TP53 alterations of hormone-naïve prostate cancer in the Chinese population

Network pharmacology, molecular docking, and in vitro study on Aspilia pluriseta against prostate cancer

BACKGROUND

Current prostate cancer treatments are associated with life-threatening side effects, prompting the search for effective and safer alternatives. Aspilia pluriseta Schweinf. ex Engl. has previously shown anticancer activity in lung and liver cancer cell lines. This study investigated its potential for prostate cancer.

METHODS

A crude extract of A. pluriseta root was prepared using dichloromethane/methanol (1:1 v/v) and partitioned into hexane, ethyl acetate, and water fractions. The MTT assay was used to assess the antiproliferative activity of the fractions. The active fractions were tested at 6.25-200 µg/ml on human prostate cancer DU-145 cells and non-cancerous Vero E6 cells. Qualitative phytochemical and gas chromatography-mass spectrometry (GC-MS) analyses were conducted to identify chemical compounds. Network pharmacology was employed to predict molecular targets and modes of action of the identified chemical compounds, with subsequent validation through molecular docking and real-time PCR.

RESULTS

Active extracts included crude dichloromethane/methanol, hexane, and ethyl acetate fractions, inhibiting DU-145 cell proliferation with IC50 values of 16.94, 20.06, and 24.14 µg/ml, respectively. Selectivity indices were determined to be 6.04 (crude), 3.62 (hexane), and 6.68 (ethyl acetate). Identified phytochemicals comprised phenols, terpenoids, flavonoids, tannins, sterols, and saponins. GC-MS analysis revealed seventy-nine (79) compounds, with seven (7) meeting ideal drug candidate parameters; their hub gene targets included MAPK3, MAPK1, IL6, TP53, ESR1, PTGS2, MMP9, MDM2, AR, and MAP2K1, implicating regulation of PI3K/Akt, MAPK, and p53 signaling pathways as potential modes of action. Core compounds such as 1-heneicosanol, lanosterol, andrographolide, and retinoic acid exhibited strong binding activities, particularly lanosterol with MAPK21 (-9.7 kcal/mol), ESR1 (-8.9 kcal/mol), and MAPK3 (-8.8 kcal/mol). Treatment with A. pluriseta downregulated AR expression and upregulated p53, while also downregulating CDK1 and BCL-2 and upregulating caspase-3.

CONCLUSIONS

A. pluriseta extracts inhibited DU-145 cell growth without causing cellular toxicity, suggesting great potential for development as an anti-prostate cancer agent. However, further in vitro and in vivo experiments are recommended.

Association of Pathological Features and Multiparametric MRI-Based Radiomics With TP53-Mutated Prostate Cancer

BACKGROUND

TP53 mutations are associated with prostate cancer (PCa) prognosis and therapy.

PURPOSE

To develop TP53 mutation classification models for PCa using MRI radiomics and clinicopathological features.

STUDY TYPE

Retrospective.

POPULATION

388 patients with PCa from two centers (Center 1: 281 patients; Center 2: 107 patients). Cases from Center 1 were randomly divided into training and internal validation sets (7:3). Cases from Center 2 were used for external validation.

FIELD STRENGTH/SEQUENCE

3.0T/T2-weighted imaging, dynamic contrast-enhanced imaging, diffusion-weighted imaging.

ASSESSMENT

Each patient's index tumor lesion was manually delineated on the above MRI images. Five clinicopathological and 428 radiomics features were obtained from each lesion. Radiomics features were selected by least absolute shrinkage and selection operator and binary logistic regression (LR) analysis, while clinicopathological features were selected using Mann-Whitney U test. Radiomics models were constructed using LR, support vector machine (SVM), and random forest (RF) classifiers. Clinicopathological-radiomics combined models were constructed using the selected radiomics and clinicopathological features with the aforementioned classifiers.

STATISTICAL TESTS

Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC). P value <0.05 indicates statistically significant.

RESULTS

In the internal validation set, the radiomics model had an AUC of 0.74 with the RF classifier, which was significantly higher than LR (AUC = 0.61), but similar to SVM (AUC = 0.69; P = 0.422). For the combined model, the AUC of RF model was 0.84, which was significantly higher than LR (0.64), but similar to SVM (0.80; P = 0.548). Both the combined RF and combined SVM models showed significantly higher AUCs than the radiomics models. In the external validation set, the combined RF and combined SVM models showed AUCs of 0.83 and 0.82.

