Incidental germline findings during molecular profiling of tumor tissues for precision oncology: molecular survey and methodological obstacles

Background A fraction of patients referred for complex molecular profiling of biopsied tumors may harbor germline variants in genes associated with the development of hereditary cancer syndromes (HCS). Neither the bioinformatic analysis nor the reporting of such incidental germline findings are standardized. Methods Data from Next-Generation Sequencing (NGS) of biopsied tumor samples referred for complex molecular profiling were analyzed for germline variants in HCS-associated genes. Analysis of variant origin was performed employing bioinformatic algorithms followed by manual curation. When possible, the origin of the variant was validated by Sanger sequencing of the sample of normal tissue. The variants’ pathogenicity was assessed according to ACMG/AMP. Results Tumors were sampled from 183 patients (Males: 75 [41.0%]; Females: 108 [59.0%]; mean [SD] age, 57.7 [13.3] years) and analysed by targeted NGS. The most common tumor types were colorectal (19%), pancreatic (13%), and lung cancer (10%). A total of 56 sequence variants in genes associated with HCS were detected in 40 patients. Of them, 17 variants found in 14 patients were predicted to be of germline origin, with 6 variants interpreted as pathogenic (PV) or likely pathogenic (LPV), and 9 as variants of uncertain significance (VUS). For the 41 out of 42 (97%) missense variants in HCS-associated genes, the results of computational prediction of variant origin were concordant with that of experimental examination. We estimate that Sanger sequencing of a sample of normal tissue would be required for ~ 1–7% of the total assessed cases with PV or LPV, when necessity to follow with genetic counselling referral in ~ 2–15% of total assessed cases (PV, LPV or VUS found in HCS genes). Conclusion Incidental findings of pathogenic germline variants are common in data from cancer patients referred for complex molecular profiling. We propose an algorithm for the management of patients with newly detected variants in genes associated with HCS.

Personalized 3-Gene Panel for Prostate Cancer Target Therapy

Many years and billions spent for research did not yet produce an effective answer to prostate cancer (PCa). Not only each human, but even each cancer nodule in the same tumor, has unique transcriptome topology. The differences go beyond the expression level to the expression control and networking of individual genes. The unrepeatable heterogeneous transcriptomic organization among men makes the quest for universal biomarkers and “fit-for-all” treatments unrealistic. We present a bioinformatics procedure to identify each patient’s unique triplet of PCa Gene Master Regulators (GMRs) and predict consequences of their experimental manipulation. The procedure is based on the Genomic Fabric Paradigm (GFP), which characterizes each individual gene by the independent expression level, expression variability and expression coordination with each other gene. GFP can identify the GMRs whose controlled alteration would selectively kill the cancer cells with little consequence on the normal tissue. The method was applied to microarray data on surgically removed prostates from two men with metastatic PCas (each with three distinct cancer nodules), and DU145 and LNCaP PCa cell lines. The applications verified that each PCa case is unique and predicted the consequences of the GMRs’ manipulation. The predictions are theoretical and need further experimental validation.

Fluorescence Molecular Targeting of Colon Cancer to Visualize the Invisible

Colorectal cancer (CRC) is a common cause of cancer and cancer-related death. Surgery is the only curative modality. Fluorescence-enhanced visualization of CRC with targeted fluorescent probes that can delineate boundaries and target tumor-specific biomarkers can increase rates of curative resection. Approaches to enhancing visualization of the tumor-to-normal tissue interface are active areas of investigation. Nonspecific dyes are the most-used approach, but tumor-specific targeting agents are progressing in clinical trials. The present narrative review describes the principles of fluorescence targeting of CRC for diagnosis and fluorescence-guided surgery with molecular biomarkers for preclinical or clinical evaluation.

