Prediction of unfavourable response to checkpoint blockade in lung cancer patients through an integrated tumour-immune expression score

BackgroundTreatment by immune checkpoint blockade (ICB) provides a remarkable survival benefit for multiple cancer types. However, disease aggravation occurs in a proportion of patients after the first couple of treatment cycles.MethodsRNA sequencing data was retrospectively collected. 6 tumour-immune related features were extracted and combined to build a lung cancer-specific predictive model to distinguish responses as progression disease (PD) or non-PD. This model was trained by 3 public pan-cancer datasets and a lung cancer cohort from our institute, and generated a lung cancer-specific integrated gene expression score, which we call LITES. It was finally tested in another lung cancer dataset.ResultsLITES is a promising predictor for checkpoint blockade (area under the curve [AUC]=0.86), superior to traditional biomarkers. It is independent of PD-L1 expression and tumour mutation burden. The sensitivity and specificity of LITES was 85.7% and 70.6%, respectively. Progression free survival (PFS) was longer in high-score group than in low-score group (median PFS: 6.0 vs. 2.4 months, hazard ratio=0.45, P=0.01). The mean AUC of 6 features was 0.70 (range=0.61-0.75), lower than in LITES, indicating that the combination of features had synergistic effects. Among the genes identified in the features, patients with high expression of NRAS and PDPK1 tended to have a PD response (P=0.001 and 0.01, respectively). Our model also functioned well for patients with advanced melanoma and was specific for ICB therapy.ConclusionsLITES is a promising biomarker for predicting an impaired response in lung cancer patients and for clarifying the biological mechanism underlying ICB therapy.     

Immune-related long noncoding RNA signature for predicting survival and immune checkpoint blockade in hepatocellular carcinoma

Long noncoding RNAs (lncRNAs) show multiple functions, including immune response. Recently, the immune-related lncRNAs have been reported in some cancers. We first investigated the immune-related lncRNA signature as a potential target in hepatocellular carcinoma (HCC) survival. The training set (n = 368) and the independent external validation cohort (n = 115) were used. Immune genes and lncRNAs coexpression were constructed to identify immune-related lncRNAs. Cox regression analyses were perfumed to establish the immune-related lncRNA signature. Regulatory roles of this signature on cancer pathways and the immunologic features were investigated. The correlation between immune checkpoint inhibitors and this signature was examined. In this study, the immune-related lncRNA signature was identified in HCC, which could stratify patients into high- and low-risk groups. This immune-related lncRNA signature was correlated with disease progression and worse survival and was an independent prognostic biomarker. Our immune-related lncRNA signature was still a powerful tool in predicting survival in each stratum of age, gender, and tumor stage. This signature mediated cell cycle, glycolysis, DNA repair, mammalian target of rapamycin signaling, and immunologic characteristics (i.e., natural killer cells vs. Th1 cells down, etc). This signature was associated with immune cell infiltration (i.e., macrophages M0, Tregs, CD4 memory T cells, and macrophages M1, etc.,) and immune checkpoint blockade (ICB) immunotherapy-related molecules (i.e., PD-L1, PD-L2, and IDO1). Our findings suggested that the immune-related lncRNA signature had an important value for survival prediction and may have the potential to measure the response to ICB immunotherapy. This signature may guide the selection of the immunotherapy for HCC.     

Rationally combining immunotherapies to improve efficacy of immune checkpoint blockade in solid tumors

With the widespread application of immune checkpoint blocking antibodies (ICBs) for the treatment of advanced cancer, immunotherapy has proven to be capable of yielding unparalleled clinical results. However, despite the initial success of ICB-treatment, still a minority of patients experience durable responses to ICB therapy. A plethora of mechanisms underlie ICB resistance ranging from low immunogenicity, inadequate generation or recruitment of tumor-specific T cells or local suppression by stromal cells to acquired genetic alterations leading to immune escape. Increasing the response rates to ICBs requires insight into the mechanisms underlying resistance and the subsequent design of rational therapeutic combinations on a per patient basis. In this review, we aim to establish order into the mechanisms governing primary and secondary ICB resistance, offer therapeutic options to circumvent different modes of resistance and plea for a personalized medicine approach to maximize immunotherapeutic benefit for all cancer patients.     

