The efficacy of transnasal endoscopy using an ultrathin endoscope has been reported in several studies. However, few studies regarding peroral endoscopy with ultrathin endoscopes with high resolution have been reported. This study investigates the pain alleviation of peroral endoscopy with an ultrathin endoscope.Patients with a history of peroral endoscopy using a conventional, normal-diameter scope with no sedation who underwent peroral esophagogastroduodenoscopy (EGD) using a thin scope between April-July 2022 were included in this study. After the procedure, the patients completed a questionnaire evaluating pain during the examination and willingness to repeat the procedure. The physicians were surveyed regarding their level of satisfaction. The primary endpoint was patient satisfaction, which corresponded to the rate of patients who rated the thin endoscope as more comfortable or somewhat more comfortable than the previously-used, conventional endoscope.One hundred and forty-five patients were included in the analyses. Patient satisfaction was achieved in 86.2% (125/145) of patients. The median visual analog scale pain score was 3 (0–7) points in this study, which is significantly lower than the pain score after the previous endoscopy (5 (0–10) points; p < 0.001). In addition, 96% (24/25) of patients who underwent EGD by an expert and 95.8% (115/120) who underwent EGD by a non-expert were willing to repeat endoscopy using the thin scope (p = 0.69).Peroral endoscopy using a thin scope reduces patient pain regardless of the endoscopist’s experience. Esophagogastroduodenoscopy (EGD) is important for the early detection of gastrointestinal tumors; however, the examination is often painful without sedation . As painThis single-center, single-arm, prospective study was registered with the University Hospital Medical Information Network (000047366) and conducted in accordance with the Declaration of Helsinki with the written consent of all patients. Approval was obtained from the institutional review board of Nihon University Hospital.Figure Patients were instructed to begin fasting at 21:00 the day before EGD. Lidocaine spray  was applied to the throat for local anesthesia as a pre-endoscopy treatment. An ultrathin endoscope with a 5.4 mm diameter  or 5.8 mm diameter  was used. All EGD examinations were performed by one of eight endoscopists with five or more years of endoscopy experience as a gastroenterologist. Three endoscopists were considered experts, while five were non-experts. Operators who were certified by the Japan Gastroenterological Endoscopy Society as endoscopy specialists were defined as experts.After the procedure, the patients evaluated the pain experienced during the previous endoscopy  and that during the present endoscopy (using the ultrathin scope) on a five-point scale . The patients also rated their throat discomfort during the previous and present endoscopies using the visual analog scale . The patients also reported their willingness to undergo repeat endoscopy using the same scope and their preference for a thin scope during endoscopy. The physicians also completed a questionnaire after the procedure regarding their satisfaction with the endoscopy. The satisfaction defined as: A, ease of endoscopy without complaints; B, uneasiness with endoscopy due to reflex or operability issues; or C, unsatisfactory endoscopy requiring a different scope or future endoscopy with sedation. A (ease of endoscopy without complaints) was defined as physician satisfaction.In a previous study, when upper EGD was performed using an ultrathin endoscope and a normal-diameter endoscope, 31% of patients who underwent EGD with the normal-diameter scope and 14% of patients who underwent EGD with the ultrathin scope requested sedation during the next endoscopy . Based oThe primary endpoint was patient satisfaction, which was defined as the rate of patients who answered that the present endoscopy was more comfortable or somewhat more comfortable than their previous peroral endoscopy. A subgroup analysis was conducted to compare the differences in the primary endpoint based on the endoscope and level of endoscopist expertise.The secondary endpoints included the physicians’ satisfaction with the thin endoscope, patients’ rate of willingness undergo repeat endoscopy using the thin endoscope, patient pain score, EGD time, biopsy success rate and time, and tumor detection rate.We also performed a sub-analysis of patients with a pain score of 5 or higher in the previous examination. We evaluated the rate of improvement in pain compared to the previous endoscopy and the rate of willingness undergo repeat endoscopy using the ultrathin scope.Continuous variables are presented as median and range. Categorical variables are presented as number and frequency. Wilcoxon’s rank sum test was used to compare the continuous variables, and Fisher’s test was used to compare the categorical variables. Statistical significance was set at p < 0.05. All statistical analyses were conducted using JMP .Of the 150 patients enrolled in this study between April 1 and July 31, 2022, five were excluded due to incomplete questionnaire entries , and 104 patients were men . However, the pain prior to the scope passing through the throat was higher among patients who underwent transnasal endoscopy. Another study reported more favorable outcomes after transnasal endoscopy, including better general tolerability, tolerability as the scope passed through the throat, and willingness to undergo repeat endoscopy with the same endoscope . HoweverThe tumor detection rate in this study was 0%. This may be due to the facts that a history of peroral endoscopy was an eligibility criterium of this study, the patients were relatively young and underwent endoscopy as part of routine screening, or the study included a low rate of patients with atrophied mucosa .Peroral endoscopy using a thin scope has several advantages, including its cost performance, safety, and low pain scores without the use of sedation. The use of a thin endoscope during peroral endoscopy reduces the pain score regardless of the endoscopist expertise as nasal pain is avoided. In addition, increasing the willingness of patients to undergo repeat endoscopy may lead to increased rates of early cancer detection, which is especially important in patients with no mucosal atrophy in whom gastric cancer may be detected. These results highlight the importance of a screening endoscopy method that minimizes the pain for the patient.This study is not without limitations. First, it was a single-center, single-arm study with a small sample size. Although the patient satisfaction was compared to that after the previous peroral endoscopy with a normal-diameter scope, this was not a randomized controlled study. Therefore, the evaluation index of the study is subjective. Since the subjects signed an informed consent form before participating in the trial and had relevant understanding of the trial situation, this may have affected the trial results due to psychological implications. Second, this study only included patients with a history of peroral endoscopy using a conventional, normal-diameter scope with no sedation. This may have resulted in a selection bias, as patients who have had previous painful experiences with endoscopy or who require sedation during the procedure may not have been included in the study. Third, the evaluation indicators of this study were subjective and may have recall bias. Fourth, the endoscopy procedures may have been performed by different endoscopists. Finally, although the physician satisfaction level was high, the imaging quality of the thin scope was not evaluated in this study. Image resolution affects the malignancy detection rate.Although this study suggested the advantage of peroral endoscopy with an ultrathin endoscopy, it is difficult to conclude that from this study alone, since patients who experienced severe distress with conventional endoscopy in the past may have been excluded from this study because they avoided undergoing endoscopy again.The use of a ultrathin endoscope during peroral endoscopy reduces patient pain.　A multi-center, prospective study comparing the cancer detection rate of EGD using a normal-diameter endoscope with that using a ultrathin endoscope is necessaryTable


In propaganda and hate speech, target groups are often compared to dangerous and disgusting animals. Exposure to these animalistic slurs is thought to increase endorsement of intergroup harm but the mechanism by which this happens remains unclear. Across two pre-registered and highly powered studies, we examined how animalistic language influences the cultural transmission of beliefs about target groups. In line with previous work, we found that describing a novel political group with animalistic slurs increased the extent to which participants endorsed harm towards them. Importantly, reading animalistic slurs did not influence the extent to which participants believed the target group possessed uniquely human qualities. Rather, the animalistic slurs influenced endorsement of harm by making the target group appear more undesirable. These findings offer a novel perspective into the nature of dehumanization and new insights into how hate speech functions. Statement of relevancePropaganda and hate speech regularly incorporate references to the victim group as dangerous and disgusting animals, such as rats and cockroaches. These animalistic slurs lead to further intergroup harm. Given the prevalence of dangerous online hate speech, accurately understanding its societal impact on attitudes and behaviours is crucial. One possibility is that animalistic slurs lead the target group to be viewed as possessing fewer uniquely human qualities. Alternatively, animalistic slurs may serve as metaphors which lead to negative perceptions of the outgroup. Despite receiving theoretical attention across the social sciences, the function of dehumanizing language in influencing beliefs about, and behaviour towards, target groups has received scant empirical attention. Across two experiments, we show that animalistic slurs increased harm by leading the target group to be perceived as undesirable. Animalistic slurs did not influence the extent to which the target group was seen to possess uniquely human character traits and emotions.. 1Propaganda and hate speech regularly incorporate references to victim groups as dangerous and disgusting animals. For example, in Nazi Germany, anti-Semitic propaganda compared Jewish people to rats, lice and parasites. Before and during the genocide in Rwanda in 1994, Hutu propaganda referred to Tutsis as snakes and cockroaches , while uResearchers have sought to analyse propaganda and hate speech in order to help understand the psychological mechanisms which contribute to intergroup harm. According to arguments across psychology, neuroscience, philosophy, history and sociology, a psychological process of dehumanization often lies at the heart of intergroup harm. When outgroup members are blatantly dehumanized, they are thought to be viewed as less than human creatures and explicitly compared to non-human animals ,8. When There is a growing debate in the literature regarding how the language used by propagandists relates to their underlying beliefs about the victim group. In line with theorizing on dehumanization, one possibility is that animalistic slurs often reflect propagandists' literal belief that victim groups are less than human. For example, Smith argues that ‘…dehumanizers are not just slinging animalistic metaphors at a vulnerable group… They sincerely believe that those whom they persecute are less than human.’ , p. 28. Der Giftpilz (The Poisonous Mushroom), both ingroup and outgroup members are compared to non-human entities: ‘There are good mushrooms and there are good people. There are poisonous, bad mushrooms and there are bad people’. In addition, animalistic slurs often appear in propaganda alongside references to the victim group as enemies, criminals and traitors—terms that make most sense when applied to humans  to be dissolved? 2.How likely would you be to attend a protest against the [MRP/NLP]? 