https://immuno-oncologyresearchtrends.com/home daily 1.0 2022-05-07 https://immuno-oncologyresearchtrends.com/home/2022/5/7/1-2-punch-dual-moa-bsabs monthly 0.5 2022-05-16 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/3ebef8d8-e8ce-4f49-940c-d5ad5454fcf2/Immune+Phenotype.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out The inflamed, immune-excluded, and immune desert phenotypes are prevalent at varying degrees within a given tumor type and across cancers. Figure illustrates and broadly classifies the approximate phenotype prevalence within each cancer and places them across the tumor immunity continuum as they correlate to TMB. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/934d7dbb-a5c4-4fe3-acd7-967e1b56f431/4-1BB+bsAb+Formats.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out At AACR2022, Christian Klein from Roche Glycard presented the 4-1BB agonism concept Roche has developed. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/591dca97-9501-4877-b850-1a5c38917a73/4-1BB+PDL1+combination.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out The solutions pursued (and under clinical development) to secure maximal efficacy of 4-1BB monotherapy while avoiding liver toxicity show synergy with PD-1 blockade. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/9af1ff23-0999-494d-8b7d-eeb427511010/RO7122290.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out First-in-human (FIH) phase I study of RO7122290 (RO), a FAP-targeted 4-1BB agonist, administered as single agent : Objective response: 2 PR occurred in part A including thymoma and RCC. (Melero I, ESMO2020) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/4d7192bb-d580-4038-b6d6-f62003f048c7/RO7122290+COmbination.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out First-in-human (FIH) phase I study of RO7122290 (RO), a FAP-targeted 4-1BB agonist, , administered in combination with atezolizumab: Objective response: 8 PR occurred in part B/IMG sub-study+ including 2 mesothelioma, 2 SCLC, 2 TNBC, 1 thymoma and 1 Merkel cell carcinoma. (Melero I, ESMO2020) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/b6bc1deb-60c1-41b5-a3a0-27015943c2dc/4-1BB.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out Protein engineering strategies to target CD137 (4-1BB) costimulation to the tumor microenvironment include targeting CD137 agonists to TAA, to proteins selectively expressed in the stroma such as fibroblast activated protein (FAP), or using antibodies targeting CD137 that become unmasked and active in the tissue microenvironment (probodies). In other instances, dual targeting of costimulatory and coinhibitory receptors enriched in the tumor microenvironment by a single multi-specific protein is being attempted with potential for synergistic effects in a single moiety https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/f0624fb9-4daf-47c9-b7eb-21dff144e1d2/Dual+MOA.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out Anti-tumor effect of mbsAb-PD-L1×4-1BB is dependent on conditional agonist activity, while the contribution of blocking MOA remains unaddressed. (A) mbsAb-PD-L1x4-1BB is a Fc-silenced bsAb of mAb-PD-L1 and mAb-4-1BB, containing L234A and L235A Fc-silencing mutations that abrogate binding to FcγR and C1q. (B) mbsAb-Ctrl-4-1BB fails to induce 4-1BB signaling, while mbsAb-PD-L1×4-1BB elicits conditional PD-L1-driven 4-1BB activation in a mouse 4-1BB reporter assay. (C) PD-L1×4-1BB was tested in CT26 syngeneic model compared to the monovalent control antibodies mbsAb-PD-L1×Ctrl and mbsAb-Ctrl×4-1BB alone or in combination, or isotype control antibody (mAb-Ctrl). Caveat of the study is that 4-1BB requires clustering to induce signaling (Muik et al. Dec 2021 (BioNTech-Genmab). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1b7ba17e-52bc-41c9-94a4-303696de8ce2/GEN1046.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out GEN1046 clinical activity in heavily pretreated patients, including cases resistant to prior PD-(L)1 immunotherapy: disease control occurred in 40/61 (65.6%) subjects in dose escalation, with 4 PR, including TNBC (n=1), ovarian cancer (n=1) and NSCLC (n=2) patients. (Jure-Kunkel, AACR2022) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/d8d2141a-b159-44bc-9a12-0d018db21bd3/PDL1+pos+vs+neg+Clinical+Response.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out Clinical activity of GEN1046 by tumor PD-L1 status across CPI-experienced patients with advanced solid tumors (biomarker evaluable only). Greater proportion of patients harboring PD-L1+ tumors exhibited reduction in tumor volume with GEN1046 treatment (n=14/30, 47%) compared to patients with PD-L1neg tumors (n=3/23, 13%). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/ece92134-ddbd-4efa-b646-0e26757d9867/AE+GEN1046.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out GEN1046 treatment-related adverse events (TRAEs) in GCT1046-01 escalation phase. TRAEs of ay grade occured in 70.5% patients, with 27.8 patients experiencing Grade 3-4 TRAEs. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/139719d2-b1db-4369-978e-9cb1ed22a581/Dose+Prediction.jpg Home - Immuno-oncology - 1-2 Punch: PD-L1 x 4-1BB et al.: Dual MOA or simply conditional bsAb ? - Make it stand out GEN1046 dose selection for expansion cohorts based on PK/PD model predicting trimer formation and PD-L1 receptor occupancy across different dose levels. Schematic of in vitro (A) and in vivo (B) semi-mechanistic PK/PD model for GEN1046, and PK/PD model output (C). Maximum levels of trimer complexes predicted at 100 mg Q3W. https://immuno-oncologyresearchtrends.com/home/2020/4/7/transforming-cars-into-off-the-shelf-therapeutics monthly 0.5 2020-05-14 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1589114078294-U0TEV3DKO8CDKZLKVR0L/F1.large.jpg Home - Immuno-oncology - CAR-NKs, CAR-Ms, Next-Gen CARs, Off-the-Shelf Therapeutics Figure 1. The full potential of CAR T cells will require parallel scientific progress to overcome primary and secondary resistance and addressing practical challenges relating to affordability and scalability (Schultz and Mackall, 2019). