Translational Oncology

ObjectiveTo integrate macro-transcriptomics and single-cell sequencing to analyze the differential gene expression between primary and brain metastatic breast cancer cells, as well as between active and dormant cancer cells within brain metastases, exploring their adaptation and remodeling abilities at different stages of brain metastasis. MethodsFour public datasets were used: three mRNA microarray datasets from breast cancer and brain metastasis tissues, and one single-cell RNA sequencing (scRNA-seq) dataset from active and dormant brain metastatic cells. Gene differential expression, pathway enrichment, and cell clustering analyses were performed to compare primary and metastatic breast cancer cells, as well as active and dormant cells in brain metastases, focusing on gene expression, metabolic pathways, and functional pathways. ResultsMetastatic breast cancer cells showed weakened pathways related to the extracellular matrix and protein digestion. Active cells exhibited enhanced cell cycle regulation, tumor proliferation, and hypoxia resistance pathways compared to dormant cells. Clustering analysis revealed that cluster 6, unique to dormant cells, had enhanced functions in epithelial-mesenchymal transition (EMT), extracellular matrix (ECM), collagen formation, tumor inflammation siganure (TIS), and IL-10 signaling. Cluster 3 and 4 in active cells had enhanced DNA replication and tumor proliferation pathways, respectively. ConclusionThis study highlights the role of cancer cell characteristics and heterogeneity in the invasiveness of brain metastasis. Understanding these mechanisms can guide the development of more effective treatment strategies for breast cancer brain metastasis (BCBM) patients.

Triple-negative breast cancer (TNBC) is an aggressive subtype often marked by resistance to neoadjuvant chemotherapy (NAC), making treatment particularly challenging. Tumor-infiltrating lymphocytes (TILs), crucial players in the immune landscape of tumors, have been associated with treatment outcomes, but the prognostic potential of TIL-derived gene markers in pre-NAC samples from TNBC patients remains understudied. In this research, we analyzed the single-cell transcriptional profiles of approximately 5,000 cells from four chemosensitive and four chemoresistant TNBC patients using publicly available datasets. Leveraging standard single-cell analysis, we identified differentially expressed gene signatures within the TIL subpopulation, highlighting significant immune activation pathways differentiating chemoresistant from chemosensitive tumors. By employing robust feature selection and repeated cross-validation across microarray and RNA-seq datasets, we developed a stable set of 30 TIL-based gene markers with notable prognostic relevance for NAC response in TNBC. These markers achieved an AUROC of 0.78 in the training set and validated with AUROCs of 0.8, 0.658, and 0.736 across five independent test datasets, demonstrating consistency across diverse platforms and sequencing technologies. Furthermore, increased expression of these gene signatures correlated with improved recurrence-free survival (RFS) in a cohort of 220 TNBC patients. This study enhances our understanding of the TIL transcriptional landscape in NAC response, identifying potential biomarkers and therapeutic targets for improving treatment outcomes in TNBC.

CD4+ T cells have critical roles in anti-tumour immunity and its differentiation is known to be regulated by the nuclear receptor co-repressor 1 (NCOR1). Previous studies suggested that high CD4+ T cells are associated with a favourable prognosis in patients with pancreatic ductal adenocarcinoma (PDAC). However, the prognostic significance of NCOR1 in PDAC is still missing. In this study, the pathological impact of NCOR1 and CD4 has been analysed by multiplex immunohistochemistry in 100 PADC patients. NCOR1 expression in tertiary lymphoid organs is positively associated with the good prognosis of PDAC patients, while its expression in tumour tissue is not. Furthermore, the presence of NCOR1+/CD4+ T cells in tertiary lymphoid organs predicts a favourable prognosis in PDAC. Mechanistically, upregulation of NCOR1 expression in CD4+ T cells increases the release of TNF-, which induces the apoptosis of the tumor cells in vitro. Together, our data highlighted the tumour suppressive role of NCOR1+/CD4+ T cells in PDAC.

