GenVisR: Genomic Visualizations in R

DNA Methylation Identifies Epigenetic Subtypes of Triple-Negative Breast Cancers With Distinct Clinicopathologic and Molecular Features

Triple-negative breast cancers (TNBC) include diverse carcinomas with heterogeneous clinical behavior. DNA methylation is a useful tool in classifying a variety of cancers. In this study, we analyzed TNBC using DNA methylation profiling and compared the results to those of mutational analysis. DNA methylation profiling (Infinium MethylationEPIC array, Illumina) and 50-gene panel-targeted DNA sequencing were performed in 44 treatment-naïve TNBC. We identified 3 distinct DNA methylation clusters with specific clinicopathologic and molecular features. Cluster 1 (phosphoinositide 3-kinase/protein kinase B-enriched cluster; n = 9) patients were significantly older (mean age, 71 years; P = .008) with tumors that were more likely to exhibit apocrine differentiation (78%; P < .001), a lower grade (44% were grade 2), a lower proliferation index (median Ki-67, 15%; P = .002), and lower tumor-infiltrating lymphocyte fractions (median, 15%; P = .0142). Tumors carried recurrent PIK3CA and AKT1 mutations and a higher percentage of low HER-2 expression (89%; P = .033). Cluster 3 (chromosomal instability cluster; n = 28) patients were significantly younger (median age, 57 years). Tumors were of higher grade (grade 3, 93%), had a higher proliferation index (median Ki-67, 75%), and were with a high fraction of tumor-infiltrating lymphocytes (median, 30%). Ninety-one percent of the germline BRCA1/2 mutation carriers were in cluster 3, and these tumors showed the highest level of copy number alterations. Cluster 2 represented cases with intermediate clinicopathologic characteristics and no specific molecular profile (no specific molecular profile cluster; n = 7). There were no differences in relation to stage, recurrence, and survival. In conclusion, DNA methylation profiling is a promising tool to classify patients with TNBC into biologically relevant groups, which may result in better disease characterization and reveal potential targets for emerging therapies.

Gene-Environment Analyses in a UK Biobank Skin Cancer Cohort Identifies Important SNPs in DNA Repair Genes That May Help Prognosticate Disease Risk

BACKGROUND

Despite well-established relationships between sun exposure and skin cancer pathogenesis/progression, specific gene-environment interactions in at-risk individuals remain poorly-understood.

METHODS

We leveraged a UK Biobank cohort of basal cell carcinoma (BCC, n = 17,221), cutaneous squamous cell carcinoma (cSCC, n = 2,331), melanoma in situ (M-is, n = 1,158), invasive melanoma (M-inv, n = 3,798), and healthy controls (n = 448,164) to quantify the synergistic involvement of genetic and environmental factors influencing disease risk. We surveyed 8,798 SNPs from 190 DNA repair genes, and 11 demographic/behavioral risk factors.

RESULTS

Clinical analysis identified darker skin (RR = 0.01-0.65) and hair (RR = 0.27-0.63) colors as protective factors. Eleven SNPs were significantly associated with BCC, three of which were also associated with M-inv. Gene-environment analysis yielded 201 SNP-environment interactions across 90 genes (FDR-adjusted q < 0.05). SNPs from the FANCA gene showed interactions with at least one clinical factor in all cancer groups, of which three (rs9926296, rs3743860, rs2376883) showed interaction with nearly every factor in BCC and M-inv.

CONCLUSIONS

We identified novel risk factors for keratinocyte carcinomas and melanoma, highlighted the prognostic value of several FANCA alleles among individuals with a history of sunlamp use and childhood sunburns, and demonstrated the importance of combining genetic and clinical data in disease risk stratification.

IMPACT

This study revealed genome-wide associations with important implications for understanding skin cancer risk in the context of the rapidly-evolving field of precision medicine. Major individual factors (including sex, hair and skin color, and sun protection use) were significant mediators for all skin cancers, interacting with >200 SNPs across four skin cancer types.

Immune-related gene-based model predicts the survival of colorectal carcinoma and reflected various biological statuses

Bakcground: Prognosis of colorectal cancer (CRC) varies due to complex genetic-microenviromental interactions, and multiple gene-based prognostic models have been highlighted. Material and Method: In this work, the immune-related genes' expression-based model was developed and the scores of each sample were calculated. The correlation between the model and clinical information, immune infiltration, drug response and biological pathways were analyzed. Results: The high-score samples have a significantly longer survival (overall survival and progression-free survival) period than those with a low score, which was validated across seven datasets containing 1,325 samples (GSE17536 (N = 115), GSE17537 (N = 55), GSE33113 (N = 90), GSE37892 (N = 130), GSE38832 (N = 74), GSE39582 (N = 481), and TCGA (N = 380)). The score is significantly associated with clinical indicators, including age and stage, and further associated with PD-1/PD-L1 gene expression. Furthermore, high-score samples have significantly higher APC and a lower MUC5B mutation rate. The high-score samples show more immune infiltration (including CD4+ and CD8+ T cells, M1/M2 macrophages, and NK cells). Enriched pathway analyses showed that cancer-related pathways, including immune-related pathways, were significantly activated in high-score samples and that some drugs have significantly lower IC50 values than those with low score. Conclusion: The model developed based on immune-related genes is robust and reflected various statuses of CRC and may be a potential clinical indicator.

Colorectal Cancer Organoid-Stroma Biobank Allows Subtype-Specific Assessment of Individualized Therapy Responses

In colorectal cancers, the tumor microenvironment plays a key role in prognosis and therapy efficacy. Patient-derived tumor organoids (PDTO) show enormous potential for preclinical testing; however, cultured tumor cells lose important characteristics, including the consensus molecular subtypes (CMS). To better reflect the cellular heterogeneity, we established the colorectal cancer organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAF) from 30 patients. Context-specific phenotyping showed that xenotransplantation or coculture with CAFs improves the transcriptomic fidelity and instructs subtype-specific stromal gene expression. Furthermore, functional profiling in coculture exposed CMS4-specific therapeutic resistance to gefitinib and SN-38 and prognostic expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as a common target. Our results demonstrate that colorectal cancer phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for a faithful representation of molecular subtypes and therapy responses ex vivo.

SIGNIFICANCE

Systematic characterization of the organoid-stroma biobank provides a resource for context dependency in colorectal cancer. We demonstrate a colorectal cancer subtype memory of PDTOs that is independent of specific driver mutations. Our data underscore the importance of functional profiling in cocultures for improved preclinical testing and identification of stromal resistance mechanisms. This article is featured in Selected Articles from This Issue, p. 2109.

Mitogen-induced defective mitosis transforms neural progenitor cells

BACKGROUND

Chromosome instability (CIN) with recurrent copy number alterations is a feature of many solid tumors, including glioblastoma (GBM), yet the genes that regulate cell division are rarely mutated in cancers. Here, we show that the brain-abundant mitogen, platelet-derived growth factor-A (PDGFA) fails to induce the expression of kinetochore and spindle assembly checkpoint genes leading to defective mitosis in neural progenitor cells (NPCs).

METHODS

Using a recently reported in vitro model of the initiation of high-grade gliomas from murine NPCs, we investigated the immediate effects of PDGFA exposure on the nuclear and mitotic phenotypes and patterns of gene and protein expression in NPCs, a putative GBM cell of origin.

RESULTS

NPCs divided abnormally in defined media containing PDGFA with P53-dependent effects. In wild-type cells, defective mitosis was associated with P53 activation and cell death, but in some null cells, defective mitosis was tolerated. Surviving cells had unstable genomes and proliferated in the presence of PDGFA accumulating random and clonal chromosomal rearrangements. The outcome of this process was a population of tumorigenic NPCs with recurrent gains and losses of chromosomal regions that were syntenic to those recurrently gained and lost in human GBM. By stimulating proliferation without setting the stage for successful mitosis, PDGFA-transformed NPCs lacking P53 function.

CONCLUSIONS

Our work describes a mechanism of transformation of NPCs by a brain-associated mitogen, raising the possibility that the unique genomic architecture of GBM is an adaptation to defective mitosis that ensures the survival of affected cells.

A prognostic model based on regulatory T-cell-related genes in gastric cancer: Systematic construction and validation

Human gastrointestinal tumours have been shown to contain massive numbers of tumour infiltrating regulatory T cells (Tregs), the presence of which are closely related to tumour immunity. This study was designed to develop new Treg-related prognostic biomarkers to monitor the prognosis of patients with gastric cancer (GC). Treg-related prognostic genes were screened from Treg-related differentially expressed genes in GC patients by using Cox regression analysis, based on which a prognostic model was constructed. Then, combined with RiskScore, survival curve, survival status assessment and ROC analysis, these genes were used to verify the accuracy of the model, whose independent prognostic ability was also evaluated. Six Treg-related prognostic genes (CHRDL1, APOC3, NPTX1, TREML4, MCEMP1, GH2) in GC were identified, and a 6-gene Treg-related prognostic model was constructed. Survival analysis revealed that patients had a higher survival rate in the low-risk group. Combining clinicopathological features, we performed univariate and multivariate regression analyses, with results establishing that the RiskScore was an independent prognostic factor. Predicted 1-, 3- and 5-year survival rates of GC patients had a good fit with the actual survival rates according to nomogram results. In addition patients in the low-risk group had higher tumour mutational burden (TMB) values. Gene Set Enrichment Analysis (GSEA) demonstrated that genes in the high-risk group were significantly enriched in pathways related to immune inflammation, tumour proliferation and migration. In general, we constructed a 6-gene Treg-associated GC prognostic model with good prediction accuracy, where RiskScore could act as an independent prognostic factor. This model is expected to provide a reference for clinicians to estimate the prognosis of GC patients.

