Basal Tumor Cell Isolation and Patient-Derived Xenograft Engraftment Identify High-Risk Clinical Bladder Cancers

Identification of tumor antigens and immune subtypes of hepatocellular carcinoma for mRNA vaccine development

BACKGROUND

mRNA vaccines have been investigated in multiple tumors, but limited studies have been conducted on their use for hepatocellular carcinoma (HCC).

AIM

To identify candidate mRNA vaccine antigens for HCC and suitable subpopulations for mRNA vaccination.

METHODS

Gene expression profiles and clinical information of HCC datasets were obtained from International Cancer Genome Consortium and The Cancer Genome Atlas. Genes with somatic mutations and copy number variations were identified by cBioPortal analysis. The differentially expressed genes with significant prognostic value were identified by Gene Expression Profiling Interactive Analysis 2 website analysis. The Tumor Immune Estimation Resource database was used to assess the correlation between candidate antigens and the abundance of antigen-presenting cells (APCs). Tumor-associated antigens were overexpressed in tumors and associated with prognosis, genomic alterations, and APC infiltration. A consensus cluster analysis was performed with the Consensus Cluster Plus package to identify the immune subtypes. The weighted gene coexpression network analysis (WGCNA) was used to determine the candidate biomarker molecules for appropriate populations for mRNA vaccines.

RESULTS

AURKA, CCNB1, CDC25C, CDK1, TRIP13, PES1, MCM3, PPM1G, NEK2, KIF2C, PTTG1, KPNA2, and PRC1 were identified as candidate HCC antigens for mRNA vaccine development. Four immune subtypes (IS1-IS4) and five immune gene modules of HCC were identified that were consistent in both patient cohorts. The immune subtypes showed distinct cellular and clinical characteristics. The IS1 and IS3 immune subtypes were immunologically "cold". The IS2 and IS4 immune subtypes were immunologically "hot", and the immune checkpoint genes and immunogenic cell death genes were upregulated in these subtypes. IS1-related modules were identified with the WGCNA algorithm. Ultimately, five hub genes (RBP4, KNG1, METTL7A, F12, and ABAT) were identified, and they might be potential biomarkers for mRNA vaccines.

CONCLUSION

AURKA, CCNB1, CDC25C, CDK1, TRIP13, PES1, MCM3, PPM1G, NEK2, KIF2C, PTTG1, KPNA2, and PRC1 have been identified as candidate HCC antigens for mRNA vaccine development. The IS1 and IS3 immune subtypes are suitable populations for mRNA vaccination. RBP4, KNG1, METTL7A, F12, and ABAT are potential biomarkers for mRNA vaccines.

Mitochondrial Aconitase ACO2 Links Iron Homeostasis with Tumorigenicity in Non-Small Cell Lung Cancer

The ability of a patient tumor to engraft an immunodeficient mouse is the strongest known independent indicator of poor prognosis in early-stage non-small cell lung cancer (NSCLC). Analysis of primary NSCLC proteomes revealed low-level expression of mitochondrial aconitase (ACO2) in the more aggressive, engrafting tumors. Knockdown of ACO2 protein expression transformed immortalized lung epithelial cells, whereas upregulation of ACO2 in transformed NSCLC cells inhibited cell proliferation in vitro and tumor growth in vivo. High level ACO2 increased iron response element binding protein 1 (IRP1) and the intracellular labile iron pool. Impaired cellular proliferation associated with high level ACO2 was reversed by treatment of cells with an iron chelator, whereas increased cell proliferation associated with low level ACO2 was suppressed by treatment of cells with iron. Expression of CDGSH iron-sulfur (FeS) domain-containing protein 1 [CISD1; also known as mitoNEET (mNT)] was modulated by ACO2 expression level and inhibition of mNT by RNA interference or by treatment of cells with pioglitazone also increased iron and cell death. Hence, ACO2 is identified as a regulator of iron homeostasis and mNT is implicated as a target in aggressive NSCLC.

IMPLICATIONS

FeS cluster-associated proteins including ACO2, mNT (encoded by CISD1), and IRP1 (encoded by ACO1) are part of an "ACO2-Iron Axis" that regulates iron homeostasis and is a determinant of a particularly aggressive subset of NSCLC.

