Literature DB >> 32269031

New emerging targets in cancer immunotherapy: the role of neoantigens.

Leticia De Mattos-Arruda1, Juan Blanco-Heredia2, Carmen Aguilar-Gurrieri3, Jorge Carrillo2, Julià Blanco4.   

Abstract

The success of cancer therapies with immune checkpoint inhibitors is transforming the treatment of patients with cancer and fostering cancer research. Therapies that target immune checkpoint inhibitors have shown unprecedented rates of durable long-lasting responses in patients with various cancer types, but only in a fraction of patients. Thus, novel approaches are needed to make immunotherapy more precise and also less toxic. The advances of next-generation sequencing technologies have allowed fast detection of somatic mutations in genes present in the exome of an individual tumour. Targeting neoantigens, the mutated peptides expressed only by tumour cells, may enable antitumour T-cell responses and tumour destruction without causing harm to healthy tissues. Currently, neoantigens can be identified in tumour clinical samples by using genomic-based computational tools. The two main treatment modalities targeting neoantigens that have been investigated in clinical trials are personalised vaccines and tumour infiltrating lymphocytes-based adoptive T-cell therapy. In this mini review, we discuss the promises and challenges for using neoantigens as emergent targets to personalise and guide cancer immunotherapy in a broader set of cancers. © Author (s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. Published by BMJ on behalf of the European Society for Medical Oncology.

Entities:  

Keywords:  adoptive T cell; checkpoint inhibitors; immunotherapy; neoantigens; next generation sequencing; vaccines

Mesh:

Substances:

Year:  2020        PMID: 32269031      PMCID: PMC7326255          DOI: 10.1136/esmoopen-2020-000684

Source DB:  PubMed          Journal:  ESMO Open        ISSN: 2059-7029


Introduction

Cancer immunotherapies prompting the immune system to attack tumours have mediated durable clinical responses in patients with metastatic melanoma, lung cancer, bladder cancer and other tumour types.1 2 The common goal of immunotherapies is to invigorate the immune system to destroy cancer cells. The activation of T-cell killing activity is a balance between positive signals provided by the specific recognition of tumour antigens, activating receptors and negative signals provided by immune checkpoint receptors.3 Therefore, the therapeutic manipulation of this balance can be achieved inhibiting negative signals using immune checkpoint inhibitors (ie, antiprogrammed cell death protein 1 (PD-1), antiprogrammed death-ligand 1 (PD-L1) or anticytotoxic T-lymphocyte antigen 4 antibodies) intended to restore T-cell function in a immunosuppressed tumour environment.4 5 The actions of immune checkpoint inhibitors rely on the presence of tumour infiltrating lymphocytes (TILs) on the tumour.6 7 Previous data suggest that melanoma regression after therapeutic PD-1 inhibition requires pre-existing CD8 +T cells that are negatively regulated by the interaction between PD-1 and PD-L1.6 More recently, PD-1-expressing neoantigen-specific T-cells have been identified in the peripheral blood of patients with melanoma and gastrointestinal cancers, correlating with the recently documented activity of PD-1 inhibitors in these populations.8 9 Evidence suggests that clinical responses in patients with cancer after the administration of immune checkpoint inhibitors may also be mediated by neoepitope-reactive T-cells.10–12 Tumours with high TILs (‘hot tumours’) have, in general, better responses to checkpoint inhibitors than those lacking or having sparse TILs (‘cold tumours’).3 Additionally, TILs can be isolated from tumour biopsies, expanded and activated in vitro, and reinfused to the same individual, showing antitumour activity in vivo.1 However, the inhibition of immune checkpoint is not antigen-specific and may modify the global T-cell response causing immunological side effects.13 In addition, and apart from a few exceptions (eg, microsatellite instability high cancers),14 approximately one-third of patients will derive benefit from checkpoint inhibitors, while many patients will experience disease progression. More precise and specific therapeutic approaches to direct T-cell responses against the tumour are needed. Here, we review an emerging tool for cancer immunotherapy, the so-called neoantigens and discuss their role as targets for cancer vaccines and adoptive T-cell therapies.

