Identification of immune microenvironment subtypes that predicted the prognosis of patients with ovarian cancer

Ovarian cancer (OC) is associated with high mortality rate. However, the correlation between immune microenvironment and prognosis of OC remains unclear. This study aimed to explore prognostic significance of OC tumour microenvironment. The OC data set was selected from the cancer genome atlas (TCGA), and 307 samples were collected. Hierarchical clustering was performed according to the expression of 756 genes. The immune and matrix scores of all immune subtypes were determined, and Kruskal-Wallis test was used to analyse the differences in the immune and matrix scores between OC samples with different immune subtypes. The model for predicting prognosis was constructed based on the expression of immune-related genes. TIDE platform was applied to predict the effect of immunotherapy on patients with OC of different immune subtypes. The 307 OC samples were classified into three immune subtypes A-C. Patients in subtype B had poorer prognosis and lower survival rate. The infiltration of helper T cells and macrophages in microenvironment indicated significant differences between immune subtypes. Enrichment analyses of immune cell molecular pathways showed that JAK–STAT3 pathway changed significantly in subtype B. Furthermore, predictive response to immunotherapy in subtype B was significantly higher than that in subtype A and C. Immune subtyping can be used as an independent predictor of the prognosis of OC patients, which may be related to the infiltration patterns of immune cells in tumour microenvironment. In addition, patients in immune subtype B have superior response to immunotherapy, suggesting that patients in subtype B are suitable for immunotherapy.     

Identification of m6A methyltransferase-related lncRNA signature for predicting immunotherapy and prognosis in patients with hepatocellular carcinoma

N6-methyladenosine (m6A) methyltransferase has been shown to be an oncogene in a variety of cancers. Nevertheless, the relationship between the long non-coding RNAs (lncRNAs) and hepatocellular carcinoma (HCC) remains elusive. We integrated the gene expression data of 371 HCC and 50 normal tissues from The Cancer Genome Atlas (TCGA) database. Differentially expressed protein-coding genes (DE-PCGs)/lncRNAs (DE-lncRs) analysis and univariate regression and Kaplan–Meier (K–M) analysis were performed to identify m6A methyltransferase-related lncRNAs. Three prognostic lncRNAs were selected by univariate and LASSO Cox regression analyses to construct the m6A methyltransferase-related lncRNA signature. Multivariate Cox regression analyses illustrated that this signature was an independent prognostic factor for overall survival (OS) prediction. The Gene Set Enrichment Analysis (GSEA) suggested that the m6A methyltransferase-related lncRNAs were involved in the immune-related biological processes (BPs) and pathways. Besides, we discovered that the lncRNAs signature was correlated with the tumor microenvironment (TME) and the expression of critical immune checkpoints. Tumor Immune Dysfunction and Exclusion (TIDE) analysis revealed that the lncRNAs could predict the clinical response to immunotherapy. Our study had originated a prognostic signature for HCC based on the potential prognostic m6A methyltransferase-related lncRNAs. The present study had deepened the understanding of the TME status of HCC patients and laid a theoretical foundation for the choice of immunotherapy.     

Pan-cancer analysis of N4-acetylcytidine adaptor THUMPD1 as a predictor for prognosis and immunotherapy

Background: THUMPD1 is a specific RNA adaptor that assists acetylation of mRNA and production of N4-acetylcytidine (ac4C). However, it remains unclear whether THUMPD1 plays a part in tumorigenesis and therapeutic efficacy. Here, we analyzed the expression profiles and prognostic value of THUMPD1 in pan-cancer and gained insights into the correlation between THUMPD1 expression level and immunotherapy efficacy.Methods: Gene expression pattern and its correlation with prognosis, immune cell infiltration in pan-cancer were obtained from Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA) databases, with Kaplan–Meier method and Spearman correlation analysis used. Western blotting and immunofluorescence on clinical samples were performed to validate our database-derived results. Correlation between THUMPD1 expression level and immunotherapy responses was also explored, based on clinical cohorts receiving programmed cell death protein 1 ligand (PD-L1) antibody therapy. Finally, gene set enrichment analysis (GSEA) was performed to show the possible tumorigenic mechanism.Results: THUMPD1 was highly expressed in most cancer types, and this elevated expression indicated poor or improved prognosis for different cancers. In kidney renal clear cell carcinoma (KIRC) and rectum adenocarcinoma (READ), patients with higher THUMPD1 expression exhibited a better prognosis, while liver hepatocellular carcinoma (LIHC) patients had worse prognosis. Besides, THUMPD1 was significantly associated with immune cell infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), immune checkpoints and neoantigen in many cancer types. Further, more clinical advantages and therapeutic responses were observed in patients with high THUMPD1 expression.Conclusions: THUMPD1 may serve as a novel predictor to evaluate cancer prognosis and immune therapy efficacy in diverse cancer types.     

