Single-cell sequencing of tumour infiltrating T cells efficiently identifies tumour-specific T cell receptors based on the T cell activation score.

Adoptively transferred T cell receptor-engineered T cells are a promising cancer treatment strategy, and the identification of tumour-specific TCRs is essential. Previous studies reported that tumour-reactive T cells and TCRs could be isolated based on the expression of activation markers. However, since T cells with different cell states could not respond uniformly to activation but show a heterogeneous expression profile of activation and effector molecules, isolation of tumour-reactive T cells based on single activation or effector molecules could result in the absence of tumour-reactive T cells; thus, combinations of multiple activation and effector molecules could improve the efficiency of isolating tumour-specific TCRs. We enrolled two patients with lung adenocarcinoma and obtained their tumour infiltrating lymphocytes (TILs) and autologous tumour cells (ATCs). TILs were cocultured with the corresponding ATCs for 12 h and subjected to single-cell RNA sequencing. First, we identified three TCRs with the highest expression levels of IFNG and TNFRSF9 mRNA for each patient, yet only the top one or two recognized the corresponding ATCs in each patient. Next, we defined the activation score based on normalized expression levels of IFNG, IL2, TNF, IL2RA, CD69, TNFRSF9, GZMB, GZMA, GZMK, and PRF1 mRNA for each T cell and then identified three TCRs with the highest activation score for each patient. We found that all three TCRs in each patient could specifically identify corresponding ATCs. In conclusion, we established an efficient approach to isolate tumour-reactive TCRs based on combinations of multiple activation and effector molecules through single-cell RNA sequencing.

Covert Communication through Robust Fragment Hiding in a Large Number of Images.

For covert communication in lossy channels, it is necessary to consider that the carrier of the hidden watermark will undergo multiple image-processing attacks. In order to ensure that secret information can be extracted without distortion from the watermarked images that have undergone attacks, in this paper, we design a novel fragmented secure communication system. The sender will fragment the secret data to be transmitted and redundantly hide it in a large number of multimodal carriers of messenger accounts on multiple social platforms. The receiver receives enough covert carriers, extracts each fragment, and concatenates the transmitted secret data. This article uses the image carrier as an example to fragment the text file intended for transmission and embeds it into a large number of images, with each fragment being redundant and embedded into multiple images. In this way, at the receiving end, only enough stego images need to be received to extract the information in each image, and then concatenate the final secret file. In order to resist various possible attacks during image transmission, we propose a strong robust image watermarking method. This method adopts a watermark layer based on DFT, which has high embedding and detection efficiency and good invisibility. Secondly, a watermark layer based on DCT is adopted, which can resist translation attacks, JPEG attacks, and other common attacks. Experiments have shown that our watermarking method is very fast; both the embedding time and the extraction time are less than 0.15 s for images not larger than 2000×2000. Our watermarking method has very good invisibility with 41dB PSNR on average. And our watermarking method is more robust than existing schemes and robust to nearly all kinds of attacks. Based on this strong robust image watermarking method, the scheme of fragmenting and hiding redundant transmission content into a large number of images is effective and practical. Our scheme can 100% restore the secret file completely under different RST or hybrid attacks, such as rotation by 1 degree and 5 degrees, scaling by 1.25 and 0.8, and cropping by 10% and 25%. Our scheme can successfully restore the secret file completely even if 30% of received images are lost. When 80% of received images are lost, our scheme can still restore 61.1% of the secret file. If all stego images can be obtained, the original text file can be completely restored.

TCR extracellular domain genetically linked to CD28, 2B4/41BB and DAP10/CD3ζ -engineered NK cells mediates antitumor effects.