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1589345727280-G64WBYPMU0UTIFZTNCWJ/Untitled-2.jpg Home - Immuno-oncology - CAR-NKs, CAR-Ms, Next-Gen CARs, Off-the-Shelf Therapeutics FIgure 2. Manufacturing of allogeneic CAR T cells. Allogeneic chimeric antigen receptor (CAR) T cells from a single manufacturing batch have the potential to benefit multiple patients. The manufacturing process for allogeneic CAR-T cell products starts with a source of third- party healthy T lymphocytes collected by leukapheresis. Technologies such as viral vector- mediated transgenesis or gene knock- in mediated by gene editing enable the permanent insertion of recombinant DNA coding for a CAR and possibly additional genes, such as a suicide gene or a costimulation receptor in said lymphocytes. Technologies can also eliminate expression of αβ T cell receptor (TCR) on said T cells (for example, gene editing- mediated TCRα [TRAC] knockdown) and CD52. T cells are then expanded using anti- CD3/anti- CD28 beads and cytokines. The remaining αβ TCR- positive cells are magnetically removed using anti- αβ TCR antibodies. The vials are then filled with the allogeneic CAR T cells. The product is then stored, frozen and shipped to hospitals when needed. (Depil et al., 2020) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1589366498451-MDGRIT0KMSHJMTKP85M7/Untitled-4.jpg Home - Immuno-oncology - CAR-NKs, CAR-Ms, Next-Gen CARs, Off-the-Shelf Therapeutics Table 1. Current clinical trials of CAR-NK cells. Clinical trials featuring CAR-NK cells against various target antigens and diseases which are currently actively recruiting or are scheduled to begin recruiting in the near future. Data was obtained from clinicaltrials.gov. Abbreviations: iPSC, induced pluripotent stem cell. (Pfefferle and Huntington, 2020) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1589366722143-76ZHAHIY1LX0BWFEMW7E/Untitled-3.jpg Home - Immuno-oncology - CAR-NKs, CAR-Ms, Next-Gen CARs, Off-the-Shelf Therapeutics Figure 3. Manufacturing timeline of CAR-T cell and CAR-natural killer (NK) cell products. Comparison of the manufacturing time for CAR-T and CAR-NK cell products, from harnessing the cells for product processing to patient monitoring after treatment. Abbreviations: CRS, cytokine release syndrome; ICANS, immune e ector cell-associated neurologic syndrome; iPSC, induced pluripotent stem cell.(Pfefferle and Huntington, 2020) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1589367414616-FB8NDEN7XQB7HV35BPHH/Untitled-5.jpg Home - Immuno-oncology - CAR-NKs, CAR-Ms, Next-Gen CARs, Off-the-Shelf Therapeutics Figure 4. Examples of 4th generation CAR construct organized by subgroups. Abbreviations: scFv, single-chain variable fragment; TM, transmembrane; TRUCK, T cells redirected for universal cytokine killing. (Pfefferle and Huntington, 2020) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1589295343052-AHXNZNY3VOGVYNGKT9QT/fate-ft596-opti.png Home - Immuno-oncology - CAR-NKs, CAR-Ms, Next-Gen CARs, Off-the-Shelf Therapeutics FT596, a next generation multi-MOA CAR-NK expresses: 1. CAR, tailor-made for NK cell anti-tumor activity, a novel high-affinity, non-cleavable variant of CD16 (hnCD16) that enhances its binding to therapeutic antibodies and prevents its down-regulation, which can significantly inhibit anti-tumor activity, IL15/R to enable NK cell persistence without the need for cytokine support. https://immuno-oncologyresearchtrends.com/home/2020/3/22/true-costs-and-risks-of-covid-19-for-immuno-therapy-patients monthly 0.5 2020-03-23 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1584897786128-VHIHCGX5HJIDV4Q8C5HL/Untitled-2.jpg Home - Immuno-oncology - True Costs and Risks of Covid-19 for Immuno-therapy Patients https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1584942048867-Q9Q8QCSBNKAR31VGX9P4/Untitled-9.jpg Home - Immuno-oncology - True Costs and Risks of Covid-19 for Immuno-therapy Patients Cancer incidence and mortality statistics worldwide. (WHO) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1584962310149-PXOATQ7V2UDKWYKXKNTP/Untitled-13.jpg Home - Immuno-oncology - True Costs and Risks of Covid-19 for Immuno-therapy Patients Chances of survival are greater if cancer is diagnosed when still confined to the organ of origin (stage I). Survival rates decline as tumors enlarge and spread regionally (stages II,III) or distantly (stage IV). (Canary Foundation) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1584940501864-UA28O4L16O6GYGZZU4CK/calculation+of+additional+years+of+life+gained+by+achieving+the+stage+distribution+of+the+best+CCG+in+England Home - Immuno-oncology - True Costs and Risks of Covid-19 for Immuno-therapy Patients Calculation of additional years of life gained by achieving the stage distribution of the best CCG in England (Cancer Research UK, 2014) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1584961324309-J3QJUCUMFNVAW4FX0W4F/Untitled-11.jpg Home - Immuno-oncology - True Costs and Risks of Covid-19 for Immuno-therapy Patients QUALYs and productivity lost per patient for treatment delays for CART cell therapies for patients with pALL and DLBCL in the first treatment cohort, relative to no delay. (Snider et al., 2019) https://immuno-oncologyresearchtrends.com/home/2019/1/2/fc-mediated-effector-functions-of-therapeutic-mab monthly 0.5 2019-01-13 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1546709735363-7D90UQ0RI4ZSO7HTDITH/Untitled-3.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Figure 1. Clinical phases for antibody therapeutics in development. Data as of November 2018. Totals include only antibody therapeutics sponsored by commercial firms; those sponsored solely by government, academic or non-profit organizations were excluded; biosimilars and Fc fusion proteins were excluded. Phase 1/2 included with Phase 2; late-stage studies include pivotal Phase 2, Phase 2/3 and Phase 3. Tables of mAbs in late-stage studies are available at www.antibodysociety.org. (Kaplon et al., 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1546703442770-OAN6P12NF7D9ULXEOTSV/Untitled-1.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Figure 2. The family of Fc receptors for IgG. Human and mouse Fc receptors for IgG (FcγRs) can be distinguished by their affinity for the antibody Fc-fragment and by the signalling pathways they induce. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1546776841428-9957UI4MCJC2NX96CPHM/Untitled-1.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Figure 3. Fcγ receptor (FcγR) expression on effector cells involved in cytotoxic, neutralizing, and agonistic antibody activity. Shown are the mouse and human immune cells and the expression of their respective FcγR repertoires (Jonsson and Daeron et al., 2012). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1546779121725-49GGAUI5UO2KBW45X89Y/Untitled-3.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Table 1 . Similarities and differences of human and murine FcγRs (Lux and Nimmerjahn, 2013). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1546778308122-PQE73AOMW3W7ENJ5A7IN/Untitled-2.