Pathology & Laboratory Medicine

Publications

Filter By Faculty

Filter by Principal Investigator

2022

Melanson SE, Zhao Z, Kumanovics A, Love T, Meng QH, Wu AH, et al. Tolerance for three commonly administered COVID-19 vaccines by healthcare professionals. Front Public Health. 2022;10:975781.

Szczepanski JM, Hissong E, Manthei DM. Use of Selective Arterial Calcium Stimulation Testing in Identification of Insulinoma in a Patient After Bariatric Surgery. Lab Med. 2022;53(2):e40-e43.

Adhikari S, Guha D, Mohan C, Mukherjee S, Tyler JK, Das C. Reprogramming Carbohydrate Metabolism in Cancer and Its Role in Regulating the Tumor Microenvironment. Subcell Biochem. 2022;100:3-65.

Webster AL, Sanders MA, Patel K, Dietrich R, Noonan RJ, Lach FP, et al. Genomic signature of Fanconi anaemia DNA repair pathway deficiency in cancer. Nature. 2022;612(7940):495-502.

Haigh DB, Woodcock CL, Lothion-Roy J, Harris AE, Metzler VM, Persson JL, et al. The METTL3 RNA Methyltransferase Regulates Transcriptional Networks in Prostate Cancer. Cancers (Basel). 2022;14(20).

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.

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.

Stover EH, Oh C, Keskula P, Choudhury AD, Tseng Y-, Adalsteinsson VA, et al. Implementation of a prostate cancer-specific targeted sequencing panel for credentialing of patient-derived cell lines and genomic characterization of patient samples. Prostate. 2022;82(5):584-597.

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.

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.