Neoantigens as targets for personalised immunotherapies

Neoantigens represent a class of tumour antigens generated by non-synonymous somatic mutations that can be identified by T-cells as non-self-proteins. Single-nucleotide variants (SNV), mutational frameshifts, splice variants or gene fusions can result in new peptide sequences (neoepitopes), which are strictly tumour specific and absent in healthy tissues.15–18 T-cells recognise neoantigens after they are processed into small peptides and presented by the major histocompatibility complex molecules (MHC or human leucocytes antigens, HLA, in humans) on the surface of the cells.19 It has been shown that 1%–2% of tumour mutations result in neoantigens that bind to HLA and is recognised by T-cell repertoire.1 While CD8 +T cells recognise peptides in the context of MHC-I molecules, which are expressed by all nucleated cells, CD4 +T cells recognise peptides presented by MHC-II molecules, which are only produced by a reduced number of immune cell subsets (mainly dendritic cells (DCs), but also B-cells and macrophages) called professional antigen presenting cells (APCs).20 Advances and widespread use of next-generation sequencing (NGS) has facilitated the rapid identification of non-synonymous somatic mutations in clinical specimens. Computational analyses of DNA sequencing (either whole exome or whole genome sequencing) and RNA sequencing detect expressed gene mutations.21 NGS data can also be used for genotyping HLA alleles of each patient.21 A number of computational pipelines for neoantigen prediction are available22 23 and they are usually based on MHC class I and II processing and presentation. Most pipelines provide peptide-HLA binding affinity predictions, and have also incorporated features like variant allele fraction, gene expression and clonality of mutations. However, there is no standard universal workflow for neoantigen prediction yet. The critical importance of neoantigens relies on their capability of being targets for antitumour-specific T-cell responses because they selectively target tumour relative to healthy tissues. Furthermore, the potential for expanding T-cell clones is intact for neoantigens, since they are completely new for the immune system, while this possibility is lower for unmutated tumour targets, such as tumour-associated antigens and cancer testis antigens, whose T-cell clones may be absent due to the mechanisms of central or peripheral tolerance. This raises the possibility that vaccines targeting specific individual mutated immunogenic epitopes may be more effective. Robust work demonstrated that T-cells target neoantigens in patients that respond to immune checkpoint inhibition, adoptive T-cell therapies and therapeutic vaccines.10 11 24–30 In general, cancers with high mutational burden and high number of predicted neoantigens exhibited better objective responses to checkpoint inhibitors.10 12 14 Neoantigens can also be potentially predicted in cancers with low tumour mutation burden. In fact, non-SNV mutations (ie, frameshifts, fusions) can be sources of potent immunogenic neoantigens.16–18 To make immunotherapy more precise, two main treatment modalities targeting neoantigens have been investigated in clinical trials: (1) personalised vaccines27 28 30–32 and, (2) TILs-based adoptive T-cell therapies24–26 33–35 (figure 1). Both approaches have demonstrated early promise in patients with advanced solid tumours, opening the gateway to new personalised immunotherapies against cancer.
Figure 1

Two strategies targeting neoantigens as cancer immunotherapy. On the left: Neoantigen vaccination; from the tumour genome a computational pipeline is ran to identify neoantigens and after in vitro validation, a vaccine is designed and administrated to the patient. On the right: TIL-based adoptive T-cell therapy, T-cells removed from the patient are expanded and reinfused back to the patient (neoantigen-specific TIL based). APC, antigen presenting cells; MHC, major histocompatibility complex; NGS, next-generation sequencing; PD1, programmed cell death protein 1; PD-L1, programmed death-ligand 1; TIL, tumour infiltrating lymphocyte; TCR, T-cell receptor.

Two strategies targeting neoantigens as cancer immunotherapy. On the left: Neoantigen vaccination; from the tumour genome a computational pipeline is ran to identify neoantigens and after in vitro validation, a vaccine is designed and administrated to the patient. On the right: TIL-based adoptive T-cell therapy, T-cells removed from the patient are expanded and reinfused back to the patient (neoantigen-specific TIL based). APC, antigen presenting cells; MHC, major histocompatibility complex; NGS, next-generation sequencing; PD1, programmed cell death protein 1; PD-L1, programmed death-ligand 1; TIL, tumour infiltrating lymphocyte; TCR, T-cell receptor.

