Graph machine learning for integrated multi-omics analysis.

Multi-omics experiments at bulk or single-cell resolution facilitate the discovery of hypothesis-generating biomarkers for predicting response to therapy, as well as aid in uncovering mechanistic insights into cellular and microenvironmental processes. Many methods for data integration have been developed for the identification of key elements that explain or predict disease risk or other biological outcomes. The heterogeneous graph representation of multi-omics data provides an advantage for discerning patterns suitable for predictive/exploratory analysis, thus permitting the modeling of complex relationships. Graph-based approaches-including graph neural networks-potentially offer a reliable methodological toolset that can provide a tangible alternative to scientists and clinicians that seek ideas and implementation strategies in the integrated analysis of their omics sets for biomedical research. Graph-based workflows continue to push the limits of the technological envelope, and this perspective provides a focused literature review of research articles in which graph machine learning is utilized for integrated multi-omics data analyses, with several examples that demonstrate the effectiveness of graph-based approaches.

Invasive margin tissue-resident macrophages of high CD163 expression impede responses to T cell-based immunotherapy.

BACKGROUND: Primary and secondary resistance is a major hurdle in cancer immunotherapy. Therefore, a better understanding of the underlying mechanisms involved in immunotherapy resistance is of pivotal importance to improve therapy outcome. METHOD: Here, two mouse models with resistance against therapeutic vaccine-induced tumor regression were studied. Exploration of the tumor microenvironment by high dimensional flow cytometry in combination with therapeutic in vivo settings allowed for the identification of immunological factors driving immunotherapy resistance. RESULTS: Comparison of the tumor immune infiltrate during early and late regression revealed a change from tumor-rejecting toward tumor-promoting macrophages. In concert, a rapid exhaustion of tumor-infiltrating T cells was observed. Perturbation studies identified a small but discernible CD163hi macrophage population, with high expression of several tumor-promoting macrophage markers and a functional anti-inflammatory transcriptome profile, but not other macrophages, to be responsible. In-depth analyses revealed that they localize at the tumor invasive margins and are more resistant to Csf1r inhibition when compared with other macrophages. In vivo studies validated the activity of heme oxygenase-1 as an underlying mechanism of immunotherapy resistance. The transcriptomic profile of CD163hi macrophages is highly similar to a human monocyte/macrophage population, indicating that they represent a target to improve immunotherapy efficacy. CONCLUSIONS: In this study, a small population of CD163hi tissue-resident macrophages is identified to be responsible for primary and secondary resistance against T-cell-based immunotherapies. While these CD163hi M2 macrophages are resistant to Csf1r-targeted therapies, in-depth characterization and identification of the underlying mechanisms driving immunotherapy resistance allows the specific targeting of this subset of macrophages, thereby creating new opportunities for therapeutic intervention with the aim to overcome immunotherapy resistance.

MediMer: a versatile do-it-yourself peptide-receptive MHC class I multimer platform for tumor neoantigen-specific T cell detection.

Peptide-loaded MHC class I (pMHC-I) multimers have revolutionized our capabilities to monitor disease-associated T cell responses with high sensitivity and specificity. To improve the discovery of T cell receptors (TCR) targeting neoantigens of individual tumor patients with recombinant MHC molecules, we developed a peptide-loadable MHC class I platform termed MediMer. MediMers are based on soluble disulfide-stabilized ß2-microglobulin/heavy chain ectodomain single-chain dimers (dsSCD) that can be easily produced in large quantities in eukaryotic cells and tailored to individual patients' HLA allotypes with only little hands-on time. Upon transient expression in CHO-S cells together with ER-targeted BirA biotin ligase, biotinylated dsSCD are purified from the cell supernatant and are ready to use. We show that CHO-produced dsSCD are free of endogenous peptide ligands. Empty dsSCD from more than 30 different HLA-A,B,C allotypes, that were produced and validated so far, can be loaded with synthetic peptides matching the known binding criteria of the respective allotypes, and stored at low temperature without loss of binding activity. We demonstrate the usability of peptide-loaded dsSCD multimers for the detection of human antigen-specific T cells with comparable sensitivities as multimers generated with peptide-tethered ß2m-HLA heavy chain single-chain trimers (SCT) and wild-type peptide-MHC-I complexes prior formed in small-scale refolding reactions. Using allotype-specific, fluorophore-labeled competitor peptides, we present a novel dsSCD-based peptide binding assay capable of interrogating large libraries of in silico predicted neoepitope peptides by flow cytometry in a high-throughput and rapid format. We discovered rare T cell populations with specificity for tumor neoepitopes and epitopes from shared tumor-associated antigens in peripheral blood of a melanoma patient including a so far unreported HLA-C*08:02-restricted NY-ESO-1-specific CD8+ T cell population. Two representative TCR of this T cell population, which could be of potential value for a broader spectrum of patients, were identified by dsSCD-guided single-cell sequencing and were validated by cognate pMHC-I multimer staining and functional responses to autologous peptide-pulsed antigen presenting cells. By deploying the technically accessible dsSCD MHC-I MediMer platform, we hope to significantly improve success rates for the discovery of personalized neoepitope-specific TCR in the future by being able to also cover rare HLA allotypes.

