Identification of Tumor Mutation Burden, Microsatellite Instability, and Somatic Copy Number Alteration derived 9-gene Signatures to Predict Clinical Outcomes in STAD

Background: Genomic features including tumor mutation burden (TMB), microsatellite instability (MSI) and somatic copy number alteration (SCNA), had been demonstrated to be involved with the tumor microenvironment (TME) and outcome of gastric cancer (GC). Methods: We obtained profiles of TMB, MSI and SCNA by processing 405 GC data from The Cancer Genome Atlas (TCGA), then conducted a comprehensive analysis though “iClusterPlus”. Another independent Gene Expression Omnibus (GEO) contained specimens from 109 GC patients was designed as an external validation. Results: Two subgroups were generated, with distinguished prognosis, somatic mutation burden, copy number changes and immune landscape. We revealed that Cluster1 was marked by a better prognosis, accompanied by higher TMB, MSIsensor score, TMEscore, and lower SCNA burden. Based on these clusters, we screened 196 differentially expressed genes (DEGs), which were subsequently projected into univariate Cox survival analysis. Thus, we constructed a 9-gene immune risk score (IRS) model using lasso penalized logistic regression. Moreover, the prognostic prediction of IRS was verified by receiver operating characteristic (ROC) curve analysis and nomogram plot.Conclusions: Our works suggested that the 9‐gene‐signature prediction model, which derived from TMB, MSI, SCNA was a promising predictive tool for clinical outcome in GC patients. This novel methodology may help clinicians uncover the underlying mechanisms and guide future treatment strategies.

Integrated exome and RNA sequencing of TFE3-translocation renal cell carcinoma

TFE3-translocation renal cell carcinoma (TFE3-tRCC) is a rare and heterogeneous subtype of kidney cancer that has no standard treatment for advanced disease. We described comprehensive molecular characteristics of 63 untreated primary TFE3-tRCCs based on whole-exome and RNA sequencing. TFE3-tRCC is highly heterogeneous, both clinicopathologically and genotypically. ASPSCR1-TFE3 fusion, certain fusion isoforms and high somatic copy number alteration burdens were associated with aggressive features and poor outcomes. Apart from tumors with MED15-TFE3 fusion, most TFE3-tRCCs exhibited low PD-L1 expression and low T-cell infiltration. Unsupervised transcriptomic analysis revealed five molecular clusters with distinct angiogenesis, stroma, proliferation and KRAS down signatures, which showed association with fusion patterns and prognosis. Specifically, the high angiogenesis/stroma/proliferation cluster exclusively consisted of tumors with ASPSCR1-TFE3 fusion, which was likely to benefit from combination of immune checkpoint and anti-angiogenesis inhibitors. Our findings reveal the genomic and transcriptomic features of TFE3-tRCC and provide insights into precision medicine for this disease.

Histone Methyltransferases Useful in Gastric Cancer Research

Gastric cancer (GC) is one of the most frequent tumors in the world. Stomach adenocarcinoma is a heterogeneous tumor, turning the prognosis prediction and patients’ clinical management difficult. Some diagnosis tests for GC are been development using knowledge based in polymorphisms, somatic copy number alteration (SCNA) and aberrant histone methylation. This last event, a posttranslational modification that occurs at the chromatin level, is an important epigenetic alteration seen in several tumors including stomach adenocarcinoma. Histone methyltransferases (HMT) are the proteins responsible for the methylation in specific amino acids residues of histones tails. Here, were presented several HMTs that could be relating to GC process. We use public data from 440 patients with stomach adenocarcinoma. We evaluated the alterations as SCNAs, mutations, and genes expression level of HMTs in these aforementioned samples. As results, it was identified the 10 HMTs most altered (up to 30%) in stomach adenocarcinoma samples, which are the PRDM14, PRDM9, SUV39H2, NSD2, SMYD5, SETDB1, PRDM12, SUV39H1, NSD3, and EHMT2 genes. The PRDM9 gene is among most mutated and amplified HMTs within the data set studied. PRDM14 is downregulated in 79% of the samples and the SUV39H2 gene is down expressed in patients with recurred/progressed disease. Several HMTs are altered in many cancers. It is important to generate a genetic atlas of alterations of cancer-related genes to improve the understanding of tumorigenesis events and to propose novel tools of diagnosis and prognosis for the cancer control.

