Immune Dysfunction as Measured by Lymphocytopenia, Minimal Residual Disease and Outcome after Radical Prostatectomy for Localized Prostate Cancer
Main Article Content
Nigel P Murray
http://orcid.org/0000-0001-8154-8550
Socrates Aedo
http://orcid.org/0000-0001-5567-3374
Cynthia Fuentealba
http://orcid.org/0000-0003-4100-6997
Eduardo Reyes
http://orcid.org/0000-0001-8430-3030
Anibal Salazar
http://orcid.org/0000-0001-9319-4219
http://orcid.org/0000-0001-8154-8550
Socrates Aedo
http://orcid.org/0000-0001-5567-3374
Cynthia Fuentealba
http://orcid.org/0000-0003-4100-6997
Eduardo Reyes
http://orcid.org/0000-0001-8430-3030
Anibal Salazar
http://orcid.org/0000-0001-9319-4219
Abstract
Background: An intact immune function may be important in eliminating or maintaining minimal residual disease latent.
Objective: Use the absolute lymphocyte count as an immune biomarker, determine its association with minimal residual disease and relation with biochemical failure.
Design, setting, and participants: prospective observational single centre study in men treated by radical prostatectomy for localized prostate cancer. One month after surgery blood and bone samples were taken to detect circulating prostate cells and micro-metastasis. A total of 404 men were enrolled, at each follow up time total PSA, ALC and CPC presence/absence were determined.
Outcome measurements and statistical analysis: observed times to biochemical failure (Kaplan-Meier) and restricted mean biochemical failure free survival times were assessed, changes in the absolute lymphocyte count and the presence/absence of circulating prostate cells were determined during follow-up and association with biochemical failure.
Results and Limitations: 404 men participated; 182 were minimal residual disease negative (Group A), 80 had only micro-metastasis (Group B) and 142 were circulating prostate cell positive (Group C); 175 men underwent biochemical failure, Group C were at high risk of early failure, Group B of late failure. One month post-surgery Group C men had lower absolute lymphocyte counts, compared to Groups A and B. During follow-up men with stable absolute lymphocyte counts did not relapse, a decreasing absolute lymphocyte count was associated with relapse within 18 months and the appearance of circulating prostate cells in the blood. After five years the absolute lymphocyte count decreased in Group B patients. A low absolute lymphocyte count one-month post-surgery or a decrease during follow-up was associated with an increased risk of treatment failure.
Conclusions: the absolute lymphocyte count is an important prognostic factor, it may change with time, a decrease is associated with pending biochemical failure and later appearance of circulating prostate cells.
Keywords:
prostate cancer, biochemical faillure, immune dysfunction, lymphocytopenia, circulating tumour cells
Article Details
How to Cite
MURRAY, Nigel P et al.
Immune Dysfunction as Measured by Lymphocytopenia, Minimal Residual Disease and Outcome after Radical Prostatectomy for Localized Prostate Cancer.
Medical Research Archives, [S.l.], v. 10, n. 12, dec. 2022.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/3453>. Date accessed: 24 apr. 2024.
doi: https://doi.org/10.18103/mra.v10i12.3453.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
1. Moreno JG, Croce CM, Fischer R, Monne M, Vikha P, Mulholland SG et al. Detection of hematogenous micrometastasis in patients with prostate cancer. Cancer 1992; 52: 6110-6112.
2. Santos MF, Mannam VKR, Craft BS, Puneky LV, Sheehan NT, Lewis RE et al. Comparative analysis of innate immune system function in metastatic breast, colorectal and prostate cancer patients with circulating tumor cells. Exp Mol Pathol 2014; 96: 367-374 http//:doi.org:10.1016/j.exmp.2014.04.001
3. Ashizawa N, Furuya S, Katsutoshi S, Sudo M, Akaike H, Hosomura N et al. Clinical significance of dynamic neutrophil-lymphocyte ratio changes in patients with colorectal cancer. Anticancer Res 2020; 40: 2311-2317 http//:doi.org:10.21873/anticanres.14197
