Differential expression of COL4A3 and collagen in upward and downward progressing types of nasopharyngeal carcinoma

Comprehensive analysis of the expression, prognostic, and immune infiltration for COL4s in stomach adenocarcinoma

BACKGROUND

Collagen (COL) genes, play a key role in tumor invasion and metastasis, are involved in tumor extracellular matrix (ECM)-receptor interactions and focal adhesion pathways. However, studies focusing on the diagnostic value of the COL4 family in stomach adenocarcinoma (STAD) are currently lacking.

METHODS

The TCGA database was employed to retrieve the clinical features and RNA sequencing expression profiles of patients with STAD. We conducted an investigation to examine the expression disparities between STAD and adjacent normal tissues. Kaplan-Meier survival analysis was utilized to assess their prognostic significance, while Spearman correlation analysis was employed to determine their association with immune checkpoint genes and immunomodulatory molecules. Furthermore, GO and KEGG analyses were performed on the COL4s-related genes, revealing potential biological pathways through gene set enrichment analysis (GSEA). Subsequently, we explored the extent of immune infiltration of the COL4 family in STAD using the TIMER database. Lastly, the expression levels of the COL4 family in STAD were further validated through quantitative PCR (qPCR) and western blot techniques.

RESULTS

The expression levels of COL4A1/2 were significantly upregulated, while COL4A5/6 were conspicuously downregulated in STAD. The survival analysis revealed that the upregulated COL4s indicated poorer overall survival, first progression and post-progression survival outcomes. Additionally, our findings demonstrated a positive correlation between the expressions of COL4A1/2/3/4 and the infiltration of immune cells, including CD8 + T cells, dendritic cells, macrophages, neutrophils and CD4 + T cells. Further correlation analysis uncovered a favorable association between the expression of COL4A1/2/3/4 and various crucial immunomodulatory molecules, immunological checkpoint molecules, and chemokines. Quantitative PCR analysis confirmed that the expression patterns of COL4A1/3/4/6 genes aligned with the finding from the TCGA database. However, gastric cancer cells exhibited downregulation of COL4A2. Consistently, the protein level of COL4A1 was elevated, whereas the protein level of COL4A2 was reduced in the gastric cancer cell lines.

CONCLUSION

COL4s could potentially serve as biomarkers for diagnosing and predicting the prognosis of STAD.

Integrated Analysis Reveals COL4A3 as a Novel Diagnostic and Therapeutic Target in UV-Related Skin Cutaneous Melanoma

Background

High levels of UV exposure are a significant factor that can trigger the onset and progression of SKCM. Moreover, this exposure is closely linked to the malignancy of the tumor and the prognosis of patients. Our objective is to identify a tumor biomarker database associated with UV exposure, which can be utilized for prognostic analysis and diagnosis and treatment of SKCM.

Methods

This study used the weighted gene co-expression network analyses (WGCNA) and gene mutation frequency analyses to screen for UV-related target genes using the GSE59455 and the cancer genome atlas databases (TCGA). The prognostic model was created using Cox regression and least absolute shrinkage and selection operator analyses (LASSCO). Furthermore, in vitro experiments further validated that the overexpression or knockdown of COL4A3 could regulate the proliferation and migration abilities of SKMEL28 and A357 melanoma cells.

Results

A prognostic model was created that included six genes with a high UV-related mutation in SKCM: COL4A3, CHRM2, DSC3, GIMAP5, LAMC2, and PSG7. The model had a strong patient survival correlation (P˂0.001, hazard ratio (HR) = 1.57) and significant predictor (P˂0.001, HR = 3.050). Furthermore, the model negatively correlated with immune cells, including CD8+ T cells (Cor=-0.408, P˂0.001), and M1-type macrophages (Cor=-0.385, P˂0.001), and immune checkpoints, including programmed cell death ligand-1. Moreover, we identified COL4A3 as a molecule with significant predictive functionality. Overexpression of COL4A3 significantly inhibited the proliferation, migration, and invasion abilities of SKMEL28 and A357 melanoma cells, while knockdown of COL4A3 yielded the opposite results. And overexpression of COL4A3 enhanced the inhibitory effects of imatinib on the proliferation, migration, and invasion abilities of SKMEL28 and A357 cells.

