good afternoon everyone the biochemical Society in Portland Press are pleased to welcome you to this webinar which is part of our biochemistry Focus webinar Series so topics in this series include different research areas in the molecular biosciences as well as practical sessions to support Career Development each webinar will give you the opportunity to ask questions and we welcome suggestions for future topics and speakers to featur in our webinar series so please see the website for more deta
ils I'm Dr Van Pekovic vaugh I'm a senior lecture in sadian muscular scal physiology in the department of muscular sceletal and aging Sciences at the University of Liverpool within the biochemical Society I'm a Committee Member of research area six which is biological systems I'm also one of the network coordinators of the ECM age Network one of the 11 ukri funded interdisciplinary aging networks which bring together EXP expertise in key aspects of Aging Matrix Biology chronobiology computationa
l modeling and tissue engineering across UK and also offers free membership and pum priming and exchange funding to support a variety of projects to learn more please go to ww. net.org now our speakers today are members of the ECM Network and I'm delighted to chare this uh webinar today in tled extracellular Matrix and Redux signaling axis from cancer to tissue repair and smarter regenerative therapies this is part of the biochemistry Focus webinar series a dedicated early career research progra
m of webinars we are therefore excited to provide you this opportunity today for several of our speakers Mia Tamara Alexander and abishek to share their fascinating work within the molecular biosciences Community before I hand over to our first speaker I'd like to mention that questions will be asked at the end of the webinar so please do send your questions during the talks as we go along if you have a question just type it in the question box as shown in the image on the screen stating who you
r question is for and we will try to answer as many questions as possible at the end so our first Speaker today is Mia Muhammad from University of s Mia is a final year PhD student at s she's undertaking muscular scal research in Dr Javan nyso lab Mia has a background in biomedical sciences and a masters in stem cell and regenerative biology after completing her PhD Mia plans to continue her research on designing new technologies in tissue engineering so today Mia will present her work entitled
proteomic insights of sex and age differences in the articular cartilage I can see your talk now great please go thank you for that um and thank you for this opportunity as well so in today's talk I'll be talking about our proteomic insights of sex and age differences in the Artica cartridge so the Artica cartrid is a crucial tissue located at the end of our joints this enables for efficient joint movement it's made up of cells called the condra sites and these cells constantly remodel the thick
uh tissue Matrix and gives it elasticity and resistance to pressure The Matrix is mostly composed of collagens Brans and water which all determine its mechanical properties factors like aging and sex can change the matrix by affecting its structure and function of the tissue and these changes may lead to osteoarthritis a chronic joint disease that affects 73% of people over the age of 55 worldwide and is more common in females however despite it high occurrence in women only 42% of the studies
consider gender differences which highlights the need for more research in this area so in order to fully understand this Association our project aims to understand young and old sex differences of the articular cage extra Matrix for a better translational understanding of aging and predisposition of OA first we performed the protom analysis of the extra cellia Matrix isolated from old and young mice this involved 12 murine Artic cartilage samples consisting of three old females three young fema
les three old males and three young young males these samples then underwent tandem Mass tag Mass spectroscopy which is a labeled quantitative proteomic approach that allows the comparison of protein levels in multiple samples using specific math tagging and then the label samples are combined prior to the subsequent processing steps which which eliminates runto run variability which can be an issue when samples are analyzed consecutively and then this uh the data was followed by bioinformatic a
nalysis the initial set of analysis then we was carried out and this involved a principles component analysis so this plot accounts for the variance between samples and triplicate samples um triplicates of the samples so from this plot we can see three out of the four sample groups are shown to be consistent across the triplicates as their plots are close in proximity however as you can see as a whole you can still observe four uh whole protein groups being old males young males old females and
young females in panel B we found 2,484 proteins which had a high FDR false Discovery rate or 5% were identified across the four groups and we observe 4% sorry 12% of those proteins were extra Matrix proteins which were manually identified using Unico database this was then confirmed in a gene set enrichment analysis as extracellular Matrix related Pathways were identified to be down regulated in the ages in I and dou I whereas in uh triple I and four uh we can see that the ages aging Sexes show
ed opposite Trends uh which displayed same the same Pathways which were U regulated in the Aging males and down regulated in the Aging females so overall these analysis determine that there are differences between the Aging sexes in relation to cartilage ECM remodeling next we show differential modulation of these identified extra matri fortive proteins using um volcano plots so these plots were able to show the specific proteins that were significantly modulated in each comparison group and as
you can see there's more significant proteins uh identified When comparing the different sectors at the same ages so the last two uh volcano plots and this supports our findings from the last slide we also conducted a string protein to protein interaction analysis that shows how these modulated proteins interact with each other so this mostly mostly displayed down or uppr protein Trends uh were interacting with each other with similar similar modulated protein and then uh this can further help i
dentify the ECM related Parkways that they are affected in additionally thanks to the pump Prime ECM EC funding we were able to go deeper into the proteomic analysis as we were as we identified structure Associated differences of those ECM related proteins using peptide location PR fingerprinting so in the collaboration with the University of Manchester we adapted their tool for evaluating age and sex related structural modification in murine articular proteum articular proteum using uh tryptic
