Immunotherapy-activated T cells recruit and skewlate-stage activated M1-like macrophagesthat are critical for therapeutic efficacy.

Total tumor clearance through immunotherapy is associated with a fully coordinated innate and adaptive immune response, but knowledge on the exact contribution of each immune cell subset is limited. We show that therapy-induced intratumoral CD8+ T cells recruited and skewed late-stage activated M1-like macrophages, which were critical for effective tumor control in two different murine models of cancer immunotherapy. The activated CD8+ T cells summon these macrophages into the tumor and their close vicinity via CCR5 signaling. Exposure of non-polarized macrophages to activated T cell supernatant and tumor lysate recapitulates the late-stage activated and tumoricidal phenotype in vitro. The transcriptomic signature of these macrophages is also detected in a similar macrophage population present in human tumors and coincides with clinical response to immune checkpoint inhibitors. The requirement of a functional co-operation between CD8+ T cells and effector macrophages for effective immunotherapy gives warning to combinations with broad macrophage-targeting strategies.

The C-type lectin DCIR contributes to the immune response and pathogenesis of colorectal cancer.

Development and progression of malignancies are accompanied and influenced by alterations in the surrounding immune microenvironment. Understanding the cellular and molecular interactions between immune cells and cancer cells has not only provided important fundamental insights into the disease, but has also led to the development of new immunotherapies. The C-type lectin Dendritic Cell ImmunoReceptor (DCIR) is primarily expressed by myeloid cells and is an important regulator of immune homeostasis, as demonstrated in various autoimmune, infectious and inflammatory contexts. Yet, the impact of DCIR on cancer development remains largely unknown. Analysis of available transcriptomic data of colorectal cancer (CRC) patients revealed that high DCIR gene expression is associated with improved patients' survival, immunologically "hot" tumors and high immunologic constant of rejection, thus arguing for a protective and immunoregulatory role of DCIR in CRC. In line with these correlative data, we found that deficiency of DCIR1, the murine homologue of human DCIR, leads to the development of significantly larger tumors in an orthotopic murine model of CRC. This phenotype is accompanied by an altered phenotype of tumor-associated macrophages (TAMs) and a reduction in the percentage of activated effector CD4+ and CD8+ T cells in CRC tumors of DCIR1-deficient mice. Overall, our results show that DCIR promotes antitumor immunity in CRC, making it an attractive target for the future development of immunotherapies to fight the second deadliest cancer in the world.

Location matters: spatial dynamics of tumor-infiltrating T cell subsets is prognostic in colon cancer.

Background: Colon cancer is a heterogeneous disease and consists of various molecular subtypes. Despite advances in high-throughput expression profiling, limitations remain in predicting clinical outcome and assigning specific treatment to individual cases. Tumor-immune interactions play a critical role, with tumors that activate the immune system having better outcome for the patient. The localization of T cells within tumor epithelium, to enable direct contact, is essential for antitumor function, but bulk DNA/RNA sequencing data lacks spatial distribution information. In this study, we provide spatial T cell tumor distribution and connect these data with previously determined genomic data in the AC-ICAM colon cancer patient cohort. Methods: Colon cancer patients (n=90) with transcriptome data available were selected. We used a custom multiplex immunofluorescence assay on colon tumor tissue sections for quantifying T cell subsets spatial distribution in the tumor microenvironment, in terms of cell number, location, mutual distance, and distance to tumor cells. Statistical analyses included the previously determined Immunologic Constant of Rejection (ICR) transcriptome correlation and patient survival, revealing potential prognostic value in T cell spatial distribution. Results: T cell phenotypes were characterized and CD3+CD8-FoxP3- T cells were found to be the predominant tumor-infiltrating subtype while CD3+FoxP3+ T cells and CD3+CD8+ T cells showed similar densities. Spatial distribution analysis elucidated that proliferative T cells, characterized by Ki67 expression, and Granzyme B-expressing T cells were predominantly located within the tumor epithelium. We demonstrated an increase in immune cell density and a decrease in the distance of CD3+CD8+ T cells to the nearest tumor cell, in the immune active, ICR High, immune subtypes. Higher densities of stromal CD3+FoxP3+ T cells showed enhanced survival outcomes, and patients exhibited superior clinical benefits when greater spatial distances were observed between CD3+CD8-FoxP3- or CD3+CD8+ T cells and CD3+FoxP3+ T cells. Conclusion: Our study's in-depth analysis of the spatial distribution and densities of major T cell subtypes within the tumor microenvironment has provided valuable information that paves the way for further research into the intricate relationships between immune cells and colon cancer development.

Multimodal profiling of chordoma immunity reveals distinct immune contextures.

