Analysis of the whole transcriptome from gingivo-buccal squamous cell carcinoma reveals deregulated immune landscape and suggests targets for immunotherapy

<div><p>Background</p><p>Gingivo-buccal squamous cell carcinoma (GBSCC) is one of the most common oral cavity cancers in India with less than 50% patients surviving past 5 years. Here, we report a whole transcriptome profile on a batch of GBSCC tumours with diverse tobacco usage habits. The study provides an entire landscape of altered expression with an emphasis on searching for targets with therapeutic potential.</p><p>Methods</p><p>Whole transcriptomes of 12 GBSCC tumours and adjacent normal tissues were sequenced and analysed to explore differential expression of genes. Expression changes were further compared with those in TCGA head and neck cohort (n = 263) data base and validated in an independent set of 10GBSCC samples.</p><p>Results</p><p>Differentially expressed genes (n = 2176) were used to cluster the patients based on their tobacco habits, resulting in 3 subgroups. Immune response was observed to be significantly aberrant, along with cell adhesion and lipid metabolism processes. Different modes of immune evasion were seen across 12 tumours with up-regulation or consistent expression of <i>CD47</i>, unlike other immune evasion genes such as <i>PDL1</i>, <i>FUT4</i>, <i>CTLA4</i> and <i>BTLA</i> which were downregulated in a few samples. Variation in infiltrating immune cell signatures across tumours also indicates heterogeneity in immune evasion strategies. A few actionable genes such as <i>ITGA4</i>, <i>TGFB1</i> and <i>PTGS1/COX1</i> were over expressed in most samples.</p><p>Conclusion</p><p>This study found expression deregulation of key immune evasion genes, such as <i>CD47</i> and <i>PDL1</i>, and reasserts their potential as effective immunotherapeutic targets for GBSCC, which requires further clinical studies. Present findings reiterate the idea of using transcriptome profiling to guide precision therapeutic strategies.</p></div

Hierarchical clustering of GBSCC tumours by 2176 deregulated gene expressions.

<p>Hierarchical clusters were constructed based on log2 transformed expression values of 1002 upregulated (represented by colours of negative values in heatmap) and 1174 downregulated genes (represented by colours of positive values in heatmap). Across all 12 tumours there is a gross similarity in deregulation pattern, with some exceptions. As a result, 3 distinct sample clusters were noticed. The coloured panel below, represent subject's smoking (orange) and/or chewing tobacco (red) and/or alcohol abuse (green)status.</p

Schematic view of fusion events.

<p>(A) ANO1-PLA2G16 fusion gene which retains exon 16 along with upstream exons of ANO1 and exon 3 along with downstream exons of PLA2G16 in tumour tissue (i.e. 23D) of the tumour-normal paired S23 sample. (B) S100A9-KRT17 fusion gene deduced from coding regions up to exon 3 of S100A9 and exon 1 to all other downstream exons of KRT17 in tumour tissue (i.e. 2D) of the tumour-normal paired S2 sample.</p

Expression deregulation of miRNA and target mRNAs.

<p>(A) Bar plots show log₂fold change in expression of miRNAs (hsa-miR-18b, hsa-miR-1293and hsa-miR-21) and their target, TIMP3. Scatter plots show negative correlation of TIMP3 expression with hsa-miR-18b and hsa-miR-21expression. Negative correlation was not observed between TIMP3 and hsa-miR-1293. Negative values of log₂fold change indicate upregulated expression whereas positive log₂fold change values indicate downregulation. (B) Bar plot showslog₂fold change of expression of miRNAs (hsa-miR-126 and hsa-miR-7) and their target, IRS1. Scatter plot shows negative correlation of IRS1 expression with hsa-miR-126 and hsa-miR-7expression. Negative values of log₂fold change indicate upregulated expression whereas positive fold change values indicate downregulation.</p

Immune response alterations in tumor compared to normal tissues.

<p>(A) Heatmap shows diverse expression levels (log fold change of FPKM values) of immune evasion genes. Orange values in color bar shows up regulation while values in blue show down regulation. The panel below shows proliferation scores per samples with green color intensity indicating higher proliferation score and numbers indicates % CCP score. The right-side panel indicates fold change values (FPKM) in TCGA HNSCC cohort (n = 263) for each gene. In case of TCGA HNCC tissues, Green color denotes downregulation while red color shows upregulation in the right-side panel. (B) The barplot shows how relative composition of immune cells is altered across 12 pairs of tumor compared to its control tissues. Plot was derived from the <i>CIBERSORT</i> [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0183606#pone.0183606.ref009" target="_blank">9</a>] estimated data output from FPKM normalized expression data. Every color stands for a type of immune cell and height of each colored bar represents relative frequency of an immune cell type. In the plot, 2N and 2D indicate normal and tumour tissues of tumour-normal paired S2sample, respectively. Similar nomenclature was used for tumour and normal tissues of other samples.</p

Heat map of correlation matrix for the expression of 11 canonical Hh-pathway component genes in TCGA-GBM (N = 149, significant cut-off |r|>0.17, MTC with FDR 0.1).

<p>Heat map of correlation matrix for the expression of 11 canonical Hh-pathway component genes in TCGA-GBM (N = 149, significant cut-off |r|>0.17, MTC with FDR 0.1).</p

A, cell cycle arrest in GBM neurospheres with vismodegib treatment <i>in vitro</i> a) A49910, b), B0027, c) B0043, d) B0051 and e) M45481.

<p><b>B</b>, Number of apoptotic cells (annexin V positive) in GBM neurospheres treated either with DMSO or with 50 μM vismodegib.</p

Log scale distribution of GLI1 mRNA expression in a) already published MB cases, along with 1 new case of MB from our repository b) distribution of GLI1 mRNA expression (RNA-Seq data) of the TCGA-GBM sub-cohort (N = 149), c) distribution of GLI1 mRNA expression in NIBMG-GBM cases (N = 19), d) distribution of GLI1 mRNA expression in GBM patient-derived early passage neurospheres (N = 6) and e) comparison of median GLI1 mRNA expression levels of high-Hh-MB (N = 13), low-Hh-MB (N-44), NIBMG-GBM (N = 19) and GBM patient-derived neurospheres (N = 6).

<p>Log scale distribution of GLI1 mRNA expression in a) already published MB cases, along with 1 new case of MB from our repository b) distribution of GLI1 mRNA expression (RNA-Seq data) of the TCGA-GBM sub-cohort (N = 149), c) distribution of GLI1 mRNA expression in NIBMG-GBM cases (N = 19), d) distribution of GLI1 mRNA expression in GBM patient-derived early passage neurospheres (N = 6) and e) comparison of median GLI1 mRNA expression levels of high-Hh-MB (N = 13), low-Hh-MB (N-44), NIBMG-GBM (N = 19) and GBM patient-derived neurospheres (N = 6).</p