High-dimensional deconstruction of pancreatic cancer identifies tumor microenvironmental and developmental stemness features that predict survival

High-dimensional deconstruction of HNSC reveals clinically distinct cellular states and ecosystems that are associated with prognosis and therapy response

BACKGROUND

Characterizing the variety of cell types in the tumor microenvironment (TME) and their organization into cellular communities is vital for elucidating the biological diversity of cancer and informing therapeutic strategies.

METHODS

Here, we employed a machine learning-based algorithm framework, EcoTyper, to analyze single-cell transcriptomes from 139 patients with head and neck squamous cell carcinoma (HNSC)and gene expression profiles from 983 additional HNSC patients, aiming to delineate the fundamental cell states and ecosystems integral to HNSC.

RESULTS

A diverse landscape of 66 cell states and 9 ecosystems within the HNSC microenvironment was identified, revealing classical cell types while also expanding upon previous immune classifications. Survival analysis revealed that specific cell states and ecotypes (ecosystems) are associated with patient prognosis, underscoring their potential as indicators of clinical outcomes. Moreover, distinct cell states and ecotypes exhibited varying responses to immunotherapy and chemotherapy, with several showing promise as predictive biomarkers for treatment efficacy.

CONCLUSION

Our large-scale integrative transcriptome analysis provides high-resolution insights into the cellular states and ecosystems of HNSC, facilitating the discovery of novel biomarkers and supporting the development of precision therapies.

Single-cell transcriptomics analysis reveals dynamic changes and prognostic signature in tumor microenvironment of PDAC

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignant tumor characterized by a complex tumor microenvironment (TME) with significant heterogeneity, posing immense challenges for devising effective therapeutic strategies. This study aims to elucidate the dynamic changes in the TME during PDAC progression and develop a prognostic model using single-cell RNA sequencing (scRNA-seq) data. We utilized a previously published comprehensive dataset comprising 31 samples (including 8 PDAC I, 9 PDAC II, 6 PDAC III, and 8 PDAC IV) to characterize the changes in TME composition with PDAC progression through advanced scRNA-seq analysis. We found that as cancer progresses, immune cells gradually become a predominant component in late-stage PDAC. We defined a novel Treg and exhausted T cell signature gene, TNFRSF4. Additionally, we identified a prognostic gene set (RPS10, MIF, MT-ATP6, CSTB, IFI30, NPC2, BTG1, CTSD, FCGR2A, SEC61G, IER3, HSPB1, HMOX1, and ZFP36L1) and differentiated high-risk from low-risk PDAC patients based on median risk score threshold. Based on these findings, we developed a novel prognostic model that identifies poorer prognosis in high-risk groups. Furthermore, our analysis revealed significant interactions between cells at different stages of PDAC and identified three promising therapeutic agents (XR-11576, Ixabepilone, and AMONAFIDE) based on correlated genes. Finally, molecular docking studies validated their potential by confirming stable binding with key protein targets. This study not only provides insights into the evolving TME of PDAC but also offers a new prognostic model and potential therapeutic strategies, contributing to improved management and treatment of this aggressive cancer.

Genomic and Epigenomic Analysis of Plasma Cell-Free DNA Identifies Stemness Features Associated with Worse Survival in Lethal Prostate Cancer

PURPOSE

Metastatic castration-resistant prostate cancer (mCRPC) resistant to androgen receptor signaling inhibitors (ARSI) is often lethal. Liquid biopsy biomarkers for this deadly form of disease remain under investigation, and underpinning mechanisms remain ill-understood.

EXPERIMENTAL DESIGN

We applied targeted cell-free DNA (cfDNA) sequencing to 126 patients with mCRPC from three academic cancer centers and separately performed genome-wide cfDNA methylation sequencing on 43 plasma samples collected prior to the initiation of first-line ARSI treatment. To analyze the genome-wide sequencing data, we performed nucleosome positioning and differential methylated region analysis. We additionally analyzed single-cell and bulk RNA sequencing data from 14 and 80 patients with mCRPC, respectively, to develop and validate a stem-like signature, which we inferred from cfDNA.