An algorithm for thoracic re-irradiation using biologically effective dose: a common language on how to treat in a “no-treat zone”

Background Re-irradiation (re-RT) is a technically challenging task for which few standardized approaches exist. This is in part due to the lack of a common platform to assess dose tolerance in relation to toxicity in the re-RT setting. To better address this knowledge gap and provide new tools for studying and developing thresholds for re-RT, we developed a novel algorithm that allows for anatomically accurate three-dimensional mapping of composite biological effective dose (BED) distributions from nominal doses (Gy). Methods The algorithm was designed to automatically convert nominal dose from prior treatment plans to corresponding BED value maps (voxel size 2.5 mm3 and α/β of 3 for normal tissue, BED3). Following the conversion of each plan to a BED3 dose distribution, deformable registration was used to create a summed composite re-irradiation BED3 plan for each patient who received two treatments. A proof-of-principle analysis was performed on 38 re-irradiation cases of initial stereotactic ablative radiotherapy (SABR) followed by either re-SABR or chemoradiation for isolated locoregional recurrence of early-stage non-small cell lung cancer. Results Evaluation of the algorithm-generated maps revealed appropriate conversion of physical dose to BED at each voxel. Of 14 patients receiving repeat SABR, there was one case each of grade 3 chest wall pain (7%), pneumonitis (7%), and dyspnea (7%). Of 24 patients undergoing repeat fractionated radiotherapy, grade 3 events were limited to two cases each of pneumonitis and dyspnea (8%). Composite BED3 dosimetry for each patient who experienced grade 2–3 events is provided and may help guide development of precise cumulative dose thresholds for organs at risk in the re-RT setting. Conclusions This novel algorithm successfully created a voxel-by-voxel composite treatment plan using BED values. This approach may be used to more precisely examine dosimetric predictors of toxicities and to establish more accurate normal tissue constraints for re-irradiation.

Identification of a Key Glioblastoma Candidate Gene, FUBP3, Based on Weighted Gene Co-expression Network Analysis

Background: Glioblastoma multiforme (GBM) is the most common aggressive malignant brain tumor. However, the molecular mechanism of glioblastoma formation is still poorly understood. To identify candidate genes that may be connected to glioma growth and development, weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network between gene sets and clinical characteristics. We also explored the function of the key candidate gene.Methods: Two GBM datasets were selected from GEO Datasets. The R language was used to identify differentially expressed genes. WGCNA was used to construct a gene co-expression network in the GEO glioblastoma samples. A custom Venn diagram website was used to find the intersecting genes. The GEPIA website was used for survival analysis to determine the significant gene, FUBP3. OS,DSS, and PFI analyses, based on the UCSC Cancer Genomics Browser, were performed to verify the significance of FUBP3. Immunohistochemistry was performed to evaluate the expression of FUBP3 in glioblastoma and adjacent normal tissue. KEGG and GO enrichment analyses were used to reveal possible functions of FUBP3. Microenvironment analysis was used to explore the relationship between FUBP3 and immune infiltration. Immunohistochemistry was performed to verify the results of the microenvironment analysis.Results: GSE70231 and GSE108474 were selected from GEO Datasets, then 715 and 694 differentially expressed genes (DEGs) from GSE70231 and GSE108474, respectively, were identified. We then performed weighted gene co-expression network analysis (WGCNA) and identified the most downregulated gene modules of GSE70231 and GSE108474, and 659 and 3915 module genes from GSE70231 and GSE108474, respectively, were selected. Five intersection genes (FUBP3, DAD1, CLIC1, ABR, and DNM1) were calculated by Venn diagram. FUBP3 was then identified as the only significant gene by survival analysis using the GEPIA website. OS, DSS, and PFI analyses verified the significance of FUBP3. Immunohistochemical analysis revealed FUBP3 expression in GBM and adjacent normal tissue. KEGG and GO analyses uncovered the possible function of FUBP3 in GBM. Tumor microenvironment analysis showed that FUBP3 may be connected to immune infiltration, and immunohistochemistry identified a positive correlation between immune cells (CD4+ T cells, CD8+ T cells, and macrophages) and FUBP3.Conclusion: FUBP3 is associated with immune surveillance in GBM, indicating that it has a great impact on GBM development and progression. Therefore, interventions involving FUBP3 and its regulatory pathway may be a new approach for GBM treatment.

