Despite significant progress regarding our knowledge of cancer biology, cancer remains a leading cause of death worldwide. In the European Union (EU-27), according to recent data (22 July 2020) released from the European Cancer Information System (ECIS), cancer burden has risen to 2.7 million new cases (all types, excluding non-melanoma skin cancer) with 1.3 million deaths in 2020 [1]. The above also records that pancreatic cancer (PC) is the seventh most common cancer for both sexes, with an incidence of approximately 3.5%, and the fourth most common cause of cancer related death for both sexes and all ages (with an estimated percentage of 7.1%) while it rises to the third place among individuals over the age of 65. Pancreatic ductal adenocarcinoma (PDAC) represents the 85% of all cases of pancreatic cancer [2]. Smoking, even after cessation, diabetes mellitus, obesity, age, and genetic predisposition are the main risk factors identified so far to be implicated in the development of PDAC ^[3][4][5][6][3,4,5,6]. Despite constant efforts to develop novel diagnostic tools and treatment approaches, it is estimated that PDAC will rise to the second most common cause of cancer death by 2030 ^[6][7][6,7]. The prognosis for PDAC patients remains unfavorable, with a 5-year overall survival rate of less than 5% [8]. Surgical resection followed by adjuvant therapy is the only therapeutic option; however, less than 15% of patients present local and potentially operable disease, while it is well known that operability and survival are better in patients with smaller lesions [9]. Patients with advanced disease at presentation or recurrence may receive palliative chemotherapy, although the rates of response and overall benefit are modest. The aggressive nature of PDAC and primary or secondary drug resistance [10] contribute significantly to this dismal prognosis. It has become evident that PDAC has a genetic component, with several relevant mutations, while its progression is characterized by high heterogeneity ^[11][12][13][11,12,13]. KRAS, TP53, CDKN2A, and SMAD4 have been identified as recurrently mutated genes in pancreatic cancer [14]. Pancreatic cancer progression and resistance are complex processes involving multiple mechanisms, including genetic and epigenetic alterations, tumor microenvironment, metabolic reprogramming, immune evasion, and tumor heterogeneity. Recent studies have shown that several protein kinases, like cyclin-dependent kinase 1 (CDK1) ^{[15][16][17][18]}[15,16,17,18], play a significant role in pancreatic cancer resistance by modifying proteins involved in key signaling pathways. These modifications can lead to the activation of cellular processes that promote cancer cell growth, survival, and resistance to chemotherapy.

Due to the reasons stated above, the scientific community is focusing on prevention, by identifying and minimizing environmental risk factors, and of course on early diagnosis, which holds the promise of improved outcomes. Chemotherapy remains the cornerstone for PC management along with tumor resection, radiotherapy, and more recently immunotherapy. However, chemotherapy is severely restricted by multiple constraints, such as severe side effects and toxicity leading to non-compliance with prolonged treatment, drug resistance, incomplete cure, and low patient quality of life. Thus, there is an urgent need to develop novel and more effective therapies capable of improving PC patients’ survival rates.

To overcome these constraints and improve the overall outcome of chemotherapy, one of the major advances in cancer treatment focuses on the application of more personalized approaches. Personalized or precision medicine is a rapidly evolving approach that allows clinicians to select treatments that carry the potential to greatly improve both treatment effectiveness as well as patients’ quality of life. Precision medicine (which is the preferred term nowadays, for more details over the debate see [19]) is the result of many years of research on tumor biology that has led scientists to understand that individual differences in genetics, lifestyle, and environment will influence the way cancer patients respond to treatment.

