Role of the fatty pancreatic infiltration in pancreatic oncogenesis.

Although pancreatic precancerous lesions are known to be related to obesity and fatty pancreatic infiltration, the mechanisms remain unclear. We assessed the role of fatty infiltration in the process of pancreatic oncogenesis and obesity. A combined transcriptomic, lipidomic and pathological approach was used to explore neoplastic transformations. Intralobular (ILF) and extralobular (ELF) lipidomic profiles were analyzed to search for lipids associated with pancreatic intraepithelial neoplasia (PanINs) and obesity; the effect of ILF and ELF on acinar tissue and the histopathological aspects of pancreatic parenchyma changes in obese (OB) and non-obese patients. This study showed that the lipid composition of ILF was different from that of ELF. ILF was related to obesity and ELF-specific lipids were correlated to PanINs. Acinar cells were shown to have different phenotypes depending on the presence and proximity to ILF in OB patients. Several lipid metabolic pathways, oxidative stress and inflammatory pathways were upregulated in acinar tissue during ILF infiltration in OB patients. Early acinar transformations, called acinar nodules (AN) were linked to obesity but not ELF or ILF suggesting that they are the first reversible precancerous pancreatic lesions to occur in OB patients. On the other hand, the number of PanINs was higher in OB patients and was positively correlated to ILF and ELF scores as well as to fibrosis. Our study suggests that two types of fat infiltration must be distinguished, ELF and ILF. ILF plays a major role in acinar modifications and the development of precancerous lesions associated with obesity, while ELF may play a role in the progression of PDAC.

Prospective observational study on biomarkers of response in pancreatic ductal adenocarcinoma.

Adjuvant chemotherapy benefits patients with resected pancreatic ductal adenocarcinoma (PDAC), but the compromised physical state of post-operative patients can hinder compliance. Biomarkers that identify candidates for prompt adjuvant therapy are needed. In this prospective observational study, 1,171 patients with PDAC who underwent pancreatectomy were enrolled and extensively followed-up. Proteomic profiling of 191 patient samples unveiled clinically relevant functional protein modules. A proteomics-level prognostic risk model was established for PDAC, with its utility further validated using a publicly available external cohort. More importantly, through an interaction effect regression analysis leveraging both clinical and proteomic datasets, we discovered two biomarkers (NDUFB8 and CEMIP2), indicative of the overall sensitivity of patients with PDAC to adjuvant chemotherapy. The biomarkers were validated through immunohistochemistry on an internal cohort of 386 patients. Rigorous validation extended to two external multicentic cohorts-a French multicentric cohort (230 patients) and a cohort from two grade-A tertiary hospitals in China (466 patients)-enhancing the robustness and generalizability of our findings. Moreover, experimental validation through functional assays was conducted on PDAC cell lines and patient-derived organoids. In summary, our cohort-scale integration of clinical and proteomic data demonstrates the potential of proteomics-guided prognosis and biomarker-aided adjuvant chemotherapy for PDAC.

Prediction of Adjuvant Gemcitabine Sensitivity in Resectable Pancreatic Adenocarcinoma Using the GemPred RNA Signature: An Ancillary Study of the PRODIGE-24/CCTG PA6 Clinical Trial.

