Identification of NID1 as a novel candidate susceptibility gene for familial non-medullary thyroid carcinoma using whole-exome sequencing

Identification of HSPG2 as a bladder pro-tumor protein through NID1/AKT signaling

PURPOSE

Heparan sulfate proteoglycans (HSPGs) are complex molecules found on the cell membrane and within the extracellular matrix, increasingly recognized for their role in tumor progression. This study aimed to investigate the involvement of Heparan sulfate proteoglycan 2 (HSPG2) in the progression of bladder cancer.

METHODS

We identified HSPG2 as a promoter of bladder tumor progression using single-cell RNA sequencing and transcriptome analysis of sequencing data from seven patient samples obtained from the Gene Expression Omnibus (GEO) database (GSE135337). Transcript profiles of 28 normal tissues and 407 bladder tumor tissues were analyzed for HSPG2 expression and survival outcomes using the Sanger tools and cBioPortal databases. HSPG2-overexpressing T24 and Biu-87 cell lines were generated, and cell proliferation and migration were assessed using CCK-8 and Transwell assays. Western blotting and immunostaining were performed to evaluate the activation of Nidogen-1 (NID1)/protein kinase B (AKT) signaling. Mouse models with patient-derived tumor organoids (HSPG2high and HSPG2low) were established to assess anticancer effects.

RESULTS

Our results demonstrated a marked upregulation of HSPG2 in malignant bladder tumors, which correlated significantly with poor patient prognosis. HSPG2 overexpression consistently enhanced bladder tumor cell proliferation and conferred chemotherapy resistance, as shown in both in vitro and in vivo experiments. Mechanistically, HSPG2 upregulated NID1 expression, leading to the activation of the AKT pro-survival signaling pathway and promoting sustained tumor growth in bladder cancer.

CONCLUSION

This study highlights the critical pro-tumor role of HSPG2/NID1/AKT signaling in bladder cancer and suggests its potential as a therapeutic target in clinical treatment.

Gene signature developed based on programmed cell death to predict the therapeutic response and prognosis for liver hepatocellular carcinoma

Background

The prognosis and therapeutic response of patients with liver hepatocellular carcinoma (LIHC) can be predicted based on programmed cell death (PCD) as PCD plays a crucial role during tumor progression. We developed a PCD-related gene signature to evaluate the therapeutic response and prognosis for patients with LIHC.

Methods

Molecular subtypes of LIHC were classified using ConsensusClusterPlus according to the gene biomarkers related to PCD. To predict the prognosis of high- and low-risk LIHC patients, a risk model was established by LASSO regression analysis based on the prognostic genes. Functional enrichment analysis was conducted using clusterProfiler package, and relative abundance of immune cells was quantified applying CIBERSORT package. Finally, to determine drug sensitivity, oncoPredict package was employed.

Results

PCD was correlated with the clinicopathologic features of LIHC. Then, we defined four molecular subtypes (C1-C4) of LIHC using PCD-related prognostic genes. Specifically, subtype C1 had the worst prognosis with enriched T cells regulatory (Tregs) and Macrophage_M0 and higher expression of T cell exhaustion markers, meanwhile, C1 also had a relatively higher TIDE score and metastasis potential. A risk model was established using 5 prognostic genes. High-risk patients tended to have higher expression of T cell exhaustion markers and TIDE score and unfavorable outcomes, and they were more sensitive to small molecule drug 5.Fluorouracil.

Conclusion

A PCD-related gene signature was developed and verified to be able to accurately predict the prognosis and drug sensitivity of LIHC patients.

Chromosomal localization of mutated genes in non-syndromic familial thyroid cancer

Familial non-medullary thyroid carcinoma (FNMTC) is a type of thyroid cancer characterized by genetic susceptibility, representing approximately 5% of all non-medullary thyroid carcinomas. While some cases of FNMTC are associated with familial multi-organ tumor predisposition syndromes, the majority occur independently. The genetic mechanisms underlying non-syndromic FNMTC remain unclear. Initial studies utilized SNP linkage analysis to identify susceptibility loci, including the 1q21 locus, 2q21 locus, and 4q32 locus, among others. Subsequent research employed more advanced techniques such as Genome-wide Association Study and Whole Exome Sequencing, leading to the discovery of genes such as IMMP2L, GALNTL4, WDR11-AS1, DUOX2, NOP53, MAP2K5, and others. But FNMTC exhibits strong genetic heterogeneity, with each family having its own pathogenic genes. This is the first article to provide a chromosomal landscape map of susceptibility genes associated with non-syndromic FNMTC and analyze their potential associations. It also presents a detailed summary of variant loci, characteristics, research methodologies, and validation results from different countries.

CHEK2 germline variants identified in familial nonmedullary thyroid cancer lead to impaired protein structure and function

Approximately 5 to 15% of nonmedullary thyroid cancers (NMTC) present in a familial form (familial nonmedullary thyroid cancers [FNMTC]). The genetic basis of FNMTC remains largely unknown, representing a limitation for diagnostic and clinical management. Recently, germline mutations in DNA repair-related genes have been described in cases with thyroid cancer (TC), suggesting a role in FNMTC etiology. Here, two FNMTC families were studied, each with two members affected with TC. Ninety-four hereditary cancer predisposition genes were analyzed through next-generation sequencing, revealing two germline CHEK2 missense variants (c.962A > C, p.E321A and c.470T > C, p.I157T), which segregated with TC in each FNMTC family. p.E321A, located in the CHK2 protein kinase domain, is a rare variant, previously unreported in the literature. Conversely, p.I157T, located in CHK2 forkhead-associated domain, has been extensively described, having conflicting interpretations of pathogenicity. CHK2 proteins (WT and variants) were characterized using biophysical methods, molecular dynamics simulations, and immunohistochemistry. Overall, biophysical characterization of these CHK2 variants showed that they have compromised structural and conformational stability and impaired kinase activity, compared to the WT protein. CHK2 appears to aggregate into amyloid-like fibrils in vitro, which opens future perspectives toward positioning CHK2 in cancer pathophysiology. CHK2 variants exhibited higher propensity for this conformational change, also displaying higher expression in thyroid tumors. The present findings support the utility of complementary biophysical and in silico approaches toward understanding the impact of genetic variants in protein structure and function, improving the current knowledge on CHEK2 variants' role in FNMTC genetic basis, with prospective clinical translation.