Papillary thyroid carcinoma with a high tumor mutation burden has a poor prognosis

SYVN1 modulates papillary thyroid carcinoma progression by destabilizing HMGB1

E3 ubiquitin ligase synoviolin (SYVN1) has been reported to participate in many human cancers. This study aimed to investigate SYVN1's roles and molecular pathways in papillary thyroid cancer (PTC). The functions of SYVN1 in PTC were further analyzed using gain- and loss-of-function methods and numerous investigations in cellular function and molecular biology. The findings demonstrated that the overexpression of SYVN1 markedly suppressed the proliferation, migration, and invasion of PTC cell lines (NPA87 and TPC-1). We found that SYVN1 interacted with HMGB1 and promoted its ubiquitination and degradation. In addition, SYVN1 effectively impairs cell proliferation, migration, invasion, and the formation of tumor xenografts in mice models. However, this effect may be partly reversed by overexpressing HMGB1. Thus, SYVN1 may inhibit the proliferation, migration, and invasion of PTC cells by disrupting HMGB1. Consequently, SYVN1 might be considered a promising therapeutic target for PTC.

In silico Screening and Validation of Achyranthes aspera as a Potential Inhibitor of BRAF and NRAS in Controlling Thyroid Cancer

BACKGROUND

Thyroid carcinoma (THCA) is one of the most prevalent endocrine tumors, accounting for 3.4% of all cancers diagnosed annually. Single Nucleotide Polymorphisms (SNPs) are the most prevalent genetic variation associated with thyroid cancer. Understanding thyroid cancer genetics will enhance diagnosis, prognosis, and treatment.

METHODS

This TCGA-based study analyzes thyroid cancer-associated highly mutated genes through highly robust in silico techniques. Pathway, gene expression, and survival studies were performed on the top 10 highly mutated genes (BRAF, NRAS, TG, TTN, HRAS, MUC16, ZFHX3, CSMD2, EIFIAX, SPTA1). Novel natural compounds from Achyranthes aspera Linn were discovered to target two highly mutated genes. The natural compounds and synthetic drugs used to treat thyroid cancer were subjected to comparative molecular docking against BRAF and NRAS targets. The ADME characteristics of Achyranthes aspera Linn compounds were also investigated.

RESULTS

The gene expression analysis revealed that the expression of ZFHX3, MCU16, EIF1AX, HRAS, and NRAS was up-regulated in tumor cells while BRAF, TTN, TG, CSMD2, and SPTA1 were down-regulated in tumor cells. In addition, the protein-protein interaction network demonstrated that HRAS, BRAF, NRAS, SPTA1, and TG proteins have strong interactions with each other as compared to other genes. The ADMET analysis shows that seven compounds have druglike properties. These compounds were further studied for molecular docking studies. The compounds MPHY012847, IMPHY005295, and IMPHY000939 show higher binding affinity with BRAF than pimasertib. In addition, IMPHY000939, IMPHY000303, IMPHY012847, and IMPHY005295 showed a better binding affinity with NRAS than Guanosine Triphosphate.

CONCLUSION

The outcomes of docking experiments conducted on BRAF and NRAS provide insight into natural compounds with pharmacological characteristics. These findings indicate that natural compounds derived from plants as a more promising cancer treatment option. Thus, the results of docking investigations conducted on BRAF and NRAS substantiate the conclusions that the molecule possesses the most suited drug-like qualities. Compared to other compounds, natural compounds are superior, and they are also druggable. This demonstrates that natural plant compounds can be an excellent source of potential anti-cancer agents. The preclinical research will pave the road for a possible anti-cancer agent.

A Novel Pyroptosis-Related Gene Signature for Prediction of Disease-Free Survival in Papillary Thyroid Carcinoma

BACKGROUND

The incidence and recurrence rate of papillary thyroid carcinoma (PTC) are high. Thus, it is critical to accurately identify patients at high risk of recurrence. Pyroptosis is a type of programmed cell death closely related to the progression and prognosis of cancer. However, the role of pyroptosis in PTC remains unclear.

METHODS

Transcriptome data for PTC patients were obtained from The Cancer Genome Atlas database. The expression level of pyroptosis-related genes (PRGs) in PTC and normal tissues was identified. Based on these differentially expressed genes, a risk score model of disease-free survival (DFS) was established using least absolute shrinkage and selection operator Cox regression. In-cluster and quantitative real-time PCR validations were carried out. A nomogram, in combination with clinical factors, was also established. In addition, its relationship with immune characteristics and tumor gene mutations is discussed.

