Single-Cell Sequencing Reveals Trajectory of Tumor-Infiltrating Lymphocyte States in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) has few effective treatments. Immunotherapy, an attractive alternative strategy, remains challenging with the lack of knowledge on the tumor-infiltrating lymphocyte (TIL) landscape in PDAC. To generate a reference of T-cell subpopulations, we profiled 80,000 T cells from 57 PDAC samples, 22 uninvolved/normal samples, and cultured TIL using single-cell transcriptomic and T-cell receptor analysis. These data revealed 20 cell states and heterogeneous distributions of TIL populations. The CD8+ TIL contained a putative transitional GZMK+ population based on T-cell receptor clonotype sharing, and cell-state trajectory analysis showed similarity to a GZMB+PRF1+ cytotoxic and a CXCL13+ dysfunctional population. Statistical analysis suggested that certain TIL states, such as dysfunctional and inhibitory populations, often occurred together. Finally, analysis of cultured TIL revealed that high-frequency clones from effector populations were preferentially expanded. These data provide a framework for understanding the PDAC TIL landscape for future TIL use in immunotherapy for PDAC

Targeting T Cell Checkpoints 41BB and LAG3 and Myeloid Cell CXCR1/CXCR2 Results in Antitumor Immunity and Durable Response in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is considered non-immunogenic, with trials showing its recalcitrance to PD1 and CTLA4 immune checkpoint therapies (ICTs). Here, we sought to systematically characterize the mechanisms underlying de novo ICT resistance and to identify effective therapeutic options for PDAC. We report that agonist 41BB and antagonist LAG3 ICT alone and in combination, increased survival and antitumor immunity, characterized by modulating T cell subsets with antitumor activity, increased T cell clonality and diversification, decreased immunosuppressive myeloid cells and increased antigen presentation/decreased immunosuppressive capability of myeloid cells. Translational analyses confirmed the expression of 41BB and LAG3 in human PDAC. Since single and dual ICTs were not curative, T cell-activating ICTs were combined with a CXCR1/2 inhibitor targeting immunosuppressive myeloid cells. Triple therapy resulted in durable complete responses. Given similar profiles in human PDAC and the availability of these agents for clinical testing, our findings provide a testable hypothesis for this lethal disease

A Spatially Resolved Single-Cell Genomic Atlas of the Adult Human Breast

The adult human breast is comprised of an intricate network of epithelial ducts and lobules that are embedded in connective and adipose tissue1-3. Although most previous studies have focused on the breast epithelial system4-6, many of the non-epithelial cell types remain understudied. Here we constructed the comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics study profiled 714,331 cells from 126 women, and 117,346 nuclei from 20 women, identifying 12 major cell types and 58 biological cell states. These data reveal abundant perivascular, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Spatial mapping using four different technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells, as well as distinct molecular differences between ductal and lobular regions. Collectively, these data provide a reference of the adult normal breast tissue for studying mammary biology and diseases such as breast cancer

Characterization of the Interactions Between Kaposi’s Sarcoma-Associated Herpesvirus ORF57 and Its RNA Partners

Kaposi's sarcoma-associated herpesvirus (KSHV; HHV-8) is a human gammaherpesvirus and the etiological agent of Kaposi's sarcoma (KS), the most common AIDS-associated malignancy. Like all herpesviruses, KSHV has evolved mechanisms to modulate both host and viral gene expression. The essential and multifunctional KSHV ORF57 protein has been reported to enhance viral gene expression at multiple levels including transcription, splicing, mRNA export, RNA stability, and translation. At least in some cases, direct interactions between ORF57 and its target RNAs are necessary for ORF57-mediated upregulation of viral gene expression. The work highlighted in this document reveals our current efforts to study the elements driving ORF57's binding specificity. We started by studying a known ORF57 target: the KSHV polyadenylated nuclear (PAN) RNA, a nuclear non-coding transcript of unknown function that is highly expressed during lytic stage. We first devised an in vitro binding assay to identify the regions in PAN RNA that were bound by ORF57. These PAN RNA fragments were also inserted into the 3' UTR of an intronless β-globin reporter to test ORF57 responsiveness in vivo. Our analyses revealed an ORF57 responsive element (ORE) at the 5' end of PAN RNA that we hypothesize functions as a high-affinity binding site to recruit ORF57. Next, we optimized the high-throughput sequencing of RNAs isolated by crosslinking and immunoprecipitation (HITS-CLIP) protocol to identify novel host and viral targets of ORF57 in the context of viral infection. Bioinformatic analysis of potential host ORF57 targets reveals that ORF57 binding is enriched near the 5' end of the transcripts and often close to the first exon-intron junction. Preferential binding at the 5' end is also seen for PAN RNA. However, our data suggests that ORF57 binding to other viral genes can be promiscuous and that, in some cases, binding can occur at multiple sites across the target RNAs. Through these studies, we hope to provide further insight into the requirements for ORF57 binding and potentially shed light into the mechanisms controlling gene expression of this oncogenic virus

HITS-CLIP Analysis Uncovers a Link between the Kaposi’s Sarcoma-Associated Herpesvirus ORF57 Protein and Host Pre-mRNA Metabolism