PURPOSE: GemPred, a transcriptomic signature predictive of the efficacy of adjuvant gemcitabine (GEM), was developed from cell lines and organoids and validated retrospectively. The phase III PRODIGE-24/CCTG PA6 trial has demonstrated the superiority of modified folinic acid, fluorouracil, irinotecan, and oxaliplatin (mFOLFIRINOX) over GEM as adjuvant therapy in patients with resected pancreatic ductal adenocarcinoma at the expense of higher toxicity. We evaluated the potential predictive value of GemPred in this population. PATIENTS AND METHODS: Routine formalin-fixed paraffin-embedded surgical specimens of 350 patients were retrieved for RNA sequencing and GemPred prediction (167 in the GEM arm and 183 in the mFOLFIRINOX [mFFX] arm). Survival analyses were stratified by resection margins, lymph node status, and cancer antigen 19-9 level. RESULTS: Eighty-nine patients' tumors (25.5%) were GemPred+ and were thus predicted to be gemcitabine-sensitive. In the GEM arm, GemPred+ patients (n = 50, 30%) had a significantly longer disease-free survival (DFS) than GemPred- patients (n = 117, 70%; median 27.3 v 10.2 months, hazard ratio [HR], 0.43 [95% CI, 0.29 to 0.65]; P < .001) and cancer-specific survival (CSS; median 68.4 v 28.6 months, HR, 0.42 [95% CI, 0.27 to 0.66]; P < .001). GemPred had no prognostic value in the mFFX arm. DFS and CSS were similar in GemPred+ patients who received adjuvant GEM and mFFX (median 27.3 v 24.0 months, and 68.4 v 51.4 months, respectively). The statistical interaction between GEM and GemPred+ status was significant for DFS (P = .008) and CSS (P = .004). GemPred+ patients had significantly more adverse events of grade ≥3 in the mFFX arm (76%) compared with those in the GEM arm (40%; P = .001). CONCLUSION: This ancillary study of a phase III randomized trial demonstrates that among the quarter of patients with a GemPred-positive transcriptomic signature, survival was comparable with that of mFOLFIRINOX, whereas those receiving adjuvant gemcitabine had fewer adverse events.

Proteogenomic Characterization of Bladder Cancer Reveals Sensitivity to Apoptosis Induced by Tumor Necrosis Factor-related Apoptosis-inducing Ligand in FGFR3-mutated Tumors.

BACKGROUND: Molecular understanding of muscle-invasive (MIBC) and non-muscle-invasive (NMIBC) bladder cancer is currently based primarily on transcriptomic and genomic analyses. OBJECTIVE: To conduct proteogenomic analyses to gain insights into bladder cancer (BC) heterogeneity and identify underlying processes specific to tumor subgroups and therapeutic outcomes. DESIGN, SETTING, AND PARTICIPANTS: Proteomic data were obtained for 40 MIBC and 23 NMIBC cases for which transcriptomic and genomic data were already available. Four BC-derived cell lines harboring FGFR3 alterations were tested with interventions. INTERVENTION: Recombinant tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), second mitochondrial-derived activator of caspases mimetic (birinapant), pan-FGFR inhibitor (erdafitinib), and FGFR3 knockdown. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Proteomic groups from unsupervised analyses (uPGs) were characterized using clinicopathological, proteomic, genomic, transcriptomic, and pathway enrichment analyses. Additional enrichment analyses were performed for FGFR3-mutated tumors. Treatment effects on cell viability for FGFR3-altered cell lines were evaluated. Synergistic treatment effects were evaluated using the zero interaction potency model. RESULTS AND LIMITATIONS: Five uPGs, covering both NMIBC and MIBC, were identified and bore coarse-grained similarity to transcriptomic subtypes underlying common features of these different entities; uPG-E was associated with the Ta pathway and enriched in FGFR3 mutations. Our analyses also highlighted enrichment of proteins involved in apoptosis in FGFR3-mutated tumors, not captured through transcriptomics. Genetic and pharmacological inhibition demonstrated that FGFR3 activation regulates TRAIL receptor expression and sensitizes cells to TRAIL-mediated apoptosis, further increased by combination with birinapant. CONCLUSIONS: This proteogenomic study provides a comprehensive resource for investigating NMIBC and MIBC heterogeneity and highlights the potential of TRAIL-induced apoptosis as a treatment option for FGFR3-mutated bladder tumors, warranting a clinical investigation. PATIENT SUMMARY: We integrated proteomics, genomics, and transcriptomics to refine molecular classification of bladder cancer, which, combined with clinical and pathological classification, should lead to more appropriate management of patients. Moreover, we identified new biological processes altered in FGFR3-mutated tumors and showed that inducing apoptosis represents a new potential therapeutic option.

