The tumour microenvironment, namely the interaction between immune cells and tumour cells plays a crucial role in the treatment outcome of immunotherapy.
In order to predict patient responses to immunotherapy a tumour stratification framework has been proposed based on PD-L1 expression and presence of CD8 Tumour Infiltrative Lymphocytes (TIL).
Advances in genomic technologies and computational tools now allow to determine compositions of different immune cell infiltrates in bulk tumors with increasing accuracy and resolution. Our aim here was to use RNA-seq and methylation 450k data to stratify 469 melanoma patients in TCGA dataset according to the presence of CD8 Tumour Infiltrative Lymphocytes (TIL) and PD-L1 mRNA expression.
Similaire à Stratification of TCGA melanoma patients according to Tumor Infiltrative CD8 Lymphocytes and PD-L1 expression using RNA-seq and 450k methylation data
Assessment of immunomolecular_expression_and_prognostic_role_of_tlr7_among_pa...dr.Ihsan alsaimary
Similaire à Stratification of TCGA melanoma patients according to Tumor Infiltrative CD8 Lymphocytes and PD-L1 expression using RNA-seq and 450k methylation data (20)
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Stratification of TCGA melanoma patients according to Tumor Infiltrative CD8 Lymphocytes and PD-L1 expression using RNA-seq and 450k methylation data
1. Stratification of TCGA melanoma patients according to
Tumor Infiltrative CD8 Lymphocytes and PD-L1 expression
using RNA-seq and 450k methylation data
Ahn, A.1, Chatterjee, A.1,2, Rodger, E.J.1,2, Eccles, M.R.1,2
Background
The tumour microenvironment, namely the interaction between immune
cells and tumour cells plays a crucial role in the treatment outcome of
immunotherapy.
In order to predict patient responses to immunotherapy a tumour
stratification framework has been proposed based on PD-L1 expression
and presence of CD8 Tumour Infiltrative Lymphocytes (TIL).
Advances in genomic technologies and computational tools now allow
to determine compositions of different immune cell infiltrates in bulk
tumors with increasing accuracy and resolution.
469 patients from the TCGA melanoma data were separated into 4 groups according to PD-
L1 and CD8 score.
A 28-gene panel was shown to
be able to predict response to
anti-PD1 therapy in melanoma
patients (6). We investigated the
expression of this 28-gene panel
in our 4 groups. Group 1
(TIL+/PDL1+) had the strongest
expression for this gene-panel.
In contrast, group 2 and group 4
had low expression. This is
consistent with literature where
high TIL and high PD-L1 levels
have been shown to have
stronger responses to treatment
in clinical trials.
Methods
Survival Analysis
References
1 - Hackl, H., et al. (2016). "Computational genomics tools for dissecting tumour-immune cell interactions." Nat Rev Genet 17(8): 441-458.
2. - Newman, A. M., et al. (2015). "Robust enumeration of cell subsets from tissue expression profiles." Nat Methods 12(5): 453-457.
3 - Becht, E., et al. (2016). "Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression." Genome Biol 17(1): 218.
4 - xCell: Aran, Hu and Butte, xCell: Digitally portraying the tissue cellular heterogeneity landscape. bioRxiv, 2017
5 - Jeschke, J., et al. (2017). "DNA methylation-based immune response signature improves patient diagnosis in multiple cancers." J Clin Invest 127(8): 3090-3102.
6 - Ayers, M., et al. (2017). "IFN-gamma-related mRNA profile predicts clinical response to PD-1 blockade." J Clin Invest 127(8): 2930-2940.
1Department of Pathology, University of Otago, Dunedin, NZ. 2Maurice Wilkins Centre, NZ.
RNA-seq
Stratify samples into 4 groups
according to presence or
absence of TIL and PD-L1 gene
expression
Generate methylation TIL
scores (meTIL-score) (5)
TCGA RNA-seq and methylation
450K data downloaded for 469
tumors/patients
Methylation 450K
Determine the CD8 T-
lymphocyte composition using
CiberSort (2), xCell (3) and
MCPcounter (4)
PD-L1 and CD8 TIL score between the 4 groups
Assessment of a gene-panel that has been
suggested to be a predictive biomarker
Overall survival was
assessed according to the 4
groups. Consistent with
literature, group 1
(TIL+/PDL1+) had a better
overall survival (log-rank p-
value 2.42 x 10-6).
Contact details
Antonio.ahn@otago.ac.nz
Aniruddha.chatterjee@otago.ac.nz
Euan.Rodger@otago.ac.nz
Michael.eccles@otago.ac.nz
Use RNA-seq and methylation 450k data to stratify 469 melanoma
patients in TCGA dataset according to the presence of CD8 Tumour
Infiltrative Lymphocytes (TIL) and PD-L1 mRNA expression.
TIL+ / PD-L1+
TIL- / PD-L1+
TIL+ / PD-L1-
TIL- / PD-L1-
Aim
Ref: Hackl, H., et al.
PD-L1 CD8 TIL - score
n = 179 (38%) n = 56 (12%) n = 56 (12%) n = 178 (38%)
n = 179 (38%) n = 56 (12%) n = 56 (12%) n = 178 (38%)
Conclusion
Here we demonstrate that computational methods can be used to group patients
according to the presence of CD8 TIL and PD-L1 mRNA expression. This can be
used to help gain insight into why certain melanoma patients are resistant to anti-
PD1 therapy.