ObjectiveTo develop a robust predictive model and nomogram for breast cancer (BC) linked to genes associated with diverse cell death methods. MethodsThe prognostic model was constructed using the LASSO Cox method. Model performance was assessed using K-M analysis, ROC curves, and independent prognostic analysis. Subsequently, we constructed a nomogram and analyzed differences in tumor microenvironment and drug sensitivity between different subgroups. The enrichment of differentially expressed genes between different subgroups was assessed. Additionally, we overexpressed CD24 in BC cell lines to assess its impact on cellular proliferation using CCK8 assays, migration through scratch and transwell assays, and apoptosis via flow cytometry. ResultsA prognostic model comprising twelve genes (CREB3L1, SFRP1, SHARPIN, AIFM1, IL-18, CD24, EDA2R, CRIP1, XBP1, BCL2A1, NKX3-1, and NME5) was constructed. BC patients were categorized into different subgroups, with the low-risk subgroup demonstrating superior survival. Additionally, we constructed a nomogram. The nomogram was validated as a reliable independent predictor of outcome. The enrichment analyses imply a connection between patient risk and immune response. The low-risk subgroup had a higher TME score. Patients in the high-risk group had improved responses to lapatinib, BI-2536, OSI-027, and SB505124, while those in the low-risk subgroup showed improved sensitivity to axitinib, epirubicin, fulvestrant, and olaparib. Furthermore, CD24 overexpression was found to promote proliferation and migration, while inhibiting apoptosis. ConclusionThese findings contribute to the individualization of treatment and aid in uncovering the tumor microenvironment characterization for BC patients.

SPOCK1 is highly expressed in many types of cancer, which has been recognized as a promoter of cancer progression, while its regulatory mechanism remains to be clear in breast cancer (BC). This study aimed to explore the precise function of SPOCK1 in BC progression and the mechanism by which SPOCK1 was involved in cell proliferation and epithelial-mesenchymal transition (EMT). Immunohistochemistry (IHC) and database analysis displayed that high expression of SPOCK1 was positively associated with histological grade, lymph node metastasis (LN) and poor clinical prognosis in BC. A series of assays both in vitro and in vivo elucidated that altering SPOCK1 level led to distinctly changes in BC cell proliferation and metastasis. Investigations of potential mechanisms revealed that SPOCK1 interacted with SIX1 could enhance cell proliferation, cell cycle and EMT process by activating the AKT/mTOR pathway, whereas inhibition of AKT/mTOR pathway or depletion of SIX1 reversed the effects of SPOCK1 overexpression. Furthermore, SPOCK1 and SIX1 were highly expressed in BC and might indicate poor prognoses. Altogether, SPOCK1/SIX1 promoted BC progression by activating AKT/mTOR pathway to accelerate cell proliferation and metastasis in BC, and SPOCK1/SIX1 might be promising clinical therapeutic targets to prevent BC progression. IMPORTANCEThe incidence of BC is alarmingly high and many patients initially diagnosed without detectable metastases will eventually develop metastatic lesions. The occurrence of metastasis is responsible for the death of many patients, which also represents a big challenge for researchers to improve the survival rates of BC patients. Hence the scientific community pays more attention on cancer targeted therapy. This research is significant for identifying the underlying mechanisms and capabilities of SPOCK1-induced BC activities, which will greatly apply novel targets and new treatment strategies for clinicians, leading to broader biomedical impacts.

Colorectal cancer (CRC) is classified into microsatellite instability (MSI) and microsatellite stabilized (MSS) based on the differences in DNA repair mechanisms. In recent years, many studies have proved that some emerging therapeutic approaches have good therapeutic effects on MSI as a subtype but are ineffective for MSS as a subtype. This paper aims to start with the molecular mechanism of MSS and try to find the characteristic target genes of MSS as a subtype. We used bioinformatics techniques and machine learning to find GTF2IRD1. The gene GTF2IRD1 is highly expressed in MSS-type CRC but is stable in MSI. Subsequently, we verified its expression and function with relevant experiments. We demonstrated that GTF2IRD1 can promote the proliferation of MSS-type colorectal cancer and correlate with the poor prognosis of MSS-type colorectal cancer patients, which may provide a potential target gene for the clinical treatment of MSS-type colorectal cancer.

BackgroundTriple-negative breast cancer (TNBC) is aggressive, lacking methods to predict recurrence and drug sensitivity. Ferroptotic heterogeneity varies in TNBC subtypes. However, the tumor microenvironment (TME) mediated by ferroptosis genes is unclear. Our study aims to integrate single-cell and bulk RNA sequencing (RNA-seq) data to reveal the ferroptosis-mediated TME in TNBC, predicting prognosis and guiding treatment. MethodsThe single-cell and bulk RNA-seq data of TNBC were sourced from the Gene Expression Omnibus (GEO) database. Using these data, a machine learning algorithm was employed to integrate and analyze the characteristics of the TME mediated by ferroptosis-related genes in TNBC. Prediction models for TNBC survival prognosis and drug treatment response were established and then validated in an independent set. ResultsAt the individual cell level, T cells were categorized into three distinct subpopulations, and local macrophages into two subpopulations. The infiltration degree of these different cell subpopulations was closely associated with prognosis and treatment outcomes. Based on this, the risk score model we developed effectively predicted recurrence-free survival in TNBC patients, with independently validated pooled predicted 3-, 4-, and 5-year Area Under the Curves (AUCs) of 0.65, 0.67, and 0.71, respectively. Additionally, we found that patients in the high-risk group may be more responsive to 27 drugs. ConclusionsWe have uncovered the tumor immune cell clusters in TNBC mediated by ferroptosis. A risk score model was constructed to identify high-risk TNBC patients, which can assist physicians in disease monitoring and precision therapy. The genes identified hold significant potential as therapeutic targets for TNBC patients. FundingThis project is funded by the National Natural Science Foundation of China (81974268, 82472000, 82304151), the Talent Incentive Program of Cancer Hospital Chinese, Academy of Medical Sciences (801032247), the Cooperation Fund of CHCAMS (CFA202202023), and the open project of Beijing Key Laboratory of Tumor Invasion and Metastasis Mechanism, Capital Medical University(2023ZLKF03). Impact StatementIntegrating single-cell and bulk RNA-seq data elucidates the role of ferroptosis in TNBC, offering a prognostic model and personalized therapeutic insights.

