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The lack of multi-omics cancer datasets with extensive follow-up information hinders the identification of accurate biomarkers of clinical outcome. In this cohort study, we performed comprehensive genomic analyses on fresh-frozen samples from 348 patients affected by primary colon cancer, encompassing RNA, whole-exome, deep T cell receptor and 16S bacterial rRNA gene sequencing on tumor and matched healthy colon tissue, complemented with tumor whole-genome sequencing for further microbiome characterization. A type 1 helper T cell, cytotoxic, gene expression signature, called Immunologic Constant of Rejection, captured the presence of clonally expanded, tumor-enriched T cell clones and outperformed conventional prognostic molecular biomarkers, such as the consensus molecular subtype and the microsatellite instability classifications. Quantification of genetic immunoediting, defined as a lower number of neoantigens than expected, further refined its prognostic value. We identified a microbiome signature, driven by Ruminococcus bromii, associated with a favorable outcome. By combining microbiome signature and Immunologic Constant of Rejection, we developed and validated a composite score (mICRoScore), which identifies a group of patients with excellent survival probability. The publicly available multi-omics dataset provides a resource for better understanding colon cancer biology that could facilitate the discovery of personalized therapeutic approaches.

Sepsis is an aberrant systemic inflammatory response mediated by the acute activation of the innate immune system. Neutrophils are important contributors to the innate immune response that controls the infection, but harbour the risk of collateral tissue damage such as thrombosis and organ dysfunction. A better understanding of the modulations of cellular processes in neutrophils and other blood cells during sepsis is needed and can be initiated via transcriptomic profile investigations. To that point, the growing repertoire of publicly accessible transcriptomic datasets serves as a valuable resource for discovering and/or assessing the robustness of biomarkers. We employed systematic literature mining, reductionist approach to gene expression profile and empirical in vitro work to highlight the role of a Nudix hydrolase family member, NUDT16, in sepsis. The relevance and implication of the expression of NUDT16 under septic conditions and the putative functional roles of this enzyme are discussed.

Viruses are the second leading cause of cancer worldwide, and human papillomavirus (HPV)-associated head and neck cancers are increasing in incidence in the United States. HPV preferentially infects the crypts of the tonsils rather than the surface epithelium. The present study sought to characterize the unique microenvironment within the crypts to better understand the viral tropism of HPV to a lymphoid-rich organ. Laser-capture microdissection of distinct anatomic areas (crypts, surface epithelium, and germinal centers) of the tonsil, coupled with transcriptional analysis and multiparameter immunofluorescence staining demonstrated that the tonsillar crypts are enriched with myeloid populations that co-express multiple canonical and noncanonical immune checkpoints, including PD-L1, CTLA-4, HAVCR2 (TIM-3), ADORA2A, IDO1, BTLA, LGALS3, CDH1, CEACAM1, PVR, and C10orf54 (VISTA). The resident monocytes may foster a permissive microenvironment that facilitates HPV infection and persistence. Furthermore, the myeloid populations within HPV-associated tonsil cancers co-express the same immune checkpoints, providing insight into potential novel immunotherapeutic targets for HPV-associated head and neck cancers.

The purpose of this study was to evaluate the association between four distinct histopathological features, (1) tumor infiltrating lymphocytes, (2) mucinous differentiation, (3) tumor-stroma ratio, (4) tumor budding and two gene expression-based classifiers, (1) consensus molecular subtypes (CMS), (2) colorectal cancer intrinsic subtypes (CRIS). All four histopathological features were retrospectively scored on hematoxylin and eosin-stained sections of the most invasive part of the primary tumor of 218 stage II and III colon cancer patients from two independent cohorts (AMC-AJCC-90 and AC-ICAM). RNA-based CMS and CRIS assignments were independently obtained for all patients. Contingency tables were constructed and χ2 test was used to test for statistical significance. Odds ratios with 95% confidence intervals were calculated. The presence of tumor infiltrating lymphocytes and a mucinous phenotype (>50% mucinous surface area) were positively correlated with CMS1 (p < 0.001 and p = 0.008) and CRIS-A (p = 0.006 and p < 0.001). The presence of mucus (≥ 10%) was strongly associated with CMS3: mucus was present in 64.1% of all CMS3 tumors. Although a strong association between tumor-stroma ratio and CMS4 was established in this study (p = 0.006), still 32 out of 61 (52.5%) CMS4 tumors were scored as stroma-low, indicating that CMS4 tumors cannot be identified solely based on stromal content. Higher budding counts were seen in CMS4 and CRIS-B tumors (p = 0.045 and p = 0.046). No other associations of the measured parameters were seen for any of the other CRIS-subtypes. Our analysis revealed that histopathologic features have limited correlation with CMS and CRIS subtypes. Identification of distinct molecular subtypes using histopathology alone proved to be infeasible. Our findings also indicate that histopathologic features and molecular subtypes should be seen as distinct biomarkers. Combining both molecular and morphologic features could potentially improve patient stratification.

