Protocol for inferring epithelial-to-mesenchymal transition trajectories from single-cell RNA sequencing data using R.

The epithelial-to-mesenchymal transition (EMT) provides crucial insights into the metastatic process and possesses prognostic value within the cancer context. Here, we present COMET, an R package for inferring EMT trajectories and inter-state transition rates from single-cell RNA sequencing data. We describe steps for finding the optimal number of EMT genes for a specific context, estimating EMT-related trajectories, optimal fitting of continuous-time Markov chain to inferred trajectories, and estimating inter-state transition rates.

Optimal phenotypic adaptation in fluctuating environments.

Phenotypic adaptation is a universal feature of biological systems navigating highly variable environments. Recent empirical data support the role of memory-driven decision making in cellular systems navigating uncertain future nutrient landscapes, wherein a distinct growth phenotype emerges in fluctuating conditions. We develop a simple stochastic mathematical model to describe memory-driven cellular adaptation required for systems to optimally navigate such uncertainty. In this framework, adaptive populations traverse dynamic environments by inferring future variation from a memory of prior states, and memory capacity imposes a fundamental trade-off between the speed and accuracy of adaptation to new fluctuating environments. Our results suggest that the observed growth reductions that occur in fluctuating environments are a direct consequence of optimal decision making and result from bet hedging and occasional phenotypic-environmental mismatch. We anticipate that this modeling framework will be useful for studying the role of memory in phenotypic adaptation, including in the design of temporally varying therapies against adaptive systems.

Quantitative approaches for decoding the specificity of the human T cell repertoire.

T cell receptor (TCR)-peptide-major histocompatibility complex (pMHC) interactions play a vital role in initiating immune responses against pathogens, and the specificity of TCRpMHC interactions is crucial for developing optimized therapeutic strategies. The advent of high-throughput immunological and structural evaluation of TCR and pMHC has provided an abundance of data for computational approaches that aim to predict favorable TCR-pMHC interactions. Current models are constructed using information on protein sequence, structures, or a combination of both, and utilize a variety of statistical learning-based approaches for identifying the rules governing specificity. This review examines the current theoretical, computational, and deep learning approaches for identifying TCR-pMHC recognition pairs, placing emphasis on each method's mathematical approach, predictive performance, and limitations.

Systematic review of preoperative n-3 fatty acids in major gastrointestinal surgery.

Objectives: Perioperative nutrition aims to replenish nutritional stores before surgery and reduce postoperative complications. 'Immunonutrition' (including omega-3 fatty acids) may modulate the immune system and attenuate the postoperative inflammatory response. Hitherto, immunonutrition has overwhelmingly been administered in the postoperative period-however, this may be too late to provide benefit. Design: A systematic literature search using MEDLINE and EMBASE for randomized controlled trials (RCTs). Setting: Perioperative major gastrointestinal surgery. Participants: Patients undergoing major gastrointestinal surgery. Interventions: Omega-3 fatty acid supplementation commenced in the preoperative period, with or without continuation into postoperative period. Main outcome measures: The effect of preoperative omega-3 fatty acids on inflammatory response and clinical outcomes. Results: 833 studies were identified. After applying inclusion and exclusion criteria, 12 RCTs, involving 1456 randomized patients, were included. Ten articles exclusively enrolled patients with cancer. Seven studies used a combination of EPA (eicosapentaenoic acid) and DHA (docosahexaenoic acid) as the intervention and five studies used EPA alone. Eight out of 12 studies continued preoperative nutritional support into the postoperative period.Of the nine studies reporting mortality, no difference was seen. Duration of hospitalisation ranged from 4.5 to 18 days with intervention and 3.5 to 23.5 days with control. Omega-3 fatty acids had no effect on postoperative C-reactive protein and the effect on cytokines (including tumor necrosis factor-α, interleukin (IL)-6 and IL-10) was inconsistent. Ten of the 12 studies had low risk of bias, with one study having moderate bias from allocation and blinding. Conclusions: There is insufficient evidence to support routine preoperative omega-3 fatty acid supplementation for major gastrointestinal surgery, even when this is continued after surgery. PROSPERO registration number: CRD42018108333.

