Cancer is a major health problem and a leading cause of death worldwide. Early cancer detection and continuous changes in treatment strategies have improved overall patient survival. The recent development of targeted drugs offers new opportunities for personalized cancer treatment. Nevertheless, individualized treatment is accompanied by the need for biomarkers predicting the response of a patient to a certain drug. One of the most promising breakthroughs in recent years that might help to overcome this problem is the organoid technology. Organoid cultures exhibit self-renewal capacity, self-organization, and long-term proliferation, while recapitulating many aspects of their primary tissue. Generated patient-derived organoid (PDO) libraries constitute “living” biobanks, allowing the in-depth analysis of tissue function, development, tumor initiation, and cancer pathobiology. Organoids can be derived from all gastrointestinal tissues, including esophageal, gastric, liver, pancreatic, small intestinal and colorectal tissues, and cancers of these tissues. PDOs are amenable to various techniques, including sequencing analyses, drug screening, targeted therapy testing, tumor microenvironment studies, and genetic engineering capabilities. In this review, we discuss the different applications of gastrointestinal organoids in basic cancer biology and clinical translation. Three-dimensional mini-organs or “organoids” derived from patients with gastrointestinal tumors can offer new insights into cancer biology and guide the selection of appropriate therapies. By cultivating gastrointestinal tumor cells with an appropriate combination of growth factors, researchers can generate organoids that recapitulate key features of the original malignancy in miniature. Therese Seidlitz and Daniel E. Stange from the University Hospital Carl Gustav Carus in Dresden, Germany have reviewed the use of such models for cancer research and clinical care. These organoids can be used to identify the treatment strategies most likely to be effective in a given patient, or to assess differences between primary tumors and their metastases. Researchers can also genetically manipulate organoids made from healthy tissue to study the biological pathways that contribute to tumor development and disease progression in cancer patients. One of the most important challenges for further improvement of cancer therapy is the translation of achieved results from bench to bedside. A plethora of results are still generated in cancer models that poorly recapitulate the behavior of patients’ tumors. This often leads to poor reproducibility in the clinic. An example is the extraordinarily high number of newly developed drugs that fail in clinical trials but perform well in cancer models2. Immortalized traditional two-dimensional (2D) cancer cell lines are still the backbone of current human cancer research. These cancer cell lines, which are characterized by low handling costs and ease of use, mostly do not reflect the parental tumor due to the outgrowth of only a few cancer cells during cell line establishment and the extensive adaption to the growth conditions on cell culture plates. Regular passaging, often over many decades, leads to monogenetic cell lines that do not recapitulate the heterogeneity of the tumors they were derived from. In contrast, patient-derived tumor xenograft (PDTx) models maintain the histology and genomic aberration patterns of their parental tumors to a much greater degree. Their use in cancer research is nevertheless restricted due to their high costs and the length of time needed for their establishment, usually months.In recent decades, our knowledge of the origin and progression of cancer has increased tremendously. Early cancer detection and improved standard-of-care cancer treatments have increased overall survival. In addition, the development of targeted therapies based on the individual genetic alterations of a patient’s tumor offers new opportunities. Despite the improved understanding, cancer remains a major worldwide health problem ranking as the leading cause of deathRecently developed three-dimensional culture systems termed organoids open up new opportunities in cancer research, including efforts to personalize cancer treatment. Organoids have been shown to retain the heterogeneity and genetic identity of the cancer tissue from which they are derived. The generation of cancer organoids is accomplished in a short time (weeks), often with high efficiency, and cultures can usually be passaged an unlimited number of times. Even though they are still expensive due to the complex growth factor cocktail in the medium and the necessity for an extracellular matrix (ECM), organoid cultures are much cheaper than mouse-based PDTx models. The recently reported development of large “living” biobanks of patient-derived cancer organoid (PDO) libraries reveals opportunities for the in-depth analysis of cancer biology as well as translational clinical applications. In this review, we describe different gastrointestinal organoid methodologies and their applications for basic and translational cancer research.4. AdSCs can only generate cells related to the tissue from which they are derived, requiring a growth factor enriched medium that mimics the stem cell niche of the original tissue. In contrast, PSCs have the ability to differentiate into any cell of the human body if a stepwise differentiation protocol has been established. Another difference is the time period until the culture is established: while AdSC-derived organoids can be set up in a short period , establishing PSC-derived organoids takes ~20–60 days depending on the complexity of the differentiation protocol. Nevertheless, the main difference is related to the tissue type, while AdSC-derived organoids contain cells from only one tissue type , PSC-derived organoids can contain cells of multiple tissue types .Organoids can be derived out of primary tissue from adult stem cells (AdSCs) or from embryonic stem cells and induced pluripotent stem cells (together PSCs)5. To achieve this, detailed knowledge about the signaling pathways active in the intestinal stem cell niche was applied. After embedding in Matrigel®, intestinal crypts were cultured in serum-free medium containing the following growth factors: Rspondin , epidermal growth factor (EGF) and Noggin (a bone morphogenetic protein inhibitor). In the case of initiation from Lgr5+ intestinal stem cells, WNT was needed in the medium for the first days until Paneth cells had formed. The organoids grew as highly polarized epithelial structures with proliferative crypts and differentiated villus compartments5. The established protocol was later adopted to develop organoids from murine and human gastrointestinal epithelial tissues, including those of the colon8, pancreas9, liver10, stomach13, and esophagus14. Generally, AdSC-derived organoids are embedded in a laminin-rich ECM (such as Matrigel® or Basement Membrane Extract (BME®)), overlaid with growth factor-supplemented medium to maintain the stem cell niche, which allows self-renewal and long-term proliferation -expressing intestinal stem cellsion Fig. . Organoi20. With this system, the epithelial cells as well as the surrounding stroma, including fibroblasts and immune cells, are cultivated together, representing a more organotypic approach  systemach Fig. . The mecium Fig. .32 and gastric cancers, including esophageal adenocarcinoma (GC/EAC)40, esophageal squamous cell carcinoma (ESCC)41, liver cancer (LC)44, pancreatic ductal adenocarcinoma (PDAC)47, and gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs)48 PDOs derived from patient tumor material have extended our molecular understanding of human cancer. As nucleic acids can be easily retrieved in high quality and without contaminating nucleic acids from the microenvironment, characterization by sequencing can be performed in a straightforward manner without DNA/RNA amplification steps and sophisticated bioinformatic approaches to denoise the data from non-tumor-derived signals Fig. . Sequenc28. In-depth DNA sequencing and RNA expression analysis showed that PDOs recapitulated the somatic copy number alterations (SCNA) as well as the mutation spectra found in CRC. Typical CRC inactivating mutations in the tumor suppressor genes APC, TP53, FBXW7, and SMAD4 as well as activating mutations in KRAS, PIK3CA, BRAF, and TGFBR1/2 were recognized. A separate study using a subset of these PDOs performed proteomic analyses, which proved that proteomic approaches in PDOs are feasible49. Distinct organoid profiles at the proteomic level were observed between the PDOs and matching healthy counterparts as well as between different patients, corroborating the importance of personalized profiling of each individual sample. In line with these studies, Fujii et al. generated an organoid biobank composed of 55 CRC PDOs of different histological subtypes and clinical statuses29. Genetic profiling of PDOs revealed the typical mutational spectrum of CRCs50. The authors revealed that individual PDO lines exhibited different growth factor dependencies on the basis of present or absent genetic alterations. As an example, all adenoma PDOs grew without WNT and Rspondin supplementation. Alterations in KrasG12V led to EGF independence. Microsatellite-stable organoids were less dependent on Noggin, A83-01, and normoxic culture conditions. Yao et al. reported a biobank of 80 locally advanced rectal cancer PDOs from biopsy specimens31. Eighteen PDO lines were analyzed by whole-exome sequencing recapitulating the mutational profile observed in the matched tumor tissue. Known cancer driver mutations were found with a 94.4% overlap with the described TCGA dataset50. Most altered genes, including APC, FBXW7, ARID1A, LRP5, and SOX9, were related to the WNT pathway (88.9%). Ganesh et al. reported that 77% of mutations in primary rectal cancers could be detected in the corresponding PDOs30.The first cancer organoid biobank generated comprised a set of 20 individual CRC PDOs38. Three focused on the molecular classification of gastric cancer and revealed that PDOs recapitulated the mutational pattern of their primary tumors36. GC can be molecularly divided into four subtypes: the chromosomal instability (CIN) subtype with frequent TP53 mutations and RTK-RAS pathway amplifications; the genomically stable (GS) subtype displaying diffuse tumor morphology and CDH1 as well as RHOA alterations; the microsatellite instability (MSI) subtype with a hypermutation phenotype; and the Epstein-Barr virus-positive (EBV) subtype showing frequent PIK3CA mutations and silencing of CDKN2A51. Of note, PDO cultures of all four GC subtypes could be established, indicating that the culture conditions do not exclude the successful outgrowth of certain subtypes36. Esophageal cancer is histologically classified as either EAC or ESCC. While EAC closely resembles the CIN subtype of GC with a high number of chromosomal aberrations, mRNA expression, DNA methylation, and SCNA data demonstrated that ESCC closely resembles head and neck squamous cell carcinoma at the molecular level52. Two studies validated the genomic landscape of primary EAC PDOs, which included the main cancer drivers TP53, CDKN2A, KCNQ3, PIK3CA, MUC6, and ARID1B40. RNA sequencing showed that primary tumor tissues, normal esophagus tissues, and PDOs formed separate clusters, reflecting the organoid culture environment compared to the heterogeneous cell type composition in the primary tumor specimen39. This highlights the issue that the microenvironment is missing in contemporary PDOs, which needs to be kept in mind when interpreting PDO-based research results.Several studies have reported the generation of GC PDO libraries9. Three additional studies also focused on the generation of PDAC PDO libraries47. All studies identified common PDAC driver mutations in KRAS, TP53, SMAD4, and CDKN2A in PDOs. Interestingly, Tiriac et al. also observed uncommon genetic alterations in ERBB2, PIK3CA, and MAP2K145. Alterations in ERBB2 and PIK3CA led to marked sensitivity to afatinib or everolimus. Additionally, 70% of the PDOs showed characteristics of the classical or progenitor subtype, and ~30% showed characteristics of the basal or quasi-mesenchymal