1.
Naito Y, Saito K, Shiiba K, et al: CD8+ T Cells Infiltrated within Cancer Cell Nests
as a Prognostic Factor in Human Colorectal Cancer. Cancer Res 1998; 58: 3491–3494.
2.
Eiichi S, Sara H, Olson J, et al: Intraepithelial CD8 Tumor-Infiltrating Lymphocytes
and a High CD8/Regulatory T Cell Ratio Are Associated with Favorable Prognosis
in Ovarian Cancer. Proc. Natl Acad. Sci. USA 2005; 102: 18538–18543.
https://doi.org/10.1073/pnas.0509182102.
3.
Marchi F, Missale F, Incandela F, et al: Prognostic Significance of Peripheral T-Cell
Subsets in Laryngeal Squamous Cell Carcinoma. Laryngoscope Investig. Otolaryngol
2019; 4: 513–519. https://doi.org/10.1002/lio2.304.
4.
Delayre T, Guilbaud T, Resseguier N, et al: Prognostic Impact of TumourInfiltrating Lymphocytes and Cancer-Associated Fibroblasts in Patients with
Pancreatic Adenocarcinoma of the Body and Tail Undergoing Resection. Br. J. Surg
2020; 107: 720–733. https://doi.org/10.1002/bjs.11434.
5.
Kim H.I., Kim H, Cho H.W., et al: The Ratio of Intra-Tumoral Regulatory T Cells
(Foxp3+)/Helper T Cells (CD4+) Is a Prognostic Factor and Associated with
Recurrence Pattern in Gastric Cardia Cancer. J. Surg. Oncol 2011; 104: 728–733.
https://doi.org/10.1002/jso.22038.
6.
Park J.Y., Sung J.Y., Lee J, et al: Polarized CD163+ Tumor-Associated Macrophages
Are Associated with Increased Angiogenesis and CXCL12 Expression in Gastric
30
Cancer.
Clin.
Res.
Hepatol.
Gastroenterol
2016;
40:
357–365.
https://doi.org/10.1016/j.clinre.2015.09.005.
7.
Zheng X, Weigert A, Reu S, et al: Spatial Density and Distribution of TumorAssociated Macrophages Predict Survival in Non-Small Cell Lung Carcinoma.
Cancer Res 2020; 80: 4414–4425. https://doi.org/10.1158/0008-5472.CAN-20-0069.
8.
Lee J, Jung Y.Y., Lee J.H., et al: The Prognostic Value of Sex-Determining Region
Y-Box 2 and CD8+ Tumor-Infiltrating Lymphocytes in Limited-Stage Small-Cell
Lung Cancer. Oncology 2021; 99: 528–538. https://doi.org/10.1159/000516444.
9.
Usó M, Jantus-Lewintre E, Bremnes R.M., et al: Analysis of the Immune
Microenvironment in Resected Non-Small Cell Lung Cancer: The Prognostic
Value of Different T Lymphocyte Markers. Oncotarget 2016; 7: 52849–52861.
https://doi.org/10.18632/oncotarget.10811.
10. Cai L, Michelakos T, Deshpande V, et al: Role of Tumor-Associated Macrophages
in the Clinical Course of Pancreatic Neuroendocrine Tumors (PanNETs). Clin.
Cancer Res 2019; 25: 2644–2655. https://doi.org/10.1158/1078-0432.CCR-18-1401.
11. Vigano L, Soldani C, Franceschini B, et al: Tumor-Infiltrating Lymphocytes and
Macrophages in Intrahepatic Cholangiocellular Carcinoma. Impact on Prognosis
after
Complete
Surgery.
J.
Gastrointest.
https://doi.org/10.1007/s11605-019-04111-5.
31
Surg
2019;
23:
2216–2224.
12. da Silva A, Bowden M, Zhang S, et al: Characterization of the Neuroendocrine
Tumor
Immune
Microenvironment.
Pancreas
2018;
47:
1123–1129.
https://doi.org/10.1097/MPA.0000000000001150.
13. Wang J, Jia Y, Wang N, et al: The Clinical Significance of Tumor-Infiltrating
Neutrophils and Neutrophil-to-CD8+ Lymphocyte Ratio in Patients with
Resectable Esophageal Squamous Cell Carcinoma. J. Transl. Med 2014; 12: 7.
https://doi.org/10.1186/1479-5876-12-7.
14. Steele K.E., Tan T.H., Korn R, et al: Measuring Multiple Parameters of CD8+
Tumor-Infiltrating Lymphocytes in Human Cancers by Image Analysis. J.
Immunother. Cancer 2018; 6: 20. https://doi.org/10.1186/s40425-018-0326-x.