Population dynamics of EMT elucidates the timing and distribution of phenotypic intra-tumoral heterogeneity.

The Epithelial-to-Mesenchymal Transition (EMT) is a hallmark of cancer metastasis and morbidity. EMT is a non-binary process, and cells can be stably arrested en route to EMT in an intermediate hybrid state associated with enhanced tumor aggressiveness and worse patient outcomes. Understanding EMT progression in detail will provide fundamental insights into the mechanisms underlying metastasis. Despite increasingly available single-cell RNA sequencing (scRNA-seq) data that enable in-depth analyses of EMT at the single-cell resolution, current inferential approaches are limited to bulk microarray data. There is thus a great need for computational frameworks to systematically infer and predict the timing and distribution of EMT-related states at single-cell resolution. Here, we develop a computational framework for reliable inference and prediction of EMT-related trajectories from scRNA-seq data. Our model can be utilized across a variety of applications to predict the timing and distribution of EMT from single-cell sequencing data.

The New Zealand drug harms ranking study: A multi-criteria decision analysis.

AIMS: The harms arising from psychoactive drug use are complex, and harm reduction strategies should be informed by a detailed understanding of the extent and nature of that harm. Drug harm is also context specific, and so any comprehensive assessment of drug harm should be relevant to the characteristics of the population in question. This study aimed to evaluate and rank drug harms within Aotearoa New Zealand using a multi-criteria decision analysis (MCDA) framework, and to separately consider harm within the total population, and among youth. METHODS: Two facilitated workshops involved the separate ranking of harm for the total population, and then for youth aged 12-17, by two expert panels. In the total population workshop, 23 drugs were scored against 17 harm criteria, and those criteria were then evaluated using a swing weighting process. Scoring and weighting were subsequently updated during the youth-specific workshop. All results were recorded and analysed using specialised MCDA software. RESULTS: When considering overall harm, the MCDA modelling results indicated that alcohol, methamphetamine and synthetic cannabinoids were the most harmful to both the overall population and the youth, followed by tobacco in the total population. Alcohol remained the most harmful drug for the total population when separately considering harm to those who use it, and harm to others. CONCLUSIONS: The results provide detailed and context-specific insight into the harm associated with psychoactive drugs use within Aotearoa New Zealand. The findings also demonstrate the value of separately considering harm for different countries, and for different population subgroups.

Non-Traditional Physical Education Classes Improve High School Students' Movement Competency and Fitness: A Mixed-Methods Program Evaluation Study.

Non-traditional physical education (PE) programs may facilitate functional movement patterns and develop fitness and work capacity to facilitate long-term physical activity. This program evaluation study compared changes in body composition, movement competency, work capacity, and fitness for high school students in CrossFit or weight training PE; both classes were hypothesized to improve each area, with greater improvements in the CrossFit class. Students participated in 57 min classes 4 days per week for 9 months. Measures including body composition, movement competencies (squat, lunge, push-up, pull-up, hinge, and brace), work capacity (two CrossFit workouts), and fitness (air squats, push-ups, inverted row, plank hold, horizontal and vertical jumps, 5 rep max back squat and press, 500 m bike, and 12 min run) were taken at baseline, midpoint, and post-test. Focus groups to assess students' experiences and outcomes were conducted at post-test. Students significantly improved in movement competencies (ps = 0.034 to <0.001), work capacity (ps < 0.001), and all fitness tests (ps = 0.036 to <0.001). The CrossFit class was only superior on the 500 m bike. Four themes were identified from the focus groups: (1) increased self-confidence, (2) health improvements, (3) newfound community, and (4) translational sports improvements. Future research should examine changes using an experimental design.