High-resolution and quantitative spatial analysis reveal intra-ductal phenotypic and functional diversification in pancreatic cancer.

A 'classical' and a 'basal-like' subtype of pancreatic cancer have been reported, with differential expression of GATA6 and different dosages of mutant KRAS. We established in situ detection of KRAS point mutations and mRNA panels for the consensus subtypes aiming to project these findings to paraffin-embedded clinical tumour samples for spatial quantitative analysis. We unveiled that, next to inter-patient and intra-patient inter-ductal heterogeneity, intraductal spatial phenotypes exist with anti-correlating expression levels of GATA6 and KRASG12D . The basal-like mRNA panel better captured the basal-like cell states than widely used protein markers. The panels corroborated the co-existence of the classical and basal-like cell states in a single tumour duct with functional diversification, i.e. proliferation and epithelial-to-mesenchymal transition respectively. Mutant KRASG12D detection ascertained an epithelial origin of vimentin-positive cells in the tumour. Uneven spatial distribution of cancer-associated fibroblasts could recreate similar intra-organoid diversification. This extensive heterogeneity with functional cooperation of plastic tumour cells poses extra challenges to therapeutic approaches. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Precision medicine for KRAS wild-type pancreatic adenocarcinomas.

BACKGROUND: KRAS mutation is the most common molecular alteration in pancreatic adenocarcinoma (PDAC), and around 10% of patients harbor KRAS wild-type tumors (KRASWT). METHODS: A retrospective chart review of clinical/molecular data was performed including all PDAC patients with a determined KRAS status (tumor molecular profiling on tissue or liquid biopsy). RESULTS: 342 patients were included with 54 KRASWT PDAC (16%) compared to 288 patients with KRASm PDAC. Median age was 61 years [IQR:54.0;67.0] and 164 pts (48%) were female. At diagnosis, KRASWT patients (63%) were more frequently diagnosed at a non-metastatic stage compared to KRASm patients (41%) (p = 0.003). Regarding metastatic sites, liver was less frequent in KRASWT (39%, p < 0.0001). Median overall survival (mOS) from initial diagnosis was significantly higher in the KRASWT group compared to KRASm (50.8 months, CI95% [32.0-NR] vs 21.1 months, CI95% [18.9-23.4] (p < 0.004 after adjustment on age, ECOG and stage at diagnosis). In first-line systemic treatment, (mostly FOLFIRINOX) progression-free survival (PFS) was also higher in KRASWT. Based on ESCAT classification, a putative actionable alteration (ESCAT I-III) was identified in 19 (36%) KRASWT pts and 46 (16%) KRASm patients (p < 0.0001) with more alterations in FGFR2, BRAF(V600E), NRTK and more MSI tumors. KRASWT harbored also fewer alterations in TP53, CDKN2A, and SMAD4. 12 KRASWT patients received a molecularly-matched treatment with clinical benefit and improved outcomes compared to KRASm patients. CONCLUSIONS: KRASWT patients display distinct disease characteristics and outcomes with prolonged overall survival. KRASWT patients also harbor more actionable molecular alterations, leading to higher survival rates after receiving molecularly matched treatments.

KRT17High/CXCL8+ tumor cells display both classical and basal features and regulate myeloid infiltration in the pancreatic cancer microenvironment.