2. Tumor Organoids in Precision Medicine for PDAC

The first work of anticancer drug testing using tumoroids took place at Muthuswamy’s lab ^[20][45]. The first test they did was to analyze the response of tumoroids from five independent patient tumors to the standard drug for PDAC, gemcitabine. According to their report, all organoid tests showed a poor response to the drug, with an average growth inhibition of 30%. Unfortunately, they did not correlate the responses of these “personalized” organoids with that of the patients, as all patients had undergone surgery and were disease-free at the time of the study. The group proceeded to use the same five personalized organoids in a drug-screening approach to test five different epigenetic inhibitors. In a well-designed experiment, they first tested these inhibitors against non-tumor pancreatic organoids for toxicity, and the two least toxic were further tested against the tumoroids as a monotherapy or in combination with gemcitabine. Through this approach, they identified at least one inhibitor that resulted in a dose-dependent decrease in the proliferation rate of four out of the five tumoroids when combined with gemcitabine. The most active inhibitor was found to be the UNC1999, an inhibitor of EZH2 [a ‘writer’ of trimethylation of histone H3 at Lys27 (H3K27me3)]. Interestingly, all sensitive tumoroids, as well as the matching tumors and non-tumor organoids, were positive for the H3K27me3 mark, suggesting a strong correlation between the organoids and the primary tumor. It would have been of great interest to see how these studies would correlate with in vivo studies in NSG xenografts developed with the use of these organoids, but the group did not perform these experiments. Authors also report that tumor organoids retained patient-specific traits, such as repressive epigenetic marks, oxygen consumption, and EZH2 dependence, observations that underline the usefulness of their system for further drug screening. Walsh et al. ^[21][46] also used the organoids they developed to test their response in gemcitabine and AZD1480 (a novel ATP-competitive JAK2 inhibitor) alone or in combination. Organoids were treated for 24 h with gemcitabine, AZD1480, and their combination. As they report, while a significant reduction in the OMI index (optical metabolic imaging, used to evaluate the effect on organoids proliferation) was detected with gemcitabine and their combination, AZD1480 alone failed to induce a significant reduction. Additionally, the authors did not report any correlation between patients’ treatment and response. In this direction, Tiriac et al. attempted to correlate tumor organoid drug response to patients’ clinical outcomes. They developed a cohort of 66 PDAC patient-derived organoids and established a drug testing platform, suggesting that drug testing in PDO cultures could be used for treatment selection in patients within a clinically relevant timeframe. The organoid response to drug testing, termed pharmacotyping, was performed on PDOs treated with 5 common clinically used chemotherapeutic agents: gemcitabine, nab-paclitaxel, irinotecan (SN-38), 5-fluorouracil (5-FU) and oxaliplatin. The authors collected retrospective clinical follow-up from 9 patients and reported that eight out of nine (89%) organoids responded similarly to the corresponding patients. More specifically, 6 patients treated with at least one drug to which PDOs were found to be sensitive showed an improved progression-free survival (PFS), whereas two out of three patients treated with a drug to which the corresponding PDOs were resistant rapidly progressed. Authors suggested that the PDOs’ response to drug screening parallels patients’ sensitivity profiles to chemotherapy ^[22][51]. The authors further evaluated the efficacy of other targeted agents as potential anticancer drugs for PDAC using these PDOs. Targeted agents like selumetinib (MEK inhibitor), afatinib, everolimus, and LY2874455 (fibroblast growth factor receptor inhibitor) were tested. Authors found that PDOs harboring ERBB2 amplifications and EGFR mutations were sensitive to the tyrosine kinase inhibitor afatinib, whereas a PDO carrying an oncogenic PIK3CA allele was sensitive to the mTOR agent everolimus. A similar correlation between clinical response and gemcitabine sensitivity was reported by Driehuis et al. ^[23][52]. The authors exposed 24 established pancreatic PDOs to an extensive drug screening with 76 chemotherapeutic agents aiming to assess PDOs’ drug sensitivity and correlate it to the patients’ clinical outcomes. However, clinical data were available only for 4 patients and all of them were treated with gemcitabine. Authors reported that one patient, with the corresponding PDO being resistant to gemcitabine, developed distant metastasis during treatment, while another patient with a PDO sensitive to gemcitabine had stable disease and a decrease in liver metastasis after gemcitabine treatment. The