The histological growth patterns in liver metastases from colorectal cancer display differences in lymphoid, myeloid, and mesenchymal cells

Abstract

Colorectal liver metastases grow following different histologic growth patterns (HGPs), classified as desmoplastic and nondesmoplastic (dHGP, non-dHGP), being the latter associated with worst prognosis. This study aimed to investigate the tumor microenvironment (TME) between HGPs supporting different survival. Multiplexed immunohistochemical staining was performed with the Opal7 system in a 100-patients cohort to evaluate the tumor–liver interface with three different cell panels: lymphoid, myeloid, and carcinoma-associated fibroblasts. Differences between HGPs were assessed by Mann–Whitney U test with Pratt correction and Holm–Bonferroni multitest adjustment. Cytotoxic T-cells were more abundant in tumoral areas of dHGP, while non-dHGP had higher macrophages infiltration, Th2, CD163⁺, and Calprotectin⁺ cells as well as higher pSMAD2 expression. Regarding carcinoma-associated fibroblasts, several subsets expressing COL1A1 were enriched in dHGP, while αSMA^low_single cells were present at higher densities in non-dHGP. Interestingly, Calprotectin⁺ cells confer better prognoses in non-dHGP, identifying a subgroup of good outcome patients that unexpectedly also show an enrichment in other myeloid cells. In summary, our results illustrate different TME landscapes with respect to HGPs. dHGP presents a higher degree of immunocompetence, higher amounts of Collagen 1 as well as lesser presence of myeloid cell populations, features that might be influencing on the better prognosis of encapsulated metastases.

Keywords

capsule / desmoplasia / hepatic metastases / histologic growth pattern / microenvironment

References

[1] Tzeng CW, Aloia TA. Colorectal liver metastases. J Gastrointest Surg. 2013; 17(1): 195-201. quiz p 201–2.

[2] Adam R, De Gramont A, Figueras J, et al. The oncosurgery approach to managing liver metastases from colorectal cancer: a multidisciplinary international consensus. Oncologist. 2012; 17(10): 1225-1239.

[3] Morris VK, Kennedy EB, Baxter NN, et al. Treatment of metastatic colorectal cancer: ASCO guideline. J Clin Oncol. 2022:JCO2201690.

[4] Van Cutsem E, Cervantes A, Adam R, et al. ESMO consensus guidelines for the management of patients with metastatic colorectal cancer. Ann Oncol. 2016; 27(8): 1386-1422.

[5] Johnsson A, Hagman H, Frodin JE, et al. A randomized phase III trial on maintenance treatment with bevacizumab alone or in combination with erlotinib after chemotherapy and bevacizumab in metastatic colorectal cancer: the Nordic ACT Trial. Ann Oncol. 2013; 24(9): 2335-2341.

[6] Overman MJ, Ernstoff MS, Morse MA. Where we stand with immunotherapy in colorectal cancer: deficient mismatch repair, proficient mismatch repair, and toxicity management. Am Soc Clin Oncol Educ Book. 2018; 38: 239-247.

[7] Latacz E, Hoppener D, Bohlok A, et al. Histopathological growth patterns of liver metastasis: updated consensus guidelines for pattern scoring, perspectives and recent mechanistic insights. Br J Cancer. 2022; 127(6): 988-1013.

[8] van Dam PJ, van der Stok EP, Teuwen LA, et al. International consensus guidelines for scoring the histopathological growth patterns of liver metastasis. Br J Cancer. 2017; 117(10): 1427-1441.

[9] Yu J, Green MD, Li S, et al. Liver metastasis restrains immunotherapy efficacy via macrophage-mediated T cell elimination. Nat Med. 2021; 27(1): 152-164.

[10] Buisman FE, Giardiello D, Kemeny NE, et al. Predicting 10-year survival after resection of colorectal liver metastases; an international study including biomarkers and perioperative treatment. Eur J Cancer. 2022; 168: 25-33.

[11] Latacz E, van Dam PJ, Vanhove C, et al. Can medical imaging identify the histopathological growth patterns of liver metastases? Semin Cancer Biol. 2021; 71: 33-41.

[12] Wei S, Gou X, Zhang Y, et al. Prediction of transformation in the histopathological growth pattern of colorectal liver metastases after chemotherapy using CT-based radiomics. Clin Exp Metastasis. 2024; 41(2): 143-154.

