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References: Cancer Targeted Therapy

  • Writer: FibonacciMD
    FibonacciMD
  • May 20, 2024
  • 5 min read

Updated: May 20

References for CME Article


References


  1. Kurnit KC, Bailey AM, Zeng J, Johnson AM, Shufean MdA, Brusco L, et al. “Personalized Cancer Therapy”: A Publicly Available Precision Oncology Resource. Cancer Research [Internet]. 2017 Oct 31 [cited 2024 May 7];77(21):e123–6. Retrieved from:  https://typeset.io/papers/personalized-cancer-therapy-a-publicly-available-precision-4a0jvev7yx

  2. Nair L, Gonzalez-Angulo AM. Chapter 13 - Personalized Therapies for Cancer Treatment. In: Singh M, Salnikova M, editors. Novel Approaches and Strategies for Biologics, Vaccines and Cancer Therapies [Internet]. San Diego: Academic Press; 2015 [cited 2024 May 7]. p. 317–46. Retrieved from: https://typeset.io/papers/personalized-therapies-for-cancer-treatment-wi5xgscufk

  3. Kumar A, Weller KP, Vilgelm AE. Chapter Twelve - Personalized cancer immunotherapy. In: Amiji MM, Milane LS, editors. Engineering Technologies and Clinical Translation [Internet]. Academic Press; 2022 [cited 2024 May 7]. p. 399–426. Retrieved from: https://typeset.io/papers/personalized-cancer-immunotherapy-3rxoo14qtf

  4. Lai X, Geier OM, Fleischer T, Garred Ø, Borgen E, Funke SW, et al. Toward Personalized Computer Simulation of Breast Cancer Treatment: A Multiscale Pharmacokinetic and Pharmacodynamic Model Informed by Multitype Patient Data. Cancer Res. 2019 Aug 15;79(16):4293–304. Retrieved from:  https://typeset.io/papers/data-from-toward-personalized-computer-simulation-of-breast-1ikjin4o

  5. Rodrigues-Ferreira S, Nahmias C. Predictive biomarkers for personalized medicine in breast cancer. Cancer Lett. 2022 Oct 1;545:215828. Retrieved from: https://typeset.io/papers/predictive-biomarkers-for-personalized-medicine-in-breast-h09fgxma

  6. Shatsky R, Parker BA, Bui NQ, Helsten T, Schwab RB, Boles SG, et al. Next-Generation Sequencing of Tissue and Circulating Tumor DNA: The UC San Diego Moores Center for Personalized Cancer Therapy Experience with Breast Malignancies. Mol Cancer Ther. 2019 May;18(5):1001–11. Retrieved from:  https://typeset.io/papers/data-from-next-generation-sequencing-of-tissue-and-19e8isbi

  7. Verma M, Abdelrahman L, Collado-Mesa F, Abdel-Mottaleb M. Multimodal Spatiotemporal Deep Learning Framework to Predict Response of Breast Cancer to Neoadjuvant Systemic Therapy. Diagnostics (Basel). 2023 Jul 3;13(13):2251. Retrieved from:  https://typeset.io/papers/multimodal-spatiotemporal-deep-learning-framework-to-predict-rt3eipz1

  8. Huang Z, Parwani AV, Huang K, Li Z. Abstract 5436: Developing artificial intelligence algorithms to predict response to neoadjuvant chemotherapy in HER2-positive breast cancer. Cancer Research [Internet]. 2023 Apr 4 [cited 2024 May 7];83(7_Supplement):5436. Retrieved from: https://doi.org/10.1158/1538-7445. Available from: https://typeset.io/papers/abstract-5436-developing-artificial-intelligence-algorithms-2m55vh44

  9. Yang M, Liu Y, Zhang C, Hsueh YC, Zhang Q, Fan Y, et al. A Genome-Informed Functional Modeling Approach to Evaluate the Responses of Breast Cancer Patients to CDK4/6 Inhibitors-Based Therapies and Simulate Real-World Clinical Trials [Internet]. medRxiv; 2023 [cited 2024 May 7]. p. 2023.05.15.23289976. Retrieved from:  https://www.medrxiv.org/content/10.1101/2023.05.15.23289976v2

  10. Shen B, Saito A, Ueda A, Fujita K, Nagamatsu Y, Hashimoto M, et al. Development of multiple AI pipelines that predict neoadjuvant chemotherapy response of breast cancer using H&E-stained tissues. J Pathol Clin Res. 2023 May;9(3):182–94. Retrieved from: https://typeset.io/papers/development-of-multiple-ai-pipelines-that-predict-2e1f3nld