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) is generally divided in two subtypes, classical and basal. Recently, single cell RNA sequencing has uncovered the co-existence of basal and classical cancer cells, as well as intermediary cancer cells, in individual tumors. The latter remains poorly understood; here, we sought to characterize them using a multimodal approach. EXPERIMENTAL DESIGN: We performed subtyping on a single cell RNA sequencing dataset containing 18 human PDAC samples to identify multiple intermediary subtypes. We generated patient-derived PDAC organoids for functional studies. We compared single cell profiling of matched blood and tumor samples to measure changes in the local and systemic immune microenvironment. We then leveraged longitudinally patient-matched blood to follow individual patients over the course of chemotherapy. RESULTS: We identified a cluster of KRT17-high intermediary cancer cells that uniquely express high levels of CXCL8 and other cytokines. The proportion of KRT17High/CXCL8+ cells in patient tumors correlated with intra-tumoral myeloid abundance, and, interestingly, high pro-tumor peripheral blood granulocytes, implicating local and systemic roles. Patient-derived organoids maintained KRT17High/CXCL8+cells and induced myeloid cell migration in an CXCL8-dependent manner. In our longitudinal studies, plasma CXCL8 decreased following chemotherapy in responsive patients, while CXCL8 persistence portended worse prognosis. CONCLUSIONS: Through single cell analysis of PDAC samples we identified KRT17High/CXCL8+ cancer cells as an intermediary subtype, marked by a unique cytokine profile and capable of influencing myeloid cells in the tumor microenvironment and systemically. The abundance of this cell population should be considered for patient stratification in precision immunotherapy.

The immunological landscape in pancreatic ductal adenocarcinoma and overcoming resistance to immunotherapy.

Pancreatic ductal adenocarcinoma is associated with a poor prognosis and there are few treatment options. The development of immunotherapy in pancreatic ductal adenocarcinoma has been difficult, and immune checkpoint inhibitors are only effective in a very small subset of patients. Most obstacles for treatment have been related to intertumoural and intratumoural heterogeneity, the composition of tumour stroma, and crosstalk with cancer cells. Improved molecular characterisation of pancreatic ductal adenocarcinoma and a better understanding of its microenvironment have paved the way for novel immunotherapy strategies, including the identification of predictive biomarkers, the development of rational combinations to optimise effectiveness, and the targeting of new mechanisms. Future immunotherapy strategies should consider individual characteristics to move beyond the traditional immune targets and circumvent the resistance to therapies that have been developed so far.

Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma.

Two tumor (Classical/Basal) and stroma (Inactive/active) subtypes of Pancreatic adenocarcinoma (PDAC) with prognostic and theragnostic implications have been described. These molecular subtypes were defined by RNAseq, a costly technique sensitive to sample quality and cellularity, not used in routine practice. To allow rapid PDAC molecular subtyping and study PDAC heterogeneity, we develop PACpAInt, a multi-step deep learning model. PACpAInt is trained on a multicentric cohort (n = 202) and validated on 4 independent cohorts including biopsies (surgical cohorts n = 148; 97; 126 / biopsy cohort n = 25), all with transcriptomic data (n = 598) to predict tumor tissue, tumor cells from stroma, and their transcriptomic molecular subtypes, either at the whole slide or tile level (112 µm squares). PACpAInt correctly predicts tumor subtypes at the whole slide level on surgical and biopsies specimens and independently predicts survival. PACpAInt highlights the presence of a minor aggressive Basal contingent that negatively impacts survival in 39% of RNA-defined classical cases. Tile-level analysis ( > 6 millions) redefines PDAC microheterogeneity showing codependencies in the distribution of tumor and stroma subtypes, and demonstrates that, in addition to the Classical and Basal tumors, there are Hybrid tumors that combine the latter subtypes, and Intermediate tumors that may represent a transition state during PDAC evolution.

Priming therapy by targeting enhancer-initiated pathways in patient-derived pancreatic cancer cells.

