A Holistic Approach to Hard-to-Treat Cancers: The Future of Immunotherapy for Glioblastoma, Triple Negative Breast Cancer, and Advanced Prostate Cancer.

Immunotherapy represents an attractive avenue for cancer therapy due to its tumour specificity and relatively low frequency of adverse effects compared to other treatment modalities. Despite many advances being made in the field of cancer immunotherapy, very few immunotherapeutic treatments have been approved for difficult-to-treat solid tumours such as triple negative breast cancer (TNBC), glioblastoma multiforme (GBM), and advanced prostate cancer (PCa). The anatomical location of some of these cancers may also make them more difficult to treat. Many trials focus solely on immunotherapy and have failed to consider or manipulate, prior to the immunotherapeutic intervention, important factors such as the microbiota, which itself is directly linked to lifestyle factors, diet, stress, social support, exercise, sleep, and oral hygiene. This review summarises the most recent treatments for hard-to-treat cancers whilst factoring in the less conventional interventions which could tilt the balance of treatment in favour of success for these malignancies.

Robust formation of optimal single spheroids towards cost-effective in vitro three-dimensional tumor models.

While useful for fundamental in vitro studies, monolayer cell cultures are not physiologically relevant. Spheroids, a complex three-dimensional (3D) structure, more closely resemble in vivo tumor growth. Spheroids allow the results obtained relating to proliferation, cell death, differentiation, metabolism, and various antitumor therapies to be more predictive of in vivo outcomes. In the protocol herein, a rapid and high-throughput method is discussed for the generation of single spheroids using various cancer cell lines, including brain cancer cells (U87 MG, SEBTA-027, SF188), prostate cancer cells (DU-145, TRAMP-C1), and breast cancer cells (BT-549, Py230) in 96-round bottom-well plates. The proposed method is associated with significantly low costs per plate without requiring refining or transferring. Homogeneous compact spheroid morphology was evidenced as early as 1 day after following this protocol. Proliferating cells were traced in the rim, while dead cells were found to be located inside the core region of the spheroid using confocal microscopy and the Incucyte® live imaging system. H&E staining of spheroid sections was utilized to investigate the tightness of the cell packaging. Through western blotting analyses, it was revealed that a stem cell-like phenotype was adopted by these spheroids. This method was also used to obtain the EC50 of the anticancer dipeptide carnosine on U87 MG 3D culture. This affordable, easy-to-follow five-step protocol allows for the robust generation of various uniform spheroids with 3D morphology characteristics.

Controlled release of carnosine from poly(lactic-co-glycolic acid) beads using nanomechanical magnetic trigger towards the treatment of glioblastoma.

Nanometer scale rods of superparamagnetic iron oxide have been encapsulated, along with the anti-cancer therapeutic carnosine, inside porous poly(lactic-co-glycolic acid) microbeads with a uniform morphology, synthesised using microfluidic arrays. The sustained and externally triggered controlled release from these vehicles was demonstrated using a rotating Halbach magnet array, quantified via liquid chromatography, and imaged in situ using magnetic resonance imaging (MRI) and scanning electron microscopy (SEM). In the absence of the external magnetic trigger, the carnosine was found to be released from the polymer in a linear profile; however, over 50% of the drug could be released within 30 minutes of exposure to the rotating magnetic field. In addition, the release of carnosine embedded on the surface of the nano-rods was delayed if it was mixed with the iron oxide nano rods before the encapsulation. These new drug delivery vesicles have the potential to pave the way towards the safe and triggered release of onsite drug delivery, as part of a theragnostic treatment for glioblastoma.

Multi-Omic Analysis of Two Common P53 Mutations: Proteins Regulated by Mutated P53 as Potential Targets for Immunotherapy.

