High PD-1/PD-L1 Checkpoint Interaction Infers Tumor Selection and Therapeutic Sensitivity to Anti-PD-1/PD-L1 Treatment

Vimentin, inversely correlating with infiltration of CD8 + T lymphocytes, promotes nuclear translocation of PD-L1 in esophageal squamous cell carcinoma

Vimentin has been considered a canonical marker of epithelial-mesenchymal transition (EMT) and is associated with tumor escape characterized by aberrant PD-L1 expression. However, whether there is a relationship between vimentin and PD-L1 in esophageal squamous cell carcinoma (ESCC) remains poorly understood. The immunological involvement of vimentin in ESCC was first analyzed by multiplex immunofluorescence staining in ESCC tissue microarray followed by a xenografted mouse model. In vivo, C57BL/6 mice were subcutaneously transplanted with AKR cells after stable silencing of vimentin. In vivo results showed that in addition to PD-L1 and PD-L2 expression, vimentin expression was inversely correlated with CD8+ T-cell infiltration. Mechanistically, vimentin can directly interact with PD-L1 and promote nuclear translocation of PD-L1 in AKR cells. In addition, SEMA6C, STC-2 and TRAILR2 were identified as cytokines modulated by vimentin. Blockade of STC-2 and TRAILR2 in co-culture with their own primary antibodies was shown to recruit more CD8+ T cells than controls. Together, these data strongly suggest targeting Vimenin to overcome the immune cycle in ESCC.

Energy metabolism as the hub of advanced non-small cell lung cancer management: a comprehensive view in the framework of predictive, preventive, and personalized medicine

Energy metabolism is a hub of governing all processes at cellular and organismal levels such as, on one hand, reparable vs. irreparable cell damage, cell fate (proliferation, survival, apoptosis, malignant transformation etc.), and, on the other hand, carcinogenesis, tumor development, progression and metastazing versus anti-cancer protection and cure. The orchestrator is the mitochondria who produce, store and invest energy, conduct intracellular and systemically relevant signals decisive for internal and environmental stress adaptation, and coordinate corresponding processes at cellular and organismal levels. Consequently, the quality of mitochondrial health and homeostasis is a reliable target for health risk assessment at the stage of reversible damage to the health followed by cost-effective personalized protection against health-to-disease transition as well as for targeted protection against the disease progression (secondary care of cancer patients against growing primary tumors and metastatic disease). The energy reprogramming of non-small cell lung cancer (NSCLC) attracts particular attention as clinically relevant and instrumental for the paradigm change from reactive medical services to predictive, preventive and personalized medicine (3PM). This article provides a detailed overview towards mechanisms and biological pathways involving metabolic reprogramming (MR) with respect to inhibiting the synthesis of biomolecules and blocking common NSCLC metabolic pathways as anti-NSCLC therapeutic strategies. For instance, mitophagy recycles macromolecules to yield mitochondrial substrates for energy homeostasis and nucleotide synthesis. Histone modification and DNA methylation can predict the onset of diseases, and plasma C7 analysis is an efficient medical service potentially resulting in an optimized healthcare economy in corresponding areas. The MEMP scoring provides the guidance for immunotherapy, prognostic assessment, and anti-cancer drug development. Metabolite sensing mechanisms of nutrients and their derivatives are potential MR-related therapy in NSCLC. Moreover, miR-495-3p reprogramming of sphingolipid rheostat by targeting Sphk1, 22/FOXM1 axis regulation, and A2 receptor antagonist are highly promising therapy strategies. TFEB as a biomarker in predicting immune checkpoint blockade and redox-related lncRNA prognostic signature (redox-LPS) are considered reliable predictive approaches. Finally, exemplified in this article metabolic phenotyping is instrumental for innovative population screening, health risk assessment, predictive multi-level diagnostics, targeted prevention, and treatment algorithms tailored to personalized patient profiles-all are essential pillars in the paradigm change from reactive medical services to 3PM approach in overall management of lung cancers. This article highlights the 3PM relevant innovation focused on energy metabolism as the hub to advance NSCLC management benefiting vulnerable subpopulations, affected patients, and healthcare at large.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00357-5.