NK cells, especially FDA-approved NK-92 cells, could be used for TCR engineering owing to their specialized cytotoxicity against tumors, safety profile and potential use as an off-the-shelf cellular therapy. The TCR complex requires assembly of TCR- α/ ß chains with CD3 molecules (CD3δ, CD3γ, CD3ε, CD3ζ) to be correctly expressed at the cell membrane, and yet NK cells lack expression of these CD3 subunits besides CD3ζ. Since transmembrane regions of TCR α and ß chains are involved in TCR complex assembly, transmembrane regions of TCR replaced by CD28 transmembrane domain could result in the expression of TCR independent of its companion CD3 subunits. However, since the absence of CD3 signaling components can influence the transmission of TCR signals to NK cells, it is necessary to add the signaling molecules of NK cells followed by CD28 transmembrane domain. Both CD3ζ and DAP10 play an important role in the activation and cytotoxicity of NK cells; moreover, 2B4 and 4-1BB are the main costimulatory molecules in NK cells. Therefore, we designed a chimeric TCR that consisted of the extracellular domains of the TCR α and ß chains specific for NYESO-1 fused to the CD28 transmembrane domain followed by the 41BB and CD3ζ signaling domains as well as the 2B4 and DAP10 signaling domain, respectively. The chimeric TCR genetically engineered NK-92 cells exhibit antigen-specific recognition and lysis of tumor cells both in vitro and in vivo. In addition, TCR-28-2B10/BBζ can be feasibly expressed in primary NK cells and exhibit antigen-reactive recognition and effect function. The overall encouraging data highlight the value of NK-92 cells and primary NK cells engineered to express therapeutic chimeric TCR for adoptive immunotherapies.

T cells engineered with full-length NKG2D linked to signaling domains of 4-1BB and CD3ζ show enhanced antitumor activity.

Since NKG2D ligands (NKG2DLs) are primarily overexpressed on multiple types of solid tumors but absent on most normal tissues, NKG2DLs could be optimal antigens for CAR-T cells. To date, there have been two types of NKG2DL CARs: (i) the extracellular domain of NKG2D fused to the CD8a transmembrane domain, signaling domains of 4-1BB and CD3ζ (NKBz) and (ii) full-length NKG2D fused to the CD3ζ signaling domain (chNKz). Although NKBz- and chNKz-engineered T cells both showed antitumor activities, a comparison of their functions has not been reported. In addition, use of the 4-1BB signaling domain into the CAR construct could prolong the persistence and resistance to antitumor activities of CAR-T cells, we designed a new NKG2DL CAR, full-length NKG2D fused to the signaling domains of 4-1BB and CD3ζ (chNKBz). Among the two types of NKG2DL CAR-T cells reported in previous studies, we found that chNKz T cells had stronger antitumor ability than NKBz T cells in vitro, but their antitumor activity in vivo is similar. The chNKBz T cells showed antitumor activity superior to that of chNKz T cells and NKBz T cells in vitro and in vivo, providing a new option for the immunotherapy of NKG2DL-positive tumor patients.

Robust PDF Watermarking against Print-Scan Attack.

Portable document format (PDF) files are widely used in file transmission, exchange, and circulation because of their platform independence, small size, good browsing quality, and the ability to place hyperlinks. However, their security issues are also more thorny. It is common to distribute printed PDF files to different groups and individuals after printing. However, most PDF watermarking algorithms currently cannot resist print-scan attacks, making it difficult to apply them in leak tracing of both paper and scanned versions of PDF documents. To tackle this issue, we propose an invisible digital watermarking technology based on modifying the edge pixels of text strokes to hide information in PDFs, which achieves high robustness to print-scan attacks. Moreover, it cannot be detected by human perception systems. This method focuses on the representation of text by embedding watermarks by changing the features of the text to ensure that changes in these features can be reflected in the scanned PDF after printing. We first segment each text line into two sub-blocks, then select the row of pixels with the most black pixels, and flip the edge pixels closest to this row. This method requires the participation of original PDF documents in detection. The experimental results show that all peak signal-to-noise ratio (PSNR) values of our proposed method exceed 32 dB, which indicates satisfactory invisibility. Meanwhile, this method can extract the hidden information with 100% accuracy under the JPEG compression attack, and has high robustness against noise attacks and print-scan attacks. In the case of no attacks, the watermark can be recovered without any loss. In terms of practical applications, our method can be applied in the practical leak tracing of official paper documents after distribution.

DSSS Signal Detection Based on CNN.

