Biology subjects

Bedognetti, D.

Publications and source records attributed to Bedognetti, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Methylation-Guided Stratification of Colorectal Cancer Reveals Immune Subtypes with Distinct Clinical Outcomes

BackgroundAberrant DNA methylation is a hallmark of colorectal cancer (CRC). Yet, how DNA methylation is linked to transcriptional states, immune programs, and tissue resident microbiome within the same tumors has not been systematically analyzed. MethodsWe profiled genome-wide DNA methylation (Illumina MethylationEPIC) in 182 colon tumors and 76 adjacent normals from AC-ICAM, and integrated with matched transcriptomes, whole exome, microbiome, and clinical data. Tumor-specific methylation, promoter methylation-expression links, microbiome associations, and survival were analyzed and validated in TCGA-COAD. ResultsTumor and normal tissues exhibited distinct DNA methylation patterns, reflecting widespread epigenetic alterations in cancer. Pathway analysis identified two major tumor pathways regulated by DNA methylation. The first involved extracellular signaling and adhesion genes, with higher methylation linked to increased proliferation and lower immune infiltration. Similarly, higher tumor methylation in nitric oxide signaling was associated with reduced adaptive immune activity and interestingly, influenced immune-related survival. These findings were also validated in the TCGA-COAD cohort. An inverse methylation-expression pattern implicated modifications of TCR signaling in naive CD8, and interferon-/{beta} signaling which were hypermethylated and hypomethylated in tumors compared to normal, respectively. Combining methylation and microbiome revealed connections between Akkermansia muciniphila and TGF-{beta} and Prevotella nigrescens with MAPK signaling pathways. Finally, a methylation-based model using 43 promoters CpGs successfully identified patients with different survival outcomes, underscoring the clinical relevance of these epigenetic alterations in colon cancer. ConclusionDNA methylation shapes the molecular and immune landscape of colon cancer, altering signaling pathways and immune programs, interacting with the microbiome, and impacting patients survival.

cancer biology↗

bioRxiv2025

A 3-genes interferon signature predicts sustained complete remission in pediatric AML patients

The immunological composition of the microenvironment has shown relevance for diagnosis, prognosis, and therapy in solid tumors but remains underexplored in acute leukemias. We investigated the significance of acute myeloid leukemia (AML) bone marrow microenvironment in predicting chemosensitivity and long-term remission in pediatric patients. We analyzed 32 non-promyelocytic pediatric AML patients at diagnosis using NanoString PanCancer IO 360 assay, RNA sequencing, and deep-phenotype flow cytometry analyses. The findings were validated using the pediatric TARGET AML dataset. A short signature of three interferon (IFN)-related genes (GBP1, PARP12, TRAT1) distinguished patients with chemosensitive disease and reduced minimal residual disease after induction chemotherapy. The signature stratified patients overall, and within the clinically defined "standard-risk" group, patients with high gene expression at diagnosis had significantly longer overall survival. The leukemia microenvironment associated with this signature showed enrichment of non-exhausted CD4+ and CD8+ T cytotoxic lymphocytes and expansion of CD8+ T effector memory cells re-expressing CD45RA (TEMRA) in patients with a favorable prognosis. Our results show the importance of the bone marrow microenvironment in pediatric AML and provide tools for a refined stratification of "standard-risk" patients, lacking adequate risk-oriented therapies. They also offer a promising guide for tackling immune pathways and exploiting immune-targeted therapies. Statement of significanceWe identified a novel three-gene IFN-related signature that distinguished pediatric AML patients by chemosensitivity and remission outcomes. It stratified patients across all risk groups, including the "standard-risk" group, with high expression linked to a T-cell-enriched microenvironment and longer survival. This signature may enhance risk stratification and guide targeted immunotherapy.

cancer biology↗

bioRxiv2025

Temporal Dynamics of Transcriptional Responses to Repeated mRNA Vaccination: Insights from Third Dose Profiling