Immune Marker Spatial Distribution and Clinical Outcome after PD-1 Blockade in Mismatch Repair-deficient, Advanced Colorectal Carcinomas

PURPOSE

Targeting the programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) interaction has led to durable responses in fewer than half of patients with mismatch repair-deficient (MMR-d) advanced colorectal cancers. Immune contexture, including spatial distribution of immune cells in the tumor microenvironment (TME), may predict immunotherapy outcome.

EXPERIMENTAL DESIGN

Immune contexture and spatial distribution, including cell-to-cell distance measurements, were analyzed by multiplex immunofluorescence (mIF) in primary colorectal cancers with d-MMR (N = 33) from patients treated with anti-PD-1 antibodies. By digital image analysis, density, ratio, intensity, and spatial distribution of PD-L1, PD-1, CD8, CD3, CD68, LAG3, TGFβR2, MHC-I, CD14, B2M, and pan-cytokeratin were computed. Feature selection was performed by regularized Cox regression with LASSO, and a proportional hazards model was fitted to predict progression-free survival (PFS).

RESULTS

For predicting survival among patients with MMR-d advanced colorectal cancer receiving PD-1 blockade, cell-to-cell distance measurements, but not cell densities or ratios, achieved statistical significance univariately. By multivariable feature selection, only mean number of PD-1+ cells within 10 μm of a PD-L1+ cell was significantly predictive of PFS. Dichotomization of this variable revealed that those with high versus low values had significantly prolonged PFS [median not reached (>83 months) vs. 8.5 months (95% confidence interval (95% CI), 4.7-NR)] with a median PFS of 28.4 months for all patients [adjusted HR (HRadj) = 0.14; 95% CI, 0.04-0.56; P = 0.005]. Expression of PD-1 was observed on CD8+ T cells; PD-L1 on CD3+ and CD8+ T lymphocytes, macrophages (CD68+), and tumor cells.

CONCLUSIONS

In d-MMR colorectal cancers, PD-1+ to PD-L1+ receptor to ligand proximity is a potential predictive biomarker for the effectiveness of PD-1 blockade.

Machine learning-based identification of glycosyltransferase-related mRNAs for improving outcomes and the anti-tumor therapeutic response of gliomas

Background: Glycosyltransferase participates in glycosylation modification, and glycosyltransferase alterations are involved in carcinogenesis, progression, and immune evasion, leading to poor outcomes. However, in-depth studies on the influence of glycosyltransferase on clinical outcomes and treatments are lacking. Methods: The analysis of differentially expressed genes was performed using the Gene Expression Profiling Interactive Analysis 2 database. A total of 10 machine learning algorithms were introduced, namely, random survival forest, elastic network, least absolute shrinkage and selection operator, Ridge, stepwise Cox, CoxBoost, partial least squares regression for Cox, supervised principal components, generalized boosted regression modeling, and survival support vector machine. Gene Set Enrichment Analysis was performed to explore signaling pathways regulated by the signature. Cell-type identification by estimating relative subsets of RNA transcripts was used for estimating the fractions of immune cell types. Results: Here, we analyzed the genomic and expressive alterations in glycosyltransferase-related genes in gliomas. A combination of 80 machine learning algorithms was introduced to establish the glycosyltransferase-related mRNA signature (GRMS) based on 2,030 glioma samples from The Cancer Genome Atlas Program, Chinese Glioma Genome Atlas, Rembrandt, Gravendeel, and Kamoun cohorts. The GRMS was identified as an independent hazardous factor for overall survival and exhibited stable and robust performance. Notably, gliomas in the high-GRMS subgroup exhibited abundant tumor-infiltrating lymphocytes and tumor mutation burden values, increased expressive levels of hepatitis A virus cellular receptor 2 and CD274, and improved progression-free survival when subjected to anti-tumor immunotherapy. Conclusion: The GRMS may act as a powerful and promising biomarker for improving the clinical prognosis of glioma patients.

