Screening the key genes of prognostic value in the microenvironment for head and neck squamous cell carcinoma

Screening Differentially Expressed Proteins in Areca Nut-Related Oral Squamous Cell Carcinoma Using Tandem Mass Tag Proteomics

OBJECTIVE

Areca nut chewing has been associated with a poor prognosis in oral squamous cell carcinoma (OSCC). This study seeks to identify differentially expressed proteins among areca nut-related OSCC,non-areca nut-related OSCC and adjacent normal epithelial tissues, with the aim of providing novel insights for the investigation of areca nut-related OSCC.

METHODS

Using Tandem mass tag (TMT)-based proteomic analysis, a comparative proteomic profiling was conducted among areca nut-related OSCC, non-areca nut-related OSCC, and adjacent normal epithelial tissues (n=15). GO and KEGG enrichment analyses were then employed to identify significant proteins pertinent to the pathogenesis of OSCC for further study. Western Blot (WB) and Immunohistochemistry (IHC) techniques were used to preliminary validate the expression patterns of LZTS1, MMP10, MYH6, MB, and TNNC1 among various groups (n=30).

RESULTS

27 differentially expressed proteins were identified when comparing the areca nut-related OSCC group with both the non-areca nut-related OSCC and normal epithelial tissue groups. Among these, 15 proteins were upregulated, while 12 were downregulated. LZTS1 and MMP10 were included in the upregulated proteins, whereas MYH6, MB, and TNNC1 were downregulated. WB and IHC analyses corroborated the proteomic findings, revealing consistent expression trends for these 5 proteins across the studied groups.

CONCLUSION

LZTS1, MMP10, MYH6, MB and TNNC1 emerge as promising biomarkers for assessing disease progression, prognosis, and potential targeted therapies in areca nut-related OSCC.

Upregulation of mRNA Expression of ADGRD1/GPR133 and ADGRG7/GPR128 in SARS-CoV-2-Infected Lung Adenocarcinoma Calu-3 Cells

Adhesion G protein-coupled receptors (aGPCRs) play an important role in neurodevelopment, immune defence and cancer; however, their role throughout viral infections is mostly unexplored. We have been searching for specific aGPCRs involved in SARS-CoV-2 infection of mammalian cells. In the present study, we infected human epithelial cell lines derived from lung adenocarcinoma (Calu-3) and colorectal carcinoma (Caco-2) with SARS-CoV-2 in order to analyse changes in the level of mRNA encoding individual aGPCRs at 6 and 12 h post infection. Based on significantly altered mRNA levels, we identified four aGPCR candidates-ADGRB3/BAI3, ADGRD1/GPR133, ADGRG7/GPR128 and ADGRV1/GPR98. Of these receptors, ADGRD1/GPR133 and ADGRG7/GPR128 showed the largest increase in mRNA levels in SARS-CoV-2-infected Calu-3 cells, whereas no increase was observed with heat-inactivated SARS-CoV-2 and virus-cleared conditioned media. Next, using specific siRNA, we downregulated the aGPCR candidates and analysed SARS-CoV-2 entry, replication and infectivity in both cell lines. We observed a significant decrease in the amount of SARS-CoV-2 newly released into the culture media by cells with downregulated ADGRD1/GPR133 and ADGRG7/GPR128. In addition, using a plaque assay, we observed a reduction in SARS-CoV-2 infectivity in Calu-3 cells. In summary, our data suggest that selected aGPCRs might play a role during SARS-CoV-2 infection of mammalian cells.

A case-control comparison of acute-phase peripheral blood gene expression in participants diagnosed with minor ischaemic stroke or stroke mimics

BACKGROUND

Past studies suggest that there are changes in peripheral blood cell gene expression in response to ischaemic stroke; however, the specific changes which occur during the acute phase are poorly characterised. The current study aimed to identify peripheral blood cell genes specifically associated with the early response to ischaemic stroke using whole blood samples collected from participants diagnosed with ischaemic stroke (n = 29) or stroke mimics (n = 27) following emergency presentation to hospital. Long non-coding RNA (lncRNA), mRNA and micro-RNA (miRNA) abundance was measured by RNA-seq, and the consensusDE package was used to identify genes which were differentially expressed between groups. A sensitivity analysis excluding two participants with metastatic disease was also conducted.

