Emerging Biomarkers for Predicting Bladder Cancer Lymph Node Metastasis

Molecular Biomarkers of Bladder Cancer: A Mini-Review

Cancers are quite common, but mostly very serious diseases and therefore belong to the most important areas of scientific research activity. Bladder cancer is one of the most common malignancies, it is a heterogeneous disease with significant diagnostic, therapeutic, and prognostic problems. It represents a disease with a variable course and a different response to therapy. The "conventional" prognostic markers used so far cannot reliably predict the natural course of the disease or estimate the tumor response to the chosen type of treatment. Molecular markers can provide us with the opportunity to diagnose a bladder tumor early, identify patients who are at risk of recurrence, or predict how tumors will respond to therapeutic approaches. As a result, diagnostics are found to help clinicians find the best therapeutic options for patients with bladder cancer. In this study, we focused on a brief description of potential molecular markers in bladder tumors in the context of precise diagnostics. Last but not least, we also focused on a new approach to the treatment of cancer using nanomaterials.

Predicting Lymph Node Metastasis Status from Primary Muscle-Invasive Bladder Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study

BACKGROUND

Accurate prediction of lymph node metastasis (LNM) status in patients with muscle-invasive bladder cancer (MIBC) before radical cystectomy can guide the use of neoadjuvant chemotherapy and the extent of pelvic lymph node dissection. We aimed to develop and validate a weakly-supervised deep learning model to predict LNM status from digitized histopathological slides in MIBC.

METHODS

We trained a multiple instance learning model with an attention mechanism (namely SBLNP) from a cohort of 323 patients in the TCGA cohort. In parallel, we collected corresponding clinical information to construct a logistic regression model. Subsequently, the score predicted by the SBLNP was incorporated into the logistic regression model. In total, 417 WSIs from 139 patients in the RHWU cohort and 230 WSIs from 78 patients in the PHHC cohort were used as independent external validation sets.

RESULTS

In the TCGA cohort, the SBLNP achieved an AUROC of 0.811 (95% confidence interval [CI], 0.771-0.855), the clinical classifier achieved an AUROC of 0.697 (95% CI, 0.661-0.728) and the combined classifier yielded an improvement to 0.864 (95% CI, 0.827-0.906). Encouragingly, the SBLNP still maintained high performance in the RHWU cohort and PHHC cohort, with an AUROC of 0.762 (95% CI, 0.725-0.801) and 0.746 (95% CI, 0.687-0.799), respectively. Moreover, the interpretability of SBLNP identified stroma with lymphocytic inflammation as a key feature of predicting LNM presence.

CONCLUSIONS

Our proposed weakly-supervised deep learning model can predict the LNM status of MIBC patients from routine WSIs, demonstrating decent generalization performance and holding promise for clinical implementation.

ANXA6/TRPV2 axis promotes lymphatic metastasis in head and neck squamous cell carcinoma by inducing autophagy

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is highly aggressive with a significant tropism of lymph nodes, which restricts treatment options and negatively impacts patient outcomes. Although progress has been made in understanding the molecular mechanisms underlying lymphatic metastasis (LM), these mechanisms remain elusive. ANXA6 is a scaffold protein that participates in tumor pathogenesis and autophagy regulation; however, how ANXA6 affects autophagy and LM in HNSCC cells remains unknown.

METHODS

RNA sequencing was performed on HNSCC clinical specimens with or without metastasis as well as on The Cancer Genome Atlas dataset to investigate ANXA6 expression and survival. Both in vitro and in vivo studies were performed to investigate the role of ANXA6 in the regulation of LM in HNSCC. The molecular mechanism by which ANXA6 interacts with TRPV2 was examined at the molecular level.

RESULTS

ANXA6 expression was significantly upregulated in HNSCC patients with LM and higher expression was associated with poor prognosis. ANXA6 overexpression promoted the proliferation and mobility of FaDu and SCC15 cells in vitro; however, ANXA6 knockdown retarded LM in HNSCC in vivo. ANXA6 induced autophagy by inhibiting the AKT/mTOR signaling pathway in HNSCC, thereby regulating the metastatic capability of the disease. Furthermore, ANXA6 expression positively correlated with TRPV2 expression both in vitro and in vivo. Lastly, TRPV2 inhibition reversed ANXA6-induced autophagy and LM.

CONCLUSIONS

These results indicate that the ANXA6/TRPV2 axis facilitates LM in HNSCC by stimulating autophagy. This study provides a theoretical basis for investigating the ANXA6/TRPV2 axis as a potential target for the treatment of HNSCC, as well as a biomarker for predicting LM.

