NRXN1 as a novel potential target of antibody-drug conjugates for small cell lung cancer

Small Cell Lung Cancer Neuronal Features and Their Implications for Tumor Progression, Metastasis, and Therapy

Small cell lung cancer (SCLC) is an epithelial neuroendocrine form of lung cancer for which survival rates remain dismal and new therapeutic approaches are greatly needed. Key biological features of SCLC tumors include fast growth and widespread metastasis, as well as rapid resistance to treatment. Similar to pulmonary neuroendocrine cells, SCLC cells have traits of both hormone-producing cells and neurons. In this study, we specifically discuss the neuronal features of SCLC. We consider how neuronal G protein-coupled receptors and other neuronal molecules on the surface of SCLC cells can contribute to the growth of SCLC tumors and serve as therapeutic targets in SCLC. We also review recent evidence for the role of neuronal programs expressed by SCLC cells in the fast proliferation, migration, and metastasis of these cells. We further highlight how these neuronal programs may be particularly relevant for the development of brain metastases and how they can assist SCLC cells to functionally interact with neurons and astrocytes. A greater understanding of the molecular and cellular neuronal features of SCLC is likely to uncover new vulnerabilities in SCLC cells, which may help develop novel therapeutic approaches. More generally, the epithelial-to-neuronal transition observed during tumor progression in SCLC and other cancer types can contribute significantly to tumor development and response to therapy.

Mechanistic insights into FEN1-mediated drug sensitivity and risk signature in colon cancer: An integrative bioinformatics study

The overexpression of Flap endonuclease 1 (FEN1) has been implicated in drug resistance and prognosis across various cancer types. However, the precise role of FEN1 in colon cancer remains to be fully elucidated. In this study, we employed comprehensive datasets from The Cancer Genome Atlas, Gene Expression Omnibus, and Human Protein Atlas to examine FEN1 expression and assess its correlation with clinical pathology and prognosis in colon cancer. We utilized the pRRophetic algorithm to evaluate drug sensitivity and performed differential expression analysis to identify genes associated with FEN1-mediated drug sensitivity. Gene set enrichment analysis was conducted to further investigate these genes. Additionally, single-cell sequencing analysis was employed to explore the relationship between FEN1 expression and functional states. Cox regression analysis was implemented to construct a prognostic model, and a nomogram for prognosis was developed. Our analysis of The Cancer Genome Atlas and Gene Expression Omnibus datasets revealed a significant upregulation of FEN1 in colon cancer. However, while FEN1 expression showed no notable correlation with prognosis, it displayed associations with metastasis. Single-cell sequencing analysis further confirmed a positive correlation between FEN1 expression and colon cancer metastasis. Furthermore, we detected marked discrepancies in drug responsiveness between the High_FEN1 and Low_FEN1 groups, identifying 342 differentially expressed genes. Enrichment analysis showed significant suppression in processes related to DNA replication, spliceosome, and cell cycle pathways in the Low_FEN1 group, while the calcium signaling pathway, cAMP signaling pathway, and other pathways were activated. Of the 197 genes differentially expressed and strongly linked to FEN1 expression, 39 were significantly implicated in colon cancer prognosis. Finally, we constructed a risk signature consisting of 5 genes, which, when combined with drug treatment and pathological staging, significantly improved the prediction of colon cancer prognosis. This study offers novel insights into the interplay among FEN1 expression levels, colon cancer metastatic potential, and sensitivity to therapeutic agents. Furthermore, we successfully developed a multi-gene prognostic risk signature derived from FEN1.

