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Precision medicine offers remarkable potential for the treatment of cancer, but is largely focused on tumors that harbor actionable mutations. Gene expression signatures can expand the scope of precision medicine by predicting response to traditional (cytotoxic) chemotherapy agents without relying on changes in mutational status. We present a new signature extraction method, inspired by the principle of convergent phenotypes, which states that tumors with disparate genetic backgrounds may evolve similar phenotypes independently. This evolutionary-informed method can be utilized to produce consensus signatures predictive of response to over 200 chemotherapeutic drugs found in the Genomics of Drug Sensitivity in Cancer (GDSC) Database. Here, we demonstrate its use by extracting the Cisplatin Response Signature (CisSig). We show that this signature can predict cisplatin response within carcinoma-based cell lines from the GDSC database, and expression of the signatures aligns with clinical trends seen in independent datasets of tumor samples from The Cancer Genome Atlas (TCGA) and Total Cancer Care (TCC) database. Finally, we demonstrate preliminary validation of CisSig for use in muscle-invasive bladder cancer, predicting overall survival in a small cohort of patients who undergo cisplatin-containing chemotherapy. This methodology can be used to produce robust signatures that, with further clinical validation, may be used for the prediction of traditional chemotherapeutic response, dramatically increasing the reach of personalized medicine in cancer., (© 2023. The Author(s).)

The ever-changing nature of cancer poses the most difficult challenge oncologists face today. Cancer's remarkable adaptability has inspired many to work toward understanding the evolutionary dynamics that underlie this disease in hopes of learning new ways to fight it. Eco-evolutionary dynamics of a tumor are not accounted for in most standard treatment regimens, but exploiting them would help us combat treatment-resistant effectively. Here, we outline several notable efforts to exploit these dynamics and circumvent drug resistance in cancer.

The reach of personalized medicine in radiation oncology has expanded greatly over the past few decades as technical precision has improved the delivery of radiation to each patient's unique anatomy. Yet, the consideration of biological heterogeneity between patients has largely not been translated to clinical care. There are innumerable promising advancements in the discovery and validation of biomarkers, which could be used to alter radiation therapy directly or indirectly. Directly, biomarker-informed care may alter treatment dose or identify patients who would benefit most from radiation therapy and who could safely avoid more aggressive care. Indirectly, a variety of biomarkers could assist with choosing the best radiosensitizing chemotherapies. The translation of these advancements into clinical practice will bring radiation oncology even further into the era of precision medicine, treating patients according to their unique anatomical and biological differences., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Despite advances in cancer genomics, radiotherapy is still prescribed on the basis of an empirical one-size-fits-all paradigm. Previously, we proposed a novel algorithm using the genomic-adjusted radiation dose (GARD) model to personalise prescription of radiation dose on the basis of the biological effect of a given physical dose of radiation, calculated using individual tumour genomics. We hypothesise that GARD will reveal interpatient heterogeneity associated with opportunities to improve outcomes compared with physical dose of radiotherapy alone. We aimed to test this hypothesis and investigate the GARD-based radiotherapy dosing paradigm., Methods: We did a pooled, pan-cancer analysis of 11 previously published clinical cohorts of unique patients with seven different types of cancer, which are all available cohorts with the data required to calculate GARD, together with clinical outcome. The included cancers were breast cancer, head and neck cancer, non-small-cell lung cancer, pancreatic cancer, endometrial cancer, melanoma, and glioma. Our dataset comprised 1615 unique patients, of