Biology subjects

Roelands, J.

Publications and source records attributed to Roelands, J..

14 recordsLinked to original sources

bioRxiv2026

Elevated MPS1 converts the fibrous corona into a source of chromosomal instability in colon cancer

Chromosomal instability (CIN), characterised by recurrent chromosome mis-segregation, fuels intratumour heterogeneity and tumour evolution. Yet, its proximal molecular causes remain ill-defined. Tumour-scale genomic and transcriptomic analyses associate MPS1 overexpression with CIN in colon carcinomas. Consistently, CIN+ patient-derived colon cancer cells (PCCCs) display elevated MPS1, frequent merotelic kinetochore-microtubule attachments and lagging chromosomes that are suppressed by partial MPS1 inhibition. Conversely, ectopic MPS1 overexpression in otherwise stable near-diploid cells phenocopies these defects, inducing micronuclei formation and karyotypic divergence. Mechanistically, MPS1 overactivity maintains ROD phosphorylation at Thr13/Ser15, continuously sustaining fibrous corona assembly despite mature end-on attachments. 3D-STED microscopy reveals split-interface configurations in which microtubules from opposing poles engage the canonical outer-kinetochore surface and a spatially distinct corona domain, explaining how merotely forms and persists into anaphase. Disrupting corona assembly restores chromosome segregation fidelity in MPS1-overexpressing RPE-1 cells and in CIN+ PCCCs. Together, our findings establish MPS1 overexpression as a driver of CIN and uncover how oncogenic transcriptional rewiring of mitotic signalling converts a transient microtubule-capture structure into a pathological source of merotely and chromosome mis-segregation in colon cancer.

cell biology↗

bioRxiv2026

Inflammation-driven reprogramming of goblet cells underlies the onset of serrated adenomas in colon cancer

In the context of inflammation, fully committed and post-mitotic cell lineages can initiate intestinal tumorigenesis in the mouse through dedifferentiation and acquisition of revival stem cell (RSC) features1,2. Likewise, by means of machine-learning analysis of whole-genome mutation spectra, the secretory goblet cell was predicted as the most frequent cell-of-origin (COO) of colon cancer in inflammatory bowel disease (IBD) patients2. Of note, even among sporadic (non-IBD) colon cancer patients, goblet cells were predicted as the most common differentiated COO of cancer in the colonic epithelium2, suggestive of the main role played by diet-induced inflammation in the onset of a large proportion of malignancies of the large bowel. However, how goblet cells respond to inflammation and reprogram their identity to become potential tumor-initiating cells remains unclear. Here, by taking advantage of publicly available single-cell RNAseq data from colonic tissues of ulcerative colitis (UC) patients3, we have characterized the inflammation-driven reprogramming of goblet cells. By means of an RNA velocity-based computational approach, we show that the mucus-producing goblet cells acquire an aberrant proliferative state earmarked by MUC5AC+ expression. Trajectory analysis of serrated adenoma cells4 reveal aberrant goblet cells as an intermediate state in the transition to revival stem cells, notably more common in BRAF-mutant cases. In support of these findings, COO predictions using whole-genome mutation spectra from a cohort of sporadic colon cancers5 connect tumors with a predicted goblet origin to BRAF mutations and reveal transcriptional remnants of the aberrant goblet cell state.

Cancer Biology↗

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

GRIDGEN: Guided Region Identification based on Density of GENes - a transcript density-based approach to characterize tissues by spatial transcriptomics

