KRT20, KRT5, ESR1 and ERBB2 Expression Can Predict Pathologic Outcome in Patients Undergoing Neoadjuvant Chemotherapy and Radical Cystectomy for Muscle-Invasive Bladder Cancer

MicroRNA expression profiles reveal wool development and fineness regulation in Gansu alpine fine-wool sheep

The development of wool has a complex regulatory mechanism both influenced by genetic and environmental factors. MicroRNAs (miRNA) were involved in various biological processes of animals, and may play an important role in the regulation of wool development. In this study, we comprehensively analyzed and identified the histological parameters of hair follicles, as well as the miRNAs, target genes, pathways, and Gene Ontology terms related to wool fineness regulation and wool growth and development using HE staining and RNA-Seqs methods. Both coarse (group C, mean fiber diameter (MFD) = 22.26 ± 0.69 μm, n = 6) and fine (group F, MFD = 16.91 ± 0.29 μm, n = 6) of Gansu alpine fine-wool sheep with different wool fineness were used in this study. The results showed that the primary follicle diameter and secondary wool fiber diameter in group C were significantly higher than those in group F (P < 0.05). And the number of primary and secondary hair follicles in group C was significantly lower than that in group F (P < 0.05). Furthermore, a total of 67 DE miRNAs and 290 potential DE miRNAs target genes were screened in the skin tissues of sheep from groups F and C, and some potential target genes related to wool fineness regulation were screened, such as CDH2, KRT82, FOXN1, LOC101106296, KRT20, MCOLN3, KRT71, and TERT. These genes were closely related to Glutathione metabolism, epidermal cell differentiation, keratinization, and regulation of hair cycle. Moreover, the regulatory network of miRNAs-mRNAs suggested that miRNAs (miR-129-x, novel m0079-3p, miR-2484-z, novel m0025-5P, etc.) may play a key role in the wool development and wool fineness regulation of Gansu alpine fine-wool sheep. In summary, this study expands the existing miRNAs database and provides new information for studying the regulation of wool development in Gansu alpine fine wool sheep.

Exploring the Targets and Molecular Mechanisms of Curcumin for the Treatment of Bladder Cancer Based on Network Pharmacology, Molecular Docking and Molecular Dynamics

Curcumin, a phenolic compound derived from turmeric, has demonstrated anti-tumor properties in preclinical models of various cancers. However, the exact mechanism of curcumin in treating bladder cancer remains unclear. This study aimed to elucidate the therapeutic targets and molecular mechanisms of curcumin in the treatment of BC through an integrated approach of network pharmacology, molecular docking, and molecular dynamics simulations. PharmMapper, SuperPred, TargetNet, and SwissTargetPrediction were utilized to acquire targets associated with curcumin, while GeneCards, CTD, DisGeNET, OMIM, and PharmGKB databases were utilized to obtain targets related to bladder cancer. The drug-disease interaction targets were obtained using Venny 2.1.0, and GO and KEGG enrichment analyses were then conducted with the DAVID tool. We constructed a protein-protein interaction (PPI) network and identified tenkey targets. In conclusion, AutoDock Tools 1.5.7 was utilized to conduct molecular docking simulations, followed by additional analysis of the central targets through the GEPIA, HPA, cBioPortal, and TIMER databases. A total of 305 potential anticancer targets of curcumin were obtained. The analysis of GO functional enrichment resulted in a total of 1105 terms, including 786 terms related to biological processes (BP), 105 terms related to cellular components (CC), and 214 terms related to molecular functions (MF). In addition, KEGG pathway enrichment analysis identified 170 relevant signaling pathways. Treating bladder cancer could potentially involve inhibiting pathways like the PI3K-Akt signaling pathway, MAPK signaling pathway, EGFR tyrosine kinase inhibitor resistance, and IL-17 signaling pathway. Activating TNF, ALB, CASP3, and ESR1 while inhibiting AKT1, EGFR, STAT3, BCL2, SRC, and HSP90AA1 can also hinder the proliferation of bladder tumor cells. According to the results of molecular docking, curcumin binds to these central targets in a spontaneous manner, exhibiting binding energies lower than - 1.631 kJ/mol. These findings were further validated at the transcriptional, translational and immune infiltration levels. By utilizing network pharmacology and molecular docking techniques, it was discovered that curcumin possesses diverse effects on multiple targets and pathways for treating bladder cancer. It has the potential to impede the growth of bladder tumor cells by suppressing various pathways including the PI3K-Akt and MAPK signaling pathways, as well as pathways associated with EGFR tyrosine kinase inhibitor resistance and the IL-17 signaling pathway. Curcumin could potentially disrupt the cell cycle advancement in bladder cancer cells by increasing the expression of TNF, ALB, CASP3, and ESR1 while decreasing AKT1, EGFR, STAT3, BCL2, SRC, HSP90AA1, and other targeted genes. These findings reveal the possible molecular pathways through which curcumin exerts its anticancer effects in bladder cancer, and this novel research strategy not only provides an important basis for an in-depth understanding of the anticancer mechanism of curcumin, but also offers new potential drugs and targets for the clinical treatment of bladder cancer. Therefore, this study is of great scientific significance and practical application value for promoting the development of bladder cancer therapeutic field. This finding provides strong support for the development of novel, safe and effective drugs for bladder cancer treatment.