mRNA vaccines have played a crucial role in combating the COVID-19 pandemic, but the long-term dynamics of immune responses to repeated vaccination remain poorly understood. In this study, we extend our previous work on first and second dose responses by characterizing the immune signatures elicited by a third dose of COVID-19 mRNA vaccines using high-resolution temporal profiling of blood transcriptomes collected daily for 9 days post-vaccination. We observed distinct patterns of gene expression related to interferon responses, inflammation, erythroid cell signatures, and plasmablast activity across the three doses. While the first dose elicited a modest response primarily characterized by interferon signaling, the second dose induced a robust, polyfunctional response. The third dose, administered approximately nine months later, maintained this polyfunctional character and matched the second dose in magnitude, though with distinct temporal dynamics. The interferon component peaked on day 2 (similar to the first dose) rather than day 1 (as seen in the second dose), while the erythroid signature showed a markedly different trajectory, with sustained elevation rather than decrease over the following week. Notably, we observed a progressive amplification of the plasmablast response across the three doses, with an earlier peak (day 4) compared to other vaccines, potentially a unique feature of mRNA vaccines. These findings demonstrate that the heightened, polyfunctional responsiveness induced by the second dose is robustly maintained even after a prolonged interval, suggesting effective immune memory. Our results contribute to understanding mRNA vaccine-induced immunity, with implications for optimizing booster strategies and developing next-generation vaccines.

immunology↗

bioRxiv2024

MUC2 Expression Modulates Immune Infiltration in Colorectal Cancer

IntroductionColorectal cancer (CRC) is a prevalent malignancy with significant morbidity and mortality worldwide. A deeper understanding of the interaction of cancer cells with other cells in the tumor microenvironment is crucial for devising effective therapeutic strategies. MUC2, a major component of the protective mucus layer in the gastrointestinal tract, has been implicated in CRC progression and immune response regulation. MethodIn this study, we sought to elucidate the relationship between MUC2 expression and immune infiltration within CRC, using in-vitro models involving two well-established cell lines, HT-29 and LS-174T. By employing CRISPR-mediated MUC2 knockout, we investigated the influence of MUC2 on tumor immune infiltration and its interplay with T cells and NK cells enriched peripheral blood mononuclear cells (PBMCs) in 3D spheroid cultures. ResultsWhile MUC2 was more abundant in LS-174T cell lines compared to HT-29, its knockout resulted in increased immune infiltration solely in the HT-29 cell line, but not in LS-174T. We revealed that the removal of MUC2 protein was compensated in LS-174T by the expression of other gel forming mucin proteins (Muc6, Muc5B) commonly expressed in gastrointestinal epithelium, while this was not observed in HT-29 cell line. DiscussionWe propose that the role of MUC2 documented in CRC progression can partially be explained by impairing immune infiltration due to physical barrier established by the gel forming proteins such as MUC2 in mucinous CRC. On the other hand, the removal of MUC2 expression can be compensated by alternative gel forming mucin proteins, thereby impeding any increase in tumor immune infiltration.

cancer biology↗

bioRxiv2024

Biological modifications of the immune response to COVID-19 vaccine in patients treated with anti-CD20 agents and immune-checkpoint inhibitors

Investigating the impact of immune-modulating therapies on mRNA vaccine efficacy transcends the immediate context of the COVID-19 pandemic. This study focuses on the differential immune responses to the third dose of COVID-19 mRNA vaccine among healthy volunteers, cancer patients treated with immune-checkpoint inhibitors (ICIs), and those treated with the anti-CD20 antibody rituximab. Utilizing RNA sequencing, serology, and interferon-{gamma} release assessment, we charted the temporal dynamics of the immune response in such cohorts. Our findings indicate that ICIs maintain an immune profile similar to that of healthy individuals, whereas treatment with rituximab is associated with impairment of type I interferon response and the upregulation of transcripts pertaining to regulatory T cells, with a global dysfunction of both humoral and cellular immunity. This research deepens our understanding of the sophisticated interplay within the immune system in health and disease states, potentially informing therapeutic strategies across a spectrum of immunological conditions. Significance statementOur study examines how cancer treatments that modify the immune system affect transcriptional, serological, and cellular responses to a model for repeated antigenic stimulation in humans, represented by the SARS-CoV-2 booster vaccine. Specifically, we investigated patients treated with rituximab (RTX), which impairs antibody production, and immune checkpoint inhibitors (ICI), which can trigger autoimmune disorders. We discovered that RTX-treated patients not only exhibit a reduced antibody response but actually show a diminished interferon-mediated immune response, indicating a broader immune disruption than anticipated. Conversely, ICI-treated patients responded to the vaccine similarly to healthy individuals, suggesting that fears of adverse vaccine reactions in these patients may be unfounded. This research highlights important considerations for the clinical management of cancer patients receiving these treatments.

