10.3390/cancers12020506.CrossRefPubMedCentral

25.

Szarek E, Stratakis C. Phosphodiesterases and adrenal Cushing in mice and humans. Hormone Metab Res. 2014;46(12):863.CrossRef

26.

Goldhoff P, Warrington NM, Limbrick DD Jr, Hope A, Woerner BM, Jackson E, et al. Targeted inhibition of cyclic AMP phosphodiesterase-4 promotes brain tumor regression. Clin Cancer Res. 2008;14(23):7717–25. https://doi.org/10.1158/1078-0432.CCR-08-0827.CrossRefPubMedPubMedCentral

27.

Cesarini V, Martini M, Vitiani LR, Gravina GL, di Agostino S, Graziani G, et al. Type 5 phosphodiesterase regulates glioblastoma multiforme aggressiveness and clinical outcome. Oncotarget. 2017;8(8):13223–39. https://doi.org/10.18632/oncotarget.14656.CrossRefPubMedPubMedCentral

28.

Zhang L, Murray F, Zahno A, Kanter JR, Chou D, Suda R, et al. Cyclic nucleotide phosphodiesterase profiling reveals increased expression of phosphodiesterase 7B in chronic lymphocytic leukemia. Proc Natl Acad Sci. 2008;105(49):19532–7. https://doi.org/10.1073/pnas.0806152105.CrossRefPubMedPubMedCentral

29.

Soderling SH, Bayuga SJ, Beavo JA. Identification and characterization of a novel family of cyclic nucleotide phosphodiesterases. J Biol Chem. 1998;273(25):15553–8.CrossRefPubMed

30.

Wang Q, Li W, Liu XS, Carroll JS, Jänne OA, Keeton EK, et al. A hierarchical network of transcription factors governs androgen receptor-dependent prostate cancer growth. Mol Cell. 2007;27(3):380–92. https://doi.org/10.1016/j.molcel.2007.05.041.CrossRefPubMedPubMedCentral

31.

Sato T, Arai E, Kohno T, Tsuta K, Watanabe SI, Soejima K, et al. DNA methylation profiles at precancerous stages associated with recurrence of lung adenocarcinoma. PLoS One. 2013;8(3):e59444. https://doi.org/10.1371/journal.pone.0059444.CrossRefPubMedPubMedCentral

32.

Krishnan MS, Racsa M, Yu H-HM. Handbook of Supportive and Palliative Radiation Oncology: Academic Press; 2016.

33.

Chen F, et al. Pan-cancer molecular subtypes revealed by mass-spectrometry-based proteomic characterization of more than 500 human cancers. Nat Commun. 2019;10(1):1–15.CrossRef

34.

Hou G-X, Liu P, Yang J, Wen S. Mining expression and prognosis of topoisomerase isoforms in non-small-cell lung cancer by using Oncomine and Kaplan–Meier plotter. PLoS One. 2017;12(3):e0174515. https://doi.org/10.1371/journal.pone.0174515.CrossRefPubMedPubMedCentral

35.

Yan P, He Y, Xie K, Kong S, Zhao W. In silico analyses for potential key genes associated with gastric cancer. PeerJ. 2018;6:e6092. https://doi.org/10.7717/peerj.6092.CrossRefPubMedPubMedCentral

36.

Rhodes DR, et al. ONCOMINE: a cancer microarray database and integrated data-mining platform. Neoplasia (New York, NY). 2004;6(1):1.CrossRef

37.

Rhodes DR, et al. Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia (New York, NY). 2007;9(2):166.CrossRef

38.

Wu Y, Xu Y. Integrated bioinformatics analysis of expression and gene regulation network of COL12A1 in colorectal cancer. Cancer Med. 2020.

39.

Chandrashekar DS, Bashel B, Balasubramanya SAH, Creighton CJ, Ponce-Rodriguez I, Chakravarthi BVSK, et al. UALCAN: a portal for facilitating tumor subgroup gene expression and survival analyses. Neoplasia. 2017;19(8):649–58. https://doi.org/10.1016/j.neo.2017.05.002.CrossRefPubMedPubMedCentral

40.

Zheng H, Zhang G, Zhang L, Wang Q, Li H, Han Y, et al. Comprehensive review of web servers and bioinformatics tools for cancer prognosis analysis. Front Oncol. 2020;10:68. https://doi.org/10.3389/fonc.2020.00068.CrossRefPubMedPubMedCentral

41.