Motivation We previously described the construction and characterization of fixed reusable blood transcriptional module repertoires. More recently we released a third iteration (‘BloodGen3’ module repertoire) that comprises 382 functionally annotated modules and encompasses 14 168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires. Results We have developed and describe here an R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performed at the module-level, and to display the results as annotated fingerprint grid plots. A parallel workflow for computing module repertoire changes for individual samples rather than groups of samples is also available; these results are displayed as fingerprint heatmaps. An illustrative case is used to demonstrate the steps involved in generating blood transcriptome repertoire fingerprints of septic patients. Taken together, this resource could facilitate the analysis and interpretation of changes in blood transcript abundance observed across a wide range of pathological and physiological states. Availability and implementation The BloodGen3Module package and documentation are freely available from Github: https://github.com/Drinchai/BloodGen3Module. Supplementary information Supplementary data are available at Bioinformatics online.

BackgroundIt is becoming clear that tumor immune T cell infiltration and its functional orientation have substantial effect on cancer progression, influencing both response to therapy and prognosis. In this pan-cancer study, the previously described Immunologic Constant of Rejection (ICR) signature is used to define opposing immune phenotypes (i.e., immuneactive and immune-silent) across 31 different histologies. We systematically analyze the interconnections between the genetic programming of neoplasms and their immune orientation across different histologies, and the prognostic impact of such interplay. Moreover, we investigated the predictive value of ICR classification across various public datasets of immune checkpoint inhibition therapy.MethodsRNA-seq data of samples from a total of 9,282 patient tumor samples representing 31 cancer types were obtained from The Cancer Genome Atlas (TCGA). We classified each cancer type based on the expression of the ICR gene signature. Oncogenic pathway gene set enrichment and mutational status were analyzed in relation to ICR phenotypes. To explore whether tumorintrinsic attributes associate with the prognostic value of ICR across cancers, we compared mutational load, oncogenic alterations and expression of oncogenic pathways between cancer types using an integrative bioinformatic pipeline.ResultsOur analyses identified a distinct prognostic connotation of ICR depending on cancer histology. We identified several oncogenic pathways whose enrichment inversely correlated with ICR in multiple tumor types. We found several cancer specific pathways that were differentially enriched between tumors in which ICR had a prognostic impact versus the ones in which ICR did not bear any prognostic connotation such as proliferation and TGF-beta signaling. Importantly, this conditional impact of ICR was also validated in the context of immune checkpoint inhibition treatment.ConclusionsWe identified tumor-intrinsic attributes that correlate with immune phenotypes and potentially influence their development. In addition, a relationship was observed between the enrichment of oncogenic pathways and the prognostic significance of the ICR and its predictive value for patients treated with anti-CTLA4 immune checkpoint inhibition. Such information can be used to prioritize potential candidates for therapies aimed at converting immune-silent into immuneactive tumors and to refine stratification algorithms.

The best current biomarker strategies for predicting response to immune checkpoint inhibitor (ICI) therapy fail to account for interpatient variability in response rates. The histologic tumor–stroma ratio (TSR) quantifies intratumoral stromal content and was recently found to be predictive of response to neoadjuvant therapy in multiple cancer types. In the current work, we predicted the likelihood of ICI therapy responsivity of 335 therapy-naive colon adenocarcinoma tumors from The Cancer Genome Atlas, using bioinformatics approaches. The TSR was scored on diagnostic tissue slides, and tumor-infiltrating immune cells (TIICs) were inferred from transcriptomic data. Tumors with high stromal content demonstrated increased T regulatory cell infiltration (p = 0.014) but failed to predict ICI therapy response. Consequently, we devised a hybrid tumor microenvironment classification of four stromal categories, based on histological stromal content and transcriptomic-deconvoluted immune cell infiltration, which was associated with previously established transcriptomic and genomic biomarkers for ICI therapy response. By integrating these biomarkers, stroma-low/immune-high tumors were predicted to be most responsive to ICI therapy. The framework described here provides evidence for expansion of current histological TIIC quantification to include the TSR as a novel, easy-to-use biomarker for the prediction of ICI therapy response.