<div><p>The Kaposi’s sarcoma associated herpesvirus (KSHV) is an oncogenic virus that causes Kaposi’s sarcoma, primary effusion lymphoma (PEL), and some forms of multicentric Castleman’s disease. The KSHV ORF57 protein is a conserved posttranscriptional regulator of gene expression that is essential for virus replication. ORF57 is multifunctional, but most of its activities are directly linked to its ability to bind RNA. We globally identified virus and host RNAs bound by ORF57 during lytic reactivation in PEL cells using high-throughput sequencing of RNA isolated by cross-linking immunoprecipitation (HITS-CLIP). As expected, ORF57-bound RNA fragments mapped throughout the KSHV genome, including the known ORF57 ligand PAN RNA. In agreement with previously published ChIP results, we observed that ORF57 bound RNAs near the oriLyt regions of the genome. Examination of the host RNA fragments revealed that a subset of the ORF57-bound RNAs was derived from transcript 5´ ends. The position of these 5´-bound fragments correlated closely with the 5´-most exon-intron junction of the pre-mRNA. We selected four candidates (BTG1, EGR1, ZFP36, and TNFSF9) and analyzed their pre-mRNA and mRNA levels during lytic phase. Analysis of both steady-state and newly made RNAs revealed that these candidate ORF57-bound pre-mRNAs persisted for longer periods of time throughout infection than control RNAs, consistent with a role for ORF57 in pre-mRNA metabolism. In addition, exogenous expression of ORF57 was sufficient to increase the pre-mRNA levels and, in one case, the mRNA levels of the putative ORF57 targets. These results demonstrate that ORF57 interacts with specific host pre-mRNAs during lytic reactivation and alters their processing, likely by stabilizing pre-mRNAs. These data suggest that ORF57 is involved in modulating host gene expression in addition to KSHV gene expression during lytic reactivation.</p></div

Sequence reads across various viral genomic loci.

<p>Mapped sequence reads of input (top) and pellet (bottom) from one biological replicate for the region surrounding (A) PAN RNA (left) and oriLyt-L (right). (B) Additional loci in which enriched clusters were observed in the high stringency dataset. (C) ORF58-ORF59 region, which was only identified in the low stringency dataset. In all panels, reads from only one strand are shown which is indicated by the plus or minus signs. The black bars above the peaks in the pellet panels mark the positions of the enriched clusters from the high stringency dataset whereas the blue bars were observed only in the low stringency dataset. The color schemes for genes are the same as <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004652#ppat.1004652.g002" target="_blank">Fig. 2</a>. The numbers at the top left of each frame are proportional to the number of reads stacked in a given window. The asterisks approximate the positions of T→C or deletion mutations observed in the pellets.</p

Identification of enriched clusters mapping to the KSHV genome.

<p>(A) Outline of the bioinformatic pipeline used to identify enriched clusters. (B) Genomic location of KSHV enriched clusters. The x-axis represents position on the KSHV genome (U75698) and the midpoint of each cluster was used as the x-coordinate. KSHV enriched clusters ranged from 19–3679 nt; the mean enriched cluster length was 176 nt and the median was 79 nt. A statistical cutoff of 0.001 was used to define enriched clusters (dashed lines). For display, the RNA fragments mapping to the KSHV plus strand were assigned -log₁₀(p-values) (black) while the minus strand clusters are displayed as log₁₀(p-values) (orange). (C) Detailed examination of the enriched clusters from KSHV genome position 23kb-40kb. The plus and minus strands are in black and orange as in (B) but both are displayed as p-value. For the genome annotations shown at the bottom of the graph, plus strand ORFs are black arrows, minus strand ORFs are orange arrows, oriLyt-L elements are in green, and RNAs with potential noncoding functions are purple. Orange arrows point to enriched clusters on PAN RNA minus strand.</p

Candidate ORF57-bound pre-RNAs display distinct steady-state level kinetics during lytic reactivation.

<p>RNA was harvested at the indicated time points subsequent to lytic reactivation of TREx BCBL1-Rta cells. (A) mRNA, (B) pre-mRNA, or (C) control RNA levels were monitored by RT-qPCR; positions of primers are shown in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004652#ppat.1004652.g005" target="_blank">Fig. 5</a>. Values were first normalized to 7SK RNA and the corresponding value for the 8 hpi time point was set to 1.0. 7SK RNA panel was only normalized to values from 8 hpi, but each experiment used equal amounts of total RNA. Mean values and standard deviation are shown (n = 3).</p

Newly made candidate ORF57-bound pre-RNAs have distinct kinetics during lytic reactivation.

<p>(A) Schematic of the time course used for 4SU metabolic labeling experiments. Cells were incubated with 4SU for two hours beginning at -2 and 10 hpi. Cells were collected and RNAs were extracted at 0 and 12 hpi, respectively. (B) Newly made RNA levels were monitored by RT-qPCR with the primers described in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004652#ppat.1004652.g005" target="_blank">Fig. 5</a>. The RT-qPCR values are listed relative to the 0 hpi samples which were set to 1.0. Note that the y-axis scales differ between the panels. The-4SU samples were collected at the same time and processed alongside the other samples, but the cells were not treated with 4SU. Mean values are shown and error bars are standard deviation (n = 3). (C) The data from (B) were plotted for direct comparison between controls (GAPDH and β-actin) and ORF57-bound candidates (EGR1, BTG1, ZFP36, and TNFSF9). The y-axis is on a log scale and the values are presented as the percent relative to the uninduced samples. The dotted line represents 100%.</p