RESULTS

Targeted cfDNA sequencing detected AR/enhancer alterations prior to first-line ARSIs that correlated with significantly worse progression-free survival (P = 0.01; HR = 2.12) and overall survival (P = 0.02; HR = 2.48). Plasma methylome analysis revealed that AR/enhancer lethal mCRPC patients have significantly higher promoter-level hypomethylation than AR/enhancer wild-type mCRPC patients (P < 0.0001). Moreover, gene ontology and CytoTRACE analysis of nucleosomally more accessible transcription factors in cfDNA revealed enrichment for stemness-associated transcription factors in patients with lethal mCRPC. The resulting stemness signature was then validated in a completely held-out cohort of 80 patients with mCRPC profiled by tumor RNA sequencing.

CONCLUSIONS

We analyzed a total of 220 patients with mCRPC, validated the importance of cell-free AR/enhancer alterations as a prognostic biomarker in lethal mCRPC, and showed that the underlying mechanism for lethality involves reprogramming developmental states toward increased stemness. See related commentary by Nawfal et al., p. 7.

CD8 + T-Cell-Related Genes: Deciphering Their Role in the Pancreatic Adenocarcinoma TME and Their Effect on Prognosis

BACKGROUND

Because of the unique tumor microenvironment (TME), immunotherapy and targeted therapies have shown limited efficacy in treating pancreatic adenocarcinoma (PAAD). CD8 + T cells play crucial roles in regulating the TME in PAAD; therefore, exploring the function of CD8 + T-cell-related genes (CD8RGs) in PAAD has high potential clinical value and could provide a comprehensive understanding of the microenvironment of PAAD.

METHODS

We employed the weighted gene coexpression network analysis and CIBERSORT algorithms to assess PAAD transcriptome data from The Cancer Genome Atlas (TCGA) dataset and identify modules strongly associated with CD8 + T cell infiltration. Using least absolute shrinkage and selection operator regression analysis and Kaplan-Meier curves, we developed a prognostic risk score model for patients with PAAD. We validated this model using single-cell and transcriptome datasets obtained from the Gene Expression Omnibus (GEO). We also examined the correlations between the risk score and factors such as the TME, clinical characteristics, and tumor mutation burden (TMB). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed on differentially expressed genes between the high- and low-risk groups. In addition, the Tumor Immune Dysfunction and Exclusion website and "pRRophetic" R package were used to predict response to immunotherapy and chemotherapy in the high- and low-risk groups, respectively. Finally, we analyzed the expressions of hub genes at the cellular level with quantitative real-time PCR.

RESULTS

A risk model based on five CD8RGs was established and validated using TCGA and GEO datasets. The low-risk group exhibited significantly longer overall and progression-free survival. A positive correlation between the TMB and the risk score was observed. The TME analysis revealed a significant correlation between the risk score and immune function, as well as immune checkpoints. The expression of hub genes was significantly correlated with the infiltration level of CD8 + T cells. The high-risk group responded better to immunotherapy, paclitaxel, cisplatin, mitomycin C, afatinib (BIBW2992), and gefitinib. In contrast, the low-risk group showed higher sensitivity to sunitinib, MK.2206, palbociclib (PD.0332991), and axitinib. Compared with that in normal pancreatic epithelial cells, the expression levels of BCL11A, PHOSPHO1, and GNG7 were significantly decreased, while those of KLK11 and VCAM1 were significantly increased in pancreatic tumor cells.

CONCLUSIONS

CD8RGs play an important role in regulating the TME of PAAD. Five hub genes-BCL11A, KLK11, GNG7, PHOSPHO1, and VCAM1-are closely associated with the prognosis of PAAD patients, providing new references for the exploration of biomarkers. Furthermore, our findings offer novel insights for clinical decision-making.