BackgroundAltered metabolism is a hallmark of cancer and glycolysis is one of the important factors promoting tumor development. Given that the absence of multi-sample big data research about glycolysis, the molecular mechanisms involved in glycolysis or the relationships between glycolysis and tumor microenvironment are not fully studied. Thus, a more comprehensive approach in a pan-cancer landscape may be needed. MethodsHere, we develop a computational pipeline to study multi-omics molecular features defining glycolysis activity and identify molecular alterations that correlate with glycolysis. We apply a 22-gene expression signature to define the glycolysis activity landscape and verify the robustness using clinically defined glycolysis samples from several previous studies. Based on gene expression signature, we classify about 5552 of 9229 tumor samples into glycolysis score-high and score-low groups across 25 cancer types from The Cancer Genome Atlas (TCGA) and demonstrate their prognostic associations. Moreover, using genomes and transcriptome data, we characterize the association of copy-number aberrations (CNAs), somatic single-nucleotide variants (SNVs) and hypoxia signature with glycolysis activity. FindingsGene set variation analysis (GSVA) score by gene set expression was verified robustly to represent glycolytic activity and highly glycolytic tumors presented a poor overall survival in some cancer types. Then, we identified various types of molecular features promoting tumor cell proliferation were associated with glycolysis activity. Our study showed that TCA cycle and respiration electron transport were active in glycolysis-high tumors, indicating glycolysis was not a symptom of impaired oxidative metabolism. The glycolytic score significantly correlated with hypoxia score across all cancer types. Glycolysis score was also associated with elevated genomic instability. In all tumor types, high glycolysis tumors exhibited characteristic driver genes altered by CNAs identified multiple oncogenes and tumor suppressors. We observed widespread glycolysis-associated dysregulation of mRNA across cancers and screened out HSPA8 and P4HA1 as the potential modulating factor to glycolysis. Besides, the expression of genes encoding glycolytic enzymes positively correlated with genes in cell cycle. InterpretationThis is the first study to identify gene expression signatures that reflect glycolysis activity, which can be easily applied to large numbers of patient samples. Our analysis establishes a computational framework for characterizing glycolysis activity using gene expression data and defines correlation of glycolysis with the hypoxia microenvironment, tumor cell cycle and proliferation at a pan-cancer landscape. The findings suggest that the mechanisms whereby hypoxia influence glycolysis are likely multifactorial. Our finding is significant not just in demonstrating definition value for glycolysis but also in providing a comprehensive molecular-level understanding of glycolysis and suggesting a framework to guide combination therapy that may block the glycolysis pathway to control tumor growth in hypoxia microenvironment.

Pancreatic cancer is one of the deadliest cancers and has very limited therapeutic options and a dismal prognosis. Among various signaling pathways which are activated during tumor development, hyperactivation of Mitogen-Activated Protein Kinase (MAPK) is responsible for high grade angiogenesis, polarization of Tumor Associated Macrophages, unfolded protein responses and exhaustion of T cells, which together contributes towards this therapeutic resistance. We therefore believe that MAPK targeting is expected to enhance sensitivity of highly resistant PDAC cells toward various cancer directed interventions. In this context, we investigated the impact of modulating p38MAPK on the sensitivity of pancreatic cancer cells towards gemcitabine. Supporting our hypothesis, our results convincely, demonstrated that indeed, p38 inhibition sensitizes both KRAS positive Panc-1 and MiaPaCa2 pancreatic carcinoma cells towards gemcitabine induced death. Interestingly p38MAPK targeting significantly reduced the cell viability, clonogenic potential of these cells and enhanced the early apoptosis. Our in-silico studies, supporting our in vitro data, potentially correlated that that high expression of p38 MAPK14 in PDAC patients is associated with poor prognosis and disease free survival. Deep miming of in silico data further demonstrated that MAPK14, in association with, hypoxia inducible factor-1 alpha and vascular endothelial growth factor signaling pathways promote angiogenic programming of PDAC which render these tumors refractory for cancer directed interventions. Based on our preliminary data, we believe that p38 MAPK based approach is potential approach for changing the faith of PDAC patients toward chemo and immunotherapy and believed to improve PDAC burden effectively in the host. HighlightsO_LIp38 MAPK inhibition enhances the sensitivity of KRAS+ pancreatic cancer cells for Gemcitabine C_LIO_LIP38MAPK knockdown cells are sensitive for Gemcitabine induced death C_LIO_LIMAPK14 (p38) is associated with angiogenesis and poor prognosis in pancreatic cancer C_LIO_LIMAPK14 Regulates Pro-Tumorigenic Pathways and immune infiltration in Pancreatic Cancer C_LI