subtype. In contrast, most established monolayer 2D cell lines show expression profiles representative of the basal or quasi-mesenchymal subtype53. Seino et al. identified three functional PDAC subtypes with distinct WNT signaling dependencies by performing extensive genotype-phenotype correlation studies46.The generation of PDAC PDOs was first reported by Boj et al.42. Here, eight different organoid lines, including three hepatocellular cancer (HCC), three cholangiocellular carcinoma (CCC) and two combined HCC/CCC PDO lines, were analyzed by sequencing and shown to recapitulate the molecular profiles of the corresponding tumor of origin. The cultures also preserved the subtype-specific histology, gene expression profile, and mutational pattern of the parent tumor. Nuciforo et al. demonstrated that HCC/CCC organoids can be generated from ultrasound-guided needle biopsy samples43. Whole-exome sequencing results of the generated biopsy-derived PDO lines and primary tumor tissues did not significantly differ in terms of mutational rate, and typical frequent mutations of HCC/CCC in the driver genes TP53, ARID1A, and TSC1 were found. However, the authors also identified several novel alterations in the PDOs that were not present in the original biopsies, indicating either detection problems in the biopsy sequencing or the preferred outgrowths of a subclone in PDO lines.The generation of LC PDOs was first reported by Broutier et al.54. They are characterized by a loss of tubular structures and diffuse expression of neuroendocrine markers. Recently, the generation of a GEP-NEN organoid library was described by the Sato lab48. Altogether, 25 GEP-NEN PDOs were generated and analyzed by comprehensive molecular characterization. Whole-genome sequencing of GEP-NENs revealed frequent genetic alterations in TP53 as well as RB1 and characteristic chromosome-wide loss of heterozygosity.GEP-NENs are rare cancers occurring in the gastrointestinal tract with distinct histopathological featuresTaken together, all these studies demonstrated that PDO libraries can be generated from the respective gastrointestinal cancer entities and that they molecularly resemble the tumor they were derived from and thus represent a powerful platform for studying cancer pathobiology in an ex vivo setting similar to the in vivo situation.55. However, these 2D cancer cell lines poorly reflect the primary tumor tissue phenotypically and genetically, which may be the main reason for the high failure rate of newly developed drugs56. PDOs may better recapitulate primary tumors and might thus represent more accurate models for drug screening and discovery. To date, different drug screening approaches on living gastrointestinal PDO biobanks have been reported  and oxaliplatin was seen. Additionally, the screen documented a sensitivity to targeted drugs, i.e., napabucasin (a STAT-3 inhibitor), abemaciclib (a CDK4/6 inhibitor), and VE-822 (an ATR inhibitor). Some of the drugs are approved or in clinical trials for disease entities other than GC, highlighting the potential of PDO biobanks in delineating potentially interesting cancer entities suitable for pharmaceutical company investments in clinical trials. A medium-scale drug screen in EAC PDOs with 24 anticancer compounds revealed resistance to classical chemotherapeutics, including 5-FU, epirubicin and cisplatin alone or in combination, but interestingly, the PDOs were sensitive to inhibitors of the receptor tyrosine kinases EGFR and ERBB2 and inhibitors of MEK1/239.GC PDOs were screened by Yan et al. in a medium-scale drug screen of 37 anticancer drugs in nine GC PDOs from seven patients42. For instance, treatment with the PI3K inhibitor taselisib resulted in a growth-inhibitory effect in five out of six LC PDOs. Additionally, ERK1/2 inhibition was proposed as a potential therapeutic approach for primary LC treatment. PDOs with insensitivity to MEK and BRAF inhibition showed an ambiguous response to ERK1/2 targeting. The lab of Selaru treated LC PDOs in a high-throughput drug screen with a library composed of 129 cancer drugs44. Overall, 13 drugs showed the ability to kill more than 90% of the LC PDOs, while nine of these drugs  were effective for treating all PDOs.LC PDOs were first screened by the Huch lab in a medium-scale drug screen with 29 anticancer compounds, including drugs in clinical use or development, which showed differential sensitivity for a subset of compounds45. The reported data revealed that 33% of PDOs were resistant to all five drugs. Screening these multidrug-resistant lines with a targeted therapy panel of 21 drugs revealed a very high sensitivity to targeted agents for half of the PDOs. The authors concluded that drug screening of individual PDOs could reveal alternative treatment regimens when resistance to standard of care treatment is found. A second study by the Clevers lab assessed the feasibility of performing larger drug screens with PDAC organoids. PDAC PDOs were exposed to a drug library of 76 targeted therapeutics and classical chemotherapeutics47. For most PDOs, multiple compounds that resulted in effective tumor killing could be identified. However, no single therapy could be detected that worked for all PDOs, indicating the necessity to test each individual PDO to define the best treatment option.The Tuveson lab analyzed the response of a PDAC organoid biobank to five chemotherapeutic drugs commonly used in PDAC treatment ® or BME® (2–100%). Depending on the experimental setup, some studies exposed organoids to the treatments directly after seeding, e.g., using pre-spotted drug plates, while others studies allowed the organoids to recover for some days before the drugs were administered. This might result in differences in the effects of drugs on cell division and proliferation, as organoids show an increased proliferation rate after splitting, which decreases over time. One of the major barriers to screening PDO biobanks with medium- to large-scale drug libraries is the high cost of Matrigel® or BME®. Reducing the required volume would directly affect this major matter of expense. Such miniaturization of the organoid platform for ultra-high-throughput drug screenings was reported by Du et al.57. Genetically engineered human colon organoids with a KRASG12D mutation were plated in 1536-well plates. For the assay, 2 µl BME® per well was mixed with ~400 cells. Each well was covered with 5 µl growth medium, and for drug testing, 0.1 µl per drug was added. The comparison of the drug response in 1536-well plates to that in 384-well plates revealed identical growth inhibitory effects of the compounds. Due to miniaturization, drug library testing with 10,240 compounds (one concentration each) became feasible. Although the authors used a genetically modified colon organoid and not PDOs with a much higher variability in their growth as well as splitting behavior, the reported data demonstrate the potential for ultra-high-throughput assays using PDOs to define novel treatment options.Overall, the experimental setup for drug screen assays on PDO biobanks slightly differs between the different research groups. In general, drug response is analyzed by using a quantitative measure to assess viability after treatment. Organoids were plated in different plate formats (96- or 384-well plates) with different concentrations of MatrigelThe main premise for personalized cancer therapy is the presence of patient-specific alterations and pathway aberrations depicting potential drug targets. Molecular profiling, drug assays, and targeted therapy testing on PDOs revealed promising results for different cancer entities. To date, different clinical studies have determined the feasibility and potential use of PDOs as a predictive test for therapy regimens Fig. .Fig. 4Pe35. As an example, the response to anti-EGFR treatment with cetuximab was analyzed in five metastatic CRC PDOs and compared to the clinical response of the respective patients. Two PDOs established from biopsies before anti-EGFR treatment showed no response in line with the clinical response of the two patients. Both patients (unsurprisingly) had mutations in KRASG12D or BRAFV600E. A third cetuximab-resistant PDO line was established from a biopsy from a progressive tumor lesion that initially responded to anti-EGFR treatment. Molecular analysis revealed EGFR amplification, no RAS pathway mutations and high amphiregulin mRNA levels. These alterations theoretically should lead to responsive cancer cells, but treatment paradoxically led to increased proliferation of the respective PDO line. This finding highlights the potential of PDOs to predict clinical outcome better than molecular analyses alone at least in some cases. Overall, the authors reported an 88% positive predictive value of PDOs in forecasting the patient’s response to chemotherapy or target therapy. Ooft et al. additionally explored the power of PDOs derived from metastatic CRCs to predict the response to classical chemotherapy32. The study focused on regimens classically used in CRC treatment, including irinotecan as well as 5-FU/capecitabine alone or in combination with oxaliplatin or irinotecan. The authors could correctly predict the response for more than 80% of patients treated with irinotecan monotherapy or 5-FU/irinotecan combination therapy, while the response for the 5-FU/oxaliplatin combination therapy could not be predicted.Vlachogiannis et al. were the first to report the potential of PDOs to predict therapy response using CRC and GC/EAC organoids generated from patients from four phase 1/2 clinical trials30. PDOs were treated with 5-FU alone or in combination with oxaliplatin. The obtained data revealed a diverse spectrum of dose responses, and the response predictions were correlated with the clinical outcomes of the patients. Furthermore, the authors tested radiation treatment, which also resulted in heterogeneous responses among PDOs. The displayed sensitivity was consistent with the patients’ clinical outcomes upon irradiation. As part of a clinical phase III trial, Yao et al. reported a locally advanced rectal cancer organoid biobank31. In this study, PDOs were exposed to 5-FU or irinotecan chemotherapy or irradiation. Different PDO lines showed diverse responses to individual treatments. The authors showed that the patients achieved a good clinical response when their corresponding PDOs were sensitive to at least one of the three treatments. Furthermore, combinatorial treatment also resulted in consistent outcomes between the PDOs and the patients. All in all, the authors could predict the therapy response in 85% of patients, illustrating the potential of rectal cancer PDOs to stratify rectal cancer patients correctly as responders and non-responders.Ganesh et al. recently described the generation of a rectal cancer organoid biobank from tumor tissues of different stages and analyzed the ex vivo response of PDOs to clinically relevant chemotherapy and radiation treatmentTo date, several co-clinical studies have already suggested a high accuracy of PDOs to correctly predict therapy response. It will now be important to optimize protocols with regard to a high culturing rate and fast expansion to allow timely drug testing. This will allow the integration of PDOs into clinical settings, which is the prerequisite to validating these promising preliminary results in prospective clinical trials.29. Cancer organoids from a primary tumor with histopathological heterogeneity resulted in an organoid culture with distinct morphologies, which could be isolated and subsequently grown independently. The majority of driver mutations were conserved between the subcloned lines, except for a TP53 mutation, which was unique to one line. Roerink et al. reported the generation of clonal CRC organoids from multiple single cells of different tumor regions of three CRC patients and adjacent normal intestinal crypts58. As expected, cancer cells showed extensive molecular diversification and carried a higher mutation burden than normal cells. Whole-genome sequencing allowed the generation of phylogenetic trees of tumor evolution for each patient. These phylogenetic trees consisted of a trunk containing mutations common to all clonal CRC cells from one patient that was then