whom 1298 (982 with radiotherapy, 316 without radiotherapy) were assessed for time to first recurrence and 677 patients (424 with radiotherapy and 253 without radiotherapy) were assessed for overall survival. We analysed two clinical outcomes of interest: time to first recurrence and overall survival. We used Cox regression, stratified by cohort, to test the association between GARD and outcome with separate models using dose of radiation and sham-GARD (ie, patients treated without radiotherapy, but modelled as having a standard-of-care dose of radiotherapy) for comparison. We did interaction tests between GARD and treatment (with or without radiotherapy) using the Wald statistic., Findings: Pooled analysis of all available data showed that GARD as a continuous variable is associated with time to first recurrence (hazard ratio [HR] 0·98 [95% CI 0·97-0·99]; p=0·0017) and overall survival (0·97 [0·95-0·99]; p=0·0007). The interaction test showed the effect of GARD on overall survival depends on whether or not that patient received radiotherapy (Wald statistic p=0·011). The interaction test for GARD and radiotherapy was not significant for time to first recurrence (Wald statistic p=0·22). The HR for physical dose of radiation was 0·99 (95% CI 0·97-1·01; p=0·53) for time to first recurrence and 1·00 (0·96-1·04; p=0·95) for overall survival. The HR for sham-GARD was 1·00 (0·97-1·03; p=1·00) for time to first recurrence and 1·00 (0·98-1·02; p=0·87) for overall survival., Interpretation: The biological effect of radiotherapy, as quantified by GARD, is significantly associated with time to first recurrence and overall survival for patients with cancer treated with radiation. It is predictive of radiotherapy benefit, and physical dose of radiation is not. We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalising radiotherapy prescription dose., Funding: None. VIDEO ABSTRACT., Competing Interests: Declaration of interests JGS, SAE, and JFT-R hold intellectual property on RSI, GARD, and prescription dose base on RSI (known as RxRSI), in addition to equity in Cvergenx, a company that seeks to commercialise these methods. Patents held by Moffitt Cancer Center are as follows: RSI (awarded) patent number 7 879 545; 8 655 598; 8 660 801, and 9 846 762; GARD (awarded) patent number 10 697 023; and Cvergenx (RxRSI [pending] application number 16/658 961). SAE and JFT-R are cofounders and board members of Cvergenx. All other authors declare no competing interests., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Personal protective equipment (PPE) is crucially important to the safety of both patients and medical personnel, particularly in the event of an infectious pandemic. As the incidence of Coronavirus Disease 2019 (COVID-19) increases exponentially in the United States and many parts of the world, healthcare provider demand for these necessities is currently outpacing supply. In the midst of the current pandemic, there has been a concerted effort to identify viable ways to conserve PPE, including decontamination after use. In this study, we outline a procedure by which PPE may be decontaminated using ultraviolet (UV) radiation in biosafety cabinets (BSCs), a common element of many academic, public health, and hospital laboratories. According to the literature, effective decontamination of N95 respirator masks or surgical masks requires UV-C doses of greater than 1 Jcm-2, which was achieved after 4.3 hours per side when placing the N95 at the bottom of the BSCs tested in this study. We then demonstrated complete inactivation of the human coronavirus NL63 on N95 mask material after 15 minutes of UV-C exposure at 61 cm (232 μWcm-2). Our results provide support to healthcare organizations looking for methods to extend their reserves of PPE., Competing Interests: JGS, the senior author, has, subsequent to this research, led a related patent for a UV decontamination device (PCT/US2021/022771, led march 17, 2021: \Decontam-ination System"). This does not alter our adherence to all PLOS ONE policies on sharing data and materials, and in fact, the patent was a reaction to this work, and so therefore was entirely performed subsequently to this research. Further, beyond the fact that the patent is for a UV-C decontamination chamber, it has little to do with this research.