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Figure 4. The human FcγR family contains orthologous receptors for mouse FcγRI (human FcγRIA), IIB (human FcγRIIB), III (human FcγRIIA), and IV (human FcγRIIIA) - based on the amino acid sequence of the extracellular domain - and can be distinguished by means of signal transduction and affinity for their respective ligands. Of note, certain human Fcγ-receptors, such as FcγRIIC and FcγRIIIB, do not exist in mice, and several of the human orthologues have nonverlapping functions compared to their mouse counterparts (Lux and Nimmerjahn, 2012). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1546779563659-B0YA73OSUTKOYNRNV4UZ/Untitled-5.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Table 2 . Affinity of human IgG subclasses with mouse and human FcγRs (Lux and Nimmerjahn, 2012) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1547407431967-TS5R9SGEPHU0B9LSITYF/Untitled-7.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Figure 5. Top: Selected engineered IgG1-Fc variants with enhanced CDC activity. Bottom: IgG1 molecule with marked E345 position. Antibodies harboring amino acid exchanges at this (or other) positions are expressed as monomeric IgG molecules but form hexamers at the cell surface of target cells after antigen binding (Kellner et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1547406786602-K2TXUQ0MV2TOOSQT5YR4/Untitled-6.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Figure 6. Antibody model of a human IgG1 molecule engineered by exchanging selected amino acid positions. Yellow: amino acid substitutions introduced in Margetuximab (Macro-Genics). Purple: amino acid substitutions introduced in MOR208, Xmab-5574 (Xencor, MorphoSys) (Kellner et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1547406590029-10DMJ8KXW220CWNDIXPG/Untitled-5.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Table 3. Approaches to manipulate antibody fucosylation (Kellner et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1547407822922-9SDCR39Z4TDB65MGT0JK/Untitled-8.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Table 4. Examples of Fc-engineered antibodies in advanced stages of clinical development (Kellner et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1547394072187-SDYWQC5PD3OJDAR9FXQ4/Untitled-2.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Figure 7. Mechanism of action (MOA) of Rituximab (left) vs Obinutuzumab (right). Rituximab relocalizes CD20 to lipid rafts and appears to evoke minimal DCD but induces significant complement-dependent cytotoxicity (CDC) and antibody-dependent cellular cytotoxicity (ADCC). In contrast, obinutuzumab does not induce CDC, but, by virtue of alternative binding to the CD20 molecule, can evoke greater DCD chiefly by mechanisms that are largely caspase-independent. The afucosylated Fc portion appears to confer more potent induction of ADCC and antibody-dependent phagocytosis (ADP) than rituximab. ADCC, antibody dependent cellular cytotoxicity, ADP, antibodydependent phagocytosis; CDC, complement dependent cytotoxicity; DCD, direct cell death; FCGR3A, Fcc receptor 3A (Freeman and Sehn, 2018). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1547394946302-RLU19ADB079WPLINLGMF/Untitled-3.jpg Home - Immuno-oncology - Next generation therapeutic mAb: Does Fc-engineering translate into clinical efficacy Figure 8. Outcome curves from comparative clinical trials. (A) PFS curve from GAUSS – no difference between obinutuzumab and rituximab monotherapy. (B) PFS curve from GALLIUM – statistically significant benefit with G-chemo arm compared with R-chemo. (C) PFS curve from CLL-11 (updated) – statistically significant benefit with G-Clb compared with R-CLB. (D) PFS curve from GOYA – no difference between G-CHOP and R-CHOP (Freeman and Sehn, 2018). https://immuno-oncologyresearchtrends.com/home/2018/9/9/i-o-in-the-era-of-precision-medicine-evaluating-the-therapies-and-predicting-the-outcome monthly 0.5 2018-09-14 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1536665244406-R7QG0101Y4O6ZHVJASIK/gr3.jpg Home - Immuno-oncology - Predicting the Efficacy and Outcome of I-O Therapies: Between Avatars, Ancers and Algorithms Figure 1. Objective responses across tumour PD-L1 expression levels (CheckMate 012; Hellmann et al., 2016) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1536741836234-A8VUC1BUZA7CME08TGQD/Nanostring.jpg Home - Immuno-oncology - Predicting the Efficacy and Outcome of I-O Therapies: Between Avatars, Ancers and Algorithms Figure 2. Actionable immune-based classification of cancer by The PanCancer IO 360™ assay (NanoString Technologies Inc.). Anticancer immunity in humans can be histologically segregated into three main phenotypes: the inflamed phenotype (also known as “hot”), the immune-excluded phenotype, and the immune-desert phenotype (the latter two considered “cold” tumours). The TIS gene expression profiling algorithm described by Ayers et al. (2017) is at the base of this decision tree. Additional mechanisms of peripheral immune suppression may exist, including other IC as well as negative regulatory cell subtypes. In the case of the non-inflamed phenotype, the next important question to be answered is whether there are defects in T cell trafficking or in appropriate T cell priming and activation (intrinsic to the tumor or specific to the host). The IO360 panel supports the development of signatures to potentially predict a patient response to a variety of immunotherapeutic interventions. Within the framework of the panel, the biology of the tumour can be matched with the mechanism of action of a particular drug. (Cesano and Warren, 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1536839267060-F9RHQW26U5EOWXN9UESL/HIS.jpg Home - Immuno-oncology - Predicting the Efficacy and Outcome of I-O Therapies: Between Avatars, Ancers and Algorithms Figure 3. Strategies to generate humanized PDXs. Sources of immune cells include tumour-infiltrating lymphocytes (TILs), peripheral blood mononuclear cells (PBMCs) or CD34‑positive haematopoietic stem cells (HSCs); HSCs may be purified from mobilized adult peripheral blood, bone marrow or umbilical cord blood. (Byrne et al., 2017) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1536929358374-014D5LP3F0AI1LRWFIS4/Untitled-1.jpg Home - Immuno-oncology - Predicting the Efficacy and Outcome of I-O Therapies: Between Avatars, Ancers and Algorithms Figure 4. Genetic modification of HIS mice to improve HSC and PBMC engraftment, and to diminish xeno-GvHD. (De La Rochere et al., 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1536926051402-GJ4YCXEHD67L1NY7TTWA/pdx.jpg Home - Immuno-oncology - Predicting the Efficacy and Outcome of I-O Therapies: Between Avatars, Ancers and Algorithms Figure 5. PDX preclinical/co-clinical study designs. a | PDX models allow population-based studies to be carried out, which better mimic the inter-tumour heterogeneity that is seen in patients and are more predictive of clinical efficacy than conventional xenografts of immortalized cancer cell lines. PDX molecular characterization and correlation with therapeutic response also facilitates biomarker discovery, as well as the identification of primary (and acquired) resistance mechanisms. b | Co‑clinical avatar studies allow for simultaneous drug testing in mice and patients for real-time adaptive therapeutic decisions. c | In the ‘biofacsimile’ or ‘proxy’ study format, integrative systems-based bioinformatics analysis can be used to pinpoint the best-matched PDX for a given patient from a collection of molecularly profiled models. PDX associated information is then leveraged to instruct clinical treatment options and/or to derive prognostic indicators. (Byrne et al., 2017) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1536843080205-XN0BHOZ26VHI68840EXW/Untitled-2.jpg Home - Immuno-oncology - Predicting the Efficacy and Outcome of I-O Therapies: Between Avatars, Ancers and Algorithms Figure 6. Comparative quantitative data of response rates in PDXs versus human patients (all non-HIS model setting). (Byrne et al., 2017) https://immuno-oncologyresearchtrends.com/home/2018/7/21/cancer-re-direction-and-t-cell-therapies-cars-vs-bites-or-tcr-and-immtacs monthly 0.5 2018-07-29 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1532757463662-LUBCUDIYDTZGDOANBNUS/Untitled-1.jpg Home - Immuno-oncology - Bridging T cells to Tumors: CARs vs BsAb Figure 1. Advantages and disadvantages of some adoptive cell therapy approaches. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1532269116182-55UQPHKB95DEX3XDUZ7L/CAR.jpg Home - Immuno-oncology - Bridging T cells to Tumors: CARs vs BsAb Figure 2. The design of a CAR T cell. A CAR comprises an extracellular domain, which is an scFv targeting TAA. The scFv is followed by a hinge of varying length and flexibility (CD8 as an example) and various combinations of endodomains that provide T-cell activation signals, such as CD3ζ, and a costimulation signal, such as CD28. TM, transmembrane. (Slaney et al., 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1532266971472-DJDP6KNH8XWICSZTXCVG/Targets-of-CAR-T-Cell-Therapy-pic-1.png Home - Immuno-oncology - Bridging T cells to Tumors: CARs vs BsAb Figure 3. The history of CAR therapy development. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1532760196685-971CMHY1OUFQICMJGCKN/Untitled-1.jpg Home - Immuno-oncology - Bridging T cells to Tumors: CARs vs BsAb Figure 4. Chimeric antigen receptor design. First generation CARs include the intracellular domain of CD3ζ, which contains 3 ITAM domains (red). Second generation CARs also include the intracellular domain of a costimulatory molecule such as 4-1BB or CD28, whereas third generation CARs include 2 or more costimulatory domains in addition to CD3ζ. (Zhukovsky et al. 2018). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1532759130111-0QOH4I7VWODVZY9C72V0/Untitled-2.jpg Home - Immuno-oncology - Bridging T cells to Tumors: CARs vs BsAb Figure 5. Solid tumor targets amenable for CAR-T cell approaches. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1532262628352-KK6FJAKFM4582JTDNL9C/Untitled-1.jpg Home - Immuno-oncology - Bridging T cells to Tumors: CARs vs BsAb Figure 6. Selected BsAb formats. BsAbs can be broadly divided into molecules that contain or do not contain an immunoglobulin G backbone with a functional Fc domain. BsABs can be created by chemical crosslinking 2 mAbs or recombinant DNA technology. Fab, fragment antigen binding; CH, heavy chain; CL, light chain; DART, dual-affinity retargeting; sc, single chain; scFv, single-chain variable fragment (Velasquez et al., 2018). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1532271744255-A0DFJIWP5BY6D43CXRB4/Untitled-3.jpg Home - Immuno-oncology - Bridging T cells to Tumors: CARs vs BsAb Figure 7. Comparison of CAR T cells and BiTEs https://immuno-oncologyresearchtrends.com/home/2018/4/28/awakening-personalization-of-cancer-vaccines-the-neo-anti-gen-era monthly 0.5 2018-05-23 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1527101985243-QXOK5OTC6R8W2JKN9IU7/Untitled-1.jpg Home - Immuno-oncology - The Neo-Anti-Gen Era introduces personalized cancer vaccines Table 1. Shared peptide antigens have been identified which can be used to broadly vaccinate patients of the same cancer type when those patients commonly express that antigen (top). Vaccines incorporating personalized neoantigens cater specifically to that individual patient or tumor, and so are promising targets to activate antitumor immunity (bottom) (Aldous et al., 2017) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1526918529122-7KNXLXNYIGDZZ46BDCAZ/Untitled-1.jpg Home - Immuno-oncology - The Neo-Anti-Gen Era introduces personalized cancer vaccines Table 2. Features of current neo-epitope prediction tools (Bjerregaard et al. 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1527014515074-WTHXTTYRTI35XI0VACTU/Untitled-1.jpg Home - Immuno-oncology - The Neo-Anti-Gen Era introduces personalized cancer vaccines Figure 1. Overview of the experimental approach of mutated peptide ligands identification by matching exome sequencing and MS immunopeptidomics. Patient tumour tissue is used for MS analysis and exome sequencing. Mutations are called and matched with MS data. Mutated peptide ligands are then further evaluated for recognition by patient’s autologous and matched allogeneic T cells (Bassani-Sternberg et al. 2016). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1527072542290-JOI65OWM261AY9FAHOBL/Untitled-1.jpg Home - Immuno-oncology - The Neo-Anti-Gen Era introduces personalized cancer vaccines Figure 2. The typical workflow for neoepitope selection and vaccine manufacture. DNA and RNA are extracted from single-cell suspensions of tumour cells and matched normal tissue cells. Somatic mutations of tumour cells are discovered by whole-exome sequencing (WES). RNA sequencing (RNA-seq) narrows the focus to mutations of expressed genes. Clinical HLA typing is carried out on DNA from normal tissue. The potential antigenicity of neoepitopes identified by WES and RNA-seq is assessed by predicting the affinity of the neoepitopes for binding to the HLA type of that individual (using NetMHCpan), thereby generating candidate vaccine epitopes. Validated epitopes are selected for incorporation into the personalized cancer vaccine, which is administered to patients in combination with an immune adjuvant (Hu et al. 