The p53 protein is mutated in more than 50% of human cancers. Mutated p53 proteins not only lose their normal function but often acquire novel oncogenic functions, a phenomenon termed mutant p53 gain-of-function. Mutant p53 has been shown to affect the transcription of a range of genes, as well as protein-protein interactions with transcription factors and other effectors; however, no one has intensively investigated and identified these proteins, or their MHC presented epitopes, from the viewpoint of their ability to act as targets for immunotherapeutic interventions. We investigated the molecular changes that occurred after the TP53 null osteosarcoma cells, SaOS-2, were transfected with one of two conformational p53-mutants, either R175H or R273H. We then examined the phenotypic and functional changes using macroscopic observations, proliferation, gene expression and proteomics alongside immunopeptidome profiling of peptide antigen presentation in the context of major histocompatibility complex (MHC) class I molecules. We identified several candidate proteins in both TP53 mutant cell lines with differential expression when compared to the TP53 null vector control, SaOS-V. Quantitative SWATH proteomics combined with immune-peptidome analysis of the class-I eluted peptides identified several epitopes presented on pMHC and in silico analysis shortlisted which antigens were expressed in a range of cancerous but not adjacent healthy tissues. Out of all the candidates, KLC1 and TOP2A showed high levels of expression in every tumor type examined. From these proteins, three A2 and four pan HLA-A epitopes were identified in both R175H and R273H from TOP2A. We have now provided a short list of future immunotherapy targets for the treatment of cancers harboring mutated TP53.

A Mutated Prostatic Acid Phosphatase (PAP) Peptide-Based Vaccine Induces PAP-Specific CD8+ T Cells with Ex Vivo Cytotoxic Capacities in HHDII/DR1 Transgenic Mice.

BACKGROUND: Current treatments for castrate (hormone)-resistant prostate cancer (CRPC) remain limited and are not curative, with a median survival from diagnosis of 23 months. The PAP-specific Sipuleucel-T vaccine, which was approved by the FDA in 2010, increases the Overall Survival (OS) by 4 months, but is extremely expensive. We have previously shown that a 15 amino accid (AA) PAP sequence-derived peptide could induce strong immune responses and delay the growth of murine TRAMP-C1 prostate tumors. We have now substituted one amino acid and elongated the sequence to include epitopes predicted to bind to several additional HLA haplotypes. Herein, we present the immunological properties of this 42mer-mutated PAP-derived sequence (MutPAP42mer). METHODS: The presence of PAP-135-143 epitope-specific CD8+ T cells in the blood of patients with prostate cancer (PCa) was assessed by flow cytometry using Dextramer™ technology. HHDII/DR1 transgenic mice were immunized with mutated and non-mutated PAP-derived 42mer peptides in the presence of CAF®09 or CpG ODN1826 (TLR-9 agonist) adjuvants. Vaccine-induced immune responses were measured by assessing the proportion and functionality of splenic PAP-specific T cells in vitro. RESULTS: PAP-135-143 epitope-specific CD8+ T cells were detected in the blood of patients with PCa and stimulation of PBMCs from patients with PCa with mutPAP42mer enhanced their capacity to kill human LNCaP PCa target cells expressing PAP. The MutPAP42mer peptide was significantly more immunogenic in HHDII/DR1 mice than the wild type sequence, and immunogenicity was further enhanced when combined with the CAF®09 adjuvant. The vaccine induced secretory (IFNγ and TNFα) and cytotoxic CD8+ T cells and effector memory splenic T cells. CONCLUSIONS: The periphery of patients with PCa exhibits immune responsiveness to the MutPAP42mer peptide and immunization of mice induces/expands T cell-driven, wild-type PAP immunity, and therefore, has the potential to drive protective anti-tumor immunity in patients with PCa.

Synthesis and Functionalisation of Superparamagnetic Nano-Rods towards the Treatment of Glioblastoma Brain Tumours.

The complete removal of glioblastoma brain tumours is impossible to achieve by surgery alone due to the complex finger-like tentacle structure of the tumour cells and their migration away from the bulk of the tumour at the time of surgery; furthermore, despite aggressive chemotherapy and radiotherapy treatments following surgery, tumour cells continue to grow, leading to the death of patients within 15 months after diagnosis. The naturally occurring carnosine dipeptide has previously demonstrated activity against in vitro cultured glioblastoma cells; however, at natural physiological concentrations, its activity is too low to have a significant effect. Towards realising the full oncological potential of carnosine, the dipeptide was embedded within an externally triggered carrier, comprising a novel nano rod-shaped superparamagnetic iron oxide nanoparticle (ca. 86 × 19 × 11 nm) capped with a branched polyethyleneimine, which released the therapeutic agent in the presence of an external magnetic field. The new nano-carrier was characterized using electron microscopy, dynamic light scattering, elemental analysis, and magnetic resonance imaging techniques. In addition to cytotoxicity studies, the carnosine carrier's effectiveness as a treatment for glioblastoma was screened in vitro using the U87 human glioblastoma astrocytoma cell line. The labile carnosine (100 mM) suppresses both the U87 cells' proliferation and mobility over 48 h, resulting in significant reduction in migration and potential metastasis. Carnosine was found to be fully released from the carrier using only mild hyperthermia conditions (40 °C), facilitating an achievable clinical application of the slow, sustained-release treatment of glioblastoma brain tumours that demonstrates potential to inhibit post-surgery metastasis with the added benefit of non-invasive monitoring via MRI.

