Optimizing individualized treatment strategy based on breast cancer organoid model.
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ABSTRACT:
SUBMITTER: Pan B
PROVIDER: S-EPMC8012563 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Gallbladder cancer is a highly aggressive malignancy with poor sensitivity to postoperative radiotherapy or chemotherapy; therefore, the development of individualized treatment strategies is paramount to improve patient outcomes. Both patient-derived tumor xenograft (PDX) and patient-derived tumor organoid (PDO) models derived from surgical specimens can better preserve the biological characteristics and heterogeneity of individual original tumors, display a unique advantage for individualized therapy and predicting clinical outcomes. In this study, PDX and PDO models of advanced gallbladder cancer were established, and the consistency of biological characteristics between them and primary patient samples was confirmed using pathological analysis and RNA-sequencing. Additionally, we tested the efficacy of chemotherapeutic drugs, targeted drugs, and immune checkpoint inhibitors using these two models. The results demonstrated that gemcitabine combined with cisplatin induced significant therapeutic effects. Furthermore, treatment with immune checkpoint inhibitors elicited promising responses in both the humanized mice and PDO immune models. Based on these results, gemcitabine combined with cisplatin was used for basic treatment, and immune checkpoint inhibitors were applied as a complementary intervention for gallbladder cancer. The patient responded well to treatment and exhibited a clearance of tumor foci. Our findings indicate that the combined use of PDO and PDX models can guide the clinical treatment course for gallbladder cancer patients to achieve individualized and effective treatment.
| S-EPMC9795198 | biostudies-literature
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.
| S-EPMC10614126 | biostudies-literature
Project description:Colorectal cancer (CRC) is the third most common cancer, and nearly half of CRC patients experience metastases. Oligometastatic CRC represents a distinct clinical state characterized by limited metastatic involvement, demonstrating a less aggressive nature and potentially improved survival with multidisciplinary treatment. However, the varied clinical scenarios giving rise to oligometastases necessitate a precise definition, considering primary tumor status and oncological factors, to optimize treatment strategies. This review delineates the concepts of oligometastatic CRC, encompassing oligo-recurrence, where the primary tumor is under control, resulting in a more favorable prognosis. A comprehensive examination of multidisciplinary treatment with local treatments and systemic therapy is provided. The overarching objective in managing oligometastatic CRC is the complete eradication of metastases, offering prospects of a cure. Essential to this management approach are local treatments, with surgical resection serving as the standard of care. Percutaneous ablation and stereotactic body radiotherapy present less invasive alternatives for lesions unsuitable for surgery, demonstrating efficacy in select cases. Perioperative systemic therapy, aiming to control micrometastatic disease and enhance local treatment effectiveness, has shown improvements in progression-free survival through clinical trials. However, the extension of overall survival remains variable. The review emphasizes the need for further prospective trials to establish a cohesive definition and an optimized treatment strategy for oligometastatic CRC.
| S-EPMC10777959 | biostudies-literature
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.
| S-EPMC5224985 | biostudies-literature
Project description:BACKGROUND & AIMS:Our 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. METHODS:Organoids 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. RESULTS:Whereas 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. CONCLUSIONS:The 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.
| S-EPMC6279812 | biostudies-literature
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.
| S-EPMC6048669 | biostudies-literature
Project description:Current guidelines for treatment decision making largely rely on data from randomized controlled trials (RCTs) studying average treatment effects. They may be inadequate to make individualized treatment decisions in real-world settings. Large-scale electronic health records (EHR) provide opportunities to fulfill the goals of personalized medicine and learn individualized treatment rules (ITRs) depending on patient-specific characteristics from real-world patient data. In this work, we tackle challenges with EHRs and propose a machine learning approach based on matching (M-learning) to estimate optimal ITRs from EHRs. This new learning method performs matching instead of inverse probability weighting as commonly used in many existing methods for estimating ITRs to more accurately assess individuals' treatment responses to alternative treatments and alleviate confounding. Matching-based value functions are proposed to compare matched pairs under a unified framework, where various types of outcomes for measuring treatment response (including continuous, ordinal, and discrete outcomes) can easily be accommodated. We establish the Fisher consistency and convergence rate of M-learning. Through extensive simulation studies, we show that M-learning outperforms existing methods when propensity scores are misspecified or when unmeasured confounders are present in certain scenarios. Lastly, we apply M-learning to estimate optimal personalized second-line treatments for type 2 diabetes patients to achieve better glycemic control or reduce major complications using EHRs from New York Presbyterian Hospital.
| S-EPMC7539620 | biostudies-literature
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.
| S-EPMC5347121 | biostudies-literature
Project description:BackgroundSeveral studies have proposed personalized strategies based on women's individual breast cancer risk to improve the effectiveness of breast cancer screening. We designed and internally validated an individualized risk prediction model for women eligible for mammography screening.MethodsRetrospective cohort study of 121,969 women aged 50 to 69 years, screened at the long-standing population-based screening program in Spain between 1995 and 2015 and followed up until 2017. We used partly conditional Cox proportional hazards regression to estimate the adjusted hazard ratios (aHR) and individual risks for age, family history of breast cancer, previous benign breast disease, and previous mammographic features. We internally validated our model with the expected-to-observed ratio and the area under the receiver operating characteristic curve.ResultsDuring a mean follow-up of 7.5 years, 2,058 women were diagnosed with breast cancer. All three risk factors were strongly associated with breast cancer risk, with the highest risk being found among women with family history of breast cancer (aHR: 1.67), a proliferative benign breast disease (aHR: 3.02) and previous calcifications (aHR: 2.52). The model was well calibrated overall (expected-to-observed ratio ranging from 0.99 at 2 years to 1.02 at 20 years) but slightly overestimated the risk in women with proliferative benign breast disease. The area under the receiver operating characteristic curve ranged from 58.7% to 64.7%, depending of the time horizon selected.ConclusionsWe developed a risk prediction model to estimate the short- and long-term risk of breast cancer in women eligible for mammography screening using information routinely reported at screening participation. The model could help to guiding individualized screening strategies aimed at improving the risk-benefit balance of mammography screening programs.
| S-EPMC7987139 | biostudies-literature
Project description:In colorectal cancers, the tumor microenvironment plays a key role in prognosis and therapy efficacy. Patient-derived tumor organoids (PDTO) show enormous potential for preclinical testing; however, cultured tumor cells lose important characteristics, including the consensus molecular subtypes (CMS). To better reflect the cellular heterogeneity, we established the colorectal cancer organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAF) from 30 patients. Context-specific phenotyping showed that xenotransplantation or coculture with CAFs improves the transcriptomic fidelity and instructs subtype-specific stromal gene expression. Furthermore, functional profiling in coculture exposed CMS4-specific therapeutic resistance to gefitinib and SN-38 and prognostic expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as a common target. Our results demonstrate that colorectal cancer phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for a faithful representation of molecular subtypes and therapy responses ex vivo.SignificanceSystematic characterization of the organoid-stroma biobank provides a resource for context dependency in colorectal cancer. We demonstrate a colorectal cancer subtype memory of PDTOs that is independent of specific driver mutations. Our data underscore the importance of functional profiling in cocultures for improved preclinical testing and identification of stromal resistance mechanisms. This article is featured in Selected Articles from This Issue, p. 2109.
| S-EPMC10551667 | biostudies-literature