Seven Genes Associated With Lymphatic Metastasis in Thyroid Cancer That Is Linked to Tumor Immune Cell Infiltration

Gene-expression profile analysis to disclose diagnostics and therapeutics biomarkers for thyroid carcinoma

The most frequent endocrine cancer of the head and neck is thyroid carcinoma (THCA). Although there is increasing evidence linking THCA to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. There is still much to learn about THCA's molecular roots and genetic biomarkers. Though drug therapies are the best choice after metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving them for a few years. Therefore, multi-targeted different variants of therapeutic drugs may be essential for effective treatment against THCA. To understand molecular mechanisms of THCA development and progression and explore multi-targeted different variants of therapeutic drugs, we detected 80 common differentially expressed genes (cDEGs) between THCA and non-THCA samples from six microarray gene expression datasets using the statistical LIMMA approach. Through protein-protein interaction (PPI) network analysis, we identified the top-ranked eight differentially expressed genes (TIMP1, FN1, THBS1, RUNX2, SHANK2, TOP2A, LRP2, and ACTN1) as the THCA-causing key genes (KGs), where 6 KGs (TIMP1, TOP2A, FN1, ACTN1, RUNX2, THBS1) are upregulated and 2 KGs (LRP2, SHANK2) are downregulated. The expression pattern analysis of KGs with the independent TCGA database by Box plots also confirmed their upregulated and downregulated patterns. The expression analysis of KGs in different stages of THCA development indicated that these KGs might be utilized as early diagnostic and prognostic biomarkers. The pan-cancer analysis of KGs indicated a substantial correlation of KGs with multiple cancers, including THCA. Some transcription factors (TFs) and microRNAs were detected as the key transcriptional and post-transcriptional regulators of KGs using gene regulatory network (GRN) analysis. The enrichment analysis of the cDEGs revealed several key molecular functions, biological processes, cellular components, and pathways significantly associated with THCA. These findings highlight critical mechanisms influenced by the identified key genes (KGs), providing deeper insight into their roles in THCA development. Then we detected 6 repurposable drug molecules (Entrectinib, Imatinib, Ponatinib, Sorafenib, Retevmo, and Pazopanib) by molecular docking with KGs-mediated receptor proteins, ADME/T analysis, and cross-validation with the independent receptors. Therefore, these findings might be useful resources for wet lab researchers and clinicians to consider an effective treatment strategy against THCA.

Bioinformatic identification reveals a m6A-binding protein, IGF2BP2, as a novel tumor-promoting gene signature in thyroid carcinoma

N6-methyladenosine (m6A) modification plays a crucial role in thyroid carcinoma (THCA). Insulin-like growth factor 2 binding protein 2 (IGF2BP2) is a m6A-binding protein. We aimed to explore the effect of IGF2BP2 on the development of THCA. Differentially expressed genes (DEGs) were screened from GSE50901 and GSE60542 datasets. LinkedOmics, Genebank, and Sequence-based RNA Adenosine Methylation Site Predictor databases were employed to find potential m6A modification sites. Protein-protein interaction network and receiver-operating characteristic curves were applied to determine hub genes of THCA. ESTIMATE revealed the effect of IGF2BP2 on tumor immunity. The mRNA expression of IGF2BP2 was detected using real-time quantitative polymerase chain reaction. The viability, migration, and invasion were assessed by Cell Counting Kit-8, wound healing, and transwell assays. A total of 166 common DEGs were identified from GSE50901 and GSE60542 datasets. One m6A-related gene, IGF2BP2, was differentially expressed in THCA and selected as the research target. The hub genes (CD44, DCN, CXCL12, ICAM1, SDC4, KIT, CTGF, and FMOD) were identified with high prediction values for THCA. Subsequently, the target genes of IGF2BP2, SDC4, and ICAM1, which had potential m6A modification sites, were screened out based on the hub genes. IGF2BP2 was upregulated in THCA and IGF2BP2 expression was positively correlated with immune infiltration in THCA. Additionally, knockdown of IGF2BP2 inhibited the proliferation, invasion, and migration of THCA cells. IGF2BP2 has a contributory effect on the progression of THCA, which is a novel biomarker and a therapeutic target for THCA.

FAM20A: a potential diagnostic biomarker for lung squamous cell carcinoma

Background

Lung squamous cell carcinoma (LUSC) ranks among the carcinomas with the highest incidence and dismal survival rates, suffering from a lack of effective therapeutic strategies. Consequently, biomarkers facilitating early diagnosis of LUSC could significantly enhance patient survival. This study aims to identify novel biomarkers for LUSC.

