Precision Medicine in Pancreatic Cancer: Patient-Derived Organoid Pharmacotyping Is a Predictive Biomarker of Clinical Treatment Response

Patient-derived organoids from pancreatic cancer after pancreatectomy: Feasibility and organoid take rate in treatment-naïve periampullary tumors

BACKGROUND/OBJECTIVE

Patient-derived organoids (PDOs) have emerged as essential for ex vivo modelling for pancreatic cancer (PDAC) but reports on efficacy and organoid take rate are scarce. This study aimed to assess the feasibility of establishing PDOs from resected specimens in periampullary tumors.

METHODS

Patients undergoing surgery for suspected periampullary cancer were included. PDO protocol amendments were tested, with organoid take rate as outcome measure. Samples from resected specimens were processed and expanded per protocol. Pooled estimate of take rates of PDOs in PDAC was derived from literature search.

RESULTS

23 specimens were available for PDO, of which 10 were PDAC. In 15 patients other histopathology was found: neuroendocrine tumors (NET; n = 2), neuroendocrine carcinoma (NEC; n = 1), intraductal papillary mucinous neoplasm (IPMN; n = 4), distal cholangiocarcinoma (dCCA; n = 1), ampullary carcinoma (n = 1), duodenal carcinoma (n = 1), intra-ampullary papillary tubular neoplasm (IAPN; n = 1), indeterminate PDAC/ampullary carcinoma(n = 1), and one patient with chronic inflammation/fibrosis. Organoid cultures were grown from 7 of 10 (70 %) PDAC, 1 dCCA, 1 NEC, 1 duodenal carcinoma, 1 indeterminate tumor type and 1 ampullary carcinoma (i.e. 12/18; 66.7 % across periampullary cancers). Overall take rate of PDOs was 12 of 23 (52.2 %) for all tumors. A pooled mean estimate PDO take rate of 62.3 % (95 % CI:54.8-69.3 %) was reported across available studies in the literature.

CONCLUSION

In the current study, we found that PDOs could be established from resected pancreatic tumors in over half of resected periampullary tumors, and highest in PDACs. As such, generating a pancreatic cancer PDO biobank for translational research was feasible after cryopreservation.

Development and validation of the Normalized Organoid Growth Rate (NOGR) metric in brightfield imaging-based assays

This study focuses on refining growth-rate-based drug response metrics for patient-derived tumor organoid screening using brightfield live-cell imaging. Traditional metrics like Normalized Growth Rate Inhibition (GR) and Normalized Drug Response (NDR) have been used to assess organoid responses to anticancer treatments but face limitations in accurately quantifying cytostatic and cytotoxic effects across varying growth rates. Here, we introduce the Normalized Organoid Growth Rate (NOGR) metric, specifically developed for brightfield imaging-based assays. A label-free image analysis model was applied to segment organoids precisely, track their growth rates over time, and classify viable and dead organoids. Testing eleven phenotypically distinct pancreatic cancer organoid models with five chemotherapeutics demonstrates that the NOGR metric more effectively captures cytostatic and cytotoxic drug effects compared to existing methods. This approach enhances the biological relevance of drug sensitivity assessments on organoids and offers a valuable tool for advancing personalized cancer treatment strategies.

Molecular Spectroscopy for the Biochemical Composition Analysis of Patient-Derived Pancreatic Cancer Organoids

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) continues to pose profound challenges within the field of oncology due to its notorious resistance to existing therapies and constant high mortality rates. The recent emergence of three-dimensional patient-derived organoid (PDO) models marks a significant advancement, opening new avenues for exploring cancer biology and assessing therapeutic approaches.

AIMS

The aim of this study focuses on the innovative use of Fourier-transform infrared (FT-IR) spectroscopy to analyze PDAC organoids, thus illuminating their biochemical intricacies.

MATERIALS AND METHODS

In this study, PDAC organoids, cultivated from specimens sourced from cancer patients, were subjected to FT-IR spectroscopic imaging. By examining the spectral data within the critical fingerprint region (950-1800 cm-1), and employing principal component analysis (PCA), biochemical disparities were detected and analyzed.

RESULTS

The results revealed distinct spectral profiles corresponding to different sample preparation techniques, which in turn highlighted variations in protein content and structure. PCA revealed a high homogeneity within classes and minimal passage number influence on spectral profiles, with variations in lipid content and protein profiles. Significantly, the biochemical fingerprint of these PDOs closely mirrored that of the original human tissue samples.

CONCLUSION

This investigation underscores the efficacy of molecular spectroscopy as a non-invasive method for profound characterization of PDAC organoids, enhancing our comprehension of tumor biochemistry. The capacity for swift and precise biochemical profiling of PDOs via molecular spectroscopy heralds a promising future for this technique in the realms of cancer diagnostics and personalized medicine.

Patient-derived organoids in precision cancer medicine

Organoids are three-dimensional (3D) cultures, normally derived from stem cells, that replicate the complex structure and function of human tissues. They offer a physiologically relevant model to address important questions in cancer research. The generation of patient-derived organoids (PDOs) from various human cancers allows for deeper insights into tumor heterogeneity and spatial organization. Additionally, interrogating non-tumor stromal cells increases the relevance in studying the tumor microenvironment, thereby enhancing the relevance of PDOs in personalized medicine. PDOs mark a significant advancement in cancer research and patient care, signifying a shift toward more innovative and patient-centric approaches. This review covers aspects of PDO cultures to address the modeling of the tumor microenvironment, including extracellular matrices, air-liquid interface and microfluidic cultures, and organ-on-chip. Specifically, the role of PDOs as preclinical models in gene editing, molecular profiling, drug testing, and biomarker discovery and their potential for guiding personalized treatment in clinical practice are discussed.

Advancing cancer research through organoid technology

The complexity of tumors and the challenges associated with treatment often stem from the limitations of existing models in accurately replicating authentic tumors. Recently, organoid technology has emerged as an innovative platform for tumor research. This bioengineering approach enables researchers to simulate, in vitro, the interactions between tumors and their microenvironment, thereby enhancing the intricate interplay between tumor cells and their surroundings. Organoids also integrate multidimensional data, providing a novel paradigm for understanding tumor development and progression while facilitating precision therapy. Furthermore, advancements in imaging and genetic editing techniques have significantly augmented the potential of organoids in tumor research. This review explores the application of organoid technology for more precise tumor simulations and its specific contributions to cancer research advancements. Additionally, we discuss the challenges and evolving trends in developing comprehensive tumor models utilizing organoid technology.

Conversion therapy in advanced perihilar cholangiocarcinoma based on patient-derived organoids: A case report

BACKGROUND

Patient-derived organoids (PDOs) have been demonstrated to predict the response to drugs in multiple cancer types. However, it remains unclear about its application in cholangiocarcinoma.

