bims-meluca 2026-06-14 papers

Respir Res. 2026 Jun 10.

Peripheral immune profiling identifies CD8⁺ TEMRA and CD4⁺ T TIGIT⁺ cells as independent prognostic markers for first-line immune checkpoint inhibitors in advanced non-small cell lung cancer.

Jieun Park, Juwhan Choi, Seunghun Lee, Chae Rin Kim, Yeonwoo Lee, Jihyun Park, Yulim Lee, Young Kee Shin, Sung Yong Lee.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have demonstrated substantial clinical benefits in advanced non-small cell lung cancer (NSCLC); however, a subset of patients experience early disease progression despite PD-L1 expression, highlighting the need for biomarkers that better reflect systemic immune competence. We performed comprehensive peripheral immune profiling of patients with advanced NSCLC receiving first-line ICI therapy.
METHODS: Blood samples were collected from patients with advanced NSCLC prior to the initiation of first-line ICI-based therapy. A total of 23 lymphocyte subsets and 13 soluble immune-related factors were analyzed, and multivariate models were used to identify independent prognostic biomarkers.
RESULTS: A total of 74 patients with advanced NSCLC who received first-line ICI therapy were included in this study, none of whom harbored EGFR, ALK, or ROS1 mutations. In multivariate analyses, elevated CD4⁺ T cell immunoreceptor with Ig and ITIM domains (TIGIT)⁺ frequencies independently predicted shorter progression-free survival (hazard ratio (HR) = 3.74, p < 0.001), along with increased CD8⁺ terminally differentiated effector memory T cells re-expressing CD45RA (TEMRA) cells (HR = 1.98, p = 0.01). Consistent with this finding, patients with CD4⁺ T TIGIT⁺ high group exhibited a higher proportion of non-responders (stable or progressive disease) at best response. Non-responder-to-responder transitions between first and best response assessments were observed in the CD4⁺ T TIGIT⁺ low and CD8⁺ TEMRA low groups (p = 0.023 and 0.041, respectively), but not in the corresponding high groups. Cytokine profiling revealed significantly lower granzyme B levels in the CD4⁺ T TIGIT⁺ high group (p = 0.023).
CONCLUSIONS: Baseline frequencies of peripheral CD4⁺ T TIGIT⁺ and CD8⁺ TEMRA cells were independently associated with survival outcomes in advanced NSCLC patients receiving first-line ICI-based therapy, suggesting that peripheral T cell immunophenotyping at treatment initiation may provide prognostic information beyond conventional biomarkers. Further studies incorporating external validation in independent cohorts, longitudinal immune profiling, and deeper T cell subset characterization are warranted to validate these findings and to elucidate the immune dynamics underlying treatment response and resistance.

Keywords: Immunotherapy; Non-small cell lung cancer; Prognostic biomarker; T lymphocytes

DOI: https://doi.org/10.1186/s12931-026-03756-6

Front Cell Dev Biol. 2026 ;14 1856014

Targeting NRF2 addiction in cancer: synthetic lethal strategies beyond direct inhibition.

Melat T Gebru, David Stokoe.

Nuclear factor erythroid 2-related factor 2 (NRF2) (encoded by NFE2L2) is a master regulator of antioxidant, metabolic, and proteostasis pathways. While protective in normal cells, constitutive NRF2 activation driven by loss-of-function mutations in KEAP1, gain-of-function mutations in NFE2L2, or non-mutational mechanisms is common in cancer, occurring in approximately 20%-30% of non-small cell lung cancers and at significant frequencies across multiple tumor types. In cancer, the NRF2 transcriptional program drives metabolic reprogramming, drug resistance, ferroptosis evasion, and immune exclusion making these tumors highly therapy resistant. Despite decades of effort, direct pharmacological inhibition of NRF2 has not achieved clinical success due to its structural undruggability, systemic toxicity, and context-dependent biology. This review focuses on targeting NRF2-driven metabolic dependencies as synthetic lethal vulnerabilities, spanning pathways such as glutaminolysis, redox imbalance, cystine metabolism, nucleotide biosynthesis and ER proteostasis. We also highlight emerging strategies, including allosteric KEAP1 activators, and discuss key challenges in translating these approaches into effective therapies.

Keywords: KEAP1; Nrf2; drug resistance; ferroptosis; glutaminolysis; lung cancer; metabolic reprogramming; reductive stress

DOI: https://doi.org/10.3389/fcell.2026.1856014

Transl Oncol. 2026 Jun 08. pii: S1936-5233(26)00185-3. [Epub ahead of print]70 102848

Pharmacological inhibition of LIF signaling reverses PD-L1-mediated immune suppression in gastric cancer.

