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Identification of a predictive gene signature to recMAGE A3 antigen-specific cancer immunotherapy in metastatic melanoma and non-small-cell lung cancer

ABSTRACT: Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGE‑A3 immunotherapeutic in metastatic melanoma patients and to validate its predictivity in adjuvant therapy of early-stage lung cancer. Patients were participants in two Phase II studies of the recombinant MAGE‑A3 antigen combined with immunological adjuvants. mRNA from tumor samples (biopsies) collected before MAGE-A3 immunotherapy was analyzed by microarray hybridization and by quantitative polymerase chain reaction (qRT-PCR). The melanoma microarray dataset was used to discover and crossvalidate a gene expression signature and classifier discriminative of Responders (R) versus Non-Responders (NR) patients; the gene signature and classifier were then applied to an adjuvant lung cancer study. Patients that were not included for analysis are denoted as NE (Non-evaluable). GSK Biologicals

ORGANISM(S): Homo sapiens

SUBMITTER: Ulloa-Montoya F

PROVIDER: S-ECPF-GEOD-35640 | biostudies-other | 2013 Jul

REPOSITORIES: biostudies-other

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Identification of a predictive gene signature to recMAGE A3 antigen-specific cancer immunotherapy in metastatic melanoma and non-small-cell lung cancer

Project description:Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGEâA3 immunotherapeutic in metastatic melanoma patients and to validate its predictivity in adjuvant therapy of early-stage lung cancer. Patients were participants in two PhaseÂ II studies of the recombinant MAGEâA3 antigen combined with immunological adjuvants. mRNA from tumor samples (biopsies) collected before MAGE-A3 immunotherapy was analyzed by microarray hybridization and by quantitative polymerase chain reaction (qRT-PCR). The melanoma microarray dataset was used to discover and crossvalidate a gene expression signature and classifier discriminative of Responders (R) versus Non-Responders (NR) patients; the gene signature and classifier were then applied to an adjuvant lung cancer study. Patients that were not included for analysis are denoted as NE (Non-evaluable). GSK Biologicals

2013-05-30 | E-GEOD-35640 | biostudies-arrayexpress

Identification of a predictive gene signature to recMAGE A3 antigen-specific cancer immunotherapy in metastatic melanoma and non-small-cell lung cancer

Project description:Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGE‑A3 immunotherapeutic in metastatic melanoma patients and to validate its predictivity in adjuvant therapy of early-stage lung cancer.

2013-05-30 | GSE35640 | GEO

Immune signature of metastatic breast cancer: Identifying predictive markers of immunotherapy response.

Project description:In breast cancer (BC), up to 10-20% patients were known to have clinical benefit with immune checkpoint inhibitors, and biomarkers are needed for optimal use of this multi-potential therapeutic strategy. Accordingly, we conducted an experiment to identify expression of genes associated with immune checkpoints that represent potential targets of cancer immunotherapy. We performed whole-transcriptome sequencing and whole-exome sequencing using 37 refractory BC specimens. In the immune pathway gene set expression analysis, we found that HER2 expression and previous taxane treatment were positively correlated with high expression of immune gene set expression (p = 0.070 and 0.008, respectively). The nine genes associated with immune checkpoints - PDCD1(PD-1), CD274(PD-L1), CD276(B7-H3), CTLA-4, IDO1, LAG3, VTCN1, HAVCR2, and TNFRSF4(OX40) - interacted with each other. In addition, HER2 expression also affected the expression levels of these genes (p = 0.044). Lastly, expression of immune checkpoint genes and tissue-infiltrating lymphocytes were positively correlated in metastatic BCs (p < 0.001). In conclusion, we suggest that HER2 expression and previous taxane treatment are potential surrogate markers for high expression of immune checkpoint genes and immune pathway gene sets. Further study of the BC immune signature with large-scale, translational data sets is warranted.

| S-EPMC5564574 | biostudies-literature

Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT).

Project description:BACKGROUND:Genomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS. PATIENTS AND METHODS:An open-label prospective phase II trial ('PREDICT') in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma. RESULTS:Of 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS+). The 1-year OS rate was 83.1%/83.3% in the GS+/GS- populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS- patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS-). There was one complete response (GS-) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile. CONCLUSION:Treatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS- and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study.This study is registered at www.clinicatrials.gov NCT00942162.

| S-EPMC5035794 | biostudies-literature

APOBEC3B and APOBEC mutational signature as potential predictive markers for immunotherapy response in non-small cell lung cancer.