Personalised cancer vaccines

Therapeutic vaccines targeting tumour-specific neoantigens are intended not only to enhance pre-existing memory or effector T-cell responses, but also to expand new antitumour naïve T-cell clones against otherwise poorly immunogenic mutations, broadening T-cell responses and contributing to tumour destruction.36 37 Because each patient shows a particular HLA type composition and a unique tumour genomic make-up, its specific neoantigen set can be identified, selected and then presented to the immune system as a personalised vaccine preparation.38 The genome-based identification of immunogenic neoantigens via NGS and further computation analyses, coupled with mass spectrometry or T-cell reactivity assays are relevant and need to be robust to maximise the immunogenicity of neoantigens loaded into the vaccine. However, for the design of cancer vaccines, several aspects beyond tumour-specific neoantigens have to be taken under consideration. Among them, formulation, immune adjuvants and the delivery system are specially relevant because they may strongly impact on the immunogenicity and vaccination outcome.38 Neoantigen vaccines can be formulated as DNA or RNA coding for neoantigens, as synthetic peptides, as virus-based systems and also as cellular preparations of DC-loaded with neoantigens or tumour cell lysates.36 However, more sophisticated presentation strategies are under development, including DC targeted recombinant immunogens,39 viral vectors or polymeric multivalent neoantigen preparations.40 Following on from encouraging neoantigen vaccine studies in mouse models,41–44 the first-in-human clinical trials testing vaccines in melanoma and glioblastoma patients have shown safety and feasibility.27–32 In a pivotal study, in vitro generated DCs loaded with neoepitopes improved pre-existing anti-tumour T-cell responses and induced responses to neoepitopes that were undetectable prior to vaccination in metastatic melanoma patients.31 In a phase 1 study, six patients with high-risk melanoma received long peptide neoantigen vaccines, two of them (stage IV) achieved complete responses after receiving subsequent PD-1 inhibitor and the other four (high-risk stage IIIB-C) showed no recurrence at follow-up.28 In another phase 1 study, 13 patients with high-risk or advanced melanoma received RNA vaccines encoding neoantigens derived from expressed mutations.27 Two of the five patients with advanced disease experienced vaccine-related objective responses; one patient developed a complete response to vaccination in combination with PD-1 inhibitor. In these first published studies, vaccines induced both CD8+ and CD4+T cell responses, probably due to the use of long peptides that may also bind to MHC-II.27 28 36 45 This fact could be relevant as effective antitumour responses seem to require both CD8 and CD4 tumour-specific T-cells, even in tumours that do not express class-II MHC molecules.45 However, the prediction of specific neoantigen to MHC-II is not yet standardised. These clinical trials showed the feasibility and safety of single agent personal vaccination. The adverse events were, in general, mild including injection site reactions, flu-like symptoms, rash and fatigue.27 28 36 The response assessment used diverse criteria. Either standard RECIST 1.1 criteria or immune-related response criteria guidelines.46 47 In the response assessment of gliomas, the Response Assessment in Neuro-oncology (RANO) criteria and the Immunotherapy Response Assessment in Neuro-Oncology criteria were applied.48 These studies evidenced that clinical responses with single agent vaccine were observed in a minority of cases, and highlighted the potential to combine vaccine with checkpoint inhibitors.27 28 36 How these results will be translated into clinical benefit of cancer patients remains to be demonstrated by future clinical trials. Personalised neoantigen vaccines in combination with immune checkpoint inhibitors or other therapies are being tested in clinical trials for a variety of solid tumours (table 1). An alternative to personalised vaccines is based on the observation that some cancer types share tumour somatic mutations among affected individuals. Although a significant minority of patients with certain common cancers may have HLA class I shared neoantigens (eg, KRAS mutation in up to 15% of colon and lung cancers), those common neoantigen specificities can be exploited to define ‘off-the-shelf’ vaccines across cancer types. For example, current clinical trials are investigating off-the-shelf neoantigen vaccines for patients with metastatic colorectal cancer with microsatellite instability-high status (NCT04041310), or neoantigens derived from KRAS mutation among non-small-cell lung cancer, pancreatic ductal adenocarcinoma and microsatellite-stable colorectal cancer in combination with an anti-PD-1 therapy (NCT03953235).
Table 1

