Almost all liver cancers develop after decades of chronic liver disease, but a new discovery by Columbia researchers may lead to treatments that could break the link.
The new research shows that during chronic liver disease a shift in the balance of quiescent and activated stellate liver cells not only promotes fibrosis but also sets the stage for the most common type of primary liver cancer, called hepatocellular carcinoma.
The findings, published online in Nature, suggest that it may be possible to prevent the development of liver cancer—the fourth-leading cause of cancer death worldwide—by interfering with stellate cell activation.
Hepatocellular carcinoma develops almost exclusively in patients with a chronic liver disease, including cirrhosis, hepatitis, or non-alcoholic fatty liver disease. These diseases often cause extensive and progressive scar tissue (aka fibrosis) in the liver.
Scientists have discovered that cervical cancer can be divided into two distinct molecular subgroups—one far more aggressive than the other—as part of the largest "omics" study of its kind, led by researchers at UCL and the University of Southampton.
Published in Nature Communications, researchers say the breakthrough findings are a "major step forward" in understanding disease and provide a tantalizing new clue in determining the best treatments for individual patients.
Cervical cancer is a major cause of cancer-related deaths in women and accounts for 528,000 new cases and 266,000 deaths worldwide each year. It is almost always caused by the human papillomavirus (HPV), a common virus that can be passed from one person to another during sex.
Even in the U.K., where NHS cervical screening has dramatically reduced cancer incidence and with the national HPV vaccination program aiming to cut rates even further, around 850 women die every year from the disease.
For the study, researchers started by applying a multi-omics approach, analyzing and comparing a combination of different markers, including DNA, RNA, proteins, and metabolites, in 236 cervical squamous cell carcinoma (CSCC) cases, the most common form of cervical cancer, available in a publicly available U.S. database.
A multi-omics analysis aims to identify molecular markers and characteristics associated with biological processes (in this case cervical cancer cells) by analyzing DNA, RNA, proteins, metabolites, etc. Omics is a branch of science incorporating multiple disciplines such as genomics, transcriptomics, proteomics, and metabolomics.
UVA Health Cancer Center researchers have developed an algorithm that will improve cancer care by quickly and easily identifying patients who will benefit from powerful cancer drugs called kinase inhibitors. The algorithm may have other diagnostic benefits for patients as well.
Kinase inhibitors are the most common cancer drugs approved by the federal Food and Drug Administration. They can be hugely effective for the right patients, but they don't work for everyone. UVA's algorithm offers a new and better way to pinpoint patients who will benefit—an important step forward in precision medicine tailored to the individual.
"We are really excited about this algorithm, which performs better than existing approaches with fewer requirements and assumptions—making it more applicable to understanding a cancer state from a single snapshot of the tumor," said researcher Kristen M. Naegle of UVA's Department of Biomedical Engineering, a joint program of UVA's schools of Medicine and Engineering. "Combining this approach with existing biomarkers for cancer diagnosis may help us to better tailor therapies, design new combination therapies, anticipate response to treatment and design better clinical trials."
KSTAR for better cancer care
Naegle and colleagues set out to overcome the limitations of existing methods to identify patients who may benefit from kinase inhibitors. Most of these methods require difficult-to-obtain and sometimes unreliable information quantifying "phosphorylation sites" within cells. UVA's new approach, however, does not need all this complex measurement. Instead, it can predict key information based upon other available data.
UT Southwestern researchers have identified a causative signaling pathway in breast cancer, providing potential new targets for treatment of the most common type of cancer in women. The findings, published in Science Advances, build on previous work in which the group identified a gene called ZMYND8 as a regulator of breast tumor growth.In the new study, the researchers further characterize a critical role for ZMYND8 and levels of 27-hydroxycholesterol in the development of breast cancer.
"This study identifies a cause of breast cancer," said lead author Weibo Luo, Ph.D., Associate Professor of Pathology and member of the Harold C. Simmons Comprehensive Cancer Center.