Global role of IGF2BP1 in controlling the expression of Wnt/β-catenin-regulated genes in colorectal cancer cells

Introduction: Wnt/β-catenin signaling controls cell division and lineage specification during embryonic development, and is crucial for stem cells maintenance and gut tissue regeneration in adults. Aberrant activation of Wnt/β-catenin signaling is also essential for the pathogenesis of a variety of malignancies. The RNA-binding protein IGF2BP1 is a transcriptional target of Wnt/β-catenin signaling, normally expressed during development and often reactivated in cancer cells, where it regulates the stability of oncogenic mRNA. Methods: In this study, we employed iCLIP and RNA sequencing techniques to investigate the role of IGF2BP1 in the post-transcriptional regulation of Wnt/β-catenin-induced genes at a global level within colorectal cancer (CRC) cells characterized by constitutively active Wnt/β-catenin signaling. Results and Discussion: In our study, we show that, in contrast to normal cells, CRC cells exhibit a much stronger dependency on IGF2BP1 expression for Wnt/β-catenin-regulated genes. We show that both untransformed and CRC cells have their unique subsets of Wnt/β-catenin-regulated genes that IGF2BP1 directly controls through binding to their mRNA. Our iCLIP analysis revealed a significant change in the IGF2BP1-binding sites throughout the target transcriptomes and a significant change in the enrichment of 6-mer motifs associated with IGF2BP1 binding in response to Wnt/β-catenin signaling. Our study also revealed a signature of IGF2BP1-regulated genes that are significantly associated with colon cancer-free survival in humans, as well as potential targets for CRC treatment. Overall, this study highlights the complex and context-dependent regulation of Wnt/β-catenin signaling target genes by IGF2BP1 in non-transformed and CRC cells and identifies potential targets for colon cancer treatment.

A new marker constructed from immune-related lncRNA pairs can be used to predict clinical treatment effects and prognosis: in-depth exploration of underlying mechanisms in HNSCC

BACKGROUND

Long non-coding RNA (lncRNA) plays a vital role in tumor proliferation, migration, and treatment. Since it is challenging to standardize the gene expression levels detected by different platforms, the signatures composed of many immune-related single lncRNAs are still inaccurate. Utilizing a gene pair formed of two immune-related lncRNAs and strategically assigning values can effectively meet the demand for a higher-accuracy dual biomarker combination.

METHODS

Co-expression and differential expression analyses were performed on immune genes and lncRNAs data from The Cancer Genome Atlas and the ImmPort database to obtain differentially expressed immune-related lncRNAs for pairwise pairing. The prognostic-related differentially expressed immune-related lncRNAs (PR-DE-irlncRNAs) pairs were then identified by univariate Cox regression and used for lasso regression to construct a prognostic model. Various methods were used to validate the predictive prognostic performance of the model. Additionally, we explored the potential guiding value of the model in immunotherapy and chemotherapy and constructed a nomogram suitable for efficient prognosis prediction. Mechanistic exploration of anti-tumor immunity and mutational perspectives are also included. We also analyzed the correlation between the model and immune checkpoint inhibitors (ICIs)-related, N6-methyadenosine (m6A)-related, and multidrug resistance genes.

RESULTS

We used a total of 20 pairs of PR-DE-irlncRNAs to create a prognosis model. Quantitative real-time polymerase chain reaction experiments further verified the abnormal expression of 11 lncRNAs in HNSCC cells. Various methods have confirmed the excellent performance of the model in predicting patient prognosis. We reasoned that lncRNAs/TP53 mutation might play a positive/negative anti-tumor role through the immune system by multi-perspective analyses. Finally, it was found that the prognostic model was closely related to immunotherapy and chemotherapy as well as the expression of ICIs/m6A/multidrug resistance-related genes.

CONCLUSION

The prognostic model performs excellently in predicting the prognosis of patients and provides the potential value of practical guidance for treatment.

ggcoverage: an R package to visualize and annotate genome coverage for various NGS data

BACKGROUND

Visualizing genome coverage is of vital importance to inspect and interpret various next-generation sequencing (NGS) data. Besides genome coverage, genome annotations are also crucial in the visualization. While different NGS data require different annotations, how to visualize genome coverage and add the annotations appropriately and conveniently is challenging. Many tools have been developed to address this issue. However, existing tools are often inflexible, complicated, lack necessary preprocessing steps and annotations, and the figures generated support limited customization.

RESULTS

Here, we introduce ggcoverage, an R package to visualize and annotate genome coverage of multi-groups and multi-omics. The input files for ggcoverage can be in BAM, BigWig, BedGraph and TSV formats. For better usability, ggcoverage provides reliable and efficient ways to perform read normalization, consensus peaks generation and track data loading with state-of-the-art tools. ggcoverage provides various available annotations to adapt to different NGS data (e.g. WGS/WES, RNA-seq, ChIP-seq) and all the available annotations can be easily superimposed with ' + '. ggcoverage can generate publication-quality plots and users can customize the plots with ggplot2. In addition, ggcoverage supports the visualization and annotation of protein coverage.

CONCLUSIONS

ggcoverage provides a flexible, programmable, efficient and user-friendly way to visualize and annotate genome coverage of multi-groups and multi-omics. The ggcoverage package is available at https://github.com/showteeth/ggcoverage under the MIT license, and the vignettes are available at https://showteeth.github.io/ggcoverage/ .

Deficiency of the Polycomb Protein RYBP and TET Methylcytosine Oxidases Promotes Extensive CpG Island Hypermethylation and Malignant Transformation

Hypermethylation of CpG islands (CGI) is a common feature of cancer cells and predominantly affects Polycomb-associated genomic regions. Elucidating the underlying mechanisms leading to DNA hypermethylation in human cancer could help identify chemoprevention strategies. Here, we evaluated the role of Polycomb complexes and 5-methylcytosine (5mC) oxidases in protecting CGIs from DNA methylation and observed that four genes coding for components of Polycomb repressive complex 1 (PRC1) are downregulated in tumors. Inactivation of RYBP, a key activator of variant PRC1 complexes, in combination with all three 5mC oxidases (TET proteins) in nontumorigenic bronchial epithelial cells led to widespread hypermethylation of Polycomb-marked CGIs affecting almost 4,000 target genes, which closely resembled the DNA hypermethylation landscape observed in human squamous cell lung tumors. The RYBP- and TET-deficient cells showed methylation-associated aberrant regulation of cancer-relevant pathways, including defects in the Hippo tumor suppressor network. Notably, the quadruple knockout cells acquired a transformed phenotype, including anchorage-independent growth and formation of squamous cell carcinomas in mice. This work provides a mechanism promoting hypermethylation of CGIs and shows that such hypermethylation can lead to cell transformation. The breakdown of a two-pronged protection mechanism can be a route towards genome-wide hypermethylation of CGIs in tumors.

SIGNIFICANCE

Dysfunction of the Polycomb component RYBP in combination with loss of 5-methylcytosine oxidases promotes widespread hypermethylation of CpG islands in bronchial cells and induces tumorigenesis, resembling changes seen in human lung tumors.

Construction of a prognostic model based on genes associated with mitochondrial energy metabolic pathway in colon adenocarcinoma and its clinical significance

Mitochondria are the main sites of oxidative metabolism and energy release of sugars, fats and amino acids in the body. According to studies, malignant tumor occurrence and development have been linked to abnormal mitochondrial energy metabolism (MEM). However, the feasible role of abnormal MEM in colon adenocarcinoma (COAD) is poorly understood. In this work, we obtained COAD patient data from The Cancer Genome Atlas (TCGA) as the training set, and GSE103479 from Gene Expression Omnibus (GEO) as the validation set. Combined with the mitochondrial energy metabolic pathway (MEMP)-related genes in Kyoto Encyclopedia of Genes and Genomes (KEGG) database, a risk prognostic model was constructed by utilizing Cox regression analysis to identify 6 feature genes (CYP4A11, PGM2, PKLR, PPARGC1A, CPT2 and ACAT2) that were significantly associated with MEMP in COAD. By stratifying the samples based on riskscore, two distinct groups, namely the high- and low-risk groups, were identified. The model demonstrated accurate assessment of the prognosis risk in COAD patients and exhibited independent prognostic capability, as evidenced by the survival curve and receiver operating characteristic (ROC) curve analysis. A nomogram was plotted based on clinical information and riskscore. We proved it could predict the survival time of COAD patients effectively combined with the calibration curve of risk prediction. Subsequently, based on the immune evaluation and mutation frequency analysis performed on COAD patients, patients in high-risk group had observably higher immune scores, immune activity and PDCD1 expression level than low-risk group. In general, the prognostic model developed using MEMP-related genes served as a valuable biomarker for forecasting the prognosis of COAD patients, which offered a reference for the prognosis evaluation and clinical cure of COAD patients.