CASE SUMMARY

A 59-year-old woman was admitted to the hospital due to upper abdominal pain for over 8 months. According to relevant examinations, she was diagnosed as perihilar cholangiocarcinoma (pCCA) with intrahepatic metastasis and perihilar lymphatic metastasis. After multidisciplinary team discussion, percutaneous transhepatic cholangiodrainage was performed to relieve biliary obstruction, and puncture biopsy was conducted to confirm the pathological diagnosis. Transarterial chemoembolization with nab-paclitaxel was used in combination with toripalimab and lenvatinib, but the levels of tumor markers including alpha fetal protein, carcinoembryonic antigen, carbohydrate antigen 15-3 and cancer antigen 125 were still raised. The PDO for drug screening showed sensitive to gemcitabine and cisplatin. Accordingly, the chemotherapy regimen was adjusted to gemcitabine and cisplatin in combination with toripalimab and lenvatinib. After 4 cycles of treatment, the tumor was assessed resectable, and radical surgical resection was performed successfully. One year after surgery, the patient was still alive, and no recurrence or occurred.

CONCLUSION

PDOs for drug sensitivity contribute to screening effective chemotherapy drugs for advanced pCCA, promoting conversion therapy and improving the prognosis.

The landscape of drug sensitivity and resistance in sarcoma

Sarcomas are rare malignancies with over 100 distinct histological subtypes. Their rarity and heterogeneity pose significant challenges to identifying effective therapies, and approved regimens show varied responses. Novel, personalized approaches to therapy are needed to improve patient outcomes. Patient-derived tumor organoids (PDTOs) model tumor behavior across an array of malignancies. We leverage PDTOs to characterize the landscape of drug resistance and sensitivity in sarcoma, collecting 194 specimens from 126 patients spanning 24 distinct sarcoma subtypes. Our high-throughput organoid screening pipeline tested single agents and combinations, with results available within a week from surgery. Drug sensitivity correlated with clinical features such as tumor subtype, treatment history, and disease trajectory. PDTO screening can facilitate optimal drug selection and mirror patient outcomes in sarcoma. We could identify at least one FDA-approved or NCCN-recommended effective regimen for 59% of the specimens, demonstrating the potential of our pipeline to provide actionable treatment information.

EUS-guided biopsies versus surgical specimens for establishing patient-derived pancreatic cancer organoids: a systematic review and meta-analysis

BACKGROUND AND AIMS

Patient-derived tumor organoids (PDTOs) are a promising new disease model in pancreatic cancer for use in personalized medicine. However, the overall success rate (SR) of establishing these cultures from EUS-guided biopsies is unknown.

METHODS

We searched relevant database publications reporting SRs of PDTO establishment from pancreatic cancer. The primary outcome was SR stratified on tissue acquisition method (EUS-guided biopsies, percutaneous biopsies, and surgical specimens).

RESULTS

Twenty-four studies were identified that included 1053 attempts at establishing PDTOs. Overall SR was 63% (95% confidence interval [CI], 54%-72%). Pooled SRs of PDTO establishment from EUS-guided biopsies, percutaneous biopsies, and surgical specimens were 60% (95% CI, 43%-76%), 36% (95% CI, 14%-61%), and 62% (95% CI, 48%-75%), respectively, and did not differ significantly (P = .1975).

CONCLUSION

The SR of PDTO establishment from EUS-guided biopsies is comparable to that from surgical specimens. Both techniques are suitable for tissue acquisition for PDTOs in clinical and research settings. (PROSPERO registration number: CRD42023425121.).

Modeling Epithelial Homeostasis and Perturbation in Three-Dimensional Human Esophageal Organoids

Background: Esophageal organoids from a variety of pathologies including cancer are grown in Advanced Dulbecco's Modified Eagle Medium-Nutrient Mixture F12 (hereafter ADF). However, the currently available ADF-based formulations are suboptimal for normal human esophageal organoids, limiting the ability to compare normal esophageal organoids with those representing a given disease state. Methods: We have utilized immortalized normal human esophageal epithelial cell (keratinocyte) lines EPC1 and EPC2 and endoscopic normal esophageal biopsies to generate three-dimensional (3D) organoids. To optimize the ADF-based medium, we evaluated the requirement of exogenous epidermal growth factor (EGF) and inhibition of transforming growth factor-(TGF)-β receptor-mediated signaling, both key regulators of the proliferation of human esophageal keratinocytes. We have modeled human esophageal epithelial pathology by stimulating esophageal 3D organoids with interleukin (IL)-13, an inflammatory cytokine, or UAB30, a novel pharmacological activator of retinoic acid signaling. Results: The formation of normal human esophageal 3D organoids was limited by excessive EGF and intrinsic TGFβ-receptor-mediated signaling. Optimized HOME0 improved normal human esophageal organoid formation. In the HOME0-grown organoids, IL-13 and UAB30 induced epithelial changes reminiscent of basal cell hyperplasia, a common histopathologic feature in broad esophageal disease conditions including eosinophilic esophagitis. Conclusions: HOME0 allows modeling of the homeostatic differentiation gradient and perturbation of the human esophageal epithelium while permitting a comparison of organoids from mice and other organs grown in ADF-based media.

Establishment of a patient-specific avatar organoid model derived from EUS-guided fine-needle biopsy for timely clinical application in pancreatic ductal adenocarcinoma (with video)

BACKGROUND AND AIMS

Pancreatic ductal adenocarcinoma (PDAC) has the worst survival rate among tumors. At the time of diagnosis, more than 80% of PDACs are considered to be surgically unresectable, and there is an unmet need for treatment options in these inoperable PDACs. This study aimed to establish a patient-derived organoid (PDO) platform from EUS-guided fine-needle biopsy (EUS-FNB) collected at diagnosis and to determine its clinical applicability for the timely treatment of unresectable PDAC.

METHODS

Patients with suspected PDAC were prospectively enrolled at the Samsung Medical Center from 2015 to 2019. PDAC tissues were acquired by means of EUS-FNB to establish PDAC PDOs, which were comprehensively analyzed for histology, genomic sequencing, and high-throughput screening (HTS) drug sensitivity test.

RESULTS

PDAC PDOs were established with a success rate of 83.2% (94/113). It took approximately 3 weeks from acquiring minimal EUS-FNB specimens to generating sufficient PDAC PDOs for the simultaneous HTS drug sensitivity test and genomic sequencing. The high concordance between PDAC tissues and matched PDOs was confirmed, and whole-exome sequencing revealed the increased detection of genetic alterations in PDOs compared with EUS-FNB tissues. The HTS drug sensitivity test showed clinical correlation between the ex vivo PDO response and the actual chemotherapeutic response of the study patients in the real world (13 out of 15 cases). In addition, whole-transcriptome sequencing identified candidate genes associated with nab-paclitaxel resistance, such as ITGB7, ANPEP, and ST3GAL1.

CONCLUSIONS

This PDAC PDO platform allows several therapeutic drugs to be tested within a short time window and opens the possibility for timely personalized medicine as a "patient avatar model" in clinical practice.