Selected clinical trials targeting neoantigens as targets for personalised or off-the-shelf vaccines

StrategyClinicalTrials.gov identifierTumour typeSettingPhaseTreatmentTarget accrual
Personalised neoantigen vaccineNCT03558945Pancreatic tumourAdvancedPhase 1Personalised neoantigen vaccine60
NCT04087252Solid tumourAdvancedPhase 1Personalised neoantigen vaccine30
NCT03715985Melanoma, lung cancer, kidney cancerAdvancedPhase 1EVAX-01-CAF09b25
Personalised neoantigen vaccine with checkpoint inhibitorsNCT03606967Breast cancer (oestrogen receptor negative, HER2/Neu negative, triple-negative)AdvancedPhase 2Carboplatin, durvalumab gemcitabine, nab-paclitaxel, personalised synthetic long peptide vaccine, poly ICLC70
NCT02950766Kidney cancerAdvancedPhase 1NeoVax, Ipilimumab15
NCT03359239Urothelial, bladder cancerAdvancedPhase 1Atezolizumab, PGV001, Poly ICLC15
NCT02287428GlioblastomaAdvancedPhase 1Radiation Therapy, personalised neoantigen vaccine, pembrolizumab46
NCT03289962Melanoma, lung cancer, bladder cancer, colorectal cancer, triple negative breast cancer, renal cancer, head and neck cancer, other solid cancersAdvancedPhase 1RO7198457/mRNA+atezolizumab770
NCT03532217Prostate cancerAdvancedPhase 1PROSTVAC-V, PROSTVAC-F, Nivolumab, Ipilimumab, Neoantigen DNA vaccine20
NCT03639714Lung cancer, microsatellite stable colorectal cancer, gastro-oesophageal adenocarcinoma, urothelial carcinomaAdvancedPhase 1/2GRT-C901/GRT-R902 +nivolumab/ipilimumab241
NCT02897765Melanoma, lung cancer, bladder cancerAdvancedPhase 1bNEO-PV-01+nivolumab55
Off-the-shelf neoantigen vaccineNCT03391232Colorectal cancerAdvancedPhase 1/2PolyPEPI1018 colorectal cancer vaccine15
Off-the-shelf neoantigen vaccine with checkpoint inhibitorsNCT03953235Lung cancer, colorectal cancer, pancreatic cancer, and other mutation-positive tumoursAdvancedPhase 1/2A fixed set of neoantigens that are shared across a subset of cancer patients+nivolumab144
NCT04041310Mismatch repair deficient or microsatellite instability high colorectal cancer, gastric, gastro-oesophageal junction and endometrial tumoursAdvancedPhase 1Nous-209 (FrameShift Peptides neoantigen-encoding genetic vaccines)+pembrolizumab34
NCT03893903GliomaAdvancedPhase 13 arms: IDH1R132H peptide vaccine, IDH1R132H peptide vaccine and avelumab, avelumab alone.60

IDH, isocitrate dehydrogenase; Poly ICLC, Polyinosinic-Polycytidylic acid stabilized with polylysine and carboxymethylcellulose.

Selected clinical trials targeting neoantigens as targets for personalised or off-the-shelf vaccines IDH, isocitrate dehydrogenase; Poly ICLC, Polyinosinic-Polycytidylic acid stabilized with polylysine and carboxymethylcellulose.