Identification immunophenotyping of lung adenocarcinomas based on the tumor microenvironment

The tumor immune microenvironment is heterogeneous, and its impact on treatment responses is not well understood. It is still a challenge to analyze the interaction between malignant cells and the tumor microenvironment to apply suitable immunotherapy in lung adenocarcinoma. We performed the nonnegative matrix factorization method to 513 messenger RNA expression profiles of lung adenocarcinomas (LUADs) from The Cancer Genome Atlas (TCGA) to obtain an immune-related expression pattern. Subsequently, we characterized the immune-related gene signatures and clinical and survival characteristics. We used 576 patients from Gene Expression Omnibus to confirm our findings. Of the patients in the training cohort, 51% had a high immune enrichment score, high expression of immune cell signaling, cytolytic activity, and interferon (IFN)-related signatures (all P < .05). We denoted these as the Immune Class. We further subdivided the Immune Class into two subclasses based on the tumor microenvironment. These were denoted the Active Immune Class and Exhausted Immune Class. The former showed significant IFN, T-cells, M1 macrophage signatures, and better prognosis (all P < .05), while the latter presented an exhausted immune response with activated stromal enrichment, M2 macrophage signatures, and immunosuppressive factors such as WNT/transforming growth factor-β (all P < .05). Furthermore, we predicted the response of our immunophenotypes to immunological checkpoint inhibitors (P < .05). Our findings provide a novel insight into the immune-related state of LUAD and can identify the patients who will be receptive to suitable immunotherapeutic treatments.     

Identification of tumor antigens as potential target antigens for immunotherapy by serological expression cloning

The presence of tumor infiltrating T cells has been shown to be associated with a favorable prognosis in different tumor types. Several strategies have been developed to identify relevant tumor antigens which can be used for active immunotherapy strategies. The SEREX technique (serological analysis of cDNA expression libraries) identifies tumor antigens based on a spontaneous humoral immune response in cancer patients. This technique is not limited to tumor types that can be grown in cell culture or depends on established T cell clones recognizing the autologous tumor. Several steps of analysis are mandatory to evaluate SEREX-defined antigens before they become new target antigens for active immunotherapy: expression analysis; serological analysis with sera from tumor patients and normal individuals; identification of potential peptide epitopes for CD8 T cells and evaluation in T cell assays. This article summarizes our approach of antigen identification and evaluation giving the example of the recently cloned breast cancer antigen NY-BR-1.This work was presented at the first Cancer Immunology and Immunotherapy Summer School, 8–13 September 2003, Ionian Village, Bartholomeio, Peloponnese, Greece.     

肿瘤浸润淋巴细胞在实体肿瘤中作用的研究进展

肿瘤是21世纪威胁人类健康的主要疾患之一。临床上,实体瘤治疗仍以手术切除、放化疗和靶向治疗为主,但这些方法往往不能根除肿瘤病灶,易导致肿瘤复发和进展。肿瘤免疫治疗是利用人体的免疫系统,通过增强或恢复抗肿瘤免疫力实现控制和杀伤肿瘤的一种新的治疗模式。肿瘤免疫治疗能够在众多患者中产生持久反应,过继性免疫治疗和免疫检查点阻断剂治疗均可产生显著的抗原特异性免疫反应。肿瘤浸润淋巴细胞(TILs)是一种存在于肿瘤组织内部具有高度异质性的淋巴细胞,在宿主抗原特异性肿瘤免疫应答中发挥关键作用。最新研究表明,在肿瘤发生和治疗过程中,TILs的亚群组成和数量与患者预后密切相关;抗肿瘤的TILs介导的过继性免疫治疗方法已在多种实体瘤中取得了良好的疗效。文中就实体肿瘤中TILs的研究进展作一综述。     

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.     

