Metavert synergises with standard cytotoxics in human PDAC organoids and is associated with transcriptomic signatures of therapeutic response.

BACKGROUND: Despite some recent advances, pancreatic ductal adenocarcinoma (PDAC) remains a growing oncological challenge. New drugs capable of targeting more than one oncogenic pathway may be one way to improve patient outcomes. This study characterizes the effectiveness of Metavert a first-in-class dual inhibitor of GSK3-ß and histone deacetylase in treating PDAC as a single agent or in combination with standard cytotoxics. METHODS: Thirty-six Patient-Derived Organoids (hPDOs) characterised by RNASeq and whole exome sequencing were treated with Metavert alone or in combination with standard cytotoxics. Transcriptomic signatures (TS) representing sensitivity to Metavert alone or sensitivity to Metavert + irinotecan (IR) were evaluated in 47 patient samples, chemo-naïve in 26 and post-chemotherapy in 21 (gemcitabine=5; FOLFIRINOX=14, both=2) with companion multiplexed immunofluorescence and RNASeq data. RESULTS: Metavert combined with gemcitabine, irinotecan, 5FU, oxaliplatin, and paclitaxel was synergistic in the hPDOs. Basal-subtype hPDOs were more sensitive to Metavert alone whereas the Metavert+IR combination exhibited synergy in Classical-subtype hPDOs with increased apoptosis and autophagy. hPDO-derived TS evaluated in PDAC tissues demonstrated that Metavert-TSHi samples were enriched for mRNA splicing and DNA repair processes; they were associated with Basal-like tissues but also with GATA6+ve-chemo-naïve samples and were higher following gemcitabine but not FOLFIRINOX treatment. In contrast, Metavert+IR-TSHI samples were enriched for TP53 pathways; they were associated with Classical-like pretreatment samples and with GATA6+ve/KRT17+ve hybrid cell types following FOLFIRINOX, but not gemcitabine treatment, and were unrelated to transcriptional subtypes. CONCLUSIONS: Metavert as a single agent and in combination with irinotecan offers novel strategies for treating pancreatic cancer.

Persister cell phenotypes contribute to poor patient outcomes after neoadjuvant chemotherapy in PDAC.

Neoadjuvant chemotherapy can improve the survival of individuals with borderline and unresectable pancreatic ductal adenocarcinoma; however, heterogeneous responses to chemotherapy remain a significant clinical challenge. Here, we performed RNA sequencing (n = 97) and multiplexed immunofluorescence (n = 122) on chemo-naive and postchemotherapy (post-CTX) resected patient samples (chemoradiotherapy excluded) to define the impact of neoadjuvant chemotherapy. Transcriptome analysis combined with high-resolution mapping of whole-tissue sections identified GATA6 (classical), KRT17 (basal-like) and cytochrome P450 3A (CYP3A) coexpressing cells that were preferentially enriched in post-CTX resected samples. The persistence of GATA6hi and KRT17hi cells post-CTX was significantly associated with poor survival after mFOLFIRINOX (mFFX), but not gemcitabine (GEM), treatment. Analysis of organoid models derived from chemo-naive and post-CTX samples demonstrated that CYP3A expression is a predictor of chemotherapy response and that CYP3A-expressing drug detoxification pathways can metabolize the prodrug irinotecan, a constituent of mFFX. These findings identify CYP3A-expressing drug-tolerant cell phenotypes in residual disease that may ultimately inform adjuvant treatment selection.

Refining the Treatment of Pancreatic Cancer From Big Data to Improved Individual Survival.

Pancreatic cancer is one of the most lethal cancers worldwide, most notably in Europe and North America. Great strides have been made in combining the most effective conventional therapies to improve survival at least in the short and medium term. The start of treatment can only be made once a diagnosis is made, which at this point, the tumor volume is already very high in the primary cancer and systemically. If caught at the earliest opportunity (in circa 20% patients) surgical resection of the primary followed by combination chemotherapy can achieve 5-year overall survival rates of 30%-50%. A delay in detection of even a few months after symptom onset will result in the tumor having only borderline resectabilty (in 20%-30% of patients), in which case the best survival is achieved by using short-course chemotherapy before tumor resection as well as adjuvant chemotherapy. Once metastases become visible (in 40%-60% of patients), cure is not possible, palliative cytotoxics only being able to prolong life by few months. Even in apparently successful therapy in resected and borderline resectable patients, the recurrence rate is very high. Considerable efforts to understand the nature of pancreatic cancer through large-scale genomics, transcriptomics, and digital profiling, combined with functional preclinical models, using genetically engineered mouse models and patient derived organoids, have identified the critical role of the tumor microenvironment in determining the nature of chemo- and immuno-resistance. This functional understanding has powered fresh and exciting approaches for the treatment of this cancer.