3.How severe do you think the limitations on [MRP/NLP] funding should be? 4.How severe do you think restrictions on [MRP/NLP] social media use should be?There were two harm endorsement blocks, one for each group condition. The four items within each block were presented in a random order and one attention check per block was included approximately halfway through . For each item, participants indicated their response on an unmarked sliding scale from Not at all [likely/severe] (0) to Extremely [likely/severe] (100).Four items measured the endorsement of harm towards each group. These were:α = 0.86 for animalistic condition; α = 0.83 for control). The items were combined using the mean into a single harm endorsement score for each target group.The four-item harm endorsement scales showed good internal reliability  questions were asked. Screening for eligibility was through Prolific and we also confirmed participants met the requirements within the demographic questions.On beginning the main study, participants were first told that they would read a short fictional story and were asked to pay close attention. They then read:In a Southern European country, political campaigns are underway for the next general election, due to be held in about a month. The vote is predicted to be extremely close between two of the country's main parties: The NLP and the MRP.To find out about voters' feelings towards the campaigns, a politically independent national newspaper gathered some vox pops from several members of the public in the country's capital.You will see some quotes extracted from these vox pops. The first set of quotes that you will see are about some of the residents' feelings towards the [‘MRP'/NLP].Following the introduction, participants read the first set of sentences. Sentences were presented individually and participants could only move on from each sentence after 3 s to ensure they had read it in full (there was no maximum time that participants could spend on each sentence). Whether the first sentences described the ‘MRP’ or the ‘NLP’ and whether they represented the animalistic or the control condition depended on which counterbalanced version the participant was assigned to (see above). Participants then completed an unrelated filler task for 1 min. After the filler task, participants completed the trait attribution scale in which they considered the typical characteristics of the party referred to in the first sentence set. Next, participants completed the harm endorsement scale with reference to the same party.Once participants had completed the harm endorsement scale for the first party, they were informed that they were halfway through the study and that they would next see some more quotes extracted from the vox pops. They were informed that the next set of quotes would be about the other party . Participants then read the second set of sentences. As for the first set, each sentence was presented individually and shown on the screen for at least 3 s before it was possible to move to the next. Participants then completed another unrelated filler task for 1 min. After the filler, participants completed trait attributions and then the harm endorsement scale for the party referred to in the second sentence set.On finishing the main study questions, participants were asked an optional question about their ethnicity and then had the opportunity to provide written feedback about the study. Finally, participants were debriefed and redirected back to Prolific for payment. Most participants took under 12 min to complete the study.. 2.2. 2.2.1A 2 × 2 × 2 (trait desirability: desirable/undesirable) within-subjects ANOVA measured the effect of animalistic slurs on trait attributions. If animalistic slurs lead to representations of the target group as less human, then an interaction between condition and humanness should show ratings of uniquely human traits to be lower in the animalistic than in the control condition. If animalistic slurs lead to representations of the target group as undesirable in character, then an interaction between condition and social desirability should show ratings of desirable traits to be lower in the animalistic than in the control condition, and ratings of undesirable traits to be higher in the animalistic than in the control condition.F1,207 = 2.03, p = 0.156, F1,207 = 38.65, p < 0.001, F1,207 = 258.98, p < 0.001, There was no main effect of condition on trait attributions, F1,207 = 10.56, p = 0.001, ps < 0.001). Further in line with our predictions, the target group were attributed undesirable uniquely human traits and undesirable shared traits to a greater extent in the animalistic condition than the control condition (both ps < 0.001).Importantly, there was a three-way interaction between condition, humanness and desirability F1,207 = 89.54, p < 0.001, ps < 0.001).Measuring whether animalistic slurs alter perceptions of social desirability, there was an interaction between condition and trait desirability, F1,207 = 14.41, p < 0.001, p = 0.085). For traits shared with other animals, ratings were overall higher for the animalistic condition than for the control condition (p = 0.001).Measuring whether animalistic slurs alter perceptions of humanness, there was an interaction between condition and trait humanness, F1,207 = 57.22, p < 0.001, p = 0.132). However, ratings were higher overall for uniquely human undesirable traits than for shared undesirable traits (p < 0.001). Ratings were higher for undesirable than desirable items across both levels of humanness (both ps < 0.001).The theoretically uninteresting interaction between trait humanness and trait desirability was also significant, . 2.2.2t-test. We predicted that endorsement of harm would be higher in the animalistic condition than in the control condition. Confirming previous theorizing, participants expressed greater harm endorsement towards the target group in the animalistic condition  than in the control condition , t207 = 7.45, p < 0.001, d = 0.52.We measured whether participants were more likely to endorse harming the target group following exposure to animalistic slurs. In order to do this, we compared harm endorsement in the animalistic condition to harm endorsement in the control condition using a within subjects . 2.2.3We tested the mechanism by which describing a group with animalistic slurs influenced endorsement of harm towards that group. If comparisons to animals increase a group's risk of harm through reducing perceptions of their humanity, then we would expect an increase in harm for the animalistic condition relative to the control to be predicted by a decrease in uniquely human trait attributions and/or an increase in attributions of traits shared with other animals for the animalistic condition relative to the control.If comparisons to non-human animals increase a group's risk of harm through changing perceptions of their social desirability, then we would expect an increase in harm for the animalistic condition relative to the control to be predicted by a decrease in desirable trait attributions and/or an increase in undesirable trait attributions.Four linear regressions tested whether an increase in harm endorsement towards targets in the animalistic condition relative to the control was predicted by (1) a decrease in uniquely human trait attributions; (2) an increase in attributions of traits shared with other animals; (3) a decrease in desirable trait attributions; (4) an increase in undesirable trait attributions.. 2.2.4To create a relative harm score representing the difference in harm endorsement for the animalistic compared with the control condition, we subtracted each participant's harm endorsement score for the control condition from their harm endorsement score for the animalistic condition.. 2.2.5To create a relative humanness attribution score representing the difference in attribution of uniquely human traits for the animalistic condition compared with the control, we created the mean of all uniquely human traits for each participant for each condition, and we then subtracted the mean uniquely human trait attribution score for the control condition from the mean uniquely human trait attribution score for animalistic condition. This gave a score showing the difference in humanness attribution between the animalistic and control conditions. Positive numbers here represent a tendency for participants to believe targets compared to animals possess uniquely human qualities to a greater extent than the control, negative numbers indicate the reverse.We used the same method to create a relative score representing the difference in attribution of traits shared with other animals for the animalistic condition compared with the control, where positive numbers represent a tendency for participants to believe targets compared to animals possess traits shared with other animals to a greater extent than the control, and negative numbers indicate the reverse.We created a relative score representing the difference in attribution of desirable traits for the animalistic condition compared with the control by creating a mean of the desirable traits for each participant for each condition, and then subtracting the mean desirable trait attribution score for the control condition from the mean desirable trait attribution score for animalistic condition. Positive numbers here represent a tendency for participants to believe targets compared to animals possess desirable qualities to a greater extent than the control, negative numbers indicate the reverse. We used the same method to create a relative score representing the difference in attribution of undesirable traits for the animalistic condition compared with the control, where positive numbers represent a tendency for participants to believe targets compared to animals possess undesirable traits to a greater extent than the control, and negative numbers indicate the reverse. 1.Is the increase in harm for the animalistic condition relative to the control predicted by a decrease in uniquely human trait attributions for the animalistic condition relative to the control? 2.Is the increase in harm for the animalistic condition relative to the control predicted by an increase in trait attributions shared with other animals for the animalistic condition relative to the control? 3.Is the increase in harm for the animalistic condition relative to the control predicted by a decrease in desirable trait attributions for the animalistic condition relative to the control? 4.Is the increase in harm for the animalistic condition relative to the control predicted by an increase in undesirable trait attributions for the animalistic condition relative to the control?A strength of this approach is that we could plausibly observe effects of both dehumanization and antipathy. That is, this approach allows us to determine whether changes in humanness perceptions (1 and 2) and changes in desirability perceptions (3 and 4) are both associated with increased endorsement of harm. The four separate linear regressions allowed us to measure humanness and desirability changes as orthogonal, testing for effects of each with neither confounded by the other.We used these relative scores to test the predictions using four linear regressions:1 The final samples for each model were well powered to detect effects of interest in the regression analyses. Full regression statistics for each of the four models, including 95% confidence intervals, are reported in  1.Is the increase in harm towards targets in the animalistic condition relative to the control predicted by a decrease in uniquely human trait attributions for targets in the animalistic condition relative to the control?Before conducting the regression analyses, assumptions of each of the four individual regression models were checked, and influential scores were identified and removed using Cook's distance.Eight data points fell outside of Cook's distance and one additional data point had a standardized residual greater than 3 and so was identified as an outlier. These nine data points were excluded, resulting in a sample of 199 for the first regression model.p = 0.859. This model explained less than 0.001% of the variance in relative harm scores. 2.Is the increase in harm towards targets in the animalistic condition relative to the control predicted by an increase in attributions of traits shared with other animals for targets in the animalistic condition relative to the control?Ten data points fell outside of Cook's distance and were excluded, resulting in a sample of 198 for the second regression model.Our first linear regression showed the increase in harm towards targets in the animalistic condition relative to the control was not predicted by a decrease in uniquely human trait attributions to targets in the animalistic condition relative to the control, p = 0.612. This model explained about 0.001% of the variance in relative harm scores. 3.Is the increase in harm towards targets in the animalistic condition relative to the control predicted by a decrease in socially desirable trait attributions for targets in the animalistic condition relative to the control?Fourteen data points fell outside of Cook's distance and were excluded, resulting in a sample of 194 for the third regression model.Our second simple linear regression showed the increase in harm towards targets in the animalistic condition relative to the control was not predicted by an increase in attributions of traits shared with other animals to targets in the animalistic condition relative to the control, p < 0.001. This model explained approximately 55% of the variance in relative harm scores. 