Molecular associations of response to the new-generation BTK inhibitor zanubrutinib in marginal zone lymphoma

Using tissue whole exome sequencing (WES) and circulating tumor cell-free DNA (ctDNA), this Australasian Leukaemia & Lymphoma Group translational study sought to characterize primary and acquired molecular determinants of response and resistance of marginal zone lymphoma (MZL) to zanubrutinib for patients treated in the MAGNOLIA clinical trial. WES was performed on baseline tumor samples obtained from 18 patients. For 7 patients, ctDNA sequence was interrogated using a bespoke hybrid-capture next-generation sequencing assay for 48 targeted genes. Somatic mutations were correlated with objective response data and survival analysis using Fisher exact test and Kaplan-Meier (log-rank) method, respectively. Baseline WES identified mutations in 33 of 48 (69%) prioritized genes. NF-κB, NOTCH, or B-cell receptor (BCR) pathway genes were implicated in samples from 16 of 18 patients (89%). KMT2D mutations (n = 11) were most common, followed by FAT1 (n = 9), NOTCH1, NOTCH2, TNFAIP3 (n = 5), and MYD88 (n = 4) mutations. MYD88 or TNFAIP3 mutations correlated with improved progression-free survival (PFS). KMT2D mutations trended to worse PFS. Acquired resistance mutations PLCG2 (R665W/R742P) and BTK (C481Y/C481F) were detected in 2 patients whose disease progressed. A BTK E41K noncatalytic activating mutation was identified before treatment in 1 patient who was zanubrutinib-refractory. MYD88, TNFAIP3, and KMT2D mutations correlate with PFS in patients with relapsed/refractory MZL treated with zanubrutinib. Detection of acquired BTK and PLCG2 mutations in ctDNA while on therapy is feasible and may herald clinical disease progression. This trial was registered at https://anzctr.org.au/ as #ACTRN12619000024145.

Genetic characterization of primary and metastatic high-grade serous ovarian cancer tumors reveals distinct features associated with survival

High-grade serous ovarian cancer (HGSC) is the most lethal histotype of ovarian cancer and the majority of cases present with metastasis and late-stage disease. Over the last few decades, the overall survival for patients has not significantly improved, and there are limited targeted treatment options. We aimed to better characterize the distinctions between primary and metastatic tumors based on short- or long-term survival. We characterized 39 matched primary and metastatic tumors by whole exome and RNA sequencing. Of these, 23 were short-term (ST) survivors (overall survival (OS) < 3.5 years) and 16 were long-term (LT) survivors (OS > 5 years). We compared somatic mutations, copy number alterations, mutational burden, differential gene expression, immune cell infiltration, and gene fusion predictions between the primary and metastatic tumors and between ST and LT survivor cohorts. There were few differences in RNA expression between paired primary and metastatic tumors, but significant differences between the transcriptomes of LT and ST survivors in both their primary and metastatic tumors. These findings will improve the understanding of the genetic variation in HGSC that exist between patients with different prognoses and better inform treatments by identifying new targets for drug development.

MAGOH is correlated with poor prognosis and is essential for cell proliferation in lower-grade glioma

OBJECTIVE

Mago-nashi homolog (MAGOH) has been shown to play a pivotal part in various tumors. However, its specific contribution in lower-grade glioma (LGG) is still unknown.

METHODS

Pan-cancer analysis was implemented to inspect the expression characteristics and prognostic significance of MAGOH in multiple tumors. The associations between MAGOH expression patterns and the pathological features of LGG were analyzed, as were the connections between MAGOH expression and the clinical traits, prognosis, biological activities, immune features, genomic variations, and responses to treatment in LGG. Additionally, in vitro studies were performed to detect the expression levels and biomedical functions of MAGOH in LGG.

RESULTS

Abnormally increased levels of MAGOH expression were connected with adverse prognosis in patients with several types of tumors, including LGG. Importantly, we found that levels of MAGOH expression were independent prognostic biomarker of patients with LGG. Increased MAGOH expression was also highly associated with several immune-related markers, immune cell infiltration, immune checkpoint genes (ICPGs), gene mutations, and responses to chemotherapy in patients with LGG. In vitro studies ascertained that abnormally increased MAGOH was essential for cell proliferation in LGG.

CONCLUSION

MAGOH is a valid predictive biomarker in LGG and may become a novel therapeutic target in these patients.

DUSP10 is a novel immune-related biomarker connected with survival and cellular proliferation in lower-grade glioma

OBJECTIVE

The role of dual-specificity phosphatase 10 (DUSP10) has been investigated in several types of cancer. Nevertheless, the underlying function of DUSP10 in lower-grade glioma (LGG) remains undetermined.

METHODS

We entirely determined the expression features and prognostic significance of DUSP10 in numerous tumors by implementing a pan-cancer analysis. Adjacently, we thoroughly inspected the correlation between DUSP10 expression and clinicopathologic features, prognosis, biological processes, immune traits, gene variations, and treatment responses based on the expression features in LGG. In vitro studies were conducted to detect the underlying functions of DUSP10 in LGG.

RESULTS

Unconventionally boosted DUSP10 expression and higher DUSP10 expression correlated with poorer prognosis were discovered in various tumors, including LGG. Fortunately, DUSP10 expression was proven to be an independent prognostic indicator of patients with LGG. Additionally, DUSP10 expression was tightly linked to the immune modulation, gene mutations, and response to immunotherapy/chemotherapy in LGG patients. In vitro studies illustrated that the DUSP10 was abnormally increased and pivotal for cell proliferation in LGG.

CONCLUSIONS

Collectively, we verified that DUSP10 was an independent prognostic indicator and may become a novelty target of targeted therapy of LGG.

Combining Solid and Liquid Biopsy for Therapy Monitoring in Esophageal Cancer

Esophageal cancer (EC) has one of the highest mortality rates among cancers, making it imperative that therapies are optimized and dynamically adapted to individuals. In this regard, liquid biopsy is an increasingly important method for residual disease monitoring. However, conflicting detection rates (14% versus 60%) and varying cell-free circulating tumor DNA (ctDNA) levels (0.07% versus 0.5%) have been observed in previous studies. Here, we aim to resolve this discrepancy. For 19 EC patients, a complete set of cell-free DNA (cfDNA), formalin-fixed paraffin-embedded tumor tissue (TT) DNA and leukocyte DNA was sequenced (139 libraries). cfDNA was examined in biological duplicates and/or longitudinally, and TT DNA was examined in technical duplicates. In baseline cfDNA, mutations were detected in 12 out of 19 patients (63%); the median ctDNA level was 0.4%. Longitudinal ctDNA changes were consistent with clinical presentation. Considerable mutational diversity was observed in TT, with fewer mutations in cfDNA. The most recurrently mutated genes in TT were TP53, SMAD4, TSHZ3, and SETBP1, with SETBP1 being reported for the first time. ctDNA in blood can be used for therapy monitoring of EC patients. However, a combination of solid and liquid samples should be used to help guide individualized EC therapy.

An integrated bioinformatic investigation of focal adhesion-related genes in glioma followed by preliminary validation of COL1A2 in tumorigenesis

Focal adhesions (FAs) allow cells to contact the extracellular matrix, helping to maintain tension and enabling signal transmission in cell migration, differentiation, and apoptosis. In addition, FAs are associated with changes in the tumor microenvironment (TME) that lead to malignant progression and drug resistance in tumors. However, there are still few studies on the comprehensive analysis of focal adhesion-related genes (FARGs) in glioma. Expression data and clinical information of glioma samples were downloaded from public databases. Two distinct molecular subtypes were identified based on FARGs using an unsupervised consensus clustering algorithm. A scoring system consisting of nine FARGs was constructed using integrated LASSO regression and multivariate Cox regression. It not only has outstanding prognostic value but also can guide immunotherapy of glioma patients, which was verified in TCGA, CGGA, GSE16011, and IMvigor210 cohorts. The results of bioinformatics analysis, immunohistochemistry staining, and western blotting all revealed that the expression of COL1A2 was up-regulated in glioblastoma and related to poor prognosis outcomes in patients from public datasets. COL1A2 promotes the proliferation, migration, and invasion of glioblastoma cells. A positive correlation between COL1A2 and CD8 was determined in GBM specimens from eight patients. Moreover, the results of cell co-cultured assay showed that COL1A2 participated in the killing of GBM cells by Jurkat cells. Our study indicates that the FARGs have prominent application value in the identification of molecular subtypes and prediction of survival outcomes in glioma patients. Bioinformatics analysis and experimental verification provide a direction for further research on FARGs.

Pan-genome of Citrullus genus highlights the extent of presence/absence variation during domestication and selection

The rich genetic diversity in Citrullus lanatus and the other six species in the Citrullus genus provides important sources in watermelon breeding. Here, we present the Citrullus genus pan-genome based on the 400 Citrullus genus resequencing data, showing that 477 Mb contigs and 6249 protein-coding genes were absent in the Citrullus lanatus reference genome. In the Citrullus genus pan-genome, there are a total of 8795 (30.5%) genes that exhibit presence/absence variations (PAVs). Presence/absence variation (PAV) analysis showed that a lot of gene PAV were selected during the domestication and improvement, such as 53 favorable genes and 40 unfavorable genes were identified during the C. mucosospermus to C. lanatus landrace domestication. We also identified 661 resistance gene analogs (RGAs) in the Citrullus genus pan-genome, which contains 90 RGAs (89 variable and 1 core gene) located on the pangenome additional contigs. By gene PAV-based GWAS, 8 gene presence/absence variations were found associated with flesh color. Finally, based on the results of gene PAV selection analysis between watermelon populations with different fruit colors, we identified four non-reference candidate genes associated with carotenoid accumulation, which had a significantly higher frequency in the white flesh. These results will provide an important source for watermelon breeding.

