We do not fully understand the resolution at which temporal information is processed by different species. Here we employed a temporal order judgment (TOJ) task in rats and humans to test the temporal precision with which these species can detect the order of presentation of simple stimuli across two modalities of vision and audition. Both species reported the order of audiovisual stimuli when they were presented from a central location at a range of stimulus onset asynchronies (SOA)s. While both species could reliably distinguish the temporal order of stimuli based on their sensory content , rats outperformed humans at short SOAs (less than 100 ms) whereas humans outperformed rats at long SOAs (greater than 100 ms). Moreover, rats produced faster responses compared to humans. The reaction time data further revealed key differences in decision process across the two species: at longer SOAs, reaction times increased in rats but decreased in humans. Finally, drift-diffusion modeling allowed us to isolate the contribution of various parameters including evidence accumulation rates, lapse and bias to the sensory decision. Consistent with the psychophysical findings, the model revealed higher temporal sensitivity and a higher lapse rate in rats compared to humans. These findings suggest that these species applied different strategies for making perceptual decisions in the context of a multimodal TOJ task. Rapid perceptual decision-making is often key to survival, for example a rat might need to quickly respond to the rustling of leaves to escape a lurking cat. To achieve rapid decisions, the brain needs to process the incoming sensory information, often requiring integration across multiple modalities, to generate an accurate percept and plan and execute the appropriate motor action, often all happening within several hundred milliseconds. The temporal precision of perceptual decisions vary across species; for instance electric fish can resolve 1 μs temporal disparity  while ecWe know that intersensory interactions occur when information from different senses arrives temporally or spatially coincident or near coincident in the brain . The braDiscriminating the order of stimuli is a key aspect of temporal processing, which is commonly measured using the well-known temporal order judgment (TOJ) paradigm. In this paradigm, the interval between the onset of two stimuli, also referred to as the stimulus onset asynchrony (SOA), is systematically varied, while requiring the participant to report which side the first of the two stimuli appeared , or whicPrevious studies have shown that both rats and humans accumulate evidence for perceptual decisions . In multFundamental similarities and differences are also observed in temporal processing in these species. For example, both rats and humans can detect temporal regularities in sound . But, inHere, by using the TOJ paradigm in rats and humans, we compare the temporal precision with which these species can detect the order of presentation of simple stimuli across two modalities of vision and audition. To this end, we designed similar audiovisual TOJ paradigms in which rats and humans were required to report which stimulus modality was presented first. Our goal was firstly to better understand how multiple sensory inputs are labeled and reported in their relative temporal occurrence in humans and rats, and secondly to investigate and directly compare the limits of temporal integration across these species. Finally, we performed drift-diffusion modeling on the human and rat data to isolate the contribution of various parameters including evidence accumulation rates, lapse and bias to the sensory decision. This data allows us to better understand how the profile of multisensory processing and labeling generalizes across species. To date, non-invasive methods such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have provided insights about neural underpinnings of multisensory temporal processing in humans . Howeverad libitum access to food and free access to water for 2 h each day after each training or testing session. Their weight was monitored throughout training to ensure that they continued to gain weight at a normal rate. In human study, ten participants  aged 26-36 years (mean age of 31.6 years) were recruited to take part in this experiment. All participants were right-handed with normal or corrected to normal visual acuity and reported normal hearing. One participant was one of the authors of this paper, two of them had experience in psychophysical experiments and the others were naive to such experiments and the purpose of this study. All gave written informed consent prior to taking part in this study. Human experiment was conducted in line with the Declaration of Helsinki  was presented from a 5 mm white transparent LED located in the center of the front wall, 6 cm (center to center) above the nose-poke hole. Both stimuli had the same duration (20 ms). All procedures including stimulus presentation, measurement of behavioral responses and reward delivery were controlled by a MATLAB program and through an Arduino interface board. During the training and testing sessions the chamber was lit using a 9 W red LED bulb for video recording.Rats were trained and tested in a custom-made wooden operant chamber, measuring 35 cm (length) × 25 cm (width) × 35 cm (height) which was placed in a dark and sound-attenuating box. The chamber had a central hole (1.5 cm depth) in the middle of its front wall, 4 cm above the floor to serve as a nose-poke area. The rats received liquid rewards (sucrose 5%) following correct responses in both training and testing sessions from two copper spouts, positioned on either side 5 cm away from the nose poke area. The spouts and nose poke used a capacitive sensor for detecting lick contacts. The capacitive sensors were connected to an arduino interface and were read by a MATLAB program at a high temporal resolution (>1 sample per ms). Animals’ contact with the spout or the metal piece at the end of the nose-poke hole, resulted in a sharp increase in the capacitance of the circuit. Applying a simple threshold allowed precise detection of behavior (nose-poke or lick at the spout). The auditory stimulus  was presented from a speaker  5 cm (center to center) above the nose-poke hole while the visual stimulus  stimuli. To this end, both stimuli were presented from a central point in front of the subjects . We deteRats were initially habituated to the chamber, and learned to receive the reward from both spouts. Assignment of the modalities to the left/right spouts started at this stage such that responses (licks) at each spout were accompanied by presentation of a stimulus in predetermined modality. For example, a rat would receive an auditory tone each time it licked at the right side and would see a visual flash each time it licked at the left spout.In this stage rats were trained to learn the assignment of modalities to left and right sides. For each modality, the left/right assignment was counterbalanced across rats. Rats initiated each trial by a nose poke into the central aperture  right, wAt this stage, we initially presented bimodal stimuli with long SOAs  and then progressively reduced the SOA to 15 ms across training. Here, only correct first choices were rewarded. Incorrect first choices resulted in the termination of the trial without any reward. No other punishment was applied. In initial stages, reduction of SOA was performed through 50 ms steps, down to 100 ms SOA. In the final stages, SOA was reduced from 100 to 75, 50, 25, and then 15 ms. Across the initial stages, passing through steps was dependent on reaching the criterion performance (>75% correct first choice for two consecutive days) in individual rats. However, for SOAs lower than 100 ms , there was no criterion applied. In each session only the most recent SOA was applied. Following this stage, rats were required to choose the reward spout, corresponding to the side of the modality of the first stimulus. A 3-s inter-trial interval (ITI) was applied between trials. The ITI was measured after the rat responded to the previous trial. For testing humans in this study, participants sat in front of an experimental panel similar to that used for rats. The distance between the experimental panel and the participant’s eyes was ∼80 cm. For collecting responses (thumb presses in p < 0.05).The asynchrony between the onset of bimodal stimuli varied from 15 to 200 ms in rats and from 25 to 200 ms in humans. The minimum SOA that rats could distinguish better than chance was 15 ms with an average performance of 58 ± 3% (mean ± standard deviation) across rats . In our d’) at each SOA using the following equation in each subject:A common analytic approach was used for rat and human experiments. In both experiments, subjects reported the modality of the first stimulus. To quantify the behavioral performance at various SOAs, we applied the Receiver Operating Characteristics (ROC) analysis from Signal Detection Theory . Accuracd’ values indicate better temporal discriminability. The hit and false alarm rates for individual SOAs are depicted in the d’, accuracy and reaction time.where, H is the hit rate, FA is the false alarm rate, and Z is the inverse of the cumulative Gaussian distribution function. Higher For analysis of reaction time, we only included correct trials in which responses were generated sooner than 4 sec after stimulus presentation. The values beyond this limit were considered as potentially not a direct response to that trial and were therefore excluded from analysis for both species. The number of excluded trials was relatively small for most humans and rats . We excluded incorrect trials in calculation of reaction time because these trials are unlikely to represent a correct reaction to the stimulus. In each condition for each rat, , we pooled trials from all testing sessions and calculated the median of the distribution as reaction time for that condition. We have also represented reaction time without exclusion of long outliers, and for both correct and incorrect trials in x value at the midpoint of psychometric function which indicates point of subjective simultaneity (PSS). The PSS is the temporal difference between two stimuli at which the subject is equally likely to report either modality as being first. In addition to slope, as an index of sensitivity we also estimated just noticeable difference (JND), where possible. The estimated value (mean ± SEM) was 0.067 ± 0.02 and 0.081 ± 0.01 in rats (n = 5) and humans (n = 10), respectively. Note that JND can reveal sensitivity in a broad range of SOAs  whereas the slope can be more informative at very short SOAs.A sigmoidal function (Equation 3) was fitted to responses at various SOAs using nonlinear least squares regression for all subjects to characterize the psychometric function . Paramet1. All SOAs  were used in the same fitting, consistent with the most common approach in the literature . Drift diffusion represents a class of integrator models, in which evidence in favor of each choice is accumulated until one of two decision thresholds (boundaries) is reached and a decision is made. The DDM was implemented using PyDDM simulatorterature .d’ and reaction time in order to examine the effect of SOA and to elucidate species differences. For reporting statistical details where the sphericity (Mauchly test) was violated, degrees of freedom were corrected according to Greenhouse-Geisser Correction in ANOVAs. For statistical comparison of psychometric parameters  and parameters derived from drift-diffusion modeling between two species, we used an independent-samples t-test in either case. In independent-samples t-test we checked homogeneity of variances using Levene’s test and in cases that homogeneity was violated we accordingly adjusted statistical details. For all statistical analysis, we used an IBM SPSS statistical package. The p value < 0.05 was considered as significant. We wrote code in MATLAB (R2021b) for extracting data and analysis including the sigmoidal fits and estimation of the fit parameters.Our approach for statistical