4. Yasui K, Shida D, Nakamura Y, Ahiko Y, Tsukamoto S, Kanemitsu Y.
Postoperative, but not preoperative, inflammatory based prognostic markers are prognostic factors in stage III colorectal cancer patients. Br J Cancer 2021; 124: 933-941 http//:doi.org:10.1038/s41416-020-01189-6
5. Lee H, Jeong SJ, Hong SK, Byun SS, Lee SE Oh JJ. High preoperative neutrophil-lymphocyte ratio predicts biochemical recurrence in patients with localized prostate cancer after radical prostatectomy. World J Urol 2016; 34: 821-827 http//:doi.org:10.1007/s00345-015-1701-6
6. Jang WS, Cho KS, Kim KH, Yoon CY, Kang YJ, Lee JY et al. Prognostic impact of pre-operative neutrophil to lymphocyte ratio after radical prostatectomy in localized prostate cancer. Prostate Cancer Prostatic Dis 2016; 19: 298-304 http://doi.org:10.1038/pcan.2016.20.
7. Bravi CA, Rosiello G, Fallara G, Vertosick E, Tin A, Sjoberg D et al. Predictive value of pre-operative neutrophil to lymphocyte ratio in localized prostate cancer: results from a surgical series at a high volumen institution. Minerva Urol Nefrol 2020; hhtp//:doi.org:10.23736/s0393-2249.20.03662-0
8. Lu Y, Huang HH, Lau WKO. Evaluation of neutrophil to lymphocyte ratio as a prognostic indicator in a Singapore cohort of patients with clinically localized prostate cancer treated with prostatectomy. World J Urol 2020; 38: 103-109 http//:doi.org:10.1007/s00345-019-02752-4
9. Wang J, Zhou X, He Y, Chen X, Liu N, Ding Z et al. Prognostic role of platelet to lymphocyte ratio in prostate cancer: a meta-analysis Medicine 2018 http//:doi.org:10.1097/med0000000000012504
10. Rajwa P, Schuettfort VM, D´Andrea D, Quhal F, Mori K,Katayama S et al. Impact of systemic immune inflammation index on oncologic outcomes in patients treated with radical prostatectomy for clinically non-metastatic prostate cancer. Urol Oncol 2021; S1078-1439(21)00208-8 http//:doi.org:10.1016/j.urolonc.2021.05.002
11. Kozak MM, von Eyben R, Pai JS, Anderson EM, Welton ML, Shelton AA et al. The prognostic significance of pretreatment hematologic parameters in patients undergoing resection for colorectal cancer. Am J Clin Oncol 2017; 40: 405-412 http//:doi.org:10.1097/coc.0000000000000183
12. Coskun A, Carobene A, Kilercik M, Serteser M, Sandberg S, Aarsand AK et al. (European Biological Variation Study Group of the EFLM Working Group on Biological Variation). Within subject and between subject biological variation estimates of 21 hematological parameters in 30 healthy subjects. Clin Chem Lab Med 2018; 56: 1309-1318 http//:doi.org:10.1515/cclm-2019-0658
13. Borgen E, Naume B, Nesland JM, Kvalheim G, Beiske K, Fodstad O,
et al (1999). Standardization of the immunocytochemical detection of cancer cells in BM and blood. I. Establishment of objective criteria for the evaluation of immunostained cells. Cytotherapy, 1999; 1: 377–88. http//:doi.org:10.1080/0032472031000141283
14. Murray NP, Reyes E, Tapia P, Badinez L, Orellana N, Fuentealba C
et al. Redefining micrometastasis in prostate cancer- a comparison of circulating prostate cells, bone marrow disseminated tumor cells and micrometastasis: Implications in determining local or systemic treatment for biochemical failure after radical prostatectomy. Int J Mol Med, 2012; 30: 896-904 http//:doi.org:10.3892/ijmm.2012.1071
15. Crowther MJ, Abrams KR, Lambert PC. Joint modeling of longitudinal and survival data. Stata Journal. 2013;13:165-84.
16.Crowther MJ. MERLIN—A unified modeling framework for data analysis and methods development in Stata. The Stata Journal. 2020; 20:763-84.
17. Cleves M, Gutierrez R, Gould W, Mrachenko Y. An introduction to survival analysis using stata. Third edition ed. Texas: Stata Press; 2010. 412 pp.
18. Royston P. Tools for checking calibration of a Cox model in external validation: Prediction of population-averaged survival curves based onrisk groups. The Stata Journal. 2015; 15: 275-91.