Patient-derived organoids of pancreatic ductal adenocarcinoma for subtype determination and clinical outcome prediction

BACKGROUND

Recently, two molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) have been proposed: the "Classical" and "Basal-like" subtypes, with the former showing better clinical outcomes than the latter. However, the "molecular" classification has not been applied in real-world clinical practice. This study aimed to establish patient-derived organoids (PDOs) for PDAC and evaluate their application in subtype classification and clinical outcome prediction.

METHODS

We utilized tumor samples acquired through endoscopic ultrasound-guided fine-needle biopsy and established a PDO library for subsequent use in morphological assessments, RNA-seq analyses, and in vitro drug response assays. We also conducted a prospective clinical study to evaluate whether analysis using PDOs can predict treatment response and prognosis.

RESULTS

PDOs of PDAC were established at a high efficiency (> 70%) with at least 100,000 live cells. Morphologically, PDOs were classified as gland-like structures (GL type) and densely proliferating inside (DP type) less than 2 weeks after tissue sampling. RNA-seq analysis revealed that the "morphological" subtype (GL vs. DP) corresponded to the "molecular" subtype ("Classical" vs. "Basal-like"). The "morphological" classification predicted the clinical treatment response and prognosis; the median overall survival of patients with GL type was significantly longer than that with DP type (P < 0.005). The GL type showed a better response to gemcitabine than the DP type in vitro, whereas the drug response of the DP type was improved by the combination of ERK inhibitor and chloroquine.

CONCLUSIONS

PDAC PDOs help in subtype determination and clinical outcome prediction, thereby facilitating the bench-to-bedside precision medicine for PDAC.

Personalized Medicine in Pancreatic Cancer: The Promise of Biomarkers and Molecular Targeting with Dr. Michael J. Pishvaian

Pancreatic cancer, with its alarming rising incidence, is predicted to become the second deadliest type of solid tumor by 2040, highlighting the urgent need for improved diagnostic and treatment strategies. Despite medical advancements, the five-year survival rate for pancreatic cancer remains about 14%, dropping further when metastasized. This review explores the promise of biomarkers for early detection, personalized treatment, and disease monitoring. Molecular classification of pancreatic cancer into subtypes based on genetic mutations, gene expression, and protein markers guides treatment decisions, potentially improving outcomes. A plethora of clinical trials investigating different strategies are currently ongoing. Targeted therapies, among which those against CLAUDIN 18.2 and inhibitors of Claudin 18.1, have shown promise. Next-generation sequencing (NGS) has emerged as a powerful tool for the comprehensive genomic analysis of pancreatic tumors, revealing unique genetic alterations that drive cancer progression. This allows oncologists to tailor therapies to target specific molecular abnormalities. However, challenges remain, including limited awareness and uptake of biomarker-guided therapies. Continued research into the molecular mechanisms of pancreatic cancer is essential for developing more effective treatments and improving patient survival rates.

Organoids for Functional Precision Medicine in Advanced Pancreatic Cancer

BACKGROUND & AIMS

Patient-derived organoids (PDOs) are promising tumor avatars that could enable ex vivo drug tests to personalize patients' treatments in the frame of functional precision oncology. However, clinical evidence remains scarce. This study aims to evaluate whether PDOs can be implemented in clinical practice to benefit patients with advanced refractory pancreatic ductal adenocarcinoma (PDAC).

METHODS

During 2021 to 2022, 87 patients were prospectively enrolled in an institutional review board-approved protocol. Inclusion criteria were histologically confirmed PDAC with the tumor site accessible. A panel of 25 approved antitumor therapies (chemogram) was tested and compared to patient responses to assess PDO predictive values and map the drug sensitivity landscape in PDAC.

RESULTS

Fifty-four PDOs were generated from 87 pretreated patients (take-on rate, 62%). The main PDO mutations were KRAS (96%), TP53 (88%), and CDKN2A/B (22%), with a 91% concordance rate with their tumor of origin. The mean turnaround time to chemogram was 6.8 weeks. In 91% of cases, ≥1 hit was identified (gemcitabine (n = 20 of 54), docetaxel (n = 18 of 54), and vinorelbine (n = 17 of 54), with a median of 3 hits/patient (range, 0-12). Our cohort included 34 evaluable patients with full clinical follow-up. We report a chemogram sensitivity of 83.3% and specificity of 92.9%. The overall response rate and progression-free survival were higher when patients received a hit treatment as compared to patients who received a nonhit drug (as part of routine management). Finally, we leveraged our PDO collection as a platform for drug validation and combo identification. We tested anti-KRASG12D (MRTX1133), alone or combined, and identified a specific synergy with anti-EGFR therapies in KRASG12D variants.

CONCLUSIONS

We report the largest prospective study aiming at implementing PDO-based functional precision oncology and identify very robust predictive values in this clinical setting. In a clinically relevant turnaround time, we identify putative hits for 91% of patients, providing unexpected potential survival benefits in this very aggressive indication. Although this remains to be confirmed in interventional precision oncology trials, PDO collection already provides powerful opportunities for drugs and combinatorial treatment development.

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

Cancer is a highly heterogeneous disease, and thus treatment responses vary greatly between patients. To improve therapy efficacy and outcome for cancer patients, more representative and patient-specific preclinical models are needed. Organoids and tumoroids are 3D cell culture models that typically retain the genetic and epigenetic characteristics, as well as the morphology, of their tissue of origin. Thus, they can be used to understand the underlying mechanisms of cancer initiation, progression, and metastasis in a more physiological setting. Additionally, co-culture methods of tumoroids and cancer-associated cells can help to understand the interplay between a tumor and its tumor microenvironment. In recent years, tumoroids have already helped to refine treatments and to identify new targets for cancer therapy. Advanced culturing systems such as chip-based fluidic devices and bioprinting methods in combination with tumoroids have been used for high-throughput applications for personalized medicine. Even though organoid and tumoroid models are complex in vitro systems, validation of results in vivo is still the common practice. Here, we describe how both animal- and human-derived tumoroids have helped to identify novel vulnerabilities for cancer treatment in recent years, and how they are currently used for precision medicine.

Building consensus on the application of organoid-based drug sensitivity testing in cancer precision medicine and drug development

Patient-derived organoids (PDOs) have emerged as a promising platform for clinical and translational studies. A strong correlation exists between clinical outcomes and the use of PDOs to predict the efficacy of chemotherapy and/or radiotherapy. To standardize interpretation and enhance scientific communication in the field of cancer precision medicine, we revisit the concept of PDO-based drug sensitivity testing (DST). We present an expert consensus-driven approach for medication selection aimed at predicting patient responses. To further standardize PDO-based DST, we propose guidelines for clarification and characterization. Additionally, we identify several major challenges in clinical prediction when utilizing PDOs.