Helicase antigen (HAGE)-derived vaccines induce immunity to HAGE and ImmunoBody®-HAGE DNA vaccine delays the growth and metastasis of HAGE-expressing tumors in vivo.

The management of patients with triple-negative breast cancer (TNBC) continues to pose a significant clinical challenge. Less than 30% of women with metastatic TNBC survive 5 years, despite adjuvant chemotherapy and the initial higher rates of clinical response that can be achieved with neoadjuvant chemotherapy. ImmunoBody is a plasmid DNA designed to encode a human antibody molecule with complementarity-determining regions engineered to express cytotoxic and helper T-cell epitopes derived from the cancer antigen of interest. The helicase antigen (HAGE) is a cancer testis antigen, which is expressed in TNBC. Herein, we have identified a 30-amino-acid-long HAGE-derived sequence containing human leukocyte antigen (HLA)-A2- and HLA-DR1-restricted epitopes and demonstrated that the use of this sequence as a peptide (with CpG/incomplete Freund's adjuvant) or incorporated into an ImmunoBody vaccine can generate specific interferon-γ-secreting splenocytes in HHDII+ DR1+ mice. T-cell responses elicited by the ImmunoBody-HAGE vaccine were superior to peptide immunization. Moreover, splenocytes from ImmunoBody-HAGE-vaccinated mice stimulated in vitro could recognize HAGE+ tumor cells and the human TNBC cell line MDA-MB-231. More importantly, the growth of implanted HHDII+ DR1+ HAGE+ Luc+ B16 cells.

Novel Combinatorial Approaches to Tackle the Immunosuppressive Microenvironment of Prostate Cancer.

Prostate cancer (PCa) is the second-most common cancer in men worldwide and treatment options for patients with advanced or aggressive prostate cancer or recurrent disease continue to be of limited success and are rarely curative. Despite immune checkpoint blockade (ICB) efficacy in some melanoma, lung, kidney and breast cancers, immunotherapy efforts have been remarkably unsuccessful in PCa. One hypothesis behind this lack of efficacy is the generation of a distinctly immunosuppressive prostate tumor microenvironment (TME) by regulatory T cells, MDSCs, and type 2 macrophages which have been implicated in a variety of pathological conditions including solid cancers. In PCa, Tregs and MDSCs are attracted to TME by low-grade chronic inflammatory signals, while tissue-resident type 2 macrophages are induced by cytokines such as IL4, IL10, IL13, transforming growth factor beta (TGFß) or prostaglandin E2 (PGE2) produced by Th2 cells. These then drive tumor progression, therapy resistance and the generation of castration resistance, ultimately conferring a poor prognosis. The biology of MDSC and Treg is highly complex and the development, proliferation, maturation or function can each be pharmacologically mediated to counteract the immunosuppressive effects of these cells. Herein, we present a critical review of Treg, MDSC and M2 involvement in PCa progression but also investigate a newly recognized type of immune suppression induced by the chronic stimulation of the sympathetic adrenergic signaling pathway and propose targeted strategies to be used in a combinatorial modality with immunotherapy interventions such as ICB, Sipuleucel-T or antitumor vaccines for an enhanced anti-PCa tumor immune response. We conclude that a strategic sequence of therapeutic interventions in combination with additional holistic measures will be necessary to achieve maximum benefit for PCa patients.

Prostate Cancer: Early Detection and Assessing Clinical Risk Using Deep Machine Learning of High Dimensional Peripheral Blood Flow Cytometric Phenotyping Data.