Based on cuproptosis-related lncRNAs, a novel prognostic signature for colon adenocarcinoma prognosis, immunotherapy, and chemotherapy response

Introduction: Colon adenocarcinoma (COAD) is a special pathological subtype of colorectal cancer (CRC) with highly heterogeneous solid tumors with poor prognosis, and novel biomarkers are urgently required to guide its prognosis. Material and methods: RNA-Seq data of COAD were downloaded through The Cancer Genome Atlas (TCGA) database to determine cuproptosis-related lncRNAs (CRLs) using weighted gene co-expression network analysis (WGCNA). The scores of the pathways were calculated by single-sample gene set enrichment analysis (ssGSEA). CRLs that affected prognoses were determined via the univariate COX regression analysis to develop a prognostic model using multivariate COX regression analysis and LASSO regression analysis. The model was assessed by applying Kaplan-Meier (K-M) survival analysis and receiver operating characteristic curves and validated in GSE39582 and GSE17538. The tumor microenvironment (TME), single nucleotide variants (SNV), and immunotherapy response/chemotherapy sensitivity were assessed in high- and low-score subgroups. Finally, the construction of a nomogram was adopted to predict survival rates of COAD patients during years 1, 3, and 5. Results: We found that a high cuproptosis score reduced the survival rates of COAD significantly. A total of five CRLs affecting prognosis were identified, containing AC008494.3, EIF3J-DT, AC016027.1, AL731533.2, and ZEB1-AS1. The ROC curve showed that RiskScore could perform well in predicting the prognosis of COAD. Meanwhile, we found that RiskScore showed good ability in assessing immunotherapy and chemotherapy sensitivity. Finally, the nomogram and decision curves showed that RiskScore would be a powerful predictor for COAD. Conclusion: A novel prognostic model was constructed using CRLs in COAD, and the CRLs in the model were probably a potential therapeutic target. Based on this study, RiskScore was an independent predictor factor, immunotherapy response, and chemotherapy sensitivity for COAD, providing a new scientific basis for COAD prognosis management.

Comut-viz: efficiently creating and browsing comutation plots online

BACKGROUND

Comutation plot is a widely used visualization method to deliver a global view of the mutation landscape of large-scale genomic studies. Current tools for creating comutation plot are either offline packages that require coding or online web servers with varied features. When a package is used, it often requires repetitive runs of code to adjust a single feature that might only be a few clicks in a web app. But web apps mostly have limited capacity for customization and cannot handle very large genomic files.

RESULTS

To improve on existing tools, we identified features that are most frequently adjusted in creating a plot and incorporate them in Comut-viz that interactively filters and visualizes mutation data as downloadable plots. It includes colored labels for numeric metadata, a preloaded palette for changing colors and two input boxes for adjusting width and height. It accepts standard mutation annotation format (MAF) files as input and can handle large MAF files with more than 200 k rows. As a front-end only app, Comut-viz guarantees privacy of user data and no latency in the analysis.

CONCLUSIONS

Comut-viz is a highly responsive and extensible web app to make comutation plots. It provides customization for frequently adjusted features and accepts large genomic files as input. It is suitable for genomic studies with more than a thousand samples.

Whole-exome sequencing of Indian prostate cancer reveals a novel therapeutic target: POLQ

PURPOSE

Prostate cancer is the second most common cancer diagnosed worldwide and the third most common cancer among men in India. This study's objective was to characterise the mutational landscape of Indian prostate cancer using whole-exome sequencing to identify population-specific polymorphisms.

METHODS

Whole-exome sequencing was performed of 58 treatment-naive primary prostate tumors of Indian origin. Multiple computational and statistical analyses were used to profile the known common mutations, other deleterious mutations, driver genes, prognostic biomarkers, and gene signatures unique to each clinical parameter. Cox analysis was performed to validate survival-associated genes. McNemar test identified genes significant to recurrence and receiver-operating characteristic (ROC) analysis was conducted to determine its accuracy. OncodriveCLUSTL algorithm was used to deduce driver genes. The druggable target identified was modeled with its known inhibitor using Autodock.

RESULTS

TP53 was the most commonly mutated gene in our cohort. Three novel deleterious variants unique to the Indian prostate cancer subtype were identified: POLQ, FTHL17, and OR8G1. COX regression analysis identified ACSM5, a mitochondrial gene responsible for survival. CYLC1 gene, which encodes for sperm head cytoskeletal protein, was identified as an unfavorable prognostic biomarker indicative of recurrence. The novel POLQ mutant, also identified as a driver gene, was evaluated as the druggable target in this study. POLQ, a DNA repair enzyme implicated in various cancer types, is overexpressed and is associated with a poor prognosis. The mutant POLQ was subjected to structural analysis and modeled with its known inhibitor novobiocin resulting in decreased binding efficiency necessitating the development of a better drug.

CONCLUSION

In this pilot study, the molecular profiling using multiple computational and statistical analyses revealed distinct polymorphisms in the Indian prostate cancer cohort. The mutational signatures identified provide a valuable resource for prognostic stratification and targeted treatment strategies for Indian prostate cancer patients. The DNA repair enzyme, POLQ, was identified as the druggable target in this study.

MGME1 associates with poor prognosis and is vital for cell proliferation in lower-grade glioma

OBJECTIVE

Mitochondrial genome maintenance exonuclease 1 (MGME1) is associated with DNA depletion, deletion, duplication, and rearrangement. However, the function of MGME1 in tumors, especially lower-grade gliomas (LGGs), has not been established.

METHODS

Pan-cancer analysis was used to define the expression patterns and prognostic value of MGME1 in various cancers. Subsequently, we systematically determined the associations between MGME1 expression and clinicopathological characteristics, prognosis, biological functions, immune characteristics, genomic mutations, and therapeutic responses of LGGs based on their expression patterns. The expression level and specific functions of MGME1 in LGGs was detected by conducting in vitro experiments.

RESULTS

Abnormally enhanced and high MGME1 expressions were associated with poor prognoses of various tumors, including LGG. Multivariate and univariate Cox regression analyses manifested that MGME1 expression was an independent prognostic biomarker for LGG. The immune-related signatures, infiltration of immune cells, immune checkpoint genes (ICPGs), copy number alteration (CNA), tumor mutation burden (TMB), and treatment responses of LGG patients were associated with the expression of MGME1. The in vitro experiments affirmed that MGME1 was elevated and tightly connected with the cell proliferation and cell cycle in LGG.

CONCLUSIONS

MGME1 is an independent prognostic biomarker and closely related to the cell proliferation in LGG.

Hereditary Breast Cancer in Romania-Molecular Particularities and Genetic Counseling Challenges in an Eastern European Country

In Romania, breast cancer (BC) is the most common malignancy in women. However, there is limited data on the prevalence of predisposing germline mutations in the population in the era of precision medicine, where molecular testing has become an indispensable tool in cancer diagnosis, prognosis, and therapeutics. Therefore, we conducted a retrospective study to determine the prevalence, mutational spectrum, and histopathological prediction factors for hereditary breast cancer (HBC) in Romania. A cohort of 411 women diagnosed with BC selected upon NCCN v.1.2020 guidelines underwent an 84-gene NGS-based panel testing for breast cancer risk assessment during 2018-2022 in the Department of Oncogenetics of the Oncological Institute of Cluj-Napoca, Romania. A total of 135 (33%) patients presented pathogenic mutations in 19 genes. The prevalence of genetic variants was determined, and demographic and clinicopathological characteristics were analyzed. We observed differences among BRCA and non-BRCA carriers regarding family history of cancer, age of onset, and histopathological subtypes. Triple-negative (TN) tumors were more often BRCA1 positive, unlike BRCA2 positive tumors, which were more often the Luminal B subtype. The most frequent non-BRCA mutations were found in CHEK2, ATM, and PALB2, and several recurrent variants were identified for each gene. Unlike other European countries, germline testing for HBC is still limited due to the high costs and is not covered by the National Health System (NSH), thus leading to significant discrepancies related to the screening and prophylaxis of cancer.

Rapid genomic surveillance of SARS-CoV-2 in a dense urban community of Kathmandu Valley using sewage samples

Understanding disease burden and transmission dynamics in resource-limited, low-income countries like Nepal are often challenging due to inadequate surveillance systems. These issues are exacerbated by limited access to diagnostic and research facilities throughout the country. Nepal has one of the highest COVID-19 case rates (915 cases per 100,000 people) in South Asia, with densely-populated Kathmandu experiencing the highest number of cases. Swiftly identifying case clusters (hotspots) and introducing effective intervention programs is crucial to mounting an effective containment strategy. The rapid identification of circulating SARS-CoV-2 variants can also provide important information on viral evolution and epidemiology. Genomic-based environmental surveillance can help in the early detection of outbreaks before clinical cases are recognized and identify viral micro-diversity that can be used for designing real-time risk-based interventions. This research aimed to develop a genomic-based environmental surveillance system by detecting and characterizing SARS-CoV-2 in sewage samples of Kathmandu using portable next-generation DNA sequencing devices. Out of 22 sites in the Kathmandu Valley from June to August 2020, sewage samples from 16 (80%) sites had detectable SARS-CoV-2. A heatmap was created to visualize the presence of SARS-CoV-2 infection in the community based on viral load intensity and corresponding geospatial data. Further, 47 mutations were observed in the SARS-CoV-2 genome. Some detected mutations (n = 9, 22%) were novel at the time of data analysis and yet to be reported in the global database, with one indicating a frameshift deletion in the spike gene. SNP analysis revealed possibility of assessing circulating major/minor variant diversity on environmental samples based on key mutations. Our study demonstrated the feasibility of rapidly obtaining vital information on community transmission and disease dynamics of SARS-CoV-2 using genomic-based environmental surveillance.

