CDKN1C as a prognostic biomarker correlated with immune infiltrates and therapeutic responses in breast cancer patients

Identification of potential biomarkers for aging diagnosis of mesenchymal stem cells derived from the aged donors

BACKGROUND

The clinical application of human bone-marrow derived mesenchymal stem cells (MSCs) for the treatment of refractory diseases has achieved remarkable results. However, there is a need for a systematic evaluation of the quality and safety of MSCs sourced from donors. In this study, we sought to assess one potential factor that might impact quality, namely the age of the donor.

METHODS

We downloaded two data sets from each of two Gene Expression Omnibus (GEO), GSE39035 and GSE97311 databases, namely samples form young (< 65 years of age) and old (> 65) donor groups. Through, bioinformatics analysis and experimental validation to these retrieved data, we found that MSCs derived from aged donors can lead to differential expression of gene profiles compared with those from young donors, and potentially affect the function of MSCs, and may even induce malignant tumors.

RESULTS

We identified a total of 337 differentially expressed genes (DEGs), including two upregulated and eight downregulated genes from the databases of both GSE39035 and GSE97311. We further identified 13 hub genes. Six of them, TBX15, IGF1, GATA2, PITX2, SNAI1 and VCAN, were highly expressed in many human malignancies in Human Protein Atlas database. In the MSCs in vitro senescent cell model, qPCR analysis validated that all six hub genes were highly expressed in senescent MSCs. Our findings confirm that aged donors of MSCs have a significant effect on gene expression profiles. The MSCs from old donors have the potential to cause a variety of malignancies. These TBX15, IGF1, GATA2, PITX2, SNAI1, VCAN genes could be used as potential biomarkers to diagnosis aging state of donor MSCs, and evaluate whether MSCs derived from an aged donor could be used for therapy in the clinic. Our findings provide a diagnostic basis for the clinical use of MSCs to treat a variety of diseases.

CONCLUSIONS

Therefore, our findings not only provide guidance for the safe and standardized use of MSCs in the clinic for the treatment of various diseases, but also provide insights into the use of cell regeneration approaches to reverse aging and support rejuvenation.

Lappaol F regulates the cell cycle by activating CDKN1C/p57 in human colorectal cancer cells

CONTEXT

Lappaol F (LAF), a natural lignan from Arctium lappa Linné (Asteraceae), inhibits tumor cell growth in vitro and in vivo. The underlying mechanism involves the suppression of the Yes-associated protein. However, the specific role of LAF in cell cycle regulation remains unknown.

OBJECTIVE

This study determined the molecular mechanism by which LAF regulates cell cycle progression.

MATERIALS AND METHODS

Various colon cancer cell lines (SW480, HCT15, and HCT116) were treated with LAF (25, 50, and 75 μmol/L) for 48 h. The effects of LAF on cell proliferation and cell cycle were determined using sulforhodamine B and flow cytometry assays. Differentially expressed proteins (DEPs) were identified using quantitative proteomics. Bioinformatic analysis of DEPs was conducted via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Expression levels of DEPs in the cell cycle pathway were analyzed using RT-qPCR and western blotting.

RESULTS

LAF suppressed the proliferation of SW480, HCT15, and HCT116 cells (IC₅₀ 47.1, 51.4, and 32.8 μmol/L, respectively) and induced cell cycle arrest at the S phase. A total of 6331 proteins were identified and quantified, of which 127 were differentially expressed between the LAF-treated and untreated groups. GO and KEGG enrichment analyses revealed that DEPs mainly participated in the cell cycle. CDKN1C/p57 showed the most significant differential expression, with the highest fold-change (3.155-fold). Knockdown of CDKN1C/p57 attenuated the S phase cell cycle arrest and proliferation inhibition induced by LAF.

CONCLUSION

LAF exerts antitumor effects via S phase arrest by activating CDKN1C/p57 in colorectal cancer cells.