Detecting the presence of prostate cancer (PCa) and distinguishing low- or intermediate-risk disease from high-risk disease early, and without the need for potentially unnecessary invasive biopsies remains a significant clinical challenge. The aim of this study is to determine whether the T and B cell phenotypic features which we have previously identified as being able to distinguish between benign prostate disease and PCa in asymptomatic men having Prostate-Specific Antigen (PSA) levels < 20 ng/ml can also be used to detect the presence and clinical risk of PCa in a larger cohort of patients whose PSA levels ranged between 3 and 2617 ng/ml. The peripheral blood of 130 asymptomatic men having elevated Prostate-Specific Antigen (PSA) levels was immune profiled using multiparametric whole blood flow cytometry. Of these men, 42 were subsequently diagnosed as having benign prostate disease and 88 as having PCa on biopsy-based evidence. We built a bidirectional Long Short-Term Memory Deep Neural Network (biLSTM) model for detecting the presence of PCa in men which combined the previously-identified phenotypic features (CD8+CD45RA-CD27-CD28- (CD8+ Effector Memory cells), CD4+CD45RA-CD27-CD28- (CD4+ Effector Memory cells), CD4+CD45RA+CD27-CD28- (CD4+ Terminally Differentiated Effector Memory Cells re-expressing CD45RA), CD3-CD19+ (B cells), CD3+CD56+CD8+CD4+ (NKT cells) with Age. The performance of the PCa presence 'detection' model was: Acc: 86.79 ( ± 0.10), Sensitivity: 82.78% (± 0.15); Specificity: 95.83% (± 0.11) on the test set (test set that was not used during training and validation); AUC: 89.31% (± 0.07), ORP-FPR: 7.50% (± 0.20), ORP-TPR: 84.44% (± 0.14). A second biLSTM 'risk' model combined the immunophenotypic features with PSA to predict whether a patient with PCa has high-risk disease (defined by the D'Amico Risk Classification) achieved the following: Acc: 94.90% (± 6.29), Sensitivity: 92% (± 21.39); Specificity: 96.11 (± 0.00); AUC: 94.06% (± 10.69), ORP-FPR: 3.89% (± 0.00), ORP-TPR: 92% (± 21.39). The ORP-FPR for predicting the presence of PCa when combining FC+PSA was lower than that of PSA alone. This study demonstrates that AI approaches based on peripheral blood phenotyping profiles can distinguish between benign prostate disease and PCa and predict clinical risk in asymptomatic men having elevated PSA levels.

Immune Escape in Glioblastoma Multiforme and the Adaptation of Immunotherapies for Treatment.

Glioblastoma multiforme (GBM) is the most frequently occurring primary brain tumor and has a very poor prognosis, with only around 5% of patients surviving for a period of 5 years or more after diagnosis. Despite aggressive multimodal therapy, consisting mostly of a combination of surgery, radiotherapy, and temozolomide chemotherapy, tumors nearly always recur close to the site of resection. For the past 15 years, very little progress has been made with regards to improving patient survival. Although immunotherapy represents an attractive therapy modality due to the promising pre-clinical results observed, many of these potential immunotherapeutic approaches fail during clinical trials, and to date no immunotherapeutic treatments for GBM have been approved. As for many other difficult to treat cancers, GBM combines a lack of immunogenicity with few mutations and a highly immunosuppressive tumor microenvironment (TME). Unfortunately, both tumor and immune cells have been shown to contribute towards this immunosuppressive phenotype. In addition, current therapeutics also exacerbate this immunosuppression which might explain the failure of immunotherapy-based clinical trials in the GBM setting. Understanding how these mechanisms interact with one another, as well as how one can increase the anti-tumor immune response by addressing local immunosuppression will lead to better clinical results for immune-based therapeutics. Improving therapeutic delivery across the blood brain barrier also presents a challenge for immunotherapy and future therapies will need to consider this. This review highlights the immunosuppressive mechanisms employed by GBM cancers and examines potential immunotherapeutic treatments that can overcome these significant immunosuppressive hurdles.

Identifying prostate cancer and its clinical risk in asymptomatic men using machine learning of high dimensional peripheral blood flow cytometric natural killer cell subset phenotyping data.