Selective autophagy of MHC-I promotes immune evasion of pancreatic cancer

ABSTRACT

Major histocompatibility complex class I (MHC-I) is a key molecule in anti-tumor adaptive immunity. MHC-I is essential for endogenous antigen presentation by cancer cells and subsequent recognition and clearance by CD8⁺ T cells. Defects in MHC-I expression occur frequently in several cancers, leading to impaired antigen presentation, immune evasion and/or resistance to immune checkpoint blockade (ICB) therapy. Pancreatic ductal adenocarcinoma (PDAC), a deadly malignancy with dismal patient prognosis, is resistant to ICB and shows frequent downregulation of MHC-I independent of genetic mutations abrogating MHC-I expression. Previously, we showed that PDAC cells exhibit elevated levels of autophagy and lysosomal biogenesis, which together support the survival and growth of PDAC tumors via both cell-autonomous and non-cell-autonomous mechanisms. In our recent study, we have identified NBR1-mediated selective macroautophagy/autophagy of MHC-I as a novel mechanism that facilitates immune evasion by PDAC cells. Importantly, autophagy or lysosome inhibition restores MHC-I expression, leading to enhanced anti-tumor T cell immunity and improved response to ICB in transplanted tumor models in syngeneic host mice. Our results highlight a previously unknown function of autophagy and the lysosome in regulation of immunogenicity in PDAC, and provide a novel therapeutic strategy for targeting this deadly disease.     

Keeping Tumors in Check: A Mechanistic Review of Clinical Response and Resistance to Immune Checkpoint Blockade in Cancer

Immune checkpoints are a diverse set of inhibitory signals to the immune system that play a functional role in adaptive immune response and self-tolerance. Dysregulation of these pathways is a vital mechanism in the avoidance of immune destruction by tumor cells. Immune checkpoint blockade (ICB) refers to targeted strategies to disrupt the tumor co-opted immune suppression to enhance anti-tumor immunity. Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death 1 (PD-1) are two immune checkpoints that have the widest range of antibody-based therapies. These therapies have gone from promising approaches to Food and Drug Administration-approved first- and second-line agents for a number of immunogenic cancers. The burgeoning investigations of ICB efficacy in blood and solid cancers have underscored the importance of identifying the predictors of response and resistance to ICB. Identification of response correlates is made complicated by the observations of mixed reactions, or different responses in multiple lesions from the same patient, and delayed responses that can occur over a year after the induction therapy. Factors that can influence response and resistance in ICB can illuminate underlying molecular mechanisms of immune activation and suppression. These same response predictors can guide the identification of patients who would benefit from ICB, reduce off-target immune-relate adverse events, and facilitate the use of combinatorial therapies to increase efficacy. Here we review the underlying principles of immune checkpoint therapy and results of single-agent ICB clinical trials, and summarize the predictors of response and resistance.     

Single-cell Analysis Technologies for Immuno-oncology Research: from Mechanistic Delineation to Biomarker Discovery

The successes with immune checkpoint blockade(ICB) and chimeric antigen receptor(CAR)-T-cell therapy in treating multiple cancer types have established immunotherapy as a powerful curative option for patients with advanced cancers. Unfortunately, many patients do not derive benefit or long-term responses, highlighting a pressing need to perform complete investigation of the underlying mechanisms and the immunotherapy-induced tumor regression or rejection.In recent years, a large number of single-cell technologies have leveraged advances in characterizing immune system, profiling tumor microenvironment, and identifying cellular heterogeneity, which establish the foundations for lifting the veil on the comprehensive crosstalk between cancer and immune system during immunotherapies. In this review, we introduce the applications of the most widely used single-cell technologies in furthering our understanding of immunotherapies in terms of underlying mechanisms and their association with therapeutic outcomes. We also discuss how single-cell analyses help to deliver new insights into biomarker discovery to predict patient response rate, monitor acquired resistance, and support prophylactic strategy development for toxicity management. Finally, we provide an overview of applying cutting-edge single-cell spatial-omics to point out the heterogeneity of tumor–immune interactions at higher level that can ultimately guide to the rational design of next-generation immunotherapies.     