peptides acquired from the tandem mpect analysis so this tool works by dividing the proteins primary sequence into 50 amino acid segments which are then Quantified using their abundances and then m to the respective segments so here in two is a line graph showing the normalized peptide abundances comparing the young and old um cartilages of or fexes and beneath you can see the amino acid segments segments aligned with the do domains and regions that they are part of so in our analysis we compare
d young versus old males and females as well as young males and females versus old males and females so as you can see this plf analysis established more than double the number of significant proteins showing structure associated changes than we had previously measured using the abundances values alone so as an example of one part of the analysis we categorized the proteins using Panther classification system and found 27 extra solo Matrix proteins which were further separated into structural pr
oteins associated with Matrix proteins and proteoglycans so the plf analysis was able to identify structural Associated differences along the proteins so as an example in call 50 Alpha One a protein which stabilizes the extra Matrix you can see a conserved modulation of the structure associate differences between the male and females and here in lamin laminin G like domain there's a higher peptide deal in both of the sectors this is expected as this domain um influences cell adhesion which is an
important characteristic of the tissue the further down you go you can see higher peptide yield in the triple helical region and of the old which implies the alteration of a higher order structure of the protein a sex Divergent structure Associated difference was shown in a pericellular matrix located protein collagen 11 Alpha 2 the fular collagen nc1 domange shows a higher pepal in the young females and old in the males this demain is susceptible to protolytic cleavage which could change the f
unction of protein as a whole um and as a whole of this analysis it helps identify sex differences which would be great for potentially identifying sex specific targets for development of targe of therapeutic protein interventions so for our first experimental application which was also funded by the EC pump priming in collaboration with the universities of Oxford and Southampton these experiments involved identifying A protein that was differentially up regulated in the in aging but was conserv
ed between the genders using the Mass Effect data we had gathered we established established collagen 5 Alpha 2 to be further assessed for its impact in aging of the extracellular Matrix um this protein has been previously associated with genetic mutation in in Elo danlo syndrome which among among its symptoms um include hypermobility and skin that appears prematurely age but also in this publication this Gene has been proposed as a biomarker of the maturity of Aging of the human articular carti
lage so with collaboration uh with our universities um we decided to generate a young inv cartilage model using gelatin meth method Cal to assess the phenotypic effect on human articular condra sites and this model is currently undergoing characterization but however we have seen promising initial results as this F Cyrus red staining shows an increase of stain intensity from uh day four to week three uh of cultivation so uh this shows that the gel can accommodate the cells as there's an increase
of collagen production overall we believe this data provides a significant insight to the sex related differences of the articular cartilage and using the same Tool uh similar data can be acquired for other tissues and disorders also we have a better understanding of sex differences in the cartilage uh biology which can help contribute to a smarter personalized treatments for parage related diseases and fin sorry and um finally our proteomic analysis has acquired a huge amount of normal data wh
ich could pay a basis of many future research so um I would like to take this opportunity to thank my funders uh Dunhill medical trust and EC our collaborators with the University of Manchester Oxford and Southampton for helping us to excel in our research and determine all findings and finally I would like to thank my supervisor javanna and our research group for all the support motivation and inspiration you have provided me in my journey thank you all for listening thank you so much Mia that
was a great talk please put in some questions for me as talk and we will discuss this at the end of our webinar um now for the next talk our invited speaker is Tamara zaket from University of Belgrade Tamara has a master's degree in molecular biology and Physiology and is currently a PhD student at The Institute for biological research University of Belgrade in Professor B cor's lab tamaras PhD thesis focuses on Redux and metabolic reprogramming in breast cancer and today she will present her wo
rk entitled Redux profiles as the pivotal features of tumor adipose tissue Corporation in breast cancer patients over to you Tamara uh thank you van and thank you for this opportunity uh so as Vana said uh the topic of my talk today uh will be Redux profiles as the pillot of features of tumor osti Corporation in breast cancer patients uh breast cancer uh is the most common malignancy among women worldwide where one in eight women will be diagnosed with breast cancer during uh their lifetime and
except uh gender there are other risk factors that affect breast cancer such as age personal history family history reproductive history or some lifestyle related factors such as obesity the relationship between obesity and breast cancer in post menopausa women is pretty much well known and around 30% uh the risk factor for breast cancer is increased in obese women postmenopausal women however uh this relationship is not very well known in premenopausal young women uh since there were many confl
icting results some of them showing positive some of them negative effects of obesity and breast cancer progression this question is really important since women diagnosed at young age have a lower survival rates and they experience poorer quality of life since they're often diagnosed at a very later stage of disease so understanding the mechanisms that underly this relationship between neoplastic transformation and obesity in premen andal women is of great importance we could consider breast ca
ncer as a complex pseudo organ due to many reasons uh behavior of breast cancer cells alone depend on their interaction with the tumor micro environment uh its stromal components and extracellular Matrix specifically in breast cancer the main component uh of the tumor micro environment are cancer Associated aryes and they contribute to cancer progression metastasis and therapeutic resistance by supplying breast cancer cells with growth factors ocin cines metabolic substrates and this communicati
on is a two-way communication since they both affect on each other which has been shown in many studies uh however the precise role of cancer associated osy in establishing breast cancer phenotype and specifically the Redux profiles of both breast cancer and cancer Associated adpo sites are still under question so uh we wanted to examine uh the Hallmarks of neoplastic transformation reflected in Redux reprogramming in both bre breast cancer and cancer Associated OS tissue in premenopausal breast
