Construction of a novel model based on cell-in-cell-related genes and validation of KRT7 as a biomarker for predicting survival and immune microenvironment in pancreatic cancer

A prognostic binary classifier comprised of five critical mRNAs stratified pancreatic cancer patients following resection

Background

Pancreatic cancer is characterized by an extremely poor prognosis, even following potentially curative resection. Classical prognostic markers such as histopathological or clinical parameters have limited predictive power. The present study aimed to establish a prognostic model combining mRNA expression data with histopathological and clinical data to better predict survival and stratify pancreatic cancer patients following resection. We pioneered three models in one study and systematically evaluated the clinical benefits of all three models.

Methods

To identify differentially expressed genes in pancreatic cancer, mRNA data from normal (GTEx database) and pancreatic cancer (TCGA database) tissues were used. Survival analysis was carried out to identify prognosis-relevant genes from the identified differentially expressed genes and LASSO regression was used to filter out hub genes. The risk score of several hub genes was calculated according to gene expression and coefficients. Validation was carried out using an independent set of GEO microarray data. Multivariate COX regression was used for identifying independent clinical and pathological risk factors related to patient's survival in the TCGA database and a prognostic model combining mRNA expression data with histopathological and clinical data was established. Another prognostic model using clinicopathological factors from the SEER database was conceived based on multivariate COX regression. NRI (net reclassification improvement) and IDI (integrated discrimination index) were used to compare the predictive capabilities of the different models.

Results

We identified 1589 differentially expressed genes (DEGs) through the comparison of normal and pancreatic cancer tissues, of whom 317 were associated with prognosis(p < 0.05). LASSO regression identified five hub genes, MYEOV, ANXA2P2, MET, CEP55, and KRT7, that were used for the five-mRNA-classifier prognostic model. The classifier could stratify patients into a short and long survival group: 5-year overall survival in the training set (TCGA, 6 % vs 52 %, p < 0.001), test set (TCGA, 18 % vs 55 %,p < 0.01) and external validation set (GEO, 0 % vs 25 %, p < 0.05). Sensitivity analysis showed that the mRNA model (model 1) was better than the clinicopathological no-mRNA model (model 2) in predicting 5-year survival in the TCGA database (AUC: 0.877 vs 0.718, z = 3.165, p < 0.01) and better than the multi-factor prognostic model (model 3) from the SEER database (AUC: 0.754, z = 2.637, p < 0.01). On predictive performance, model 1 improved model 2 (NRI = 0.084, z = 1.288, p = 0.198; IDI = 0.055, z = 1.041,p = 0.298) and model 3 (NRI = 0.167,z = 1.961,p = 0.05; IDI = 0.086, z = 1.427, p = 0.154).

Conclusion

The five-mRNA-classifier is a reliable and feasible instrument to predict the prognosis of pancreatic cancer patients following resection. It might help in patiens counseling and assist clinicians in providing individualized treatment for patients in different risk groups.

PANoptosis subtypes predict prognosis and immune efficacy in gastric cancer

PANoptosis is a form of inflammatory programmed cell death that is regulated by the PANoptosome. This PANoptosis possesses key characteristics of pyroptosis, apoptosis, and necroptosis, yet cannot be fully explained by any of these cell death modes. The unique nature of this cell death mechanism has garnered significant interest. However, the specific role of PANoptosis-associated features in gastric cancer (GC) is still uncertain. Patients were categorized into different PAN subtypes based on the expression of genes related to the PANoptosome. We conducted a systematic analysis to investigate the variations in prognosis and tumor microenvironment (TME) among these subtypes. Furthermore, we developed a risk score, called PANoptosis-related risk score (PANS), which is constructed from genes associated with the PANoptosis. We comprehensively analyzed the correlation between PANS and GC prognosis, TME, immunotherapy efficacy and chemotherapeutic drug sensitivity. Additionally, we performed in vitro experiments to validate the impact of Keratin 7 (KRT7) on GC. We identified two PAN subtypes (PANcluster A and B). PANoptosome genes were highly expressed in PANcluster A. PANcluster A has the characteristics of favorable prognosis, abundant infiltration of anti-tumor lymphocytes, and sensitivity to immunotherapy, thus it was categorized as an immune-inflammatory type. Meanwhile, our constructed PANS can effectively predict the prognosis and immune efficacy of GC. Patients with low PANS have a good prognosis, and have the characteristics of high tumor mutation load (TMB), high microsatellite instability (MSI), low tumor purity and sensitivity to immunotherapy. In addition, PANS can also identify suitable populations for different chemotherapy drugs. Finally, we confirmed that KRT7 is highly expressed in GC. Knocking down the expression of KRT7 significantly weakens the proliferation and migration abilities of GC cells. The models based on PANoptosis signature help to identify the TME features of GC and can effectively predict the prognosis and immune efficacy of GC. Furthermore, the experimental verification results of KRT7 provide theoretical support for anti-tumor treatment.

