Mutational signature and prognosis in adenocarcinoma of the bladder.

Adenocarcinoma of the bladder is a rare urinary bladder carcinoma with limited therapy options due to lack of molecular characterization. Here, we aimed to reveal the mutational and transcriptomic landscapes of adenocarcinoma of the bladder and assess any relationship with prognosis. Between February 2015 and June 2021, a total of 23 patients with adenocarcinoma of the bladder were enrolled. These included 16 patients with primary bladder adenocarcinomas and seven patients with urachal adenocarcinoma. Whole exome sequencing (16 patients), whole genome sequencing (16 patients), bulk RNA sequencing (RNA-seq) (19 patients), and single-cell RNA-seq (5 patients) were conducted for the specimens. Correlation analysis, survival analysis, and t-tests were also performed. Prevalent T>A substitutions were observed among somatic mutations, and major trinucleotide contexts included 5'-CTC-3' and 5'-CTG-3'. This pattern was mainly contributed by COSMIC signature 22 related to chemical carcinogen exposure (probably aristolochic acid), which has not been reported in bladder adenocarcinoma. Moreover, genes with copy number changes were also enriched in the KEGG term 'chemical carcinogenesis'. Transcriptomic analysis suggested high immune cell infiltration and luminal-like features in the majority of samples. Interestingly, a small fraction of samples with an APOBEC-derived mutational signature exhibited a higher risk of disease progression compared with samples with only a chemical carcinogen-related signature, confirming the molecular and prognostic heterogeneity of bladder adenocarcinoma. This study presents mutational and transcriptomic landscapes of bladder adenocarcinoma, and indicates that a chemical carcinogen-related mutational signature may be related to a better prognosis compared with an APOBEC signature in adenocarcinoma of the bladder. © 2024 The Pathological Society of Great Britain and Ireland.

scCURE identifies cell types responding to immunotherapy and enables outcome prediction.

A deep understanding of immunotherapy response/resistance mechanisms and a highly reliable therapy response prediction are vital for cancer treatment. Here, we developed scCURE (single-cell RNA sequencing [scRNA-seq] data-based Changed and Unchanged cell Recognition during immunotherapy). Based on Gaussian mixture modeling, Kullback-Leibler (KL) divergence, and mutual nearest-neighbors criteria, scCURE can faithfully discriminate between cells affected or unaffected by immunotherapy intervention. By conducting scCURE analyses in melanoma and breast cancer immunotherapy scRNA-seq data, we found that the baseline profiles of specific CD8+ T and macrophage cells (identified by scCURE) can determine the way in which tumor microenvironment immune cells respond to immunotherapy, e.g., antitumor immunity activation or de-activation; therefore, these cells could be predictive factors for treatment response. In this work, we demonstrated that the immunotherapy-associated cell-cell heterogeneities revealed by scCURE can be utilized to integrate the therapy response mechanism study and prediction model construction.

Single-cell RNA sequencing reveals the heterogeneity and intercellular communication of hepatic stellate cells and macrophages during liver fibrosis.

Uncontrolled and excessive progression of liver fibrosis is thought to be the prevalent pathophysiological cause of liver cirrhosis and hepatocellular cancer, and there are currently no effective antifibrotic therapeutic options available. Intercellular communication and cellular heterogeneity in the liver are involved in the progression of liver fibrosis, but the exact nature of the cellular phenotypic changes and patterns of interregulatory remain unclear. Here, we performed single-cell RNA sequencing on nonparenchymal cells (NPCs) isolated from normal and fibrotic mouse livers. We identified eight main types of cells, including endothelial cells, hepatocytes, dendritic cells, B cells, natural killer/T (NK/T) cells, hepatic stellate cells (HSCs), cholangiocytes and macrophages, and revealed that macrophages and HSCs exhibit the most variance in transcriptional profile. Further analyses of HSCs and macrophage subpopulations and ligand-receptor interaction revealed a high heterogeneity characterization and tightly interregulated network of these two groups of cells in liver fibrosis. Finally, we uncovered a profibrotic Thbs1+ macrophage subcluster, which expands in mouse and human fibrotic livers, activating HSCs via PI3K/AKT/mTOR signaling pathway. Our findings decode unanticipated insights into the heterogeneity of HSCs and macrophages and their intercellular crosstalk at a single-cell level, and may provide potential therapeutic strategies in liver fibrosis.

