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Artificial intelligence (AI) is concretely reshaping the landscape and horizons of oncology, opening new important opportunities for improving the management of cancer patients. Analysing the AI-based devices that have already obtained the official approval by the Federal Drug Administration (FDA), here we show that cancer diagnostics is the oncology-related area in which AI is already entered with the largest impact into clinical practice. Furthermore, breast, lung and prostate cancers represent the specific cancer types that now are experiencing more advantages from AI-based devices. The future perspectives of AI in oncology are discussed: the creation of multidisciplinary platforms, the comprehension of the importance of all neoplasms, including rare tumours and the continuous support for guaranteeing its growth represent in this time the most important challenges for finalising the ‘AI-revolution’ in oncology.

Intraductal papillary mucinous neoplasm (IPMN) of the pancreas is one of the most well-established precursors of pancreatic cancer. Its progression to acquire invasiveness is a complex process, based on the accumulation of morphological and genetic alterations. Recent advances in DNA sequencing also showed that co-occurring IPMNs and pancreatic cancers could be totally independent, further complicating our understanding of this complex scenario. The distinction between IPMN and related pancreatic cancer vs IPMN and co-occurring—but not related—pancreatic cancer is a challenging task in routine diagnostic activity, but may have important implications for precision oncology. Of note, recent multiregional sequencing-based studies focused not only on IPMN multi-step tumourigenesis, but also on the divergent intratumoural heterogeneity of this neoplasm. Globally considered, there are three different situations in which co-occurring IPMNs and invasive carcinomas can be found in the same pancreata, indicated with different terminologies: (1) IPMN-associated carcinoma: this definition indicates a carcinoma arising from an IPMN and can be also defined as IPMN-derived carcinoma, sequential or likely related; (2) independent IPMN and invasive carcinoma: the two lesions are not related, and this situation is defined as concomitant, de novo or likely independent; (3) branch-off pathway, where an invasive carcinoma and an adjacent IPMN develop divergently in a forked fashion from a common ancestral clone. In this review, we aim at clarifying the most important nomenclature/definitions of these different situations, also providing an overview of the molecular state-of-the-art and of the clinical implications of this complex landscape.

Overweight and obesity are some of the most important health challenges. Many diseases are related to these metabolic disorders, and, among them, the pancreatic fat accumulation, also called \"pancreatic steatosis\" or “nonalcoholic fatty pancreas”, seems to have an emerging role in different conditions. There are different method to evaluate the fat content in the pancreas, such as histology, different imaging techniques and endoscopic ultrasound, but there is no gold standard for the correct diagnosis and for the identification of “inter/intralobular” and “intra-acinar” pancreatic fat. However, the fat storage in the pancreas is linked to chronic inflammation and to several conditions, such as acute and chronic pancreatitis, type 2 diabetes mellitus and pancreatic cancer. In addition, pancreatic fat accumulation has also been demonstrated to play a role in surgical outcome after pancreatectomy, in particular for the development of postoperative pancreatic fistula. Different possible therapeutic approaches have been proposed, but there is still a lack of evidence. The aim of this review is to report the current evidence about the relationship between the obesity, the pancreatic fat accumulation and its potential role in pancreatic diseases.

The examination of small pancreatic biopsies is a difficult task for pathologists. This is due to the scant and fragmented material often obtained from diagnostic procedures as well as the significant overlap between different neoplastic and nonneoplastic entities. In the upcoming neoadjuvant era, biopsies could become even more important, representing the only possibility to look at the real histomorphology of tumors before chemotherapy-induced modifications. To summarize and discuss the state-of-the-art diagnostic workflow for small pancreatic biopsies, including the most important morphologic and immunohistochemical features and molecular alterations. The main diagnostic pearls and pitfalls of this challenging scenario are also discussed. The most important topics of this review are represented by: (1) pancreatic ductal adenocarcinoma, along with its main differential diagnoses, including autoimmune pancreatitis; (2) solid hypercellular neoplasms, including neuroendocrine neoplasms, acinar cell carcinoma, pancreatoblastoma, and solid pseudopapillary neoplasms; and (3) cystic lesions. Real-world considerations will also be presented and discussed. Sources included a literature review of published studies and the author's own work. The correct diagnosis of pancreatic lesions is a crucial step in the therapeutic journey of patients. It should be based on robust, standardized, and reliable hallmarks. As presented and discussed here, the integration of morphology with immunohistochemistry, and, in selected cases, with molecular analysis, represents a decisive step in this complex scenario.

Undifferentiated sarcomatoid carcinoma of the pancreas (SCP) is a rare and aggressive subtype of pancreatic cancer. Histologically, SCP is a poorly differentiated tumor characterized by the lack of glandular differentiation and the presence of mesenchymal-like, spindle-shaped tumor cells. Due to its rarity, only sporadic cases have been reported, while its molecular characterization has not been sufficiently described. Surgical resection with curative intent is the gold-standard of SCP management, but this strategy is possible only in a small proportion of cases due to SCP early metastasization. Although SCP is generally associated with a poor prognosis, some clinical cases amenable to surgical resection and followed by adjuvant chemotherapy have demonstrated a remarkably long survival. Preliminary molecular insights on the SCP molecular landscape have demonstrated the recurrent presence of KRAS and TP53 mutations, highlighting genetic similarities with conventional pancreatic ductal adenocarcinoma (PDAC). Although the use of immunotherapy in PDAC remains an unmet challenge, recent insights indicated a potentially significant role of the PD-L1/Notch3 axis in SCP, opening new horizons for immunotherapy in this cancer subtype. In this review, we described the most important clinic-pathologic features of SCP, with a specific focus on their molecular landscape and the potential targets for precision oncology.