A cancer immune phenotype characterized by an active T-helper 1 (Th1)/cytotoxic response is associated with responsiveness to immunotherapy and favorable prognosis across different tumors. However, in some cancers, such an intratumoral immune activation does not confer protection from progression or relapse. Defining mechanisms associated with immune evasion is imperative to refine stratification algorithms, to guide treatment decisions and to identify candidates for immune-targeted therapy. Molecular alterations governing mechanisms for immune exclusion are still largely unknown. The availability of large genomic datasets offers an opportunity to ascertain key determinants of differential intratumoral immune response. We follow a network-based protocol to identify transcription regulators (TRs) associated with poor immunologic antitumor activity. We use a consensus of four different pipelines consisting of two state-of-the-art gene regulatory network inference techniques, regularized gradient boosting machines and ARACNE to determine TR regulons, and three separate enrichment techniques, including fast gene set enrichment analysis, gene set variation analysis and virtual inference of protein activity by enriched regulon analysis to identify the most important TRs affecting immunologic antitumor activity. These TRs, referred to as master regulators (MRs), are unique to immune-silent and immune-active tumors, respectively. We validated the MRs coherently associated with the immune-silent phenotype across cancers in The Cancer Genome Atlas and a series of additional datasets in the Prediction of Clinical Outcomes from Genomic Profiles repository. A downstream analysis of MRs specific to the immune-silent phenotype resulted in the identification of several enriched candidate pathways, including NOTCH1, TGF-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\beta $\end{document}, Interleukin-1 and TNF-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\alpha $\end{document} signaling pathways. TGFB1I1 emerged as one of the main negative immune modulators preventing the favorable effects of a Th1/cytotoxic response.

BackgroundImmunotherapy is quickly coming to the forefront of cancer treatment; however, the implementation of immunotherapy in solid pediatric cancers, which classically display a low mutational load, is hindered by insufficient understanding of the determinants of cancer immune responsiveness in children. In order to better understand tumor-host interplay, we sought to characterize solid pediatric cancers based on immunological parameters using analytes extracted from gene expression data.MethodsWe used RNAseq data from the publicly available TARGET studies for five pediatric solid tumor types (408 patients): Wilms tumor (WT), neuroblastoma (NBL), osteosarcoma (OS), clear cell sarcoma of the kidney (CCSK) and rhabdoid tumor of the kidney (RT). We assessed the performance of previously identified immune signatures like the Immunologic Constant of Rejection (ICR), which captures an active Th1/cytotoxic response associated with favorable prognosis and responsiveness to immunotherapy. We also performed gene set enrichment analysis (ssGSEA) and clustering, using more than 100 immune signatures to define immune subtypes in pediatric tumors and compared the overall survival across subtypes. The expression of immune checkpoints and enrichment of oncogenic pathways were also assessed across the immune subtypes.ResultsThe five tumor types showed distinct ICR score distributions. A higher ICR score was associated with better survival in OS and NBL-HR-MYCN_NA, but with poorer survival in WT. The clustering of immune signatures revealed the same five principal modules observed in adult solid tumors: Wound Healing, TGF-B signaling, IFN-G signaling, Macrophages, and Lymphocytes. These modules clustered pediatric patients into six immune subtypes (S1-S6) with distinct survival outcomes. The S2 cluster showed the best overall survival and was characterized by low enrichment of the wound healing signature, high Th1, low Th2. Conversely, cluster S4 showed the worst survival and highest enrichment of wound healing signature, low Th1, and high Th2. Furthermore, the upregulation of the WNT/Beta-catenin pathway is associated with unfavorable outcomes and lack of T-cell infiltration in OS.ConclusionsWe demonstrated that extracranial solid pediatric tumors could be classified according to their immune disposition, unveiling similarity with adults’ tumors. Immunological parameters might be explored to refine diagnostic and prognostic biomarkers and to identify potential immune-responsive tumors.

Understanding the contribution of the host’s genetic background to cancer immunity may lead to improved stratification for immunotherapy and to the identification of novel therapeutic targets. We investigated the effect of common and rare germline variants on 139 well-defined immune traits in ∼9000 cancer patients enrolled in TCGA. High heritability was observed for estimates of NK cell and T cell subset infiltration and for interferon signaling. Common variants of IFIH1, TMEM173 (STING1), and TMEM108 were associated with differential interferon signaling and variants mapping to RBL1 correlated with T cell subset abundance. Pathogenic or likely pathogenic variants in BRCA1 and in genes involved in telomere stabilization and Wnt-β-catenin also acted as immune modulators. Our findings provide evidence for the impact of germline genetics on the composition and functional orientation of the tumor immune microenvironment. The curated datasets, variants, and genes identified provide a resource toward further understanding of tumor-immune interactions. We are grateful to the Society for Immunotherapy of Cancer (SITC) for the logistical support of the investigator meeting within the SITC Cancer Immune Responsiveness Workshop (San Francisco CA, US, April 2018; Houston, TX, US, May 2019). We are also grateful to Noah Zaitlen and Andy Dahl for useful discussions on heritability interaction analyses. This work was funded in part by the National Institutes of Health R01CA227466 and K24CA169004 to EZ and T32CA221709 postdoctoral fellowship to RWS, Qatar National Research Fund (QNRF) NPRP11S-0121-180351 grant and the Sidra Precision Medicine Program internal grant (SDR100035 and SDR400023) to DB, Associazione Italiana per la Ricerca sul cancro (AIRC) grant IG2018-21846 to MC, the Cancer Research Institute funding to VT, and the Fundació Bancaria La Caixa, a La Caixa Junior Leader Fellowship (LCF/BQ/PI18/11630003) to EP-P.