TILs-based adoptive T-cell therapies

The enhancement of T-cell responses can be also achieved by expanding or generating tumour reactive T-cells ex vivo and using them as cellular therapeutic products that, once infused into cancer patients, can kill tumour cells.24–26 33 34 TIL-based adoptive cell transfer has shown the most encouraging clinical activity to date. Most strategies use bulk, randomly isolated TILs from the tumour tissue for ex-vivo expansion and infusion.49 50 However, targeting unique, tumour-specific neoantigens have been pursued as an attractive cell therapy strategy. Current methodology employed to identify and expand neoantigen-reactive TILs involve NGS of tumour derived DNA and RNA, tumour culture in high-dose interleukin-2 (IL-2) to expand antitumour TILs in the presence of neoantigens and APCs.1 The T-cells are then analysed for upregulation of activation markers to identify neoantigen-reactive T-cells. The resulting cell preparation can be then infused as a cellular therapeutic product (figure 1). Adoptive transfer of autologous TILs that specifically target proteins encoded by somatic mutations have mediated objective clinical regressions in patients with metastatic melanoma,34 35 bile duct,26 colon24 and breast cancers25 demonstrating that treatment enhances T-cell recognition of tumour-specific neoantigens. A patient with metastatic cholangiocarcinoma was treated with ERBB2IP mutation-reactive T-cells isolated from TILs (containing 25% of mutation-specific T-cells),26 resulting in reduction in size of target lesions of 30% at 7 months post-treatment with prolonged stabilisation of the disease. After disease progression, patient was retreated with a >95% pure population of mutation-reactive CD4 +T cells, showing again a reduction in size of target lesions in lung and liver. These results provide evidence that a CD4 +T cell response against a mutated antigen can be employed to mediate regression of a metastatic epithelial cancer. A metastatic colorectal cancer patient that showed the KRAS mutation G12D and the HLA-C*08:02 was treated with mutant KRAS specific CD8 +T cells.24 After T-cell infusion, an objective regression of all lung metastases of the patient was observed. After a 9-month period of partial response, one lung metastasis showed clinical progression associated with the loss of the HLA-C*08:02 locus in the chromosome 6. The loss of expression of this molecule provided a direct mechanism of tumour immune evasion and T-cell-mediated selection pressure. A third case report revealed a chemorefractory hormonal receptor-positive metastatic breast cancer patient who was treated with TILs reactive against mutant versions of four proteins—SLC3A2, KIAA0368, CADPS2 and CTSB. Following an infusion of TILs with high levels of neoantigen-specific T-cell reactivity in conjunction with interleukin-2 and PD-1 inhibitor, a complete durable regression of the metastatic breast cancer was observed. The patient’s complete tumour regression did not seem consistent with a response to a short course of single-agent pembrolizumab.25 In general, the most common toxicities during TIL therapy are due to the effects of the lymphodepleting preparative regimens and the subsequent IL-2 after TIL infusion.51 52 TIL-related toxicity is less common, but patients may develop, mostly transient, dyspnoea, chills and fever shortly after infusion of TIL.51 52 Autoimmune-like toxicity such as uveitis, hearing loss and vitiligo after TIL therapy can also occur. Alternatively, targeting neoantigens derived from clonal mutations (ie, present in all cancer cells) are expected to effectively enhance the ability of the immune system to attack all of the tumour cells in the body.53 Previous data showed that clonal neoantigens elicit T-cell immunoreactivity and sensitivity to immune checkpoint inhibition.54 This strategy is being explored in clinical trials. Clonal neoantigens are identified, TILs are ex vivo primed to recognise them and patients receive their own expanded clonal neoantigen-reactive T-cell product.53 Several clinical trials are ongoing to explore adoptive cellular therapy as monotherapy or in combination with checkpoint inhibitors (table 2).
Table 2

Selected clinical trials for using TIL-based adoptive T-cell therapy

StrategyClinicalTrials.gov identifierTumour typeSettingPhaseTreatmentTarget accrual
TIL-based adoptive T-cell therapyNCT04072263Ovarian cancerAdvancedPhase 1, Phase 2TILs, interferon alfa 2A, carboplatin, paclitaxel12
NCT03992326Solid tumourAdvancedPhase 1TILs, cyclophosphamide, fludarabine, IL-2, radiotherapy60
NCT03412526Ovarian cancerAdvancedPhase 2Fludarabine, radiation, TIL administration, IL-215
TIL-based adoptive T-cell therapy with checkpoint inhibitorsNCT03296137CancerAdvancedPhase 1/2Autologous TILs, ipilimumab, nivolumab, IL-2, cyclophosphamide, fludarabine25
NCT03158935Ovarian cancer, melanomaAdvancedPhase 1Cyclophosphamide, fludarabine, pembrolizumab, TILs, IL-224
NCT02652455MelanomaAdvancedEarly Phase 1Nivolumab, surgery to remove tumour for growth of TIL, CD137cyclophosphamide, fludarabine, TIL Infusion, IL-211
NCT03935347UrothelialAdvancedPhase 2Cyclophosphamide, fludarabine, pembrolizumab, autologous TILs, LN-145, IL-212
NCT02621021MelanomaAdvancedPhase 2Cyclophosphamide, fludarabine, IL-2, pembrolizumab, young TIL170
NCT03645928Melanoma, head and neck, lung cancerAdvancedPhase 2Lifileucel, LN-145, pembrolizumab48
Clonal neoantigen adoptive T-cell therapyNCT04032847Lung cancerAdvancedPhase I/IIaATL001, autologous clonal neoantigen T- cells50
NCT03997474MelanomaAdvancedPhase I/IIaATL001, autologous clonal neoantigen T-cells20