Methods

Utilizing the TCGA, GTEx, and CGGA databases, we focused on the gene encoding Family with Sequence Similarity 20, Member A (FAM20A) across various cancers. We then corroborated these bioinformatic predictions with clinical samples. A range of analytical tools, including Kaplan-Meier, MethSurv database, Wilcoxon rank-sum, Kruskal-Wallis tests, Gene Set Enrichment Analysis, and TIMER database, were employed to assess the diagnostic and prognostic value of FAM20A in LUSC. These tools also helped evaluate immune cell infiltration, immune checkpoint genes, DNA repair-related genes, DNA methylation, and tumor-related pathways.

Results

FAM20A expression was found to be significantly reduced in LUSC, correlating with lower survival rates. It exhibited a negative correlation with key proteins in DNA repair signaling pathways, potentially contributing to LUSC's radiotherapy resistance. Additionally, FAM20A showed a positive correlation with immune checkpoints like CTLA-4, indicating potential heightened sensitivity to immunotherapies targeting these checkpoints.

Conclusion

FAM20A emerges as a promising diagnostic and prognostic biomarker for LUSC, offering potential clinical applications.

Repurposing homoharringtonine for thyroid cancer treatment through TIMP1/FAK/PI3K/AKT signaling pathway

Homoharringtonine (HHT), an alkaloid isolated from Cephalotaxus, is an effective anti-leukemia agent and exhibits inhibitory effects in various solid tumors. However, the impacts of HHT treatment on thyroid cancer (TC) remain unclear. Our findings demonstrated that HHT exhibited remarkable anti-TC activity that involved inhibiting cell proliferation, invasion, and migration, as well as inducing apoptosis. Proteomics analysis revealed that the expression of the tissue inhibitor of metalloproteinase 1 (TIMP1) was downregulated in TC cells after HHT treatment. TIMP1 overexpression promoted TC progression and partially reversed the anti-TC effects of HHT, while TIMP1 downregulation inhibited TC progression and enhanced the anti-TC effects of HHT. Furthermore, TIMP1 re-expression attenuated the enhancement of anti-TC effects of HHT induced by TIMP1 knockdown. Mechanistically, HHT exerted anti-TC effects by downregulating TIMP1 expression and then inactivating the FAK/PI3K/AKT signaling pathway. Taken together, our study demonstrated that HHT could inhibit TC progression by inhibiting the TIMP1/FAK/PI3K/AKT signaling pathway.

CEBPB-mediated upregulation of SERPINA1 promotes colorectal cancer progression by enhancing STAT3 signaling

Colorectal cancer (CRC) is a highly malignant carcinoma associated with poor prognosis, and metastasis is one of the most common causes of death in CRC. Serpin Family A Member 1 (SERPINA1) is a serine protease inhibitor from the Serpin family. Till now, the function and mechanism of SERPINA1 in CRC progression have not been fully illustrated. We established highly metastatic colorectal cancer cells named as RKO-H and Caco2-H by mice liver metastasis model. By integrative bioinformatic approaches, we analyzed the prognostic value and clinical significance of SERPINA1 in CRC, and predicted potential transcription factors. Colony formation, EDU, MTS, Transwell and wound healing assay were performed to evaluate the biological functions of SERPINA1 in CRC in vitro. Experiments in vivo were conducted to explore the effects of SERPINA1 on liver metastasis of CRC. ChIP and luciferase reporter gene assays were performed to identify the transcriptional regulatory mechanism of SERPINA1 by CEBPB. Our results show that SERPINA1 is highly expressed in CRC and correlated with poor clinical outcomes. SERPINA1 promotes the proliferation, migration by activating STAT3 pathway. Mechanistically, CEBPB binds SERPINA1 gene promoter sequence and promotes the transcription of SERPINA1. SERPINA1 drives CEBPB-induced tumor cell growth and migration via augmenting STAT3 signaling. Our results suggest that SERPINA1 is a potential prognostic marker and may serve as a novel treatment target for CRC.

