Advertisement

Three gold indicators for breast cancer prognosis: a case–control study with ROC analysis for novel ratios related to CBC with (ALP and LDH)

  • Noha Mohamed SaidEmail author
Original Article
  • 24 Downloads

Abstract

Science is still unable to develop a specific strategy for predicting breast cancer in humans. Several attempts are done to obtain the best and closest prognostic predictive biomarkers for breast cancer. The present study aimed to evaluate the impact of novel ratios calculated between the blood indices with CA15.3, alkaline phosphatase and lactate dehydrogenase as prognostic biomarkers in breast cancer. This study was conducted on two groups (Breast cancer Patients group in comparison to a control group who has no tumor family history). All the volunteers are subjected to the routine analysis included liver and kidney function tests, complete blood count with blood indices, tumor markers (CA15.3) assessment, alkaline phosphatase, and lactate dehydrogenase analysis. Thirty different ratios were calculated in the present research between blood indices and three inexpensive serum biomarkers; CA15.3, alkaline phosphatase and lactate dehydrogenase. Fifteen ratios of them were significant in breast cancer group than the control group. Three ratios (PDW/lymphocytes, MPV/lymphocytes, and ALP/RDW) of them gave a sensitivity of 100% with high specificity as indicators for breast cancer incidence. The correlation between significant ratios was very interesting. The more interesting was in the results of subgroup analysis which showed that the ALP/RDW ratio is more specific for pre-menopause while PDW/lymphocytes ratio is more specific for post-menopause. The ratios PDW/lymphocytes, MPV/lymphocytes, and ALP/RDW can be used as prognostic biomarkers in breast cancer patients. The interesting advantage in the results depends on the availability of these indicators in routine blood analysis and will not increase the cost of the diagnostic plan.

Keywords

Breast cancer Platelets distribution width Red cell distribution width Mean platelets volume Alkaline phosphatase Lactate dehydrogenase 

Notes

Acknowledgements

We appreciate the collaboration of all participants and staff at Zagazig University Hospital, Egypt.

Compliance with ethical standards

Conflict of interest

The author declares no conflict of interests.

Ethical approval

The study was approved by the Ethics Committee of the Zagazig University.

Informed consent

Written informed consent was obtained from all participants.

