Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing.

Systematic interrogation of tumor-infiltrating lymphocytes is key to the development of immunotherapies and the prediction of their clinical responses in cancers. Here, we perform deep single-cell RNA sequencing on 5,063 single T cells isolated from peripheral blood, tumor, and adjacent normal tissues from six hepatocellular carcinoma patients. The transcriptional profiles of these individual cells, coupled with assembled T cell receptor (TCR) sequences, enable us to identify 11 T cell subsets based on their molecular and functional properties and delineate their developmental trajectory. Specific subsets such as exhausted CD8+ T cells and Tregs are preferentially enriched and potentially clonally expanded in hepatocellular carcinoma (HCC), and we identified signature genes for each subset. One of the genes, layilin, is upregulated on activated CD8+ T cells and Tregs and represses the CD8+ T cell functions in vitro. This compendium of transcriptome data provides valuable insights and a rich resource for understanding the immune landscape in cancers.

Decoding the genetic basis of anti-tumor immunity.

Substantial variations of tumor immune properties exist among cancer patients, but the contributing factors underlying those variations are poorly understood. In this issue of Immunity, Sayaman et al. uncover associations between germline genetic variants and tumor immune properties, revealing candidate causal genes.

Lineage tracking reveals dynamic relationships of T cells in colorectal cancer.

T cells are key elements of cancer immunotherapy1 but certain fundamental properties, such as the development and migration of T cells within tumours, remain unknown. The enormous T cell receptor (TCR) repertoire, which is required for the recognition of foreign and self-antigens2, could serve as lineage tags to track these T cells in tumours3. Here we obtained transcriptomes of 11,138 single T cells from 12 patients with colorectal cancer, and developed single T cell analysis by RNA sequencing and TCR tracking (STARTRAC) indices to quantitatively analyse the dynamic relationships among 20 identified T cell subsets with distinct functions and clonalities. Although both CD8+ effector and 'exhausted' T cells exhibited high clonal expansion, they were independently connected with tumour-resident CD8+ effector memory cells, implicating a TCR-based fate decision. Of the CD4+ T cells, most tumour-infiltrating T regulatory (Treg) cells showed clonal exclusivity, whereas certain Treg cell clones were developmentally linked to several T helper (TH) cell clones. Notably, we identified two IFNG+ TH1-like cell clusters in tumours that were associated with distinct IFNγ-regulating transcription factors -the GZMK+ effector memory T cells, which were associated with EOMES and RUNX3, and CXCL13+BHLHE40+ TH1-like cell clusters, which were associated with BHLHE40. Only CXCL13+BHLHE40+ TH1-like cells were preferentially enriched in patients with microsatellite-instable tumours, and this might explain their favourable responses to immune-checkpoint blockade. Furthermore, IGFLR1 was highly expressed in both CXCL13+BHLHE40+ TH1-like cells and CD8+ exhausted T cells and possessed co-stimulatory functions. Our integrated STARTRAC analyses provide a powerful approach to dissect the T cell properties in colorectal cancer comprehensively, and could provide insights into the dynamic relationships of T cells in other cancers.

High-Performance GeTe Thermoelectrics in Both Rhombohedral and Cubic Phases.

GeTe experiences phase transition between cubic and rhombohedral through distortion along the [111] direction. Cubic GeTe shares the similarity of a two-valence-band structure (high-energy L and low-energy Σ bands) with other cubic IV-VI semiconductors such as PbTe, SnTe, and PbSe, and all show a high thermoelectric performance due to a high band degeneracy. Very recently, the two valence bands were found to switch in energy in rhombohedral GeTe and to be split due to symmetry-breaking of the crystal structure. This enables the overall band degeneracy to be manipulated either by the control of symmetry-induced degeneracy or by the design of energy-aligned orbital degeneracy. Here, we show Sb-doping for optimizing carrier concentration and manipulating the degree of rhombohedral lattice distortion to maximize the band degeneracy and then electronic performance. In addition, Sb-doping significantly promotes the solubility of PbTe, enhancing the scattering of phonons by Ge/Pb substitutional defects for minimizing the lattice thermal conductivity. This successfully realizes a superior thermoelectric figure of merit, zT of >2 in both rhombohedral and cubic GeTe, demonstrating these alloys as top candidates for thermoelectric applications at T < 800 K. This work further sheds light on the importance of crystal structure symmetry manipulation for advancing thermoelectrics.

A novel memory-like Tfh cell subset is precursor to effector Tfh cells in recall immune responses.