We demonstrate that prostate cancer can be identified by flow cytometric profiling of blood immune cell subsets. Herein, we profiled natural killer (NK) cell subsets in the blood of 72 asymptomatic men with Prostate-Specific Antigen (PSA) levels < 20 ng ml-1, of whom 31 had benign disease (no cancer) and 41 had prostate cancer. Statistical and computational methods identified a panel of eight phenotypic features ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]) that, when incorporated into an Ensemble machine learning prediction model, distinguished between the presence of benign prostate disease and prostate cancer. The machine learning model was then adapted to predict the D'Amico Risk Classification using data from 54 patients with prostate cancer and was shown to accurately differentiate between the presence of low-/intermediate-risk disease and high-risk disease without the need for additional clinical data. This simple blood test has the potential to transform prostate cancer diagnostics.

With an estimated 1.8 million new cases in 2018 alone, prostate cancer is the fourth most common cancer in the world. Catching the disease early increases the chances of survival, but this cancer remains difficult to detect. The best diagnostic test currently available measures the blood level of a protein called the prostate-specific antigen (PSA for short). Heightened amounts of PSA may mean that the patient has cancer, but 15% of individuals with prostate cancer have normal levels of the protein, and many healthy people can have high amounts of PSA. This blood test is therefore not widely accepted as a reliable diagnostic tool. Other methods exist to detect prostate cancer, yet their results are limited. A small piece of the prostate can be taken for analysis, but results from this invasive procedure are often incorrect. Scans can help to spot a tumor, but they are not accurate enough to be conclusive on their own. New tests are therefore urgently needed. Prostate cancer is often associated with changes in the immune system that can be detected through a blood test. In particular, the appearance of a type of white blood (immune) cells called natural killer cells may be altered. Yet, it was unclear whether measurements based on these cells could help to detect prostate cancer and assess the severity of the disease. Here, Hood, Cosma et al. collected and examined the natural killer cells of 72 participants with slightly elevated PSA levels and no other symptoms. Amongst these, 31 individuals had prostate cancer and 41 were healthy. These biological data were then used to produce computer models that could detect the presence of the disease, as well as assess its severity. The algorithms were developed using machine learning, where previous patient information is used to make prediction on new data. This work resulted in a new detection tool which was 12.5% more accurate than the PSA test in detecting prostate cancer; and in a detection tool that was 99% accurate in predicting the risk of the disease (in terms of clinical significance) in individuals with prostate cancer. Although these new approaches first need to be validated in the clinic before being deployed, they could ultimately improve the detection and diagnosis of prostate cancer, saving lives and reducing the need for further tests.

Flow cytometry and targeted immune transcriptomics identify distinct profiles in patients with chronic myeloid leukemia receiving tyrosine kinase inhibitors with or without interferon-α.

BACKGROUND: Tumor cells have evolved complex strategies to escape immune surveillance, a process which involves NK cells and T lymphocytes, and various immunological factors. Indeed, tumor cells recruit immunosuppressive cells [including regulatory T-cells (Treg), myeloid-derived suppressor cells (MDSC)] and express factors such as PD-L1. Molecularly targeted therapies, such as imatinib, have off-target effects that may influence immune function. Imatinib has been shown to modulate multiple cell types involved in anti-cancer immune surveillance, with potentially detrimental or favorable outcomes. Imatinib and other tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) have dramatically changed disease course. Our study aimed to characterize the different populations of the immune system in patients with CML affected by their treatment. METHODS: Forty-one patients with CML [33 treated with TKIs and 8 with TKIs plus interferon (IFN)-α] and 20 controls were enrolled in the present study. Peripheral blood populations of the immune system [referred to as the overview of immune system (OVIS) panel, Treg cells and MDSCs] and PD-1 expression were evaluated by flow cytometry. The immunological profile was assessed using the mRNA Pan-Cancer Immune Profiling Panel and a NanoString nCounter FLEX platform. RESULTS: Patients receiving combination therapy (TKIs + IFN-α) had lower numbers of lymphocytes, particularly T cells [838/µL (95% CI 594-1182)] compared with healthy controls [1500/µL (95% CI 1207 - 1865), p = 0.017]. These patients also had a higher percentage of Treg (9.1%) and CD4+PD-1+ cells (1.65%) compared with controls [Treg (6.1%) and CD4+/PD-1+(0.8%); p ≤ 0.05]. Moreover, patients treated with TKIs had more Mo-MDSCs (12.7%) whereas those treated with TKIs + IFN-α had more Gr-MDSC (21.3%) compared to controls [Mo-MDSC (11.4%) and Gr-MDSC (8.48%); p ≤ 0.05]. CD56bright NK cells, a cell subset endowed with immune-regulatory properties, were increased in patients receiving TKIs plus IFN-α compared with those treated with TKIs alone. Interestingly, serum IL-21 was significantly lower in the TKIs plus IFN-α cohort. Within the group of patients treated with TKI monotherapy, we observed that individuals receiving 2nd generation TKIs had lower percentages of CD4+ Treg (3.63%) and Gr-MDSC (4.2%) compared to patients under imatinib treatment (CD4+ Treg 6.18% and Gr-MDSC 8.2%), but higher levels of PD-1-co-expressing CD4+ cells (1.92%). CONCLUSIONS: Our results suggest that TKIs in combination with IFN-α may promote an enhanced immune suppressive state.

