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Summary: DNA sequencing continues to get cheaper and faster. In parallel, algorithmic innovations have allowed inference of a wide range of nuclear, mitochondrial, somatic and evolutionary from DNA sequencing data. To make automated, high-quality DNA sequencing more readily available, we created an extensible Nextflow meta-pipeline called metapipeline-DNA. Metapipeline-DNA supports processing raw sequencing reads through alignment, variant detection, quality control and subclonal reconstruction. Each step supports quality-control, data-visualization and multiple algorithms. Metapipeline-DNA is cloud-compatible and highly configurable, with options to subsect, optimize and optimize analyses, including with automated failure-recovery. Metapipeline-DNA enables high-scale, fault-tolerant, comprehensive analysis of genome sequencing., Availability: Metapipeline-DNA is an open-source Nextflow pipeline under the GPLv2 license and is available at https://github.com/uclahs-cds/metapipeline-DNA., Competing Interests: Conflict of Interest Statement PCB sits on the Scientific Advisory Boards of Intersect Diagnostics Inc., BioSymetrics Inc. and previously sat on that of Sage Bionetworks. All other authors have no conflicts of interest to declare.

We developed and evaluated the Digital Platform for Exercise (DPEx): a decentralized, patient-centric approach designed to enhance all aspects of clinical investigation of exercise therapy. DPEx integrated provision of a treadmill with telemedicine and remote biospecimen collection permitting all study procedures to be conducted in patient's homes. Linked health biodevices enabled high-resolution monitoring of lifestyle and physiological response. Here we describe the rationale and development of DPEx as well as feasibility evaluation in three different cohorts of patients with cancer: a phase 0a development study among three women with post-treatment primary breast cancer; a phase 0b proof-of-concept trial of neoadjuvant exercise therapy in 13 patients with untreated solid tumors; and a phase 1a level-finding trial of neoadjuvant exercise therapy in 53 men with localized prostate cancer. Collectively, our study demonstrates the utility of a fully digital, decentralized approach to conduct clinical trials of exercise therapy in a clinical population., (© 2024. The Author(s).)

In visual-based localization, prior research falls short in addressing challenges for the Internet of Things with limited computational resources. The dominant state-of-the-art models are based on separate feature extractors and descriptors without consideration of the constraints of small hardware, the issue of inconsistent image scale, or the presence of multi-objects. We introduce "OOPose", a real-time object-oriented pose estimation framework that leverages dense features from off-the-shelf object detection neural networks. It balances between pixel-matching accuracy and processing speed, enhancing overall performance. When input images share a comparable set of features, their matching accuracy is substantially heightened, while the reduction in image size facilitates faster processing but may compromise accuracy. OOPose resizes both the original library and cropped query object images to a width of 416 pixels. This adjustment results in a 2.4-fold improvement in pose accuracy and an 8.6-fold increase in processing speed. Moreover, OOPose eliminates the need for traditional sparse point extraction and description processes by capitalizing on dense network backbone features and selecting the detected query objects and sources of object library images, ensuring not only 1.3 times more accurate results but also three times greater stability compared to real-time sparse ORB matching algorithms. Beyond enhancements, we demonstrated the feasibility of OOPose in an autonomous mobile robot, enabling self-localization with a single camera at 10 FPS on a single CPU. It proves the cost-effectiveness and real-world applicability of OOPose for small embedded devices, setting the stage for potential markets and providing end-users with distinct advantages.

Mutated Ras and Raf kinases are well-known to promote cancer metastasis via flux through the Ras/Raf/MEK/ERK (mitogen-activated protein kinase [MAPK]) pathway. A role for non-mutated Raf in metastasis is also emerging, but the key mechanisms remain unclear. Elevated expression of any of the three wild-type Raf family members (C, A, or B) can drive metastasis. We utilized an in vivo model to show that wild-type C-Raf overexpression can promote metastasis of immortalized prostate cells in a gene dosage-dependent manner. Analysis of the transcriptomic and phosphoproteomic landscape indicated that C-Raf-driven metastasis is accompanied by upregulated MAPK signaling. Use of C-Raf mutants demonstrated that the dimerization domain, but not its kinase activity, is essential for metastasis. Endogenous Raf monomer knockouts revealed that C-Raf's ability to form dimers with endogenous Raf molecules is important for promoting metastasis. These data identify wild-type C-Raf heterodimer signaling as a potential target for treating metastatic disease., Competing Interests: O.N.W. currently has consulting, equity, and/or board relationships with Trethera Corporation, Kronos Biosciences, Sofie Biosciences, Breakthrough Properties, Vida Ventures, Nammi Therapeutics, Two River, Iconovir, Appia BioSciences, Neogene Therapeutics, 76Bio, and Allogene Therapeutics. None of these companies contributed to or directed any of the research reported in this article.