Application status and future prospects of the PDX model in lung cancer

Lung cancer is one of the most prevalent, fatal, and highly heterogeneous diseases that, seriously threaten human health. Lung cancer is primarily caused by the aberrant expression of multiple genes in the cells. Lung cancer treatment options include surgery, radiation, chemotherapy, targeted therapy, and immunotherapy. In recent decades, significant progress has been made in developing therapeutic agents for lung cancer as well as a biomarker for its early diagnosis. Nonetheless, the alternative applications of traditional pre-clinical models (cell line models) for diagnosis and prognosis prediction are constrained by several factors, including the lack of microenvironment components necessary to affect cancer biology and drug response, and the differences between laboratory and clinical results. The leading reason is that substantial shifts accrued to cell biological behaviors, such as cell proliferative, metastatic, invasive, and gene expression capabilities of different cancer cells after decades of growing indefinitely in vitro. Moreover, the introduction of individualized treatment has prompted the development of appropriate experimental models. In recent years, preclinical research on lung cancer has primarily relied on the patient-derived tumor xenograft (PDX) model. The PDX provides stable models with recapitulate characteristics of the parental tumor such as the histopathology and genetic blueprint. Additionally, PDXs offer valuable models for efficacy screening of new cancer drugs, thus, advancing the understanding of tumor biology. Concurrently, with the heightened interest in the PDX models, potential shortcomings have gradually emerged. This review summarizes the significant advantages of PDXs over the previous models, their benefits, potential future uses and interrogating open issues.

CDC25C as a Predictive Biomarker for Immune Checkpoint Inhibitors in Patients With Lung Adenocarcinoma

The application of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer has significantly improved patient survival. However, most patients fail to respond to ICIs or develop drug resistance during treatment. Therefore, novel biomarkers are needed to predict the efficacy of ICIs or provide clues on how to overcome drug resistance. Here, it was revealed that cell division cycle 25C (CDC25C) expression was upregulated in lung adenocarcinoma (LUAD) compared to that of normal lung tissue in multiple databases. This was further verified by q-PCR. Furthermore, higher CDC25C expression was associated with shorter overall survival and worse pathological stage. Most importantly, a higher CDC25C expression was associated with shorter progression-free survival in LUAD patients treated with nivolumab, suggesting the role of the cell cycle in immunotherapy. In addition, CDC25C expression was significantly associated with immune cell infiltration and immune-related signatures in the LUAD tumor microenvironment. Moreover, CDC25C was differentially expressed and correlated with overall survival in multiple tumors, indicating that CDC25C is a broad-spectrum biomarker. Taken together, our study demonstrates that CDC25C is a prognostic biomarker for LUAD patients, especially for patients treated with ICIs. Our study also provides strong evidence for the role of the cell cycle in ICIs therapy and tumor microenvironment.

Patient derived models of bladder cancer enrich the signal of the tumor cell transcriptome facilitating the analysis of the tumor cell compartment

The evolving paradigm of the molecular classification of bladder cancer requires models that represent the classifications with less heterogeneity. Robust transcriptome based molecular classifications are essential to address tumor heterogeneity. Patient derived models (PDMs) are a powerful preclinical tool to study specific tumor compartments. We tested if the consensus molecular subtype analysis was applicable to PDMs and evaluated the tumor compartment each model represents. PDMs derived from surgical specimens were established as xenografts (PDX), organoids (PDO), and spheroids (PDS). The surgical specimens and PDMs were molecularly characterized by RNA sequencing. PDMs that were established in immune deficient mice or in vitro significantly downregulated transcripts related to the immune and stromal compartments compared to the surgical specimens. However, PDMs upregulate a patient-specific bladder cancer cell signal which allowed for analysis of cancer cell pathways independent of the tumor microenvironment. Based on transcriptomic signatures, PDMs are more similar to their surgical specimen than the model type; indicating that the PDMs retained unique features of the tumor from which the PDM was derived. When comparing models, PDX models were the most similar to the surgical specimen, while PDO and PDS models were most similar to each other. When the consensus molecular subtype classification system was applied to both the surgical samples and the three PDMs, good concordance was found between all samples indicating that this system of classification can be applied to PDO and PDS models. PDMs reduce tumor heterogeneity and allow analysis of tumor cells while maintaining the gene expression profile representative of the original tumor.

