High CHK2 protein expression is a strong and independent prognostic feature in ERG negative prostate cancer

Development and validation of a mitotic catastrophe-related genes prognostic model for breast cancer

Background

Breast cancer has become the most common malignant tumor in women worldwide. Mitotic catastrophe (MC) is a way of cell death that plays an important role in the development of tumors. However, the exact relationship between MC-related genes (MCRGs) and the development of breast cancer is still unclear, and further research is needed to elucidate this complexity.

Methods

Transcriptome data and clinical data of breast cancer were downloaded from the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. We identified differential expression of MCRGs by comparing tumor tissue with normal tissue. Subsequently, we used COX regression analysis and LASSO regression analysis to construct the prognosis risk model of MCRGs. Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used to evaluate the predictive ability of prognostic model. Moreover, the clinical relevance, gene set enrichment analysis (GSEA), immune landscape, tumor mutation burden (TMB), and immunotherapy and drug sensitivity analysis between high-risk and low-risk groups were systematically investigated. Finally, we validated the expression levels of genes involved in constructing the prognostic model through real-time quantitative polymerase chain reaction (RT-qPCR) at the cellular and tissue levels.

Results

We identified 12 prognostic associated MCRGs, four of which were selected to construct prognostic model. The Kaplan-Meier analysis suggested that patients in the high-risk group had a shorter overall survival (OS). The Cox regression analysis and ROC analysis indicated that risk model had independent and excellent ability in predicting prognosis of breast cancer patients. Mechanistically, a remarkable difference was observed in clinical relevance, GSEA, immune landscape, TMB, immunotherapy response, and drug sensitivity analysis. RT-qPCR results showed that genes involved in constructing the prognostic model showed significant abnormal expressions and the expression change trends were consistent with the bioinformatics results.

Conclusions

We established a prognosis risk model based on four MCRGs that had the ability to predict clinical prognosis and immune landscape, proposing potential therapeutic targets for breast cancer.

Immunohistochemical findings and clinicopathological features of breast cancers with pathogenic germline mutations in Non-BRCA genes

Deleterious germline mutations in multiple genes confer an increased breast cancer (BC) risk. Immunohistochemical (IHC) expression of protein products of mutated high-risk genes has not been investigated in BC. We hypothesized that pathogenic mutations may lead to an abnormal IHC expression pattern in the tumor cells. BCs with deleterious germline mutations in CHEK2, ATM, PALB2 & PTEN were identified. Immunohistochemistry was performed using Dako staining platform on formalin fixed paraffin embedded tumor tissue. Primary antibodies for PALB2 (ab202970), ATM [2C1(1A10)}, CHK2 (EPR4325), and PTEN (138G6) proteins were used for BCs with respective deleterious mutations. IHC expression was assessed in tumor and adjacent benign breast tissue. Total 27 BCs with 10 CHEK2, 9 ATM, 6 PALB2 & 2 PTEN deleterious germline mutations were identified. IHC staining was performed on 8 CHEK2, 7 ATM, 6 PALB2 & 2 PTEN cases. Abnormal CHEK2 IHC staining was identified in 7/8(88%) BCs. Three distinct CHK2 IHC patterns were noted: 1) Strong diffuse nuclear positivity (5 BC), 2) Null-pattern (2 BC), & 3) Normal breast-like staining in 1 BC Four of 5 (80%) strong CHK2 staining BC had missense CHEK2 mutations. Null-pattern was present with a missense & a frameshift mutation. Normal breast-like CHEK2 IHC staining pattern was present in 1 BC with CHEK2 frameshift mutation. Loss of nuclear/cytoplasmic PTEN IHC expression was noted in 2 in-situ carcinomas. Abnormal PTEN and CHK2 IHC were present in atypical ductal hyperplasia and flat epithelial atypia. ATM and PALB2 IHC expression patterns were similar in tumor cells and benign breast epithelium: mild to moderate intensity nuclear and cytoplasmic staining. We report abnormal CHEK2 IHC expression in 88% of BCs with pathogenic CHEK2 mutations. With PTEN and CHEK2 pathogenic mutations, abnormal IHC patterns are seen in early atypical proliferative lesions. IHC may be applied to identify CHEK2 & PTEN mutated BCs and precursor lesions.

Relationship between the Expression of CHK2 and p53 in Tumor Tissue and the Course of Papillary Thyroid Cancer in Patients with CHEK2 Germline Mutations

The aim of this study was to determine whether the expression of CHK2 and p53 in tumor tissue in carriers of germline CHEK2 mutations can serve as a prognostic marker for PTC, and whether CHEK2 and TP53 copy numbers correlates with the course of PTC disease. This study included 156 PTC patients previously tested for the presence of CHEK2. Clinicopathological features, treatment response, disease outcome, and germline mutation status of the CHEK2 gene were assessed with respect to CHK2 and p53 expression, and CHEK2 and TP53 gene copy statuses. In patients with and without a germline mutation in CHEK2 and with higher CHK2 expression, the chances of an excellent treatment response and no evidence of disease were lower than in patients without or with lower CHK2 expression. TP53 deletion was associated with angioinvasion. In patients with a truncating mutation, the chance of a CHEK2 deletion was higher than in patients with WT CHEK2 alone or those with WT CHEK2 and with the missense I157T mutation. Higher CHK2 expression was associated with poorer treatment responses and disease outcomes. Higher CHK2 expression and positive p53 together with a TP53 deletion could be a prognostic marker of unfavorable disease outcomes in patients with germline truncating mutations in CHEK2.

