MiMARK’s Post

We're gearing up for the American Association for Cancer Research (AACR) Annual Meeting, which is just a couple of weeks away! Join us on April 8th to delve into groundbreaking research with three poster presentations by Smita Agrawal, Executive Director of ConcertAI. In the morning session on April 8th from 9:00 AM – 12:30 PM, we'll explore a retrospective analysis uncovering the response of STK11+ aNSCLC patients to ICIs, revealing promising avenues for enhancing treatment outcomes in this subgroup. Additionally, we'll delve into the distribution of KRAS mutations and their impact on patient outcomes in pancreatic cancer (PC) with insights from ConcertAI’s Genome360TM PC dataset. In the afternoon session from 1:30 PM – 5:00 PM, join us as we dive into the genomic landscape of HR+/HER2- mBC patients who relapsed or were refractory to AIs, identifying key biomarkers and high-frequency mutations associated with resistance. These findings pave the way for the development of innovative therapies to overcome AI resistance. Don't miss out on these impactful presentations! Learn more about these presentations: https://lnkd.in/eafmt7H9 https://lnkd.in/eMPQFD2a https://lnkd.in/eNPSu_r3 #AACR2024 #CancerResearch #PosterPresentations

Something to celebrate – independent research has confirmed that X-ZELL can dramatically reduce the number of inconclusive cancer diagnoses from minimally invasive samples! It’s been a long time in the making and the validation of years of hard work and dedication, so thank you everyone who has been part of the journey or cheered us on from the sidelines – you're the reason we kept going! Here's the breakdown: In a blinded study from Germany, 213 suspected cancer samples were tested with both X-ZELL and traditional IHC technology. Both identified 23 malignant cases. However, 15% of IHC tests returned inconclusive – potentially leading to repeat testing, delayed treatment, and tremendous anxiety. X-ZELL was able to diagnose all these inconclusive cases correctly! What does that mean on a global scale? According to the World Health Organization, we see a staggering 55,000 new cancer diagnoses per day globally. Just imagine how many lives we could improve by ruling out inconclusive results, anxious waiting and repeat testing at that scale?  🤯 Now combine this with 90% less turnaround time and digital multichannel imaging instead of manually comparing microscope slides, and you might just agree that X-ZELL has the potential to revolutionise cancer diagnostics for good. The full study is yet to be released, but I hope the medical world is taking note already. X-ZELL is coming! More here: https://lnkd.in/eWjzKyWb #startup #news #pathology #cytology #cancer #diagnostics #nextgenerationcytology #medicine #immunostaining

What about this for innovation in early ovarian cancer detection? Researchers from the Georgia Institute of Technology have developed machine learning models to detect ovarian cancer using patient metabolic profiles. This approach addresses the issue of heterogeneity amongst ovarian cancer patients, which has obstructed early detection mechanisms due to limited common biomarkers. The models, which distinguished cancerous samples with a 93% accuracy, based on testing over 564 samples, could aid in boosting survival rates that currently sit at 31% for late-stage ovarian cancer, but can reach over 90% when diagnosed early. Professor John McDonald, lead researcher and Director of Integrated Cancer Research Center at Georgia Tech, emphasised the value of artificial intelligence in diagnosing individual targets, as only about 5% of patients benefit from current therapies due to patient differences. Their machine learning methodology can recognise patterns amongst the vast amount of uncharacterized metabolites – over 90% of metabolites in human blood – and correlate this with an individual’s likelihood of developing ovarian cancer. By doing so, patients identified with higher probabilities can be immediately screened and treated. #medicalinnovation #ovariancancer #HIPEC #CombatMedical

🌍🎗️ This World Cancer Day, we are kicking off a series of posts introducing the hearts and minds behind Precision CancerCare, our groundbreaking precision medicine proposition for cancer. Meet Ana Antunes, Global Head of Operations. "We live in a time of inspiring advancements in cancer diagnosis and treatment, with genomics driving a new era of medicine. However, people who seek cancer care hit known (and unknown) barriers at every turn, and the gap between medical advances and patient access impacts everyone. We at Further are on a mission to close that gap. Each type of cancer presents a unique set of challenges, where factors like the location of the tumour, the stage, and the genetic makeup of the cancer cells play a crucial role in determining the most effective treatment plan. Further Group provides insurers with a comprehensive solution designed to democratise complex healthcare access. Precision CancerCare encompasses extensive genomics for somatic and germline and optimised case management, ensuring that patients and medical teams have seamless access to the most advanced tools and Molecular Tumour Board expertise, when it matters most.” #WorldCancerDay #HealthcareInnovation #Cancer 🌐🎗️

Decoding Cancer: Revolutionary Insights and Breakthroughs presents an in-depth exploration into the multifaceted world of cancer, discussing various types, genetic and lifestyle factors, and the importance of early detection. The article illuminates emerging diagnostic tools like liquid biopsies, a variety of treatment strategies, and the advent of precision medicine. It also underlines the complexities of survivorship, the promise of innovative research, and the hope for a future where cancer can be conquered.

What about this for innovation in early ovarian cancer detection? Researchers from the Georgia Institute of Technology have developed machine learning models to detect ovarian cancer using patient metabolic profiles. This approach addresses the issue of heterogeneity amongst ovarian cancer patients, which has obstructed early detection mechanisms due to limited common biomarkers. The models, which distinguished cancerous samples with a 93% accuracy, based on testing over 564 samples, could aid in boosting survival rates that currently sit at 31% for late-stage ovarian cancer, but can reach over 90% when diagnosed early. Professor John McDonald, lead researcher and Director of Integrated Cancer Research Center at Georgia Tech, emphasised the value of artificial intelligence in diagnosing individual targets, as only about 5% of patients benefit from current therapies due to patient differences. Their machine learning methodology can recognise patterns amongst the vast amount of uncharacterized metabolites – over 90% of metabolites in human blood – and correlate this with an individual’s likelihood of developing ovarian cancer. By doing so, patients identified with higher probabilities can be immediately screened and treated. #medicalinnovation #ovariancancer #HIPEC #CombatMedical

Decoding Cancer: Revolutionary Insights and Breakthroughs presents an in-depth exploration into the multifaceted world of cancer, discussing various types, genetic and lifestyle factors, and the importance of early detection. The article illuminates emerging diagnostic tools like liquid biopsies, a variety of treatment strategies, and the advent of precision medicine. It also underlines the complexities of survivorship, the promise of innovative research, and the hope for a future where cancer can be conquered.

𝐖𝐨𝐫𝐥𝐝 𝐂𝐚𝐧𝐜𝐞𝐫 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐃𝐚𝐲   Today marks World Cancer Research Day, an excellent opportunity to acknowledge and recognise the life-changing cancer research that is conducted daily at Chris O’Brien Lifehouse (COBL). Research is at the heart of COBL, as we continue to develop new treatments and techniques, with the overall aim to improve cancer patient outcomes.   This year’s World Cancer Research Day theme is “Innovation In Cancer Research Drives Progress Toward Health Equity”. Innovations, such as early detection screenings, have allowed more people to access cancer care and prevention treatments, helping to achieve health equity worldwide.   COBL is significantly involved in cancer research and innovation, facilitated through the Chris O’Brien Lifehouse Research Institute. It is a multidisciplinary environment that allows innovators, researchers, and clinicians to work together to solve complex problems and advance cancer research.   Swipe through to learn about the research interests of COBL Research Faculty members A/Prof Kate Mahon, Dr Rebecca Venchiarutti and A/Prof Sanjay Warrier. Chris O'Brien Lifehouse Research Institute Integrated Prosthetics & Reconstruction #cobl #worldcancerresearchday #cancerresearch #research #innovation #choosehope #cancercare #chrisobrienlifehouse

Decoding Cancer: Revolutionary Insights and Breakthroughs presents an in-depth exploration into the multifaceted world of cancer, discussing various types, genetic and lifestyle factors, and the importance of early detection. The article illuminates emerging diagnostic tools like liquid biopsies, a variety of treatment strategies, and the advent of precision medicine. It also underlines the complexities of survivorship, the promise of innovative research, and the hope for a future where cancer can be conquered.

A new study led by investigators from Mass General Brigham and @bidmchealth has identified blood proteins that may predict liver cancer risk years before diagnosis. Liver cancer is the third leading cause of cancer globally and the second leading cause of cancer-related deaths. Early detection is crucial, especially for high-risk individuals like those with cirrhosis and hepatitis, but current tools are inadequate, expensive, invasive and limited to major hospitals. The research team utilized proteomics to develop an early detection model for liver cancer. Using the SomaScan Assay Kit, they measured 1,305 proteins in blood samples from health study participants. They identified 56 elevated proteins in liver cancer patients, selecting four for a predictive model. When tested, this model showed higher accuracy in predicting liver cancer than traditional risk factors. #cancer #medical_tourism #hospital #liver_cancer #chinesehospitals #Turkiyehospitals #Singapore