With the wide application of direct sequence spread spectrum (DSSS) signals, the comprehensive performance of DSSS communication systems has been continuously improved, making the electronic reconnaissance link in communication countermeasures more difficult. Electronic reconnaissance technology, as the fundamental means of modern electronic warfare, mainly includes signal detection, recognition, and parameter estimation. At present, research on DSSS detection algorithms is mostly based on the correlation characteristics of DSSS signals, and autocorrelation algorithm is the most mature and widely used method in practical engineering. With the continuous development of deep learning, deep-learning-based methods have gradually been introduced to replace traditional algorithms in the field of signal processing. This paper proposes a spread spectrum signal detection method based on convolutional neural network (CNN). Through experimental analysis, the detection performance of the CNN model proposed in this paper on DSSS signals in various situations has been compared and analyzed with traditional autocorrelation detection methods for different signal-to-noise ratios. The experiments verified the estimation performance of the model in this paper under different signal-to-noise ratios, different spreading code lengths, different spreading code types, and different modulation methods and compared it with the autocorrelation detection algorithm. It was found that the detection performance of the model in this paper was higher than that of the autocorrelation detection method, and the overall performance was improved by 4 dB.

Period Estimation of Spread Spectrum Codes Based on ResNet.

In order to more effectively monitor and interfere with enemy signals, it is particularly important to accurately and efficiently identify the intercepted signals and estimate their parameters in the increasingly complex electromagnetic environment. Therefore, in non-cooperative situations, it is of great practical significance to study how to accurately detect direct sequence spread spectrum (DSSS) signals in real time and estimate their parameters. The traditional time-delay correlation algorithm encounters the challenges such as peak energy leakage and false peak interference. As an alternative, this paper introduces a Pseudo-Noise (PN) code period estimation method utilizing a one-dimensional (1D) convolutional neural network based on the residual network (CNN-ResNet). This method transforms the problem of spread spectrum code period estimation into a multi-classification problem of spread spectrum code length estimation. Firstly, the In-phase/Quadrature(I/Q) two-way of the received DSSS signals is directly input into the CNN-ResNet model, which will automatically learn the characteristics of the DSSS signal with different PN code lengths and then estimate the PN code length. Simulation experiments are conducted using a data set with DSSS signals ranging from -20 to 10 dB in terms of signal-to-noise ratios (SNRs). Upon training and verifying the model using BPSK modulation, it is then put to the test with QPSK-modulated signals, and the estimation performance was analyzed through metrics such as loss function, accuracy rate, recall rate, and confusion matrix. The results demonstrate that the 1D CNN-ResNet proposed in this paper is capable of effectively estimating the PN code period of the non-cooperative DSSS signal, exhibiting robust generalization abilities.

Resampling-Detection-Network-Based Robust Image Watermarking against Scaling and Cutting.

Watermarking is an excellent solution to protect multimedia privacy but will be damaged by attacks such as noise adding, image filtering, compression, and especially scaling and cutting. In this paper, we propose a watermarking scheme to embed the watermark in the DWT-DCT composite transform coefficients, which is robust against normal image processing operations and geometric attacks. To make our scheme robust to scaling operations, a resampling detection network is trained to detect the scaling factor and then rescale the scaling-attacked image before watermark detection. To make our scheme robust to cutting operations, a template watermark is embedded in the Y channel to locate the cutting position. Experiments for various low- and high-resolution images reveal that our scheme has excellent performance in terms of imperceptibility and robustness.

A Real-Time Cup-Detection Method Based on YOLOv3 for Inventory Management.

Inventory is the basis of business activities; inventory management helps industries keep their inventories stocked with reasonable quantities, which ensures consumers demand while minimizing storage costs. The traditional manual inventory management has low efficiency and a high labor cost. In this paper, we used improved YOLOv3 to detect the cups stored on the warehouse shelves and counted their numbers to realize automated inventory management. The warehouse images are collected by the camera and transmitted to the industrial computer, which runs the YOLOv3 network. There are three feature maps in YOLOv3, the two smaller feature maps and the structure behind them are removed, and the k-means algorithm is used to optimize the default anchor size. Moreover, the detection range is limited to a specified area. Experiments show that, by eliminating those two feature maps, the network parameter is reduced from 235 MB to 212 MB, and detection FPS is improved from 48.15 to 54.88 while mAP is improved from 95.65% to 96.65% on our test dataset. The new anchors obtained by the k-means algorithm further improve the mAP to 96.82%. With those improvements, the average error rate of detection is reduced to 1.61%. Restricted detection areas eliminate irrelevant items to ensure the high accuracy of the detection result. The accurately counted number of cups and its change provide significant data for inventory management.

