Tissue‐specific tumor microenvironments influence responses to immunotherapies

Investigation of variable response rates to cancer immunotherapies has exposed the immunosuppressive tumor microenvironment (TME) as a limiting factor of therapeutic efficacy. A determinant of TME composition is the tumor location, and clinical data have revealed associations between certain metastatic sites and reduced responses. Preclinical models to study tissue‐specific TMEs have eliminated genetic heterogeneity, but have investigated models with limited clinical relevance.

[1]  Graham Roberts.  Real‐life data , 2020, Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology.

[2]  M. Merad,et al.  Host tissue determinants of tumour immunity , 2019, Nature Reviews Cancer.

[3]  J. Utikal,et al.  Immunosuppression mediated by myeloid-derived suppressor cells (MDSCs) during tumour progression , 2018, British Journal of Cancer.

[4]  Hidekazu Suzuki,et al.  Clinical Characteristics of Liver Metastasis in Nivolumab-treated Patients with Non-small Cell Lung Cancer , 2018, AntiCancer Research.

[5]  S. Loi,et al.  Dual PD-1 and CTLA-4 Checkpoint Blockade Promotes Antitumor Immune Responses through CD4+Foxp3− Cell–Mediated Modulation of CD103+ Dendritic Cells , 2018, Cancer Immunology Research.

[6]  L. Kwak,et al.  Targeting myeloid-derived suppressor cells for cancer immunotherapy , 2018, Cancer Immunology, Immunotherapy.

[7]  R. Kefford,et al.  Metastasis‐specific patterns of response and progression with anti‐PD‐1 treatment in metastatic melanoma , 2018, Pigment cell & melanoma research.

[8]  R. Weinberg,et al.  Understanding the tumor immune microenvironment (TIME) for effective therapy , 2018, Nature Medicine.

[9]  R. Sun,et al.  Tumor immunotherapy: New aspects of natural killer cells. , 2018, Chinese journal of cancer research = Chung-kuo yen cheng yen chiu.

[10]  W. Pao,et al.  Tissue-Specific Immunoregulation: A Call for Better Understanding of the "Immunostat" in the Context of Cancer. , 2018, Cancer discovery.

[11]  G. Salles,et al.  A phase 1 study of lirilumab (antibody against killer immunoglobulin-like receptor antibody KIR2D; IPH2102) in patients with solid tumors and hematologic malignancies , 2018, Oncotarget.

[12]  Hidekazu Suzuki,et al.  Metastatic site as a predictor of nivolumab efficacy in patients with advanced non-small cell lung cancer: A retrospective multicenter trial , 2018, PloS one.

[13]  S. Loi,et al.  Tissue-Dependent Tumor Microenvironments and Their Impact on Immunotherapy Responses , 2018, Front. Immunol..

[14]  X. Mielgo-Rubio,et al.  Predictive and prognostic clinical and pathological factors of nivolumab efficacy in non-small-cell lung cancer patients , 2018, Clinical and Translational Oncology.

[15]  A. Gupta,et al.  Population Modeling of Tumor Kinetics and Overall Survival to Identify Prognostic and Predictive Biomarkers of Efficacy for Durvalumab in Patients With Urothelial Carcinoma , 2018, Clinical pharmacology and therapeutics.

[16]  B. Becher,et al.  Restoration of Natural Killer Cell Antimetastatic Activity by IL12 and Checkpoint Blockade. , 2017, Cancer research.

[17]  O. Merimsky,et al.  Effectiveness and safety of nivolumab in advanced non-small cell lung cancer: The real-life data. , 2017, Lung cancer.

[18]  Peter Schmid,et al.  LBA13Relationship between tumor infiltrating lymphocyte (TIL) levels and response to pembrolizumab (pembro) in metastatic triple-negative breast cancer (mTNBC): Results from KEYNOTE-086 , 2017 .

[19]  Young Hak Kim,et al.  Liver Metastasis Is Associated with Poor Progression-Free Survival in Patients with Non-Small Cell Lung Cancer Treated with Nivolumab. , 2017, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[20]  Weiping Zou,et al.  Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy , 2017, Nature Reviews Immunology.

[21]  G. Shen,et al.  Identification and causes of metabonomic difference between orthotopic and subcutaneous xenograft of pancreatic cancer , 2017, Oncotarget.

[22]  J. Taube,et al.  Liver Metastasis and Treatment Outcome with Anti-PD-1 Monoclonal Antibody in Patients with Melanoma and NSCLC , 2017, Cancer Immunology Research.

[23]  F. Souza-Fonseca-Guimaraes,et al.  Bench to bedside: NK cells and control of metastasis. , 2017, Clinical immunology.

[24]  G. Siegal,et al.  Location of tumor affects local and distant immune cell type and number , 2017, Immunity, inflammation and disease.

[25]  J. Wargo,et al.  Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy , 2017, Cell.

[26]  C. Gedye,et al.  Patterns of response to anti-PD-1 treatment: an exploratory comparison of four radiological response criteria and associations with overall survival in metastatic melanoma patients , 2016, British Journal of Cancer.

[27]  J. Wolchok,et al.  Safety of the natural killer (NK) cell-targeted anti-KIR antibody, lirilumab (liri), in combination with nivolumab (nivo) or ipilimumab (ipi) in two phase 1 studies in advanced refractory solid tumors , 2016 .

[28]  Jian Huang,et al.  Worse outcome in breast cancer with higher tumor-infiltrating FOXP3+ Tregs : a systematic review and meta-analysis , 2016, BMC Cancer.

[29]  Camille Guillerey,et al.  Targeting natural killer cells in cancer immunotherapy , 2016, Nature Immunology.

