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The landscape of non-coding mutations in cancer progression and immune evasion is largely unexplored. Here, we identify transcrptome-wide somatic and germline 3′ untranslated region (3′-UTR) variants from 375 gastric cancer patients from The Cancer Genome Atlas. By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3′-UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration and T cell receptor diversity. Using a massively parallel reporter assay, we distinguish between causal and correlative effects of 3′-UTR eQTLs in immune-related genes. Our approach identifies numerous 3′-UTR eQTLs and ilQTLs, providing a unique resource for the identification of immunotherapeutic targets and biomarkers. A prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer. The role of non-coding mutations in cancer progression and immune evasion needs to be further explored. Here, the authors investigate the potential of common somatic and germline 3′ untranslated region variants in predicting response to immunotherapy in gastric patients. [ABSTRACT FROM AUTHOR]

The quality of standard single-cell experiments often depends on the immediate processing of cells or tissues post-harvest to preserve fragile and vulnerable cell populations, unless the samples are adequately fixed and stored. Despite the recent rise in popularity of probe-based and aldehyde-fixed RNA assays, these methods face limitations in species and target availability and are not suitable for immunoprofiling or assessing chromatin accessibility. Recently, a reversible fixation strategy known as FixNCut has been successfully deployed to separate sampling from downstream applications in a reproducible and robust manner, avoiding stress or necrosis-related artifacts. In this article, we present an optimized and robust practical guide to the FixNCut protocol to aid the end-to-end adaptation of this versatile method. This protocol not only decouples tissue or cell harvesting from single-cell assays but also enables a flexible and decentralized workflow that unlocks the potential for single-cell analysis as well as unconventional study designs that were previously considered unfeasible. Key features • Reversible fixation: Preserves cellular and molecular structures with the option to later reverse the fixation for downstream applications, maintaining cell integrity • Compatibility with single-cell assays: Supports single-cell genomic assays such as scRNA-seq and ATAC-seq, essential for high-resolution analysis of cell function and gene expression • Flexibility in sample handling: Allows immediate fixation post-collection, decoupling sample processing from analysis, beneficial in settings where immediate processing is impractical • Preservation of RNA and DNA integrity: Effectively preserves RNA and DNA, reducing degradation to ensure accurate transcriptomic and genomic profiling • Suitability for various biological samples: Applicable to a wide range of biological samples, including tissues and cell suspensions, whether freshly isolated or post-dissociated • Enables multi-center studies: Facilitates collaborative research across multiple centers by allowing sample fixation at the point of collection, enhancing research scale and diversity • Avoidance of artifacts: Minimizes stress or necrosis-related artifacts, preserving the natural cellular physiology for accurate genomic and transcriptomic analysis., Competing Interests: Competing interestsH.H. is a co-founder and shareholder of Omniscope, a scientific advisory board member of MiRXES and Nanostring, and a consultant to Moderna and Singularity. L.G.M is an advisor and shareholder of Omniscope, and advisor for ArgenTAG and BioScryb. Omniscope has filed a patent related to the application of the FixNCut protocol. All other authors declare no competing interests., (©Copyright : © 2024 The Authors; This is an open access article under the CC BY-NC license.)

Osteosarcoma is a rare primary bone tumor for which no significant therapeutic advancement has been made since the late 1980s despite ongoing efforts. Overall, the five-year survival rate remains about 65%, and is much lower in patients with tumors unresponsive to methotrexate, doxorubicin, and cisplatin therapy. Genetic studies have not revealed actionable drug targets, but our group, and others, have reported that epigenomic biomarkers, including regulatory RNAs, may be useful prognostic tools for osteosarcoma. We tested if microRNA (miRNA) transcriptional patterns mark the transition from a chemotherapy sensitive to resistant tumor phenotype. Small RNA sequencing was performed using 14 patient matched pre-chemotherapy biopsy and post-chemotherapy resection high-grade osteosarcoma frozen tumor samples. Independently, small RNA sequencing was performed using 14 patient matched biopsy and resection samples from untreated tumors. Separately, miRNA specific Illumina DASL arrays were used to assay an independent cohort of 65 pre-chemotherapy biopsy and 26 patient matched post-chemotherapy resection formalin fixed paraffin embedded (FFPE) tumor samples. mRNA specific Illumina DASL arrays were used to profile 37 pre-chemotherapy biopsy and five post-chemotherapy resection FFPE samples, all of which were also used for Illumina DASL miRNA profiling. The National Cancer Institute Therapeutically Applicable Research to Generate Effective Treatments dataset, including PCR based miRNA profiling and RNA-seq data for 86 and 93 pre-chemotherapy tumor samples, respectively, was also used. Paired differential expression testing revealed a profile of 17 miRNAs with significantly different transcriptional levels following chemotherapy. Genes targeted by the miRNAs were differentially expressed following chemotherapy, suggesting the miRNAs may regulate transcriptional networks. Finally, an in vitro pharmacogenomic screen using miRNAs and their target transcripts predicted response to a set of candidate small molecule therapeutics which potentially reverse the chemotherapy resistance phenotype and synergize with chemotherapy in otherwise treatment resistant tumors. Importantly, these novel therapeutic targets are distinct from targets identified by a similar pharmacogenomic analysis of previously published prognostic miRNA profiles from pre chemotherapy biopsy specimens.

Multiple Myeloma (MM) remains incurable despite advances in treatment options. Although tumor subtypes and specific DNA abnormalities are linked to worse prognosis, the impact of immune dysfunction on disease emergence and/or treatment sensitivity remains unclear. We established a harmonized consortium to generate an Immune Atlas of MM aimed at informing disease etiology, risk stratification, and potential therapeutic strategies. We generated a transcriptome profile of 1,149,344 single cells from the bone marrow of 263 newly diagnosed patients enrolled in the CoMMpass study and characterized immune and hematopoietic cell populations. Associating cell abundances and gene expression with disease progression revealed the presence of a proinflammatory immune senescence-associated secretory phenotype in rapidly progressing patients. Furthermore, signaling analyses suggested active intercellular communication involving APRIL-BCMA, potentially promoting tumor growth and survival. Finally, we demonstrate that integrating immune cell levels with genetic information can significantly improve patient stratification.