References

  1. 1.
    Wang H, Naghavi M, Allen C et al (2016) Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. The Lancet 388:1459–1544.  https://doi.org/10.1016/S0140-6736(16)31012-1 CrossRefGoogle Scholar
  2. 2.
    Global Burden of Disease Cancer Collaboration, Fitzmaurice C, Allen C et al (2017) Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 32 cancer groups, 1990 to 2015: a systematic analysis for the global burden of disease study. JAMA Oncol 3:524–548.  https://doi.org/10.1001/jamaoncol.2016.5688 CrossRefPubMedCentralGoogle Scholar
  3. 3.
    Silverstein A, Sood R, Costas-Chavarri A (2016) Breast Cancer in Africa: Limitations and Opportunities for Application of Genomic Medicine. Int J Breast Cancer. https://www.hindawi.com/journals/ijbc/2016/4792865/. Accessed 12 Dec 2018
  4. 4.
    Brinton L, Figueroa J, Adjei E, Ansong D, Biritwum R et al (2017) Factors contributing to delays in diagnosis of breast cancers in Ghana, West Africa. Breast Cancer Res Treat 162:105–114.  https://doi.org/10.1007/s10549-016-4088-1 CrossRefPubMedGoogle Scholar
  5. 5.
    Pace LE, Shulman LN (2016) Breast cancer in sub-saharan africa: challenges and opportunities to reduce mortality. Oncologist 21:739–744.  https://doi.org/10.1634/theoncologist.2015-0429 CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Stegner D, Dütting S, Nieswandt B (2014) Mechanistic explanation for platelet contribution to cancer metastasis. Thromb Res 133(Suppl 2):S149–S157.  https://doi.org/10.1016/S0049-3848(14)50025-4 CrossRefPubMedGoogle Scholar
  7. 7.
    Takeuchi H, Abe M, Takumi Y et al (2017) The prognostic impact of the platelet distribution width-to-platelet count ratio in patients with breast cancer. PLoS ONE 12:e0189166.  https://doi.org/10.1371/journal.pone.0189166 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Franco AT, Corken A, Ware J (2015) Platelets at the interface of thrombosis, inflammation, and cancer. Blood 126:582–588.  https://doi.org/10.1182/blood-2014-08-531582 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Takagi S, Takemoto A, Takami M et al (2014) Platelets promote osteosarcoma cell growth through activation of the platelet-derived growth factor receptor-Akt signaling axis. Cancer Sci 105:983–988.  https://doi.org/10.1111/cas.12464 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Paulsson J, Sjöblom T, Micke P et al (2009) Prognostic significance of stromal platelet-derived growth factor β-receptor expression in human breast cancer. Am J Pathol 175:334–341.  https://doi.org/10.2353/ajpath.2009.081030 CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Kang DW, Min DS (2010) Platelet-derived growth factor increases phospholipase D1 but not phospholipase D2 expression via NFκB signaling pathway and enhances invasion of breast cancer cells. Cancer Lett 294:125–133.  https://doi.org/10.1016/j.canlet.2010.01.031 CrossRefPubMedGoogle Scholar
  12. 12.
    Takeuchi H, Fukuyama S, Kubo N et al (2016) The prognostic significance of the preoperative platelet-lymphocyte ratio in japanese patients with localized breast cancer. Adv Breast Cancer Res 05:49–57.  https://doi.org/10.4236/abcr.2016.52005 CrossRefGoogle Scholar
  13. 13.
    Takeuchi H, Kawanaka H, Fukuyama S et al (2017) Comparison of the prognostic values of preoperative inflammation-based parameters in patients with breast cancer. PLoS ONE 12:e0177137.  https://doi.org/10.1371/journal.pone.0177137 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Martin J, Bath PM, Burr M (1991) Influence of platelet size on outcome after myocardial infarction. Lancet 338:1409–1411.  https://doi.org/10.1016/0140-6736(91)92719-I CrossRefPubMedGoogle Scholar
  15. 15.
    Yuri Gasparyan A, Ayvazyan L, Mikhailidis DP, Kitas DG (2011) Mean platelet volume: a link between thrombosis and inflammation? Curr Pharm Des 17:47–58.  https://doi.org/10.2174/138161211795049804 CrossRefGoogle Scholar
  16. 16.