Conclusion

The efficacy of the prognostic model was validated by analyzing the prognosis, immune infiltration, and immune checkpoint profiles. COL4A3 stands out as a novel diagnostic and therapeutic target for SKCM, offering new strategies for small-molecule targeted drug therapies.

Interleukin-30 subverts prostate cancer-endothelium crosstalk by fostering angiogenesis and activating immunoregulatory and oncogenic signaling pathways

BACKGROUND

Cancer-endothelial interplay is crucial for tumor behavior, yet the molecular mechanisms involved are largely unknown. Interleukin(IL)-30, which is expressed as a membrane-anchored cytokine by human prostate cancer (PC) cells, promotes PC vascularization and progression, but the underlying mechanisms have yet to be fully explored.

METHODS

PC-endothelial cell (EC) interactions were investigated, after coculture, by flow cytometry, transcriptional profiling, western blot, and ELISA assays. Proteome profiler phospho-kinase array unveiled the molecular pathways involved. The role of tumor-derived IL30 on the endothelium's capacity to generate autocrine circuits and vascular budding was determined following IL30 overexpression, by gene transfection, or its deletion by CRISPR/Cas9 genome editing. Clinical value of the experimental findings was determined through immunopathological study of experimental and patient-derived PC samples, and bioinformatics of gene expression profiles from PC patients.

RESULTS

Contact with PC cells favors EC proliferation and production of angiogenic and angiocrine factors, which are boosted by PC expression of IL30, that feeds autocrine loops, mediated by IGF1, EDN1, ANG and CXCL10, and promotes vascular budding and inflammation, via phosphorylation of multiple signaling proteins, such as Src, Yes, STAT3, STAT6, RSK1/2, c-Jun, AKT and, primarily CREB, GSK-3α/β, HSP60 and p53. Deletion of the IL30 gene in PC cells inhibits endothelial expression of IGF1, EDN1, ANG and CXCL10 and substantially impairs tumor angiogenesis. In its interaction with IL30-overexpressing PC cells the endothelium boosts their expression of a wide range of immunity regulatory genes, including CCL28, CCL4, CCL5, CCR2, CCR7, CXCR4, IL10, IL13, IL17A, FASLG, IDO1, KITLG, TNFA, TNFSF10 and PDCD1, and cancer driver genes, including BCL2, CCND2, EGR3, IL6, VEGFA, KLK3, PTGS1, LGALS4, GNRH1 and SHBG. Immunopathological analyses of PC xenografts and in silico investigation of 1116 PC cases, from the Prostate Cancer Transcriptome Atlas, confirmed the correlation between the expression of IL30 and that of both pro-inflammatory genes, NOS2, TNFA, CXCR5 and IL12B, and cancer driver genes, LGALS4, GNRH1 and SHBG, which was validated in a cohort of 80 PC patients.

CONCLUSIONS

IL30 regulates the crosstalk between PC and EC and reshapes their transcriptional profiles, triggering angiogenic, immunoregulatory and oncogenic gene expression programs. These findings highlight the angiostatic and oncostatic efficacy of targeting IL30 to fight PC.

AI-assisted compressed sensing and parallel imaging sequences for MRI of patients with nasopharyngeal carcinoma: comparison of their capabilities in terms of examination time and image quality

OBJECTIVE

To compare examination time and image quality between artificial intelligence (AI)-assisted compressed sensing (ACS) technique and parallel imaging (PI) technique in MRI of patients with nasopharyngeal carcinoma (NPC).

METHODS

Sixty-six patients with pathologically confirmed NPC underwent nasopharynx and neck examination using a 3.0-T MRI system. Transverse T2-weighted fast spin-echo (FSE) sequence, transverse T1-weighted FSE sequence, post-contrast transverse T1-weighted FSE sequence, and post-contrast coronal T1-weighted FSE were obtained by both ACS and PI techniques, respectively. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and duration of scanning of both sets of images analyzed by ACS and PI techniques were compared. The images from the ACS and PI techniques were scored for lesion detection, margin sharpness of lesions, artifacts, and overall image quality using the 5-point Likert scale.