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1527075101451-1IU2QJAQXIBMI1P54PNP/Untitled-4.jpg Home - Immuno-oncology - The Neo-Anti-Gen Era introduces personalized cancer vaccines Figure 3. Strategies to improve personalized neoantigen vaccines for cancer (Hu et al. 2017). https://immuno-oncologyresearchtrends.com/home/2018/2/1/moa-of-oncolytic-virotherapy-oncolysisantitumor-immunityantiviral-immunity monthly 0.5 2018-04-12 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1523288589630-FYL4GRYYZME6IG77THH1/nihms301993f1.jpg Home - Immuno-oncology - Oncolysis + Antitumor&Antiviral Immunity = Success of Oncolytic Virotherapy Figure 1. Mechanisms of tumor targeting by oncolytic viruses. (a) Transcriptional targeting. An essential viral gene is placed under the control of a tumor-specific promoter (some virus promoters are naturally tumor specific). (b) Translational targeting. The virus is engineered (or adapted) to disable viral proteins that antagonize the cellular interferon (IFN) response. (c) Pro-apoptotic targeting. The virus is engineered (or adapted) to disable viral proteins that prevent apoptosis. (d) Transductional targeting. The virus gains entry to its target cells through a receptor expressed more abundantly on tumor cells than on normal cells. Alternatively, the attachment specificity of the virus can be reprogrammed towards tumor antigens by the display of single-chain antibodies or other polypeptide-binding ligands on the viral surface. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1523449697098-WF67GS40WUFE1IZR5FKV/Untitled-2.jpg Home - Immuno-oncology - Oncolysis + Antitumor&Antiviral Immunity = Success of Oncolytic Virotherapy Figure 2. OVs as immunotherapeutics. (Chaurasiya et al., 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1523522935144-FQ70GNJPKZ75XUYGQQVW/Untitled-2.jpg Home - Immuno-oncology - Oncolysis + Antitumor&Antiviral Immunity = Success of Oncolytic Virotherapy Figure 3. Modulation of the tumor microenvironment by OVs and elicitation of anti-tumor immunity. (i) OVs induce inflammation and increase proinflammatory cytokines (IL-6 and IL-8) and foster tumor infiltration by NK cells and other TILs. (ii) OV infection increases NK cell-mediated tumor cell killing (reduction in MHC I). (iii) Oncolysis by OVs causes ICD with the release of tumor-associated/specific antigens. (iv) Antigen-loaded APCs migrate to the lymph node, where (v) they cross-present tumor antigens to CD8+ T cells. (vi) Following activation, the tumor-specific CD8+ T cells undergo expansion. (vii) The tumor-specific T cells move to both OV injected and un-injected tumors (distant metastases) where they can exert anti-tumor effect. (Chaurasiya et al., 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1523375355327-I0YRRJZ13S0Z84GECW0K/Untitled-1.jpg Home - Immuno-oncology - Oncolysis + Antitumor&Antiviral Immunity = Success of Oncolytic Virotherapy Table 1. Combination therapy of armed oncolytic viruses and immune modulators. (Graaf et al., 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1517590969770-BUDQLX292SGXUAJE2LZA/Untitled-2.jpg Home - Immuno-oncology - Oncolysis + Antitumor&Antiviral Immunity = Success of Oncolytic Virotherapy Figure 4. Maraba treatment results in complete responses in the window of opportunity setting. (A) Schematic representation of the treatment schedule used for the tumor rechallenge model. (B to D) Tumor growth and Kaplan-Meier survival curves obtained using 4T1 (B), EMT6 (C), or E0771 (D) cells in the tumor rechallenge model (n = 10 mice per group per experiment). Maraba treatments were administered intratumorally. NT, no treatment. (E and F) The same experiment as in (B) was repeated using intravenous delivery of Maraba virus (E) or immunocompromised CD-1 nude mice (F). (G) Primary EMT6 or 4T1 tumors were treated with Maraba or left untreated and were resected, and all animals were rechallenged with 4T1 tumors. The dotted lines indicate the time of Maraba treatment. Statistical analysis for tumor measurements: *P < 0.05, **P < 0.01, ***P < 0.001 (unpaired multiple two-tailed t test). Statistical analysis for survival curves: *P < 0.05, **P < 0.01, ***P < 0.001 (Mantel-Cox test). (Bourgeois-Daigneault etal., 2018) https://immuno-oncologyresearchtrends.com/home/2018/3/2/heating-up-the-tumors-sting-vs-inflammasome monthly 0.5 2018-03-11 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1520064424575-7TE9D9PQCKXOBETI0Y82/Untitled-1.jpg Home - Immuno-oncology - Battle of the hottest: STING and Inflammasome - Heating up the tumors Figure 1. Selected precision innate immune system agonists (Mullard, 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1520068149258-7XMNR848CKTLTYLS9NPE/F1.large.jpg Home - Immuno-oncology - Battle of the hottest: STING and Inflammasome - Heating up the tumors Figure 2. The tumor immunity continuum. Representative images of tumor CD8 IHC show three patterns of T cells associated with tumor cells. Tumors with preexisting immunity are represented by abundance of TILs, dense functional CD8+ T-cell infiltration reflected by increased IFNγ signaling, expression of checkpoint markers, including PD-L1, and high mutational burden. These characteristics reflect highly inflamed tumors. Despite high mutational burden, tumors with the excluded infiltrate or stromal T-cell phenotype are represented by increased influence of immunosuppressive reactive stroma, myeloid-derived suppressor cells (MDSC), and angiogenesis, all of which prevent infiltration of T cells into the tumors or suppress activation of T cells in the tumor milieu. Finally, immunologically ignorant tumors that contain very low infiltration of T cells are genomically stable with highly proliferating tumor cells. These are representative of noninflamed tumors. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1520678663379-9ZVUKISFDX1M7D9QEU1I/Untitled-2.jpg Home - Immuno-oncology - Battle of the hottest: STING and Inflammasome - Heating up the tumors Figure 3. Mammalian TLR signalling pathways. TLR5, TLR11, TLR4, and the heterodimers of TLR2–TLR1 or TLR2–TLR6 bind to their respective ligands at the cell surface, whereas TLR3, TLR7–TLR8, TLR9 and TLR13 localize to the endosomes, where they sense microbial and host-derived nucleic acids. TLR4 localizes at both the plasma membrane and the endosomes. (O'Neill et al., 2013) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1520139223971-C714Y7TJXS5RM56VE5XA/Untitled-2.jpg Home - Immuno-oncology - Battle of the hottest: STING and Inflammasome - Heating up the tumors Figure 3. Stimulator of interferon genes (STING) is activated by cyclic dinucleotides (CDNs) produced by certain bacteria or by cyclic GMP–AMP synthase (cGAS), which in the presence of ATP and GTP catalyses the production of a type of CDN referred to as cGAMP (cyclic GMP–AMP) following binding to cytosolic DNA species (from viruses or bacteria, or self -DNA from the nucleus or mitochondria). STING is associated with the endoplasmic reticulum (ER) and, following binding to CDNs, STING forms a complex with TANK-binding kinase 1 (TBK1). This complex traffics to the perinuclear Golgi via pre-autophagosomal-like structures — a process resembling autophagy — to deliver TBK1 to endolysosomal compartments where it phosphorylates the transcription factors interferon regulatory factor 3 (IRF3) and nuclear factor-κB (NF-κB). Stimulation of the IRF3 and NF-κB signalling pathways leads to the induction of cytokines and proteins, such as the type I interferons (IFNs), that exert anti-pathogen activity. c-di-AMP, cyclic di-AMP; dsDNA, double-stranded DNA; ISGF3, interferon-stimulated gene factor 3; JAK, Janus kinase; STAT, signal transducer and activator of transcription; TYK, tyrosine kinase. (Barber, 2015) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1520696713623-2G73LVCWHW7H6CN82YBM/Untitled-3.jpg Home - Immuno-oncology - Battle of the hottest: STING and Inflammasome - Heating up the tumors Figure 4. STING-dependent antitumour cytotoxic T lymphocyte (CTL) priming. Dying tumour cells are engulfed by antigen-presenting cells such as CD8α+ dendritic cells (DCs). DNA from the engulfed cell triggers STING-dependent cytokine production in the phagocyte, which facilitates cross-presentation and antitumour CTL responses. Agonists of STING have been shown to exert potent antitumour activity. (Barber, 2015) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1520698923867-7WGHD4OQ3SJIXXNHB1LL/Untitled-4.jpg Home - Immuno-oncology - Battle of the hottest: STING and Inflammasome - Heating up the tumors Table 1. . Current and Potential Therapeutic Mechanisms Enhance or Target cGAS–STING Signaling. (Ng et al., 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1520700446980-SK53RGKOOSU3YYROXDPI/Untitled-3.jpg Home - Immuno-oncology - Battle of the hottest: STING and Inflammasome - Heating up the tumors Figure 5. The inflammasome. Before 2002, it was known that, in response to infection by a bacterial pathogen, the enzyme caspase 1 can promote the release of inflammatory signalling molecules, such as interleukin-1β (IL-1β) and IL-18, and that caspase 1 also has a role in pyroptosis, a type of cell death that can eliminate immune cells. However, how caspase 1 is activated and induces pyroptosis was unknown. In 2002, Martinon, Burns and Tschopp discovered that innate-immune receptor proteins from the NLR protein family and the adaptor protein ASC assemble into an inflammasome complex that recruits and activates caspase 1. Diverse inflammasome complexes have been identified and the innate-immune receptors in some inflammasomes are not NLRs but are instead AIM2 or pyrin proteins. Another key advance was the identification of the non-canonical inflammasome pathway, in which caspase 4, 5 or 11 act upstream of caspase 1 activation. Caspase mediated cleavage of the protein gasdermin D is the mechanism that enables inflammatory caspase activation to induce pyroptosis in both the canonical and non-canonical inflammasome pathways. (Lamkanfi and Dixit, 2017) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1520146322554-9U4LYNUJKJ1DCUSWAM32/Untitled-2.jpg Home - Immuno-oncology - Battle of the hottest: STING and Inflammasome - Heating up the tumors Figure 5. Activation of the NLRP3 inflammasome and its inhibition by CY-09 and sulfonylurea compounds. Activation of the NLRP3 inflammasome involves two steps. First, TLR4 stimulation induces transcriptional up-regulation of NLRP3 and the inflammasome substrate proIL-1β. In the second activation step, NLRP3 agonists such as ATP, the ionophore nigericin, pore-forming toxins and internalized crystals, and β-fibrils trigger NLRP3 oligomerization, ASC speck formation, and inflammasome-mediated caspase-1 autoactivation. Caspase-1 cleaves its cytokine substrates IL-1β and IL-18, and it induces pyroptosis through cleavage of gasdermin D, which promotes the passive release of IL-1β and IL-18 along with DAMPs such as IL-1α and HMGB1. CY-09 inhibits NLRP3 inflammasome assembly by blocking ATP/dATP binding in the central NACHT domain, whereas the target and mechanism of action of sulfonylurea compound MCC950/CRID3 are unknown. (Lamkanfi and Dixit, 2017) https://immuno-oncologyresearchtrends.com/home/2018/2/5/epigenetics-meets-immune-oncology monthly 0.5 2018-02-10 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1518270638844-D1W0E9MHCSZ752URIXLK/Untitled-1.jpg Home - Immuno-oncology - Epigenetics meets immuno-oncology Figure 1. Chromatin regulators involved in transcription induction. List of chromatin remodellers, chromatin modifiers (writers and erasers of histone posttranslational modifications (PTMs)) and histone PTM readers. Their function and status in cancer are indicated (Marazzi et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1518006290663-8AON3JNFO07NOZDA1V9N/Fig+1.jpg Home - Immuno-oncology - Epigenetics meets immuno-oncology Figure 2: Major epigenetic mechanisms affecting gene activity (Rajender et al., 2011). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1518271146713-TQV9OTP7YADT384HIC8M/Untitled-2.jpg Home - Immuno-oncology - Epigenetics meets immuno-oncology Figure 3. Chromatin remodelling and susceptibility to inhibitors. Chemical inhibitors of regulatory proteins that control gene activation preferentially affect the expression of genes that require chromatin remodelling for induction in response to inflammatory or mitogenic stimuli. (a) Illustration of drug inhibitors acting on their respective targets to affect inducible gene expression. Inhibition (denoted by an ‘i’) of chromatin factors involved in RNA polymerase II (Pol II) pause–release, such as bromodomain and extra-terminal domain (BET) proteins and cyclin-dependent kinases (CDK7, CDK8 and CDK9), primarily affect genes with promoters that are linked to super enhancers and more in general to highly-induced genes. Inhibition of protein arginine N-methyltransferases (PRMTs) at R-loops and inhibition of DNA topoisomerase 1 (TOP1) also preferentially affect inducible genes such as those linked to the inflammatory response. (b) Chromatin features of chromatin-remodelling-independent genes and chromatin-remodelling-dependent genes. (c) Chromatin regulators and examples of their inhibitors (Mazzini et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1518244255751-LM1OOU2T6X2YQU9XFFB4/Fig.