immunology↗

bioRxiv2023

Modulation of SLFN11 induces changes in DNA Damage response

BackgroundLack of Schlafen family member 11 (SLFN11) expression has been recently identified as a dominant genomic determinant of response to DNA damaging agents in numerous cancer types. Thus, strategies aimed at increasing SLFN11 could be used to restore chemosensitivity of refractory cancers. As oncogenic downregulation is often driven by methylation of the promotor region, we explore the demethylation effect of 5-aza-2-deoxycytidine (decitabine), on the SLFN11 gene methylation. Since SLFN11 has been reported as an interferon inducible gene, and interferon is secreted during an active anti-tumor immune response, we investigated the in vitro effect of IFN-{gamma} on SLFN11 expression in breast cancer cell lines. A second broader approach to show cross talk between immune cells and SLFN11 expression is indirect co-culture of breast cancer cells with activated PBMCs and evaluate if this can drive SLFN11 upregulation. Finally, as a definitive and specific way to modulate SLFN11 expression we implemented SLFN11 dCas9 (dead CRISPR associated protein 9) systems to specifically increase or decrease SLFN11 expression. ResultsWe first confirmed a correlation previously reported between methylation of SLFN11 promoter and its expression across multiple cell lines. We showed in-vitro that decitabine and IFN-{gamma} could increase moderately the expression of SLFN11 in both BT- 549 and T47D cell lines, but not in strongly methylated cell lines such as MDA-MB-231. Though, in-vitro, the co-culture of the same cell lines with CD8-CD25 activated PBMC failed to increase SLFN11 expression. On the one hand, the use of a CRISPR-dCas9 UNISAM system could increase SLFN11 expression significantly (up to 5-fold), stably and specifically in BT-549 and T47D cancer cell lines. Though, this system also failed to force a strong expression of SLFN11 in cell lines with robust SLFN11 promoter methylation such as MDA-MB-231. On the other hand, the use of CRISPR-dCas9 KRAB could significantly reduce the expression of SLFN11 in BT-549 and T47D. We then used the modified cell lines to confirm the alteration in chemo sensitivity of those cells to treatment with DNA Damaging Agents (DDAs) such as Cisplatin and Epirubicin or DNA Damage Response (DDRs) drugs like Olaparib. RNAseq was used to elucidate the mechanisms of action affected by the alteration in SLFN11 expression. ConclusionTo our knowledge this is the first report of the stable non-lethal increase of SLFN11 expression in a cancer cell line. Our results show that induction of SLFN11 expression can enhance DDA and DDR sensitivity in breast cancer cells and dCas9 systems may represent a novel approach to increase SLFN11 and achieve higher sensitivity to chemotherapeutic agents, improving outcome or decreasing required drug concentrations. SLFN11-targeting therapies might be explored pre-clinically to develop personalized approaches.

cancer biology↗

bioRxiv2022

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1. ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy. Context summaryO_ST_ABSKey objectiveC_ST_ABSNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC. Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response. Relevance

cancer biology↗

bioRxiv2021

High temporal resolution transcriptomic profiling delineates distinct patterns of interferon response following Covid-19 mRNA vaccination and SARS-CoV2 infection

Knowledge of the mechanisms underpinning the development of protective immunity conferred by mRNA vaccines is fragmentary. Here we investigated responses to COVID-19 mRNA vaccination via ultra-low-volume sampling and high-temporal-resolution transcriptome profiling (23 subjects across 22 timepoints, and with 117 COVID-19 patients used as comparators). There were marked differences in the timing and amplitude of the responses to the priming and booster doses. Notably, we identified two distinct interferon signatures. The first signature (A28/S1) was robustly induced both post-prime and post-boost and in both cases correlated with the subsequent development of antibody responses. In contrast, the second interferon signature (A28/S2) was robustly induced only post-boost, where it coincided with a transient inflammation peak. In COVID19 patients, a distinct phenotype dominated by A28/S2 was associated with longer duration of intensive care. In summary, high-temporal-resolution transcriptomic permitted the identification of post- vaccination phenotypes that are determinants of the course of COVID-19 disease.

immunology↗

bioRxiv2021

The Immune landscape of solid pediatric tumors.

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.

cancer biology↗

bioRxiv2020

Blood transcriptional module repertoire analysis and visualization using R

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.

bioinformatics↗

bioRxiv2020

SLFN11 captures cancer-immunity interactions associated with platinum sensitivity in ovarian cancer

Large independent analyses on cancer cell lines followed by functional studies have identified Schlafen 11 (SLFN11), a putative DNA/RNA helicase, as the strongest predictor of sensitivity to DNA-damaging agents. However, its role as a prognostic biomarker is undefined, partially due to the lack of validated methods to score SLFN11 in human tissues. Here, we implemented a pipeline to quantify SLFN11 in human cancer samples. By analyzing a cohort of high-grade serous ovarian carcinoma specimens prior platinum-based chemotherapy treatment, we demonstrate that SLFN11 is expressed by infiltrating innate and adaptive immune cells. We show, for the first time, that SLFN11 density in both the neoplastic and microenvironmental components was independently associated with favorable outcome. Transcriptomic analyses suggested the presence of a hitherto modulation of the cancer-immunity cycle orchestrated by SLFN11. We propose SLFN11 as a dual biomarker capturing simultaneously interconnected immunological and cancercell-intrinsic functional dispositions associated with sensitivity to DNA damaging agents.

