scholarly journals Adjuvant Autologous Melanoma Vaccine for Macroscopic Stage III Disease: Survival, Biomarkers, and Improved Response to CTLA-4 Blockade

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Michal Lotem ◽  
Sharon Merims ◽  
Stephen Frank ◽  
Tamar Hamburger ◽  
Aviram Nissan ◽  
...  

Background. There is not yet an agreed adjuvant treatment for melanoma patients with American Joint Committee on Cancer stages III B and C. We report administration of an autologous melanoma vaccine to prevent disease recurrence.Patients and Methods. 126 patients received eight doses of irradiated autologous melanoma cells conjugated to dinitrophenyl and mixed with BCG. Delayed type hypersensitivity (DTH) response to unmodified melanoma cells was determined on the vaccine days 5 and 8. Gene expression analysis was performed on 35 tumors from patients with good or poor survival.Results. Median overall survival was 88 months with a 5-year survival of 54%. Patients attaining a strong DTH response had a significantly better (p=0.0001) 5-year overall survival of 75% compared with 44% in patients without a strong response. Gene expression array linked a 50-gene signature to prognosis, including a cluster of four cancer testis antigens: CTAG2 (NY-ESO-2), MAGEA1, SSX1, and SSX4. Thirty-five patients, who received an autologous vaccine, followed by ipilimumab for progressive disease, had a significantly improved 3-year survival of 46% compared with 19% in nonvaccinated patients treated with ipilimumab alone (p=0.007).Conclusion. Improved survival in patients attaining a strong DTH and increased response rate with subsequent ipilimumab suggests that the autologous vaccine confers protective immunity.

2021 ◽  
Vol 22 (14) ◽  
pp. 7511
Author(s):  
Albina Fejza ◽  
Maurizio Polano ◽  
Lucrezia Camicia ◽  
Evelina Poletto ◽  
Greta Carobolante ◽  
...  

The use of immune checkpoint inhibitors has revolutionized the treatment of melanoma patients, leading to remarkable improvements in the cure. However, to ensure a safe and effective treatment, there is the need to develop markers to identify the patients that would most likely respond to the therapies. The microenvironment is gaining attention in this context, since it can regulate both the immunotherapy efficacyand angiogenesis, which is known to be affected by treatment. Here, we investigated the putative role of the ECM molecule EMILIN-2, a tumor suppressive and pro-angiogenic molecule. We verified that the EMILIN2 expression is variable among melanoma patients and is associated with the response to PD-L1 inhibitors. Consistently, in preclinical settings,the absence of EMILIN-2 is associated with higher PD-L1 expression and increased immunotherapy efficacy. We verified that EMILIN-2 modulates PD-L1 expression in melanoma cells through indirect immune-dependent mechanisms. Notably, upon PD-L1 blockage, Emilin2−/− mice displayed improved intra-tumoral vessel normalization and decreased tumor hypoxia. Finally, we provide evidence indicating that the inclusion of EMILIN2 in a number of gene expression signatures improves their predictive potential, a further indication that the analysis of this molecule may be key for the development of new markers to predict immunotherapy efficacy.


2004 ◽  
Vol 22 (13) ◽  
pp. 2671-2680 ◽  
Author(s):  
Hiroya Takeuchi ◽  
Donald L. Morton ◽  
Christine Kuo ◽  
Roderick R. Turner ◽  
David Elashoff ◽  
...  