Targeted SPP1 Inhibition of Tumor-Associated Myeloid Cells Effectively Decreases Tumor Sizes

Secreted phosphosprotein 1 (SPP1)High tumor-associated macrophages (TAM) are abundant tumor myeloid cells that are immunosuppressive, pro-tumorigenic, and have a highly negative prognostic factor. Despite this, there is a lack of efficient TAM-specific therapeutics capable of reducing SPP1 expression. Here, on a phenotypic screen is reported to identify small molecule SPP1 modulators in macrophages. Several hits and incorporated them into a TAM-avid systemic nanoformulation are identified. It is shown that the lead compound (CANDI460) can down-regulate SPP1 in vitro and in vivo and lead to tumor remissions in different murine models. These findings are important as they offer a promising avenue for developing novel therapeutic strategies targeting TAM.

CAFomics: convergence to translation for precision stroma approaches

A noticeable characteristic of pancreatic ductal adenocarcinoma (PDAC) tumors is a dense tumor microenvironment with abundant and dense, desmoplastic stroma woven tightly with both cellular and matrix components. The high stromal density is associated with higher intratumor pressures which, until the last decade, was largely assumed to be tumor protective, confirmed by early studies demonstrating that altering the stroma was effective in genetically engineered models of PDAC. However, clinical trials using these approaches have been disappointing. There is increasing recognition that stroma heterogeneity is much greater than initially thought with an explosion of investigation into cancer-associated fibroblast (CAF) subpopulations led by experimental and single-cell transcriptomic studies. This review summarizes and attempts to harmonize the current transcriptomic data of CAF subpopulations. Understanding the heterogeneity of CAFs, the matrix, and other tumor microenvironment features will be critical to developing effective therapeutic approaches. Identifying model systems that best recapitulate the clinical behavior and treatment response of human PDAC will be important. Examining subpopulations as defined by clinical outcome will remain a critical step in defining clinically impactful CAF subtypes in larger clinical cohorts. The future of precision oncology in PDAC will depend on the integration of precision tumor epithelial and precision stroma approaches.

Circadian rhythms of macrophages are altered by the acidic tumor microenvironment

Tumor-associated macrophages (TAMs) are prime therapeutic targets due to their pro-tumorigenic functions, but varying efficacy of macrophage-targeting therapies highlights our incomplete understanding of how macrophages are regulated within the tumor microenvironment (TME). The circadian clock is a key regulator of macrophage function, but how circadian rhythms of macrophages are influenced by the TME remains unknown. Here, we show that conditions associated with the TME such as polarizing stimuli, acidic pH, and lactate can alter circadian rhythms in macrophages. While cyclic AMP (cAMP) has been reported to play a role in macrophage response to acidic pH, our results indicate pH-driven changes in circadian rhythms are not mediated solely by cAMP signaling. Remarkably, circadian disorder of TAMs was revealed by clock correlation distance analysis. Our data suggest that heterogeneity in circadian rhythms within the TAM population level may underlie this circadian disorder. Finally, we report that circadian regulation of macrophages suppresses tumor growth in a murine model of pancreatic cancer. Our work demonstrates a novel mechanism by which the TME influences macrophage biology through modulation of circadian rhythms.

Spatial transcriptomic analysis of primary and metastatic pancreatic cancers highlights tumor microenvironmental heterogeneity

Although the spatial, cellular and molecular landscapes of resected pancreatic ductal adenocarcinoma (PDAC) are well documented, the characteristics of its metastatic ecology remain elusive. By applying spatially resolved transcriptomics to matched primary and metastatic PDAC samples, we discovered a conserved continuum of fibrotic, metabolic and immunosuppressive spatial ecotypes across anatomical regions. We observed spatial tumor microenvironment heterogeneity spanning beyond that previously appreciated in PDAC. Through comparative analysis, we show that the spatial ecotypes exhibit distinct enrichment between primary and metastatic sites, implying adaptability to the local environment for survival and progression. The invasive border ecotype exhibits both pro-tumorigenic and anti-tumorigenic cell-type enrichment, suggesting a potential immunotherapy target. The ecotype heterogeneity across patients emphasizes the need to map individual patient landscapes to develop personalized treatment strategies. Collectively, our findings provide critical insights into metastatic PDAC biology and serve as a valuable resource for future therapeutic exploration and molecular investigations.