15. Kim, J. Y., Hong, S. M., Ro, J. Y: Recent updates on grading and classification of
neuroendocrine
tumors.
Ann
Diagn
Pathol
2017;
11-16.
https://doi.org/10.1016/j.anndiagpath.2017.04.005.
16. Öberg, K, Modlin, I.M., De Herder W, et al: Consensus on Biomarkers for
Neuroendocrine
Tumour
Disease.
Lancet
Oncol
2015;
16:
e435–e446.
https://doi.org/10.1016/S1470-2045(15)00186-2.
17. Dasari, A, Shen C, Halperin D, et al: Trends in the Incidence, Prevalence, and
Survival Outcomes in Patients with Neuroendocrine Tumors in the United States.
JAMA Oncol 2017; 3: 1335–1342. https://doi.org/10.1001/jamaoncol.2017.0589.
18. Yang, M. W, Fu, X. L, Jiang, Y. S. et al: Clinical significance of programmed death
32
1/programmed death ligand 1 pathway in gastric neuroendocrine carcinomas.
World J Gastroenterol 2019; 25: 1684-1696. https://doi.org/10.3748/wjg.v25.i14.1684.
19. Grosse C, Noack P, Silye R: Accuracy of Grading Pancreatic Neuroendocrine
Neoplasms with Ki-67 Index in Fine-Needle Aspiration Cellblock Material.
Cytopathology 2019; 30: 187–193. https://doi.org/10.1111/cyt.12643.
20. Hamilton S.R., Aaltonen L.A: World Health Organization Classification of
Tumours. Pathology and Genetics of Tumours of the Digestive System.
International Agency for Research on Cancer (IARC) Press, Lyon, France, 2000.
21. DeLellis R.A., Lloyd R.V., Heitz P.U: World Health Organization of Tumours.
Pathology and Genetics of Tumours of Endocrine Organs. International Agency for
Research on Cancer (IARC) Press, Lyon, France, 2004.
22. Bosman T, Carneiro F, Hruban N.D: World Health Organization of Tumours.
WHO Classification of Tumours of the Digestive System. International Agency for
Research on Cancer (IARC) Press, Lyon, France, 2010.
23. Lloyd, R.V.; Osamura R.Y., Klöppel G: World Health Organization of Tumours.
WHO Classification of Tumours of Endocrine Organs, 4th ed, International Agency
for Research on Cancer (IARC) Press, Lyon, France, 2017.
24. Frizziero, M, Wang X, Chakrabarty B, et al: Retrospective Study on Mixed
Neuroendocrine Non-Neuroendocrine Neoplasms from Five European Centres.
World J. Gastroenterol 2019; 25: 5991–6005. https://doi.org/10.3748/wjg.v25.i39.5991.
33
25. Woischke, C: In-depth mutational analyses of colorectal neuroendocrine
carcinomas with adenoma or adenocarcinoma components. Mod Pathol 2017; 95103. https://doi.org/ 10.1038/modpathol.2016.150.
26. Kim, K: Genetic evidence for the multi-step progression of mixed glandularneuroendocrine gastric carcinomas. Virchows Arch 2002; 1: 85-93. https://doi.org/
10.1007/s004280100540.
27. Shia J: Is non-small cell type high-grade neuroendocrine carcinoma of the tubular
gastrointestinal tract a distinct disease entity? Am J Surg Pathol 2008; 32: 719–731.
https://doi.org/ 10.1097/PAS.0b013e318159371c.
28. Karkouche R: Colorectal neuroendocrine carcinomas and adenocarcinomas share
oncogenic pathways. A clinico-pathologic study of 12 cases. Eur J Gastroenterol
Hepatol 2012;
24:
1430–1437. https://doi.org/ 10.1097/MEG.0b013e3283583c87.
29. La Rosa S, Marando A, Sessa F, Capella C: Mixed Adenoneuroendocrine
Carcinomas (MANECs) of the Gastrointestinal Tract: An Update. Cancers 2012; 4:
11–30. https://doi.org/10.3390/cancers4010011.
30. La Rosa S, Marando A, Furlan D, et al: Colorectal Poorly Differentiated
Neuroendocrine Carcinomas and Mixed Adenoneuroendocrine Carcinomas:
Insights into the Diagnostic Immunophenotype, Assessment of Methylation
Profile, and Search for Prognostic Markers. Am. J. Surg. Pathol 2012; 36: 601–611.
https://doi.org/10.1097/PAS.0b013e318242e21c.
34
31. Jiang M, Tan Y, Li X, et al: Clinicopathological Features and Prognostic Factors of
Colorectal Neuroendocrine Neoplasms. Gastroenterol Res Pract 2017; 4206172.
https://doi.org/10.1155/2017/4206172.