4.Is the increase in harm towards targets in the animalistic condition relative to the control predicted by an increase in socially undesirable trait attributions for targets in the animalistic condition relative to the control?Seventeen data points fell outside of Cook's distance and were excluded, resulting in a sample of 191 for the fourth regression model.Our third linear regression showed increased harm towards targets in the animalistic condition relative to the control was significantly associated with decreased desirable attributions to targets in the animalistic condition relative to the control, p < 0.001. This model explained approximately 48% of the variance in relative harm scores.Our fourth linear regression showed increased harm towards targets in the animalistic condition relative to the control was significantly associated with increased undesirable trait attributions to targets in the animalistic condition relative to the control, Increased harm for targets in the animalistic condition relative to the control was predicted by altering perceptions of social desirability but not of humanness . Electro. 2.3Describing a group with animalistic slurs did not lead to trait-based dehumanization of its members compared with a control. Rather, comparing a group to animals changed the extent to which its members were judged to possess socially desirable character traits. Members of the group compared to animals were rated as possessing desirable traits to a lesser extent but undesirable traits to a greater extent than the control, regardless of whether or not these traits were perceived as being unique to humans. Describing a group in animalistic terms increased harm endorsement relative to a control. Crucially, this increased harm was not predicted by changes in the extent to which the group was believed to have uniquely human character traits. Rather, it was predicted by perceptions that members of the target group possessed desirable traits to a lesser extent, and undesirable traits to a greater extent, than the control. We next measured whether this pattern of results would replicate using a different operationalization of dehumanization.. 3In Study 2, we sought to measure whether the results of Study 1 would replicate when employing an alternative characterization of dehumanization based on emotion attribution. According to infrahumanization theory, outgroups are dehumanized to the extent they are denied the experience of uniquely human emotions such as pride, nostalgia and guilt ,12. We mA dehumanization view predicts that reading animalistic slurs will lead participants to view the target group as less human, here shown in the denial of uniquely human emotions. This view further predicts that a dehumanized perception of the target group will explain the connection between animalistic slurs and harmWe predicted that reading animalistic slurs about a group would lead participants to view the target group more negatively, shown in a denial of socially desirable emotions, but increased attribution of socially undesirable emotions. We further predicted that this negative perception of the target group would explain the connection between animalistic slurs and endorsement of harm.. 3.1. 3.1.1Based on the same power analyses described for Study 1, 208 participants completed the study. Participants were again 18 or over, fluent in English, and UK nationals living in the UK. In line with our pre-registration, we excluded and replaced six participants who failed the attention check. Of the final sample, 161 participants identified as female, 44 as male and three as non-binary. Participants were aged from 18 to 74 with a mean age of 38.0 (s.d. = 12.8).. 3.1.2The design and data analysis strategy was as described for Study 1, though with emotion attributions in place of trait attributions.. 3.1.3. 3.1.3.1The language manipulation and the harm endorsement scale were exactly as described for Study 1  to Very much so (100), with the midpoint Somewhat (50), though they could not see the numbers. For example, a block could begin:Participants indicated the extent to which they thought members of each group (the MRP and the NLP) typically feel each of the emotions. Emotion attributions were made across two blocks, one for each group condition. For each item, participants indicated their response on a sliding scale from Using the sliding scales below, please consider the extent to which you think members of the NLP typically feel each emotion.Then, participants would respond to each item, such as ‘Members of the NLP typically feel admiration’ using the unmarked sliding scale. The 12 items within each block were randomized. One attention check per block was included halfway through .Following our pre-registered plan, attribution scores for each emotion category for each target group were obtained by calculating the mean of the three emotions within the category for each participant. For example, a participant's attribution of uniquely human desirable emotion for each group was the mean of their ratings for admiration, humility and optimism.. 3.1.3.3The harm endorsement scale used was exactly as described for Study 1.. 3.1.4Participants were informed that the study was designed to help us understand the ways in which people ascribe emotions to different groups of individuals and make behavioural decisions about them. The procedure was then exactly as described for Study 1, though with the emotion attribution scale in place of the trait attribution scale.. 3.2. 3.2.1We measured how comparing a target group to animals influenced subsequent emotion attributions for that group. There were four emotion conditions: uniquely human and desirable, uniquely human and undesirable, shared with other animals and desirable, and shared with other animals and undesirable.A 2  × 2  × 2  within-subjects ANOVA measured the effect of animalistic language on emotion attributions. If animalistic slurs lead to representations of the target group as less human, then an interaction between condition and humanness should show ratings of uniquely human emotions to be lower in the animalistic than in the control condition. If animalistic slurs lead to representations of the target group as undesirable in character, then an interaction between condition and social desirability should show ratings of desirable emotions to be lower in the animalistic than in the control condition, and ratings of undesirable emotions to be higher in the animalistic than in the control condition. As noted for Study 1, this design also allows us to detect evidence for both effects operating simultaneously.F1,207 = 001, p = 0.974, F1,207 = 51.06, p < 0.001, F1,207 = 285.01, p < 0.001, There was no main effect of condition, F1,207 = 0.40, p = 0.529, In this study, the three-way interaction between condition, humanness and desirability was not significant, F1,207 = 78.97, p < 0.001, ps < 0.001).Measuring whether animalistic slurs alter perceptions of social desirability, there was a significant interaction between condition and desirability, F1,207 = 1.06, p = 0.305, Measuring whether animalistic slurs alter perceptions of humanness, the interaction between condition and humanness was not significant, F2071, = 56.36, p < 0.001, p = 0.561). However, ratings were higher overall for undesirable emotions that were shared with other animals than for uniquely human undesirable emotions (p < 0.001). Ratings were higher for undesirable than desirable emotions across both levels of humanness (both ps < 0.001).The theoretically uninteresting interaction between humanness and desirability was significant, Animalistic slurs change perceptions of a target's social desirability, but not of their humanness . The ove. 3.2.2M = 50.6, s.e. = 1.56) than in the control condition , t207 = 5.97, p < 0.001, d = 0.41.In line with previous theorizing, participants were more willing to endorse harm against the target group in the animalistic condition  a decrease in uniquely human emotion attributions; (2) an increase in attributions of emotions shared with other animals; (3) a decrease in desirable emotion attributions; (4) an increase in undesirable emotion attributions.. 3.2.4As for Study 1, to create a relative harm score representing the difference in harm endorsement for the animalistic compared with the control condition, we subtracted each participant's harm endorsement score for the control condition from their harm endorsement score for the animalistic condition.. 3.2.5Similar to Study 1, to create a relative humanness attribution score representing the difference in attribution of uniquely human emotions for the animalistic condition compared with the control, we created the mean of all uniquely human emotions for each participant for each condition, and we then subtracted the mean uniquely human emotions attribution score for the control condition from the mean uniquely human emotions attribution score for animalistic condition. This gave a score showing the difference in humanness attribution between the animalistic and control conditions. Positive numbers here represent a tendency for participants to believe targets compared to animals possess uniquely human emotions to a greater extent than the control, negative numbers indicate the reverse.We used the same method to create a relative score representing the difference in attribution of emotions shared with other animals for the animalistic condition compared with the control, where positive numbers represent a tendency for participants to believe targets compared to animals possess emotions shared with other animals to a greater extent than the control, and negative numbers indicate the reverse.We created a relative score representing the difference in attribution of desirable emotions for the animalistic condition compared with the control by creating a mean of the desirable emotions for each participant for each condition, and then subtracting the mean desirable emotion attribution score for the control condition from the mean desirable emotion attribution score for animalistic condition. Positive numbers here represent a tendency for participants to believe targets compared to animals possess desirable emotions to a greater extent than the control, negative numbers indicate the reverse. We used the same method to create a relative score representing the difference in attribution of undesirable emotions for the animalistic condition compared with the control, where positive numbers represent a tendency for participants to believe targets compared to animals possess undesirable emotions to a greater extent than the control, and negative numbers indicate the reverse. 1.Is the increase in harm for the animalistic condition relative to the control predicted by a decrease in uniquely human emotion attributions for the animalistic condition relative to the control? 2.Is the increase in harm for the animalistic condition relative to the control predicted by an increase in emotion attributions shared with other animals for the animalistic condition relative to the control? 3.Is the increase in harm for the animalistic condition relative to the control predicted by a decrease in desirable emotion attributions for the animalistic condition relative to the control? 4.Is the increase in harm for the animalistic condition relative to the control predicted by an increase in undesirable emotion attributions for the animalistic condition relative to the control?Note that it is again plausible we could see evidence for both accounts using this approach.We used these relative scores to test the predictions using four linear regressions.2 The final samples for each model were well powered to detect effects of interest. Full regression statistics are shown in  1.Is the increase in harm towards targets in the animalistic condition relative to the control predicted by a decrease in uniquely human emotion attributions for targets in the animalistic condition relative to the control?Assumptions of each of the four individual regression models were checked and influential scores were identified and removed using Cook's distance.Eleven data points fell outside of Cook's distance and were excluded, resulting in a sample of 197 for the first regression model.p = 0.766). This model explained less than 0.001% of the variance in relative harm scores. 