Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data

Finotello, Francesca; Mayer, Clemens; Plattner, Christina; Laschober, Gerhard; Rieder, Dietmar; Hackl, Hubert; Krogsdam, Anne; Loncová, Zuzana; Posch, Wilfried; Wilflingseder, Doris; Sopper, Sieghart; Ijsselsteijn, Marieke E.; Brouwer, Thomas P.; Johnson, Douglas B.; Xu, Yaomin; Wang, Yu; Sanders, Melinda E.; Estrada, Mónica Valéria; Ericsson-Gonzalez, Paula I.; Charoentong, Pornpimol; Balko, Justin M.; Miranda, Noel F C C de; Trajanoski, Zlatko

doi:10.1186/s13073-019-0638-6

Cited by 821 publications

(575 citation statements)

References 65 publications

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“…By running ESTIMATE on TCGA RNA-seq data, the stromal and immune score of each sample can be estimated as previously described [90][91][92]. We quantified the proportion of cells that belonged to each of 10 immune cell types (B cells, M1 macrophages, M2 macrophages, monocytes, neutrophils, NK cells, CD4+ T cells, CD8+ T cells, regulatory T cells, and dendritic cells) using the quanTIseq package in R [93]. CMS classifications of COAD were performed using the CMSCaller package in R [64].…”

Section: Estimation Of Tumor Cellular Components and Crc Subtypesmentioning

confidence: 99%

Cancer Stem Cell Marker DCLK1 Correlates with Tumorigenic Immune Infiltrates in the Colon and Gastric Adenocarcinoma Microenvironments

Weygant

et al. 2020

Cancers

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Immunotherapy that has proven efficacy in several solid cancers plays a partial role in improving clinical outcomes of advanced gastrointestinal (GI) cancers. There is an unmet need to find new immune-related therapeutic targets. Doublecortin-like kinase 1 (DCLK1) marks tuft cells which are recognized as cancer-initiating cells and regulators of the type II immune response, and has been studied for its role in many cancers including colon and gastric cancers, but its role in tumor immunity remains unexplored. In the current study, we analyzed colon and gastric cancer RNA sequencing data from 283 and 415 patients, respectively, from The Cancer Genome Atlas (TCGA). High DCLK1 expression predicted the worse clinical outcomes in colon and gastric cancer patients and correlated with increased immune and stromal components. Further analysis indicated that DCLK1 was strongly linked to infiltration of multiple immune cell types, especially TAMs and Treg, and strongly correlated with increased CD8+ T cell inhibitors TGFB1 and CXCL12 and their receptors, suggesting it may contribute to TAM-mediated inhibition of CD8+ T cells. Interestingly, we found that DCLK1 was a prognostic biomarker in left-sided colon cancer, which has worse outcomes and demonstrates a reduced response to existing immunotherapies. In conclusion, our results demonstrate that DCLK1 is linked with functional regulation of the tumor microenvironment and may have potential as a prognostic biomarker and adjuvant target to promote immunotherapy sensitivity in colon and gastric cancer patients.

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Section: Estimation Of Tumor Cellular Components and Crc Subtypesmentioning

confidence: 99%

Cancer Stem Cell Marker DCLK1 Correlates with Tumorigenic Immune Infiltrates in the Colon and Gastric Adenocarcinoma Microenvironments

Weygant

et al. 2020

Cancers

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“…A description of all methods is provided in Table 1 and Additional file 1: Table S2. First, while the Spearman correlations between microscopic (red) and all methylomic (blue) or transcriptomic (green) estimates were poor to moderate, our analysis showed that stromal infiltration correlates better [20]; digTMA, tissue microarray scored by Visiopharm (digital analysis); MCP, MCP-counter [22]; meTIL, methylation TIL score [27]; metCBS, methylCIBERSORT [25]; itTIL, intra-tumoral TIL on H&E; qSEQ, quanTIseq [21]; sTIL, stromal TIL on H&E; TILrna, TIL score based on transcriptome [26]; TMA (H&E), sTIL scored on TMA; TMA (IHC), tissue microarray scored by pathologists with CD3 and CD20 markers to calculate the sTIL; WS (IHC), whole slide immunohistochemistry of CD3 and CD20 by pathologists with all other methods, including transcriptomic and methylomic methods, as compared to the intra-tumoral infiltration (Fig. 3a).…”

Section: Comparison Of Microscopic Transcriptomic and Methylomic Evmentioning

confidence: 77%

“…Finally, of the methods that predict global immune infiltration based on the transcriptome (green label in Fig. 3a), TILrna showed the highest correlations with the various immune gene signatures (pink label, r = 0.90-0.94), while quanTIseq [21] showed the poorest correlations (r = 0.16-0.18). Similar analyses were further carried on separately for ER-negative and ER-positive tumors as the biological significance of the immune infiltrate may be different [46,47] (Fig.…”