Functional Engagement of the PD-1/PD-L1 Complex But Not PD-L1 Expression Is Highly Predictive of Patient Response to Immunotherapy in Non-Small-Cell Lung Cancer

PURPOSE

In many cancers, the expression of immunomodulatory ligands leads to immunoevasion, as exemplified by the interaction of PD-L1 with PD-1 on tumor-infiltrating lymphocytes. Profound advances in cancer treatments have come with the advent of immunotherapies directed at blocking these immuno-suppressive ligand-receptor interactions. However, although there has been success in the use of these immune checkpoint interventions, correct patient stratification for these therapies has been challenging.

MATERIALS AND METHODS

To address this issue of patient stratification, we have quantified the intercellular PD-1/PD-L1 interaction in formalin-fixed paraffin-embedded tumor samples from patients with non-small cell lung carcinoma, using a high-throughput automated quantitative imaging platform (quantitative functional proteomics [QF-Pro]).

RESULTS

The multisite blinded analysis across a cohort of 188 immune checkpoint inhibitor-treated patients demonstrated the intra- and intertumoral heterogeneity of PD-1/PD-L1 immune checkpoint engagement and notably showed no correlation between the extent of PD-1/PD-L1 interaction and PD-L1 expression. Importantly, PD-L1 expression scores used clinically to stratify patients correlated poorly with overall survival; by contrast, patients showing a high PD-1/PD-L1 interaction had significantly better responses to anti-PD-1/PD-L1 treatments, as evidenced by increased overall survival. This relationship was particularly strong in the setting of first-line treatments.

CONCLUSION

The functional readout of PD-1/PD-L1 interaction as a predictive biomarker for the stratification of patients with non-small-cell lung carcinoma, combined with PD-L1 expression, should significantly improve the response rates to immunotherapy. This would both capture patients excluded from checkpoint immunotherapy (high PD-1/PD-L1 interaction but low PD-L1 expression, 24% of patients) and additionally avoid treating patients who despite their high PD-L1 expression do not respond and suffer from side effects.

Identification of HPV16 positive cervical cancer subsets characterized by divergent immune and oncogenic phenotypes with potential implications for immunotherapy

BACKGROUND

Cervical cancers (CaCx), like many other cancer types, portray high molecular heterogeneity that affects response to therapy, including immunotherapy. In India and other developing countries, CaCx mortality rates are very high because women report to the clinics with advanced cancers in absence of organized screening programs. This calls for implementation of newer therapeutic regimens for CaCx, like immunotherapy, which is again not used commonly in such countries.

OBJECTIVE

Therefore, we focused on dissecting tumour immune heterogeneity, if any, identify immune gene-based biomarkers of heterogeneity and subsets of such cancers with the potential for immunotherapy. We also attempted to characterize the cancer-associated phenotypes of such subsets, including viral load, to decipher the relationship of tumour immunogenicity with oncogenicity.

METHODS

Employing RNA-seq analysis of 44 HPV16 positive CaCx patients, immune subtypes were identified by unsupervised hierarchical clustering of global immune-gene expression profiles. Proportions of tumor infiltrating immune cells in the tumor milieu were estimated, employing Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), using gene expression data from RNA-seq. The oncogenic phenotypes of the immune subtypes of CaCx were deciphered through differential gene expression (DEGs) and pathway enrichment analysis. Viral load was estimated through TaqMan-based qRT-PCR analysis.

RESULTS

Analysis revealed the presence of two immune subtypes of CaCx, A (26/44; 59.09%) and B (18/44; 40.90%). Compared to Subtype-A, Subtype-B portrayed overexpression of immune genes and high infiltration of immune cells, specifically CD8+ T cells (p < 0.0001). Besides, a significant correlation between PD-1 and PD-L1 co-expression among Subtype-B, as opposed to Subtype-A, confirmed the interactive roles of these immune checkpoint molecules in Subtype B. Stepwise discriminant analysis pin-pointed ten immune-genes that could classify 100% of the patients significantly (p < 0.0001) into the two immune subtypes and serve as potential biomarkers of CaCx immunity. Differential gene expression analysis between the subtypes unveiled that Subtype-B was more biologically aggressive than Subtype-A, reflecting loss of structural integrity and promotion of cancer progression. The viral load was significantly lower in Subtype-B (average viral load = 10.74/100 ng of genomic DNA) compared to Subtype-A (average viral load = 14.29/100 ng of genomic DNA). Thus viral load and the ten-gene panel underscore their association with immunogenicity and oncogenicity.