Introduction Natural killer (NK) cells and natural killer T (NKT) cells are implicated in the development and progression of colorectal cancer (CRC). Tumor cells express NK cell receptor ligands that modulate their function. This study aimed to investigate the expression of such ligands in CRC in relation to the phenotype of circulating NK- and NKT cells, and clinical outcome. Methods Primary tumor tissues were analyzed for protein expression of NK cell ligands using immunohistochemistry with automated image analysis in a cohort of 78 CRC patients. For 24 of the 78 patients, RNA expression of NK cell ligands was analyzed in primary tumor tissue using RNA sequencing. Receptor expression on circulating NK- and NKT cells was previously measured by us in 71 of the 78 patients using flow cytometry. Results High Proliferating Cell Nuclear Antigen (PCNA) protein expression in the primary tumor associated with shorter disease-free survival (DFS) of CRC patients (P = 0.026). A trend was observed towards shorter DFS in CRC patients with above-median galectin-3 protein expression in the primary tumor (P = 0.055). High protein expression of galectin-3, CD1d, and human leukocyte antigen (HLA) class I, and high RNA expression of UL16-binding protein (ULBP)-1, -2, and -5, and HLA-E in the tumor tissue correlated with low expression of the corresponding receptors on circulating NK- or NKT cells (P Conclusions Galectin-3 and PCNA expression in the primary tumor may be prognostic biomarkers in CRC patients. Furthermore, our results suggest that NK cell receptor ligands expressed by tumor cells may modulate the phenotype of circulating NK- and NKT cells, and facilitate immune escape of metastasizing cells.

Background It is now well established that the immune system has a substantial role in controlling cancer growth and progression. Immunotherapy is quickly coming to the forefront of cancer treatment,however the implementation of immunotherapy in pediatric solid cancers, which classically display a low mutational load, is hindered by insufficient understanding of the determinants of cancer immune responsiveness in children. In order to better understand tumor-host interplay, we sought to characterize solid pediatric cancers based on immunological parameters(1)using analytes extracted from gene expression data. Methods We performed single sample GeneSet Enrichment Analysis for 105 immune signatures previously described on 5pediatric tumors (410patients) from TARGET dataset(1) to identify coherent signature modules. Then we clustered samples according to representative signatures (1)and compared survival across clusters. We completed the analysis by analyzing the enrichment of immune subpopulations and the expression of the immune checkpoints. The degree of dysregulation of oncogenic pathways was also assessed. The performance of previously identified immune signatures as the Immunologic Constant of Rejection(2,3),which captures an active Th1/cytotoxic response associated with favorable prognosis and responsiveness to immunotherapy, was also checked within each tumor subtype. Results We found 5main modules, in agreement with results obtained in adult solid tumors:Wound Healing,TGF-B signaling,IFN-G signaling, Macrophages and Lymphocytes (figure 1). These 5 modules clustered pediatric patients into 6 immune subtypes S1-S6 with distinct survival (S2vsS4,p=0.0044, adjusted for cancer type),S2 cluster has the best overall survival and characterized by low enrichment of wound healing signature, high Th1, low Th2 and high expression of HLA 1 and HLA2, while the opposite holds true for cluster S4 with the worst survival and highest enrichment of wound healing signature, high Th2, and low Th1.The S6 cluster is characterized by highest enrichment of lymphocyte signature, the highest expression of immune checkpoints accompanied by elevated expression of exhaustion markers, and an unpolarized immune response with high abundance of macrophages. Additionally, pan-cancer, the upregulation of WNT-Beta catenin pathway is associated with adverse outcome and lack of T-cell infiltration. In the per-cancer analysis, ICR is associated with better survival in osteosarcoma and with worse survival in Wilms’ tumors,similarly with what observed in adult kidney’s cancer despite the different embryological origin. Conclusions We demonstrated that pediatric solid cancers can be classified according to their immune disposition, unveiling unexpected similarity with adults’ tumors.Immunological parameters might be explored to refine diagnostic and prognostic biomarkers and to identify potential immune responsive tumors. This is the first pan-cancer immunogenomic analysis in children. References Thorsson V, Gibbs DL, Brown SD, et al. The immune landscape of cancer. Immunity 2018. 48(4):812–830. Roelands J, Hendrickx W, et al. ‘Oncogenic states dictate the prognostic and predictive connotations of intratumoral immune response.’ Journal for immunotherapy of cancer 2020;vol. 8:1. Galon J, Angell HK, Bedognetti D, Marincola FM. The continuum of cancer immunosurveillance: prognostic, predictive, and mechanistic signatures. Immunity 2013;39:11–26.