Tumor-specific T cells support chemokine-driven spatial organization of intratumoral immune microaggregates needed for long survival.

BACKGROUND: The composition of the tumor immune microenvironment (TIME) associated with good prognosis generally also predicts the success of immunotherapy, and both entail the presence of pre-existing tumor-specific T cells. Here, the blueprint of the TIME associated with such an ongoing tumor-specific T-cell response was dissected in a unique prospective oropharyngeal squamous cell carcinoma (OPSCC) cohort, in which tumor-specific tumor-infiltrating T cells were detected (immune responsiveness (IR+)) or not (lack of immune responsiveness (IR-)). METHODS: A comprehensive multimodal, high-dimensional strategy was applied to dissect the TIME of treatment-naive IR+ and IR- OPSCC tissue, including bulk RNA sequencing (NanoString), imaging mass cytometry (Hyperion) for phenotyping and spatial interaction analyses of immune cells, and combined single-cell gene expression profiling and T-cell receptor (TCR) sequencing (single-cell RNA sequencing (scRNAseq)) to characterize the transcriptional states of clonally expanded tumor-infiltrating T cells. RESULTS: IR+ patients had an excellent survival during >10 years follow-up. The tumors of IR+ patients expressed higher levels of genes strongly related to interferon gamma signaling, T-cell activation, TCR signaling, and mononuclear cell differentiation, as well as genes involved in several immune signaling pathways, than IR- patients. The top differently overexpressed genes included CXCL12 and LTB, involved in ectopic lymphoid structure development. Moreover, scRNAseq not only revealed that CD4+ T cells were the main producers of LTB but also identified a subset of clonally expanded CD8+ T cells, dominantly present in IR+ tumors, which secreted the T cell and dendritic cell (DC) attracting chemokine CCL4. Indeed, immune cell infiltration in IR+ tumors is stronger, highly coordinated, and has a distinct spatial phenotypical signature characterized by intratumoral microaggregates of CD8+CD103+ and CD4+ T cells with DCs. In contrast, the IR- TIME comprised spatial interactions between lymphocytes and various immunosuppressive myeloid cell populations. The impact of these chemokines on local immunity and clinical outcome was confirmed in an independent The Cancer Genome Atlas OPSCC cohort. CONCLUSION: The production of lymphoid cell attracting and organizing chemokines by tumor-specific T cells in IR+ tumors constitutes a positive feedback loop to sustain the formation of the DC-T-cell microaggregates and identifies patients with excellent survival after standard therapy.

NKG2A is a late immune checkpoint on CD8 T cells and marks repeated stimulation and cell division.

The surface inhibitory receptor NKG2A forms heterodimers with the invariant CD94 chain and is expressed on a subset of activated CD8 T cells. As antibodies to block NKG2A are currently tested in several efficacy trials for different tumor indications, it is important to characterize the NKG2A+ CD8 T cell population in the context of other inhibitory receptors. Here we used a well-controlled culture system to study the kinetics of inhibitory receptor expression. Naïve mouse CD8 T cells were synchronously and repeatedly activated by artificial antigen presenting cells in the presence of the homeostatic cytokine IL-7. The results revealed NKG2A as a late inhibitory receptor, expressed after repeated cognate antigen stimulations. In contrast, the expression of PD-1, TIGIT and LAG-3 was rapidly induced, hours after first contact and subsequently down regulated during each resting phase. This late, but stable expression kinetics of NKG2A was most similar to that of TIM-3 and CD39. Importantly, single-cell transcriptomics of human tumor-infiltrating lymphocytes (TILs) showed indeed that these receptors were often coexpressed by the same CD8 T cell cluster. Furthermore, NKG2A expression was associated with cell division and was promoted by TGF-ß in vitro, although TGF-ß signaling was not necessary in a mouse tumor model in vivo. In summary, our data show that PD-1 reflects recent TCR triggering, but that NKG2A is induced after repeated antigen stimulations and represents a late inhibitory receptor. Together with TIM-3 and CD39, NKG2A might thus mark actively dividing tumor-specific TILs.