PurposeDetection of micrometastases in sentinel lymph nodes (SLNs) is important for accurate staging and prognosis in melanoma patients. However, a significant number of patients with histopathology-negative SLNs subsequently develop recurrent disease. We hypothesized that a quantitative realtime reverse transcriptase polymerase chain reaction (qRT) assay using multiple specific mRNA markers could detect occult metastasis in paraffin-embedded (PE) SLNs to upstage and predict disease outcome.Patients and MethodsqRT was performed on retrospectively collected PE SLNs from 215 clinically node-negative patients who underwent lymphatic mapping and sentinel lymphadenectomy for melanoma and were followed up for at least 8 years. PE SLNs (n = 308) from these patients were sectioned and assessed by qRT for mRNA of four melanoma-associated genes: MART-1 (antigen recognized by T cells-1), MAGE-A3 (melanoma antigen gene-A3 family), GalNAc-T (β1→4-N-acetylgalactosaminyl-transferase), and Pax3 (paired-box homeotic gene transcription factor 3).ResultsFifty-three (25%) patients had histopathology-positive SLNs by hemotoxylin and eosin and/or immunohistochemistry. Of the 162 patients with histopathology-negative SLNs, 48 (30%) had nodes that expressed at least one of the four qRT markers, and these 48 patients also had a significantly increased risk of disease recurrence by a Cox proportional hazards model analysis (P < .0001; risk ratio, 7.48; 95% CI, 3.70 to 15.15). The presence of ≥ one marker in histopathology-negative SLNs was also a significant independent prognostic factor by multivariate analysis for overall survival (P = .0002; risk ratio, 11.42; 95% CI, 3.17 to 41.1).ConclusionMolecular upstaging of PE histopathology-negative SLNs by multiple-marker qRT assay is a significant independent prognostic factor for long-term disease recurrence and overall survival of patients with early-stage melanoma.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18033-e18033
Author(s):  
Jun Chen ◽  
Bei Zhang

e18033 Background: Genomic expression profiles have enabled the classification of head and neck squamous cell carcinoma (HNSCC) into molecular sub-types and provide prognostic information, which have implications for the personalized treatment of HNSCC beyond clinical and pathological features. Methods: Gene-expression profiling was identified in TCGA- HNSCC (n = 492) and validated with the Gene Expression Ominibus (GEO) dataset(n = 270) for which RNA sequencing data and clinical covariates were available. A single-sample gene set enrichment analysis (ssGSEA) algorithm were used to quantified the levels of various hallmarks of cancer. And LASSO Cox regression model was used to screen robust prognostic biomarkers to identify the best set of survival-associated gene signatures in HNSCC. Statistical analyses were performed using R version 3.4.4. Results: We identified unfolded protein response as the primary risk factor for survival(cox coefficient = 17.4 [8.4-26.3], P < 0.001)among various hallmarks of cancer in TCGA- HNSCC. And unfolded protein response ssGESA scores were significantly elevated in patients who died during follow up (P = 0.009). Kaplan-Meier analysis showed that patients with low ssGSEA scores of unfolded protein response exhibited better OS (HR = 0.69, P = 0.008). And we established an unfolded protein response-related gene signature based on lasso cox. We then apply the unfolded protein response -related gene signature to classify patients into the high risk group and the low risk group with the cutoff of 0.18. Adjusted for stage,age,gender, our signature was an independent risk factor for overall survival in TCGA cohorts (HR = 0.39 [0.28-0.53],P = < 0.001). In external independent cohorts, similar results were observed. In the validation cohort GEO65858, the patients with high unfolded protein response score showed longer survival (HR = 0.62 [0.38-1.0], P = 0.049). And adjusted for stage,age,HPV state, the multivariate cox regression analysis showed that unfolded protein response-related gene signature exhibited an independent risk prediction for overall survival in 270 patients with HNSCC (HR = 0.57 [0.35-0.94], P = 0.026). Conclusions: By analyzing the gene-expression data with bioinformation approach, we developed and validated a risk prediction model with unfolded protein response -related expression scores in HNSCC, which have the potential to identify patients who could have better overall survival.