Cancer Vaccines: Adjuvant Potency, Importance of Age, Lifestyle, and Treatments.

Although the discovery and characterization of multiple tumor antigens have sparked the development of many antigen/derived cancer vaccines, many are poorly immunogenic and thus, lack clinical efficacy. Adjuvants are therefore incorporated into vaccine formulations to trigger strong and long-lasting immune responses. Adjuvants have generally been classified into two categories: those that 'depot' antigens (e.g. mineral salts such as aluminum hydroxide, emulsions, liposomes) and those that act as immunostimulants (Toll Like Receptor agonists, saponins, cytokines). In addition, several novel technologies using vector-based delivery of antigens have been used. Unfortunately, the immune system declines with age, a phenomenon known as immunosenescence, and this is characterized by functional changes in both innate and adaptive cellular immunity systems as well as in lymph node architecture. While many of the immune functions decline over time, others paradoxically increase. Indeed, aging is known to be associated with a low level of chronic inflammation-inflamm-aging. Given that the median age of cancer diagnosis is 66 years and that immunotherapeutic interventions such as cancer vaccines are currently given in combination with or after other forms of treatments which themselves have immune-modulating potential such as surgery, chemotherapy and radiotherapy, the choice of adjuvants requires careful consideration in order to achieve the maximum immune response in a compromised environment. In addition, more clinical trials need to be performed to carefully assess how less conventional form of immune adjuvants, such as exercise, diet and psychological care which have all be shown to influence immune responses can be incorporated to improve the efficacy of cancer vaccines. In this review, adjuvants will be discussed with respect to the above-mentioned important elements.

Immune-Phenotyping and Transcriptomic Profiling of Peripheral Blood Mononuclear Cells From Patients With Breast Cancer: Identification of a 3 Gene Signature Which Predicts Relapse of Triple Negative Breast Cancer.

Background: Interactions between the immune system and tumors are highly reciprocal in nature, leading to speculation that tumor recurrence or therapeutic resistance could be influenced or predicted by immune events that manifest locally, but can be detected systemically. Methods: Multi-parameter flow cytometry was used to examine the percentage and phenotype of natural killer (NK) cells, myeloid-derived suppressor cells (MDSCs), monocyte subsets and regulatory T (Treg) cells in the peripheral blood of of 85 patients with breast cancer (50 of whom were assessed before and after one cycle of anthracycline-based chemotherapy), and 23 controls. Transcriptomic profiles of peripheral blood mononuclear cells (PBMCs) in 23 patients were generated using a NanoString gene profiling platform. Results: An increased percentage of immunosuppressive cells such as granulocytic MDSCs, intermediate CD14++CD16+ monocytes and CD127negCD25highFoxP3+ Treg cells was observed in patients with breast cancer, especially patients with stage 3 and 4 disease, regardless of ER status. Following neoadjuvant chemotherapy, B cell numbers decreased significantly, whereas monocyte numbers increased. Although chemotherapy had no effect on the percentage of Treg, MDSC and NK cells, the expression of inhibitory receptors CD85j, LIAR and NKG2A and activating receptors NKp30 and NKp44 on NK cells increased, concomitant with a decreased expression of NKp46 and DNAM-1 activating receptors. Transcriptomic profiling revealed a distinct group of 3 patients in the triple negative breast cancer (TNBC) cohort who expressed high levels of mRNA encoding genes predominantly involved in inflammation. The analysis of a large transcriptomic dataset derived from the tumors of patients with TNBC revealed that the expression of CD163, CXCR4, THBS1 predicted relapse-free survival. Conclusions: The peripheral blood immunome of patients with breast cancer is influenced by the presence and stage of cancer, but not by molecular subtypes. Furthermore, immune profiling coupled with transcriptomic analyses of peripheral blood cells may identify patients with TNBC that are at risk of relapse after chemotherapy.