Identifying novel biomarkers associated with bladder cancer treatment outcomes

Bladder cancer is a complex disease with variable prognosis. Recent investigations into the molecular landscape of bladder cancer have revealed frequent genetic alterations and molecular subtypes with therapeutic implications. Consequently, a shift toward personalized treatment of bladder cancer is underway. To this end, several biomarkers have been developed and tested in their ability to predict response to treatment in patients with bladder cancer and potentially help direct therapy. We performed a search of recently published PubMed articles using terms "biomarker," "bladder cancer," and the respective treatment discussed (i.e., "neoadjuvant" or "BCG"). In this review, we summarize the latest studies on novel biomarkers in bladder cancer with a focus on those intended to improve risk stratification and treatment selection.

Predicting Complete Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer

Muscle-invasive bladder cancer is a life-threatening disease best managed with multimodal therapy. Neoadjuvant chemotherapy prior to cystectomy significantly improves survival with the greatest benefit noted in patients with a complete pathologic response noted at cystectomy. While radical cystectomy is currently an important part of the treatment plan, surgical morbidity remains high. Accurate prediction of complete responses to chemotherapy would enable avoiding the morbidity of radical cystectomy. Multiple clinical, pathologic, molecular, and radiographic predictors have been evaluated. Clinical and standard pathologic findings have not been found to be accurate predictors of complete response. To date, tumor genomic findings have been the most promising and have led to multiple clinical trials to evaluate if bladder preservation is possible in select patients. Radiomics has shown initial promise with larger validation series needed. These predictors can be further characterized as treatment specific and non-treatment specific. With the potential changing landscape of neoadjuvant therapy prior to radical cystectomy and the limitations of individual predictors of a complete response, a panel of several biomarkers may enhance patient selection for bladder preservation. The aim of this review is to summarize predictors of complete response to neoadjuvant chemotherapy.

Prediction of Response to Cisplatin-Based Neoadjuvant Chemotherapy of Muscle-Invasive Bladder Cancer Patients by Molecular Subtyping including KRT and FGFR Target Gene Assessment

Patients with muscle-invasive urothelial carcinoma achieving pathological complete response (pCR) upon neoadjuvant chemotherapy (NAC) have improved prognosis. Molecular subtypes of bladder cancer differ markedly regarding sensitivity to cisplatin-based chemotherapy and harbor FGFR treatment targets to various content. The objective of the present study was to evaluate whether preoperative assessment of molecular subtype as well as FGFR target gene expression is predictive for therapeutic outcome—rate of ypT0 status—to justify subsequent prospective validation within the “BladderBRIDGister”. Formalin-fixed paraffin-embedded (FFPE) tissue specimens from transurethral bladder tumor resections (TUR) prior to neoadjuvant chemotherapy and corresponding radical cystectomy samples after chemotherapy of 36 patients were retrospectively collected. RNA from FFPE tissues were extracted by commercial kits, Relative gene expression of subtyping markers (e.g., KRT5, KRT20) and target genes (FGFR1, FGFR3) was analyzed by standardized RT-qPCR systems (STRATIFYER Molecular Pathology GmbH, Cologne). Spearman correlation, Kruskal−Wallis, Mann−Whitney and sensitivity/specificity tests were performed by JMP 9.0.0 (SAS software). The neoadjuvant cohort consisted of 36 patients (median age: 69, male 83% vs. female 17%) with 92% of patients being node-negative during radical cystectomy after 1 to 4 cycles of NAC. When comparing pretreatment with post-treatment samples, the median expression of KRT20 dropped most significantly from DCT 37.38 to 30.65, which compares with a 128-fold decrease. The reduction in gene expression was modest for other luminal marker genes (GATA3 6.8-fold, ERBB2 6.3-fold). In contrast, FGFR1 mRNA expression increased from 33.28 to 35.88 (~6.8-fold increase). Spearman correlation revealed positive association of pretreatment KRT20 mRNA levels with achieving pCR (r = 0.3072: p = 0.0684), whereas pretreatment FGFR1 mRNA was associated with resistance to chemotherapy (r = −0.6418: p < 0.0001). Hierarchical clustering identified luminal tumors of high KRT20 mRNA expression being associated with high pCR rate (10/16; 63%), while the double-negative subgroup with high FGFR1 expression did not respond with pCR (0/9; 0%). Molecular subtyping distinguishes patients with high probability of response from tumors as resistant to neoadjuvant chemotherapy. Targeting FGFR1 in less-differentiated bladder cancer subgroups may sensitize tumors for adopted treatments or subsequent chemotherapy.

