BRAFV600E mutational status assessment in cutaneous melanocytic neoplasms in a group of the Egyptian population.

BACKGROUND: Melanocytic neoplasms range from banal nevi to malignant melanomas. The genetic background has been extensively studied in the Caucasian population. BRAF mutations were reported among the early driver mutations in nevogenesis. Nevertheless, the pathogenesis in the Egyptian population has not been elucidated. AIM AND METHODS: The present study was carried out to assess the sensitivity and specificity of immunohistochemistry (IHC) using the RM-08 clone in reference to allele-specific real-time PCR (CAST-PCR) for the detection of the BRAF V600E mutation in 50 formalin-fixed paraffin-embedded blocks of melanocytic neoplasms with prior bleaching using hydrogen peroxide in Tris-HCL and Bovine Serum Albumin respectively. RESULTS: IHC staining was interpreted using staining reaction (positive versus negative) and staining pattern (negative and heterogeneous versus homogenous). Using the staining pattern, the specificity increased from 73.3 to 88.2%, the negative predictive value increased from 73.3 to 100%, the diagnostic accuracy increased from 71.4 to 90.48% and the overall accuracy increased from 69.9 to 77.3%. The sensitivity and positive predictive value remained unchanged. The K-agreement coefficient increased from 0.364 (fair agreement) to 0.741 (good agreement) and was statistically significant (p = 0.00). Next-generation sequencing was performed in 11 cases, 8 cases with IHC-positive and BRAF wild type in addition to 3 cases that failed PCR analysis and revealed no BRAF V600E. No statistically significant difference was found in the clinicopathological parameters between BRAF V600E and BRAF wild-type melanomas. CONCLUSIONS: These findings suggest that IHC staining homogeneity may be more accurate in predicting BRAF V600E mutational status. However, IHC cannot replace molecular methods.

Evaluation of Galanin Expression in Colorectal Cancer: An Immunohistochemical and Transcriptomic Study.

Colorectal cancer (CRC) represents around 10% of all cancers, with an increasing incidence in the younger age group. The gut is considered a unique organ with its distinctive neuronal supply. The neuropeptide, human galanin, is widely distributed in the colon and expressed in many cancers, including the CRC. The current study aimed to explore the role of galanin at different stages of CRC. Eighty-one CRC cases (TNM stages I - IV) were recruited, and formalin-fixed paraffin-embedded samples were analyzed for the expression of galanin and galanin receptor 1 (GALR1) by immunohistochemistry (IHC). Galanin intensity was significantly lower in stage IV (n= 6) in comparison to other stages (p= 0.037 using the Mann-Whitney U test). Whole transcriptomics analysis using NGS was performed for selected samples based on the galanin expression by IHC [early (n=5) with high galanin expression and late (n=6) with low galanin expression]. Five differentially regulated pathways (using Absolute GSEA) were identified as drivers for tumor progression and associated with higher galanin expression, namely, cell cycle, cell division, autophagy, transcriptional regulation of TP53, and immune system process. The top shared genes among the upregulated pathways are AURKA, BIRC5, CCNA1, CCNA2, CDC25C, CDK2, CDK6, EREG, LIG3, PIN1, TGFB1, TPX2. The results were validated using real-time PCR carried out on four cell lines [two primaries (HCT116 and HT29) and two metastatic (LoVo and SK-Co-1)]. The current study shows galanin as a potential negative biomarker. Galanin downregulation is correlated with advanced CRC staging and linked to cell cycle and division, autophagy, transcriptional regulation of TP53 and immune system response.

Expression of GPR68, an Acid-Sensing Orphan G Protein-Coupled Receptor, in Breast Cancer.

Breast cancer (BC) is the most diagnosed cancer and the leading cause of global cancer incidence in 2020. It is quite known that highly invasive cancers have disrupted metabolism that leads to the creation of an acidic tumor microenvironment. Among the proton-sensing G protein-coupled receptors is GPR68. In this study, we aimed to explore the expression pattern of GPR68 in tissues from BC patients as well as different BC cell lines. METHODS: In-silico tools were used to assess the expression of GPR68 in BC patients. The expression pattern was validated in fresh and paraffin-embedded sections of BC patients using qPCR and immunohistochemistry (IHC), respectively. Also, in-silico tools investigated GPR68 expression in different BC cell lines. Validation of GPR68 expression was performed using qPCR and immunofluorescence techniques in four different BC cell lines (MCF-7, MDA-MB-231, BT-549 and SkBr3). RESULTS: GPR68 expression was found to be significantly increased in BC patients using the in-silico tools and validation using qPCR and IHC. Upon classification according to the molecular subtypes, the luminal subtype showed the highest GPR68 expression followed by triple-negative and Her2-enriched cells. However, upon validation in the recruited cohort, the triple-negative molecular subtype of BC patients showed the highest GPR68 expression. Also, in-silico and validation data revealed that the triple-negative breast cancer cell line MDA-MB-231 showed the highest expression of GPR68. CONCLUSION: Therefore, this study highlights the potential utilization of GPR68 as a possible diagnostic and/or prognostic marker in BC.

M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient Outcome.

Background: Breast cancer heterogeneity is an essential element that plays a role in the therapy response variability and the patient's outcome. This highlights the need for more precise subtyping methods that focus not only on tumor cells but also investigate the profile of stromal cells as well as immune cells. Objectives: To mine publicly available transcriptomic breast cancer datasets and reanalyze their transcriptomic profiling using unsupervised clustering in order to identify novel subsets in molecular subtypes of breast cancer, then explore the stromal and immune cells profile in each subset using bioinformatics and systems immunology approaches. Materials and Methods: Transcriptomic data from 1,084 breast cancer patients obtained from The Cancer Genome Atlas (TCGA) database were extracted and subjected to unsupervised clustering using a recently described, multi-step algorithm called Iterative Clustering and Guide-gene Selection (ICGS). For each cluster, the stromal and immune profile was investigated using ESTIMATE and CIBERSORT analytical tool. Clinical outcomes and differentially expressed genes of the characterized clusters were identified and validated in silico and in vitro in a cohort of 80 breast cancer samples by immunohistochemistry. Results: Seven unique sub-clusters showed distinct molecular and clinical profiles between the well-known breast cancer subtypes. Those unsupervised clusters identified more homogenous subgroups in each of the classical subtypes with a different prognostic profile. Immune profiling of the identified clusters showed that while the classically activated macrophages (M1) are correlated with the more aggressive basal-like breast cancer subtype, the alternatively activated macrophages (M2) showed a higher level of infiltration in luminal A and luminal B subtypes. Indeed, patients with higher levels of M1 expression showed less advanced disease and better patient outcomes presented as prolonged overall survival. Moreover, the M1 high basal-like breast cancer group showed a higher expression of interferon-gamma induced chemokines and guanylate-binding proteins (GBPs) involved in immunity against microbes. Conclusion: Adding immune profiling using transcriptomic data can add precision for diagnosis and prognosis and can cluster patients according to the available modalities of therapy in a more personalized approach.