The maintenance of telomere length supports repetitive cell division and therefore plays a central role in cancer development and progression. Telomeres are extended by either the enzyme telomerase or the alternative lengthening of telomeres (ALT) pathway. Here, we found that the telomere-associated protein SLX4IP dictates telomere proteome composition by recruiting and activating the E3 SUMO ligase PIAS1 to the SLX4 complex. PIAS1 SUMOylated the telomere-binding protein RAP1, which disrupted its interaction with the telomere-binding protein TRF2 and facilitated its nucleocytoplasmic shuttling. In the cytosol, RAP1 bound to IκB kinase (IKK), resulting in activation of the transcription factor NF-κB and its induction of Jagged-1 expression, which promoted Notch signaling and the institution of ALT. This axis could be targeted therapeutically in ALT-driven cancers and in tumor cells that develop resistance to antitelomerase therapies. Our results illuminate the mechanisms underlying SLX4IP-dependent telomere plasticity and demonstrate the role of telomere proteins in directly coordinating intracellular signaling and telomere maintenance dynamics., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Purpose: In the treatment of patients with metastatic cancer, the current paradigm states that metastasis-directed therapy does not prolong life. This paradigm forms the basis of clinical trial null hypotheses, where trials are built to test the null hypothesis that patients garner no overall survival benefit from targeting metastatic lesions. However, with advancing imaging technology and increasingly precise techniques for targeting lesions, a much larger proportion of metastatic disease can be treated. As a result, the life-extending benefit of targeting metastatic disease is becoming increasingly clear., Methods and Materials: In this work, we suggest shifting this qualitative null hypothesis and describe a mathematical model that can be used to frame a new, quantitative null. We begin with a very simple formulation of tumor growth, an exponential function, and illustrate how the same intervention (removing a given number of cells from the tumor) at different times affects survival. Additionally, we postulate where recent clinical trials fit into this parameter space and discuss the implications of clinical trial design in changing these quantitative parameters., Results: Our model shows that although any amount of cell kill will extend survival, in many cases the extent is so small as to be unnoticeable in a clinical context or is outweighed by factors related to toxicity and treatment time., Conclusions: Recasting the null in these quantitative terms will allow trialists to design trials specifically to increase understanding of the circumstances (patient selection, disease burden, tumor growth kinetics) that can lead to improved overall survival when targeting metastatic lesions, rather than whether targeting metastases extends survival for patients with (oligo-) metastatic disease., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Introduction: Cancer sequencing efforts have revealed that cancer is the most complex and heterogeneous disease that affects humans. However, radiation therapy (RT), one of the most common cancer treatments, is prescribed on the basis of an empirical one-size-fits-all approach. We propose that the field of radiation oncology is operating under an outdated null hypothesis: that all patients are biologically similar and should uniformly respond to the same dose of radiation., Methods: We have previously developed the genomic-adjusted radiation dose, a method that accounts for biological heterogeneity and can be used to predict optimal RT dose for an individual patient. In this article, we use genomic-adjusted radiation dose to characterize the biological imprecision of one-size-fits-all RT dosing schemes that result in both over- and under-dosing for most patients treated with RT. To elucidate this inefficiency, and therefore the opportunity for improvement using a personalized dosing scheme, we develop a patient-specific competing hazards style mathematical model combining the canonical equations for tumor control probability and normal tissue complication probability. This model simultaneously optimizes tumor control and toxicity by personalizing RT dose using patient-specific genomics., Results: Using data from two prospectively collected cohorts of patients with NSCLC, we validate the competing hazards model by revealing that it predicts the results of RTOG 0617. We report how the failure of RTOG 0617 can be explained by the biological imprecision of empirical uniform dose escalation which results in 80% of patients being overexposed to normal tissue toxicity without potential tumor control benefit., Conclusions: Our data reveal a tapestry of radiosensitivity heterogeneity, provide a biological framework that explains the failure of empirical RT dose escalation, and quantify the opportunity to improve clinical outcomes in lung cancer by incorporating genomics into RT., (Copyright © 2020 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Advances in the treatment of Ewing's sarcoma (EWS) are desperately needed, particularly in the case of metastatic disease. A deeper understanding of collateral sensitivity, where the evolution of therapeutic resistance to one drug aligns with sensitivity to another drug, may improve our ability to effectively target this disease. For the first time in