BackgroundAdenocarcinomas are malignancies arising from glandular epithelial cells or secretory tissue, and account for most cancer-related mortalities worldwide, despite advances in treatment. New treatments are often developed in the context of the organ from which the tumor originates. However, there exists shared biology across glandular epithelium at the molecular level regardless of organ system, and there has been a shift towards the molecular classification of tumors. Defining and targeting pan-adenocarcinoma specific molecular features may facilitate the development of treatments applicable across adenocarcinomas, expediting drug discovery efforts and translation to the clinical setting. MethodsWe performed an integrated transcriptomics analysis of adenocarcinomas originating from different organ systems. RNA sequencing expression profiles from lung adenocarcinoma (LUAD), stomach adenocarcinoma (STAD), and colorectal adenocarcinoma (COAD) with matched normal tissue from The Cancer Genome Atlas (TCGA) was used to discover a pan-adenocarcinoma specific transcriptomic module. A standardized DESeq2 based pipeline was used to test for differentially expressed genes (DEGs) between each adenocarcinoma and its matched normal tissues, followed by cross-cancer comparisons to identify a consensus transcriptional module. Enrichment analysis was performed to reveal biological pathways associated with the consensus module, with a particular focus on those involved in oncogenesis. Prognostic significance of the consensus transcriptional module was evaluated using survival modeling, and the module was tested against in vitro transcriptomic drug perturbation signatures using Connectivity Map (cMAP) analysis to identify candidate drugs targeting adenocarcinomas, regardless of organ system of origin. ResultsDespite the diversity of adenocarcinomas tested, there existed a significant and large overlap of the genes dysregulated across tested tumors. A consensus transcriptomic module was defined, and it predicted patient prognosis in each of the three adenocarcinomas. Leveraging the top shared biomarkers through cMAP analysis, we identified 36 FDA-approved drugs that are capable of reversing the shared malignant transcriptional module towards the normal state. Among the FDA-approved drugs were the EGFR and ALK inhibitors gefitinib and crizotinib, both currently used for treating LUAD, providing validation the pipeline could discover efficacious drugs. Taken together, we developed an approach for organ system independent cancer biomarkers and drug discovery, and leveraged it to identify drug candidates for expanded use in adenocarcinomas. The FDA-approved drugs identified through this pipeline serve as candidates to repurpose as pan-adenocarcinoma anti-cancer therapeutics, reducing both time and cost for drug development. ConclusionOur research provided insights into the common molecular mechanisms across multiple adenocarcinomas and unveiled potential drug candidates for future therapeutic testing.

PurposeNeoadjuvant therapy (NAT) is increasingly being used for pancreatic ductal adenocarcinoma (PDAC) treatment. However, its distinct effects on carcinoma cells and the tumor microenvironment (TME) are not fully understood. This study employs spatial transcriptomics and single-cell RNA sequencing to investigate how NAT differentially remodels PDACs carcinoma cells and TME. Experimental DesignWe used spatial transcriptomics to compare gene expression profiles in carcinoma cells and the TME between NAT-treated and NAT-naive PDAC patients and correlated with their clinicopathologic features. Complementary single-nucleus RNA sequencing (snRNA-seq) analysis was conducted to validate our findings and identify cell types driving NAT-induced gene expression alterations. ResultsWe found NAT not only induces apoptosis and inhibits proliferation in carcinoma cells but also significantly remodels the TME. Notably, NAT induces a coordinated upregulation of multiple key complement genes (C3, C1S, C1R, C4B and C7) in the TME, making the complement pathway one of the most significantly affected pathways by NAT. Patients with higher TME complement expression following NAT exhibit improved overall survival; more immunomodulatory and neurotrophic cancer-associated fibroblasts (CAFs); more CD4+ T cells, monocytes and mast cells; and lower immune exhaustion gene expression. snRNA-seq analysis demonstrates C3 complement upregulation specifically in CAFs but not in other stroma cell types. ConclusionsOur findings indicate that NAT may reduce immunosuppression in PDAC by enhancing complement production and signaling within the TME. These findings suggest that local complement dynamics could serve as a novel biomarker for prognosis, evaluating treatment response and resistance, and guiding therapeutic strategies in NAT-treated PDAC patients. Translational RelevanceAs neoadjuvant therapy (NAT) increasingly becomes the preferred approach in treating resectable and borderline resectable pancreatic ductal adenocarcinoma (PDAC), there is a growing demand for novel biomarkers specifically tailored for post-NAT PDAC patients. Our study focused on how NAT differentially remodels the tumor cells and the tumor microenvironment (TME). We demonstrate that NAT can enhance local complement production and signaling in PDACs TME, which is associated with reduced immune exhaustion and improved overall survival. Our results highlight the importance of local complement dynamics in influencing treatment response, resistance, and overall clinical outcomes in PDAC. This new mechanism provides new opportunities in biomarker development which could facilitate more accurate prognostication and precise treatment stratification, particularly for patients undergoing NAT in PDAC.