RESULTS

The examination time with ACS technique was significantly shorter than that with PI technique (p < 0.0001). The comparison of SNR and CNR showed that ACS technique was significantly superior with PI technique (p < 0.005). Qualitative image analysis showed that the scores of lesion detection, margin sharpness of lesions, artifacts, and overall image quality were higher in the ACS sequences than those in the PI sequences (p < 0.0001). Inter-observer agreement was evaluated for all qualitative indicators for each method, in which the results showed satisfactory-to-excellent agreement (p < 0.0001).

CONCLUSION

Compared with the PI technique, the ACS technique for MR examination of NPC can not only shorten scanning time but also improve image quality.

CLINICAL RELEVANCE STATEMENT

The artificial intelligence (AI)-assisted compressed sensing (ACS) technique shortens examination time for patients with nasopharyngeal carcinoma, while improving the image quality and examination success rate, which will benefit more patients.

KEY POINTS

• Compared with the parallel imaging (PI) technique, the artificial intelligence (AI)-assisted compressed sensing (ACS) technique not only reduced examination time, but also improved image quality. • Artificial intelligence (AI)-assisted compressed sensing (ACS) pulls the state-of-the-art deep learning technique into the reconstruction procedure and helps find an optimal balance of imaging speed and image quality.

Identification of Angiogenesis-Related Prognostic Biomarkers Associated With Immune Cell Infiltration in Breast Cancer

Background: This study aimed to explore the prognostic value of angiogenesis-related genes (ARGs) and their association with immune cell infiltration (ICI) in breast cancer (BC).

Methods: Transcriptome data of BC were obtained from the TCGA and GEO databases. Differentially expressed ARGs were identified by the limma package. The identification of key genes and construction of the risk score model were performed by univariate and multivariate Cox regression algorithms. The prognostic value of the risk score was assessed by ROC curves and nomogram. GO, KEGG pathway, and GSEA were used to investigate the biological functions of differentially expressed genes (DEGs), and CIBERSORT, ssGSEA, and xCell algorithms were performed to estimate the ICI in high-risk and low-risk groups. The correlations between prognostic biomarkers and differentially distributed immune cells were assessed. Moreover, a ceRNA regulatory network based on prognostic biomarkers was constructed and visualized by Cytoscape software.

Results: A total of 18 differentially expressed ARGs were identified between tumor and adjacent normal tissue samples. TNFSF12, SCG2, COL4A3, and TNNI3 were identified as key prognostic genes by univariate and multivariate Cox regression analyses. The risk score model was further constructed based on the four-gene signature and validated in GSE7390 and GSE88770 datasets. ROC curves and nomogram indicated that the risk score had good accuracy for determining BC patient survival. Biological function analysis showed that DEGs in high- and low-risk groups had a high enrichment in immune-related biological processes and signaling pathways. Moreover, significantly different ICIs were found between high- and low-risk groups, such as memory B cells, CD8⁺ T cells, resting memory CD4⁺ T cells, follicular helper T cells, regulatory T cells, monocytes, M2 macrophages, and neutrophils, and each prognostic biomarker was significantly correlated with one or more immune cell types.

Conclusion: The current study identified novel prognostic ARGs and developed a prognostic model for predicting survival in patients with BC. Furthermore, this study indicated that ICI may act as a bond between angiogenesis and BC. These findings enhance our understanding of angiogenesis in BC and provide novel guidance on developing therapeutic targets for BC patients.

