Optimizing individualized treatment strategy based on breast cancer organoid model.
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ABSTRACT:
SUBMITTER: Pan B
PROVIDER: S-EPMC8012563 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
Publications
Optimizing individualized treatment strategy based on breast cancer organoid model.
Pan Bo B Li Xuelu X Zhao Dongyi D Li Ning N Wang Kainan K Li Man M Zhao Zuowei Z
Clinical and translational medicine 20210401 4
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Project description:A novel functional additive model is proposed, which is uniquely modified and constrained to model nonlinear interactions between a treatment indicator and a potentially large number of functional and/or scalar pretreatment covariates. The primary motivation for this approach is to optimize individualized treatment rules based on data from a randomized clinical trial. We generalize functional additive regression models by incorporating treatment-specific components into additive effect components. A structural constraint is imposed on the treatment-specific components in order to provide a class of additive models with main effects and interaction effects that are orthogonal to each other. If primary interest is in the interaction between treatment and the covariates, as is generally the case when optimizing individualized treatment rules, we can thereby circumvent the need to estimate the main effects of the covariates, obviating the need to specify their form and thus avoiding the issue of model misspecification. The methods are illustrated with data from a depression clinical trial with electroencephalogram functional data as patients' pretreatment covariates.
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Project description:BackgroundPatients with pancreatic ductal adenocarcinoma (PDAC) who undergo surgical resection and receive effective chemotherapy have the best chance for long-term survival. Unfortunately, because of the heterogeneity of pancreatic cancer, it is difficult to find a personalized treatment strategy for patients. Organoids are ideal preclinical models for personalized medicine. Therefore, we explore the cultivation conditions and construction methods of PDAC organoid models to screen the individualized therapy strategy.MethodsFresh PDAC tissues from surgical resection were collected and digested with digestive enzymes; then the tumor cells were embedded in Matrigel with a suitable medium to establish the PDAC organoid models. The genetic stability of the organoids was analyzed using whole exon sequencing; hematoxylin and eosin staining and immunohistochemistry of organoids were performed to analyze their consistency with the pathological morphology of the patient's tumor tissue; After 2 days of organoid culture, we selected four commonly used clinical chemotherapy drugs for single or combined treatment to analyze drug sensitivity.ResultsTwo cases of PDAC organoid models were successfully established, and the results of their pathological characteristics and exome sequencing were consistent with those of the patient's tumor tissue. Both PDAC organoids showed more sensitivity to gemcitabine and cisplatin, and the combined treatment was more effective than monotherapy.ConclusionBoth organoids better retained the pathological characteristics, genomic stability, and heterogeneity with the original tumor. Individual PDAC organoids exhibited different sensitivities to the same drugs. Thus, this study provided ideal experimental models for screening individualized therapy strategy for patients with PDAC.
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Project description:PurposePatients diagnosed with invasive breast cancer (BC) or ductal carcinoma in situ are increasingly choosing to undergo contralateral prophylactic mastectomy (CPM) to reduce their risk of contralateral BC (CBC). This is a particularly disturbing trend as a large proportion of these CPMs are believed to be medically unnecessary. Many BC patients tend to substantially overestimate their CBC risk. Thus, there is a pressing need to educate patients effectively on their CBC risk. We develop a CBC risk prediction model to aid physicians in this task.MethodsWe used data from two sources: Breast Cancer Surveillance Consortium and Surveillance, Epidemiology, and End Results to build the model. The model building steps are similar to those used in developing the BC risk assessment tool (popularly known as Gail model) for counseling women on their BC risk. Our model, named CBCRisk, is exclusively designed for counseling women diagnosed with unilateral BC on the risk of developing CBC.ResultsWe identified eight factors to be significantly associated with CBC-age at first BC diagnosis, anti-estrogen therapy, family history of BC, high-risk pre-neoplasia status, estrogen receptor status, breast density, type of first BC, and age at first birth. Combining the relative risk estimates with the relevant hazard rates, CBCRisk projects absolute risk of developing CBC over a given period.ConclusionsBy providing individualized CBC risk estimates, CBCRisk may help in counseling of BC patients. In turn, this may potentially help alleviate the rate of medically unnecessary CPMs.
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Project description:The development of human epidermal growth factor 2 (HER2)-directed therapy has resulted in significant improvement in outcomes for patients with early-stage HER2-overexpressing (HER2+) breast cancer. In recent years, newer HER2-directed agents and novel treatment strategies have been developed with ongoing improvements in overall outcomes. However, with the addition of newer agents, there is an increasing need to risk stratify patients to maximize efficacy and minimize toxicity of treatment. De-escalation of therapy with the potential to shorten the duration of adjuvant therapy and minimize chemotherapy administration in patients with favorable disease can be considered. On the other hand, escalation of therapy with the addition of novel HER2-directed agents and extended duration of therapy in patients at high risk of relapse can help improve long-term cure rates. Herein, we discuss recent developments in neoadjuvant and adjuvant strategies for the treatment of potentially curable HER2+ breast cancer.
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Project description:Background & aimsOur goal was to develop an initial study for the proof of concept whereby gastric cancer organoids are used as an approach to predict the tumor response in individual patients.MethodsOrganoids were derived from resected gastric cancer tumors (huTGOs) or normal stomach tissue collected from sleeve gastrectomies (huFGOs). Organoid cultures were treated with standard-of-care chemotherapeutic drugs corresponding to patient treatment: epirubicin, oxaliplatin, and 5-fluorouracil. Organoid response to chemotherapeutic treatment was correlated with the tumor response in each patient from whom the huTGOs were derived. HuTGOs were orthotopically transplanted into the gastric mucosa of NOD scid gamma mice.ResultsWhereas huFGOs exhibited a half maximal inhibitory concentration that was similar among organoid lines, divergent responses and varying half maximal inhibitory concentration values among the huTGO lines were observed in response to chemotherapeutic drugs. HuTGOs that were sensitive to treatment were derived from a patient with a near complete tumor response to chemotherapy. However, organoids resistant to treatment were derived from patients who exhibited no response to chemotherapy. Orthotropic transplantation of organoids resulted in the engraftment and development of human adenocarcinoma. RNA sequencing revealed that huTGOs closely resembled the patient's native tumor tissue and not commonly used gastric cancer cell lines and cell lines derived from the organoid cultures.ConclusionsThe treatment of patient-derived organoids alongside patients from whom cultures were derived will ultimately test their usefulness to predict individual therapy response and patient outcome.
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Project description:Interactions of high-frequency radio waves (RF) with biological tissues are currently being investigated as a therapeutic platform for non-invasive cancer hyperthermia therapy. RF delivers thermal energy into tissues, which increases intra-tumoral drug perfusion and blood-flow. Herein, we describe an optical-based method to optimize the short-term treatment schedules of drug and hyperthermia administration in a 4T1 breast cancer model via RF, with the aim of maximizing drug localization and homogenous distribution within the tumor microenvironment. This method, based on the analysis of fluorescent dyes localized into the tumor, is more time, cost and resource efficient, when compared to current analytical methods for tumor-targeting drug analysis such as HPLC and LC-MS. Alexa-Albumin 647 nm fluorphore was chosen as a surrogate for nab-paclitaxel based on its similar molecular weight and albumin driven pharmacokinetics. We found that RF hyperthermia induced a 30-40% increase in Alexa-Albumin into the tumor micro-environment 24 h after treatment when compared to non-heat treated mice. Additionally, we showed that the RF method of delivering hyperthermia to tumors was more localized and uniform across the tumor mass when compared to other methods of heating. Lastly, we provided insight into some of the factors that influence the delivery of RF hyperthermia to tumors.
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