cancer patients uh we had both paired biopsies of tumor and arpus tissue which were divided uh by pathohistological analysis tumor tissue was divided into benign FIB denoma as well as into malignant type A invasive ductal carcinoma while arpus tissue was divided into breast arpus tissue or cancer associate arpus tissue women were divided dived by body mass index into normal weight and overweight or obese women making four groups total normal weight women with benign tumors overweight obese wome
n with benign tumors normal weight with malignant and overweight women with malignant tumors firstly uh we examine the Redux profile of breast cancer tissue uh we observed uh increase protein expressions of the main antioxidant defense enzymes in maligant tumor tissue compared to benign tumor tissue irrespective of obesity uh next we wanted to see um indirect to to indirectly assess rust Levels by measuring for hedro ananal protein levels as well as imun fluoresence which showed no significant d
ifferences between the groups uh these results point to the high redu threshold that is present in breast cancer tissue which was already uh reported and it is in accordance with previous results and it actually does not point to increased oxidative uh stress just to increase Redux threshold additionally we examine the protein expression of Nrf2 as the main um transcriptional regulator and we see its protein level increase only in obese women with malignant patients this increase could be explai
ned uh since means uh the new role of Nrf2 in metabolic programing reprogramming is uh recognized and it is well known that obese uh patients have altered uh metabolism so we can see that the Redux response of breast cancer tissue is actually uh here not uh associated with obesity unlike uh tumor tissue We examined cancer Associated arpus tissue that uh displayed increased protein expression of main antioxidant defense enzymes only in normal weight women and this was in accordance with the prote
in expression of Nrf2 pointing to its role in the regulation of redu programming of cancer Associated arpus tissue uh additionally uh we measured uh the four hydroxyl modified proteins their level protein level level and imuno florescence where we observed increased um levels in only in obese women with malignant tumors this was also expected uh since obese women are known to have a pro increased prooxidant State uh along with the reduced antioxidant capacity which was shown with expression of a
ntioxidant defense enzymes uh since the tumor micro environment of breast cancer is U heterogenous uh we wanted to examine s specific local ation of antioxidant defense enzymes in both cancer tissue and adipose tissue we observed increased uh expression of antioxidant defense enzymes in malignant tumor tissue compared to benign tumor tissue just like our vestern blood results and their specific localizations in either mitochondria or cytoplasm we also examined Regional differences in the express
ion of this enzymes where we observed that clusters of cancer cells at the invasive front uh were much more immunopositive for antioxid defense enzymes than in cancer cells in tumor core we did the same analysis on the cancer Associated Arbus tissue where we also observed their increased uh expression in women with malignant tumors they specifically localize just like in cancer cells and the expression of these enzymes increases with proximity to cancer cells uh we here confirmed that there is a
high redex homeostasis threshold in both cancer tissue and cancer associate therapist tissue and their their responses Redux responses are synchron and finally uh we uh examine serial tissue sections on light microscope where we observed only in malignant tissue and especially in uh obese patients that there is a physical association between these two tissues with extracellular Matrix serving as a connecting tissue between the two we can draw a few conclusions from these results that breast can
cer and uh is associated OS tissue exhibit synchronous tissue responses when it comes to Redux reprogramming that their mirroring phenotypes reveal tissue specific High Redux homostasis thresholds their complementary differences points to their dependent cooperation and that obesity might change the Redux interface of cancer edus tissue cross talk finally I would like to thank my team from the institute for biological research sisha stankovich led by Professor V kach and our colleagues from facu
lty of biology faculty of medicine and Institute of live course in medical sciences and thank you all for your attention thank you for lovely talk we will now go to our next speaker our third speaker is Alex easle from University of Manchester Alex is a new lecturer in skin Health at Manchester funded by Walgreens boots Alliance Alex is developing novel Mass spectrometry tools for identification of extracellular Matrix Targets in aging and connective tissue diseases he has contributed to the des
ign of new matrine peptides used in the skin cosmetic future renew product line launched by boots in 2023 and has also developed in vitro human skill cell culture assays for multiomic characterization this has all led to four patterns where he's a named coinventor today Alex is presenting his work entitled Matrix derived peptides for the Regeneration of photo AG schin over to you Alex apologies is that is that better can you hear me okay now yes perfect am I am my screen showing it's showing tha
nk you excellent so thank you very much to you van and to the rest of the organizers for giving me the opportunity to present today I'll be talking a little bit about a large collaborative project we've been running over the last six seven years together with our industrial Partners at at Walgreens boots Alliance so the first important thing to note is that ECM components are markedly long lived for example only 80% of collagen 2 turns over in cartilage in an average 80y old and as far as we can
tell elastic fibers uh do not turn over so the ones that are there from birth remain present throughout your lifetime this means that ECM components like elastic fibers can accumulate damage over time uh through repeated exposure to aging mechanisms like um reactive oxygen species Ross uh proteases and UV in photoexposed skin which can lead to fragmentation and degeneration of their architectures so the first question becomes are we able to predict which skin ECM components are susceptible to t
hese damage mechanisms so when it comes to UV and photodynamically induced Ross our Labs have shown that susceptibility to these mechanisms scales with the content of certain UV Ross absorbing amino acids namely cysteine methionine tryptophan and tyrosine u meaning we can predict UV raw susceptible ECM proteins based on the presence of these residues prote suceptibility however is harder to predict as it relies on higher order structure as well as amino acid sequence there are machine learning a