Comprehensive Genomic Review of TCGA Head and Neck Squamous Cell Carcinomas (HNSCC)

The aim of this present study was to comprehensively describe somatic DNA alterations and transcriptional alterations in the last extension of the HNSCC subsets in TCGA, encompassing a total of 528 tumours. In order to achieve this goal, transcriptional analysis, functional enrichment assays, survival analysis, somatic copy number alteration analysis and somatic alteration analysis were carried out. A total of 3491 deregulated genes were found in HNSCC patients, and the functional analysis carried out determined that tissue development and cell differentiation were the most relevant signalling pathways in upregulated and downregulated genes, respectively. Somatic copy number alteration analysis showed a “top five” altered HNSCC genes: CDKN2A (deleted in 32.03% of patients), CDKN2B (deleted in 28.34% of patients), PPFIA1 (amplified in 26.02% of patients), FADD (amplified in 25.63% of patients) and ANO1 (amplified in 25.44% of patients). Somatic mutations analysis revealed TP53 mutation in 72% of the tumour samples followed by TTN (39%), FAT1 (23%) and MUC16 (19%). Another interesting result is the mutual exclusivity pattern that was discovered between the TP53 and PIK3CA mutations, and the co-occurrence of CDKN2A with the TP53 and FAT1 alterations. On analysis to relate differential expression genes and somatic copy number alterations, some genes were overexpressed and amplified, for example, FOXL2, but other deleted genes also showed overexpression, such as CDKN2A. Survival analysis revealed that overexpression of some oncogenes, such as EGFR, CDK6 or CDK4 were associated with poorer prognosis tumours. These new findings help us to develop new therapies and programs for the prevention of HNSCC.

Chromosomal instability of circulating tumor DNA reflect therapeutic responses in advanced gastric cancer

Gastric cancer is characterized by chromosomal instability. In this study, we investigated chromosomal instability quantified by copy number instability (CNI) score of circulating tumor DNA (ctDNA) during the drug treatment in advanced gastric cancer (AGC). A total of 55 pretherapeutic plasmas from 55 AGC patients and 75 plasmas during drug treatment of 26 AGC patients were collected. Plasma ctDNA was extracted and assessed by whole-genome sequencing (WGS) for somatic copy number alteration (SCNA), and according to which we calculated the CNI scores. We next assessed the correlations between chromosomal instability and therapeutic response. The cutoff value of chromosomal instability was defined as the mean + SD of the CNI scores (56.60) in cfDNA of plasmas from 100 healthy people. For 55 enrolled cases, chromosomal instability was observed in 27 (49%) prior to drug treatment, whose response rate (59%, 16/27) was higher than in 28 patients with stable chromosomes (32%, 9/28, P = 0.043). We also observed that CNI scores fluctuated during treatment in 26 patients. Specifically, the CNI scores in 93% (14/15) of patients sensitive to drug treatment reduced to the level of chromosomal stability and the CNI scores in 52% (13/25) of patients resistant to treatment elevated again. For ctDNA with developed resistance, the SCNA patterns were identical to those before treatment, whereas the CNI scores were lower than the pretherapeutic scores. We found that chromosomal instability based on ctDNA could predict and monitor therapeutic response in gastric cancer, although validation in a larger cohort will be necessary.

DEFOR: depth- and frequency-based somatic copy number alteration detector

Motivation Detection of somatic copy number alterations (SCNAs) using high-throughput sequencing has become popular because of rapid developments in sequencing technology. Existing methods do not perform well in calling SCNAs for the unstable tumor genomes. Results We developed a new method, DEFOR, to detect SCNAs in tumor samples from exome-sequencing data. The evaluation showed that DEFOR has a higher accuracy for SCNA detection from exome sequencing compared with the five existing tools. This advantage is especially apparent in unstable tumor genomes with a large proportion of SCNAs. Availability and implementation DEFOR is available at https://github.com/drzh/defor. Supplementary information Supplementary data are available at Bioinformatics online.