Actionable Driver Events in Small Cell Lung Cancer

Small cell lung cancer (SCLC) stands out as the most aggressive form of lung cancer, characterized by an extremely high proliferation rate and a very poor prognosis, with a 5-year survival rate that falls below 7%. Approximately two-thirds of patients receive their diagnosis when the disease has already reached a metastatic or extensive stage, leaving chemotherapy as the remaining first-line treatment option. Other than the recent advances in immunotherapy, which have shown moderate results, SCLC patients cannot yet benefit from any approved targeted therapy, meaning that this cancer remains treated as a uniform entity, disregarding intra- or inter-tumoral heterogeneity. Continuous efforts and technological improvements have enabled the identification of new potential targets that could be used to implement novel therapeutic strategies. In this review, we provide an overview of the most recent approaches for SCLC treatment, providing an extensive compilation of the targeted therapies that are currently under clinical evaluation and inhibitor molecules with promising results in vitro and in vivo.

Unlocking New Horizons in Small-Cell Lung Cancer Treatment: The Onset of Antibody-Drug Conjugates

Small-cell lung cancer (SCLC) is a highly aggressive disease, accounting for about 15% of all lung cancer cases. Despite initial responses to chemoimmunotherapy, SCLC recurs and becomes resistant to treatment. Recently, antibody-drug conjugates (ADCs) have emerged as a promising therapeutic option for SCLC. ADCs consist of an antibody that specifically targets a tumor antigen linked to a cytotoxic drug. The antibody delivers the drug directly to the cancer cells, minimizing off-target toxicity and improving the therapeutic index. Several ADCs targeting different tumor antigens are currently being evaluated in clinical trials for SCLC. Despite the negative results of rovalpituzumab tesirine (Rova-T), other ADCs targeting different antigens, such as B7-H3, seizure-related homolog 6 (SEZ6), and CEACAM5, have also been investigated in clinical trials, including for SCLC, and their results suggest preliminary activity, either alone or in combination with other therapies. More recently, sacituzumab govitecan, an anti-TROP2 ADC, demonstrated promising activity in lung cancer, including SCLC. Furthermore, an anti-B7-H3 (CD276), ifinatamab deruxtecan (DS7300A), showed a high response rate and durable responses in heavily pretreated SCLC. Overall, ADCs represent an intriguing approach to treating SCLC, particularly in the relapsed or refractory setting. Further studies are needed to determine their efficacy and safety and the best location in the treatment algorithm for SCLC. In this review, we aim to collect and describe the results regarding the past, the present, and the future of ADCs in SCLC.

Inferring ligand-receptor cellular networks from bulk and spatial transcriptomic datasets with BulkSignalR

The study of cellular networks mediated by ligand-receptor interactions has attracted much attention recently owing to single-cell omics. However, rich collections of bulk data accompanied with clinical information exists and continue to be generated with no equivalent in single-cell so far. In parallel, spatial transcriptomic (ST) analyses represent a revolutionary tool in biology. A large number of ST projects rely on multicellular resolution, for instance the Visium™ platform, where several cells are analyzed at each location, thus producing localized bulk data. Here, we describe BulkSignalR, a R package to infer ligand-receptor networks from bulk data. BulkSignalR integrates ligand-receptor interactions with downstream pathways to estimate statistical significance. A range of visualization methods complement the statistics, including functions dedicated to spatial data. We demonstrate BulkSignalR relevance using different datasets, including new Visium liver metastasis ST data, with experimental validation of protein colocalization. A comparison with other ST packages shows the significantly higher quality of BulkSignalR inferences. BulkSignalR can be applied to any species thanks to its built-in generic ortholog mapping functionality.

Identification of immune-related molecular markers in intracranial aneurysm (IA) based on machine learning and cytoscape-cytohubba plug-in

BACKGROUND

Intracranial aneurysm (IA) is a common cerebrovascular disease. The immune mechanism of IA is more complicated, and it is unclear so far. Therefore, it is necessary to continue to explore the immune related molecular mechanism of IA.