lgorithms capable of predicting um this like Prosper for example however we found that this didn't work very well with ECM and so together with our colleague matis oal we developed our own um called the Manchester pep Manchester proteum susceptibility calculator which worked U much better when it came to um when we validated it experimentally this means that we can predict proteas stability um on proteins based on their cleavage Cy load uh and even the fragments that are yielded as a result of t
his cleavage so why is it important to predict ECM protein damage and fragmentation um well that's because some CCM fragments called major kinds are able to modulate cell behaviors like migration apoptosis proliferation uh meaning that some major kinds have the capacity to drive tissue repair and maybe even ECM deposition and indeed maxide peptides are currently used within the anti-aging cosmetical um industry with some proven efficacy however there's no clear hypothesis that drives new discove
ry of bioactive peptides so we hypothesize that small bioactive pepti es also known as matri kinds that are capable of skin regeneration can be predicted via insilico digestion of dermal ECM proteins through the action of proteases we selected 27 Target proteins based on their their predicted UV Ross and protea susceptibilities uh and they and they're being previously reported as affected aging skin we use our machine learning algorithm to predict the cleavage products of these proteins by relev
ant ECM cleaving proteases and this Pro alone led to around a thousand you thousands of possible peptides which we filtered down to 453 based on the length um we only wanted four to five amino acid long peptides which are capable of of penetrating skin more readily um our partners at sederma then filtered those based on their manufacturability and stability this resulted in a final list of eight ECM typic tetrapeptides which we could which could be synthesized by our industrial Partners all of w
hich came from a a diverse source of ECM proteins including collagens ECM glycoproteins Etc so now that we had our eight peptide matrikine candidates we wanted to know if they could enhance their position of keym markers in primary hemmal fire blasts and importantly if they exhibit differential effects on cell activity and this work was carried out by our PhD student Nathan who has since passed his vior I'm happy to say um so the first thing we found through immun florescence andyes was that all
eight peptides do enhance the deposition of key ECM markers when exposed to skin fiber blast in vitro but interestingly they had differential effects with some such as P1 um and p7 significantly increasing fibril in one um and others like P4 and P5 increasing prolen one and fibrant for example um so this shows that depending on the target sequence these matri kind peptides seem to Target unique processes for ECM deposition we also extracted The Matrix and secretomes from peptid treated dermopla
st and analyzed them by prote proteic masspec and again found that they each had differential effects with some like P1 um enhancing multiple ECM deposition and tissue generation protein classes um red being enhanced in the bubble plot whereas others like p7 um suppressing many of these classes it's clear that all eight peptides are capable of modulating ECM deposition by skin fireblast in different ways but we wanted a deeper understanding of their potential for regeneration so we selected two
out of these eight peptides for further study peptide one which is um GP kg amino acid sequence and p7 which was the lsvd amino acid sequence um which were chosen uh because their sequences were found in several ECM components and um because they both they're both capable of enhancing ECM deposition uh both on the marker and proteomic level so to help Define the effect of these two peptides we incubated primary fire blast with three different um skin um from different three different skin sites
for 12 hours with our peptides extract extracted their total RNA and analyze them by RNA seek and the first thing we found by principal component analysis which was no surprise that the transcripton clustered by sight as in where the skin came from um but if we do look at the individual pcas we can see that these peptides are leading to large changes in transcriptional activity um and indeed we found these peptides enhan gene expression of of Pathways pertinent to ECM remodeling um as well as se
lf proliferation and even Ross response we ran a parallel proteomic analysis of the secreted Matrix and this also showed uh shifts in in matone profile following peptide treatments we next wanted to know whether these peptides could act synergistically on a fire blast and so we treated cells this time from the same site butok with a combination of um the two peptides and found that they had a strong effect on the transcriptional activity um um in the secreted matome of thaly blast as strong in f
act as our positive control all trans retinoic acid which is a vitamin a derivative and one of of the most research bioactives um used to to rejuvenate photoaging skin you can see that the combination uh treated group clustered nicely compared to the control and even um against the retinoic acid um showing that peptides have a strong um but differential um effect um even to the positive control uh and like the individual treatments we found that peptide combination enhanced transcriptional Pathw
ays pertinent to ECM remodeling as well perhaps most um importantly we found that the combination of peptides 1 and seven led to a higher number of upregulated ECM Associated proteins compared to individual peptide treatments highlighting the fact that these peptides really do act synergistically to enhance ECM production at least in vitro so we know these peptide major kinds show promising activities in vro especially in combination and of course the next step is to test this in Vivo so our ind
ustrial Partners at boots created a topical formulation containing our combination blend um which we assessed in skin patch tests of human volunteers which was carried out in collaboration with Professor Rachel Watson and doctors Abby lton and Bez Mambo here at the University of Manchester we applied it to photoage forearms of eight healthy individuals for 12 days the treatments were compared um to anud control a vehicle control which is made up of the cream exian but without the peptides and al
so against an ALR retinoic acid positive control punch biopsies were then taken and analyzed by amist chemistry for fiin microf fibral and transcriptomics as well if you think back to the first slide I showed the elastic fibers which are made up of fiin microf fial and elastin are the first components to degenerate in photoaging skin um and you can see in our control photoage forearms a lack of fulin fluorescent in the pillar dermis encouragingly we found um that um the peptide combination treat