2.Is the increase in harm towards targets in the animalistic condition relative to the control predicted by increased attributions of emotions shared with other animals for targets in the animalistic condition relative to the control?Fourteen data points fell outside of Cook's distance and were excluded, resulting in a sample of 194 for the second regression model.Our first linear regression showed that the increase in harm towards targets in the animalistic condition relative to the control was not predicted by reduced uniquely human emotion attributions to targets in the animalistic condition relative to the control , aniFurther supporting our central findings, in both studies, the increased harm endorsement to the target group brought about by the animalistic slurs was not predicted by perceptions that its members possessed uniquely human attributes to a lesser extent. Instead, increased endorsement of harm was predicted by perceptions that the target group possessed desirable attributes to a lesser extent and undesirable attributes to a greater extent.It is crucial to emphasize that we are not seeking to provide an exhaustive account of how animalistic slurs lead to harm. We focused on two different models of dehumanization—the dual model  and infrIn this work, we focused on how animalistic slurs influence attitudes towards novel political groups, and we focused on group-level differences across our two experimental conditions. However, some work has suggested important individual differences in the propensity to dehumanize others, such as political ideology and social status . It willOur measures of harm were procedural rather than relating to the endorsement of physical violence. While our work provides a basis for understanding this complex topic, future work could include measures of other types of harm endorsement such as physical harm along with incorporating, where ethically possible, behavioural measures of harm. Such work could help provide a bridge between laboratory-based research on subtle dehumanization, and philosophical and sociological research on dehumanization and extreme intergroup harm.It is also important to acknowledge that labelling a group of people as apes, dogs or cockroaches can be intended to degrade, shame and humiliate the target group themselves. This kind of language is likely to damage the psychological wellbeing of targets independently of the attitudes and behaviours it evokes in others, and may indeed feel dehumanizing . FurtherWe recognize that not all animal comparisons are equally offensive. Some animal comparisons may be more deeply offensive than others, and different animalistic comparisons may evoke different types of trait representations. For example, whereas referring to a group as ape-like may evoke stereotypes of stupidity, referring to a group as snake-like may evoke stereotypes of dishonesty and betrayal . The rolpost hoc justification for historical harm, are also important areas for further study.In this work, we examined the causal role of dehumanizing language in influencing beliefs about others and motivations for harm. Some thinkers have suggested that the role of dehumanizing language in violence may be better characterized as reinforcing social norms surrounding ongoing violence and justifying harms that have already been committed . The rolUnderstanding the specific ways in which animalistic slurs, commonly found in propaganda and hate speech, influence the cultural transmission of beliefs about others has important implications. Given historical links between comparisons to non-human animals and intergroup harm, along with the rising prevalence of dehumanizing hate speech online –39, accu


Background: Although the importance of walking for promoting a better cardiometabolic health is widely known (this includes both cardiovascular and metabolic/endocrine systems), there is little knowledge regarding its appropriate pace to provide adults with more cardiometabolic benefits. Aim: To analyze the associations between different walking pace categories and cardiometabolic health markers in the adult Chilean population. Methods: Cross-sectional study. A total of 5520 participants aged 15 to 90 years old from the Chilean National Health Survey (CNHS) 2016–2017 were included. Walking pace categories  were collected through self-reported methods. Glycaemia, glycosylated hemoglobin (HbA1c), gamma glutamyl transferase (GGT), vitamin D2, vitamin D3, systolic and diastolic blood pressure, and lipid profile  were determined using blood sample tests and measured with the standardized methods described in the CNHS 2016–2017. Results: People who had a brisk walking pace were associated with lower levels of glycaemia, HbA1c, GGT, systolic and diastolic blood pressure, and higher vitamin D3 levels compared with those with a slow walking pace. Moreover, people with a brisk walking pace had lower levels of VLDL cholesterol compared with those with a slow walking pace. However, after adjusting the model to include sociodemographic background, nutritional status, and lifestyle variables, the differences remained only for glycaemia, HbA1c and systolic blood pressure levels. Conclusions: A brisk walking pace was associated with better cardiometabolic health markers and lipid profile compared with a slow walking pace. Lifestyle changes and demographic and socioeconomic changes globally have been one of the causes of changes in epidemiological profiles of the population worldwide. They have also caused an increase in cardiovascular diseases . DiabeteIn populations with different ages  and undeThe scientific evidence establishes walking pace as a predictor of health status ,18. Howen = 6233) who took part in the CNHS 2016-2017, only (n = 5520) participants were available in the data to study outcomes and covariates, and they were included in all the analyses. The CNHS 2016–2017 was funded by the Chilean Ministry of Health and approved by the Ethics Research Committee of School of Medicine at the Pontificia Universidad Católica de Chile (code n°16-019). All participants provided written consent before participation [Non-experimental study, analytical and cross-sectional design. This is a secondary study from the CNHS 2016–2017. The CNHS 2016–2017 was conducted within Chilean households with participants aged from 15 to 90 years old. From the original simple size  and glycaemia levels from a blood sample, which was drawn by trained nurses after 11 h of fasting by participants. The results were classified according to the parameters proposed by the American Diabetes Association (ADA)—HbA1c: 5.7%: normal, HbA1c: 5.7–6.4%: pre-diabetes, HbA1c greater than 6.5%: T2D; and glycaemia: >100 to 125 mg/dL: pre-diabetes, glycemia: >126 mg/dL: diabetes) .Age, sex , age group , educational level , area of residence  were determined using the questionnaires of the CHNS 2016–2017 .Smoking habits, alcohol use (Alcohol Use Disorders Identification Test (AUDIT)), salt, fruit and vegetable intake, hours of sleep, self-perception of health, and personal wellbeing were also obtained using the questionnaires of the CHNS 2016–2017.The time allocated for PA related to commuting activities  and for PA with moderate or vigorous intensity during leisure and work were obtained using the GPAQ analysis guide  ,22. To eAdditionally, sedentary behavior was determined using the time (hours) allocated to activities that involve sitting or reclining during free time or work  ,24. ®) and height was measured with a height rod in participants’ homes. Participants did not wear shoes and were dressed in light clothing for both measurements. Weight and height measurements were both carried out by trained nurses or midwives using standardized methods. Nutritional status and body fat were determined according to body mass index (BMI) based on the WHO’s cut-off points: underweight: <18.5 kg/m2; normal weight: 18.5–24.9 kg/m2; overweight: 25.0–29.9 kg/m2; and obesity: ≥30.0 kg/m2. In addition, central obesity was defined as waist circumference (WC) ≥ 88 cm for women and ≥102 cm for men [Weight was measured using a digital scale . Then, the associations of walking pace categories with cardiometabolic health and lipid profile markers were investigated using linear regression analyses. Data were presented as mean scores with their 95% CI and β-coefficient (95% CI) per walking pace category (slow/average/brisk) and Delta (95% CI); ce group . p < 0.05. All statistical analyses were performed with STATA 15 software .All analyses were incrementally adjusted according to different confounding factors, and included four models: Model 0: unadjusted; Model 1: adjusted by sociodemographic factors: age, sex , education level (≤ 8 years/9–12 years/>12 years) and place of residence ; Model 2: adjusted by model 1 plus BMI; and Model 3: adjusted by Model 2 plus lifestyle factors . Statistically significant values were considered when A total of 17.9% of participants self-reported a slow walking pace, whereas 27.4% reported a brisk walking pace. Compared with brisk walkers, those who reported being slow walkers were older . Participants in the slow walking pace category were women (60.8 2%) and had a lower education level (36.8% had ≤8 years). Slow walkers reported consuming more salt (9.5 g/day) compared with average and brisk walkers. The rates of total PA, transport-related PA, moderate intensity of PA, and vigorous intensity of PA were lower in slow walkers. Additionally, slow walkers had a higher prevalence of physical inactivity, sedentary time, central obesity, and obesity status compared with brisk walkers .Associations between walking pace categories and cardiometabolic health markers are shown in p = 0.022), HbA1c ; p = 0.002) and systolic blood pressure ; p = 0.011) were observed for each increase in walking pace category. In addition, brisk walkers had lower levels of glycaemia (p = 0.049) and HbA1c (p = 0.002), and both average and brisk walkers had lower systolic blood pressure (0.006) compared with slow walkers ; Model 3, .For the unadjusted model, average and brisk walkers had lower levels of VLDL-C  compared with slow walkers. However, after adjusting Model 3, these differences were not maintained  and chanThe aim of this study was to analyze the association between different walking pace categories and cardiometabolic health markers in the adult Chilean population. The main results of this study indicated that people who had a brisk walking pace possessed lower levels of glycaemia, HbA1c, GGT, systolic and diastolic blood pressure, and higher levels of vitamin D3 compared with those who had a slow walking pace. In addition, walking pace was associated with lower levels of VLDL-C for participants with a slow walking pace. However, after adjusting the model for confounding factors—sociodemographic background, nutritional status, and lifestyle—the levels of glycaemia, HbA1c and systolic blood pressure were maintained.p = 0.022) and a lower concentration of HDL cholesterol compared with those who reported walking at a fast pace [p = 0.14; LDL-C 3.4 ± 0.5 vs. 3.7 ± 0.8 mmol/L, p = 0.22; and triglycerides 1.1 ± 0.5 vs. 1.5 ± 0.9 mmol/L, p = 0.12, respectively) [The associations identified between walking pace categories and blood glucose levels are consistent with existing evidence on this topic. Considering previous research, people who walk at a fast average pace have lower fasting glucose and HbA1c levels compared with slow walkers   . In addiast pace . Other pctively) .n = 191) participants with a follow-up of 30 years, which indicated that high systolic and diastolic BP is associated with a slower walking pace. It was concluded that exposure to higher BP levels from youth to middle age is associated with a slower walking pace in midlife [On the other hand, blood pressure was an indicator that presented changes when participants performed a fast walking pace. This is compared with a study of ( midlife . Moreove midlife . This ra midlife .This study reinforces the idea that a higher walking pace is associated with better cardiometabolic health and a better lipid profile ,32. In aIn addition, walking pace has been studied as a factor associated with severity and mortality in people affected by COVID-19. Indeed, it has been observed that people who had a slow walking pace presented a significantly higher risk of severe symptoms  and a hiOn the other hand, in practical terms, a walking pace assessment could be used by health professionals as a tool to identify patients who have a higher risk of contracting chronic non-communicable diseases . TherefoThe results of this study can be generalized to the Chilean population with more confidence than previous estimates due to the representativeness of the population sample. More importantly, this is the first study to report associations between walking pace and cardiometabolic health. However, it is not exempt from limitations. Firstly, self-reported data on walking pace were used due to a lack of objectively measured summary-level data, which might lead to a misclassification bias. However, self-reported walking pace is highly correlated with actual measured walking pace . WalkingRegardless of the different sociodemographic and lifestyle characteristics of this adult cohort, the Chilean National Health Survey revealed that the adult population who had a ‘brisk’ walking pace possessed lower levels of glycaemia, HbA1c and systolic blood pressure, showing a healthier profile overall. Further investigation is needed to thoroughly understand the associations between other physical-capability markers and health outcomes in Chile.