DATA CONCLUSION

Pathological-radiomics combined models with RF, SVM show the association of TP53 mutations and pathological-radiomics features of PCa.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

The modification role and tumor association with a methyltransferase: KMT2C

Histone methylation can affect chromosome structure and binding to other proteins, depending on the type of amino acid being modified and the number of methyl groups added, this modification may promote transcription of genes (H3K4me2, H3K4me3, and H3K79me3) or reduce transcription of genes (H3K9me2, H3K9me3, H3K27me2, H3K27me3, and H4K20me3). In addition, advances in tumor immunotherapy have shown that histone methylation as a type of protein post-translational modification is also involved in the proliferation, activation and metabolic reprogramming of immune cells in the tumor microenvironment. These post-translational modifications of proteins play a crucial role in regulating immune escape from tumors and immunotherapy. Lysine methyltransferases are important components of the post-translational histone methylation modification pathway. Lysine methyltransferase 2C (KMT2C), also known as MLL3, is a member of the lysine methyltransferase family, which mediates the methylation modification of histone 3 lysine 4 (H3K4), participates in the methylation of many histone proteins, and regulates a number of signaling pathways such as EMT, p53, Myc, DNA damage repair and other pathways. Studies of KMT2C have found that it is aberrantly expressed in many diseases, mainly tumors and hematological disorders. It can also inhibit the onset and progression of these diseases. Therefore, KMT2C may serve as a promising target for tumor immunotherapy for certain diseases. Here, we provide an overview of the structure of KMT2C, disease mechanisms, and diseases associated with KMT2C, and discuss related challenges.

Network pharmacology and experimental validation to explore the role and potential mechanism of Liuwei Dihuang Decoction in prostate cancer

OBJECTIVE

To evaluate the anti-tumor effector of Liuwei Dihuang Decoction (LWDHD) in prostate cancer (PCa) and explore the potential mechanism using experimental validation, network pharmacology, bioinformatics analysis, and molecular docking.

METHODS

CCK test, Clone formation assay and wound-healing assays were used to determine the effect of LWDHD on prostate cancer growth and metastasis. The active ingredients and targets of LWDHD were obtained from the TCMSP database, and the relevant targets were selected by GeneCards, OMIM and DisGeNET databases for PCa. The cross-targets of drugs and disease were imported into the STRING database to construct protein interactions. The network was also visualized using Cytoscape software and core targets are screened using the Network Analyzer plug-in. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed using R software. TCGA database was used to analyze the correlation of bioinformatics genes. AutoDock vina was used to predict the molecular docking and binding ability of active ingredients to key targets. Through WB and q-PCR experiments, the above gene targets were detected to verify the effect of LWDHD on PCa.

RESULTS

CCK and scratch tests confirmed that LWDHD could inhibit the proliferation, invasion and migration of prostate cancer cells. Clone formation experiments showed that LWDHD inhibited the long-term proliferative capacity of PC3 cells. LWDHD and PCa had a total of 99 common targets, establishing a "drug-ingredient-common target" network. Through GO and KEGG enrichment analysis, PI3K/AKT, MAPK, TP53 pathway, MYC, TNF pathway and other signaling pathways were found. Bioinformatics analysis showed that MYC gene was highly expressed and CCND1 and MAPK1 were low expressed in prostate cancer tissues. In addition, TP53, AKT1, MYC, TNF and CCND1 were positively correlated with MAPK1, among which AKT1 and CCND1 were most closely correlated with MAPK1. Molecular docking results showed that quercetin, kaempferol, β-sitosterol and other main active ingredients of LWDHD treatment for PCa were combined with core proteins MAPK1 and AKT1 well. WB and q-PCR results showed that LWDHD inhibited the expression of PI3K and AKT in PC3 cells.

CONCLUSION

The mechanism of LWDHD therapy for PCa is a multi-target and multi-pathway complex process, which may be related to the biological processes mediated by MAPK1 and AKT1 pathways, such as cell proliferation and inhibition of metastasis, and the regulation of signaling pathways. The PI3K/AKT signaling pathway may be a central pathway of LWDHD to inhibit prostate cancer proliferation.