    Kaito K, Otsubo H, Usui N et al (2005) Platelet size deviation width, platelet large cell ratio, and mean platelet volume have sufficient sensitivity and specificity in the diagnosis of immune thrombocytopenia. Br J Haematol 128:698–702.  https://doi.org/10.1111/j.1365-2141.2004.05357.x CrossRefPubMedGoogle Scholar
  17. 17.
    Zhang F, Chen Z, Wang P et al (2016) Combination of platelet count and mean platelet volume (COP-MPV) predicts postoperative prognosis in both resectable early and advanced stage esophageal squamous cell cancer patients. Tumor Biol 37:9323–9331.  https://doi.org/10.1007/s13277-015-4774-3 CrossRefGoogle Scholar
  18. 18.
    Gu M, Zhai Z, Huang L et al (2016) Pre-treatment mean platelet volume associates with worse clinicopathologic features and prognosis of patients with invasive breast cancer. Breast Cancer 23:752–760.  https://doi.org/10.1007/s12282-015-0635-6 CrossRefPubMedGoogle Scholar
  19. 19.
    Cho SY, Yang JJ, You E et al (2013) Mean platelet volume/platelet count ratio in hepatocellular carcinoma. Platelets 24:375–377.  https://doi.org/10.3109/09537104.2012.701028 CrossRefPubMedGoogle Scholar
  20. 20.
    Inagaki N, Kibata K, Tamaki T et al (2014) Prognostic impact of the mean platelet volume/platelet count ratio in terms of survival in advanced non-small cell lung cancer. Lung Cancer 83:97–101.  https://doi.org/10.1016/j.lungcan.2013.08.020 CrossRefPubMedGoogle Scholar
  21. 21.
    Kumagai S, Tokuno J, Ueda Y et al (2015) Prognostic significance of preoperative mean platelet volume in resected non-small-cell lung cancer. Mol Clin Oncol 3:197–201.  https://doi.org/10.3892/mco.2014.436 CrossRefPubMedGoogle Scholar
  22. 22.
    Kim SH, Yeon JH, Park KN et al (2016) The association of Red cell distribution width and in-hospital mortality in older adults admitted to the emergency department. Scand J Trauma Resuscitation Emerg Med.  https://doi.org/10.1186/s13049-016-0274-8 CrossRefGoogle Scholar
  23. 23.
    Wang F-M, Xu G, Zhang Y, Ma L-L (2014) Red cell distribution width is associated with presence, stage, and grade in patients with renal cell carcinoma. Dis Markers 2014:1–7.  https://doi.org/10.1155/2014/860419 CrossRefGoogle Scholar
  24. 24.
    Zhang X, Wu Q, Hu T et al (2018) Elevated red blood cell distribution width contributes to poor prognosis in patients undergoing resection for nonmetastatic rectal cancer. Medicine 97:e9641.  https://doi.org/10.1097/MD.0000000000009641 CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Yazici P, Demir U, Bozkurt E et al (2017) The role of red cell distribution width in the prognosis of patients with gastric cancer. Cancer Biomarkers 18:19–25.  https://doi.org/10.3233/CBM-160668 CrossRefPubMedGoogle Scholar
  26. 26.
    Podhorecka M, Halicka D, Szymczyk A et al (2016) Assessment of red blood cell distribution width as a prognostic marker in chronic lymphocytic leukemia. Oncotarget.  https://doi.org/10.18632/oncotarget.9055 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Qin Y, Wang P, Huang Z et al (2017) The value of red cell distribution width in patients with ovarian cancer. Medicine 96:e6752.  https://doi.org/10.1097/MD.0000000000006752 CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Zhou D, Wu Y, Lin Z et al (2018) Prognostic value of combination of pretreatment red cell distribution width and neutrophil-to-lymphocyte ratio in patients with gastric cancer. Gastroenterol Res Pract 2018:1–8.  https://doi.org/10.1155/2018/8042838 CrossRefGoogle Scholar
  29. 29.
    Koma Y, Onishi A, Matsuoka H et al (2013) Increased red blood cell distribution width associates with cancer stage and prognosis in patients with lung cancer. PLoS ONE 8:e80240.  https://doi.org/10.1371/journal.pone.0080240 CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Baicus C, Caraiola S, Rimbas M et al (2011) Utility of routine hematological and inflammation parameters for the diagnosis of cancer in involuntary weight loss. J Investig Med 59:951–955.  https://doi.org/10.2310/JIM.0b013e31822467a3 CrossRefPubMedGoogle Scholar
  31. 31.
