Ribosomal Incorporation of Lithocholic Acid into Peptides for the De Novo Discovery Of Peptide-Lithocholic Acid Hybrid Macrocyclic Peptides.

Peptide-bile acid hybrids offer promising drug candidates due to enhanced pharmacological properties, such as improved protease resistance and oral bioavailability. However, it remains unknown whether bile acids can be incorporated into peptide chains by the ribosome to produce a peptide-bile acid hybrid macrocyclic peptide library for target-based de novo screening. In this study, we achieved the ribosomal incorporation of lithocholic acid (LCA)-d-tyrosine into peptide chains. This led to the construction of a peptide-LCA hybrid macrocyclic peptide library, which enabled the identification of peptides TP-2C-4L3 (targeting Trop2) and EP-2C-4L5 (targeting EphA2) with strong binding affinities. Notably, LCA was found to directly participate in binding to EphA2 and confer on the peptides improved stability and resistance to proteases. Cell staining experiments confirmed the high specificity of the peptides for targeting Trop2 and EphA2. This study highlights the benefits of LCA in peptides and paves the way for de novo discovery of stable peptide-LCA hybrid drugs.

PepExplainer: An explainable deep learning model for selection-based macrocyclic peptide bioactivity prediction and optimization.

Macrocyclic peptides possess unique features, making them highly promising as a drug modality. However, evaluating their bioactivity through wet lab experiments is generally resource-intensive and time-consuming. Despite advancements in artificial intelligence (AI) for bioactivity prediction, challenges remain due to limited data availability and the interpretability issues in deep learning models, often leading to less-than-ideal predictions. To address these challenges, we developed PepExplainer, an explainable graph neural network based on substructure mask explanation (SME). This model excels at deciphering amino acid substructures, translating macrocyclic peptides into detailed molecular graphs at the atomic level, and efficiently handling non-canonical amino acids and complex macrocyclic peptide structures. PepExplainer's effectiveness is enhanced by utilizing the correlation between peptide enrichment data from selection-based focused library and bioactivity data, and employing transfer learning to improve bioactivity predictions of macrocyclic peptides against IL-17C/IL-17 RE interaction. Additionally, PepExplainer underwent further validation for bioactivity prediction using an additional set of thirteen newly synthesized macrocyclic peptides. Moreover, it enabled the optimization of the IC50 of a macrocyclic peptide, reducing it from 15 nM to 5.6 nM based on the contribution score provided by PepExplainer. This achievement underscores PepExplainer's skill in deciphering complex molecular patterns, highlighting its potential to accelerate the discovery and optimization of macrocyclic peptides.

A latent profile analysis of resilience and their relation to differences in sleep quality in patients with lung cancer.

PURPOSE: Sleep problems are a significant issue in patients with lung cancer, and resilience is a closely related factor. However, few studies have identified subgroups of resilience and their relationship with sleep quality. This study aimed to investigate whether there are different profiles of resilience in patients with lung cancer, to determine the sociodemographic characteristics of each subgroup, and to determine the relationship between resilience and sleep quality in different subgroups. METHODS: A total of 303 patients with lung cancer from four tertiary hospitals in China completed the General Sociodemographic sheet, the Connor-Davidson Resilience Scale, and the Pittsburgh Sleep Quality Index. Latent profile analysis was applied to explore the latent profiles of resilience. Multivariate logistic regression was used to analyze the sociodemographic variables in each profile, and ANOVA was used to explore the relationships between resilience profiles and sleep quality. RESULTS: The following three latent profiles were identified: the "high-resilience group" (30.2%), the "moderate-resilience group" (46.0%), and the "low-resilience group" (23.8%). Gender, place of residence, and average monthly household income significantly influenced the distribution of resilience in patients with lung cancer. CONCLUSION: The resilience patterns of patients with lung cancer varied. It is suggested that health care providers screen out various types of patients with multiple levels of resilience and pay more attention to female, rural, and poor patients. Additionally, individual differences in resilience may provide an actionable means for addressing sleep problems.

Social Support and Life Satisfaction in Women With Cervical Cancer: A Serial Multiple Mediation Model.