Molecular landscape for risk prediction and personalized therapeutics of castration-resistant prostate cancer: at a glance

Prostate cancer (PCa) is commonly occurred with high incidence in men worldwide, and many patients will be eventually suffered from the dilemma of castration-resistance with the time of disease progression. Castration-resistant PCa (CRPC) is an advanced subtype of PCa with heterogeneous carcinogenesis, resulting in poor prognosis and difficulties in therapy. Currently, disorders in androgen receptor (AR)-related signaling are widely acknowledged as the leading cause of CRPC development, and some non-AR-based strategies are also proposed for CRPC clinical analyses. The initiation of CRPC is a consequence of abnormal interaction and regulation among molecules and pathways at multi-biological levels. In this study, CRPC-associated genes, RNAs, proteins, and metabolites were manually collected and integrated by a comprehensive literature review, and they were functionally classified and compared based on the role during CRPC evolution, i.e., drivers, suppressors, and biomarkers, etc. Finally, translational perspectives for data-driven and artificial intelligence-powered CRPC systems biology analysis were discussed to highlight the significance of novel molecule-based approaches for CRPC precision medicine and holistic healthcare.

Comprehensive single-cell analysis reveals heterogeneity of fibroblast subpopulations in ovarian cancer tissue microenvironment

Background

Ovarian cancer, as a highly malignant tumor, features the critical involvement of tumor-associated fibroblasts in the ovarian cancer tissue microenvironment. However, due to the apparent heterogeneity within fibroblast subpopulations, the specific functions of these subpopulations in the ovarian cancer tissue microenvironment remain insufficiently elucidated.

Methods

In this study, we integrated single-cell sequencing data from 32 ovarian cancer samples derived from four distinct cohorts and 3226 bulk RNA-seq data from GEO and TCGA-OV cohorts. Utilizing computational frameworks such as Seurat, Monocle 2, Cellchat, and others, we analyzed the characteristics of the ovarian cancer tissue microenvironment, focusing particularly on fibroblast subpopulations and their differentiation trajectories. Employing the CIBERSORTX computational framework, we assessed various cellular components within the ovarian cancer tissue microenvironment and evaluated their associations with ovarian cancer prognosis. Additionally, we conducted Mendelian randomization analysis based on cis-eQTL to investigate causal relationships between gene expression and ovarian cancer.

Results

Through integrative analysis, we identified 13 major cell types present in ovarian cancer tissues, including CD8+ T cells, malignant cells, and fibroblasts. Analysis of the tumor microenvironment (TME) cell proportions revealed a significant increase in the proportion of CD8+ T cells and CD4+ T cells in tumor tissues compared to normal tissues, while fibroblasts predominated in normal tissues. Further subgroup analysis of fibroblasts identified seven subgroups, with the MMP11+Fib subgroup showing the highest activity in the TGFβ signaling pathway. Single-cell analysis suggested that oxidative phosphorylation could be a key pathway driving fibroblast differentiation, and the ATRNL1+KCN + Fib subgroup exhibited chromosomal copy number variations. Prognostic analysis using a large sample size indicated that high infiltration of MMP11+ fibroblasts was associated with poor prognosis in ovarian cancer. SMR analysis identified 132 fibroblast differentiation-related genes, which were linked to pathways such as platinum drug resistance.

Conclusions

In the context of ovarian cancer, fibroblasts expressing MMP11 emerge as the primary drivers of the TGF-beta signaling pathway. Their presence correlates with an increased risk of adverse ovarian prognoses. Additionally, the genetic regulation governing the differentiation of fibroblasts associated with ovarian cancer correlates with the emergence of drug resistance.

Molecular biomarkers in prostate cancer tumorigenesis and clinical relevance

Prostate cancer (PCa) is the second most frequent type of cancer in men and assessing circulating tumor cells (CTCs) by liquid biopsy is a promising tool to help in cancer early detection, staging, risk of recurrence evaluation, treatment prediction and monitoring. Blood-based liquid biopsy approaches enable the enrichment, detection and characterization of CTCs by biomarker analysis. Hence, comprehending the molecular markers, their role on each stage of cancer development and progression is essential to provide information that can help in future implementation of these biomarkers in clinical assistance. In this review, we studied the molecular markers most associated with PCa CTCs to better understand their function on tumorigenesis and metastatic cascade, the methodologies utilized to analyze these biomarkers and their clinical significance, in order to summarize the available information to guide researchers in their investigations, new hypothesis formulation and target choice for the development of new diagnostic and treatment tools.