19. Pepe MS. The Statistical Evaluation of Medical Tests for Classification and Prediction: Oxford University Press; 2004
20. Lambert J, Chevret S. Summary measure of discrimination in survival models based on cumulative/dynamic time-dependent ROC curves. Stat Methods Med Res. 2016; 25: 2088-102.
21. Si T, Guo Z, Hao X. Immunologic response to primary cryoablation of high risk prostate cancer. Cryobiology 2008; 57: 66-71 http//:doi.org:10.1016/j.cryobiol.2008.06.003
22. Si TG, Wang JP, Guo Z. Analysis of circulating regulatory T cells (CD4+CD25+CD127´) after cryosurgery in prostate cancer. Asian J Androl 2013; 15: 461-465 http//:doi.org:10.1038/aja.2013.22
23. Brusa D, Carletto S, Cucchiarate G, Gontero P, Greco A, Simone M et al. Prostatectomy restores the maturation competence of blood dendritic cell precursors and feverses the abnormal expression of regulatory T lymphocytes. Prostate 2011; 71: 344-352 http//:doi.org:10.1002/pros.21248
24. Watanabe J, Saito M, Horimoto Y, Nakamoto S. A maintained absolute lymphocyte count predicts the overall survial benefit from eribulin therapy, including eribulin re-administration, in HER-2 negative advanced breast cancer: a single institutional experience. Breast Cancer Res Treat 2020; 181: 211-2020 http//:doi.org:10.1007/s10549-020-05626-1
25. Nakamoto S, Ikeda M, Kubo S, Yamamoto M, Yamashita T. Dynamic changes in absolute lymphocyte counts during eribulin therapy are associated with survival benefit. Anticancer Res 2021; 41: 3109-3119 http//:doi.org:10.21873/anticanres.15095
26. De Giorgi U, Mego M, Scarpi E, Giuliano M, Giordano A, Reuben JM et al. Relationship between lymphocytopenia and circulating tumor cells as prognostic factors for overall survival in metastatic breast cancer. Clin Breast Cancer 2012; 12: 264-269 http//:doi.org:10.1016/j.clbc.2012.04.004
27. Qian C, Cai R, Zhang W, Wang J, Hu X, Zhang Y et al. Neutrophil-lymphocyte ratio and circulating tumor cell counts predict prognosis in gastrointestinal cancer patients. Front Oncol 2021; 11: 710704 http//:doi.org:10.3389/fonc2021.710704
28. Chong W, Zhang Z, Luo R, Gu J, Lin J, Wei Q et al. Integration of circulating resistant prostate cancer patients BMC Cancer 2021; 21: 655 http//:doi.org:10.1186/s12885-021-08405-3
29. De Angulo A, Faris R, Cavazos D, Jolly C, Daniel B, DeGraffenried L. Age realted alterations in T-lymphocytes modulate key pathways in prostate tumorigenesis. Prostate 2013; 73: 855-864 http//:doi.org:10.1002/pros.22631
30. van der Toom EE, Verdone JE, Pienta KJ. Disseminated tumor cells and dormancy in prostate cancer. Curr Opin Biotechnol 2016; 40: 9-15 http//:doi.org:10.1016/j.copbio.2016.02.002
31. Shiao SL, Chu GC, Chung LWK. Regulation of prostate cancer progression by the tumor microenvironment. Cancer Lett 2016; 380: 340-348 http//:doi.org:10.1016/j.canlet.2015.12.022
32. Olechnowicz SWZ, Edwards CM. Contributions of the host microenvironment to cancer induced bone disease. Cancer Res 2014; 74: 1625-1631 http//:doi.org:10.1158/0008-5472.CAN-13-2645
ch