CONCLUSION

Our study provides strong evidence that only a subset, about 41% of HPV16 positive CaCx patients in India, portray immune enrichment of the tumor milieu coupled with aggressive phenotypes. Such subtypes are therefore likely to benefit through checkpoint molecule-based or tumor infiltrating lymphocyte-based immunotherapy, which could be a leap forward in tackling aggressive forms of such CaCx in India and other developing countries.

Determination of Interactive States of Immune Checkpoint Regulators in Lung Metastases after Radiofrequency Ablation

BACKGROUND

Cases of the spontaneous regression of multiple pulmonary metastases, after radiofrequency ablation (RFA), of a single lung metastasis, have been documented to be mediated by the immune system. The interaction of immune checkpoints, e.g., PD-1/PD-L1 and CTLA-4/CD80, may explain this phenomenon. The purpose of this study is to identify and quantify immune mechanisms triggered by RFA of pulmonary metastases originating from colorectal cancer.

METHODS

We used two-site time-resolved Förster resonance energy transfer as determined by frequency-domain FLIM (iFRET) for the quantification of receptor-ligand interactions. iFRET provides a method by which immune checkpoint interaction states can be quantified in a spatiotemporal manner. The same patient sections were used for assessment of ligand-receptor interaction and intratumoral T-cell labeling.

CONCLUSION

The checkpoint interaction states quantified by iFRET did not correlate with ligand expression. We show that immune checkpoint ligand expression as a predictive biomarker may be unsuitable as it does not confirm checkpoint interactions. In pre-RFA-treated metastases, there was a significant and negative correlation between PD-1/PD-L1 interaction state and intratumoral CD3+ and CD8+ density. The negative correlation of CD8+ and interactive states of PD-1/PD-L1 can be used to assess the state of immune suppression in RFA-treated patients.

Role of the Immune System in Renal Transplantation, Types of Response, Technical Approaches and Current Challenges

Advances over the last decades have made renal transplantation an important therapy for patients with end-stage renal disease, as the incidences of acute rejection and short-term transplant loss have been significantly reduced. However, long-term transplant survival remains a challenge in the renal transplantation community. The main causes of long-term graft loss are acute and chronic rejection, as well as the complications related to immunosuppression therapy. In spite of the breakthroughs achieved in recent years, histology is the gold standard technique to confirm the activation of the immune system against the graft with all the ensuing problems that taking biopsies brings to immunosuppressed patients. For this reason, several assays have been developed to try to monitor the immune function, but they show serious constraints owing to the fact that they require substantial laboratory work, they are not clinically available and they provide controversial results, so the combination of multiple assays is often needed to obtain a reliable diagnosis. Thus, the aim of this review is to perform a retrospective study of the immune system in renal transplantation, with special emphasis on the cutting-edge technological developments for monitoring, classification and early detection of rejection episodes in order to contribute to a better adjustment of immunosuppressive therapies and, hence, to a more personalized medicine that improves the quality of life of patients.

The Fusion of Quantitative Molecular Proteomics and Immune-Oncology: A Step Towards Precision Medicine in Cancer Therapeutics

Innate and adaptive immune systems are built-in homeostatic functions of many multicellular organisms and protect the host against foreign pathogens and infections. Dysregulation of the molecular mechanisms of the immune system can result in autoimmune diseases. The immune system can also be harnessed and manipulated to provide targeted cancer therapies, some of them relying on the blockade of immune-checkpoint receptors. Two prominent immune checkpoints, PD-1/PD-L1 and CTLA-4/CD80, comprise receptor-ligand pairs that prevent the host immune cells from attacking host tissues. However, cancer cells upregulate the respective PD-L1 and CD80 ligands for PD-1 and CTLA-4 and thereby evade the host-immune response. Therapeutic drugs that block PD-1/PD-L1 and CTLA-4/CD80 interactions re-enable the immune system to attack cancer cells, but their prognostic biomarker remains challenging. In this review, we discuss how the use of quantitative molecular imaging can be exploited to predict the response to anti-PD-1/PD-L1 therapies and to identify cancer patients who would benefit from them.