Primary vulvar squamous cell carcinomas with high T cell infiltration and active immune signaling are potential candidates for neoadjuvant PD-1/PD-L1 immunotherapy.

BACKGROUND: A profound insight into the immune landscape of vulvar squamous cell carcinoma (VSCC) is lacking. Here, an in-depth interrogation of T cell infiltration, local immune contexture, signaling pathways and checkpoint molecule expression was performed in early-stage and late-stage VSCC. METHODS: The type, location, and infiltration pattern of T cells were studied in 109 patients with primary VSCC FIGO stage I-III. RNA expression of genes involved in immune oncology and oncogenic signaling pathways was analyzed in 40 VSCC, matched for prognostic clinicopathological variables, analyzed for HPV and p53 status, and selected based on T cell infiltration. RESULTS: High intraepithelial infiltration with CD4 or CD8 T cells was associated with longer overall and recurrence-free survival and formed an independent prognostic factor, outperforming molecular subtype and stage of the disease. Strong T cell infiltrated VSCC displayed a coordinated immune response reflected by a positive association between T cells and different lymphocyte and myeloid cell subsets. The expression of genes involved in the migration of T cells and myeloid cells, T cell activation and costimulation, interferon (IFN)-γ signaling, cytotoxicity and apoptosis was higher than in low infiltrated tumors. An active immune signaling profile was observed in all inflamed, part of the altered-excluded and not in altered-immunosuppressed or deserted VSCC. While several checkpoint molecules were overexpressed, only PD-L1 expression displayed discriminatory ability and clinical usefulness. High PD-L1 expression was detected in all inflamed and ~60% of the altered-excluded VSCC. CONCLUSION: An active immune signaling profile is present in 35% of primary FIGO I-III VSCCs, suggesting potential responsiveness to neoadjuvant PD-1/PD-L1 immunotherapy.

Frequent Molecular Subtype Switching and Gene Expression Alterations in Lung and Pleural Metastasis From Luminal A-Type Breast Cancer.

PURPOSE: Conversion of tumor subtype frequently occurs in the course of metastatic breast cancer but is a poorly understood phenomenon. This study aims to compare molecular subtypes with subsequent lung or pleural metastasis. PATIENTS AND METHODS: In a cohort of 57 patients with breast cancer and lung or pleural metastasis (BCLPM), we investigated paired primary and metastatic tissues for differential gene expression of 269 breast cancer genes. The PAM50 classifier was applied to identify intrinsic subtypes, and differential gene expression and cluster analysis were used to further characterize subtypes and tumors with subtype conversion. RESULTS: In primary breast cancer, the most frequent molecular subtype was luminal A (lumA; 49.1%); it was luminal B (lumB) in BCLPM (38.6%). Subtype conversion occurred predominantly in lumA breast cancers compared with other molecular subtypes (57.1% v 27.6%). In lumA cancers, 62 genes were identified with differential expression in metastatic versus primary disease, compared with only 10 differentially expressed genes in lumB, human epidermal growth factor receptor 2 (HER2)-enriched, and basal subtypes combined. Gene expression changes in lumA cancers affected not only the repression of the estrogen receptor pathway and cell cycle-related genes but also the WNT pathway, proteinases (MME, MMP11), and motility-associated cytoskeletal proteins (CK5, CK14, CK17). Subtype-switched lumA cancers were further characterized by cell proliferation and cell cycle checkpoint gene upregulation and dysregulation of the p53 pathway. This involved 83 notable gene expression changes. CONCLUSION: Our results indicate that gene expression changes and subsequent subtype conversion occur on a large scale in metastatic luminal A-type breast cancer compared with other molecular subtypes. This underlines the significance of molecular changes in metastatic disease, especially in tumors of initially low aggressive potential.

IDO1+ Paneth cells promote immune escape of colorectal cancer.