ment led to the new deposition fibr and microfibrils in this region and that this was significantly different as effective as our positive control or trans retinoic acid our transatomic analysis showed that exposure to the peptide formulations not only affected bulk changes in gene expression and skin but also the enhancement of biological processes crucial to skin regeneration including um the epidermal maturation of keratinocytes development of Skin Barrier um expression of ECM components um e
lastic fiber deposition as well as modulation of biomechanical um Pathways um pertinent to biomechanical properties um so finally I just want to say that these peptides um peptide 1 and seven um are now um they've been Incorporated in boots' new number seven product launched last year future renew so literally um this collaboration project going from in silico to in Vivo are not launched in an anti-aging cream which I think is pretty amazing this is of course made possible by Professor Mike sher
ret who led the collaboration and our uh Partners at Boots Mike Bell Dr Mike Bell and Dr Ellie Bradley uh and this just to say thank you to the whole team both at University of Manchester WBA so boots and sder for making this work possible thank you very much thank you Alex for that fascinating talk and I'm sure this our attendees will be Keen to put some questions in question box about your work and the future of this work um and now for the next speaker um which is our fourth and final speaker
today is abishek Mahajan from clatterbridge cancer center Liverpool Dr Mahajan is a consultant radiologist at the Clutter Bridge Center Liverpool with special interest in headen NE thoratic and neurological cancers he's been an active contributor to the field of AI pck cancers neurooncology and oncology literature by authoring hundreds of Publications several book chapters and also has written and edited a textbook on oncological Imaging today he will present his work entitled Imaging based ass
essment sarcopenia and its implications on outcomes in oncology over to you AB thank you I can see your slide now oh thank you um thank you for the opportunity to speak at this webinar I think I'm I'm just the odd man out here uh which is probably speaking on something which we do in the clinics and how we assess sopin and its implication in oncology so a to give a background sarcopenia is an important subject in the current field of oncology because it not only predicts outcomes but also assess
es whether the patient can handle the Cho chemotherapy and radiotherapy patients who are actually sarcopenic tend to do worse in terms of progression fee and overall survival as well as response to therapy compared to the patients who are normal weight with nonsarcopenic and something which we now commonly come across is sarcopenic obesity that means their BMI is normal or maybe obese but their muscle quality is very poor so what we understand from sarcopenia is it's a syndrome characterized by
generalized loss of skeletal mass and also the strength of the uh muscle which actually denotes the body composition and also reflects on the nutritional status of the patient so as per the uh European consensus guidelines the the pr sarcopenic patients are the one who have loss of uh muscle strength once the muscle quantity and quality starts to deteriorate that kinds of uh leads to sarop sarcopenia and once there's loss of performance that means the patient is unable to do day-to-day activitie
s that is seious sarcopenia so this is what we try to analyze in our clinics H we assess the BMI we look at the nutritional status we try to upregulate the nutrition to see whether the patients can do better during the therapy and in terms of overall survival however uh primary primary sarcopenia which is related to aging can add on to the cancer related secondary sarcopenia and make the patient very caic so what happens in uh the oncology is we see that there are certain factors which you guys
would be more aware that the tumor necrosis alphafactor interlukin which acts on the muscle leads to lipolysis thermogenesis and Browning which actually is the causitive factor behind loss of muscle mass increased viseral obesity and increased visel fat that in turns leads to cancer CIA and once these cancer patients receive chemotherapy they have higher incidence of GI toxicities they have higher myis they their response uh to chemotherapy is less and they have higher incidence of chemol relate
d overall toxicities that reduces the amount of CH uh Cycles given to a patient that means a patient who sarcopenic may not receive adequate number of chemotherapy cycles and if the sarcopenia is not corrected a full treatment may not be provided to the patient and that adds on to the overall survival of the patient keeping in this mind we explored way back in 2015 uh that how could we evaluate the sarcopenia on Imaging which could play as a surrogate marker at the time of staging of the patient
to understand whether these patients can be subjected to additional support uh with nutrition benefit supplements and uh we found that the patient BMI wasn't a true representative of the uh overall nutrition status as seen in these two patients you can see that the patient BMI in these two cases was uh near comparable however the muscle quality in the first patient is very poor you can see lot of green areas which represents the fat within the intramuscular septum so this intramuscular fat incr
ease shows that the muscle quantity is less and also within the muscles if you see the density of the muscle is low that is a skeletal muscle density which indirectly represents the quality of the muscle so the quantity is less the quality is less and then hence the overall performance of the muscle is less compared to the other patient who had the same BMI of 26.8 however there is hardly any intramuscular sepal fat the muscle quality is very good the skeletal muscle index is very good and this
this this patient is a nonsarcopenic patient comparing the two the patient would have this patient would have done better in terms of response to chemotherapy toxicities related to chemotherapy and overall survival with this hypothesis in mind we looked at the effect of body composition on CT scan and comparing the outcomes in patients with esophagal Cancers and what we looked at was the skeletal muscle density and overall skeletal muscle index what we found apart from the most important factor
which uh predicts the outcomes in patient that is lymphovascular Invasion the skeletal muscle density was an independent factor for predicting the response so patients who had better skeletal muscle density that means the muscle were more denser did better than the patients who had poor skeletal muscle density we further went on to exploring the inflammation with related to cancer and this is commonly known as cancer inflammation index which is represented by the neutrophil to index you use PMI