Spatiotemporal assessment of immunogenomic heterogeneity in multiple myeloma

Spatial heterogeneity is a common phenomenon in metastatic solid tumors and an evolving concept in multiple myeloma (MM). The interplay between malignant plasma cells (PCs) and the microenvironment has not yet been analyzed in MM. For this purpose, we performed bone marrow aspirates and imaging-guided biopsies of corresponding lesions in newly diagnosed MM (NDMM) and relapsed/refractory MM (RRMM) patients. PCs were isolated and subjected to whole-exome sequencing (WES). Non-PCs were studied with next-generation flow (NGF) and T-cell receptor sequencing (TCRseq) to analyze the connection between malignant and nonmalignant cells in the bone marrow and in lesions. Although we observed a strong overlap from WES, NGF, and TCRseq in patients with intramedullary disease, WES revealed significant spatial heterogeneity in patients with extramedullary disease. NGF showed significant immunosuppression in RRMM compared with NDMM as indicated by fewer myeloid dendritic cells, unswitched memory B cells, Th9 cells, and CD8 effector memory T cells but more natural killer and regulatory T cells. Additionally, fewer T-cell receptor (TCR) sequences were detected in RRMM compared with NDMM and healthy individuals. After induction therapy, TCR repertoire richness increased to levels of healthy individuals, and NGF showed more regulatory T cells and myeloid-derived suppressor cells, regardless of depth of response. Clinical significance of imaging-guided biopsies of lesions was demonstrated by detection of monoclonal PCs in patients without measurable residual disease (MRD) in aspirates from the iliac crest as well as identification of secondary primary malignancies in MRD- patients. Furthermore, site-specific clones with different drug susceptibilities and genetically defined high-risk features were detected by our workflow.

Structural variations and environmental specificities of flowering time-related genes in Brassica napus

We found that the flowering time order of accessions in a genetic population considerably varied across environments, and homolog copies of essential flowering time genes played different roles in different locations. Flowering time plays a critical role in determining the life cycle length, yield, and quality of a crop. However, the allelic polymorphism of flowering time-related genes (FTRGs) in Brassica napus, an important oil crop, remains unclear. Here, we provide high-resolution graphics of FTRGs in B. napus on a pangenome-wide scale based on single nucleotide polymorphism (SNP) and structural variation (SV) analyses. A total of 1337 FTRGs in B. napus were identified by aligning their coding sequences with Arabidopsis orthologs. Overall, 46.07% of FTRGs were core genes and 53.93% were variable genes. Moreover, 1.94%, 0.74%, and 4.49% FTRGs had significant presence-frequency differences (PFDs) between the spring and semi-winter, spring and winter, and winter and semi-winter ecotypes, respectively. SNPs and SVs across 1626 accessions of 39 FTRGs underlying numerous published qualitative trait loci were analyzed. Additionally, to identify FTRGs specific to an eco-condition, genome-wide association studies (GWASs) based on SNP, presence/absence variation (PAV), and SV were performed after growing and observing the flowering time order (FTO) of plants in a collection of 292 accessions at three locations in two successive years. It was discovered that the FTO of plants in a genetic population changed a lot across various environments, and homolog copies of some key FTRGs played different roles in different locations. This study revealed the molecular basis of the genotype-by-environment (G × E) effect on flowering and recommended a pool of candidate genes specific to locations for breeding selection.

Integrated multi-omics analyses and functional validation reveal TTK as a novel EMT activator for endometrial cancer

BACKGROUND

Cancer-testis antigens (CTAs) are often expressed in tumor and testicular tissues but not in other normal tissues. To date, there has been no comprehensive study of the expression and clinical significance of CTA genes associated with endometrial cancer (EC) development. Additionally, the clinical relevance, biological role, and molecular mechanisms of the CTA gene TTK protein kinase (TTK) in EC are yet to be fully understood.

METHODS

Using bioinformatics methods, we comprehensively investigated the genomic, transcriptomic, and epigenetic changes associated with aberrant TTK overexpression in EC samples from the TCGA database. We further investigated the mechanisms of the lower survival associated with TTK dysregulation using single-cell data of EC samples from the GEO database. Cell functional assays were used to confirm the biological roles of TTK in EC cells.

RESULTS

We identified 80 CTA genes that were more abundant in EC than in normal tissues, and high expression of TTK was significantly linked with lower survival in EC patients. Furthermore, ROC analysis revealed that TTK could accurately distinguish stage I EC tissues from benign endometrial samples, suggesting that TTK has the potential to be a biomarker for early EC detection. We found TTK overexpression was more prevalent in EC patients with high-grade, advanced tumors, serous carcinoma, and TP53 alterations. Furthermore, in EC tissue, TTK expression showed a strong positive correlation with EMT-related genes. With single-cell transcriptome data, we identified a proliferative cell subpopulation with high expression of TTK and known epithelial-mesenchymal transition (EMT)-related genes and transcription factors. When proliferative cells were grouped according to TTK expression levels, the overexpressed genes in the TTK^high group were shown to be functionally involved in the control of chemoresistance. Utilizing shRNA to repress TTK expression in EC cells resulted in substantial decreases in cell proliferation, invasion, EMT, and chemoresistance. Further research identified microRNA-21 (miR-21) as a key downstream regulator of TTK-induced EMT and chemoresistance. Finally, the TTK inhibitor AZ3146 was effective in reducing EC cell growth and invasion and enhancing the apoptosis of EC cells generated by paclitaxel.

CONCLUSION

Our findings establish the clinical significance of TTK as a new biomarker for EC and an as-yet-unknown carcinogenic function. This present study proposes that the therapeutic targeting of TTK might provide a viable approach for the treatment of EC.

Identification of a robust scoring system based on metabolic genes followed by in-depth validation of ATP1A3 in glioma

AIMS

In the past few decades, the prognosis of glioma patients has not significantly improved. Therefore, to provide more precise medical services for glioma patients, it is urgent to identify more clinically meaningful subtypes, establish more robust clinical prediction models, and find more effective therapeutic targets.

MATERIALS AND METHODS

Four distinct metabolic-associated subtypes were identified by the NMF algorithm based on metabolic genes (MEGs). A robust scoring system was constructed based on the differentially expressed genes (DEGs) screened from the four metabolic-associated subtypes with the LASSO regression algorithm and multivariate Cox regression analysis. Further analysis of scoring systems was done by different R packages. In addition, the ATP1A3 gene was screened and bioinformatics analysis of it was conducted on several public websites. GSEA software was utilized to search hallmark signaling pathways closely related to ATP1A3. Cytological experiments were used to investigate the role of ATP1A3 in the malignant progression of glioblastoma (GBM) cells.

KEY FINDINGS

Four metabolic-associated subtypes with significantly different clinicopathological characteristics were identified, and a robust scoring system with outstanding clinical application value was established. In addition, a tumor suppressor gene ATP1A3 was found, which is expected to be a potential therapeutic target for glioma.

SIGNIFICANCE

This study is of great significance in the diagnosis, prognosis, and prediction of the response to immune checkpoint blockers (ICBs) for glioma patients. More importantly, this study found a potential therapeutic target for glioma.

Genome-wide copy number variant screening of Saudi schizophrenia patients reveals larger deletions in cases versus controls

Introduction

Genome-wide association studies have discovered common polymorphisms in regions associated with schizophrenia. No genome-wide analyses have been performed in Saudi schizophrenia subjects.

Methods

Genome-wide genotyping data from 136 Saudi schizophrenia cases and 97 Saudi controls in addition to 4,625 American were examined for copy number variants (CNVs). A hidden Markov model approach was used to call CNVs.

Results

CNVs in schizophrenia cases were twice as large on average than CNVs in controls (p = 0.04). The analyses focused on extremely large >250 kilobases CNVs or homozygous deletions of any size. One extremely large deletion was noted in a single case (16.5 megabases on chromosome 10). Two cases had an 814 kb duplication of chromosome 7 spanning a cluster of genes, including circadian-related loci, and two other cases had 277 kb deletions of chromosome 9 encompassing an olfactory receptors gene family. CNVs were also seen in loci previously associated with schizophrenia, namely a 16p11 proximal duplication and two 22q11.2 deletions.

Discussion

Runs of homozygosity (ROHs) were analyzed across the genome to investigate correlation with schizophrenia risk. While rates and sizes of these ROHs were similar in cases and controls, we identified 10 regions where multiple cases had ROHs and controls did not.

Impact of EGFRA289T/V mutation on relapse pattern in glioblastoma

BACKGROUND

Molecular factors influence relapse patterns in glioblastoma. The hotspot mutation located at position 289 of the extracellular domain of the epidermal growth factor receptor (EGFR^A289mut) is associated with a more infiltrative phenotype. The primary objective of this study was to explore the impact of the EGFR^A289 mutation on the pattern of relapse after chemoradiotherapy-based treatment of patients suffering from newly diagnosed glioblastoma.

PATIENTS AND METHODS

An ancillary study from a prospective cohort of patients suffering from glioblastoma was conducted. All patients received radiotherapy and concomitant temozolomide. The population was divided into two groups according to EGFR^A289 status (mutated versus wild-type). The primary endpoint was the overlap score (varying from 0 to 1) between the initial irradiated tumor volume (Vinit) and the relapse volume (Vr). Secondary endpoints explored the impact of EGFR^A289mut on survival.

RESULTS

One hundred twenty-eight patients were included and analyzed: 11% had EGFR^A289mut glioblastoma (n = 14/128). EGFR^A289mut glioblastomas had a relapse pattern that was more marginal than EGFR^A289wt glioblastomas: a median overlap score Vinit/Vr of 0.96 was observed in the EGFR^A289mut group versus 1 in the EGFR^A289wt group (P = 0.05). Half of the population with EGFR^A289mut tumor (n = 7/14) had a marginal relapse (i.e. overlap score^Vr/Vinit ≤ 0.95) compared to 23.7% (n = 27/114) in the EGFR^A289wt group, P = 0.035. EGFR^A289mut did not influence survival.

