Genomic Deletion of BAP1 and CDKN2A Are Useful Markers for Quality Control of Malignant Pleural Mesothelioma (MPM) Primary Cultures

3-Dimensional mesothelioma spheroids provide closer to natural pathophysiological tumor microenvironment for drug response studies

Traditional studies using cancer cell lines are often performed on a two-dimensional (2D) cell culture model with a low success rate of translating to Phase I or Phase II clinical studies. In comparison, with the advent of developments three-dimensional (3D) cell culture has been championed as the latest cellular model system that better mimics in vivo conditions and pathological conditions such as cancer. In comparison to biospecimens taken from in vivo tissue, the details of gene expression of 3D culture models are largely undefined, especially in mesothelioma – an aggressive cancer with very limited effective treatment options. In this study, we examined the veracity of the 3D mesothelioma cell culture model to study cell-to-cell interaction, gene expression and drug response from 3D cell culture, and compared them to 2D cell and tumor samples. We confirmed via SEM analysis that 3D cells grown using the spheroid methods expressed highly interconnected cell-to-cell junctions. The 3D spheroids were revealed to be an improved mini-tumor model as indicated by the TEM visualization of cell junctions and microvilli, features not seen in the 2D models. Growing 3D cell models using decellularized lung scaffold provided a platform for cell growth and infiltration for all cell types including primary cell lines. The most time-effective method was growing cells in spheroids using low-adhesive U-bottom plates. However, not every cell type grew into a 3D model using the the other methods of hanging drop or poly-HEMA. Cells grown in 3D showed more resistance to chemotherapeutic drugs, exhibiting reduced apoptosis. 3D cells stained with H&E showed cell-to-cell interactions and internal architecture that better represent that of in vivo patient tumors when compared to 2D cells. IHC staining revealed increased protein expression in 3D spheroids compared to 2D culture. Lastly, cells grown in 3D showed very different microRNA expression when compared to that of 2D counterparts. In conclusion, 3D cell models, regardless of which method is used. Showed a more realistic tumor microenvironment for architecture, gene expression and drug response, when compared to 2D cell models, and thus are superior preclinical cancer models.

Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration

Background

p16, p53, and proliferating cell nuclear antigen (pcna) genes play significant roles in many chromatin modifications and have been found to be highly expressed in a variety of tumor tissues. Therefore, they have been used as target genes for some tumor therapies. However, the differential expressions of the p16, p53, and pcna genes in human sarcomas and their effects on prognosis have not been widely reported.

Methods

The Oncomine dataset was used to analyze the transcription levels of p16, p53, and pcna genes, and the gene expression profile interactive analysis (GEPIA) dataset was used to analyze the differential expressions of p16, p53, and pcna. The expression levels of p16, p53, and pcna were further analyzed by Western Blotting. GEPIA and Kaplan–Meier analyses were used to analyze the prognostic value of p16, p53, and pcna. Furthermore, p16, p53, and pcna gene mutations and their association with overall survival (OS) and disease-free survival (DFS) were analyzed using cBioPortal datasets. In addition, genes co-expressed with p16, p53, and pcna were analyzed using Oncomine. The DAVID dataset was used to analyze the functional enrichment of p16, p53, pcna, and their co-expressed genes by Gene Ontology (GO) and Metascape were used to construct a network map. Finally, the immune cell infiltration of p16, p53, and pcna in patients with sarcoma was reported by Tumor Immune Estimation Resource (TIMER).

Results

p16, p53, and pcna were up-regulated in human sarcoma tissues and almost all sarcoma cell lines. Western Blotting showed that the expression of p16, p53, and pcna was elevated in osteosarcoma cell lines. The expression of pcna was correlated with OS, the expression of p16, p53, and pcna was correlated with relapse-free survival, and the genetic mutation of p16 was negatively correlated with OS and DFS. We also found that p16, p53, and pcna genes were positively/negatively correlated with immune cell infiltration in sarcoma.

Conclusions

The results of this study showed that p16, p53, and pcna can significantly affect the survival and immune status of sarcoma patients. Therefore, p16, p53, and pcna could be used as potential biomarkers of prognosis and immune infiltration in human sarcoma and provide a possible therapeutic target for sarcoma.