BACKGROUND: Systems biology leveraging multi-OMICs technologies, is rapidly advancing development of precision therapies and matching patients to targeted therapies, leading to improved responses. A new pillar of precision oncology lies in the power of chemogenomics to discover drugs that sensitizes malignant cells to other therapies. Here, we test a chemogenomic approach using epigenomic inhibitors (epidrugs) to reset patterns of gene expression driving the malignant behavior of pancreatic tumors. METHODS: We tested a targeted library of ten epidrugs targeting regulators of enhancers and super-enhancers on reprogramming gene expression networks in seventeen patient-derived primary pancreatic cancer cell cultures (PDPCCs), of both basal and classical subtypes. We subsequently evaluated the ability of these epidrugs to sensitize pancreatic cancer cells to five chemotherapeutic drugs that are clinically used for this malignancy. FINDINGS: To comprehend the impact of epidrug priming at the molecular level, we evaluated the effect of each epidrugs at the transcriptomic level of PDPCCs. The activating epidrugs showed a higher number of upregulated genes than the repressive epidrugs (χ2 test p-value <0.01). Furthermore, we developed a classifier using the baseline transcriptome of epidrug-primed-chemosensitized PDPCCs to predict the best epidrug-priming regime to a given chemotherapy. Six signatures with a significant association with the chemosensitization centroid (R ≤ -0.80; p-value < 0.01) were identified and validated in a subset of PDPCCs. INTERPRETATION: We conclude that targeting enhancer-initiated pathways in patient-derived primary cells, represents a promising approach for developing new therapies for human pancreatic cancer. FUNDING: This work was supported by INCa (Grants number 2018-078 to ND and 2018- 079 to JI), Canceropole PACA (ND), Amidex Foundation (ND), and INSERM (JI).

Intratumoral microbiome is driven by metastatic site and associated with immune histopathological parameters: An ancillary study of the SHIVA clinical trial.

BACKGROUND: Data on the role of the microbiota in cancer have accumulated in recent years, with particular interest in intratumoral bacteria. Previous results have shown that the composition of intratumoral microbiome is different depending on the type of primary tumour and that bacteria from the primary tumour could migrate to metastatic sites. METHODS: Seventy-nine patients with breast, lung, or colorectal cancer and available biopsy samples from lymph node, lung, or liver site, treated in the SHIVA01 trial were analysed. We performed bacterial 16S rRNA gene sequencing on these samples to characterise the intratumoral microbiome. We assessed the association between microbiome composition, clinicopathological characteristics, and outcomes. RESULTS: Microbial richness (Chao1 index), evenness (Shannon index) and beta-diversity (Bray Curtis distance) were associated with biopsy site (p = 0.0001, p = 0.03 and p < 0.0001, respectively) but not with primary tumour type (p = 0.52, p = 0.54 and p = 0.82, respectively). Furthermore, microbial richness was inversely associated with tumour-infiltrating lymphocytes (TILs, p = 0.02), and PD-L1 expression on immune cells (p = 0.03), or assessed by Tumor Proportion Score (TPS, p = 0.02) or Combined Positive Score (CPS, p = 0.04). Beta-diversity was also associated with these parameters (p < 0.05). Patients with lower intratumoral microbiome richness had shorter overall survival (p = 0.03) and progression-free survival (p = 0.02) in multivariate analysis. CONCLUSION: Biopsy site, rather than primary tumour type, was strongly associated with microbiome diversity. Immune histopathological parameters such as PD-L1 expression and TILs were significantly associated with alpha and beta-diversity supporting the cancer-microbiome-immune axis hypothesis.

Correction: Ponzo et al. Nucleolin Therapeutic Targeting Decreases Pancreatic Cancer Immunosuppression. Cancers 2022, 14, 4265.

In the original publication [...].

Nucleolin Therapeutic Targeting Decreases Pancreatic Cancer Immunosuppression.

Background: The pancreatic ductal adenocarcinoma (PDAC) microenvironment is highly fibrotic and hypoxic, with poor immune cell infiltration. Recently, we showed that nucleolin (NCL) inhibition normalizes tumour vessels and impairs PDAC growth. Methods: Immunocompetent mouse models of PDAC were treated by the pseudopeptide N6L, which selectively inhibits NCL. Tumour-infiltrating immune cells and changes in the tumour microenvironment were analysed. Results: N6L reduced the proportion of regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) and increased tumour-infiltrated T lymphocytes (TILs) with an activated phenotype. Low-dose anti-VEGFR2 treatment normalized PDAC vessels but did not modulate the immune suppressive microenvironment. RNAseq analysis of N6L-treated PDAC tumours revealed a reduction of cancer-associated fibroblast (CAF) expansion in vivo and in vitro. Notably, N6L treatment decreased IL-6 levels both in tumour tissues and in serum. Treating mPDAC by an antibody blocking IL-6 reduced the proportion of Tregs and MDSCs and increased the amount of TILs, thus mimicking the effects of N6L. Conclusions: These results demonstrate that NCL inhibition blocks the amplification of lymphoid and myeloid immunosuppressive cells and promotes T cell activation in PDAC through a new mechanism of action dependent on the direct inhibition of the tumoral stroma.