β-catenin inhibitors in cancer therapeutics: intricacies and way forward

β-catenin is an evolutionary conserved, quintessential, multifaceted protein that plays vital roles in cellular homeostasis, embryonic development, organogenesis, stem cell maintenance, cell proliferation, migration, differentiation, apoptosis, and pathogenesis of various human diseases including cancer. β-catenin manifests both signaling and adhesive features. It acts as a pivotal player in intracellular signaling as a component of versatile WNT signaling cascade involved in embryonic development, homeostasis as well as in carcinogenesis. It is also involved in Ca2+ dependent cell adhesion via interaction with E-cadherin at the adherens junctions. Aberrant β-catenin expression and its nuclear accumulation promote the transcription of various oncogenes including c-Myc and cyclinD1, thereby contributing to tumor initiation, development, and progression. β-catenin's expression is closely regulated at various levels including its stability, sub-cellular localization, as well as transcriptional activity. Understanding the molecular mechanisms of regulation of β-catenin and its atypical expression will provide researchers not only the novel insights into the pathogenesis and progression of cancer but also will help in deciphering new therapeutic avenues. In the present review, we have summarized the dual functions of β-catenin, its role in signaling, associated mutations as well as its role in carcinogenesis and tumor progression of various cancers. Additionally, we have discussed the challenges associated with targeting β-catenin molecule with the presently available drugs and suggested the possible way forward in designing new therapeutic alternatives against this oncogene.

TP53 gene implications in prostate cancer evolution: potential role in tumor classification

Background and aims

Prostate adenocarcinoma (PRAD) is a complex disease that can be driven by alterations in both coding and noncoding genes. Recent research has identified coding and non-coding genes that are considered to play important roles in prostate cancer evolution and which may be used as biomarkers for disease diagnosis, prognosis, and treatment. TP53 is a critical hub gene in prostate cancer. Advanced studies have demonstrated the crosstalk between coding and non-coding RNAs, particularly microRNAs (miRNAs).

Methods

In this study, we investigated the roundabout of TP53 and their regulatory miRNAs (miR-15a-5p, miR-34a-5p, and miR-141-3p) based on the TCGA data set. We validated an additional patient cohort of 28 matched samples of patients with PRAD at tissue and plasma level.

Results

Therefore, using the UALCAN online database, we evaluated the expression level in PRAD of these genes revealing overexpression of TP53. qRT-PCR validation step endorsed the expression level for these genes. Additionally, we evaluated the expression level of the four key miRNAs (miR-15a-5p, miR-34a-5p, and miR-141-3p) interconnected as a network at tissue and plasma levels.

Conclusions

Through these results, we demonstrated the essential function of TP53 and its associated miRNAs that play a significant role in tumor control, highlighting miRNAs' potential as future therapeutic targets and biomarkers with important implications in managing prostate cancer.

Novel signatures of prostate cancer progression and therapeutic resistance

INTRODUCTION

The extensive heterogeneity of prostate cancer (PCa) and multilayered complexity of progression to castration-resistant prostate cancer (CRPC) have contributed to the challenges of accurately monitoring advanced disease. Profiling of the tumor microenvironment with large-scale transcriptomic studies have identified gene signatures that predict biochemical recurrence, lymph node invasion, metastases, and development of therapeutic resistance through critical determinants driving CRPC.

AREAS COVERED

This review encompasses understanding of the role of different molecular determinants of PCa progression to lethal disease including the phenotypic dynamic of cell plasticity, EMT-MET interconversion, and signaling-pathways driving PCa cells to advance and metastasize. The value of liquid biopsies encompassing circulating tumor cells and extracellular vesicles to detect disease progression and emergence of therapeutic resistance in patients progressing to lethal disease is discussed. Relevant literature was added from PubMed portal.

EXPERT OPINION

Despite progress in the tumor-targeted therapeutics and biomarker discovery, distant metastasis and therapeutic resistance remain the major cause of mortality in patients with advanced CRPC. No single signature can encompass the tremendous phenotypic and genomic heterogeneity of PCa, but rather multi-threaded omics-derived and phenotypic markers tailored and validated into a multimodal signature.

Serrate RNA Effector Molecule (SRRT) Is Associated with Prostate Cancer Progression and Is a Predictor of Poor Prognosis in Lethal Prostate Cancer

Arsenite-resistance protein 2, also known as serrate RNA effector molecule (ARS2/SRRT), is known to be involved in cellular proliferation and tumorigenicity. However, its role in prostate cancer (PCa) has not yet been established. We investigated the potential role of SRRT in 496 prostate samples including benign, incidental, advanced, and castrate-resistant patients treated by androgen deprivation therapy (ADT). We also explored the association of SRRT with common genetic aberrations in lethal PCa using immunohistochemistry (IHC) and performed a detailed analysis of SRRT expression using The Cancer Genome Atlas (TCGA PRAD) by utilizing RNA-seq, clinical information (pathological T category and pathological Gleason score). Our findings indicated that high SRRT expression was significantly associated with poor overall survival (OS) and cause-specific survival (CSS). SRRT expression was also significantly associated with common genomic aberrations in lethal PCa such as PTEN loss, ERG gain, mutant TP53, or ATM. Furthermore, TCGA PRAD data revealed that high SRRT mRNA expression was significantly associated with higher Gleason scores, PSA levels, and T pathological categories. Gene set enrichment analysis (GSEA) of RNAseq data from the TCGA PRAD cohort indicated that SRRT may play a potential role in regulating the expression of genes involved in prostate cancer aggressiveness. Conclusion: The current data identify the SRRT's potential role as a prognostic for lethal PCa, and further research is required to investigate its potential as a therapeutic target.