Pancreatic cancer environment: from patient-derived models to single-cell omics

Pancreatic cancer (PC) is a highly malignant cancer characterized by poor prognosis, high heterogeneity, and intricate heterocellular systems. Selecting an appropriate experimental model for studying its progression and treatment is crucial. Patient-derived models provide a more accurate representation of tumor heterogeneity and complexity compared to cell line-derived models. This review initially presents relevant patient-derived models, including patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived explants (PDEs), which are essential for studying cell communication and pancreatic cancer progression. We have emphasized the utilization of these models in comprehending intricate intercellular communication, drug responsiveness, mechanisms underlying tumor growth, expediting drug discovery, and enabling personalized medical approaches. Additionally, we have comprehensively summarized single-cell analyses of these models to enhance comprehension of intercellular communication among tumor cells, drug response mechanisms, and individual patient sensitivities.

Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Inflammation in Cancer Cells in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by an immunosuppressive tumor microenvironment enriched with cancer-associated fibroblasts (CAF). This study used a convergence approach to identify tumor cell and CAF interactions through the integration of single-cell data from human tumors with human organoid coculture experiments. Analysis of a comprehensive atlas of PDAC single-cell RNA sequencing data indicated that CAF density is associated with increased inflammation and epithelial-mesenchymal transition (EMT) in epithelial cells. Transfer learning using transcriptional data from patient-derived organoid and CAF cocultures provided in silico validation of CAF induction of inflammatory and EMT epithelial cell states. Further experimental validation in cocultures demonstrated integrin beta 1 (ITGB1) and vascular endothelial factor A (VEGFA) interactions with neuropilin-1 mediating CAF-epithelial cell cross-talk. Together, this study introduces transfer learning from human single-cell data to organoid coculture analyses for experimental validation of discoveries of cell-cell cross-talk and identifies fibroblast-mediated regulation of EMT and inflammation.

SIGNIFICANCE

Adaptation of transfer learning to relate human single-cell RNA sequencing data to organoid-CAF cocultures facilitates discovery of human pancreatic cancer intercellular interactions and uncovers cross-talk between CAFs and tumor cells through VEGFA and ITGB1.

Mesothelin CAR T Cells Secreting Anti-FAP/Anti-CD3 Molecules Efficiently Target Pancreatic Adenocarcinoma and its Stroma

PURPOSE

Targeting solid tumors with chimeric antigen receptor (CAR) T cells remains challenging due to heterogenous target antigen expression, antigen escape, and the immunosuppressive tumor microenvironment (TME). Pancreatic cancer is characterized by a thick stroma generated by cancer-associated fibroblasts (CAF), which may contribute to the limited efficacy of mesothelin-directed CAR T cells in early-phase clinical trials. To provide a more favorable TME for CAR T cells to target pancreatic ductal adenocarcinoma (PDAC), we generated T cells with an antimesothelin CAR and a secreted T-cell-engaging molecule (TEAM) that targets CAF through fibroblast activation protein (FAP) and engages T cells through CD3 (termed mesoFAP CAR-TEAM cells).

EXPERIMENTAL DESIGN

Using a suite of in vitro, in vivo, and ex vivo patient-derived models containing cancer cells and CAF, we examined the ability of mesoFAP CAR-TEAM cells to target PDAC cells and CAF within the TME. We developed and used patient-derived ex vivo models, including patient-derived organoids with patient-matched CAF and patient-derived organotypic tumor spheroids.

RESULTS

We demonstrated specific and significant binding of the TEAM to its respective antigens (CD3 and FAP) when released from mesothelin-targeting CAR T cells, leading to T-cell activation and cytotoxicity of the target cell. MesoFAP CAR-TEAM cells were superior in eliminating PDAC and CAF compared with T cells engineered to target either antigen alone in our ex vivo patient-derived models and in mouse models of PDAC with primary or metastatic liver tumors.

CONCLUSIONS

CAR-TEAM cells enable modification of tumor stroma, leading to increased elimination of PDAC tumors. This approach represents a promising treatment option for pancreatic cancer.

Establishment of Human Pituitary Neuroendocrine Tumor Derived Organoid and Its Pilot Application for Drug Screening

CONTEXT

Precision medicine for pituitary neuroendocrine tumors (PitNETs) is limited by the lack of reliable research models.

OBJECTIVE

To generate patient-derived organoids (PDOs), which could serve as a platform for personalized drug screening for PitNET patients.

DESIGN

From July 2019 to May 2022, a total of 32 human PitNET specimens were collected for the establishment of organoids with an optimized culture protocol.

SETTING

This study was conducted at Sun Yat-Sen University Cancer Center.

PATIENTS

PitNET patients who were pathologically confirmed were enrolled in this study.

INTERVENTIONS

Histological staining and whole-exome sequencing were utilized to confirm the pathologic and genomic features of PDOs. A drug response assay on PDOs was also performed.

MAIN OUTCOME MEASURES

PDOs retained key genetic and morphological features of their parental tumors.

RESULTS

PDOs were successfully established from various types of PitNET samples with an overall success rate of 87.5%. Clinical nonfunctioning PitNETs-derived organoids (22/23, 95.7%) showed a higher likelihood of successful generation compared to those from functioning PitNETs (6/9, 66.7%). Preservation of cellular structure, subtype-specific neuroendocrine profiles, mutational features, and tumor microenvironment heterogeneity from parental tumors was observed. A distinctive response profile in drug tests was observed among the organoids from patients with different subtypes of PitNETs. With the validation of key characteristics from parental tumors in histological, genomic, and microenvironment heterogeneity consistency assays, we demonstrated the predictive value of the PDOs in testing individual drugs.

CONCLUSION

The established PDOs, retaining typical features of parental tumors, indicate a translational significance in innovating personalized treatment for refractory PitNETs.

Integration of pan-omics technologies and three-dimensional in vitro tumor models: an approach toward drug discovery and precision medicine

Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer.

In Neoadjuvant FOLFIRINOX Chemotherapy for Pancreatic Ductal Adenocarcinoma, Which Response is the More Reliable Indicator for Prognosis, Radiologic or Biochemical?

BACKGROUND

In this era of increasing neoadjuvant chemotherapy, methods for evaluating responses to neoadjuvant chemotherapy are still diverse among institutions. Additionally, the efficacy of adjuvant chemotherapy for patients undergoing neoadjuvant chemotherapy remains unclear. Therefore, this retrospective study was performed to evaluate the effectiveness of methods for assessing response to neoadjuvant chemotherapy and the need for adjuvant chemotherapy in treating patients with non-metastatic pancreatic ductal adenocarcinoma.

METHODS

The study identified 150 patients who underwent neoadjuvant FOLFIRINOX chemotherapy followed by curative-intent pancreatectomy. The patients were stratified by biochemical response based on the normalization of carbohydrate antigen 19-9 and by radiologic response based on size change at imaging.

RESULTS

The patients were classified into the following three groups based on their response to neoadjuvant chemotherapy and prognosis: biochemical responders (BR+), radiology-only responders (BR-/RR+), and non-responders (BR-/RR-). The 3-year overall survival rate was higher for BR+ (71.0%) than for BR-/RR+ (53.6%) or BR-/RR- (33.1%) (P < 0.001). Response to neoadjuvant chemotherapy also was identified as a significant risk factor for recurrence in a comparison between BR-/RR+ and BR+ (hazard ratio [HR], 2.15; 95% confidence interval [CI] 1.19-3.88; P = 0.011) and BR-/RR- (HR, 3.82; 95% CI 2.41-6.08; P < 0.001). Additionally, regardless of the response to neoadjuvant chemotherapy, patients who completed adjuvant chemotherapy had a significantly higher 3-year overall survival rate than those who did not.

