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      FLASH Proton Radiotherapy Spares Normal Epithelial and Mesenchymal Tissues While Preserving Sarcoma Response

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          Abstract

          These findings will spur investigation of FLASH radiotherapy in sarcoma and additional cancers where mesenchymal tissues are at risk, including head and neck cancer, breast cancer, and pelvic malignancies.

          Abstract

          In studies of electron and proton radiotherapy, ultrahigh dose rates of FLASH radiotherapy appear to produce fewer toxicities than standard dose rates while maintaining local tumor control. FLASH-proton radiotherapy (F-PRT) brings the spatial advantages of PRT to FLASH dose rates (>40 Gy/second), making it important to understand if and how F-PRT spares normal tissues while providing antitumor efficacy that is equivalent to standard-proton radiotherapy (S-PRT). Here we studied PRT damage to skin and mesenchymal tissues of muscle and bone and found that F-PRT of the C57BL/6 murine hind leg produced fewer severe toxicities leading to death or requiring euthanasia than S-PRT of the same dose. RNA-seq analyses of murine skin and bone revealed pathways upregulated by S-PRT yet unaltered by F-PRT, such as apoptosis signaling and keratinocyte differentiation in skin, as well as osteoclast differentiation and chondrocyte development in bone. Corroborating these findings, F-PRT reduced skin injury, stem cell depletion, and inflammation, mitigated late effects including lymphedema, and decreased histopathologically detected myofiber atrophy, bone resorption, hair follicle atrophy, and epidermal hyperplasia. F-PRT was equipotent to S-PRT in control of two murine sarcoma models, including at an orthotopic intramuscular site, thereby establishing its relevance to mesenchymal cancers. Finally, S-PRT produced greater increases in TGFβ1 in murine skin and the skin of canines enrolled in a phase I study of F-PRT versus S-PRT. Collectively, these data provide novel insights into F-PRT-mediated tissue sparing and support its ongoing investigation in applications that would benefit from this sparing of skin and mesenchymal tissues.

          Significance:

          These findings will spur investigation of FLASH radiotherapy in sarcoma and additional cancers where mesenchymal tissues are at risk, including head and neck cancer, breast cancer, and pelvic malignancies.

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          Most cited references50

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          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

            Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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              Ultrahigh dose-rate FLASH irradiation increases the differential response between normal and tumor tissue in mice.

              In vitro studies suggested that sub-millisecond pulses of radiation elicit less genomic instability than continuous, protracted irradiation at the same total dose. To determine the potential of ultrahigh dose-rate irradiation in radiotherapy, we investigated lung fibrogenesis in C57BL/6J mice exposed either to short pulses (≤ 500 ms) of radiation delivered at ultrahigh dose rate (≥ 40 Gy/s, FLASH) or to conventional dose-rate irradiation (≤ 0.03 Gy/s, CONV) in single doses. The growth of human HBCx-12A and HEp-2 tumor xenografts in nude mice and syngeneic TC-1 Luc(+) orthotopic lung tumors in C57BL/6J mice was monitored under similar radiation conditions. CONV (15 Gy) triggered lung fibrosis associated with activation of the TGF-β (transforming growth factor-β) cascade, whereas no complications developed after doses of FLASH below 20 Gy for more than 36 weeks after irradiation. FLASH irradiation also spared normal smooth muscle and epithelial cells from acute radiation-induced apoptosis, which could be reinduced by administration of systemic TNF-α (tumor necrosis factor-α) before irradiation. In contrast, FLASH was as efficient as CONV in the repression of tumor growth. Together, these results suggest that FLASH radiotherapy might allow complete eradication of lung tumors and reduce the occurrence and severity of early and late complications affecting normal tissue.
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                Author and article information

                Journal
                Cancer Res
                Cancer Res
                Cancer Research
                American Association for Cancer Research
                0008-5472
                1538-7445
                15 September 2021
                28 July 2021
                : 81
                : 18
                : 4808-4821
                Affiliations
                [1 ]Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
                [2 ]Department of Electrical & Computer Engineering, University of Thessaly, Greece.
                [3 ]Hellenic Pasteur Institute, Athens, Greece.
                [4 ]Department of Clinical Studies and Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
                [5 ]Department of Orthopedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
                [6 ]DIANA-Lab, Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece.
                [7 ]Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
                [8 ]Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
                Author notes
                [#]

                K.A. Cengel, A. Maity, and T.M. Busch contributed equally as a co-senior authors of this article.

                [* ] Corresponding Author: Theresa M. Busch, Department of Radiation Oncology, University of Pennsylvania Smilow Center for Translational Research, Room 8-126, 3400 Civic Center Blvd, Bldg 421, Philadelphia, PA 19104-5156. E-mail: theresa.busch@ 123456pennmedicine.upenn.edu
                Author information
                https://orcid.org/0000-0003-1642-1996
                https://orcid.org/0000-0003-1100-1298
                https://orcid.org/0000-0001-9022-6334
                https://orcid.org/0000-0002-0755-4511
                https://orcid.org/0000-0002-0652-2075
                https://orcid.org/0000-0003-0073-2730
                https://orcid.org/0000-0002-2885-0221
                https://orcid.org/0000-0002-4869-6575
                https://orcid.org/0000-0003-2623-3198
                https://orcid.org/0000-0001-5945-4726
                Article
                CAN-21-1500
                10.1158/0008-5472.CAN-21-1500
                8715480
                34321243
                a120bd06-a15b-4de1-85bd-621d4717bcf8
                ©2021 The Authors; Published by the American Association for Cancer Research

                This open access article is distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.

                History
                : 13 May 2021
                : 29 June 2021
                : 27 July 2021
                Page count
                Pages: 14
                Funding
                Funded by: IKY, DOI http://dx.doi.org/10.13039/501100003447;
                Award ID: MIS-5000432
                Categories
                Translational Science

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