Breast cancer is a leading cause of cancer death among women worldwide. The new discovery may represent a step toward developing effective therapies and identifying breast cancer risk in patients early.
The development of breast cancer begins with a population of cells called breast cancer stem cells that have the remarkable ability to self-replicate. These "bad seeds" drive tumor growth, but how this occurs is not well understood.
Following the identification of ZMYND8 as a regulator of breast cancer growth, Dr. Luo and his colleagues wondered if the gene also played a role in the development of tumors.
Using a mouse model in which the researchers had knocked out the ZMYND8 gene and complementary cell culture experiments, the researchers found that ZMYND8 promotes breast cancer stem cell maintenance and self-renewal, and stimulates the transformation of these cells into tumor cells, leading to breast tumor initiation.
This Single Blood Test Can Detect Multiple Kinds of Cancer Early by Colin Pritchard
November 2, 2022
Introduction:
(Science Alert) Detecting cancer early before it spreads throughout the body can be lifesaving. This is why doctors recommend regular screening for several common cancer types, using a variety of methods.
Colonoscopies, for example, screen for colon cancer, while mammograms screen for breast cancer.
While important, getting all these tests done can be logistically challenging, expensive, and sometimes uncomfortable for patients. But what if a single blood test could screen for most common cancer types all at once?
This is the promise of multicancer early detection tests, or MCEDs. This year, President Joe Biden identified developing MCED tests as a priority for the Cancer Moonshot, a US$1.8 billion federal effort to reduce the cancer death rate and improve the quality of life of cancer survivors and those living with cancer.
As a laboratory medicine physician and researcher who develops molecular tests for cancer, I believe MCED tests are likely to transform cancer screening in the near future, particularly if they receive strong federal support to enable rapid innovation.
The latest developmental drugs, particularly for use in oncology, rely on the targeted degradation of harmful pathogenic proteins. In a recent study published in Nature Chemical Biology, researchers at CeMM, the Research Center for Molecular Medicine of the Austrian Academy of Sciences, and the University of Dundee (U.K.) identify potential resistance mechanisms and provide insights on how to overcome them.
Traditional targeted cancer therapies mainly rely on drugs that bind pathogenic proteins and inhibit their function. Newer drugs have advanced chemical molecules known as degraders, which force the targeted degradation of disease-relevant proteins. This method of targeted protein degradation is not only more efficient, but also better at overcoming potential drug resistance.
For many years, CeMM Principal Investigator Georg Winter and his research group have been working on further developing this paradigm. Small-molecule degraders work like a glue by recruiting the defective, disease-causing protein to effectors of the cellular waste disposal systems, which are known as E3 ubiquitin ligases. This binding in turn kick-starts the degradation process of the defective protein.
Alexander Hanzl, first author and Ph.D. student in the Winter Lab at CeMM, conducted a study to investigate which resistances can arise during the degradation process. He explains, "One challenge with degraders is that they have to bind two sites at once—both the defective protein and a protein of our cell's own degradation system, the E3 ligase. It is therefore all the more important to understand the process of binding and ubiquitination in functional detail. Only then can future degraders be modeled in the best possible way."
Shorter course of radiation therapy yields comparable results for patients with non-metastatic soft tissue sarcoma https://medicalxpress.com/news/2022-11- ... ients.html
by University of Texas M. D. Anderson Cancer Center
Patients with non-metastatic soft tissue sarcoma (STS) who need pre-operative radiation therapy can safely receive hypofractionated treatment over three weeks instead of five, with comparable tumor control and no increased risk of major complications in wound healing, according to researchers at The University of Texas MD Anderson Cancer Center.
Results from the study, led by Ashleigh Guadagnolo, M.D., professor of Radiation Oncology, were published today in The Lancet Oncology. Guadagnolo also presented results at the 2022 American Society for Radiation Oncology (ASTRO) Annual Meeting.
On the single-arm, non-randomized trial, patients received hypofractionated radiation therapy, consisting of higher daily radiation therapy doses per treatment over fewer days relative to conventional therapy. Thirty-one percent of patients developed major wound complications within 120 days of surgery, while local tumor control was 93% at two-year follow-up—both comparable to historically reported rates with the longer treatment course.