[30]  Ping Yang,et al.  Prognostic effect of liver metastasis in lung cancer patients with distant metastasis , 2016, Oncotarget.

[31]  Marco Y. Hein,et al.  The Perseus computational platform for comprehensive analysis of (prote)omics data , 2016, Nature Methods.

[32]  M. Vetizou,et al.  Resistance Mechanisms to Immune-Checkpoint Blockade in Cancer: Tumor-Intrinsic and -Extrinsic Factors. , 2016, Immunity.

[33]  R. Dummer,et al.  Evaluation of clinicopathological factors in PD-1 response: derivation and validation of a prediction scale for response to PD-1 monotherapy , 2017, British Journal of Cancer.

[34]  R. Childs,et al.  Therapeutic approaches to enhance natural killer cell cytotoxicity against cancer: the force awakens , 2015, Nature Reviews Drug Discovery.

[35]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[36]  Paul Theodor Pyl,et al.  HTSeq—a Python framework to work with high-throughput sequencing data , 2014, bioRxiv.

[37]  B. Seliger,et al.  Inhibition of Tumor-Derived Prostaglandin-E2 Blocks the Induction of Myeloid-Derived Suppressor Cells and Recovers Natural Killer Cell Activity , 2014, Clinical Cancer Research.

[38]  R. Kefford,et al.  Lesion-specific patterns of response and progression with anti-PD-1 treatment in metastatic melanoma (MM). , 2014 .

[39]  M. De la Fuente,et al.  Chronic Inflammation and Cytokines in the Tumor Microenvironment , 2014, Journal of immunology research.

[40]  C. Meyer,et al.  Frequencies of circulating MDSC correlate with clinical outcome of melanoma patients treated with ipilimumab , 2014, Cancer Immunology, Immunotherapy.

[41]  V. Kuchroo,et al.  Reversal of NK-Cell Exhaustion in Advanced Melanoma by Tim-3 Blockade , 2014, Cancer Immunology Research.

[42]  D. Schadendorf,et al.  Myeloid-Derived Suppressor Cells Predict Survival of Patients with Advanced Melanoma: Comparison with Regulatory T Cells and NY-ESO-1- or Melan-A–Specific T Cells , 2013, Clinical Cancer Research.

[43]  S. Azzi,et al.  Vascular Permeability and Drug Delivery in Cancers , 2013, Front. Oncol..

[44]  C. Lan,et al.  Expression of M2-Polarized Macrophages is Associated with Poor Prognosis for Advanced Epithelial Ovarian Cancer , 2013, Technology in cancer research & treatment.

[45]  Douglas Hanahan,et al.  Accessories to the Crime: Functions of Cells Recruited to the Tumor Microenvironment Prospects and Obstacles for Therapeutic Targeting of Function-enabling Stromal Cell Types , 2022 .

[46]  Steven L Salzberg,et al.  Fast gapped-read alignment with Bowtie 2 , 2012, Nature Methods.

[47]  V. Bronte,et al.  Myeloid-derived suppressor cell heterogeneity and subset definition. , 2010, Current opinion in immunology.

[48]  M. Caligiuri,et al.  Preclinical characterization of 1-7F9, a novel human anti-KIR receptor therapeutic antibody that augments natural killer-mediated killing of tumor cells. , 2009, Blood.

[49]  M. Manns,et al.  Myeloid derived suppressor cells inhibit natural killer cells in patients with hepatocellular carcinoma via the NKp30 receptor , 2009, Hepatology.

[50]  P. Debré,et al.  HLA-E upregulation on IFN-γ-activated AML blasts impairs CD94/NKG2A-dependent NK cytolysis after haplo-mismatched hematopoietic SCT , 2009, Bone Marrow Transplantation.

[51]  S. Quezada,et al.  CTLA4 blockade and GM-CSF combination immunotherapy alters the intratumor balance of effector and regulatory T cells. , 2006, The Journal of clinical investigation.

[52]  M. Smyth,et al.  Eradication of established tumors in mice by a combination antibody-based therapy , 2006, Nature Medicine.

[53]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[54]  C. Restall,et al.  Genomic analysis of a spontaneous model of breast cancer metastasis to bone reveals a role for the extracellular matrix. , 2005, Molecular cancer research : MCR.

[55]  D. Foster,et al.  IL-21 in Synergy with IL-15 or IL-18 Enhances IFN-γ Production in Human NK and T Cells1 , 2003, The Journal of Immunology.

[56]  G. Leclercq,et al.  Differential effects of interleukin-15 and interleukin-2 on differentiation of bipotential T/natural killer progenitor cells , 1996, The Journal of experimental medicine.

[57]  Per Capita,et al.  About the authors , 1995, Machine Vision and Applications.

[58]  G. Trinchieri,et al.  Identification and purification of natural killer cell stimulatory factor (NKSF), a cytokine with multiple biologic effects on human lymphocytes , 1989, Journal of Experimental Medicine.

[59]  J. Sosman,et al.  Clinical Correlates of Response to Anti-PD-1–based Therapy in Patients With Metastatic Melanoma , 2019, Journal of immunotherapy.

[60]  J. Flynn,et al.  Tissues in different anatomical sites can sculpt and vary the tumor microenvironment to affect responses to therapy. , 2014, Molecular therapy : the journal of the American Society of Gene Therapy.

[61]  Kevin R Coombes,et al.  Gene expression profile of metastatic human pancreatic cancer cells depends on the organ microenvironment. , 2007, Cancer research.

[62]  宇野 友康.  Eradication of established tumors in mice by a combination antibody-based therapy , 2007 .