CCL3 predicts exceptional response to TGFβ inhibition in basal-like pancreatic cancer enriched in LIF-producing macrophages

The TGFβ receptor inhibitor galunisertib showed promising efficacy in patients with pancreatic ductal adenocarcinoma (PDAC) in the phase 2 H9H-MC-JBAJ study. Identifying biomarkers for this treatment remains essential. Baseline plasma levels of chemokine CCL3 were integrated with clinical outcomes in PDAC patients treated with galunisertib plus gemcitabine (n = 104) or placebo plus gemcitabine (n = 52). High CCL3 was a poor prognostic factor in the placebo group (mOS 3.6 vs. 10.1 months; p < 0.01) but a positive predictor for galunisertib (mOS 9.2 vs. 3.6 months; p < 0.01). Mechanistically, tumor-derived CCL3 activates Tgfβ signaling in macrophages, inducing their M2 phenotype and Lif secretion, sustaining a mesenchymal/basal-like ecotype. TGFβ inhibition redirects macrophage polarization to M1, reducing Lif and shifting PDAC cells to a more epithelial/classical phenotype, improving gemcitabine sensitivity. This study supports exploring TGFβ-targeting agents in PDAC with a mesenchymal/basal-like ecotype driven by high CCL3 levels.

Histological variants of pancreatic ductal adenocarcinoma: a survival analysis

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) can be classified into distinct histological subtypes based on the WHO nomenclature. The aim of this study was to compare the prognosis of conventional PDAC (cPDAC) against the other histological variants at the population level.

METHODS

The Surveillance, Epidemiology and End Results (SEER) database was used to identify patients with microscopically confirmed PDAC. These patients were divided into 9 histological subgroups. Overall survival was assessed using the Kaplan-Meier method and Cox regression models stratified by tumor histology.

RESULTS

A total of 159,548 patients with PDAC were identified, of whom 95.9% had cPDAC, followed by colloid carcinoma (CC) (2.6%), adenosquamous carcinoma (ASqC) (0.8%), signet ring cell carcinoma (SRCC) (0.5%), undifferentiated carcinoma (UC) (0.1%), undifferentiated carcinoma with osteoclast-like giant cells (UCOGC) (0.1%), hepatoid carcinoma (HC) (0.01%), medullary carcinoma of the pancreas (MCP) (0.006%) and pancreatic undifferentiated carcinoma with rhabdoid phenotype (PUCR) (0.003%). Kaplan-Meier curves showed that PUCR had the worst prognosis (median survival: 2 months; 5-year survival: 0%), while MCP had the best prognosis (median survival: 41 months; 5-year survival: 33.3%). In a multivariable Cox model, several histological subtypes (i.e. CC, ASqC, SRCC, UCOGC) were identified as independent predictors of overall survival when compared to cPDAC.

CONCLUSION

PDAC is a heterogenous disease and accurate identification of variant histology is important for risk stratification, as these variants may have different biological behavior.

Comparative transcriptomic analysis reveals the molecular changes of acute pancreatitis in experimental models

BACKGROUND

Acute pancreatitis (AP) encompasses a spectrum of pancreatic inflammatory conditions, ranging from mild inflammation to severe pancreatic necrosis and multisystem organ failure. Given the challenges associated with obtaining human pancreatic samples, research on AP predominantly relies on animal models. In this study, we aimed to elucidate the fundamental molecular mechanisms underlying AP using various AP models.