Transcriptional modules have been widely used for the analysis, visualization and interpretation of transcriptome data. We have previously described the construction and characterization of generic and reusable blood transcriptional module repertoires. The third and latest version that we have recently made available comprises 382 functionally annotated gene sets (modules) and encompasses 14,168 transcripts. We developed R scripts for performing module repertoire analyses and custom fingerprint visualization. These are made available here along with detailed descriptions. An illustrative public transcriptome dataset and corresponding intermediate output files are also included as supplementary material. Briefly, the steps involved in module repertoire analysis and visualization include: First, the annotation of the gene expression data matrix with module membership information. Second, running of statistical tests to determine for each module the proportion of its constitutive genes which are differentially expressed. Third, the results are expressed “at the module level” as percent of genes increased or decreased and plotted in a fingerprint grid format. A parallel workflow has been developed for computing module repertoire changes for individual samples rather than groups of samples. Such results are plotted in a heatmap format. The use case that is presented illustrates the steps involved in the generation of blood transcriptome repertoire fingerprints of septic patients at both group and individual levels.

The expression of Annexin A3 (ANXA3), a member of a family of calcium‐binding proteins, is restricted to neutrophils. Its abundance is increased in septic patients, yet the functional relevance of ANXA3 in this context remains unknown. Upon reviewing evidence from public transcriptome repositories and the literature, we hypothesize that during sepsis ANXA3 could mediate neutrophils microbicidal activity while also prolonging their survival, and thus also possibly contributing to organ damage., Summary According to publicly available transcriptome datasets, the abundance of Annexin A3 (ANXA3) is robustly increased during the course of sepsis; however, no studies have examined the biological significance or clinical relevance of ANXA3 in this pathology. Here we explored this interpretation gap and identified possible directions for future research. Based on reference transcriptome datasets, we found that ANXA3 expression is restricted to neutrophils, is upregulated in vitro after exposure to plasma obtained from septic patients, and is associated with adverse clinical outcomes. Secondly, an increase in ANXA3 transcript abundance was also observed in vivo, in the blood of septic patients in multiple independent studies. ANXA3 is known to mediate calcium‐dependent granules–phagosome fusion in support of microbicidal activity in neutrophils. More recent work has also shown that ANXA3 enhances proliferation and survival of tumour cells via a Caspase‐3‐dependent mechanism. And this same molecule is also known to play a critical role in regulation of apoptotic events in neutrophils. Thus, we posit that during sepsis ANXA3 might either play a beneficial role, by facilitating microbial clearance and resolution of the infection; or a detrimental role, by prolonging neutrophil survival, which is known to contribute to sepsis‐mediated organ damage.

BackgroundAn immune active cancer phenotype typified by a T helper 1 (Th-1) immune response has been associated with increased responsiveness to immunotherapy and favorable prognosis in some but not all cancer types. The reason of this differential prognostic connotation remains unknown.MethodsTo explore the contextual prognostic value of cancer immune phenotypes, we applied a multimodal pan-cancer analysis among 31 different histologies (9282 patients), encompassing immune and oncogenic transcriptomic analysis, mutational and neoantigen load and copy number variations.ResultsWe demonstrated that the favorable prognostic connotation conferred by the presence of a Th-1 immune response was abolished in tumors displaying specific tumor-cell intrinsic attributes such as high transforming growth factor-beta (TGF-β) signaling and low proliferation capacity. This observation was independent of mutation rate. We validated this observation in the context of immune checkpoint inhibition. WNT-βcatenin, barrier molecules, Notch, hedgehog, mismatch repair, telomerase activity and AMPK signaling were the pathways most coherently associated with an immune silent phenotype together with mutations of driver genes includingIDH1/2, FOXA2, HDAC3, PSIP1, MAP3K1, KRAS, NRAS, EGFR, FGFR3, WNT5AandIRF7.ConclusionsThis is the first systematic study demonstrating that the prognostic and predictive role of a bona fide favorable intratumoral immune response is dependent on the disposition of specific oncogenic pathways. This information could be used to refine stratification algorithms and prioritize hierarchically relevant targets for combination therapies.