Optimal cancer evasion in a dynamic immune microenvironment generates diverse post-escape tumor antigenicity profiles.

The failure of cancer treatments, including immunotherapy, continues to be a major obstacle in preventing durable remission. This failure often results from tumor evolution, both genotypic and phenotypic, away from sensitive cell states. Here, we propose a mathematical framework for studying the dynamics of adaptive immune evasion that tracks the number of tumor-associated antigens available for immune targeting. We solve for the unique optimal cancer evasion strategy using stochastic dynamic programming and demonstrate that this policy results in increased cancer evasion rates compared to a passive, fixed strategy. Our foundational model relates the likelihood and temporal dynamics of cancer evasion to features of the immune microenvironment, where tumor immunogenicity reflects a balance between cancer adaptation and host recognition. In contrast with a passive strategy, optimally adaptive evaders navigating varying selective environments result in substantially heterogeneous post-escape tumor antigenicity, giving rise to immunogenically hot and cold tumors.

Epigenetic memory acquired during long-term EMT induction governs the recovery to the epithelial state.

Epithelial-mesenchymal transition (EMT) and its reverse mesenchymal-epithelial transition (MET) are critical during embryonic development, wound healing and cancer metastasis. While phenotypic changes during short-term EMT induction are reversible, long-term EMT induction has been often associated with irreversibility. Here, we show that phenotypic changes seen in MCF10A cells upon long-term EMT induction by TGFß need not be irreversible, but have relatively longer time scales of reversibility than those seen in short-term induction. Next, using a phenomenological mathematical model to account for the chromatin-mediated epigenetic silencing of the miR-200 family by ZEB family, we highlight how the epigenetic memory gained during long-term EMT induction can slow the recovery to the epithelial state post-TGFß withdrawal. Our results suggest that epigenetic modifiers can govern the extent and time scale of EMT reversibility and advise caution against labelling phenotypic changes seen in long-term EMT induction as 'irreversible'.

Contact map dependence of a T-cell receptor binding repertoire.

The T-cell arm of the adaptive immune system provides the host protection against unknown pathogens by discriminating between host and foreign material. This discriminatory capability is achieved by the creation of a repertoire of cells each carrying a T-cell receptor (TCR) specific to non-self-antigens displayed as peptides bound to the major histocompatibility complex (pMHC). The understanding of the dynamics of the adaptive immune system at a repertoire level is complex, due to both the nuanced interaction of a TCR-pMHC pair and to the number of different possible TCR-pMHC pairings, making computationally exact solutions currently unfeasible. To gain some insight into this problem, we study an affinity-based model for TCR-pMHC binding in which a crystal structure is used to generate a distance-based contact map that weights the pairwise amino acid interactions. We find that the TCR-pMHC binding energy distribution strongly depends both on the number of contacts and the repeat structure allowed by the topology of the contact map of choice; this in turn influences T-cell recognition probability during negative selection, with higher variances leading to higher survival probabilities. In addition, we quantify the degree to which neoantigens with mutations in sites with higher contacts are recognized at a higher rate.

Effect of annealing on properties and performance of HfO2/SiO2 optical coatings for UV-applications.

The field of ultraviolet (UV)-laser applications is currently experiencing rapid growth in the semiconductor processing, laser micromachining and biomedical markets. Key enablers for these technologies are optical coatings used to manipulate and guide laser beams in a targeted manner. As laser power, laser fluence and pulse frequencies increase, the demands on the physical properties of the coating materials become more stringent. Ion beam sputtering is a technique that allows producing optical coatings with the low losses required in these applications. In this study, we investigate the influence of ion beam sputtering (IBS) parameters on the optical properties of HfO2 and SiO2 single layers as well as the impact of annealing duration at 475 °C for anti-reflective (AR) and highly reflective (HR) optical coatings at 355 nm. For HfO2 sputtered from a metal target the O2 flow during the coating process is a key parameter to reduce absorption. SiO2 single layers exhibit improved transmission in the UV-range as the ion beam energy for the sputtering process is reduced. Furthermore, a complex behavior for film stress, absorption, surface roughness and coating structure was unraveled as a function of annealing duration for AR- and HR-coatings at 355 nm. The reflectance of the HR-mirror after optimized annealing exceeded 99.94% at 355 nm and a high laser induced damage threshold (LIDT) of 6.9 J/cm2 was measured after 2 hours of annealing. For the AR-coating a LIDT-value of 15.7 J/cm2 was observed after 12 hours of annealing.