Prognostic significance of AP-2α/γ targets as cancer therapeutics

Identifying genes with prognostic importance could improve cancer treatment. An increasing number of reports suggest the existence of successful strategies based on seemingly "untargetable" transcription factors. In addition to embryogenesis, AP-2 transcription factors are known to play crucial roles in cancer development. Members of this family can be used as prognostic factors in oncological patients, and AP-2α/γ transcription factors were previously investigated in our pan-cancer comparative study using their target genes. The present study investigates tumors that were previously found similar with an emphasis on the possible role of AP-2 factors in specific cancer types. The RData workspace was loaded back to R environment and 3D trajectories were built via Monocle3. The genes that met the requirement of specificity were listed using top_markers(), separately for mutual and unique targets. Furthermore, the candidate genes had to meet the following requirements: correlation with AP-2 factor (through Correlation AnalyzeR) and validated prognostic importance (using GEPIA2 and subsequently KM-plotter or LOGpc). Eventually, the ROC analysis was applied to confirm their predictive value; co-dependence of expression was visualized via BoxPlotR. Some similar tumors were differentiated by AP-2α/γ targets with prognostic value. Requirements were met by only fifteen genes (EMX2, COL7A1, GRIA1, KRT1, KRT14, SLC12A5, SEZ6L, PTPRN, SCG5, DPP6, NTSR1, ARX, COL4A3, PPEF1 and TMEM59L); of these, the last four were excluded based on ROC curves. All the above genes were confronted with the literature, with an emphasis on the possible role played by AP-2 factors in specific cancers. Following ROC analysis, the genes were verified using immunohistochemistry data and progression-related signatures. Staining differences were observed, as well as co-dependence on the expression of e.g. CTNNB1, ERBB2, KRAS, SMAD4, EGFR or MKI67. In conclusion, prognostic value of targets suggested AP-2α/γ as candidates for novel cancer treatment. It was also revealed that AP-2 targets are related to tumor progression and that some mutual target genes could be inversely regulated.

Identification of Novel Prognostic Markers Associated With Laryngeal Squamous Cell Carcinoma Using Comprehensive Analysis

Background

Laryngeal squamous cell carcinoma (LSCC) is a leading malignant cancer of the head and neck. Patients with LSCC, in which the cancer has infiltrated and metastasized, have a poor prognosis. Therefore, there is an urgent need to identify more potential targets for drugs and biomarkers for early diagnosis.

Methods

RNA sequence data from LSCC and patients’ clinical traits were obtained from the Gene Expression Omnibus (GEO) (GSE142083) and The Cancer Genome Atlas (TCGA) database. Differentially expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify hub genes. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, prognostic value analysis, receiver operating characteristic (ROC) curve analysis, gene mutation analysis, tumor-infiltrating immune cell abundance profile estimation, gene set variation analysis (GSVA), and gene set enrichment analysis (GSEA) were performed. Single-gene RNA sequencing data were obtained from the GSE150321 dataset. Cell proliferation and viability were confirmed by the CCK-8 assay and real-time PCR.

Results

A total of 701 DEGs, including 329 upregulated and 372 downregulated genes, were screened in the GSE142083 dataset. Using WGCNA, three modules were identified to be closely related to LSCC. After intersecting the DEGs and performing univariate and multivariate Cox analyses, a novel prognostic model based on three genes (SLC35C1, HOXB7, and TEDC2) for LSCC was established. Interfering TEDC2 expression inhibited tumor cell proliferation and migration.

Conclusions

Our results show that SLC35C1, HOXB7, and TEDC2 have the potential to become new therapeutic targets and prognostic biomarkers for LSCC.

The Stromal and Immune Landscape of Nasopharyngeal Carcinoma and Its Implications for Precision Medicine Targeting the Tumor Microenvironment

The evolution of the tumor microenvironment (TME) is a cancer-dependent and dynamic process. The TME is often a complex ecosystem with immunosuppressive and tumor-promoting functions. Conventional chemotherapy and radiotherapy, primarily focus on inducing tumor apoptosis and hijacking tumor growth, whereas the tumor-protective microenvironment cannot be altered or destructed. Thus, tumor cells can quickly escape from extraneous attack and develop therapeutic resistance, eventually leading to treatment failure. As an Epstein Barr virus (EBV)-associated malignancy, nasopharyngeal carcinoma (NPC) is frequently infiltrated with varied stromal cells, making its microenvironment a highly heterogeneous and suppressive harbor protecting tumor cells from drug penetration, immune attack, and facilitating tumor development. In the last decade, targeted therapy and immunotherapy have emerged as promising options to treat advanced, metastatic, recurrent, and resistant NPC, but lack of understanding of the TME had hindered the therapeutic development and optimization. Single-cell sequencing of NPC-infiltrating cells has recently deciphered stromal composition and functional dynamics in the TME and non-malignant counterpart. In this review, we aim to depict the stromal landscape of NPC in detail based on recent advances, and propose various microenvironment-based approaches for precision therapy.