    John A, Kaman L, Behera A et al (2018) Role of red cell distribution width and other blood cell indices in differentiating between benign and malignant diseases of gallbladder. HPB 20:S707–S708.  https://doi.org/10.1016/j.hpb.2018.06.1413 CrossRefGoogle Scholar
  32. 32.
    Ozkalemkas F, Ali R, Ozkocaman V et al (2005) The bone marrow aspirate and biopsy in the diagnosis of unsuspected nonhematologic malignancy: a clinical study of 19 cases. BMC Cancer  https://doi.org/10.1186/1471-2407-5-144 CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Spell DW, Jones DV, Harper WF, David Bessman J (2004) The value of a complete blood count in predicting cancer of the colon. Cancer Detect Prev 28:37–42.  https://doi.org/10.1016/j.cdp.2003.10.002 CrossRefPubMedGoogle Scholar
  34. 34.
    Lee M (1992) Colorectal cancer. Recent developments and continuing controversies. Rehab Oncol 10:18.  https://doi.org/10.1097/01893697-199210030-00023 CrossRefGoogle Scholar
  35. 35.
    Seitanides B, Giakoumakis G, Tsakona C (1988) Increased red cell volume distribution width in patients with bone marrow metastases. J Clin Pathol 41:1246–1246.  https://doi.org/10.1136/jcp.41.11.1246 CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Sharma U, Pal D, Prasad R (2014) Alkaline Phosphatase: An Overview. Indian J Clin Biochem 29:269–278.  https://doi.org/10.1007/s12291-013-0408-y CrossRefPubMedGoogle Scholar
  37. 37.
    Hoylaerts MF, Manes T, Millán JL (1997) Mammalian Alkaline Phosphatases Are Allosteric Enzymes. J Biol Chem 272:22781–22787.  https://doi.org/10.1074/jbc.272.36.22781 CrossRefPubMedGoogle Scholar
  38. 38.
    Fishman WH (1990) Alkaline phosphatase isozymes: recent progress. Clin Biochem 23:99–104.  https://doi.org/10.1016/0009-9120(90)80019-F CrossRefPubMedGoogle Scholar
  39. 39.
    Pavkovic B, Nenadic LK, Brankovic M et al (2015) P-120 * Serum alkaline phosphatase level as an early diagnostic tool in colorectal cancer. Ann Oncol 26:iv34–iv34.  https://doi.org/10.1093/annonc/mdv233.120 CrossRefGoogle Scholar
  40. 40.
    Ji F, Fu S-J, Guo Z-Y et al (2016) Prognostic value of combined preoperative lactate dehydrogenase and alkaline phosphatase levels in patients with resectable pancreatic ductal adenocarcinoma. Medicine 95:e4065.  https://doi.org/10.1097/MD.0000000000004065 CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Tan P, Xie N, Ai J et al (2018) The prognostic significance of albumin-to-alkaline phosphatase ratio in upper tract urothelial carcinoma. Sci Rep 8:12311.  https://doi.org/10.1038/s41598-018-29833-5 CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Ren H-Y, Sun L-L, Li H-Y, Ye Z-M (2015) Prognostic significance of serum alkaline phosphatase level in osteosarcoma: a meta-analysis of published data. Biomed Res Int 2015:1–11.  https://doi.org/10.1155/2015/160835 CrossRefGoogle Scholar
  43. 43.
    Rao SR, Snaith AE, Marino D et al (2017) Tumour-derived alkaline phosphatase regulates tumour growth, epithelial plasticity and disease-free survival in metastatic prostate cancer. Br J Cancer 116:227–236.  https://doi.org/10.1038/bjc.2016.402 CrossRefPubMedGoogle Scholar
  44. 44.
    Ohno I, Mitsunaga S, Nakachi K et al (2011) Clinical significance of serum alkaline phosphatase level in advanced pancreatic cancer. J Clin Oncol 29:183–183.  https://doi.org/10.1200/jco.2011.29.4_suppl.183 CrossRefGoogle Scholar
  45. 45.
    Singh AK, Pandey A, Tewari M et al (2013) Advanced stage of breast cancer hoist alkaline phosphatase activity: risk factor for females in India. 3 Biotech 3:517–520.  https://doi.org/10.1007/s13205-012-0113-1 CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Keshaviah A, Dellapasqua S, Rotmensz N et al (2006) CA15-3 and alkaline phosphatase as predictors for breast cancer recurrence: a combined analysis of seven International Breast Cancer Study Group trials. Ann Oncol 18:701–708.  https://doi.org/10.1093/annonc/mdl492 CrossRefGoogle Scholar
  47. 47.