analysis was to find out which factors affected performance in discrimination of temporal order of audiovisual stimuli and to examine whether these factors differ across the two species. To this end, we applied a mixed repeated measures ANOVA to either We implemented a similar TOJ task in rats and humans to test the temporal precision with which these species detect the order of presentation of simple stimuli across two modalities of vision and audition . Each trd’) in both species for all SOAs. We used hit (H) and false alarm (FA) rates  in each subject to quantify d’ at each SOA using the equation d’ = Z (H) – Z (FA), where Z is the inverse of the cumulative Gaussian distribution function. Higher d’ values indicate better temporal discriminability. d’ gradually increased from 25 to 100 ms SOA and reached a plateau in SOAs longer than 100 ms. In humans, on the other hand, the increase in d’ by increasing SOA revealed a more linear trend. We used a mixed-measures ANOVA  to examine the effect of SOA on d’ value and to examine any statistical differences between humans and rats. The effect of Species was not significant  = 0.17; p = 0.68, 2ηp = 0.01). This indicates that, when collapsed across the SOAs, the average d’ and therefore, the overall temporal discriminability was comparable between humans and rats. However, the main effect of SOA was highly significant  = 78.62; p = 0.001, 2ηp = 0.83), showing that the interval between stimuli determined their temporal discriminability. Post-hoc analysis with Bonferroni correction revealed significant differences between all pairs of SOA. The highest p value was 0.009 indicating difference between 50 and 75 ms SOAs. Importantly, there was a significant interaction between the SOA and Species factors  = 19.13; p = 0.001, 2ηp = 0.54) indicating that the relationship between discriminability and SOA does not follow the same pattern in two species. Rats exhibited higher d’ in short SOAs  whereas humans outperform rats at higher SOAs (>100 ms)  = 3.69, p = 0.004). On the other hand, at 200 ms SOA, d’ was significantly higher in humans (t (11.93) = −3.67, p = 0.003).Here we aimed to determine the similarity and differences of performance across the two species by measuring temporal discriminability (>100 ms) . To quanF  = 4.08; p = 0.06, 2ηp = 0.20), its interaction with Species  = 0.07; p = 0.79, 2ηp = 0.005) and SOA  = 0.39; p = 0.6, 2ηp = 0.024) were not significant. These findings indicate that in both species, order of modalities did not affect discrimination accuracy across the range of SOAs.To further investigate the effect of modality on performance, we included accuracy of choices in visual-leading  rate) and auditory-leading ) trials in a mixed-measures ANOVA using SOA (6 SOAs) and Modality  as within-subject factors and Species as a between-subject factor. The main effect of Modality  = 9.28; p = 0.01, 2ηp = 0.37). However, given the differences in the apparatus and the type of response required from the two species, the absolute differences in reaction time are hard to interpret. The main effect of Modality was significant  = 8.3; p = 0.01, 2ηp = 0.34): we observed shorter reaction times in visual-first trials. Interaction between the effects of Modality and Species was not statistically significant  = 1.67; p = 0.21, 2ηp = 0.09)  = 4.15; p = 0.04, 2ηp = 0.21), which means that the temporal interval between stimuli had an effect on reaction time. Importantly, there was a significant interaction between the SOA and Species factors  = 5.73; p = 0.02, 2ηp = 0.26) indicating that SOA affected reaction times differently in the two species. Interaction between SOA, Species and Modality  = 0.8; p = 0.45, 2ηp = 0.05) was not significant. Also, no significant interaction was revealed between the effects of Modality and SOA factors  = 0.66; p = 0.51, 2ηp = 0.04). Visual inspection of data  and auditory-first  choices were positively correlated with SOA. In humans, however, a significant but negative correlation was found in both the visual-first  and auditory-first  choices. Overall, these findings indicate that while for humans, reaction times increased with task difficulty, the opposite relation was observed in rats.We next asked whether reaction times were also systematically different between the two species. In a decision process, a trade-off often exists between speed and accuracy, whereby difficult decisions often correspond to longer reaction times . We calc = 0.09) . The mai of data  revealedt-test: t (16) = 4.75, p = 0.001) which indicates that rats delivered more unattended or random responses specially in visual first trials compared to humans even when detecting temporal order of stimuli was easy. However, the lower lapse rate was similar in two species (independent samples t-test: t (16) = 1.52, p = 0.15). There was a significant difference in slope of the psychometric function fitted to human and rat data (independent samples t-test: t (16) = 4.64, p = 0.001) indicating that slope of psychometric function was different in two species. This revealed temporal sensitivity of rats was higher than humans. Therefore, rats compared to humans are able to distinguish stimuli with smaller temporal intervals from each other. In other words, rats had higher sensitivity to changes in SOAs. No significant difference existed between PSS of humans and rats, determined by independent samples t-test (t (11.04) = −0.908, p = 0.38). In rats, the average PSS (−4 ms) was not different from zero (one-sided t-test: t (7) = 0, p = 0.5), showing that they were unbiased to auditory and visual stimuli. Finally, in humans, the average PSS was +19 ms which was not statistically different from zero (one-sided t-test: t (9) = 0, p = 0.5), revealing no evidence for a modality bias in humans.In this section, for obtaining performance measures and examining the similarities and differences between the two species, we applied psychometric function to responses of individual rats and humans. To this end, we fit a cumulative Gaussian sigmoid curve to accuracy rates for rats and humans. These methods allowed us to isolate key parameters of the performance including (i) the temporal sensitivity which is captured by the slope of the sigmoidal function (ii) the interval at which the two stimuli are perceived as simultaneous (PSS) and (iii) the lapse rate which represents the probability of delivering unattended responses, regardless of the difficulty of stimulus. drift rate reflects the rate of sensory information accumulation. The decision threshold determines the amount of sensory evidence that needs to be accumulated before the choice is made. The nondecision time is the portion of reaction time which is not related to the decision process . The leak reflects the amount of sensory information that is lost over time. Finally, we fit a collapsing bounds parameter (tau) to capture the rat’s impulsivity where less evidence is needed at longer reaction times. t (16) = 5.58, p < 0.001) and the leak rate (t (16) = 2.91, p = 0.001). Rats also exhibited a trend towards a lower decision bounds (thresholds) compared to human participants (t (16) = 1.71, p = 0.11). Altogether, having a faster collapse of bounds and rate for information leak along with lower bounds could explain the earlier observation that rats had significantly faster reaction times across all SOAs, whereas humans showed longer reaction times with short SOAs. As rats’ bounds collapse more quickly, they tended not to delay their response at short SOAs despite the reduced evidence. This potentially explains why despite having higher lapse rates, rats exhibited a superior performance at low SOAs. Unlike the classic global dot motion paradigms, where sensory evidence continuously flows in, here the information is provided in a single time at the onset of the trial. Therefore, any delays in the decision can potentially corrupt the evidence through leakage. It is, therefore, unsurprising short SOAs where reaction times were longer corresponded to inferior performance in humans.So far we have found that rats have higher performances at short SOAs compared with humans, but exhibited lower performances at longer SOAs. There were no systematic differences between the two species in the point of subjective simultaneity. One difference that stood out in the psychometric function was the high lapse rate of rats compared to humans. The more impulsive behavior in rats, that may be partially due to task demands, could explain their high lapse rate. This is also consistent with the reaction time data where rats showed systematically faster responses and did not decrease their speeds with increasing task difficulty. To provide a more quantitative understanding of the underlying mechanisms that determined these sensory decisions in rats and humans, and to incorporate decision accuracy and reaction time into a single framework, we used drift diffusion modeling . Drift dd’) systematically decreased by decreasing the SOA in both species. However, rats showed greater sensitivity at short SOAs (shorter than 100 ms) whereas humans showed greater performance at long SOAs (longer than 100 ms)  . We founvia increasing accuracy. For the current experiment, correct responses in rats were accompanied by a sucrose reward, therefore, incentive anticipation of reward probably may have promoted unattended impulsive responses  in the visual-leading and auditory-leading trials responded to the left and right sides, respectively. However, we did not observe any systematic differences in reaction times, and lack of bias in the PSS implies that overall performance was not influenced by nonspecific factors such as handedness or any potential intrinsic left/right bias in subjects. Only a modality-dependent bias was observed for reaction time, such that the average reaction time was shorter in the visual choices. Because visual choices were mapped to the left hand, therefore shorter response times in the left/visual choices (compared to right-auditory choices) suggests the presence of a modality effect rather than a handedness bias which would have been expected to favor the right choices in right-handed individuals. Future studies could adjust the human and rat paradigms to remove some of the methodological differences here including the extent of training and the presence of feedback. These studies could also record signals in the form of EEG from humans and neural activity in behaving rats undertaking this task to investigate the neuronal mechanisms that underlie perceptual decisions in such multimodal contexts.By implementing a similar psychophysical paradigm in rats and humans, we found that both species could reliably distinguish the temporal order of audio-visual stimuli based on the modality label. Rats showed superior performance at difficult trials, with SOAs shorter than 100 ms, whereas humans showed superior performance at easier trials, with SOAs greater than 100 ms. Rats exhibited a high temporal precision by performing better than chance even at the 15 ms SOA. Overall, rats produced faster responses compared to humans and did not increase their reaction time as difficulty increased. Despite their higher temporal precision, rats’ overall performance was hampered due to a high level of lapse rate and this was most evident at the easy trials with long SOAs. Despite a few similarities, our findings indicate that rats and humans apply different strategies in terms of speed and accuracy in resolving perceptual decisions when the difficulty of decisions varies across trials.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Ethics Committee of Kerman University of Medical Sciences. The patients/participants provided their written informed consent to participate in this study.FM, MA, and EA designed the initial project. FM performed the experiments. All authors contributed to the data analysis and interpretation. FM, SG, and EA designed and built the experimental apparatus and wrote code to control the stimuli and monitor the behavior. MT performed the initial modeling. FM and EA drafted the first version of the manuscript. All authors contributed to the subsequent revisions.