Integrated analysis of single-cell and bulk RNA sequencing identifies a signature based on macrophage marker genes involved in prostate cancer prognosis and treatment responsiveness

In the tumor microenvironment, tumor-associated macrophages (TAMs) interact with cancer cells and contribute to the progression of solid tumors. Nonetheless, the clinical significance of TAM-related biomarkers in prostate cancer (PCa) is largely unexplored. The present study aimed to construct a macrophage-related signature (MRS) for predicting PCa patient prognosis based on macrophage marker genes. Six cohorts comprising 1056 PCa patients with RNA-Seq and follow-up data were enrolled. Based on macrophage marker genes identified by single-cell RNA-sequencing (scRNA-seq) analysis, univariate analysis, least absolute shrinkage and selection operator (Lasso)-Cox regression, and machine learning procedures were performed to derive a consensus MRS. Receiver operating characteristic curve (ROC), concordance index, and decision curve analyses were used to confirm the predictive capacity of the MRS. The predictive performance of the MRS for recurrence-free survival (RFS) was stable and robust, and the MRS outperformed traditional clinical variables. Furthermore, high-MRS-score patients presented abundant macrophage infiltration and high-expression levels of immune checkpoints (CTLA4, HAVCR2, and CD86). The frequency of mutations was relatively high in the high-MRS-score subgroup. However, the low-MRS-score patients had a better response to immune checkpoint blockade (ICB) and leuprolide-based adjuvant chemotherapy. Notably, abnormal ATF3 expression may be associated with docetaxel and cabazitaxel resistance in PCa cells, T stage, and the Gleason score. In this study, a novel MRS was first developed and validated to accurately predict patient survival outcomes, evaluate immune characteristics, infer therapeutic benefits, and provide an auxiliary tool for personalized therapy.

MAPK8IP2 is a potential prognostic biomarker and promote tumor progression in prostate cancer

Background

MAPK8IP2 is one of the JNK-interacting proteins (JIPs) family members, and is involved in the regulation of the JNK and P38 MAPK signaling pathways. MAPK8IP2 has been reported to be closely associated with several cancers. However, the biological function of MAPK8IP2 in prostate cancer (PCa) remains unclear.

Methods

MAPK8IP2 expression in PCa and subgroups of PCa was analyzed by public databases. The prognostic role of MAPK8IP2 in prostate cancer was analyzed using the Cox regression method. The potential mechanism by which MAPK8IP2 affects PCa progression was investigated by utilizing public data, including genetic alteration, DNA methylation, m6A methylation, and immune infiltration data. We further performed in vitro assays to validate the effect of MAPK8IP2 on PCa cell proliferation, migration and invasion.

Results

MAPK8IP2 is highly expressed in PCa tissues. Overexpression of MAPK8IP2 is associated with adverse clinicopathological factors and a poor prognosis in PCa. Receiver operating curve analysis showed that MAPK8IP2 can distinguish PCa tissues from non-PCa tissues with a certain accuracy (AUC = 0.814). The MAPK8IP2 genetic alteration rate was 2.6% and MAPK8IP2 alterations correlated with a poor prognosis. We also found that CDK12 and TP53 mutations were associated with MAPK8IP2 expression. The DNA methylation level of MAPK8IP2 was higher in primary tumors than in normal tissues, and the high MAPK8IP2 DNA methylation group of PCa patients had poor survival. Enrichment analysis indicated that MAPK8IP2 was involved in the MAPK signaling pathway. In vitro, knockdown of MAPK8IP2 inhibited PCa cell proliferation, migration and invasion.

Conclusion

MAPK8IP2 is a potential target for PCa treatment and can serve as a novel biomarker for PCa diagnosis and prognosis evaluation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10259-2.