a solid tumor, we produced a temporal collateral sensitivity map that demonstrates the evolution of collateral sensitivity and resistance in EWS. We found that the evolution of collateral resistance was predictable with some drugs but had significant variation in response to other drugs. Using this map of temporal collateral sensitivity in EWS, we can see that the path toward collateral sensitivity is not always repeatable, nor is there always a clear trajectory toward resistance or sensitivity. Identifying transcriptomic changes that accompany these states of transient collateral sensitivity could improve treatment planning for patients with EWS., Competing Interests: Declaration of Interests Stephen Lessnick serves as a Scientific Advisor for Salarius Pharmaceuticals., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Human cytomegalovirus (HCMV) is a widespread pathogen that is particularly skillful at evading immune detection and defense mechanisms, largely due to extensive co-evolution with its host. One aspect of this co-evolution involves the acquisition of virally encoded G protein-coupled receptors (GPCRs) with homology to the chemokine receptor family. GPCRs are the largest family of cell surface proteins, found in organisms from yeast to humans, and they regulate a variety of cellular processes including development, sensory perception, and immune cell trafficking. The US27 and US28 genes are encoded by human and primate CMVs, but homologs are not found in the genomes of viruses infecting rodents or other species. Phylogenetic analysis was used to investigate the US27 and US28 genes, which are adjacent in the unique short (US) region of the HCMV genome, and their relationship to one another and to human chemokine receptor genes. The results indicate that both US27 and US28 share the same common ancestor with human chemokine receptor CX3CR1, suggesting that a single host gene was captured and a subsequent viral gene duplication event occurred. The US28 gene product (pUS28) has maintained the function of the ancestral gene and has the ability to bind and signal in response to CX3CL1/fractalkine, the natural ligand for CX3CR1. In contrast, pUS27 does not bind to any known chemokine ligand, and the sequence has diverged significantly, highlighted by the fact that pUS27 currently exhibits greater sequence similarity to human CCR1. While the evolutionary advantage of the gene duplication and neofunctionalization event remains unclear, the US27 and US28 genes are highly conserved among different HCMV strains and retained even in laboratory strains that have lost many virulence genes, suggesting that US27 and US28 have each evolved distinct, important functions during virus infection., (Copyright © 2017 Elsevier B.V. All rights reserved.)

In this paper we describe a new type of non-centrosomal microtubule-organising centre (MTOC), which is induced by cold treatment of certain cultured Drosophila cells and allows rapid reassembly of microtubule (MT) arrays. Prolonged cooling of two types of cultured Drosophila cells, muscle cells in primary culture and a wing imaginal disc cell line Cl.8+ results in disassembly of MT arrays and induces the formation of clusters of short MTs that have not been described before. Upon rewarming, the clusters are lost and the MT array is re-established within 1 h. In Cl.8+ cells, gamma-tubulin-containing centrosomes are detected, both in cell extensions and in the expected juxtanuclear position, and gamma-tubulin co-localises with the cold-induced MT clusters. The MT plus-end-binding protein, Drosophila EB1, decorates growing tips of MTs extending from clusters. We conclude that the cold-induced MT clusters represent acentrosomal MTOCs, allowing rapid reassembly of MT arrays following exposure to cold., (Copyright (c) 2005 Wiley-Liss, Inc.)

Using primary embryonic Drosophila cell cultures, we have investigated the assembly of transcellular microtubule bundles in epidermal tendon cells. Muscles attach to the tendon cells of previously undescribed epidermal balls that form shortly after culture initiation. Basal capture of microtubule ends in cultured tendon cells is confined to discrete sites that occupy a relatively small proportion of the basal cell surface. These capturing sites are associated with hemiadherens junctions that link the ends of muscle cells to tendon cell bases. In vivo, muscle attachment and microtubule capture occur across the entire cell base. The cultured tendon cells reveal that the basal ends of their microtubules can be precisely targeted to small, pre-existing, structurally well-defined cortical capturing sites. However, a search and capture targeting procedure, such as that undertaken by kinetochore microtubules, cannot fully account for the precision of microtubule capture and positioning in tendon cells. We propose that cross-linkage of microtubules is also required to zip them into apicobasally oriented alignment, progressing from captured basal plus ends to apical minus ends. This involves repositioning of apical minus ends before they become anchored to an apical set of hemiadherens junctions. The proposal is consistent with our finding that hemiadherens junctions assemble at tendon cell bases before they do so at cell apices in both cultures and embryos. It is argued that control of microtubule positioning in the challenging spatial situations found in vitro involves the same procedures as those that operate in vivo., (Copyright 2004 Wiley-Liss, Inc.)