corresponding PDOs from the two other patients showed an intermediate response in the in vitro assays, and in accordance with this finding, the two patients showed stable disease during gemcitabine treatment. Based on these findings, authors suggest that the in vitro sensitivity of the PDOs to gemcitabine correlates to patients’ clinical response. However, it should be noted that the patients’ cohort and the number of corresponding PDOs in this study were relatively small ^[23][52]. In the same study, authors used PDOs to evaluate the potential of a new targeted agent, EZP01556, as an anticancer agent. This inhibitor specifically targets the arginine methyltransferase 5 (PRMT5) protein. PRMT5 is reported as a synthetic lethal gene in methylthioadenosine phosphorylase deficient (MTAP⁻) cells ^[24][53]. In their study, Romero-Calvo et al. ^[25][22] reported the testing of organoids for dosage-dependent and drug-specific responses. They studied the response of organoids from two patients to gemcitabine and a combination of gemcitabine and abraxane. The authors reported a dose-response relationship to gemcitabine in both cases; however, this did not reflect the patients’ clinical outcome, as both patients were unresponsive to gemcitabine. Organoids from one patient were also tested with a combination of gemcitabine plus abraxane and showed a very good response consistent with the corresponding PDX. Nevertheless, this could not be correlated with clinical data since this patient did not receive this regimen. However, the key finding of the study is the isolation of two clones from the organoids, which underline the potential of these models to provide valuable information about clonal populations. Another study from Seppälä et al. ^[26][54] aimed to determine whether the PDOs’ pharmacotyping could guide the patients’ postoperative chemotherapeutic selection within a clinically relevant time frame. Authors first studied PDOs’ drug sensitivity in early-, as compared to late-passage organoids derived from the same primary tumor. Interestingly, they found that the established clones showed a similar pharmacotyping profile, which was consistent across over a dozen of samples (7–89 days between passages). Since they confirmed the PDOs’ pharmacotyping stability, authors reported the days in culture before pharmacotyping for 13 PDOs and found that they managed to complete the drug screening within a range of 18–102 days (median 48 days). Considering the median time between surgery and the initiation of chemotherapy, which was 62 days, authors suggest that rapid PDOs’ pharmacotyping could be a feasible strategy with clinical relevance in PDAC treatment. However, once again in this study, authors did not report any correlation between patients’ response and outcome ^[26][54]. In another study, Farshadi et al. ^[27][55] developed 5 PDOs from pancreatic cancer patients who has undergone eight cycles of the FOLFIRINOX regimen and 5 PDOs from treatment-naive patients. The authors studied the PDOs’ drug response to oxaliplatin, 5-FU, and SN38 as monotherapies. The results suggest that the clinical drug response for three out of five treatment-naive patients, who received FOLFIRINOX treatment, mirrored the in vitro drug sensitivity of their corresponding PDOs. Interestingly, one out of five FOLFIRINOX-treated PDOs showed higher sensitivity to oxaliplatin in vitro compared to the others, and computerized tomography of this patient’s tumor showed that this was the only patient with a partial response (PR) to FOLFIRINOX. Congruently, one out of five treatment-naive PDOs showed less sensitivity to different concentrations of FOLFIRINOX in vitro, mirroring the observed clinical resistance of this patient to adjuvant FOLFIRINOX. However, these results have been observed in a very small number of patients to draw definite conclusions and must be validated in a larger cohort. In a more recent study, Grossman et al. ^[28][56] established 12 PDOs suitable for drug testing from 12 patients with pancreatic cancer enrolled in the study. PDOs sensitivities to various drugs such as gemcitabine, 5-FU, oxaliplatin, SN-38, and paclitaxel were tested. The drugs tested in each PDO were selected according to the treatments each patient received or was likely to receive. Researchers calculated the area under the curve (AUC) for each drug on each PDO as an index for the clinical response prediction, and they observed a high degree of correlation between clinical and PDO responses. For example, in one patient, the developed PDO showed the highest degree of sensitivity to irinotecan, followed by trametinib, and in accordance with this finding, the patient from whom this PDO was derived showed stable disease (SD) on the agent FOLFIRINOX (contains irinotecan) and partial response (PR) on trametinib/lapatinib, suggesting that the AUC values calculated from the PDOs could provide useful insights into the clinical responses to treatment ^[28][56].