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Abstract Background Lung cancer is the leading cause of cancer death, partially owing to its extensive heterogeneity. The analysis of intertumor heterogeneity has been limited by an inability to concurrently obtain tissue from synchronous metastases unaltered by multiple prior lines of therapy. Methods In order to study the relationship between genomic, epigenomic and T cell repertoire heterogeneity in a rare autopsy case from a 32-year-old female never-smoker with left lung primary late-stage lung adenocarcinoma (LUAD), we did whole-exome sequencing (WES), DNA methylation and T cell receptor (TCR) sequencing to characterize the immunogenomic landscape of one primary and 19 synchronous metastatic tumors. Results We observed heterogeneous mutation, methylation, and T cell patterns across distinct metastases. Only TP53 mutation was detected in all tumors suggesting an early event while other cancer gene mutations were later events which may have followed subclonal diversification. A set of prevalent T cell clonotypes were completely excluded from left-side thoracic tumors indicating distinct T cell repertoire profiles between left-side and non left-side thoracic tumors. Though a limited number of predicted neoantigens were shared, these were associated with homology of the T cell repertoire across metastases. Lastly, ratio of methylated neoantigen coding mutations was negatively associated with T-cell density, richness and clonality, suggesting neoantigen methylation may partially drive immunosuppression. Conclusions Our study demonstrates heterogeneous genomic and T cell profiles across synchronous metastases and how restriction of unique T cell clonotypes within an individual may differentially shape the genomic and epigenomic landscapes of synchronous lung metastases.

Relevant features of T cell repertoire in human cancer remain to be delineated. Here the authors show, by TCR sequencing in a large cohort of lung cancer patients, that while a majority of T cell clones are shared between tumor and adjacent lung tissue, less frequent tumor-unique T cell clones correlate with worse prognosis.

Hepatocellular carcinoma (HCC) accounts for approximately 85–90% of all liver cancer cases and has poor relapse-free survival. There are many gene expression studies that have been performed to elucidate the genetic landscape and driver pathways leading to HCC. However, existing studies have been limited by the sample size and thus the pathogenesis of HCC is still unclear. In this study, we performed an integrated characterization using four independent datasets including 320 HCC samples and 270 normal liver tissues to identify the candidate genes and pathways in the progression of HCC. A total of 89 consistent differentially expression genes (DEGs) were identified. Gene-set enrichment analysis revealed that these genes were significantly enriched for cellular response to zinc ion in biological process group, collagen trimer in the cellular component group, extracellular matrix (ECM) structural constituent conferring tensile strength in the molecular function group, protein digestion and absorption, mineral absorption and ECM-receptor interaction. Network system biology based on the protein–protein interaction (PPI) network was also performed to identify the most connected and important genes based on our DEGs. The top five hub genes including osteopontin (SPP1), Collagen alpha-2(I) chain (COL1A2), Insulin-like growth factor I (IGF1), lipoprotein A (LPA), and Galectin-3 (LGALS3) were identified. Western blot and immunohistochemistry analysis were employed to verify the differential protein expression of hub genes in HCC patients. More importantly, we identified that these five hub genes were significantly associated with poor disease-free survival and overall survival. In summary, we have identified a potential clinical significance of these genes as prognostic biomarkers for HCC patients who would benefit from experimental approaches to obtain optimal outcome.

Somatic rearrangements, which are commonly found in human cancer genomes, contribute to the progression and maintenance of cancers. Conventionally, the verification of somatic rearrangements comprises many manual steps and Sanger sequencing. This is labor intensive when verifying a large number of rearrangements in a large cohort. To increase the verification throughput, we devised a high-throughput workflow that utilizes benchtop next-generation sequencing and in-house bioinformatics tools to link the laboratory processes. In the proposed workflow, primers are automatically designed. PCR and an optional gel electrophoresis step to confirm the somatic nature of the rearrangements are performed. PCR products of somatic events are pooled for Ion Torrent PGM and/or Illumina MiSeq sequencing, the resulting sequence reads are assembled into consensus contigs by a consensus assembler, and an automated BLAT is used to resolve the breakpoints to base level. We compared sequences and breakpoints of verified somatic rearrangements between the conventional and high-throughput workflow. The results showed that next-generation sequencing methods are comparable to conventional Sanger sequencing. The identified breakpoints obtained from next-generation sequencing methods were highly accurate and reproducible. Furthermore, the proposed workflow allows hundreds of events to be processed in a shorter time frame compared with the conventional workflow.

Helicobacter pylori is a gastric pathogen that causes several gastroduodenal disorders such as peptic ulcer disease and gastric cancer. Eradication efforts of H. pylori are often hampered by antimicrobial resistance in many countries, including Vietnam. Here, the study aimed to investigate the occurrence of antimicrobial resistance among H. pylori clinical isolates across 13 hospitals in Vietnam. The study further evaluated the clarithromycin resistance patterns of H. pylori strains. In order to address the study interests, antimicrobial susceptibility testing, epsilometer test and PCR-based sequencing were performed on a total of 193 strains isolated from patients, including 136 children (3–15 years of age) and 57 adults (19–69 years of age). Antimicrobial susceptibility testing showed that the overall resistance to amoxicillin, clarithromycin, levofloxacin, metronidazole, and tetracycline was 10.4%, 85.5%, 24.4%, 37.8%, and 23.8% respectively. The distribution of minimum inhibitory concentrations (MICs) of clarithromycin-resistant strains was 85.5% with MIC >0.5 μg/mL. The majority of the clarithromycin resistant isolates (135 of 165 subjects) have MICs ranging from 2 μg/mL to 16 μg/mL. Furthermore, sequencing detection of mutations in 23S rRNA gene revealed that strains resistant and susceptible to clarithromycin contained both A2143G and T2182C mutations. Of all isolates, eight clarithromycin-resistant isolates (MIC >0.5 μg/mL) had no mutations in the 23S rRNA gene. Collectively, these results demonstrated that a proportion of clarithromycin-resistant H. pylori strains, which are not related to the 23S rRNA gene mutations, could be potentially related to other mechanisms such as the presence of an efflux pump or polymorphisms in the CYP2C19 gene. Therefore, the present study suggests that providing susceptibility testing prior to treatment or alternative screening strategies for antimicrobial resistance is important for future clinical practice. Further studies on clinical guidelines and treatment efficacy are pivotal for successful eradication of H. pylori infection.

Chromatin interactions play important roles in transcription regulation. To better understand the underlying evolutionary and functional constraints of these interactions, we implemented a systems approach to examine RNA polymerase-II-associated chromatin interactions in human cells. We found that 40% of the total genomic elements involved in chromatin interactions converged to a giant, scale-free-like, hierarchical network organized into chromatin communities. The communities were enriched in specific functions and were syntenic through evolution. Disease-associated SNPs from genome-wide association studies were enriched among the nodes with fewer interactions, implying their selection against deleterious interactions by limiting the total number of interactions, a model that we further reconciled using somatic and germline cancer mutation data. The hubs lacked disease-associated SNPs, constituted a nonrandomly interconnected core of key cellular functions, and exhibited lethality in mouse mutants, supporting an evolutionary selection that favored the nonrandom spatial clustering of the least-evolving key genomic domains against random genetic or transcriptional errors in the genome. Altogether, our analyses reveal a systems-level evolutionary framework that shapes functionally compartmentalized and error-tolerant transcriptional regulation of human genome in three dimensions.