    Chang TC, Wang JK, Hung MW et al (1994) Regulation of the expression of alkaline phosphatase in a human breast cancer cell line. Biochem J 303:199–205.  https://doi.org/10.1042/bj3030199 CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Kato M, Brijlall D, Adler SA et al (1992) Effect of hyperosmolality on alkaline phosphatase and stress-response protein 27 of MCF-7 breast cancer cells. Breast Cancer Res Treat 23:241–249.  https://doi.org/10.1007/BF01833521 CrossRefPubMedGoogle Scholar
  49. 49.
    Chalbos D (1983) 397 Progestin-regulated proteins released by the T47D human breast cancer cell line. J Steroid Biochem 19:132.  https://doi.org/10.1016/0022-4731(83)91897-6 CrossRefGoogle Scholar
  50. 50.
    Tsai L-C, Hung M-W, Chen Y-H et al (2000) Expression and regulation of alkaline phosphatases in human breast cancer MCF-7 cells: Alkaline phosphatases in MCF-7 cells. Eur J Biochem 267:1330–1339.  https://doi.org/10.1046/j.1432-1327.2000.01100.x CrossRefPubMedGoogle Scholar
  51. 51.
    Pelizzari G, Gerratana L, Basile D et al (2018) Prognostic role of alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) in metastatic breast cancer (MBC) patients: First clues for cost-effective biomarkers. J Clin Oncol 36:e13079–e13079.  https://doi.org/10.1200/JCO.2018.36.15_suppl.e13079 CrossRefGoogle Scholar
  52. 52.
    Chen B, Dai D, Tang H et al (2016) Pre-treatment serum alkaline phosphatase and lactate dehydrogenase as prognostic factors in triple negative breast cancer. J Cancer 7:2309–2316.  https://doi.org/10.7150/jca.16622 CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Mayne PD, Thakrar S, Rosalki SB et al (1987) Identification of bone and liver metastases from breast cancer by measurement of plasma alkaline phosphatase isoenzyme activity. J Clin Pathol 40:398–403.  https://doi.org/10.1136/jcp.40.4.398 CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Ben-Arie A, Hagay Z, Ben-Hur H et al (1999) Elevated serum alkaline phosphatase may enable early diagnosis of ovarian cancer. Eur J Obstet Gynecol Reprod Biol 86:69–71.  https://doi.org/10.1016/S0301-2115(99)00054-8 CrossRefPubMedGoogle Scholar
  55. 55.
    Benham FJ, Povey MS, Harris H (1978) Placental-like alkaline phosphatase in malignant and benign ovarian tumors. Clin Chim Acta 86:201–215.  https://doi.org/10.1016/0009-8981(78)90134-1 CrossRefPubMedGoogle Scholar
  56. 56.
    Ind T, Iles R, Desouza K et al (1995) Serum placental-type alkaline-phosphatase levels in patients with epithelial ovarian-carcinoma. Int J Oncol.  https://doi.org/10.3892/ijo.6.2.385 CrossRefPubMedGoogle Scholar
  57. 57.
    Orsaria M, Londero AP, Marzinotto S et al (2017) Placental type alkaline phosphatase tissue expression in ovarian serous carcinoma. Cancer Biomarkers 17:479–486.  https://doi.org/10.3233/CBM-160665 CrossRefGoogle Scholar
  58. 58.
    Vergote I, Onsrud M, Nustad K (1987) Placental alkaline phosphatase as a tumor marker in ovarian cancer. Int J Gynecol Obstet 25:485–485.  https://doi.org/10.1016/0020-7292(87)90077-4 CrossRefGoogle Scholar
  59. 59.
    Jurisic V, Radenkovic S, Konjevic G (2015) The actual role of LDH as tumor marker, biochemical and clinical aspects. In: Scatena R (ed) Advances in cancer biomarkers. Springer, Dordrecht, pp 115–124CrossRefGoogle Scholar
  60. 60.
    Vesell ES, Bearn AG (1961) Isozymes of lactic dehydrogenase in human tissues*. J Clin Investig 40:586–591.  https://doi.org/10.1172/JCI104287 CrossRefPubMedGoogle Scholar
  61. 61.
    Miao P, Sheng S, Sun X et al (2013) Lactate dehydrogenase a in cancer: a promising target for diagnosis and therapy: LDHA in Cancer. IUBMB Life 65:904–910.  https://doi.org/10.1002/iub.1216 CrossRefPubMedGoogle Scholar
  62. 62.
    Agrawal A, Gandhe MB, Gupta D, Reddy MV (2016) Preliminary study on serum lactate dehydrogenase (LDH)-prognostic biomarker in carcinoma breast. J Clin Diagn Res 10:BC06.  https://doi.org/10.7860/JCDR/2016/17111.7364 CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Schneider D, Halperin R, Langer R et al (1997) Peritoneal fluid lactate dehydrogenase in ovarian cancer. Gynecol Oncol 66:399–404.  https://doi.org/10.1006/gyno.1997.4792 CrossRefPubMedGoogle Scholar