Development of a MRI-Based Radiomics Nomogram for Prediction of Response of Patients With Muscle-Invasive Bladder Cancer to Neoadjuvant Chemotherapy

Objective

To develop and evaluate the performance of a magnetic resonance imaging (MRI)-based radiomics nomogram for prediction of response of patients with muscle-invasive bladder cancer (MIBC) to neoadjuvant chemotherapy (NAC).

Methods

A total of 70 patients with clinical T2-4aN0M0 MIBC were enrolled in this retrospective study. For each patient, 1316 radiomics features were extracted from T2-weighted images (T2WI), diffusion-weighted images (DWI), and apparent diffusion coefficient (ADC) maps. The variance threshold algorithm and the Student's t-test or the Mann-Whitney U test were applied to select optimal features. Multivariate logistic regression analysis was used to eliminate irrelevant features, and the retained features were incorporated into the final single-modality radiomics model. Combined radiomic models were generated by combining single-modality radiomics models. A radiomics nomogram, incorporating radiomics signatures and independent clinical risk factors, was developed to determine whether the performance of the model in predicting tumor response to NAC could be further improved.

Results

Based on pathological T stage post-surgery, 36 (51%) patients were classified as good responders (GR) and 34 (49%) patients as non-good responders (non-GR). In addition, 3 single-modality radiomics models and 4 combined radiomics models were established. Among all radiomics models, the combined radiomics model based on T2WI_Score, DWI_Score, and ADC_Score yielded the highest area under the receiver operating characteristics curve (AUC) (0.967, 95% confidence interval (CI): 0.930-0.995). A radiomics nomogram, integrating the clinical T stage and 3 single-modality radiomics models, yielded a higher AUC (0.973, 95%CI: 0.934-0.998) than other combined radiomics models.

Conclusion

The proposed MRI-based radiomics nomogram has the potential to be used as a non-invasive tool for the quantitatively prediction of tumor response to NAC in patients with MIBC.

Molecular Subtypes as a Basis for Stratified Use of Neoadjuvant Chemotherapy for Muscle-Invasive Bladder Cancer-A Narrative Review

There are no established biomarkers to guide patient selection for neoadjuvant chemotherapy prior to radical cystectomy for muscle-invasive bladder cancer. Recent studies suggest that molecular subtype classification holds promise for predicting chemotherapy response and/or survival benefit in this setting. Here, we summarize and discuss the scientific literature examining transcriptomic or panel-based molecular subtyping applied to neoadjuvant chemotherapy-treated patient cohorts. We find that there is not sufficient evidence to conclude that the basal subtype of muscle-invasive bladder cancer responds well to chemotherapy, since only a minority of studies support this conclusion. More evidence indicates that luminal-like subtypes may have the most improved outcomes after neoadjuvant chemotherapy. There are also conflicting data concerning the association between biopsy stromal content and response. Subtypes indicative of high stromal infiltration responded well in some studies and poorly in others. Uncertainties when interpreting the current literature include a lack of reporting both response and survival outcomes and the inherent risk of bias in retrospective study designs. Taken together, available studies suggest a role for molecular subtyping in stratifying patients for receiving neoadjuvant chemotherapy. The precise classification system that best captures such a predictive effect, and the exact subtypes for which other treatment options are more beneficial remains to be established, preferably in prospective studies.