RESULTS

A risk score model with four PRGs, including CASP6, CASP9, IL-18, and NOD1, was established. The samples were divided into high- and low-risk clusters, according to the risk score, revealing significant differences in DFS between the two clusters. A nomogram was established combining age, lymph node metastasis and extrathyroidal extension. The area under the curve (AUC) of predicting one-, five-, and 10-year DFS in PTC patients was 0.745, 0.801, and 0.803, respectively. The low-risk cluster showed higher levels of immune infiltration and immune checkpoint gene expression, while the high-risk cluster demonstrated a higher tumor mutation burden.

CONCLUSION

A predictive DFS model was established, based on PRGs, which may aid in identifying patients at high risk of recurrence. The present study helps to better understand the role of pyroptosis in the progression and prognosis of PTC.

High tumor mutation burden indicates better prognosis in colorectal cancer patients with KRAS mutations

OBJECTIVE

Colorectal cancer (CRC) is a common type of malignant tumor of the digestive tract. Tumor mutation burden (TMB) is a potential prognostic indicator of numerous malignant tumors. This study investigated the prognostic value of TMB in CRC.

METHODS

This study analyzed the clinical and somatic mutation data of patients with CRC from the Memorial Sloan Kettering Cancer Center (MSKCC) and The Cancer Genome Atlas (TCGA) cohorts. The genetic landscape was visualized using the maftools package in R software. Survival curves were constructed using the Kaplan-Meier method, and Cox regression analysis was performed to confirm that TMB is an independent prognostic indicator. A nomogram was developed to construct the prognostic model, which was evaluated using the C-index, calibration curve, and decision curve analysis.

RESULTS

In patients with CRC, APC mutations indicated longer overall survival (OS), whereas KRAS mutations indicated shorter OS. For all included patients, there was no significant difference in the OS between the TMB-high and TMB-low groups. For patients with KRAS mutations, the OS in the TMB-high group was longer than that in the TMB-low group. Cox regression analysis showed that TMB was an independent prognostic factor in CRC patients with KRAS mutations. This explains the good accuracy of the nomogram prognostic model using TMB and indicates its good prospect in clinical applications.

CONCLUSIONS

A high TMB indicates better prognosis in CRC patients with KRAS mutations, thus confirming the value of TMB in clinical applications.

A recurrent somatic missense mutation in GNAS gene identified in familial thyroid follicular cell carcinomas in German longhaired pointer dogs

BACKGROUND

We previously reported a familial thyroid follicular cell carcinoma (FCC) in a large number of Dutch German longhaired pointers and identified two deleterious germline mutations in the TPO gene associated with disease predisposition. However, the somatic mutation profile of the FCC in dogs has not been investigated at a genome-wide scale.

RESULTS

Herein, we comprehensively investigated the somatic mutations that potentially contribute to the inherited tumor formation and progression using high depth whole-genome sequencing. A GNAS p.A204D missense mutation was identified in 4 out of 7 FCC tumors by whole-genome sequencing and in 20 out of 32 dogs' tumors by targeted sequencing. In contrast to this, in the human TC, mutations in GNAS gene have lower prevalence. Meanwhile, the homologous somatic mutation in humans has not been reported. These findings suggest a difference in the somatic mutation landscape between TC in these dogs and human TC. Moreover, tumors with the GNAS p.A204D mutation had a significantly lower somatic mutation burden in these dogs. Somatic structural variant and copy number alterations were also investigated, but no potential driver event was identified.

CONCLUSION

This study provides novel insight in the molecular mechanism of thyroid carcinoma development in dogs. German longhaired pointers carrying GNAS mutations in the tumor may be used as a disease model for the development and testing of novel therapies to kill the tumor with somatic mutations in the GNAS gene.

Genotypes of Papillary Thyroid Carcinoma With High Lateral Neck Metastasis in Chinese Population