Anaya J. OncoLnc: linking TCGA survival data to mRNAs, miRNAs, and lncRNAs. PeerJ Comput Sci. 2016;2:e67. https://doi.org/10.7717/peerj-cs.67.CrossRef

42.

Mizuno H, Kitada K, Nakai K, Sarai A. PrognoScan: a new database for meta-analysis of the prognostic value of genes. BMC Med Genet. 2009;2(1):18. https://doi.org/10.1186/1755-8794-2-18.CrossRef

43.

Park S-J, Yoon BH, Kim SK, Kim SY. GENT2: an updated gene expression database for normal and tumor tissues. BMC Med Genet. 2019;12(5):101. https://doi.org/10.1186/s12920-019-0514-7.CrossRef

44.

Ouyang S, Liu J‑H, Ni Z, Ding G‑F, Wang Q‑Z. Downregulation of ST3GAL5 is associated with muscle invasion, high grade and a poor prognosis in patients with bladder cancer. Oncol Lett. 2020;20(1):828–40. https://doi.org/10.3892/ol.2020.11597.CrossRefPubMedPubMedCentral

45.

Goldman Mary J, et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nature biotechnology. 2020;38(6):675–8.

46.

Cui X, Yi Q, Jing X, Huang Y, Tian J, Long C, et al. Mining prognostic significance of MEG3 in human breast cancer using bioinformatics analysis. Cell Physiol Biochem. 2018;50(1):41–51. https://doi.org/10.1159/000493956.CrossRefPubMed

47.

Cerami Ethan, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. 2012:401–404.

48.

Gao J, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6(269):pl1.CrossRefPubMedPubMedCentral

49.

Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017;45(W1):W98–W102. https://doi.org/10.1093/nar/gkx247.CrossRefPubMedPubMedCentral

50.

Xue C, Zhang J, Zhang G, Xue Y, Zhang G, Wu X. Elevated SPINK2 gene expression is a predictor of poor prognosis in acute myeloid leukemia. Oncol Lett. 2019;18(3):2877–84. https://doi.org/10.3892/ol.2019.10665.CrossRefPubMedPubMedCentral

51.

Safran M, Dalah I, Alexander J, Rosen N, Iny Stein T, Shmoish M, et al. GeneCards version 3: the human gene integrator. Database. 2010;2010(0). https://doi.org/10.1093/database/baq020.

52.

Stelzer G, et al. The GeneCards suite: from gene data mining to disease genome sequence analyses. Curr Protocols Bioinform. 2016;54(1):1.30 1–1.30. 33.CrossRef

53.

Warde-Farley D, et al. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010;38(suppl_2):W214–20.CrossRefPubMedPubMedCentral

54.

Szklarczyk Damian, et al. The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic acids research. 2016: gkw937.

55.

Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607–13. https://doi.org/10.1093/nar/gky1131.CrossRefPubMed

56.

De Las Rivas J, Fontanillo C. Protein–protein interactions essentials: key concepts to building and analyzing interactome networks. PLoS Comput Biol. 2010;6(6):e1000807.CrossRefPubMedPubMedCentral

57.

Paillas S, Causse A, Marzi L, de Medina P, Poirot M, Denis V, et al. MAPK14/p38α confers irinotecan resistance to TP53-defective cells by inducing survival autophagy. Autophagy. 2012;8(7):1098–112. https://doi.org/10.4161/auto.20268.CrossRefPubMedPubMedCentral

58.

Loweth AC, Williams GT, Scarpello JHB, Morgan NG. Evidence for the involvement of cGMP and protein kinase G in nitric oxide-induced apoptosis in the pancreatic B-cell line, HIT-T15. FEBS Lett. 1997;400(3):285–8. https://doi.org/10.1016/S0014-5793(96)01392-0.CrossRefPubMed

59.

Shimojo T, Hiroe M, Ishiyama S, Ito H, Nishikawa T, Marumo F. Nitric oxide induces apoptotic death of cardiomyocytes via a cyclic-GMP-dependent pathway. Exp Cell Res. 1999;247(1):38–47. https://doi.org/10.1006/excr.1998.4310.CrossRefPubMed

60.

Eigenthaler M, et al. Signal transduction by cGMP-dependent protein kinases and their emerging roles in the regulation of cell adhesion and gene expression. Rev Physiol Biochem Pharmacol. 1999;135:173–209.CrossRefPubMed

61.