Despite advancements in breast cancer treatment, metastasis remains a significant challenge, contributing to high mortality rates. This study investigates the mechanisms underlying breast cancer lung metastasis, with a particular emphasis on the role of SH3PXD2B in driving epithelial-to-mesenchymal transition. Here, we analyzed RNA sequencing data from CCLE and TCGA databases and characterized that SH3PXD2B expression is elevated in breast cancer (BC) and lung cancer (LC) tissues compared to non-transformed tissues. Bioinformatics analysis revealed that SH3PXD2B regulates several cellular processes and is associated with poor prognosis in breast cancer (BRCA) and lung adenocarcinoma (LUAD) patients. Functional experiments underscore that the upregulation of SH3PXD2B promoted BC and LC cell migration in vitro; however, its knockdown inhibited the effect. Mechanistically, the mass spectrometry analysis was utilized to pull down interacting partners of SH3PXD2B, and the findings were substantiated by immunoblotting. Additionally, our findings on immunofluorescence and gene expression analysis demonstrated the additive role of SH3PXD2B and migratory proteins in promoting breast cancer progression. Further, we performed bioluminescent IVIS imaging analysis to trace the metastatic spread of MDA-MB-468 cells and observed strong signals and a high degree of dissemination to distant organs. Collectively, our results highlight the importance of SH3 domains in aggravating breast transformation, which can therefore serve as a promising therapeutic strategy in counteracting breast-related malignancy. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/618596v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@1fe7792org.highwire.dtl.DTLVardef@15c4481org.highwire.dtl.DTLVardef@9575f4org.highwire.dtl.DTLVardef@72ea93_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly aggressive disease with a poor prognosis. PDAC has a high propensity for metastasis, particularly to the lungs and liver. Cancer associated fibroblasts (CAFs) represent a major stromal component of PDAC with both tumor-promoting and restraining properties. Of note, CAFs play a significant role in the creation of an immunosuppressive tumor microenvironment (TME) and the metastasis of PDAC. Studies have demonstrated functional heterogeneity among different subpopulations of CAFs, highlighting the need to identify specific subpopulations when targeting CAFs. MethodsThe orthotopic model was used for both KPC-4545 and KPC-3403 cell lines, which were derived from the primary tumors of KPC mice with liver metastases and lung metastases only, respectively. In brief, 2x106 KPC cells were injected subcutaneously into the flanks of synergic female C57BI6 mice. Tumors were harvested and cut into 2-3 mm3 pieces before being implanted into the pancreas of new 6-8-week-old syngeneic female C57Bl/6 mice. Murine orthotopic tumors were dissected, mechanically and enzymatically processed with Miltenyi Tumor Dissociation Kit (Miltenyi Biotec) thirteen days after tumor implantation. Samples were filtered with a 100 {micro}m strainer, washed with T cell media, and centrifuged twice. Two different samples underwent single cell RNA-sequencing (scRNA-seq) for each cell line: an unenriched sample, which represents all cells following dissociation of the tumor, and a CAF-enriched sample. To further obtain the CAF-enriched sample, cells were then stained with CD45-AF657 (BioLegend clone 30-F11, 1:20), CD31-AF647 (BioLegend clone 390, 1:20), EPCAM-AF647 (BioLegend, clone G8.8, 1:20), and TER119-AF647 (BioLegend clone TER-119 1:20) for 30 minutes on ice. After two washes, CD45-, CD31-, EPCAM-, and TER119-negative cells, representing the CAF-enriched fraction, were obtained via cell sorting. scRNA-seq of both the unenriched and CAF-enriched fractions were performed using 10X Chromium microfluidic chips and data was analyzed using CellRanger v6.1.1, mm10 transcriptome reference, and 10X Loupe Browser. ResultsWe found that scRNA-seq of the unenriched whole tumor showed only one cluster of CAFs for both cells lines, making it difficult for studying CAF heterogeneity. Enriching for CAFs prior to scRNA-seq allowed for better capture of CAFs and provided more granularity on CAF heterogeneity for both KPC-4545 and KPC-3403. ConclusionsWhile enrichment provides more information on CAF heterogeneity, the process results in the loss of other cells within the TME. The need to capture CAF heterogeneity while studying cell-cell interaction between CAFs and other cells within the TME and identifying how distinct CAF populations respond differently to treatment warrants the use of other methods such as single-nuclear RNA-seq.