Immune-related signature identifies IL1R2 as an immunological and prognostic biomarker in pancreatic cancer

Objective

Pancreatic cancer is one of the most aggressive malignancies, a robust prognostic signature and novel biomarkers are urgently needed for accurate stratification of the patients and optimization of clinical decision-making.

Methods

A list of bioinformatic analysis were applied in public dataset to construct an immune-related signature. Furthermore, the most pivotal gene in the signature was identified. The potential mechanism of the core gene function was revealed through GSEA, CIBERSORT, ESTIMATE, immunophenoscore (IPS) algorithm, single-cell analysis, and functional experiment.

Results

An immune-related prognostic signature and associated nomogram were constructed and validated. Among the genes constituting the signature, interleukin 1 receptor type II (IL1R2) was identified as the gene occupying the most paramount position in the risk signature. Meanwhile, knockdown of IL1R2 significantly inhibited the proliferation, invasion, and migration ability of pancreatic cancer cells. Additionally, high IL1R2 expression was associated with reduced CD8+ T cell infiltration in pancreatic cancer microenvironment, which may be due to high programmed cell death-ligand-1 (PD-L1) expression in cancer cells. Finally, the IPS algorithm proved that patients with high IL1R2 expression possessed a higher tumor mutation burden and a higher probability of benefiting from immunotherapy.

Conclusion

In conclusion, our study constructed an efficient immune-related prognostic signature and identified the key role of IL1R2 in the development of pancreatic cancer, as well as its potential to serve as a biomarker for immunotherapy efficacy prediction for pancreatic cancer.

Clinical significance of KRT7 in bladder cancer prognosis

BACKGROUND

Typically, the overexpressed keratin 7 (KRT7) is considered a validated therapeutic target and prognosis marker in bladder cancer. However, the crucial roles of KRT7 in the clinical prognosis and immune microenvironment in bladder cancer remain unclear.

METHODS

Initially, the expression levels of KRT7 in public databases were analyzed that is,Tumor Immune Estimation Resource (TIMER) 2.0 and Gene Expression Profiling Interactive Analysis (GEPIA). Further, the clinical tissue samples from patients (n = 10 pairs) were collected to confirm the expression trends of KRT7 and detected by immunohistochemistry (IHC) analysis. Meanwhile, the relationship between KRT7 and the prognosis of bladder cancer patients was analyzed by Kaplan-Meier plotter estimation and Cox regression analysis. Finally, TIMER 2.0 and IHC staining analyses were performed to calculate the infiltration abundances of three kinds of immune cells in eligible bladder tumor samples.

RESULTS

The TIMER 2.0 and GEPIA datasets suggested the differences in the expression levels of KRT7 in tumors, in which KRT7 was significantly upregulated in bladder cancer. The KRT7 expression was closely associated with patients' gender, tumor histologic subtypes, T status, and American Joint Committee on Cancer stages. Notably, the increased KRT7 indicated poor overall survival and disease-free survival rates. Moreover, KRT7 expression could be responsible for immune infiltration in the cancer microenvironment of the bladder. Finally, the high expression level of KRT7 increased the presence of regulatory T cells (Tregs) but reduced the infiltration of CD8+ T and natural killer cells.

CONCLUSION

KRT7 as a biomarker potentiated the prediction of bladder cancer prognosis and the immune microenvironment.