CDKN2A and MTAP Are Useful Biomarkers Detectable by Droplet Digital PCR in Malignant Pleural Mesothelioma: A Potential Alternative Method in Diagnosis Compared to Fluorescence In Situ Hybridisation

Background

The diagnosis of malignant pleural mesothelioma (MPM) can be difficult, in part due to the difficulty in distinguishing between MPM and reactive mesothelial hyperplasia (RMH). The tumor suppressor gene, CDKN2A, is frequently silenced by epigenetic mechanisms in many cancers; in the case of MPM it is mostly silenced via genomic deletion. Co-deletion of the CDKN2A and methylthioadenosine phosphorylase (MTAP) genes has been researched extensively and discovered to be a highly specific characteristic of MPM. Most studies have used FISH to detect the deletion of CDKN2A and IHC for MTAP as a surrogate for this. In this study, we aim to investigate and validate droplet digital PCR (ddPCR) as an emerging alternative and efficient testing method in diagnosing MPM, by particularly emphasizing on the loss of MTAP and CDKN2A.

Methods

This study included 75 formalin fixed paraffin embedded (FFPE) MPM tissue, and 12 normal pleural tissue and 10 RMH as control. Additionally, primary MPM cell lines and normal pleural samples were used as biomarker detection controls, as established in our previous publication. All FFPE specimens were processed to isolate the DNA, that was subsequently used for ddPCR detection of CDKN2A and MTAP. FFPE samples were also analyzed by fluorescence in situ hybridization (FISH) for CDKN2A and MTAP deletion, and for MTAP IHC expression. Concordance of IHC and ddPCR with FISH were studied in these samples.

Results

95% and 82% of cases showed co-deletion of both MTAP and CDKN2A when determined by FISH and ddPCR respectively. ddPCR has a sensitivity of 72% and specificity of 100% in detecting CDKN2A homozygous loss in MPM. ddPCR also has a concordance rate of 92% with FISH in detecting homozygous loss of CDKN2A. MTAP IHC was 68% sensitive and 100% specific for detecting CDKN2A homozygous loss in MPM when these losses were determined by ddPCR.

Conclusion

Our study confirms that MTAP is often co-deleted with CDKN2A in MPM. Our in-house designed ddPCR assays for MTAP and CDKN2A are useful in differentiating MPM from RMH, and is highly concordant with FISH that is currently used in diagnosing MPM. ddPCR detection of these genetic losses can potentially be utilized as an alternative method in the diagnosis of MPM and for the future development of a less-invasive MPM-specific detection technique on MPM tumor tissue DNA.

An Emerging Model for Cancer Development from a Tumor Microenvironment Perspective in Mice and Humans

In the past, cancer development was studied in terms of genetic mutations acquired in cancer cells at each stage of the development. We present an emerging model for cancer development in which the tumor microenvironment (TME) plays an integral part. In this model, the tumor development is initiated by a slowly growing nearly homogeneous colony of cancer cells that can evade detection by the cell's innate mechanism of immunity such as natural killer (NK) cells (first stage; colonization). Subsequently, the colony develops into a tumor filled with lymphocytes and stromal cells, releasing pro-inflammatory cytokines, growth factors, and chemokines (second stage; lymphocyte infiltration). Cancer progression proceeds to a well-vesiculated silent tumor releasing no inflammatory signal, being nearly devoid of lymphocytes (third stage; silenced). Eventually some cancer cells within a tumor undertake epithelial-to-mesenchymal transition (EMT), which leads to cancer metastasis (fourth stage; EMT). If a circulating metastasized cancer cell finds a niche in a new tissue and evades detection by NK cells, it can establish a new colony in which very few stromal cells are present (fifth stage; metastasis), which is much like a colony at the first stage of development. At every stage, cancer cells influence their own TME, and in turn, the TME influences the cancer cells contained within, either by direct interaction between cancer cells and stromal cells or through exchange of cytokines. In this article, we examine clinical findings and animal experiments pertaining to this paradigm-shifting model and consider if, indeed, some aspects of cancer development are governed solely by the TME.

Special Issue on Mechanisms of Mesothelioma Heterogeneity: Highlights and Open Questions

This editorial aims to synthesize the eleven papers that have contributed to this special issue, where the mechanisms of mesothelioma heterogeneity have been tackled from different angles.