divided into subsequent trees, with the ultimate tree containing individual mutations of an individual clonal organoid line. In general, clonal organoids from one region clustered together and shared common driver mutations, but individual organoid lines from one region still exhibited substantial differences in their mutational pattern (up to 40% of mutations were not shared). Most interestingly, molecular diversification translated into differential responses upon drug treatments. Of note, even within clonal organoid lines of one tumor region, substantial differences were observed for classical chemotherapeutics and targeted therapies. In line with this, a further study by Schumacher et al. investigated the impact of intratumoral heterogeneity on treatment effects in CRC59. The authors generated five sibling organoid cultures from separate regions of one patient and showed that the sibling cultures exhibited remarkable genetic heterogeneity and did not respond uniformly to targeted therapies.Gastrointestinal cancers have been shown to contain to varying degrees different subclones that differ genetically from each other. PDOs now provide an excellent platform to study the functional relevance of intratumoral heterogeneity, i.e., if genetic differences have an impact on the biological behavior and drug response Fig. . Fujii e44. Comparisons of PDOs from different regions of GC specimens revealed marked differences in the aberration patterns33. While key driver genes such as TP53, CDH1, and ARID1A were again common to both tumor regions, six out of nine PDOs showed subclonal mutations, including mutations in genes such as APC and BRCA2, that were only present in one of the two analyzed regional PDOs. Similar to CRC, differential responses of regional PDOs to drug treatments were observed. Li et al. did not analyze different tumor regions but instead used spectral karyotyping to reveal the clonal hierarchy and dynamics in EAC PDOs39. The data revealed that most PDO cells were aneuploid, and all cultures consisted of heterogeneous cell populations with a variety of chromosome numbers and chromosomal rearrangements. To investigate clonal dynamics, whole-genome sequencing was performed at different time points up to 6 months. These analyses revealed that during the process of establishing PDOs, selection pressure exists that selects genetic subclones but that organoid heterogeneity is maintained during subsequent culturing. Interestingly, the dynamic clonal behavior varied between the lines, from relatively stable to ongoing in others.Intratumoral heterogeneity can also be found in LC and GC/EAC and resolved in PDO cultures. LC PDOs derived from distinct tumor regions of five patients were assessed by drug screening, revealing pan-, inter- and intra-patient effective drugs29. Exome sequencing confirmed common driver mutations between the primary and metastatic couples. Interestingly, the metastasis-derived organoids showed a higher metastatic capacity upon xenotransplantation, indicating that PDOs of different sites (primary vs. metastatic) functionally differ while harboring similar aberrations. Yan et al. analyzed paired organoid cultures of primary tumors and lymph node metastases of GC, detecting varying degrees of heterogeneity from couple to couple33. PDOs from primary tumors and lymph node metastases of diffuse-type GC showed only a few differences. However, marked differences were recognized in mixed-type GC, as only 23% of mutations were shared between the primary tumor and metastasis. Histologically, the primary tumor showed a diffuse growth pattern, while lymph node metastases had a glandular morphology.Cancer organoids have also been used to study tumor evolution by comparing PDOs from primary and metastatic sites of a patient Fig. . As an eOverall, the performed studies indicate that PDOs from different tumor regions and from different sites of metastatic spread exhibit similarities in molecular features, e.g., in driver gene mutations, but vary strikingly in terms of their drug responses or metastatic capability. This emphasizes the value of PDOs as a “living system”, allowing researchers to perform functional assays such as drug tests and metastasis assays to reveal important differences.62. The tumor microenvironment plays an essential role in tumor development and progression, as bi-directional signaling between tumor and environment fosters tumor growth. For example, cancer-associated fibroblasts (CAFs) have the potential to secrete ECM molecules and soluble factors that can further stimulate tumor growth, cell survival, and metastasis64. Nevertheless, the positive impact of the microenvironment on tumor growth or therapy resistance provides novel therapeutic points of interference. To date, the interaction of the microenvironment with tumor cells has mainly been studied only in vivo. Nevertheless, there is a need to study the interactions in vitro in a controlled environment enabling direct visualization. However, cancer organoids typically consist of pure tumor cells with no additional stroma or immune cells. Fibroblasts are usually observed in the initial organoid culture after plating but are lost in early passages of culturing. To circumvent this limitation, the Tuveson lab used a co-cultivation approach of human PDAC organoids and murine CAFs  cells) detect the presence of tumor-associated antigens expressed on tumor cells, which can then be killed by immune effector cells. Similar to what has been discussed above, observing the process of activation of the immune system followed by cytotoxic killing of malignant cells in vitro would greatly help to understand the biology behind and allow functional testing of the effectiveness of immunotherapeutics for a certain patient. Recent studies have successfully activated immune cells by co-cultivation with PDOs, which resulted in a killing cancer organoids . The co-culture led to antigen-specific stimulation and activation of T cells. Two applications of this co-culture method can be foreseen. First, the potential effect of immunotherapeutics could be evaluated in vitro. Second, patient-specific T cells can be generated and expanded for adoptive T cell transfer. Another study assessed the functionality of tumor-infiltrating T lymphocytes upon chemoradiotherapy in CRC organoids74. In a proof-of-principle study, rectal cancer organoids and infiltrating T lymphocytes were separately expanded, co-cultured and analyzed for cytotoxic effects. The killing effects of T cells were significantly greater for organoids from patients who responded well to chemoradiotherapy than for organoids from non-responders. The additional blockage of PD-1 on T lymphocytes with increased PDL-1 expression led to a recovery of antitumor immunity against PDOs in some patients.Since its initial success in the clinic, cancer immunotherapy has become the rising star of cancer therapy in recent yearsids Fig. . As an e75. The application of CAR T cells in solid cancers is more challenging due to the limited number of expressed neoantigens, among other reasons. Nevertheless, in a proof of concept study, the Farin laboratory established a platform to test CAR cell cytotoxicity toward PDOs76. Using an NK cell line in which CAR was introduced to target the ubiquitously expressed epithelial antigen EPCAM, CAR-mediated toxicity could be analyzed in CRC as well as in healthy organoids. Next, NK-CAR cells targeting the tumor-specific neoantigen epidermal growth factor receptor variant III (EGFRvIII) were used in conjunction with an EGFRvIII-expressing CRC PDO, resulting in efficient killing of the PDO, while normal organoids remained unharmed. The results demonstrated the usefulness of organoid CAR platforms for assessing tumor cell specificity.Immunotherapies using chimeric antigen receptor (CAR) lymphocytes have led to impressive responses in various hematological malignancies, and the use of CAR-engineered T cells for leukemia therapy was recently approved by the FDAThe presented studies demonstrate the potential applications of co-cultivation assays of PDOs from different malignant tumors combined with stromal, immune, or CAR cells in the discovery and development of novel therapeutic strategies that will target stromal compartments or help to direct immune cells to their target.Organoids derived from cancers are unique in their genetic makeup. Each PDO is an avatar of the cancer it is derived from, making it an ideal tool to study individual therapeutic strategies or to test new substances in large PDO biobanks to find the ideal cancer entity for further clinical studies. Nevertheless, when general biological questions are the focus of research, genetically defined models are necessary. The genetic manipulation of healthy tissue-derived human organoids, e.g., by CRISPR/Cas9, enables the generation of such defined models. Such models are ideal tools to study, among others, initial malignant transformation, the effect of certain altered signaling pathways on the tissue of interest or the functional analysis of putative oncogenic candidate genes Fig. .21. The Kuo laboratory generated mouse lines combining up to four floxed alleles of Apc, Trp53, KrasG12D, and Smad4, which were recombined by Cre in vitro and subsequently analyzed21. While pancreatic and gastric ALI organoids displayed dysplasia in vitro, quadruple-mutant colon ALI organoids could be transformed to adenocarcinomas. Starting from healthy intestinal organoids, two studies reported the use of CRISPR/Cas9 genome editing technology to introduce different combinations of common CRC driver mutations to dissect cancer progression. Drost et al. from the Clevers lab sequentially mutated the tumor suppressor genes APC, TP53, and SMAD4 and added G12D activation of the KRAS oncogene to generate quadruple-mutant organoids77. Matano et al. from the Sato lab in parallel generated the same quadruple-mutant organoids and added an activating mutation in the PIK3CA gene78. Both studies showed that these driver mutations resulted in tumor growth independently of all human intestinal stem cell niche factors by growing them in medium without EGF, WNT, Rspondin, and Noggin. After subcutaneous xenotransplantation into mice, the quadruple-mutant tumor organoids from the Clevers lab formed tumors with invasive features without metastatic spread. Of note, orthotopic implantation of the quadruple-mutant tumor organoids, but not any kind of combination of triple-mutant organoids, into the cecum of mice led to spontaneous metastatic spread into the lung and liver79. Interestingly, when the Sato lab engineered triple-mutant organoids starting from chromosomally unstable human adenomas, splenic injection resulted in micrometastases in the liver78. The de Sauvage laboratory modeled the quadruple-mutant model with the combination of Apc, Kras, Trp53, and Smad4 changes in murine small intestinal organoids, combined Cre/Lox with CRISPR/Cas9 technology, and transplanted these organoids orthotopically into mice80. Invasive CRC carcinoma with metastatic spread was observed, but most interestingly, simultaneous depletion of Lgr5-positive cancer stem cells led to a substantial decrease in liver metastatic burden. Two additional studies underline the need for an orthotopic transplantation environment of engineered organoids to study CRC metastasis82. Taken together, several studies thus indicate that in addition to the genetic composition of the engineered tumor organoids, the site of transplantation and therefore the local environmental conditions are also important.The first organoid model with a defined genetic setup was generated using ALI technology from murine pancreatic, gastric and colonic tissueTP53 and BP1 combined with the overexpression of key transcription factors in normal colonic epithelium led to a GEP-NEN organoid phenotype with neuroendocrine marker expression, a high KI67 index and a solid morphology48. Seino et al. reported the in vitro generation of PDAC organoids by combining a KRASG12V mutation and loss-of-function mutations in CDKN2A, TP53, and SMAD4 starting from normal human pancreas organoids46. The quadruple-mutant organoids showed histological transformation into cancer cells with features ranging from benign lesions to invasive PDACs after subcutaneous