  64. 64.
    Williams J (2008) The Declaration of Helsinki and public health. Bull World Health Organ 86:650–651.  https://doi.org/10.2471/BLT.08.050955 CrossRefPubMedPubMedCentralGoogle Scholar
  65. 65.
    Korean Medical Association (2014) World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. J Korean Med Assoc 57:899.  https://doi.org/10.5124/jkma.2014.57.11.899 CrossRefGoogle Scholar
  66. 66.
    Rumble BA (1979) Quality of commercial optimized reagents for measurement of alkaline phosphatase activity in human serum. Pathology 11:332.  https://doi.org/10.1016/S0031-3025(16)40006-1 CrossRefGoogle Scholar
  67. 67.
    Henry RJ, Chiamori N, Golub OJ, Berkman S (1960) Revised spectrophotometric methods for the determination of glutamic-oxalacetic transaminase, glutamic-pyruvic transaminase, and lactic acid dehydrogenase. Am J Clin Pathol 34:381–398.  https://doi.org/10.1093/ajcp/34.4_ts.381 CrossRefPubMedGoogle Scholar
  68. 68.
    Jia W, Wu J, Jia H et al (2015) The peripheral blood neutrophil-to-lymphocyte ratio is superior to the lymphocyte-to-monocyte ratio for predicting the long-term survival of triple-negative breast cancer patients. PLoS ONE 10:e0143061.  https://doi.org/10.1371/journal.pone.0143061 CrossRefPubMedPubMedCentralGoogle Scholar
  69. 69.
    Azab B, Bhatt VR, Phookan J et al (2012) Usefulness of the neutrophil-to-lymphocyte ratio in predicting short- and long-term mortality in breast cancer patients. Ann Surg Oncol 19:217–224.  https://doi.org/10.1245/s10434-011-1814-0 CrossRefPubMedGoogle Scholar
  70. 70.
    Wen J, Ye F, Huang X et al (2015) Prognostic significance of preoperative circulating monocyte count in patients with breast cancer: based on a large cohort study. Medicine 94:e2266.  https://doi.org/10.1097/MD.0000000000002266 CrossRefPubMedPubMedCentralGoogle Scholar
  71. 71.
    Krenn-Pilko S, Langsenlehner U, Thurner E-M et al (2014) The elevated preoperative platelet-to-lymphocyte ratio predicts poor prognosis in breast cancer patients. Br J Cancer 110:2524–2530.  https://doi.org/10.1038/bjc.2014.163 CrossRefPubMedPubMedCentralGoogle Scholar
  72. 72.
    Krenn-Pilko S, Langsenlehner U, Stojakovic T et al (2015) An elevated preoperative plasma fibrinogen level is associated with poor disease-specific and overall survival in breast cancer patients. Breast 24:667–672.  https://doi.org/10.1016/j.breast.2015.08.003 CrossRefPubMedGoogle Scholar
  73. 73.
    Tabassum U, Reddy O, Mukherjee G (2012) Elevated serum haptoglobin is associated with clinical outcome in triple-negative breast cancer patients. Asian Pac J Cancer Prev 13:4541–4544.  https://doi.org/10.7314/APJCP.2012.13.9.4541 CrossRefPubMedGoogle Scholar
  74. 74.
    Sicking I, Edlund K, Wesbuer E et al (2014) Prognostic influence of pre-operative C-reactive protein in node-negative breast cancer patients. PLoS ONE 9:e111306.  https://doi.org/10.1371/journal.pone.0111306 CrossRefPubMedPubMedCentralGoogle Scholar
  75. 75.
    Yamamoto K, Awogi T, Okuyama K, Takahashi N (2003) Nuclear localization of alkaline phosphatase in cultured human cancer cells. Med Electron Microsc 36:47–51.  https://doi.org/10.1007/s007950300006 CrossRefPubMedGoogle Scholar
  76. 76.
    Xu X-S, Miao R-C, Zhang L-Q et al (2015) Model based on alkaline phosphatase and gamma-glutamyltransferase for gallbladder cancer prognosis. Asian Pac J Cancer Prev 16:6255–6259.  https://doi.org/10.7314/APJCP.2015.16.15.6255 CrossRefPubMedGoogle Scholar
  77. 77.
    Skillen AW, Fifield RD, Sheraidah GS (1972) Serum alkaline phosphatase isoenzyme patterns in disease. Clin Chim Acta 40:21–25.  https://doi.org/10.1016/0009-8981(72)90246-X CrossRefPubMedGoogle Scholar
  78. 78.
    Stieber P, Nagel D, Ritzke C et al (1992) Significance of Bone Alkaline Phosphatase, CA 15 – 3 and CEA in the Detection of Bone Metastases During the Follow-Up of Patients Suffering from Breast Carcinoma. Clin Chem Lab Med.  https://doi.org/10.1515/cclm.1992.30.12.809 CrossRefGoogle Scholar
  79. 79.
