Biology subjects

Keddar, M. R.

Publications and source records attributed to Keddar, M. R..

5 recordsLinked to original sources

bioRxiv2025

Pan-cancer analysis in the real-world setting uncovers immunogenomic drivers of acquired resistance post-immunotherapy

Immune checkpoint blockade (ICB) has revolutionised cancer therapy, yet resistance -- both primary and acquired -- remains a significant obstacle, affecting the majority of patients. Here, we leveraged a large-scale, real-world clinicogenomic dataset to systematically explore the molecular underpinnings of ICB resistance in the post-progression setting. Analysing over 5,000 pan-cancer patients with clinical and pre-/post-treatment genomic and transcriptomic data, we identify distinct immunogenomic drivers of acquired vs. primary ICB resistance. Post-ICB progression, acquired resistance showed extended survival compared to primary resistance across all cancer types. The acquired resistance clinical phenotype was paralleled by a universally immune-inflamed, albeit dysfunctional, tumour microenvironment (TME) at the onset of acquired resistance, with sustained or ICB-induced inflammatory and interferon responses. We confirm previously described mechanisms of acquired resistance, including B2M loss-of-function (LoF) in non-small cell lung cancer (NSCLC), and identify novel potential mediators, including LoF of TGFBR2 in NSCLC, CYLD in head and neck cancer, and RUNX1 in triple negative breast cancer. Further supporting their involvement in resistance, these acquired ICB alterations associated with immune-escaped TMEs, characterised by active immunomodulatory oncogenic signalling, hyperproliferation and invasiveness, or altered tumour metabolism. These findings emphasise the heterogeneity of molecular drivers of acquired resistance to ICB within and across cancers, and highlight the potential for personalised therapeutic interventions post-progression to improve patient outcomes.

cancer biology↗

bioRxiv2023

Mechanistic insights into the interactions between cancer drivers and the tumour immune microenvironment

The crosstalk between cancer and the tumour immune microenvironment (TIME) has attracted significant interest because of its impact on cancer evolution and response to treatment. Despite this, cancer-specific tumour-TIME interactions and their mechanisms of action are still poorly understood. Here we identified the interactions between cancer-specific genetic drivers and anti- or pro-tumour TIME features in individual samples of 32 cancer types. The resulting 477 TIME drivers are multifunctional genes whose alterations are selected early in cancer evolution and recur across and within cancer types. Moreover, the anti-tumour TIME driver burden is predictive of overall response to immunotherapy. Focusing on head and neck squamous cancer (HNSC), we rebuilt the functional networks linking specific TIME driver alterations to the TIME state. We showed that TIME driver alterations predict the immune profiles of HNSC molecular subtypes, and that deregulation of keratinization, apoptosis and interferon signalling underpin specific driver-TIME interactions. Overall, our study provides a comprehensive resource of TIME drivers giving mechanistic insights into their immune-regulatory role.

cancer biology↗

bioRxiv2021

Comparative assessment of genes driving cancer and somatic evolution.

Genetic alterations of somatic cells can drive nonmalignant clone formation and promote cancer initiation. However, the link between these processes remains unclear hampering our understanding of tissue homeostasis and cancer development. Here we collect a literature-based repertoire of 3355 well-known or predicted drivers of cancer and noncancer somatic evolution in 122 cancer types and 12 noncancer tissues. Mapping the alterations of these genes in 7953 pancancer samples reveals that, despite the large size, the known compendium of drivers is still incomplete and biased towards frequently occurring coding mutations. High overlap exists between drivers of cancer and noncancer somatic evolution, although significant differences emerge in their recurrence. We confirm and expand the unique properties of drivers and identify a core of evolutionarily conserved and essential genes whose germline variation is strongly counter-selected. Somatic alteration in even one of these genes is sufficient to drive clonal expansion but not malignant transformation. Our study offers a comprehensive overview of our current understanding of the genetic events initiating clone expansion and cancer revealing significant gaps and biases that still need to be addressed. The compendium of cancer and noncancer somatic drivers, their literature support and properties are accessible at http://www.network-cancer-genes.org/.

cancer biology↗

bioRxiv2021

A SIMPLI (Single-cell Identification from MultiPLexed Images) approach for spatially resolved tissue phenotypingat single-cell resolution.

Multiplexed imaging technologies enable the study of biological tissues at single-cell resolution while preserving spatial information. Currently, high-dimension imaging data analysis is technology-specific and requires multiple tools, restricting analytical scalability and result reproducibility. Here we present SIMPLI (Single-cell Identification from MultiPlexed Images), a novel, flexible and technology-agnostic software that unifies all steps of multiplexed imaging data analysis. After raw image processing, SIMPLI performs a spatially resolved, single-cell analysis of the tissue slide as wells as cell-independent quantifications of marker expression to investigate features undetectable at the cell level. SIMPLI is highly customisable and can run on desktop computers as well as high-performance computing environments, enabling workflow parallelisation for large datasets. SIMPLI produces multiple tabular and graphical outputs at each step of the analysis. Its containerised implementation and minimum configuration requirements make SIMPLI a portable and reproducible solution for multiplexed imaging data analysis. SIMPLI is available at: https://github.com/ciccalab/SIMPLI.

bioinformatics↗

bioRxiv2020

Immunogenomic profile of colorectal cancer response to immune checkpoint blockade

Colorectal cancers (CRCs) show variable response to immune checkpoint blockade, which can only partially be explained by the variability of tumour mutational burden. To dissect the cellular and molecular determinants of response we performed a multi-omic screen of 721 cancer regions from patients treated with Pembrolizumab (KEYNOTE 177 clinical trial) or Nivolumab. Multi-regional whole exome, RNA and T-cell receptor sequencing show that, within hypermutated CRCs, response to both anti-PD1 agents is not positively associated with tumour mutational burden but with high clonality of immunogenic mutations, expanded T cells, low activation of the WNT pathway and active immune escape mechanisms. Coupling high-dimensional imaging mass cytometry with multiplexed immunofluorescence and computational spatial analysis, we observe that responsive hypermutated CRCs are rich in cytotoxic and proliferating PD1-expressing CD8 cells interacting with high-density clusters of PDL1-expressing antigen presenting macrophages. We propose that anti-PD1 agents release the PD1-PDL1 interaction between CD8 T cells and macrophages thus promoting cytotoxic anti-tumour activity.

cancer biology↗