Cristina Di Giorgio, Silvia Marchianò, Michele Biagioli, Ginevra Lachi, Carmen Massa, Benedetta Sensini, Eleonora Giannelli, Maria Rosaria Sette, Ginevra Urbani, Francesca Paniconi, Luigi Cari, Maria Chiara Monti, Valentina Sepe, Nicola Natalizi, Luigina Graziosi, Eleonora Distrutti, Annibale Donini, Angela Zampella, Stefano Fiorucci.

INTRODUCTION: Gastric cancer (GC) is a major clinical challenge, characterized by limited response rates to immune checkpoint inhibitors (ICIs) and persistent immune evasion. Leukemia Inhibitory Factor (LIF), an IL-6 family cytokine, reshapes the tumor microenvironment, yet its contribution to PD-L1-mediated immune suppression in GC has not been investigated.
MATERIAL AND METHODS: LIF and PD-L1 expression were quantified in resected GC specimens and matched mucosa by immunohistochemistry and gene expression (Log2), and their associations with clinicopathological variables and survival were evaluated. GC cell lines were exposed to recombinant LIF and to anovel LIF antagonist, LRI-305. Activation of the JAK1/STAT3 pathway, PD-L1 transcription and protein and epithelial-mesenchymal transition (EMT) markers were analyzed. By t-SNE analysis we profiled LIF⁺/PD-L1⁺ cell subsets across myeloid and non-haematopoietic compartments, and by functional assays we have assessed whether LIF blockade modulates T cell activation.
RESULTS: LIF expression was significantly elevated in GC tissues and correlates with poor prognosis and increased PD-L1 levels. LIF promotes immune escape by activating the JAK1/STAT3 pathway, leading to transcriptional upregulation of PD-L1 and enhancement of EMT. The t-SNE analysis revealed that LIF⁺/PD-L1⁺ myeloid and non-hematopoietic cells were enriched in the neoplastic mucosa. Pharmacological blockade of LIF signaling effectively suppressed STAT3 phosphorylation and downregulated PD-L1 expression. LRI-305 treatment partially restored immune activation signatures, supporting its potential as a therapeutic adjuvant to ICIs.
DISCUSSION: LIF/STAT3 enhances PD-L1 expression and participate to GC immune evasion. Targeting LIF signaling could be a strategy to overcome resistance to immunotherapy.

Keywords: Checkpoint blockade; Gastric cancer; Immune evasion; Leukemia inhibitory factor; PD-L1; STAT3; Tumor microenvironment

DOI: https://doi.org/10.1016/j.tranon.2026.102848

BMC Cancer. 2026 Jun 11.

Characteristics and hematological indicators predictors of immunotherapy response in advanced non-small cell lung cancer.

Nan Zhao, Xinyu Wu, Wensi Zhao, Xiang Cheng, Hua He, Dedong Cao.