An immunophenotyping of renal clear cell carcinoma with characteristics and a potential therapeutic target for patients insensitive to immune checkpoint blockade

Renal clear cell carcinoma (RCC) patients who do not achieve optimal control of progression with immune checkpoint blockade (ICB) should be further studied. Unsupervised consensus clustering was used to group 525 RCC patients based on two typical ICB pathways, CTLA-4 and pogrammed death 1 (PD-1)/programmed death-ligand 1 (PD-L1), as well as two new discovered regulators, CMTM6 and CMTM4. Three immune molecular subtypes (IMMSs) with different clinical and immunological characteristics were identified (type I, II, and III), among which there were more stage I and low-grade tumors in type I RCC than in type II and III. The proportion of males was highest in type II RCC. Overall survival of type II and III was similar (5.2 and 6 years) and statistically shorter than that of type I (7.6 years) before and after adjusting for age and gender. When conducting stratified analysis, our IMMSs were able to identify high-risk patients among middle-aged patients, males, and stage IV patients. Among the differentially expressed genes, approximately 84% were highly expressed in type II and III RCC. Genes related to ICB (CTLA-4, CD274, and PDCD1LG2) and cytotoxic lymphocytes (CD8A, GZMA, and PRF1) were all highly expressed in type II and III RCC. These results documented that patients with type II and III cancer may be more sensitive to anti-CTLA-4 therapy, anti-PD-1/PD-L1 therapy, and a combination of immunotherapies. High expression of CMTM4 in type I RCC (69%) and a statistically significant interaction of CD274 and CMTM6 indicated that CMTM4/6 might be new therapy targets for type I, who are resistant to ICB.     

Construction of a prognostic immune signature for lower grade glioma that can be recognized by MRI radiomics features to predict survival in LGG patients

BackgroundThis study aimed to identify a series of prognostically relevant immune features by immunophenoscore. Immune features were explored using MRI radiomics features to prediction the overall survival (OS) of lower-grade glioma (LGG) patients and their response to immune checkpoints.MethodLGG data were retrieved from TCGA and categorized into training and internal validation datasets. Patients attending the First Affiliated Hospital of Harbin Medical University were included in an external validation cohort. An immunophenoscore-based signature was built to predict malignant potential and response to immune checkpoint inhibitors in LGG patients. In addition, a deep learning neural network prediction model was built for validation of the immunophenoscore-based signature.ResultsImmunophenotype-associated mRNA signatures (IMriskScore) for outcome prediction and ICB therapeutic effects in LGG patients were constructed. Deep learning of neural networks based on radiomics showed that MRI radiomic features determined IMriskScore. Enrichment analysis and ssGSEA correlation analysis were performed. Mutations in CIC significantly improved the prognosis of patients in the high IMriskScore group. Therefore, CIC is a potential therapeutic target for patients in the high IMriskScore group. Moreover, IMriskScore is an independent risk factor that can be used clinically to predict LGG patient outcomes.ConclusionsThe IMriskScore model consisting of a sets of biomarkers, can independently predict the prognosis of LGG patients and provides a basis for the development of personalized immunotherapy strategies. In addition, IMriskScore features were predicted by MRI radiomics using a deep learning approach using neural networks. Therefore, they can be used for the prognosis of LGG patients.     

Enhancing immune checkpoint blockade therapy of genitourinary malignancies by co-targeting PMN-MDSCs

Immune checkpoint blockade (ICB) as a powerful immunotherapy has transformed cancer treatment. The application of ICB to genitourinary malignancies has generated substantial clinical benefits for patients with advanced kidney cancer or bladder cancer, yet very limited response to ICB therapy was observed from metastatic castration-resistant prostate cancer. The efficacy of ICB in rare genitourinary tumors (e.g. penile cancer) awaits results from ongoing clinical trials. A potential barrier for ICB is tumor-infiltrating polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) with their functions and mechanisms recently revealed. Preclinical studies suggest that successful therapeutic inhibition of PMN-MDSCs synergizes effectively with ICB to eradicate ICB-refractory genitourinary malignancies.     