Accurate tumor clonal structures require single-cell analysis.

Tumor clonal structure is closely related to future progression, which has been mainly investigated as mutation abundance clustering in bulk samples. With relatively limited studies at single-cell resolution, a systematic comparison of the two approaches is still lacking. Here, using bulk and single-cell mutational data from the liver and colorectal cancers, we checked whether co-mutations determined by single-cell analysis had corresponding bulk variant allele frequency (VAF) peaks. While bulk analysis suggested the absence of subclonal peaks and, possibly, neutral evolution in some cases, the single-cell analysis identified coexisting subclones. The overlaps of bulk VAF ranges for co-mutations from different subclones made it difficult to separate them. Complex subclonal structures and dynamic evolution could be hidden under the seemingly clonal neutral pattern at the bulk level, suggesting single-cell analysis is necessary to avoid underestimation of tumor heterogeneity.

Inhibition of Arid1a increases stem/progenitor cell-like properties of liver cancer.

ARID1A, a key subunit of the SWI/SNF chromatin remodeling complex, exhibits recurrent mutations in various types of human cancers, including liver cancer. However, the function of ARID1A in the pathogenesis of liver cancer remains controversial. Here, we demonstrate that Arid1a knockout may result in states of different cell differentiation, as indicated by single-cell RNA sequencing (scRNA-seq) analysis. Bulk RNA-seq also revealed that Arid1a deficiency upregulated these genes related to cell stemness and differentiation, but downregulated genes related to the hepatic functions. Furthermore, we confirmed that deficiency of Arid1a increased the expression of hepatic stem/progenitor cell markers, such as Cd133 and Epcam, and enhanced the self-renewal ability of cells. Mechanistic studies revealed that Arid1a loss remodeled the chromatin accessibility of some genes related to liver functions. Thus, Arid1a deficiency might contribute to cancer development by increasing the number of stem/progenitor-like cells through dysregulating the expression of these genes related to cell stemness, differentiation and liver functions.

Cinobufagin Is a Selective Anti-Cancer Agent against Tumors with EGFR Amplification and PTEN Deletion.

Glioblastoma multiforme (GBM) is the most common and malignant brain tumor, and almost half of the patients carrying EGFR-driven tumor with PTEN deficiency are resistant to EGFR-targeted therapy. EGFR amplification and/or mutation is reported in various epithelial tumors. This series of studies aimed to identify a potent compound against EGFR-driven tumor. We screened a chemical library containing over 600 individual compounds purified from Traditional Chinese Medicine against GBM cells with EGFR amplification and found that cinobufagin, the major active ingredient of Chansu, inhibited the proliferation of EGFR amplified GBM cells and PTEN deficiency enhanced its anti-proliferation effects. Cinobufagin also strongly inhibited the proliferation of carcinoma cell lines with wild-type or mutant EGFR expression. In contrast, the compound only weakly inhibited the proliferation of cancer cells with low or without EGFR expression. Cinobufagin blocked EGFR phosphorylation and its downstream signaling, which additionally induced apoptosis and cytotoxicity in EGFR amplified cancer cells. In vivo, cinobufagin blocked EGFR signaling, inhibited cell proliferation, and elicited apoptosis, thereby suppressing tumor growth in both subcutaneous and intracranial U87MG-EGFR xenograft mouse models and increasing the median survival of nude mice bearing intracranial U87MG-EGFR tumors. Cinobufagin is a potential therapeutic agent for treating malignant glioma and other human cancers expressing EGFR.

Discovery of Novel PTP1B Inhibitors Derived from the BH3 Domain of Proapoptotic Bcl-2 Proteins with Antidiabetic Potency.

