CXCL9 correlates with antitumor immunity and is predictive of a favorable prognosis in uterine corpus endometrial carcinoma

Natural killer cells: the immune frontline against circulating tumor cells

Natural killer (NK) play a key role in controlling tumor dissemination by mediating cytotoxicity towards cancer cells without the need of education. These cells are pivotal in eliminating circulating tumor cells (CTCs) from the bloodstream, thus limiting cancer spread and metastasis. However, aggressive CTCs can evade NK cell surveillance, facilitating tumor growth at distant sites. In this review, we first discuss the biology of NK cells, focusing on their functions within the tumor microenvironment (TME), the lymphatic system, and circulation. We then examine the immune evasion mechanisms employed by cancer cells to inhibit NK cell activity, including the upregulation of inhibitory receptors. Finally, we explore the clinical implications of monitoring circulating biomarkers, such as NK cells and CTCs, for therapeutic decision-making and emphasize the need to enhance NK cell-based therapies by overcoming immune escape mechanisms.

Hepatic Growth Factor as a Potential Biomarker for Lung Adenocarcinoma: A Multimodal Study

(1) Background: Despite previous studies linking inflammatory cytokines to lung adenocarcinoma (LUAD), their causal mechanisms remain unclear. This study aims to explore the causal relationship between inflammatory cytokines and LUAD to fill this knowledge gap. (2) Methods: This study employs a comprehensive approach, integrating Mendelian randomization (MR) analysis, single-cell RNA sequencing (scRNA-seq), and transcriptomic sequencing (RNA-seq) data to investigate the relationship between inflammatory cytokines and LUAD. (3) Results: In forward MR analysis, elevated levels of hepatocyte growth factor (HGF), interleukin-1 receptor antagonist (IL-1RA), IL-5, monocyte chemoattractant protein-3, and monokine induced by interferon-γ were causally associated with an increased risk of LUAD. In reverse MR analysis, LUAD exhibited a positive causal relationship with the levels of regulated upon activation normal T cell expressed and secreted factor (RANTES) and stromal cell-derived factor-1α. The scRNA-seq data further identified specific cell populations that may influence LUAD onset and progression through the expression of particular inflammatory genes and intercellular communication. RNA-seq data analysis highlighted the role of the HGF gene in LUAD diagnosis, demonstrating its strong correlation with patient prognosis and immune cell infiltration within the tumor microenvironment. (4) Conclusions: The findings reveal a causal relationship between inflammatory cytokines and LUAD, with HGF emerging as a potential biomarker of significant clinical relevance. This study provides new insights into the molecular mechanisms underlying LUAD and lays the foundation for future therapeutic strategies.

Quantification and Profiling of Early and Late Differentiation Stage T Cells in Mantle Cell Lymphoma Reveals Immunotherapeutic Targets in Subsets of Patients

With the aim to advance the understanding of immune regulation in MCL and to identify targetable T-cell subsets, we set out to combine image analysis and spatial omic technology focused on both early and late differentiation stages of T cells. MCL patient tissue (n = 102) was explored using image analysis and GeoMx spatial omics profiling of 69 proteins and 1812 mRNAs. Tumor cells, T helper (TH) cells and cytotoxic (TC) cells of early (CD57-) and late (CD57+) differentiation stage were analyzed. An image analysis workflow was developed based on fine-tuned Cellpose models for cell segmentation and classification. TC and CD57+ subsets of T cells were enriched in tumor-rich compared to tumor-sparse regions. Tumor-sparse regions had a higher expression of several key immune suppressive proteins, tentatively controlling T-cell expansion in regions close to the tumor. We revealed that T cells in late differentiation stages (CD57+) are enriched among MCL infiltrating T cells and are predictive of an increased expression of immune suppressive markers. CD47, IDO1 and CTLA-4 were identified as potential targets for patients with T-cell-rich MCL TIME, while GITR might be a feasible target for MCL patients with sparse T-cell infiltration. In subgroups of patients with a high degree of CD57+ TC-cell infiltration, several immune checkpoint inhibitors, including TIGIT, PD-L1 and LAG3 were increased, emphasizing the immune-suppressive features of this highly differentiated T-cell subset not previously described in MCL.