From rough to precise: PD-L1 evaluation for predicting the efficacy of PD-1/PD-L1 blockades

Developing biomarkers for accurately predicting the efficacy of immune checkpoint inhibitor (ICI) therapies is conducive to avoiding unwanted side effects and economic burden. At the moment, the quantification of programmed cell death ligand 1 (PD-L1) in tumor tissues is clinically used as one of the combined diagnostic assays of response to anti-PD-1/PD-L1 therapy. However, the current assays for evaluating PD-L1 remain imperfect. Recent studies are promoting the methodologies of PD-L1 evaluation from rough to precise. Standardization of PD-L1 immunohistochemistry tests is being promoted by using optimized reagents, platforms, and cutoff values. Combining novel in vivo probes with PET or SPECT will probably be of benefit to map the spatio-temporal heterogeneity of PD-L1 expression. The dynamic change of PD-L1 in the circulatory system can also be realized by liquid biopsy. Consider PD-L1 expressed on non-tumor (immune and non-immune) cells, and optimized combination detection indexes are further improving the accuracy of PD-L1 in predicting the efficacy of ICIs. The combinations of artificial intelligence with novel technologies are conducive to the intelligence of PD-L1 as a predictive biomarker. In this review, we will provide an overview of the recent progress in this rapidly growing area and discuss the clinical and technical challenges.

Genomic Variations and Immune-Related Features of TMB, PD-L1 Expression and CD8+ T Cell Infiltration in Chinese Pulmonary Sarcomatoid Carcinoma

Background

Pulmonary sarcomatoid carcinoma (PSC) is a rare and distinct subtype of lung cancer characterized by its aggressiveness and dismal prognosis. However, genomic landscape and immune contexture have not been fully elucidated among PSC patients.

Methods

In the present study, whole-exome-sequencing (WES) analyses were performed to depict genomic landscape of 38 independent PSC samples. Tumor mutation burden (TMB) was calculated with the total number of non-synonymous SNVs and indel variants per megabase of coding regions. PD-L1 expression and CD8⁺ T cell density were evaluated by immunohistochemistry in PSC samples. Their associations with genomic mutation were further assessed in genes with most frequent mutation. Overall survival (OS) of PSC patients with top mutated genes and high and low TMB, PD-L1 and CD8⁺ TIL expressions were further compared. Subgroup analyses of OS stratified by morphology and pathological type were conducted. Their correlation with TMB, PD-L1 and CD8⁺ T cell were further assessed.

Results

We identified a cohort of genomic and somatic mutation in PSC patients. Subgroup patients with distinct clinicopathological features were found to harbor different genomic mutations and immunologic features. Besides, genomic profiles influenced outcomes, with SARS mutation associated with worsened prognosis.

Conclusion

Through the mapping of genetic and immunologic landscape, we find the heterogeneity among the subgroups of PSC. Our findings may provide opportunities for therapeutic susceptibility among Chinese PSC patients.

Association of PD-1/PD-L1 Co-location with Immunotherapy Outcomes in Non-Small Cell Lung Cancer

PURPOSE

Programmed cell death protein 1(PD-1)/programmed death-ligand 1 (PD-L1) interaction suppresses local T cell responses and promotes peripheral tolerance. In the present study, we focus on PD-1/PD-L1 co-location as a surrogate for this interaction and assess its association with immunotherapy outcomes in patients with non-small cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

Pre-treatment biopsies from a retrospective cohort of 154 immunotherapy-treated patients with advanced NSCLC were analysed. Expression of PD-1 and PD-L1 was assessed by multiplexed quantitative immunofluorescence (QIF) and PD-1 expression in the same pixels as PD-L1 (called a co-location score) was measured using an algorithm to define overlapping expression areas. Co-location scores were correlated with immunotherapy outcomes and PD-L1 tumor proportion score.

RESULTS

PD-1/PD-L1 co-location score was associated with best overall response (p=0.0012), progression free survival (p=0.0341) and overall survival after immunotherapy (p=0.0249). The association was driven by patients receiving immune checkpoint inhibitors in the second or subsequent line of treatment. PD-L1 TPS by IHC was also correlated with best overall response and progression-free survival. PD-L1 measured within the tumor compartment by QIF did not show any significant association with either best overall response or overall survival. Finally, co-location score was not associated with PD-L1 expression by either method.