METHODS

All data were downloaded from the public database. Limma package and ssGSEA algorithm was used to identify differentially expressed mRNAs (DEmRNAs) and analyze immune cell infiltration, respectively. Machine learning and cytoscape-cytohubba plug-in was used to identify key immune types and multicentric DEmRNAs of IA, respectively. Multicentric DEmRNAs related to key immune cells were screened out as key DEmRNAs by Spearman correlation analysis. Diagnostic models, competing endogenous RNA (ceRNA) regulatory network and transcription factor regulatory network were constructed based on key DEmRNAs. Meanwhile, drugs related to key DEmRNAs were screened out based on DGIdb database. The expression of key DEmRNAs was also verified by real time-PCR.

RESULTS

In this study, 7 key DEmRNAs (NRXN1, GRIA2, SLC1A2, SLC17A7, IL6, VEGFA and SYP) associated with key differential immune cell infiltration (CD56bright natural killer cell, Immature B cell and Type 1 T helper cell) were identified. Functional enrichment analysis showed that VEGFA and IL6 may be involved in the regulation of the PI3K-Akt signaling pathway. Moreover, IL6 was also found to be enriched in cytokine-cytokine receptor interaction signaling pathway. In the ceRNA regulatory network, a large number of miRNAs and lncRNAs were found. In the transcription factor regulatory network, the transcription factor SP1 was correlated with VEGFA, SYP and IL6. It is also predicted that drugs related to key DEmRNAs such as CARBOPLATIN, FENTANYL and CILOSTAZOL may contribute to the treatment of IA. In addition, it was also found that SVM and RF models based on key DEmRNAs may be potential markers for diagnosing IA and unruptured intracranial aneurysm (UIA), respectively. The expression trend of key DEmRNAs verified by real-time PCR was consistent with the bioinformatics analysis results.

CONCLUSION

The identification of molecules and pathways in this study provides a theoretical basis for understanding the immune related molecular mechanism of IA. Meanwhile, the drug prediction and diagnosis model construction may also be helpful for clinical diagnosis and management.

LINE-1 hypomethylation is associated with poor outcomes in locoregionally advanced oropharyngeal cancer

BACKGROUND AND PURPOSE

Currently, human papillomavirus (HPV) positivity represents a strong prognostic factor for both reduced risk of relapse and improved survival in patients with oropharyngeal squamous cell carcinoma (OPSCC). However, a subset of HPV-positive OPSCC patients still experience poor outcomes. Furthermore, HPV-negative OPSCC patients, who have an even higher risk of relapse, are still lacking suitable prognostic biomarkers for clinical outcome. Here, we evaluated the prognostic value of LINE-1 methylation level in OPSCC patients and further addressed the relationship between LINE-1 methylation status and p53 protein expression as well as genome-wide/gene-specific DNA methylation.

RESULTS

In this study, DNA was extracted from 163 formalin-fixed paraffin-embedded tissue samples retrospectively collected from stage III-IVB OPSCC patients managed with curative intent with up-front treatment. Quantitative methylation-specific PCR revealed that LINE-1 hypomethylation was directly associated with poor prognosis (5-year overall survival-OS: 28.1% for LINE-1 methylation < 35% vs. 69.1% for ≥ 55%; p < 0.0001). When LINE-1 methylation was dichotomized as < 55% versus ≥ 55%, interaction with HPV16 emerged: compared with hypermethylated HPV16-positive patients, subjects with hypomethylated HPV16-negative OPSCC reported an adjusted higher risk of death (HR 4.83, 95% CI 2.24-10.38) and progression (HR 4.54, 95% CI 2.18-9.48). Tumor protein p53 (TP53) gene is often mutated and overexpressed in HPV-negative OPSCC. Since p53 has been reported to repress LINE-1 promoter, we then analyzed the association between p53 protein expression and LINE-1 methylation levels. Following p53 immunohistochemistry, results indicated that among HPV16-negative patients with p53 ≥ 50%, LINE-1 methylation levels declined and remained stable at approximately 43%; any HPV16-positive patient reported p53 ≥ 50%. Finally, DNA methylation analysis demonstrated that genome-wide average methylation level at cytosine-phosphate-guanine sites was significantly lower in HPV16-negative OPSCC patients who relapsed within two years. The subsequent integrative analysis of gene expression and DNA methylation identified 20 up-regulated/hypomethylated genes in relapsed patients, and most of them contained LINE-1 elements in their promoter sequences.