Periostin- and podoplanin-positive cancer-associated fibroblast subtypes cooperate to shape the inflamed tumor microenvironment in aggressive pancreatic adenocarcinoma.

Cancer-associated fibroblasts (CAFs) are orchestrators of the pancreatic ductal adenocarcinoma (PDAC) microenvironment. Previously we described four CAF subtypes with specific molecular and functional features. Here, we have refined our CAF subtype signatures using RNAseq and immunostaining with the goal of defining bioinformatically the phenotypic stromal and tumor epithelial states associated with CAF diversity. We used primary CAF cultures grown from patient PDAC tumors, human data sets (in-house and public, including single-cell analyses), genetically engineered mouse PDAC tissues, and patient-derived xenografts (PDX) grown in mice. We found that CAF subtype RNAseq signatures correlated with immunostaining. Tumors rich in periostin-positive CAFs were significantly associated with shorter overall survival of patients. Periostin-positive CAFs were characterized by high proliferation and protein synthesis rates and low α-smooth muscle actin expression and were found in peri-/pre-tumoral areas. They were associated with highly cellular tumors and with macrophage infiltrates. Podoplanin-positive CAFs were associated with immune-related signatures and recruitment of dendritic cells. Importantly, we showed that the combination of periostin-positive CAFs and podoplanin-positive CAFs was associated with specific tumor microenvironment features in terms of stromal abundance and immune cell infiltrates. Podoplanin-positive CAFs identified an inflammatory CAF (iCAF)-like subset, whereas periostin-positive CAFs were not correlated with the published myofibroblastic CAF (myCAF)/iCAF classification. Taken together, these results suggest that a periostin-positive CAF is an early, activated CAF, associated with aggressive tumors, whereas a podoplanin-positive CAF is associated with an immune-related phenotype. These two subpopulations cooperate to define specific tumor microenvironment and patient prognosis and are of putative interest for future therapeutic stratification of patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Therapeutic advances in metastatic pancreatic cancer: a focus on targeted therapies.

Mortality from pancreatic ductal adenocarcinoma (PDAC) is increasing worldwide and effective new treatments are urgently needed. The current treatment of metastatic PDAC in fit patients is based on two chemotherapy combinations (FOLFIRINOX and gemcitabine plus nab-paclitaxel) which were validated more than 8 years ago. Although almost all treatments targeting specific molecular alterations have failed so far when administered to unselected patients, encouraging results were observed in the small subpopulations of patients with germline BRCA 1/2 mutations, and somatic gene fusions (neurotrophic tyrosine receptor kinase, Neuregulin 1, which are enriched in KRAS wild-type PDAC), KRAS G12C mutations, or microsatellite instability. While targeted tumor metabolism therapies and immunotherapy have been disappointing, they are still under investigation in combination with other drugs. Optimizing pharmacokinetics and adapting available chemotherapies based on molecular signatures are other promising avenues of research. This review evaluates the current expectations and limits of available treatments and analyses the existing trials. A permanent search for actionable vulnerabilities in PDAC tumor cells and microenvironments will probably result in a more personalized therapeutic approach, keeping in mind that supportive care must also play a major role if real clinical efficacy is to be achieved in these patients.

Multi-omics data integration and modeling unravels new mechanisms for pancreatic cancer and improves prognostic prediction.