Smolenski A, Burkhardt AM, Eigenthaler M, Butt E, Gambaryan S, Lohmann SM, et al. Functional analysis of cGMP-dependent protein kinases I and II as mediators of NO/cGMP effects. Naunyn Schmiedeberg's Arch Pharmacol. 1998;358(1):134–9. https://doi.org/10.1007/PL00005234.CrossRef

62.

Vaandrager AB, de Jonge HR. Signalling by cGMP-dependent protein kinases. Mol Cell Biochem. 1996;157(1–2):23–30. https://doi.org/10.1007/BF00227877.CrossRefPubMed

63.

Saravani R, Karami-Tehrani F, Hashemi M, Aghaei M, Edalat R. Inhibition of phosphodiestrase 9 induces c GMP accumulation and apoptosis in human breast cancer cell lines, MCF-7 and MDA-MB-468. Cell Prolif. 2012;45(3):199–206. https://doi.org/10.1111/j.1365-2184.2012.00819.x.CrossRefPubMedPubMedCentral

64.

Fajardo AM, Piazza GA, Tinsley HN. The role of cyclic nucleotide signaling pathways in cancer: targets for prevention and treatment. Cancers. 2014;6(1):436–58. https://doi.org/10.3390/cancers6010436.CrossRefPubMedPubMedCentral

65.

Andreeva SG, Dikkes P, Epstein PM, Rosenberg PA. Expression of cGMP-specific phosphodiesterase 9A mRNA in the rat brain. J Neurosci. 2001;21(22):9068–76. https://doi.org/10.1523/JNEUROSCI.21-22-09068.2001.CrossRefPubMedPubMedCentral

66.

Razmkhah F, Ghasemi S, Soleimani M, Amini Kafi-abad S. LY86, LRG1 and PDE9A genes overexpression in umbilical cord blood hematopoietic stem progenitor cells by acute myeloid leukemia (M3) microvesicles. Exp Hematol Oncol. 2019;8(1):23. https://doi.org/10.1186/s40164-019-0147-8.CrossRefPubMedPubMedCentral

67.

Shen L, Kantarjian H, Guo Y, Lin E, Shan J, Huang X, et al. DNA methylation predicts survival and response to therapy in patients with myelodysplastic syndromes. J Clin Oncol. 2010;28(4):605–13. https://doi.org/10.1200/JCO.2009.23.4781.CrossRefPubMed

68.

Rauluseviciute I, Drabløs F, Rye MB. DNA hypermethylation associated with upregulated gene expression in prostate cancer demonstrates the diversity of epigenetic regulation. BMC Med Genet. 2020;13(1):6. https://doi.org/10.1186/s12920-020-0657-6.CrossRef

69.

Li D, Bai Y, Feng Z, Li W, Yang C, Guo Y, et al. Study of promoter methylation patterns of HOXA2, HOXA5, and HOXA6 and its clinicopathological characteristics in colorectal cancer. Front Oncol. 2019;9:394. https://doi.org/10.3389/fonc.2019.00394.CrossRefPubMedPubMedCentral

70.

Kerachian MA, et al. Crosstalk between DNA methylation and gene expression in colorectal cancer, a potential plasma biomarker for tracing this tumor. Sci Rep. 2020;10(1):1–13.CrossRef

71.

Freitas M, Ferreira F, Carvalho S, Silva F, Lopes P, Antunes L, et al. A novel DNA methylation panel accurately detects colorectal cancer independently of molecular pathway. J Transl Med. 2018;16(1):45. https://doi.org/10.1186/s12967-018-1415-9.CrossRefPubMedPubMedCentral

72.

Idos GE, et al. The prognostic implications of tumor infiltrating lymphocytes in colorectal Cancer: a systematic review and meta-analysis. Sci Rep. 2020;10(1):1–14.CrossRef

73.

Bian Q, Chen J, Qiu W, Peng C, Song M, Sun X, et al. Four targeted genes for predicting the prognosis of colorectal cancer: a bioinformatics analysis case. Oncol Lett. 2019;18(5):5043–54. https://doi.org/10.3892/ol.2019.10866.CrossRefPubMedPubMedCentral

74.