Changes in Triple-Negative Breast Cancer Molecular Subtypes in Patients Without Pathologic Complete Response After Neoadjuvant Systemic Chemotherapy.

PURPOSE: Lehmann et al have identified four molecular subtypes of triple-negative breast cancer (TNBC)-basal-like (BL) 1, BL2, mesenchymal (M), and luminal androgen receptor-and an immunomodulatory (IM) gene expression signature modifier. Our group previously showed that the response of TNBC to neoadjuvant systemic chemotherapy (NST) differs by molecular subtype, but whether NST affects the subtype was unknown. Here, we tested the hypothesis that in patients without pathologic complete response, TNBC subtypes can change after NST. Moreover, in cases with the changed subtype, we determined whether epithelial-to-mesenchymal transition (EMT) had occurred. MATERIALS AND METHODS: From the Pan-Pacific TNBC Consortium data set containing TNBC patient samples from four countries, we examined 64 formalin-fixed, paraffin-embedded pairs of matched pre- and post-NST tumor samples. The TNBC subtype was determined using the TNBCtype-IM assay. We analyzed a partial EMT gene expression scoring metric using mRNA data. RESULTS: Of the 64 matched pairs, 36 (56%) showed a change in the TNBC subtype after NST. The most frequent change was from BL1 to M subtypes (38%). No tumors changed from M to BL1. The IM signature was positive in 14 (22%) patients before NST and eight (12.5%) patients after NST. The EMT score increased after NST in 28 (78%) of the 36 patients with the changed subtype (v 39% of the 28 patients without change; P = .002254). CONCLUSION: We report, to our knowledge, for the first time that the TNBC molecular subtype and IM signature frequently change after NST. Our results also suggest that EMT is promoted by NST. Our findings may lead to innovative adjuvant therapy strategies in TNBC cases with residual tumor after NST.

Obstructive jaundice, a rare presentation of lung cancer: A case report.

Lung cancer metastases to the pancreas are rare but potentially life-threatening. Oftentimes, the presence of symptoms is indicative of extensive disease burden. This report describes a case of primary lung adenocarcinoma metastasizing to the head of the pancreas presenting as obstructive jaundice. The patient was a 61-year-old female veteran who presented with a chronic dyspnea, weight loss, and 3-weeks of nausea and vomiting found to have jaundice, elevated alkaline phosphatase levels, hyperbilirubinemia, and transaminitis. Imaging of her chest revealed large pulmonary parenchymal nodules throughout both lungs with a large left lower lobe mass and consolidation. Abdominal imaging showed a large heterogeneous mass in the pancreatic head, a grossly dilated common bile duct, and enlarged retroperitoneal lymph nodes contiguous with the mass. Pancreatic head biopsies revealed metastatic cancer cells from her lung adenocarcinoma which was confirmed via cytology and the presence of thyroid transcription factor - 1 and cytokeritin-7 expression and the absence of tumor protein 63 staining. Lung adenocarcinomas commonly metastasize to the bones, liver, and central nervous system but very rarely to the pancreas. There have been only a few reported cases of pancreatic tumors that manifested clinically as a result of primary lung cancer metastases however, even though uncommon, hematogenous spread of cancerous tissue should be considered on the differential as a cause for obstructive jaundice in the setting of lung adenocarcinoma.