ALKBH5 activates FAK signaling through m6A demethylation in ITGB1 mRNA and enhances tumor-associated lymphangiogenesis and lymph node metastasis in ovarian cancer

Background: Lymph node (LN) metastasis is common in patients with epithelial ovarian cancer (EOC) and is associated with poor prognosis. Tumor-associated lymphangiogenesis is the first stage of LN metastasis. Research on lymphangiogenesis and lymph node metastases can help develop new anti-LN-targeted therapies. Aberrant N6-methyladenosine (m6A) modifications have been reported to be linked to LN metastasis in several cancers, however, their role in EOC lymphangiogenesis and LN metastasis remains unclear. Methods: m6A levels in EOC tissues with or without LN metastases were evaluated by dot blot analysis. Real-time polymerase chain reaction (PCR) and immunofluorescence were used to examine the expression of m6A-related enzymes. Additionally, in vitro and in vivo functional studies were performed to discover the importance of the AlkB homolog 5 (ALKBH5) gene in EOC lymphatic metastasis. To identify the downstream target genes regulated by ALKBH5, we performed RNA pulldown, RNA-binding protein immunoprecipitation-quantitative PCR, co-immunoprecipitation, m6A-modified RNA immunoprecipitation-quantitative PCR, and luciferase reporter assays. Results: m6A modification was reduced in ovarian cancers with LN metastases. ALKBH5 overexpression increased tumor-associated lymphangiogenesis and LN metastasis both in vitro and in vivo. ALKBH5 overexpression also reversed the m6A modification in ITGB1 mRNA and suppressed the YTHDF2 protein-mediated m6A-dependent ITGB1 mRNA degradation, which resulted in increased expression of ITGB1 and phosphorylation of the focal adhesion kinase (FAK) and Src proto-oncogene proteins, thereby increasing LN metastasis. Furthermore, hypoxia induced the expression of hypoxia inducible factor 1 subunit alpha, which increased ALKBH5 expression and enhanced LN metastasis in EOC. Conclusions: The ALKBH5/m6A-ITGB1/FAK signalling axis is important in ovarian cancer lymphangiogenesis and LN metastasis. Antibodies that block ITGB1 and FAK kinase-inhibitors are promising anti-metastatic agents.

Association Between Interleukin-6 Levels and Lymph Node Metastasis in Bladder Cancer Patients

Background

Bladder cancer (BC) is one of the urological cancers with high prevalence, mortality, morbidity, and expenditure rates. Urothelial malignancies account for about 90% cases of BC, with squamous and adenocarcinomas making up the remaining 10%. Lymph node metastasis (LNM), the most common type of BC metastasis, is generally found in the pelvic lymph nodes. LNM significantly affects the chances of survival and prognosis for patients with BC. It is feasible to stratify and assess the malignancy of the tumor and its response to therapies using potential tumor markers. Interleukin-6 (IL-6) has been observed to be a predictor of metastasis in lymph nodes in BC. The aim of this study was to evaluate the relationship between IL-6 levels and lymph node metastases in BC patients.

Methods

Thirty-two BC patients between August 2021 and January 2022 were admitted to this study. Data on patient characteristics, clinical data, TNM staging, and IL-6 levels were collected. Univariate analysis was used in the characteristics of the patients.

Results

The total subjects were 32 with 15 results in LNM. The difference in IL-6 levels between the LNM (+) group and the LNM (-) was statistically significant by Fisher's exact test (P = 0.041) and Mann-Whitney U tests (P = 0.003).

Conclusions

The BC patients who had lymph node metastases also had higher serum levels of IL-6.

Identification and validation of a novel cuproptosis-related lncRNA gene signature to predict prognosis and immune response in bladder cancer

PURPOSE

Bladder cancer (BCa) is one of the most common malignant tumors in the urogenital system, characterized by the high recurrence rate, mortality rate and poor prognosis. Based on cuproptosis-related long noncoding RNAs (CRLs), this study set out to create a prediction signature to evaluate the prognosis of patients with BCa.

METHODS

RNA-seq data including CRLs and related clinicopathological data were gathered from The Cancer Genome Atlas (TCGA) database (n = 428). The predictive signature was constructed after correlation analysis. Subsequently, relying on the analyzed data from the TCGA database and our sample collection, we examined and verified the connections between CRLs model and important indexes included prognosis, route and functional enrichment, tumor immune evasion, tumor mutation, and treatment sensitivity.