"Our data indicate the three-week regimen offers patients a likely safe and effective alternative to the current standard of care with comparable outcomes in disease control and no increased risks of major wound complications," Guadagnolo said. "We are excited by the current results of this study, which demonstrate the value of a hypofractionated approach to radiation therapy, which is more convenient for patients."
Researchers from Barts Cancer Institute at Queen Mary University of London have identified a new channel of communication through which non-cancerous cells drive the invasion of cancer cells in pancreatic cancer.
By blocking a particular signaling molecule within this pathway, called Fibroblast Growth Factor Receptor 1 (FGFR1), the team was able to reduce invasion of pancreatic cancer cells in the laboratory.
The findings, published today in Oncogene, may pave the way for the development of new treatment approaches for pancreatic cancer that target the cross-talk between cancer cells and their environment.
Silencing the communication between cancer cells and healthy cells
Researchers at the University of Pennsylvania's Basser Center for BRCA at the Abramson Cancer Center have discovered factors that may make breast and ovarian cancers associated with BRCA1/2 gene mutations more likely to recur.
These mutations strongly predispose women to breast and ovarian cancers, and these cancers have a high risk of recurrence after initial treatment. In the new study, published this week in Nature Communications, the researchers compared a large set of tumors from patients with primary and recurrent BRCA1/2 mutation-associated breast and ovarian cancers, and found multiple features associated with recurrence, including features that would be expected to improve tumors' ability to repair treatment-caused DNA damage.
"These results suggest key biological features of therapy-resistant recurrences, which point to new possibilities for treating BRCA1/2-mutation cancers," said the study's senior author Katharine Nathanson, MD, the Pearl Basser Professor for BRCA-Related Research in Penn's Perelman School of Medicine, Deputy Director of the Abramson Cancer Center, and Director of Genetics at the Basser Center for BRCA.
A national Return-to-Screening effort initiated and led by the American College of Surgeons (ACS) helped restore cancer screenings to pre-pandemic levels and contributed to a significant number of additional screening tests, according to new research published in JAMA Network Open.
In response to growing concerns about missed cancer screenings related to COVID-19 restrictions and lockdowns, the ACS Cancer Programs, together with the American Cancer Society, launched a Return-to-Screening national Quality Improvement (QI) Project in early 2021 to help accredited programs estimate and reduce local cancer screening deficits.
The article in JAMA Network Open reveals, for the first time, final data from the QI project, which included 786 Commission on Cancer (CoC) and National Accreditation Program of Breast Centers (NAPBC) accredited programs. These programs include hospitals, treatment centers, and other cancer facilities. It is estimated that the CoC programs treat nearly 70 percent of recently diagnosed cancer patients in the U.S. annually.
Predicting which patients will respond well to treatment is a quandary that has plagued the field of cancer immunotherapy for more than four decades. Now, researchers at the Johns Hopkins Kimmel Cancer Center and its Bloomberg~Kimmel Institute for Cancer Immunotherapy are one step closer to solving that problem. In a small study, they successfully trained a machine learning algorithm to predict, in hindsight, which patients with melanoma would respond to treatment and which would not respond.
The open-source program, DeepTCR, proved valuable as a predictive clinical tool, but it also functioned as a powerful instructor, teaching the researchers about the biological mechanisms underlying patients' responses to immunotherapy.
"DeepTCR's predictive power is exciting," says John-William Sidhom, M.D., Ph.D., first author of the study, "but what I found more fascinating is that we were able to view what the model learned about the immune system's response to immunotherapy. We can now exploit that information to develop more robust models, and possibly better treatment approaches, for many diseases, even those outside of oncology."
A summary of the research was published in the journal Science Advances.
DeepTCR was developed at the Johns Hopkins University School of Medicine by Sidhom when he was an M.D./Ph.D. student. It uses deep learning, a form of artificial intelligence, to recognize patterns in large volumes of data. In this case, the data is the amino acid sequences of proteins called T cell receptors (TCRs).