Multigene testing panels reveal pathogenic variants in sporadic breast cancer patients in northern China

Background: Breast cancer, the most prevalent malignancy in women worldwide, presents diverse onset patterns and genetic backgrounds. This study aims to examine the genetic landscape and clinical implications of rare mutations in Chinese breast cancer patients. Methods: Clinical data from 253 patients, including sporadic and familial cases, were analyzed. Comprehensive genomic profiling was performed, categorizing identified rare variants according to the American College of Medical Genetics (ACMG) guidelines. In silico protein modeling was used to analyze potentially pathogenic variants' impact on protein structure and function. Results: We detected 421 rare variants across patients. The most frequently mutated genes were ALK (22.2%), BARD1 (15.6%), and BRCA2 (15.0%). ACMG classification identified 7% of patients harboring Pathogenic/Likely Pathogenic (P/LP) variants, with one case displaying a pathogenic BRCA1 mutation linked to triple-negative breast cancer (TNBC). Also identified were two pathogenic MUTYH variants, previously associated with colon cancer but increasingly implicated in breast cancer. Variants of uncertain significance (VUS) were identified in 112 patients, with PTEN c.C804A showing the highest frequency. The role of these variants in sporadic breast cancer oncogenesis was suggested. In-depth exploration of previously unreported variants led to the identification of three potential pathogenic variants: ATM c.C8573T, MSH3 c.A2723T, and CDKN1C c.C221T. Their predicted impact on protein structure and stability suggests a functional role in cancer development. Conclusion: This study reveals a comprehensive overview of the genetic variants landscape in Chinese breast cancer patients, highlighting the prevalence and potential implications of rare variants. We emphasize the value of comprehensive genomic profiling in breast cancer management and the necessity of continuous research into understanding the functional impacts of these variants.

N76-1, a novel CDK7 inhibitor, exhibits potent anti-cancer effects in triple negative breast cancer

Emerging evidence suggests that genetically highly specific triple-negative breast cancer (TNBC) possesses a relatively uniform transcriptional program that is abnormally dependent on cyclin-dependent kinase 7 (CDK7). In this study, we obtained an inhibitor of CDK7, N76-1, by attaching the side chain of the covalent CDK7 inhibitor THZ1 to the core of the anaplastic lymphoma kinase inhibitor ceritinib. This study aimed to elucidate the role and underlying mechanism of N76-1 in TNBC and evaluate its potential value as an anti-TNBC drug. The results of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and colony formation assays showed that N76-1 inhibited the viability of TNBC cells. Kinase activity and cellular thermal shift assays showed that N76-1 directly targeted CDK7. Flow cytometry results revealed that N76-1 induced apoptosis and cell cycle arrest in the G2/M phase. N76-1 also effectively inhibited the migration of TNBC cells by high-content detection. The RNA-seq analysis showed that the transcription of genes, especially those related to transcriptional regulation and cell cycle, was suppressed after N76-1 treatment. Moreover, N76-1 markedly inhibited the growth of TNBC xenografts and phosphorylation of RNAPII in tumor tissues. In summary, N76-1 exerts potent anticancer effects in TNBC by inhibiting CDK7 and provides a new strategy and research basis for the development of new drugs for TNBC.

Identification and validation of core genes for type 2 diabetes mellitus by integrated analysis of single-cell and bulk RNA-sequencing

BACKGROUND

The exact mechanisms of type 2 diabetes mellitus (T2DM) remain largely unknown. We intended to authenticate critical genes linked to T2DM progression by tandem single-cell sequencing and general transcriptome sequencing data.

METHODS

T2DM single-cell RNA-sequencing data were submitted by the Gene Expression Omnibus (GEO) database and ArrayExpress (EBI), from which gene expression matrices were retrieved. The common cell clusters and representative marker genes were ascertained by principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), CellMarker, and FindMarkers in two datasets (GSE86469 and GSE81608). T2DM-related differentially expressed marker genes were defined by intersection analysis of marker genes and GSE86468-differentially expressed genes. Receiver operating characteristic (ROC) curves were utilized to assign representative marker genes with diagnostic values by GSE86468, GSE29226 and external validation GSE29221, and their prospective target compounds were forecasted by PubChem. Besides, the R package clusterProfiler-based functional annotation was designed to unveil the intrinsic mechanisms of the target genes. At last, western blot was used to validate the alternation of CDKN1C and DLK1 expression in primary pancreatic islet cells cultured with or without 30mM glucose.

