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Genome Biology Papers on Tumor Thrombus Transcriptomes, RNA-Seq Method, More

A team from Peking University, the Chinese Academy of Sciences, and elsewhere shares results from a transcriptomic analysis of clear cell renal cell carcinoma (ccRCC) cases marked by venous tumor thrombus (TT), an invasion of the tumor into veins. With single-cell RNA sequencing on 19 ccRCC tumor samples from eight individuals with the kidney cancer who were experiencing tumor thrombus, the researchers saw gene expression shifts in the TT tissue compared to primary tumor samples, including extracellular matrix remodeling and a rise in tissue resident CD8-positive T cells in a "progenitor exhausted" state. "[T]his study provides evidence of phenotypic heterogeneity between primary tumors and tumor thrombus, in terms of tumor cells, immune cells, and stromal cells," the authors report. "Our data can be a valuable resource, facilitating a deeper understanding of the mechanisms associated with tumor thrombus and assisting in developing more effective neoadjuvant molecular therapies and biomarkers for advanced ccRCC patients with TT."

Researchers in Germany and Sweden describe improvements to a barcoding-based bulk RNA sequencing method called prime-seq, an efficient, sensitive, and relatively inexpensive method that builds on prior RNA-seq methods, including single-cell RNA-seq. "[W]e have optimized and validated a bulk RNA-seq method that combines several methodological developments from scRNA-seq to generate a very sensitive and cost-efficient bulk RNA-seq method we call prime-seq," they write, noting that the approach has already been used to sequence transcripts in a wide range of organisms described in published studies. Along with comparisons to other bulk RNA-seq approaches, the team outlined a direct RNA isolation step that was developed and validated in the prime-seq process. The authors suggest that "tag protocols allow flexible designs of RNA-seq experiments that should be helpful for many biological questions and have a vast potential when readily accessible for many labs."

Finally, University of Oxford researchers outline a software tool to search for a target sequence, find sequence orthologs, and place these sequences within a broader phylogenetic tree — a phylogenetic search engine approach that they compared to BLAST searches and conventional phylogenetic tree inference methods. The method, known as SHOOT, "efficiently and accurately places query sequences directly into phylogenetic trees," the team writes. "In this way, the phylogenetic history of the query sequence and its orthologs can be immediately visualized, interpreted, and retrieved."

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