Corrigendum: Clinical impact of molecular subtyping of pancreatic cancer.

[This corrects the article DOI: 10.3389/fcell.2021.743908.].

Clinical Impact of Molecular Subtyping of Pancreatic Cancer.

Pancreatic ductal adenocarcinoma is a highly lethal malignancy, which has now become the seventh most common cause of cancer death in the world, with the highest mortality rates in Europe and North America. In the past 30 years, there has been some progress in 5-year survival (rates increasing from 2.5 to 10%), but this is still extremely poor compared to all other common cancer types. Targeted therapies for advanced pancreatic cancer based on actionable mutations have been disappointing, with only 3-5% showing even a short clinical benefit. There is, however, a molecular diversity beyond mutations in genes responsible for producing classical canonical signaling pathways. Pancreatic cancer is almost unique in promoting an excess production of other components of the stroma, resulting in a complex tumor microenvironment that contributes to tumor development, progression, and response to treatment. Various transcriptional subtypes have also been described. Most notably, there is a strong alignment between the Classical/Pancreatic progenitor and Quasi-mesenchymal/Basal-like/Squamous subtype signatures of Moffit, Collinson, Bailey, Puleo, and Chan-Seng-Yue, which have potential clinical impact. Sequencing of epithelial cell populations enriched by laser capture microscopy combined with single-cell RNA sequencing has revealed the potential genomic evolution of pancreatic cancer as being a consequence of a gene expression continuum from mixed Basal-like and Classical cell populations within the same tumor, linked to allelic imbalances in mutant KRAS, with metastatic tumors being more copy number-unstable compared to primary tumors. The Basal-like subtype appears more chemoresistant with reduced survival compared to the Classical subtype. Chemotherapy and/or chemoradiation will also enrich the Basal-like subtype. Squamous/Basal-like programs facilitate immune infiltration compared with the Classical-like programs. The immune infiltrates associated with Basal and Classical type cells are distinct, potentially opening the door to differential strategies. Single-cell and spatial transcriptomics will now allow single cell profiling of tumor and resident immune cell populations that may further advance subtyping. Multiple clinical trials have been launched based on transcriptomic response signatures and molecular subtyping including COMPASS, Precision Promise, ESPAC6/7, PREDICT-PACA, and PASS1. We review several approaches to explore the clinical relevance of molecular profiling to provide optimal bench-to-beside translation with clinical impact.

Highly Resolved Dynamic Emissions of Air Pollutants and Greenhouse Gas CO2 during COVID-19 Pandemic in East China.

The unintentional emission reductions caused by the COVID-19 pandemic provides an opportunity to investigate the impact of energy, industry, and transportation activities on air pollutants and CO2 emissions and their synergy. Here, we constructed an approach to estimate city-level high resolution dynamic emissions of both anthropogenic air pollutants and CO2 by introducing dynamic temporal allocation coefficients based on real-time multisource activity data. We first apply this approach to estimate the spatiotemporal evolution of sectoral emissions in eastern China, focusing on the period around the COVID-19 lockdown. Comparisons with observational data show that our approach can well capture the spatiotemporal changes of both short-lived precursors (NOx and NMVOCs) and CO2 emissions. Our results show that air pollutants (SO2, NOx, and NMVOCs) were reduced by up to 31%-53% during the lockdown period accompanied by simultaneous changes of 40% CO2 emissions. The declines in power and heavy industry sectors dominated regional SO2 and CO2 reductions. NOx reductions were mainly attributed to mobile sources, while NMVOCs emission reductions were mainly from light industry sectors. Our findings suggest that differentiated emission control strategies should be implemented for different source categories to achieve coordinated reduction goals.