GNAQ and GNA11 are involved in the process of carcinogenesis and are mutated in 80–90% of these tumours. Historically, there has been speculation as to whether these two genes are involved in the progression of primary uveal melanoma to metastatic disease, in addition to the oncogenic process itself. For this reason, both genes have been the subject of multiple research studies. Additionally, due to their high mutation rate in uveal melanoma, these genes and the downstream signaling pathways in which they are involved have been postulated as interesting therapeutic targets. This review aims to provide a current comprehensive view of what we know about GNAQ and GNA11 genes on oncogenesis, prognosis and therapeutic opportunities in uveal melanoma.The development of uveal melanoma is a multifactorial and multi-step process, in which specific and recurrent mutations arise early. Among the recurrently mutated genes, GNAQ and GNA11 genes are mutated in almost 80–90% of uveal melanomas in a mutually exclusive pattern. These genes encode the alpha subunits of the heterotrimeric G proteins, Gq and G11; thus, mutations of these genes result in the activation of several important signaling pathways, including phospholipase C, and activation of the transcription factor YAP. It is well known that both of them act as driver genes in the oncogenic process and it has been assumed that they do not play a role in the prognosis of these tumours. However, it has been hypothesised that mutations in these genes could give rise to molecularly and clinically distinct types of uveal melanomas. It has also been questioned whether the type and location of mutation in the GNAQ and GNA11 genes may affect the progression of these tumours. All of these questions, except for their implications in carcinogenesis, remain controversial. Uveal melanoma has a distinctive genetic profile, and specific recurrent mutations, which make it a potential candidate for treatment with targeted therapy. Given that the most frequent mutations are those observed in the GNAQ and GNA11 genes, and that both genes are involved in oncogenesis, these molecules, as well as the downstream signalling pathways in which they are involved, have been proposed as promising potential therapeutic targets. Therefore, in this review, special attention is paid to the current data related to the possible prognostic implications of both genes from different perspectives, as well as the therapeutic options targeting them.The  BRAF or NRAS oncogenes, which are typically mutated in CMM [Uveal melanoma (UM) is the most common intraocular malignancy in adults and the second most prevalent type of melanoma after cutaneous malignant melanoma (CMM) ,2. This d in CMM ,6,7,8. Id in CMM . In factThe genetic analysis of tumoral samples in UM is crucial for metastatic risk prediction, as well as for patient management and follow-up. Historically, several histopathological, clinical and radiological parameters with prognostic value have been considered to evaluate the risk of metastasis. Nevertheless, the presence of specific somatic cytogenetic and genetic biomarkers can estimate more accurately the progression to metastatic disease. Among these specific alterations, cytogenetic studies highlighted that tumours with monosomy 3 (M3) or gain of 8q are associated with poor prognosis. Monosomy 3 is present in nearly 50% of UMs acting as an independent risk factor for metastasis that strongly correlates with significantly reduced disease-free survival (DFS). This chromosomal aberration has become the most significant prognostic parameter in UM ,10. The BAP1 gene (encoding BRCA1-associated protein 1 and located in chromosome 3). The biallelic inactivation of this gene occurs in approximately 50% of primary UMs, combining M3 and a deleterious somatic mutation in the second BAP1 allele. BAP1-inactivated UMs are at a high risk of metastasis [Another recurrent genetic alteration that is strongly associated with a bad prognosis is the inactivation tastasis . GNAQ) and its paralogue guanosine nucleotide-binding protein alpha-11 gene (GNA11). Those two genes are mutated in nearly 90% of these tumours in a generally mutually exclusive pattern [GNAQ and GNA11 genes encode protein members of the q class of G-protein alpha subunits involved in mediating signals between G-protein coupled receptors (GPCRs) and downstream effectors [GNAQ and GNA11 genes arise early in UM and are even present at the very early stages corresponding to benign melanocytic lesions [GNA11 were found more frequently than GNAQ mutations in patient cohorts with metastatic UM (MUM) [In addition to those genetic alterations with strongly prognostic values, UM frequently exhibit other chromosomal aberrations and somatic mutations. Indeed, the most common detected somatic mutations in UM are located in the guanosine nucleotide-binding protein Q gene  ,22. GNAQ and GNA11 genes in UM was discovered, there has been speculation as to whether or not they might be involved in the genetic prognosis of the disease. Additionally, due to their high mutational rate in UM, both genes have also been the subject of therapeutic studies as they act as the switch of the MAPK/ERK signalling pathway, which is constitutively active in these tumours. Currently, important efforts are being addressed to develop effective therapies to prevent metastatic disease, which is actually the principal determinant factor of a patient’s survival. Therefore, the inactivation of GNAQ/GNA11 mutants has been proposed as a potential strategy to treat UM, leading to a rapid expansion of clinical trials [Since the role of l trials ,24,25,26GNAQ and GNA11 mutated genes in the disease oncogenesis, prognosis as well as target therapeutic options for UM. In this review, we present and update the recent discoveries and studies about the role of GNAQ and GNA11 genes are located on chromosomes 9q21.2 and 19p13.3, respectively. They are paralogous genes with a sequence homology of approximately 90% and have a coding region comprising seven exons. The proteins encoded by these genes have similar molecular weights , and consist of 359 amino acids that comprise the αq and α11 nucleotide-binding subunits of heterotrimeric G proteins [The proteins . GNAQ/GNA11 mutations is approximately 80–90% of the UM cases [GNAQ mutations have been reported to range from 24.2 to 53.3% and those of GNA11 mutations from 24.2 to 60% [The frequency of UM cases ,20,21. I2 to 60% ,29,30,312 to 60% ,33. ThisGNAQ and GNA11 in UM showed an exclusive pattern of somatic mutations in both genes [GNA11 mutations in codon 209 leads to glutamine to leucine (p.Q209L) and proline (p.Q209P) substitutions [GNAQ gene, a one-base change at codon 209 (CAA) can predict the substitution of glutamine by leucine  and proline , in most cases [GNAQ and p.Q209Y, p.E234K, p.E221D in GNA11, have also been described [The pioneering sequencing studies of th genes . Subsequth genes . Mutatioitutions ,32,34. Titutions . Contrasst cases ,28. In eescribed  , and CC > TT transitions at codons 182-183, which predict the replacement of arginine to cysteine (p.R183C) or histidine (p.R183H). Likewise, the few mutations reported to affect the codon 183 of GNAQ (CGA) are caused exclusively by G > A transitions [GNAQ are p.P170S, p.I189T, p.Q176R, and p.P193L, which achieve an overall frequency of 8.9% in some series [Overall, the frequency of mutations in the exon 4 of nsitions . Other me series   comprise the largest family of cell surface receptors encoded by the human genome. While cancer-related mutations in GPCR signalling are less common than those in receptor tyrosine kinases, comprehensive sequencing of the human cancer genome has revealed that roughly 20% of human cancer mutations are associated with altered GPCR signalling . GPCRs hFollowing activation, proteins belonging to the family of regulators of G protein signalling accelerate the G subunit’s intrinsic GTPase activity, reverting the G protein to an inactive GDP-bound state and so promoting the formation of the inactive heterotrimeric protein complex. The p.R183 and p.Q209 mutations are located in the Gq/11 proteins’ switch I and II domains, respectively. These mutations transform G proteins to a constitutively active state by decreasing their GTPase activity .BRAF mutations [GNAQ mutations [GNAQ/11 mutation is present [Primary and metastatic UMs showed that high levels of phosphorylated MEK and ERK proteins occur in the absence of utations . It is wutations . Then, iutations . These putations . Subsequ present .In vitro analysis using protein kinase C (PKC) inhibitors of various specificities support the concept that the mutant GNAQ protein increases UM proliferation through PKC activation. Wu et al. discovered that enzastaurin, which is a potent PKCβ inhibitor [GNAQ cell lines at considerably higher rates than in wild-type GNAQ and GNA11 cell lines [GNAQ mutations. This fact indicates that PKC signalling is crucial in mediating the oncogenic effects of mutant Gq in UM [nhibitor , inducesll lines . This efGq in UM ,45. InteIn vitro investigations of the GNAQ mutant in UM cell lines demonstrated that the suppression of PI3K-alpha and P13K-beta had little effect on proliferation, indicating that PI3K is not the primary growth promoting factor . HoweverGNAQ and GNA11 lead to YAP/TAZ activation under physiological conditions. In vitro cell lines and human samples with GNAQ or GNA11 p.Q209 mutations showed higher amounts of YAP dephosphorylation and nuclear localisation in comparison to cell lines with wild-type GNAQ and GNA11, confirming these findings [The Hippo-YAP pathway is a regulator of cell contact inhibition, proliferation and death . Yu et afindings . Moreovefindings .GNAQ-p.Q209 mutant model [A parallel investigation by Feng et al. further defined the molecular mechanism of YAP activation using a nt model . Other rnt model . GNAQ sint model . Dynamicnt model . Actin pnt model .GNAQ and GNA11 genes in the prognosis of these tumours. Firstly, it was suggested that several lines of evidence indicate that GNA11 mutations may have a stronger effect on melanocytes than those mutations in GNAQ [GNA11 p.Q209 than GNAQ p.Q209 mutations in UM metastases. These mutations were also more common in locally advanced primary tumours, specifically in those originating from ciliochoroidal region, which is per se a prognostically adverse feature [Prognostication of UM patients can be achieved by analysing the mutational tumour status. Since the initial UM sequencing studies, there has been controversy about the possible involvement of the  in GNAQ . The fir feature . This ob feature .GNAQ mutations and those with GNA11 mutations in their study, even though they observed a trend toward increased survival among patients with tumours carrying a GNA11 mutations [Several years later, Van Raamsdonk et al. also speculated that the differences observed in mice may be a functional consequence of the different mutations rather than a real difference in function between GNA11 and GNAQ proteins. In contrast, these authors observed no significant differences in survival among those patients with utations , which cGNAQ were not suitable to predict DFS in patients with UM [GNAQ mutations have been shown to have similar frequencies at different clinical stages of UM progression, and to be independent of chromosomal aberrations, acting as an early oncogenic event [One year prior to this, Bauer et al. described that mutations in  with UM . This waic event .GNAQ and GNA11 genes are not associated with patient