Identification of Prognostic and Immune Characteristics of Two Lung Adenocarcinoma Subtypes Based on TRPV Channel Family Genes

Lung adenocarcinoma (LUAD) is one of the deadliest malignant tumors worldwide. Transient receptor potential vanilloid (TRPV) channels take pivotal parts in many cancers, but their impact on LUAD remains unexplored. In this study, LUAD samples were classified into two subtypes according to the expression characteristics of TRPV1-6 genes, with LUAD subtype cluster2 exhibiting significantly higher survival rates than cluster1. Subsequently, analysis of differentially expressed genes (DEGs) was performed between cluster1 and cluster2, revealing enrichment of DEGs in channel activity and Ca2+ signaling pathways. We established a protein-protein interaction network based on DEGs and constructed a LUAD prognostic model by using Cox regression analysis based on genes corresponding to 170 protein nodes. The prognostic model demonstrated good predictive ability for patient prognosis, with higher survival rates observed in the low-risk (LR) group. The risk score was validated as an independent prognostic indicator, according to Cox regression analysis. A clinically applicable nomogram was plotted. Immunological analysis indicated that the LR and high-risk (HR) groups had varied proportions of immune cell infiltration. The immunotherapy prediction indicated that LUAD patients in LR group had a greater likelihood to benefit from immune checkpoint blockade therapy. Furthermore, we hypothesized that the expression patterns of feature genes in the LUAD model were related to the sensitivity to lung cancer therapeutic drugs TAS-6417 and Erlotinib. To sum up, our LUAD prognostic model possessed clinical applicability for prognosis and immunotherapy response prediction.

EVA1A, a novel and promising prognostic biomarker in colorectal cancer

Purpose

The purpose of this study was to investigate the potential of EVA1A as a prognostic biomarker for Colorectal cancer (CRC).

Methods

The study utilized public databases to analyze the difference in Evala mRNA expression between CRC tumor tissues and adjacent normal tissues. Additionallymunohistochemical staining was performed on 90 paired tissue samples to detect EVA1A expression. The relationship between EVA1A and clinicopathological features was examined, and a Kaplan-Meier survival analysis was conducted. Univariate and multivariate Cox analyses were employed to identify prognostic factors affecting the overall survival (OS) of CRC patients.

Results

The analysis revealed a significant increase in Evala mRNA expression in CRC tumor cells compared to normal controls from public databases (P< 0.05). Immunohistochemical staining further confirmed a significant upregulation of EVA1A expression in CRC tissues (P< 0.05). High EVA1A expression was associated with age, pathological M stage, total tumor stage, and Carbohydrate antigen CA19-9 (CA19-9). Kaplan-Meier analysis demonstrated a significant association between high EVA1A expression and poor OS. Univariate and multivariate analysis identified EVA1A as an independent risk factor for CRC prognosis.

Conclusion

The study suggests that EVA1A is increased in CRC tumor tissues and may serve as a potential biomarker for poor prognosis in CRC.

m6A reader IGF2BP2 promotes lymphatic metastasis by stabilizing DPP4 in papillary thyroid carcinoma

Lymph node metastasis (LNM) is a major cause of locoregional recurrence of papillary thyroid carcinoma (PTC). However, the mechanisms responsible for LNM are unclear. Aberrant N6-methyladenosine (m6A) RNA modification plays a vital role in cancer progression and metastasis, and whether m6A modification regulates LNM in PTC remains to be determined. This study showed that IGF2BP2 was upregulated in PTC and positively associated with LNM. Functionally, IGF2BP2 knockdown significantly inhibited PTC cell proliferation and invasion in vitro, and vice versa. Moreover, IGF2BP2 knockdown significantly inhibited lymphatic metastasis in vivo. Mechanistically, Human m6A epitranscriptomic microarray, MeRIP, and RIP assays demonstrated that IGF2BP2 activated the NF-KB pathway by enhancing DPP4 stability in an m6A-dependent manner. Furthermore, IGF2BP2 knockdown increased the sensitivity of PTC cells to cisplatin therapy to a certain extent, while its overexpression produced the opposite effects. Overall, this study uncovers that IGF2BP2 promotes lymphatic metastasis via stabilizing DPP4 in an m6A-dependent manner, and provides new insights for understanding the mechanism of lymphatic metastasis in PTC.

Development and validation of survival nomograms for patients with differentiated thyroid cancer with distant metastases: a SEER Program-based study

BACKGROUND

We aimed to develop a nomogram model of overall survival (OS) and cancer-specific survival (CSS) in patients with differentiated thyroid cancer with distant metastases, and to evaluate and validate the nomogram. Also, its prognostic value was compared with that of the 8th edition of the American Joint Committee on Cancer tumor-node-metastasis staging system (AJCC8SS).