BACKGROUND: Chordomas are rare cancers from the axial skeleton which present a challenging clinical management with limited treatment options due to their anatomical location. In recent years, a few clinical trials demonstrated that chordomas can respond to immunotherapy. However, an in-depth portrayal of chordoma immunity and its association with clinical parameters is still lacking. METHODS: We present a comprehensive characterization of immunological features of 76 chordomas through application of a multimodal approach. Transcriptomic profiling of 20 chordomas was performed to inform on the activity of immune-related genes through the immunologic constant of rejection (ICR) signature. Multidimensional immunophenotyping through imaging mass cytometry was applied to provide insights in the different immune contextures of 32 chordomas. T cell infiltration was further evaluated in all 76 patients by means of multispectral immunofluorescence and then associated with clinical parameters through univariate and multivariate Cox proportional hazard models as well as Kaplan-Meier estimates. Moreover, distinct expression patterns of human leukocyte antigen (HLA) class I were assessed by immunohistochemical staining in all 76 patients. Finally, clonal enrichment of the T cell receptor (TCR) was sought through profiling of the variable region of TCRB locus of 24 patients. RESULTS: Chordomas generally presented an immune "hot" microenvironment in comparison to other sarcomas, as indicated by the ICR transcriptional signature. We identified two distinct groups of chordomas based on T cell infiltration which were independent from clinical parameters. The highly infiltrated group was further characterized by high dendritic cell infiltration and the presence of multicellular immune aggregates in tumors, whereas low T cell infiltration was associated with lower overall cell densities of immune and stromal cells. Interestingly, patients with higher T cell infiltration displayed a more pronounced clonal enrichment of the TCR repertoire compared with those with low T cell counts. Furthermore, we observed that the majority of chordomas maintained HLA class I expression. CONCLUSION: Our findings shed light on the natural immunity against chordomas through the identification of distinct immune contextures. Understanding their immune landscape could guide the development and application of immunotherapies in a tailored manner, ultimately leading to an improved clinical outcome for patients with chordoma.

An integrated tumor, immune and microbiome atlas of colon cancer.

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.

Transcriptomic and immunophenotypic profiling reveals molecular and immunological hallmarks of colorectal cancer tumourigenesis.

OBJECTIVE: Biological insights into the stepwise development and progression of colorectal cancer (CRC) are imperative to develop tailored approaches for early detection and optimal clinical management of this disease. Here, we aimed to dissect the transcriptional and immunologic alterations that accompany malignant transformation in CRC and to identify clinically relevant biomarkers through spatial profiling of pT1 CRC samples. DESIGN: We employed digital spatial profiling (GeoMx) on eight pT1 CRCs to study gene expression in the epithelial and stromal segments across regions of distinct histology, including normal mucosa, low-grade and high-grade dysplasia and cancer. Consecutive histology sections were profiled by imaging mass cytometry to reveal immune contextures. Finally, publicly available single-cell RNA-sequencing data was analysed to determine the cellular origin of relevant transcripts. RESULTS: Comparison of gene expression between regions within pT1 CRC samples identified differentially expressed genes in the epithelium (n=1394 genes) and the stromal segments (n=1145 genes) across distinct histologies. Pathway analysis identified an early onset of inflammatory responses during malignant transformation, typified by upregulation of gene signatures such as innate immune sensing. We detected increased infiltration of myeloid cells and a shift in macrophage populations from pro-inflammatory HLA-DR+CD204- macrophages to HLA-DR-CD204+ immune-suppressive subsets from normal tissue through dysplasia to cancer, accompanied by the upregulation of the CD47/SIRPα 'don't eat me signal'. CONCLUSION: Spatial profiling revealed the molecular and immunological landscape of CRC tumourigenesis at early disease stage. We identified biomarkers with strong association with disease progression as well as targetable immune processes that are exploitable in a clinical setting.

Correlation of Immunological and Histopathological Features with Gene Expression-Based Classifiers in Colon Cancer Patients.

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, plus (4) tumor budding and two gene expression-based classifiers­(1) consensus molecular subtypes (CMS) plus (2) colorectal cancer intrinsic subtypes (CRIS). All four histopathological features were retrospectively scored on hematoxylin and eosin sections of the most invasive part of the primary tumor in 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 a 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 strongly 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 associated with CMS3: mucus was present in 64.1% of all CMS3 tumors (p < 0.001). Although a clear 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 clear associations between histopathologic features and CMS or CRIS subtypes. However, identification of distinct molecular subtypes solely based on histopathology proved to be infeasible. Combining both molecular and morphologic features could potentially improve patient stratification.

Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting.