32. Shi H, Qi C, Meng L, et al: Do Neuroendocrine Carcinomas and Mixed
Neuroendocrine-Non-Neuroendocrine Neoplasm of the Gastrointestinal Tract
Have the Same Prognosis? A SEER Database Analysis of 12,878 Cases. Ther. Adv.
Endocrinol.
Metab
2020;
11:
2042018820938304.
https://doi.org/10.1177/2042018820938304.
33. Zhang, P., Li, Z., Li, J. et al: Clinicopathological features and lymph node and
distant metastasis patterns in patients with gastroenteropancreatic mixed
neuroendocrine-non-neuroendocrine neoplasm. Cancer Med 2021; 14: 4855-4863.
https://doi.org/ 10.1002/cam4.4031.
34. Xu, H., Zhao, Z., Zhu, Y: CD8+ T Cells Infiltrated within Cancer Cell Nests as a
Prognostic Factor in Human Colorectal Cancer. Endocrine 2022; 2: 474–483. https://
10.1007/s12020-022-02992-2.
35. Chen I, Zhang D, Velez M, et al: Poorly differentiated neuroendocrine carcinomas
of the gastrointestinal tract: A single-institute study of 43 cases. Pathol Res Pract
2021; 226: https://doi.org/10.1016/j.prp.2021.153614.
36. Hendry S, Salgado R, Gevaert T, et al: Assessing Tumor-Infiltrating Lymphocytes
in Solid Tumors: A Practical Review for Pathologists and Proposal for a
Standardized Method from the International Immunooncology Biomarkers
35
Working Group: Part 1: Assessing the Host Immune Response, TILs in Invasive
Breast Carcinoma and Ductal Carcinoma in Situ, Metastatic Tumor Deposits and
Areas
for
Further
Research.
Adv.
Anat.
Pathol
2017;
24:
235–251.
https://doi.org/10.1097/PAP.0000000000000162.
37. Challoner B.R., von Loga K, Woolston A, et al: Computational Image Analysis of
T-Cell Infiltrates in Resectable Gastric Cancer: Association with Survival and
Molecular
Subtypes.
J.
Natl
Cancer
Inst
2021;
113:
88–98.
https://doi.org/10.1093/jnci/djaa051.
38. Heo Y.J., Lee T, Byeon S.J., et al: Digital Image Analysis in Pathologist-Selected
Regions of Interest Predicts Survival More Accurately than Whole-Slide Analysis:
A Direct Comparison Study in 153 Gastric Carcinomas. J. Pathol. Clin. Res 2021; 7:
42–51. https://doi.org/10.1002/cjp2.179.
39. Jäntti T., Luhtala S, Mäenpää J, et al: Characterization of Immunoreactivity with
Whole-Slide Imaging and Digital Analysis in High-Grade Serous Ovarian Cancer.
Tumour Biol 2020; 42: 1010428320971404. https://doi.org/10.1177/1010428320971404.
40. Silva M.A., Triltsch N, Leis S, et al: Biomarker Recommendation for PD-1/PD-L1
Immunotherapy Development in Pediatric Cancer Based on Digital Image
Analysis of PD-L1 and Immune Cells. J. Pathol. Clin. Res 2020; 6: 124–137.
https://doi.org/10.1002/cjp2.152.
36
41. Felip E: Adjuvant atezolizumab after adjuvant chemotherapy in resected stage IB–
IIIA non-small-cell lung cancer (IMpower010): a randomised, multicentre, openlabel, phase 3 trial. The Lancet 2021; 398: 1344-1357.
42. Tamaki K, Moriya T, Sato Y, et al: Vasohibin-1 in human breast carcinoma: a
potential negative feedback regulator of angiogenesis. Cancer Sci 2009; 100: 88–
94. https://doi.org/ 10.1111/j.1349-7006.2008.01015.x.
43. Nakagawa S, Miki Y, Miyashita M, et al: Tumor microenvironment in invasive
lobular carcinoma: possible therapeutic targets. Breast Cancer Res 2016; 155, 65-75.
44. Konno-Kumagai T, Fujishima F, Nakamura Y, et al: Programmed death-1 Ligands
and Tumor Infiltrating T Lymphocytes in Primary and Lymph Node Metastasis of
Esophageal
Cancer
Patients.
Dis.
Esophagus
2019;
32:
https://doi.org/10.1093/dote/doy063.