OBJECTIVE: Immune checkpoint inhibitors (ICIs) have significantly improved the treatment outcomes for advanced non-small cell lung cancer (NSCLC), but patient benefits vary individually. Therefore, identifying biomarkers to predict the efficacy and prognosis of immunotherapy is crucial. Hematological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), albumin-bilirubin (ALBI) score, and lactate dehydrogenase (LDH) levels may correlate with tumor prognosis. This study aimed to evaluate the prognostic value of these hematological and clinical markers in advanced NSCLC patients treated with ICIs, providing a basis for individualized treatment strategies.
METHODS: This retrospective study included NSCLC patients treated with ICIs at the Tumor Centers of Renmin Hospital of Wuhan University and Macheng City People's Hospital between January 2021 and December 2023. Clinical data such as gender, age, ECOG PS score, clinical stage, and treatment details were collected. Patients were stratified based on NLR, PLR, LDH, and ALBI scores. ROC curve analysis assessed the predictive capacity of these markers for mortality risk. Chi-square tests, logistic regression, Kaplan-Meier survival analysis, and log-rank tests were used to analyze short-term efficacy, immune-related adverse events (irAEs), progression-free survival (PFS), and overall survival (OS). Cox regression identified independent prognostic factors for PFS and OS.
RESULTS: A total of 198 advanced NSCLC patients (median follow-up: 28.1 months) were included. Median PFS (mPFS) and OS (mOS) were 7.7 months (95% CI: 6.9 ~ 8.5) and 20.1 months (95% CI: 18.2 ~ 21.9), respectively. ROC analysis demonstrated significant predictive value for baseline NLR, PLR, ALBI, and LDH in mortality risk (AUC: 0.804, 0.694, 0.684, 0.726, respectively). Efficacy analysis revealed PD-L1 positivity (OR = 0.361, 95% CI: 0.161 ~ 0.808, P = 0.013) and ALBI < -2.68 (OR = 2.524, 95% CI: 1.148-5.552, P = 0.021) as independent predictors of objective response rate (ORR: 25.8%), while camrelizumab significantly reduced response rates (OR = 0.157, P = 0.006). Baseline NLR, PLR, ALBI, and LDH significantly stratified PFS (P < 0.05): low NLR (8.7 vs. 7.1 months, P = 0.001), low PLR (7.9 vs. 7.4 months, P = 0.007), low ALBI (8.1 vs. 7.0 months, P = 0.028), and low LDH (9.5 vs. 7.1 months; 46.3% risk reduction, P < 0.001). In the adenocarcinoma subgroup, LDH remained an independent prognostic factor (9.5 vs. 6.8 months, P = 0.032). For squamous cell carcinoma, low NLR (9.1 vs. 7.1 months, P = 0.002), low PLR (10.2 vs. 7.4 months, P = 0.002), low ALBI (8.7 vs. 7.1 months, P = 0.022), and low LDH (9.1 vs. 7.5 months, P = 0.002) were significant. Baseline markers also predicted OS: low NLR (21.4 vs. 17.5 months, P < 0.001), low PLR (20.4 vs. 17.7 months, P = 0.009), and low LDH (21.4 months; 42.5% risk reduction, P < 0.001). Subtype analysis showed adenocarcinoma benefited from low NLR (21.4 vs. 16.5 months, P = 0.013) and low LDH (20.1 vs. 17.5 months, P = 0.021), while squamous carcinoma relied on low NLR (21.4 vs. 16.8 months, P = 0.008), low PLR (21.8 vs. 20.1 months, P = 0.024), low ALBI (21.4 vs. 18.2 months, P = 0.047), and low LDH (24.6 vs. 19.8 months, P = 0.001). Multivariate Cox analysis identified radiotherapy, NLR, and LDH as independent predictors of PFS: Radiotherapy reduced risk by 37.5% (HR = 0.625, P = 0.004); NLR ≥ 3.72 (HR = 1.642) and LDH ≥ 226.5 U/L (HR = 1.821) increased risk by 64.2% and 82.1% (P < 0.05). For OS, adenocarcinoma (HR = 0.361) and squamous carcinoma (HR = 0.350) reduced mortality risk by 63.9% and 65.0% (P < 0.05), while NLR ≥ 3.72 (HR = 1.536), and LDH ≥ 226.5 U/L (HR = 1.728) increased risk by 53.6% and 72.8% (P < 0.05). LDH ≥ 226.5 U/L (HR = 2.372) stained highest risk in squamous carcinoma (P < 0.05).
CONCLUSIONS: Baseline hematological markers (NLR, PLR, ALBI, LDH) are valuable predictors of efficacy and prognosis in advanced NSCLC patients undergoing immunotherapy. Their prognostic roles vary by pathological subtype: squamous carcinoma relies more on inflammatory markers, while adenocarcinoma emphasizes metabolic markers and genetic mutations. This study provides a hematological biomarker-based stratification framework for individualized immunotherapy decisions in advanced NSCLC, offering critical guidance for optimizing treatment and prognosis management.

Keywords: Biomarkers; Immunotherapy; Inflammatory markers; NSCLC; Predictive factors

DOI: https://doi.org/10.1186/s12885-026-16302-w

Methods Cell Biol. 2026 ;pii: S0091-679X(26)00077-4. [Epub ahead of print]208 165-202

Murine models of lung cancer as a platform to investigate cell death.

Marta Tonietto, Vanessa Jäger, Kathrin Maitz, Bettina Flasch, Andreas Reinisch, Julia Kargl, Michael A Dengler, Philipp J Jost.

Alterations in programmed cell death pathways play a critical role in cancer development and maintenance. Yet the detailed mechanisms contributing to tumor initiation, progression, and therapeutic response in lung cancer remain incompletely understood. Also, models to study how changes in the cell death machinery impact tumor-immune interactions are limited. To address this, we describe two complementary murine models of lung adenocarcinoma that enable functional interrogation of cell death pathways in vivo. The first model is a clinically relevant, genetically engineered mouse model (GEMM) driven by KrasG12D activation and Tp53 loss, in which somatic CRISPR-Cas9-mediated gene editing permits tumor cell-specific knockout of candidate genes, facilitates in-depth studies of programmed cell death and immune signaling within 19 weeks. The second approach illustrates how a syngeneic orthotopic transplantation model can be used to study target genes and pathways that influence the tumor microenvironment and immunogenic cell death in a two-week timeframe. Together, these methods provide reproducible and versatile tools to investigate how modulation of cell death pathways impacts lung cancer development and progression and affects the tumor immune microenvironment, thus providing important information to guide the development of novel therapeutic strategies in lung cancer.

