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The screening and treatment of laryngeal squamous cell carcinoma (LSCC) still perplexes clinicians, making it necessary to explore new markers. To this end, this research examined the underlying molecular mechanism of LSCC based on high-throughput datasets ( n = 249) from multiple databases. It also identified transcription factors (TFs) independently associated with LSCC prognosis. Through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, differential expression genes of LSCC were deemed relevant to the extracellular matrix and its related structures or pathways, suggesting that the extracellular matrix plays an important role in LSCC. At the same time, several hub genes that may also have important roles in LSCC were identified via protein–protein interaction analysis, including CDC45, TPX2, AURKA, KIF2C, NUF, MUC1, MUC7, MUC4, MUC15, and MUC21 . Eight unreported LSCC prognostic TFs – BCAT1, CHD4, FOXA2, GATA6, HNF1A, HOXB13, MAFF, and TCF4 – were screened via Kaplan–Meier curves. Cox analysis determined for the first time that HOXB13 expression and gender were independently associated with LSCC prognosis. Compared to control tissues, elevated expression of HOXB13 was found in LSCC tissues (standardized mean difference = 0.44, 95% confidence interval [0.13–0.76]). HOXB13 expression also makes it feasible to screen LSCC from non-LSCC (area under the curve = 0.77), and HOXB13 may play an essential role in LSCC by regulating HOXB7 . In conclusion, HOXB13 may be a novel marker for LSCC clinical screening and treatment.

During the pandemic of the coronavirus disease 2019, there exist quite a few studies on angiotensin-converting enzyme 2 (ACE2) and SARS-CoV-2 infection, while little is known about ACE2 in hepatocellular carcinoma (HCC). The detailed mechanism among ACE2 and HCC still remains unclear, which needs to be further investigated. In the current study with a total of 6,926 samples, ACE2 expression was downregulated in HCC compared with non-HCC samples (standardized mean difference = −0.41). With the area under the curve of summary receiver operating characteristic = 0.82, ACE2 expression showed a better ability to differentiate HCC from non-HCC. The mRNA expression of ACE2 was related to the age, alpha-fetoprotein levels and cirrhosis of HCC patients, and it was identified as a protected factor for HCC patients via Kaplan-Meier survival, Cox regression analyses. The potential molecular mechanism of ACE2 may be relevant to catabolic and cell division. In all, decreasing ACE2 expression can be seen in HCC, and its protective role for HCC patients and underlying mechanisms were explored in the study.

Synaptojanin 2 (SYNJ2) regulates cell proliferation and apoptosis via dephosphorylating plasma membrane phosphoinositides. Aim of this study is to first seek the full-scale expression levels and potential emerging roles of SYNJ2 in hepatocellular carcinoma (HCC). We systematically analyzed SYNJ2 mRNA expression and protein levels in HCC tissues based on large-scale data and in-house immunohistochemistry (IHC). The clinical significance and risk factors for SYNJ2-related HCC cases were identified. A nomogram of prognosis was created and its performance was validated by concordance index (C-index) and shown in calibration plots. Based on the identified differentially coexpressed genes (DCGs) of SYNJ2, enriched annotations and potential pathways were predicted, and the protein interacting networks were mapped. Upregulated SYNJ2 in 3,728 HCC and 3,203 non-HCC tissues were verified and in-house IHC showed higher protein levels of SYNJ2 in HCC tissues. Pathologic T stage was identified as a risk factor. Upregulated mRNA levels and mutated SYNJ2 might cause a poorer outcome. The C-index of the nomogram model constructed by SYNJ2 level, age, gender, TNM classification, grade, and stage was evaluated as 0.643 (95% CI = 0.619-0.668) with well-calibrated plots. A total of 2,533 DCGs were extracted and mainly functioned together with SYNJ2 in metabolic pathways. Possible transcriptional axis of CTCF/ POLR2A-SYNJ2/INPP5B (transcription factor-target) in metabolic pathways was discovered based on ChIP-seq datasets. In summary, transcriptional regulatory axis CTCF/POLR2A-SYNJ2 might influence SYNJ2 expression levels. Increased SYNJ2 expression level could be utilized for predicting HCC prognosis and potentially accelerates the occurrence and development of HCC via metabolic perturbations pathways.