Immune checkpoint blockade impairs immunosuppressive mechanisms of regulatory T cells in B-cell lymphoma

In malignant disease, CD4⁺Foxp3⁺ regulatory T cells (Tregs) hamper antitumor immune responses and may provide a target for immunotherapy. Although immune checkpoint blockade (ICB) has become an established therapy for several cancer entities including lymphoma, its mechanisms have not been entirely uncovered. Using endogenously arising λ-MYC-transgenic mouse B-cell lymphomas, which can effectively be suppressed by either Treg ablation or ICB, we investigated which mechanisms are used by Tregs to suppress antitumor responses and how ICB affects these pathways. During tumor development, Tregs up-regulated Foxp3, CD25, CTLA-4 and IL-10, which correlated with enhanced immunosuppressive functions. Thus, in contrast to other tumors, Tregs did not become dysfunctional despite chronic stimulation in the tumor microenvironment and progressive up-regulation of PD-1. Immunosuppression was mediated by direct contacts between Tregs and effector T cells and by IL-10. When λ-MYC mice were treated with ICB antibodies, Tregs revealed a less profound up-regulation of Foxp3, CD25 and IL-10 and a decreased suppressive capacity. This may be due to the shift towards a pro-inflammatory milieu fostered by ICB. In summary, an ICB-induced interference with Treg-dependent immunosuppression may contribute to the success of ICB.     

Homologous Recombination Repair Deficiency and the Immune Response in Breast Cancer: A Literature Review

The success of cancer immunotherapy with immune checkpoint blockade (ICB) has demonstrated the importance of targeting a preexisting immune response in a broad spectrum of tumors. This is particularly novel and relevant for less immunogenic tumors, such as breast cancer (BC), where the efficacy of ICB was more evident in the triple-negative (TNBC) subtype, in earlier stages, and in association with chemotherapy. Tumors harboring homologous recombination DNA repair (HRR) deficiency (HRD) are supposed to have a higher number of mutations, hence a higher tumor mutational burden, which could potentially make them more sensitive to immunotherapy. However, the mechanisms involved in ICB sensitivity and patient selection are still yet to be defined in BC: whether the innate system could play a role and how the adaptive immunity could be linked with HRR pathways are the two key points of debate that we will discuss in this article. The aim of this review was to close the loop between what was found in clinical trial results so far, go back to laboratory theory and preclinical results and point out what needs to be clarified from now on.     

The joint role of methylation and immune-related lncRNAs in ovarian cancer: Defining molecular subtypes and developing prognostic signature

IntroductionComplex outcome of ovarian cancer (OC) stems from the tumor immune microenvironment (TIME) influenced by genetic and epigenetic factors. This study aimed to comprehensively explored the subclasses of OC through lncRNAs related to both N6-methyladenosine (m6A)/N1-methyladenosine (m1A)/N7-methylguanosine (m7G)/5-methylcytosine (m5C) in terms of epigenetic variability and immune molecules and develop a new set of risk predictive systems.Material and methodsThe lncRNA data of OC were collected from TCGA. Spearman correlation analysis on lncRNA data of OC with immune-related gene expression and with m6A/m5C/m1A/m7G were respectively conducted. The m6A/m5C/m1A/m7G-related m6A/m5C/m1A/m7G related immune lncRNA subtypes were identified on the basis of the prognostic lncRNAs. Heterogeneity among subtypes was evaluated by tumor mutation analysis, tumor microenvironment (TME) component analysis, response to immune checkpoint blocked (ICB) and chemotherapeutic drugs. A risk predictive system was developed based on the results of Cox regression analysis and random survival forest analysis of the differences between each specific cluster and other clusters.ResultsThree m6A/m5C/m1A/m7G-related immune lncRNA subtypes of OC showing distinct differences in prognosis, mutation pattern, TIME components, immunotherapy and chemotherapy response were identified. A set of risk predictive system consisting of 10 lncRNA for OC was developed, according to which the risk score of samples in each OC dataset was calculated and risk type was defined.ConclusionsThis study classified three m6A/m5C/m1A/m7G-related immune lncRNA subtypes with distinct heterogeneous mutation patterns, TME components, ICB therapy and immune response, and provided a set of risk predictive system consisted of 10 lncRNA for OC.     