Papillary Thyroid Carcinoma (PTC) is one of the most commonly diagnosed cancer types in China, characterized by its early age at diagnosis and high 25-year survival rate. Distinct mutational patterns in PTC have been linked to activation of the mitogen-activated protein kinase (MAPK) signaling pathway. To explore the clinical significance of genomic variation patterns in Chinese patients with thyroid carcinoma, we investigated the genomic variants in 83 PTC cases with complete clinical records. The mutational patterns were evaluated using a 688-gene panel which covered known driver genes in PTC tumorigenesis, and featured genetic markers in various PTC-related pathways. We evaluated the relationship between mutational landscape and various clinical information in PTC patients with lateral lymph node metastasis. BRAF V600E was the most common mutation. Mutations in NF1, CDC27, PMS2 and PPP4R2 were more common in men, and mutations in NF1, PMS2 and TERT were related to lateral lymph node metastasis. According to the clustering of mutational patterns, we show that the underline driving mechanisms in lateral lymph node metastasis can be divided into two major groups (BRAF-TERT pathway, and NF1-PMS2 pathway). When combined with the TERT mutations, the BRAF mutation group was prone to lateral lymph node metastasis, particularly in elderly women. The NF1 mutations usually co-existed with PMS2 mutations, and this group included more men and young patients who had a high tumor mutational burden and lateral lymph node metastasis rate.

Correlation between BTG3, CASP9 and LRP4 single-nucleotide polymorphisms and susceptibility to papillary thyroid carcinoma

Objective: To study the association of BTG3, CASP9 and LRP4 single-nucleotide polymorphisms with susceptibility to papillary thyroid carcinoma (PTC). Methods: The BTG3 rs9977638, CASP9 rs884363 and LRP4 rs898604 genotypes of 175 PTC patients and 175 controls were analyzed. Results: Rs9977638 TC genotype and CC genotype, rs884363 CC genotype and rs898604 GG genotype were related to a lower PTC susceptibility risk (p < 0.01). The risk of PTC susceptibility was higher when carrying BTG3 rs9977638 CC, CASP9 rs884363 AC and LRP4 rs898604 AG at the same time (p < 0.01). Conclusion: Combined BTG3, CASP9 and LRP4 genotype analysis has a certain application value in the diagnosis of PTC.

High tumor mutation burden indicates a poor prognosis in patients with intrahepatic cholangiocarcinoma

BACKGROUND

Intrahepatic cholangiocarcinoma (ICC) is malignancies of the biliary duct system and constitutes approximately 10%-20% of all primary liver cancers. Tumor mutation burden (TMB) is a useful biomarker across many cancer types for the identification of patients who will benefit from immunotherapy. Despite the role of TMB in calculating the effectiveness and prognosis of immune checkpoint inhibitors has been confirmed in multiple human cancer types, the prognostic value of TMB in ICC patients is rare investigated.

AIM

To investigate the prognostic value of TMB in patients with ICC.

METHODS

Data of 412 patients with ICC were included in the study. TMB was calculated as the total number of somatic non-silent protein-coding mutations divided by the coding region. The Kaplan-Meier method was used to analyze overall survival (OS), and relapse free survival (RFS). The cut-off value of TMB was determined by time-dependent receiver operating characteristic (ROC) curve. Cox regression was performed for multivariable analysis of OS. The nomogram and calibration curve were analyzed to construct and evaluate the prognostic model.

RESULTS

In the analysis of the time-dependent ROC curve, we defined 3.1 mut/Mb as the cut-off value of TMB. The Kaplan-Meier plot revealed that patients with high TMB had poor OS (HR = 1.47, P = 0.002) and RFS (HR = 1.42, P = 0.035). Cox regression analysis also demonstrated that TMB was an independent risk predictor for ICC (HR = 1.43, P = 0.0240). Furthermore, independent prognostic factors of ICC included CA19-9 (HR = 1.78, P = 0.0005), chronic viral hepatitis (HR = 1.72, P = 0.0468), tumor resection (HR = 2.58, P < 0.0001) and disease progression (metastatic disease vs. solitary liver tumor; HR = 2.55, P = 0.0002). The nomogram and calibration curve also indicated the effectiveness of the constructed prognostic model.

CONCLUSION

TMB was an independent prognostic biomarker in patients with ICC. Moreover, patients with ICC with high TMB had poor OS and RFS as compared to those with low TMB.

Construction and Evaluation of a Tumor Mutation Burden-Related Prognostic Signature for Thyroid Carcinoma