Spatial omics brought unprecedented power to study biological processes within tissues while preserving spatial context and morphology. Most spatial proteomics and transcriptomics analyses methods are cell-centric, relying on cell segmentation to identify and characterize individual cells before downstream tasks. However, certain biological questions may be better addressed using cell-free approaches, which also eliminate unnecessary computations when cell segmentation is not essential. To address this need, we developed GRIDGENE (Guided Region Identification based on Density of GENEs), an approach for defining regions of interest based on transcript density. GRIDGENE enables the identification of biologically relevant tissue compartments, including interfaces between regions, phenotype-enriched areas, and zones defined by specific gene signatures, supporting analyses such as pathway enrichment. We demonstrated the utility of GRIDGENE by applying it to spatial transcriptomics data from CosMx and Xenium platforms in colorectal cancer (CRC) samples. By bypassing cell segmentation, our approach enables flexible analysis of spatial omics data, supporting the study of biological processes across diverse tissue structures and microenvironments. Nevertheless, GRIDGENE can be easily integrated with cell segmentation strategies for complementary analyses. GRIDGENE thus broadens the analytical toolkit for spatial omics, enabling both cell-free and cell-based insights.

bioinformatics↗

bioRxiv2025

Divergent Therapeutic and Prognostic Impacts of Immunogenic Features in Undifferentiated Soft Tissue Sarcoma and Myxofibrosarcoma

Myxofibrosarcoma and undifferentiated soft tissue sarcoma (USTS) are genetically complex soft tissue sarcomas with distinct morphological features. Treatment typically involves surgery, often combined with neoadjuvant chemo- or radiotherapy. To better understand the immunobiology of these sarcomas and its associations with treatment response and prognosis, we performed transcriptomic and immunophenotypic profiling. RNA sequencing was performed on 13 USTS and 10 myxofibrosarcomas and immunological profiles were compared with soft tissue sarcoma data from The Cancer Genome Atlas (n = 206 including 44 USTS and 17 myxofibrosarcomas). Immune contextures were further evaluated in 16 USTS and 11 myxofibrosarcomas using imaging mass cytometry. Characterization of T cell and macrophage infiltration in tumors was further assessed in 23 USTS and 22 myxofibrosarcomas through multispectral immunofluorescence and immunohistochemical analysis. USTS and myxofibrosarcomas demonstrated immunogenic features compared to other soft tissue sarcomas, with subsets of USTS and myxofibrosarcomas demonstrating high T cell infiltration while USTS demonstrated a higher infiltration by myeloid cells as compared to myxofibrosarcoma. Prognostically, T cells and CD68+CD163+ macrophages were associated with metastasis-free survival in USTS but not in myxofibrosarcomas. Notably, in USTS, neoadjuvant radiotherapy appeared to induce cytotoxic T cell infiltration and depletion of myeloid cells, whereas these effects were not observed in myxofibrosarcomas. These findings highlight important differences in the immunobiology of USTS and myxofibrosarcomas with therapeutic and prognostic implications. These differences should be taken into account given the growing availability of immunotherapeutic options for treating patients with soft tissue sarcomas.

cancer biology↗

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↗

bioRxiv2021

Revisiting colorectal cancer tumorigenesis with spatially-resolved gene expression profiling

Early detection and treatment are paramount to the clinical outcome of patients with colorectal cancer (CRC). Deciphering the dynamic interactions that occur between epithelial cells and stromal cells during tumorigenesis requires in-depth analyses of early-stage CRC lesions in spatial context. Here we employed spatially-resolved gene expression profiling to dissect molecular processes that associate with malignant transformation in CRC. We provide the transcriptional landscapes of colorectal cancer tumorigenesis from healthy mucosa, through different degrees of dysplasia, to cancer. The complementary examination of epithelial and stromal fractions allowed us to define whether specific oncogenic processes involved cancer cells, stromal cells, or the tumor microenvironment as a whole. We identified several genes that were consistently deregulated during CRC onset that could serve as clinical biomarkers for early-stage CRC. Furthermore, we uncovered an essential role for the innate immune system during CRC tumorigenesis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/462502v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@c24d1forg.highwire.dtl.DTLVardef@554113org.highwire.dtl.DTLVardef@1236f99org.highwire.dtl.DTLVardef@173ac8c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

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

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

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↗

bioRxiv2018

The abundance of Nudix hydrolase 16 transcripts is elevated in human sepsis: perspectives gained during a hands-on reductionist investigation workshop.

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.

immunology↗