Cancer-Associated Fibroblast Induces Acinar-to-Ductal Cell Transdifferentiation and Pancreatic Cancer Initiation Via LAMA5/ITGA4 Axis

BACKGROUND & AIMS

Pancreatic ductal adenocarcinoma (PDAC) is characterized by desmoplastic stroma surrounding most tumors. Activated stromal fibroblasts, namely cancer-associated fibroblasts (CAFs), play a major role in PDAC progression. We analyzed whether CAFs influence acinar cells and impact PDAC initiation, that is, acinar-to-ductal metaplasia (ADM). ADM connection with PDAC pathophysiology is indicated, but not yet established. We hypothesized that CAF secretome might play a significant role in ADM in PDAC initiation.

METHODS

Mouse and human acinar cell organoids, acinar cells cocultured with CAFs and exposed to CAF-conditioned media, acinar cell explants, and CAF cocultures were examined by means of quantitative reverse transcription polymerase chain reaction, RNA sequencing, immunoblotting, and confocal microscopy. Data from liquid chromatography with tandem mass spectrometry analysis of CAF-conditioned medium and RNA sequencing data of acinar cells post-conditioned medium exposure were integrated using bioinformatics tools to identify the molecular mechanism for CAF-induced ADM. Using confocal microscopy, immunoblotting, and quantitative reverse transcription polymerase chain reaction analysis, we validated the depletion of a key signaling axis in the cell line, acinar explant coculture, and mouse cancer-associated fibroblasts (mCAFs).

RESULTS

A close association of acino-ductal markers (Ulex europaeus agglutinin 1, amylase, cytokeratin-19) and mCAFs (α-smooth muscle actin) in LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx1Cre (KPC) and LSL-KrasG12D/+; Pdx1Cre (KC) autochthonous progression tumor tissue was observed. Caerulein treatment-induced mCAFs increased cytokeratin-19 and decreased amylase in wild-type and KC pancreas. Likewise, acinar-mCAF cocultures revealed the induction of ductal transdifferentiation in cell line, acinar-organoid, and explant coculture formats in WT and KC mice pancreas. Proteomic and transcriptomic data integration revealed a novel laminin α5/integrinα4/stat3 axis responsible for CAF-mediated acinar-to-ductal cell transdifferentiation.

CONCLUSIONS

Results collectively suggest the first evidence for CAF-influenced acino-ductal phenotypic switchover, thus highlighting the tumor microenvironment role in pancreatic carcinogenesis inception.

KRT80 Promotes Lung Adenocarcinoma Progression and Serves as a Substrate for VCP

Background: Keratin 80(KRT80) encodes a type II intermediate filament protein, known for maintaining cell integrity of cells and its involvement in the tumorigenesis and progression of various cancers. However, comprehensive research on its relevance to lung adenocarcinoma remains limited. Methods: In this study, we utilized multiple databases to investigate the transcriptional expression of KRT80 and its correlation with clinicopathological features. A range of assays, including the Cell Counting Kit 8 assay, colony formation assay, cell migration assay, and flow cytometry, were employed to elucidate the impact of KRT80 on the malignant behavior of lung adenocarcinoma. Immunoprecipitation and mass spectrometry were also used to identify putative genes interacting with KRT80. Results: The expression of KRT80 was elevated in lung adenocarcinoma and patients with high levels of KRT80 expression had poor clinical outcomes. Silencing KRT80 suppressed cell viability, and migration, while overexpression had the opposite effect. In addition, Immunoprecipitation and mass spectrometry revealed an interaction between KRT80 and valosin-containing protein (VCP), with VCP knockdown reducing the stability of KRT80 protein. Overexpression of KRT80 mitigated the inhibitory effect of VCP knockdown to some extent. Conclusion: Our findings collectively suggest that KRT80 is a promising diagnostic and prognostic indicator for lung adenocarcinoma. Additionally, the interaction between KRT80 and VCP plays a crucial role in the progression of lung adenocarcinoma, which implies that KRT80 is a promising therapeutic target.

