Gastric cancer is the world's third leading cause of cancer mortality. In spite of significant therapeutic improvements, the clinical outcome for patients with advanced gastric cancer is poor; thus, the identification and validation of novel targets is extremely important from a clinical point of view. We generated a wide, multilevel platform of gastric cancer models, comprising 100 patient-derived xenografts (PDX), primary cell lines, and organoids. Samples were classified according to their histology, microsatellite stability, Epstein-Barr virus status, and molecular profile. This PDX platform is the widest in an academic institution, and it includes all the gastric cancer histologic and molecular types identified by The Cancer Genome Atlas. PDX histopathologic features were consistent with those of patients' primary tumors and were maintained throughout passages in mice. Factors modulating grafting rate were histology, TNM stage, copy number gain of tyrosine kinases/KRAS genes, and microsatellite stability status. PDX and PDX-derived cells/organoids demonstrated potential use-fulness to study targeted therapy response. Finally, PDX transcriptomic analysis identified a cancer cell-intrinsic microsatellite instability (MSI) signature, which was efficiently exported to gastric cancer, allowing the identification, among microsatellite stable (MSS) patients, of a subset of MSI-like tumors with common molecular aspects and significant better prognosis. In conclusion, we generated a wide gastric cancer PDX platform, whose exploitation will help identify and validate novel "druggable" targets and optimize therapeutic strategies. Moreover, transcriptomic analysis of gastric cancer PDXs allowed the identification of a cancer cell-intrinsic MSI signature, recognizing a subset of MSS patients with MSI transcriptional traits, endowed with better prognosis.Significance: This study reports a multilevel platform of gastric cancer PDXs and identifies a MSI gastric signature that could contribute to the advancement of precision medicine in gastric cancer.

Immune evasion is a hallmark of cancer and a central mechanism underlying acquired resistance to immune therapy. In allogeneic hematopoietic cell transplantation (alloHCT), late relapses can arise after prolonged alloreactive T-cell control, but the molecular mechanisms of immune escape remain unclear. To identify mechanisms of immune evasion, we performed a genetic analysis of serial samples from 25 patients with myeloid malignancies who relapsed ≥1 year after alloHCT. Using targeted sequencing and microarray analysis to determine HLA allele-specific copy number, we identified copy-neutral loss of heterozygosity events and focal deletions spanning class 1 HLA genes in 2 of 12 recipients of matched unrelated-donor HCT and in 1 of 4 recipients of mismatched unrelated-donor HCT. Relapsed clones, although highly related to their antecedent pretransplantation malignancies, frequently acquired additional mutations in transcription factors and mitogenic signaling genes. Previously, the study of relapse after haploidentical HCT established the paradigm of immune evasion via loss of mismatched HLA. Here, in the context of matched unrelated-donor HCT, HLA loss provides genetic evidence that allogeneic immune recognition may be mediated by minor histocompatibility antigens and suggests opportunities for novel immunologic approaches for relapse prevention.

Variable Number Tandem Repeats (VNTRs) are tandem repeat (TR) loci that vary in copy number across a population. Using our program, VNTRseek, we analyzed human whole genome sequencing datasets from 2770 individuals in order to detect minisatellite VNTRs, i.e., those with pattern sizes ≥7 bp. We detected 35 638 VNTR loci and classified 5676 as commonly polymorphic (i.e. with non-reference alleles occurring in >5% of the population). Commonly polymorphic VNTR loci were found to be enriched in genomic regions with regulatory function, i.e. transcription start sites and enhancers. Investigation of the commonly polymorphic VNTRs in the context of population ancestry revealed that 1096 loci contained population-specific alleles and that those could be used to classify individuals into super-populations with near-perfect accuracy. Search for quantitative trait loci (eQTLs), among the VNTRs proximal to genes, indicated that in 187 genes expression differences correlated with VNTR genotype. We validated our predictions in several ways, including experimentally, through the identification of predicted alleles in long reads, and by comparisons showing consistency between sequencing platforms. This study is the most comprehensive analysis of minisatellite VNTRs in the human population to date.

Variable Number Tandem Repeats (VNTRs) are tandem repeat (TR) loci that vary in copy number across a population. Using our program, VNTRseek, we analyzed human whole-genome sequencing datasets from 2,770 individuals in order to detect minisatellite VNTRs, i.e., those with pattern sizes ranging from 7 bp to 126 bp, and with array lengths up to 230 bp. We detected 35,638 VNTR loci and classified 5,676 as common (occurring in >5% of the population). Common VNTR loci were found to be enriched in genomic regions with regulatory function, i.e., transcription start sites and enhancers. Investigation of the common VNTRs in the context of population ancestry revealed that 1,096 loci contained population-specific alleles and that those could be used to classify individuals into super-populations with near perfect accuracy. Comparison of genotyping results with proximal genes indicated that in 120 cases (118 genes), expression differences correlated with VNTR genotype. We validated our predictions in several ways, including experimentally, through identification of predicted alleles in long reads, and by comparisons showing consistency between sequencing platforms. This study is the most comprehensive analysis of minisatellites VNTRs in the human population to date.

<p>Microsatellite instability (MSI) phenotype in primary gastric tumours and their corresponding PDX/ organoid</p>