    Ramaswamy G, Rao VR, Krishnamoorthy L et al (2000) Serum levels of bone alkaline phosphatase in breast and prostate cancers with bone metastasis. Indian J Clin Biochem 15:110–113.  https://doi.org/10.1007/BF02883737 CrossRefPubMedPubMedCentralGoogle Scholar
  80. 80.
    Mishra S, Sharma DC, Sharma P (2004) Studies of biochemical parameters in breast cancer with and without metastasis. Indian J Clin Biochem 19:71–75.  https://doi.org/10.1007/BF02872394 CrossRefPubMedPubMedCentralGoogle Scholar
  81. 81.
    Choudhari A, Desai P, Indumati V, Kadi S (2013) Activities of serum Ada, GGT and alp in carcinoma breast-a case-control study for diagnostic and prognostic significance. Indian J Med Sci 67:123.  https://doi.org/10.4103/0019-5359.122740 CrossRefPubMedGoogle Scholar
  82. 82.
    Kim JM, Kwon CHD, Joh J-W et al (2013) The effect of alkaline phosphatase and intrahepatic metastases in large hepatocellular carcinoma. World J Surg Oncol 11:40.  https://doi.org/10.1186/1477-7819-11-40 CrossRefPubMedPubMedCentralGoogle Scholar
  83. 83.
    Han KS, Hong SJ (2014) Serum alkaline phosphatase differentiates prostate-specific antigen flare from early disease progression after docetaxel chemotherapy in castration-resistant prostate cancer with bone metastasis. J Cancer Res Clin Oncol 140:1769–1776.  https://doi.org/10.1007/s00432-014-1710-7 CrossRefPubMedGoogle Scholar
  84. 84.
    Tong P-J, Yin L-M, Du W-X et al (2014) Serum bone-specific alkaline phosphatase as a biomarker for osseous metastases in patients with malignant carcinomas: a systematic review and meta-analysis. J Cancer Res Ther 10:140.  https://doi.org/10.4103/0973-1482.145842 CrossRefGoogle Scholar
  85. 85.
    Augoff K, Hryniewicz-Jankowska A, Tabola R (2015) Lactate dehydrogenase 5: an old friend and a new hope in the war on cancer. Cancer Lett 358:1–7.  https://doi.org/10.1016/j.canlet.2014.12.035 CrossRefPubMedGoogle Scholar
  86. 86.
    Han X, Sheng X, Jones HM et al (2015) Evaluation of the anti-tumor effects of lactate dehydrogenase inhibitor galloflavin in endometrial cancer cells. J Hematol Oncol 8:2.  https://doi.org/10.1186/s13045-014-0097-x CrossRefPubMedPubMedCentralGoogle Scholar
  87. 87.
    Le Scodan R, Massard C, Jouanneau L et al (2012) Brain metastases from breast cancer: proposition of new prognostic score including molecular subtypes and treatment. J Neuro Oncol 106:169–176.  https://doi.org/10.1007/s11060-011-0654-x CrossRefGoogle Scholar
  88. 88.
    Nieder C, Dalhaug A, Haukland E et al (2015) Tumor marker analyses in patients with brain metastases: patterns of practice and implications for survival prediction research. Tumor Biolo 36:6471–6476.  https://doi.org/10.1007/s13277-015-3337-y CrossRefGoogle Scholar
  89. 89.
    Passardi A, Scarpi E, Tamberi S et al (2015) Impact of pre-treatment lactate dehydrogenase levels on prognosis and bevacizumab efficacy in patients with metastatic colorectal cancer. PLoS ONE 10:e0134732.  https://doi.org/10.1371/journal.pone.0134732 CrossRefPubMedPubMedCentralGoogle Scholar
  90. 90.
    Scartozzi M, Giampieri R, Maccaroni E et al (2012) Pre-treatment lactate dehydrogenase levels as predictor of efficacy of first-line bevacizumab-based therapy in metastatic colorectal cancer patients. Br J Cancer 106:799–804.  https://doi.org/10.1038/bjc.2012.17 CrossRefPubMedPubMedCentralGoogle Scholar
  91. 91.
    Brown JE, Cook RJ, Lipton A, Coleman RE (2012) Serum lactate dehydrogenase is prognostic for survival in patients with bone metastases from breast cancer: a retrospective analysis in bisphosphonate-treated patients. Clin Cancer Res 18:6348–6355.  https://doi.org/10.1158/1078-0432.CCR-12-1397 CrossRefGoogle Scholar
  92. 92.
    Shen J, Ran ZH, Zhang Y et al (2009) Biomarkers of altered coagulation and fibrinolysis as measures of disease activity in active inflammatory bowel disease: a gender-stratified, cohort analysis. Thromb Res 123:604–611.  https://doi.org/10.1016/j.thromres.2008.04.004 CrossRefPubMedGoogle Scholar
  93. 93.