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection., (© 2023. The Author(s).)

The establishment of an "interferon (IFN) signature" to subset SLE patients on disease severity has led to therapeutics targeting IFNα. Here, we investigate IFN signaling in SLE using multiplexed protein arrays and single cell cytometry by time of flight (CyTOF). First, the IFN signature for SLE patients (n=81) from the Stanford Lupus Registry is determined using fluidigm qPCR measuring 44 previously determined IFN-inducible transcripts. IFN-high (IFN-H) patients have increased SLE criteria and renal/CNS/immunologic involvement, and increased autoantibody reactivity against spliceosome-associated antigens. CyTOF analysis is performed on non-stimulated and stimulated (IFNα, IFNγ, IL-21) PBMCs from SLE patients (n=25) and HCs (n=9) in a panel identifying changes in phosphorylation of intracellular signaling proteins (pTOF). Another panel is utilized to detect changes in intracellular cytokine (ICTOF) production in non-stimulated and stimulated (PMA/ionomycin) PBMCs from SLE patients (n=31) and HCs (n=17). Bioinformatic analysis by MetaCyto and OMIQ reveal phenotypic changes in immune cell subsets between IFN-H and IFN-low (IFN-L) patients. Most notably, IFN-H patients exhibit increased STAT1/3/5 phosphorylation downstream of cytokine stimulation and increased phosphorylation of non-canonical STAT proteins. These results suggest that IFN signaling in SLE modulates STAT phosphorylation, potentially uncovering possible targets for future therapeutic approaches., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yiu, Rasmussen, Tsai, Diep, Haddon, Tsoi, Miller, Comin-Anduix, Deleuran, Crooks and Utz.)

Cross-reactivity and direct killing of target cells remain underexplored for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-specific CD8 + T cells. Isolation of T cell receptors (TCRs) and overexpression in allogeneic cells allows for extensive T cell reactivity profiling. We identify SARS-CoV-2 RNA-dependent RNA polymerase (RdRp/NSP12) as highly conserved, likely due to its critical role in the virus life cycle. We perform single-cell TCRαβ sequencing in human leukocyte antigen (HLA)-A ∗ 02:01-restricted, RdRp-specific T cells from SARS-CoV-2-unexposed individuals. Human T cells expressing these TCRαβ constructs kill target cell lines engineered to express full-length RdRp. Three TCR constructs recognize homologous epitopes from common cold coronaviruses, indicating CD8 + T cells can recognize evolutionarily diverse coronaviruses. Analysis of individual TCR clones may help define vaccine epitopes that can induce long-term immunity against SARS-CoV-2 and other coronaviruses., Competing Interests: Declaration of interests O.N.W., J.M., and P.A.N. are inventors of a patent application in progress that will be filed prior to manuscript publication. J.R.H. is a board member of PACT Pharma and Isoplexis. O.N.W. currently has consulting, equity, and/or board relationships with Trethera Corporation, Kronos Biosciences, Sofie Biosciences, Breakthrough Properties, Vida Ventures, Nammi Therapeutics, Two River, Iconovir, Appia BioSciences, Neogene Therapeutics, and Allogene Therapeutics. None of these companies contributed to or directed any of the research reported in this article., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Undergraduate students participating in the UCLA Undergraduate Research Consortium for Functional Genomics (URCFG) have conducted a two-phased screen using RNA interference (RNAi) in combination with fluorescent reporter proteins to identify genes important for hematopoiesis in Drosophila. This screen disrupted the function of approximately 3500 genes and identified 137 candidate genes for which loss of function leads to observable changes in the hematopoietic development. Targeting RNAi to maturing, progenitor, and regulatory cell types identified key subsets that either limit or promote blood cell maturation. Bioinformatic analysis reveals gene enrichment in several previously uncharacterized areas, including RNA processing and export and vesicular trafficking. Lastly, the participation of students in this course-based undergraduate research experience (CURE) correlated with increased learning gains across several areas, as well as increased STEM retention, indicating that authentic, student-driven research in the form of a CURE represents an impactful and enriching pedagogical approach., (© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America.)