CONCLUSIONS

This response evaluation criterion for neoadjuvant chemotherapy is feasible and can significantly predict prognosis. Additionally, completion of adjuvant chemotherapy could be helpful to patients who undergo neoadjuvant chemotherapy regardless of their response to neoadjuvant chemotherapy.

Development and validation of a nomogram model based on pretreatment ultrasound and contrast-enhanced ultrasound to predict the efficacy of neoadjuvant chemotherapy in patients with borderline resectable or locally advanced pancreatic cancer

OBJECTIVES

To develop a nomogram using pretreatment ultrasound (US) and contrast-enhanced ultrasound (CEUS) to predict the clinical response of neoadjuvant chemotherapy (NAC) in patients with borderline resectable pancreatic cancer (BRPC) or locally advanced pancreatic cancer (LAPC).

METHODS

A total of 111 patients with pancreatic ductal adenocarcinoma (PDAC) treated with NAC between October 2017 and February 2022 were retrospectively enrolled. The patients were randomly divided (7:3) into training and validation cohorts. The pretreatment US and CEUS features were reviewed. Univariate and multivariate logistic regression analyses were used to determine the independent predictors of clinical response in the training cohort. Then a prediction nomogram model based on the independent predictors was constructed. The area under the curve (AUC), calibration plot, C-index and decision curve analysis (DCA) were used to assess the nomogram's performance, calibration, discrimination and clinical benefit.

RESULTS

The multivariate logistic regression analysis showed that the taller-than-wide shape in the longitudinal plane (odds ratio [OR]:0.20, p = 0.01), time from injection of contrast agent to peak enhancement (OR:3.64; p = 0.05) and Peaktumor/ Peaknormal (OR:1.51; p = 0.03) were independent predictors of clinical response to NAC. The predictive nomogram developed based on the above imaging features showed AUCs were 0.852 and 0.854 in the primary and validation cohorts, respectively. Good calibration was achieved in the training datasets, with C-index of 0.852. DCA verified the clinical usefulness of the nomogram.

CONCLUSIONS

The nomogram based on pretreatment US and CEUS can effectively predict the clinical response of NAC in patients with BRPC and LAPC; it may help guide personalized treatment.

The effect of extracellular matrix on the precision medicine utility of pancreatic cancer patient-derived organoids

The use of patient-derived organoids (PDOs) to characterize therapeutic sensitivity and resistance is a promising precision medicine approach, and its potential to inform clinical decisions is now being tested in several large multiinstitutional clinical trials. PDOs are cultivated in the extracellular matrix from basement membrane extracts (BMEs) that are most commonly acquired commercially. Each clinical site utilizes distinct BME lots and may be restricted due to the availability of commercial BME sources. However, the effect of different sources of BMEs on organoid drug response is unknown. Here, we tested the effect of BME source on proliferation, drug response, and gene expression in mouse and human pancreatic ductal adenocarcinoma (PDA) organoids. Both human and mouse organoids displayed increased proliferation in Matrigel compared with Cultrex and UltiMatrix. However, we observed no substantial effect on drug response when organoids were cultured in Matrigel, Cultrex, or UltiMatrix. We also did not observe major shifts in gene expression across the different BME sources, and PDOs maintained their classical or basal-like designation. Overall, we found that the BME source (Matrigel, Cultrex, UltiMatrix) does not shift PDO dose-response curves or drug testing results, indicating that PDO pharmacotyping is a robust approach for precision medicine.

A Phase I Expansion Cohort Study Evaluating the Safety and Efficacy of the CHK1 Inhibitor LY2880070 with Low-dose Gemcitabine in Patients with Metastatic Pancreatic Adenocarcinoma

PURPOSE

Combining gemcitabine with CHK1 inhibition has shown promise in preclinical models of pancreatic ductal adenocarcinoma (PDAC). Here, we report the findings from a phase I expansion cohort study (NCT02632448) investigating low-dose gemcitabine combined with the CHK1 inhibitor LY2880070 in patients with previously treated advanced PDAC.

PATIENTS AND METHODS

Patients with metastatic PDAC were treated with gemcitabine intravenously at 100 mg/m2 on days 1, 8, and 15, and LY2880070 50 mg orally twice daily on days 2-6, 9-13, and 16-20 of each 21-day cycle. Pretreatment tumor biopsies were obtained from each patient for correlative studies and generation of organoid cultures for drug sensitivity testing and biomarker analyses.

RESULTS

Eleven patients with PDAC were enrolled in the expansion cohort between August 27, 2020 and July 30, 2021. Four patients (36%) experienced drug-related grade 3 adverse events. No objective radiologic responses were observed, and all patients discontinued the trial by 3.2 months. In contrast to the lack of efficacy observed in patients, organoid cultures derived from biopsies procured from two patients demonstrated strong sensitivity to the gemcitabine/LY2880070 combination and showed treatment-induced upregulation of replication stress and DNA damage biomarkers, including pKAP1, pRPA32, and γH2AX, as well as induction of replication fork instability.

CONCLUSIONS

No evidence of clinical activity was observed for combined low-dose gemcitabine and LY2880070 in this treatment-refractory PDAC cohort. However, the gemcitabine/LY2880070 combination showed in vitro efficacy, suggesting that drug sensitivity for this combination in organoid cultures may not predict clinical benefit in patients.

Advances towards the use of gastrointestinal tumor patient-derived organoids as a therapeutic decision-making tool

In December 2022 the US Food and Drug Administration (FDA) removed the requirement that drugs in development must undergo animal testing before clinical evaluation, a declaration that now demands the establishment and verification of ex vivo preclinical models that closely represent tumor complexity and that can predict therapeutic response. Fortunately, the emergence of patient-derived organoid (PDOs) culture has enabled the ex vivo mimicking of the pathophysiology of human tumors with the reassembly of tissue-specific features. These features include histopathological variability, molecular expression profiles, genetic and cellular heterogeneity of parental tissue, and furthermore growing evidence suggests the ability to predict patient therapeutic response. Concentrating on the highly lethal and heterogeneous gastrointestinal (GI) tumors, herein we present the state-of-the-art and the current methodology of PDOs. We highlight the potential additions, improvements and testing required to allow the ex vivo of study the tumor microenvironment, as well as offering commentary on the predictive value of clinical response to treatments such as chemotherapy and immunotherapy.

Discriminative performance of pancreatic stone protein in predicting ICU mortality and infection severity in adult patients with infection: a systematic review and individual patient level meta-analysis

BACKGROUND

Several studies suggested pancreatic stone protein (PSP) as a promising biomarker to predict mortality among patients with severe infection. The objective of the study was to evaluate the performance of PSP in predicting intensive care unit (ICU) mortality and infection severity among critically ill adults admitted to the hospital for infection.