outcome to an equal extent. They studied samples from 92 ciliary body and choroidal melanomas and correlated the mutational status of both two genes with DFS and other parameters. The authors concluded that the univariate analysis of patients with tumours harbouring mutations in GNAQ or GNA11 genes was not significantly lower than in wild-type tumours. They also examined whether mutations in these genes affected the prognosis of patients with M3 tumours by using a survival analysis for changes in chromosome 3 stratified for GNAQ and GNA11 mutations. Again, no significant effect on the DFS in tumours with M3 and the presence of mutations in GNAQ or GNA11 was observed [In 2013, Koopmans et al. published that GNA11 mutations in MUM, and a poorer disease-specific survival of GNA11-mutant tumours in a cohort of 30 UM patients with metastasis [Subsequently, numerous sequencing studies on UM tumour samples have been published. The results were always diverse and controversial, since although both genes showed some correlation with other prognostic features or different trends in relation to OS, no specific and reproducible pattern was ever observed among the different cohorts of the patients studied . In 2014tastasis .GNAQ mutations were associated with the absence of ciliary body involvement and greater largest basal diameter; both of these are defined as bad-prognosis characteristics. On the other hand, GNA11 mutations were not associated with any of the analysed clinicopathologic features with prognostic value [GNAQ/GNA11 mutations in Chinese patients affected by UM, finding that metastasis-free survival was not significantly associated with the GNAQ/11 mutations in the Kaplan–Meier analysis . Those results indicated that GNAQ and GNA11 mutations were not significantly associated with metastasis [Later, Decatur et al. found that ic value . In the tastasis .GNA11 mutations, 2 harboured GNAQ mutations and only 1 of them had no mutations in neither of those 2 genes. Once more, regarding these results, the authors proposed a bias towards GNA11 p.Q209L mutations in metastatic disease [GNAQ and GNA11 mutations was also published by Staby et al. in 2018, whom found no significant differences in the prevalence of GNAQ and GNA11 mutations between the patients with or without metastatic disease. Despite this, these authors found that GNAQ mutations showed a tendency to be inversely associated with progression to metastatic disease [On the other hand, in 2018, Kennedy et al. described that in a patient cohort composed of 36 patients with primary UM, where 9 patients developed metastasis, 6 of them harboured  disease . However disease .GNAQ and GNA11 and patient survival could be demonstrated in most of the studies published to date. This is because, although most of them showed a trend supporting that mutations in the GNA11 gene are likely to lead to more aggressive disease development, this tendency has rarely been accompanied by statistically significant results. Nonetheless, very recently, Piaggio et al. demonstrated, for the first time, that UM with mutated GNA11 has worse prognosis than those with mutations in GNAQ . They analysed the association between GNAQ and GNA11 mutations with disease-specific survival, gene expression profiles, and cytogenetic alterations in 219 primary UMs from three different cohorts . In their study, these authors concluded that GNA11 mutated UMs have worse prognosis, and it is associated with high risk cytogenetic, mutational and molecular tumour characteristics that might be determined, at least in part, by differential DNA-methylation. Therefore, to date, this is the only published study in which statistical results support the existence of an association between mutations in the GNA11 gene and worse disease prognosis in patients with UM [GNA11 gene in terms of prognosis had been observed, could be due to a reduced number of analysed samples, or due to the insufficient follow-up time of patients.As it can be observed, no correlation between the presence of mutations in  with UM . TherefoIn most types of tumours, immunological characteristics, such as inflammation, infiltrate, and HLA molecules expression, correlate with the prognosis of the disease. In UM, it has been described that inflammatory phenotype, which is characterised by the presence of immune cells, such as T lymphocytes, macrophages, and an increased HLA expression, is closely related to bad prognosis ,57,58.GNAQ/GNA11 mutational status, to the specific type of mutation (p.Q209P/p.Q209L), and whether or not mutations in those two genes are responsible for different degrees of inflammation. As result, they found no differences in the expression of inflammatory markers, such as HLA expression, or levels of infiltrating leukocyte, according to the presence of GNAQ/GNA11 mutations. They also found no significant differences between the GNAQ/GNA11 or p.Q209L/p.Q209P mutations for the survival of patients [GNAQ and GNA11 do not play a direct role in the regulation of inflammation, and that the type and location of mutations in these genes do not appear to affect the progression of UM.In 2019, van Weeghel et al. tried to investigate whether the expression of different types of HLA molecules in UM is similarly related to M3 or might be related to the patients . These oGNAQ and GNA11 genes exhibit similar mutations rates in primary UM; however, less is known about the prevalence and significance of mutations in these genes in MUM. Indeed, most of the published investigations regarding somatic mutations in UM focused on the evaluation of elapsed time from the initial diagnosis and treatment of the primary UM to the development of metastasis or death.Many studies had showed that GNAQ and GNA11 in the prognosis of UM had reported that the distribution of GNA11 and GNAQ mutations differs between primary and MUM, with a GNA11 to GNAQ ratio of 0.7 in primary UM, and 2.6 in MUM [GNA11 mutations were considerably more frequent than GNAQ mutations in these specimens. Additionally, they found that patients with GNA11-mutant tumours had poorer disease-specific survival  and OS , than those with tumours lacking GNA11 mutations. Thus, they proposed that the survival data, combined with the predominance of GNA11 mutations in metastasis, raises the possibility that GNA11-mutant tumours may be associated with a higher risk of metastasis and poorer prognosis than those tumours bearing GNAQ-mutants [The pioneering studies on the role of 6 in MUM . Griewan-mutants .GNAQ and GNA11 mutations, the frequency of mutations in MUM specimens, and the commonly mutated GNAQ/GNA11 genes in survival after development of systemic metastasis. They found similar rate frequencies for both genes in patients, where mutations in GNAQ and GNA11 genes were observed in 44.8% and 47.1% of patients, respectively [GNAQ and GNA11 genes themselves [Recently, Terai et al. investigated the possible existence of a correlation between metastasis-to-death in MUM patients with ectively . This reectively ,19. Furtemselves .GNA11 to GNAQ ratio was 1.2. Contrary to other studies, the GNA11-mutated tumours demonstrated a longer average time to first metastasis (GNA11 vs. GNAQ: 77.8 vs. 43.1 months) and a better OS (79.8 vs. 33.7 months). Nonetheless, they discuss that the differences between their results, and those from other investigations, could be due to the ratio of metastatic vs. primary tumour examined, and also to the small number of samples [Subsequently, Isaacson et al. reported that in their cohort of patients, the  samples .GNAQ and GNA11 genes [Targeted therapy is a therapeutic modality that refers to the drugs designed to interfere with a specific molecular pathway that is believed to play a critical role in tumour development or progression . As it w11 genes ,20,62, tThe growing relevance of this therapeutic strategy is now evidenced by the numerous relevant papers that regularly report the latest results and knowledge on UM-targeted therapies ,74,75,76The main action of GDIs is to prevent the release of GDP, i.e., they inhibit GDP/GTP exchange, which leads to the G protein remaining in an inactivated state, and therefore, blocking its signalling. Two molecules stand out within this group, FR900359 and YM-254890 .The first of these, FR900359, is a cyclic depsipeptide derived from the plant Ardisia crenata, which selectively inhibits Gαq, Gα11 and Gα14, and is inactive in cells lacking these proteins . It was GNAQ mutant cells were less sensitive than GNA11 mutant cells to YM-254890 [On the other hand, the YM-254890 molecule is a cyclic depsipeptide isolated from Chromobacterium sp. QS3666  also witM-254890 .Despite the fact that heterotrimeric Gαq/11 G proteins have been known for decades, their selective inhibition is still considered a challenge. The reasons include the high affinity of GDP/GTP for the G-protein, as well as the fact that its high intracellular levels hinder biochemical competition, and that this “mutation-nonspecific” type of inhibitor can block both wildtype and oncogenic protein forms .It is well known that Gαq/11 activation leads to the stimulation of the downstream signalling pathway MAPK, which contributes greatly to UM carcinogenesis .GNAQ/11 mutant UM [One of the most important intermediate effectors in this pathway are the MEK enzymes. Within the subgroup of MEK inhibitors, one of the best known and most tested molecules is selumetinib (MEK1/2 inhibitor). Ambrosini et al. demonstrated that treatment with selumetinib (AZD6244) regulated the expression of the genes involved in proliferation, cell invasion and drug resistance in tumour tissues of patients with metastatic utant UM . Thus, butant UM .In 2014, the results of a clinical trial (NCT01143402) in patients with advanced UM were presented. In this study, selumetinib as monotherapy was compared to chemotherapy (temozolomide or dacarbazine), showing only a modest improvement in progression-free survival (PFS) and response rate, with no improvement in OS . SubsequFollowing the previous approach, Decaudin et al. evaluated the potential of drug combinations to increase the efficacy of selumetinib in UM cell lines and patient-derived xenograft models (PDXs) by first assessing the combination of selumetinib and dacarbazine. They observed that this chemotherapy agent did not improve the in vitro or in vivo antitumour efficacy of selumetinib, which is consistent with the results of the Carvajal et al. clinical trial. Thus, they tested other combinations of selumetinib with docetaxel (chemotherapy agent), AZ6197 (ERK inhibitor), and vistusertib-AZD2014 (mistusertib-AZD2014), with the latter two appearing to be the most effective in UM PDXs . A multiGNAQ mutation), and four had stable disease for ≥16 weeks (including two who received treatment for >40 weeks) [Another orally administered selective MEK1/2 inhibitor is trametinib (GSK1120212). Falchook et al. conducted a trial (NCT00687622) including 81 patients with CMM, and 16 with advanced UM and. Although efficacy was mainly observed in BRAF-mutated CMM, among the trametinib-treated UM patients, two achieved 24% tumour shrinkage (one of whom had a 0 weeks) .Phospholipase C beta (PLCβ) is able to activate several protein kinase C (PKC) isoforms and RasGRPs . In UM, GNAQ-mutated UM cells. Down-regulation of these PKC isoforms resulted in enhanced antitumour action through the induction of apoptosis and G1 cell cycle arrest on GNAQ mutant UM cells, compared to those wild type [GNAQ/11 mutations that induces G1 cell cycle arrest [In an experimental