BACKGROUND: Although the number of studies focusing on life satisfaction in women with cervical cancer is increasing, there are limited studies on the pathway between social support and life satisfaction in this population. OBJECTIVE: This study explored the pathway between social support and life satisfaction in women with cervical cancer by examining the serial mediating effects of self-care self-efficacy, coping strategies, and depressive symptoms. METHODS: In this cross-sectional study, a total of 292 women with cervical cancer completed a questionnaire for assessing social support, self-efficacy, coping strategies, depressive symptoms, and life satisfaction. Structural equation modeling was used to test the direct and/or indirect effects of the variables on life satisfaction. RESULTS: Structural equation modeling analysis indicated that self-efficacy, coping strategies, and depressive symptoms mediates the effect of social support on life satisfaction. Direct paths from social support to life satisfaction, social support to self-efficacy, self-efficacy to coping strategies, coping strategies to depressive symptoms, and depressive symptoms to life satisfaction were significant ( P < .05). Moreover, indirect paths from social support to life satisfaction, self-efficacy to life satisfaction, and coping strategies to life satisfaction were also significant ( P < .05). CONCLUSIONS: Self-care self-efficacy, coping strategies, and depressive symptoms are potential pathways through which social support may affect life satisfaction in women with cervical cancer. IMPLICATION: Healthcare providers, family, and friends should offer more social support to the patients and make efforts to strengthen their self-care self-efficacy, facilitate active coping, and alleviate depressive symptoms to improve women's life satisfaction.

The value of combined detailed first-trimester ultrasound-biochemical analysis for screening fetal aneuploidy in the era of non-invasive prenatal testing.

PURPOSE: This study aimed to investigate the performance, cost-effectiveness and additional findings of combined detailed ultrasound and biochemical screening for risks of major fetal trisomies in the first-trimester. METHODS: This is a retrospective analysis study, we estimated the risk of trisomies 21, 18 and 13 based on maternal age, fetal nuchal translucency thickness, nasal bone, ductus venosus pulsatility index velocity, tricuspid regurgitation, fetal heart rate, free beta-human chorionic gonadotropin, and pregnancy-associated plasma protein A in singleton pregnant women, and performed non-invasive prenatal testing for women with risks of trisomy 21 between 1:500 and 1:300. Invasive diagnostic testing was performed for women with positive or failed non-invasive prenatal testing result and in the high-risk group of this screening method. The direct costs were compared between this strategy and the non-invasive prenatal testing which alone used as first-line screening for all pregnant women. RESULTS: Among 25,155 singleton pregnant women who underwent screening, 24,361 were available for analysis, of these, 194 cases underwent non-invasive prenatal testing. Among the 24,361 women, 39, 19, and 7 had trisomies 21, 18 and 13, respectively. The use of this strategy could potentially detect approximately 94.87% of trisomy 21 cases, 100% of trisomy 18 cases, and 100% of trisomy 13 cases, with false-positive rates of 2.49%, 0.41%, and 0.49%, respectively. The overall detection rate and overall false-positive rates were 96.92% and 2.52%, respectively. The detection rate was 100% in the advanced age group and 94.12% in the general age group. Additionally, structural abnormalities were detected in 137 fetuses, and 44 fetuses had other chromosomal abnormalities. The total cost of this strategy was $3,730,843.30, and the cost per person tested was $153.15. The total cost of using non-invasive prenatal testing as the first-line strategy would be $6,813,387.04 and the cost per person tested was $279.68. CONCLUSIONS: Our strategy is an efficient and cost-effective approach for detecting major trisomies and identifying more fetuses with a potential abnormality. Therefore, this strategy is a valuable screening method and highly feasible in the clinical setting.

PepScaf: Harnessing Machine Learning with In Vitro Selection toward De Novo Macrocyclic Peptides against IL-17C/IL-17RE Interaction.

The combination of library-based screening and artificial intelligence (AI) has been accelerating the discovery and optimization of hit ligands. However, the potential of AI to assist in de novo macrocyclic peptide ligand discovery has yet to be fully explored. In this study, an integrated AI framework called PepScaf was developed to extract the critical scaffold relative to bioactivity based on a vast dataset from an initial in vitro selection campaign against a model protein target, interleukin-17C (IL-17C). Taking the generated scaffold, a focused macrocyclic peptide library was rationally constructed to target IL-17C, yielding over 20 potent peptides that effectively inhibited IL-17C/IL-17RE interaction. Notably, the top two peptides displayed exceptional potency with IC50 values of 1.4 nM. This approach presents a viable methodology for more efficient macrocyclic peptide discovery, offering potential time and cost savings. Additionally, this is also the first report regarding the discovery of macrocyclic peptides against IL-17C/IL-17RE interaction.