An Efficient Dehazing Algorithm Based on the Fusion of Transformer and Convolutional Neural Network.

The purpose of image dehazing is to remove the interference from weather factors in degraded images and enhance the clarity and color saturation of images to maximize the restoration of useful features. Single image dehazing is one of the most important tasks in the field of image restoration. In recent years, due to the progress of deep learning, single image dehazing has made great progress. With the success of Transformer in advanced computer vision tasks, some research studies also began to apply Transformer to image dehazing tasks and obtained surprising results. However, both the deconvolution-neural-network-based dehazing algorithm and Transformer based dehazing algorithm magnify their advantages and disadvantages separately. Therefore, this paper proposes a novel Transformer-Convolution fusion dehazing network (TCFDN), which uses Transformer's global modeling ability and convolutional neural network's local modeling ability to improve the dehazing ability. In the Transformer-Convolution fusion dehazing network, the classic self-encoder structure is used. This paper proposes a Transformer-Convolution hybrid layer, which uses an adaptive fusion strategy to make full use of the Swin-Transformer and convolutional neural network to extract and reconstruct image features. On the basis of previous research, this layer further improves the ability of the network to remove haze. A series of contrast experiments and ablation experiments not only proved that the Transformer-Convolution fusion dehazing network proposed in this paper exceeded the more advanced dehazing algorithm, but also provided solid and powerful evidence for the basic theory on which it depends.

Helmet Wearing State Detection Based on Improved Yolov5s.

At many construction sites, whether to wear a helmet is directly related to the safety of the workers. Therefore, the detection of helmet use has become a crucial monitoring tool for construction safety. However, most of the current helmet wearing detection algorithms are only dedicated to distinguishing pedestrians who wear helmets from those who do not. In order to further enrich the detection in construction scenes, this paper builds a dataset with six cases: not wearing a helmet, wearing a helmet, just wearing a hat, having a helmet, but not wearing it, wearing a helmet correctly, and wearing a helmet without wearing the chin strap. On this basis, this paper proposes a practical algorithm for detecting helmet wearing states based on the improved YOLOv5s algorithm. Firstly, according to the characteristics of the label of the dataset constructed by us, the K-means method is used to redesign the size of the prior box and match it to the corresponding feature layer to increase the accuracy of the feature extraction of the model; secondly, an additional layer is added to the algorithm to improve the ability of the model to recognize small targets; finally, the attention mechanism is introduced in the algorithm, and the CIOU_Loss function in the YOLOv5 method is replaced by the EIOU_Loss function. The experimental results indicate that the improved algorithm is more accurate than the original YOLOv5s algorithm. In addition, the finer classification also significantly enhances the detection performance of the model.

Pre-depletion of TRBC1+ T cells promotes the therapeutic efficacy of anti-TRBC1 CAR-T for T-cell malignancies.

Targeting T cell receptor ß-chain constant region 1 (TRBC1) CAR-T could specifically kill TRBC1+ T-cell malignancies. However, over-expressed CARs on anti-TRBC1 CAR transduced TRBC1+ T cells (CAR-C1) bound to autologous TRBC1, masking TRBC1 from identification by other anti-TRBC1 CAR-T, and moreover only the remaining unoccupied CARs recognized TRBC1+ cells, considerably reducing therapeutic potency of CAR-C1. In addition, co-culture of anti-TRBC1 CAR-T and TRBC1+ cells could promote exhaustion and terminal differentiation of CAR-T. These findings provide a rationale for pre-depleting TRBC1+ T cells before anti-TRBC1 CAR-T manufacturing.

TCR repertoire intratumor heterogeneity of CD4+ and CD8+ T cells in centers and margins of localized lung adenocarcinomas.