Pancreatic ductal adenocarcinoma (PDAC), has recently been found to be a heterogeneous disease, although the extension of its diversity remains to be fully understood. Here, we harmonize transcriptomic profiles derived from both PDAC epithelial and microenvironment cells to develop a Master Regulators (MR)-Gradient model that allows important inferences on transcriptional networks, epigenomic states, and metabolomics pathways that underlies this disease heterogeneity. This gradient model was generated by applying a blind source separation based on independent components analysis and robust principal component analyses (RPCA), following regulatory network inference. The result of these analyses reveals that PDAC prognosis strongly associates with the tumor epithelial cell phenotype and the immunological component. These studies were complemented by integration of methylome and metabolome datasets generated from patient-derived xenograft (PDX), together experimental measurements of metabolites, immunofluorescence microscopy, and western blot. At the metabolic level, PDAC favorable phenotype showed a positive correlation with enzymes implicated in complex lipid biosynthesis. In contrast, the unfavorable phenotype displayed an augmented OXPHOS independent metabolism centered on the Warburg effect and glutaminolysis. Epigenetically, we find that a global hypermethylation profile associates with the worst prognosis. Lastly, we report that, two antagonistic histone code writers, SUV39H1/SUV39H2 (H3K9Me3) and KAT2B (H3K9Ac) were identified key deregulated pathways in PDAC. Our analysis suggests that the PDAC phenotype, as it relates to prognosis, is determined by a complex interaction of transcriptomic, epigenomic, and metabolic features. Furthermore, we demonstrated that PDAC prognosis could be modulated through epigenetics.

Whole-Transcriptome Profiling on Small FFPE Samples: Which Sequencing Kit Should Be Used?

RNA sequencing (RNA-Seq) appears as a great tool with huge clinical potential, particularly in oncology. However, sufficient sample size is often a limiting factor and the vast majority of samples from patients with cancer are formalin-fixed paraffin-embedded (FFPE). To date, several sequencing kits are proposed for FFPE samples yet no comparison on low quantities were performed. To select the most reliable, cost-effective, and relevant RNA-Seq approach, we applied five FFPE-compatible kits (based on 3' capture, exome-capture and ribodepletion approaches) using 8 ng to 400 ng of FFPE-derived RNA and compared them to Nanostring on FFPE samples and to a reference PolyA (Truseq) approach on flash-frozen samples of the same tumors. We compared gene expression correlations and reproducibility. The Smarter Pico V3 ribodepletion approach appeared systematically the most comparable to Nanostring and Truseq (p < 0.001) and was a highly reproducible technique. In comparison with exome-capture and 3' kits, the Smarter appeared more comparable to Truseq (p < 0.001). Overall, our results suggest that the Smarter is the most robust RNA-Seq technique to study small FFPE samples and 3' Lexogen presents an interesting quality−price ratio for samples with less limiting quantities.

Molecular deciphering of primary liver neuroendocrine neoplasms confirms their distinct existence with foregut-like profile.

Isolated hepatic localizations of neuroendocrine tumors (NETs) are generally considered as metastatic NETs of unknown primary but could correspond to primary hepatic NETs (PHNETs), a poorly explored entity. We aimed to describe the clinicopathological and molecular features of PHNETs and compare them with other primary NETs. We assembled a retrospective cohort of patients managed for hepatic localization of NET without extra-hepatic primary tumor after exhaustive clinical, imaging, and immunohistochemical characterization. We performed whole-exome sequencing with mutational and copy number analysis. Transcriptomic profiles were compared with pancreatic (n = 31), small-bowel (n = 22), and lung (n = 15) NETs using principal component analysis, unsupervised clustering, and gene set enrichment analysis. Among 27 screened patients, 16 had PHNET (solitary tumor in 63%, median size 11 cm, G2 NETs in 81%) following clinical and pathological review. DNA analyses showed 'foregut-like' genomic profiles with frequent alterations in pathways of Fanconi DNA repair (75%), histone modifiers (58%), adherens junctions (58%), and cell cycle control (50%). The most frequently involved genes were KMT2A (58%), ATM (42%), CDH1, CDKN2C, FANCF, and MEN1 (33% each). Transcriptomic analyses showed that PHNETs clustered closer to foregut (pancreatic, lung) NETs than to midgut (small-bowel) NETs, while remaining a distinct entity with a specific profile. Assessment of potentially predictive biomarkers suggested efficacy of treatments usually active in foregut NETs. In conclusion, PHNETs display a foregut-like molecular profile distinct from other types of NETs, with recurrent molecular alterations. Upon exhaustive work-up to exclude an unrecognized primary tumor, PHNETs should not be considered metastatic NETs from an unknown primary. © 2022 The Pathological Society of Great Britain and Ireland.