IL-2, interleukin-2; TILs, tumour infiltrating lymphocytes.

Selected clinical trials for using TIL-based adoptive T-cell therapy IL-2, interleukin-2; TILs, tumour infiltrating lymphocytes.

Conclusions

Vaccines and TILs-based adoptive T-cell therapies hold promise to make individually tailored medicines to a wide range of patients while targeting individual neoepitopes. They have shown to be safe, feasible and capable of eliciting strong T-cell responses. However, it should be noted that T-cell recognition may not be necessarily translated into long-term clinical objective responses. The use of a personal neoantigen vaccine is anticipated to help address two major challenges for effective cancer immunotherapy. First, addressing tumour heterogeneity and clonal evolution when analysing clinical specimens.54 55 A single resected metastasis might not reflect the most up to date landscape of tumour neoantigens. Targeting highly heterogeneous tumours might likely need to target a diversity of malignant clones per patient, as well as minimising the chance of tumour escape by loss of antigen. Second, these therapies are selectively targeting tumours relative to healthy tissues, potentially reducing side effects. The selection of ideal antigens is still deficient and lacks validation. Such a validation will need the definition of the role of elicited immune responses in clinical efficacy. However, classical technologies to quantify T-cell responses (ELISPOT, tetramer) require large amount of blood, thus limiting their use in large clinical trials. Therefore, high-throughput and unbiased computational strategies for prediction and new single cell sequencing techniques for in vivo measurements will be required to definitively validate, understand and improve neoantigen-based immunotherapies. Expansion of T-cell responses (either by vaccination or cellular therapy) and checkpoint inhibition represent synergic strategies to drive immune control of tumours, and therefore, it is plausible that their combination may enhance efficacy. It is currently unknown whether neoantigen-based immunotherapy should be given before, after or concurrently with checkpoint inhibitors. The combination of vaccination with adoptive T-cell therapy might cause a sustained immune response that could be coupled to enhance the efficacy of transferred T-cells, and if feasible, should be tested in clinical trials. The field is expected to advance in the next few years in terms of better detection of immunogenic neoantigens, standardisation of techniques and delivery platforms, in addition to have trained staff personal in centres with high expertise.
  52 in total

1.  Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group.

Authors:  Patrick Y Wen; David R Macdonald; David A Reardon; Timothy F Cloughesy; A Gregory Sorensen; Evanthia Galanis; John Degroot; Wolfgang Wick; Mark R Gilbert; Andrew B Lassman; Christina Tsien; Tom Mikkelsen; Eric T Wong; Marc C Chamberlain; Roger Stupp; Kathleen R Lamborn; Michael A Vogelbaum; Martin J van den Bent; Susan M Chang
Journal:  J Clin Oncol       Date:  2010-03-15       Impact factor: 44.544

2.  Neoantigen vaccine generates intratumoral T cell responses in phase Ib glioblastoma trial.

Authors:  Derin B Keskin; Annabelle J Anandappa; Jing Sun; Itay Tirosh; Nathan D Mathewson; Shuqiang Li; Giacomo Oliveira; Anita Giobbie-Hurder; Kristen Felt; Evisa Gjini; Sachet A Shukla; Zhuting Hu; Letitia Li; Phuong M Le; Rosa L Allesøe; Alyssa R Richman; Monika S Kowalczyk; Sara Abdelrahman; Jack E Geduldig; Sarah Charbonneau; Kristine Pelton; J Bryan Iorgulescu; Liudmila Elagina; Wandi Zhang; Oriol Olive; Christine McCluskey; Lars R Olsen; Jonathan Stevens; William J Lane; Andres M Salazar; Heather Daley; Patrick Y Wen; E Antonio Chiocca; Maegan Harden; Niall J Lennon; Stacey Gabriel; Gad Getz; Eric S Lander; Aviv Regev; Jerome Ritz; Donna Neuberg; Scott J Rodig; Keith L Ligon; Mario L Suvà; Kai W Wucherpfennig; Nir Hacohen; Edward F Fritsch; Kenneth J Livak; Patrick A Ott; Catherine J Wu; David A Reardon
Journal:  Nature       Date:  2018-12-19       Impact factor: 49.962

