High <i>TXLNA</i> Expression Predicts Favourable Outcome for Pancreatic Adenocarcinoma Patients

Lv, Shuangyu; Zhang, Guosen; Xie, Longxiang; Yan, Zhongyi; Wang, Qiang; Li, Yongqiang; Zhang, Lu; Han, Yali; Li, Huimin; Du, Yaowu; Yang, Yanjie; Guo, Xiangqian

doi:10.1155/2020/2585862

Cited by 9 publications

(8 citation statements)

References 27 publications

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“…It has been reported that CCL22 controls T-cell immunity by recruiting Tregs to tumor tissues and facilitating the formation of DC-Treg contacts in the lymph nodes [ 20 ]. Lv et al found that the high expression of TXLNA indicates a good prognosis for pancreatic cancer [ 21 ]. These genes are an important guarantee for the gene set contributing to an accurate prognosis prediction of OSCC.…”

Section: Discussionmentioning

confidence: 99%

A Novel Immune-Associated Gene Signature for Overall Survival Prediction in Patients with Oral Squamous Cell Carcinoma

Yang

Feng

Yuan

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Objective. To explore a novel Immune-associated gene signature for overall survival (OS) in patients with oral squamous cell carcinoma (OSCC). Methods. Expression profiles of genes and corresponding clinical materials of OSCC patients were obtained through the TCGA database. With a LASSO Cox regression model, a multigene signature was established to predict the OS of OSCC patients. Some molecular experiments including RNA interference, MTT, and Transwell assay were applied to verify the role of the risk gene FGF9 in OSCC. Results. 43 immune-related prognostic DEGs were identified in OSCC. A 17-gene signature was established to assign the patients to either a high-risk group (HG) or a low-risk group (LG). The HG presented a shorter OS than the LG ( P < 0.05 ). According to multivariate Cox regression analyses, the risk score was considered an independent factor for OS prediction (training set: HR = 3.485, 95% CI = 2.037–5.961, P < 0.001 ; test set: HR = 4.531, 95% CI = 2.120–9.682, P < 0.001 ). ROC curve-based analysis revealed the signature’s ability for prediction. According to functional analysis, the immune cell expression and immune function of the HG were significantly inhibited. After knocking down the high-risk gene FGF9, the migration, proliferation, and invasion capabilities of OSCC cells HSC6 were significantly suppressed ( P < 0.05 ). Conclusion. A novel immune-associated gene signature was identified for predicting the prognosis of OSCC. These risk genes show great potential as targets for OSCC treatment.

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Section: Discussionmentioning

confidence: 99%

A Novel Immune-Associated Gene Signature for Overall Survival Prediction in Patients with Oral Squamous Cell Carcinoma

Yang

Feng

Yuan

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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“…33,34 Alpha-taxilin (TXLNA) has been reported in renal cell cancer, hepatocellular cancer, and pancreatic cancer. [35][36][37] To our knowledge, no study has found an association between TXLNA and breast cancer. Nectin-4 (PVRL4) is expressed in cancer tissues such as breast cancer.…”

Section: Discussionmentioning

confidence: 95%

Efficacy and safety of pyrotinib combined with albumin‐bound paclitaxel as first‐line treatment for HER2‐positive metastatic breast cancer in patients previously treated with adjuvant and/or neoadjuvant trastuzumab therapy: The stage 1 results of a single‐arm, phase 2 prospective clinical trial

Man,

Huang,

Sun

et al. 2024

Clinical & Translational Med

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ObjectiveIt has been observed that the prognosis of patients with HER2‐positive metastatic breast cancer has improved significantly with HER2‐targeted agents. However, there is still a lack of evidence regarding first‐line anti‐HER2 treatment options for patients who have received adjuvant and/or neoadjuvant trastuzumab for HER2‐positive metastatic breast cancer. Besides, there are no reliable markers that can predict the efficacy of anti‐HER2 treatment in these patients.MethodsPatients who have received adjuvant and/or neoadjuvant trastuzumab for HER2‐positive metastatic breast cancer were enrolled. Pyrotinib plus albumin‐bound paclitaxel were used as first‐line treatment. The primary endpoint was the objective response rate (ORR). The safety profile was also assessed. In order to explore predictive biomarkers using Olink technology, blood samples were collected dynamically.ResultsFrom December 2019 to August 2023, the first stage of the study involved 27 eligible patients. It has not yet reached the median PFS despite the median follow‐up being 17.8 months. Efficacy evaluation showed that the ORR was 92.6%, and the DCR was 100%. Adverse events of grade 3 or higher included diarrhoea (29.6%), leukopenia (11.1%), neutropenia (25.9%), oral mucositis (3.7%), and hand‐foot syndrome (3.7%). Toll‐like receptor 3 (TLR3) and Proto‐oncogene tyrosine‐protein kinase receptor (RET) were proteins with significant relevance to PFS in these patients.ConclusionsThis study demonstrates that pyrotinib plus albumin‐bound paclitaxel as a first‐line treatment regimen shows good efficacy and manageable safety for patients who have received adjuvant and/or neoadjuvant trastuzumab for HER2‐positive metastatic breast cancer. Besides, a significant association was identified between the expression levels of TLR3 and RET and the PFS in patients.