Pulmonary Large Cell Neuroendocrine Carcinoma: A Rare Type of Non-Small Cell Lung Cancer.

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is an uncommon type of non-small cell lung cancer (NSCLC) with an incidence of approximately 3% of all lung cancer diagnoses. The patient was a 60-year-old male with a 90-pack year smoking history who presented with dyspnea on exertion and productive cough for five weeks. Decreased breath sounds without respiratory distress and generalized cachexia were noted on the initial physical exam. Laboratory results were unremarkable except for chronic microcytic anemia. Computed tomography revealed extensive lymphadenopathy of the paratracheal, paraaortic, hilar, and nodes surrounding the left pulmonary arteries. Additionally, there were areas of necrosis in the left upper lobe, lingula, and left lower lobe with extensive pleural thickening extending to the abdomen and subcutaneous tissue of the anterior chest wall. Biopsy and staining showed disorganized tight cell clusters with irregular and prominent nuclei and numerous lymphocytes consistent with LCNEC. Immunohistochemistry was positive for neural cell adhesion molecule CD56 and synaptophysin, which was indicative of neuroendocrine origin. It was also positive for pan-cytokeratin antibody AE1 and AE3 and cytokeratin (CAM) 5.2, which arise from epithelial origin consistent with NSCLCs. Lastly, the patient's tissue was positive for thyroid transcription factor-1, which confirmed the tumor's primary lung origin. This combination of neuroendocrine and primary lung tumor markers, in conjunction with the histology, confirmed the patient's diagnosis of LCNEC.

Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum.

Inflammatory breast cancer (IBC) is a highly aggressive breast cancer that metastasizes largely via tumor emboli, and has a 5-year survival rate of less than 30%. No unique genomic signature has yet been identified for IBC nor has any specific molecular therapeutic been developed to manage the disease. Thus, identifying gene expression signatures specific to IBC remains crucial. Here, we compare various gene lists that have been proposed as molecular footprints of IBC using different clinical samples as training and validation sets and using independent training algorithms, and determine their accuracy in identifying IBC samples in three independent datasets. We show that these gene lists have little to no mutual overlap, and have limited predictive accuracy in identifying IBC samples. Despite this inconsistency, single-sample gene set enrichment analysis (ssGSEA) of IBC samples correlate with their position on the epithelial-hybrid-mesenchymal spectrum. This positioning, together with ssGSEA scores, improves the accuracy of IBC identification across the three independent datasets. Finally, we observed that IBC samples robustly displayed a higher coefficient of variation in terms of EMT scores, as compared to non-IBC samples. Pending verification that this patient-to-patient variability extends to intratumor heterogeneity within a single patient, these results suggest that higher heterogeneity along the epithelial-hybrid-mesenchymal spectrum can be regarded to be a hallmark of IBC and a possibly useful biomarker.

Implications of Tumor-Immune Coevolution on Cancer Evasion and Optimized Immunotherapy.

Cancer represents a diverse collection of diseases characterized by heterogeneous cell populations that dynamically evolve in their environment. As painfully evident in cases of treatment failure and recurrence, this general feature makes identifying long-term successful therapies difficult. It is now well-established that the adaptive immune system recognizes and eliminates cancer cells, and various immunotherapeutic strategies have emerged to augment this effect. These therapies, while promising, often fail as a result of immune-specific cancer evasion. Increasingly available empirical evidence details both cancer and immune system populations pre- and post-treatment, providing rich opportunity for mathematical models of the tumor-immune interaction and subsequent co-evolution. Integrated mathematical and experimental efforts bear immediate relevance for optimized therapies and will undoubtedly accelerate our understanding of this emergent field.

Rapid Assessment of T-Cell Receptor Specificity of the Immune Repertoire.