45. Katz S.C., Bamboat Z.M., Maker A.V., et al: Regulatory T cell infiltration predicts
outcome following resection of colorectal cancer liver metastases. Ann. Surg. Oncol
2013; 20: 946–955. https://doi.org/10.1245/s10434-012-2668-9.
46. Lim Y.J., Koh J, Kim K, et al: High ratio of programmed cell death protein 1 (PD1) (+)/CD8(+) tumor-infiltrating lymphocytes identifies a poor prognostic subset of
extrahepatic
bile
chemoradiotherapy.
duct
cancer
undergoing
Radiother.
Oncol
https://doi.org/10.1016/j.radonc.2015.07.003.
37
surgery
2015;
plus
117:
adjuvant
165–170.
47. Pardoll D.M: The blockade of immune checkpoints in cancer immunotherapy. Nat.
Rev. Cancer 2012; 12: 252–264. https://doi.org/10.1038/nrc3239.
48. Tartour E, Pere H, Maillere B, et al: Angiogenesis and Immunity: A Bidirectional
Link Potentially Relevant for the Monitoring of Antiangiogenic Therapy and the
Development of Novel Therapeutic Combination with Immunotherapy. Cancer
Metastasis Rev 2011; 30: 83–95. https://doi.org/10.1007/s10555-011-9281-4.
49. Prakhar P, Alvarez-Delvalle J, Keller H, et al: The Small Intestine Epithelium
Exempts Foxp3+ Tregs from Their IL-2 Requirement for Homeostasis and Effector
Function. JCI Insight 2021; 6: https://doi.org/10.1172/jci.insight.149656.
50. Watson Ng W.S., Hampartzoumian T, Lloyd A.R., et al: A Murine Model of
Appendicitis and the Impact of Inflammation on Appendiceal Lymphocyte
Constituents. Clin. Exp. Immunol 2007; 150: 169–178. https://doi.org/10.1111/j.13652249.2007.03463.x.
51. Garcia C.R., Sorbye H, Baudin E, et al: Enets Consensus Guidelines for High-Grade
Gastroenteropancreatic
Carcinomas.
Neuroendocrine
Neuroendocrinology
Tumors
2017;
and
103:
Neuroendocrine
186–194.
https://doi.org/10.1159/000443172.
52. Taube, J. M., Galon, J., Sholl, L. M. et al: Implications of the tumor immune
microenvironment for staging and therapeutics. Mod Pathol 2018; 214-234.
https://doi.org/ 10.1038/modpathol.2017.156.
53. Patel, S. P. Kurzrock, R: PD-L1 Expression as a Predictive Biomarker in Cancer
38
Immunotherapy. Mol Cancer Ther 2015; 14: 847-56. https://doi.org/10.1158/15357163.MCT-14-0983.
54. Sawa-Wejksza K, Dudek A, Lemieszek M, et al: Colon Cancer-Derived
Conditioned Medium Induces Differentiation of THP-1 Monocytes into a Mixed
Population of M1/M2 Cells.
Tumour Biol 2018; 40: 1010428318797880.
https://doi.org/10.1177/1010428318797880.
55. Zeng Y.J., Lai W, Wu H, et al: Neuroendocrine-Like Cells -Derived CXCL10 and
CXCL11 Induce the Infiltration of Tumor-Associated Macrophage Leading to the
Poor Prognosis of Colorectal Cancer. Oncotarget 2016; 7: 27394–27407.
https://doi.org/10.18632/oncotarget.8423.
56. Lee, G. T. Kwon, S. J. Lee, J. H. et al: Macrophages induce neuroendocrine
differentiation of prostate cancer cells via BMP6-IL6 Loop. Prostate 2011; 14: 152537. https://doi.org/10.1002/pros.21369.
57. Ge, D. Gao, A. C. Zhang, Q. et al: LNCaP prostate cancer cells with autocrine
interleukin-6 expression are resistant to IL-6-induced neuroendocrine
differentiation due to increased expression of suppressors of cytokine signaling.
Prostate 2012; 72: 1306-16. https://doi.org/10.1002/pros.22479.
58. Matsuda Y, Hagio M, Ishiwata T: Nestin: a novel angiogenesis marker and
possible target for tumor angiogenesis, World J Gastroenterol 2013; 19: 42-8.
https://doi.org/10.3748/wjg.v19.i1.42
39
59. Jain RK: Normalizing tumor vasculature with anti-angiogenic therapy: a new
paradigm
for
combination
therapy.
Nat
Med
2001;
7:
987-989.
https://doi.org/10.1007/s11864-021-00834-3.
60. Jain RK: Normalization of tumor vasculature: an emerging concept in
antiangiogenic therapy. Science 2005; 307: 58-62. https://doi.org/
10.1126/science.1104819.