Immunophenotypic and molecular characterization of pancreatic neuroendocrine tumors producing serotonin.

Serotonin producing pancreatic neuroendocrine tumors (SP-PanNET) account for 0.58-1.4% of all pancreatic neuroendocrine tumors (PanNET). They may present with atypical symptoms, such as acute pancreatitis and are often radiologically characterized by main pancreatic duct dilatation. SP-PanNET are well differentiated neuroendocrine tumors (NET) distinct from classical PanNET by atypical serotonin secretion and abundant dense stroma deposition, like serotonin producing ileal NET leading in some cases to difficulties to reliably distinguish SP-PanNET from ileal NET metastases. The biology and molecular profile of SP-PanNET remain poorly characterized and the cell of origin within the pancreas is unclear. To address these questions, we analyzed a large cohort of SP-PanNET by immunohistochemistry (n = 29; ATRX, DAXX, MENIN, Islet1, PAX6, PDX1, ARX, CDX2), whole genome copy number array (Oncoscan™) and a large NGS panel (NovoPM™) (n = 10), FISH (n = 13) and RNA sequencing (n = 24) together with 21 ileal NET and 29 nonfunctioning PanNET (NF-PanNET). These analyses revealed a unique genomic profile with frequent isolated loss of chromosome 1 (14 cases-61%) and few pathogenic mutations (KMT2C in 2 cases, ARID1A in 1 case). Unsupervised RNAseq-based clustering showed that SP-PanNET were closer to NF-PanNET than ileal NET with an exclusive beta cell-like signature. SP-PanNET showed TGF-ß pathway activation signatures associated with extracellular matrix remodeling and similar signature were reproduced in vitro when pancreatic stellate cells were exposed to serotonin. SP-PanNET immunohistochemical profile resemble that of ileal NET except for PDX1 and PAX6 expression to a lesser extend suggesting that these two markers may be useful to diagnose SP-PanNET. Taken together, this suggests that SP-PanNET are a very specific PanNET entity with a peculiar biology leading to the characteristic fibrotic aspect.

DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification.

BACKGROUND: Quantification of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specificities. Bioinformatic tools to assess the different cell populations from single-omic datasets as bulk transcriptome or methylome samples have been recently developed, including reference-based and reference-free methods. Improved methods using multi-omic datasets are yet to be developed in the future and the community would need systematic tools to perform a comparative evaluation of these algorithms on controlled data. RESULTS: We present DECONbench, a standardized unbiased benchmarking resource, applied to the evaluation of computational methods quantifying cell-type heterogeneity in cancer. DECONbench includes gold standard simulated benchmark datasets, consisting of transcriptome and methylome profiles mimicking pancreatic adenocarcinoma molecular heterogeneity, and a set of baseline deconvolution methods (reference-free algorithms inferring cell-type proportions). DECONbench performs a systematic performance evaluation of each new methodological contribution and provides the possibility to publicly share source code and scoring. CONCLUSION: DECONbench allows continuous submission of new methods in a user-friendly fashion, each novel contribution being automatically compared to the reference baseline methods, which enables crowdsourced benchmarking. DECONbench is designed to serve as a reference platform for the benchmarking of deconvolution methods in the evaluation of cancer heterogeneity. We believe it will contribute to leverage the benchmarking practices in the biomedical and life science communities. DECONbench is hosted on the open source Codalab competition platform. It is freely available at: https://competitions.codalab.org/competitions/27453 .