Tumor mutation burden (TMB) is an emerging biomarker, whose calculation requires targeted sequencing of many genes. We investigated if the measurement of mutation counts within a single gene is representative of TMB. Whole-exome sequencing (WES) data from the pan-cancer cohort (n = 10,224) of TCGA, and targeted sequencing (tNGS) and TTN gene sequencing from 24 colorectal cancer samples (AMC cohort) were analyzed. TTN was identified as the most frequently mutated gene within the pan-cancer cohort, and its mutation number best correlated with TMB assessed by WES (rho = 0.917, p < 2.2e-16). Colorectal cancer was one of good candidates for the application of this diagnostic model of TTN-TMB, and the correlation coefficients were 0.936 and 0.92 for TMB by WES and TMB by tNGS, respectively. Higher than expected TTN mutation frequencies observed in other FLAGS (FrequentLy mutAted GeneS) are associated with late replication time. Diagnostic accuracy for high TMB group did not differ between TTN-TMB and TMB assessed by tNGS. Classification modeling by machine learning using TTN-TMB for MSI-H diagnosis was constructed, and the diagnostic accuracy was 0.873 by area under the curve in external validation. TTN mutation was enriched in samples possessing high immunostimulatory signatures. We suggest that the mutation load within TTN represents high TMB status.

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Background The intrinsic immuno-ge7nomic characteristics of colorectal cancer cells that affect tumor biology and shape the tumor immune microenvironment (TIM) are unclear. Methods We developed a patient-derived colorectal cancer organoid (CCO) model and performed pairwise analysis of 87 CCOs and their matched primary tumors. The TIM type of the primary tumor was classified as immuno-active, immuno-exhausted, or immuno-desert. Results The gene expression profiles, signaling pathways, major oncogenic mutations, and histology of the CCOs recapitulated those of the primary tumors, but not the TIM of primary tumors. Two distinct intrinsic molecular subgroups of highly proliferative and mesenchymal phenotypes with clinical significance were identified in CCOs with various cancer signaling pathways. CCOs showed variable expression of cancer-specific immune-related genes such as those encoding HLA-I and HLA-II, and molecules involved in immune checkpoint activation/inhibition. Among these genes, the expression of HLA-II in CCOs was associated with favorable patient survival. K-means clustering analysis based on HLA-II expression in CCOs revealed a subgroup of patients, in whom cancer cells exhibited Intrinsically Immunogenic Properties (Ca-IIP), and were characterized by high expression of signatures associated with HLA-I, HLA-II, antigen presentation, and immune stimulation. Patients with the Ca-IIP phenotype had an excellent prognosis, irrespective of age, disease stage, intrinsic molecular type, or TIM status. Ca-IIP was negatively correlated with intrinsic E2F/MYC signaling. Analysis of the correlation between CCO immuno-genotype and TIM phenotype revealed that the TIM phenotype was associated with microsatellite instability, Wnt/β-catenin signaling, APC/KRAS mutations, and the unfolded protein response pathway linked to the FBXW7 mutation in cancer cells. However, Ca-IIP was not associated with the TIM phenotype. Conclusions We identified a Ca-IIP phenotype from a large set of CCOs. Our findings may provide an unprecedented opportunity to develop new strategies for optimal patient stratification in this era of immunotherapy.

Molecular testing is increasingly important in cancer diagnosis. Targeted next generation sequencing (NGS) is widely accepted method but structural variation (SV) detection by targeted NGS remains challenging. In the brain tumor, identification of molecular alterations, including 1p/19q co-deletion, is essential for accurate glial tumor classification. Hence, we used targeted NGS to detect 1p/19q co-deletion using a newly developed deep learning (DL) model in 61 tumors, including 19 oligodendroglial tumors. An ensemble 1-dimentional convolution neural network was developed and used to detect the 1p/19q co-deletion. External validation was performed using 427 low-grade glial tumors from The Cancer Genome Atlas (TCGA). Manual review of the copy number plot from the targeted NGS identified the 1p/19q co-deletion in all 19 oligodendroglial tumors. Our DL model also perfectly detected the 1p/19q co-deletion (area under the curve, AUC = 1) in the testing set, and yielded reproducible results (AUC = 0.9652) in the validation set (n = 427), although the validation data were generated on a completely different platform (SNP Array 6.0 platform). In conclusion, targeted NGS using a cancer gene panel is a promising approach for classifying glial tumors, and DL can be successfully integrated for the SV detection in NGS data.