BH3 peptide analogues are generally believed to exhibit great potency as cancer therapeutics via targeting antiapoptotic Bcl-2 proteins. Here, we describe the synthesis and identification of a new class of palmitoylated peptide BH3 analogues derived from the core region (h1-h4) of BH3 domains of proapoptotic Bcl-2 proteins and as alternative PTP1B inhibitors with antidiabetic potency in vitro and in vivo. PTP1B inhibitors are attractive for treatment of type 2 diabetes. We design the analogues using a simple lipidation approach and discovered novel lead analogues with promising antidiabetic potency in vitro and in vivo. The results presented here expanded the alternative target and function for the BH3 peptide analogues from one member Bim to other members of the proapoptotic Bcl-2 proteins and emphasize their therapeutic potential in T2DM. Furthermore, our findings may provide new proof of the regulatory function of Bcl-2 family proteins in mitochondrial nutrient and energy metabolism.

Clonal evolution in liver cancer at single-cell and single-variant resolution.

Genetic heterogeneity of tumor is closely related to its clonal evolution, phenotypic diversity and treatment resistance, and such heterogeneity has only been characterized at single-cell sub-chromosomal scale in liver cancer. Here we reconstructed the single-variant resolution clonal evolution in human liver cancer based on single-cell mutational profiles. The results indicated that key genetic events occurred early during tumorigenesis, and an early metastasis followed by independent evolution was observed in primary liver tumor and intrahepatic metastatic portal vein tumor thrombus. By parallel single-cell RNA-Seq, the transcriptomic phenotype of HCC was found to be related with genetic heterogeneity. For the first time we reconstructed the single-cell and single-variant clonal evolution in human liver cancer, and dissection of both genetic and phenotypic heterogeneity will facilitate better understanding of their relationship.

LZP is required for hepatic triacylglycerol transportation through maintaining apolipoprotein B stability.

The conserved zona pellucida (ZP) domain is found in hundreds of extracellular proteins that are expressed in various organs and play a variety of roles as structural components, receptors and tumor suppressors. A liver-specific zona pellucida domain-containing protein (LZP), also named OIT3, has been shown to be mainly expressed in human and mouse hepatocytes; however, the physiological function of LZP in the liver remains unclear. Here, we show that Lzp deletion inhibited very low-density lipoprotein (VLDL) secretion, leading to hepatic TG accumulation and lower serum TG levels in mice. The apolipoprotein B (apoB) levels were significantly decreased in the liver, serum, and VLDL particles of LZP-deficient mice. In the presence of LZP, which is localized to the endoplasmic reticulum (ER) and Golgi apparatus, the ER-associated degradation (ERAD) of apoB was attenuated; in contrast, in the absence of LZP, apoB was ubiquitinated by AMFR, a known E3 ubiquitin ligase specific for apoB, and was subsequently degraded, leading to lower hepatic apoB levels and inhibited VLDL secretion. Interestingly, hepatic LZP levels were elevated in mice challenged with a high-fat diet and humans with simple hepatic steatosis, suggesting that LZP contributes to the physiological regulation of hepatic TG homeostasis. In general, our data establish an essential role for LZP in hepatic TG transportation and VLDL secretion by preventing the AMFR-mediated ubiquitination and degradation of apoB and therefore provide insight into the molecular function of LZP in hepatic lipid metabolism.

A novel neoantigen discovery approach based on chromatin high order conformation.