xenotransplantation. Nanki et al. modeled the impact of two frequently co-occurring mutations in diffuse gastric cancer  in normal human gastric organoids34. The loss of CDH1 led to a phenotypical change from normal cystic structures to a grape-like morphology and induced migratory activity. Nevertheless, without additional inhibition of RHOA-ROCK-induced cell death either via ROCK inhibitor treatment or via generation of a compound mutant line with RHOA knockout, the CDH1 single knockout organoids diminished over time. This study intriguingly demonstrated the power of combining organoid technology with genome editing techniques. Artegiani et al. used normal human cholangiocyte organoids and knocked out the tumor suppressor BAP1, resulting in impaired chromatin accessibility, a loss of multiple epithelial characteristics and an increase in motility83. The combination of common cholangiocarcinoma mutations  concomitant with BAP1 resulted in the acquisition of tumorigenic features after subcutaneous or intrahepatic injection83.In addition to CRC, CRISPR/Cas9 technology has also been used to model other gastrointestinal cancer entities. For example, the knockout of 84. While TA organoids can be easily cultured, SSA cells do not grow as organoids. Therefore, the prototypic mutation of SSAs, the BRAFV600E mutation, was genetically engineered in normal colon organoids. While TA organoids responded with apoptosis to TGFβ treatment, a mesenchymal phenotype was induced in SSA organoids. The authors conclude that the activation of the RAS pathway by BRAFV600E combined with TGFβ stimulation leads to the development of the mesenchymal subtype of CRCs. Interestingly, SSAs are not only characterized by BRAFV600E mutations but also show recurrent Rspondin gene fusions. Therefore, Kawasaki et al. studied the effect of Rspondin fusions in human colon organoids by generating chromosomal rearrangements for the first time using the CRISPR/Cas9 system85. Chromosomal rearrangements, including deletions and inversions affecting Rspondin2, were introduced into TP53-disrupted human colon organoids. Additionally, BRAFV600E mutations were inserted, and the TGFβ inhibitor gremlin (GREM1) was overexpressed. Xenografted tumors originating from triple-mutant organoids formed flat serrated lesions similar to SSAs. This study impressively shows that CRISPR/Cas9 technology can not only be used to mutate genes but can also be used to induce chromosomal fusion generated by deletion or inversion as well as interchromosomal translocation. CRISPR/Cas9 can also be used to delineate treatment strategies by specifically altering a certain pathway. Verissimo et al. studied the EGFR/MEK/ERK pathway in CRC organoids and introduced the oncogenic KRASG12D mutation in CRC organoids with APC and TP53 alterations86. The effect of KRAS was analyzed in single or combinational therapies using the dual EGFR/HER2 inhibitor afatinib and the MEK inhibitor selumetinib. No response to single-agent treatment was seen in the genetically modified organoids, while sensitivity to the combination treatment was observed. In conclusion, CRISPR/Cas9 technology provides an excellent experimental platform for mechanistic studies on cancer genes and pathways in a human context.In addition to generating organoid models with multiple alterations culminating in advanced carcinomas, CRISPR/Cas9 technology can be used to study the early tumorigenesis of tumor subtypes. For example, the Medema lab analyzed the response of two distinct CRC precursor lesions, tubular adenomas (TA), and sessile serrated adenomas (SSA), to TGFβ treatment87 or afamin-stabilized WNT3A88. The greatest current challenge in organoid culture is certainly the absence of the microenvironment. Nevertheless, the field is advancing rapidly, and protocols are developed that allow the incorporation of cells from the tumor microenvironment, such as fibroblasts and immune cells. Genomic, transcriptomic, and proteomic analyses of human cancer organoids help to better understand tumor biology and define targeted therapies, and the treatment of organoids allows direct assessment of the response to the identified drugs. The first co-clinical trials of patients and PDOs treated side-by-side have shown the power of organoids in predicting the treatment response. If these results are confirmed in prospective clinical trials, PDOs could ultimately be involved in clinical decision making. In conclusion, cancer organoids might bridge the gap between molecular genetics, the current biological understanding and clinical therapy in the near future.Organoid cultures of various cancers revealed to have a great impact on cancer research with widespread usage in basic and translational cancer research. Individual PDOs constitute avatars of patients’ tumors, which might help clinicians tailor treatment strategies on an individual level by predicting the response to anticancer drugs. Collections of PDOs, constituting living biobanks containing a broad spectrum of different molecular and histological subtypes of a certain cancer entity, are thought to help with identifying patient subgroups that should respond to newly developed drugs or repurposing existing drugs. However, some cancer entities  do not regularly form organoids, and the frequency of successful organoid outgrowth for some entities is far from being close to 80–90%, indicating that a relevant subtype exists that is in need of special growth conditions. Thus, new protocols and the continuous improvement of existing culturing methodologies are needed. The culturing costs are substantial, and the reagents and culture conditions differ among laboratories, so a consensus is needed. The presence of serum in conditioned medium used for some growth factors  prohibits the use of organoids in the clinical setting, but the problem might be bypassed with artificial WNT3A agonists


The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics. PGx variants modify a drug’s pharmacokinetics by impacting its absorption, distribution, metabolism, and excretion (ADME), its pharmacodynamics by perturbing proteins involved in the drug’s mechanism of action, or immune regulation.,To date, the Clinical Pharmacogenetics Implementation Consortium (CPIC)As encouraging results from these initiatives bring us a step closer to a widespread clinical implementation of PGx, this review takes a step back to discuss key milestones in the development of PGx methodology aiming at the identification, functional validation, and mechanistic understanding of clinically actionable germline variants . Purpose,300908, 305900).Box 1Allele: one of two or more versions of a genetic region.Biomarker: measure of a biological state that is indicative of a physiological or pathological process.Diplotype: combination of two haplotypes present in an individual.Epistasis: phenomenon whereby the phenotypic consequence of a genetic variant is dependent on the presence of one or multiple other genetic variants .Expression quantitative trait locus (eQTL): genetic locus harboring markers that explain a certain proportion of the variance in expression of a given gene.Fine-mapping: statistical approach aiming at determining the most likely causal genetic variant(s) for an observed association signal.Forward genetics: identification of the genetic basis of a phenotype.Genetic architecture: underlying genetic basis of a phenotype .Genetic reference population: collection of strains from a model organism that were generated through specific breeding and for which broad genotype and phenotype data are available.Genome-wide significance: threshold of significance that accounts for the fact that genome-wide association studies (GWASs) perform a large number of associations on not fully independent genetic variants. Typically, p ≤ 5 × 10−8 is used.Haplotype: group of alleles that are inherited together from a single parent.Heritability: proportion of phenotypic variation in a given population that is due to genetic variation.Imputation: inference of genetic variants that were not directly genotyped using haplotype reference panels. Imputation is possible as blocks of variants in linkage disequilibrium (LD) tend to be co-inherited, so that the presence of a given variant is predictive of the genotype at an adjacent location.Linkage disequilibrium (LD): non-random association of alleles at two or more loci in a population.Missense variant: SNV leading to the substitution of a different amino acid in the resulting protein.Monogenic trait: trait influenced by genetic variants in or near a single gene.Oligogenic trait: trait influenced by genetic variants in or near a few genes.Pleiotropy: phenomenon whereby a single gene or variant affects multiple phenotypes.Polygenic score (PGS): estimate of an individual’s genetic liability to a trait calculated as the weighted sum of phenotype-associated variants, weights being the effect sizes from GWAS summary statistics.Polygenic trait: trait influenced by genetic variants in or near a large number of genes.Polypharmacy: co-prescription of several drugs.Population differentiation: accumulation of differences in allele frequencies between populations with restricted gene flow due to natural selection or genetic drift.Population stratification: presence of sub-populations with different allele frequencies within a seemingly homogeneous population. If not accounted for, population stratification can lead to spurious genotype-phenotype associations.Reverse genetics: identification of the phenotypic consequence(s) of a particular genetic variant.Sequencing coverage: number of unique reads that include a particular base pair.Single nucleotide variant (SNV): substitution of a single nucleotide at a specific genomic location.Star allele: allele following the standardized nomenclature for genetic polymorphisms in pharmacogenetics (PGx) genes. Star alleles are not restricted to single variants but can refer to functional haplotypes of PGx genes.Summary statistics: aggregated GWAS results lacking individual genotype and phenotype data and typically including the variant’s identifier, genomic location, reference and alternative allele, and their respective frequencies, a metrics for the strength of association with incertitude and a p value.Box 2Why is diversity relevant?,,Ability to assess the phenotypic impact of a variant depends on its frequency in the studied population. Early on, it was observed that different populations do not respond equally to certain drugs.What are the consequences of lack of diversity?Despite growing awareness around the importance of inclusiveness, the majority of genetic studies remain Eurocentric, undermining the ability to discover new PGx variants and implement equitable clinical guidelines. A 2021 systematic review showed that 88% of discovery PGx genome-wide association studies (GWASs) participants were of European ancestry.How can diversity be leveraged to enable new PGx discoveries?IFNL3 genotype was comparable in both populations and that the increased prevalence of the unfavorable IFNL3 genotype in Africans explained a large fraction of the differences in treatment responsiveness across groups . Inability to metabolize these compounds is strongly correlated and was believed to be controlled by the recently discovered cytochrome P450 (CYP) system.,Acknowledging the role of genetics in drug response promoted usage of classical human genetics tools to the study of PGx.CYP2D6 (MIM: 124030), one of the best studied PGx genes. Human CYP2D6 is part of a family of 57 putatively functional genes, a dozen of which being responsible for the oxidative biotransformation of 70%–80% of all drugs,142830), a severe multisystemic response experienced by HLA-B∗5701 as the main genetic risk factor for abacavir hypersensitivity.,A drawback of early PGx studies was their inability to map differential drug responses. Progress in molecular biology and improved understanding of cellular and physiological processes set the stage for candidate gene studies (CGSs), which use prior knowledge to identify PGx interactions typically involving common or large-effect-size variants. After selecting candidate genes based on reported roles in drug ADME or relevant biological pathways, association between drug response and