BackgroundColorectal cancer (CRC) development is accompanied by the gradual accumulation of genetic alterations in epithelial cells of the colon and rectum.1 2 The paradigm of the adenoma-carcinoma sequence was originally centered around cancer cells; however, it is now clear that the tumor microenvironment plays a substantial role in cancer progression and patient outcome.3 In recent years, technologies have evolved rapidly, allowing the multiplexed quantification of gene expression while preserving spatial context.4 Furthermore, some spatial transcriptomic technologies also allow the parallel interrogation of different cell populations in the tumor microenvironment. Here, we performed digital spatial profiling on early-stage CRC samples to elucidate the biological processes that are at the basis of malignant transformation and to identify novel therapeutic targets and (immune) biomarkers.MethodsEndoscopically resected early-stage CRC samples were obtained at Leiden University Medical Center. In total, 144 areas of illumination were interrogated with GeoMx digital spatial profiling using the Cancer Transcriptome Atlas (>1,800 genes). In each of eight samples, nine regions of interest with different levels of cancer progression were selected, including normal epithelium, transition areas, low-, and high-grade dysplasia, and invasive carcinoma (figure 1A). We segmented each region based on cytokeratin and vimentin protein expression (figure 1B). Immunohistochemical detection was performed on these samples and 26 additional samples to validate targets associated with disease progression.ResultsDigital spatial profiling allowed us to dissect transcriptional alterations in epithelial and stromal fractions between different regions from healthy tissue, different degrees of dysplasia, and cancer. Gene expression data revealed a clear separation of profiled areas by histologic category. Interestingly, gene expression features in the stromal compartment provided a better data-driven separation of histologic categories than the epithelial fraction (figure 1C). Substantial changes in immune-related pathways were identified, including differential expression of specific immunomodulators. We validated the expression of several candidate biomarkers/targets that demonstrated consistent alterations from normal tissue to cancer by immunohistochemistry. Several proteins were identified that could clearly discriminate benign from malignant tissue.ConclusionsWe here demonstrated the unique biological insights that are provided by spatial examination of early-stage CRC by digital spatial profiling. We identified specific genes that were altered during CRC tumorigenesis, in epithelial and stromal/immune fractions. Furthermore, our results indicate an essential role for innate immunity in colorectal cancer onset and progression. The genes identified by this approach could potentially serve as novel biomarkers and targets for early interception or prevention of CRC development.AcknowledgementsThis work was supported by the European Research Council (ERC) Starting grant awarded to Dr. Noel F. de Miranda and the Stichting Management Apothekers en de Gezondheidszorg (STIMAG) Research grant awarded to Jessica Roelands.Trial RegistrationN/AReferencesFearon ER, Vogelstein B. A genetic model for colorectal tumorigenesis. Cell 1990;61(5):759–767. doi: 10.1016/0092-8674(90)90186-I.Nowell PC. The clonal evolution of tumor cell populations. Science 1976;194(4260):23–28. doi: 10.1126/science.959840.Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011;144(5):646–674. doi: 10.1016/j.cell.2011.02.013.Merritt CR, et al. Multiplex digital spatial profiling of proteins and RNA in fixed tissue. Nat Biotechnol 2020;38(5):586–599. doi: 10.1038/s41587-020-0472-9.Ethics ApprovalThis study was approved by the METC Leiden-Den Haag-Delft (protocol B20.039). Patient samples were anonymised and handled according to the medical ethical guidelines described in the Code of Conduct for Proper Secondary Use of Human Tissue of the Dutch Federation of Biomedical Scientific Societies.Abstract 673 Figure 1Transcriptional alterations in early-stage colorectal cancer. Digital spatial profiling defines transcriptional alterations in early-stage colorectal cancer. (A) Schematic representation of an early-stage CRC sample containing regions with different levels of cancer progression, including normal epithelium, transition areas, low-, and high-grade dysplasia, and invasive carcinoma. (B) Segmentation based immunofluorescent labelling with antibodies directed against PanCK and Vimentin in one of the early-stage CRC samples. Artificial overlay of implemented segmentation is indicated for each ROI, visualizing Vimentin+ (pink) and PanCK+ (orange) segments. Inset: higher magnification of an individual ROI. (C) Dimension reduction of expression of all quantified genes by t-Distributed Stochastic Neighbor Embedding (tSNE). tSNE plots are annotated by segment (left), and histological region (right).

With the advent of checkpoint inhibition, immunotherapy has revolutionized the clinical management of several cancers, but has demonstrated limited efficacy in mammary carcinoma. Transcriptomic profiling of cancer samples defined distinct immunophenotypic categories characterized by different prognostic and predictive connotations. In breast cancer, genomic alterations leading to the dysregulation of mitogen-activated protein kinase (MAPK) pathways have been linked to an immune-silent phenotype associated with poor outcome and treatment resistance. These aberrations include mutations of MAP3K1 and MAP2K4, amplification of KRAS, BRAF, and RAF1, and truncations of NF1. Anticancer therapies targeting MAPK signaling by BRAF and MEK inhibitors have demonstrated clear immunologic effects. These off-target properties could be exploited to convert the immune-silent tumor phenotype into an immune-active one. Preclinical evidence supports that MAPK-pathway inhibition can dramatically increase the efficacy of immunotherapy. In this review, we provide a detailed overview of the immunomodulatory impact of MAPK-pathway blockade through BRAF and MEK inhibitions. While BRAF inhibition might be relevant in melanoma only, MEK inhibition is potentially applicable to a wide range of tumors. Context-dependent similarities and differences of MAPK modulation will be dissected, in light of the complexity of the MAPK pathways. Therapeutic strategies combining the favorable effects of MAPK-oriented interventions on the tumor microenvironment while maintaining T-cell function will be presented. Finally, we will discuss recent studies highlighting the rationale for the implementation of MAPK-interference approaches in combination with checkpoint inhibitors and immune agonists in breast cancer.

