Abstract 2157
Background
The molecular analysis of melanoma has improved our understanding of the disease. The Cancer Genome Atlas (TCGA) Network proposed the molecular classification of melanoma in three subtypes: keratin-high, immune-high and membrane-low. However, this classification has not translated into therapeutic advances so far. Immunotherapy has contributed to improve survival, yet the mechanisms explaining differences in efficacy have not been elucidated. The aim of this study is to characterize the immune status of melanoma tumors through gene expression, and to analyze if these differences have an impact in the response to immunotherapy.
Methods
A probabilistic graphical model, followed by successive sparse k-means and consensus cluster analyses, was used to classify melanoma tumor samples from the TCGA cohort. Findings were translated into a cohort of patients treated with anti-PD1 antibodies (GSE78220, Hugo W et al) as a validation dataset.
Results
A probabilistic graphical model, including the 2,971 more variable genes from 472 melanoma samples from the TCGA dataset was built, and the resulting graph was processed to seek functional structures. Sparse k-means selected 119 genes. Gene ontology analysis showed that these genes were mainly related with immune processes. Immune genes split the population into two groups with different immune status. The so-called immune-high group included 232 patients (49%) and the immune-low group groups 238 patients (51%). The validation dataset GSE78220 provided mRNA expression in melanomas being treated with anti-PD-1 antibodies (28 biopsies belonging to 27 patients). The immune layer was translated to the new cohort by centroid method: 9 patients had immune-low tumors, whereas the remaining 18 had immune-high tumors. Kaplan Meier analysis using the clinical data from the GSE78220 cohort found a favorable response in patients with immune-low tumors (90% long-term survival).
Conclusions
We found a gene signature related to the tumor immune status that split the TCGA cohort in two groups. When applied to a cohort of patients treated with anti-PD1 antibodies, the group with immune-low tumors had 90% of long-term survival.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
5822 - Greek nursing students experience facing death in clinical practice
Presenter: Maria Dimoula
Session: Poster Display session 3
Resources:
Abstract
2866 - HOPEVOL: Hospice care appropriate to the wishes and needs of patients in the palliative terminal phase.
Presenter: Merel van Klinken
Session: Poster Display session 3
Resources:
Abstract
829 - Mindfulness-based stress reduction in early palliative care for advanced cancer patients : an italian single-centre study. MINDEEP
Presenter: Emilia Gianotti
Session: Poster Display session 3
Resources:
Abstract
2702 - Optimising Inpatient Oncology Care
Presenter: Lisa Judge
Session: Poster Display session 3
Resources:
Abstract
1527 - Analysis on the Implementation Results of Family Sickbed for Oncology Patients in Dongshi Township Health Centers from 2015 to 2017
Presenter: Yayu Huang
Session: Poster Display session 3
Resources:
Abstract
2054 - Exploring needs for palliative care and quality of life for oncology patients with advanced disease who undergo radiotherapy
Presenter: Foteini Antonopoulou
Session: Poster Display session 3
Resources:
Abstract
5605 - Cytotoxic contamination in cancer care settings – Risks and safety awareness among cancer nurses
Presenter: Sandra Lundman Vikberg
Session: Poster Display session 3
Resources:
Abstract
5769 - Understanding Chemotherapy - group education sessions prior to commencing chemotherapy
Presenter: Aileen McHale
Session: Poster Display session 3
Resources:
Abstract
2620 - Estimation of HPQ-based absenteeism and presenteeism in cancer patients via ResearchKit
Presenter: Shunsuke Kondo
Session: Poster Display session 3
Resources:
Abstract
4705 - Identifying falls-related variables and risk factors in hospitalised cancer patients
Presenter: Maria Montserrat Martí Dillet
Session: Poster Display session 3
Resources:
Abstract