<abstract> <sec><title>Background</title><p>Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers in the world, the detection and prognosis of which are still unsatisfactory. Thus, it is essential to explore the factors that may identify ESCC and evaluate the prognosis of ESCC patients.</p> </sec> <sec><title>Results</title><p>Both protein and mRNA expression levels of BIRC5 are upregulated in ESCC group rather than non-ESCC group (standardized mean difference &gt; 0). <italic>BIRC5</italic> mRNA expression is related to the age, tumor location, lymph node stage and clinical stage of ESCC patients (<italic>p</italic> &lt; 0.05). BIRC5 expression makes it feasible to distinguish ESCC from non-ESCC (area under the curve &gt; 0.9), and its high expression is related to poor prognosis of ESCC patients (restrictive survival time difference = -0.036, <italic>p</italic> &lt; 0.05). BIRC5 may play an important role in ESCC by influencing the cell cycle pathway, and <italic>CDK1</italic>, <italic>MAD2L</italic> and <italic>CDC20</italic> may be the hub genes of this pathway. The transcription factors-<italic>MAZ</italic> and <italic>TFPD1</italic> -are likely to regulate the transcription of <italic>BIRC5</italic>, which may be one of the factors for the high expression of BIRC5 in ESCC.</p> </sec> <sec><title>Conclusions</title><p>The current study shows that upregulation of BIRC5 may have essential clinical value in ESCC, and contributes to the understanding of the pathogenesis of ESCC.</p> </sec> </abstract>

Background: Coronavirus disease 2019 (COVID-19) has been a public threat and healthcare concern caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. During the period of the pandemic of COVID-19, cancer patients should be paid more attention as more severe events are found in cancer patients infected with SARS-CoV-2. Basigin (BSG) is an essential factor for the infection and progression of COVID-19 and tumorigenesis of multiple tumors, which may serve as a novel target for the effective treatment against COVID-19 and multiple human cancers.Methods: A total of 19,020 samples from multiple centers were included in our research for the comprehensive investigation of the differences in BSG expression among human organs, cancer cells, cancer tissues, and normal tissues. Cox regression analysis and Kaplan–Meier curves were utilized to explore the prognosis factor of BSG in cancers. Correlation analyses were used to determine associations of BSG expression with tumor mutational burden, the immune microenvironment, etc. Gene set enrichment analysis was applied to explore the underlying mechanisms of BSG in cancers.Results: Compared with normal tissues, BSG expression was high in 13 types of cancers (cholangiocarcinoma, etc.) and low in colon adenocarcinoma and rectum adenocarcinoma. BSG expression was related to the prognosis of eight cancers (e.g., invasive breast carcinoma) (p &lt; 0.05). The gene also demonstrated a pronounced effect in identifying 12 cancers (cholangiocarcinoma, etc.) from their control samples (AUC &gt;0.7). The BSG expression was associated with DNA methyltransferases, mismatch repair genes, immune infiltration levels, tumor mutational burden, microsatellite instability, neoantigen, and immune checkpoints, suggesting the potential of BSG as an exciting target for cancer treatment. BSG may play its role in several cancers by affecting several signaling pathways such as drug cytochrome metabolism P450 and JAK-STAT.Conclusion:BSG may be a novel biomarker for treating and identifying multiple human cancers.

Background: Idiopathic pulmonary fibrosis (IPF) is the interstitial lung disease with the highest incidence and mortality. The lack of specific markers results in limited treatment methods for IPF patients. Numerous prognostic signatures represented effective indexes in predicting the survival of patients in various diseases; however, little is investigated on their application in IPF.Methods: This study attempted to explore the clinical markers suitable for IPF by constructing a prognostic signature from the perspective of 7-methylguanosine (m7G). An m7G-related prognostic signature (m7GPS) was established based on the discovery cohort with the LASSO algorithm and was verified by internal and external validation cohorts. The area under the curve (AUC) values were utilized to assess the accuracy of m7GPS in predicting the prognosis of IPF patients and the ability of m7GPS in screening IPF patients. Kaplan-Meier curves and Cox regression analyses were used to identify the relationship of m7GPS with the prognosis of IPF individuals. Enrichment analyses, CIBERSORT algorithm, and weighted gene co-expression network analysis were applied to explore the underlying mechanisms and correlation of m7GPS in IPF.Results: The two m7G regulatory genes can divide IPF into subtypes 1 and 2, and subtype 2 demonstrated a poor prognosis for IPF patients (p &lt; 0.05). For the first time in this field, the m7GPS was constructed. m7GPS made it feasible to predict the 1–5 years survival status of IPF patients (AUC = 0.730–0.971), and it was an independent prognostic risk factor for IPF patients (hazard ratio &gt; 1, p &lt; 0.05). The conspicuous ability of m7GPS to screen IPF patients from the healthy was also revealed by an AUC value of 0.960. The roles of m7GPS in IPF may link to inflammation, immune response, and immune cell levels. Seven genes (CYR61, etc.) were identified as hub genes of m7GPS in IPF. Three drugs (ZM447439-1050, AZD1332-1463, and Ribociclib-1632) were considered sensitive to patients with high m7GPS risk scores.Conclusion: This study developed a novel m7GPS, which is a reliable indicator for predicting the survival status of IPF patients and is identified as an effective marker for prognosis and screening of IPF patients.

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