METHODS

A systematic search across Cochrane Central Register of Controlled Trials and MEDLINE databases (1966 to February 2022) for studies on PSP published in English using 'pancreatic stone protein', 'PSP', 'regenerative protein', 'lithostatin' combined with 'infection' and 'sepsis' found 46 records. The search was restricted to the five trials that measured PSP using the enzyme-linked immunosorbent assay technique (ELISA). We used Bayesian hierarchical regression models for pooled estimates and to predict mortality or disease severity using PSP, C-Reactive Protein (CRP) and procalcitonin (PCT) as main predictor. We used statistical discriminative measures, such as the area under the receiver operating characteristic curve (AUC) and classification plots.

RESULTS

Among the 678 patients included, the pooled ICU mortality was 17.8% (95% prediction interval 4.1% to 54.6%) with a between-study heterogeneity (I-squared 87%). PSP was strongly associated with ICU mortality (OR = 2.7, 95% credible interval (CrI) [1.3-6.0] per one standard deviation increase; age, gender and sepsis severity adjusted OR = 1.5, 95% CrI [0.98-2.8]). The AUC was 0.69 for PSP 95% confidence interval (CI) [0.64-0.74], 0.61 [0.56-0.66] for PCT and 0.52 [0.47-0.57] for CRP. The sensitivity was 0.96, 0.52, 0.30 for risk thresholds 0.1, 0.2 and 0.3; respective false positive rate values were 0.84, 0.25, 0.10.

CONCLUSIONS

We found that PSP showed a very good discriminative ability for both investigated study endpoints ICU mortality and infection severity; better in comparison to CRP, similar to PCT. Combinations of biomarkers did not improve their predictive ability.

Currently Debated Topics on Surgical Treatment of Pancreatic Ductal Adenocarcinoma: A Narrative Review on Surgical Treatment of Borderline Resectable, Locally Advanced, and Synchronous or Metachronous Oligometastatic Tumor

BACKGROUND

Previously considered inoperable patients (borderline resectable, locally advanced, synchronous oligometastatic or metachronous pancreatic adenocarcinoma (PDAC)) are starting to become resectable thanks to advances in chemo/radiotherapy and the reduction in operative mortality.

METHODS

This narrative review presents a chosen literature selection, giving a picture of the current state of treatment of these patients.

RESULTS

Neoadjuvant therapy (NAT) is generally recognized as the treatment of choice before surgery. However, despite the increased efficacy, the best pathological response is still limited to 10.9-27.9% of patients. There are still limited data on the selection of possible NAT responders and how to diagnose non-responders early. Multidetector computed tomography has high sensitivity and low specificity in evaluating resectability after NAT, limiting the resection rate of resectable patients. Ca 19-9 and Positron emission tomography are giving promising results. The prediction of early recurrence after a radical resection of synchronous or metachronous metastatic PDAC, thus identifying patients with poor prognosis and saving them from a resection of little benefit, is still ongoing, although some promising data are available.

CONCLUSION

In conclusion, high-level evidence demonstrating the benefit of the surgical treatment of such patients is still lacking and should not be performed outside of high-volume centers with interdisciplinary teams of surgeons and oncologists.

Organoid: Bridging the gap between basic research and clinical practice

Nowadays, the diagnosis and treatment system of malignant tumors has increasingly tended to be more precise and personalized while the existing tumor models are still unable to fully meet the needs of clinical practice. Notably, the emerging organoid platform has been proven to have huge potential in the field of basic-translational medicine, which is expected to promote a paradigm shift in personalized medicine. Here, given the unique advantages of organoid platform, we mainly explore the prominent role of organoid models in basic research and clinical practice from perspectives of tumor biology, tumorigenic microbes-host interaction, clinical decision-making, and regenerative strategy. In addition, we also put forward some practical suggestions on how to construct a new generation of organoid platform, which is destined to vigorously promote the reform of basic-translational medicine.

Flourishing tumor organoids: History, emerging technology, and application

Malignant tumors are one of the leading causes of death which impose an increasingly heavy burden on all countries. Therefore, the establishment of research models that closely resemble original tumor characteristics is crucial to further understanding the mechanisms of malignant tumor development, developing safer and more effective drugs, and formulating personalized treatment plans. Recently, organoids have been widely used in tumor research owing to their advantages including preserving the structure, heterogeneity, and cellular functions of the original tumor, together with the ease of manipulation. This review describes the history and characteristics of tumor organoids and the synergistic combination of three-dimensional (3D) culture approaches for tumor organoids with emerging technologies, including tissue-engineered cell scaffolds, microfluidic devices, 3D bioprinting, rotating wall vessels, and clustered regularly interspaced short palindromic repeats-CRISPR-associated protein 9 (CRISPR-Cas9). Additionally, the progress in research and the applications in basic and clinical research of tumor organoid models are summarized. This includes studies of the mechanism of tumor development, drug development and screening, precision medicine, immunotherapy, and simulation of the tumor microenvironment. Finally, the existing shortcomings of tumor organoids and possible future directions are discussed.

The challenge of making the right choice: patient avatars in the era of cancer immunotherapies

Immunotherapies are a key therapeutic strategy to fight cancer. Diverse approaches are used to activate tumor-directed immunity and to overcome tumor immune escape. The dynamic interplay between tumor cells and their tumor(immune)microenvironment (T(I)ME) poses a major challenge to create appropriate model systems. However, those model systems are needed to gain novel insights into tumor (immune) biology and a prerequisite to accurately develop and test immunotherapeutic approaches which can be successfully translated into clinical application. Several model systems have been established and advanced into so-called patient avatars to mimic the patient´s tumor biology. All models have their advantages but also disadvantages underscoring the necessity to pay attention in defining the rationale and requirements for which the patient avatar will be used. Here, we briefly outline the current state of tumor model systems used for tumor (immune)biological analysis as well as evaluation of immunotherapeutic agents. Finally, we provide a recommendation for further development to make patient avatars a complementary tool for testing and predicting immunotherapeutic strategies for personalization of tumor therapies.

