Machine learning-based immune phenotypes correlate with STK11/KEAP1 co-mutations and prognosis in resectable NSCLC: a sub-study of the TNM-I trial by Rakaee, Mehrdad, Andersen, S, Giannikou, K, Paulsen, Erna-Elise, Kilvær, Thomas Karsten, Rasmussen Busund, Lill-Tove, Berg, Thomas, Richardsen, Elin, Lombardi, Ana Paola, Adib, E, Pedersen, Mona Irene, Tafavvoghi, Masoud, Wahl, Sissel Gyrid Freim, Petersen, R.H, Bondgaard, A.L, Yde, C.W, Baudet, C, Licht, P, Lund-Iversen, Marius, Grønberg, Bjørn Henning, Fjellbirkeland, Lars, Helland, Åslaug, Pøhl, M, Kwiatkowski, D.J, Dønnem, Tom

Request full text

OP0026 Gene expression profiling identifies FYN as important in tamoxifen resistance and a predictor of early recurrence in patients treated with endocrine therapy by Elias, D, Hansen, H, Lænkholm, A.-V, Gjerstorff, M.F, Yde, C.W, Lykkesfeldt, A.E, Ditzel, H.J

Get full text

TP53 mutations are frequently concurrent in patients with BRAF V600E mutated solid tumors and is associated with shorter duration of response to BRAF targeted therapy by Eriksen, M., Yde, C.W., Ahlborn, L.B., Qvortrup, C., Lassen, U., Højgaard, M., Spanggaard, I., Rohrberg, K.S.

Get full text

A kinase inhibitor screen identifies Mcl-1 and Aurora kinase A as novel treatment targets in antiestrogen-resistant breast cancer cells by Thrane, S, Pedersen, A M, Thomsen, M B H, Kirkegaard, T, Rasmussen, B B, Duun-Henriksen, A K, Lænkholm, A V, Bak, M, Lykkesfeldt, A E, Yde, C W

Get full text

Machine learning-based immune phenotypes correlate with STK11/KEAP1 co-mutations and prognosis in resectable NSCLC: a sub-study of the TNM-I trial by Rakaee, Mehrdad, Andersen, S, Giannikou, K, Paulsen, Erna-Elise, Kilvær, Thomas Karsten, Rasmussen Busund, Lill-Tove, Berg, Thomas, Richardsen, Elin, Lombardi, Ana Paola, Adib, E, Pedersen, Mona Irene, Tafavvoghi, Masoud, Wahl, Sissel Gyrid Freim, Petersen, R.H, Bondgaard, A.L, Yde, C.W, Baudet, C, Licht, P, Lund-Iversen, Marius, Grønberg, Bjørn Henning, Fjellbirkeland, Lars, Helland, Åslaug, Pøhl, M, Kwiatkowski, D.J, Dønnem, Tom

Request full text

Comprehensive analysis of failure to carry out successful genomic profiling in a phase I setting by Belcaid, L., Iden, C., Jacobsen, I., Højgaard, M., Spanggaard, I., Tuxen, I.V., Mau-Sørensen, M., Lassen, U., Yde, C.W., Rohrberg, K.S.

Get full text

87P Enhancing treatment strategies for metastatic high-grade neuroendocrine neoplasms: Insights from extensive genomic profiling through WES and WGS in a phase I clinical setting by Krogshede, S.K., Buhl, I.K., Perino, L., Baudet, C., Yde, C.W., Clausen, M.M., Tuxen, I.E.V., Hoejgaard, M., Langer, S.W., Spanggaard, I., Rohrberg, K.S.

Get full text

Gene expression profiling identifies FYN as an important molecule in tamoxifen resistance and a predictor of early recurrence in patients treated with endocrine therapy by Elias, D, Vever, H, Laenkholm, A.-V, Gjerstorff, M.F, Yde, C.W, Lykkesfeldt, A.E, Ditzel, H.J

Get full text

Machine learning-based immune phenotypes correlate with STK11/KEAP1 co-mutations and prognosis in resectable NSCLC: a sub-study of the TNM-I trial by Rakaee, Mehrdad, Andersen, S, Giannikou, K, Paulsen, Erna-Elise, Kilvær, Thomas Karsten, Rasmussen Busund, Lill-Tove, Berg, Thomas, Richardsen, Elin, Lombardi, Ana Paola, Adib, E, Pedersen, Mona Irene, Tafavvoghi, Masoud, Wahl, Sissel Gyrid Freim, Petersen, R.H, Bondgaard, A.L, Yde, C.W, Baudet, C, Licht, P, Lund-Iversen, Marius, Grønberg, Bjørn Henning, Fjellbirkeland, Lars, Helland, Åslaug, Pøhl, M, Kwiatkowski, D.J, Dønnem, Tom

Request full text

The length distribution of frangible biofilaments by Michaels, Thomas C T, Yde, Pernille, Willis, Julian C W, Jensen, Mogens H, Otzen, Daniel, Dobson, Christopher M, Buell, Alexander K, Knowles, Tuomas P J

Get full text