genetic variants within these genes is assessed.These success stories sparked the idea that new PGx knowledge could be brought into the clinic to optimize treatment. Given genotyping costs in the early 2000s,th century.HLA-B∗5701 as the main genetic risk factor for abacavir hypersensitivity,,HLA-B∗5701 screening by randomizing HLA-B∗5701-negative patients received the drug. The study demonstrated that pre-emptive screening reduced the incidence of clinically diagnosed abacavir hypersensitivity from 7.8% to 3.4%  have become the gold standard of evidence-based medicine over the course of the 20,CYP2C19-guided prescription of anti-platelet medication .CYP2C19  is required to activate clopidogrel,CYP2C19 loss-of-function (LOF) carriers in the genotype-guided group were prescribed ticagrelor instead of clopidogrel.CYP2C19 testing. Notwithstanding, recent meta-analyses suggest that CYP2C19-guided prescription could identify patients benefiting from alternative anti-platelet medication,,CYP2C19 genetic test results.,,RCTs provide strong support of causality between an exposure and an outcome, but their role in PGx has been called into question.Slow clinical implementation of PGx is often credited to lack of supporting evidence by RCTs, which can partially be attributed to the limitations described above. RCTs remain an important epidemiological tool, as demonstrated by the more than 800 PGx trials reported over the last 20 years, of which 155 are still recruiting or ongoing. However, RCTs should not be the sole approach to validate PGx interactions. Proof of efficacy of genetic testing often needs to meet higher standards compared with non-genetic tests, and most physicians unconsciously practice PGx by adjusting patient’s treatments.,genetics into pharmacogenomics. Conceptually similar and therefore both referred to as PGx hereafter, pharmacogenomics aims at discovering genetic variants affecting drug response by probing the entire genome, as opposed to a few candidate loci. This progress enabled the exploration of the pharmacogenome, which we define as regions of the human genome that influence response to medication.Box 3Microarray genotyping: Genomic variability can be assessed with genotyping microarrays that probe the identity of 250,000–4,000,000 predefined single nucleotide variants (SNVs).Short-read sequencing: A major breakthrough came from the development of high-throughput next-generation sequencing (NGS) methods that implement massively parallel sequencing of short DNA fragments.,Long-read sequencing: Bypassing the need for polymerase chain reaction, third-generation sequencing based on long reads reduces the risk of amplification-related errors and biases. By sequencing DNA fragments over 1 Mb long,,CRISPR-based genome editing: CRISPR technologies allow to assess the impact of precise genetic modifications, ranging from point mutations,,Sequencing of the human genome in the early 2000spharmacogenetics/pharmacogenomics returned over 30,000 PubMed entries published between 2000 and 2020, testifying how the genomic revolution allowed the collection of data and knowledge at an unprecedented scale.For PGx to embrace the genomic revolution, ways to effectively organize, store, and share newly generated knowledge were required, leading to the creation of PGx databases . The furGenome-wide association studies (GWASs) are observational studies wherein a large set of genetic variants spread across the genome, typically single nucleotide variants (SNVs) assessed with microarrays , is scanSLCO1B1 rs4149056 T−9; MIM: 604843).,One of the first PGx GWASs found that each additional copy of the ,VKORC1 (MIM: 608547) and CYP2C9 (MIM: 601130) in determining an individual’s drug dosage and ADR risk due to drug concentrations outside the therapeutic index.VKORC1.VKORC1, CYP2C9, and CYP4F2 (MIM: 604426).So far, most examples focused on ADRs, which are easy to identify but rare. Conversely, providing sufficient technical and financial means, drug response can be assessed in all treated subjects, offering greater statistical power to detect PGx interactions. One of the first drug responses investigated by GWAS was warfarin maintenance dose.IFNL3 .,IFNL3 genotype.GWASs also discovered new PGx interactions. Before 2011, hepatitis C was treated with a poorly tolerated combination of pegylated interferons and ribavirin that failed to clear the infection in ,A long unanswered question relates to the genetic architecture of PGx traits. In 1918, R.A. Fisher showed that continuous traits can be explained through Mendelian inheritance of many genetic variants with a genuine, albeit small, effect.,,Improving genotype-based patient classification, polygenic scores (PGSs) have gained popularity to estimate the cumulative effect of genome-wide genetic variation on a phenotype. Given their success in identifying individuals at risk for common diseases,CYPs and HLA). Though newer arrays include more PGx content, they do not yet provide perfect coverage of known PGx alleles.,Beyond classical challenges , limitations intrinsic to microarray data will have to be overcome to fully understand the genetic architecture of PGx traits. It is difficult to design probes for the highly polymorphic, repetitive, or complex regions many PGx-relevant loci map to  has widely been used to gauge the mutational landscape of known PGx genes. If non-targeted approaches, such as whole-exome sequencing (WES) or whole-genome sequencing (WGS)  allow thBox 4Burden tests collapse rare variants within a predefined region or gene into a genetic score. As they falsely assume the same direction and magnitude of effect for all grouped variants, they can be inaccurate. For instance, variants in CYP2C9 can increase, decrease, or abolish CYP2C9’s ability to metabolize warfarin.Variance-component tests investigate rare and common variants within a region simultaneously and have increased power in the presence of opposite effect variants or when only a small fraction of the variants is causal. This comes at the cost of requiring larger sample sizes, which can be challenging in PGx. The best known variance-component test is the sequence kernel association test (SKAT).Combined tests combine features from both above-mentioned tests, increasing robustness and performance in small sample sizes. The most widely used is the optimal unified SKAT test (SKAT-O).At fixed effect size, sample size required to detect an association increases with decreasing allele frequency, so that GWASs lack the power to detect rare variant associations. This led to the development of statistical methods for cumulative rare variant association testingSLCO1B1 and statin-induced myopathy, the variant originally identified by the GWAS was intronic. Only after linkage disequilibrium (LD) analysis was the likely causal missense variant, rs4149056, identified.Despite most GWAS signals mapping to non-coding regions, fine-mapping and mechanistic interpretation of these signals remains difficult.601487),ABCA1 (MIM: 600046).ABCA1 upon administration of the drug.142410) and the lncRNA HNF1α-AS1 form a regulatory network that controls the expression of several CYP genes.,Non-coding variants can mechanistically influence drug response, e.g., by influencing the binding of drug-regulated transcription factors. This concept is demonstrated by a variant  and reduce the influence of confounders,CYP2D6 revealed which one was responsible for increasing the expression of the gene.,Reverse genetics investigates the phenotypic impact of a specific polymorphism by itself or in different sexes, genetic backgrounds, tissues, and/or environments. Before 2012, reverse genetics relied on laborious cloning techniques. Since, clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9)CYP2C9.in vivo multi-tissue characterization of drug responses and can be coupled to extensive phenotyping and follow-up studies.in vitro alternative that directly mimics human genetic diversity is to harvest patient cells, which can be studied as primary cells or induced into pluripotent stem cells to generate organoids, as in the previously described drug-induced liver injury PGS study.,Forward genetics exploits genetically diverse population maintained under controlled environmental conditions to facilitate the identification of genetic modifiers of drug response. Contrasting with targeted approach, CRISPR technologies can also be used to perform high-throughput gene-level genome-wide knockout, knockdown, or knockin screens to assess the low-dimension combinatorial effect of genetic perturbations. Screens can be coupled to high-throughput molecular techniques, such as bulk or single-cell RNA sequencing, allowing measurement of downstream consequences of induced mutations.,in vitro and in vivo experimentation in model organismsBy studying appropriate and genetically diverse model systems, questions that were unanswerable due to ethical, logistical, or technical concerns become solvable. Experimental studies have their limitations, such as high costs, limited throughput, and/or poor reproducibility and translatability,Electronic health records (EHRs) have become widespread over the past decade as, besides supporting and improving diagnosis, clinical decisions, and treatment coordination, they provide new data analytics opportunities.,,Increasingly, biobanks match genotype entries with EHRs, broadening the phenotype query space exploitable for PGx research.CYP2C9 and a novel CYP2C19 variant as determinants for warfarin dosage.NAT2 (MIM: 612182) genotype.EHR-coupled biobanks accelerate our understanding of PGx by enabling the replication of known interactions and catalyzing new discoveries. Associations between drug maintenance dose and 9 PGx genes were tested in 200,000 UKB participants by assigning individuals to a metabolizer class  based on their genotype, revealing known CYP2C19 LOF carriers experienced a 0.28% increased risk of stroke (p = 0.048) while on clopidogrel.CYP2C19-based anti-platelet prescription  algorithms predicting drug responsein vitro and in vivo perturbation experiments measuring drug effects on multiple omics layers,,Despite promising results, most predictive models are not ready for the clinics. Limited size and number of available multi-omics datasets increase the risk of model overfitting and prevents independent replication, respectively.in silico approaches necessary, but they can advance PGx faster and beyond what can be achieved with traditional methods. Functional impact of common variants can be characterized through association studies, in vitro heterologous expression systems, or computational prediction tools. However, these typically fall short when assessing rare variants.CYP2C9 variantsThe wealth of rare variants in known PGx genes discovered by NGS makes it challenging to infer their function through classical methods. Not only are ,in vitro enzymatic activity of both known and unknown CYP2D6 haplotypes could be predicted.Variant combinations—within the same or different genes—can also affect drug response. Employing deep learning algorithms, haplotype effects were investigated to predict CYP2D6 enzymatic activity.We previously introduced statistical methods that integrate GWASs’ findings with other datasets to identify causal biomarker-drug response relationships. Assuming a biomarker alteration is causal to a disease, identifying drugs achieving their therapeutic effect by inducing the opposite change should provide viable treatment options. This hypothesis was tested by searching for drugs inducing gene expression patterns opposite to the ones observed in seven psychiatric disorders within the Connectivity Map (CMap),in silico models will improve prediction of drug mechanisms and safety before human clinical testing.Alternatively to data-driven top-down strategies are bottom-up approaches, such as the ones used in systems biology.in silico study of pharmaco-omics.Seventy years of methodological development have transformed PGx from an emerging science into an interdisciplinary area of research key to the implementation of personalized medicine. Pharmacogenetics established the role of genetics in pharmacological responses, with RCTs validating the first CGSs discoveries. Completion of the Human Genome Project triggered the transition to pharmacogenomics: sequencing technologies allowed ascertainment of the human PGx landscape while genome-editing tools enabled discovery and functional validation of PGx interactions. Finally, tools and concepts from statistics and computer science have been and will be key to analyze and integrate ever more complex datasets, bringing us a step closer to the in vitro and in vivo experiments, as well as high-quality in silico mechanistic and predictive models, can generate robust hypotheses, thereby improving prioritization of new putative PGx interactions. Awareness and incorporation of this knowledge in RCT design might increase their success rate and/or promote development of companion diagnostics gauging the suitability of a treatment for a given patient.Despite indisputable progress, numerous challenges lay ahead. Throughout the review, we highlighted areas of research we imagine will be decisive for the future of PGx and that overlap challenges recently laid out.,19,,All of US will recruit one million US citizens to build the largest and most diverse cohort in history, marking an important shift from the paradigm of studying white-male individuals to representing the full spectrum of a globalized world, including its minorities.Solutions to the above-mentioned challenges should ensure that progress in PGx benefits all. Genomic research remains predominantly conducted in populations of European ancestry, despite general agreement that more diversity is needed to understand the human genome.


