bims-meluca 2025-01-19 papers

Technol Cancer Res Treat. 2025 Jan-Dec;24:24 15330338251313945

Dynamics of VEGF-А, Аngiopoietin-2 and HIF-1α Levels in Patients with Brain Metastases Treated with Cyberknife Radiosurgery.

Veselin Popov, Gabriela Raycheva, Zhanet Grudeva-Popova.

The contemporary concept of carcinogenesis summarizes the role of hypoxia, neoangiogenesis, and hemostasis, including in the stage of progression and metastasis of the tumor process. Metastatic disease is a serious therapeutic challenge for any oncological condition. The purpose of this study was to evaluate the dynamics of specific indicators of neoangiogenesis and hypoxia as potential biomarkers for therapeutic efficacy or risk of disease progression in patients with brain metastases (BM) undergoing robotic stereotactic radiosurgery. Two groups of patients (lung cancer and other types of cancers) with oligometastatic disease and brain metastases were included. The patients (n = 66) were treated CyberKnife system. Human Angiopoietin-2, Hypoxia inducible factor 1 α (HIF-1α) and human Vascular Endothelial Growth Factor-А (VEGF-А) were measured in this prospective longitudinal study. Analysis of human Angiopoietin-2, HIF-1α, human VEGF-A in the post-treatment period showed a statistically significant decrease between the baseline and the 6 months post-treatment time point in both patient groups. The baseline value of serum VEGF-А in the group with lung cancer decreased by 40%, Аngiopoietin-2-by 48%, HIF-1α -by 43%. In the group with other types of cancers, VEGF-А decreased by 54.75%, Аngiopoietin-2-by 52%, HIF-1α -by 39.5%. Despite the significant reduction, the levels remained significantly higher in both groups than in healthy controls. This study underscores the potential of integrating molecular markers like VEGF-A, Angiopoietin-2, and HIF-1α into clinical decision-making to enhance outcomes for patients with brain metastases undergoing RSRS.

Keywords: CyberKnife; Hypoxia inducible factor 1 (HIF-1α); brain metastases; human Angiopoietin-2; human VEGF-A; robotic stereotactic radiosurgery; solid tumors

DOI: https://doi.org/10.1177/15330338251313945

Transl Cancer Res. 2024 Dec 31. 13(12): 6936-6946

IRF5 as a potential immunological biomarker in lung adenocarcinoma.

Simei Li, Fangling Zhou, Huahong Lan, Xiaofei Cao, Alice Mogenet, Roberto Díaz-Peña, Meiling Zhao.

Background: In the clinic, the primary conventional treatments of advanced non-small cell lung cancer (NSCLC) are surgery, radiation therapy, and chemotherapy. In recent years, immune checkpoint inhibitors (ICIs) have shown promise in optimizing therapeutic benefits when combined with other immunotherapies or standard therapies. However, effective biomarkers for distant metastasis or recurrence have yet to be identified, making it difficult to determine the best therapeutic approaches. The effect of tumor immunotherapy, as well as metastasis and recurrence, are thought to be significantly affected by the tumor immunosuppressive microenvironment. Transcription factor interferon regulatory factor 5 (IRF5) is a critical regulator of the immune response. It has been found to play an important role in malignant tumor transformation, immune regulation, clinical prognosis, and the treatment response. Nevertheless, its precise role in the advancement of NSCLC, including lung adenocarcinoma (LUAD) remains poorly understood. This study sought to investigate the expression of IRF5 in LUAD and its effect on patient prognosis, and examine the biological function of IRF5. Additionally, the study aimed to examine the association between IRF5 expression and immune cell infiltration, as well as its correlation with key immune checkpoint genes relevant to NSCLC.
Methods: LUAD RNA-sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and analyzed. A tissue microarray (TMA) analysis was conducted to detect IRF5 expression, and immunofluorescence staining was performed to determine immune infiltration. Bioinformatics and TMA analyses, including a differential expression analysis, prognosis prediction analysis, correlation analysis, immune infiltration analysis, and gene set enrichment analysis (GSEA), were conducted using the TCGA dataset.
Results: The results showed that the expression levels of IRF5 were lower in the LUAD tissues than the normal lung tissues. Patients with high IRF5 expression had longer survival times than those with low IRF5 expression. IRF5 was also found to be correlated with lymph node metastasis. Nine distinct types of immune cells were identified between the groups with high and low IRF5 expression levels. Eight major immune checkpoint genes were found to be upregulated in LUAD patients with high IRF5 expression levels. The enrichment analyses showed that various immune pathways were enriched in the LUAD samples with IRF5, including T cell activation, lymphocyte activation, and T cell receptor activation.
Conclusions: IRF5 expression is closely related to tumor immunity and immunotherapy in LUAD patients. IRF5 may be indicative of prognosis in LUAD patients.

Keywords: Interferon regulatory factor 5 (IRF5); biomarker; lung adenocarcinoma (LUAD)

DOI: https://doi.org/10.21037/tcr-2024-2354

Cancer Manag Res. 2025 ;17 45-56

Gut Microbiome and Metabolite Characteristics Associated With Different Clinical Stages in Non-Small Cell Lung Cancer Patients.

Fan Liu, Xingbing Lu, Mengli Tang, Yuzuo Chen, Xi Zheng.