Intratumor heterogeneity (ITH) of T cell receptor (TCR) repertoire in different T-cell subsets and locations in lung adenocarcinomas was unclear. Here, we investigated percentages and TCR repertoire of freshly isolated CD4+ and CD8+ tumor infiltrating lymphocytes (TILs) in tumor centers and margins by flow cytometry on 80 tumor samples from 20 patients and high-throughput TCR sequencing on 27 and 25 samples of CD4+ and CD8+ TILs from seven patients. Our results demonstrated that amount and TCR repertoire diversity of CD4+ TILs were significantly higher than those of CD8+ TILs and moreover substantial ITH regarding amount and TCR repertoire of CD4+ and CD8+ TILs were observed. Additionally, ITH of CD4/CD8 T-cell ratio and CD8+ TIL repertoire across center regions was lower than that across margin regions. The amount and TCR repertoire ITH of CD4+ and CD8+ TILs and mean clonality of CD8+ TILs in tumor centers were associated with relapse. Our study provides insights into amount and TCR repertoire ITH of CD4+ and CD8+ TILs in tumor centers and margins as well as corresponding association with prognosis in lung adenocarcinoma patients, suggesting potential clinical significance of TCR repertoire.

T cell receptor ß-chain repertoire analysis of tumor-infiltrating lymphocytes in pancreatic cancer.

Pancreatic cancer is lethal due to lack of perceptible symptoms and effective treatment methods. Immunotherapy may provide promising therapeutic choices for malignant tumors like pancreatic cancer. Tumor-infiltrating lymphocytes (TIL) in tumor mesenchyme could recognize peptide antigens presented on the surface of tumor cells. The present study aimed to test the relationship between the T cell receptor (TCR) ß repertoire of the tumor and peripheral blood, and also to investigate the intra-tumor spatial heterogeneity of the TCR ß repertoire in pancreatic cancer. To the best of our knowledge, this is the first study to evaluate the clonal composition of TCR ß repertoire in TIL across the spatial extent of pancreatic cancer. In this study, we studied 5 patients who were diagnosed with primary pancreatic cancer. Ultra-deep sequencing was used to assess the rearrangement of the TCR ß-chain (TCR ß) gene. HE staining and immunohistochemistry of CD3, CD4, CD8 and HLA class I were used to show histopathology and immune conditions macroscopically. TIL repertoire showed that different regions of the same tumor showed a greater number of repertoire overlaps between each other than between peripheral blood, which suggested that T cell clones in pancreatic cancer might be quite different from those in peripheral blood. In contrast, intra-tumoral TCR ß repertoires were spatially homogeneous between different regions of a single tumor tissue. Based on these results, we speculated that the cellular adaptive immune response in pancreatic cancer was spatially homogeneous; this may pave the way for immunotherapy for the treatment of pancreatic cancer patients.

Genome-Wide Analysis of Epstein-Barr Virus Isolated from Extranodal NK/T-Cell Lymphoma, Nasal Type.

BACKGROUND: Extranodal natural killer (NK) cell/T-cell lymphoma (NKTCL), a rare type of non-Hodgkin's lymphoma, has strongly been associated with Epstein-Barr virus (EBV) infection. However, there are no EBV genomes isolated from NKTCL, and the roles the variations of EBV strains play in the pathogenesis of NKTCL are still unclear. MATERIALS AND METHODS: In this study, whole EBV genomes from eight primary NKTCL biopsy specimens were obtained using next-generation sequencing, designated NKTCL-EBV1 to NKTCL-EBV8. RESULTS: Compared with the six mostly referenced EBV strains, NKTCL-EBVs closely resemble the GD1 strain but still harbor 2,072 variations, including 1,938 substitutions, 58 insertions, and 76 deletions. The majority of nonsynonymous mutations were located in latent and tegument genes. Moreover, the results from phylogenetic analysis of whole NKTCL genomes and specific genes demonstrated that all the NKTCL-EBVs were related to Asian EBV strains. Based on the amino acid changes in certain residues of latent membrane protein 1 (LMP1) and EBV-determined nuclear antigen 1 (EBNA1), all the NKTCL-EBVs were sorted to China 1 and V-val subtype, respectively. Furthermore, changes in CD4+ and CD8+ T-cell epitopes of EBNA1 and LMP1 may affect the efficacy for a cytotoxic T lymphocyte (CTL)-based therapy. CONCLUSION: This is the first large study to our knowledge to obtain EBV genomes isolated from NKTCL and show the diversity of EBV genomes in a whole genome level by phylogenetic analysis. IMPLICATIONS FOR PRACTICE: In this study, the full-length sequence of Epstein-Barr virus (EBV) isolated from eight patients with nasal natural killer/T-cell lymphoma (NKTCL) was determined and further compared with the sequences previously reported isolated from other malignancies. Phylogenetic analysis showed that NKTCL-EBV strains are close to other Asian subtypes instead of non-Asian ones, leading to the conclusion that EBV infections are more likely affected by different geographic regions rather than particular EBV-associated malignancies. Therefore, these data have implications for the development of effective prophylactic and therapeutic vaccine approaches targeting the personalized or geographic-specific EBV antigens in these aggressive diseases.