into serum albumine divided by lymy neutr to lymy ratio what we did we substituted the BMI with the skeletal muscle index uh as we found that was a better predictor of the outcomes and compared the out uh the overall in the progression for survival and uh the number of toxicities and we found that the sarcopenic patients did did worse than the nonsarcopenic patients in this cohort and also the patients who had uh the progression Fe survival also in the these patients were better than in terms wi
th as compared to the non-sarcopenic patients apart from the sarcopenia the skeletal muscle density was also an independent predictor of progression and free and overall survival and hence was the modified inflammation index similar results have been published in the literature where people have where the researchers have found that the uh sarcopenic patients in hepatocellular cancer tend to do the the pink denotes the sarcopenic patients and the blue denotes the nonsarcopenic patients the SOP s
arcopenic tends to do better than the sarcopenic patients and in terms of toxicity again it has been shown that the in chactl cancer the the nonsarcopenic patients had lesser amount of toxicities that you can see two out of 15 as compared to the sarcopenic patients and the P value was significant with this there is a recent uh metaanalysis and systematic review which was published which showed that the sarcopenic patients who have lesser uh muscle strength and quality uh tend to do do worse in t
erms of overall survival progression survival and quality of life index so with this hypothesis what we started to do at clatter Brides We this is the normal pathway we do the initial workup for the patient we look whether the patient is of Curative intent or paliative intent uh and hence the patient is offered surgery or pre-operative NE Adent chemotherapy or postoperative NE Adent chemotherapy however now what we do is we look at the Baseline uh Imaging of the patient evaluate the sarcopenia a
nd if this uh if the patient is sarcopenic we give nutritional supplement correct the sarcopenia and also uh support the nutrition supplementation during the course of the treatment and after the course of treatment with high protein diet this has led to better outcomes in our clinical cohort now the way forward to look at this is to develop automated tools using machine learning to say sarcopenia because uh calculating Imaging based sarcopenia is still a timec consuming process and not all Radi
ologists are uh trained to to assess this and second is to delve into the molecular mechanisms of multiomics in cancer related sarcopenia uh there is something which is recently published which is detection of sarcopenia using deep learning based body part measure system that is the am bi amb which looks which automatically uh calculates this SMI that is skeletal muscle index and calculat the sarcopenic index as well and uh recently I've come across this paper which talks about perspective role
of liquid biopsy sarcopenia to assess uh and compared with the Imaging based sarcopenia and has shown to uh play a quite an important role in the clinics and liquid biopsies are commonly available for these patients because they are part of the bio Banks so various Pathways which are beyond the confines of my knowledge have been tested in these and they have been found to be related to sarcopenia in uh oncology patients the idea for this present this topic was to build up collaborations with uh
the uh people who are working in the lab and if there is any uh future prospects to do a joint work with somebody who's interested in this from Liverpool and across with that I thank you for your patient hearing any questions I'll be happy to take abish thank you very much for that great talk um now we um welcome questions for any of the speakers so please if you have a question uh type it in a question box as Shan on the image on the screen um and then we can have the next 10 to 15 minutes havi
ng some questions for the speakers okay so I have um a question here from the attendees um for the first Speaker Mia so for the recombinant call 582 is this a single long polypeptide or is it expected to Tri trimerize and also would it stay intact or would it be converted to active fragments over to you thank you for the great question so it's not as long as the other collagen strands such as Co 2 and Co one but um it is a prone to fragmentation because it also has an nc1 domain so it can be pra
gmatize and uh I think also there's a different chy chyom of that as well um I don't know too much into it because it has looked into the ELO stanlo syndrome more in depth whereas in when in relation to aging of cartilage is only like one or two sample papers into it and usually it's in relation with interactions with other uh collagen molecules or other extracell Matrix related molecules so it would be something that we can specifically look further into especially with pepti location fingerpri
nting and um other analysis and P as well thank you Mia um I also have a question for you um so would you be able to tell us a little bit about um so what are some of the challenges you experienced looking at proteum and exos Matrix from these young and old um tissues and um some of the challenges you might have experienced with mass back analys disease um so the main challenges was actually at the beginning like the just getting the tissue so the big thing I noticed the difference with is getti
ng the articular cartridge off young tissue was a lot easier it slid off the B the femoral head very easy whereas it when it came to um the old tissue it was quite anchored solid onto the femoral head so it meant that we had to break them in pieces or alternatively like um use a calcification solution to get rid of the bone and then um take the cartilage aside for the proteomic analysis and um as I've never done any proteomic analysis before this there was a lot to learn and understand so um yea
h I had the help of Alex so he was one of my collaborators with the plf um and also other help from the University of um understanding what approaches uh where to start off with and how to further go down in the line of what is the importance because there is so much data you can get out of it and yeah just finding the key one that I want to stick to so the extra selling Matrix and then finding what what um Pathways I want to go down eventually with all the learning and then all the training I w
as able to get overcome these challenges thank you Mia that that sounds so a really like a a very determination path pathway there for you to get to those samples could you also just tell us um you mentioned that there was differences between um obviously sex and age and um there were some um for example targets that were upregulated in males and downregulated in females so could you tell us some whether there were any specific subpathways within exell Matrix um protone that were of interest the
re or or is that something your still sort of working out so um in the gene set enrichment analysis it was mainly just like a whole topic of ECM remodeling so showing that there's collagen being synthesized collagen being broken down so this whole ECM remodeling Pathways that were related and found in the Aging but one big thing we found when we were as seeing the age like young versus um old in the specific Sexes we noed that there were opposite Trends in the female and males which was an inter