METHODS

Patients with distant metastatic differentiated thyroid cancer (DMDTC) from 2004 to 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) Program to extract the clinical variables used for analysis. A total of 906 patients were divided into a training set (n = 634) and validation set (n = 272). OS and CSS were selected as the primary end point and secondary end point. LASSO regression analysis and multivariate Cox regression analysis were applied to screen variables for constructing OS and CSS nomograms for survival probability at 3, 5, and 10 years. Nomograms were evaluated and validated using the consistency index (C-index), time-dependent receiver operator characteristic (ROC) curves, area under the ROC curve, calibration curves, and decision curve analysis (DCA). The predictive survival of the nomogram was compared with that of AJCC8SS. Kaplan-Meier curves and log-rank tests were used to evaluate the risk-stratification ability OS and CSS nomograms.

RESULTS

CS and CSS nomograms included six independent predictors: age, marital status, type of surgical procedure, lymphadenectomy, radiotherapy, and T stage. The C-index for the OS nomogram was 0.7474 (95% CI = 0.7199-0.775), and that for the CSS nomogram was 0.7572 (0.7281-0.7862). The nomogram showed good agreement with the "ideal" calibration curve in the training set and validation sets. DCA confirmed that the survival probability predicted by the nomogram had high clinical predictive value. The nomogram could stratify patients more accurately, and showed more robust accuracy and predictive power, than AJCC8SS.

CONCLUSIONS

We established and validated prognostic nomograms for patients with DMDTC, which had significant clinical value compared with AJCC8SS.

Integrated analysis of tumor microenvironment features to establish a diagnostic model for papillary thyroid cancer using bulk and single-cell RNA sequencing technology

BACKGROUND

Characterizing tumor microenvironment using single-cell RNA sequencing has been a promising strategy for cancer diagnosis and treatment. However, a few studies have focused on diagnosing papillary thyroid cancer (PTC) through this technology. Therefore, our study explored tumor microenvironment (TME) features and identified potential biomarkers to establish a diagnostic model for papillary thyroid cancer.

METHODS

The cell types were identified using the markers from the CellMarker database and published research. The CellChat package was conducted to analyze the cell-cell interaction. The SCEVAN package was used to identify malignant thyroid cells. The SCP package was used to perform multiple single-cell downstream analyses, such as GSEA analysis, enrichment analysis, pseudotime trajectory analysis, and differential expression analysis. The diagnostic model of PTC was estimated using the calibration curves, receiver operating characteristic curves, and decision curve analysis. RT-qPCR was performed to validate the expression of candidate genes in human papillary thyroid samples.

RESULTS

Eight cell types were identified in the scRNA-seq dataset by published cell markers. Extensive cell-cell interactions like FN1/ITGB1 existed in PTC tissues. We identified 26 critical genes related to PTC progression. Further, eight subgroups of PTC tumor cells were identified and exhibited high heterogeneity. The MDK/LRP1, MDK/ALK, GAS6/MERTK, and GAS6/AXL were identified as potential ligand-receptor pairs involved in the interactions between fibroblasts/endothelial cells and tumor cells. Eventually, the diagnostic model constructed by TRPC5, TENM1, NELL2, DMD, SLC35F3, and AUTS2 showed a good efficiency for distinguishing the PTC and normal tissues.

CONCLUSIONS

Our study comprehensively characterized the tumor microenvironment in papillary thyroid cancer. Through combined analysis with bulk RNA-seq, six potential diagnostic biomarkers were identified and validated. The diagnostic model we constructed was a promising tool for PTC diagnosis. Our findings provide new insights into the heterogeneity of thyroid cancer and the theoretical basis for diagnosing thyroid cancer.

Identification of disulfidptosis-related subtypes, characterization of tumor microenvironment infiltration, and development of a prognosis model in colorectal cancer

BACKGROUND

Colorectal cancer is the second leading cause of cancer-related deaths, which imposes a significant societal burden. Regular screening and emerging molecular tumor markers have important implications for detecting the progression and development of colorectal cancer. Disulfidptosis is a newly defined type of programmed cell death triggered by abnormal accumulation of disulfide compounds in cells that stimulate disulfide stress. Currently, there is no relevant discussion on this mechanism and colorectal cancer.

METHODS

We classified the disulfidptosis-related subtypes of colorectal cancer using bioinformatics methods. Through secondary clustering of differentially expressed genes between subtypes, we identified characteristic genes of the disulfidptosis subtype, constructed a prognostic model, and searched for potential biomarkers through clinical validation.

RESULTS

Using disulfidptosis-related genes collected from the literature, we classified colorectal cancer patients from public databases into three subtypes. The differentially expressed genes between subtypes were clustered into three gene subtypes, and eight characteristic genes were screened to construct a prognostic model.