T follicular helper (Tfh) cells, essential for germinal center reactions, are not identical, with different phenotypes reported. Whether, when, and how they generate memory cells is still poorly understood. Here, through single-cell RNA-sequencing analysis of CXCR5+Bcl6+ Tfh cells generated under different conditions, we discovered, in addition to PD-1hi effector Tfh cells, a CD62L+PD1low subpopulation. CD62L-expressing Tfh cells developed independently from PD-1+ cells and not in direct contact with B cells. More importantly, CD62L+ Tfh cells expressed memory- and stemness-associated genes, and with better superior long-term survival, they readily generated PD-1hi cells in the recall response. Finally, KLF2 and IL7R, also highly expressed by CD62L+ Tfh cells, were required to regulate their development. Our work thus demonstrates a novel Tfh memory-like cell subpopulation, which may benefit our understanding of immune responses and diseases.

STARTRAC analyses of scRNAseq data from tumor models reveal T cell dynamics and therapeutic targets.

Single-cell RNA sequencing is a powerful tool to examine cellular heterogeneity, novel markers and target genes, and therapeutic mechanisms in human cancers and animal models. Here, we analyzed single-cell RNA sequencing data of T cells obtained from multiple mouse tumor models by PCA-based subclustering coupled with TCR tracking using the STARTRAC algorithm. This approach revealed various differentiated T cell subsets and activation states, and a correspondence of T cell subsets between human and mouse tumors. STARTRAC analyses demonstrated peripheral T cell subsets that were developmentally connected with tumor-infiltrating CD8+ cells, CD4+ Th1 cells, and T reg cells. In addition, large amounts of paired TCRα/ß sequences enabled us to identify a specific enrichment of paired public TCR clones in tumor. Finally, we identified CCR8 as a tumor-associated T reg cell marker that could preferentially deplete tumor-associated T reg cells. We showed that CCR8-depleting antibody treatment provided therapeutic benefit in CT26 tumors and synergized with anti-PD-1 treatment in MC38 and B16F10 tumor models.

Pan-cancer single-cell landscape of tumor-infiltrating T cells.

T cells play a central role in cancer immunotherapy, but we lack systematic comparison of the heterogeneity and dynamics of tumor-infiltrating T cells across cancer types. We built a single-cell RNA-sequencing pan-cancer atlas of T cells for 316 donors across 21 cancer types and revealed distinct T cell composition patterns. We found multiple state-transition paths in the exhaustion of CD8+ T cells and the preference of those paths among different tumor types. Certain T cell populations showed specific correlation with patient properties such as mutation burden, shedding light on the possible determinants of the tumor microenvironment. T cell compositions within tumors alone could classify cancer patients into groups with clinical trait specificity, providing new insights into T cell immunity and precision immunotherapy targeting T cells.

SSCC: A Novel Computational Framework for Rapid and Accurate Clustering Large-scale Single Cell RNA-seq Data.

Clustering is a prevalent analytical means to analyze single cell RNA sequencing (scRNA-seq) data but the rapidly expanding data volume can make this process computationally challenging. New methods for both accurate and efficient clustering are of pressing need. Here we proposed Spearman subsampling-clustering-classification (SSCC), a new clustering framework based on random projection and feature construction, for large-scale scRNA-seq data. SSCC greatly improves clustering accuracy, robustness, and computational efficacy for various state-of-the-art algorithms benchmarked on multiple real datasets. On a dataset with 68,578 human blood cells, SSCC achieved 20% improvement for clustering accuracy and 50-fold acceleration, but only consumed 66% memory usage, compared to the widelyused software package SC3. Compared to k-means, the accuracy improvement of SSCC can reach 3-fold. An R implementation of SSCC is available at https://github.com/Japrin/sscClust.

Deep single-cell RNA sequencing data of individual T cells from treatment-naïve colorectal cancer patients.

T cells, as a crucial compartment of the tumour microenvironment, play vital roles in cancer immunotherapy. However, the basic properties of tumour-infiltrating T cells (TILs) such as the functional state, migratory capability and clonal expansion remain elusive. Here, using Smart-seq2 protocol, we have generated a RNA sequencing dataset of 11,138 T cells isolated from peripheral blood, adjacent normal and tumour tissues of 12 colorectal cancer (CRC) patients, including 4 with microsatellite instability (MSI). The dataset contained an expression profile of 10,805 T cells, as well as the full-length T cell receptor (TCR) sequences of 9,878 cells after quality control. To facilitate data mining of our T cell dataset, we developed a web-based application to deliver systematic interrogations and customizable functionalities ( http://crctcell.cancer-pku.cn/ ). Functioning with our dataset, the web tool enables the characterization of TILs based on both transcriptome and assembled TCR sequences at the single cell level, which will help unleash the potential value of our CRC T cell data resource.

Publisher Correction: Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing.

In the version of this article originally published, the P statistic described in Fig. 3d was incorrect. It was described as "P < 22 × 10-16". It should have been "P < 2.2 × 10-16". Also, the "CD8+ Treg" label in Fig. 4f was incorrect. It should have been "CD4+ Treg". The errors have been corrected in the HTML and PDF versions of this article.

Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing.