Accurate assessment of TCR-antigen specificity at the whole immune repertoire level lies at the heart of improved cancer immunotherapy, but predictive models capable of high-throughput assessment of TCR-peptide pairs are lacking. Recent advances in deep sequencing and crystallography have enriched the data available for studying TCR-p-MHC systems. Here, we introduce a pairwise energy model, RACER, for rapid assessment of TCR-peptide affinity at the immune repertoire level. RACER applies supervised machine learning to efficiently and accurately resolve strong TCR-peptide binding pairs from weak ones. The trained parameters further enable a physical interpretation of interacting patterns encoded in each specific TCR-p-MHC system. When applied to simulate thymic selection of an MHC-restricted T-cell repertoire, RACER accurately estimates recognition rates for tumor-associated neoantigens and foreign peptides, thus demonstrating its utility in helping address the large computational challenge of reliably identifying the properties of tumor antigen-specific T-cells at the level of an individual patient's immune repertoire.

Post-Discharge Mortality and Rehospitalization among Participants in a Comprehensive Acute Kidney Injury Rehabilitation Program.

Background: Hospitalization-associated AKI is common and is associated with markedly increased mortality and morbidity. This prospective cohort study examined the feasibility and association of an AKI rehabilitation program with postdischarge outcomes. Methods: Adult patients hospitalized from September 1, 2019 to February 29, 2020 in a large health system in Pennsylvania with stage 2-3 AKI who were alive and not on dialysis or hospice at discharge were evaluated for enrollment. The intervention included patient education, case manager services, and expedited nephrology appointments starting within 1-3 weeks of discharge. We examined the association between AKI rehabilitation program participation and risks of rehospitalization or mortality in logistic regression analyses adjusting for comorbidities, discharge disposition, and sociodemographic and kidney parameters. Sensitivity analysis was performed using propensity score matching. Results: Among the high-risk patients with AKI who were evaluated, 77 of 183 were suitable for inclusion. Out of these, 52 (68%) patients were enrolled and compared with 400 contemporary, nonparticipant survivors of stage 2/3 AKI. Crude postdischarge rates of rehospitalization or death were lower for participants versus nonparticipants at 30 days (15% versus 34%; P=0.01) and at 90 days (31% versus 51%; P=0.01). After multivariable adjustment, participation in the AKI rehabilitation program was associated with lower risk of rehospitalization or mortality at 30 days (OR, 0.41; 95% CI, 0.16 to 0.93), with similar findings at 90 days (OR, 0.52; 95% CI, 0.25 to 1.05). Due to small sample size, propensity-matched analyses were limited. The participants' rehospitalization or mortality was numerically lower but not statistically significant at 30 days (18% versus 31%; P=0.22) or at 90 days (47% versus 58%; P=0.4). Conclusions: The AKI rehabilitation program was feasible and potentially associated with improved 30-day rehospitalization or mortality. Our interventions present a roadmap to improve enrollment in future randomized trials.

Transcriptomic-Based Quantification of the Epithelial-Hybrid-Mesenchymal Spectrum across Biological Contexts.

Epithelial-mesenchymal plasticity (EMP) underlies embryonic development, wound healing, and cancer metastasis and fibrosis. Cancer cells exhibiting EMP often have more aggressive behavior, characterized by drug resistance, and tumor-initiating and immuno-evasive traits. Thus, the EMP status of cancer cells can be a critical indicator of patient prognosis. Here, we compare three distinct transcriptomic-based metrics-each derived using a different gene list and algorithm-that quantify the EMP spectrum. Our results for over 80 cancer-related RNA-seq datasets reveal a high degree of concordance among these metrics in quantifying the extent of EMP. Moreover, each metric, despite being trained on cancer expression profiles, recapitulates the expected changes in EMP scores for non-cancer contexts such as lung fibrosis and cellular reprogramming into induced pluripotent stem cells. Thus, we offer a scoring platform to quantify the extent of EMP in vitro and in vivo for diverse biological applications including cancer.