A novel artificial intelligence blood testing technology developed and used by Johns Hopkins Kimmel Cancer Center researchers to successfully detect lung cancer in a 2021 study has now detected more than 80% of liver cancers in a new study of 724 people.
The blood test, called DELFI (DNA evaluation of fragments for early interception) detects fragmentation changes among DNA from cancer cells shed into the bloodstream, known as cell-free DNA (cfDNA). In the most recent study, investigators used the DELFI technology on blood plasma samples obtained from 724 individuals in the U.S., the European Union (E.U.) and Hong Kong to detect hepatocellular cancer (HCC), a type of liver cancer.
The researchers believe this is the first genome-wide fragmentation analysis independently validated in two high-risk populations and across different racial and ethnic groups with different causes associated with their liver cancers.
Their findings were reported Nov. 18 in Cancer Discovery and at the American Association for Cancer Research Special Conference: Precision Prevention, Early Detection, and Interception of Cancer.
A vaccine (DCVax-L), trialed at King's College Hospital and other centers around the world, using patients' immune cells to target brain cancer can extend survival by many months or, in some cases, years, the final unblinded results from a phase 3 clinical trial has shown. The final results were published on Thursday, November 17 in JAMA Oncology.
This is the first time in 17 years that such significant outcomes have been achieved in a phase 3 trial for a systemic treatment in newly diagnosed glioblastoma, and the first time in 27 years that any treatment has been shown to extend survival in recurrent glioblastoma.
The vaccine is created for each patient individually by isolating specific immune cells, known as dendritic cells, from their blood. These cells are then primed with biomarkers from a sample of the patient's tumor. When the vaccine containing the cells is injected back into the patient, it shares that information so that the body's entire immune system recognizes and attacks the target.
The most comprehensive study of kidney cancer at single-cell level has discovered a potential drug target to treat renal cell carcinoma, a cancer with a high mortality rate that is hard to detect. Researchers from the Wellcome Sanger Institute, the University of Cambridge and Cambridge University Hospitals identified immune cells known as macrophages that express the gene IL1B as crucial to tumor development.
The study, published today in Cancer Cell, recommends IL1B macrophages as a promising therapeutic target to treat renal cell carcinoma given that this cell type has already been targeted using existing drugs that prevent lung cancer. The next step, which is already being explored, will be clinical trials to prove that targeting IL1B can be used to effectively prevent renal cell carcinoma from forming or progressing.
Renal cell carcinoma (RCC) is the seventh most common cancer in the UK, with three quarters of cases and the majority of deaths caused by clear cell renal cell carcinoma (ccRCC). The disease has a 50% mortality rate, partially because three in five patients show no symptoms until the cancer is at a late stage.
Lipid nanoparticle (LNP)-based messenger ribonucleic acid (mRNA) vaccines have recently emerged as a promising strategy for the prevention and treatment of cancers, as well as infectious diseases. LNPs are carriers that safely and effectively deliver nucleic acid vaccines, eliciting a strong immune response.
One milestone is the clinical use of leading LNP mRNA vaccines against COVID-19, which exhibits different degrees of protection efficacy, as well as some side effects. As these vaccines are known to be safe, efficient and easily developed, they have been widely used as protection against various human diseases, especially malignant cancers. Despite its high take-up rate in cancer treatment, the common side effects of pain, swelling, and fever, continue to be present, potentially due to inflammatory qualities within the LNPs, that form part of vaccines.
In the study published in Advanced Materials, Prof Chen and his team synthesized a series of alternating copolymers, which can work as vehicles and help mRNA cargos deliver into cells. After entry into cells, mRNA is translated into protein antigens and kill the disease. In the process, the stability of polymeric nanoparticle (PNP) is maintained, which can ensure accurate transmission of all genetic information to the targeted action sites of the antigen to kill the disease. This ensures the efficacy and safety of the vaccine.