Identification of microenvironment-related genes with prognostic value in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney tumor. Previous studies have shown that the interaction between tumor cells and microenvironment has an important impact on prognosis. Immune and stromal cells are two vital components of the tumor microenvironment. Our study aimed to better understand and explore the genes involved in immune/stromal cells on prognosis. We used the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm to calculate immune/stromal scores. According to the scores, we divided ccRCC patients from The Cancer Genome Atlas database into low and high groups and identified the genes which were differentially expressed and significantly associated with prognosis. The result of functional enrichment analysis and protein-protein interaction networks indicated that these genes mainly were involved in extracellular matrix and regulation of cellular activities. Then another independent cohort from the International Cancer Genome Consortium database was used to validate these genes. Finally, we acquired a list of microenvironment-related genes that can predict prognosis for ccRCC patients.     

Profiles of immune-related genes and immune cell infiltration in the tumor microenvironment of diffuse lower-grade gliomas

The tumor microenvironment is highly correlated with tumor occurrence, progress, and prognosis. We aimed to investigate the immune-related gene (IRG) expression and immune infiltration pattern in the tumor microenvironment of lower-grade glioma (LGG). We employed the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm to calculate immune and stromal scores and identify prognostic IRG based on The Cancer Genome Atlas data set. The potential molecular functions of these genes were explored with the help of functional enrichment analysis and the protein–protein interaction network. Remarkably, three cohorts that were downloaded from the Chinese Glioma Genome Atlas database were analyzed to further verify the prognostic values of these genes. Moreover, the Tumor IMmune Estimation Resource (TIMER) algorithm was used to estimate the abundance of infiltrating immune cells and explore the immune infiltration pattern in LGG. And unsupervised cluster analysis determined three clusters of the immune infiltration pattern and indicated that CD8⁺ T cells and macrophages were significantly associated with LGG outcomes. Altogether, our study identified a list of prognostic IRGs and provided a perspective to explore the immune infiltration pattern in LGG.     

Immune modulation by melanoma and ovarian tumor cells through expression of the immunosuppressive molecule CD200

Background and Objective Immune escape by tumors can occur by multiple mechanisms, each a significant barrier to immunotherapy. We previously demonstrated that upregulation of the immunosuppressive molecule CD200 on chronic lymphocytic leukemia cells inhibits Th1 cytokine production required for an effective cytotoxic T cell response. CD200 expression on human tumor cells in animal models prevents human lymphocytes from rejecting the tumor; treatment with an antagonistic anti-CD200 antibody restored lymphocyte-mediated tumor growth inhibition. The current study evaluated CD200 expression on solid cancers, and its effect on immune response in vitro. Methods and Results CD200 protein was expressed on the surface of 5/8 ovarian cancer, 2/4 melanoma, 2/2 neuroblastoma and 2/3 renal carcinoma cell lines tested, but CD200 was absent on prostate, lung, breast, astrocytoma, or glioblastoma cell lines. Evaluation of patient samples by immunohistochemistry showed strong, membrane-associated CD200 staining on malignant cells of melanoma (4/4), ovarian cancer (3/3) and clear cell renal cell carcinoma (ccRCC) (2/3), but also on normal ovary and kidney. CD200 expression on melanoma metastases was determined by RT-QPCR, and was found to be significantly higher in jejunum metastases (2/2) and lung metastases (2/6) than in normal samples. Addition of CD200-expressing, but not CD200-negative solid tumor cell lines to mixed lymphocyte reactions downregulated the production of Th1 cytokines. Inclusion of antagonistic anti-CD200 antibody restored Th1 cytokine responses. Conclusion These data suggest that melanoma, ccRCC and ovarian tumor cells can express CD200, thereby potentially suppressing anti-tumor immune responses. CD200 blockade with an antagonistic antibody may permit an effective anti-tumor immune response in these solid tumor types.     