CONCLUSIONS

Evaluation of the methylation level of LINE-1 may help in identifying the subset of OPSCC patients with bad prognosis regardless of their HPV status. Aberrant LINE-1 hypomethylation might occur along with TP53 mutations and lead to altered gene expression in OPSCC.

Role of miRNA-495 and NRXN-1 and CNTN-1 mRNA Expression and Its Prognostic Importance in Breast Cancer Patients

Breast cancer is a heterogeneous disease in which genetic factors are involved in disease worsening and higher mortality. Epidemiological and clinical research revealed that breast cancer incidence continues to rise. 100 histopathologically confirmed untreated newly diagnosed cases of invasive ductal carcinoma (IDC) of breast and 100 healthy subjects were involved and blood samples were collected in non-EDTA plain vials. Serum was separated by centrifugation, total RNA was extracted from serum, and cDNA synthesis was done to study the miRNA-495 and neurexin-1 (NRXN-1) and contactin 1 (CNTN-1) mRNA expression by QRT-PCR. The expression levels of miRNA-495, NRXN-1, and CNTN-1 were expressed in fold change. The present study observed decreased relative miRNA-495 expression (0.07-fold) while an increase in NRXN-1 (11.61-fold) and CNTN-1 (4.92-fold) was observed among breast cancer patients compared to healthy controls. A significant difference was observed in miRNA-495 expression with menopausal status (p=0.0001) and TNM stages (p=0.02). It was observed that NRXN-1 expression was significantly associated with menopausal status (p=0.03), lymph node involvement (p < 0.0001), estrogen receptor (ER) status (p=0.03), progesterone receptor (PR) status (p=0.005), TNM stages (p < 0.0001), and distant metastases (p < 0.0001). CNTN-1 expression was also found to be associated with lymph node involvement (p=0.01), PR status (p=0.03), HER2 status (p=0.04), TNM stages (p < 0.0001), and distant metastases (p < 0.0001). ROC suggested that NRXN-1 and CNTN-1 could be the important predictive marker for disease advancement and distant organ metastases. The study concluded that the decreased expression of miR-495 observed in breast cancer patients showed a negative correlation with NRXN-1 while the increased expression of NRXN-1 and CNTN-1 was linked with disease advancement and distant metastases and could be the important predictive marker for breast cancer patients.

miR-196a-2 Promotes Malignant Progression of Thyroid Carcinoma by Targeting NRXN1

Thyroid cancer (TC) is the most common endocrine malignant disease with a rising morbidity year by year. Accumulating studies have shown that microRNAs (miRNAs) play a regulatory role in the progression of various tumors, but the molecular regulatory mechanism of miR-196a-2 in TC is still unknown. qRT-PCR was employed to measure the expression of miR-196a-2 and NRXN1 mRNA in TC cells, while western blot was used to detect the protein expression of NRXN1. CCK-8, colony formation and flow cytometry assays were used to measure cell proliferation and apoptosis of TC cells. Dual-luciferase reporter gene assay was used to predict and verify the targeted binding relationship between miR-196a-2 and NRXN1. Our study results manifested that miR-196a-2 was dramatically overexpressed in cells of TC, while NRXN1 was lowly expressed. miR-196a-2 could promote cell proliferation and inhibit cell apoptosis of TC. Additionally, miR-196a-2 could also target and inhibit the expression of NRXN1. Silencing NRXN1 could reverse the inhibitory effect of miR-196a-2 downregulation on cell proliferation of TC, as well as the promoting effect on cell apoptosis. In a conclusion, we found that miR-196a-2 could promote cell proliferation and inhibit cell apoptosis of TC by targeting NRXN1. Therefore, miR-196a-2/NRXN1 is potential to be a molecular therapeutic target for TC.