Cancer immunotherapies have shown sustained clinical responses in treating non-small-cell lung cancer1-3, but efficacy varies and depends in part on the amount and properties of tumor infiltrating lymphocytes4-6. To depict the baseline landscape of the composition, lineage and functional states of tumor infiltrating lymphocytes, here we performed deep single-cell RNA sequencing for 12,346 T cells from 14 treatment-naïve non-small-cell lung cancer patients. Combined expression and T cell antigen receptor based lineage tracking revealed a significant proportion of inter-tissue effector T cells with a highly migratory nature. As well as tumor-infiltrating CD8+ T cells undergoing exhaustion, we observed two clusters of cells exhibiting states preceding exhaustion, and a high ratio of "pre-exhausted" to exhausted T cells was associated with better prognosis of lung adenocarcinoma. Additionally, we observed further heterogeneity within the tumor regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of those activated tumor Tregs, which included IL1R2, correlated with poor prognosis in lung adenocarcinoma. Our study provides a new approach for patient stratification and will help further understand the functional states and dynamics of T cells in lung cancer.

Whole Exome Sequencing Identifies Frequent Somatic Mutations in Cell-Cell Adhesion Genes in Chinese Patients with Lung Squamous Cell Carcinoma.

Lung squamous cell carcinoma (SQCC) accounts for about 30% of all lung cancer cases. Understanding of mutational landscape for this subtype of lung cancer in Chinese patients is currently limited. We performed whole exome sequencing in samples from 100 patients with lung SQCCs to search for somatic mutations and the subsequent target capture sequencing in another 98 samples for validation. We identified 20 significantly mutated genes, including TP53, CDH10, NFE2L2 and PTEN. Pathways with frequently mutated genes included those of cell-cell adhesion/Wnt/Hippo in 76%, oxidative stress response in 21%, and phosphatidylinositol-3-OH kinase in 36% of the tested tumor samples. Mutations of Chromatin regulatory factor genes were identified at a lower frequency. In functional assays, we observed that knockdown of CDH10 promoted cell proliferation, soft-agar colony formation, cell migration and cell invasion, and overexpression of CDH10 inhibited cell proliferation. This mutational landscape of lung SQCC in Chinese patients improves our current understanding of lung carcinogenesis, early diagnosis and personalized therapy.

De novo assembly of soybean wild relatives for pan-genome analysis of diversity and agronomic traits.

Wild relatives of crops are an important source of genetic diversity for agriculture, but their gene repertoire remains largely unexplored. We report the establishment and analysis of a pan-genome of Glycine soja, the wild relative of cultivated soybean Glycine max, by sequencing and de novo assembly of seven phylogenetically and geographically representative accessions. Intergenomic comparisons identified lineage-specific genes and genes with copy number variation or large-effect mutations, some of which show evidence of positive selection and may contribute to variation of agronomic traits such as biotic resistance, seed composition, flowering and maturity time, organ size and final biomass. Approximately 80% of the pan-genome was present in all seven accessions (core), whereas the rest was dispensable and exhibited greater variation than the core genome, perhaps reflecting a role in adaptation to diverse environments. This work will facilitate the harnessing of untapped genetic diversity from wild soybean for enhancement of elite cultivars.

Exome capture sequencing of adenoma reveals genetic alterations in multiple cellular pathways at the early stage of colorectal tumorigenesis.

Most of colorectal adenocarcinomas are believed to arise from adenomas, which are premalignant lesions. Sequencing the whole exome of the adenoma will help identifying molecular biomarkers that can predict the occurrence of adenocarcinoma more precisely and help understanding the molecular pathways underlying the initial stage of colorectal tumorigenesis. We performed the exome capture sequencing of the normal mucosa, adenoma and adenocarcinoma tissues from the same patient and sequenced the identified mutations in additional 73 adenomas and 288 adenocarcinomas. Somatic single nucleotide variations (SNVs) were identified in both the adenoma and adenocarcinoma by comparing with the normal control from the same patient. We identified 12 nonsynonymous somatic SNVs in the adenoma and 42 nonsynonymous somatic SNVs in the adenocarcinoma. Most of these mutations including OR6X1, SLC15A3, KRTHB4, RBFOX1, LAMA3, CDH20, BIRC6, NMBR, GLCCI1, EFR3A, and FTHL17 were newly reported in colorectal adenomas. Functional annotation of these mutated genes showed that multiple cellular pathways including Wnt, cell adhesion and ubiquitin mediated proteolysis pathways were altered genetically in the adenoma and that the genetic alterations in the same pathways persist in the adenocarcinoma. CDH20 and LAMA3 were mutated in the adenoma while NRXN3 and COL4A6 were mutated in the adenocarcinoma from the same patient, suggesting for the first time that genetic alterations in the cell adhesion pathway occur as early as in the adenoma. Thus, the comparison of genomic mutations between adenoma and adenocarcinoma provides us a new insight into the molecular events governing the early step of colorectal tumorigenesis.