Intravenous injection of the oncolytic virus M1 awakens antitumor T cells and overcomes resistance to checkpoint blockade

Reversing the highly immunosuppressive tumor microenvironment (TME) is essential to achieve long-term efficacy with cancer immunotherapy. Despite the impressive clinical response to checkpoint blockade in multiple types of cancer, only a minority of patients benefit from this approach. Here, we report that the oncolytic virus M1 induces immunogenic tumor cell death and subsequently restores the ability of dendritic cells to prime antitumor T cells. Intravenous injection of M1 disrupts immune tolerance in the privileged TME, reprogramming immune-silent (cold) tumors into immune-inflamed (hot) tumors. M1 elicits potent CD8⁺ T cell-dependent therapeutic effects and establishes long-term antitumor immune memory in poorly immunogenic tumor models. Pretreatment with M1 sensitizes refractory tumors to subsequent checkpoint blockade by boosting T-cell recruitment and upregulating the expression of PD-L1. These findings reveal the antitumor immunological mechanism of the M1 virus and indicated that oncolytic viruses are ideal cotreatments for checkpoint blockade immunotherapy.Subject terms: Cancer microenvironment, Targeted therapies     

microRNA在实体肿瘤免疫反应中的调节作用

免疫反应的作用逐渐成为调节各种复杂癌症的关键因素。免疫治疗也逐渐成为癌症肿瘤的有效干预方式。肿瘤微环境包含不同类型的免疫细胞,这有助于调节抗肿瘤信号中先天性和适应性免疫系统之间的细微平衡。在这种环境下,肿瘤细胞与免疫细胞之间相互关联的机制有待广泛阐明,但目前已被证明,多种microRNA在实体肿瘤相关免疫细胞的发育和功能中起调控作用,其通过肿瘤及免疫细胞介导免疫抑制或免疫刺激因子分泌增强或抑制免疫应答,靶向调控肿瘤发生的相关免疫途径,从而在癌症起始、转移进展的所有阶段中起关键作用,近而在肿瘤免疫治疗中寻找新的治疗靶点。本文针对microRNA在肿瘤免疫反应中的相关调节进行综述。     

Integrated pathological analysis to develop a Gal-9 based immune survival stratification to predict the outcome of lung large cell neuroendocrine carcinoma and its usefulness in immunotherapy

This study aimed to integrate the cell spatial organization to develop a Gal-9-based immune survival stratification in the lung large cell neuroendocrine carcinoma (LCNEC) and investigate its potentials to immunotherapy.The expression of Gal-9 and other twelve immune markers were evaluated in 122 cases of surgical LCNEC samples from our center using immunohistochemistry. The Gal-9-based immune survival stratification risk score was constructed and its predictive performance was evaluated. Then, we thoroughly explored the effects of Gal-9 and immune risk score on LCNEC immune pathways, immune micro-environment and immunotherapy sensitivity in different cohort and platform, and made a validation in pathology images using Histology-based Digital-Staining (HDS).In 122 LCNEC samples, 43 cases were positive Gal-9 expression on tumor cells (Gal-9 TC). Increased Gal-9 TC predicted worse overall survival. Gal-9''s interaction with other immune markers added to the immune suppression and immune tolerance in LCNEC. Immune protein marker-based risk score consisting of Gal-9, CD3, CD4, PD-L1, and PD-1 was developed and validated to robustly discriminate survival high-risk or low-risk in LCNEC patients. The high-risk group characterized by immune-desert tumor had less various T cells. The low-risk group featuring immune-inflamed tumor was more likely to respond to anti-PD1 immunotherapy. HDS in 122 LCNEC samples'' 108,369 cells validated that the high-risk group had more tumor cells, less stromal cells, less lymphocytes, higher tumor cell nucleic solidity and lower stromal cells nucleic solidity.An integrated pathological analysis confirms the Gal-9 based immune survival stratification is distinctively related to micro-environment status involved in immune suppression and immune tolerance and could act as a combinatorial biomarker to predict the outcome of LCNEC. These findings may help effectively stratify LCNEC patients sensitive to immunotherapy.     