We sought to define the landscape of alternative pre-mRNA splicing in prostate cancers and the relationship of exon choice to known cancer driver alterations. To do so, we compiled a metadataset composed of 876 RNA-sequencing (RNA-Seq) samples from five publicly available sources representing a range of prostate phenotypes from normal tissue to drug-resistant metastases. We subjected these samples to exon-level analysis with rMATS-turbo, purpose-built software designed for large-scale analyses of splicing, and identified 13,149 high-confidence cassette exon events with variable incorporation across samples. We then developed a computational framework, pathway enrichment-guided activity study of alternative splicing (PEGASAS), to correlate transcriptional signatures of 50 different cancer driver pathways with these alternative splicing events. We discovered that Myc signaling was correlated with incorporation of a set of 1,039 cassette exons enriched in genes encoding RNA binding proteins. Using a human prostate epithelial transformation assay, we confirmed the Myc regulation of 147 of these exons, many of which introduced frameshifts or encoded premature stop codons. Our results connect changes in alternative pre-mRNA splicing to oncogenic alterations common in prostate and many other cancers. We also establish a role for Myc in regulating RNA splicing by controlling the incorporation of nonsense-mediated decay-determinant exons in genes encoding RNA binding proteins., Competing Interests: Competing interest statement: O.N.W. currently has consulting, equity, and/or board relationships with Trethera Corporation, Kronos Biosciences, Sofie Biosciences, and Allogene Therapeutics. D.L.B. and Y.X. are scientific cofounders of Panorama Medicine. None of these companies contributed to or directed any of the research reported in this article., (Copyright © 2020 the Author(s). Published by PNAS.)

Small cell carcinoma of the bladder (SCCB) is a rare and lethal phenotype of bladder cancer. The pathogenesis and molecular features are unknown. Here, we established a genetically engineered SCCB model and a cohort of patient SCCB and urothelial carcinoma samples to characterize molecular similarities and differences between bladder cancer phenotypes. We demonstrate that SCCB shares a urothelial origin with other bladder cancer phenotypes by showing that urothelial cells driven by a set of defined oncogenic factors give rise to a mixture of tumor phenotypes, including small cell carcinoma, urothelial carcinoma, and squamous cell carcinoma. Tumor-derived single-cell clones also give rise to both SCCB and urothelial carcinoma in xenografts. Despite this shared urothelial origin, clinical SCCB samples have a distinct transcriptional profile and a unique transcriptional regulatory network. Using the transcriptional profile from our cohort, we identified cell surface proteins (CSPs) associated with the SCCB phenotype. We found that the majority of SCCB samples have PD-L1 expression in both tumor cells and tumor-infiltrating lymphocytes, suggesting that immune checkpoint inhibitors could be a treatment option for SCCB. We further demonstrate that our genetically engineered tumor model is a representative tool for investigating CSPs in SCCB by showing that it shares a similar a CSP profile with clinical samples and expresses SCCB-up-regulated CSPs at both the mRNA and protein levels. Our findings reveal distinct molecular features of SCCB and provide a transcriptional dataset and a preclinical model for further investigating SCCB biology., Competing Interests: Competing interest statement: O.N.W. currently has consulting, equity, and/or board relationships with Trethera Corporation, Kronos Biosciences, Sofie Biosciences, and Allogene Therapeutics. T.G.G. currently has consulting and equity relationships with Trethera Corporation. The laboratory of T.G.G. has completed a research agreement with ImmunoActiva. None of these companies contributed to or directed any of the research reported in this article., (Copyright © 2020 the Author(s). Published by PNAS.)

The use of potent therapies inhibiting critical oncogenic pathways active in epithelial cancers has led to multiple resistance mechanisms, including the development of highly aggressive, small cell neuroendocrine carcinoma (SCNC). SCNC patients have a dismal prognosis due in part to a limited understanding of the molecular mechanisms driving this malignancy and the lack of effective treatments. Here, we demonstrate that a common set of defined oncogenic drivers reproducibly reprograms normal human prostate and lung epithelial cells to small cell prostate cancer (SCPC) and small cell lung cancer (SCLC), respectively. We identify shared active transcription factor binding regions in the reprogrammed prostate and lung SCNCs by integrative analyses of epigenetic and transcriptional landscapes. These results suggest that neuroendocrine cancers arising from distinct epithelial tissues may share common vulnerabilities that could be exploited for the development of drugs targeting SCNCs., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Cancer progression to an aggressive phenotype often co-opts aspects of stem cell biology. Here, we developed gene signatures for normal human stem cell populations to understand the relationship between epithelial cancers and stem cell transcriptional programs. Using a pan-cancer approach, we reveal that aggressive epithelial cancers are enriched for a transcriptional signature shared by epithelial adult stem cells. The adult stem cell signature selected for epithelial cancers with worse overall survival and alterations of oncogenic drivers. Lethal small cell neuroendocrine lung, prostate, and bladder cancers transcriptionally converged onto the adult stem cell signature and not other stem cell signatures tested. We found that DNA methyltransferase expression correlated with adult stem cell signature status and was enriched in small cell neuroendocrine cancers. DNA methylation analysis uncovered a shared epigenomic profile between small cell neuroendocrine cancers. These pan-cancer findings establish a molecular link between human adult stem cells and aggressive epithelial cancers., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)