Background: Individuals with cancer are at an increased risk of venous thromboembolism (VTE). There is a continued increased risk of recurrent VTE after the initial event as well as increased bleed risk related to VTE treatment.Objectives: This study sought to observe the incidence of recurrent VTE, major bleeding, and death in a geriatric oncology population during treatment for a cancer-associated VTE.Methods: We utilized an insurance claims database of Medicare Advantage beneficiaries 65 and older. The index VTE was identified and individuals were followed up to 180 days to observe an outcome event. Treatment groups were classified among those receiving warfarin, low-molecular weight heparins (LMWH), vena cava (VC) filters with or without anticoagulation, or no treatment. Treatment groups were compared on baseline demographic and clinical characteristics and an inverse probability of treatment weight was used to balance these factors between the groups. A competing risks, time-to-event analysis was performed including treatment only models as well as adjusted models with additional covariates. Causespecific hazards ratios (HRs) and their 95% confidence intervals were reported.Results: Treatment groups differed on baseline variables including age, comorbidities, and tumor sites. After balancing the treatment groups on baseline characteristics, those receiving LMWHs had no difference in recurrent VTE compared to warfarin but had less than half the risk of major bleeding (HR=0.48 [0.27-0.85]). Those receiving VC filters had increased risk of all outcome events relative to warfarin.Conclusions: Patients over the age of 65 with cancer are at a high risk of experiencing recurrent VTE and major bleeding during treatment for a cancer-associated VTE. These results are consistent with United States guidelines which recommend LMWHs over warfarin for treatment and secondary prevention of VTE.


Adhesive bonding of carbon-fiber-reinforced polymers (CFRPs) is a key enabling technology for the assembly of lightweight structures. Surface pretreatment is necessary to remove contaminants related to material manufacturing and ensure bond reliability. The present experimental study focuses on the effect of mechanical abrasion on the damage mechanisms and fracture toughness of CFRP/epoxy joints. The analyzed CFRP plates were provided with a thin layer of surface epoxy matrix and featured enhanced sensitivity to surface preparation. Various degrees of morphological modification and fairly controllable carbon fiber exposure were obtained using sanding with emery paper and grit-blasting with glass particles. In the sanding process, different grit sizes of SiC paper were used, while the grit blasting treatment was carried by varying the sample-to-gun distance and the number of passes. Detailed surveys of surface topography and wettability were carried out using various methods, including scanning electron microscopy (SEM), contact profilometry, and wettability measurements. Mechanical tests were performed using double cantilever beam (DCB) adhesive joints. Two surface conditions were selected for the experiments: sanded interfaces mostly made of a polymer matrix and grit-blasted interfaces featuring a significant degree of exposed carbon fibers. Despite the different topographies, the selected surfaces displayed similar wettability. Besides, the adhesive joints with sanded interfaces had a smooth fracture response (steady-state crack growth). In contrast, the exposed fibers at grit-blasted interfaces enabled large-scale bridging and a significant R-curve behavior. While it is often predicated that quality composite joints require surfaces with a high percentage of the polymer matrix, our mechanical tests show that the exposure of carbon fibers can facilitate a remarkable toughening effect. These results open up for additional interesting prospects for future works concerning toughening of composite joints in automotive and aerospace applications. Lightweight materials have played a significant role in product design since the inception of the aerospace industry. More recently, global trends toward emissions reduction and resource efficiency have further increased the importance of this topic . Indeed,t growth , but alst growth .Thermoset CFRPs have excellent properties, such as high strength, low weight, and corrosion and fatigue resistance, but the automotive industry application is limited due to the long production cycle . For thiCFRPs surfaces are primarily composed of a polymer matrix and are affected by a range of contaminants that include silicones from release agents, e.g., fluorocarbon release sprays. As contaminants are mainly embedded within the outermost surface layer of the laminates, a light removal of epoxy matrix from the adjoining interfaces has a beneficial effect on adhesion and bond reliability ,11,12. TRecent studies indicated that specialized equipment to attain high surface free energy and roughness is not always necessary for high joint strength. Indeed, obtaining a contaminant-free matrix layer using classical grit-blasting  or dry eA common mechanism of failure occurring in monolithic CFRP is represented by fiber bridging. Such an extrinsic source of energy dissipation can provide a significant toughening effect in mode I fracture testing of composite laminates ,21. It mComposite substrates were prepared using carbon-fiber-reinforced polymer (CFRP) prepregs , comprising a toughened epoxy matrix and nominal fiber volume fraction of about 60%. Unidirectional laminates . The mechanical properties are reported in The CFRP plates were surface treated before bonding using various methods, including degreasing (DG), grit-blasting (GB), and sanding (S). The DG process was carried out using an ultrasonic bath with isopropyl alcohol for a duration of 5’. The DG step was accomplished before (and after) any of the surface preparation processes used herein. After DG, the substrates were dried at 40 The cured plates have been imaged using a Zeiss Merlin scanning electron microscope (SEM), equipped with a Schottky field emission gun. The SEM images were acquired collecting the secondary electron (SE) signal, with the microscope working at an acceleration voltage of 5 kV, a beam current of 100 pA, and by using the in-chamber SE detector. All samples were sputter-coated with an Iridium layer of 4 nm-thickness before SEM analysis.n is the number of sampling points and Surface roughness was determined using a contact profilometer . A gauge length of 4 mm was selected, while the hardware’s measurement resolution was equal to 100 μm. A minimum number of three scans was carried out to ensure redundancy and consistency of the obtained results. Measurements were done in the directions parallel (0d) and polar (p) components, the following thermodynamic equilibrium equation of a solid-liquid-vapor system (s-l-v) is obtained:Surface free energy of the CFRP substrates was evaluated using the Owens–Wendt theory . By usinobtained:γlvγlvp−For a given liquid adhesive, if the corresponding polar and dispersive components of surface free energy will provide a point enclosed within the wetting envelope, then spontaneous spreading and complete wetting are expected.Double cantilever beam (DCB) adhesive joints were fabricated to determine the fracture toughness. The DCB is a convenient test configuration to ascertain the effect of surface contaminants or highlight deficiencies in surface pretreatments . A schemates see . An overThe crack length was measured along the edge of the specimen by using a GigE high-resolution camera (Prosilica GT) with a max resolution of 2448 × 2050 pixels, pixel dimension equal to 3.45 μm × 3.45 m, maximum frame rate of 15 fps, and a 2/3’’ CCD sensor (Sony ICX625). The camera was interfaced with commercial software , and snapshots of the crack propagation process were acquired through an acquisition board . A voltage proportional to the cross-head displacement was used to register an image every 0.5 mm and to correlate crack dimension with load-displacement data. Samples edges were marked every millimeter to aid crack measurement. At least four repetitions were carried out for each surface treatment. The mode-I fracture toughness (lined in  and summThe as-received (AR) material in pristine conditions is shown in the SEM images of SEM images of grit-blasted (GB) CFRP surfaces are reported in x-) and perpendicular (y-) to the direction of the fibers, and representative results are reported in Sanding with emery paper was carried out using four distinct grit sizes and the corresponding SEM images are compared in Surface roughness  are given in During each DCB test, a region of interest surrounding the advancing crack front was recorded with the aid of a high-resolution camera to track damage in the course of fracture. The key features of the crack propagation process extracted from the images are given in The images of the fracture surfaces reported in As shown in The schematic of The combined results pinpoint the high sensitivity of the tested material to surface preparation and that exposed fibers can significantly modify the mechanism of fracture. It is customary to attribute interlaminar fracture of composite joints to the weak resistance of laminates to peel stresses ,28. HoweWe have investigated the effects of mechanical treatments, such as sanding and grit-blasting, on the toughness of CFRP/epoxy joints. Using tailored sanding and grit-blasting treatments, we achieved a controllable level of fiber exposure across the interfaces of CFRP substrates. We identified model interfaces that displayed similar wettability but featured either light removal of the surface matrix or a significant number of exposed carbon fibers. Mechanical tests of double cantilever beam (DCB) adhesive joints revealed that surfaces mostly made of the polymer matrix provided a smooth fracture response and ensured fairly good crack propagation resistance. Besides, surface damage of CFRP and exposed fibers did not have a detrimental impact on joint resistance to crack propagation. Indeed, the associated fiber bridging promoted a beneficial R-curve behavior and a toughening effect. Remarkably, in all tests performed, the joint’s fracture toughness exceeded the interlaminar toughness of the monolithic CFRPs. In summary, this paper points out the significant effect of fiber bridging for toughening adhesively bonded joints. Our preliminary test results indicate that there is additional scope for future research opportunities. For instance, understanding how the surface of CFRPs can be engineered to ensure consistent fiber bridging levels across different tests and loading conditions would enable the fabrication of tough and damage-tolerant composite joints.