RESULTS

Three common cell clusters were authenticated in two independent T2DM single-cell sequencing data, covering neurons, epithelial cells, and smooth muscle cells. Functional ensemble analysis disclosed an intimate association of these cell clusters with peptide/insulin secretion and pancreatic development. Pseudo-temporal trajectory analysis indicated that almost all epithelial and smooth muscle cells were of neuron origin. We characterized CDKN1C and DLK1, which were notably upregulated in T2DM samples, with satisfactory availability in recognizing three representative marker genes in non-diabetic and T2DM samples, and they were also robustly interlinked with the clinical characteristics of patients. Western blot also demonstrated that, compared with control group, the expression of CDKN1C and DLK1 were increased in primary pancreatic islet cells cultured with 30 mM glucose for 48 h. Additionally, PubChem projected 11 and 21 potential compounds for CDKN1C and DLK1, respectively.

CONCLUSION

It is desirable that the emergence of the 2 critical genes indicated (CDKN1C and DLK1) could be catalysts for the investigation of the mechanisms of T2DM progression and the exploitation of innovative therapies.

Concomitant PIK3CA and TP53 Mutations in Breast Cancer: An Analysis of Clinicopathologic and Mutational Features, Neoadjuvant Therapeutic Response, and Prognosis

PURPOSE

PIK3CA and TP53 are the most prevalently mutated genes in breast cancer (BC). Previous studies have indicated an association between concomitant PIK3CA/TP53 mutations and shorter disease-free survival. As its clinical utility remains largely unknown, we aimed to analyze the prognostic and predictive roles of this co-mutation.

METHODS

We retrospectively analyzed patients who were diagnosed with BC at Guangdong Provincial People's Hospital (GDPH) who underwent next-generation sequencing. The correlation of concomitant PIK3CA/TP53 mutations with clinicopathological and mutational characteristics, and neoadjuvant systemic therapy (NST) responses was analyzed. The Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset was used to verify associations between concurrent mutations and survival outcomes.

RESULTS

In the GDPH cohort, concomitant PIK3CA/TP53 mutations were associated with more aggressive phenotypes, including human epidermal growth factor receptor 2 positive status, hormone receptor negative status, high Ki-67 expression, high histological grade, advanced TNM stage, and additional genetic alterations. Co-mutations also portended a worse response to NST, especially taxane-containing regimens, when compared with the TP53 mutant alone (odds ratio, 3.767; 95% confidence interval, 1.205-13.087; p = 0.028). A significant association was observed between concomitant PIK3CA/TP53 mutations and poor survival outcomes in the METABRIC cohort.

CONCLUSION

Concomitant PIK3CA/TP53 mutations not only suggested unfavorable features and poor prognosis in BC but also conferred less benefit to NST than TP53 mutations alone.

The Mechanism of DNA Methylation and miRNA in Breast Cancer

Breast cancer is the most prevalent cancer in the world. Currently, the main treatments for breast cancer are radiotherapy, chemotherapy, targeted therapy and surgery. The treatment measures for breast cancer depend on the molecular subtype. Thus, the exploration of the underlying molecular mechanisms and therapeutic targets for breast cancer remains a hotspot in research. In breast cancer, a high level of expression of DNMTs is highly correlated with poor prognosis, that is, the abnormal methylation of tumor suppressor genes usually promotes tumorigenesis and progression. MiRNAs, as non-coding RNAs, have been identified to play key roles in breast cancer. The aberrant methylation of miRNAs could lead to drug resistance during the aforementioned treatment. Therefore, the regulation of miRNA methylation might serve as a therapeutic target in breast cancer. In this paper, we reviewed studies on the regulatory mechanisms of miRNA and DNA methylation in breast cancer from the last decade, focusing on the promoter region of tumor suppressor miRNAs methylated by DNMTs and the highly expressed oncogenic miRNAs inhibited by DNMTs or activating TETs.