study, the molecule enzastaurin was shown to decrease the expression and/or phosphorylation of several PKC isoforms including βII, ε and θ in ild type . In the e arrest ,95.GNAQ mutations through the PKC/NF-κB and PKC/ERK1/2 pathways specifically, by the inhibition of the expression of PKC isoforms α, β, δ, ε, and θ [In a similar preclinical approach, it was shown that the PKC inhibitor, AEB071 (sotrastaurin), was able to significantly reduce the viability of UM cells harboring ε, and θ . Based oε, and θ . Howeverε, and θ ,97.In the same way, it was shown that AEB071, together with CGM097 (MDM2 inhibitor) showed an additive effect enhancing the anti-proliferative and apoptotic effect, as well as the inhibition of tumour growth . SubsequGNAQ/11 mutant UM cells observed that the combination of LSX196 with trametinib (MEK1/2 inhibitor), showed a strong synergistic effect in reducing cell viability, while the combined treatment of this first molecule with VS-4718 (FAK inhibitor) reflected a more limited synergy [A promising novel PKC inhibitor is the LSX196 molecule, later registered as IDE196 (darovasertib). An in vitro study with  synergy .GNAQ/11 mutations, including MUM, CMM, and colorectal cancer among others, with an approximate completion date of late 2022–2023, presented in July 2021 a preliminary robust 57% 1-year OS in monotherapy and early partial responses, in combination with binimetinib (MEK inhibitor) and crizotinib (c-MET inhibitor), in the group of patients with MUM. More specifically, a partial response in 22% of cases, and tumour shrinkage in 79% was observed with darovasertib and binimetinib combination therapy .Several clinical trials are currently underway for evaluation. A phase I/II study, (NCT03947385) designed to characterise the safety and anti-tumour action of darovasertib in patients with solid tumours harbouring Another clinical trial (NCT02601378), with an estimated completion date of June 2022, aims to characterise the pharmacokinetics/pharmacodynamics, tolerability, safety and antitumour activity of LXS196 as a single agent and in combination with HDM201 (siremadlin), an MDM2 inhibitor, in patients with MUM. In 2019, Kapiteijn et al. published preliminary analyses suggesting tolerable toxicity and encouraging clinical activity of LXS196 as monotherapy in these patients .GNAQ oncogene is able to control the Hippo pathway through a cytoplasmic protein tyrosine kinase called focal adhesion kinase (FAK). They detailed that Gαq activates FAK through a non-canonical TRIO-RhoA signalling pathway, which in turn positively regulates the yes-associated Protein (YAP) by tyrosine phosphorylation of MOB1, inhibiting the Hippo kinase cascade and promoting tumour growth in the UM [Feng et al. demonstrated that the n the UM . Therefoin vivo, that the pharmacological combination of MEK-ERK and FAKi showed a negative synergistic action on cell growth, as well as cytotoxic effects leading to tumour regression [It is well known that FAK can be stimulated when tumour cells are exposed to other types of tyrosine kinase inhibitors, implying therapeutic resistance . On the gression . Two exaPI3K/AKT/mTOR is a downstream signalling pathway that can also be activated and deregulated in the UM due to oncogenic Gα action. Within this pathway, mTOR inhibitor RAD001 (everolimus) is one of the most studied drugs, both alone, and in combination. It showed reduced cell line viability and significantly delayed UM growth in preclinical studies , whereasEverolimus was also studied together with the PI3K inhibitor GDC0941, which synergistically increased apoptosis in several UM cell lines compared to monotherapies, and enhanced the antitumour effect of each agent alone in UM PDXs. Evaluation of the combination of everolimus with the PKC inhibitor AEB071 (sotrastaurin) demonstrated greater activity than single molecules, inducing cell death and observing tumour regression in several UM PDXs .GNAQ/GNA11 UM cell lines, and similarly, inhibits tumour growth in vivo in a GNAQ mutant xenograft model [Following the strategy of these synergistic effects, the PI3Kα inhibitor alpelisib (BYL719) was studied in combination with sotrastaurin. In the first study, it was observed that the combination of BYL719/AEB071 decreases cell viability and induces apoptosis in ft model . In the ft model .GNAQ mutant cell lines and xenograft models, but no impact on apoptosis [Finally, molecules of this pathway have been tested in combination with MEK inhibitors. AZD8055 (mTOR inhibitor) and MK2206 (AKT inhibitor) in combination with selumetinib (MEK1/2 inhibitor) showed, in preclinical studies, a synergistic inhibition of viability in poptosis ,109.On the other side, GSK2126458 (PI3K inhibitor) was combined with trametinib (MEK inhibitor), a trial that showed a higher rate of apoptosis with the combination therapy compared to each PI3K and MEK inhibitor alone . In thisADP rybosylation factor 6 (ARF6) is a GTPase that triggers, in the presence of the oncogenic Gαq mutation, multiple downstream signalling pathways, such as Rho/Rac/YAP and PLCβ/PKC. The pyrazolopyrimidinone compound NAV-2729 was identified as a promising direct inhibitor of ARF6, reducing UM cell proliferation and tumorigenesis in a mouse model. Therefore, ARF6 is a potential therapeutic target for patients with oncogenic GNAQ-driven UM .As previously mentioned, c-MET inhibitors are also targets of study. Within this group, cabozantinib obtained, in a first trial (NCT00940225), encouraging results from a PFS and OS point of view . HoweverGNAQ/GNA11 genes in UM and their putative therapeutic opportunities. It seems clear that both genes play an important role in the oncogenic process of UM, but their role in the prognosis of these tumours remains controversial.In this review, we have attempted an interrelated assessment of the possible prognostic implication of mutations in the GNAQ and GNA11 genes are only involved in the early development of UM, playing a lesser role in its progression. Nevertheless, even in the absence of statistically significant results, several investigations have suggested a more aggressive course of tumours with the mutated GNA11 gene, due to the general observation of a trend towards longer survival among patients with tumours carrying GNAQ mutations. Irrespective of these results, it should be noted that most of the published investigations regarding somatic mutations in UM focused on the evaluation of time from the initial diagnosis and treatment of the primary UM to the development of metastasis or death. Moreover, there is even less knowledge about the role of these mutations in the advanced state of UM, and even less, in MUM. Regarding this, the few published studies that focuse on assessing the role of these mutations in MUM observed similar rate frequencies for both genes in patients with metastasis, and suggested that the survival of MUM patients could be predicted according to the mutation (p.Q209 vs. p.Q209L) rather than the mutated gene [GNA11 have worse prognosis than those with mutations in GNAQ [Most published studies agree that ted gene . After a in GNAQ .GNAQ and GNA11 genes are involved in various signalling pathways that are essential for the proliferation of tumoral cells in UM. This, in combination with its high mutational rate of these tumours, makes them promising targets and regulators of the therapeutic response in UM. Despite the relatively good response of the primary UM to treatment, almost 50% of patients will develop metastatic disease [The  disease ,117. Fur disease . It is fGNAQ/GNA11 signalling pathways could support the idea that these genes are not really involved in UM prognosis.Today, there are still important limitations that hinder and slow down the progress in the development of new adjuvant therapies. Overall, it is worth noting that many studies are in the preclinical phase, that trials include a small sample size of patients, and that the absence of randomisation is common, as well as the fact that molecular knowledge on UM is mostly based on primary tumour samples, and not so much on metastatic specimens ,105. MorGNAQ/GNA11 genes, and more sequencing studies involving a larger number of tumour samples at different follow-up times to generate preliminary findings that will require further clinical validation.Ultimately, to overcome these obstacles and obtain consistent conclusions on the benefit of different targeted therapies, it will be necessary, in the near future, to develop protocolised in vivo studies in advanced UM that consider key aspects such as the individualised molecular-genetic profile of each patient. This includes more studies to investigate the functional and prognostic relevance of oncogenic mutations in GNAQ gene, GNA11 gene, MAPK signalling pathway, targeted therapy in uveal melanoma, genetic basis of UM, sequencing studies in UM. The results of that search form the basis for publishing this article.This article was developed in the context of an intensive literature review. The considered publications were mainly searched in PubMed using key words or sentences such as the following: UM prognosis, driver mutations in UM, oncogenic mutations in UM, G-protein coupled receptors in UM,


Vaccine hesitancy has seen an uprising over the decades, even though there have been many advances regarding vaccine-preventable diseases. Of late, vaccine hesitancy has resurged towards the coronavirus disease 2019 (COVID-19) vaccine. The SARS-CoV-2 virus has major effects on the human body and has led to the development of different vaccines, which have been shown to provide immunity against the novel coronavirus. Dentists are at an increased risk to COVID-19 because of the nature of their work. It is imperative to have high vaccination coverage for this group.The aim of this study is to determine vaccine hesitancy and drivers associated with vaccine hesitancy among dental students at a university in South Africa.A dental school in South Africa was chosen as the setting for this study.An analytical cross-sectional study was conducted by means of an anonymous, online, validated questionnaire to determine vaccine hesitancy.n = 172) students were vaccine not hesitant. The main concerns regarding the vaccines were identified as safety and efficacy of the vaccine. Pressure by family or friends and the university to get vaccinated was evident.Of the 205 dental students participated, 83.9% (Vaccine hesitancy is high despite mandatory vaccination policies in South Africa. Specific drivers contributing to vaccine hesitancy were identified as doubt in the efficacy and safety of the vaccine.This study has highlighted the prevalence of vaccine hesitancy among dental students at University of the Western Cape, prior to compulsory vacccination implementations. According to MacDonald , vaccineNations worldwide are trying to reduce the spread of the COVID-19 virus by enforcing different preventative measures such as physical distancing and wearing of face coverings as well as lockdown and travel restrictions. Regarding the latest omicron variant, there has been a reduction in COVID-19-related deaths and morbidity in South Africa  Oral Health Centres. The secondary aim is to determine the drivers associated with vaccine hesitancy in this population.n = 416) were included in this study and recruited from September 2021 to October 2021. A convenience sampling technique was utilised to recruit participants, as this sampling technique is simple and cost effective  between vaccine hesitancy and whether the participants felt that vaccines