BACKGROUND: Advances in our understanding of the tumor microenvironment have radically changed the cancer field, highlighting the emerging need for biomarkers of an active, favorable tumor immune phenotype to aid treatment stratification and clinical prognostication. Numerous immune-related gene signatures have been defined; however, their prognostic value is often limited to one or few cancer types. Moreover, the area of non-coding RNA as biomarkers remains largely unexplored although their number and biological roles are rapidly expanding. METHODS: We developed a multi-step process to identify immune-related long non-coding RNA signatures with prognostic connotation in multiple TCGA solid cancer datasets. RESULTS: Using the breast cancer dataset as a discovery cohort we found 2988 differentially expressed lncRNAs between immune favorable and unfavorable tumors, as defined by the immunologic constant of rejection (ICR) gene signature. Mapping of the lncRNAs to a coding-non-coding network identified 127 proxy protein-coding genes that are enriched in immune-related diseases and functions. Next, we defined two distinct 20-lncRNA prognostic signatures that show a stronger effect on overall survival than the ICR signature in multiple solid cancers. Furthermore, we found a 3 lncRNA signature that demonstrated prognostic significance across 5 solid cancer types with a stronger association with clinical outcome than ICR. Moreover, this 3 lncRNA signature showed additional prognostic significance in uterine corpus endometrial carcinoma and cervical squamous cell carcinoma and endocervical adenocarcinoma as compared to ICR. CONCLUSION: We identified an immune-related 3-lncRNA signature with prognostic connotation in multiple solid cancer types which performed equally well and in some cases better than the 20-gene ICR signature, indicating that it could be used as a minimal informative signature for clinical implementation.

The immune landscape of solid pediatric tumors.

BACKGROUND: Large immunogenomic analyses have demonstrated the prognostic role of the functional orientation of the tumor microenvironment in adult solid tumors, this variable has been poorly explored in the pediatric counterpart. METHODS: We performed a systematic analysis of public RNAseq data (TARGET) for five pediatric tumor types (408 patients): Wilms tumor (WLM), neuroblastoma (NBL), osteosarcoma (OS), clear cell sarcoma of the kidney (CCSK) and rhabdoid tumor of the kidney (RT). We assessed the performance of the Immunologic Constant of Rejection (ICR), which captures an active Th1/cytotoxic response. We also performed gene set enrichment analysis (ssGSEA) and clustered more than 100 well characterized immune traits to define immune subtypes and compared their outcome. RESULTS: A higher ICR score was associated with better survival in OS and high risk NBL without MYCN amplification but with poorer survival in WLM. Clustering of immune traits revealed the same five principal modules previously described in adult tumors (TCGA). These modules divided pediatric patients into six immune subtypes (S1-S6) with distinct survival outcomes. The S2 cluster showed the best overall survival, characterized by low enrichment of the wound healing signature, high Th1, and low Th2 infiltration, while the reverse was observed in S4. Upregulation of the WNT/Beta-catenin pathway was associated with unfavorable outcomes and decreased T-cell infiltration in OS. CONCLUSIONS: We demonstrated that extracranial pediatric tumors could be classified according to their immune disposition, unveiling similarities with adults' tumors. Immunological parameters might be explored to refine diagnostic and prognostic biomarkers and to identify potential immune-responsive tumors.

Transcriptomic profile investigations highlight a putative role for NUDT16 in sepsis.

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.

Analytic pipelines to assess the relationship between immune response and germline genetics in human tumors.

Germline genetic variants modulate human immune response. We present analytical pipelines for assessing the contribution of hosts' genetic background to the immune landscape of solid tumors using harmonized data from more than 9,000 patients in The Cancer Genome Atlas (TCGA). These include protocols for heritability, genome-wide association studies (GWAS), colocalization, and rare variant analyses. These workflows are developed around the structure of TCGA but can be adapted to explore other repositories or in the context of cancer immunotherapy. For complete details on the use and execution of this protocol, please refer to Sayaman et al. (2021).

Combined Assessment of the Tumor-Stroma Ratio and Tumor Immune Cell Infiltrate for Immune Checkpoint Inhibitor Therapy Response Prediction in Colon Cancer.

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.

Myeloid Cells Are Enriched in Tonsillar Crypts, Providing Insight into the Viral Tropism of Human Papillomavirus.

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.

Integrated transcriptional-phenotypic analysis captures systemic immunomodulation following antiangiogenic therapy in renal cell carcinoma patients.