AIM

To investigate the shared molecular changes underlying the development of AP across varying severity levels.

METHODS

AP was induced in animal models through treatment with caerulein alone or in combination with lipopolysaccharide (LPS). Additionally, using Ptf1α to drive the specific expression of the hM3 promoter in pancreatic acinar cells transgenic C57BL/6J- hM3/Ptf1α(cre) mice were administered Clozapine N-oxide to induce AP. Subsequently, we conducted RNA sequencing of pancreatic tissues and validated the expression of significantly different genes using the Gene Expression Omnibus (GEO) database.

RESULTS

Caerulein-induced AP showed severe inflammation and edema, which were exacerbated when combined with LPS and accompanied by partial pancreatic tissue necrosis. Compared with the control group, RNA sequencing analysis revealed 880 significantly differentially expressed genes in the caerulein model and 885 in the caerulein combined with the LPS model. Kyoto Encyclopedia of Genes and Genomes enrichment analysis and Gene Set Enrichment Analysis indicated substantial enrichment of the TLR and NOD-like receptor signaling pathway, TLR signaling pathway, and NF-κB signaling pathway, alongside elevated levels of apoptosis-related pathways, such as apoptosis, P53 pathway, and phagosome pathway. The significantly elevated genes in the TLR and NOD-like receptor signaling pathways, as well as in the apoptosis pathway, were validated through quantitative real-time PCR experiments in animal models. Validation from the GEO database revealed that only MYD88 concurred in both mouse pancreatic tissue and human AP peripheral blood, while TLR1, TLR7, RIPK3, and OAS2 genes exhibited marked elevation in human AP. The genes TUBA1A and GADD45A played significant roles in apoptosis within human AP. The transgenic mouse model hM3/Ptf1α(cre) successfully validated significant differential genes in the TLR and NOD-like receptor signaling pathways as well as the apoptosis pathway, indicating that these pathways represent shared pathological processes in AP across different models.

CONCLUSION

The TLR and NOD receptor signaling pathways play crucial roles in the inflammatory progression of AP, notably the MYD88 gene. Apoptosis holds a central position in the necrotic processes of AP, with TUBA1A and GADD45A genes exhibiting prominence in human AP.

Neoadjuvant chemotherapy is associated with suppression of the B cell-centered immune landscape in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is typically diagnosed at advanced stages and associated with early distant metastasis and poor survival. Besides clinical factors, the tumor microenvironment (TME) emerged as a crucial determinant of patient survival and therapy response in many tumors, including PDAC. Thus, the presence of tumor-infiltrating lymphocytes and the formation of tertiary lymphoid structures (TLS) is associated with longer survival in PDAC. Although neoadjuvant therapy (NeoTx) has improved the management of locally advanced tumors, detailed insight into its effect on various TME components is limited. While a remodeling towards a proinflammatory state was reported for PDAC-infiltrating T cells, the effect of NeoTx on B cell subsets, including plasma cells, and TLS formation is widely unclear. We thus investigated the frequency, composition, and spatial distribution of PDAC-infiltrating B cells in primary resected (PR) versus neoadjuvant-treated patients using a novel multiplex immunohistochemistry panel. The NeoTx group displayed significantly lower frequencies of pan B cells, GC B cells, plasmablasts, and plasma cells, accompanied by a reduced abundance of TLS. This finding was supported by bulk RNA-sequencing analysis of an independent fresh frozen tissue cohort, which revealed that major B cell pathways were downregulated in the NeoTx group. We further observed that plasma cells frequently formed aggregates that localized close to TLS and that TLS+ patients displayed significantly higher plasma cell frequencies compared to TLS- patients in the PR group. Additionally, high densities of CD20+ intratumoral B cells were significantly associated with longer overall survival in the PR group. While CD20+ B cells held no prognostic value for NeoTx patients, an increased frequency of proliferating CD20+Ki67+ B cells emerged as an independent prognostic factor for longer survival in the NeoTx group. These results indicate that NeoTx differentially affects PDAC-infiltrating immune cells and may have detrimental effects on the existing B cell landscape and the formation of TLS. Gaining further insight into the underlying molecular mechanisms is crucial to overcome the intrinsic immunotherapy resistance of PDAC and develop novel strategies to improve the long-term outcome of PDAC patients.