CONCLUSION

The disulfidptosis mechanism has important value in the classification of colorectal cancer patients, and characteristic genes selected based on this mechanism can serve as a new potential biological marker for colorectal cancer.

Channeling the Natural Properties of Sindbis Alphavirus for Targeted Tumor Therapy

Sindbis alphavirus vectors offer a promising platform for cancer therapy, serving as valuable models for alphavirus-based treatment. This review emphasizes key studies that support the targeted delivery of Sindbis vectors to tumor cells, highlighting their effectiveness in expressing tumor-associated antigens and immunomodulating proteins. Among the various alphavirus vectors developed for cancer therapy, Sindbis-vector-based imaging studies have been particularly extensive. Imaging modalities that enable the in vivo localization of Sindbis vectors within lymph nodes and tumors are discussed. The correlation between laminin receptor expression, tumorigenesis, and Sindbis virus infection is examined. Additionally, we present alternative entry receptors for Sindbis and related alphaviruses, such as Semliki Forest virus and Venezuelan equine encephalitis virus. The review also discusses cancer treatments that are based on the alphavirus vector expression of anti-tumor agents, including tumor-associated antigens, cytokines, checkpoint inhibitors, and costimulatory immune molecules.

An Analysis of the Gene Expression Associated with Lymph Node Metastasis in Colorectal Cancer

Objective

This study aimed to explore the genes regulating lymph node metastasis in colorectal cancer (CRC) and to clarify their relationship with tumor immune cell infiltration and patient prognoses.

Methods

The data sets of CRC patients were collected through the Cancer Gene Atlas database; the differentially expressed genes (DEGs) associated with CRC lymph node metastasis were screened; a protein-protein interaction (PPI) network was constructed; the top 20 hub genes were selected; the Gene Ontology functions and the Kyoto Encyclopedia of Genes and Genomes pathways were enriched and analyzed. The Least Absolute Shrinkage and Selection Operator (LASSO) regression method was employed to further screen the characteristic genes associated with CRC lymph node metastasis in 20 hub genes, exploring the correlation between the characteristic genes and immune cell infiltration, conducting a univariate COX analysis on the characteristic genes, obtaining survival-related genes, constructing a risk score formula, conducting a Kaplan-Meier analysis based on the risk score formula, and performing a multivariate COX regression analysis on the clinical factors and risk scores.

Results

A total of 62 DEGs associated with CRC lymph node metastasis were obtained. Among the 20 hub genes identified via PPI, only calcium-activated chloride channel regulator 1 (CLCA1) expression was down-regulated in lymph node metastasis, and the rest were up-regulated. A total of nine characteristic genes associated with CRC lymph node metastasis (KIF1A, TMEM59L, CLCA1, COL9A3, GDF5, TUBB2B, STMN2, FOXN1, and SCN5A) were screened using the LASSO regression method. The nine characteristic genes were significantly related to different kinds of immune cell infiltration, from which three survival-related genes (TMEM59L, CLCA1, and TUBB2B) were screened. A multi-factor COX regression showed that the risk scores obtained from TMEM59L, CLCA1, and TUBB2B were independent prognostic factors. Immunohistochemical validation was performed in tissue samples from patients with rectal and colon cancer.

Conclusion

TMEM59L, CLCA1, and TUBB2B were independent prognostic factors associated with lymphatic metastasis of CRC.

Loss of MXRA8 Delays Mammary Tumor Development and Impairs Metastasis

Matrix-remodeling-associated protein 8 or MXRA8 is a transmembrane protein that can bind arthritogenic alpha viruses like the Chikungunya virus and provide viral entry into cells. MXRA8 can also interact with integrin β3 and thus possibly regulate cell-cell interactions and binding to the extracellular matrix. While MXRA8 has been associated with reduced survival in patients with colorectal and renal clear cell cancers, the role of MXRA8 in breast cancer remains largely unexplored. Therefore, the aim of this research was to determine the role of MXRA8 in breast cancer by knocking out MXRA8 in the human triple-negative breast cancer cell line MDA-MB-231. The loss of MXRA8 reduced cell proliferation in vitro but had no effect on apoptosis or migration in cultured cells. However, the loss of MXRA8 significantly delayed tumor development and reduced metastatic dissemination to the lungs in a xenograft model. RNA sequencing identified three genes, ADMATS1, TIE1, and BMP2, whose expression were significantly reduced in MXRA8-knockout tumors compared to control tumors. MXRA8 staining of a human breast cancer tissue array revealed higher levels of MXRA8 in primary tumors and metastases of aggressive tumor subtypes (TNBC and HER2+) compared to less aggressive, ER+ breast cancers. Our findings demonstrate for the first time that MXRA8 regulates the progression of human TNBC possibly through influencing the interaction of tumor cells with their microenvironment.

