Plasma proteometabolome in lung cancer: exploring biomarkers through bidirectional Mendelian randomization and colocalization analysis.

Unlike other cancers with widespread screening (breast, colorectal, cervical, prostate, and skin), lung nodule biopsies for positive screenings have higher morbidity with clinical complications. Development of non-invasive diagnostic biomarkers could thereby significantly enhance lung cancer management for at-risk patients. Here, we leverage Mendelian Randomization (MR) to investigate the plasma proteome and metabolome for potential biomarkers relevant to lung cancer. Utilizing bidirectional MR and co-localization analyses, we identify novel associations, highlighting inverse relationships between plasma proteins SFTPB and KDELC2 in lung adenocarcinoma (LUAD) and positive associations of TCL1A with lung squamous cell carcinoma (LUSC) and CNTN1 with small cell lung cancer (SCLC). Additionally, our work reveals significant negative correlations between metabolites such as theobromine and paraxanthine, along with paraxanthine-related ratios, in both LUAD and LUSC. Conversely, positive correlations are found in caffeine/paraxanthine and arachidonate (20:4n6)/paraxanthine ratios with these cancer types. Through single-cell sequencing data of normal lung tissue, we further explore the role of lung tissue-specific protein SFTPB in carcinogenesis. These findings offer new insights into lung cancer etiology, potentially guiding the development of diagnostic biomarkers and therapeutic approaches.

Multicellular ecotypes shape progression of lung adenocarcinoma from ground-glass opacity toward advanced stages.

Lung adenocarcinoma is a type of cancer that exhibits a wide range of clinical radiological manifestations, from ground-glass opacity (GGO) to pure solid nodules, which vary greatly in terms of their biological characteristics. Our current understanding of this heterogeneity is limited. To address this gap, we analyze 58 lung adenocarcinoma patients via machine learning, single-cell RNA sequencing (scRNA-seq), and whole-exome sequencing, and we identify six lung multicellular ecotypes (LMEs) correlating with distinct radiological patterns and cancer cell states. Notably, GGO-associated neoantigens in early-stage cancers are recognized by CD8+ T cells, indicating an immune-active environment, while solid nodules feature an immune-suppressive LME with exhausted CD8+ T cells, driven by specific stromal cells such as CTHCR1+ fibroblasts. This study also highlights EGFR(L858R) neoantigens in GGO samples, suggesting potential CD8+ T cell activation. Our findings offer valuable insights into lung adenocarcinoma heterogeneity, suggesting avenues for targeted therapies in early-stage disease.

Tet methylcytosine dioxygenase 2 (TET2) deficiency elicits EGFR-TKI (tyrosine kinase inhibitors) resistance in non-small cell lung cancer.

Despite epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) have shown remarkable efficacy in patients with EGFR-mutant non-small cell lung cancer (NSCLC), acquired resistance inevitably develops, limiting clinical efficacy. We found that TET2 was poly-ubiquitinated by E3 ligase CUL7FBXW11 and degraded in EGFR-TKI resistant NSCLC cells. Genetic perturbation of TET2 rendered parental cells more tolerant to TKI treatment. TET2 was stabilized by MEK1 phosphorylation at Ser 1107, while MEK1 inactivation promoted its proteasome degradation by enhancing the recruitment of CUL7FBXW11. Loss of TET2 resulted in the upregulation of TNF/NF-κB signaling that confers the EGFR-TKI resistance. Genetic or pharmacological inhibition of NF-κB attenuate the TKI resistance both in vitro and in vivo. Our findings exemplified how a cell growth controlling kinase MEK1 leveraged the epigenetic homeostasis by regulating TET2, and demonstrated an alternative path of non-mutational acquired EGFR-TKI resistance modulated by TET2 deficiency. Therefore, combined strategy exploiting EGFR-TKI and inhibitors of TET2/NF-κB axis holds therapeutic potential for treating NSCLC patients who suffered from this resistance.

Drug-tolerant persister cells in cancer: the cutting edges and future directions.

Drug-tolerant persister (DTP) cell populations were originally discovered in antibiotic-resistant bacterial biofilms. Similar populations with comparable features have since been identified among cancer cells and have been linked with treatment resistance that lacks an underlying genomic alteration. Research over the past decade has improved our understanding of the biological roles of DTP cells in cancer, although clinical knowledge of the role of these cells in treatment resistance remains limited. Nonetheless, targeting this population is anticipated to provide new treatment opportunities. In this Perspective, we aim to provide a clear definition of the DTP phenotype, discuss the underlying characteristics of these cells, their biomarkers and vulnerabilities, and encourage further research on DTP cells that might improve our understanding and enable the development of more effective anticancer therapies.