The landscape of drug sensitivity and resistance in sarcoma

Sarcomas are a family of rare malignancies composed of over 100 distinct histological subtypes. The rarity of sarcoma poses significant challenges in conducting clinical trials to identify effective therapies, to the point that many rarer subtypes of sarcoma do not have standard-of-care treatment. Even for established regimens, there can be substantial heterogeneity in responses. Overall, novel, personalized approaches for identifying effective treatments are needed to improve patient out-comes. Patient-derived tumor organoids (PDTOs) are clinically relevant models representative of the physiological behavior of tumors across an array of malignancies. Here, we use PDTOs as a tool to better understand the biology of individual tumors and characterize the landscape of drug resistance and sensitivity in sarcoma. We collected n=194 specimens from n=126 sarcoma patients, spanning 24 distinct subtypes. We characterized PDTOs established from over 120 biopsy, resection, and metastasectomy samples. We leveraged our organoid high-throughput drug screening pipeline to test the efficacy of chemotherapeutics, targeted agents, and combination therapies, with results available within a week from tissue collection. Sarcoma PDTOs showed patient-specific growth characteristics and subtype-specific histopathology. Organoid sensitivity correlated with diagnostic subtype, patient age at diagnosis, lesion type, prior treatment history, and disease trajectory for a subset of the compounds screened. We found 90 biological pathways that were implicated in response to treatment of bone and soft tissue sarcoma organoids. By comparing functional responses of organoids and genetic features of the tumors, we show how PDTO drug screening can provide an orthogonal set of information to facilitate optimal drug selection, avoid ineffective therapies, and mirror patient outcomes in sarcoma. In aggregate, we were able to identify at least one effective FDA-approved or NCCN-recommended regimen for 59% of the specimens tested, providing an estimate of the proportion of immediately actionable information identified through our pipeline.

Highlights

Standardized organoid culture preserve unique sarcoma histopathological featuresDrug screening on patient-derived sarcoma organoids provides sensitivity information that correlates with clinical features and yields actionable information for treatment guidanceHigh-throughput screenings provide orthogonal information to genetic sequencingSarcoma organoid response to treatment correlates with patient response to therapyLarge scale, functional precision medicine programs for rare cancers are feasible within a single institution.

Streamlined DNA-encoded small molecule library screening and validation for the discovery of novel chemotypes targeting BET proteins

Targeting aberrant epigenetic programs that drive tumorigenesis is a promising approach to cancer therapy. DNA-encoded library (DEL) screening is a core platform technology increasingly used to identify drugs that bind to protein targets. Here, we use DEL screening against bromodomain and extra-terminal motif (BET) proteins to identify inhibitors with new chemotypes, and successfully identified BBC1115 as a selective BET inhibitor. While BBC1115 does not structurally resemble OTX-015, a clinically active pan-BET inhibitor, our intensive biological characterization revealed that BBC1115 binds to BET proteins, including BRD4, and suppresses aberrant cell fate programs. Phenotypically, BBC1115-mediated BET inhibition impaired proliferation in acute myeloid leukemia, pancreatic, colorectal, and ovarian cancer cells in vitro. Moreover, intravenous administration of BBC1115 inhibited subcutaneous tumor xenograft growth with minimal toxicity and favorable pharmacokinetic properties in vivo. Since epigenetic regulations are ubiquitously distributed across normal and malignant cells, it will be critical to evaluate if BBC1115 affects normal cell function. Nonetheless, our study shows integrating DEL-based small-molecule compound screening and multi-step biological validation represents a reliable strategy to discover new chemotypes with selectivity, efficacy, and safety profiles for targeting proteins involved in epigenetic regulation in human malignancies.

Organoids: The current status and biomedical applications

Organoids are three-dimensional (3D) miniaturized versions of organs or tissues that are derived from cells with stem potential and can self-organize and differentiate into 3D cell masses, recapitulating the morphology and functions of their in vivo counterparts. Organoid culture is an emerging 3D culture technology, and organoids derived from various organs and tissues, such as the brain, lung, heart, liver, and kidney, have been generated. Compared with traditional bidimensional culture, organoid culture systems have the unique advantage of conserving parental gene expression and mutation characteristics, as well as long-term maintenance of the function and biological characteristics of the parental cells in vitro. All these features of organoids open up new opportunities for drug discovery, large-scale drug screening, and precision medicine. Another major application of organoids is disease modeling, and especially various hereditary diseases that are difficult to model in vitro have been modeled with organoids by combining genome editing technologies. Herein, we introduce the development and current advances in the organoid technology field. We focus on the applications of organoids in basic biology and clinical research, and also highlight their limitations and future perspectives. We hope that this review can provide a valuable reference for the developments and applications of organoids.

Viability Analysis and High-Content Live-Cell Imaging for Drug Testing in Prostate Cancer Xenograft-Derived Organoids

Tumor organoids have been pushed forward as advanced model systems for in vitro oncology drug testing, with the eventual goal to direct personalized cancer treatments. However, drug testing efforts suffer from a large variation in experimental conditions for organoid culturing and organoid treatment. Moreover, most drug tests are restricted to whole-well viability as the sole read-out, thereby losing important information about key biological aspects that might be impacted due to the use of administered drugs. These bulk read-outs also discard potential inter-organoid heterogeneity in drug responses. To tackle these issues, we developed a systematic approach for processing organoids from prostate cancer (PCa) patient-derived xenografts (PDXs) for viability-based drug testing and identified essential conditions and quality checks for consistent results. In addition, we generated an imaging-based drug testing procedure using high-content fluorescence microscopy in living PCa organoids to detect various modalities of cell death. Individual organoids and cell nuclei in organoids were segmented and quantified using a dye combination of Hoechst 33342, propidium iodide and Caspase 3/7 Green, allowing the identification of cytostatic and cytotoxic treatment effects. Our procedures provide important insights into the mechanistic actions of tested drugs. Moreover, these methods can be adapted for tumor organoids originating from other cancer types to increase organoid-based drug test validity, and ultimately, accelerate clinical implementation.

The impact of extracellular matrix on the precision medicine utility of pancreatic cancer patient-derived organoids

The use of patient-derived organoids (PDOs) to characterize therapeutic sensitivity and resistance (pharmacotyping) is a promising precision medicine approach. The potential of this approach to inform clinical decisions is now being tested in several large multi-institutional clinical trials. PDOs are cultivated in extracellular matrix from basement membrane extracts (BMEs) that are most commonly acquired commercially. Each clinical site utilizes distinct BME lots and may be restricted due to the availability of commercial BME sources. However, the impact of different sources and lots of BMEs on organoid drug response is unknown. Here, we tested the impact of BME source and lot on proliferation, chemotherapy and targeted therapy drug response, and gene expression in mouse and human pancreatic ductal adenocarcinoma (PDA) organoids. Both human and mouse organoids displayed increased proliferation in Matrigel (Corning) compared to Cultrex (RnD) and UltiMatrix (RnD). However, we observed no substantial impact on drug response when oragnoids were cultured in Matrigel, Cultrex, or UltiMatrix. We also did not observe major shifts in gene expression across the different BME sources, and PDOs maintained their Classical or Basal-like designation. Overall, we find that BME source (Matrigel, Cultrex, UltiMatrix) does not shift PDO dose-response curves and drug testing results, indicating that PDO pharmacotyping is a robust approach for precision medicine.

Genomic Biomarkers Associated with Response to Induction Chemotherapy in Patients with Localized Pancreatic Ductal Adenocarcinoma

PURPOSE

There is increasing use of neoadjuvant chemotherapy in the management of localized pancreatic ductal adenocarcinoma (PDAC), yet there are few validated biomarkers to guide therapy selection. We aimed to determine whether somatic genomic biomarkers predict response to induction FOLFIRINOX or gemcitabine/nab-paclitaxel.