Prior studies demonstrate that Hill-type muscle parameters are encoded within dynamometric data. But, a generalizable approach for estimating these parameters from dynamometric data has not been realized. We aimed to leverage musculoskeletal models and artificial neural networks to classify one Hill-type muscle parameter (maximum isometric force) from easily measurable dynamometric data . We tested two neural networks (feedforward and long short-term memory) to identify if accounting for dynamic behavior improved accuracy.Hill-type muscle models are widely employed in simulations of human movement. Yet, the parameters underlying these models are difficult or impossible to measure We generated four datasets via forward dynamics, each with increasing complexity from adjustments to more muscles. Simulations were grouped and evaluated to show how varying the maximum isometric force of thumb muscles affects lateral pinch force. Both neural networks classified these groups from lateral pinch force alone.flexor pollicis longus and/or the abductor pollicis longus. The inclusion of muscles with redundant functions dropped model accuracies to below 30%. While both neural networks were consistently more accurate than random guess, the long short-term memory model was not consistently more accurate than the feedforward model.Both neural networks achieved accuracies above 80% for datasets which varied only the Our investigations demonstrate that artificial neural networks provide an inexpensive, data-driven approach for approximating Hill-type muscle-tendon parameters from easily measurable data. However, muscles of redundant function or of little impact to force production make parameter classification more challenging. Accurately simulating human movement requires the appropriate selection of muscle-tendon parameters. These parameters define the modeled muscle-tendon actuators that mathematically transform neural excitations into muscle forces, thereby enabling joint movement. Hill-type muscle models , 2 are tin vivo, and the need to estimate these parameters compromises musculoskeletal model accuracy. For example, generic parameter values are typically estimated from cadaveric specimens . Th. Th29]. flexor pollicis longus (FPL), abductor pollicis longus (APL), transverse head of the adductor pollicis (ADPt), and the oblique head of the adductor pollicis (ADPo)]. We selected these muscle actuators as they contribute substantially to lateral pinch thumb-tip force [in vivo and in vitro studies [2 [Each simulation varied the maximum isometric force input for thumb muscle actuators [the ip force . To prod studies –32. We eudies [2  and the udies [2 .To enable isolated variation of the maximum isometric force of thumb muscles, we used forward dynamics to simulate lateral pinch . Muscle We generated four datasets  to examiAll four simulation datasets were prepared to train and test both neural network models. To prevent neural network model bias favoring simulations of longer length, each simulation was interpolated to contain exactly 1000 time instances (i.e. 667 Hz). All simulations within a dataset were then grouped and labeled by whether the varied muscles were above (“high”) or below (“low”) the mean maximum isometric force values. This labeling reflects each neural network model’s task of predicting the maximum isomtric force of each muscle during lateral pinch. The modification of more muscles resulted in more labeled groups, and therefore 2, 4, 8, or 16 groupings of maximum isometric force value combinations in Datasets 1 through 4, respectively. To prevent neural network model bias, simulations were randomly assigned to training and testing sets; these sets defined the folds used during 5-fold cross validation.To inform how to predict maximum isometric force from minimal data, we employed feedforward and LSTM neural network models . For eacin vivo and directly impacted by the modifications to the maximum isometric force of muscles of the thumb. Each neural network employs a sigmoid activation function, an Adam learning rate optimizer [Both neural network models were similar in structure, containing 4 input nodes , 4 hidden nodes, and 2, 4, 8, or 16 output nodes (one “high” or one “low” node for each muscle) for Datasets 1 through 4, respectively. Three-component thumb-tip force vectors were selected as they are easily measurable ptimizer , and con−7 to 1 and selected the final learning rate via the criteria of minimizing losses [The learning rate has a substantial impact on neural network model performance; thus, we adjusted this value for the analysis of each dataset for both neural network models. During learning rate tuning, training terminated when either the losses did not decrease for 25 consecutive epochs or the network trained for 100 epochs. These termination criteria were selected to provide enough epochs for convergence of weights while halting neural network model training for those that were not converging. We tested learning rates between 10g losses . The finPredicting maximum isometric force from thumb-tip force is only feasible if this parameter considerably influences thumb-tip force. We therefore first examined how varying maximum isometric force of thumb muscle actuators affects thumb-tip force. For this analysis, we calculated the means and standard deviations of peak thumb-tip forces across all simulations within each labeled group. This provided mean distributions of force vectors in 3D space for each unique simulation scenario. Within each dataset, we then calculated the percent volume overlap between these distributions. No volume overlap indicates that the simulated values of maximum isometric force uniquely map to the produced thumb-tip forces, while high overlap indicates that this mapping is not unique. Thus, the thumb-tip force distributions and percent overlap reveal to what extent thumb-tip force is sensitive to alterations in the maximum isometric forces of thumb muscles. Furthermore, the overlap in thumb-tip force across labeled groups reveals possible sources of classification error for each neural network model.We also analyzed the distribution of test accuracies and losses associated with the final neural network models as evaluated via 5-fold cross-validation. For a well-performing model, accuracies should generally increase and losses should decrease across epochs until stabilizing at their final values. Training was terminated after 100 epochs, as the losses and accuracies were stable, indicating solution convergence. We calculated 95% confidence intervals for the test accuracies and losses for each neural network model across epochs. To test whether accounting for the dynamic behavior of the simulation increases neural network accuracy, we performed two-sample t-tests (p < 0.05) for each dataset to evaluate whether the average peak accuracies achieved by the feedforward and LSTM models were significantly different. The achieved accuracies and losses display the overall performance of each neural network model, whereas the relative performance of the neural network models is revealed via comparisons of their peak accuracies.The simulation datasets successfully characterized the relative contributions of each muscle to the production of thumb-tip force . Unique Feedforward neural network accuracy was substantially lower and less stable in datasets with variations to more muscles. The analyses of Dataset 1 and Dataset 2 showed losses to decrease across epochs  before cSimilar to the feedforward model, the LSTM model performance decreased substantially for datasets that adjusted more muscles. Analyses of simpler datasets produced lower losses than those of datasets which varied additional muscles . Losses Both neural network models achieved comparably high accuracies relative to random guess . The LSTLeveraging artificial neural networks and musculoskeletal models, we predicted changes in difficult-to-measure muscle parameters from minimal, measurable data. We specifically quantified feedforward and LSTM neural network performance in predicting the maximum isometric force of thumb muscles from simulated lateral pinch data. We report two key findings: 1. Under relatively simple conditions, neural network models can predict high and low maximum isometric force from lateral pinch data and 2. Accounting for long-term temporal dependencies in simulated lateral pinch data did not significantly improve neural network model performance. Although we did not predict explicit values of maximum isometric force in this study, accurately predicting changes in this parameter is a critical step that demonstrates the feasibility of using artificial neural networks to perform this task. With considerations for task complexity, dataset size, and Hill-type parameter of interest, the foundational work developed here could be expanded to define specific values of Hill-type parameters through categorization or regression.adductor pollicis. The ADPt and ADPo have been shown to contribute to similar directional components of lateral pinch thumb-tip force in cadaveric specimens [The observed decrement in model performance for datasets which varied more muscle actuators may be attributable to redundancies in actuator function. The ADPt and ADPo both adduct the thumb and represent two heads of the same muscle: the pecimens . We obseClassifying the maximum isometric force of multiple, interrelated muscles from thumb-tip force alone is challenging. The substantially higher accuracies and lower losses observed for Dataset 1 and Dataset 2 as compared to Dataset 3 and Dataset 4 may reflect a need for more diverse input variables. Datasets scaled substantially in complexity through the inclusion of changes to additional muscles. Neural network models used to classify parameters of redundant muscles may require additional types of biomechanical inputs. Artificial neural networks have been widely employed to map measured electromyographic, kinematic, and kinetic parameters . These qcurse of dimensionality, whereby high-dimensional models learn inadequately from too few observations in a large feature space [in vivo, this is an approximation. It is also important to note that the datasets we employed did not vary in posture, likely limiting the generalizability of the reported neural network models to new postures. In the present work, this constant posture across simulations enabled the isolated variation of the maximum isometric force. Understanding to what extent changes in behavior of dynamic thumb-tip force production is attributable to the maximum isometric force enhances our fundamental understanding of thumb biomechanics, and future work could focus on expanding these