CONCLUSIONS

Based on our findings, co-location score shows promise as a biomarker associated with outcome after immunotherapy. With further validation, it could have value as a predictive biomarker for the selection of NSCLC patients receiving treatment with immune checkpoint inhibitors.

Non-small cell lung cancer: Emerging molecular targeted and immunotherapeutic agents

Non-small cell lung cancer (NSCLC) represents the most common and fatal type of primary lung malignancies. NSCLC is often diagnosed at later stages and requires systemic therapies. Despite recent advances in surgery, chemotherapy, and targeted molecular therapies the outcomes of NSCLC remain disproportionately poor. Immunotherapy is a rapidly developing area in NSCLC management and presents opportunities for potential improvements in clinical outcomes. Indeed, different immunotherapeutics have been approved for clinical use in various settings for NSCLC. Their promise is especially poignant in light of improved survival and quality of life outcomes. Herein, we comprehensively review emerging NSCLC therapeutics. We discuss the limitations of such strategies and summarize the present status of various immunotherapeutic agents in key patient populations. We also examine the data from ongoing studies in immunotherapy and consider future areas of study, including novel inhibition targets, therapeutic vaccination, tumor genome modification, and improvements to drug delivery systems.

Quantification of PD-1/PD-L1 Interaction between Membranes from PBMCs and Melanoma Samples Using Cell Membrane Microarray and Time-Resolved Förster Resonance Energy Transfer

Melanoma is a carcinoma known to evade the host immune defenses via the downregulation of the immune response. One of the molecules involved in this mechanism is programmed cell death ligand 1 (PD-L1), which interacts with its receptor, programmed cell death protein 1 (PD-1), expressed on T cells, leading to a reduction in cytokine release and cytotoxic activity, as well as a halt in T-cell proliferation. The approved therapeutic monoclonal antibodies, such as pembrolizumab, target the PD-1/PD-L1 interaction and are revolutionizing cancer treatments. We developed an assay that provides a quantitative readout of PD-1/PD-L1 interactive states between cell membranes of human immune cells (peripheral blood mononuclear cells, PBMCs) and PD-L1-expressing samples. For this purpose, cell membrane microarrays (CMMAs) were developed from membranes isolated from a HT144 cell line and melanoma samples, and PD-L1 expression was quantified using immunofluorescence (IF). CMMAs were incubated with cell membranes of PBMCs expressing PD-1, and the interaction with PD-L1 was quantified by time-resolved Förster resonance energy transfer, in the presence and absence of pembrolizumab as a blocking drug. The developed assay was able to quantify the PD-1/PD-L1 interaction, and this engagement was disrupted in the presence of the blocking antibody. This demonstrates the potential of the method to analyze monoclonal antibody drugs, as well as the functional states of immune checkpoint regulators. Furthermore, our findings provide evidence to support the future implementation of this methodology for both drug discovery and immune system monitoring in cancer, transplantation, and inflammatory and autoimmune diseases.

Immunogenomics of Colorectal Cancer Response to Checkpoint Blockade: Analysis of the KEYNOTE 177 Trial and Validation Cohorts

BACKGROUND & AIMS

Colorectal cancer (CRC) shows variable response to immune checkpoint blockade, which can only partially be explained by high tumor mutational burden (TMB). We conducted an integrated study of the cancer tissue and associated tumor microenvironment (TME) from patients treated with pembrolizumab (KEYNOTE 177 clinical trial) or nivolumab to dissect the cellular and molecular determinants of response to anti- programmed cell death 1 (PD1) immunotherapy.

METHODS

We selected multiple regions per tumor showing variable T-cell infiltration for a total of 738 regions from 29 patients, divided into discovery and validation cohorts. We performed multiregional whole-exome and RNA sequencing of the tumor cells and integrated these with T-cell receptor sequencing, high-dimensional imaging mass cytometry, detection of programmed death-ligand 1 (PDL1) interaction in situ, multiplexed immunofluorescence, and computational spatial analysis of the TME.