CONCLUSION

We highlighted a link between the EGFR^A289 mutation and the relapse pattern in glioblastoma. The independent role of EGFR^A289mut and its clinical implication should now be explored in further studies.

A Comprehensive Analysis of Cutaneous Melanoma Patients in Greece Based on Multi-Omic Data

Cutaneous melanoma (CM) is the most aggressive type of skin cancer, and it is characterised by high mutational load and heterogeneity. In this study, we aimed to analyse the genomic and transcriptomic profile of primary melanomas from forty-six Formalin-Fixed, Paraffin-Embedded (FFPE) tissues from Greek patients. Molecular analysis for both germline and somatic variations was performed in genomic DNA from peripheral blood and melanoma samples, respectively, exploiting whole exome and targeted sequencing, and transcriptomic analysis. Detailed clinicopathological data were also included in our analyses and previously reported associations with specific mutations were recognised. Most analysed samples (43/46) were found to harbour at least one clinically actionable somatic variant. A subset of samples was profiled at the transcriptomic level, and it was shown that specific melanoma phenotypic states could be inferred from bulk RNA isolated from FFPE primary melanoma tissue. Integrative bioinformatics analyses, including variant prioritisation, differential gene expression analysis, and functional and gene set enrichment analysis by group and per sample, were conducted and molecular circuits that are implicated in melanoma cell programmes were highlighted. Integration of mutational and transcriptomic data in CM characterisation could shed light on genes and pathways that support the maintenance of phenotypic states encrypted into heterogeneous primary tumours.

Immunogenomic analysis of human brain metastases reveals diverse immune landscapes across genetically distinct tumors

Brain metastases (BrMs) are the most common form of brain tumors in adults and frequently originate from lung and breast primary cancers. BrMs are associated with high mortality, emphasizing the need for more effective therapies. Genetic profiling of primary tumors is increasingly used as part of the effort to guide targeted therapies against BrMs, and immune-based strategies for the treatment of metastatic cancer are gaining momentum. However, the tumor immune microenvironment (TIME) of BrM is extremely heterogeneous, and whether specific genetic profiles are associated with distinct immune states remains unknown. Here, we perform an extensive characterization of the immunogenomic landscape of human BrMs by combining whole-exome/whole-genome sequencing, RNA sequencing of immune cell populations, flow cytometry, immunofluorescence staining, and tissue imaging analyses. This revealed unique TIME phenotypes in genetically distinct lung- and breast-BrMs, thereby enabling the development of personalized immunotherapies tailored by the genetic makeup of the tumors.

Establishment of experimental salivary gland cancer models using organoid culture and patient-derived xenografting

Purpose

Depending on its histological subtype, salivary gland carcinoma (SGC) may have a poor prognosis. Due to the scarcity of preclinical experimental models, its molecular biology has so far remained largely unknown, hampering the development of new treatment modalities for patients with these malignancies. The aim of this study was to generate experimental human SGC models of multiple histological subtypes using patient-derived xenograft (PDX) and organoid culture techniques.

Methods

Tumor specimens from surgically resected SGCs were processed for the preparation of PDXs and patient-derived organoids (PDOs). Specimens from SGC PDXs were also processed for PDX-derived organoid (PDXO) generation. In vivo tumorigenicity was assessed using orthotopic transplantation of SGC organoids. The pathological characteristics of each model were compared to those of the original tumors using immunohistochemistry. RNA-seq was used to analyze the genetic traits of our models.

Results

Three series of PDOs, PDXs and PDXOs of salivary duct carcinomas, one series of PDOs, PDXs and PDXOs of mucoepidermoid carcinomas and PDXs of myoepithelial carcinomas were successfully generated. We found that PDXs and orthotopic transplants from PDOs/PDXOs showed similar histological features as the original tumors. Our models also retained their genetic traits, i.e., transcription profiles, genomic variants and fusion genes of the corresponding histological subtypes.

Conclusion

We report the generation of SGC PDOs, PDXs and PDXOs of multiple histological subtypes, recapitulating the histological and genetical characteristics of the original tumors. These experimental SGC models may serve as a useful resource for the development of novel therapeutic strategies and for investigating the molecular mechanisms underlying the development of these malignancies.

Collaborative Sense-Making in Genomic Research: The Role of Visualisation

Genomic research emerges from collaborative work within and across different scientific disciplines. A diverse range of visualisation techniques has been employed to aid this research, yet relatively little is known as to how these techniques facilitate collaboration. We conducted a case study of collaborative research within a biomedical institute to learn more about the role visualisation plays in genomic mapping. Interviews were conducted with molecular biologists (N = 5) and bioinformaticians (N = 6). We found that genomic research comprises a variety of distinct disciplines engaged in complex analytic tasks that each resist simplification, and their complexity influences how visualisations were used. Visualisation use was impacted by group-specific interactions and temporal work patterns. Visualisations were also crucial to the scientific workflow, used for both question formation and confirmation of hypotheses, and acted as an anchor for the communication of ideas and discussion. In the latter case, two approaches were taken: providing collaborators with either interactive or static imagery representing a viewpoint. The use of generic software for simplified visualisations, and quick production and curation was also noted. We discuss these findings with reference to group-specific interactions and present recommendations for improving collaborative practices through visual analytics.

The genetic landscape of SMARCB1 alterations in SMARCB1-deficient spectrum of mesenchymal neoplasms

SMARCB1 biallelic inactivation resulting in SMARCB1/INI1 deficiency drives a wide range of malignancies, including many mesenchymal tumors. However, the specific types of SMARCB1 alterations and spectrum of cooperating mutations among various types of sarcomas has not been well investigated. We profiled SMARCB1 genetic alterations by targeted DNA sequencing and fluorescence in situ hybridization (FISH) in a large cohort of 118 soft tissue and bone tumors, including SMARCB1-deficient sarcomas (78, 66%): epithelioid sarcomas, epithelioid peripheral nerve sheath tumors, poorly differentiated chordomas, malignant rhabdoid tumors, and soft tissue myoepithelial tumors, as well as non-SMARCB1-deficient sarcomas (40, 34%) with various SMARCB1 genetic alterations (mutations, copy number alterations). SMARCB1 loss by immunohistochemistry was present in 94% SMARCB1 pathogenic cases. By combined sequencing and FISH assays, 80% of SMARCB1-deficient tumors harbored homozygous (biallelic) SMARCB1 loss, while 14% demonstrated heterozygous SMARCB1 loss-of-function (LOF) alterations, and 6% showed no demonstrable SMARCB1 alterations. FISH and sequencing were concordant in the ability to detect SMARCB1 loss in 48% of cases. Epithelioid sarcomas most commonly (75%) harbored homozygous deletions, while a subset showed focal intragenic deletions or LOF mutations (nonsense, frameshift). In contrast, most soft tissue myoepithelial tumors (83%) harbored SMARCB1 nonsense point mutations without copy number losses. Additionally, clinically significant, recurrent co-occurring genetic events were rare regardless of histotype. By sequencing, extended 22q copy number loss in genes flanking the SMARCB1 locus (22q11.23) occurred in one-third of epithelioid sarcomas and the majority of poorly differentiated chordomas. Poorly differentiated chordomas and soft tissue myoepithelial tumors showed significantly worse overall and disease-free survival compared to epithelioid sarcomas. Overall, SMARCB1 LOF alterations predominate and account for SMARCB1 protein loss in most cases: majority being biallelic but a subset were heterozygous. In contrast, SMARCB1 alterations of uncertain significance can be seen in diverse sarcomas types and does not indicate a SMARCB1-deficient entity.

A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non-Small Cell Lung Cancer

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research.

SIGNIFICANCE

Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

MACF1 mutations predict poor prognosis: a novel potential therapeutic target for breast cancer

OBJECTIVE

Microtubule actin cross-linking factor 1 (MACF1) mutations are known to play an important role in the progression of various cancers. However, its role in breast cancer remains to be determined. In this study, we investigated how MACF1 mutations may play a role in breast cancer development.

METHODS

The gene-expression profile data of patients with breast cancer were obtained from The Cancer Genome Atlas (TCGA)-Breast cancer cohort. We estimated the influence of MACF1 mutations on patient clinical prognosis using the Kaplan-Meier method. Further, patients with MACF1-mutant (MACF1-MT) and MACF1-wild-type (MACF1-WT) were compared to identify the differentially expressed genes (DEGs). We also performed functional enrichment analyses, constructed protein-protein interaction (PPI) and competing endogenous RNA (ceRNA) networks, and investigated the correlation between MACF1 mutations and immune-cell infiltration. To explore the prognostic value of MACF1 mutations, a nomogram was developed based on MACF1 mutations and other clinicopathological parameters.

RESULTS

Patients with MACF1-MT had a worse prognosis and higher tumor mutation burden score (P < 0.05) than patients with MACF1-WT. MACF1 mutations were demonstrated to upregulate the mTOR signaling pathway and alter energy metabolism and tumor immune microenvironment. Thus, MACF1 mutations might affect immunogenicity and result in a lower response to immunotherapy. By analyzing the Genomics of Drug Sensitivity in Cancer (GDSC), the sensitivity of breast cancer cells to 13 drugs was found to be significantly enhanced by MACF1 mutations. The prognostic model was verified in predicting the outcome of breast cancer patients.

CONCLUSION

MACF1 mutations might be a potential prognostic biomarker and a therapeutic target for breast cancer.

