<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Bhattacharya S</submitter><funding>NICHD NIH HHS</funding><funding>Howard Hughes Medical Institute</funding><funding>NIDDK NIH HHS</funding><funding>NCRR NIH HHS</funding><funding>NCI NIH HHS</funding><pagination>eadk0015</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11328906</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>10(33)</volume><pubmed_abstract>Assays that measure morphology, proliferation, motility, deformability, and migration are used to study the invasiveness of cancer cells. However, native invasive potential of cells may be hidden from these contextual metrics because they depend on culture conditions. We created a micropatterned chip that mimics the native environmental conditions, quantifies the invasive potential of tumor cells, and improves our understanding of the malignancy signatures. Unlike conventional assays, which rely on indirect measurements of metastatic potential, our method uses three-dimensional microchannels to measure the basal native invasiveness without chemoattractants or microfluidics. No change in cell death or proliferation is observed on our chips. Using six cancer cell lines, we show that our system is more sensitive than other motility-based assays, measures of nuclear deformability, or cell morphometrics. In addition to quantifying metastatic potential, our platform can distinguish between motility and invasiveness, help study molecular mechanisms of invasion, and screen for targeted therapeutics.</pubmed_abstract><journal>Science advances</journal><pubmed_title>A high-throughput microfabricated platform for rapid quantification of metastatic potential.</pubmed_title><pmcid>PMC11328906</pmcid><funding_grant_id>T32 HD075735</funding_grant_id><funding_grant_id>P30 CA196521</funding_grant_id><funding_grant_id>R37 CA266853</funding_grant_id><funding_grant_id>F31 DK124135</funding_grant_id><funding_grant_id>R01 DK118222</funding_grant_id><funding_grant_id>S10 RR027609</funding_grant_id><pubmed_authors>Ettela A</pubmed_authors><pubmed_authors>Azeloglu EU</pubmed_authors><pubmed_authors>Haydak J</pubmed_authors><pubmed_authors>Hobson CM</pubmed_authors><pubmed_authors>Gallagher EJ</pubmed_authors><pubmed_authors>Bhattacharya S</pubmed_authors><pubmed_authors>Yoo M</pubmed_authors><pubmed_authors>Hone JC</pubmed_authors><pubmed_authors>Stern A</pubmed_authors><pubmed_authors>Chew TL</pubmed_authors><pubmed_authors>Gusella GL</pubmed_authors></additional><is_claimable>false</is_claimable><name>A high-throughput microfabricated platform for rapid quantification of metastatic potential.</name><description>Assays that measure morphology, proliferation, motility, deformability, and migration are used to study the invasiveness of cancer cells. However, native invasive potential of cells may be hidden from these contextual metrics because they depend on culture conditions. We created a micropatterned chip that mimics the native environmental conditions, quantifies the invasive potential of tumor cells, and improves our understanding of the malignancy signatures. Unlike conventional assays, which rely on indirect measurements of metastatic potential, our method uses three-dimensional microchannels to measure the basal native invasiveness without chemoattractants or microfluidics. No change in cell death or proliferation is observed on our chips. Using six cancer cell lines, we show that our system is more sensitive than other motility-based assays, measures of nuclear deformability, or cell morphometrics. In addition to quantifying metastatic potential, our platform can distinguish between motility and invasiveness, help study molecular mechanisms of invasion, and screen for targeted therapeutics.</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Aug</publication><modification>2026-06-05T06:25:28.478Z</modification><creation>2025-04-04T02:50:20.544Z</creation></dates><accession>S-EPMC11328906</accession><cross_references><pubmed>39151003</pubmed><doi>10.1126/sciadv.adk0015</doi></cross_references></HashMap>