RESULTS

In hypermutated CRCs, response to anti-PD1 immunotherapy was not associated with TMB but with high clonality of immunogenic mutations, clonally expanded T cells, low activation of Wnt signaling, deregulation of the interferon gamma pathway, and active immune escape mechanisms. Responsive hypermutated CRCs were also rich in cytotoxic and proliferating PD1+CD8 T cells interacting with PDL1+ antigen-presenting macrophages.

CONCLUSIONS

Our study clarified the limits of TMB as a predictor of response of CRC to anti-PD1 immunotherapy. It identified a population of antigen-presenting macrophages interacting with CD8 T cells that consistently segregate with response. We therefore concluded that anti-PD1 agents release the PD1-PDL1 interaction between CD8 T cells and macrophages to promote cytotoxic antitumor activity.

p53 Activation Effect in the Balance of T Regulatory and Effector Cell Subsets in Patients With Thyroid Cancer and Autoimmunity

Carcinomas evade the host immune system by negatively modulating CD4+ and CD8+ T effector lymphocytes through forkhead box protein 3 (FOXP3) positive T regulatory cells’ increased activity. Furthermore, interaction of the programmed cell death 1 (PD1) molecule and its ligand programmed cell death ligand 1 (PDL1) inhibits the antitumor activity of PD1+ T lymphocytes. Immunotherapy has become a powerful strategy for tailored cancer patients’ treatment both in adult and pediatric patients aiming to generate potent antitumor responses. Nevertheless, immunotherapies can generate autoimmune responses. This study aimed to investigate the potential effect of the transformation-related protein 53 (p53) reactivation by a peptide-based inhibitor of the MDM2/MDM4 heterodimer (Pep3) on the immune response in a solid cancer, i.e., thyroid carcinoma frequently presenting with thyroid autoimmunity. In peripheral blood mononuclear cell of thyroid cancer patients, Pep3 treatment alters percentages of CD8+ and CD4+ T regulatory and CD8+ and CD4+ T effector cells and favors an anticancer immune response. Of note that reduced frequencies of activated CD8+ and CD4+ T effector cells do not support autoimmunity progression. In evaluating PD1 expression under p53 activation, a significant decrease of activated CD4+PD1+ cells was detected in thyroid cancer patients, suggesting a defective regulation in the initial activation stage, therefore generating a protective condition toward autoimmune progression.

CML derived exosomes promote tumor favorable functional performance in T cells

Background

Leukemic cells facilitate the creation of the tumor-favorable microenvironment in the bone marrow niche using their secreted factors. There are not comprehensive details about immunosuppressive properties of chronic myelogenous leukemia-derived exosomes in the bone marrow stromal and immune compartment. We explained here that K562-derived exosomes could affect the gene expression, cytokine secretion, nitric oxide (NO) production, and redox potential of human primary cord blood-derived T cells (CB T cells).

Methods

Human primary cord blood-derived T cells were treated with K562-derived exosomes. We evaluated the expression variation of some critical genes activated in suppressor T cells. The alterations of some inflammatory and anti-inflammatory cytokines levels were assessed using ELISA assay and real-time PCR. Finally, NO production and intracellular ROS level in CB T cells were evaluated using Greiss assay and flow cytometry, respectively.

Results

Our results showed the over-expression of the genes involved in inhibitory T cells, including NQO1, PD1, and FoxP3. In contrast, genes involved in T cell activation such as CD3d and NFATc3 have been reduced significantly. Also, the expression of interleukin 10 (IL-10) and interleukin 6 (IL-6) mRNAs were significantly up-regulated in these cells upon exosome treatment. In addition, secretion of the interleukin 10, interleukin 6, and interleukin 17 (IL-17) proteins increased in T cells exposed to K562-derived exosomes. Finally, K562-derived exosomes induce significant changes in the NO production and intracellular ROS levels in CB T cells.