esting thing to see um because um I think from what I remember in males that they were actually um uppr regulated so that means there was more remodeling going on whereas this process was downregulated in females and this might indicate why there is sex differences and what we should look at differently and how we can kind of um find specific Targets in those Pathways using the volcano PL that I showed and the protein to protein interactions to find exactly what pathway you would want so I was j
ust doing the whole o overall proteome analysis and then if we do want to look specifically into one we will just go into depth and find one well thank you Mia that's great so um whilst I'm waiting maybe for some more questions from our attendees I'll go to our next speaker and ask her a couple of questions so this was Tamara so Tamara you showed us an interesting work about Redux uh reprogramming between breast cancer tissue and cancer Associated atos tissue so tell us a bit more about how do y
ou explain these really interesting differences in Nrf2 expression level one of the key antioxidant markers um between for example um breast issue and tissue and do you think that maybe Nrf2 plays a different role in these tissues and is there much work out there linking the Nrf2 levels to um different um uh levels of weight and and okay thank uh thank you for the question um well uh here we just measured the protein expression of Nrf2 and that would be one of the explanations for the difference
s in breast tissue and arpus tissue since we didn't measure the actual activity or the nuclear expression of Nrf2 uh so that that might be one of the reasons why they defer in OS and breast tissue and uh there are many uh many papers on the role of nf2 in cancer some of them pointing uh its positive or negative effect or helping in breast cancer progression um some of them uh confirming the other uh and regarding the role of an2 in edus tissue there are not so many results so this protein expres
sion of N2 is just the beginning of seeing its role in atus tissue and as far as cancer tissue is concerned it's still under debate and it's different in different tumors and in different types of breast tumor the its expression and its activity so uh I think definitely the further studies are needed to determine its exact role specifically in breast cancer tissue that sounds great so I have here a question from the attendees for abishek so the attendee would like to know whether and what nutrit
ional interventions composed of um different aspects and for how long um might be needed to correct sarcopenia um in cancer patients prior to treatment yeah so uh prior to I would say 2018 we didn't have a nutritional supplementation or available for patients and patients were not referred to the Nutrition department but now based on the Imaging uh each patient Plage is defined as sarcopenic or nonsarcopenic higher priority is given to because there is Li limited number of slots availability in
NHS high high priorities given to patients who are Sly sarcopenic the nutrition supplement can be through peroral which is directly if the patient is able to swallow we give protein based and vitamin D based high protein diets uh if the patient cannot swallow we put nasogastric tubes for these patients and also for cancers such as head neck cancers where patient is not unable to swallow we preamp the situation and put nasogastric tubes and improve the give supplementation improve the nutrition t
hen start the therapy rather than directly jumping onto the therapy as some patients we find even difficult to put a nasogastric tube such as esophagal cancers with the tube may not pass so what we do is we puncture a hole into the anti abdomen put a peg which is direct communication with the stomach and start giving nutrition supplementation to the stomach to the patient and what we've seen is the failure rate and uh has reduced and patients tend to do more Cycles as compared to the patients wh
o have not received nutrition supplement a following our research what we've tried to to do is we are now focusing more on high priority patients than the less priority because we do not want to lose the patients who are severely sarcopenic thank you abish so I have just a simple question for you so so obviously with with the loss of muscle mass um um you mentioned some of the things that you also find associated with it like Browning of U white OS tissue or some inflammatory markers and myosis
so so do we know what happens to the connective tissue like the extracell Matrix the collagens and and and so on I honestly have no clue about it I haven't come across any literature on that the what about the extra cell metrics I'm sure there would be some changes into the venting pathway which have been related to metastasis would be one of the causitive factors for poor prognosis I I just had a comment about tamaras I've I've done some research on uh breast ad osity and related to uh outcomes
uh independently through mammograms what we found was if you if you go back and look what kind of tumors you were dealing with whether they were estrogen and endogen progesterone receptor positive or negative that will give you an independent outcome because the receptor positivity is directly linked to the uh hormone production and the tumorogenesis uh and uh the Obesity is indirectly related to outcomes because of sarop because most of these patients are sarcopenic obese rather than healthy o
bese if if there are if if there are some uh groups who are looking at actual patient cohort uh I'm happy to help them with calculating sarcopenia on the images great thank you abishek and so um please attendees if you have any questions for any of the speakers do put it in a question box but I'll also ask a couple of question to Alex so Alex you told us about this amazing story from uh doing a molecular research all the way to pharmacological um and um applications and and and cosmetic developm
ent so tell us a little bit about the challenges along the way that you had and maybe also um how do you see your work progressing from here yeah so I mean uh I think a lot of the challenges it's quite is quite a long project right span seven seven years so really it's forming those relationships with industry um so there's a lot a lot of brainstorming a lot a lot of conversation a lot of proof proofs of principle that came before um any any of the work and it kind of just built um you know it s
tarted in silico then we start then we went on to cells and so of course we had to build that work before we finally took it to patch testing um and and you know we we had um um two different uh industrial partment was here we had Walgreens boots Alliance that helped us in in in in a few of of the experiments but also funded um the research and then we also had sedma who who helped us when it when it came to to to synthesizing um these peptides and looking at at their stability and and their pen