2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Jun Liu ◽  
Jianjun Lu ◽  
Zhanzhong Ma ◽  
Wenli Li

Background. Hepatocellular carcinoma (HCC) is a common cancer with an extremely high mortality rate. Therefore, there is an urgent need in screening key biomarkers of HCC to predict the prognosis and develop more individual treatments. Recently, AATF is reported to be an important factor contributing to HCC. Methods. We aimed to establish a gene signature to predict overall survival of HCC patients. Firstly, we examined the expression level of AATF in the Gene Expression Omnibus (GEO), the Cancer Genome Atlas (TCGA), and the International Union of Cancer Genome (ICGC) databases. Genes coexpressed with AATF were identified in the TCGA dataset by the Poisson correlation coefficient and used to establish a gene signature for survival prediction. The prognostic significance of this gene signature was then validated in the ICGC dataset and used to build a combined prognostic model for clinical practice. Results. Gene expression data and clinical information of 2521 HCC patients were downloaded from three public databases. AATF expression in HCC tissue was higher than that in matched normal liver tissues. 644 genes coexpressed with AATF were identified by the Poisson correlation coefficient and used to establish a three-gene signature (KIF20A, UCK2, and SLC41A3) by the univariate and multivariate least absolute shrinkage and selection operator Cox regression analyses. This three-gene signature was then used to build a combined nomogram for clinical practice. Conclusion. This integrated nomogram based on the three-gene signature can predict overall survival for HCC patients well. The three-gene signature may be a potential therapeutic target in HCC.


2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 10583-10583
Author(s):  
N. Van Zandwijk

10583 Background: Current staging methods are imprecise for predicting the outcome of treatment of non-small-cell lung cancer (NSCLC). We have developed a 28-gene signature that is closely associated with recurrence-free and overall survival. Methods: We used whole-genome gene expression microarrays to analyze frozen-tumor samples from 174 patients (pT1&2, N0&1, MO), who had undergone complete surgical resection in 5 European institutions. Randomly generated numbers were used to assign 2/3 of the samples to an algorithm training group with the remaining 1/3 set aside for independent validation. Cox proportional hazards models were used to evaluate the association between the level of expression and patient survival. We used risk scores and nearest centroid analysis to develop a gene-expression model for the prediction of treatment outcome. Leave-one-out cross validation was used to prevent model over-training. Results: 28 genes that correlated with survival were identified by analyzing microarray data and risk scores. Based on the expression of these genes, patients in training and validation groups were classified as either high (48%) or low (52%) risk. Analysis of predicted risk groups revealed significantly different survival distributions for patients in both the training set (p<0.001) and independent validation set (p=0.006). Genes in our prognostic signature encode for several membrane-bound proteins with previously demonstrated involvement in cell cycle regulation and cell proliferation processes. Conclusions: Our 28-gene signature is closely associated with time to recurrence and overall survival of completely-resected NSCLC patients. [Table: see text]


2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e21045-e21045
Author(s):  
Emma O'Connor ◽  
Eileen E. Parkes ◽  
Leeona Galligan ◽  
James Bradford ◽  
Shauna Lambe ◽  
...  