Clonal distribution and intratumour heterogeneity of the B-cell repertoire in oesophageal squamous cell carcinoma.

Recent successes in tumour immunotherapies have highlighted the importance of tumour immunity. However, most previous studies to date have focused on T-cell immune response, although B cells are key players in the core immune network and are associated with T-cell immune response. Based on our previous study delineating T-cell receptor (TCR) repertoire in seven patients with oesophageal squamous cell carcinoma (ESCC), this study profiled the B-cell receptor (BCR) repertoire of multiple tumour regions, adjacent normal tissue, and blood from the same seven patients to reveal the characteristics of B-cell immunity and the relationship to TCR repertoire in ESCC patients. We found that intratumour BCR repertoire was significantly more oligoclonal than matched adjacent normal tissue or peripheral blood and, moreover, clonal amplification of B cells in multiple tumour regions was significantly heterogeneous, although clonal amplification of the TCR repertoire across different tissue compartments and regions of the same tumour was similar. However, both BCR and TCR repertoires in the tumour microenvironment were distinct from those in adjacent normal tissues and blood, and thus represented a group of B and T cells that were spatially confined to the tumour microenvironment and could react to tumour antigens. Additionally, B- and T-cell clones varying between different tumour regions showed intratumour heterogeneity of B- and T-cell immune response. Thus, multiple tumour biopsies could be essential to comprehensively delineate the adaptive immune response to an individual ESCC. These findings expand our understanding of adaptive anti-tumour immunity and shed more light on ESCC immunotherapy. This study provides insights into the intratumour heterogeneity of the BCR repertoire as well as the difference and relationship between the BCR and TCR repertoire in ESCC, expanding our understanding of adaptive anti-tumour immunity and ESCC immunotherapy. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Immediate and substantial evolution of T-cell repertoire in peripheral blood and tumor microenvironment of patients with esophageal squamous cell carcinoma treated with preoperative chemotherapy.

Preoperative chemotherapy could decrease tumor size and improve overall survival for esophageal squamous cell carcinoma (ESCC), and moreover, rational combination of chemotherapy and immunotherapy could increase likelihood of inducing an effective antitumor immune response. However, the immunologic impact of chemotherapeutic drugs originally chosen for cancer treatment due to the direct toxicity is poorly understood. We assess the effect of a combination of clinically approved chemotherapeutic drugs [paclitaxel-nedaplatin (PTX-NDP)] on T-cell receptor (TCR) repertoires of peripheral T cells and tumor-infiltrating lymphocytes (TILs) from five patients with primary ESCC. We found that PTX-NDP therapy induced immediate and substantial changes in clonotype frequencies of peripheral T cells and TILs, and moreover, compared with clonal amplification, clonal contraction was more likely to occur in more abundant clones in patients with ESCC. Significant increases in TCR diversity were observed in peripheral T cells but not in TILs after PTX-NDP therapy. Reconstruction of posttreatment TILs was not merely a result of local expansion or contraction of pretreatment TILs, but also-at least in part-a consequence of the migration of peripheral T cells into the chronically inflamed tumor microenvironment. Our findings uncover further insight into T-cell immune response modulated with chemotherapy, providing for theoretical bases for rational combination strategy of chemotherapy and immunotherapy.