+3.jpg Home - Immuno-oncology - Epigenetics meets immuno-oncology Figure 4. Re-education of cancers cell towards visibility for immune attack (Dunn and Rao, 2018). (A) Several key papers have recently identified IFN signalling genes (1) that are activated in response to DNA demethylation (Roulois et al., 2015 and Chiappinelli et al., 2016) or (2) that have genomic defects in immune checkpoint resistant tumours (Gao et al., 2016). (B) At the chromatin level, immune genes are silenced in a closed heterochromatin state in tumour cells and the addition of epigenetic drugs re-educates immune genes to become open and transcriptionally active (Dunn and Rao, 2018) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1518247450863-NRFSFIYFTV4SBQLO3N8M/Figure+3.jpg Home - Immuno-oncology - Epigenetics meets immuno-oncology Figure 5. The differences in action of epigenetic modulation on anti-CTLA4 and anti-PD1 IC therapy (Gallagher et al., 2017). (A) Anti-CTLA4 (αCTLA4) enhances T-cell priming in draining lymph nodes by blocking the inhibitory B7-CTLA4 interactions while permitting the co-stimulatory B7-CD28 engagement. B7 expression on dendritic cells is increased as it is controlled by Treg-cells in a CTLA4 dependent fashion. DNMTi increase the availability of tumor antigens, including neo-antigens, while HDACi improve antigen uptake, thus facilitating priming of novel tumor-specific T-cell clones. (B) Anti-PD1 (αPD1) activates T-cells at the tumor site and its efficacy depends upon the presence of tumor immune infiltrate including CD8 T-cells but also CD4 T-cells and antigen-presenting cells such as tumor-associated macrophages and dendritic cells. Antigen persistence and chronic inflammation render tumor-infiltrating T-cells dysfunctional through epigenetic modifications and also convert CD4 T-cells into immunosuppressive Treg-cells. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1518249479953-MHLY0WO2CY5Q9BGVHDOE/Fig.+4.jpg Home - Immuno-oncology - Epigenetics meets immuno-oncology Table 1. Clinical trials combining epigenetic modulators and immune checkpoint inhibitors in cancer (Gallagher et al., 2017). https://immuno-oncologyresearchtrends.com/home/2018/1/12/resurgence-of-cancer-vaccines monthly 0.5 2018-01-20 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1515921559328-8TY0M0ST5URSMVJP36DV/Untitled-3.jpg Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 1. ORRs-based (arbitrary) comparison of efficacy of conventional chemotherapy/radiotherapy, targeted therapy, cytokine therapy, DC vaccines, and specific ICIs against melanoma, glioblastoma, and renal cell carcinoma (RCC). (Garg et al., 2017) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1515915053056-RL3Y0VVJE6029QFTKNUR/Untitled-1.jpg Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 2. History of cancer vaccines (Hu et al., 2017) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1516282419114-ZTBX4722WXCPJXE7027H/nri.2017.9-f2.jpg Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 3. The initiation of adaptive immunity by dying cells requires a set of immunological events, the coordination of which leads to the priming of T cells. Four dendritic cell (DC)-derived signals act on T cells (lower panel): signal 1 is the antigen-recognition event that is mediated through the T cell receptor (TCR), and triggered by MHC class I-associated or MHC class II-associated peptides processed from the antigen after the phagocytosis of dying cells. Signal 2 is the co-stimulation event, which is mediated by engagement of CD28 by CD80 and CD86. Signal 3 is the polarizing and differentiation signal delivered from the DC to the T cell that determines its differentiation into an effector cell. Soluble molecules such as interleukin-12 (IL-12) family members, and interferon-α (IFNα) and IFNβ, are mediators that deliver signal 3. There are data indicating that DCs may also provide T-cells with an additional signal (tentatively termed 'signal 4'), which regulates organ-specific trafficking of immune cells. The upregulation of co-stimulatory molecules (signal 2) and the secretion of inflammatory cytokines by DCs (signal 3) depend on the activation of pattern recognition receptors (PRRs) by microbe-associated molecular patterns (MAMPs), or by constitutive or inducible damage-associated molecular patterns (cDAMPs or iDAMPs, respectively; lower left panel). The DC activation event has been termed signal 0. Recent data have established that the activation of innate immune pathways within dying cells, such as the nuclear factor-κB (NF-κB) pathway, represents an earlier immunological event that regulates the outcome of T cell priming. We propose to designate this event signal −1 (upper panel), although the manner by which it influences the immune response is still unclear. IRF, IFN-regulatory factor. The dashed arrow indicates crosstalk between cell death effectors and innate immune pathways. (Yatim et al., 2017) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1515776669080-163AI6UZGR4PWBAWAU3Z/Untitled-2.jpg Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 4. Important tumor antigens for vaccines (Finn, 2017) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1516468095706-P94NFD24KW4MGG7R0H3W/Untitled-5.jpg Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 5. Neoantigen-based therapeutic cancer vaccines. a | The typical workflow for neoepitope selection and vaccine manufacture. b | The schema of three phase I clinical trials of personalized neoantigen vaccines in patients with melanoma. c | Strategies to improve personalized neoantigen vaccines for cancer (Hu et al., 2017) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1516467897955-ZNO6N0DWMW29YCL9HPR6/Untitled-4.jpg Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 6. Mechanisms and components of an effective cancer vaccine. a | The tumour antigen presentation process. b | There are four key components of cancer vaccines: tumour antigens, formulations, immune adjuvants and delivery vehicles (Hu et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1516462194756-DAAH5SDGFKUAFEYR3JK7/Untitled-1.jpg Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 7. Multiple novel oncogenic drivers have been identified in non-small-cell lung cancer (NSCLC) that might be amenable to therapeutic targeting (Rotow et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1516464534086-DVTUXGDXVWX5P1K5I4H2/Untitled-2.jpg Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 8. Leading mRNA vaccine developers: research focus, partners and therapeutic platforms (Pardi et al. 