The Association between Cyclin Dependent Kinase 2 Associated Protein 1 (CDK2AP1) and Molecular Subtypes of Lethal Prostate Cancer

Prostate cancer (PCa) is one of the most commonly diagnosed types of malignancy and is the second leading cause of cancer-related death in men in developed countries. Cyclin dependent kinase 2 associate protein 1(CDK2AP1) is an epigenetic and cell cycle regulator gene which has been downregulated in several malignancies, but its involvement in PCa has not yet been investigated in a clinical setting. We assessed the prognostic value of CDK2AP1 expression in a cohort of men diagnosed with PCa (n = 275) treated non-surgically by transurethral resection of the prostate (TURP) and studied the relationship between CDK2AP1 expression to various PCa molecular subtypes (ERG, PTEN, p53 and AR) and evaluated the association with clinical outcome. Further, we used bioinformatic tools to analyze the available TCGA PRAD transcriptomic data to explore the underlying mechanism. Our data confirmed increased expression of CDK2AP1 with higher Gleason Grade Group (GG) and metastatic PCa (p <0.0001). High CDK2AP1 expression was associated with worse overall survival (OS) (HR: 1.62, CI: 1.19−2.21, p = 0.002) and cause-specific survival (CSS) (HR: 2.012, CI 1.29−3.13, p = 0.002) using univariate analysis. When compared to each sub-molecular type. High CDK2AP1/PTEN-loss, abnormal AR or p53 expression showed even worse association to poorer OS and CCS and remained significant when adjusted for GG. Our data indicates that CDK2AP1 directly binds to p53 using the Co-Immunoprecipitation (Co-IP) technique, which was validated using molecular docking tools. This suggests that these two proteins have a significant association through several binding features and correlates with our observed clinical data. In conclusion, our results indicated that the CDK2AP1 overexpression is associate with worse OS and CSS when combined with certain PCa molecular subtypes; interaction between p53 stands out as the most prominent candidate which directly interacts with CDK2AP1.

Assessing the Mechanism of Action of “Fructus Ligustri Lucidi-Cuscutae Semen” in Prostate Cancer Treatment Using Network Pharmacology and Molecular Docking

Objective

To explore the mechanism of action of “Fructus Ligustri Lucidi-Cuscutae Semen” in the treatment of prostate cancer using network pharmacology and molecular docking.

Methods

The active ingredients and targets of “Fructus Ligustri Lucidi-Cuscutae Semen” were obtained by searching the TCMSP and DrugBank databases. These were matched and corrected using the UniProt platform. A drug “active ingredient-target” network map was constructed using Cytoscape 3.8.0. Prostate cancer-related targets were acquired from GeneCards, Disgenet, DrugBank, and other databases. The protein-protein interaction (PPI) network between the drug and prostate cancer was constructed with BioGenet; the crossover network of the two targets was extracted derive the key targets of “Fructus Ligustri Lucidi-Cuscutae Semen” for prostate cancer treatment. We used the Metascape platform for GO and KEGG enrichment analysis of the key targets. AutoDockTools1.5.6 and PyMOL software were used to perform molecular docking.

Results

We obtained 13 active ingredients, 221 drug targets, 1511 prostate cancer targets (including 221 key targets), and 305 KEGG pathways from “Fructus Ligustri Lucidi-Cuscutae Semen.” Paclitaxel, quercetin, kaempferol, TP53, β-sitosterol, EGFR, and ESR1 in “Fructus Ligustri Lucidi-Cuscutae Semen” showed good docking activity.

Conclusion

“Fructus Ligustri Lucidi-Cuscutae Semen” is a valuable clinical guide for the treatment of prostate cancer with multicomponent, multitarget, and multipathway characteristics.

Prostate cancer treatment - China's perspective

Prostate cancer (PCa) incidence and mortality have rapidly increased in China. Notably, unique epidemiological characteristics of PCa are found in the Chinese PCa population, including a low but rising incidence and an inferior but improving disease prognosis. Consequently, the current treatment landscape of PCa in China demonstrates distinct features. Establishing a more thorough understanding of the characteristics of Chinese patients may help provide novel insights into potential treatment strategies for PCa patients. Herein, we review the epidemiological status and differences in treatment modalities of Chinese PCa patients. In addition, we discuss the underlying socioeconomic and biological factors that contribute to such diversity and further propose directions for future efforts in optimizing the PCa treatment in China.