Review 3.  Atypical MHC class II-expressing antigen-presenting cells: can anything replace a dendritic cell?

Authors:  Taku Kambayashi; Terri M Laufer
Journal:  Nat Rev Immunol       Date:  2014-10-17       Impact factor: 53.106

4.  NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data.

Authors:  Vanessa Jurtz; Sinu Paul; Massimo Andreatta; Paolo Marcatili; Bjoern Peters; Morten Nielsen
Journal:  J Immunol       Date:  2017-10-04       Impact factor: 5.422

Review 5.  Adoptive cell transfer as personalized immunotherapy for human cancer.

Authors:  Steven A Rosenberg; Nicholas P Restifo
Journal:  Science       Date:  2015-04-03       Impact factor: 47.728

Review 6.  Approaches to treat immune hot, altered and cold tumours with combination immunotherapies.

Authors:  Jérôme Galon; Daniela Bruni
Journal:  Nat Rev Drug Discov       Date:  2019-03       Impact factor: 84.694

Review 7.  Immune checkpoint blockade therapy for cancer: An overview of FDA-approved immune checkpoint inhibitors.

Authors:  Kristian M Hargadon; Coleman E Johnson; Corey J Williams
Journal:  Int Immunopharmacol       Date:  2018-07-02       Impact factor: 4.932

8.  PD-1 blockade induces responses by inhibiting adaptive immune resistance.

Authors:  Paul C Tumeh; Christina L Harview; Jennifer H Yearley; I Peter Shintaku; Emma J M Taylor; Lidia Robert; Bartosz Chmielowski; Marko Spasic; Gina Henry; Voicu Ciobanu; Alisha N West; Manuel Carmona; Christine Kivork; Elizabeth Seja; Grace Cherry; Antonio J Gutierrez; Tristan R Grogan; Christine Mateus; Gorana Tomasic; John A Glaspy; Ryan O Emerson; Harlan Robins; Robert H Pierce; David A Elashoff; Caroline Robert; Antoni Ribas
Journal:  Nature       Date:  2014-11-27       Impact factor: 49.962

9.  The Genomic and Immune Landscapes of Lethal Metastatic Breast Cancer.

Authors:  Leticia De Mattos-Arruda; Stephen-John Sammut; Edith M Ross; Rachael Bashford-Rogers; Erez Greenstein; Havell Markus; Sandro Morganella; Yvonne Teng; Yosef Maruvka; Bernard Pereira; Oscar M Rueda; Suet-Feung Chin; Tania Contente-Cuomo; Regina Mayor; Alexandra Arias; H Raza Ali; Wei Cope; Daniel Tiezzi; Aliakbar Dariush; Tauanne Dias Amarante; Dan Reshef; Nikaoly Ciriaco; Elena Martinez-Saez; Vicente Peg; Santiago Ramon Y Cajal; Javier Cortes; George Vassiliou; Gad Getz; Serena Nik-Zainal; Muhammed Murtaza; Nir Friedman; Florian Markowetz; Joan Seoane; Carlos Caldas
Journal:  Cell Rep       Date:  2019-05-28       Impact factor: 9.423

Review 10.  Best practices for bioinformatic characterization of neoantigens for clinical utility.

Authors:  Megan M Richters; Huiming Xia; Katie M Campbell; William E Gillanders; Obi L Griffith; Malachi Griffith
Journal:  Genome Med       Date:  2019-08-28       Impact factor: 11.117

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  12 in total

Review 1.  Neoantigen prediction and computational perspectives towards clinical benefit: recommendations from the ESMO Precision Medicine Working Group.