Mutational profiling of low-grade gliomas identifies prognosis and immunotherapy-related biomarkers and tumour immune microenvironment characteristics

Low-grade glioma (LGG) is a heterogeneous tumour with the median survival rate less than 10 years. Therefore, it is urgent to develop efficient immunotherapy strategies of LGG. In this study, we analysed mutation profiles based on the data of 510 LGG patients from the Cancer Genome Atlas (TCGA) database and investigated the prognostic value of mutated genes and evaluate their immune infiltration. Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to indicate the characteristics of gliomas that respond to immune checkpoint blockade (ICB) therapy. Univariate and multivariate cox regression analysis was performed to identify indicators to construct the nomogram model. 485 (95.47%) of 508 LGG samples showed gene mutation, and 9 mutated genes were significantly related to overall survival (OS), among which 6 mutated genes were significantly correlated with OS between mutation and wildtypes. Immune infiltration and immune score analyses revealed that these six mutated genes were significantly associated with tumour immune microenvironment in LGG. The response of LGG with different characteristics to ICB was evaluated by TIDE algorithm. Finally, CIC gene was screened through both univariate and multivariate Cox regression analyses, and the nomogram model was established to determine the potential prognostic value of CIC in LGG. Our study provides comprehensive analysis of mutated genes in LGG, supporting modulation of mutated genes in the management of LGG.     

A comprehensive analysis of IDO1 expression with tumour‐infiltrating immune cells and mutation burden in gynaecologic and breast cancers

Gynaecologic and breast cancers share some similarities at the molecular level. The aims of our study are to highlight the similarities and differences about IDO1, an important immune‐related gene in female cancers. The NGS data from TCGA of cervical squamous cell carcinoma (CESC), ovarian serous cystadenocarcinoma (OV), uterine corpus endometrial carcinoma (UCEC), uterine carcinosarcoma (UCS) and breast invasive carcinoma (BRCA) were analysed to identify molecular features, and clinically significant and potential therapeutic targets of IDO1. We found IDO1 was significantly up‐regulated in four gynaecologic cancers and breast cancer. According to breast cancer PAM50 classification scheme, IDO1 expression was higher in tumours of basal than other subtypes and showed better survival prognosis in BRCA and OV. Through immune infiltration analysis, we found a strong correlation between IDO1 and immune cell populations especially for dendritic cells and T cells. In addition, we investigated the association between IDO1 and tumour mutation burden (TMB) and found that IDO1 was significantly correlated with TMB in BRCA and CESC. GSVA revealed that hallmarks significantly correlated with IDO1 were involved in interferon gamma response, allograft rejection and inflammatory response. We also found PD‐L1 and LAG3 were highly positive related to IDO1 in gynaecologic cancers when comparing with their corresponding normal tissues. Our results indicated that IDO1 participated in anti‐tumour immune process and is correlated with mutation burden. These findings may expand our outlook of potential anti‐IDO1 treatments.     

Immune Checkpoint Blockade Augments Changes Within Oncolytic Virus-induced Cancer MHC-I Peptidome,Creating Novel Antitumor CD8 T Cell Reactivities

The combination cancer immunotherapies with oncolytic virus (OV) and immune checkpoint blockade (ICB) reinstate otherwise dysfunctional antitumor CD8 T cell responses. One major mechanism that aids such reinstatement of antitumor CD8 T cells involves the availability of new class I major histocompatibility complex (MHC-I)-bound tumor epitopes following therapeutic intervention. Thus, therapy-induced changes within the MHC-I peptidome hold the key to understanding the clinical implications for therapy-reinstated CD8 T cell responses. Here, using mass spectrometry–based immuno-affinity methods and tumor-bearing animals treated with OV and ICB (alone or in combination), we captured the therapy-induced alterations within the tumor MHC-I peptidome, which were then tested for their CD8 T cell response-stimulating activity. We found that the oncolytic reovirus monotherapy drives up- as well as downexpression of tumor MHC-I peptides in a cancer type and oncolysis susceptibility dependent manner. Interestingly, the combination of reovirus + ICB results in higher numbers of differentially expressed MHC-I-associated peptides (DEMHCPs) relative to either monotherapies. Most importantly, OV+ICB-driven DEMHCPs contain biologically active epitopes that stimulate interferon-gamma responses in cognate CD8 T cells, which may mediate clinically desired antitumor attack and cancer immunoediting. These findings highlight that the therapy-induced changes to the MHC-I peptidome contribute toward the reinstated antitumor CD8 T cell attack established following OV + ICB combination cancer immunotherapy.     