Clinical Outcome-Related Cancer Pathways and Mutational Signatures in Patients With Unresectable Esophageal Squamous Cell Carcinoma Treated With Chemoradiotherapy

PURPOSE

Definitive chemoradiotherapy (dCRT) is a standard-of-care for locally advanced unresectable esophageal squamous cell carcinoma (ESCC). However, even in individuals treated with the same dCRT regimen, differences in the local control rate and radiation-induced thoracic toxicity exist (radiation-induced esophagitis [RIE]).

METHODS AND MATERIALS

Here, we describe a comprehensive genomic evaluation of pretreatment tumor tissue samples from 183 patients with ESCC using targeted sequencing of 474 cancer-related genes. The association between endpoints (progression-free survival [PFS], overall survival, locoregional relapse-free survival, distant metastasis-free survival), toxicity (RIE) and genomic features, including altered pathways and the mutational signature, was analyzed. An independent cohort of 84 stage II-III patients with ESCC was used for validation.

RESULTS

Gene alterations in the cell cycle pathway were identified in 87% of cases. Other frequently altered pathways included PI3K-AKT (45.9%), NOTCH (38.3%), NRF2 (36.6%), RKT-RAS (28.4%), and homologous recombination repair (HRR; 20.2%). HRR pathway alterations correlated with shortened PFS (mutation vs wild-type: 9.00 vs 14.40 months, hazard ratio, 2.10; 95% confidence interval, 1.29-3.44), while altered RTK-RAS pathways were correlated with worse overall survival in patients with ESCC treated with chemoradiotherapy (mutation vs wild-type: 23.70 vs 33.50 months; hazard ratio, 1.65; 95% confidence interval, 1.01-2.69). Furthermore, enrichment of apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures (signatures 2 and 13) was identified in ESCC tumors with altered HRR pathways. High APOBEC signatures and an altered HRR pathway were correlated with poor prognoses in dCRT-treated ESCC. Moreover, the APOBEC signature and/or the presence of HRR pathway alterations were associated with poor PFS and overall survival, which was validated in an independent whole exome sequence cohort. Notably, the altered HRR pathway was also associated with high-grade RIE toxicity in patients with ESCC.

CONCLUSIONS

Collectively, our results support the use of comprehensive genomic profiling to guide treatment and minimize RIE in patients with ESCC.

Development of a metabolism-related signature for predicting prognosis, immune infiltration and immunotherapy response in breast cancer

Breast cancer (BRCA) is the most commonly diagnosed cancer and among the top causes of cancer deaths globally. The abnormality of the metabolic process is an important characteristic that distinguishes cancer cells from normal cells. Currently, there are few metabolic molecular models to evaluate the prognosis and treatment response of BRCA patients. By analyzing RNA-seq data of BRCA samples from public databases via bioinformatic approaches, we developed a prognostic signature based on seven metabolic genes (PLA2G2D, GNPNAT1, QPRT, SHMT2, PAICS, NT5E and PLPP2). Low-risk patients showed better overall survival in all five cohorts (TCGA cohort, two external validation cohorts and two internal validation cohorts). There was a higher proportion of tumor-infiltrating CD8⁺ T cells, CD4⁺ memory resting T cells, gamma delta T cells and resting dendritic cells and a lower proportion of M0 and M2 macrophages in the low-risk group. Low-risk patients also showed higher ESTIMATE scores, higher immune function scores, higher Immunophenoscores (IPS) and checkpoint expression, lower stemness scores, lower TIDE (Tumor Immune Dysfunction and Exclusion) scores and IC50 values for several chemotherapeutic agents, suggesting that low-risk patients could respond more favorably to immunotherapy and chemotherapy. Two real-world patient cohorts receiving anti-PD-1 therapy were applied for validating the predictive results. Molecular subtypes identified based on these seven genes also showed different immune characteristics. Immunohistochemical data obtained from the human protein atlas database demonstrated the protein expression of signature genes. This research may contribute to the identification of metabolic targets for BRCA and the optimization of risk stratification and personalized treatment for BRCA patients.