TMErisk score: A tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma

Tumor microenvironment (TME) is closely associated with the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). To investigate potential biomarkers for predicting therapeutic outcomes in HNSCC, we analyzed the immune and stromal status of HNSCC based on the genes associated with TME using the ESTIMATE algorithm. Immune and stromal genes were identified with differential gene expression and weighted gene co-expression network analysis (WGCNA). From these genes, 118 were initially selected through Cox univariate regression and then further input into least absolute shrinkage and selection operator (LASSO) regression analysis. As a result, 11 genes were screened out for the TME-related risk (TMErisk) score model which presented promising overall survival predictive potential. The TMErisk score was negatively associated with immune and stromal scores but positively associated with tumor purity. Individuals with high TMErisk scores exhibited decreased expression of most immune checkpoints and all human leukocyte antigen family genes, and reduced abundance of infiltrating immune cells. Divergent genes were mutated in HNSCC. In both high and low TMErisk score groups, the tumor protein P53 exhibited the highest mutation frequency. A higher TMErisk score was found to be associated with reduced overall survival probability and worse outcomes of immunotherapy. Therefore, the TMErisk score could serve as a valuable model for the outcome prediction of HNSCC in clinic.

Hantavirus Pulmonary Syndrome Caused by Puumala Orthohantavirus-A Case Report and Literature Review

In this article, we report on a rare case of acute respiratory distress syndrome (ARDS) caused by the Puumala orthohantavirus (PUUV), which is typically associated with hemorrhagic fever with renal syndrome (HFRS). This is the first documented case of PUUV-associated ARDS in Southeast Europe. The diagnosis was confirmed by serum RT-PCR and serology and corroborated by phylogenetic analysis and chemokine profiling. The patient was a 23-year-old male from Zagreb, Croatia, who had recently traveled throughout Europe. He presented with fever, headache, abdominal pain, and sudden onset of ARDS. Treatment involved high-flow nasal cannula oxygen therapy and glucocorticoids, which resulted in a full recovery. A systematic literature review identified 10 cases of hantavirus pulmonary syndrome (HPS) caused by PUUV in various European countries and Turkey between 2002 and 2023. The median age of patients was 53 years (range 24-73), and six of the patients were male. Most patients were treated in intensive care units, but none received antiviral therapy targeting PUUV. Eight patients survived hospitalization. The presented case highlights the importance of considering HPS in the differential diagnosis of ARDS, even in areas where HFRS is the dominant form of hantavirus infection.

CT radiomics prediction of CXCL9 expression and survival in ovarian cancer

BACKGROUND

C-X-C motif chemokine ligand 9 (CXCL9), which is involved in the pathological processes of various human cancers, has become a hot topic in recent years. We developed a radiomic model to identify CXCL9 status in ovarian cancer (OC) and evaluated its prognostic significance.

METHODS

We analyzed enhanced CT scans, transcriptome sequencing data, and corresponding clinical characteristics of CXCL9 in OC using the TCIA and TCGA databases. We used the repeat least absolute shrinkage (LASSO) and recursive feature elimination(RFE) methods to determine radiomic features after extraction and normalization. We constructed a radiomic model for CXCL9 prediction based on logistic regression and internal tenfold cross-validation. Finally, a 60-month overall survival (OS) nomogram was established to analyze survival data based on Cox regression.

RESULTS

CXCL9 mRNA levels and several other genes involving in T-cell infiltration were significantly relevant to OS in OC patients. The radiomic score (rad_score) of our radiomic model was calculated based on the five features for CXCL9 prediction. The areas under receiver operating characteristic (ROC) curves (AUC-ROC) for the training cohort was 0.781, while that for the validation cohort was 0.743. Patients with a high rad_score had better overall survival (P < 0.001). In addition, calibration curves and decision curve analysis (DCA) showed good consistency between the prediction and actual observations, demonstrating the clinical utility of our model.

CONCLUSION

In patients with OC, the radiomics signature(RS) of CT scans can distinguish the level of CXCL9 expression and predict prognosis, potentially fulfilling the ultimate purpose of precision medicine.