Yu Y, Carey M, Pollett W, Green J, Dicks E, Parfrey P, et al. The long-term survival characteristics of a cohort of colorectal cancer patients and baseline variables associated with survival outcomes with or without time-varying effects. BMC Med. 2019;17(1):150. https://doi.org/10.1186/s12916-019-1379-5.CrossRefPubMedPubMedCentral

75.

Hassan MRA, et al. Survival analysis and prognostic factors for colorectal cancer patients in Malaysia. Asian Pac J Cancer Prev. 2016;17(7):3575–81.PubMed

76.

Franz M, Rodriguez H, Lopes C, Zuberi K, Montojo J, Bader GD, et al. GeneMANIA update 2018. Nucleic Acids Res. 2018;46(W1):W60–4. https://doi.org/10.1093/nar/gky311.CrossRefPubMedPubMedCentral

77.

Yi JM, Dhir M, van Neste L, Downing SR, Jeschke J, Glöckner SC, et al. Genomic and epigenomic integration identifies a prognostic signature in colon cancer. Clin Cancer Res. 2011;17(6):1535–45. https://doi.org/10.1158/1078-0432.CCR-10-2509.CrossRefPubMedPubMedCentral

78.

Rotimi S, et al. Gene expression profiling analysis reveals putative Phytochemotherapeutic target for castration-resistant prostate Cancer. Front Oncol. 2019;9:714. https://doi.org/10.3389/fonc.2019.00714.CrossRefPubMedPubMedCentral

79.

Thompson J, Seitz M, Chastre E, Ditter M, Aldrian C, Gespach C, et al. Down-regulation of carcinoembryonic antigen family member 2 expression is an early event in colorectal tumorigenesis. Cancer Res. 1997;57(9):1776–84.PubMed

80.

Thompson J, et al. CGM2, a member of the carcinoembryonic antigen gene family is down-regulated in colorectal carcinomas. J Biol Chem. 1994;269(52):32924–31.CrossRefPubMed

81.

Gemei M, et al. Carcinoembryonic antigen family cell adhesion molecules (CEACAM) as colorectal cancer biomarkers. In: Biomarkers in Disease: Methods, Discoveries and Applications: Biomarkers in Cancer: Springer Netherlands; 2015. p. 685–705.

82.

Messick CA, Sanchez J, DeJulius KL, Hammel J, Ishwaran H, Kalady MF. CEACAM-7: a predictive marker for rectal cancer recurrence. Surgery. 2010;147(5):713–9. https://doi.org/10.1016/j.surg.2009.10.056.CrossRefPubMed

83.

Song W, et al. Rhomboid domain containing 1 promotes colorectal cancer growth through activation of the EGFR signalling pathway Nat. Commun. 2015;6(1):1–13.

84.

Feng Hailiang, et al. ALDH1A3 affects colon cancer in vitro proliferation and invasion depending on CXCR4 status. British journal of cancer. 2018;118(2):224–32.

85.

Sun HD, et al. Down-regulation of circPVRL3 promotes the proliferation and migration of gastric cancer cells. Sci. Rep. 2018;8(1):1–13.

Title: Prognostic and clinicopathological insights of phosphodiesterase 9A gene as novel biomarker in human colorectal cancer
Authors: Tasmina Ferdous Susmi
Atikur Rahman
Md. Moshiur Rahman Khan
Farzana Yasmin
Md. Shariful Islam
Omaima Nasif
Sulaiman Ali Alharbi
Gaber El-Saber Batiha
Mohammad Uzzal Hossain
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Colorectal Cancer
Colorectal Cancer
Biomarkers
Colon Cancer
Colon Cancer
Published in: BMC Cancer / Issue 1/2021
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-021-08332-3

Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras

Prof. Fabrice Barlesi

Developed by: Springer Medicine

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 1/2021

Multizonal anogenital neoplasia in women: a cohort analysis

Preferences of first-degree relatives of gastric cancer patients for gastric cancer screening: a discrete choice experiment

Forecasting lung cancer incidence, mortality, and prevalence to year 2030

MiR-105-3p acts as an oncogene to promote the proliferation and metastasis of breast cancer cells by targeting GOLIM4

COXIBs and 2,5-dimethylcelecoxib counteract the hyperactivated Wnt/β-catenin pathway and COX-2/PGE2/EP4 signaling in glioblastoma cells

Primary effusion lymphoma occurring in the setting of transplanted patients: a systematic review of a rare, life-threatening post-transplantation occurrence

Keynote webinar | Spotlight on antibody–drug conjugates in cancer