were generally effective , participated in this study. Thirty-three participants (16.1%) were vaccine hesitant. Among the participants, there were no statistically significant associations between vaccine hesitancy and demographics, including the year of study, age or sex . Internaffective .p < 0.001) (A majority of the participants did not have vaccine hesitancy . There w< 0.001) .n = 103) with only 4.4% (n = 9) of students admitting ‘excellent’ knowledge (n = 125), ‘health officials’ (n = 125) and ‘social media’ (n = 122). Although 77.1% (n = 158) of participants believed that the vaccine is necessary to combat the pandemic, 27.8% (n = 57) of participants did not fully understand the concept of herd immunity   .n = 140) did not feel pressured to get vaccinated; however, the pressure felt from the university (n = 46) followed by family and friends were reported (n = 39). Almost 45% (n = 90) of participants said that they have doubts regarding the COVID-19 vaccine, with concerns regarding the safety (n = 97) of the vaccine being the major contributing factor. Concerns regarding the efficacy (n = 67) and mistrust in the development of the vaccines (n = 65) were also evident. Interestingly, dental students having doubts regarding the vaccine, 81.5% (n = 167) would recommend the vaccine to their family and friends.Most students , p = 0.031, of experiencing vaccine hesitancy compared to participants who did not experience vaccine hesitancy, respectively  adjusted odds of experiencing vaccine hesitancy,  = 0.008 . In addiesitancy . Furtherectively .There is a very high rate of vaccine hesitancy (16.1%) prevalence in this population. Among the UWC’s dental students, 29.3% do not believe that the vaccines available can prevent COVID-19 and its associated complications, which is similar to a study conducted among 248 dental students from three schools, which reported that 54% of dental students were concerned that the vaccine may not be effective , which is applicable to the age of the sample population. Information on social media is, however, not controlled and may provide misinformation, driven by spectator value and excitement, contributing to doubt and uncertainties among students. A study that was done in France indicated that vaccine acceptance and practices were better when information is obtained from healthcare providers as opposed to receiving information from relatives or from the Internet (Charron, Gautier & Jestin Social media was also identified as a primary source of knowledge (A study done by Kelekar et al.  conducteAccording to the authors’ knowledge this type of study has not been conducted before in Africa. A limitation of this study is the small sample size. This could be because of non-response bias, as vaccine-hesitant participants would be less likely to participate.Vaccine hesitancy among undergraduate dental students at this healthcare facility is astonishingly high. Students still expressed doubts regarding the efficacy, safety, long-term side effects and effectiveness of the vaccines. Further research should be conducted to determine the feelings of students and to record any side effects experienced by dental students, after mandatory vaccination implementation on dental students in South Africa.


Cellular senescence and apoptosis were historically thought of as two distinct cell fate pathways. However, many of the proteins involved are integral to both pathways. In particular, the ability of p53 to regulate both senescence and apoptosis meant it was seen as the decisive factor in these decisions, yet questions remain about its ability to select on its own the most appropriate cell fate according to each situation. Therefore, cell fates are no longer considered fixed endpoints but dynamic states that can be shifted given the right combination of activation and/or inhibitions of cofactors.When a cell is damaged, it must decide how to respond. As a consequence of a variety of stresses, cells can induce well-regulated programmes such as senescence, a persistent proliferative arrest that limits their replication. Alternatively, regulated programmed cell death can be induced to remove the irreversibly damaged cells in a controlled manner. These programmes are mainly triggered and controlled by the tumour suppressor protein p53 and its complex network of effectors, but how it decides between these wildly different responses is not fully understood. This review focuses on the key proteins involved both in the regulation and induction of apoptosis and senescence to examine the key events that determine cell fate following damage. Furthermore, we examine how the regulation and activity of these proteins are altered during the progression of many chronic diseases, including cancer. Over time, cells are subject to a variety of external and endogenous stresses. Faced with these stresses, cells mount an appropriate response with two main end points—survival or death. Survival may mean permanent cell cycle arrest in the form of senescence or repair and continued proliferation after a temporary arrest . Howeverp53 is one of the most well-studied proteins and has a key role in DNA damage repair, cell cycle arrest, apoptosis and senescence. Its domain structure is critical to its ability to participate in the different molecular mechanisms . The N-tIn unstressed cells, p53 is maintained at low levels by the E3 ubiquitin-ligase MDM2. However, when stress is detected, p53 is phosphorylated, which prevents its binding to MDM2 and stabilises its levels . Once stThe DNA damage response (DDR) is a complex pathway that has evolved to detect DNA damage and facilitate its repair. In humans, two proteins central to DDR are ataxia telangiectasia mutated (ATM) and ataxia telangiectasia and RAD3 related (ATR). ATM is primarily involved in responding to double-strand breaks whilst ATR senses stalled or stressed DNA replication forks and is particularly important in detecting DNA damage in the S phase ,11. OnceApoptosis is a well-characterised programme, first described in 1972 as being a morphologically distinct form of cell death . FurtherThe intrinsic or mitochondrial apoptotic pathway is triggered by stresses including oxidative stress, irradiation, DNA damage and treatment with cytotoxic drugs. Crucial in regulating the intrinsic pathway is the BCL-2 family of proteins, which can be divided into three groups based on their function: firstly, the multi-domain anti-apoptotic proteins, BCL-2, BCL-xL, BCL-w, MCL-1 and BFL-1/A1; secondly, the pro-apoptotic effector proteins BAK, BAX and BOK; and finally, the pro-apoptotic BH3-only proteins, BAD, BID, BIM, BMF, HRK, NOXA and PUMA . The relIn response to internal damage, effector proteins BAK or BAX are activated at the outer mitochondrial membrane. Detailed structural and biochemical analysis has determined multiple steps required for both BAK and BAX activation ,23, inclThe extrinsic route to apoptosis, or the death receptor (DR) pathway, is mediated by transmembrane receptors that are members of the tumour necrosis factor (TNF) receptor protein superfamily . These rp53 principally serves as an apoptotic regulator by modulating the expression of key proteins in both the intrinsic and extrinsic pathways, including BCL-2 family proteins, death receptors CD95 and Death Receptor 5 (DR5), APAF-1 and Caspases . AdditioAlthough initiation of apoptosis is often thought of as the point of no return, some cancers have found ways to reverse or halt the process and thus change cell fate, a process known as anastasis . SeveralIn addition to cell death via the canonical apoptotic pathways, p53 has been reported to also be central to several forms of non-apoptotic cell death. One example of this is an alternative p53 driven cell death pathway first identified in experiments where caspase activity was inhibited using the inhibitor ZVAD.fmk . In thisSenescence was first observed in normal human cultured cells . Human fA senescent cell may be identified as being in a state of irreversible cell cycle arrest, though metabolically active while displaying phenotypic changes. Other forms of growth arrest exist, such as quiescence and terminal differentiation, which are distinct from senescence in terms of the pathways triggered and the resultant phenotype. Senescence can be activated by numerous cell stressors, such as DNA damage, hypoxia, oncogene activation and nutrient deprivation, with most mitotic cells in the body, including cancer cells, able to undergo senescence ,49. If tSenescence can occur due to perturbation of the balance between transcriptionally inert heterochromatin or the more open transcriptionally active form euchromatin. The extent to which each conformation exists depends largely on histone modifications such as acetylation or methylation. The nuclei of senescent cells contain areas of facultative heterochromatin known as senescence-associated heterochromatin foci (SAHF), which appear as punctate foci upon DAPI staining . SAHF arSenescence can be caused by stresses such as ionising radiation due to an accumulation of double-strand breaks leading to the activation of ATM and a DDR  53]. Th. Th53]. Oncogene-induced senescence (OIS) occurs when normal cells undergo senescence in response to oncogene activation and acts as a tumour-suppressive mechanism that prevents benign lesions from progressing to malignant tumours . RAS proWhilst the traditional definition of senescence implied that the cell cycle arrest had to be irreversible, some studies are now proposing that cell fate decisions can be changed. Modulating the key proteins involved in cell cycle arrest, such as p53 and p21, may allow cells to escape senescence. Whilst p53 levels in a non-stressed state are low, the pulsatile dynamics of p53 in stress may allow the cell options of quickly switching to sustained levels of p53 and arrest or a drop in levels and return to proliferation. This subtle balance may be therapeutically exploited in the right context to push tumour cells into senescence or potentially remove senescent cells from aged tissues. Additionally, there is growing evidence that the p53–p21 cell cycle arrest pathway is not simply unidirectional but that the dynamics of p21 may affect cell fate decisions following stress. For example, overexpressed p21 has been shown to render glioma cells resistant to chemotherapy-induced apoptosis by allowing the repair of damaged DNA . Moreove−/− cells display increased p53 levels without drug-induced DNA damage, which also correlates with an increased expression of p14ARF that may promote p53 stability by binding to MDM2 [Several studies have revealed functions for p21 aside from cell cycle arrest, which may contribute to determining cell fate. For instance, HCT116/p21 to MDM2 . These c to MDM2 . All thiMutant p53 can also cause normal cells to evade senescence . Near seAlthough therapeutic strategies that cause senescence have been developed over the last few decades, a growing number of studies have shown that TIS may not be a therapeutic endpoint as first thought. A small population of cells can evade growth arrest following a clinically relevant dose of chemotherapy and may contribute to a drug-resistant phenotype, aided by the cytokines and other factors secreted by the cells that have undergone TIS . In partThis suggests that a tumour cell turned senescent may sometimes not be therapeutically relevant and may sometimes even contribute to resistance and relapse. One strategy to bypass this issue would be to first push tumour cells into senescence, followed