Subgroups of self-directed learning ability and their differences in professional identity among nursing undergraduates during the COVID-19 pandemic: a latent profile analysis.

BACKGROUND: Promoting self-directed learning (SDL) among nursing undergraduates is crucial to meet the new requirements of the healthcare system and to adapt to online learning contexts during the COVID-19 pandemic. Therefore, identifying the classification features of SDL ability and developing targeted interventions are both critical. Professional identity (PI) may contribute to the cultivation of SDL ability, but their relationship remains relatively unknown. This study aimed to explore the subgroups of SDL ability and their differences in PI among nursing undergraduates during the COVID-19 pandemic. METHODS: A total of 2438 nursing undergraduates at four universities in China were enrolled in this cross-sectional study from November 2021 to February 2022. The Self-Directed Learning Scale of Nursing Undergraduates (SLSNU) and the Professional Identity Scale for Nursing Students (PISNS) were administered. A latent profile analysis was performed to explore SDL ability latent profiles. Multinomial logistic regression analysis was conducted to examine the predictors of profile membership, and a one-way analysis of variance was applied to compare the PI scores in each latent profile. RESULTS: Three latent profiles were identified and labeled 'low SDL ability' (n = 749, 30.7%), 'low initiative of help-seeking' (n = 1325, 54.4%) and 'high SDL ability' (n = 364, 14.9%). Multinomial logistic regression analysis suggested that nursing undergraduates who voluntarily chose a nursing major, had served as a student cadre, and had participated in clinical practicum were less likely to be included in the "low SDL ability" group. The average PI score was statistically different across the three profiles (F = 884.40, p < 0.001). CONCLUSION: The SDL ability among nursing undergraduates was divided into three profiles, and results show that promoting PI may effectively foster SDL ability. This study highlights the importance of targeted interventions by considering their distinct SDL ability patterns, especially during the COVID-19 pandemic.

Dyadic interventions in older people with chronic diseases: An integrative review.

This integrative review aims to explore the current state of dyadic interventions in older people with chronic diseases and to review how these interventions are developed and conducted. 'Older people' and 'dyadic intervention' were searched in six databases to include studies published before August 2021. The constant comparison method was used for data synthesis, combined with the Joanna Briggs Institute (JBI)1 and mixed methods appraisal tool (MMAT)2 to assess the quality of the literature. Nineteen studies were included and could be divided into four types in which caregivers could be seen as subordinators, directors, cooperators and collaborators. Dyadic interaction could be observed in all studies, including dyad coled, patient-led, and caregiver-led interactions. The outcome indicators included patient-, caregiver-, dyad-, and family-related indicators. It is important not only to include the dyad but also to consider the dyadic interactions. In the future, dyadic intervention can be guided by matching dyadic theories. NO PATIENT OR PUBLIC CONTRIBUTION: This study is an integrative review; the study population was not directly contacted. Data from included studies were analysed and interpreted.

Self-efficacy and positive coping mediate the relationship between social support and resilience in patients undergoing lung cancer treatment: A cross-sectional study.

Background: The prognosis of patients undergoing lung cancer treatment might be influenced by mental health status. Resilience is one of the important predictors to reflect the mental health status. It has been shown that patients with higher levels of social support, self-care self-efficacy, and positive coping have greater resilience. This study aimed to determine the mediating role of self-efficacy and positive coping in the relationship between social support and psychological resilience in patients with lung cancer. Method: This is a cross-sectional study that was conducted in in the oncology departments and thoracic surgical wards of four tertiary hospitals in Hunan Province, China, between November 2016 and November 2017. Three hundred and three patients who were undergoing treatment for lung cancer volunteered their participation in the study. Participants completed questionnaires, including the Chinese version of the Perceived Social Support Seale Scale, the Chinese version of Strategies Used by People to Promote Health Scale, and the Chinese version of the Connor-Davidson Resilience Scale. Results: Mediation analysis indicated that self-care self-efficacy and social support partially mediate the effect of social support on resilience. Direct paths from social support to self-efficacy, self-efficacy to positive coping, positive coping to psychological resilience, self-efficacy to psychological resilience, and social support to psychological resilience were significant (p < 0.001). The indirect paths from social support to self-efficacy and self-efficacy to psychological resilience were also significant. The chain mediation from social support to self-efficacy, self-efficacy to positive coping, and positive coping to resilience were significant. Conclusion: Self-efficacy and positive coping play an important role in the relationship between social support and resilience in patients receiving cancer treatment. Social support not only directly influenced psychological resilience but also indirectly influenced psychological resilience through self-efficacy and positive coping.