Section: Comparison Of Microscopic Transcriptomic and Methylomic Evmentioning

confidence: 99%

Comprehensive evaluation of methods to assess overall and cell-specific immune infiltrates in breast cancer

et al. 2019

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Background: Breast cancer (BC) immune infiltrates play a critical role in tumor progression and response to treatment. Besides stromal tumor infiltrating lymphocytes (sTILs) which have recently reached level 1B evidence as a prognostic marker in triple negative BC, a plethora of methods to assess immune infiltration exists, and it is unclear how these compare to each other and if they can be used interchangeably. Methods: Two experienced pathologists scored sTIL, intra-tumoral TIL (itTIL), and 6 immune cell types (CD3 + , CD4 + , CD8 + , CD20 + , CD68 + , FOXP3 +) in the International Cancer Genomics Consortium breast cancer cohort using hematoxylin and eosin-stained (n = 243) and immunohistochemistry-stained tissue microarrays (n = 254) and whole slides (n = 82). The same traits were evaluated using transcriptomic-and methylomic-based deconvolution methods or signatures. Results: The concordance correlation coefficient (CCC) between pathologists for sTIL was very good (0.84) and for cellspecific immune infiltrates slightly lower (0.63-0.66). Comparison between tissue microarray and whole slide pathology scores revealed systematically higher values in whole slides (ratio 2.60-5.98). The Spearman correlations between microscopic sTIL and transcriptomic-or methylomic-based assessment of immune infiltrates were highly variable (r = 0.01-0.56). Similar observations were made for cell type-specific quantifications (r = 0.001-0.54). We observed a strong inter-method variability between the omics-derived estimations, which is further cell type dependent. Finally, we demonstrated that most methods more accurately identify highly infiltrated (sTIL ≥ 60%; area under the curve, AUC, 0.64-0.99) as compared to lowly infiltrated tumors (sTIL ≤ 10%; AUC 0.52-0.82).

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“…However, the effort was limited to available knowledge from cell type profiling in vitro and in bulk [28][29][30]37] , and does not account for all cell-type specific expression differences, particularly where the differences in miRNA expression levels are more subtle or unknown. Cell deconvolution of bulk tissue sequencing data based on gene expression is in itself a large and rapidly developing field [79][80][81] . As of yet, development of rigorous miRNA expression profiles on the cellular level is still in its infancy [82] .…”

Section: Resultsmentioning

confidence: 99%

A microRNA Signature of Metastatic Colorectal Cancer

Høye

Fromm

Böttger

et al. 2020

Preprint

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BackgroundAlthough microRNAs (miRNAs) are involved in all hallmarks of cancer, miRNA dysregulation in the metastatic process remains poorly understood. We investigated the role of miRNAs in metastatic evolution of colorectal cancer (CRC) by analyzing smallRNA-seq datasets from primary CRC, metastatic locations (liver, lung and peritoneum), and corresponding adjacent tissues. Addressing main challenges of miRNA analysis, a bioinformatics pipeline was developed that contains bona fide miRNA annotations from MirGeneDB, utilizes the quality control software miRTrace, applies physiologically meaningful cutoffs and accounts for contribution of cell-type specific miRNAs and host tissue effects. ResultsTwo hundred-and-seventy-five miRNA sequencing datasets were analyzed, and after adjusting for the contribution of heterogeneity in cellular composition, strong signatures for primary and metastatic CRC were identified. The signature for primary CRC contained many previously known miRNAs with known functions. Deregulation of specific miRNAs was associated with individual metastatic sites, but the metastatic signatures contained overlapping miRNAs involved in key elements of the metastatic process, such as epithelial-to-mesenchymal transition and hypoxia. Notably, four of these miRNAs (MIR-8, MIR-10, MIR-375, MIR-210) belong to deeply conserved families present in many other organisms, triggering questions about their evolutionary functions and opportunities for experimental validation. Conclusion:Applying a meticulous pipeline for the analysis of smallRNA-seq data, miRNA signatures for primary and metastatic CRC were identified, contributing novel insights into miRNA involvement in CRC metastatic evolution and site-specific metastatic adaptations. New datasets can easily be included in this publicly available pipeline to continuously improve the knowledge in the field.

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Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data

Cited by 821 publications

References 65 publications

Cancer Stem Cell Marker DCLK1 Correlates with Tumorigenic Immune Infiltrates in the Colon and Gastric Adenocarcinoma Microenvironments

Cancer Stem Cell Marker DCLK1 Correlates with Tumorigenic Immune Infiltrates in the Colon and Gastric Adenocarcinoma Microenvironments

Comprehensive evaluation of methods to assess overall and cell-specific immune infiltrates in breast cancer

A microRNA Signature of Metastatic Colorectal Cancer

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