methods to evaluate the effects of other variables.Rather than use measured thumb-tip force, we simulated dynamic thumb-tip force to input into our machine learning framework. This approach had two advantages: it enabled the efficient generation of large datasets and enabled the isolated adjustment of the maximum isometric force of the muscles we investigated. Large datasets are necessary, as a common pitfall when applying machine learning to biomechanical datasets is the re space . Forwardre space  within ±The simple artificial neural network structures employed may have limited the performance achieved by each neural network model. Across each of the datasets analyzed, the feedforward and LSTM models maintained the same depth (1 layer) and width (4 hidden nodes). Maintaining the same architecture across feedforward and LSTM models enabled the fair comparison of their performance, regardless of model complexity. These models performed relatively well for Datasets 1 and 2, achieving accuracies above 96% and 80%, respectively. However, accuracies were below 30% for Dataset 4. Deeper structures may be more appropriate for complex datasets, as this would enable the model to discover more abstract features . EspeciaIn general, the LSTM model did not perform consistently better or worse than the feedforward model . NotablyOur investigations identified artificial neural networks as a tool for approximating underlying Hill-type muscle parameters from limited lateral pinch data. Furthermore, we proposed the employment of a simulation framework to assist in the production of large datasets from which the neural network model may learn. Although accuracies calculated for all datasets were well above random guess, datasets which included muscles with similar function compromised neural network performance. Future work should test whether including other easily measurable quantities assists the classification or regression of properties for muscles of redundant function. Additionally, these investigations revealed that feedforward models, as opposed to LSTM models, may be sufficient for classifying parameters for datasets that vary only slightly over time. These investigations inform a data-driven approach to classifying Hill-type muscle parameters.


Knowledge obtained at the undergraduate level regarding molar incisor hypomineralisation (MIH) has an impact on future practice of dentists and paediatric dentists. This cross-sectional study aimed to assess final-year dental students’ knowledge, attitudes and beliefs towards MIH in all Swiss universities.A previously utilised survey (in both English and German) was distributed among final-year dental students in all Swiss dental schools . It probed students’ knowledge, attitudes and beliefs regarding the diagnosis, prevalence, aetiology, and management of MIH, and was structured in two parts: knowledge/perception and clinical application. The students’ responses were analysed statistically with descriptive statistics.113 out of 133 final-year Swiss dental students took part in the study (85%). Nearly all students were familiar with MIH (99%), but only 12% of them felt confident when diagnosing MIH clinically. Direct composite fillings (66%), indirect restorations (28%) and preformed stainless-steel crowns (26%) were chosen as most suitable treatment options for MIH-affected teeth.Final-year Swiss dental students are well informed about MIH. However, they report low level of confidence when clinically confronted with MIH-affected teeth regarding its diagnosis and treatment. Swiss Universities curricula should be revisited accordingly. The term Molar-Incisor Hypomineralisation (MIH) was first suggested in 2001 by Weerheijm et al., to describe demarcated enamel lesions mainly encountered in the first permanent molars with frequent involvement of upper permanent incisors . All afoA handful of factors have been hypothesised to be at least partly responsible for the aetiology of MIH. These include, but are not limited to: genetic factors, exposure to environmental pollutants, common childhood illnesses, and birth complications . The preIt is safe to assume that the knowledge and experience acquired during the undergraduate level shapes the perception and behaviour of future dentists in dealing with clinical challenges.As MIH continues to pose a serious clinical challenge for both patients and dentists –10, it iThe current study is reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement . A prevird-year dental students  who were asked to re-take the survey after one month.The survey started with a brief description of MIH with clinical photos, followed by demographic questions about the participants and then by specific questions on MIH regarding its diagnosis, prevalence, students’ attitude and beliefs towards its management and educational need. A native German speaker translated the original English survey into German, which was then back translated into English by an independent English native speaker. To estimate the intra-rater reliability (κ = 0.78), the final survey was piloted among 3Following data extraction by a single author, data was analysed statistically with descriptive statistics, after checking the distribution of continuous outcomes graphically and with the Shapiro–Wilk test. Categorical variables were summarised with absolute/relative frequencies, while non-normally distributed continuous variables were summarised with medians and their Interquartile Range (IQR). All analyses were done in StataSE 13.0  and the anonymised dataset was openly available through Zenodo (10.5281/zenodo.5159386).All invited dental schools in Switzerland agreed to participate in the study. In total, 113/133 final-year dental students  answered and returned the survey. As this was an optional and anonymous survey, the students who did not participate (n = 20) and their reasons remain unclear. Participants were on average 25-year-old  and 61% of them (n = 69) were female. The geographic distribution of the participants according to their universities was as follows: Basel , Bern , Geneva  and Zurich .Table The most common MIH feature seen by the students were yellow/brown demarcations, followed by white demarcations and post-eruptive enamel breakdown. Only one-quarter of the students (26%) had encountered demarcated hypomineralised defects in permanent teeth other than the first permanent molars and incisors, mainly in premolars. More than two-thirds of the students (67%) had never seen MIH-similar lesions in primary second molars. The majority of the students (82%) held genetic factors responsible for the aetiology of MIH, followed by chronic diseases affecting the mother during pregnancy (46%), environmental contaminants (43%) and antibiotics/medications taken by the mother during pregnancy (38%).Regarding treatment options of MIH-affected teeth, 66% of the students believed direct resin composite to be a suitable treatment option, followed by indirect Computer-Aided Design and Computer-Aided Manufacturing (CAD/CAM) restorations (28%), and preformed stainless-steel crowns (26%). The main factors that influenced the students’ choice of treatment materials were adhesion (80%), durability (62%), and aesthetics (50%).The vast majority of students (95%) believed that MIH was a serious clinical problem, mostly regarding the possibility of achieving a long-term restoration success (61%) and diagnosis (58%). Eighty-nine percent of the students suggested including more clinical training on MIH-affected teeth in the curriculum, especially regarding treatment (87%), diagnosis (80%) and aetiology (41%).This is, to our knowledge, the first nationwide study to report on the knowledge, attitudes, and beliefs of final-year dental students toward MIH in Switzerland. The basic idea behind such studies is to report any knowledge gaps that need to be addressed during the undergraduate studies, where the fundamental competence and the know-how of future dentists is shaped. This study shows that Swiss final-year students are theoretically familiar with MIH, but lack the confidence when it comes to clinically diagnose and manage it. A statistical analysis to point out the differences between the four Swiss dental schools was deemed unnecessary. However, and for what it is worth, the answers of the students from all dental schools did not seem to be systematically different.The survey used in this study has been pre-validated and distributed among dental students and/or dentists in earlier studies –16.As thNinety-nine percent of Swiss students had heard of MIH during their undergraduate study. A similar percentage of students also reported themselves to be familiar with MIH in Germany (99%) . In SaudMost Swiss students predicted the prevalence of MIH in Switzerland to be between 0 and 25%, which is in accordance with the globally estimated pooled prevalence of MIH (13.1–14.2%) , 10. TwoRegarding the clinical management of MIH-affected teeth, direct composite filling was chosen as the most suitable treatment choice by most Swiss and German students . Preformed stainless-steel crowns were the fourth most preferable treatment choice in this study (26%), whereas more German students chose it as a treatment option . Differences in the preferred treatment options for MIH-affected teeth might also be associated with the differential insurance coverage of some dental procedures between the two countries.It is safe to assume—based on the present results—that undergraduate students in Switzerland need more clinical training regarding the clinical diagnosis and management of MIH. It could be interesting to distribute the same survey used in this study among well-experienced dentists to figure if post-graduate studies, continuous-education courses or even learn-by-doing in the praxis bring any further knowledge regarding MIH. Similar nationwide surveys in other parts of the globe could also shed light on different management approaches regarding MIH-affected teeth. This might initiate a beneficial academic exchange between dental schools. It could be argued that some questions in the survey could be modified in future surveys to obtain more specific answers. However, going into details in every aspect/question, might result in very long and tiring-to-fill surveys and significantly affect the number of participants.Based on the results of this study, knowledge, attitudes and beliefs of Swiss final-year dental students are in need of improvement. Swiss Universities’ curricula should be revisited to include more educational material about the diagnosis/management of MIH-affected teeth in order to increase the confidence of future dentists when confronted with such challenge.