• P-ISSN 0973-7200 E-ISSN 2454-8405
  • Follow us

Journal of Pharmaceutical Research

Article

Journal of Pharmaceutical Research

Year: 2024, Volume: 23, Issue: 3, Pages: 154-156

Original Article

Evaluation of PD-1 Gene Susceptibility and Prognosis in Breast Cancer Patients in Iranian Population

Abstract

Programmed cell death-1 (PD1) protein has an inhibitory effect that reduces the activity of T cells. In this study, gene expression PD1 in patients with breast cancer compared to healthy subjects discussed. This study was performed on 25 patients with breast cancer as a case group and 25 healthy individuals as a control group. Real-time PCR method was used to evaluate gene expression. For the case group, the mean age was 2.75 ± 12.18 and for the control group 30.6 ± 2.6. The results of our study showed that the expression of PD1 gene in the case group was higher than the control (p<0.05). As a result of our study show that expression of gene in the development of breast cancer, So PD1 can be used as prognostic gene in breast cancer study be considered.

Keywords: Breast cancer, Gene expresion, Programmed cell death-1

References

  1. Jemal A, Siegel R, Ward E, Murray T, Xu J, Thun MJ. Cancer Statistics, 2007. CA: A Cancer Journal for Clinicians. 2007;57(1):43–66. Available from: https://doi.org/10.3322/canjclin.57.1.43
  2. Kanduc D, Mittelman A, Serpico R, Sinigaglia, E, Sinha AA, Natale C, et al. Cell death: apoptosis versus necrosis (review. International Journal of Oncology. 2002;21(1):165–170. Available from: https://pubmed.ncbi.nlm.nih.gov/12063564/
  3. Kam PC, Ferch NI. Apoptosis: mechanisms and clinical implications. Anaesthesia. 2000;55(11):1081–1093. Available from: https://doi.org/10.1046/j.1365-2044.2000.01554.x
  4. Danial NN. BCL-2 family proteins: critical checkpoints of apoptotic cell death. Clinical Cancer Research. 2007;13(24):7254–7263. Available from: https://doi.org/10.1158/1078-0432.ccr-07-1598
  5. Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Research. 1988;16(3):1215. Available from: https://doi.org/10.1093/nar/16.3.1215
  6. Xie T, Ho SL, Ma OC. High resolution single strand conformation polymorphism analysis using formamide and ethidium bromide staining. Journal of Molecular Pathology. 1997;50(5):276–278. Available from: https://doi.org/10.1136/mp.50.5.276
  7. Koda M, Kanczuga-Koda L, Reszec J, Sulkowska M, Famulski W, Baltaziak M, et al. Expression of the apoptotic markers in normal breast epithelium, benign mammary dysplasia and in breast cancer. Folia Morphologica. 2004;63(3):337–341. Available from: https://pubmed.ncbi.nlm.nih.gov/15478112/
  8. Ghayad SE, Vendrell JA, Bleche I, Spyratos F, Dumontet C, Treilleux I, et al. Identification of TACC1, NOV, and PTTG1 as new candidate genes associated with endocrine therapy resistance in breast cancer. Journal of Molecular Endocrinology. 2009;42(2):87–103. Available from: https://doi.org/10.1677/JME-08-0076
  9. Sorbello V, Fuso L, Sfiligoi C, Ponzone R, Biglia N, Weisz A, et al. Quantitative real-time RTPCR analysis of eight novel estrogen-regulated genes in breast cancer. International Journal of Biological Markers. 2003;18(2):123–129. Available from: https://doi.org/10.1177/172460080301800205
  10. Schena M, Shalon D, Davis RW, Brown PO. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science. 1995 ;270(5235):467–470. Available from: https://doi.org/10.1126/science.270.5235.467
  11. Baldwin D, Crane V, Rice D. A comparison of gel-based, nylon filter and microarray techniques to detect differential RNA expression in plants. Current Opinion in Plant Biology. 1999;2(2):96–103. Available from: https://doi.org/10.1016/S1369-5266(99)80020-X
  12. Watson A, Mazumder A, Stewart M, Balasubramanian S. Technology for microarray analysis of gene expression. Current Opinion in Biotechnology. 1998;9(6):609–614. Available from: https://doi.org/10.1016/S0958-1669(98)80138-9
  13. Schena M, Heller RA, Theriault TP, Konrad K, Lachenmeier E, Davis RW. Microarrays: biotechnology's discovery platform for functional genomics. Trends in Biotechnology. 1998;16(7):301–306. Available from: https://doi.org/10.1016/S0167-7799(98)01219-0
  14. McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM. REporting recommendations for tumour MARKer prognostic studies (REMARK) British Journal of Cancer. 2005;93(4):387–391. Available from: https://doi.org/10.1038%2Fsj.bjc.6602678
  15. Chang M, Pho M, Dutta D, Stephans JC, Shak S, Kiefer MC, et al. Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay. American Journal of Pathology. 2004;164(1):35–42. Available from: https://doi.org/10.1016/s0002-9440(10)63093-3
  16. Cobleigh MA, Tabesh B, Bitterman P, Baker J, Cronin M, Liu ML, et al. Tumor gene expression and prognosis in breast cancer patients with 10 or more positive lymph nodes. Clinical Cancer Research. 2005;11(24 Pt 1):8623–8631. Available from: https://doi.org/10.1158/1078-0432.ccr-05-0735
  17. Esteva FJ, Sahin AA, Cristofanilli M, Coombes K, Lee SJ, Baker J. Prognostic role of a multigene reverse transcriptasePCR assay in patients with node-negative breast cancer not receiving adjuvant systemic therapy. Clinical Cancer Research. 2005;11(9):3315–3319. Available from: https://doi.org/10.1158/1078-0432.ccr-04-1707
  18. Habel LA, Shak S, Jacobs MK, Capra A, Alexander C, Pho M, et al. A population based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Research. 2006;8(3):1–15. Available from: https://doi.org/10.1186/bcr1412
  19. Mina L, Soule SE, Badve S, Baehner FL, Baker J, Cronin M, et al. Predicting response to primary chemotherapy: gene expression profiling of paraffin-embedded core biopsy tissue. Breast Cancer Research and Treatment. 2007;103(2):197–208. Available from: https://dx.doi.org/10.1007/s10549-006-9366-x
  20. Paik S, Tang G, Shak S, Kim C, Baker J, Kim W, et al. Gene Expression and Benefit of Chemotherapy in Women With Node-Negative, Estrogen Receptor–Positive Breast Cancer. Journal of Clinical Oncology. 2023;41(20):3565–3575. Available from: https://dx.doi.org/10.1200/jco.22.02570
  21. Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. PNAS. 2003;100(4):8418–8423. Available from: https://doi.org/10.1073/pnas.0932692100
  22. Oratz R, Paul D, Cohn AL, Sedlacek SM. Impact of a Commercial Reference Laboratory Test Recurrence Score on Decision Making in Early-Stage Breast Cancer. JCO Oncology Practice. 2007;3(4):182 –186. Available from: https://doi.org/10.1200/JOP.0742001
  23. Zhou AM, Floore A, Delahaye LJMJ, Witteveen AT, Pover RCF, Bakx N, et al. Converting a breast cancer microarray signature into a highthroughput diagnostic test. BMC Genomics. 2006;7:1–10. Available from: https://doi.org/10.1186/1471-2164-7-278

Copyright

© 2024 Published by Krupanidhi College of Pharmacy. This is an open-access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/

DON'T MISS OUT!

Subscribe now for latest articles and news.