Immune Landscape of Breast Cancers.

Breast cancer is a very heterogeneous disease, both at a molecular and a histological level. Five intrinsic subtypes were initially identified-Luminal-A, Luminal-B, HER2⁺, Triple negative/basal like (TNBC) and normal like-subsequently expanded to seven (Basal-like-1 and 2, mesenchymal, mesenchymal stem-like, luminal androgen receptor, immuno-modulatory and unstable). Although genetic and epigenetic changes are key pathogenic events, the immune system plays a substantial role in promoting progression and metastasis. This review will discuss the extent to which immune cells can be detected within the tumor microenvironment, as well as their prognostic role and relationship with the microbiome, with an emphasis on TNBC.

Phenotype and Function of Activated Natural Killer Cells From Patients With Prostate Cancer: Patient-Dependent Responses to Priming and IL-2 Activation.

Background: Although immunotherapy has emerged as the "next generation" of cancer treatments, it has not yet been shown to be successful in the treatment of patients with prostate cancer, for whom therapeutic options remain limited to radiotherapy and androgen (hormone) deprivation therapy. Previous studies have shown that priming natural killer (NK) cells isolated from healthy individuals via co-incubation with CTV-1 cells derived from an acute lymphoblastic leukemia (ALL) enhances their cytotoxicity against human DU145 (metastatic) prostate cancer cells, but it remains unknown to what extent NK cells from patients with prostate cancer can be triggered to kill. Herein, we explore the phenotype of peripheral blood NK cells in patients with prostate cancer and compare the capacity of CTV-1 cell-mediated priming and IL-2 stimulation to trigger NK cell-mediated killing of the human PC3 (metastatic) prostate cancer cell line. Methods: The phenotype of resting, primed (co-incubation with CTV-1 cells for 17 h) and IL-2 activated (100 IU/ml IL-2 for 17 h) NK cells isolated from frozen-thawed peripheral blood mononuclear cell (PBMC) preparations from patients with benign disease (n = 6) and prostate cancer (n = 18) and their cytotoxicity against PC3 and K562 cells was determined by flow cytometry. Relationship(s) between NK cell phenotypic features and cytotoxic potential were interrogated using Spearman Rank correlation matrices. Results and Conclusions: NK cell priming and IL-2 activation of patient-derived NK cells resulted in similar levels of cytotoxicity, but distinct NK cell phenotypes. Importantly, the capacity of priming and IL-2 stimulation to trigger cytotoxicity was patient-dependent and mutually exclusive, in that NK cells from ~50% of patients preferentially responded to priming whereas NK cells from the remaining patients preferentially responded to cytokine stimulation. In addition to providing more insight into the biology of primed and cytokine-stimulated NK cells, this study supports the use of autologous NK cell-based immunotherapies for the treatment of prostate cancer. However, our findings also indicate that patients will need to be stratified according to their potential responsiveness to individual therapeutic approaches.

Identifying the Presence of Prostate Cancer in Individuals with PSA Levels <20 ng ml-1 Using Computational Data Extraction Analysis of High Dimensional Peripheral Blood Flow Cytometric Phenotyping Data.