61. Magnussen, A. L. Mills, I. G: Vascular normalisation as the stepping stone into
tumour microenvironment transformation. Br J Cancer 2021; 125: 324-336.
https://doi.org/ 10.1038/s41416-021-01330-z.
62. Maria Cristina H, Cattini, L., Facchini, A: Possible prognostic role of IL-17R in
osteosarcoma. J Cancer Res Clin Oncol 2007; 133: 1017–1021. https://doi.org/
10.1007/s00432-007-0296-8.
IX.
図の説明
図 1. 免疫組織学的染色の結果を示す．(a)CD3，(b)CD4，(c)CD8，(d）CD68，
（e）
CD163，
（f）PD-1，
（g）PD-L1，
（h）Foxp3，
（i）CD31，
（j）vasohibin-1，
（k）Synaptophysin，
（l）Chromogranin A，
（m）INSM1，(n)Nestin，(o)CD31/Nestin 二重染色を示して
いる．(i)(j)(n)では各々CD31，VASH-1，Nestin 陽性の微小血管を矢印で示す．また，
40
(o)では赤色矢印が CD31 陽性の，茶色矢印が Nestin 陽性の微小血管を示す．黒実
線：50μm
図 2. 腫瘍胞巣周囲での TILs や TAMs の評価例を示す (左図は HE 染色，右図は CD8
染色)．腫瘍胞巣と正常間質の境界線を中心に 1mm 以内の領域とした (腫瘍胞巣周囲
領域)．NEN と非 NEN で各々3 領域 (0.75 mm²の円形領域)ずつ測定し，その平均値
を算出した．黒実線：1 mm
図 3. 腫瘍胞巣内での TILs や TAMs の評価例を示す (左図は HE 染色，右図は CD8
染色)．腫瘍胞巣周囲領域よりも腫瘍内側において，NEN と非 NEN で各々3 領域
(0.75 mm²の円形領域)ずつ測定し，その平均値を算出した．黒実線：1 mm
図 4. 非 NEN 領域と NEN 領域それぞれの hot spot での Ki-67 index (%)を図示した
(縦軸：非 NEN 領域，横軸：NEN 領域)．Ki-67 index の範囲は非 NEN 領域で 1～
99％，NEN 領域では 21～98％であった．
図 5. NEN 領域と非 NEN 領域における各抗体陽性を呈する浸潤リンパ球を Wilcoxon
符号付き順位和検定で解析し，各症例に対応するプロット線を引いた
[a)腫瘍胞巣
内 CD3，b)腫瘍胞巣周囲 CD3，c)腫瘍胞巣内 CD4，d)腫瘍胞巣周囲 CD4，e)腫瘍胞
41
巣内 CD8，f)腫瘍胞巣周囲 CD8]．いずれの抗体においても，浸潤したリンパ球は
NEN/非 NEN 間で有意差を認めなかった．点は外れ値を示す．
＊略語：NEN neuroendocrine neoplasm
図 6. NEN 領域と非 NEN 領域における各抗体陽性を呈する浸潤リンパ球を Wilcoxon
符号付順位和検定で解析し，各症例に対応するプロット線を引いた
[a)腫瘍胞巣内
Foxp3，b)腫瘍胞巣周囲 Foxp3，c)腫瘍胞巣内 PD-1，d)腫瘍胞巣周囲 PD-1]．PD-1
陽性リンパ球に関しては，非 NEN 成分よりも NEN 成分に多く浸潤していた（胞巣
内：p = 0.13，胞巣周囲：p = 0.013）．Foxp3 陽性リンパ球の浸潤に有意差は認めなか
った．点は外れ値を示す．
＊略語：NEN neuroendocrine neoplasm
図 7. 症例毎の CD3，CD4，CD8，Foxp3 陽性リンパ球の割合を算出し，NEN 領域
と非 NEN 領域間で有意差が存在するか Wilcoxon 符号付き順位和検定で解析し，各
症例に対応するプロット線を引いた
[a)腫瘍胞巣内 CD4/CD3，b)腫瘍胞巣周囲
CD4/CD3，c)腫瘍胞巣内 CD8/CD3，d)腫瘍胞巣周囲 CD8/CD3，e)腫瘍胞巣内
Foxp3/CD4，f)腫瘍胞巣周囲 Foxp3/CD4]．NEN/非 NEN 領域間で CD4/CD3 比，
Foxp3/CD4 比に有意差は認めなかったものの，CD8/CD3 比は特に腫瘍胞巣内で
NEC 領域により高い浸潤傾向を有していた（胞巣内：p = 0.15，胞巣周囲：p = 0.39）．