Increased Risk of Hereditary Prostate Cancer in Italian Families with Hereditary Breast and Ovarian Cancer Syndrome Harboring Mutations in BRCA and in Other Susceptibility Genes

Hereditary prostate cancer (HPCa) has the highest heritability of any cancer in men. Interestingly, it occurs in several hereditary syndromes, including breast and ovarian cancer (HBOC) and Lynch syndrome (LS). Several gene mutations related to these syndromes have been identified as biomarkers in HPCa. The goal of this study was to screen for germline mutations in susceptibility genes by using a multigene panel, and to subsequently correlate the results with clinical and laboratory parameters. This was undertaken in 180 HBOC families, which included 217 males with prostate cancer (PCa). Mutational analysis was further extended to 104 family members of mutated patients. Screening of HBOC families revealed that 30.5% harbored germline mutations in susceptibility genes, with 21.6% harboring pathogenic variants (PVs) and 8.9% having variants of uncertain significance (VUS). We found PVs at similar frequency in BRCA1 and BRCA2 genes (8.8% and 9.4%, respectively), while 0.56% of PVs were present in well-established susceptibility genes PALB2, TP53 and RAD51C. Moreover, 0.56% of monoallelic PVs were present in MUTYH, a gene whose function in tumorigenesis in the context of PCa is still unclear. Finally, we reported double heterozygosity (DH) in BRCA1/2 genes in a single family, and found double mutation (DM) present in BRCA2 in a separate family. There was no significant difference between the mean age of onset of PCa in HBOC families with or without germline mutations in susceptibility genes, while the mean survival was highest in mutated patients compared to wild type. Furthermore, PCa is the second most recurrent cancer in our cohort, resulting in 18% of cases in both mutated and non-mutated families. Our investigation shows that PVs were located mostly in the 3′ of BRCA1 and BRCA2 genes, and in BRCA2, most PVs fell in exon 11, suggesting a mutation cluster region relating to risk of HPCa. A total of 65 family members inherited the proband’s mutation; of these, 24 developed cancer, with 41 remaining unaffected.

Impact of TP53 mutations in Triple Negative Breast Cancer

Identifying triple negative breast cancer (TNBC) patients expected to have poor outcomes provides an opportunity to enhance clinical management. We applied an Evolutionary Action Score to functionally characterize TP53 mutations (EAp53) in 96 TNBC patients and observed that EAp53 stratification may identify TP53 mutations associated with worse outcomes. These findings merit further exploration in larger TNBC cohorts and in patients treated with neoadjuvant chemotherapy regimens.

Cuproptosis-related lncRNA predict prognosis and immune response of lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) accounts for 50% of lung cancers, with high mortality and poor prognosis. Long non-coding RNA (lncRNA) plays a vital role in the progression of tumors. Cuproptosis is a newly discovered form of cell death that is highly investigated. Therefore, in the present study, we aimed to investigate the role of cuproptosis-related lncRNA signature in clinical prognosis prediction and immunotherapy and the relationship with drug sensitivity.

MATERIAL AND METHODS

Genomic and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and cuproptosis-related genes were obtained from cuproptosis-related studies. The prognostic signature was constructed by co-expression analysis and Cox regression analysis. Patients were divided into high and low risk groups, and then, a further series of model validations were carried out to assess the prognostic value of the signature. Subsequently, lncRNAs were analyzed for gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes Enrichment (KEGG), immune-related functions, and tumor mutation burden (TMB). Finally, we used tumor immune dysfunction and exclusion (TIDE) algorithms on immune escape and immunotherapy of cuproptosis-related lncRNAs, thereby identifying its sensitivity toward potential drugs for LUAD.

RESULTS

A total of 16 cuproptosis-related lncRNAs were obtained, and a prognostic signature was developed. We found that high-risk patients had worse overall survival (OS) and progression-free survival (PFS) and higher mortality. Independent prognostic analyses, ROC, C-index, and nomogram showed that the cuproptosis-related lncRNAs can accurately predict the prognosis of patients. The nomogram and heatmap showed a distinct distribution of the high- and low-risk cuproptosis-related lncRNAs. Enrichment analysis showed that the biological functions of lncRNAs are associated with tumor development. We also found that immune-related functions, such as antiviral activity, were suppressed in high-risk patients who had mutations in oncogenes. OS was poorer in patients with high TMB. TIDE algorithms showed that high-risk patients have a greater potential for immune escape and less effective immunotherapy.

CONCLUSION

To conclude, the 16 cuproptosis-related lncRNAs can accurately predict the prognosis of patients with LUAD and may provide new insights into clinical applications and immunotherapy.

TP53 /KRAS Co-Mutations Create Divergent Prognosis Signatures in Intrahepatic Cholangiocarcinoma

Background: Due to high invasiveness and heterogeneity, the morbidity and mortality of intrahepatic cholangiocarcinoma (ICC) remain unsatisfied. Recently, the exploration of genomic variants has decoded the underlying mechanisms of initiation and progression for multiple tumors, while has not been fully investigated in ICC.