Thyroid carcinoma is a type of prevalent cancer. Its prognostic evaluation depends on clinicopathological features. However, such conventional methods are deficient. Based on mRNA, single nucleotide variants (SNV), and clinical information of thyroid carcinoma from The Cancer Genome Atlas (TCGA) database, this study statistically analyzed mutational signature of patients with this disease. Missense mutation and SNV are the most common variant classification and variant type, respectively. Next, tumor mutation burden (TMB) of sample was calculated. Survival status of high/low TMB groups was analyzed, as well as the relationship between TMB and clinicopathological features. Results revealed that patients with high TMB had poor survival status, and TMB was related to several clinicopathological features. Through analysis on DEGs in high/low TMB groups, 381 DEGs were obtained. They were found to be mainly enriched in muscle tissue development through enrichment analysis. Then, through Cox regression analysis, a 5-gene prognostic signature was established, which was then evaluated through survival curves and receiver operation characteristic (ROC) curves. The result showed that the signature was able to effectively predict patient's prognosis and to serve as an independent prognostic risk factor. Finally, through Gene Set Enrichment Analysis (GSEA) on high/low-risk groups, DEGs were found to be mainly enriched in signaling pathways related to DNA repair. Overall, based on the TCGA-THCA dataset, we constructed a 5-gene prognostic signature through a trail of bioinformatics analysis.

Development and validation of a ferroptosis-related prognostic model for the prediction of progression-free survival and immune microenvironment in patients with papillary thyroid carcinoma

BACKGROUND

Ferroptosis is an iron-dependent and regulated cell death that has been widely reported in a variety of malignancies. The overall survival of papillary thyroid cancer (PTC) is excellent, but the identification of patients with poor prognosis still faces challenges. Nevertheless, whether ferroptosis-related genes (FRGs) can be used to screen high-risk patients is not clear.

METHODS

We obtained the clinical data of patients with PTC and FRGs from the UCSC Xena platform and the FerrDb respectively. Differentially expressed genes (DEGs) of FRGs were obtained from the entire The Cancer Genome Atlas (TCGA). Subsequently, the entire TCGA dataset was randomly split into two subsets: training and test datasets. Based on DEGs, we constructed a predictive model which was tested in the test dataset and the entire TCGA dataset to predict progression-free survival (PFS). Patients were categorized into high- or low-risk groups based on their median risk score. We analyzed differences in some aspects, including pathway enrichment analysis, single-sample Gene Set Enrichment Analysis (ssGSEA), tumor microenvironment (TME), human leukocyte antigen (HLA) genes, and tumor mutation burden (TMB) analyses, between high-risk and low-risk groups.

RESULTS

A predictive model with three FRGs (HSPA5, AURKA, and TSC22D3) was constructed. Patients in the high-risk group had worse PFS compared with patients in the low-risk group. Functional analysis results revealed that ssGSEA, immune cell infiltration, TME, HLA, and TMB were closely associated with ferroptosis.

CONCLUSION

The prognostic model constructed in this study can effectively predict PFS for patients with PTC.

Transcriptome Analyses Identify a Metabolic Gene Signature Indicative of Antitumor Immunosuppression of EGFR Wild Type Lung Cancers With Low PD-L1 Expression

Purpose

With the development and application of targeted therapies like tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), non-small cell lung cancer (NSCLC) patients have achieved remarkable survival benefits in recent years. However, epidermal growth factor receptor (EGFR) wild-type and low expression of programmed death-ligand 1 (PD-L1) NSCLCs remain unmanageable. Few treatments for these patients exist, and more side effects with combination therapies have been observed. We intended to generate a metabolic gene signature that could successfully identify high-risk patients and reveal its underlying molecular immunology characteristics.

Methods

By identifying the bottom 50% PD-L1 expression level as PD-L1 low expression and removing EGFR mutant samples, a total of 640 lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) tumor samples and 93 adjacent non-tumor samples were finally extracted from The Cancer Genome Atlas (TCGA). We identified differentially expressed metabolic genes (DEMGs) by R package limma and the prognostic genes by Univariate Cox proportional hazards regression analyses. The intersect genes between DEMGs and prognostic genes were put into the least absolute shrinkage and selection operator (LASSO) penalty Cox regression analysis. The metabolic gene signature contained 18 metabolic genes generated and successfully stratified LUAD and LUSC patients into the high-risk and low-risk groups, which was also validated by the Gene Expression Omnibus (GEO) database. Its accuracy was proved by the time-dependent Receiver Operating Characteristic (ROC) curve, Principal Components Analysis (PCA), and nomogram. Furthermore, the Single-sample Gene Set Enrichment Analysis (ssGSEA) and diverse acknowledged methods include XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT-ABS, and CIBERSORT revealed its underlying antitumor immunosuppressive status. Besides, its relationship with somatic copy number alterations (SCNAs) and tumor mutational burden (TMB) was also discussed.

Results

It is noteworthy that metabolism reprogramming is associated with the survival of the double-negative LUAD and LUSC patients. The SCNAs and TMB of critical metabolic genes can inhibit the antitumor immune process, which might be a promising therapeutic target.