Activation of oncogenes through DNA amplification/overexpression plays an important role in cancer initiation and progression. Chromosome 17 has many cancer-associated genetic anomalies. This cytogenetic anomaly is strongly associated with poor prognosis of breast cancer. FOXK2 gene is located on 17q25 and encodes a transcriptional factor with a forkhead DNA binding domain. By integrative analysis of public genomic datasets of breast cancers, we found that FOXK2 is frequently amplified and overexpressed in breast cancers. FOXK2 overexpression in breast cancer patients is associated with poor overall survival. FOXK2 knockdown significantly inhibits cell proliferation, invasion and metastasis, and anchorage-independent growth, as well as causes G0/G1 cell cycle arrest in breast cancer cells. Moreover, inhibition of FOXK2 expression sensitizes breast cancer cells to frontline anti-tumor chemotherapies. More importantly, co-overexpression of FOXK2 and PI3KCA with oncogenic mutations (E545K or H1047R) induces cellular transformation in non-tumorigenic MCF10A cells, suggesting that FOXK2 is an oncogene in breast cancer and is involved in PI3KCA-driven tumorigenesis. Our study identified CCNE2, PDK1, and Estrogen receptor alpha (ESR1) as direct transcriptional targets of FOXK2 in MCF-7 cells. Blocking CCNE2- and PDK1-mediated signaling by using small molecule inhibitors has synergistic anti-tumor effects in breast cancer cells. Furthermore, FOXK2 inhibition by gene knockdown or inhibitors for its transcriptional targets (CCNE2 and PDK1) in combination with PI3KCA inhibitor, Alpelisib, showed synergistic anti-tumor effects on breast cancer cells with PI3KCA oncogenic mutations. In summary, we provide compelling evidence that FOXK2 plays an oncogenic role in breast tumorigenesis and targeting FOXK2-mediated pathways may be a potential therapeutic strategy in breast cancer.

Neoadjuvant chemotherapy with cisplatin + 5-fluorouracil followed by radical surgery is the standard treatment for stage II and III esophageal cancers. Although, a more potent regimen comprising cisplatin + 5-fluorouracil with docetaxel, has shown superiority in overall survival compared to the cisplatin + 5-fluorouracil regimen, it involves worsening of Grade 3 or higher adverse events due to docetaxel. Based on these reports, this study aimed to construct a prognostic system for cisplatin + 5-fluorouracil regimens, particularly for locally advanced cancers, to guide selection of neoadjuvant chemotherapy. Biopsy specimens from 82 patients who underwent a cisplatin + 5-fluorouracil regimen plus radical surgery at Saitama Medical University International Medical Center between May 2012 and June 2020 were analyzed. Variants in 56 autophagy- and esophageal cancer-related genes were identified using targeted enrichment sequencing. Overall, 13 single nucleotide variants, including eight non-synonymous group single nucleotide variants predicting recurrence were identified using Fishers exact test with recurrence as a two-group event, which showed a significant difference (p < 0.05). Additionally, machine learning was used to predict recurrence using 21 features, including eight patient backgrounds. The results showed that the Naive Bayes was highly reliable with an accuracy of 0.88 and Area Under the Curve of 0.9. Thus, we constructed a machine learning model to predict recurrence in patients with esophageal cancer treated with a cisplatin + 5-fluorouracil regimen. We believe that our results will provide useful guidance for the selection of neoadjuvant adjuvant chemotherapy, including the avoidance of docetaxel.