Implications of N7-hydrogen and C8-keto on the base pairing, mutagenic potential and repair of 8-oxo-2'-deoxy-adenosine: Investigation by nucleotide analogues.

Oxidative lesions, such as 8-oxo-dG and 8-oxo-dA, are continuously generated from exposure to reactive oxygen species. While 8-oxo-dG has been extensively studied, 8-oxo-dA has not received as much attention until recently. Herein, we report the synthesis of duplex DNAs incorporating dA, 8-oxo-dA, 7-deaza-dA, 8-Br-dA, and 8-Br-7-deaza-dA, which have different substitutions at 7- and 8-position, for the investigation into the implications of N7-hydrogen and C8-keto on the base pairing preference, mutagenic potential and repair of 8-oxo-dA. Base pairing study suggested that the polar N7-hydrogen and C8-keto of 8-oxo-dA, rather than the syn-preference, might be essential for 8-oxo-dA to form a stable base pair with dG. Insertion and extension studies using KF-exo- and human DNA polymerase ß indicated that the efficient dGTP insertion opposite 8-oxo-dA and extension past 8-oxo-dA:dG are contingent upon not only the stable base pair with dG, but also the flexibility of the active site in polymerase. The N7-hydrogen in 8-oxo-dA or C7-hydrogen in 7-deaza-dA and 8-Br-7-deaza-dA was suggested to be important for the recognition by hOGG1, although the excision efficiencies of 7-deaza-dA and 8-Br-7-deaza-dA were much lower than 8-oxo-dA. This study provides an insight into the structure-function relationship of 8-oxo-dA by nucleotide analogues.

Subtypes of work engagement in frontline supporting nurses during COVID-19 pandemic: A latent profile analysis.

AIM: The aim was to examine the subgroups of work engagement in frontline nurses during the COVID-19 pandemic. BACKGROUND: The pandemic may affect the work engagement of nurses who have direct contact with infected patients and lead to a poor quality of care. Identifying classification features of work engagement and tailoring interventions to support frontline nurses is imperative. DESIGN: This study utilized a cross-sectional study design. METHODS: Three hundred fifty-five nurses were enrolled in this cross-sectional study from 14 February to 15 April 2020. A latent profile analysis was performed to identify classification features of work engagement. Multiple logistic regression analyses were used to examine predictors of profile membership. RESULTS: A four-profile model provided the best fit. The four profiles were titled 'low work engagement' (n = 99), 'high vigour-low dedication and absorption' (n = 58), 'moderate work engagement' (n = 63) and 'high work engagement' (n = 135). A regression analysis suggested that young nurses and nurses who were the only children of their family were more likely to be in the 'low work engagement' and 'high vigour-low dedication and absorption' groups. CONCLUSION: This study highlights the importance of tailoring interventions for frontline supporting nurses by considering their distinct work engagement patterns, especially during the COVID-19 pandemic, to improve the promotion of work satisfaction and quality of care. IMPACT: This was the first study to explore the latent profiles of work engagement in frontline nurses during the COVID-19 pandemic. Over 40% of nurses were in the 'low work engagement' and 'high vigour-low dedication and absorption' groups and reported low levels of work engagement. Understanding different patterns of work engagement in frontline nurses can help nursing managers provide emotional, material and organizational support based on the features of each latent profile, which may improve the quality of care and patient safety.

Design and Ribosomal Incorporation of Noncanonical Disulfide-Directing Motifs for the Development of Multicyclic Peptide Libraries.