[13] Abe H, Yasunaga Y, Yamazawa S, et al. Histological growth patterns of colorectal cancer liver metastases: a strong prognostic marker associated with invasive patterns of the primary tumor and p53 alteration. Hum Pathol. 2022; 123: 74-83.

[14] Bohlok A, Inchiostro L, Lucidi V, et al. Tumor biology reflected by histological growth pattern is more important than surgical margin for the prognosis of patients undergoing resection of colorectal liver metastases. Eur J Surg Oncol. 2023; 49(1): 217-224.

[15] Fernandez Moro C, Bozoky B, Gerling M. Growth patterns of colorectal cancer liver metastases and their impact on prognosis: a systematic review. BMJ Open Gastroenterol. 2018; 5(1): e000217.

[16] Fernandez Moro C, Geyer N, Harrizi S, et al. An idiosyncratic zonated stroma encapsulates desmoplastic liver metastases and originates from injured liver. Nat Commun. 2023; 14(1): 5024.

[17] Gong Z, Jia H, Yu J, et al. Nuclear FOXP3 inhibits tumor growth and induced apoptosis in hepatocellular carcinoma by targeting c-Myc. Oncogenesis. 2020; 9(10): 97.

[18] Takenaka M, Seki N, Toh U, et al. FOXP3 expression in tumor cells and tumor-infiltrating lymphocytes is associated with breast cancer prognosis. Mol Clin Oncol. 2013; 1(4): 625-632.

[19] Coussens LM, Zitvogel L, Palucka AK. Neutralizing tumor-promoting chronic inflammation: a magic bullet?. Science. 2013; 339(6117): 286-291.

[20] Pollard JW. Trophic macrophages in development and disease. Nat Rev Immunol. 2009; 9(4): 259-270.

[21] Huang M, Wu R, Chen L, et al. S100A9 regulates MDSCs-mediated immune suppression via the RAGE and TLR4 signaling pathways in colorectal carcinoma. Front Immunol. 2019; 10: 2243.

[22] Wagner NB, Weide B, Gries M, et al. Tumor microenvironment-derived S100A8/A9 is a novel prognostic biomarker for advanced melanoma patients and during immunotherapy with anti-PD-1 antibodies. J Immunother Cancer. 2019; 7(1): 343.

[23] Mezheyeuski A, Micke P, Martin-Bernabe A, et al. The immune landscape of colorectal cancer. Cancers (Basel). 2021; 13(21).

[24] Pruenster M, Vogl T, Roth J, Sperandio M. S100A8/A9: from basic science to clinical application. Pharmacol Ther. 2016; 167: 120-131.

[25] Kwak T, Wang F, Deng H, et al. Distinct populations of immune-suppressive macrophages differentiate from monocytic myeloid-derived suppressor cells in cancer. Cell Rep. 2020; 33(13): 108571.

[26] MacParland SA, Liu JC, Ma XZ, et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat Commun. 2018; 9(1): 4383.

[27] Mezheyeuski A, Backman M, Mattsson J, et al. An immune score reflecting pro-and anti-tumoural balance of tumour microenvironment has major prognostic impact and predicts immunotherapy response in solid cancers. EBioMedicine. 2023; 88: 104452.

[28] Koh HM, Lee HJ, Kim DC. High expression of S100A8 and S100A9 is associated with poor disease-free survival in patients with cancer: a systematic review and meta-analysis. Transl Cancer Res. 2021; 10(7): 3225-3235.

[29] Srikrishna G. S100A8 and S100A9: new insights into their roles in malignancy. J Innate Immun. 2012; 4(1): 31-40.

[30] Nagy A, Munkacsy G, Gyorffy B. Pancancer survival analysis of cancer hallmark genes. Sci Rep. 2021; 11(1): 6047.

[31] Bhattacharjee S, Hamberger F, Ravichandra A, et al. Tumor restriction by type I collagen opposes tumor-promoting effects of cancer-associated fibroblasts. J Clin Invest. 2021; 131(11).

[32] Chen Y, Kim J, Yang S, et al. Type I collagen deletion in alphaSMA(+) myofibroblasts augments immune suppression and accelerates progression of pancreatic cancer. Cancer Cell. 2021; 39(4): 548-565. e6.