Background: Elucidation of the mechanism of ubiquitation has led to novel ways to treat glioblastoma (GBM). A tripartite motif (TRIM) protein mediates a reversible, stringent ubiquitation which is closely related to glioma malignancy. This study intends to screen the most vital and abnormal regulating component of the tripartite motif protein and to explore its underlying mechanisms.Methods: TRIM21 is identified as an important oncogene that accelerates the progression of glioma cell through database in a multidimensional way and this is confirmed in human samples and cells. Tandem Mass Tags (TMT) and MS analysis are performed to discover the substrates of TRIM21.The underlying mechanisms are further investigated by CO-IP, luciferase reporter assays and gain and loss of function assays. In vivo treatment with siRNA is applied to evaluate the therapeutic significance of TRIM21.Result: We screened a panel of TRIM proteins and identified TRIM21, a E3 ubiquitin-protein ligase and autoantigen, as well as a prognostic biomarker for GBM. Functionally, high expression of wild-type TRIM21 accelerates tumor progression in vitro and in vivo, whereas TRIM21 mutants, including one with a critical RING-finger deletion, do not. Mechanistically, TRIM21 stimulates K63-linked ubiquitination and subcellular translocation of active β-catenin from the cytoplasm to the nucleus. Moreover, TRIM21 forms a complex with the β-catenin upstream regulator, TIF1γ, in the nucleus and accelerated its degradation by inducing K48-linked ubiquitination at K5 site, consequently increasing further nuclear β-catenin presence. Endogenous TRIM21 levels are found to be inversely correlated with TIF1γ but positively correlated with β-catenin in glioma tissue microarray experiments. Furthermore, direct injection of TRIM21 small interfering RNA (siRNA) into U87 cell-derived tumors (in vivo treatment with siRNA) is proved to inhibit tumor growth in nude mice.Conclusion: This work suggests that TRIM21/TIF1γ/β-catenin axis is involved in the progression of human GBM. TRIM21 is a promising therapeutic and prognostic biomarker for glioma with hyperactive β-catenin. GBM is prevalent in adult brain cancer, characterized by its rapid growth, invasiveness and poor survival TRIM family members frequently emerge in many tumor types, ultimately affecting various tumor properties The tripartite-motif (TRIM) protein family contains approximately 80 members and represents one of the largest collections of E3 ubiquitin ligases. Structurally, these proteins featured an N-terminal TRIM motif that includes one RING-finger domain, one or two B box motifs, and a coiled-coil region The canonical Wnt signaling pathway often remains activated in GBM Of the TRIM proteins, TRIM21 is identified as a prognostic biomarker and a regulator of malignancy for GBM using public databases and clinical glioma specimens. Depending on the cancer type and the carcinogenesis effector, TRIM21 may change cancer progression, alternatively through increasing the ubiquitination of oncogenic or tumor suppressor proteins Recombinant human Wnt3a and Ubiquitin inhibitor MG132 were purchased from Med-Chem-Express . Cycloheximide (CHX) was got from Sigma-Aldrich . Anti-TRIM21 antibody (67136-1-Ig), Anti-C-MYC antibody (10828-1-AP) and Anti-GAPDH antibodies (60004-1-Ig) were acquired from Proteintech. Anti-HA antibody (#3724), Anti-TIF1γ antibody (#90051), Anti-Flag antibody (#2368), Anti-β-catenin antibody (#8480) and Anti-HIS (#8761) antibodies were obtained from Cell Signaling Technology , and Anti-Ki-67 (ab92742) antibody was got from Abcam. .All glioma tissue microarrays were purchased from Biochip , which were collected from 2008 to 2011. All patients were followed up for 5 years and clinic pathologic parameters were shown in http://gliovis.bioinfo.cnio.es/).The gene expression in human GBMs with follow-up information was analyzed using gene profiling data  from the TCGA database and the Rembrandt database (For the GEO database (GSE108474), TRIM21 expression and positively regulative Wnt signalling pathway score were calculated by GSTA algorithm. The DEG functional analyses were performed using the clusterProfiler and ggplot2 R packages, with P < 0.05 considered statistically significant.The tissue microarray was deparaffinized, hydrated and incubated with rabbit monoclonal anti-TRIM21  and rabbit polyclonal anti-TIF1γ , anti-β-catenin , anti-IDH1-R132H (MAB-#0062) antibodies respectively at 4 °C overnight, followed by subsequent incubation for 1 h with goat anti-rabbit IgG-HRP for detection. DAB  was used as a chromogen. We followed a previously described protocol to quantify staining intensity Primary GBM cells (GBM-1) were isolated from human GBM specimens as previously described Plasmid constructs for ectopic expression of full-length TRIM21 pcDNA3.1-HIS-TRIM21-FL; a RING-finger domain deletion mutant of TRIM21 (pcDNA3.1-HIS-TRIM21-ΔRING) and other TRIM21-mutants were purchased from Sino Biological (Beijing). Additionally, the expression vectors encoding pcDNA3.1-FLAG-TIF1γ, and pcDNA3.1-FLAG-TIF1γ-mutants , other FLAG-TIF1γ- domain deletion, pcDNA3.1-β-catenin, and pcDNA3.1-S33Y-β-catenin, pcDNA3.1-K354R-β-catenin, other β-catenin - domain deletion mutants HA-UB, His-UB and His-UB-mutants were also generated and purchased from Sino Biological , SMARTpool siRNA duplexes specific for TIF1γ, LAMC2 and a nontargeting siRNA (siControl) were purchased from RiboBio. The sequences of siRNA were as follows:siTIF1γ-1 GGAAGATGCTGGCTAAGT; siTIF1γ-2: GCCAGATATTCCACCATA; siLAMC1-1: GCAAGCGAGTGTATGAAGA; siLAMC1-2: GCAAGCAG-GTGTTGTTGAGTTA. siTRIM21: 5'-GAUGGUGUCUGCUAUUGUATT-3'. HEK 293T, U87-MG and U251-MG cells were transfected with siRNA or plasmid using Lipo 3000 .R443W-HA, TIF1γ-Flag cDNA was cloned into pLOV-CMV-eGFP-EF1a-PuroR lentiviral vector . Lentiviral particles containing TRIM21-HA and TIF1γ-Flag were packaged by Helper 1.0. Cells with stable TRIM21 or/and TIF1γ. To generate stable TRIM21 knockdown GBM cells, U87-MG and GBM-1 cells (1×106 /well) were transfected with lentiviral vector  carrying self-complementary hairpin DNA fragments that could generate TRIM21-specific shRNA, or scrambled RNA (scramble). The list of shRNA was shown as follows: Scramble: 5'-TTCTCCGAACGTGTCACGT-3'; shTRIM21-1: 5'-TGGCATGGTCTCCTTCTACAA-3'; shTRIM21-2: 5'-GAGTTGGCTGAGAAGTT'GGAA-3'; shTRIM21-3: 5'-CTGCCTTCTTTATGGGACTTA-3'. The cells were treated overnight with the medium containing retrovirus or lentivirus harvested 72 h after transfection. Selection of stable clones was carried out using puromycin.For overexpression of TRIM21-HA, a R443W mutant of TRIM21-HA, TIF1γ-Flag in GBM cells, the TRIM21-HA, TRIM21Cytoplasmic and nuclear fractions were extracted from cells using a Minute™ Cytoplasmic and Nuclear Extraction Kit , according to the manufacturer's instructions.qPCR was conducted as the previous study. The sequences of the PCR primers were as follows: β-catenin forward, 5'-AGGAATGAAGGTGTGGCGACA-3'; β-catenin reverse, 5'-TGGCAGCCCATCAACTGGAT-3'; GAPDH forward, 5-AATCCCATCA CCATCTTCCA-3; GAPDH reverse, 5'-TGGACTCCACGACGTACTCA-3'; TIF1γ Forward 5'-AGCAACGGCGACATCCA-3; TIF1γ reverse 5'-CCAGCCCTCCTAGAGC -3'.For immunoblotting, the cells were lysed with 300 μL RIPA lysis buffer containing a protease and phosphatase inhibitor cocktail (Thermo Fisher) at various time points and protein concentrations were detected using the BCA Protein Assay Kit . Total proteins  were then separated by 8% or 10% SDS-PAGE , transferred using a 0.22-μm polyvinylidene fluoride (PVDF) filter (Millipore) and blocked with blocking solution . The PVDF filter was incubated with 1:1000 rabbit anti-TRIM21 (Proteintech), 1:1000 rabbit anti-TIF1γ , 1:1000 rabbit anti-β-catenin , 1:1000 rabbit anti-Cmyc (Proteintech), 1:1000 rabbit anti-Flag , 1:1000 rabbit anti-HA , 1:1000 rabbit anti-HIS , and 1:1000 mouse anti-GAPDH (Proteintech) overnight at 4 °C. After washing with TBST, membranes were incubated with appropriate HRP-conjugated secondary antibodies (1:10000) for 1 h at the room temperature, and then washed with TBST three times and visualized by chemiluminescent detection, then the densitometric values were determined by a gel image analysis system .For immunoprecipitation, cells were grown in 6-well plates and transfected with the appropriate plasmids, which was extracted by cell lysis buffer for western and IP  with protease inhibitors. IP lysates was were captured with the appropriate anti-Flag M2 magnetic beads , TIF1γ for 1 h at 4°C according to the manufacturer's instructions. After washing three times with equilibrium buffer , the beads were boiled with SDS-PAGE loading buffer for 10 min. The total cell lysates (input) were loaded and separated by 10% SDS-PAGE, after that, the immunoprecipitates were eluted, neutralized, and SDS degenerated for further immunoblotting.To detect TIF1γ or β-catenin ubiquitination, 293T cells or U87-MG cells were transfected with HA-Ub (ubiquitin) or HA-Ub mutants and indicated vectors, pretreated with MG132 for 4 h. Whole-cell lysates were collected using by  and incubated at 95 °C for 5 min. After that, 900 μl Tris-HCl buffer  were added, sonicated. and centrifugated, the cell lysates were subjected to immunoprecipitation.2 and 2 mM DTT), containing purified Flag-β-catenin, UBE1 , UbcH13/Uev1a , His-ubiquitin and TRIM21 protein or IgG. The reaction mixtures were heated and then diluted with buffer  For the purification of ubiquitinated β-catenin using Ni-NTA beads (Qiagen). The eluted proteins were analysed by immunoblotting.In vitro ubiquitination of β-catenin was performed at 37 °C for 60 min in 50 μl reaction buffer  as variable modifications. The remaining mixture for each group of TMT experiment was fractionated using high pH reverse phase chromatography into 60 fractions and further concatenated into 20 fractions. Each fraction was vacuum-dried and stored at -80 °C until MS analysis. For the liquid chromatography-MS analysis, the gel pieces with TRIM21-FLAG immunoprecipitated complex or control were dehydrated in acetonitrile, dried in a speed vacuum and digested with trypsin. The peptides were extracted from the polyacrylamide and were evaporated for MS analysis using LTQ-Orbitrap Elite Mass Spectrometer System . TMT and MS analysis was finished by Jinkairui Biological Engineering company in WuHan. GO pathway enrichment analysis were performed using Dr. Tom, an online analysis system of BGI. The images of Venn diagram, and heatmap plots were performed using the OmicStudio tools at an open website (https://www.omicstudio.cn). Fold change > 2.0 and p < 0.05 were the cut off.For Tandem Mass Tags (TMT), TMT labeling was performed according to manufacturer's instructions The plasmids for GST-His-TIF1γ and His-tagged β-catenin were transfected into E. coli. Crude bacterial lysates were then prepared by sonication in ice-cold PBS in the presence of a protease inhibitor mixture. The in vitro transcription and translation experiments were performed with rabbit reticulocyte lysate . Approximately 100 µg