Project description:Non-small cell lung cancer (NSCLC) is known to carry heavy mutation load. Besides smoking, cytidine deaminase APOBEC3B plays a key role in the mutation process of NSCLC. APOBEC3B is also reported to be upregulated and predicts bad prognosis in NSCLC. However, targeting APOBEC3B high NSCLC is still a big challenge. Here we show that APOBEC3B upregulation is significantly associated with immune gene expression, and APOBEC3B expression positively correlates with known immunotherapy response biomarkers, including: PD-L1 expression and T-cell infiltration in NSCLC. Importantly, APOBEC mutational signature is specifically enriched in NSCLC patients with durable clinical benefit after immunotherapy and APOBEC mutation count can be better than total mutation in predicting immunotherapy response. In together, this work provides evidence that APOBEC3B upregulation and APOBEC mutation count can be used as novel predictive markers in guiding NSCLC checkpoint blockade immunotherapy.

| S-EPMC6053356 | biostudies-literature

Safety and immunogenicity of MAGE-A3 cancer immunotherapeutic with dacarbazine in patients with MAGE-A3-positive metastatic cutaneous melanoma: an open phase I/II study with a first assessment of a predictive gene signature.

Project description:Background:We assessed safety, immunogenicity and clinical activity of recombinant MAGE-A3 antigen combined with AS15 immunostimulant (MAGE-A3 immunotherapeutic) in association with dacarbazine in patients with metastatic melanoma. Methods:In this open-label, phase I/II, uncontrolled multicentre trial conducted in Belgium and France, patients with MAGE-A3-positive melanoma received up to 24 doses of MAGE-A3 immunotherapeutic (four cycles) coadministered with eight doses of dacarbazine. Adverse events (AE) were recorded until 31 days postvaccination, and serious AEs (SAE), until 30 days following the last dose. MAGE-A3-specific antibodies were measured by ELISA. Clinical activity of MAGE-A3 immunotherapeutic was assessed in patients positive/negative for previously identified gene signature (GS) associated with clinical outcome. Results:Forty-eight patients were enrolled and treated (32 GS+, 15 GS-, 1 unknown GS status); two patients completed the study. All patients reported AEs, the most common were 'general disorders and administration site conditions' (94%). Treatment-related AEs were reported by 85% of patients; the most common was pain at injection site (38%). Sixteen SAEs were reported by 21% of patients; two were considered as treatment related (neutropenia and thrombocytopenia; grade 4). Postdose 4, all patients were seropositive for MAGE-A3-specific antibodies, with a geometric mean titre of 2778.7 ELISA units (EU)/mL (95% CI 1638.3 to 4712.8). One complete and three partial responses were reported (only in GS+ patients). Median overall survival was 11.4 months for GS+ and 5.3 months for GS- patients. Conclusion:Although this trial shows poor results compared with the new results with checkpoint inhibitors, it gives an interesting insight in rapidly developing fields like combinations of immunotherapy and chemotherapy, new generation vaccines and the use of gene profile as a predictive marker. Trial registration number:NCT00849875.

| S-EPMC5687540 | biostudies-literature

Metastatic melanoma and immunotherapy.

Project description:Harnessing the immune system to attack cancer cells has represented a holy grail for greater than 100years. While prospects of tumor-selective durable immune based therapies have provided small clinical signals for many decades, recent years have demonstrated a virtual explosion in progress. Melanoma has led the field of cancers in which immunotherapy has produced major clinical inroads. The most significant and impactful immunotherapies for melanoma utilize immune checkpoint inhibition to stimulate T cell mediated tumor killing. The major targets of checkpoint blockade have thus far been CTLA4 and PD1, two key receptors for central and peripheral immune tolerance. This review discusses current understanding of how these checkpoint blockade therapeutics have led to major clinical responses in patients with advanced melanoma. It is likely that we are poised to see significantly greater anti-cancer immunotherapy efficacy, both in improving response rates and durability for melanoma, and for other less immunogenic malignancies.

| S-EPMC5569887 | biostudies-other

Avoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer.