RESULTS

The mean time from symptom onset to blood collection was 2.6 h. Most strokes were mild (median NIH stroke scale score 2.0). Ten mRNAs (all down-regulated in samples provided by patients experiencing ischaemic stroke) and 30 miRNAs (14 over-expressed and 16 under-expressed in participants with ischaemic stroke) were significantly different between groups in the whole cohort and sensitivity analyses. No significant over-representation of gene ontology categories by the differentially expressed genes was observed. Random forest analysis suggested a panel of differentially expressed genes (ADGRG7 and miRNAs 96, 532, 6766, 6798 and 6804) as potential ischaemic stroke biomarkers, although modelling analyses demonstrated that these genes had poor diagnostic performance.

CONCLUSIONS

This study provides evidence suggesting that the early response to minor ischaemic stroke is predominantly reflected by changes in the expression of miRNAs in peripheral blood cells. Further work in independent cohorts particularly in patients with more severe stroke is needed to validate these findings and investigate their clinical relevance.

Quantitative Analysis on Molecular Characteristics Evolution of Gastric Cancer Progression and Prognosis

The dynamic changes of key biological characteristics from gastric low-grade intraepithelial neoplasia (LGIN) to high-grade intraepithelial neoplasia (HGIN) to early gastric cancer (EGC) are still unclear, which greatly affect the accurate diagnosis and treatment of EGC and prognosis evaluation of gastric cancer (GC). In this study, bioinformatics methods/tools are applied to quantitatively analyze molecular characteristics evolution of GC progression, and a prognosis model is constructed. This study finds that some dysregulated differentially expressed mRNAs (DEmRNAs) in the LGIN stage may continue to promote the occurrence and development of EGC. Among the LGIN, HGIN, and EGC stages, there are differences and relevance in the transcription expression patterns of DEmRNAs, and the activation related to immune cells is very different. The biological functions continuously changed during the progression from LGIN to HGIN to EGC. The COX model constructed based on the three EGC-related DEmRNAs has GC prognostic risk prediction ability. The evolution of biological characteristics during the development of EGC mined by the authors provides new insight into understanding the molecular mechanism of EGC occurrence and development. The three-gene prognostic risk model provides a new method for assisting GC clinical treatment decisions.

Establishment and validation of an aging-related risk signature associated with prognosis and tumor immune microenvironment in breast cancer

BACKGROUND

Breast cancer (BC) is a highly malignant and heterogeneous tumor which is currently the cancer with the highest incidence and seriously endangers the survival and prognosis of patients. Aging, as a research hotspot in recent years, is widely considered to be involved in the occurrence and development of a variety of tumors. However, the relationship between aging-related genes (ARGs) and BC has not yet been fully elucidated.

MATERIALS AND METHODS

The expression profiles and clinicopathological data were acquired in the Cancer Genome Atlas (TCGA) and the gene expression omnibus (GEO) database. Firstly, the differentially expressed ARGs in BC and normal breast tissues were investigated. Based on these differential genes, a risk model was constructed composed of 11 ARGs via univariate and multivariate Cox analysis. Subsequently, survival analysis, independent prognostic analysis, time-dependent receiver operating characteristic (ROC) analysis and nomogram were performed to assess its ability to sensitively and specifically predict the survival and prognosis of patients, which was also verified in the validation set. In addition, functional enrichment analysis and immune infiltration analysis were applied to reveal the relationship between the risk scores and tumor immune microenvironment, immune status and immunotherapy. Finally, multiple datasets and real-time polymerase chain reaction (RT-PCR) were utilized to verify the expression level of the key genes.

RESULTS

An 11-gene signature (including FABP7, IGHD, SPIB, CTSW, IGKC, SEZ6, S100B, CXCL1, IGLV6-57, CPLX2 and CCL19) was established to predict the survival of BC patients, which was validated by the GEO cohort. Based on the risk model, the BC patients were divided into high- and low-risk groups, and the high-risk patients showed worse survival. Stepwise ROC analysis and Cox analyses demonstrated the good performance and independence of the model. Moreover, a nomogram combined with the risk score and clinical parameters was built for prognostic prediction. Functional enrichment analysis revealed the robust relationship between the risk model with immune-related functions and pathways. Subsequent immune microenvironment analysis, immunotherapy, etc., indicated that the immune status of patients in the high-risk group decreased, and the anti-tumor immune function was impaired, which was significantly different with those in the low-risk group. Eventually, the expression level of FABP7, IGHD, SPIB, CTSW, IGKC, SEZ6, S100B, CXCL1, IGLV6-57 and CCL19 was identified as down-regulated in tumor cell line, while CPLX2 up-regulated, which was mostly similar with the results in TCGA and Human Protein Atlas (HPA) via RT-PCR.