Mutation analysis of the EBV-lymphoblastoid cell line cautions their use as antigen-presenting cells.

Lymphoblastoid cell lines (LCLs) have been widely used as professional antigen-presenting cells (APCs). However, neoantigen-loaded LCLs could induce nonspecific T-cell response, which could be due to expression of both Epstein-Barr virus (EBV) antigens and nonsynonymous mutations arising in LCLs. Since the number of passages could influence mutational characteristics of LCLs, and moreover extensive proliferation of LCLs in vitro is necessary to activate T cells for immunotherapy, we comprehensively profiled mutational characteristics by comparing eight sets of B cells and matched high-passage LCLs using whole-exome sequencing in order to assess the effect of nonsynonymous mutations arising in LCLs on nonspecific T-cell response. We found 315 nongermline mutations (approximately 40mut/subject) randomly distributed across all chromosomes including 18 mutations in immunoglobulin V and J genes in eight LCLs, of which 137 candidate neoantigens (approximately 17mut/subject) were identified. The underlying mutational processes linked to EBV-transformed LCLs could be attributed to activation induced cytidine deaminase gene expression which contributes to cytosine mutation clusters in LCLs through cytosine deamination. Pathways significantly enriched by nonsilent mutations of each LCL were totally different among all LCLs. In conclusion, high-passage LCLs may not be suitable to serve as APCs due to random nonsilent mutations, particularly for presentation of neoantigens of low immunogenicity, although further experimental proofs are needed.

Differential DNA methylation profiles of human B lymphocytes and Epstein-Barr virus-immortalized B lymphocytes.

OBJECTIVE: This study aimed to comprehensively assess Epstein-Barr virus (EBV)-induced methylation alterations of B cell across whole genome. METHODS: We compared DNA methylation patterns of primary B cells and corresponding lymphoblastoid cell lines (LCLs) from eight participants. The genome-wide DNA methylation profiles were compared at over 850,000 genome-wide methylation sites. RESULTS: DNA methylation analysis revealed 87,732 differentially methylated CpG sites, representing approximately 12.41% of all sites in LCLs compared to primary B cells. The hypermethylated and hypomethylated CpG sites were about 22.75% or 77.25%, respectively. Only 0.8% of hypomethylated sites and 4.5% of hypermethylated sites were located in CpG islands, whereas 8.0% of hypomethylated sites and 16.3% of hypermethylated sites were located in shore (N_shore and S_shore). Using principal component analysis of the DNA methylation profiles, primary B cells and LCLs could be accurately predicted. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of differently methylated genes revealed that most of the top GO biological processes were related to cell activation and immune response, and some top enrichment pathways were related with activation and malignant transformation of human B cells. CONCLUSIONS: Our study demonstrated genome-wide DNA methylation variations between primary B cells and corresponding LCLs, which might yield new insight on the methylation mechanism of EBV-induced immortalization.

T cell receptor ß-chain repertoire analysis reveals the association between neoantigens and tumour-infiltrating lymphocytes in multifocal papillary thyroid carcinoma.

To explore whether a few nonsynonymous somatic mutations could induce activation and proliferation of neoantigen-specific tumour-infiltrating lymphocytes (TILs) in tumours with low mutation rates, we analysed a patient with multifocal papillary thyroid carcinoma (seven noncontiguous cancer foci) to investigate the relationship between neoantigens and TILs. These seven foci had a few or no nonsynonymous somatic mutations; moreover, multiple loci had similar or different spectra of mutations. We used high-throughput sequencing of the rearranged genes in T cell receptor ß-chain (TCRß) to reveal the basic characteristics of T cells in seven tumour foci and matched adjacent normal tissue. We found that in multifocal papillary thyroid carcinoma the number of nonsynonymous somatic mutations was positively associated with oligoclonal TCRß repertoire, and tumour foci with similar spectra of mutations had higher overlap of TCRß repertoire. In conclusion, the number of nonsynonymous somatic mutations is small in tumours with low mutation rates but these mutations still play an important role in activating neoantigen-specific TILs.