Identification of Five Cytotoxicity-Related Genes Involved in the Progression of Triple-Negative Breast Cancer

Background: Breast cancer is one of the deadly tumors in women, and its incidence continues to increase. This study aimed to identify novel therapeutic molecules using RNA sequencing (RNA-seq) data of breast cancer from our hospital.Methods: 30 pairs of human breast cancer tissue and matched normal tissue were collected and RNA sequenced in our hospital. Differentially expressed genes (DEGs) were calculated with raw data by the R package “edgeR”, and functionally annotated using R package “clusterProfiler”. Tumor-infiltrating immune cells (TIICs) were estimated using a website tool TIMER 2.0. Effects of key genes on therapeutic efficacy were analyzed using RNA-seq data and drug sensitivity data from two databases: the Cancer Cell Line Encyclopedia (CCLE) and the Cancer Therapeutics Response Portal (CTRP).Results: There were 2,953 DEGs between cancerous and matched normal tissue, as well as 975 DEGs between primary breast cancer and metastatic breast cancer. These genes were primarily enriched in PI3K-Akt signaling pathway, calcium signaling pathway, cAMP signaling pathway, and cell cycle. Notably, CD8+ T cell, M0 macrophage, M1 macrophage, regulatory T cell and follicular helper T cell were significantly elevated in cancerous tissue as compared with matched normal tissue. Eventually, we found five genes (GALNTL5, MLIP, HMCN2, LRRN4CL, and DUOX2) were markedly corelated with CD8+ T cell infiltration and cytotoxicity, and associated with therapeutic response.Conclusion: We found five key genes associated with tumor progression, CD8+ T cell and therapeutic efficacy. The findings would provide potential molecular targets for the treatment of breast cancer.

Alterations in the Ca2+ toolkit in oesophageal adenocarcinoma

Aim: To investigate alterations in transcription of genes, encoding Ca2+ toolkit proteins, in oesophageal adenocarcinoma (OAC) and to assess associations between gene expression, tumor grade, nodal-metastatic stage, and patient survival. Methods: The expression of 275 transcripts, encoding components of the Ca2+ toolkit, was analyzed in two OAC datasets: the Cancer Genome Atlas [via the University of Alabama Cancer (UALCAN) portal] and the oesophageal-cancer, clinical, and molecular stratification [Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS)] dataset. Effects of differential expression of these genes on patient survival were determined using Kaplan-Meier log-rank tests. OAC grade- and metastatic-stage status was investigated for a subset of genes. Adjustment for the multiplicity of testing was made throughout. Results: Of the 275 Ca2+-toolkit genes analyzed, 75 displayed consistent changes in expression between OAC and normal tissue in both datasets. The channel-encoding genes, N-methyl-D-aspartate receptor 2D (GRIN2D), transient receptor potential (TRP) ion channel classical or canonical 4 (TRPC4), and TRP ion channel melastatin 2 (TRPM2) demonstrated the greatest increase in expression in OAC in both datasets. Nine genes were consistently upregulated in both datasets and were also associated with improved survival outcomes. The 6 top-ranking genes for the weighted significance of altered expression and survival outcomes were selected for further analysis: voltage-gated Ca2+ channel subunit α 1D (CACNA1D), voltage-gated Ca2+ channel auxiliary subunit α2 δ4 (CACNA2D4), junctophilin 1 (JPH1), acid-sensing ion channel 4 (ACCN4), TRPM5, and secretory pathway Ca2+ ATPase 2 (ATP2C2). CACNA1D, JPH1, and ATP2C2 were also upregulated in advanced OAC tumor grades and nodal-metastatic stages in both datasets. Conclusions: This study has unveiled alterations of the Ca2+ toolkit in OAC, compared to normal tissue. Such Ca2+ signalling findings are consistent with those from studies on other cancers. Genes that were consistently upregulated in both datasets might represent useful markers for patient diagnosis. Genes that were consistently upregulated, and which were associated with improved survival, might be useful markers for patient outcome. These survival-associated genes may also represent targets for the development of novel chemotherapeutic agents.