Single-cell RNA-Seq of follicular lymphoma reveals malignant B-cell types and coexpression of T-cell immune checkpoints.

Follicular lymphoma (FL) is a low-grade B-cell malignancy that transforms into a highly aggressive and lethal disease at a rate of 2% per year. Perfect isolation of the malignant B-cell population from a surgical biopsy is a significant challenge, masking important FL biology, such as immune checkpoint coexpression patterns. To resolve the underlying transcriptional networks of follicular B-cell lymphomas, we analyzed the transcriptomes of 34 188 cells derived from 6 primary FL tumors. For each tumor, we identified normal immune subpopulations and malignant B cells, based on gene expression. We used multicolor flow cytometry analysis of the same tumors to confirm our assignments of cellular lineages and validate our predictions of expressed proteins. Comparison of gene expression between matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin (Ig) light chain expression (either Igκ or Igλ), as well the expected upregulation of the BCL2 gene, but also downregulation of the FCER2, CD52, and major histocompatibility complex class II genes. By analyzing thousands of individual cells per patient tumor, we identified the mosaic of malignant B-cell subclones that coexist within a FL and examined the characteristics of tumor-infiltrating T cells. We identified genes coexpressed with immune checkpoint molecules, such as CEBPA and B2M in regulatory T (Treg) cells, providing a better understanding of the gene networks involved in immune regulation. In summary, parallel measurement of single-cell expression in thousands of tumor cells and tumor-infiltrating lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.

Tandem Oligonucleotide Probe Annealing and Elongation To Discriminate Viral Sequence.

New approaches for genomic DNA/RNA detection are in high demand in order to provide controls for existing enzymatic technologies and to create alternatives for emerging applications. In particular, there is an unmet need in rapid, reliable detection of short RNA regions which could open up new opportunities in transcriptome analysis, virology, and other fields. Herein, we report for the first time a "click" chemistry approach to oligonucleotide probe elongation as a novel approach to specifically detect a viral sequence. We hybridized a library of short, terminally labeled probes to Ebola virus RNA followed by click assembly and analysis of the read sequence by various techniques. As we demonstrate in this paper, using our new approach, a viral RNA sequence can be detected in less than 2 h without the need for cDNA synthesis or any other enzymatic reactions and with a sensitivity of <10 pM target RNA.

The Gastric Cancer Registry: A Genomic Translational Resource for Multidisciplinary Research in Gastric Cancer.

BACKGROUND: Gastric cancer is a leading cause of cancer morbidity and mortality. Developing information systems which integrate clinical and genomic data may accelerate discoveries to improve cancer prevention, detection, and treatment. To support translational research in gastric cancer, we developed the Gastric Cancer Registry (GCR), a North American repository of clinical and cancer genomics data. METHODS: Participants self-enrolled online. Entry criteria into the GCR included the following: (i) diagnosis of gastric cancer, (ii) history of gastric cancer in a first- or second-degree relative, or (iii) known germline mutation in the gene CDH1. Participants provided demographic and clinical information through a detailed survey. Some participants provided specimens of saliva and tumor samples. Tumor samples underwent exome sequencing, whole-genome sequencing, and transcriptome sequencing. RESULTS: From 2011 to 2021, 567 individuals registered and returned the clinical questionnaire. For this cohort 65% had a personal history of gastric cancer, 36% reported a family history of gastric cancer, and 14% had a germline CDH1 mutation. 89 patients with gastric cancer provided tumor samples. For the initial study, 41 tumors were sequenced using next-generation sequencing. The data was analyzed for cancer mutations, copy-number variations, gene expression, microbiome, neoantigens, immune infiltrates, and other features. We developed a searchable, web-based interface (the GCR Genome Explorer) to enable researchers' access to these datasets. CONCLUSIONS: The GCR is a unique, North American gastric cancer registry which integrates clinical and genomic annotation. IMPACT: Available for researchers through an open access, web-based explorer, the GCR Genome Explorer will accelerate collaborative gastric cancer research across the United States and world.

Characterization of the consensus mucosal microbiome of colorectal cancer.

Dysbioisis is an imbalance of an organ's microbiome and plays a role in colorectal cancer pathogenesis. Characterizing the bacteria in the microenvironment of a cancer through genome sequencing has advantages compared to culture-based profiling. However, there are notable technical and analytical challenges in characterizing universal features of tumor microbiomes. Colorectal tumors demonstrate microbiome variation among different studies and across individual patients. To address these issues, we conducted a computational study to determine a consensus microbiome for colorectal cancer, analyzing 924 tumors from eight independent RNA-Seq data sets. A standardized meta-transcriptomic analysis pipeline was established with quality control metrics. Microbiome profiles across different cohorts were compared and recurrently altered microbial shifts specific to colorectal cancer were determined. We identified cancer-specific set of 114 microbial species associated with tumors that were found among all investigated studies. Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria were among the four most abundant phyla for the colorectal cancer microbiome. Member species of Clostridia were depleted and Fusobacterium nucleatum was one of the most enriched bacterial species in tumors. Associations between the consensus species and specific immune cell types were noted. Our results are available as a web data resource for other researchers to explore (https://crc-microbiome.stanford.edu).

Joint single cell DNA-seq and RNA-seq of gastric cancer cell lines reveals rules of in vitro evolution.

Cancer cell lines are not homogeneous nor are they static in their genetic state and biological properties. Genetic, transcriptional and phenotypic diversity within cell lines contributes to the lack of experimental reproducibility frequently observed in tissue-culture-based studies. While cancer cell line heterogeneity has been generally recognized, there are no studies which quantify the number of clones that coexist within cell lines and their distinguishing characteristics. We used a single-cell DNA sequencing approach to characterize the cellular diversity within nine gastric cancer cell lines and integrated this information with single-cell RNA sequencing. Overall, we sequenced the genomes of 8824 cells, identifying between 2 and 12 clones per cell line. Using the transcriptomes of more than 28 000 single cells from the same cell lines, we independently corroborated 88% of the clonal structure determined from single cell DNA analysis. For one of these cell lines, we identified cell surface markers that distinguished two subpopulations and used flow cytometry to sort these two clones. We identified substantial proportions of replicating cells in each cell line, assigned these cells to subclones detected among the G0/G1 population and used the proportion of replicating cells per subclone as a surrogate of each subclone's growth rate.

Whole genome analysis identifies the association of TP53 genomic deletions with lower survival in Stage III colorectal cancer.

DNA copy number aberrations (CNA) are frequently observed in colorectal cancers (CRC). There is an urgent need for CNA-based biomarkers in clinics,. n For Stage III CRC, if combined with imaging or pathologic evidence, these markers promise more precise care. We conducted this Stage III specific biomarker discovery with a cohort of 134 CRCs, and with a newly developed high-efficiency CNA profiling protocol. Specifically, we developed the profiling protocol for tumor-normal matched tissue samples based on low-coverage clinical whole-genome sequencing (WGS). We demonstrated the protocol's accuracy and robustness by a systematic benchmark with microarray, high-coverage whole-exome and -genome approaches, where the low-coverage WGS-derived CNA segments were highly accordant (PCC >0.95) with those derived from microarray, and they were substantially less variable if compared to exome-derived segments. A lasso-based model and multivariate cox regression analysis identified a chromosome 17p loss, containing the TP53 tumor suppressor gene, that was significantly associated with reduced survival (P = 0.0139, HR = 1.688, 95% CI = [1.112-2.562]), which was validated by an independent cohort of 187 Stage III CRCs. In summary, this low-coverage WGS protocol has high sensitivity, high resolution and low cost and the identified 17p-loss is an effective poor prognosis marker for Stage III patients.