by the selective killing of these cells using specific compounds . This “one-two punch therapy” approach was demonstrated in liver cancer cells containing p53 mutations induced to senesce by inhibiting CDC7 kinase, which was followed by sertraline treatment to induce apoptosis in these cells through mTOR inhibition . AdditioAt first glance, it would appear that senescence and apoptosis are two distinct cell fate pathways. However, many of the proteins induced are integral to both pathways. The ability of p53 to regulate both senescence and apoptosis makes it an important protein in tumour suppression, as confirmed by the fact that it is mutated in about 50% of all cancers . The majARF, which in turn is stabilised by oncogenic c-MYC transcriptionally upregulating USP10. p14ARF stabilises p53 by sequestering MDM2 in the nucleolus and prevents MDM2 from binding and ubiquitinating p53 [p53 activation in response to oncogenic signalling is prevalent in pre-malignant and malignant cells . OIS canting p53 . In additing p53 . Conversting p53 . p21 hasting p53 ,79. p21 ting p53 . p21-medting p53 . It has ting p53 .As mentioned above, p53 regulates apoptosis by both transcription-dependent and independent mechanisms, the latter requiring p53 to be transported out of the nucleus ,83. FromIt has been observed that p53 binds to BAK and aids in oligomerisation. The binding of p53 to BAK is through the H2 helix, Loop 1 and Loop 3 within the DNA binding domain (DBD) of p53 to the N-terminal side of BAK, specifically the electropositive residues R280 (H2 helix), R248 (L3 loop) and K120 (L1 loop). These residues then interact with the electronegative residues E24, E25 and D160 on BAK , and p532O2), superoxide anion radical (O2•−), nitric oxide (NO), hydroxyl ion (OH−) and hydroxyl radical (OH•), the ions and radicals being highly reactive due to the presence of an unpaired electron. ROS are normally a by-product of mitochondrial oxidative phosphorylation in the electron transport chain (ETC) [2•− and may be converted to H2O2 by superoxide dismutases (SODs), which act as the first line of defence in controlling ROS levels [ROS have been known as chemical entities for over 100 years, and their importance in biological systems has been studied since the 1950s . The reain (ETC) . Not allS levels ,93. AnotS levels . It has S levels . As ROS S levels .The connection between senescence and intracellular oxidants can easily be seen by the application of low concentrations of hydrogen peroxide to human diploid fibroblasts, which causes them to enter a senescent-like growth arrest . AdditioThe anti-apoptotic BCL-2 family of proteins also plays important roles in regulating both apoptosis and senescence, influencing whether a cell undergoes cell death or survives. After oxidative stress, an increase in BCL-2 expression is observed during the growth arrest, but these levels decline during apoptosis . MoreoveCell fate decisions in response to stress were initially seen in a simplistic way as being mainly proportional to the damage exerted. Whether a cell that survived after the necessary repairs entered senescence or died seemed to depend on the magnitude of the insult. However, a more complex picture emerged over the years, particularly with the discovery of the many different functions of p53. For a while, p53 was seen as the decisive factor in these decisions until questions emerged about its ability to select on its own the most appropriate cell fate according to each situation. This gave rise to two antagonistic models. In the first one, p53 was proposed to induce either apoptotic or arrest genes in a selective way, mostly through differential post-translational modifications (p53 smart), while the alternative (p53 dumb) suggested that p53 would induce both sets of genes simultaneously and other factors would help determine which one would dominate .Currently, the most accepted view is likely an amalgam of both hypotheses: cell fate decisions are still not completely understood but are seen as the result of the interaction of many different factors, probably with p53 still at the centre of an intricate network, but not alone at the commanding seat. The conjunction of these modulators is what eventually determines which p53 function eventually prevails . Among tIndeed, identifying the factors that modulate cell fates is particularly relevant in the context of cancer treatments in order to improve therapeutic outcomes. Senescence, once seen as a safe tumour-suppressor mechanism, is now a fate to be avoided since it is considered no longer irreversible or innocuous. Importantly, the accumulation of senescent cells after therapy has been shown to create a microenvironment in the tumour that enhances cancer cell survival and eventually fosters relapse . ConvertMore research is needed to fully understand how cell fate decisions are made and can be modulated. This could lead to a better understanding of an intricate network of biological events but also to improved therapies for many cancers. For this, it will be important to keep p53 centre stage but open the focus enough to include the many helpers that end up contributing to these processes.


Any women with newly diagnosed Stage I–III breast cancer scheduled to receive taxane-containing chemotherapy was eligible. The primary outcome was development of grade 2 or higher CIPN during chemotherapy graded by the clinician before each chemotherapy cycle (NCI-CTCAE v5 criteria). We measured p16 expression in peripheral blood T cells by qPCR before and at the end of chemotherapy. A multivariate model identified risk factors for CIPN and included taxane regimen type, p16Age Gap, a measure of discordance between chronological age and p16 expression, and p16 expression before chemotherapy. Participants with higher p16Age Gap—higher chronological age but lower p16 expression prior to chemotherapy - were at the highest risk. In addition, higher levels of p16 before treatment, regardless of patient age, conferred an increased risk of CIPN. Incidence of CIPN positively correlated with chemotherapy-induced increase in p16 expression, with the largest increase seen in participants with the lowest p16 expression before treatment. We have shown that p16 expression levels before treatment can identify patients at high risk for taxane-induced CIPN. If confirmed, p16 might help guide chemotherapy selection in early breast cancer.Identifying patients at higher risk of chemotherapy-induced peripheral neuropathy (CIPN) is a major unmet need given its high incidence, persistence, and detrimental effect on quality of life. We determined if the expression of  CIPN can limit post-treatment quality of life, particularly important for patients receiving chemotherapy for stages I–III breast cancer5 since most receive a neurotoxic taxane and will have long-term survival. Unfortunately, up to 30% of these patients experience moderate to severe CIPN8. Symptoms occur predominantly in the hands and feet and include burning or shooting pain, paresthesia (numbness/tingling), pain perception abnormalities like allodynia and hyper- or hypo-algesia, temperature sensitivity, weakness, and, rarely, ataxia. In addition, multiple studies have shown that moderate to severe CIPN can be dose-limiting, raising concerns about compromised treatment efficacy10.Chemotherapy-induced peripheral neuropathy (CIPN) is among the most debilitating, common, and persistent chemotherapy toxicities11, with symptoms persisting five or more years post-treatment5 that dramatically impact quality of life14. Numbness in the feet can increase the risk of falling, particularly consequential in older patients where fractures can lead to inpatient rehabilitation and loss of independence17. Unfortunately, drug therapies to treat or prevent CIPN are largely ineffective18, especially among patients receiving taxanes19. Patients with severe, persistent, and painful CIPN may also be prescribed opioids, with a risk for opioid addiction22.Even with dose-reductions, over 50% of patients receiving weekly paclitaxel experience limited recovery from CIPN26 and/or selection of a less neurotoxic agent. In Stages I–III breast cancer, neurotoxic taxanes (docetaxel and paclitaxel) are commonly used in both the adjuvant and neoadjuvant settings. Paclitaxel confers a much greater risk of CIPN than docetaxel27, therefore docetaxel may be preferred in at-risk patients. In addition, several preventive pharmacotherapies are under development28.Given the potential severity of symptoms and lack of effective treatments, CIPN prevention becomes critical. Available strategies include cryotherapy31, though there is no consensus about their relative importance or application in CIPN prevention2. Recently, cellular senescence was found to positively associate with cisplatin-induced peripheral neuropathy in mice, and depletion of senescent cells abolished neuropathy32.Identifying patients at-risk of CIPN is essential for prevention. Epidemiological risk factors include diabetes, obesity, and age39. Senescent cells undergo permanent growth arrest, are resistant to apoptosis, and secrete both inflammatory and pro-fibrotic cytokines, disrupting tissue function and homeostasis41. Recent studies elegantly demonstrated that induction of senescence in just the immune compartment, and T cells specifically, can induce both senescence and organ damage in tissues throughout the body43. Expression of p16INK4a (p16) mRNA in peripheral blood T lymphocytes has emerged as a key biomarker of senescence and a measure of senescent cell load44.Cellular senescence is a fundamental mechanism of aging and plays a causative role in nearly all chronic age-related diseases and physical declinep16 expression would associate with the risk of CIPN.Cellular senescence has not been evaluated as a risk factor for peripheral neuropathy in humans. We hypothesized that 27. Overall, 29% of participants experienced grade 2 or higher CIPN, of which 82% received paclitaxel and 18% docetaxel-based therapy. In a univariate analysis, none of the patient or clinical characteristics (except for chemotherapy regimen) were different between the CIPN and no CIPN groups, including age , diabetes  and p16 expression .Characteristics of 152 study participants with early-stage breast cancer receiving taxane-containing chemotherapies are shown in Table p16 and comorbidities may not be independent (see Methods for details). Taxane type (paclitaxel vs docetaxel) was also included given the difference in CIPN incidence between these two agents. The optimal model from these variables (Model 1) is shown in Table p16 expression before chemotherapy, chronological age, arthritis, and osteoporosis, contributed to model performance.Since no variables in Table p16 and age in the univariate vs. multivariate analyses prompted us to develop a measure called p16Age Gap, the difference between an individual patient’s pre-treatment p16 and population-average p16 levels by age. First, we developed a method to convert p16 expression from log2 arbitrary units into years, and then directly compared p16-based age and chronological age (see Methods). Figure p16, with p16 converted to years (p16Age), and the difference between p16 and chronological age (p16Age Gap). p16Age Gap can also be thought of as a residual in the p16/chronological age regression model. A negative p16Age Gap suggests that an individual has p16 expression levels below an age-appropriate population mean; a p16Age Gap around zero suggests that p16 expression is similar to the population