PRF1 is a prognostic marker and correlated with immune infiltration in head and neck squamous cell carcinoma

PurposeHead and neck squamous cell carcinoma (HNSCC) is a highly invasive malignancy with poor survival. Perforin (PRF1) plays essential roles in host immunity. Our research intended to identify the correlations of PRF1 with clinical prognosis and tumor immune infiltration in HNSCC.MethodsWe explored PRF1 expression and its associations with the clinical features of HNSCC via the Tumor Immune Estimation Resource (TIMER), Oncomine and The Cancer Genome Atlas (TCGA) databases. The prognostic value of PRF1 for HNSCC was further explored by Kaplan–Meier plotter and TIMER. Finally, the relation between PRF1 and immune infiltration in HNSCC was estimated via CIBERSORT and TIMER.ResultsPRF1 expression was remarkably elevated in HNSCC and associated with clinical stage and HPV infection. High PRF1 expression predicted favorable outcomes in HNSCC, especially in HPV+ HNSCC. Moreover, higher infiltration of CD8+ T cells and CD4+ T cells were found in the PRF1^high group of HNSCC. PRF1 expression in HNSCC was strongly correlated with infiltrating CD8+ T cells and dendritic cells (DCs), with higher relevance in HPV+ HNSCC.ConclusionOur findings suggested that PRF1 could be a novel prognostic biomarker in HNSCC and that its expression was related to immune cell infiltration, which was impacted by HPV status.Key words: PRF1, prognosis, head and neck squamous cell carcinoma, tumor immune infiltration, HPV     

Proceedings of the 2016 China Cancer Immunotherapy Workshop

A1 Proceedings of 2016 China Cancer Immunotherapy Workshop, Beijing, China Bin Xue, Jiaqi Xu, Wenru Song, Zhimin Yang, Ke Liu, Zihai Li A2 Set the stage: fundamental immunology in forty minutes Zihai Li A3 What have we learnt from the anti-PD-1/PD-L1 therapy of advanced human cancer? Lieping Chen A4 Immune checkpoint inhibitors in lung cancer Edward B. Garon A5 Mechanisms of response and resistance to checkpoint inhibitors in melanoma Siwen Hu-Lieskovan A6 Checkpoint inhibitor immunotherapy in lymphoid malignancies Wei Ding A7 Translational research to improve the efficacy of immunotherapy in genitourinary malignancies Chong-Xian Pan A8 Immune checkpoint inhibitors in gastrointestinal malignancies Weijing Sun A9 What’s next beyond PD-1/PDL1? Yong-Jun Liu A10 Cancer vaccines: new insights into the oldest immunotherapy strategy Lei Zheng A11 Bispecific antibodies for cancer immunotherapy Delong Liu A12 Updates on CAR-T immunotherapy Michel Sadelain A13 Adoptive T cell therapy: personalizing cancer treatment Cassian Yee A14 Immune targets and neoantigens for cancer immunotherapy Rongfu Wang A15 Phase I/IIa trial of chimeric antigen receptor modified T cells against CD133 in patients with advanced and metastatic solid tumors Meixia Chen, Yao Wang, Zhiqiang Wu, Hanren Dai, Can Luo, Yang Liu, Chuan Tong, Yelei Guo, Qingming Yang, Weidong Han A16 Cancer immunotherapy biomarkers: progress and issues Lisa H. Butterfield A17 Shaping of immunotherapy response by cancer genomes Timothy A. Chan A18 Unique development consideration for cancer immunotherapy Wenru Song A19 Immunotherapy combination Ruirong Yuan A20 Immunotherapy combination with radiotherapy Bo Lu A21 Cancer immunotherapy: past, present and future Ke Liu A22 Breakthrough therapy designation drug development and approval Max Ning A23 Current European regulation of innovative oncology medicines: opportunities for immunotherapy Harald Enzmann, Heinz Zwierzina     

Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients

Immunotherapy has made great progress in hepatocellular carcinoma (HCC), yet there is still a lack of biomarkers for predicting response to it. Cancer stem cells (CSCs) are the primary cause of the tumorigenesis, metastasis, and multi-drug resistance of HCC. This study aimed to propose a novel CSCs-related cluster of HCC to predict patients'' response to immunotherapy. Based on RNA-seq datasets from The Cancer Genome Atlas (TCGA) and Progenitor Cell Biology Consortium (PCBC), one-class logistic regression (OCLR) algorithm was applied to compute the stemness index (mRNAsi) of HCC patients. Unsupervised consensus clustering was performed to categorize HCC patients into two stemness subtypes which further proved to be a predictor of tumor immune microenvironment (TIME) status, immunogenomic expressions and sensitivity to neoadjuvant therapies. Finally, four machine learning algorithms (LASSO, RF, SVM-RFE and XGboost) were applied to distinguish different stemness subtypes. Thus, a five-hub-gene based classifier was constructed in TCGA and ICGC HCC datasets to predict patients'' stemness subtype in a more convenient and applicable way, and this novel stemness-based classification system could facilitate the prognostic prediction and guide clinical strategies of immunotherapy and targeted therapy in HCC.     