  11. Krishnamurthy S, Jain P, Tripathy D, Basset R, Randhawa R, Muhammad H, et al. Predicting Response of Triple-Negative Breast Cancer to Neoadjuvant Chemotherapy Using a Deep Convolutional Neural Network-Based Artificial Intelligence Tool. JCO Clin Cancer Inform. 2023 Mar;7:e2200181.Retrieved from:  https://typeset.io/papers/predicting-response-of-triple-negative-breast-cancer-to-jou5dlc1

  12. Adnan N, Najnin T, Ruan J. A Robust Personalized Classification Method for Breast Cancer Metastasis Prediction. Cancers (Basel). 2022 Oct 29;14(21):5327. Retrieved from: https://typeset.io/papers/a-robust-personalized-classification-method-for-breast-18dd68lk

  13. Klocker EV, Balic M, Steger G. Molecular profiling leading to personalized treatment in breast cancer. memo [Internet]. 2022 Sep 1 [cited 2024 May 7];15(3):196–200. Retrieved from:  https://typeset.io/papers/molecular-profiling-leading-to-personalized-treatment-in-3i20ovt9

  14. Köhn-Luque A, Lai X, Frigessi A. Towards personalized computer simulations of breast cancer treatment [Internet]. arXiv; 2020 [cited 2024 May 7]. Retrieved from:  https://typeset.io/papers/towards-personalized-computer-simulations-of-breast-cancer-2ndi5nqsvk

  15. Graham DM, Rupprecht G, Bankaitis ED, Force JM, Watlington W, Metzger SW, et al. Abstract 192: A novel and rapid patient-derived organoid breast cancer platform for precision medicine. Cancer Research [Internet]. 2023 Apr 4 [cited 2024 May 7];83(7_Supplement):192. Retrieved from:  https://doi.org/10.1158/1538-7445.AM2023-192

  16. Önder CE, Ziegler TJ, Becker R, Brucker SY, Hartkopf AD, Engler T, et al. Advancing Cancer Therapy Predictions with Patient-Derived Organoid Models of Metastatic Breast Cancer. Cancers [Internet]. 2023 Jan [cited 2024 May 7];15(14):3602. Retrieved from:  https://www.mdpi.com/2072-6694/15/14/3602

  17. Ryu WJ, Park S, Lee JD, Hwang Y, Jo S, Yong KT, et al. Abstract 178: Establishment of patient-derived organoid of breast cancer. Cancer Research [Internet]. 2023 Apr 4 [cited 2024 May 7];83(7_Supplement):178. Retrieved from:  https://doi.org/10.1158/1538-7445.AM2023-178

  18. Li X, Zhu D. Advances in breast cancer organoid for individualized treatment. Organs-on-a-Chip [Internet]. 2023 Dec 1 [cited 2024 May 7];5:100028. Available from: https://www.sciencedirect.com/science/article/pii/S2666102023000034

  19. Ding S, Kanikarla Marie P, Baro N, Raman R, Helman E, Hsu SD, et al. Refractory colorectal cancer patient derived MicroOrganoSpheres (MOS) to enable correlation of targeted therapy combination response with clinical outcomes. JCO [Internet]. 2023 Jun [cited 2024 May 7];41(16_suppl):e15574–e15574. Retrieved from: https://ascopubs.org/doi/10.1200/JCO.2023.41.16_suppl.e15574

  20. Dayanidhi DL, Rupprecht G, Watlington W, Mantyh J, Kim SY, McCall SJ, et al. MicroOrganoSpheres as a clinically applicable precision oncology platform for the discovery of novel therapies in colorectal cancer. JCO [Internet]. 2023 Jun [cited 2024 May 7];41(16_suppl):3592–3592. Retrieved from:  https://ascopubs.org/doi/10.1200/JCO.2023.41.16_suppl.3592

  21. Jacobs AT, Martinez Castaneda-Cruz D, Rose MM, Connelly L. Targeted therapy for breast cancer: An overview of drug classes and outcomes. Biochemical Pharmacology [Internet]. 2022 Oct 1 [cited 2024 May 7];204:115209. Retrieved from: https://www.sciencedirect.com/science/article/pii/S0006295222003033