42
点は外れ値を示す．
＊略語：NEN neuroendocrine neoplasm
図 8. 症例毎の CD4，CD8，Foxp3，PD-1 陽性リンパ球の割合を算出し，NEN 領域
と非 NEN 領域間で有意差が存在するか Wilcoxon 符号付き順位和検定で解析し，各
症例に対応するプロット線を引いた
[a)腫瘍胞巣内 Foxp3/CD8，b)腫瘍胞巣周囲
Foxp3/CD8，c)腫瘍胞巣内 PD-1/CD4，d)腫瘍胞巣周囲 PD-1/CD4，e)腫瘍胞巣内
PD-1/CD8，f)腫瘍胞巣周囲 PD-1/CD8]．浸潤リンパ球の Foxp3/CD8 比は，腫瘍胞
巣内では NEC 領域で高い傾向にあった（胞巣内：p = 0.072，胞巣周囲：p = 0.55）．
PD-1/CD4 比および PD-1/CD8 比は共に、腫瘍胞巣内および胞巣周囲で NEC 領域
が有意差をもって高値であった（PD-1/CD4 胞巣内: p = 0.013，胞巣周囲: p = 0.0070，
PD-1/CD8 胞巣内: p = 0.018，胞巣周囲: p = 0.048)．点は外れ値を示す．
＊略語：NEN neuroendocrine neoplasm
図 9. NEN 領域と非 NEN 領域における各抗体陽性を呈する浸潤マクロファージの差
と，症例毎の CD68，CD163 陽性マクロファージの割合を算出し (CD163/CD68)，
NEN 領域と非 NEN 領域間で有意差が存在するか Wilcoxon 符号付き順位和検定で解
析し，各症例に対応するプロット線を引いた [a)腫瘍胞巣内 CD68，b)腫瘍胞巣周囲
CD68，c)腫瘍胞巣内 CD163，d)腫瘍胞巣周囲 CD163，e)腫瘍胞巣内 CD163/CD68，
43
f)腫瘍胞巣周囲 CD163/CD68]．CD68 陽性および CD163 陽性マクロファージはい
ずれも非 NEN 領域よりも NEN 領域に強く浸潤していた（CD68 胞巣内: p = 0.0017，
胞巣周囲: p < 0.0001，CD163 胞巣内: p = 0.0049，胞巣周囲: p = 0.14）．浸潤マクロ
ファージの CD163/CD68 比は，特に胞巣周囲では非 NEN 領域よりも NEN 領域で
有意差をもって低値であった (胞巣内: p = 0.73，胞巣周囲: p = 0.029)．点は外れ値
を示す．
＊略語：NEN neuroendocrine neoplasm
図 10. NEN 領域と非 NEN 領域における各抗体に陽性を呈する微小血管の発現数の
差を Wilcoxon 符号付き順位和検定で解析し，各症例に対応するプロット線を引いた
[a)MVD，b)VASH-1 発現数，c)VASH-1 発現率]．MVD は NEN 領域で低下傾向に
あった（p = 0.072）．VASH-1 発現数は NEN 領域で増加傾向を示し，VASH-1 発現
率は NEN 領域で有意差をもって増加していた（VASH-1 発現数：p = 0.13，VASH1 発現率：p ＜ 0.0010）．点は外れ値を示す。
*略語 MVD micro-vessel density, NEN neuroendocrine neoplasm
図 11. NEN 領域と非 NEN 領域における各抗体に陽性を呈する微小血管の発現数の
差を Wilcoxon 符号付き順位和検定で解析し，各症例に対応するプロット線を引いた
[a)Nestin，b)CD31/Nestin 二重染色]．Nestin に陽性を呈する微小血管は，NEN/非
44
NEN 領域間で有意差を認めなかった．CD31/Nestin 二重染色でいずれの抗体にも陽
性を呈する微小血管は，NEN 領域で低下傾向にあった（p＝0.067）．点は外れ値を示
す．
＊略語：NEN neuroendocrine neoplasm
図 12. NEN 領域と非 NEN 領域における全腫瘍細胞での PD-L1 発現とリンパ球にお
ける PD-1 発現の関連を t 検定で解析した [a)NEN，b)非 NEN]．PD-L1 は，全腫瘍
細胞の内 1%以上の細胞膜に染色性を有しているものを PD-L1 高値群，1%未満のも
のを PD-L1 低値群とした．NEN/非 NEN 領域では，いずれにおいても PD-L1 と PD1 の発現に相関は認めなかった．
＊略語：NEN neuroendocrine neoplasm
45
X.
図 1.
図 2.
46
図 3.
図 4.
47
図 5.
図 6.
48
図 7.
