STK11 pathway in vitro validation

Lehtiö, Janne; Arslan, Taner; Siavelis, Ioannis; Pan, Yifei; Socciarelli, Fabio; Berkovska, Olena; Umer, Husen M.; Mermelekas, Georgios; Pirmoradian, Mohammad; Jönsson, Mats; Brunnström, Hans; Brustugun, Odd Terje; Purohit, Krishna Pinganksha; Cunningham, Richard; Asl, Hassan Foroughi; Isaksson, Sten; Arbajian, Elsa; Aine, Mattias; Karlsson, Anna; Kotevska, Marija; Hanson, Carsten Gram; Haakensen, Vilde Drageset; Helland, Åslaug; Tamborero, David; Johansson, Henrik J.; Branca, Rui M.; Staaf, Johan; Orre, Lukas M.

doi:10.21203/rs.3.pex-1561/v1

Cited by 3 publications

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“…There is an urgent need to better link multi-omic analysis with clinically relevant cohorts and outcomes. This was attempted in a cohort of mostly early-stage (87%) NSCLC tumors using proteogenomics [80].…”

Section: Phosphoproteomic Analysis Revealed Interesting Insights Into...mentioning

confidence: 99%

Clinical applications of mass spectrometry‐based proteomics in cancer: Where are we?

et al. 2022

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Tumor tissue processing methodologies in combination with data‐independent acquisition mass spectrometry (DIA‐MS) have emerged that can comprehensively analyze the proteome of multiple tumor samples accurately and reproducibly. Increasing recognition and adoption of these technologies has resulted in a tranche of studies providing novel insights into cancer classification systems, functional tumor biology, cancer biomarkers, treatment response and drug targets. Despite this, with some limited exceptions, MS‐based proteomics has not yet been implemented in routine cancer clinical practice. Here, we summarize the use of DIA‐MS in studies that may pave the way for future clinical cancer applications, and highlight the role of alternative MS technologies and multi‐omic strategies. We discuss limitations and challenges of studies in this field to date and propose steps for integrating proteomic data into the cancer clinic.

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Section: Phosphoproteomic Analysis Revealed Interesting Insights Into...mentioning

confidence: 99%

Clinical applications of mass spectrometry‐based proteomics in cancer: Where are we?

et al. 2022

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“…Mutations in liver kinase B1 (LKB1) gene, which encodes Serine/Threonine Kinase 11 (STK11), the 3 rd most mutated gene in the mKRAS cohort (after KRAS and TP53), regulates metabolism, energy sensing and modulates the stimulator of interferon genes (STING) pathway (Esteve-Puig et al, 2014;Kim et al, 2019). STK11 mutations are associated with immunologically cold tumors (Schabath et al, 2016), increased neutrophil accumulation (Koyama et al, 2016), high expression of LAG3 ligand, FLG1 (Wang et al, 2019;Lehtiö et al, 2021), and poor outcomes in patients with mKRAS (Skoulidis et al, 2018). Anaplastic Lymphoma Kinase (ALK) mutations, found in 7.7% (24/ 313) of WT tumors, 4% (7/163) of mKRAS tumors, can generate an immunosuppressive microenvironment unresponsive to checkpoint blockade alone (Hellmann et al, 2018;Sankar et al, 2021).…”

Section: Mutations In Driver Genes With Possible Immune Consequencesmentioning

confidence: 99%

Evolutionary selection identifies critical immune-relevant genes in lung cancer subtypes

et al. 2022

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In an evolving population, proliferation is dependent on fitness so that a numerically dominant population typically possesses the most well adapted phenotype. In contrast, the evolutionary “losers” typically disappear from the population so that their genetic record is lost. Historically, cancer research has focused on observed genetic mutations in the dominant tumor cell populations which presumably increase fitness. Negative selection, i.e., removal of deleterious mutations from a population, is not observable but can provide critical information regarding genes involved in essential cellular processes. Similar to immunoediting, “evolutionary triage” eliminates mutations in tumor cells that increase susceptibility to the host immune response while mutations that shield them from immune attack increase proliferation and are readily observable (e.g., B2M mutations). These dynamics permit an “inverse problem” analysis linking the fitness consequences of a mutation to its prevalence in a tumor cohort. This is evident in “driver mutations” but, equally important, can identify essential genes in which mutations are seen significantly less than expected by chance. Here we utilized this new approach to investigate evolutionary triage in immune-related genes from TCGA lung adenocarcinoma cohorts. Negative selection differs between the two cohorts and is observed in endoplasmic reticulum aminopeptidase genes, ERAP1 and ERAP2 genes, and DNAM-1/TIGIT ligands. Targeting genes or molecular pathways under positive or negative evolutionary selection may permit new treatment options and increase the efficacy of current immunotherapy.

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Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune-evasion mechanisms

et al. 2021

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Despite major advancements in lung cancer treatment, long-term survival is still rare, and a deeper understanding of molecular phenotypes would allow the identification of specific cancer dependencies and immune evasion mechanisms. Here we performed in-depth mass spectrometry (MS)-based proteogenomic analysis of 141 tumors representing all major histologies of non-small cell lung cancer (NSCLC). We identified six distinct proteome subtypes with striking differences in immune cell composition and subtype-specific expression of immune checkpoints. Unexpectedly, high neoantigen burden was linked to global hypomethylation and complex neoantigens mapped to genomic regions, such as endogenous retroviral elements and introns, in immune-cold subtypes. Further, we linked immune evasion with LAG3 via STK11 mutation-dependent HNF1A activation and FGL1 expression. Finally, we develop a data-independent acquisition MS-based NSCLC subtype classification method, validate it in an independent cohort of 208 NSCLC cases and demonstrate its clinical utility by analyzing an additional cohort of 84 late-stage NSCLC biopsy samples.

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STK11 pathway in vitro validation

Cited by 3 publications

References 0 publications

Clinical applications of mass spectrometry‐based proteomics in cancer: Where are we?

Clinical applications of mass spectrometry‐based proteomics in cancer: Where are we?

Evolutionary selection identifies critical immune-relevant genes in lung cancer subtypes

Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune-evasion mechanisms

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