The engineering of naturally occurring disulfide-rich peptides (DRPs) has been significantly hampered by the difficulty of manipulating disulfide pairing. New DRPs that take advantage of fold-directing motifs and noncanonical thiol-bearing amino acids are easy-to-fold with expected disulfide connectivities, representing a new class of scaffolds for the development of peptide ligands and therapeutics. However, the limited diversity of the scaffolds and particularly the use of noncanonical amino acids [e.g., penicillamine (Pen)] that are difficult to be translated by ribosomes greatly hamper the further development and application of these DRPs. Here, we designed and synthesized noncanonical bisthiol motifs bearing sterically obstructed thiol groups analogous to the Pen thiol to direct the folding of peptides into specific bicyclic and tricyclic structures. These bisthiol motifs can be ribosomally incorporated into peptides through a commercially available PURE system integrated with genetic code reprograming, which enables, for the first time, the in vitro expression of bicyclic peptides with two noncanonical and orthogonal disulfide bonds. We further constructed a bicyclic peptide library encoded by mRNA, with which new bicyclic peptide ligands with nanomolar affinity to proteins were successfully selected. Therefore, this study provides a new, general, and robust method for discovering de novo DRPs with new structures and functions not derived from natural peptides, which would greatly benefit the field of peptide drug discovery.

Metagenomic sequencing-driven multidisciplinary approaches to shed light on the untapped microbial natural products.

The advantage of metagenomics over the culture-based natural product (NP) discovery pipeline is the ability to access the biosynthetic potential of uncultivable microbes. Advances in DNA sequencing are revolutionizing conventional metagenomics approaches for microbial NP discovery. The genomes of (in)cultivable bugs can be resolved straightforwardly from environmental samples, enabling in situ prediction of biosynthetic gene clusters (BGCs). The predicted chemical diversities could be realized not only by heterologous expression of gene clusters originating from DNA synthesis or direct cloning, but also potentially by bioinformatic-directed organic synthesis or chemoenzymatic total synthesis. In this review, we suggest that metagenomic sequencing in tandem with multidisciplinary approaches will form a versatile platform to shed light on a plethora of microbial 'dark matter'.

Merging the Versatile Functionalities of Boronic Acid with Peptides.

Peptides inherently feature the favorable properties of being easily synthesized, water-soluble, biocompatible, and typically non-toxic. Thus, boronic acid has been widely integrated with peptides with the goal of discovering peptide ligands with novel biological activities, and this effort has led to broad applications. Taking the integration between boronic acid and peptide as a starting point, we provide an overview of the latest research advances and highlight the versatile and robust functionalities of boronic acid. In this review, we summarize the diverse applications of peptide boronic acids in medicinal chemistry and chemical biology, including the identification of covalent reversible enzyme inhibitors, recognition, and detection of glycans on proteins or cancer cell surface, delivery of siRNAs, development of pH responsive devices, and recognition of RNA or bacterial surfaces. Additionally, we discuss boronic acid-mediated peptide cyclization and peptide modifications, as well as the facile chemical synthesis of peptide boronic acids, which paved the way for developing a growing number of peptide boronic acids.

In Vitro Selection of Macrocyclic d/l-Hybrid Peptides against Human EGFR.

d/l-Hybrid peptides are an attractive class of molecular modality because they are able to exhibit high proteolytic stability and unique structural diversity which cannot be accessed by those consisting of only proteinogenic l-amino acids. Despite such an expectation, it has not been possible to devise de novo d/l-hybrid peptides capable of disrupting the function of a protein target(s) due to the lack of an effective method that reliably constructs a highly diverse library and screens active species. Here we report for the first time construction of a library consisting of 1012 members of macrocyclic d/l-hybrid peptides containing five kinds of d-amino acids and performance of the RaPID selection against human EGFR as a showcase to uncover PPI (protein-protein interaction) inhibitors.

Lasso-grafting of macrocyclic peptide pharmacophores yields multi-functional proteins.

Protein engineering has great potential for devising multifunctional recombinant proteins to serve as next-generation protein therapeutics, but it often requires drastic modifications of the parental protein scaffolds e.g., additional domains at the N/C-terminus or replacement of a domain by another. A discovery platform system, called RaPID (Random non-standard Peptides Integrated Discovery) system, has enabled rapid discovery of small de novo macrocyclic peptides that bind a target protein with high binding specificity and affinity. Capitalizing on the optimized binding properties of the RaPID-derived peptides, here we show that RaPID-derived pharmacophore sequences can be readily implanted into surface-exposed loops on recombinant proteins and maintain both the parental peptide binding function(s) and the host protein function. We refer to this protein engineering method as lasso-grafting and demonstrate that it can endow specific binding capacity toward various receptors into a diverse set of scaffolds that includes IgG, serum albumin, and even capsid proteins of adeno-associated virus, enabling us to rapidly formulate and produce bi-, tri-, and even tetra-specific binder molecules.