Lymph node metastasis-related gene signature shows good performance in predicting prognosis and immune infiltration in cervical cancer

Aims

This study aimed to construct a lymph node metastasis-related gene signature to predict prognosis and immune infiltration in patients with cervical cancer.

Methods

Clinical and RNA sequencing data of 193 patients with cervical cancer, which were divided into lymph node metastasis (N1) and non-lymph node metastasis (N0) groups, were acquired from TCGA. Differentially expressed genes (DEGs) between the N1 and N0 groups were detected, and protein-protein interaction combined with LASSO analysis was conducted to further screen lymph node metastasis-related genes. Univariate and multivariate Cox regression analyses were performed to establish a predictive signature. The genetic features, potential biological behavior, and immune infiltration characteristics of the predictive signature were explored. Furthermore, the sensitivity of patients to chemotherapy drugs was estimated based on the predictive signature and the expression of TEKT2 and RPGR was investigated in the cervical cancer tissue samples.

Results

A total of 271 lymph node metastasis-related DEGs, including 100 upregulated and 171 downregulated genes, were identified. Two genes, TEKT2 and RPGR, were associated with lymph node metastasis and prognosis in cervical cancer, and were used to construct a lymph node metastasis-related predictive signature. Based on the predictive signature, patients with cervical cancer were divided into high- and low-risk groups. The high-risk group, characterized by a higher tumor mutation burden and somatic mutation rate, indicated a poor overall survival. The activation of immune infiltration and increased expression of checkpoint genes were observed in the high-risk group, indicating that they might benefit from immunotherapy. Cytarabine, FH535, and procaspase-activating compound-1 were estimated as reasonable chemotherapy options for patients in the high-risk group, whereas two taxanes and five tyrosine kinase inhibitors, including etoposide and vinorelbine, had therapeutic significance for patients in the low-risk group. The expression of TEKT2 and RPGR was significantly downregulated in cervical cancer tissues, especially in metastatic lymph node tissues.

Discussion

The lymph node metastasis-related predictive signature based on TEKT2 and RPGR showed good performance in predicting the survival outcomes of patients with cervical cancer. The risk score of the predictive signature was related to genetic variation and immune infiltration, which could guide immunotherapy and chemotherapy strategies.

Integration of transcriptomics and metabolomics reveals a novel gene signature guided by FN1 associated with immune response in oral squamous cell carcinoma tumorigenesis

PURPOSE

Oral squamous cell carcinomas (OSCCs) are primary head and neck malignant tumours with a high incidence and mortality. However, the molecular mechanisms involved in OSCC tumorigenesis are not fully understood.

METHODS

OSCC and paired para-carcinoma samples were collected and used to perform multi-omics study. Transcriptomic analysis was used to reveal significant alterations in inflammatory and immune processes in OSCC. Ingenuity Pathway Analysis (IPA) combined with the LASSO Cox algorithm was used to identify and optimize a crucial gene signature. Metabolomics analysis was performed to identify the important metabolites which linked to the crucial gene signature. The public data TCGA-HNSCC cohort was used to perform the multiple bioinformatic analysis.

RESULTS

These findings identified a FN1-mediated crucial network that was composed of immune-relevant genes (FN1, ACP5, CCL5, COL1A1, THBS1, BCAT1, PLAU, IGF2BP3, TNF, CSF2, CXCL1 and CXCL5) associated with immune infiltration and influences the tumour microenvironment, which may contribute to OSCC tumorigenesis and progression. Moreover, we integrated the relevant genes with altered metabolites identified by metabolic profiling and identified 7 crucial metabolites (Glu-Glu-Lys, Ser-Ala, Ser-Ala, N-(octadecanoyl) sphing-4-enine-1-phosphocholine, N-methylnicotinamide, pyrrhoxanthinol and xanthine) as potential downstream targets of the FN1-associated gene signature in OSCC. Importantly, FN1 expression is positively correlated with immune infiltration levels in HNSCC, which was confirmed at the single-cell level.

CONCLUSIONS

Overall, these results revealed the differential genetic and metabolic patterns associated with OSCC tumorigenesis and identified an essential molecular network that plays an oncogenic role in OSCC by affecting amino acid and purine metabolism. These genes and metabolites might, therefore, serve as predictive biomarkers of survival outcomes and potential targets for therapeutic intervention in OSCC.