Tumors have evolved mechanisms to escape anti-tumor immunosurveillance. They limit humoral and cellular immune activities in the stroma and render tumors resistant to immunotherapy. Sensitizing tumor cells to immune attack is an important strategy to revert immunosuppression. However, the underlying mechanisms of immune escape are still poorly understood. Here we discover Indoleamine-2,3-dioxygenase-1 (IDO1)+ Paneth cells in the stem cell niche of intestinal crypts and tumors, which promoted immune escape of colorectal cancer (CRC). Ido1 expression in Paneth cells was strictly Stat1 dependent. Loss of IDO1+ Paneth cells in murine intestinal adenomas with tumor cell-specific Stat1 deletion had profound effects on the intratumoral immune cell composition. Patient samples and TCGA expression data suggested corresponding cells in human colorectal tumors. Thus, our data uncovered an immune escape mechanism of CRC and identify IDO1+ Paneth cells as a target for immunotherapy.

OXPHOS remodeling in high-grade prostate cancer involves mtDNA mutations and increased succinate oxidation.

Rewiring of energy metabolism and adaptation of mitochondria are considered to impact on prostate cancer development and progression. Here, we report on mitochondrial respiration, DNA mutations and gene expression in paired benign/malignant human prostate tissue samples. Results reveal reduced respiratory capacities with NADH-pathway substrates glutamate and malate in malignant tissue and a significant metabolic shift towards higher succinate oxidation, particularly in high-grade tumors. The load of potentially deleterious mitochondrial-DNA mutations is higher in tumors and associated with unfavorable risk factors. High levels of potentially deleterious mutations in mitochondrial Complex I-encoding genes are associated with a 70% reduction in NADH-pathway capacity and compensation by increased succinate-pathway capacity. Structural analyses of these mutations reveal amino acid alterations leading to potentially deleterious effects on Complex I, supporting a causal relationship. A metagene signature extracted from the transcriptome of tumor samples exhibiting a severe mitochondrial phenotype enables identification of tumors with shorter survival times.

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

It was highlighted that the original article [1] contained a typesetting mistake in the name of Noel Filipe da Cunha Carvalho de Miranda. This was incorrectly captured as Noel Filipe da Cunha Carvahlo de Miranda. It was also highlighted that in Fig. 3C the left panels Y-axis were cropped and in Fig. 5C, CD8 bar was cropped. This Correction article shows the correct Figs. 3 and 5. The original article has been updated.

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

We introduce quanTIseq, a method to quantify the fractions of ten immune cell types from bulk RNA-sequencing data. quanTIseq was extensively validated in blood and tumor samples using simulated, flow cytometry, and immunohistochemistry data.quanTIseq analysis of 8000 tumor samples revealed that cytotoxic T cell infiltration is more strongly associated with the activation of the CXCR3/CXCL9 axis than with mutational load and that deconvolution-based cell scores have prognostic value in several solid cancers. Finally, we used quanTIseq to show how kinase inhibitors modulate the immune contexture and to reveal immune-cell types that underlie differential patients' responses to checkpoint blockers.Availability: quanTIseq is available at http://icbi.at/quantiseq .

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study.

BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether deep convolutional neural networks (CNNs) can extract prognosticators directly from these widely available images. METHODS AND FINDINGS: We hand-delineated single-tissue regions in 86 CRC tissue slides, yielding more than 100,000 HE image patches, and used these to train a CNN by transfer learning, reaching a nine-class accuracy of >94% in an independent data set of 7,180 images from 25 CRC patients. With this tool, we performed automated tissue decomposition of representative multitissue HE images from 862 HE slides in 500 stage I-IV CRC patients in the The Cancer Genome Atlas (TCGA) cohort, a large international multicenter collection of CRC tissue. Based on the output neuron activations in the CNN, we calculated a "deep stroma score," which was an independent prognostic factor for overall survival (OS) in a multivariable Cox proportional hazard model (hazard ratio [HR] with 95% confidence interval [CI]: 1.99 [1.27-3.12], p = 0.0028), while in the same cohort, manual quantification of stromal areas and a gene expression signature of cancer-associated fibroblasts (CAFs) were only prognostic in specific tumor stages. We validated these findings in an independent cohort of 409 stage I-IV CRC patients from the "Darmkrebs: Chancen der Verhütung durch Screening" (DACHS) study who were recruited between 2003 and 2007 in multiple institutions in Germany. Again, the score was an independent prognostic factor for OS (HR 1.63 [1.14-2.33], p = 0.008), CRC-specific OS (HR 2.29 [1.5-3.48], p = 0.0004), and relapse-free survival (RFS; HR 1.92 [1.34-2.76], p = 0.0004). A prospective validation is required before this biomarker can be implemented in clinical workflows. CONCLUSIONS: In our retrospective study, we show that a CNN can assess the human tumor microenvironment and predict prognosis directly from histopathological images.