Conclusions

These results demonstrate that K562-derived exosomes stimulate the immunosuppressive properties in CB-derived T cells by inducing anti-inflammatory cytokines such as IL-10, reducting ROS levels, and arising of NO synthesis in these cells. Moreover, considering the elevation of FOXP3, IL-6, and IL-17 levels in these cells, exosomes secreted by CML cells may induce the fates of T cells toward tumor favorable T cells instead of conventional activated T cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08734-3.

CD8+ T Cell Exhaustion in Cancer

A paradigm shift in the understanding of the exhausted CD8⁺ T cell (T_ex) lineage is underway. Originally thought to be a uniform population that progressively loses effector function in response to persistent antigen, single-cell analysis has now revealed that CD8⁺ T_ex is composed of multiple interconnected subpopulations. The heterogeneity within the CD8⁺ T_ex lineage is comprised of immune checkpoint blockade (ICB) permissive and refractory subsets termed stem-like and terminally differentiated cells, respectively. These populations occupy distinct peripheral and intratumoral niches and are characterized by transcriptional processes that govern transitions between cell states. This review presents key findings in the field to construct an updated view of the spatial, transcriptional, and functional heterogeneity of anti-tumoral CD8⁺ T_ex. These emerging insights broadly call for (re-)focusing cancer immunotherapies to center on the driver mechanism(s) underlying the CD8⁺ T_ex developmental continuum aimed at stabilizing functional subsets.

Antibody-drug conjugates, immune-checkpoint inhibitors, and their combination in breast cancer therapeutics

INTRODUCTION

Advanced breast cancer (aBC) remains incurable and the quest for more effective systemic anticancer agents continues. Promising results have led to the FDA approval of three antibody-drug conjugates (ADCs) and two immune checkpoint inhibitors (ICIs) to date for patients with aBC.

AREAS COVERED

With the anticipated emergence of newer ADCs and ICIs for patients with several subtypes of breast cancer, and given their potential synergy, their use in combination is of clinical interest. In this article, we review the use of ADCs and ICIs in patients with breast cancer, assess the scientific rationale for their combination, and provide an overview of ongoing trials and some early efficacy and safety results of such dual therapy.

EXPERT OPINION

Improvement in the medicinal chemistry of next-generation ADCs, their rational combination with ICIs and other agents, and the development of multiparametric immune biomarkers could help to significantly improve the outlook for patients with refractory aBC.

Quantification of biomarker functionality predicts patient outcomes

Implementation of a quantitative molecular imaging method (iFRET), which determines receptor-ligand interactions, has led to the finding that patients with a low extent of PD-1/PD-L1 interaction in metastatic NSCLC, and malignant melanoma, display significantly worsened overall survival compared to those with a high level of interaction.

Insights into Urological Cancer

The year the Covid-19 pandemic appeared has been quite prolific in urological cancer research, and the collection of articles, perspectives, and reviews on renal, prostate, and urinary tract tumors merged in this Urological Cancer 2020 issue is just a representative sample of this assertion [...].

Predicting Response to Immunotherapy in Metastatic Renal Cell Carcinoma

Simple Summary

Immunotherapy-based treatment options have become standard of care in metastatic renal cell carcinoma. Despite significant improvement in overall survival with these therapies, the tumors of many patients will eventually progress. This review highlights the ongoing efforts to develop biomarkers to help predict which patients are most likely to benefit from treatment with immunotherapy.

Abstract

Immunotherapy-based combinations, driven by PD-1, PD-L1, and CTLA-4 inhibitors, has altered the treatment landscape for metastatic renal cell carcinoma (RCC). Despite significant improvements in clinical outcomes, many patients do not experience deep or lasting benefits. Recent efforts to determine which patients are most likely to benefit from immunotherapy and immunotherapy-based combinations have shown promise but have not yet affected clinical practice. PD-L1 expression via immunohistochemistry (IHC) has shown promise in a few clinical trials, although variations in the IHC assays as well as the use of different values for positivity presents unique challenges for this potential biomarker. Several other candidate biomarkers were investigated including tumor mutational burden, gene expression signatures, single gene mutations, human endogenous retroviruses, the gastrointestinal microbiome, and peripheral blood laboratory markers. While individually these biomarkers have yet to explain the heterogeneity of treatment response to immunotherapy, using aggregate information from these biomarkers may inform clinically useful predictive biomarkers.