33. Ganguly SS. Li X, Miranti CK. The host microenvironment influences prostate cancer invasión, systemic spread, bone colonizaction and osteoblastic metástasis. Front Oncol http//:doi.org:/10.3389/fonc.2014.00364
34. Zheng Y, Zhou H, Dunstan CR et al. The role of the bone marrow microenvironment in skeletal metástasis. J Bone Oncol 2013; 2: 47-57 http//:doi.org:/10.1016/j.jbo.2012.11.002
35. Morrissey C, Vessella RL, Lange PH et al. The biology and clinical implications of prostate cancer dormancy and metástasis. J Molec Med 2016; 94: 259-265 http//:doi.org:/10.1007/s00109-015-1353-4
36. Cross MC. Minimal residual disease in chronic myeloid leukaemia. Hematol Cell Ther 1998: 40: 224-228
37. Bain B. Bone marrow biopsy morbidity: review of 2003. J Clin Pathol 2003; 58: 406-408 http//:doi.org: 10.1136/jcp.2004.022178
38. Rietbergen JB, Kruger AE, Krause R Schroder F. Complications of ultrasound guided systemic sextant biopsies of prostate: evaluation of complication rates and risk factors within a population based screening population. Urology 1997; 49: 875-880
39. Chandra S, Chandra H. Comparison of bone marrow aspirate cytology, touch imprint cytology and trephine biopsy for bone marrow evaluation. Hematol Rep 2011; 3: 65.68 http//:doi.org:/10.4081/hr.2011.e22
40. Panteleakou Z, Lembessis P, Sourla A et al. Detection of circulating tumour cells in prostate cancer patients: methodological pitfalls and clinical relevance. Mol Med 2009; 15: 101-114 http//:doi.org/10.2119/molmed.2008.00116
41. Murray NP, Aedo S, Fuentealba C et al. Combining the prostate cancer risk index (PRIX) with the presense of secondary circulating prostate cells to predict risk of biochemical failure after radical prostatectomy for prostate cancer. Asian Pac J Cancer Prev 2018; 19: 3375-3381 http//:doi.org:/10.31557/APJCP.2018.19.12.3375
2. Santos MF, Mannam VKR, Craft BS, Puneky LV, Sheehan NT, Lewis RE et al. Comparative analysis of innate immune system function in metastatic breast, colorectal and prostate cancer patients with circulating tumor cells. Exp Mol Pathol 2014; 96: 367-374 http//:doi.org:10.1016/j.exmp.2014.04.001
3. Ashizawa N, Furuya S, Katsutoshi S, Sudo M, Akaike H, Hosomura N et al. Clinical significance of dynamic neutrophil-lymphocyte ratio changes in patients with colorectal cancer. Anticancer Res 2020; 40: 2311-2317 http//:doi.org:10.21873/anticanres.14197
4. Yasui K, Shida D, Nakamura Y, Ahiko Y, Tsukamoto S, Kanemitsu Y.
Postoperative, but not preoperative, inflammatory based prognostic markers are prognostic factors in stage III colorectal cancer patients. Br J Cancer 2021; 124: 933-941 http//:doi.org:10.1038/s41416-020-01189-6
5. Lee H, Jeong SJ, Hong SK, Byun SS, Lee SE Oh JJ. High preoperative neutrophil-lymphocyte ratio predicts biochemical recurrence in patients with localized prostate cancer after radical prostatectomy. World J Urol 2016; 34: 821-827 http//:doi.org:10.1007/s00345-015-1701-6
6. Jang WS, Cho KS, Kim KH, Yoon CY, Kang YJ, Lee JY et al. Prognostic impact of pre-operative neutrophil to lymphocyte ratio after radical prostatectomy in localized prostate cancer. Prostate Cancer Prostatic Dis 2016; 19: 298-304 http://doi.org:10.1038/pcan.2016.20.