Establishment of Real-Time Multispectral Imaging for the Detection of Bladder Cancer Using a Preclinical in Vivo Model

BACKGROUND: Emerging imaging technologies such as real-time multispectral imaging (rMSI) hold great potential for simultaneous visualization of multiple target structures using fluorophores on various tumours including bladder cancer (BC). These technologies, however, require a multi-step preclinical evaluation process, including mouse models. OBJECTIVE: To demonstrate the suitability of the new rMSI technology for the detection of premalignant lesions and malignant BC in a preclinical mouse model using contrast agents. METHODS: Tumours were induced by N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN), which is known to induce BC in rodent models. In total, 30 mice (C57BL/6) were fed with 0.1% BBN ad libitum in drinking water for up to 5 months. Bladders were excised at 3 (n = 6) and 5 months (n = 24) of treatment and incubated ex vivo with Hexaminolevulinat (HAL, Hexvix®), CD47-FITC, CD90.2-FITC or a combination of CD90.2-FITC/CD47-FITC and HAL. The bladders were analyzed by an endoscopic rMSI prototype system equipped with a spectral filter (Chroma), a 4 mm endoscope (Karl Storz) with 30° optic, a LED light source and a PC with a microcontroller board. RESULTS: 5-month treatment of mice with 0.1% BBN led to the formation of squamous carcinoma (46%, n = 11) while urothelial carcinoma was observed only in one mouse (4%, n = 1). Carcinoma in situ (CIS) was detectable in twelve out of twenty-four mice (50%, n = 12) treated for 5 month and in three out of six mice (50%, n = 3) treated for 3 months.The metabolite of HAL, protoporphyrin IX (PpIX), could be reliably and specifically detected in all of mouse bladder tumours and CIS. However, detection of the CD90.2 surface marker was less reliable, potentially due to species- or tumour-subtype specificity. CONCLUSIONS: This model offers the potential for preclinical imaging studies with combined fluorescence targets, e.g. HAL, in combination with BC-specific antibodies.

The value and limitations of urothelial bladder carcinoma molecular classifications to predict oncological outcomes and cancer treatment response: A systematic review and meta-analysis

AIM

To evaluate the predictive value of molecular subtypes on oncological outcomes and response to cancer treatment in patients with urothelial bladder carcinoma (UBC).

MATERIALS AND METHODS

A literature search using PubMed, Scopus, and Cochrane Library was conducted on April 2020 to identify relevant studies according to the preferred reporting items for systematic review and meta-analysis guidelines. The pooled overall survival (OS), cancer-specific survival (CSS), and progression-free survival were calculated using a fixed or random effects model.

RESULTS

We identified 66 studies (including 21,447 molecular subtype records) evaluating the impact of molecular classification on oncologic outcomes in patients with UBC. We found significant association of different molecular subtypes with OS, CSS, progression-free survival, recurrence-free survival, and response to treatment. Totally, 11 studies were included in the meta-analysis. Basal group and NE-like subtypes were associated with worse OS (pooled HR: 1.78, 95%CI: 1.49-2.12, and pooled HR: 2.67, 95%CI: 1.08-6.60, respectively) in patients with muscle invasive bladder cancer. Luminal group was also associated with worse CSS (pooled HR of 3.67, 95%CI: 2.19-6.14).

CONCLUSIONS

Based on these data, UBC molecular classifications are significant predictors of oncological outcomes and identify patients who are most likely to benefit from intensified or different therapies. The optimal consensus on molecular classification remains to be verified in well-designed prospective studies to allow precise prognostic and predictive value assessment.

Patient-Derived Urothelial Cancer Xenograft Models: A Systematic Review and Future Perspectives