A robust immune-related lncRNA signature for the prognosis of human colorectal cancer

Background: Colorectal cancer (CRC) is one of the most prevalent malignant cancers worldwide. Immune-related long non-coding RNAs (IRlncRNAs) are proved to be essential in the development and progression of carcinoma. The purpose of the present study was to develop and validate a prognostic IRlncRNA signature for CRC patients.Methods: Gene expression profiles of CRC samples were downloaded from The Cancer Genome Atlas (TCGA) database. Immune-related genes were obtained from the ImmPort database and were used to identify IRlncRNA by correlation analysis. Through LASSO Cox regression analyses, a prognostic signature was constructed. Functional enrichment analysis was performed by gene set enrichment analysis (GSEA). TIMER2.0 web server and tumor immune dysfunction and exclusion (TIDE) algorithm were employed to analyze the association between our model and tumor-infiltrating immune cells and immunotherapy response. The expression levels of IRlncRNAs in cell lines were detected by quantitative real-time PCR (qPCR).Results: A 9-IRlncRNA signature was developed by a LASSO Cox proportional regression model. Based on the signature, CRC patients were divided into high- and low-risk groups with different prognoses. GSEA results indicated that patients in high-risk group were associated with cancer-related pathways. In addition, patients in low-risk group were found to have more infiltration of anti-tumor immune cells and might show a favorable response to immunotherapy. Finally, the result of qPCR revealed that most IRlncRNAs were differently expressed between normal and tumor cell lines.Conclusion: The constructed 9-IRlncRNA signature has potential to predict the prognosis of CRC patients and may be helpful to guide personalized immunotherapy.     

Regressing and progressing metastatic lesions: resistance to immunotherapy is predetermined by irreversible HLA class I antigen alterations

Despite the significant efforts to enhance immune reactivity against malignancies the clinical effect of anti-tumor vaccines and cancer immunotherapy is still below expectations. Understanding of the possible causes of such poor clinical outcome has become very important for improvement of the existing cancer treatment modalities. In particular, the critical role of HLA class I antigens in the success of T cell based immunotherapy has led to a growing interest in investigating the expression and function of these molecules in metastatic cancer progression and, especially in response to immunotherapy. In this report, we illustrate that two types of metastatic lesions are commonly generated in response to immunotherapy according to the pattern of HLA class I expression. We found that metastatic lesions, that progress after immunotherapy have low level of HLA class I antigens, while the regressing lesions demonstrate significant upregulation of these molecules. Presumably, immunotherapy changes tumor microenvironment and creates an additional immune selection pressure on tumor cells. As a result, two subtypes of metastatic lesions arise from pre-existing malignant cells: (a) regressors, with upregulated HLA class I expression after therapy, and (b) progressors with resistance to immunotherapy and with low level of HLA class I. Tumor cells with reversible defects (soft lesions) respond to therapy by upregulation of HLA class I expression and regress, while tumor cells with structural irreversible defects (hard lesions) demonstrate resistance to immunostimulation, fail to upregulate HLA class I antigens and eventually progress. These two types of metastases appear independently of type of the immunotherapy used, either non-specific immunomodulators (cytokines or BCG) or autologous tumor vaccination. Similarly, we also detected two types of metastatic colonies in a mouse fibrosarcoma model after in vitro treatment with IFN-gamma. One type of metastases characterized by upregulation of all MHC class I antigens and another type with partial IFN-gamma resistance, namely with lack of expression of L(d)-MHC class I molecule. Our observations may shed new light on the understanding of the mechanisms of tumor escape and might have implications for improvement of the efficacy of cancer immunotherapy.