7. Bravi CA, Rosiello G, Fallara G, Vertosick E, Tin A, Sjoberg D et al. Predictive value of pre-operative neutrophil to lymphocyte ratio in localized prostate cancer: results from a surgical series at a high volumen institution. Minerva Urol Nefrol 2020; hhtp//:doi.org:10.23736/s0393-2249.20.03662-0
8. Lu Y, Huang HH, Lau WKO. Evaluation of neutrophil to lymphocyte ratio as a prognostic indicator in a Singapore cohort of patients with clinically localized prostate cancer treated with prostatectomy. World J Urol 2020; 38: 103-109 http//:doi.org:10.1007/s00345-019-02752-4
9. Wang J, Zhou X, He Y, Chen X, Liu N, Ding Z et al. Prognostic role of platelet to lymphocyte ratio in prostate cancer: a meta-analysis Medicine 2018 http//:doi.org:10.1097/med0000000000012504
10. Rajwa P, Schuettfort VM, D´Andrea D, Quhal F, Mori K,Katayama S et al. Impact of systemic immune inflammation index on oncologic outcomes in patients treated with radical prostatectomy for clinically non-metastatic prostate cancer. Urol Oncol 2021; S1078-1439(21)00208-8 http//:doi.org:10.1016/j.urolonc.2021.05.002
11. Kozak MM, von Eyben R, Pai JS, Anderson EM, Welton ML, Shelton AA et al. The prognostic significance of pretreatment hematologic parameters in patients undergoing resection for colorectal cancer. Am J Clin Oncol 2017; 40: 405-412 http//:doi.org:10.1097/coc.0000000000000183
12. Coskun A, Carobene A, Kilercik M, Serteser M, Sandberg S, Aarsand AK et al. (European Biological Variation Study Group of the EFLM Working Group on Biological Variation). Within subject and between subject biological variation estimates of 21 hematological parameters in 30 healthy subjects. Clin Chem Lab Med 2018; 56: 1309-1318 http//:doi.org:10.1515/cclm-2019-0658
13. Borgen E, Naume B, Nesland JM, Kvalheim G, Beiske K, Fodstad O,
et al (1999). Standardization of the immunocytochemical detection of cancer cells in BM and blood. I. Establishment of objective criteria for the evaluation of immunostained cells. Cytotherapy, 1999; 1: 377–88. http//:doi.org:10.1080/0032472031000141283
14. Murray NP, Reyes E, Tapia P, Badinez L, Orellana N, Fuentealba C
et al. Redefining micrometastasis in prostate cancer- a comparison of circulating prostate cells, bone marrow disseminated tumor cells and micrometastasis: Implications in determining local or systemic treatment for biochemical failure after radical prostatectomy. Int J Mol Med, 2012; 30: 896-904 http//:doi.org:10.3892/ijmm.2012.1071
15. Crowther MJ, Abrams KR, Lambert PC. Joint modeling of longitudinal and survival data. Stata Journal. 2013;13:165-84.
16.Crowther MJ. MERLIN—A unified modeling framework for data analysis and methods development in Stata. The Stata Journal. 2020; 20:763-84.
17. Cleves M, Gutierrez R, Gould W, Mrachenko Y. An introduction to survival analysis using stata. Third edition ed. Texas: Stata Press; 2010. 412 pp.
18. Royston P. Tools for checking calibration of a Cox model in external validation: Prediction of population-averaged survival curves based onrisk groups. The Stata Journal. 2015; 15: 275-91.
19. Pepe MS. The Statistical Evaluation of Medical Tests for Classification and Prediction: Oxford University Press; 2004
20. Lambert J, Chevret S. Summary measure of discrimination in survival models based on cumulative/dynamic time-dependent ROC curves. Stat Methods Med Res. 2016; 25: 2088-102.
21. Si T, Guo Z, Hao X. Immunologic response to primary cryoablation of high risk prostate cancer. Cryobiology 2008; 57: 66-71 http//:doi.org:10.1016/j.cryobiol.2008.06.003
22. Si TG, Wang JP, Guo Z. Analysis of circulating regulatory T cells (CD4+CD25+CD127´) after cryosurgery in prostate cancer. Asian J Androl 2013; 15: 461-465 http//:doi.org:10.1038/aja.2013.22
23. Brusa D, Carletto S, Cucchiarate G, Gontero P, Greco A, Simone M et al. Prostatectomy restores the maturation competence of blood dendritic cell precursors and feverses the abnormal expression of regulatory T lymphocytes. Prostate 2011; 71: 344-352 http//:doi.org:10.1002/pros.21248