BACKGROUND: The combination of immune checkpoint blockade (ICB) with standard therapies is becoming a common approach for overcoming resistance to cancer immunotherapy in most human malignancies including metastatic renal cell carcinoma (mRCC). In this regard, insights into the immunomodulatory properties of antiangiogenic agents may help designing multidrug schedules based on specific immune synergisms. METHODS: We used orthogonal transcriptomic and phenotyping platforms combined with functional analytic pipelines to elucidate the immunomodulatory effect of the antiangiogenic agent pazopanib in mRCC patients. Nine patients were studied longitudinally over a period of 6 months. We also analyzed transcriptional data from The Cancer Genome Atlas (TCGA) RCC cohort (N = 571) to assess the prognostic implications of our findings. The effect of pazopanib was assessed in vitro on NK cells and T cells. Additionally, myeloid-derived suppressor (MDSC)-like cells were generated from CD14+ monocytes transfected with mimics of miRNAs associated with MDSC function in the presence or absence of pazopanib. RESULTS: Pazopanib administration caused a rapid and dramatic reshaping in terms of frequency and transcriptional activity of multiple blood immune cell subsets, with a downsizing of MDSC and regulatory T cells in favor of a strong enhancement in PD-1 expressing cytotoxic T and Natural Killer effectors. These changes were paired with an increase of the expression of transcripts reflecting activation of immune-effector functions. This immunomodulation was marked but transient, peaking at the third month of treatment. Moreover, the intratumoral expression level of a MDSC signature (MDSC INT) was strongly associated with poor prognosis in RCC patients. In vitro experiments indicate that the observed immunomodulation might be due to an inhibitory effect on MDSC-mediated suppression, rather than a direct effect on NK and T cells. CONCLUSIONS: The marked but transient nature of this immunomodulation, peaking at the third month of treatment, provides the rationale for the use of antiangiogenics as a preconditioning strategy to improve the efficacy of ICB.

Network-based identification of key master regulators associated with an immune-silent cancer phenotype.

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-$\beta $, Interleukin-1 and TNF-$\alpha $ signaling pathways. TGFB1I1 emerged as one of the main negative immune modulators preventing the favorable effects of a Th1/cytotoxic response.

BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R.

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.

Ancestry-associated transcriptomic profiles of breast cancer in patients of African, Arab, and European ancestry.

Breast cancer largely dominates the global cancer burden statistics; however, there are striking disparities in mortality rates across countries. While socioeconomic factors contribute to population-based differences in mortality, they do not fully explain disparity among women of African ancestry (AA) and Arab ancestry (ArA) compared to women of European ancestry (EA). In this study, we sought to identify molecular differences that could provide insight into the biology of ancestry-associated disparities in clinical outcomes. We applied a unique approach that combines the use of curated survival data from The Cancer Genome Atlas (TCGA) Pan-Cancer clinical data resource, improved single-nucleotide polymorphism-based inferred ancestry assignment, and a novel breast cancer subtype classification to interrogate the TCGA and a local Arab breast cancer dataset. We observed an enrichment of BasalMyo tumors in AA patients (38 vs 16.5% in EA, p = 1.30E - 10), associated with a significant worse overall (hazard ratio (HR) = 2.39, p = 0.02) and disease-specific survival (HR = 2.57, p = 0.03). Gene set enrichment analysis of BasalMyo AA and EA samples revealed differences in the abundance of T-regulatory and T-helper type 2 cells, and enrichment of cancer-related pathways with prognostic implications (AA: PI3K-Akt-mTOR and ErbB signaling; EA: EGF, estrogen-dependent and DNA repair signaling). Strikingly, AMPK signaling was associated with opposing prognostic connotation (AA: 10-year HR = 2.79, EA: 10-year HR = 0.34). Analysis of ArA patients suggests enrichment of BasalMyo tumors with a trend for differential enrichment of T-regulatory cells and AMPK signaling. Together, our findings suggest that the disparity in the clinical outcome of AA breast cancer patients is likely related to differences in cancer-related and microenvironmental features.

Germline genetic contribution to the immune landscape of cancer.

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-ß-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.

Organizing training workshops on gene literature retrieval, profiling, and visualization for early career researchers.

Early-career researchers must acquire the skills necessary to effectively search and extract information from biomedical literature. This ability is for instance crucial for evaluating the novelty of experimental results, and assessing potential publishing opportunities. Given the rapidly growing 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. In this context, we present a hands-on training curriculum aimed at retrieval, profiling, and visualization of literature associated with a given topic. The curriculum was implemented in a workshop in January 2021. Here we provide supporting material and step-by-step implementation guidelines with the ISG15 gene literature serving as an illustrative use case. Workshop participants can learn several skills, including: 1) building and troubleshoot PubMed queries in order to retrieve the literature associated with a gene of interest; 2) identifying key concepts relevant to given themes (such as cell types, diseases, and biological processes); 3) measuring the prevalence of these concepts in the gene literature; 4) extracting key information from relevant articles, and 5) developing 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.

A balance score between immune stimulatory and suppressive microenvironments identifies mediators of tumour immunity and predicts pan-cancer survival.

BACKGROUND: 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. METHODS: 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 TGFß, EMT and PI3Kγ signatures. RESULTS: 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. CONCLUSIONS: 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.