Small cell lung cancer (SCLC) is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models. Here, we analyzed formalin-fixed, paraffin-embedded (FFPE) samples of surgical resections by proteomic profiling, and stratified SCLC into three proteomic subtypes (S-I, S-II, and S-III) with distinct clinical outcomes and chemotherapy responses. The proteomic subtyping was an independent prognostic factor and performed better than current TNM or Veterans Administration Lung Study Group (VALG) staging methods. The subtyping results could be further validated using FFPE biopsy samples from an independent center, extending the analysis to both surgical and biopsy samples. The signatures of the S-II subtype in particular suggest potential benefits from immunotherapy. Differentially overexpressed proteins in S-III, the worst prognostic subtype, allowed us to nominate potential therapeutic targets, indicating that patient selection may bring new hope for previously failed clinical trials. Finally, analysis of an independent cohort of SCLC patients who had received immunotherapy validated the prediction that the S-II patients had better Progression Free Survival (PFS) and Overall Survival (OS) after first-line immunotherapy. Collectively, our study provides the rationale for future clinical investigations to validate the current findings for more accurate prognosis prediction and precise treatments.

BackgroundT cells exhibit heterogeneous functional states in the tumor microenvironment. Immune checkpoint inhibitors (ICIs) can reinvigorate only the stem cell-like progenitor exhausted T cells, which suggests that inhibiting the exhaustion progress will improve the efficacy of immunotherapy. Thus, regulatory factors promoting T-cell exhaustion could serve as potential targets for delaying the process and improving ICI efficacy. MethodsWe analyzed the single-cell transcriptome data derived from human melanoma and non-small cell lung cancer (NSCLC) samples and classified the tumor-infiltrating (TI) CD8+ T-cell population based on PDCD1 (PD-1) levels, i.e. PDCD1-high and PDCD1-low cells. Additionally, we identified differentially expressed genes as candidate factors regulating intra-tumoral T-cell exhaustion. The co-expression of candidate genes with immune checkpoint (IC) molecules in the TI CD8+ T cells was confirmed by single-cell trajectory and flow-cytometry analyses. The loss-of-function effect of the candidate regulator was examined by a cell-based knockdown assay. The clinical effect of the candidate regulator was evaluated based on the overall survival and anti-PD-1 responses. ResultsWe retrieved many known factors for regulating T-cell exhaustion among the differentially expressed genes between PDCD1-high and PDCD1-low subsets of the TI CD8+ T cells in human melanoma and NSCLC. TOX was the only transcription factor (TF) predicted in both tumor types. TOX levels tend to increase as CD8+ T cells become more exhausted. Flow-cytometry analysis revealed a correlation between TOX expression and severity of intra-tumoral T-cell exhaustion. TOX knockdown in the human TI CD8+ T cells resulted in downregulation of PD-1, TIM-3, TIGIT, and CTLA-4, which suggests that TOX promotes intra-tumoral T-cell exhaustion by upregulating IC proteins in cancer. Finally, the TOX level in the TI T cells was found to be highly predictive of overall survival and anti-PD-1 efficacy in melanoma and NSCLC. ConclusionsWe predicted the regulatory factors involved in T-cell exhaustion using single-cell transcriptome profiles of human TI lymphocytes. TOX promoted intra-tumoral CD8+ T-cell exhaustion via upregulation of IC molecules. This suggested that TOX inhibition can potentially impede T-cell exhaustion and improve ICI efficacy. Additionally, TOX expression in the TI T cells can be used for patient stratification during anti-tumor treatments, including anti-PD-1 immunotherapy.

Frequent metastatic relapses in Triple-Negative Breast Cancer (TNBC) patients with residual disease is a clinical challenge, largely due to tumor heterogeneity and absence of strategies that target proliferating chemo-tolerant cells. Here, we longitudinally modeled cellular state transitions from dormant drug-tolerant persister (DTP) into proliferating drug-tolerant persister (PDTP) in cells representing all TNBC subtypes. Combining subcellular imaging with phenotypic and biochemical assays, we identified distinct and converged spectrums of alterations in TNBC-PDTPs. We show that PDTPs retain acquired resistance with increased invasion potential. Moreover, Basal-Like DTPs enter into a non-reversible mesenchymal state while luminal androgen receptor-positive gain partial-Epithelial-to-Mesenchymal Transition (EMT) with vimentin upregulation. PDTP state dwells on high autophagy with reduced glutathione and GPX4 levels, rendering it vulnerable to autophagy suppression and ferroptosis. Interestingly, we find that GPX4 negatively regulates EMT and autophagy in TNBC, and an inverse correlation of GPX4-VIM expression along with autophagy genes predicts survival in TNBC patients undergoing chemotherapy.