The Anatomical Location Shapes the Immune Infiltrate in Tumors of Same Etiology and Affects Survival.

PURPOSE: The tumor immune microenvironment determines clinical outcome. Whether the original tissue in which a primary tumor develops influences this microenvironment is not well understood. EXPERIMENTAL DESIGN: We applied high-dimensional single-cell mass cytometry [Cytometry by Time-Of-Flight (CyTOF)] analysis and functional studies to analyze immune cell populations in human papillomavirus (HPV)-induced primary tumors of the cervix (cervical carcinoma) and oropharynx (oropharyngeal squamous cell carcinoma, OPSCC). RESULTS: Despite the same etiology of these tumors, the composition and functionality of their lymphocytic infiltrate substantially differed. Cervical carcinoma displayed a 3-fold lower CD4:CD8 ratio and contained more activated CD8+CD103+CD161+ effector T cells and less CD4+CD161+ effector memory T cells than OPSCC. CD161+ effector cells produced the highest cytokine levels among tumor-specific T cells. Differences in CD4+ T-cell infiltration between cervical carcinoma and OPSCC were reflected in the detection rate of intratumoral HPV-specific CD4+ T cells and in their impact on OPSCC and cervical carcinoma survival. The peripheral blood mononuclear cell composition of these patients, however, was similar. CONCLUSIONS: The tissue of origin significantly affects the overall shape of the immune infiltrate in primary tumors.

NKG2A Blockade Potentiates CD8 T Cell Immunity Induced by Cancer Vaccines.

Tumor-infiltrating CD8 T cells were found to frequently express the inhibitory receptor NKG2A, particularly in immune-reactive environments and after therapeutic cancer vaccination. High-dimensional cluster analysis demonstrated that NKG2A marks a unique immune effector subset preferentially co-expressing the tissue-resident CD103 molecule, but not immune checkpoint inhibitors. To examine whether NKG2A represented an adaptive resistance mechanism to cancer vaccination, we blocked the receptor with an antibody and knocked out its ligand Qa-1b, the conserved ortholog of HLA-E, in four mouse tumor models. The impact of therapeutic vaccines was greatly potentiated by disruption of the NKG2A/Qa-1b axis even in a PD-1 refractory mouse model. NKG2A blockade therapy operated through CD8 T cells, but not NK cells. These findings indicate that NKG2A-blocking antibodies might improve clinical responses to therapeutic cancer vaccines.

Topography of cancer-associated immune cells in human solid tumors.

Lymphoid and myeloid cells are abundant in the tumor microenvironment, can be quantified by immunohistochemistry and shape the disease course of human solid tumors. Yet, there is no comprehensive understanding of spatial immune infiltration patterns ('topography') across cancer entities and across various immune cell types. In this study, we systematically measure the topography of multiple immune cell types in 965 histological tissue slides from N = 177 patients in a pan-cancer cohort. We provide a definition of inflamed ('hot'), non-inflamed ('cold') and immune excluded patterns and investigate how these patterns differ between immune cell types and between cancer types. In an independent cohort of N = 287 colorectal cancer patients, we show that hot, cold and excluded topographies for effector lymphocytes (CD8) and tumor-associated macrophages (CD163) alone are not prognostic, but that a bivariate classification system can stratify patients. Our study adds evidence to consider immune topographies as biomarkers for patients with solid tumors.

High-Throughput Screening of Combinatorial Immunotherapies with Patient-Specific In Silico Models of Metastatic Colorectal Cancer.

Solid tumors are rich ecosystems of numerous different cell types whose interactions lead to immune escape and resistance to immunotherapy in virtually all patients with metastatic cancer. Here, we have developed a 3D model of human solid tumor tissue that includes tumor cells, fibroblasts, and myeloid and lymphoid immune cells and can represent over a million cells over clinically relevant timeframes. This model accurately reproduced key features of the tissue architecture of human colorectal cancer and could be informed by individual patient data, yielding in silico tumor explants. Stratification of growth kinetics of these explants corresponded to significantly different overall survival in a cohort of patients with metastatic colorectal cancer. We used the model to simulate the effect of chemotherapy, immunotherapies, and cell migration inhibitors alone and in combination. We classified tumors according to tumor and host characteristics, showing that optimal treatment strategies markedly differed between these classes. This platform can complement other patient-specific ex vivo models and can be used for high-throughput screening of combinatorial immunotherapies.Significance: This patient-informed in silico tumor growth model allows testing of different cancer treatment strategies and immunotherapies on a cell/tissue level in a clinically relevant scenario. Cancer Res; 78(17); 5155-63. ©2018 AACR.

