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	<title>Medical Research | Tissuepathology.com</title>
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		<title>ASCO: Now and Then</title>
		<link>https://tissuepathology.com/2026/06/11/asco-now-and-then/</link>
		
		<dc:creator><![CDATA[Dr. Keith J. Kaplan]]></dc:creator>
		<pubDate>Thu, 11 Jun 2026 18:00:28 +0000</pubDate>
				<category><![CDATA[Advocacy]]></category>
		<category><![CDATA[Anatomic Pathology]]></category>
		<category><![CDATA[Business]]></category>
		<category><![CDATA[Clinical Laboratories]]></category>
		<category><![CDATA[Clinical Pathology]]></category>
		<category><![CDATA[Conferences]]></category>
		<category><![CDATA[Current Affairs]]></category>
		<category><![CDATA[Digital Pathology Conferences]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Education]]></category>
		<category><![CDATA[Health Technology Collaboration]]></category>
		<category><![CDATA[Histology]]></category>
		<category><![CDATA[Humor]]></category>
		<category><![CDATA[Informatics]]></category>
		<category><![CDATA[Laboratory Informatics]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Microscopy]]></category>
		<category><![CDATA[Molecular Pathology]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Personal]]></category>
		<category><![CDATA[Reports]]></category>
		<category><![CDATA[Science]]></category>
		<category><![CDATA[Whole slide]]></category>
		<category><![CDATA[ASCO]]></category>
		<category><![CDATA[conferences]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24484</guid>

					<description><![CDATA[<p>In medical school I drove a cab at night to make ends meet. I rented the medallion from a guy for $50 and kept the difference I made. The Army paid me $692 a month stipend on the Health Professions Scholarship and the studio apartment in downtown Chicago was $1000/month. I wasshort over $300 a [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/06/11/asco-now-and-then/">ASCO: Now and Then</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
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		<title>Call for papers: Breast cancer biomarkers in diagnostic and translational pathology – Breast Cancer: Targets and Therapy</title>
		<link>https://tissuepathology.com/2026/05/20/call-for-papers-breast-cancer-biomarkers-in-diagnostic-and-translational-pathology-breast-cancer-targets-and-therapy/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Wed, 20 May 2026 11:28:40 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Image Analysis]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[breast cancer]]></category>
		<category><![CDATA[Breast Cancer: Targets and Therapy]]></category>
		<category><![CDATA[call for papers]]></category>
		<category><![CDATA[diagnostic pathology]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[Pathology]]></category>
		<category><![CDATA[taylor & francis]]></category>
		<category><![CDATA[translational pathology]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24430</guid>

					<description><![CDATA[<p>Taylor &#38; Francis is pleased to invite you to submit your work to an upcoming Article Collection on “Breast cancer biomarkers in diagnostic and translational pathology” in the journal Breast Cancer: Targets and Therapy. This Article Collection will focus on investigating immunohistochemical and molecular biomarker testing in breast cancer, with particular emphasis on optimizing reproducibility and [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/05/20/call-for-papers-breast-cancer-biomarkers-in-diagnostic-and-translational-pathology-breast-cancer-targets-and-therapy/">Call for papers: Breast cancer biomarkers in diagnostic and translational pathology – Breast Cancer: Targets and Therapy</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
		<item>
		<title>American Center for Cancer Research: DNA methylation &#8220;fingerprints&#8221; identify primary sites in metastatic cancers</title>
		<link>https://tissuepathology.com/2026/04/21/american-center-for-cancer-research-dna-methylation-fingerprints-identify-primary-sites-in-metastatic-cancers/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Tue, 21 Apr 2026 13:47:18 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Reports]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[American Center for Cancer Research]]></category>
		<category><![CDATA[cancer]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[DNA]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[metastatic cancers]]></category>
		<category><![CDATA[methylation]]></category>
		<category><![CDATA[Pathology]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24363</guid>