図 8.
49
図 9.
図 10.
50
図 11.
図 12.
51
XI.
表 1. 本研究における MiNEN 患者の臨床病理学的因子
症例数
GEP
33
年齢 (歳)
平均値
72 (56-86)
男性 (%)
26 (79)
女性 (%)
7 (21)
前腸 (消化管/胆膵) (%)
27 (16/11) (82)
中腸 (%)
2 (6)
後腸 (%)
4 (12)
消化管/胆膵 (%)
22/11 (67/33)
手術 (%)
31 (94)
ESD (%)
2 (6)
小細胞型 (%)
20 (60)
大細胞型 (%)
13 (40)
高分化型 (%)
14 (42)
中分化型 (%)
13 (40)
低分化型 (%)
5 (15)
粘液癌 (%)
1 (3)
ly- (%)
13 (40)
ly+ (%)
20 (60)
v- (%)
13 (40)
v+ (%)
20 (60)
性別 (%)
腫瘍部位 (%)
治療 (%)
病理学的組織型 (NEN) (%)
病理学的組織型 (非 NEN) (%)
リンパ管侵襲 (%)
静脈侵襲 (%)
pT (%)
pN (%)
T1-2 (%)
22 (67)
T3-4 (%)
11 (33)
pN- (%)
17 (52)
pN+ (%)
16 (48)
略語 ：GEP gastroenteropancreatic, NEN neuroendocrine neoplasm, ESD endoscopic mucosal
dissection
52
表 2. 本研究での免疫組織化学染色の概要
抗体
メーカー
ホスト
CD3
DAKO
Rabbit
CD4
Nichirei
Mouse
CD8
DAKO
Mouse
CD31
DAKO
Mouse
CD68
DAKO
Mouse
CD163
Leica
Mouse
microsystem
抗原賦活
希釈
緩衝液
一次抗体
濃度
pH
反応時間
9.0
4℃, 一晩
1/80
9.0
4℃, 一晩
1/50
7.0
4℃, 一晩
1/40
6.0
4℃, 一晩
Histofine
1/200
なし
4℃, 一晩
Histofine
1/600
6.0
4℃, 一晩
Histofine
1/200
6.0
4℃, 一晩
Histofine
1/100
6.0
4℃, 一晩
Histofine
AC, 121℃,
Ready
5分
to use
AC, 121℃,
5分
AC, 121℃,
5分
AC, 121℃,
5分
Trypsin (37℃, 15
分)
AC, 121℃,
二次抗体
EnVision
FLEX
Histofine
EnVision
FLEX
5分
Foxp3
Abcam
Mouse
PD-1
Abcam
Mouse
AC, 121℃,
5分
AC, 121℃,
5分
VENTANA
PD-L1
Roche, sp263
Rabbit
不明
RTV
不明
不明
Optiview DAB
universal kit
SYN
ChgA
DAKO
Agilent
technologies
Mouse
AC, 121℃,
1/300
6.0
4℃, 一晩
Histofine
1/1,500
6.0
4℃, 一晩
Histofine
1/200
6.0
4℃, 一晩
Histofine
PT Link (97℃,
Ready
High
20 分)
to use
pH
1/400
8.0
4℃, 一晩
Histofine
1/8,000
6.0
4℃, 一晩
Histofine
5分
Microwave
Rabbit
(210W,
15 分)
INSM1
Santacruz
Mouse
Ki-67
DAKO
Mouse
VASH-1
Donated
Mouse
Nestin
Merck
Rabbit
AC, 121℃,
5分
AC, 121℃,
5分
AC, 121℃,
5分
室温, 20 分
EnVision
FLEX
略 語 ： CD cluster differentiation, AC autoclave, PD-1 programmed cell death-1, PD-L1
programmed cell death ligand-1, SYN synaptophysin, ChgA chromogranin A, INSM1 insulinoma53
associated 1, VASH-1 vasohibin-1
表 3. NEN と非 NEN 間の各抗体陽性 TILs，TAMs や血管新生に関わる因子の差と、
各抗体において陽性細胞が NEN 領域>非 NEN 領域となる症例の比率
NEN－非 NEN
抗体
腫瘍胞巣内
NEN>非 NEN
(%)
腫瘍胞巣周囲
NEN>非 NEN
(%)
CD3
9.33 ± 359.25
54.5
43.33 ± 332.71
57.6
CD4
－0.67 ± 142.78
42.4
0 ± 108.94
39.4
CD8
－9.67 ± 277.47
36.4
0.67 ± 199.06
51.5
Foxp3
5.00 ± 75.63
54.5
0.33 ± 68.18
48.5
PD-1