Background It is now clear that the immune system has a substantial effect on the progression of colon cancer. Typically, an immune response defined by a polarized Th1 phenotype, characterized by expression of CXCR3/CCR5 chemokine-receptor ligands, activation of interferon stimulated genes and production of cytotoxic molecules by effector immune cells, has been associated with immune-mediated tumor rejection. We have previously introduced a gene signature, called Immunology Constant of Rejection (ICR), that reflects these immune components. This signature was able to differentiate quite well the patients with an active immune environment and improved survival vs those who did not display this phenotype. This phenomenon although expected based on other immune infiltration studies could not be observed in the TCGA colon cancer cohort, likely due to the per protocol exclusion of samples with low purity. To gain more insight in the underlying mechanism of cancer tissue rejection by the immune system, we build an extensive data repository from high quality colon cancer samples unbiased for tumor purity. Methods RNA and DNA were isolated from fresh frozen tissue samples of a cohort of 366 colon cancer patients collected over the last decade at the University of Leiden, Netherlands. Tissue sections flanking the corresponding samples were hematoxylin and eosin stained. RNA-seq (HiSeq4000) data was obtained using HISAT2 alignment and quantile normalization of the GC corrected raw counts. Whole Exome Sequencing (>100X) for our cohort for normal and cancer tissue respectively. T-cell repertoire profiling of 150 tumors was achieved using Adaptive immunoSEQ. Tumor immune phenotype classification was done using unsupervised consensus clustering based on the expression of ICR genes. Results Our preliminary data supports a positive impact of ICR gene expression in our colon cancer cohort: patients in ICR High cluster had a significantly improved survival compared to other clusters. Conclusions This newly generated immune centric NGS dataset, generated in Qatar, will is used to elucidate the genetic determinants of immune phenotype in colon cancer and the relationship of the immune phenotype, the tumors genetics the TCR diversity. Legal entity responsible for the study Sidra Medicine. Funding Qatar National Research Fund. Disclosure All authors have declared no conflicts of interest.

A potential role for the long-chain acyl-CoA synthetase family member 1 (ACSL1) in the immunobiology of sepsis was explored during a hands-on training workshop. Participants first assessed the robustness of the potential gap in biomedical knowledge identified via an initial screen of public transcriptome data and of the literature associated with ACSL1. Increase in ACSL1 transcript abundance during sepsis was confirmed in several independent datasets. Querying the ACSL1 literature also confirmed the absence of reports associating ACSL1 with sepsis. Inferences drawn from both the literature (via indirect associations) and public transcriptome data (via correlation) point to the likely participation of ACSL1 and ACSL4, another family member, in inflammasome activation in neutrophils during sepsis. Furthermore, available clinical data indicate that levels of ACSL1 and ACSL4 induction was significantly higher in fatal cases of sepsis. This denotes potential translational relevance and is consistent with involvement in pathways driving potentially deleterious systemic inflammation. Finally, while ACSL1 expression was induced in blood in vitro by a wide range of pathogen-derived factors as well as TNF, induction of ACSL4 appeared restricted to flagellated bacteria and pathogen-derived TLR5 agonists and IFNG. Taken together, this joint review of public literature and omics data records points to two members of the acyl-CoA synthetase family potentially playing a role in inflammasome activation in neutrophils. Translational relevance of these observations in the context of sepsis and other inflammatory conditions remain to be investigated.

Steps involved in reductionist investigation approaches can be imitated using public transcriptome datasets as source of training material. In the present report trainees explored an apparent gap in biological knowledge for FAM129A (family with sequence similarity 129 member A). Elevated abundance of FAM129A transcripts were observed in a transcriptome dataset where neutrophils were exposed in vitro to plasma of patients with sepsis. However, no literature linking FAM129A and either neutrophils, sepsis or inflammation could be identified. Additional datasets were selected to independently validate this initial observation and further explore differential expression of FAM129A in the context of sepsis studies. Follow on investigations carried out at the bench confirmed restriction of the expression of FAM129A protein at the surface of circulating blood neutrophils and monocytes. A potential role for FAM129A in neutrophil survival was inferred from profiling of literature associated with FAM129A, which remains to be investigated in further follow on investigations.

A hands-on training workshop was devised with omics data used as source material to emulate reductionist investigation approaches. NUDT16, a member of the Nudix hydrolase family was selected as a candidate gene on the basis of: 1) it being upregulated in neutrophils exposed in vitro to serum of patients with sepsis, AND 2) the absence of overlap between the NUDT16 and sepsis, inflammation or neutrophil literature. We next sought to corroborate the initial finding in five public transcriptome sepsis datasets in which NUDT16 transcript levels were measured. In each of these dataset NUDT16 transcript abundance was found to be significantly increased in septic patients in vivo in comparison to uninfected controls. Next, biological concepts were extracted from the NUDT16 literature. The main concepts to emerge from profiling this literature were RNA decapping, inosine triphosphate, and inosine diphosphate. Through these concepts, indirect links could be established between NUDT16 and the sepsis/inflammation/neutrophil literature. A potential role for NUDT16 could, in turn, be inferred in the degradation of mRNAs in activated neutrophils. Follow on experiments that would be necessary in order to further explore such inference are discussed.