Whole-genome sequencing of chronic lymphocytic leukemia identifies subgroups with distinct biological and clinical features

The value of genome-wide over targeted driver analyses for predicting clinical outcomes of cancer patients is debated. Here, we report the whole-genome sequencing of 485 chronic lymphocytic leukemia patients enrolled in clinical trials as part of the United Kingdom's 100,000 Genomes Project. We identify an extended catalog of recurrent coding and noncoding genetic mutations that represents a source for future studies and provide the most complete high-resolution map of structural variants, copy number changes and global genome features including telomere length, mutational signatures and genomic complexity. We demonstrate the relationship of these features with clinical outcome and show that integration of 186 distinct recurrent genomic alterations defines five genomic subgroups that associate with response to therapy, refining conventional outcome prediction. While requiring independent validation, our findings highlight the potential of whole-genome sequencing to inform future risk stratification in chronic lymphocytic leukemia.

Construction and Validation of a Prognostic Model Based on mRNAsi-Related Genes in Breast Cancer

Background

Breast cancer is a big threat to the women across the world with substantial morbidity and mortality. The pressing matter of our study is to establish a prognostic gene model for breast cancer based on mRNAsi for predicting patient's prognostic survival.

Methods

From The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we downloaded the expression profiles of genes in breast cancer. On the basis of one-class logistic regression (OCLR) machine learning algorithm, mRNAsi of samples was calculated. Kaplan-Meier (K-M) and Kruskal-Wallis (K-W) tests were utilized for the assessment of the connection between mRNAsi and clinicopathological variables of the samples. As for the analysis on the correlation between mRNAsi and immune infiltration, ESTIMATE combined with Spearman test was employed. The weighted gene coexpression network analysis (WGCNA) network was established by utilizing the differentially expressed genes in breast cancer, and the target module with the most significant correlation with mRNAsi was screened. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to figure out the biological functions of the target module. As for the construction of the prognostic model, univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were performed on genes in the module. The single sample gene set enrichment analysis (ssGSEA) and tumor mutational burden were employed for the analysis on immune infiltration and gene mutations in the high- and low-risk groups. As for the analysis on whether this model had the prognostic value, the nomogram and calibration curves of risk scores and clinical characteristics were drawn.

Results

Nine mRNAsi-related genes (CFB, MAL2, PSME2, MRPL13, HMGB3, DCTPP1, SHCBP1, SLC35A2, and EVA1B) comprised the prognostic model. According to the results of ssGSEA and gene mutation analysis, differences were shown in immune cell infiltration and gene mutation frequency between the high- and low-risk groups.

Conclusion

Nine mRNAsi-related genes screened in our research can be considered as the biomarkers to predict breast cancer patients' prognoses, and this model has a potential relationship with individual somatic gene mutations and immune regulation. This study can offer new insight into the development of diagnostic and clinical treatment strategies for breast cancer.

Landscape of exitrons in gastric cancer

BACKGROUND

Exitron is a new type of non-canonical alternative splicing. Accumulating evidence implies exitron may have pathological function and contribute to another source of anti-tumor immunogenicity in various cancers. Its role in gastric cancer remains poorly understood. Large-scale, multi-omics analysis could comprehensively characterize the landscape of exitrons in gastric cancer, reveal undiscovered mechanism and hopefully identify molecular biomarkers for predicting immunotherapy response.

METHODS

We collected datasets from five studies for analysis. RNA sequencing was used for exitron identification. Somatic mutations were detected by whole exome sequencing. Neopeptides were confirmed by proteome mass spectrometry.

FINDINGS

42174 gastric cancer-specific exitrons (GCSEs) were identified in 632 patients. GCSEs were clinically relevant to gender, age, Lauren type, tumor stage and prognosis. Tissue specificity test and pathogenic exitron prediction revealed their unique functional impact. GCSEs were mutually exclusive with mutations and demonstrated both unique and complementary function against TP53 mutation in gastric cancer. We further established splicing regulatory network to reveal upstream regulation of exitron splicing. We also evaluated the immunogenicity and diagnostic potential of GCSEs. Evidence of GCSEs-derived neopeptide expression was validated by whole proteome mass spectrometry. PD-1 and Siglecs were significantly increased in high neoantigen load patients. But exitron-related biomarkers failed to predict immunotherapy response, possibly due to small sample size and insufficient sequencing depth.

INTERPRETATION

The present study provided a comprehensive multidimensional landscape of gastric cancer exitrons and underscores insights into underexplored mechanism in gastric cancer pathology.

FUNDING

The Guangdong Provincial Key Laboratory of Precision Medicine for Gastroinstestinal Cancer (2020B121201004), the Guangdong Provincial Major Talents Project (No. 2019JC05Y361) and National Natural Science Foundation of China (grant number:82172960 and 81872013).

Genomic landscape of the lung cancer in the young

Background

Lung cancer in the young is a rare entity of great interest due to the high frequency of targetable mutations. In this study, we explored the genomic landscape of non-small cell lung cancer (NSCLC) in young patients and compared it with genetic alterations in older patients.

Methods

Comparative study of the genomic profile of NSCLC young (≤40 years old) vs older patients (>40 years old) from Instituto Nacional de Enfermedades Neoplásicas (INEN) in Lima, Peru. Archival paraffin-embedded tumor samples were profiled with FoundationOne CDx assay to identify short variants alterations (insertions and deletions), copy number variations (CNV), tumor mutational burden and microsatellite instability in 324 driver genes and rearrangements in 28 commonly rearranged genes. A targetable alteration was defined as any alteration in a driver oncogene for which an FDA approved therapy existed at the time of study enrollment.

Results

Overall, 62 tumors were profiled, 32 from young and 30 from older patients. All clinicopathological features (smoking status, clinical stage, and histology) were similar between groups, except for gender (65.6% of females in the younger group vs 40% in the older group, P=0.043). At least one actionable mutation was present in 84.4% and 83.3% in younger and older patients, respectively. Alteration rates in the main genes were: BRAF, 3.1%(n=1) vs 0%; EGFR, 46.9% (n=15) vs 43.3% (n=13); ERBB2, 12.5% (n=4) vs 16.7% (n=5); KRAS, 15.6% (n=5) vs 16.7% (n=5); ALK, 6.3% (n=2) vs 3.3% (n=1); RET, 0.0% vs 3.3% (n=1); ROS1, 3.1% (n=1) vs 3.3% (n=1); NTRK1, 0.0% vs 3.3% (n=1) and MET, 3.1% (n=1) vs 13.3% (n=4). Mean TMB was 4.04 Mut/Mb (SD ± 3.98) for young vs 8.06 Mut/Mb (SD ± 9.84) for older patients (P=0.016). There were not significant differences in CNV, frequency of gene rearrangements, or microsatellites instability.

Conclusion

NSCLC in the young in our cohort was characterized by a high frequency of actionable genetic aberrations and a low TMB, which was also true for our older patients. The enrichment of actionable mutations in young patients described in other reports might be attributed to differences in the etiology and clinicopathological characteristics between younger and older patients and therefore not be applicable to all populations.

A Risk-Assessing Signature Based on Hypoxia- and Immune-Related Genes for Prognosis of Lung Adenocarcinoma Patients

Lung Adenocarcinoma (LUAD) drastically influences human health. Tumor hypoxia and immunity impact hugely on the immunotherapeutic effect of LUAD patients. This study is aimed at exploring the prognostic markers associated with hypoxia and immunity in LUAD patients and evaluates their reliability. The relationship between hypoxia and immune-related genes and prognoses of LUAD patients was investigated by the univariate regression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods were used to reveal the enriched pathways and biological processes of prognosis-related genes. Univariate, LASSO, and multivariate Cox regression analyses were used to construct a prognostic signature and verify its independence. The reliability of the signature was evaluated by the Principal Component Analysis (PCA), the Kaplan-Meier (K-M) curve, and the receiver operating characteristic (ROC) curve. Gene set enrichment analysis (GSEA), tumor mutational burden (TMB), and single-sample GSEA (ssGSEA) further verified the performance of the signature. Finally, a prognostic signature for LUAD was constructed based on 7 hypoxia- and immune-related genes. According to riskScores acquired from the signature, the test set was divided into groups, where the prognosis of high-risk patients was poor. The feature genes had good reliability, and the riskScore could be used as an independent prognostic factor for LUAD patients. Meanwhile, high TMB scores and low immune scores were found in high-risk patients, and feature genes were enriched in signaling pathways such as cell cycle and p53 signaling pathway. In sum, a prognostic signature based on 7 hypoxia- and immune-related genes was constructed.

Pharmacogenomic Cluster Analysis of Lung Cancer Cell Lines Provides Insights into Preclinical Model Selection in NSCLC

Human lung cell lines are utilized widely for investigating tumor biology, experimental therapy, anticancer drug screening and biomarkers identification. However, the consistency of drug responses of these established cell lines and non-small cell lung cancer (NSCLC) is uncertain. In this study, we assessed the drug response consistency between lung cell lines and NSCLC tumors in The Cancer Genome Atlas by hierarchical clustering using copy number variations in driver genes, and profiled the molecular patterns and correlations in cell lines. We found that some frequently used cell lines of NSCLC subtypes were not clustered with their matched subtypes of tumor. Mutation profiles in the oxidative stress response and squamous differentiation pathway in lung cell lines were in concordance with lung squamous cell carcinoma. Furthermore, lung cell lines and tumors in the same sub-cluster had very similar responses to certain drugs but some were inconsistent, suggesting that clustering through copy number variation data could capture part of the suitability of lung cell lines. The analysis of these results could aid investigators in evaluating drug response models and eventually enabling personalized treatment recommendations for individual patients with NSCLC.