BACKGROUND: High-throughput sequencing technology has yielded reliable and ultra-fast sequencing for DNA and RNA. For tumor cells of cancer patients, when combining the results of DNA and RNA sequencing, one can identify potential neoantigens that stimulate the immune response of the T cell. However, when the somatic mutations are abundant, it is computationally challenging to efficiently prioritize the identified neoantigen candidates according to their ability of activating the T cell immuno-response. METHODS: Numerous prioritization or prediction approaches have been proposed to address this issue but none of them considers the original DNA loci of the neoantigens from the perspective of 3D genome. Based on our previous discoveries, we propose to investigate the distribution of neoantigens with different immunogenicity abilities in 3D genome and propose to adopt this important information into neoantigen prediction. RESULTS: We retrospect the DNA origins of the immuno-positive and immuno-negative neoantigens in the context of 3D genome and discovered that DNA loci of the immuno-positive neoantigens and immuno-negative neoantigens have very different distribution pattern. Specifically, comparing to the background 3D genome, DNA loci of the immuno-positive neoantigens tend to locate at specific regions in the 3D genome. We thus used this information into neoantigen prediction and demonstrated the effectiveness of this approach. CONCLUSION: We believe that the 3D genome information will help to increase the precision of neoantigen prioritization and discovery and eventually benefit precision and personalized medicine in cancer immunotherapy.

DeepAntigen: a novel method for neoantigen prioritization via 3D genome and deep sparse learning.

MOTIVATION: The mutations of cancers can encode the seeds of their own destruction, in the form of T-cell recognizable immunogenic peptides, also known as neoantigens. It is computationally challenging, however, to accurately prioritize the potential neoantigen candidates according to their ability of activating the T-cell immunoresponse, especially when the somatic mutations are abundant. Although a few neoantigen prioritization methods have been proposed to address this issue, advanced machine learning model that is specifically designed to tackle this problem is still lacking. Moreover, none of the existing methods considers the original DNA loci of the neoantigens in the perspective of 3D genome which may provide key information for inferring neoantigens' immunogenicity. RESULTS: In this study, we discovered that DNA loci of the immunopositive and immunonegative MHC-I neoantigens have distinct spatial distribution patterns across the genome. We therefore used the 3D genome information along with an ensemble pMHC-I coding strategy, and developed a group feature selection-based deep sparse neural network model (DNN-GFS) that is optimized for neoantigen prioritization. DNN-GFS demonstrated increased neoantigen prioritization power comparing to existing sequence-based approaches. We also developed a webserver named deepAntigen (http://yishi.sjtu.edu.cn/deepAntigen) that implements the DNN-GFS as well as other machine learning methods. We believe that this work provides a new perspective toward more accurate neoantigen prediction which eventually contribute to personalized cancer immunotherapy. AVAILABILITY AND IMPLEMENTATION: Data and implementation are available on webserver: http://yishi.sjtu.edu.cn/deepAntigen. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mutational and transcriptomic landscapes of a rare human prostate basal cell carcinoma.

BACKGROUND: As a rare subtype of prostate carcinoma, basal cell carcinoma (BCC) has not been studied extensively and thus lacks systematic molecular characterization. METHODS: Here, we applied single-cell genomic amplification and RNA-Seq to a specimen of human prostate BCC (CK34ßE12+ /P63+ /PAP- /PSA- ). The mutational landscape was obtained via whole exome sequencing of the amplification mixture of 49 single cells, and the transcriptomes of 69 single cells were also obtained. RESULTS: The five putative driver genes mutated in BCC are CASC5, NUTM1, PTPRC, KMT2C, and TBX3, and the top three nucleotide substitutions are C>T, T>C, and C>A, similar to common prostate cancer. The distribution of the variant allele frequency values indicated that these single cells are from the same tumor clone. The 69 single cells were clustered into tumor, stromal, and immune cells based on their global transcriptomic profiles. The tumor cells specifically express basal cell markers like KRT5, KRT14, and KRT23 and epithelial markers EPCAM, CDH1, and CD24. The transcription factor covariance network analysis showed that the BCC tumor cells have distinct regulatory networks. By comparison with current prostate cancer datasets, we found that some of the bulk samples exhibit basal cell signatures. Interestingly, at single-cell resolution the gene expression patterns of prostate BCC tumor cells show uniqueness compared with that of common prostate cancer-derived circulating tumor cells. CONCLUSIONS: This study, for the first time, discloses the comprehensive mutational and transcriptomic landscapes of prostate BCC, which lays a foundation for the understanding of its tumorigenesis mechanism and provides new insights into prostate cancers in general.

Cancer type prediction based on copy number aberration and chromatin 3D structure with convolutional neural networks.