MXRA8 is an immune-relative prognostic biomarker associated with metastasis and CD8+ T cell infiltration in colorectal cancer

Background

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths worldwide. Tumor metastasis and CD8⁺ T cell infiltration play a crucial role in CRC patient survival. It is important to determine the etiology and mechanism of the malignant progression of CRC to develop more effective treatment strategies.

Methods

We conducted weighted gene co-expression network analysis (WGCNA) to explore vital modules of tumor metastasis and CD8⁺ T cell infiltration, then with hub gene selection and survival analysis. Multi-omics analysis is used to explore the expression pattern, immunity, and prognostic effect of MXRA8. The molecular and immune characteristics of MXRA8 are analyzed in independent cohorts, clinical specimens, and in vitro.

Results

MXRA8 expression was strongly correlated with tumor malignancy, metastasis, recurrence, and immunosuppressive microenvironment. Furthermore, MXRA8 expression predicts poor prognosis and is an independent prognostic factor for OS in CRC.

Conclusion

MXRA8 may be a potential immunotherapeutic and prognostic biomarker for CRC.

Regulation of secretory pathway kinase or kinase-like proteins in human cancers

Secretory pathway kinase or kinase-like proteins (SPKKPs) are effective in the lumen of the endoplasmic reticulum (ER), Golgi apparatus (GA), and extracellular space. These proteins are involved in secretory signaling pathways and are distinctive from typical protein kinases. Various reports have shown that SPKKPs regulate the tumorigenesis and progression of human cancer via the phosphorylation of various substrates, which is essential in physiological and pathological processes. Emerging evidence has revealed that the expression of SPKKPs in human cancers is regulated by multiple factors. This review summarizes the current understanding of the contribution of SPKKPs in tumorigenesis and the progression of immunity. With the epidemic trend of immunotherapy, targeting SPKKPs may be a novel approach to anticancer therapy. This study briefly discusses the recent advances regarding SPKKPs.

Single-cell CRISPR immune screens reveal immunological roles of tumor intrinsic factors

Genetic screens are widely exploited to develop novel therapeutic approaches for cancer treatment. With recent advances in single-cell technology, single-cell CRISPR screen (scCRISPR) platforms provide opportunities for target validation and mechanistic studies in a high-throughput manner. Here, we aim to establish scCRISPR platforms which are suitable for immune-related screens involving multiple cell types. We integrated two scCRISPR platforms, namely Perturb-seq and CROP-seq, with both in vitro and in vivo immune screens. By leveraging previously generated resources, we optimized experimental conditions and data analysis pipelines to achieve better consistency between results from high-throughput and individual validations. Furthermore, we evaluated the performance of scCRISPR immune screens in determining underlying mechanisms of tumor intrinsic immune regulation. Our results showed that scCRISPR platforms can simultaneously characterize gene expression profiles and perturbation effects present in individual cells in different immune screen conditions. Results from scCRISPR immune screens also predict transcriptional phenotype associated with clinical responses to cancer immunotherapy. More importantly, scCRISPR screen platforms reveal the interactive relationship between targeting tumor intrinsic factors and T cell-mediated antitumor immune response which cannot be easily assessed by bulk RNA-seq. Collectively, scCRISPR immune screens provide scalable and reliable platforms to elucidate molecular determinants of tumor immune resistance.

Construction and validation of a prognostic model based on stage-associated signature genes of head and neck squamous cell carcinoma: a bioinformatics study

Background

Head and neck squamous cell carcinoma (HNSCC) is a malignancy of epithelial origin and with poor prognosis. Exploring the biomarkers and prognostic models that can contribute to early tumor detection is meaningful. A comprehensive analysis was conducted according to the stage-related signature genes of HNSCC, and a prognostic model was developed to validate their ability to predict the prognosis.

Methods

The transcriptome profiles and clinical information of HNSCC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) respectively. mRNA expressions of differentially expressed genes (DEGs) were analyzed in stage I-II patients and stage III-IV patients from TCGA by R packages. A protein-protein interaction (PPI) network and core-gene network map were constructed, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to examine pathway enrichment. Kaplan-Meier, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were applied to establish a stage-associated signature model. A Spearman analysis was conducted to examine the correlations between the characteristic genes and immune cell infiltration. Kaplan-Meier analysis and a receiver operating characteristic (ROC) curve were used to test the effectiveness of the model. Univariate multivariate Cox regression analyses were used to assess whether the risk score was an independent prognostic indicator for HNSCC.