TGFβ-specific T cells induced by a TGFβ-derived immune modulatory vaccine both directly and indirectly modulate the phenotype of tumor-associated macrophages and fibroblasts

The tumor microenvironment (TME) of pancreatic cancer is highly immunosuppressive. We recently developed a transforming growth factor (TGF)β-based immune modulatory vaccine that controlled tumor growth in a murine model of pancreatic cancer by targeting immunosuppression and desmoplasia in the TME. We found that treatment with the TGFβ vaccine not only reduced the percentage of M2-like tumor-associated macrophages (TAMs) and cancer-associated fibroblasts (CAFs) in the tumor but polarized CAFs away from the myofibroblast-like phenotype. However, whether the immune modulatory properties of the TGFβ vaccine on TAM and CAF phenotypes are a direct consequence of the recognition and subsequent targeting of these subsets by TGFβ-specific T cells or an indirect consequence of the overall modulation induced within the TME remains unknown. Recognition of M2 macrophages and fibroblast by TGFβ-specific T cells was assessed by ELISpot and flow cytometry. The indirect and direct effects of the TGFβ vaccine on these cell subsets were evaluated by culturing M2 macrophages or fibroblasts with tumor-conditioned media or with T cells isolated from the spleen of mice treated with the TGFβ vaccine or a control vaccine, respectively. Changes in phenotype were assessed by flow cytometry and Bio-Plex multiplex system (Luminex). We found that TGFβ-specific T cells induced by the TGFβ vaccine can recognize M2 macrophages and fibroblasts. Furthermore, we demonstrated that the phenotype of M2 macrophages and CAFs can be directly modulated by TGFβ-specific T cells induced by the TGFβ vaccine, as well as indirectly modulated as a result of the immune-modulatory effects of the vaccine within the TME. TAMs tend to have tumor-promoting functions, harbor an immunosuppressive phenotype and are linked to decreased overall survival in pancreatic cancer when they harbor an M2-like phenotype. In addition, myofibroblast-like CAFs create a stiff extracellular matrix that restricts T cell infiltration, impeding the effectiveness of immune therapies in desmoplastic tumors, such as pancreatic ductal adenocarcinoma. Reducing immunosuppression and immune exclusion in pancreatic tumors by targeting TAMs and CAFs with the TGFβ-based immune modulatory vaccine emerges as an innovative strategy for the generation of a more favorable environment for immune-based therapies, such as immune checkpoint inhibitors.

Genomic and epigenomic analysis of plasma cell-free DNA identifies stemness features associated with worse survival in AR -altered lethal prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) resistant to androgen receptor (AR)-targeted agents is often lethal. Unfortunately, biomarkers for this deadly disease remain under investigation, and underpinning mechanisms are ill-understood. Here, we applied deep sequencing to ∼100 mCRPC patients prior to the initiation of first-line AR-targeted therapy, which detected AR /enhancer alterations in over a third of patients, which correlated with lethality. To delve into the mechanism underlying why these patients with cell-free AR /enhancer alterations developed more lethal prostate cancer, we next performed genome-wide cell-free DNA epigenomics. Strikingly, we found that binding sites for transcription factors associated with developmental stemness were nucleosomally more accessible. These results were corroborated using cell-free DNA methylation data, as well as tumor RNA sequencing from a held-out cohort of mCRPC patients. Thus, we validated the importance of AR /enhancer alterations as a prognostic biomarker in lethal mCRPC, and showed that the underlying mechanism for lethality involves reprogramming developmental states toward increased stemness.