Functional regulations between genetic alteration-driven genes and drug target genes acting as prognostic biomarkers in breast cancer

Differences in genetic molecular features including mutation, copy number alterations and DNA methylation, can explain interindividual variability in response to anti-cancer drugs in cancer patients. However, identifying genetic alteration-driven genes and characterizing their functional mechanisms in different cancer types are still major challenges for cancer studies. Here, we systematically identified functional regulations between genetic alteration-driven genes and drug target genes and their potential prognostic roles in breast cancer. We identified two mutation and copy number-driven gene pairs (PARP1-ACSL1 and PARP1-SRD5A3), three DNA methylation-driven gene pairs (PRLR-CDKN1C, PRLR-PODXL2 and PRLR-SRD5A3), six gene pairs between mutation-driven genes and drug target genes (SLC19A1-SLC47A2, SLC19A1-SRD5A3, AKR1C3-SLC19A1, ABCB1-SRD5A3, NR3C2-SRD5A3 and AKR1C3-SRD5A3), and four copy number-driven gene pairs (ADIPOR2-SRD5A3, CASP12-SRD5A3, SLC39A11-SRD5A3 and GALNT2-SRD5A3) that all served as prognostic biomarkers of breast cancer. In particular, RARP1 was found to be upregulated by simultaneous copy number amplification and gene mutation. Copy number deletion and downregulated expression of ACSL1 and upregulation of SRD5A3 both were observed in breast cancers. Moreover, copy number deletion of ACSL1 was associated with increased resistance to PARP inhibitors. PARP1-ACSL1 pair significantly correlated with poor overall survival in breast cancer owing to the suppression of the MAPK, mTOR and NF-kB signaling pathways, which induces apoptosis, autophagy and prevents inflammatory processes. Loss of SRD5A3 expression was also associated with increased sensitivity to PARP inhibitors. The PARP1-SRD5A3 pair significantly correlated with poor overall survival in breast cancer through regulating androgen receptors to induce cell proliferation. These results demonstrate that genetic alteration-driven gene pairs might serve as potential biomarkers for the prognosis of breast cancer and facilitate the identification of combination therapeutic targets for breast cancers.

CDKN1C as a prognostic biomarker correlated with immune infiltrates and therapeutic responses in breast cancer patients

Breast cancer (BC) prognosis and therapeutic sensitivity could not be predicted efficiently. Previous evidence have shown the vital roles of CDKN1C in BC. Therefore, we aimed to construct a CDKN1C‐based model to accurately predicting overall survival (OS) and treatment responses in BC patients. In this study, 995 BC patients from The Cancer Genome Atlas database were selected. Kaplan‐Meier curve, Gene set enrichment and immune infiltrates analyses were executed. We developed a novel CDKN1C‐based nomogram to predict the OS, verified by the time‐dependent receiver operating characteristic curve, calibration curve and decision curve. Therapeutic response prediction was followed based on the low‐ and high‐nomogram score groups. Our results indicated that low‐CDKN1C expression was associated with shorter OS and lower proportion of naïve B cells, CD8 T cells, activated NK cells. The predictive accuracy of the nomogram for 5‐year OS was superior to the tumour‐node‐metastasis stage (area under the curve: 0.746 vs. 0.634, p < 0.001). The nomogram exhibited excellent predictive performance, calibration ability and clinical utility. Moreover, low‐risk patients were identified with stronger sensitivity to therapeutic agents. This tool can improve BC prognosis and therapeutic responses prediction, thus guiding individualized treatment decisions.