Objective: Our research has pinpointed the gut microbiome's role in the progression of various pathological types of non-small cell lung cancer (NSCLC). Nonetheless, the characteristics of the gut microbiome and its metabolites across different clinical stages of NSCLC are yet to be fully understood. The current study seeks to explore the distinctive gut flora and metabolite profiles of NSCLC patients across varying TNM stages.
Methods: The research team gathered stool samples from 52 patients diagnosed with non-small cell lung cancer (NSCLC) and 29 healthy individuals. Subsequently, they performed 16S rRNA gene amplification sequencing and untargeted gas/liquid chromatography-mass spectrometry metabolomics analysis.
Results: The study revealed that the alpha-diversity of the gut microbiome in NSCLC patients at different stages did not exhibit statistically significant differences. Notably, Lachnospira and Blautia were more abundant in healthy controls. The distribution of gut microbial species in patients with varying stages of NSCLC was uneven, with Bacteroides and Bacteroidaceae being most prevalent in stage T2, and Prevotella dominating in stage T4. Levels of Ruminococcus gnavus were notably elevated in stages N3 and M. The genus levels of Klebsiella, Parabacteroides, and Tannerellaceae were higher in stage II patients. Rodentibacter was the bacterium with increased levels in stage III NSCLC patients. Further metabolomics studies revealed significantly elevated levels of quinic acid and 3-hydroxybenzoic acid in the healthy control group. In contrast, Stage I+II non-small cell lung cancer (NSCLC) patients exhibited reduced levels of L-cystathionine. Notably, quinic acid, phthalic acid, and L-lactic acid were observed to be increased in Stage III+IV NSCLC patients.
Conclusion: Compared to the analysis of a single microbial dataset, this study provides deeper functional insights by incorporating comprehensive metabolomic profiling. This approach demonstrates that both the gut microbiome and associated metabolites are altered in NSCLC patients across different clinical stages. Our findings may offer novel perspectives on the pathogenesis of NSCLC at various TNM stages. Further research is warranted to validate and clinically apply these potential biomarkers.

Keywords: clinical stages; gut microbiome; metabolites; non-small cell lung cancer

DOI: https://doi.org/10.2147/CMAR.S499003

Cancers (Basel). 2024 Dec 26. pii: 37. [Epub ahead of print]17(1):

Prognostic Value of Blood-Based Inflammatory Markers in Cancer Patients Receiving Immune Checkpoint Inhibitors.

Mustafa Murat Midik, Damla Gunenc, Pınar Fatma Acar, Burcak Saziye Karaca.

Background: Although immune checkpoint inhibitors (ICIs) have significantly improved cancer treatment, a substantial proportion of patients do not benefit from these therapies, revealing the crucial need to identify reliable biomarkers. Inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), pan-immune inflammation value (PIV), systemic inflammation response index (SIRI), lactate dehydrogenase (LDH), and C-reactive protein (CRP), may provide insights into treatment outcomes. Objectives: This study aimed to evaluate the prognostic value of multiple inflammatory markers in patients with cancer receiving ICI-based therapies. Methods: A retrospective analysis was performed on 226 patients treated with ICI-based therapies at a single center between 2012 and 2023. The inflammatory markers NLR, PIV, SII, SIRI, LDH, CRP, and albumin were assessed. Cut-off values were determined using maximally selected rank statistics, and overall survival (OS) and progression-free survival (PFS) were evaluated using the Kaplan-Meier method and Cox regression analysis. Results: High NLR, PIV, SII, SIRI, LDH, and CRP, as well as low albumin levels, were associated with worse OS and PFS (p < 0.001). In the multivariate analysis, high CRP, LDH, NLR, PIV, and SII independently predicted worse OS. Conclusions: Our findings confirm the prognostic utility of several inflammatory biomarkers in patients with cancer receiving ICIs, highlighting their potential for treatment stratification. Further studies are necessary to standardize cut-off values and validate these findings across broader, more diverse populations.

Keywords: cancer prognosis; immune checkpoint inhibitors; inflammatory biomarkers; neutrophil-to-lymphocyte ratio (NLR); overall survival (OS); systemic immune-inflammation index (SII)

DOI: https://doi.org/10.3390/cancers17010037

Nat Commun. 2025 Jan 12. 16(1): 614

Integration of clinical, pathological, radiological, and transcriptomic data improves prediction for first-line immunotherapy outcome in metastatic non-small cell lung cancer.

Nicolas Captier, Marvin Lerousseau, Fanny Orlhac, Narinée Hovhannisyan-Baghdasarian, Marie Luporsi, Erwin Woff, Sarah Lagha, Paulette Salamoun Feghali, Christine Lonjou, Clément Beaulaton, Andrei Zinovyev, Hélène Salmon, Thomas Walter, Irène Buvat, Nicolas Girard, Emmanuel Barillot.

Immunotherapy is improving the survival of patients with metastatic non-small cell lung cancer (NSCLC), yet reliable biomarkers are needed to identify responders prospectively and optimize patient care. In this study, we explore the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We analyze baseline multimodal data from a cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, including positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information. Testing multiple integration strategies, most of them yield multimodal models surpassing both the best unimodal models and established univariate biomarkers, such as PD-L1 expression. Additionally, several multimodal combinations demonstrate improved patient risk stratification compared to models built with routine clinical features only. Our study thus provides evidence of the superiority of multimodal over unimodal approaches, advocating for the collection of large multimodal NSCLC datasets to develop and validate robust and powerful immunotherapy biomarkers.

DOI: https://doi.org/10.1038/s41467-025-55847-5