cancer biology↗

bioRxiv2020

A modular framework for the development of targeted Covid-19 blood transcript profiling panels

Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of focused blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection. We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates. As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: therapeutic development relevance, SARS biology relevance and immunological relevance. Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.

immunology↗

bioRxiv2020

Pazopanib induces dramatic but transient contraction of myeloid suppression compartment in favor of adaptive immunity

Anti-angiogenic tyrosine-kinase inhibitors (TKIs) and immune checkpoint blockade (ICB) constitute the backbone of metastatic renal cell carcinoma (mRCC) treatment. The development of the optimal combinatorial or sequential approach is hindered by the lack of comprehensive data regarding TKI-induced immunomodulation and its kinetics. Through the use of orthogonal transcriptomic and phenotyping platforms combined with functional analytic pipelines, we demonstrated that the anti-angiogenic TKI pazopanib induces a dramatic and coherent reshaping of systemic immunity in mRCC patients, downsizing the myeloid-derived suppressor cell (MDSC) compartment in favor of a strong enhancement of cytotoxic T and Natural Killer (NK) cell effector functions. The intratumoral expression level of a MDSC signature here generated was strongly associated with poor prognosis in mRCC patients. The marked but transient nature of this immunomodulation, peaking at the 3rd month of treatment, provides the rationale for the use of TKIs as a preconditioning strategy to improve the efficacy of ICB.

cancer biology↗

bioRxiv2020

Germline genetic contribution to the immune landscape of cancer

The role of germline genetics in shaping the tumor immune landscape is largely unknown. Using genotypes from >9,000 individuals in The Cancer Genome Atlas, we investigated the association of common and rare variants with 139 well-defined immune traits. Our analysis of common variants identified 10 immune traits with significant heritability estimates, and an additional 23 with suggestive heritability, including estimates of T-cell subset abundance and interferon signaling. We performed genome-wide association on the 33 heritable traits and identified 23 genome-wide significant loci associated with at least one immune trait, including SNPs in the IFIH1 locus previously associated with several autoimmune diseases. We also found significant associations between immune traits and pathogenic or likely-pathogenic rare variants in BRCA1 and in genes functionally linked to telomere stabilization, and Wnt/Beta-catenin signaling. We conclude that germline genetic variants significantly impact the composition and functional orientation of the tumor immune microenvironment.

immunology↗

bioRxiv2019

A MAP of tumor-host interactions in glioma at single cell resolution

Single-cell RNA sequencing is the reference technique to characterize the heterogeneity of tumor microenvironment and can be efficiently used to discover cross-talk mechanisms between immune cells and cancer cells. We present a novel method, single cell Tumor-Host Interaction tool (scTHI), to identify significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand-receptor interactions in glioma using six publicly available human glioma datasets encompassing 71 patients. We provide a comprehensive map of the signalling mechanisms between malignant cells and non-malignant cells in glioma uncovering potential novel therapeutic targets.

bioinformatics↗

bioRxiv2019

Conditional activation of immune-related signatures and prognostic significance: a pan-cancer analysis

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.

cancer biology↗

bioRxiv2019

Elevation of FAM129A in neutrophils exposed to serum of patients with severe sepsis: in silico investigations during a hands on training workshop and follow on validation of protein expression in neutrophils

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.

immunology↗

bioRxiv2019

A Novel Repertoire of Blood Transcriptome Modules Based on Co-expression Patterns Across Sixteen Disease and Physiological States

As the capacity for generating large scale data continues to grow the ability to extract meaningful biological knowledge from it remains a limitation. Here we describe the development of a new fixed repertoire of transcriptional modules. It is meant to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome profiling data. It is supported by customized resources, which include analysis workflows, fingerprint grid plots data visualizations, interactive web applications providing access to a vast number of module-specific functional profiling reports, reference transcriptional profiles and give users the ability to visualize of changes in transcript abundance across the modular repertoire at different granularity levels. A use case focusing on a set of six modules comprising interferon-inducible genes is also provided. Altogether we hope that this resource will also serve as a framework for improving over time our collective understanding of the immunobiology underlying blood transcriptome profiling data.

immunology↗