EXPERIMENTAL DESIGN

This single-institution cohort study included consecutive patients (N = 322) with localized PDAC (2011-2020) who received at least one cycle of FOLFIRINOX (N = 271) or gemcitabine/nab-paclitaxel (N = 51) as initial treatment. We assessed somatic alterations in four driver genes (KRAS, TP53, CDKN2A, and SMAD4) by targeted next-generation sequencing, and determined associations between these alterations and (1) rate of metastatic progression during induction chemotherapy, (2) surgical resection, and (3) complete/major pathologic response.

RESULTS

The alteration rates in driver genes KRAS, TP53, CDKN2A, and SMAD4 were 87.0%, 65.5%, 26.7%, and 19.9%, respectively. For patients receiving first-line FOLFIRINOX, SMAD4 alterations were uniquely associated with metastatic progression (30.0% vs. 14.5%; P = 0.009) and decreased rate of surgical resection (37.1% vs. 66.7%; P < 0.001). For patients receiving induction gemcitabine/nab-paclitaxel, alterations in SMAD4 were not associated with metastatic progression (14.3% vs. 16.2%; P = 0.866) nor decreased rate of surgical resection (33.3% vs. 41.9%; P = 0.605). Major pathologic response was rare (6.3%) and not associated with type of chemotherapy regimen.

CONCLUSIONS

SMAD4 alterations were associated with more frequent development of metastasis and lower probability of reaching surgical resection during neoadjuvant FOLFIRINOX but not gemcitabine/nab-paclitaxel. Confirmation in a larger, diverse patient cohort will be important before prospective evaluation of SMAD4 as a genomic biomarker to guide treatment selection.

Functional precision oncology using patient-derived assays: bridging genotype and phenotype

Genomics-based precision medicine has revolutionized oncology but also has inherent limitations. Functional precision oncology is emerging as a complementary approach that aims to bridge the gap between genotype and phenotype by modelling individual tumours in vitro. These patient-derived ex vivo models largely preserve several tumour characteristics that are not captured by genomics approaches and enable the functional dissection of tumour vulnerabilities in a personalized manner. In this Review, we discuss several examples of personalized functional assays involving tumour organoids, spheroids and explants and their potential to predict treatment responses and drug-induced toxicities in individual patients. These developments have opened exciting new avenues for precision oncology, with the potential for successful clinical applications in contexts in which genomic data alone are not informative. To implement these assays into clinical practice, we outline four key barriers that need to be overcome: assay success rates, turnaround times, the need for standardized conditions and the definition of in vitro responders. Furthermore, we discuss novel technological advances such as microfluidics that might reduce sample requirements, assay times and labour intensity and thereby enable functional precision oncology to be implemented in routine clinical practice.

Pancreatic Organoids: A Frontier Method for Investigating Pancreatic-Related Diseases

The pancreas represents an important organ that has not been comprehensively studied in many fields. To fill this gap, many models have been generated, and traditional models have shown good performance in addressing pancreatic-related diseases, but are increasingly struggling to keep up with the need for further research due to ethical issues, genetic heterogeneity and difficult clinical translation. The new era calls for new and more reliable research models. Therefore, organoids have been proposed as a novel model for the evaluation of pancreatic-related diseases such as pancreatic malignancy, diabetes, and pancreatic cystic fibrosis. Compared with common traditional models, including 2D cell culture and gene editing mice, organoids derived from living humans or mice cause minimal harm to the donor, raise fewer ethical concerns, and reasonably address the claims of heterogeneity, which allows for the further development of pathogenesis studies and clinical trial analysis. In this review, we analyse studies on the use of pancreatic organoids in research on pancreatic-related diseases, discuss the advantages and disadvantages, and hypothesize future trends.

Advances in small molecule maintenance therapies for high-grade serous ovarian cancer

INTRODUCTION

Ovarian cancer is one of the most lethal gynecological tumors with a lack of effective treatment modalities especially in advanced/recurrent disease. Nevertheless, recently, new small molecules have emerged as an effective approach for the management of ovarian cancer patients, especially in the maintenance setting.

AREAS COVERED

This review summarizes the role of small molecules used in the management of high-grade serous ovarian cancer. The authors performed a critical review of current evidence and ongoing studies. Of note, tyrosine kinase inhibitors (TKIs) and poly(ADP-ribose) polymerase (PARP) inhibitors are the most intriguing medications in this setting.

EXPERT OPINION

Protein-targeted therapies against tumor tissues have progressed significantly in the last years due to an enhanced knowledge of the biological and molecular processes of carcinogenesis. Treatment with small molecules allows the targeting of specific proteins involved in cancer biology. TKIs seem promising but further data are necessary to assess the pros and cons of adopting this treatment modality. PARP inhibitors represent the new standard of care for ovarian cancer patients harboring either a BRCA mutation or with homologous recombination deficiency (HRD). Interestingly, the accumulation of data has highlighted that PARP inhibitors provide benefits even in patients with HR proficient tumors.

How to build a tumor: An industry perspective

During the past 15 years, a plethora of innovative 3D in vitro systems has been developed. They offer the possibility of identifying crucial cellular and molecular contributors to the disease by permitting manipulation of each in isolation. However, improvements are needed particularly with respect to the predictivity and validity of those models. The major challenge now is to identify which assay and readout combination(s) best suits the current scientific question(s). A deep understanding of the different platforms along with their pros and cons is a prerequisite to make this decision. This review aims to give an overview of the most prominent systems with a focus on applications, translational relevance and adoption drivers from an industry perspective.

Patient-Derived Organoid Pharmacotyping Guides Precision Medicine for Pancreatic Cancer

The patient-derived organoids (PDO) platform recapitulates the phenotype, genotype, and molecular characteristics of primary tumors. High-throughput drug screening in terms of pharmacotyping using standard-of-care chemotherapy agents in the PDO platform has shown promising sensitivities to guide precision medicine for individual patients with pancreatic ductal adenocarcinoma (PDAC) within a clinically relevant time frame. See related article by Seppälä et al., p. 3296.

Challenges in genomic analysis of model systems and primary tumors of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is characterized by aggressive tumor behavior and poor prognosis. Recent next-generation sequencing (NGS)-based genomic studies have provided novel treatment modes for pancreatic cancer via the identification of cancer driver variants and molecular subtypes in PDAC. Genome-wide approaches have been extended to model systems such as patient-derived xenografts (PDXs), organoids, and cell lines for pre-clinical purposes. However, the genomic characteristics vary in the model systems, which is mainly attributed to the clonal evolution of cancer cells during their construction and culture. Moreover, fundamental limitations such as low tumor cellularity and the complex tumor microenvironment of PDAC hinder the confirmation of genomic features in the primary tumor and model systems. The occurrence of these phenomena and their associated complexities may lead to false insights into the understanding of mechanisms and dynamics in tumor tissues of patients. In this review, we describe various model systems and discuss differences in the results based on genomics and transcriptomics between primary tumors and model systems. Finally, we introduce practical strategies to improve the accuracy of genomic analysis of primary tissues and model systems.