mean; and positive p16Age Gap signifies p16 expression above the population mean.Differences in the behavior of p16 (log2), p16Age, p16Age Gap, and chronological age in this study cohort are shown in Fig. p = 0.94, Student’s t-test) , or older participants who are molecularly younger (negative p16Age Gap). p16Age Gap is strongly associated with p16Age  Fig. , demonstp16, and taxane shown to achieve similar performance to Model 1 (see Arc and BIC). When variables were analyzed for their individual contributions to the CIPN outcome (see Methods), p16Age Gap contributed 41% to the model as an individual predictor and 52% when considered with pre-chemotherapy p16 expression. Patients with a negative p16Age Gap  were at a higher risk for CIPN . Interestingly however, higher pre-chemotherapy p16 expression was also associated with a higher risk of CIPN in a multivariate model .To assess the role of this new measure, p16Age Gap, as a predictor of CIPN risk, we built a second regression model Table , Model 2The probability of CIPN in patients receiving paclitaxel- versus docetaxel-based chemotherapy was derived from regression Model 2 and shown in Fig. In addition to the regression model, we used the same variables to build a neural network to predict CIPN (see Methods). The relationship between the probability of CIPN and p16Age Gap as defined by the neural network algorithm is shown in Fig. p16 expression may be at higher risk of CIPN. We previously showed that p16 expression prior to chemotherapy is inversely correlated with the magnitude of chemotherapy-induced p16 increase45  as patients whose p16 did not change  as well as patients with high p16 exression levels were at the highest risk for CIPN. Although our findings of higher CIPN risk for those with age-inappropriately low p16 (negative p16Age Gap) initially seemed counterintuitive, we observed that patients with lower baseline p16 expression are more likely to have a larger chemotherapy-induced increase in p1645  is associated with highest CIPN risk  to Model 2 did not change model performance . This reduction in velocity might be perceived by the brain as more severe CIPN. Nerve conduction velocity studies might verify this hypothesis but are beyond the scope of this study.Peripheral neurotoxicity mechanisms of anticancer drugs are not fully understood and are likely to be complex. One hypothesis that could explain our findings centers on age-related changes in nerve conduction velocity. Because nerve conduction velocity is slower in older patientsp16 expression is modulated by p16 levels prior to chemotherapy. Tsygankov et al showed that p16 expression plateaus in late middle age after increasing exponentially with age in early to mid-adulthood47. Thus, participants with lower baseline p16 levels may have the capacity for a larger increase in p16 following chemotherapy, while participants with higher baseline p16 levels may have already reached a maximum threshold for senescent cell accumulation, suggesting that p16 levels cannot increase further without causing morbidity. p16Age Gap, measured at baseline, can therefore be interpreted as a predictor of patients that will accumulate more senescent cells in response to chemotherapy, leading to higher p16 expression and CIPN. Regardless of mechanism, our results, once validated, would allow identification of high risk patients, who could then consider CIPN prevention options like cryotherapy, substituting docetaxel for paclitaxel, or chemotherapy regimens without taxanes. Such high-risk patients would also be ideal candiates to be included in trials evaluating CIPN preventive strategies.Presently, it is unclear why chemotherapy-induced 32. However, in this study p16 expression was measured in dorsal root ganglia and not in blood. Although these discoveries may lead to ways to prevent CIPN through depletion of senescent cells (i.e. senolytic therapies), much work remains to understand human senescence and identify safe and efficacious senolytic therapies.While our study provides evidence for a connection between p16, senescence, and CIPN in humans, a causal relationship between senescence and CIPN has been demonstarted in mice. Removal of the p16+ senescent cells in cisplatin-treated mice completely reversed symptoms of CIPN48.In this study, we did not find diabetes, obesity, or age to be important contributors to multivariate models of CIPN. A larger study is now underway  that will provide the opportunity to validate p16Age Gap findings, further interrogate comorbidities such as diabetes and age as risk factors, and analyze other variables not available in this study such as taxane dose intensity and metabolism. There is also great interest in genetic polymorhisms as predictors of CIPN with different chemotherapeutic agents, including taxanes, which may ulimately improve risk predictionp16 versus age but, as noted above, the best fit between p16 and chronological age is likely non-linear later in life. This may explain the extreme negative p16Age Gap values for some patients in our analysis. We are currenlty conducting a study to build a computational model of senescence in multiple patient cohorts to provide a better estimator of p16Age Gap. But regardless of the absolute value for the p16Age Gap, low p16 expression in patients with higher chronologic age is a significant risk factor.In addition to the sample size, another limitation of this study is that measurement of p16Age Gap was calculated using linear regression of 27. Patients with age-inappropriate low p16 may be offered docetaxel regimens, possibly in combination with other efforts to reduce CIPN such as cryotherapy, or closer monitoring for CIPN symptoms26. Additionally, anthracycline regimens that lack taxanes but have similar efficacy but different toxicity profiles, might be preferable for some pateints where even moderate risk of loss of function due to neuropathy may be unacceptable .Our ongoing studies are designed to validate this p16Age Gap-based model for CIPN prediction for early-stage breast cancer patients and advance it into a lab-developed test to be used clinically to obtain a CIPN risk score. The planned studies will use patient reported outcomes (EORTC-QLQ-CIPN20) in addition to clinician-assessed (NCI-CTCAE) toxicity. If validated, this score may help to guide chemotherapy selection, given that regimens for this indication usually employ one of two different taxanes (paclitaxel or docetaxel) with similar efficacy but different risks of CIPN incidenceIn summary, measures of senescent cell load could ultimately help guide clinicians to avoid dose-limiting toxicities and improve quality of life in breast cancer patients. These observations may also be clinically relevant in other cancers that are treated with neurotoxic chemotherapies.7 and had p16 mRNA expression measures were included in this analysis. All patients who were offered and consented to adjuvant or neoadjuvant chemotherapy were eligible to participate. Studies were led by the University of North Carolina with REX Healthcare, Ohio State University, MD Andersen, and Duke University participating, and were approved by the IRB of participating sites. The study was performed in agreement with the guidelines of the International Conference on Harmonization, the ethical principles in the Declaration of Helsinki, and all applicable regulations. All patients provided written informed consent before participation in any study-related activities.Women newly diagnosed with stage I–III breast cancer, enrolled in NCT02167932 or NCT02328313, who received a chemotherapy regimen containing a taxane7. For weekly regimens toxicity data was collected every other week so that all toxicity reports were either biweekly or triweekly. Briefly, CIPN symptoms were graded by an oncologist using the NCI-CTCAE v5 system. Symptoms were graded as none (0), mild (1), moderate (2), severe (3), or life-threatening (4). Clinicians assessed patients prior to each cycle of chemotherapy. In this study, measures to prevent CIPN such as cryotherapy or prescription medications were not captured as they were not widely utilized when the study was conducted.Chemotherapy regimens were classified as paclitaxel- or docetaxel-containing. CIPN toxicity data was collected as describedp16 mRNA expression was analyzed by real-time qPCR as described51, using reagents provided by Sapere Bio (SapereX). Positive and negative controls were included in each run; overall precision of p16 measurement  was 0.8 Ct. Each measurement was performed once on each sample.Peripheral blood samples were collected prior to starting chemotherapy and again at the end of chemotherapy, T cells were isolated, and p16 expression in 633 subjects52. The p16 value corresponding to the participants’ chronological age at the start of chemotherapy was then subtracted from p16Age to calculate p16Age Gap.P16 expression levels were converted into equivalent years of aging (p16Age) using a linear regression formula derived from analysis of Chi-square tests, Fisher exact tests, and Student t tests were used to compare patient and clinical characteristics. All tests were two-sided with statistical significance set at 0.05. Analyses were conducted using SAS/JMP 15.1 software .p16 prior to chemotherapy, comorbidities, and their interactions were tested, as variables may not be independent. Comorbidities considered were obesity (BMI ≥ 30), diabetes, peripheral circulatory issues, osteoporosis, arthritis, high blood pressure, emphysema, and liver or kidney disease. Coronary heart disease and stroke were not used due to low prevalence in the CIPN group. Variables and their interactions were considered in the regression model and retained by forward stepwise addition to minimize the Akaike information criterion (AICc). The resulting CIPN probabilities were calculated and plotted. To determine the importance of each variable we calculated indices measuring the importance of factors in a model, in a manner independent of model type and fitting method. The fitted model is used only in calculating predicted values. This method estimates the variability in the predicted response based on a range of variation for each factor. If variation in the factor causes high variability in the response, then that effect is important to the model. Calculations assumed each variable was independent. In this analysis, for each factor, Monte Carlo samples were drawn from a uniform distribution defined by minimum and maximum observed values. Main Effect of importance reflects the relative contribution of that factor alone. Total Effect of importance reflects the relative contribution of that factor both alone and in combination with other factors. To mitigate overfitting when building a neural network model, 1/3 of the data set was reserved as a validation set using a holdback function and learning rate of 0.1. The model was built using a TanH activation function to fit one hidden layer with three nodes. The resulting probabilities of CIPN were calculated and plotted.To generate a multivariate linear regression model of CIPN risk, chronological age, race, p16 and CIPN incidence, p16 expression measured prior to chemotherapy was subtracted from p16 expression measured at the end of treatment and stratified into 2 groups: p16 increase  and no increase (p16 change ≤ 0.4). Fisher’s exact test (2-sided) was used for group comparison.For the association between chemotherapy-induced change in Further information on research design is available in the Supplementary MaterialReporting Summary