Determining whether an asymptomatic individual with Prostate-Specific Antigen (PSA) levels below 20 ng ml-1 has prostate cancer in the absence of definitive, biopsy-based evidence continues to present a significant challenge to clinicians who must decide whether such individuals with low PSA values have prostate cancer. Herein, we present an advanced computational data extraction approach which can identify the presence of prostate cancer in men with PSA levels <20 ng ml-1 on the basis of peripheral blood immune cell profiles that have been generated using multi-parameter flow cytometry. Statistical analysis of immune phenotyping datasets relating to the presence and prevalence of key leukocyte populations in the peripheral blood, as generated from individuals undergoing routine tests for prostate cancer (including tissue biopsy) using multi-parametric flow cytometric analysis, was unable to identify significant relationships between leukocyte population profiles and the presence of benign disease (no prostate cancer) or prostate cancer. By contrast, a Genetic Algorithm computational approach identified a subset of five flow cytometry features (CD8+CD45RA-CD27-CD28- (CD8+ Effector Memory cells); CD4+CD45RA-CD27-CD28- (CD4+ Terminally Differentiated Effector Memory Cells re-expressing CD45RA); CD3-CD19+ (B cells); CD3+CD56+CD8+CD4+ (NKT cells)) from a set of twenty features, which could potentially discriminate between benign disease and prostate cancer. These features were used to construct a prostate cancer prediction model using the k-Nearest-Neighbor classification algorithm. The proposed model, which takes as input the set of flow cytometry features, outperformed the predictive model which takes PSA values as input. Specifically, the flow cytometry-based model achieved Accuracy = 83.33%, AUC = 83.40%, and optimal ROC points of FPR = 16.13%, TPR = 82.93%, whereas the PSA-based model achieved Accuracy = 77.78%, AUC = 76.95%, and optimal ROC points of FPR = 29.03%, TPR = 82.93%. Combining PSA and flow cytometry predictors achieved Accuracy = 79.17%, AUC = 78.17% and optimal ROC points of FPR = 29.03%, TPR = 85.37%. The results demonstrate the value of computational intelligence-based approaches for interrogating immunophenotyping datasets and that combining peripheral blood phenotypic profiling with PSA levels improves diagnostic accuracy compared to using PSA test alone. These studies also demonstrate that the presence of cancer is reflected in changes in the peripheral blood immune phenotype profile which can be identified using computational analysis and interpretation of complex flow cytometry datasets.

HAGE in Triple-Negative Breast Cancer Is a Novel Prognostic, Predictive, and Actionable Biomarker: A Transcriptomic and Protein Expression Analysis.

PURPOSE: The expression of HAGE as a novel prognostic and predictive tool was assessed in 1,079 triple-negative breast cancers (TNBC). EXPERIMENTAL DESIGN: HAGE protein expression was investigated in an early primary TNBC (EP-TNBC; n = 520) cohort who received adjuvant chemotherapy (ACT) and in a locally advanced primary TNBC cohort who received anthracycline combination Neo-ACT (n = 110; AC-Neo-ACT). HAGE-mRNA expression was evaluated in the METABRIC-TNBC cohort (n = 311) who received ACT and in a cohort of patients with TNBC who received doxorubicin/cyclophosphamide Neo-ACT, followed by 1:1 randomization to ixabepilone (n = 68) or paclitaxel (n = 64) as part of a phase II clinical trial. Furthermore, a cohort of 128 tumors with integrated HAGE gene copy number changes, mRNA, and protein levels were analyzed. RESULTS: In patients with EP-TNBC, who were chemotherapy-naïve, high HAGE protein expression (HAGE(+)) was associated with a higher risk of death [HR, 1.3; 95% confidence interval (CI), 1.2-1.5; P = 0.000005] when compared with HAGE(-) cases. Patients who received ACT and expressed mRNA-HAGE(+) were at a lower risk of death than those who were mRNA-HAGE(-) (P = 0.004). The expression of HAGE was linked to the presence of tumor-infiltrating lymphocytes (TIL), and both features were found to be independent predictors for pathologic complete response (pCR, P < 0.001) and associated with prolonged survival (P < 0.01), following AC-Neo-ACT. In patients with residual disease, HAGE(+) had a 2-fold death risk increase (P = 0.018) compared with HAGE(-). CONCLUSIONS: HAGE expression is a potential prognostic marker and a predictor of response to anthracycline treatment in TNBC. A prospective clinical trial to examine the therapeutic value of HAGE for TNBC cases is warranted.