Methods: We comprehensively analyzed 899 clinical and somatic mutation data of ICC patients from three large-scale cohorts. Based on the mutation landscape, we identified the common high-frequency mutation genes (FMGs). Subsequently, the clinical features, prognosis, tumor mutation burden (TMB), and pharmacological landscape from patients with different mutation carriers were further analyzed.

Results: We found TP53 and KRAS were the common FMGs in the three cohorts. Kaplan–Meier survival curves and univariate and multivariate analysis displayed that TP53 and KRAS mutations were associated with poor prognosis. Considering the co-mutation phenomenon of TP53 and KRAS, we stratified patients into “Double-WT,” “Single-Hit,” and “Double-Hit” phenotypes by mutation status. Patients with the three phenotypes showed significant differences in the mutation landscape. Additionally, compared with “Double-WT” and “Single-Hit” phenotypes, patients with “Double-Hit” presented a dismal prognosis and significantly high TMB. Through chemotherapy sensitivity analysis, we identified a total of 30 sensitive drugs for ICC patients, of which 22 were drugs sensitive to “Double-WT,” 7 were drugs sensitive to “Double-Hit,” and only one was a drug sensitive to “Single-Hit.”

Conclusion: Our study defined a novel mutation classification based on the common FMGs, which may contribute to the individualized treatment and management of ICC patients.

Cross-Talk between p53 and Wnt Signaling in Cancer

Targeting cancer hallmarks is a cardinal strategy to improve antineoplastic treatment. However, cross-talk between signaling pathways and key oncogenic processes frequently convey resistance to targeted therapies. The p53 and Wnt pathway play vital roles for the biology of many tumors, as they are critically involved in cancer onset and progression. Over recent decades, a high level of interaction between the two pathways has been revealed. Here, we provide a comprehensive overview of molecular interactions between the p53 and Wnt pathway discovered in cancer, including complex feedback loops and reciprocal transactivation. The mutational landscape of genes associated with p53 and Wnt signaling is described, including mutual exclusive and co-occurring genetic alterations. Finally, we summarize the functional consequences of this cross-talk for cancer phenotypes, such as invasiveness, metastasis or drug resistance, and discuss potential strategies to pharmacologically target the p53-Wnt interaction.

Ethnic Pharmacogenomic Differences in the Management of Asian Patients with Metastatic Prostate Cancer

Progression to metastatic disease occurs in about half of all men who develop prostate cancer (PC), one of the most common cancers in men worldwide. Androgen deprivation therapy has been the mainstay therapy for patients with metastatic PC (mPC) since the 1940s. In the last decade, there has been unprecedented advancement in systemic therapies, e.g., taxane, androgen-signalling pathway inhibitors, and biomarker-driven targeted therapies for various stages of disease, resulting in overall survival improvement. Adding to ongoing controversies over how best to treat these patients is the recognition that ethnicity may influence prognosis and outcomes. This review discusses recent evidence for the impacts of Asian ethnicity specifically, which includes environmental, sociocultural, and genetic factors, on the approach to pharmacological management of mPC. Clear inter-ethnic differences in drug tolerability, serious adverse events (AEs), and genetic heterogeneity must all be considered when dosing and scheduling for treatment, as well as designing future precision studies in PC.

A Personalized Genomics Approach of the Prostate Cancer

Decades of research identified genomic similarities among prostate cancer patients and proposed general solutions for diagnostic and treatments. However, each human is a dynamic unique with never repeatable transcriptomic topology and no gene therapy is good for everybody. Therefore, we propose the Genomic Fabric Paradigm (GFP) as a personalized alternative to the biomarkers approach. Here, GFP is applied to three (one primary—“A”, and two secondary—“B” & “C”) cancer nodules and the surrounding normal tissue (“N”) from a surgically removed prostate tumor. GFP proved for the first time that, in addition to the expression levels, cancer alters also the cellular control of the gene expression fluctuations and remodels their networking. Substantial differences among the profiled regions were found in the pathways of P53-signaling, apoptosis, prostate cancer, block of differentiation, evading apoptosis, immortality, insensitivity to anti-growth signals, proliferation, resistance to chemotherapy, and sustained angiogenesis. ENTPD2, AP5M1 BAIAP2L1, and TOR1A were identified as the master regulators of the “A”, “B”, “C”, and “N” regions, and potential consequences of ENTPD2 manipulation were analyzed. The study shows that GFP can fully characterize the transcriptomic complexity of a heterogeneous prostate tumor and identify the most influential genes in each cancer nodule.