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Gene panel test enables highly accurate diagnosis of liposarcomas


Gene panel test enables highly accurate diagnosis of liposarcomas
Researchers have leveraged the latest advances in RNA technology and machine learning methods to develop a gene panel test that allows for highly accurate diagnosis of the most common types of liposarcoma. It quickly and reliably distinguishes benign lipomas from liposarcomas and can be performed in laboratories at a lower cost than current gold standard tests. The new assay is described in
The Journal of Molecular Diagnosis, published by Elsevier.
Liposarcomas are a type of malignant cancer that is difficult to diagnose because, even under a microscope, it is hard to differentiate liposarcomas from benign tumors or other types of cancer that need different treatments. Many liposarcomas look like their benign and relatively common counterparts, lipomas. Diagnostic delay and uncertainty cause severe stress for patients, and misdiagnosis can have many consequences including delayed or inadequate treatme ....

United Kingdom , British Columbia , Xiu Qing Jenny Wang , Torsten Owen Nielsen , Emily Henderson , University Of British Columbia , Department Of Pathology , Genetic Pathology Evaluation Centre , Laboratory Medicine , Molecular Diagnosis , Lowen Nielsen , Lead Author , Cancer Genome Atlas , Xiu Qing , Machine Learning , ஒன்றுபட்டது கிஂக்டம் , பிரிட்டிஷ் கொலம்பியா , க்ஷிு குயிங் ஜென்னி வாங் , எமிலி ஹென்டர்சன் , பல்கலைக்கழகம் ஆஃப் பிரிட்டிஷ் கொலம்பியா , துறை ஆஃப் நோயியல் , ஜெநெடிக் நோயியல் மதிப்பீடு மையம் , ஆய்வகம் மருந்து , மூலக்கூறு நோயறிதல் , ஓவந் நீல்சன் , வழி நடத்து நூலாசிரியர் ,

Researchers to create computational models to improve treatments for ovarian cancer


Researchers to create computational models to improve treatments for ovarian cancer
The 5-year research project involves 14 organizations in seven EU countries and is funded by €15 M from the EU.
The Genome Data Science lab, led by ICREA researcher Fran Supek, will analyze the evolution of ovarian tumors to develop computational models for predicting treatment resistance.
The EU has granted €15 M to fund a 5-year project that seeks to improve personalized treatments for ovarian cancer. The international DECIDER project involves partners from 14 organizations in seven EU countries.
In Europe, over 40000 women die of ovarian cancer every year. In addition to surgery, most patients are treated with platinum-based chemotherapy. Unfortunately, the effect of the chemotherapy often decreases with treatment cycles, and few effective treatments are currently available for patients who develop resistance to platinum-based drugs. ....

Comunidad Autonoma De Cataluna , Eteläuomen Läi , Sampsa Hautaniemi , Fran Supek , Emily Henderson , University Of Helsinki , Genome Data Science , Ovarian Cancer , Research Project , காமுனிடட தன்னாட்சி டி கடலுள் , எமிலி ஹென்டர்சன் , பல்கலைக்கழகம் ஆஃப் ஹெல்சின்கி , மரபணு தகவல்கள் அறிவியல் , ஓவாயரியந் புற்றுநோய் , ஆராய்ச்சி ப்ராஜெக்ட் , அறுவை சிகிச்சை ,