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“…3 ). miR-1271 targeted TXLNA , and high TXLNA expression could be a favorable biomarker and therapeutic target for pancreatic adenocarcinoma patients [ 30 ]. In our study, TXLNA expression was significantly lower in the high-yielding goats than in the low-yielding goats, and the dual luciferase reporter assay showed that its expression was regulated by miR-1271.…”

Section: Discussionmentioning

confidence: 99%

Integrated analyses of miRNA-mRNA expression profiles of ovaries reveal the crucial interaction networks that regulate the prolificacy of goats in the follicular phase

Liu

Zhou

et al. 2021

BMC Genomics

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Background Litter size is an important index of mammalian prolificacy and is determined by the ovulation rate. The ovary is a crucial organ for mammalian reproduction and is associated with follicular development, maturation and ovulation. However, prolificacy is influenced by multiple factors, and its molecular regulation in the follicular phase remains unclear. Methods Ten female goats with no significant differences in age and weight were randomly selected and divided into either the high-yielding group (n = 5, HF) or the low-yielding group (n = 5, LF). Ovarian tissues were collected from goats in the follicular phase and used to construct mRNA and miRNA sequencing libraries to analyze transcriptomic variation between high- and low-yield Yunshang black goats. Furthermore, integrated analysis of the differentially expressed (DE) miRNA-mRNA pairs was performed based on their correlation. The STRING database was used to construct a PPI network of the DEGs. RT–qPCR was used to validate the results of the predicted miRNA-mRNA pairs. Luciferase analysis and CCK-8 assay were used to detect the function of the miRNA-mRNA pairs and the proliferation of goat granulosa cells (GCs). Results A total of 43,779 known transcripts, 23,067 novel transcripts, 424 known miRNAs and 656 novel miRNAs were identified by RNA-seq in the ovaries from both groups. Through correlation analysis of the miRNA and mRNA expression profiles, 263 negatively correlated miRNA-mRNA pairs were identified in the LF vs. HF comparison. Annotation analysis of the DE miRNA-mRNA pairs identified targets related to biological processes such as “estrogen receptor binding (GO:0030331)”, “oogenesis (GO:0048477)”, “ovulation cycle process (GO:0022602)” and “ovarian follicle development (GO:0001541)”. Subsequently, five KEGG pathways (oocyte meiosis, progesterone-mediated oocyte maturation, GnRH signaling pathway, Notch signaling pathway and TGF-β signaling pathway) were identified in the interaction network related to follicular development, and a PPI network was also constructed. In the network, we found that CDK12, FAM91A1, PGS1, SERTM1, SPAG5, SYNE1, TMEM14A, WNT4, and CAMK2G were the key nodes, all of which were targets of the DE miRNAs. The PPI analysis showed that there was a clear interaction among the CAMK2G, SERTM1, TMEM14A, CDK12, SYNE1 and WNT4 genes. In addition, dual luciferase reporter and CCK-8 assays confirmed that miR-1271-3p suppressed the proliferation of GCs by inhibiting the expression of TXLNA. Conclusions These results increase the understanding of the molecular mechanisms underlying goat prolificacy. These results also provide a basis for studying interactions between genes and miRNAs, as well as the functions of the pathways in ovarian tissues involved in goat prolificacy in the follicular phase.

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High TXLNA Expression Predicts Favourable Outcome for Pancreatic Adenocarcinoma Patients

Cited by 9 publications

References 27 publications

A Novel Immune-Associated Gene Signature for Overall Survival Prediction in Patients with Oral Squamous Cell Carcinoma

A Novel Immune-Associated Gene Signature for Overall Survival Prediction in Patients with Oral Squamous Cell Carcinoma

Integrated analyses of miRNA-mRNA expression profiles of ovaries reveal the crucial interaction networks that regulate the prolificacy of goats in the follicular phase

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