Developing the skills needed to effectively search and extract information from biomedical literature is essential for early-career researchers. It is, for instance, on this basis that the novelty of experimental results, and therefore publishing opportunities, can be evaluated. Given the unprecedented volume of publications in the field of biomedical research, new systematic approaches need to be devised and adopted for the retrieval and curation of literature relevant to a specific theme. Here we describe a hands-on training curriculum aimed at retrieval, profiling, and visualization of literature associated with a given topic. This curriculum was implemented in a workshop in January 2021. We provide supporting material and step-by-step implementation guidelines with the ISG15 gene literature serving as an illustrative use case. Through participation in such a workshop, trainees can learn: 1) to build and troubleshoot PubMed queries in order to retrieve the literature associated with a gene of interest; 2) to identify key concepts relevant to given themes (such as cell types, diseases, and biological processes); 3) to measure the prevalence of these concepts in the gene literature; 4) to extract key information from relevant articles, and 5) to develop a background section or summary on the basis of this information. Finally, trainees can learn to consolidate the structured information captured through this process for presentation via an interactive web application.

The balance between immune-stimulatory and immune-suppressive mechanisms in the tumour microenvironment is associated with tumour rejection and can predict the efficacy of immune checkpoint-inhibition therapies. We consider the observed differences between the transcriptional programmes associated with cancer types where the levels of immune infiltration predict a favourable prognosis versus those in which the immune infiltration predicts an unfavourable prognosis and defined a score named Mediators of Immune Response Against Cancer in soLid microEnvironments (MIRACLE). MIRACLE deconvolves T cell infiltration, from inhibitory mechanisms, such as TGFβ, EMT and PI3Kγ signatures. Our score outperforms current state-of-the-art immune signatures as a predictive marker of survival in TCGA (n = 9305, HR: 0.043, p value: 6.7 × 10−36). In a validation cohort (n = 7623), MIRACLE predicts better survival compared to other immune metrics (HR: 0.1985, p value: 2.73 × 10−38). MIRACLE also predicts response to checkpoint-inhibitor therapies (n = 333). The tumour-intrinsic factors inversely associated with the reported score such as EGFR, PRKAR1A and MAP3K1 are frequently associated with immune-suppressive phenotypes. The association of cancer outcome with the level of infiltrating immune cells is mediated by the balance of activatory and suppressive factors. MIRACLE accounts for this balance and predicts favourable cancer outcomes.

The evolutionary selection of malaria parasites within individual hosts is an important factor in the emergence of drug resistance but is still not well understood. We have examined the selection process for drug resistance in the mouse malaria agent Plasmodium berghei and compared the dynamics of the selection for atovaquone and pyrimethamine. Resistance to these drugs has been shown to be associated with genetic lesions in the dihydrofolate reductase gene in the case of pyrimethamine and in the mitochondrial cytochrome b gene for atovaquone. A mouse malaria model for the selection of drug resistance, based on repeated incomplete treatment (RICT) with a therapeutic dose of antimalarial drugs, was established. The number of treatment cycles for the development of stable resistance to atovaquone (2.47 ± 0.70; n = 19) was found to be significantly lower than for pyrimethamine (5.44 ± 1.46; n = 16; P < 0.0001), even when the parental P. berghei Leiden strain was cloned prior to the resistance selection. Similar results were obtained with P. berghei Edinburgh. Mutational changes underlying the resistance were identified to be S110N in dihydrofolate reductase for pyrimethamine and Y268N, Y268C, Y268S, L271V-K272R, and G280D in cytochrome b for atovaquone. These results are consistent with the rate of mitochondrial DNA mutation being higher than that in the nucleus and suggest that mutation leading to pyrimethamine resistance is not a rare event.

The immune system has a substantial effect on colorectal cancer (CRC) progression. Additionally, the response to immunotherapeutics and conventional treatment options (e.g., chemotherapy, radiotherapy and targeted therapies) is influenced by the immune system. The molecular characterization of colorectal cancer (CRC) has led to the identification of favorable and unfavorable immunological attributes linked to clinical outcome. With the definition of consensus molecular subtypes (CMSs) based on transcriptomic profiles, multiple characteristics have been proposed to be responsible for the development of the tumor immune microenvironment and corresponding mechanisms of immune escape. In this review, a detailed description of proposed immune phenotypes as well as their interaction with different therapeutic modalities will be provided. Finally, possible strategies to shift the CRC immune phenotype towards a reactive, anti-tumor orientation are proposed per CMS.