Stathmin-1 Is a Useful Diagnostic Marker for High-Grade Lung Neuroendocrine Tumors

Stathmin 1 expression in neuroendocrine and proliferating prostate cancer

Prostate cancer (PCa) is the second leading cause of cancer-related mortality among men in the United States. While PCa initially responds to androgen deprivation therapy, a significant portion progresses to castration-resistant PCa. Approximately 20-25% of these cases acquire aggressive neuroendocrine (NE) features, ultimately leading to neuroendocrine prostate cancer (NEPC). In this study, we investigated the expression of stathmin 1 (STMN1) across PCa subtypes using bioinformatics, western blotting, and immunohistochemical staining analyses in human and murine models. We found that elevated STMN1 expression correlated with high Gleason Scores, increased cell proliferation, and poor clinical outcomes in PCa patients. Notably, STMN1 expression was significantly higher in NEPC compared to prostate adenocarcinoma, suggesting its role in NEPC progression. Findings from TRAMP tumors, a murine NEPC model, further supported these results. In conclusion, STMN1 expression is elevated in advanced PCa, particularly in NEPC, suggesting its involvement in the progression of aggressive forms of PCa. While STMN1 shows potential as a diagnostic and prognostic marker for aggressive PCa, further studies are necessary to establish its clinical utility.

STNM1 in human cancers: role, function and potential therapy sensitizer

STMN1 belongs to the stathmin gene family, it encodes a cytoplasmic phosphorylated protein, stathmin1, which is commonly observed in vertebrate cells. STMN1 is a structural microtubule-associated protein (MAP) that binds to microtubule protein dimers rather than microtubules, with each STMN1 binding two microtubule protein dimers and preventing their aggregation, leading to microtubule instability. STMN1 expression is elevated in a number of malignancies, and inhibition of its expression can interfere with tumor cell division. Its expression can change the division of tumor cells, thereby arresting cell growth in the G2/M phase. Moreover, STMN1 expression affects tumor cell sensitivity to anti-microtubule drug analogs, including vincristine and paclitaxel. The research on MAPs is limited, and new insights on the mechanism of STMN1 in different cancers are emerging. The effective application of STMN1 in cancer prognosis and treatment requires further understanding of this protein. Here, we summarize the general characteristics of STMN1 and outline how STMN1 plays a role in cancer development, targeting multiple signaling networks and acting as a downstream target for multiple microRNAs, circRNAs, and lincRNAs. We also summarize recent findings on the function role of STMN1 in tumor resistance and as a therapeutic target for cancer.

A Novel Strategy for the Diagnosis of Pulmonary High-Grade Neuroendocrine Tumor

Correctly diagnosing a histologic type of lung cancer is important for selecting the appropriate treatment because the aggressiveness, chemotherapy regimen, surgical approach, and prognosis vary significantly among histologic types. Pulmonary NETs, which are characterized by neuroendocrine morphologies, represent approximately 20% of all lung cancers. In particular, high-grade neuroendocrine tumors (small cell lung cancer and large cell neuroendocrine tumor) are highly proliferative cancers that have a poorer prognosis than other non-small cell lung cancers. The combination of hematoxylin and eosin staining, Ki-67, and immunostaining of classic neuroendocrine markers, such as chromogranin A, CD56, and synaptophysin, are normally used to diagnose high-grade neuroendocrine tumors; however, they are frequently heterogeneous. This article reviews the diagnostic methods of lung cancer diagnosis focused on immunostaining. In particular, we describe the usefulness of immunostaining by Stathmin-1, which is a cytosolic phosphoprotein and a key regulator of cell division due to its microtubule depolymerization in a phosphorylation-dependent manner, for the diagnosis of high-grade neuroendocrine tumors.

[Advances in Molecular Biomarker for Pulmonary Large Cell Neuroendocrine Carcinoma]

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a pathological subtype of lung neuroendocrine cancer, which accounts for 2.4%-3.1% in surgical specimens of lung cancer. It is characterized by high invasiveness and poor prognosis, and highly correlated with smoking. There are few relevant studies due to the low incidence and small sample size. Therefore, it is relatively difficult to diagnosis and treatment in clinical practice. In this review, we described molecular subtype, diagnostic and prognostic-related markers about large cell neuroendocrine carcinoma of lung based on the recent progress in genomic sequencing and molecular markers, to find the direction for the next research.
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Identification of novel transcription factor-microRNA-mRNA co-regulatory networks in pulmonary large-cell neuroendocrine carcinoma

Background

Large cell neuroendocrine carcinoma (LCNEC) of the lung is a rare neuroendocrine neoplasm. Previous studies have shown that microRNAs (miRNAs) are widely involved in tumor regulation through targeting critical genes. However, it is unclear which miRNAs play vital roles in the pathogenesis of LCNEC, and how they interact with transcription factors (TFs) to regulate cancer-related genes.

Methods

To determine the novel TF-miRNA-target gene feed-forward loop (FFL) model of LCNEC, we integrated multi-omics data from Gene Expression Omnibus (GEO), Transcriptional Regulatory Relationships Unraveled by Sentence-Based Text Mining (TRRUST), Transcriptional Regulatory Element Database (TRED), and The experimentally validated microRNA-target interactions database (miRTarBase database). First, expression profile datasets for mRNAs (GSE1037) and miRNAs (GSE19945) were downloaded from the GEO database. Overlapping differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified through integrative analysis. The target genes of the FFL were obtained from the miRTarBase database, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed on the target genes. Then, we screened for key miRNAs in the FFL and performed gene regulatory network analysis based on key miRNAs. Finally, the TF-miRNA-target gene FFLs were constructed by the hypergeometric test.

Results

A total of 343 DEGs and 60 DEMs were identified in LCNEC tissues compared to normal tissues, including 210 down-regulated and 133 up-regulated genes, and 29 down-regulated and 31 up-regulated miRNAs. Finally, the regulatory network of TF-miRNA-target gene was established. The key regulatory network modules included ETS1-miR195-CD36, TAOK1-miR7-1-3P-GRIA1, E2F3-miR195-CD36, and TEAD1-miR30A-CTHRC1.

Conclusions

We constructed the TF-miRNA-target gene regulatory network, which is helpful for understanding the complex LCNEC regulatory mechanisms.

Complementary multiple hydrogen-bond-based magnetic composite microspheres for high coverage and efficient phosphopeptide enrichment in bio-samples

Due to the number of phosphorylation sites, mono- and multiple-phosphopeptides exhibit significantly different biological effects. Therefore, comprehensive profiles of mono- and multiple-phosphopeptides are vital for the analysis of these biological and pathological processes. However, the most commonly used affinity materials based on metal oxide affinity chromatography (MOAC) show stronger selectivity toward mono-phosphopeptides, thus losing most information on multiple-phosphopeptides. Herein, we report polymer functionalized magnetic nanocomposite microspheres as an ideal platform to efficiently enrich both mono- and multiple-phosphopeptides from complex biological samples. Driven by complementary multiple hydrogen bonding interactions, the composite microspheres exhibited remarkable performance for phosphopeptide enrichment from model proteins and real bio-samples. Excellent selectivity (the molar ratio of nonphosphopeptides/phosphopeptides was 5000 : 1), high enrichment sensitivity (2 fmol) and coverage, as well as high capture rates of multiple-phosphopeptides revealed their great potential in comprehensive phosphoproteomics studies. More importantly, we successfully captured the cancer related phosphopeptides (from the phosphoprotein Stathmin-1) and identified their relevant phosphorylation sites from oral carcinoma patients' saliva and tissue lysate, demonstrating the potential of this material for phosphorylated disease marker detection and discovery.