Keywords: apotosis; immune signalling; immunogenic cell death; lung adenocarcinoma; murine models; necroptosis; non-small cell lung cancer; preclinical models; programmed cell death; syngeneic orthotopic transplantation model; target validation; translational research; tumor initation; tumor microenvironment; tumor progression

DOI: https://doi.org/10.1016/bs.mcb.2026.02.009

JCI Insight. 2026 Jun 08. pii: e203262. [Epub ahead of print]11(11):

Endoplasmic reticulum-resident α-glucosidase II drives non-small cell lung cancer progression via regulation of secretory glycoproteins.

Shike Wang, Na Ding, Angelo Chen, Derrick Cardin, Yuting Xu, Kate Grimley, William K Russell, Jun Xu, Jonathan M Kurie, Guan-Yu Xiao, Xiaochao Tan.

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide, yet its molecular drivers are not fully defined. Emerging evidence highlights the importance of tumor-stroma interactions mediated by secreted glycoproteins. However, the mechanisms by which cancer cells regulate the secretion of these protumorigenic proteins remain largely unknown. Endoplasmic reticulum-resident (ER-resident) N-glycan-processing enzymes regulate proper protein folding, a prerequisite for glycoproteins to exit the ER and undergo secretion. By evaluating their prognostic significance in lung tumors and conducting functional screening in lung cancer cells, we identify α-glucosidase II (α-Glc II) as a key regulator of NSCLC progression. α-Glc II promotes tumor growth and dissemination in a glucosidase activity-dependent manner in orthotopic mouse lung tumor model. Genetic disruption of α-Glc II induced ER stress and reduced cell proliferation and motility. Mechanistically, α-Glc II-mediated N-glycan modification regulated the ER-to-Golgi trafficking and secretion of specific oncogenic glycoproteins, including lysyl hydroxylase 2 (LH2), Tissue Inhibitor of Metalloproteinase 1 (TIMP1), and TGF-β, which are known to be associated with extracellular matrix remodeling. These findings uncover a role for ER glycosylation machinery in shaping the NSCLC secretome and highlight α-Glc II as a potential therapeutic target.

Keywords: Cancer; Cell biology; Lung cancer; Oncology; Protein traffic

DOI: https://doi.org/10.1172/jci.insight.203262

Sci Rep. 2026 Jun 10.

Bulk and single-cell transcriptomics reveal prognostic signatures of phosphoinositide metabolism in lung adenocarcinoma.

Lihua Zhou, Peng Lei, Zhouguang Luo, Jie Xiao, Zongyu Chen.

Lung adenocarcinoma (LUAD) is one of the most severe malignant tumors. Phosphoinositides metabolism (PIM) plays an important role in maintaining the normal life activities of the organism and regulating tumor development. This study aimed to comprehensively investigate the association between LUAD and PIM. Data on LUAD and PIM-related genes (PIM-RGs) were sourced from public databases. Differential expression, univariate Cox regression analyses, and machine learning were conducted to identify prognostic genes. A risk model was subsequently developed, and LUAD patients were categorized into a high-risk group (HRG) and a low-risk group (LRG). Independent prognostic factors for LUAD were identified, and a nomogram was constructed. Functional enrichment, tumor microenvironment, mutations, and drug sensitivity analyses were also conducted to investigate the molecular mechanisms underlying LUAD. Additionally, single-cell RNA sequencing (scRNA-seq) data analysis was employed to identify key cells and clarify the dynamics of prognostic genes' expression. Ultimately, prognostic gene expression was investigated in clinical samples. MTMR7, GDPD1, MTMR4, and MTMR10 were recognized as prognostic genes. The risk model and nomogram (incorporating risk score and Stage) had good predictive performance. Notably, LUAD's malignant progression might be closely associated with biological processes including cellular protein synthesis, abnormal activation of neuroactive ligand-receptor interactions, and anti-tumor immune responses. Additionally, there was a general positive correlation between the differentially infiltrated immune cells of HRG and LRG. Moreover, TP53 and TTN had relatively high mutation frequencies in both HRG and LRG, and 142 drugs exhibited differential sensitivity between the 2 groups. Interestingly, epithelial cells were identified as LUAD's key cell type, with prognostic gene expression showing dynamic changes as these cells differentiated. Consistently, compared with the control group, GDPD1 and MTMR4 were upregulated, MTMR10 was downregulated, and MTMR7 showed no statistical difference but a certain upward trend in the LUAD group. This study identified 4 prognostic genes and constructed an effective risk model, providing a new perspective on the treatment of LUAD.

Keywords: Lung adenocarcinoma; Phosphoinositides metabolism; Prognostic genes; Risk model; Single-cell transcriptomics

DOI: https://doi.org/10.1038/s41598-026-56684-2