Fibroblast heterogeneity is increasingly recognised across cancer conditions. Given their important contribution to disease progression, mapping fibroblasts’ heterogeneity is critical to devise effective anti-cancer therapies. Cancer-associated fibroblasts (CAFs) represent the most abundant cell population in pancreatic ductal adenocarcinoma (PDAC). Whether CAF phenotypes are differently specified by PDAC cell lineages remains to be elucidated. Here, we reveal an important role for the MAPK signalling pathway in defining PDAC CAF phenotypes. We show that epithelial MAPK activity promotes the myofibroblastic differentiation of CAFs by sustaining the expression and secretion of TGF-β1. We integrate single-cell profiling of post-perturbation transcriptional responses from mouse models with cellular and spatial profiles of human tissues to define a MAPK high CAF (mapCAF) phenotype. We show that this phenotype associates with basal-like tumour cells and reduced frequency of CD8 + T cells. In addition to elevated MAPK activity, this mapCAF phenotype is characterized by TGF-β signalling, hypoxia responsive signatures, and immunoregulatory gene programs. Furthermore, the mapCAF signature is enriched in myofibroblastic CAFs from various cancer conditions and correlates with reduced response to immune checkpoint inhibition in melanoma. Altogether, our data expand our knowledge on CAF phenotype heterogeneity and reveal a potential strategy for targeting myofibroblastic CAFs in vivo. Phenotypic and functional heterogeneity of cancer associated fibroblasts (CAFs) has been reported in pancreatic ductal adenocarcinoma (PDAC). Here the authors show that epithelial MAPK activity promotes myofibroblastic differentiation of CAFs. Furthermore, the epithelial basal-like subtype is associated with a CAF phenotype characterized by elevated MAPK activity and TGF-β signalling, associated with T cell exclusion in PDAC.

Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease, whose main molecular trait is the MAPK pathway activation due to KRAS mutation, which is present in 90% of cases. The genetic landscape of KRAS wild type PDAC can be divided into three categories. The first is represented by tumors with an activated MAPK pathway due to BRAF mutation that occur in up to 4% of cases. The second includes tumors with microsatellite instability (MSI) due to defective DNA mismatch repair (dMMR), which occurs in about 2% of cases, also featuring a high tumor mutational burden. The third category is represented by tumors with kinase fusion genes, which marks about 4% of cases. While therapeutic molecular targeting of KRAS is an unresolved challenge, KRAS -wild type PDACs have potential options for tailored treatments, including BRAF antagonists and MAPK inhibitors for the first group, immunotherapy with anti-PD-1/PD-L1 agents for the MSI/dMMR group, and kinase inhibitors for the third group. This calls for a complementation of the histological diagnosis of PDAC with a routine determination of KRAS followed by a comprehensive molecular profiling of KRAS -negative cases.

Microsatellite instability (MSI)/defective DNA mismatch repair (dMMR) is receiving more attention as a biomarker for eligibility for immune checkpoint inhibitors in advanced diseases. However, due to high costs and resource limitations, MSI/dMMR testing is not widely performed. Some attempts are in progress to predict MSI/dMMR status through histomorphological features on H&E slides using artificial intelligence (AI) technology. In this study, the potential predictive role of this new methodology was reviewed through a systematic review. Studies up to September 2021 were searched through PubMed and Embase database searches. The design and results of each study were summarized, and the risk of bias for each study was evaluated. For colorectal cancer, AI-based systems showed excellent performance with the highest standard of 0.972; for gastric and endometrial cancers they showed a relatively low but satisfactory performance, with the highest standard of 0.81 and 0.82, respectively. However, analyzing the risk of bias, most studies were evaluated at high-risk. AI-based systems showed a high potential in predicting the MSI/dMMR status of different cancer types, and particularly of colorectal cancers. Therefore, a confirmation test should be required only for the results that are positive in the AI test.

Histopathologically scoring the response of pancreatic ductal adenocarcinoma (PDAC) to neoadjuvant treatment can guide the selection of adjuvant therapy and improve prognostic stratification. However, several tumor response scoring (TRS) systems exist, and consensus is lacking as to which system represents best practice. An international consensus meeting on TRS took place in November 2019 in Amsterdam, The Netherlands. Here, we provide an overview of the outcomes and consensus statements that originated from this meeting. Consensus (≥80% agreement) was reached on a total of seven statements: (1) TRS is important because it provides information about the effect of neoadjuvant treatment that is not provided by other histopathology-based descriptors. (2) TRS for resected PDAC following neoadjuvant therapy should assess residual (viable) tumor burden instead of tumor regression. (3) The CAP scoring system is considered the most adequate scoring system to date because it is based on the presence and amount of residual cancer cells instead of tumor regression. (4) The defining criteria of the categories in the CAP scoring system should be improved by replacing subjective terms including “minimal” or “extensive” with objective criteria to evaluate the extent of viable tumor. (5) The improved, consensus-based system should be validated retrospectively and prospectively. (6) Prospective studies should determine the extent of tissue sampling that is required to ensure adequate assessment of the residual cancer burden, taking into account the heterogeneity of tumor response. (7) In future scientific publications, the extent of tissue sampling should be described in detail in the “Materials and methods” section.