LINC00887 Fosters Development of Clear Cell Renal Cell Carcinoma via Inhibiting CD8+ T Cell Immune Infiltration

BACKGROUND

lncRNAs affect adaptive and innate immunity of cancer via mediating functional states of immune cells, genes, and pathways. Nonetheless, little is known about the molecular mechanism of lncRNA-mediated CD8+ T cell immune infiltration in progression of clear cell renal cell carcinoma (ccRCC). We designed this work to investigate the role of LINC00887 in regulating CD8+ T cell immune infiltration in ccRCC.

METHODS

Correlation between LINC00887 and immune factors and the expression level of LINC00887 in ccRCC were analyzed by bioinformatics methods (TCGA-KIRC database, "edgeR" package, "clusterProfiler" package, and "CIBERSORT" package). LINC00887 expression in ccRCC was examined via RT-qPCR. The cytokilling capacity of CD8+ T cells was evaluated by the lactate dehydrogenase assay. The apoptotic ability of CD8+ T cells was measured by flow cytometry. The chemotactic ability of CD8+ T cells was revealed by chemotaxis assay. CXCR3, CXCL9, and CXCL10 levels were assessed by RT-qPCR.

RESULTS

As suggested by bioinformatics analysis, LINC00887 was markedly upregulated in ccRCC patients and associated with expression of immune-suppression molecule, thereby abating the immune infiltration level of CD8+ cells in tumor tissue. As revealed by cellular assay, LINC00887 was upregulated in ccRCC cells, and knockdown of LINC00887 resulted in a decreased PD-L1 expression, increased CD8+ T cell toxicity, decreased apoptotic levels, and enhanced chemotaxis. Moreover, we found that LINC00887 exhibited inhibitory effect on immune infiltration of CD8+ cells in clinical tissues.

CONCLUSIONS

The results of this study suggested that LINC00887 promoted ccRCC progression by inhibiting immune infiltration of CD8+ T cells, providing new insights into pathogenesis of ccRCC and suggesting LINC00887 being a promising immunotherapy target for ccRCC.

Clinical, Pathological, and Molecular Characteristics of Diffuse Spinal Cord Gliomas

Diffuse spinal cord gliomas (SCGs) are rare tumors associated with a high morbidity and mortality that affect both pediatric and adult populations. In this retrospective study, we sought to characterize the clinical, pathological, and molecular features of diffuse SCG in 22 patients with histological and molecular analyses. The median age of our cohort was 23.64 years (range 1-82) and the overall median survival was 397 days. K27M mutation was significantly more prevalent in males compared to females. Gross total resection and chemotherapy were associated with improved survival, compared to biopsy and no chemotherapy. While there was no association between tumor grade, K27M status (p = 0.366) or radiation (p = 0.772), and survival, males showed a trend toward shorter survival. K27M mutant tumors showed increased chromosomal instability and a distinct DNA methylation signature.

Constructing a novel gene signature derived from oxidative stress specific subtypes for predicting survival in stomach adenocarcinoma

Oxidative stress (OS) response is crucial in oncogenesis and progression of tumor. But the potential prognostic importance of OS-related genes (OSRGs) in stomach adenocarcinoma (STAD) lacked comprehensive study. STAD clinical information and transcriptome data were retrieved from the Gene Expression Omnibus and The Cancer Genome Atlas databases. The prognostic OSRGs were filtered via the univariate Cox analysis and OSRG-based molecular subtypes of STAD were developed using consensus clustering. Weighted gene co-expression network analysis (WGCNA) was subsequently conducted to filter molecular subtype-associated gene modules. The prognosis-related genes were screened via univariate and least absolute shrinkage and selection operator Cox regression analysis were used to construct a prognostic risk signature. Finally, a decision tree model and nomogram were developed by integrating risk signature and clinicopathological characteristics to analyze individual STAD patient’s survival. Four OSRG-based molecular subtypes with significant diversity were developed based on 36 prognostic OSRGs for STAD, and an OSRGs-based subtype-specific risk signature with eight genes for prognostic prediction of STAD was built. Survival analysis revealed a strong prognostic performance of the risk signature exhibited in predicting STAD survival. There were significant differences in mutation patterns, chemotherapy sensitivity, clinicopathological characteristics, response to immunotherapy, biological functions, immune microenvironment, immune cell infiltration among different molecular subtypes and risk groups. The risk score and age were verified as independent risk factors for STAD, and a nomogram integrating risk score and age was established, which showed superior predictive performance for STAD prognosis. We developed an OSRG-based molecular subtype and identified a novel risk signature for prognosis prediction, providing a useful tool to facilitate individual treatment for patients with STAD.

TCF7L2 promotes anoikis resistance and metastasis of gastric cancer by transcriptionally activating PLAUR

Gastric cancer (GC) is the most common gastrointestinal malignant tumor, and distant metastasis is a critical factor in the prognosis of patients with GC. Understanding the mechanism of GC metastasis will help improve patient prognosis. Studies have confirmed that urokinase-type plasminogen activator receptor (PLAUR) promotes GC metastasis; however, its relationship with anoikis resistance and associated mechanisms remains unclear. In this study, we demonstrated that PLAUR promotes the anoikis resistance and metastasis of GC cells and identified transcription Factor 7 Like 2 (TCF7L2) as an important transcriptional regulator of PLAUR. We also revealed that TCF7L2 is highly expressed in GC and promotes the anoikis resistance and metastasis of GC cells. Moreover, we found that TCF7L2 transcription activates PLAUR. Finally, we confirmed that TCF7L2 is an independent risk factor for poor prognosis of patients with GC. Our results show that TCF7L2 and PLAUR are candidate targets for developing therapeutic strategies for GC metastasis.

Somatic mutations in DCC are associated with genomic instability and favourable outcomes in melanoma patients treated with immune checkpoint inhibitors

BACKGROUND

Deleted in colorectal cancer (DCC) encodes a transmembrane dependence receptor and is frequently mutated in melanoma. The associations of DCC mutation with chromosomal instability and immunotherapeutic efficacy in melanoma are largely uncharacterised.

METHODS

We performed an integrated study based on biological experiments and multi-dimensional data types, including genomic, transcriptomic and clinical immune checkpoint blockade (ICB)-treated melanoma cohorts from public databases.

RESULTS

DCC mutation was significantly correlated with the tumour mutational burden (TMB) in The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and ICB-treated melanoma cohorts. DCC expression levels were correlated with DNA damage response and repair (DDR) pathways responsive to irradiation (IR) in the Malme-3M and SK-MEL-2 cell lines. In the TCGA cohort, DCC-mutated samples presented more neoantigens, higher proportions of infiltrating antitumour immunocytes and lower proportions of infiltrating pro-tumour immunocytes than DCC wild-type samples. DCC-mutated samples were significantly enriched in activated immune response and DDR pathways. Furthermore, patients harbouring mutated DCC treated with ICB showed remarkable clinical benefits in terms of the response rate and overall survival.

CONCLUSIONS

Somatic mutations in DCC are associated with improved clinical outcomes in ICB-treated melanoma patients. Once further validated, the DCC mutational status can improve patient selection for clinical practice and future study enrolment.

Usefulness of circulating tumor DNA from cerebrospinal fluid in recurrent high-grade glioma

Molecular documentation at relapse of high-grade glioma is an urgent need for patient care. A prospective pilot study was conducted to assess the rate of mutation detection using targeted deep sequencing on circulating tumor DNA from cerebrospinal fluid (CSF) after chemo-radiotherapy based treatment. Fifteen patients were included: 13 patients with glioblastoma, 1 patient with gliosarcoma and 1 patient with anaplastic astrocytoma. At progression, 10/15 patients (67%) had detectable mutations in the CSF. Among them, 5/10 patients harbored at least one common mutation between initial tumor and ctDNA. CSF protein level and cfDNA concentration were higher, although not significant, in the ctDNA positive group versus ctDNA negative group (1.17g/L vs. 0.79g/L). Molecular documentation obtained from ctDNA in CSF at the time of relapse is informative in around two-thirds of the patients.

Tumor treating fields affect mesothelioma cell proliferation by exerting histotype-dependent cell cycle checkpoint activations and transcriptional modulations

Although clinical antitumor activity of Tumor Treating Fields (TTFields) has been reported in malignant pleural mesothelioma (MPM) patients, the mechanisms behind the different selectivity displayed by the various MPM histotypes to this physical therapy has not been elucidated yet. Taking advantage of the development of well characterized human MPM cell lines derived from pleural effusion and/or lavages of patients' thoracic cavity, we investigated the biological effects of TTFields against these cells, representative of epithelioid, biphasic, and sarcomatoid histotypes. Growth inhibition and cell cycle perturbations caused by TTFields were investigated side by side with RNA-Seq analyses at different exposure times to identify pathways involved in cell response to treatment. We observed significant differences of response to TTFields among the cell lines. Cell cycle analysis revealed that the most sensitive cells (epithelioid CD473) were blocked in G₂M phase followed by formation of polyploid cells. The least sensitive cells (sarcomatoid CD60) were only slightly affected by TTFields with a general delay in all cell cycle phases. Apoptosis was present in all samples, but while epithelioid cell death was already observed during the first 24 h of treatment, sarcomatoid cells needed longer times before they engaged apoptotic pathways. RNA-Seq experiments demonstrated that TTFields induced a transcriptional response already detectable at early time points (8 h). The number of differentially expressed genes was higher in CD473 than in CD60 cells, involving several pathways, such as those pertinent to cell cycle checkpoints, DNA repair, and histone modifications. Our data provide further support to the notion that the antitumor effects of TTFields are not simply related to a non-specific reaction to a physical stimulus, but are dependent on the biological background of the cells and the particular sensitivity to TTFields observed in epithelioid MPM cells is associated with a higher transcriptional activity than that observed in sarcomatoid models.