RESULTS

Patients in the high-risk group had lower overall survival (OS) than that of low-risk group. Compared with clinicopathological variables, CRLs features have better predictive value according to receiver operating characteristic (ROC) curve. The expression level of CRLs was highly associated with the tumor progress, tumor microenvironment and tumor immune escape. Additionally, we identified that the mutation of TP53, TTN, KMT2D and MUC16 gene were founded in patients with BCa. Lapatinib, pazopanib, saracatinib, gemcitabine, paclitaxel and palenolactone had good antitumor effects for BCa patients in the high-risk group (all P < 0.001).

CONCLUSION

This study revealed the effects of CRLs on BCa and further established CRLs model, which can be used in clinic for predicting prognosis, immunological response and treatment sensitivity inpatient with BCa.

Biomarkers of Bladder Cancer: Cell-Free DNA, Epigenetic Modifications and Non-Coding RNAs

Bladder cancer (BC) is the 10th most frequent cancer in the world. The initial diagnosis and surveillance of BC require a combination of invasive and non-invasive methods, which are costly and suffer from several limitations. Cystoscopy with urine cytology and histological examination presents the standard diagnostic approach. Various biomarkers (e.g., proteins, genes, and RNAs) have been extensively studied in relation to BC. However, the new trend of liquid biopsy slowly proves to be almost equally effective. Cell-free DNA, non-coding RNA, and other subcellular structures are now being tested for the best predictive and diagnostic value. In this review, we focused on published gene mutations, especially in DNA fragments, but also epigenetic modifications, and non-coding RNA (ncRNA) molecules acquired by liquid biopsy. We performed an online search in PubMed/Medline, Scopus, and Web of Science databases using the terms "bladder cancer", in combination with "markers" or "biomarkers" published until August 2022. If applicable, we set the sensitivity and specificity threshold to 80%. In the era of precision medicine, the development of complex laboratory techniques fuels the search and development of more sensitive and specific biomarkers for diagnosis, follow-up, and screening of BC. Future efforts will be focused on the validation of their sensitivity, specificity, predictive value, and their utility in everyday clinical practice.

Downregulation of PTCD1 in Bladder Urothelial Carcinoma Predicts Poor Prognosis and Levels of Immune Infiltration

Pentatricopeptide repeat domain 1 (PTCD1) was reported to regulate mitochondrial metabolism and oxidative phosphorylation. However, the effect and mechanism of PTCD1 in the development of bladder urothelial carcinoma (BLCA) remain unclear. The databases from The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) were used to analyze the expression changes, clinical features, and prognostic values of PTCD1. A nomogram was built to predict the prognostic outcomes of BLCA cases. The potential genes interacting with PTCD1 were explored by Weighted Gene Coexpression Network Analysis (WGCNA). The estimation of associations between PTCD1 and tumor mutations, tumor immunities, and m6A methylations was performed. The study found that the gradual decrease of PTCD1 expression was observed with the increase of stage and grade. Low PTCD1 expression was greatly correlated with higher pathological stage, N stage, and poor prognosis in TCGA cohorts; interestingly, low-grade BLCA cases all exhibited high expression of PTCD1. HPA database analysis implied that the expression of PTCD1 protein in BLCA was lower than that in normal bladder tissue, and the protein expression of PTCD1 in high-grade BLCA was lower than that in low-grade BLCA. Multivariate Cox regression analysis indicated that PTCD1 may serve as an independent factor influencing prognosis of BLCA. Mechanistically, PTCD1 played a regulatory role in BLCA progression through multiple tumor-related pathways containing PI3K-Akt signaling, ECM-receptor interaction, oxidative phosphorylation, and extracellular matrix organization. WGCNA reported that PTCD1 had a strong positive correlation with POLR2J, ZNHT1, ATP5MF, PDAP1, BUD31, and COPS6. Besides, the mRNA expression of PTCD1 was negatively associated with immune cells' infiltrations, immune functions, and checkpoints, especially with some m6A methylation regulators in BLCA. In sum, downregulation of PTCD1 expression may be involved in the development of BLCA and remarkably correlated with poor prognosis. Meantime, it showed an influence in immune cell infiltration and may serve as an agreeable prognostic indicator in BLCA.

RNA N6-methyladenosine reader IGF2BP2 promotes lymphatic metastasis and epithelial-mesenchymal transition of head and neck squamous carcinoma cells via stabilizing slug mRNA in an m6A-dependent manner

Background

Lymph node metastasis is the main cause of poor prognosis of head and neck squamous carcinoma (HNSCC) patients. N6-methyladenosine (m6A) RNA modification is an emerging epigenetic regulatory mechanism for gene expression, and as a novel m6A reader protein, IGF2BP2 has been implicated in tumor progression and metastasis. However, not much is currently known about the functional roles of IGF2BP2 in HNSCC, and whether IGF2BP2 regulates lymphatic metastasis through m6A modification in HNSCC remains to be determined.