[33] Biffi G, Tuveson DA. Diversity and biology of cancer-associated fibroblasts. Physiol Rev. 2021; 101(1): 147-176.

[34] Geng X, Chen H, Zhao L, et al. Cancer-associated fibroblast (CAF) heterogeneity and targeting therapy of CAFs in pancreatic cancer. Front Cell Dev Biol. 2021; 9: 655152.

[35] Ohlund D, Handly-Santana A, Biffi G, et al. Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. J Exp Med. 2017; 214(3): 579-596.

[36] Nicolas AM, Pesic M, Engel E, et al. Inflammatory fibroblasts mediate resistance to neoadjuvant therapy in rectal cancer. Cancer Cell. 2022; 40(2): 168-184. e13.

[37] Giguelay A, Turtoi E, Khelaf L, et al. The landscape of cancer-associated fibroblasts in colorectal cancer liver metastases. Theranostics. 2022; 12(17): 7624-7639.

[38] Kieffer Y, Hocine HR, Gentric G, et al. Single-cell analysis reveals fibroblast clusters linked to immunotherapy resistance in cancer. Cancer Discov. 2020; 10(9): 1330-1351.

[39] Terayama N, Terada T, Nakanuma Y. Histologic growth patterns of metastatic carcinomas of the liver. Jpn J Clin Oncol. 1996; 26(1): 24-29.

[40] Vermeulen PB, Colpaert C, Salgado R, et al. Liver metastases from colorectal adenocarcinomas grow in three patterns with different angiogenesis and desmoplasia. J Pathol. 2001; 195(3): 336-342.

[41] Frentzas S, Simoneau E, Bridgeman VL, et al. Vessel co-option mediates resistance to anti-angiogenic therapy in liver metastases. Nat Med. 2016; 22(11): 1294-1302.

[42] Illemann M, Bird N, Majeed A, et al. Two distinct expression patterns of urokinase, urokinase receptor and plasminogen activator inhibitor-1 in colon cancer liver metastases. Int J Cancer. 2009; 124(8): 1860-1870.

[43] Illemann M, Eefsen RH, Bird NC, et al. Tissue inhibitor of matrix metalloproteinase-1 expression in colorectal cancer liver metastases is associated with vascular structures. Mol Carcinog. 2016; 55(2): 193-208.

[44] Garcia-Vicien G, Mezheyeuski A, Banuls M, Ruiz-Roig N, Mollevi DG. The tumor microenvironment in liver metastases from colorectal carcinoma in the context of the histologic growth patterns. Int J Mol Sci. 2021; 22(4).

[45] Lee JC, Mehdizadeh S, Smith J, et al. Regulatory T cell control of systemic immunity and immunotherapy response in liver metastasis. Sci Immunol. 2020; 5(52).

[46] Golubovskaya V, Wu L. Different subsets of T cells, memory, effector functions, and CAR-T immunotherapy. Cancers (Basel). 2016; 8(3).

[47] Edwards J, Wilmott JS, Madore J, et al. CD103(+) tumor-resident CD8(+) T cells are associated with improved survival in immunotherapy-naive melanoma patients and expand significantly during anti-PD-1 treatment. Clin Cancer Res. 2018; 24(13): 3036-3045.

[48] Nizard M, Roussel H, Diniz MO, et al. Induction of resident memory T cells enhances the efficacy of cancer vaccine. Nat Commun. 2017; 8: 15221.

[49] Savas P, Virassamy B, Ye C, et al. Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis. Nat Med. 2018; 24(7): 986-993.

[50] Wang T, Shen Y, Luyten S, Yang Y, Jiang X. Tissue-resident memory CD8(+) T cells in cancer immunology and immunotherapy. Pharmacol Res. 2020; 159: 104876.

[51] Han J, Khatwani N, Searles TG, Turk MJ, Angeles CV. Memory CD8(+) T cell responses to cancer. Semin Immunol. 2020; 49: 101435.

[52] Ando M, Ito M, Srirat T, Kondo T, Yoshimura A. Memory T cell, exhaustion, and tumor immunity. Immunol Med. 2020; 43(1): 1-9.