0 ± 38.43
36.4
0 ± 23.76
45.5
CD68
66.00 ± 224.67
60.6
58.67 ± 237.92
75.8
CD163
16.67 ± 154.52
66.7
2.33 ± 103.05
51.5
MVD (CD31)
-5.00 ± 22.97
36.4
VASH-1 発現数
1.00 ± 11.14
57.7
21.43 ± 26.19
72.7
Nestin
0.00 ± 12.49
48.5
CD31/Nestin
1.00 ± 4.20
51.5
CD4/CD3
－0.0057 ± 1.18
45.5
－0.0017 ± 0.50
33.3
CD8/CD3
－0.077 ± 0.84
39.4
－0.052 ± 1.33
45.5
Foxp3/CD4
0 ± 34.15
45.5
0.074 ± 26.88
51.5
Foxp3/CD8
0.32 ± 2.82
57.6
0.034 ± 0.77
57.6
CD163/CD68
－0.041 ± 11.63
39.4
－0.14 ± 0.86
30.3
PD-1/CD4
0 ± 2.50
36.4
0 ± 7.55
45.5
PD-1/CD8
0 ± 0.27
42.4
0 ± 0.058
42.4
VASH-1 発現率
(%)
* 中央値±SD
54
表 4. NEN と非 NEN 領域における TILs や TAMs，血管新生に関与する各分子の差
(NEN 領域－非 NEN 領域)の大小と，リンパ節転移・リンパ管侵襲の関連の有無
抗体
pN
リンパ管侵襲 (ly)
胞巣内
胞巣周囲
胞巣内
胞巣周囲
pN+
pN-
pN+
pN-
ly+
ly-
ly+
ly-
high
0.73
0.73
11
1.00
10
0.30
low
10
high
11
11
low
10
12
12
high
11
low
10
11
11
high
10
10
low
10
11
high
low
12
10
13
11
high
11
low
12
high
10
12
low
10
12
high
low
11
high
10
low
10
CD3
CD4
0.17
0.30
0.73
0.48
CD8
0.17
0.73
0.48
0.73
Foxp3
0.73
0.49
0.48
0.48
PD-1
0.48
0.73
1.00
1.00
CD68
1.00
1.00
0.30
0.48
CD163
1.00
0.73
1.00
1.00
MVD
1.00
0.73
Nestin
1.00
55
1.00
表 4 の続き.
VASH-1 発現数
high
low
high
low
high
low
10
1.00
12
11
13
0.30
VASH-1 発現率 (%)
1.00
0.83
CD31/
Nestin
0.73
0.47
Fisher の正確検定で解析した．
表 5. NEN と非 NEN 領域における TILs や TAMs，血管新生に関与する各分子の差
(NEN 領域－非 NEN 領域)の大小と，リンパ節転移・静脈侵襲の関連の有無
抗体
静脈侵襲 (v)
胞巣内
胞巣周囲
v+
v-
v+
v-
high
12
0.30
11
0.73
low
high
11
low
11
11
high
10
17
10
low
10
10
high
10
11
low
10
high
10
low
12
10
CD3
CD4
0.48
0.033*
CD8
1.00
1.00
Foxp3
1.00
0.73
PD-1
0.72
0.72
56
表 5 の続き.
CD68
high
low
12
high
low
12
high
low
13
high
low
11
high
low
12
high
10
low
10
high
low
12
0.30
10
10
10
10
1.00
CD163
1.00
1.00
MVD
0.080
Nestin
0.73
VASH-1 発現数
0.23
VASH-1 発現率 (%)
0.83
CD31/Nestin
1.00
Fisher の正確検定で解析した．*統計学的有意 (p < 0.05)
57
XII.
謝辞
本研究のご指導いただきました東北大学病院病理部前部長
学病院総合外科教授
亀井
笹野
公伸先生，東北大
尚先生，東北大学医学系研究科病理診断学分野教授
貴先生，東北大学病院病理部准教授
藤島
史喜先生に深く御礼申し上げます．
対象症例の情報を御提供頂きました，宮城県立がんセンター病理診断科
先生，宮城県立がんセンター消化器外科
三浦
坂元 和宏先生，仙台医療センター病理診断科
佐藤
郁郎
康先生，大崎市民病院病理診断科
鈴木
博義先生，仙台オープン病院
病理診断科 澤井
高志先生，石巻赤十字病院病理診断科
市立病院内科 星
達也先生に深く御礼申し上げます．また東北大学病院病理部
照樹氏，菅原
弥生氏，小泉
板倉
裕子先生，気仙沼
隆譲氏には実験の御指導を頂きました．深く感謝
しております．
58
...
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