BackgroundGastric cancer (GC) continues to be among the most commonly identified cancers worldwide. This study integrates glycosylation and inflammation-related gene features for the first time to construct a prognostic model for gastric cancer, providing new theoretical basis for revealing immune escape mechanisms and personalized treatment strategies. MethodsTranscriptomic and clinical data derived from GC samples were meticulously examined, utilizing resources from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Through differential expression analysis, we successfully identified glycosylation and inflammatory-related differentially expressed genes (GANDIRDEGs). To construct a prognostic gene signature, we applied least absolute shrinkage and selection operator (LASSO) analysis in conjunction with Cox regression analysis. Additionally, we performed somatic mutation (SM) along with copy number variation (CNV) analyses, alongside gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, we conducted gene set enrichment analysis (GSEA) along with a comprehensive evaluation of immune infiltration and drug sensitivity. ResultsWe identified and validated a six-gene (INHBA, OLR1, ROS1, EPHA5, TACR1, and IL6) signature, termed GANDIRDEGs, which showed excellent performance in distinguishing overall survival (OS) between high-risk (HR) and low-risk (LR) cohorts. Moreover, we developed a prognostic nomogram utilizing this six-gene signature that provides highly accurate predictions of GC patient outcomes.SM and CNV analyses revealed that MSR1 had the highest mutation rate among the GANDIRDEGs, with a mutation rate of 5%. GO, KEGG, and GSEA revealed significant associations of each pivotal gene with pathways, including cytokine signaling, the inflammatory response, and apoptosis mediated by CDKN1A through TP53, among various biological functions and signal transduction pathways. Our findings offer a novel gene signature, GANDIRDEGs, that correlated with prognosis, immune infiltration, and therapeutic sensitivity in patients with GC. ConclusionThis study establishes a prognostic signature integrating glycosylation and inflammatory pathways in GC, providing valuable insights into the mechanisms of immune evasion and potential personalized treatment approaches.

BackgroundDormant or slow cycling cells (SSCs) pre-exist in tumor and responsible for chemo-resistant and tumor recurrence. Due to their low differentiation and dormancy characteristics, SCCs are resistant to standard chemotherapy and targeted therapy. Label-retaining is a common method used to identify and isolate live SCCs. However, it remains unclear whether different label-retaining methods yield distinct SCC subpopulations. In this study, we investigated that various label-retaining methods result in overlapping yet heterogeneous subpopulations of SCCs. Additionally, we explored the molecular mechanisms regulating dormancy in triple-negative breast cancer (TNBC). MethodsWe employed multiple label-retaining methods to simultaneously label MDA-MB-231 cells, thereby generating distinct subpopulations of SCCs. We subsequently analyzed these subpopulations for heterogeneity in cell cycle distribution, drug resistance, invasive capacity, and other characteristics using real-time PCR, flow cytometry, and Transwell assays. RNA-seq analysis was performed to characterize the gene expression profiles of the SCCs. Furthermore, we used real-time PCR, Western blotting, immunofluorescence, and luciferase assays to investigate the role of characteristic AP-1 expression in dormancy regulation. Finally, the therapeutic effects of targeting AP-1 in the treatment of TNBC were assessed using a cell-derived xenograft model. ResultsWe labeled and separated three overlapping but non-identical SCCs subpopulations. We found that all three SCCs subgroups are cell cycle arrested. Additionally, Violet enriched SCCs showed stronger drug resistance and more G1 phase arrest, while Claret enriched SCCs demonstrated enhanced migratory and invasive abilities, along with more G2/M phase arrest. Furthermore, we observed upregulation of AP-1 expression in SCCs, and the JunB subunit of AP-1 promoted the expression of CDKN1A and GADD45A, thereby maintaining cell cycle arrest. CC-930 can inhibit AP-1 transcriptional activity by suppressing JNK activity, ultimately improving the therapeutic efficacy and prognosis of TNBC when used in combination with chemotherapy drugs. ConclusionsWe obtained three subpopulations of SCCs with heterogeneous drug resistance. Our findings suggest that AP-1 plays a regulatory role in dormancy regulation in TNBC, and elucidated the molecular function of JunB subunit. Targeting AP-1 with CC-930 has the potential to improve the treatment and prognosis of TNBC. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/566980v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@129ce76org.highwire.dtl.DTLVardef@1b1cfa1org.highwire.dtl.DTLVardef@b68315org.highwire.dtl.DTLVardef@57faf1_HPS_FORMAT_FIGEXP M_FIG C_FIG TNBC harbors both fast-cycling cells (FCCs) and functionally overlapping slow-cycling cell (SCC) subpopulations that manifest differential drug sensitivities and motility (A) but are commonly regulated by the JunB-containing AP1 complex (B). (A). Slow-cycling (quiescent) TNBC cells in culture (a) identified by different label-retaining approaches phenotypically overlap (b), display differential drug sensitivities (c, d) and motility (e) but share common gene expression profiles (f). (B). Schematic depicting regulation of proliferation in FCCs by the c-Jun/c-Fos AP1 complex (left) and regulation of cellular dormancy in SCCs by c-Jun/JunB AP1 complex.