BACKGROUND: Lack of appropriate models that recapitulate the diversity, heterogeneity, and tumor microenvironment of urothelial cancer (UC) is a limitation to preclinical models. Patient-derived xenograft (PDX) models are a promising tool to overcome some of these issues, and thus we present an up-to-date and comprehensive overview of UC PDX models to aid in their future use. OBJECTIVE: To provide an overview on methodology, applications and limitations as well as future perspectives on bladder cancer PDX models. METHODS: Literature searches using PubMed and Web of Science databases were performed for relevant articles according to the following MeSH terms: “urothelial carcinoma(s)” OR “urothelial cancer” OR “urothelial tumor” OR “bladder cancer(s)” OR “bladder carcinoma(s)” OR “transitional cell carcinoma(s)” AND “xenograft(s)” OR “xenotransplant” at December 6th, 2019. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS: Of the 49 studies extracted, 41 studies after the year 2000 were finally analyzed. Published studies show that (1) UC PDX platforms retained the histology and genomic characteristics of the corresponding patient tumors. (2) UC PDX can be applied to ask various questions including to study the mechanisms of disease progression and treatment resistance, to develop novel drugs and biomarkers, as well as to potentially realize personalized drug selection. Recent topics of research using PDX have included the development of humanized mice as well as the use of 3D culture to complement some of the limitations of PDX models. CONCLUSIONS: UC PDX models serve as tools for understanding cancer biology, drug development and empowering precision medicine. The improvement of experimental systems using humanized mice to recapitulate the immune microenvironment of tumors will optimize UC PDX to study future questions in the field of immunotherapy.

The role of CDC25C in cell cycle regulation and clinical cancer therapy: a systematic review

One of the most prominent features of tumor cells is uncontrolled cell proliferation caused by an abnormal cell cycle, and the abnormal expression of cell cycle-related proteins gives tumor cells their invasive, metastatic, drug-resistance, and anti-apoptotic abilities. Recently, an increasing number of cell cycle-associated proteins have become the candidate biomarkers for early diagnosis of malignant tumors and potential targets for cancer therapies. As an important cell cycle regulatory protein, Cell Division Cycle 25C (CDC25C) participates in regulating G2/M progression and in mediating DNA damage repair. CDC25C is a cyclin of the specific phosphatase family that activates the cyclin B1/CDK1 complex in cells for entering mitosis and regulates G2/M progression and plays an important role in checkpoint protein regulation in case of DNA damage, which can ensure accurate DNA information transmission to the daughter cells. The regulation of CDC25C in the cell cycle is affected by multiple signaling pathways, such as cyclin B1/CDK1, PLK1/Aurora A, ATR/CHK1, ATM/CHK2, CHK2/ERK, Wee1/Myt1, p53/Pin1, and ASK1/JNK-/38. Recently, it has evident that changes in the expression of CDC25C are closely related to tumorigenesis and tumor development and can be used as a potential target for cancer treatment. This review summarizes the role of CDC25C phosphatase in regulating cell cycle. Based on the role of CDC25 family proteins in the development of tumors, it will become a hot target for a new generation of cancer treatments.

Current status and perspectives of patient-derived xenograft models in cancer research

Cancers remain a major public health problem worldwide, which still require profound research in both the basic and preclinical fields. Patient-derived xenograft (PDX) models are created when cancerous cells or tissues from patients' primary tumors are implanted into immunodeficient mice to simulate human tumor biology in vivo, which have been extensively used in cancer research. The routes of implantation appeared to affect the outcome of PDX research, and there has been increasing applications of patient-derived orthotopic xenograft (PDOX) models. In this review, we firstly summarize the methodology to establish PDX models and then go over recent application and function of PDX models in basic cancer research on the areas of cancer characterization, initiation, proliferation, metastasis, and tumor microenvironment and in preclinical explorations of anti-cancer targets, drugs, and therapeutic strategies and finally give our perspectives on the future prospects of PDX models.

Patient-derived xenografts as in vivo models for research in urological malignancies

Lack of appropriate models that recapitulate the complexity and heterogeneity of urological tumours precludes most of the preclinical reagents that target urological tumours from receiving regulatory approval. Patient-derived xenograft (PDX) models are characterized by direct engraftment of patient-derived tumour fragments into immunocompromised mice. PDXs can maintain the original histology, as well as the molecular and genetic characteristics of the source tumour. Thus, PDX models have various advantages over conventional cell-line-derived xenograft (CDX) and other models, which has resulted in an increase in the use of urological tumour PDXs in the analysis of tumour biology and, importantly, for drug development and treatment decisions in personalized medicine. PDX models of urological malignancies have great potential to be used for both basic and clinical research, but limitations exist and need to be overcome. In particular, several agents targeting the immune system have shown promising results in kidney and bladder cancer; however, establishing PDX models in mice with an intact immune system so that an immune response against the tumour is triggered is important to investigate these new therapeutics. Moreover, international collaboration to share PDX models is essential for research concerning fatal urological tumours.