CONCLUSIONS

In summary, our study constructed a risk model composed of ARGs, which could be used as a solid model for predicting the survival and prognosis of BC patients. Moreover, this model also played an important role in tumor immunity, providing a new direction for patient immune status assessment and immunotherapy selection.

Automated Nuclear Segmentation in Head and Neck Squamous Cell Carcinoma Pathology Reveals Relationships between Cytometric Features and ESTIMATE Stromal and Immune Scores

The tumor microenvironment (TME) plays an important role in the progression of head and neck squamous cell carcinoma (HNSCC). Currently, pathologic assessment of TME is nonstandardized and subject to observer bias. Genome-wide transcriptomic approaches to understanding the TME, while less subject to bias, are expensive and not currently a part of the standard of care for HNSCC. To identify pathology-based biomarkers that correlate with genomic and transcriptomic signatures of TME in HNSCC, cytometric feature maps were generated in a publicly available data set from a cohort of patients with HNSCC, including whole-slide tissue images and genomic and transcriptomic phenotyping (N = 49). Cytometric feature maps were generated based on whole-slide nuclear detection, using a deep-learning algorithm trained for StarDist nuclear segmentation. Cytometric features in each patient were compared to transcriptomic measurements, including Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) scores and stemness scores. With correction for multiple comparisons, one feature (nuclear circularity) demonstrated a significant linear correlation with ESTIMATE stromal score. Two features (nuclear maximum and minimum diameter) correlated significantly with ESTIMATE immune score. Three features (nuclear solidity, nuclear minimum diameter, and nuclear circularity) correlated significantly with transcriptomic stemness score. This study provides preliminary evidence that observer-independent, automated tissue-slide analysis can provide insights into the HNSCC TME which correlate with genomic and transcriptomic assessments.

Whole exome analysis reveals the genomic profiling related to chemo-resistance in Chinese population with limited-disease small cell lung cancer

PURPOSE

The mechanism of chemo-resistance in small cell lung cancer (SCLC) is unclear. This study aims to explore the resistance-related genomic profiles of residual tumors after neo-adjuvant chemotherapy (NAC) in SCLC through the whole-exome sequencing (WES).

EXPERIMENTAL DESIGN

A total of 416 limited diseases (LD) SCLC patients underwent surgery were retrospectively analyzed, of which 40 patients received NAC. Then we selected 29 patients undergoing NAC (n = 19) and chemotherapy naïve (CTN, n = 10) to perform WES sequence with formalin-fixed paraffin-embedded samples including tumor and paired para-tumor.

RESULTS

In total, single nucleotide variation and mutation rate were similar between NAC and CTN groups. The mutation signatures were significantly discrepant between NAC and CTN groups, as well as among patients with partial response (PR), stable disease (SD), and progressive disease. There were more copy number variation deletions in NAC group compared with CTN group. The inactivation of TP53 and RB1 were the most significantly events in both NAC and CTN groups. RB1 nonsense mutations were recurrent in NAC group (9/19 vs. 0/9, 47.4% vs. 0%) with favorable survival, while the frame-shift deletions were frequent in CTN group (3/9 vs. 3/19, 33.3% vs.15.8%). Integrated function enrichment revealed that the frequently mutant genes were involved in cell cycle, metabolic reprogramming, and oncogenic signaling pathways in NAC group, such as BTG2 pathway, glycolysis in senescence and P53 pathway. A total of 27 genes presented frequently mutant in NAC group and might played a positive role in drug resistance. Multiple genes including BRINP3, MYH6, ST18, and PCHD15, which were associated with prognosis, occurred mutant frequently in PR and SD groups.

CONCLUSION

Residual tumors after neo-adjuvant therapy exhibited different mutation signature spectrum. Multiple genes including RB1 nonsense mutations, BRINP3, MYH6, ST18, and PCHD15 were with frequent mutation in residual tumors, which might participate chemo-resistance and influenced the prognosis in patients with limited disease SCLC.