Combining NMR-Based Metabolic Profiling and Genome Mining for the Accelerated Discovery of Archangiumide, an Allenic Macrolide from the Myxobacterium Archangium violaceum SDU8.

An unprecedented 19-membered allenic macrolide archangiumide (1) was discovered from the myxobacterium Archangium violaceum SDU8 by integrating NMR-based metabolic profiling and genome mining. Its biosynthesis pathway was proposed based on the architectural analysis of the encoding trans-AT PKS genes and validated by isotope labeling. The methodology of combing 2D NMR-based metabolic profiling and bioinformatics-aided structure prediction, as exemplified by this study, is anticipated to improve discovery efficiency of a broader range of microbial "dark matter".

Resilience in Patients With Lung Cancer: Structural Equation Modeling.

BACKGROUND: Resilience is important for patients with cancer. However, the relationships among factors affecting the resilience of patients with lung cancer have not been studied sufficiently. OBJECTIVE: The aim of this study was to clarify the relationships among social support, resilience, self-efficacy, and symptom distress among patients with lung cancer. METHODS: Through simple random sampling, 303 patients with lung cancer from 4 tertiary hospitals in Changsha, China, were recruited for a cross-sectional descriptive correlational survey. Data were collected using demographic and disease-related information, the Connor-Davidson Resilience Scale, Strategies Used by People to Promote Health, the Perceived Social Support Scale, and the Symptom Distress Scale. RESULTS: Patients' mean total resilience score was 50.01 ± 15.25. The fit indices for the model indicated a good fit. Social support had multiple effects on resilience; specifically, it had direct and indirect effects through the mediating role of self-efficacy. Symptom distress had only an indirect effect on resilience through self-efficacy. CONCLUSIONS: Social support, symptom distress, and self-efficacy are key factors associated with resilience in patients with lung cancer. These factors had direct and indirect effects on each other and on resilience. IMPLICATIONS FOR PRACTICE: To enhance resilience among patients with lung cancer, interventions that strengthen self-efficacy, provide social support, and reduce symptom distress should be developed.

Targeting human MutT homolog 1 (MTH1) for cancer eradication: current progress and perspectives.

Since accelerated metabolism produces much higher levels of reactive oxygen species (ROS) in cancer cells compared to ROS levels found in normal cells, human MutT homolog 1 (MTH1), which sanitizes oxidized nucleotide pools, was recently demonstrated to be crucial for the survival of cancer cells, but not required for the proliferation of normal cells. Therefore, dozens of MTH1 inhibitors have been developed with the aim of suppressing cancer growth by accumulating oxidative damage in cancer cells. While several inhibitors were indeed confirmed to be effective, some inhibitors failed to kill cancer cells, complicating MTH1 as a viable target for cancer eradication. In this review, we summarize the current status of developing MTH1 inhibitors as drug candidates, classify the MTH1 inhibitors based on their structures, and offer our perspectives toward the therapeutic potential against cancer through the targeting of MTH1.

Macrocyclic Peptide-Mediated Blockade of the CD47-SIRPα Interaction as a Potential Cancer Immunotherapy.

Medium-sized macrocyclic peptides are an alternative to small compounds and large biomolecules as a class of pharmaceutics. The CD47-SIRPα signaling axis functions as an innate immune checkpoint that inhibits phagocytosis in phagocytes and has been implicated as a promising target for cancer immunotherapy. The potential of macrocyclic peptides that target this signaling axis as immunotherapeutic agents has remained unknown, however. Here we have developed a macrocyclic peptide consisting of 15 amino acids that binds to the ectodomain of mouse SIRPα and efficiently blocks its interaction with CD47 in an allosteric manner. The peptide markedly promoted the phagocytosis of antibody-opsonized tumor cells by macrophages in vitro as well as enhanced the inhibitory effect of anti-CD20 or anti-gp75 antibodies on tumor formation or metastasis in vivo. Our results suggest that allosteric inhibition of the CD47-SIRPα interaction by macrocyclic peptides is a potential approach to cancer immunotherapy.