Pathology & Laboratory Medicine

Publications

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2021

Imada EL, Sanchez DF, Dinalankara W, Vidotto T, Ebot EM, Tyekucheva S, et al. Transcriptional landscape of PTEN loss in primary prostate cancer. BMC Cancer. 2021;21(1):856.

Wangsiricharoen S, Wakely PE, Siddiqui MT, Ali SZ. Cytopathology of chondromyxoid fibroma: a case series and review of the literature. J Am Soc Cytopathol. 2021;10(4):366-381.

Conteduca V, Ku S-, Fernandez L, Dago-Rodriquez A, Lee J, Jendrisak A, et al. Circulating tumor cell heterogeneity in neuroendocrine prostate cancer by single cell copy number analysis. NPJ Precis Oncol. 2021;5(1):76.

Mahdi Z, Ettel MG, Gonzalez RS, Hart J, Alpert L, Fang J, et al. Metastases can occur in cirrhotic livers with patent portal veins. Diagn Pathol. 2021;16(1):18.

Shah RB, Cai Q, Aron M, Berney DM, Cheville JC, Deng F-, et al. Diagnosis of "cribriform" prostatic adenocarcinoma: an interobserver reproducibility study among urologic pathologists with recommendations. Am J Cancer Res. 2021;11(8):3990-4001.

Jacob RP, Flynn J, Devlin SM, Maloy M, Giralt SA, Maslak P, et al. Universal Engraftment after Allogeneic Hematopoietic Cell Transplantation Using Cryopreserved CD34-Selected Grafts. Transplant Cell Ther. 2021;27(8):697.e1-697.e5.

Manning DK, Shivdasani P, Koeller DR, Schwartz A, Rana HQ, Garber JE, et al. Assessment of genomic alterations in non-syndromic von Hippel-Lindau: Insight from integrating somatic and germline next generation sequencing genomic data. Data Brief. 2021;39:107653.

Moskowitz AJ, Ghione P, Jacobsen E, Ruan J, Schatz JH, Noor S, et al. A phase 2 biomarker-driven study of ruxolitinib demonstrates effectiveness of JAK/STAT targeting in T-cell lymphomas. Blood. 2021;138(26):2828-2837.

Jesser EA, Brady NJ, Huggins DN, Witschen PM, O'Connor CH, Schwertfeger KL. STAT5 is activated in macrophages by breast cancer cell-derived factors and regulates macrophage function in the tumor microenvironment. Breast Cancer Res. 2021;23(1):104.

Ikemura K, Bellin E, Yagi Y, Billett H, Saada M, Simone K, et al. Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study. J Med Internet Res. 2021;23(2):e23458.