Targeting immune checkpoints potentiates immunoediting and changes the dynamics of tumor evolution.

The cancer immunoediting hypothesis postulates a dual role of the immune system: protecting the host by eliminating tumor cells, and shaping the tumor by editing its genome. Here, we elucidate the impact of evolutionary and immune-related forces on editing the tumor in a mouse model for hypermutated and microsatellite-instable colorectal cancer. Analyses of wild-type and immunodeficient RAG1 knockout mice transplanted with MC38 cells reveal that upregulation of checkpoint molecules and infiltration by Tregs are the major tumor escape mechanisms. Our results show that the effects of immunoediting are weak and that neutral accumulation of mutations dominates. Targeting the PD-1/PD-L1 pathway using immune checkpoint blocker effectively potentiates immunoediting. The immunoediting effects are less pronounced in the CT26 cell line, a non-hypermutated/microsatellite-instable model. Our study demonstrates that neutral evolution is another force that contributes to sculpting the tumor and that checkpoint blockade effectively enforces T-cell-dependent immunoselective pressure.

Intratumoral HPV16-Specific T Cells Constitute a Type I-Oriented Tumor Microenvironment to Improve Survival in HPV16-Driven Oropharyngeal Cancer.

Purpose: Human papillomavirus (HPV)-associated oropharyngeal squamous cell cancer (OPSCC) has a much better prognosis than HPV-negative OPSCC, and this is linked to dense tumor immune infiltration. As the viral antigens may trigger potent immunity, we studied the relationship between the presence of intratumoral HPV-specific T-cell responses, the immune contexture in the tumor microenvironment, and clinical outcome.Experimental Design: To this purpose, an in-depth analysis of tumor-infiltrating immune cells in a prospective cohort of 97 patients with HPV16-positive and HPV16-negative OPSCC was performed using functional T-cell assays, mass cytometry (CyTOF), flow cytometry, and fluorescent immunostaining of tumor tissues. Key findings were validated in a cohort of 75 patients with HPV16-positive OPSCC present in the publicly available The Cancer Genome Atlas database.Results: In 64% of the HPV16-positive tumors, type I HPV16-specific T cells were present. Their presence was not only strongly related to a better overall survival, a smaller tumor size, and less lymph node metastases but also to a type I-oriented tumor microenvironment, including high numbers of activated CD161+ T cells, CD103+ tissue-resident T cells, dendritic cells (DC), and DC-like macrophages.Conclusions: The viral antigens trigger a tumor-specific T-cell response that shapes a favorable immune contexture for the response to standard therapy. Hence, reinforcement of HPV16-specific T-cell reactivity is expected to boost this process. Clin Cancer Res; 24(3); 634-47. ©2017 AACRSee related commentary by Laban and Hoffmann, p. 505.

MicroRNAs and their role for T stage determination and lymph node metastasis in early colon carcinoma.

Worldwide, colon cancer is among the most common cancer entities. Understanding the molecular background is the key to enable accurate stage determination, which is crucial to assess optimal therapy options. The search for preoperative biomarkers is ongoing. In recent years, several studies have proposed a diagnostic and prognostic role for miRNAs in cancer. Aim of this study was to evaluate miRNA expression patterns correlating with tumor stage, especially lymph node metastasis, in primary colon carcinoma tissue. Screening was accomplished using GeneChip® miRNA v3.0 arrays (Thermo Fisher Scientific, Waltham, MA, USA) and validated via TaqMan® qPCR assays (Thermo Fisher Scientific, Waltham, MA, USA) to investigate miRNA expressions in 168 FFPE and 83 fresh frozen colon carcinoma samples. Regarding lymph node status, analyses displayed no significantly differential miRNA expression. Interestingly, divergent expression of miR-18a-5p, miR-20a-5p, miR-21-5p, miR-152-3p and miR-1973 was detected in stage pT1. Although miRNAs might not represent reliable biomarkers regarding lymph node metastasis status, they could support risk assessment in stage T1 tumors.