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1515921996003-UPCHMI2M91DXXL3VTMRR/Untitled-4.png Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 9. Integrating next-generation vaccines into highly efficacious, biomarkers-driven, combinatorial regimens against cancer. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1516466955008-8UPSTP9561O3RJAIYDW0/nri.2017.140-f1.jpg Home - Immuno-oncology - Guidelines for the next-generation cancer vaccines Figure 8. The dawn of vaccines for cancer prevention (Finn, 2017) https://immuno-oncologyresearchtrends.com/home/2017/12/29/the-io-recap-of-2017 monthly 0.5 2018-01-05 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1514890604868-57LUWGPHE5U6K6KFCJYX/modpathol2017156f3.jpg Home - Immuno-oncology - I-O Research: 2017 Recap & Proleptic Challenges for the Field in 2018 Figure 1. Timeline of FDA approvals for immune checkpoint blocking agents, including PD-L1 immunohistochemistry companion and complementary diagnostics (Taube et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1514732109819-VYRB2QBY0DZSHRTIVF6N/1-s2.0-S009286741730065X-gr2_lrg.jpg Home - Immuno-oncology - I-O Research: 2017 Recap & Proleptic Challenges for the Field in 2018 Figure 2. Known Intrinsic Mechanisms of Resistance to Immunotherapy (A) Intrinsic factors that lead to primary or adaptive resistance including lack of antigenic mutations, loss of tumor antigen expression, loss of HLA expression, alterations in antigen processing machinery, alterations of several signaling pathways (signaling through MAPK and loss of PTEN expression, which enhances PI3K signaling, expression of WNT/b-catenin, loss of IFNg signaling pathways), and constitutive PD-L1 expression. (B) Intrinsic factors that are associated with acquired resistance of cancer, including loss of target antigen, HLA, and altered interferon signaling, as well as loss of T cell functionality. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1514733015449-MAWVTOVKJS06K5O542BL/1-s2.0-S009286741730065X-gr3_lrg.jpg Home - Immuno-oncology - I-O Research: 2017 Recap & Proleptic Challenges for the Field in 2018 Figure 3. Known Extrinsic Mechanisms of Resistance to immunotherapy. This includes CTLA-4, PD1, and other immune checkpoints, T cell exhaustion and phenotype change, immune suppressive cell populations (Tregs, MDSC, type II macrophages), and cytokine and metabolite release in the tumor microenvironment (CSF-1, tryptophan metabolites, TGF-b, adenosine). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1515142157893-G25QBC9YLLPFA10NXV9N/Immunity.jpg Home - Immuno-oncology - I-O Research: 2017 Recap & Proleptic Challenges for the Field in 2018 Figure 4. Combination Immunological Interventions Can Form an Effective Combinatorial Cancer Immunotherapy. The 3pRNA-mediated MDSC reprogramming and reversal of the tumor’s immunosuppressive environment will ensure that high levels of IFN-a will be produced locally.MDSC reprogramming should be accompanied by a vaccination optimized to induce maximum CD8+ T cell immunity. A large panel of antigens covering CD4+ helper T cell and CD8+ cytotoxic T-cell-specific epitopes should be employed in the form of overlapping synthetic long peptides (SLPs). Coupling these SLPs directly to an adjuvant augments dendritic cell (DC) activation and subsequent antigen presentation. Choosing the adjuvant to ensure IL-12 and IFNa production by the activated DCs augments T cell priming and effector function. By using systemic antibody-mediated CTLA4 or PD-1 blockade, physiological immune checkpoints to limit T cell proliferation upon activation or T cell effector function upon target cell recognition, respectively, are blocked. T cells proliferate in the IL-12 and IFNa inflammatory environment, and tumor cell killing can initiate upon target cell recognition. (Boorn et al., 2016) https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1514989229410-RCB392QEMBCEQL995T70/Untitled-2.jpg Home - Immuno-oncology - I-O Research: 2017 Recap & Proleptic Challenges for the Field in 2018 Figure 4. Side-by-side comparison of attributes of TCR and CAR gene-engineered T cells for targeting tumor antigens https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1515067712636-V42U8RFCC3K60339TURY/Untitled-1.jpg Home - Immuno-oncology - I-O Research: 2017 Recap & Proleptic Challenges for the Field in 2018 Figure 5. Coggle diagram of completed and ongoing TCR and CAR gene-engineered T-cell immunotherapy clinical trials (per ClinicalTrials.gov). https://immuno-oncologyresearchtrends.com/privacy daily 0.75 2017-12-29 https://immuno-oncologyresearchtrends.com/about-the-io-research-trends daily 0.75 2017-12-30 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1514576139237-LH602P6N2M48IVBV8QEE/I-O+Research+Trends-logo.png About the I-O Research Trends https://immuno-oncologyresearchtrends.com/terms daily 0.75 2017-12-29 https://immuno-oncologyresearchtrends.com/contact-us daily 0.75 2017-12-29 https://immuno-oncologyresearchtrends.com/be-a-contributor daily 0.75 2017-12-30 https://immuno-oncologyresearchtrends.com/new-page daily 0.75 2018-01-05 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1514651795442-HHU9E0GZO90YT7VIDNNR/13045_2017_457_Fig2_HTML.gif The (R)evolution/Success(ion) of I-O Figure 1. A timeline of important clinical and translational events and timelines in the evolution of cancer immunotherapy. Black represents basic science discoveries and red represents clinical or translational discoveries (Mehta et al., 2017). https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1515162841174-FKSDOQ9IN58D8O9EM31P/Untitled-1.jpg The (R)evolution/Success(ion) of I-O Figure 2. The overview of 2,004 immuno-oncology (IO) agents. Six classes of IO agents are identified on the basis of different mechanisms of actions. https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1514635217754-NBX2Y5B58LFLZ5CAQGM9/Untitled-1.png The (R)evolution/Success(ion) of I-O Figure 3. Mechanisms operating in the establishment of immunoresistant niches (Syn et al., 2017). https://immuno-oncologyresearchtrends.com/about-us daily 0.75 2018-01-01 https://images.squarespace-cdn.com/content/v1/5a461197e5dd5b896a68a545/1514832758910-JUZ0IU3DB79YRZV78D0N/cancer-immunity-cycle.png About Cancer Immunity Figure 1. Cancer Immunity Cycle https://immuno-oncologyresearchtrends.com/disclaimer daily 0.75 2018-02-04 https://immuno-oncologyresearchtrends.com/privacy-tudor daily 0.75 2025-05-12