CHEK2 is a potential prognostic biomarker associated with immune infiltration in clear cell renal cell carcinoma

Checkpoint kinase 2 (CHEK2) plays a crucial role in responding to DNA damage and is linked to diverse cancer types. However, its significance in the prediction of prognosis and impacts on the immune status of clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to identify the role of CHEK2 in prognosis and immune microenvironment of ccRCC. We analyzed transcriptome and clinicopathological data from the cancer genome atlas (TCGA) database and conducted functional enrichment analysis to explore molecular mechanisms. The relationship between CHEK2 and immune infiltration was evaluated, and drug sensitivity analysis was performed using the CellMiner database. The results showed that CHEK2 was an independent predictor of ccRCC prognosis and was closely associated with immune-related processes. Additionally, high expression of CHEK2 was linked to resistance to certain targeted drugs. These findings suggest that CHEK2 could serve as a biomarker for ccRCC, providing insights into tumor immune microenvironment alterations and immunotherapeutic response. Further investigation is needed to fully understand the potential of CHEK2 as a prognostic predictor and therapeutic target for ccRCC.

Could Inhibiting the DNA Damage Repair Checkpoint Rescue Immune-Checkpoint-Inhibitor-Resistant Endometrial Cancer?

Endometrial cancer (EC) is increasingly undermining female health worldwide, with poor survival rates for advanced or recurrent/metastatic diseases. The application of immune checkpoint inhibitors (ICIs) has opened a window of opportunity for patients with first-line therapy failure. However, there is a subset of patients with endometrial cancer who remain insensitive to immunotherapy alone. Therefore, it is necessary to develop new therapeutic agents and further explore reliable combinational strategies to optimize the efficacy of immunotherapy. DNA damage repair (DDR) inhibitors as novel targeted drugs are able to generate genomic toxicity and induce cell death in solid tumors, including EC. Recently, growing evidence has demonstrated the DDR pathway modulates innate and adaptive immunity in tumors. In this review, we concentrate on the exploration of the intrinsic correlation between DDR pathways, especially the ATM-CHK2-P53 pathway and the ATR-CHK1-WEE1 pathway, and oncologic immune response, as well as the feasibility of adding DDR inhibitors to ICIs for the treatment of patients with advanced or recurrent/metastatic EC. We hope that this review will offer some beneficial references to the investigation of immunotherapy and provide a reasonable basis for "double-checkpoint inhibition" in EC.

Protein-based prognostic signature for predicting the survival and immunotherapeutic efficiency of endometrial carcinoma

Background

Endometrial cancer (EC) is the most frequent malignancy of the female genital tract worldwide. Our study aimed to construct an effective protein prognostic signature to predict prognosis and immunotherapy responsiveness in patients with endometrial carcinoma.

Methods

Protein expression data, RNA expression profile data and mutation data were obtained from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA). Prognosis-related proteins in EC patients were screened by univariate Cox regression analysis. Least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis were performed to establish the protein-based prognostic signature. The CIBERSORT algorithm was used to quantify the proportions of immune cells in a mixed cell population. The Immune Cell Abundance Identifier (ImmuCellAI) and The Cancer Immunome Atlas (TCIA) web tools were used to predict the response to immunochemotherapy. The pRRophetic algorithm was used to estimate the sensitivity of chemotherapeutic and targeted agents.

Results

We constructed a prognostic signature based on 9 prognostic proteins, which could divide patients into high-risk and low-risk groups with distinct prognoses. A novel prognostic nomogram was established based on the prognostic signature and clinicopathological parameters to predict 1, 3 and 5-year overall survival for EC patients. The results obtained with Clinical Proteomic Tumor Analysis Consortium (CPTAC), Human Protein Atlas (HPA) and immunohistochemical (IHC) staining data from EC samples in our hospital supported the predictive ability of these proteins in EC tumors. Next, the CIBERSORT algorithm was used to estimate the proportions of 22 immune cell types. The proportions of CD8 T cells, T follicular helper cells and regulatory T cells were higher in the low-risk group. Moreover, we found that the prognostic signature was positively associated with high tumor mutation burden (TMB) and high microsatellite instability (MSI-H) status in EC patients. Finally, ImmuCellAI and TCIA analyses showed that patients in the low-risk group were more inclined to respond to immunotherapy than patients in the high-risk group. In addition, drug sensitivity analysis indicated that our signature had potential predictive value for chemotherapeutics and targeted therapy.

Conclusion

Our study constructed a novel prognostic protein signature with robust predictive ability for survival and efficiency in predicting the response to immunotherapy, chemotherapy and targeted therapy. This protein signature represents a promising predictor of prognosis and response to cancer treatment in EC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09402-w.