  22. Więsyk PJ, Oleksa P, Chilimoniuk Z, Dobosz M, Sobczyk M, Słaboń M. Targeted therapy with histamine antagonists - New challenges to fight with breast cancer. Journal of Education, Health and Sport [Internet]. 2022 Nov 15 [cited 2024 May 7];12(12):87–93. Retrieved from: https://apcz.umk.pl/JEHS/article/view/40145

  23. Ye F, Dewanjee S, Li Y, Jha NK, Chen ZS, Kumar A, et al. Advancements in clinical aspects of targeted therapy and immunotherapy in breast cancer. Molecular Cancer [Internet]. 2023 Jul 6 [cited 2024 May 7];22(1):105. Retrieved from:  https://doi.org/10.1186/s12943-023-01805-y

  24. Xu D, Liu Z, Liang MX, Fei YJ, Zhang W, Wu Y, et al. Endoplasmic reticulum stress targeted therapy for breast cancer. Cell Communication and Signaling [Internet]. 2022 Nov 7 [cited 2024 May 7];20(1):174. Retrieved from:  https://doi.org/10.1186/s12964-022-00964-7

  25. An J, Peng C, Xie X, Peng F. New Advances in Targeted Therapy of HER2-Negative Breast Cancer. Front Oncol [Internet]. 2022 Mar 4 [cited 2024 May 7];12. Retrieved from: https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.828438/full

  26. Demir Cetinkaya B, Biray Avci C. Molecular perspective on targeted therapy in breast cancer: a review of current status. Med Oncol [Internet]. 2022 Jul 14 [cited 2024 May 7];39(10):149.  Retrieved from: https://doi.org/10.1007/s12032-022-01749-1

  27. Zhang Y, Pan H, Yu C, Liu R, Xing B, Jia B, et al. Phytoestrogen-derived multifunctional ligands for targeted therapy of breast cancer. Asian Journal of Pharmaceutical Sciences [Internet]. 2023 Jul 1 [cited 2024 May 7];18(4):100827. Retrieved from: https://www.sciencedirect.com/science/article/pii/S1818087623000545

  28. Subhan MA, Torchilin VP. Advances in Targeted Therapy of Breast Cancer with Antibody-Drug Conjugate. Pharmaceutics [Internet]. 2023 Apr [cited 2024 May 7];15(4):1242. Retrieved from:  https://www.mdpi.com/1999-4923/15/4/1242

  29. Sacituzumab Govitecan (Trodelvy): CADTH Reimbursement Recommendation [Internet]. Ottawa (ON): Canadian Agency for Drugs and Technologies in Health; 2022 [cited 2023 Nov 21]. (CADTH Reimbursement Reviews and Recommendations). Retrieved from: http://www.ncbi.nlm.nih.gov/books/NBK595400/

  30. Bardia A, Tolaney SM, Loirat D, Punie K, Oliveira M, Rugo HS, et al. Sacituzumab govitecan (SG) versus treatment of physician’s choice (TPC) in patients (pts) with previously treated, metastatic triple-negative breast cancer (mTNBC): Final results from the phase 3 ASCENT study. JCO [Internet]. 2022 Jun [cited 2023 Nov 21];40(16_suppl):1071–1071.Retrieved from:  https://ascopubs.org/doi/abs/10.1200/JCO.2022.40.16_suppl.1071

  31. TRODELVY (sacituzumab govitecan-hziy) prescribing information. Gilead website. Revised 4/2024. Retrieved from: https://www.trodelvyhcp.com/-/media/project/trodelvy/trodelvyhcp/hcp/resource-pdf/trodelvy_pi.pdf

  32. André F, Hee Park Y, Kim SB, Takano T, Im SA, Borges G, et al. Trastuzumab deruxtecan versus treatment of physician’s choice in patients with HER2-positive metastatic breast cancer (DESTINY-Breast02): a randomised, open-label, multicentre, phase 3 trial. Lancet. 2023 May 27;401(10390):1773–85. Retrieved from: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(23)00725-0/abstract

  33. Van Cutsem E, di Bartolomeo M, Smyth E, Chau I, Park H, Siena S, et al. Trastuzumab deruxtecan in patients in the USA and Europe with HER2-positive advanced gastric or gastroesophageal junction cancer with disease progression on or after a trastuzumab-containing regimen (DESTINY-Gastric02): primary and updated analyses from a single-arm, phase 2 study. Lancet Oncol. 2023 Jul;24(7):744–56. Retrieved from: https://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(23)00215-2/abstract



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