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Carlo M. Croce

Researcher at Ohio State University

Publications -  1156
Citations -  199822

Carlo M. Croce is an academic researcher from Ohio State University. The author has contributed to research in topics: microRNA & Cancer. The author has an hindex of 198, co-authored 1135 publications receiving 189007 citations. Previous affiliations of Carlo M. Croce include University of Nebraska Medical Center & University of California, Los Angeles.

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Linkage relationship between the genes for thymidine kinase and galactokinase in different primates.

TL;DR: The results indicate that the linkage relationship between galactokinase and thymidine kinase has been maintained in 3 divergent primate species—man, chimpanzee, and Old World monkey.
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A Fhit-mimetic peptide suppresses annexin A4-mediated chemoresistance to paclitaxel in lung cancer cells

TL;DR: It is demonstrated that Fhit physically interacts with A4 through its N-terminus, which might lead to the generation of novel anticancer drugs to be used in combination with conventional therapies in Fhit-negative tumors to prevent or delay chemoresistance.
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Melanoma and Immunotherapy Bridge 2015 : Naples, Italy. 1-5 December 2015

Vashisht Gopal Yennu Nanda, +399 more
TL;DR: The immunoscore in colorectal cancer highlights the importance of digital scoring systems in surgical pathology and economic sustainability of melanoma treatments: regulatory, health technology assessment and market access issues.
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Chromosome Assignment of the T-Antigen Gene of Simian Virus 40 in African Green Monkey Cells Transformed by Adeno 7-SV40 Hybrid

TL;DR: Somatic cell hybrids between mouse cells deficient in thymidine kinase and monkey cell lines transformed by an adeno 7-SV40 hybrid have been produced using both a semiselective and a double selective procedure and positive correlation between the SV40 T antigen and the same monkey chromosome has been observed.
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Determination of absolute expression profiles using multiplexed miRNA analysis.

TL;DR: This work demonstrates Ligo-miR’s ability to quantify miRNA expression down to 20 copies per cell sensitivity, accurately discriminate between closely related miRNA, and reliably measure differential changes as small as 1.2-fold and the utility of copy number analysis for providing layered insight into expression profile changes.