GST- His-TIF1γ fusion protein was immobilized in 50 µL of glutathione agarose and equilibrated before being incubatedtogether at 4 °C for 60 min with gentle rocking motion. His-tagged β-catenin and/or His-tagged TRIM21 (MCE HY-P71791) were added to the immobilized GST-His-TIF1γ and incubated overnight at 4 °C under gentle rotation. The pull-down samples were analysed by immunoblotting.U87-MG cells were transfected with the TOP-FLASH or FOP-FLASH reporter plasmids together with pRL-TK (Beyotime) using lipo-3000 respectively for 24 h. Luciferase activity was measured with the Dual-Luciferases Reporter Assay kit (Beyotime) according to manufacturer's protocols after transfection. It was detected using the Dual-Luciferase® Reporter Assay System .The growth of GBM cells were measured using BeyoClick™ EdU Cell Proliferation Kit with TMB , according to the manufacturer's instructions. Cells were then examined and counted under Fluorescence microscope.3 cells per well were cultured in 96-well plates and then detected using Cell Counting Kit-8  reagent by measuring the absorbance at 450 nm.For CCK8 assay, 1×10A wound-healing assay and transwell Invasion assay were carried to examine the mobility and invasion of cancer cell respectively, as previously described Cells were fixed with 4% buffered paraformaldehyde and permeabilized with 0.5% Triton X-100 for 3 min. Cells were incubated with the primary antibody overnight at 4 °C and then incubated with fluorescent secondary antibodies and DAPI at 37 °C Images were observed using a confocal microscope .5) with pLVX -linker-luciferase lentivirus transfected were injected intracranially into the frontal lobes of 5-week-oldfemale NOD-SCID mice (n = 5 per group) as previously described U87-MG (1×10 6) suspended in 100 μl of PBS were subcutaneously injected into the dorsal surfaces of 5-week-old nude mice that had been previously anesthetized. Ten days after implantation, tumors were treated with siNC or siTRIM21 together with atelocollagen  to facilitate siRNA introduction into tumors. Briefly, A 200 μl volume of siRNA solution (30 μmol/L in 0.5% (v/v) atelocollagen) was injected directly the base of each tumor. The animal experiments were approved by the Ethics Committee of Third Military Medical University.For in vivo siRNA treatment U87-MG cells  was significantly up-regulated or down-regulated in GBM compared to normal brain samples. Secondly, the particular TRIM expression change was significantly correlated with overall survival (OS) of GBM patients. Based on these guidelines, TRIM21 and TRIM48 were identified as candidate cancer-relevant TRIM genes from our database screen Figure A-B. To f(P < 0.05), Grade II (P < 0.05), Grade I (P < 0.01) or Normal brain samples  with TRIM21 depleted were established via lentiviral particle transfection Figure A. GBM ce and one as full-length (FL) and then assessed biological consequences following transfection into U87-MG or U251-MG Figure C. InvasiTRIM21 cell  conducted on GEO database, genes associated with positive regulation of the WNT signaling pathway were enriched in TRIM21-high tissue samples relative to TRIM21-low tissue samples Figure A. As shol Figure B. Then, l Figure A. Converl Figure B. Moreovl Figure E. Similal Figure C-3D. ThuTo explore the biological significance of the TRIM21-mediated Wnt/β-catenin, the activation T-cell factor/β-catenin transcription assays was further assessed. The transcriptional activity of β-catenin was up-regulated upon overexpression of TRIM21-FL, a cellular phenotype not observed with TRIM21-ΔRING E. In thein vivo  and found that the K5 and K1115 may have been ubiquitylated  results showed that the R443W mutation abolished the interaction between TRIM21 and TIF1γ  and progression-free survival (PFS) as compared with others and TRIM21-low and β-catenin-low group . Next, control or TRIM21 siRNA was mixed with atelocollagen and injected in tumor every day. After ten days, the nude mice were sacrificed. Such in vivo treatment with TRIM21 siRNA reduced the volumes and weights of the tumors , encodes for a ubiquitously expressed protein known as RING dependent E3 ligase that can be detected in the cell cytoplasm and nucleus Studies indicated that TRIM21 ubiquitinates both itself and TRIM5a through its ligase activity, yet does not facilitate proteasomal degradation The β-catenin pathway is one of the most commonly activated and mutated in GBM. TRIM21 is essential for tumor growth and invasion of GBM cells and its upregulation may correlate with β-catenin activation. These results indicate a potential use of TRIM21 as a drug target and a prognostic marker for GBM driven by β-catenin hyper-activation.Supplementary figures and tables.Click here for additional data file.


A subset of triple-negative breast cancers (TNBCs) have homologous recombination deficiency with upregulation of compensatory DNA repair pathways. PIKTOR, a combination of TAK-228 (TORC1/2 inhibitor) and TAK-117 (PI3Kα inhibitor), is hypothesized to increase genomic instability and increase DNA damage repair (DDR) deficiency, leading to increased sensitivity to DNA-damaging chemotherapy and to immune checkpoint blockade inhibitors.2 plus nab paclitaxel 220 mg/m2 every 3 weeks for up to 6 cycles. Patients received subsequent treatment with pembrolizumab and/or chemotherapy. Primary endpoints were objective response rate with cisplatin/nab paclitaxel and safety. Biopsies of a metastatic lesion were collected prior to and at PD on PIKTOR. Whole exome and RNA-sequencing and reverse phase protein arrays (RPPA) were used to phenotype tumors pre- and post-PIKTOR for alterations in DDR, proliferation, and immune response.10 metastatic TNBC patients received 4 mg TAK-228 and 200 mg TAK-117 (PIKTOR) orally each day for 3 days followed by 4 days off, weekly, until disease progression (PD), followed by intravenous cisplatin 75 mg/m≥ 6 months) and continued to have durable benefit in progression-free survival with pembrolizumab post-cis/nab pac for 1.2, 2, and 3.6 years. Their post-PIKTOR metastatic tissue displayed decreased mismatch repair (MMR), increased tumor mutation burden, and significantly lower levels of 53BP1, DAG Lipase β, GCN2, AKT Ser473, and PKCzeta Thr410/403 compared to pre-PIKTOR tumor tissue.With cisplatin/nab paclitaxel (cis/nab pac) therapy post PIKTOR, 3 patients had clinical benefit  and 2 stable disease (SD) Priming patients’ chemotherapy-pretreated metastatic TNBC with PIKTOR led to very prolonged response/disease control with subsequent cis/nab pac, followed by pembrolizumab, in 3 of 10 treated patients. Our multi-omics approach revealed a higher number of genomic alterations, reductions in MMR, and alterations in immune and stress response pathways post-PIKTOR in patients who had durable responses.This clinical trial was registered on June 21, 2017, at ClinicalTrials.gov using identifier NCT03193853.The online version contains supplementary material available at 10.1186/s40364-023-00511-7. A subset of triple-negative breast cancers (TNBCs) have homologous recombination deficiency with upregulation of compensatory DNA repair pathways. We observed 3 patients with pretreated metastatic TNBC that had prolonged progression-free survival > 1 year with the immune checkpoint inhibitor, pembrolizumab, following sequential treatment with PIKTOR followed by cis/nab pac. These patients tended to have higher copy number alterations and/or tumor mutation burden in their metastatic disease after PIKTOR treatment, loss of DNA damage signatures, and increased expression of PD-1/PD-L1 pathway genes, with significant decreases in DNA damage response, stress and proliferation proteins. Their metastatic lymph node disease may have been primed or altered by the antecedent PIKTOR and/or cis/nab pac therapy. The results should be interpreted prudently due to the small sample size. However, this proof of concept study supports pursing larger, multi-site studies for PI3K and TORC1/2 and immune checkpoint blockade in metastatic TNBC.Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype characterized by high mutational burden and high proliferation . Up to 7Fanconi Anemia (FA) genes [TP53 mutation [PIK3CA, AKT1, and mTOR are frequent in TNBC [HRD can occur through BRCA1/2 mutation, methylation/silencing of A) genes , loss ofA) genes , loss ofA) genes , TP53 mumutation , and/or mutation . TNBC ismutation , 10. NHEmutation . A key nmutation . Further in TNBC , 14, and in TNBC ). Loss o in TNBC .Serine/threonine kinase mechanistic target of rapamycin (mTOR) is a downstream effector of the PI3K pathway and key component of two protein complexes, mTORC1 and mTORC2, which have distinct cellular functions. In preclinical studies, the dual inhibition of mTORC1 and mTORC2 decreased DDR and also decreased the activity of AKT . This du50s have been shown to reduce PI3K/AKT/mTOR (PAM) pathway activation, activate autophagy, and induce cell cycle arrest [TAK-228 (formerly INK128 and MLN0128) is an investigational, highly selective, orally bioavailable adenosine 5’ triphosphate (ATP)-competitive inhibitor of mTOR. TAK-228 targets both mTORC1 and mTORC2. TAK-117 (formerly MLN1117/INK1117) is an investigational, orally available, selective small molecule inhibitor of the Class I phosphoinositide 3-kinase (PI3K) alpha isoform (PI3Kα). This combination, referred to as “PIKTOR”, is hypothesized to achieve greater inhibition of the PI3K/AKT pathway than either agent alone . Indeed,e arrest . Inhibite arrest . Dual AKe arrest . Successe arrest .Several preclinical studies have shown that a variety of dual PI3K/mTOR inhibitors are synergistic with cisplatin in triple-negative breast cancer preclinical models –30. One PI3K inhibitors have also demonstrated reduced PD-L1 expression in tumors in triple-negative breast cancer, allowing enhanced detection by CD8 + T-cells . A recenWe investigated genomic and proteomic alterations in metastatic tissues for patients with mTNBC treated with the combination of TAK-228 and TAK-117 (PIKTOR) followed by cisplatin and nab paclitaxel (cis/nab pac) chemotherapy. This study evaluated whether PIKTOR increases genomic instability and increases DDR deficiency in patients’ metastatic tissue, leading to increased sensitivity to DNA damaging chemotherapy and immune checkpoint inhibitor therapy. We observed in our study that 3 patients with pretreated metastatic TNBC had prolonged progression-free survival > 1 year with the immune checkpoint inhibitor, pembrolizumab, following sequential treatment with PIKTOR followed by cis/nab pac. These patients tended to have higher copy number alterations and/or tumor mutation burden in their metastatic disease after PIKTOR treatment, loss of DNA damage repair deficiency signatures, and increased expression of PD-1/PD-L1 pathway genes. These 3 patients also had significantly lower levels of 5 proteins involved in DNA damage response, stress response, and proliferation.Following Baylor University Medical Center IRB-approved informed consent, 10 female patients aged ≥ 18 years with metastatic TNBC