Methods

The expression and overall survival (OS) probability of m6A-related regulators in HNSCC were analyzed with The Cancer Genome Atlas (TCGA) dataset and GEPIA website tool, respectively. The expression levels of IGF2BP2 were measured in HNSCC tissues and normal adjacent tissues. To study the effects of IGF2BP2 on HNSCC cell metastasis in vitro and in vivo, gain- and loss- of function methods were employed. RIP, MeRIP, luciferase reporter and mRNA stability assays were performed to explore the epigenetic mechanism of IGF2BP2 in HNSCC.

Results

We investigated 20 m6A-related regulators in HNSCC and discovered that only the overexpression of IGF2BP2 was associated with a poor OS probability and an independent prognostic factor for HNSCC patients. Additionally, we demonstrated that IGF2BP2 was overexpressed in HNSCC tissues, and significantly correlated to lymphatic metastasis and poor prognosis. Functional studies have shown that IGF2BP2 promotes both HNSCC cell migration as well as invasion via the epithelial-mesenchymal transition (EMT) process in vitro, and IGF2BP2 knockdown significantly inhibited lymphatic metastasis and lymphangiogenesis in vivo. Mechanistic investigations revealed that Slug, a key EMT-related transcriptional factor, is the direct target of IGF2BP2, and essential for IGF2BP2-regulated EMT and metastasis in HNSCC. Furthermore, we demonstrated that IGF2BP2 recognizes and binds the m6A site in the coding sequence (CDS) region of Slug and promotes its mRNA stability.

Conclusions

Collectively, our study uncovers the oncogenic role and potential mechanism of IGF2BP2, which serves as a m6A reader, in controlling lymphatic metastasis and EMT in HNSCC, suggesting that IGF2BP2 may act as a therapeutic target and prognostic biomarker for HNSCC patients with metastasis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-02212-1.

Identification of a Nomogram from Ferroptosis-Related Long Noncoding RNAs Signature to Analyze Overall Survival in Patients with Bladder Cancer

Purpose

This study aimed to establish a nomogram to predict the overall survival (OS) of patients with bladder cancer (BC) by ferroptosis-related long noncoding RNAs (FRlncRNAs) signature.

Methods

We obtained FRlncRNAs expression profiles and clinical data of patients with BC from the Cancer Genome Atlas database. The patients were divided into the training set, testing set, and overall set. Lasso regression and multivariate Cox regression were used to establish the FRlncRNAs signature, the prognosis of each group was compared by Kaplan–Meier (K-M) analysis, and the receiver operating characteristic (ROC) curve evaluated the accuracy of the model. The Gene Set Enrichment Analysis (GSEA) was used for the visualization of the functional enrichment for FRlncRNAs. The databases of GEPIA and K-M Plotter were used for subsequent functional analysis of major FRlncRNAs.

Results

Thirteen prognostic FRlncRNAs (LINC00942, MAFG-DT, AL049840.3, AL136084.3, OCIAD1-AS1, AC062017.1, AC008074.2, AC018653.3, AL031775.1, USP30-AS1, LINC01767, AC132807.2, and AL354919.2) were identified to be significantly different, constituting an FRlncRNAs signature. Patients with BC were divided into low-risk group and high-risk group by this signature in the training, testing, and overall sets. K-M analysis showed that the prognosis of patients in the high-risk group was poor and the difference in the subgroup analyses was statistically significant. ROC analysis revealed that the predictive ability of the model was more accurate than traditional assessment methods. A risk score based on FRlncRNAs signature was an independent prognostic factor for the patients with BC (HR = 1.388, 95%CI = 1.228–1.568, P < 0.001). Combining the FRlncRNAs signature and clinicopathological factors, a predictive nomogram was constructed. The nomogram can accurately predict the overall survival of patients and had high clinical practicability. The GSEA analysis showed that the primary pathways were WNT, MAPK, and cell-matrix adhesion signaling pathways. The major FRlncRNAs (MAFG-DT) were associated with poor prognosis in the GEPIA and K-M Plotter database.

Conclusion

Thirteen prognostic FRlncRNAs and their nomogram were accurate tools for predicting the OS of BC, which might be molecular biomarkers and therapeutic targets.