24. Watanabe J, Saito M, Horimoto Y, Nakamoto S. A maintained absolute lymphocyte count predicts the overall survial benefit from eribulin therapy, including eribulin re-administration, in HER-2 negative advanced breast cancer: a single institutional experience. Breast Cancer Res Treat 2020; 181: 211-2020 http//:doi.org:10.1007/s10549-020-05626-1
25. Nakamoto S, Ikeda M, Kubo S, Yamamoto M, Yamashita T. Dynamic changes in absolute lymphocyte counts during eribulin therapy are associated with survival benefit. Anticancer Res 2021; 41: 3109-3119 http//:doi.org:10.21873/anticanres.15095
26. De Giorgi U, Mego M, Scarpi E, Giuliano M, Giordano A, Reuben JM et al. Relationship between lymphocytopenia and circulating tumor cells as prognostic factors for overall survival in metastatic breast cancer. Clin Breast Cancer 2012; 12: 264-269 http//:doi.org:10.1016/j.clbc.2012.04.004
27. Qian C, Cai R, Zhang W, Wang J, Hu X, Zhang Y et al. Neutrophil-lymphocyte ratio and circulating tumor cell counts predict prognosis in gastrointestinal cancer patients. Front Oncol 2021; 11: 710704 http//:doi.org:10.3389/fonc2021.710704
28. Chong W, Zhang Z, Luo R, Gu J, Lin J, Wei Q et al. Integration of circulating resistant prostate cancer patients BMC Cancer 2021; 21: 655 http//:doi.org:10.1186/s12885-021-08405-3
29. De Angulo A, Faris R, Cavazos D, Jolly C, Daniel B, DeGraffenried L. Age realted alterations in T-lymphocytes modulate key pathways in prostate tumorigenesis. Prostate 2013; 73: 855-864 http//:doi.org:10.1002/pros.22631
30. van der Toom EE, Verdone JE, Pienta KJ. Disseminated tumor cells and dormancy in prostate cancer. Curr Opin Biotechnol 2016; 40: 9-15 http//:doi.org:10.1016/j.copbio.2016.02.002
31. Shiao SL, Chu GC, Chung LWK. Regulation of prostate cancer progression by the tumor microenvironment. Cancer Lett 2016; 380: 340-348 http//:doi.org:10.1016/j.canlet.2015.12.022
32. Olechnowicz SWZ, Edwards CM. Contributions of the host microenvironment to cancer induced bone disease. Cancer Res 2014; 74: 1625-1631 http//:doi.org:10.1158/0008-5472.CAN-13-2645
ch
33. Ganguly SS. Li X, Miranti CK. The host microenvironment influences prostate cancer invasión, systemic spread, bone colonizaction and osteoblastic metástasis. Front Oncol http//:doi.org:/10.3389/fonc.2014.00364
34. Zheng Y, Zhou H, Dunstan CR et al. The role of the bone marrow microenvironment in skeletal metástasis. J Bone Oncol 2013; 2: 47-57 http//:doi.org:/10.1016/j.jbo.2012.11.002
35. Morrissey C, Vessella RL, Lange PH et al. The biology and clinical implications of prostate cancer dormancy and metástasis. J Molec Med 2016; 94: 259-265 http//:doi.org:/10.1007/s00109-015-1353-4
36. Cross MC. Minimal residual disease in chronic myeloid leukaemia. Hematol Cell Ther 1998: 40: 224-228
37. Bain B. Bone marrow biopsy morbidity: review of 2003. J Clin Pathol 2003; 58: 406-408 http//:doi.org: 10.1136/jcp.2004.022178
38. Rietbergen JB, Kruger AE, Krause R Schroder F. Complications of ultrasound guided systemic sextant biopsies of prostate: evaluation of complication rates and risk factors within a population based screening population. Urology 1997; 49: 875-880
39. Chandra S, Chandra H. Comparison of bone marrow aspirate cytology, touch imprint cytology and trephine biopsy for bone marrow evaluation. Hematol Rep 2011; 3: 65.68 http//:doi.org:/10.4081/hr.2011.e22
40. Panteleakou Z, Lembessis P, Sourla A et al. Detection of circulating tumour cells in prostate cancer patients: methodological pitfalls and clinical relevance. Mol Med 2009; 15: 101-114 http//:doi.org/10.2119/molmed.2008.00116
41. Murray NP, Aedo S, Fuentealba C et al. Combining the prostate cancer risk index (PRIX) with the presense of secondary circulating prostate cells to predict risk of biochemical failure after radical prostatectomy for prostate cancer. Asian Pac J Cancer Prev 2018; 19: 3375-3381 http//:doi.org:/10.31557/APJCP.2018.19.12.3375