BACKGROUND: With the developments of DNA sequencing technology, large amounts of sequencing data have been produced that provides unprecedented opportunities for advanced association studies between somatic mutations and cancer types/subtypes which further contributes to more accurate somatic mutation based cancer typing (SMCT). In existing SMCT methods however, the absence of high-level feature extraction is a major obstacle in improving the classification performance. RESULTS: We propose DeepCNA, an advanced convolutional neural network (CNN) based classifier, which utilizes copy number aberrations (CNAs) and HiC data, to address this issue. DeepCNA first pre-process the CNA data by clipping, zero padding and reshaping. Then, the processed data is fed into a CNN classifier, which extracts high-level features for accurate classification. Experimental results on the COSMIC CNA dataset indicate that 2D CNN with both cell lines of HiC data lead to the best performance. We further compare DeepCNA with three widely adopted classifiers, and demonstrate that DeepCNA has at least 78% improvement of performance. CONCLUSIONS: This paper demonstrates the advantages and potential of the proposed DeepCNA model for processing of somatic point mutation based gene data, and proposes that its usage may be extended to other complex genotype-phenotype association studies.

Conditional knockin of Dnmt3a R878H initiates acute myeloid leukemia with mTOR pathway involvement.

DNMT3A is frequently mutated in acute myeloid leukemia (AML). To explore the features of human AML with the hotspot DNMT3A R882H mutation, we generated Dnmt3a R878H conditional knockin mice, which developed AML with enlarged Lin-Sca1+cKit+ cell compartments. The transcriptome and DNA methylation profiling of bulk leukemic cells and the single-cell RNA sequencing of leukemic stem/progenitor cells revealed significant changes in gene expression and epigenetic regulatory patterns that cause differentiation arrest and growth advantage. Consistent with leukemic cell accumulation in G2/M phase, CDK1 was up-regulated due to mTOR activation associated with DNA hypomethylation. Overexpressed CDK1-mediated EZH2 phosphorylation resulted in an abnormal trimethylation of H3K27 profile. The mTOR inhibitor rapamycin elicited a significant therapeutic response in Dnmt3aR878H/WT mice.

Chromatin accessibility contributes to simultaneous mutations of cancer genes.

Somatic mutations of many cancer genes tend to co-occur (termed co-mutations) in certain patterns during tumor initiation and progression. However, the genetic and epigenetic mechanisms that contribute to the co-mutations of these cancer genes have yet to be explored. Here, we systematically investigated the association between the somatic co-mutations of cancer genes and high-order chromatin conformation. Significantly, somatic point co-mutations in protein-coding genes were closely associated with high-order spatial chromatin folding. We propose that these regions be termed Spatial Co-mutation Hotspots (SCHs) and report their occurrence in different cancer types. The conserved mutational signatures and DNA sequences flanking these point co-mutations, as well as CTCF-binding sites, are also enriched within the SCH regions. The genetic alterations that are harboured in the same SCHs tend to disrupt cancer driver genes involved in multiple signalling pathways. The present work demonstrates that high-order spatial chromatin organisation may contribute to the somatic co-mutations of certain cancer genes during tumor development.

Transport of haloacids across biological membranes.

Haloacids are considered to be environmental pollutants, but some of them have also been tested in clinical research. The way that haloacids are transported across biological membranes is important for both biodegradation and drug delivery purposes. In this review, we will first summarize putative haloacids transporters and the information about haloacids transport when studying carboxylates transporters. We will then introduce MCT1 and SLC5A8, which are respective transporter for antitumor agent 3-bromopyruvic acid and dichloroacetic acid, and monochloroacetic acid transporters Deh4p and Dehp2 from a haloacids-degrading bacterium. Phylogenetic analysis of these haloacids transporters and other monocarboxylate transporters reveals their evolutionary relationships. Haloacids transporters are not studied to the extent that they deserve compared with their great application potentials, thus future inter-discipline research are desired to better characterize their transport mechanisms for potential applications in both environmental and clinical fields.