were treated with PIKTOR, then with cis/nab pac at disease progression in this pilot, proof-of-concept trial. Key eligibility criteria included no more than three prior chemotherapy regimens for metastatic disease, ECOG PS 0–2, and metastatic disease amenable to core needle biopsy, and adequate hematologic, liver, and renal function.2 cisplatin (cis) plus 175–200 mg/m2 nab paclitaxel (nab pac) IV every 3 weeks until progression of disease (PD) or for a maximum of 6 cycles. Patients were then treated with pembrolizumab, alone or in combination with chemotherapy, regardless of PD-L1 status, or with chemotherapy or targeted therapy if not a candidate for immunotherapy based on disease course , and was carried out in accordance with the principles of Good Clinical Practice and the Declaration of Helsinki. Patients received 4 mg TAK-228 PO and 200 mg TAK-117 PO (PIKTOR) both QD for 3 days on, followed by 4 days off, weekly until disease progression (PD), followed by 75 mg/m93853, anBlood samples and a research biopsy of a metastatic lesion were collected prior to initiation of PIKTOR and again upon disease progression on PIKTOR. Blood samples were collected in 10mL purple-top EDTA hematology tubes, processed within 1 h into plasma and buffy coat, and stored at -80 °C. Buffy coat was used for germline whole exome sequencing as described below. Biopsies were snap frozen in a cryovial by submerging into liquid nitrogen and stored at -80 °C prior to analysis with whole exome sequencing, RNA sequencing, and proteomics as described below. Patient demographics and tumor characteristics are summarized in Table The primary objectives of this pilot clinical trial were to determine the objective response rate and safety associated with cis/nab pac following PIKTOR therapy. Secondary objectives were to determine duration of response and to assess mTNBC tissues obtained pre- and post-PIKTOR for homologous recombination proficiency and deficiency using next-generation sequencing and reverse phase protein array.Fresh frozen tumor biopsies were disrupted and homogenized with BulletBlender Gold tissue homogenizer (Next Advance) and divided for DNA and RNA extraction using DNeasy Blood & Tissue kit (Qiagen) and RNeasy kit (Qiagen), respectively, per manufacturer’s protocols. DNA was eluted into Qiagen’s AE buffer, and RNA was eluted into water.Isolated DNA (200ng) was used to generate libraries for whole exome sequencing. DNA was fragmented to target peaks of 200 bp by sonication on a Covaris E220. DNA samples were prepared for next generation exome sequencing with SureSelect XT (Agilent), according to manufacturer’s protocol with the following modifications: Library amplification conditions: initial denaturation at 98 °C for 2 min, 8 cycles of 98 °C for 30 s, 60 °C for 30 s, and 72 °C for 60 s, then final extension at 72 °C for 5 min. Whole exome libraries were captured using Agilent SureSelect XT v7. The samples were sequenced on a NovaSeq6000  to an average depth of 352x ± 67x coverage.Isolated RNA  was used to generate libraries for RNA-seq. RNA samples were prepared for next generation sequencing with KAPA stranded RNA HyperPrep Kit with RiboErase (Roche) with KAPA Unique Dual Index adapters (Roche), as per manufacturer’s protocol with the following modifications: fragmentation at 94 °C for 6 min; 10 cycles of library amplification; purifications with AMPure XP beads (Beckman Coulter Genomics). The libraries were sequenced on a single lane on a NovaSeq6000  to an average total reads of 1.94E + 08 ± 0.84E + 08 reads.https://github.com/tgen/phoenix). BCL files were converted to FASTQs with bcl2fastq2 Conversion Software (Illumina). DNA FASTQs were aligned to the human reference genome (GRCh38) with BWA v0.7.17. Duplicates were marked using Samtools v1.10 markdup. BAMs were used for the identification of somatic variants , structural variants (SVs), and copy number variants (CNVs). Variant calling was performed using Strelka2 v2.9.10, Lancet v1.1.0, GATK v4.1.8.0 Mutect2, VarDictJava 1.7.0, and Octopus v0.603-beta. Final somatic SNVs were called by at least 2 out of 5 callers. CNVs were predicted with GATK v4.1.8.0 CNV. SVs were predicted using Manta v1.6.0 and Pairoscope 0.4.2. Somatic variants, SVs, and CNVs were annotated using Ensemble v98, then filtered by removing variants predicted to have no protein coding sequence consequence, as well as removal of genes flagged as LOWQC (https://github.com/tgen/GemDb/wiki/Filtering). Where known oncogenes and tumor suppressor genes are reported, variants were annotated against Catalog of Somatic Mutations in Cancer (COSMIC) gene list (v82) and filtered if gene does not occur in COSMIC database. cBioPortal’s Oncoprinter was used to generate oncoprint plots. Variant calls were confirmed by visual inspection of BAM and SEG files in Integrative Genomics Viewer v2.8.9. DNA damage repair gene list was generated using gene ontology terms for “DNA repair”, “chromatin remodeling”, and “methyltransferase”. Full list of genes is in Supplemental Table 1.Primary analysis was performed using the Translational Genomics Research Institute (TGen) Jetstream pipeline Phoenix . BCL files were converted to FASTQs with bcl2fastq2 Conversion Software (Illumina). RNA FASTQs were aligned using STAR v2.7.5a. Gene expression estimates were performed using Salmon v1.2.1  and STAR v2.7.5a GeneCounts quantMode / HTSeq v0.12.3 (for counts). DESeq2 v1.34.0 was used to determine differential gene expression changes between the specified groups using sequencing batch and patient ID as covariates. Results from all protein coding genes from DESeq2 results were analyzed with the use of QIAGEN IPA , which was run with the following settings: log2FoldChange cutoff of +/- 1.2, p-value cutoff of 0.05, Ingenuity Knowledge Base (Genes Only) reference set. Canonical Pathway results from IPA were generated using default settings, and pathways where a Z-score could not be calculated were filtered out of analysis. Common pathway grouping  were manually curated.Primary analysis was performed using the Translational Genomics Research Institute (TGen) Jetstream pipeline Phoenix  compound and sectioned (8 μm) onto plain glass microscope slides. Histomorphology was assessed with hematoxylin-eosin (H&E) staining following standard protocols .Tumor and stromal cells were isolated as separate enriched cell populations using LCM (ArcturusXT or PixCell IIe instruments) in infrared capture mode as previously described . Frozen RPPA were constructed with microdissected breast tissue lysates diluted to 0.25 µg/mL, commercial cell line lysates, and bovine serum albumin  –38. LysaImmunostaining was performed on a Dako Autostainer per manufacturer’s instructions  , 40. Eachttp://capmm.gmu.edu/rpma-analysis-suite) was used to quantify and normalize the relative intensity value to the total protein/spot [Spot (pixel) intensity with adjusted background correction was analyzed using ImageQuant v5.2 (Molecular Dynamic) , 39. Datein/spot .Statistical significance was calculated using the Mann-Whitney test with the Holm-Bonferroni method to correct for multiple comparisons. Mean comparisons were performed using Wilcoxon Rank Sum due to small sample size. Potentially significant variables were selected based on non-corrected p-values. A p-value < 0.05 was used to indicate statistical significance. Heatmaps were created using unsupervised two-way hierarchical clustering (RStudio). Correlograms were prepared by calculating Spearman correlations between all protein endpoints for the indicated group of samples. All statistical calculations were performed using R 4.1.0 . Violin Between July 2017 and December 2018, a planned 10 patients with metastatic TNBC were enrolled from a single site to receive PIKTOR with subsequent cis/nab pac chemotherapy at disease progression ; the 3 patients considered durable “responders” had a median time on PIKTOR of 11 weeks (range: 7–14 weeks) and the 7 patients who did not show clinical benefit had a median time on PIKTOR of 7 weeks (range: 3–14 weeks). The median time between previous platinum/taxane exposure and study cis/nab pac for all patients was 58.5 weeks (range: 19–163 weeks) with a median time for the 3 durable “responders” of 101 weeks (range: 19–134 weeks) and a median time for the 7 “non-responders” of 48 weeks (range: 19–163 weeks). The median time for all patients on cis/nab pac was 8 weeks (range: 3–18 weeks). PIKTOR administration was generally well tolerated. PIKTOR-related adverse events (AEs) experienced in ≥ 30% of patients included: fatigue (90%); nausea (80%), diarrhea (60%), vomiting (40%), stomatitis (40%), hyperglycemia (30%), rash (30%), cough (30%), and chest pain (30%). Incidence and grade of cis/nab pac-related AEs were as expected and were not obviously increased or decreased post-PIKTOR therapy .≥ 6 months, 1 patient had SD for less than 6 months, and 6 patients had disease progression as best response (PD). The objective response rate was 10% and the clinical benefit rate was 30%. Three of 10 patients , each of whom had carboplatin-pretreated disease metastatic to lymph nodes, as well as in bone (n = 1), and whose pre-PIKTOR tumor biopsies were PD-L1-negative by IHC (n = 2) or PD-L1-positive (n = 1), had durable SD on single agent pembrolizumab following PIKTOR and cis/nab pac therapy for 106, 190 and 65 weeks, respectively. These patients were considered durable “responders” for the purpose of biomarker exploration in this study , 2 patients had stable disease (SD) TP53 mutations were found in all 10 patients. No COSMIC oncogenes or tumor suppressors were unique to or were consistently mutated in the responders’ tumor tissues. PTEN, LIFR, and CREBBP alterations were found only in non-responders.The 3 patients 1,6,8) who had prolonged response to single agent pembrolizumab following PIKTOR and cis/nab pac therapy were considered responders. Their tumor and pre-treatment characteristics are summarized in Table ,6,8 who To determine the effect of PIKTOR treatment on transcription, we performed differential expression analysis on pre- and post-PIKTOR biopsies . When the entire cohort of 10 patients was analyzed together, only 3 genes were significantly differentially expressed between pre- and post-PIKTOR biopsies: PKHD1L1, COL4A3, and DERL3 and each was significantly decreased. We further assessed cellular pathway alterations using Ingenuity Pathway Analysis (IPA), and similarly found that one pathway, GP6 signaling, had a p-value < 0.05, attributable to changes in expression of collagen genes after PIKTOR treatment (data not shown).To determine if specific pathways correlated with potential immune response priming with PIKTOR treatment, we separately analyzed responders and non-responders. With this we were able to detect many more statistically significant differential expression changes . For pathway analysis, we focused on patients whose pre- and post-PIKTOR biopsies were obtained from lymph nodes (N = 6), as this was the most common biopsy site, which avoided pathway signature expression