    Plantureux L, Mège D, Crescence L et al (2018) Impacts of cancer on platelet production, activation and education and mechanisms of cancer-associated thrombosis. Cancers 10:441.  https://doi.org/10.3390/cancers10110441 CrossRefPubMedCentralGoogle Scholar
  94. 94.
    Lin RJ, Afshar-Kharghan V, Schafer AI (2014) Paraneoplastic thrombocytosis: the secrets of tumor self-promotion. Blood 124:184–187.  https://doi.org/10.1182/blood-2014-03-562538 CrossRefPubMedPubMedCentralGoogle Scholar
  95. 95.
    Kayacan O, Karnak D, Beder S et al (2006) Impact of TNF-α and IL-6 levels on development of cachexia in newly diagnosed NSCLC patients. Am J Clin Oncol 29:328–335.  https://doi.org/10.1097/01.coc.0000221300.72657.e0 CrossRefPubMedGoogle Scholar
  96. 96.
    Cain CJ, Manilay JO (2013) Hematopoietic stem cell fate decisions are regulated by Wnt antagonists: comparisons and current controversies. Exp Hematol 41:3–16.  https://doi.org/10.1016/j.exphem.2012.09.006 CrossRefPubMedGoogle Scholar
  97. 97.
    Sulzbacher I, Birner P, Trieb K et al (2003) Expression of platelet-derived growth factor-AA is associated with tumor progression in osteosarcoma. Mod Pathol 16:66–71.  https://doi.org/10.1097/01.MP.0000043522.76788.0A CrossRefPubMedGoogle Scholar
  98. 98.
    Seretis (2013) Is red cell distribution width a novel biomarker of breast cancer activity? Data from a pilot study. J Clin Med Res 5:121–126.  https://doi.org/10.4021/jocmr1214w CrossRefPubMedPubMedCentralGoogle Scholar
  99. 99.
    Shrihari TG (2017) Inflammation-related cancer or cancer-related inflammation. Eur Res J 4: 1–5.  https://doi.org/10.18621/eurj.312327 CrossRefGoogle Scholar
  100. 100.
    Balkwill FR, Mantovani A (2012) Cancer-related inflammation: common themes and therapeutic opportunities. Semin Cancer Biol 22:33–40.  https://doi.org/10.1016/j.semcancer.2011.12.005 CrossRefPubMedGoogle Scholar
  101. 101.
    Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144:646–674.  https://doi.org/10.1016/j.cell.2011.02.013 CrossRefPubMedPubMedCentralGoogle Scholar
  102. 102.
    Allen MD, Jones LJ (2015) The role of inflammation in progression of breast cancer: friend or foe? (Review). Int J Oncol 47:797–805.  https://doi.org/10.3892/ijo.2015.3075 CrossRefPubMedGoogle Scholar
  103. 103.
    Demirkol S, Balta S, Cakar M et al (2013) Red cell distribution width: a novel inflammatory marker in clinical practice. Cardiol J 20:209.  https://doi.org/10.5603/CJ.2013.0037 CrossRefPubMedGoogle Scholar
  104. 104.
    Periša V, Zibar L, Sinčić-Petričević J et al (2015) Red blood cell distribution width as a simple negative prognostic factor in patients with diffuse large B-cell lymphoma: a retrospective study. Croatian Med J 56:334–343.  https://doi.org/10.3325/cmj.2015.56.334 CrossRefGoogle Scholar
  105. 105.
    Riedl J, Posch F, Königsbrügge O et al (2014) Red cell distribution width and other red blood cell parameters in patients with cancer: association with risk of venous thromboembolism and mortality. PLoS ONE 9:e111440.  https://doi.org/10.1371/journal.pone.0111440 CrossRefPubMedPubMedCentralGoogle Scholar
  106. 106.
    Fu P, Yao M, Liu Y et al (2014) Prognostic value of preoperative inflammatory markers in Chinese patients with breast cancer. Onco Targets Ther 7:1743–1752.  https://doi.org/10.2147/OTT.S69657 CrossRefPubMedPubMedCentralGoogle Scholar
  107. 107.
    Huang D-P, Ma R-M, Xiang Y-Q (2016) Utility of red cell distribution width as a prognostic factor. Young Breast Cancer Patients Med 95:e3430.  https://doi.org/10.1097/MD.0000000000003430 CrossRefGoogle Scholar
  108. 108.
    Moon H, Roh J-L, Lee S et al (2016) Prognostic value of nutritional and hematologic markers in head and neck squamous cell carcinoma treated by chemoradiotherapy. Radiother Oncol 118:330–334.  https://doi.org/10.1016/j.radonc.2015.10.029 CrossRefPubMedGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Biochemistry Division, Chemistry Department, Faculty of ScienceZagzig UniversityZagazigEgypt

Personalised recommendations