Drug-tolerant persister cells withstand treatments by adapting their identity through lineage-dependent plasticity during systemic anti-cancer therapies. This phenomenon is evident in small-cell lung carcinoma (SCLC), a lethal neuroendocrine cancer initially responsive (60-80%) to platinum-based chemotherapy but succumbing to resistance within 6 months in advanced stages. This resistance associates with the transdifferentiation of residual tumour cells into a non-neuroendocrine state, a process intricately tied to SCLC's chemotolerance, yet molecular mechanisms governing this lineage conversion remain completed understood. Here we report that first-line chemotherapy induces translation initiation factor eIF6 in drug-tolerant persister-like cells in SCLC, associating with the non-neuroendocrine state in both SCLC genetically engineered mouse model and patient samples. Intervening eIF6 inhibits non-neuroendocrine transdifferentiation, thus enhancing SCLC responsiveness to chemotherapy. Mechanistically, therapy-induced eIF6 dissociates from ribosomes whereas interacts with the extracellular matrix complex CD104/FAK, leading to the activation of MAPK pathway and a global translational remodelling in SCLC drug-tolerant persister-like cells. This prompts us to develop an eIF6-CD104/FAK proximity ligation assay applicable to clinical samples, showing its prognostic value for SCLC clinical outcomes. This study of eIF6’s moonlight function sheds light on its potential therapeutic interventions to mitigate treatment resistance in SCLC.

Tumors often face energy deprivation due to mutations, hypoxia, and nutritional deficiencies within the harsh tumor microenvironment (TME), and as an effect of anticancer treatments. This metabolic stress triggers adaptive reprogramming of mRNA translation, which in turn adjusts metabolic plasticity and associated signaling pathways to ensure tumor cell survival. Emerging evidence is beginning to reveal the complex interplay between metabolism and mRNA translation, shedding light on the mechanisms that synchronize ribosome assembly and reconfigure translation programs under metabolic stress. This review explores recent advances in our understanding of the coordination between metabolism and mRNA translation, offering insights that could inform therapeutic strategies targeting both cancer metabolism and translation, with the aim of disrupting cancer cell plasticity and survival.

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.

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.

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.