e21045 Background: Traditionally gene expression signatures (GES) are used individually to classify patients into subgroups. Signatures targeting the same biology are often developed independently and may not classify identically. We developed the claraT software tool that uses consensus between multiple published GES categorised by the Hallmarks of Cancer (Hanahan & Weinberg, 2011) to classify cancers. As metastatic melanoma represents poor prognostic disease (5-yr survival 15-20%), we applied claraT to the TCGA melanoma dataset to identify targetable biologies, validated in a cohort of melanoma patients treated with Ipilimumab. Methods: TCGA RNA-seq data ( n= 472) was analysed using the claraT platform including GES for immune ( n= 14), angiogenesis ( n= 9) and epithelial-mesenchymal transition (EMT) ( n= 12) Hallmarks. Samples were clustered for the combined and individual Hallmarks. Median progression-free (PFS) and overall-survival (OS) differences were analysed across identified subgroups. Analysis was validated in an Ipilimumab treated melanoma dataset ( n= 42) (Van Allen, 2015). Results: Clustering the combined Hallmarks identified 4 subgroups in the TCGA cohort: 1) Immune active, 2) Immune-EMT active, 3) EMT-Angiogenesis active, 4) All inactive. Groups 1&2 had significantly improved OS compared to Groups 3&4 (HR = 0.50, p< 0.0001). Clustering using single Hallmarks revealed that immune-positive tumours had significantly improved OS (HR = 0.53, p< 0.0001) compared to immune-negative tumours. Angiogenesis-negative tumours displayed improved PFS (HR = 0.73, p= 0.03) and OS (HR = 0.53, p <0.0001) compared to angiogenesis-negative tumours. Interestingly the EMT Hallmark was not found to be individually prognostic. When validated in the Ipilimumab treated dataset, patients classified as immune-positive had improved OS (HR = 0.357, p= 0.010) when compared to immune-negative. Similar trends were also observed for angiogenesis and EMT Hallmarks. Conclusions: This study demonstrates how simultaneous analysis of multiple GES ( n= 35 in this study) can identify robust biologies through consensus expression. This platform may have value in the identification of reliable biomarkers for clinical trials and could inform how combination therapies targeting key biologies may be used in cancer treatment.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 5193-5193
Author(s):  
Simone Ragaini ◽  
Sarah Wagner ◽  
Giovanni Marconi ◽  
Sarah Parisi ◽  
Chiara Sartor ◽  
...  

Introduction: ELN intermediate-risk AML poses considerable challenges to clinicians both in terms of accurate prognostication and optimal treatment. Indoleamine 2,3-dioxygenase 1 (IDO1) plays a central role as a mediator of immune tolerance in AML through the increase of Treg cells. IDO1 activity is negatively regulated by the BIN1 proto-oncogene. Herein, we analyzed the correlation between BIN1 and IDO1 expression in AML, also focusing on IDO1-interacting genes, with the aim to identify a predictive gene signature for OS. Methods: Biological and clinical data of 732 patients with de novo AML were retrieved from public TCGA and HOVON datasets. Since details on chemotherapy regimens were not available in the HOVON dataset, we decided to exclude patients >= 65 years from survival analyses. IDO1-interacting genes were selected through a co-expression analysis performed on TCGA RNA-sequencing data accessed through cBioPortal. The best genes combination predicting overall survival was plotted in a gene expression score. Patients were split in three different groups using score quartiles as cut-off. Results: In the HOVON dataset, IDO1 and BIN1 mRNA expression were negatively correlated (r = -0.40, P<0.0001). Our analysis of TCGA data identified PLXNC1 as an IDO1-interacting gene and a predictor of patient survival (median split of mRNA expression, P<0.001, survival analysis performed on the BloodSpot online portal). The correlation between PLXNC1 and IDO1 was validated in the HOVON dataset (r=-0.24, P<0.0001). PLXNC1 expression was combined with IDO1 and BIN1 expression to obtain the gene expression score. The 3-gene score predicted survival in ELN intermediate-risk patients who did not receive allogeneic HSCT both in the HOVON dataset (P<0.0001) and the TCGA dataset (P<0.05). In particular, the highest score values predicted the shortest OS. Conclusions: Our study shows a negative correlation between IDO1 and BIN1 in AML, suggesting IDO1 inhibition by BIN1, and identifies for the first time PLXNC1, a receptor for semaphorines, as an IDO1-interacting gene potentially implicated in immune response regulation. This finding corroborates the role of IDO1 and its interacting genes in the promotion of a tolerogenic microenvironment in AML. Lastly, our gene expression score predicted OS in intermediate-risk AML patients not undergoing HSCT, a finding which has clinical implications for accurate patient stratification and for clinical decision making, i.e., bridging these patients to transplant. Figure Disclosures Papayannidis: Pfizer: Honoraria; Amgen: Honoraria; Incyte: Honoraria; Novartis: Honoraria; Shire: Honoraria; Teva: Honoraria. Cavo:celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria; takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Rutella:MacroGenics, Inc.: Research Funding; NanoString Technologies, Inc.: Research Funding; Kura Oncology: Research Funding.