A Systems Biology-Based Gene Expression Classifier of Glioblastoma Predicts Survival with Solid Tumors

Accurate prediction of survival of cancer patients is still a key open problem in clinical research. Recently, many large-scale gene expression clusterings have identified sets of genes reportedly predictive of prognosis; however, those gene sets shared few genes in common and were poorly validated using independent data. We have developed a systems biology-based approach by using either combined gene sets and the protein interaction network (Method A) or the protein network alone (Method B) to identify common prognostic genes based on microarray gene expression data of glioblastoma multiforme and compared with differential gene expression clustering (Method C). Validations of prediction performance show that the 23-prognostic gene classifier identified by Method A outperforms other gene classifiers identified by Methods B and C or previously reported for gliomas on 17 of 20 independent sample cohorts across five tumor types. We also find that among the 23 genes are 21 related to cellular proliferation and two related to response to stress/immune response. We further find that the increased expression of the 21 genes and the decreased expression of the other two genes are associated with poorer survival, which is supportive with the notion that cellular proliferation and immune response contribute to a significant portion of predictive power of prognostic classifiers. Our results demonstrate that the systems biology-based approach enables to identify common survival-associated genes.     

Mapping tumor-suppressor genes with multipoint statistics from copy-number-variation data

Array-based comparative genomic hybridization (arrayCGH) is a microarray-based comparative genomic hybridization technique that has been used to compare tumor genomes with normal genomes, thus providing rapid genomic assays of tumor genomes in terms of copy-number variations of those chromosomal segments that have been gained or lost. When properly interpreted, these assays are likely to shed important light on genes and mechanisms involved in the initiation and progression of cancer. Specifically, chromosomal segments, deleted in one or both copies of the diploid genomes of a group of patients with cancer, point to locations of tumor-suppressor genes (TSGs) implicated in the cancer. In this study, we focused on automatic methods for reliable detection of such genes and their locations, and we devised an efficient statistical algorithm to map TSGs, using a novel multipoint statistical score function. The proposed algorithm estimates the location of TSGs by analyzing segmental deletions (hemi- or homozygous) in the genomes of patients with cancer and the spatial relation of the deleted segments to any specific genomic interval. The algorithm assigns, to an interval of consecutive probes, a multipoint score that parsimoniously captures the underlying biology. It also computes a P value for every putative TSG by using concepts from the theory of scan statistics. Furthermore, it can identify smaller sets of predictive probes that can be used as biomarkers for diagnosis and therapeutics. We validated our method using different simulated artificial data sets and one real data set, and we report encouraging results. We discuss how, with suitable modifications to the underlying statistical model, this algorithm can be applied generally to a wider class of problems (e.g., detection of oncogenes).     

CD8+ cytotoxic T lymphocytes in cancer immunotherapy: A review

CD8⁺ cytotoxic T lymphocytes (CTLs) are preferred immune cells for targeting cancer. During cancer progression, CTLs encounter dysfunction and exhaustion due to immunerelated tolerance and immunosuppression within the tumor microenvironment (TME), with all favor adaptive immune-resistance. Cancer-associated fibroblasts (CAFs), macrophage type 2 (M2) cells, and regulatory T cells (Tregs) could make immunologic barriers against CD8 ⁺ T cell-mediated antitumor immune responses. Thus, CD8 ⁺ T cells are needed to be primed and activated toward effector CTLs in a process called tumor immunity cycle for making durable and efficient antitumor immune responses. The CD8 ⁺ T cell priming is directed essentially as a corroboration work between cells of innate immunity including dendritic cells (DCs) and natural killer (NK) cells with CD4 ⁺ T cells in adoptive immunity. Upon activation, effector CTLs infiltrate to the core or invading site of the tumor (so-called infiltrated–inflamed [I–I] TME) and take essential roles for killing cancer cells. Exogenous reactivation and/or priming of CD8 ⁺ T cells can be possible using rational immunotherapy strategies. The increase of the ratio for costimulatory to coinhibitory mediators using immune checkpoint blockade (ICB) approach. Programmed death-1 receptor (PD-1)–ligand (PD-L1) and CTL-associated antigen 4 (CTLA-4) are checkpoint receptors that can be targeted for relieving exhaustion of CD8 ⁺ T cells and renewing their priming, respectively, and thereby eliminating antigen-expressing cancer cells. Due to a diverse relation between CTLs with Tregs, the Treg activity could be dampened for increasing the number and rescuing the functional potential of CTLs to induce immunosensitivity of cancer cells.