differences due to different metastatic organ sites. Pathways related to the biosynthesis of PI3K pathway substrates or signaling of PI3K/AKT/mTOR did not pass our p-value filter but were detected in the IPA analysis  post-PIKTOR indicating functional suppression of signaling by PIKTOR . Considering the small patient sample size (n = 10), we evaluated statistical significance without multiple comparisons correction to determine possible trends within the data that may highlight protein endpoints for further analysis. Protein levels pre- and post-PIKTOR were compared for all metastatic samples for both lung and lymph node metastatic sties. The post-PIKTOR samples revealed overall increased protein levels for Androgen Receptor (AR) (p < 0.05), AMPKα Thr172 p < 0.037), EGFR Thr654 (p = 0.004), Estrogen Receptor alpha (ERα) Ser118 (p = 0.014), Retinoblastoma (Rb) (p = 0.009), and General Control Non-depressible 2 (GCN2) (p = 0.002) . Unsupervised hierarchical clustering of PI3K/AKT/mTOR signaling nodes . Further analysis of only the microdissected tumor cells metastatic to lymph nodes (n = 6) showed higher levels of stress and immune signaling proteins  . Overall, mutation status of 22 known cancer genes changed between pre- and post-PIKTOR biopsies, occurring in 5 of 10 patients. We did not detect definitive changes that might explain the TMB and copy number alterations observed .Patients’ tumors may have differential response to PIKTOR treatment based on either baseline or acquired alterations in DDR deficiency. Using mutation signature analysis, genomic signatures of DDR including homologous recombination (HR), APOBEC, mismatch repair (MMR), and DNA proofreading were assessed Fig. A. The moTP53 mutations in both pre- and post-PIKTOR biopsies. No known inactivating mutations in DDR genes were observed in patients’ biopsy samples except for patient 1 whose cancer harbored a germline frameshift mutation in BRCA1 (data not shown) without loss of heterozygosity, suggesting at least partial HR proficiency.We also examined how DDR genes themselves may have been altered either at baseline or following PIKTOR treatment by examining somatic variants and copy number alterations Fig. B includi2FC = -3.00), a homologous recombination repair gene, following PIKTOR treatment, which was not observed in non-responders. Interestingly, global changes in gene expression in DDR pathways were largely absent in our analysis of the pre- and post-PIKTOR tissues . Given the loss of MMR deficiency signatures in the 3 responders, we looked specifically at changes in gene expression of 22 MMR genes [Only a few DDR genes were amongst the differentially expressed genes in our RNA-seq analyses . The 3 responders had a statistically significant decrease in ZNF365 expression . The commonality among the 3 responders is a decrease in CD45 and increase in Lck Y505 protein levels post PIKTOR. CD45 activates lymphocytes by dephosphorylating Lck Y505 . This paThe DNA damage repair response was heterogeneous among our responder and non-responder groups. We therefore sought to determine if any of the protein biomarkers could potentially be used to identify responders and non-responders. We performed a statistical comparison of all protein levels for all lung and lymph node metastatic specimens (n = 10). Higher expression of DAG Lipaseβ (p < 0.05) and GCN2 (p < 0.05) were found among the non-responder cohort (n = 7) compared to the responder cohort (n = 3) Fig. C. DAG Lip = 0.048).To decipher specific proteins that could potentially be used as biomarkers for likelihood of response to immune checkpoint inhibitors, we compared protein levels only for the patients who received pembrolizumab . GlucocWe found a set of 5 proteins that were significantly lower following PIKTOR in the patients who had a durable response to pembroluzimab Fig. B. 53BP1,PIK3CA mutation or a germline PALB2 mutation [PIK3CA mutation in their pre-PIKTOR biopsies, and patient 1 had a germline BRCA1 mutation, although this PARP inhibitor-pretreated patient’s pre- and post-PIKTOR biopsies did not demonstrate somatic BRCA1 loss of heterozygosity.The goals of this pilot trial were to examine the safety and efficacy of combined PIK3CA and TORC1/2 inhibition with PIKTOR, followed by cis/nab pac chemotherapy in patients with metastatic TNBC, and to investigate whether dual inhibition of the PI3K pathway would increase DDR deficiency and tumor immunogenicity. Interestingly, 3 of the 10 patients benefited durably with prolonged response/stable disease with cis/nab pac  followed by single agent pembrolizumab. These 3 patients had platinum-pretreated, nodal-dominant metastatic TNBC , two PD-L1 negative and one PD-L1 positive, and would not have been likely to have a durable response to chemotherapy nor to pembrolizumab. A recent trial of the mTOR inhibitor, everolimus, in combination with cisplatin given preoperatively to TNBC patients with residual disease following preoperative anthracycline/taxane showed responses to therapy in patients whose cancers had a mutation . None ofPreclinical studies have demonstrated that PI3K inhibition can enhance antitumor immunity and susceptibility of TNBC to immune checkpoint inhibition , 57. PI3The underlying premise for the trial was that PIKTOR would sensitize TNBC to subsequent DNA damage-inducing therapy by impairing DDR pathways. We calculated tumor mutation burden and fraction of copy number altered genome and observed increases in both measures post-PIKTOR in the responders, consistent with this hypothesis. Mismatch repair deficiency signatures were lost in the post-PIKTOR biopsies from all three responders, compared with none of the non-responders, signifying loss of mismatch repair deficiency. However, we cannot exclude two possibilities: clonal heterogeneity based on sampling variation within the metastatic lymph nodes, and/or that the observed increase in TMB in the responders’ tissues post-PIKTOR may have affected ascertainment of the MMR deficiency signatures, though most other signatures were concordant. We did not observe genomic alterations in DDR genes in responders that could explain the loss of the MMR deficiency signature and increased TMB post-PIKTOR. We may have expected HRD signatures to change more, particularly in the responders, but that was not observed. However, we did see some evidence of change to components of the HR pathway, including strong decreases in ZNF365 expression in responders only after PIKTOR treatment. It is thus possible that signatures of DDR deficiency are complex and masked by the simplification of DDR signatures to common DNA mutation patterns. A further limitation to evaluating these factors is the timing of biopsies, where further pressure from DNA damaging cis/nab pac may have exposed more DNA repair deficiency. However, to avoid complications analyzing potentially necrotic tissue post-cis/nab pac, we opted to do the second biopsy following PIKTOR treatment.The three patients who responded durably to single agent pembrolizumab after PIKTOR followed by cis/nab pac therapy had high tumor mutational burden in their post-PIKTOR biopsies, a known predictor of benefit from pembrolizumab in metastatic TNBC patients , 59. PatFunctional proteomic analysis of immune and inflammation pathways showed changes in regulators of immune cell activation. CD45 is a positive regulator of T cell antigen receptor (TCR)- and B cell antigen receptor (BCR)-mediated signaling activation and lymphocytic development . ElevateWe found patients who had a durable response to pembrolizumab following PIKTOR and cis/nab pac , 6, 8 ha2-M check point arrest and phosphorylate Chk2 and BRCA1, activating DNA damage repair [DNA damage repair protein signaling involves intersecting and discreet protein pathways. We noted variation of DNA pathway repair protein levels between patients that could be due to the underlying genomic alterations as well as differences in protein signaling due to the patient’s prior therapies Table . Proteine repair . Bouwmane repair  showed tLower protein levels of GCN2 following PIKTOR treatment in the responders were likely a by-product of PI3K and mTOR pathway inhibition, thus disrupting energy acquisition and metabolism regulation Figs. C and 7. Metabolic cell stress could lead to a nucleotide pool imbalance, thus affecting DNA repair efficiency and genomic stability , 72. Die+), and its reduced form NADH, are crucial cofactors for oxidation/reduction enzymes that regulate cell metabolism. NAD is synthesized in the kynurenine pathway which uses L-tryptophan as a precursor for synthesis of NAD [+ [Nicotinamide adenine dinucleotide  , 78. DisLimitations of this pilot study include small sample size, analysis of microdissected tissue for proteomic studies versus heterogeneous whole tissue samples for genomic studies, and variability in tumor biopsy sites pre- and post-PIKTOR, i.e., lymph node and lung in one patient. However, this study does show the ability to procure serial research biopsies and the prognostic and theranostic utility of multi-omic analysis of TNBC patients with advanced metastatic disease. Additional interpretations on DDR signatures, immune response, stress pathways and others would have been aided by an extended set of serial research biopsies following cis/nab-pac and immunotherapies. However, these research biopsies were not originally in the trial design and are unavailable for analysis. Although only a subset of patients demonstrated clinical benefit from the sequential administration schema, it is likely that combined inhibition of PI3K and TORC1/2 with PIKTOR would be too toxic to combine with therapeutic doses of cytotoxic agents.In conclusion, inhibition of PIK3CA and TORC1/2 with oral PIKTOR prior to treatment with cis/nab pac in metastatic TNBC patients is safe, and a subset of patients with platinum-pretreated metastases had multi-year disease control with sequential treatment with PIKTOR, cis/nab pac, then pembrolizumab. In the patients with durable responses, metastatic nodal disease assessed following disease progression on PIKTOR showed increased TMB, loss of MMR deficiency signature, decreased immune/inflammation pathway protein levels for DNA damage, cellular stress, and proliferation compared to their pre-PIKTOR nodal metastatic disease. At this time, PIKTOR is no longer being evaluated in mTNBC patients, however, trials including other PI3K/AKT pathway inhibitors, alpelisib and capivasertib, in combination with cytotoxic therapy in mTNBC patients are ongoing. Our findings may help inform analyses in these trials seeking biomarkers of therapeutic benefit.Below is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2Supplementary Material 3Supplementary Material 4Supplementary Material 5Supplementary Material 6Supplementary Material 7Supplementary Material 8Supplementary Material 9Supplementary Material 10Supplementary Material 11Supplementary Material 12Supplementary Material 13Supplementary Material 14Supplementary Material 15Supplementary Material 16Supplementary Material 17