2019 ◽  
Author(s):  
Megan L. Insco ◽  
Brian J. Abraham ◽  
Sara J. Dubbury ◽  
Sofia Dust ◽  
Constance Wu ◽  
...  

AbstractTranscriptional Cyclin Dependent Kinases modulate RNA Polymerase II function to impact gene expression. Here, we show that CDK13 is mutated in 4% of patient melanomas and mutation or downregulation is associated with poor overall survival. Mutant CDK13 lacks kinase activity and overexpression in zebrafish leads to accelerated melanoma. CDK13 mutant fish and human melanomas accumulate prematurely terminated RNAs that are translated into truncated proteins. CDK13 binds to and regulates the phosphorylation of ZC3H14, a member of the PolyA eXosome Targeting (PAXT) RNA degradation complex. ZC3H14 phosphorylation recruits the PAXT complex to degrade prematurely terminated polyadenylated transcripts in the nucleus. In the presence of mutant CDK13, ZC3H14 phosphorylation is compromised and consequently fails to recruit the PAXT complex, leading to truncated transcript stabilization. This work establishes a role for CDK13 and the PAXT nuclear RNA degradation complex in cancer and has prognostic significance for melanoma patients with mutated or downregulated CDK13.


Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 3507-3507 ◽  
Author(s):  
Vivian G. Oehler ◽  
KaYee Yeung ◽  
Ailin Zhang ◽  
Theodore A. Gooley ◽  
Jerald P. Radich

Abstract Abstract 3507 Disease phase, transplant donor type, donor recipient match, age, and interval from diagnosis to transplantation (the EBMT risk score) are recognized variables that affect transplant outcomes for chronic myeloid leukemia (CML), but do not entirely account for the heterogeneity in outcomes. We have previously applied a probabilistic method to a large CML microarray gene expression dataset, and found a 6-gene signature of disease phase that discriminated between early and late chronic phase (CP). The combined expression of all 6 genes could be represented as a probability score where values closer to 0 are more similar to CP and values closer to 1 are more similar to blast crisis (BC). Moreover, in 17 accelerated phase (AP) CML patients, the 6-gene probability score was associated with outcomes after transplantation. We thus hypothesized that genes predictive of CML progression could be used to predict outcomes after transplantation regardless of disease phase. We derived 6 additional models (i.e. gene sets) from our CML microarray data, each consisting of 6–10 genes (total of 35 genes), that are also highly predictive of CML progression. These gene sets were derived using a novel network-driven approach aimed to identify genes that are functionally related to genes in pathways that are known to be associated with CML. We then examined expression of the genes in these models using quantitative PCR in bone marrow samples from 213 patients (176 CP, 23 AP, and 14 BC remission patients) prior to myeloablative allogeneic transplantation. GUSB was used as an endogenous control to correct for RNA integrity. Transplants occurred between 1993 and 2007 and a majority of patients did not receive prior tyrosine kinase inhibitor therapy. For CP patients, gene expression for all genes and models was independent of white blood cell and blast count. Among 176 CP CML patients, 45 patients died and 24 patients relapsed by last contact, leading to 1-year and 5-year estimates of overall survival of 85% and 78%, respectively, and 1-year and 5-year estimates of relapse of 7% and 12%, respectively. In CP patients we found not only that the expression of the original six-gene model (NOB1, DDX47, CD101, LTB4R, SCARB1, SLC25A3) was associated with a trend towards increased relapse, but that another model (RALGDS, LASP1, G6PD, ADRBKI, LRPPRC, PSMA1) was statistically significantly associated with an increased risk of relapse. In CP patients we found that an increase of 0.2 in the 6-gene probability score correlated with an increase in relapse of 46% (HR=1.46 (1.06-2.02, p=.02)) after adjustment for EBMT risk score (Figure 1a). Lastly, we also found that, individually, several of our progression-associated genes were statistically significantly associated with overall survival (G6PD and CAMK1D (Figure 1b)), relapse (RAC2 and ADRBK1), and non-relapse mortality (G6PD, CIQBP, and CAMK1D). In conclusion, these data suggest that gene expression prior to therapy is associated with treatment outcomes even after considering the contribution from known risk factors. These data provide evidence that a molecular signature associated with disease progression when detected in CP patients drives outcomes after transplantation. Given that all treatment outcomes are dependent on phase, it is possible that the expression of these genes prior to tyrosine kinase inhibitor therapy may also predict response. Figure 1. After adjustment for EBMT risk score, the probability of expression (Prob Score) of a 6-gene signature (RALGDS, LASP1, G6PD, ADRBKI, LRPPRC, PSMA1) correlates with relapse (Figure 1a) and CAMK1D expression correlates with overall survival (Figure 1b) after allogeneic transplantation in CP CML patients. Figure 1. After adjustment for EBMT risk score, the probability of expression (Prob Score) of a 6-gene signature (RALGDS, LASP1, G6PD, ADRBKI, LRPPRC, PSMA1) correlates with relapse (Figure 1a) and CAMK1D expression correlates with overall survival (Figure 1b) after allogeneic transplantation in CP CML patients. Disclosures: Oehler: Pfizer: Research Funding. Radich:Novartis: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria.