etration and whether they'll get through skin or not um and also um sensitivity whether they're whether they're safe um to to apply apply to people so you know the challenge is really was was was trying to communicate between all the all of these different groups and collaborators and to come together with a a very clear coherent hypothesis and project and of course an output um which which we're hoping to publish very soon um yes and um next steps yeah so I mean I I I would really be interested
in learning more about so we know that these peptides have differential effects but we don't really know yet how they're working so what is the mechanism are they being metabolized which is which is leading to a change are they binding to to receptors um is it is it a general damage um um signal or or or or is or is it a bit bit more Nuance um and that's something that I'm quite interested in because if we can figure that out um then when it comes to predicting uh peptides that might that might
um lead to Regeneration of tissue and skin um then that make things a lot easier um and of course we're also looking at application of these peptides across multiple um you know different scenarios as well that would that that would be interesting yes that was a little bit of my follow-up question you know are you thinking of some other applications any particular connective tissue diseases where this may be of interest yeah I mean we're we're we're we're in discussions at the moment I I think
my primary focus now is just understanding understanding it a bit more in skin um before we we we we take it take it anywhere else um but yeah I think you make an important point in assum that that we're thinking about yes thank you Alex I have one more question actually for abishek um so um so they're asking um when you mentioned um fat burning in sarcopenia um is the primary target um addressing sarcopenic obesity sorry I so so when you mention um about the idea of of fat burning um do you mea
n that the primary target may be also reducing sarcopenic obesity uh no no no it's actually the opposite it's it's the a Browning of the fat and that's a bad fat in the body so the interferon Alpha and tumor necrosis Alpha Factor until you can six they actually act on the muscle the muscles to cause myolysis and also on the fat to cause lipolysis but the the fat they acting on is the healthy fat not the bad fat the increasing the brown fat of the body which is not good for the body and that lead
s to more visceral opacity that means you have more visceral fat and then you have more intramuscular fat along the uh muscle tissue and that's not needed so basically the muscle is shrinking the brown fat around the muscle is increasing and the lipolysis is happening into the the the good fat and that leads to sarcopenic obesity rather than reducing sarcopenic capacity Okay so we've got a couple of more questions as well Tamara just a quick question for you have you covered any inflammatory mar
kers in your model uh inflammatory models no unfortunately uh not we we have I think we have done some inflammatory markers maybe but uh we have focused mostly uh on just on metabolic and redu reprogramming and we haven't um we haven't examined uh the possible inflammation in obesity since um we we do not believe that the Obesity could be just having negative effects and that the inflammation could be bad so we didn't go into that okay Tamar question for Alex so in your MPC Alex um did you have
anium protein that was fragmented or whole length in the original sample and if you see an increase in collagen six with age in skin from aspect would you know whether it was Ross fragmented um so when it kept so we we we let the the human dur fire blast um secrete and deposit their Matrix um and we and we then um collect it whole we tripson it and then we analyze it by mass spectrometry so it's not pref fragmented it might be fragmented because of endogenous proteases or proteases that the cell
s release um but you know re re really we're just looking at at whether um we see increases and or or or or decreases in in in protein um abundance and composition um with response to these these peptides um collagen six um I I don't I I'd have to go back and check to see if if collagen 6 as a specific marker was was affected by these peptides um yeah I'm not sure okay and just a couple of last points uh for you um also Alex uh could you mention what type of AI you used in your research yeah sur
e it was a um bidirectional uh uh neural network machine learning um algorithm that took into consideration both the secondary structure as well as the the um the predicted cleavage sites um um based on based on similar to the Prosper model but in incorporates um um um a two-dimensional um sorry um so um secondary structure as well as as just the primary sequence um yeah you can find this so we published it um back in 2021 um um it's the paper is predicting proteolysis in complex proteom using d
eep learning um uh so you can you can find that and and the link to that that tool is there as well okay and and the last question for Alex is so do you know whether the effect of randomized peptide sequences on ECM production and how these sequences would function when part of a polypeptide chain sorry can you repeat the question I I couldn't really hear okay so the attendee is asking um do you have an idea of the effects of randomized peptide sequences on ECM production and how these sequences
might function when part of a polypeptide chain no so so we haven't looked at randomize and that's something that actually we would like to to incorporate and and you know that's part of of the Journey of understanding the mechanism we know that we that we predicted these these these tetr peptides that that come from Matrix and they seem to work but the idea is if we were to change one of the amino acids to a different one along the sequence does it have an effect um is something that would we
we would really be interested in in in in in finding out um randomize might be a good way of of figuring out what um you know what works and and what doesn't we have to be a little bit more targeted I think if we're looking at mechanism um maybe change one me ass at a time and see what the what the effect might be um yeah okay thank you very much Alex well I think that concludes all our questions for today so I'm going to thank every everyone for attending this webinar and for speakers for their
brilliant talks and you can continue this conversation online by following Pam so or PP publishing on Twitter uh or X so we uh just want to say that we welcome submissions for speakers to present their work in 2024 webinar series if you've been inspired by our speakers today and would like the opportunity to present your research then please submit an abstract for consideration by 22nd of February and you can visit our website for more detail details all of the upcoming webinars are listed on t
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