Emerging insights into keratin 7 roles in tumor progression and metastasis of cancers

Keratin 7 (KRT7), also known as cytokeratin-7 (CK-7) or K7, constitutes the principal constituent of the intermediate filament cytoskeleton and is primarily expressed in the simple epithelia lining the cavities of the internal organs, glandular ducts, and blood vessels. Various pathological conditions, including cancer, have been linked to the abnormal expression of KRT7. KRT7 overexpression promotes tumor progression and metastasis in different human cancers, although the mechanisms of these processes caused by KRT7 have yet to be established. Studies have indicated that the suppression of KRT7 leads to rapid regression of tumors, highlighting the potential of KRT7 as a novel candidate for therapeutic interventions. This review aims to delineate the various roles played by KRT7 in the progression and metastasis of different human malignancies and to investigate its prognostic significance in cancer treatment. Finally, the differential diagnosis of cancers based on the KRT7 is emphasized.

Improving the prognosis of pancreatic cancer: insights from epidemiology, genomic alterations, and therapeutic challenges

Pancreatic cancer, notorious for its late diagnosis and aggressive progression, poses a substantial challenge owing to scarce treatment alternatives. This review endeavors to furnish a holistic insight into pancreatic cancer, encompassing its epidemiology, genomic characterization, risk factors, diagnosis, therapeutic strategies, and treatment resistance mechanisms. We delve into identifying risk factors, including genetic predisposition and environmental exposures, and explore recent research advancements in precursor lesions and molecular subtypes of pancreatic cancer. Additionally, we highlight the development and application of multi-omics approaches in pancreatic cancer research and discuss the latest combinations of pancreatic cancer biomarkers and their efficacy. We also dissect the primary mechanisms underlying treatment resistance in this malignancy, illustrating the latest therapeutic options and advancements in the field. Conclusively, we accentuate the urgent demand for more extensive research to enhance the prognosis for pancreatic cancer patients.

Cell-in-cell structure in cancer: evading strategies from anti-cancer therapies

One of the regulated forms of cell death is the cell-in-cell (CIC) structure, in which a surviving cell is engulfed by another cell, a mechanism that causes the death of the engulfed cell by an adjacent cell. Several investigators have previously shown that the presence of CICs is an independent risk factor significantly associated with decreased survival in patients with various types of cancer. In this review, we summarize the role of CIC in the tumor microenvironment (TME), including changes and crosstalk of molecules and proteins in the surrounding CIC, and the role of these factors in contributing to therapeutic resistance acquisition. Moreover, CIC structure formation is influenced by the modulation of TME, which may lead to changes in cellular properties. Future use of CIC as a clinical diagnostic tool will require a better understanding of the effects of chemotherapy on CIC, biomarkers for each CIC formation process, and the development of automated CIC detection methods in tissue sections of tumor specimens.

The role of BHLHE40 in clinical features and prognosis value of PDAC by comprehensive analysis and in vitro validation

Pancreatic ductal adenocarcinoma (PDAC) is the leading cause of cancer-related mortality, primarily due to the abundance of cancer-associated fibroblasts (CAFs), depleted effector T cells, and increased tumor cell stemness; hence, there is an urgent need for efficient biomarkers with prognostic and therapeutic potential. Here, we identified BHLHE40 as a promising target for PDAC through comprehensive analysis and weighted gene coexpression network analysis of RNA sequencing data and public databases, taking into account the unique characteristics of PDAC such as cancer-associated fibroblasts, infiltration of effector T cells, and tumor cell stemness. Additionally, we developed a prognostic risk model based on BHLHE40 and three other candidate genes (ITGA2, ITGA3, and ADAM9) to predict outcomes in PDAC patients. Furthermore, we found that the overexpression of BHLHE40 was significantly associated with T stage, lymph node metastasis, and American Joint Committee on Cancer (AJCC) stage in a cohort of 61 PDAC patients. Moreover, elevated expression levels of BHLHE40 were validated to promote epithelial-mesenchymal transition (EMT) and stemness-related proteins in BXPC3 cell lines. Compared to the parent cells, BXPC3 cells with BHLHE40 overexpression showed resistance to anti-tumor immunity when co-cultured with CD8⁺ T cells. In summary, these findings suggest that BHLHE40 is a highly effective biomarker for predicting prognosis in PDAC and holds great promise as a target for cancer therapy.