Project description:Immunotherapy has been focused on by many oncologists and researchers. While, due to technical biases of absolute quantification, few traditional biomarkers for anti-PD-1 immunotherapy have been applied in regular clinical practice of non-small cell lung cancer (NSCLC). Therefore, there is an urgent and unmet need for a feasible tool-immune to data source bias-for identifying patients who might benefit from ICIs in clinical practice. Using the strategy based on the relative ranking of gene expression levels, we herein proposed the novel BRGP index (BRGPI): four BRGPs significantly related with progression-free survival of NSCLC patients treated with anti-PD-1 immunotherapy in the multicohort analysis. Moreover, stratification and multivariate Cox regression analyses demonstrated that BRGPI was an independent prognostic factor. Notably, compared to PD-L1, BRGPI exerted the best predictive ability. Further analysis showed that the patients in the BRGPI-low and PD-L1-high subgroup derived more clinical benefits from anti-PD-1 immunotherapy. In conclusion, the prospect of applying the BRGPI to real clinical practice is promising owing to its powerful and reliable predictive value.

| S-EPMC8640493 | biostudies-literature

Prognostic and Predictive Gene Signature for Adjuvant Chemotherapy in Resected Non-Small Cell Lung Cancer

Project description:Background: The JBR.10 trial demonstrated significant survival benefit from adjuvant cisplatin/vinorelbine (ACT) in stage IB-II NSCLC (HR 0.69, p=0.04), but stage IB patients did not derive significant benefit (HR: 0.94, p= 0.79). We hypothesized that expression profiling could identify stage-independent subgroups of patients who might benefit from adjuvant chemotherapy. Methods: Gene expression profiling was conducted on mRNA isolated from frozen JBR.10 tumor samples (either from patients under observation [OBS], or treated with ACT). The minimum gene set that selected for the greatest separation of good and poor prognosis patient subgroups in OBS patients was identified and this gene signature was used to classify patients into high and low risk for death after surgery, and predict ACT effect. The prognostic gene signature was additionally tested on ACT patients and publicly available microarray datasets. Results: A 15-gene signature separated OBS patients into equal high and low risk subgroups with significantly different prognoses (HR 15.02, 95% CI 5.12-44.04, p=0.0001). The signature was prognostic in both stage IB and II. It was also predictive of improved survival following ACT treatment in high-risk patients (HR 0.33, 95% CI 0.17-0.63, p=0.0005), but not in low risk patients (HR 3.67, 95% CI 1.22-11.06, p=0.0133; interaction p=0.0001). The prognostic effect of the signature was validated in two independent gene expression datasets of 169 stage I-II adenocarcinoma and 106 squamous cell carcinoma patients. Conclusions: This microarray-based 15-gene prognostic expression signature is stage and histology independent and may select early stage NSCLC patients who are most likely to benefit from adjuvant chemotherapy with cisplatin/vinorelbine. Keywords: Expression profiling by microarray; prognosis prediction 90 samples

| S-ECPF-GEOD-14814 | biostudies-other

A predictive phosphorylation signature of lung cancer.

Project description:BackgroundAberrant activation of signaling pathways drives many of the fundamental biological processes that accompany tumor initiation and progression. Inappropriate phosphorylation of intermediates in these signaling pathways are a frequently observed molecular lesion that accompanies the undesirable activation or repression of pro- and anti-oncogenic pathways. Therefore, methods which directly query signaling pathway activation via phosphorylation assays in individual cancer biopsies are expected to provide important insights into the molecular "logic" that distinguishes cancer and normal tissue on one hand, and enables personalized intervention strategies on the other.ResultsWe first document the largest available set of tyrosine phosphorylation sites that are, individually, differentially phosphorylated in lung cancer, thus providing an immediate set of drug targets. Next, we develop a novel computational methodology to identify pathways whose phosphorylation activity is strongly correlated with the lung cancer phenotype. Finally, we demonstrate the feasibility of classifying lung cancers based on multi-variate phosphorylation signatures.ConclusionsHighly predictive and biologically transparent phosphorylation signatures of lung cancer provide evidence for the existence of a robust set of phosphorylation mechanisms (captured by the signatures) present in the majority of lung cancers, and that reliably distinguish each lung cancer from normal. This approach should improve our understanding of cancer and help guide its treatment, since the phosphorylation signatures highlight proteins and pathways whose phosphorylation should be inhibited in order to prevent unregulated proliferation.

| S-EPMC2777383 | biostudies-literature

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