[53] DeNardo DG, Ruffell B. Macrophages as regulators of tumour immunity and immunotherapy. Nat Rev Immunol. 2019; 19(6): 369-382.

[54] Kielbassa K, Vegna S, Ramirez C, Akkari L. Understanding the origin and diversity of macrophages to tailor their targeting in solid cancers. Front Immunol. 2019; 10: 2215.

[55] Goyette J, Geczy CL. Inflammation-associated S100 proteins: new mechanisms that regulate function. Amino Acids. 2011; 41(4): 821-842.

[56] Chen Y, Ouyang Y, Li Z, Wang X, Ma J. S100A8 and S100A9 in cancer. Biochim Biophys Acta Rev Cancer. 2023; 1878(3): 188891.

[57] Mihaila AC, Ciortan L, Macarie RD, et al. Transcriptional profiling and functional analysis of N1/N2 neutrophils reveal an immunomodulatory effect of S100A9-blockade on the pro-inflammatory N1 subpopulation. Front Immunol. 2021; 12: 708770.

[58] Hedrick CC, Malanchi I. Neutrophils in cancer: heterogeneous and multifaceted. Nat Rev Immunol. 2022; 22(3): 173-187.

[59] Gebhardt C, Nemeth J, Angel P, Hess J. S100A8 and S100A9 in inflammation and cancer. Biochem Pharmacol. 2006; 72(11): 1622-1631.

[60] Fan B, Zhang LH, Jia YN, et al. Presence of S100A9-positive inflammatory cells in cancer tissues correlates with an early stage cancer and a better prognosis in patients with gastric cancer. BMC Cancer. 2012; 12: 316.

[61] Wong SW, McCarroll J, Hsu K, Geczy CL, Tedla N. Intranasal delivery of recombinant S100A8 protein delays lung cancer growth by remodeling the lung immune microenvironment. Front Immunol. 2022; 13: 826391.

[62] Li S, Xu F, Li H, et al. S100A8(+) stroma cells predict a good prognosis and inhibit aggressiveness in colorectal carcinoma. Oncoimmunology. 2017; 6(1): e1260213.

[63] Lunevicius R, Nakanishi H, Ito S, et al. Clinicopathological significance of fibrotic capsule formation around liver metastasis from colorectal cancer. J Cancer Res Clin Oncol. 2001; 127(3): 193-199.

[64] Pellinen T, Paavolainen L, Martin-Bernabe A, et al. Fibroblast subsets in non-small cell lung cancer: associations with survival, mutations, and immune features. J Natl Cancer Inst. 2023; 115(1): 71-82.

[65] Chen Y, Yang S, Tavormina J, et al. Oncogenic collagen I homotrimers from cancer cells bind to alpha3beta1 integrin and impact tumor microbiome and immunity to promote pancreatic cancer. Cancer Cell. 2022; 40(8): 818-834. e9.

[66] Affo S, Nair A, Brundu F, et al. Promotion of cholangiocarcinoma growth by diverse cancer-associated fibroblast subpopulations. Cancer Cell. 2021; 39(6): 866-882. e11.

[67] Han Y, Chai F, Wei J, et al. Identification of predominant histopathological growth patterns of colorectal liver metastasis by multi-habitat and multi-sequence based radiomics analysis. Front Oncol. 2020; 10: 1363.

[68] Li WH, Wang S, Liu Y, Wang XF, Wang YF, Chai RM. Differentiation of histopathological growth patterns of colorectal liver metastases by MRI features. Quant Imaging Med Surg. 2022; 12(1): 608-617.

[69] Starmans MPA, Buisman FE, Renckens M, et al. Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study. Clin Exp Metastasis. 2021; 38(5): 483-494.

[70] Galjart B, Nierop PMH, van der Stok EP, et al. Angiogenic desmoplastic histopathological growth pattern as a prognostic marker of good outcome in patients with colorectal liver metastases. Angiogenesis. 2019; 22(2): 355-368.

[71] Hoppener DJ, Galjart B, Nierop PMH, et al. Histopathological growth patterns and survival after resection of colorectal liver metastasis: an external validation study. JNCI Cancer Spectr. 2021; 5(3): pkab026.

[72] Mezheyeuski A, Strell C. Multiplexed imaging for immune profiling on human FFPE material. Methods Mol Biol. 2021; 2350: 125-144.

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