Background and Aims: Despite the epidemiological association between intrahepatic cholangiocarcinoma (iCCA) and HBV infection, little is known about the relevant oncogenic effects. We sought to identify the landscape and mechanism of HBV integration, along with the genomic architecture of HBV-infected iCCA (HBV-iCCA) tumors. Approach and Results:We profiled a cohort of 108 HBV-iCCAs using wholegenome sequencing, deep sequencing, and RNA sequencing, together with preconstructed data sets of HBV-infected HCC (HBV-HCC; n = 167) and

Dear Editor,The origin and the phenotypic heterogeneity of cancerassociated fibroblasts (CAFs) are suggested by various models, but not completely understood. [1][2][3] We used six publicly available single-cell RNA sequencing (scRNAseq) datasets of five cancer types (except breast cancer) on CAFs and corresponding normal fibroblasts (NFs) (Figure 1A) [4][5][6] and established a comprehensive model for CAF development and gene expression dynamics over time. The fibroblast fraction constituted less than 10% of all cellular components in each dataset (Figure 1B). This relatively low fraction may be ascribed to our two-step, strict procedure for defining fibroblasts.Based on the global gene expression patterns, breast cancer CAFs were markedly different from CAFs from other organs (Figure 1C). K-means clustering with optimal k number calculated using the sum of squared error for each sample and subsequent principal component analyses revealed the presence of several CAF and NF clusters (Figure S1). Based on the recent discovery of PRRX1 as a critical regulator of the fibroblast-specific key transcriptional network, 7 we examined PRRX1 expression in each cluster. None of the NFs exhibited PRRX1 activity, whereas certain CAF clusters showed significantly high PRRX1 expression (Figure 1E). Furthermore, the known CAF-related genes in various functional categories were upregulated only in the CAF clusters with high PRRX1 activity (Figure 1F). Thus, we labeled these CAFs as "perpetually activated CAFs" (paCAFs), which were constituted approximately 50%-80% of all CAFs in each dataset (Figure 1D).Bone marrow-derived mesenchymal stem cells (BM-MSCs) or local tissue-resident (tr)-fibroblasts were suggested as the primary source of CAFs; therefore, we examined BM-MSC markers. 2,8 CAFs generally express higher levels of BM-MSC markers than NFs (Figure S2). Subgroup analysis revealed that the CAF clusters with higherThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Purpose: This work aimed to explore in depth the genomic and molecular underpinnings of hepatocellular carcinoma (HCC) with increased 2[18F]fluoro-2-deoxy-d-glucose (FDG) uptake in PET and to identify therapeutic targets based on this imaging-genomic surrogate. Experimental Design: We used RNA sequencing and whole-exome sequencing data obtained from 117 patients with HCC who underwent hepatic resection with preoperative FDG-PET/CT imaging as a discovery cohort. The primary radiogenomic results were validated with transcriptomes from a second cohort of 81 patients with more advanced tumors. All patients were allocated to an FDG-avid or FDG–non-avid group according to the PET findings. We also screened potential drug candidates targeting FDG-avid HCCs in vitro and in vivo. Results: High FDG avidity conferred worse recurrence-free survival after HCC resection. Whole transcriptome analysis revealed upregulation of mTOR pathway signals in the FDG-avid tumors, together with higher abundance of associated mutations. These clinical and genomic findings were replicated in the validation set. A molecular signature of FDG-avid HCCs identified in the discovery set consistently predicted poor prognoses in the public-access datasets of two cohorts. Treatment with an mTOR inhibitor resulted in decreased FDG uptake followed by effective tumor control in both the hyperglycolytic HCC cell lines and xenograft mouse models. Conclusions: Our PET-based radiogenomic analysis indicates that mTOR pathway genes are markedly activated and altered in HCCs with high FDG retention. This nuclear imaging biomarker may stimulate umbrella trials and tailored treatments in precision care of patients with HCC.

BackgroundSomatic mutations are a major driver of cancer development and many have now been identified in various cancer types, but the comprehensive somatic mutation status of the normal tissues matched to tumours has not been revealed.MethodWe analysed the somatic mutations of whole exome sequencing data in 392 patient tumour and normal tissue pairs based on the corresponding blood samples across 10 tumour types.ResultsMany of the mutations involved in oncogenic pathways such as PI3K, NOTCH and TP53, were identified in the normal tissues. The ageing-related mutational signature was the most prominent contributing signature found and the mutations in the normal tissues were frequently in genes involved in late replication time (p<0.0001). Variants were rarely overlapping across tissue types but shared variants between normal and matched tumour tissue were present. These shared variants were frequently pathogenic when compared with non-shared variants (p=0.001) and showed a higher variant-allele-fraction (p<0.0001). Normal tissue-specific mutated genes were frequently non-cancer-associated (p=0.009). PIK3CA mutations were identified in 6 normal tissues and were harboured by all of the matched cancer tissues. Multiple types of PIK3CA mutations were found in normal breast and matched cancer tissues. The PIK3CA mutations exclusively present in normal tissue may indicate clonal expansions unrelated to the tumour. In addition, PIK3CA mutation was appeared that they arose before the occurrence of the allelic imbalance.ConclusionOur current results suggest that somatic mutant clones exist in normal tissues and that their clonal expansion could be linked to cancer development.