					<description><![CDATA[<p>A machine learning model analyzing CpG-based DNA methylation accurately predicted the origin of many different cancer types in patients with cancers of unknown primary (CUP), according to research presented at the American Association for Cancer Research (AACR) Annual Meeting 2026, held April 17-22. CUP are metastatic malignancies in which the primary cancer site could not [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/04/21/american-center-for-cancer-research-dna-methylation-fingerprints-identify-primary-sites-in-metastatic-cancers/">American Center for Cancer Research: DNA methylation “fingerprints” identify primary sites in metastatic cancers</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
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		<item>
		<title>Cancer Survival Rises</title>
		<link>https://tissuepathology.com/2026/01/14/cancer-survival-rises/</link>
		
		<dc:creator><![CDATA[Dr. Keith J. Kaplan]]></dc:creator>
		<pubDate>Wed, 14 Jan 2026 15:51:58 +0000</pubDate>
				<category><![CDATA[Anatomic Pathology]]></category>
		<category><![CDATA[Current Affairs]]></category>
		<category><![CDATA[Education]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Patient Advocacy]]></category>
		<category><![CDATA[Science]]></category>
		<category><![CDATA[cancer]]></category>
		<category><![CDATA[Immunotherapy]]></category>
		<category><![CDATA[Survival Rates]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24173</guid>

					<description><![CDATA[<p>From CNN: The five-year cancer survival rate in the US has reached 70% for the first time, according to an American Cancer Society report released yesterday. The figure, based on diagnoses from 2015 to 2021, is up from 49% in the mid-1970s and 63% in the mid-1990s. The ACS attributes the rise to wider and earlier screening, lower smoking [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/01/14/cancer-survival-rises/">Cancer Survival Rises</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
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		<title>Lunit study shows higher HER2 diagnostic agreement between AI and pathologists</title>
		<link>https://tissuepathology.com/2025/12/23/lunit-study-shows-higher-her2-diagnostic-agreement-between-ai-and-pathologists/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Tue, 23 Dec 2025 13:28:43 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Image Analysis]]></category>
		<category><![CDATA[International]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Publications]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[bile duct cancer]]></category>
		<category><![CDATA[Diagnostics]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[HER2]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[Laboratory Investigation]]></category>
		<category><![CDATA[Lunit]]></category>
		<category><![CDATA[Pathology]]></category>
		<category><![CDATA[USCAP]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24131</guid>

					<description><![CDATA[<p>Lunit said Tuesday that it has published research showing that its AI biomarker platform, Lunit SCOPE, can improve HER2 (human epidermal growth factor receptor 2) diagnosis in advanced bile duct cancer. The study was published in Laboratory Investigation, the official journal of the United States and Canadian Academy of Pathology (USCAP) (Impact Factor 4.2). Biliary tract [&#8230;]</p>
The post <a href="https://tissuepathology.com/2025/12/23/lunit-study-shows-higher-her2-diagnostic-agreement-between-ai-and-pathologists/">Lunit study shows higher HER2 diagnostic agreement between AI and pathologists</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
		<item>
		<title>UCL: AI tool helps predict treatment success in rectal cancer patients</title>
		<link>https://tissuepathology.com/2025/11/20/ucl-ai-tool-helps-predict-treatment-success-in-rectal-cancer-patients/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Thu, 20 Nov 2025 13:18:14 +0000</pubDate>
				<category><![CDATA[Anatomic Pathology]]></category>
		<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Press Release]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[Pathology]]></category>
		<category><![CDATA[rectal cancer]]></category>
		<category><![CDATA[UCL]]></category>
		<category><![CDATA[University College of London]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24059</guid>

					<description><![CDATA[<p>Artificial intelligence (AI) can predict how well patients with rectal cancer will respond to treatment by analysing standard tissue samples taken during diagnosis, finds a new study from researchers at UCL and UCLH. In most cancers, the immune landscape surrounding a tumour plays a major role in determining how cancer progresses and how patients respond [&#8230;]</p>
The post <a href="https://tissuepathology.com/2025/11/20/ucl-ai-tool-helps-predict-treatment-success-in-rectal-cancer-patients/">UCL: AI tool helps predict treatment success in rectal cancer patients</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
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