2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14209-e14209
Author(s):  
Haider Mahdi ◽  
Peter Graham Rose ◽  
Fadi W Abdul-Karim ◽  
Bradley J. Monk ◽  
Ying Ni

e14209 Background: Immunotherapy is promising option given low toxicity and potential durable response. In mismatch repair proficient endometrial and ovarian cancers, the reported response rate is ranging from 10-15% in recurrent setting. We need to better identify subset of patients who benefits from immunotherapy. Multigene immune signatures represent a robust means of capturing a complex, T cell–inflamed phenotype necessary for the clinical activity of PD-1–/PD-L1–directed monoclonal antibodies. IFN-γ is a key cytokine produced by activated T cells, as well as natural killer (NK) and NK T cells, in the tumor microenvironment. An immune-related IFN-γ 18-gene profile was derived through a cross-validated penalized regression modeling strategy to predict response to anti-PD1 therapy across 9 different tumor types. We want to test if this gene panel can also predict cancer outcome and response to chemotherapy. Methods: We used whole transcriptome sequencing of RNA matched tumor-normal samples from 38 high stage (Stage III and IV) uterine serous cancer patients. All patients received chemotherapy with platinum and taxanes. IFN-18 gene expression score was calculated by averaging the normalized and log transformed individual gene read counts. The optimized score cut off was selected to best separating the progression free survival. Then the cut off score was tested in The Cancer Genomic Atlas (TCGA) uterine and ovarian cancer RNAseq datasets. Results: The IFN score of 2.46 was determined based on 18-gene expression derived from 38 high-stage uterine serous cancer samples. Average age was 67 years (range: 56-82 years). Uterine serous cancer is known to be MSI stable. Patients with score higher than 2.46 showed significantly longer progression free survival (PFS – 57.6 months vs 15months, p = 0.002) and longer overall survival (73.1 months vs 51.1 months), not statistically significant given our small sample size, p = 0.13) compared to the patients with score lower than 2.46. Then this IFN based gene signature was then applied to TCGA 541 uterine cancer samples with RNAseq data. Similarly, this signature predicted significant improvement in both progression-free survival (p = 0.001) and overall survival (p = 0.005). Interestingly, this score cannot separate outcome for TCGA ovarian cancer cohort. Conclusions: Immune-related IFN-γ gene signature predicted prognosis and response to chemotherapy. We plan to assess if this signature will predict endometrial cancer patients who benefits from anti-PD1 therapy.


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