Pathology & Laboratory Medicine

Publications

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2022

Weinberg OK, Siddon A, Madanat YF, Gagan J, Arber DA, Dal Cin P, et al. TP53 mutation defines a unique subgroup within complex karyotype de novo and therapy-related MDS/AML. Blood Adv. 2022;6(9):2847-2853.

Feng H, Jiang B, Xing W, Sun J, Greenblatt MB, Zou W. Skeletal stem cells: origins, definitions, and functions in bone development and disease. Life Med. 2022;1(3):276-293.

Cyrta J, Prandi D, Arora A, Hovelson DH, Sboner A, Rodriguez A, et al. Comparative genomics of primary prostate cancer and paired metastases: insights from 12 molecular case studies. J Pathol. 2022;257(3):274-284.

Rosenthal J, Carelli R, Omar M, Brundage D, Halbert E, Nyman J, et al. Building Tools for Machine Learning and Artificial Intelligence in Cancer Research: Best Practices and a Case Study with the PathML Toolkit for Computational Pathology. Mol Cancer Res. 2022;20(2):202-206.

Magro C, Shapiro L. Exploring the pathophysiologic basis of constrictive pericarditis of Kohlmeier Degos disease: A case series and review of the literature. Ann Diagn Pathol. 2022;59:151943.

Marzio A, Kurz E, Sahni JM, Di Feo G, Puccini J, Jiang S, et al. EMSY inhibits homologous recombination repair and the interferon response, promoting lung cancer immune evasion. Cell. 2022;185(1):169-183.e19.

Qiu X, Boufaied N, Hallal T, Feit A, de Polo A, Luoma AM, et al. MYC drives aggressive prostate cancer by disrupting transcriptional pause release at androgen receptor targets. Nat Commun. 2022;13(1):2559.

De La Vega LL, Comeau H, Sallan S, Al-Ibraheemi A, Gupta H, Li YY, et al. Rare FGFR Oncogenic Alterations in Sequenced Pediatric Solid and Brain Tumors Suggest FGFR Is a Relevant Molecular Target in Childhood Cancer. JCO Precis Oncol. 2022;6:e2200390.

Cao XE, Ongagna-Yhombi SY, Wang R, Ren Y, Srinivasan B, Hayden JA, et al. A diagnostic platform for rapid, simultaneous quantification of procalcitonin and C-reactive protein in human serum. EBioMedicine. 2022;76:103867.

Liechty B, Xu Z, Zhang Z, Slocum C, Bahadir CD, Sabuncu MR, et al. Machine learning can aid in prediction of IDH mutation from H&E-stained histology slides in infiltrating gliomas. Sci Rep. 2022;12(1):22623.