Immunotherapy for Recurrent Glioma-From Bench to Bedside.

Glioma is the most aggressive malignant tumor of the central nervous system, and most patients suffer from a recurrence. Unfortunately, recurrent glioma often becomes resistant to established chemotherapy and radiotherapy treatments. Immunotherapy, a rapidly developing anti-tumor therapy, has shown a potential value in treating recurrent glioma. Multiple immune strategies have been explored. The most-used ones are immune checkpoint blockade (ICB) antibodies, which are barely effective in monotherapy. However, when combined with other immunotherapy, especially with anti-angiogenesis antibodies, ICB has shown encouraging efficacy and enhanced anti-tumor immune response. Oncolytic viruses and CAR-T therapies have shown promising results in recurrent glioma through multiple mechanisms. Vaccination strategies and immune-cell-based immunotherapies are promising in some subgroups of patients, and multiple new tumor antigenic targets have been discovered. In this review, we discuss current applicable immunotherapies and related mechanisms for recurrent glioma, focusing on multiple preclinical models and clinical trials in the last 5 years. Through reviewing the current combination of immune strategies, we would like to provide substantive thoughts for further novel therapeutic regimes treating recurrent glioma.

Spatial patterns of the cap-binding complex eIF4F in human melanoma cells.

As a central node of protein synthesis, the cap-binding complex, eukaryotic translation initiation factor 4 F (eIF4F), is involved in cell homeostasis, development and tumorigenesis. A large body of literature exists on the regulation and function of eIF4F in cancer cells, however the intracellular localization patterns of this complex are largely unknown. Since different subsets of mRNAs are translated in distinct subcellular compartments, understanding the distribution of translation initiation factors in the cell is of major interest. Here, we developed an in situ detection method for eIF4F at the single cell level. By using an image-based spot feature analysis pipeline as well as supervised machine learning, we identify five distinct spatial patterns of the eIF4F translation initiation complex in human melanoma cells. The quantity of eIF4F complex per cell correlated with the global mRNA translation activity, and its variation is dynamically regulated by cell state or extracellular stimuli. In contrast, the spatial patterns of eIF4F complexes at the single cell level could distinguish melanoma cells harboring different oncogenic driver mutations. This suggests that different tumorigenic contexts differentially regulate the subcellular localization of mRNA translation, with specific localization of eIF4F potentially associated with melanoma cell chemoresistance.

The multiple roles of LDH in cancer.

High serum lactate dehydrogenase (LDH) levels are typically associated with a poor prognosis in many cancer types. Even the most effective drugs, which have radically improved outcomes in patients with melanoma over the past decade, provide only marginal benefit to those with high serum LDH levels. When viewed separately from the oncological, biochemical, biological and immunological perspectives, serum LDH is often interpreted in very different ways. Oncologists usually see high serum LDH only as a robust biomarker of a poor prognosis, and biochemists are aware of the complexity of the various LDH isoforms and of their key roles in cancer metabolism, whereas LDH is typically considered to be oncogenic and/or immunosuppressive by cancer biologists and immunologists. Integrating these various viewpoints shows that the regulation of the five LDH isoforms, and their enzymatic and non-enzymatic functions is closely related to key oncological processes. In this Review, we highlight that serum LDH is far more than a simple indicator of tumour burden; it is a complex biomarker associated with the activation of several oncogenic signalling pathways as well as with the metabolic activity, invasiveness and immunogenicity of many tumours, and constitutes an extremely attractive target for cancer therapy.

A mathematical model to study the impact of intra-tumour heterogeneity on anti-tumour CD8+ T cell immune response.

Intra-tumour heterogeneity (ITH) has a strong impact on the efficacy of the immune response against solid tumours. The number of sub-populations of cancer cells expressing different antigens and the percentage of immunogenic cells (i.e. tumour cells that are effectively targeted by immune cells) in a tumour are both expressions of ITH. Here, we present a spatially explicit stochastic individual-based model of the interaction dynamics between tumour cells and CD8+ T cells, which makes it possible to dissect out the specific impact of these two expressions of ITH on anti-tumour immune response. The set-up of numerical simulations of the model is defined so as to mimic scenarios considered in previous experimental studies. Moreover, the ability of the model to qualitatively reproduce experimental observations of successful and unsuccessful immune surveillance is demonstrated. First, the results of numerical simulations of this model indicate that the presence of a larger number of sub-populations of tumour cells that express different antigens is associated with a reduced ability of CD8+ T cells to mount an effective anti-tumour immune response. Secondly, the presence of a larger percentage of tumour cells that are not effectively targeted by CD8+ T cells may reduce the effectiveness of anti-tumour immunity. Ultimately, the mathematical model presented in this paper may provide a framework to help biologists and clinicians to better understand the mechanisms that are responsible for the emergence of different outcomes of immunotherapy.