Results

In TCGA cohort, 5 genes (i.e., BRINP1, IL17A, ALB, FOXA2, and ZCCHC12) in the constructed prognostic risk model were associated with prognosis. Patients in the low-risk group had a better prognosis outcome than those in the high-risk group. The predictive power was good because all the area under the curve (AUC) of the risk score was higher than 0.6. Risk score [hazard ratio (HR) =1.985; P<0.001] was an independent risk factor for the prognosis of HNSCC. The results in the GEO cohort were consistent with those in the TCGA cohort.

Conclusions

We constructed and verified a prognostic risk model of stage-related signature genes for HNSCC based on the GEO and TCGA data. Due to the good predictive accuracy of this model, the prognosis of and the tumor immune cell infiltration with patients can be estimated.

Screening of ulcerative colitis biomarkers and potential pathways based on weighted gene co-expression network, machine learning and ceRNA hypothesis

BACKGROUND

Ulcerative colitis (UC) refers to an intractable intestinal inflammatory disease. Its increasing incidence rate imposes a huge burden on patients and society. The UC etiology has not been determined, so screening potential biomarkers is critical to preventing disease progression and selecting optimal therapeutic strategies more effectively.

METHODS

The microarray datasets of intestinal mucosal biopsy of UC patients were selected from the GEO database, and integrated with R language to screen differentially expressed genes and draw proteins interaction network diagrams. GO, KEGG, DO and GSEA enrichment analyses were performed to explore their biological functions. Through machine learning and WGCNA analysis, targets that can be used as UC potential biomarkers are screened out. ROC curves were drawn to verify the reliability of the results and predicted the mechanism of marker genes from the aspects of immune cell infiltration, co-expression analysis, and competitive endogenous network (ceRNA).

RESULTS

Two datasets GSE75214 and GSE87466 were integrated for screening, and a total of 107 differentially expressed genes were obtained. They were mainly related to biological functions such as humoral immune response and inflammatory response. Further screened out five marker genes, and found that they were associated with M0 macrophages, quiescent mast cells, M2 macrophages, and activated NK cells in terms of immune cell infiltration. The co-expression network found significant co-expression relationships between 54 miRNAs and 5 marker genes. According to the ceRNA hypothesis, NEAT1-miR-342-3p/miR-650-SLC6A14, NEAT1-miR-650-IRAK3, and XIST-miR-342-3p-IRAK3 axes were found as potential regulatory pathways in UC.

CONCLUSION

This study screened out five biomarkers that can be used for the diagnosis and treatment of UC, namely SLC6A14, TIMP1, IRAK3, HMGCS2, and APOBEC3B. Confirmed that they play a role in the occurrence and development of UC at the level of immune infiltration, and proposed a potential RNA regulatory pathway that controls the progression of UC.

ERBB2 as a prognostic biomarker correlates with immune infiltrates in papillary thyroid cancer

Epidermal growth factor receptor 2 (ERBB2) is commonly over-expressed in advanced or metastatic tissues of papillary thyroid cancer (PTC) with poor prognosis, while it remains unknown whether ERBB2 plays a role in the progression of PTC. Thus, we analyzed the data derived from online repositories, including TCGA, KEGG, GO, GeneMANIA, and STRING, to explore the relationship between ERBB2 expression and prognosis, tumor phenotypes of interest, and immune infiltrates in PTC. Compared to normal thyroid tissue, ERBB2 was up-regulated in PTC samples (p < 0.001); In comparison with the group with low expression of ERBB2, the group with high expression of ERBB2 had poorer progression-free interval in stage III/IV patients (p = 0.008) and patients aged >45 years (p = 0.019). The up-regulated ERBB2 was associated with iodine metabolism dysfunction, proliferation, metastasis, angiogenesis, and drug resistance. The expression of ERBB2 negatively correlated with enrichment scores of B cells (r = −0.176, p < 0.001), CD8⁺ T cells (r = −0.160, p < 0.001), cytotoxic cells (r = −0.219, p < 0.001), NK CD56dim cells (r = −0.218, p < 0.001), plasmacytoid dendritic cells (r = −0.267, p < 0.001), T cells (r = −0.164, p < 0.001), T follicular helper cells (r = −0.111, p = 0.012), gamma delta T cells (r = −0.105, p = 0.017), and regulatory T cells (r = −0.125, p = 0.005). In conclusion, ERBB2 may serve as a prognostic biomarker and an immunotherapeutic target in PTC, deserving further exploration.