Authors:  L De Mattos-Arruda; M Vazquez; F Finotello; R Lepore; E Porta; J Hundal; P Amengual-Rigo; C K Y Ng; A Valencia; J Carrillo; T A Chan; V Guallar; N McGranahan; J Blanco; M Griffith
Journal:  Ann Oncol       Date:  2020-06-28       Impact factor: 32.976

2.  Prognostic Significance of mRNA Expression RBBP8 or Its Methylation in Gliomas.

Authors:  Zhendong Liu; Xingbo Cheng; Shaochong Lin; Zhibin Han; Haoran Jin; Zheyu Luan; Pengxu Li; Wenjia Liang; Rongjun Qian; Yanzheng Gao
Journal:  Cell Mol Neurobiol       Date:  2022-02-01       Impact factor: 5.046

Review 3.  Landscape of Immunotherapy Options for Colorectal Cancer: Current Knowledge and Future Perspectives beyond Immune Checkpoint Blockade.

Authors:  Alecsandra Gorzo; Diana Galos; Simona Ruxandra Volovat; Cristian Virgil Lungulescu; Claudia Burz; Daniel Sur
Journal:  Life (Basel)       Date:  2022-02-02

Review 4.  Narrative review of emerging roles for AKT-mTOR signaling in cancer radioimmunotherapy.

Authors:  Changxian Shen; Yuqi He; Qiang Chen; Haihua Feng; Terence M Williams; Yuanzhi Lu; Zhengfu He
Journal:  Ann Transl Med       Date:  2021-10

5.  Targeting the tumor mutanome for personalized vaccination in a TMB low non-small cell lung cancer.

Authors:  Katy McCann; Adrian von Witzleben; Jaya Thomas; Chuan Wang; Oliver Wood; Divya Singh; Konstantinos Boukas; Kaidre Bendjama; Nathalie Silvestre; Finn Cilius Nielsen; Gareth Thomas; Tilman Sanchez-Elsner; Jason Greenbaum; Stephen Schoenberger; Bjoern Peters; Pandurangan Vijayanand; Natalia Savelyeva; Christian Ottensmeier
Journal:  J Immunother Cancer       Date:  2022-03       Impact factor: 12.469

Review 6.  Immune escape mechanisms and therapeutic approaches in cancer: the cancer-immunity cycle.

Authors:  Angelika M Starzer; Matthias Preusser; Anna S Berghoff
Journal:  Ther Adv Med Oncol       Date:  2022-04-30       Impact factor: 5.485

Review 7.  Neoantigens and NK Cells: "Trick or Treat" the Cancers?

Authors:  Dan Lv; Muhammad Babar Khawar; Zhengyan Liang; Yu Gao; Haibo Sun
Journal:  Front Immunol       Date:  2022-07-07       Impact factor: 8.786

Review 8.  VISTA: A Promising Target for Cancer Immunotherapy?

Authors:  Marco Tagliamento; Elisa Agostinetto; Roberto Borea; Mariana Brandão; Francesca Poggio; Alfredo Addeo; Matteo Lambertini
Journal:  Immunotargets Ther       Date:  2021-06-22

9.  The temporal mutational and immune tumour microenvironment remodelling of HER2-negative primary breast cancers.

Authors:  Leticia De Mattos-Arruda; Javier Cortes; Juan Blanco-Heredia; Daniel G Tiezzi; Guillermo Villacampa; Samuel Gonçalves-Ribeiro; Laia Paré; Carla Anjos Souza; Vanesa Ortega; Stephen-John Sammut; Pol Cusco; Roberta Fasani; Suet-Feung Chin; Jose Perez-Garcia; Rodrigo Dienstmann; Paolo Nuciforo; Patricia Villagrasa; Isabel T Rubio; Aleix Prat; Carlos Caldas
Journal:  NPJ Breast Cancer       Date:  2021-06-07

10.  A six-gene signature related with tumor mutation burden for predicting lymph node metastasis in breast cancer.

Authors:  Cenzhu Wang; Kun Xu; Fei Deng; Yiqiu Liu; Jinyi Huang; Runtian Wang; Xiaoxiang Guan
Journal:  Transl Cancer Res       Date:  2021-05       Impact factor: 1.241

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