A PD-1/PD-L1 Proximity Assay as a Theranostic Marker for PD-1 Blockade in Patients with Metastatic Melanoma.

PURPOSE: Less than 50% of patients with melanoma respond to anti-programmed cell death protein 1 (anti-PD-1), and this treatment can induce severe toxicity. Predictive markers are thus needed to improve the benefit/risk ratio of immune checkpoint inhibitors (ICI). Baseline tumor parameters such as programmed death ligand 1 (PD-L1) expression, CD8+ T-cell infiltration, mutational burden, and various transcriptomic signatures are associated with response to ICI, but their predictive values are not sufficient. Interaction between PD-1 and its main ligand, PD-L1, appears as a valuable target of anti-PD-1 therapy. Thus, instead of looking at PD-L1 expression only, we evaluated the predictive value of the proximity between PD-1 and its neighboring PD-L1 molecules in terms of response to anti-PD-1 therapy. EXPERIMENTAL DESIGN: PD-1/PD-L1 proximity was assessed by proximity ligation assay (PLA) on 137 samples from two cohorts (exploratory n = 66 and validation n = 71) of samples from patients with melanoma treated with anti-PD-1±anti-CTLA-4. Additional predictive biomarkers, such as PD-L1 expression (MELscore), CD8+ cells density, and NanoString RNA signature, were also evaluated. RESULTS: A PD-1/PD-L1 PLA model was developed to predict tumor response in an exploratory cohort and further evaluated in an independent validation cohort. This score showed higher predictive ability (AUC = 0.85 and 0.79 in the two cohorts, respectively) for PD-1/PD-L1 PLA as compared with other parameters (AUC = 0.71-0.77). Progression-free and overall survival were significantly longer in patients with high PLA values (P = 0.00019 and P < 0.0001, respectively). CONCLUSIONS: The proximity between PD-1 and PD-L1, easily assessed by this PLA on one formalin-fixed paraffin-embedded section, appears as a new biomarker of anti-PD-1 efficacy.

The Role of mRNA Translational Control in Tumor Immune Escape and Immunotherapy Resistance.

Tremendous advances have been made in cancer immunotherapy over the last decade. Among the different steps of gene expression, translation of mRNA is emerging as an essential player in both cancer and immunity. Changes in mRNA translation are both rapid and adaptive, and translational reprogramming is known to be necessary for sustaining cancer cell proliferation. However, the role of mRNA translation in shaping an immune microenvironment permissive to tumors has not been extensively studied. Recent studies on immunotherapy approaches have indicated critical roles of mRNA translation in regulating the expression of immune checkpoint proteins, tuning the secretion of inflammation-associated factors, modulating the differentiation of immune cells in the tumor microenvironment, and promoting cancer resistance to immunotherapies. Careful consideration of the role of mRNA translation in the tumor-immune ecosystem could suggest more effective therapeutic strategies and may eventually change the current paradigm of cancer immunotherapy. In this review, we discuss recent advances in understanding the relationship between mRNA translation and tumor-associated immunity, the potential mechanisms of immunotherapy resistance in cancers linked to translational reprogramming, and therapeutic perspectives and potential challenges of modulating translational regulation in cancer immunotherapy.

In situ detection of the eIF4F translation initiation complex in mammalian cells and tissues.

The eukaryotic translation initiation complex eIF4F plays an important role in gene expression. The methods that are used to monitor the formation of the eIF4F complex are usually indirect and provide no information on its subcellular localization. This protocol describes a proximity ligation assay-based procedure allowing the direct in situ visualization of the eIF4F complex, as well as its absolute quantification per cell using adapted image analysis software. For complete details on the use and execution of this protocol, please refer to Boussemart et al. (2014).

Persistent Cancer Cells: The Deadly Survivors.

Persistent cancer cells are the discrete and usually undetected cells that survive cancer drug treatment and constitute a major cause of treatment failure. These cells are characterized by their slow proliferation, highly flexible energy consumption, adaptation to their microenvironment, and phenotypic plasticity. Mechanisms that underlie their persistence offer highly coveted and sought-after therapeutic targets, and include diverse epigenetic, transcriptional, and translational regulatory processes, as well as complex cell-cell interactions. Although the successful clinical targeting of persistent cancer cells remains to be realized, immense progress has been made in understanding their persistence, yielding promising preclinical results.

Melanoma Persister Cells Are Tolerant to BRAF/MEK Inhibitors via ACOX1-Mediated Fatty Acid Oxidation.