Federated machine learning enables the largest brain tumor study to-date, without sharing patient data https://medicalxpress.com/news/2022-12- ... brain.html
by Perelman School of Medicine at the University of Pennsylvania
Researchers at Penn Medicine and Intel Corporation led the largest-to-date global machine learning effort to securely aggregate knowledge from brain scans of 6,314 glioblastoma (GBM) patients at 71 sites around the globe and develop a model that can enhance identification and prediction of boundaries in three tumor sub-compartments, without compromising patient privacy. Their findings were published today in Nature Communications.
"This is the single largest and most diverse dataset of glioblastoma patients ever considered in the literature, and was made possible through federated learning," said senior author Spyridon Bakas, Ph.D., an assistant professor of Pathology & Laboratory Medicine, and Radiology, at the Perelman School of Medicine at the University of Pennsylvania. "The more data we can feed into machine learning models, the more accurate they become, which in turn can improve our ability to understand, treat, and remove glioblastoma in patients with more precision."
Researchers studying rare conditions, like GBM, an aggressive type of brain tumor, often have patient populations limited to their own institution or geographical location. Due to privacy protection legislation, such as the Health Insurance Portability and Accountability Act of 1996 (HIPAA) in the United States, and General Data Protection Regulation (GDPR) in Europe, data sharing collaborations across institutions without compromising patient privacy data is a major obstacle for many healthcare providers.
Scientists from the National University of (NUS) have discovered a novel low-cost method of testing for cancers. Called the Heatrich-BS assay, this new test sequences clinical samples that have been heated in order to isolate cancer-specific signatures found in a patient's blood.
The new method provides a promising non-invasive alternative to tissue biopsies. It costs around S$50 (approximately $37 USD) from start to finish, compared to other sequencing methods that can cost up to S$1,000 to conduct. Led by Assistant Professor Cheow Lih Feng, the team comprising researchers from the NUS Department of Biomedical Engineering under the College of Design and Engineering as well as the NUS Institute for Health Innovation & Technology, is now exploring industry partnerships to bring their technology to market.
"When you have a S$50 test, it opens up a lot of avenues because it is affordable, so you can do the test quite regularly," said Asst. Prof. Cheow, pointing to the potential for their assay to be used in regular cancer monitoring.
A short, simple and safe drug treatment developed at Tel Aviv University reduced the risk of the spread of cancer metastases after surgery to remove the primary tumor—according to the first clinical study of its kind conducted among 34 colon cancer patients operated on at Sheba Tel Hashomer Medical Center.
The research was led by Prof. Shamgar Ben-Eliyahu of TAU's Sagol School of Neuroscience and School of Psychological Sciences and Prof. Oded Zamora of TAU's Sackler Faculty of Medicine, and its results were published in the European Journal of Surgical Oncology.
At the same time, an overview of the theory and principles underlying the research was published in Nature Reviews Cancer.
Although surgery to remove primary tumors is the mainstay of all cancer treatments, the risk of metastases after tumor removal is estimated at 35% among colon cancer patients, with higher risk in patients with more advance stages of the disease.
Everyone knows someone who has had cancer. In 2020, around 19 million new cases—and around 10 million deaths—were registered worldwide. Treatments are improving all the time, but can damage healthy cells or have severe side effects that are hard on patients. In the search for new, more targeted cancer drugs, traditional medicine offers many possible candidates.
A team of Polish scientists led by Magdalena Winkiel at Adam Mickiewicz University, publishing today in Frontiers in Pharmacology, has reviewed the bioactive compounds called glycoalkaloids, found in vegetables like potatoes and tomatoes, to demonstrate their potential to treat cancer.
"Scientists around the world are still searching for the drugs which will be lethal to cancer cells but at the same time safe for healthy cells," said Winkiel.
"It is not easy despite the advances in medicine and powerful development of modern treatment techniques. That is why it might be worth going back to medicinal plants that were used years ago with success in the treatment of various ailments. I believe that it is worth reexamining their properties and perhaps rediscovering their potential."