Emerging evidence indicates that non-mutational drug tolerance mechanisms underlie the survival of residual cancer "persister" cells. Here, we find that BRAF(V600E) mutant melanoma persister cells tolerant to BRAF/MEK inhibitors switch their metabolism from glycolysis to oxidative respiration supported by peroxisomal fatty acid ß-oxidation (FAO) that is transcriptionally regulated by peroxisome proliferator-activated receptor alpha (PPARα). Knockdown of the key peroxisomal FAO enzyme, acyl-CoA oxidase 1 (ACOX1), as well as treatment with the peroxisomal FAO inhibitor thioridazine, specifically suppresses the oxidative respiration of persister cells and significantly decreases their emergence. Consistently, a combination treatment of BRAF/MEK inhibitors with thioridazine in human-melanoma-bearing mice results in a durable anti-tumor response. In BRAF(V600E) melanoma samples from patients treated with BRAF/MEK inhibitors, higher baseline expression of FAO-related genes and PPARα correlates with patients' outcomes. These results pave the way for a metabolic strategy to overcome drug resistance.

Cell plasticity in cancer cell populations.

In this review, we propose a recension of biological observations on plasticity in cancer cell populations and discuss theoretical considerations about their mechanisms.

Emerging role of mRNA epitranscriptomic regulation in chemoresistant cancer cells.

Cancer persister cells remain a significant barrier to effective anti-cancer therapy. We found that melanoma persister cells undergo a reversible reprogramming of mRNA translation. A subset of mRNAs, harboring N6-methyladenosine in their 5'-untranslated regions, is translationally up-regulated in an eIF4A-dependent manner. Targeting eIF4A prevents the emergence of resistant clones.

Engineering a Circular Riboregulator in Escherichia coli.

RNAs of different shapes and sizes, natural or synthetic, can regulate gene expression in prokaryotes and eukaryotes. Circular RNAs have recently appeared to be more widespread than previously thought, but their role in prokaryotes remains elusive. Here, by inserting a riboregulatory sequence within a group I permuted intron-exon ribozyme, we created a small noncoding RNA that self-splices to produce a circular riboregulator in Escherichia coli. We showed that the resulting riboregulator can trans-activate gene expression by interacting with a cis-repressed messenger RNA. We characterized the system with a fluorescent reporter and with an antibiotic resistance marker, and we modeled this novel posttranscriptional mechanism. This first reported example of a circular RNA regulating gene expression in E. coli adds to an increasing repertoire of RNA synthetic biology parts, and it highlights that topological molecules can play a role in the case of prokaryotic regulation.

An epitranscriptomic mechanism underlies selective mRNA translation remodelling in melanoma persister cells.

Cancer persister cells tolerate anticancer drugs and serve as the founders of acquired resistance and cancer relapse. Here we show that a subpopulation of BRAFV600 mutant melanoma cells that tolerates exposure to BRAF and MEK inhibitors undergoes a reversible remodelling of mRNA translation that evolves in parallel with drug sensitivity. Although this process is associated with a global reduction in protein synthesis, a subset of mRNAs undergoes an increased efficiency in translation. Inhibiting the eIF4A RNA helicase, a component of the eIF4F translation initiation complex, abrogates this selectively increased translation and is lethal to persister cells. Translation remodelling in persister cells coincides with an increased N6-methyladenosine modification in the 5'-untranslated region of some highly translated mRNAs. Combination of eIF4A inhibitor with BRAF and MEK inhibitors effectively inhibits the emergence of persister cells and may represent a new therapeutic strategy to prevent acquired drug resistance.

Translational control of tumor immune escape via the eIF4F-STAT1-PD-L1 axis in melanoma.

Preventing the immune escape of tumor cells by blocking inhibitory checkpoints, such as the interaction between programmed death ligand-1 (PD-L1) and programmed death-1 (PD-1) receptor, is a powerful anticancer approach. However, many patients do not respond to checkpoint blockade. Tumor PD-L1 expression is a potential efficacy biomarker, but the complex mechanisms underlying its regulation are not completely understood. Here, we show that the eukaryotic translation initiation complex, eIF4F, which binds the 5' cap of mRNAs, regulates the surface expression of interferon-γ-induced PD-L1 on cancer cells by regulating translation of the mRNA encoding the signal transducer and activator of transcription 1 (STAT1) transcription factor. eIF4F complex formation correlates with response to immunotherapy in human melanoma. Pharmacological inhibition of eIF4A, the RNA helicase component of eIF4F, elicits powerful antitumor immune-mediated effects via PD-L1 downregulation. Thus, eIF4A inhibitors, in development as anticancer drugs, may also act as cancer immunotherapies.

Model-based design of RNA hybridization networks implemented in living cells.

Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations.